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Alabama Chapter Hosts Miniconference in Mississippi

Sun, 07/01/2018 - 7:00am

Chapter officers (from left) Hailin Sang, Jon Woody, Jeff Syzchowski, and Bob Oster with ASA Past President Barry Nussbaum


Student award winners (from left): Justin Leach, Mojtaba Khanzadeh, Ralph Vital, and Zavia Epps

    The Alabama Chapter hosted a miniconference April 6 at Mississippi State University. Approximately 40 current and prospective chapter members attended from Alabama and Mississippi who were affiliated with Mississippi State University, Jackson State University, the University of Mississippi, and the University of Alabama at Birmingham.

    The keynote speaker was Barry Nussbaum, ASA past president. The title of his talk was “The Only Thing We Have to Fear Are the Data Themselves … And That Is Not a Very Big Fear.” The purpose of the presentation was to demonstrate what to do—and what not to do—in terms of the ability of statisticians to succinctly explain results so decision-makers may correctly integrate analyses into their actions. The role of examining the opportunities and pitfalls of big data was a major focus of the presentation. Nussbaum delivered his talk with a mix of seriousness and humor, and his talk was well received by those in attendance.

    Student presenters and their topics included the following:

    • Justin Leach of the University of Alabama at Birmingham, “Penalized Smoothing Splines in Adolescent Growth Studies”
    • Ralph Vital of Mississippi State University, “Goodness-of-fit Test for the Hazard Rate”
    • Mojtaba Khanzadeh of Mississippi State University, “In-Situ Monitoring of Melt Pool Images for Porosity Prediction in Directed Energy Deposition Processes”
    • Zavia Epps of Jackson State University, “Monte Carlo Methodology Using Bootstrapping to Investigate Weight in Motion Data on Bridge Load Rating Factor”

    The chapter also held a business meeting that covered the newly written Alabama Chapter constitution and bylaws, chapter activities, a possible name change for the chapter to recognize that members are from both Alabama and Mississippi, and JSM activities.

    In addition, the chapter held elections for its officers. Jon Woody of Mississippi State University was elected president and Bob Oster of the University of Alabama at Birmingham was re-elected treasurer. Hailin Sang of the University of Mississippi continues his term as secretary. Former President Jeff Szychowski will assume the role of chapter representative. A new vice president will be selected later. Elections for vice president and secretary will be held in 2019.

    Bureau of Labor Statistics’ Wendy Martinez Elected ASA President

    Sun, 07/01/2018 - 7:00am

    Wendy Martinez
    Photo/Studio B

    The membership has voted, and it elected Wendy Martinez, director of the Mathematical Statistics Research Center at the Bureau of Labor Statistics, as the 115th president of the American Statistical Association. Before she takes office as president on January 1, 2020, she will serve as president-elect, beginning January 1, 2019.



    Richard De Veaux


    Members also elected Richard De Veaux, professor of statistics at Williams College, as vice president. De Veaux’s term also begins January 1, 2019.



    Additionally, the ASA membership elected the following:

    • Anamaria Kazanis of ASKSTATS Consulting as the Council of Chapters Governing Board Representative to the ASA Board
    • Mark Glickman of Harvard University as the Council of Sections Governing Board Representative to the ASA Board
    • Mary Kwasny of Northwestern University as chair-elect of the Council of Chapters Governing Board
    • Ofer Harel of the University of Connecticut as chair-elect of the Council of Sections Governing Board

    Following is a list of the entire slate of election results, including officers for each of the ASA’s sections:

    Board of Directors

    President-Elect 2019
    Wendy Martinez

    ASA Vice President 2019–2021
    Richard De Veaux

    Council of Chapters Representative to the ASA Board of Directors
    Anamaria Kazanis

    Council of Sections Representative to the ASA Board of Directors
    Mark Glickman

    Council of Sections Governing Board
    Ofer Harel

    Vice Chair
    Alyson Wilson

    Council of Chapters Governing Board
    Mary Kwasny

    Vice Chair District 4, Region 2
    Jo Wick

    Vice Chair District 3, Region 2
    Ruth Cassidy

    Section on Bayesian Statistical Science

    Chair-Elect 2019
    Marina Vannucci

    Program Chair-Elect 2019
    Surya Tokdar

    Secretary/Treasurer 2019–2020
    Yanxun Yu

    Council of Sections Representative 2019–2021
    Ying Yuan

    Biometrics Section

    Chair-Elect 2019
    Sherri Rose

    Elizabeth Ogburn

    Council of Sections Representative 2019–2021
    Page Moore

    Biopharmaceutical Section

    Chair-Elect 2019
    Bruce Binkowitz

    Program Chair-Elect 2019
    Stephine Keeton

    Publications Officer 2019–2021
    Yongming Qu

    Council of Sections Representative 2019–2021
    Veronica Powell

    Business and Economic Statistics Section

    Chair-Elect 2019
    Adriana Kugler

    Program Chair-Elect 2019
    Mariana Saenz-Ayala

    Secretary/Treasurer 2019–2020
    Maggie Jones

    Section on Statistical Computing

    Chair-Elect 2019
    John Castelloe

    Program Chair-Elect 2019
    Kary Myers

    Council of Sections Representative 2019–2021
    Lucy D’Agostino McGowan

    Section on Statistical Consulting

    Chair-Elect 2019
    Manisha Desai

    Publications Officer 2019–2020
    Joseph Rigdon

    Executive Committee-at-Large 2019–2021
    Robyn Ball

    Council of Sections Representative 2019–2021
    Dean Johnson

    Section on Statistical Education

    Chair-Elect 2019
    Michael Posner

    Secretary/Treasurer 2019–2021
    Jennifer Broatch

    Executive Committee-at-Large 2019–2021
    Jessica Chapman

    Executive Committee-at-Large 2019–2021
    Beverly Wood

    Section on Statistics and the Environment

    Chair-Elect 2019
    Amanda Hering

    Program Chair-Elect 2019
    Ephraim Hanks

    Treasurer 2019
    Henry Scharf

    Section on Statistics in Epidemiology

    Chair-Elect 2019
    Jing Cheng

    Program Chair-Elect 2019
    Alisa Stephens-Shields

    Secretary/Treasurer 2019–2021
    Nicole Bohme Carnegie

    Section on Government Statistics

    Chair-Elect 2019
    Katherine Thompson

    Program Chair-Elect 2019
    Michael Yang

    Publications Officer 2019–2020
    Jenny Guarino

    Secretary/Treasurer 2019–2020
    Tara Murphy

    Council of Sections Representative 2019–2021
    Jennifer Parker

    Section on Statistical Graphics

    Chair-Elect 2019
    Isabella Ghement

    Program Chair-Elect 2019
    Shailaja Surywanshi

    Secretary/Treasurer 2019–2020
    Stefano Castruccio

    Council of Sections Representative 2019–2021
    Ritwik Mitra

    Health Policy Statistics Section

    Chair-Elect 2019
    Laura Hatfield

    Section on Statistics in Marketing

    Chair-Elect 2019
    Lan Luo

    Program Chair-Elect 2019
    Daniel McCarthy

    Secretary/Publications Officer 2019–2020
    Seshadri Tirunillai

    Section on Physical and Engineering Sciences

    Chair-Elect 2019
    Robert Gramacy

    Program Chair-Elect 2019
    Mary Frances Dorn

    Council of Sections Representative 2019–2021
    Kimberly Kaufeld

    Section on Quality and Productivity

    Chair-Elect 2019
    Chris Gotwalt

    Program Chair-Elect 2019
    Terri Henderson

    Section on Risk Analysis

    Chair-Elect 2019
    Elena Rantou

    Program Chair-Elect 2019
    Qian Li

    Social Statistics Section

    Chair-Elect 2019
    Eileen O’Brien

    Program Chair-Elect 2019
    Antje Kirchner

    Publications Officer 2019–2020
    Liana Fox

    Council of Sections Representative 2019–2021
    John Finamore

    Section on Statistics in Sports

    Chair-Elect 2019
    Phil Yates

    Program Chair-Elect 2019
    Sarah Morris

    Survey Research Methods Section

    Chair-Elect 2019
    Morgan Earp

    Program Chair-Elect 2019
    Yang Chang

    Treasurer 2019–2020
    Darcy Steeg Morris

    Publications Officer 2019–2020
    Steven Pedlow

    Council of Sections Representative 2019–2021
    Julia Soulakova

    Education Officer 2019–2020
    James Wagner

    Section on Teaching of Statistics in the Health Sciences

    Chair-Elect 2019
    Laila Poisson

    Council of Sections Representative 2019–2021
    Jose-Miguel Yamal

    Section on Nonparametric Statistics

    Chair-Elect 2019
    Runze Li

    Program Chair-Elect 2019
    Yanyuan Ma

    Treasurer 2019
    Jelena Bradic

    Council of Sections Representative 2019–2021
    Aurore Delaigle

    Statistics in Defense and National Security

    Chair-Elect 2019
    Douglas Ray

    Program Chair-Elect 2019
    Karl Pazdernik

    Publications Officer 2019–2020
    Kelly Townsend

    Council of Sections Representative 2019–2021
    Joe Warfield

    Section for Statistical Programmers and Analysts

    Chair-Elect 2019
    Vipin Arora

    Program Chair-Elect 2019
    Navneet Hakhu

    Council of Sections Representative 2019–2021
    Ben Joseph Barnard

    Section on Statistical Learning and Data Science

    Chair-Elect 2019
    Helen Zhang

    Program Chair-Elect 2019
    Adam Rothman

    Council of Sections Representative 2019–2021
    Xiao Wang

    Section on Statistics in Imaging

    Chair-Elect 2019
    Anuj Srivastava

    Imaging Program Chair-Elect 2019
    Linglong Kong

    Mental Health Statistics Section

    Chair-Elect 2019
    Wes Thompson

    Program Chair-Elect 2019
    Knashawn Morales

    Council of Sections Representative 2019–2021
    Christine Mauro

    Section on Medical Devices and Diagnostics

    Chair-Elect 2019
    Matyin Ho

    Program Chair-Elect 2019
    Tyson Rogers

    Section on Statistics in Genomics and Genetics

    Chair-Elect 2019
    Saonli Basu

    Program Chair-Elect 2019
    Qionshi Lu

    NIST Sponsors Data Science Competition

    Sun, 07/01/2018 - 7:00am

    The National Institute of Standards and Technology is sponsoring a data science competition with a prize purse of $190,000 called The Unlinkable Data Challenge: Advancing Methods in Differential Privacy.

    The goal of this series of competitions is to propose a new or improved mechanism to enable the protection of personally identifiable information while maintaining the usefulness of data sets to be used by researchers for positive purposes and outcomes.

    Excitement, Sleeplessness, Relief: ASA Members Express How It Feels to Win NSF Graduate Research Fellowship

    Sun, 07/01/2018 - 7:00am

    “I was super elated,” says Brian Kwan, upon hearing he had been awarded a National Science Foundation Graduate Research Fellowship—so much so that he couldn’t sleep that night. Receiving the fellowship—one of 16 awarded to statistics students out of 2,000 recipients—was the culmination of years of anticipation, during which he resisted the temptation to rush an application while an undergraduate and, instead, deepened his knowledge of statistics by working on projects with faculty members at the University of California, Irvine, University of Pittsburgh, and his current home, University of California, San Diego.

    Quoting the line from John Tukey that “The best thing about being a statistician is you get to play in everyone’s backyard,” Kwan says collaborating with different investigators gave him a chance to learn about the statistical literature in each scientific field and to reason which statistical methods could apply best to the statistical analysis needed. Working with Loki Natarajaran on research to develop novel statistical approaches to predicting future kidney function decline among type 2 diabetics deepened Kwan’s interest in prediction modeling and gave him the confidence, he says, to apply for the fellowship.

    Maria Jahja heard from a friend she had been selected, and after checking the email, she immediately texted her parents. “It was all typos because I was so excited,” she says. “I know so many great students who applied in my field, I didn’t think I really had a chance.” As an undergraduate research assistant in the lab of Eric Laber at North Carolina State University, Jahja began building artificial intelligence agents for video games. “I would code fun games, then implement learning algorithms for sequential decision-making under uncertainty.” This led to her research proposal on using statistically rigorous uncertainty measures to inform decision-making, which she will pursue at Carnegie Mellon University.

    “Computers are astonishingly efficient at solving formal problems,” she says, “but building an intelligent system for uncertain situations is much more difficult. Human intuition and reasoning are hard for a machine to reproduce, especially in complex environments where even a human expert might be unsure what the best choice is. It might even be that there is no ‘optimal’ choice, as it depends on individual preference. But if we could make some hybrid data-driven system capturing the strength of both—an expert and algorithm-driven decision-making system—I think that has immense value for society.”

    Derek Hansen came to his research proposal, in part, through working at the Federal Reserve Board as a research assistant, where he used state-space techniques to estimate models in economic and financial applications and wrote lots of code in R and Julia to tackle the technical problems encountered (he will present the results of this research at JSM in a presentation titled “Randomized Missing Data Approach to Robust Filtering with Applications to Economics and Finance”). His NSF proposal will look at whether similar techniques can be used to improve model selection.

    “To be honest, I wasn’t expecting at all to win the NSF fellowship,” says Hansen. “In fact, I found out because a fellow research assistant at the Federal Reserve saw my name on the website and congratulated me. I was absorbed in [a] Bayesian particle filtering project, so I hadn’t even checked my non-work email in a few days.” Hansen says the news was both a pleasant surprise and reassuring. “It’s a little scary working on a research proposal and sending it off to be evaluated—I also am relieved that experts in the field of statistics don’t think my ideas are completely crazy.” Hansen will begin a PhD program in statistics at the University of Michigan this fall.

    The NSF fellowships provide financial support for three years across a five-year period.

    The Commutative Property Is Neither Necessary nor Sufficient: It’s Time to Consider Implementing Distance PhD Programs

    Sun, 07/01/2018 - 7:00am

    Seth T. Lirette is an assistant professor in the department of data science at the University of Mississippi Medical Center. He supports biomedical research across the entire university, while focusing on radiological and aging research. He is also president of the private analytics and statistical consulting firm Blackshear & Lirette. He holds an MS in statistics from Mississippi State University and a PhD in biostatistics from the University of Alabama at Birmingham.

      With the data revolution firmly upon us, it has never been more imperative to have highly skilled data practitioners building models and conducting analyses. Many of those doing data science–type work have no formal training, and this often results in questionable analyses.

      One potential way to rectify this situation is to provide easier access to those people who wish to pursue advanced training in analytics-related disciplines, but—for various reasons—are unwilling to take residential status at or commute to campus. While there is a litany of master’s degrees offered completely online, I am unaware of any programs for distance PhDs in statistics, biostatistics, data science, or any other analytics field. I propose it is time we loosen the reigns on the seemingly ubiquitous residential requirement for admission to PhD programs.

      Disproving the sufficiency of commuting to a campus for obtaining a PhD is trivial, as we know lots of people who drive onto campuses for 4+ years and never receive doctorates. Disproving the necessity of commutation (or residentiality) is a bit more challenging. Although anecdotal, my personal experience gives a good counterexample. This essay seeks to document my experience in a distance (although officially residential) PhD program, explaining the positives and negatives alongside what worked and what needs to be improved upon.


      I began my stint at the University of Mississippi Medical Center (UMMC) as an unpaid intern during the summer between the two years of my master’s degree. During this internship, I was offered a full-time biostatistician position once I completed my MS degree. I accepted this position in May 2012. Then, in the spring of 2013, I was approached by who would eventually be the head of my department with an interesting proposition. He had explained that everyone was impressed with my work, and that he and the other faculty members would eventually like me to join the faculty. At the risk of sounding obvious, I would need a PhD for this to take place.

      UMMC had no program related to statistics or biostatistics (we now have PhD and master’s programs in biostatistics and data science). Therefore, I needed to take the degree from somewhere afar. But I had no desire to uproot my family, nor did the department want to relinquish me. This is where the interesting proposition enters: UMMC had worked out an unofficial agreement with the department of biostatistics at the University of Alabama at Birmingham (UAB) in which I could take my PhD from UAB, but stay employed full time at UMMC. I would complete every degree requirement necessary (complete 60 hours of coursework, pass comprehensive exams, complete 24 research credit hours with a dissertation, and other requirements). The only difference between me and my student-peers would be that they were full-time graduate students living in Birmingham, Alabama, and I was a full-time biostatistician living in Jackson, Mississippi.

      My Experience

      From my anecdotal evidence, it seems to be somewhat common for a student to complete his or her dissertation while not living in the same locale as his or her adviser. However, I could not find a documented instance of a person doing an entire statistics PhD from a distance. So, this was going to be an exercise in faith and completely an (N=1) experiment. There were some growing pains, but for the most part, things went rather smoothly.

      It was first agreed upon that I should show up for classes, at least initially. So, for the entirety of the fall semester of 2013, I made the four-hour one-way commute from Jackson to Birmingham to attend my Tuesday/Thursday classes in person and made the trek back, twice per week. This was obviously less than ideal, but everyone involved wanted to make sure I would not be falling behind on my coursework. In retrospect, this was unnecessary, as we will later see.

      During the second semester, spring of 2014, I spoke with my professors, and we agreed that, given my success in the first semester, I could cut the commute back to once per week. At the end of the first year, I had logged many, many miles on I-20.

      From that point on, and since my grades were exemplary, I would make it standard practice to meet face-to-face on the first day of class and then only be physically present if needed (i.e., to take an exam or to present a formal presentation).

      Every professor I encountered was more than willing to be helpful in any way. Any questions I had about assignments or methods were answered over telephone calls or email exchange. I never felt as though I did not have adequate access to my instructors.

      One caveat to this does need mentioning. Because this was not an official distance program, most of the classes consisted only of traditional face-to-face lectures. I took two official online classes (Writing for Research and Introduction to Epidemiology), but other than these, there was not an official platform for disseminating lectures other than face-to-face. As a result, I sometimes felt like I was not “getting my money’s worth” from some classes. I cannot fault them for this, as it was not an official distance program, but I love hearing people lecture on subjects they know intricately, and this is one thing I wish I had more of. That being said, by the time of my last course (Advanced Clinical Trials), we had a very nice virtual classroom where I was able to fully participate from four hours away via webcam. If a school chooses to fully implement a distance program, this would be vitally necessary.

      Another downside to the distance model is that many people meet lifelong friends in graduate school, as I did during my master’s degree. Not living in the same city or seeing them often obviously limited the amount of interaction I had with my classmates. I knew a few through email and casual conversations, but I would have liked the chance to get to know them better.

      I, however, was able to take solace in the fact that working full time provides a much better salary than that typically received through assistantship and fellowship stipends. And if I am being completely honest, my family of five needed a full-time salary more than I needed new friends.

      One of the biggest advantages of working full time while pursuing the degree is that I was constantly exposed to real-world issues of data analysis. It is no secret that the curated data sets provided in classroom settings are usually nothing like data in the wild. The latter is what I was exposed to on a daily basis and would only serve to sharpen my skills. Also, with almost every new technique I learned in the classroom, I could envision somewhere at UMMC to apply it. These two worlds synergized very well. In fact, the topic of my dissertation directly resulted from one of my collaborations with the department of radiology at UMMC.

      By the time it came to write my dissertation, everyone knew about my situation and I had assembled a wonderful committee willing to provide me with anything I needed to succeed.

      Given my entrance into the program in August of 2013, we were initially aiming for a graduation date of May 2018. In fact, I earned my degree in August of 2017. This was, in no small part, due to both the helpfulness of the entire department of biostatistics at UAB and the generosity of what would become the department of data science at UMMC.

      While I realize this option is not for everyone seeking a PhD, I hope I have made the argument that implementing a distance PhD should now be a viable option for most departments. Adding more highly trained statisticians, biostatisticians, and data scientists to the academic, governmental, social, industrial, and technological workforce can only improve some of the issues we currently face.

      With more educational options, we can go a step further in adding more well-qualified practitioners of the data sciences, and we can hopefully make progress into taming what sometimes currently looks like a Wild West of analytics.

      NC Chapter Sees Speed-Mentoring Success

      Sun, 07/01/2018 - 7:00am

      Gabe Farkas (right) chats with two students during the speed mentoring program.


      Breda Munoz and Rishi Chakraborty answer students’ questions during the speed mentoring program.

        The North Carolina Chapter hosted a speed mentoring event in April during which students and young professionals had the opportunity to meet with established career professionals in a small-group setting. Mentors and mentees discussed networking, goal setting, and career development with targeted questions and activities.

        Mentors included Abie Ekangaki of UCB, Kirsten Foley of the Environmental Protection Agency, Gabe Farkas of the San Antonio Spurs, Breda Munoz of RTI, and Rishi Chakraborty of DCRI.

        Mentees found the format efficient and liked that there were opportunities to talk to or hear from everyone while going more in-depth with the mentor they were assigned to.

        The chapter’s next mentoring event will be a full-day workshop on November 30. Mentees will have the opportunity to attend the chapter’s fall dinner that evening to mingle with the larger North Carolina Chapter community and have a small group meeting with ASA President Lisa LaVange. See more photos on the chapter’s website.

        What Does Samanthi Konarasinghe Like to Do When She Is Not Being a Statistician?

        Sun, 07/01/2018 - 7:00am

        Konarasinghe is made up before a theater performance.

          Konarasinghe’s painting, “My Dream”

            Who are you, and what is your statistics position?

            I am Samanthi Konarasinghe, statistician and director of the Institute of Mathematics and Management in Sri Lanka. I am a senior lecturer in mathematics, statistics, and financial management at universities and tertiary education institutions.


              Tell us about what you like to do for fun when you are not being a statistician.

              When I am being a statistician or not, I am an artist. I am an actress, painter, violinist, and writer. I have produced several stage plays and won the best actress award, as well. I have conducted a solo art exhibition, named “My Dream.” I am a nature lover. I walk miles and miles of roads full of trees and flowers. I enjoy feeding and talking to animals. I love parties and dancing.

              What drew you to this hobby, and what keeps you interested?

              As everyone says, I was born an artist. From my small days, I was equally interested in arts and mathematics. For me, painting, singing, dancing … are not hobbies; they are part of my life. My scientific and artistic lives are intertwined.

              Session Proposals Sought for JSM 2019

              Sun, 07/01/2018 - 7:00am
              Rich Levine, JSM 2019 Program Chair

                Rich Levine

                You read that right. JSM 2019 program planning has begun. This call always takes me aback. Here we each are in the throes of preparing for JSM 2018 Vancouver—organizing our alumni gatherings, salivating over the slam-packed conference program, locating the best eateries, stressing because we should have planned the pre-conference trip to Banff earlier—and then some highly organized, energetic, new program chair springs 2019 on us.

                I know the dog days of summer are busy, but don’t let this opportunity pass you by. 2019 ASA President Karen Kafadar has set the JSM 2019 theme as “Statistics: Making an Impact.” Take a morning to organize your thoughts on one of the five session types highlighted below. The proposal process is easy—the deadline is September 6. Aim to make an impact in Denver!

                Invited Paper and Panel Sessions

                The classic invited session format consists of a session of talks, and perhaps commentary, by two to six speakers and discussants or a panel of three to six expert discussants. We are seeking sessions that address a hot topic of broad audience interest by a slate of engaging speakers/panelists. In fact, the most stimulating invited sessions present diverse viewpoints and strategies on a common topic, with speakers coming from different institutions and taking different approaches toward similar problems.

                To organize a session, first set a theme and contact potential participants. Once these are determined, the proposal consists of the session title, a brief description/rationale, the list of participants, and tentative titles for the talks (these may be modified later). Proposals are submitted through the JSM online system, which opens July 18. The deadline for submission is September 6 at 11:59 p.m. ET.

                As part of the submission process, you will select up to three sponsors (partner society, ASA section, etc.) in rank order for your proposed session. Once you submit a proposal through the online system, campaign for a sponsor! Most of the 209 invited sessions are allocated to partner societies and ASA sections. Furthermore, the ASA sections will select up to two proposals to enter into a competition for the remaining slots in the invited session program. You may find the contact for your desired sponsor on the program committee roster, which you can find on the JSM website when it goes up at the end of this month. Enlisting a proposal champion at the program committee table is a desired strategy. You must submit your proposal through the online system before contacting a program committee member sponsor representative. Given a meeting of this size and the number of balls the program committee juggles, the online submission ensures your proposal does not fall through the cracks.

                As you are probably gathering, given the annual growth of JSM, the competition for an invited session slot is now fierce. Take the time to identify a fresh and important topic and provide an inspiring session description. You may also revise your proposal following a discussion with the program committee sponsor representative until the September 6 deadline. The goal is to make your proposal appealing to other committee members in the event it enters the selection competition. Finally, make sure your session participants follow the strict rules for participation.

                Decisions about the invited program will be made by the end of September. Due to the limited number of sessions and increasing attendance, many strong invited session proposals will not be selected. Do not lose hope—you may submit your proposal later as a topic-contributed session.

                Memorial Sessions

                We will slot five memorial sessions at JSM 2019. Proposals must be submitted through the online invited session system, choosing “memorial session” as the sponsor. To maximize the odds of being selected for inclusion in the invited program, I recommend submitting memorial sessions by September 6 to enter the competition for an invited session. If the session is not selected by a partner organization or ASA section, the session proposal will be entered into the competition for one of the five memorial session slots. That said, I encourage you to contact me if you are planning to submit a memorial session. Final decisions will be made in the fall.

                Invited Poster Sessions

                We will continue the new tradition of an invited poster session of up to 30 electronic posters during the Opening Mixer. This session is an excellent opportunity for presenters to interact one-on-one with JSM attendees. Email your ideas to the JSM 2019 poster chair.

                Introductory Overview Lectures

                We are shooting for four Introductory Overview Lectures (IOLs) addressing state-of-the-art, important statistical topics of broad interest to JSM attendees. An IOL may be presented by an individual or a team. That said, I am looking for engaging, experienced lecturers with a facility for imparting potentially subtle ideas and deep concepts to a large audience. Do note that IOL speakers may also present an invited or contributed paper, panel, or poster at JSM. Contact me with suggestions for topics and/or speakers.

                Statistics: Making an Impact

                On behalf of all program committee members, I thank you in advance for helping JSM 2019 make an impact worthy of the majestic Rocky Mountains that will greet us each day in Denver July 27 to August 1, 2019!

                Universities, Industry Collaborate to Benefit All

                Sun, 07/01/2018 - 7:00am

                Members of the ASA Committee on Funded Research (CFR), whose charge includes facilitating communication and interaction between the statistical community and funding organizations, sought to learn about how university departments engage industry in research collaborations. They found many departments willing to share their experiences by answering the following questions. CRF members hope this information furthers industry collaborations by the statistical community.


                Max Morris is professor and chair of the department of statistics at Iowa State University and a statistical consultant affiliated with Los Alamos National Laboratory.

                Please describe your department’s industry and/or government engagements/collaborations.

                We have a set of agreements with various companies that provide support and professional experience for some of our more advanced graduate students. In brief, we sign a contract with the company to provide statistical support for 20 hours per week (the typical research assistant load) for one or more semesters. The contract is signed by the company and university and is processed through our grants and contracts office. The company pays the university, and the funds are used to support a graduate assistantship for the student (tuition and stipend at our usual rate) for the prescribed length of time.

                With this setup, the student is an employee of the university, rather than the company—an arrangement especially helpful for some international students. For the most part, department faculty are not directly involved. The work done by the student is generally what we would call “consulting” or “applied research” and most often not related to their dissertation research. The experience is comparable to that of many industrial summer internships, but may last more than one term and is such that the student can do the work from campus.

                How did the engagement/collaborations come about? How are the collaborations sustained in a way that is mutually beneficial to students, the university, industry, and the community-at-large?

                These agreements are usually initiated by the companies, with communication to our department asking about opportunities to work with our students. Beyond financial support, the benefit to the student is primarily in the form of professional experience. Although the immediate benefit to the company is the work done by the student, there is often an interest in getting an “early look” at a potential employee, much as with many summer internship programs.

                What arrangements about the collaborations might be helpful to share?

                The arrangements are formalized through a contract between the company and university. I (as department chair) handle setting these up and, along with the associate chair, identify students who are good candidates. In some cases, the company also participates by interviewing students we identify as candidates. Before it is finalized, a contract must be approved by the university grants and contracts office; invoicing and fund transfer is handled by our central administration. There is usually little direct faculty oversight of the students (and so they must be relatively mature and independent), but as the university contact for these arrangements, I receive feedback from the companies about the students’ performance. In most cases, the students involved in these arrangements participate with a company for multiple semesters.

                What benefits for the department have you seen come out of these collaborations?

                For the department, these arrangements supplement our state-funded teaching assistantships and grant-funded research assistantships, giving us a bit more flexibility in how we arrange support for our students.


                Lynne Stokes is chair of the department of statistical science at Southern Methodist University. Work on problems for the US Census Bureau, National Center for Education Statistics, National Oceanic and Atmospheric Administration, US Energy Information Administration, and other federal agencies has been some of the most interesting of her career.

                Please describe your department’s industry and/or government engagements/collaborations.

                We have several types of engagements with business/government that pay our graduate students. Besides the usual grants, we currently have the following two activities:

                • Local business (management consulting) provides stipend/overhead for a PhD student (just completed second year of this) in exchange for his time. This is in lieu of a teaching or research assistantship in the department. This has been mutually beneficial, as company has extended full-time offer to student on graduation. Student has accepted. We have had similar arrangements with hospital systems in the past.
                • We have a long-term consultancy with a federal agency. The funding goes through our department’s statistical consulting center. Three students have received funding (stipends, summer funding) for work on various projects as needed. Some projects are short term (a few weeks) and some are long term (several years).

                Other kinds of relationships:

                • We have relationships in the area with companies who come to our department to interview students for summer internships. We facilitate the interviewing process by setting up appointments and giving them space. This is for grad students at both the master’s and PhD levels.
                • We provide a forum for local companies to discuss their company’s projects (i.e., give a work-related seminar). This is for our master’s students. This is mostly to facilitate their recruiting of our students, but also provides these students with information about what statistical methods are used in the workplace.
                • Local companies provided people (a lot of them the same as mentioned in the previous paragraphs) to serve as judges at the DataFest contest we held this year.
                • We provide free consulting services to companies/nonprofits willing to be clients for our graduate students in their required consulting class.
                How did the engagement/collaborations come about? How are the collaborations sustained in a way that is mutually beneficial to students, the university, industry, and community-at-large?

                Some are cold calls that companies make to our department looking for help either on consulting problems or for recruiting.

                The federal agency relationship resulted from a National Academies panel I served on. I met people at the agency who were trying to implement changes. This relationship has now been ongoing for more than 10 years.

                A fair number of these relationships were from local companies hiring our students and having them work out well. They are interested in a pipeline to students. Then, over time, our students continue the recruitment cycle.

                Some of the relationships are from the local ASA chapter meetings. We hold them on our campus, and so we get to know industry people who come to the meetings.

                What arrangements about the collaborations might be helpful to share?

                The consulting center is a good vehicle for supporting nondomestic students in the summer. The immigration laws allow people holding student visas to work on campus, but it is more difficult for them to get authorization to work off campus. If a company is willing to give up “control” and let the student be supervised by us and work on our campus, this allows them access to scarce talent.

                What benefits for the department have you seen come out of these collaborations?

                We have had a variety of benefits, including the following:

                • We have been able to place our master’s students well locally, which helps us in recruitment.
                • We have been able to have more PhD students (larger number of stipends) and provide more of them support in the summer on a part-time (flexible) basis, so they can work on dissertations and still earn enough to survive.
                • We have generated research topics. Two current dissertation topics are from the federal agency consultancy.
                • We have not yet hired adjuncts from our industry contacts, but we have discussed this with our industry friends, and will use them if we find ourselves short-handed.
                • We have had the opportunity to train our students in consulting.
                What benefits for the broader community have you seen come out of these collaborations?

                Companies have been very happy with our students as employees. We are now working with two local companies to facilitate their employees’ participation in our master’s program. To do this, we are moving some of our courses to the evening, allowing them to receive credit in some courses (e.g., consulting) from their work experience. This is providing a better workforce for the companies and good (tuition-paying) students for us.

                As mentioned above, we do provide free consulting to companies willing to work with our students. This has been especially useful for nonprofits without funds to hire statistical help.

                What are the challenges or barriers to such collaborations? What have you learned since your department began these collaborations to deal with these challenges?

                Challenges are locating people within the industry to partner with. Then, even after you have a working relationship with someone in a company, they may move on and you lose your contact.

                We have not found an effective way to locate people in industry with whom to partner. We rely on them finding us. Because we are in a large metropolitan area, this has worked for us, but I can see it would take a lot more resources than a faculty member/chair would have to cultivate relationships if you were in a smaller area.

                Most problems we get from local companies do not rise to the level of research problems for PhD students. They are still beneficial to train students in consulting. However, occasionally, there is a reluctance on the part of the company to pay the full cost of consultation, thinking the problem is helping supply our PhD students with dissertation problems. This has led to some awkward conversations and wasted time in scoping potential problems.

                VIRGINIA TECH

                Jennifer H. Van Mullekom is the director of the Statistical Applications and Innovations Group (SAIG) at Virginia Tech. She has collaborated on both sides of the fence as an industrial statistician for more than 18 years and now as an associate professor of practice.
                Anne Ryan Driscoll is an assistant collegiate professor at Virginia Tech. Her research interests include statistical process monitoring, design of experiments, and statistics education. She has also collaborated on projects for the Department of Defense and NASA.


                Please describe your department’s industry and/or government engagements/collaborations.

                The Virginia Tech Department of Statistics collaboration projects span grants from various government agencies, partners in the Virginia Tech Corporate Research Center, department of statistics corporate partners, and private companies that contact the department independently of our other programs.

                We currently have a large number of collaborations not related to large federal granting agencies such as the National Institutes of Health or National Science Foundation. Our longstanding Corporate Partners Program creates an opportunity to exchange ideas between corporate statistics leadership and our department. Corporate Partners creates a forum to receive input on our program, place our students in internships and permanent positions, and facilitate collaboration.

                We now have a new way to collaborate on short-term and long-term projects through the Statistical Applications and Innovations Group (SAIG), which recently became an external service center. SAIG can provide quotes for design, analysis, and reporting, which also may lead to research collaborations.

                How did the engagement/collaborations come about? How are the collaborations sustained in a way that is mutually beneficial to students, the university, industry, and the community-at-large?

                Collaborations originate in a variety of ways. Many of our government and industry collaborations have come through alumni employed at various agencies. They often encounter research questions in their daily work that are “important, but not urgent.” Their organizations lack the personnel to devote to these projects, so they turn to the university for both expertise and cost-effective flexible staffing to devote to the projects.

                Other collaborations result from master agreements negotiated at either the university or college level. When these projects are presented at conferences, we often create interest from other partners. And, of course, networking at national conferences through the American Statistical Association and other professional societies such as the American Society for Quality also lead to these relationships.

                The relationships are sustained by a successful track record of meeting deliverables. Our faculty purposely seek opportunities that align with their research interests and the interests of their students. They also scope opportunities properly and negotiate appropriate compensation for supervision and the students’ funding.

                The “important, but not urgent” distinction is also made so we set expectations appropriately. Students have course and degree requirements, so they are not capable of dropping everything to devote all their time to solving a highly time-sensitive problem. Regular program reviews and communications are essential to keeping the program on track.

                Another, often overlooked, avenue for research is that of a research associate or research professor. These are degreed staff members and faculty within the university who can be devoted full time to a more urgent problem.

                The Corporate Partners Program is another way our department fosters collaborations with outside entities. This program was established 19 years ago with the goal of solidifying the informal ties with industry and government built over many years. Most of the partnerships originate because of ties to alumni who are employed at various companies.

                Currently, our department benefits from partnerships with five companies. These partnerships are sustained by providing value to both the department and the company. Benefits to the company include an annual symposium and advisory board meeting to learn about initiatives at the department and university, opportunities to recruit students for internships and full-time employment, and easy access to faculty to foster joint research projects. The department benefits from feedback from the partners about refining our curriculum to tune our program to the rapidly changing needs of users of statistics, funding for graduate student scholarships and awards, research projects for faculty and students, and also employment opportunities for students.

                What arrangements about the collaborations might be helpful to share?

                Our Office of Sponsored Programs and the Virginia Tech Business Engagement Center provide excellent support in working through the logistics of relationships with outside entities. Existing relationships and agreements between VT industry affiliates and Corporate Research Center partners facilitate development of specific collaborations.

                A relationship can be initiated by any faculty member. With respect to business relationships, the faculty member then completes a request for appropriate legal agreements on behalf of the university. Once the appropriate documents have been negotiated and signed, the relationship progresses through the appropriate channels in the university depending on its nature. Smaller projects may be handled at the departmental level, while others are handled at the college level.

                Collaborations have varied time frames. For example, a short-term analysis collaboration with SAIG could be initiated by me and last a few weeks to a few years. Many of our long-term research relationships with professors and research groups within the department have lasted five years or more.

                What benefits for the department have you seen come out of these collaborations?

                The publications resulting from our collaborations are quite numerous, including ones in journals such as Journal of Quality Technology and Quality Engineering. A collaboration between Yili Hong and DuPont resulted in multiple publications and a SPES [Section on Physical and Engineering Sciences] award from the American Statistical Association, whereas one between Geoff Vining and NASA resulted in a NASA Engineering Safety Council Engineering Excellence Award. Those collaborations have also led to student dissertation topics with members of the sponsoring organization serving on the student’s committee.

                Anne Driscoll also works on the latter collaboration with NASA. Both Vining and Driscoll collaborate with the Department of Defense. An organically evolving collaboration between Baker Hughes, a GE Company, under Robert Gramacy has led to a line of research on computer model calibration of a seal used in oil and gas extraction that is the topic of a student’s dissertation. William (Bill) Woodall has worked with many external collaborators over the years, most recently with the Food and Drug Administration to provide input on their Quality Metrics Program. Additionally, Robertson Evia- has collaborated on K–12 STEM education studies to provide analysis resulting in Science Communication publications for the National Academy for the Advancement of Science.

                We have given short courses and webinars for our corporate partners and are continuing to evolve that relationship. We also look forward to forging new collaborations with external companies through SAIG.

                What benefits for the broader community have you seen come out of these collaborations?

                Our collaborations have certainly established strategic national government and industry partnerships, but our department also focuses on serving the local community. Christian Lucero is working through SAIG with Virginia Cooperative Extension to develop an analysis tool for a multicenter Centers for Disease Control and Prevention–sponsored diabetes management and prevention program. Our work has also resulted in grant applications for the local school systems, analytics supporting the building of a new dormitory for the Virginia Tech Corp of Cadets, and analytics to support policy and staffing in county governments.

                What are the challenges or barriers to such collaborations? What have you learned since your department began these collaborations that help with these challenges?

                Two of the barriers to collaborations with universities include the speed of establishing the legal relationships and data security. Both these problems typically have pre-existing solutions at most large research universities, but it often takes perseverance to execute these aspects of the projects properly. All parties involved must be familiar with the legal process and who to contact to initiate and sign agreements. A basic understanding of intellectual property is also important.

                Some of our statistics/data science relationships are more consulting in nature, whereas others may involve proprietary algorithm or software development. The boundaries of these relationships and IP [intellectual property] ownership must be established up front. Statisticians and data scientists also need to be able to educate their lawyers regarding the differences of applications versus IP-containing projects. Members of our profession also need to be aware when a project crosses the line into IP development and how to protect their contribution.

                Government and corporations have varying IT [information technology] security requirements. Personal health information creates its own unique challenges. Academicians are not typically “raised in this environment.” There is typically much more freedom in sharing information in academia. There is a learning curve associated with both partner requirements and on-campus resources for creating a secure IT environment. Due diligence on this front ahead of time can pay off in expedited project start-up.

                Any other comments?

                Professional development courses and leadership training provided by the American Statistical Association are crucial to the development of collaborations. An understanding of vision, mission, project management, emotional intelligence, and execution are essential to building and sustaining collaborations.


                Jennifer Broatch, an assistant professor and BS program lead at Arizona State University’s West Campus, assists junior faculty.
                Michelle Mancenido works to establish and coordinate industry collaborations and projects for BS statistics majors.


                Please describe your department’s industry and/or government engagements/collaborations.

                Our primary involvement with industry is a semester-long senior capstone project.

                We have three industry partners for this: a health care provider, a professional sports organization, and a global manufacturing company.

                The capstone sites present the student team with a sufficiently diverse range of statistical applications to choose from. Students are mentored by faculty from statistics and applied mathematics, but they are ultimately responsible for scoping their projects, collecting data, coordinating with sponsors, formulating statistical models, coding, and—most importantly—presenting the results of their study to their sponsors. Mentors (one per team) are only expected to provide students with advice and help overcome stumbling blocks in the course of the project.

                How did the engagement/collaborations come about? How are the collaborations sustained in a way that is mutually beneficial to students, the university, industry, and the community-at-large?

                The collaborations are based on faculty network connections. The arrangement is mutually beneficial. For ASU, students are able to work and deal with real-world data that can sometimes be massive and dirty. For the sponsors, the students come in with skills that help them solve business problems they do not have the manpower or resources to tackle. It has also provided a pipeline for qualified job applicants.

                The business problem tackled by the student team is selected in collaboration with our industry partners. Students are not simply handed data to analyze. They are active participants in the selection of the research project.

                What arrangements about the collaborations might be helpful to share?

                Each project is a semester-long contract. The contract is in the form of a project charter, which includes opportunity or problem statements, objectives, scope and limitations, and expected deliverables. The students develop these charters as part of their project management training. The students are also responsible and accountable for ensuring the delivery of quality output and meeting sponsor requirements such as deadlines.

                What benefits for the department have you seen come out of these collaborations?

                Our partnerships have directly led to jobs and internships within the industry partner. We also use an industry partner as an adjunct faculty to ensure the most current job skills. The capstone offers experience for junior faculty in business problems and the application of statistics (similar to a consulting center).

                What benefits for the broader community have you seen come out of these collaborations?

                In addition to the capstone, we partner with a local nonprofit conservation society. They have a great need for quality analysis, and—in turn—our students can get experience and help the local community at the same time.

                What are the challenges or barriers to such collaborations? What have you learned since your department began these collaborations to deal with these challenges?

                Always team dynamics. The students have a very tight timeline (four months), so they are pressured to deliver, which boils over when the dynamics are shaky to begin with. Hence, we add a team-building and leadership component to the course.

                Another is the scoping of the project. For most of the project sites, it is a part-time job, so the students sometimes find themselves overwhelmed with meetings, onsite data collection, etc. The faculty mentors are instrumental in ensuring the deliverables and project timeline are feasible.

                Company logistics and human resources are another hurdle. For example, our health care partner requires at least two months to get a student started in their system (HIPPA training, vaccinations, etc.)

                Finally, we have developed an excellent relationship with our sponsors; as long as the students keep delivering high-quality output, they are willing to accommodate the students year-in and year-out.

                Any other comments?

                I know these projects can often be a lot of work, but they have been overwhelmingly rewarding for our students.

                GMU Students Win Best Data Visualization

                Sun, 07/01/2018 - 7:00am
                Ilhan M. Izmirli, GMU Student Chapter Faculty Adviser

                  From left: Brooke Gipson, Alyssa McDonald, Evan Cypher, and Megan Maloney

                    This past April, the George Mason University (GMU) Student Chapter experienced two significant successes.

                    The first occurred when the GMU Student Chapter competed at DataFest DC 2018, hosted by Summit Consulting April 20–22, with 11 other area universities. Two teams participated:

                    Stat of the Art

                    Brooke Gipson
                    Evan Cypher
                    Megan Maloney
                    Alyssa McDonald
                    Mariya Prokhorenko

                    The Patriots

                    Ray Koser
                    Anushka Prativadhi
                    Abhinav Kimar
                    Jesse Scearce

                    George Mason’s presentation, “How Can Indeed Better Connect US Health Care Employers with Nurses?” won first place for Best Data Visualization.

                    The second success took place during Data Challenge DC the weekend of April 28. The GMU Student Chapter, led by Glen Hui, was instrumental in organizing the meeting. More than 30 students participated, six of which were from GMU. One of GMU’s graduate statistics students was on the team that won for best data visualization.

                    The EU General Data Protection Regulation Is Affecting—Maybe—Your Work

                    Sun, 07/01/2018 - 7:00am
                    ASA Privacy and Confidentiality Committee

                      The European Union’s (EU) recently adopted General Data Protection Regulation (GDPR) marks a major transition in data privacy protections in the European Union. And it may affect approaches to data access and confidentiality protections more broadly, including in US research and other statistical activities.

                      After four years of preparation and debate, the GDPR was approved and adopted by the EU Parliament in April 2016 and went into effect May 25, 2018. Many detailed daily practices remain to be worked out, including extraterritorial enforcement, but one thing is certain: The GDPR means more bureaucracy for all involved.

                      The GDPR replaces the Data Protection Directive. (A regulation—as is the GDPR—is a binding legislative act. It must be applied in its entirety across the EU, while a directive is a legislative act that sets out a goal all EU countries must achieve. However, it is up to the individual countries to decide how.) Unlike the current EU privacy directive, an EU regulation does not require any enabling legislation by member nations. It is designed to harmonize data privacy laws across Europe, protect and empower all EU residents’ data privacy, and reshape the way organizations across the region approach data privacy. The regulation applies to EU members and nation states that are not EU members but are members of the EU economic area.

                      In this increasingly data-driven world where privacy cannot be completely guaranteed, the GDPR seeks to protect EU residents’ privacy and against breaches and misuses of “personal data.” Personal data is defined in a broad context as any information relating to an identified or identifiable natural person (data subject). An identifiable natural person is one who can be identified—directly or indirectly—in particular by reference to an identifier such as a name; identification number; location data; online identifier; or one or more factors specific to the physical, physiological, genetic, mental, economic, cultural, or social identity of that natural person.

                      Some personal data is categorized as special data, which is essentially sensitive personal data covering religious or philosophical beliefs, health, racial or ethnic origin, trade union membership, political beliefs, sex life or sexual orientation, genetic data, and biometric data (including photos when used for the purpose of uniquely identifying a natural person) of individuals. The collection and use of special data is subject to greater restrictions than other types of personal data.

                      Pseudonymization is the processing of personal data in such a way that the data can no longer be attributed to a specific data subject without the use of additional information. This is the central feature of data protection by design. The GDPR looks favorably upon data controllers that keep “additional information” separate. To explain further, direct identifiers (name, Social Security number, or contact information) should be kept in a separate file from indirect identifiers, which can reveal identities if combined with additional data points. Personal data that has been pseudonymized (e.g., key-coded or as described above) falls short of being anonymized and therefore can fall within the scope of the GDPR, depending on how difficult it is to attribute the pseudonymized data to a particular individual.

                      The GDPR has important extraterritorial applications. It applies to personal information on EU residents even when they are outside the EU. It applies not only to personal data controllers and processors located in the EU, but also to those located outside the EU if their activities involve personal information on EU residents.

                      Coverage is triggered if the activities relate to offering goods or services to EU residents, irrespective of whether payment is required (e.g., over the internet), and monitoring behavior that takes place in the EU. When personal information on non-EU residents (e.g., for US residents) is transferred to an EU data controller or processor, that data becomes subject to the GDPR (Article 3).

                      Of course, breaking privacy is always a serious activity. Under GDPR, breaking privacy is now costly. Organizations—processors and controllers—in breach of GDPR can be fined up to 4% of the annual global turnover or 20 million euros (whichever is greater). This is the maximum fine that can be imposed for the most serious infringements (e.g., not having sufficient customer consent to process data or violating the core of Privacy by Design concepts).

                      Main Topics

                      Main topics in the GDPR include the following:

                      • In the GDPR, conditions for consent have been strengthened. Requests for consent must be given in an intelligible and easily accessible form, with the purpose for data processing attached to that consent, using clear and plain language. It must be as easy to withdraw consent as it is to give it.
                      • Under the GDPR, breach notification will become mandatory in all member states where a data breach is likely to “result in a risk for the rights and freedoms of individuals.”

                      GDPR has increased data transparency and empowers data subjects. It gives data subjects the right to obtain from the data controller confirmation of whether personal data concerning them is being processed, and if so, where and for what purpose. The controller shall provide a copy of the personal data, free of charge.

                      The right to be forgotten entitles the data subject to have the data controller erase his/her personal data, cease further dissemination of the data, and potentially have third parties halt processing of the data. The conditions for erasure, as outlined in Article 17, include the data no longer being relevant to original purposes for processing or a data subjects’ withdrawing consent.

                      Privacy by design is also included in the GDPR. Privacy by design calls for the inclusion of data protection from the onset of the designing of systems, rather than an addition. More specifically, “The controller shall … implement appropriate technical and organisational measures … in an effective way … in order to meet the requirements of this Regulation and protect the rights of data subjects.” Article 23.

                      GDPR and Research

                      Research occupies a privileged position in the GDPR. By harmonizing privacy legislation across the EU member states and carving out exemptions for scientific, historical, statistical, and health research, the GDPR seeks to reconcile the often-competing values of privacy and innovation.

                      The research regime set out in Article 89 expressly allows across the EU the following:

                      • Broad consents for scientific research where consent cannot be secured for all specific purposes at the outset of data collection
                      • Further use of personal data for scientific or statistical research as a secondary compatible purpose
                      • The right of the data subject to object to processing of personal data (unless necessary in public interest)
                      • Restriction of the right of a data subject to exercise their “right to erasure” if it is likely to significantly impair processing for scientific research purposes
                      • Relaxation of the storage limitation principle granting the ability to store personal data for longer periods
                      • Isolated transfers of personal data to third countries taking into account legitimate expectations of society for an increase in knowledge

                      Additionally, information obligations in scientific research do not apply if they would involve a disproportionate effort. Consideration of this takes into account the number of data subjects and age of the data and appropriate safeguards must be adopted. Furthermore, there is “no right to be forgotten” if it is likely to significantly impair processing for scientific research purposes. Use of the Article 89 research regime is subject to the following conditions:

                      • Appropriate safeguards to protect the right and freedoms of the data subject
                      • Adequate technical and security measures entrenching the principle of data minimization and using pseudonymized data as default
                      • Compliance with recognized ethical safeguards

                      The grounds that researchers can use to process personal data are the following:

                      • Consent of the data subject/research participant for the research purpose(s).
                      • Legitimate interests of the data controller (or a third party). In determining what these legitimate interests are, you need to ensure you balance the interests of the controller with any prejudice to the rights and freedoms or the interests of the data subject. In assessing whether the data controller has a legitimate interest, you need to take into account the reasonable expectations of the data subject. Public authorities cannot base processing on this ground.
                      • Performance of a public interest task or exercise of official authority.
                      GDPR and EU-US Privacy Shield

                      Under both the GDPR and the earlier directive, the EU doesn’t allow the transfer of data on EU residents outside the EU unless the country is deemed to have adequate data privacy laws. Unfortunately, the EU has deemed that the United States does not currently have adequate data privacy laws, but organizations can navigate this by adhering to the EU-US Privacy Shield.

                      The EU-US Privacy Shield is a program in which participating US companies are considered to have adequate data protection and can therefore facilitate the transfer of EU data. The EU-US Privacy Shield’s predecessor, the Safe Harbour Framework, was overhauled because the EU did not consider this agreement strict enough on data protection for their citizens. The GDPR protects the data of all EU residents, regardless of whether they currently live in the EU.

                      Being certified under the EU-US Privacy Shield can give your company a jump-start on fulfilling the GDPR’s standards and provide legal clarity and direction on the EU’s data protection laws, but it will not guarantee total GDPR compliance. It is also important to note that the EU-US Privacy Shield will be revisited every year and could change, so it is important to have an assigned employee/person to stay current with all the updates.

                      Helpful Resources

                      General Data Protection Regulation (GDPR) Guidance Note for the Research Sector: Appropriate Use of Different Legal Bases Under the GDPR.

                      What You Need to Know About the EU-US Privacy Shield and the GDPR.

                      ICO (2018) Guide to the General Data Protection Regulation (GDPR). Information Commissioner’s Office.

                      ICO (2017) Preparing for the General Data Protection Regulation (GDPR): 12 Steps to Take Now. Information Commissioner’s Office.

                      Insights Association (2017) GDPR: FAQs on the EU General Data Protection Regulation.

                      Maldoff, G. (2016) Top 10 Operational Impacts of the GDPR: Part 8 – Pseudonymization. The Privacy Advisor.

                      Government Statistics Section Announces JSM Program

                      Sun, 07/01/2018 - 7:00am
                      Submitted by Gina Walejko, GSS Program Chair

                        The Government Statistics Section (GSS) organized three invited sessions, including a panel on using multiple data sources for federal statistics; seven topic-contributed sessions, including an update on the US Commission on Evidence-Based Policymaking; three roundtables, including a lunch discussion on combating breaks in time series when using multiple data sources; five contributed sessions; and one poster session. In addition to sponsoring these events, GSS is co-sponsoring eight invited sessions, six topic-contributed sessions, and six speed sessions.

                        In addition, GSS is co-sponsoring a short course with the Section on Survey Research Methods (SRMS), titled “Applications of Hot Deck Imputation to Survey Data,” July 31 with Rebecca Andridge of The Ohio State University and Jenny Thompson of the U.S. Census Bureau as instructors.

                        Hot deck imputation is commonly used for handling missing data in which each missing value (recipient) is replaced with an observed value from a “similar” unit (donor). This half-day course is designed for survey practitioners who are interested in “seeing the methods in action.” Using examples from household and establishment surveys, the instructors will explore each step of hot deck imputation, beginning with different donor selection options through variance estimation methods. The course will cover classical hot deck methods alongside more cutting-edge approaches, including fractional hot deck imputation. The instructors will share their experiences with challenges that arise in the implementation of the hot deck—such as having fewer donors than recipients—and discuss various methods for overcoming these challenges.

                        More information about sessions, roundtables, and courses can be found online. As a reminder, roundtable and course space is limited, so sign up soon.

                        Physical and Engineering Sciences Section Readies for JSM

                        Sun, 07/01/2018 - 7:00am
                        Byran Smucker, SPES Chair-Elect, and Yili Hong, SPES JSM 2018 Program Chair

                          The events formerly known as the SPES/Q&P and Risk/SDNS mixers are morphing into one four-section joint mixer. This year, it will be the SPES/Q&P/Risk/Defense mixer at the 2018 Joint Statistical Meetings in Vancouver. We hope to see you Tuesday, July 31, in the Fairmont Waterfront Ballroom A from 6:30 p.m. to 8:30 p.m. 

                          In the past, generous organizations and individuals have donated items such as books, software, CDs, DVDs, T-shirts, hats, ties, overalls (yes, overalls), pens, bags, water bottles, golf balls, blankets, coffee mugs, thumb drives, and the coveted Doughboy! Donated gifts have been both statistics and nonstatistics related.

                          We appreciate the generosity of our donors and hope you will consider adding to the excitement of the evening by donating door prizes this year. Of course, we will acknowledge all donors at the mixer.

                          The meetings are fast approaching, but there is still time to donate. Just complete the form at Survey Monkey to provide contact information and donation descriptions.

                          We would prefer you bring the items to the mixer or have them available at your booth for pickup. Also, mark the box of items “For SPES/Q&P/Risk/SDNS” in large letters so it is easily identified.

                          SPES JSM Contributed Sessions in Vancouver

                          SPES has the following four contributed sessions in place for the upcoming JSM in Vancouver:


                          • Computer Experiments, Statistical Engineering, and Applications in Physical Sciences


                          • New Development in Reliability Models and Innovative Applications


                          • Machine Learning and Applications in Complex Engineering Systems
                          • Recent Developments in Designs of Experiments and Responses Surface Models

                          For more information, check out the JSM 2018 Online Program.

                          Q&P Section Highlights Topic-Contributed, Contributed Sessions

                          Sun, 07/01/2018 - 7:00am

                          The Quality and Productivity (Q&P) section is sponsoring the following topic-contributed and contributed sessions at the Joint Statistical Meetings this year:

                          • New-Generation Experimental Design and Causal Inference in High-Tech Companies, organized by Tirthankar Dasgupta, Rutgers University
                          • Statistical Process Monitoring of High-Volume Data Streams, organized by Emmanuel Yashchin, IBM Research
                          • Field to Fork: Leading with Statistics in the Food Industry, organized by Shankang Qu, PepsiCo
                          • Modeling, Analysis, and Assessment, chaired by Douglas Ray, US Army RDECOM ARDEC
                          • Advances in Statistical Process Control, chaired by Ronald Fricker, Virginia Tech

                          Attendees are encouraged to use the online program to search for Q&P sessions. The Q&P Section also works closely with other ASA sections to co-sponsor sessions. In these situations, you will see Q&P listed as a co-sponsor in the online program, which contains more sessions than are listed above.

                          Planning for Data for Good at JSM

                          Sun, 07/01/2018 - 7:00am
                          This column is written for those interested in learning about the world of Data for Good, where statistical analysis is dedicated to good causes that benefit our lives, our communities, and our world. If you would like to know more or have ideas for articles, contact David Corliss.

                          With a PhD in statistical astrophysics, David Corliss works in analytics architecture at Ford Motor Company while continuing astrophysics research on the side. He serves on the steering committee for the Conference on Statistical Practice and is president-elect of the Detroit Chapter. He is the founder of Peace-Work, a volunteer cooperative of statisticians and data scientists providing analytic support for charitable groups and applying statistical methods to issue-driven advocacy in poverty, education, and social justice.

                          With JSM just around the corner, it’s a good time to think about how to include Data for Good in your JSM activities. JSM is a huge event and can seem overwhelming. However, with a bit of planning, the Joint Statistical Meetings can be tamed and enjoyed.

                          It’s important to resist the temptation to overbook, dashing from one presentation to the next. JSM is about so much more than the papers! One strategy is to find the “big rocks”—a small number of activities most important to you—put them in your schedule, and then plan around them.

                          Every person can make sure Data for Good is one of those big rocks. Be sure to include time for meeting, networking, and just enjoying the event. As Student t often plays a role in my own D4G work, I always pay proper homage to William Gossett by raising a glass of a certain Irish stout.

                          When selecting papers, note how important it is to attend in person. For example, I don’t know why anyone would want to attend mine, which is about keeping your skill set up to date by doing Data for Good projects, because the content is just as good in print (but the rest of the invited session is great). Make a list of the papers you can read later and the big rocks to see in person.

                          Networking is a huge part of conferences! Plan time for this. If there is a person you want to meet, attend a paper they are presenting (if there is one) and don’t book the following time slot.

                          Highlighted D4G Papers

                          An invited session, Data Science for Social Good, will be presented Thursday, August 2, from 10:30 a.m. to 12:20 p.m. DataKind founder Jake Porway will speak about designing for impact, followed by Darren Banks from RTI, who will touch on arrest-related deaths, and Erika Salomon from The University of Chicago, who will discuss interventions for people at risk of incarceration. The papers—and especially the discussion time at the end of the session—will be an important D4G highlight for JSM 2018.

                          Projects by Statistics without Borders (SWB) and their partners are featured in several presentations. An invited session August 1 from 8:30 a.m. to 10:20 a.m. will highlight recent SWB projects, including work related to the European migrant crisis and winter shelter for survivors of the 2015 Gorka earthquake.

                          Keep in mind that many of the most valuable presentations will be those on methodology that normally don’t say D4G on the label. Margaret Levenstein’s paper, “Transparency, Reproducibility, and Replicability in Work with Social and Economic Data” is one good example. Presentations about working with public data sources, such as those mentioned in the May Stats4Good column, and those focusing on collaboration and communication with nonstatisticians will be especially helpful.

                          Not Attending JSM?

                          Not going to JSM, but interested in doing more with Data for Good? The presentations and other resources are not for attendees only. As JSM is a nexus of all things statistical, searching the speakers, talks, and posters is valuable for anyone, but perhaps most of all for those unable to attend. Most of the research for this month’s column came from the JSM online program, which is a tremendously valuable resource. Each person will want to look for subjects and speakers that interest them most. If you can’t be there in person, you can still mine the presentations, look for opportunities, and make connections for your next project.

                          Bringing Data for Good Home

                          There are so many great opportunities at JSM, and everyone can make Data for Good one of them. Be sure to take some time to talk with presenters. Think about possibilities for your next D4G project and get connected with the people involved. When you are ready to leave, be sure to bring JSM—and Data for Good—home with you!

                          Obituaries for June 2018

                          Fri, 06/01/2018 - 11:01am
                          Prodyot Kumar Bhattacharya

                            Prodyot Kumar Bhattacharya

                            Prodyot Kumar Bhattacharya passed away March 9, 2018, at his home in Davis, California. He was professor emeritus at the University of California at Davis and contributed to the field of statistics during a career that spanned more than 50 years.

                            PK, as he was called by many colleagues and friends, entered Presidency College to earn his bachelor’s degree in statistics and ultimately received his master’s degree and PhD under the supervision of H.K. Nandi from Calcutta University. In 1960, he traveled to the United States and held postdoctoral positions at The University of North Carolina at Chapel Hill and Stanford University. After a brief period at the Indian Statistical Institute (ISI) in Calcutta, he returned permanently to the US in 1965 upon accepting a position at the University of Arizona. He spent sabbatical terms at the University of Minnesota, ISI, and Massachusetts Institute of Technology. In 1980, he left Arizona to help establish the UC Davis Division of Statistics, where he remained until his retirement in 1994. He supervised PhD students, served on the editorial boards of Sankhya and the Annals of Statistics, and, in 2016, published Theory and Methods of Statistics, a book for advanced graduate students and research statisticians, with his co-author, Prabir Burman.

                            PK’s early seminal work, published in the Annals of Mathematical Statistics in 1966, proposed a uniformly superior estimator for the mean of a multivariate normal vector under unknown variance and generalized loss function, an important expansion on Charles Stein’s surprising result showing inadmissibility of the ordinary least squares estimator in dimensions exceeding two. Throughout his career, PK maintained special interest in nonparametric estimation functions and change-point analysis, an area that led to demonstrating the large sample behavior of the maximum likelihood estimator of an unknown change-point through a Brownian motion process with drift. His research was motivated by unusual problems across a spectrum of disciplines. Of particular note, his collaboration in a cosmological application led to a nonparametric inference method for a regression model having errors with infinite variance and a truncated response, an approach that reconciles the red shift effect of a light source in an ever-expanding universe and the truncation arising from the low luminosity of distant objects. The method allows analysis and interpretation of complex astronomical data, such as those collected by the Hubble Space Telescope.

                            PK was born on September 30, 1930, in Calcutta, India. The fourth of six children, he lost his mother and younger sister when he was a young boy. Despite hardship at an early age, he found joy in the books he discovered at the local Boys’ Own Library. He developed a special fondness for Bengali and English poetry and, for the rest of his life, could recite from memory the verses that moved him during his school days. He loved popular and classical Indian and western music, all kinds of food and spirits, and traveling to all corners of the world. He was happiest when sharing these lifelong passions with others, whether it was setting out his favorite selection of cheeses, introducing his grandchildren to classic movies, or attending an opera performance in San Francisco or New York.

                            PK left an indelible mark on science and the lives he touched through his intellect, humor, generosity, and spirit of adventure. He is survived by his wife of 54 years, Srilekha; his daughters, Suparna Jain and Aparna Anderson; and his grandchildren, Arjun and Anjali Jain and Anil and Mira Anderson.

                            Eun Sul Lee

                            “The man departs—there remains his shadow.”
                            -Chinese aphorism

                            Eun Sul Lee, age 83, died peacefully with his family surrounding him on April 2, 2018, at the Mirabella retirement community in Portland, Oregon. The retired professor was a scholar; teacher and mentor; author; origami master; true gentleman; and devoted husband, father, and grandfather of three.

                            Born in Gongju, Korea, in 1934, Eun Sul lived through the end of the Japanese occupation (1945) and the Korean War (1950–1953) before he went to college at Seoul National University, where he studied sociology. After college, he worked as a translator at the Christian Children’s Fund in Seoul, where he met his future wife, Chong Mahn. They were engaged in Seoul before they both moved to the United States to attend graduate school—he at the University of Kentucky (for an MA in statistics) and she at the Pittsburgh Theological Seminary. Later, he earned his PhD in experimental statistics and sociology from North Carolina State University.

                            Eun Sul began his academic career at the University of Texas School of Public Health in Houston in 1969 and remained there for 36 years, until his retirement. While at UT, he advised master’s and doctoral students and taught classes in demography, biostatistics, survey sampling and community health assessment, planning, and evaluation. He also participated in numerous funded research projects and served on review committees for the National Cancer Institute; National Heart, Lung, & Blood Institute; and National Institute of Mental Health (NIMH). He also consulted extensively with the NIMH and the World Health Organization.

                            While on leave from UT from 1994 to 1996, he developed and chaired the department of preventive medicine and public health at Ajou University Medical School in Suwon, Korea. He also taught and consulted at several universities in Asia, including Seoul National University, Yonsei University, Gunma University, and the Hokkaido University.

                            Upon his retirement in 2005, Eun Sul and Chong Mahn moved to Portland, Oregon, where he became an adjunct professor in the department of public health and preventive medicine at the Oregon Health & Science University (OHSU). He also provided statistical consulting services for the Mental Health Services Research Program at the Portland Veteran Affairs Medical Center.

                            Eun Sul participated in the writing of more than 100 journal articles and scholarly reports, authored three textbooks (one in Korean and two in English), and wrote a memoir titled Dreaming with One Eye Open for his children and grandchildren. In his memoir, he chronicled his family history, childhood in Korea, life during wartime, move to the United States, and, later in life, coming to terms with his father’s legacy.

                            His father, Lee Chul Ha, died in 1936 after being imprisoned by the Japanese for protesting colonial rule in Korea. Eun Sul grew up knowing little about his father. While on sabbatical in Korea in 1992, he discovered his father was one of the leaders of the nationalist resistance movement in his hometown and was active in a student revolutionary group in Seoul. When these findings were made known to the South Korean government, his father was honored with a Patriot’s Medal in 1993 and his grave was moved to the National Cemetery shortly thereafter.

                            Eun Sul is survived by his wife, Chong Mahn Lee; daughter, Margaret Juhae Lee; son-in-law, Steven Paul Francis Olson; son, Edward Tongju Lee; daughter-in-law, Amy Lee Lacks; and three grandchildren, Owen Sung Ya Lee Olson, Dahlia Mina Lee, and Kiana Yong Mi Lee Olson.

                            A private ceremony will be held. Memorial donations may be made to the Oregon Health & Science University Foundation.

                            Herman Rubin Written by Anirban DasGupta

                              Herman Rubin, professor of statistics and mathematics at Purdue University, passed away in West Lafayette, Indiana, on April 23, 2018; he was 91.

                              Herman was among the last remaining great polymaths of the 20th century. To all who knew him or had heard about him, he was an inexplicable outlier in numerous ways. His unique ability to understand a new problem and arrive at the answer almost instantly baffled even the wittiest mathematicians. He never forgot a fact or a theorem or a proof. He would solve a complete stranger’s problem without expecting co-authorship or anything in return. He would fight for someone who opposed him at every step. He would stand on his principles with the last drop of blood in his body. Herman’s death marks the end of a unique era following World War II that saw the emergence of a group of supremely talented statisticians who would mold the foundations of the subject for decades to come.

                              Herman earned his PhD from The University of Chicago at a young age; he was a student of Paul Halmos. After a stint at the Cowles Commission, he formed a productive intellectual affinity with Ted Anderson, Charles Stein, and Ingram Olkin; at that same time, he also became professionally close to David Blackwell and Meyer Girshick. With Ted Anderson, he wrote two phenomenal papers on fundamental multivariate analysis that worked out the fixed sample and asymptotic distribution theory of MLEs in factor analysis models and structural equation models. These results have entered into all standard multivariate analysis and econometrics texts and have remained there for more than a half century. Herman’s most famous and classic contribution to inference is the widely used and fundamental idea of monotone likelihood ratio families. Anyone who has ever taken a course on testing of hypotheses knows how fundamental the idea and results in the 1956 paper with Samuel Karlin were. It was this work that led to Karlin’s hugely influential TP2 and variation diminishing families with shadows of Isaac Schoenberg and Bill Studden lurking in the background.

                              Following this period, Herman made novel entries into various aspects of probability and asymptotics. With J. Sethuraman, he did theory of moderate deviations. With Herman Chernoff, he attacked the then novel problem of estimating locations of singularities, and how, precisely, the asymptotics were new. With Prakasa Rao as his student, he got into the problem of cube root asymptotics for monotone densities. With C. R. Rao, he gave the classic Rao-Rubin characterization theorem. And, to many, the crown of the jewel was the invention of the Stratonovich integral.

                              Herman really did enjoy particular problems, as long as they were not mundane particular problems. Classic examples are his papers with Rick Vitale that show sets of independent events characterize an underlying probability measure, degeneracies aside; his work with Jeesen Chen and Burgess Davis on how nonuniform a uniform sample can look to the eye; his work with Tom Sellke on roots of smooth characteristic functions; his work on the Bayesian formulation of quality control with Meyer Girshick; the hilariously bizarre but hard problem of estimating a rational mean; his papers with Andrew Rukhin on the positive normal mean; his work on the notorious Binomial N problem; and his work on Bayesian robustness of frequentist nonparametric tests. There are others. Herman never thought of who would cite or read a result; if he wanted to solve a problem, he did.

                              Herman was probably one of the lifelong Bayesians, but a purely axiomatic one. He really did take most of the Savagian theory and axioms literally; he expanded on them, though later. An expansion was published in Statistics and Decisions (to my knowledge, with extremely active help from Jim Berger). He would not budge an inch from his conviction that the likelihood and prior are inseparable. He would refuse to discuss what an appropriate loss function was; he would insist you ask the client. He would nevertheless want to see the full risk function of a procedure and would study Bayes through the lens of Bayes risk, and even exclusively Bayes risk, namely the double integral. On asymptotic behaviors of procedures, he did not appear to care for second-order terms. He has shown his concern for only calculating a limit time and again. A glorious example of this is his work with J. Sethuraman on efficiency defined through Bayes risks; this was so novel it entered into the classic asymptotic text of Robert Serfling. He came back to it many years later in joint work with Kai-Sheng Song in an Annals of Statistics article.

                              In certain ways, Herman came across as self-contradictory. He would publicly say only Bayes procedures should be used. But he would oppose the use of a single prior with all his teeth. He would be technically interested in robustness of traditional frequentist procedures, although he would portray them as coming out of wrong formulations. Well-known examples are his well-cited papers with Joe Gastwirth on the performance of the t-test under dependence. He did not have the personal desire to burn the midnight oil on writing a comprehensive review of some area, but he would be an invaluable asset if someone was writing one such. An example is his review of infinitely divisible distributions with Arup Bose (and this writer). An all-time classic is his text Equivalents of the Axiom of Choice, jointly written with his wife, Jean Rubin. Jim Berger thanks Herman profusely in the preface of his classic Springer book on decision theory and Bayesian analysis; Charles Stein acknowledges Herman and Herbert Robbins in his first shrinkage paper.

                              There was a fairly long period when nearly every paper written in Herman’s home department had his contributions in it. He never asked for or got credit for them. He defined the term scholar in its literal dictionary sense. With the passing of Herman Rubin, a shining beacon of knowledge and wisdom is gone. Herman was an absolute and consummate master of simulation, characteristic functions, and infinitely divisible distributions. He kept to himself a mountain of facts and results on these and other topics. There was never a person who did not respect Herman Rubin’s brain; even Paul Erdös did. He was an inaugural fellow of the American Mathematical Society and a fellow of the Institute of Mathematical Statistics.

                              Herman had sophisticated taste in music and literature. He was often seen at classical concerts and operas. He helped mathematical causes financially. Herman was probably one of the few people who could work out the NY Times crossword puzzle on any day in about an hour. Herman is survived by his son, Arthur, and daughter, Leonore.

                              Two Selected for Natrella Scholarship

                              Fri, 06/01/2018 - 7:00am
                              Will Guthrie, Natrella Scholarship Selection Committee Chair

                                The Quality and Productivity Section will award Mary G. and Joseph Natrella scholarships to Anh Bui, a PhD candidate in industrial engineering and management sciences at Northwestern University, and Xiaowei Yue, a PhD candidate in the department of industrial and systems engineering at the Georgia Institute of Technology, during the 2018 Joint Research Conference on Statistics in Quality, Industry, and Technology, which will be held June 11–14 in Santa Fe, New Mexico.


                                Both Bui and Yue will give a research presentation at the conference and receive a $3,500 scholarship, plus $500 for travel expenses and complimentary registration for the conference and pre-conference short course.

                                Bui was recommended for the award by Daniel W. Apley of Northwestern University and Chi-Hyuck Jun of Pohang University of Science and Technology in Pohang, South Korea. His presentation at the conference is titled, “Monitoring Stochastic Textured Surfaces.”


                                Yue was recommended for the award by Jianjun Shi and Chuck Zhang of Georgia Institute of Technology. The title of his presentation is “Engineering-Driven Data Analytics for Quality Improvement.”

                                The winners were chosen for their outstanding teaching, community service, mentoring, leadership, scholarship, and commitment to the pursuit of quality improvement through the use of statistical methods.

                                Update from the ASA Task Force on Sexual Harassment and Assault

                                Fri, 06/01/2018 - 7:00am
                                Leslie McClure, Task Force on Sexual Harassment and Assault Chair

                                  Over the past few years, public acknowledgement of sexual harassment/assault has emerged as a critical workplace and professional issue in need of greater attention. No social environment is immune to it. Members of associations like the American Statistical Association deserve policies that preserve the dignity of members individually and professionally. In November of 2017, the ASA Board of Directors approved the formation of the Task Force on Sexual Harassment and Assault.

                                  The charge of the task force is as follows:

                                  1. Assess the extent of sexual harassment/assault in the ASA community.
                                    • Review surveys used by other professional organizations to assess the prevalence of sexual harassment/assault.
                                    • Develop an ASA membership survey to assess the frequency, location, and kinds of harassment/assault occurring.
                                    • Distribute the survey to ASA membership.
                                    • Summarize the findings from the survey.
                                  2. Review the current best practices of professional organizations and academic institutions with respect to sexual harassment/assault.
                                  3. Consider creation of a resource that allows victims of sexual harassment and assault to anonymously receive support.
                                  4. Make recommendations to the ASA Board of Directors regarding sexual harassment/assault policy changes for the organization.

                                  What follows is an update on our activities since the task force was approved by the board.

                                  During the two months following the formulation of these charges, the ASA president, in consultation with the executive director, appointed task force members with the goal of including a diverse, representative cross-section of the ASA membership. The membership of the task force can be found on the ASA website.

                                  The task force members convened for the first time at the end of January and have met a few more times since. There are regular meetings scheduled going forward and members have begun addressing the charges above. Task force members are diverse and each brings different experiences to the table, thus enabling lively discussion with a variety of perspectives.

                                  Following is the progress made on each of the four main charges:

                                  Survey of Sexual Harassment/Assault in the ASA Community
                                  We are fortunate to have experienced survey statisticians among our task force membership who drafted a plan describing options for developing and implementing a way to gather information about our membership’s experiences and perceptions of sexual harassment. As we reviewed the potential paths available for this effort (e.g., formal or informal survey, census), it became clear this was an undertaking larger than could be handled by the task force. The ASA has thus graciously agreed to fund a membership survey and has put out a request for proposals (RFP) to external organizations.

                                  The chosen organization will contact all ASA members and give them an opportunity to answer a set of questions related to their experiences and perceptions of sexual harassment. The responses will not constitute a probability sample, but will provide valuable information about the severity of these issues among our membership.

                                  In addition to the obvious benefits of allowing professionals to manage this effort, it also allows the data to “live” outside of the ASA, which is important given the sensitive nature of the data collection.

                                  The RFP was developed by the ASA staff and has been reviewed and revised by the task force. It was made publicly available on April 25, 2018.

                                  Early in our discussions, we reached out to colleagues at the American Political Science Association (APSA), which recently published the results of its survey on sexual misconduct in their discipline. We received important and useful feedback from their executive director that helped guide some of our discussions about our approach.

                                  Review of Best Practices
                                  We have been assembling information from other professional organizations regarding their policies on sexual assault and harassment, both for meetings and professional conduct. In this vein, we included a request for input from ASA members in the April 18 member e-newsletter.

                                  Resource for Anonymous Reporting
                                  We have not yet directly addressed the development of a mechanism for anonymous reporting of incidents of sexual assault and harassment; however, for most of our discussions, reporting is an issue we have touched on. As we move forward with developing policy recommendations, discussions of a reporting mechanism will be the next step.

                                  Policy Recommendations to the ASA Board
                                  With respect to policy recommendations to the ASA Board, we have started the process of examining the current meeting conduct policy and are brainstorming ways to improve the policy and the means by which it is communicated to the ASA membership. This has led to discussions about policy for meeting conduct vs. policy for professional conduct. In addition, we have had much discussion about psychological, confidentiality, legal, and reporting issues that may arise through implementation of such policies, thus resulting in recommendations that the ASA employ an ombudsperson for the Joint Statistical Meetings. This would allow reporting to occur in a confidential manner and to someone who has training in the psychological and legal actions necessary in these situations.

                                  In addition to the topics described above, we have talked about how to engage the ASA community more broadly in our efforts. We have therefore reached out to the Committee on Women in Statistics, Committee on Professional Ethics, and Committee on Membership Retention and Recruitment to ensure we align our efforts. We are particularly interested in working with the Committee on Professional Ethics to ensure we address the professional conduct aspects of sexual misconduct. In addition, as described above, we have solicited input from the ASA membership regarding best practices for an inclusive meeting/organization and plan to solicit input on our draft policy recommendations.

                                  We have made a decision to be proactive, rather than reactive, and to think about the long-term goals of our recommendations. It is our hope that the recommendations we make are approved by the ASA and make an impact on the health and happiness of our organization.

                                  The ASA Task Force on Sexual Harassment and Assault welcomes your input and invites you to provide feedback.

                                  Section on Statistics in Epidemiology Holds Annual Young Investigator Awards

                                  Fri, 06/01/2018 - 7:00am

                                  The Section on Statistics in Epidemiology (SIE) grants annual Young Investigator awards to new researchers for the best papers in statistics in epidemiology presented at JSM. Among the Young Investigator Award winners, the Breslow Award further recognizes the top paper.

                                  The section presents the 2018 Young Investigator awards to the following individuals:

                                  • Maria Cuellar, Statistics, Carnegie Mellon University (Breslow Award Winner)
                                  • Parichoy Pal Choudhury, Biostatistics, The Johns Hopkins University
                                  • Kwonsang Lee, Biostatistics, Harvard University
                                  • Maya Mathur, Biostatistics, Harvard University
                                  • Ran Tao, Biostatistics, Vanderbilt University
                                  • Kai Yang, Biostatistics, University of Florida

                                  An awards ceremony will be held at this year’s JSM in Vancouver on Tuesday, July 31, at 6:30 p.m. in recognition of the awardees. The ceremony will be followed by a joint mixer with the Mental Health Statistics Section. Visit the JSM online program for an up-to-date location.

                                  You Can Count on Us

                                  Fri, 06/01/2018 - 7:00am

                                  Lisa LaVange

                                  A new term entered our national vernacular last year: “alternative facts.” Although its use has provided new material for the comic stage and late-night talk shows, it has caused consternation among scientists.

                                  JSM 2017 featured no fewer than five sessions about government statistics, including one titled “Doomed Data … When National Governments, Coerced Narratives, and Alternative Facts Override the Quality, Importance of Statistics.” And earlier this year, the AAAS annual meeting featured a brainstorming session about ways to deal with or push back against alternative facts shown to be false.

                                  Even before alternative facts became a reality (pun intended), ASA Board members had an interest in determining our membership’s views on official statistics and whether public confidence in them had been affected by public dialogue. We engaged Stanton Communications to conduct focus group interviews to this effect, and out of this initial data gathering grew an exciting ASA initiative: Count on Statistics.

                                  In early May, I had the opportunity to interview Megan Berry from Stanton Communications about the initiative. Here is what she had to say:

                                  Why did the ASA decide such a project was needed?

                                  Berry: Amid rising concerns about public confidence in US government statistics, the American Statistical Association commissioned Stanton Communications to conduct a study to determine the feasibility of a public outreach initiative to enhance awareness of the importance, reliability, and trustworthiness of government statistics.

                                  We conducted more than a dozen interviews with key ASA leaders, members, and subject-matter experts with a perspective on this topic. One such interviewee stated, “We do not need to determine if there is a problem. There is a problem. The public doesn’t trust government statistics or understand where the data are coming from.”

                                  Through these candid conversations, Stanton determined the opportunities, challenges, and objectives a strategic communications program may involve. Clearly, there was a need for a program with the mission to “distinguish federal statistics as absolutely essential to the functions of our democracy.” With the support of ASA leadership and the board, we created Count on Stats to do just that.

                                  What approach has the campaign taken and why?

                                  Berry: The campaign has focused on communicating the benefits of the federal statistical system—how we, as a society, “Count on Stats.” To promote this message, we work to influence the influencers, engage the user base, and amplify agency and partner communications through a variety of channels. We have engaged our key audiences—our allies, the press, members of Congress, the business community, and statistical agencies—through social media, op-eds, blogs, media interviews, press releases and statements, monthly e-newsletters, and even articles in Amstat News.

                                  What has been accomplished thus far?

                                  Berry: Our early efforts have focused on developing a social following, primarily on Twitter, responding to threats to the system, and building relationships with key members of the media. We have garnered direct mentions in CQ Magazine, Associations Now, and City Lab. ASA Executive Director Ron Wasserstein was also featured on the Consortium of Social Science Association’s Why Social Science series, expressing how statistical agencies produce data essential for democracy. Last week, Count on Stats also sponsored a panel at SABEW18 on accessing accurate government statistics and concerns about disappearing data.

                                  What is planned for the future?

                                  Berry: In the coming months, we will be doing more to reach out to members of the media and policymakers. This will help us proactively influence the conversation and gain a further reach. We also plan to continue emphasizing the importance of the federal statistical system by featuring a statistical agency on Twitter every week. In addition, the Count on Stats team is working to develop and host a panel featuring speakers from Congress, the press, and the federal statistical community. With this integrative approach, we hope to better educate our audiences and rebuild the public’s trust in federal statistics.

                                  Learn more about the Count on Stats initiative. Also, search for it on Twitter using @CountonStats.

                                  Whether encouraging and training statisticians to fulfill their leadership potential or making sure official statistics are understood and valued, just remember—you can count on the ASA!

                                  Meet Erica Groshen

                                  Former BLS Commissioner and Leadership Institute Steering Committee Member

                                  A former director of the second-largest federal statistical agency, the Bureau of Labor Statistics (BLS), is the final member of the ASA Leadership Institute’s Steering Committee to be in the President’s Corner spotlight. We are privileged to have Erica Groshen, BLS commissioner from 2013–2017, advising the institute on the development of strong statistical leaders. Erica is currently a visiting senior scholar at Cornell University’s School of Industrial and Labor Relations (ILR). Prior to leading the BLS, she worked in the Federal Reserve System. Throughout her career, she has maintained a focus on research, development, and outreach. As a labor economist, Erica’s research taps into employer data to better understand the role of employers in the labor market and to gain insight into wage differences, rigidity, and the impact of recessions.

                                  Regarding statistical leadership, Erica contributed one of my favorite quotes to date from the Institute’s Steering Committee. When discussing the importance of leadership training for statisticians during our first meeting, she noted that, “People rise to leadership positions from different career paths, and CEOs were something else before becoming CEOs.” Traditionally, she noted, these roles went to those trained in business or law, but with the increasing importance of data and analytics in all employment sectors, it is perhaps inevitable that statisticians should be tapped for these top posts and should not feel limited in pursuing them.

                                  Regarding the Count on Statistics initiative, Erica commented that federal statistics are very much a public service and represent the baseline for methodological work seeking to improve the way data from surveys and other sources are used today. Thoughtful critiques of official statistics are valuable. Data sources and methods are evolving, and it is important that users understand the limitations of their use. But this is not the same as uninformed critiques, attacking without that understanding. Statisticians should be defending official statistics on a regular basis in their social and professional environments. Otherwise, we are missing an opportunity to defend our own work.

                                  About the Leadership Institute, Erica noted that, “There is a role for professional associations like the ASA to help their members advance in their careers.”

                                  We are fortunate to have Erica and the other steering committee members guiding the planning and operation of the institute and look forward to their continued commitment.