The control and administration of the affairs of the Society shall be vested in an Executive Committee consisting of the Officers, 2 Members-at Large, a Secretary, and Treasurer. For all purposes, the Executive Committee shall also constitute the Board of Directors of the Society. The officers of the Society shall serve on the Executive Committee during their term of office. The remaining members of the Executive Committee shall serve for a term of three years. The President of the Society shall be the Chair of the Executive Committee. For the purpose of establishing the Society leadership, staggering terms of each position may be set during the initial 3-year cycle of the Society.
Current members of the Society are eligible to vote. Voting will begin on March 1, 2022 and will close April 18, 2022.
President-Elect Candidates One candidate to be elected.
Elizabeth Tipton, Northwestern University
I am an Associate Professor of Statistics at Northwestern University, where I am also a Faculty Fellow at the Institute for Policy Research and where I co-direct the Statistics for Evidence Based Policy and Practice (STEPP) Center. Prior to my position here, I was faculty at Teachers College, Columbia University.
My research focuses on the design and analysis of randomized field experiments, with particular focus on methods for improved generalizability, and on methods for meta-analysis. Much of my work is situated in the fields of education and psychology, though I’ve contributed too to economics, medicine, and nutrition. I am on the Boards of the Society of Research on Educational Effectiveness and of Blueprints for Healthy Youth, and I am an elected member of the Society for Research Synthesis Methods.
I am also an Associate Editor at the Journal of Educational and Behavioral Statistics, as well as an Editorial Board member of Observational Studies. Additionally, I have served on the Program Committees of two ACIC meetings (NYC, Montreal).
As President, I would focus on developing the Society in a way that embraces the diversity of fields and research focused on causal inference. This includes statistical and computational methods, but also the empirical research and policy needs that drive these innovations. My background and experience sits nicely at the nexus of these areas – I often work closely with applied researchers encountering causal problems and, in my own work, I develop and study statistical methods meant to improve these analyses. I think it is important for those developing methods to keep these real, on the ground, questions, problems, and constraints in mind. I can imagine the Society being a place that connects researchers across these fields and foci, through conferences, trainings, and partnerships with other organizations.
I am honored to be nominated for SCI president. When I was an assistant professor in a statistics department working on causal inference research, I felt lonely. Few statisticians worked on causal inference and I had little connection with most of the causal inference researchers in other fields whose work I cited and drew inspiration from. The Atlantic Causal Inference Conference (ACIC) helped to fill the loneliness. I am proud to have played a role in organizing three ACICs at Penn. But the ACIC was just a once-a-year event. The development of the Society for Causal Inference (SCI) is an exciting step forward that will build on the ACIC to foster a year-round supportive community for causal inference researchers across fields.
I would like to listen and work with SCI members to represent members’ interests. Particular interests of mine for SCI include the following: ensuring SCI has the resources to prosper, supporting early career researchers, supporting researchers working in isolated environments and keeping SCI members feeling part of our community.
I hope that SCI will be an inclusive society. As president, I would try to foster an inclusive path to influence and leadership in SCI by supporting the development of the SCI committees, encouraging members that they are welcome to join the committees and conveying the message that a good way to obtain leadership positions in the future is to get involved with the committees.
Secretary Candidates One candidate to be elected.
Nandita Mitra, PhD is Professor of Biostatistics, Vice Chair of Education, and Vice Chair of Faculty Professional Development in the Department of Biostatistics, Epidemiology, and Informatics at the University of Pennsylvania. She is also the Chair of the Graduate Group in Epidemiology and Biostatistics and Co-Director of the Center for Causal Inference at Penn. She received her BA in Mathematics from Brown University, MA in Biostatistics from the University of California, Berkeley, and her PhD in Biostatistics from Columbia University and completed a postdoctoral fellowship at Harvard. Her primary research area is causal inference with a focus on developing propensity score, instrumental variable, and sensitivity analysis methods for observational data with applications in cancer, health policy, and health economics. Dr. Mitra has published over 250 peer-reviewed papers in journals such as Biometrics, Biostatistics, Annals of Applied Statistics, Journal of the Royal Statistical Society C, Statistics in Medicine, New England Journal of Medicine, Lancet, Nature, and JAMA. She is the Editor-in-Chief of Observational Studies and is a Fellow of the American Statistical Association.
Dr. Mitra’s relevant professional society activities include: ENAR Regional Advisory Board Member (2011-2013), ENAR Spring Meeting Educational Advisory Committee Member (2013), ENAR Spring Meeting Program Chair (2017), ENAR Spring Meeting Local Arrangements Chair (2019), ASA Statistics in Epidemiology Section Elected Representative (2018-2020); International Biometric Society Budget & Finance Committee Council Member (2018); ASA Committee on Policy member (2020-present), IBS Budget & Finance Committee Chair (2018-present); ASA Statistics in Epidemiology Section Chair-Elect (2022).
Statement: I am delighted to run for the position of Secretary for the newly formed Society for Causal Inference. The mission of the SCI is near and dear to my heart: to bring together researchers across different disciplines to promote the development and application of causal inference methods that have a true impact on policy decisions. Over the past several years, I have collaborated closely with policy makers to assess the effectiveness of the Supplemental Nutrition Assistance Program (SNAP) across the US, the effect of the Philadelphia beverage tax on volume intake and health, and the effect of community health workers on chronic conditions, just to name a few. As a member of the Executive Committee, I would be committed to increasing participation among students, post-docs, and junior investigators and ensure that they are included in the governance of the society. I would also like to prioritize professional development activities such as grant writing workshops, teaching workshops, skill-building courses, and opportunities for one-on-one mentorship with leaders in the field. I would also devote time for outreach to under-represented high school and college students to encourage them to pursue a career in fields that rely on causal inference. I look forward to the opportunity to join the SCI to have a real impact on its future activities in fostering collaborations across disciplines, mentoring junior investigators, and increasing diversity in the field.
I am an Associate Professor and Biostatistician in the Department of Population Medicine at the Harvard Medical School and Harvard Pilgrim Health Care Institute. I also hold a secondary appointment in the Department of Epidemiology, and am a member of the CAUSALab, at the Harvard Chan School of Public Health. First introduced to causal inference as a graduate student at UC Berkeley, I began my formal training in causal inference in 2007 as a postdoc in the Program on Causal Inference at Harvard.
I like thinking about how to make causal inferences from longitudinal data grounded in meaningful causal questions that can inform how to extend lives and improve different aspects of human health. My methods work of late focuses on addressing existing challenges to causal inference in the face of competing events as well as estimating causal effects when the underlying conceptual exposure/treatment is unmeasured in available data sources.
This work is inspired by problems I come across as a collaborating biostatistician with subject matter researchers across different areas of public health and medicine. Some causal questions I am currently working to help address with real-world data include questions about effects of dietary interventions in pregnancy, infancy, and early childhood on later health outcomes, medical interventions during pregnancy on birth outcomes, medication choices on weight gain, timing of antibiotic initiation on mortality in patients with suspected sepsis, and PrEP prescribing interventions on HIV and Bacterial STI incidence in men who have sex with men.
I feel privileged and grateful for my training, mentorship, and collaboration experiences to date and prioritize paying that forward. My enthusiasm and passion for the ideas that the causal inference literature provides to science and society grows every year with the new generation of scientists I have been further blessed to know, work with, and/or learn from.
Moving forward, I believe strong efforts are needed to expand access to rigorous training in causal inference to students at institutions across the United States and the world. I also believe we need increased collaboration and communication between causal inference enthusiasts and experts in a broader variety of subject matter areas, particularly related to social justice and health equity. It would be an honor to serve in the position of Secretary within the leadership of the new Society for Causal Inference and directly help support these and other efforts for increased access, communication, and collaboration.
Treasurer Candidates One candidate to be elected.
I am very excited and honoured to run for the position of treasurer for the new Society for Causal Inference.
My path to causal inference began with my training in medicine. As a practicing sport medicine clinician, I have to make treatment decisions for every patient. If we don’t treat the causes, problems recur. After practicing medicine for 3 years, I needed to understand more about causes and obtained a PhD in Physiology. Most of physiology is about understanding the causal mechanisms that underlie how our body responds to its environment. After conducting physiological research for a few years, I did post-doctoral training in Epidemiology to better understand how we can control bias in population-based studies. This broad background and strong foundation in both substantive and methodological issues has allowed me to address many different types of questions, and to be a source of knowledge translation on methodology in the field of sport and exercise medicine.
New Societies always face important challenges, including how to grow membership, diversity and influence. I believe that having a diverse range of experiences on the Executive committee helps new societies find creative pathways to success. In addition to my unique background in causal-related research, I also have considerable experience as a member of Executive committees in other national and international societies.
With specific reference to the Treasurer role I am seeking, I was the treasurer for the Canadian Academy of Sport and Exercise Medicine for four years (1998-2001) and was a Director of the Cochrane Trading Company for 4 years (2015-2019). The Cochrane Trading Company was responsible for managing the finances of the Trust portfolio of the international Cochrane Collaboration that is officially located in the United Kingdom. I have also been the Chair of two international conferences (Canadian Academy of Sport and Exercise Medicine, Society for Research Synthesis Methodology).
In addition to my experiences and direct responsibility with the financial management and oversight of national and international societies, I have also served on the Board of Directors/Trustees in other roles. I was on the Board of Directors for the Canadian Academy of Sport Medicine for 11 years (1993-2004), including serving as President-elect, President, past-president between 2001-2004. I was on the Board of Trustees for the American College of Sports Medicine between 2011-2014, and Society for Research Synthesis Methodology Board of Directors between 2013-2020. Finally, I have administrative experience with multiple academic peer-reviewed journals, including co-Editor-in-Chief of Research Synthesis Methods (2014-2020), and editorial Board Member of Translational Sports Medicine (2017-present), Scandinavian Journal of Medicine & Science in Sports (2006-present), Journal of Science and Medicine in Sport (2004-present), British Journal of Sports Medicine (2001-2017), and the Clinical Journal of Sport Medicine (1995-2012).
In summary, I am a clinician and researcher dedicated to best practices in causal inference. I believe my administrative experience in diverse organizations will help the Society for Causal Inference to anticipate and tackle potential challenges as it establishes itself as a leading organization for international thought leaders and learners.
I am an Instructor of Investigation at the Biostatistics Center at Massachusetts General Hospital (MGH) and partly funded by an NIH Early Independence Award (DP5) I received in 2016. I obtained a joint doctoral degree in Biostatistics and Environmental Health under the guidance of Profs. Schwartz and Coull at the Harvard School of Public Health in 2014. During my thesis, I, for instance, worked on causal mediation analysis with Prof. VanderWeele. After my thesis, I became a two-year Ziff postdoctoral fellow at the Harvard University Center for the Environment and learned how to apply the Rubin Causal Model to address causal questions related to extreme temperatures. In 2017, I became a John Harvard Distinguished Science Fellow (JHDSF) at the Department of Statistics, Harvard University, and developed and applied causal inference methods to examine whether environmental exposures (e.g., air pollution) are related to poorly-understood diseases (e.g., multiple sclerosis).
Recently, I have promoted the use of randomization-based inference, especially in the context of air pollution chamber studies. In 2021, I accepted an academic position of Instructor of Investigation at the MGH Biostatistics Center. I am being recommended for a faculty appointment as Assistant Professor at the Harvard Medical School, Department of Medicine. At MGH, I am part of the teams of blinded biostatisticians of the current HEALEY platform trial on amyotrophic lateral sclerosis (ALS) and of the RECOVER team, a NIH initiative that seeks to understand, prevent, and treat long COVID. Since the beginning of my thesis, I have attended and presented my work at national and international research meetings. I have also been invited to give talks and short courses on causal inference in prestigious European, Asian, and US research institutes and universities.
I am happy to run for the Treasurer position within the leadership of the Society for Causal Inference (SCI). As treasurer, I will participate on all calls related to the finances of the SCI and will be responsible for developing a preliminary budget based on input from the Executive Director and the Officers, which will then be approved by the Executive Committee. As treasurer, I will make sure that the budget is allocated to activities that concern all members of the Society. To ensure this, I will be closely working with the Equity and Inclusion Committee. I am hoping that the Society can continue to grow into a warm family of junior and senior colleagues sharing causal inference interests.
Member at Large Candidates Two candidates to be elected.
I have dedicated my career to supporting the use of causal inference in public policymaking. To the leadership team of the Society for Causal Inference, I will bring a collaborative spirit and the perspective of policymakers to strengthen the application and impact of causal inference researchers’ work.
Cihak leads evidence-informed practice and partnerships for the regional government of the 12th largest county in the United States. Cihak guides County agencies on community outcomes and impact, with a strong focus on advancing racial equity. Former roles at the County include three years leading learning and evidence practice and partnerships at King County Metro Transit; serving as an inaugural member of the community mitigation team in the County’s pandemic response; and eight years as Chief of Policy for the King County Executive with responsibility for identifying the highest priority policy areas and community outcomes for leadership focus and developing and launching innovative solutions to complex, controversial, and cross-sector issues.
Cihak has served as sponsor for the County’s nationally-recognized work on equity and social justice and is architect of several County initiatives such as Best Starts for Kids. Cihak also served for eight years as a senior-level policy and budget analyst for the King County Council and as lead staff for the King County Board of Health.
Cihak is trained as a Ph.D.-level (ABD) economist specializing in Japan and served as staff economist on international trade and finance for President Clinton’s Council of Economic Advisers. Cihak is a Local Government Fellow and serves on the Advisory Committee for the Federal Standards of Excellence at Results for America, a non-profit organization that supports all levels of government in making the use of data and evidence in decision making the “new normal”. Cihak was the first government Policy Fellow at the Center for Advanced Study in the Behavioral Sciences at Stanford University (CASBS) in 2017-18 and has been a Research Affiliate at CASBS since that time. With Jake Bowers (University of Illinois – Statistics & Political Science), Cihak co-founded and co-directs the Causal Inference for Social Impact Lab at CASBS that brings policymakers and academic researchers together to innovate on causal inference methodology and practice.
Rocío Titiunik is Professor of Politics at Princeton University, where she is also an affiliated faculty with the Center for Statistics and Machine Learning, the Center for the Study of Democratic Politics, and the Program in Latin American Studies. She specializes in quantitative methodology for the social and behavioral sciences, with emphasis on quasi-experimental methods for causal inference and program evaluation. Her research interests lie at the intersection of political economy, political science, statistics, and data science, particularly on the development and application of quantitative methods to the study of political institutions. Her recent methodological research includes the development of statistical methods for regression discontinuity (RD) designs. Her recent substantive research centers on democratic accountability and the role of party systems in developing democracies.
In 2016, she received the Emerging Scholar Award from the Society for Political Methodology, which honors a young researcher who is making notable contributions to the field of political methodology. She was elected as fellow of the Society for Political Methodology in 2020. Rocio is one of the Principal Investigators of the Empirical Implications of Theoretical Models (EITM) Summer Institute, and has served in various leadership roles for the American Political Science Association and for the Society for Political Methodology. She is currently associate editor for Science Advances and a member of the Board of Reviewing Editors for Science. She is also a member of the Advisory Committee for the Social, Behavioral, and Economic Sciences Directorate of the National Science Foundation. Rocío was born and raised in Buenos Aires, Argentina, where she completed her undergraduate education at the Universidad de Buenos Aires. She received her Ph.D. in Agricultural and Resource Economics from UC-Berkeley in May 2009. Between 2010 and 2019, she was a faculty member in the Department of Political Science at the University of Michigan, where she was also affiliated with the Center for Political Studies and the Michigan Institute for Data Science.
I am a professor and the Director of PhD Graduate Program in Biostatistics within the Graduate School of Public Health (GSPH) at the University of Pittsburgh. I have been teaching statistics to graduate and undergraduate students at different institutions for over 20 years. My primary research area is statistical methods for SMART trials and dynamic treatment regimes. I use the counter-factual framework of causal inference as a tool to assess the causal effect of interventions from complex multi-stage treatment sequences in observational studies and clinical trials. This led to inverse-probability-weighted and double-robust efficient methods for the analysis of sequentially randomized trials for comparing dynamic treatment regimes. Results appeared in statistics and biostatistics journals including JASA, Biometrics, Biometrika, Biostatistics, JRSS-A, JRSS-C, Statistics in Medicine, and JSPI. I am currently an Associate Editor for the journals Biometrics, Biostatistics, and the Journal of Statistical Theory and Practice. I am a fellow of the American Statistical Association (ASA), and a recipient of the Pittsburgh Chapter Statistician of the Year award.
I served as the 2012-2013 President of the Pittsburgh Chapter of the American Statistical Association. I have previously served on the International Biometric Society (ENAR) Regional Advisory Board, on the ASA Committee on International Relations in Statistics as Vice-Chair, ENAR representative to AAAS, and many other committees of the ASA and ENAR. I currently chair the Committee of the Presidents of Statistical Societies (COPSS) Award Committee. Details of my credentials can be found here:
While statistics as a discipline has embraced the notion of causal inference a century ago with the seminal counterfactual framework of Neyman (Neyman, 1923), the widespread application of causal inference started only in the last quarter of the 20th Century. And the role of causal inference in the advancement of society has been recognized through the awarding of the Nobel prize in Economics to two causal inference methodologists in 2021. With this comes a greater responsibility for the causal inference enthusiasts and our new platform SCI. Grabbing this opportunity, I would like to serve as a member-at-large on the SCI board to help SCI: 1) provide learning opportunities for novices and experts alike in the form of seminars, workshops, conferences, and podcasts, 2) start centralized repositories, either independently or using current online platforms (e.g., GitHub) to develop and disseminate tools (e.g., apps and software packages) for wide-spread application of causal inference, 3) promote proper use of causal inference techniques in scientific research in collaboration with professional societies and sponsors (e.g., NIH, NSF), 4) introduce SCI annual awards to acknowledge the contributions in causal inference research, and 5) encourage young researchers to venture into the field of causal inference by introducing student awards.
Hello fellow causal inference enthusiasts, my name is David “Ami” Wulf, and I hope to serve as a Member at Large on the Executive Committee.
This past year I earned my PhD in Statistics from UCLA with a focus on causal inference, and I currently work for Etsy as a senior research data scientist specializing in inference, experimentation design, machine learning, and marketplace economics. Prior to starting my degree, I was at Kaiser Permanente conducting healthcare outcomes research, and have a growing list of publications, invited presentations, consulting experience, and service, between that work and my PhD research.
I am running for this position because I am passionate about the development of a more connected causal inference field and community. I believe we and our work continue to be impaired by a lack of communication across Stats, Epi, CS, and Econ; between practitioners in academia and industry; and in sharing that work with those less familiar with causal inference. I am confident that my fresh (and now industry-incorporating) view of the field, my breadth of experience (conditioning on my early career status) across those gaps, and my enthusiasm for this work and interpersonal bridge-building, will all make me an impactful member at large and contributor to these critical and exciting early years at SCI.
Thank you for considering my candidacy,