Claude Messan Setodji

Photo of Claude Setodji
Codirector, RAND Center for Causal Inference; Senior Statistician
Pittsburgh Office

Education

Ph.D. in statistics, University of Minnesota

Media Resources

This researcher is available for interviews.

To arrange an interview, contact the RAND Office of Media Relations at (310) 451-6913, or email media@rand.org.

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Overview

Claude Messan Setodji is a senior statistician at the RAND Corporation and codirector of the RAND Center for Causal Inference. His research interests include applications of statistics to public policy, especially in health care cost and care, causal inferences, sampling techniques, and data reduction and visualization.

Setodji's current work focuses on improved quantitative methods in health and child development quality assessments and the development of statistical methods for inference on ecological momentary assessment of health and behavior intention outcomes. He is currently working on causal inference propensity score methods in the presence of measurement errors in covariates.

He recently led RAND projects including the evaluation of the redesign of the Nationwide Inpatient Sample and the development of small area estimation cost-effective and statistically reliable approaches for deriving estimates of the prevalence of various health risk behaviors, risk factors, and outcomes in small racial, ethnic, and other hard-to-reach populations in the U.S. Setodji also has interests in international education and health care policy.

Setodji earned his Ph.D. in statistics from the University of Minnesota.

Concurrent Non-RAND Positions

Adjunct Professor at Heinz College, School of public policy and Management, Carnegie Mellon University

Recent Projects

  • Consumer Assessment of Healthcare Providers and Systems CAHPS IV
  • Evaluating Legally Feasible Tobacco Advertising Regulations at Retail Point-of-Sale
  • Assessment of Advertising on Smoking Behavior
  • Evaluation of Federally Qualified Health Center Demonstration
  • American Educator Panel (AEP)

Selected Publications

Setodji, C.M., Martino, S.C., Dunbar, M.S., & Shadel, W.G., "An Exponential Effect Persistence Model for Intensive Longitudinal Data," Psychological Methods, 24(5), 2019

Setodji, C.M., Martino, S.C., Gong M., Kusuke, D., Sicker, A., & Shadel, W.G. , "How Do Tobacco Power Walls Influence Adolescents? A Study of Mediating Mechanisms," Health Psychology, 37(2), 2018

Setodji C.M., McCaffrey D.F., Burgette L.F., Almirall D., and Griffin B.A., "The Right Tool for the Job: Choosing Between Covariate Balancing and Generalized Boosted Model Propensity Scores," Epidemiology, 28(6), 2017

Robbins M.W. and Setodji C.M., "Causal Inference Using Mixture Models: A Word of Caution," Medical Care, 52(9), 2014

Setodji C.M., Martino S.C., Scharf D., and Shadel W. G., "Quantifying the Persistence of Pro-Smoking Media Effects on College Students’ Smoking Risk," Journal of Adolescent Health, 54, 2014

Setodji C.M., Le, V. and Schaack D., "Using Generalized Additive Modeling to Empirically Identify Thresholds Within the ITERS in Relation to Toddlers' Cognitive Development," Developmental Psychology, 49(4), 2013 (forthcoming)

Setodji C.M., Elliott M.N., Abel G., Burt J., Roland M., Campbell J., "Evaluating Differential Item Functioning in the English General Practice Patient Survey: Comparison of South Asian and White British Subgroups.," Medical Care, 53(9), 2015

Cook, R.D. and Setodji, M.C., "A Model-Free Test for Reduced Ranked in Multivariate Regression," Journal of the American Statistical Association, 98, 2002

Languages

French; Ewe; Adja; Mina

Commentary

  • A TV reporter wearing a mask, photo by brightstars/Getty Images

    Don't Make the Pandemic Worse with Poor Data Analysis

    The need for immediate answers in the face of severe public health and economic distress may create a temptation to relax statistical standards. But urgency should not preclude expert analysis and honest assessments of uncertainty. Mistaken assumptions could lead to counterproductive actions.

    May 6, 2020 The RAND Blog

  • Nurses discussing patient records

    On Nurse Staffing Ballot Measure, Massachusetts Voters Should Look to Evidence from California

    Massachusetts residents will soon vote on the Patient Safety Act, a mandate to increase nurse-to-patient ratios in acute care facilities. Evaluating existing data on the impact of a similar nurse staffing law implemented in California in 2004 may help inform voters as they head to the polls.

    Nov 2, 2018 Health Affairs Blog

Publications