B.A. in Mathematics from the University of Chicago (1985). M.S. in Biostatistics from the University of Michigan (1997). Ph.D. in Biostatistics from the University of Michigan (1999).
Dr. Elliott's statistical research interests focus around the broad topic of "missing data," including the design and analysis of sample surveys, casual and counterfactual inference, and latent variable models.
Xia, X., Elliott, M.R. (2016). Weight Smoothing for Generalized Linear Models Using a Laplace Prior, to appear in Journal of Official Statistics.
Zhou, H., Elliott, M.R., Raghunathan, T.E. (2016). A Two-Step Semiparametric Method to Accommodate Sampling Weights in Multiple Imputation, to appear in Biometrics.
Jiang, B., Elliott, M.R., Sammel, M.D., Wang, N. (2015). Joint Modeling of Cross-Sectional Health Outcomes and Longitudinal Predictors via Mixtures of Means and Variances, Biometrics, 71, 487-497.
Elliott, M.R., Conlon, A.S.C., Li, Y., Kaciroti, N., Taylor, J.M.G. (2015). Surrogacy Marker Paradox Measures in Meta-Analytic Settings, Biostatistics, 16, 400-12.
Huang, X., Harlow, S.D, Elliott, M.R. (2014). Modeling Menstrual Cycle Length and Variability at the Approach of Menopause Using Bayesian Changepoint Models Applied Statistics, 63, 445-466.