was named a fellow of the International Society for Bayesian Analysis and of the Institute of Mathematical Statistics.
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My biostatistical research areas include Bayesian methods; meta-analysis; univariate and multivariate longitudinal data analysis; hierarchical modeling; and complex non-linear models. I also work in model development, model selection and model checking. Motivation for much of my research comes from the statistical difficulties seen in my collaborative work, particularly in the analysis of human behavior. My colleagues and I study HIV+ and HIV-at-risk individuals, drug abusers, child nutrition in Kenya, Hospital Emergency Department visitors, and meta-analyses of cardiac intervention data and Syncope among many other areas of application.
I teach classes in Statistical Graphics (Biostat 230), Bayesian Data Analysis (Biostat 234), Bayesian Theory (Biostat 202C), Longitudinal Data Analysis (Biostat 236 and 411) and multivariate statistics (Biostat 251). My classes have computing and writing components, because statistical practice requires that you calculate inferences and then communicate what you have learned. I particularly like working in an academic environment because of the variety of projects I get to work on and because I get to work with many students on research projects, paper writing, and as dissertation advisor.