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Department faculty have wide-ranging research interests, including survival analysis, sequential analysis, clinical trial design, longitudinal data analysis, missing data methods, causal inference, analysis of categorical data, measurement error models, multiple testing, analysis of gene expression data, network inference, statistical genetics, nonparametric smoothing and curve estimation, model selection techniques, robust inference, mathematical and stochastic modeling of complex biological systems, order restricted inference, ROC curve analysis, nonparametric inference, Bayesian inference, functional response models, and small-sample asymptotics. The department has expertise in virtually all fields of modern theoretical and applied statistics.

For a complete list of faculty associated with the Graduate Program in Statistics, click here.