STAT 52600 - Advanced Statistical Methodology

Credit Hours: 3.00.  As a sequel to STAT 52500, this course introduces statistical modeling tools for situations where standard least-squares techniques may not apply. This includes an extensive coverage of generalized linear models (GLM) for non-Gaussian responses, mixed effects models to describe correlated data, nonparametric regression, and lastly, parametric and nonparametric survival models for the analysis of (possibly censored) time-to-event data. Among issues to be discussed are the estimation of the models, the testing of hypotheses, and the checking of model adequacy. Data examples will be used throughout the course to illustrate the methodologies and the related software tools in R.

Learning Outcomes
1. Understand the concepts and methods in generalized linear models, survival analysis, linear mixed models and GEE methods.
2. Apply these methods properly to real data using R, drawing valid conclusions, and presenting the results concisely.

Credits: 3.00

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STAT 52600 - Advanced Statistical Methodology