Statistics 526

Advanced Statistical Methodology

Fall 2009

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Course outline

As a sequel to STAT 525, this course introduces some statistical modeling tools that are developed for situations where least squares regression and standard ANOVA techniques may not naturally apply. Our coverage centers around two lines of models that are closely related, the generalized linear models (GLM) for regression (and ANOVA) with non Gaussian responses, and survival models for the analysis of lifetime 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.

Prerequisite

Working knowledge of basic statistical inference and modeling, such as the maximum likelihood estimate, the likelihood ratio test, and the standard linear models.

Textbook

• An introduction to generalized linear models (3rd ed.), by Dobson and Barnett.

References

• Modern Applied Statistics with S-Plus (4th ed), by Venables & Ripley.
• Extending the Linear Model with R, by Faraway.
• Applying Generalized Linear Models, by Lindsey.
• Generalized Linear Models (2nd ed), by McCullagh & Nelder.
• The Statistical Analysis of Failure Time Data (2nd ed), by Kalbfleisch and Prentice.
• Applied Survival Analysis, by Le.

Software

We will be using R, an open-source environment not unlike S/Splus, as the primary platform for computation and graphics. R resources are to be found at CRAN, the Comprehensive R Archive Network.

The following tutorial documents should be helpful to you, especially if you had little previous exposure to R/S/Splus.

• An Introduction to R, by Venables, Smith, and the R Development Core Team.
• Using R for Data Analysis and Graphics: An Introduction, by John Maindonald.

Course Work

There will be biweekly homework assignments, a midterm, and a final. The assignments will contribute about 40% to the course grade, the midterm 30%, and the final 30%. You are encouraged to discuss with each other on the homework assignments, but you are expected to do your independent work.

Lecture Notes

Homework Assignments