CATEGORICAL DATA

STA 841

This course covers statistical methods for analyzing categorical data. Model and theory includes: generalized linear models, including models for binary data, polytomous data (ordered and unordered), counts, contingency tables, matrix and graphical data. Classical and Bayesian inference in these models involves: latent variable representations, conditional likelihood, profile likelihood, and iterative algorithms. More advanced methods include: analysis of repeated measurements, data with cluster structure, nonparametric analysis, adaptive testing in contingency tables, multiple testing and data analysis in high-dimensions. Instructor: Ma or Steorts

Day / Time: 

WF 11:45 AM-01:00 PM

Location: 

Allen 326

Instructor: 

Herring, Amy

Section: 

01