Graduate Course Directory and Schedules

Categorical Data Analysis is the third course in the required sequence for applied Biostatistics (Bsta 511, Bsta 512, Bsta 513 or Bsta 611, Bsta 612, Bsta 613). This course covers topics in categorical data analysis such as cross tabulation statistics, statistics for matched samples, and methods to assess confounding and interaction via stratified tables. Students will learn logistic regression, and relate results back to those found with stratified analyses. Similar to linear regression in Bsta 512/Bsta 612, topics for logistic regression will include parameter interpretation, statistical adjustment, variable selection techniques and model fit assessment. Students will have the opportunity to be exposed to other analysis methods, such as Poisson regression and multinomial logistic regression, etc. We will also learn some machine learning techniques other than logistic regression model. Most homework assignments for this course require the use of statistical software.
 

Prerequisites:

1. BSTA 511/611: Estimation & Hypothesis Testing for Applied Biostatistics
2. BSTA 512/612: Linear Models

Slash Listed Courses

Also offered as BSTA 613 for doctoral students.