Target group
Biostatisticians, epidemiologists, social scientists, and physical scientists who analyze categorical response data and predictive modelers who would like to learn more about the statistical background of logistic regression
Course structure
Categorical Data and Contingency Table Analysis
- introduction to categorical data
- associations among categorical variables
- stratified contingency table analysis
Binary Logistic Regression
- introduction to logistic regression
- adding categorical predictors and the CLASS statement
Model Building
- empirical logit plots
- confounding and interactions
- automatic model selection
- variable clustering for variable reduction
- customized tests
Model Illustration and Assessment
- interaction illustration
- model sssessment
- ROC curves
- outlier detection
Multinomial Logistic Regression
- ordinal logistic regression
- nominal logistic regression
Advanced Topics
- correlated observations
- GEE regression models
- conditional logistic regression
- failure to converge and small samples
