Regression for Categorical Data

Course Content:
This courses explores the use of regression techniques for data that has nominal or ordinal outcome variables.  The course includes a review of multiple regression and then focuses on three main categorical techniques: binary logistic, ordinal and multinomial regression. 

Course Objectives:

  • To refresh participants' knowledge of using multivariate statistical methods to analyse data.
  • To introduce participants to the use of regression techniques for categorical outcome variables.
  • To provide experience of analysing data using SPSS and interpreting the output.

The topics covered during this course include:

  • Multiple regression
    • Simple regression
    • Multiple regression - the basics
    • Maximising prediction
    • Interpreting the co-efficients - Bs versus Betas
    • Interacctions
    • Nominal IVs
    • Warnings
    • Running Multiple Regression in SPSS
    • Assumptions for testing hypotheses using regression
  • Logistic Regression
    • Introduction to logistic models
    • Notation for logistic models
    • Can we fit a linear model to binary variables?
    • Model formation in binary logistic regression
    • Assumptions of logistic regression
    • Running logistic regression in SPSS
    • Examples of logistic regression
    • Interpreting the logit scale
    • Interpreting the odds scale
    • Interpreting categorical X variables
    • Interpreting continuous X variables
    • The proportional odds model
    • Model diagnostics
    • Measure of effect size
    • Using logistic regression for prediction
    • Interpreting reference categories and interaction effects
  • Ordinal regression
    • Introduction to ordinal regression
    • Can we fit a linear model to ordinal variables?
    • Assumptions of ordinal regression
    • Odds of the cumulative probability
    • The proportional odds model
    • Ordinal intercepts or thresholds
    • Ordinal regression model formulation
    • Link functions
    • Example from SCJS 2008/09
    • Running ordinal regression in SPSS
    • Interpreting the results
    • Alternative models
  • Multinomial logistic regression
    • Introduction to multinomial logistic regression
    • Can we fit a linear model to nominal variables?
    • Model formation in mutinomial regression
    • Assumptions of multinomial regression
    • Running multinomial regression in SPSS
    • Interpreting output from multinomial regression

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