Logistic regression enables you to investigate the relationship between a categorical outcome and a set of explanatory variables. The outcome, or response, can be dichotomous (yes, no) or ordinal (low ...

A way to avoid the problem would be to test in a single step all dummy variables corresponding to the same categorical variable rather than one dummy variable at a time, such as in the analysis of ...

Topics include: Study designs, review of inference and regression, categorical data, logistic regression, rates and proportions, and nonparametric methods. Additional topics may be considered if time ...

Jeroen K. Vermunt, Latent Class Modeling with Covariates: Two Improved Three-Step Approaches, Political Analysis, Vol. 18, No. 4 (Autumn 2010), pp. 450-469 ...

Course Topics"Logistic and Poisson Regression," Wednesday, November 5: The fourth LISA mini course focuses on appropriate model building for categorical response data, specifically binary and count ...

You may want to consider the CATMOD procedure for logistic regression since it handles classification variables; however it isn't efficient for this purpose when you have continuous variables with a ...