When/How to use Logistic Regression and Discriminant Analysis?
From the above definitions, it appears that the same research questions can be answered by both methods. The logistic regression may be better suitable for cases when the dependant variable is dichotomous such as Yes/No, Pass/Fail, Healthy/Ill, life/death, etc., while the independent variables can be nominal, ordinal, ratio or interval. The discriminant analysis might be better suited when the dependant variable has more than two groups/categories. However, the real difference in determining which one to use depends on the assumptions regarding the distribution and relationship among the independent variables and the distribution of the dependent variable. So, what is the difference? Well, for both methods the categories in the outcome (i.e. the dependent variable) must be mutually exclusive. One of the ways to determine whether to use logistic regression or discriminant analysis in the cases where there are more than two groups in the dependant variable is to analyze the assumptions p
