Variable Selection to Discriminate between Two Groups: Stepwise Logistic Regression or Stepwise Discriminant Analysis?

Monte Carlo methods were used to compare the stepwise variable selection procedure in discriminant analysis with the stepwise procedure using logistic regression. In these studies four of the candidate variables were related to group membership and four were not.The data sets were generated from normal, lognormal, and Bernoulli distributions.Several sample sizes, mean vectors, and covariance matrices were used.In most situations there was little difference between stepwise logistic regression and discriminant analysis in the probability of selecting the related variables.In some situations stepwise discriminant analysis gave a greater probability of selecting the related variables.