Generalized Linear and Nonlinear Models

• Stepwise and Best Subset Probit Regression
  Creates best-subset and stepwise binary probit regression for categorical and continuous predictors (use also Generalized Linear Models for ANOVA/ANCOVA-like designs); builds a generalized linear model for categorical and continuous predictor variables, for one or more categorical dependent variables (one at a time).
• Stepwise and Best Subset Logit Regression
  Creates best-subset and stepwise binary logit (logistic) regression for continuous and categorical predictors (use also Generalized Linear Models for ANOVA/ANCOVA-like designs); builds a generalized linear model for categorical and continuous predictor variables, for one or more categorical dependent variables (one at a time).
• Generalized Linear Models
  Builds a generalized linear model to predict a continuous or categorical dependent variable. Best-subset and stepwise selection of continuous and categorical (ANOVA-like) predictor effects are also supported. The parameters in Statistica allow full access to the GLZ syntax for specifying models. Default results include the parameter estimates, overall fit indices, and results for best subset or stepwise model building; set the Level of detail parameter to All results to request additional results.

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