General Regression Models

  • Best-Subset and Stepwise Regression
    Best-subset and stepwise multiple regression; builds a linear model for continuous predictor variables, for one or more continuous dependent variable; use Best-Subset and Stepwise ANOCVA to include categorical predictors.
  • Best-Subset and Stepwise ANCOVA
    Best-subset and stepwise multiple regression with categorical factor effects; builds a linear model for continuous and categorical predictor variables, for one or more continuous dependent variables. By default, only main effects will be evaluated for categorical predictors; you can also construct factorial designs up to a certain degree (e.g., to degree 3, to include all 2-way and 3-way interactions of categorical predictors). Note that the algorithm for stepwise and best subset selection of categorical factor effects ensures that complete (possibly multiple-degrees-of-freedom) effects are moved into and out of the model.
  • General Best-Subset and Stepwise Regression
    General regression models; builds a linear model to predict continuous dependent variables. The parameters in Statistica allow full access to the GRM syntax for specifying models and for controlling the parameters for stepwise and best-subset selection of predictor effects (for categorical and continuous predictor variables). Default results include the ANOVA/ANCOVA (MANOVA/MANCOVA) table; set the Level of detail parameter to All results to produce tables of means and other statistics. Residual and predicted values can be computed on request.