General Linear Models

  • Main Effects Linear Models
    Builds a linear model to include main-effects only for categorical predictors (use factorial ANCOVA to include continuous predictors). Both univariate (single continuous dependent variable) and multivariate (multiple continuous dependent variables) designs can be analyzed. Default results include the ANOVA (MANOVA) table and plots of means; set the Level of detail parameter to All results to request tables of means and other statistics.
  • Factorial ANCOVA MANCOVA Models
    Factorial designs and analysis of covariance models; builds a linear model to include main-effects and interactions for categorical predictors (to a specified degree, e.g., two-way effects, three-way effects, etc.). Both univariate (single continuous dependent variable) and multivariate (multiple continuous dependent variables) designs can be analyzed. Default results include the ANOVA/ANCOVA (MANOVA/MANCOVA) table; set the Level of detail parameter to All results to request tables of means and other statistics.
  • Repeated Measure Models
    Factorial designs with a repeated (within-subject) factor; use General Linear Models to specify and analyze complex between-within models. Use this module script to specify designs that include main-effects and interactions for categorical predictors (to a specified degree, e.g., two-way effects, three-way effects, etc.), covariates, and a single repeated measures factor. Both univariate (single dependent measure) and multivariate (multiple dependent measures) designs can be analyzed. Default results include the ANOVA/ANCOVA (MANOVA/MANCOVA) table; set the Level of detail parameter to All results to request tables of means and other statistics.
  • Response Surface and Mixture Models
    Fits the second-order response surface or central composite model for continuous predictors to one or more dependent variables; a single categorical predictor (blocking factor) can also be specified. Use the General Linear Models options to specify custom designs.
  • 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.