Design & Analysis of Experiments with Three-Level Factors - Analyze Design Tab

Select the Analyze design tab of the Design & Analysis of Experiments with Three-Level Factors dialog to access options to specify the variables to use in analyzing a three-level factor design.

Variables

Click the Variables button to display the standard variable selection dialog, in which you specify the dependent variables of interest, the independent variable list (list of factors in the design), and an optional blocking variable. After selecting the variables for the analysis, Statistica reads the data and determines whether a valid three-level design is specified in the selected variables. Specifically, the program checks whether the selected list of factors contains three distinct values. Note that if your design is not a typical three-level factorial design (with or without center points), then use the option Central composite, non-factorial, surface designs from the Quick tab of the Startup Panel; there, no assumptions are made about the nature of the design, and any combination of factor settings, with any number of distinct levels, can be analyzed).

Note: Multiple dependent variables and missing data. When more than one dependent variable is specified, then, when reading the data, Statistica performs casewise deletion of missing data. Thus, a case or run will be excluded from the analysis if it has missing data for any of the dependent variables specified for the analysis.

Note: most of these designs can also be analyzed via General Linear Models (GLM) or General Regression Models (GRM), or via (nonlinear) Generalized Linear/Nonlinear Models (GLZ).