Generalized Feature Selection Analysis

Double-click Feature selection with interaction effects on the Quick tab of the Feature & Method Selection Startup Panel to display the Generalized Feature Selection Analysis dialog box. You also can select Feature selection with interaction effects and click the OK button to display this dialog, which contains two tabs: Quick and Advanced.

In general, the options available on this dialog are very similar in terms of the results that can be computed as the Feature Selection and Variable Screening module. The main generalization of these techniques as implemented via these options is that you can also screen the interactions (e.g., products) of predictor variables. Specifically, the program will generate a "design matrix of predictor effects," and apply the standard feature selection algorithm (as discussed in the Feature Selection and Variable Screening Introductory Overview) to the columns in that design matrix. For example, you can include in your analyses not only the simple (main) effects for each predictor, but also their two-way interactions, three-way interactions, and so on. Final variable lists can then be extracted for further analyses that include all variables that were found in important simple or interaction effects during the screening process. Note that by including interactions between predictors, the total number of effects that must be screened by the program can quickly become astronomically large; even when an analysis problem involves only a few hundred variables, it is best to use the simple feature selection methods (for main effects only) first; even including only the 2-way interactions with a few hundred predictors can quickly grow the total number of predictors and their interactions into the tens or even hundreds of thousands!

Summary

Click the Summary button to compute the results; if no variables have been specified, the program will display the standard four-variable selection dialog where you can select the dependent (outcome) and predictor variables for the analyses; both continuous and categorical dependent variables and predictors can be specified, and the analyses will be performed for each dependent variable one at a time. See also the Feature Selection and Variable Screening Introductory Overview for additional details.

If variables have been selected, clicking the Summary button will begin the analyses and display the requested results. Use the options on the Advanced tab to select which results to compute.

Cancel

Click the Cancel button to close the dialog without performing an analysis.

Options

Click the Options button to display the Options menu.

Open Data

Click the Open Data button to display the Select Spreadsheet dialog, which is used to choose the spreadsheet on which to perform the analysis. The Select Spreadsheet dialog contains a list of the spreadsheets that are currently active.

SELECT CASES

Click the Select Cases button to display the Analysis/Graph Case Selection Conditions dialog, which is used to create conditions for which cases will be included (or excluded) in the current analysis. More information is available in the Case Selection Conditions Overview, Case Selection Conditions Syntax Summary, and Case Selection Conditions dialog description.

W

Click the W (Weight) button to display the Analysis/Graph Case Weights dialog, which is used to adjust the contribution of individual cases to the outcome of the current analysis by "weighting" those cases in proportion to the values of a selected variable.

MD casewise deletion

If the casewise deletion of missing data is selected, STATISTICA will ignore in the analyses all cases (observations) that have missing data for any of the variables selected for the analyses. Selecting casewise deletion of missing data may not be desirable when many predictor variables are specified, each with many missing data. In that case it can happen that practically all observations are excluded from the analyses. An alternative strategy is to first perform an initial feature (variable) selection without selecting this option, followed by a second analysis with casewise deletion of missing data for only those variables selected in the first pass.