Expands the Capabilities of SPSS and Excel 

Program Dynamic

For many regression problems, analysts like to mean center the continuous predictor variables.  It also is  useful to mean center covariates in analysis of covariance when the analysis of covariance is approached from the perspective of the general linear model.  ZumaStat provides a utility to mean center variables very easily.

In this program, the user is shown on the left side of the dialog box the variables that are in the SPSS active data file (see the example below).  Note the 'Sort' and 'Label' buttons below the listbox.  The 'Labels' button is a toggle switch that allows the user to see the labels associated with the variables or to not see the labels.  In this example, the labels are not shown.  The 'Sort' button is a toggle switch that allows the user to sort the variable list by file order or alphabetically by variable name.  The actions produced by these buttons are instantaneous.

The user chooses the variables that s/he wants to mean center and moves them to the 'Variables Chosen' list box.  By checking the 'Include SDs' box, the user is asking ZumaStat to generate three new variables for each original variable, one that is mean centered (i.e., the raw scores minus the mean), one that is centered 1 standard deviation above the mean (i.e., the raw scores minus a constant that is equal in value to one standard deviation above the mean), and a variable that is centered 1 standard deviation below the mean (i.e., the raw scores minus a constant that is equal in value to one standard deviation below the mean)

If the 'Filter cases' box is checked, the constants would be defined based on the active filter that is in place (using the SPSS Select Cases option).

When the user presses 'Create,' three new variables are added to the end of the active data file for each variable in the list.  For example, the variables cacademe, aacademe, and bacademe would be added that represent the transformed variables for academe that are mean centered, centered one standard deviation above the mean, and centered one standard deviation below the mean, respectively.  Variable labels also are added to clearly tell the user which variables are which. 

For the current example, nine variables would be added to the data set, three for each of the variables in the 'Variable Chosen' list.

Calculating centered scores is a snap!

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