Analysis of an Experiment with Two- and Three-Level Factors - Design Tab

Designs for Factors at 2 and 3 Levels

Select the Design tab in the Analysis of an Experiment with Two- and Three-Level Factors dialog box to access the options described here. Note that these results are for the currently specified model. You can specify a new model on the Model tab.

Display design and observed means

Click this button to produce a spreadsheet showing the unique runs (those with unique combinations of factor settings) in the experiment. In addition, for each unique run, STATISTICA computes the mean, standard deviation, and standard error of the mean (if there is more than one run for the respective unique combination of factor settings).

Show text labels instead of factor values

When this check box is selected, the factor settings in this spreadsheet will be identified by their respective text labels. If there are no text labels in the file (for the list of independent variables or factors), this check box will not be available. Note that the setting of this check box also determines whether or not text labels are shown in spreadsheets with marginal means, and in marginal means plots.

Correlations

Use the options in the Correlations group box to review correlations for the design matrix as well as the effects.

Corr. matrix of design variables (X'X).

Click this button to produce a correlation matrix of the columns of the current design matrix. Thus, the number of effects displayed in this matrix depend on the current choice of the model in the Include in model group box on the Model tab. For analysis purposes, the factor values are recoded so that the range of values for each factor is ±1 (see also option Summary: Effect estimates on the ANOVA/Effects tab). The interaction effects are then obtained by multiplying out the respective main effect vectors or columns. However, note that the coding for interactions is also affected by the setting of the Use centered & scaled polynomials check box on the Quick tab. The correlations in this matrix, reflect on the redundancy of the respective effects. To aid in the review of this matrix, all correlations that are not equal to 0.0 will be highlighted in this matrix.

Correlation of effects (X'X inverse)

Click this button to produce the standardized inverse of the correlation matrix. This matrix can be interpreted as the correlation matrix of effects, that is, it is the standardized variance/covariance matrix of the parameter estimates for the current model. The greater the absolute value of a correlation between effects in this matrix, the more redundant are the respective effects. To aid in the review of this matrix, all correlations that are not equal to 0.0 are highlighted in this matrix. Also, note that option Display matrices in compressed format (see below) applies to this option as well.

Display matrices in compressed format

When this check box is selected, the width for the columns in the spreadsheet with the correlations will be set to 4 (4 characters, including the decimal point, will show in each cell of the correlation matrix, e.g., value 0.31). Use this compressed format to review large matrices efficiently. Clear this check box to display the cells in the spreadsheet in the usual default width of 8 characters per cell (e.g., to display 0.312345). Of course, you can always use the standard spreadsheet option Format - Cells to change the display format for all spreadsheets; (remember that, regardless of display format, values in spreadsheets are always stored in their highest precision).