Analysis of a Screening Experiment with Two-Level Factors - Prediction and Profiling Tab

Analyzing the Results of a 2(k-p) Experiment

Select the Prediction & profiling tab in the Analysis of a Screening Experiment with Two-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.

Response desirability profiling

Click the Response desirability profiling button to display the Profiler dialog box. Use the Profiler to inspect the predicted values for the dependent variables at different combinations of levels of the independent variables, to specify desirability functions for the dependent variables, and to specify a search for the levels of the independent variables that produce the most desirable response on the dependent variables.

Surface plot (fitted response). Click this button to plot the currently fitted model in a surface plot, along with the observed points in the experiment. If there are more than two factors in the current design, the Select factors for 3D plot dialog box is displayed when you click the Surface plot (fitted response) button. In this dialog box, select the two variables for the plot.

When there are more than two factors in the current experiment and/or there are block effects included in the current model, the Select factor values dialog box also is displayed, in which you specify the values for those additional factors, for which to compute the surface plot (i.e., for which to compute the fitted values). Remember that the block effects are computed from added (to the design) coded variables. The coding for those effects is described in the description of Main Effects and Interactions.

If the Show fitted function check box is selected (see below), the plot will also contain, as custom text, the currently fitted function (model). Note that the parameters shown in this function pertain to the regression coefficients, that is, to the factor settings in their original metric (see also options Summary: Effect estimates and Regression coefficients on the ANOVA/Effects tab for additional details). Thus, this surface will always show the predicted values for the dependent variable, given the original factor settings.

Contour plot (fitted response). Click the Contour plot (fitted response) button to plot the currently fitted model in a contour plot, along with the observed points in the experiment. If there are more than two factors in the current design, the Select factors for 3D plot dialog box is displayed when you click the Surface plot (fitted response) button. In this dialog box, select the two variables for the plot.

When there are more than two factors in the current experiment and/or there are block effects included in the current model, the Select factor values dialog box also is displayed, in which you specify the values for those additional factors, for which to compute the surface plot (i.e., for which to compute the fitted values). Remember that the block effects are computed from added (to the design) coded variables. The coding for those effects is described in the description of Main Effects and Interactions.

If the Show fitted function check box is selected (see below), the plot will also contain, as custom text, the currently fitted function (model). Note that the parameters shown in this function pertain to the regression coefficients, that is, to the factor settings in their original metric (see also options Summary: Effect estimates and Regression coefficients on the ANOVA/Effects tab for additional details). Thus, this surface will always show the predicted values for the dependent variable, given the original factor settings.

Show fitted function. When this check box is selected, the surface or contour plot will include, as custom text, the currently fitted function. Note that you can edit this text in the usual manner, as described in Graph Options dialog - Custom function.

Show area contours. When this check box is selected, the contours in the contour plot will be area (filled) contours; otherwise the surface contours will be indicated by lines.

Predicted vs. observed values. Click this button to produce a scatterplot of the predicted values (given the current model) versus the observed values for the dependent variable.

Predict dependent variable values. Use this option to compute predicted values for the dependent variable, based on values for the factors that you define, and based on the current model as specified in the Include in model group box on the Model tab. Click the Predict dependent variable values button to display the Select factor values dialog box. The values should be specified in terms of the original factor metric, not in terms of the recoded (to ±1) factor values (for additional details, see option Summary: Effect estimates and Regression coefficients on the ANOVA/Effects tab). After specifying the factor values from which to compute the predicted value, a spreadsheet is displayed with the results. If available, the spreadsheet will also display the confidence interval for the respective predicted value. Those confidence limits are computed from the current ANOVA error term, and the percentile value specified in the Confidence interval box on the ANOVA/Effects tab.

Block effects

If the current model contains block effects, you can also specify values for those (added to the design) block variables. The coding (and thus interpretation) for those effects are described in Main Effects and Interactions for Experiments with Two- and Three-Level Factors.