Analysis of a Mixture Experiment - Quick Tab
Select the Quick tab of the Analysis of a Mixture Experiment dialog to access options to quickly review the results of your analysis. Note that these results are for the currently specified model. You can specify a new model on the Model tab.
- ANOVA
- Use the ANOVA group box to access the options described here.
- Summary: Estimates, pseudo-components
- Click the Summary: Estimates, pseudo-components button to display a spreadsheet with the parameter (coefficient) estimates for the current model based on the transformed pseudo-components. The effects computed depend on the current model, as specified via the options on the
Model tab. Additional options for confidence intervals, Alpha highlighting, and sorting effects are available on the
ANOVA/Effects tab.
All estimates in this spreadsheet pertain to the rescaled factor settings, that is, to pseudo-components. To see the results for the original (untransformed) factor settings, use option Estimates, original comps on the ANOVA/Effects tab. See also the description of the Estimates, Pseudo-Components Spreadsheet.
- Estimates, original comps
- Click the Estimates, original comps button to display a spreadsheet with the coefficient estimates for the original (untransformed) component values. The coefficients computed depend on the current model, as specified via the options on the
Model tab. If a residual variance estimate is available, the spreadsheet also includes the standard errors of the coefficients. Additional options for confidence intervals, Alpha highlighting and sorting effects are available on the
ANOVA/Effects tab. Note that the Statistical significance (if computed) for the main effect coefficients must be interpreted with caution. Because of the general mixture constraint (sum of component values must be constant), there are only q-1 degrees of freedom associated with the q components.
Note: this option is only available if the current component settings are not proportions in the standard 0-1 range; otherwise, the pseudo-component transformation doesn't affect the component values, and the results for the original component values are the same as those reported for the pseudo-components.
- ANOVA table
- Click the ANOVA table button to display two ANOVA tables for the current model, as specified on the Model tab. For a description of the two tables, see ANOVA tables for mixture experiments.
- Trace plot of expected response
- Click the Trace plot of expected response button to display the
Values for Reference Blend dialog, in which you select the values for the reference blend for which to compute the response traces (see the explanation of
trace plots). Click the OK button on this dialog to display a trace plot for the predicted dependent variable values by the pseudo-component values.
Surface plot (fitted response). Click the Surface plot (fitted response) button to plot the currently fitted model in a surface plot, along with the observed points in the experiment. If there are more than three factors in the current design, the Select factors for triangular graph dialog is displayed when you click the Surface plot (fitted response) button. From this dialog, select the three variables for the plot.
When there are more than three factors in the current experiment, the Select factor values dialog 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). Note that, even though the triangular graph (optionally) shows the fitted function for the pseudo-components, Statistica expects the values to be entered in terms of the original (untransformed) components.
If the Show fitted function check box on the Prediction & profiling tab is selected, the plot will also contain, as custom text, the currently fitted function (model). Note that the parameters shown in this function pertain to the estimates for the pseudo-components (see also options Summary: Estimates, pseudo-components and Estimates, original components, above, for additional details). If there are more than three factors in the experiment, then the pseudo-components are further rescaled in the graph to reflect the residual mixture after holding other factors constant.
- 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 three factors in the current design, the
Select factors for triangular graph dialog is displayed when you click the Contour plot (fitted response) button. From this dialog, select the three variables for the plot.
When there are more than three factors in the current experiment, the Select factor values dialog also is displayed, in which you specify the values for those additional factors, for which to compute the contour plot (i.e., for which to compute the fitted values). Note that, even though the triangular graph (optionally) shows the fitted function for the pseudo-components, Statistica expects the values to be entered in terms of the original (untransformed) components.
If the Show fitted function check box on the Prediction & profiling tab is selected, the plot will also contain, as custom text, the currently fitted function (model). Note that the parameters shown in this function pertain to the estimates for the pseudo-components (see also options Summary: Estimates, pseudo-components and Estimates, original components, above, for additional details). If there are more than three factors in the experiment, then the pseudo-components are further rescaled in the graph to reflect the residual mixture after holding other factors constant.