GLM, GRM, and ANOVA More Results - Profiler Tab

Select the Profiler tab of the GLM More Results or the ANOVA More Results dialogs to access the options described here. For an overview of response/desirability profiling see Desirability Profiling in GLM, GRM, and MANOVA and Experimental Design Profiling Predicted Responses and Response Desirability.

Vars

Click the Vars button to display a standard variable selection dialog box, in which you select the dependent variables to profile. If multiple dependent variables are specified for the analysis, use this button to select the dependent variable or variables for which to profile responses. Note that you can specify desirability function settings for all dependent variables in the analysis, thus, with this option, you can easily select subsets of dependent variables or single dependent variables to profile.

Set factors at value

Use the options in the Set factors at value group box to specify the current levels of the predictor variables for the prediction profile compound graph (available via the View button), the surface plot (available via the Surface button), and the contour plot (available via the Contour button).

Mean

Select the Mean option button to set the current level of each predictor variable to the mean of the respective variable. This is the default option.

User def. values.

Select the User def. values option button to set the current level of each predictor variable to user-specified values. These values can be inspected and/or specified by clicking the accompanying button, which will display the Select factor/covariate values dialog box, in which you can specify the current level for each predictor variable.

Optimum

Select the Optimum option button to set the current level of each predictor variable to the value determined by optimizing the response desirability.

Grid

Click the Grid button to specify the range and the grid points for each of the predictor variables in the analysis. Use the drop-down list adjacent to the Grid button to specify the factor for which you want to specify grid points. Clicking the Grid button will then display the Specifications for Factor Grid dialog box, in which you can specify the minimum value, the maximum value, and the number of intervals in the grid for the factor. These specifications determine the grid points for the factor, by setting the lowest grid point to the minimum value, the next lowest grid point to the minimum value plus the difference of the minimum value from the maximum value divided by the number of intervals, and so on up to the highest grid point.

Grid points serve two functions in the response/desirability profiler. They determine the plot points for the factors on the prediction profile compound graph (available via the View button), the surface plot (available via the Surface button), and the contour plot (available via the Contour button).

View

Click the View button to display a compound graph of the prediction profiles for each of the dependent variables that are selected to be profiled. The prediction profile compound graph contains a number of features that are useful for interpreting the effects of the predictor variables on responses on the dependent variables. For each dependent variable, a graph is produced showing the predicted values of the dependent variables at the minimum and maximum values of each predictor variable, and at each additional grid point for each predictor variable. Also shown are the current levels for each predictor variable. The predicted values that are shown for the dependent variables are the predicted responses at each level of each factor, holding all the other factors (including the block factor) constant at their current levels. Confidence intervals or prediction intervals for the predicted values are also shown if the Confidence intervals or the Prediction intervals option buttons, respectively, are selected in the Options for Response Profiler dialog box (accessed by clicking the Options button).

If the Show desirability function check box is selected in the Desirability function specifications group box (see below), clicking the View button will also produce a desirability function graph accompanying the predicted values for each of the dependent variables. The desirability function graph shows the desirability of the response (which can range from 0.0 for undesirable up to 1.0 for very desirable) across the observed range of each dependent variable (see Desirability function specifications options for details on specifying desirability function values for each dependent variable). Similar to the graphs of the predicted values for each dependent variable, graphs are produced for the overall desirability at each level of each factor, holding all other factors (including the block factor) constant at their current levels. Inspection of the desirability function graphs shows how the desirability of the responses on the dependent variables changes as the levels of the factors change.

Surface

Click the Surface button to plot the desirability function values in a surface plot, along with the specified grid points for the factors. A surface graph will be produced for each pair of factors, showing how the response desirability varies at each combination of grid points for each pair of factors, holding all other factors constant at their current levels. Note that several different options can be specified for fitting the desirability function values to the surface in the Options for Response Profiler dialog box (accessed by clicking the Options button).

Contour

Click the Contour button to plot the contours of the desirability function, along with the specified grid points for the factors. A contour plot will be produced for each pair of factors, showing how the response desirability varies at each combination of grid points for each pair of factors, holding all other factors constant at their current levels. Note that several different options can be specified for fitting the contours of the desirability function in the Options for Response Profiler dialog box (accessed by clicking the Options button).

Options

Click the Options button to display the Options for Response Profiler dialog box.

Desirability function specifications. Use the Desirability function specifications group box to enter desirability function specifications for the class displayed in the Variable combo box. These specifications determine the desirability function values (from 0.0 for undesirable to 1.0 for very desirable) corresponding to predicted values on the class. These specifications are entered in the Value and Desirability edit fields (see below). Note that the majority of the options in this group box are not available unless the Show desirability function check box is selected.

Show desirability function

Select the Show desirability function check box to enable the Desirability function specifications edit fields. By default, the Show desirability function check box is not selected and the Desirability function specifications edit fields are disabled. The Show desirability function check box is always selected when the Set factors at value Optimum option button has been selected. If the Set factors at value Optimum option has been selected and the Show desirability function check box is deselected, STATISTICA will then deselect the Optimum option button and select the Mean option button.

Variable

The Variable combo box allows you to select a class for which to specify Desirability function specifications. Select the class for which you want to specify Desirability function settings by selecting the class from the Variable button or combo box, and then enter the settings in the Value and Desirability edit fields.

Value - Low, Medium, and High Values

STATISTICA allows for up to three "inflection points" in the desirability function for predicted values for each dependent variable. For example, suppose that some intermediate predicted value on a dependent variable is highly desirable, and that lower and higher predicted values on the variable become progressively less desirable as they depart further from the "target" intermediate value. This type of desirability function would have three inflection points: the low value for the dependent variable, below which the response is undesirable, the high value for the dependent variable, above which the response is undesirable, and the medium value for the dependent variable, at which the response becomes increasingly desirable as it approaches the target value. The default specifications for the low value, medium value, and high value settings use a simple "higher is better" type of desirability function with only two inflection points. The low value is set to the observed minimum value for the dependent variable, the high value is set to the observed maximum value for the dependent variable, and the medium value is set to the mid-point between these two extremes. You can specify any other type of desirability function with up to three inflection points by entering the inflection points for the variable in the low value, medium value, and high value boxes. The only restriction is that adjacent inflection points must be in ascending order or equal in value.

Desirability - Low, Medium, and High Values

Desirability values (from 0.0 for undesirable to 1.0 for very desirable) can be specified for the corresponding inflection points of the desirability function for each of the dependent variables. For the example "target" type of desirability function described above, you would want to specify desirability values of 0.0 for responses with values below the low inflection point or above the high inflection point, and a desirability value of 1.0 for the targeted intermediate value. You would therefore specify values of 0.0, 1.0, and 0.0 for desirability in the low value, medium value, and high value boxes. The default specifications for the level of desirability at the three inflection points are based on a simple "higher is better" type of desirability function. Desirability is set to 0.0 at the low value, 0.5 at the medium value, and 1.0 at the high value. You can specify any other valid desirability values (from 0.0 to 1.0) by entering the appropriate value in the respective boxes.

Curvature - s and t parameters

The desirability of responses need not decrease (or increase) linearly between inflection points in the desirability function. Perhaps there is a "critical region" close to a desired, intermediate response on a dependent variable beyond which the desirability of the response at first drops off very quickly, but drops off less quickly as the departure from the "targeted" value becomes greater. To model this type of desirability function requires "curvature" parameters to take into account the nonlinearity in the "falloff" of desirability between inflection points. In the s parameter and t parameter boxes, you can specify a value for the exponent of the desirability function (from 0.0 up to 50, inclusive) representing the curvature in the desirability function between the low and medium inflection points of the function, and between the medium and high inflection points of the function, respectively. Assuming that an intermediate response is most desirable, values greater than 1.0 for the s parameter and t parameter represent initial quicker "falloff" in desirability but subsequent slower "falloff" in desirability as the departure from the "targeted" value becomes greater. Values less than 1.0 for the s parameter and t parameter represent initial slower "falloff" in desirability but subsequent quicker "falloff" in desirability as the departure from the "targeted" value becomes greater. The default specifications for the s parameter and t parameter are values of 1.0, representing linear "falloff" in desirability between the medium and low inflection points as well as between the medium and high inflection points. Further descriptions of the s parameter and t parameter and their effects in the desirability function can be found in the discussions of "two-sided" desirability functions in Derringer and Suich (1980) and in Box and Draper (1987).

Apply specs to all vars

Click the Apply specs to all vars button to apply the desirability settings you specify for one dependent variable to all the dependent variables in the analysis. This option is particularly useful if the same dependent variable is measured on, say, successive days. For example, you could specify the desirability of radioactivity readings of waste materials on the first day after the materials are discharged from a factory, then apply the same desirability settings for the radioactivity readings on subsequent days. If many days of readings are taken, the Apply desirability specifications to all variables option can save considerable data entry.

Reset specs

Click the Reset specs button to reset any changed desirability function settings for a dependent variable back to the default desirability function specifications for the variable (for details on default specifications, see Desirability function settings, above).

all vars

Click the all vars button to reset all desirability function settings for all dependent variables back to the default desirability function specifications (for details on default specifications, see Desirability function settings, above).

Open specs

Click the Open specs button to display a standard Open File dialog box that will prompt you for a file in which the desirability function settings specified for the classes in the analysis have been saved using the Save specs button (see below). Retrieval of previously saved settings can save considerable data entry in specifying desirability functions, especially when the analysis contains many classes each with distinct desirability function specifications.

Save specs

Click the Save specs button to display a standard Save As File dialog box that will prompt you for a file in which to save the desirability function settings specified for the classes in the analysis. These settings are then available for retrieval at a later time by using the Open specs option (see above). This can save considerable data entry in specifying desirability functions, especially when the analysis contains many classes each with distinct desirability function specifications.