GDA - Response/Desirability Profiler

This topic explains in detail the options on the GDA Models Results - Profiler tab. For an overview of response/desirability profiling see the Experimental Design Profiling Predicted Responses and Response Desirability topic.

Note: the names and organization of the options on the Profiler tab may be different depending if you are viewing the smaller or the larger GDA Models Results dialog. The order of the options below reflect that of the smaller GDA Models Results - Profiler tab. The names of the options below reflect that of the smaller GDA Models Results - Profiler tab with the names of the larger GDA Models Results - Profiler tab in parentheses.
Element Name Description
Classes Click the Classes button to display the Classes for Residuals dialog, which is used to select the classes (levels) of the dependent variables to profile by selecting those classes on the list. Note that you can specify desirability function settings for all classes of the dependent variable in the analysis, thus the Classes option allows you to easily select subsets of classes or a single class to profile.
View Click the View button to display a compound graph of the prediction profiles for each of the Classes that were 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 classes. For each class a graph is produced showing the predicted values of the classes at the minimum and maximum values of each predictor variable, and at each additional grid point for each predictor variable (see the Grid button below for details on specifying these values). Also shown are the current levels for each predictor variable (see the Set factors at value group box below for details on specifying these values). The predicted values that are shown for the classes are the predicted responses at each class, holding all the other classes 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, have been selected on the Options for Response Profiler dialog.

If the Show desirability function check box is selected, clicking the View button will also display a desirability function graph accompanying the predicted values for each of the classes. 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 class (see Desirability function specifications group box below for details on specifying desirability function values for each class). Similar to the graphs of the predicted values for each class, graphs are produced for the overall desirability at each class, holding all other classes constant at their current levels. Inspection of the desirability function graphs shows how the desirability of the responses on the classes changes as the classes change.

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

  1. Click the 1 button to plot the desirability function values in a plot, along with the specified grid points for the classes. A surface graph will be produced for each pair of classes, showing how the response desirability varies at each combination of grid points for each pair of classes, holding all other classes constant at their current levels. Note that several different options can be specified for fitting the desirability function values to the surface on the Options for Response Profiler dialog.
  2.  Click the 2 button to plot the contours of the desirability function, along with the specified grid points for the classes. A contour plot will be produced for each pair of classes, showing how the response desirability varies at each combination of grid points for each pair of classes, holding all other classes constant at their current levels. Note that several different options can be specified for fitting the contours of the desirability function on the Options for Response Profiler dialog.
Set factors at value The Set factors at value group box allows you 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 1 button), and the contour plot (available via the 2 button). 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. Select the User vals (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 , which will display the Select Factor/Covariate Values dialog on which you can specify the current level for each predictor variable. 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 experimental range and the grid points for each of the predictor variables in the analysis. The combo box by the Grid button allows you 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 on 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 1 button), and the contour plot (available via the 2 button).

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 cleared, 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.
Values to profile  Use the options in the Values to profile group box to select to profile Posterior classification probabilities or Regression predicted values for the classes (groups) specified via the Classes button. See Profiling Regression-like Predicted Responses and Profiling Posterior Probabilities for further details on the options in this box. This group box is only available on the larger GDA Models Results dialog. If you can not see this group box, select the More results button at the button of the smaller GDA Models Results dialog.
Value - Low, Med., and High. Enter up to three "inflection points" in the desirability function for predicted values for each class in the Value edit fields. For example, suppose that some intermediate predicted value on a class 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 class, below which the response is undesirable, the high value for the class, above which the response is undesirable, and the medium value for the class, 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 class, the High value is set to the observed maximum value for the class, and the Med. 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, Med Value, and High Value edit fields. The only restriction is that adjacent inflection points must be in ascending order or equal in value.
Desirability - Low, Med., and High Desirability values (from 0.0 for undesirable to 1.0 for very desirable) can be entered for the corresponding inflection points of the desirability function for each of the classes. 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, Med. Value, and High Value edit fields. 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 Med. Value, and 1.0 at the High Value. You can specify any other valid (from 0.0 to 1.0) desirability values by entering the appropriate value in the respective edit field.
Curvature - s (low) and t (high) Enter the Curvature parameters in the s and t edit fields. 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 class 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 and t edit fields 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 become 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 become greater. The default specifications for the s parameter and t parameter are values of 1.0, representing linear "falloff" in desirability between the Med. and Low inflection points as well as between the Med. 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 to all vars (Apply specs to all vars) Click the Apply to all vars button to apply the desirability settings you specify for one class to all the classes in the analysis. This option is particularly useful if the same class 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 to all vars button can save considerable data entry.
Reset specs Click the Reset specs button to reset any changed desirability function settings for a class back to the default desirability function specifications for the variable (for details on default specifications, see above).
all vars Choosing the all vars option will reset any changed desirability function settings for the classes back to the default desirability function specifications for each respective class (for details on default specifications, see above).
Open specs Click the Open specs button to display a standard Open File dialog 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 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.