Produces a 95% confidence interval for each parameter (by default), using the profile-likelihood method. Shift-click the platform red triangle menu and select Confidence Intervals to input alpha values other than 0.05.
Shows the predicted utility for different factor settings. The utility is the value predicted by the linear model. See Explore the Model for an example of the Utility Profiler. For details about the Utility Profiler options, see the Prediction Profiler Options section in the Profiler chapter of the Profilers book.
Shows the predicted probability for choosing the given factor settings compared with baseline factor settings. This predicted probability is defined as , where U is the utility for the current settings and Ub is the utility for the baseline settings. See Compare to Baseline for an example of using the Probability Profiler. For details about the Probability Profiler options, see the Prediction Profiler Options section in the Profiler chapter of the Profilers book.
Enables you to set up a number of choice sets and see the probabilities of choosing each set relative to the other choices. See Multiple Choice Comparison for an example of using the Multiple Choice Profiler. For details about the Multiple Choice Profiler options, see the Prediction Profiler Options section in the Profiler chapter of the Profilers book.
Performs comparisons between specific alternative choice profiles. Enables you to select factor values and the values that you want to compare. From here you can compare specific configurations, including comparing all settings on the left or right by selecting the Any check boxes. Using Any does not compare all combinations across features, but rather all combinations of comparisons, one feature at a time, using the left settings as the settings for the other factors.
Calculates how much a price must change allowing for the new feature settings to produce the same predicted outcome. The result is calculated using the Baseline settings (for each background setting) and then determining the outcome after altering the Role, including.
The Include baseline settings in report table option adds the baseline settings with a price change of zero, which is useful if you make an output table of these prices displaying all the baseline settings as well as the featured settings.
Makes a new column with a formula for the utility, or linear model, that is estimated. This is in the profile data table, except if there are subject effects. In that case, it makes a new data table for the formula. This formula can be used with various profilers with subsequent analyses. For more details about the Utility Formula, see Statistical Details.
Constructs a new table that has a row for each subject containing the average (Hessian-scaled-gradient) steps on each parameter. This corresponds to using a Lagrangian multiplier test for separating that subject from the remaining subjects. These values can later be clustered, using the built-in-script, to indicate unique market segments represented in the data. For more details, see Segmentation.