Create new variables which contain the utilities from a Choice Modeling - Latent Class Analysis, Choice Modeling - Hierarchical Bayes or Choice Modeling - Ensemble of Models output.
Technical details
Description
Individual-level coefficients are not able to be saved to variables for models with simulated data and models created using a CHO data file where respondent IDs were not specified.
If the choice model contains a "None of these" alternative, the utility of the "None of these" parameter will need to be adjusted in order to take into account the changes made to the utilities of the other attributes. For example, if there are 3 attributes in the model (not including the Alternative attribute), and their utilities needed to be shifted by +0.3, -0.5, +0.8 respectively, then the "None of these" utility will need to be shifted by +0.6 (= 0.3 - 0.5 + 0.8), in addition to any shifting and scaling done as part of the Alternative attribute.
Inputs
An R-based choice-model output.
Output
This automation will produce a new variable, which will appear in your data set for use in further analyses.
The various scaling options are described below:
- Individual-level coefficients - the respondent-level utilities unchanged.
- Utilities (Mean 0) - individual-level coefficients shifted so that for each individual and attribute the mean utility across the levels is zero.
- Utilities (Mean 0, Max Range 100) - individual-level coefficients scaled and shifted so that, for each individual and attribute, the lowest utility of any level is zero and the greatest utility of any level is 100.
- Utilities (Mean 0, Mean Range 100) - individual-level coefficients shifted so that, for each individual and attribute, the mean utility across the levels is zero. Utilities are then all multiplied by a scaling factor per individual, so that the average range of utilities per individual across the levels of each attribute is 100.
- Utilities (Min 0) - individual-level coefficients shifted so that, for each individual and attribute, the lowest utility of any level is zero.
- Utilities (Min 0, Max Range 100) - individual-level coefficients shifted so that, for each individual and attribute, the mean utility across the levels is zero. Utilities are then all multiplied by a scaling factor per individual, so that the maximum range of utilities per individual across the levels of any attribute is 100.
- Utilities (Min 0, Mean Range 100) - individual-level coefficients shifted so that, for each individual and attribute, the mean utility across the levels is zero. Utilities are then all multiplied by a scaling factor per individual, so that the average range of utilities per individual across the levels of each attribute is 100.
References
McLean, M. W. (2018, July 24). How to Use Hierarchical Bayes for Choice Modeling in Displayr [Blog post]. Accessed from https://www.displayr.com/how-to-hierarchical-bayes-choice-model-displayr/.
Method
- In Q: How to Save Utilities from a Choice Model
- In Displayr: How to Save Utilities from a Choice Model
See also
- QScript for more general information about QScripts.
- QScript Examples Library for other examples.
- Online JavaScript Libraries for the libraries of functions that can be used when writing QScripts.
- QScript Reference for information about how QScript can manipulate the different elements of a project.