Choice Modeling - Save Variable(s) - Individual-Level Coefficients

Create new variables which contain the individual-level coefficients from a Choice Modeling - Latent Class Analysis, Choice Modeling - Hierarchical Bayes] or Choice Modeling - Ensemble of Models output. 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.

Output

Running this QScript will produce a new variable, which will appear in your data set, for use in further analyses.

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/.

How to apply this QScript

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Click on the QScript when it appears in the QScripts and Rules section of the search results.

OR

Select Automate > Browse Online Library.
Select this QScript from the list.

Customizing the QScript

This QScript is written in JavaScript and can be customized by copying and modifying the JavaScript.

Customizing QScripts in Q4.11 and more recent versions

Start typing the name of the QScript into the Search features and data box in the top right of the Q window.
Hover your mouse over the QScript when it appears in the QScripts and Rules section of the search results.
Press Edit a Copy (bottom-left corner of the preview).
Modify the JavaScript (see QScripts for more detail on this).
Either:
- Run the QScript, by pressing the blue triangle button.
- Save the QScript and run it at a later time, using Automate > Run QScript (Macro) from File.

Customizing QScripts in older versions

Copy the JavaScript shown on this page.
Create a new text file, giving it a file extension of .QScript. See here for more information about how to do this.
Modify the JavaScript (see QScripts for more detail on this).
Run the file using Automate > Run QScript (Macro) from File.

JavaScript

includeWeb('QScript R Output Functions');

saveVariables('Individual-level coefficients', 'Latent Class Analysis or Hierarchical Bayes Choice Model',
              'input.choicemodel = ',
              '\nif (!is.null(input.choicemodel$simulated.respondent.parameters)) stop()\n' +
              'flipChoice::RespondentParameters(input.choicemodel)', null, null, 'ind.coef',
              ['FitChoice', 'ChoiceEnsemble']);