Choice Modeling - Save Variable(s) - Class Membership Probabilities

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Save variables that contain the probability of each case being in each latent class (if applicable)

Create new variables which contain the probability for each respondent to belong to each class, for a Choice Modeling - Latent Class Analysis output.

Output

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

How to apply this QScript

  • Start typing the name of the QScript into the Search features and data box in the top right of the Q window.
  • 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");
 
main();
 
function main() {
    var selected_item = getSelectedROutputFromPage([]);
    var expected_class = selected_item !== null &&
                         selected_item.outputClasses.indexOf("FitChoiceLCA") == -1 &&
                         selected_item.data.get("algorithm")[0] == "LCA"  ? "FitChoice" : "FitChoiceLCA";

    saveVariables("Class membership probabilities", "Latent Class Analysis or Hierarchical Bayes", 
    "input.choicemodel = ", 
    "\nif (is.null(input.choicemodel$lca.data)) stop()\n"
    + "input.choicemodel$posterior.probabilities", null, null, "cls.memb.prob", expected_class);
}

See also