UPCOMING WEBINAR: From Thousands of Tables To One Clear Story: using AI in survey analysis This article describes how to go from a MaxDiff Latent Class Analysis output:
To new variables that contain the Sawtooth-style preference shares (formula here) for the alternatives in a MaxDiff latent class analysis, MaxDiff hierarchical Bayes, or MaxDiff ensemble output. The shares are computed from the individual-level coefficients generated by the MaxDiff analysis.
Requirements
- A document containing a MaxDiff Latent Class Analysis, Hierarchical Bayes, or model ensembles output.
Method
- Select your latent class analysis output.
- From Properties
, click Data > Save Variable(s) > Sawtooth-Style Preference Shares (K Alternatives).
A new variable will appear in the Data Sources tree with the preference share values.
When displayed in a SUMMARY table, the output shows the preference shares as an Average in decimal form.
To show this as a percentage, you can change the Statistics > Cells to % Share or % Column Share (if the table is a crosstab).
Next
How to Do Latent Class Analysis
How to Do MaxDiff Latent Class Analysis
How to Use Hierarchical Bayes for MaxDiff
How to Create MaxDiff Model Ensembles
How to Create a MaxDiff Model Comparison Table
How to Create a MaxDiff Experimental Design
How to Save Respondent-Level Preference Shares from a MaxDiff Latent Class Analysis
How to Convert Alchemer MaxDiff Data for Analysis in Displayr