Research Methods

Extracting Meaningful Segments from HB Utilities

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About this presentation

In this presentation we illustrate how latent class (LC) clustering should be performed on HB utilities to avoid strange results, and describe the situations where Latent GOLD’s scale-adjusted (SALC) model would be expected to result in more meaningful segments. Our MaxDiff example yields 88% agreement with the gold standard, vs. 60% when clustering is done incorrectly. Attendees will take away new insights into the segmentation process when latent class models are applied to HB utilities.

Jay Magidson
Statistical Innovations
Jeroen K. Vermunt
Tilburg University
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