How to Estimate Scale-Adjusted Latent Class (SALC) Models and Obtain Better Segments with Discrete Choice Data
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چکیده
Researchers frequently use Latent Class (LC) choice models for strategic segmentation and targeting purposes to 1) find meaningful segments of respondents having different preferences, and 2) estimate part-worth utilities for these segments. However, LC models can form spurious segments that mainly differ in terms of scale (response error) but don’t differ much in terms of real preference patterns.
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How to Estimate Scale-Adjusted Latent Class (SALC) Models and Obtain Better Segments with Discrete Choice Data
Researchers frequently use Latent Class (LC) choice models for strategic segmentation and targeting purposes to 1) find meaningful segments of respondents having different preferences, and 2) estimate part-worth utilities for these segments. However, LC models can form spurious segments that mainly differ in terms of scale (response error) but don’t differ much in terms of real preference patte...
متن کاملHow to Estimate Scale-Adjusted Latent Class (SALC) Models and Obtain Better Segments with Discrete Choice Data
Introduction and Goal of this tutorial Researchers frequently use Latent Class (LC) choice models for strategic segmentation and targeting purposes to 1) find meaningful segments of respondents having different preferences, and 2) estimate part-worth utilities for these segments. However, LC models can form spurious segments (such as Class 4 in Figure 1 below) that differ primarily in terms of ...
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