EconPapers    
Economics at your fingertips  
 

Does Controlling for Scale Heterogeneity Better Explain Respondents’ Preference Segmentation in Discrete Choice Experiments? A Case Study of US Health Insurance Demand

Suzana Karim, Benjamin M. Craig and Stephen Poteet
Additional contact information
Suzana Karim: Department of Economics, University of South Florida, Tampa, FL, USA
Benjamin M. Craig: Department of Economics, University of South Florida, Tampa, FL, USA
Stephen Poteet: Department of Economics, University of South Florida, Tampa, FL, USA

Medical Decision Making, 2021, vol. 41, issue 5, 573-583

Abstract: Analyses of preference evidence frequently confuse heterogeneity in the effects of attribute parameters (i.e., taste coefficients) and the scale parameter (i.e., variance). Standard latent class models often produce unreasonable classes with high variance and disordered coefficients because of confounding estimates of effect and scale heterogeneity. In this study, we estimated a scale-adjusted latent class model in which scale classes (heteroskedasticity) were identified using respondents’ randomness in choice behavior on the internet panel (e.g., time to completion and time of day). Hence, the model distinctly explained the taste/preference variation among classes associated with individual socioeconomic characters, in which scales are adjusted. Using data from a discrete-choice experiment on US health insurance demand among single employees, the results demonstrated how incorporating behavioral data enhances the interpretation of heterogeneous effects. Once scale heterogeneity was controlled, we found substantial heterogeneity with 4 taste classes. Two of the taste classes were highly premium sensitive (economy class), coming mostly from the low-income group, and the class associated with better educational backgrounds preferred to have a better quality of coverage of health insurance plans. The third class was a highly quality-sensitive class, with a higher SES background and lower self-stated health condition. The last class was identified as stayers, who were not premium or quality sensitive. This case study demonstrates that one size does not fit all in the analysis of preference heterogeneity. The novel use of behavioral data in the latent class analysis is generalizable to a wide range of health preference studies.

Keywords: discrete-choice experiments; latent class model; preference heterogeneity; heteroskedasticity; health insurance (search for similar items in EconPapers)
Date: 2021
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/0272989X21997345 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:medema:v:41:y:2021:i:5:p:573-583

DOI: 10.1177/0272989X21997345

Access Statistics for this article

More articles in Medical Decision Making
Bibliographic data for series maintained by SAGE Publications ().

 
Page updated 2025-03-19
Handle: RePEc:sae:medema:v:41:y:2021:i:5:p:573-583