A Latent Class Approach to Inequity in Health Using Biomarker Data

Carrieri, Vincenzo, Davillas, Apostolos and Jones, Andrew M. (2019) A Latent Class Approach to Inequity in Health Using Biomarker Data.

Full text not available from this repository. (Request a copy)

Abstract

We develop an empirical approach to analyse, measure and decompose Inequality of Opportunity (IOp) in health, based on a latent class model. This addresses some of the limitations that affect earlier work in this literature concerning the definition of types, such as partial observability, the ad hoc selection of circumstances, the curse of dimensionality and unobserved type-specific heterogeneity that may lead to either upwardly or downwardly biased estimates of IOp. We apply the latent class approach to measure IOp in allostatic load, a composite measure of our biomarker data. Using data from Understanding Society (UKHLS), we find that a latent class model with three latent types best fits the data and that these types differ in terms of their observed circumstances. Decomposition analysis shows that about two-thirds of the total inequality in allostatic load can be attributed to the direct and indirect contribution of circumstances.

Item Type: Article
Uncontrolled Keywords: health(social science),economics and econometrics ,/dk/atira/pure/subjectarea/asjc/3300/3306
Faculty \ School: Faculty of Medicine and Health Sciences > Norwich Medical School
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 04 Feb 2020 04:52
Last Modified: 15 Sep 2020 23:58
URI: https://ueaeprints.uea.ac.uk/id/eprint/73972
DOI:

Actions (login required)

View Item View Item