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Measuring Worksite Health Promotion Programs: an application of Structural Equation Modeling with ordinal data

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  • Fredrik Ødegaard
  • Pontus Roos

Abstract

This paper presents a model for measuring the outcome of Worksite Health Promotion Programs through an application of Structural Equation Modeling with ordinal data. We model the function “being healthy” as a vector comprised of three latent or unobservable variables: Health Status, Lifestyle and Stress. Each variable can be measured only indirectly through a set of manifest or observable ordinal indicators. The objective is to derive and analyze the distributions, and changes in distributions over time, of the latent variables on an individual level. The model is analyzed empirically on data from three large Swedish manufacturing firms. Copyright Springer-Verlag 2013

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  • Fredrik Ødegaard & Pontus Roos, 2013. "Measuring Worksite Health Promotion Programs: an application of Structural Equation Modeling with ordinal data," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 14(4), pages 639-653, August.
    • Handle: RePEc:spr:eujhec:v:14:y:2013:i:4:p:639-653
    DOI: 10.1007/s10198-012-0409-4
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    Cited by:

    1. Roselinde Kessels & Guido Erreygers, 2016. "Structural equation modeling for decomposing rank-dependent indicators of socioeconomic inequality of health: an empirical study," Health Economics Review, Springer, vol. 6(1), pages 1-13, December.

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    JEL classification:

    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • I1 - Health, Education, and Welfare - - Health
    • M5 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics

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