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Modeling healthcare costs in simultaneous presence of asymmetry, heteroscedasticity and correlation


  • Ileana Baldi
  • Eva Pagano
  • Paola Berchialla
  • Alessandro Desideri
  • Alberto Ferrando
  • Franco Merletti
  • Dario Gregori


Highly skewed outcome distributions observed across clusters are common in medical research. The aim of this paper is to understand how regression models widely used for accommodating asymmetry fit clustered data under heteroscedasticity. In a simulation study, we provide evidence on the performance of the Gamma Generalized Linear Mixed Model (GLMM) and log-Linear Mixed-Effect (LME) model under a variety of data-generating mechanisms. Two case studies from health expenditures literature, the cost of strategies after myocardial infarction randomized clinical trial on the cost of strategies after myocardial infarction and the European Pressure Ulcer Advisory Panel hospital prevalence survey of pressure ulcers, are analyzed and discussed. According to simulation results, the log-LME model for a Gamma response can lead to estimations that are biased by as much as 10% of the true value, depending on the error variance. In the Gamma GLMM, the bias never exceeds 1%, regardless of the extent of heteroscedasticity, and the confidence intervals perform as nominally stated under most conditions. The Gamma GLMM with a log link seems to be more robust to both Gamma and log-normal generating mechanisms than the log-LME model.

Suggested Citation

  • Ileana Baldi & Eva Pagano & Paola Berchialla & Alessandro Desideri & Alberto Ferrando & Franco Merletti & Dario Gregori, 2013. "Modeling healthcare costs in simultaneous presence of asymmetry, heteroscedasticity and correlation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 298-310, February.
  • Handle: RePEc:taf:japsta:v:40:y:2013:i:2:p:298-310
    DOI: 10.1080/02664763.2012.740628

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    References listed on IDEAS

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    Cited by:

    1. Besstremyannaya, Galina, 2017. "Measuring income equity in the demand for healthcare with finite mixture models," Applied Econometrics, Publishing House "SINERGIA PRESS", vol. 46, pages 5-29.
    2. Galina Besstremyannaya, 2014. "Heterogeneous effect of coinsurance rate on healthcare costs: generalized finite mixtures and matching estimators," Discussion Papers 14-014, Stanford Institute for Economic Policy Research.

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