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A marginalized two-part model for semicontinuous data.

Valerie A Smith1, John S Preisser, Brian Neelon

  • 1Center for Health Services Research in Primary Care, Durham VAMC, Durham, NC, U.S.A.; Department of Biostatistics, University of North Carolina, Chapel Hill, NC, 27599-7420, U.S.A.

Statistics in Medicine
|July 22, 2014
PubMed
Summary
This summary is machine-generated.

We introduce a new marginalized two-part model for analyzing semicontinuous health data. This model offers interpretable covariate effects on overall health care expenditures, improving upon traditional two-part models.

Keywords:
health-care expenditureslog-skew-normal distributionmarginalized modelssemicontinuous datatwo-part modelweight loss intervention

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Area of Science:

  • Health Services Research
  • Biostatistics
  • Econometrics

Background:

  • Semicontinuous data, common in health services research (e.g., health expenditures), present a zero mass and a right-skewed distribution.
  • Traditional two-part mixture models analyze these data by separately modeling service use and expenditure levels.
  • Conventional models lack marginal interpretation of covariate effects on the entire population, hindering understanding of overall impacts.

Purpose of the Study:

  • To propose a marginalized two-part model for analyzing semicontinuous health data.
  • To provide interpretable marginal effect estimates for covariate impacts on overall health care expenditures.
  • To address limitations of conventional two-part models in health services research.

Main Methods:

  • Developed a marginalized two-part model by parameterizing in terms of the marginal mean.
  • The model retains capabilities for handling zero-inflation and right-skewness.
  • Utilized a simulation study to assess the properties of maximum likelihood estimates.

Main Results:

  • The proposed marginalized two-part model yields interpretable effect estimates for the overall population.
  • Simulation results examined the performance of maximum likelihood estimates under various conditions.
  • The model was applied to evaluate a weight loss intervention's effect on healthcare expenditures.

Conclusions:

  • The marginalized two-part model offers a valuable alternative for analyzing semicontinuous health data.
  • It provides a marginal interpretation of covariate effects, crucial for policy and intervention evaluations.
  • This approach enhances the analysis of health expenditures and similar data types in health services research.