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Modeling Semicontinuous Longitudinal Expenditures: A Practical Guide.

Valerie A Smith1,2, Matthew L Maciejewski1,2, Maren K Olsen1,3

  • 1Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, NC.

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|January 10, 2018
PubMed
Summary
This summary is machine-generated.

Analyzing longitudinal expenditure data with zero values requires careful model selection. The marginalized two-part (MTP) model is best for population means, while the conditional two-part (CTP) model suits incurred expenditures.

Keywords:
Semicontinuous datacostsexpenditurestwo-part modelszero-inflated

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Area of Science:

  • Biostatistics
  • Health Economics
  • Econometrics

Background:

  • Longitudinal expenditure data frequently exhibit a point mass at zero.
  • Analyzing such data requires specialized statistical models to account for the excess zeros and right-skewed positive values.

Purpose of the Study:

  • To compare different statistical strategies for analyzing longitudinal expenditure data with a point mass at zero.
  • To provide guidance on parameter interpretation, research questions, and model selection for these data.

Main Methods:

  • Comparison of one-part models, uncorrelated two-part models, correlated conditional two-part (CTP) models, and correlated marginalized two-part (MTP) models.
  • Illustration using longitudinal specialty care expenditures of veterans with hypertension (2000-2003) from Veterans Administration data.

Main Results:

  • The four modeling strategies address different research questions and data structures, yielding distinct results.
  • The MTP model is optimal for population mean expenditures when a point mass at zero exists.
  • The CTP model is preferable for analyzing expenditures conditional on them being incurred.

Conclusions:

  • Model selection for longitudinal expenditure outcomes should align with specific research aims and data characteristics.
  • Understanding the nuances of CTP and MTP models is crucial for appropriate application in health economics and biostatistics.