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Stat Med. 2013 Oct 30;32(24):4306-18. doi: 10.1002/sim.5838. Epub 2013 May 13.

A flexible model for the mean and variance functions, with application to medical cost data.

Author information

1
Department of Preventive Medicine, Northwestern University, Chicago, IL, USA.

Abstract

Medical cost data are often skewed to the right and heteroscedastic, having a nonlinear relation with covariates. To tackle these issues, we consider an extension to generalized linear models by assuming nonlinear associations of covariates in the mean function and allowing the variance to be an unknown but smooth function of the mean. We make no further assumption on the distributional form. The unknown functions are described by penalized splines, and the estimation is carried out using nonparametric quasi-likelihood. Simulation studies show the flexibility and advantages of our approach. We apply the model to the annual medical costs of heart failure patients in the clinical data repository at the University of Virginia Hospital System.

KEYWORDS:

generalized cross-validation; generalized linear model; health econometrics; semiparametric regression; smoothing parameter

PMID:
23670952
PMCID:
PMC4669967
DOI:
10.1002/sim.5838
[Indexed for MEDLINE]
Free PMC Article
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