title: A flexible model for correlated medical costs, with application to medical expenditure panel survey data.
abstract: We propose a flexible model for correlated medical cost data with several appealing features. First, the mean function is partially linear. Second, the distributional form for the response is not specified. Third, the covariance structure of correlated medical costs has a semiparametric form. We use extended generalized estimating equations to simultaneously estimate all parameters of interest. B-splines are used to estimate unknown functions, and a modification to Akaike information criterion is proposed for selecting knots in spline bases. We apply the model to correlated medical costs in the Medical Expenditure Panel Survey dataset. Simulation studies are conducted to assess the performance of our method.
authors.affiliation: Department of Medicine, University of Illinois at Chicago, Chicago, IL, U.S.A.
authors.forename: Jinsong
authors.initials: J
authors.lastname: Chen
authors.affiliation: Department of Preventive Medicine, Northwestern University, Chicago, IL, U.S.A.
authors.forename: Lei
authors.initials: L
authors.lastname: Liu
authors.affiliation: Department of Medicine, The University of Chicago, Chicago, IL, U.S.A.
authors.forename: Ya-Chen T
authors.initials: YC
authors.lastname: Shih
authors.affiliation: Department of Statistics, North Carolina State University, Raleigh, NC, U.S.A.
authors.forename: Daowen
authors.initials: D
authors.lastname: Zhang
authors.affiliation: Department of Statistics, Northwestern University, Evanston, IL, U.S.A.
authors.forename: Thomas A
authors.initials: TA
authors.lastname: Severini
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015982:Bias; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D017048:Health Care Costs / Q000706:statistics & numerical data* / Q000639:trends; D005102:Health Expenditures / Q000706:statistics & numerical data* / Q000639:trends; D006801:Humans; D016014:Linear Models; D008297:Male; D018803:Models, Economic; D014481:United States
keywords: generalized estimating equation; generalized linear model; health econometrics; model selection; semiparametric regression