title: Efficient quantile marginal regression for longitudinal data with dropouts.
abstract: In many biomedical studies independent variables may affect the conditional distribution of the response differently in the middle as opposed to the upper or lower tail. Quantile regression evaluates diverse covariate effects on the conditional distribution of the response with quantile-specific regression coefficients. In this paper, we develop an empirical likelihood inference procedure for longitudinal data that accommodates both the within-subject correlations and informative dropouts under missing at random mechanisms. We borrow the matrix expansion idea of the quadratic inference function and incorporate the within-subject correlations under an informative working correlation structure. The proposed procedure does not assume the exact knowledge of the true correlation structure nor does it estimate the parameters of the correlation structure. Theoretical results show that the resulting estimator is asymptotically normal and more efficient than one attained under a working independence correlation structure. We expand the proposed approach to account for informative dropouts under missing at random mechanisms. The methodology is illustrated by empirical studies and a real-life example of HIV data analysis.
authors.affiliation: Department of Statistics, Western Michigan University, Kalamazoo, MI 49008, USA.
authors.forename: Hyunkeun
authors.initials: H
authors.lastname: Cho
authors.affiliation: Department of Statistics and Probability, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: Hyokyoung Grace
authors.initials: HG
authors.lastname: Hong
authors.affiliation: Division of Biostatistics and Epidemiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA miok.kim@cchmc.org.
authors.forename: Mi-Ok
authors.initials: MO
authors.lastname: Kim
mesh_terms: D003627:Data Interpretation, Statistical; D015658:HIV Infections / Q000097:blood / Q000188:drug therapy; D006801:Humans; D008137:Longitudinal Studies; D015233:Models, Statistical; D010352:Patient Dropouts; D012044:Regression Analysis
keywords: Empirical likelihood; Longitudinal data; Missing at random; Quadratic inference function; Quantile regression