Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/62729
Title: A uniform semiparametric approach for longitudinal data analysis
Authors: Zhou, X
Sun, L
Sun, J
Keywords: Counting process
Estimating function
Longitudinal study
Repeated measurements
Issue Date: 2004
Publisher: Pushpa Publishing House
Source: Far East journal of theoretical statistics, 2004, v. 13, no. 2, p. 233-256 How to cite?
Journal: Far East journal of theoretical statistics 
Abstract: Longitudinal data commonly occur in medical follow-up studies and epidemiological experiments. They usually include repeated measurements of the response variable and covariates at a set of distinct, irregularly spaced time points for each subject. One of the difficulties for the analysis of such data is that the set of observation times may vary from subject to subject. For their analysis, a number of methods have been proposed, but most of them were developed under specific models. In this paper, a class of general and uniform models is presented for semiparametric analysis of longitudinal data. For inference about regression parameters, a class of consistent and asymptotically normal estimators is proposed. Extensive simulation studies are conducted and an example with data from an AIDS clinical trial is presented to illustrate the proposed methodology.
URI: http://hdl.handle.net/10397/62729
ISSN: 0972-0863
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