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Regression Analysis of Longitudinal Data with Time‐Dependent Covariates and Informative Observation Times
Author(s) -
SONG XINYUAN,
MU XIAOYUN,
SUN LIUQUAN
Publication year - 2012
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/j.1467-9469.2011.00776.x
Subject(s) - covariate , estimator , mathematics , statistics , regression analysis , longitudinal data , estimating equations , latent variable , econometrics , regression , inference , statistical inference , data mining , computer science , artificial intelligence
. Longitudinal data frequently occur in many studies, and longitudinal responses may be correlated with observation times. In this paper, we propose a new joint modelling for the analysis of longitudinal data with time‐dependent covariates and possibly informative observation times via two latent variables. For inference about regression parameters, estimating equation approaches are developed and asymptotic properties of the proposed estimators are established. In addition, a lack‐of‐fit test is presented for assessing the adequacy of the model. The proposed method performs well in finite‐sample simulation studies, and an application to a bladder tumour study is provided.