Literature DB >> 18078478

Regression analysis of panel count data with dependent observation times.

Jianguo Sun1, Xingwei Tong, Xin He.   

Abstract

Panel count data often occur in long-term studies that concern occurrence rate of a recurrent event. Methods have been proposed for regression analysis of panel count data, but most of the existing research focuses on situations where observation times are independent of longitudinal response variables and therefore rely on conditional inference procedures given the observation times. This article considers a different situation where the independence assumption may not hold. That is, the observation times and the response variable may be correlated. For inference, estimating equation approaches are proposed for estimation of regression parameters and both large and finite sample properties of the proposed estimates are established. An illustrative example from a cancer study is provided.

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Year:  2007        PMID: 18078478     DOI: 10.1111/j.1541-0420.2007.00808.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  13 in total

1.  Semiparametric analysis of panel count data with correlated observation and follow-up times.

Authors:  Xin He; Xingwei Tong; Jianguo Sun
Journal:  Lifetime Data Anal       Date:  2008-12-10       Impact factor: 1.588

2.  Regression analysis of longitudinal data with correlated censoring and observation times.

Authors:  Yang Li; Xin He; Haiying Wang; Jianguo Sun
Journal:  Lifetime Data Anal       Date:  2015-06-30       Impact factor: 1.588

3.  Robust estimation for panel count data with informative observation times and censoring times.

Authors:  Hangjin Jiang; Wen Su; Xingqiu Zhao
Journal:  Lifetime Data Anal       Date:  2018-12-12       Impact factor: 1.588

4.  Joint analysis of panel count data with an informative observation process and a dependent terminal event.

Authors:  Jie Zhou; Haixiang Zhang; Liuquan Sun; Jianguo Sun
Journal:  Lifetime Data Anal       Date:  2016-07-23       Impact factor: 1.588

5.  Semiparametric partially linear varying coefficient models with panel count data.

Authors:  Xin He; Xuenan Feng; Xingwei Tong; Xingqiu Zhao
Journal:  Lifetime Data Anal       Date:  2016-04-27       Impact factor: 1.588

6.  A semiparametric likelihood-based method for regression analysis of mixed panel-count data.

Authors:  Liang Zhu; Ying Zhang; Yimei Li; Jianguo Sun; Leslie L Robison
Journal:  Biometrics       Date:  2017-09-15       Impact factor: 2.571

7.  Semiparametric Random Effects Models for Longitudinal Data with Informative Observation Times.

Authors:  Yang Li; Yanqing Sun
Journal:  Stat Interface       Date:  2016       Impact factor: 0.582

8.  Semiparametric analysis for recurrent event data with time-dependent covariates and informative censoring.

Authors:  C-Y Huang; J Qin; M-C Wang
Journal:  Biometrics       Date:  2009-05-12       Impact factor: 2.571

9.  Marginal mark regression analysis of recurrent marked point process data.

Authors:  Benjamin French; Patrick J Heagerty
Journal:  Biometrics       Date:  2009-06       Impact factor: 2.571

10.  Biased and unbiased estimation in longitudinal studies with informative visit processes.

Authors:  Charles E McCulloch; John M Neuhaus; Rebecca L Olin
Journal:  Biometrics       Date:  2016-03-17       Impact factor: 2.571

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