Joint modeling of longitudinal and survival data with missing and left-censored time-varying covariates-Reference-Cited by-同舟云学术

Joint modeling of longitudinal and survival data with missing and left-censored time-varying covariates

Published:2014-06-20 Issue:26 Volume:33 Page:4560-4576
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statist. Med.

Author:

Chen Qingxia¹²,May Ryan C.³,Ibrahim Joseph G.⁴,Chu Haitao⁵,Cole Stephen R.⁶

Affiliation:

1. Department of Biostatistics; Vanderbilt University; Nashville TN 37232 U.S.A.

2. Department of Biomedical Informatics; Vanderbilt University; Nashville TN 37232 U.S.A.

3. The EMMES Corporation; Rockville MD 20850 U.S.A.

4. Department of Biostatistics; University of North Carolina at Chapel Hill; Chapel Hill NC 27599 U.S.A.

5. Division of Biostatistics, School of Public Health; University of Minnesota; Minneapolis MN 55455 U.S.A.

6. Department of Epidemiology; University of North Carolina at Chapel Hill; Chapel Hill NC 27599 U.S.A.

Funder

National Institutes of Health

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/sim.6242/fullpdf

Reference44 articles.

1. A joint model for survival and longitudinal data measured with error;Wulfsohn;Biometrics,1997

2. Modeling progression of CD-4 lymphocyte count and its relationship to survival time;DeGruttola;Biometrics,1994

3. Basic concepts and methods for joint models of longitudinal and survival data;Ibrahim;Journal of Clinical Oncology,2010

4. Zhang D Chen MH Ibrahim JG Boye ME Wang P Shen W Assessing model fit in joint models of longitudinal and survival data with applications to cancer clinical trials Technical Report

5. Statistical Analysis with Missing Data

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