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Default Priors Based on Pseudo-Likelihoods for the Poisson-GPD Model Read chapter Read first chapter

2013 | OriginalPaper | Chapter

19. Joint Modeling of Longitudinal and Time-to-Event Data: Challenges and Future Directions

Author : Dimitris Rizopoulos

Published in: Advances in Theoretical and Applied Statistics

Publisher: Springer Berlin Heidelberg

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Abstract

In longitudinal studies measurements are often collected on different types of outcomes for each subject. These may include several longitudinally measured responses (such as blood values relevant to the medical condition under study) and the time at which an event of particular interest occurs (e.g., death, development of a disease or dropout from the study). These outcomes are often separately analyzed; however, in many instances, a joint modeling approach is either required or may produce a better insight into the mechanisms that underlie the phenomenon under study. In this chapter we provide a general overview of the joint modeling framework, discuss its main features, and we refer to future directions.

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Literature
1.
Brown, E., Ibrahim, J.: A Bayesian semiparametric joint hierarchical model for longitudinal and survival data. Biometrics 59, 221–228 (2003)MathSciNetMATHCrossRef
2.
Brown, E., Ibrahim, J., DeGruttola, V.: A flexible b-spline model for multiple longitudinal biomarkers and survival. Biometrics 61, 64–73 (2005)MathSciNetMATHCrossRef
3.
4.
Ding, J., Wang, J.L.: Modeling longitudinal data with nonparametric multiplicative random effects jointly with survival data. Biometrics 64, 546–556 (2008)MathSciNetMATHCrossRef
5.
Elashoff, R., Li, G., Li, N.: A joint model for longitudinal measurements and survival data in the presence of multiple failure types. Biometrics 64, 762–771 (2008)MathSciNetMATHCrossRef
6.
Faucett, C., Schenker, N., Elashoff, R.: Analysis of censored survival data with intermittently observed time-dependent binary covariates. J. Am. Stat. Assoc. 93, 427–437 (1998)MATHCrossRef
7.
Follmann, D., Wu, M.: An approximate generalized linear model with random effects for informative missing data. Biometrics 51, 151–168 (1995)MathSciNetMATHCrossRef
8.
Henderson, R., Diggle, P., Dobson, A.: Joint modelling of longitudinal measurements and event time data. Biostatistics 1, 465–480 (2000)MATHCrossRef
9.
Hsieh, F., Tseng, Y.K., Wang, J.L.: Joint modeling of survival and longitudinal data: likelihood approach revisited. Biometrics 62, 1037–1043 (2006)MathSciNetMATHCrossRef
10.
Kalbfleisch, J., Prentice, R.: The Statistical Analysis of Failure Time Data, 2nd edn. Wiley, New York (2002)MATHCrossRef
11.
12.
Little, R., Rubin, D.: Statistical Analysis with Missing Data, 2nd edn. Wiley, New York (2002)MATH
13.
Murtaugh, P., Dickson, E., Van Dam, G., Malincho, M., Grambsch, P., Langworthy, A., Gips, C.: Primary biliary cirrhosis: prediction of short-term survival based on repeated patient visits. Hepatology 20, 126–134 (1994)CrossRef
14.
15.
Proust-Lima, C., Joly, P., Dartigues, J.F., Jacqmin-Gadda, H.: Joint modelling of multivariate longitudinal outcomes and a time-to-event: a nonlinear latent class approach. Comput. Stat. Data Anal. 53, 1142–1154 (2009)MathSciNetMATHCrossRef
16.
Rizopoulos, D.: JM: an R package for the joint modelling of longitudinal and time-to-event data. J. Stat. Software 35(9), 1–33 (2010)
17.
Rizopoulos, D., Ghosh, P.: A Bayesian semiparametric multivariate joint model for multiple longitudinal outcomes and a time-to-event. Stat. Med. 30, 1366–1380 (2011)MathSciNetCrossRef
18.
Rizopoulos, D., Verbeke, G., Lesaffre, E.: Fully exponential laplace approximations for the joint modelling of survival and longitudinal data. J. Roy. Stat. Soc. Ser. B 71, 637–654 (2009)MathSciNetMATHCrossRef
19.
Rizopoulos, D., Verbeke, G., Molenberghs, G.: Shared parameter models under random effects misspecification. Biometrika 95, 63–74 (2008)MathSciNetMATHCrossRef
20.
Rizopoulos, D., Verbeke, G., Molenberghs, G.: Multiple-imputation-based residuals and diagnostic plots for joint models of longitudinal and survival outcomes. Biometrics 66, 20–29 (2010)MathSciNetMATHCrossRef
21.
22.
Song, X., Davidian, M., Tsiatis, A.: A semiparametric likelihood approach to joint modeling of longitudinal and time-to-event data. Biometrics 58, 742–753 (2002)MathSciNetMATHCrossRef
23.
Therneau, T., Grambsch, P.: Modeling Survival Data: Extending the Cox Model. Springer, New York (2000)
24.
Tsiatis, A., Davidian, M.: A semiparametric estimator for the proportional hazards model with longitudinal covariates measured with error. Biometrika 88, 447–458 (2001)MathSciNetMATHCrossRef
25.
Tsiatis, A., Davidian, M.: Joint modeling of longitudinal and time-to-event data: an overview. Statistica Sinica 14, 809–834 (2004)MathSciNetMATH
26.
Verbeke, G., Molenberghs, G.: Linear Mixed Models for Longitudinal Data. Springer, New York (2000)MATH
27.
Wang, Y., Taylor, J.: Jointly modeling longitudinal and event time data with application to acquired immunodeficiency syndrome. J. Am. Stat. Assoc. 96, 895–905 (2001)MathSciNetMATHCrossRef
28.
Wu, M., Bailey, K.: Analysing changes in the presence of informative right censoring caused by death and withdrawal. Stat. Med. 7, 337–346 (1988)CrossRef
29.
Wu, M., Carroll, R.: Estimation and comparison of changes in the presence of informative right censoring by modeling the censoring process. Biometrics 44, 175–188 (1988)MathSciNetMATHCrossRef
30.
31.
Xu, J., Zeger, S.: Joint analysis of longitudinal data comprising repeated measures and times to events. Appl. Stat. 50, 375–387 (2001)MathSciNetMATH
32.
Yu, M., Law, N., Taylor, J., Sandler, H.: Joint longitudinal-survival-cure models and their application to prostate cancer. Statistica Sinica 14, 835–832 (2004)MathSciNetMATH
Metadata
Title
Joint Modeling of Longitudinal and Time-to-Event Data: Challenges and Future Directions
Author
Dimitris Rizopoulos
Copyright Year
2013
Publisher
Springer Berlin Heidelberg
Book
Advances in Theoretical and Applied Statistics

Print ISBN: 978-3-642-35587-5

Electronic ISBN: 978-3-642-35588-2

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-3-642-35588-2_19

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