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A semiparametric likelihood approach to joint modeling of longitudinal and time-to-event data.

Publication ,  Journal Article
Song, X; Davidian, M; Tsiatis, AA
Published in: Biometrics
December 2002

Joint models for a time-to-event (e.g., survival) and a longitudinal response have generated considerable recent interest. The longitudinal data are assumed to follow a mixed effects model, and a proportional hazards model depending on the longitudinal random effects and other covariates is assumed for the survival endpoint. Interest may focus on inference on the longitudinal data process, which is informatively censored, or on the hazard relationship. Several methods for fitting such models have been proposed, most requiring a parametric distributional assumption (normality) on the random effects. A natural concern is sensitivity to violation of this assumption; moreover, a restrictive distributional assumption may obscure key features in the data. We investigate these issues through our proposal of a likelihood-based approach that requires only the assumption that the random effects have a smooth density. Implementation via the EM algorithm is described, and performance and the benefits for uncovering noteworthy features are illustrated by application to data from an HIV clinical trial and by simulation.

Duke Scholars

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Published In

Biometrics

DOI

ISSN

0006-341X

Publication Date

December 2002

Volume

58

Issue

4

Start / End Page

742 / 753

Location

England

Related Subject Headings

  • Statistics & Probability
  • Randomized Controlled Trials as Topic
  • Proportional Hazards Models
  • Monte Carlo Method
  • Longitudinal Studies
  • Likelihood Functions
  • Humans
  • HIV Infections
  • Disease Progression
  • Computer Simulation
 

Citation

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Song, X., Davidian, M., & Tsiatis, A. A. (2002). A semiparametric likelihood approach to joint modeling of longitudinal and time-to-event data. Biometrics, 58(4), 742–753. https://doi.org/10.1111/j.0006-341x.2002.00742.x
Song, Xiao, Marie Davidian, and Anastasios A. Tsiatis. “A semiparametric likelihood approach to joint modeling of longitudinal and time-to-event data.Biometrics 58, no. 4 (December 2002): 742–53. https://doi.org/10.1111/j.0006-341x.2002.00742.x.
Song X, Davidian M, Tsiatis AA. A semiparametric likelihood approach to joint modeling of longitudinal and time-to-event data. Biometrics. 2002 Dec;58(4):742–53.
Song, Xiao, et al. “A semiparametric likelihood approach to joint modeling of longitudinal and time-to-event data.Biometrics, vol. 58, no. 4, Dec. 2002, pp. 742–53. Pubmed, doi:10.1111/j.0006-341x.2002.00742.x.
Song X, Davidian M, Tsiatis AA. A semiparametric likelihood approach to joint modeling of longitudinal and time-to-event data. Biometrics. 2002 Dec;58(4):742–753.
Journal cover image

Published In

Biometrics

DOI

ISSN

0006-341X

Publication Date

December 2002

Volume

58

Issue

4

Start / End Page

742 / 753

Location

England

Related Subject Headings

  • Statistics & Probability
  • Randomized Controlled Trials as Topic
  • Proportional Hazards Models
  • Monte Carlo Method
  • Longitudinal Studies
  • Likelihood Functions
  • Humans
  • HIV Infections
  • Disease Progression
  • Computer Simulation