A random effects model for multivariate failure time data from multicenter clinical trials

Biometrics
Jianwen CaiH Zhou

Abstract

A random effects model for analyzing multivariate failure time data is proposed. The work is motivated by the need for assessing the mean treatment effect in a multicenter clinical trial study, assuming that the centers are a random sample from an underlying population. An estimating equation for the mean hazard ratio parameter is proposed. The proposed estimator is shown to be consistent and asymptotically normally distributed. A variance estimator, based on large sample theory, is proposed. Simulation results indicate that the proposed estimator performs well in finite samples. The proposed variance estimator effectively corrects the bias of the naive variance estimator, which assumes independence of individuals within a group. The methodology is illustrated with a clinical trial data set from the Studies of Left Ventricular Dysfunction. This shows that the variability of the treatment effect is higher than found by means of simpler models.

References

Aug 1, 1991·The New England Journal of Medicine·UNKNOWN SOLVD InvestigatorsJay N Cohn
Apr 1, 1983·Journal of Clinical Oncology : Official Journal of the American Society of Clinical Oncology·B FisherJ Wittliff
Feb 1, 1983·European Journal of Cancer & Clinical Oncology·C SchmoeckelO Braun-Falco

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Citations

Sep 22, 2007·Contemporary Clinical Trials·Sandrine KatsahianRaphaël Porcher
Aug 27, 2019·Statistical Methods in Medical Research·Di ShuSengwee Toh
Jan 30, 2004·Statistics in Medicine·David V Glidden, Eric Vittinghoff

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