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A comparison of frailty models for multivariate survival data.

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A comparison of frailty models for multivariate survival data. / Pickles, Andrew R.; Crouchley, Rob.
In: Statistics in Medicine, Vol. 14, No. 13, 15.07.1995, p. 1447-1461.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Pickles, AR & Crouchley, R 1995, 'A comparison of frailty models for multivariate survival data.', Statistics in Medicine, vol. 14, no. 13, pp. 1447-1461. https://doi.org/10.1002/sim.4780141305

APA

Pickles, A. R., & Crouchley, R. (1995). A comparison of frailty models for multivariate survival data. Statistics in Medicine, 14(13), 1447-1461. https://doi.org/10.1002/sim.4780141305

Vancouver

Pickles AR, Crouchley R. A comparison of frailty models for multivariate survival data. Statistics in Medicine. 1995 Jul 15;14(13):1447-1461. doi: 10.1002/sim.4780141305

Author

Pickles, Andrew R. ; Crouchley, Rob. / A comparison of frailty models for multivariate survival data. In: Statistics in Medicine. 1995 ; Vol. 14, No. 13. pp. 1447-1461.

Bibtex

@article{338857c07cb54abb9da63c4dceaa69d2,
title = "A comparison of frailty models for multivariate survival data.",
abstract = "This paper reviews some of the main approaches to the analysis of multivariate censored survival data. Such data typically have correlated failure times. The correlation can be a consequence of the observational design, for example with clustered sampling and matching, or it can be a focus of interest as in genetic studies, longitudinal studies of recurrent events and other studies involving multiple measurements. We assume that the correlation between the failure or survival times can be accounted for by fixed or random frailty effects. We then compare the performance of conditional and mixture likelihood approaches to estimating models with these frailty effects in censored bivariate survival data. We find that the mixture methods are surprisingly robust to misspecification of the frailty distribution. The paper also contains an illustrative example on the times to onset of chest pain brought on by three endurance exercise tests during a drug treatment trial of heart patients.",
author = "Pickles, {Andrew R.} and Rob Crouchley",
year = "1995",
month = jul,
day = "15",
doi = "10.1002/sim.4780141305",
language = "English",
volume = "14",
pages = "1447--1461",
journal = "Statistics in Medicine",
issn = "1097-0258",
publisher = "John Wiley and Sons Ltd",
number = "13",

}

RIS

TY - JOUR

T1 - A comparison of frailty models for multivariate survival data.

AU - Pickles, Andrew R.

AU - Crouchley, Rob

PY - 1995/7/15

Y1 - 1995/7/15

N2 - This paper reviews some of the main approaches to the analysis of multivariate censored survival data. Such data typically have correlated failure times. The correlation can be a consequence of the observational design, for example with clustered sampling and matching, or it can be a focus of interest as in genetic studies, longitudinal studies of recurrent events and other studies involving multiple measurements. We assume that the correlation between the failure or survival times can be accounted for by fixed or random frailty effects. We then compare the performance of conditional and mixture likelihood approaches to estimating models with these frailty effects in censored bivariate survival data. We find that the mixture methods are surprisingly robust to misspecification of the frailty distribution. The paper also contains an illustrative example on the times to onset of chest pain brought on by three endurance exercise tests during a drug treatment trial of heart patients.

AB - This paper reviews some of the main approaches to the analysis of multivariate censored survival data. Such data typically have correlated failure times. The correlation can be a consequence of the observational design, for example with clustered sampling and matching, or it can be a focus of interest as in genetic studies, longitudinal studies of recurrent events and other studies involving multiple measurements. We assume that the correlation between the failure or survival times can be accounted for by fixed or random frailty effects. We then compare the performance of conditional and mixture likelihood approaches to estimating models with these frailty effects in censored bivariate survival data. We find that the mixture methods are surprisingly robust to misspecification of the frailty distribution. The paper also contains an illustrative example on the times to onset of chest pain brought on by three endurance exercise tests during a drug treatment trial of heart patients.

U2 - 10.1002/sim.4780141305

DO - 10.1002/sim.4780141305

M3 - Journal article

VL - 14

SP - 1447

EP - 1461

JO - Statistics in Medicine

JF - Statistics in Medicine

SN - 1097-0258

IS - 13

ER -