Proportional hazards models with discrete frailty.

Lifetime Data Analysis
Chrys CaroniAlan Kimber

Abstract

We extend proportional hazards frailty models for lifetime data to allow a negative binomial, Poisson, Geometric or other discrete distribution of the frailty variable. This might represent, for example, the unknown number of flaws in an item under test. Zero frailty corresponds to a limited failure model containing a proportion of units that never fail (long-term survivors). Ways of modifying the model to avoid this are discussed. The models are illustrated on a previously published set of data on failures of printed circuit boards and on new data on breaking strengths of samples of cord.

References

Jul 26, 1988·Biochemistry·R D PressD A Goldthwait
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Sep 26, 1997·Statistics in Medicine·X Xue, R Brookmeyer
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Jul 12, 2008·Lifetime Data Analysis·C LegrandR Sylvester

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Citations

Jun 14, 2013·Lifetime Data Analysis·Sangbum ChoiYi-Hau Chen
Jun 29, 2017·Statistical Methods in Medical Research·Daiane de SouzaNarayanaswamy Balakrishnan
Dec 28, 2018·Biostatistics·Francesca GasperoniLinda Sharples
Feb 9, 2019·BMC Public Health·Yigzaw Alemu Limenih, Demeke Lakew Workie
Apr 11, 2019·Lifetime Data Analysis·Vicente G CanchoKatherine E C Zavaleta
Nov 28, 2020·Statistical Methods in Medical Research·Ali KaramoozianAbbas Bahrampour
May 7, 2021·Statistical Methods in Medical Research·Katy C MolinaEder A Milani

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