Power family of transformation for Cox's regression with random effects

Kelvin K.W. Yau; C. A. McGilchrist

doi:10.1016/S0167-9473(98)00103-0

Power family of transformation for Cox's regression with random effects

Kelvin K.W. Yau, C. A. McGilchrist

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

3 Citations (Scopus)

Abstract

A random effect survival model with Box-Cox type relative risk function is proposed. It extends the model considered in McGilchrist (1993) by allowing the relative risk function to belong to a power family of transformations. This power family chooses the exponential relative risk function when the transformation parameter (k) tends to zero and the linear hazard when k equals one. Optimal value of k is obtained by maximizing an appropriate log-likelihood function. The proposed scheme is used to analyse two sets of multivariate failure time data. One data set confirms the choice of exponential relative risk function while the other concludes that the usual exponential specification is not optimal. © 1998 Elsevier Science B.V.

Original language	English
Pages (from-to)	57-66
Journal	Computational Statistics and Data Analysis
Volume	30
Issue number	1
DOIs	https://doi.org/10.1016/S0167-9473(98)00103-0
Publication status	Published - 28 Mar 1999

Research Keywords

Cox's regression model
General relative risk function
GLMM
Multivariate failure time data
Random effect

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title = "Power family of transformation for Cox's regression with random effects",

abstract = "A random effect survival model with Box-Cox type relative risk function is proposed. It extends the model considered in McGilchrist (1993) by allowing the relative risk function to belong to a power family of transformations. This power family chooses the exponential relative risk function when the transformation parameter (k) tends to zero and the linear hazard when k equals one. Optimal value of k is obtained by maximizing an appropriate log-likelihood function. The proposed scheme is used to analyse two sets of multivariate failure time data. One data set confirms the choice of exponential relative risk function while the other concludes that the usual exponential specification is not optimal. {\textcopyright} 1998 Elsevier Science B.V.",

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author = "Yau, {Kelvin K.W.} and McGilchrist, {C. A.}",

year = "1999",

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doi = "10.1016/S0167-9473(98)00103-0",

language = "English",

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TY - JOUR

T1 - Power family of transformation for Cox's regression with random effects

AU - Yau, Kelvin K.W.

AU - McGilchrist, C. A.

PY - 1999/3/28

Y1 - 1999/3/28

N2 - A random effect survival model with Box-Cox type relative risk function is proposed. It extends the model considered in McGilchrist (1993) by allowing the relative risk function to belong to a power family of transformations. This power family chooses the exponential relative risk function when the transformation parameter (k) tends to zero and the linear hazard when k equals one. Optimal value of k is obtained by maximizing an appropriate log-likelihood function. The proposed scheme is used to analyse two sets of multivariate failure time data. One data set confirms the choice of exponential relative risk function while the other concludes that the usual exponential specification is not optimal. © 1998 Elsevier Science B.V.

AB - A random effect survival model with Box-Cox type relative risk function is proposed. It extends the model considered in McGilchrist (1993) by allowing the relative risk function to belong to a power family of transformations. This power family chooses the exponential relative risk function when the transformation parameter (k) tends to zero and the linear hazard when k equals one. Optimal value of k is obtained by maximizing an appropriate log-likelihood function. The proposed scheme is used to analyse two sets of multivariate failure time data. One data set confirms the choice of exponential relative risk function while the other concludes that the usual exponential specification is not optimal. © 1998 Elsevier Science B.V.

KW - Cox's regression model

KW - General relative risk function

KW - GLMM

KW - Multivariate failure time data

KW - Random effect

UR - http://www.scopus.com/inward/record.url?scp=0040964907&partnerID=8YFLogxK

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-0040964907&origin=recordpage

U2 - 10.1016/S0167-9473(98)00103-0

DO - 10.1016/S0167-9473(98)00103-0

M3 - RGC 21 - Publication in refereed journal

SN - 0167-9473

VL - 30

SP - 57

EP - 66

JO - Computational Statistics and Data Analysis

JF - Computational Statistics and Data Analysis

IS - 1

ER -

Power family of transformation for Cox's regression with random effects

Abstract

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