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Additive gamma frailty models with applications to competing risks in related individuals
Author(s) -
Eriksson Frank,
Scheike Thomas
Publication year - 2015
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.12326
Subject(s) - estimator , truncation (statistics) , inference , event (particle physics) , econometrics , statistics , class (philosophy) , sample (material) , cluster (spacecraft) , computer science , mathematics , artificial intelligence , physics , chemistry , chromatography , programming language , quantum mechanics
Summary Epidemiological studies of related individuals are often complicated by the fact that follow‐up on the event type of interest is incomplete due to the occurrence of other events. We suggest a class of frailty models with cause‐specific hazards for correlated competing events in related individuals. The frailties are based on sums of gamma distributed variables and offer closed form expressions for the observed intensities. An inference procedure with a recursive baseline estimator is proposed, and its large sample properties are established. The estimator readily handles cluster left‐truncation as occurring in the Nordic twin registers. The performance in finite samples is investigated by simulations and an example on prostate cancer in twins is provided for illustration.