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Estimations of the joint distribution of failure time and failure type with dependent truncation
Author(s) -
Cheng YuJen,
Wang MeiCheng,
Tsai ChangYu
Publication year - 2019
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.13017
Subject(s) - truncation (statistics) , joint probability distribution , joint (building) , computer science , statistics , event (particle physics) , data set , type (biology) , failure rate , type i and type ii errors , set (abstract data type) , mathematics , engineering , structural engineering , ecology , physics , quantum mechanics , biology , programming language
In biomedical studies involving survival data, the observation of failure times is sometimes accompanied by a variable which describes the type of failure event (Kalbeisch and Prentice, 2002). This paper considers two specific challenges which are encountered in the joint analysis of failure time and failure type. First, because the observation of failure times is subject to left truncation, the sampling bias extends to the failure type which is associated with the failure time. An analytical challenge is to deal with such sampling bias. Second, in case that the joint distribution of failure time and failure type is allowed to have a temporal trend, it is of interest to estimate the joint distribution of failure time and failure type nonparametrically. This paper develops statistical approaches to address these two analytical challenges on the basis of prevalent survival data. The proposed approaches are examined through simulation studies and illustrated by using a real data set.