WEIGHTED LEAST-SQUARES ESTIMATION FOR AALEN ADDITIVE RISK MODEL

被引:109
作者
HUFFER, FW
MCKEAGUE, IW
机构
关键词
ATOMIC BOMB SURVIVORS; GROUPED SURVIVAL DATA; MARTINGALE METHODS; MONTECARLO; MULTIVARIATE COUNTING PROCESSES; NONPROPORTIONAL HAZARDS;
D O I
10.2307/2289721
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Cox's proportional hazards model has so far been the most popular model for the regression analysis of censored survival data. However, the additive risk model of Aalen can provide a useful and biologically more plausible alternative. Aalen's model stipulates that the conditional hazard function for a subject, whose covariates are Y = (Y1,..., Y(p))', has the form h(t/Y) = Y'alpha-(t), where alpha = (alpha-1, ..., alpha-p)' is an unknown vector of hazard functions. This article discusses inference for alpha based on a weighted least squares (WLS) estimator of the vector of cumulative hazard functions. The asymptotic distribution of the WLS estimator is derived and used to obtain confidence intervals and bands for the cumulative hazard functions. Both a grouped data and a continuous data version of the estimator are examined. An extensive simulation study is carried out. The method is applied to grouped data on the incidence of cancer mortality among Japanese atomic bomb survivors.
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页码:114 / 129
页数:16
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