نتایج جستجو برای: additive hazards model
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Introduction: Colorectal cancer (CRC) is a commonly fatal cancer that ranks as third worldwide and third and the fifth in Iranian women and men, respectively. There are several methods for analyzing time to event data. Additive hazards regression models take priority over the popular Cox proportional hazards model if the absolute hazard (risk) change instead of hazard ratio is of primary concer...
There are several statistical methods for time-to-event analysis, among which is the Cox proportional hazards model that is most commonly used. However, when the absolute change in risk, instead of the risk ratio, is of primary interest or when the proportional hazard assumption for the Cox proportional hazards model is violated, an additive hazard regression model may be more appropriate. In t...
Competing risk failure time data occur frequently in medical studies, and a number of methods have been proposed for the analysis of these data. To assess covariate effects, a standard approach is to model the cause-specific hazard functions of different failure types. Recently, Fine and Gray (1999) proposed directly modeling the subdistribution of a competing risk with a Cox type model. In thi...
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Marginal additive hazards models are considered for multivariate survival data in which individuals may experience events of several types and there may also be correlation between individuals. Estimators are proposed for the parameters of such models and for the baseline hazard functions. The estimators of the regression coefficients are shown asymptotically to follow a multivariate normal dis...
Abstract The paper considers smooth modelling of hazard functions, where dynamics is modelled in both, duration time and calendar time. The model is specified with time dynamic covariate effects to replace restrictive assumptions of proportional hazards. Additivity of the time effects is assumed which allows for simple estimation in a backfitting style. Penalized splines are employed, which pro...
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