Lifetime Data Anal - Events per variable for risk differences and relative risks using pseudo-observations.

Tópicos

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Resumo

A method based on pseudo-observations has been proposed for direct regression modeling of functionals of interest with right-censored data, including the survival function, the restricted mean and the cumulative incidence function in competing risks. The models, once the pseudo-observations have been computed, can be fitted using standard generalized estimating equation software. Regression models can however yield problematic results if the number of covariates is large in relation to the number of events observed. Guidelines of events per variable are often used in practice. These rules of thumb for the number of events per variable have primarily been established based on simulation studies for the logistic regression model and Cox regression model. In this paper we conduct a simulation study to examine the small sample behavior of the pseudo-observation method to estimate risk differences and relative risks for right-censored data. We investigate how coverage probabilities and relative bias of the pseudo-observation estimator interact with sample size, number of variables and average number of events per variable.

Resumo Limpo

method base pseudoobserv propos direct regress model function interest rightcensor data includ surviv function restrict mean cumul incid function compet risk model pseudoobserv comput can fit use standard general estim equat softwar regress model can howev yield problemat result number covari larg relat number event observ guidelin event per variabl often use practic rule thumb number event per variabl primarili establish base simul studi logist regress model cox regress model paper conduct simul studi examin small sampl behavior pseudoobserv method estim risk differ relat risk rightcensor data investig coverag probabl relat bias pseudoobserv estim interact sampl size number variabl averag number event per variabl

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