Quantile regression analysis of length-biased survival data
نویسندگان
چکیده
منابع مشابه
Quantile Regression Analysis of Length-Biased Survival Data
Analysis of length-biased time-to-event data, which commonly arise in epidemiological cohort studies and cross-sectional surveys, has attracted considerable attention recently. Ignoring length-biased sampling often leads to severe bias in estimating the survival time in the general population. Existing work either completely ignore the covariate effects or use hazard or accelerated failure time...
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Length biased data occurs when a prevalent sampling is used to recruit subjects into a study that investigates the time from an initial event to a terminal event. Such data are usually left-truncated and right-censored. While there have been accurate and efficient methods to estimate the survival function, not much work has been done regarding the estimation of the residual life time distributi...
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Biased sampling occurs frequently in economics, epidemiology and medical studies either by design or due to data collecting mechanism. Failing to take into account the sampling bias usually leads to incorrect inference. We propose a unified estimation procedure and a computationally fast resampling method to make statistical inference for quantile regression with survival data under general bia...
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We show that relative mean survival parameters of a semiparametric log-linear model can be estimated using covariate data from an incident sample and a prevalent sample, even when there is no prospective follow-up to collect any survival data. Estimation is based on an induced semiparametric density ratio model for covariates from the two samples, and it shares the same structure as for a logis...
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In this paper we deduce a confidence bands construction for the nonparametric estimation of a regression curve from length biased data, where a result from Bickel and Rosenblatt (1973, The Annals of Statistics, 1, 1071-1095) is adapted to this new situation. The construction also involves the estimation of the variance of the local linear estimator of the regression, where we use a finite sampl...
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ژورنال
عنوان ژورنال: Stat
سال: 2014
ISSN: 2049-1573
DOI: 10.1002/sta4.42