Pseudo-observations for competing risks with covariate dependent censoring
نویسندگان
چکیده
منابع مشابه
Pseudo-observations for competing risks with covariate dependent censoring.
Regression analysis for competing risks data can be based on generalized estimating equations. For the case with right censored data, pseudo-values were proposed to solve the estimating equations. In this article we investigate robustness of the pseudo-values against violation of the assumption that the probability of not being lost to follow-up (un-censored) is independent of the covariates. M...
متن کاملHeteroskedastic Transformation Models with Covariate Dependent Censoring
In this paper we propose an inferential procedure for transformation models with conditional heteroskedasticity in the error terms. The proposed method is robust to covariate dependent censoring of arbitrary form. We provide sufficient conditions for point identification. We then propose a consistent estimator and show that it is asymptoticaly √ n normal. We conduct a simulation study that reve...
متن کاملAnalysis of Progressive Censoring Competing Risks Data with Binomial Removals
In several studies in reliability and in medical science, the cause of failure/death of items or individuals may be attributable to more then one cause. In this paper, we will study the competing risks model when the data is progressively Type-II censored with random removals. We study the model under the assumption of independent causes of failure and exponential lifetimes, where the number of...
متن کاملMarginal Regression Analysis for Semi-Competing Risks Data Under Dependent Censoring
Multiple events data are commonly seen in medical applications. There are two types of events, namely terminal and non-terminal. Statistical analysis for non-terminal events is complicated due to dependent censoring. Consequently, joint modelling and inference are often needed to avoid the problem of non-identifiability. This article considers regression analysis for multiple events data with m...
متن کاملA note on including time-dependent covariate in regression model for competing risks data.
Recently, regression analysis of the cumulative incidence function has gained interest in competing risks data analysis, through the model proposed by Fine and Gray (JASA 1999; 94: 496-509). In this note, we point out that inclusion of time-dependent covariates in this model can lead to serious bias. We illustrate the problems arising in such a context, using bone marrow transplant data as a wo...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Lifetime Data Analysis
سال: 2013
ISSN: 1380-7870,1572-9249
DOI: 10.1007/s10985-013-9247-7