Comparing conditional survival functions with missing population marks in a competing risks model
نویسندگان
چکیده
منابع مشابه
Parametric Estimation in a Recurrent Competing Risks Model
A resource-efficient approach to making inferences about the distributional properties of the failure times in a competing risks setting is presented. Efficiency is gained by observing recurrences of the compet- ing risks over a random monitoring period. The resulting model is called the recurrent competing risks model (RCRM) and is coupled with two repair strategies whenever the system fails. ...
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A new function for the competing risks model, the conditional cumulative hazard function, is introduced, from which the conditional distribution of failure times of individuals failing due to cause j can be studied. The standard Nelson-Aalen estimator is not appropriate in this setting, as population membership (mark) information may be missing for some individuals owing to random right-censori...
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Competing risks data usually arises in studies in which the failure of an individual may be classified into one of k (k > 1) mutually exclusive causes of failure. When competing risks are present, there are two main differences with classical survival analysis: (i) survival functions are not mainly used to describe cause-specific failures and, (ii) classical estimation techniques may provide bi...
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Rivest & Wells (2001) proposed estimators of the marginal survival functions in a right-censored model that assumes an Archimedean copula between the survival time and the censoring time. We study the extension of these estimators to the context of rightcensored semi-competing risks data with an independent second level censoring time. We intensively use martingale techniques to derive their la...
متن کاملMissing covariates in competing risks analysis
Studies often follow individuals until they fail from one of a number of competing failure types. One approach to analyzing such competing risks data involves modeling the cause-specific hazards as functions of baseline covariates. A common issue that arises in this context is missing values in covariates. In this setting, we first establish conditions under which complete case analysis (CCA) i...
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ژورنال
عنوان ژورنال: Computational Statistics & Data Analysis
سال: 2016
ISSN: 0167-9473
DOI: 10.1016/j.csda.2015.10.001