Literature DB >> 20717497

NONPARAMETRIC ESTIMATION OF CONDITIONAL CUMULATIVE HAZARDS FOR MISSING POPULATION MARKS.

Dipankar Bandyopadhyay1, Amalia Jácome Pumar.   

Abstract

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-censoring. We propose the use of imputed population marks for the censored individuals through fractional risk sets. Some asymptotic properties, including uniform strong consistency, are established. We study the practical performance of this estimator through simulation studies and apply it to a real data set for illustration.

Entities:  

Year:  2010        PMID: 20717497      PMCID: PMC2921901          DOI: 10.1111/j.1467-842X.2009.00567.x

Source DB:  PubMed          Journal:  Aust N Z J Stat        ISSN: 1369-1473            Impact factor:   0.640


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4.  The choice of treatment for cancer patients based on covariate information.

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  1 in total

1.  Comparing conditional survival functions with missing population marks in a competing risks model.

Authors:  Dipankar Bandyopadhyay; M Amalia Jácome
Journal:  Comput Stat Data Anal       Date:  2016-03-01       Impact factor: 1.681

  1 in total

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