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A non-parametric maximum likelihood estimator for bivariate interval censored data

✍ Scribed by Rebecca A. Betensky; Dianne M. Finkelstein


Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
106 KB
Volume
18
Category
Article
ISSN
0277-6715

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✦ Synopsis


We derive a non-parametric maximum likelihood estimator for bivariate interval censored data using standard techniques for constrained convex optimization. Our approach extends those taken for univariate interval censored data. We illustrate the estimator with bivariate data from an AIDS study.


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✍ Ross L. Prentice πŸ“‚ Article πŸ“… 1999 πŸ› John Wiley and Sons 🌐 English βš– 171 KB πŸ‘ 1 views

The likelihood function for the bivariate survivor function F, under independent censorship, is maximized to obtain a non-parametric maximum likelihood estimator F K . F K may or may not be unique depending on the con"guration of singly-and doubly-censored pairs. The likelihood function can be maxim