Abstract:
:We explore the 'reassessment' design in a logistic regression setting, where a second wave of sampling is applied to recover a portion of the missing data on a binary exposure and/or outcome variable. We construct a joint likelihood function based on the original model of interest and a model for the missing data mechanism, with emphasis on non-ignorable missingness. The estimation is carried out by numerical maximization of the joint likelihood function with close approximation of the accompanying Hessian matrix, using sharable programs that take advantage of general optimization routines in standard software. We show how likelihood ratio tests can be used for model selection and how they facilitate direct hypothesis testing for whether missingness is at random. Examples and simulations are presented to demonstrate the performance of the proposed method.
journal_name
Stat Medjournal_title
Statistics in medicineauthors
Lin J,Lyles RHdoi
10.1002/sim.6456subject
Has Abstractpub_date
2015-05-20 00:00:00pages
1925-39issue
11eissn
0277-6715issn
1097-0258journal_volume
34pub_type
杂志文章abstract::Performance of a diagnostic test is ideally evaluated by a comparison of the test results to a gold standard for all the patients in a study. In practice, however, it is common for a subset of study patients to have the gold standard not verified (missing) due to ethical or expense considerations. Sensitivity and spec...
journal_title:Statistics in medicine
pub_type: 杂志文章
doi:10.1002/sim.3899
更新日期:2010-07-10 00:00:00
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journal_title:Statistics in medicine
pub_type: 杂志文章
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pub_type: 杂志文章
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journal_title:Statistics in medicine
pub_type: 杂志文章
doi:10.1002/sim.7823
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pub_type: 杂志文章
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pub_type: 杂志文章,评审
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更新日期:2004-01-15 00:00:00
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pub_type: 杂志文章
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pub_type: 杂志文章
doi:10.1002/sim.8173
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pub_type: 杂志文章
doi:10.1002/sim.1411
更新日期:2003-04-15 00:00:00
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journal_title:Statistics in medicine
pub_type: 杂志文章
doi:10.1002/sim.2656
更新日期:2007-05-10 00:00:00
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pub_type: 杂志文章
doi:10.1002/sim.4780080306
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pub_type: 杂志文章
doi:10.1002/sim.3589
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pub_type: 杂志文章
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pub_type: 临床试验,杂志文章,随机对照试验
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