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Accounting for Informatively Missing Data in Logistic Regression by Means of Reassessment Sampling

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 th...

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Shranjeno v:
Bibliografske podrobnosti
izdano v:Stat Med
Main Authors: Lin, Ji, Lyles, Robert H.
Format: Artigo
Jezik:Inglês
Izdano: 2015
Teme:
Online dostop:https://ncbi.nlm.nih.gov/pmc/articles/PMC4469083/
https://ncbi.nlm.nih.gov/pubmed/25707010
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/sim.6456
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