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Using an Approximate Bayesian Bootstrap to Multiply Impute Nonignorable Missing Data

An Approximate Bayesian Bootstrap (ABB) offers advantages in incorporating appropriate uncertainty when imputing missing data, but most implementations of the ABB have lacked the ability to handle nonignorable missing data where the probability of missingness depends on unobserved values. This paper...

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Autors principals: Siddique, Juned, Belin, Thomas R.
Format: Artigo
Idioma:Inglês
Publicat: 2008
Matèries:
Accés en línia:https://ncbi.nlm.nih.gov/pmc/articles/PMC2678725/
https://ncbi.nlm.nih.gov/pubmed/20016665
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.csda.2008.07.042
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