Ignorability for categorical data

Manfred Jaeger

doi:10.1214/009053605000000363

Ignorability for categorical data

Manfred Jaeger

Institut for Datalogi

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

16 Citationer (Scopus)

Abstract

We study the problem of ignorability in likelihood-based inference from incomplete categorical data. Two versions of the coarsened at random assumption (car) are distinguished, their compatibility with the parameter distinctness assumption is investigated and several conditions for ignorability that do not require an extra parameter distinctness assumption are established.

Originalsprog	Engelsk
Tidsskrift	Annals of Statistics
Vol/bind	33
Udgave nummer	4
Sider (fra-til)	1964-1981
Antal sider	17
ISSN	0090-5364
DOI	https://doi.org/10.1214/009053605000000363
Status	Udgivet - aug. 2005

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10.1214/009053605000000363

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Citationsformater

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AB - We study the problem of ignorability in likelihood-based inference from incomplete categorical data. Two versions of the coarsened at random assumption (car) are distinguished, their compatibility with the parameter distinctness assumption is investigated and several conditions for ignorability that do not require an extra parameter distinctness assumption are established.

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DO - 10.1214/009053605000000363

M3 - Journal article

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JF - Annals of Statistics

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