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The beta‐binomial convolution model for 2×2 tables with missing cell counts
Author(s) -
Eisinga Rob
Publication year - 2009
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/j.1467-9574.2008.00404.x
Subject(s) - estimator , binomial (polynomial) , mathematics , convolution (computer science) , statistics , missing data , beta (programming language) , maximum likelihood , beta binomial distribution , multinomial distribution , binomial distribution , negative binomial distribution , computer science , artificial intelligence , artificial neural network , poisson distribution , programming language
This paper considers the beta‐binomial convolution model for the analysis of 2×2 tables with missing cell counts. We discuss maximum‐likelihood (ML) parameter estimation using the expectation–maximization algorithm and study information loss relative to complete data estimators. We also examine bias of the ML estimators of the beta‐binomial convolution. The results are illustrated by two example applications.