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Title: Pseudo-likelihood methodology for partitioned large and complex samples
Authors: Molenberghs, Geert ×
Verbeke, Geert
Iddi, Samuel #
Issue Date: Jul-2011
Publisher: North-Holland Pub. Co.
Series Title: Statistics & Probability Letters vol:81 issue:7 pages:892-901
Abstract: Large data sets, either coming from a large number of independent replications, or because of hierarchies in the data with large numbers of within-unit replication, may pose challenges to the data analyst up to the point of making conventional inferential methods, such as maximum likelihood, prohibitive. Based on general pseudo-likelihood concepts, we propose a method to partition such a set of data, analyze each partition member, and properly combine the inferences into a single one. It is shown that the method is fully efficient for independent partitions, while with dependent sub-samples efficiency is sometimes but not always equal to one. It is argued that, for important realistic settings, efficiency is often very high. Illustrative examples enhance insight in the method's operation, while real-data analysis underscores its power for practice. (C) 2011 Elsevier B.V. All rights reserved.
URI: 
ISSN: 0167-7152
Publication status: published
KU Leuven publication type: IT
Appears in Collections:Leuven Biostatistics and Statistical Bioinformatics Centre (L-BioStat)
× corresponding author
# (joint) last author

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