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http://hdl.handle.net/1942/12010
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DC Field | Value | Language |
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dc.contributor.author | MOLENBERGHS, Geert | - |
dc.contributor.author | VERBEKE, Geert | - |
dc.contributor.author | IDDI, Samuel | - |
dc.date.accessioned | 2011-06-23T06:59:45Z | - |
dc.date.available | NO_RESTRICTION | - |
dc.date.available | 2011-06-23T06:59:45Z | - |
dc.date.issued | 2011 | - |
dc.identifier.citation | STATISTICS & PROBABILITY LETTERS, 81 (7). p. 892-901 | - |
dc.identifier.issn | 0167-7152 | - |
dc.identifier.uri | http://hdl.handle.net/1942/12010 | - |
dc.description.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. | - |
dc.description.sponsorship | We acknowledge financial support from IAP research Network P6/03 of the Belgian Government (Belgian Science Policy). | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER SCIENCE BV | - |
dc.rights | © 2011 Elsevier B.V. All rights reserved. | - |
dc.subject.other | asymptotic relative efficiency; compound-symmetry; small-sample relative efficiency | - |
dc.subject.other | Asymptotic relative efficiency; Compound-symmetry; Small-sample relative efficiency | - |
dc.title | Pseudo-likelihood methodology for partitioned large and complex samples | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 901 | - |
dc.identifier.issue | 7 | - |
dc.identifier.spage | 892 | - |
dc.identifier.volume | 81 | - |
local.format.pages | 10 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | [Molenberghs, Geert; Verbeke, Geert] Univ Hasselt, Interuniv Inst Biostat & Stat Bioinformat, B-3590 Diepenbeek, Belgium. [Molenberghs, Geert; Verbeke, Geert; Iddi, Samuel] Katholieke Univ Leuven, Interuniv Inst Biostat & Stat Bioinformat, B-3000 Louvain, Belgium. | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.bibliographicCitation.oldjcat | A1 | - |
dc.identifier.doi | 10.1016/j.spl.2011.01.012 | - |
dc.identifier.isi | 000291175200024 | - |
item.validation | ecoom 2012 | - |
item.fulltext | With Fulltext | - |
item.fullcitation | MOLENBERGHS, Geert; VERBEKE, Geert & IDDI, Samuel (2011) Pseudo-likelihood methodology for partitioned large and complex samples. In: STATISTICS & PROBABILITY LETTERS, 81 (7). p. 892-901. | - |
item.accessRights | Restricted Access | - |
item.contributor | MOLENBERGHS, Geert | - |
item.contributor | VERBEKE, Geert | - |
item.contributor | IDDI, Samuel | - |
crisitem.journal.issn | 0167-7152 | - |
crisitem.journal.eissn | 1879-2103 | - |
Appears in Collections: | Research publications |
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File | Description | Size | Format | |
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verbeke 1.pdf Restricted Access | Published version | 253.29 kB | Adobe PDF | View/Open Request a copy |
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