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http://hdl.handle.net/1942/30008
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DC Field | Value | Language |
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dc.contributor.author | FLOREZ POVEDA, Alvaro | - |
dc.contributor.author | MOLENBERGHS, Geert | - |
dc.contributor.author | VERBEKE, Geert | - |
dc.contributor.author | Abad, Ariel Alonso | - |
dc.date.accessioned | 2019-11-18T13:12:23Z | - |
dc.date.available | 2019-11-18T13:12:23Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 29(2), p. 318-332 | - |
dc.identifier.issn | 1054-3406 | - |
dc.identifier.uri | http://hdl.handle.net/1942/30008 | - |
dc.description.abstract | Estimating complex linear mixed models using an iterative full maximum likelihood estimator can be cumbersome in some cases. With small and unbalanced datasets, convergence problems are common. Also, for large datasets, iterative procedures can be computationally prohibitive. To overcome these computational issues, an unbiased two-stage closed-form estimator for the multivariate linear mixed model is proposed. It is rooted in pseudo-likelihood-based split-sample methodology and useful, for example, when evaluating normally distributed endpoints in a meta-analytic context. However, applications go well beyond this framework. Its statistical and computational performance is assessed via simulation. The method is applied to a study in schizophrenia. | - |
dc.description.sponsorship | This work was supported by the IAP research network #P7=6 of the Belgian Government and by European Seventh Framework program FP7 2007-2013: [grant number 602552]. Financial support from the IAP research network #P7 = 6 of the Belgian Government (Belgian Science Policy) is gratefully acknowledged. Alvaro J. Flórez acknowledges funding from the European Seventh Framework program FP7 2007–2013: [grant agreement no. 602552 | - |
dc.language.iso | en | - |
dc.publisher | TAYLOR & FRANCIS INC | - |
dc.rights | 2018 Taylor & Francis Group, LLC | - |
dc.subject.other | Hierarchical data; linear mixed model; unequal cluster size; surrogacy evaluation; weighting | - |
dc.subject.other | Hierarchical data; linear mixed model; unequal cluster size; surrogacy evaluation; weighting | - |
dc.title | A closed-form estimator for meta-analysis and surrogate markers evaluation | - |
dc.type | Journal Contribution | - |
dc.identifier.epage | 332 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 318 | - |
dc.identifier.volume | 29 | - |
local.format.pages | 15 | - |
local.bibliographicCitation.jcat | A1 | - |
dc.description.notes | [Florez, Alvaro J.; Molenberghs, Geert; Verbeke, Geert] Univ Hasselt, I BioStat, Diepenbeek, Belgium. [Molenberghs, Geert; Verbeke, Geert; Abad, Ariel Alonso] Katholieke Univ Leuven, I BioStat, Leuven, Belgium. | - |
local.publisher.place | PHILADELPHIA | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1080/10543406.2018.1535504 | - |
dc.identifier.isi | 000458877800006 | - |
item.fulltext | With Fulltext | - |
item.fullcitation | FLOREZ POVEDA, Alvaro; MOLENBERGHS, Geert; VERBEKE, Geert & Abad, Ariel Alonso (2019) A closed-form estimator for meta-analysis and surrogate markers evaluation. In: JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 29(2), p. 318-332. | - |
item.accessRights | Open Access | - |
item.validation | ecoom 2020 | - |
item.contributor | FLOREZ POVEDA, Alvaro | - |
item.contributor | MOLENBERGHS, Geert | - |
item.contributor | VERBEKE, Geert | - |
item.contributor | Abad, Ariel Alonso | - |
crisitem.journal.issn | 1054-3406 | - |
crisitem.journal.eissn | 1520-5711 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
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10.1080@10543406.2018.1535504.pdf Restricted Access | Published version | 1.49 MB | Adobe PDF | View/Open Request a copy |
JBSpaper.pdf | Peer-reviewed author version | 351.12 kB | Adobe PDF | View/Open |
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