Contribution to the discussion of “When should meta-analysis avoid making hidden normality assumptions?” Using general-purpose GLMM software for meta-analysis

Hans Peter Piepho; Laurence V. Madden; Emlyn R. Williams

doi:10.1002/bimj.201800096

Contribution to the discussion of “When should meta-analysis avoid making hidden normality assumptions?” Using general-purpose GLMM software for meta-analysis

Hans Peter Piepho^*, Laurence V. Madden, Emlyn R. Williams

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	1059-1061
Number of pages	3
Journal	Biometrical Journal
Volume	60
Issue number	6
DOIs	https://doi.org/10.1002/bimj.201800096
Publication status	Published - Nov 2018

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10.1002/bimj.201800096

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title = "Contribution to the discussion of “When should meta-analysis avoid making hidden normality assumptions?” Using general-purpose GLMM software for meta-analysis",

keywords = "Kenward–Roger method, best linear unbiased prediction, hierarchical likelihood, restricted maximum likelihood, restricted pseudo-likelihood",

author = "Piepho, {Hans Peter} and Madden, {Laurence V.} and Williams, {Emlyn R.}",

year = "2018",

month = nov,

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pages = "1059--1061",

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T1 - Contribution to the discussion of “When should meta-analysis avoid making hidden normality assumptions?” Using general-purpose GLMM software for meta-analysis

AU - Piepho, Hans Peter

AU - Madden, Laurence V.

AU - Williams, Emlyn R.

PY - 2018/11

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KW - Kenward–Roger method

KW - best linear unbiased prediction

KW - hierarchical likelihood

KW - restricted maximum likelihood

KW - restricted pseudo-likelihood

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DO - 10.1002/bimj.201800096

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EP - 1061

JO - Biometrical Journal

JF - Biometrical Journal

IS - 6

ER -

Contribution to the discussion of “When should meta-analysis avoid making hidden normality assumptions?” Using general-purpose GLMM software for meta-analysis

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