Literature DB >> 26096892

We know less than we should about methods of meta-analysis.

David C Hoaglin1,2.   

Abstract

Keywords:  Q statistic; heterogeneity; inverse-variance weights; random-effects model; software

Mesh：

Year:  2015        PMID： 26096892     DOI： 10.1002/jrsm.1146

Source DB:  PubMed          Journal:  Res Synth Methods        ISSN： 1759-2879            Impact factor:   5.273


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  7 in total

1.  Graphical augmentations to sample-size-based funnel plot in meta-analysis.

Authors:  Lifeng Lin
Journal:  Res Synth Methods       Date:  2019-02-07       Impact factor: 5.273

2.  Meta-analytic approaches for examining complexity and heterogeneity in studies of adolescent development.

Authors:  Nicholas J Parr; Maria L Schweer-Collins; Todd M Darlington; Emily E Tanner-Smith
Journal:  J Adolesc       Date:  2019-11-15

3.  Evaluation of various estimators for standardized mean difference in meta-analysis.

Authors:  Lifeng Lin; Ariel M Aloe
Journal:  Stat Med       Date:  2020-11-12       Impact factor: 2.373

4.  The statistical importance of a study for a network meta-analysis estimate.

Authors:  Gerta Rücker; Adriani Nikolakopoulou; Theodoros Papakonstantinou; Georgia Salanti; Richard D Riley; Guido Schwarzer
Journal:  BMC Med Res Methodol       Date:  2020-07-14       Impact factor: 4.615

Review 5.  When should meta-analysis avoid making hidden normality assumptions?

Authors:  Dan Jackson; Ian R White
Journal:  Biom J       Date:  2018-07-30       Impact factor: 2.207

6.  Sensitivity and identification quantification by a relative latent model complexity perturbation in Bayesian meta-analysis.

Authors:  Małgorzata Roos; Sona Hunanyan; Haakon Bakka; Håvard Rue
Journal:  Biom J       Date:  2021-08-10       Impact factor: 1.715

7.  New models for describing outliers in meta-analysis.

Authors:  Rose Baker; Dan Jackson
Journal:  Res Synth Methods       Date:  2015-11-27       Impact factor: 5.273
  7 in total

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