Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews

Rebecca M Turner; Jonathan Davey; Mike J Clarke; Simon G Thompson; Julian Pt Higgins

doi:10.1093/ije/dys041

Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews

Rebecca M Turner, Jonathan Davey, Mike J Clarke, Simon G Thompson, Julian Pt Higgins

Research output: Contribution to journal › Article (Academic Journal) › peer-review

491 Citations (Scopus)

Abstract

Many meta-analyses contain only a small number of studies, which makes it difficult to estimate the extent of between-study heterogeneity. Bayesian meta-analysis allows incorporation of external evidence on heterogeneity, and offers advantages over conventional random-effects meta-analysis. To assist in this, we provide empirical evidence on the likely extent of heterogeneity in particular areas of health care.

Original language	English
Pages (from-to)	818-27
Number of pages	10
Journal	International Journal of Epidemiology
Volume	41
Issue number	3
DOIs	https://doi.org/10.1093/ije/dys041
Publication status	Published - 2012

Access to Document

10.1093/ije/dys041

Handle.net

Persistent link

Cite this

@article{333eb2cab3c04fa3bc8afe43432cd42e,

title = "Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews",

abstract = "Many meta-analyses contain only a small number of studies, which makes it difficult to estimate the extent of between-study heterogeneity. Bayesian meta-analysis allows incorporation of external evidence on heterogeneity, and offers advantages over conventional random-effects meta-analysis. To assist in this, we provide empirical evidence on the likely extent of heterogeneity in particular areas of health care.",

author = "Turner, {Rebecca M} and Jonathan Davey and Clarke, {Mike J} and Thompson, {Simon G} and Higgins, {Julian Pt}",

year = "2012",

doi = "10.1093/ije/dys041",

language = "English",

volume = "41",

pages = "818--27",

journal = "International Journal of Epidemiology",

issn = "0300-5771",

publisher = "Oxford University Press",

number = "3",

}

TY - JOUR

T1 - Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews

AU - Turner, Rebecca M

AU - Davey, Jonathan

AU - Clarke, Mike J

AU - Thompson, Simon G

AU - Higgins, Julian Pt

PY - 2012

Y1 - 2012

N2 - Many meta-analyses contain only a small number of studies, which makes it difficult to estimate the extent of between-study heterogeneity. Bayesian meta-analysis allows incorporation of external evidence on heterogeneity, and offers advantages over conventional random-effects meta-analysis. To assist in this, we provide empirical evidence on the likely extent of heterogeneity in particular areas of health care.

AB - Many meta-analyses contain only a small number of studies, which makes it difficult to estimate the extent of between-study heterogeneity. Bayesian meta-analysis allows incorporation of external evidence on heterogeneity, and offers advantages over conventional random-effects meta-analysis. To assist in this, we provide empirical evidence on the likely extent of heterogeneity in particular areas of health care.

U2 - 10.1093/ije/dys041

DO - 10.1093/ije/dys041

M3 - Article (Academic Journal)

C2 - 22461129

VL - 41

SP - 818

EP - 827

JO - International Journal of Epidemiology

JF - International Journal of Epidemiology

SN - 0300-5771

IS - 3

ER -

Predicting the extent of heterogeneity in meta-analysis, using empirical data from the Cochrane Database of Systematic Reviews

Abstract

Access to Document

Handle.net

Fingerprint

Cite this