The heterogeneity statistic I2 can be biased in small meta-analyses

Dietary Fiber Intake and Total Mortality: A Meta-Analysis of Prospective Cohort Studies

(2014) Youngyo Kim et al.   AMERICAN JOURNAL OF EPIDEMIOLOGY

Coffee Consumption and Mortality From All Causes, Cardiovascular Disease, and Cancer: A Dose-Response Meta-Analysis

(2014) Alessio Crippa et al.   AMERICAN JOURNAL OF EPIDEMIOLOGY

Physical Activity and the Risk of Preeclampsia

(2014) Dagfinn Aune et al.   EPIDEMIOLOGY

Cumulative Meta-analysis of Job Strain and CHD

(2014) Mika Kivimäki et al.   EPIDEMIOLOGY

The effects of clinical and statistical heterogeneity on the predictive values of results from meta-analyses

(2013) W.G. Melsen et al.   CLINICAL MICROBIOLOGY AND INFECTION

Avoiding zero between-study variance estimates in random-effects meta-analysis

(2013) Yeojin Chung et al.   STATISTICS IN MEDICINE

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

(2012) Rebecca M Turner et al.   INTERNATIONAL JOURNAL OF EPIDEMIOLOGY

Characteristics of meta-analyses and their component studies in the Cochrane Database of Systematic Reviews: a cross-sectional, descriptive analysis

(2011) Jonathan Davey et al.   BMC Medical Research Methodology

Statins and All-Cause Mortality in High-Risk Primary Prevention

(2010) Kausik K. Ray   ARCHIVES OF INTERNAL MEDICINE

Undue reliance on I 2 in assessing heterogeneity may mislead

(2008) Gerta Rücker et al.   BMC Medical Research Methodology

A re-evaluation of random-effects meta-analysis

(2008) Julian P. T. Higgins et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES A-STATISTICS IN SOCIETY

The exact distribution of Cochran's heterogeneity statistic in one-way random effects meta-analysis

(2008) Brad J. Biggerstaff et al.   STATISTICS IN MEDICINE