{"doi":"10.1016/j.jclinepi.2006.02.013","title":"Extreme between-study homogeneity in meta-analyses could offer useful insights","abstract":"<h4>Objectives</h4>Meta-analyses are routinely evaluated for the presence of large between-study heterogeneity. We examined whether it is also important to probe whether there is extreme between-study homogeneity.<h4>Study design</h4>We used heterogeneity tests with left-sided statistical significance for inference and developed a Monte Carlo simulation test for testing extreme homogeneity in risk ratios across studies, using the empiric distribution of the summary risk ratio and heterogeneity statistic. A left-sided P=0.01 threshold was set for claiming extreme homogeneity to minimize type I error.<h4>Results</h4>Among 11,803 meta-analyses with binary contrasts from the Cochrane Library, 143 (1.21%) had left-sided P-value <0.01 for the asymptotic Q statistic and 1,004 (8.50%) had left-sided P-value <0.10. The frequency of extreme between-study homogeneity did not depend on the number of studies in the meta-analyses. We identified examples where extreme between-study homogeneity (left-sided P-value <0.01) could result from various possibilities beyond chance. These included inappropriate statistical inference (asymptotic vs. Monte Carlo), use of a specific effect metric, correlated data or stratification using strong predictors of outcome, and biases and potential fraud.<h4>Conclusion</h4>Extreme between-study homogeneity may provide useful insights about a meta-analysis and its constituent studies.","journal":"Journal of Clinical Epidemiology","year":2006,"id":2143,"datarank":0.5641800173540344,"base_score":3.7612001156935624,"endowment":3.7612001156935624,"self_citation_contribution":0.5641800173540344,"citation_network_contribution":0.0,"self_endowment_contribution":0.5641800173540344,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":42,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.037,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2006-10-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":11861,"name":"Thomas A. Trikalinos","orcid":"0000-0002-3990-1848","position":1,"is_corresponding":false},{"id":1316,"name":"Elias Zintzaras","orcid":null,"position":2,"is_corresponding":false},{"id":148,"name":"John P. A. Ioannidis","orcid":"0000-0003-3118-6859","position":3,"is_corresponding":false}],"reference_count":48,"raw_metadata":null,"created_at":"2026-03-01T18:20:47.508186Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}