{"doi":"10.1371/journal.pone.0252415","title":"Neglect of publication bias compromises meta-analyses of educational research","abstract":"<jats:p>Because negative findings have less chance of getting published, available studies tend to be a biased sample. This leads to an inflation of effect size estimates to an unknown degree. To see how meta-analyses in education account for publication bias, we surveyed all meta-analyses published in the last five years in the Review of Educational Research and Educational Research Review. The results show that meta-analyses usually neglect publication bias adjustment. In the minority of meta-analyses adjusting for bias, mostly non-principled adjustment methods were used, and only rarely were the conclusions based on corrected estimates, rendering the adjustment inconsequential. It is argued that appropriate state-of-the-art adjustment (e.g., selection models) should be attempted by default, yet one needs to take into account the uncertainty inherent in any meta-analytic inference under bias. We conclude by providing practical recommendations on dealing with publication bias.</jats:p>","journal":"PLOS ONE","year":2021,"id":612386,"datarank":0.6038027536102726,"base_score":4.02535169073515,"endowment":4.02535169073515,"self_citation_contribution":0.6038027536102726,"citation_network_contribution":0.0,"self_endowment_contribution":0.6038027536102726,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":55,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":550394,"name":"Matúš Adamkovič","orcid":"0000-0002-9648-9108","position":1,"is_corresponding":false},{"id":1576740,"name":"David Greger","orcid":"0000-0002-1615-0404","position":2,"is_corresponding":false},{"id":550411,"name":"Ivan Ropovik","orcid":"0000-0001-5222-1233","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Neglect of publication bias compromises meta-analyses of educational research","abstract":"<jats:p>Because negative findings have less chance of getting published, available studies tend to be a biased sample. This leads to an inflation of effect size estimates to an unknown degree. To see how meta-analyses in education account for publication bias, we surveyed all meta-analyses published in the last five years in the Review of Educational Research and Educational Research Review. The results show that meta-analyses usually neglect publication bias adjustment. In the minority of meta-analyses adjusting for bias, mostly non-principled adjustment methods were used, and only rarely were the conclusions based on corrected estimates, rendering the adjustment inconsequential. It is argued that appropriate state-of-the-art adjustment (e.g., selection models) should be attempted by default, yet one needs to take into account the uncertainty inherent in any meta-analytic inference under bias. 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