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Updating meta-analyses leads to larger type I errors than publication bias · Study

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ArticleUpdating meta-analyses leads to larger type I errors than publication bias

George F. Borm2009

Article2009

Updating meta-analyses leads to larger type I errors than publication bias

George F. Borm · A. Rogier T. Donders

103 citations·0/0 files stored·Journal of Clinical Epidemiology

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Meta-analysis and systematic reviews Statistical Methods in Clinical Trials Statistical Methods in Epidemiology

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References

2003Measuring inconsistency in meta-analyses 1986Meta-analysis in clinical trials 2007Trial sequential analysis may establish when firm evidence is reached in cumulative meta-analysis 2005Contradicted and Initially Stronger Effects in Highly Cited Clinical Research 2000Publication bias in meta-analysis its causes and consequences 1997Discrepancies between Meta-Analyses and Subsequent Large Randomized, Controlled Trials 2008Trial sequential analysis reveals insufficient information size and potentially false positive results in many meta-analyses 1997Publication bias: evidence of delayed publication in a cohort study of clinical research projects

Cited by

2015Acceptance and commitment therapy – Do we know enough? Cumulative and sequential meta-analyses of randomized controlled trials 2019Trial sequential analysis: adding a new dimension to meta‐analysis 2012Obtaining evidence by a single well-powered trial or several modestly powered trials 2013Trial sequential methods for meta‐analysis 2021Living Systematic Reviews

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Details

Year2009

Typearticle

Published2009-01-11

VenueJournal of Clinical Epidemiology

ISSN-L0895-4356

Languageen

Citations103

Files0 public / 0

ShelfMeta-analysis and systematic reviews

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doi10.1016/j.jclinepi.2008.08.010

openalex_workW2012793344

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2018Increased risks for random errors are common in outcomes graded as high certainty of evidence

2020Using Trial Sequential Analysis for estimating the sample sizes of further trials: example using smoking cessation intervention

2016Can systematic reviews with sparse data be trusted?