Common statistical errors in systematic reviews: A tutorial
The aim of this article is to present the most common statistical errors in meta‐analyses included in systematic reviews; these are confusing standard deviation and standard error, using heterogeneity estimators for choosing between a common‐effect and random‐effects model, improper handling of mult...
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| Vydáno v: | Cochrane evidence synthesis and methods Ročník 3; číslo 2; s. e70013 - n/a |
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| Hlavní autoři: | , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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England
John Wiley and Sons Inc
01.03.2025
Wiley |
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| ISSN: | 2832-9023, 2832-9023 |
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| Abstract | The aim of this article is to present the most common statistical errors in meta‐analyses included in systematic reviews; these are confusing standard deviation and standard error, using heterogeneity estimators for choosing between a common‐effect and random‐effects model, improper handling of multiarm trials, and unnecessary and misinterpreted subgroup analyses. We introduce some useful terminology and explain what authors can do to avoid these errors and how peer reviewers can spot them. We have also developed a micro‐learning module to provide practical hands‐on tutorial.
The aim of this article is to present the most common statistical errors in meta‐analyses included in systematic reviews; these are confusing standard deviation and standard error, using heterogeneity estimators for choosing between a common‐effect and random‐effects model, improper handling of multiarm trials, and unnecessary and misinterpreted subgroup analyses. We introduce some useful terminology and explain what authors can do to avoid these errors and how peer reviewers can spot them. We have also developed a micro‐learning module to provide practical hands‐on tutorial. Common Statistical Errors micro learning module |
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| AbstractList | Abstract The aim of this article is to present the most common statistical errors in meta‐analyses included in systematic reviews; these are confusing standard deviation and standard error, using heterogeneity estimators for choosing between a common‐effect and random‐effects model, improper handling of multiarm trials, and unnecessary and misinterpreted subgroup analyses. We introduce some useful terminology and explain what authors can do to avoid these errors and how peer reviewers can spot them. We have also developed a micro‐learning module to provide practical hands‐on tutorial. The aim of this article is to present the most common statistical errors in meta‐analyses included in systematic reviews; these are confusing standard deviation and standard error, using heterogeneity estimators for choosing between a common‐effect and random‐effects model, improper handling of multiarm trials, and unnecessary and misinterpreted subgroup analyses. We introduce some useful terminology and explain what authors can do to avoid these errors and how peer reviewers can spot them. We have also developed a micro‐learning module to provide practical hands‐on tutorial. The aim of this article is to present the most common statistical errors in meta‐analyses included in systematic reviews; these are confusing standard deviation and standard error, using heterogeneity estimators for choosing between a common‐effect and random‐effects model, improper handling of multiarm trials, and unnecessary and misinterpreted subgroup analyses. We introduce some useful terminology and explain what authors can do to avoid these errors and how peer reviewers can spot them. We have also developed a micro‐learning module to provide practical hands‐on tutorial. The aim of this article is to present the most common statistical errors in meta‐analyses included in systematic reviews; these are confusing standard deviation and standard error, using heterogeneity estimators for choosing between a common‐effect and random‐effects model, improper handling of multiarm trials, and unnecessary and misinterpreted subgroup analyses. We introduce some useful terminology and explain what authors can do to avoid these errors and how peer reviewers can spot them. We have also developed a micro‐learning module to provide practical hands‐on tutorial. Common Statistical Errors micro learning module The aim of this article is to present the most common statistical errors in meta-analyses included in systematic reviews; these are confusing standard deviation and standard error, using heterogeneity estimators for choosing between a common-effect and random-effects model, improper handling of multiarm trials, and unnecessary and misinterpreted subgroup analyses. We introduce some useful terminology and explain what authors can do to avoid these errors and how peer reviewers can spot them. We have also developed a micro-learning module to provide practical hands-on tutorial.The aim of this article is to present the most common statistical errors in meta-analyses included in systematic reviews; these are confusing standard deviation and standard error, using heterogeneity estimators for choosing between a common-effect and random-effects model, improper handling of multiarm trials, and unnecessary and misinterpreted subgroup analyses. We introduce some useful terminology and explain what authors can do to avoid these errors and how peer reviewers can spot them. We have also developed a micro-learning module to provide practical hands-on tutorial. The aim of this article is to present the most common statistical errors in meta‐analyses included in systematic reviews; these are confusing standard deviation and standard error, using heterogeneity estimators for choosing between a common‐effect and random‐effects model, improper handling of multiarm trials, and unnecessary and misinterpreted subgroup analyses. We introduce some useful terminology and explain what authors can do to avoid these errors and how peer reviewers can spot them. We have also developed a micro‐learning module to provide practical hands‐on tutorial. The aim of this article is to present the most common statistical errors in meta‐analyses included in systematic reviews; these are confusing standard deviation and standard error, using heterogeneity estimators for choosing between a common‐effect and random‐effects model, improper handling of multiarm trials, and unnecessary and misinterpreted subgroup analyses. We introduce some useful terminology and explain what authors can do to avoid these errors and how peer reviewers can spot them. We have also developed a micro‐learning module to provide practical hands‐on tutorial. Common Statistical Errors micro learning module |
| Author | Richardson, Rachel Kanellopoulou, Afroditi Dwan, Kerry |
| AuthorAffiliation | 2 Department of Hygiene and Epidemiology Faculty of Medicine University of Ioannina Ioannina Greece 1 Methods Support Unit, Evidence Production and Methods Directorate Cochrane London UK 3 Department of Clinical Sciences Liverpool School of Tropical Medicine Liverpool UK |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/40475918$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1136/bmj.327.7414.557 10.1371/journal.pone.0128804 10.1016/j.cegh.2018.05.005 10.1002/sim.1186 10.1002/cesm.12033 |
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