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How to interpret meta-analysis models: fixed effect and random effects meta-analyses
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  1. Adriani Nikolakopoulou1,
  2. Dimitris Mavridis1,2,
  3. Georgia Salanti1
  1. 1Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece;
  2. 2Department of Primary Education, University of Ioannina, Ioannina, Greece
  1. Correspondence to Dr Dimitris Mavridis, Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, 45110, Greece; dmavridi{at}cc.uoi.gr

Abstract

This section of the journal is aimed at providing the essential information readers should know about the topics that are addressed in the ‘Statistics in practice’ paper published in the same issue of the journal. This stand-alone section has to be seen as an articulated summary of the main notions clinicians have to know about some basic concepts in statistics, which may be useful for their evidence-based practice. After going through these notes, readers are encouraged to read the ‘Statistics in practice’ articles. Of course, we welcome any feedback from you (via email or Twitter) about this!

The EBMH Editors

Relative treatment effects studied in trials are typically measured using an effect size. The observed effect sizes are synthesised to obtain a summary treatment effect via meta-analysis.

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