Meta-analysis of non-statistically significant unreported effects

Author:

Albajes-Eizagirre Anton12,Solanes Aleix123,Radua Joaquim12345ORCID

Affiliation:

1. FIDMAG Germanes Hospitalàries, Barcelona, Spain

2. Mental Health Research Networking Center (CIBERSAM), Madrid, Spain

3. Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain

4. Department of Clinical Neuroscience, Centre for Psychiatric Research and Education, Karolinska Institutet, Stockholm, Sweden

5. Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK

Abstract

Published studies in Medicine (and virtually any other discipline) sometimes report that a difference or correlation did not reach statistical significance but do not report its effect size or any statistic from which the latter may be derived. Unfortunately, meta-analysts should not exclude these studies because their exclusion would bias the meta-analytic outcome, but also they cannot be included as null effect sizes because this strategy is also associated to bias. To overcome this problem, we have developed MetaNSUE, a novel method based on multiple imputations of the censored information. We also provide an R package and an easy-to-use Graphical User Interface for non-R meta-analysts.

Funder

Instituto de Salud Carlos III

Publisher

SAGE Publications

Subject

Health Information Management,Statistics and Probability,Epidemiology

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