Multiplicity in systematic reviews and meta-analysis: Dealing with multiple source multiple outcomes
Loading...
Other Version
External File or Record
Can’t use the file because of accessibility barriers? Contact us
Date
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Indiana University Workshop in Methods
Permanent Link
Abstract
Publication and reporting bias are well-documented in the scientific literature. Increased data and code sharing, and access to other sources of information such as Clinical Study Reports (CSRs), address concerns about the non-reproducibility of individual studies. Ironically, greater transparency has given rise to new problems. That is, systematic reviewers and meta-analysts can choose from among dozens of effect sizes that could be included in their analyses. Initiatives that increase validity and reproducibility in individual studies also create opportunities for bias in research synthesis and clinical guideline development. Scientists could adopt new methods to avoid cherry-picking at all stages of research and evidence synthesis.
Series and Number:
EducationalLevel:
Is Based On:
Target Name:
Teaches:
Table of Contents
Description
Dr. Evan Mayo-Wilson is an Associate Professor in the Department of Epidemiology and Biostatistics at the Indiana University School of Public Health-Bloomington.
Keywords
Citation
Journal
DOI
Rights
This work may be protected by copyright unless otherwise stated.