Quasi-experimental study designs series—paper 6: risk of bias assessment

Hugh Waddington; Ariel M Aloe; Betsy Jane Becker; Eric W Djimeu; Jorge Garcia Hombrados; Peter Tugwell; George Wells; Barney Reeves

doi:10.1016/j.jclinepi.2017.02.015

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Quasi-experimental study designs series—paper 6: risk of bias assessment

Journal article

Peer reviewed

Quasi-experimental study designs series—paper 6: risk of bias assessment

Hugh Waddington, Ariel M Aloe, Betsy Jane Becker, Eric W Djimeu, Jorge Garcia Hombrados, Peter Tugwell, George Wells and Barney Reeves

Journal of clinical epidemiology, Vol.89, pp.43-52

09/2017

DOI: 10.1016/j.jclinepi.2017.02.015

PMID: 28351693

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https://hdl.handle.net/1983/b126c1af-76f8-4ca9-86b0-25207d152307View

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Abstract

Rigorous and transparent bias assessment is a core component of high-quality systematic reviews. We assess modifications to existing risk of bias approaches to incorporate rigorous quasi-experimental approaches with selection on unobservables. These are nonrandomized studies using design-based approaches to control for unobservable sources of confounding such as difference studies, instrumental variables, interrupted time series, natural experiments, and regression-discontinuity designs. We review existing risk of bias tools. Drawing on these tools, we present domains of bias and suggest directions for evaluation questions. The review suggests that existing risk of bias tools provide, to different degrees, incomplete transparent criteria to assess the validity of these designs. The paper then presents an approach to evaluating the internal validity of quasi-experiments with selection on unobservables. We conclude that tools for nonrandomized studies of interventions need to be further developed to incorporate evaluation questions for quasi-experiments with selection on unobservables.

Meta-Analysis

Risk of bias

Difference in differences

Systematic review

Quasi-experiment

Instrumental variables

Regression discontinuity

Interrupted time series

Natural experiment

Details

Title: Subtitle: Quasi-experimental study designs series—paper 6: risk of bias assessment
Creators: Hugh Waddington - International Initiative for Impact Evaluation, New Delhi, India
Ariel M Aloe - University of Iowa, Iowa City, IA, USA
Betsy Jane Becker - Florida State University, Tallahassee, FL, USA
Eric W Djimeu - International Initiative for Impact Evaluation, New Delhi, India
Jorge Garcia Hombrados - University of Sussex, Brighton, UK
Peter Tugwell - Department of Medicine, University of Ottawa, Ottawa, Canada
George Wells - Department of Medicine, University of Ottawa, Ottawa, Canada
Barney Reeves - University of Bristoln, Bristol, UK
Resource Type: Journal article
Publication Details: Journal of clinical epidemiology, Vol.89, pp.43-52
DOI: 10.1016/j.jclinepi.2017.02.015
PMID: 28351693
NLM abbreviation: J Clin Epidemiol
ISSN: 0895-4356
eISSN: 1878-5921
Publisher: Elsevier Inc
Language: English
Date published: 09/2017
Academic Unit: Psychological and Quantitative Foundations
Record Identifier: 9983993321902771

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