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Quasi-experimental study designs series—paper 6: risk of bias assessment
- Source :
- Waddington, H, Aloe, A, Becker, B, Djimeu, E W, Hombrados, J G, Tugwell, P, Wells, G & Reeves, B 2017, ' Quasi-experimental study designs series—paper 6 : risk of bias assessment ', Journal of Clinical Epidemiology, vol. 89, pp. 43-52 . https://doi.org/10.1016/j.jclinepi.2017.02.015
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- Rigorous and transparent critical appraisal is a core component of high quality systematic reviews. Well-conducted quasi-experiments have been empirically shown to estimate credible, unbiased treatment quantities. Conversely, when inappropriately designed or executed, these estimates are likely to be biased. This paper draws on recent advances in risk of bias assessment. It presents an approach to evaluating the internal validity of credible quasi-experiments. These are non-randomised 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. Our review suggests that existing risk of bias tools provide, to different degrees, incomplete transparent criteria to assess the validity of credible quasi-experiments. We argue that a tool is needed to assess risk of bias consistently across credible quasi-experiments. Drawing on existing tools, in particular Cochrane’s new tool for non-randomized studies of interventions (Sterne et al., 2014), we discuss domains of bias and suggest directions for evaluation questions.
- Subjects :
- regression discontinuity
Non-Randomized Controlled Trials as Topic
Epidemiology
Computer science
media_common.quotation_subject
BTC (Bristol Trials Centre)
Risk Assessment
Unobservable
03 medical and health sciences
0302 clinical medicine
systematic review
Bias
risk of bias
Econometrics
Humans
interrupted time series
030212 general & internal medicine
Internal validity
natural experiment
media_common
quasi-experiment
Selection bias
instrumental variables
difference in differences
propensity score matching
030503 health policy & services
Instrumental variable
meta-analysis
Systematic review
Research Design
Meta-analysis
Regression discontinuity design
0305 other medical science
Quasi-experiment
Subjects
Details
- ISSN :
- 08954356
- Volume :
- 89
- Database :
- OpenAIRE
- Journal :
- Journal of Clinical Epidemiology
- Accession number :
- edsair.doi.dedup.....d30816252048fed925429dc2ff219b4b