Risk of Bias in Experiments, Quasi-Experiments and Natural Experiments Across Disciplines: Discussion Paper and...

Area of Science:

• Social Sciences
• Natural Sciences
• Impact Evaluation

Background:

• Decision-making relies on rigorously appraised evidence.
• Impact evaluations in social and natural sciences use various experimental and quasi-experimental designs.
• Existing bias assessment tools often fail to address both randomized controlled trials (RCTs) and non-randomized studies (QEDs) adequately.

Purpose of the Study:

• To discuss the risk of bias in impact evaluations.
• To present a novel heuristic for assessing confidence in causal inferences.
• To address limitations of existing bias assessment tools for diverse study designs.

Main Methods:

• Discussed risk of bias in impact evaluations.
• Presented a heuristic to assist reviewers in assessing confidence in causal inferences.
• Developed signaling questions to evaluate common bias sources across study types.

Main Results:

• Existing bias tools are often limited to either RCTs or QEDs.
• Common bias sources include group equivalence, study fidelity, measurement adequacy, and analysis reporting.
• The proposed heuristic addresses bias sources specific to different designs, like participant reactivity or selection mechanisms.

Conclusions:

• A unified approach is needed to assess bias across various impact evaluation designs.
• The presented heuristic aids reviewers in evaluating bias and strengthening causal inferences.
• The approach emphasizes four key bias sources applicable to RCTs, QEDs, and natural experiments.