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the claim
Repeated measures designs in cognitive research permit causal inference
the verdict
CONTESTED
the evidence cuts both ways
confidence 35/100

While repeated measures and longitudinal designs are frequently employed to track change and support causal claims in cognitive and psychological research, methodologists emphasize that they do not automatically guarantee valid causal inference and can introduce complex biases.

Evidence for · 2
The Unfulfilled Promise of Longitudinal Designs for Causal Inference
2023 · cited by 18
Longitudinal and repeated measures designs are explicitly chosen with the intuitive goal of bolstering validity and strengthening causal conclusions over time.
Evidence against · 2
The Unfulfilled Promise of Longitudinal Designs for Causal Inference
2023 · cited by 18
Adjusting for previous measurements in longitudinal designs can simultaneously strengthen and undermine causal inferences, frequently inducing or reducing bias in complex ways.
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More for · 1
To advance sleep science, let's study change.
2026 · cited by 0
Multi-time point longitudinal designs are described as approaches that can illuminate temporal dynamics and offer stronger, potentially causal conclusions regarding health outcomes.
More against · 1
Selecting a Within- or Between-Subject Design for Mediation: Validity, Causality, and Statistical Power
2020 · cited by 3
Within-subject repeated measures designs carry specific threats to validity, such as carry-forwards and unverified assumptions, making causal inference far from straightforward.
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first checked01 Aug 2026
judged → CONTESTED · 3501 Aug 2026
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