Whether results represent causal effects requires knowledge and assumptions about data, design, and methods in both experimental and non-experimental work¶

Claim · All claims
Evidence · 1 study · theoretical r2 · q1
Currency · newest study 2023 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q1 i? The article argues that the blurry dichotomy of scientific experimental versus unscientific non-experimental work falls short, since causal interpretation in either design rests on assumptions about data, design, and methods. → Zitzmann 2023

Evidence¶

Zitzmann 2023¶

Zitzmann, S., Machts, N., Hübner, N., Schauber, S., Möller, J., & Lindner, C. (2023). The Yet Underestimated Importance of Communicating Findings from Educational Trials to Teachers, Schools, School Authorities, or Policy Makers (Comment on Brady et al. (2023)). Educational Psychology Review. https://doi.org/10.1007/s10648-023-09776-8

q1 · i? · theoretical · r2

Theoretical argument in the commentary, citing Wadhwa et al. (2019) and Hübner et al. (2023): causal interpretation requires assumptions in both experimental and non-experimental work, and challenges to replicate randomized experiments further complicate the dichotomy. The authors do not dispute that causality should be at the core of research informing practice.

"whether or not results represent causal effects can only be answered with great knowledge and assumptions about the data, design, and the methods used, and this holds for non-experimental as well as for experimental work (Wadhwa et al., 2019)."

Discussion¶

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