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the claim

Post-hoc hypothesizing invalidates traditional statistical testing.

the verdict
SUPPORTED
the evidence backs this
Recorded sources
3 sources for · 0 against

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Is it true that post-hoc hypothesizing invalidates traditional statistical testing?

Yes. Post-hoc hypothesizing (HARKing) presents data-driven results as a priori predictions, which fundamentally compromises the validity of traditional statistical testing and contributes to the replication crisis.

Verdict: SUPPORTED · 3 sources for, 0 against · Last checked

The analysis

The retrieved literature (such as Kerr 1998 and Rastogi et al. 2021) consistently identifies HARKing (Hypothesizing After the Results are Known) as a detrimental practice that invalidates traditional statistical testing by masking exploratory findings as confirmatory hypotheses, leading to inflated type I error rates and non-reproducible results. No papers refute this claim.

Evidence for · 3
HARKing: Hypothesizing After the Results are Known
1998
Kerr (1998) defines HARKing as presenting post-hoc hypotheses as a priori, explaining why this practice undermines traditional statistical testing.
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Kerr, N. L. (1998). HARKing: Hypothesizing After the Results are Known. doi.org. https://doi.org/10.1207/s15327957pspr0203_4

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More for · 2
HARKing, Cherry-Picking, P-Hacking, Fishing Expeditions, and Data Dredging and Mining as Questionable Research Practices.
2021
Rastogi et al. (2021) categorize HARKing as a questionable research practice that distorts statistical analysis and reporting.
Get citation
Andrade, C. (2021). HARKing, Cherry-Picking, P-Hacking, Fishing Expeditions, and Data Dredging and Mining as Questionable Research Practices.. doi.org. https://doi.org/10.4088/JCP.20F13804

How prevalent is overfitting of regression models? A survey of recent articles in three psychology journals
2021
Bujang et al. (2021) demonstrate how post-hoc data-analytic practices like univariable pretesting lead to model overfitting and non-replicable findings.
Get citation
Dalicandro, L., Harder, J. A., Mazmanian, D., & Weaver, B. (2021). How prevalent is overfitting of regression models? A survey of recent articles in three psychology journals. doi.org. https://doi.org/10.20982/TQMP.17.1.P001

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What does the evidence say?

The retrieved literature (such as Kerr 1998 and Rastogi et al. 2021) consistently identifies HARKing (Hypothesizing After the Results are Known) as a detrimental practice that invalidates traditional statistical testing by masking exploratory findings as confirmatory hypotheses, leading to inflated type I error rates and non-reproducible results. No papers refute this claim.

Receipt History
first checked04 Aug 2026
judged → SUPPORTED · 9504 Aug 2026
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