The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
The Insignificance of Null Hypothesis Significance Testing
Abstract
The current method of hypothesis testing in the social sciences is under intense criticism, yet most political scientists are unaware of the important issues being raised. Criticisms focus on the construction and interpretation of a procedure that has dominated the reporting of empirical results for over fifty years. There is evidence that null hypothesis significance testing as practiced in political science is deeply flawed and widely misunderstood. This is important since most empirical work argues the value of findings through the use of the null hypothesis significance test. In this article I review the history of the null hypothesis significance testing paradigm in the social sciences and discuss major problems, some of which are logical inconsistencies while others are more interpretive in nature. I suggest alter native techniques to convey effectively the importance of data-analytic findings. These recommendations are illustrated with examples using empirical political science publications.
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Jenkins, D. G., & Quintana-Ascencio, P. F. (2020) · PLOS ONE · doi:10.1371/journal.pone.0229345 · Cited by 665
“Power analyses carry forward fundamental problems with null hypothesis inference, which is the long-standing basis for statistical analyses but that has been recently and widely criticized for several reasons [25,26,27,28,29].”
BackgroundThe perils of policy by p-value: Predicting civil conflicts
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An Empirical Evaluation of Explanations for State Repression
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Significance tests as sorcery: Science is empirical—significance tests are not
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Metadata
- Authors
- Gill, J.
- Venue
- Political Research Quarterly
- Publisher
- SAGE Publications
- Published
- 1999-09
- Volume
- 52
- Issue
- 3
- Pages
- 647-674
- ISSN
- 1065-9129 (ISSN-L)
- 1938-274X
- OpenAlex
- W2024096835
- Cited by
- 338
- References
- 13
- FWCI
- 78.05
- Type
- journal article
- Language
- en
- Open access
- closed
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