Quantitative Political Science Research Is Greatly Underpowered

The social sciences face a replicability crisis. A key determinant of replication success is statistical power. We assess the power of political science research by collating over 16,000 hypothesis tests from about 2,000 articles in 46 areas of the discipline. Under generous assumptions, we show that quantitative research in political science is greatly underpowered: the median analysis has about 10% power, and only about 1 in 10 tests have at least 80% power to detect the consensus effects reported in the literature. We also find substantial heterogeneity in tests across research areas, with some being characterized by high power but most having very low power. To contextualize our findings, we survey political methodologists to assess their expectations about power levels. Most methodologists greatly overestimate the statistical power of political science research.

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Publication Details

Journal
The Journal of Politics
Published
2024-12-13
DOI
https://doi.org/10.1086/734279
Citations
8
Primary Topic
Qualitative Comparative Analysis Research
Type
article
Field-Weighted Citation Impact
7.92
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article

Quantitative Political Science Research Is Greatly Underpowered

Hristos Doucouliagos, T. D. Stanley, Vincent Arel‐Bundock, Marco Mendoza Aviña et al.
8 citations
The Journal of Politics
Qualitative Comparative Analysis Research
7.92
article

Quantitative Political Science Research Is Greatly Underpowered

Hristos Doucouliagos, T. D. Stanley, Vincent Arel‐Bundock, Marco Mendoza Aviña, Ryan C. Briggs
article en
8 citations

Abstract

The social sciences face a replicability crisis. A key determinant of replication success is statistical power. We assess the power of political science research by collating over 16,000 hypothesis tests from about 2,000 articles in 46 areas of the discipline. Under generous assumptions, we show that quantitative research in political science is greatly underpowered: the median analysis has about 10% power, and only about 1 in 10 tests have at least 80% power to detect the consensus effects reported in the literature. We also find substantial heterogeneity in tests across research areas, with some being characterized by high power but most having very low power. To contextualize our findings, we survey political methodologists to assess their expectations about power levels. Most methodologists greatly overestimate the statistical power of political science research.

The Journal of PoliticsVol. 88(1)
Deakin University (AU), Harvard University Press (US), Université de Montréal (CA), University of Guelph (CA)
Openalex Percentile: Top 3%
Qualitative Comparative Analysis Research
7.92
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