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Heterogeneity in effect size estimates
Felix Holzmeister1, Magnus Johannesson2, Robert Böhm3,4
1Department of Economics, University of Innsbruck, A-6020 Innsbruck, Austria.
Summary
Scientific studies show that variations in sample, design, and analysis (heterogeneity) can significantly lower the probability that a hypothesis is true, impacting research generalizability.
Area of Science:
- Social Sciences
- Empirical Research Methods
Background:
- Empirical studies involve choices in sample, research design, and analysis.
- Variations in these choices create heterogeneity, increasing uncertainty and limiting generalizability of findings.
Purpose of the Study:
- To provide a framework for studying heterogeneity in the social sciences.
- To categorize heterogeneity into population, design, and analytical types.
- To assess the impact of heterogeneity on the probability of a hypothesis being true.
Main Methods:
- Framework developed for analyzing heterogeneity.
- Estimation of population, design, and analytical heterogeneity.
- Data sourced from 70 multilab replication studies, 11 prospective meta-analyses, and 5 multianalyst studies.
Main Results:
- Population heterogeneity was relatively small.
- Design and analytical heterogeneity were found to be large.
- Accounting for heterogeneity suggests a lower probability of hypothesis truth than nominal error rates.
Conclusions:
- Heterogeneity, particularly design and analytical, significantly affects research findings.
- Results highlight the need to parse and account for heterogeneity in social science research.
- Caution is advised due to limited data and uncertainty in heterogeneity estimates.
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