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Meta-regression to explain shrinkage and heterogeneity in large-scale replication projects

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  • Heyard, Rachel
  • Held, Leonhard

Abstract

Recent large-scale replication projects (RPs) have estimated alarmingly low replicability rates have been estimated. Within these RPs, the original-replication study pairs can vary substantially with respect to aspects of study design, outcome measures, and descriptive features of both the original and replication study population and study team. When broader claims about the replicability of an entire field are based on such heterogeneous data, it becomes imperative to conduct a rigorous analysis of the heterogeneity among study pairs included in the RP. Methodology from the meta-analysis literature provides an approach for quantifying the heterogeneity present in RPs, as additive or multiplicative parameter. Meta-analysis methodology further allows for an investigation of the sources of the heterogeneity through meta-regressions. Notably, we propose the use of location-scale meta-regressions as a means to directly relate the identified characteristics with shrinkage (represented by the location) and the heterogeneity variance (represented by the scale). The proposed methodology is illustrated using data from the Reproducibility Project Psychology and the Reproducibility Project Experimental Economics. All analysis scripts and data are available online.

Suggested Citation

  • Heyard, Rachel & Held, Leonhard, 2024. "Meta-regression to explain shrinkage and heterogeneity in large-scale replication projects," MetaArXiv e9nw2, Center for Open Science.
    • Handle: RePEc:osf:metaar:e9nw2
    DOI: 10.31219/osf.io/e9nw2
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    References listed on IDEAS

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    1. Samuel Pawel & Leonhard Held, 2020. "Probabilistic forecasting of replication studies," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-23, April.
    2. Viechtbauer, Wolfgang, 2010. "Conducting Meta-Analyses in R with the metafor Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 36(i03).
    3. Adam Altmejd & Anna Dreber & Eskil Forsell & Juergen Huber & Taisuke Imai & Magnus Johannesson & Michael Kirchler & Gideon Nave & Colin Camerer, 2019. "Predicting the replicability of social science lab experiments," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-18, December.
    4. Christopher J. Bryan & Elizabeth Tipton & David S. Yeager, 2021. "Behavioural science is unlikely to change the world without a heterogeneity revolution," Nature Human Behaviour, Nature, vol. 5(8), pages 980-989, August.
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