ArticlePloS one2019
Predicting the replicability of social science lab experiments.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed.
- A framework for assessing the trustworthiness of scientific research findings.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- In Search of the Lost Interaction: A Theoretical and Methodological Framework for Researching Interactions.Europe's journal of psychology · 2025Article
- A metric of knowledge as information compression reflects reproducibility predictions for biomedical experiments.Royal Society open science · 2025Article
- Examining the replicability of online experiments selected by a decision market.Nature human behaviour · 2025Article
- Predicting the replicability of social and behavioural science claims in COVID-19 preprints.Nature human behaviour · 2025Article
- Meta-regression to explain shrinkage and heterogeneity in large-scale replication projects.PloS one · 2025Article
- Can large language models help predict results from a complex behavioural science study?Royal Society open science · 2024Article
- ScreeningProceedings of the National Academy of Sciences of the United States of America · 2024Article
- Article
- Challenging the N-Heuristic: Effect size, not sample size, predicts the replicability of psychological science.PloS one · 2024Article
- Eleven years of student replication projects provide evidence on the correlates of replicability in psychology.Royal Society open science · 2023Article
- A discipline-wide investigation of the replicability of Psychology papers over the past two decades.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Three-variable systems: An integrative moderation and mediation framework for developmental psychopathology.Development and psychopathology · 2023Article
- Article
- Establishing ground truth in the traumatic brain injury literature: if replication is the answer, then what are the questions?Brain communications · 2023Review
- Article
- Examining the generalizability of research findings from archival data.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- The effects of U.S. county and state income inequality on self-reported happiness and health are equivalent to zero.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2022Article
- Dimensionality of the Chinese CES-D: Is It Stable across Gender, Time, and Samples?International journal of environmental research and public health · 2021Article
- Food on the Move: The Impact of Implied Motion in Pictures on Food Perceptions through Anticipated Pleasure of Consumption.Foods (Basel, Switzerland) · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We measure how accurately replication of experimental results can be predicted by black-box statistical models. With data from four large-scale replication projects in experimental psychology and economics, and techniques from machine learning, we train predictive models and study which variables drive predictable replication. The models predicts binary replication with a cross-validated accuracy rate of 70% (AUC of 0.77) and estimates of relative effect sizes with a Spearman ρ of 0.38. The accuracy level is similar to market-aggregated beliefs of peer scientists [1, 2]. The predictive power is validated in a pre-registered out of sample test of the outcome of [3], where 71% (AUC of 0.73) of replications are predicted correctly and effect size correlations amount to ρ = 0.25. Basic features such as the sample and effect sizes in original papers, and whether reported effects are single-variable main effects or two-variable interactions, are predictive of successful replication. The models presented in this paper are simple tools to produce cheap, prognostic replicability metrics. These models could be useful in institutionalizing the process of evaluation of new findings and guiding resources to those direct replications that are likely to be most informative.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.