Many Labs 2: Investigating Variation in Replicability Across Samples and Settings

By R. A. Klein, M. Vianello, Fred Hasselman, Byron G. Adams, Reginald B. Adams, Sinan Alper, M. Aveyard, Jordan R. Axt, Mayowa T. Babalola, Š. Bahník and 180 more. Advances in Methods and Practices in Psychological Science, 2018

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We conducted preregistered replications of 28 classic and contemporary published findings, with protocols that were peer reviewed in advance, to examine variation in effect magnitudes across samples and settings. Each protocol was administered to approximately half of 125 samples that comprised 15,305 participants from 36 countries and territories. Using the conventional criterion of statistical significance (p < .05), we found that 15 (54%) of the replications provided evidence of a statistically significant effect in the same direction as the original finding. With a strict significance criterion (p < .0001), 14 (50%) of the replications still provided such evidence, a reflection of the extremely high-powered design. Seven (25%) of the replications yielded effect sizes larger than the original ones, and 21 (75%) yielded effect sizes smaller than the original ones. The median comparable Cohen’s ds were 0.60 for the original findings and 0.15 for the replications. The effect sizes were small (< 0.20) in 16 of the replications (57%), and 9 effects (32%) were in the direction opposite the direction of the original effect. Across settings, the Q statistic indicated significant heterogeneity in 11 (39%) of the replication effects, and most of those were among the findings with the largest overall effect sizes; only 1 effect that was near zero in the aggregate showed significant heterogeneity according to this measure. Only 1 effect had a tau value greater than .20, an indication of moderate heterogeneity. Eight others had tau values near or slightly above .10, an indication of slight heterogeneity. Moderation tests indicated that very little heterogeneity was attributable to the order in which the tasks were performed or whether the tasks were administered in lab versus online. Exploratory comparisons revealed little heterogeneity between Western, educated, industrialized, rich, and democratic (WEIRD) cultures and less WEIRD cultures (i.e., cultures with relatively high and low WEIRDness scores, respectively). Cumulatively, variability in the observed effect sizes was attributable more to the effect being studied than to the sample or setting in which it was studied.

Subfields: Applied Psychology, Communication, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/c09441deaa6a6ced4bf2fd021b7aa9cc2122af3e

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Citations in the corpus

Evaluation of a decided sample size in machine learning applications (2023, background): “An insufficient sample size has insignificant statistical power, which causes an adverse impact on the true effect and the reproducibility of the findings [22, 23].”
Variability in the analysis of a single neuroimaging dataset by many teams (2019, background): “Concerns over replicability across many areas of science have led to a number of projects in recent years that attempted to assess the replicability of empirical findings across labs 3,34,47,48 .”