Many Labs 2: Investigating Variation in Replicability Across Samples and Settings
Richard Klein; Michelangelo Vianello; Fred Hasselman; Byron G. Adams; Reginald B. Adams; Sinan Alper; Mark Aveyard; Jordan Axt · 2018 · Advances in Methods and Practices in Psychological Science
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
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…
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WASTE indexes this work — it does not host or republish it. Failure-type classification is automated and approximate.
Metadata source: OpenAlex · DOI 10.1177/2515245918810225
