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Many Labs 3: Evaluating participant pool quality across the academic semester via replication
- Charles R. Ebersole
- Olivia E. Atherton
- Aimee L. Belanger
- Hayley M Skulborstad
- Jill Allen
- Jonathan Britten Banks
- Erica Baranski
- Michael Jason Bernstein
- Diane B. V. Bonfiglio
- Leanne Boucher
- Elizabeth R. Brown
- Nancy I. Budiman
- Athena Cairo
- Colin Capaldi
- Christopher R. Chartier
- David C Cicero
- Jennifer A. Coleman
- Morgan Conway
- William E. Davis
- Thierry Devos
- Raelyne L. Dopko
- Jon Grahe
- Komi German
- Joshua A. Hicks
- Anthony Hermann
- Brandon Humphrey
- David J. Johnson
- Jennifer Joy-Gaba
- Hannah Juzeler
- Richard A. Klein
- Richard E. Lucas
- Christopher J. N. Lustgraaf
- Madhavi Menon
- Mitchell Metzger
- Jaclyn M. Moloney
- Patrick J. Morse
- Anthony J. Nelson
- Radmila Prislin
- Timothy Razza
- Daniel E. Re
- Nicholas Rule
- Donald Sacco
- Kyle Sauerberger
- Megan Shultz
- Jessi L. Smith
- Karin Sobocko
- Troy G. Steiner
- Weylin Sternglanz
- Konstantin Tskhay
- Leigh Ann Vaughn
- Zack van Allen
- Ryan J. Walker
- John Paul Wilson
- James H. Wirth
- Jessica Wortman
- John M. Zelenski
- Brian A. Nosek
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Description: Many Labs 3 is a crowdsourced project that systematically evaluated time-of-semester effects across many participant pools. See the Wiki for a table of contents of files and to download the manuscript.
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Observe, hypothesize, test, repeat: Luttrell, Petty, and Xu (2017) demonstrate good science
Many Labs 3 (Ebersole et al., 2016) failed to replicate a classic finding from the Elaboration Likelihood Model of persuasion (Cacioppo, Petty, & ...
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