Faculty Opinions recommendation of Many Labs 2: Investigating Variation in Replicability Across Samples and Settings.

By T. Barrett. 2019

356 citations recorded by the source corpus.

Subfields: Education, Media Technology

View Paper: https://www.semanticscholar.org/paper/35aaa9ccb29943af4a3ddd73e3fcc7bd759ee478

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Education

1. Burak Doğruyol
2. Malte Friese
3. Timo Gnambs
4. Farid Anvari
5. Michael Inzlicht
6. Onurcan Yılmaz
7. Markus Appel
8. Sinan Alper

In Media Technology

1. Burak Doğruyol
2. Malte Friese
3. Farid Anvari
4. Michael Inzlicht
5. Onurcan Yılmaz
6. Sinan Alper
7. Daniël Lakens

Citations in the corpus

• The five-factor model of the moral foundations theory is stable across WEIRD and non-WEIRD cultures (2019, methodology): “Data were retrieved from the Many Labs 2 Project (Klein et al., 2018) for the current study.”
• Are Social Media Ruining Our Lives? A Review of Meta-Analytic Evidence (2019, background): “Regarding research on social media, meta-analyses can scrutinize the stability of associations across, for example, different social media platforms, populations, or activities on SNSs (Ebersole et al., 2016; Klein et al., 2014; Klein et al., 2018; O’Donnell et al., 2018).”
• The past, present, and future of ego depletion (2019, background): “Broad tests of the replicability of psychology suggest that the case of ego depletion might be less exception and more rule in social psychology, where a majority of papers have failed the replication test (Klein et al., 2018; Nosek & Lakens, 2014; Open Science Collaboration, 2015).”
• Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis (2021, unknown): “…al., 2016; Bedeian et al., 2010; Begley & Ellis, 2012; Bergh et al., 2017; Camerer et al., 2016, 2018; Chang & Li, in press; Ebersole et al., 2016; Klein et al., 2014; 2018; Landy et al., 2020; O’Boyle et al., 2019; Open Science Collaboration, 2015; Prinz, Schlange, & Asadullah, 2011) highlight…”
• Using Anchor-Based Methods to Determine the Smallest Effect Size of Interest (2019, background): “…of ‘statistically significant’ as ‘meaningful’, which is becoming increasingly important given the rise of big data and the uptake of large-scale collaborative projects (e.g., Klein et al., 2014, 2018; Moshontz et al., 2018), where trivially small differences can be statistically significant.”