Advancing Theory by Assessing Boundary Conditions With Metaregression: A Critical Review and Best-Practice Recommendations

By Erik Gonzalez‐Mulé, Herman Aguinis. 2018

158 citations recorded by the source corpus.

Subfields: Accounting, Statistics and Probability, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/a775b76ba597320226f91a19e50a2476a4531047

How researchers see this paper

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

In Accounting

1. Yan Chen
2. Thomas G. Lechler
3. Serhan Kotiloglu

In Statistics and Probability

1. J. Sánchez-Meca
2. Fulgencio Marín-Martínez
3. W. Viechtbauer
4. Mark S. Allen
5. Yan Chen
6. S. Howard
7. Thomas G. Lechler
8. J. Botella

In Strategy and Management

1. Yan Chen
2. Thomas G. Lechler
3. Serhan Kotiloglu
4. Ofer Zwikael
5. J. Smyrk

Citations in the corpus

• Self-regulation in childhood as a predictor of future outcomes: A meta-analytic review. (2020, background): “In many instances, the sample size was small meaning the meta-regression models likely had insufficient power to detect even a large effect (see Gonzalez-Mulé & Aguinis, 2018).”
• Testing Categorical Moderators in Mixed-Effects Meta-analysis in the Presence of Heteroscedasticity (2019, methodology): “…adequate control of the Type I error rate in several simulation studies (Huizenga, Visser, & Dolan, 2011; Knapp & Hartung, 2003; Sidik & Jonkman, 2005; Viechtbauer, L opez-L opez, S anchez-Meca, & Mar ın-Mart ınez, 2015) and is routinely recommended nowadays (Gonzalez-Mul e & Aguinis, 2017).”
• Organizational responses to performance feedback: A meta-analytic review (2019, methodology): “We used meta-analytic regressions to examine whether and the extent to which certain variables can help explain effect sizes’ heterogeneity (Aguinis et al., 2011; Gonzalez-Mulé and Aguinis, 2018).”