Handbook of structural equation modeling
By R. Hoyle. 2012
1,124 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/acfac2cc763e1c40986d2fc749642a7a97334a4d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- M. Milyavskaya
- Han Y. H. Chen
- Yu Zhang
- Baoguo Xie
- Wen-xia Zhou
- Jason L. Huang
- Michael Inzlicht
- A. Taylor
Citations in the corpus
- A Gentle Introduction to Bayesian Analysis: Applications to Developmental Research (2013, unknown): “Concerning the latter, we used the Gelman – Rubin criterion (for more information, see Gelman et al., 2004) to monitor convergence, which is the default setting of Mplus.”
- Lack of Theory Building and Testing Impedes Progress in The Factor and Network Literature (2020, background): “(Vaidyanathan et al., 2015) Factor models require little introduction, and represent a sophisticated statistical framework (Brown, 2015; Hoyle, 2012; Kline, 2015).”
- Using goal facilitation theory to explain the relationships between calling and organization-directed citizenship behavior and job satisfaction (2017, methodology): “As the CFA analysis above supported the structural validity of our measurement model, we proceeded to conduct structural equation modeling focused on directional relations between observed variables (Hoyle, 2012).”
- What’s So Great About Self-Control? Examining the Importance of Effortful Self-Control and Temptation in Predicting Real-Life Depletion and Goal Attainment (2015, background): “BIC difference of 0–2 suggests weak evidence in favor of model with smaller BIC; 2–6 suggests positive evidence; 6–10 strong evidence, and >10 suggests very strong evidence (Kaplan & Depaoli, 2012).”