Structural Equation Modeling: A Bayesian Approach

By Sik-Yum Lee. 2007

549 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/4cf0eddb43e4e4e697338ad4fa2fcd2e36b327e9

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Citations in the corpus

Teacher-student relationship and mathematical problem-solving ability: mediating roles of self-efficacy and mathematical anxiety (2020, methodology): “We calculated the intra-class correlation coefficient (ICC) of students’ mathematical problem-solving scores and assessed whether multilevel structure equation modelling or structural equation modelling was necessary (Lee, 2007).”
Applications of structural equation modeling (SEM) in ecological studies: an updated review (2016, methodology): “BIC is widely used, and many statisticians suggest posterior predictive checking to estimate the predictive ability of the model (Raftery 1993; Lee 2007; Kaplan and Depaoli 2012).”
Bayesian Inference and Application of Robust Growth Curve Models Using Student's t Distribution (2013, methodology): “The use of Bayesian methods for complex data analysis has been made popular by Lee and colleagues (e.g., Lee, 2007; Lee & Shi, 2000; Lee & Song, 2008; Lee & Xia, 2008).”
Methods and Measures: Growth mixture modeling: A method for identifying differences in longitudinal change among unobserved groups (2009, background): “Interested readers are referred to Muthén and Shedden (1999) for technical aspects of the EM estimation algorithms and Lee (2007) for the Bayesian approach.”
An evaluation of WLSMV and Bayesian methods for confirmatory factor analysis with categorical indicators (2014, methodology): “Based on the results from previous studies (Asparouhov and Muthén, 2010a; Lee, 2007), we considered sample sizes less than 200 as small.”
Predicting Wine Tourism Intention: Destination Image and Self-congruity (2014, methodology): “To test the hypothesized effects of wine involvement, it was first necessary to test the different kinds of invariances among the model for different groups (Lee, 2007) through multigroup analysis.”
Seed and seedling traits affecting critical life stage transitions and recruitment outcomes in dryland grasses (2015, background): “Bayesian estimation does not depend on asymptotic theory and was preferred given small sample size (Lee 2007).”
Comparison of Inverse Wishart and Separation-Strategy Priors for Bayesian Estimation of Covariance Parameter Matrix in Growth Curve Analysis (2016, unknown): “…2012), full Bayesian estimation methods are increasingly used for growth curve models (e.g., Elliott, Gallo, Ten Have, Bogner, & Katz, 2005; Lee, 2007; P. Song, Zhang, & Qu, 2007; X. Y. Song & Lee, 2001, 2002; Zhang, Hamagami, Wang, Grimm, & Nesselroade, 2007; Zhang, Lai, Lu, & Tong, 2013).”
Bayesian structural equation modeling: a more flexible representation of substantive theory. (2012, methodology): “Bayesian exploration of model fit can be done in a flexible way using posterior predictive checking (see, e.g., Gelman et al., 2004, chapter 6; Gelman, Meng, Stern, & Rubin, 1996; Lee, 2007, chapter 5; Scheines et al., 1999).”
A Bayesian Approach for Estimating Multilevel Latent Contextual Models (2016, unknown): “…Gelman & Hill, 2007; Hamaker & Klugkist, 2011; Zhang, Hamagami, Wang, Nesselroade, & Grimm, 2009), SEM (e.g., Arminger & Muthén, 1998; Kaplan & Depaoli, 2012; Lee, 2007; B. O. Muthén & Asparouhov, 2012; Song & Lee, 2009), and multilevel SEM (e.g., Ansari & Jedidi, 2000; Depaoli & Clifton, 2015).”
Dynamic Structural Equation Models (2018, background): “Alternatively, these details can be found in Arminger and Muthen (1998) or Lee (2007).”
Latent Variable Modelling: A Survey * (2007, methodology): “Markov chain Monte Carlo has also been used (e.g. Zeger & Karim, 1991; Lee, 2007), typically with vague prior distributions.”
On the specification of structural equation models for ecological systems. (2010, methodology): “…Bayesian ideas andmethods have been incorporated in structural equation models (e.g., Raftery 1993) and estimation using Markov Chain Monte Carlo methods in combinationwith Bayes’ theorem is becoming increasingly common (Scheines et al. 1999, Rupp et al. 2004, Arhonditsis et al. 2006, Lee 2007).”
A Bayesian Approach to Multilevel Structural Equation Modeling With Continuous and Dichotomous Outcomes (2015, methodology): “Bayesian estimation of SEMs (Kaplan & Depaoli, 2012; Lee, 2007; Muthén & Asparouhov, 2012a; Scheines, Hoijtink, & Boomsma, 1999) and MLMs (Congdon, 2010; Gelman & Hill, 2007; Lynch, 2007) is a prevalent methodological topic because Bayesian methods are useful for solving problems that are unique to…”
Guidelines for a graph-theoretic implementation of structural equation modeling (2012, methodology): “Details of the estimation options for SEMs with latent variables are described by Lee (2007).”
Do homes that are more energy efficient consume less energy?: A structural equation model for England's residential sector (2011, background): “At the most basic level SEM’s are a type of factor analysis and can therefore be viewed as a form of exploratory data analysis (EDA) where the number of factors, factor loadings and rotation of the factor loading matrix are determined through exploratory analysis (Lee 2007).”
Multivariate Meta-Analysis as Structural Equation Models (2013, background): “On the other side, Bayesian inferences are also getting more and more attention in SEM (Lee, 2007).”