Constructing Approximate Confidence Intervals for Parameters With Structural Equation Models

By Mike W.-L. Cheung. 2009

81 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Experimental and Cognitive Psychology, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/c313a9452620551bd82e5c27b3d98fefac56970d

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In Computer Networks and Communications

In Experimental and Cognitive Psychology

In Management Science and Operations Research

Citations in the corpus

Introduction of International Accounting Standards, Disclosure Quality and Accuracy of Analysts' Earnings Forecasts (2013, unknown): “Furthermore, SEM allows the estimation of impact multipliers in the form of indirect (mediated) and total effects and their standard errors (see Cheung, 2009 ).”
metaSEM: an R package for meta-analysis using structural equation modeling (2015, methodology): “Due to space constraint, I did not include topics, such as using REML as the estimation method (see Cheung, 2013a), constructing likelihood-based confidence interval (LBCI) (see Cheung, 2009), and using alternative random-effects MASEM (see Cheung and Cheung, under review).”
Classroom climate and children’s academic and psychological wellbeing: A systematic review and meta-analysis (2020, methodology): “This integrated modeling approach provides additional methodological advantages, such as flexible parameter constraints, a greater accuracy for confidence intervals, and the use of full information maximum likelihood for handling missing covariates (Cheung, 2009, 2014).”
Multivariate Meta-Analysis as Structural Equation Models (2013, methodology): “For example, likelihood-based CIs are often preferred to Wald CIs (Cheung, 2009a; Neale & Miller, 1997).”
The technology acceptance model (TAM): A meta-analytic structural equation modeling approach to explaining teachers' adoption of digital technology in education (2019, methodology): “-L. Cheung, 2015; M. W.-L. Cheung & Chan, 2005).”
cocor: A Comprehensive Solution for the Statistical Comparison of Correlations (2015, unknown): “Second, cocor does not allow one to employ structural equation models that are needed for more advanced, but also more complex approaches to the statistical comparison of correlations [38, 39].”
“My Questionnaire is Too Long!” The assessments of motivational-affective constructs with three-item and single-item measures (2014, methodology): “…the Pearson correla tion with the full scale and the Pearson correlation with the short form (as well as the single item Pearson correlation) and the 95% confidence intervals for each difference between the two correla tions were calculated according to the formula provided by Cheung (2009).”
Modeling dependent effect sizes with three-level meta-analyses: a structural equation modeling approach. (2014, background): “…; we move the parameter estimate (treated as variable) as far away as possible to the right for ̂Upper (or to the left for ̂Lower) from its maximum likelihood estimate (MLE), such that it is just significant at the desired level (for more details, see M. W.-L. Cheung, 2009; Neale & Miller, 1997).”