Meta-Analysis: A Structural Equation Modeling Approach

By Mike W.-L. Cheung. 2015

351 citations recorded by the source corpus.

Subfields: Complementary and alternative medicine, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/a6e6f9b1cb6a94f0faf0212fe11c94fad1118e32

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Citations in the corpus

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).”
The relationship between symbolic play and language acquisition: A meta-analytic review (2018, background): “…meta-analysis by including random effects at the level of study.2 While this approach can accommodate correlated effect sizes within studies, it cannot accommodate the correlated sampling errors within studies that are due to effect sizes being calculated on the same participants (Cheung, 2015).”
Loneliness and the Big Five Personality Traits: A Meta–Analysis (2020, methodology): “Estimation of multivariate effects We assessed the unique relations of each Big Five personality trait with loneliness when controlling for the other four traits by adopting a two-stage structural equation modelling (TSSEM) approach to MASEM (Cheung & Chan, 2005b; Cheung, 2015).”
Anonymity and Online Self-Disclosure: A Meta-Analysis (2019, methodology): “A random effects model was tested because it allows researchers to “estimate the average effect on all possible studies and the variability of the effect sizes” (Cheung, 2015, p. 94).”
Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage (2019, background): “According to Cheung (2015), the dummy-coded TR inhibitors and motivators should be tested simultaneously by fixing the model’s level 1 intercept to zero; otherwise the model will not be identified (Web Appendix C).”
Beyond intelligence: a meta-analytic review of the relationship among metacognition, intelligence, and academic performance (2018, methodology): “…+k, the number of study samples added for the trim-and-fill method ***p < .001 Meta-analytic structural equation modeling The degree to which metacognition predicted academic performance, with intelligence controlled for, was assessed using MASEM via the metaSEM package in R (Cheung 2015b).”
Psychological Ownership: A Meta-Analysis and Comparison of Multiple Forms of Attachment in the Workplace (2020, methodology): “This approach ensures that the statistical parameters and the standard errors are correct (see Cheung, 2015, for details).”
A Guide to Conducting a Meta-Analysis with Non-Independent Effect Sizes (2019, methodology): “Many books introducing how to conduct a systematic review and meta-analysis have already been published (e.g., Borenstein, Hedges, Higgins, & Rothstein, 2009; Card, 2012; Cheung, 2015a; Cooper, Hedges, & Valentine, 2009; Hedges & Olkin, 1985).”
Are Social Media Ruining Our Lives? A Review of Meta-Analytic Evidence (2019, background): “SNS use was found to be unrelated to study time, r = −.03, 95% CI [−.11, .06], therefore, providing no support for a time-displacement rationale in a related meta-analytical structural equation model (MASEM; Cheung, 2015).”
A meta-analysis of the relations between personality and workplace deviance: Big Five versus HEXACO (2019, methodology): “A two-stage random-effects meta-analytical structural equation modeling (MASEM) was conducted to calculate the variance in workplace deviance explained by the B5 and the HEXACO personality model (Cheung, 2014, 2015).”
A Meta-Analysis of the Relation Between RAN and Mathematics (2017, background): “Forthcoming research may better understand the heterogeneity of the RAN–mathematics relationship and moderator associations within a meta-analytic structural equation modeling framework (Cheung, 2008, 2015a, 2015b).”