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Premature conclusions about the signal‐to‐noise ratio in structural equation modeling research : A commentary on Yuan and Fang (2023)

2023

In a recent article published in this journal, Yuan and Fang (British Journal of Mathematical and Statistical Psychology, 2023) suggest comparing structural equation modeling (SEM), also known as covariance-based SEM (CB-SEM), estimated by normal-distribution-based maximum likelihood (NML), to regression analysis with (weighted) composites estimated by least squares (LS) in terms of their signal-to-noise ratio (SNR). They summarize their findings in the statement that “[c]ontrary to the common belief that CB-SEM is the preferred method for the analysis of observational data, this article shows that regression analysis via weighted composites yields parameter estimates with much smaller stan…

Statistics and ProbabilityHenseler-Ogasawara specificationeffect sizetilastomenetelmätpartial least squares structural equation modelingGeneral MedicinerakenneyhtälömallitregressioanalyysiArts and Humanities (miscellaneous)sum scorescovariance-based structural equation modelingcomposite modelregression analysis with weighted compositesfactor score regressionGeneral Psychology
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