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Structural Equation Modeling

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Dolan, Conor V.	1
McQuitty, Shaun	1
Molenaar, Peter C. M.	1
Wicherts, Jelte M.	1

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Reports - Evaluative	1

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A Note on the Relationship between the Number of Indicators and Their Reliability in Detecting Regression Coefficients in Latent Regression Analysis

Peer reviewed

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Dolan, Conor V.; Wicherts, Jelte M.; Molenaar, Peter C. M. – Structural Equation Modeling, 2004

We consider the question of how variation in the number and reliability of indicators affects the power to reject the hypothesis that the regression coefficients are zero in latent linear regression analysis. We show that power remains constant as long as the coefficient of determination remains unchanged. Any increase in the number of indicators…

Descriptors: Error of Measurement, Factor Analysis, Regression (Statistics), Evaluation Methods

Effects of Employing Ridge Regression in Structural Equation Models.

Peer reviewed

McQuitty, Shaun – Structural Equation Modeling, 1997

LISREL 8 invokes a ridge option when maximum likelihood or generalized least squares are used to estimate a structural equation model with a nonpositive definite covariance or correlation matrix. Implications of the ridge option for model fit, parameter estimates, and standard errors are explored through two examples. (SLD)

Descriptors: Error of Measurement, Estimation (Mathematics), Goodness of Fit, Least Squares Statistics