Biases and standard errors of standardized regression coefficients

DOI10.1007/S11336-011-9224-6zbMath1231.62134OpenAlexW2084585094WikidataQ88116900 ScholiaQ88116900MaRDI QIDQ658145

Ke-Hai Yuan, Wai Chan

Publication date: 11 January 2012

Published in: Psychometrika (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11336-011-9224-6

zbMATH Keywords

consistencyasymptoticsMonte Carlo

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Monte Carlo methods (65C05)

Related Items (5)

Simple and flexible Bayesian inferences for standardized regression coefficients ⋮ Standardized regression coefficients and newly proposed estimators for \({R}^{{2}}\) in multiply imputed data ⋮ Some improvements in confidence intervals for standardized regression coefficients ⋮ Which method delivers greater signal‐to‐noise ratio: Structural equation modelling or regression analysis with weighted composites? ⋮ The normal-theory and asymptotic distribution-free (ADF) covariance matrix of standardized regression coefficients: theoretical extensions and finite sample behavior

Uses Software

• Mplus
• LISREL
• EQS
• bootstrap

Cites Work

• Analysis of covariance and correlation structures
• Inferences on correlation coefficients in some classes of nonnormal distributions
• Estimation of Standardized Regression Coefficients
• SIMPLIFIED FORMULAE FOR STANDARD ERRORS IN MAXIMUM‐LIKELIHOOD FACTOR ANALYSIS
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