Performance of Modified Test Statistics in Covariance and Correlation Structure Analysis Under Conditions of Multivariate Nonnormality

By Rachel T. Fouladi. 2000

163 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/da3c7f4f32c82fed3fd2e7c0ff8e4a099266849f

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In Statistics and Probability

Citations in the corpus

The effects of service quality, image, and customer satisfaction on customer complaints and loyalty in high-speed rail service in Turkey: a proposal of the structural equation model (2017, background): “This is because the normality assumption ensures that asymptotically unbiased, efficient, and consistent estimators are obtained, and when this assumption is not validated, the estimators obtained will not have such properties (Curran, West, and Finch 1996; Fouladi 2000).”
Structural Equation Modeling: Reviewing the Basics and Moving Forward (2006, result): “Similar conclusions were found in studies by Fouladi (2000) , Hoogland (1999), and Satorra (2000).”
Small Sample Statistics for Incomplete Nonnormal Data: Extensions of Complete Data Formulae and a Monte Carlo Comparison (2010, methodology): “The second study by Nevitt and Hancock (2004) had the goal of studying larger models than those considered by Fouladi (2000).”
Sample Size Requirements of the Robust Weighted Least Squares Estimator (2014, background): “As levels of non-normality increase, the superiority of robust WLS over ML can be assumed to be even more pronounced (Flora & Curran, 2004; Fouladi, 2000).”
Small Sample Size Solutions (2020, methodology): “Variations of this correction exist, but the one most studied (Nevitt & Hancock, 2004; see also Fouladi, 2000; Savalei, 2010) is a simplified correction proposed by Bartlett (1950) in the context of exploratory factor analysis.”
Bootstrap approach to inference and power analysis based on three test statistics for covariance structure models. (2003, methodology): “This is in contrast to conclusions regarding the performance of T B when referring to a chi-square distribution (Hu et al., 1992; Fouladi, 2000; Yuan & Bentler, 1997).”
A Two-Stage Approach to Synthesizing Covariance Matrices in Meta-Analytic Structural Equation Modeling (2009, background): “Browne and Arminger (1995) , and Fouladi (2000) also provided detailed discussion on how to fit correlation structures and correlation matrices in SEM.”
In Search of Underlying Dimensions: The Use (and Abuse) of Factor Analysis in Personality and Social Psychology Bulletin (2002, methodology): “Subsequent research has indicated that this adjustment to the chi-square statistic and the standard errors of the parameters performs well for moderately large samples (i.e., 250 or more cases) (Bentler & Yuan, 1999; Fouladi, 2000).”
Development of the Serious Leisure Inventory and Measure (2008, methodology): “Note: The Satorra-Bentler scaled maximum likelihood was applied to reconfigure the reliance on multivariate normality (Fouladi, 2000 & McDonald & Ho, 2002). a Standardized root mean square (SRMR), root mean square error of approximation (RMSEA) (Steiger, 1990): Values .05 indicate excellent fit. b…”
A New Strategy for Testing Structural Equation Models (2016, background): “…when the H0 is true and noncentral χ2(df, λ) distributed when the H1 is true.3 Concerning normal theory estimation, several conditions might lead to violations of these assumptions, including multivariate nonnormality (e.g., Fouladi, 2000) and large covariance matrices (e.g., Moshagen, 2012).”
Structural equation modeling: strengths, limitations, and misconceptions. (2005, methodology): “Numerous Monte Carlo studies support the usefulness of these corrections (Chou et al. 1991, Curran et al. 1996, Fouladi 2000, Hu et al. 1992) and they are highly recommended when working with nonnormal data.”
A Note on Sample Size and Solution Propriety for Confirmatory Factor Analytic Models (2013, background): “Given its past performance (Fouladi, 2000; Herzog & Boomsma, 2009; Herzog et al., 2007), we anticipated that the Swain (1975) correction would adequately correct ¦(2) values across a broader range of models than previously shown.”
Revisiting the Model Size Effect in Structural Equation Modeling (2018, methodology): “However, researchers later suggested also using the Bartlett-corrected statistic for general SEM 2The empirical means of the chi-square statistics become larger than their expected values (= df). models (Fouladi, 2000).”
Small-Sample Robust Estimators of Noncentrality-Based and Incremental Model Fit (2009, unknown): “However, T MLb more closely follows a chi–square distribution when N is small (Fouladi, 2000; Herzog et al., 2007; Nevitt & Hancock, 2004).”
Multidimensional and Hierarchical Assessment of School Motivation: Cross‐cultural validation (2006, methodology): “The SatorraBentler scaled maximum likelihood procedure was applied to ameliorate reliance on multivariate normality (Fouladi, 2000; McDonald & Ho, 2002).”