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Cain, Meghan K.; Zhang, Zhiyong; Yuan, Ke-Hai – Grantee Submission, 2017
Nonnormality of univariate data has been extensively examined previously (Blanca et al., 2013; Micceri, 1989). However, less is known of the potential nonnormality of multivariate data although multivariate analysis is commonly used in psychological and educational research. Using univariate and multivariate skewness and kurtosis as measures of…
Descriptors: Multivariate Analysis, Probability, Statistical Distributions, Psychological Studies
Yuan, Ke-Hai; Zhang, Zhiyong; Zhao, Yanyun – Grantee Submission, 2017
The normal-distribution-based likelihood ratio statistic T[subscript ml] = nF[subscript ml] is widely used for power analysis in structural Equation modeling (SEM). In such an analysis, power and sample size are computed by assuming that T[subscript ml] follows a central chi-square distribution under H[subscript 0] and a noncentral chi-square…
Descriptors: Statistical Analysis, Evaluation Methods, Structural Equation Models, Reliability
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Yuan, Ke-Hai; Guarnaccia, Charles A.; Hayslip, Bert, Jr. – Educational and Psychological Measurement, 2003
Studied the sample coefficient alpha for each of the five subscales of the Hopkins Symptom Checklist (HSL; L. Derogaitis and others, 1974) in a sample of 419 adults. Findings show that the normal-theory-based distribution has a systematic bias in describing the behavior of the sample coefficient alpha. (SLD)
Descriptors: Adults, Reliability, Statistical Distributions
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Yuan, Ke-Hai; Bentler, Peter M. – Psychometrika, 2002
Developed a sandwich-type covariance matrix to evaluate parameters and provide a rescaled statistic to evaluate a hypothesized general multilevel model. A simulation study with a two-level factor model implies that the rescaled statistic is preferable. (SLD)
Descriptors: Equations (Mathematics), Simulation, Statistical Distributions
Peer reviewed Peer reviewed
Yuan, Ke-Hai; Bentler, Peter M. – Psychometrika, 2002
Examined the asymptotic distributions of three reliability coefficient estimates: (1) sample coefficient alpha; (2) reliability estimate of a composite score following factor analysis; and (3) maximal reliability of a linear combination of item scores after factor analysis. Findings show that normal theory based asymptotic distributions for these…
Descriptors: Estimation (Mathematics), Factor Analysis, Reliability, Robustness (Statistics)
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Yuan, Ke-Hai; Bentler, Peter M. – Psychometrika, 2004
Since data in social and behavioral sciences are often hierarchically organized, special statistical procedures for covariance structure models have been developed to reflect such hierarchical structures. Most of these developments are based on a multivariate normality distribution assumption, which may not be realistic for practical data. It is…
Descriptors: Statistical Analysis, Statistical Inference, Statistical Distributions, Multivariate Analysis
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Yuan, Ke-Hai; Lambert, Paul L.; Fouladi, Rachel T. – Multivariate Behavioral Research, 2004
Mardia's measure of multivariate kurtosis has been implemented in many statistical packages commonly used by social scientists. It provides important information on whether a commonly used multivariate procedure is appropriate for inference. Many statistical packages also have options for missing data. However, there is no procedure for applying…
Descriptors: Social Science Research, Research Methodology, Statistical Distributions, Statistical Analysis
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Yuan, Ke-Hai; Maxwell, Scott – Journal of Educational and Behavioral Statistics, 2005
Retrospective or post hoc power analysis is recommended by reviewers and editors of many journals. Little literature has been found that gave a serious study of the post hoc power. When the sample size is large, the observed effect size is a good estimator of the true power. This article studies whether such a power estimator provides valuable…
Descriptors: Effect Size, Computation, Monte Carlo Methods, Bias
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Yuan, Ke-Hai; Bentler, Peter M.; Chan, Wai – Psychometrika, 2004
Data in social and behavioral sciences typically possess heavy tails. Structural equation modeling is commonly used in analyzing interrelations among variables of such data. Classical methods for structural equation modeling fit a proposed model to the sample covariance matrix, which can lead to very inefficient parameter estimates. By fitting a…
Descriptors: Structural Equation Models, Statistical Distributions, Evaluation Methods, Data Analysis