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Direct linkQu, Wen; Liu, Haiyan; Zhang, Zhiyong – Grantee Submission, 2020
In social and behavioral sciences, data are typically not normally distributed, which can invalidate hypothesis testing and lead to unreliable results when being analyzed by methods developed for normal data. The existing methods of generating multivariate non-normal data typically create data according to specific univariate marginal measures…
Descriptors: Social Science Research, Multivariate Analysis, Statistical Distributions, Monte Carlo Methods
Qu, Wen; Liu, Haiyan; Zhang, Zhiyong – Grantee Submission, 2020
In social and behavioral sciences, data are typically not normally distributed, which can invalidate hypothesis testing and lead to unreliable results when being analyzed by methods developed for normal data. The existing methods of generating multivariate non-normal data typically create data according to specific univariate marginal measures…
Descriptors: Social Science Research, Statistical Distributions, Multivariate Analysis, Monte Carlo Methods
Bishara, Anthony J.; Hittner, James B. – Educational and Psychological Measurement, 2015
It is more common for educational and psychological data to be nonnormal than to be approximately normal. This tendency may lead to bias and error in point estimates of the Pearson correlation coefficient. In a series of Monte Carlo simulations, the Pearson correlation was examined under conditions of normal and nonnormal data, and it was compared…
Descriptors: Research Methodology, Monte Carlo Methods, Correlation, Simulation
Lee, Sik-Yum; Xia, Ye-Mao – Psychometrika, 2006
By means of more than a dozen user friendly packages, structural equation models (SEMs) are widely used in behavioral, education, social, and psychological research. As the underlying theory and methods in these packages are vulnerable to outliers and distributions with longer-than-normal tails, a fundamental problem in the field is the…
Descriptors: Maximum Likelihood Statistics, Statistical Distributions, Structural Equation Models, Robustness (Statistics)
