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Full-Text Articles in Statistics and Probability

An Assessment Of The Performances Of Several Univariate Tests Of Normality, James Olusegun Adefisoye Mar 2015

An Assessment Of The Performances Of Several Univariate Tests Of Normality, James Olusegun Adefisoye

FIU Electronic Theses and Dissertations

The importance of checking the normality assumption in most statistical procedures especially parametric tests cannot be over emphasized as the validity of the inferences drawn from such procedures usually depend on the validity of this assumption. Numerous methods have been proposed by different authors over the years, some popular and frequently used, others, not so much. This study addresses the performance of eighteen of the available tests for different sample sizes, significance levels, and for a number of symmetric and asymmetric distributions by conducting a Monte-Carlo simulation. The results showed that considerable power is not achieved for symmetric distributions when …


Meta-Analysis Of Type I Error Rates For Detecting Differential Item Functioning With Logistic Regression And Mantel-Haenszel In Monte Carlo Studies, Eva Van De Water Ph. D. Jul 2014

Meta-Analysis Of Type I Error Rates For Detecting Differential Item Functioning With Logistic Regression And Mantel-Haenszel In Monte Carlo Studies, Eva Van De Water Ph. D.

Eva Van De Water

Differential item functioning (DIF) occurs when individuals from different groups who have equal levels of a latent trait fail to earn commensurate scores on a testing instrument. Type I error occurs when DIF-detection methods result in unbiased items being excluded from the test while a Type II error occurs when biased items remain on the test after DIF-detection methods have been employed. Both errors create potential issues of injustice amongst examinees and can result in costly and protracted legal action. The purpose of this research was to evaluate two methods for detecting DIF: logistic regression (LR) and Mantel-Haenszel (MH).

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