Open Access. Powered by Scholars. Published by Universities.®
Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 3 of 3
Full-Text Articles in Social and Behavioral Sciences
Probability Coverage And Interval Length For Welch’S And Yuen’S Techniques: Shift In Location, Change In Scale, And (Un)Equal Sizes, S. Jonathan Mends-Cole
Probability Coverage And Interval Length For Welch’S And Yuen’S Techniques: Shift In Location, Change In Scale, And (Un)Equal Sizes, S. Jonathan Mends-Cole
Journal of Modern Applied Statistical Methods
Coverage for Welch’s technique was less than the confidence-level when size was inversely proportional to variance and skewness was extreme. Under negative kurtosis, coverage for Yuen’s technique was attenuated. Under skewness and heteroscedasticity, coverage for Yuen’s technique was more accurate than Welch’s technique.
Operating Characteristics Of The Dif Mimic Approach Using Jöreskog’S Covariance Matrix With Ml And Wls Estimation For Short Scales, Michaela N. Gelin, Bruno D. Zumbo
Operating Characteristics Of The Dif Mimic Approach Using Jöreskog’S Covariance Matrix With Ml And Wls Estimation For Short Scales, Michaela N. Gelin, Bruno D. Zumbo
Journal of Modern Applied Statistical Methods
Type I error rate of a structural equation modeling (SEM) approach for investigating differential item functioning (DIF) in short scales was studied. Muthén’s SEM model for DIF was examined using a covariance matrix (Jöreskog, 2002). It is conditioned on the latent variable, while testing the effect of the grouping variable over-and-above the underlying latent variable. Thus, it is a multiple-indicators, multiple-causes (MIMIC) DIF model. Type I error rates were determined using data reflective of short scales with ordinal item response formats typically found in the social and behavioral sciences. Results indicate Type I error rates for the DIF MIMIC model, …
Practical Unit-Root Analysis Using Information Criteria: Simulation Evidence, Kosei Fukuda
Practical Unit-Root Analysis Using Information Criteria: Simulation Evidence, Kosei Fukuda
Journal of Modern Applied Statistical Methods
The information-criterion-based model selection method for detecting a unit root is proposed. The simulation results suggest that the performances of the proposed method are usually comparable to and sometimes better than those of the conventional unit-root tests. The advantages of the proposed method in practical applications are also discussed.