Open Access. Powered by Scholars. Published by Universities.®

Social and Behavioral Sciences Commons

Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics

Journal of Modern Applied Statistical Methods

Heteroscedasticity

2019

Articles 1 - 2 of 2

Full-Text Articles in Social and Behavioral Sciences

On The Conditional And Unconditional Type I Error Rates And Power Of Tests In Linear Models With Heteroscedastic Errors, Patrick J. Rosopa, Alice M. Brawley, Theresa P. Atkinson, Stephen A. Robertson Mar 2019

On The Conditional And Unconditional Type I Error Rates And Power Of Tests In Linear Models With Heteroscedastic Errors, Patrick J. Rosopa, Alice M. Brawley, Theresa P. Atkinson, Stephen A. Robertson

Journal of Modern Applied Statistical Methods

Preliminary tests for homoscedasticity may be unnecessary in general linear models. Based on Monte Carlo simulations, results suggest that when testing for differences between independent slopes, the unconditional use of weighted least squares regression and HC4 regression performed the best across a wide range of conditions.


Robust Ancova, Curvature, And The Curse Of Dimensionality, Rand Wilcox Mar 2019

Robust Ancova, Curvature, And The Curse Of Dimensionality, Rand Wilcox

Journal of Modern Applied Statistical Methods

There is a substantial collection of robust analysis of covariance (ANCOVA) methods that effectively deals with non-normality, unequal population slope parameters, outliers, and heteroscedasticity. Some are based on the usual linear model and others are based on smoothers (nonparametric regression estimators). However, extant results are limited to one or two covariates. A minor goal here is to extend a recently-proposed method, based on the usual linear model, to situations where there are up to six covariates. The usual linear model might provide a poor approximation of the true regression surface. The main goal is to suggest a method, based on …