Title
On the Conditional and Unconditional Type I Error Rates and Power of Tests in Linear Models with Heteroscedastic Errors
Document Type
Article
Publication Date
3-7-2019
Department 1
Management
Abstract
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.
Copyright Note
This is the publisher's version of the work. This publication appears in Gettysburg College's institutional repository by permission of the copyright owner for personal use, not for redistribution.
DOI
10.22237/jmasm/1551966828
Version
Version of Record
Recommended Citation
Rosopa, P. J., Brawley, A. M., Atkinson, T. P., & Robertson, S. A. (2018). On the conditional and unconditional Type I error rates and power of tests in linear models with heteroscedastic errors. Journal of Modern Applied Statistical Methods, 17(2), eP2647. doi: 10.22237/jmasm/1551966828