On the Conditional and Unconditional Type I Error Rates and Power of Tests in Linear Models with Heteroscedastic Errors

被引：6

作者：

Rosopa, Patrick ^{[1
]}

Brawley, Alice M. ^{[2
]}

Atkinson, Theresa P. ^{[3
]}

Robertson, Stephen ^{[1
]}

机构：

[1] Clemson Univ, Clemson, SC 29631 USA

[2] Gettysburg Coll, Gettysburg, PA 17325 USA

[3] Allstate, Dallas, TX USA

来源：

JOURNAL OF MODERN APPLIED STATISTICAL METHODS | 2018年 / 17卷 / 02期

关键词：

Heterogeneity of variance; heteroscedasticity; linear models; Behrens-Fisher problem;

D O I：

10.22237/jmasm/1551966828

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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.

引用

页数：25

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