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Appraisal of the Homogeneity of Error Variance Assumption and Alternatives to Multiple Regression for Estimating Moderating Effects of Categorical Variables
被引:45
|作者:
Aguinis, Herman
[1
]
Petersen, Scott A.
[2
]
Pierce, Charles A.
[3
]
机构:
[1] Univ Colorado, Management, Denver, CO 80217 USA
[2] US Mil Acad, Org Behav, West Point, NY USA
[3] Montana State Univ, Social & Ind Org Psychol, Bozeman, MT USA
关键词:
D O I:
10.1177/109442819924001
中图分类号:
B849 [应用心理学];
学科分类号:
040203 ;
摘要:
Homogeneity of within-subgroup error variance is a necessary condition for using multiple regression to estimate moderating effects of categorical variables. A 12-year review of Academy of Management Journal, Journal of Applied Psychology, and Personnel Psychology indicates that the assumption is violated in 40% to 60% of cases. The authors reanalyze published research to illustrate how violating the assumption may change substantive conclusions. To remedy this situation, they develop and present a computer program (i.e., ALTMMR) that (a) assesses whether a data set suffers from heterogeneity of error variance and (b) computes alternative inferential statistics to the traditional multiple regression F test when heterogeneity exists. ALTMMR, which can also be used as a teaching tool, was written in Java and is executable using an Internet Web browser or as a stand-alone application.
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页码:315 / 339
页数:25
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