Tests for homogeneity of variances using robust weighted likelihood estimates
- Authors
- Sarkar, S; Kim, C; Basu, A
- Issue Date
- 1999
- Publisher
- AKADEMIE VERLAG GMBH
- Keywords
- common variance; Brown-Forsythe's test; Hellinger distance; Levene's test; power; robustness; simulation; weighted likelihood estimation
- Citation
- BIOMETRICAL JOURNAL, v.41, no.7, pp 857 - 871
- Pages
- 15
- Journal Title
- BIOMETRICAL JOURNAL
- Volume
- 41
- Number
- 7
- Start Page
- 857
- End Page
- 871
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/47481
- DOI
- 10.1002/(SICI)1521-4036(199911)41:7<857::AID-BIMJ857>3.3.CO;2-O
- ISSN
- 0323-3847
1521-4036
- Abstract
- The classical normal-theory tests for testing the null hypothesis of common variance and the classical estimates of scale have long been known to be quite nonrobust to even mild deviations from normality assumptions for moderate sample sizes. LEVENE (1960) suggested a one-way ANOVA type statistic as a robust test. BROWN and FORSYTHE (1974) considered a modified version of Levene's test by replacing the sample means with sample medians as estimates of population locations, and their rest is computationally the simplest among the three tests recommended by CONOVER, JOHNSON, and JOHNSON (1981) in terms of robustness and power. In this paper a new robust and powerful test for homogeneity of variances is proposed based on a modification of Levene's test using the weighted likelihood estimates (MARKATOU, BASU, and LINDSAY, 1996) of the population means. For two and three populations the proposed test using the Hellinger distance based weighted likelihood estimates is observed to achieve better empirical level and power than Brown-Forsythe's test in symmetric distributions having a thicker tail than the normal, and higher empirical power in skew distributions under the use of F distribution critical values.
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Collections - College of Business & Economics > Department of Applied Statistics > 1. Journal Articles
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