Article
A Note on Using the Nonparametric Levene Test When Population Means Are Unequal Public Deposited
Downloadable Content
Download PDF
https://scholar.colorado.edu/concern/articles/3t945r44q
- Abstract
- This computer simulation study evaluates the robustness of the nonparametric Levene test of equal variances (Nordstokke & Zumbo, 2010) when sampling from populations with unequal (and unknown) means. Testing for population mean differences when population variances are unknown and possibly unequal is often referred to as the Behrens-Fisher problem when the populations are normally distributed, and the generalized Behrens-Fisher problem when the populations are non-normal. The nonparametric Levene test was developed to overcome reductions in power of the original Levene test of equal variances in the case of the generalized Behrens-Fisher problem. We use a Monte Carlo computer simulation to demonstrate that sampling from populations with unequal and unknown means can lead to incorrect (either inflated or decreased) Type I error rates of the nonparametric Levene test. Centering samples using ei ther sample means or medians does not correct the Type I error rates. This note is intended to make applied researchers aware of this problem when testing for the equality of population variances with the NPL test and in general.
- Creator
- Date Issued
- 2018-01-01
- Academic Affiliation
- Journal Title
- Journal Issue/Number
- 13
- Journal Volume
- 23
- Subject
- Last Modified
- 2019-12-05
- Resource Type
- Rights Statement
- ISSN
- 1531-7714
- Language
Relationships
Items
Thumbnail | Title | Date Uploaded | Visibility | Actions |
---|---|---|---|---|
aNoteOnUsingTheNonparametricLeveneTestWhenPopulationMea.pdf | 2019-12-05 | Public | Download |