Power of the t test for normal and mixed normal distributions

Marilyn Thompson; Samuel B. Green; Yi Hsin Chen; Shawn Stockford; Wen Juo Lo

doi:10.22237/jmasm/1130804640

Power of the t test for normal and mixed normal distributions

Marilyn Thompson, Samuel B. Green, Yi Hsin Chen, Shawn Stockford, Wen Juo Lo

Research output: Contribution to journal › Review article › peer-review

1 Scopus citations

Abstract

Previous research suggests that the power of the independent-samples t test decreases when population distributions are mixed normal rather than normal, and that robust methods have superior power under these conditions. However, under some conditions, the power for the independent-samples t test can be greater when the population distributions for the independent groups are mixed normal rather than normal. The implications of these results are discussed.

Original language	English (US)
Pages (from-to)	591-597
Number of pages	7
Journal	Journal of Modern Applied Statistical Methods
Volume	4
Issue number	2
DOIs	https://doi.org/10.22237/jmasm/1130804640
State	Published - Nov 2005

Keywords

Mixed normal
Power
t test

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.22237/jmasm/1130804640

Cite this

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abstract = "Previous research suggests that the power of the independent-samples t test decreases when population distributions are mixed normal rather than normal, and that robust methods have superior power under these conditions. However, under some conditions, the power for the independent-samples t test can be greater when the population distributions for the independent groups are mixed normal rather than normal. The implications of these results are discussed.",

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Power of the t test for normal and mixed normal distributions

Abstract

Keywords

ASJC Scopus subject areas

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