How to keep the Type I Error Rate in ANOVA if Variances are Heteroscedastic
By K. Moder. 2016
50 citations recorded by the source corpus.
One essential prerequisite to ANOVA is homogeneity of variances in underlying populations. Violating this assumption may lead to an increased type I error rate. The reason for this undesirable effect is due to the calculation of the corresponding F-value. A slightly different test statistic keeps the level ®. The underlying distribution of this alternative method is Hotelling’s T2. As Hotelling’s T2 can be approximated by a Fisher’s F-distribution, this alternative test is very similar to an ordinary analysis of variance.
Subfields: Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/9dab96344217922a31f9dc8a63440bd43ac3e7f9
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In Statistics and Probability
Citations in the corpus
- Comparing Welch ANOVA, a Kruskal-Wallis test, and traditional ANOVA in case of heterogeneity of variance (2015, methodology): “(2) More statistical methods are needed to be examined in this study, like Hotelling’s T(2) test.”