Dear researchers;
I know that one of the prerequisites of parametric tests is that variances must show homogeneity. However, if the variances of my data are not homogeneous, the tests to be used in cases where variances are not homogeneous in the post hoc part of the anova test; Is there any criticism for a research I made using Tamhane's T2, Dunnett's T3, Games Howell and Dunnett's C tests?
Best wishes.
Hello dear Ariel Lindorff
Thank you for your attention and time. On this topic, I know that the sample count of the groups should be n> 30. Other than that, I could not find any information regarding the number of other samples. The related link also includes the topics you mentioned. However, I could not see any numbers. If you have sampling information other than these, can you please share
Best Regards...
It really depends on some other aspects. Some texts make a blanket statement that ANOVA is robust to violations of the homogeneity of variance assumption, but depending on whether sample sizes are equal, the overall sample size and the extent of the violation, etc., this may be more or less the case. You may want to have a look at this discussion: https://www.researchgate.net/post/Is_ANOVA_robust_and_to_what_extent
Hello dear Ariel Lindorff
Thank you for your attention and time. On this topic, I know that the sample count of the groups should be n> 30. Other than that, I could not find any information regarding the number of other samples. The related link also includes the topics you mentioned. However, I could not see any numbers. If you have sampling information other than these, can you please share
Best Regards...
The ANOVA is based on the law of total variance, where the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether two or more population means are equal, and therefore generalizes the t-test beyond two means. https://en.m.wikipedia.org/wiki/Analysis_of_variance
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