Equal variances [🇷 for BE/BA]

posted by Helmut Homepage – Vienna, Austria, 2010-04-26 14:55 (5532 d 17:25 ago) – Posting: # 5231
Views: 62,421

Dear D. Labes,

❝ ❝ boxplot(lnAUC0t ~ drug, col="lightgray", yl)

❝ Ooops: > Error in eval(expr, envir, enclos) : object 'yl' not found


Shit! Of course instead of
boxplot(lnAUC0t ~ drug, col="lightgray", yl)
use
boxplot(lnAUC0t ~ drug, col="lightgray")

❝ A very fine example of hetero-scedasticity and eventually of non-normality :cool:.


Maybe. But we are not allowed to test that anyhow. ;-)
For non-bears, here is the dataset (imbalanced, 27 subjects) for download.

❝ With t-test assuming equal variances one gets:

         Point Estimate   CL90 lower   CL90 upper

❝ Ratio           101.61        83.31       123.92


❝ Homework: Compare this to the results of lm() or lme() in this thread

:-D.


Yes, sure. What else? That's why we should avoid it.

❝ To repeat my question above: Any hint for more then 2 groups?

❝ Very seldom for BE studies, I know. But according to Murphy's law I have to deal with a 3-parallel-group design already tomorrow.


I went through the literature last week and did not come to a conclusion yet. Essentially there are two approaches:So if you want to get an opinion for tomorrow: I would go with Welch-tests, because ANOVA (or lm and lme) assume homoscedasticity. See also:

Moser BK, Stevens GR. Homogeneity of variance in the two-sample means test. Amer Statist. 1992;46:19-21.


Depending on the study’s target I would consider a Bonferroni-adjustment (that’s even the original application: independent tests).

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