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I have four treatments. The variables to study, which are weights and lengths, do not follow a normal distribution and the groups do not have the same variance so the question is: which kind of test should I use?
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@LPC22 wrote:
I have four treatments. The variables to study, which are weights and lengths, do not follow a normal distribution and the groups do not have the same variance so the question is: which kind of test should I use?
It will help if you can tell us what your research question is. Are you testing for identical means or median? A known/suspected difference in a mean or median? Distribution of values?
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Non parametric tests do not rely on the normality of data for validity. Look at the documentation for proc npar1way.
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Heteroscedasticity might not be a real problem here. Variables such as weights and lengths are typically not very skewed. ANOVA is quite robust to mild non-normality and might be perfectly fine. Heteroscedasticity will cost you some power in K-W analysis, but inferences will remain valid. Try both ANOVA and K-W. If you get similar p-values, you're fine. Otherwise, you should look more closely at your data for outliers, subgroups, etc.