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2 votes

Addressing Non-Normality of Random Effects in Linear Mixed Model

The quantiles on the x-axis represent what is often called 'theoretical quantiles' in QQ-plots; the distribution of quantiles in a standard normal distribution, in this case. The quantiles on the y-...
Marjolein Fokkema's user avatar
1 vote

Anova model assumptions. How to go by?

Why do you think you are "going wrong" at all? Sometimes, there isn't homongeneity of variances. What you should do about it depends on various things. You could look at some plots. Yes, ...
Peter Flom's user avatar
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3 votes

Normality assumption n=48

From my understanding, more important than normally distributed variables (prior to modelling) is the normality of model residuals (evaluated from a Q-Q plot, for example) after your model has been ...
sylvesterspot's user avatar
0 votes

Does shapiro.test() automatically work out residuals on your data?

No, nor should it. Residuals only exist once you've defined a model that makes predictions, so you first have to define a such a model, probably a linear regression if you're interested in normal ...
Dave's user avatar
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