Hello,
with 4 different linear mixed models (continuous dependent) I find that my
residuals do not follow the normality assumption (significant Shapiro-Wilk
with values equal/higher than 0.976; sample sizes 750 or 1200). I find,
instead, that my residuals are really well fitted by a t distribution with
dofs' ranging, in the different datasets, from 5 to 12.
Should this be considered such a severe violation of the normality
assumption as to make model-based inferences invalid?
Thanks a lot,
Bruno
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