Hi all was hoping of a little bit of advice here.

As far as I am aware, 4 of the assumptions of a mixed effects mode are:

-Normally distributed residuals

-Heteroskedasticity of residuals

-Normally distributed residuals of the random effects potion of the model (i.e. Blups)

-Heteroskedasicity of the random effects potion of the model (i.e. Blups)

Is this correct? If so, then how would you test for it in R?

I am struggling the most with the last one, as I can get qqnorm plots for looking at normality. I have been using the package 'nlme' -

'''model1<-lme(Outcome~Height*Weight,data=data,random=~1|Individual,method="REML")'''

'''residual_1<-fitted(model1,type="pearson")'''

'''hist(residual_1)'''

'''qqnorm(residual_1)""

I think I also figured how to plot the fitted residuals against the he fitted residuals against the residuals to check heteroskedasicit

'''fits<-fitted(model1)'''

'''plot(residual_1~fits)'''

or

"plot(model1)"

Is this correct? What would this look like if the assumption of homoskedasicity was met?

And how do I get R to run this in the random effect residuals instead?

Many thanks!