I am running a linear mixed model and want to check its assumptions. The model I run is comparing if males and females behave differently over time (timeclass=1,2,3,4):
x <- lme(response ~ timeclass*sex, random = ~ 1|subject, method="ML", data=dat)
The code to create the plots:
plot(x) plot(x, response ~ fitted(.) | sex, abline = c(0,1)) qqnorm(x,~resid(.)|timeclass) qqnorm(x,~resid(.)|sex) hist((resid(x) - mean(resid(x), na.rm=T)) / sd(resid(x), na.rm=T), freq=F); curve(dnorm, add = TRUE)
This is the output I get:
The plots except the residual plot seem to show that there seems to be a linear relationship between the fitted values per sex and the response and that the errors are relatively normally distributed in both sex and across the four time classes. However, the first plot has a very clear diamond shape, almost so clear that it seems values are cut off in the four triangular angles.
Can someone help me understand what is going on and what this means? Is the model I run valid based on the plots for assumptions?