I am building a really simple linear model. I want to test if the frass I got over 3 days from butterfly larvae depend upon the food they ate (diet), the butterfly family (the mother line) and subsequent survival (called "survived", obviously larvae which may latter die are likely to show e.g. problems to eat at larval stage). I'm also interested in the two way interactions: diet:family and survived:family. The interaction diet:survived could not be included because there is only one individual in one of the two diet that died.
mod=lm(log(frass.weight)~diet*family+survived+family:survived,data=dat) Anova(mod) # all the variables are significant. summary(mod) #the R2adj is of 0.81 shapiro.test(resid(mod)) # p-value = 0.2389
I have not looked at the variance as I have a small sample size. Only 3 individuals of seven family have been recorded for their frass on both the 2 diets.
All looks nice, except that when I plot the model
plot(mod) I get the following warning:
"Warning messages: 1: not plotting observations with leverage one: 3, 20, 30, 35 "
Is it just a warning or I have a real issue that these points clearly influence the variance?
When I remove these points, the final model I get is simplier:
The residuals are good and the plot works now fine.
Therefore, is the warning about the leverage something to not really consider and my first model should be kept or not? Are my points real outliers?