# Diagnostic plot of glmm model

I am very new to R and I have a problem with the diagnostics of my models...can anyone help me please?

I have run my model:

Modell_ia8 <- glmer(vote~edu1 + age1 + female + eink1 + scltrst + poltrst + links1 +
links1:edu1 + rechts1 + rechts1:edu1 + (1|country),
family = binomial(link = "logit"), data = all)


Then I came across the DHARMa package and did this:

simulationOutput1 <- simulateResiduals(fittedModel = Modell_ia8,n=100)
plot(simulationOutput1)


which gives me this:

I guess the QQ Plot looks good but I do not understand the residual plot at all:

1. Why is it all black?
2. What do the read lines in the middle and at 0 and 1 mean?
• The plot is just cluttered with residuals. Try running it with a small subset of your data to see what is usually looks like. Also: The answer is given in the title of the plot. The dashed line at 0.50 more or less follows the solid line, so there is no trend in residual variance (which is good). – Frans Rodenburg May 27 at 3:54
• Thank you for your answer! But what do the red points at 0 and 1 mean? – Blerta Salihi May 28 at 14:11
• According to the documentation (rdocumentation.org/packages/DHARMa/versions/0.2.4/topics/…), these are marked 'outliers', although I would be surprised not to see any supposed outliers at such a sample size. – Frans Rodenburg May 29 at 12:16