I have data about around 100,000 protests nested within 40 countries and I want to analyze when the claims of a protest are directed at the state, based on action and country level characteristics, using glmer. So, I would like to obtain p-values of both the fixed and random effects. My model looks like this:
targets <- glmer(state ~ ENV + HLH + HRI + LAB + SMO + Capital + (1 + rile + parties + rep + rep2 + gdppc + election| Country), data = df, family = binomial)
After centering and standardizing the predictors, the model converges fine after some hours. However, the output only gives me the Variance & Std.Dev. of the random effects, as well as the correlations among them, which makes sense for most multilevel analyses but not for my purposes. I am not so much interested in the variation of the intercepts and slopes of the model by country, but I rather want to know the direction of the impact of both action and state level characteristics, as well as whether it is significant. The summary of the glmer model gives me already that for the fixed effects. Is there any way I can get the estimates and the p-values for the random effects too?
If this cannot be done with Multilevel Regression Models or lme4 does not provide that output, is there any other model or software that would give such an output?