Heuristic for using LMM as a two step process: 1) determine whether the slopes of your effects differ, 2) test your main effects.
In order to do 1):
Build the more complex (maximal) model.
Check convergence with a large number of iterations.
Build a reduced model by removing 1 element.
Compare models in descending order: if there is a significant reduction in fit, accept the more complex model; if there is no decrease, continue descending.
If further descending is needed, remove 1 element from the previously reduced model and repeat the process.
Continue until a significant reduction in fit is found.
Pro tip: The suggested reduction order is interactions > main effects.
In order to do 2), one can use Chi square likelihood ratio test. In R, this is what the "summary()" function does.
Pro tip: You can get the effect size (odds ratio) by exponentiating the beta estimate. In R, "exp()" will do it for you.