I ran a logistics mixed effects model with brms as follows:

y ~ x1 * (x2 + … x10) + x11 + (1|ID) + (1|HID)

And obtained a series of outputs from summary() call with the brms model. My question is, are the coefficients provided from summary() taking into account the random intercepts? Because plotting the results via conditional_effects(, re_formula=NULL) gave me a few different results.

I estimated the significance of the independent variables via MAP p-value (the function p_map) and an independent variable yielded p<0.05, but the plot from conditional_effects as mentioned above yielded a plot indicating non-significant difference.