In the case of lm(), the result is the number of coefficients For a linear mixed model fit with lmer() there are 3 options. "edf": effective degrees of freedom as computed by sum of diagonal values of the hat matrix return by lmer() . "countLevels", returns the number of fixed effects + number of levels in random effects + 1 for residual variance term. This treats each level of a random effect as a parameter. "lme4", returns number of fixed effects + number of variance components. Here a random effect with 10 levels is only counted as 1 parameter. This tends to underpenalize.
nparam(object, nparamsMethod = c("edf", "countLevels", "lme4"))number of parameters