Plotting random effects in mixed-effects model

Question

I have tried reading the documentation in sjPlot but couldn't figure it out. In a multilevel / hierarchical / mixed-effect model, ran with lme4 in R, the summary() output give an estimated variance and standard deviation for each random effect. I wanted to plot this variance by level of one of my random intercepts (stimuli), to see differences across stimuli: for the model:

m.EDA = lmer(EDA_cs ~ Cond * Time_sd + (1|Participant) + (1|Stim),
                data= phys)

I used the following code from sjPlot to visualize the variance of each level of my random intercept Stim:

plot_model(m.EDA, type = "re")

The question... how come the x-axis (which I thought represents the variance) has negative values?

Variance can't be negative, which makes me think that the x-axis in this plot is plotting something else other than the random effects (which is what the documentation suggests: https://strengejacke.github.io/sjPlot/reference/plot_model.html)

Answer 1

It is plotting the random effects, not the variances of anything. This is what the manual says:

plot_model() creates plots from regression models, either estimates (as so-called forest or dot whisker plots) or marginal effects.

and

type = "re"

For mixed effects models, plots the random effects.

also, you write:

summary() output give an estimated variance and standard deviation for each random effect.

which is correct. If you want to plot those variances against something else, you will have to capture them. You can, I believe, find the right term from using str() with the name of your model in the parens, and then use that to create a plot.