I'm looking for some advice as to how to best show graphically the results of my GLMER model. In my model I try to explain Y (a count variable for a business related outcome), in terms of X, Xsquared, and FirmSize, with random effects for Industry/Firm, by year. My results, here below, appear to show a positive relationship between Y and X, but with an inverted-U shape (the Xsquared term is negative and significant). Ideally I would like to obtain a graph showing this inverted-U relationship, but I'm clueless as to how to move forward (I'm relatively new to R and GLMER models).

My GLMER model:

model <- glmer(Y ~ Year + X + Xsquared + Size + (1 + Year|Industry/Firm), data = mydata, family = poisson)

My results:

Random effects:
 Groups        Name        Variance  Std.Dev. Corr
 Firm:Industry (Intercept) 5.840e-01 0.764205     
               cYear       5.546e-03 0.074474 0.38
 Industry      (Intercept) 8.243e-05 0.009079     
               cYear       2.011e-05 0.004485 0.54
Number of obs: 436, groups:  Firm:Industry, 109; Industry, 37

Fixed effects:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept) -2.87753    0.47970  -5.999 1.99e-09 ***
cYear       -0.02303    0.02778  -0.829    0.407    
X            1.32358    0.33632   3.935 8.30e-05 ***
Xsquared    -0.27628    0.14217  -1.943    0.049 *  
FirmSize     0.31789    0.04989   6.371 1.87e-10 ***

1 Answer 1


sjPlot package is awesome for plotting graphs for GLMER Model.


You can use the sjPlot package to plot the model. I think that you can do

sjp.glmer(model, type = "pred", vars = c("X", "FirmSize"))

to plot the way you want!


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