Understanding and reporting the output of a lmer

Hierarchical and Mixed Effects Models in R

Richard Erickson

Data Scientist

The model

out <- lmer(BirthRate ~ AverageAgeofMother +
                        (AverageAgeofMother | State), 
            data = county_births_data)

Print

out # print(out) is what R is calling

Linear mixed model fit by REML ['lmerMod']
Formula: BirthRate ~ AverageAgeofMother + (AverageAgeofMother | State)
   Data: county_births_data
REML criterion at convergence: 2337.506
Random effects:
 Groups   Name               Std.Dev. Corr 
 State    (Intercept)        8.8744        
          AverageAgeofMother 0.2912   -0.99
 Residual                    1.6742        
Number of obs: 578, groups:  State, 50
Fixed Effects:
       (Intercept)  AverageAgeofMother  
           27.2204             -0.5235

Summary

summary(out)

#    ...
Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-2.8399 -0.5966 -0.1133  0.5228  5.1815 

Random effects:
 Groups   Name               Variance Std.Dev. Corr 
 State    (Intercept)        78.75478 8.8744        
          AverageAgeofMother  0.08482 0.2912   -0.99
 Residual                     2.80306 1.6742        
Number of obs: 578, groups:  State, 50

Fixed effects:
                   Estimate Std. Error t value
(Intercept)        27.22041    2.41279  11.282
AverageAgeofMother -0.52347    0.08302  -6.306

Correlation of Fixed Effects:
            (Intr)
AvrgAgfMthr -0.997

Extracting fixed-effects estimates

fixef(out)

       (Intercept) AverageAgeofMother 
        34.5756764         -0.7556129

Extracting fixed-effects confidence intervals

confint(out)

    Computing profile confidence intervals ...
                            2.5 %    97.5 %
    .sig01              0.9458700  1.612440 
    .sigma              1.6091447  1.815929
    (Intercept)        24.0121843 31.146685
    AverageAgeofMother -0.6605319 -0.411231

Extracting random-effects

ranef(out)

    $State
    AK  1.03549148
    AL -0.52500819
    AR  0.48023356
    AZ -1.04094123
    CA  0.50530542
    CO  0.09585582
    CT -1.91638101
    DC  0.96029531
    DE -0.38938118
    FL -1.87440508
    GA  0.39776424
    #...

Reporting lmer output

Know your audience
Figures
Table
In-text

Let's practice!

Hierarchical and Mixed Effects Models in R