First confidence rating
## $Exam
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Confidence ~ Exam + (1 | id)
## Data: grades.nomiss.mod
##
## REML criterion at convergence: 14731.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -2.85773 -0.60222 0.06379 0.60927 3.11544
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 279.7 16.72
## Residual 292.8 17.11
## Number of obs: 1647, groups: id, 528
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 61.0045 1.0918 1178.7753 55.873 <2e-16 ***
## Exam2 -0.1146 1.1549 1178.5228 -0.099 0.921
## Exam3 1.0977 1.1715 1182.7624 0.937 0.349
## Exam4 -1.2043 1.3472 1217.7833 -0.894 0.372
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Exam2 Exam3
## Exam2 -0.526
## Exam3 -0.518 0.500
## Exam4 -0.454 0.441 0.434
Second confidence rating
## $Exam
## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Confidence ~ Exam + (1 | id)
## Data: grades.nomiss.mod
##
## REML criterion at convergence: 8234.3
##
## Scaled residuals:
## Min 1Q Median 3Q Max
## -3.3424 -0.5681 0.0129 0.5665 2.3939
##
## Random effects:
## Groups Name Variance Std.Dev.
## id (Intercept) 333.8 18.27
## Residual 258.0 16.06
## Number of obs: 926, groups: id, 307
##
## Fixed effects:
## Estimate Std. Error df t value Pr(>|t|)
## (Intercept) 54.3418 1.4220 583.6833 38.216 <2e-16 ***
## Exam2 0.4676 1.4039 644.7823 0.333 0.739
## Exam3 0.9923 1.4083 644.6669 0.705 0.481
## Exam4 0.8582 1.8850 670.9568 0.455 0.649
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Correlation of Fixed Effects:
## (Intr) Exam2 Exam3
## Exam2 -0.468
## Exam3 -0.466 0.486
## Exam4 -0.349 0.365 0.360