Linear mixed model fit by REML. t-tests use Satterthwaite's method [
lmerModLmerTest]
Formula: rwc$rwc ~ rwc$Treatment + (1 | as.factor(rwc$Expt_no))

REML criterion at convergence: -47.7

Scaled residuals: 
     Min       1Q   Median       3Q      Max 
-1.33698 -0.34848  0.06959  0.32783  1.21858 

Random effects:
 Groups                 Name        Variance  Std.Dev.
 as.factor(rwc$Expt_no) (Intercept) 6.511e-04 0.025516
 Residual                           8.678e-05 0.009316
Number of obs: 12, groups:  as.factor(rwc$Expt_no), 6

Fixed effects:
                      Estimate Std. Error       df t value Pr(>|t|)    
(Intercept)           0.844919   0.011089 5.622377  76.192 1.08e-09 ***
rwc$TreatmentFeedback 0.002139   0.005378 5.000000   0.398    0.707    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
            (Intr)
rwc$TrtmntF -0.243
