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

REML criterion at convergence: 92.2

Scaled residuals: 
     Min       1Q   Median       3Q      Max 
-0.87172 -0.57306 -0.09893  0.48362  0.99926 

Random effects:
 Groups                    Name        Variance Std.Dev.
 as.factor(sum.la$Expt_no) (Intercept) 1401.68  37.439  
 Residual                                59.69   7.726  
Number of obs: 12, groups:  as.factor(sum.la$Expt_no), 6

Fixed effects:
                         Estimate Std. Error      df t value Pr(>|t|)    
(Intercept)               195.557     15.606   5.208  12.531 4.35e-05 ***
sum.la$TreatmentFeedback   34.538      4.460   5.000   7.743 0.000574 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
            (Intr)
sm.l$TrtmnF -0.143
