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

REML criterion at convergence: 94.7

Scaled residuals: 
     Min       1Q   Median       3Q      Max 
-0.98338 -0.46647 -0.09292  0.77353  0.86753 

Random effects:
 Groups                     Name        Variance Std.Dev.
 as.factor(sum.sla$Expt_no) (Intercept) 1057     32.52   
 Residual                                125     11.18   
Number of obs: 12, groups:  as.factor(sum.sla$Expt_no), 6

Fixed effects:
                          Estimate Std. Error      df t value Pr(>|t|)    
(Intercept)                206.730     14.037   5.556  14.727 1.15e-05 ***
sum.sla$TreatmentFeedback    8.542      6.455   5.000   1.323    0.243    
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
            (Intr)
sm.sl$TrtmF -0.230
