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

REML criterion at convergence: -6

Scaled residuals: 
     Min       1Q   Median       3Q      Max 
-0.96800 -0.57429  0.00865  0.44440  1.38588 

Random effects:
 Groups                    Name        Variance Std.Dev.
 as.factor(sum.dw$Expt_no) (Intercept) 0.039194 0.19798 
 Residual                              0.005987 0.07738 
Number of obs: 12, groups:  as.factor(sum.dw$Expt_no), 6

Fixed effects:
                         Estimate Std. Error      df t value Pr(>|t|)    
(Intercept)               0.95492    0.08678 5.70600  11.004 4.68e-05 ***
sum.dw$TreatmentFeedback  0.13374    0.04467 5.00000   2.994   0.0303 *  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
            (Intr)
sm.dw$TrtmF -0.257
