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

REML criterion at convergence: -73.6

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-1.2000 -0.4608 -0.1381  0.5152  0.9612 

Random effects:
 Groups                    Name        Variance  Std.Dev.
 as.factor(der.dw$Expt_no) (Intercept) 5.007e-05 0.007076
 Residual                              6.331e-06 0.002516
Number of obs: 12, groups:  as.factor(der.dw$Expt_no), 6

Fixed effects:
                         Estimate Std. Error       df t value Pr(>|t|)    
(Intercept)              0.038111   0.003066 5.592539  12.430 2.76e-05 ***
der.dw$TreatmentFeedback 0.008124   0.001453 5.000000   5.592  0.00252 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
            (Intr)
dr.dw$TrtmF -0.237
