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

REML criterion at convergence: -31.3

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-1.2090 -0.4323 -0.1050  0.4319  1.2890 

Random effects:
 Groups                    Name        Variance  Std.Dev.
 as.factor(der.fw$Expt_no) (Intercept) 0.0069130 0.08314 
 Residual                              0.0002272 0.01507 
Number of obs: 12, groups:  as.factor(der.fw$Expt_no), 6

Fixed effects:
                         Estimate Std. Error       df t value Pr(>|t|)    
(Intercept)              0.258002   0.034497 5.161627   7.479 0.000587 ***
der.fw$TreatmentFeedback 0.052132   0.008702 5.000000   5.990 0.001859 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
            (Intr)
dr.fw$TrtmF -0.126
