Generalized linear mixed model fit by maximum likelihood (Adaptive
  Gauss-Hermite Quadrature, nAGQ = 9) [glmerMod]
 Family: binomial  ( logit )
Formula: cbind(clicks, n - clicks) ~ arm + (1 | item)
   Data: dat
Control: glmerControl(optimizer = "bobyqa", optCtrl = list(maxfun = 1e+05))

      AIC       BIC    logLik -2*log(L)  df.resid 
   1902.8    1916.0    -948.4    1896.8       597 

Scaled residuals: 
     Min       1Q   Median       3Q      Max 
-2.56576 -0.60743 -0.07019  0.40270  2.44223 

Random effects:
 Groups Name        Variance Std.Dev.
 item   (Intercept) 1.584    1.259   
Number of obs: 600, groups:  item, 300

Fixed effects:
             Estimate Std. Error z value Pr(>|z|)    
(Intercept) -6.258742   0.075676  -82.70   <2e-16 ***
arm          0.186280   0.006152   30.28   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
    (Intr)
arm -0.044