GLMM and two slopes My outcome variable is binomial, and I have 11 independent variables and a time variable. The time variable has different slopes, so I fixed it to time-before and time-after. I used the lme4 package (the glmer function).  I have a random intercept and two random slopes. I created my model like this: 
m3.glmm <- glmer(y ~ timebefore + timeafter + x1 + x2 +...+ x11 +     
(1+timebefore+timeafter|id),
             data = data, family = binomial (link="logit"), nAGQ=3)

When I used this model, I had this error:
Error in updateGlmerDevfun(devfun, glmod$reTrms, nAGQ = nAGQ) : 
  nAGQ > 1 is only available for models with a single, scalar random-effects term

Anyone have a simple explanation of how to fit (or code) this model?
 A: The problem is the number of abscissas, or nodes, you've selected for the Adaptive Gaussian Quadrature (AGQ) approximation of the log-likelihood, specified by nAGQ.  The default value is 1 (equivalent to the Laplacian approximation).  
The glmer function's Details section (page 29 in the lme4 help page) states:

The most reliable approximation for GLMMs is adaptive Gauss-Hermite quadrature, at present implemented only for models with a single scalar random effect.

Limiting the AGQ approximation to single scalar random effects is not a limitation of AGQ, but appears to be a decision made by the lme4 package writers, as noted here by Douglas Bates back in 2011 (relevant piece quoted below):

It may seem that this issue could be put to rest by incorporating an
  adaptive Gauss-Hermite method in glmer ...
  there has been such a method in versions of glmer but only for very
  specific models. We will add it but right now we are concentrating on
  other issues in the development.

So, to get your code to execute, I believe setting nAGQ to 1 would work.
