title: Trouble with GLMM with glmer in R: Error in pwrssUpdate...halvings failed to reduce deviance in pwrssUpdate
body: <p>Here's a snipped of randomly selected data from my full dataframe:</p>
  
  <pre><code>canopy&lt;-structure(list(Stage = structure(c(6L, 5L, 3L, 6L, 7L, 5L, 4L, 
  7L, 2L, 7L, 5L, 1L, 1L, 4L, 3L, 6L, 5L, 7L, 4L, 4L), .Label = c("milpa", 
  "robir", "jurup che", "pak che kor", "mehen che", "nu kux che", 
  "tam che"), class = c("ordered", "factor")), ID = c(44L, 34L, 
  18L, 64L, 54L, 59L, 28L, 51L, 11L, 56L, 33L, 1L, 7L, 25L, 58L, 
  48L, 36L, 51L, 27L, 66L), Sample = c(4L, 2L, 2L, 10L, 6L, 9L, 
  4L, 3L, 3L, 8L, 1L, 1L, 7L, 1L, 10L, 8L, 4L, 3L, 3L, 10L), Subsample = c(2L, 
  3L, 4L, 3L, 2L, 1L, 3L, 2L, 4L, 3L, 1L, 3L, 2L, 4L, 1L, 1L, 3L, 
  1L, 1L, 4L), Size..ha. = c(0.5, 0.5, 0.5, 0.5, 6, 0.5, 0.5, 0.25, 
  0.5, 6, 1, 1, 0.5, 2, 1, 0.5, 1, 0.25, 0.5, 2), Avg.Subsample.Canopy = c(94.8, 
  94.8, 97.92, 96.88, 97.14, 92.46, 93.24, 97.4, 25.64, 97.4, 94.8, 
  33.7, 13.42, 98.18, 85.44, 96.36, 97.4, 95.58, 85.7, 92.2), dec = c(0.948, 
  0.948, 0.9792, 0.9688, 0.9714, 0.9246, 0.9324, 0.974, 0.2564, 
  0.974, 0.948, 0.337, 0.1342, 0.9818, 0.8544, 0.9636, 0.974, 0.9558, 
  0.857, 0.922)), .Names = c("Stage", "ID", "Sample", "Subsample", 
  "Size..ha.", "Avg.Subsample.Canopy", "dec"), row.names = c(693L, 
  537L, 285L, 1017L, 853L, 929L, 441L, 805L, 173L, 889L, 513L, 
  9L, 101L, 397L, 913L, 753L, 569L, 801L, 417L, 1053L), class = "data.frame")
  </code></pre>
  
  <p>I am trying to code a GLMM of dec as a function of Stage and Size..ha.
  The GLMM is necessary because each row represents a point Subsample measured within a larger Sample area.  I am also using a binomial distribution given dec are proportional data.</p>
  
  <p>I tried the model:</p>
  
  <pre><code>canopy.binomial.mod&lt;-glmer(dec~Stage*Size..ha.+(1|Sample),family="binomial",data=canopy)
  summary(canopy.binomial.mod)
  </code></pre>
  
  <p>but get the error:</p>
  
  <blockquote>
    <p>Error in pwrssUpdate(pp, resp, tol = tolPwrss, GQmat = GQmat, compDev
    = compDev, : (maxstephalfit) PIRLS step-halvings failed to reduce deviance in pwrssUpdate</p>
  </blockquote>
  
  <p>I've seen online that this can be a result of needing to scale a predictor variable, so I tried:</p>
  
  <pre><code>cs. &lt;- function(x) scale(x,scale=TRUE,center=TRUE)    
  canopy.binomial.mod&lt;-glmer(dec~Stage*cs.(Size..ha.)+(1|Sample),family="binomial",data=canopy.rmna)
  summary(canopy.binomial.mod)
  </code></pre>
  
  <p>Which doesn't seem to help.  I also thought that maybe I'm asking too much of the model and it's not converging due to too many predictor variables, so let's remove the Size variable, which is of less interest to me.</p>
  
  <pre><code>canopy.binomial.mod&lt;-glmer(dec~Stage+(1|Sample),family="binomial",data=canopy.rmna)
  summary(canopy.binomial.mod)
  </code></pre>
  
  <p>Still no luck.  Any ideas how to address this?</p>