title: glmer mixed models inconsistent between lme4 updates
body: <p>This is a long post. I’m having trouble attaining consistent model results between lme4 versions. My old computer was running R 3.0.0 “Masked Marvel”, with the 0.999999-2 version of lme4, and my new work computer is running R 3.0.2 “Frisbee Sailing” with lme4 version 1.1-2. They are not giving me the same model outputs. Omitting the new lme4, I installed every package update on my old laptop one-by-one and ran the models. Then, updated R itself and ran the models. Finally, I made further updates to packages for R 3.0.2, and ran the models once more. They remained consistent with the original analysis. I wasn’t able to run the models with the most recent MASS package with R 3.0.0, and with the most recent nlme package in R 3.0.2. The error message I received in those cases was the same, and is below:
  “Error in validObject(.Object) : invalid class “mer” object: Slot L must be a monotonic LL' factorization of size dims['q']”</p>
  
  <p>I’m wondering if someone can help shed light on this before I update to lme4 1.1-2 to complete my analyses. There doesn’t appear to be a changelog at the address linked in R Studio…<a href="http://cran.rstudio.com/web/packages/lme4/NEWS" rel="nofollow noreferrer">http://cran.rstudio.com/web/packages/lme4/NEWS</a> </p>
  
  <p>Maybe something else has changed on my end? I’ve been using the same datafile, and setting it up the same within R. </p>
  
  <p>I am not sure how to attach data, or how to make this easiest for you all to run through yourselves. I can do that with some instruction. Below are the outputs for 2 models before the updates, and the same models after. The variation occurs in models that I haven't included here as well, some worse than others. It definitely affects an AIC ranking.</p>
  
  <p>lme4 version 0.999999-2
  R version 3.0.0 (2013-04-03) -- "Masked Marvel"</p>
  
  <pre><code>at1500o &lt;- glmer(apred ~ 
                   (1 | fFarm) + (1 | Eps) + (1 | fExp),
                   family = binomial,
                   data = PU3.atristis)                
  summary(at1500o)
  
  Number of levels of a grouping factor for the random effects
  is *equal* to n, the number of observations
  Warning message: In mer_finalize(ans) : false convergence (8)
  
  Generalized linear mixed model fit by the Laplace approximation 
  Formula: apred ~ (1 | fFarm) + (1 | Eps) + (1 | fExp) 
     Data: PU3.atristis 
     AIC      BIC     logLik      deviance
     182.2    193     -87.11      174.2
  Random effects:
   Groups      Name           Variance    Std.Dev.  
   Eps        (Intercept)     1.6630e+01  4.0780e+00
   fFarm      (Intercept)     2.4393e+00  1.5618e+00
   fExp       (Intercept)     5.8587e-13  7.6542e-07
  Number of obs: 110, groups: Eps, 110; fFarm, 17; fExp, 2
  
  Fixed effects:
                  Estimate  Std. Error  z value   Pr(&gt;|z|)    
  (Intercept)     -6.1406     0.7126    -8.618   &lt;2e-16 ***
  ---
  Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
  </code></pre>
  
  <p>False convergence <a href="https://stackoverflow.com/questions/9299451/warning-message-in-mixed-model-lme4">didn’t seem to be a problem</a></p>
  
  <pre><code>at1500a &lt;- glmer(apred ~ 
                        pctfield1500 * factor(SiteTrt) +
                        (1 | fFarm) + (1 | Eps) + (1 | fExp),
                      family = binomial,
                      data = PU3.atristis)                
  summary(at1500a)
  
  Number of levels of a grouping factor for the random effects
  is *equal* to n, the number of observations
  Warning message: In mer_finalize(ans) : false convergence (8)
  
  Generalized linear mixed model fit by the Laplace approximation 
  Formula: apred ~ pctfield1500 + factor(SiteTrt) + pctfield1500:factor(SiteTrt) + (1 | fFarm) + (1 | Eps) + (1 | fExp) 
     Data: PU3.atristis 
  
     AIC      BIC     logLik      deviance
     185.2    209.5   -83.59      167.2
  
  Random effects:
   Groups     Name            Variance    Std.Dev.  
   Eps        (Intercept)     2.4539e+01  4.95370375
   fFarm      (Intercept)     8.1397e-01  0.90220336
    fExp      (Intercept)     1.3452e-08  0.00011598
  Number of obs: 110, groups: Eps, 110; fFarm, 17; fExp, 2
  
  Fixed effects:
                                 Estimate  Std. Error  z value  Pr(&gt;|z|)   
  (Intercept)                    -6.82245    2.64044    -2.584   0.00977 **
  pctfield1500                   -0.01041    0.10849    -0.096   0.92353   
  factor(SiteTrt)2               2.47654     3.97069     0.624   0.53282   
  factor(SiteTrt)3               4.33391     4.65551     0.931   0.35190   
  pctfield1500:factor(SiteTrt)2  -0.05073    0.13117    -0.387   0.69895   
  pctfield1500:factor(SiteTrt)3  -0.05729    0.14524    -0.394   0.69323   
  ---
  Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
  
  Correlation of Fixed Effects:
                  (Intr)  pc1500    f(ST)2   f(ST)3  p1500:(ST)2
  pctfild1500         -0.876                                 
  fctr(StTr)2     -0.665  0.582                          
  fctr(StTr)3     -0.571  0.504     0.380                   
  p1500:(ST)2     0.724   -0.827   -0.850   -0.417            
  p1500:(ST)3     0.654   -0.747   -0.435   -0.887    0.618
  </code></pre>
  
  <p>Lme4 version 1.1-2
  R version 3.0.2 (2013-09-25) -- "Frisbee Sailing"</p>
  
  <pre><code>at1500o &lt;- glmer(apred ~ 
                   (1 | fFarm) + (1 | Eps) + (1 | fExp),
                   family = binomial,
                   data = PU3.atristis)                
  summary(at1500o)
  
  Generalized linear mixed model fit by maximum likelihood ['glmerMod']
   Family: binomial ( logit )
  Formula: apred ~ (1 | fFarm) + (1 | Eps) + (1 | fExp) 
     Data: PU3.atristis 
  
        AIC           BIC         logLik      deviance 
        236.8296      247.6316    -114.4148   228.8296 
  
  Random effects:
   Groups      Name           Variance    Std.Dev. 
   Eps        (Intercept)     4.799e+01   6.927e+00
   fFarm      (Intercept)     6.542e-01   8.088e-01
   fExp       (Intercept)     6.056e-10   2.461e-05
  Number of obs: 110, groups: Eps, 110; fFarm, 17; fExp, 2
  
  Fixed effects:
               Estimate     Std. Error     z value   Pr(&gt;|z|)    
  (Intercept)   -7.975        1.115        -7.154   8.43e-13 ***
  ---
  Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
  </code></pre>
  
  <p>No warnings anymore, but everything is pretty different. The model fit statement has changed from the Laplace approximation, to maximum likelihood [‘glmerMod’].</p>
  
  <pre><code>at1500a &lt;- glmer(apred ~ 
                        pctfield1500 * factor(SiteTrt) +
                        (1 | fFarm) + (1 | Eps) + (1 | fExp),
                      family = binomial,
                      data = PU3.atristis)                
  summary(at1500a)
  
  Generalized linear mixed model fit by maximum likelihood ['glmerMod']
   Family: binomial ( logit )
  Formula: apred ~ pctfield1500 + factor(SiteTrt) + pctfield1500:factor(SiteTrt) + (1 | fFarm) + (1 | Eps) + (1 | fExp) 
     Data: PU3.atristis 
  
        AIC           BIC         logLik      deviance 
        242.7874      267.0917    -112.3937   224.7874 
  
  Random effects:
   Groups     Name            Variance    Std.Dev. 
   Eps        (Intercept)     3.346e+01   5.784e+00
   fFarm      (Intercept)     1.809e-07   4.253e-04
   fExp       (Intercept)     4.380e-11   6.618e-06
  Number of obs: 110, groups: Eps, 110; fFarm, 17; fExp, 2
  
  Fixed effects:
                                Estimate  Std. Error  z value   Pr(&gt;|z|)  
  (Intercept)                   -7.46800      3.04197     -2.455    0.0141 *
  pctfield1500                   0.00032      0.12301     0.003     0.9979  
  factor(SiteTrt)2               2.05618      4.57444     0.450     0.6531  
  factor(SiteTrt)3               6.72139      5.20895     1.290     0.1969  
  pctfield1500:factor(SiteTrt)2 -0.04882      0.14911     -0.327    0.7434  
  pctfield1500:factor(SiteTrt)3 -0.11324      0.16495     -0.686    0.4924  
  ---
  Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
  
  Correlation of Fixed Effects:
              (Intr)  pc1500    f(ST)2   f(ST)3  p1500:(ST)2
  pctfild1500 -0.875                                 
  fctr(StTr)2 -0.665  0.582                          
  fctr(StTr)3 -0.584  0.511     0.388                   
  p1500:(ST)2 0.722   -0.825   -0.850   -0.422            
  p1500:(ST)3 0.653   -0.746   -0.434   -0.886    0.615 
  </code></pre>
  
  <p>Cheers,
  Nava</p>