Hello All,

I'm new to R and new to this mailing list, so I hope I've presented the proper info in this post.  I'm using GLMMs to model the selection of urban roosting locations by crows.  My dataset consists of 22 cities, with each city containing 1000 unused locations and from 83 to 2000 used locations.  I have three covariates for each used or unused location which I've standardized across all observations: % canopy (CANS), % impervious surfaces (IMPS), and nighttime light level (LTS).  Using the default setting nAGQ=1, my full model is fitted without error:

> CIL_CIL<-glmer(USED~1+CANS+IMPS+LTS+(1+CANS+IMPS+LTS|CITY),family=binomial,data=sitescale)
> CIL_CIL
Generalized linear mixed model fit by the Laplace approximation 
Formula: USED ~ 1 + CANS + IMPS + LTS + (1 + CANS + IMPS + LTS | CITY) 
   Data: sitescale 
   AIC   BIC logLik deviance
 15122 15237  -7547    15094
Random effects:
 Groups Name        Variance   Std.Dev. Corr                 
 CITY   (Intercept) 321.698184 17.93595                      
        CANS          0.073271  0.27069  0.026               
        IMPS          0.661947  0.81360  0.080 -0.698        
        LTS         455.829122 21.35016 -0.988  0.031 -0.132 
Number of obs: 27128, groups: CITY, 22

Fixed effects:
             Estimate Std. Error z value Pr(>|z|)    
(Intercept) -16.21878    4.01227  -4.042 5.29e-05 ***
CANS          0.07881    0.07162   1.100 0.271147    
IMPS          0.63137    0.17750   3.557 0.000375 ***
LTS          19.50827    4.78822   4.074 4.62e-05 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Correlation of Fixed Effects:
     (Intr) CANS   IMPS  
CANS  0.020              
IMPS  0.074 -0.500       
LTS  -0.989  0.025 -0.124

When I increase nAGQ to 8, however, I get the following error:

> CIL_CIL.nAGQ8<-glmer(USED~1+CANS+IMPS+LTS+(1+CANS+IMPS+LTS|CITY),family=binomial,data=sitescale,nAGQ=8)
> CIL_CIL.nAGQ8
Error in asMethod(object) : matrix is not symmetric [1,2]

I get the same error message with other values for nAGQ (I tried nAGQ = 2, 3, 5, and 50).  Is there anything I can do to fit the model using nAGQ > 1 without error?  Thanks in advance for your help!

-Grant Stokke


> sessionInfo()
R version 2.9.0 (2009-04-17) 
i386-pc-mingw32 

locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] mgcv_1.5-5         lme4_0.999375-30   Matrix_0.999375-26 lattice_0.17-22   

loaded via a namespace (and not attached):
[1] grid_2.9.0  nlme_3.1-90 tools_2.9.0
> CIL_CIL.nAGQ8
Error in asMethod(object) : matrix is not symmetric [1,2]
> traceback()
18: .Call(dense_to_symmetric, from, "U", TRUE)
17: asMethod(object)
16: as(from, "symmetricMatrix")
15: .class1(object)
14: as(as(from, "symmetricMatrix"), "dMatrix")
13: .class1(object)
12: as(as(as(from, "symmetricMatrix"), "dMatrix"), "denseMatrix")
11: .class1(object)
10: as(as(as(as(from, "symmetricMatrix"), "dMatrix"), "denseMatrix"), 
        "dpoMatrix")
9: asMethod(object)
8: as(sigma(object)^2 * chol2inv(object@RX, size = object@dims["p"]), 
       "dpoMatrix")
7: vcov(object)
6: vcov(object)
5: summary(x)
4: summary(x)
3: printMer(object)
2: function (object) 
   standardGeneric("show")(<S4 object of class "mer">)
1: function (object) 
   standardGeneric("show")(<S4 object of class "mer">)



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