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errors with lme4

2 messages · Alessio Unisi, ONKELINX, Thierry

Alessio Unisi
# 
Dear list,
i'm a new R user, so I apologize if the topic is already being addressed 
by some other user.

I'm trying to determine if the reproductive success of a species of bird 
is related to a list of covariates.

These are the covariates:
?    elev: elevation of nest (meters)
?    seadist: distance from the sea (meters)
?    meanterranova: records of temperature
?    minpengS1: records of temperature
?    wchillpengS1: records of temperature
?    minpengS2: records of temperature
?    wchillpengS2: records of temperature
?    nnd: nearest neighbour distance
?    npd: nearest penguin distance
?    eggs: numbers of eggs
?    lay: laying date (julian calendar)
?    hatch: hatching date (julian calendar)
I have some NAs in the data.

I want to test the model with all the variable then i want to remove 
some, but the ideal model:
GLM.1 <-lmer(fledgesucc ~ +lay +hatch +elev +seadist +nnd +npd 
+meanterranova +minpengS1 +minpengS2 +wchillpengS1 +wchillpengS2 
+(1|territory), family=binomial(logit), data=fledge)

doesn't work because of these errors:
'Warning message: In mer_finalize(ans) : gr cannot be computed at 
initial par (65)'.
"matrix is not symmetric [1,2]"

If i delete one or more of the T records (i.e. minpengS2 +wchillpengS2) 
the model works...below and example:

 GLM.16 <-lmer(fledgesucc ~ lay +hatch +elev +seadist +nnd +npd 
+meanterranova +minpengS1 +(1|territory), family=binomial(logit), 
data=fledge)

 > summary(GLM.16)
Generalized linear mixed model fit by the Laplace approximation
Formula: fledgesucc ~ lay + hatch + elev + seadist + nnd + npd + 
meanterranova +      minpengS1 + (1 | territory)
   Data: fledge
 AIC   BIC logLik deviance
 174 204.2    -77      154
Random effects:
 Groups    Name        Variance Std.Dev.
 territory (Intercept) 0.54308  0.73694
Number of obs: 152, groups: territory, 96

Fixed effects:
               Estimate Std. Error z value Pr(>|z|)
(Intercept)   14.136846  14.510089   0.974    0.330
lay           -0.007642   0.267913  -0.028    0.977
hatch         -0.025947   0.267318  -0.097    0.923
elev           0.007481   0.027765   0.270    0.788
seadist       -0.004277   0.004550  -0.940    0.347
nnd           -0.035535   0.026504  -1.341    0.180
npd            0.003788   0.005521   0.686    0.493
meanterranova  1.242570   1.426158   0.871    0.384
minpengS1     -0.399852   0.418722  -0.955    0.340

Correlation of Fixed Effects:
            (Intr) lay    hatch  elev   seadst nnd    npd    mntrrn
lay          0.411                                                
hatch       -0.515 -0.993                                         
elev        -0.015  0.141 -0.135                                  
seadist     -0.003 -0.023  0.019 -0.440                           
nnd         -0.061  0.066 -0.059 -0.020  0.231                    
npd          0.033 -0.108  0.100  0.298 -0.498 -0.338             
meanterranv  0.459 -0.118  0.075 -0.061  0.014 -0.048  0.130      
minpengS1   -0.540  0.015  0.035  0.032  0.000  0.039 -0.086 -0.970


I've attached an example of my dataset only 15 rows just to see the 
dataset. Let me know if you need more informations.

Thanks in advance for your help and advices!
regards
ONKELINX, Thierry
# 
Dear Alessio,

A few remarks.

- R-sig-mixed models is a better list for this kind of questions
- use the glmer() function if you want logistic or poisson regression
- the error you are getting is an indication that the model is too complex for the data
- watch for colinearity in the covariates

Best regards,

Thierry