# GLMM output interpretation (correct text)

I used the lmer function in the lme4 package in order to assess the effects of 2 categorical fixed effects (1º Animal Group: rodents and ants; 2º Microhabitat: bare soil and under cover) on seed predation (a count dependent variable). I have 2 Sites, with 10 trees per site and 4 seed stations per tree. Site and Tree are my (philosophically) random factors, but given that I have only two level for Site, it must be treated as a fixed factor. I have questions about how to interpret the results:

1. I made a model selection criterion based on QAICc, but the best model (lower QAICc) does not result in any significant fixed effect and other models with higher QAIC (e.g. the Full Model) did find significant fixed factors. Does this make sense?
2. Given a fixed factor that is important to the model, how do I distinguish which level of fixed factor is influencing the response variable?

Finally, correlation between the fixed factors implies an incorrect estimation of the model?

FullModel=lmer(SeedPredation ~ AnimalGroup*Microhabitat*Site + (1|Site:Tree) +
(1|obs), data=datos,  family="poisson")

QAICc(FM)104.9896

enterGeneralized linear mixed model fit by the Laplace approximation
Formula: SP ~ AG * MH * Site + (1 | Site:Tree) + (1 | obs)
Data: datos
AIC   BIC logLik deviance
101.8 125.6  -40.9     81.8
Random effects:
Groups    Name        Variance Std.Dev.
obs       (Intercept) 0.20536  0.45317
Site:Tree (Intercept) 1.19762  1.09436
Number of obs: 80, groups: obs, 80; Site:Tree, 20

Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept)       0.01161    0.47608   0.024   0.9805
AGR             -18.97679 3130.76500  -0.006   0.9952
MHUC             -1.60704    0.63626  -2.526   0.0115 *
Site2            -0.91424    0.74506  -1.227   0.2198
AGR:MHUC         19.92369 3130.76508   0.006   0.9949
AGR:Site2         1.02241 4431.84919   0.000   0.9998
MHUC:Site2        1.80029    0.86235   2.088   0.0368 *
AGR:MHUC:Site2   -3.49042 4431.84933  -0.001   0.9994
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
(Intr) AGR    MHUC   Site2  AGR:MHUC AGR:S2 MHUC:S
AGR          0.000
MHUC        -0.281  0.000
Site2       -0.639  0.000  0.180
AGR:MHUC     0.000 -1.000  0.000  0.000
AGR:Site2    0.000 -0.706  0.000  0.000  0.706
MHUC:Site2   0.208  0.000 -0.738 -0.419  0.000    0.000
AGR:MHUC:S2  0.000  0.706  0.000  0.000 -0.706   -1.000  0.000 code here

BestModel=lmer(SP ~ AG * MH + (1|Site:Tree) + (1|obs), data=datos,
family = "poisson")

QAICc(M) 101.4419

Generalized linear mixed model fit by the Laplace approximation
Formula: SP ~ AG + AG:MH + (1 | Site:Tree) + (1 | obs)
Data: datos
AIC   BIC logLik deviance
100.3 114.6 -44.15     88.3
Random effects:
Groups    Name        Variance Std.Dev.
obs       (Intercept) 0.76027  0.87194
Site:Tree (Intercept) 1.14358  1.06938
Number of obs: 80, groups: obs, 80; Site:Tree, 20

Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept)   -0.5153     0.4061  -1.269    0.205
AGR          -18.7146  2603.4397  -0.007    0.994
AGA:MHUC      -0.7301     0.5045  -1.447    0.148
AGR:MHUC      17.7221  2603.4397   0.007    0.995

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Please delete your previous version of this question. –  whuber Jan 13 '11 at 16:56
I do not find the option to remove the previous (incomplete) post, could you tell me how? –  user2486 Jan 13 '11 at 18:08
On the left below the text of the question you should find a list of options: "link edit delete flag". –  whuber Jan 13 '11 at 19:27
@whuber I deleted the other question. –  Shane Jan 13 '11 at 19:29
thank Wuber and Shane –  user2486 Jan 13 '11 at 21:13
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