[R-sig-ME] lmer and standard error

[Alexandre Lafontaine]

Dear R users,
I have a question regarding how lmer (either lme4 or lmerTest) handles the degrees of freedom and calculation of the standard error for repeated observations.
I have a dataset in wich I have multiple observations for 57 different idyears in two different regions (range).
head(database) idyear      range overlapok cut05 c0620 regen water roads  elevaju36 GJ502006 charlevoix         1     0     0     0     0     0 223.888937 GJ502006 charlevoix         1     0   100     0     0     0 220.582938 GJ502006 charlevoix         1     0   100     0     0     0 219.411039 GJ502006 charlevoix         1     0   100     0     0     0 219.411040 GJ502006 charlevoix         1     0   100     0     0     0 219.411041 GJ502006 charlevoix         1     0   100     0     0     0 219.0555
Here is my lmer formula in which i nested idyears in range as random effects:
fidint5 <- lmer(overlapok ~ natdist + cut05 + c0620 + regen +(1|range/idyear) , data=database)summary(fidint5)
The summary identifies the good number of  groups (57) for 2 range. However, the df shows that the error is computed on between 2404 and 2418 df which returns really high t values and therefore extremely small p values.

Random effects: Groups       Name        Variance Std.Dev. idyear:range (Intercept) 0.16211  0.4026   range        (Intercept) 0.00000  0.0000   Residual                 0.01709  0.1307  Number of obs: 2429, groups:  idyear:range, 33; range, 2
Fixed effects:                Estimate   Std. Error           df t value(Intercept)    0.6691140    0.0704710   32.1000000   9.495natdist       -0.0023431    0.0015088 2404.1000000  -1.553cut05          0.0092084    0.0005473 2407.9000000  16.824c0620          0.0041097    0.0004459 2418.0000000   9.217regen         -0.0089785    0.0003203 2407.3000000 -28.027                        Pr(>|t|)    (Intercept)      0.0000000000765 ***natdist                    0.121    cut05       < 0.0000000000000002 ***c0620       < 0.0000000000000002 ***regen       < 0.0000000000000002 ***
Are the groups specified in the random term considered in this result? Is the way I specified the random effects incorrect or is this the way lmer function is designed? I am really only beginning to use mixed models and would really appreciate any help on this.
Thanks a lot for your time and wisdom, 
Alexandre Lafontaine


 		 	   		  
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