[R-sig-ME] Output glmer

[Davide Bellone]

Good afternoon,

I have a little problem in my glmer output. In my model, before run the
model I used

options(contrasts=c("contr.sum", "contr.poly"))

So after stepwise deletion I arrive at the finel output:

Formula: y ~ Model$Manage + Model$age + Model$veg + Model$wood +
Model$under +
    Model$veg * Model$Manage + Model$age * Model$veg + Model$under *
 Model$wood + Model$veg * Model$under + (1 | Model$Site) +
    (1 | obs)

     AIC      BIC   logLik deviance df.resid
   568.0    604.1   -272.0    544.0      138

Scaled residuals:
     Min       1Q   Median       3Q      Max
-0.76077 -0.15913  0.00041  0.26754  0.70326

Random effects:
 Groups     Name        Variance Std.Dev.
 obs        (Intercept) 11.954   3.458
 Model$Site (Intercept)  7.405   2.721
Number of obs: 150, groups:  obs, 150; Model$Site, 10

Fixed effects:
                                              Estimate      d. Error z
value Pr(>|z|)
(Intercept)                                16.67112     7.73426   2.155
0.0311 *
Model$Manage1                         -5.72100    2.79907  -2.044   0.0410 *
Model$age                                -2.10245     0.84062  -2.501
0.0124 *
Model$veg                                -0.62276     0.29968  -2.078
0.0377 *
Model$wood1                             0.36500     0.41976   0.870
0.3846
Model$under1                             3.69383     2.73372   1.351
0.1766
Model$Manage1:Model$veg          0.20478     0.09007   2.274   0.0230 *
Model$age:Model$veg                  0.08319    0.03326   2.502   0.0124 *
Model$wood1:Model$under1          1.02751    0.44610   2.303   0.0213 *
Model$veg:Model$under1             -0.17567    0.08846  -1.986   0.0470 *
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Manage, wood and under are categorical with 2 levels each.

My question is: how can I find the real value of the estimates in the
summary output (since I used the contrast)? Also, how it works with the
interactions estimate?
The books that I am reading don´t help much since they don´t show
interactions between variables. Usually, they show only one variable with
more levels.  I Hope this is the right section to ask this question.

Thank you for who can help to understand this (maybe simple) problem.

Davide

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