[R] GLMM post- hoc comparisons

[Silvina Velez]

Hi All,
I have data about seed predation (SP) in fruits of three differents colors (yellow, motted, dark) and in two fruiting seasons (2007, 2008). I performed a GLMM (lmer function, lme4 package) and the outcome showed that the interaction term (color:season) was significant, and some combinations of this interaction have significant Pr(>|z|), but I don't think they are the right significant combinations, because when I look the bwplot, this combinations seems to be very different from the other ones. So, I would like to know if there is any test "a posteriori" to know the p-values ​​for each combination of color:season, and thereby be able to know what conbination/s is/are really significant.

m1=lmer(SP ~ color + season:color +(1|Site:tree), data=datosfl, family="poisson")
AIC   BIC logLik deviance
178.3 196.6 -81.14    162.3
Random effects:
Groups      Name        Variance Std.Dev.
obsBR       (Intercept) 0.064324 0.25362 
Site:tree   (Intercept) 0.266490 0.51623 
Number of obs: 73, groups: obsBR, 73; Site:tree, 37

                    Estimate Std. Error z value Pr(>|z|)    
(Intercept)            2.5089     0.2750   9.125   <2e-16 ***
colorM                -0.1140     0.3242  -0.352   0.7250    
colorD                -0.6450     0.4178  -1.544   0.1227    
Season2008            -0.7343     0.3104  -2.365   0.0180 *  
colorM:Season2008      0.2505     0.4352   0.576   0.5648    
colorD:Season2008      1.1445     0.5747   1.992   0.0464 *