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 *
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