Dear R gurus

I am running a GLMM that looks at whether chimpanzees spend time in shade
more than sun (response variable 'y': used cbind() on counts in the sun and
shade) based on the time of day (Time) and the availability of shade
(Tertile). I've included some random factors too which are the chimpanzee
in question (Individual) and where they are in a given area (Zone). There
are also two continuous predictors (Minimum daily temperature: Min; Maximum
daily temperature: Max). I have run my GLMM and I know that Time and Min
are significant predictors of the patterns of shade use while Tertile and
Max are not. In addition, a Time*Tertile interaction effect is a good
predictor as well.

I now need to assess how the specific interaction effect conditions differ
to one another. So, for example, how does shade use differ between 10h00 at
low shade and 10h00 at high shade? I tried using the package multcomp, but
that will only allow me to work out the contrasts for the first-order
effects (Time, Tertile) but won't allow me to do so for the interaction
effects. Any ideas?

My code:

> m1 <- lmer(y ~ Time*Tertile + (1|Individual) + (1|Zone) + Max +
Min,family=binomial,REML=F)
> Anova(m1,type=3,test="Wald")
Analysis of Deviance Table (Type III tests)

Response: y
               Chisq Df Pr(>Chisq)
(Intercept)   0.9511  1     0.3294
Time         60.7807  4  1.988e-12 ***
Tertile       0.3391  1     0.5603
Max           1.3198  1     0.2506
Min          77.7736  1  < 2.2e-16 ***
Time:Tertile 38.9038  4  7.292e-08 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> summary(m1)
Generalized linear mixed model fit by the Laplace approximation
Formula: y ~ Time * Tertile + (1 | Individual) + (1 | Zone) + Max + Min
  AIC  BIC logLik deviance
 1168 1224 -569.9     1140
Random effects:
 Groups     Name        Variance Std.Dev.
 Zone       (Intercept) 0.81949  0.90526
 Individual (Intercept) 0.36417  0.60347
Number of obs: 412, groups: Zone, 8; Individual, 7

Fixed effects:
                     Estimate Std. Error z value Pr(>|z|)
(Intercept)           0.77498    0.79465   0.975 0.329439
Time11h00            -1.54259    0.24351  -6.335 2.38e-10 ***
Time12h00             0.01695    0.77829   0.022 0.982627
Time13h00            -4.26913    0.78217  -5.458 4.81e-08 ***
Time14h00            -1.34503    0.43831  -3.069 0.002150 **
TertileLow            0.32614    0.56003   0.582 0.560323
Max                   0.03751    0.03265   1.149 0.250630
Min                  -0.30912    0.03505  -8.819  < 2e-16 ***
Time11h00:TertileLow  1.03079    0.28579   3.607 0.000310 ***
Time12h00:TertileLow -2.26187    0.79930  -2.830 0.004658 **
Time13h00:TertileLow  2.38129    0.79214   3.006 0.002646 **
Time14h00:TertileLow  1.72263    0.49397   3.487 0.000488 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Correlation of Fixed Effects:
            (Intr) Tm1100 Tm1200 Tm1300 Tm1400 TrtlLw Max    Min    T1100:
Time11h00   -0.026
Time12h00   -0.035  0.177
Time13h00   -0.004  0.223  0.068
Time14h00   -0.073  0.259  0.081  0.103
TertileLow  -0.450  0.153  0.043  0.051  0.097
Max         -0.711 -0.169 -0.004 -0.061 -0.023  0.019
Min          0.146  0.186  0.014  0.055  0.099 -0.036 -0.455
Tm11h00:TrL  0.059 -0.851 -0.153 -0.190 -0.222 -0.198  0.096 -0.155
Tm12h00:TrL  0.095 -0.160 -0.974 -0.062 -0.081 -0.067 -0.079  0.012  0.192
Tm13h00:TrL  0.026 -0.208 -0.067 -0.983 -0.099 -0.075  0.024 -0.026  0.229
Tm14h00:TrL  0.126 -0.215 -0.069 -0.088 -0.876 -0.185 -0.047  0.006  0.254
            T1200: T1300:
Time11h00
Time12h00
Time13h00
Time14h00
TertileLow
Max
Min
Tm11h00:TrL
Tm12h00:TrL
Tm13h00:TrL  0.081
Tm14h00:TrL  0.098  0.116

Luke Duncan

*Post-doctoral** Fellow*
*School of Animal, Plant and Environmental Sciences*
*University of the Witwatersrand*
*Johannesburg, South Africa*
**
*+27 72 312 0330*
*+27 11 717 6452*

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