[R-sig-eco] lme post-hoc help

[Nathan Lemoine]

Hi all,

I'm attempting to analyze some data on log-transformed algae grazing  
rates that I've collected in different habitats. I when collecting the  
data, I blocked for day to account for temporal variation in grazing  
intensity, and I'm considering DAY as a random factor in my model. As  
such, I've used the lme model to construct the mixed-effects model as  
follows:

 > al_lme <- lme(grazing~habitat, random = ~1|day, data=algae)

The ANOVA summary shows a significant result:

 > anova(al_lme)

            numDF   denDF   F-value        p-value
(Intercept)     1    32        174.97322    <.0001
HAB               3    32          3.31776       0.0321

Yet, when I do a post-hoc comparison, none of the pairwise tests are  
significant:

 > pairs <- glht(al_lme, linfct = mcp("habitat"="Tukey")
 > summary(pairs)

                                       Estimate Std. Error  z value  
Pr(>|z|)
Fake - Complex == 0    0.2125     0.5390   0.394    0.978
Far - Complex == 0       1.1937     0.5390   2.215    0.114
Near - Complex == 0   0.7758     0.3623   2.142    0.134
Far - Fake == 0              0.9813     0.4437   2.211    0.115
Near - Fake == 0           0.5633     0.5390   1.045    0.715
Near - Far == 0             -0.4179     0.5390  -0.775    0.861
(Adjusted p values reported -- single-step method)

How is this possible? In visually inspecting the data, it is apparent  
that at least the Far-Complex ought to be significant. To be sure, I  
double checked my statistics using SPSS, which is where I'm getting  
more confused.

In SPSS, I built a blocked, general linear model with Loss as the  
dependent, Habitat as the fixed factor, and Day as a random factor. I  
used the default Type III SS because the design was not balanced. SPSS  
also returns a significant effect:

Habitat F = 4.741, denom df = 33, p = 0.015

and the Tukey's HSD post-hoc test returns a significant difference  
between the Far-Complex habitats, like expected. My questions are:  
First, how can I receive a significant result in R and have no  
significant pairwise effects? Second, what are the differences between  
SPSS and R, that SPSS uses a different denominator df to calculate the  
F-statistic? This is probably the reason that the p-value for SPSS is  
lower, but I'm not sure that this is part of the reason for the  
different post-hoc results.

Thanks for any help,

Nate Lemoine