[R-sig-ME] Binary response ordering

[John Haart]

Dear List,

I have a quick question regarding the setup of my data for analysis with a glmm.  I hope this is the appropriate list, i apologise if it is not.

I have a response variable, TRUE or FALSE. I have coded this as 0 = False and 1 = TRUE in excel.

I have 3 categorical factors with C,D and E

I then read in the data frame and run the model as follows-

lmer(trueorfalse~1+(1|A/B) + C + D+ E ,family=binomial)

And this is the output

Generalized linear mixed model fit by the Laplace approximation 
Formula: threatornot ~ 1 + (1 | A/B) + C + D+  E ,family=binomial)
  AIC  BIC logLik deviance
 1410 1450 -696.8     1394
Random effects:
 Groups       Name        Variance   Std.Dev.  
 family:order (Intercept) 6.7869e-01 8.2382e-01
 order        (Intercept) 7.8204e-11 8.8433e-06
Number of obs: 1116, groups: A:B, 43; B, 9

Fixed effects:
            Estimate Std. Error z value Pr(>|z|)  
(Intercept)  0.11281    0.42232   0.267   0.7894  
C1   -0.02414    0.19964  -0.121   0.9038  
D2  -0.16482    0.38602  -0.427   0.6694  
E2       0.95381    0.54316   1.756   0.0791 .
E3      0.75733    0.87275   0.868   0.3855  
E4       0.03044    0.47328   0.064   0.9487  

What i am unsure about is the inference, if a term is significant does this relate to TRUE or FALSE?

I.E E2 has a p value of 0.079, does this 0.079 relate to the probability of it resulting in a true or false response? Does it matter how i code the input i.e FALSE = 1, TRUE =2 for instance?

Maybe i am reading the output wrong?

Thanks

John