
Hi, 

If any one has time I need some help understanding the P-values given in the lmer output.

Using AIC for model selection I find my minimal model is FOLLOW~MOVERSTATUS+DISTANCE however it appears DISTANCE is not significant at 95% confidence, see output quoted below.
However, removing DISTANCE gives a higher AIC=433.5, therefore I will keep it in, but am confused as to what is adds to the model. 
Are the p values given in output to be taken lightly?  

Thanks
Krys

>model<-lmer(FOLLOW~MOVERSTATUS+DISTANCE+(1|DATE), REML=FALSE, family=binomial,data=m1)
>model
#Generalized linear mixed model fit by the Laplace approximation 
#Formula: FOLLOW ~ MOVERSTATUS + DISTANCE + (1 | DATE) 
#  Data: m1 
#   AIC   BIC logLik deviance
#430.8 448.4 -211.4    422.8
# Random effects:
# Groups Name            Variance Std.Dev.
# DATE   (Intercept)     0.5957   0.77182 
# Number of obs: 611, groups: DATE, 122

#Fixed effects:
#                            Estimate    Std. Error   z value    Pr(>|z|)    
#(Intercept)              2.06881    0.31086     6.655      2.83e-11 ***
#MOVERSTATUSSUB   -0.82564    0.28118    -2.936     0.00332 ** 
#DISTANCE                0.02311    0.01298     1.780      0.07503 .  


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Krystyna Golabek
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