[R-sig-ME] mixed effects model glmer
M West
westm490 at gmail.com
Wed Sep 23 20:36:05 CEST 2015
I am trying to fit a mixed effects model with repeated measures data.
Data are:
y variable = percentage (# females/total)
x variable = percentage
measured across multiple sites for 4 years.
here's the model:
y <- cbind(total females, (Total - total females)))
mod1 <- with(data, glmer(y ~ disease prevalence + (1|Site) + (1|Year),
family = binomial, data = data1))
1) This model runs, but the summary(mod1) just generates a series of the
following....which doesn't make any sense so something must be wrong with
the model specification...I'm just not sure what.
2) Also, what is the default AR correlation on these models (i.e., do I
need to specify it or is the temporal psuedoreplication taken care of)?
3) Finally, do you suggest another form of the model that's better etc.?
Fixed effects:
Estimate Std. Error z value
Pr(>|z|)
(Intercept) -1.60267 0.11618 -13.794 <
2e-16 ***
disease prevalence -0.40212 0.15557 -2.585 0.009745 **
disease prevalence 0.035088231 -1.46452 0.22860 -6.406 1.49e-10
***
disease prevalence 0.064935065 -0.36344 0.30810 -1.180 0.238157
disease prevalence 0.078507945 -2.57479 0.46537 -5.533 3.15e-08
***
disease prevalence 0.120039255 -3.30998 0.71915 -4.603 4.17e-06
***
disease prevalence 0.182623706 -0.14362 0.19899 -0.722 0.470438
Many thanks in advance,
M.
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