[R-sig-ME] mixed effects model glmer

[M West]

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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