Hi,
I have three questions concerning GLMMs.
First, I ' m looking for a measure for the significance of the random variable
in a glmm.
I'm fitting a glmm (lmer) to telemetry-locations of 12 wildcat-individuals
against random locations (binomial response). The individual is the random
variable. Now I want to know, if the individual ("TIER") has a significant
effect on the model outcome. Does such a measure exist in R?
My second question is, if there is a "predict"-function for glmms in R? Because
I would like to produce a predictive habitat-map (someone asked that before,
but I think there was no answer so far).
And the third, why the method "laplace" doesn't work with all my models.
thank you very much
nina klar
R output for a model, which works with laplace:
> model4a<-lmer(RESPONSE~ D_TO_FORAL +
+ I((DIST_WATER-200)*(DIST_WATER<200)) +
+ I((DIST_VILL-900)*(DIST_VILL<900)) +
+ (1|TIER), family=binomial, method="Laplace")
> summary(model4a)
Generalized linear mixed model fit using Laplace
Formula: RESPONSE ~ D_TO_FORAL + I((DIST_WATER - 200) * (DIST_WATER <
200)) + I((DIST_VILL - 900) * (DIST_VILL < 900)) + (1 | TIER)
Family: binomial(logit link)
AIC BIC logLik deviance
3291.247 3326.739 -1639.623 3279.247
Random effects:
Groups Name Variance Std.Dev.
TIER (Intercept) 5e-10 2.2361e-05
# of obs: 2739, groups: TIER, 12
Estimated scale (compare to 1) 1.476153
Fixed effects:
Estimate Std. Error z value
Pr(>|z|)
(Intercept) 0.19516572 0.05812049 3.3580
0.0007852 ***
D_TO_FORAL -0.01091458 0.00113453 -9.6204 <
2.2e-16 ***
I((DIST_WATER - 200) * (DIST_WATER < 200)) -0.00551492 0.00061907 -8.9084 <
2.2e-16 ***
I((DIST_VILL - 900) * (DIST_VILL < 900)) 0.00307265 0.00025708 11.9521 <
2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Correlation of Fixed Effects:
(Intr) D_TO_F I-2*(<2
D_TO_FORAL -0.247
I((DI-2*(<2 0.561 -0.023
I((DI-9*(<9 0.203 0.047 -0.206
here is the R-output for a model which doesn't work with laplace:
> model4b<-lmer(RESPONSE~ D_TO_FORAL +
+ I((DIST_GREEN-300)*(DIST_GREEN<300))+
+ I((DIST_WATER-200)*(DIST_WATER<200)) +
+ I((DIST_VILL-900)*(DIST_VILL<900)) +
+ I((DIST_HOUSE-200)*(DIST_HOUSE<200)) +
+ (1|TIER), family=binomial, method="Laplace")
Fehler in optim(PQLpars, obj, method = "L-BFGS-B", lower = ifelse(const, :
non-finite finite-difference value [7]
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