Displaying 3 results from an estimated 3 matches for "glmm2".
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2008 Nov 19
1
F-Tests in generalized linear mixed models (GLMM)
...ma <- mu * 1
> a <- mu^2/sigma^2
> s <- sigma^2/mu
> y <- rgamma(n, shape=a, scale=s)
>
> library(mgcv)
>
> # a mixed model without Gamma-distribution and without log-link works
as follows:
> glmm1 <- gamm(y ~ x1 + x2, random=list(random1 = ~1))
> glmm2 <- gamm(y ~ 1, random=list(random1 = ~1))
>
> anova(glmm1$lme)
numDF denDF F-value p-value
X 3 295 103.4730 <.0001
> anova(glmm2$lme, glmm1$lme)
Model df AIC BIC logLik Test L.Ratio p-value
glmm2$lme 1 3 4340.060 4351.172 -2167.030
glmm1$lme 2 5 4292.517 4311.036 -2141.258 1 vs 2...
2004 Nov 09
1
Some questions to GLMM
...ct, that I do not have to take care about over-
dispersion.
Question 4: When I use "poly(thick,2)" instead of "thick+I(thick^2)" I get
completly different estimate-values (the latter one are the correct one). I
thought it should be the same.
============================
> glmm2<-GLMM(count~poly(thick,2),random=~poly(thick,2)
|plantid,poisson,data=Dataset,control=list(PQLmaxIt=10000))
> summary(glmm2)
[...]
Fixed effects:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -0.69293 0.10711 -6.4694 9.837e-11 ***
poly(thick, 2)1 -47.232...
2008 May 07
3
predict lmer
Hi,
I am using lmer to analyze habitat selection in wolverines using the
following model:
(me.fit.of <-
lmer(USED~1+STEP+ALT+ALT2+relM+relM:ALT+(1|ID)+(1|ID:TRKPT2),data=vdata,
control=list(usePQL=TRUE),family=poisson,method="Laplace"))
Here, the habitat selection is calaculated using a so-called discrete
choice model where each used location has a certain number of
alternatives