[R] predict lmer
Dear all, I've been reading for many days trying to predict with lmer but I haven't managed to do it. I've fitted an allometric model for trees where I have included climatic variables and diameter in the fixed part and in the random part I've included the experimental sites where trees are and also their provenance region. The model is like this : f431-lmer(log(H05)~log(DN05)*(PwS+ PoS+ PpS+ TpS)+PoP:log(DN05)+PwP:log(DN05)+(log(DN05)-1|P)+(log(DN05)-1|S/B)+(log(DN05)|SP), data=data) once I 've fitted the model I would like to make predictions for a new data frame of values. But i don't know how to do it. For example I am interested in know how height varies (at a fixed diameter) for a mean rainfall of a site in each provenance region to contrast with how height response is for a mean rainfall provenance of each site and things like this. If someone can give any suggestion I will be pleased to listen to. Thanks very much for your time, The best Natalia [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] predict lmer
Natalia Vizcaíno Palomar natalia.vizcaino.palomar at gmail.com writes: I've been reading for many days trying to predict with lmer but I haven't managed to do it. I've fitted an allometric model for trees where I have included climatic variables and diameter in the fixed part and in the random part I've included the experimental sites where trees are and also their provenance region. [snip] f431-lmer(log(H05)~log(DN05)*(PwS+ PoS+ PpS+ TpS)+PoP:log(DN05)+PwP:log(DN05)+(log(DN05)-1|P)+ (log(DN05)-1|S/B)+(log(DN05)|SP), data=data) [snip snip] Have you looked at the code on http://glmm.wikidot.com/faq about this ... ? If you look at it and still can't work it out I would suggest that requesting help on the r-sig-mixed-models list will be more useful ... Ben Bolker __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] predict lmer
The following function is designed to work with a logit link. It can
easily be generalized to work with any link. The SEs and CIs are
evaluated accounting for all sources of random variation. The plot
may not be much help unless there is just one explanatory variate.
`ciplot` -
function(obj=glmm2, data=data.site, xcol=2, nam=litter){
cilim - function(obj, xcol){
b - fixef(obj)
vcov - summary(obj)@vcov
X - unique(model.matrix(obj))
hat - X%*%b
pval - exp(hat)/(1+exp(hat)) # NB, designed for logit link
U - chol(as.matrix(summary(obj)@vcov))
se - sqrt(apply(X%*%t(U), 1, function(x)sum(x^2)))
list(hat=hat, se=se, x=X[,xcol])
}
limfo - cilim(obj, xcol)
hat - limfo$hat
se - limfo$se
x - limfo$x
upper - hat+2*se
lower - hat-2*se
ord - order(x)
plot(x, hat, yaxt=n, type=l, xlab=nam, ylab=)
rug(x)
lines(x[ord], lower[ord])
lines(x[ord], upper[ord])
ploc - c(0.01, 0.05, 0.1, 0.2, 0.5, 0.8, 0.9)
axis(2, at=log(ploc/(1-ploc)), labels=paste(ploc), las=2)
}
## Usage
glmm2 - lmer(rcr ~ litter + (1 | Farm), family=binomial,
data=data.site)
ciplot(obj=glmm2)
John Maindonald email: [EMAIL PROTECTED]
phone : +61 2 (6125)3473fax : +61 2(6125)5549
Centre for Mathematics Its Applications, Room 1194,
John Dedman Mathematical Sciences Building (Building 27)
Australian National University, Canberra ACT 0200.
On 8 May 2008, at 8:00 PM, [EMAIL PROTECTED] wrote:
From: May, Roel [EMAIL PROTECTED]
Date: 8 May 2008 12:23:15 AM
To: r-help@r-project.org
Subject: [R] 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 which the animal could have chosen. These sets of
locations
are captured using the TRKPT2 random grouping. However, these sets are
also clustered over the different individuals (ID). USED is my binary
dependent variable which is 1 for used locations and zero for unused
locations. The other are my predictors.
I would like to predict the model fit at different values of the
predictors, but does anyone know whether it is possible to do this? I
have looked around at the R-sites and in help but it seems that there
doesn't exist a predict function for lmer???
I hope someone can help me with this; point me to the right
functions or
tell me to just forget it
Thanks in advance!
Cheers Roel
Roel May
Norwegian Institute for Nature Research
Tungasletta 2, NO-7089 Trondheim, Norway
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and provide commented, minimal, self-contained, reproducible code.
[R] 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 which the animal could have chosen. These sets of locations are captured using the TRKPT2 random grouping. However, these sets are also clustered over the different individuals (ID). USED is my binary dependent variable which is 1 for used locations and zero for unused locations. The other are my predictors. I would like to predict the model fit at different values of the predictors, but does anyone know whether it is possible to do this? I have looked around at the R-sites and in help but it seems that there doesn't exist a predict function for lmer??? I hope someone can help me with this; point me to the right functions or tell me to just forget it Thanks in advance! Cheers Roel Roel May Norwegian Institute for Nature Research Tungasletta 2, NO-7089 Trondheim, Norway [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] predict lmer
?fixef gets you the coefficient vector, from which you can make your predictions. -- Bert Gunter Genentech -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of May, Roel Sent: Wednesday, May 07, 2008 7:23 AM To: r-help@r-project.org Subject: [R] 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 which the animal could have chosen. These sets of locations are captured using the TRKPT2 random grouping. However, these sets are also clustered over the different individuals (ID). USED is my binary dependent variable which is 1 for used locations and zero for unused locations. The other are my predictors. I would like to predict the model fit at different values of the predictors, but does anyone know whether it is possible to do this? I have looked around at the R-sites and in help but it seems that there doesn't exist a predict function for lmer??? I hope someone can help me with this; point me to the right functions or tell me to just forget it Thanks in advance! Cheers Roel Roel May Norwegian Institute for Nature Research Tungasletta 2, NO-7089 Trondheim, Norway [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] predict lmer
Sorry, my reply below may be too terse. You'll need to also construct the appropriate design matrix to which to apply the fixef() results to. If newDat is a data.frame containing **exactly the same named regressor and response columns** as your original vdata dataframe, and if me.fit.of is your fitted lmer object as you have defined it below, then model.matrix(terms(me.fit.of),newDat) %*% fixef(me.fit.of) gives your predictions. Note that while the response column in newDat is obviously unnecessary for prediction (you can fill it with 0's,say), it is nevertheless needed for model.matrix to work. This seems clumsy to me, so there may well be better ways to do this, and **I would appreciate suggestions for improvement.*** Cheers, Bert -Original Message- From: bgunter Sent: Wednesday, May 07, 2008 9:53 AM To: May, Roel; r-help@r-project.org Subject: RE: [R] predict lmer ?fixef gets you the coefficient vector, from which you can make your predictions. -- Bert Gunter Genentech -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of May, Roel Sent: Wednesday, May 07, 2008 7:23 AM To: r-help@r-project.org Subject: [R] 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 which the animal could have chosen. These sets of locations are captured using the TRKPT2 random grouping. However, these sets are also clustered over the different individuals (ID). USED is my binary dependent variable which is 1 for used locations and zero for unused locations. The other are my predictors. I would like to predict the model fit at different values of the predictors, but does anyone know whether it is possible to do this? I have looked around at the R-sites and in help but it seems that there doesn't exist a predict function for lmer??? I hope someone can help me with this; point me to the right functions or tell me to just forget it Thanks in advance! Cheers Roel Roel May Norwegian Institute for Nature Research Tungasletta 2, NO-7089 Trondheim, Norway [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] predict lmer
One question that arises is: at what level is the prediction desired? Within a given ID:TRKPT2 level? Within a given ID level? At the marginal level (which Bert's code appears to produce). Also, there is the question: how confident can you be in your predictions. This thread discusses possible ways to get prediction intervals: https://stat.ethz.ch/pipermail/r-sig-mixed-models/2008q2/thread.html#841 Finally, why assume a Poisson error distribution for a binary response? Kingsford Jones On Wed, May 7, 2008 at 10:13 AM, Bert Gunter [EMAIL PROTECTED] wrote: Sorry, my reply below may be too terse. You'll need to also construct the appropriate design matrix to which to apply the fixef() results to. If newDat is a data.frame containing **exactly the same named regressor and response columns** as your original vdata dataframe, and if me.fit.of is your fitted lmer object as you have defined it below, then model.matrix(terms(me.fit.of),newDat) %*% fixef(me.fit.of) gives your predictions. Note that while the response column in newDat is obviously unnecessary for prediction (you can fill it with 0's,say), it is nevertheless needed for model.matrix to work. This seems clumsy to me, so there may well be better ways to do this, and **I would appreciate suggestions for improvement.*** Cheers, Bert -Original Message- From: bgunter Sent: Wednesday, May 07, 2008 9:53 AM To: May, Roel; r-help@r-project.org Subject: RE: [R] predict lmer ?fixef gets you the coefficient vector, from which you can make your predictions. -- Bert Gunter Genentech -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of May, Roel Sent: Wednesday, May 07, 2008 7:23 AM To: r-help@r-project.org Subject: [R] 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 which the animal could have chosen. These sets of locations are captured using the TRKPT2 random grouping. However, these sets are also clustered over the different individuals (ID). USED is my binary dependent variable which is 1 for used locations and zero for unused locations. The other are my predictors. I would like to predict the model fit at different values of the predictors, but does anyone know whether it is possible to do this? I have looked around at the R-sites and in help but it seems that there doesn't exist a predict function for lmer??? I hope someone can help me with this; point me to the right functions or tell me to just forget it Thanks in advance! Cheers Roel Roel May Norwegian Institute for Nature Research Tungasletta 2, NO-7089 Trondheim, Norway [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
