Displaying 20 results from an estimated 200 matches similar to: "error using user-defined link function with mixed models (LMER)"
2006 Apr 16
3
second try; writing user-defined GLM link function
I apologize for my earlier posting that, unbeknownst to me before,
apparently was not in the correct format for this list. Hopefully this
attempt will go through, and no-one will hold the newbie mistake
against me.
I could really use some help in writing a new glm link function in
order to run an analysis of daily nest survival rates. I've struggled
with this for weeks now, and can at least
2008 Mar 17
2
stepAIC and polynomial terms
Dear all,
I have a question regarding the use of stepAIC and polynomial (quadratic to be specific) terms in a binary logistic regression model. I read in McCullagh and Nelder, (1989, p 89) and as far as I remember from my statistics cources, higher-degree polynomial effects should not be included without the main effects. If I understand this correctly, following a stepwise model selection based
2010 Mar 26
1
Linear mixed models with custom link functions in R
Hello All,
I am looking for an R library/function that allows the specification
of a custom link function in a linear mixed model. I've been using
glm() in library MASS to fit fixed-effect models with a custom link but
my study design demands mixed models. Any suggestions on the best R
library/function to achieve this would be greatly appreciated. I have
tried, to no avail, to
2009 Jul 21
0
Custom Link/Family for lmer
Hello List,
I am modeling a binomial response (nest survival) and I want to incorporate
a random effect, in this case site. I had previously been using glm with a
custom link function, but my understanding is that lmer does not currently
allow a custom link. Therefore, I was investigating if other procedures for
mixed models will allow a custom link function. here is the custom link
function:
2004 May 27
1
Getting the same values of adjusted mean and standard errors as SAS
Hello,
I am trying to get the same values for the adjusted means and standard
errors using R that are given in SAS for the
following data. The model is Measurement ~ Age + Gender + Group. I can
get the adusted means at the mean age
by using predict. I do not know how to get the appropriate standard
errors at the adjusted means for Gender
using values from predict. So I attempted to get them
2004 Feb 26
1
Distance and Aggregate Data - Again...
I appreciate the help I've been given so far. The issue I face is
that the data I'm working with has 53000 rows, so in calculating
distance, finding all recids that fall within 2km and summing the
population, etc. - a) takes too long and b) have no sense of progress.
Below is a loop that reads each recid one at a time, calculates the
distance and identifies the recids that fall within 2
2009 Jul 24
1
metafor
I had found the author's (Wolfgang Viechtbauer) earlier meta-analytic code in R, MiMa, useful. so I have been exploring metafor using an example dataset from MiMa. metafor provides a lot more. However, MiMa provided parameter estimates, standard errors, z values, etc. for individual moderators in the meta-analysis, but I don't see how to obtain these from metafor. Have you any help
2008 Apr 03
1
help with R semantics
Greetings:
I'm running R2.6.2 on a WinXP DELL box with 2 gig RAM.
I have created a new glm link function to be used with family = binomial.
The function works (although any suggested improvements would be welcome),
logit.FC <- function(POD.floor = 0, POD.ceiling =1)
{ if (POD.floor < 0 | POD.floor > 1) stop ("POD.floor must be between zero
and one.")
if
2008 May 20
1
"NOTE" warning
Dear all
I am using NAMESPACE in my package but I would like the user to be able
to overwrite four functions:
own.linkfun, own.linkinv, own.mu.eta and own.valideta.
These are used to defined "own" link functions.
Is there any way of doing that without getting the when I am checking
the package?
This is what I am getting:
make.link.gamlss : linkfun: no visible binding for global
2008 Jun 13
1
Writing a new link for a GLM.
Hi,
I wish to write a new link function for a GLM. R's glm routine does
not supply the "loglog" link. I modified the make.link function adding
the code:
}, loglog = {
linkfun <- function(mu) -log(-log(mu))
linkinv <- function(eta) exp(-exp(-eta))
mu.eta <- function(eta) exp(-exp(-eta)-eta)
valideta <- function(eta) all(eta != 0)
2005 Apr 14
0
predict.glm(..., type="response") dropping names (and a propsed (PR#7792)
Here's a patch that should make predict.glm(..., type="response") retain the
names. The change passes make check on our Opteron running SLES9. One
simple test is:
names(predict(glm(y ~ x, family=binomial,
data=data.frame(y=c(1, 0, 1, 0), x=c(1, 1, 0, 0))),
newdata=data.frame(x=c(0, 0.5, 1)), type="response"))
which gives
[1]
2012 Aug 10
0
error applying user-defined link function to lmer
Dear R users,
I'm struggling with applying a user-defined link function in lmer. For analyzing data of a 2AFC psychophysical experiment, I would like to model my binary data with a logistic function with a lower limit at 0.5 instead of 0. In a previous question this has been described as a halflogit function. To do so I wrote my own link function and would like to submit it to lmer, however
2005 Jun 16
1
mu^2(1-mu)^2 variance function for GLM
Dear list,
I'm trying to mimic the analysis of Wedderburn (1974) as cited by
McCullagh and Nelder (1989) on p.328-332. This is the leaf-blotch on
barley example, and the data is available in the `faraway' package.
Wedderburn suggested using the variance function mu^2(1-mu)^2. This
variance function isn't readily available in R's `quasi' family object,
but it seems to me
2009 Jan 23
4
glm binomial loglog (NOT cloglog) link
I would like to do an R glm() with
family = binomial(link="loglog")
Right now, the cloglog link exists, which is nice when the data have a
heavy tail to the left. I have the opposite case and the loglog link
is what I need. Can someone suggest how to add the loglog link onto
glm()? It would be lovely to have it there by default, and it
certainly makes sense to have the two opposite
2012 Nov 27
4
Fitting and plotting a coxph with survfit, package(surv)
Hi Dear R-users
I have a database with 18000 observations and 20 variables. I am running
cox regression on five variables and trying to use survfit to plot the
survival based on a specific variable without success.
Lets say I have the following coxph:
>library(survival)
>fit <- coxph(Surv(futime, fustat) ~ age + rx, data = ovarian)
>fit
what I am trying to do is plot a survival
2008 Aug 13
1
re placing default labels in lattice
Dear all,
I am having a little trouble deciphering how to change the default x-axis
labels in a lattice xyplot (or any type of lattice plot for that matter). I
have tried using the "demo("labels") function but the code is truncated at
precisely the wrong moment!
All I am trying to do is to add superscript to two of the labels for which i
tried using the expression function. It
2002 Feb 27
1
Bug in glm.fit? (PR#1331)
G'day all,
I had a look at the GLM code of R (1.4.1) and I believe that there are
problems with the function "glm.fit" that may bite in rare
circumstances. Note, I have no data set with which I ran into
trouble. This report is solely based on having a look at the code.
Below I append a listing of the glm.fit function as produced by my
system. I have added line numbers so that I
2006 Jul 30
1
Parametric links for glm?
At useR 2006 I mentioned that it would be nice to have a way to
specify binomial links
that involved free parameters and described some experience with a
Gosset link involving
a free degrees of freedom parameter, and a Tukey-lambda link with two
free parameters.
My implementation of this involved some rather kludgey modifications
of binomial,
make.link and glm that (essentially) added a
2005 Aug 12
1
Help converting a function from S-Plus to R: family$weight
Hi all
I am converting an S-Plus function into R. The S-Plus code
uses some of the glm families, and family objects.
The family objects in S-Plus and R have many different
features, for example:
In R:
> names(Gamma())
[1] "family" "link" "linkfun" "linkinv" "variance"
[6] "dev.resids" "aic"
2007 Aug 10
0
half-logit and glm (again)
I know this has been dealt with before on this list, but the previous
messages lacked detail, and I haven't figured it out yet.
The model is:
\x_{ij} = \mu + \alpha_i + \beta_j
\alpha is a random effect (subjects), and \beta is a fixed effect
(condition).
I have a link function:
p_{ij} = .5 + .5( 1 / (1 + exp{ -x_{ij} } ) )
Which is simply a logistic transformed to be between .5 and 1.