similar to: error applying user-defined link function to lmer

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.

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

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)

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]

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

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:

Greetings, everyone. I've been trying to analyze bird nest survival data using generalized linear mixed models (because we documented several consecutive nesting attempts by the same individuals; i.e. repeated measures data) and have been unable to persuade the various GLMM models to work with my user-defined link function. Actually, glmmPQL seems to work, but as I want to evaluate a suite of

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

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

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

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

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"

under "Details" (version 2015-11-29 r69717; not quite cutting-edge, but nothing has changed in src/library/stats/man/family.Rd in 5 months [sorry for using the Github mirror, but I prefer the interface ... <https://github.com/wch/r-source/blob/trunk/src/library/stats/man/family.Rd>]) it says: valid.mu: logical function. Returns ?TRUE? if a mean vector ?mu? is within the

Hi, I'm trying to calculate the value of the variable, dp, below, in the argument to the integral of dnorm(x-dp) * pnorm(x)^(m-1). This corresponds to the estimate of the sensitivity of an observer in an m-alternative forced choice experiment, given the probability of a correct response, Pc, a Gaussian assumption for the noise and no bias. The function that I wrote below gives me an error:

New packages psyphy and MLDS are available on CRAN: psyphy ncludes an assortment of functions useful in analyzing data from pyschophysical experiments. It includes functions for calculating d' from several different experimental designs, links for mafc to be used with the binomial family in glm (and possibly other contexts) and selfStart functions for estimating gamma values

New packages psyphy and MLDS are available on CRAN: psyphy ncludes an assortment of functions useful in analyzing data from pyschophysical experiments. It includes functions for calculating d' from several different experimental designs, links for mafc to be used with the binomial family in glm (and possibly other contexts) and selfStart functions for estimating gamma values

Dear All, Is it possible to run a GEE analysis with a custom link function in R? In particular I'm wanting to use a mafc.logit() generated link function (using the package psyphy). I can use this with a GLM, but it looks like the gee package only accepts predefined link functions. Thanks, Mark This message has been checked for viruses but the contents of an attachment may still contain

Below is a SIMEX object that was generated with the "simex" function from the "simex" package applied to a logistic regression fit. From this mountain of information I would like to extract all of the values summarized in this line: .. ..$ variance.jackknife: num [1:5, 1:4] 1.684 1.144 0.85 0.624 0.519 ... Can someone suggest how to go about doing this? I can extract the

Since the d_off in the first dirent for "." (that originates from the 4th argument "offset" of filldir() for the 2nd dirent for "..") is wrongly assigned in btrfs_real_readdir(), telldir returns same offset for different locations. | # mkfs.btrfs /dev/sdb1 | # mount /dev/sdb1 fs0 | # cd fs0 | # touch file0 file1 | # ../test | telldir: 0 | readdir: d_off = 2,

Dear all, My package has Depends: lme4.0 in the DESCRIPTION. I need to extract the fixed effect of a model and their standard errors. I use coef(summary(model)) inside a function to do that. Model is the output of a call to glmer() from the lme4.0 package. coef(summary(model)) throws an error: $ operator is invalid for atomic vectors I have tracked it down to a problem with summary(model)