similar to: Could generic functions check different S3 methods for an object when one of them produces an error?

Dear Iago, The R S3 object system works as expected here, using the first available method processing the class vector from left to right. The problem is that the broom package doesn't export the confint.geeglm() method but rather reserves it for internal use. I can't think why the package authors chose to do that but you could ask them. The following therefore works (following on with

I'm using the package geepack to fit GEE models. Does anyone know of methods for add1 and drop1 for a 'geeglm' model object, or perhaps a method for extractAIC based on the QIC of Pan 2001? I see there has been some mention of this on R-help a few years ago (RSiteSearch("QIC")). The package does provide an anova method for its model objects, and update() seems to work:

Dear R users I am analysing data from a group of twins and their siblings. The measures that we are interested in are all correlated within families, with the correlations being stronger between twins than between non-twin siblings. The measures are all calculated from survey answers and by definition have limited ranges (e.g. -5 to +5), though within the range they are approximately normally

Hello R Forum members. I have installed for my statistician user, apparently without error, both the concord and geepack packages. The target system is R 2.10.1 on a 64-bit RedHat Enterprise Linux platform. However when she attempts to invoke a function in geepack, for example... geeglm((abuse_total ~ case),id=mother, family="poisson") the resultant error is Error: could not find

Dear R-users, I was doing some Poisson regression using the geepack package and I found a "strange" behaviour of the geeglm command when defining an offset. Maybe it's my limited knowledge of R syntax, or maybe it's something else. Let's make an example. After loading the geepack library, you may write

Dear all, Is it possible to incorporate a nested design in GEE? I have measurements on trees that where measured in two years. The trees are nested in plots. Each plot contains 24 trees. The number of plots is 72. Hence we would expect 2 * 24 * 72 = 3456 data points. A few are missing, so we end up wih 3431 data points. This is what I have tried until now. #assuming independence between trees

Dear all, I need to fit a gee model with an auto-regressive correlation structure and I faced some problems. I attach a simple example: ####################################################### library(gee) library(geepack) # I SIMULATE DATA FROM POISSON DISTRIBUTION, 10 OBS FOR EACH OF 50 GROUPS set.seed(1) y <- rpois(500,50) x <- rnorm(500) id <- rep(1:50,each=10) # EXAMPLES FOR

Hi, I'm running GEE using geepack. I set corstr = "ar1" as below: > m.ar <- geeglm(L ~ O + A, + data = firstgrouptxt, id = id, + family = binomial, corstr = "ar1") > summary(m.ar) Call: geeglm(formula = L ~ O + A, family = binomial, data = firstgrouptxt, id = id, corstr = "ar1") Coefficients:

Hi all, I am trying to do a generalized estimating equation (GEE) with the "geepack" package and I am not 100% sure what exactly the "id" argument means. It seems to be an important argument because results differ considerably defining different clusters. I have a data set of counts (poisson distribution): numbers of butterfly species counted every month during a period of

Puedes poner el post de kaggle? Get Outlook for Android<https://aka.ms/ghei36> ________________________________ From: Emilio L. Cano <emilopezcano en gmail.com> Sent: Friday, July 31, 2020 6:05:57 PM To: Jesús Para Fernández <j.para.fernandez en hotmail.com> Cc: r-help-es en r-project.org <r-help-es en r-project.org> Subject: Re: [R-es] Mejor paquete machine learning Yo

I'm trying to fit a generalized mixed effects model to a data set where each subject has paired categorical responses y (so I'm trying to use a binomial logit link). There are about 183 observations and one explanatory factor x. I'm trying to fit something like: (lmer(y~x+(1|subject))) I also tried fitting the same type of model using glmmPQL from MASS. In both cases, I get a

El problema es que te obligaran a usar tibbles y yo soy mas de data.table.... Get Outlook for Android<https://aka.ms/ghei36> ________________________________ From: Emilio L. Cano <emilopezcano en gmail.com> Sent: Friday, July 31, 2020 5:58:00 PM To: Jesús Para Fernández <j.para.fernandez en hotmail.com> Cc: r-help-es en r-project.org <r-help-es en r-project.org> Subject:

I am trying to create a loop that will perform a series of analyses. I am using geeglm from geepack, which fails if there are any null values. Creating a subset solves this, but do not seem to be able to set the subset dynamically based on a changing variable. while (j <= y.num) { strSubset = as.character(df.IV$IV[j]) #Gives column name in quotes df.data.sub = subset(df.data,

Hello, I've problems installing several packages in my R on Fedora 27 64 bit. I found out that it has to do something with a missing compiler (libgfortran.so.3, see below). It works if I downgrade the current version of libgfortran to the specified version by downloading libgfortran-6.2.1-2.fc25.x86_64.rpm and manually installing it. However, I don't want to mess up my system,

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Dear all I am struggling with how to deal with missing values using geeglm. I know that geeglm only works with complete datasets, but I cannot seem to get the na.omit function to work. For example assuming DataMiss contains 3 columns, each of which has missing observations, and an id column with no missing info then identifies the clusters. Outcome: 2 level integer Predictor: numeric variable

I'm sorry I haven't boiled this down to a more-minimal example yet, but ... I'm working on an S3 method (tidy.merMod, in the 'broom' package). It normally handles 'merMod' objects from the lme4 package, but I'm trying to make it handle 'merModLmerTest' objects from the lmerTest package too. The merModLmerTest class inherits (as an S4) class from the

*H*i, I am trying to fit a GEE model with *geeglm* function. The model is the following: Modelo<-geeglm(sqrt ~Tra+ Mes, id=Lugar , data=datos, family=gaussian(identity), corstr="independence") *Tra( is a experimental treatment, 2 levels)*, *Mes* (is the month of take data, 4 levels) and *Lugar* (is the site of study, 3 levels) are categorical variables and *sqrt* (sqrt of Total

Dear R users, I included 2 internal functions in the package 'dlnm', called 'mkbasis' and 'mklagbasis'. Despite they are not meant to be called by the users, I included them in the namespace in order to make them available, keeping the process more transparent and giving the opportunity to change or improve them. I included an help page 'dlnm-internal.Rd' to

Dear R users, I included 2 internal functions in the package 'dlnm', called 'mkbasis' and 'mklagbasis'. Despite they are not meant to be called by the users, I included them in the namespace in order to make them available, keeping the process more transparent and giving the opportunity to change or improve them. I included an help page 'dlnm-internal.Rd' to