similar to: glht() used with coxph()

Hello, In package survival should be a dataset bladder1. http://stat.ethz.ch/R-manual/R-devel/library/survival/html/bladder.html I can not open it (not found). Both bladder and bladder2 are there. Thanks, Petra

Dear All, simetimes when I load an Rdata I get this message ####### Code: load('bladder1.RData') Carico il pacchetto richiesto: rpart ( Bad traslastion: Load required package-...) Carico il pacchetto richiesto: MASS Carico il pacchetto richiesto: mlbench Carico il pacchetto richiesto: survival Carico il pacchetto richiesto: splines Carico il pacchetto richiesto: 'survival'

> On Apr 16, 2018, at 3:20 PM, David Winsemius <dwinsemius at comcast.net> wrote: > >> >> On Apr 16, 2018, at 2:58 PM, Therneau, Terry M., Ph.D. via R-devel <r-devel at r-project.org> wrote: >> >> A user asked me about this and I can't figure it out. >> >> tmt% R >> R Under development (unstable) (2018-04-09 r74565) --

Hi All, I am fitting a tree to censored survival data using the rpart package and wanted to better understand the results. I am trying to interpret the output from the tree. I am interested in understanding what "yval" is for a survival tree. I see in the output of summary, the phrase "estimated rate". The estimated rate is 1 for the entire tree, and more of less for each

Last week Giovanni Parrinello posted a message asking why various packages were loaded when he loaded an .Rdata file. Brian Ripley replied saying he thought it was because the saved workspace contained a reference to the namespace of ipred. (Correspondence copied below). This begs the question: how did the reference to the namespace of ipred come to be in the .Rdata file? Brian did say it is

Hi there, I perform a stratified cox and then I need the strata as a  numeric array "straft.ln" ft.ln <- coxph(Surv(times,deaths)~ages+chemos+chemos:f1+chemos:f2+horms+horms:f1+horms:f2+grades+grades:f1+grades:f2+positives+positives:f1+positives:f2+sizes+sizes:f1+sizes:f2+strata(stra),data=ddd) basehazzft.ln=basehaz(ft.ln,centered=FALSE) H0ft.ln=c(basehazzft.ln[,1])

Last week Giovanni Parrinello posted a message asking why various packages were loaded when he loaded an .Rdata file. Brian Ripley replied saying he thought it was because the saved workspace contained a reference to the namespace of ipred. (Correspondence copied below). This begs the question: how did the reference to the namespace of ipred come to be in the .Rdata file? Brian did say it is

A user asked me about this and I can't figure it out. tmt% R R Under development (unstable) (2018-04-09 r74565) -- "Unsuffered Consequences" Copyright (C) 2018 The R Foundation for Statistical Computing Platform: x86_64-pc-linux-gnu (64-bit) > library(survival) > data(cgd0) Warning message: In data(cgd0) : data set ?cgd0? not found ---- The data set is present and can be

It's been a few weeks I'm racking my brains on how to use the function glht the package multcomp to test interactions. Unfortunately, the creator of the package forgot to put a sample in pdf package how to do it. I have looked in several places, but found nothing. If someone for the love of God can help me I'll be extremely grateful. The model is glm. -- View this message in context:

Dear List, Could you tell why I get the error message? > library(multcomp) > data("cholesterol") > m = aov(response ~ trt, data = cholesterol) > cht <- glht(m, linfct = mcp(trt = "Tukey")) Error: could not find function "glht" Thank you G?bor

Hi All, I have used glm to model my data, I have two factors and a covariate as described in the example code below (mod.1). I have been able to "force" glht to perform multiple comparisons by creating a combined variable for the factors, accepting that there will be a loss of statistical power as it seems to do what I want. I then use the cld function to generate the letters of

Dear all, glht (from the multcomp package) needs a term and a model component in it's fitted model. In fitted models from e.g. repeated measurements ANOVAs I do not find neither model nor term. Is it possible to build together a model and term component myself, so that glht will work for repeated measurements ANOVAs? If so, how would I do that? Best regards, Michael Zehetleitner

Hi, i was working with this model > mq<-glm(rojos~edadysexo*zona*estacion,quasipoisson) and i get this minimal adequate model > anova(mq5,test="F") Df Deviance Resid. Df Resid. Dev F Pr(>F) NULL 518 64799 edadysexo 2 1556.5 516 63243 8.9434 0.0001524 *** zona 4

fixed @ R-forge. New version should appear on CRAN soon. Thanks for the report! Torsten > > ---------- Forwarded message ---------- > Date: Sat, 3 Sep 2011 23:56:35 +0200 > From: Ulrich Halekoh <Ulrich.Halekoh at agrsci.dk> > To: "r-help at r-project.org" <r-help at r-project.org> > Subject: [R] glht (multcomp): NA's for confidence intervals using

Dear R-user I used lme to fit a linear mixed model inlcuding weights=varPower(). Additionally I wanted to use glht to calculate Tukey-Kramer multiple comparision. error: > glht(modelF, linfct=mcp(Species="Tukey")) Error in glht.matrix(model = list(modelStruct = list(reStruct = list(SubPlot = -0.305856275920955, : ?ncol(linfct)? is not equal to ?length(coef(model))? >

Hi everyone, I am new to R and have a question that relates to unplanned post-hoc comparisons using the multcomp package after a mixed effects model. I couldn't find the answer to it in the archive or in any manual. I have a dataset in which several plants have been treated in a particular way and a continuous response variable has been measured depending on several leaves per plant. I am

Hi all, I've posted this question before, but did not get any reply. I post it again here and see if anybody can help. Thank you. I have a nested model with the following effects fixed: treatments random: experiment_date I used lme() to model the data mod1 <- lme(N_cells ~treatments-1, random=~1|experiment_date, method='ML') Then I want to compare all the other

Greetings, In the following one-way ANOVA I am attempting to calculate the means of each treatment along with their 95% Tukey confidence intervals for the data shown below using a routine from the HH package. library(HH) options(digits=10) # load data treat voltage 1 130 1 74 1 155 1 180 2 150 2 159 2 188 2 126 3 138 3 168 3 110 3 160 4 34

Hi, I have data with binomial response variable (survival) and 2 categorical independent variables (site and treatment) (see below).? I have run a binomial GLM and found that both IVs and the interaction are significant.? Now I want to do a post-hoc test for all pairwise comparisons to see which treatment groups differ.? I tried the glht function in the multcomp package, but I get surprising

Hi dears, I do > CHOL<-lme(chol~rt*cd4+sex+age+rf+nadir+pharmac+factor(hcv)+factor(hbs)+ haartd+hivdur+factor(arv), random= ~rt|id, na.action=na.omit) ...runs sweet,..then ....try a multicomparisons approach for the categorical rf > summary(glht(CHOL, linfct=mcp(rf="Tukey"))) * Error in model.frame.default(object, data, xlev = xlev) : l'oggetto non è una matrice