similar to: Correct Interpretation of survreg() coeffs

I downloaded binary of survival5 for windows95 (also the splines, date). The function survsum shows up in content, has a help page, but the function itself is missing. Can we cut and paste the survsum from survival4 ? Mai Zhou P.S. I am not picking on R, not even complaining. I think R is great and I am try to contribute my (small) part to make it even better in way of bug report (or

Dear All, a Surv object I put in a data frame behaves somehow unexpected (see example). If I do a Cox regression on the original Surv object it works. If I put it in a data.frame and do the regression on the data frame it does not work. Seemingly it has to do with the class attribute, because if I change the class attribute to let "Surv" appeare first, again it works. Is this known?

Dear R-helpers: I am trying to fit a multivariate Cox proportional hazards model, modelling survival outcome as a function of treatment and receptor status. The data look like below: # structure of the data str(sample.data) List of 4 $ survobj : Surv [1:129, 1:2] 0.8925+ 1.8836+ 2.1191+ 5.3744+ 1.6099+ 5.2567 0.2081+ 0.2108+ 0.2683+ 0.4873+ ... ..- attr(*, "dimnames")=List of 2

Hello All, ? Am replicating in R an analysis I did earlier using SAS. See this as a test of whether I'm ready to start using R in my day-to-day work. ? Just finished replicating a Kaplan Meier analysis. Everything seems to work out fine except for one thing. The 95% CI around my estimate for the median is substantially larger in R than in SAS. For example, in SAS I have a median of 3.29 with a

I am not sure if this is the right place for that kind of questions, but I wondered that the recommended package survival did not pass R's check procedure without warnings: 1) unbalanced braces: * Rd files with unbalanced braces: * man/Surv.Rd * man/cluster.Rd * man/cox.zph.Rd * man/coxph.Rd * man/coxph.detail.Rd * man/date.ddmmmyy.Rd * man/lines.survfit.Rd *

Dear R users, I am using lmer combined with AIC model selection and averaging (in the MuMIn package) to try and assess how isotope values (which indicate diet) vary within a population of animals. I have multiple measures from individuals (variable 'Tattoo') and multiple individuals within social groups within 4 locations (A, B, C ,D) crucially I am interested if there are

Dear All, Trying to combine two data frames with identical structure by rbind() or merge() I cannot find a way to preserve the class of a Surv object (see example). Reading the help page for rbind, I an uncertain if I could expect that a Surf oject retains it's class, but I would wish it did. Thanks Heinz T?chler R version 2.4.0 Patched (2006-11-03 r39792) Windows XP library(survival) ##

Dear All, there seems to be some strange influence of the Design package on data.frame. If I build a data.frame containing a Surv object without loading the package Design, the data frame is usable to coxph. If instead I just load Design and build a data.frame afterwards, the naming of the Surv object is different and it does not work with coxph. (In my real application I loaded Design to use the

Dear all, This is off-topic, however I hope someone can give me useful suggestion.. Given the regression model y = b0 + b1*x + e I am interested in testing for positive coeffs, namely H0: b0>0 AND b1>0 H1: b0,b1 unconstrained It is simple to estimate the model under H0 and H1 (there are several suggestions on the Rlist about estimation but nothing about testing..) perform a likelihood

Is there any way in R to do a linear regression with positive coefficients only? Thanks for any help! Sandor Lehoczky -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not the subject !) To:

Hi, I am a new R user. I am using it develop regression models with categorical variables. Is there a way to force some regression coefficients to be zero for some of the values in a categorical variable (with 12 factor levels)? I am recoding the values to the default value (1st in the order of dummy's). But I am not sure if this is the correct approach if I want to force coefficients to be

I'm a new user, so my apologies for what is likely a dumb question... I am having a hard time getting a table of regression results when using Koenker's code for quantile regression with fixed effects (http://www.econ.uiuc.edu/~roger/research/panel/rq.fit.panel.R). I use the example data parameters that Koenker provides (see below). m <- 3 n <- 10 s <- rep(1:n,rep(m,n)) x <-

Greetings, I am working in the sem package on a model with 3 exogenous variables (2 are nominal-categorical), and 4 endogenous, continuous variables. To use sem with the nominal variables, I created dummy variables. Now, in my sem output I have estimates for path coefficients for the relationship between each level of the nominal variables and the endogenous variables they are associated

Hi everyone, I am trying to write a title for a plot which has a superscript like D^2 and a value of a variable stored in that variable..... i am not sure if i am clear so i will try an example: Suppose i want my title to be like: Family: Gaussian; D^2 = 0.45 where i have the value 0.45 stored in variable d2 (which comes from some previous calculations, and depending which actual variables

Hello R experts I have two linear regressions for sexes (Male, Female, Unknown). All have a good correlation between body length (response variable) and head length (explanatory variable). I know it is not recommended, but for a good practical reason (the purpose of study is to find a single conversion factor from head length to body length), the regressions need to go through the origin (0

Hi I would really appreciate some help with my code for coxme... My data set I'm interested in survival of animals after an experiment with 4 treatments, which was performed on males and females. I also have two random factors: Response variable: survival (death) Factor 1: treatment (4 levels) Factor 2: sex (male / female) Random effects 1: person nested within day (2 people did

Dear R-helpers: I am trying to fit a multivariate Cox proportional hazards model, modelling survival outcome as a function of treatment and receptor status. The data look like below: # structure of the data str(sample.data) List of 4 $ survobj : Surv [1:129, 1:2] 0.8925+ 1.8836+ 2.1191+ 5.3744+ 1.6099+ 5.2567 0.2081+ 0.2108+ 0.2683+ 0.4873+ ... ..- attr(*, "dimnames")=List of 2

Hi, I have the following data data1 <- data.frame(count = c(0,1,1,2,4,5,13,16,14), weeks = 1:9,                     treat=c(rep("1mg",3),rep("5mg",3),rep("10mg",3))) and I am using library(splines) to fit glm.m <- glm(count~bs(weeks)+as.factor(treat),family=poisson,data=data1) and I am interested in predicting the count variale for the weeks 10, 11 and

Hello Everyone! It's been a while since I last posted a question! Hope everyone has been doing well! ~~~ CONTEXT ~~~ I have recently entered a beginner-level competition on kaggle. The goal of the competition is to build a model that predicts who did/did not survive on the Titanic. I decided to use random forests as I have been wanting to learn the algorithm and the competition

I have a process where I am creating a effects plot similar to the cowles effect example. I would like to add the point estimates to the effects plot, can someone show me the correct syntax. I have included the "R" effects example, so you can show me the correct syntax. Thanks mod.cowles <- glm(volunteer ~ sex + neuroticism*extraversion, data=Cowles, family=binomial)