similar to: Syntax for iter.max in rms

I am cleaning up the rms package to not export functions not to be called directly by users. rms uses generic functions defined in other packages. For example there is a latex method in the Hmisc package, and rms has a latex method for objects of class "anova.rms" so there are anova.rms and latex.anova.rms functions in rms. I use:

Hi, I am trying to simulate a regression on survival data under a few conditions: 1. Under different error distributions 2. Have the error term be dependent on the covariates But I'm not sure how to specify either conditions. I am using the Design package to perform the survival analysis using the survreg, bj, coxph functions. Any help is greatly appreciated. This is what I have so far:

Hello, I am using Dr. Harrell's rms package to make a nomogram. I was able to make a beautiful one. However, I want to change 5-year survival probability to 5-year failure probability. I couldn?t get hazard rate from Hazard(f1) because I used cph for the model. Here is my code: library(rms) f1 <- cph(Surv(retime,dfs) ~ age+her2+t_stage+n_stage+er+grade+cytcyt+Cyt_PCDK2 , data=data11,

Already outdated, but rounded ;) I literally just opened the 5yrs logo, changed the text and then done: inkscape -z -o logo/fish-10yrs.{png,svg} cp {logo,website}/fish-10yrs.svg and then updated the rest of the files. Signed-off-by: Martin Kletzander <mkletzan@redhat.com> --- Makefile.am | 2 + logo/fish-10yrs.png | Bin 0 -> 65790 bytes logo/fish-10yrs.svg |

Hi, in Design package, a plot of survival probability vs. a covariate can be generated by survplot() on a cph object using the folliowing code: n <- 1000 set.seed(731) age <- 50 + 12*rnorm(n) label(age) <- "Age" sex <- factor(sample(c('male','female'), n, TRUE)) cens <- 15*runif(n) h <- .02*exp(.04*(age-50)+.8*(sex=='Female')) dt <-

A problem has been pointed out by a French user of the survival package and I'm looking for a pointer. > options(OutDec= ",") > fit <- survfit(Surv(1:6 /2) ~ 1) > fit$time [1] NA 1 NA 2 NA 3 A year or two ago some test cases that broke survfit were presented to me. The heart of the problem was numbers that were almost identical, where table(x) and unique(x) gave

The answer to this may be obvious, but I was wondering in the rms package and the survfit(), how you can plot the censored time points as ticks. Take for example, library(survival) library(rms) foo <- data.frame(Time=c(1,2,3,4,5,6,10), Status=c(1,1,0,0,1,1,1)) answer <- survfit(Surv(foo$Time, foo$Status==1) ~1) # this shows the censored time points as ticks at Time = 3 and 4 plot(answer)

Hello, I have a question regarding competing risk regression using cmprsk package (function crr()). I am using R2.9.1. How can I do to assess the effect of qualitative predictor (gg) with more than two categories (a,b,c) categorie c is the reference category. See above results, gg is considered like a ordered predictor ! Thank you for your help Jan > # simulated data to test > set.seed(10)

A new version of rms is now available on CRAN for Linux and Windows (Mac will probably be available very soon). Largest changes include latex methods for validate.* and adding the capability to force a subset of variables to be included in all backwards stepdown models (single model or validation by resampling). Recent updates: * In survplot.rms, fixed bug (curves were undefined if

A new version of rms is now available on CRAN for Linux and Windows (Mac will probably be available very soon). Largest changes include latex methods for validate.* and adding the capability to force a subset of variables to be included in all backwards stepdown models (single model or validation by resampling). Recent updates: * In survplot.rms, fixed bug (curves were undefined if

Hi, I am trying to convert a colleague from using SPSS to R, but am having trouble generating a result that is similar enough to a bootstrapped cox regression analysis that was run in SPSS. I tried unsuccessfully with bootcens, but have had some success with the bootcov function in the rms package, which at least generates confidence intervals similar to what is observed in SPSS. However, the

Hi, I would like to write a function which has the following syntax: myfn <- function(formula, ftime, fstatus, data) { # step 1: obtain terms in `formula' from dataframe `data' # step 2: obtain ftime from `data' # step 3: obtain fstatus from `data' # step 4: do model estimation # step 5: return results } The user would call this function as: myfn(formula=myform,

Dear list members, I have a probably simple question concerning the RSvgDevice. After upgrading from R 1.9.0 to R 2.0.1 the computet svg files looking empty. Each time the RSvgDevice 0.5.3 were used. Scales and headers are printed but the plots are missing: <rect x="433.10" y="246.13" width="0.93" height="29.74"

Dear list, I'm facing the following problem : A cox model with my sex variable interacting with several continuous variables : cph(S~sex*(x1+x2+x3)) And I'd like to make a nomogram. I know it's a bit tricky and one mights argue that nomogram is not a good a choice... I could use the parameter interact=list(sex=("male","female"),x1=c(a,b,c))... but with rcs or pol

Readers, The attempt is to create a bar plot with text labels adjacent to each datum value. Data file: 1,3,A 1,8,B 1,1,C 1,9,D 2,5,C 2,4,E 2,2,F 2,0,G testbarplot<-read.csv('data1.csv', header=FALSE) barplot(axes=FALSE, ann=FALSE, horiz=TRUE, testbarplot[,2], ylab= 'group', xlab= '(x values)', space=c(1,0,0,0, 1,0,0,0)) text(testbarplot[,2], testbarplot[,1],

Use only plain text emails. Don't attach file types that will be stripped. See the footer at the bottom of your email for more information. Do give us the data using dput(): > dput(testbarplot) structure(list(V1 = c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L), V2 = c(3L, 8L, 1L, 9L, 5L, 4L, 2L, 0L), V3 = structure(c(1L, 2L, 3L, 4L, 3L, 5L, 6L, 7L), .Label = c("A", "B",

Hello everyone, (This is my second question posted today on the R list). I am carrying out a competing risks analysis using the cuminc function...this takes the form: cuminc(ftime,fstatus,group) In my study, fstatus has 3 different causes of failure (1,2,3) there are also censored cases (0). "group" has two levels (0 and 1). I therefore have 6 different cumulative incidence curves:

Dear R-help, I am trying to obtain the baseline survival estimate of a fitted Cox model (S_0 (t)). I know that previous posts have said use 'basehaz' but this gives the baseline hazard function and not the baseline survival estimate. Is there a way to obtain the baseline survival estimate or do I have to use the formula which does something like S(t) = exp[- the integral from 0 to t of

Hi I use RSvgDevice to output plot, and modify them using svg editor (inkscape or sodipodi on Linux). Some month ago, results were perfect. I did exactly the same analysis today on the same data, and unfortunatly the results are different. While looking to the svg file, it seems that all information concerning "fill" and "stroke" of objects are lost. The consequence is that

Hi I am trying to install "rms" package but while installing it shows following error package 'survival' 2.36-2 is loaded, but >= 2.36.3 is required by 'rms' what to do? i am using linux OS I have tried by updated r-base-core but it didnt work regards GRR [[alternative HTML version deleted]]