search for: nomograms

The rms package includes the nomogram function, which generates a list object that can be passed to plot for graphical production of nomograms. I would like to remove the "linear predictor" line in the graph, which means (I suspect) removing it from the nomogram output object. I've looked at the nomogram output object, but it is not clear to me if or how it might be edited to remove the linear predictor content. Simila...

Hi all R users I did a logistic regression with my binary variable Y (0/1) and 2 explanatory variables. Now I try to draw my nomogram with predictive value. I visited the help of R but I have problem to understand well the example. When I use glm fonction, I have a problem, thus I use lrm. My code is: modele<-lrm(Y~L+P,data=donnee) fun<- function(x) plogis(x-modele$coef[1]+modele$coef[2])

Dear volunteer: I am a graduate student of medcine in china.And now,I am devoting myself to constructing a nomograms of bladder cancer.I want to do it with R-project.However, I do not know how to construct a nomograms with R-project.I want to get yours help,thank you! I wish you can tell me the operating procedure of the R-project. And I apologize for my english,it is poor,sorry!...

...use the parameter interact=list(sex=("male","female"),x1=c(a,b,c))... but with rcs or pol transformations of x1, x2 and x3, the choice of the categorization (a,b,c,...) is arbitrary and the nomogram not so useful... Considering that sex is the problem, I thought I could draw two nomograms, one for each sex... based on one model. These would be great. Do you think it's possible ? Taking the exemple of the help of nomogram() (package "rms") : f <- psm(Surv(d.time,death) ~ sex*age, dist=if(.R.)'lognormal' else 'gaussian') Let's add the previously...

Dear R-users, I am a novice R-user with some experience in using the RMS package for taking nomograms after various survival models. This time, I am trying to plot a nomogram after a Random Effects Cox, implemented by the "coxme" package. My questions are: 1. Is it possible to take a nomogram directly after the coxme survival function? 2. If not is there a way to take the linear predictor...

Hello, I am constructing a nomogram using cph and nomogram commands in Dr. Harrell's Design/RMS package. The HR that I obtain for dichotomous and categorical variables are identical to those that I obtain using STATA stcox. However, the inter-quartile HR I obtain for continuous variables is obviously different, since STATA gives me HR for each unit (year, centimeter, etc) like coxph would

Hello, I am using Dr. Harrell's design package to make a nomogram. I was able to make a beautiful one without stratifying, however, I will need to stratify to meet PH assumptions. This is where I go wrong, but I'm not sure where. Non-Stratified Nomogram:

Dear R-users, I have used the nomogram function from the rms package for a logistic regresison model made with lrm(). Everything works perfectly (r version 2.15.1 on a mac). My question is this: if my final model is not the one created by lrm, but I internally validated the model and 'shrunk' the regression coefficients and computed a new intercept, how can I build a nomogram using that

Hi, I would like to emphasize ("zoom") the zone of a nomogram where the probability are > 0.01 (nomogram built with nomogram, Design). As a consequence, I don't need to draw the part of the "Total points" axis with score < 60 equivalent in my case to a linear predictor < 4.5 - As far as I know, this is not possible with the arguments of the function. - Changing

Hello, I am using Dr. Harrell's design 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: f1 <- cph(Surv(retime,dfs) ~ age+her2+t_stage+n_stage+er+grade+cytcyt+Cyt_PCDK2 , data=data11, surv=T,

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,

Hi R users, I'd like to draw a nomogram using a competing-risks regression (crr function in R), rather than a cox regression. However, the nomogram function provided in the Design package is not good for this purpose. Do you have any suggestion. I really appreciate your help Many thanks F.Abdollah, MD San-Raffele hospital Milan, Italy -- View this message in context:

..., +?????????????????????? +??????????????????????funlabel="5year survival", +??????????????????????fun=surv5.CFdata5,fun.at= c(0.01,seq(0.1,0.9,by=0.2),0.99)) Error inapprox(fu[s], xseq[s], fat, ties = mean) : ??needat least two non-NA values to interpolate ? ? I have fit similar nomograms based on cox ph models usingsimilar code, so I?m not sure what I?m doing wrong this time. ? I heard there might be some an issue because of a softwareupdate? ? Thanks, Annie [[alternative HTML version deleted]]

...am(full.approx.lrm, fun.at=c(0.05,0.1,0.2,0.4,0.6,0.8,0.9,0.95), fun=plogis) > plot(full.approx.lrm.nom) Another nomogram using ols model, > full.ols.approx.nom <- nomogram(full.ols.approx, fun.at=c(0.05,0.1,0.2,0.4,0.6,0.8,0.9,0.95), fun=plogis) > plot(full.ols.approx.nom) These two nomograms are very similar but a little bit different. My questions are; 1. Am I doing right? 2. Which nomogram is correct I would appreciate your help in advance. -- KH

I don't think Spencer replied to your message. It wasn't addressed to you. He was replying to a specific post on nomograms. However you might try being less specific as a search on "spatial cluster" gave back [R] mclust - clustering by spatial patterns http://finzi.psych.upenn.edu/R/Rhelp02a/archive/13474.html [R] Spatial Clustering http://finzi.psych.upenn.edu/R/Rhelp02a/archive/19480.html amongst others....

Hi, I used Dr. Harrell's rms package to make a nomogram. Below is my code for nomogram and calculate total points and probability *in original data set* used for building the nomogram. *My question is how I get the formula for calculating the survival probability for this nomogram. Then I can use this formula to do validation by using other data set. * f1 <- cph(Surv(retime,dfs) ~

dear professor: I have a problem about the nomogram.I have got the result through analysing the dataset "exp2.sav" through multinominal logistic regression by SPSS 17.0. and I want to deveop the nomogram through R-Projject,just like this : > n<-100 > set.seed(10) > T.Grade<-factor(0:3,labels=c("G0", "G1", "G2","G3")) >

dear professor: I am a doctor of urinary,and I am developing a nomogram of bladder tumor.Now I have a problem about this. I have got the result like this through analysing the dataset "exp11.sav" through multinominal logistic regression by SPSS 17.0.(the Sig. is high,that is good ,it is just aexperimental data ) Parameter Estimates Ya B Std. Error Wald df Sig. Exp(B) 95%

Hi R users. I have a model of cox that already it is estimated (I have only the model estimated, I haven't data), how can I determine a nomogram with R? Is it posible to do nomograms in Design package? I think that's only when the model (Cox Regression in this case) is before estimated in R. Thanks

...from the fastbw function as inputs to nomogram(). I seem to be failing at this, -- I obtain a subscript out of range error. That I can't do this may speak to technical failings, but I suspect it is because Prof Harrell thinks/knows it injudicious. However, I can't invent a reason why nomograms should be restricted to the full models, if the purpose of fastbw is to generate parsimonious models with appropriate standard errors. I'd welcome comments on either the technical or the theoretical issues. Many thanks in advance, Rob James