similar to: calibration curve options

Hi, the calibrate.cph() function in rms package generate calibration curve for Cox model on the same dataset where the model was derived using bootstrapping or cross-validation. If I have the model built on dataset 1, and now I want to produce a calibration curve for this model on an independent dataset 2, how can I do that? Thanks John [[alternative HTML version deleted]]

Hi, I created a logistic regression model using the glmnet package. This model is of class "glmnet" or "lognet". I wanted to plot a calibration curve for this model using the calibrate() function from rms package, but the objects used are different, rms requires a fit from lrm(). Is there another function for getting the calibration plot for this glmnet object, or can anyone

While sm4.6ll<-fit.mult.impute(Surv(agesi, si)~partner+ in.love+ pubty+ FPA+ strat(gender),fitter = cph, xtrans = dated.sexrisk2.i, data = dated.sexrisk2, x=T,y=T,surv=T, time.inc=16) runs perfectly using Hmisc, Design and mice under R11 run via Sciviews-K, with library(Design) library(mice) ds2d<-datadist(dated.sexrisk2) options(datadist="ds2d")

Hi, Sorry not to provide R-code in my previous mail. R code is below #install.packages("rms") require(rms) #install.packages("mstate") library(mstate) require(splines) library(ggplot2) library(survival) library(splines) #install.packages("survsim") require(survsim) set.seed(10) df<-crisk.sim(n=500, foltime=10, dist.ev=rep("lnorm",2),

Good afternoon! I need to evaluate the goodness-of-fit (aka calibration) for survival probability estimates from a Cox model. I tried to use 'calibrate' in the Design package but I'm not sure if it should/would produce what I need (ie a chi-sq type statistic with a table of expected vs observed probabilities). Any other functions I should be aware of? Also, has anybody come across

Hi, I have a binary variable and corresponding predicted probability (using logistic regression on some explanatoey variables); I want to check that the model is well-calibrated using a calibration plot. how can I have the calibration plot for my data? thanks. [[alternative HTML version deleted]]

Dear all, when i do the calibration plot, i put the x label y label , there is some labels are i did not put it , like "resample optimism added ..." i want to get rid of the these label , is any body know how can i get rid of these label. these are the following command i used cal <- calibrate(f, u=12, method=c("boot"), B=100,m=70, data=a1)

I have been working on fitting Cox model for prediction by using rms package. I want to measure model's calibartion and discrimination. Discrimination was measured by using validate() in rms, Dxy can be transferred to Harrell's c index. But in this way, I cannot get 95%CI of c index. How can I do this in R? And by the way, what value should be in c index to present the model's well?

I'm looking to buy some new UPSs and am thinking of parting ways with APC to explore other brands. Can anyone suggest another brand that handles doing calibration runs (or maybe another brand doesn't need them) that I can automate with NUT? Thanks, -Ben

Dear Geskus, I want to develop a prediction model. I followed your paper and analysed thro' weighted coxph approach. I can develop nomogram based on the final model also. But I do not know how to do internal validation of the model and subsequently obtain calibration plot. Is it possible to use Wolbers et al Epid 2009 approach 9 (R code for internal validation and calibration) . It is

Hi R experts, I am trying to do a prognostic model validation study, using cancer survival data. There are 2 data sets - 1500 cases used to develop a nomogram, and another of 800 cases used as an independent validation cohort. I have validated the nomogram in the original data (easy with the Design tools), and then want to show that it also has good results with the independent data using 60

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:

Is there a way to calibrate gamepads for wine? I have managed to get my PS3 sixaxis working, but when I play a game, everything works properly but the analogue stick. If I move it all the way to the right or down, it goes in the opposite direction, respectively. Anyone know how I might fix this?

Hi! How can I exclude the legends from calibration plots  generated by calibrate.cph regards, Salvo [[alternative HTML version deleted]]

Hola a todos, Estoy iniciandome en R y la verdad es que aun estoy muy muy verde.... Estoy intentando clasificar unos datos con support vector machines, pero me da fallo al usar la funcion predict. El código que uso es el siguiente: calibrate<-read.table("calibration.txt", header=TRUE) calibrate$calibration<-as.factor(calibrate$calibration)

Hello, I am using an APC UPS (Smart-UPS 2200 RM) to secure my SAN. The SAN runs on FreeBSD 9.1-RELEASE-p5 and is using NUT 2.6.5 version 2. Since the UPS has also a Network card AP9630 I am using the snmp-ups driver to connect the SAN to the UPS for signaling. Last week I need to change the battery pack and then I needed to perform a runtime calibration. I used the web interface of the AP9630

Hi; Does anyone know how to create a calibration and validation set from a particular dataset? I have a dataframe with nearly 20,000 rows! and I would like to select (randomly) a subset from the original dataset (...I found how to do that) to use as calibration set. However, I don't know how to remove this "calibration" set from the original dataframe in order to get my

Dear R users, I am a new R user and something stops me when I try to write a academic article. I want to make a nomogram to predict the risk of prostate cancer (PCa) using several factors which have been selected from the Logistic regression run under the SPSS. Always, a calibration plot is needed to validate the prediction accuracy of the nomogram. However, I tried many times and read a lot of

Hola de nuevo, Esta es la información de mi sesion: R version 2.10.1 (2009-12-14) i386-pc-mingw32 locale: [1] LC_COLLATE=Spanish_Spain.1252 LC_CTYPE=Spanish_Spain.1252 [3] LC_MONETARY=Spanish_Spain.1252 LC_NUMERIC=C [5] LC_TIME=Spanish_Spain.1252 attached base packages: [1] stats graphics grDevices utils datasets methods base Lo que yo prentendo es

Dear R users, I am new to R and wanted to apply competing risk methods in my research work. I used the R code given by Zhang et al in his paper 'Nomogram for survival analysis in the presence of competing risks published in Ann Trans Med 2017:5(20):403. I am struggling with getting calibration curve thro' internal validation. I am happy to receive suggestion in the coding as well