similar to: ImproveProb Function in Design Package

Dear list, I am trying to work out how the improveProb() function works and how to interpret the results, and I have a few questions. I would be grateful if anyone could shed some light on these. in the Net Reclassification Improvement section of the output, is the 2P column the two-sided p-value for the differences in classification? So if a limit is set at 0.05, then lower values indicate

Hi, I am trying to calculate net reclassification improvement (NRI) and Inegrated Discrimination Improvement (IDI) for a survival dataset to compare 2 risk models. It seems that the improveProb() in Hmisc package does this only for binary outcome, while rcorrp.cens() does take survival object, but doesn't output NRI or IDI. Can anyone suggest any other packages that can calculate NRI and IDI

Dear Sirs. I am working with the R packages Hmisc and PredictABEL to make NRI estimates from my Cox models with and without a specific biomarker. According to Pencina et al (Statistics in Medicine 2010, DOI: 0.1002/sim.4085 ), a continuous/non-categorical NRI (NRI>0) is to be used when there are no obvious reason to categorize risk, such as the risk of future cardiovascular events in patients

As describe in the Hmisc package's improveProb function, that function is for binary Y. And it's best to use category-free methods. Frank Petergodsk wrote > Hi > > I'm new to R. > > Is it possible to use the improveProb function to generate categorybased > NRI using a Cox model? > I believe I saw someone mentioning the possibility, but I can't find the

Greetings, I have generated several ROC curves and would like to compare the AUCs. The data are cross sectional and the outcomes are binary. I am testing which of several models provide the best discrimination. Would it be most appropriate to report AUC with 95% CI's? I have been looking in to the "net reclassification improvement" (see below for reference) but thus far I can only

Dear all, I am interested to evaluate reclassification using net reclassification improvement and Integrated Discrimination Index IDI after survival analysis (Cox proportional hazards using stcox). I search a R package or a R code that specifically addresses the categorical NRI for time-to-event data in the presence of censored observation and, if possible, at different follow-up time points. I

Dear all I am trying to compare the performances of several methods using the AUC0.1 and not the whole AUC. (meaning I wanted to compare to AUC's whose x axis only goes to 0.1 not 1) I came to know about the Mcneil Hanley test from Bernardo Rangel Tura and I referred to the original paper for the calculation of "r" which is an argument of the function cROC. I can only find the

Dear, I wanna to compare AUC generated by two distribution models using the same sample. The AUC for model 1 consists of two columns, column A for 0/1 and column B for probability, eahc with the same row number of 3000. The AUC for model 2 consists of two columns, column A for 0/1 and column B for probability, eahc with the same row number of 10000 rows. I am wondering what value I should put

Dear R users Function improveProb in the rms library calculate NRI and IDI for predictions of binary outcome. Do anyone extent its use in survival data? Many thanks. *Yao Zhu* *Department of Urology Fudan University Shanghai Cancer Center Shanghai, China* [[alternative HTML version deleted]]

Hi, I would like to compare differences in AUC from 2 different models, glm and gam for predicting presence / absence. I know that in theory the model with a higher AUC is better, but what I am interested in is if statistically the increase in AUC from the glm model to the gam model is significant. I also read quite extensive discussions on the list about ROC and AUC but I still didn't find

Dear, I wanna to compare AUC generated by two distribution models using the same sample. The AUC for model 1 consists of two columns, column A for 0/1 and column B for probability, eahc with the same row number of 3000. The AUC for model 2 consists of two columns, column A for 0/1 and column B for probability, eahc with the same row number of 10000 rows. I am wondering what value I should put

Dear, I wanna to compare AUC generated by two distribution models using the same sample. I tried improveProb function's example code below. set.seed(1) library(survival) x1 <- rnorm(400) x2 <- x1 + rnorm(400) d.time <- rexp(400) + (x1 - min(x1)) cens <- runif(400,.5,2) death <- d.time <= cens d.time <- pmin(d.time, cens) rcorrp.cens(x1, x2, Surv(d.time, death))

Dear all I have used the lda and predict functions to classify a set of objects of unknown origin. I would like to use a jackknife reclassification to assess the degree to which the outcomes deviate from that expected by chance. However, I can't find any function that allows me to do this. Any suggestions of how to generate the jackknife reclassification to assess classification accuracy?

I have recently started a new job at an NHS hospital in Scotland. Since I took up this post 6 months ago I have had an ongoing dispute with the IT secutiry dept. who refuse to install R on my computer. I previously worked in another branch of the NHS where R was widely used and yet there is nothing I can say which will persuade the IT dept here to even visit the website! With some help from our

Dear all, here is a example of my problem: /#data# g<-c(1,1,1,2,2,2) A<-runif(6,min=1,max=5) B<-runif(6,min=100,max=1000) C<-runif(6,min=30,max=31) D<-runif(6,min=67,max=98765) var<-cbind(A,B,C,D) label<-colnames(var) store<-data.frame(matrix(ncol=2)) colnames(store)=c("usedVar","prediction") library(MASS)#get lda for (i in c(1:4)) { for (k in

Hi! I replace some elements of a matrix a > a [,1] [,2] [,3] [1,] 1 2 3 [2,] 4 5 6 [3,] 7 8 9 [4,] 10 11 12 according to a reclassification matrix such > pares [,1] [,2] [1,] 1 2 [2,] 5 6 [3,] 8 7 to get > b [,1] [,2] [,3] [1,] 1 2 3 [2,] 4 5 6 [3,] 7 8 9 [4,] 10 11 12 As both a and

Dear All, I am using a specific approach for my master thesis. In essence, a supervised reclassification is used as an intermediate step to find chemical parameters which are able to reclassify defined groups. These variables will be used in a next step where location and scale estimators of the groups are important. Traditionally linear discriminant analysis is used for reclassification which

Hi, I have a custom agi which at times does not exit gracefull and crashes in between. The logging options are set to the maximum but I dont see something conclusive in the asterisk log. I have noticed it crash after issuing the "SAY NUMBER" and "GET DATA" agi commands and the agi is spawned with no apparent reason after that. I tried running the application locally and

This isn't an esp urgent issue, but I'd like to use a certain RAM diagnostic (Doc Mem) which I've already posted a note about a couple of months ago. Simply won't work booting the floppy disk image via MEMDISK. In the interim, I've tried to resolve this by changing things on my side. I'm pretty sure it's a XMS incompatibility, as it fails differently depending on

Hi All: In creating a R Notebook I know that in the text I can link to a (sub) section by using the command: [Header 1](#anchor) and putting the appropriate anchor name at the appropriate header. But can the same be done for code chunks, if the code chunk is named? What I want to do is say that such and such code chunk is an example of how to do something, and have that link to the