search for: reclassifing

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

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 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

Hi all, Is the reclassify function useful for really reclassifing ? I couldnt find any samples or documents about this function. I want to pick a packet that''s over a specific rate, and reclassify that to arbitrary class that I specify. I''ve tested with the ingress filter, but it didnt work. (the script below in the ingress, and a simple qdisc,...

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

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 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?

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

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 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

Hello Thanks to Frank Harrell for the great Design package. I noted from Pencina's Article (Statistics in Medicine Vol 27, pp157-172) that the result obtained for the Net Reclassification Index depends upon categorical cut-offs for risk (eg in the paper <6%, 6-20% and >20%). I wondered how the improveprob function arrives at its cut-offs, and whether there was any function to change the

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 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

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

I'm trying to do a rewrite of the dspam_plugin for dovecot 1.1b1. There are some API changes that warranted an update of the plugin. Also, I wanted the dspam_plugin to be able to handle pristine mails for dspam retraining, as opposed to the signature based retraining. Question: How can I retrieve the full unix path for a specific mail? The original code uses mail_get_first_header() to

Dear R-Help, I have a clustering problem with hclust that I hope someone can help me with. Consider the classic hclust example: hc <- hclust(dist(USArrests), "ave") plot(hc) I would like to cut the tree up in such a way so as to avoid small clusters, so that we get a minimum number of items in each cluster, and therefore avoid singletons. e.g. in this example, you can see

Hello, What exactly is the use of the "reclassify" option in the policing options of tc filters? According to LARTC: " reclassify Most often comes down to reclassification to Best Effort. This is the default action. " I don''t quite get the meaning of that. It could mean to let other filters handle it, but that is exactly the "continue" option. Could

Hi, on my small Xen-virtualised server with 48 MiB RAM I use Postfix and Dovecot, because the Debian administrators dislike qmail [1], which is in my opinion despite some maintainability and code quality issues a quite well designed software, because it mostly follows the UNIX principles. Postfix is not able to sort my E-Mail into different Maildir folders and after I looked at procmail's