similar to: How to calculate the area under the curve

Dear all, I want to manipulate a character string such as ex<-"cbind(data$response1,data$response2)" in R in two ways: 1) extracting the "response1" portion of ex 2) replacing "$" with "." I am wondering that is it possible efficiently doing these in R? Best Ozgur -- View this message in context:

Hello, I am making some use of ROC curve analysis. I find much help on the mailing list, and I have used the Area Under the Curve (AUC) functions from the ROC function in the bioconductor project... http://www.bioconductor.org/repository/release1.5/package/Source/ ROC_1.0.13.tar.gz However, I read here... http://www.medcalc.be/manual/mpage06-13b.php "The 95% confidence interval for

Hi everyone, I am doing 5 years mortality predictive index score with survival analysis using a Cox proportional hazard model where I have a continous predictive variable and a right censored response which is the mortality, and the individuals were followed a maximum of 7 years. I'd like to asses the discrimination ability of survival analysis Cox model by computing a ROC curve and area

Hello! I would like to draw a graph like the following: http://www.optics.rochester.edu/workgroups/cml/opt307/spr04/pavel/plot_small.jpg Aim is to plot confidence intervals of treatments for X(=response1) and Y(=response2) axis simultaneously to visualize aggreement of confidence interval for two responses. Can anyone please provide me some direction to start with? Thanks! -- Kim.

I know how to compute the ROC curve and the empirical AUC from the logistic regression after fitting the model. But here is my question, how can I compute the standard error for the AUC estimator resulting form logistic regression? The variance should be more complicated than AUC based on known test results. Does anybody know a reference on this problem? [[alternative HTML version deleted]]

Dear R-helpers: I want to calculate area under a Receiver Operator Characteristic curve. Where can I find related functions? Thank you in advance Xiao

Question on graphs: The default case for drawing a graph in R, is where a little space is left on the x and y axis before the first tick i.e. even if I say xlim=c(0,1) -- there will be some space between the edge of the x-axis and where 0 is placed. If I want 0 on the edge, how do I do it in R? Area under the curve: I have a 45 degree line and a curve above or below it. Is there a way in R

Dear Sir or Madam? I am a doctor of urology,and I am engaged in developing a nomogram of bladder cancer. May I ask for your help on below issue? I set up a dataset which include 317 cases. I got the Binary Logistic Regression model by SPSS.And then I try to reconstruct the model ?lrm(RECU~Complication+T.Num+T.Grade+Year+TS)? by R-Project,and try to internal validate the model through

Hi, I'm trying to set up a prediction software, now i testing the performance of my method, so i need to calculate a ROC curve, specially auc, cut-off, sens and spec, i just looking at ROCH package, but it's a mass for me, i'm not a math guy and I'm getting lost Could any of you recommend me an easy-to-use package to do this task? i just have a list of positive/negative samples

hello, I am using the ROC package to evaluate predictive models I have successfully plot the ROC curve, however ?is there anyway to obtain the value of operating point=optimal threshold value (i.e. the nearest point of the curve to the top-left corner of the axes)? thank you very much, jose daniel anadon area de ecologia universidad miguel hernandez espa?a

Hello I am new in R. I am trying to implement Biomod 2 package. However, I have a doubt. I want to calculate the mean and sd of "Testing.data" (ROC and TSS) > # let's print the ROC scores of all selected models > myBiomodModelEval_55["ROC","Testing.data",,,] RUN1 RUN2 RUN3 RUN4 RUN5 RUN6 RUN7 RUN8 RUN9 RUN10 0.938 0.938 0.926 0.931 0.939

Dear list   I have 5 markers that can be used to detect an infection in combination. Could you please advise me how to use functions in ROCR/ other package to produce the ROC curve for a combination of markers?   I have used the following to get ROC statistics for each marker. pred <- prediction(y$marker1, y$infectn) perf <-performance(pred,"tpr","fpr")

Hi Group, I have a question about obtaining the bias-corrected c-index using validate from the Design library. As an example, consider the example from help page: library(Design) ?validate.lrm n <- 1000 age <- rnorm(n, 50, 10) blood.pressure <- rnorm(n, 120, 15) cholesterol <- rnorm(n, 200, 25) sex <- factor(sample(c('female','male'),

Hello I am trying to make a graph of 10 different lines built each from 4 different segments and to add a darker line that will represent the average of all graphs - all in the same plot.Actually each line is a ROC plot The code I'm using for plotting one line is as follows: logit.roc.plot <- function(r, title="ROC curve") { old.par <- par(no.readonly = TRUE);

Dear R-philes, I am plotting ROC curves for several cross-validation runs of a classifier (using the function below). In addition to the average AUC, I am interested in obtaining a confidence interval for the average AUC. Is there a straightforward way to do this via the ROCR package? plot_roc_curve <- function(roc.dat, plt.title) { #print(str(vowel.ROC)) pred <-

Dear R-users, The numerical integration example given in Gentleman and Ihaka (2000), "Lexical Scope and Statistical Computing," JCGS, 9, 491-508, is very interesting and helpful in understanding how lexical scope is about. However, I got some questions that I just can't figure out. First all, allow me to copy the two functions given by the authors: midpoint <- function(f, a,

Dear R-helpers, I recently switched from SAS to R, in order to model the occurrence of rare events through logistic regression. Is there a package available in R to calculate the Goodman-Kruskal Gamma? After searching a bit I found a function "rcorr.cens" which should do the job, but it is not clear to me how to define the input vectors? Is "x" a vector with the fitted

Dear all, I want to measure the goodness of prediction of my linear model. That's why I was thinking about the area under roc curve. I'm trying the following, but I don't know how to avoid the error. Any help would be appreciated. library(ROCR) model.lm <- lm(log(outcome)~log(v1)+log(v2)+factor1) pred<-predict(model.lm) pred<-prediction(as.numeric(pred),

Hi R-users, I'm having some problems in using the Hmisc package. I'm estimating a cox ph model and want to test whether the drop in concordance index due to omitting one covariate is significant. I think (but I'm not sure) here are two ways to do that: 1) predict two cox model (the full model and model without the covariate of interest) and estimate the concordance index (i.e. area

Hola! Tengo que hacer una curva ROC com unos datos que obtuve de hacer una macro de excel y aplicar unas reglas, y basicamente tengo que a partir de la variacion del tiempo y la velocidad del barco obtengo diferentes porcentajes de true positives (TP) y false positives (FP) y con eso deberia de construir una curva ROC. Dada mi ignorância en este tema, no se muy bien por donde empezar , estuve