Re: [R] AUC/Volume under the surface

You need to grasp two concepts: 1) Models in R conventionally have predict methods. To plot your model, predict the dependent variable based on the model object and a grid of your independent variable(s). Whether you have interactions or logistic regression shouldn't be relevant to getting a

[R] AUC/Volume under the surface

Dear Members,I am having trouble in plotting a 3D ROC curve based on multinomial logistic regression. I am also interested in finding AUC/Volume under the surface based on final multivariate model. I do have an interaction term in my final model.  I tried using "HUM" library. But I failed to

[R] AUC from ENFA model

Dear all, I am currently running an ENFA in R using Adehabitat pkg to assess species distribution and I am really stuck and need some help to finalize my project. I run the ENFA in both original location data and pseudo-absence points (the latter randomly generated using dismo pkg), and now I

[R] AUC from ENFA model

Dear all, I am currently running an ENFA in R using Adehabitat pkg to assess species distribution and I am really stuck and need some help to finalize my project. I run the ENFA in both original location data and pseudo-absence points (the latter randomly generated using dismo pkg), and now I

[R] AUC, C-index and p-value of Wilcoxon

Dear all, I am using the ROCR library to compute the AUC and also the Hmisc library to compute the C-index of a predictor and a group variable. The results of AUC and C-index are similar and give a value of about 0.57. The Wilcoxon p-value is 0.001! Why the AUC is showing small value and the

Re: [R] AUC, C-index and p-value of Wilcoxon

On Thu, Feb 09, 2012 at 02:05:08PM +, linda Porz wrote: Dear all, I am using the ROCR library to compute the AUC and also the Hmisc library to compute the C-index of a predictor and a group variable. The results of AUC and C-index are similar and give a value of about 0.57. The Wilcoxon

Re: [R] AUC, C-index and p-value of Wilcoxon

On Thu, Feb 09, 2012 at 06:33:09PM +0100, Petr Savicky wrote: On Thu, Feb 09, 2012 at 02:05:08PM +, linda Porz wrote: Dear all, I am using the ROCR library to compute the AUC and also the Hmisc library to compute the C-index of a predictor and a group variable. The results of AUC

[R] AUC calculated from Epi package

Hi, I have a dataset (see attached) with 2 variables Y is binary, x is a continuous variable. I want to calculate area under the curve (AUC) for the ROC curve, but I got different AUC values using ROC() from Epi package vs. rcorr.cens() from rms package:

Re: [R] auc function

On Thu, Jan 20, 2011 at 03:14:01PM -0800, Changbin Du wrote: ROCR I appreciate this information, which is new for me. Up to now, i was using the function get.auc - function(statistic, label, negative, positive) { xmove - as.numeric(label == negative) ymove - as.numeric(label

[R] auc function

Hi, there. Suppose I already have sensitivities and specificities. What is the quick R-function to calculate AUC for the ROC plot? There seem to be many R functions to calculate AUC. Thanks. Yulei [[alternative HTML version deleted]] __

Re: [R] auc function

ROCR On Thu, Jan 20, 2011 at 3:04 PM, He, Yulei h...@hcp.med.harvard.edu wrote: Hi, there. Suppose I already have sensitivities and specificities. What is the quick R-function to calculate AUC for the ROC plot? There seem to be many R functions to calculate AUC. Thanks. Yulei

[R] AUC

Hello, Is there is any R function computes the AUC for paired data? Many thanks, Samuel [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting

Re: [R] AUC

Samuel, Since the difference in AUCs has insufficient power and doesn't really take into account the pairing of predictions, I recommend the Hmisc package's rcorrp.cens function. Its method has good power and asks the question is one predictor more concordant than the other in the same

Re: [R] AUC / ROC for presence only.

Dear Miltinho, It depends on the species (rare or widespread), and also on how well its distribution is known. You have to make some assumptions about where the species might not be present and generate the pseudo-absences in these areas. However, other people just simply create pseudo-absence

Re: [R] AUC / ROC for presence only.

Dear Miltinho, Since you don´t have absence, I think that you cannot calculate the AUC. However, you can create pseudoabsences (by selecting areas from where you know that the species is not present) at random and use them as surrogates of absences data. This process has its drawbacks, which have

[R] AUC / ROC for presence only.

Dear all, I have a probability of presence of distribution of a species of interest (varying from 0 to 1 in continuous form) and I have a set of points where I know that species really occurs. But I don´t have points of absence. So, for each true presence I know the estimated presence. I

[R] AUC steady state calculations

Hi, a collegue has send me an excel sheet with some plasma values, and now he wants to know the AUC steady state. I took a look at the CRAN taskviews, and came up with PK, PKtools, ... The AUC calculation, no problem with that, but how do I calculate the steady state? One way of thinking was

Re: [R] AUC values from LRM and ROCR

Colin Robertson wrote: Dear List, I am trying to assess the prediction accuracy of an ordinal model fit with LRM in the Design package. I used predict.lrm to predict on an independent dataset and am now attempting to assess the accuracy of these predictions. From what I have read, the

[R] AUC values from LRM and ROCR

Dear List, I am trying to assess the prediction accuracy of an ordinal model fit with LRM in the Design package. I used predict.lrm to predict on an independent dataset and am now attempting to assess the accuracy of these predictions. From what I have read, the AUC is good for this because it