similar to: Problem with Slope.test function

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, I try to compare the performances of several parameters to diagnose lameness in dogs. I have several ROC curves from the same dataset. I plotted the ROC curves and calculated AUC with the ROCR package. I would like to compare the AUC. I used the following program I found on R-help archives : From: Bernardo Rangel Tura Date: Thu 16 Dec 2004 - 07:30:37 EST

I might be missing something but I thought that AUC was a measure for comparing ROC curves, so there is nothing else needed to "compare" them. The larger AUC is the higher correlation of 2 variables compared. No other measures or calculations are needed. Jarek Tuszynski -----Original Message----- From: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch] On

Dear Rusers, The error for the following was that it cannot allocate the vector of length 1920165909. a <- expand.grid(se1=0:100/100, sp1=0:100/100, se2=0:100/100, sp2=0:100/100, DR=0:100/100) How to solve it? Maybe setwd(dir) can, i am not very sure about it. Any ideas about it? [[alternative HTML version deleted]]

This is a very basic question, so please bear with me. I've been learning about AB Testing, which is largely used in internet marketing to examine the effectiveness of certain aspects of ads, websites, etc. Here's a couple links to people who want to know more about AB Testing:

Please help. I found the code in the archive. The author of this script says: "The first function (seROC) calculate the standard error of ROC curve, the second function (cROC) compare ROC curves." Can some one explain to me what are the na, nn and r parameters which are used as the input to the following two functions? Thanks much in advance. > From: Bernardo Rangel Tura >

Dear R-helper, I would like to compare the AUC of two logistic regression models (same population). Is it possible with R ? Thank you Roman Rouzier [[alternative HTML version deleted]]

Dear List, This may be related to this email thread initiated by Ben Bolker last month: https://stat.ethz.ch/pipermail/r-devel/2011-July/061630.html In answering this Question on StackOverflow http://stackoverflow.com/q/7195628/429846 I noticed that `methods()` was not listing some S3 methods for `plot()` provided by the mgcv package. At the time I wanted to check the development version of R as

Maybe embarassing, but I can't quickly find out how to do this: Mix expression() text and regular text __in a variable__ for plotting: I can easily do plot(1,type="n",main=expression(paste("Plot of ", x ^ alpha, "; ", alpha==2.3) However, if alpha is really just in a variable, I don't know what to do alpha <- 2.3 ch.a <- format(alpha) and now

Maybe embarassing, but I can't quickly find out how to do this: Mix expression() text and regular text __in a variable__ for plotting: I can easily do plot(1,type="n",main=expression(paste("Plot of ", x ^ alpha, "; ", alpha==2.3) However, if alpha is really just in a variable, I don't know what to do alpha <- 2.3 ch.a <- format(alpha) and now

Dear Md Kamruzzaman, I've copied this response to the r-help list, where you originally asked your question. That way, other people can follow the conversation, if they're interested and there will be a record of the solution. Please keep r-help in the loop See below: On 2024-01-17 9:47 p.m., Md. Kamruzzaman wrote: > > Caution: External email. > > > Dear John >

I am attempting to run a glm with a binomial model to analyze proportion data. I have been following Crawley's book closely and am wondering if there is an accepted standard for how much is too much overdispersion? (e.g. change in AIC has an accepted standard of 2). In the example, he fits several models, binomial and quasibinomial and then accepts the quasibinomial. The output for residual

hello I'm learning mgcv and would like to obtain numerical output corresponding to plot.gam. I can do so when seWithMean=FALSE (the default) but only approximately when seWithMean=TRUE. Can anyone show how to obtain the exact values? Alternatively, can you clarify the explanation in the manual "Note that, if seWithMean=TRUE, the confidence bands include the uncertainty about the

Hi All: I have a Cisco3620 with a proper T1/PRI card installed with asterisk running on the same LAN. Since I have lit up the line, I can dial out and make calls to regular lands lines. However when a call comes back in it rings the destination phone once and disconnects. Here is an error from my router 15:40:45: ISDN Se1/0:23 SERROR: L3_GetUser_NLCB: EVENT 0X45 No NLCB 2 15:40:45: ISDN

Hi, I found some info messages below in /var/spool/mail/root. To reduce the size of that file, I'm wondering if there's a way to prevent those unimportant messages from entering /var/spool/mail/root. Thanks. 2010-05-10T10:32:27-05:00 <authpriv.info> se1 su: pam_unix(su-l:session): session closed for user root 2010-05-10T10:01:28-05:00 <local1.info> se1 Keepalived_vrrp:

I am running R version 2.9.2 on Windows XP OS with RODBC version Version: 1.3-0. Has anyone out there in the R user community successfully appended records to a DB2 table on a remote database using the sqlSave function in the RODBC package? (or by any other means from R?) I posed a similar question a few months ago and unfortunately, did not receive a response. I was hoping recent upgrades to

Dear all, May I ask is there any functions in R to evaluate the fitness of "coxph" and "survreg" in survival analysis, please? For example, the results from Cox regression and Parametric survival analysis are shown below. Which method is prefered and how to see that / how to compare the methods? 1. coxph(formula = y ~ pspline(x1, df = 2))

Hi, I would like to do a meta-analysis, i.e., a mixed-effects regression, but I don't seem to get what I want using both the nlme or metafor packages. My question: is there indeed no way to do it? And if so, is there another package I could use? Here are the details: In my meta-analysis I'm comparing different studies that report a measure at time zero and after a certain followup

# Using Moving/Rolling Windows, here we do an OLS Regression with corrections for #Heteroscedasticity and Autocorrelations (HAC) using Newey West Method. This code is a #extension of Ajay Shah?s code for moving windows simple OLS regression. # The easiest way to adjust for Autocorrelations and Heteroscedasticity in the OLS residuals is to #use the coeftest function that is included in the

Dear List, How do I extract the approximate Wald test for the frailty (in the following example 17.89 value)? What about the P-values, other Chisq, DF, se(coef) and se2? How can they be extracted? ######################################################> kfitm1 Call: coxph(formula = Surv(time, status) ~ age + sex + disease + frailty(id, dist = "gauss"), data = kidney)