search for: rcorrp

...tribution 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)) #rcorrp.cens(x1, x2, y) ## no censoring set.seed(1) x1 <- runif(1000) x2 <- runif(1000) y <- sample(0:1, 1000, TRUE) rcorrp.cens(x1, x2, y) improveProb(x1, x2, y) However, a error message jumped out, saying "rcorrp.cens" not found. Please kin...

Dear R-help, Would it be appropriate to do the following to calculate a p-value for the difference between c-ind of x1 and c-inx of x2 using the output from rcorrp.senc() > r<-rcorrp.senc(x1,x1,y) > pValue<-1-pnorm((r[11]-r[12])/(r[2]/r[5])*1.96) Osman O. Al-Radi, MD, MSc, FRCSC Chief Resident, Cardiac Surgery University of Toronto, Canada

...cox model (the full model and model without the covariate of interest) and estimate the concordance index (i.e. area under the ROC curve) with rcorr.cens for both models, then compute the difference 2) predict the two cox models and estimate directly the difference between the two c-indices using rcorrp.cens. But it seems that the rcorrp.cens gives me the drop of Dxy index. Do you have any hint? Thanks Stefano [[alternative HTML version deleted]]

I have two alternative Cox models with C-statistics 0.72 and 0.78. My question is if 0.78 is significantly greater than 0.72. I'm using rcorrp.cens. I cannot find the U statistics in the output of the function. This is the output of the help example: > 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 <- pm...

...observation and, if possible, at different follow-up time points. I know that the ?PredictABEL? Package contains functions for NRI and IDI calculation but it is unclear for me if it allows censored observation. Package ?survIDINRI? calculates only continuous NRI and the function of Package ?Hmisc?[#rcorrp.cens(x1, x2, y) ##] is only for no censored observations. Many thanks. Sincerely, Mario Petretta Dpt. Internal Medicine, Cardiology and Heart Surgery Naples University Federico II - Italy

...ity measure with the "old" comorbidity measure, Charlson's Comorbidity Index. I have nearly 10,000 deaths and 36 candidate comorbidities. I wish to compare the discrimination of the two comorbidity measures, i.e. I have two non-nested Cox models. I get the following output with > rcorrp.cens(myscore.lp, charlson.lp, Surv(time, dead), method=1): x1 = My comorbidity score, x2 = Charlson [,1] Dxy "-0.0605" S.D. "0.00648" x1 more concordant "0.4697" x2 more concordant "0.5302" n &...

...y measure with the "old" comorbidity measure, Charlson's Comorbidity Index. I have nearly 10,000 deaths and 36 candidate comorbidities. I wish to compare the discrimination of the two comorbidity measures, i.e. I have two non-nested Cox models. I get the following output with > rcorrp.cens(myscore.lp, charlson.lp, Surv(time, dead), method=1): x1 = My comorbidity score, x2 = Charlson [,1] Dxy "-0.0605" S.D. "0.00648" x1 more concordant "0.4697" x2 more concordant "0.5302" n...

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 for survival data? The reference for NRI extending to survival data is: Pencina MJ, D'Agostino RB, Steyerberg EW (2011): Extensions of net reclassification...

...thod to compare two C-statistics (Harrells's C - rcorr.cens) obtained from 2 different models in partially paired datasets (i.e. some similar and some different cases), with one continuous independent variable in each separate model? (in a survival analysis context)? I have noticed that the rcorrp.cens function can be used for paired data. Thanks for any help, Hanneke Wijnhoven -- Hanneke A.H. Wijnhoven (PhD) Institute of Health Sciences Vrije Universiteit Amsterdam De Boelelaan 1085 1081 HV Amsterdam The Netherlands Tel. +31 (0) 20 5989951 Fax. +31 (0) 20 5986940 hanneke.wijn...

Hey all, In order to test if a marker is a risk factor, I built two models (using cox proportional hazard model). One model included this marker, and the other is not. Then, I use R package risksetROC to test how much predictive value did the marker add to this model. I get two C statistics by analyzing the linear predictors of the two models into this package. The qustion is How to test if two

Hi, Is there any package or code to compare and display correlated ROC curves in R? Thanks, Reza [[alternative HTML version deleted]]

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

Hello, Is there is any R function computes the AUC for paired data? Many thanks, Samuel [[alternative HTML version deleted]]

Dear All, I am trying to calculate a 95% confidence interval for the difference in two c statistics (or equivalently D statistics). In Stata I gather that this can be done using the lincom command. Is there anything similar in R? As you can see below I have two datasets (that are actually two independent subsets of the same data) and the respective c statistics for the variables in both cases.

Hello, I'm a biostatistician in Toronto. I would like to know if there is anything in survival analysis developed in R for the method "Evaluating the Yield of Medical Test" (JAMA. May 14,1982--Vol 247, No.18 Frank E. Harrell, Jr,PhD; Robert M. Califf, MD; David B. Pryor, MD;Kerry L.Lee, PhD; Robert A. Rosait,MD.) Hope to hear from you and thanks Lisa Wang, MSc Project Organiser

Hello R Community, I'm continuing to work through logistic regression (thanks for all the help on score test) and have come up against a new opposition. I'm trying to compute Somers Dyx as some suggest this is the preferred method to Somers Dxy (Demaris, 1992). I have searchered the [R] archieves to no avail for a function or code to compute Dyx (not Dxy). The overview of Hmisc has

Hi R experts, I am trying to do a prognostic model validation study, using cancer survival data. There are 2 data sets - 1500 cases used to develop a nomogram, and another of 800 cases used as an independent validation cohort. I have validated the nomogram in the original data (easy with the Design tools), and then want to show that it also has good results with the independent data using 60

...at vanderbilt.edu CC: r-help at r-project.org To: samuoko at yahoo.com Date: Mon, 23 Aug 2010 10:26:05 -0500 Subject: 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 pairs of observations?". Frank Frank E Harrell Jr Professor and Chairman School of Medicine Department of Biostatistics Vanderbil...