Displaying 20 results from an estimated 1000 matches similar to: "use of "rcorr.cens" with binary response?"
2011 Mar 01
1
which does the "S.D." returned by {Hmisc} rcorr.cens measure?
Dear R-help,
This is an example in the {Hmisc} manual under rcorr.cens function:
> set.seed(1)
> x <- round(rnorm(200))
> y <- rnorm(200)
> round(rcorr.cens(x, y, outx=F),4)
C Index Dxy S.D. n missing
uncensored Relevant Pairs Concordant Uncertain
0.4831 -0.0338 0.0462 200.0000
2011 May 22
1
How to calculate confidence interval of C statistic by rcorr.cens
Hi,
I'm trying to calculate 95% confidence interval of C statistic of
logistic regression model using rcorr.cens in rms package. I wrote a
brief function for this purpose as the followings;
CstatisticCI <- function(x) # x is object of rcorr.cens.
{
se <- x["S.D."]/sqrt(x["n"])
Low95 <- x["C Index"] - 1.96*se
Upper95 <- x["C
2011 Jun 13
1
Somers Dyx
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
2009 Mar 09
1
rcorr.cens Goodman-Kruskal gamma
Dear r-helpers!
I want to classify my vegetation data with hierachical cluster analysis.
My Dataset consist of Abundance-Values (Braun-Blanquet ordinal scale; ranked) for each plant species and relev?.
I found a lot of r-packages dealing with cluster analysis, but none of them is able to calculate a distance measure for ranked data.
Podani recommends the use of Goodman and Kruskals' Gamma for
2007 Dec 19
1
using rcorr.cens for Goodman Kruskal gamma
Dear List,
I would like to calculate the Goodman-Kruskal gamma for the predicted
classes obtained from an ordinal regression model using lrm in the Design
package. I couldn't find a way to get gamma for predicted values in Design
so have found previous positings suggesting to use :
Rcorr.cens(x, S outx = TRUE) in the Hmisc package
My question is, will this work for predicted vs
2006 Apr 21
1
rcorrp.cens
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
2004 Mar 11
5
Receiver Operator Characteristic curve
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
2013 Jan 24
4
Difference between R and SAS in Corcordance index in ordinal logistic regression
lrm does some binning to make the calculations faster. The exact calculation
is obtained by running
f <- lrm(...)
rcorr.cens(predict(f), DA), which results in:
C Index Dxy S.D. n missing
0.96814404 0.93628809 0.03808336 32.00000000 0.00000000
uncensored Relevant Pairs Concordant Uncertain
32.00000000
2008 Mar 26
2
pseudo R square and/or C statistic in R logistic regression
Dear all,
I am now doing the logistic regression using R. (glm, family=binomial). Besides the standardize summary statistics generated from R, I am also interested in some more informations concerning the model fitting / prediction etc; Particularly I am interested in "pseudo R squar" and "C statistic". I searched the R- help and could only get very limited information. (Post
2009 Sep 08
1
rcorrp.cens and U statistics
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
2009 Jul 17
2
Getting the C-index for a dataset that was not used to generate the logistic model
Does anyone know how to get the C-index from a logistic model - not using
the dataset that was used to train the model, but instead using a fresh
dataset on the same model?
I have a dataset of 400 points that I've split into two halves, one for
training the logistic model, and the other for evaluating it. The structure
is as follows:
column headers are "got a loan" (dichotomous),
2011 Jun 21
0
relation between tdrocc AUC and c-statistic from rcorr.cens
I am using the rcorr.cens function from the Hmisc package and the time-dependent ROC curve obtained using tdrocc in the survcomp package.
I understand that the C statistic from rcorr.cens has to be subtracted from 1 if high values of the risk variable lower survival.
Given that I wonder what the connection is between that C statistic and the AUC from the tdrocc object. If they are substantially
2004 Jul 19
2
Evaluating the Yield of Medical Tests
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
2006 Jan 04
1
silly, extracting the value of "C" from the results of somers2
Sorry I have a very simple question:
I used somers2 function from Design package:
> z<- somers2(x,y, weights=w)
results are:
>z
C Dxy n Missing
0.88 0.76 500 0.00
Now I want to call only the value of C to be used in further analyses, but I
fail to do it. I have tried:
> z$C
NULL
> z[,C]
Error in z[,C]: incorrect number of dimensions
and some other silly
2008 Sep 08
2
ROC curve from logistic regression
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?
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2005 Jul 19
1
ROC curve with survival data
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
2005 Nov 25
3
obtaining a ROC curve
Hello,
I have a classification tree. I want to obtain a ROC curve for this test. What is the easiest way to obtain one?
-Anjali
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2008 Mar 06
2
calculate AUC and plot ROC in R
Hi, there:
Could someone tell me a simple function of plot ROC curve and calculate
AUC in R? My setting is very simple, a column of the true binary
response and another column of predicted probabilities.
Thanks!
Yulei
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2010 Jan 22
2
Computing Confidence Intervals for AUC in ROCR Package
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 <-
2008 Jan 05
1
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 is threshold
independent. I obtained the AUC for the fit model output from the c score (c
=