Displaying 20 results from an estimated 110 matches similar to: "How to calculate confidence interval of C statistic by rcorr.cens"
2011 Nov 20
1
Cox proportional hazards confidence intervals
I am calculating cox propotional hazards models with the coxph
function from the survival package. My data relates to failure of
various types of endovascular interventions. I can successfully
obtain the LR, Wald, and Score test p-values from the coxph.object, as
well as the hazard ratio as follows:
formula.obj = Surv(days, status) ~ type
coxph.model = coxph(formula.obj, df)
fit =
2004 Jun 04
1
use of "rcorr.cens" with binary response?
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
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
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
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
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
How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction
2011 Aug 17
4
How to use PC1 of PCA and dim1 of MCA as a predictor in logistic regression model for data reduction
Hi all,
I'm trying to do model reduction for logistic regression. I have 13
predictor (4 continuous variables and 9 binary variables). Using subject
matter knowledge, I selected 4 important variables. Regarding the rest 9
variables, I tried to perform data reduction by principal component
analysis (PCA). However, 8 of 9 variables were binary and only one
continuous. I transformed the data by
2009 Aug 26
1
Within factor & random factor
Hi,
I am quite new to R and trying to analyze the following data. I have 28
controls and 25 patients. I measured X values of 4 different locations
(A,B,C,D) in the brain image of each subject. And X ranges from 0 to 1.
I think "control or patient" is a between subject factor and location is
a within subject factor. So,
controls: 28
patients: 25 (unbalanced data set)
respone measure:
2011 Jul 20
0
Cleveland Dot plots: tick labels and error bars
Dear list,
I've been learning how to make a 2x2 paneled dotplot in lattice without any
previous experience using lattice.
my code thusfar is:
nut<-read.table("/Users/colinwahl/Desktop/nutsimp_noerror.csv", T, sep=
",")
attach(nut)
nut1<-data.frame(Nitrate, Total_Nitrogen, Phosphate, Total_Phosphorus)
nut1<-as.matrix(nut1)
rownames(nut1)<-group
2012 Dec 23
0
permutation test for PLS/PLSDA
Hi,
Is there any R package doing permutation/randomization test for
PLS/PLSDA? I found some codes for MatLab, but I want to use R program.
Thank you very much in advance.
Kohkichi Hosoda
2011 May 15
5
Question on approximations of full logistic regression model
Hi,
I am trying to construct a logistic regression model from my data (104
patients and 25 events). I build a full model consisting of five
predictors with the use of penalization by rms package (lrm, pentrace
etc) because of events per variable issue. Then, I tried to approximate
the full model by step-down technique predicting L from all of the
componet variables using ordinary least squares
2010 Jan 04
1
no "rcorrp.cens" in hmisc package
Dear,
I wanna to compare AUC generated by two distribution 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))
2012 Apr 08
0
Need help interpreting output from rcorrp.cens with Cox regression
Dear R-listers,
I am an MD and clinical epidemiologist developing a measure of comorbidity severity for patients with liver disease. Having developed my comorbidity score as the linear predictor from a Cox regression model I want to compare the discriminative ability of my comorbidity measure with the "old" comorbidity measure, Charlson's Comorbidity Index. I have nearly 10,000
2012 Aug 17
0
REPOST: Need help interpreting output from rcorrp.cens with Cox regression
I am reposting my message from April 8th because I never received a response to the original post:
Dear R-listers,
I am an MD and clinical epidemiologist developing a measure of comorbidity severity for patients with liver disease. Having developed my comorbidity score as the linear predictor from a Cox regression model I want to compare the discriminative ability of my comorbidity measure with
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
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
2008 Nov 11
1
how to export results of rcorr into excel
Hi,
I try to export the outputs of rcorr into excel. but I got error message,"cannot coerce class "rcorr" into a data.frame". Actually i just need export part of results of this analysis,e.g. p-values or stat-values.
Does anyone have sort of exprience before or you can help on how to export subset of results of analysis?
Many Thanks!
Xin
2008 Jul 31
0
Sperman Correlation with rcorr (Hmisc)
Hello R-User!
I have a data.frame with 82 variables (columns) and 290 rows.
The variables are set to classes factor, ordered factor and numeric.
I used the following code
Matrix.My.data<-as.matrix(Df.My.Data[2:82])
Matrix.My.data.rcorr<-rcorr(Matrix.My.data, type="spearman")
and got the following message:
Fehler in storage.mode(x) <- if (.R.) "double" else
2009 Jul 01
1
Rcorr
Hi,
I've just run an rcorr on some data in Spearman's mode and it's just
produced the following values;
[,1] [,2]
[1,] 1.00 -0.55
[2,] -0.55 1.00
n= 46
P
[,1] [,2]
[1,] 0
[2,] 0
I presume this means the p-value is lower than 0.00005, but is there any
way of increasing the number of significant figures used? How should I
interpret this value?
Cheers
Jim
2010 May 05
1
rcorr p-values for pearson's correlation coefficients
Hi! All,
To find co-expressed genes from a expression matrix of dimension (9275
X 569), I used rcorr function from library(Hmisc) to calculate pearson
correlation coefficient (PCC) and their corresponding p-values. From
the correlation matrix (9275 X 9275) and pvalue matrix (9275 X 9275)
obtained using rcorr function, I wanted to select those pairs whose
PCC's are above 0.8 cut-off and then