similar to: weight factor in somers2 function

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

I have columns in two tables that need to be compared in order to get a statistic. The function calculating the statistic is somers2. Here are the two columns I must calculate, row by row. name1 name2 1 Pred_pres_a_indpdt[,3,,] population[,23] 2 Pred_pres_b_indpdt[,3,,] population[,24] 3 Pred_pres_c_indpdt[,3,,] population[,25] 4 Pred_pres_d_indpdt[,3,,]

This code works: x<-letters[1:6] ycols<-23:28 xcols<-rep(c(3,4,5,8),each=length(ycols)) somertime<-function(i,j)somers2(Pred_pres_a_indpdt[,i,,], population[,j]) results<-mapply(somertime,xcols,ycols) How can I make variable "h" work? x<-letters[1:6] ycols<-23:28 xcols<-rep(c(3,4,5,8),each=length(ycols))

I have a series of columns that need to be evaluated in various tables. I need to apply a function in the following manner somers2(name1,name2). name1 is a vector of x inputs for the function which correspond to a vector of y inputs in name2. y<-rep(c(3,4,5,8),6) z<-rep(c(23,24,25,26,27,28),4) name1<-sprintf("Pred_pres_%s_indpdt[,%s,,]",x,y)

Dear R-Gurus: This afternoon I was installing the "Hmisc" package. I use R in Linux (Fedora Core 1 (yarrow)) on a Compaq presario with 128 MB RAM laptop. Opening an R session as a root user (superuser), I issued install.packages("Hmisc") and waited. R downloaded the package, installation was going on, and on the standard output I could see that a list of

Dear R, Short verse of the question: Is there R code which will calculate surrogate splits and/or delta impurity for decision trees at each node? Long Version: I have local, legacy code which I use to calculate my decision trees. I would like to switch to R, but as I understand it surrogate splits are not implemented. Surrogate splits and feature ranking are described in Breiman et al

Dear r-help, I am looking for additional documentation on the "adj" column in rpart's splits matrix. The help says: adj gives the adjusted concordance for surrogate splits I am looking info about "adjusted concordance". I cannot find this phrase in either Therneau & Atkinson original RPART documentation or the CART book. This question came up in the

R helpers, I am working with the R program performing multivariate regression trees (MRT). I have a matrix with species and environmental variables saved as a CSV file (sprot_matrix.csv), I have 42 species and 8 environmental variables (SECCHI+PH+TA+PTOT+NTOT+CHLA+AREA+ MEANDEP) for 104 samples Title SpA SpB SpC SpD Varible1 Variable2 Variable3 Sample1 Sample 2

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

Dear R-help, I would like to compute the variance for the proportion of treatment effect by a surrogate in a survival model (Lin, Fleming, and De Gruttola 1997 in Statistics in Medicine). The paper mentioned that the covariance matrix matches that of the covariance matrix estimator for the marginal hazard modelling of multiple events data (Wei, Lin, and Weissfeld 1989 JASA), and is implemented

Dear All, I am new to R and am trying to learn how to create functions using R. Below is code which calculates Lin's Concordance Coefficient. After I calculate the coefficient I want to create a scatter plot which annotates the coefficient along with preceding text onto the plot. The below code doesn't seem to work. If I use only the object 'lincc' on the text command it works

I am using GLM to calculate logit models based on cross-sectional data. I am now down to the hard work of making the results intelligible to very average readers. Is there any way to calculate a psuedo analoque to the R^2 in standard linear regression for use as a purely descriptive statistic of goodness of fit? Most of the readers of my report will be vaguely familiar and more comfortable with

Dear colleagues in R, Has anybody implemented the 1) (Goodman & Kruskal) lambda or the 2) (Thiel's) uncertainty coefficient statistics (in the asymmetric and symmetric forms), or is anyone aware that they might reside in some package? A search in the R archives does indicate that they are (somehow) part of the CoCo package, but I would rather not start learning how to transform my

Hello everyone. This is a question regarding generation of the concordance index (c index) in R using the function rcorr.cens. In particular about interpretation of its direction and form of the 'predictor'. One of the arguments is a "numeric predictor variable" ( presumably this is just a *single* predictor variable). Say this variable takes numeric values.... Am I

Dear all, As I said in my previous email I have just upgraded to R 2.14.0 on Windows 7. I have just run the 'coxph' function and notice that a Concordance statistic is produced. Is there any way to extract this information from the output? E.g. can I call the concordance value independently of calling the output? Many thanks, Laura [[alternative HTML version deleted]]

R helpers, I would like to know if it is possible that the last version of R is not giving the surrogate splits when you perform a Multivariate regression tree analysis? I installed the programm in different computers and i run the some matrix and it didn't gave me this information. With a previus version R 2.1.1. I do get the information for the surrogates. Please let me know how to get the

Hi, When I look at the summary of an rpart object run on my data, I get 7 nodes but when I plot the rpart object, I get only 3 nodes. Should the number of nodes not match in the results of the 2 functions (summary and plot) or it is not always the same? Look forward to your reply, Carol -------------------------------------------- ?summary(rpart.res) Call: rpart(formula = mydata$class ~ ., data

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

Dear R users, I’m trying to understand how correlated predictors impact the Relative Importance measure in Stochastic Boosting Trees (J. Friedman). As Friedman described “ …with single decision trees (referring to Brieman’s CART algorithm), the relative importance measure is augmented by a strategy involving surrogate splits intended to uncover the masking of influential variables by others

--- included message ---- Thus, my question is: *What common measures exists for ranking/measuring variable importance of participating variables in a CART model? And how can this be computed using R (for example, when using the rpart package)* ---end ---- Consider the following printout from rpart summary(rpart(time ~ age + ph.ecog + pat.karno, data=lung)) Node number 1: 228 observations,