search for: 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...

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,,] population[,26] 5 Pred_pres_e_indpdt...

Hi! I?m trying to calculate de C index (concordance probability) through the somers2 function (library Hmisc). I?m interesting on including the sampling effort as a weight factor for the evaluation of model predictions with real data. I?ve some questions about that: first of all I?m not really sure if I can include sampling effort as a weight factor. Since the weight factor should...

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)) somertime<-function(h,i,j)somers2(Pred_pres_h_indpdt[,i,,], population[,j]) results...

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) name2<-sprintf("population[,%s]",z) rank<-functi...

...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 "documentation filenames" being put out. When the list of filenames came to "somers2", the computer hung up for sometime and then started rebooting. I went back to read the manuals (installation guides), and I tried to install Hmisc again and made two attempts to install Hmisc. On both the occassions the laptop started rebooting when the list of "documentation filenames...

...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 by Frank Harrell mentioning about "the somers2 or rcorr.cens functions in the Hmisc library." ) However, I tried but still could not get through it. Also I found someone mentioned about do it manually. Could someone give me a more detailed information on how I could get these two summary statistics after performed the the logistic regress...

...ow to transform my data into CoCo-format in order to access these functions, regardless of whether the CoCo versions are actually intended for calculating the actual statistic or for some other package internal purposes, as may sometimes be the case. Furthermore, it appears to me that the 'somers2' function in the Hmisc package applies Somers' D only to 2x2 and not larger tables. Am I mistaken, or does there exist somewhere else an implementation of the Somers' D statistic for the more general RxC tables? This was queried in 1999, but no response seemed then to be forthcoming...

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

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 --------------------------------- [[alternative HTML version deleted]]

Hi there, Sorry for the double email. Does R have the packages for the following clustering methods? And if it does, what the commands for them? 1. SOM (Self-organization map) 2. Graph partitioning: 3. Neural network 4. Probability Binning Thank you very much! Linda [[alternative HTML version deleted]]

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 [[alternative HTML version deleted]]

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

...ect random effect, and the fixed effect of Race was significant for the first time. With the Subject effect included, Race is not significant. This also happens if Race is treated as random, though the effect is smaller then. The following table shows the various pairs of model fits, from somers2(), and the p-values given by anova(). Somers' Dxy p from anova() random Subject term no Subject term Somers' Dxy no Race term 0.8487 0.4096 vs. 0.30 0.00064 fixed Race term 0.8483 0.4332 no Race term 0.8487 0.4096 vs. 0.96 0.0047...

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

dear:teacher i have a problem which about the polr()(package "MASS"), if the response must have 3 or more levels? and how to fit the polr() to 2 levels? thank you. turly yours [[alternative HTML version deleted]]

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 all, Some functions like 'ROC(Epi)' can be used to perform ROC analyssi, but it needs us to specify the fitting model in the argument. Now i have got the predicted p-values (0,1) for the 0/1 response variable using some other approach, see the following example dataset: id mark predict.pvalue 1 1 0.927 2 0 0.928 3 1 0.928 ..................

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),

Question on graphs: The default case for drawing a graph in R, is where a little space is left on the x and y axis before the first tick i.e. even if I say xlim=c(0,1) -- there will be some space between the edge of the x-axis and where 0 is placed. If I want 0 on the edge, how do I do it in R? Area under the curve: I have a 45 degree line and a curve above or below it. Is there a way in R