similar to: silly, extracting the value of "C" from the results of somers2

Dear list-members, I have made a logistic regression analysis of the spatial distribution of an ecological phenomenon (wildlife-caused crop damage). I divided the region into 5x5 km grids, and in each grid I have performed a number of questionnaires to asses the presence of crop damage in particular houses. As a result, my dependent variable is not a simple presence/ absence data but a

Dear all, I'm having a few problems trying to reshape a data frame. I tried with reshape{stats} and melt{reshape} but I was missing something. Any help is very welcome. Please find details below: ################################# # data in its original shape: indiv <- rep(c("A","B"),c(10,10)) level.1 <- rpois(20, lambda=3) covar.1 <- rlnorm(20, 3, 1) level.2

Hi, I'm plotting a multiple histogram using the function multhist {package plotrix}, something like: library(plotrix) mh <- list(rnorm(200, mean=200, sd=50), rnorm(200, mean=250, sd=50)) multhist(mh) In this graph y-axis represents the frequency of observations.... but I would like it to be scaled into relative frequencies, does anybody know how to do this with multhist or similar

Dear all, I'm trying to estimate the parameters of a lognormal distribution fitted from some data. The tricky thing is that my data represent the time at which I recorded certain events. However, in many cases I don't really know when the event happened. I' only know the time at which I recorded it as already happened. Therefore I want to fit the lognormal from the cumulative

Dear useRs, In a data.frame (df) I have several columns (x1, x2, x3....xn) containing data as a continuous numerical response: df var x1 x2 x3 1 143 147 137 2 93 93 117 3 164 39 101 4 123 118 97 5 63 125 97 6 129 83 124 7 123 93 136 8 123 80 79 9 89 107 150 10 78 95 121 I want to

Dear mailing group, This is my first time here. Glad to have this resource! I am currently trying to load an Excel file into R (limma package loaded) using the source(*name of directory*) command, but it cannot open the file. I renamed the file as .R and .RData, to no avail. The Excel data contains one gene name per row and about 100 data points per gene (columns). I am only used to

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 be a numeric

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,,]

Dear useRs, I am fitting a mixed model using the function lmer from the package lme4, but I have some problems when I try to test the effect of my factors of interest. First let me explain the structure of the model: I'm measuring animal movements. Explicitly, I am interested in displacement (straight-line distance from an initial point). Displacements are measured longitudinally, with one

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 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 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

Dear R Admins, I received an unsolicited e-mail from BlueInference as an R user. Does it mean that R that our e-mails (and names) is sharing it's user database with third parties without our consent? Or perhaps the BlueInference guys are using an e-mail address miner to get our contact details? [SNIP] Dear Gorden Jemwa, As a fellow R user, I am sure you agree with me that R is a

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

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

I have a large dataset where each Subject answered seven similar Items, which are binary yes/no questions. So I've always used Subject and Item random effects in my models, fit with lmer(), e.g.: model<-lmer(Response~Race+Gender+...+(1|Subject_ID)+(1| Item_ID),data,binomial) But I recently realized something. Most of the variables that I've tested as fixed effects are properties

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]]

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