similar to: Rcorr

Dear all ?Hmisc::rcorr states that it takes as main argument "a numeric matrix". But is it normal that it fails in such an ugly way on a data frame? (See below.) If the function didn't attempt any conversion to a matrix, I would have expected it to state that in the error message that it didn't accept 'data.frame' objects in its input. Also, I vaguely remember having used

Dear all, I am trying to compute a matrix of Pearson's `r' or Spearman's `rho' rank correlation coefficients using rcorr (Hmisc) the following way: > mx<-rcorr(x, type="spearman")[1] but then ... > is.matrix(mx) [1] FALSE Even if I use as.matrix the result is not better. What can I do? Thank you all Luca

Dear list, I get the following message when I use rcorr in library "Hmisc" ------------------------------------------------------ > rcorr(lskPox0t30, type=c("spearman")) Error in "[<-.data.frame"(*tmp*, is.na(x), value = 1e+30) : matrix subscripts not allowed in replacement ------------------------------------------------------ I do not understand

Hi, I have a dataset with four categories of data, the number of samples are not the same in each category. I want to find the Spearaman's Rho. Let me give an example. x=(14.22770439,26.49420624,46.7277932,19.02550707,23.37379361,16.97789862,19.77100085,23.11270162,13.72929843,33.54430621,14.4756979,70.15811106,11.22789833,NA,NA,NA)

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

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

Dear all, in package Hmisc `rcorr' computes a matrix of Spearman's `rho' rank correlation coefficients for all possible pairs of columns of a matrix. What if I want a matrix of rank correlation coefficients for pair of columns of two different matrices? I have the same question about distance metrics in package Vegan. The function 'vegdist' computes distance indexes for all

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

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

Hi all, Sorry about posting a really novice question. I was able to run rcorr after converting the list to a matrix by your help. I'm though wondering if there is any way to find out an exact p value as the output only gave me 0 for P value as shown below. I've added options(digits=10), which doesn't seem to help at all. Any help would be appreciated. P D Prime T

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

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

Hello, Also, the other file, NPA.csv, is not in tabular form. Can you please reformat it? Rui Barradas Citando ruipbarradas at sapo.pt: > Hello, > > Please keep this on the list, always cc r-help. > One of the files in your attachment is empty: > > y <- read.csv(file.choose("GT.csv")) > Error in read.table(file = file, header = header, sep = sep, quote =

Hello, Please keep this on the list, always cc r-help. One of the files in your attachment is empty: y <- read.csv(file.choose("GT.csv")) Error in read.table(file = file, header = header, sep = sep, quote = quote,? : ? no lines available in input Rui Barradas ? Citando Chaitanya Ganne <Chaitanya.Ganne at jefferson.edu>: > Thank you so much for your input. > > I am

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

Hi, Is there a limit on the number of observations for using cor.test. For example, > library(ctest) > cor.test(rnorm(3000), rnorm(3000), method="spearman") Error in if (q > (n^3 - n)/6) pspearman(q - 1, n, lower.tail = FALSE) else pspearman(q, : missing value where logical needed In addition: Warning message: NAs introduced by coercion I mainly want to calculate

Greetings. There seems to be a problem with the P-value computation in the cor.test with method="spearman". In R1.8.0 (MS Windows) I seem to be getting intermittently nonsense P-values, but the rho's are OK. I can get this reproducibly with the toy example attached where the first use is OK and subsequent calls with the same data give nonsense. (I have also seen the problem

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

Dear all Is there an easy way to display only one half (top-right or bottom-left) of a correlation matrix? > require(Hmisc) > rcorr(as.matrix(mtcars[ , 1:4])) mpg cyl disp hp mpg 1.00 -0.85 -0.85 -0.78 cyl -0.85 1.00 0.90 0.83 disp -0.85 0.90 1.00 0.79 hp -0.78 0.83 0.79 1.00 n= 32 P mpg cyl disp hp mpg 0 0 0 cyl 0 0 0 disp 0 0

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