similar to: nominal data

Hello, I'm trying to calculate a chi-squared test to see if my data are different from the theoretical distribution or not: chisq.test(rbind(c(79, 52, 69, 71, 82, 87, 95, 74, 55, 78, 49, 60),c(80,80,80, 80, 80, 80, 80, 80, 80, 80, 80, 80))) Pearson's Chi-squared test data: rbind(c(79, 52, 69, 71, 82, 87, 95, 74, 55, 78, 49, 60), c(80, 80, 80, 80, 80, 80, 80, 80, 80, 80, 80,

Hi, I try to calculate Kendall's W coefficient and I have a bizarre error. little.app.mat<-matrix(c(1,3,4,2,6,5,2,4,3,1,5,6,3,2,5,1,5,4),nrow=3,byrow=TRUE) print(kendall.w(little.app.mat[-1,])) >>> Kendall's W for ordinal data >>> W = 0.7753623Error in if (is.na(x$p.table)) { : argument is of length zero

Greetings. I've been experimenting with some algorithms for document classification (specifically, a Naive Bayes classifier and a kNN classifier) and I would now like to calculate some inter-rater reliability scores. I have the data in a PostgreSQL database, such that for each document, each measure (there are 9) has three variables: ap_(measure), nb_(measure), and knn_(measure). ap is me

Dear all, I am having a hard time to figure out a suitable test for the match between two nominal classifications of the same set of data. I have used hierarchical clustering with multiple methods (ward, k-means,...) to classify my dat into a set number of classesa, and I would like to compare the resulting automated classification with the actual - objective benchmark one. So in principle I

Hello, I?m looking for a way to measure the goodness of fit of my model with Cohen?s Kappa (scaling between 0 and 1). The kappa function does not give the results I?m looking for. Heres the code: z<-glm(x~y,binomial) kappa(z, exact = T) Does anyone know more? many thanks Christian -- _______________________________________________ Search for businesses by name, location, or phone number.

Hi All: Could anyone point me to a package that can calculate stratified kappa? My design is like this, 4 raters, 30 types of diagnosis scores, 20 patients. Each rater will rate each patient for each type of diagnosis score. The rater's value is nominal. I know I can measure the agreement between raters for each type of diagnosis score, e.g., calculate out 30 kappa values. My problem is I

Hi, I am having problems getting cohen's kappa to work. I have been using the function: ><-ckappa(x,y) from the psy package. I am trying to test for inter-observer reliability, I have 2 observers and 26 categories, however, the two observers might not necessarily have the same range of categories (I have unequal score ranges). However, I thought R could cope with this. Each time I

Is there a function that calculates the inter-rater agreement index (kappa) in R? Thanks ../Murli [[alternative HTML version deleted]]

Hello there, I would like to test the agreement amongst 6 raters for nominal data on a scale from 1-4, and conduct a latent class analysis in R. How should the data be formatted and what code should I use? Thank you very much Lisa Wang Princess Margaret Hospital Biostatistics tel:416 946 4501

Dear all I apologize for cross-posting, but first it is accepted custom to thank the repliers and give a summary, and second I have still the feeling that this problem might be a general statistical problem and not necessarily related to microarrays only, but I might be wrong. First, I want to thank Robert Gentleman, Mark Kimpel and Mark Reiners for their kind replies. Robert Gentleman kindly

Hi, R people, I wonder if there is a statistics than can measure the correlation for more than two random variables, instead of computing the correlation coefficient matrix. If so, what R package should I use? Right now I can only think of the mean of all pair-wise correlation coefficients, e.g., (corr(x,y) + corr(x,z) + corr(y,z)) / 3 for three random variables (x, y, z). Thanks a

Hi R Users, Sorry if its out of topic. I would like to ask you about twin peaks - normal distribution. How R can handle it, any example to explain it in R. Thanks, regards, Unung

Hi All, I am using fleiss kappa for inter rater agreement. Are there any know issues with Fleiss kappa calculation in R? Even when I supply mock data with total agreement among the raters I do not get a kappa value of 1. instead I am getting negative values. I am using the irr package version 0.70 Any help is much appreciated. Thanks and Regards M [[alternative HTML version deleted]]

Hi, im little bit confused about Cohen's Kappa and i should be look into the Kappa function code. Is the easy formula really wrong? kappa=agreement-chance/(1-chance) many thanks christian ############################################################################### true-negativ:7445 false-positive:3410 false-negativ:347 true-positiv:772 classification-aggrement:68,6%

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Sorry, it's simple question: example : > data.test label value 1 one 21.35746 2 two 22.07592 3 three 20.74098 > I would like the return : label value 3 three 20.74098 1 one 21.35746 2 two 22.07592 Anyone can help it? Thanks, regards Unung Istopo

Hello, I am trying to perform a two-factor ANOVA analysis using a blocking design with "Vol" as the response variable. My intent is to have "Rater" treated as the treatment variable and the "Pipe" treated as the blocking variable. I am reading and preparing my dataset using the following three lines of code: values <- read.table("filename",

Dear R-colleagues, I am quite a newbie to R fighting my stupidity to solve a probably quite simple problem of generating artificial data with defined features. I am conducting a study of inter-observer-agreement in child-bronchoscopy. One of the most important measures is Kappa according to Fleiss, which is very comfortable available in R through the irr-package. Unfortunately medical doctors

Folks, I'm trying to get Asterisk to load my voicemail configuration from MySQL. I've followed the instructions at: http://www.voip-info.org/wiki-Asterisk+voicemail+database I restarted Asterisk, but no luck: the voicemail.conf does not get updated. I started with a sample voicemail.conf that I found on the Wiki. Or was it from Voicepulse? I can't remember. For initial testing, I

Hi All, Is there an easy way to reduce a data.frame to 1 'id' per row while keeping information from the other rows of that same variable, if applicable? e.g.: # data multi[1:15,] id r n wi wi.tau z k alliance a.rater eml treatment outcome o.rater german 1 100 0.2800000 44 41 21.72514 0.2876821 210 <NA> <NA> <NA> <NA>