similar to: Multi-response, multi-rater kappa?

I'm looking for a function in R that extends kappa to multiple raters when there is more than one response per subject. For example, say a group of doctors have to assign diseases to patients. Each patient will be assigned one to many diseases, and the number of doctors assigning diseases to any one patient will be two to many. Here's an extremely simple example of the type of data I

Hello, I have 50 raters and 180 cases which are rated as malignant, probably malignant, probably benign, and benign. I want to compare all the raters but I want a weighted kappa to penalize differences between malignant and benign more than differences between malignant and probably malignant. I only found the weighted option in the 2-rater functions (kappa2, wkappa, cohen.kappa). The

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

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 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]]

Hello Everyone I am calculating Fleiss Kappa, I have 28 raters, 5 Subjects and 5 ratings. The problem is that there are 2 missing values in the data. Would it better to replace those with "0" or should those be omitted? By omission I will be left wit only 3 subjects. and my second problem is that overall agreement comes to zero, whereas the data is not showing agreement to be close

Dear useRs, I have written an ecological model, based on the epidemiology SIR model. I've been trying to simulate it in R. However, I can't simulate it properly. Two guesses: my script isn't right; I'm not setting the parameters properly I have uploaded an image to the model here: http://img24.imageshack.us/img24/743/imagemutr.jpg The script I am using is as it follows:

Using the input below, can I do something more elegant (and more efficient) than the loop also listed below to pad strings to a width of 5? The true matrix is about 300K rows and 31 columns. ####################### #INPUT ####################### > temp DX1 DX2 DX3 1 13761 8125 49178 2 63371 v75 22237 3 51745 77703 93500 4 64081 32826 v72 5 78477 43828 87645 >

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.

Hello, I am writing a package with a collection of several models. In order to allow users to play interactively with the models (in contrast to hacking lengthy scripts), I want to put all what is needed to run a particular model into a single list object for each model. Then there will be a collection of functions to run the model or to modify parameters, time steps, integration method ...,

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 R-users, I've a question regardiing multiple linear regression. Is it possible to regress a function of the type y=b0+b1*x1+b2*x2 constraining the partial derivatives dy/dx1 and dy/dx2 to be greater than 0 ??? Thank you very much for any possible suggestion. Best regards Marco -- Marco Pagani - PhD Student Dipartimento di Scienze della Terra - Sezione Geofisica Universita' degli

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

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

Greetings, I am a bit confused by the results returned by the functions: cohen.kappa {concord} classAgreement {e1071} when using a two-way table. for example, if I have an matrix A, and a similar matrix B (same dimensions), then: matrix A and B can be found: http://casoilresource.lawr.ucdavis.edu/drupal/files/a_40.txt http://casoilresource.lawr.ucdavis.edu/drupal/files/b_40.txt A <-

Hello, When evaluating different learning methods for a categorization problem with the (really useful!) caret package, I'm getting confusing results from the Kappa computation. The data is about 20,000 rows and a few dozen columns, and the categories are quite asymmetrical, 4.1% in one category and 95.9% in the other. When I train a ctree model as: model <- train(dat.dts,

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%

Dear all, I have a question on Cohen's kappa: Assume I have two datasets, one has 500 objects, 10 methods and the other, 1000 different objects, 20 different methods. Could I compare between the two datasets to conclude the 10 methods are more "concordant" than the 20 ones by looking at some output, for example, cohen.kappa{concord} ? One more, could anyone explain in brief,

I have a simple R script which uses the psych package to calculate cohens kappa (weighted) from a csv file. The csv file has 2 columns of ordinal data - one ranked by an experienced observer and the other by a novice who is undergoing training. What I would like to do is measure kappa for subsets of this data (say 30-50 ratings) and check whether the observed agreement between novice and

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