similar to: caret's Kappa for categorical resampling

Like earth can be trained simultaneously for degree and nprune, is there a way to train ctree simultaneously for mincriterion and maxdepth? Also, I notice there are separate methods ctree and ctree2, and if both options are attempted to tune with one method, the summary averages the option it doesn't support. The full log is attached, and notice these lines below for

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, 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 R-user, Did anybody know how to calculate the kappa statistics of two vectors for the agreement? for example: a<-c(0,1,0,0,1,0) b<-c(0,1,1,0,0,1) I know the percent of agreement is 3/6, but how to get the kappa? [[alternative HTML version deleted]]

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]]

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,

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

Hallo all, I am looking for an R implementation of the four parameter kappa distribution (cdf, pdf, quantile, and ransom numbers), or at a minimum, the generalized logistic distribution. Any suggestions? Thank you very much, Serguei

Dear list, I calculated the kappa-accuracy for two differnt classifications. How can I test now the two kappa-value for significance? thanks, Mark ..................................................................... Markus Schwarz Wissenschaftliche Mitarbeiterin Eidg. Forschungsanstalt WSL Forschungsprogramm Musterland Z??rcherstrasse 111 CH-8903 Birmensdorf Telefon +41-44-739 22 87 Fax

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 <-

Hi, I was using a density estimation function as follows: > est <- KernSmooth::bkde(x3, bandwidth=10) When setting bandwidth less than 5, I got the error "longer object length, is not a multiple of shorter object length in: kappa * gcounts ". I wonder if there is anybody who can explain the error for me? Thanks! Hui

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've got two vectors with ratings from two coders, like this: x<-c("red", "yellow", "blue", "red") #coder number 1 y<-c("red", "blue", "blue", "red") #coder number 2 I want to find Cohen's Kappa using the wkappa function in the psych package. The only example in the docs is using a matrix, which

Hi Everyone, I am trying to use NLS to fit a dataset using a Kappa function, but I am having problems. Depending on the start values that I provide, I get either: Error in numericDeriv(form[[3L]], names(ind), env) : Missing value or an infinity produced when evaluating the model Or Error in nls(FldFatRate ~ funct3(MeanDepth_m, h, k, z, a), data = data1, : singular gradient I think these

Dear Guru's, Is there a package (R of course) with programs for diagnostics - roc, sens , spec, kappa etc? Best wishes Fredrik L

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

Hi there, I really tried hard to understand and find my own solution, but now I think I have to ask for your help. I already developed some script code for my problem but I doubt that it is correct. I have the following problem: Image you develop a logistic regression model with a binary outcome Y (0/1) with possible preditors (X1,X2,X3......). The development of the final model would be

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

Hi, Could anyone help me understand how the mincriterion threshold works in ctree and cforest of the party package? I've seen examples which state that to satisfy the p < 0.05 condition before splitting I should use mincriterion = 0.95 while the documentation suggests I should use mincriterion = qnorm(0.95) which would obviously feed the function a different value. Thanks in advance,

I tried to use ctree but am not sure about the meaning of the plot. My.data.ct<-ctree(Resp~., data=My.data) plot(My.data.ct) My data.frame contains 88 explanatory variables (continous,ordered/unordered multistate,count data) and one response with two groups. In the plot are only two variables shown (2 internal nodes) and 3 final nodes. Does it mean that only these two variables show a