similar to: Odds ratio in fisher.test()

I'm wondering how odds ratio is computed. I thought that it is (n11/n12)/(n21/n22), but it is not what fisher.test() computes. Could somebody let me know? > n11=3 > n12=1 > n21=1 > n22=3 > > n1_=n11+n12 > n2_=n21+n22 > > n_1=n11+n21 > n_2=n12+n22 > > x=rbind(c(n11,n12),c(n21,n22)) > > threshold=dhyper(n11,n1_,n2_,n_1) >

Hopefully a quick question: is there a package/routine to perform Box's M (like proc discrim in SAS) or some other test for whether two multivariate samples (presumed multivariate normal) have the same v-c matrix? I've looked, but can't find it. If not, I can certainly code it up myself (and perhaps submit it for inclusion in the mvtnormtest package), but I wanted to check if it

Hello, I am using WinXP, R version 2.3.1, and SAS for PC version 8.1. I have mostly used SAS over the last 4 years and would like to compare the output of PROC DISCRIM to that of lda( ) with respect to a very specific aspect. My data have k=3 populations and there are 3 variates in the feature space. When using using the code PROC DISCRIM DATA = FOO OUT = FOO_OUT OUTSTAT = FOOSTAT

Peter & Michael, I just came across the following on another mailing list and realized that my use (and the authors of the article use of the term 'odds ratio' ) is probably incorrect. I believe my interest is in the 'odds' of schizophrenia among the population of homicide, rather than a comparison of odds . "Yours seems a good idea, Kevin, if you are only interested

Hi, I am trying to run a simple logistic regression using lrm() to calculate a odds ratio. I found a confusing output when I use summary() on the fit object which gave some OR that is totally different from simply taking exp(coefficient), see below: > dat<-read.table("dat.txt",sep='\t',header=T,row.names=NULL) > d<-datadist(dat) > options(datadist='d')

Pass to --commands-from-file the name of a file containing customization commands in each line, as if they were specified as command line arguments. This eases the reuse of commands among different builder/customize/sysprep invocations. --- builder/cmdline.ml | 3 +- customize/customize_run.ml | 5 +++ generator/customize.ml | 98 ++++++++++++++++++++++++++++++++++++++++++++-- 3

I am trying to write the following code in R. The code works in S+ and i am trying to do the program in R. x=discrim(admit~gpa+gmat,prior=c("uniform"),data=data.mm) i wrote the following in R: x=lda(admit~gpa+gmat,data=data.mm) i could not figure out how to write prior=c("uniform") in R. I would get an error every time. I think that it has something to do with

Dear list, I made a logistic regression model (MyModel) using lrm and penalization by pentrace for data of 104 patients, which consists of 5 explanatory variables and one binary outcome (poor/good). Then, I found bootcov and robcov function in rms package for calculation of confidence range of coefficients and odds ratio by bootstrap covariance matrix and Huber-White sandwich method,

Dear list, I'm currently trying to use the rms package to get predicted ordinal responses from a conditional ratio model. As you will see below, my model seems to fit well to the data, however, I'm having trouble getting predicted mean (or fitted) ordinal response values using the predict function. I have a feeling I'm missing something simple, however I haven't been able to

Hello. I'm looking for a method to simulate n different 2x2 tables having all the same odds ratio. For example. I need 100 tables with odds ratio 1 100 tables with odds ratio 2 100 tables with odds ratio 3 and so on. All tables should have the same marginal frequencies. Thank you -- View this message in context:

mantelhaen.test() gives the exact conditional p-value (for independence) and confidence intervals (CIs)for the common odds ratio for a stratified 2x2 table. The epitools package by Tomas Aragon (available via CRAN) contains functions which use fisher.test() to calculate mid-p exact p-values and CIs for the CMLE odds ratio for a single 2x2 table. The mid-p p-value for independence for a stratified

Hi list, I am trying to calculate the sensitivity, specificity, and odds ratio(and confidence interval). Say, my data looks like this 42.53, 37.56, 40.51, 32.67, 38.19, 81.74, 41.55, 68.94, 59, 63, 54.13, 48.85, 50.46, 51.78 Is there any packages in R that does this? Espeically the odds ratio confidence interval. Mike [[alternative HTML version deleted]]

Hi friends, I have a doubt reg the application of odds ratio. When evaluating a diagnostic test, what odds ratio I should apply? When I use.. *>oddsratio (X)** * the OR I get is not ad/bc. Thank you. Regards, Dr Manoj Aravind, PG Resident, Dept of Community Medicine, Osmania Medical College, Hyderabad, India. [[alternative HTML version deleted]]

Please don't post in HTML. Your post is almost unreadable Also,lease have a look at http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example and/or http://adv-r.had.co.nz/Reproducibility.html for some suggestions about what you should include in your question. Welcome to R. John Kane Kingston ON Canada > -----Original Message----- > From: rosita21 at

Hello R people I now know how to run my discriminant analysis with the lda function in MASS: lda.alain=lda(Groupes ~ Ht.D0 + Lc.Dc + Ram + IDF, gr, CV = FALSE) and it works fine. But I am missing a test and cannot find any help on how to get it, if it exist. The "S" equivalent: discrim(structure(.Data = Groupes ~ Ht.D0 + Lc.Dc + Ram + IDF, class = "formula"), data = gr,

Add a new Getopt module to mllib, to parse command line arguments with handlers close to the ones used with Arg, but using getopt(3) (actually getopt_long_only) to do the real parsing. This allow us to provide options for OCaml tools with a syntax similar to the C tools, and use the additional features getopt offers and Arg does not. Do a single-step conversion of Common_utils and all the OCaml

Hi, I am new to R. Anyone can explain the following from R-help or anyone can direct me how to calculate odds ratio from logistic model in R. Thank you very much. Guoya Stefano <stecalza at tiscalinet.it <https://stat.ethz.ch/mailman/listinfo/r-help> > writes: >Hi all. > >A simple question. >Is there a function to compute the Odds Ratio and its confidence intervall,

Dear all, How can i obtain odds ratio in logistic regression when the model contains interaction terms in R? how can i obtain OR for a special case? Thanks in advance for any help. Amin

Dear all, is there a automatic method to obtain Odds Ratio estimates and their confidence intervals from a GLM Logistic model? Thanks Cristian ============================================= Cristian Pattaro ============================================= Unit of Epidemiology & Medical Statistics Department of Medicines and Public Health University of Verona cristian@biometria.univr.it

Hi all. A simple question. Is there a function to compute the Odds Ratio and its confidence intervall, from a logistic model (glm(.......,family=binomial....). I've written my own, but certainly someone did a better job. Thank you in advance, Stefano *********************************************** Stefano Calza Istituto di Statistica Medica e Biometria Universit? degli Studi di Milano Via