similar to: Row mean scores differ association

Suppose that we have o 2-D contingency table where the row variable is nominal and the column one is ordinal. In SAS it is possible to compute the statistic named as row mean scores differ. How can we programmed it in R? (See also Aggresti (2002), Categorical Data Analysis, p. 302) With regards --------------------------------- [[alternative HTML version deleted]]

Dear All, We are about to purchase the second edition of Agresti's "Categorical Data Analysis" (my old copy of the first ed. of that wonderful book is falling apart). I would appreciate suggestions about other comparable books which, if possible, have examples using R/S code (instead of SAS). Thanks, Ram?n -- Ram?n D?az-Uriarte Bioinformatics Unit Centro Nacional de

Does anybody know if there is an implementation of Goodman-Kruskal lambda measures of association in R? Also, how we can analyze ordered contingency tables and compute the relative measures of associations in R? Thank in advance --------------------------------- [[alternative HTML version deleted]]

Hi, I asked this question before, which was hidden in a bunch of questions. I repharse it here and hope I can get some help this time: I have 2 contingency tables which have the same group variable Y. I want to compare the strength of association between X1/Y and X2/Y. I am not sure if comparing p-values IS the way even though the probability of seeing such "weird" observation under H0

Hi, Can one tell me which procedure will fit an ordinal logistic regression model for longitudinal data set. To be precise, I have both dichotomous and polytomous items. Also, I would like to specify different covariance structures (unstructured, ar1 etc) for trial runs. Thanks -- View this message in context:

If I do not make a mistake,the partial association model is an extension of log-linear model.I read a papers which gives an example of it.(Sloane and Morgan,1996,An Introduction to Categorical Data Analysis,Annual Review of Sociology.22:351-375) Can R fit such partial association model? ps:Another somewhat off-topic question.What's the motivations to use log-linear model?Or why use

Dear Sirs, Could you please be so kind as to send us some information on residuals in multinomial logistic models? Is it possible to use R software? We thank you in advance. Sincerely yours Luciana Alves,MSc Beatriz Leimann, MD -- Luciana Correia Alves Doutoranda em Sa??de P??blica ENSP - Fiocruz

I'm trying to find a clever way to re-map data from a database query into a data.frame. Querying a database often returns a table (data.frame) like this: GeneID MethodID Value 6 1 123 6 2 456 6 3 987 7 1 234 7 3 432 8 2 190 8 3 34 8 1 864 Note that GeneID=7 doesn't have a value for MethodID=2. Note that GeneID=8 doesn't have the

Hi Peter and others, If it helps, I wrote a small function glm.scoretest() for the statmod package on CRAN to compute score tests from glm fits. The score test for adding a covariate, or any set of covariates, can be extracted very neatly from the standard glm output, although you probably already know that. Regards Gordon --------------------------------------------- Professor Gordon K

Hi list, I would really like to see support for .cda as input files. The cda format is the one used on regular audio CDs. Support for this format would make it even easier to encode to FLAC from CDs -- Daniel Aleksandersen

Hello All: I am looking for you help. I am trying to replicate the results of an example found in Alan Agresti's "Categorical Data Analysis" on pages 267-269. The example is one of a 2 x 2 cross-classification table of ordinal counts: job satisfaction and income. I am able to get Agresti's results for the independence model (G^2 = 12.03 with df = 9) assuming as he does that

I am trying to call a funtion within another function and I clearly am misunderstanding what I should do. Below is a simple example. I know lstfun works on its own but I cannot seem to figure out how to get it to work within ukn. Basically I need to create the variable "nts". I have probably missed something simple in the Intro or FAQ. Any help would be much appreciated. EXAMPLE

On 2007-09-13, Brian wrote: > On Sep 13, 2007, at 12:08, Daniel Aleksandersen wrote: >> I would really like to see support for .cda as input files. The cda >> format >> is the one used on regular audio CDs. >> >> Support for this format would make it even easier to encode to FLAC >> from CDs > > You are mistaken, Daniel. Regular audio CDs do not use

Dear list members, I want to perform in R the analysis "simultaneous confidence interval for multiple proportions", as illustrated in the article of Agresti et al. (2008) "Simultaneous confidence intervals for comparing binomial parameter", Biometrics 64, 1270-1275. If I am not wrong the R function implementing the Agresti et al. method is prop.test(). I ask an help because I

Dear all, I'm testing the effect of species and sex in my sample by using the principal component scores of a PCA analysis. I have 30 PCs and I tried to see if there is any significant difference from males to females, given that there is a significant effect of phylogeny (factor with several species). I didi it like this: Y<-PCA$pc.scores[,1:30] fit <- manova(Y ~ sp*sex)

Hi, Is it possible to add labels to variables in R (so as to have a better description of what the variables represent)? Thanks, Neil

I have been using gnls with the weights argument (and varConstPower) to specify a variance structure for curve fits. In attempting to extract the parameters for the variance model I am seeing results I don't understand. When I simply display the model (or use "summary" on the model), I get what seem like reasonable values for both "power" and "const". When I

ConstantDataArray * cda = cast<ConstantDataArray>(v); throws this error: Assertion failed: (isa<X>(Val) && "cast<Ty>() argument of incompatible type!"), function cast, file /Users/rcatlin1/lldb/llvm/include/llvm/Support/Casting.h, line 208 Thanks for the help. Richard Catlin On Sat, Apr 20, 2013 at 3:37 PM, Sean Silva <silvas at purdue.edu> wrote:

Hi Sergio Doing those tests 30 times is going to give you a huge Type I error rate, even if there was a function that did that. There is a reason why TukeyHSD doesn't make it easy. In general, if there are useful comparisons among the species, you are better off setting up and testing contrasts than doing all-pairwise Tukey tests. Also, the PCA scores are ordered in terms of variance

I have installed the binary packages for Debian GNU/Linux release 2.3 (woody) in the U.S. mirror of the CRAN archive. They should propagate to the main CRAN archive within a day and to the other mirrors within two days. These packages have been compiled with gcc-3.0 and g77-3.0. I believe the testing distribution currently provides only a snapshot of gcc-3.0, not the latest released version, so