similar to: polr (MASS)

Hi all, I need some help using read.ftable to read a contingency table. My columns are organized as follows: order--family--species--location--number of individuals I couldn't figure out how to change the data on my text file to be imported into R; and after you do that, is it possible to convert the table into a data frame? Any tips would be greatly appreciatted! Thanks a lot, Naiara.

Dear all, I need to do a Manova but I have an unbalanced design. I have morphological measurements similar to the iris dataset, but I don't have the same number of measurements for all species. Does anyone know a procedure to do Manova with this kind of input in R? Thank you very much, Naiara. -------------------------------------------- Naiara S. Pinto Ecology, Evolution and Behavior 1

Hello all, I am importing data from a txt file and try to get a histogram, I get the message: "Error in hist: 'x' must be numeric". When I use mode R returns "List". However when I use srt I get: `data.frame': 456 obs. of 1 variable: $ V1: num 0.6344 0.4516 0.0968 0.7634 0.7957 ... My file consists of one column only (no headers) and I can't figure out why

Hi folks, I'd like to use scatter3d (which is in R commander) to plot more than one dataset in the same graph, each dataset with a different color. The kind of stuff you would do with "holdon" in Matlab. I read a recent message that was posted to this list with a similar problem, but I couldn't understand the reply. Could someone give me one example? How do you plot subgroups

Dear all, I would like to use a tree regression method to analyze my dataset. I am interested in the fact that random forests creates in-bag and out-of-bag datasets, but I also need an estimate of support for each split. That seems hard to do in random forests since each tree is grown using a subset of the predictor variables. I was thinking of setting mtry = number of predictor variables,

For the following model, library(vcd) arth.polr <- polr(Improved ~ Sex + Treatment + Age, data=Arthritis) summary(arth.polr) where Improved is an ordered, 3-level response I'm looking for a *simple* way to test the validity of the proportional odds assumption, typically done via a score test for equal slopes/effects over the predictors. I do find a po.test= option in the repolr package

Greetings: I'm running R-1.9.1 on Fedora Core 2 Linux. I tested a proportional odds logistic regression with MASS's polr and Design's lrm. Parameter estimates between the 2 are consistent, but the standard errors are quite different, and the conclusions from the t and Wald tests are dramatically different. I cranked the "abstol" argument up quite a bit in the polr

In polr.R the (several) functions gmin and fmin contain the code > theta <- beta[pc + 1L:q] > gamm <- c(-100, cumsum(c(theta[1L], exp(theta[-1L]))), 100) That's bad. There's no reason to suppose beta[pc+1L] is larger than -100 or that the cumulative sum is smaller than 100. For practical datasets those assumptions are frequently violated, causing the

Hello, I am trying to run an ordinal logistic regression (polr) using the package 'MASS'. I have successfully run other regression classes (glm, multinom) without much problem, but with the 'polr' class I get the following error: " Error in svd(X) : infinite or missing values in 'x' " which appears when I run the "summary" command. The data file is

I would like to do a SS type III analysis on a proportional odds logistic regression model. I use drop1(), but dropterm() shows the same behaviour. It works as expected for regular main effects models, however when the model includes an interaction effect it seems to have problems with matching the parameters to the predictor terms. An example: library("MASS"); options(contrasts =

Hi all, I have a dataset where each point is assigned to a class A, B, C, or D. Each point is also assigned to a study site. Each study site is coded with a number ranging between 1-100. This information is stored in the vector studySites. I want to run randomForests using stratified sampling, so I chose the option strata = factor(studySites) But I am not sure how to control the number of

First, my apologies for not giving all the details in my first post. Second, the problem was somewhat more complicated than simply using help.search('polr') or library(MASS). When I tried these, I got notices that polr could not be found anywhere, and that no package called MASS existed. When I went to the CRAN site, there was no package called MASS. I am not sure how I installed R

Dear all, It appears that MASS::polr() and Design::lrm() return the same point estimates but different st.errs when fitting proportional odds models, grade<-c(4,4,2,4,3,2,3,1,3,3,2,2,3,3,2,4,2,4,5,2,1,4,1,2,5,3,4,2,2,1) score<-c(525,533,545,582,581,576,572,609,559,543,576,525,574,582,574,471,595, 557,557,584,599,517,649,584,463,591,488,563,553,549) library(MASS) library(Design)

Dear all, I am doing a regression in ramdomForest, using the option "sampsize" reduce the number of records used to produce the randomForest object. The manual says "For classification, if sampsize is a vector of the length the number of strata, then sampling is stratified by strata, and the elements of sampsize indicate the numbers to be drawn from the strata". I need my

Dear all, I get an error message when I use polr() in MASS. These are my data: skugg grupp frekv 4 1 gr3 0 5 2 gr3 3 6 3 gr3 6 10 1 gr5 1 11 2 gr5 12 12 3 gr5 1 > > summary(polr(skugg ~ grupp, weights=frekv, data= skugg.cpy1.dat)) Error in optim(start, fmin, gmin, method = "BFGS", hessian = Hess, ...) :

Dear all, I am trying to install rgdal from source on a Mac OS 10.4.11. I installed GDAL and PROJ as frameworks so the installation does not work unless I explicitly state where the GDAL and PROJ libraries are. I tried: R CMD INSTALL rgdal_0.5-25 --configure-args=--with-proj-include=/Library/Frameworks/PROJ.framework/unix/include --with-proj-lib=/Library/Frameworks/PROJ.framework/unix/lib but I

Hi, I am trying to test the proportional-odds model using the "polr" function in the MASS library with the dataset of "housing" contained in the MASS book ("Sat" (factor: low, medium, high) is the dependent variable, "Infl" (low, medium, high), "Type" (tower, apartment, atrium, terrace) and "Cont" (low, high) are the predictor variables

I'm running polr() and getting warning messages from glm.fit(). It seems reasonable to use glm.control() to turn on the trace and follow what glm.fit() does when called by polr(); or is it? glm.control(maxit=10, trace=TRUE) polr(act~., data=mm) The glm.control() sets the trace TRUE, but there's no change in the output from polr(). Many thanks in advance for any help/pointers.

Dear all, I have used polr in MASS but I am uncertain about the summary(polr.object) interpretation and would be happy for help on that. This is my summary: > summary(shade.polr) Re-fitting to get Hessian Call: polr(formula = as.ordered(shade) ~ as.factor(objekt), data = sof, weights = as.numeric(frek)) Coefficients: Value Std. Error t value 2.1699520 0.3681840 5.8936612

Dear community, I am currently trying to fit an ordinal logistic regression model with the polr function. I often get the same error message : "attempt to find suitable starting values failed", for example with : require(MASS) data(iris) polr(Species~Sepal.Length+Sepal.Width+Petal.Length+Petal.Width,iris) (I know the response variable Species should be nominal but I do as levels