similar to: ordinal data simulation

I'm trying to install the ordinal package (http://popgen.unimaas.nl/~plindsey/rlibs.html). I downloaded ordinal03.tgz and untarred it. rmutil was previously installed (and appears to work ok.) Then I installed ordinal: [root at localhost ~]# R CMD INSTALL /home/chippy/Download/ordinal * Installing to library '/usr/lib/R/library' * Installing *source* package 'ordinal' ... **

Hi, I am working on a regression tree in Rpart that uses a continuous response variable that is ordered. I read a previous response by Pfr. Ripley to a inquiry regarding the ability of rpart to handle ordinal responses in 2003. At that time rpart was unable to implement an algorithm to handle ordinal responses. Has there been any effort to rectify this in recent years? Thanks! Stacey On

Hello I've been asked to help evaluate a vegetation data set, specifically to examine it for community similarity. The initial problem I see is that the data is ordinal. At best this only captures a relative ranking of abundance and ordinal ranks are assigned after data collection. I've been trying to find a procedure in R that can handle ordinal based classification and so far have

I have been asked to analyse some questionnaire data- which is not data I'm that used to dealing with. I'm hoping that I can make use of the nabble expertise (again). The questionnaire has a section which contains a particular issue and then questions which are related to this issue (and potentially to each other): 1) importance of the issue (7 ordinal categories from -3 to +3) 2) impact

Hi I would like to analyse an ordinal categorical variable. I know how I can analyse a nominal categorical variable (with multinom or if there are only two levels with glm). Does somebody know which command I need in R to analyse an ordinal categorical variable? I want to describe the variable y with the variables x1,x2,x3 and x4. So my model looks like: y ~ x1+x2+x3+x4. y: ordinal factor

Dear colleagues, i am carrying out an ordinal regression model. I try it on SPSS but I "flirt" with R as well. I have a few questions. 1. What is the most reliable/tested/trusted package for ordinal regression in the R world? 2. Also, I have a statistical question. What is the danger of having to many 'empty cells' in ordinal regression? How many empty cells are too many? Do

After working on some more plugins I realized that the naming for flac's ordinal types were not going to cut it. There is too much chance for conflicts with other libraries/programs with names like 'bool' and 'uint32' so I went back and prefixed all flac ordinal types with 'FLAC__'. It makes the code a little harder to read until you get used to it but should make the

Hi there, during my work I have to use kernel smoothing methods for multivariate ordinal data. The R-package "KernSmooth" unfortunately includes only a version for continous scaled variables. Does anybody know whether there exists also a version for ordinal data? Thanks for help! --

Dear all, For a population of about 200 I have a continuous variable and an ordinal variable. The question I would like to ask is whether the continuously increases (or decreases) as the rank of the ordinal variable increases. I was thinking that a Spearmen's rank correlation or or a chi squared trend might be appropriate. I don't have any experience dealing with ordinal variables so I

Dear List, I have two questions about how to do predictions using lrm, specifically how to predict the ordinal response for each observation *individually*. I'm very new to cumulative odds models, so my apologies if my questions are too basic. I have a dataset with 4000 observations. Each observation consists of an ordinal outcome y (i.e., rating of a stimulus with four possible

Hello,dear all: I want to install the package "ordinal",but I don't see the package listed under package sources. I try to search it by "google",then I found this: http://euridice.tue.nl/~plindsey/rlibs.html but the connect does not work. Where can I found the package "ordinal" ? Is it still available? Thanks in advance. ^^

Dear R specialists, I have a multivariate statistics question that I want to submit to the R community (which conveys a very good statistical knowledge). I need to perform an optimal scaling based on a discrete variable and an ordinal variable. The discrete variable, Area, defines a geographical area. The ordinal variable, EducationLevel, describes the education level of individuals (the

There is a difference in the p- value from 0.000 and 0.012 when I am using SPSS. 0.000 when I am using the independent variable as scaled 0.012 if I am using the variable as ordinal. The independent variable is ordinal but it seems that R is using the variable as an scaled, because the P- Value is computed with 4.66e-06 so I am not sure which description I am misunderstanding: SPSS;:

When I run "lrm" from the Design package, I get a warning about contrasts when I include an ordinal variable: Warning message: Variable ordfac is an ordered factor. You should set options(contrasts=c("contr.treatment","contr.treatment")) or Design will not work properly. in: Design(eval(m, sys.parent())) I don't get this message if I use glm with

Hi! I'm looking for a solution to analyse data, which consists of dichotomous responses (yes/no) for 2 multinomial ordinal variables. I was trying glm() and got hierarhical models treating all variables as nominal, but I can't figure out how to tell glm() to use a model for ordinal data like this: log(Mij) = intercept + X + Y + Z + beta*(x-x')*(y-y') where beta is a

I'm trying to develop a linear model for crop productivity based on variables published as part of the SSURGO database released by the USDA. My default is to just run lm() with continuous predictor variables as numeric, and discrete predictor variables as factors, but some of the discrete variables are ordinal (e.g. drainage class, which ranges from excessively drained to excessively poorly

Hello, I am trying to build a generalised linear mixed model.? My dependent variable is ordinal.? I have a random factor (7 individuals), and a repeated measure where the dependent variable was measured three times for each of four attempts (so the repeats are nested).? I also have a few covariates.? I am a complete novice in R, being used to using SPSS.? SPSS lets me build an ordinal model

I would consider this is a question for a statistics forum such as stats.stackexchange.com, not R-help, which is about R programming. They do sometimes intersect, as here, but I think you need to *understand what you're doing* before you write the R code to do it. Obviously, IMO. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and

Hello All: I know the function loglin() and loglm() from librarary(MASS) performs analysis on nominal categorical data. Are there any libraries, functions or examples available for analysis of ordinal categorical data? I have in mind procedures that can replicate results in Alan Agresti (1984) "Analysis of Ordinal Categorical Data." Thanks, ANDREW

I have a spatial data set with ordinal response variable containing four levels. I would like to know if and how spatial autocorrelation can be taken into account when ordinal logistic regression is used (e.g. the function lrm from the Design package). Thanks for your help! Christof