similar to: Test of Parallel Regression Assumption in R

Dear R listers, I am learning the MLE utility optim() in R to program ordered logit models just as an exercise. See below I have three independent variables, x1, x2, and x3. Y is coded as ordinal from 1 to 4. Y is not yet a factor variable here. The ordered logit model satisfies the parallel regression assumption. The following codes can run through, but results were totally different from what I

I want to test whether the proportional odds assumption for an ordered regression is met. The UCLA website points out that there is no mathematical way to test the proportional odds assumption (http://www.ats.ucla.edu/stat//R/dae/ologit.htm), and use graphical inspection ("We were unable to locate a facility in R to perform any of the tests commonly used to test the parallel slopes

Dear All, I have a problem in understanding how the interactions of 2 ways ANOVA work, because I get conflicting results from a t-test and an anova. For most of you my problem is very simple I am sure. I need an help with an example, looking at one table I am analyzing. The table is in attachment and can be imported in R by means of this command: scrd<-

Hi all, I am trying to use nonlinear regression (nls) to analyze some seed germination data, but am having problems with error codes. The data that I have closely matches the germination dataset included in the drc package. Here is the head of the data temp species start end germinated TotSeeds TotGerminated Prop 1 10 wheat 0 1 0 20 0 0.0 2 10 wheat

Hello :) I'm just starting out with R and would appreciate your help with a couple of problems I am running into. I have used Sys.glob to get a list of all filenames having a particular file extension (in my case, *.txt) I would now like to use this list in the following manner: I would like to use each filename from the list and open that file into a tab separated matrix and proceed. How can

Hi All, I am working on some ordinal logistic regresssions using LRM in the Design package. My response variable has three categories (1,2,3) and after using the creating my model and using a call to predict some values and I wanted to use a simple .5 cut-off to classify my probabilities into the categories. I had two questions: a) first, I am having trouble directly accessing the

Hello, I want to use lme to fit two (or more) models, and then compare the fits on each individual. I know how to write my own code to do this (for each individual, plot the raw data, followed by lines() to plot each fitted curve) but I would like to use plot(augPred(... as it produces a nice trellis plot. I thought I could do this with par(new=T) but it does not seem to work.

Hi, I am trying to fit a model with an ordered response variable (3 levels) and 13 predictor variables. The sample has complex survey design and I've used 'svydesign' command from the survey package to specify the sampling design. After reading the manual of 'svyglm' command, I've found that you can fit a logistic regression (binary response variable) by specifying the

Hi everyone, If I compute a "Ordered Logistic or Probit Regression" with the polr function from MASS package. the summary give me : coefficients, Standard error and Tvalue.. but not directly the p.value. I can compute "manualy" the Pvalue, but Is there a way to directly obtain the pa.value, and I wonder why the p.valeu is not directly calculated, is there a reason? exemple

Hi, I'm new to R, and I'm STATA user before, could you help me where I can get document about comparison command between STATA and R. Thank you very much, Best regards, -iip-

Hi, I am new in R and I have problem with reading this data file 0 TITLE Title 0 XLEGEND Legend -1 LABEL x 1 1 12 1 2 30 1 3 34 I want to read only lines starting with 1 (it indicates 1st plotting line) and create data set from second and third value on this row. Thank for advice Jakub Zlamal -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list

Hello, I'm estimating an ordered logit model on a probability weighted survey sample. polr permits case weights with the "weights" option, but I cannot figure out from existing documentation what it actually does with these weights. I'm concerned about this because I get somewhat different results using Stata's ologit command with the pweights option and very

Hi, ?? Are there any packages which prints out p-values for OLR's (like `ologit' from Stata)? I want to run a bunch of OLRs and print the p-value for the first coefficient from each of them. ? I checked polr() under MASS and it doesn't. ?There's a lrm() function under Design which does print out p-values but I couldn't extract p-values from the output. ? Thanks, ? Debs

Hello, I am trying to impute data with the mi() function (mi package) and keep receiving an error message. When imputing the variable, "sex," the mi() function accesses the mi.categorical() function, which then accesses the nnet() function. I then receive the following error message (preceded by my code below): > imputed.england=mi(england.pre.imputed, n.iter=6, add.noise=FALSE)

Hi Keep your messages in the list, you increase your chance to get some answer. I changed your data to groupedData object (see below), but I did not find any problem in it. plot(wlg) gives reasonable picture and I am not such expert to see any problem with data. Seems to me, that something has to be wrong with nlsList function. > wheat.list <- nlsList(Prop ~ SSlogis(end,Asym, xmid,

We had been using R1.2.3 "print tip lowess function" as described by Terry Speed's group to normalize microarray data and up until this week the commands we were using were working fine. First, we load our data using arrayname<-read.table("filename", header=T) and then check that the table is OK. We format the data list using setup1<-init.data() and usually get a

This bug is not quite fixed - the example from my original report now = works using R-2.2.1, but plot(Uniform, 6) does not. The bug is due to if (show[6]) { ymx <- max(cook, na.rm =3D TRUE) * 1.025 g <- hatval/(1 - hatval) # Potential division by zero here # plot(g, cook, xlim =3D c(0, max(g)), ylim =3D c(0, ymx),=20 main =3D main, xlab =3D

Thanks for reporting the bug below. You''re absolutely right. Renamed Range#to_s implementation to #mocha_inspect and checked first and last respond_to?(:to_f) as you suggested. Sorry for the delay - I wasn''t monitoring the rubyforge trackers. I am now! Should be fixed in revision 99 of trunk. -- James. http://blog.floehopper.org ---------- Forwarded message ---------- From:

To the list: What R commands will perform the score test on an ordered multinomial logit model to evaluate the proportional odds assumption? Many thanks. Mtichell Wachtel [[alternative HTML version deleted]]

I would like to test the parallel regression assumption for an ordered logistic regression model using either a score/LM test, or preferably, a Wald/Brant test. I have been unable to find an R function (either in the base or in a package available on cran) that performs either of these tests. Does one exist that I am overlooking or is there code available elsewhere to do this? As background, I