similar to: glm - prediction of a factor with several levels

Hi! I'm trying to do some ploytomous logistic regression using multinom() in the nnet package, but am a bit confused about interpretation of the results Is it possible to get the following quantities: I: maximum likelihood estimates to test for fit of model and significance of each predictor (I would like to produce a table of the following type) Analysis of Variance: MLE (values are

Hi there, Does anyone know a method to calculate the number of different patterns in a given data frame. The variables are of polytomous type and not binary (for the latter i found a package called "countpattern" which unfortunately only functions for binary variables). V1 V2 V3 0 3 1 1 2 0 1 2 0 So, in this case, i would like to get "2" as output. Thanks

Hi all, After writing data in MMF(Memory Map File) using SEXP structure, can i reference in R? If input data is larger than 2GB, Can i reference MMF Data in R? my work environment : R version : 2.11.1 OS : WinXP Pro sp3 Thanks and best regards. Park, Young-Ju from Korea. ---------[ ???????? ???????? ???????? ]---------- ???????? : R-help Digest, Vol 89,

lrm does some binning to make the calculations faster. The exact calculation is obtained by running f <- lrm(...) rcorr.cens(predict(f), DA), which results in: C Index Dxy S.D. n missing 0.96814404 0.93628809 0.03808336 32.00000000 0.00000000 uncensored Relevant Pairs Concordant Uncertain 32.00000000

Hello, Would someone have ever heard or developed any Item Response Models library for R ? Of course, a Rasch model can be estimated through glm() but it is not the case for more complex (polytomous) response models. Similarly I would be interested in any R implementation of nonlinear multivariate analyses a la GIFI (HOMALS, PRINCALS, OVERALS). Thanks a lot in advance, Yvonnick Noel, PhD.

Hi, I found that using different contrasts (e.g. contr.helmert vs. contr.treatment) will generate different fitted probabilities from multinomial logistic regression using multinom(); while the fitted probabilities from binary logistic regression seem to be the same. Why is that? and for multinomial logisitc regression, what contrast should be used? I guess it's helmert? here is an example

Hello list, Is there any mean to fit models for ordinal response other than multinomial polytomous ("multinom" from nnet ) and cumulative logit ("polr" from MASS)? I am particularly interested in continuation-ratio model and adjacent-category logit model. It is for the sake of epidemiology in wild-living populations! Many thanks, Emmanuelle Fromont

Hi all, I am trying to make a script that prints all possible models from a model I've created using nls(). It is a logisitc model which in total includes 13 variables. So its >8000 models I need to create, which I don't want to do manually. I've tried modify scripts made for linear models with no results. I've tried these scripts on a two variable model (c,a1 and a2 is what I

Dear all, As I am new to the R community - although eager to advance- I would like to pose a question to the community. I have an SPSS file which I have imported it in R (with the read.spss command) which conists of scale (continuous) variable "adiponectin" and the corresponding categorical value "death" (0=No, 1=Yes). In all there are 60 observations (among which

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

Dear R-users I am introducing my collegue to R and she is interested to use R to perform Polytomous Logistic Regression called also Multi-category logistic regression. Is there any program in R doing this? Thank you so much for any feedback. I take this opportunity to thank people who were kind to answer my query about how to include a postscript file generated from R, in a latex file and

Hi everyone: Polyclass is a polytomous logistic regression model using linear splines and their tensor products. It provides estimates for conditional class probabilities which can then be used to predict class labels. I know there is Polyclass package in S-plus. So I'm wondering if there is a corresponding package in R? I have been searching for it for quite a while, but still

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:

Using SUSE Linux, Windows 32 bit and Windows 64 bit R 3.0.2 , I am unable to use R CMD check successfully. Here is the Windows 64 bit report: Z:\R\source\effects>R CMD check pkg * using log directory 'Z:/R/source/effects/pkg.Rcheck' * using R version 3.0.2 (2013-09-25) * using platform: x86_64-w64-mingw32 (64-bit) * using session charset: ISO8859-1 * checking for file

Hi all, I'm working on a multinomial (or "polytomous") logistic regression using R and have made great progress using multinom() from the nnet library. My response variable has three categories, and there are two different possible predictors. I'd like to use the likelihoods of certain models (ie, saturated, fitteds, and null) to calculate Nagelkerke R-squared values for

Dear useRs, I very much like the effect display of the proportional odds model on page 29 (Figure 8) of the following paper by John Fox: http://socserv.mcmaster.ca/jfox/Papers/logit-effect-displays.pdf It really gives a very concise overview of the model. I would like to use it to illustrate the proportional odds mixed models we fit here for a project on Diabetes but I can't seem to reproduce

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

Hai, Can anyone help me with some literature (R related) about latent models? Thanx, Wilfred

I tried to use the effect() to get predicted marginals for multinomial logistic as I did for general logistic regression, but failed. Is there anyway to do that? Thx! -- View this message in context: http://www.nabble.com/How-to-get-predicted-marginal-%28aka-predicted-mean%29-after-multinomial-logistic--tp17200114p17200114.html Sent from the R help mailing list archive at Nabble.com.

Dear All; I have used fbmSim to simulate a fbm sequence, however, when I tried to estimate the Hurst effect, none of the nine procedures gave me an answer close enough to the real value, which is 0.5 (n=1000). So, would you please advice, 1. which is the best method to estimate the H among the 9 mehods, R/S, higuchi or Whittle? 2. how to choose the levels (default=50), minnpts, cutoff values or