similar to: automating sequence of multinomial regressions

Hola: Si aún hay alguien que no está de vacaciones, igual me pueden ayudar. Quiero ajustar unos modelos: REG_LOG <- glm (low ~ X, family = "binomial", data = DATOS) Ejemplo: library(MASS) data(birthwt, package="MASS") birthwt$low <- factor(birthwt$low) birthwt$race <- factor(birthwt$smoke) REG_LOG <- glm (low ~ smoke, family =

Hello, after calculating a multinomial logit regression on my data, I compared the output to an output retrieved with SPSS 18 (Mac). The coefficients appear to be the same, but the logLik (and therefore fit) values differ widely. Why? The regression in R: set.seed(1234) df <- data.frame( "y"=factor(sample(LETTERS[1:3], 143, repl=T, prob=c(4, 1, 10))), "a"=sample(1:5,

The birth weight example from ?stepAIC in package MASS runs well as indeed it should. However when I change stepAIC() calls to step() calls I get warning messages that I don't understand, although the output is similar. Warning messages: 1: In model.response(m, "numeric") : using type="numeric" with a factor response will be ignored (and three more the same.) Checked

Hola Carlos: Te adjunto un ejemplo de aplicación: las funciones (he borrado los path de las funciones y las ordenes "source()" que las carga ) y un ejemplo para ejecutarlas para las opciones que tengo implementadas con la tabla de datos birthwt del paquete"MASS": - Descriptiva de todas las variables de una tabla. - Análisis univariado de todas las variables de una tabla

Hola Carlos: Gracias por responder! Ayer caí en esta página al buscar el problema con google, pero no conseguir entender y implementar lo que sugiere. Sin entender nada, lo que hice fue: ======================== > library(MASS) > library (sqldf) # Per SQL > data(Aids2, package="MASS") > SQL_PROVA = function (XDADES, XWHE) + { + XDADES_SQL = sqldf ("select * from

Hola: No consigo que la función sqldf () funcione dentro de una función. Alguien puede echarme una mano. En resumen, el problema es que cuando lo ejecuto fuera de una función no tengo ningún problema: ========================== > # install.packages("sqldf") > library(MASS) > library (sqldf) > data(Aids2, package="MASS") > options(digits=3) > table

I'm trying to figure out a good way to smooth binary data. The ideal approach appears to be the "sm.logit" function in library "sm", but I haven't had success with it. Below, is some code illustrating what I've come up with so far, but I'm hoping there is a better approach. I'm using R 1.2 (development) under Windows 98. -Bill library(MASS) data(birthwt)

Hi, Because I'm new to R and trying to move off of SPSS, I have another question. I downloaded the "Foreign" package which I understand reads in various datasets from programs such as SPSS and SAS. There isn't much documentation that I can find regarding the specifics of this in the online docs, but I assume that it is like read.table. So, here is what I wrote and here is

Dear All, I am looking at discriminating among several individuals based on a few variable sets (I think some variables do not make sense unless they are entered together, so I "force" them into the models together, hence datasets). I have done so with linear discriminant analysis (LDA) using "MASS::lda", with acceptable results. However, one of my collaborators

Happy New Year to all, I am using RW0631 and WIN98. 1. The command DATA only works for the base library. 2. The following code on page 312 of Venables and Ripley 1997 sitka.lme <- lme(size~treat*ordered(Time),random=~1,cluster=~tree,data=Sitka, serial.structure="ar1.continuous",serial.covariate=~Time) produced the following error message Error in lme(size ~ treat *

Thanks for your answers Stephen and Ben, I hope I am posting on the correct list now. I managed so far to run the multinomial model with random effect with the following command: MCMCglmm(fixed=cbind(Apsy,Mygl,Crle,Crru,Miag,empty) ~ habitat:trait,random=~idh(trait):mesh,family="multinomial12", data=dataA,rcov=~trait:units) (where multiple responses are different species, Habitat

I have two questions: 1. If I want to do a binomial logit, how to handle the categorical response variable? Data for the response variables are not numerical, but text. 2. What if I want to do a multinomial logit, still with categorical response variable? The variable has 5 non-numerical response levels, I have to do it with a multinomial logit. Any input is highly appreciated! Thanks! Ed

Good morning, I'd like to estimate a simple multinomial logit model in R (not a McFadden conditional logit). For instance, I'd like to estimate the probability of someone having one of eight titles in a company with the independent variables being the company characteristics. A binary logit is well documented. What about the multinomial? Thanks, Walt Paczkowski

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

Sir, I want to fit a multinomial logistic regression in R.I think mlogit() is the function for doing this. mlogit () is in packege globaltest.But, I can not install this package. I use the following: install.packages("globaltest") Can you help me? Regards, Suman Dhara [[alternative HTML version deleted]]

I want to get the logLik to calculate McFadden.R2 ,ML.R2 and Cragg.Uhler.R2, but the value from multinom does not have logLik.So my quetion is : is logLik meaningful to multinomial logistic model from multinom?If it does, how can I get it? Thank you! ps: I konw VGAM has function to get the multinomial logistic model with logLik, but I prefer use the function from "official" R

Hi, how can I do multinomial logistic regression in R? I think glm() can only handle binary response variable, and polr() can only handle ordinal response variable. how to do logistic regression with multinomial response variable? Thanks __________________________________

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.

I have had plenty of succes generating one dimensional variables and plotting them, but what do i do for more (specifically 2) dimensional multinomial variables? I figure i have to create a vector consisting of two 1 dim normallly distributed variables, that way i can also control the correlation. But how do i do this :) ? Many thanks -- View this message in context:

Hi everyone? Does anybody know how can I estimate a Latent class multinomial (or conditional) logit using R? I have tried flexmix, poLCA, and they do not seem to support this model. thanks in advance adan -- View this message in context: http://r.789695.n4.nabble.com/Latent-class-multinomial-or-conditional-logit-using-R-tp4230083p4230083.html Sent from the R help mailing list archive at