similar to: Multinomial Logit with multiple groups

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

Hi, I am trying to obtain p-values for coefficient estimates in a multinomial logit model. Although I am able to test for significance using other methods (e.g., Wald statistics), I can't seem to get R to give me simple p-values. I am sure there is a very simple solution to this, but the R archives seem to have nothing on this issue. I would appreciate any help. Thanks in advance! Best,

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

I am attempted to examine the temporal independence of my data set and think I need an unordered multinomial logistic regression (or logit model) with repeated measures to do so. The data in question is location of chickens. Chickens could be in any one of 5 locations when a snapshot sample was taken. The locations of chickens (bird) in 8 pens (pen) were scored twice a day (AMPM) for 20 days

Dear all, I am having a hard time attempting to do a multinomial logit modeling in R. I am trying to analyze a dataset whereby there are 3 scenarios with 4 difference choice parameters. In particular ? I am having a hard time arranging this into a .csv format. What sorts of headings should I put in the column headers to reflect the variables and parameters for the total number of choice made

Dear R users, I would like to know if there is a package in R that estimates multinomial logit models (without using surrogate Poisson models) -or even better- nested multinomial logit models? I am using the Windows version of R (Windows 95). To my understanding, the S package called nnet does that, but it seems not to work in R. Thanking in advance for any help, Marjo Pyy-Martikainen

Please, could you tell me how to enter a mixed or a purely conditional multinomial logit model in NNET. I know how to do a multinomial logit in NNET but I don't know how to do conditional or mixed models using this package. I do know how to do this with VGAM - but would like to compare my results to those obtained by NNET. Thanks. Raffaele.

I'm attempting to creat multinomial logistic regression model using the following code: mlogit<- vglm(ME ~ HIST,family=multinomial(),na.action = na.pass) ME (dependent variable) has three levels (0,1,2) How do I declare a reference outcome (either 0,1,2)?

I am trying to estimate a latent class multinomial logit regression with flexmix. I am not sure if I should do it as follows: m4<-flexmix(cbind(y,1-y)~x1+x2|id,model=FLXMRglm(family="binomial"),data=NPreg,k=2) , where id links each row with the corresponding respondent. Each respondent has 4 alternatives to chose from. y takes the value 1 only for the alternative chosen; x1 and

Hi I am wanting to fit some multinomial logit models (multinom command in package nnet) Is it possible to do any model checking techniques on these models e.g. residual, leverage etc. I cannot seem to find any commands that will allow me to do this. Many thanks ---------------------- L.E.Gross L.E.Gross at maths.hull.ac.uk

Hi all, I have a dataset with a response variable with three categories (1, 2, 3) and a lot of continuous variables. I'd like to make a MLR with these variables. I've been watching the libraries nnet and zelig for this purpose but I don't understand them well. I use a training sample data to make the MLR. train.set <- sample(1:1000,1000*0.7) I have done this: library(nnet) net

Hi, I'm struggling trying to specify a multinomial logit discrete choice model in R. Any help and/or code examples appreciated. I am specifically interested in specifying a model where no universal choice set exists and each choice set has a variable number of alternatives (one of which is chosen) see data below. Many Thanks, David PS I have asked earlier but without reply. Is it

Dear all, I am trying to run a mixed multinomial logit model in R since my response variable has 4 non-ordinal categories. I am using the package mlogit that estimates the parameters by maximum likelihood methods. First of all, I prepared my data using the mlogit.data command. In the mlogit command, one can introduce alternative-specific (fixed factors??) and individual-specific (random

I need to estimate a model that predicts the proportional split of travel among the vehicles of a household based on vehicle characteristics such as age, fuel economy, and travel cost per mile. The model estimation dataset has a record for each household vehicle with information about the vehicle, the household, and the proportion of the total household vehicle travel using that vehicle. I have

Dear R-Help, I'm hoping to find a Multinomial Nested Logit package in R. It would be great to find something analogous to "PROC MDC" in SAS: > The MDC (Multinomial Discrete Choice) procedure analyzes models > where the > choice set consists of multiple alternatives. This procedure > supports conditional logit, > mixed logit, heteroscedastic extreme value,

Hi All, I am attempting to build a Multinomial Logit model with dummy variables of the following form: Dependent Variable : 0-8 Discrete Choices Dummy Variable 1: 965 dummy varsghpow at student.monash.edu.augh@gp1.com Dummy Variable 2: 805 dummy vars The data set I am using has the dummy columns pre-created, so it's a table of 72,381 rows and 1770 columns. The first 965 columns represent

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,

A multinomial logit model can be specified as a conditional logit model after restructuring the data. Doing so gives flexibility in imposing restrictions on the dependent variable. One application is to specify a loglinear model for square tables, e.g. quasi-symmetry or quasi-independence, as a multinomial logit model with covariates. Further details on this technique and examples with several

Hi, I've got one thats really stumping me... rsync 2.6.9 from FreeBSD ports on both ends. /usr/local/tmp/rsync --dry-run -v -v -v -v -v -v -v -v -v -v -v -v --dry-run -vrlptHDgozxS --partial --force --delete --numeric-ids --exclude='A/*' --include='*/' /usr/local/etc/machines/ rsync@A:/usr/local/etc/machines/ It seems to be sending over files that I can't understand

Dear all, I'm trying to analyze data with the following structure: ind cat tx age 40.2 por fol peq vh 35 41.9 por fol med vh 35 68.9 por fol preov vh 35 71.5 por fol peq ser 37 67.5 por fol med ser 37 76.9 por fol preov ser 37 78.7 por fol peq otr 37 78.3 por fol med otr 37 82.1 por fol