similar to: latent class regression

Dear list, I have been comparing the outputs of two packages for latent class regression, namely 'flexmix', and 'mmlcr'. What I have noticed is that the flexmix package appears to come up with a much better fit than the mmlcr package (based on logLik, AIC, BIC, and visual inspection). Has anyone else observed such behaviour? Has anyone else been successful in using the mmlcr

Dear Listers, My post might be somewhat OT. Currently, I am trying to use flexmix to build a finite mixture model. For instance, I am getting the prior probability and coefficients for each latent class from training data. Is there a way to get the posterior probablity and prediction of a new dataset? What I am thinking is to apply the prior prob and coefficient from training set to testing data

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

Hello list, Has anyone had any luck creating an M-step driver for negative binomial regression for use with package flexmix? I've had a look here: http://cran.r-project.org/web/packages/flexmix/vignettes/flexmix-intro.pdf as well as poking around in the flexmix source, but I haven't had much luck getting anything to work. I can't figure out how to a) come up with an initial estimate

Dear R-help listers, I am a new convert to R. I am trying to use a r package to conduct latent class analysis as a triangulation check of my cluster analysis using the cluster package in R. I have about 30 cases and 6 indicators, some of which are binary indicators and others are ratio-level variables (percentages). I looked around for information in flexmix, lca, and poLCA, and couldn't find

I would like to extract the information criteria from an hlme object (lcmm package). Would you please advise me on how to extract just the BIC (AIC)? On another topic, when I apply hlme (lcmm) and flexmix (flexmix package) to the same data set, I get BIC values that suggest two different latent class structures. Flexmix using FLXMRlmm predicts two classes while hlme says 4. Can you suggest a

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

Dear All, I've used mice package for my latent class analysis and binary logistic regression I've imputed five data sets and with long format I've added new variable that shows latent class membership. And then in addition to other variables, I'll use binary logistic regression and try to pool the estimates. However I couldn't create data.frame to mids objects, and therefore

Hi Can anyone please suggest me a package where I can estimate a non-linear regression model? One of the independent variables is latent or unobserved. I have an indicator variable for this unobserved variable; however the relationship is known to be non-linear also. In terms of equations my problem is y=f(latent, fixed) q=g(latent) where q is the indicator variable For me both f and g are

Dear R-users, I would like to use the package flexmix to fit latent classes to a regression model. My data are repeated measurements of bernouilli variables so I can use the binomial family link to the glm function. The design is not balanced, meaning that for some individuals in my data set I have 10 measurements or more, for others I only have 5 or even less. My question is the following. Can

As an alternative to Latent GOLD, I'm wondering if anyone knows of and R package that can manage Latent Class Analysis with mixed variable types (continuous, ordinal, and nominal/binary). [[alternative HTML version deleted]]

What's the best approach to running latent class analysis with R? I've downloaded both randomLCA and poLCA packages, but I am interesting in running a standard LCA with individual records (not frequency table) as input data. Wen Gu John Jay College of Criminal Justice445 West 59 StreetNew York, NY 10029 wgu@gc.cuny.edu _________________________________________________________________

Dear all Last week, I posted a question and some of you spent their valuable time to respond. Thank you (once again). This time, after doing a lot of homework, I return with  a second question on the issue. I was advised to use poLCA for a Latent Class Analysis with covariates. The software works well, although I feel a bit uncomfortable with the fact that you need to run many times the

Hello there, I would like to test the agreement amongst 6 raters for nominal data on a scale from 1-4, and conduct a latent class analysis in R. How should the data be formatted and what code should I use? Thank you very much Lisa Wang Princess Margaret Hospital Biostatistics tel:416 946 4501

Hi, I perform latent class analysis on a matrix of dichotomous variables to create an indicator of class/category membership for each observation. I would like to know whether there is a function that selects the best fit in terms of number of classes/categories. Currently, I am doing this with the lca() function of the e1071 package. This function requires me to specify the number of classes

Dear R users, I would like to perform Latent Class Logit Models for the analysis of choice experiments in environmental valuation. This kind of analysis is usually performed with NLogit Software (http://www.limdep.com). I attach the results I usually obtain using NLogit and NLogit model specifications. For Random parameter models and Logit Models I usually perform my analysis with the package

Hi, I am using the package "flexmix" and would like get some assistance. I am trying to run two equations jointly Y1=X1B+E1 Y2=X2G+E2 So that I have X and Y in a matrix format and would like to run the latent class model using flexmix. Though, my problem here is that Flexmix automatically generates intercepts. I have intercept for both of the equations that my X matrix looks like

Dear list members I am new to the list and would be much appreciated if you could help me. I am very interested in applying Latent Class Model for analysing multiple raters agreement data. I have recently found a paper by Uebersax, J. (1993) which described a method in a form of Located Latent Class Analysis (llca). Uebersax has written a Fortran program which is available on the web, for the

Hi r-help, I use lavaan:sem() for structural equation modelling with latent variables. Below is a reproducible example (the code requires a working installation of lavaan) where the latent variable criminality is in focus. Besides criminality in general, I am specifically interested one of the manifest variables that make up the latent variable criminality, namely fire.setting. My question is:

_____ De : Pousset [mailto:maud.pousset@noos.fr] Envoyé : mardi 4 juillet 2006 18:38 À : 'r-help@stat.math.ethz.ch' Objet : Latent Class Analysis Hello everybody, I am working on latent class analysis and have already used the ‘R’ function « lca » (in the e1071 package). I ‘ve got interesting results but I can’t simply find out the methodology used by this routine : 1) What