Displaying 20 results from an estimated 7000 matches similar to: "latent class models"
2011 Feb 28
1
mixture models/latent class regression comparison
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
2011 Dec 21
0
Estimating a latent class multinomial logit regression with flexmix
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
2011 Feb 23
0
negative binomial latent class regression in package flexmix
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
2011 Dec 23
2
Latent class multinomial (or conditional) logit using R?
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
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2012 May 29
1
model frame and formula mismatch with latent class analysis poLCA
Dear R-users,
I keep getting an ERROR saying " Error in model.matrix.default(formula,
mframe) : model frame and formula mismatch in model.matrix() " when i fit
poLCA with more than 63 variables. Below are the details.
I am trying to do a Latent Class Analysis using poLCA. My data set contains
binary scores of, for instance, 200 students on 100 items. These numbers
could even be more
2007 Nov 08
1
finite mixture model (or latent class)
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
2008 Nov 05
0
latent class analysis of nominal and continuous indicators
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
2011 May 23
2
Latent class analysis, selection of the number of classes
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
2005 Apr 14
0
latent class regression
As far as I know, there are 2 libraries for latent class regression,
flexmix and mmlrc. Since I don't have experience with either one, can
someone give me some advice which library is better?
Thank you so much.
2010 Jul 24
1
latent class analysis with mixed variable types
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).
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2006 Mar 21
0
finite mixture model, using flexmix
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
2011 Jan 31
2
Latent Class Logit Models in discrete choice experiments
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
2011 Feb 28
0
Gamma mixture models with flexmix
I've been trying with no success to model mixtures of Gamma distributions using
the package flexmix (see examples below). Can anyone help me get it to model
better? Thanks very much.
-Ben
##
## Please help me get flexmix to correctly model mixtures of
## Gamma distributions. See examples below.
##
library('flexmix')
##
## Plot a histogram of dat and the Gamma mixture model given
2009 Feb 25
2
run latent class analysis with R
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
_________________________________________________________________
2005 Apr 12
1
R Package: mmlcr and/or flexmix
Greetings
I'm a relatively new R user and I'm trying to build a latent class model.
I've used the 'R Site Search' and it appears there's not much dialogue on
these packages
On mmlcr, I've gotten it working, but not sure if I'm using it correctly.
On flexmix, I can only seem to get results for one class.
I'm attaching my code below - if anyone
2012 Jun 15
0
Flexmix 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
2006 Feb 09
2
latent class modle for rater agreement
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
2006 Jul 13
1
TR: Latent Class Analysis
_____
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
2005 Mar 15
0
New package for latent trait models
Dear R-users,
I'd like to announce the release of my new package "ltm" (available
from CRAN), for fitting Latent Trait Models (including the Rasch
model) under the Item Response Theory approach. The latent trait model
is the analogous of the factor analysis model for Bernoulli response
data. "ltm" fits the linear one- and two-factor models but also allows
for
2005 Mar 15
0
New package for latent trait models
Dear R-users,
I'd like to announce the release of my new package "ltm" (available
from CRAN), for fitting Latent Trait Models (including the Rasch
model) under the Item Response Theory approach. The latent trait model
is the analogous of the factor analysis model for Bernoulli response
data. "ltm" fits the linear one- and two-factor models but also allows
for