similar to: FIML in R

Is there a way to use full information maximum likelihood (FIML) to estimate missing data in the sem package? For example, suppose I have a dataset with complete information on X1-X3, but missing data (MAR) on X4. Is there a way to use FIML in this case? I know lavaan and openmx allow you to do it, but I couldn't find anything in the documentation for the sem package. Thanks! -- Dustin Fife

Hi, I am wondering if anyone knows of an easy way to fit a saturated model using the sem package on raw data? Say the data were: mtcars[, c("mpg", "hp", "wt")] The model would estimate the three means (intercepts) of c("mpg", "hp", "wt"). The variances of c("mpg", "hp", "wt"). The covariance of mpg with

Hello! I am trying to reproduce (for a publication) analyses that I ran several months ago using lavaan, I'm not sure which version, probably 0.4-12. A sample model is given below: pathmod='mh30days.log.w2 ~ mh30days.log + joingroup + leavegroup + alwaysgroup + grp.partic.w2 + black + age + bivoc + moved.conf + local.noretired + retired + ds + ministrytime + hrswork + nomoralescore.c +

Is there an equivalent to MPlus's Full Information Maximum Likelihood (FIML) missing data estimator for R? If so, is there a way to take covariance structures produced by such a package and perform multiple regression with these? If you are unfamiliar with Mplus' FIML below is a link to their manual. Their estimation technology is discussed on page 25. I have asked the developer of the

Hi I was asked if lme can use FIML (Full Information Maximum Likelihood) instead of REML or ML but I don't know the answer. Does anybody know if this is implemented in R? Thanks Francisco

Full_Name: Michael Spiegel Version: 2.10 OS: Windows Vista Submission from: (NULL) (76.104.24.156) The following error is produced when attempting to call install.packages. Here is the results of the traceback: > source('http://openmx.psyc.virginia.edu/getOpenMx.R') Error in f(res) : invalid subscript type 'list' > traceback() 7: f(res) 6: available.packages(contriburl =

Hi, I recently tried to estimate a linear unconditional latent growth curve on 7 repeated measures using lavaan (most recent version): modspec=' alpha =~ 1*read_g0 + 1*read_g1 + 1*read_g2 + 1*read_g3 + 1*read_g4 + 1*read_g5 + 1*read_g6 beta =~ 0*read_g0 + 1*read_g1 + 2*read_g2 + 3*read_g3 + 4*read_g4 + 5*read_g5 + 6*read_g6 ' gmod=lavaan(modspec, data=math, meanstructure=T,

Dear all, I would like to know if it is possible to estimate multi-group SEM by using R... Thank you _________________________________________________________________ ¿Cuánto espacio necesitas para guardar tus emails? Con Hotmail tienes 5GB y puede ampliarse a más. [[alternative HTML version deleted]]

I am the guy who compiles the OpenMx binaries. We would be delighted to place our package on CRAN, once the project is stable enough so that we are comfortable releasing it to the larger public. Let's try to track down where I made a mistake. Our Makevars.in file contains the line: PKG_LIBS=$(FLIBS) $(BLAS_LIBS) $(LAPACK_LIBS) In addition, on the build machine I noticed that a copy of

Full_Name: Timothy Brick Version: 2.10 OS: Mac OS X (seen on both 10.6 and 10.5) Submission from: (NULL) (63.255.24.5) When using install.packages in R on Mac OS X, packages that require gfortran throws an error (Example below from installation of OpenMx package): Loading required package: OpenMx Error in dyn.load(file, DLLpath = DLLpath, ...) : unable to load shared library

Dear R users/developers I requested help to solve the problem of formulating Multivariate Sample selection model by using Full Information Maximum Likelihood (FIML)estimation method. I could not get any response. I formulated the following code of FIML to analyse univariate sample selection problem. Would you please advise me where is my problem library (sem) library(nrmlepln) Selection

Dear all, I am trying to estimate simultaneous equation model concerning growth in russian regions. I run the analysis by means of FIML in R sem package. I am not familiar with SEM yet, but I've just got several suitable estimated specifications. Nevertheless, sometimes R gives the following warning message: Warning message: Negative parameter variances. Model is probably underidentified.

Dear R-help, I am interested in using structural equation modeling. Just getting started with it, but I'm looking for suggestions for packages. As an aside, what's the best way for looking for packages at CRAN? -- Robert Terwilliger Biomedical Physicist Laboratory of Neurocognitive Development Western Psychiatric Institute and Clinic University of Pittsburgh Medical Center Loeffler

HI, I am relatively new to R and would appreciate some help or directions for this. I am trying to model 3 longitudinal outcomes jointly and to identify some predictors for these 3 joint outcomes (all continuous). I am trying to find some codes that I may modify to do this but cannot seem to find anything. -- View this message in context:

Hi,I have a fundamental questions that I'm a bit confused. If any guru from this circle could help me out, I would really appreciate.I have a system of equations in which some of the endogs appear on right hand sides of some equations. To solve this, one needs a technique like 2SLS or FIML to circumvent inconsistency of the estimated coefficients. My question is that if I apply the nonlinear

Hello: Has anyone tried to model-based recursive partition (using mob from package party; thanks Achim and colleagues) a data set based on a multinomial logit model (using mlogit from package mlogit; thanks Yves)? I attempted to do so, but there are at least two reasons why I could not. First, in mob I am not quite sure that a model of class StatModel exists for mlogit models. Second, as

Dear R Devel Some of our R users are still insisting we run R-2.15.3 because of difficulties with a package called OpenMX. It can't cooperate with new R, oh well. Other users need to run R-3.0.1. I'm looking for the most direct route to install both, and allow users to choose at runtime. In the cluster, things run faster if I install RPMs to each node, rather than putting R itself on

Hello All, Recently, I was asked to help out with an SEM cross-validation analysis. Initially, the project was based on "sample-splitting" where half of cases were randomly assigned to a training sample and half to a testing sample. Attempts to replicate a model developed in the training sample using the testing sample were not entirely successful. A number of parameter estimates were

I have a student that I'm encouraging to use R rather than SAS or Stata and within just 2 weeks he has come up with a question that stumps me. What does a person do about endogeneity in generalized linear models? Suppose Y1 and Y2 are 5 category ordinal dependent variables. I see that MASS has polr for estimation of models like that, as long as they are independent. But what if the

Hi, I saw on the mailing list and in the NEWS file that some unsafe math transformations were disabled for the reference BLAS implementation that is used in R. We have a set of performance tests for the OpenMx library, and some of the tests have a x3-10 slowdown in R 2.12.0 versus 2.11.1. When I copy the shared library libRblas.0.dylib from the 2.11.1 installation into the 2.12.0 installation,