similar to: OpenMX structural equation software

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 =

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

Hello, I am trying to profile a function of OpenMx (http://openmx.psyc.virginia.edu) for CPU time. My operating system is OS X 10.10. OpenMx contains C++ and Fortran code. I have read the section regarding profiling compiled code in the manual (https://cran.r-project.org/doc/manuals/r-release/R-exts.html#Profiling-compiled-code). This section and this post (http://blog.fellstat.com/?p=337)

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

Dear r-help list members, I'm teaching a one-day workshop on "An Introduction to Structural Equation Modeling with the sem Package for R" at McMaster University in Hamilton, Ontario, Canada, on November 22. The workshop is open to non-McMaster attendees at a small charge. Further information, including on how to register, is in the attached poster. Best, John

Dear R-help list members, I forgot to copy my reply to the r-help list. Here's most of it. John -------------------------------- John Fox Department of Sociology McMaster University Hamilton, Ontario Canada L8S 4M4 905-525-9140x23604 http://socserv.mcmaster.ca/jfox -------------------------------- -----Original Message----- From: John Fox [mailto:jfox at mcmaster.ca] Sent: Sunday,

Hi John Thanks a lot for the reply. Could you suggest how I can correct this problem? I tried using a correlation matrix instead of raw moments, but still got the same error. I also fixed parameters v1,v2,v3,a1 at 1; then it gave me the error that the system is exatly singular. To answer the points that you raised: 1. x1-x6 are not causes; they are just indicatiors. Does that change my

Hi there, I want to estimate simultaneous equation model with panel data. The model looks as follows Y1=a0+a1*X1+a2*X2 Y2=b0+b1*X2+b2*X1 X1=Z1-(Y1/a1) X2=Z2-(Y2/b1) I In this model Y1, Y2, X1 and X2 are endogenous variables; Z1, Z2 are exogenous variables and a0, a1, a2, b0, b1 and b2 are parameters. Could any one please help me how to estimate this model in R. Thanking you in anticipation

Dear Helplist, I want to produce forecasts from a structural equation model. With the SEM package the model setup and its estimation is possible. However, I have not figured out how to obtain ex ante forecasts, i.e. applying the Gauss-Seidel algorithm to the estimated structural equations for provided values of the exogenous variables (i.e.: y_t = -inv(A)*B*x_t). Does anyone know if the there is

I am looking for study materisl?on how to conduct 'small area estimation' using structural equations models in R for both longtudinal and repeated cross-section data.?Tried google did not work. There are other regression technique my interest is on structural equation models.?

Hi all, I am using package lavaan and have created a structural equation model with two exogenous and seven endogenous variables with the following relationships #specify the model m1 = ' # regressions D ~ ma + hs + b4 + b5 + b15 + b16 ma ~ hs + b4 + b5 + b15 + b16 hs ~ b4 + b5 + b15 + b16 b4 ~ el + la b5 ~ el + la

Dear R users, Apologies for the total beginner's question. I was wondering whether you could tell me if there is a structural equation modelling function that can handle binary data i.e. in similar manner to the GLM function with a binomial family. Best wishes, Mario

Dear R-users, A new package called `lavaan' (for latent variable analysis) has been uploaded to CRAN. The current version of lavaan (0.3-1) can be used for path analysis, confirmatory factor analysis, structural equation modeling, and growth curve modeling. More information can be found on the website: http://lavaan.org Some notable features of lavaan: - the 'lavaan model

Dear R-users, A new package called `lavaan' (for latent variable analysis) has been uploaded to CRAN. The current version of lavaan (0.3-1) can be used for path analysis, confirmatory factor analysis, structural equation modeling, and growth curve modeling. More information can be found on the website: http://lavaan.org Some notable features of lavaan: - the 'lavaan model

Dear R-users, I am running a large number of simulations and estimating a structural equation model for each one using the SEM package. Each run of my program has around 8000 simulations. Most of the time the program completes all of them correctly but sometimes I get a segmentation fault in the sem routine and my program stops with the following error message: > *** caught

Hi I am running a structural equation model with R using the sem command; am getting the following error: "Error in sem.default : The model has negative degrees of freedom = -4" My model is as follows: s_model = specify.model() x1->m1, b1,NA x2->m1, b2,NA x3->m2, b3,NA x4->m2, b4,NA x5->m2, b5,NA x6->m2, b6,NA m1->y, a1,NA m2->y, a2,NA m1<->m1, v1,NA

Hi - I am confronting a situation where I have a set of structural equation and one or two of my responses are multinomial. I understand that sem would not deal with the unordered response. So I am thinking of the following two ways: 1. Expanding my response to a new set of binary variables corresponding to each label of my multinomial response. Then use each of these as a separate response in my

I am trying to work my way through the book "Singer, JD and Willett, JB, Applied Longitudinal Data Analysis. Oxford University Press, 2003" using R. I have the SAS code and S-Plus code from the UCLA site (doesn't include chapter 8 or later problems). In chapter 8, there is a structural equation/path model which can be specified for the sem package as follows S <- cov(al2)

I am a new user of the function sem in package sem and lavaan for structural equation modeling 1. I don?t know what is the difference between this function and CFA function, I know that cfa for confirmatory analysis but I don?t know what is the difference between confirmatory analysis and structural equation modeling in the package lavaan. 2. I have data that I want to analyse but I have some