OpenMx General Help
Product of Variables Identification
my aim is to use product of variables to fit a random-intercept random-slope model with latent mean centering. To be precise, my model is as follows. $i$ indexes person, $t$ indexes observations within a person.
$$Y_{it} = \beta_i (X_{it}-meanX_i) + meanY_i + residualY_{ij}$$
$$X_{it} = meanX_i + residualX_{ij} $$
$$\beta_i \sim N(\mu_\beta, \sigma_\beta^2), \quad meanX_i \sim N(\mu_X, \sigma_X^2), \quad meanY_i \sim N(\mu_Y, \sigma_Y^2)$$
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Sampling weights for mxFitFunctionMultigroup()
I was wondering if there is a way to specify sampling weights in a multi-group model? I want all observations in a certain group to be weighed equally, but groups with a larger weight should have more influence on the estimation of parameters that are shared/equal between groups.
Best,
Manuel
Seek copy of MX varimax rotation code posted years ago at VA Tech web site
Several years back we posted a varimax - quartimax script that worked well under an earlier implementation of MX.
1) Can you direct me to a site so I can retrieve this script and its documentation?
2) Would like to revise the script so it will run under R (Win 11) in the latest MX configuration. Could we get permission to get help from Neale and other administrators to guide us in making revisions to get the script to work in 2024?
Thank you for your advice and direction, best, Paul Hoon
Can't solve dimname associated error
pheno2 <- read.csv("pheno2.csv")
library(OpenMx)
colnames(pheno2) <- gsub("\\.", "_", colnames(pheno2))
any(is.na(pheno2))
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Can´t get the fit indices for DoC model, as Saturated DZ gets non pos def
Can't derive CIs in multiple groups twin model. Too nested!
**Summary**: if I try go get cis for parameters in multiple groups twin models (written in matrix algebra only), open mx complains about it being too nested. Multiple groups here refers to running the model for males and females, for example. See MWE.
**Error**:
Unable to install OpenMx with NPSOL
I have been trying to install the OpenMx Team's build of OpenMx with the NPSOL optimizer, using the following line as per instructions (https://openmx.ssri.psu.edu/installing-openmx):
source('https://vipbg.vcu.edu/vipbg/OpenMx2/software/getOpenMx.R')
I have tried several times and with several R versions (4.1.3, 4.2.3, and 4.3.1), but I always get the warning that the package ‘OpenMx’ is not available as a binary package for this version of R (see full warning message attached).
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Trouble with importing specific functions from OpenMx into my package
I am currently developing an R package called nlpsem, and I am trying to use some functions from the OpenMx package. Specifically, I am trying to use the mxOption and imxReportProgress functions. However, I am encountering some issues when trying to use these functions without explicitly loading the OpenMx package with library(OpenMx).
In my DESCRIPTION file, I have the following lines:
Imports:
OpenMx, ggplot2, dplyr, tidyr, stringr, Matrix, nnet, readr, methods
Error message when searching two words or phrase in OpenMx Forum
"Forbidden
You don't have permission to access /search/node/TERM1 TERM2 on this server."
Google doesn't seem to search the posts itself but only the forum overview.
Announcing umxCLPM() TESTERS NEEDED
All I really want is another single-author paper complaining about cookie-cutter models, so I wrote the ultimate cookie-cutter (\s) for CLPM:
https://github.com/tbates/umx/commit/26a9cf01da4cc789be3fc66ddf16ab40050cf87d
It is hard to find spect details for some of these models on the original papers, so I need testers. In particular, I wonder whether the 'uv' correlation is really equated across in Heise's and in STARTS. I believe it is fixed for Hamaker's.
Enjoy.
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