OpenMx General Help
sbremer
Joined: 11/08/2011
lbound for variances
Hello again :)
I need some assistance:
When running my model (factor analysis with four indicators) with mxRun() I get a negative residual variance. So I used lbound = 0 for the estimate of this variance. The output gives me 0 for the estimate. I wonder whether OpenMx really estimates there or does it try to estimate in the direction of the old, negative estimate and stop at the lower bound of 0.
If this is not detailed enough I could provide my script and full output.
Thanks in advance!
Sophia
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Charlotte
Joined: 07/02/2012
Freely estimate genetic correlation DOS twins
Hi,
I'm adapting the BIVARIATE Boulder-skript atm and I'm trying to freely estimate the paths connecting the As of the two phenotypes for the DOS-twins. So it should be 0.5 for the DZ twins, but freely estimated for the DOS twins.
With this skrip, I get ONE estimate for both paths:
pathRados <- mxMatrix (type="Full", nrow=1, ncol=1, free=TRUE, values=0.5, label="rados", lbound=-1, ubound=1, name="ra")
expCovDOS <- mxAlgebra(name = "expCovDOS",
expression = rbind (cbind(Am+Cm+Em, (ra%x%(am%*%t(af)))+cm%*%t(cf)),
rabil
Joined: 01/14/2010
Upper and lower bounds of confidence interval equal the parameter estimate
I've written a simple latent class model (simplified the OpenMx example code for the growth mixture model). I've run it with 1,000 random starts using the approach shown in the docs and I get the maximum likelihood estimates. When I use the same starting values that were used for the smallest -2LL (which has a status code of 0), I get the same estimates but when I request confidence interals, the upper and lower bounds equal the estimates. Usually, when I run various OpenMx models, I have few problems estimating the CI's.
Docherty
Joined: 02/20/2012
heritability estimates for unequal family sizes in R
I'm working with pedigrees where one family member has schizophrenia and all family members share 1/2 DNA. The program SOLAR seems to use a separate matrix for mother and father id when samples have families of varying sizes. Does anyone know of sample R/OpenMx syntax for this? I have a smaller sample and want to use all family data possible, but my first-degree family members are unequal--it would be nice to eyeball what matrices look like in this type of analysis.
koak
Joined: 05/10/2012
Bivariate or multivariate correlated factors model script
I am super new to twin analyses, R, Mx and the whole shebang ... I am wondering if anyone has a script for a bivariate or multivariate correlated model. I have been using the Cholesky Decomposition, Independent Pathways and Common Pathways models to look at my multivariate data and would like to be able to at the data from a correlated factors perspective.
Any help much and greatly appreciated!
Karen
brauer
Joined: 01/28/2012
Lagrange Multiplier Test
Hi, is there a way to get the Lagrange Multiplier Test with OpenMx? I am usually not a fan of this type of data-driven test but I am currently analyzing a dataset where a LM Test might help me understand what is going on. I am running a four-factor CFA model with three indicators. The fit is OK but not great. The correlation residuals tell me that I am drastically underestimating the relationship between one indicator of the first factor and one indicator of the second factor.
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Julia
Joined: 03/29/2012
Does it really take that long?
Hello.
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kspoon
Joined: 06/17/2011
Assessing Model Fit - Any Insight?
I was wondering if anyone had some insight on which measure of model fit is the most appropriate (in reference mostly to the 5 different AIC and BIC values output by OpenMX) - both in general situations and in my particular situation. This is most important to us since in our models they aren't agreeing on an answer.
For my particular problem, we're looking at 8 variables (in a twin modeling framework, but we're looking at non-twin models as well) and these variables are split into 4 closely correlated pairs (correlations around .5) that are loosely correlated with one another.
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Mrkwht
Joined: 03/27/2012
RMSEA returns NA
I fit a basic latent growth curve model (using covariance data and means) and everything seems to work fine, but the RMSEA is returning NA in the summary function. Looking at the behavior of the summary function, it appears that this is because the squaredRMSEA is less than 0 (model chi-sq=3 with df=4). I am just now in the process of learning SEM, so forgive the basic question. But I thought that RMSEA should be given as 0 if this happens, not NA. I'm sure that I'm just missing something, but what is the reasoning behind returning NA?
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brauer
Joined: 01/28/2012