Dear Mike and other users,
I am doing random effects TSSEM and had run into problems with openmx status=6 with tssem1(). In earlier communication with Mike, he noted that some of the heterogeneity variances (I2) were near 0 (e.g., .0000, .0001) and said that tssem1() does not handle them well. Thus he suggested fixing the near 0 heterogeneity variances to 0, and letting the larger heterogeneity variance vary with starting value 0.01, then running tssem1() with this user-defined structure:
Try user-defined structure for the random effects
Fix the elements in 1, 2, 3, 4, and 6
RE <- Diag(c(0,0,0,0, "0.01Tau2_5", 0, "0.01Tau2_7", "0.01Tau2_8", "0.01Tau2_9", "0.01*Tau2_10"))
RE
random1 <- tssem1(vector, n, method="REM", RE.type="User",
RE.constraints = RE)
Openmx status became 0 after doing this. I will need to conduct similar analyses with several other datasets and thus have some follow-up questions about fixing heterogeneity variances in further analyses.
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Mike suggested previously that I should fix a heterogeneity variance only if there are "NA in the estimated heterogeneity or the OpenMx status is not 0 or 1," and only if the variance is as small as 1e-8 or 1e-10. But how do I check that the heterogeneity variance for any intercept is <1e-8, since the tssem1() output shows only up to 4 decimal places?
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For some of my analyses, openmx status is 0 after running/rerunning tssem1() and running tssem2(), but I get the following error message after running tssem2():
hIn .solve(x = objectmx.fit@outputmx.fit@outputcalculatedHessian, parameters = my.name) :
Error in solving the Hessian matrix. Generalized inverse is used. The standard errors may not be trustworthy.
Thus I fixed to 0 the heterogeneity variances between .0000 and .0003 in the tssem1() output, and then reran tssem1() with user-defined structure, which made the error message go away. I can't tell how small the .0000 really is, but the .0003 is >1e-8. So if openmx status=0, is it better to set heterogeneity variances to 0 to avoid the error, or better not to set to 0 if the variances are >1e-8 but get the error?
Does the error really matter for interpretation of findings, since the Std Error is NA in my tssem2() output anyway, and I use the lbound and ubound to interpret whether the coefficients, indirect effect, and direct effect are significant?
Any suggestions or advice would be much appreciated!
Mei Yi