General question about assumptions
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mirusem
Joined: 11/19/2018
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So it seems to me that there are two key things one should do if one wants an unbiased use (/estimates) of the ACE model. One is making sure the classical twin design assumptions are met (e.g. variances equal across groups), etc. I am wondering, on top of this, should normality be explicitly tested for as well? I had read that if the assumptions needed in general for a classical twin design (those relating to mean and variance equality) are violated, that then that would then indicate the data is potentially nonnormal. But, if all the assumptions are satisfied, does that necessarily mean that the data are necessarily normal 'enough' for the ACE model? Or should that also be explicitly tested for using some normality test (even if the variables are fisher-z transformed and all other assumptions are met successfully)?
I appreciate it!
Cannot prove all assumptions are met
Note also that if there are ordinal level of measurement data, they should be analyzed as ordinal by, e.g., integrating over the multivariate normal done semi-automatically in OpenMx with ordinal (ordered factor) variables. You need to provide a model for the thresholds in this case. WLS provides an alternative fit function that is less restrictive - elliptical is required but normality is not.
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Thanks! and a follow-up question
So I guess it makes sense to test for all of these entirely in that case.
I guess that only raises one question for now--if the concern is for multivariate normality, then, do we care about normality involving twin 1 and twin 2 separately in a given population (specifically a multivariate normality test, as opposed to a single normality test on just the population of all MZ twins for the given phenotype, etc.)?
As for ordinal methods: I am thinking of excluding the nonnormal/violating assumption phenotypes of interest for consistency, but maybe will also look into ordinal methods at some point and that's definitely a useful reference point.
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In reply to Thanks! and a follow-up question by mirusem
SEM as generally robust to nonnormality?
to say that in general nonnormality isn't as clear of an issue in these kinds of studies? I would wonder at what point a cut-off of too 'nonnormal' (bivariate nonnormal specifically as it involves both twins) would be if you are assessing it using any kind of multviariate normal test.
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In reply to SEM as generally robust to nonnormality? by mirusem
imxRobustSE if data are nonnormal for SEs/CIs
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