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Accounting for Different Levels of Twin Relatedness in SAS PROC MIXED

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I have a dataset with a number of identical twin pairs and fraternal twin pairs. I want to examine the relationship between two variables (let's call them INDEPENDENT and DEPENDENT). However, I can't run a normal OLS regression because each twin's dependent variable is correlated with their co-twin's.

The way I have been dealing with this is to use SAS PROC MIXED and include a random intercept defined by twin pair (FAMILYID). Here is my syntax:

proc mixed method=ml covtest noclprint;<br>
class FAMILYID; <br>
model DEPENDENT = INDEPENDENT/solution;<br>
random intercept/sub=FAMILYID type=un gcorr;<br>
run;

However, I've realized that I have a heteroskedasticity problem. The identical twins are likely to be more related to each other than the fraternal twins (variable indicating whether twins are fraternal or identical is called TWINTYPE), and the model doesn't reflect this.

According to SAS documentation for the RANDOM statement: "GRP=effect defines an effect specifying heterogeneity in the covariance structure of G. All observations having the same level of the group effect have the same covariance parameters."

It sounds like this is exactly what I want. However, I am confused how this relates to the REPEATED statement and whether I need to use the REPEATED statement with "GROUP" instead of "RANDOM" or in addition to random. Conceptually, what are each of these doing and are they redundant for my purposes?

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