That would enable you to model a single variance component based on the composite variable. However, if you wish to model a 2 level design, where person is nested within household, you might try:
proc mixed data=hrs noclprint ;
class HHID PN;
model age=
/solution ;
random intercept HHID/ subject= PN;
run;
I removed the covtest option from the PROC MIXED statement, as it depends on a Wald test that is really not a good test given the distribution of variances, and also removed the ddfm=bw, as you now want a containment hierarchy for the variance components.
If you truly need to test whether the variance components are non-zero I would recommend changing to PROC GLIMMIX and using the options under the COVTEST statement, which give likelihood ratio based tests that are more appropriate.
SteveDenham
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