Hello!
I am writing a paper regarding the relationship between sexual orientation and risk behaviors based on the 2015 Youth Risk Behavior Survey (CDC).
I successfully created a table based on the interaction of each of my dependent variables and the sexual orientation identifying response, but when attempting to run mlogit, I hit on two variables which are omitted due to multicollinearity:
qn11 | -.126644 .0739262 -1.71 0.087 -.2716207 .0183326
qn12 | .0182417 .0329616 0.55 0.580 -.0463992 .0828826
qn29 | -.2315899 .0690746 -3.35 0.001 -.3670522 -.0961276
qn59 | -.1794645 .0439278 -4.09 0.000 -.2656113 -.0933177
q60 | 0 (omitted)
qn63 | 0 (omitted)
qn89 | .0556139 .0397618 1.40 0.162 -.022363 .1335908
qnothhpl | -.0052826 .0420503 -0.13 0.900 -.0877475 .0771823
qndualbc | -.0796317 .066723 -1.19 0.233 -.2104822 .0512188
qnbcnone | -.0852495 .0521206 -1.64 0.102 -.1874633 .0169643
This output was created with the commands:
I understand where the issue is, as q60 is "ever having sexual intercourse" and qn63 is "currently sexually active." Naturally, one of these is perfectly 0, which I believe is causing the problem. However, the both need to be present in the model. How do I adjust my tests for this? Should I be analyzing using a different type of test? It obviously needs to be accounted for, as those variable are not insignificant with regard to the outcomes of interest.
I have tried using estat vif after a svy: regression for these, and, as I've seen in other posts, included something for [pw], but it didn't change the outcome.
How should I proceed?
I am writing a paper regarding the relationship between sexual orientation and risk behaviors based on the 2015 Youth Risk Behavior Survey (CDC).
I successfully created a table based on the interaction of each of my dependent variables and the sexual orientation identifying response, but when attempting to run mlogit, I hit on two variables which are omitted due to multicollinearity:
qn11 | -.126644 .0739262 -1.71 0.087 -.2716207 .0183326
qn12 | .0182417 .0329616 0.55 0.580 -.0463992 .0828826
qn29 | -.2315899 .0690746 -3.35 0.001 -.3670522 -.0961276
qn59 | -.1794645 .0439278 -4.09 0.000 -.2656113 -.0933177
q60 | 0 (omitted)
qn63 | 0 (omitted)
qn89 | .0556139 .0397618 1.40 0.162 -.022363 .1335908
qnothhpl | -.0052826 .0420503 -0.13 0.900 -.0877475 .0771823
qndualbc | -.0796317 .066723 -1.19 0.233 -.2104822 .0512188
qnbcnone | -.0852495 .0521206 -1.64 0.102 -.1874633 .0169643
This output was created with the commands:
Code:
regress sexid age male qn9 qn11 qn12 qn29 qn59 q60 qn63 qn89 qnothhpl qndualbc qnbcnone black hisplat other
I have tried using estat vif after a svy: regression for these, and, as I've seen in other posts, included something for [pw], but it didn't change the outcome.
How should I proceed?
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