I am looking at the relationship between housing characteristics and a health outcome. To make the example simple, I have data for a continuous predictor (exposure) collected from 1000 homes and health outcomes S (a binary outcome) for 2000 people (1000 couples) living in each of those homes. I would like to look at the relationship between S and E using binary logistic regression. Apart from sharing the same exposure, there is no mechanistic reason to believe that status of partner 1 in the couple can affect the status of partner 2 e.g. its not a transmissible disease etc.
Can I do an ordinary logistic regression? Or must I take into account the fact that people are clustered within homes? If so, why? What syntax would be appropriate in Stata, xtlogit with i(house)? or some kind of xtmixed?
Many thanks
Best Answer
For me, this sounds like a (more or less typical) dyadic data set and I would definitely control for dyadic dependencies (i.e. at the houshold level) via multilevel/structural equation modeling.
David Kenny owns a great website on Dyadic Analysis. He also is co-author of a book on Dyadic Data Analysis that is highly recommanded.
Since you seem to use Stata, I would use the
xtmelogitcommand (see here for more information).