A fairly innocuous question -- how best to interpret odds ratio results from a xtlogit model estimation -- unleashed a torrent of commentary on the StataList (click here). As this is a not uncommon model used in many ELS papers, I thought others may benefit from the (extended) discussion.
One of the (many) points that garners attention includes the numeric range for odds ratios: "There is no reason an odds ratio can't be greater than 2. On the other hand, an odds ratio can never be less than 0. The possible values for an odds ratio range from 0 to + infinity. And the interpretation does not depend on the size of the odds ratio. In your case, assuming the predictor is dichotomous, it means that the odds of a positive outcome when the predictor is 1 is 2.46 times the odds of a positive outcome when the predictor is 0. If the predictor is continuous, it means that a unit difference in the value of the predictor is associated with the odds of a positive outcome increasing by a factor of 2.46."
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