In terms of my field of rehabilitation, where our outcomes are overwhelmingly true ordinal variables improperly treated using parametric approaches, I’d say your method opens up a large realm of positive possibilities:
- Retrospective and prospective meta-analyses are now permissible. I don’t think many people have thought about the ramifications of the problems that this uncritical acceptance of linear methods on ordinal data by primary researchers hampers the attempts by meta-analysts to synthesize the results.
I think I can prove formally that MA’s of ordinal outcomes using parametric approaches (ie. meta-analyses of treatment for low back pain using average pain scores as an outcome) provide essentially 0 information – we can’t even trust the reported sign of the MA. But that is for another post.
- For fields that will be constrained by small samples, the ability of proportional odds models to adjust for covariates might permit the use of a prospective synthesis of N-of-1 studies to simulate a more traditional parallel group study.
Please correct me if I’ve made an error in any of the above assertions.