Schedule for categorical outcome estimation

As soon as we give Tim a bit of breathing space, it should not take too long. There's a bit of a trade-off depending on whether we go for the joint continuous and ordinal FIML straight out of the box, or do just ordinal first, then add - with some loss of efficiency - the joint part. Given the proximity of open beta, I'd say we should go for straight ordinal to begin with, and have people beat on it while coding the joint piece. All depends on Tim's other responsibilities over the next couple of months - afaik he has everything necessary outlined by me, but will likely want a bit of fine tuning here and there. An option for specifying what the highest category is (not necessarily what is observed in the dataset) are very important. They're critical for ML estimation of factor scores, for example.

There're still open questions about both the user experience and the front-end/back-end interface for ordinal models. I have most of a first back-end implementation for pure-ordinal estimation already prepared, so once the specifications are ironed out, it's just a matter of implementing those, generating some tests, and debugging.

We need to define how thresholds are represented in the front end and how they're passed to the back-end, as well as answering questions about ordinal levels that don't appear in the data.

I'm with Mike in recommending we start with a pure ordinal function. The joint ordinal/continuous estimation can follow afterwards.