Basic censored data models #2
Description
When we started this repo, the main purpose was to work on those StackExchange examples we found and get them to work, and have them documented so we understand what they are doing. For the next task, we'll focus on those models and some other basic models. Each example should include a writeup with a description of the example, working Stan code, the likelihood model, and the interpretation of the results.
- Model with one censored predictor and an uncensored, normally-distributed outcome
- There appeared to be two ways to do that one, can we get both of them working?
- Model with a censored, normally-distributed latent outcome and a completely observed predictor.
- Are there two ways to do this one also? Or do we have to update the target likelihood always?
- Model where both the outcome and predictor are censored.