Ordinal Cumulative Logit Hurdle Model (OCLHM)
This is a code repository for the Journal of Research on Educational Effectiveness (JREE) article titled "Addressing Uncodable Behaviors: a Bayesian Ordinal Mixture Model Applied to a Mathematics Learning Trajectory Teaching Experiment" (2024) by P Chernyavskiy, TS Kutaka, C Keeter, J Sarama, and DH Clements. Link to published article: coming soon
A short guide to implementation is contained in the article's Appendix. The contents of this repository are as follows:
- oclhm_function_08022023.R (Main estimation and fitted values functions)
- Length_meas_reanalysis_08102023.R (R code used for analysis)
All code is based on the initial version created by @CarsonLKeeter (https://github.com/CarsonLKeeter/Learning-Trajectories-Length-Measurement-Analysis-2021).
Regrettably, we cannot yet provide the data used in the article due to a mandatory embargo. We intend to make the data available when the embargo period ends.
An earlier version of this article was uploaded as a preprint to PsyArXiv: 10.31234/osf.io/p4qjf.