Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Graded Response Model #82

Open
mathmonstergo opened this issue Jan 7, 2025 · 2 comments
Open

Graded Response Model #82

mathmonstergo opened this issue Jan 7, 2025 · 2 comments

Comments

@mathmonstergo
Copy link

Great project! By the way, have you ever considered implementing the Graded Response Model (Polytomous IRT)?

@jplalor
Copy link
Collaborator

jplalor commented Jan 10, 2025

Thanks! Yes, we've thought about the graded response model but just haven't had the bandwidth to implement it. I'd be very open to reviewing a PR if someone wants to take a pass at it!

@zouharvi
Copy link
Contributor

zouharvi commented Jan 14, 2025

We do have a continuous scoring model here https://github.com/zouharvi/py-irt that's being used in the subset2evaluate package.

Essentially instead of predicting the binary outcome, it predicts a score in [0, 1]. Maybe that'd suit your needs, @mathmonstergo?

The reason why I didn't file a PR for it just yet is because of some technicalities. Technically the output should be a Beta distribution but for us the Normal distribution worked better for which we don't have a good explanation. The way it works is that instead of predicting the Bernoulli p and compare with 0 or 1 coming from the observations, we predict the Normal distribution mean and compare it with the observed score.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

3 participants