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Bayesian IRT submodule for GIRTH

Home Page: https://eribean.github.io/girth/

License: MIT License

Python 100.00%
bayesian irt item-response-theory monte-carlo

girth_mcmc's Introduction

Ryan C. Sanchez

I am a data scientist / engineer, psychometrician, and fullstack enthusiast. I focus on providing open-source solutions and developing novel algorithms to benefit the education domain.

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Repositories and Projects

GIRTH: An Item Response Theory Package
PyPI - Downloads

GIRTH MCMC: A Markov Chain Monte Carlo add on for Girth
PyPI - Downloads

RyStats: A collection of inferential statistical functions.
PyPI - Downloads

GoFactr: Online Statistical Web Application.
Graphical User Interface for commonly used Inferential Statistics

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girth_mcmc's Issues

Inverted results for difficulty compared to mirt

Just did a quick comparison for a 2PL model on a dichotomous dataset between the R package mirt and girth_mcmc. Are there any specific reasons that the scale for the difficulty values are inverted (for lack of a better term)?

girth_vs_mirt_1

Add Graded Unfolding Model

The graded unfolding model is an ideal point IRT model and an extension of the PCM #9. The framework for this model reuses a lot from the partial credit model and should be straightforward to implement. Not so straightforward is obtaining good initial estimates for item locations. The polarity ambiguity of item locations can cause posterior methods to diverge since to stable points will exist....

Investigate GPU support

Future PYMC3 is going to incorporate JAX and will bring with it better GPU support, keep an eye on this.

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