SAEM_IRT

Eugene Geis, Greg Camilli, Stochastic Approximation Estimation Maximization algorithm as applied to an Multidimensional Item Response Theory model of dichotomous and polythomous response data, with a cumulative normal ogive response function.

Keywords: IRT, SAEM, MIRT, 2PNO, 3PNO

Thesis: https://arxiv.org/abs/1912.12755

Directions to get started

The best way to create an environment for this code is to create a new R-project, cloning this github repo.

1. In RStudio, choose: File > New Project > Version Control > Git

2. The repository URL: https://github.com/genobobeno/SAEM_IRT i) Project directory will auto-fill. ii) Your choice of subdirectory is your prerogative.

3. Once your session is initiated, open the "START_HERE.Rmd" file to follow the tutorial. If you're most interested in the polytomous fits, open the "START_HERE_POLY_DEMO.Rmd" file.

Hope you enjoy!!

Distributed under the AGPL-3.0 License

This is the SAEM-IRT Code, used to simulate and estimate multi-dimensional Item Response Theory models using Stochastic Approximation Expectation Maximization with Gibbs Sampling.

Copyright (C) 2019  Eugene J. Geis

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or (at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License
along with this program.  If not, see http://www.gnu.org/licenses/ and
https://opensource.org/licenses/AGPL-3.0