Multidimensional item response theory

Code that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. **Superseded by the models-by-example repo**.

Computerized Adaptive Testing Simulator

The Model Zoo of Cognitive Diagnosis Models, including classic Item Response Ranking (IRT), Multidimensional Item Response Ranking (MIRT), Deterministic Input, Noisy "And" model(DINA), and advanced Fuzzy Cognitive Diagnosis Framework (FuzzyCDF), Neural Cognitive Diagnosis Model (NCDM) and Item Response Ranking framework (IRR).

An Item Response Theory Package for Python

A python library of IRT algorithm

A Java library for classical test theory, item response theory, factor analysis, and other measurement techniques. It provide tools commonly used in psychometrics and operational testing programs.

Computerized Adaptive Testing with Multidimensional Item Response Theory

idealstan offers item-response theory (IRT) ideal-point estimation for binary, ordinal, counts and continuous responses with time-varying and missing-data inference. Latent space model also included. Full and approximate Bayesian sampling with 'Stan' (www.mc-stan.org).

◽ <- ⚪ Structural Equation Modeling from a broader context.

IRT ideal point models in R using Stan

Nefit / Buderus iRT protocol encoder / decoder for ESP8266

Bayesian IRT submodule for GIRTH

JavaScript implementation of functions related to Item Response Theory

Dynamic estimation of group-level opinion in R

Estimate the Deterministic Input, Noisy "And" Gate (DINA) cognitive diagnostic model parameters using the Gibbs sampler described by Culpepper (2015) <doi:10.3102/1076998615595403>.

IR-Tree Modeling in mirt, Mplus, or TAM

Kot is a basic toolkit for getting started with computerised adaptive testing (CAT) in Ruby.

Automated Test Assembly with Julia

IRT models using various Bayesian methods