JuliaPsychometrics Organization Stats:
The aim of the JuliaPsychometrics organization is to provide a consistent and coherent ecosystem for psychometric modeling. It offers a collection of performance optimized tools:
- unified APIs to provide a "common ground" for a consistent experience in developing and applying tools for psychometric modeling
- implementation of concrete psychometric methods for developing, estimating and testing a wide range of models (e.g. Rasch Models)
- pre-defined, yet highly extendable visualization packages providing publication-ready plots (e.g. expected score plots, ICCs, IICs)
The currently developed packages are:
- AbstractItemResponseModels.jl: A package providing an abstract interface for item response modeling.
- RaschModels.jl: A modeling package combining frequentist an bayesian methods for estimating and testing the following item response models: Rasch Model and LLTM for dichotomous data, (Linear) Partial Credit and (Linear) Rating Scale Model for polytomous data.
- ItemResponsePlots.jl: A plotting package for item response models based on Makie.jl. Includes item characteristic curves, item information curves, expected score plots, and test information plots.
JuliaPsychometrics was originally created and is now managed by Tobias Alfers and Philipp Gewessler.
JuliaPsychometrics is an open source project (developed under the MIT license). If you are interested in contributing to our ecosystem please do get in touch with one of us. You can contribute by opening Github issues or implementing additional features on your own before making an adequate and comprehensible pull request.
