Automatic Item Generation and Validation via Network-Integrated Evaluation

Automated psychological scale development and structural validation using large language models (LLMs) and network psychometric methods. Implements the AI-GENIE framework (Automatic Item Generation and Validation via Network-Integrated Evaluation) to generate candidate items, compute embedding representations, and estimate dimensional structure using Exploratory Graph Analysis (EGA). Item quality is evaluated using Unique Variable Analysis to identify redundant items and Bootstrap EGA to assess item and dimension stability. Supports both fully automated item generation and analysis of user-provided item sets, facilitating efficient, theory-informed measurement development prior to empirical data collection.


Reference manual

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install.packages("AIGENIE")

2.1.2 by Hudson Golino, a month ago


https://laralee.github.io/AIGENIE/, https://github.com/laralee/AIGENIE


Report a bug at https://github.com/laralee/AIGENIE/issues


Browse source code at https://github.com/cran/AIGENIE


Authors: Lara Russell-Lasalandra [aut, cph] (ORCID: , Alexander Christensen [aut, cph] (ORCID: , Hudson Golino [aut, cre, cph] (ORCID:


Documentation:   PDF Manual  


AGPL (>= 3) license


Imports reticulate, ggplot2, igraph, patchwork, jsonlite

Depends on EGAnet

Suggests testthat, tictoc, knitr, rmarkdown


See at CRAN