GMLTM - Generalized Multicomponent Latent Trait Model for Diagnosis

Provides Bayesian estimation of Item Response Theory models that decompose item difficulty into cognitive operations or rules. Implements the Linear Logistic Test Model (LLTM; Fischer (1973) <doi:10.1016/0001-6918(73)90003-6>), the Multicomponent Latent Trait Model for Diagnosis (MLTM-D; Embretson and Yang (2013) <doi:10.1007/s11336-012-9296-y>), and the Generalized Multicomponent Latent Trait Model for Diagnosis (GMLTM-D; Ramirez et al. (2024) <doi:10.3390/jintelligence12070067>). All models are estimated via Hamiltonian Monte Carlo using 'Stan' through the 'rstan' interface. Includes tools for model validation, reliability estimation, and visualization of item characteristic curves. Supports user-defined prior distributions for all model parameters.