Theory-Driven Item Response Theory (IRT) Models
learned correlations
get_lambdas
Geweke Convergence
irt_m
irt_vis
M_constrained_irt
Methodological Codes
Mean Squared Error
pair_gen_anchors
Standardize Theta
Average Thetas
Theta Lambda Traceplots
IRT-M is a semi-supervised approach based on Bayesian Item Response Theory that produces theoretically identified underlying dimensions from input data and a constraints matrix. The methodology is fully described in 'Morucci et al. (2024), "Measurement That Matches Theory: Theory-Driven Identification in Item Response Theory Models"'. Details are available at <https://www.cambridge.org/core/journals/american-political-science-review/article/measurement-that-matches-theory-theorydriven-identification-in-item-response-theory-models/395DA1DFE3DCD7B866DC053D7554A30B>.