An R package for estimating generalized additive mixed models with latent variables
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Updated
Apr 8, 2024 - C++
An R package for estimating generalized additive mixed models with latent variables
Estimate the Deterministic Input, Noisy "And" Gate (DINA) cognitive diagnostic model parameters using the Gibbs sampler described by Culpepper (2015) <doi:10.3102/1076998615595403>.
Jointly model the accuracy of cognitive responses and item choices within a bayesian hierarchical framework as described by Culpepper and Balamuta (2015) <doi:10.1007/s11336-015-9484-7>. In addition, the package contains the datasets used within the analysis of the paper.
Estimate Barton & Lord's (1981) <doi:10.1002/j.2333-8504.1981.tb01255.x> four parameter IRT model with lower and upper asymptotes using Bayesian formulation described by Culpepper (2016) <doi:10.1007/s11336-015-9477-6>.
Perform a Bayesian estimation of the Exploratory reduced Reparameterized Unified Model (errum) described by Culpepper and Chen (2018) <doi:10.3102/1076998618791306>.
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