hmcdm - Hidden Markov Cognitive Diagnosis Models for Learning
Fitting hidden Markov models of learning under the cognitive diagnosis framework. The estimation of the hidden Markov diagnostic classification model, the first order hidden Markov model, the reduced-reparameterized unified learning model, and the joint learning model for responses and response times.
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cognitive-diagnostic-modelspsychometricsrcpprcpparmadilloopenblascppopenmp
6.28 score 8 stars 20 scripts 467 downloads
cIRT - Choice Item Response Theory
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.
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armadillobayesianchoicecognitive-diagnostic-modelsgibbs-samplingitem-response-theoryrcpparmadilloopenblascppopenmp
5.35 score 4 stars 37 scripts 403 downloads
simcdm - Simulate Cognitive Diagnostic Model ('CDM') Data
Provides efficient R and 'C++' routines to simulate cognitive diagnostic model data for Deterministic Input, Noisy "And" Gate ('DINA') and reduced Reparameterized Unified Model ('rRUM') from Culpepper and Hudson (2017) <doi: 10.1177/0146621617707511>, Culpepper (2015) <doi:10.3102/1076998615595403>, and de la Torre (2009) <doi:10.3102/1076998607309474>.
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cognitive-diagnostic-modelspsychometricsrcpprcpparmadillosimulationopenblascpp
5.01 score 2 dependents 17 scripts 436 downloads
pg - Polya Gamma Distribution Sampler
Provides access to a series of highly performant random distribution samplers for the Polya Gamma Distribution as described by Polson, Scott, and Windle (2013) <arXiv:1205.0310> using either 'C++' headers for 'Rcpp' or 'RcppArmadillo' and 'R'. The 'C++' header approach was developed to enable computations in Balamuta (2021) <https://www.ideals.illinois.edu/items/121209>.
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cpp
4.13 score 2 stars 3 dependents 15 scripts 263 downloads
edmdata - Data Sets for Psychometric Modeling
Collection of data sets from various assessments that can be used to evaluate psychometric models. These data sets have been analyzed in the following papers that introduced new methodology as part of the application section: Jimenez, A., Balamuta, J. J., & Culpepper, S. A. (2023) <doi:10.1111/bmsp.12307>, Culpepper, S. A., & Balamuta, J. J. (2021) <doi:10.1080/00273171.2021.1985949>, Yinghan Chen et al. (2021) <doi:10.1007/s11336-021-09750-9>, Yinyin Chen et al. (2020) <doi:10.1007/s11336-019-09693-2>, Culpepper, S. A. (2019a) <doi:10.1007/s11336-019-09683-4>, Culpepper, S. A. (2019b) <doi:10.1007/s11336-018-9643-8>, Culpepper, S. A., & Chen, Y. (2019) <doi:10.3102/1076998618791306>, Culpepper, S. A., & Balamuta, J. J. (2017) <doi:10.1007/s11336-015-9484-7>, and Culpepper, S. A. (2015) <doi:10.3102/1076998615595403>.
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cognitive-diagnostic-modelsdataedm
4.02 score 7 stars 1 dependents 8 scripts 615 downloads
dina - Bayesian Estimation of DINA Model
Estimate the Deterministic Input, Noisy "And" Gate (DINA) cognitive diagnostic model parameters using the Gibbs sampler described by Culpepper (2015) <doi:10.3102/1076998615595403>.
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armadillobayesiangibbs-samplerirtitem-response-theorypsychometricsrcpprcpparmadilloopenblascpp
3.93 score 17 stars 3 scripts 417 downloads
edina - Bayesian Estimation of an Exploratory Deterministic Input, Noisy and Gate Model
Perform a Bayesian estimation of the exploratory deterministic input, noisy and gate (EDINA) cognitive diagnostic model described by Chen et al. (2018) <doi:10.1007/s11336-017-9579-4>.
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cognitive-diagnostic-modelscppdinaecdmitem-response-theorypsychometricsrcpparmadilloopenblascpp
3.18 score 3 stars 1 scripts 395 downloadsslcm - Sparse Latent Class Model for Cognitive Diagnosis
Perform a Bayesian estimation of the exploratory Sparse Latent Class Model for Binary Data described by Chen, Y., Culpepper, S. A., and Liang, F. (2020) <doi:10.1007/s11336-019-09693-2>.
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latent-class-modelpsychometricsrcpparmadillosparseopenblascppopenmp
3.00 score 2 stars 2 scripts 319 downloads
iccbeta - Multilevel Model Intraclass Correlation for Slope Heterogeneity
A function and vignettes for computing an intraclass correlation described in Aguinis & Culpepper (2015) <doi:10.1177/1094428114563618>. This package quantifies the share of variance in a dependent variable that is attributed to group heterogeneity in slopes.
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armadillocorrelationintraclass-correlationrcpprcpparmadilloopenblascpp
3.00 score 2 stars 8 scripts 466 downloads
rrum - Bayesian Estimation of the Reduced Reparameterized Unified Model with Gibbs Sampling
Implementation of Gibbs sampling algorithm for Bayesian Estimation of the Reduced Reparameterized Unified Model ('rrum'), described by Culpepper and Hudson (2017) <doi: 10.1177/0146621617707511>.
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armadillocdmcognitive-diagnostic-modelsgibbs-sampling-algorithmpsychometricsrcpparmadillorrumopenblascppopenmp
2.70 score 3 scripts 449 downloads
ohoegdm - Ordinal Higher-Order Exploratory General Diagnostic Model for Polytomous Data
Perform a Bayesian estimation of the ordinal exploratory Higher-order General Diagnostic Model (OHOEGDM) for Polytomous Data described by Culpepper, S. A. and Balamuta, J. J. (2021) <doi:10.1080/00273171.2021.1985949>.
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diagnostic-modelexploratory-diagnostic-modelspsychometricsopenblascppopenmp
2.70 score 1 scripts 344 downloads
errum - Exploratory Reduced Reparameterized Unified Model Estimation
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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cognitive-diagnostic-modelingcppecdmitem-response-theorypsychometricsrcpparmadillorrumopenblascppopenmp
2.70 score 1 scripts 376 downloads