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type: software
license: GPL-3.0-only
title: 'birtRcpp: BIvariate Response Time Modeling with ''Rcpp'''
version: 0.3.0
abstract: 'Item response and response time models fitted from their full conditionals.
  A built-in model is chosen with ecm(data, model = ...) or gibbs(data, model = ...):
  the two-parameter logistic model, alone or with log-normal response times (van der
  Linden, 2007, <https://doi.org/10.1007/s11336-006-1478-z>), latent regressions of
  ability and speed, cross-relations between ability and the log response times, and
  their quantile (asymmetric Laplace) versions. The main estimator is ECM (ecm();
  Meng and Rubin, 1993, <https://doi.org/10.1093/biomet/80.2.267>): one conditional
  maximization per block of parameters, Polya-Gamma bounds for logistic likelihoods
  (Polson, Scott and Windle, 2013, <https://doi.org/10.1080/01621459.2013.829001>),
  adaptive or Bock-Aitkin quadrature (Bock and Aitkin, 1981, <https://doi.org/10.1007/BF02293801>)
  with normal-linear latent variables integrated exactly, and Louis'' standard errors;
  quantile models maximize the asymmetric Laplace working likelihood, with sandwich
  standard errors. The same steps drive Gibbs sampling (gibbs(); conjugate updates
  and Metropolis-adjusted Langevin steps), with samplers in C++ (''RcppArmadillo'')
  that port the ''Julia'' package ''ExtendedRtIrtModeling.jl'' (its function names
  are kept as aliases). Both estimators have a check: check_ecm(), and check_sampler()
  with the Geweke (2004, <https://doi.org/10.1198/016214504000001132>) test and simulation-based
  calibration. equations() and algorithm() write out the model and every step, before
  or after fitting.'
authors:
- family-names: Tsai
  given-names: Jie-Wen
  email: tsai.jiewen@gmail.com
repository: https://jiewentsai.r-universe.dev
repository-code: https://github.com/jiewenTsai/birtRcpp
commit: fa2e3dc270d1bc47d98979efcbfcb071f010918a
url: https://github.com/jiewenTsai/birtExamples
date-released: '2026-10-29'
contact:
- family-names: Tsai
  given-names: Jie-Wen
  email: tsai.jiewen@gmail.com