Package: IRTC
Type: Package
Title: Marginal Maximum Likelihood Estimation for Item Response Models
Version: 1.1.1
Date: 2026-07-17
Authors@R: c(
    person("Kunxiang", "Ma", role = c("aut", "cre"),
           email = "makunxiang@weiandata.com"),
    person("WEIAN DATA TECH (Beijing) Co., Ltd.",
           role = c("cph", "fnd"), email = "contact@weiandata.com"))
Description: Self-contained marginal maximum likelihood (MML) estimation for
    unidimensional and multidimensional item response models, including the
    Rasch / one-parameter logistic, partial credit, rating scale, two-parameter
    logistic and generalised partial credit models, with latent regression,
    multiple groups and case weights. A parallelised, dimension-factorised
    streaming estimation engine supports large between-item (simple-structure)
    multidimensional models with bounded memory and an opt-in controlled-accuracy
    quadrature mode that reports a measured approximation error. A usability
    layer serves non-specialists and automated pipelines: one-stop estimation
    from common file formats ('Excel', delimited text, 'SPSS', 'Stata', 'SAS')
    with automatic cleaning and answer-key scoring, pre-estimation data checks,
    classical item statistics and item fit, plain-language quality ratings,
    bilingual (English/Chinese) output, spreadsheet exports for item banking and
    cross-year linking, audience-specific 'Word'/'HTML' reports, and
    machine-readable results with structured error conditions. Methods follow
    Adams, Wilson and Wang (1997) <doi:10.1177/0146621697211001>.
License: GPL (>= 2)
Copyright: See file inst/COPYRIGHTS.
URL: https://github.com/weiandata/IRTC
BugReports: https://github.com/weiandata/IRTC/issues
Depends: R (>= 3.5.0)
Imports: Rcpp, stats, utils, methods, MASS, tools, graphics, grDevices
Suggests: testthat (>= 3.0.0), mvtnorm, sfsmisc, readxl, writexl,
        haven, openxlsx, officer, jsonlite
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-07-17 09:53:17 UTC; makunxiang
Author: Kunxiang Ma [aut, cre],
  WEIAN DATA TECH (Beijing) Co., Ltd. [cph, fnd]
Maintainer: Kunxiang Ma <makunxiang@weiandata.com>
Repository: CRAN
Date/Publication: 2026-07-24 10:30:22 UTC
Built: R 4.6.1; x86_64-w64-mingw32; 2026-09-02 02:43:15 UTC; windows
Archs: x64
