# ------------------------------------------------ # CITATION.cff file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # ------------------------------------------------ cff-version: 1.2.0 message: 'To cite package "IRTC" in publications use:' type: software license: GPL-2.0-or-later title: 'IRTC: Marginal Maximum Likelihood Estimation for Item Response Models' version: 1.1.2 doi: 10.32614/CRAN.package.IRTC abstract: '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) .' authors: - family-names: Ma given-names: Kunxiang email: makunxiang@weiandata.com repository: https://weiandata.r-universe.dev repository-code: https://github.com/weiandata/IRTC commit: e44f0bd4d931f90ffcc404dd300305349fee134c url: https://github.com/weiandata/IRTC date-released: '2026-08-27' contact: - family-names: Ma given-names: Kunxiang email: makunxiang@weiandata.com