# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "mstATA" in publications use:'
type: software
license: MIT
title: 'mstATA: Automated Test Assembly for Multistage Tests Using Mixed-Integer Linear
  Programming'
version: 0.1.0
doi: 10.32614/CRAN.package.mstATA
abstract: Provides a suite of mixed-integer linear programming (MILP) model builders
  and solvers—including 'Gurobi', 'HiGHS', 'Symphony', 'GNU Linear Programming Kit
  (GLPK)', and 'lpSolve'—for automated test assembly (ATA) in multistage testing (MST).
  Offers filtering of decision variables through item–module eligibility and the application
  of explicit bounds to simplify the MILP model and accelerate the optimization process.
  Supports bottom up, top down, and hybrid assembly strategies; enemy-item and enemy-stimulus
  exclusions; stimulus all in/all out or partial selection; anchor item/stimulus specification;
  and item exposure control. Accommodates both single-objective and multi-objective
  optimization ('weighted sum', 'maximin', 'capped maximin', 'minimax', and 'goal
  programming'). Enables simultaneous assembly of multiple panels with item and stimulus
  content balancing and exposure control. Provides analytical evaluation of assembled
  MST performance within seconds. Includes tools for diagnosing infeasible optimization
  models by systematically identifying sources of infeasibility and reformulating
  models with slack variables to restore feasibility.Methods implemented in this package
  build on established work in optimal test assembly (van der Linden, 2005 <https://doi.org/10.1007/0-387-29054-0>),
  item-set constrained test assembly (van der Linden, 2000 <https://doi.org/10.1177/01466210022031697>),
  hybrid assembly (Xiong, 2018 <https://doi.org/10.1177/0146621618762739>), recursion-based
  analytic methods (Lim et al., 2021 <https://doi.org/10.1111/jedm.12276>), and classification
  evaluation (Rudner, 2000 <https://doi.org/10.7275/an9m-2035>; Rudner, 2005 <https://doi.org/10.7275/56a5-6b14>).
authors:
- family-names: Chen
  given-names: Hong
  email: hongchen030@gmail.com
repository: https://hongchen030.r-universe.dev
repository-code: https://github.com/Hongchen030/mstATA
commit: 4c6ec22caba582b3f3b6d82559a7fd52b4f6a3cf
url: https://github.com/Hongchen030/mstATA
date-released: '2026-05-12'
contact:
- family-names: Chen
  given-names: Hong
  email: hongchen030@gmail.com