ThSQCA: Threshold-Sweep Qualitative Comparative Analysis in R

Statistics > Methodology [Submitted on 16 Jan 2026 (v1), last revised 30 May 2026 (this version, v4)] Title:ThSQCA: Threshold-Sweep Qualitative Comparative Analysis in R View PDF HTML (experimental)Abstract:Qualitative Comparative Analysis (QCA) requires researchers to choose calibration and dichotomization thresholds, and these choices can substantially affect truth tables, minimization, and resulting solution formulas. Despite this dependency, threshold sensitivity is often examined only in an ad hoc manner because repeated analyses are time-intensive and error-prone. We present ThSQCA, an R package that automates threshold-sweep analyses by treating thresholds as explicit analytical variables. It provides four sweep functions (otSweep, ctSweepS, ctSweepM, dtSweep) to explore outcome thresholds, single-condition thresholds, multi-condition threshold grids, and joint outcome-condition threshold spaces, respectively. ThSQCA integrates with the established CRAN package QCA for truth table construction and Boolean minimization, while returning structured S3 objects with consistent print/summary methods and optional detailed results. The package also supports automated Markdown report generation and configuration-chart output to facilitate reproducible documentation of cross-threshold results. Submission history From: Yuki Toyoda [view email][v1] Fri, 16 Jan 2026 12:19:01 UTC (227 KB) [v2] Mon, 19 Jan 2026 03:19:30 UTC (227 KB) [v3] Wed, 18 Feb 2026 07:42:40 UTC (230 KB) [v4] Sat, 30 May 2026 12:16:13 UTC (231 KB) References & Citations Loading... Bibliographic and Citation Tools Bibliographic Explorer (What is the Explorer?) Connected Papers (What is Connected Papers?) Litmaps (What is Litmaps?) scite Smart Citations (What are Smart Citations?) Code, Data and Media Associated with this Article alphaXiv (What is alphaXiv?) CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub (What is DagsHub?) Gotit.pub (What is GotitPub?) Hugging Face (What is Huggingface?) ScienceCast (What is ScienceCast?) Demos Recommenders and Search Tools Influence Flower (What are Influence Flowers?) CORE Recommender (What is CORE?) arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.