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Archivio (CaSty 2.4 - executable, source code, user manual)
Licenza: GNU Public License v.3 (GPL 3) Download (672MB) |
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Archivio (Files used to produce the examples presented in the CaSty 2.4 user manual)
Licenza: Creative Commons: Attribuzione 4.0(CC BY 4.0) Download (85kB) |
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Archivio (Examples of CaSty 2.4 use cases. Files used to produce the elaborations presented in the article: Scappini, E. (2021) in Sociological Methodology, Vol. 51(1), 166–187, DOI 10.1177/0081175020927438)
Licenza: Creative Commons: Attribuzione 4.0(CC BY 4.0) Download (63kB) |
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Archivio (Examples of CaSty 2.4 use cases. Files used to produce the elaborations presented in the article: Scappini, E. (2025) in Methodology, Vol. 21(3), 197–219, DOI 10.5964/meth.13215)
Licenza: Creative Commons: Attribuzione 4.0(CC BY 4.0) Download (83kB) |
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Archivio (Examples of CaSty 2.4 use cases. Files used to produce the elaborations presented in the article: Scappini, E. (2026). Structural bias in stylized items with point-valued categories: A calibrated approach. (Manuscript under decision))
Licenza: Creative Commons: Attribuzione 4.0(CC BY 4.0) Download (289kB) |
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Documento di testo(rtf) (CaSty 2.4 - software and data README file)
Licenza: Creative Commons: Attribuzione 4.0(CC BY 4.0) Download (97kB) |
Abstract
CaSty is a Python-based software tool for calibrating stylized survey items with grouped or point-valued response categories. It addresses two related problems: the direct calibration of stylized items that may generate structural distortion, and the calibration of stylized questionnaire data using diary-based reference values. Version 2.4 revises the calculation procedures and data-checking routines and introduces the computation of the Structural Bias Component (SBC). The program is controlled through a plain-text input file and produces a structured Excel workbook and a log file. CaSty implements four calibration models, reports cumulative or retro-cumulative calibrated estimates, and provides graphical outputs, checked data, and diagnostics such as the Error Index and SBC. CaSty is intended for survey researchers who need a transparent and reproducible workflow for improving the quantitative interpretation of stylized survey measures.


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