Necessary Condition Analysis (NCA) allows researchers and practitioners to identify necessary (but not sufficient) conditions in data sets.
This is a Python implementation of the original NCA R package including only the basic functionality of NCA for users who want to have a native implementation in Python.
Please see the getting started jupyter notebook for a complete example of how to use the Necessary Condition Analysis in Python package.
Please cite the NCA package as:
Chavelas, R. (2024). Necessary Condition Analysis in Python.
This package is based on:
Dul, J. (2016). Necessary Condition Analysis (NCA): Logic and Methodology of “Necessary but Not Sufficient” Causality. Organizational Research Methods, 19(1), 10-52. https://doi.org/10.1177/1094428115584005
and
Dul, Jan, Necessary Condition Analysis (NCA) with R (Version 4.0.0): A Quick Start Guide (February 16, 2024). Based on: Dul, J. (2016) "Necessary Condition Analysis (NCA): Logic and Methodology of 'Necessary but Not Sufficient' Causality." Organizational Research Methods 19(1), 10-52; Dul, J. (2020) "Conducting Necessary Condition Analysis" SAGE Publications ISBN: 9781526460141, Available at SSRN: https://ssrn.com/abstract=2624981_
For general information about NCA see: http://www.erim.nl/nca