Necessary Condition Analysis (NCA) with R (Version 3.1.0): A Quick Start Guide

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 and: Dul, J. (2020) "Conducting Necessary Condition Analysis" SAGE Publications ISBN: 9781526460141

25 Pages Posted: 30 Jun 2015 Last revised: 2 Mar 2021

See all articles by Jan Dul

Jan Dul

Erasmus University, Rotterdam School of Management

Date Written: March 2, 2021

Abstract

Necessary Condition Analysis (NCA) is an approach and data analysis technique for identifying necessary conditions in datasets. It can complement traditional regression based data analysis as well as methods like QCA (see the NCA website www.erim.nl/nca for a short introduction to NCA).

Details of the method can be found in:

• 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.

• Dul, J., van der Laan, E., & Kuik, R. (2020). A statistical significance test for Necessary Condition Analysis. Organizational Research Methods, 23(2), 385-395.

Keywords: software, R package, manual, data analysis

JEL Classification: C00, C10, C40, C70, C80, C90, M00

Suggested Citation

Dul, Jan, Necessary Condition Analysis (NCA) with R (Version 3.1.0): A Quick Start Guide (March 2, 2021). 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 and: Dul, J. (2020) "Conducting Necessary Condition Analysis" SAGE Publications ISBN: 9781526460141, Available at SSRN: https://ssrn.com/abstract=2624981

Jan Dul (Contact Author)

Erasmus University, Rotterdam School of Management ( email )

Rotterdam School of Management, Erasmus University
P.O. Box 1738
3000 DR Rotterdam
Netherlands
+31 10 408 1719 (Phone)
+31 10 408 9014 (Fax)

HOME PAGE: http://www.rsm.nl/jdul

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