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Necessary condition analysis (NCA) is a research approach and tool employed to discern "necessary conditions" within datasets.[1] These indispensable conditions stand as pivotal determinants of particular outcomes, wherein the absence of such conditions ensures the absence of the intended result. For example, the admission of a student into a Ph.D. program necessitates a prior degree; the progression of AIDS necessitates the presence of HIV; and organizational change necessitates communication.
The absence these conditions guarantees the outcome cannot occur, and no other condition can overcome the lack of this condition. Further, necessary conditions are not always sufficient. For example, AIDS necessitates HIV, but HIV does not always cause AIDS. In such instances, the condition demonstrates its necessity but lacks sufficiency. NCA seeks to use statistical methods to test for such conditions.
^Dul, Jan (January 2016). "Necessary Condition Analysis (NCA): Logic and Methodology of "Necessary but Not Sufficient" Causality". Organizational Research Methods. 19 (1): 10–52. doi:10.1177/1094428115584005. hdl:1765/90024. ISSN 1094-4281. S2CID 54590079.
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