nca.example

<p>This data set has Individualism and Risk taking	as conditions,
and Innovation performance as the output for 28 countries.</p>

datasets

Performs a Necessary Condition Analysis (NCA). (Dul, J. 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>.
NCA identifies necessary (but not sufficient) conditions in datasets, where x causes (e.g. precedes) y. Instead of drawing a regression line ''through the middle of the data'' in an xy-plot, NCA draws the ceiling line. The ceiling line y = f(x) separates the area with observations from the area without observations.
(Nearly) all observations are below the ceiling line: y <= f(x). The empty zone is in the upper left hand corner of the xy-plot (with the convention that the x-axis is ''horizontal'' and the y-axis is ''vertical'' and that values increase ''upwards'' and ''to the right''). The ceiling line is a (piecewise) linear non-decreasing line: a linear step function or a straight line. It indicates which level of x (e.g., an effort, a characteristic) is necessary but not sufficient for a (desired or undesired) level of y (e.g., good performance or disease). A quick start guide for using this package can be found here: <https://repub.eur.nl/pub/78323/> or <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2624981>.

Govert Buijs

Necessary Condition Analysis

Jan Dul

nca.example function

<p>A matrix containing 28 observations, incl. headers and row names.</p>

nca.example: NCA example data with 2 conditions and 1 output

Description

Usage

Arguments

Format