d.educate

This artificial dataset of macro-sociological factors on high levels of education is from Baumgartner (2009).

datasets

Provides comprehensive functionalities for causal modeling with Coincidence Analysis (CNA), which is a configurational comparative method of causal data analysis that was first introduced in Baumgartner (2009) <doi:10.1177/0049124109339369>, and generalized in Baumgartner & Ambuehl (2018) <doi:10.1017/psrm.2018.45>. CNA is designed to recover INUS-causation from data, which is particularly relevant for analyzing processes featuring conjunctural causation (component causation) and equifinality (alternative causation). CNA is currently the only method for INUS-discovery that allows for multiple effects (outcomes/endogenous factors), meaning it can analyze common-cause and causal chain structures.

Mathias Ambuehl

Causal Modeling with Coincidence Analysis

Michael Baumgartner

Ruedi Epple

Veli-Pekka Parkkinen

Alrik Thiem

d.educate function

The data frame contains 8 rows (cases) and the following 5 columns featuring Boolean factors taking values 1 and 0 only:
<table class="table">
<tr><td>[ , 1]</td><td>U</td><td>existence of strong unions</td></tr>
<tr><td>[ , 2]</td><td>D</td><td>high level of disparity</td></tr>
<tr><td>[ , 3]</td><td>L</td><td>existence of strong left parties</td></tr>
<tr><td>[ , 4]</td><td>G</td><td>high gross national product</td></tr>
<tr><td>[ , 5]</td><td>E</td><td>high level of education</td></tr>
</table>

Format

Artificial data on education levels and left-party strength — d.educate

The data frame contains 8 rows (cases) and the following 5 columns featuring Boolean factors taking values 1 and 0 only:
<table class='table'>
<tr><td>[ , 1]</td><td>U</td><td>existence of strong unions</td></tr>
<tr><td>[ , 2]</td><td>D</td><td>high level of disparity</td></tr>
<tr><td>[ , 3]</td><td>L</td><td>existence of strong left parties</td></tr>
<tr><td>[ , 4]</td><td>G</td><td>high gross national product</td></tr>
<tr><td>[ , 5]</td><td>E</td><td>high level of education</td></tr>
</table>

d.educate: Artificial data on education levels and left-party strength

Description

Usage

Arguments

Format

[ , 1]	U	existence of strong unions
[ , 2]	D	high level of disparity
[ , 3]	L	existence of strong left parties
[ , 4]	G	high gross national product
[ , 5]	E	high level of education