sample_data

A small artificial dataset with variables:<dl>
<dt>Y</dt>
<dd>Outcome (numeric)</dd><dt>X1</dt>
<dd>Condition 1</dd><dt>X2</dt>
<dd>Condition 2</dd><dt>X3</dt>
<dd>Condition 3</dd>
</dl>

datasets

Provides threshold sweep methods for Qualitative Comparative
Analysis (QCA). Implements Condition Threshold Sweep-Single (CTS-S),
Condition Threshold Sweep-Multiple (CTS-M), Outcome Threshold Sweep (OTS),
and Dual Threshold Sweep (DTS) for systematic exploration of threshold
calibration effects on crisp-set QCA results. These methods extend
traditional robustness approaches by treating threshold variation as an
exploratory tool for discovering causal structures. Built on top of the
'QCA' package by Dusa (2019) <doi:10.1007/978-3-319-75668-4>, with function
arguments following 'QCA' conventions. Based on set-theoretic methods by
Ragin (2008) <doi:10.7208/chicago/9780226702797.001.0001> and established
robustness protocols by Rubinson et al. (2019)
<doi:10.1177/00491241211036158>.

Yuki Toyoda

TSQCA

Threshold Sweep Extensions for Qualitative Comparative Analysis

Japan Society for the Promotion of Science 

sample_data function

A data frame with 80 rows and 4 variables.

Format

A small artificial dataset with variables:<dl>
<dt>Y</dt>
<dd>Outcome (numeric)</dd>

<dt>X1</dt>
<dd>Condition 1</dd>

<dt>X2</dt>
<dd>Condition 2</dd>

<dt>X3</dt>
<dd>Condition 3</dd>


</dl>

sample_data: Sample dataset for TSQCA examples

Description

Usage

Arguments

Format