validate_pre_calibrated

Checks that all names in <code>pre_calibrated</code> exist in <code>conditions</code>
and that the corresponding values in <code>dat</code> are within the <code>[0, 1]</code>
range required for fuzzy membership scores.

internal

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 

validate_pre_calibrated function

<dl><dt>pre_calibrated</dt>
<dd>Character vector or NULL.</dd>
<dt>conditions</dt>
<dd>Character vector. Valid condition variable names.</dd>
<dt>dat</dt>
<dd>Data frame containing the variables.</dd></dl>

Arguments

Validate the pre_calibrated parameter — validate_pre_calibrated

<dl>

<dt>pre_calibrated</dt>
<dd>Character vector or NULL.</dd>


<dt>conditions</dt>
<dd>Character vector. Valid condition variable names.</dd>


<dt>dat</dt>
<dd>Data frame containing the variables.</dd>

</dl>

validate_pre_calibrated: Validate the pre_calibrated parameter

Description

Usage

Value

Arguments