msqca-analysis
CommunityRun msQCA with theory-guided calibration.
Education & Research#report generation#calibration#research workflow#truth table#causal mechanisms#msqca#boolean minimization
Authorptreezh
Version1.0.0
Installs0
System Documentation
What problem does it solve?
msQCA analysis coordinates qualitative theory building with data calibration and boolean minimization to derive causal condition configurations for complex cases.
Core Features & Use Cases
- Four-phase integrated workflow: theoretical analysis → calibration guidance → quantitative msQCA computation → result interpretation.
- Calibration planning guidance: generates per-variable calibration decisions by combining theoretical anchors with data characteristics and quality checks.
- Truth table + minimization engine: builds a truth table, flags contradiction configurations, and produces multiple solution types (complex/minimal/parsimonious).
- Report-oriented outputs: produces an integrated report structure and quality metrics to support transparent interpretation.
Quick Start
Ask the AI to run an msQCA integrated analysis by providing your dataset (CSV) with case_id, condition variables, and a calibrated outcome variable Y, then request an interpretation of the best solution and its causal mechanisms.
Dependency Matrix
Required Modules
pandasnumpyscipyscikit-learn
Components
scriptsreferencesassets
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: msqca-analysis Download link: https://github.com/ptreezh/sscisubagent-skills/archive/main.zip#msqca-analysis Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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