quant-empirical-analysis

name	Quant Empirical Analysis
description	Use this skill for quantitative model specification, robustness planning, and interpretation discipline.
version	0.1.0

Quant Empirical Analysis

Inputs

• Constructs and measures
• Candidate model strategy
• Data constraints and assumptions

Config Keys Read

• method.family
• method.rigor_checks
• claims.distinguish_empirical_vs_theoretical
• journal.emphasis

Required Rules

• quant_empirical_rigor
• theory_claims_discipline
• research_ethics_data

Outputs

• variable_operationalization.md
• model_spec_ladder.md
• robustness_plan.md

Process Logic

1. Map constructs to operational measures.
2. Specify baseline and alternative models.
3. Define robustness, interpretation, and limitation notes.

Failure / Uncertainty Handling

• If identification assumptions are weak, downgrade causal language and list required robustness checks.