Skill UI

This guide provides a rigorous framework for defending causal identification claims in empirical microeconomics, tailored for top-tier journals like AEJ: Applied. It covers modern techniques and anti-patterns for RCTs, Difference-in-Differences (DiD), Regression Discontinuity (RDD), and Instrumental Variables (IV), ensuring the mapping from variation to the causal estimand is explicit, defensible, and falsifiable.

This comprehensive guide details the structured method for drafting author responses to peer reviewers' comments for major conferences like AISTATS. It covers best practices for addressing statistical validity, novelty, and technical concerns in a constrained, anonymous, text-only format. Learn how to triage objections, anchor claims to existing evidence, and handle specific statistical pushback patterns.

This resource simulates the rigorous peer review process of a top journal, focusing on educational relevance, theoretical mechanism, design rigor (especially nested data analysis), and transparency standards (JARS, preregistration). Use this guide to stress-test your manuscript before submission, preemptively address common rejection patterns, or interpret a complex decision letter, ensuring your work meets the highest academic standards.

This guide provides expert standards for creating rigorous, self-contained tables and figures for top-tier academic journals (like JFE). It covers detailed conventions, such as structuring exhibits to convey a single, clear message, consistently reporting statistical metrics (SEs/t-stats), and ensuring figures visualize patterns rather than merely decorate. Essential for submitting polished, publication-ready empirical research.

Details the rigorous, masked peer review process for top academic journals. It outlines the critical "dual gate" criteria—theoretical contribution and methodological rigor—and common desk-reject patterns. Use this guide to stress-test your manuscript, structure your arguments, and set realistic expectations for submission and revision rounds.

This guide provides rigorous standards for transforming complex behavioral and risk data into clear, statistically sound, and academically rigorous tables and figures. It ensures that key decision-theoretic content, such as choice patterns, parameter estimates, and uncertainty, are visibly and interpretably presented for academic publication.

Provides comprehensive guidelines for constructing self-contained, highly legible tables and figures for population and development research manuscripts. It emphasizes that exhibits must communicate not only raw demographic patterns but also their broader development and policy significance to a wide, non-specialist readership (e.g., economists, environmental scholars). Key principles include showing uncertainty, using appropriate specialized graphics (e.g., population pyramids, survival curves), and maintaining data reproducibility.

This guide provides a structured framework for presenting complex empirical results in academic manuscripts, particularly for international marketing journals. It details the essential 'spine exhibits' (conceptual models, invariance tables, cross-national patterns) and teaches techniques like the 'claim test' and 'triage' to ensure arguments are clear, rigorous, and adhere to strict page limits.

A comprehensive guide to building production-ready Apache Airflow Directed Acyclic Graphs (DAGs). This skill covers best practices for operators, sensors, testing, deployment, and designing robust data pipelines. Use this when orchestrating complex workflows, managing ETL processes, or ensuring reliable batch job execution in a production environment.

A guide to production-ready patterns for dbt (data build tool). It covers essential practices for robust data pipeline development, including model organization (staging, intermediate, marts), implementing advanced testing strategies, ensuring data quality, and optimizing incremental processing for large datasets.

This skill analyzes oral health data to identify patterns and assess overall status. It provides personalized advice for oral care and hygiene. It supports correlation analysis with nutrition, chronic diseases, and medication. Suitable for analyzing trends, caries risk, and periodontal issues. Users can generate reports based on long-term records.

This skill analyzes skin health data to identify problem patterns and assess overall status. It supports correlation analysis with nutrition, chronic diseases, and medication data. Users should consult the detailed guide before execution to ensure safety and accuracy.