Skill UI

A comprehensive framework for conducting rigorous empirical data analysis required for top-tier academic journals. It guides users through building transparent archival samples, specifying appropriate panel data estimators (like firm/year fixed effects), ensuring correct standard error clustering, and executing sophisticated identification strategies (e.g., Difference-in-Differences, Instrumental Variables). Essential for addressing endogeneity and passing deep reviewer scrutiny.

This comprehensive guide helps researchers evaluate whether a clinical or health-services study is appropriate for publication in JAMA Internal Medicine. It details the journal's high bar for methodological rigor, including requirements for randomized trials (CONSORT), observational studies (STROBE), and systematic reviews (PRISMA). It covers everything from study design and statistical reporting to addressing potential desk-reject triggers, ensuring authors submit high-quality, impactful research.

Provides a comprehensive guide to the Journal of Applied Econometrics (JAE) submission and review process. It details the single-blind peer review structure, the final decision authority of the Editor-in-Chief, and the high standards for empirical rigor, including data reproducibility, appropriate inference methods, and mandatory data archiving. Essential for authors planning submissions and resubmissions.

This router guides authors through the entire lifecycle of a manuscript submitted to the Journal of Business & Economic Statistics (JBES). It does not perform analysis, but rather diagnoses the current bottleneck—whether in topic selection, data analysis, or rebuttal—and directs the user to the appropriate specialized skill within the JBES workflow, ensuring the work maintains both methodological novelty and empirical relevance.

This comprehensive guide outlines the best practices for preparing a complete and reproducible research package for submission to the Journal of Banking & Finance (JBF) following Elsevier Option C guidelines. It details requirements for data availability statements, proper structuring of code and data access materials, and best methods for managing proprietary or restricted datasets (such as CRSP or Compustat), ensuring research transparency and verifiability.

This guide provides comprehensive guidelines for preparing high-quality, publication-ready tables and figures specifically tailored for Journal of Banking & Finance (JBF) submissions. It covers everything from structuring descriptive statistics and regression results to designing event-study plots and ensuring proper notes and execution workflows.

A comprehensive guide for authors submitting to the Journal of Corporate Finance (JCF). It details how to comply with Elsevier's Option C data availability requirements, focusing on drafting the data availability statement and structuring the research archive. It provides best practices for handling licensed, proprietary data (e.g., Compustat, CRSP) by recommending the sharing of construction code and access instructions, rather than raw data deposits.

A comprehensive guide for designing and presenting rigorous experiments for top-tier computer science journals. It covers best practices for ensuring reproducibility, matching evidence to claims, selecting appropriate baselines, performing statistical significance testing, and handling modern challenges like LLM contamination and system scalability measurements. Essential for passing double-blind peer review.

A comprehensive guide detailing the mandatory replication and data policy required by journals like JDE. It outlines how to build a self-contained, reproducible package containing master scripts, documented data provenance, pinned environments, and strategies for handling restricted or proprietary data, ensuring readiness for review and acceptance.

A guide for structuring rigorous academic manuscripts in educational psychology. It teaches researchers how to state a clear psychological mechanism, derive directional and testable hypotheses, and properly distinguish between confirmatory (preregistered) and exploratory analyses, adhering to high academic standards.

A comprehensive guide for assembling the required data and code replication package for manuscripts submitted to the Journal of the European Economic Association (JEEA). This package ensures compliance with the DCAS standard, enabling the journal's Data Editor to verify the reproducibility of empirical, simulation, or experimental results before formal acceptance. It outlines the mandatory structure, README contents, and execution steps.

A comprehensive framework designed to ensure environmental economics manuscripts meet rigorous data-availability and reproducibility standards, especially for journals like JEEM. This package guides users to document the entire research pipeline, handling complex issues like data versioning, proprietary satellite/admin data, and multi-step spatial operations by establishing a credible end-to-end reproduction path.