Skill UI

A comprehensive guide for authors preparing empirical research manuscripts (especially in accounting). It details best practices for structuring main tables (keeping them lean), transforming statistical coefficients into interpretable economic magnitudes, and properly visualizing dynamic effects using event study graphs. It emphasizes moving beyond simple significance stars to provide deep academic context.

This guide helps researchers rigorously evaluate if their project meets the criteria for a 'systems analysis' in high-impact journals. It teaches how to shift the research focus from single-factor field trials to complex systems questions that analyze interactions, trade-offs, and emergent behaviors across multiple hierarchical levels, such as the farm to the food system. Essential for properly framing scope and article type before submission.

A comprehensive planning tool for developmental psychology researchers designing studies that must support a claim of change. It systematically guides users through critical methodological issues, including addressing age vs. cohort confounds, planning for measurement invariance across ages, handling attrition, and properly justifying sample size for growth slopes. Essential for strengthening the pre-analysis plan of longitudinal and cross-sectional designs.

This guide outlines the mandatory structure for creating a reproducible research package, required by academic journals like the European Economic Review (EER). It details how to properly assemble raw data, master analysis scripts, environmental specifications, and comprehensive documentation (README) to ensure that reported results can be independently verified by others. It is essential for any paper involving empirical analysis or simulations.

This guide details the necessary steps for achieving and reporting reproducibility in Human-Robot Interaction (HRI) studies. Since HRI involves unique elements like human participants and physical environments, reproducibility focuses on making the study protocol, robot behavior specifications, analysis code, and de-identified data transparent. Learn how to properly assemble a comprehensive replication package and ethically disclose limitations to enhance academic credibility in top-tier HRI publications.

A comprehensive guide for authors preparing submissions for ICDE conferences. It details how to properly segment content into the main 12-page body versus the supplementary material, ensuring the core argument remains self-contained while providing reviewers with runnable artifacts, extended experiments, and full technical documentation.

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.

This guide provides essential best practices for presenting spatial evidence in academic papers, particularly in economic geography. It emphasizes that maps and tables must make an explicit argument—show variation, spatial discontinuity, or gradients—rather than merely decorating the data. Learn how to properly report spatial model coefficients, handle projections, and avoid common cartographic and statistical pitfalls.

This comprehensive guide details the strict replication and data deposit policies required by the Journal of International Economics (JIE). It ensures that all components—including raw data, cleaning scripts, structural solver code, and master scripts—are properly deposited in a secure repository (like Mendeley Data) before publication acceptance, guaranteeing full research reproducibility.

This guide provides detailed instructions on structuring the online appendix for high-impact academic manuscripts. It emphasizes the critical balance between maintaining a self-contained, readable main text and providing comprehensive, verifiable supporting material. Learn how to properly place derivations, robustness checks, and data construction details to enhance the scientific rigor and credibility of your research.

This guide helps researchers refine their academic work to meet the rigorous standards of top economics journals like JPE. It teaches users to move beyond simple correlation by structuring their research around clear economic mechanisms, linking evidence to established theory, ensuring generality, and properly considering equilibrium effects. Use this when developing a paper pitch or deciding the overall scope of a manuscript.

This guide details how to conduct rigorous, reproducible numerical simulations for mathematical finance research. It emphasizes that numerical experiments must strictly support a theoretical theorem (e.g., convergence rates, error bounds) rather than performing empirical data fitting. Learn how to properly specify schemes, report theoretical vs. empirical error rates, and maintain full reproducibility to meet high academic standards.