Skill UI

This tool helps authors assess if their research manuscript is suitable for the Journal of Business and Economic Statistics (JBES). It evaluates the fit across methodological rigor, economic relevance, time series analysis, and microeconometrics, providing a comprehensive self-check against the journal's high standards and suggesting alternative venues.

This guide enforces rigorous standards for reporting clinical trial statistics, moving beyond simple P values. It mandates the use of confidence intervals, absolute and relative effect sizes, clear designation of the primary analysis population (ITT), and proper handling of multiplicity and missing data, aligning with standards set by top-tier medical journals.

A comprehensive guide for auditing and planning the analysis of linguistic manuscripts. It emphasizes that the analysis must credibly support the theoretical claim, covering quantitative modeling (mixed-effects models in R), phonetic measurements, and corpus statistics. Use this skill to stress-test the analysis chain, ensuring rigor and transparency in all generalizations.

This guide details best practices for rigorous statistical reporting in clinical trials, following guidelines from top medical journals like NEJM. It emphasizes using confidence intervals (CIs) over bare P-values, defining primary analysis populations (ITT), controlling for multiplicity, and reporting absolute risks (NNT). It helps researchers ensure their findings are statistically robust, transparent, and defensible.

A comprehensive guide based on high-impact journal requirements (like PNAS), detailing how to report quantitative scientific claims rigorously. It emphasizes moving beyond simple P values to include effect sizes, confidence intervals, sample size justification, distinction between biological and technical replicates, and ensuring full code and data reproducibility.

This guide provides comprehensive standards for achieving statistical rigor in scientific research reporting. It mandates that every quantitative claim must include effect sizes, uncertainty, sample size (n), and justified statistical tests. Key areas covered include distinguishing biological vs. technical replication, conducting power analyses, implementing multiple comparison corrections, and utilizing Registered Reports to prevent publication bias, ensuring maximum transparency and reliability in scientific findings.

This skill guides researchers in transforming raw meta-analysis results (e.g., pooled effects, moderator analyses) into a genuine, high-impact theoretical contribution suitable for integrative review journals. It teaches how to interpret conflicting findings, build or refine theoretical models, clearly state scope conditions (boundary conditions), and set concrete future research agendas, ensuring the findings advance the field beyond mere statistics.

This guide outlines the comprehensive policy and architecture required for submitting a fully reproducible replication package to The Review of Economics and Statistics (REStat). It details how to structure the repository, including data, master scripts, and the README file, ensuring that every result can be traced and regenerated by other researchers.

This specialized router guides the entire manuscript development process for submissions to The Review of Economics and Statistics (REStat). It does not replace specialized skills but systematically directs users through the full research pipeline—from initial topic selection and causal identification to robustness testing, figure creation, and rebuttal strategy—ensuring a structured approach to applied econometrics research.

This guide outlines best practices for developing self-contained, rigorous tables and figures for empirical academic research, particularly in accounting. It covers the complete exhibit set—including variable definitions, descriptive statistics, main results, and advanced diagnostic plots (e.g., DiD event-time plots)—ensuring the work withstands intense academic scrutiny.

This skill acts as a specialized guide for researchers submitting applied econometrics or empirical economics manuscripts. It helps authors assess the suitability of their work for the Review of Economics and Statistics (REStat) venue. It emphasizes framing the contribution around careful identification, robust measurement, and clean design, rather than general interest, providing crucial pre-submission self-checks and identifying potential desk-reject risks.

This comprehensive guide provides a rigorous framework for scientific reporting, ensuring statistical integrity and full reproducibility. It instructs authors on essential elements like reporting effect sizes, justifying sample sizes, controlling for multiple comparisons, and distinguishing biological from technical replicates, helping manuscripts meet the high standards of top-tier scientific journals.