Skill UI

A comprehensive guide detailing the quantitative and econometric standards required for submissions to top-tier monetary and macroeconomic journals. It covers advanced techniques like VAR/SVAR, Local Projections, and DSGE modeling, focusing on proper inference, robustness checks, and diagnostic reporting to ensure scholarly rigor.

This comprehensive guide assists in developing rigorous research designs for family science. It covers quantitative methodologies (longitudinal, dyadic, life-course, event history), qualitative approaches, and mixed-methods integration. The focus is on strengthening the design's defensibility by explicitly addressing units of analysis, interdependencies, and critical statistical challenges like selection bias and non-independence.

This guide provides comprehensive standards for defending rigorous data analysis in academic submissions, particularly for the Journal of Management Studies (JMS). It details specific requirements for both quantitative work (e.g., robustness checks, SEM, endogeneity) and qualitative work (e.g., coding transparency, abductive logic, trustworthiness), ensuring the analysis credibly supports the theoretical claims.

A comprehensive guide for structuring rigorous academic research in management studies. It helps researchers align theoretical claims (causal, exploratory, mechanism testing) with appropriate methods—including qualitative, quantitative, and multi-method designs. The guide covers advanced topics such as addressing common-method bias, endogeneity, and cross-level analysis, ensuring methodological rigor for top-tier publications.

A comprehensive guide for academic finance researchers to assess if their quantitative manuscript is suitable for submission to the Journal of Financial and Quantitative Analysis (JFQA). It covers the journal's elite positioning, necessary methodological rigor (e.g., causal identification, standard errors), required structure, and common desk-reject pitfalls, helping authors refine their work for top-tier quantitative finance venues.

This skill provides detailed guidance on assessing a research paper's alignment with the scope of quantitative economics and technical economics journals. It helps determine if the core contribution lies in advanced quantitative methods, econometrics, efficiency measurements (TFP, DEA), or input-output analysis, guiding authors toward the most suitable academic publication venue.

This guide provides a rigorous framework for advanced econometric modeling in quantitative economics. It covers time series, panel data, cointegration, and mixed-frequency techniques (VAR, VECM, GMM, MIDAS). It emphasizes proper model diagnostics, stationarity testing, and grounding models in specific data properties and economic contexts.

A comprehensive guide for researchers focusing on quantitative economic measurement, including TFP, efficiency analysis (DEA/SFA), and index construction. It emphasizes the necessity of methodological transparency, data traceability, reproducible calculations, and rigorous sensitivity testing to ensure the scientific validity of quantitative findings.

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 provides comprehensive standards for analyzing and reporting results in Organization Science, a field characterized by diverse methodologies. It ensures methodological rigor and transparency whether the work is qualitative (establishing trustworthiness), quantitative (matching estimators to design), computational (reporting seeds and sensitivity), or formal/analytical. It emphasizes full reproducibility and mechanism-based inference.

This skill guides authors in assembling a comprehensive transparency package for academic submissions (especially meta-analyses). It ensures adherence to Open Science principles by detailing requirements for protocol preregistration (PROSPERO/OSF), depositing the coded database, codebook, and analysis scripts. It is essential for proving the full reproducibility of quantitative research findings.

A comprehensive guide for executing and reporting quantitative analyses for high-stakes public policy research. This skill emphasizes methodological rigor, demanding transparency in uncertainty reporting (effect size, intervals), robust checks (heterogeneity, alternative specifications), and ensuring full reproducibility through master scripts and pinned versions for journal submission.