Skill UI

A comprehensive guide for authors preparing medical manuscripts for high-impact journals. It outlines rigorous standards for statistical reporting, emphasizing the use of effect sizes with 95% Confidence Intervals (CIs) over p-values alone. Key topics include pre-specification, intention-to-treat analysis, multiplicity control, handling missing data through imputation, and reporting both relative and absolute effects to ensure maximum statistical rigor and reproducibility.

A comprehensive guide for authors to select, defend, and strengthen the internal validity of clinical study designs (RCT, Cohort, Diagnostic, etc.). It provides detailed safeguards—covering topics like intention-to-treat analysis, confounding control, blinding, and power calculations—to ensure manuscripts meet the rigorous reporting standards of top-tier medical journals like JAMA.

This comprehensive aid helps researchers determine the suitability of their surgical trials, outcomes studies, or perioperative research for JAMA Surgery. It details required scientific rigor, including comparative, patient-centered outcomes, robust risk adjustment, and advanced statistical methods. It also covers specific reporting standards (CONSORT, STROBE, PRISMA) and the current JAMA Network house style, ensuring manuscripts are submission-ready.

A comprehensive guide for structuring and validating empirical research designs (Survey/SEM, Secondary Data, Experiments, Meta-analysis) intended for high-impact journals. It addresses critical methodological issues such as construct validity, endogeneity control, robust identification strategies, and ensuring overall rigor across diverse academic genres.

This guide details the rigorous standards for creating empirical tables and figures in academic marketing science (JAMS style). It covers building conceptual models, structural path coefficient tables, measurement validity checks, and creating highly actionable 'managerial exhibits' that translate statistical estimates into decision-making insights, ensuring all work is self-contained and adheres to APA guidelines.

A comprehensive guide for econometricians submitting manuscripts to top journals. It details how to structure analyses for full reproducibility, including using master scripts, pinning software versions, and exporting results to plain-text formats. Coverage includes advanced robust inference techniques such as HAC, cluster bootstrapping, and weak-IV diagnostics, ensuring the work satisfies rigorous archival standards.

This guide details the rigorous, reproducible empirical strategies required to identify causal parameters in applied econometrics, meeting high standards (e.g., JAE). It covers various designs—including DID, IV, panel data, and time-series—and mandates that every assumption and diagnostic test must be explicitly stated, tested, and reproducible using deposited code/data.

This guide helps researchers structure the literature review for applied econometrics papers targeting the Journal of Applied Econometrics (JAE). It emphasizes moving beyond simple literature surveys by creating an "empirical audit trail." Users must position their work across method lineage, applied precedent, and engagement with the journal's archived data and prior replicable results, ensuring the contribution is an advance through application or replication.

This guide outlines the mandatory data and code deposit policy for articles published in the Journal of Applied Econometrics (JAE). Authors must submit a complete, non-confidential set of input data (plain ASCII/CSV), programs that replicate every result, and a detailed README file. It emphasizes strict adherence to archival format rules, ensuring the research is fully reproducible for the academic community.

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 guide provides best practices for structuring tables and figures in academic econometrics manuscripts, especially when adhering to strict journal page limits. It advises researchers on exhibit triage—determining which core findings belong in the main text versus supplementary online appendices—and guarantees reproducibility by detailing required note components and generating scripts.

This resource guides researchers through the rigorous criteria for publishing in the Journal of Applied Econometrics (JAE). It helps determine if a paper is sufficiently 'applied' (focusing on real data and economic questions) rather than purely theoretical. It outlines the necessity of replicability, the mandatory data archiving process, and the strategic choice between a standard Research Article and a Replication Article.