Skill UI

This skill provides a comprehensive guide for authors targeting JAMA Cardiology. It helps authors evaluate the suitability of cardiovascular trials, outcomes, and registry studies against the journal's high standards. It covers required endpoints, reporting guidelines (e.g., CONSORT, STROBE), house style, and submission prerequisites, aiding in optimizing manuscript fit before submission.

A comprehensive guide and checklist for ensuring that figures and tables in medical manuscripts comply with the rigorous reporting standards of JAMA. It covers mandatory elements such as CONSORT flow diagrams, reporting effect sizes with 95% CIs, structuring baseline characteristics, and avoiding statistical misrepresentation (e.g., using p-values instead of CIs).

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.

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.

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 comprehensive guide details the rigorous methodological standards required for validating new statistical estimators, tests, or algorithms. It moves beyond simple causal inference, emphasizing foundational proofs of identification, regularity conditions, asymptotic consistency, and finite-sample robustness. It serves as a checklist for assuring the credibility and reliability of methods in academic statistical journals.

A comprehensive preflight checklist designed for submitting manuscripts to the Journal of Business & Economic Statistics (JBES). This guide ensures authors have verified all necessary components—including the data/code supplement, conflict disclosures, and cover letter targeting—against the latest academic standards. It functions as a critical final review step before formal submission, emphasizing the need to cross-reference live journal guidelines.

A comprehensive guide for structuring and polishing empirical tables and figures for top-tier academic journals, such as the Journal of Business Venturing (JBV). It covers the standards for presenting descriptives, main model coefficients, interaction plots, survival curves, process models, and qualitative data structures. This skill ensures exhibits are self-contained, interpretable, and adhere to rigorous academic house styles.