Skill UI

Comprehensive guidelines for preparing and reporting complex empirical evidence across various methodologies (SEM, econometrics, design science, qualitative). This guide ensures results meet the high academic standards of top-tier journals by emphasizing theoretical traceability, statistical rigor, and required data transparency, including full correlation/covariance matrices.

This guide provides comprehensive methodological advice for academic submissions in Information Systems (IS), particularly for journals like JAIS. It covers selecting and rigorously defending diverse research designs—including behavioral experiments, causal inference (Economics of IS), design science, qualitative studies, and literature reviews. Use it when you need to validate the suitability of your methodology against your research claims and underlying phenomena.

This comprehensive guide provides a rigorous framework for developing original theoretical contributions in Information Systems (IS) research, particularly for top-tier academic journals. It outlines various theoretical genres—including behavioral mechanisms, economic models, and design theories—and teaches authors how to move beyond mere description. Key principles include constructing novel, well-defined constructs; identifying clear boundary conditions; and executing deep 'round-trip' theoretical integrations to ensure the contribution is genuinely original.

This comprehensive guide is designed for researchers planning submissions to highly specialized academic journals, such as JAIS. It provides a rigorous framework to test whether an Information Systems (IS) topic is theoretically load-bearing, how to select the precise manuscript category (e.g., Theory, Research Article, Literature Review), and how to frame the work to meet high academic standards. Essential for pre-submission planning.

This comprehensive guide helps researchers evaluate whether a clinical or health-services study is appropriate for publication in JAMA Internal Medicine. It details the journal's high bar for methodological rigor, including requirements for randomized trials (CONSORT), observational studies (STROBE), and systematic reviews (PRISMA). It covers everything from study design and statistical reporting to addressing potential desk-reject triggers, ensuring authors submit high-quality, impactful research.

A comprehensive guide designed to help researchers assess the suitability and structure of clinical neurology studies for submission to JAMA Neurology. It covers scope fit, evidence requirements (e.g., validated endpoints, adequate power), mandated reporting guidelines (CONSORT, STROBE, PRISMA), and specific journal house style and submission checklists. This is a venue-fit aid, not clinical advice.

This comprehensive guide maps various study designs (e.g., RCT, Observational, Systematic Review) to mandatory reporting checklists and flow diagrams (such as CONSORT, PRISMA, STROBE, STARD). It ensures researchers meet the rigorous, standardized reporting requirements for top-tier medical journal submissions.

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 guide serves as a critical preflight checklist for authors submitting manuscripts to high-impact journals like JAMA. It meticulously verifies completeness across multiple dimensions, including adhering to specific word/format limits, confirming required ethical statements (IRB, COI, data sharing), and ensuring all supplementary files (e.g., CONSORT/PRISMA checklists, flow diagrams) are correctly uploaded. It is designed as a final quality gate to prevent common submission errors.

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, 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.

A comprehensive orchestrator skill guiding the entire lifecycle of an applied econometrics manuscript targeting the Journal of Applied Econometrics (JAE). It ensures the paper maintains an applied, real-data focus and rigorously follows the necessary steps, including literature positioning, identification strategy, reproducible data analysis, and mandatory data archival deposit. Designed to prevent common pitfalls by integrating data integrity checks at every stage.