Skill UI

A comprehensive guide for executing rigorous empirical accounting studies. This resource details best practices for advanced econometric techniques, including correct standard error clustering (firm-level, two-way clustering), executing identification strategies (DiD, RD, IV/2SLS), validating accounting constructs, and performing extensive robustness checks (falsification, placebo tests). It also emphasizes data provenance and reproducibility, critical for top-tier academic publications.

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 guide is designed for systematic reviews and meta-analyses, providing a rigorous framework to stress-test the robustness and completeness of reported findings. It mandates advanced checks such as saturation evidence, risk-of-bias appraisal, and statistical diagnostics (e.g., heterogeneity, publication bias) to ensure conclusions are not artifacts of omission or methodological weakness. Essential for high-level academic research.

Provides a comprehensive guide for authors submitting to the Review of Educational Research (RER). It helps authors anticipate reviewer and editor expectations, framing their work as a significant advance rather than a simple summary. The guide covers rigorous methodological standards, addressing predictable objections (e.g., search incompleteness, coding reliability) and ensuring the manuscript is appropriately positioned relative to other academic venues.

This comprehensive guide details the rigorous methodology for conducting systematic literature reviews and meta-analyses, particularly in educational research. It ensures the reproducibility and defensibility of the evidence corpus by documenting the entire PRISMA flow, from exhaustive multi-database searching and dual screening to structured data extraction and subsequent synthesis of findings.

This tool guides the transformation of a coded, screened corpus into a robust analytical spine for academic synthesis. It moves beyond simple annotated bibliography summaries by requiring the construction of a conceptual framework (e.g., taxonomy, theoretical model, tensions). This structure ensures the review advances theory or policy, providing a coherent, critical argument for the field.

A comprehensive guide for developing a rigorous, a-priori protocol for systematic reviews and meta-analyses in educational research. This tool ensures methodological transparency by defining the scope (PICO), eligibility criteria, search strategies, screening procedures, and synthesis plans before any data is collected, protecting the integrity of the research findings.

A comprehensive checklist for authors preparing a scholarly review manuscript for submission (e.g., RER). It guides users through critical pre-submission checks, including masking requirements, adherence to APA 7th edition, abstract length constraints, and proper assembly of the three-file set (unblinded title page, blinded main manuscript, author bios).

A comprehensive guide for designing essential exhibits—such as PRISMA flow diagrams, forest plots, and evidence maps—for systematic reviews, meta-analyses, and critical syntheses. These exhibits are crucial for allowing readers to audit the search process and understand the synthesis at a glance, ensuring methodological rigor and clarity.

Provides a structured framework for vetting potential review topics for high-impact educational journals. It guides researchers through four critical fit tests—educational importance, literature maturity, current need for synthesis, and scope tractability—before committing to a full search or writing a protocol, ensuring the proposal genuinely advances academic understanding.

A comprehensive guide detailing how to make systematic reviews and meta-analyses fully auditable and reproducible for academic publishing. It emphasizes adhering to standards like PRISMA and MARS, quantifying inter-coder reliability (e.g., Kappa/ICC), and sharing all open materials, including search strings, coding datasets, and analysis code (via OSF/DOI).

This skill helps authors assess the suitability of their accounting manuscripts for prestigious academic journals like Review of Accounting Studies (RAST). It analyzes the paper's fit, rigor, methodological strength, and structure against top-tier academic standards in areas like valuation, disclosure, and information economics. It provides actionable feedback on potential rejection risks and alternative venues.