Skill UI

A comprehensive guide for authors preparing replication and transparency packages for submissions to the British Journal of Political Science (BJPS). It outlines requirements for depositing quantitative and qualitative data and code into the BJPolS Dataverse, ensuring that research findings are fully reproducible and adhering to the Data Access and Research Transparency (DA-RT) statement.

This guide provides a framework for rigorously defending the methodological design of scientific manuscripts in conservation biology. It covers advanced topics including detection modeling (occupancy, capture-recapture), addressing spatial structure and pseudoreplication, quasi-experimental designs (BACI, difference-in-differences), and systematic review protocols (PRISMA). The goal is to ensure that the evidence presented directly and credibly supports transferable, decision-relevant conservation conclusions.

This skill provides rigorous standards and best practices for running and reporting analyses within Comparative Political Studies (CPS). It addresses common pitfalls in cross-national data, such as measurement error, few clusters, and spurious correlation, ensuring the resulting research is transparent, robust, and replication-ready for academic review.

This guide outlines the rigorous standards required by Comparative Political Studies (CPS) for manuscripts, especially quantitative papers. It details how to prepare a complete reproducibility package, including data, code, log files, and a data availability statement, ensuring that analysis is rigorous and verifiable for final acceptance.

This guide outlines the rigorous standards for creating a research replication package required by major academic journals (like The Economic Journal). It details the necessary components—including a comprehensive README, raw data, executable master code, and output logs—to ensure that all figures, tables, and results are fully reproducible by third parties. Crucial for pre-acceptance checks and maintaining academic rigor.

This guide outlines the creation of a complete, verifiable research package for economic policy manuscripts. It ensures that all empirical, experimental, or simulation results are fully reproducible by providing raw data guides, cleaning scripts, analysis code, and a single 'master' script that runs end-to-end. This process is critical for academic acceptance, allowing reviewers and discussants to independently verify every figure, table, and key number reported in the paper.

This guide details the requirements for creating a comprehensive replication package for manuscripts submitted to Econometric Society journals. It ensures full reproducibility of all results, including code, data provenance, and parameter settings, adhering to the journal's Data and Code Availability Policy. Key components include a master script, reproducible data, and detailed documentation.

This guide outlines best practices for submitting theoretical econometrics manuscripts to ET. It addresses how to handle extensive proofs, auxiliary lemmas, and simulation results that exceed page limits. The core focus is utilizing the voluntary Supplementary Material policy to ensure full reproducibility and transparency without requiring mandatory data or code archives.

This comprehensive guide outlines the strict requirements for preparing replication and data packages for submission to The Econometrics Journal (EctJ). It covers everything from README structure and detailed code inclusion to ensuring Monte Carlo determinism and managing restricted data, ensuring the method's credibility for reviewers.

This guide details the comprehensive review process for academic econometrics journals, outlining key stages from initial submission to final revision. It helps authors anticipate pitfalls, such as scope mismatch, formatting non-conformance, and weak replication packages. Users can plan their submission package by structuring a strong opening packet and managing expectations for the one-week desk screen and the three-month decision timeline.

This guide outlines the mandatory structure for creating a reproducible research package, required by academic journals like the European Economic Review (EER). It details how to properly assemble raw data, master analysis scripts, environmental specifications, and comprehensive documentation (README) to ensure that reported results can be independently verified by others. It is essential for any paper involving empirical analysis or simulations.

This comprehensive preflight checklist guides researchers through the final essential steps before submitting a manuscript to the European Economic Review (EER). It ensures adherence to Elsevier formatting standards, addresses mandatory replication policies (data/code availability), verifies funding declarations, and confirms all necessary fees and ethical statements are in place. Use this guide as the ultimate final check before pressing submit.