Skill UI

This tool provides a comprehensive guide to the manuscript review process for Demography journal. It details the double-blind review structure, the mandatory pre-review desk screening (by Editor/Deputy Editor), and the common grounds for desk rejection. By stress-testing your paper against these academic standards, authors can significantly improve their work, ensuring methodological rigor and general interest before submission.

A comprehensive guide for analyzing and reporting longitudinal data in Developmental Psychology manuscripts, ensuring compliance with high academic standards. It emphasizes modeling developmental change (e.g., growth curves, multilevel models, SEM), establishing measurement invariance (configural, metric, scalar) before interpretation, and rigorously reporting effect sizes and confidence intervals (CIs) using JARS guidelines. It guides the distinction between confirmatory and exploratory findings.

A comprehensive guide for researchers in Developmental Psychology on meeting rigorous Open Science standards. It details best practices for data and materials sharing using Persistent Identifiers (DOIs), mandatory preregistration of hypotheses, sample-size justification, and adhering to ethical requirements when working with minors and vulnerable populations. It ensures compliance and reproducibility in modern scientific reporting.

This guide details the rigorous review standards and criteria for developmental psychology manuscripts, covering masked peer review, developmental significance, methodological rigor (age/cohort effects, invariance, attrition), JARS reporting, and TOP transparency. Use this resource to stress-test your paper before submission, understand expected revisions, or interpret complex decision letters.

Provides detailed guidelines for developing tables and figures in Developmental Psychology manuscripts, adhering to APA 7th edition standards. Focuses on making developmental change explicit by using age/time on the x-axis, plotting individual trajectories (spaghetti plots), and displaying model-implied mean curves with confidence intervals, moving beyond simple group mean comparisons.

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.

A comprehensive skill guide designed to help researchers assess the suitability of their economics manuscripts for submission to 《Economic Review》. It covers journal positioning, required empirical rigor, structural expectations (abstract, citation style), common rejection pitfalls, and advice on necessary revisions and alternative journals. This tool is crucial for navigating academic publishing standards in Chinese economics.

This guide outlines rigorous standards for incorporating theoretical and quantitative models into economic policy manuscripts. It emphasizes that models must be minimal, transparent, and directly bear policy weight—converting estimates into statements about welfare, fiscal costs, or clear mechanisms. It teaches how to design models that pass 'the necessity test,' ensuring policymakers can trace headline numbers directly back to key, identifiable assumptions.

A comprehensive preflight checklist for authors submitting manuscripts to Econometrica. It details strict guidelines on manuscript length (main body and supplemental material), formatting, anonymization protocols, membership requirements, and adhering to the latest Data and Code Availability Policy. Use this guide before submission to ensure full compliance with the journal's standards.

This tool helps researchers diagnose whether their empirical or theoretical result meets the high standards required for top-tier academic journals like Econometrica. It guides users to evaluate the generality, methodological novelty, and theoretical depth of their work, ensuring the contribution is a generalizable estimator or theorem, not merely an application.

A comprehensive guide detailing the rigorous standards for presenting statistical exhibits in high-level econometric theory journals. It covers best practices for Monte Carlo simulations, constructing diagnostic plots (size, power, coverage, bias), ensuring legibility at print reduction, and adhering to specific file formats (TIFF/EPS/PDF).

This guide provides comprehensive standards for conducting and reporting rigorous empirical and simulation evidence in econometrics. It covers designing Monte Carlo simulations, creating minimum evidence maps, ensuring reproducibility through detailed logging, and linking theoretical claims directly to finite-sample evidence. Essential for high-level statistical research.