Skill UI

A comprehensive guide for designing rigorous experimental studies in behavioral science. It covers establishing causal links, testing psychological mechanisms (mediation and moderation), controlling confounding variables, conducting power analysis, and adhering to modern academic standards like pre-registration, ensuring research meets the high bar of top-tier journals.

A guide for academic researchers to determine if a consumer phenomenon belongs in the Journal of Consumer Psychology (JCP) or a related journal (like JCR or JMR). It helps set the scope, confirm the psychological mechanism, and select the appropriate manuscript type (e.g., Research Report vs. full Article), ensuring the contribution is theory-driven and experimentally testable.

This comprehensive guide assists users in analyzing and reporting data for high-impact academic journals, specifically following the rigorous standards of the Journal of Consumer Research (JCR). It covers advanced statistical process evidence (mediation, moderation, effect sizes) for behavioral experiments, as well as methods for establishing trustworthiness in interpretive (CCT) research. It emphasizes transparency, replication code, and adherence to modern research reporting mandates.

Provides a comprehensive guide for designing rigorous academic studies for high-impact journals. Whether planning multi-study behavioral experiments, interpretive Consumer Culture Theory (CCT) fieldwork, or mixed designs, this resource ensures that the evidence collected is optimally structured to support the conceptual claim, emphasizing internal validity and transparency.

A comprehensive guide for researchers preparing exhibits for high-impact journals like JCR. It details best practices for summarizing multi-study experimental packages, presenting complex statistical results (mediation, moderation, simple slopes), and developing conceptual figures while adhering to strict house style (Chicago Manual of Style) and page limits. Focuses on maximizing data clarity and earning space through effective visualization.

A comprehensive guide for developing the conceptual core of academic manuscripts in consumer research, aligning with high standards like JCR. It instructs users on defining psychological mechanisms (mediators/moderators) for experimental papers, or building robust conceptual frameworks for interpretive/CCT papers, ensuring the theory advances, deepens, or repudiates existing knowledge.

A comprehensive guide for designing and presenting rigorous experiments for top-tier computer science journals. It covers best practices for ensuring reproducibility, matching evidence to claims, selecting appropriate baselines, performing statistical significance testing, and handling modern challenges like LLM contamination and system scalability measurements. Essential for passing double-blind peer review.

Provides a comprehensive guide on structuring scientific manuscripts, addressing the proper placement of core evidence, detailed proofs, extended experiments, and large datasets in appendices and supplementary materials for academic journals. Ensures crucial findings are in the main text while maintaining clarity and adhering to double-blind review standards.

This comprehensive guide establishes the rigorous methodological standards for developing credible causal identification strategies in development economics. It details best practices for modern quasi-experimental methods, including RCTs, DID, IV, and RDD. Authors learn how to meet the high empirical norms required by top-tier journals by ensuring robustness, addressing biases (e.g., TWFE), and validating external validity.

A comprehensive guide designed to stress-test the causal identification of behavioral mechanisms for top-tier economic journals (e.g., JEBO). It provides stringent criteria across lab/field experiments, observational data (DiD, IV, RDD), and simulations, ensuring the design isolates the claimed psychological or institutional channel, not just a correlation. Use this when standard econometric methods are insufficient to prove mechanism causality.

A comprehensive workflow guide for authors responding to major journal decision letters (R&R or reject-and-resubmit). This resource provides a structured approach to triaging conflicting referee comments, prioritizing editor concerns, planning necessary new experimental treatments, and crafting a professional, persuasive response letter to maximize publication chances in top-tier academic journals.

A comprehensive guide for assembling a complete and reproducible materials package for experimental economics research, specifically for JEBO submissions. It details required components, including participant instructions, z-Tree/oTree code, anonymized raw data, detailed analysis scripts, and environment specifications, ensuring rigorous academic reproducibility.