Skill UI

This comprehensive guide outlines the strict analytical and reporting standards required for top-tier conservation biology manuscripts. It covers everything from selecting appropriate statistical models (e.g., hierarchical, spatial) to honestly quantifying uncertainty, ensuring full reproducibility, and translating complex findings into actionable, decision-relevant conservation insights. Use this skill when performing main analyses or preparing manuscripts for expert peer review.

This skill automatically converts structured data from Excel (.xlsx) workbooks into a clean, readable Markdown format. It is essential for enabling accurate analysis, summarization, and data extraction of spreadsheet contents, especially when the user asks to 'read', 'analyze', or 'compare' data without specifying a conversion method. It supports both single files and batch processing of entire folders.

This guide provides a comprehensive framework for conducting heterogeneity and conditionality analysis in Chinese Public Administration (CPA) research. It outlines theory-guided methods for selecting dimensions (e.g., administrative level, governance context, institutional structure) and details best practices for both quantitative (Chow test, interaction terms) and qualitative (QCA) comparison, ensuring findings are theoretically grounded and methodologically rigorous.

This comprehensive guide provides a rigorous framework for identifying and testing the causal mechanisms underlying public administration outcomes. It moves beyond merely stating an effect, guiding researchers to detail the specific processes—such as policy execution, attention allocation, or central-local relations—that cause the observed outcome. It covers both quantitative mediation analysis (e.g., causal inference frameworks) and qualitative process evidence gathering, ensuring theoretical grounding and causal rigor in academic manuscripts.

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 provides rigorous methodology and theoretical frameworks for conducting heterogeneity analysis, particularly for academic manuscripts focused on rural Chinese economies. It outlines criteria for dimension selection (e.g., household endowment, regional environment, policy timing), ensuring theoretical justification, and setting minimum sample size requirements to avoid superficial findings and common pitfalls.

A comprehensive guide for rigorous data analysis execution and reporting in criminology research. This skill covers advanced econometric techniques required for analyzing complex crime data, including count models (Negative Binomial, Zero-Inflated), fixed-effects panel data, and survival/recidivism modeling. It emphasizes transparently reporting uncertainty, addressing selection bias, and ensuring methods are fully reproducible for expert peer review.

This guide provides comprehensive standards for achieving auditability and transparency in Computer-Supported Cooperative Work (CSCW) research. It teaches researchers how to document non-shareable evidence, such as field interviews, log traces, and system deployments, by focusing on detailed analysis trails, decision logs, and rigorous process documentation, thus strengthening academic rigor.

A comprehensive methodological guide designed for researchers writing economics and finance papers. It specifies the rigorous requirements for conducting heterogeneity analysis, emphasizing the need for theoretical justification, sufficient sample size, and alignment with the underlying economic or institutional mechanisms (especially within the Chinese finance and trade context).

This guide provides an expert framework for advanced econometric analysis, focusing on establishing causal inference in fields like finance and trade. It details best practices for quasi-experimental designs (DID, IV, RDD, DML) and rigorously addresses common endogeneity issues such as policy bias, reverse causality, and anticipation effects, ensuring robust research methodology.

This guide provides rigorous methodologies for conducting mechanism analysis in empirical economics, particularly for submissions to finance and trade journals. It teaches how to open the 'policy black box' by identifying measurable, causal channels (e.g., changes in firm investment, credit flow, or government expenditure) that explain the relationship between a policy shock and an outcome. It covers mediation/moderation techniques and sub-sample comparisons.

A comprehensive guide for strengthening the methodological design of anthropological manuscripts. It provides frameworks for defending evidence across multiple modes—including ethnographic fieldwork, archival analysis, and quantitative biological data—by anticipating and structurally refuting potential expert critiques. Essential for rigorous qualitative and mixed-methods research.