e1

What it does

The skill provides a comprehensive guide for both quantitative and qualitative analysis, applying a VS-Research 5-Phase process to recommend diverse methodologies beyond routine tests. It includes phases for context collection, method identification, long-tail sampling, execution guidance, and suitability verification, with explicit procedures, checks, and code templates for quantitative analysis. It also adds qualitative analysis support (thematic analysis, grounded theory, content, narrative) and ties in software tools (NVivo, ATLAS.ti, MAXQDA, Dedoose) and coding practices. It absorbs capabilities related to generating analysis code and conducting sensitivity analyses, and references programming in R, Python, SPSS syntax, and relevant workflows.

How it works

• Phase 0 collects mandatory context data before applying methods (research_question, independent_variable, dependent_variable, design; optional controls, sample size, target journal).
• Phase 1 identifies the modal analysis method commonly used for the design and then prompts to confirm optimality and consider alternatives.
• Phase 2 presents three direction levels (A, B, C) with increasing methodological novelty and aligns method suggestions to journal type or research aims.
• Phase 3 selects a low-typicality method based on statistical fit, research question alignment, feasibility, and contribution potential.
• Phase 4 provides execution guidance: describe primary method, assumptions, power analysis, and provide or reference code blocks for R or Python; includes effect size calculations and reporting format.
• Phase 5 verifies suitability, ensuring the chosen method is justified and robust, with quality checks and assumption procedures.
• The skill also covers qualitative analysis methods (Thematic Analysis, Grounded Theory) with structured phases for coding, theme development, and reporting, plus software options and coding approaches.

When to use it

Use when selecting statistical/qualitative methods, interpreting results, checking assumptions, generating code, and conducting sensitivity analysis. Triggers include statistical tests (ANOVA, regression, t-test, power analysis) and qualitative workflows (thematic analysis, grounded theory, content, narrative).

What it can touch

Affects methods and tools for quantitative analysis including R code, Python code, SPSS syntax, and accompanying code blocks. It references software and coding workflows, and provides templates for analysis code and reporting.

Caveats

Prerequisites must approve with diverga_check_prerequisites("e1"); if not approved, it prompts for missing checkpoints. The skill version is 12.0.1 and uses Claude-code as the declared tool. It emphasizes not overpromising outcomes and sticks to stated procedures and checks.