界面已本地化;技能介绍与说明文档按所选语言由 AI 自动翻译,代码、命令、路径和专业术语保留原文,以原作者文档为准。
探索技能
设计与创意 · SKILL.md

quantitative-methods

quantitative-methods

【设计与创意】Design and execute statistical analyses including regression modeling, hypothesis testing, power analysis, and robustness checks using R, Stata, SPSS, or Python

独立 GitHub 快照 · 自动分类 · 以原作者文档为准

技能说明

GitHub

name: quantitative-methods description: Design and execute statistical analyses including regression modeling, hypothesis testing, power analysis, and robustness checks using R, Stata, SPSS, or Python allowed-tools:

  • Read
  • Write
  • Edit
  • Grep
  • Glob
  • Bash graph: domains: [domain:social-sciences] skillAreas: [skill-area:statistical-analysis, skill-area:data-analysis, skill-area:machine-learning-frameworks] workflows: [workflow:experiment-design, workflow:peer-review-cycle] roles: [role:data-scientist, role:research-scientist]

Quantitative Methods Skill

Design and execute rigorous statistical analyses for social science research using modern analytical tools.

Overview

The Quantitative Methods skill enables design and execution of statistical analyses including regression modeling, hypothesis testing, power analysis, and robustness checks using R, Stata, SPSS, or Python for rigorous quantitative social science research.

Capabilities

Regression Analysis

  • Linear regression modeling
  • Logistic and multinomial regression
  • Panel data methods
  • Time series analysis
  • Hierarchical/multilevel modeling

Hypothesis Testing

  • Parametric tests
  • Non-parametric alternatives
  • Multiple comparison correction
  • Effect size estimation
  • Confidence interval construction

Power Analysis

  • Sample size determination
  • Effect size specification
  • Power calculation
  • Design optimization
  • Sensitivity analysis

Robustness Checking

  • Specification testing
  • Outlier analysis
  • Assumption verification
  • Alternative estimators
  • Sensitivity analysis

Tool Proficiency

  • R/RStudio workflows
  • Stata programming
  • SPSS procedures
  • Python (statsmodels, scipy)
  • Output visualization

Usage Guidelines

When to Use

  • Designing quantitative studies
  • Analyzing survey data
  • Testing hypotheses
  • Building predictive models
  • Validating findings

Best Practices

  • Pre-register analyses
  • Check assumptions
  • Report fully
  • Conduct robustness checks
  • Document code

Integration Points

  • Causal Inference Methods skill
  • Survey Design and Administration skill
  • Psychometric Assessment skill
  • Mixed Methods Integration skill

References

  • Statistical Analysis Pipeline process
  • Experimental Design process
  • Multilevel/Hierarchical Modeling process
  • Quantitative Research Methodologist agent
我的收藏