How does it ensure research reproducibility?

The skill enforces a strict folder structure, uses Git for version control across analysis phases, and produces a master script to ensure the entire pipeline can be rerun from raw data to final tables.

Can it produce charts and tables for my manuscript?

Yes, it is designed to create publication-quality outputs using libraries like modelsummary, etable, and ggplot2, covering everything from coefficient plots to marginal effects.

What types of statistical models can it handle?

It supports a wide range of social science methods, including Difference-in-Differences (DiD), Instrumental Variables (IV), matching, panel fixed effects, Bayesian sensitivity analysis, and nonlinear models like Logit or Poisson.

Does this skill require existing R knowledge?

The skill functions as a collaborative expert assistant. While it automates complex coding and implementation, the user provides the substantive domain expertise and makes the final research decisions.

R Statistical Analyst for Sociology

Name: R Statistical Analyst for Sociology
Author: nealcaren

bynealcaren

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データサイエンスとML

Conducts publication-ready quantitative sociological research using phased R workflows and rigorous econometric methods.

The R Analyst skill transforms Claude into a specialized quantitative research assistant tailored for high-stakes academic sociology. It guides researchers through a structured six-phase lifecycle—from initial identification strategy and data familiarization to advanced model specification, robustness testing, and the generation of publication-quality tables and figures. By integrating best practices in reproducibility and causal inference, it ensures that every analysis is methodologically sound, fully documented via Git, and ready for submission to top-tier social science journals.

主な機能

01Support for advanced econometrics including DiD, IV, matching, and panel methods

02Reproducible project management with Git-tracked phases and master scripts

03Structured six-phase analysis workflow from research design to final output

04Built-in sensitivity analysis and robustness checking protocols

05Automated generation of publication-quality tables and ggplot2 visualizations

063 GitHub stars

ユースケース

01Executing a rigorous Difference-in-Differences (DiD) analysis for a policy evaluation paper

02Generating descriptive statistics and data quality reports for large-scale social surveys

03Conducting sensitivity tests and placebo checks to validate causal claims in a manuscript

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nealcaren/sociology-skillset r-analyst

For use in Claude.ai and ChatGPT

Download Skill