skillboardUpdated every 6 hours
skillboardComplex survey analysis: strata/PSU/weights, variance estimation (Taylor, BRR, jackknife, bootstrap), survey GLM, domain analysis, calibration. Polars-native. Use for NHANES, CPS, ACS PUMS, BRFSS, DHS. Non-survey regression: statsmodels/pyfixest.
svy Skill svy: design based analysis of complex survey data in Python. Covers survey design specification (strata, PSU, weights, FPC), variance estimation (Taylor linearization, BRR, jackknife, bootstrap), descriptive estimation (means, totals, proportions, ratios, medians), survey weighted GLM regression (gaussian, binomial, Poisson), domain/subpopulation analysis, calibration, and survey data I/O (SAS, SPSS, Stata). Uses Polars DataFrames natively. Use when analyzing data from complex sample…
Full body not shown for this license – view the source on GitHub →Copy a source-pinned command for your client. You run it yourself.
Destination: .claude/skills/svy · pinned to the source commit
git clone https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills.git
cd Auto-Empirical-Research-Skills
git checkout 692e9fa3fea40bbdf614584d461851f8fb968ac2
mkdir -p ".claude/skills/svy"
cp -r "skills/17-DAAF-Contribution-Community-daaf/dot-claude/skills/svy" ".claude/skills/svy"Review the source before running. This copies files into your project; it is not a one-click install and does not verify runtime safety.
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