svy
svy is a Statistical modelling skill for AI agents, published by DAAF-Contribution-Community in the daaf repository on GitHub. Skillspace rates svy D (66/100) and it passed the safety scan; the rating is based on static analysis only.
Complex survey analysis: strata/PSU/weights, variance estimation (Taylor, BRR, jackknife, bootstrap), survey GLM, domain analysis, calibration, survey data I/O (SAS, SPSS, Stata formats). Polars-native. Use for any complex-sample survey: NHANES, CPS, ACS PUMS, BRFSS, DHS, ECLS-K, MEPS-HC. CRITICAL: statsmodels WLS and pyfixest clustered SEs are NOT substitutes for proper survey-weighted analysis — they ignore stratification and unequal probability sampling. Non-survey regression: statsmodels/pyfixest. R equivalent: survey-r (use when execution language is R).
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 220
Unproven: rated by static analysis only, not yet compared head-to-head.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 84 / 100
- Maturity
- Structured: ships references or scripts
- Security scan
- No issues found
- License
- LGPL-3.0
- Adoption
- Adopted by 0 other repositories, in 0 collections
Not checked yet
- Not judged on the rubric yet (not a contender in its category)
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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