define-variables
FeaturedLiterature-grounded variable operationalization for observational research. Turns a data dictionary + research question into a citation-backed table of exposure/outcome/covariate definitions, cutoffs, and DB variable mappings. Prevents ad-hoc phenotype definitions that invite reviewer rejection. Bridges /search-lit output into /write-protocol Methods.
Install
Quality Score: 95/100
Skill Content
Details
- Author
- Aperivue
- Repository
- Aperivue/medsci-skills
- Created
- 5 months ago
- Last Updated
- 4 days ago
- Language
- Python
- License
- MIT
Bundled in these plugins
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generate-codebook
Generate a citable data dictionary / codebook from a tabular dataset (CSV/TSV/Excel/Parquet/Stata/SAS). Profiles every variable — role, type, units placeholder, level frequencies, range/quantiles, missingness — and emits codebook.md + codebook.json. Flags coded variables whose level meanings are unknown as [NEEDS DICTIONARY] rather than guessing them, feeding /define-variables and the dictionary-first workflow.
lookdnbc
Look up DNBC (Danish National Birth Cohort) study variables by topic across all questionnaire waves. Use this whenever the user asks to find, list, or identify DNBC variables related to a concept (e.g. "find variables about smoking", "which variables cover maternal depression / breastfeeding / infections / childhood adversity?"), asks what variables exist in a given wave, needs variable names, descriptions, or answer labels from the DNBC codebooks, or is deciding which variables to pull during preprocessing. Searches a pre-built dictionary of ~7,900 variables from the Interview 1-4, 7-year, 11-year (child & adult) and 18-year follow-up codebooks and returns matches grouped by wave with each variable's name, description, and value labels. Trigger this even when the user only names a topic and asks "what DNBC variables are there for this?", or references a codebook, a wave, or a variable code such as A018, E_QDATE, Z004_1, or A031_5.
design-study
Study design and validity review for radiology and medical AI research. Identifies analysis unit, cohort logic, leakage risks, comparator design, validation strategy, and reporting guideline fit before drafting or submission.