Scientific Knowledge Base
Understand every method, from first step to algorithm.
Practical workflows, methodological reasoning, equations, implementation details, verified references, and honest validation boundaries.
Transparent by designDocumentation maps public methods to the code, tests, estimators, defaults, and benchmark evidence actually in Surv.lytics.
01
Getting started11 articles
02Methodology guide4 articles
03Technical & algorithm documentation12 articles
Library
Clear filters 5 published articles
Understand variable types and measurement levels
Review detected numeric, text, categorical, ordinal, and scale-like variables before analysis.
Review missing data
Inspect missing counts and patterns before choosing a handling strategy.
Review potential outliers
Use distribution and quality evidence to identify observations that need researcher review.
Reverse coding and composite scores
Prepare consistently oriented indicators and construct scores through explicit transformations.
Data-quality algorithms and transformations
Technical inventory of missingness, distribution, response-pattern, multicollinearity and controlled transformation algorithms.