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weightflow
1.3.1
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From raw sample to final weights
The weighting cascade
Preparing the sample: eligibility and response before weighting
Nonresponse: weighting classes, propensities and calibration
Calibration: raking, post-stratification and GREG
Ways to specify calibration totals
Model calibration (model-assisted weighting)
Calibrating to a reference survey
Non-probability samples
Trimming survey weights
Machine learning, cross-fitting and robust calibration
Reporting
Documenting and auditing the weights: the quality report
Inspecting and auditing the cascade
weightflow in production (GSBPM 5.6)
Case study
A full weighting pipeline on a real household survey (ECH 2019)
Panels
Rotating panels: net change, chaining and gross flows
Pure panels: the longitudinal weight and gross flows
Coordinated replication: what travels between waves
Composite estimation: borrowing strength from the previous wave
Variance and validation
Variance estimation
Two-phase (double) sampling
Validation against survey and ReGenesees
Reference
Changelog
License
YEAR: 2026 COPYRIGHT HOLDER: Juan Pablo Ferreira
