weightflow: Declarative API for Staged Survey Weights

Builds survey weights from design base weights by chaining hierarchical adjustments (unknown eligibility, nonresponse and calibration) through a declarative, pipeable, 'tidymodels'-style API. Calibration follows Deville and Sarndal (1992) <doi:10.2307/2290268>. Variances are obtained with a bootstrap that resamples primary sampling units and re-applies the whole recipe on each replicate, following the rescaling bootstrap of Rao and Wu (1988) <doi:10.1080/01621459.1988.10478591>, so the replicate weights carry the variability of every adjustment. The weights also bridge to the 'survey' and 'srvyr' packages for design-based inference.

Package overview README.md Calibration: raking, post-stratification and GREG From raw sample to final weights Machine learning, cross-fitting and robust calibration Model calibration (model-assisted weighting) Nonresponse: weighting classes and propensities Preparing the sample: eligibility and response before weighting Staged survey weighting: the adjustment logic Validation against the survey package Variance estimation Ways to specify calibration totals

Vignettes Man pages API and functions Files

Package details
Author	Juan Pablo Ferreira [aut, cre]
Maintainer	Juan Pablo Ferreira <juanpablo.ferreira@fcea.edu.uy>
License	MIT + file LICENSE
Version	0.2.0
URL	https://github.com/jpferreira33/weightflow https://jpferreira33.github.io/weightflow/
Package repository	View on CRAN
Installation	Install the latest version of this package by entering the following in R: `install.packages("weightflow")`