# Declarative API for Staged Survey Weights

## Documentation for package ‘weightflow’ version 0.2.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

as_svrepdesign | Export weightflow weights to a survey design
as_svydesign | Export weightflow weights to a survey design
bootstrap_estimate | Bootstrap estimate, standard error and confidence interval
bootstrap_weights | Bootstrap replicate weights that re-apply the recipe
boot_mean | Bootstrap estimate, standard error and confidence interval
boot_total | Bootstrap estimate, standard error and confidence interval
collect_replicate_weights | Collect replicate weights into a data frame ready for srvyr
collect_weights | Extract the data with the computed weights
design_effect | Kish design effect from unequal weighting
jackknife_estimate | Jackknife estimate, standard error and confidence interval
jackknife_weights | Delete-a-PSU jackknife replicate weights that re-apply the recipe
jack_mean | Jackknife estimate, standard error and confidence interval
jack_total | Jackknife estimate, standard error and confidence interval
plot.prepped_weighting_spec | Diagnostic plots for the weights
population | Example target population for weightflow
prep | Estimate the weighting cascade
report_weighting | Build a nice HTML report of the weighting recipe
sample_one | Example survey sample (select-one-person, multistage)
sample_survey | Example survey sample (take-all roster)
step_assert | Assert conditions on the weights at this point of the cascade
step_calibrate | Calibration to population totals
step_drop_ineligible | Drop ineligible (out-of-scope) units
step_model_calibration | Model calibration (model-assisted, Wu & Sitter 2001)
step_nonresponse | Nonresponse adjustment
step_rescale | Rescale (normalize) the weights
step_round | Round the final weights
step_select_within | Within-household selection adjustment
step_trim | Trim extreme weights
step_trim_weights | Automatic weight trimming (survey-style)
step_unknown_eligibility | Unknown-eligibility adjustment
summary.prepped_weighting_spec | Detailed per-step diagnostics
weighting_spec | Start a weighting specification
weight_factors | Per-unit adjustment factors table
y_model | Specify a working model for a study variable y