as_svydesign            Export weightflow weights to a survey design
bootstrap_estimate      Bootstrap estimate, standard error and
                        confidence interval
bootstrap_weights       Recipe-aware bootstrap replicate weights
collect_propensities    Recover the fitted response propensities of a
                        nonresponse step
collect_replicate_weights
                        Collect replicate weights into a data frame
                        ready for srvyr
collect_step_detail     Per-unit detail of one step of the cascade
collect_weights         Extract the data with the computed weights
design_effect           Kish design effect from unequal weighting
domain_summary          Per-domain weight summary at every stage of the
                        cascade
jackknife_estimate      Jackknife estimate, standard error and
                        confidence interval
jackknife_weights       Recipe-aware delete-a-PSU jackknife replicate
                        weights
plot.prepped_weighting_spec
                        Diagnostic plots for the weights
population              Synthetic target population (sampling frame)
prep                    Estimate the weighting cascade
print.weightflow_boot   Print a bootstrap replicate-weight object
print.weightflow_jack   Print a jackknife replicate-weight object
report_weighting        Self-contained HTML quality report for a
                        weighting recipe
sample_one              Synthetic address sample with one selected
                        person per household
sample_survey           Synthetic person sample with a take-all
                        household roster
step_assert             Assert quality conditions on the weights
step_calibrate          Calibration to population totals
step_drop_ineligible    Drop ineligible (out-of-scope) units
step_model_calibration
                        Model-assisted calibration (Wu and Sitter 2001)
step_nonresponse        Nonresponse adjustment
step_rescale            Rescale the weights to a fixed sum
step_round              Round the final weights
step_select_within      Within-cluster selection adjustment
step_trim               Trim extreme weights against a ratio
step_trim_calibrated    Trimmed calibration (range-restricted,
                        totals-preserving)
step_trim_weights       Automatic weight trimming to an absolute band
step_unknown_eligibility
                        Unknown-eligibility adjustment
summary.prepped_weighting_spec
                        Detailed per-step diagnostics
weight_factors          Per-unit adjustment factors table
weightflow-concepts     Conventions shared by every weightflow step
weighting_spec          Start a weighting specification
y_model                 Specify a working model for a study variable y
