Workflow-Oriented Survey Weight Calibration

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Documentation for package ‘WFC’ version 2.0.1

Help Pages

as.data.frame.wf_quality_report Convert a weighting quality report to a data frame
as.data.frame.wf_variance_result Coerce a variance result to a data frame
as_svrepdesign Convert WFC replicate weights to a survey replicate design
as_svydesign Convert WFC weights to a survey design
augment.wf_weights Broom-style projections for WFC results
glance.wf_blend_result Broom-style projections for WFC results
glance.wf_diagnostics Broom-style projections for WFC results
glance.wf_variance_result Broom-style projections for WFC results
glance.wf_weights Broom-style projections for WFC results
plot.wf_auto_trim Plot an automatic trim frontier
plot.wf_blend_result Plot blend lambda sensitivity
plot.wf_diagnostics Plot weight diagnostics
plot.wf_propensity_weights Plot propensity overlap and covariate balance
plot.wf_weights Plot calibrated weight distributions
print.wf_attrition_weights Print attrition weights
print.wf_autoweigh_result Print a guided weighting result
print.wf_auto_trim Print an automatic trim recommendation
print.wf_blend_result Print a blend result.
print.wf_cell_merge_plan Print an outcome-blind cell merge plan
print.wf_collapse_plan Print a collapse plan
print.wf_design_data Print outcome-free survey design data
print.wf_diagnostics Print diagnostics
print.wf_impact Print post-lock outcome impact
print.wf_influence Print influence diagnostics
print.wf_ladder_draft Print a collapse-ladder draft
print.wf_pipeline Print a pipeline specification
print.wf_poststrat_plan Print a post-stratification plan
print.wf_precheck Print a precheck result
print.wf_quality_report Print a weighting quality report
print.wf_replicate_weights Print replicate weights
print.wf_validation Print a weight-validation result
print.wf_variance_result Print a variance result
print.wf_weights Print calibrated weights
print.wf_weight_plan Print a reviewable weight plan
summary.wf_poststrat_plan Summarize a post-stratification plan
tidy.wf_blend_result Broom-style projections for WFC results
tidy.wf_diagnostics Broom-style projections for WFC results
tidy.wf_variance_result Broom-style projections for WFC results
tidy.wf_weights Broom-style projections for WFC results
wfc-tidiers Broom-style projections for WFC results
wfc_example Simulated survey weighting example data
wf_apply_collapse Apply a category collapse plan
wf_approve_plan Record a human attestation for a reviewed weight plan
wf_assess_impact Assess descriptive outcome impact after weights are locked
wf_attach_weights Attach locked weights to analysis data by exact unit ID
wf_attrition Estimate panel attrition weights
wf_audit_export Export a self-contained WFC audit file
wf_autoweigh Run a guided workflow from verified design and target objects
wf_auto_trim Recommend a weight-trimming cap
wf_blend Blend online and offline calibrated estimates
wf_calibrate Calibrate weights from verified design and target objects
wf_collapse_ladder Declare a post-stratification collapse ladder
wf_compose Compose multiple weighting stages
wf_diagnose Diagnose calibrated weights
wf_dims Declare calibration dimensions
wf_execute_plan Execute an approved plan and lock its weights
wf_guided_execute Execute a guided workflow with an external human approval
wf_guided_plan Prepare a guided safe weighting workflow
wf_import_reference Import a verified external reference-sample target
wf_import_target Import a verified external population target
wf_influence Diagnose high-influence calibrated units
wf_pipeline Declare a production weighting pipeline
wf_plan_cells Plan deterministic, outcome-blind support-cell merging
wf_plan_poststrat Plan post-stratification cell resolution
wf_plan_weights Build a reviewable outcome-blind weight plan
wf_poststrat Post-stratify verified design data to a verified joint target
wf_precheck Precheck sample and target compatibility
wf_prepare_design Prepare outcome-free survey design data
wf_propensity Correct a non-probability sample by inverse-propensity pseudo-weighting.
wf_rake Rake verified design data to a verified external target
wf_replicates Generate re-calibrated replicate weights for variance estimation.
wf_report Build a weighting quality report
wf_run Run a production weighting pipeline
wf_suggest_collapse Suggest collapse plans from precheck findings
wf_suggest_ladder Draft a post-stratification collapse ladder
wf_target_population Target from external population data
wf_target_propensity Build a propensity target: stacked reference frame and membership model spec.
wf_target_reference Target from a weighted reference sample
wf_target_template Create a safe external-target import template
wf_validate Compare calibrated weights against a reference release
wf_variance Combine replicate weights and an estimator into a variance and CI.