Package index • svrep

Convert a Survey Design Object to a Data Frame

as_data_frame_with_weights(): Convert Survey Design to Data Frame

Nonresponse Adjustments

redistribute_weights(): Weighting Class Adjustment

Creating Bootstrap Replicate Weights

as_bootstrap_design(): Convert Survey Design to Bootstrap Replicate Design

make_doubled_half_bootstrap_weights(): Weights for "Doubled Half Bootstrap" of Antal and Tillé (2014)

make_rwyb_bootstrap_weights(): Weights for Rao-Wu-Yue-Beaumont Bootstrap

estimate_boot_reps_for_target_cv(): Control Bootstrap Simulation Error

estimate_boot_sim_cv(): Estimate Bootstrap Simulation Error

Generalized Replication Method (including the Generalized Bootstrap)

Fay’s Generalized Replication Method

as_fays_gen_rep_design(): Convert Survey Design to Fay's Generalized Replication Design

make_fays_gen_rep_factors(): Factors for Fay's Generalized Replication Method

Generalized Bootstrap

as_gen_boot_design(): Convert Survey Design to Generalized Bootstrap Replicate Design

make_gen_boot_factors(): Factors for the Generalized Survey Bootstrap

Variance Estimators Available for the Generalized Replication Methods

The generalized replication methods (Fay’s method and the generalized bootstrap) work by “mimicking” a target variance estimator, such as the Horvitz-Thompson estimator. This help page describes the variance estimators that can be used as the target for the generalized replication methods.

variance-estimators: Variance Estimators

Helper Functions for Working with Quadratic Forms

These functions help the user specify the quadratic form representation of common variance estimators and, if necessary, adjust them so that they are positive semidefinite (a necessary prerequisite for using the generalized replication methods).

get_design_quad_form(): Quadratic Form Matrix of Variance Estimator for a Survey Design

make_quad_form_matrix(): Get Variance Estimator's Quadratic Form Matrix

make_twophase_quad_form(): Quadratic Form Matrix for a Two-phase Design

get_nearest_psd_matrix(): Positive Semidefinite Matrix Approximation

is_psd_matrix(): Check if Matrix is Positive Semidefinite

make_kernel_var_matrix(): Quadratic Form Matrix of Kernel-based Variance Estimator

Creating Jackknife Replicate Weights

as_random_group_jackknife_design(): Convert Survey Design to Random Group Jackknife Replicate Design

Create Replicate Weights Using Successive Differences Replication

as_sdr_design(): Convert Survey Design to Successive Differences Replicate Design

make_sdr_replicate_factors(): Factors for the Successive Difference Replication Method

Calibrating to Estimated Control Totals

calibrate_to_estimate(): Sample-based Calibration to An Estimate

calibrate_to_sample(): Sample-based Calibration with Replicates

General-Purpose Helper Functions

shuffle_replicates(): Shuffle Order of Replicates in a Replicate Design Object

stack_replicate_designs(): Combine Replicate Designs by Stacking

subsample_replicates(): Subsample Replicates in a Replicate Design Object

rescale_replicates(): Rescale Replicate Factors

add_inactive_replicates(): Add Inactive Replicates to a Survey Design Object

svyby_repwts(): Survey Statistics for Multiple Replicate Design Objects

Diagnostic Functions to Check Replicate Weights

summarize_rep_weights(): Summarize Replicate Weights in a Replicate Design

Package-level Options

svrep-package-options: Package-level Options for svrep

Example Datasets

lou_pums_microdata: Auxiliary Data for Louisville Vaccination Survey

lou_vax_survey: Data of Louisville Vaccination Survey

lou_vax_survey_control_totals: Control Totals for Louisville Vaccination Survey

library_census library_multistage_sample library_stsys_sample: U.S. Public Libraries Survey