Skip to contents

surveywts provides tidy tools for calibrating survey weights to known population totals, adjusting for nonresponse, and diagnosing weight quality — all with full weighting history tracking for reproducible survey analysis.

Installation

# From GitHub (development version)
pak::pak("JDenn0514/surveywts")

# From r-universe (pre-built binaries, no GitHub PAT needed)
install.packages("surveywts", repos = "https://jdenn0514.r-universe.dev")

Overview

surveywts is part of the surveyverse ecosystem. It provides three calibration methods, nonresponse adjustment, and weight diagnostics — all using tidy, formula-free syntax.

Function Purpose
calibrate() GREG calibration to population totals
rake() Raking (iterative proportional fitting)
poststratify() Post-stratification to cell counts or proportions
adjust_nonresponse() Nonresponse adjustment via weighting classes
effective_sample_size() ESS (Kish approximation)
weight_variability() CV and design effect of weights
summarize_weights() Summary statistics, optionally by group

Every function tracks the full weighting history so you can audit exactly what transformations were applied and in what order.

Learn more

Full documentation is available at https://jdenn0514.github.io/surveywts/.