surveysd

Survey Standard Error Estimation for Cumulated Estimates and their Differences in Complex Panel Designs


Keywords
bootstrap, error-estimation, r, survey
Licenses
CNRI-Python-GPL-Compatible/CNRI-Python-GPL-Compatible

Documentation

surveysd

Travis build status Coverage Status Lifecycle: stable GitHub last commit GitHub code size in bytes Downloads CRAN

Mentioned in Awesome Official Statistics

This is the development place for the R-package surveysd. The package can be used to estimate the standard deviation of estimates in complex surveys using bootstrap weights.

Installation

# Install release version from CRAN
install.packages("surveysd")

# Install development version from GitHub
devtools::install_github("statistikat/surveysd")

Concept

Bootstrapping has long been around and used widely to estimate confidence intervals and standard errors of point estimates. This package aims to combine all necessary steps for applying a calibrated bootstrapping procedure with custom estimating functions.

Workflow

A typical workflow with this package consists of three steps. To see these concepts in practice, please refer to the getting started vignette.

  • Calibrated weights can be generated with the function ipf() using an iterative proportional updating algorithm.
  • Bootstrap samples are drawn with rescaled bootstrapping in the function draw.bootstrap().
  • These samples can then be calibrated with an iterative proportional updating algorithm using recalib().
  • Finally, estimation functions can be applied over all bootstrap replicates with calc.stError().

Further reading

More information can be found on the github-pages site for surveysd.