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.


# Install release version from CRAN

# Install development version from GitHub


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.


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.