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

Calculate point estimates and their standard errors in complex household surveys using bootstrap replicates. Bootstrapping considers survey design with a rotating panel. A comprehensive description of the methodology can be found under <>.

Build Status Lifecycle: maturing GitHub last commit GitHub code size in bytes

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.


Like any other R package on github, this package can be installed via install_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.

  • 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.


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.


1.0.0 by Johannes Gussenbauer, a month ago

Report a bug at

Browse source code at

Authors: Johannes Gussenbauer [aut, cre] , Alexander Kowarik [aut] , Gregor de Cillia [aut] , Matthias Till [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports Rcpp, data.table, matrixStats, ggplot2, laeken, methods, dplyr

Suggests testthat, simPop

Linking to Rcpp

See at CRAN