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.
- The methodology is covered in the methodology vignette.
- A more comprehensive documentation of
calc.stError()is available in the error estimation vignette.
