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