Survey Standard Error Estimation for Cumulated Estimates and their Differences in Complex Panel De….

surveysd

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.