Package: svyweight 0.1.0

svyweight: Quick and Flexible Survey Weighting

Quickly and flexibly calculates weights for survey data, in order to correct for survey non-response or other sampling issues. Uses rake weighting, a common technique also know as rim weighting or iterative proportional fitting. This technique allows for weighting on multiple variables, even when the interlocked distribution of the two variables is not known. Interacts with Thomas Lumley's 'survey' package, as described in Lumley, Thomas (2011, ISBN:978-1-118-21093-2). Adds additional functionality, more adaptable syntax, and error-checking to the base weighting functionality in 'survey.'

Authors:Ben Mainwaring [aut, cre]

svyweight_0.1.0.tar.gz
svyweight_0.1.0.zip(r-4.5)svyweight_0.1.0.zip(r-4.4)svyweight_0.1.0.zip(r-4.3)
svyweight_0.1.0.tgz(r-4.4-any)svyweight_0.1.0.tgz(r-4.3-any)
svyweight_0.1.0.tar.gz(r-4.5-noble)svyweight_0.1.0.tar.gz(r-4.4-noble)
svyweight_0.1.0.tgz(r-4.4-emscripten)svyweight_0.1.0.tgz(r-4.3-emscripten)
svyweight.pdf |svyweight.html
svyweight/json (API)

# Install 'svyweight' in R:
install.packages('svyweight', repos = c('https://mainwaringb.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/mainwaringb/svyweight/issues

Datasets:
  • gles17 - Partial Data from the 2017 German Election Survey

On CRAN:

rakesamplingsurveyweighting

7 exports 2 stars 0.83 score 12 dependencies 1 scripts 127 downloads

Last updated 2 years agofrom:6c89bf0dd8. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 27 2024
R-4.5-winNOTEAug 27 2024
R-4.5-linuxNOTEAug 27 2024
R-4.4-winNOTEAug 27 2024
R-4.4-macNOTEAug 27 2024
R-4.3-winOKAug 27 2024
R-4.3-macOKAug 27 2024

Exports:as.w8margineff_nimpute_w8marginrakesvyrakew8w8margin_matchedweight_eff

Dependencies:DBIgdatagtoolslatticeMatrixminqamitoolsnumDerivRcppRcppArmadillosurveysurvival