bbw: Blocked Weighted Bootstrap

The blocked weighted bootstrap (BBW) is an estimation technique for use with data from two-stage cluster sampled surveys in which either prior weighting (e.g. population-proportional sampling or PPS as used in Standardized Monitoring and Assessment of Relief and Transitions or SMART surveys) or posterior weighting (e.g. as used in rapid assessment method or RAM and simple spatial sampling method or S3M surveys). The method was developed by Accion Contra la Faim, Brixton Health, Concern Worldwide, Global Alliance for Improved Nutrition, UNICEF Sierra Leone, UNICEF Sudan and Valid International. It has been tested by the Centers for Disease Control (CDC) using infant and young child feeding (IYCF) data. See Cameron et al (2008) <doi:10.1162/rest.90.3.414> for application of bootstrap to cluster samples. See Aaron et al (2016) <doi:10.1371/journal.pone.0163176> and Aaron et al (2016) <doi:10.1371/journal.pone.0162462> for application of the blocked weighted bootstrap to estimate indicators from two-stage cluster sampled surveys.

Version: 0.1.3
Depends: R (≥ 3.0.1)
Imports: car
Suggests: knitr, rmarkdown, testthat
Published: 2018-01-17
Author: Mark Myatt [aut], Ernest Guevarra [ctb, cre]
Maintainer: Ernest Guevarra <ernestgmd at gmail.com>
BugReports: https://github.com/validmeasures/bbw/issues
License: AGPL-3
URL: https://github.com/validmeasures/bbw
NeedsCompilation: no
Materials: README NEWS
CRAN checks: bbw results

Downloads:

Reference manual: bbw.pdf
Vignettes: Blocked Weighted Bootstrap
Package source: bbw_0.1.3.tar.gz
Windows binaries: r-devel: bbw_0.1.3.zip, r-release: bbw_0.1.3.zip, r-oldrel: bbw_0.1.3.zip
OS X binaries: r-release: bbw_0.1.3.tgz, r-oldrel: not available

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