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) is implemented. 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.

Package details

AuthorMark Myatt [aut], Ernest Guevarra [aut, cre] (<https://orcid.org/0000-0002-4887-4415>)
MaintainerErnest Guevarra <ernestgmd@gmail.com>
LicenseGPL-3
Version0.2.0
URL https://github.com/rapidsurveys/bbw https://rapidsurveys.io/bbw/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("bbw")

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bbw documentation built on May 30, 2022, 9:10 a.m.