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.
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