Multi-stage cluster surveys of households are commonly performed by governments and programmes to monitor population-level demographic, social, economic, and health outcomes. Generally, communities are sampled from subpopulations (strata) in a first stage, and then households are listed and sampled in a second stage. In this typical two-stage design, sampled communities are the Primary Sampling Units (PSUs) and households are the Secondary Sampling Units (SSUs). Census data typically serve as the sample frame from which PSUs are selected. However, if census data are outdated inaccurate, or too geographically course, gridded population data (such as < http://www.worldpop.org.uk>) can be used as a sample frame instead. GridSample generates PSUs from gridded population data according to user-specified complex survey design characteristics and household sample size. In gridded population sampling, like census sampling, PSUs are selected within each stratum using a serpentine sampling method, and can be oversampled in urban or rural areas to ensure a minimum sample size in each of these important sub-domains. Furthermore, because grid cells are uniform in size and shape, gridded population sampling allows for samples to be representative of both the population and of space, which is not possible with a census sample frame.
Grid-based alternative to doing DHS-style survey sample design. An open source R package developed as a WorldPop project.