  The R package optimall offers a collection of functions that efficiently
streamline the design process of sampling in surveys ranging from simple to
complex. The package's main functions allow users to interactively define and
adjust strata cut points based on values or quantiles of auxiliary covariates,
adaptively calculate the optimum number of samples to allocate to each stratum
using Neyman or Wright allocation, and select specific IDs to sample based on a
stratified sampling design. Using real-life epidemiological study examples, we
demonstrate how optimall facilitates an efficient workflow for the design and
implementation of surveys in R. Although tailored towards multi-wave sampling
under two- or three-phase designs, the R package optimall may be useful for any
sampling survey.
