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.
翻译:R包最佳方案提供一系列功能,高效率地简化简单到复杂的调查中抽样设计过程,使用户能够根据辅助共变值或四分位数对层切分点进行互动界定和调整,利用Neyman或Wright分配,根据每个层分配最佳样本数量进行适应性计算,并根据分层抽样设计选择具体的样本标识。我们利用现实的流行病学研究实例,展示如何最优化地便利设计和实施R调查的有效工作流程。尽管R包适合两或三阶段设计下的多波抽样,但对于任何抽样调查都可能有用。