Optimum Allocation for Adaptive Multi-Wave Sampling in R: The R Package optimall

Area of Science:

• Statistics
• Survey Methodology
• Computational Statistics

Background:

• Designing complex surveys requires efficient and adaptable tools.
• Traditional survey design methods can be time-consuming and lack flexibility.
• Implementing stratified sampling designs presents unique challenges.

Purpose of the Study:

• To introduce the R package optimall for streamlining survey sampling design.
• To provide functions for interactive strata definition and sample allocation.
• To demonstrate the utility of optimall in real-world epidemiological surveys.

Main Methods:

• Utilizing R programming for statistical analysis and survey design.
• Implementing functions for interactive strata cut point adjustment.
• Applying Neyman and Wright allocation methods for optimal sample size determination.
• Demonstrating stratified sampling unit selection within the R environment.

Main Results:

• The optimall package offers efficient functions for survey design.
• Interactive adjustment of strata cut points based on auxiliary covariates is supported.
• Adaptive calculation of optimal sample allocation per stratum is enabled.
• The package facilitates the design and implementation of complex survey sampling.

Conclusions:

• The optimall R package provides a comprehensive solution for survey sampling design.
• It enhances efficiency and flexibility in defining strata and allocating samples.
• Optimall is valuable for various survey types, including multi-wave and multi-phase designs.