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

Jasper B. Yang et al.

Journal of Statistical Software2025https://doi.org/10.18637/jss.v114.i10article
ABDC A
Weight
0.41

What the paper says

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 units 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.

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https://doi.org/https://doi.org/10.18637/jss.v114.i10

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@article{jasper2025,
  title        = {{Optimum Allocation for Adaptive Multi-Wave Sampling in R: The R Package optimall}},
  author       = {Jasper B. Yang et al.},
  journal      = {Journal of Statistical Software},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.18637/jss.v114.i10},
}

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

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.