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NPBBBdesigns
View on CRAN: Click
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Download and install NPBBBdesigns package within the R console
Install from CRAN:
install.packages("NPBBBdesigns")
Install from Github:
library("remotes")
install_github("cran/NPBBBdesigns") Install by package version:
library("remotes")
install_version("NPBBBdesigns", "1.0.0") Attach the package and use:
library("NPBBBdesigns")
Maintained by
Vinayaka
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First Published: 2026-07-04
Latest Update: 2026-07-04
Description:
Construction and evaluation of nested partially balanced bipartite block (NPBBB) designs for comparing a set of test treatments with a set of control treatments under a nested (blocks within blocks) structure. Six systematic construction methods are provided: composing partially balanced bipartite block designs with nested balanced incomplete block designs; augmenting nested partially balanced incomplete block designs with controls; merging rows of group-divisible nested designs; direct construction from group-divisible schemes; and expansion of partially balanced incomplete block designs (Vinayaka et al. 2026: In press). The A-efficiencies of the block and sub-block classifications are computed against the A-optimal completely symmetric reference design, following the test-versus-control optimality framework of Gupta and Parsad (1996) <doi:10.1080/03610929608831743> and Vinayaka et al. (2024) <doi:10.1080/03610926.2023.2251623>. These designs are particularly suited to agricultural, animal husbandry, industrial, and clinical trials involving multiple standard checks under nested experimental conditions, such as multi-environment trials where field heterogeneity (blocks) and within-field variation (sub-blocks) must be controlled simultaneously.
How to cite:
Vinayaka (2026). NPBBBdesigns: Construction and a-Efficiency of Nested Partially Balanced Bipartite Block Designs. R package version 1.0.0, https://cran.r-project.org/web/packages/NPBBBdesigns. Accessed 24 Oct. 2026.
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