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blocksdesign  

Nested and Crossed Block Designs for Factorial and Unstructured Treatment Sets
View on CRAN: Click here


Download and install blocksdesign package within the R console
Install from CRAN:
install.packages("blocksdesign")

Install from Github:
library("remotes")
install_github("cran/blocksdesign")

Install by package version:
library("remotes")
install_version("blocksdesign", "4.9")



Attach the package and use:
library("blocksdesign")
Maintained by
Rodney Edmondson
[Scholar Profile | Author Map]
First Published: 2014-09-29
Latest Update: 2021-04-07
Description:
Constructs treatment and block designs for linear treatment models with crossed or nested block factors. The treatment design can be any feasible linear model and the block design can be any feasible combination of crossed or nested block factors. The block design is a sum of one or more block factors and the block design is optimized sequentially with the levels of each successive block factor optimized conditional on all previously optimized block factors. D-optimality is used throughout except for square or rectangular lattice block designs which are constructed algebraically using mutually orthogonal Latin squares. Crossed block designs with interaction effects are optimized using a weighting scheme which allows for differential weighting of first and second-order block effects. Outputs include a table showing the allocation of treatments to blocks and tables showing the achieved D-efficiency factors for each block and treatment design. Edmondson, R.N. Multi-level Block Designs for Comparative Experiments. JABES 25, 500
How to cite:
Rodney Edmondson (2014). blocksdesign: Nested and Crossed Block Designs for Factorial and Unstructured Treatment Sets. R package version 4.9, https://cran.r-project.org/web/packages/blocksdesign. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.0 (2014-09-29 07:23), 1.1 (2014-10-03 10:00), 1.2 (2014-11-02 12:36), 1.3 (2014-12-02 00:38), 1.4 (2015-01-13 19:41), 1.5 (2015-03-08 19:15), 1.6 (2015-05-06 14:46), 1.7 (2015-08-21 11:48), 1.8 (2015-10-12 00:20), 1.9 (2015-11-23 12:20), 2.0 (2016-02-07 15:55), 2.1 (2016-03-27 20:43), 2.2 (2016-09-02 02:03), 2.3 (2016-12-09 13:13), 2.4 (2017-01-08 15:42), 2.5 (2017-06-15 17:29), 2.6 (2017-07-18 23:06), 2.7 (2017-09-11 21:54), 2.8 (2018-04-19 01:17), 2.9 (2018-06-12 15:33), 3.0 (2018-07-01 20:00), 3.1 (2018-10-18 13:10), 3.2 (2018-12-18 18:10), 3.3 (2019-01-11 18:00), 3.4 (2019-02-20 18:00), 3.5 (2019-05-28 13:40), 3.6 (2019-10-08 21:30), 3.7 (2019-10-22 10:50), 3.8 (2019-11-03 12:50), 3.9 (2020-02-29 23:40), 4.0 (2020-05-06 18:30), 4.1 (2020-06-01 08:30), 4.2 (2020-06-11 21:00), 4.3 (2020-07-09 20:50), 4.4 (2020-08-28 14:30), 4.5 (2020-10-12 23:30), 4.6 (2020-11-14 20:30), 4.7 (2021-01-12 22:20), 4.8 (2021-02-26 16:20)
Other packages that cited blocksdesign R package
View blocksdesign citation profile
Other R packages that blocksdesign depends, imports, suggests or enhances
Complete documentation for blocksdesign
Functions, R codes and Examples using the blocksdesign R package
Some associated functions: A_bound . GraecoLatin . HCF . MOLS . blocks . blocksdesign-package . design . durban . fraction . isPrime . isPrimePower . nestedBlocks . rectlattice . squarelattice . 
Some associated R codes: A_bound.R . GraecoLatin.R . HCF.R . MOLS.R . blocks.R . blocksdesign-package.R . data.R . design.R . fraction.R . isPrime.R . isPrmePower.R . nestedBlocks.R . rectlattice.R . squarelattice.R .  Full blocksdesign package functions and examples
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