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tightenBlock  

Tightens an Observational Block Design by Balanced Subset Matching
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("tightenBlock", "0.1.7")



Attach the package and use:
library("tightenBlock")
Maintained by
Paul Rosenbaum
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-12-15
Latest Update: 2023-12-15
Description:
Tightens an observational block design into a smaller design with either smaller or fewer blocks while controlling for covariates. The method uses fine balance, optimal subset matching (Rosenbaum, 2012 <doi:10.1198/jcgs.2011.09219>) and two-criteria matching (Zhang et al 2023 <doi:10.1080/01621459.2021.1981337>).The main function is tighten().The suggested 'rrelaxiv' package for solving minimum cost flow problems: (i) derives from Bertsekas and Tseng (1988) <doi:10.1007/BF02288322>, (ii) is not available on CRAN due to its academic license, (iii) may be downloaded from GitHub at <https://github.com/josherrickson/rrelaxiv/>, (iv) is not essential to use the package.
How to cite:
Paul Rosenbaum (2023). tightenBlock: Tightens an Observational Block Design by Balanced Subset Matching. R package version 0.1.7, https://cran.r-project.org/web/packages/tightenBlock. Accessed 05 Jan. 2025.
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Complete documentation for tightenBlock
Functions, R codes and Examples using the tightenBlock R package
Some associated functions: aHDLt . addMahal . addNearExact . makematch . makenetwork . startcost . tighten . tightenBlock-package . 
Some associated R codes: addMahal.R . addNearExact.R . makematch.R . makenetwork.R . startcost.R . tighten.R .  Full tightenBlock package functions and examples
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