Implements a heuristic algorithm to build blocks of a given size aiming to maximize similarity within strata across multiple covariates. The blocking structure can be used for causal inference and for sensitivity analysis to unmeasured confounding. A stratified structure gives more flexibility for using multiple instrumental variables and direct treatment vs. control analysis as evidence factors. Karmakar, B., Small, D. S., and Rosenbaum, P. R. (2018). Rosenbaum, P. R. (2010)<ISBN:978-1-4419-1213-8>.
| Version: | 1.0 |
| Suggests: | MASS |
| Enhances: | optmatch |
| Published: | 2018-09-21 |
| Author: | Bikram Karmakar |
| Maintainer: | Bikram Karmakar <bikramk at wharton.upenn.edu> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| CRAN checks: | blockingChallenge results |
| Reference manual: | blockingChallenge.pdf |
| Package source: | blockingChallenge_1.0.tar.gz |
| Windows binaries: | r-devel: blockingChallenge_1.0.zip, r-release: blockingChallenge_1.0.zip, r-oldrel: blockingChallenge_1.0.zip |
| OS X binaries: | r-release: not available, r-oldrel: not available |
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