Package: SeqAlloc 1.0
Xiaoshu Zhu
SeqAlloc: Sequential Allocation for Prospective Experiments
Potential randomization schemes are prospectively evaluated when units are assigned to treatment arms upon entry into the experiment. The schemes are evaluated for balance on covariates and on predictability (i.e., how well could a site worker guess the treatment of the next unit enrolled).
Authors:
SeqAlloc_1.0.tar.gz
SeqAlloc_1.0.tar.gz(r-4.7-any)SeqAlloc_1.0.tar.gz(r-4.6-any)
SeqAlloc_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
SeqAlloc/json (API)
| # Install 'SeqAlloc' in R: |
| install.packages('SeqAlloc', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:76a7446462. Checks:4 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 98 | ||
| source / vignettes | OK | 206 | ||
| linux-release-x86_64 | OK | 96 | ||
| wasm-release | OK | 81 |
Exports:bcdalloccaitalloccaralloccguesscovimbalMAICimbalSeqAllocSeqAllocplotstratblockallocsummary95WAICimbalweight_x
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Sequential Allocation for Randomized Experiments | SeqAlloc-package |
| Biased Coin Design Allocation | bcdalloc |
| Sequential Allocation for CAIT Method | caitalloc |
| Sequential Allocation Using Covariate Adaptive Randomization | caralloc |
| Evaluate Optimal Guess | cguess |
| Evaluate covariate imbalance using R-squared. | covimbal |
| Maximum Allocation Imbalance for Covariates | MAICimbal |
| Sequential Allocation for Prospective Experiments | SeqAlloc |
| Plot the evaluation criteria for the designs | SeqAllocplot |
| Stratified permuted block allocation | stratblockalloc |
| Find summary statistics | summary95 |
| Weighted Average of Allocation Imbalance for Covariates | WAICimbal |
| Calculate weight matrix from matrix of covariates | weight_x |