Package: causalBatch 1.4.0
Eric W. Bridgeford
causalBatch: Causal Batch Effects
Software which provides numerous functionalities for detecting and removing group-level effects from high-dimensional scientific data which, when combined with additional assumptions, allow for causal conclusions, as-described in our manuscripts Bridgeford et al. (2024) <doi:10.1101/2021.09.03.458920> and Bridgeford et al. (2023) <doi:10.48550/arXiv.2307.13868>. Also provides a number of useful utilities for generating simulations and balancing covariates across multiple groups/batches of data via matching and propensity trimming for more than two groups.
Authors:
causalBatch_1.4.0.tar.gz
causalBatch_1.4.0.zip(r-4.7)causalBatch_1.4.0.zip(r-4.6)causalBatch_1.4.0.zip(r-4.5)
causalBatch_1.4.0.tgz(r-4.6-any)causalBatch_1.4.0.tgz(r-4.5-any)
causalBatch_1.4.0.tar.gz(r-4.7-any)causalBatch_1.4.0.tar.gz(r-4.6-any)
causalBatch_1.4.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
causalBatch/json (API)
| # Install 'causalBatch' in R: |
| install.packages('causalBatch', repos = c('https://neurodata.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/neurodata/causal_batch/issues
Last updated from:b73e581699. Checks:8 ERROR, 1 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | ERROR | 252 | ||
| source / vignettes | ERROR | 316 | ||
| linux-release-x86_64 | ERROR | 272 | ||
| macos-release-arm64 | ERROR | 267 | ||
| macos-oldrel-arm64 | ERROR | 224 | ||
| windows-devel | ERROR | 223 | ||
| windows-release | ERROR | 280 | ||
| windows-oldrel | ERROR | 231 | ||
| wasm-release | OK | 168 |
Exports:cb.align.kway_matchcb.align.vm_trimcb.correct.aipw_cComBatcb.correct.apply_aipw_cComBatcb.correct.apply_cComBatcb.correct.matching_cComBatcb.detect.caus_cdcorrcb.sims.cate.heteroskedastic_simcb.sims.cate.kclass_sigmoidal_simcb.sims.cate.nonmonotone_simcb.sims.cate.sigmoidal_simcb.sims.sim_impulsecb.sims.sim_impulse_asycovcb.sims.sim_linearcb.sims.sim_sigmoid
Dependencies:annotateAnnotationDbiaskpassbackportsBHBiobaseBiocGenericsBiocParallelBiostringsbitbit64blobbootcachemcdcsischkclicodetoolscpp11crayoncubaturecurlDBIdplyredgeRfastmapFNNformatRfutile.loggerfutile.optionsgenefiltergenericsgluehttrIRangesjsonliteKEGGRESTkernlabKernSmoothkslambda.rlatticelifecyclelimmalocfitmagrittrMASSMatchItMatrixMatrixGenericsMatrixModelsmatrixStatsmclustmemoisemgcvmimemulticoolmvtnormnlmennetnpopensslpillarpkgconfigpngpracmaquadprogquantregR6RcppRcppProgressrlangRSQLiteS4VectorsSeqinfosnowSparseMstatmodsurvivalsvasystibbletidyselectutf8vctrswithrXMLxtableXVector
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| K-Way matching | cb.align.kway_match |
| Vector Matching | cb.align.vm_trim |
| Augmented Inverse Probability Weighting Conditional ComBat | cb.correct.aipw_cComBat |
| Fit AIPW ComBat model for batch effect correction | cb.correct.apply_aipw_cComBat |
| Adjust for batch effects using an empirical Bayes framework | cb.correct.apply_cComBat |
| Matching Conditional ComBat | cb.correct.matching_cComBat |
| Causal Conditional Distance Correlation | cb.detect.caus_cdcorr |
| Simulate Data with Heteroskedastic Conditional Average Treatment Effects | cb.sims.cate.heteroskedastic_sim |
| K-class Sigmoidal CATE Simulation | cb.sims.cate.kclass_sigmoidal_sim |
| Non-monotone CATE Simulation | cb.sims.cate.nonmonotone_sim |
| Sigmoidal CATE Simulation | cb.sims.cate.sigmoidal_sim |
| Impulse Simulation | cb.sims.sim_impulse |
| Impulse Simulation with Asymmetric Covariates | cb.sims.sim_impulse_asycov |
| Linear Simulation | cb.sims.sim_linear |
| Sigmoidal Simulation | cb.sims.sim_sigmoid |
