Package: vecmatch 1.3.0.9000

vecmatch: Generalized Propensity Score Estimation and Matching for Multiple Groups

Implements the Vector Matching algorithm to match multiple treatment groups based on previously estimated generalized propensity scores. The package includes tools for visualizing initial confounder imbalances, estimating treatment assignment probabilities using various methods, defining the common support region, performing matching across multiple groups, and evaluating matching quality. For more details, see Lopez and Gutman (2017) <doi:10.1214/17-STS612>.

Authors:Mateusz Kolek [aut, cre, cph]

vecmatch_1.3.0.9000.tar.gz
vecmatch_1.3.0.9000.zip(r-4.7)vecmatch_1.3.0.9000.zip(r-4.6)vecmatch_1.3.0.9000.zip(r-4.5)
vecmatch_1.3.0.9000.tgz(r-4.6-any)vecmatch_1.3.0.9000.tgz(r-4.5-any)
vecmatch_1.3.0.9000.tar.gz(r-4.7-any)vecmatch_1.3.0.9000.tar.gz(r-4.6-any)
vecmatch_1.3.0.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
vecmatch/json (API)

# Install 'vecmatch' in R:
install.packages('vecmatch', repos = c('https://polymerase3.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/polymerase3/vecmatch/issues

Datasets:
  • cancer - Patients with Colorectal Cancer and Adenoma

On CRAN:

Conda:

5.32 score 3 stars 5 scripts 286 downloads 13 exports 92 dependencies

Last updated from:bc0ba937bc (on main). Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK226
source / vignettesOK570
linux-release-x86_64OK270
macos-release-arm64OK269
macos-oldrel-arm64OK180
windows-develOK146
windows-releaseOK159
windows-oldrelOK154
wasm-releaseOK180

Exports:balqualcsregionestimate_gpsget_select_paramshspinemake_opt_argsmatch_gpsmosaicoptimize_gpsraincloudrun_selected_matchingselect_optvspine

Dependencies:abindbackportsbootbroomcarcarDatachkclicodetoolscolorspacecorrplotcowplotcpp11DerivdigestdoBydplyrfarverforeachforecastFormulafracdiffgenericsggplot2ggppggpubrggrepelggsciggsignifgluegridExtragtableisobanditeratorslabelinglatticelifecyclelme4lmtestlubridatemagrittrMASSMatchingMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrnlmenloptrnnetnumDerivoptmatchpbkrtestpillarpkgconfigplyrpolynomproductplotsprogressrpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrlemonrstatixS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDateurcautf8vctrsviridisLitewithrxtszoo

Optimizing the Matching Process with a Random Search Algorithm
Practical Example: Optimizing the Matching Process | Step 2: Run the Optimizer | Step 3: Select Optimal Configurations | Step 4: Refit the Optimized Model
Rendered fromoptimizing-matching.Rmdusingknitr::rmarkdown

Last update: 2025-12-01
Started: 2025-06-17

Matching Patients in the cancer Dataset with vecmatch
Practical Example of the Vector Matching Workflow | Step 1: Data Exploration and Initial Imbalance Assessment | Step 2: Estimation of Generalized Propensity Scores | Step 3: Calculating Common Support Region Borders | Step 4: k-Means Clustering and Matching | Step 5: Post-Matching Quality Assessment | References
Rendered fromvecmatch.Rmdusingknitr::rmarkdown

Last update: 2025-04-24
Started: 2024-12-23