Package: stratamatch 0.1.9

stratamatch: Stratification and Matching for Large Observational Data Sets

A pilot matching design to automatically stratify and match large datasets. The manual_stratify() function allows users to manually stratify a dataset based on categorical variables of interest, while the auto_stratify() function does automatically by allocating a held-aside (pilot) data set, fitting a prognostic score (see Hansen (2008) <doi:10.1093/biomet/asn004>) on the pilot set, and stratifying the data set based on prognostic score quantiles. The strata_match() function then does optimal matching of the data set in parallel within strata.

Authors:Rachael C. Aikens [aut, cre], Joseph Rigdon [aut], Justin Lee [aut], Michael Baiocchi [aut], Jonathan Chen [aut]

stratamatch_0.1.9.tar.gz
stratamatch_0.1.9.zip(r-4.7)stratamatch_0.1.9.zip(r-4.6)stratamatch_0.1.9.zip(r-4.5)
stratamatch_0.1.9.tgz(r-4.6-any)stratamatch_0.1.9.tgz(r-4.5-any)
stratamatch_0.1.9.tar.gz(r-4.7-any)stratamatch_0.1.9.tar.gz(r-4.6-any)
stratamatch_0.1.9.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
stratamatch/json (API)

# Install 'stratamatch' in R:
install.packages('stratamatch', repos = c('https://raikens1.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/raikens1/stratamatch/issues

Datasets:
  • ICU_data - Demographics and comorbidities of 10,157 ICU patients

On CRAN:

Conda:

2.30 score 8 scripts 552 downloads 10 exports 65 dependencies

Last updated from:6f51f1b48a. Checks:8 OK, 1 ERROR. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK155
source / vignettesOK240
linux-release-x86_64OK152
macos-release-arm64OK196
macos-oldrel-arm64OK160
windows-develERROR102
windows-releaseOK98
windows-oldrelOK101
wasm-releaseOK132

Exports:auto_stratifyextract_cut_pointsis.auto_stratais.manual_stratais.stratamake_match_distancesmake_sample_datamanual_stratifysplit_pilot_setstrata_match

Dependencies:backportsbase64encbslibcachemcheckmatecliclustercolorspacecpp11data.tabledigestdplyrevaluatefarverfastmapfontawesomeforeignFormulafsgenericsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMatrixmemoisemimennetpillarpkgconfigR6rappdirsRColorBrewerrlangrmarkdownrpartrstudioapiS7sassscalesstringistringrsurvivaltibbletidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

Introduction to stratamatch
Contents | Introduction and Background | How stratamatch Works | Generating an Example Data Set | How to Stratify a Data Set | Manual Stratification | Automatic Stratification | A note on splitting the pilot set | Alternative methods for automatic stratification. | Diagnostics for Stratified Data Sets | Strata Tables | Issue Tables | Plots | Size-Ratio Plots | Propensity Score Histograms | Assignment-Control Plots for Automatically Stratified Data | Prognostic Model Plots for Automatically Stratified Data | Prognostic Model Diagnostics for Automatically Stratified Data | Matching Stratified Data | References
Rendered fromIntro_to_stratamatch.Rmdusingknitr::rmarkdown

Last update: 2022-03-31
Started: 2019-10-24

Advanced Functionality
Set up | Splitting the pilot set | Fitting the prognostic model | Outcomes: Binary or Continuous | A lasso | An elastic net | A random forest | Alternative matching schemes | Distance measure: Mahalanobis Distance | Matching procedure: Full Matching | Matching with other software | References
Rendered fromAdvanced_functionality.Rmdusingknitr::rmarkdown

Last update: 2022-03-02
Started: 2021-05-26