Package: imt 1.1.0

Ignacio Martinez

imt: Impact Measurement Toolkit

A toolkit for causal inference in experimental and observational studies. Implements various simple Bayesian models including linear, negative binomial, and logistic regression for impact estimation. Provides functionality for randomization and checking baseline equivalence in experimental designs. The package aims to simplify the process of impact measurement for researchers and analysts across different fields. Examples and detailed usage instructions are available at <https://book.martinez.fyi>.

Authors:Ignacio Martinez [aut, cre]

imt_1.1.0.tar.gz
imt_1.1.0.zip(r-4.7)imt_1.1.0.zip(r-4.6)imt_1.1.0.zip(r-4.5)
imt_1.1.0.tgz(r-4.6-x86_64)imt_1.1.0.tgz(r-4.6-arm64)imt_1.1.0.tgz(r-4.5-x86_64)imt_1.1.0.tgz(r-4.5-arm64)
imt_1.1.0.tar.gz(r-4.7-arm64)imt_1.1.0.tar.gz(r-4.7-x86_64)imt_1.1.0.tar.gz(r-4.6-arm64)imt_1.1.0.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
imt/json (API)

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

Bug tracker:https://github.com/google/imt/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cpp

4.18 score 5 stars 8 scripts 227 downloads 22 exports 120 dependencies

Last updated from:8f96307782. Checks:11 WARNING, 1 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
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linux-devel-x86_64WARNING690
source / vignettesOK570
linux-release-arm64WARNING650
linux-release-x86_64WARNING675
macos-release-arm64WARNING722
macos-release-x86_64WARNING862
macos-oldrel-arm64WARNING509
macos-oldrel-x86_64WARNING750
windows-develWARNING898
windows-releaseWARNING880
windows-oldrelWARNING908
wasm-releaseFAIL229

Exports:%>%balancePlotbasieblmcalculateDIDEffectcalculateEffectSizescheckBaselinecleanDatacountMissingcreateDatacredibleIntervalfitgetStanParameterhedgesGhurdleLogNormallatentLogitlogitmcmcChecksmetaAnalysisnegativeBinomialrandomizerandomizer

Dependencies:abindbackportsbase64encbayesplotBHbslibcachemcallrcaretcheckmateclasscliclockcodetoolscpp11data.tabledescdiagramdigestdistributionaldplyre1071evaluatefarverfastmapfontawesomeforeachfsfuturefuture.applygenericsggplot2ggridgesglobalsgluegowergridExtragtablehardhathighrhtmltoolshtmlwidgetsinlineipredisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglatticelavalifecyclelistenvloolubridatemagrittrMASSMatrixmatrixStatsmemoisemimeModelMetricsnlmennetnumDerivotelparallellypillarpkgbuildpkgconfigplyrposteriorpROCprocessxprodlimprogressrproxypspurrrQuickJSRR6rappdirsRColorBrewerRcppRcppEigenRcppParallelrecipesreshape2rlangrmarkdownrpartrstanrstantoolsS7sassscalesshapesparsevctrsSQUAREMStanHeadersstringistringrsurvivaltensorAtibbletidyrtidyselecttimechangetimeDatetinytextzdbutf8vctrsviridisLitevizdrawswithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
Combine and Unite Columns.combineColumns
Add a Random Treatment Indicator Column to a Data Frame.randomize_internal
Create a Baseline Balance Plot.balancePlot
Computes the BASIE (BAyeSian Interpretation of Estimates) posterior distributionbasie
Bayesian Linear Model Factoryblm
Calculate Probability of Posterior Draws Falling Within a RangecalcProb
Calculate Difference-in-Differences EffectcalculateDIDEffect
Calculate Effect Sizes for Treatment vs. ControlcalculateEffectSizes
Check Baseline Equivalency.checkBaseline
Cleans and prepares data for analysiscleanData
Count missing values (NA) in a dataframecountMissing
Cox's Proportional Hazards Index (Cox's C)coxsIndex
Converts a dataframe into a named list to provide data to a Stan modelcreateData
Calculate credible interval from MCMC drawscredibleInterval
Fits Stan model.fit
Extracts parameter from Stan model.getStanParameter
Hedges' g Effect Size with Pooled Standard DeviationhedgesG
Bayesian Hurdle Log-Normal Model FactoryhurdleLogNormal
Bayesian Logit Model Factorylogit
Calculate logit link and sample from binomial distributionlogitRng
MCMC ChecksmcmcChecks
Create a Meta-Analysis Object Using Data From Previous StudiesmetaAnalysis
Bayesian Negative Binomial Model FactorynegativeBinomial
Calculate Point Estimate (Median or Mean) as PercentagepointEstimate
Randomly Assign Treatment While Controlling for Baseline Equivalencyrandomize
Randomization Class for Treatment Assignmentrandomizer
Validate a Logical Subgroup Vectorvalidate_logical_vector