Package: inferference 1.0.3

Bradley Saul

inferference: Methods for Causal Inference with Interference

Provides methods for estimating causal effects in the presence of interference described in B. Saul and M. Hugdens (2017) <doi:10.18637/jss.v082.i02>. Currently it implements the inverse-probability weighted (IPW) estimators proposed by E.J. Tchetgen Tchetgen and T.J. Vanderweele (2012) <doi:10.1177/0962280210386779>.

Authors:Bradley Saul [aut, cre]

inferference_1.0.3.tar.gz
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inferference_1.0.3.tgz(r-4.6-any)inferference_1.0.3.tgz(r-4.5-any)
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inferference_1.0.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
inferference/json (API)

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

Bug tracker:https://github.com/cranhaven/cranhaven.r-universe.dev/issues

Datasets:

On CRAN:

Conda:

archivedpackagesr-universe

4.44 score 5 stars 55 scripts 533 downloads 18 exports 32 dependencies

Last updated from:3fedca353c (on package/inferference). Checks:7 ERROR, 2 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-develERROR139
source / vignettesOK207
linux-releaseERROR136
macos-releaseERROR91
macos-oldrelERROR117
windows-develERROR210
windows-releaseERROR182
windows-oldrelERROR198
wasm-releaseOK94

Exports:diagnose_weightsdirect_effectget_argsieindirect_effectinterferencelog_likelihoodlogit_integrandoeoverall_effectscore_calcscore_matrixtetotal_effectwght_calcwght_deriv_arraywght_deriv_calcwght_matrix

Dependencies:abindbackportsbootcheckmatecliFormulageometrygmplatticelinproglme4lpSolvemagicMASSMatrixmatrixStatsminqanlmenloptrnumDerivpbapplyproxyrbibutilsRcppRcppEigenRcppProgressRdpackreformulasregistryROIslamspaMM

Plotting Causal Effects with inferference
Direct Effects | Indirect Effects
Rendered frominferference_plots.Rmdusingknitr::rmarkdown

Last update: 2026-11-14
Started: 2026-11-14

inferference Vignette
JSS article | Using inferference | User's guide | The interference object | Utility functions | Example: Vaccine Study | Plotting effect estimates | Diagnostics | Example: Voting Experiment | Household-level propensity | Coding the propensity function | Evidence of a peer influence effect | Computational Issues with IPW Estimators | References
Rendered frominferference_intro.Rmdusingknitr::rmarkdown

Last update: 2026-11-14
Started: 2026-11-14