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) . Currently it implements the inverse-probability weighted (IPW) estimators proposed by E.J. Tchetgen Tchetgen and T.J. Vanderweele (2012) .

Provides methods for estimating causal effects in the presence of interference. Currently it implements the IPW estimators proposed by EJ Tchetgen Tchetgen and TJ Vanderweele in "On causal inference in the presence of interference" (Statistical Methods in Medical Research, 21(1) 55-75).

See vignette('inferference_intro') for usage.


inferference 0.5.3

  • fixes small issue with diagnose_weights() function

inferference 0.5.3

  • fixes issue where weightd object was not showing up in output

inferference 0.5.2

  • adds JSS citation

inferference 0.5.1

  • updates vignettes to a stripped down version of the JSS paper

  • effect utilities now only return a smaller subset of columns: alphas, treatments, estimate, std.error, and confidence limits

inferference 0.5.0

  • Eliminates set_NA_to_0 to interference.

  • Modifies the integrate_allocation argument to interference. The default is now to include the allocation parameter in the weight term.

  • Adds diagnose_weights function which prints histograms of group-level weights.

inferference 0.4.62

  • To avoid confusion with the method argument of numDeriv::grad(), the causal_estimation_options of interference() has changed. variance_estimation = 'simple' is now variance_estimation = 'naive'.

Reference manual

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1.0.2 by Bradley Saul, 7 months ago

Browse source code at

Authors: Bradley Saul

Documentation:   PDF Manual  

GPL (>= 2) license

Imports numDeriv, lme4, Formula, methods

Suggests testthat, knitr, markdown

Suggested by geex.

See at CRAN