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inferference

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.

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Version

Install

install.packages('inferference')

Monthly Downloads

256

Version

1.0.2

License

GPL (>= 2)

Maintainer

Bradley Saul

Last Published

April 21st, 2021

Functions in inferference (1.0.2)

logit_integrand

Default integrand for the group-level propensity score
wght_deriv_array

Create an array of group weight derivatives
wght_deriv_calc

Compute the derivative(s) of a weight
voters

Voting Contagion Experiment Data
wght_calc

Compute IPW weight
score_matrix

Calculate matrix of log Likelihood derivatives
score_calc

Compute scores for a single group
wght_matrix

Creates a number of groups by number of allocation schemes matrix of group weights. Allocation schemes are selected by the user.
vaccinesim

Vaccine Study Sample Data
total_effect

Retrieve Total Effect estimates
print.interference

Prints a summary of an interference object
direct_effect

Retreive Direct Effect estimates
indirect_effect

Retreive Indirect Effect estimates
diagnose_weights

Plot histograms of weights from an interference object
log_likelihood

Log Likelihood
inferference

Methods for causal inference with interference
get_args

Get arguments from a function
overall_effect

Retrieve Overall Effect Estimates
interference

Estimate Causal Effects in presence of interference