out_NEgraph: Generating Null Exposure Graph

In dpuelz/CliqueRT: Randomization-Based Testing of Causal Effects under General Interference

Generating Null Exposure Graph

Description

One of the main functions for implementing the methodology. Outputs the null-exposure graph based on binary matrices describing exposure conditions in the null hypothesis. The null hypothesis is represented as: H_0: Y_i(a) = Y_i(b) for all i, and states that potential outcomes are equal for all units exposed to either a or b.

Usage

out_NEgraph(Z_a, Z_b, Z, exclude_treated = TRUE)

Arguments

Z_a	A binary matrix with dimension (number of units x number of randomizations, i.e. assignments.) Row i, column j of the matrix corresponds to whether a unit i is exposed to a under assignment j. Please see example.
Z_b	A binary matrix with (number of units x number of randomizations, i.e. assignments.) Row i, column j of the matrix corresponds to whether a unit i is exposed to b under assignment j. Please see example. Z_b should have the same dimension as Z_a.
Z	A binary matrix of dimension (number of units x number of randomizations, i.e. assignments.) storing the assignment vectors.
exclude_treated	A Boolean denoting whether or not treated units are considered in the hypothesis. Default is TRUE.

Value

NEgraph, a matrix of dimension (number of units x number of randomizations, i.e. assignments.). Row i, column j of the matrix either equals -1 (unit i is exposed to a under assignment j), 1 (unit i is exposed to b under assignment j), 0 (unit i is neither exposed to a nor b under assignment j).

dpuelz/CliqueRT documentation built on Jan. 6, 2023, 11:20 p.m.