Description Usage Arguments Details Value Functions References Examples
View source: R/make_exposure_map_AS.R
Create treatment exposure conditions according to selected exposure mappings.
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make_exposure_map_AS(adj_matrix, tr_vector, hop) make_exposure_map_full_neighborhood(adj_matrix, tr_vector)
a numeric vector of length
make_exposure_map_AS produces treatment exposure conditions according
to two different exposure mappings. An exposure mapping that assumes that
interference happens only through direct peer connections (first-degree
interference) which produces four exposure conditions: Direct + Indirect
Exposure, Isolated Direct Exposure, Indirect Exposure, No
Exposure. And an exposure mapping that assumes second-degree interference
which produces eight exposure conditions.
N * K numeric matrix, where K corresponds to the number of
make_exposure_map_full_neighborhood: Create treatment exposure conditions
according to an exposure mapping that assumes first-degree interference and
that produces two exposure conditions: All Treat; a unit and 100% of
its first-degree neighbors are treated, and All Control; a unit and
100% of its first-degree neighbors are in the control condition.
Aronow, P.M. & Samii, C. (2017). Estimating average causal effects under general interference, with application to a social network experiment. The Annals of Applied Statistics, 11(4), 1912–1947.
Aronow, P.M. et al. (2020). Spillover effects in experimental data. arXiv preprint, arXiv:2001.05444.
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# Create an adjacency matrix and a treatment vector: adj_matrix <- make_adj_matrix(N = 9, model = 'sq_lattice') tr_vector <- make_tr_vec_permutation(N = 9, p = 0.2, R = 1, seed = 357) # Create treatment exposure conditions: make_exposure_map_AS(adj_matrix, tr_vector, hop = 1) make_exposure_map_AS(adj_matrix, tr_vector, hop = 2) make_exposure_map_full_neighborhood(adj_matrix, tr_vector)
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