Description Usage Arguments Details Value Functions References Examples
View source: R/make_dilated_out.R
Create potential dilated outcomes for simulation.
1 2 3 4 5 6 7 8  make_dilated_out(adj_matrix, make_corr_out, seed, hop, multipliers = NULL)
make_dilated_out_full_neighborhood(
adj_matrix,
make_corr_out,
multipliers = NULL,
seed = NULL
)

adj_matrix 
an 
make_corr_out 
unused. 
seed 
random number for result replicability. 
hop 
number; either 
multipliers 
numeric vector with dilated effects multipliers. Must be
of length 3 if 
make_dilated_out
produces potential dilated outcomes for simulation
according to two different exposure mappings. An exposure mapping that
assumes that interference happens only through direct peer connections
(firstdegree interference) which produces four exposure conditions:
Direct + Indirect Exposure, Isolated Direct Exposure,
Indirect Exposure, No Exposure. And an exposure mapping that
assumes seconddegree interference which produces eight exposure conditions.
The values for the baseline No Exposure condition are drawn from an
absolute standard normal distribution which is correlated with the unit's
first and second order degree. The values for the other exposure conditions
are obtained by multiplying the vector of multipliers by the baseline No
Exposure value.
An K * N
named numeric matrix, where K corresponds to the number of
exposure conditions and N
number of units.
make_dilated_out_full_neighborhood
: Produces potential dilated outcomes for simulation according to
an exposure mapping that assumes firstdegree interference and that
produces two exposure conditions: All Treat, a condition in which a
unit and 100% of its firstdegree neighbors are treated, and All Control,
a unit and 100% of its firstdegree neighbors are in the control
condition.
Aronow, P.M. et al. (2020). Spillover effects in experimental data. arXiv preprint, arXiv:2001.05444.
1 2 3 4 5 6 7 8 9 10 11  adj_matrix < make_adj_matrix(N = 9, model = 'sq_lattice')
multipliers < c(2, 1.5, 1.25)
make_dilated_out(adj_matrix, make_corr_out, seed = 357,
multipliers = multipliers, hop = 1)
multipliers < c(2.25,2,1.75,1.5,1.375,1.25,1.125)
make_dilated_out(adj_matrix, make_corr_out, seed = 357,
multipliers = multipliers, hop = 2)
multiplier < 4
make_dilated_out_full_neighborhood(adj_matrix, make_corr_out,
multipliers=multiplier,
seed=357)

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