| clique_test_contrast | R Documentation |
The main randomization test function for contrast hypothesis.
clique_test_contrast( Y, Z, Z_a, Z_b, Zobs_id, Xadj = NULL, alpha = 0.05, tau = 0, decom = "bimax", ret_ci = FALSE, ci_dec = 2, ci_method = "grid", ... )
Y |
The observed outcome vector. |
Z |
A binary matrix of dimension (number of units x number of randomizations, i.e. assignments.) storing the assignment vectors. Please see example. |
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 |
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 |
Zobs_id |
The index location of the observed assignment vector in |
Xadj |
The covariates that might affect Y. If not |
alpha |
The significance level. By default it's 0.05. |
tau |
The τ in the null Y_i(b) = Y_i(a) + τ for all i. By default is 0. |
decom |
The algorithm used to calculate the biclique decomposition. Currently supported algorithms are "bimax" and "greedy". |
ret_ci |
Whether calculates the 1-α confidence interval or not. Default is |
... |
Other stuff ... |
A list of items summarizing the randomization test. If for some focal assignments
in the biclique that contains Zobs, exposures for each unit are the same, it will
contain an error message, and the test decision will be NA.
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