Returns permutation test pvalue; used in the construction
of exact confidence intervals by the function exactCI
1  pval(eff, est, null, y0.a0, y1.a0, y0.a1, y1.a1, h, n, m.a0, m.a1, C2)

eff 
treatment effect of interest; either “DEa0”, “DEa1”, “IE”, “TE”, or “OE” 
est 
estimated treatment effect using estimators from Hudgens and Halloran (2008) 
null 
value of treatment effect of interest under the sharp null hypothesis 
y0.a0 
hypothesized vector \vec{y}(0;α_{0}) under the sharp null hypothesis 
y1.a0 
hypothesized vector \vec{y}(1;α_{0}) under the sharp null hypothesis 
y0.a1 
hypothesized vector \vec{y}(0;α_{1}) under the sharp null hypothesis 
y1.a1 
hypothesized vector \vec{y}(1;α_{1}) under the sharp null hypothesis 
h 
the number of groups out of k total to be randomized to strategy α_{1} 
n 
group size vector where element i=1,…,k is equal to the number of subjects in group i 
m.a0 
α_{0} randomization vector where element i=1,…,k is equal to the number of subjects in group i who would receive treatment if group i was randomized to strategy α_{0} 
m.a1 
α_{1} randomization vector where element i=1,…,k is equal to the number of subjects in group i who would receive treatment if group i was randomized to strategy α_{1} 
C2 
number of rerandomizations (experiments) to conduct in computing the null distribution of the estimator 
See equation (6) in Rigdon and Hudgens (2014)
Joseph Rigdon jrigdon@bios.unc.edu
Hudgens, M.G. and Halloran, M.E. “Toward causal inference with interference.” Journal of the American Statistical Association 2008 103:832842.
Rigdon, J. and Hudgens, M.G. “Exact confidence intervals in the presence of interference.” Submitted to Statistics and Probability Letters 2014.
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