Estimates and bounds for treatment effects on a binary outcome in a two-stage randomized experiment with interference

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Description

Computes the estimators of Hudgens and Halloran (2008) and bounds of Rigdon and Hudgens (2014) for treatment effects on a binary outcome in a two-stage randomized experiment with interference

Usage

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estbound(g, data, m.a0, m.a1)

Arguments

g

1st stage of randomization vector where element i=1,…,k is equal to 1 if group i was randomized to strategy α_{1} and 0 if randomized to strategy α_{0}

data

2 \times 2\times k array of 2 \times 2 table data where row 1 is treatment=yes, row 2 is treatment=no, column 1 is outcome=yes, and column 2 is outcome=no

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}

Details

Function will return many values (to be used by other functions in this package), but the only important value here is tab.eff

Value

tab.eff

Labeled table of estimates and bounds

Author(s)

Joseph Rigdon jrigdon@bios.unc.edu

References

Hudgens, M.G. and Halloran, M.E. “Toward causal inference with interference.” Journal of the American Statistical Association 2008 103:832-842.

Rigdon, J. and Hudgens, M.G. “Exact confidence intervals in the presence of interference.” Submitted to Statistics and Probability Letters 2014.

Examples

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#Made up example with 10 groups of 10 where half are randomized to a0 and half to a1
#a0 is assign 3 of 10 to treatment and half to a1 is assign 6 of 10 to treatment
d = c(1,1,5,3,0,6,3,1,0,4,3,3,0,5,3,2,1,1,5,3,2,2,4,2,1,5,2,2,2,3,4,1,1,1,5,3,1,5,2,2)
data.ex = array(d,c(2,2,10))
assign.ex = c(1,0,0,0,1,1,0,1,1,0)

#Estimates and bounds
e = estbound(assign.ex,data.ex,rep(3,10),rep(6,10))
e$tab.eff