Learn R Programming

interferenceCI (version 1.1)

HH: Large sample confidence intervals for treatment effects on a binary outcome in a two-stage randomized experiment with interference

Description

Computes the large sample confidence intervals of Liu and Hudgens (2014) for treatment effects on a binary outcome in a two-stage randomized experiment with interference

Usage

HH(eff, g, data, m.a0, m.a1, level)

Arguments

eff
treatment effect of interest; either ``DEa0'', ``DEa1'', ``IE'', ``TE'', or ``OE''
g
1st stage of randomization vector where element $i=1,\ldots,k$ is equal to 1 if group $i$ was randomized to strategy $\alpha_{1}$ and 0 if randomized to strategy $\alpha_{0}$
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
$\alpha_{0}$ randomization vector where element $i=1,\ldots,k$ is equal to the number of subjects in group $i$ who would receive treatment if group $i$ was randomized to strategy $\alpha_{0}$
m.a1
$\alpha_{1}$ randomization vector where element $i=1,\ldots,k$ is equal to the number of subjects in group $i$ who would receive treatment if group $i$ was randomized to strategy $\alpha_{1}$
level
significance level, i.e., method yields a 1-level confidence interval

Value

est
estimated treatment effect
v
estimated variance
lower.w
lower limit to Wald confidence interval
upper.w
upper limit to Wald confidence interval
lower.ch
lower limit to Chebyshev confidence interval
upper.ch
upper limit to Chebyshev confidence interval

References

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

Liu, L. and Hudgens, M.G. ``Large sample randomization inference of causal effects in the presence of interference.'' Journal of the American Statistical Association 2014 109:288-301.

Examples

Run this code
#Table 3 from Hudgens and Halloran (2008) 
hh = array(c(16,18,12541-16,12541-18,26,54,11513-26,11513-54,17,119,10772-17,
     25134-119,22,122,8883-22,20727-122,15,92,5627-15,13130-92),c(2,2,5))
e1 = HH('OE',c(1,1,0,0,0),hh,round(0.3*c(25082,23026,35906,29610,18757),0),
     round(0.5*c(25082,23026,35906,29610,18757),0),0.05)
round(1000*e1$est,3)
round(1000000*e1$v,3)

Run the code above in your browser using DataLab