mcontrol {rbounds} | R Documentation |
Sensitivity Analysis For Multiple Matched Controls
Description
Function to calculate Rosenbaum bounds for continuous or ordinal outcomes based on Wilcoxon sign rank test p-value when there are multiple matched control units.
Usage
# Default Method
mcontrol(y, grp.id, treat.id, group.size = 3, Gamma = 4, GammaInc = 1)
Arguments
y |
Vector of grouped matched outcomes. |
treat.id |
A vector indicating the treated unit in each matched group. |
grp.id |
A vector indicating matched groups. |
group.size |
The size of the matched groups. Three for one treated unit and two control units. |
Gamma |
Upper-bound on gamma parameter. |
GammaInc |
To set increments for gamma parameter. |
Details
The matched data needs to be in a very particular form for this function to work. The data must be sorted by matched groups with indicators for each matched group and for treated and control units. The simplest way to prepare the data is to use the Match() function and use the data.prep() function to format the data.
Currently this function only takes matched data with 2 or 3 controls units matched to each treated unit.
This function does cannot handle data where the number of control units is not the same for every treated unit.
Author(s)
Luke Keele, University of Pennsylvania, luke.keele@gmail.com
References
Rosenbaum, Paul R. (2002) Observational Studies. Springer-Verlag.
See Also
See also binarysens
, psens
,
hlsens
Examples
grp <- c(1, 1, 1, 2, 2, 2, 3, 3, 3, 4, 4, 4, 5, 5, 5, 6,
6, 6, 7, 7, 7, 8, 8, 8, 9, 9, 9, 10,10,10,11,
11,11,12,12,12)
trt <- rep(c(1,0,0), 12)
score <- c(-11.39,-8.45, -19.57,-8.33, 3.06, -19.93,-18.73,-11.99,-7.55,
11.94, 9.4, -25.16,-0.77, -10.46,-7.27, 24.03, -8.23, 2.67,
-4.04, -6.67, -1.12, -14.4, -26.21,5, -1.7, -15.3, -7.73,
-0.87, -19.71,-12.69, -3.36, -11.21,-35.83,5.89, -10.79,2)
mcontrol(score, grp, trt, group.size=3)