matchMultisens {matchMulti} | R Documentation |
Rosenbaum Bounds after Multilevel Matching
Description
Function to calculate Rosenbaum bounds for continuous outcomes after multilevel matching.
Usage
matchMultisens(
obj,
out.name = NULL,
schl_id_name = NULL,
treat.name = NULL,
Gamma = 1
)
Arguments
obj |
A multilevel match object |
out.name |
Outcome variable name |
schl_id_name |
Level 2 ID variable name, that is this variable identifies clusters matched in the data. |
treat.name |
Treatment indicator name |
Gamma |
Sensitivity analysis parameter value. Default is one. |
Details
This function returns a single p-value, but actually conducts two tests. The first assumes that the treatment effect does not vary with cluster size. The second allows the treatment effect to vary with cluster size. The function returns a single p-value that is corrected for multiple testing. This p-value is the upper bound for a single Gamma value
Value
pval |
Upper bound on one-sided approximate p-value for test of the sharp null. |
Author(s)
Luke Keele, University of Pennsylvania, luke.keele@gmail.com
Sam Pimentel, University of California, Berkeley, spi@berkeley.edu
References
Rosenbaum, Paul R. (2002) Observational Studies. Springer-Verlag.
See Also
See Also as matchMulti
,
matchMultioutcome
Examples
## Not run:
# Load Catholic school data
data(catholic_schools)
student.cov <- c('minority','female','ses','mathach')
# Check balance student balance before matching
balanceTable(catholic_schools[c(student.cov,'sector')], treatment = 'sector')
#Match schools but not students within schools
match.simple <- matchMulti(catholic_schools, treatment = 'sector',
school.id = 'school', match.students = FALSE)
#Check balance after matching - this checks both student and school balance
balanceMulti(match.simple, student.cov = student.cov)
#Estimate treatment effect
output <- matchMultioutcome(match.simple, out.name = "mathach",
schl_id_name = "school", treat.name = "sector")
# Perform sensitivity analysis using Rosenbaum bound -- increase Gamma to increase effect of
# possible hidden confounder
matchMultisens(match.simple, out.name = "mathach",
schl_id_name = "school",
treat.name = "sector", Gamma=1.3)
## End(Not run)