Description Usage Arguments References Examples
This function performs sensitivity analysis for time to event outcomes in observational studies
1 2 |
x |
name of the matching object. Should be either a |
data |
dataset. |
exp |
name of treatment variable. |
outcome |
name of outcome variable. |
failtime |
name of event time variable. |
Gamma |
upper bound for sensitivity parameter. |
Gammainterval |
value by which to increament sensitivity parameter from zero to |
plot_title |
main title of your plot. |
Rosenbum 2011
1 2 3 4 5 6 7 8 9 10 | data(toy)
psmodel <- glm(treated ~ covA + covB + covC + covD + covE + covF + Asqr + BC + BD, family=binomial(), data=toy)
toy$ps <- psmodel$fitted
toy$linps <- psmodel$linear.predictors
X <- toy$linps ## matching on the linear propensity score
Tr <- as.logical(toy$treated)
Y <- toy$out3.time
match1 <- Match(Y=Y, Tr=Tr, X=X, M = 1, replace=FALSE, ties=FALSE)
match.it <- matchit(treated ~ covA + covB + covC + covD + covE + covF + Asqr + BC + BD, data = toy, method='nearest', ratio=1)
Survsens(x= match.it,data =toy,exp='treated',outcome = 'out2',failtime = 'out3.time',Gamma=2.4,Gammainterval = 0.01,alpha = 0.05,plot_title = 'Time To Event Outcome Sensitivity Plot')
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