This function summarizes the results
Usage
# S3 method for class 'tteICE'
print(x, digits = 3, ...)Arguments
- x
A fitted object returned by the function
tteICE,surv.tteICE, orscr.tteICE.- digits
The digits of the results
- ...
Other arguments in function
print.default
Examples
## load data
data(bmt)
bmt = transform(bmt, d4=d2+d3)
A = as.numeric(bmt$group>1)
bmt$A = A
## print the results
fit1 = surv.tteICE(A, bmt$t2, bmt$d4, "composite")
print(fit1)
#> Input:
#> surv.tteICE(A = A, Time = bmt$t2, cstatus = bmt$d4, strategy = "composite")
#> -----------------------------------------------------------------------
#> Data type: competing risks
#> Strategy: composite variable strategy
#> Estimation method: nonparametric estimation
#> Observations: 137 (including 99 treated and 38 control)
#> Maximum follow-up time: 2640
#> P-value of the average treatment effect: 0.591
fit2 = scr.tteICE(A, bmt$t1, bmt$d1, bmt$t2, bmt$d2, "composite")
print(fit2)
#> Input:
#> scr.tteICE(A = A, Time = bmt$t1, status = bmt$d1, Time_int = bmt$t2,
#> status_int = bmt$d2, strategy = "composite")
#> -----------------------------------------------------------------------
#> Data type: semicompeting risks
#> Strategy: composite variable strategy
#> Estimation method: nonparametric estimation
#> Observations: 137 (including 99 treated and 38 control)
#> Maximum follow-up time: 2640
#> P-value of the average treatment effect: 0.591
library(survival)
fit3 = tteICE(Surv(t2, factor(d4))~A|z1+z3+z5,
data=bmt, strategy="composite", method='eff')
print(fit3, digits=4)
#> Input:
#> tteICE(formula = Surv(t2, factor(d4)) ~ A | z1 + z3 + z5, data = bmt,
#> strategy = "composite", method = "eff")
#> -----------------------------------------------------------------------
#> Data type: competing risks
#> Strategy: composite variable strategy
#> Estimation method: semiparametrically efficient estimation
#> Observations: 137 (including 99 treated and 38 control)
#> Maximum follow-up time: 2640
#> P-value of the average treatment effect: 0.1366