Computes the survival function for a triivariate outcome. The survival function for a trivariate outcome is analogous to the Kaplan-Meier estimator for a univariate outcome. Optionally (bootstrap) confidence intervals for the survival function may also be computed.
KM3(
Y1,
Y2,
Y3,
Delta1,
Delta2,
Delta3,
newT1 = NULL,
newT2 = NULL,
newT3 = NULL,
conf.int = FALSE,
R = 1000,
...
)
Vectors of event times (continuous).
Vectors of censoring indicators (1=event, 0=censored).
Optional vectors of new times at which to estimate the survival function. Defaults to the unique values in Y1/Y2 if not specified.
Should bootstrap confidence intervals be computed?
Number of bootstrap replicates. This argument is passed to the boot function. Defaults to 1000. Ignored if conf.int is FALSE.
Additional arguments to the boot function.
A list containing the following elements:
Unique values of Y1 at which Fhat was computed
Unique values of Y2 at which Fhat was computed
Unique values of Y3 at which Fhat was computed
Estimated survival function (computed at T1, T2, T3)
Lower 95% confidence bounds for Fhat
Upper 95% confidence bounds for Fhat
Estimated marginal survival function for variable 1 (computed at newT1)
Lower 95% confidence bounds for Fmarg1
Upper 95% confidence bounds for Fmarg1
Estimated marginal survival function for variable 2 (computed at newT2)
Lower 95% confidence bounds for Fmarg2
Upper 95% confidence bounds for Fmarg2
Estimated marginal survival function for variable 3 (computed at newT3)
Lower 95% confidence bounds for Fmarg3
Upper 95% confidence bounds for Fmarg3
Estimated survival function (computed at newT1, newT2, newT3)
Lower 95% confidence bounds for Fhat_est
Upper 95% confidence bounds for Fhat_est
Pairwise marginal cross ratio estimator C110
Pairwise marginal cross ratio estimator C101
Pairwise marginal cross ratio estimator C011
Trivariate dependency estimator C111
If conf.int is TRUE, confidence intervals will be computed using the boot function in the boot package. Currently only 95% confidence intervals computed using the percentile method are implemented. If conf.int is FALSE, confidence intervals will not be computed, and confidence bounds will not be returned in the output.
Prentice, R., Zhao, S. "Nonparametric estimation of the multivariate survivor function: the multivariate Kaplan<U+2013>Meier estimator", Lifetime Data Analysis (2018) 24:3-27. Prentice, R., Zhao, S. "The statistical analysis of multivariate failure time data: A marginal modeling approach", CRC Press (2019).
# NOT RUN {
x <- genClayton3(200, 0, 0.5, 0.5, 0.5)
x.km3 <- KM3(x$Y1, x$Y2, x$Y3, x$Delta1, x$Delta2, x$Delta3)
# }
# NOT RUN {
x.km3.ci <- KM3(x$Y1, x$Y2, x$Y3, x$Delta1, x$Delta2,
x$Delta3, conf.int=TRUE, R=500)
# }
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