observed event time of primary outcome, equal to min(T, C) where T is the event time and C is the censoring time.
dl
event indicator, equal to I(T<C) where T is the event time and C is the censoring time.
tt
the time of interest, function estimates the probability of survival past this time
landmark
the landmark time
short
a matrix of intermediate event information, there should be two columns for each intermediate event, the first column contains the observed intermediate event time, equal to min(TS, C) where TS is the event time and C is the censoring time, and the second column contains the event indicator, equal to I(TS<C)
z.cov
matrix of baseline covariate information
var
TRUE or FALSE; indicates whether a variance estimate for survival is requested, default is FALSE.
conf.int
TRUE or FALSE; indicates whether a 95% confidence interval for survival is requested, default is FALSE.
ps.weights
propensity score (or inverse probability of treatment) weights
weight.perturb
a n by x matrix of weights where n = length of tl; used for perturbation-resampling, default is null. If var or conf.int is TRUE and weight.perturb is not provided, the function generates exponential(1) weights.
perturb.ps
TRUE or FALSE indicating whether the weight.perturb matrix includes the perturbed propensity score (or inverse probability of treatment) weights
perturb.vector
TRUE or FALSE; indicates whether a vector of the perturbed values of the survival estimate is requested, default is FALSE. This argument is ignored if both var and conf.int are FALSE.
bw
bandwidth used for kernel estimation, default is NULL
Details
See documentation for delta.land.obs for details.
Value
A list is returned:
S.estimate
the estimate of survival at the time of interest, hat{S}(t) = P(T>t)
S.var
the variance estimate of hat{S}(t); if var = TRUE or conf.int = TRUE
conf.int.normal.S
a vector of size 2; the 95% confidence interval for hat{S}(t) based on a normal approximation; if conf.int = TRUE
conf.int.quantile.S
a vector of size 2; the 95% confidence interval for hat{S}(t) based on sample quantiles of the perturbed values, described above; if conf.int = TRUE
perturb.vector
a vector of size x where x is the number of columns of the provided weight.perturb matrix (or x=500 if weight.perturb is not provided); the perturbed values of hat{S}(t); if perturb.vector = TRUE and either var=TRUE or conf.int = TRUE
Author(s)
Layla Parast
References
Parast, L. & Griffin B.A. (2015). Landmark Estimation of Survival and Treatment Effects in Observational Studies, in press.
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