Description Usage Arguments Details Value Author(s) References Examples
View source: R/landest_functions.R
Estimates the probability of survival past some specified time using Kaplan-Meier estimation
1 2 |
tl |
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 |
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. |
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.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. |
See documentation for delta.km for details.
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 |
Layla Parast
Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457-481.
1 2 3 | data(example_rct)
example_rct.treat = example_rct[example_rct$treat == 1,]
surv.km(tl=example_rct.treat$TL, dl = example_rct.treat$DL, tt=2)
|
$S.estimate
[1] 0.4439353
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.