| reslifefsr {reslife} | R Documentation |
Calculate Residual Life Values Using a flexsurvreg() Object
Description
Calculate residual life values using a flexsurvreg() object. Contains an option to supply new data and returns the output as a vector.
Usage
reslifefsr(obj, life, p = 0.5, type = "mean", newdata = data.frame())
Arguments
obj |
Name of a flexsurvreg() object from which data is extracted. |
life |
Value at which the user wants to calculate residual life. Must be a scalar. |
p |
percentile for percentile residual life, default is .5 |
type |
can be 'mean', 'median', 'percentile', or 'all'. Default is 'mean'. |
newdata |
a data frame containing new data values to calculate residual life for. Default is a blank data frame. |
Value
A vector of residual life values
References
Jackson CH (2016). “flexsurv: a platform for parametric survival modeling in R.” Journal of statistical software, 70.
Poynor V (2010). “Bayesian inference for mean residual life functions in survival analysis.” Masters diss., University of California, Santa Cruz.
Prentice RL (1975). “Discrimination among some parametric models.” Biometrika, 62(3), 607–614.
Stacy EW (1962). “A generalization of the gamma distribution.” The Annals of mathematical statistics, pp. 1187–1192
Examples
library(flexsurv)
fitg <- flexsurv::flexsurvreg(formula = Surv(futime, fustat) ~ 1,
data = ovarian, dist="gengamma")
reslifefsr(obj = fitg, life = 6, p= .75, type= 'all')
fitg2 <- flexsurv::flexsurvreg(formula = Surv(futime, fustat) ~ age,
data = ovarian, dist="gengamma")
df_new = data.frame(age = 12)
reslifefsr(obj = fitg2, life = 3, type = 'median', newdata = df_new)