surv_prob: Survival probability based on parametric distribution

In parmsurvfit: Parametric Models for Survival Data

Description

Computes probability of survival beyond time t given that the data follows a specified parametric distribution.

Usage

surv_prob(data, dist, x, lower.tail = F, time = "time",
  censor = "censor", by = "")

Arguments

data	A dataframe containing a time column and a censor column.
dist	A string name for a distribution that has a corresponding density function and a distribution function. Examples include "norm", "lnorm", "exp", "weibull", "logis", "llogis", "gompertz", etc.
x	A scalar quantity, time at which the probability of survival is computed
lower.tail	Logical; if F (default), probability is P(T > x), otherwise, P(T < x).
time	The string name of the time column of the dataframe. Defaults to "time".
censor	The string name of the censor column of the dataframe. Defaults to "censor". The censor column must be a numeric indicator variable where complete times correspond to a value of 1 and incomplete times correspond to 0.
by	The string name of a grouping variable. If specified, the function prints probability for each group individually along with the overall probability. Variable can contain logical, string, character, or numeric data.

Examples

data("rearrest")
surv_prob(rearrest, "lnorm", 110, time = "months")
surv_prob(rearrest, "weibull", 90, time = "months", lower.tail = TRUE)

parmsurvfit documentation built on May 2, 2019, 5:41 a.m.