CompParaSurv {Temporal}

Compare Parametric Survival Distribution

Description

Compares the means and medians of parametric survival distributions fit to two treatment arms. Available distributions include: exponential, gamma, generalized gamma, log-normal, and Weibull.

Usage

CompParaSurv(
  data,
  arm_name = "arm",
  dist1 = "weibull",
  dist0 = NULL,
  eps = 1e-06,
  init1 = NULL,
  init0 = NULL,
  maxit = 10,
  report = FALSE,
  reps = NULL,
  sig = 0.05,
  status_name = "status",
  tau = NULL,
  time_name = "time"
)

Arguments

data

Data.frame.

arm_name

Name of the column containing the treatment group, coded as 1 for treatment, 0 for reference.

dist1

Distribution to fit for the target group. Selected from among: exp, gamma, gengamma, log-normal, and weibull.

dist0

Distribution to fit for the reference group. Same choices as for the target group. If omitted, defaults to the distribution specified for the target group.

eps

Tolerance for Newton-Raphson iterations.

init1

Initial parameter values for the target group.

init0

Initial parameter values for the reference group.

maxit

Maximum number of Newton-Raphson iterations.

report

Report fitting progress?

reps

Number of permutation replicates, if requesting permutation p-values.

sig

Significance level, for constructing confidence intervals.

status_name

Name of the status indicator, 1 if observed, 0 if censored.

tau

Optional truncation times for calculating RMST.

time_name

Name of column containing the time to event.

Details

Status should be coded as 0 for censored and 1 for observed. Arm is coded as 0 for reference, 1 for target. Tau is an optional numeric vector of truncation times for calculating restricted mean survival time, which is the area under the survival curve up to the specified truncation point.

Value

An object of class contrast containing the following:

Model1

The fitted model for the target group.

Model0

The fitted model for the reference group.

Contrast

Contrasts of means and medians.

RMST

Contrasts of the RMSTs, if 'tau' was specified.

Examples

set.seed(100)
# Weibull and Weibull, different means and medians.
n <- 1e3

# Generate data.
df1 <- GenData(n = n, dist = "weibull", theta = c(1, 1), p = 0.2)
df1$arm <- 1
df0 <- GenData(n = n, dist = "weibull", theta = c(1, 2), p = 0.2)
df0$arm <- 0
data <- rbind(df1, df0)

# Comparison.
comp <- CompParaSurv(data, dist1 = "weibull")

# Add RMST at time 1.
comp <- CompParaSurv(data, dist1 = "weibull", tau = 1)

# Calculate permutation p-values (slow).
comp <-  CompParaSurv(data, dist1 = "weibull", tau = 1, reps = 100)