surv_param_sim

From survParamSim v0.1.0 by Kenta Yoshida

Simulation of parametric survival model

The main function to generate predicted survival using a model object generated with survreg function.

Usage

surv_param_sim(
  object,
  newdata,
  n.rep = 1000,
  censor.dur = NULL,
  coef.var = TRUE,
  na.warning = TRUE
)
surv_param_sim_resample(
  object,
  newdata,
  n.rep = 1000,
  censor.dur = NULL,
  n.resample,
  strat.resample = NULL
)

Arguments

object

A `survreg` class object. Currently accept exponential, lognormal, weibull, loglogistic, and gaussian distributions.

newdata

A required data frame for simulation that contain covariates in the survival model. It is required even if this is the same as the one used for survreg function.

It also has to contain columns for survival information. These can be used in plot_km_pi and plot_hr_pi function as observed data. Survival information can be dummy data, but time need to be long enough so that simulated KM plot will be long enough for plot_km_pi to draw simulated survival curves.

Subjects with NA for covariates in `survreg` model will be removed from the simulation and subsequent plotting of observed data.

n.rep

An integer defining numbers of parametric bootstrap runs

censor.dur

A two elements vector specifying duration of events censoring. Censoring time will be calculated with uniform distribution between two numbers. No censoring will be applied if NULL is provided.

coef.var

Boolean specifying whether parametric bootstrap are performed on survival model coefficients, based on variance-covariance matrix. If FALSE, prediction interval only reflects inherent variability from survival events.

na.warning

Boolean specifying whether warning will be shown if `newdata` contain subjects with missing model variables.

n.resample

Number of subjects for resampled simulations. If `strat.resample` is provided, this needs to be a vector of the length equal to the number of categories in the stratification variable.

strat.resample

String specifying stratification variable for resampling.

Details

surv_param_sim returns simulation using the provided subject in `newdata` as it is, while surv_param_sim_resample perform simulation based on resampled subjects from the dataset. The latter allows more flexibility in terms of simulating future trials with different number of subjects.

Currently we have not tested whether this function work for a `survreg` model with stratification variables.

Value

A `survparamsim` object that contains the original `survreg` class object, newdata, and a data frame for predicted survival profiles with the following columns:

event: event status, 0=censored, 1=event
rep: ID for parametric bootstrap runs
subj: ID for subjects in newdata (currently original ID is not retained and subj is sequentially assigned as 1:nrow(newdata))

Examples

# NOT RUN {
library(survival)

fit.lung <- survreg(Surv(time, status) ~ sex + ph.ecog, data = lung)

object <- fit.lung
n.rep  <-  30
newdata <-
  tibble::as_tibble(dplyr::select(lung, time, status, sex, ph.ecog)) %>%
  tidyr::drop_na()
censor.dur <- c(200, 1100)

sim <- surv_param_sim(object, newdata, n.rep, censor.dur)



# }

Documentation reproduced from package survParamSim, version 0.1.0, License: GPL-3

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