collett (version 0.1.2)

simdata: Simulated data

Description

Simulated data with left truncated follow-up and potentially right censored outcomes.

Usage

simdata

Format

A data frame with 30 observations and 8 variables:

id

integer index each individual

trt

numeric for whether treated (1=treated; 0=not treated)

age

integer for age in years

entry_time

numeric for year of entry

observed_duration

numeric for years that an individual was observed

status

integer for status at the end of follow-up (1=event, 0=censored)

event_calendar_time

numeric hypothetical event time in calendar time

stop_calendar_time

numeric end of follow-up in calendar time

Examples

## Simulate 30 individuals survival based on Weibull distribution
set.seed(13579)
n <- 30

## Randomly assign treatment groups (15 each)
trt <- sample(c(1, 0), n, replace = TRUE)

## Randomly assign integer age 50-80 to each individual
age <- sample(50:80, n, replace = TRUE)

## Simulate true event times based on Weibull distribution
true_shape <- 3
true_scale <- 8
true_times <- rweibull(n, shape = true_shape, scale = true_scale)

## Simulate right censoring times based on exponential distribution
censoring_rate <- 0.1
censoring_times <- rexp(n, rate = censoring_rate)

## Random entry times
entry_time <- runif(n, min = 2000, max = 2010)

## Convert durations (time-on-study) to calendar times
event_calendar_time <- entry_time + true_times
censor_calendar_time <- entry_time + censoring_times

## Study end time (Administrative Censoring)
study_end_time <- 2012
study_censor_calendar_time <- rep(study_end_time, n)

## Determine the calendar time when observation ends
stop_calendar_time <- pmin(event_calendar_time, censor_calendar_time,
                           study_censor_calendar_time)

## Calculate the observed duration
observed_duration <- stop_calendar_time - entry_time

## Create tied data
observed_duration <- round(observed_duration * 2) / 2

## Determine the final status (1 if event, 0 if censored)
status <- as.integer(event_calendar_time <= pmin(censor_calendar_time, study_censor_calendar_time))

## Create a data frame
simdata <- data.frame(
  id = 1:n,
  trt, ## Treatment group
  age, ## Age at diagnosis
  entry_time, ## When they entered (Calendar time)
  observed_duration, ## Time-on-study
  status, ## Event status (1=event, 0=censored)
  event_calendar_time, ## Hypothetical event time (Calendar time)
  stop_calendar_time ## When observation ended (Calendar time)
)
## Save the data frame
## save(simdata, file = "~/src/R/collett/data/simdata.rda")