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The simIC
package provides tools for simulating and
analyzing interval-censored survival data, including
left-, right-, and uncensored observations, using a variety of
parametric distributions. It is useful for teaching, model development,
and method evaluation in survival analysis.
Supports commonly used parametric distributions:
Simulates survival data with interval,
left, right, and
uncensored observations using user-defined visit
schedules (start_time
, end_time
) and an
optional tolerance (uncensored_tol
) for detecting exact
event times.
Provides two estimation functions:
mle_int()
F(Ri) - F(Li)
F(Ri)
1 - F(Li)
f(ti)
mle_imp()
(Li, Ri)
using midpoint, random, medians, or survival-based
methodsF(Ri)
1 - F(Li)
f(ti)
You can install the development version of simIC
from
GitHub:
```r install.packages(“remotes”) remotes::install_github(“jayarasan/simIC”) library(simIC)
🧪 Simulate Survival Data # Interval-censored data only (no visit window) data <- simIC(n = 100, dist = “weibull”, shape = 1.5, scale = 5, width = 2)
data <- simIC(n = 100, dist = “weibull”, shape = 1.5, scale = 5, width = 2, start_time = 0, end_time = 10, uncensored_tol = 0.1)
📈 Model Fitting Examples
fit_int <- mle_int(data\(left, data\)right, dist = “weibull”) print(fit_int$estimates)
fit_imp <- mle_imp(data\(left, data\)right, dist = “weibull”, impute = “midpoint”) print(fit_imp$estimates)
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.