sim_data: Simulate data.

In niaidMI: Markov Model Multiple Imputation for NIAID OS

Simulate data.

Description

Simulate data for the purpose of testing the package.

Usage

sim_data(
  n,
  fit = list(Pri = list(c(0, 0, 0, 0.5, 0.25, 0.25, 0, 0)), Tran = list(matrix(c(0.74,
    0.16, 0.04, 0.01, 0, 0, 0, 0, 0.19, 0.63, 0.15, 0.04, 0.01, 0, 0, 0, 0.05, 0.16,
    0.61, 0.15, 0.04, 0.01, 0, 0, 0.02, 0.04, 0.15, 0.6, 0.15, 0.04, 0.01, 0, 0, 0.01,
    0.04, 0.15, 0.6, 0.15, 0.04, 0, 0, 0, 0.01, 0.04, 0.15, 0.61, 0.16, 0, 0, 0, 0, 0.01,
    0.04, 0.15, 0.63, 0, 0, 0, 0, 0, 0.01, 0.04, 0.16, 1), 8, 8))),
  strata = c(s1 = 0.2, s2 = 0.8),
  days = paste0("D", 1:28),
  bin = rep(1, length(days) - 1),
  drop_out_rate = 0.01,
  sporatic_rate = 0.05,
  miss_not_dead_rate = 0.2
)

Arguments

n	Number of samples.
fit	Contains transition and prior parameters.
strata	Named vector with probabilities to simulate strata.
days	Names of the output columns that contain the score for each day.
bin	The assigned bin for pooling together information across transitions. Must be a numeric vector of length=(length(days)-1). By defualt all transitions are pooled together.
drop_out_rate	Parameter for simulating dropout. Rate is per day.
sporatic_rate	Parameter for simulating missing.
miss_not_dead_rate	Parameter to control missing but not dead rate.

Details

This simulation function is used to generated data for examples and testing of the package.

Value

Returns wide format data. Possible niad os values may be:

• Not missing:An integer from 1 to 8.

• Missing:NA

• Partially Missing: range which may be code as a characters string such as '[1,7]' or '[1,2]'. Such a character string indicates that while the actual value is unknown, it is known that the value falls within the specified range.

Examples

test <- sim_data(200)

niaidMI documentation built on March 18, 2022, 7:26 p.m.