Create an input data frame X for simulated data

sim.create_x(
N,
covariates,
names,
n_categs,
t_data,
t_jitter,
t_effect_range,
continuous_info
)

## Arguments

N Number of individuals. Integer vector that defines the types of covariates (other than id and age). If not given, only the id and age covariates are created. Different integers correspond to the following covariate types: 0 = disease-related age 1 = other continuous covariate 2 = a categorical covariate that interacts with age 3 = a categorical covariate that acts as a group offset 4 = a categorical covariate that that acts as a group offset AND is restricted to have value 0 for controls and 1 for cases Covariate names. An integer vector defining the number of categories for each categorical covariate, so that length(n_categs) equals to the number of 2's and 3's in the covariates vector. Measurement times (same for each individual, unless t_jitter > 0 in which case they are perturbed). Standard deviation of the jitter added to the given measurement times. Time interval from which the disease effect times are sampled uniformly. Alternatively, This can any function that returns the (possibly randomly generated) real disease effect time for one individual. Info for generating continuous covariates. Must be a list containing fields lambda and mu, which have length 3. The continuous covariates are generated so that x <- sin(a*t + b) + c, where t <- seq(0, 2*pi, length.out = k) a <- mu[1] + lambda[1]*stats::runif(1) b <- mu[2] + lambda[2]*stats::runif(1) c <- mu[3] + lambda[3]*stats::runif(1)

a list