simu_cov | R Documentation |
This function generates continuous and binary covariates through simulating from a multivariate normal distribution. Outcomes are further converted to binary variables using quantiles of the normal distribution calculated from the probability provided. Then the covariates are added to the external trial and treatment arm indicators.
simu_cov(ssObj, covObj, driftHR, HR, nsim, seed, path)
ssObj |
an object of class |
covObj |
an object of class |
driftHR |
hazard ratio of external control and internal control arms |
HR |
a list of hazard ratio of treatment and control arms |
nsim |
number of simulation. Default is 5 |
seed |
the seed of R‘s random number generator. Default is the first element of .Random.seed |
path |
file name for saving the output including folder path |
a list of matrix
containing simulated covariates information
# simulate patient-level data with 1 continuous covariate sample = set_n(ssC = 10, ssE = 20, ssExt = 40) cov1 = set_cov(n_cat = 0, n_cont = 1, mu_int = 0, mu_ext = 0, var = 1) simu_cov(ssObj = sample, covObj = cov1, HR = 0.5, driftHR = 1, nsim = 2) # simulate patient-level data with 1 binary and 2 continuous covariate cov2 = set_cov(n_cat = 1, n_cont = 2, mu_int = 0, mu_ext = 0, var = 1, cov = 0.3, prob_int = 0.2, prob_ext = 0.3) simu_cov(ssObj = sample, covObj = cov2, HR = 0.5, driftHR = 1, nsim = 2)
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