simdata {CALIBERrfimpute} | R Documentation |
Creates multivariate normal or normal and binary data, as used in the simulation study.
simdata(n = 2000, mymean = rep(0, 4), mysigma = matrix( c( 1, 0.2, 0.1, -0.7, 0.2, 1, 0.3, 0.1, 0.1, 0.3, 1, 0.2, -0.7, 0.1, 0.2, 1), byrow = TRUE, nrow = 4, ncol = 4), residsd = 1, x2binary = FALSE)
n |
number of observations to create. |
mymean |
vector of length 4, giving the mean of each variable. |
mysigma |
variance-covariance matrix of multivariate normal distribution from which x1-x4 are to be drawn. |
residsd |
residual standard deviation. |
x2binary |
if TRUE, x2 is converted to a binary factor variable (1, 2) with probability equal to the logistic of the underlying normally distributed variable. |
Data frame with 5 columns:
y |
continuous, generated by y = x1 + x2 + x3 + normal error if x2 is continuous, or y = x1 + x2 + x3 - 1 + normal error if x2 is a factor with values 1 or 2 |
x1 |
continuous |
x2 |
continuous or binary (factor) with value 1 or 2 |
x3 |
continuous |
x4 |
continuous |
set.seed(1) simdata(n=4, x2binary=TRUE) # y x1 x2 x3 x4 # 1 -0.06399616 -1.23307320 2 -0.6521442 1.6141842 # 2 1.00822173 -0.05167026 1 0.4659907 0.5421826 # 3 2.87886825 0.43816687 1 1.5217240 0.2808691 # 4 0.79129101 -0.72510640 1 0.7342611 0.1820001