genCorData {simstudy}

Create correlated data

Description

Create correlated data

Usage

genCorData(
  n,
  mu,
  sigma,
  corMatrix = NULL,
  rho,
  corstr = "ind",
  cnames = NULL,
  idname = "id"
)

Arguments

n

Number of observations

mu

A vector of means. The length of mu must be nvars.

sigma

Standard deviation of variables. If standard deviation differs for each variable, enter as a vector with the same length as the mean vector mu. If the standard deviation is constant across variables, as single value can be entered.

corMatrix

Correlation matrix can be entered directly. It must be symmetrical and positive semi-definite. It is not a required field; if a matrix is not provided, then a structure and correlation coefficient rho must be specified.

rho

Correlation coefficient, -1 <= rho <= 1. Use if corMatrix is not provided.

corstr

Correlation structure of the variance-covariance matrix defined by sigma and rho. Options include "ind" for an independence structure, "cs" for a compound symmetry structure, and "ar1" for an autoregressive structure.

cnames

Explicit column names. A single string with names separated by commas. If no string is provided, the default names will be V#, where # represents the column.

idname

The name of the index id name. Defaults to "id."

Value

A data.table with n rows and the k + 1 columns, where k is the number of means in the vector mu.

Examples

mu <- c(3, 8, 15)
sigma <- c(1, 2, 3)

corMat <- matrix(c(1, .2, .8, .2, 1, .6, .8, .6, 1), nrow = 3)

dtcor1 <- genCorData(1000, mu = mu, sigma = sigma, rho = .7, corstr = "cs")
dtcor2 <- genCorData(1000, mu = mu, sigma = sigma, corMatrix = corMat)

dtcor1
dtcor2

round(var(dtcor1[, .(V1, V2, V3)]), 3)
round(cor(dtcor1[, .(V1, V2, V3)]), 2)

round(var(dtcor2[, .(V1, V2, V3)]), 3)
round(cor(dtcor2[, .(V1, V2, V3)]), 2)