# genCorData: Create correlated data In kgoldfeld/simstudy: Simulation of Study Data

## Description

Create correlated data

## Usage

 ```1 2``` ```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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```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) ```

kgoldfeld/simstudy documentation built on Nov. 8, 2018, 7:41 p.m.