Simulate Covariate Data

Generates a covariate matrix mimicking FeatureExtraction output.

Usage

simulateCovariateData(n = 1000, nCovariates = 50, seed = 42)

Arguments

n

Number of individuals.

nCovariates

Number of covariates to generate.

seed

Random seed for reproducibility.

Value

A data frame with person_id and nCovariates columns of binary or continuous covariates.

Examples

covData <- simulateCovariateData(n = 100, nCovariates = 10)
head(covData)
#>   person_id covariate_1 covariate_2 covariate_3 covariate_4 covariate_5
#> 1         1           1           0           0           0           0
#> 2         2           0           0           0           1           1
#> 3         3           1           1           0           0           0
#> 4         4           0           1           1           0           0
#> 5         5           0           0           0           0           0
#> 6         6           1           0           0           0           0
#>   covariate_6 covariate_7 covariate_8 covariate_9 covariate_10
#> 1   1.2449329   0.5428314   1.5977432   0.3625802    1.2499199
#> 2  -1.0512478  -0.5304505  -0.6919057  -0.2747531    1.1463134
#> 3  -0.6650712   0.1811529  -1.1865409   1.1425879   -0.0569313
#> 4   0.7340706   1.1606279  -0.4467962  -0.3645218    0.5824822
#> 5  -0.5089338   0.6364922   1.3443038   0.6579949   -0.4493756
#> 6  -0.4272471   0.5952489   0.7001235  -1.2361387   -0.4379546