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Synthesise data from marginal distributions

synthesise_data.Rd

Allows the synthesis of data from marginal distributions obtained from a Trusted Research Environment (TRE)

Usage

synthesise_data(marginals, correlation_matrix = NULL, correlations = NULL, ...)

synthesize_data(marginals, correlation_matrix = NULL, correlations = NULL, ...)

Arguments

marginals

an object of class RESIDE

correlation_matrix

No longer supported, use correlations. Default: NULL

correlations

A list of correlations created with the correlation function, Default: NULL

...

Additional parameters currently none are used.

Value

a data frame of simulated data, or a named list of data frames for marginals from multiple data frames.

Details

This function will synthesise a dataset from marginals imported using import_marginal_distributions. By default the dataset will not contain correlations, however user specified correlations can be added using the correlations parameter, see correlation. Categorical variables are correlated using a single category, specified with factor_name.x or factor_name.y. Correlated variables are synthesised together, one row per subject, and joined to each data frame by subject. Correlated variables therefore take a single value per subject within each data frame. It is not possible to entirely maintain the marginal distributions when specifying correlations.

See also

correlation

Examples

marginals <- get_marginal_distributions(
  IST,
  variables = c("SEX", "AGE", "RSBP", "RATRIAL")
)
df <- synthesise_data(marginals)
df_cor <- synthesise_data(
  marginals,
  correlations = list(
    correlation("AGE", "RSBP", 0.3),
    correlation("SEX", "AGE", -0.2, factor_name.x = "M")
  )
)