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Exporting Marginal Distributions

Obtaining Marginal Distributions

Marginal distributions should first be obtained using the get_marginal_distributions() function.

To obtain the marginal distributions for all variables you should only specify the dataset:

library(RESIDE)
marginals <- get_marginal_distributions(IST)

To obtain marginal distributions for select variables, you should specify the variables using the variables parameter:

library(RESIDE)
marginals <- get_marginal_distributions(
  IST,
  variables = c(
    "SEX",
    "AGE",
    "ID14",
    "RSBP",
    "RATRIAL",
    "SET14D",
    "DSIDED"
  )
)

Printing the Marginal Distributions Prior to Export

Marginal distributions can be printed when generating marginal distributions using the print parameter:

library(RESIDE)
marginals <- get_marginal_distributions(
  IST,
  print = TRUE
)

Or from a stored marginals object:

library(RESIDE)
marginals <- get_marginal_distributions(IST)
print(marginals)

Exporting Marginal Distributions

Marginal distributions can be exported using the export_marginal_distributions() function, specifying the marginal distributions (generated by `get_marginal_distributions()’) and a folder path:

library(RESIDE)
marginals <- get_marginal_distributions(IST)
export_marginal_distributions(
  marginals,
  folder_path = "/Users/ryan/marginals"
)

This folder should exist and not contain any previously exported marginal distributions. You can create the folder automatically using the create_folder parameter:

library(RESIDE)
marginals <- get_marginal_distributions(IST)
export_marginal_distributions(
  marginals,
  folder_path = "/Users/ryan/marginals",
  create_folder = TRUE
)

Files created by `export_marginal_distributions()`

The following files will be created by the export_marginal_distributions() function:

binary_variables.csv - Contains the marginal distributions for binary variables including:
- Variable Name
  - Mean
  - Number of Missing Observations
categorical_variables.csv Contains the marginal distributions for categorical variables including:
- Variable Name & Category Name
- Number of Observations in Each Category
- NB Missing Observations are coded as a separate category labelled missing.
continuous_variables.csv - Contains the marginal distributions for continuous variables including:
- Variable Name
- Transformed Mean
- Transformed Standard Deviation
- Number of Missing Observations
- Number of Decimal Places
continuous_quantiles.csv - Contains the Quantile mapping to allow for back transformation. For each continuous variable this contains:
- The original quantile value
- The transformed quantile value
- An epsilon value to indicate the amount of thinning applied
summary.csv - Contains and overall summary of the dataset including:
- Number of Rows
- Number of Columns
- Variable Names (for validation)

These files should then be sent to the user.

NB If there are no variables of a certain type the corresponding file will not be created.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.

Exporting Marginal Distributions

Obtaining Marginal Distributions

Printing the Marginal Distributions Prior to Export

Exporting Marginal Distributions

Files created by export_marginal_distributions()

Files created by `export_marginal_distributions()`