Compare univariate distributions of synthesised and observed data

Compare synthesised data set with the original (observed) data set using percent frequency tables and histograms. When more than one synthetic data set has been generated (object$m > 1), by default pooled synthetic data are used for comparison.

This function can be also used with synthetic data NOT created by syn(), but then an additional parameter cont.na might need to be provided.

Usage

# S3 method for synds
compare(object, data, vars = NULL,
        msel = NULL, stat = "percents", breaks = 20,
        nrow = 2, ncol = 2, rel.size.x = 1,
        utility.stats = c("pMSE", "S_pMSE", "df"),
        utility.for.plot = "S_pMSE",
        cols = c("#1A3C5A","#4187BF"),
        plot = TRUE, table = FALSE, ...)

# S3 method for data.frame
compare(object, data, vars = NULL, cont.na = NULL,
        msel = NULL, stat = "percents", breaks = 20,
        nrow = 2, ncol = 2, rel.size.x = 1,
        utility.stats = c("pMSE", "S_pMSE", "df"),
        utility.for.plot = "S_pMSE",
        cols = c("#1A3C5A","#4187BF"),
        plot = TRUE, table = FALSE, ...)

# S3 method for list
compare(object, data, vars = NULL, cont.na = NULL,
        msel = NULL, stat = "percents", breaks = 20,
        nrow = 2, ncol = 2, rel.size.x = 1,
        utility.stats = c("pMSE", "S_pMSE", "df"),
        utility.for.plot = "S_pMSE",
        cols = c("#1A3C5A","#4187BF"),
        plot = TRUE, table = FALSE, ...)

# S3 method for compare.synds
print(x, ...)

Arguments

object: An object of class synds, which stands for 'synthesised data set'. It is typically created by function syn() and it includes object$m synthesised data set(s) as object$syn. Alternatively, when data are synthesised not using syn(), it can be a data frame with a synthetic data set or a list of data frames with synthetic data sets, all created from the same original data with the same variables and the same method.
data: An original (observed) data set.
vars: Variables to be compared. If vars is NULL (the default) all synthesised variables are compared.
msel: Index or indices of synthetic data copies for which a comparison is to be made. If NULL pooled synthetic data copies are compared with the original data.
stat: Determines whether tables and plots present percentages (stat = "percents"), the default, or counts (stat = "counts"). If m > 1 and msel = NULL average counts for synthetic data are derived.
breaks: The number of cells for the histogram.
nrow: The number of rows for the plotting area.
ncol: The number of columns for the plotting area.
rel.size.x: A number representing the relative size of x-axis labels.
utility.stats: A single string or a vector of strings that determines which utility measures to print. Must be a selection from: VW, FT, JSD, SPECKS, WMabsDD, U, G, pMSE, PO50, MabsDD, dBhatt, S_VW, S_FT, S_JSD, S_WMabsDD, S_G, S_pMSE, df. If utility.stats = "all", all of these will be printed. For more information see the details section for utility.tab.
utility.for.plot: A single string that determines which utility measure to print in facet labels of the plot. Set to NULL to print variable names only.
cols: Bar colors.
plot: A logical value with default set to TRUE indicating whether plots should be produced.
table: A logical value with default set to FALSE indicating whether tables should be printed.
...: Additional parameters.
cont.na: A named list of codes for missing values for continuous variables if different from the R missing data code NA. The names of the list elements must correspond to the variables names for which the missing data codes need to be specified.

Value

An object of class compare.synds which is a list including a list of comparative frequency tables (tables) and a ggplot object (plots) with bar charts/histograms. If multiple plots are produced they and their corresponding frequency tables are stored as a list.

Details

Missing data categories for numeric variables are plotted on the same plot as non-missing values. They are indicated by miss. suffix.

Numeric variables with fewer than 6 distinct values are changed to factors in order to make plots more readable.

References

Nowok, B., Raab, G.M and Dibben, C. (2016). synthpop: Bespoke creation of synthetic data in R. Journal of Statistical Software, 74(11), 1-26. DOI: 10.18637/jss.v074.i11

Examples

if (FALSE) {
ods <- SD2011[, c("sex", "age", "edu", "marital", "ls", "income")]
s1 <- syn(ods, cont.na = list(income = -8))

# synthetic data provided as a 'synds' object
compare(s1, ods, vars = "ls")
compare(s1, ods,
  vars = "income", stat = "counts",
  table = TRUE, breaks = 10
)

# synthetic data provided as 'data.frame'
compare(s1$syn, ods, vars = "ls")
compare(s1$syn, ods,
  vars = "income", cont.na = list(income = -8),
  stat = "counts", table = TRUE, breaks = 10
)
}