  The synthpop package for R https://www.synthpop.org.uk provides tools to
allow data custodians to create synthetic versions of confidential microdata
that can be distributed with fewer restrictions than the original. The
synthesis can be customized to ensure that relationships evident in the real
data are reproduced in the synthetic data. A number of measures have been
proposed to assess this aspect, commonly known as the utility of the synthetic
data. We show that all these measures, including those calculated from
tabulations, can be derived from a propensity score model. The measures will be
reviewed and compared, and relations between them illustrated. All the measures
compared are highly correlated and some are shown to be identical. The method
used to define the propensity score model is more important than the choice of
measure. These measures and methods are incorporated into utility modules in
the synthpop package that include methods to visualize the results and thus
provide immediate feedback to allow the person creating the synthetic data to
improve its quality. The utility functions were originally designed to be used
for synthetic data objects of class \code{synds}, created by the \pkg{synthpop}
function syn() or syn.strata(), but they can now be used to compare one or more
synthesised data sets with the original records, where the records are R data
frames or lists of data frames.
