2000115-Strengthening-Communities-with-Neighborhood-Data

Advances in Analytic Methods for Neighborhood Data 293
methodological advances are the development of indexes of well-being
applicable to small areas and the creation of typologies of places.
There is a long history of efforts to develop indexes that can provide
a comprehensive measure of the overall well-being of the population
(Hagerty et al. 2001; Hagerty and Land 2007; Land 2000). Most of this
work has been at the national level, or has been comparative across nations,
and has focused on quality of life across multiple domains. Much has been
learned over the years about how to formulate multi-indicator indexes,
and many of the principles can be applied to small areas such as neighborhoods.
First, each of the indicators that go into the index should be as
reliable as possible. Second, the indicators must be standardized or put
on a common scale in order to combine them. Third, a decision has to
be made about how to weight the indicators relative to one another. They
can be weighted equally, but this is still a choice and requires justification.
Fourth, it is important to be aware of the degree to which the indicators are
correlated with one another and the pattern of the correlations. Depending
on the purpose of the index, the indicators do not necessarily need
to be correlated, but an index that is multidimensional may need to be
decomposed into its subcomponents for additional analysis. Finally, it
is desirable that the index be tested against external criteria to determine
its validity. These criteria would ideally be both objective (e.g., in
predicting trends or events) and subjective (e.g., as compared with the
judgment of individuals).
The Child Well-Being Index in England (Bradshaw et al. 2009), which
relies on administrative records data collected for all locales in the nation
and is estimated for small areas with populations of approximately 1,500,
is an example of a carefully developed small-area index. Its basic indicators
are rates and proportions. When the rates are deemed unreliable due
to small numbers, shrinkage estimates (see above) are used to reduce
the margin of error (Noble et al. 2006). All indicators are standardized
before being summed into one of several domains. Within domains,
varying weights are applied. In some domains, equal weights are applied
and in others, the weights are generated through factor analysis. The
domains are then summed to form an index that allows all areas to
be ranked.
A challenge for any indexes of well-being is to establish the correct
weights for combining the individual indicators (Noble et al. 2006). When
this is done by factor analysis, the weights come from the overall contribution
of each indicator to the common variance among them. If the