To enable comparisons between the various organisations, a Multidimensional
Scaling tool PROXSCAL (PROXimity SCAling) was used,
as this can be very useful in highlighting relationships within data
(Young, 1987; Garson, 2012) and is more flexible for visualising
and data analysing than other methods such as ALSCAL (Jung and
Takane, 2015). PROXSCAL is often used in fields such as ecology
and psychology (Borg and Groenen, 2005; Gatrell 1983), and has
been previously used to visualise correlations in survey responses
(e.g. Grunert et al., 2012). In this study PROXSCAL was used to
compare individual advisors in terms of the measures they recommended
and then derive an overall proximity matrix indicating
the degrees of difference between them. The same data were also
used to assess the similarities between measures in terms of which
advisors recommended them.
To enable comparisons between the various organisations, a MultidimensionalScaling tool PROXSCAL (PROXimity SCAling) was used,as this can be very useful in highlighting relationships within data(Young, 1987; Garson, 2012) and is more flexible for visualisingand data analysing than other methods such as ALSCAL (Jung andTakane, 2015). PROXSCAL is often used in fields such as ecologyand psychology (Borg and Groenen, 2005; Gatrell 1983), and hasbeen previously used to visualise correlations in survey responses(e.g. Grunert et al., 2012). In this study PROXSCAL was used tocompare individual advisors in terms of the measures they recommendedand then derive an overall proximity matrix indicatingthe degrees of difference between them. The same data were alsoused to assess the similarities between measures in terms of whichadvisors recommended them.
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