The psychopathology of everyday art: a quantitative Study - World ...

addition it leaves out other variables which are not necessarily non-discriminatory
independently, but their ability to add to the discrimination having taken account of the
other variables already used is judged low. It reduces the test to a subset of useful
variables from a larger set of candidates and indicates to what extent a combination of
independent variables will allow discrimination between controls and patients.
Discriminant analysis was used to find a combination of variables that
classified a large proportion of subjects into the correct group as an instrument of
allocation or diagnosis for new subjects. The analysis used the same subject group
detailed in table 1 (109 subjects: 23 controls and 86 patients). The method is robust and
makes few assumptions, but two recommendations are suggested for the sake of
interpretation 263 :
1. that most variables have a normal distribution with the same s.d. within each group
(although some authorities have argued that discriminant analysis is robust for binary
distributions); and
2. five times as many subjects are recommended per group as variables.
It was appropriate to consider this method, then, for 2 groups: patients and controls;
subgroup analysis would require more cases. The Mahalanobis method, which is a
variation on the stepwise method, was selected. Using SPSS, the steps of the calculation
are clearly shown. The analysis works by finding a combination of variables that
maximises the distance (D 2 ) between the groups. It may, perhaps, do slightly less well
263 Altman (1994), op.cit. recommends that in order to correctly interpret the associated significance that
variables should have a normal distribution, but generally authorities are mixed on whether this issue is
critical.
210