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

The difficulty with using t-tests is that multiple significance testing gives a high
probability of a type 1 error (a false positive result) because the probability becomes
much more than 5%. Duncan's multiple range test controls the overall type 1 error rate
at no more than 5% using the Bonferroni correction for multiple comparisons. The
procedure is suitable for groups with uncorrected variances and can also be adjusted for
unbalanced design 261 . The disadvantage of this and similar methods available on SPSS is
that they are 'conservative' so that errors are on the side of safety (non-significance).
Therefore small numbers of group comparisons (up to 5) are recommended, with
specified research objectives 262 . In addition, since it is likely that some of the measures
for ANOVA are correlated: in real life we can assume some correlation between multiple
tests, it is more likely that the Bonferroni estimate would be conservative, placing any
suspicion on non-significant data.
Discriminatory power between controls and patients
This final analysis aims to give distinct answers to 2 direct questions;
(i) Is the DAPA as effective as other art assessments; and
(ii) can the DAPA practically discriminate between patients and controls.
These two questions need to be attacked differently because they are respectively
conjectural and pragmatic; (i) is answered through the illustration of effect sizes from t-
test results, using the methodology explained in Chapter 2, which derived effect sizes for
261
It is a popular misconception that groups must be orthogonal for comparison tests, R. West (1991),
Computing for Psychol ogists (London: Harwood).
262 D.G. Altman (1994),
Practical Statistics for Medical Research , London, 3rd. reprint, original 1991:
208