comparative value priorities of chinese and new zealand

East Asia. China and New Zealand were not included. Schwartz and Boehnke’s
analyses concluded that with this set of samples, the Quasi-Circumplex model shown in
Figure 4.9 was validated. This result would be more convincing with a more globally
representative set of countries sampled.
Spini (2003) used nested multigroup confirmatory factor analysis, effectively an itemto-scale
reliability analysis, to examine the reliability properties of each of the ten SVS
individual values separately, accepting the assumption that the ten dimensions were a
valid description of societal culture. The confirmatory factor models demonstrated that
configural and metric equivalence and factor variance invariance (Van de Vijver and
Leung, 1997a, 1997b) held for most value types across 21 national university student
samples. The only exception is Hedonism for which metric equivalence was rejected
and configural equivalence impossible to evaluate due to too few items in the scale.
Spini generally confirms Schwartz (1994) and Schwartz and Sagiv (1995) that the SVS
is a legitimate instrument for cross-cultural research, perhaps with the exception of the
Hedonism dimension.
The distributions of scores for most value items deviate from normality; well over 90%
of the items for both samples have negative skewness. Large sample sizes are needed
for assurance of reliability, especially given the relatively large number of items in the
SVS. Schwartz’ original multi-country samples for generating and validating the theory
had an average sample size of only 244 respondents per sample; with 57 value items
(multi-group CFA is a questionable procedure for studying structural variation across
the societies with small samples).
Fontaine, Poortinga, Delbeke and Schwartz (2008) selected original SVS project data
from 38 countries that had both a student and a teacher sample; these included China
and New Zealand. They examined the cross-cultural equivalence of the internal
structure of the SVS values domain. The authors sought to distinguish between lack of
fit of the theorized value model from a lack of equivalence in the data, and the impact of
random sampling fluctuations, from valid structural differences. The authors found the
following, quoted directly from the article:
� sampling fluctuation causes deviations from this average structure;
� sampling fluctuation cannot account for all these deviations;
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