comparative value priorities of chinese and new zealand

Initial mailings in 2004 used pre-printed mailing labels and yielded only a 1.4% return.
After the initial mailing monthly batches were mailed with addresses hand-written on
the envelopes, which increased the return rate, varying from approximately 5% during
the summer months to approximately 15% in November to mid-December. Collecting
data in New Zealand proved to be particularly expensive using mail as the delivery and
return mechanism, averaging approximately NZ$20 per survey returned. In retrospect,
employing people to deliver and retrieve the surveys in New Zealand as I did in China
might have been less expensive than mail. Mail appears to be more effective in the
spring months. Surveys were qualified and data entered and cleaned as they were
received, and 222 valid surveys were obtained when money and time ran out.
METHODS OF ANALYSIS
Before analysis, data for both surveys were cleaned according to standards specified in
Appendix 5 - Data Cleaning.
As correlation analysis tests co-variation of scores rather than differences in magnitude
of scores, raw scores for the samples will be employed for correlations. As Structural
Equation analysis is a correlation technique, raw scores will be used for those analyses.
Based upon the techniques applied in studies employed using the LBDQXII and the
SVS, the following common analysis procedures were employed.
� Internal reliability is tested by Cronbach alpha scores and item-to-scale
correlations, to evaluate reliability of the scales operationalising the dimensions.
� Structural Equation Modelling analysis is employed to test the goodness of fit of
the sample data to the theoretical models operationally defined by the SVS and
LBDQXII.
� Correlational analysis is employed to investigate the relationships between value
dimensions and preferred leader behaviour dimensions. This is a widely used
technique, providing clear indications of the existence of relationships between
variables. Correlational analysis will also be employed to identify any possible
covariables that could affect differences between the country samples.
� Analysis of variance and covariance will be used to test differences between the
samples, comparing mean differences on and amongst the SVS and LBDQXII
dimensions.
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