Abstract
Frequently, empirical studies rely on a wide variety of variables – so-called item batteries – to describe a certain state of affairs (Fig. 8.1). An example for such a collection of variables is the study of preferred toothpaste attributes by Malhotra (2010, p. 639). Thirty people were asked the following questions:
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Notes
- 1.
A discussion of the anti-image covariance matrix (AIC) lies beyond the scope of this book, though most software programmes are able to calculate it.
- 2.
There are other rotation methods in addition to varimax, e.g. quartimax, equamax, promax, and oblimin. Even within varimax rotation, different calculation methods can be used, yielding minor (and usually insignificant) differences in the results.
- 3.
prevent cavities: agree = 6 → z = 1.04; whiten teeth: agree = 2 → z = -1.38; strengthen gums: totally agree = 7 → z = (1.41); freshen breath: neither agree or disagree = 4 → z = (-0.07); not prevent tooth decay: totally disagree = 1 → z = (-1.31); make teeth attractive: somewhat disagree = 3 → z = (-0.84).
References
Backhaus, K., Erichson, B., Plinke, W., & Weiber, R. (2008). Multivariate analysemethoden. Eine Anwendungsorientierte Einführung (12th ed.). Berlin, Heidelberg: Springer.
Carifio, J., & Perla, R. (2008). Resolving the 50-year debate around using and misusing Likert scales. Medical Education, 42, 1150–1152.
Enders, C. K. (2010). Applied missing data analysis. New York: Guilford Press.
Kaiser, H. F., & Rice, J. (1974). Little Jiffy, Mark IV. Educational and Psychological Measurement, 34, 111–117.
Malhotra, N. K. (2010): Marketing Research. An Applied Approach, 6th Global Edition, London: Pearson.
Pell, G. (2005). Use and misuse of Likert scales. Medical Education, 39, 970.
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Cleff, T. (2014). Factor Analysis. In: Exploratory Data Analysis in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-01517-0_8
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