Abstract
Frequently, empirical studies rely on a wide variety of variables—so-called item batteries—to describe a certain state of affairs. 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 questions in Fig. 13.1.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsNotes
- 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
Carifio, J., Perla, R. (2008). Resolving the 50-year debate around using and misusing Likert scales. Medical Education, 42, 1150–1152.
Backhaus, K., Erichson, B., Plinke, W., Weiber, R. (2016). Multivariate Analysemethoden. Eine Anwendungsorientierte Einführung, 14th Edition. Berlin, Heidelberg: Springer.
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.
Russell, D.W. (2002). In Search of Underlying Dimension: The Use (and Abuse) of Factor Analysis. Personality and Social Psychological Bulletin, 28(12), 1629-1646.
Widaman, K.F. (1993). Common factor analysis versus principal component analysis: Differential bias in representing model parameters? Multivariate Behavioral Research, 28(3), 263-311.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Cleff, T. (2019). Factor Analysis. In: Applied Statistics and Multivariate Data Analysis for Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-030-17767-6_13
Download citation
DOI: https://doi.org/10.1007/978-3-030-17767-6_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-17766-9
Online ISBN: 978-3-030-17767-6
eBook Packages: Economics and FinanceEconomics and Finance (R0)