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How do you classify various multivariate techniques?

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CLASSIFICATION OF MULTIVARIATE TECHNIQUES

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CLASSIFICATION OF MULTIVARIATE TECHNIQUES

Today, there exist a great variety of multivariate techniques which can be conveniently classified into two broad categories viz., dependence methods and interdependence methods. This sort of classification depends upon the question: Are some of the involved variables dependent upon others? If the answer is ‘yes’, we have dependence methods; but in case the answer is ‘no’, we have interdependence methods. Two more questions are relevant for understanding the nature of multivariate techniques. Firstly, in case some variables are dependent, the question is how many variables are dependent? The other question is, whether the data are metric or non-metric? This means whether the data are quantitative, collected on interval or ratio scale, or whether the data are qualitative, collected on nominal or ordinal scale. The technique to be used for a given situation depends upon the answers to all these very questions. Jadish N. Sheth in his article on “The multivariate revolution in marketing research” has given the flow chart that clearly exhibits the nature of some important multivariate techniques as shown in Fig. below. Thus, we have two types of multivariate techniques: one type for data containing both dependent and independent variables, and the other type for data containing several variables without dependency relationship. In the former category are included techniques like multiple regression analysis, multiple discriminant analysis, multivariate analysis of variance and canonical analysis, whereas in the latter category we put techniques like factor analysis, cluster analysis, multidimensional scaling or MDS (both metric and non-metric) and the latent structure analysis.