Download Analysis of Multivariate Social Science Data, Second Edition by Bartholomew, David J. PDF

By Bartholomew, David J.

ISBN-10: 1584889616

ISBN-13: 9781584889618

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16 Dendrogram for farthest neighbour (complete linkage) cluster analysis for the attitude to abortion data (distance = 11 − similarity) pattern 16 (1111) and other patterns with several 1s. 15. Perhaps respondents in cluster 1 have a generally unfavourable attitude to abortion while those in cluster 2 have a more favourable attitude. But there are two exceptions. © 2008 by Taylor and Francis Group, LLC ADDITIONAL EXAMPLES AND FURTHER WORK 51 Pattern 3 (0010) has been allocated to cluster 2 and pattern 14 (1101) to cluster 1.

We shall review a few of them beginning with the case when all of the xs are continuous. Distance and similarity measures between objects based on continuous variables The most commonly used distance measure is Euclidean distance. The Euclidean distance between objects i and j is p (xik − xjk )2 . 1) k=1 For p = 2, the Euclidean distance corresponds to the “straight line” distance between the two points (xi1 , xi2 ) and (xj1 , xj2 ). Often the variables (columns in the data matrix) will be standardized prior to calculating distances.

Different variables might be used in subdividing different clusters. ii) Non-hierarchical methods. These come in many forms. Some use multivariate analysis of variance ideas in the sense that they divide the objects into groups such that the between-group variation is large and the within-group variation is small. One of the most intriguing is known as “Chernoff’s faces”. The value of each variable determines one feature of a human face — for example, whether the mouth is turned up or down at the corners.

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