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Time-Frequency Filtering for Seismic Waves Clustering Read chapter Read first chapter

2014 | OriginalPaper | Chapter

Clustering of Stratified Aggregated Data Using the Aggregate Association Index: Analysis of New Zealand Voter Turnout (1893–1919)

Authors : Eric J. Beh, Duy Tran, Irene L. Hudson, Linda Moore

Published in: Analysis and Modeling of Complex Data in Behavioral and Social Sciences

Publisher: Springer International Publishing

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Abstract

Recently, the Aggregate Association Index (AAI) was proposed to identify the likely association structure between two dichotomous variables of a 2×2 contingency table when only aggregate, or equivalently the marginal, data are available. In this paper we shall explore the utility of the AAI and its features for analysing gendered New Zealand voting data in 11 national elections held between 1893 and 1919. We shall demonstrate that, by using these features, one can identify clusters of homogeneous electorates that share similar voting behaviour between the male and female voters. We shall also use these features to compare the association between gender and voting behaviour across each of the 11 elections.

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previous chapter Modeling Longitudinal Data by Latent Markov Models with Application to Educational and Psychological Measurement
next chapter Estimating a Rasch Model via Fuzzy Empirical Probability Functions
Literature
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Metadata
Title
Clustering of Stratified Aggregated Data Using the Aggregate Association Index: Analysis of New Zealand Voter Turnout (1893–1919)
Authors
Eric J. Beh
Duy Tran
Irene L. Hudson
Linda Moore
Copyright Year
2014
Book
Analysis and Modeling of Complex Data in Behavioral and Social Sciences

Print ISBN: 978-3-319-06691-2

Electronic ISBN: 978-3-319-06692-9

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-319-06692-9_3

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