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Ecological Analyses in Electoral Research

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EN
In social sciences we often have to do with aggregated data which pose both methodological and practical problems. Erroneous inference of individual characteristics and behaviors from this kind of data, described and named by Robinson as 'ecological fallacy', has been known for more than fifty years now. Several statistical approaches were developed to deal with the problem and produce valid and reliable results. This paper provides on overview of the most popular and frequently used methods of ecological inference. First one is ecological regression as developed by Goodman in a direct answer to Robinson's article. The last one is quite new entropy maximization approach. The purpose of paper is to give Polish reader a review of useful techniques in analysis of aggregate data along with their pros and cons. .
Sociológia (Sociology)
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2015
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vol. 47
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issue 4
340 – 364
EN
This study addresses the often debated importance of structure for explaining voting behaviour and cleavage formation in post-communist countries. Based on ecological analysis this study applies multivariate regression analysis (MRA) to test the possibilities and limits of structure in explaining the results of the 2012 parliamentary elections and 2014 presidential elections in Slovakia. The study reveals the high importance of general structure compared to findings in Western Europe, as all tested structural factors together explain from 46 to 77 per cent of electoral variation for the parliamentary election and from 25 to almost 99 per cent of the presidential candidates’ support. MRA confirms some findings from previous research, e.g. the significance of ethnicity and the rural-urban divide. However, our model does not confirm the strength of the religious factor for the Christian Democrats (KDH). Discussing the findings, the study suggests that to improve structure-based explanations in post-communist countries it is necessary to adjust the conceptualization of the structure to fit the region’s unique history.
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