A Bayesian analysis of suicide data

A Bayesian analysis of suicide data The identification of change points in a sequence of suicide rates is one of the fundamental aspects of Durkheim’s theory. The specification of a statistical standard suitable for this purpose is the main condition for making inferences about the causes of suicide with distinctive trends of persistency and variability just as Durkheim theorized. At present, the statistical ‘strategy’ employed by the French social scientist is too ‘rudimentary’. A hundred years later, I take the opportunity to test Durkheim’s theory through modern methodological instruments, specifically the Bayesian change-point analysis. First of all, I analyzed the same suicide data which Durkheim took into consideration. Change-point analysis corroborates the Durkheimian analysis revealing the same change-points identified by the author. Secondly, I analyzed Italian suicide rates from 1864 to 2005. The change-point analysis was very useful. Durkheim’s theory ‘works’ until 1961: suicides rates increased as industrial development increased. However, after 1961 and the economic boom, they declined, and when they began increasing again, after 1984, they did not reach the same level as before. This finding obliges us to ‘adjust’ the Durkheim’s theory giving space to Halbwach’s convergence law. Therefore, as high economic and social development levels are attained, suicide rates tend to level-off: People adapt to the stress of modernization associated to low social integration levels. Although we are more ‘egoist’, individualism does not destroy identity and the sense of life as Durkheim had maintained. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

A Bayesian analysis of suicide data

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Springer Netherlands
Copyright © 2011 by Springer Science+Business Media B.V.
Social Sciences, general; Methodology of the Social Sciences; Social Sciences, general
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