On Statistical Methods for Clustering

This article considers the interfamily clustering of infant mortality (defined as mortality during the first year of life). We developed and evaluated statistical tools to detect clustering and a measure to quantify excess clustering for nineteenth-century data from Skellefteå, Sweden. The detection was performed using the standard methods of generalized linear models and logistic regression. The index of clustering was constructed by comparing the observed numbers of families with specific numbers of deaths to the corresponding observed numbers, after correcting for explanatory variables. To the best of our knowledge, no clustering index of this kind has ever been created

Cluster analysis · Econometrics · Logistic regression · Sociology · Statistics · Census and Population Estimation · Computer Science · demographic modeling and climate adaptation · Demography · Historical and modern epidemiology studies · Mathematics

• Early-life mortality clustering in families

  Open Access•Ingrid K Van Dijk•Population Studies•2019

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• Exploring unobserved heterogeneity in perinatal and neonatal mortality risks

  Francesco Scalone, Patrizia Agati et al.•Population Studies•2017

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• Use of Sibling Data to Estimate Family Mortality Effects in Guatemala

  Open Access•G Guo•Demography•1993

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• Risk Factors for Infant Mortality in Nineteenth-Century Sweden

  Katherine A Lynch, Joel B Greenhouse•Population Studies•1994

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• Socio-economic Status and Clustering of Child Deaths in Rural Punjab

  M Das Gupta•Population Studies•1997

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• High-risk families

  Edvinsson, Sören Edvinsson et al.•Population Studies•2005

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• Death Clustering, Mothers' Education and the Determinants of Child Mortality in Rural Punjab, India

  M Das Gupta•Population Studies•1990

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