On statistical methods for clustering: a case study on infant mortality, Northern Sweden, 1831-1890

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.