Abstract
This paper considers partial homogeneity of a population within the context of Bayesian population variability analyses. Partial homogeneity is defined as a condition in which within an otherwise non-homogeneous population, homogeneous sub-populations can be recognized. Partial homogeneity can be modelled using a revised likelihood model. Doing so results in an increase of the inferential strength of the available evidence and reduction of uncertainty bounds, even though a failure to recognize partial homogeneity does not invalidate the population variability analysis.
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Groen, F.J., Mosleh, A., Droguett, E.L. (2004). Treatment of Partial Homogeneity in Population Variability Analysis of Data. In: Spitzer, C., Schmocker, U., Dang, V.N. (eds) Probabilistic Safety Assessment and Management. Springer, London. https://doi.org/10.1007/978-0-85729-410-4_169
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DOI: https://doi.org/10.1007/978-0-85729-410-4_169
Publisher Name: Springer, London
Print ISBN: 978-1-4471-1057-6
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