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30 quartz grains. OSL ages were calculated using both the finite mixture model and minimum age model; comparison of the ages for samples with radiocarbon ages for overlying organic-rich sediment indicates that the finite mixture model gives more accurate results. Samples collected from along the same reach of palaeochannel do not always give consistent burial ages, and careful interpretation of the results is needed. This study demonstrates the importance of the selection of sample locations, and the need for appropriate analysis of the equivalent dose distributions to derive the burial dose and hence the age of a sample.
doi:10.1016/S0167-9473(02)00187-1 
Copyright © 2002 Elsevier Science B.V. All rights reserved.
Finite Mixture, Zero-inflated Poisson and Hurdle models with application to SIDS
Received 1 February 2002;
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Abstract
This study examines the incidence of sudden infant death syndrome (SIDS) in Canterbury (1973–1989) in relation to climate. Three mixture models (Finite Mixture, Zero-inflated Poisson and Hurdle) are used as novel methods which are able to highlight differential effects of climatic covariates between months of SIDS and no SIDS. These methods accommodate the extra zeros, heterogeneity and autocorrelation found in the SIDS series. Mixture models are comprehensive methods applicable to many discrete chronological series including the Canterbury SIDS data. This analysis leads to a better understanding of the association between climate and SIDS deaths.
Results show a deviance-temperature (a measure of extreme change from the fortnightly average) is significantly associated with SIDS risk (p<0.005). Months where there is a high deviance-temperature are associated with increased risk of SIDS, compared to months where the temperature has remained reasonably constant. This finding is consistent with the theory that hyperthermia, or overheating of infants leads to increased SIDS risk. In months where at least one SIDS death occurs, increased humidity leads to increased risk of SIDS (p<0.001).
Author Keywords: Mixture models; Heterogeneity; Excess zeros; Sudden infant death syndrome; Climate
