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| dc.contributor.editor | ROBERT D. HOPPA JAMES W. VAUPEL | |
| dc.date.accessioned | 2019-02-19T06:46:30Z | |
| dc.date.accessioned | 2023-07-22T06:49:19Z | |
| dc.date.available | 2019-02-19T06:46:30Z | |
| dc.date.available | 2023-07-22T06:49:19Z | |
| dc.date.issued | 2002 | |
| dc.identifier.isbn | 978-0-511-06326-8 | |
| dc.identifier.uri | http://10.215.13.25/handle/123456789/45080 | |
| dc.description | In June 1999, the Laboratory of Survival and Longevity at the Max Planck Institute for Demographic Research in Rostock, Germany, hosted a threeday workshop entitled ‘‘Mathematical Modelling for Palaeodemography: Coming to Consensus’’. The title chosen reflected two issues the workshop was meant to deal with. First, the use of biostatistical methods as a means for estimating demographic profiles from skeletal data was clearly emerging as the right direction for the future. A number of individuals were invited who had published such techniques. Second, coming to consensus was a play on words for evaluating and finding a methodological approach that best did the job for paleodemography. The initial workshop focused specifically on adult aging techniques. This was partly a reflection of the need to find methods that could capture the right-most tail of the age distribution in archaeological populations — the oldest old. Although nonadult aging techniques have increased levels of accuracy and precision, assessing the complete age structure of the population is absolutely imperative. The statistical approaches presented in this volume, while presented in the context of adult age estimation, are more broadly applicable to age indicator methods for any group (see e.g., Konigsberg and Holman 1999). The purpose of the workshop was to provide individuals with an identical dataset on which to test their techniques. Thus everyone would be able to use their methods to estimate the demographic profile for a real target sample using a series of skeletal age indicator stages for which known-age data were associated, but not revealed. The assumption here was that, for the first time, the presentation of these newly emerging statistical techniques could be evaluated in terms of their accuracy and reliability in estimating age profiles on a level playing field — comparing apples with apples, if you will. | |
| dc.language | en | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Cambridge University Press | en_US |
| dc.subject | Age distributions | en_US |
| dc.title | Paleodemography | en_US |
| dc.type | Book | en_US |
