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Fordisc and the Determination of Ancestry from Craniometric Data FORDISC AND THE DETERMINATION OF ANCESTRY FROM CRANIOMETRIC DATA By Marina Elliott B.A., The University of British Columbia, 2005 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS In THE DEPARTMENT OF ARCHAEOLOGY © Marina Elliott, 2008 SIMON FRASER UNIVERSITY Summer 2008 All rights reserved. This work may not be reproduced in whole or in part, by photocopy or other means, without permission of the author. APPROVAL Name: Marina Elliott Degree: Master of Arts Title of Thesis: FORDISC and the determination of ancestry from craniometric data Examining Committee: Chair: Catherine D'Andrea Graduate Program Chair Mark Collard Senior Supervisor Associate Professor, Archaeology Mark Skinner Supervisor Professor, Archaeology Brian Chisholm Internal Examiner Senior Instructor, University of British Columbia Date Defended/Approved: ii SIMON FRASER UNIVERSITY LIBRARY Declaration of Partial Copyright Licence The author, whose copyright is declared on the title page of this work, has granted to Simon Fraser University the right to lend this thesis, project or extended essay to users of the Simon Fraser University Library, and to make partial or single copies only for such users or in response to a request from the library of any other university, or other educational institution, on its own behalf or for one of its users. The author has further granted permission to Simon Fraser University to keep or make a digital copy for use in its circulating collection (currently available to the public at the "Institutional Repository" link of the SFU Library website <www.lib.sfu.ca> at: <http://ir.lib.sfu.ca/handle/1892/112>) and, without changing the content, to translate the thesis/project or extended essays, if technically possible, to any medium or format for the purpose of preservation of the digital work. The author has further agreed that permission for multiple copying of this work for scholarly purposes may be granted by either the author or the Dean of Graduate Studies. It is understood that copying or publication of this work for financial gain shall not be allowed without the author's written permission. Permission for public performance, or limited permission for private scholarly use, of any multimedia materials forming part of this work, may have been granted by the author. This information may be found on the separately catalogued multimedia material and in the signed Partial Copyright Licence. While licensing SFU to permit the above uses, the author retains copyright in the thesis, project or extended essays, including the right to change the work for subsequent purposes, including editing and publishing the work in whole or in part, and licensing other parties, as the author may desire. The original Partial Copyright Licence attesting to these terms, and signed by this author, may be found in the original bound copy of this work, retained in the Simon Fraser University Archive. Simon Fraser University Library Burnaby, BC, Canada Revised: Fall 2007 Abstract FORDISC is a computer program designed to determine ancestry from human skeletal remains. It is widely used, yet its accuracy has been challenged. In this study, 200 specimens from one of FORDISC's reference samples are used to investigate four issues that are central to debate: (1) the inclusion of the source population in the reference sample, (2) the influence of sex, (3) the impact of variable number, and (4) the effect of different anatomical regions. The results indicate that the source population must be present and the sex of the specimen known before FORDISC can provide an accurate determination of ancestry. Additionally, a determination will be successful only if more than 10 measurements pertaining to multiple anatomical regions are used. Even when these conditions are met, few determinations may be considered unambiguously correct. Overall, FORDISC performed below expectations and the results suggest that the program should be used cautiously. Keywords: FORDISC; ancestry determination; cranial morphology; forensic identification; discriminant function analysis Subject Terms: biological anthropology; forensics; craniometry; skull; human variation iii Acknowledgements This research could not have happened without the encouragement and assistance of many people. In particular, I would like to thank my supervisor, Dr. Mark Collard for his generous advice, support and patience throughout this process. In addition to all of his other duties and responsibilities, he always seemed to have time for my questions and concerns. I would also like to thank my committee members, Dr. Mark Skinner and Dr. Brian Chisholm, both of whom took precious time out of their summer schedules to read and provide feedback on this research. In addition, I am extremely fortunate to have an excellent group of colleagues, friends and family members. I am especially grateful to Alan Cross, Mana Dembo, Kevan Edinborough, Luseadra McKerracher and the other members of the Laboratory of Biological Anthropology whose intelligence, curiosity and enthusiasm for their research inspired my own efforts. Many thanks also go to my friends and family for providing valuable comments, welcome distractions and incalculable kindnesses along the way. Although no words can truly express how lucky I am to have them, thanks also go to my parents - their example gives me something to strive for. Finally, I would like to thank my husband, Robin Elliott. His writing and editing contributions were invaluable, as were his computer skills when things went awry. More importantly, his love, support, encouragement and apparently endless tolerance of my interests (academic and otherwise) are a constant source of wonder and admiration to me. I hope I have made him proud. iv Table of Contents Approval ii Abstract iii Acknowledgements iv Table of Contents v List of Tables vii List of Figures viii 1. Introduction 1 1.1. Aims and objectives 1 1.2. FORDISC and its applications 3 1.3. The FORDISC debate 6 1.4. Issues investigated 12 1.5. Outline of analyses 16 2. Materials and Methods 18 2.1. Data 18 2.2. Analyses 20 3. Results 28 3.1. Impact of including source population and specifying sex 28 3. 1. 1. Number ofcorrect assignments accepting all posterior and typicality probabilities 28 3.1.2. Number ofcorrect assignments using >0.5 posterior probability and >0.01 typicality probability 31 3.1.3. Number ofcorrect assignments using >0.8 posterior probability and >0.01 typicality probability 32 3. 1.4. Summary 33 3.2. Impact of variable number 34 3.2. 1 Number ofcorrect assignments accepting all posterior and typicality probabilities 34 3.2.2 Number ofcorrect assignments using >0.5 posterior probability and >0.01 typicality probability 36 3.2.3. Number ofcorrect assignments using >0.8 posterior probability and >0.01 typicality probability 38 3.2.4. Variable number and population differences 39 3.2.4.1. Number ofcorrect assignments accepting all posterior and typicality probabilities 39 3.2.4.2 Number ofcorrect classifications using >0.5 posterior probability and >0.01 typicality probability 44 3.2.4.3 Number ofcorrect classifications using >0.8 posterior probability and >0.01 typicality probability 46 3.2.5. Summary 48 3.3 Impact of cranial region 49 v 3.3. 1. Number of correct assignments accepting all posterior and typicality probabilities 49 3.3.2. Number of correct assignments using >0.5 posterior probability and >0.01 typicality probability 51 3.3.3. Number of correct assignments using >0.8 posterior probability and >0.01 typicality probability 53 3.3.4. Cranial region and population differences 54 3.3.4.1. Number ofcorrect assignments accepting all posterior and typicality probabilities 54 3.3.4.2. Number ofcorrect assignments using >0.5 posterior probability and >0.01 typicality probability 58 3.3.5. Summary 61 4. Discussion 62 4.1. Main findings 62 4.2. Implications for use of FORDISC 66 4.3. Future considerations 70 5. Conclusions 74 References 78 Appendix I 86 Appendix II 89 Appendix III 91 vi List of Tables Table 1. Total number of test specimens correctly classified (n=200) 30 Table 2. Number of test specimens correctly classified using >0.5 posterior probability and >0.01 typicality probability (n=200) 32 Table 3. Number of test specimens correctly classified using >0.8 posterior probability and >0.01 typicality probability (n=200) 33 Table 4. Total number of test specimens correctly classified by variable number (n=200) 36 Table 5. Number of test specimens correctly classified using >0.5 posterior probability and >0.01 typicality probability (n=200) 38 Table 6. Number of test specimens correctly c1assi'fied using >0.8 posterior probability and >0.01 typicality probability (n=200) 39 Table 7. Results by population accepting all posterior and typicality probabilities (n=40) 42 Table 8. Results by population using >0.5 posterior probability and >0.01 typicality probability (n=40) 45 Table 9. Results by population using >0.8 posterior probability and >0.01 typicality probability (n=40) 47 Table 10.Total number of test specimens correctly classified (n=200) 50 Table 11. Number of test specimens correctly classified using >0.5 posterior probability and >0.01 typicality criteria (n=200) 52 Table 12. Number of test specimens correctly classified using >0.8 posterior probability and >0.01 typicality probability (n=200) 54 Table 13. Total results for each cranial region by population (n=40) 57 Table 14. Results for each cranial region using >0.5 posterior probability and >0.01 typicality probability (n=40) 60 Table 15: Range of posterior and typicality probabilities for correct and incorrect assignments by population 68 vii List of Figures Figure 1: Genetic tree for 26 European populations 26 Figure 2: Genetic tree for 33 African populations 26 Figure 3: Genetic tree for 21 Asian populations 27 Figure 4: Genetic tree for 23 American populations 27 viii 1.
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