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Population and Sex Determination Based on Measurements of the Talus

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Population and Sex Determination Based on Measurements of the Talus POPULATION AND SEX DETERMINATION BASED ON MEASUREMENTS OF THE TALUS Terri B. Torres A Thesis Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of Master of Science Committee: Richard N. McGrath John T. Chen Nancy Boudreau ii ABSTRACT Dr. R.N. McGrath, Advisor Categorizing human remains by sex and race has long been a challenge for the medicolegal profession. Logistic regression models and multicategory logit models can be used to accurately place individuals into their respective groups using measurements of the talus bone. Successful placement was achieved in 93% of the individuals for the response variable of sex. The percentage of correct placement for race alone was 95%. The correct placement for sex with race ranged from 76% to 95% depending on the group. The goal of this paper was to show that in addition to the pelvis and skull, the talus can be used with equal or greater success rates to classify human remains. iii ACKNOWLEDGEMENTS At this time I wish to express my thanks to Dr. R. N. McGrath, Dr. Nancy Boudreau and Dr. John Chen for their unselfish support and encouragement that helped me understand and love statistics. Terri Torres iv TABLE OF CONTENTS ABSTRACT .................................................................................................................................... ii ACKNOWLEGEMENT ................................................................................................................ iii LIST OF TABLES ...........................................................................................................................v LIST OF FIGURES ....................................................................................................................... vi LIST OF APPENDICES ............................................................................................................... vii INTRODUCTION ...........................................................................................................................1 MATERIALS AND METHODS .....................................................................................................2 DISCUSSION 1. Sex...................................................................................................................................4 2. Race..............................................................................................................................15 3. Sex with Race ...............................................................................................................20 CONCLUSION ..............................................................................................................................26 FIGURES .......................................................................................................................................28 APPENDICES ...............................................................................................................................35 LITERATURE CITED ..................................................................................................................72 v LIST OF TABLES Table Page 1.1 Descriptive Statistics and Analysis for “Sex” ........................................... 4 1.2 Model Selection for “Sex” ...................................................................... 13 2.1 Descriptive Statistics and Analysis for “Race” ....................................... 15 2.2 Model Selection for “Race” .................................................................... 18 2.3 Model Refinement for “Race” ................................................................ 19 3.1 Summary of ANOVA for “Sex” with “Race” ..................................... 20 3.2 Summary of Placement for Validating Set ............................................. 24 3.3 Summary of Placement for Large Set ..................................................... 24 3.4 Comparison of Models ............................................................................ 25 iii LIST OF FIGURES Figure 1 Bones of the Human Foot ............................................................................ 28 2 Superior View of the Right Talus ................................................................ 29 3 Medial View of the Right Talus .................................................................. 30 4 Anterior View of the Right Talus ................................................................ 31 5 Lateral View of the Right Talus ................................................................. 32 6 Inferior View of Talus ................................................................................ 33 7 Superior View of Talus Showing Neck Length ........................................... 34 iii LIST OF APPENDICES Appendix Page A Box Plots for “Sex” ................................................................................. 35 B Correlation Matrix for “Sex” .................................................................. 36 C Matrix Plot for Eleven Variables ............................................................ 37 D SAS Model Selection for “Sex” .............................................................. 38 E MINITAB Five variable Model Selection for “Sex” .............................. 40 F Measures of Association for “Sex” ......................................................... 41 G Box Plots for “Sex”, Validating Set ........................................................ 42 H Box Plots for “Sex”, Entire Set .............................................................. 43 I Matrix Plot for Model Independent Variables, Validating Set ............... 44 J Logit Model for Model Set without Influential Values .......................... 45 K Boxplots for “Race” ................................................................................ 46 L SAS Model Selection for “Race” ............................................................ 47 M MINITAB Model for “Race” .................................................................. 50 N MINITAB Output for Interaction Models for “Race” ............................ 51 O ANOVA and Tukey Comparisons for “Sex” with “Race” ..................... 55 P SAS Output for Model Selection for “Sex” with “Race” ....................... 65 Q MINITAB Output for “Sex” with “Race” Models ................................. 70 R SAS Code for Model Selection .............................................................. 71 1 INTRODUCTION Within a medicolegal context, the objective of the forensic scientist when working with recovered skeletal remains is the determination of sex, stature, age, and ancestry. There exist several techniques in the field of forensic anthropology which make it possible to determine the demographics (e.g., sex and race) of the skeletal material under investigation. One method relies on basic visual inspection and the recognition of physical characteristics which are unique to individual elements of the human skeleton (Byers, 2008). A more quantitative approach (osteometry) requires taking measurements directly from the bone (Introna et al., 1997; Bass, 1995; Trotter, 1970; Trotter & Gleser, 1958; McKern & Stewart, 1957). For example, the human skull possesses several unique and quantifiable character traits; one method often employed by forensic anthropologists in cranial studies is the use of discriminant function analysis (De Vito, C., & Saunders, S.R., 1990; Giles, E., & Elliot, O., 1963). The application of discriminant function analysis is also applicable to the postcranial skeleton; several studies specifically focused on elements of the foot (Bidmos, M.A., & Dayal, M.R., 2004; Bidmos, M.A., & Asala, S.A., 2004; Steele, D.G., 1976). The results from previous studies on the postcranial skeleton, notably the elements of the foot provided accuracy values of 89% for correct sex determination (i.e. male or female). However, an alternative method for determining the sex and estimating ancestry on unknown skeletal material is the application of logistic regression. The objective of this study is to demonstrate that logistic regression can predict with high levels of accuracy both sex and race based exclusively measurements taken directly from the talus (Figure 1). These measurements will be used along with multicategory logit model to assist in the prediction of the four categories of sex with race. In this paper the only two races included will be black and white. Surface or even shallow burials often result in the loss of skeletal material which can greatly impede an investigation. Unlike the skull and long bones such as the femur or humerus, the compactness and the association of soft tissue (ligaments) makes the talus more resistance to taphonomic factors, thus increasing its chances of preservation and eventual field recovery. In situations requiring post-mortem identification where recovered skeletal material may be limited, this quality makes the talus an appropriate alternative for osteological analysis. 2 MATERIALS AND METHODS The osteological material used in this study is part of the Hamann-Todd Osteological Collection, housed at the Cleveland Museum of Natural History, Cleveland Ohio. The collection contains more than 3,100 human skeletons from Cuyahoga County, Ohio which were acquired during the early part of the 1900‟s. To maintain consistency throughout the study, only the right talus was used for data collecting. A total of 270 specimens were randomly selected. Any tali which
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