Paleodemography: Age Distributions from Skeletal Samples

Half-title......Page 3
Series-title......Page 5
Title......Page 7
Copyright......Page 8
Dedication......Page 9
Contents......Page 11
Contributors......Page 13
Acknowledgments......Page 15
Introduction......Page 17
The need for better osteological methods......Page 19
The need for better reference samples......Page 20
The need to use Bayes’ theorem......Page 21
The need to assess the distribution of lifespans in the target population......Page 22
References......Page 23
Historical perspectives......Page 25
Ethnographic analogy for prehistoric demography......Page 29
The great debate: paleodemography on trial......Page 31
Answering Petersen’s challenge......Page 33
References......Page 34
Introduction......Page 45
Methods......Page 46
Discussion......Page 47
Acknowledgments......Page 57
References......Page 58
Introduction......Page 64
The evolution of age markers: single-trait systems......Page 66
Issues of validity and reliability......Page 69
Validity......Page 71
Phases or components? The case of the pubic symphysis......Page 73
From single-to multiple-trait techniques......Page 74
Complex method......Page 75
Multifactorial summary age......Page 76
Transition analysis method......Page 77
Interpersonal differences–young versus old individuals......Page 78
Interpopulation differences–horizontal considerations......Page 79
Interpopulation differences–vertical considerations......Page 80
Conclusions......Page 81
References......Page 82
Introduction......Page 89
Problems of adult age estimation......Page 91
Skeletal sample......Page 95
Transition analysis for a single trait......Page 97
Transition analysis for multiple traits......Page 101
Approximate confidence intervals......Page 102
Using an "external" f (a )......Page 103
Transition analysis for a single trait......Page 104
Discussion......Page 109
Appendix 5.1......Page 112
Symphyseal relief......Page 113
Superior apex......Page 114
Ventral symphyseal margin......Page 115
Iliac portion of the sacroiliac joint......Page 116
Superior, apical, and inferior surface morphology......Page 117
Superior and inferior posterior iliac exostoses......Page 118
Coronal pterica, sagittal obelica, lambdoidal asterica, zygomaticomaxillary, interpalatine (median palatine, posterior…......Page 119
References......Page 120
Morphological age estimation methods versus tooth cementum annulation......Page 123
Development of tooth cementum annulation age estimation......Page 124
Biological basis of tooth cementum annulation......Page 128
The concept of the current validation study......Page 129
The sample in the validation study......Page 131
Methods......Page 132
Preliminary results......Page 136
Perspectives......Page 140
Acknowledgments......Page 141
References......Page 142
Introduction......Page 145
What exactly do we need to model?......Page 149
What does the human mortality curve look like?......Page 153
Ways of modeling mortality......Page 156
Relational models......Page 157
Weibull, Rayleigh, and bi-Weibull models......Page 159
The Gompertz model......Page 161
The Gompertz–Makeham model......Page 162
The Siler model......Page 163
Interpreting competing hazards models when mortality is heterogeneous......Page 166
The mixed-Makeham model......Page 167
A more general approach to modeling heterogeneity......Page 169
Capturing the sex differential......Page 171
Discussion......Page 174
The age-at-death distribution for skeletons deposited over time......Page 175
The implications of heterogeneity for competing hazards models......Page 177
References......Page 178
Introduction......Page 185
The Historical Perspectives on Human Demography Database......Page 186
Modeling procedure......Page 188
Epidemic cycles......Page 190
Results......Page 191
Discussion......Page 192
References......Page 194
The problem......Page 197
Some theory behind the weight functions......Page 200
Estimating the weight functions......Page 202
Solution: Part II Estimating the mortality schedule......Page 203
Solution: Part III Estimating age-at-death for an individual......Page 205
Solution: Part IV Goodness-of-fit......Page 206
An application of our solution......Page 207
References......Page 208
Introduction......Page 209
Estimation of an age-at-death distribution......Page 210
Missing skeletal observations......Page 212
The life table method......Page 215
Estimating the target age-at-death distribution......Page 216
Estimating parameters for the reference distribution......Page 217
Parametric methods with ‘‘stage’’ or ‘‘phase’’ data......Page 219
Estimating parameters of the reference distribution using staged indicators......Page 222
Estimating parameters of the reference distribution......Page 223
Estimating parameters of the reference distribution......Page 224
Estimating the target age-at-death distribution......Page 225
Nonindependent indicators: the latent-trait method......Page 226
Estimating the target age-at-death distribution......Page 229
Application......Page 230
Conclusions......Page 233
References......Page 234
Introduction......Page 238
Modeling the dependence of a discontinuous ‘‘age indicator’’ on age......Page 239
Modeling survivorship......Page 241
Example of estimating Gompertz–Makeham parameters from pubic symphyseal data......Page 242
Gibbs sampling......Page 244
Simulating transition ages......Page 246
Simulating the Weibull parameters......Page 247
Example of estimating Weibull parameters from pubic symphyseal data......Page 249
Multivariate age estimation......Page 251
Mixed and missing data......Page 252
Whither now?......Page 253
Acknowledgments......Page 255
References......Page 256
Indian Knoll history......Page 259
Mathematical approach......Page 262
Comparative samples......Page 265
Standard error estimation......Page 266
Results......Page 267
Discussion......Page 269
Acknowledgments......Page 271
References......Page 272
Index......Page 274