The past decade has produced considerable debate over the feasibility of paleodemographic research, with much attention focusing on the question of reliability of age estimates. We show here that in cases where age is estimated rather than known, the traditional method of assigning individuals to age classes will produce biased estimates of age structure. We demonstrate the effect of this bias both mathematically and by computer simulation, and show how a more appropriate method from the fisheries literature (the "iterated age length key") can be used to estimate age structure. Because it is often the case that ages are also estimated for extant groups, we suggest that our results are relevant to the general field of anthropological demography, and that it is time for us to improve the statistical basis for age structure estimation. We further suggest that the oft noted paucity of older individuals in skeletal collections is a simple result of the use of inappropriate methods of age estimation, and that this problem can be rectified in the future by using maximum likelihood estimates of life table or hazard functions incorporating the uncertainty of age estimates.

In 1992 in this Journal (Konigsberg and Frankenberg [1992] Am. J. Phys. Anthropol. 89:235-256), we wrote about the use of maximum likelihood methods for the "estimation of age structure in anthropological demography." More specifically, we presented a particular method (the "iterated age-length key") from the fisheries literature and suggested that the method could be used in human and primate demography and paleodemography as well. In our paper (section titled "Some Future Directions"), we spelled out two broad areas that we expected to see develop over the ensuing years. First, we felt that the use of explicit likelihood methods would open up interest in basic estimation issues, such as the calculation of standard errors for demographic estimates and the formulation of tests for whether samples differed in their demographic structure. Second, we felt that the time was ripe for hazards analyses that would incorporate the uncertainty in estimation that follows from using age "indicators" rather than known ages. While some of these developments have occurred during the last decade, few have been reported in the American Journal of Physical Anthropology. In this paper we resolve some issues from our 1992 paper, and attempt to redress this deficit in the literature by reviewing some recent developments in paleodemography over the past decade.

Biological distance analysis, the dominant type of skeletal biological research during the 19th century, has become less visible in recent years. Although the proportion of American Journal of Physical Anthropology articles and published abstracts focusing on biodistance has remained fairly constant over the three decades between 1955 and 1985, the proportion of biodistance contributions relative to other skeletal biology studies has decreased. Emphasis in skeletal biology has shifted from the analysis of biological variation to investigations of health and diet, and within biodistance studies methodological issues have assumed prominence over purely analytical approaches. This paper investigates trends in biological distance analysis through a survey of articles and meetings abstracts published in the American Journal of Physical Anthropology from 1955 to 1985. The survey provides the historical context for five symposium papers on skeletal biological distance presented at the 1986 meeting of the American Association of Physical Anthropologists.

In this article, we both contend and illustrate that biological anthropologists, particularly in the Americas, often think like Bayesians but act like frequentists when it comes to analyzing a wide variety of data. In other words, while our research goals and perspectives are rooted in probabilistic thinking and rest on prior knowledge, we often proceed to use statistical hypothesis tests and confidence interval methods unrelated (or tenuously related) to the research questions of interest. We advocate for applying Bayesian analyses to a number of different bioanthropological questions, especially since many of the programming and computational challenges to doing so have been overcome in the past two decades. To facilitate such applications, this article explains Bayesian principles and concepts, and provides concrete examples of Bayesian computer simulations and statistics that address questions relevant to biological anthropology, focusing particularly on bioarchaeology and forensic anthropology. It also simultaneously reviews the use of Bayesian methods and inference within the discipline to date. This article is intended to act as primer to Bayesian methods and inference in biological anthropology, explaining the relationships of various methods to likelihoods or probabilities and to classical statistical models. Our contention is not that traditional frequentist statistics should be rejected outright, but that there are many situations where biological anthropology is better served by taking a Bayesian approach. To this end it is hoped that the examples provided in this article will assist researchers in choosing from among the broad array of statistical methods currently available. Am J Phys Anthropol 57: 2013. V C 2013 Wiley Periodicals, Inc."The Bayesian approach can have a clarifying effect on one's thinking about evidence." (Koehler and Saks, 1991, p 364) Traditional training in statistical methods for those who go on to become practicing biological anthropologists has focused primarily on classical hypothesis testing. This is apparent in both textbooks geared toward anthropologists in general (Thomas, 1986;Madrigal, 1998;Bernard, 2011) and specialized texts for biological anthropologists (Slice, 2005;D'Aoãut and Vereecke, 2011). While Bayes' Theorem may be mentioned in passing in introductory statistics courses, this is typically restricted to examples of such limited interest that the student has little motivation to recall the theorem, and even less motivation to assume that there may be future value in having learned about Bayes' Theorem. In Bayesian terms, the prior probability that the student will retain Bayes' Theorem is quite low. In contrast, the student and eventual practitioner is likely to learn about confidence intervals, Type I and Type II errors in hypothesis testing, and P-values, and to blithely assume that what they have learned represents the near totality of what is available and useful within modern statistical practice. This represents an unfortunate omission of Ba...

As Kim Hill1 recently noted in Evolutionary Anthropology, humans are unique among the hominoids with regard to the length of their lives, as well as other elements in the individual life histories. The evolutionary details that modified a basic pongid life history into a hominid one remain obscure, but aspects of recent human demographic history are assailable. Study of the last 10,000 years or so is an important part of ongoing anthropological discourse, for demographic changes may be intimately linked to such major developments as agriculture and urbanization.2‐8 Whether demographic changes are antecedents for or consequences of these major developments is a matter of great contention, but at the least we should attempt to document the nature of human demographic changes in the recent past. Although this documentation can take different forms, the principal sources are archeological information on past settlement patterns and analyses of prehistoric human skeletal material.

The results from the analysis of the Todd pubic symphysis scores show that researchers should use goodness-of-fit tests for parametric models before deciding to collapse scores. Further, such goodness-of-fit tests are an essential tool in answering questions concerning the suitability of various parametric models. For the 15-stage scoring of the second mandibular molar, the log-normal model is appropriate for attainment ages.

The completion of the third molar roots has played an important role in ascertaining whether individuals may be at or over a legal threshold of age, often taken as 18 years. This study demonstrates that root apex completion in the third molar is relatively uninformative regarding the threshold of age 18 years in a sample of 1184 males, where mean age‐of‐attainment of root apex completion for third mandibular molars is about 19.4 years. This paper also considers the legal age threshold problem for cases where the third mandibular molar is not completely formed, and outlines the use of parametric models and Bayes’ factors to evaluate dental evidence in statistically appropriate ways. It attempts to resolve confusion over age‐within‐stage versus age‐of‐attainment, likelihood ratios versus other diagnostic tests, and prior odds for a case versus the prior density for an age distribution.

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