Living with observational data in biological anthropology

The establishment of cause and effect relationships is a fundamental objective of scientific research. Many lines of evidence can be used to make cause–effect inferences. When statistical data are involved, alternative explanations for the statistical relationship need to be ruled out. These include chance (apparent patterns due to random factors), confounding effects (a relationship between two variables because they are each associated with an unmeasured third variable), and sampling bias (effects due to preexisting properties of compared groups). The gold standard for managing these issues is a controlled randomized experiment. In disciplines such as biological anthropology, where controlled experiments are not possible for many research questions, causal inferences are made from observational data. Methods that statisticians recommend for this difficult objective have not been widely adopted in the biological anthropology literature. Issues involved in using statistics to make valid causal inferences from observational data are discussed.     

Geostatistics and spatial analysis in biological anthropology

A variety of methods have been used to make evolutionary inferences based on the spatial distribution of biological data, including reconstructing population history and detection of the geographic pattern of natural selection. This article provides an examination of geostatistical analysis, a method used widely in geology but which has not often been applied in biological anthropology. Geostatistical analysis begins with the examination of a variogram, a plot showing the relationship between a biological distance measure and the geographic distance between data points and which provides information on the extent and pattern of spatial correlation. The results of variogram analysis are used for interpolating values of unknown data points in order to construct a contour map, a process known as kriging. The methods of geostatistical analysis and discussion of potential problems are applied to a large data set of anthropometric measures for 197 populations in Ireland. The geostatistical analysis reveals two major sources of spatial variation. One pattern, seen for overall body and craniofacial size, shows an east-west cline most likely reflecting the combined effects of past population dispersal and settlement. The second pattern is seen for craniofacial height and shows an isolation by distance pattern reflecting rapid spatial changes in the midlands region of Ireland, perhaps attributable to the genetic impact of the Vikings. The correspondence of these results with other analyses of these data and the additional insights generated from variogram analysis and kriging illustrate the potential utility of geostatistical analysis in biological anthropology.     

Multivariate analysis in biological anthropology: Some considerations

The relation between modern multivariate statistical analysis and common objectives in biological anthropology is discussed. Many formal statistical assumptions should be satisfied to fully justify multi-variate analysis, but rarely are. Their failure does not have as adverse an effect upon scientific research as some procedural errors in research design. These include the treatment of single specimens as if they are samples, and the failure to separate considerations of size and shape. The superiority of elaborate multivariate distances over simpler quantitative techniques, inferred from the former's consideration of trait intercorrelations, is unwarranted from both theoretical and practical aspects. Based on these points and several comparative examples of analyses, it is argued that simpler, non-statistical approaches such as those of the school of numerical taxonomy have much to offer primato-logical studies. Classic multivariate statistics, while useful for studying closely similar living populations, are considerably more limited in usefulness and significance for paleoanthropological studies.     

Testing type II error rates in biological anthropology

This paper presents a look at the underused procedure of testing for Type II errors when "negative" results are encountered during research. It recommends setting a statistical alternative hypothesis based on anthropologically derived information and calculating the probability of committing this type of error. In this manner, the process is similar to that used for testing Type I errors, which is clarified by examples from the literature. It is hoped that researchers will use the information presented here as a means of attaching levels of probability to acceptance of null hypotheses.     

Understanding racism in physical (biological) anthropology

The mainstream of American physical anthropology began as racist and eugenical science that defended slavery, restricted “non-Nordic” immigration, and justified Jim Crow segregation. After World War II, the field became more anti-racial than anti-racist. It has continued as a study of natural influences on human variation and thus continues to evade the social histories of inequitable biological variation. Also reflecting its occupancy of white space, biological anthropology continues to deny its own racist history and marginalizes the contributions of Blacks. Critical disciplinary history and a shift toward biocultural studies might begin an anti-racist human biology.     

The continuing misuse of null hypothesis significance testing in biological anthropology

There is over 60 years of discussion in the statistical literature concerning the misuse and limitations of null hypothesis significance tests (NHST). Based on the prevalence of NHST in biological anthropology research, it appears that the discipline generally is unaware of these concerns. The p values used in NHST usually are interpreted incorrectly. A p value indicates the probability of the data given the null hypothesis. It should not be interpreted as the probability that the null hypothesis is true or as evidence for or against any specific alternative to the null hypothesis. P values are a function of both the sample size and the effect size, and therefore do not indicate whether the effect observed in the study is important, large, or small. P values have poor replicability in repeated experiments. The distribution of p values is continuous and varies from 0 to 1.0. The use of a cut‐off, generally p ≤ 0.05, to separate significant from nonsignificant results, is an arbitrary dichotomization of continuous variation. In 2016, the American Statistical Association issued a statement of principles regarding the misinterpretation of NHST, the first time it has done so regarding a specific statistical procedure in its 180‐year history. Effect sizes and confidence intervals, which can be calculated for any data used to calculate p values, provide more and better information about tested hypotheses than p values and NHST.     

Skeletal biological distance studies in American physical anthropology: recent trends

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.     

Cyber anthropology or anthropology in cyberspace

As a variety of anthropology, cyber anthropology is considered to be the fastest growing sub branch in the science. It is based on synergic effects of multimedia systems and hypermedia, using their comparative advantages. One of the least researched fields of cyber anthropology is the relationship of individuals and social groups with a multimedia document in terms of their perception of such subject. This is because the foundation of social-informatics perception in the society is created based on the evidence of a real life, whereas here the perception is established at the level of virtual, i.e. online life. The rhetorical question here is whether an identical content causes the same or different user reactions, depending on whether it was perceived offline or online, i.e. to what extend does the medium (and not the information content) dictate the user perception. In this respect the research titled "Perception of online museum content creators and actual habits of Croatian online museum visitors" can be a "case study" for the impact of "cyber potential" on the classic anthropological paradigm.     

Anthropometry and numerical taxonomy in clinical genetics: An example of applied biological anthropology

Biological anthropologists can contribute a unique perspective as well as technical expertise to the diagnosis and classification of genetic disorders. Anthropometry has been used with increasing frequency to characterize syndromes and to establish ranges of variation within syndromes. The specific anthropometric-radiologic technique of metacarpophalangeal pattern profile analysis has proven useful in discriminating individuals with the Prader-Labhart-Willi (PLW) syndrome from unaffected persons. Analysis of these data also indicate a negative correlation between age and Z-score transformations of individual hand bone lengths. These findings sound a cautionary note to clinical investigators who would use the Z-score transformation to standardize for age and sex. Problems encountered in the classification of genetic syndromes afford many parallels with those faced by anthropologists in the classification of living and fossil populations. The reliance on “key” traits and the necessity of focusing on pedigree analysis results in a deemphasis of the total range of variation and typological thinking. Application of numerical taxonomic techniques to the classification of the heterogeneous connective tissue disease osteogenesis imperfecta (OI) illustrates the heuristic value of this technique and points out the need to consider phenotypic overlap when defining typologies. Clinical genetics affords just one example of an area in medicine where the unique training and generalist perspective of the biological anthropologist is in demand. The decline in the availability of positions in the traditional academic habitat for biological anthropologists makes it imperative that graduate students be aware of alternatives and that they obtain training in the practical skills which such alternatives will demand.     

Kant on epigenesis, monogenesis and human nature: the biological premises of anthropology

The aim of this paper is to show that for Kant, a combination of epigenesis and monogenesis is the condition of possibility of anthropology as he conceives of it and that moreover, this has crucial implications for the biological dimension of his account of human nature. More precisely, I begin by arguing that Kant's conception of mankind as a natural species is based on two premises: firstly the biological unity of the human species (monogenesis of the human races); and secondly the existence of 'seeds' which may or may not develop depending on the environment (epigenesis of human natural predispositions). I then turn to Kant's account of man's natural predispositions and show that far from being limited to the issue of races, it encompasses unexpected human features such as gender, temperaments and nations. These predispositions, I argue, are means to the realisation of Nature's overall purpose for the human species. This allows me to conclude that man's biological determinism leads to the species' preservation, cultivation and civilisation.     

Hacking anthropology

This essay outlines how the ‘hack’ might offer a model for anthropological research in the face of the distributed relations evidenced by digital data. The argument builds on fieldwork with citizens and activists and looks at their attempts to understand and make use of the data produced by energy sensors and monitors. Drawing on their experiences, I suggest that ‘the hack’ emerges as an important form of practice that helps people navigate the place of data in social relations. Taking the hack not just as ethnographic observation but also as a methodological proposition, I use my ethnographic material on the practice of the hack to reconsider the anthropological challenge of doing ethnography of processes that are only perceptible through numerical or digital data. To explore the value of the hack for anthropology, I introduce an example of an attempt to do ethnography in the mode of the hack. The essay ends with reflections on how the hack might provide us with new ways of getting to grips with the anthropological implications of systemic and emergent relations that are both brought to light and remade through data.