A multivariate analysis of temporal change in Arikara craniometrics: A methodological approach

We have examined temporal changes in the cranial architecture of Arikara Amerindians from five archaeological sites in South Dakota which span a time period of approximately 230 years (ca. A.D. 1600–1830). We have utilized a multivariate statistical method based on a principal components analysis of the pooled within-groups correlation matrix rather than the more traditional methods of ascertaining morphological relationships, e.g., discriminant functions, Mahalanobis' D², or Penrose's Size and Shape. Our component structure, based on a regional sample and the mathematically simpler principal components analysis, is very similar to the factor structure obtained by Howells (1973) using a world-wide sample and factor analysis proper. This supports the notion of the “universality” of cranial structure. An axis of temporal variation was introduced into the component space by means of multiple regression. This analysis indicates that a substantial portion of the intergroup variation is temporal in nature and that systematic temporal changes occur along the facial height, transverse frontal flatness, and frontal profile flatness components. Earlier analyses of the same material by more conventional methods either did not detect the temporal trends at all or failed to isolate the specific nature of the temporal changes. The success of the present analysis attests to the value of examining morphological relationships by means of principal components.     

Statistical measures of intrasample variability

We have implemented a multivariate statistical methodology to assess the degree and pattern of variability in skeletal samples. Specifically, it is designed to test whether variability in a skeletal sample exceeds that of a local breeding population, defined in the present instance as variability present among crania from an endogamous village. It involves the use of covariance matrices derived from hypothesis and reference samples. The methodology has been applied to subsamples of a Plains Indian craniometric database consisting of 80 variables taken on some 1000 individuals. The subsamples are assumed to reflect varying patterns and degrees of intrasample variability. The assumed group structures are assembled posthoc and subject to various analyses. The excellent results attest to the great potential of the methodology.     

Statistical assessment of DNA extraction reagent lot variability in real‐time quantitative PCR

Aims: The aim of this study was to evaluate the variability in lots of a DNA extraction kit using real‐time PCR assays for Bacillus anthracis, Francisella tularensis and Vibrio cholerae. Methods and Results: Replicate aliquots of three bacteria were processed in duplicate with three different lots of a commercial DNA extraction kit. This experiment was repeated in triplicate. Results showed that cycle threshold values were statistically different among the different lots. Conclusions: Differences in DNA extraction reagent lots were found to be a significant source of variability for qPCR results. Steps should be taken to ensure the quality and consistency of reagents. Minimally, we propose that standard curves should be constructed for each new lot of extraction reagents, so that lot‐to‐lot variation is accounted for in data interpretation. Significance and Impact of the Study: This study highlights the importance of evaluating variability in DNA extraction procedures, especially when different reagent lots are used. Consideration of this variability in data interpretation should be an integral part of studies investigating environmental samples with unknown concentrations of organisms.     

The assessment and meaning of intraobserver error in population studies based on discontinuous cranial traits.

Intraobserver scoring precision of 50 discontinuous (discrete) cranial traits was assessed on a sample of 125 intact Iroquois crania using the square of the phi coefficient. Scoring consistency was high for most traits although several were subject to low precision (phi 2 less than 0.7). Most errors were random rather than systematic. Taken collectively the problematic traits exceeded their expected contribution to MMD coefficients among four Woodland samples from southern Ontario. A traitlist with the problematic variants excluded produced more meaningful biological relationships among the samples. Further, the % contribution of the problematic traits increased with the time interval between the scoring of the individual samples. It was suggested that intraobserver error could effectively distort the interpretation of biological relationships and that it must in part be responsible for the poor performance reported for discontinuous traits in some studies. Therefore, it was argued that the results support rather than compromise the use of discontinuous skeletal traits in population studies and that the assessment of intraobserver error should be a standard procedure of the research design.     

The use of nonmetric variation in estimating human population admixture: a test case with Brazilian blacks, whites, and mulattos

Measurements in populations which serve as valid indicators of biological relationship should be proportional to genetic distance. In order to test the utility of discrete cranial traits for estimating genetic distances among populations, estimates of admixture are obtained for gene frequency data and nonmetric cranial data in São Paulo mulattos (M). The gene frequency data serve as a control that the three populations are related as stated: estimates of admixture are obtained by using São Paulo whites (W) and blacks (B) as parental populations and by estimating the parameter of admixture, m, in the model p_M = (1 ? m) p_W + mp_B (Elston, 1971) where the p's are either gene frequencies or nonmetric trait frequencies. A test of goodness of fit of the model provides a means of ascertaining whether or not the data fit this linear model. While the gene frequency data indicate distances among the three populations which are highly compatible with the linear model of admixture, the nonmetric data show significant deviations from the model. This implies that the frequencies of the nonmetric traits in the populations used in this analysis are not a linear function of genetic distance. This discourages the use of nonmetric traits in making quantitative conclusions about genetic relationships. It also suggests the need for investigation of the use of other skeletal characters for estimating genetic distance, as well as approaches for such investigations through the study of hybrid individuals.     

Speed of fetal growth: a new methodological approach

We suggest a new method to calculate fetal growth velocity. Fetal growth curves are divided in small linear units, and corresponding slopes calculated as growth rates. An example is detailed to set out statistical contingencies for methodological reliability. Specific interest of the method is discussed.     

The statistical treatment of correlated bilateral traits in the analysis of cranial material.

At present there is no standardized method to derive frequencies from bilateral non-metric traits. In this paper the commonly used methods are evaluated in light of statistical considerations and degree of sample preservation. In particular, we explore the question of dependence between sides for the bilateral traits. Several workers have tested for bilateral trait correlation in incorrect ways, confusing tests for differences in side frequencies with tests for independence. An easy method to test for independence, using the chi-squared test, is recommended. This test is used on 16 bilateral traits in a large sample of prehistoric carnia from Central California and significant dependence is found for all 16 of these traits. We suggest the traditional method of deriving frequencies be used. Both sides of the cranium should be considered, dividing the number of times the trait occurs by the number of sides available for observation. This method can be used even in poorly preserved samples. Side to side correlation may be compensated for by modifying the constants subtracted in the mean measure of divergence and in the expression for the approximate variance of the mean measure of divergence when the samples are drawn from identical populations.     

Revisiting the homoiology hypothesis: the impact of phenotypic plasticity on the reconstruction of human population history from craniometric data

Homoiologies are homoplasies that are caused by nongenetic environmental factors. The homoiology hypothesis predicts that osseous regions subject to repeated biomechanical stress during growth should be more variable and, therefore, less reliable for the reconstruction of phylogeny compared with osseous regions relatively unaffected by stress. Previous studies based on the analysis of multiple primate species found that regions of the cranium subject to masticatory-induced stress were significantly more variable than non-masticatory regions, as predicted by the homoiology hypothesis. However, these studies also found that the masticatory regions were no less reliable for reconstructing primate phylogenetic relationships when subjected to parsimony analysis. It was suggested, therefore, that homoiology may be a more potent problem for the reconstruction of phylogeny at the intraspecific level rather than interspecific phylogenetics. This suggestion was tested here using matched molecular and craniometric data for 12 modern human populations. The results show that, as predicted by the homoiology hypothesis, regions of the human cranium related to mastication were more variable than non-masticatory regions. However, masticatory regions were no less reliable for inferring human population history. Therefore, the results match those found from the interspecific analysis of primate species and do not support the suggestion that homoiology is a greater problem for the analysis of intraspecific taxa. The results also suggest that within-taxon variability cannot be relied upon to predict the phylogenetic efficacy of morphometric characters.     

Statistical fluctuations in population bargaining in the ultimatum game: Static and evolutionary aspects

We explore the emergent behavior in heterogeneous populations where players negotiate via an ultimatum game: two players are offered a gift, one of them (the proposer) suggests how to divide the offer while the other player (the responder) can either accept or reject the deal. Rejection is detrimental to both players as it results in no earnings. In this context, our contribution is twofold: (i) we consider a population where the distribution of used strategies is constant over time and properties of the random payoff received by the players (average and higher moments) are reported from simple exact methods and corroborated by computer simulations; (ii) the evolution of a population is analyzed via Monte Carlo simulations where agents may change independently the proposing and accepting parameters of their strategy depending on received payoffs. Our results show that evolution leads to a stationary state in which wealth (accumulated payoff) is fairly distributed. As time evolves, an increase in average payoff and a simultaneous variance decrease is observed when we use a dynamics based on a probabilistic version of the saying: “One should not comply with small earnings, but one's greed must be limited.”     

Craniometric variation and the settlement of the Americas: testing hypotheses by means of R-matrix and matrix correlation analyses

New archaeological findings and the incorporation of new South American skull samples have raised fundamental questions for the classical theories of the Americas' settlement. The aim of this study was to estimate craniometric variability among several Asian and Native American populations in order to test goodness of fit of the data to different models of ancient population entries and dispersions into the New World. Our data set includes Howells' variables recorded on East Asian, North American, and South American natives (except for Na-Dene speakers). Five Fuego-Patagonian samples and one Paleoamerican sample were also included. A multivariate extension of the R-matrix method for quantitative traits was used to obtain Fst values, which were considered estimations of intergroup variation. Three main models for the peopling of the New World were represented in hypothetical design matrices. Matrix permutation tests were performed to quantify the fit of the observed data with 1) geographical separation of the samples and 2) three ways of settlement, which were the Three Migration Model (TMM), the Single Wave Migration model (SWM), and the Two Components Settlement Model (TCS). R-matrix results showed high levels of heterogeneity among Native Americans. Matrix permutation analyses suggested that the model involving high Amerindian heterogeneity and two different morphological patterns or components (derived "Mongoloid" vs. generalized "non-Mongoloid") explains better the variation observed, even when the effects of geographical separation are removed. Whether these patterns arose as a result of two separate migration events or by local evolution from Paleoamericans to Amerindians remains unresolved.     

Work-based physiological assessment of physically-demanding trades: a methodological overview

Technological advances, modified work practices, altered employment strategies, work-related injuries, and the rise in work-related litigation and compensation claims necessitate ongoing trade analysis research. Such research enables the identification and development of gender- and age-neutral skills, physiological attributes and employment standards required to satisfactorily perform critical trade tasks. This paper overviews a methodological approach which may be adopted when seeking to establish trade-specific physiological competencies for physically-demanding trades (occupations). A general template is presented for conducting a trade analyses within physically-demanding trades, such as those encountered within military or emergency service occupations. Two streams of analysis are recommended: the trade analysis and the task analysis. The former involves a progressive dissection of activities and skills into a series of specific tasks (elements), and results in a broad approximation of the types of trade duties, and the links between trade tasks. The latter, will lead to the determination of how a task is performed within a trade, and the physiological attributes required to satisfactorily perform that task. The approach described within this paper is designed to provide research outcomes which have high content, criterion-related and construct validities.     

The use of inverse sine transformations in the analysis of non-metric cranial data

In recent years osteologists have frequently used non-metric (dichotomous) cranial data to measure biological distance between skeletal samples of Homo sapiens. Applying methods used earlier by biologists, these workers begin by attempting to stabilize the variance of the measures used by transforming the observed trait frequencies using some type of inverse sine transformation. The frequently used Grewal-Smith transformation doesn't work well for small samples of the size often considered by osteologists. As a consequence the mean measure of divergence between populations determined by this method is strongly influenced by a bias which depends on sample size. This paper compares several transformations in terms of how close the actual variance of the transformed frequency corresponds to its nominal value. It is suggested that the traditional (Grewal-Smith) inverse sine transformation not be used, and several alternatives are considered.     

Combined application of life cycle assessment and data envelopment analysis as a methodological approach for the assessment of fisheries

Background, aim, and scope  

The synergistic use of life cycle assessment (LCA) and data envelopment analysis (DEA) is proposed as a new methodological approach to link environmental and socioeconomic assessments of fisheries. Therefore, the goal is to combine LCA and DEA in order to increase the assessment ability of both tools when applied to these fisheries. Specifically, the joint inclusion of economic aspects and the consideration of currently underrepresented environmental impact categories are tackled.     

Cluster analysis of short-term tests: a new methodological approach

A totally data-based approach to the evaluation of short-term tests is proposed. The performances of 22 tests over a range of 42 chemicals (data from literature) were studied by cluster analysis. The comparison between them was performed only on the basis of their responses to the chemicals. Two different clustering methods produced a coincident classification, pointing to a clear resolution of all tests into 3 groups with common characteristics. With respect to carcinogen discrimination, cluster 1 showed the highest sensitivity and the lowest specificity. Cluster 3 had opposite characteristics. The tests of cluster 2 showed intermediate features. As far as the membership to clusters is concerned, the literature data about the responses to chemicals indicated a strong test system specificity. This apparently overcame both phylogeny and end-point community. A major characteristic of the present approach is the ability to elicit underlying patterns, the knowledge of which can contribute both to hypothesis formulation and be useful for practical purposes.     

Statistical power in physical anthropology: a technical report

A statistical power analysis of The American Journal of Physical Anthropology (Volume 44, 1976) was conducted. Twenty-five articles, which included 3,304 major significance tests, constituted the final sample. Resultant power estimates of 0.38, 0.62, and 0.81, corresponding to small, medium, and large population effects respectively, were obtained. Although the medium effect size estimate falls short of the recommended 0.80 level, the statistical power of physical anthropological research fares well relative to several of the social scientific fields of inquiry.     

Antler and Body Weight Allometry in Red Deer: A Comparison of Statistical Estimators

In allometric expressions, both variables are measured with error. Such structural relationships require specific statistical techniques for precise and valid estimation of equation parameters. The relative growth pattern for antler weight and body weight was examined for 1700 red deer (Cervus elaphus L.) stags from the Harz mountain district in West Germany. Coefficients for the allometric equation were determined using several statistical estimation procedures and the results were compared and evaluated. There is evidence that the magnitude of the exponent in the allometric expression increases with the onset of sexual maturity.     

Application of formal methods to biological regulatory networks: extending Thomas' asynchronous logical approach with temporal logic

Based on the discrete definition of biological regulatory networks developed by René Thomas, we provide a computer science formal approach to treat temporal properties of biological regulatory networks, expressed in computational tree logic. It is then possible to build all the models satisfying a set of given temporal properties. Our approach is illustrated with the mucus production in Pseudomonas aeruginosa. This application of formal methods from computer science to biological regulatory networks should open the way to many other fruitful applications.     

Statistical analysis of microarray data: a Bayesian approach

The potential of microarray data is enormous. It allows us to monitor the expression of thousands of genes simultaneously. A common task with microarray is to determine which genes are differentially expressed between two samples obtained under two different conditions. Recently, several statistical methods have been proposed to perform such a task when there are replicate samples under each condition. Two major problems arise with microarray data. The first one is that the number of replicates is very small (usually 2-10), leading to noisy point estimates. As a consequence, traditional statistics that are based on the means and standard deviations, e.g. t-statistic, are not suitable. The second problem is that the number of genes is usually very large (approximately 10,000), and one is faced with an extreme multiple testing problem. Most multiple testing adjustments are relatively conservative, especially when the number of replicates is small. In this paper we present an empirical Bayes analysis that handles both problems very well. Using different parametrizations, we develop four statistics that can be used to test hypotheses about the means and/or variances of the gene expression levels in both one- and two-sample problems. The methods are illustrated using experimental data with prior knowledge. In addition, we present the result of a simulation comparing our methods to well-known statistics and multiple testing adjustments.