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L W Konigsberg

Publications and source records attributed to L W Konigsberg.

At least 19 recordsLinked to original sources
PubMed2000

Estimating stature in fossil hominids: which regression model and reference sample to use?

coResearchers have long appreciated the significant relationship between body size and an animal's overall adaptive strategy and life history. However, much more emphasis has been placed on interpreting body size than on the actual calculation of it. One measure of size that is especially important for human evolutionary studies is stature. Despite a long history of investigation, stature estimation remains plagued by two methodological problems: (1) the choice of the statistical estimator, and (2) the choice of the reference population from which to derive the parameters. This work addresses both of these problems in estimating stature for fossil hominids, with special reference to A.L. 288-1 (Australopithecus afarensis) and WT 15000 (Homo erectus). Three reference samples of known stature with maximum humerus and femur lengths are used in this study: a large (n=2209) human sample from North America, a smaller sample of modern human pygmies (n=19) from Africa, and a sample of wild-collected African great apes (n=85). Five regression techniques are used to estimate stature in the fossil hominids using both univariate and multivariate parameters derived from the reference samples: classical calibration, inverse calibration, major axis, reduced major axis and the zero-intercept ratio model. We also explore a new diagnostic to test extrapolation and allometric differences with multivariate data, and we calculate 95% confidence intervals to examine the range of variation in estimates for A.L. 288-1, WT 15000 and the new Bouri hominid (contemporary with [corrected] Australopithecus garhi). Results frequently vary depending on whether the data are univariate or multivariate. Unique limb proportions and fragmented remains complicate the choice of estimator. We are usually left in the end with the classical calibrator as the best choice. It is the maximum likelihood estimator that performs best overall, especially in scenarios where extrapolation occurs away from the mean of the reference sample. The new diagnostic appears to be a quick and efficient way to determine at the outset whether extrapolation exists in size and/or shape of the long bones between the reference sample and the target specimen.

Animals↗
PubMed1999

Recognizing species diversity among large-bodied hominoids: a simulation test using missing data finite mixture analysis.

A persistent problem in paleoanthropology is the recognition of intra- vs. inter-specific differences within fossil samples. Exacerbating this situation is the often fragmentary nature of the fossils themselves, thus precluding rote applications of many multivariate approaches designed for complete case analyses. In this paper we apply finite mixture analysis to samples of large-bodied hominoids to test this procedure's efficacy in clustering individuals by species without a priori knowledge of group membership. In addition, we stochastically remove individual specimens and measurements, simulating small, incomplete fossil samples, and re-apply the finite mixture procedure to test how often it correctly assigns these "fragmentary" specimens. Finite mixture analysis can be highly accurate, even when confronted with small sample sizes and missing data. For example, a combination of 124 chimpanzees and humans are correctly identified in one analysis, and the accuracy drops only 2% to become 98% when the total sample size is reduced to 16 and missing data patterns are applied. In comparisons to better known methods that have been used to recognize groups in the fossil record, such as k-means, the benefits of finite mixture analysis are readily apparent. First, k-means is unable to accommodate missing data, an obvious deficiency when investigating the fossil record. Second, in direct comparisons of their ability to accurately assign "unknowns" to taxa, finite mixture performed at least as well as, and often better than, k-means in our analyses. A potential test that can be used to identify species in the fossil record, derived from comparisons of results generated from a general vs. a restricted (isometry-corrected) finite mixture analysis, is presented.

Animals↗
PubMed1999

Allocation of crania to groups via the "new morphometry".

An investigation regarding the variation in cranial morphology between American blacks and whites was conducted using triangulation schemes of inter-landmark distances and converting these to three dimensional coordinate data. A least squares superimposition method and Euclidean distance analysis were utilized to obtain parameters for classifying individuals in our sample, consisting of 19 black and nineteen white crania from the William M. Bass, III Donated and Forensic collections curated at the University of Tennessee, Knoxville. Thirty-six caliper measurements were collected on each skull based on 14 homologous cranial landmarks (nasion, bregma, lambda, prosthion, subspinale, basion, frontomalare (left and right), zygoorbitale (left and right), zygotemporale (left and right), and left and right asterion). The results are compared to traditional discriminant analysis. The classification results using the new morphometry are comparable to traditional discriminant analysis. However, the new morphometry can provide information as to the specific location of morphological variation that cannot be obtained with discriminant analysis.

Black People↗
PubMed1998

Stature estimation and calibration: Bayesian and maximum likelihood perspectives in physical anthropology.

Many applied problems in physical anthropology involve estimation of an unobservable quantity (such as age at death or stature) from quantities that are observable. Two of the more disparate subdisciplines of our discipline, paleoanthropology and forensic anthropology, routinely make use of various estimation methods on a case-by-case basis. We discuss the rationales for making estimations on isolated cases, taking stature estimation from femoral and humerus lengths as an example. We show that the entirety of our discussion can be placed within the context of calibration problems, where a large calibration sample is used to estimate an unobservable quantity for a single skeleton. Taking a calibration approach to the problem highlights the essentially Bayesian versus maximum likelihood nature of the question of stature estimation. On the basis of both theoretical arguments and practical examples, we show that inverse calibration (regression of stature on bone length) is generally preferred when the stature distribution for a reference sample forms a reasonable prior, while classical calibration (regression of bone length on stature followed by solving for stature) is preferred when there is reason to suspect that the estimated stature will be an extrapolation beyond the useful limits of the reference sample statures. The choice between these two approaches amounts to the decision to use either a Bayesian or a maximum likelihood method.

Anthropology, Physical↗
PubMed1998

Use of ordinal categorical variables in skeletal assessment of sex from the cranium.

In anthropological studies, visual indicators of sex are traditionally scored on an ordinal categorical scale. Logistic and probit regression models are commonly used statistical tools for the analysis of ordinal categorical data. These models provide unbiased estimates of the posterior probabilities of sex conditional on observed indicators, but they do so only under certain conditions. We suggest a more general method for sexing using a multivariate cumulative probit model and examine both single indicator and multivariate indicator models on a sample of 138 crania from a Late Mississippian site in middle Tennessee. The crania were scored for five common sex indicators: superciliary arch form, chin form, size of mastoid process, shape of the supraorbital margin, and nuchal cresting. Independent assessment of sex for each individual is based on pubic indicators. The traditional logistic regressions are cumbersome because of limitations imposed by missing data. The logistic regression correctly classified 66/74 males and 46/64 females, with an overall correct classification of 81%. The cumulative probit model classified 64/74 males correctly and 51/64 females correctly for an overall correct classification rate of 83%. Finally, we apply parameters estimated from the logit and probit models to find posterior probabilities of sex assignment for 296 additional crania for which pubic indicators were absent or ambiguous.

Aging↗
PubMed1998

Estimation of African ape body length from femur length.

The estimation from long bone lengths of stature in humans or body size in apes has a deep history in physical anthropology. To date, we can enumerate at least five different statistical methods for making such estimations. These methods are: (1) the regression of body length on long bone length (inverse calibration), (2) regression of long bone length on body length followed by solving for body length (classical calibration), (3) major axis regression of body length on long bone length, (4) reduced major axis regression of body length on long bone length, and (5) use of a long bone/body length ratio. We examine some of the statistical properties of these estimators using a large sample of humans (n = 2053) to derive the estimators, and applying them to smaller samples of Pan troglodytes (n = 42), Pan paniscus (n = 8), and Gorilla gorilla (n = 35). Based on the root mean-squared error (RMSE), the reduced major axis is the preferred estimator for body length in the combined Pan sample. However, inverse calibration is the best estimator for body length in gorillas based on the RMSE. Many estimators grossly underestimate body length in the apes. Differences in allometries between humans and great apes are obvious, but it is important to show the assumptions necessary in estimating body size from fossil remains, especially when isolated long bones are recovered and the global allometry is consequently unknown.

Africa↗
PubMed1995

Statistical study of sexual dimorphism in the human fetal sciatic notch.

Whether human fetal skeletal remains exhibit sexual dimorphism has been the subject of considerable debate. Most attention in this debate has focused on the greater sciatic notch of the ilium, since it is a gross morphological characteristic with known sex differences in the adult and is easily seen in fetal skeletal remains. Unfortunately, previous traditional morphometric analyses of the fetal sciatic notch have led to ambiguous results. The purpose of this study is to determine whether differences between the sexes can be discerned when modern morphometric techniques are applied to the fetal sciatic notch. Photographs of the ventral side of 133 fetal ilia of known age and sex from the Trotter Collection of Washington University were digitized, and the trace coordinates used for all subsequent analyses. The results of the analysis demonstrate that there is significant sexual dimorphism in the anterior to posterior location of the maximum depth of the sciatic notch, but that the depth of the notch itself is not dimorphic. While there is significant sexual dimorphism in the shape of the sciatic notch, the amount of overlap between males and females is too great for the sciatic notch to be used as a reliable indicator of sex.

Anthropology, Physical↗
PubMed1995

Multivariate quantitative genetics of anthropometric traits from the Boas data.

The use of multivariate quantitative trait information to address questions of population relationships and evolutionary issues has a long-standing history in human anthropometry. Previous analyses have usually rested on a number of explicit or implicit assumptions that allow phenotypic information to be used as a proxy for quantitative genetic information. One (usually implicit) assumption is that the additive genetic variance-covariance matrix (G) among traits is proportional to the phenotypic variance-covariance matrix (P). In this study we discuss the implications of this assumption, demonstrating that if it is true that G = h2P, where h2 is some constant of proportionality, then (1) the biological (phenotypic) Mahalanobis distance will be proportional to genetic distance, (2) phenotypic and genetic allometry coefficients will be equal, and (3) evolutionary models will become simplified. We then use a multivariate quantitative genetic analysis of 12 anthropometric traits in 5 tribes to demonstrate that G = h2P for at least a portion of the Boas data.

Adult↗
PubMed1993

Cranial deformation and nonmetric trait variation.

Cranial deformation is known to influence many traditional craniometric variables, but its effects on nonmetric trait variation are not well characterized. In this study, we examine the effects of three types of deformation (annular, lambdoid flattening, and fronto-occipital) on nonmetric traits, using a large sample of protohistoric and prehistoric crania. Our results indicate that a few traits are increased or decreased in relative frequency by particular types of deformation, but that these effects have little impact on the calculation of biological distances between groups.

Anthropology, Cultural↗
PubMed1993

Multivariate quantitative genetic simulations in anthropology with an example from the South Pacific.

Computer simulation is a commonly used tool both in genetic epidemiology and in anthropological genetics. We describe here various methods for simulating multivariate quantitative genetic evolution and apply these methods in an analysis of craniometrics from two Pacific island samples. The results of this application indicate that the two samples (one from the Tolai and one from the Moriori) are significantly different, even when allowing for founder effect, intense selection on founders, and genetic drift. The simulation methods we describe and use are commonly applied in animal breeding studies and are much more efficient and general than the multilocus gene-dropping technique usually used in anthropological genetics simulations.

Animals↗
PubMed1992

Effects of fronto-occipital artificial cranial vault modification on the cranial base and face.

Artificial reshaping of the cranial vault has been practiced by many human groups and provides a natural experiment in which the relationships of neurocranial, cranial base, and facial growth can be investigated. We test the hypothesis that fronto-occipital artificial reshaping of the neurocranial vault results in specific changes in the cranial base and face. Fronto-occipital reshaping results from the application of pads or a cradle board which constrains cranial vault growth, limiting growth between the frontal and occipital and allowing compensatory growth of the parietals in a mediolateral direction. Two skeletal series including both normal and artificially modified crania are analyzed, a prehistoric Peruvian Ancon sample (47 normal, 64 modified crania) and a Songish Indian sample from British Columbia (6 normal, 4 modified). Three-dimensional coordinates of 53 landmarks were measured with a diagraph and used to form 9 finite elements as a prelude to finite element scaling analysis. Finite element scaling was used to compare average normal and modified crania and the results were evaluated for statistical significance using a bootstrap test. Fronto-occipitally reshaped Ancon crania are significantly different from normal in the vault, cranial base, and face. The vault is compressed along an anterior-superior to posterior-inferior axis and expanded along a mediolateral axis in modified individuals. The cranial base is wider and shallower in the modified crania and the face is foreshortened and wider with the anterior orbital rim moving inferior and posterior towards the cranial base. The Songish crania display a different modification of the vault and face, indicating that important differences may exist in the morphological effects of fronto-occipital reshaping from one group to another.

British Columbia↗
PubMed1992

Estimation of age structure in anthropological demography.

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.

Age Factors↗
PubMed1991

Mixed model segregation analysis of LDL-C concentration with genotype-covariate interaction.

Mixed model complex segregation analyses have in the past ignored the possibility of genotype-covariate interaction. Only in the nonmixed model with polygenic heritability equal to zero have segregation analyses been performed that allowed for genotype specific regression of the phenotype on covariates. We present an extension of Hasstedt's [1982] mixed model likelihood approximation which does allow for genotype-covariate interaction in the mixed model. Following description of this approximation, we validate the likelihood calculation by a Monte Carlo procedure based on the actual pedigree and missing data structure used in a complex segregation analysis of low density plus very low density lipoprotein cholesterol (LDL-C + VLDL-C) in baboons. The observed averages of the bootstrap parameter estimates adequately recover the generating values, which included parameters specifying genotype-covariate interaction. We then applied both a traditional complex segregation analysis and an analysis with genotype-covariate interaction to test for the presence of a major locus affecting LDL-C levels in baboons. The model including genotype-covariate interaction was significantly different from the model without interactions, and strongly supported the hypothesis that there is a segregating Mendelian locus as opposed to a random environmental factor. This major locus accounts for approximately 46% of the variance in LDL-C levels, as compared to 40% explained by a locus with no genotype-covariate interaction.

Animals↗
PubMed1991

Multivariate segregation analysis using the mixed model.

Most major genes involved in the etiology of complex diseases are likely to have pleiotropic effects on a number of intervening quantitative traits. Methods of segregation analysis that incorporate the additional information from such multiple traits will exhibit greater power for detecting the effects of major genes and allow explicit tests of major locus pleiotropy hypotheses. In this study, we present a new method for multivariate segregation analysis that utilizes a multivariate generalization of Hasstedt's [1982] technique for calculating approximate mixed model likelihoods on pedigrees. The method is based on a simplification of the multivariate conditional likelihood via a transformation that simultaneously orthogonalizes the residual additive genetic and environmental covariance matrices. This transformation allows the multivariate conditional likelihood to be factored into the product of independent univariate conditional likelihoods. Resulting computations are relatively fast, making it feasible to analyze multiple traits in extended pedigrees. We demonstrate our method with a bivariate analysis of high-density lipoprotein cholesterol (HDL-C) and apolipoprotein AI (apo AI) serum levels in 585 pedigreed baboons.

Apolipoprotein A-I↗