The evaluation of measurements on characteristics of trace evidence found at a crime scene and on a suspect is an important part of forensic science. Five methods of assessment for the value of the evidence for multivariate data are described. Two are based on significance tests and three on the evaluation of likelihood ratios. The likelihood ratio which compares the probability of the measurements on the evidence assuming a common source for the crime scene and suspect evidence with the probability of the measurements on the evidence assuming different sources for the crime scene and suspect evidence is a well-documented measure of the value of the evidence. One of the likelihood ratio approaches transforms the data to a univariate projection based on the first principal component. The other two versions of the likelihood ratio for multivariate data account for correlation among the variables and for two levels of variation: that between sources and that within sources. One version assumes that between-source variability is modelled by a multivariate normal distribution; the other version models the variability with a multivariate kernel density estimate. Results are compared from the analysis of measurements on the elemental composition of glass. Copyright 2004 Royal Statistical Society.

The aim of this paper is to consider the diagnostic criteria for tuberculosis in ancient populations. It investigates the frequency of periosteal new bone formation on the visceral surfaces of ribs from 1718 individuals from the Terry Collection, Smithsonian Institution, Washington D.C. and attempts to determine the aetiological factors producing these lesions. Numbers of individuals with lesions according to cause of death were recorded and the patterning of lesions compared between people who had died from tuberculosis and those whose cause of death was unrelated to a pulmonary disease. Rib lesions were more common in individuals dying from tuberculosis (61.6% or 157 of 255) than in individuals dying from other causes (15.2% or 165 of 1086). It is suggested that tuberculosis at a peripheral lung focus may disseminate directly through the pleura to the visceral surfaces of the ribs, or that pulmonary tuberculosis may be the cause of empyema of the pleural cavity and that this, per se, may initiate inflammatory change on the visceral surfaces of ribs. The nonrecognition or description of these often very subtle proliferative lesions on ribs by radiological examination of tuberculous victims is significant in the discussion of bone changes in tuberculosis. The possibility that individuals with no recorded history of tuberculosis at death actually suffered from the disease was considered in light of the frequency of rib lesions and noncorrelation with a tuberculous cause of death. Differential diagnoses are discussed including the possibility that the lesions represent a general non-specific indicator of stress.

Accurate estimation of human adult age has always been a problem for anthropologists, archaeologists and forensic scientists. The main factor contributing to the difficulties is the high variability of physiological age indicators. However, confounding this variability in many age estimation applications is a systematic tendency for age estimates, regardless of physiological indicator employed, to assign ages which are too high for young individuals, and too low for older individuals. This paper shows that at least part of this error is the inevitable consequence of the statistical procedures used to extract an estimate of age from age indicators, and that the magnitude of the error is inversely related to how well an age indicator is correlated with age. The use of classical calibration over inverse calibration is recommended for age estimation.

Much of the data which appears in the forensic and archaeological literature is ordinal or categorical. This is particularly true of the age related indicators presented by Gustafson [1] in his method of human adult age estimation using the structural changes in human teeth. This technique is still being modified and elaborated. However, the statistical methods of regression analysis employed by Gustafson and others are not particularly appropriate to this type of data, but are still employed because alternatives have not yet been explored. This paper presents a novel approach based upon the application of Bayes' theorem to ordinal and categorical data, which overcomes many of the problems associated with regression analysis.

The pattern of degenerative joint disease (DJD) of the intervertebral and apophyseal joints of the vertebral column of 81 skeletons from the thirteenth to fourteenth century medieval priory cemetery of St. Andrew, Fishergate, York, was recorded in relation to their location of interment: eastern cemetery, southern cemetery, and intramurally (within the priory buildings). Archaeological context and ethnohistorical accounts support the interpretation that people of different social status were buried in these areas. Linear discriminant function analysis and paired Kolmogorov-Smirnov tests showed that the differences in vertebral column DJD pattern and severity among the three subgroups were not statistically significant. As the archaeological and historical evidence seems reliable, it is argued that the analysis of DJD of the vertebral column might not be ideal to study the effects of normal activity patterns, a conclusion which supports the results of recent bioarchaeological research. Further, high-low plots demonstrate that the differences in DJD pattern were located between intervertebral and apophyseal joints of individuals rather than between subgroups of the cemetery. It is thought that this difference was produced as a response to erect posture during bipedal locomotion, reflecting vertebral curvatures, rather than differing occupational stresses. Thus, due to biological constraints on its function, the vertebral column might not be an ideal structure to study markers of occupational stress.

A random effects model using two levels of hierarchical nesting has been applied to the calculation of a likelihood ratio as a solution to the problem of comparison between two sets of replicated multivariate continuous observations where it is unknown whether the sets of measurements shared a common origin. Replicate measurements from a population of such measurements allow the calculation of both within-group and between-group variances/covariances. The within-group distribution has been modelled assuming a Normal distribution, and the between-group distribution has been modelled using a kernel density estimation procedure. A graphical method of estimating the dependency structure among the variables has been used to reduce this highly multivariate problem to several problems of lower dimension. The approach was tested using a database comprising measurements of eight major elements from each of four fragments from each of 200 glass objects and found to perform well compared with previous approaches, achieving a 15.2% false-positive rate, and a 5.5% false-negative rate. The modelling was then applied to two examples of casework in which glass found at the scene of the criminal activity has been compared with that found in association with a suspect.

It is generally assumed that life expectancy in antiquity was considerably shorter than it is now. In the limited number of cases where skeletal or dental age-at-death estimates have been made on adults for whom there are other reliable indications of age, there appears to be a clear systematic trend towards overestimating the age of young adults, and underestimating that of older individuals. We show that this might be a result of the use of regression-based techniques of analysis for converting age indicators into estimated ages. Whilst acknowledging the limitations of most age-at-death indicators in the higher age categories, we show that a Bayesian approach to converting age indicators into estimated age can reduce this trend of underestimation at the older end. We also show that such a Bayesian approach can always do better than regression-based methods in terms of giving a smaller average difference between predicted age and known age, and a smaller average 95-percent confidence interval width of the estimate. Given these observations, we suggest that Bayesian approaches to converting age indicators into age estimates deserve further investigation. In view of the generality and flexibility of the approach, we also suggest that similar algorithms may have a much wider application.

No abstract