Discussion of: Statistical analysis of an archeological find

Discussion of ``Statistical analysis of an archeological find'' by Andrey Feuerverger [arXiv:0804.0079]Comment: Published in at http://dx.doi.org/10.1214/08-AOAS99F the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Sensitivity of inferences in forensic genetics to assumptions about founding genes

Many forensic genetics problems can be handled using structured systems of discrete variables, for which Bayesian networks offer an appealing practical modeling framework, and allow inferences to be computed by probability propagation methods. However, when standard assumptions are violated--for example, when allele frequencies are unknown, there is identity by descent or the population is heterogeneous--dependence is generated among founding genes, that makes exact calculation of conditional probabilities by propagation methods less straightforward. Here we illustrate different methodologies for assessing sensitivity to assumptions about founders in forensic genetics problems. These include constrained steepest descent, linear fractional programming and representing dependence by structure. We illustrate these methods on several forensic genetics examples involving criminal identification, simple and complex disputed paternity and DNA mixtures.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS235 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Identification and separation of DNA mixtures using peak area information (Updated version of Statistical Research Paper No. 25)

We introduce a new methodology, based upon probabilistic expert systems, for analysing forensic identification problems involving DNA mixture traces using quantitative peak area information. Peak area is modelled with conditional Gaussian distributions. The expert system can be used for ascertaining whether individuals, whose profiles have been measured, have contributed to the mixture, but also to predict DNA profiles of unknown contributors by separating the mixture into its individual components. The potential of our probabilistic methodology is illustrated on case data examples and compared with alternative approaches. The advantages are that identification and separation issues can be handled in a unified way within a single probabilistic model and the uncertainty associated with the analysis is quantified. Further work, required to bring the methodology to a point where it could be applied to the routine analysis of casework, is discussed

Probabilistic expert systems for handling artifacts in complex DNA mixtures

This paper presents a coherent probabilistic framework for taking account of allelic dropout, stutter bands and silent alleles when interpreting STR DNA profiles from a mixture sample using peak size information arising from a PCR analysis. This information can be exploited for evaluating the evidential strength for a hypothesis that DNA from a particular person is present in the mixture. It extends an earlier Bayesian network approach that ignored such artifacts. We illustrate the use of the extended network on a published casework example

Inference about complex relationships using peak height data from DNA mixtures

In both criminal cases and civil cases there is an increasing demand for the analysis of DNA mixtures involving relationships. The goal might be, for example, to identify the contributors to a DNA mixture where the donors may be related, or to infer the relationship between individuals based on a mixture. This paper introduces an approach to modelling and computation for DNA mixtures involving contributors with arbitrarily complex relationships. It builds on an extension of Jacquard's condensed coefficients of identity, to specify and compute with joint relationships, not only pairwise ones, including the possibility of inbreeding. The methodology developed is applied to two casework examples involving a missing person, and simulation studies of performance, in which the ability of the methodology to recover complex relationship information from synthetic data with known `true' family structure is examined. The methods used to analyse the examples are implemented in the new KinMix R package, that extends the DNAmixtures package to allow for modelling DNA mixtures with related contributors. KinMix inherits from DNAmixtures the capacity to deal with mixtures with many contributors, in a time- and space-efficient way.Comment: 29 pages, 12 figures, 20 tables; V2 has different casework examples, and general minor edits; V3 has general edits following review, including lengthier exposition; V4 has further explanation, and a supplementary appendix on related softwar

Analysis of forensic DNA mixtures with artefacts

DNA is now routinely used in criminal investigations and court cases, although DNA samples taken at crime scenes are of varying quality and therefore present challenging problems for their interpretation. We present a statistical model for the quantitative peak information obtained from an electropherogram of a forensic DNA sample and illustrate its potential use for the analysis of criminal cases. In contrast with most previously used methods, we directly model the peak height information and incorporate important artefacts that are associated with the production of the electropherogram. Our model has a number of unknown parameters, and we show that these can be estimated by the method of maximum likelihood in the presence of multiple unknown individuals contributing to the sample, and their approximate standard errors calculated; the computations exploit a Bayesian network representation of the model. A case example from a UK trial, as reported in the literature, is used to illustrate the efficacy and use of the model, both in finding likelihood ratios to quantify the strength of evidence, and in the deconvolution of mixtures for finding likely profiles of the individuals contributing to the sample. Our model is readily extended to simultaneous analysis of more than one mixture as illustrated in a case example. We show that the combination of evidence from several samples may give an evidential strength which is close to that of a single-source trace and thus modelling of peak height information provides a potentially very efficient mixture analysis

Testing the CAPM: Evidences from Italian Equity Markets

The aim of the following work is to exploit principal econometric tecniques to test the Capital Asset Pricing Model theory in Italian equity markets. CAPM is a financial model which describes expected returns of any assets (or asset portfolio) as a function of the expected return on the market portfolio. In this paper I will first explain the meaning of the market risk and I will measure it via the estimation of beta coeffcients, which are seen as a measure of assets sensitivity to market portfolio fluctuations. The theoretical framework is based on the Sharpe (1964) and Lintner (1965) version of the CAPM and on the Pettengill's hypothesis (1995) over the relationship between betas and returns. Secondly, I will test the presence of specific effects which usually occur in financial markets; in particular, I will check the presence of the well-known January effect and detect the existence of structural breaks over the considered period of time

Changing Attitudes towards Hepatitis B among Asian Americans: From Saving Face to Getting Serious

Background: Asian Americans have the highest prevalence of hepatitis B virus (HBV) in the US. The San Francisco Hep B Free (SFHBF) campaign aimed to increase awareness and access to HBV education and services among Asian Americans in San Francisco. Purpose: We sought to examine attitudes and knowledge among Asian Americans regarding HBV at baseline (2009) and benefits of the SFHBF outreach campaign four years later (2013). Methods: Four focus groups were conducted (n=45) in 2009, followed by in-depth interviews (n=40) in 2013. Results: In 2009, many participants were misinformed about HBV symptoms and transmission. They also reported stigma associated with HBV, which hindered Asian Americans from discussing the disease and seeking services. The 2013 interviews revealed that SFHBF had contributed towards awareness of HBV screenings and vaccinations, and also instilled acute seriousness that HBV could affect them directly. Conclusion: The in-depth interviews conducted in 2013 illustrated that there was less concern about “saving face,” but a shift to a level of seriousness associated with HBV. Future efforts among Asian Americans should continue to focus on self-efficacy regarding HBV prevention, including screening and vaccination