Bayes Factors for Forensic Decision Analyses with R

Bayes Factors for Forensic Decision Analyses with R provides a self-contained introduction to computational Bayesian statistics using R. With its primary focus on Bayes factors supported by data sets, this book features an operational perspective, practical relevance, and applicability—keeping theoretical and philosophical justifications limited. It offers a balanced approach to three naturally interrelated topics: – Probabilistic Inference: Relies on the core concept of Bayesian inferential statistics, to help practicing forensic scientists in the logical and balanced evaluation of the weight of evidence. – Decision Making: Features how Bayes factors are interpreted in practical applications to help address questions of decision analysis involving the use of forensic science in the law. – Operational Relevance: Combines inference and decision, backed up with practical examples and complete sample code in R, including sensitivity analyses and discussion on how to interpret results in context. Over the past decades, probabilistic methods have established a firm position as a reference approach for the management of uncertainty in virtually all areas of science, including forensic science, with Bayes' theorem providing the fundamental logical tenet for assessing how new information—scientific evidence—ought to be weighed. Central to this approach is the Bayes factor, which clarifies the evidential meaning of new information, by providing a measure of the change in the odds in favor of a proposition of interest, when going from the prior to the posterior distribution. Bayes factors should guide the scientist's thinking about the value of scientific evidence and form the basis of logical and balanced reporting practices, thus representing essential foundations for rational decision making under uncertainty. This book would be relevant to students, practitioners, and applied statisticians interested in inference and decision analyses in the critical field of forensic science. It could be used to support practical courses on Bayesian statistics and decision theory at both undergraduate and graduate levels, and will be of equal interest to forensic scientists and practitioners of Bayesian statistics for driving their evaluations and the use of R for their purposes

Bayes Factors for Forensic Decision Analyses with R

Bayes Factors for Forensic Decision Analyses with R provides a self-contained introduction to computational Bayesian statistics using R. With its primary focus on Bayes factors supported by data sets, this book features an operational perspective, practical relevance, and applicability—keeping theoretical and philosophical justifications limited. It offers a balanced approach to three naturally interrelated topics: – Probabilistic Inference: Relies on the core concept of Bayesian inferential statistics, to help practicing forensic scientists in the logical and balanced evaluation of the weight of evidence. – Decision Making: Features how Bayes factors are interpreted in practical applications to help address questions of decision analysis involving the use of forensic science in the law. – Operational Relevance: Combines inference and decision, backed up with practical examples and complete sample code in R, including sensitivity analyses and discussion on how to interpret results in context. Over the past decades, probabilistic methods have established a firm position as a reference approach for the management of uncertainty in virtually all areas of science, including forensic science, with Bayes' theorem providing the fundamental logical tenet for assessing how new information—scientific evidence—ought to be weighed. Central to this approach is the Bayes factor, which clarifies the evidential meaning of new information, by providing a measure of the change in the odds in favor of a proposition of interest, when going from the prior to the posterior distribution. Bayes factors should guide the scientist's thinking about the value of scientific evidence and form the basis of logical and balanced reporting practices, thus representing essential foundations for rational decision making under uncertainty. This book would be relevant to students, practitioners, and applied statisticians interested in inference and decision analyses in the critical field of forensic science. It could be used to support practical courses on Bayesian statistics and decision theory at both undergraduate and graduate levels, and will be of equal interest to forensic scientists and practitioners of Bayesian statistics for driving their evaluations and the use of R for their purposes

Bayes Factors for Forensic Decision Analyses with R

Bayes Factors for Forensic Decision Analyses with R provides a self-contained introduction to computational Bayesian statistics using R. With its primary focus on Bayes factors supported by data sets, this book features an operational perspective, practical relevance, and applicability—keeping theoretical and philosophical justifications limited. It offers a balanced approach to three naturally interrelated topics: Probabilistic Inference - Relies on the core concept of Bayesian inferential statistics, to help practicing forensic scientists in the logical and balanced evaluation of the weight of evidence. Decision Making - Features how Bayes factors are interpreted in practical applications to help address questions of decision analysis involving the use of forensic science in the law. Operational Relevance - Combines inference and decision, backed up with practical examples and complete sample code in R, including sensitivity analyses and discussion on how to interpret results in context. Over the past decades, probabilistic methods have established a firm position as a reference approach for the management of uncertainty in virtually all areas of science, including forensic science, with Bayes' theorem providing the fundamental logical tenet for assessing how new information—scientific evidence—ought to be weighed. Central to this approach is the Bayes factor, which clarifies the evidential meaning of new information, by providing a measure of the change in the odds in favor of a proposition of interest, when going from the prior to the posterior distribution. Bayes factors should guide the scientist's thinking about the value of scientific evidence and form the basis of logical and balanced reporting practices, thus representing essential foundations for rational decision making under uncertainty. This book would be relevant to students, practitioners, and applied statisticians interested in inference and decision analyses in the critical field of forensic science. It could be used to support practical courses on Bayesian statistics and decision theory at both undergraduate and graduate levels, and will be of equal interest to forensic scientists and practitioners of Bayesian statistics for driving their evaluations and the use of R for their purposes. This book is Open Access

Forging a Stable Relationship?: Bridging the Law and Forensic Science Divide in the Academy

The marriage of law and science has most often been represented as discordant. While the law/science divide meme is hardly novel, concerns over the potentially deleterious coupling within the criminal justice system may have reached fever pitch. There is a growing chorus of disapproval addressed to ‘forensic science’, accompanied by the denigration of legal professionals for being unable or unwilling to forge a symbiotic relationship with forensic scientists. The 2009 National Academy of Sciences Report on forensic science heralds the latest call for greater collaboration between ‘law’ and ‘science’, particularly in Higher Education Institutions (HEIs) yet little reaction has been apparent amid law and science faculties. To investigate the potential for interdisciplinary cooperation, the authors received funding for a project: ‘Lowering the Drawbridges: Forensic and Legal Education in the 21st Century’, hoping to stimulate both law and forensic science educators to seek mutually beneficial solutions to common educational problems and build vital connections in the academy. A workshop held in the UK, attended by academics and practitioners from scientific, policing, and legal backgrounds marked the commencement of the project. This paper outlines some of the workshop conclusions to elucidate areas of dissent and consensus, and where further dialogue is required, but aims to strike a note of optimism that the ‘cultural divide’ should not be taken to be so wide as to be beyond the legal and forensic science academy to bridge. The authors seek to demonstrate that legal and forensic science educators can work cooperatively to respond to critics and forge new paths in learning and teaching, creating an opportunity to take stock and enrich our discipline as well as answer critics. As Latham (2010:34) exhorts, we are not interested in turning lawyers into scientists and vice versa, but building a foundation upon which they can build during their professional lives: “Instead of melding the two cultures, we need to establish conditions of cooperation, mutual respect, and mutual reliance between them.” Law and forensic science educators should, and can assist with the building of a mutual understanding between forensic scientists and legal professionals, a significant step on the road to answering calls for the professions to minimise some of the risks associated with the use of forensic science in the criminal process. REFERENCES Latham, S.R. 2010, ‘Law between the cultures: C.P.Snow’s The Two Cultures and the problem of scientific illiteracy in law’ 32 Technology in Society, 31-34. KEYWORDS forensic science education legal education law/science divid

Open Labeled Randomized Controlled Clinical Trial on Impaired Glucose Tolerance – IGT (Munneerizhivu)

To evaluate the efficacy of Thiripala Chooranam Tablet (T.TPC) in reversal of Impaired Glucose Tolerance (IGT) through Clinical and Preclinical methods, the null hypothesis stated was TPC will not stop progression of IGT to Diabetic. This study is a pioneer in nature aimed to test the efficacy of T.TPC in Pre-diabetes through Clinical trial. The Trial drug was prepared using Thiripala Chooranam with its decoction as excipient is an innovative idea employed here. The tablet prepared matched the PLIM standards. The drugs used were authenticated by Pharmacognosy Department, SCRI. Physico-chemical and Phytochemical testing was done as per the guidelines. The results revealed that the drug is pure and is free from heavy metals, aflatoxins and microbial load. Pharmacognosy results approved the presence of Polysaccharides. The drug exhibited satisfactory results in inhibition of two glycosidic enzymes namely alpha amylase and alpha glycosidase. The FTIR analysis carried out on the trial drug indicated that there was no chemical interaction between Thiripala Chooranam tablet and excipients, suitability of the excipients in the formulation also tested. The LC_MS analysis showed the presence of Gallic acid, Quercetin, dihydro Corilagin and Chebulinic acid. ICP-OES analysis revealed the presence of essential micro-nutrient in the trial drug. The Open clinical trial carried out helped in identification of T. TPC in reversing Prediabetes by reducing the blood glucose parameters of HbA1c, FBS and OGTT 2hours from Glucose intolerance to Glucose tolerance level. Apart from maintaining Normoglycemia during the follow up period, the drug significantly reduced Serum cholesterol levels (TC, TGL, LDL). The drug compliance was good and no adverse reactions were reported during the treatment period. After the follow up period of 1 month, all (except 2 subjects in the LTPC arm) had normal OGTT levels. Diabetes’ Risk prediction between the two groups by Responder analysis, Calculation of ARR, RRR and RR showed there is significant risk reduction in the LTPC arm by 71.2%, a notable measure. Siddhar’s intuition has once again been proved through this study in causation, prognosis and treatment of Munnerizhivu through concepts of Humoral (Vali, Azhal, Aiyam) pathology and body constitution (Udaliyal) assessment. The outcome measures were reduction in blood glucose parameters and reversal of IGT which was well observed with administration of TPC tablets. Further the trial drug was helpful in reducing the Serum cholesterol levels. The risk of progression to type 2 diabetes is hence well controlled by intake of TPC tablets. Improved the QALY (Quality of Adjusted Life years) is expected in subjects with reduced disease burden. CONCLUSION: The Clinical and Pre – clinical studies conducted disproved the null hypothesis and proved the efficacy of the trial drug, TPC tablet to be a good hypoglycaemic, hypolipidemic and antioxidant which is able to not only treat but also reverse Pre-diabetes, risk of Diabetes and dyslipidaemia. Being a Kayakalpam, the trial drug can be used alongside Convention hypoglycaemic drugs in order to prevent future microvascular complications of Diabetes and hence reduce the disease burden of High risk population

Applications of chemometrics to the analysis and interpretation of forensic physical evidence

Forensic investigations often rely upon items of physical evidence. However, current interpretation protocols for such evidence are subjective, leading to potential bias in forensic examinations. Chemometric techniques may be used to develop more objective methods for assessing evidential significance, as well as establishing statistically validated evidential procedures. This dissertation describes the application of chemometrics to various aspects of physical evidence examination, with a specific focus on textile fibres, pen inks and explosive residues