Chemical profiling of different hashish seizures by gas chromatography-mass spectrometry and statistical methodology: a case report

Limited information is available regarding the methodology required to characterize hashish seizures for assessing the presence or the absence of a chemical link between two seizures. This casework report presents the methodology applied for assessing that two different police seizures were coming from the same block before this latter one was split. The chemical signature was extracted using GC-MS analysis and the implemented methodology consists in a study of intra- and inter-variability distributions based on the measurement of the chemical profiles similarity using a number of hashish seizures and the calculation of the Pearson correlation coefficient. Different statistical scenarios (i.e., a combination of data pretreatment techniques and selection of target compounds) were tested to find the most discriminating one. Seven compounds showing high discrimination capabilities were selected on which a specific statistical data pretreatment was applied. Based on the results, the statistical model built for comparing the hashish seizures leads to low error rates. Therefore, the implemented methodology is suitable for the chemical profiling of hashish seizures.

A statistical methodology for the comparison of blue gel pen inks analyzed by laser desorption/ionization mass spectrometry

A statistical methodology for the objective comparison of LDI-MS mass spectra of blue gel pen inks was evaluated. Thirty-three blue gel pen inks previously studied by RAMAN were analyzed directly on the paper using both positive and negative mode. The obtained mass spectra were first compared using relative areas of selected peaks using the Pearson correlation coefficient and the Euclidean distance. Intra-variability among results from one ink and inter-variability between results from different inks were compared in order to choose a differentiation threshold minimizing the rate of false negative (i.e. avoiding false differentiation of the inks). This yielded a discriminating power of up to 77% for analysis made in the negative mode. The whole mass spectra were then compared using the same methodology, allowing for a better DP in the negative mode of 92% using the Pearson correlation on standardized data. The positive mode results generally yielded a lower differential power (DP) than the negative mode due to a higher intra-variability compared to the inter-variability in the mass spectra of the ink samples.

Threshold detection: matching statistical methodology to ecological questions and conservation planning objectives

Two types of ecological thresholds are now being widely used to develop conservation targets: breakpoint-based thresholds represent tipping points where system properties change dramatically, whereas classification thresholds identify groups of data points with contrasting properties. Both breakpoint-based and classification thresholds are useful tools in evidence-based conservation. However, it is critical that the type of threshold to be estimated corresponds with the question of interest and that appropriate statistical procedures are used to determine its location. On the basis of their statistical properties, we recommend using piecewise regression methods to identify breakpoint-based thresholds and discriminant analysis or classification and regression trees to identify classification thresholds.

Statistical methodology for a comparison of the individual characteristics and death rates of disabled-worker beneficiaries in 1972 and 1985 /

"September 1992."

Exploring the knowledge contained in neuroimages: Statistical discriminant analysis and automatic segmentation of the most significant changes

Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. All rights reserved.

Statistical methods for examining genetic influences of resistance to anti-epileptic drugs

It is generally accepted that genetics may be an important factor in explaining the variation between patients’ responses to certain drugs. However, identification and confirmation of the responsible genetic variants is proving to be a challenge in many cases. A number of difficulties that maybe encountered in pursuit of these variants, such as non-replication of a true effect, population structure and selection bias, can be mitigated or at least reduced by appropriate statistical methodology. Another major statistical challenge facing pharmacogenetics studies is trying to detect possibly small polygenic effects using large volumes of genetic data, while controlling the number of false positive signals. Here we review statistical design and analysis options available for investigations of genetic resistance to anti-epileptic drugs.

Accessing extremes of mid-latitudinal wave activity: methodology and application

A statistical methodology is proposed and tested for the analysis of extreme values of atmospheric wave activity at mid-latitudes. The adopted methods are the classical block-maximum and peak over threshold, respectively based on the generalized extreme value (GEV) distribution and the generalized Pareto distribution (GPD). Time-series of the ‘Wave Activity Index’ (WAI) and the ‘Baroclinic Activity Index’ (BAI) are computed from simulations of the General Circulation Model ECHAM4.6, which is run under perpetual January conditions. Both the GEV and the GPD analyses indicate that the extremes ofWAI and BAI areWeibull distributed, this corresponds to distributions with an upper bound. However, a remarkably large variability is found in the tails of such distributions; distinct simulations carried out under the same experimental setup provide sensibly different estimates of the 200-yr WAI return level. The consequences of this phenomenon in applications of the methodology to climate change studies are discussed. The atmospheric configurations characteristic of the maxima and minima of WAI and BAI are also examined.

Draft biennial programme of regional and international cooperation activities of the Statistical Conference of the Americas of ECLAC, 2007-2009

Includes bibliography

Statistical issues on studies of mixed longitudinal design

Mixed longitudinal designs are important study designs for many areas of medical research. Mixed longitudinal studies have several advantages over cross-sectional or pure longitudinal studies, including shorter study completion time and ability to separate time and age effects, thus are an attractive choice. Statistical methodology used in general longitudinal studies has been rapidly developing within the last few decades. Common approaches for statistical modeling in studies with mixed longitudinal designs have been the linear mixed-effects model incorporating an age or time effect. The general linear mixed-effects model is considered an appropriate choice to analyze repeated measurements data in longitudinal studies. However, common use of linear mixed-effects model on mixed longitudinal studies often incorporates age as the only random-effect but fails to take into consideration the cohort effect in conducting statistical inferences on age-related trajectories of outcome measurements. We believe special attention should be paid to cohort effects when analyzing data in mixed longitudinal designs with multiple overlapping cohorts. Thus, this has become an important statistical issue to address. ^ This research aims to address statistical issues related to mixed longitudinal studies. The proposed study examined the existing statistical analysis methods for the mixed longitudinal designs and developed an alternative analytic method to incorporate effects from multiple overlapping cohorts as well as from different aged subjects. The proposed study used simulation to evaluate the performance of the proposed analytic method by comparing it with the commonly-used model. Finally, the study applied the proposed analytic method to the data collected by an existing study Project HeartBeat!, which had been evaluated using traditional analytic techniques. Project HeartBeat! is a longitudinal study of cardiovascular disease (CVD) risk factors in childhood and adolescence using a mixed longitudinal design. The proposed model was used to evaluate four blood lipids adjusting for age, gender, race/ethnicity, and endocrine hormones. The result of this dissertation suggest the proposed analytic model could be a more flexible and reliable choice than the traditional model in terms of fitting data to provide more accurate estimates in mixed longitudinal studies. Conceptually, the proposed model described in this study has useful features, including consideration of effects from multiple overlapping cohorts, and is an attractive approach for analyzing data in mixed longitudinal design studies.^

Statistical analysis of shape through triangulation of landmarks: A study of sexual dimorphism in hominids

Two objects with homologous landmarks are said to be of the same shape if the configuration of landmarks of one object can be exactly matched with that of the other by translation, rotation/reflection, and scaling. In an earlier paper, the authors proposed statistical analysis of shape by considering logarithmic differences of all possible Euclidean distances between landmarks. Tests of significance for differences in the shape of objects and methods of discrimination between populations were developed with such data. In the present paper, the corresponding statistical methodology is developed by triangulation of the landmarks and by considering the angles as natural measurements of shape. This method is applied to the study of sexual dimorphism in hominids.

Inspeção sanitária em creches: uma proposta de roteiro de inspeção

O trabalho apresenta um projeto de intervenção na realidade concreta das ações de Vigilância Sanitária, através da proposição de um roteiro para inspeção destinado a creches. Os objetivos específicos foram identificar os fundamentos jurídicos, técnico-científicos e sanitários que possam nortear a prática de inspeções sanitárias em creches; elaborar uma proposta de roteiro que permita um processo de análise mais explícito, objetivo e homogêneo e discutir a contribuição do instrumento proposto para a atividade de Vigilância Sanitária, com base na literatura científica pesquisada. Para a realização do trabalho foi feita uma revisão fundamentada em textos didáticos e normativos das áreas de educação e saúde, legislação sobre Vigilância Sanitária e Educação Infantil, outros roteiros já existentes e artigos da literatura científica sobre agravos à saúde em crianças que frequentam creches. O trabalho focaliza o conteúdo da legislação específica vigente e sua aplicabilidade na prática da inspeção sanitária em creches e baseia-se na Portaria - MS n. 321 de 26.05.1988. Este estudo apresenta um instrumento para avaliar a qualidade do atendimento nas creches sob o aspecto da promoção da saúde e sugere estudos posteriores de validação para o contexto, com a possível inclusão de um sistema de classificação para os padrões de conformidade, por meio de uma metodologia estatística

Interspecific variation in plumage colour among birds: species recognition or light environment?

The traditional explanation for interspecific plumage colour variation in birds is that colour differences between species are adaptations to minimize the risk of hybridization. Under this explanation, colour differences between closely related species of birds represent reproductive character displacement. An alternative explanation is that interspecific variation in plumage colour is an adaptive response to variation in light environments across habitats. Under this explanation, differences in colour between closely related species are a product of selection on signal efficiency. We use a comparative approach to examine these two hypotheses, testing the effects of sympatry and habitat use, respectively, on divergence in male plumage colour. Contrary to the prediction of the Species Isolation Hypothesis, we find no evidence that sympatric pairs of species are consistently more divergent in coloration than are allopatric pairs of species. However, in agreement with the Light Environment Hypothesis, we find significant associations between plumage coloration and habitat use. All of these results remain qualitatively unchanged irrespective of the statistical methodology used to compare reflectance spectra, the body regions used in the analyses, or the exclusion of areas of plumage not used in sexual displays. Our results suggest that, in general, interspecific variation in plumage colour among birds is more strongly influenced by the signalling environment than by the risk of hybridization.