4 resultados para Bivariate analysis
Resumo:
Although it is well known that sandstone porosity and permeability are controlled by a range of parameters such as grain size and sorting, amount, type, and location of diagenetic cements, extent and type of compaction, and the generation of intergranular and intragranular secondary porosity, it is less constrained how these controlling parameters link up in rock volumes (within and between beds) and how they spatially interact to determine porosity and permeability. To address these unknowns, this study examined Triassic fluvial sandstone outcrops from the UK using field logging, probe permeametry of 200 points, and sampling at 100 points on a gridded rock surface. These field observations were supplemented by laser particle-size analysis, thin-section point-count analysis of primary and diagenetic mineralogy, quantitiative XRD mineral analysis, and SEM/EDAX analysis of all 100 samples. These data were analyzed using global regression, variography, kriging, conditional simulation, and geographically weighted regression to examine the spatial relationships between porosity and permeability and their potential controls. The results of bivariate analysis (global regression) of the entire outcrop dataset indicate only a weak correlation between both permeability porosity and their diagenetic and depositional controls and provide very limited information on the role of primary textural structures such as grain size and sorting. Subdividing the dataset further by bedding unit revealed details of more local controls on porosity and permeability. An alternative geostatistical approach combined with a local modelling technique (geographically weighted regression; GWR) subsequently was used to examine the spatial variability of porosity and permeability and their controls. The use of GWR does not require prior knowledge of divisions between bedding units, but the results from GWR broadly concur with results of regression analysis by bedding unit and provide much greater clarity of how porosity and permeability and their controls vary laterally and vertically. The close relationship between depositional lithofacies in each bed, diagenesis, and permeability, porosity demonstrates that each influences the other, and in turn how understanding of reservoir properties is enhanced by integration of paleoenvironmental reconstruction, stratigraphy, mineralogy, and geostatistics.
Resumo:
This research aims to use the multivariate geochemical dataset, generated by the Tellus project, to investigate the appropriate use of transformation methods to maintain the integrity of geochemical data and inherent constrained behaviour in multivariate relationships. The widely used normal score transform is compared with the use of a stepwise conditional transform technique. The Tellus Project, managed by GSNI and funded by the Department of Enterprise Trade and Development and the EU’s Building Sustainable Prosperity Fund, involves the most comprehensive geological mapping project ever undertaken in Northern Ireland. Previous study has demonstrated spatial variability in the Tellus data but geostatistical analysis and interpretation of the datasets requires use of an appropriate methodology that reproduces the inherently complex multivariate relations. Previous investigation of the Tellus geochemical data has included use of Gaussian-based techniques. However, earth science variables are rarely Gaussian, hence transformation of data is integral to the approach. The multivariate geochemical dataset generated by the Tellus project provides an opportunity to investigate the appropriate use of transformation methods, as required for Gaussian-based geostatistical analysis. In particular, the stepwise conditional transform is investigated and developed for the geochemical datasets obtained as part of the Tellus project. The transform is applied to four variables in a bivariate nested fashion due to the limited availability of data. Simulation of these transformed variables is then carried out, along with a corresponding back transformation to original units. Results show that the stepwise transform is successful in reproducing both univariate statistics and the complex bivariate relations exhibited by the data. Greater fidelity to multivariate relationships will improve uncertainty models, which are required for consequent geological, environmental and economic inferences.
Resumo:
Purpose: There is an urgent need to develop diagnostic tests to improve the detection of pathogens causing life-threatening infection (sepsis). SeptiFast is a CE-marked multi-pathogen real-time PCR system capable of detecting DNA sequences of bacteria and fungi present in blood samples within a few hours. We report here a systematic review and meta-analysis of diagnostic accuracy studies of SeptiFast in the setting of suspected sepsis.
Methods: A comprehensive search strategy was developed to identify studies that compared SeptiFast with blood culture in suspected sepsis. Methodological quality was assessed using QUADAS. Heterogeneity of studies was investigated using a coupled forest plot of sensitivity and specificity and a scatter plot in receiver operator characteristic space. Bivariate model method was used to estimate summary sensitivity and specificity.
Results: From 41 phase III diagnostic accuracy studies, summary sensitivity and specificity for SeptiFast compared with blood culture were 0.68 (95 % CI 0.63–0.73) and 0.86 (95 % CI 0.84–0.89) respectively. Study quality was judged to be variable with important deficiencies overall in design and reporting that could impact on derived diagnostic accuracy metrics.
Conclusions: SeptiFast appears to have higher specificity than sensitivity, but deficiencies in study quality are likely to render this body of work unreliable. Based on the evidence presented here, it remains difficult to make firm recommendations about the likely clinical utility of SeptiFast in the setting of suspected sepsis.
Resumo:
This paper examines relationships between religion and two forms of homonegativity
across 43 European countries using a bivariate response binary logistic multilevel model. The model analyzes effects of religious believing, belonging and practice on two response variables: a) a moral rejection of homosexuality as a practice and b) intolerance toward homosexuals as a group. The findings indicate that both forms of homonegativity are prevalent in Europe. Traditional doctrinal religious believing (belief in a personal God) is positively related to a moral rejection of homosexuality but to a much lesser extent associated with intolerance toward homosexuals as a group. Members of religious denominations are more likely than non-members to reject homosexuality as morally wrong and to reject homosexuals as neighbors. The analysis found significant differences between denominations that are likely context-dependent. Attendance at religious services is positively related to homonegativity in a majority of countries. The findings vary considerably across countries: Religion is more strongly related to homonegativity in Western than in Eastern Europe. In the post-soviet countries homonegativity appears to be largely a secular phenomenon. National contexts of high religiosity, high perceived government corruption, high income inequality and shortcomings in the implementation of gay rights in the countries’ legislations are statistically related to higher levels of both moralistic homonegativity and intolerance toward homosexuals as a group.