986 resultados para Probability and statistics
Resumo:
Previous research on pavement markings from a safety perspective tackled various issues such as pavement marking retroreflectivity variability, relationship between pavement marking retroreflectivity and driver visibility, or pavement marking improvements and safety. A recent research interest in this area has been to find a correlation between retroreflectivity and crashes, but a significant statistical relationship has not yet been found. This study investigates such a possible statistical relationship by analyzing five years of pavement marking retroreflectivity data collected by the Iowa Department of Transportation (DOT) on all state primary roads and corresponding crash and traffic data. This study developed a spatial-temporal database using measured retroreflectivity data to account for the deterioration of pavement markings over time along with statewide crash data to attempt to quantify a relationship between crash occurrence probability and pavement marking retroreflectivity. First, logistic regression analyses were done for the whole data set to find a statistical relationship between crash occurrence probability and identified variables, which are road type, line type, retroreflectivity, and traffic (vehicle miles traveled). The analysis looked into subsets of the data set such as road type, retroreflectivity measurement source, high crash routes, retroreflectivity range, and line types. Retroreflectivity was found to have a significant effect in crash occurrence probability for four data subsets—interstate, white edge line, yellow edge line, and yellow center line data. For white edge line and yellow center line data, crash occurrence probability was found to increase by decreasing values of retroreflectivity.
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This study explores the statistical relationship between crash occurrence probability and longitudinal pavement marking retroreflectivity. Problem Statement Previous research on pavement markings, from a safety perspective, tackled various issues, such as pavement marking retroreflectivity variability, relationship between pavement marking retroreflectivity and driver visibility, and pavement marking improvements and safety. A recent research interest in this area is to find a correlation between retroreflectivity and crashes, as a significant statistical relationship is undefined to date.
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This is an "Industrial-Economic Survey" of Clinton, Iowa and the surrounding area that was compiled and assembled for the use of any manufacturing of commercial organization which has in interest in setting up operations in the general Clinton area. Facts and statistics are shown to use for location analysis. Numerous photos and maps are included.
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Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path
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The present paper focuses on the analysis and discussion of a likelihood ratio (LR) development for propositions at a hierarchical level known in the context as 'offence level'. Existing literature on the topic has considered LR developments for so-called offender to scene transfer cases. These settings involve-in their simplest form-a single stain found on a crime scene, but with possible uncertainty about the degree to which that stain is relevant (i.e. that it has been left by the offender). Extensions to multiple stains or multiple offenders have also been reported. The purpose of this paper is to discuss a development of a LR for offence level propositions when case settings involve potential transfer in the opposite direction, i.e. victim/scene to offender transfer. This setting has previously not yet been considered. The rationale behind the proposed LR is illustrated through graphical probability models (i.e. Bayesian networks). The role of various uncertain parameters is investigated through sensitivity analyses as well as simulations.
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This project is part of an effort conducted by the Justice Research and Statistics Association (JRSA) under a grant whose objective is to provide states with descriptions of existing methodologies to collect Domestic Violence (DV) and Sexual Assault (SA) data. JRSA has identified three different methodologies to collect such data: · Incident-based reporting as part of the Uniform Crime Reports · Specialized data collection from law enforcement through a separate data collection system · Specialized data collection coming directly from service providers. One state has been selected as an example of each type of data collection above, with Iowa selected as a representative of states with incident based reporting (IBR) as part of the UCR system.
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In this paper, we analyze the prospective method of paying hospitals when the within-DRG variance is high. To avoid patients dumping, an outlier payment system is implemented. In the APDRG Swiss System, it consists in a mixture of fully prospective payments for low costs patients and partially cost-based system for high cost patients. We show how the optimal policy depends on the degree to which hospitals take patients' interest into account. A fixed-price policy is optimal when the hospital is sufficiently benevolent. When the hospital is weakly benevolent, a mixed policy solving a trade-off between rent extraction, efficiency and dumping deterrence must be preferred. Following Mougeot and Naegelen (2008), we show how the optimal combination of fixed price and partially costbased payment depends on the degree of benevolence of the hospital, the social cost of public funds and the distribution of patients severity. [Authors]
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The effect of heterogeneous environments upon the dynamics of invasion and the eradication or control of invasive species is poorly understood, although it is a major challenge for biodiversity conservation. Here, we first investigate how the probability and time for invasion are affected by spatial heterogeneity. Then, we study the effect of control program strategies (e.g. species specificity, spatial scale of action, detection and eradication efficiency) on the success and time of eradication. We find that heterogeneity increases both the invasion probability and the time to invasion. Heterogeneity also reduces the probability of eradication but does not change the time taken for successful eradication. We confirm that early detection of invasive species reduces the time until eradication, but we also demonstrate that this is true only if the local control action is sufficiently efficient. The criterion of removal efficiency is even more important for an eradication program than simply ensuring control effort when the invasive species is not abundant.
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A new model for dealing with decision making under risk by considering subjective and objective information in the same formulation is here presented. The uncertain probabilistic weighted average (UPWA) is also presented. Its main advantage is that it unifies the probability and the weighted average in the same formulation and considering the degree of importance that each case has in the analysis. Moreover, it is able to deal with uncertain environments represented in the form of interval numbers. We study some of its main properties and particular cases. The applicability of the UPWA is also studied and it is seen that it is very broad because all the previous studies that use the probability or the weighted average can be revised with this new approach. Focus is placed on a multi-person decision making problem regarding the selection of strategies by using the theory of expertons.
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Our goal was to evaluate the diagnostic utility of C-reactive protein (CRP) alone or combined with clinical probability assessment in patients with suspected pulmonary embolism (PE), and to compare its performance to a D-dimer assay. We conducted a prospective study in which we performed a common immuno-turbidimetric CRP test and a rapid enzyme-linked immunosorbent assay (ELISA) D-dimer test in 259 consecutive outpatients with suspected PE at the emergency department of a teaching hospital. We assessed clinical probability of PE by a validated prediction rule overridden by clinical judgment. Patients with D-dimer levels > or = 500 microg/l underwent a work-up consisting of lower-limb venous ultrasound, spiral computerized tomography, ventilation-perfusion scan, or pulmonary angiography. Patients were followed up for three months. Seventy-seven (30%) of the patients had PE. The CRP alone had a sensitivity of 84% (95% confidence interval [CI).: 74 to 92%) and a negative predictive value (NPV) of 87% (95% CI: 78 to 93%) at a cutpoint of 5 mg/l. Overall, 61 (24%) patients with a low clinical probability of PE had a CRP < 5 mg/l. Due to the low prevalence of PE (9%) in this subgroup, the NPV increased to 97% (95% CI: 89 to 100%). The D-dimer (cutpoint 500 micro g/l) showed a sensitivity of 100% (95% CI: 95 to 100%) and a NPV of 100% (95% CI: 94 to 100%) irrespective of clinical probability and accurately rule out PE in 56 (22%) patients. Standard CRP tests alone or combined with clinical probability assessment cannot safely exclude PE.
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At a time when disciplined inference and decision making under uncertainty represent common aims to participants in legal proceedings, the scientific community is remarkably heterogenous in its attitudes as to how these goals ought to be achieved. Probability and decision theory exert a considerable influence, and we think by all reason rightly do so, but they go against a mainstream of thinking that does not embrace-or is not aware of-the 'normative' character of this body of theory. It is normative, in the sense understood in this article, in that it prescribes particular properties, typically (logical) coherence, to which reasoning and decision making ought to conform. Disregarding these properties can result in diverging views which are occasionally used as an argument against the theory, or as a pretext for not following it. Typical examples are objections according to which people, both in everyday life but also individuals involved at various levels in the judicial process, find the theory difficult to understand and to apply. A further objection is that the theory does not reflect how people actually behave. This article aims to point out in what sense these examples misinterpret the analytical framework in its normative perspective. Through examples borrowed mostly from forensic science contexts, it is argued that so-called intuitive scientific attitudes are particularly liable to such misconceptions. These attitudes are contrasted with a statement of the actual liberties and constraints of probability and decision theory and the view according to which this theory is normative.
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Market segmentation is an important issue when estimating the implicit price for an environmental amenity from a surrogate market like property. This paper tests the hypothesis of a segmentation of the housing market between tourists and residents and computes the implicit price for natural landscape quality in Swiss alpine resorts. The results show a clear segmentation between both groups of consumers, although tests also show that the estimated coefficient for landscape is similar in the tourists' model and in the residents'. However, since the functional form is non linear, the nominal - rather than relative - value of a change in natural landscape quality is higher in the tourist housing market than in the residents'. Hence, considering the segmentation of the market between tourists and residents is essential in order to provide valid estimates of the nominal implicit price of natural landscape quality.
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Social reciprocity may explain certain emerging psychological processes, which are likely to be founded on dyadic relations. Although some indices and statistics have been proposed to measure and make statistical decisions regarding social reciprocity in groups, these were generally developed to identify association patterns rather than to quantify the discrepancies between what each individual addresses to his/her partners and what is received from them in return. Additionally, social researchers are not only interested in measuring groups at the global level, since dyadic and individual measurements are also necessary for a proper description of social interactions. This study is concerned with a new statistic for measuring social reciprocity at the global level and with decomposing it in order to identify those dyads and individuals which account for a significant part of asymmetry in social interactions. In addition to a set of indices some exact analytical results are derived and a way of making statistical decisions is proposed.