940 resultados para Statistical concordance


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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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BACKGROUND: PCR has the potential to detect and precisely quantify specific DNA sequences, but it is not yet often used as a fully quantitative method. A number of data collection and processing strategies have been described for the implementation of quantitative PCR. However, they can be experimentally cumbersome, their relative performances have not been evaluated systematically, and they often remain poorly validated statistically and/or experimentally. In this study, we evaluated the performance of known methods, and compared them with newly developed data processing strategies in terms of resolution, precision and robustness. RESULTS: Our results indicate that simple methods that do not rely on the estimation of the efficiency of the PCR amplification may provide reproducible and sensitive data, but that they do not quantify DNA with precision. Other evaluated methods based on sigmoidal or exponential curve fitting were generally of both poor resolution and precision. A statistical analysis of the parameters that influence efficiency indicated that it depends mostly on the selected amplicon and to a lesser extent on the particular biological sample analyzed. Thus, we devised various strategies based on individual or averaged efficiency values, which were used to assess the regulated expression of several genes in response to a growth factor. CONCLUSION: Overall, qPCR data analysis methods differ significantly in their performance, and this analysis identifies methods that provide DNA quantification estimates of high precision, robustness and reliability. These methods allow reliable estimations of relative expression ratio of two-fold or higher, and our analysis provides an estimation of the number of biological samples that have to be analyzed to achieve a given precision.

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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This report is the final product of a two-year study that began October 1, 2013. In addition to the funding provided for this study by the Iowa Highway Research Board and the Iowa Department of Transportation (TR-669), the project was also funded by the U.S. Army Corps of Engineers and the U.S. Geological Survey. The report was published as an online report on January 4, 2016. The report is available online at http://dx.doi.org/10.3133/ofr20151214 . The main body of the report provides a description of the statistics presented for the streamgages and an explanation of the streamgage summaries, also included is a discussion of the USGS streamgage network in Iowa. Individual streamgage summaries are available as links listed in table 1, or all 184 streamgage summaries are available in a zipped file named “Streamgage Summaries.”

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This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

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A-1 - Monthly Public Assistance Statistical Report Family Investment Program

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Methods used to analyze one type of nonstationary stochastic processes?the periodically correlated process?are considered. Two methods of one-step-forward prediction of periodically correlated time series are examined. One-step-forward predictions made in accordance with an autoregression model and a model of an artificial neural network with one latent neuron layer and with an adaptation mechanism of network parameters in a moving time window were compared in terms of efficiency. The comparison showed that, in the case of prediction for one time step for time series of mean monthly water discharge, the simpler autoregression model is more efficient.

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BACKGROUND: Mortality among HIV-infected persons is decreasing, and causes of death are changing. Classification of deaths is hampered because of low autopsy rates, frequent deaths outside of hospitals, and shortcomings of International Statistical Classification of Diseases and Related Health Problems (ICD-10) coding. METHODS: We studied mortality among Swiss HIV Cohort Study (SHCS) participants (1988-2010) and causes of death using the Coding Causes of Death in HIV (CoDe) protocol (2005-2009). Furthermore, we linked the SHCS data to the Swiss National Cohort (SNC) cause of death registry. RESULTS: AIDS-related mortality peaked in 1992 [11.0/100 person-years (PY)] and decreased to 0.144/100 PY (2006); non-AIDS-related mortality ranged between 1.74 (1993) and 0.776/100 PY (2006); mortality of unknown cause ranged between 2.33 and 0.206/100 PY. From 2005 to 2009, 459 of 9053 participants (5.1%) died. Underlying causes of deaths were: non-AIDS malignancies [total, 85 (19%) of 446 deceased persons with known hepatitis C virus (HCV) status; HCV-negative persons, 59 (24%); HCV-coinfected persons, 26 (13%)]; AIDS [73 (16%); 50 (21%); 23 (11%)]; liver failure [67 (15%); 12 (5%); 55 (27%)]; non-AIDS infections [42 (9%); 13 (5%); 29 (14%)]; substance use [31 (7%); 9 (4%); 22 (11%)]; suicide [28 (6%); 17 (7%), 11 (6%)]; myocardial infarction [28 (6%); 24 (10%), 4 (2%)]. Characteristics of deceased persons differed in 2005 vs. 2009: median age (45 vs. 49 years, respectively); median CD4 count (257 vs. 321 cells/μL, respectively); the percentage of individuals who were antiretroviral therapy-naïve (13 vs. 5%, respectively); the percentage of deaths that were AIDS-related (23 vs. 9%, respectively); and the percentage of deaths from non-AIDS-related malignancies (13 vs. 24%, respectively). Concordance in the classification of deaths was 72% between CoDe and ICD-10 coding in the SHCS; and 60% between the SHCS and the SNC registry. CONCLUSIONS: Mortality in HIV-positive persons decreased to 1.33/100 PY in 2010. Hepatitis B or C virus coinfections increased the risk of death. Between 2005 and 2009, 84% of deaths were non-AIDS-related. Causes of deaths varied according to data source and coding system.

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We describe a series of experiments in which we start with English to French and English to Japanese versions of an Open Source rule-based speech translation system for a medical domain, and bootstrap correspondign statistical systems. Comparative evaluation reveals that the rule-based systems are still significantly better than the statistical ones, despite the fact that considerable effort has been invested in tuning both the recognition and translation components; also, a hybrid system only marginally improved recall at the cost of a los in precision. The result suggests that rule-based architectures may still be preferable to statistical ones for safety-critical speech translation tasks.

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A general criterion for the design of adaptive systemsin digital communications called the statistical reference criterionis proposed. The criterion is based on imposition of the probabilitydensity function of the signal of interest at the outputof the adaptive system, with its application to the scenario ofhighly powerful interferers being the main focus of this paper.The knowledge of the pdf of the wanted signal is used as adiscriminator between signals so that interferers with differingdistributions are rejected by the algorithm. Its performance isstudied over a range of scenarios. Equations for gradient-basedcoefficient updates are derived, and the relationship with otherexisting algorithms like the minimum variance and the Wienercriterion are examined.

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The general objective of this study was to conduct astatistical analysis on the variation of the weld profiles and their influence on the fatigue strength of the joint. Weld quality with respect to its fatigue strength is of importance which is the main concept behind this thesis. The intention of this study was to establish the influence of weld geometric parameters on the weld quality and fatigue strength. The effect of local geometrical variations of non-load carrying cruciform fillet welded joint under tensile loading wasstudied in this thesis work. Linear Elastic Fracture Mechanics was used to calculate fatigue strength of the cruciform fillet welded joints in as-welded condition and under cyclic tensile loading, for a range of weld geometries. With extreme value statistical analysis and LEFM, an attempt was made to relate the variation of the cruciform weld profiles such as weld angle and weld toe radius to respective FAT classes.

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A maximum entropy statistical treatment of an inverse problem concerning frame theory is presented. The problem arises from the fact that a frame is an overcomplete set of vectors that defines a mapping with no unique inverse. Although any vector in the concomitant space can be expressed as a linear combination of frame elements, the coefficients of the expansion are not unique. Frame theory guarantees the existence of a set of coefficients which is “optimal” in a minimum norm sense. We show here that these coefficients are also “optimal” from a maximum entropy viewpoint.

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To enable a mathematically and physically sound execution of the fatigue test and a correct interpretation of its results, statistical evaluation methods are used to assist in the analysis of fatigue testing data. The main objective of this work is to develop step-by-stepinstructions for statistical analysis of the laboratory fatigue data. The scopeof this project is to provide practical cases about answering the several questions raised in the treatment of test data with application of the methods and formulae in the document IIW-XIII-2138-06 (Best Practice Guide on the Statistical Analysis of Fatigue Data). Generally, the questions in the data sheets involve some aspects: estimation of necessary sample size, verification of the statistical equivalence of the collated sets of data, and determination of characteristic curves in different cases. The series of comprehensive examples which are given in this thesis serve as a demonstration of the various statistical methods to develop a sound procedure to create reliable calculation rules for the fatigue analysis.