Sample records for statistical methods employed
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Statistical methods in personality assessment research.
Schinka, J A; LaLone, L; Broeckel, J A
1997-06-01
Emerging models of personality structure and advances in the measurement of personality and psychopathology suggest that research in personality and personality assessment has entered a stage of advanced development, in this article we examine whether researchers in these areas have taken advantage of new and evolving statistical procedures. We conducted a review of articles published in the Journal of Personality, Assessment during the past 5 years. Of the 449 articles that included some form of data analysis, 12.7% used only descriptive statistics, most employed only univariate statistics, and fewer than 10% used multivariate methods of data analysis. We discuss the cost of using limited statistical methods, the possible reasons for the apparent reluctance to employ advanced statistical procedures, and potential solutions to this technical shortcoming.
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Trends in study design and the statistical methods employed in a leading general medicine journal.
Gosho, M; Sato, Y; Nagashima, K; Takahashi, S
2018-02-01
Study design and statistical methods have become core components of medical research, and the methodology has become more multifaceted and complicated over time. The study of the comprehensive details and current trends of study design and statistical methods is required to support the future implementation of well-planned clinical studies providing information about evidence-based medicine. Our purpose was to illustrate study design and statistical methods employed in recent medical literature. This was an extension study of Sato et al. (N Engl J Med 2017; 376: 1086-1087), which reviewed 238 articles published in 2015 in the New England Journal of Medicine (NEJM) and briefly summarized the statistical methods employed in NEJM. Using the same database, we performed a new investigation of the detailed trends in study design and individual statistical methods that were not reported in the Sato study. Due to the CONSORT statement, prespecification and justification of sample size are obligatory in planning intervention studies. Although standard survival methods (eg Kaplan-Meier estimator and Cox regression model) were most frequently applied, the Gray test and Fine-Gray proportional hazard model for considering competing risks were sometimes used for a more valid statistical inference. With respect to handling missing data, model-based methods, which are valid for missing-at-random data, were more frequently used than single imputation methods. These methods are not recommended as a primary analysis, but they have been applied in many clinical trials. Group sequential design with interim analyses was one of the standard designs, and novel design, such as adaptive dose selection and sample size re-estimation, was sometimes employed in NEJM. Model-based approaches for handling missing data should replace single imputation methods for primary analysis in the light of the information found in some publications. Use of adaptive design with interim analyses is increasing after the presentation of the FDA guidance for adaptive design. © 2017 John Wiley & Sons Ltd.
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Recent statistical methods for orientation data
NASA Technical Reports Server (NTRS)
Batschelet, E.
1972-01-01
The application of statistical methods for determining the areas of animal orientation and navigation are discussed. The method employed is limited to the two-dimensional case. Various tests for determining the validity of the statistical analysis are presented. Mathematical models are included to support the theoretical considerations and tables of data are developed to show the value of information obtained by statistical analysis.
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ERIC Educational Resources Information Center
Lovett, Jennifer Nickell
2016-01-01
The purpose of this study is to provide researchers, mathematics educators, and statistics educators information about the current state of preservice secondary mathematics teachers' preparedness to teach statistics. To do so, this study employed an explanatory mixed methods design to quantitatively examine the statistical knowledge and statistics…
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ERIC Educational Resources Information Center
Karadag, Engin
2010-01-01
To assess research methods and analysis of statistical techniques employed by educational researchers, this study surveyed unpublished doctoral dissertation from 2003 to 2007. Frequently used research methods consisted of experimental research; a survey; a correlational study; and a case study. Descriptive statistics, t-test, ANOVA, factor…
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Køppe, Simo; Dammeyer, Jesper
2014-09-01
The evolution of developmental psychology has been characterized by the use of different quantitative and qualitative methods and procedures. But how does the use of methods and procedures change over time? This study explores the change and development of statistical methods used in articles published in Child Development from 1930 to 2010. The methods used in every article in the first issue of every volume were categorized into four categories. Until 1980 relatively simple statistical methods were used. During the last 30 years there has been an explosive use of more advanced statistical methods employed. The absence of statistical methods or use of simple methods had been eliminated.
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Machine Learning Methods for Attack Detection in the Smart Grid.
Ozay, Mete; Esnaola, Inaki; Yarman Vural, Fatos Tunay; Kulkarni, Sanjeev R; Poor, H Vincent
2016-08-01
Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used to classify measurements as being either secure or attacked. An attack detection framework is provided to exploit any available prior knowledge about the system and surmount constraints arising from the sparse structure of the problem in the proposed approach. Well-known batch and online learning algorithms (supervised and semisupervised) are employed with decision- and feature-level fusion to model the attack detection problem. The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods. The proposed algorithms are examined on various IEEE test systems. Experimental analyses show that machine learning algorithms can detect attacks with performances higher than attack detection algorithms that employ state vector estimation methods in the proposed attack detection framework.
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Task-based data-acquisition optimization for sparse image reconstruction systems
NASA Astrophysics Data System (ADS)
Chen, Yujia; Lou, Yang; Kupinski, Matthew A.; Anastasio, Mark A.
2017-03-01
Conventional wisdom dictates that imaging hardware should be optimized by use of an ideal observer (IO) that exploits full statistical knowledge of the class of objects to be imaged, without consideration of the reconstruction method to be employed. However, accurate and tractable models of the complete object statistics are often difficult to determine in practice. Moreover, in imaging systems that employ compressive sensing concepts, imaging hardware and (sparse) image reconstruction are innately coupled technologies. We have previously proposed a sparsity-driven ideal observer (SDIO) that can be employed to optimize hardware by use of a stochastic object model that describes object sparsity. The SDIO and sparse reconstruction method can therefore be "matched" in the sense that they both utilize the same statistical information regarding the class of objects to be imaged. To efficiently compute SDIO performance, the posterior distribution is estimated by use of computational tools developed recently for variational Bayesian inference. Subsequently, the SDIO test statistic can be computed semi-analytically. The advantages of employing the SDIO instead of a Hotelling observer are systematically demonstrated in case studies in which magnetic resonance imaging (MRI) data acquisition schemes are optimized for signal detection tasks.
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Optimization of Microphone Locations for Acoustic Liner Impedance Eduction
NASA Technical Reports Server (NTRS)
Jones, M. G.; Watson, W. R.; June, J. C.
2015-01-01
Two impedance eduction methods are explored for use with data acquired in the NASA Langley Grazing Flow Impedance Tube. The first is an indirect method based on the convected Helmholtz equation, and the second is a direct method based on the Kumaresan and Tufts algorithm. Synthesized no-flow data, with random jitter to represent measurement error, are used to evaluate a number of possible microphone locations. Statistical approaches are used to evaluate the suitability of each set of microphone locations. Given the computational resources required, small sample statistics are employed for the indirect method. Since the direct method is much less computationally intensive, a Monte Carlo approach is employed to gather its statistics. A comparison of results achieved with full and reduced sets of microphone locations is used to determine which sets of microphone locations are acceptable. For the indirect method, each array that includes microphones in all three regions (upstream and downstream hard wall sections, and liner test section) provides acceptable results, even when as few as eight microphones are employed. The best arrays employ microphones well away from the leading and trailing edges of the liner. The direct method is constrained to use microphones opposite the liner. Although a number of arrays are acceptable, the optimum set employs 14 microphones positioned well away from the leading and trailing edges of the liner. The selected sets of microphone locations are also evaluated with data measured for ceramic tubular and perforate-over-honeycomb liners at three flow conditions (Mach 0.0, 0.3, and 0.5). They compare favorably with results attained using all 53 microphone locations. Although different optimum microphone locations are selected for the two impedance eduction methods, there is significant overlap. Thus, the union of these two microphone arrays is preferred, as it supports usage of both methods. This array contains 3 microphones in the upstream hard wall section, 14 microphones opposite the liner, and 3 microphones in the downstream hard wall section.
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Cooperative Learning in Virtual Environments: The Jigsaw Method in Statistical Courses
ERIC Educational Resources Information Center
Vargas-Vargas, Manuel; Mondejar-Jimenez, Jose; Santamaria, Maria-Letica Meseguer; Alfaro-Navarro, Jose-Luis; Fernandez-Aviles, Gema
2011-01-01
This document sets out a novel teaching methodology as used in subjects with statistical content, traditionally regarded by students as "difficult". In a virtual learning environment, instructional techniques little used in mathematical courses were employed, such as the Jigsaw cooperative learning method, which had to be adapted to the…
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ERIC Educational Resources Information Center
National Centre for Vocational Education Research (NCVER), 2017
2017-01-01
This publication presents information on employers' use and views of the vocational education and training (VET) system. The findings relate to the various ways in which Australian employers use the VET system and unaccredited training to meet their skill needs, and their satisfaction with these methods of training. Australian employers can engage…
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NASA Technical Reports Server (NTRS)
Goldhirsh, J.
1982-01-01
The first absolute rain fade distribution method described establishes absolute fade statistics at a given site by means of a sampled radar data base. The second method extrapolates absolute fade statistics from one location to another, given simultaneously measured fade and rain rate statistics at the former. Both methods employ similar conditional fade statistic concepts and long term rain rate distributions. Probability deviations in the 2-19% range, with an 11% average, were obtained upon comparison of measured and predicted levels at given attenuations. The extrapolation of fade distributions to other locations at 28 GHz showed very good agreement with measured data at three sites located in the continental temperate region.
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Peer-Assisted Learning in Research Methods and Statistics
ERIC Educational Resources Information Center
Stone, Anna; Meade, Claire; Watling, Rosamond
2012-01-01
Feedback from students on a Level 1 Research Methods and Statistics module, studied as a core part of a BSc Psychology programme, highlighted demand for additional tutorials to help them to understand basic concepts. Students in their final year of study commonly request work experience to enhance their employability. All students on the Level 1…
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Lam, Lun Tak; Sun, Yi; Davey, Neil; Adams, Rod; Prapopoulou, Maria; Brown, Marc B; Moss, Gary P
2010-06-01
The aim was to employ Gaussian processes to assess mathematically the nature of a skin permeability dataset and to employ these methods, particularly feature selection, to determine the key physicochemical descriptors which exert the most significant influence on percutaneous absorption, and to compare such models with established existing models. Gaussian processes, including automatic relevance detection (GPRARD) methods, were employed to develop models of percutaneous absorption that identified key physicochemical descriptors of percutaneous absorption. Using MatLab software, the statistical performance of these models was compared with single linear networks (SLN) and quantitative structure-permeability relationships (QSPRs). Feature selection methods were used to examine in more detail the physicochemical parameters used in this study. A range of statistical measures to determine model quality were used. The inherently nonlinear nature of the skin data set was confirmed. The Gaussian process regression (GPR) methods yielded predictive models that offered statistically significant improvements over SLN and QSPR models with regard to predictivity (where the rank order was: GPR > SLN > QSPR). Feature selection analysis determined that the best GPR models were those that contained log P, melting point and the number of hydrogen bond donor groups as significant descriptors. Further statistical analysis also found that great synergy existed between certain parameters. It suggested that a number of the descriptors employed were effectively interchangeable, thus questioning the use of models where discrete variables are output, usually in the form of an equation. The use of a nonlinear GPR method produced models with significantly improved predictivity, compared with SLN or QSPR models. Feature selection methods were able to provide important mechanistic information. However, it was also shown that significant synergy existed between certain parameters, and as such it was possible to interchange certain descriptors (i.e. molecular weight and melting point) without incurring a loss of model quality. Such synergy suggested that a model constructed from discrete terms in an equation may not be the most appropriate way of representing mechanistic understandings of skin absorption.
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Statistics and Title VII Proof: Prima Facie Case and Rebuttal.
ERIC Educational Resources Information Center
Whitten, David
1978-01-01
The method and means by which statistics can raise a prima facie case of Title VII violation are analyzed. A standard is identified that can be applied to determine whether a statistical disparity is sufficient to shift the burden to the employer to rebut a prima facie case of discrimination. (LBH)
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ERIC Educational Resources Information Center
Zorn, Klaus
1973-01-01
Discussion of statistical apparatus employed in L. Doncheva-Mareva's article on the wide-spread usage of the present and future tense forms with future meaning in German letters, Deutsch als Fremdsprache, n1 1971. (RS)
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Gis-Based Spatial Statistical Analysis of College Graduates Employment
NASA Astrophysics Data System (ADS)
Tang, R.
2012-07-01
It is urgently necessary to be aware of the distribution and employment status of college graduates for proper allocation of human resources and overall arrangement of strategic industry. This study provides empirical evidence regarding the use of geocoding and spatial analysis in distribution and employment status of college graduates based on the data from 2004-2008 Wuhan Municipal Human Resources and Social Security Bureau, China. Spatio-temporal distribution of employment unit were analyzed with geocoding using ArcGIS software, and the stepwise multiple linear regression method via SPSS software was used to predict the employment and to identify spatially associated enterprise and professionals demand in the future. The results show that the enterprises in Wuhan east lake high and new technology development zone increased dramatically from 2004 to 2008, and tended to distributed southeastward. Furthermore, the models built by statistical analysis suggest that the specialty of graduates major in has an important impact on the number of the employment and the number of graduates engaging in pillar industries. In conclusion, the combination of GIS and statistical analysis which helps to simulate the spatial distribution of the employment status is a potential tool for human resource development research.
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Redshift data and statistical inference
NASA Technical Reports Server (NTRS)
Newman, William I.; Haynes, Martha P.; Terzian, Yervant
1994-01-01
Frequency histograms and the 'power spectrum analysis' (PSA) method, the latter developed by Yu & Peebles (1969), have been widely employed as techniques for establishing the existence of periodicities. We provide a formal analysis of these two classes of methods, including controlled numerical experiments, to better understand their proper use and application. In particular, we note that typical published applications of frequency histograms commonly employ far greater numbers of class intervals or bins than is advisable by statistical theory sometimes giving rise to the appearance of spurious patterns. The PSA method generates a sequence of random numbers from observational data which, it is claimed, is exponentially distributed with unit mean and variance, essentially independent of the distribution of the original data. We show that the derived random processes is nonstationary and produces a small but systematic bias in the usual estimate of the mean and variance. Although the derived variable may be reasonably described by an exponential distribution, the tail of the distribution is far removed from that of an exponential, thereby rendering statistical inference and confidence testing based on the tail of the distribution completely unreliable. Finally, we examine a number of astronomical examples wherein these methods have been used giving rise to widespread acceptance of statistically unconfirmed conclusions.
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Monitoring of an antigen manufacturing process.
Zavatti, Vanessa; Budman, Hector; Legge, Raymond; Tamer, Melih
2016-06-01
Fluorescence spectroscopy in combination with multivariate statistical methods was employed as a tool for monitoring the manufacturing process of pertactin (PRN), one of the virulence factors of Bordetella pertussis utilized in whopping cough vaccines. Fluorophores such as amino acids and co-enzymes were detected throughout the process. The fluorescence data collected at different stages of the fermentation and purification process were treated employing principal component analysis (PCA). Through PCA, it was feasible to identify sources of variability in PRN production. Then, partial least square (PLS) was employed to correlate the fluorescence spectra obtained from pure PRN samples and the final protein content measured by a Kjeldahl test from these samples. In view that a statistically significant correlation was found between fluorescence and PRN levels, this approach could be further used as a method to predict the final protein content.
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An overview of the mathematical and statistical analysis component of RICIS
NASA Technical Reports Server (NTRS)
Hallum, Cecil R.
1987-01-01
Mathematical and statistical analysis components of RICIS (Research Institute for Computing and Information Systems) can be used in the following problem areas: (1) quantification and measurement of software reliability; (2) assessment of changes in software reliability over time (reliability growth); (3) analysis of software-failure data; and (4) decision logic for whether to continue or stop testing software. Other areas of interest to NASA/JSC where mathematical and statistical analysis can be successfully employed include: math modeling of physical systems, simulation, statistical data reduction, evaluation methods, optimization, algorithm development, and mathematical methods in signal processing.
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Descriptive and inferential statistical methods used in burns research.
Al-Benna, Sammy; Al-Ajam, Yazan; Way, Benjamin; Steinstraesser, Lars
2010-05-01
Burns research articles utilise a variety of descriptive and inferential methods to present and analyse data. The aim of this study was to determine the descriptive methods (e.g. mean, median, SD, range, etc.) and survey the use of inferential methods (statistical tests) used in articles in the journal Burns. This study defined its population as all original articles published in the journal Burns in 2007. Letters to the editor, brief reports, reviews, and case reports were excluded. Study characteristics, use of descriptive statistics and the number and types of statistical methods employed were evaluated. Of the 51 articles analysed, 11(22%) were randomised controlled trials, 18(35%) were cohort studies, 11(22%) were case control studies and 11(22%) were case series. The study design and objectives were defined in all articles. All articles made use of continuous and descriptive data. Inferential statistics were used in 49(96%) articles. Data dispersion was calculated by standard deviation in 30(59%). Standard error of the mean was quoted in 19(37%). The statistical software product was named in 33(65%). Of the 49 articles that used inferential statistics, the tests were named in 47(96%). The 6 most common tests used (Student's t-test (53%), analysis of variance/co-variance (33%), chi(2) test (27%), Wilcoxon & Mann-Whitney tests (22%), Fisher's exact test (12%)) accounted for the majority (72%) of statistical methods employed. A specified significance level was named in 43(88%) and the exact significance levels were reported in 28(57%). Descriptive analysis and basic statistical techniques account for most of the statistical tests reported. This information should prove useful in deciding which tests should be emphasised in educating burn care professionals. These results highlight the need for burn care professionals to have a sound understanding of basic statistics, which is crucial in interpreting and reporting data. Advice should be sought from professionals in the fields of biostatistics and epidemiology when using more advanced statistical techniques. Copyright 2009 Elsevier Ltd and ISBI. All rights reserved.
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Lee, L.; Helsel, D.
2007-01-01
Analysis of low concentrations of trace contaminants in environmental media often results in left-censored data that are below some limit of analytical precision. Interpretation of values becomes complicated when there are multiple detection limits in the data-perhaps as a result of changing analytical precision over time. Parametric and semi-parametric methods, such as maximum likelihood estimation and robust regression on order statistics, can be employed to model distributions of multiply censored data and provide estimates of summary statistics. However, these methods are based on assumptions about the underlying distribution of data. Nonparametric methods provide an alternative that does not require such assumptions. A standard nonparametric method for estimating summary statistics of multiply-censored data is the Kaplan-Meier (K-M) method. This method has seen widespread usage in the medical sciences within a general framework termed "survival analysis" where it is employed with right-censored time-to-failure data. However, K-M methods are equally valid for the left-censored data common in the geosciences. Our S-language software provides an analytical framework based on K-M methods that is tailored to the needs of the earth and environmental sciences community. This includes routines for the generation of empirical cumulative distribution functions, prediction or exceedance probabilities, and related confidence limits computation. Additionally, our software contains K-M-based routines for nonparametric hypothesis testing among an unlimited number of grouping variables. A primary characteristic of K-M methods is that they do not perform extrapolation and interpolation. Thus, these routines cannot be used to model statistics beyond the observed data range or when linear interpolation is desired. For such applications, the aforementioned parametric and semi-parametric methods must be used.
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Kimko, Holly; Berry, Seth; O'Kelly, Michael; Mehrotra, Nitin; Hutmacher, Matthew; Sethuraman, Venkat
2017-01-01
The application of modeling and simulation (M&S) methods to improve decision-making was discussed during the Trends & Innovations in Clinical Trial Statistics Conference held in Durham, North Carolina, USA on May 1-4, 2016. Uses of both pharmacometric and statistical M&S were presented during the conference, highlighting the diversity of the methods employed by pharmacometricians and statisticians to address a broad range of quantitative issues in drug development. Five presentations are summarized herein, which cover the development strategy of employing M&S to drive decision-making; European initiatives on best practice in M&S; case studies of pharmacokinetic/pharmacodynamics modeling in regulatory decisions; estimation of exposure-response relationships in the presence of confounding; and the utility of estimating the probability of a correct decision for dose selection when prior information is limited. While M&S has been widely used during the last few decades, it is expected to play an essential role as more quantitative assessments are employed in the decision-making process. By integrating M&S as a tool to compile the totality of evidence collected throughout the drug development program, more informed decisions will be made.
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Two Paradoxes in Linear Regression Analysis.
Feng, Ge; Peng, Jing; Tu, Dongke; Zheng, Julia Z; Feng, Changyong
2016-12-25
Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection.
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Weather related continuity and completeness on Deep Space Ka-band links: statistics and forecasting
NASA Technical Reports Server (NTRS)
Shambayati, Shervin
2006-01-01
In this paper the concept of link 'stability' as means of measuring the continuity of the link is introduced and through it, along with the distributions of 'good' periods and 'bad' periods, the performance of the proposed Ka-band link design method using both forecasting and long-term statistics has been analyzed. The results indicate that the proposed link design method has relatively good continuity and completeness characteristics even when only long-term statistics are used and that the continuity performance further improves when forecasting is employed. .
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A new statistical method for design and analyses of component tolerance
NASA Astrophysics Data System (ADS)
Movahedi, Mohammad Mehdi; Khounsiavash, Mohsen; Otadi, Mahmood; Mosleh, Maryam
2017-03-01
Tolerancing conducted by design engineers to meet customers' needs is a prerequisite for producing high-quality products. Engineers use handbooks to conduct tolerancing. While use of statistical methods for tolerancing is not something new, engineers often use known distributions, including the normal distribution. Yet, if the statistical distribution of the given variable is unknown, a new statistical method will be employed to design tolerance. In this paper, we use generalized lambda distribution for design and analyses component tolerance. We use percentile method (PM) to estimate the distribution parameters. The findings indicated that, when the distribution of the component data is unknown, the proposed method can be used to expedite the design of component tolerance. Moreover, in the case of assembled sets, more extensive tolerance for each component with the same target performance can be utilized.
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ERIC Educational Resources Information Center
General Accounting Office, Washington, DC. Div. of Human Resources.
A study examined local U.S. Employment Service (ES) office placement performance and the role of the U.S. Department of Labor (DOL) in guiding and monitoring state and local ES program performance. Regression and other statistical methods were used to analyze state and local program performance based on the following: placement data for…
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Two Paradoxes in Linear Regression Analysis
FENG, Ge; PENG, Jing; TU, Dongke; ZHENG, Julia Z.; FENG, Changyong
2016-01-01
Summary Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection. PMID:28638214
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Simultaneous ocular and muscle artifact removal from EEG data by exploiting diverse statistics.
Chen, Xun; Liu, Aiping; Chen, Qiang; Liu, Yu; Zou, Liang; McKeown, Martin J
2017-09-01
Electroencephalography (EEG) recordings are frequently contaminated by both ocular and muscle artifacts. These are normally dealt with separately, by employing blind source separation (BSS) techniques relying on either second-order or higher-order statistics (SOS & HOS respectively). When HOS-based methods are used, it is usually in the setting of assuming artifacts are statistically independent to the EEG. When SOS-based methods are used, it is assumed that artifacts have autocorrelation characteristics distinct from the EEG. In reality, ocular and muscle artifacts do not completely follow the assumptions of strict temporal independence to the EEG nor completely unique autocorrelation characteristics, suggesting that exploiting HOS or SOS alone may be insufficient to remove these artifacts. Here we employ a novel BSS technique, independent vector analysis (IVA), to jointly employ HOS and SOS simultaneously to remove ocular and muscle artifacts. Numerical simulations and application to real EEG recordings were used to explore the utility of the IVA approach. IVA was superior in isolating both ocular and muscle artifacts, especially for raw EEG data with low signal-to-noise ratio, and also integrated usually separate SOS and HOS steps into a single unified step. Copyright © 2017 Elsevier Ltd. All rights reserved.
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[Research & development on computer expert system for forensic bones estimation].
Zhao, Jun-ji; Zhang, Jan-zheng; Liu, Nin-guo
2005-08-01
To build an expert system for forensic bones estimation. By using the object oriented method, employing statistical data of forensic anthropology, combining the statistical data frame knowledge representation with productions and also using the fuzzy matching and DS evidence theory method. Software for forensic estimation of sex, age and height with opened knowledge base was designed. This system is reliable and effective, and it would be a good assistant of the forensic technician.
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ERIC Educational Resources Information Center
Ramseyer, Gary C.; Tcheng, Tse-Kia
The present study was directed at determining the extent to which the Type I Error rate is affected by violations in the basic assumptions of the q statistic. Monte Carlo methods were employed, and a variety of departures from the assumptions were examined. (Author)
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A Complex Network Approach to Stylometry
Amancio, Diego Raphael
2015-01-01
Statistical methods have been widely employed to study the fundamental properties of language. In recent years, methods from complex and dynamical systems proved useful to create several language models. Despite the large amount of studies devoted to represent texts with physical models, only a limited number of studies have shown how the properties of the underlying physical systems can be employed to improve the performance of natural language processing tasks. In this paper, I address this problem by devising complex networks methods that are able to improve the performance of current statistical methods. Using a fuzzy classification strategy, I show that the topological properties extracted from texts complement the traditional textual description. In several cases, the performance obtained with hybrid approaches outperformed the results obtained when only traditional or networked methods were used. Because the proposed model is generic, the framework devised here could be straightforwardly used to study similar textual applications where the topology plays a pivotal role in the description of the interacting agents. PMID:26313921
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The Effect of General Statistical Fiber Misalignment on Predicted Damage Initiation in Composites
NASA Technical Reports Server (NTRS)
Bednarcyk, Brett A.; Aboudi, Jacob; Arnold, Steven M.
2014-01-01
A micromechanical method is employed for the prediction of unidirectional composites in which the fiber orientation can possess various statistical misalignment distributions. The method relies on the probability-weighted averaging of the appropriate concentration tensor, which is established by the micromechanical procedure. This approach provides access to the local field quantities throughout the constituents, from which initiation of damage in the composite can be predicted. In contrast, a typical macromechanical procedure can determine the effective composite elastic properties in the presence of statistical fiber misalignment, but cannot provide the local fields. Fully random fiber distribution is presented as a special case using the proposed micromechanical method. Results are given that illustrate the effects of various amounts of fiber misalignment in terms of the standard deviations of in-plane and out-of-plane misalignment angles, where normal distributions have been employed. Damage initiation envelopes, local fields, effective moduli, and strengths are predicted for polymer and ceramic matrix composites with given normal distributions of misalignment angles, as well as fully random fiber orientation.
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An adaptive approach to the dynamic allocation of buffer storage. M.S. Thesis
NASA Technical Reports Server (NTRS)
Crooke, S. C.
1970-01-01
Several strategies for the dynamic allocation of buffer storage are simulated and compared. The basic algorithms investigated, using actual statistics observed in the Univac 1108 EXEC 8 System, include the buddy method and the first-fit method. Modifications are made to the basic methods in an effort to improve and to measure allocation performance. A simulation model of an adaptive strategy is developed which permits interchanging the two different methods, the buddy and the first-fit methods with some modifications. Using an adaptive strategy, each method may be employed in the statistical environment in which its performance is superior to the other method.
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Analysis of Statistical Methods Currently used in Toxicology Journals
Na, Jihye; Yang, Hyeri
2014-01-01
Statistical methods are frequently used in toxicology, yet it is not clear whether the methods employed by the studies are used consistently and conducted based on sound statistical grounds. The purpose of this paper is to describe statistical methods used in top toxicology journals. More specifically, we sampled 30 papers published in 2014 from Toxicology and Applied Pharmacology, Archives of Toxicology, and Toxicological Science and described methodologies used to provide descriptive and inferential statistics. One hundred thirteen endpoints were observed in those 30 papers, and most studies had sample size less than 10, with the median and the mode being 6 and 3 & 6, respectively. Mean (105/113, 93%) was dominantly used to measure central tendency, and standard error of the mean (64/113, 57%) and standard deviation (39/113, 34%) were used to measure dispersion, while few studies provide justifications regarding why the methods being selected. Inferential statistics were frequently conducted (93/113, 82%), with one-way ANOVA being most popular (52/93, 56%), yet few studies conducted either normality or equal variance test. These results suggest that more consistent and appropriate use of statistical method is necessary which may enhance the role of toxicology in public health. PMID:25343012
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Analysis of Statistical Methods Currently used in Toxicology Journals.
Na, Jihye; Yang, Hyeri; Bae, SeungJin; Lim, Kyung-Min
2014-09-01
Statistical methods are frequently used in toxicology, yet it is not clear whether the methods employed by the studies are used consistently and conducted based on sound statistical grounds. The purpose of this paper is to describe statistical methods used in top toxicology journals. More specifically, we sampled 30 papers published in 2014 from Toxicology and Applied Pharmacology, Archives of Toxicology, and Toxicological Science and described methodologies used to provide descriptive and inferential statistics. One hundred thirteen endpoints were observed in those 30 papers, and most studies had sample size less than 10, with the median and the mode being 6 and 3 & 6, respectively. Mean (105/113, 93%) was dominantly used to measure central tendency, and standard error of the mean (64/113, 57%) and standard deviation (39/113, 34%) were used to measure dispersion, while few studies provide justifications regarding why the methods being selected. Inferential statistics were frequently conducted (93/113, 82%), with one-way ANOVA being most popular (52/93, 56%), yet few studies conducted either normality or equal variance test. These results suggest that more consistent and appropriate use of statistical method is necessary which may enhance the role of toxicology in public health.
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Comparison of Creativity and Self-Esteem in Students with Employed and Household Mothers
ERIC Educational Resources Information Center
Safara, Maryam; Alkaran, Zeinab Blori; Salmabadi, Mojtaba; Rostami, Najmieh
2017-01-01
Objective: The present study was carried out to compare creativity and self-esteem in the university students with employed and household mothers in academic years 2014-2015. Method: This research is a descriptive one which is of comparative-casual type. The statistical population includes all undergraduate students of Azad universities of…
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Misyura, Maksym; Sukhai, Mahadeo A; Kulasignam, Vathany; Zhang, Tong; Kamel-Reid, Suzanne; Stockley, Tracy L
2018-02-01
A standard approach in test evaluation is to compare results of the assay in validation to results from previously validated methods. For quantitative molecular diagnostic assays, comparison of test values is often performed using simple linear regression and the coefficient of determination (R 2 ), using R 2 as the primary metric of assay agreement. However, the use of R 2 alone does not adequately quantify constant or proportional errors required for optimal test evaluation. More extensive statistical approaches, such as Bland-Altman and expanded interpretation of linear regression methods, can be used to more thoroughly compare data from quantitative molecular assays. We present the application of Bland-Altman and linear regression statistical methods to evaluate quantitative outputs from next-generation sequencing assays (NGS). NGS-derived data sets from assay validation experiments were used to demonstrate the utility of the statistical methods. Both Bland-Altman and linear regression were able to detect the presence and magnitude of constant and proportional error in quantitative values of NGS data. Deming linear regression was used in the context of assay comparison studies, while simple linear regression was used to analyse serial dilution data. Bland-Altman statistical approach was also adapted to quantify assay accuracy, including constant and proportional errors, and precision where theoretical and empirical values were known. The complementary application of the statistical methods described in this manuscript enables more extensive evaluation of performance characteristics of quantitative molecular assays, prior to implementation in the clinical molecular laboratory. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
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Transport Coefficients from Large Deviation Functions
NASA Astrophysics Data System (ADS)
Gao, Chloe; Limmer, David
2017-10-01
We describe a method for computing transport coefficients from the direct evaluation of large deviation function. This method is general, relying on only equilibrium fluctuations, and is statistically efficient, employing trajectory based importance sampling. Equilibrium fluctuations of molecular currents are characterized by their large deviation functions, which is a scaled cumulant generating function analogous to the free energy. A diffusion Monte Carlo algorithm is used to evaluate the large deviation functions, from which arbitrary transport coefficients are derivable. We find significant statistical improvement over traditional Green-Kubo based calculations. The systematic and statistical errors of this method are analyzed in the context of specific transport coefficient calculations, including the shear viscosity, interfacial friction coefficient, and thermal conductivity.
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A Study on Predictive Analytics Application to Ship Machinery Maintenance
2013-09-01
Looking at the nature of the time series forecasting method , it would be better applied to offline analysis . The application for real- time online...other system attributes in future. Two techniques of statistical analysis , mainly time series models and cumulative sum control charts, are discussed in...statistical tool employed for the two techniques of statistical analysis . Both time series forecasting as well as CUSUM control charts are shown to be
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Employment status and heart disease risk factors in middle-aged women: the Rancho Bernardo Study.
Kritz-Silverstein, D; Wingard, D L; Barrett-Connor, E
1992-01-01
BACKGROUND. In recent years, an increasing number of women have been entering the labor force. It is known that in men, employment is related to heart disease risk, but there are few studies examining this association among women. METHODS. The relation between employment status and heart disease risk factors including lipid and lipoprotein levels, systolic and diastolic blood pressure, fasting and postchallenge plasma glucose and insulin levels, was examined in 242 women aged 40 to 59 years, who were participants in the Rancho Bernardo Heart and Chronic Disease Survey. At the time of a follow-up clinic visit between 1984 and 1987, 46.7% were employed, primarily in managerial positions. RESULTS. Employed women smoked fewer cigarettes, drank less alcohol, and exercised more than unemployed women, but these differences were not statistically significant. After adjustment for covariates, employed women had significantly lower total cholesterol and fasting plasma glucose levels than unemployed women. Differences on other biological variables, although not statistically significant, also favored the employed women. CONCLUSIONS. Results of this study suggest that middle-aged women employed in managerial positions are healthier than unemployed women. PMID:1739150
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Technical Notes on the Multifactor Method of Elementary School Closing.
ERIC Educational Resources Information Center
Puleo, Vincent T.
This report provides preliminary technical information on a method for analyzing the factors involved in the closing of elementary schools. Included is a presentation of data and a brief discussion bearing on descriptive statistics, reliability, and validity. An intercorrelation matrix is also examined. The method employs 9 factors that have a…
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Changing Patterns in Methods of Suicide by Race and Sex.
ERIC Educational Resources Information Center
McIntosh, John L.; Santos, John F.
1982-01-01
Examined annual official national statistics for specific methods of suicide by sex and racial group from 1923 to 1978. Shifts were found in suicide methods employed, most notably for women and Asian Americans. Generally, firearm use increased among nearly all ethnic/racial-sex groups while the use of poisons declined. (JAC)
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In-school service predictors of employment for individuals with intellectual disability.
Park, Jiyoon; Bouck, Emily
2018-06-01
Although there are many secondary data analyses of the National Longitudinal Transition Study-2 (NLTS-2) to investigate post-school outcome for students with disabilities, there has been a lack of research with in-school service predictors and post-school outcome for students with specific disability categories. This study was a secondary data analysis of NLTS-2 to investigate the relationship between current employment status and in-school services for individuals with intellectual disability. Statistical methods such as descriptive statistics and logistic regression were used to analyze NLTS-2 data set. The main findings included that in-school services were correlated with current employment status, and that primary disability (i.e., mild intellectual disability and moderate/severe intellectual disability) was associated with current employment status. In-school services are critical in predicting current employment for individuals with intellectual disability. Also, data suggest additional research is needed to investigate various in-school services and variables that could predict employment differences between individuals with mild and moderate/severe intellectual disability. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Blind image quality assessment based on aesthetic and statistical quality-aware features
NASA Astrophysics Data System (ADS)
Jenadeleh, Mohsen; Masaeli, Mohammad Masood; Moghaddam, Mohsen Ebrahimi
2017-07-01
The main goal of image quality assessment (IQA) methods is the emulation of human perceptual image quality judgments. Therefore, the correlation between objective scores of these methods with human perceptual scores is considered as their performance metric. Human judgment of the image quality implicitly includes many factors when assessing perceptual image qualities such as aesthetics, semantics, context, and various types of visual distortions. The main idea of this paper is to use a host of features that are commonly employed in image aesthetics assessment in order to improve blind image quality assessment (BIQA) methods accuracy. We propose an approach that enriches the features of BIQA methods by integrating a host of aesthetics image features with the features of natural image statistics derived from multiple domains. The proposed features have been used for augmenting five different state-of-the-art BIQA methods, which use statistical natural scene statistics features. Experiments were performed on seven benchmark image quality databases. The experimental results showed significant improvement of the accuracy of the methods.
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Yang, Hyeri; Na, Jihye; Jang, Won-Hee; Jung, Mi-Sook; Jeon, Jun-Young; Heo, Yong; Yeo, Kyung-Wook; Jo, Ji-Hoon; Lim, Kyung-Min; Bae, SeungJin
2015-05-05
Mouse local lymph node assay (LLNA, OECD TG429) is an alternative test replacing conventional guinea pig tests (OECD TG406) for the skin sensitization test but the use of a radioisotopic agent, (3)H-thymidine, deters its active dissemination. New non-radioisotopic LLNA, LLNA:BrdU-FCM employs a non-radioisotopic analog, 5-bromo-2'-deoxyuridine (BrdU) and flow cytometry. For an analogous method, OECD TG429 performance standard (PS) advises that two reference compounds be tested repeatedly and ECt(threshold) values obtained must fall within acceptable ranges to prove within- and between-laboratory reproducibility. However, this criteria is somewhat arbitrary and sample size of ECt is less than 5, raising concerns about insufficient reliability. Here, we explored various statistical methods to evaluate the reproducibility of LLNA:BrdU-FCM with stimulation index (SI), the raw data for ECt calculation, produced from 3 laboratories. Descriptive statistics along with graphical representation of SI was presented. For inferential statistics, parametric and non-parametric methods were applied to test the reproducibility of SI of a concurrent positive control and the robustness of results were investigated. Descriptive statistics and graphical representation of SI alone could illustrate the within- and between-laboratory reproducibility. Inferential statistics employing parametric and nonparametric methods drew similar conclusion. While all labs passed within- and between-laboratory reproducibility criteria given by OECD TG429 PS based on ECt values, statistical evaluation based on SI values showed that only two labs succeeded in achieving within-laboratory reproducibility. For those two labs that satisfied the within-lab reproducibility, between-laboratory reproducibility could be also attained based on inferential as well as descriptive statistics. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
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[Evaluation of using statistical methods in selected national medical journals].
Sych, Z
1996-01-01
The paper covers the performed evaluation of frequency with which the statistical methods were applied in analyzed works having been published in six selected, national medical journals in the years 1988-1992. For analysis the following journals were chosen, namely: Klinika Oczna, Medycyna Pracy, Pediatria Polska, Polski Tygodnik Lekarski, Roczniki Państwowego Zakładu Higieny, Zdrowie Publiczne. Appropriate number of works up to the average in the remaining medical journals was randomly selected from respective volumes of Pol. Tyg. Lek. The studies did not include works wherein the statistical analysis was not implemented, which referred both to national and international publications. That exemption was also extended to review papers, casuistic ones, reviews of books, handbooks, monographies, reports from scientific congresses, as well as papers on historical topics. The number of works was defined in each volume. Next, analysis was performed to establish the mode of finding out a suitable sample in respective studies, differentiating two categories: random and target selections. Attention was also paid to the presence of control sample in the individual works. In the analysis attention was also focussed on the existence of sample characteristics, setting up three categories: complete, partial and lacking. In evaluating the analyzed works an effort was made to present the results of studies in tables and figures (Tab. 1, 3). Analysis was accomplished with regard to the rate of employing statistical methods in analyzed works in relevant volumes of six selected, national medical journals for the years 1988-1992, simultaneously determining the number of works, in which no statistical methods were used. Concurrently the frequency of applying the individual statistical methods was analyzed in the scrutinized works. Prominence was given to fundamental statistical methods in the field of descriptive statistics (measures of position, measures of dispersion) as well as most important methods of mathematical statistics such as parametric tests of significance, analysis of variance (in single and dual classifications). non-parametric tests of significance, correlation and regression. The works, in which use was made of either multiple correlation or multiple regression or else more complex methods of studying the relationship for two or more numbers of variables, were incorporated into the works whose statistical methods were constituted by correlation and regression as well as other methods, e.g. statistical methods being used in epidemiology (coefficients of incidence and morbidity, standardization of coefficients, survival tables) factor analysis conducted by Jacobi-Hotellng's method, taxonomic methods and others. On the basis of the performed studies it has been established that the frequency of employing statistical methods in the six selected national, medical journals in the years 1988-1992 was 61.1-66.0% of the analyzed works (Tab. 3), and they generally were almost similar to the frequency provided in English language medical journals. On a whole, no significant differences were disclosed in the frequency of applied statistical methods (Tab. 4) as well as in frequency of random tests (Tab. 3) in the analyzed works, appearing in the medical journals in respective years 1988-1992. The most frequently used statistical methods in analyzed works for 1988-1992 were the measures of position 44.2-55.6% and measures of dispersion 32.5-38.5% as well as parametric tests of significance 26.3-33.1% of the works analyzed (Tab. 4). For the purpose of increasing the frequency and reliability of the used statistical methods, the didactics should be widened in the field of biostatistics at medical studies and postgraduation training designed for physicians and scientific-didactic workers.
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Investigation of Attitudinal Differences among Individuals of Different Employment Status
2010-10-28
be included in order to statistically control for common method variance (see Podsakoff , MacKenzie, Lee, & Podsakoff , 2003). Results Hypotheses 1...social identity theory. Social Psychology Quarterly, 58, 255-269. Podsakoff , P. M., MacKenzie, S. B., Lee, J., & Podsakoff , N. P. (2003). Common method
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On-chip generation of Einstein-Podolsky-Rosen states with arbitrary symmetry
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gräfe, Markus; Heilmann, René; Nolte, Stefan
We experimentally demonstrate a method for integrated-optical generation of two-photon Einstein-Podolsky-Rosen states featuring arbitrary symmetries. In our setting, we employ detuned directional couplers to impose a freely tailorable phase between the two modes of the state. Our results allow to mimic the quantum random walk statistics of bosons, fermions, and anyons, particles with fractional exchange statistics.
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Fuller, Daniel; Buote, Richard; Stanley, Kevin
2017-11-01
The volume and velocity of data are growing rapidly and big data analytics are being applied to these data in many fields. Population and public health researchers may be unfamiliar with the terminology and statistical methods used in big data. This creates a barrier to the application of big data analytics. The purpose of this glossary is to define terms used in big data and big data analytics and to contextualise these terms. We define the five Vs of big data and provide definitions and distinctions for data mining, machine learning and deep learning, among other terms. We provide key distinctions between big data and statistical analysis methods applied to big data. We contextualise the glossary by providing examples where big data analysis methods have been applied to population and public health research problems and provide brief guidance on how to learn big data analysis methods. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
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Karimi, Davood; Samei, Golnoosh; Kesch, Claudia; Nir, Guy; Salcudean, Septimiu E
2018-05-15
Most of the existing convolutional neural network (CNN)-based medical image segmentation methods are based on methods that have originally been developed for segmentation of natural images. Therefore, they largely ignore the differences between the two domains, such as the smaller degree of variability in the shape and appearance of the target volume and the smaller amounts of training data in medical applications. We propose a CNN-based method for prostate segmentation in MRI that employs statistical shape models to address these issues. Our CNN predicts the location of the prostate center and the parameters of the shape model, which determine the position of prostate surface keypoints. To train such a large model for segmentation of 3D images using small data (1) we adopt a stage-wise training strategy by first training the network to predict the prostate center and subsequently adding modules for predicting the parameters of the shape model and prostate rotation, (2) we propose a data augmentation method whereby the training images and their prostate surface keypoints are deformed according to the displacements computed based on the shape model, and (3) we employ various regularization techniques. Our proposed method achieves a Dice score of 0.88, which is obtained by using both elastic-net and spectral dropout for regularization. Compared with a standard CNN-based method, our method shows significantly better segmentation performance on the prostate base and apex. Our experiments also show that data augmentation using the shape model significantly improves the segmentation results. Prior knowledge about the shape of the target organ can improve the performance of CNN-based segmentation methods, especially where image features are not sufficient for a precise segmentation. Statistical shape models can also be employed to synthesize additional training data that can ease the training of large CNNs.
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ERIC Educational Resources Information Center
Pustejovsky, James E.; Runyon, Christopher
2014-01-01
Direct observation recording procedures produce reductive summary measurements of an underlying stream of behavior. Previous methodological studies of these recording procedures have employed simulation methods for generating random behavior streams, many of which amount to special cases of a statistical model known as the alternating renewal…
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ERIC Educational Resources Information Center
Konold, Timothy R.; Glutting, Joseph J.
2008-01-01
This study employed a correlated trait-correlated method application of confirmatory factor analysis to disentangle trait and method variance from measures of attention-deficit/hyperactivity disorder obtained at the college level. The two trait factors were "Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition" ("DSM-IV")…
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Methods of Suicide by Age: Sex and Race Differences among the Young and Old.
ERIC Educational Resources Information Center
McIntosh, John L.; Santos, John F.
1986-01-01
Annual official statistics for specific methods of suicide (firearms, hanging, poisons) by age for different sex and racial groups (Whites, Blacks, non-Whites excluding Black) were examined from 1960 to 1978. Comparisons among the age-sex-race groups, along with trends over time and differences in the methods employed, were noted. (Author/ABL)
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Zapater, E; Moreno, S; Fortea, M A; Campos, A; Armengot, M; Basterra, J
2000-11-01
Many studies have investigated prognostic factors in laryngeal carcinoma, with sometimes conflicting results. Apart from the importance of environmental factors, the different statistical methods employed may have influenced such discrepancies. A program based on artificial intelligence techniques is designed to determine the prognostic factors in a series of 122 laryngeal carcinomas. The results obtained are compared with those derived from two classical statistical methods (Cox regression and mortality tables). Tumor location was found to be the most important prognostic factor by all methods. The proposed intelligent system is found to be a sound method capable of detecting exceptional cases.
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Receiver Statistics for Cognitive Radios in Dynamic Spectrum Access Networks
2012-02-28
SNR) are employed by many protocols and processes in direct-sequence ( DS ) spread-spectrum packet radio networks, including soft-decision decoding...adaptive modulation protocols, and power adjustment protocols. For DS spread spectrum, we have introduced and evaluated SNR estimators that employ...obtained during demodulation in a binary CDMA receiver. We investigated several methods to apply the proposed metric to the demodulator’s soft-decision
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ToNER: A tool for identifying nucleotide enrichment signals in feature-enriched RNA-seq data.
Promworn, Yuttachon; Kaewprommal, Pavita; Shaw, Philip J; Intarapanich, Apichart; Tongsima, Sissades; Piriyapongsa, Jittima
2017-01-01
Biochemical methods are available for enriching 5' ends of RNAs in prokaryotes, which are employed in the differential RNA-seq (dRNA-seq) and the more recent Cappable-seq protocols. Computational methods are needed to locate RNA 5' ends from these data by statistical analysis of the enrichment. Although statistical-based analysis methods have been developed for dRNA-seq, they may not be suitable for Cappable-seq data. The more efficient enrichment method employed in Cappable-seq compared with dRNA-seq could affect data distribution and thus algorithm performance. We present Transformation of Nucleotide Enrichment Ratios (ToNER), a tool for statistical modeling of enrichment from RNA-seq data obtained from enriched and unenriched libraries. The tool calculates nucleotide enrichment scores and determines the global transformation for fitting to the normal distribution using the Box-Cox procedure. From the transformed distribution, sites of significant enrichment are identified. To increase power of detection, meta-analysis across experimental replicates is offered. We tested the tool on Cappable-seq and dRNA-seq data for identifying Escherichia coli transcript 5' ends and compared the results with those from the TSSAR tool, which is designed for analyzing dRNA-seq data. When combining results across Cappable-seq replicates, ToNER detects more known transcript 5' ends than TSSAR. In general, the transcript 5' ends detected by ToNER but not TSSAR occur in regions which cannot be locally modeled by TSSAR. ToNER uses a simple yet robust statistical modeling approach, which can be used for detecting RNA 5'ends from Cappable-seq data, in particular when combining information from experimental replicates. The ToNER tool could potentially be applied for analyzing other RNA-seq datasets in which enrichment for other structural features of RNA is employed. The program is freely available for download at ToNER webpage (http://www4a.biotec.or.th/GI/tools/toner) and GitHub repository (https://github.com/PavitaKae/ToNER).
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ERIC Educational Resources Information Center
Yung-Kuan, Chan; Hsieh, Ming-Yuan; Lee, Chin-Feng; Huang, Chih-Cheng; Ho, Li-Chih
2017-01-01
Under the hyper-dynamic education situation, this research, in order to comprehensively explore the interplays between Teacher Competence Demands (TCD) and Learning Organization Requests (LOR), cross-employs the data refined method of Descriptive Statistics (DS) method and Analysis of Variance (ANOVA) and Principal Components Analysis (PCA)…
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Unbiased estimation of oceanic mean rainfall from satellite borne radiometer measurements
NASA Technical Reports Server (NTRS)
Mittal, M. C.
1981-01-01
The statistical properties of the radar derived rainfall obtained during the GARP Atlantic Tropical Experiment (GATE) are used to derive quantitative estimates of the spatial and temporal sampling errors associated with estimating rainfall from brightness temperature measurements such as would be obtained from a satelliteborne microwave radiometer employing a practical size antenna aperture. A basis for a method of correcting the so called beam filling problem, i.e., for the effect of nonuniformity of rainfall over the radiometer beamwidth is provided. The method presented employs the statistical properties of the observations themselves without need for physical assumptions beyond those associated with the radiative transfer model. The simulation results presented offer a validation of the estimated accuracy that can be achieved and the graphs included permit evaluation of the effect of the antenna resolution on both the temporal and spatial sampling errors.
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Rapid analysis of pharmaceutical drugs using LIBS coupled with multivariate analysis.
Tiwari, P K; Awasthi, S; Kumar, R; Anand, R K; Rai, P K; Rai, A K
2018-02-01
Type 2 diabetes drug tablets containing voglibose having dose strengths of 0.2 and 0.3 mg of various brands have been examined, using laser-induced breakdown spectroscopy (LIBS) technique. The statistical methods such as the principal component analysis (PCA) and the partial least square regression analysis (PLSR) have been employed on LIBS spectral data for classifying and developing the calibration models of drug samples. We have developed the ratio-based calibration model applying PLSR in which relative spectral intensity ratios H/C, H/N and O/N are used. Further, the developed model has been employed to predict the relative concentration of element in unknown drug samples. The experiment has been performed in air and argon atmosphere, respectively, and the obtained results have been compared. The present model provides rapid spectroscopic method for drug analysis with high statistical significance for online control and measurement process in a wide variety of pharmaceutical industrial applications.
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Employing Sensitivity Derivatives for Robust Optimization under Uncertainty in CFD
NASA Technical Reports Server (NTRS)
Newman, Perry A.; Putko, Michele M.; Taylor, Arthur C., III
2004-01-01
A robust optimization is demonstrated on a two-dimensional inviscid airfoil problem in subsonic flow. Given uncertainties in statistically independent, random, normally distributed flow parameters (input variables), an approximate first-order statistical moment method is employed to represent the Computational Fluid Dynamics (CFD) code outputs as expected values with variances. These output quantities are used to form the objective function and constraints. The constraints are cast in probabilistic terms; that is, the probability that a constraint is satisfied is greater than or equal to some desired target probability. Gradient-based robust optimization of this stochastic problem is accomplished through use of both first and second-order sensitivity derivatives. For each robust optimization, the effect of increasing both input standard deviations and target probability of constraint satisfaction are demonstrated. This method provides a means for incorporating uncertainty when considering small deviations from input mean values.
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Accuracy Evaluation of the Unified P-Value from Combining Correlated P-Values
Alves, Gelio; Yu, Yi-Kuo
2014-01-01
Meta-analysis methods that combine -values into a single unified -value are frequently employed to improve confidence in hypothesis testing. An assumption made by most meta-analysis methods is that the -values to be combined are independent, which may not always be true. To investigate the accuracy of the unified -value from combining correlated -values, we have evaluated a family of statistical methods that combine: independent, weighted independent, correlated, and weighted correlated -values. Statistical accuracy evaluation by combining simulated correlated -values showed that correlation among -values can have a significant effect on the accuracy of the combined -value obtained. Among the statistical methods evaluated those that weight -values compute more accurate combined -values than those that do not. Also, statistical methods that utilize the correlation information have the best performance, producing significantly more accurate combined -values. In our study we have demonstrated that statistical methods that combine -values based on the assumption of independence can produce inaccurate -values when combining correlated -values, even when the -values are only weakly correlated. Therefore, to prevent from drawing false conclusions during hypothesis testing, our study advises caution be used when interpreting the -value obtained from combining -values of unknown correlation. However, when the correlation information is available, the weighting-capable statistical method, first introduced by Brown and recently modified by Hou, seems to perform the best amongst the methods investigated. PMID:24663491
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Bayesian Tracking of Emerging Epidemics Using Ensemble Optimal Statistical Interpolation
Cobb, Loren; Krishnamurthy, Ashok; Mandel, Jan; Beezley, Jonathan D.
2014-01-01
We present a preliminary test of the Ensemble Optimal Statistical Interpolation (EnOSI) method for the statistical tracking of an emerging epidemic, with a comparison to its popular relative for Bayesian data assimilation, the Ensemble Kalman Filter (EnKF). The spatial data for this test was generated by a spatial susceptible-infectious-removed (S-I-R) epidemic model of an airborne infectious disease. Both tracking methods in this test employed Poisson rather than Gaussian noise, so as to handle epidemic data more accurately. The EnOSI and EnKF tracking methods worked well on the main body of the simulated spatial epidemic, but the EnOSI was able to detect and track a distant secondary focus of infection that the EnKF missed entirely. PMID:25113590
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Robbins, L G
2000-01-01
Graduate school programs in genetics have become so full that courses in statistics have often been eliminated. In addition, typical introductory statistics courses for the "statistics user" rather than the nascent statistician are laden with methods for analysis of measured variables while genetic data are most often discrete numbers. These courses are often seen by students and genetics professors alike as largely irrelevant cookbook courses. The powerful methods of likelihood analysis, although commonly employed in human genetics, are much less often used in other areas of genetics, even though current computational tools make this approach readily accessible. This article introduces the MLIKELY.PAS computer program and the logic of do-it-yourself maximum-likelihood statistics. The program itself, course materials, and expanded discussions of some examples that are only summarized here are available at http://www.unisi. it/ricerca/dip/bio_evol/sitomlikely/mlikely.h tml. PMID:10628965
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Validation of chemistry models employed in a particle simulation method
NASA Technical Reports Server (NTRS)
Haas, Brian L.; Mcdonald, Jeffrey D.
1991-01-01
The chemistry models employed in a statistical particle simulation method, as implemented in the Intel iPSC/860 multiprocessor computer, are validated and applied. Chemical relaxation of five-species air in these reservoirs involves 34 simultaneous dissociation, recombination, and atomic-exchange reactions. The reaction rates employed in the analytic solutions are obtained from Arrhenius experimental correlations as functions of temperature for adiabatic gas reservoirs in thermal equilibrium. Favorable agreement with the analytic solutions validates the simulation when applied to relaxation of O2 toward equilibrium in reservoirs dominated by dissociation and recombination, respectively, and when applied to relaxation of air in the temperature range 5000 to 30,000 K. A flow of O2 over a circular cylinder at high Mach number is simulated to demonstrate application of the method to multidimensional reactive flows.
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Lee, L.; Helsel, D.
2005-01-01
Trace contaminants in water, including metals and organics, often are measured at sufficiently low concentrations to be reported only as values below the instrument detection limit. Interpretation of these "less thans" is complicated when multiple detection limits occur. Statistical methods for multiply censored, or multiple-detection limit, datasets have been developed for medical and industrial statistics, and can be employed to estimate summary statistics or model the distributions of trace-level environmental data. We describe S-language-based software tools that perform robust linear regression on order statistics (ROS). The ROS method has been evaluated as one of the most reliable procedures for developing summary statistics of multiply censored data. It is applicable to any dataset that has 0 to 80% of its values censored. These tools are a part of a software library, or add-on package, for the R environment for statistical computing. This library can be used to generate ROS models and associated summary statistics, plot modeled distributions, and predict exceedance probabilities of water-quality standards. ?? 2005 Elsevier Ltd. All rights reserved.
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Accelerated battery-life testing - A concept
NASA Technical Reports Server (NTRS)
Mccallum, J.; Thomas, R. E.
1971-01-01
Test program, employing empirical, statistical and physical methods, determines service life and failure probabilities of electrochemical cells and batteries, and is applicable to testing mechanical, electrical, and chemical devices. Data obtained aids long-term performance prediction of battery or cell.
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Jenkinson, Garrett; Abante, Jordi; Feinberg, Andrew P; Goutsias, John
2018-03-07
DNA methylation is a stable form of epigenetic memory used by cells to control gene expression. Whole genome bisulfite sequencing (WGBS) has emerged as a gold-standard experimental technique for studying DNA methylation by producing high resolution genome-wide methylation profiles. Statistical modeling and analysis is employed to computationally extract and quantify information from these profiles in an effort to identify regions of the genome that demonstrate crucial or aberrant epigenetic behavior. However, the performance of most currently available methods for methylation analysis is hampered by their inability to directly account for statistical dependencies between neighboring methylation sites, thus ignoring significant information available in WGBS reads. We present a powerful information-theoretic approach for genome-wide modeling and analysis of WGBS data based on the 1D Ising model of statistical physics. This approach takes into account correlations in methylation by utilizing a joint probability model that encapsulates all information available in WGBS methylation reads and produces accurate results even when applied on single WGBS samples with low coverage. Using the Shannon entropy, our approach provides a rigorous quantification of methylation stochasticity in individual WGBS samples genome-wide. Furthermore, it utilizes the Jensen-Shannon distance to evaluate differences in methylation distributions between a test and a reference sample. Differential performance assessment using simulated and real human lung normal/cancer data demonstrate a clear superiority of our approach over DSS, a recently proposed method for WGBS data analysis. Critically, these results demonstrate that marginal methods become statistically invalid when correlations are present in the data. This contribution demonstrates clear benefits and the necessity of modeling joint probability distributions of methylation using the 1D Ising model of statistical physics and of quantifying methylation stochasticity using concepts from information theory. By employing this methodology, substantial improvement of DNA methylation analysis can be achieved by effectively taking into account the massive amount of statistical information available in WGBS data, which is largely ignored by existing methods.
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Assessment of statistical methods used in library-based approaches to microbial source tracking.
Ritter, Kerry J; Carruthers, Ethan; Carson, C Andrew; Ellender, R D; Harwood, Valerie J; Kingsley, Kyle; Nakatsu, Cindy; Sadowsky, Michael; Shear, Brian; West, Brian; Whitlock, John E; Wiggins, Bruce A; Wilbur, Jayson D
2003-12-01
Several commonly used statistical methods for fingerprint identification in microbial source tracking (MST) were examined to assess the effectiveness of pattern-matching algorithms to correctly identify sources. Although numerous statistical methods have been employed for source identification, no widespread consensus exists as to which is most appropriate. A large-scale comparison of several MST methods, using identical fecal sources, presented a unique opportunity to assess the utility of several popular statistical methods. These included discriminant analysis, nearest neighbour analysis, maximum similarity and average similarity, along with several measures of distance or similarity. Threshold criteria for excluding uncertain or poorly matched isolates from final analysis were also examined for their ability to reduce false positives and increase prediction success. Six independent libraries used in the study were constructed from indicator bacteria isolated from fecal materials of humans, seagulls, cows and dogs. Three of these libraries were constructed using the rep-PCR technique and three relied on antibiotic resistance analysis (ARA). Five of the libraries were constructed using Escherichia coli and one using Enterococcus spp. (ARA). Overall, the outcome of this study suggests a high degree of variability across statistical methods. Despite large differences in correct classification rates among the statistical methods, no single statistical approach emerged as superior. Thresholds failed to consistently increase rates of correct classification and improvement was often associated with substantial effective sample size reduction. Recommendations are provided to aid in selecting appropriate analyses for these types of data.
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Event time analysis of longitudinal neuroimage data.
Sabuncu, Mert R; Bernal-Rusiel, Jorge L; Reuter, Martin; Greve, Douglas N; Fischl, Bruce
2014-08-15
This paper presents a method for the statistical analysis of the associations between longitudinal neuroimaging measurements, e.g., of cortical thickness, and the timing of a clinical event of interest, e.g., disease onset. The proposed approach consists of two steps, the first of which employs a linear mixed effects (LME) model to capture temporal variation in serial imaging data. The second step utilizes the extended Cox regression model to examine the relationship between time-dependent imaging measurements and the timing of the event of interest. We demonstrate the proposed method both for the univariate analysis of image-derived biomarkers, e.g., the volume of a structure of interest, and the exploratory mass-univariate analysis of measurements contained in maps, such as cortical thickness and gray matter density. The mass-univariate method employs a recently developed spatial extension of the LME model. We applied our method to analyze structural measurements computed using FreeSurfer, a widely used brain Magnetic Resonance Image (MRI) analysis software package. We provide a quantitative and objective empirical evaluation of the statistical performance of the proposed method on longitudinal data from subjects suffering from Mild Cognitive Impairment (MCI) at baseline. Copyright © 2014 Elsevier Inc. All rights reserved.
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Njoh, Eni N.; Trainor, John K.; O’Connor, Danielle R.; Barnett, Scott D.; Ottomanelli, Lisa
2015-01-01
Background: Return to work is associated with positive rehabilitation outcomes for persons with spinal cord injury (SCI); however, more research is needed on vocational support for persons with disabilities seeking employment. Objective: The association between facilitators and barriers of employment and employment outcome was examined among Veterans with SCI who participated in an evidence-based supported employment (EBSE) program. Methods: Using a mixed-methods, nested case-control design, data on facilitators and barriers to employment were extracted from qualitative interviews and quantitative measures administered in person to 34 Veterans with SCI who completed 12 months of an EBSE program. Participants who did (case) and did not (control) obtain competitive employment were matched on time since SCI. Facilitators and barriers to employment were compared between the groups. Results: Self-report measures administered at baseline were examined; there were no statistically significant factors that predicted employment outcomes after 12 months of EBSE program participation. Qualitative interview data revealed program-specific facilitators and Veteran characteristics that were associated with employment outcomes. Conclusions: Qualitative data illustrate how the integration of the vocational rehabilitation specialist on the medical team is helpful for addressing identified disability-specific barriers, including practical matters such as transportation and caregiving schedules, to facilitate employment outcomes. PMID:25762857
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ERIC Educational Resources Information Center
Harrison, Don K.; Brown, Dorothy R.
Although calculated by various statistical methods, retention (in this monograph) refers to the time that a former hard core member stays on the job. These rates may be tallied from the first day of pre-vocational training at a center, from the first day of a plant's vestibule training, or the first day of work at the job site. The hard core need…
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Application of the Bootstrap Statistical Method in Deriving Vibroacoustic Specifications
NASA Technical Reports Server (NTRS)
Hughes, William O.; Paez, Thomas L.
2006-01-01
This paper discusses the Bootstrap Method for specification of vibroacoustic test specifications. Vibroacoustic test specifications are necessary to properly accept or qualify a spacecraft and its components for the expected acoustic, random vibration and shock environments seen on an expendable launch vehicle. Traditionally, NASA and the U.S. Air Force have employed methods of Normal Tolerance Limits to derive these test levels based upon the amount of data available, and the probability and confidence levels desired. The Normal Tolerance Limit method contains inherent assumptions about the distribution of the data. The Bootstrap is a distribution-free statistical subsampling method which uses the measured data themselves to establish estimates of statistical measures of random sources. This is achieved through the computation of large numbers of Bootstrap replicates of a data measure of interest and the use of these replicates to derive test levels consistent with the probability and confidence desired. The comparison of the results of these two methods is illustrated via an example utilizing actual spacecraft vibroacoustic data.
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Valuing Eastern Visibility: A Field Test of the Contingent Valuation Method (1993)
The report describes the Eastern visibility survey design in detail, presents the implementation of and data obtained from the surveys, provides summary statistics on the overall response and discusses the econometric techniques employed to value benefits.
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Slotnick, Scott D
2017-07-01
Analysis of functional magnetic resonance imaging (fMRI) data typically involves over one hundred thousand independent statistical tests; therefore, it is necessary to correct for multiple comparisons to control familywise error. In a recent paper, Eklund, Nichols, and Knutsson used resting-state fMRI data to evaluate commonly employed methods to correct for multiple comparisons and reported unacceptable rates of familywise error. Eklund et al.'s analysis was based on the assumption that resting-state fMRI data reflect null data; however, their 'null data' actually reflected default network activity that inflated familywise error. As such, Eklund et al.'s results provide no basis to question the validity of the thousands of published fMRI studies that have corrected for multiple comparisons or the commonly employed methods to correct for multiple comparisons.
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Fully Bayesian tests of neutrality using genealogical summary statistics.
Drummond, Alexei J; Suchard, Marc A
2008-10-31
Many data summary statistics have been developed to detect departures from neutral expectations of evolutionary models. However questions about the neutrality of the evolution of genetic loci within natural populations remain difficult to assess. One critical cause of this difficulty is that most methods for testing neutrality make simplifying assumptions simultaneously about the mutational model and the population size model. Consequentially, rejecting the null hypothesis of neutrality under these methods could result from violations of either or both assumptions, making interpretation troublesome. Here we harness posterior predictive simulation to exploit summary statistics of both the data and model parameters to test the goodness-of-fit of standard models of evolution. We apply the method to test the selective neutrality of molecular evolution in non-recombining gene genealogies and we demonstrate the utility of our method on four real data sets, identifying significant departures of neutrality in human influenza A virus, even after controlling for variation in population size. Importantly, by employing a full model-based Bayesian analysis, our method separates the effects of demography from the effects of selection. The method also allows multiple summary statistics to be used in concert, thus potentially increasing sensitivity. Furthermore, our method remains useful in situations where analytical expectations and variances of summary statistics are not available. This aspect has great potential for the analysis of temporally spaced data, an expanding area previously ignored for limited availability of theory and methods.
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Geospatial methods and data analysis for assessing distribution of grazing livestock
USDA-ARS?s Scientific Manuscript database
Free-ranging livestock research must begin with a well conceived problem statement and employ appropriate data acquisition tools and analytical techniques to accomplish the research objective. These requirements are especially critical in addressing animal distribution. Tools and statistics used t...
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Code of Federal Regulations, 2014 CFR
2014-07-01
... methods employed in statistical compilations. The principal title of each exhibit should state what it... furnished: (i) Market research. (a) The following data and information shall be provided: (1) A clear and detailed description of the sample, observational, and data preparation designs, including definitions of...
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Code of Federal Regulations, 2013 CFR
2013-07-01
... item of information used and the methods employed in statistical compilations. The principal title of... furnished: (i) Market research. (a) The following data and information shall be provided: (1) A clear and detailed description of the sample, observational, and data preparation designs, including definitions of...
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Code of Federal Regulations, 2012 CFR
2012-07-01
... item of information used and the methods employed in statistical compilations. The principal title of... should be furnished: (i) Market research. (a) The following data and information shall be provided: (1) A clear and detailed description of the sample, observational, and data preparation designs, including...
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Code of Federal Regulations, 2011 CFR
2011-07-01
... item of information used and the methods employed in statistical compilations. The principal title of... should be furnished: (i) Market research. (a) The following data and information shall be provided: (1) A clear and detailed description of the sample, observational, and data preparation designs, including...
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Code of Federal Regulations, 2010 CFR
2010-07-01
... item of information used and the methods employed in statistical compilations. The principal title of... should be furnished: (i) Market research. (a) The following data and information shall be provided: (1) A clear and detailed description of the sample, observational, and data preparation designs, including...
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ERIC Educational Resources Information Center
Kostadinov, Boyan
2013-01-01
This article attempts to introduce the reader to computational thinking and solving problems involving randomness. The main technique being employed is the Monte Carlo method, using the freely available software "R for Statistical Computing." The author illustrates the computer simulation approach by focusing on several problems of…
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Can We Spin Straw Into Gold? An Evaluation of Immigrant Legal Status Imputation Approaches
Van Hook, Jennifer; Bachmeier, James D.; Coffman, Donna; Harel, Ofer
2014-01-01
Researchers have developed logical, demographic, and statistical strategies for imputing immigrants’ legal status, but these methods have never been empirically assessed. We used Monte Carlo simulations to test whether, and under what conditions, legal status imputation approaches yield unbiased estimates of the association of unauthorized status with health insurance coverage. We tested five methods under a range of missing data scenarios. Logical and demographic imputation methods yielded biased estimates across all missing data scenarios. Statistical imputation approaches yielded unbiased estimates only when unauthorized status was jointly observed with insurance coverage; when this condition was not met, these methods overestimated insurance coverage for unauthorized relative to legal immigrants. We next showed how bias can be reduced by incorporating prior information about unauthorized immigrants. Finally, we demonstrated the utility of the best-performing statistical method for increasing power. We used it to produce state/regional estimates of insurance coverage among unauthorized immigrants in the Current Population Survey, a data source that contains no direct measures of immigrants’ legal status. We conclude that commonly employed legal status imputation approaches are likely to produce biased estimates, but data and statistical methods exist that could substantially reduce these biases. PMID:25511332
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NASA Technical Reports Server (NTRS)
Mei, Chuh; Dhainaut, Jean-Michel
2000-01-01
The Monte Carlo simulation method in conjunction with the finite element large deflection modal formulation are used to estimate fatigue life of aircraft panels subjected to stationary Gaussian band-limited white-noise excitations. Ten loading cases varying from 106 dB to 160 dB OASPL with bandwidth 1024 Hz are considered. For each load case, response statistics are obtained from an ensemble of 10 response time histories. The finite element nonlinear modal procedure yields time histories, probability density functions (PDF), power spectral densities and higher statistical moments of the maximum deflection and stress/strain. The method of moments of PSD with Dirlik's approach is employed to estimate the panel fatigue life.
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ToNER: A tool for identifying nucleotide enrichment signals in feature-enriched RNA-seq data
Promworn, Yuttachon; Kaewprommal, Pavita; Shaw, Philip J.; Intarapanich, Apichart; Tongsima, Sissades
2017-01-01
Background Biochemical methods are available for enriching 5′ ends of RNAs in prokaryotes, which are employed in the differential RNA-seq (dRNA-seq) and the more recent Cappable-seq protocols. Computational methods are needed to locate RNA 5′ ends from these data by statistical analysis of the enrichment. Although statistical-based analysis methods have been developed for dRNA-seq, they may not be suitable for Cappable-seq data. The more efficient enrichment method employed in Cappable-seq compared with dRNA-seq could affect data distribution and thus algorithm performance. Results We present Transformation of Nucleotide Enrichment Ratios (ToNER), a tool for statistical modeling of enrichment from RNA-seq data obtained from enriched and unenriched libraries. The tool calculates nucleotide enrichment scores and determines the global transformation for fitting to the normal distribution using the Box-Cox procedure. From the transformed distribution, sites of significant enrichment are identified. To increase power of detection, meta-analysis across experimental replicates is offered. We tested the tool on Cappable-seq and dRNA-seq data for identifying Escherichia coli transcript 5′ ends and compared the results with those from the TSSAR tool, which is designed for analyzing dRNA-seq data. When combining results across Cappable-seq replicates, ToNER detects more known transcript 5′ ends than TSSAR. In general, the transcript 5′ ends detected by ToNER but not TSSAR occur in regions which cannot be locally modeled by TSSAR. Conclusion ToNER uses a simple yet robust statistical modeling approach, which can be used for detecting RNA 5′ends from Cappable-seq data, in particular when combining information from experimental replicates. The ToNER tool could potentially be applied for analyzing other RNA-seq datasets in which enrichment for other structural features of RNA is employed. The program is freely available for download at ToNER webpage (http://www4a.biotec.or.th/GI/tools/toner) and GitHub repository (https://github.com/PavitaKae/ToNER). PMID:28542466
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ERIC Educational Resources Information Center
Longford, Nicholas T.
Large scale surveys usually employ a complex sampling design and as a consequence, no standard methods for estimation of the standard errors associated with the estimates of population means are available. Resampling methods, such as jackknife or bootstrap, are often used, with reference to their properties of robustness and reduction of bias. A…
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NASA Astrophysics Data System (ADS)
Oregui, M.; Li, Z.; Dollevoet, R.
2015-03-01
In this paper, the feasibility of the Frequency Response Function (FRF)-based statistical method to identify the characteristic frequencies of railway track defects is studied. The method compares a damaged track state to a healthy state based on non-destructive field hammer test measurements. First, a study is carried out to investigate the repeatability of hammer tests in railway tracks. By changing the excitation and measurement locations it is shown that the variability introduced by the test process is negligible. Second, following the concepts of control charts employed in process monitoring, a method to define an approximate healthy state is introduced by using hammer test measurements at locations without visual damage. Then, the feasibility study includes an investigation into squats (i.e. a major type of rail surface defect) of varying severity. The identified frequency ranges related to squats agree with those found in an extensively validated vehicle-borne detection system. Therefore, the FRF-based statistical method in combination with the non-destructive hammer test measurements has the potential to be employed to identify the characteristic frequencies of damaged conditions in railway tracks in the frequency range of 300-3000 Hz.
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The economic impact of Mexico City's smoke-free law
Guerrero López, Carlos Manuel; Jiménez Ruiz, Jorge Alberto; Reynales Shigematsu, Luz Myriam
2011-01-01
Objective To evaluate the economic impact of Mexico City's 2008 smoke-free law—The Non-Smokers' Health Protection Law on restaurants, bars and nightclubs. Material and methods We used the Monthly Services Survey of businesses from January 2005 to April 2009—with revenues, employment and payments to employees as the principal outcomes. The results are estimated using a differences-in-differences regression model with fixed effects. The states of Jalisco, Nuevo León and México, where the law was not in effect, serve as a counterfactual comparison group. Results In restaurants, after accounting for observable factors and the fixed effects, there was a 24.8% increase in restaurants' revenue associated with the smoke-free law. This difference is not statistically significant but shows that, on average, restaurants did not suffer economically as a result of the law. Total wages increased by 28.2% and employment increased by 16.2%. In nightclubs, bars and taverns there was a decrease of 1.5% in revenues and an increase of 0.1% and 3.0%, respectively, in wages and employment. None of these effects are statistically significant in multivariate analysis. Conclusions There is no statistically significant evidence that the Mexico City smoke-free law had a negative impact on restaurants' income, employees' wages and levels of employment. On the contrary, the results show a positive, though statistically non-significant, impact of the law on most of these outcomes. Mexico City's experience suggests that smoke-free laws in Mexico and elsewhere will not hurt economic productivity in the restaurant and bar industries. PMID:21292808
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NASA Astrophysics Data System (ADS)
Zhu, Meng-Hua; Liu, Liang-Gang; You, Zhong; Xu, Ao-Ao
2009-03-01
In this paper, a heuristic approach based on Slavic's peak searching method has been employed to estimate the width of peak regions for background removing. Synthetic and experimental data are used to test this method. With the estimated peak regions using the proposed method in the whole spectrum, we find it is simple and effective enough to be used together with the Statistics-sensitive Nonlinear Iterative Peak-Clipping method.
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Assessing Creative Problem-Solving with Automated Text Grading
ERIC Educational Resources Information Center
Wang, Hao-Chuan; Chang, Chun-Yen; Li, Tsai-Yen
2008-01-01
The work aims to improve the assessment of creative problem-solving in science education by employing language technologies and computational-statistical machine learning methods to grade students' natural language responses automatically. To evaluate constructs like creative problem-solving with validity, open-ended questions that elicit…
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Advanced building energy management system demonstration for Department of Defense buildings.
O'Neill, Zheng; Bailey, Trevor; Dong, Bing; Shashanka, Madhusudana; Luo, Dong
2013-08-01
This paper presents an advanced building energy management system (aBEMS) that employs advanced methods of whole-building performance monitoring combined with statistical methods of learning and data analysis to enable identification of both gradual and discrete performance erosion and faults. This system assimilated data collected from multiple sources, including blueprints, reduced-order models (ROM) and measurements, and employed advanced statistical learning algorithms to identify patterns of anomalies. The results were presented graphically in a manner understandable to facilities managers. A demonstration of aBEMS was conducted in buildings at Naval Station Great Lakes. The facility building management systems were extended to incorporate the energy diagnostics and analysis algorithms, producing systematic identification of more efficient operation strategies. At Naval Station Great Lakes, greater than 20% savings were demonstrated for building energy consumption by improving facility manager decision support to diagnose energy faults and prioritize alternative, energy-efficient operation strategies. The paper concludes with recommendations for widespread aBEMS success. © 2013 New York Academy of Sciences.
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NASA Astrophysics Data System (ADS)
Kovalevsky, Louis; Langley, Robin S.; Caro, Stephane
2016-05-01
Due to the high cost of experimental EMI measurements significant attention has been focused on numerical simulation. Classical methods such as Method of Moment or Finite Difference Time Domain are not well suited for this type of problem, as they require a fine discretisation of space and failed to take into account uncertainties. In this paper, the authors show that the Statistical Energy Analysis is well suited for this type of application. The SEA is a statistical approach employed to solve high frequency problems of electromagnetically reverberant cavities at a reduced computational cost. The key aspects of this approach are (i) to consider an ensemble of system that share the same gross parameter, and (ii) to avoid solving Maxwell's equations inside the cavity, using the power balance principle. The output is an estimate of the field magnitude distribution in each cavity. The method is applied on a typical aircraft structure.
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NASA Astrophysics Data System (ADS)
Roberts, B. M.; Blewitt, G.; Dailey, C.; Derevianko, A.
2018-04-01
We analyze the prospects of employing a distributed global network of precision measurement devices as a dark matter and exotic physics observatory. In particular, we consider the atomic clocks of the global positioning system (GPS), consisting of a constellation of 32 medium-Earth orbit satellites equipped with either Cs or Rb microwave clocks and a number of Earth-based receiver stations, some of which employ highly-stable H-maser atomic clocks. High-accuracy timing data is available for almost two decades. By analyzing the satellite and terrestrial atomic clock data, it is possible to search for transient signatures of exotic physics, such as "clumpy" dark matter and dark energy, effectively transforming the GPS constellation into a 50 000 km aperture sensor array. Here we characterize the noise of the GPS satellite atomic clocks, describe the search method based on Bayesian statistics, and test the method using simulated clock data. We present the projected discovery reach using our method, and demonstrate that it can surpass the existing constrains by several order of magnitude for certain models. Our method is not limited in scope to GPS or atomic clock networks, and can also be applied to other networks of precision measurement devices.
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Techniques in teaching statistics : linking research production and research use.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Martinez-Moyano, I .; Smith, A.; Univ. of Massachusetts at Boston)
In the spirit of closing the 'research-practice gap,' the authors extend evidence-based principles to statistics instruction in social science graduate education. The authors employ a Delphi method to survey experienced statistics instructors to identify teaching techniques to overcome the challenges inherent in teaching statistics to students enrolled in practitioner-oriented master's degree programs. Among the teaching techniques identi?ed as essential are using real-life examples, requiring data collection exercises, and emphasizing interpretation rather than results. Building on existing research, preliminary interviews, and the ?ndings from the study, the authors develop a model describing antecedents to the strength of the link between researchmore » and practice.« less
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Gender and Employment. Current Statistics and Their Implications.
ERIC Educational Resources Information Center
Equity Issues, 1996
1996-01-01
This publication contains three fact sheets on gender and employment statistics and their implications. The fact sheets are divided into two sections--statistics and implications. The statistics present the current situation of men and women workers as they relate to occupations, education, and earnings. The implications express suggestions for…
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Statistical mechanics of broadcast channels using low-density parity-check codes.
Nakamura, Kazutaka; Kabashima, Yoshiyuki; Morelos-Zaragoza, Robert; Saad, David
2003-03-01
We investigate the use of Gallager's low-density parity-check (LDPC) codes in a degraded broadcast channel, one of the fundamental models in network information theory. Combining linear codes is a standard technique in practical network communication schemes and is known to provide better performance than simple time sharing methods when algebraic codes are used. The statistical physics based analysis shows that the practical performance of the suggested method, achieved by employing the belief propagation algorithm, is superior to that of LDPC based time sharing codes while the best performance, when received transmissions are optimally decoded, is bounded by the time sharing limit.
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Garcia, F; Arruda-Neto, J D; Manso, M V; Helene, O M; Vanin, V R; Rodriguez, O; Mesa, J; Likhachev, V P; Filho, J W; Deppman, A; Perez, G; Guzman, F; de Camargo, S P
1999-10-01
A new and simple statistical procedure (STATFLUX) for the calculation of transfer coefficients of radionuclide transport to animals and plants is proposed. The method is based on the general multiple-compartment model, which uses a system of linear equations involving geometrical volume considerations. By using experimentally available curves of radionuclide concentrations versus time, for each animal compartment (organs), flow parameters were estimated by employing a least-squares procedure, whose consistency is tested. Some numerical results are presented in order to compare the STATFLUX transfer coefficients with those from other works and experimental data.
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Total Quality Management in Libraries. ERIC Digest.
ERIC Educational Resources Information Center
Masters, Denise G.
Total Quality Management (TQM) is "a system of continuous improvement employing participative management and centered on the needs of customers." Key components of TQM are employee involvement and training, problem-solving teams, statistical methods, long-term goals and thinking, and recognition that the system, not people, produces…
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Pasaniuc, Bogdan; Zaitlen, Noah; Lettre, Guillaume; Chen, Gary K; Tandon, Arti; Kao, W H Linda; Ruczinski, Ingo; Fornage, Myriam; Siscovick, David S; Zhu, Xiaofeng; Larkin, Emma; Lange, Leslie A; Cupples, L Adrienne; Yang, Qiong; Akylbekova, Ermeg L; Musani, Solomon K; Divers, Jasmin; Mychaleckyj, Joe; Li, Mingyao; Papanicolaou, George J; Millikan, Robert C; Ambrosone, Christine B; John, Esther M; Bernstein, Leslie; Zheng, Wei; Hu, Jennifer J; Ziegler, Regina G; Nyante, Sarah J; Bandera, Elisa V; Ingles, Sue A; Press, Michael F; Chanock, Stephen J; Deming, Sandra L; Rodriguez-Gil, Jorge L; Palmer, Cameron D; Buxbaum, Sarah; Ekunwe, Lynette; Hirschhorn, Joel N; Henderson, Brian E; Myers, Simon; Haiman, Christopher A; Reich, David; Patterson, Nick; Wilson, James G; Price, Alkes L
2011-04-01
While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations.
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Reporting Practices and Use of Quantitative Methods in Canadian Journal Articles in Psychology.
Counsell, Alyssa; Harlow, Lisa L
2017-05-01
With recent focus on the state of research in psychology, it is essential to assess the nature of the statistical methods and analyses used and reported by psychological researchers. To that end, we investigated the prevalence of different statistical procedures and the nature of statistical reporting practices in recent articles from the four major Canadian psychology journals. The majority of authors evaluated their research hypotheses through the use of analysis of variance (ANOVA), t -tests, and multiple regression. Multivariate approaches were less common. Null hypothesis significance testing remains a popular strategy, but the majority of authors reported a standardized or unstandardized effect size measure alongside their significance test results. Confidence intervals on effect sizes were infrequently employed. Many authors provided minimal details about their statistical analyses and less than a third of the articles presented on data complications such as missing data and violations of statistical assumptions. Strengths of and areas needing improvement for reporting quantitative results are highlighted. The paper concludes with recommendations for how researchers and reviewers can improve comprehension and transparency in statistical reporting.
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A critique of the usefulness of inferential statistics in applied behavior analysis
Hopkins, B. L.; Cole, Brian L.; Mason, Tina L.
1998-01-01
Researchers continue to recommend that applied behavior analysts use inferential statistics in making decisions about effects of independent variables on dependent variables. In many other approaches to behavioral science, inferential statistics are the primary means for deciding the importance of effects. Several possible uses of inferential statistics are considered. Rather than being an objective means for making decisions about effects, as is often claimed, inferential statistics are shown to be subjective. It is argued that the use of inferential statistics adds nothing to the complex and admittedly subjective nonstatistical methods that are often employed in applied behavior analysis. Attacks on inferential statistics that are being made, perhaps with increasing frequency, by those who are not behavior analysts, are discussed. These attackers are calling for banning the use of inferential statistics in research publications and commonly recommend that behavioral scientists should switch to using statistics aimed at interval estimation or the method of confidence intervals. Interval estimation is shown to be contrary to the fundamental assumption of behavior analysis that only individuals behave. It is recommended that authors who wish to publish the results of inferential statistics be asked to justify them as a means for helping us to identify any ways in which they may be useful. PMID:22478304
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2011-01-01
Background This study aims to identify the statistical software applications most commonly employed for data analysis in health services research (HSR) studies in the U.S. The study also examines the extent to which information describing the specific analytical software utilized is provided in published articles reporting on HSR studies. Methods Data were extracted from a sample of 1,139 articles (including 877 original research articles) published between 2007 and 2009 in three U.S. HSR journals, that were considered to be representative of the field based upon a set of selection criteria. Descriptive analyses were conducted to categorize patterns in statistical software usage in those articles. The data were stratified by calendar year to detect trends in software use over time. Results Only 61.0% of original research articles in prominent U.S. HSR journals identified the particular type of statistical software application used for data analysis. Stata and SAS were overwhelmingly the most commonly used software applications employed (in 46.0% and 42.6% of articles respectively). However, SAS use grew considerably during the study period compared to other applications. Stratification of the data revealed that the type of statistical software used varied considerably by whether authors were from the U.S. or from other countries. Conclusions The findings highlight a need for HSR investigators to identify more consistently the specific analytical software used in their studies. Knowing that information can be important, because different software packages might produce varying results, owing to differences in the software's underlying estimation methods. PMID:21977990
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Analysis of Publications and Citations from a Geophysics Research Institute.
ERIC Educational Resources Information Center
Frohlich, Cliff; Resler, Lynn
2001-01-01
Performs an analysis of all 1128 publications produced by scientists during their employment at the University of Texas Institute for Geophysics, thus assessing research performance using as bibliometric indicators such statistics as publications per year, citations per paper, and cited half-lives. Evaluates five different methods for determining…
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21 CFR 58.185 - Reporting of nonclinical laboratory study results.
Code of Federal Regulations, 2010 CFR
2010-04-01
...) Statistical methods employed for analyzing the data. (4) The test and control articles identified by name... characteristics. (5) Stability of the test and control articles under the conditions of administration. (6) A... scientists or professionals, and the names of all supervisory personnel, involved in the study. (11) A...
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Examining Multidimensional Middle Grade Outcomes after Early Elementary School Grade Retention
ERIC Educational Resources Information Center
Hwang, Sophia; Cappella, Elise; Schwartz, Kate
2016-01-01
Recently, researchers have begun to employ rigorous statistical methods and developmentally-informed theories to evaluate outcomes for students retained in non-kindergarten early elementary school. However, the majority of this research focuses on academic outcomes. Gaps remain regarding retention's effects on psychosocial outcomes important to…
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Cluster Analysis of Minnesota School Districts. A Research Report.
ERIC Educational Resources Information Center
Cleary, James
The term "cluster analysis" refers to a set of statistical methods that classify entities with similar profiles of scores on a number of measured dimensions, in order to create empirically based typologies. A 1980 Minnesota House Research Report employed cluster analysis to categorize school districts according to their relative mixtures…
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Federal Register 2010, 2011, 2012, 2013, 2014
2013-03-29
... by dividing the Bureau of Labor Statistics Occupational Employment Statistics Survey (OES survey... DEPARTMENT OF LABOR Employment and Training Administration 20 CFR Part 655 RIN 1205-AB61 Wage Methodology for the Temporary Non-Agricultural Employment H- 2B Program; Delay of Effective Date AGENCY...
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Barnes, Stephen; Benton, H. Paul; Casazza, Krista; Cooper, Sara; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H.; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K.; Renfrow, Matthew B.; Tiwari, Hemant K.
2017-01-01
Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites, and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. PMID:28239968
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Temporal variation and scale in movement-based resource selection functions
Hooten, M.B.; Hanks, E.M.; Johnson, D.S.; Alldredge, M.W.
2013-01-01
A common population characteristic of interest in animal ecology studies pertains to the selection of resources. That is, given the resources available to animals, what do they ultimately choose to use? A variety of statistical approaches have been employed to examine this question and each has advantages and disadvantages with respect to the form of available data and the properties of estimators given model assumptions. A wealth of high resolution telemetry data are now being collected to study animal population movement and space use and these data present both challenges and opportunities for statistical inference. We summarize traditional methods for resource selection and then describe several extensions to deal with measurement uncertainty and an explicit movement process that exists in studies involving high-resolution telemetry data. Our approach uses a correlated random walk movement model to obtain temporally varying use and availability distributions that are employed in a weighted distribution context to estimate selection coefficients. The temporally varying coefficients are then weighted by their contribution to selection and combined to provide inference at the population level. The result is an intuitive and accessible statistical procedure that uses readily available software and is computationally feasible for large datasets. These methods are demonstrated using data collected as part of a large-scale mountain lion monitoring study in Colorado, USA.
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Impact of Coal Mining on Self-Rated Health among Appalachian Residents
Woolley, Shannon M.; Bear, Todd M.; Balmert, Lauren C.; Talbott, Evelyn O.; Buchanich, Jeanine M.
2015-01-01
Objective. To determine the impact of coal mining, measured as the number of coal mining-related facilities nearby one's residence or employment in an occupation directly related to coal mining, on self-rated health in Appalachia. Methods. Unadjusted and adjusted ordinal logistic regression models calculated odds ratio estimates and associated 95% confidence intervals for the probability of having an excellent self-rated health response versus another response. Covariates considered in the analyses included number of coal mining-related facilities nearby one's residence and employment in an occupation directly related to coal mining, as well as potential confounders age, sex, BMI, smoking status, income, and education. Results. The number of coal mining facilities near the respondent's residence was not a statistically significant predictor of self-rated health. Employment in a coal-related occupation was a statistically significant predictor of self-rated health univariably; however, after adjusting for potential confounders, it was no longer a significant predictor. Conclusions. Self-rated health does not seem to be associated with residential proximity to coal mining facilities or employment in the coal industry. Future research should consider additional measures for the impact of coal mining. PMID:26240577
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Cherry, Kevin M; Peplinski, Brandon; Kim, Lauren; Wang, Shijun; Lu, Le; Zhang, Weidong; Liu, Jianfei; Wei, Zhuoshi; Summers, Ronald M
2015-01-01
Given the potential importance of marginal artery localization in automated registration in computed tomography colonography (CTC), we have devised a semi-automated method of marginal vessel detection employing sequential Monte Carlo tracking (also known as particle filtering tracking) by multiple cue fusion based on intensity, vesselness, organ detection, and minimum spanning tree information for poorly enhanced vessel segments. We then employed a random forest algorithm for intelligent cue fusion and decision making which achieved high sensitivity and robustness. After applying a vessel pruning procedure to the tracking results, we achieved statistically significantly improved precision compared to a baseline Hessian detection method (2.7% versus 75.2%, p<0.001). This method also showed statistically significantly improved recall rate compared to a 2-cue baseline method using fewer vessel cues (30.7% versus 67.7%, p<0.001). These results demonstrate that marginal artery localization on CTC is feasible by combining a discriminative classifier (i.e., random forest) with a sequential Monte Carlo tracking mechanism. In so doing, we present the effective application of an anatomical probability map to vessel pruning as well as a supplementary spatial coordinate system for colonic segmentation and registration when this task has been confounded by colon lumen collapse. Published by Elsevier B.V.
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Graphical method for comparative statistical study of vaccine potency tests.
Pay, T W; Hingley, P J
1984-03-01
Producers and consumers are interested in some of the intrinsic characteristics of vaccine potency assays for the comparative evaluation of suitable experimental design. A graphical method is developed which represents the precision of test results, the sensitivity of such results to changes in dosage, and the relevance of the results in the way they reflect the protection afforded in the host species. The graphs can be constructed from Producer's scores and Consumer's scores on each of the scales of test score, antigen dose and probability of protection against disease. A method for calculating these scores is suggested and illustrated for single and multiple component vaccines, for tests which do or do not employ a standard reference preparation, and for tests which employ quantitative or quantal systems of scoring.
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Application of one-way ANOVA in completely randomized experiments
NASA Astrophysics Data System (ADS)
Wahid, Zaharah; Izwan Latiff, Ahmad; Ahmad, Kartini
2017-12-01
This paper describes an application of a statistical technique one-way ANOVA in completely randomized experiments with three replicates. This technique was employed to a single factor with four levels and multiple observations at each level. The aim of this study is to investigate the relationship between chemical oxygen demand index and location on-sites. Two different approaches are employed for the analyses; critical value and p-value. It also presents key assumptions of the technique to be satisfied by the data in order to obtain valid results. Pairwise comparisons by Turkey method are also considered and discussed to determine where the significant differences among the means is after the ANOVA has been performed. The results revealed that there are statistically significant relationship exist between the chemical oxygen demand index and the location on-sites.
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Statistical variances of diffusional properties from ab initio molecular dynamics simulations
NASA Astrophysics Data System (ADS)
He, Xingfeng; Zhu, Yizhou; Epstein, Alexander; Mo, Yifei
2018-12-01
Ab initio molecular dynamics (AIMD) simulation is widely employed in studying diffusion mechanisms and in quantifying diffusional properties of materials. However, AIMD simulations are often limited to a few hundred atoms and a short, sub-nanosecond physical timescale, which leads to models that include only a limited number of diffusion events. As a result, the diffusional properties obtained from AIMD simulations are often plagued by poor statistics. In this paper, we re-examine the process to estimate diffusivity and ionic conductivity from the AIMD simulations and establish the procedure to minimize the fitting errors. In addition, we propose methods for quantifying the statistical variance of the diffusivity and ionic conductivity from the number of diffusion events observed during the AIMD simulation. Since an adequate number of diffusion events must be sampled, AIMD simulations should be sufficiently long and can only be performed on materials with reasonably fast diffusion. We chart the ranges of materials and physical conditions that can be accessible by AIMD simulations in studying diffusional properties. Our work provides the foundation for quantifying the statistical confidence levels of diffusion results from AIMD simulations and for correctly employing this powerful technique.
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Comparison of ANN and SVM for classification of eye movements in EOG signals
NASA Astrophysics Data System (ADS)
Qi, Lim Jia; Alias, Norma
2018-03-01
Nowadays, electrooculogram is regarded as one of the most important biomedical signal in measuring and analyzing eye movement patterns. Thus, it is helpful in designing EOG-based Human Computer Interface (HCI). In this research, electrooculography (EOG) data was obtained from five volunteers. The (EOG) data was then preprocessed before feature extraction methods were employed to further reduce the dimensionality of data. Three feature extraction approaches were put forward, namely statistical parameters, autoregressive (AR) coefficients using Burg method, and power spectral density (PSD) using Yule-Walker method. These features would then become input to both artificial neural network (ANN) and support vector machine (SVM). The performance of the combination of different feature extraction methods and classifiers was presented and analyzed. It was found that statistical parameters + SVM achieved the highest classification accuracy of 69.75%.
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Antweiler, Ronald C.; Taylor, Howard E.
2008-01-01
The main classes of statistical treatment of below-detection limit (left-censored) environmental data for the determination of basic statistics that have been used in the literature are substitution methods, maximum likelihood, regression on order statistics (ROS), and nonparametric techniques. These treatments, along with using all instrument-generated data (even those below detection), were evaluated by examining data sets in which the true values of the censored data were known. It was found that for data sets with less than 70% censored data, the best technique overall for determination of summary statistics was the nonparametric Kaplan-Meier technique. ROS and the two substitution methods of assigning one-half the detection limit value to censored data or assigning a random number between zero and the detection limit to censored data were adequate alternatives. The use of these two substitution methods, however, requires a thorough understanding of how the laboratory censored the data. The technique of employing all instrument-generated data - including numbers below the detection limit - was found to be less adequate than the above techniques. At high degrees of censoring (greater than 70% censored data), no technique provided good estimates of summary statistics. Maximum likelihood techniques were found to be far inferior to all other treatments except substituting zero or the detection limit value to censored data.
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Smith, Peter M; Mustard, Cameron A; Payne, Jennifer I
2004-01-01
This paper presents a methodology for estimating the size and composition of the Ontario labour force eligible for coverage under the Ontario Workplace Safety & Insurance Act (WSIA). Using customized tabulations from Statistics Canada's Labour Force Survey (LFS), we made adjustments for self-employment, unemployment, part-time employment and employment in specific industrial sectors excluded from insurance coverage under the WSIA. Each adjustment to the LFS reduced the estimates of the insured labour force relative to the total Ontario labour force. These estimates were then developed for major occupational and industrial groups stratified by gender. Additional estimates created to test assumptions used in the methodology produced similar results. The methods described in this paper advance those previously used to estimate the insured labour force, providing researchers with a useful tool to describe trends in the rate of injury across differing occupational, industrial and gender groups in Ontario.
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Robust matching for voice recognition
NASA Astrophysics Data System (ADS)
Higgins, Alan; Bahler, L.; Porter, J.; Blais, P.
1994-10-01
This paper describes an automated method of comparing a voice sample of an unknown individual with samples from known speakers in order to establish or verify the individual's identity. The method is based on a statistical pattern matching approach that employs a simple training procedure, requires no human intervention (transcription, work or phonetic marketing, etc.), and makes no assumptions regarding the expected form of the statistical distributions of the observations. The content of the speech material (vocabulary, grammar, etc.) is not assumed to be constrained in any way. An algorithm is described which incorporates frame pruning and channel equalization processes designed to achieve robust performance with reasonable computational resources. An experimental implementation demonstrating the feasibility of the concept is described.
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Spatial analysis on future housing markets: economic development and housing implications.
Liu, Xin; Wang, Lizhe
2014-01-01
A coupled projection method combining formal modelling and other statistical techniques was developed to delineate the relationship between economic and social drivers for net new housing allocations. Using the example of employment growth in Tyne and Wear, UK, until 2016, the empirical analysis yields housing projections at the macro- and microspatial levels (e.g., region to subregion to elected ward levels). The results have important implications for the strategic planning of locations for housing and employment, demonstrating both intuitively and quantitatively how local economic developments affect housing demand.
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Spatial Analysis on Future Housing Markets: Economic Development and Housing Implications
Liu, Xin; Wang, Lizhe
2014-01-01
A coupled projection method combining formal modelling and other statistical techniques was developed to delineate the relationship between economic and social drivers for net new housing allocations. Using the example of employment growth in Tyne and Wear, UK, until 2016, the empirical analysis yields housing projections at the macro- and microspatial levels (e.g., region to subregion to elected ward levels). The results have important implications for the strategic planning of locations for housing and employment, demonstrating both intuitively and quantitatively how local economic developments affect housing demand. PMID:24892097
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Who Gets Promoted? Gender Differences in Science and Engineering Academia
NASA Astrophysics Data System (ADS)
Olson, Kristen
Using a nationally representative sample of doctoral academic scientists and engineers, this study examines gender differences in the likelihood of having tenure and senior faculty ranks after controlling for academic age, field, doctoral origins, employing educational institution, productivity, postdoctoral positions, work activities, and family characteristics. Logistic regressions show that many of these controls are significant; that biology and employment at comprehensive universities have a gender-specific advantage for women; and that postdoctoral positions, teaching instead of doing administrative work, and having children have a gender-specific disadvantage. Although the statistical methods employed here do not reveal the exact nature of how gender inequities in science and engineering careers arise, the author suggests that they exist.
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It has been fifty years since Kirkham and Bartholmew (1954) presented the conceptual framework and derived the mathematical equations that formed the basis of the now commonly employed method of 15N isotope dilution. Although many advances in methodology and analysis have been ma...
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NASA Technical Reports Server (NTRS)
Hong, Z. C.
1975-01-01
A review of various methods of calculating turbulent chemically reacting flow such as the Green Function, Navier-Stokes equation, and others is presented. Nonequilibrium degrees of freedom were employed to study the mixing behavior of a multiscale turbulence field. Classical and modern theories are discussed.
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Rota, Cristina; Cristoni, Simone; Trenti, Tommaso; Cariani, Elisabetta
2013-01-01
Oxidative attack to DNA is of particular interest since DNA modifications can lead to heritable mutations. The most studied product of DNA oxidation is 8-oxo-7,8-dihydro-2′-deoxyguanosine (8-oxodG). While 8-oxodG determination in blood and tissue cells is prone to artifacts, its measurement in urine employing liquid chromatography tandem mass spectrometry (LC-MS/MS) has gained more and more interest for increased reliability. LC-MS/MS can be affected by matrix effects and this is particularly true when ion trap is used as MS analyzer, due to ion accumulation in the trap and related space charge effect. In the present work, we have developed a LC-MS/MS method where the combination of cation exchange and reverse phase solid phases resulted in LC separation optimization. This together with the employment of an isotopically labeled internal standard, allowed the usage of ion trap LC-MS/MS, typically not employed for quantitative measurement in biological samples, for the measurement of 8-oxodG in urine samples from control populations. Four different urine matrices were employed for method validation. Limit of quantitation was set at least at 0.5 ng/ml. While analyzing urine samples from healthy volunteers, 8-oxodG levels reported as ng/ml were statistically different comparing males with females (p<0.05, Mann Whitney test); while comparing results normalized for creatinine no statistical significant difference was found. Mean urinary 8-oxodG level found in healthy volunteers was 1.16±0.46 nmol/mmol creatinine. The present method by enhancing at best the chromatographic performances allows the usage of ion trap LC-MS/MS for the measurement of 8-oxodG in urine samples from control populations. PMID:24251117
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Hutton, Brian; Wolfe, Dianna; Moher, David; Shamseer, Larissa
2017-05-01
Research waste has received considerable attention from the biomedical community. One noteworthy contributor is incomplete reporting in research publications. When detailing statistical methods and results, ensuring analytic methods and findings are completely documented improves transparency. For publications describing randomised trials and systematic reviews, guidelines have been developed to facilitate complete reporting. This overview summarises aspects of statistical reporting in trials and systematic reviews of health interventions. A narrative approach to summarise features regarding statistical methods and findings from reporting guidelines for trials and reviews was taken. We aim to enhance familiarity of statistical details that should be reported in biomedical research among statisticians and their collaborators. We summarise statistical reporting considerations for trials and systematic reviews from guidance documents including the Consolidated Standards of Reporting Trials (CONSORT) Statement for reporting of trials, the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) Statement for trial protocols, the Statistical Analyses and Methods in the Published Literature (SAMPL) Guidelines for statistical reporting principles, the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement for systematic reviews and PRISMA for Protocols (PRISMA-P). Considerations regarding sharing of study data and statistical code are also addressed. Reporting guidelines provide researchers with minimum criteria for reporting. If followed, they can enhance research transparency and contribute improve quality of biomedical publications. Authors should employ these tools for planning and reporting of their research. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
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Federal Register 2010, 2011, 2012, 2013, 2014
2011-07-27
... for OMB Review; Comment Request; Report on Current Employment Statistics ACTION: Notice. SUMMARY: The Department of Labor (DOL) is submitting the revised Bureau of Labor Statistics (BLS) sponsored information collection request (ICR) titled, ``Report on Current Employment Statistics,'' to the Office of Management and...
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Hamel, Jean-Francois; Saulnier, Patrick; Pe, Madeline; Zikos, Efstathios; Musoro, Jammbe; Coens, Corneel; Bottomley, Andrew
2017-09-01
Over the last decades, Health-related Quality of Life (HRQoL) end-points have become an important outcome of the randomised controlled trials (RCTs). HRQoL methodology in RCTs has improved following international consensus recommendations. However, no international recommendations exist concerning the statistical analysis of such data. The aim of our study was to identify and characterise the quality of the statistical methods commonly used for analysing HRQoL data in cancer RCTs. Building on our recently published systematic review, we analysed a total of 33 published RCTs studying the HRQoL methods reported in RCTs since 1991. We focussed on the ability of the methods to deal with the three major problems commonly encountered when analysing HRQoL data: their multidimensional and longitudinal structure and the commonly high rate of missing data. All studies reported HRQoL being assessed repeatedly over time for a period ranging from 2 to 36 months. Missing data were common, with compliance rates ranging from 45% to 90%. From the 33 studies considered, 12 different statistical methods were identified. Twenty-nine studies analysed each of the questionnaire sub-dimensions without type I error adjustment. Thirteen studies repeated the HRQoL analysis at each assessment time again without type I error adjustment. Only 8 studies used methods suitable for repeated measurements. Our findings show a lack of consistency in statistical methods for analysing HRQoL data. Problems related to multiple comparisons were rarely considered leading to a high risk of false positive results. It is therefore critical that international recommendations for improving such statistical practices are developed. Copyright © 2017. Published by Elsevier Ltd.
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Discriminative Random Field Models for Subsurface Contamination Uncertainty Quantification
NASA Astrophysics Data System (ADS)
Arshadi, M.; Abriola, L. M.; Miller, E. L.; De Paolis Kaluza, C.
2017-12-01
Application of flow and transport simulators for prediction of the release, entrapment, and persistence of dense non-aqueous phase liquids (DNAPLs) and associated contaminant plumes is a computationally intensive process that requires specification of a large number of material properties and hydrologic/chemical parameters. Given its computational burden, this direct simulation approach is particularly ill-suited for quantifying both the expected performance and uncertainty associated with candidate remediation strategies under real field conditions. Prediction uncertainties primarily arise from limited information about contaminant mass distributions, as well as the spatial distribution of subsurface hydrologic properties. Application of direct simulation to quantify uncertainty would, thus, typically require simulating multiphase flow and transport for a large number of permeability and release scenarios to collect statistics associated with remedial effectiveness, a computationally prohibitive process. The primary objective of this work is to develop and demonstrate a methodology that employs measured field data to produce equi-probable stochastic representations of a subsurface source zone that capture the spatial distribution and uncertainty associated with key features that control remediation performance (i.e., permeability and contamination mass). Here we employ probabilistic models known as discriminative random fields (DRFs) to synthesize stochastic realizations of initial mass distributions consistent with known, and typically limited, site characterization data. Using a limited number of full scale simulations as training data, a statistical model is developed for predicting the distribution of contaminant mass (e.g., DNAPL saturation and aqueous concentration) across a heterogeneous domain. Monte-Carlo sampling methods are then employed, in conjunction with the trained statistical model, to generate realizations conditioned on measured borehole data. Performance of the statistical model is illustrated through comparisons of generated realizations with the `true' numerical simulations. Finally, we demonstrate how these realizations can be used to determine statistically optimal locations for further interrogation of the subsurface.
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Economic Impacts of Wind Turbine Development in U.S. Counties
DOE Office of Scientific and Technical Information (OSTI.GOV)
J., Brown; B., Hoen; E., Lantz
2011-07-25
The objective is to address the research question using post-project construction, county-level data, and econometric evaluation methods. Wind energy is expanding rapidly in the United States: Over the last 4 years, wind power has contributed approximately 35 percent of all new electric power capacity. Wind power plants are often developed in rural areas where local economic development impacts from the installation are projected, including land lease and property tax payments and employment growth during plant construction and operation. Wind energy represented 2.3 percent of the U.S. electricity supply in 2010, but studies show that penetrations of at least 20 percentmore » are feasible. Several studies have used input-output models to predict direct, indirect, and induced economic development impacts. These analyses have often been completed prior to project construction. Available studies have not yet investigated the economic development impacts of wind development at the county level using post-construction econometric evaluation methods. Analysis of county-level impacts is limited. However, previous county-level analyses have estimated operation-period employment at 0.2 to 0.6 jobs per megawatt (MW) of power installed and earnings at $9,000/MW to $50,000/MW. We find statistically significant evidence of positive impacts of wind development on county-level per capita income from the OLS and spatial lag models when they are applied to the full set of wind and non-wind counties. The total impact on annual per capita income of wind turbine development (measured in MW per capita) in the spatial lag model was $21,604 per MW. This estimate is within the range of values estimated in the literature using input-output models. OLS results for the wind-only counties and matched samples are similar in magnitude, but are not statistically significant at the 10-percent level. We find a statistically significant impact of wind development on employment in the OLS analysis for wind counties only, but not in the other models. Our estimates of employment impacts are not precise enough to assess the validity of employment impacts from input-output models applied in advance of wind energy project construction. The analysis provides empirical evidence of positive income effects at the county level from cumulative wind turbine development, consistent with the range of impacts estimated using input-output models. Employment impacts are less clear.« less
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Valid statistical inference methods for a case-control study with missing data.
Tian, Guo-Liang; Zhang, Chi; Jiang, Xuejun
2018-04-01
The main objective of this paper is to derive the valid sampling distribution of the observed counts in a case-control study with missing data under the assumption of missing at random by employing the conditional sampling method and the mechanism augmentation method. The proposed sampling distribution, called the case-control sampling distribution, can be used to calculate the standard errors of the maximum likelihood estimates of parameters via the Fisher information matrix and to generate independent samples for constructing small-sample bootstrap confidence intervals. Theoretical comparisons of the new case-control sampling distribution with two existing sampling distributions exhibit a large difference. Simulations are conducted to investigate the influence of the three different sampling distributions on statistical inferences. One finding is that the conclusion by the Wald test for testing independency under the two existing sampling distributions could be completely different (even contradictory) from the Wald test for testing the equality of the success probabilities in control/case groups under the proposed distribution. A real cervical cancer data set is used to illustrate the proposed statistical methods.
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Summary Statistics of Public TV Licensees, 1972.
ERIC Educational Resources Information Center
Lee, S. Young; Pedone, Ronald J.
Statistics in the areas of finance, employment, broadcast and production for public TV licenses in 1972 are given in this report. Tables in the area of finance are presented specifying total funds, income, direct operating costs, and capital expenditures. Employment is divided into all employment with subdivisions for full- and part-time employees…
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Some Aspects of Part-Time Work.
ERIC Educational Resources Information Center
Australian Dept. of Labour and National Service, Melbourne. Women's Bureau.
Of major importance to many married women seeking employment in Australia is the availability of part-time work. To describe the economic aspects of part-time employment for women, a review was made of statistics published by the Commonwealth Bureau of Census and Statistics and of research on part-time employment in overseas countries, and a…
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Tipping points in the arctic: eyeballing or statistical significance?
Carstensen, Jacob; Weydmann, Agata
2012-02-01
Arctic ecosystems have experienced and are projected to experience continued large increases in temperature and declines in sea ice cover. It has been hypothesized that small changes in ecosystem drivers can fundamentally alter ecosystem functioning, and that this might be particularly pronounced for Arctic ecosystems. We present a suite of simple statistical analyses to identify changes in the statistical properties of data, emphasizing that changes in the standard error should be considered in addition to changes in mean properties. The methods are exemplified using sea ice extent, and suggest that the loss rate of sea ice accelerated by factor of ~5 in 1996, as reported in other studies, but increases in random fluctuations, as an early warning signal, were observed already in 1990. We recommend to employ the proposed methods more systematically for analyzing tipping points to document effects of climate change in the Arctic.
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Development of hi-resolution regional climate scenarios in Japan by statistical downscaling
NASA Astrophysics Data System (ADS)
Dairaku, K.
2016-12-01
Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. To meet with the needs of stakeholders such as local governments, a Japan national project, Social Implementation Program on Climate Change Adaptation Technology (SI-CAT), launched in December 2015. It develops reliable technologies for near-term climate change predictions. Multi-model ensemble regional climate scenarios with 1km horizontal grid-spacing over Japan are developed by using CMIP5 GCMs and a statistical downscaling method to support various municipal adaptation measures appropriate for possible regional climate changes. A statistical downscaling method, Bias Correction Spatial Disaggregation (BCSD), is employed to develop regional climate scenarios based on CMIP5 RCP8.5 five GCMs (MIROC5, MRI-CGCM3, GFDL-CM3, CSIRO-Mk3-6-0, HadGEM2-ES) for the periods of historical climate (1970-2005) and near future climate (2020-2055). Downscaled variables are monthly/daily precipitation and temperature. File format is NetCDF4 (conforming to CF1.6, HDF5 compression). Developed regional climate scenarios will be expanded to meet with needs of stakeholders and interface applications to access and download the data are under developing. Statistical downscaling method is not necessary to well represent locally forced nonlinear phenomena, extreme events such as heavy rain, heavy snow, etc. To complement the statistical method, dynamical downscaling approach is also combined and applied to some specific regions which have needs of stakeholders. The added values of statistical/dynamical downscaling methods compared with parent GCMs are investigated.
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Bouda, Martin; Caplan, Joshua S.; Saiers, James E.
2016-01-01
Fractal dimension (FD), estimated by box-counting, is a metric used to characterize plant anatomical complexity or space-filling characteristic for a variety of purposes. The vast majority of published studies fail to evaluate the assumption of statistical self-similarity, which underpins the validity of the procedure. The box-counting procedure is also subject to error arising from arbitrary grid placement, known as quantization error (QE), which is strictly positive and varies as a function of scale, making it problematic for the procedure's slope estimation step. Previous studies either ignore QE or employ inefficient brute-force grid translations to reduce it. The goals of this study were to characterize the effect of QE due to translation and rotation on FD estimates, to provide an efficient method of reducing QE, and to evaluate the assumption of statistical self-similarity of coarse root datasets typical of those used in recent trait studies. Coarse root systems of 36 shrubs were digitized in 3D and subjected to box-counts. A pattern search algorithm was used to minimize QE by optimizing grid placement and its efficiency was compared to the brute force method. The degree of statistical self-similarity was evaluated using linear regression residuals and local slope estimates. QE, due to both grid position and orientation, was a significant source of error in FD estimates, but pattern search provided an efficient means of minimizing it. Pattern search had higher initial computational cost but converged on lower error values more efficiently than the commonly employed brute force method. Our representations of coarse root system digitizations did not exhibit details over a sufficient range of scales to be considered statistically self-similar and informatively approximated as fractals, suggesting a lack of sufficient ramification of the coarse root systems for reiteration to be thought of as a dominant force in their development. FD estimates did not characterize the scaling of our digitizations well: the scaling exponent was a function of scale. Our findings serve as a caution against applying FD under the assumption of statistical self-similarity without rigorously evaluating it first. PMID:26925073
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White, H; Racine, J
2001-01-01
We propose tests for individual and joint irrelevance of network inputs. Such tests can be used to determine whether an input or group of inputs "belong" in a particular model, thus permitting valid statistical inference based on estimated feedforward neural-network models. The approaches employ well-known statistical resampling techniques. We conduct a small Monte Carlo experiment showing that our tests have reasonable level and power behavior, and we apply our methods to examine whether there are predictable regularities in foreign exchange rates. We find that exchange rates do appear to contain information that is exploitable for enhanced point prediction, but the nature of the predictive relations evolves through time.
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Application of Taguchi methods to infrared window design
NASA Astrophysics Data System (ADS)
Osmer, Kurt A.; Pruszynski, Charles J.
1990-10-01
Dr. Genichi Taguchi, a prominent quality consultant, reduced a branch of statistics known as "Design of Experiments" to a cookbook methodology that can be employed by any competent engineer. This technique has been extensively employed by Japanese manufacturers, and is widely credited with helping them attain their current level of success in low cost, high quality product design and fabrication. Although this technique was originally put forth as a tool to streamline the determination of improved production processes, it can also be applied to a wide range of engineering problems. As part of an internal research project, this method of experimental design has been adapted to window trade studies and materials research. Two of these analyses are presented herein, and have been chosen to illustrate the breadth of applications to which the Taguchi method can be utilized.
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The Value of a Well-Being Improvement Strategy
Guo, Xiaobo; Coberley, Carter; Pope, James E.; Wells, Aaron
2015-01-01
Objective: The objective of this study is to evaluate effectiveness of a firm's 5-year strategy toward improving well-being while lowering health care costs amidst adoption of a Consumer-Driven Health Plan. Methods: Repeated measures statistical models were employed to test and quantify association between key demographic factors, employment type, year, individual well-being, and outcomes of health care costs, obesity, smoking, absence, and performance. Results: Average individual well-being trended upward by 13.5% over 5 years, monthly allowed amount health care costs declined 5.2% on average per person per year, and obesity and smoking rates declined by 4.8 and 9.7%, respectively, on average each year. The results show that individual well-being was significantly associated with each outcome and in the expected direction. Conclusions: The firm's strategy was successful in driving statistically significant, longitudinal well-being, biometric and productivity improvements, and health care cost reduction. PMID:26461860
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NASA Astrophysics Data System (ADS)
Herrera-Oliva, C. S.
2013-05-01
In this work we design and implement a method for the determination of precipitation forecast through the application of an elementary neuronal network (perceptron) to the statistical analysis of the precipitation reported in catalogues. The method is limited mainly by the catalogue length (and, in a smaller degree, by its accuracy). The method performance is measured using grading functions that evaluate a tradeoff between positive and negative aspects of performance. The method is applied to the Guadalupe Valley, Baja California, Mexico. Using consecutive intervals of dt=0.1 year, employing the data of several climatological stations situated in and surrounding this important wine industries zone. We evaluated the performance of different models of ANN, whose variables of entrance are the heights of precipitation. The results obtained were satisfactory, except for exceptional values of rain. Key words: precipitation forecast, artificial neural networks, statistical analysis
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Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M; Grün, Sonja
2017-01-01
Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis.
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Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M.; Grün, Sonja
2017-01-01
Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis. PMID:28596729
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Health Status After Cancer: Does It Matter Which Hospital You Belong To?
2010-01-01
Background Survival rates are widely used to compare the quality of cancer care. However, the extent to which cancer survivors regain full physical or cognitive functioning is not captured by this statistic. To address this concern we introduce post-diagnosis employment as a supplemental measure of the quality of cancer care. Methods This study is based on individual level data from the Norwegian Cancer Registry (n = 46,720) linked with data on labor market outcomes and socioeconomic status from Statistics Norway. We study variation across Norwegian hospital catchment areas (n = 55) with respect to survival and employment five years after cancer diagnosis. To handle the selection problem, we exploit the fact that cancer patients in Norway (until 2001) have been allocated to local hospitals based on their place of residence. Results We document substantial differences across catchment areas with respect to patients' post-diagnosis employment rates. Conventional quality indicators based on survival rates indicate smaller differences. The two sets of indicators are only moderately correlated. Conclusions This analysis shows that indicators based on survival and post-diagnosis employment may capture different parts of the health status distribution, and that using only one of them to capture quality of care may be insufficient. PMID:20626866
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Radioactivity Registered With a Small Number of Events
NASA Astrophysics Data System (ADS)
Zlokazov, Victor; Utyonkov, Vladimir
2018-02-01
The synthesis of superheavy elements asks for the analysis of low statistics experimental data presumably obeying an unknown exponential distribution and to take the decision whether they originate from one source or have admixtures. Here we analyze predictions following from non-parametrical methods, employing only such fundamental sample properties as the sample mean, the median and the mode.
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User Involvement in Designing a Survey of People Directly Employing Care and Support Workers
ERIC Educational Resources Information Center
Dixon, Josie; McNaughton-Nicholls, Carol; d'Ardenne, Joanna; Doyle-Francis, Melanie; Manthorpe, Jill
2013-01-01
User involvement in social care research has generally been the preserve of qualitative methodologies, while user involvement in quantitative research has tended to be limited by the assumed inflexibility of statistical designs and concerns that lay people may require specialist training to engage with quantitative methods. Using the example of…
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ERIC Educational Resources Information Center
Chance, Shannon Massie
2010-01-01
This descriptive, exploratory study focused on how institutions of higher education have used the United States Green Building Council's (USGBC) Leadership in Energy and Environmental Design (LEED[R]) Green Building Rating system. It employed statistical methods to assess which types of universities have used LEED, what ratings they earned, and…
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ERIC Educational Resources Information Center
Marson, Stephen M.; DeAngelis, Donna; Mittal, Nisha
2010-01-01
Objectives: The purpose of this article is to create transparency for the psychometric methods employed for the development of the Association of Social Work Boards' (ASWB) exams. Results: The article includes an assessment of the macro (political) and micro (statistical) environments of testing social work competence. The seven-step process used…
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Parental Socio-Economic Status as Correlate of Child Labour in Ile-Ife, Nigeria
ERIC Educational Resources Information Center
Elegbeleye, O. S.; Olasupo, M. O.
2012-01-01
This study investigated the relationship between parental socio-economic status and child labour practices in Ile-Ife, Nigeria. The study employed survey method to gather data from 200 parents which constituted the study population. Pearson Product Moment Correlation and t-test statistics were used for the data analyses. The outcome of the study…
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Statistics in the pharmacy literature.
Lee, Charlene M; Soin, Herpreet K; Einarson, Thomas R
2004-09-01
Research in statistical methods is essential for maintenance of high quality of the published literature. To update previous reports of the types and frequencies of statistical terms and procedures in research studies of selected professional pharmacy journals. We obtained all research articles published in 2001 in 6 journals: American Journal of Health-System Pharmacy, The Annals of Pharmacotherapy, Canadian Journal of Hospital Pharmacy, Formulary, Hospital Pharmacy, and Journal of the American Pharmaceutical Association. Two independent reviewers identified and recorded descriptive and inferential statistical terms/procedures found in the methods, results, and discussion sections of each article. Results were determined by tallying the total number of times, as well as the percentage, that each statistical term or procedure appeared in the articles. One hundred forty-four articles were included. Ninety-eight percent employed descriptive statistics; of these, 28% used only descriptive statistics. The most common descriptive statistical terms were percentage (90%), mean (74%), standard deviation (58%), and range (46%). Sixty-nine percent of the articles used inferential statistics, the most frequent being chi(2) (33%), Student's t-test (26%), Pearson's correlation coefficient r (18%), ANOVA (14%), and logistic regression (11%). Statistical terms and procedures were found in nearly all of the research articles published in pharmacy journals. Thus, pharmacy education should aim to provide current and future pharmacists with an understanding of the common statistical terms and procedures identified to facilitate the appropriate appraisal and consequential utilization of the information available in research articles.
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Fassihi, Afshin; Sabet, Razieh
2008-01-01
Quantitative relationships between molecular structure and p56lck protein tyrosine kinase inhibitory activity of 50 flavonoid derivatives are discovered by MLR and GA-PLS methods. Different QSAR models revealed that substituent electronic descriptors (SED) parameters have significant impact on protein tyrosine kinase inhibitory activity of the compounds. Between the two statistical methods employed, GA-PLS gave superior results. The resultant GA-PLS model had a high statistical quality (R2 = 0.74 and Q2 = 0.61) for predicting the activity of the inhibitors. The models proposed in the present work are more useful in describing QSAR of flavonoid derivatives as p56lck protein tyrosine kinase inhibitors than those provided previously. PMID:19325836
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Barnes, Stephen; Benton, H Paul; Casazza, Krista; Cooper, Sara J; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K; Renfrow, Matthew B; Tiwari, Hemant K
2016-08-01
Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
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NASA Astrophysics Data System (ADS)
Uchidate, M.
2018-09-01
In this study, with the aim of establishing a systematic knowledge on the impact of summit extraction methods and stochastic model selection in rough contact analysis, the contact area ratio (A r /A a ) obtained by statistical contact models with different summit extraction methods was compared with a direct simulation using the boundary element method (BEM). Fifty areal topography datasets with different autocorrelation functions in terms of the power index and correlation length were used for investigation. The non-causal 2D auto-regressive model which can generate datasets with specified parameters was employed in this research. Three summit extraction methods, Nayak’s theory, 8-point analysis and watershed segmentation, were examined. With regard to the stochastic model, Bhushan’s model and BGT (Bush-Gibson-Thomas) model were applied. The values of A r /A a from the stochastic models tended to be smaller than BEM. The discrepancy between the Bhushan’s model with the 8-point analysis and BEM was slightly smaller than Nayak’s theory. The results with the watershed segmentation was similar to those with the 8-point analysis. The impact of the Wolf pruning on the discrepancy between the stochastic analysis and BEM was not very clear. In case of the BGT model which employs surface gradients, good quantitative agreement against BEM was obtained when the Nayak’s bandwidth parameter was large.
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Drifter-based estimate of the 5 year dispersal of Fukushima-derived radionuclides
NASA Astrophysics Data System (ADS)
Rypina, I. I.; Jayne, S. R.; Yoshida, S.; Macdonald, A. M.; Buesseler, K.
2014-11-01
Employing some 40 years of North Pacific drifter-track observations from the Global Drifter Program database, statistics defining the horizontal spread of radionuclides from Fukushima nuclear power plant into the Pacific Ocean are investigated over a time scale of 5 years. A novel two-iteration method is employed to make the best use of the available drifter data. Drifter-based predictions of the temporal progression of the leading edge of the radionuclide distribution are compared to observed radionuclide concentrations from research surveys occupied in 2012 and 2013. Good agreement between the drifter-based predictions and the observations is found.
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Recommendations for research design of telehealth studies.
Chumbler, Neale R; Kobb, Rita; Brennan, David M; Rabinowitz, Terry
2008-11-01
Properly designed randomized controlled trials (RCTs) are the gold standard to use when examining the effectiveness of telehealth interventions on clinical outcomes. Some published telehealth studies have employed well-designed RCTs. However, such methods are not always feasible and practical in particular settings. This white paper addresses not only the need for properly designed RCTs, but also offers alternative research designs, such as quasi-experimental designs, and statistical techniques that can be employed to rigorously assess the effectiveness of telehealth studies. This paper further offers design and measurement recommendations aimed at and relevant to administrative decision-makers, policymakers, and practicing clinicians.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Gilbert, Richard O.; O'Brien, Robert F.; Wilson, John E.
2003-09-01
It may not be feasible to completely survey large tracts of land suspected of containing minefields. It is desirable to develop a characterization protocol that will confidently identify minefields within these large land tracts if they exist. Naturally, surveying areas of greatest concern and most likely locations would be necessary but will not provide the needed confidence that an unknown minefield had not eluded detection. Once minefields are detected, methods are needed to bound the area that will require detailed mine detection surveys. The US Department of Defense Strategic Environmental Research and Development Program (SERDP) is sponsoring the development ofmore » statistical survey methods and tools for detecting potential UXO targets. These methods may be directly applicable to demining efforts. Statistical methods are employed to determine the optimal geophysical survey transect spacing to have confidence of detecting target areas of a critical size, shape, and anomaly density. Other methods under development determine the proportion of a land area that must be surveyed to confidently conclude that there are no UXO present. Adaptive sampling schemes are also being developed as an approach for bounding the target areas. These methods and tools will be presented and the status of relevant research in this area will be discussed.« less
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Employing Introductory Statistics Students at "Stats Dairy"
ERIC Educational Resources Information Center
Keeling, Kellie
2011-01-01
To combat students' fear of statistics I employ my students at a fictional company, Stats Dairy, run by cows. Almost all examples used in the class notes, exercises, humour and exams use data "collected" from this company.
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Cotner, Bridget A; Njoh, Eni N; Trainor, John K; O'Connor, Danielle R; Barnett, Scott D; Ottomanelli, Lisa
2015-01-01
Return to work is associated with positive rehabilitation outcomes for persons with spinal cord injury (SCI); however, more research is needed on vocational support for persons with disabilities seeking employment. The association between facilitators and barriers of employment and employment outcome was examined among Veterans with SCI who participated in an evidence-based supported employment (EBSE) program. Using a mixed-methods, nested case-control design, data on facilitators and barriers to employment were extracted from qualitative interviews and quantitative measures administered in person to 34 Veterans with SCI who completed 12 months of an EBSE program. Participants who did (case) and did not (control) obtain competitive employment were matched on time since SCI. Facilitators and barriers to employment were compared between the groups. Self-report measures administered at baseline were examined; there were no statistically significant factors that predicted employment outcomes after 12 months of EBSE program participation. Qualitative interview data revealed program-specific facilitators and Veteran characteristics that were associated with employment outcomes. Qualitative data illustrate how the integration of the vocational rehabilitation specialist on the medical team is helpful for addressing identified disability-specific barriers, including practical matters such as transportation and caregiving schedules, to facilitate employment outcomes.
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Random matrices and condensation into multiple states
NASA Astrophysics Data System (ADS)
Sadeghi, Sina; Engel, Andreas
2018-03-01
In the present work, we employ methods from statistical mechanics of disordered systems to investigate static properties of condensation into multiple states in a general framework. We aim at showing how typical properties of random interaction matrices play a vital role in manifesting the statistics of condensate states. In particular, an analytical expression for the fraction of condensate states in the thermodynamic limit is provided that confirms the result of the mean number of coexisting species in a random tournament game. We also study the interplay between the condensation problem and zero-sum games with correlated random payoff matrices.
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Tolerancing aspheres based on manufacturing statistics
NASA Astrophysics Data System (ADS)
Wickenhagen, S.; Möhl, A.; Fuchs, U.
2017-11-01
A standard way of tolerancing optical elements or systems is to perform a Monte Carlo based analysis within a common optical design software package. Although, different weightings and distributions are assumed they are all counting on statistics, which usually means several hundreds or thousands of systems for reliable results. Thus, employing these methods for small batch sizes is unreliable, especially when aspheric surfaces are involved. The huge database of asphericon was used to investigate the correlation between the given tolerance values and measured data sets. The resulting probability distributions of these measured data were analyzed aiming for a robust optical tolerancing process.
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NASA Astrophysics Data System (ADS)
Shih, A. L.; Liu, J. Y. G.
2015-12-01
A median-based method and a z test are employed to find characteristics of seismo-ionospheric precursor (SIP) of the total electron content (TEC) in global ionosphere map (GIM) associated with 129 M≥5.5 earthquakes in Taiwan during 1999-2014. Results show that both negative and positive anomalies in the GIM TEC with the statistical significance of the z test appear few days before the earthquakes. The receiver operating characteristic (ROC) curve is further applied to see whether the SIPs exist in Taiwan.
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Campos-Filho, N; Franco, E L
1989-02-01
A frequent procedure in matched case-control studies is to report results from the multivariate unmatched analyses if they do not differ substantially from the ones obtained after conditioning on the matching variables. Although conceptually simple, this rule requires that an extensive series of logistic regression models be evaluated by both the conditional and unconditional maximum likelihood methods. Most computer programs for logistic regression employ only one maximum likelihood method, which requires that the analyses be performed in separate steps. This paper describes a Pascal microcomputer (IBM PC) program that performs multiple logistic regression by both maximum likelihood estimation methods, which obviates the need for switching between programs to obtain relative risk estimates from both matched and unmatched analyses. The program calculates most standard statistics and allows factoring of categorical or continuous variables by two distinct methods of contrast. A built-in, descriptive statistics option allows the user to inspect the distribution of cases and controls across categories of any given variable.
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Qualitative versus quantitative methods in psychiatric research.
Razafsha, Mahdi; Behforuzi, Hura; Azari, Hassan; Zhang, Zhiqun; Wang, Kevin K; Kobeissy, Firas H; Gold, Mark S
2012-01-01
Qualitative studies are gaining their credibility after a period of being misinterpreted as "not being quantitative." Qualitative method is a broad umbrella term for research methodologies that describe and explain individuals' experiences, behaviors, interactions, and social contexts. In-depth interview, focus groups, and participant observation are among the qualitative methods of inquiry commonly used in psychiatry. Researchers measure the frequency of occurring events using quantitative methods; however, qualitative methods provide a broader understanding and a more thorough reasoning behind the event. Hence, it is considered to be of special importance in psychiatry. Besides hypothesis generation in earlier phases of the research, qualitative methods can be employed in questionnaire design, diagnostic criteria establishment, feasibility studies, as well as studies of attitude and beliefs. Animal models are another area that qualitative methods can be employed, especially when naturalistic observation of animal behavior is important. However, since qualitative results can be researcher's own view, they need to be statistically confirmed, quantitative methods. The tendency to combine both qualitative and quantitative methods as complementary methods has emerged over recent years. By applying both methods of research, scientists can take advantage of interpretative characteristics of qualitative methods as well as experimental dimensions of quantitative methods.
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ERIC Educational Resources Information Center
Murray, Scott; Shillington, Richard
2012-01-01
Examining costs and savings associated with moving every Canadian with a Literacy Level 1 or 2 (on the international literacy scale) to Level 3, this analysis is based upon statistically matched data from the "2003 International Adult Literacy and Skills Survey and the 2005-2009 Surveys of Labour and Income Dynamics." The methods provide…
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A new method for determining the acid number of biodiesel based on coulometric titration.
Barbieri Gonzaga, Fabiano; Pereira Sobral, Sidney
2012-08-15
A new method is proposed for determining the acid number (AN) of biodiesel using coulometric titration with potentiometric detection, basically employing a potentiostat/galvanostat and an electrochemical cell containing a platinum electrode, a silver electrode, and a combination pH electrode. The method involves a sequential application of a constant current between the platinum (cathode) and silver (anode) electrodes, followed by measuring the potential of the combination pH electrode, using an isopropanol/water mixture as solvent and LiCl as the supporting electrolyte. A preliminary evaluation of the new method, using acetic acid for doping a biodiesel sample, showed an average recovery of 100.1%. Compared to a volumetric titration-based method for determining the AN of several biodiesel samples (ranging from about 0.18 to 0.95 mg g(-1)), the new method produced statistically similar results with better repeatability. Compared to other works reported in the literature, the new method presented an average repeatability up to 3.2 times better and employed a sample size up to 20 times smaller. Copyright © 2012 Elsevier B.V. All rights reserved.
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Souza, Erica Silva; Zaramello, Laize; Kuhnen, Carlos Alberto; Junkes, Berenice da Silva; Yunes, Rosendo Augusto; Heinzen, Vilma Edite Fonseca
2011-01-01
A new possibility for estimating the octanol/water coefficient (log P) was investigated using only one descriptor, the semi-empirical electrotopological index (ISET). The predictability of four octanol/water partition coefficient (log P) calculation models was compared using a set of 131 aliphatic organic compounds from five different classes. Log P values were calculated employing atomic-contribution methods, as in the Ghose/Crippen approach and its later refinement, AlogP; using fragmental methods through the ClogP method; and employing an approach considering the whole molecule using topological indices with the MlogP method. The efficiency and the applicability of the ISET in terms of calculating log P were demonstrated through good statistical quality (r > 0.99; s < 0.18), high internal stability and good predictive ability for an external group of compounds in the same order as the widely used models based on the fragmental method, ClogP, and the atomic contribution method, AlogP, which are among the most used methods of predicting log P. PMID:22072945
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Souza, Erica Silva; Zaramello, Laize; Kuhnen, Carlos Alberto; Junkes, Berenice da Silva; Yunes, Rosendo Augusto; Heinzen, Vilma Edite Fonseca
2011-01-01
A new possibility for estimating the octanol/water coefficient (log P) was investigated using only one descriptor, the semi-empirical electrotopological index (I(SET)). The predictability of four octanol/water partition coefficient (log P) calculation models was compared using a set of 131 aliphatic organic compounds from five different classes. Log P values were calculated employing atomic-contribution methods, as in the Ghose/Crippen approach and its later refinement, AlogP; using fragmental methods through the ClogP method; and employing an approach considering the whole molecule using topological indices with the MlogP method. The efficiency and the applicability of the I(SET) in terms of calculating log P were demonstrated through good statistical quality (r > 0.99; s < 0.18), high internal stability and good predictive ability for an external group of compounds in the same order as the widely used models based on the fragmental method, ClogP, and the atomic contribution method, AlogP, which are among the most used methods of predicting log P.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata
Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detectmore » changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.« less
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Lin, Yi-Jiun; Huang, I-Chun; Wang, Yun-Tung
2014-01-01
The aim of this exploratory study is to gain an understanding of the outcomes of home-based employment service programs for people with disabilities and their related factors in Taiwan. This study used survey method to collect 132 questionnaires. Descriptive and two-variable statistics including chi-square (χ(2)), independent sample t-test and analysis of variance were employed. The results found that 36.5% of the subjects improved their employment status and 75.8% of them improved in employability. Educational level and and vocational categories including "web page production", "e-commerce", "internet marketing", "on-line store" and "website set-up and management" were significantly "positively" associated with either of the two outcome indicators - change of employment status and employability. This study is the first evidence-based study about the outcomes of home-based employment service programs and their related factors for people with disabilities in Taiwan. The outcomes of the home-based employment service programs for people with disabilities were presented. Implications for Rehabilitation Home-based rehabilitation for people with disabilities can be effective. A programme of this kind supports participants in improving or gaining employment status as well as developing employability skills. Further consideration should be given to developing cost-effective home-based programmes and evaluating their effectiveness.
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NASA Astrophysics Data System (ADS)
Santiago-Lona, Cynthia V.; Hernández-Montes, María del Socorro; Mendoza-Santoyo, Fernando; Esquivel-Tejeda, Jesús
2018-02-01
The study and quantification of the tympanic membrane (TM) displacements add important information to advance the knowledge about the hearing process. A comparative statistical analysis between two commonly used demodulation methods employed to recover the optical phase in digital holographic interferometry, namely the fast Fourier transform and phase-shifting interferometry, is presented as applied to study thin tissues such as the TM. The resulting experimental TM surface displacement data are used to contrast both methods through the analysis of variance and F tests. Data are gathered when the TMs are excited with continuous sound stimuli at levels 86, 89 and 93 dB SPL for the frequencies of 800, 1300 and 2500 Hz under the same experimental conditions. The statistical analysis shows repeatability in z-direction displacements with a standard deviation of 0.086, 0.098 and 0.080 μm using the Fourier method, and 0.080, 0.104 and 0.055 μm with the phase-shifting method at a 95% confidence level for all frequencies. The precision and accuracy are evaluated by means of the coefficient of variation; the results with the Fourier method are 0.06143, 0.06125, 0.06154 and 0.06154, 0.06118, 0.06111 with phase-shifting. The relative error between both methods is 7.143, 6.250 and 30.769%. On comparing the measured displacements, the results indicate that there is no statistically significant difference between both methods for frequencies at 800 and 1300 Hz; however, errors and other statistics increase at 2500 Hz.
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Timpka, T; Lindqvist, K; Ekstrand, J; Karlsson, N
2005-01-01
Objectives: As physical activity is promoted as part of a healthy lifestyle, sports injuries are becoming an important public health concern in many countries. The objective of this study is to investigate rates of sports injuries before and after implementation of a WHO Safe Community program. Methods: Sports injury data were collected pre- and post-implementation from all individuals below 65 years of age during 1 year in the targeted municipality (population 41 000) and in a control municipality (population 26 000). A quasi-experimental design was used and individuals were divided into three categories based on household relationship to the labour market. Results: There were no differences between socio-economic categories regarding pre-intervention injury rates. No statistically significant post-intervention changes in injury rate were observed in the control area or among any females in either area. In the intervention area, a statistically significant (p = 0.011) decrease in injury rate was observed among male members of households in which the vocationally important member was employed. A statistically significant decrease was observed in injuries sustained in team sports among male members of households in which the vocationally important member was employed (p = 0.001) and among members of households in which the vocationally important member was self employed (p<0.05). Conclusions: The study indicates areas for improvement in the civic network based WHO Safe Community model. The results show that females, participants in individual sports, and members of non-vocationally active households were less affected by the interventions. These facts have to be addressed in planning future community based sports injury prevention programmes and their evaluations. PMID:15976170
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A novel data-driven learning method for radar target detection in nonstationary environments
Akcakaya, Murat; Nehorai, Arye; Sen, Satyabrata
2016-04-12
Most existing radar algorithms are developed under the assumption that the environment (clutter) is stationary. However, in practice, the characteristics of the clutter can vary enormously depending on the radar-operational scenarios. If unaccounted for, these nonstationary variabilities may drastically hinder the radar performance. Therefore, to overcome such shortcomings, we develop a data-driven method for target detection in nonstationary environments. In this method, the radar dynamically detects changes in the environment and adapts to these changes by learning the new statistical characteristics of the environment and by intelligibly updating its statistical detection algorithm. Specifically, we employ drift detection algorithms to detectmore » changes in the environment; incremental learning, particularly learning under concept drift algorithms, to learn the new statistical characteristics of the environment from the new radar data that become available in batches over a period of time. The newly learned environment characteristics are then integrated in the detection algorithm. Furthermore, we use Monte Carlo simulations to demonstrate that the developed method provides a significant improvement in the detection performance compared with detection techniques that are not aware of the environmental changes.« less
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Incorporating spatial context into statistical classification of multidimensional image data
NASA Technical Reports Server (NTRS)
Bauer, M. E. (Principal Investigator); Tilton, J. C.; Swain, P. H.
1981-01-01
Compound decision theory is employed to develop a general statistical model for classifying image data using spatial context. The classification algorithm developed from this model exploits the tendency of certain ground-cover classes to occur more frequently in some spatial contexts than in others. A key input to this contextural classifier is a quantitative characterization of this tendency: the context function. Several methods for estimating the context function are explored, and two complementary methods are recommended. The contextural classifier is shown to produce substantial improvements in classification accuracy compared to the accuracy produced by a non-contextural uniform-priors maximum likelihood classifier when these methods of estimating the context function are used. An approximate algorithm, which cuts computational requirements by over one-half, is presented. The search for an optimal implementation is furthered by an exploration of the relative merits of using spectral classes or information classes for classification and/or context function estimation.
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Inference of missing data and chemical model parameters using experimental statistics
NASA Astrophysics Data System (ADS)
Casey, Tiernan; Najm, Habib
2017-11-01
A method for determining the joint parameter density of Arrhenius rate expressions through the inference of missing experimental data is presented. This approach proposes noisy hypothetical data sets from target experiments and accepts those which agree with the reported statistics, in the form of nominal parameter values and their associated uncertainties. The data exploration procedure is formalized using Bayesian inference, employing maximum entropy and approximate Bayesian computation methods to arrive at a joint density on data and parameters. The method is demonstrated in the context of reactions in the H2-O2 system for predictive modeling of combustion systems of interest. Work supported by the US DOE BES CSGB. Sandia National Labs is a multimission lab managed and operated by Nat. Technology and Eng'g Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell Intl, for the US DOE NCSA under contract DE-NA-0003525.
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No-reference image quality assessment based on statistics of convolution feature maps
NASA Astrophysics Data System (ADS)
Lv, Xiaoxin; Qin, Min; Chen, Xiaohui; Wei, Guo
2018-04-01
We propose a Convolutional Feature Maps (CFM) driven approach to accurately predict image quality. Our motivation bases on the finding that the Nature Scene Statistic (NSS) features on convolution feature maps are significantly sensitive to distortion degree of an image. In our method, a Convolutional Neural Network (CNN) is trained to obtain kernels for generating CFM. We design a forward NSS layer which performs on CFM to better extract NSS features. The quality aware features derived from the output of NSS layer is effective to describe the distortion type and degree an image suffered. Finally, a Support Vector Regression (SVR) is employed in our No-Reference Image Quality Assessment (NR-IQA) model to predict a subjective quality score of a distorted image. Experiments conducted on two public databases demonstrate the promising performance of the proposed method is competitive to state of the art NR-IQA methods.
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Multi-classification of cell deformation based on object alignment and run length statistic.
Li, Heng; Liu, Zhiwen; An, Xing; Shi, Yonggang
2014-01-01
Cellular morphology is widely applied in digital pathology and is essential for improving our understanding of the basic physiological processes of organisms. One of the main issues of application is to develop efficient methods for cell deformation measurement. We propose an innovative indirect approach to analyze dynamic cell morphology in image sequences. The proposed approach considers both the cellular shape change and cytoplasm variation, and takes each frame in the image sequence into account. The cell deformation is measured by the minimum energy function of object alignment, which is invariant to object pose. Then an indirect analysis strategy is employed to overcome the limitation of gradual deformation by run length statistic. We demonstrate the power of the proposed approach with one application: multi-classification of cell deformation. Experimental results show that the proposed method is sensitive to the morphology variation and performs better than standard shape representation methods.
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The mean time-limited crash rate of stock price
NASA Astrophysics Data System (ADS)
Li, Yun-Xian; Li, Jiang-Cheng; Yang, Ai-Jun; Tang, Nian-Sheng
2017-05-01
In this article we investigate the occurrence of stock market crash in an economy cycle. Bayesian approach, Heston model and statistical-physical method are considered. Specifically, Heston model and an effective potential are employed to address the dynamic changes of stock price. Bayesian approach has been utilized to estimate the Heston model's unknown parameters. Statistical physical method is used to investigate the occurrence of stock market crash by calculating the mean time-limited crash rate. The real financial data from the Shanghai Composite Index is analyzed with the proposed methods. The mean time-limited crash rate of stock price is used to describe the occurrence of stock market crash in an economy cycle. The monotonous and nonmonotonous behaviors are observed in the behavior of the mean time-limited crash rate versus volatility of stock for various cross correlation coefficient between volatility and price. Also a minimum occurrence of stock market crash matching an optimal volatility is discovered.
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Neutron/Gamma-ray discrimination through measures of fit
DOE Office of Scientific and Technical Information (OSTI.GOV)
Amiri, Moslem; Prenosil, Vaclav; Cvachovec, Frantisek
2015-07-01
Statistical tests and their underlying measures of fit can be utilized to separate neutron/gamma-ray pulses in a mixed radiation field. In this article, first the application of a sample statistical test is explained. Fit measurement-based methods require true pulse shapes to be used as reference for discrimination. This requirement makes practical implementation of these methods difficult; typically another discrimination approach should be employed to capture samples of neutrons and gamma-rays before running the fit-based technique. In this article, we also propose a technique to eliminate this requirement. These approaches are applied to several sets of mixed neutron and gamma-ray pulsesmore » obtained through different digitizers using stilbene scintillator in order to analyze them and measure their discrimination quality. (authors)« less
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Exposure of the surgeon's hands to radiation during hand surgery procedures.
Żyluk, Andrzej; Puchalski, Piotr; Szlosser, Zbigniew; Dec, Paweł; Chrąchol, Joanna
2014-01-01
The objective of the study was to assess the time of exposure of the surgeon's hands to radiation and calculate of the equivalent dose absorbed during surgery of hand and wrist fractures with C-arm fluoroscope guidance. The necessary data specified by the objective of the study were acquired from operations of 287 patients with fractures of fingers, metacarpals, wrist bones and distal radius. 218 operations (78%) were percutaneous procedures and 60 (22%) were performed by open method. Data on the time of exposure and dose of radiation were acquired from the display of the fluoroscope, where they were automatically generated. These data were assigned to the individual patient, type of fracture, method of surgery and the operating surgeon. Fixations of distal radial fractures required longer times of radiation exposure (mean 61 sec.) than fractures of the wrist/metacarpals and fingers (38 and 32 sec., respectively), which was associated with absorption of significantly higher equivalent doses. Fixations of distal radial fractures by open method were associated with statistically significantly higher equivalent doses (0.41 mSv) than percutaneous procedures (0.3 mSv). Fixations of wrist and metacarpal bone fractures by open method were associated with lower equivalent doses (0.34 mSv) than percutaneous procedures (0.37 mSv),but the difference was not significant. Fixations of finger fractures by open method were associated with lower equivalent doses (0.13 mSv) than percutaneous procedures (0.24 mSv), the difference being statistically non-significant. Statistically significant differences in exposure time and equivalent doses were noted between 4 surgeons participating in the study, but no definitive relationship was found between these parameters and surgeons' employment time. 1. Hand surgery procedures under fluoroscopic guidance are associated with mild exposure of the surgeons' hands to radiation. 2. The equivalent dose was related to the type of fracture, operative technique and - to some degree - to the time of employment of the surgeon.
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A study of correlations between crude oil spot and futures markets: A rolling sample test
NASA Astrophysics Data System (ADS)
Liu, Li; Wan, Jieqiu
2011-10-01
In this article, we investigate the asymmetries of exceedance correlations and cross-correlations between West Texas Intermediate (WTI) spot and futures markets. First, employing the test statistic proposed by Hong et al. [Asymmetries in stock returns: statistical tests and economic evaluation, Review of Financial Studies 20 (2007) 1547-1581], we find that the exceedance correlations were overall symmetric. However, the results from rolling windows show that some occasional events could induce the significant asymmetries of the exceedance correlations. Second, employing the test statistic proposed by Podobnik et al. [Quantifying cross-correlations using local and global detrending approaches, European Physics Journal B 71 (2009) 243-250], we find that the cross-correlations were significant even for large lagged orders. Using the detrended cross-correlation analysis proposed by Podobnik and Stanley [Detrended cross-correlation analysis: a new method for analyzing two nonstationary time series, Physics Review Letters 100 (2008) 084102], we find that the cross-correlations were weakly persistent and were stronger between spot and futures contract with larger maturity. Our results from rolling sample test also show the apparent effects of the exogenous events. Additionally, we have some relevant discussions on the obtained evidence.
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[Application of statistics on chronic-diseases-relating observational research papers].
Hong, Zhi-heng; Wang, Ping; Cao, Wei-hua
2012-09-01
To study the application of statistics on Chronic-diseases-relating observational research papers which were recently published in the Chinese Medical Association Magazines, with influential index above 0.5. Using a self-developed criterion, two investigators individually participated in assessing the application of statistics on Chinese Medical Association Magazines, with influential index above 0.5. Different opinions reached an agreement through discussion. A total number of 352 papers from 6 magazines, including the Chinese Journal of Epidemiology, Chinese Journal of Oncology, Chinese Journal of Preventive Medicine, Chinese Journal of Cardiology, Chinese Journal of Internal Medicine and Chinese Journal of Endocrinology and Metabolism, were reviewed. The rate of clear statement on the following contents as: research objectives, t target audience, sample issues, objective inclusion criteria and variable definitions were 99.43%, 98.57%, 95.43%, 92.86% and 96.87%. The correct rates of description on quantitative and qualitative data were 90.94% and 91.46%, respectively. The rates on correctly expressing the results, on statistical inference methods related to quantitative, qualitative data and modeling were 100%, 95.32% and 87.19%, respectively. 89.49% of the conclusions could directly response to the research objectives. However, 69.60% of the papers did not mention the exact names of the study design, statistically, that the papers were using. 11.14% of the papers were in lack of further statement on the exclusion criteria. Percentage of the papers that could clearly explain the sample size estimation only taking up as 5.16%. Only 24.21% of the papers clearly described the variable value assignment. Regarding the introduction on statistical conduction and on database methods, the rate was only 24.15%. 18.75% of the papers did not express the statistical inference methods sufficiently. A quarter of the papers did not use 'standardization' appropriately. As for the aspect of statistical inference, the rate of description on statistical testing prerequisite was only 24.12% while 9.94% papers did not even employ the statistical inferential method that should be used. The main deficiencies on the application of Statistics used in papers related to Chronic-diseases-related observational research were as follows: lack of sample-size determination, variable value assignment description not sufficient, methods on statistics were not introduced clearly or properly, lack of consideration for pre-requisition regarding the use of statistical inferences.
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Cancer Survival Estimates Due to Non-Uniform Loss to Follow-Up and Non-Proportional Hazards
K M, Jagathnath Krishna; Mathew, Aleyamma; Sara George, Preethi
2017-06-25
Background: Cancer survival depends on loss to follow-up (LFU) and non-proportional hazards (non-PH). If LFU is high, survival will be over-estimated. If hazard is non-PH, rank tests will provide biased inference and Cox-model will provide biased hazard-ratio. We assessed the bias due to LFU and non-PH factor in cancer survival and provided alternate methods for unbiased inference and hazard-ratio. Materials and Methods: Kaplan-Meier survival were plotted using a realistic breast cancer (BC) data-set, with >40%, 5-year LFU and compared it using another BC data-set with <15%, 5-year LFU to assess the bias in survival due to high LFU. Age at diagnosis of the latter data set was used to illustrate the bias due to a non-PH factor. Log-rank test was employed to assess the bias in p-value and Cox-model was used to assess the bias in hazard-ratio for the non-PH factor. Schoenfeld statistic was used to test the non-PH of age. For the non-PH factor, we employed Renyi statistic for inference and time dependent Cox-model for hazard-ratio. Results: Five-year BC survival was 69% (SE: 1.1%) vs. 90% (SE: 0.7%) for data with low vs. high LFU respectively. Age (<45, 46-54 & >54 years) was a non-PH factor (p-value: 0.036). However, survival by age was significant (log-rank p-value: 0.026), but not significant using Renyi statistic (p=0.067). Hazard ratio (HR) for age using Cox-model was 1.012 (95%CI: 1.004 -1.019) and the same using time-dependent Cox-model was in the other direction (HR: 0.997; 95% CI: 0.997- 0.998). Conclusion: Over-estimated survival was observed for cancer with high LFU. Log-rank statistic and Cox-model provided biased results for non-PH factor. For data with non-PH factors, Renyi statistic and time dependent Cox-model can be used as alternate methods to obtain unbiased inference and estimates. Creative Commons Attribution License
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Assessing Continuous Operator Workload With a Hybrid Scaffolded Neuroergonomic Modeling Approach.
Borghetti, Brett J; Giametta, Joseph J; Rusnock, Christina F
2017-02-01
We aimed to predict operator workload from neurological data using statistical learning methods to fit neurological-to-state-assessment models. Adaptive systems require real-time mental workload assessment to perform dynamic task allocations or operator augmentation as workload issues arise. Neuroergonomic measures have great potential for informing adaptive systems, and we combine these measures with models of task demand as well as information about critical events and performance to clarify the inherent ambiguity of interpretation. We use machine learning algorithms on electroencephalogram (EEG) input to infer operator workload based upon Improved Performance Research Integration Tool workload model estimates. Cross-participant models predict workload of other participants, statistically distinguishing between 62% of the workload changes. Machine learning models trained from Monte Carlo resampled workload profiles can be used in place of deterministic workload profiles for cross-participant modeling without incurring a significant decrease in machine learning model performance, suggesting that stochastic models can be used when limited training data are available. We employed a novel temporary scaffold of simulation-generated workload profile truth data during the model-fitting process. A continuous workload profile serves as the target to train our statistical machine learning models. Once trained, the workload profile scaffolding is removed and the trained model is used directly on neurophysiological data in future operator state assessments. These modeling techniques demonstrate how to use neuroergonomic methods to develop operator state assessments, which can be employed in adaptive systems.
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Wang, Quanfu; Hou, Yanhua; Yan, Peisheng
2012-06-01
Statistical experimental designs were employed to optimize culture conditions for cold-adapted lysozyme production of a psychrophilic yeast Debaryomyces hansenii. In the first step of optimization using Plackett-Burman design (PBD), peptone, glucose, temperature, and NaCl were identified as significant variables that affected lysozyme production, the formula was further optimized using a four factor central composite design (CCD) to understand their interaction and to determine their optimal levels. A quadratic model was developed and validated. Compared to the initial level (18.8 U/mL), the maximum lysozyme production (65.8 U/mL) observed was approximately increased by 3.5-fold under the optimized conditions. Cold-adapted lysozymes production was first optimized using statistical experimental methods. A 3.5-fold enhancement of microbial lysozyme was gained after optimization. Such an improved production will facilitate the application of microbial lysozyme. Thus, D. hansenii lysozyme may be a good and new resource for the industrial production of cold-adapted lysozymes. © 2012 Institute of Food Technologists®
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Optimal application of Morrison's iterative noise removal for deconvolution. Appendices
NASA Technical Reports Server (NTRS)
Ioup, George E.; Ioup, Juliette W.
1987-01-01
Morrison's iterative method of noise removal, or Morrison's smoothing, is applied in a simulation to noise-added data sets of various noise levels to determine its optimum use. Morrison's smoothing is applied for noise removal alone, and for noise removal prior to deconvolution. For the latter, an accurate method is analyzed to provide confidence in the optimization. The method consists of convolving the data with an inverse filter calculated by taking the inverse discrete Fourier transform of the reciprocal of the transform of the response of the system. Various length filters are calculated for the narrow and wide Gaussian response functions used. Deconvolution of non-noisy data is performed, and the error in each deconvolution calculated. Plots are produced of error versus filter length; and from these plots the most accurate length filters determined. The statistical methodologies employed in the optimizations of Morrison's method are similar. A typical peak-type input is selected and convolved with the two response functions to produce the data sets to be analyzed. Both constant and ordinate-dependent Gaussian distributed noise is added to the data, where the noise levels of the data are characterized by their signal-to-noise ratios. The error measures employed in the optimizations are the L1 and L2 norms. Results of the optimizations for both Gaussians, both noise types, and both norms include figures of optimum iteration number and error improvement versus signal-to-noise ratio, and tables of results. The statistical variation of all quantities considered is also given.
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Estimating short-run and long-run interaction mechanisms in interictal state.
Ozkaya, Ata; Korürek, Mehmet
2010-04-01
We address the issue of analyzing electroencephalogram (EEG) from seizure patients in order to test, model and determine the statistical properties that distinguish between EEG states (interictal, pre-ictal, ictal) by introducing a new class of time series analysis methods. In the present study: firstly, we employ statistical methods to determine the non-stationary behavior of focal interictal epileptiform series within very short time intervals; secondly, for such intervals that are deemed non-stationary we suggest the concept of Autoregressive Integrated Moving Average (ARIMA) process modelling, well known in time series analysis. We finally address the queries of causal relationships between epileptic states and between brain areas during epileptiform activity. We estimate the interaction between different EEG series (channels) in short time intervals by performing Granger-causality analysis and also estimate such interaction in long time intervals by employing Cointegration analysis, both analysis methods are well-known in econometrics. Here we find: first, that the causal relationship between neuronal assemblies can be identified according to the duration and the direction of their possible mutual influences; second, that although the estimated bidirectional causality in short time intervals yields that the neuronal ensembles positively affect each other, in long time intervals neither of them is affected (increasing amplitudes) from this relationship. Moreover, Cointegration analysis of the EEG series enables us to identify whether there is a causal link from the interictal state to ictal state.
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Papanikolaou, Yannis; Tsoumakas, Grigorios; Laliotis, Manos; Markantonatos, Nikos; Vlahavas, Ioannis
2017-09-22
In this paper we present the approach that we employed to deal with large scale multi-label semantic indexing of biomedical papers. This work was mainly implemented within the context of the BioASQ challenge (2013-2017), a challenge concerned with biomedical semantic indexing and question answering. Our main contribution is a MUlti-Label Ensemble method (MULE) that incorporates a McNemar statistical significance test in order to validate the combination of the constituent machine learning algorithms. Some secondary contributions include a study on the temporal aspects of the BioASQ corpus (observations apply also to the BioASQ's super-set, the PubMed articles collection) and the proper parametrization of the algorithms used to deal with this challenging classification task. The ensemble method that we developed is compared to other approaches in experimental scenarios with subsets of the BioASQ corpus giving positive results. In our participation in the BioASQ challenge we obtained the first place in 2013 and the second place in the four following years, steadily outperforming MTI, the indexing system of the National Library of Medicine (NLM). The results of our experimental comparisons, suggest that employing a statistical significance test to validate the ensemble method's choices, is the optimal approach for ensembling multi-label classifiers, especially in contexts with many rare labels.
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A hybrid fault diagnosis approach based on mixed-domain state features for rotating machinery.
Xue, Xiaoming; Zhou, Jianzhong
2017-01-01
To make further improvement in the diagnosis accuracy and efficiency, a mixed-domain state features data based hybrid fault diagnosis approach, which systematically blends both the statistical analysis approach and the artificial intelligence technology, is proposed in this work for rolling element bearings. For simplifying the fault diagnosis problems, the execution of the proposed method is divided into three steps, i.e., fault preliminary detection, fault type recognition and fault degree identification. In the first step, a preliminary judgment about the health status of the equipment can be evaluated by the statistical analysis method based on the permutation entropy theory. If fault exists, the following two processes based on the artificial intelligence approach are performed to further recognize the fault type and then identify the fault degree. For the two subsequent steps, mixed-domain state features containing time-domain, frequency-domain and multi-scale features are extracted to represent the fault peculiarity under different working conditions. As a powerful time-frequency analysis method, the fast EEMD method was employed to obtain multi-scale features. Furthermore, due to the information redundancy and the submergence of original feature space, a novel manifold learning method (modified LGPCA) is introduced to realize the low-dimensional representations for high-dimensional feature space. Finally, two cases with 12 working conditions respectively have been employed to evaluate the performance of the proposed method, where vibration signals were measured from an experimental bench of rolling element bearing. The analysis results showed the effectiveness and the superiority of the proposed method of which the diagnosis thought is more suitable for practical application. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
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Education and Employment Patterns of Bioscientists. A Statistical Report.
ERIC Educational Resources Information Center
National Academy of Sciences - National Research Council, Washington, DC.
This report contains a compilation of manpower statistics describing the education and employment of bioscientists. The tables also include data from other major disciplines to allow for comparisons with other scientists and nonscientists. Bioscientists include those with degrees in anatomy, biochemistry, biophysics, genetics, microbiology,…
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OCCUPATIONS IN COLORADO. PART I, OUTLOOK BY INDUSTRIES.
ERIC Educational Resources Information Center
1966
CURRENT AND PROJECTED EMPLOYMENT STATISTICS ARE GIVEN FOR THE STATE AND FOR THE DENVER STANDARD METROPOLITAN STATISTICAL AREA WHICH INCLUDES ADAMS, ARAPAHOE, BOULDER, DENVER, AND JEFFERSON COUNTIES. DATA WERE OBTAINED FROM THE COLORADO DEPARTMENT OF EMPLOYMENT, DENVER RESEARCH INSTITUTE, U.S. CENSUS, UNIVERSITY OF COLORADO, MOUNTAIN STATES…
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Xu, Liping; Vagner, Josef; Alleti, Ramesh; Rao, Venkataramanarao; Jagadish, Bhumasamudram; Morse, David L; Hruby, Victor J; Gillies, Robert J; Mash, Eugene A
2010-04-15
A labeled variant of MSH(4), a tetrapeptide that binds to the human melanocortin 4 receptor (hMC4R) with low microM affinity, was prepared by solid-phase synthesis methods, purified, and characterized. The labeled ligand, Eu-DTPA-PEGO-His-dPhe-Arg-Trp-NH(2), exhibited a K(d) for hMC4R of 9.1+/-1.4 microM, approximately 10-fold lower affinity than the parental ligand. The labeled MSH(4) derivative was employed in a competitive binding assay to characterize the interactions of hMC4R with monovalent and divalent MSH(4) constructs derived from squalene. The results were compared with results from a similar assay that employed a more potent labeled ligand, Eu-DTPA-NDP-alpha-MSH. While results from the latter assay reflected only statistical effects, results from the former assay reflected a mixture of statistical, proximity, and/or cooperative binding effects. Copyright 2010 Elsevier Ltd. All rights reserved.
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Round-off errors in cutting plane algorithms based on the revised simplex procedure
NASA Technical Reports Server (NTRS)
Moore, J. E.
1973-01-01
This report statistically analyzes computational round-off errors associated with the cutting plane approach to solving linear integer programming problems. Cutting plane methods require that the inverse of a sequence of matrices be computed. The problem basically reduces to one of minimizing round-off errors in the sequence of inverses. Two procedures for minimizing this problem are presented, and their influence on error accumulation is statistically analyzed. One procedure employs a very small tolerance factor to round computed values to zero. The other procedure is a numerical analysis technique for reinverting or improving the approximate inverse of a matrix. The results indicated that round-off accumulation can be effectively minimized by employing a tolerance factor which reflects the number of significant digits carried for each calculation and by applying the reinversion procedure once to each computed inverse. If 18 significant digits plus an exponent are carried for each variable during computations, then a tolerance value of 0.1 x 10 to the minus 12th power is reasonable.
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Individual Fit Testing of Hearing Protection Devices Based on Microphone in Real Ear.
Biabani, Azam; Aliabadi, Mohsen; Golmohammadi, Rostam; Farhadian, Maryam
2017-12-01
Labeled noise reduction (NR) data presented by manufacturers are considered one of the main challenging issues for occupational experts in employing hearing protection devices (HPDs). This study aimed to determine the actual NR data of typical HPDs using the objective fit testing method with a microphone in real ear (MIRE) method. Five available commercially earmuff protectors were investigated in 30 workers exposed to reference noise source according to the standard method, ISO 11904-1. Personal attenuation rating (PAR) of the earmuffs was measured based on the MIRE method using a noise dosimeter (SVANTEK, model SV 102). The results showed that means of PAR of the earmuffs are from 49% to 86% of the nominal NR rating. The PAR values of earmuffs when a typical eyewear was worn differed statistically ( p < 0.05). It is revealed that a typical safety eyewear can reduce the mean of the PAR value by approximately 2.5 dB. The results also showed that measurements based on the MIRE method resulted in low variability. The variability in NR values between individuals, within individuals, and within earmuffs was not the statistically significant ( p > 0.05). This study could provide local individual fit data. Ergonomic aspects of the earmuffs and different levels of users experience and awareness can be considered the main factors affecting individual fitting compared with the laboratory condition for acquiring the labeled NR data. Based on the obtained fit testing results, the field application of MIRE can be employed for complementary studies in real workstations while workers perform their regular work duties.
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Modelling the effect of structural QSAR parameters on skin penetration using genetic programming
NASA Astrophysics Data System (ADS)
Chung, K. K.; Do, D. Q.
2010-09-01
In order to model relationships between chemical structures and biological effects in quantitative structure-activity relationship (QSAR) data, an alternative technique of artificial intelligence computing—genetic programming (GP)—was investigated and compared to the traditional method—statistical. GP, with the primary advantage of generating mathematical equations, was employed to model QSAR data and to define the most important molecular descriptions in QSAR data. The models predicted by GP agreed with the statistical results, and the most predictive models of GP were significantly improved when compared to the statistical models using ANOVA. Recently, artificial intelligence techniques have been applied widely to analyse QSAR data. With the capability of generating mathematical equations, GP can be considered as an effective and efficient method for modelling QSAR data.
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Statistical scaling of geometric characteristics in stochastically generated pore microstructures
Hyman, Jeffrey D.; Guadagnini, Alberto; Winter, C. Larrabee
2015-05-21
In this study, we analyze the statistical scaling of structural attributes of virtual porous microstructures that are stochastically generated by thresholding Gaussian random fields. Characterization of the extent at which randomly generated pore spaces can be considered as representative of a particular rock sample depends on the metrics employed to compare the virtual sample against its physical counterpart. Typically, comparisons against features and/patterns of geometric observables, e.g., porosity and specific surface area, flow-related macroscopic parameters, e.g., permeability, or autocorrelation functions are used to assess the representativeness of a virtual sample, and thereby the quality of the generation method. Here, wemore » rely on manifestations of statistical scaling of geometric observables which were recently observed in real millimeter scale rock samples [13] as additional relevant metrics by which to characterize a virtual sample. We explore the statistical scaling of two geometric observables, namely porosity (Φ) and specific surface area (SSA), of porous microstructures generated using the method of Smolarkiewicz and Winter [42] and Hyman and Winter [22]. Our results suggest that the method can produce virtual pore space samples displaying the symptoms of statistical scaling observed in real rock samples. Order q sample structure functions (statistical moments of absolute increments) of Φ and SSA scale as a power of the separation distance (lag) over a range of lags, and extended self-similarity (linear relationship between log structure functions of successive orders) appears to be an intrinsic property of the generated media. The width of the range of lags where power-law scaling is observed and the Hurst coefficient associated with the variables we consider can be controlled by the generation parameters of the method.« less
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Employment and Earnings. Volume 35, Number 3, March 1988.
ERIC Educational Resources Information Center
Employment and Earnings, 1988
1988-01-01
This document presents the following monthly statistical data for the population of United States: (1) employment status; (2) characteristics of the unemployed; (3) characteristics of the employed and their job categories; (4) seasonally adjusted employment and unemployment; (5) national employment; (6) employment in states and areas; (7) national…
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Relative mass distributions of neutron-rich thermally fissile nuclei within a statistical model
NASA Astrophysics Data System (ADS)
Kumar, Bharat; Kannan, M. T. Senthil; Balasubramaniam, M.; Agrawal, B. K.; Patra, S. K.
2017-09-01
We study the binary mass distribution for the recently predicted thermally fissile neutron-rich uranium and thorium nuclei using a statistical model. The level density parameters needed for the study are evaluated from the excitation energies of the temperature-dependent relativistic mean field formalism. The excitation energy and the level density parameter for a given temperature are employed in the convolution integral method to obtain the probability of the particular fragmentation. As representative cases, we present the results for the binary yields of 250U and 254Th. The relative yields are presented for three different temperatures: T =1 , 2, and 3 MeV.
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A Ground Flash Fraction Retrieval Algorithm for GLM
NASA Technical Reports Server (NTRS)
Koshak, William J.
2010-01-01
A Bayesian inversion method is introduced for retrieving the fraction of ground flashes in a set of N lightning observed by a satellite lightning imager (such as the Geostationary Lightning Mapper, GLM). An exponential model is applied as a physically reasonable constraint to describe the measured lightning optical parameter distributions. Population statistics (i.e., the mean and variance) are invoked to add additional constraints to the retrieval process. The Maximum A Posteriori (MAP) solution is employed. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The approach is feasible for N greater than 2000, and retrieval errors decrease as N is increased.
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Three Empirical Strategies for Teaching Statistics
ERIC Educational Resources Information Center
Marson, Stephen M.
2007-01-01
This paper employs a three-step process to analyze three empirically supported strategies for teaching statistics to BSW students. The strategies included: repetition, immediate feedback, and use of original data. First, each strategy is addressed through the literature. Second, the application of employing each of the strategies over the period…
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USDA-ARS?s Scientific Manuscript database
Cover: The electrospinning technique was employed to obtain conducting nanofibers based on polyaniline and poly(lactic acid). A statistical model was employed to describe how the process factors (solution concentration, applied voltage, and flow rate) govern the fiber dimensions. Nanofibers down to ...
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Regional frequency analysis of extreme rainfalls using partial L moments method
NASA Astrophysics Data System (ADS)
Zakaria, Zahrahtul Amani; Shabri, Ani
2013-07-01
An approach based on regional frequency analysis using L moments and LH moments are revisited in this study. Subsequently, an alternative regional frequency analysis using the partial L moments (PL moments) method is employed, and a new relationship for homogeneity analysis is developed. The results were then compared with those obtained using the method of L moments and LH moments of order two. The Selangor catchment, consisting of 37 sites and located on the west coast of Peninsular Malaysia, is chosen as a case study. PL moments for the generalized extreme value (GEV), generalized logistic (GLO), and generalized Pareto distributions were derived and used to develop the regional frequency analysis procedure. PL moment ratio diagram and Z test were employed in determining the best-fit distribution. Comparison between the three approaches showed that GLO and GEV distributions were identified as the suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation used for performance evaluation shows that the method of PL moments would outperform L and LH moments methods for estimation of large return period events.
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NASA Technical Reports Server (NTRS)
Engberg, Robert; Ooi, Teng K.
2004-01-01
New methods for structural health monitoring are being assessed, especially in high-performance, extreme environment, safety-critical applications. One such application is for composite cryogenic fuel tanks. The work presented here attempts to characterize and investigate the feasibility of using imbedded piezoelectric sensors to detect cracks and delaminations under cryogenic and ambient conditions. A variety of damage detection methods and different Sensors are employed in the different composite plate samples to aid in determining an optimal algorithm, sensor placement strategy, and type of imbedded sensor to use. Variations of frequency, impedance measurements, and pulse echoing techniques of the sensors are employed and compared. Statistical and analytic techniques are then used to determine which method is most desirable for a specific type of damage. These results are furthermore compared with previous work using externally mounted sensors. Results and optimized methods from this work can then be incorporated into a larger composite structure to validate and assess its structural health. This could prove to be important in the development and qualification of any 2" generation reusable launch vehicle using composites as a structural element.
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The impact of the 2007-2009 recession on workers' health coverage.
Fronstin, Paul
2011-04-01
IMPACT OF THE RECESSION: The 2007-2009 recession has taken its toll on the percentage of the population with employment-based health coverage. While, since 2000, there has been a slow erosion in the percentage of individuals under age 65 with employment-based health coverage, 2009 was the first year in which the percentage fell below 60 percent, and marked the largest one-year decline in coverage. FEWER WORKERS WITH COVERAGE: The percentage of workers with coverage through their own job fell from 53.2 percent in 2008 to 52 percent in 2009, a 2.4 percent decline in the likelihood that a worker has coverage through his or her own job. The percentage of workers with coverage as a dependent fell from 17 percent in 2008 to 16.3 percent in 2009, a 4.5 percent drop in the likelihood that a worker has coverage as a dependent. These declines occurred as the unemployment rate increased from an average of 5.8 percent in 2008 to 9.3 percent in 2009 (and reached a high of 10.1 percent during 2009). FIRM SIZE/INDUSTRY: The decline in the percentage of workers with coverage from their own job affected workers in private-sector firms of all sizes. Among public-sector workers, the decline from 73.4 percent to 73 percent was not statistically significant. Workers in all private-sector industries experienced a statistically significant decline in coverage between 2008 and 2009. HOURS WORKED: Full-time workers experienced a decline in coverage that was statistically significant while part-time workers did not. Among full-time workers, those employed full year experienced a statistically significant decline in coverage from their own job. Those employed full time but for only part of the year did not experience a statistically significant change in coverage. Among part-time workers, those employed full year experienced a statistically significant increase in the likelihood of having coverage in their own name, as did part-time workers employed for only part of the year. ANNUAL EARNINGS: The decline in the percentage of workers with coverage through their own job was limited to workers with lower annual earnings. Statistically significant declines were not found among any group of workers with annual earnings of at least $40,000. Workers with a high school education or less experienced a statistically significant decline in the likelihood of having coverage. Neither workers with a college degree nor those with a graduate degree experienced a statistically significant decline in coverage through their own job. Workers of all races experienced statistically significant declines in coverage between 2008 and 2009. Both men and women experienced a statistically significant decline in the percentage with health coverage through their own job. IMPACT OF STRUCTURAL CHANGES TO THE WORK FORCE: The movement of workers from the manufacturing industry to the service sector continued between 2008 and 2009. The percentage of workers employed on a full-time basis decreased while the percentage working part time increased. While there was an overall decline in the percentage of full-time workers, that decline was limited to workers employed full year. The percentage of workers employed on a full-time, part-year basis increased between 2008 and 2009. The distribution of workers by annual earnings shifted from middle-income workers to lower-income workers between 2008 and 2009.
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Statistical analysis of radioimmunoassay. In comparison with bioassay (in Japanese)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nakano, R.
1973-01-01
Using the data of RIA (radioimmunoassay), statistical procedures for dealing with two problems of the linearization of dose response curve and calculation of relative potency were described. There were three methods for linearization of dose response curve of RIA. In each method, the following parameters were shown on the horizontal and vertical axis: dose x, (B/T)/sup -1/; c/x + c, B/T (C: dose which makes B/T 50%); log x, logit B/T. Among them, the last method seems to be most practical. The statistical procedures for bioassay were employed for calculating the relative potency of unknown samples compared to the standardmore » samples from dose response curves of standand and unknown samples using regression coefficient. It is desirable that relative potency is calculated by plotting more than 5 points in the standard curve and plotting more than 2 points in unknow samples. For examining the statistical limit of precision of measuremert, LH activity of gonadotropin in urine was measured and relative potency, precision coefficient and the upper and lower limits of relative potency at 95% confidence limit were calculated. On the other hand, bioassay (by the ovarian ascorbic acid reduction method and anteriol lobe of prostate weighing method) was done in the same samples, and the precision was compared with that of RIA. In these examinations, the upper and lower limits of the relative potency at 95% confidence limit were near each other, while in bioassay, a considerable difference was observed between the upper and lower limits. The necessity of standardization and systematization of the statistical procedures for increasing the precision of RIA was pointed out. (JA)« less
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Statistics of dislocation pinning at localized obstacles
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dutta, A.; Bhattacharya, M., E-mail: mishreyee@vecc.gov.in; Barat, P.
2014-10-14
Pinning of dislocations at nanosized obstacles like precipitates, voids, and bubbles is a crucial mechanism in the context of phenomena like hardening and creep. The interaction between such an obstacle and a dislocation is often studied at fundamental level by means of analytical tools, atomistic simulations, and finite element methods. Nevertheless, the information extracted from such studies cannot be utilized to its maximum extent on account of insufficient information about the underlying statistics of this process comprising a large number of dislocations and obstacles in a system. Here, we propose a new statistical approach, where the statistics of pinning ofmore » dislocations by idealized spherical obstacles is explored by taking into account the generalized size-distribution of the obstacles along with the dislocation density within a three-dimensional framework. Starting with a minimal set of material parameters, the framework employs the method of geometrical statistics with a few simple assumptions compatible with the real physical scenario. The application of this approach, in combination with the knowledge of fundamental dislocation-obstacle interactions, has successfully been demonstrated for dislocation pinning at nanovoids in neutron irradiated type 316-stainless steel in regard to the non-conservative motion of dislocations. An interesting phenomenon of transition from rare pinning to multiple pinning regimes with increasing irradiation temperature is revealed.« less
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Statistical significance of trace evidence matches using independent physicochemical measurements
NASA Astrophysics Data System (ADS)
Almirall, Jose R.; Cole, Michael; Furton, Kenneth G.; Gettinby, George
1997-02-01
A statistical approach to the significance of glass evidence is proposed using independent physicochemical measurements and chemometrics. Traditional interpretation of the significance of trace evidence matches or exclusions relies on qualitative descriptors such as 'indistinguishable from,' 'consistent with,' 'similar to' etc. By performing physical and chemical measurements with are independent of one another, the significance of object exclusions or matches can be evaluated statistically. One of the problems with this approach is that the human brain is excellent at recognizing and classifying patterns and shapes but performs less well when that object is represented by a numerical list of attributes. Chemometrics can be employed to group similar objects using clustering algorithms and provide statistical significance in a quantitative manner. This approach is enhanced when population databases exist or can be created and the data in question can be evaluated given these databases. Since the selection of the variables used and their pre-processing can greatly influence the outcome, several different methods could be employed in order to obtain a more complete picture of the information contained in the data. Presently, we report on the analysis of glass samples using refractive index measurements and the quantitative analysis of the concentrations of the metals: Mg, Al, Ca, Fe, Mn, Ba, Sr, Ti and Zr. The extension of this general approach to fiber and paint comparisons also is discussed. This statistical approach should not replace the current interpretative approaches to trace evidence matches or exclusions but rather yields an additional quantitative measure. The lack of sufficient general population databases containing the needed physicochemical measurements and the potential for confusion arising from statistical analysis currently hamper this approach and ways of overcoming these obstacles are presented.
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Baker, Arthur W; Haridy, Salah; Salem, Joseph; Ilieş, Iulian; Ergai, Awatef O; Samareh, Aven; Andrianas, Nicholas; Benneyan, James C; Sexton, Daniel J; Anderson, Deverick J
2017-11-24
Traditional strategies for surveillance of surgical site infections (SSI) have multiple limitations, including delayed and incomplete outbreak detection. Statistical process control (SPC) methods address these deficiencies by combining longitudinal analysis with graphical presentation of data. We performed a pilot study within a large network of community hospitals to evaluate performance of SPC methods for detecting SSI outbreaks. We applied conventional Shewhart and exponentially weighted moving average (EWMA) SPC charts to 10 previously investigated SSI outbreaks that occurred from 2003 to 2013. We compared the results of SPC surveillance to the results of traditional SSI surveillance methods. Then, we analysed the performance of modified SPC charts constructed with different outbreak detection rules, EWMA smoothing factors and baseline SSI rate calculations. Conventional Shewhart and EWMA SPC charts both detected 8 of the 10 SSI outbreaks analysed, in each case prior to the date of traditional detection. Among detected outbreaks, conventional Shewhart chart detection occurred a median of 12 months prior to outbreak onset and 22 months prior to traditional detection. Conventional EWMA chart detection occurred a median of 7 months prior to outbreak onset and 14 months prior to traditional detection. Modified Shewhart and EWMA charts additionally detected several outbreaks earlier than conventional SPC charts. Shewhart and SPC charts had low false-positive rates when used to analyse separate control hospital SSI data. Our findings illustrate the potential usefulness and feasibility of real-time SPC surveillance of SSI to rapidly identify outbreaks and improve patient safety. Further study is needed to optimise SPC chart selection and calculation, statistical outbreak detection rules and the process for reacting to signals of potential outbreaks. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
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ERIC Educational Resources Information Center
Altonji, Joseph G.; Pierret, Charles R.
A statistical analysis was performed to test the hypothesis that, if profit-maximizing firms have limited information about the general productivity of new workers, they may choose to use easily observable characteristics such as years of education to discriminate statistically among workers. Information about employer learning was obtained by…
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Summary Statistics of CPB-Qualified Public Radio Stations, Fiscal Year 1972.
ERIC Educational Resources Information Center
Lee, S. Young; Pedone, Ronald J.
Statistics in the areas of finance, employment, and broadcast and production for CPB-qualified (Corporation for Public Broadcasting) public radio stations are given in this report. Tables in the area of finance are presented specifying total funds, income, direct operating costs, and capital expenditure. Employment is divided into all employment…
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A Study of Arizona Labor Market Demand Data for Vocational Education Planning.
ERIC Educational Resources Information Center
Gould, Albert W.; Manning, Doris E.
A study examined the project methodology used by the Bureau of Labor Statistics and the related projections made by the state employment security agencies. Findings from a literature review indicated that the system has steadily improved since 1979. Projections made from the Occupational Employment Statistics Surveys were remarkably accurate.…
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Conference Report on Youth Unemployment: Its Measurements and Meaning.
ERIC Educational Resources Information Center
Employment and Training Administration (DOL), Washington, DC.
Thirteen papers presented at a conference on employment statistics and youth are contained in this report. Reviewed are the problems of gathering, interpreting, and applying employment and unemployment data relating to youth. The titles of the papers are as follow: "Counting Youth: A Comparison of Youth Labor Force Statistics in the Current…
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Multivariate analysis in thoracic research.
Mengual-Macenlle, Noemí; Marcos, Pedro J; Golpe, Rafael; González-Rivas, Diego
2015-03-01
Multivariate analysis is based in observation and analysis of more than one statistical outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest. The development of multivariate methods emerged to analyze large databases and increasingly complex data. Since the best way to represent the knowledge of reality is the modeling, we should use multivariate statistical methods. Multivariate methods are designed to simultaneously analyze data sets, i.e., the analysis of different variables for each person or object studied. Keep in mind at all times that all variables must be treated accurately reflect the reality of the problem addressed. There are different types of multivariate analysis and each one should be employed according to the type of variables to analyze: dependent, interdependence and structural methods. In conclusion, multivariate methods are ideal for the analysis of large data sets and to find the cause and effect relationships between variables; there is a wide range of analysis types that we can use.
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Structural Health Monitoring of Composite Plates Under Ambient and Cryogenic Conditions
NASA Technical Reports Server (NTRS)
Engberg, Robert C.
2005-01-01
Methods for structural health monitoring are now being assessed, especially in high-performance, extreme environment, safety-critical applications. One such application is for composite cryogenic fuel tanks. The work presented here attempts to characterize and investigate the feasibility of using imbedded piezoelectric sensors to detect cracks and delaminations under cryogenic and ambient conditions. Different types of excitation and response signals and different sensors are employed in composite plate samples to aid in determining an optimal algorithm, sensor placement strategy, and type of imbedded sensor to use. Variations of frequency and high frequency chirps of the sensors are employed and compared. Statistical and analytic techniques are then used to determine which method is most desirable for a specific type of damage and operating environment. These results are furthermore compared with previous work using externally mounted sensors. More work is needed to accurately account for changes in temperature seen in these environments and be statistically significant. Sensor development and placement strategy are other areas of further work to make structural health monitoring more robust. Results from this and other work might then be incorporated into a larger composite structure to validate and assess its structural health. This could prove to be important in the development and qualification of any 2nd generation reusable launch vehicle using composites as a structural element.
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Traffic Sign Detection System for Locating Road Intersections and Roundabouts: The Chilean Case.
Villalón-Sepúlveda, Gabriel; Torres-Torriti, Miguel; Flores-Calero, Marco
2017-05-25
This paper presents a traffic sign detection method for signs close to road intersections and roundabouts, such as stop and yield (give way) signs. The proposed method relies on statistical templates built using color information for both segmentation and classification. The segmentation method uses the RGB-normalized (ErEgEb) color space for ROIs (Regions of Interest) generation based on a chromaticity filter, where templates at 10 scales are applied to the entire image. Templates consider the mean and standard deviation of normalized color of the traffic signs to build thresholding intervals where the expected color should lie for a given sign. The classification stage employs the information of the statistical templates over YCbCr and ErEgEb color spaces, for which the background has been previously removed by using a probability function that models the probability that the pixel corresponds to a sign given its chromaticity values. This work includes an analysis of the detection rate as a function of the distance between the vehicle and the sign. Such information is useful to validate the robustness of the approach and is often not included in the existing literature. The detection rates, as a function of distance, are compared to those of the well-known Viola-Jones method. The results show that for distances less than 48 m, the proposed method achieves a detection rate of 87.5 % and 95.4 % for yield and stop signs, respectively. For distances less than 30 m, the detection rate is 100 % for both signs. The Viola-Jones approach has detection rates below 20 % for distances between 30 and 48 m, and barely improves in the 20-30 m range with detection rates of up to 60 % . Thus, the proposed method provides a robust alternative for intersection detection that relies on statistical color-based templates instead of shape information. The experiments employed videos of traffic signs taken in several streets of Santiago, Chile, using a research platform implemented at the Robotics and Automation Laboratory of PUC to develop driver assistance systems.
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Traffic Sign Detection System for Locating Road Intersections and Roundabouts: The Chilean Case
Villalón-Sepúlveda, Gabriel; Torres-Torriti, Miguel; Flores-Calero, Marco
2017-01-01
This paper presents a traffic sign detection method for signs close to road intersections and roundabouts, such as stop and yield (give way) signs. The proposed method relies on statistical templates built using color information for both segmentation and classification. The segmentation method uses the RGB-normalized (ErEgEb) color space for ROIs (Regions of Interest) generation based on a chromaticity filter, where templates at 10 scales are applied to the entire image. Templates consider the mean and standard deviation of normalized color of the traffic signs to build thresholding intervals where the expected color should lie for a given sign. The classification stage employs the information of the statistical templates over YCbCr and ErEgEb color spaces, for which the background has been previously removed by using a probability function that models the probability that the pixel corresponds to a sign given its chromaticity values. This work includes an analysis of the detection rate as a function of the distance between the vehicle and the sign. Such information is useful to validate the robustness of the approach and is often not included in the existing literature. The detection rates, as a function of distance, are compared to those of the well-known Viola–Jones method. The results show that for distances less than 48 m, the proposed method achieves a detection rate of 87.5% and 95.4% for yield and stop signs, respectively. For distances less than 30 m, the detection rate is 100% for both signs. The Viola–Jones approach has detection rates below 20% for distances between 30 and 48 m, and barely improves in the 20–30 m range with detection rates of up to 60%. Thus, the proposed method provides a robust alternative for intersection detection that relies on statistical color-based templates instead of shape information. The experiments employed videos of traffic signs taken in several streets of Santiago, Chile, using a research platform implemented at the Robotics and Automation Laboratory of PUC to develop driver assistance systems. PMID:28587071
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Wuellner, Sara E.; Bonauto, David K.
2016-01-01
Background Little research has been done to identify reasons employers fail to report some injuries and illnesses in the Bureau of Labor Statistics Survey of Occupational Injuries and Illnesses (SOII). Methods We interviewed the 2012 Washington SOII respondents from establishments that had failed to report one or more eligible workers’ compensation claims in the SOII about their reasons for not reporting specific claims. Qualitative content analysis methods were used to identify themes and patterns in the responses. Results Non‐compliance with OSHA recordkeeping or SOII reporting instructions and data entry errors led to unreported claims. Some employers refused to include claims because they did not consider the injury to be work‐related, despite workers’ compensation eligibility. Participant responses brought the SOII eligibility of some claims into question. Conclusion Systematic and non‐systematic errors lead to SOII underreporting. Insufficient recordkeeping systems and limited knowledge of reporting requirements are barriers to accurate workplace injury records. Am. J. Ind. Med. 59:343–356, 2016. © 2016 The Authors. American Journal of Industrial Medicine Published by Wiley Periodicals, Inc. PMID:26970051
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Analysis strategies for longitudinal attachment loss data.
Beck, J D; Elter, J R
2000-02-01
The purpose of this invited review is to describe and discuss methods currently in use to quantify the progression of attachment loss in epidemiological studies of periodontal disease, and to make recommendations for specific analytic methods based upon the particular design of the study and structure of the data. The review concentrates on the definition of incident attachment loss (ALOSS) and its component parts; measurement issues including thresholds and regression to the mean; methods of accounting for longitudinal change, including changes in means, changes in proportions of affected sites, incidence density, the effect of tooth loss and reversals, and repeated events; statistical models of longitudinal change, including the incorporation of the time element, use of linear, logistic or Poisson regression or survival analysis, and statistical tests; site vs person level of analysis, including statistical adjustment for correlated data; the strengths and limitations of ALOSS data. Examples from the Piedmont 65+ Dental Study are used to illustrate specific concepts. We conclude that incidence density is the preferred methodology to use for periodontal studies with more than one period of follow-up and that the use of studies not employing methods for dealing with complex samples, correlated data, and repeated measures does not take advantage of our current understanding of the site- and person-level variables important in periodontal disease and may generate biased results.
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Analyzing Kernel Matrices for the Identification of Differentially Expressed Genes
Xia, Xiao-Lei; Xing, Huanlai; Liu, Xueqin
2013-01-01
One of the most important applications of microarray data is the class prediction of biological samples. For this purpose, statistical tests have often been applied to identify the differentially expressed genes (DEGs), followed by the employment of the state-of-the-art learning machines including the Support Vector Machines (SVM) in particular. The SVM is a typical sample-based classifier whose performance comes down to how discriminant samples are. However, DEGs identified by statistical tests are not guaranteed to result in a training dataset composed of discriminant samples. To tackle this problem, a novel gene ranking method namely the Kernel Matrix Gene Selection (KMGS) is proposed. The rationale of the method, which roots in the fundamental ideas of the SVM algorithm, is described. The notion of ''the separability of a sample'' which is estimated by performing -like statistics on each column of the kernel matrix, is first introduced. The separability of a classification problem is then measured, from which the significance of a specific gene is deduced. Also described is a method of Kernel Matrix Sequential Forward Selection (KMSFS) which shares the KMGS method's essential ideas but proceeds in a greedy manner. On three public microarray datasets, our proposed algorithms achieved noticeably competitive performance in terms of the B.632+ error rate. PMID:24349110
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Using complexity metrics with R-R intervals and BPM heart rate measures.
Wallot, Sebastian; Fusaroli, Riccardo; Tylén, Kristian; Jegindø, Else-Marie
2013-01-01
Lately, growing attention in the health sciences has been paid to the dynamics of heart rate as indicator of impending failures and for prognoses. Likewise, in social and cognitive sciences, heart rate is increasingly employed as a measure of arousal, emotional engagement and as a marker of interpersonal coordination. However, there is no consensus about which measurements and analytical tools are most appropriate in mapping the temporal dynamics of heart rate and quite different metrics are reported in the literature. As complexity metrics of heart rate variability depend critically on variability of the data, different choices regarding the kind of measures can have a substantial impact on the results. In this article we compare linear and non-linear statistics on two prominent types of heart beat data, beat-to-beat intervals (R-R interval) and beats-per-min (BPM). As a proof-of-concept, we employ a simple rest-exercise-rest task and show that non-linear statistics-fractal (DFA) and recurrence (RQA) analyses-reveal information about heart beat activity above and beyond the simple level of heart rate. Non-linear statistics unveil sustained post-exercise effects on heart rate dynamics, but their power to do so critically depends on the type data that is employed: While R-R intervals are very susceptible to non-linear analyses, the success of non-linear methods for BPM data critically depends on their construction. Generally, "oversampled" BPM time-series can be recommended as they retain most of the information about non-linear aspects of heart beat dynamics.
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Computer-Assisted Instruction in Statistics. Technical Report.
ERIC Educational Resources Information Center
Cooley, William W.
A paper given at a conference on statistical computation discussed teaching statistics with computers. It concluded that computer-assisted instruction is most appropriately employed in the numerical demonstration of statistical concepts, and for statistical laboratory instruction. The student thus learns simultaneously about the use of computers…
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Public health workforce employment in US public and private sectors.
Kennedy, Virginia C
2009-01-01
The purpose of this study was to describe the number and distribution of 26 administrative, professional, and technical public health occupations across the array of US governmental and nongovernmental industries. This study used data from the Occupational Employment Statistics program of the US Bureau of Labor Statistics. For each occupation of interest, the investigator determined the number of persons employed in 2006 in five industries and industry groups: government, nonprofit agencies, education, healthcare, and all other industries. Industry-specific employment profiles varied from one occupation to another. However, about three-fourths of all those engaged in these occupations worked in the private healthcare industry. Relatively few worked in nonprofit or educational settings, and less than 10 percent were employed in government agencies. The industry-specific distribution of public health personnel, particularly the proportion employed in the public sector, merits close monitoring. This study also highlights the need for a better understanding of the work performed by public health occupations in nongovernmental work settings. Finally, the Occupational Employment Statistics program has the potential to serve as an ongoing, national data collection system for public health workforce information. If this potential was realized, future workforce enumerations would not require primary data collection but rather could be accomplished using secondary data.
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Zhang, Ying; Wang, Yang; Wang, Zhi-Gang; Wang, Xi; Guo, Huo-Sheng; Meng, Dong-Fang; Wong, Po-Keung
2012-01-01
Statistical experimental designs provided by statistical analysis system (SAS) software were applied to optimize the fermentation medium composition for the production of atrazine-degrading Acinetobacter sp. DNS(32) in shake-flask cultures. A "Plackett-Burman Design" was employed to evaluate the effects of different components in the medium. The concentrations of corn flour, soybean flour, and K(2)HPO(4) were found to significantly influence Acinetobacter sp. DNS(32) production. The steepest ascent method was employed to determine the optimal regions of these three significant factors. Then, these three factors were optimized using central composite design of "response surface methodology." The optimized fermentation medium composition was composed as follows (g/L): corn flour 39.49, soybean flour 25.64, CaCO(3) 3, K(2)HPO(4) 3.27, MgSO(4)·7H(2)O 0.2, and NaCl 0.2. The predicted and verifiable values in the medium with optimized concentration of components in shake flasks experiments were 7.079 × 10(8) CFU/mL and 7.194 × 10(8) CFU/mL, respectively. The validated model can precisely predict the growth of atrazine-degraing bacterium, Acinetobacter sp. DNS(32).
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Bastistella, Luciane; Rousset, Patrick; Aviz, Antonio; Caldeira-Pires, Armando; Humbert, Gilles; Nogueira, Manoel
2018-02-09
New experimental techniques, as well as modern variants on known methods, have recently been employed to investigate the fundamental reactions underlying the oxidation of biochar. The purpose of this paper was to experimentally and statistically study how the relative humidity of air, mass, and particle size of four biochars influenced the adsorption of water and the increase in temperature. A random factorial design was employed using the intuitive statistical software Xlstat. A simple linear regression model and an analysis of variance with a pairwise comparison were performed. The experimental study was carried out on the wood of Quercus pubescens , Cyclobalanopsis glauca , Trigonostemon huangmosun , and Bambusa vulgaris , and involved five relative humidity conditions (22, 43, 75, 84, and 90%), two mass samples (0.1 and 1 g), and two particle sizes (powder and piece). Two response variables including water adsorption and temperature increase were analyzed and discussed. The temperature did not increase linearly with the adsorption of water. Temperature was modeled by nine explanatory variables, while water adsorption was modeled by eight. Five variables, including factors and their interactions, were found to be common to the two models. Sample mass and relative humidity influenced the two qualitative variables, while particle size and biochar type only influenced the temperature.
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Statistical imprints of CMB B -type polarization leakage in an incomplete sky survey analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Santos, Larissa; Wang, Kai; Hu, Yangrui
2017-01-01
One of the main goals of modern cosmology is to search for primordial gravitational waves by looking on their imprints in the B -type polarization in the cosmic microwave background radiation. However, this signal is contaminated by various sources, including cosmic weak lensing, foreground radiations, instrumental noises, as well as the E -to- B leakage caused by the partial sky surveys, which should be well understood to avoid the misinterpretation of the observed data. In this paper, we adopt the E / B decomposition method suggested by Smith in 2006, and study the imprints of E -to- B leakage residualsmore » in the constructed B -type polarization maps, B( n-circumflex ), by employing various statistical tools. We find that the effects of E -to- B leakage are negligible for the B-mode power spectrum, as well as the skewness and kurtosis analyses of B-maps. However, if employing the morphological statistical tools, including Minkowski functionals and/or Betti numbers, we find the effect of leakage can be detected at very high confidence level, which shows that in the morphological analysis, the leakage can play a significant role as a contaminant for measuring the primordial B -mode signal and must be taken into account for a correct explanation of the data.« less
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A wavelet-based statistical analysis of FMRI data: I. motivation and data distribution modeling.
Dinov, Ivo D; Boscardin, John W; Mega, Michael S; Sowell, Elizabeth L; Toga, Arthur W
2005-01-01
We propose a new method for statistical analysis of functional magnetic resonance imaging (fMRI) data. The discrete wavelet transformation is employed as a tool for efficient and robust signal representation. We use structural magnetic resonance imaging (MRI) and fMRI to empirically estimate the distribution of the wavelet coefficients of the data both across individuals and spatial locations. An anatomical subvolume probabilistic atlas is used to tessellate the structural and functional signals into smaller regions each of which is processed separately. A frequency-adaptive wavelet shrinkage scheme is employed to obtain essentially optimal estimations of the signals in the wavelet space. The empirical distributions of the signals on all the regions are computed in a compressed wavelet space. These are modeled by heavy-tail distributions because their histograms exhibit slower tail decay than the Gaussian. We discovered that the Cauchy, Bessel K Forms, and Pareto distributions provide the most accurate asymptotic models for the distribution of the wavelet coefficients of the data. Finally, we propose a new model for statistical analysis of functional MRI data using this atlas-based wavelet space representation. In the second part of our investigation, we will apply this technique to analyze a large fMRI dataset involving repeated presentation of sensory-motor response stimuli in young, elderly, and demented subjects.
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Dashtban, M; Balafar, Mohammadali
2017-03-01
Gene selection is a demanding task for microarray data analysis. The diverse complexity of different cancers makes this issue still challenging. In this study, a novel evolutionary method based on genetic algorithms and artificial intelligence is proposed to identify predictive genes for cancer classification. A filter method was first applied to reduce the dimensionality of feature space followed by employing an integer-coded genetic algorithm with dynamic-length genotype, intelligent parameter settings, and modified operators. The algorithmic behaviors including convergence trends, mutation and crossover rate changes, and running time were studied, conceptually discussed, and shown to be coherent with literature findings. Two well-known filter methods, Laplacian and Fisher score, were examined considering similarities, the quality of selected genes, and their influences on the evolutionary approach. Several statistical tests concerning choice of classifier, choice of dataset, and choice of filter method were performed, and they revealed some significant differences between the performance of different classifiers and filter methods over datasets. The proposed method was benchmarked upon five popular high-dimensional cancer datasets; for each, top explored genes were reported. Comparing the experimental results with several state-of-the-art methods revealed that the proposed method outperforms previous methods in DLBCL dataset. Copyright © 2017 Elsevier Inc. All rights reserved.
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Application of a data-mining method based on Bayesian networks to lesion-deficit analysis
NASA Technical Reports Server (NTRS)
Herskovits, Edward H.; Gerring, Joan P.
2003-01-01
Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.
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Structural equation modeling in pediatric psychology: overview and review of applications.
Nelson, Timothy D; Aylward, Brandon S; Steele, Ric G
2008-08-01
To describe the use of structural equation modeling (SEM) in the Journal of Pediatric Psychology (JPP) and to discuss the usefulness of SEM applications in pediatric psychology research. The use of SEM in JPP between 1997 and 2006 was examined and compared to leading journals in clinical psychology, clinical child psychology, and child development. SEM techniques were used in <4% of the empirical articles appearing in JPP between 1997 and 2006. SEM was used less frequently in JPP than in other clinically relevant journals over the past 10 years. However, results indicated a recent increase in JPP studies employing SEM techniques. SEM is an under-utilized class of techniques within pediatric psychology research, although investigations employing these methods are becoming more prevalent. Despite its infrequent use to date, SEM is a potentially useful tool for advancing pediatric psychology research with a number of advantages over traditional statistical methods.
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Validation of Physics Standardized Test Items
NASA Astrophysics Data System (ADS)
Marshall, Jill
2008-10-01
The Texas Physics Assessment Team (TPAT) examined the Texas Assessment of Knowledge and Skills (TAKS) to determine whether it is a valid indicator of physics preparation for future course work and employment, and of the knowledge and skills needed to act as an informed citizen in a technological society. We categorized science items from the 2003 and 2004 10th and 11th grade TAKS by content area(s) covered, knowledge and skills required to select the correct answer, and overall quality. We also analyzed a 5000 student sample of item-level results from the 2004 11th grade exam using standard statistical methods employed by test developers (factor analysis and Item Response Theory). Triangulation of our results revealed strengths and weaknesses of the different methods of analysis. The TAKS was found to be only weakly indicative of physics preparation and we make recommendations for increasing the validity of standardized physics testing..
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NASA Astrophysics Data System (ADS)
Zhang, Pei; Barlow, Robert; Masri, Assaad; Wang, Haifeng
2016-11-01
The mixture fraction and progress variable are often used as independent variables for describing turbulent premixed and non-premixed flames. There is a growing interest in using these two variables for describing partially premixed flames. The joint statistical distribution of the mixture fraction and progress variable is of great interest in developing models for partially premixed flames. In this work, we conduct predictive studies of the joint statistics of mixture fraction and progress variable in a series of piloted methane jet flames with inhomogeneous inlet flows. The employed models combine large eddy simulations with the Monte Carlo probability density function (PDF) method. The joint PDFs and marginal PDFs are examined in detail by comparing the model predictions and the measurements. Different presumed shapes of the joint PDFs are also evaluated.
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NASA Astrophysics Data System (ADS)
Nemoto, Mitsutaka; Nomura, Yukihiro; Hanaoka, Shohei; Masutani, Yoshitaka; Yoshikawa, Takeharu; Hayashi, Naoto; Yoshioka, Naoki; Ohtomo, Kuni
Anatomical point landmarks as most primitive anatomical knowledge are useful for medical image understanding. In this study, we propose a detection method for anatomical point landmark based on appearance models, which include gray-level statistical variations at point landmarks and their surrounding area. The models are built based on results of Principal Component Analysis (PCA) of sample data sets. In addition, we employed generative learning method by transforming ROI of sample data. In this study, we evaluated our method with 24 data sets of body trunk CT images and obtained 95.8 ± 7.3 % of the average sensitivity in 28 landmarks.
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NASA Astrophysics Data System (ADS)
Jaber, Abobaker M.
2014-12-01
Two nonparametric methods for prediction and modeling of financial time series signals are proposed. The proposed techniques are designed to handle non-stationary and non-linearity behave and to extract meaningful signals for reliable prediction. Due to Fourier Transform (FT), the methods select significant decomposed signals that will be employed for signal prediction. The proposed techniques developed by coupling Holt-winter method with Empirical Mode Decomposition (EMD) and it is Extending the scope of empirical mode decomposition by smoothing (SEMD). To show performance of proposed techniques, we analyze daily closed price of Kuala Lumpur stock market index.
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External Threat Risk Assessment Algorithm (ExTRAA)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Powell, Troy C.
Two risk assessment algorithms and philosophies have been augmented and combined to form a new algorit hm, the External Threat Risk Assessment Algorithm (ExTRAA), that allows for effective and statistically sound analysis of external threat sources in relation to individual attack methods . In addition to the attack method use probability and the attack method employment consequence, t he concept of defining threat sources is added to the risk assessment process. Sample data is tabulated and depicted in radar plots and bar graphs for algorithm demonstration purposes. The largest success of ExTRAA is its ability to visualize the kind ofmore » r isk posed in a given situation using the radar plot method.« less
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A study of speech emotion recognition based on hybrid algorithm
NASA Astrophysics Data System (ADS)
Zhu, Ju-xia; Zhang, Chao; Lv, Zhao; Rao, Yao-quan; Wu, Xiao-pei
2011-10-01
To effectively improve the recognition accuracy of the speech emotion recognition system, a hybrid algorithm which combines Continuous Hidden Markov Model (CHMM), All-Class-in-One Neural Network (ACON) and Support Vector Machine (SVM) is proposed. In SVM and ACON methods, some global statistics are used as emotional features, while in CHMM method, instantaneous features are employed. The recognition rate by the proposed method is 92.25%, with the rejection rate to be 0.78%. Furthermore, it obtains the relative increasing of 8.53%, 4.69% and 0.78% compared with ACON, CHMM and SVM methods respectively. The experiment result confirms the efficiency of distinguishing anger, happiness, neutral and sadness emotional states.
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Validation tools for image segmentation
NASA Astrophysics Data System (ADS)
Padfield, Dirk; Ross, James
2009-02-01
A large variety of image analysis tasks require the segmentation of various regions in an image. For example, segmentation is required to generate accurate models of brain pathology that are important components of modern diagnosis and therapy. While the manual delineation of such structures gives accurate information, the automatic segmentation of regions such as the brain and tumors from such images greatly enhances the speed and repeatability of quantifying such structures. The ubiquitous need for such algorithms has lead to a wide range of image segmentation algorithms with various assumptions, parameters, and robustness. The evaluation of such algorithms is an important step in determining their effectiveness. Therefore, rather than developing new segmentation algorithms, we here describe validation methods for segmentation algorithms. Using similarity metrics comparing the automatic to manual segmentations, we demonstrate methods for optimizing the parameter settings for individual cases and across a collection of datasets using the Design of Experiment framework. We then employ statistical analysis methods to compare the effectiveness of various algorithms. We investigate several region-growing algorithms from the Insight Toolkit and compare their accuracy to that of a separate statistical segmentation algorithm. The segmentation algorithms are used with their optimized parameters to automatically segment the brain and tumor regions in MRI images of 10 patients. The validation tools indicate that none of the ITK algorithms studied are able to outperform with statistical significance the statistical segmentation algorithm although they perform reasonably well considering their simplicity.
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Unicomb, Rachael; Colyvas, Kim; Harrison, Elisabeth; Hewat, Sally
2015-06-01
Case-study methodology studying change is often used in the field of speech-language pathology, but it can be criticized for not being statistically robust. Yet with the heterogeneous nature of many communication disorders, case studies allow clinicians and researchers to closely observe and report on change. Such information is valuable and can further inform large-scale experimental designs. In this research note, a statistical analysis for case-study data is outlined that employs a modification to the Reliable Change Index (Jacobson & Truax, 1991). The relationship between reliable change and clinical significance is discussed. Example data are used to guide the reader through the use and application of this analysis. A method of analysis is detailed that is suitable for assessing change in measures with binary categorical outcomes. The analysis is illustrated using data from one individual, measured before and after treatment for stuttering. The application of this approach to assess change in categorical, binary data has potential application in speech-language pathology. It enables clinicians and researchers to analyze results from case studies for their statistical and clinical significance. This new method addresses a gap in the research design literature, that is, the lack of analysis methods for noncontinuous data (such as counts, rates, proportions of events) that may be used in case-study designs.
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Wingate, Savanna; Sng, Eveleen; Loprinzi, Paul D
2018-01-01
Background: The purpose of this study was to evaluate the extent, if any, that the association between socio-ecological parameters and physical activity may be influenced by common method bias (CMB). Methods: This study took place between February and May of 2017 at a Southeastern University in the United States. A randomized controlled experiment was employed among 119 young adults.Participants were randomized into either group 1 (the group we attempted to minimize CMB)or group 2 (control group). In group 1, CMB was minimized via various procedural remedies,such as separating the measurement of predictor and criterion variables by introducing a time lag (temporal; 2 visits several days apart), creating a cover story (psychological), and approximating measures to have data collected in different media (computer-based vs. paper and pencil) and different locations to control method variance when collecting self-report measures from the same source. Socio-ecological parameters (self-efficacy; friend support; family support)and physical activity were self-reported. Results: Exercise self-efficacy was significantly associated with physical activity. This association (β = 0.74, 95% CI: 0.33-1.1; P = 0.001) was only observed in group 2 (control), but not in group 1 (experimental group) (β = 0.03; 95% CI: -0.57-0.63; P = 0.91). The difference in these coefficients (i.e., β = 0.74 vs. β = 0.03) was statistically significant (P = 0.04). Conclusion: Future research in this field, when feasible, may wish to consider employing procedural and statistical remedies to minimize CMB.
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Wingate, Savanna; Sng, Eveleen; Loprinzi, Paul D.
2018-01-01
Background: The purpose of this study was to evaluate the extent, if any, that the association between socio-ecological parameters and physical activity may be influenced by common method bias (CMB). Methods: This study took place between February and May of 2017 at a Southeastern University in the United States. A randomized controlled experiment was employed among 119 young adults.Participants were randomized into either group 1 (the group we attempted to minimize CMB)or group 2 (control group). In group 1, CMB was minimized via various procedural remedies,such as separating the measurement of predictor and criterion variables by introducing a time lag (temporal; 2 visits several days apart), creating a cover story (psychological), and approximating measures to have data collected in different media (computer-based vs. paper and pencil) and different locations to control method variance when collecting self-report measures from the same source. Socio-ecological parameters (self-efficacy; friend support; family support)and physical activity were self-reported. Results: Exercise self-efficacy was significantly associated with physical activity. This association (β = 0.74, 95% CI: 0.33-1.1; P = 0.001) was only observed in group 2 (control), but not in group 1 (experimental group) (β = 0.03; 95% CI: -0.57-0.63; P = 0.91). The difference in these coefficients (i.e., β = 0.74 vs. β = 0.03) was statistically significant (P = 0.04). Conclusion: Future research in this field, when feasible, may wish to consider employing procedural and statistical remedies to minimize CMB. PMID:29423361
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Modeling Ka-band low elevation angle propagation statistics
NASA Technical Reports Server (NTRS)
Russell, Thomas A.; Weinfield, John; Pearson, Chris; Ippolito, Louis J.
1995-01-01
The statistical variability of the secondary atmospheric propagation effects on satellite communications cannot be ignored at frequencies of 20 GHz or higher, particularly if the propagation margin allocation is such that link availability falls below 99 percent. The secondary effects considered in this paper are gaseous absorption, cloud absorption, and tropospheric scintillation; rain attenuation is the primary effect. Techniques and example results are presented for estimation of the overall combined impact of the atmosphere on satellite communications reliability. Statistical methods are employed throughout and the most widely accepted models for the individual effects are used wherever possible. The degree of correlation between the effects is addressed and some bounds on the expected variability in the combined effects statistics are derived from the expected variability in correlation. Example estimates are presented of combined effects statistics in the Washington D.C. area of 20 GHz and 5 deg elevation angle. The statistics of water vapor are shown to be sufficient for estimation of the statistics of gaseous absorption at 20 GHz. A computer model based on monthly surface weather is described and tested. Significant improvement in prediction of absorption extremes is demonstrated with the use of path weather data instead of surface data.
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ERIC Educational Resources Information Center
Loycano, Robert J.
The data presented in these tabulations are based on the 1976 National Science Foundation survey of scientific and engineering personnel employed at universities and colleges. The data are contained in 60 statistical tables organized under the following broad headings: trends; type of institution; field, employment status, control, educational…
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ERIC Educational Resources Information Center
National Center for Health Statistics (DHEW/PHS), Hyattsville, MD.
First in a series of statistical reports on personnel providing vision and eye care assistance, the report presents data collected by the Bureau of Census (geographic location, age, sex, education, type and place of employment, training, specialties, activities, and time spent at work) concerning opticians actively engaged in their profession…
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Statistical tools for transgene copy number estimation based on real-time PCR.
Yuan, Joshua S; Burris, Jason; Stewart, Nathan R; Mentewab, Ayalew; Stewart, C Neal
2007-11-01
As compared with traditional transgene copy number detection technologies such as Southern blot analysis, real-time PCR provides a fast, inexpensive and high-throughput alternative. However, the real-time PCR based transgene copy number estimation tends to be ambiguous and subjective stemming from the lack of proper statistical analysis and data quality control to render a reliable estimation of copy number with a prediction value. Despite the recent progresses in statistical analysis of real-time PCR, few publications have integrated these advancements in real-time PCR based transgene copy number determination. Three experimental designs and four data quality control integrated statistical models are presented. For the first method, external calibration curves are established for the transgene based on serially-diluted templates. The Ct number from a control transgenic event and putative transgenic event are compared to derive the transgene copy number or zygosity estimation. Simple linear regression and two group T-test procedures were combined to model the data from this design. For the second experimental design, standard curves were generated for both an internal reference gene and the transgene, and the copy number of transgene was compared with that of internal reference gene. Multiple regression models and ANOVA models can be employed to analyze the data and perform quality control for this approach. In the third experimental design, transgene copy number is compared with reference gene without a standard curve, but rather, is based directly on fluorescence data. Two different multiple regression models were proposed to analyze the data based on two different approaches of amplification efficiency integration. Our results highlight the importance of proper statistical treatment and quality control integration in real-time PCR-based transgene copy number determination. These statistical methods allow the real-time PCR-based transgene copy number estimation to be more reliable and precise with a proper statistical estimation. Proper confidence intervals are necessary for unambiguous prediction of trangene copy number. The four different statistical methods are compared for their advantages and disadvantages. Moreover, the statistical methods can also be applied for other real-time PCR-based quantification assays including transfection efficiency analysis and pathogen quantification.
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Plescia, Carolina; De Sio, Lorenzo
2018-01-01
Ecological inference refers to the study of individuals using aggregate data and it is used in an impressive number of studies; it is well known, however, that the study of individuals using group data suffers from an ecological fallacy problem (Robinson in Am Sociol Rev 15:351-357, 1950). This paper evaluates the accuracy of two recent methods, the Rosen et al. (Stat Neerl 55:134-156, 2001) and the Greiner and Quinn (J R Stat Soc Ser A (Statistics in Society) 172:67-81, 2009) and the long-standing Goodman's (Am Sociol Rev 18:663-664, 1953; Am J Sociol 64:610-625, 1959) method designed to estimate all cells of R × C tables simultaneously by employing exclusively aggregate data. To conduct these tests we leverage on extensive electoral data for which the true quantities of interest are known. In particular, we focus on examining the extent to which the confidence intervals provided by the three methods contain the true values. The paper also provides important guidelines regarding the appropriate contexts for employing these models.
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NASA Astrophysics Data System (ADS)
Giovanna, Vessia; Luca, Pisano; Carmela, Vennari; Mauro, Rossi; Mario, Parise
2016-01-01
This paper proposes an automated method for the selection of rainfall data (duration, D, and cumulated, E), responsible for shallow landslide initiation. The method mimics an expert person identifying D and E from rainfall records through a manual procedure whose rules are applied according to her/his judgement. The comparison between the two methods is based on 300 D-E pairs drawn from temporal rainfall data series recorded in a 30 days time-lag before the landslide occurrence. Statistical tests, employed on D and E samples considered both paired and independent values to verify whether they belong to the same population, show that the automated procedure is able to replicate the expert pairs drawn by the expert judgment. Furthermore, a criterion based on cumulated distribution functions (CDFs) is proposed to select the most related D-E pairs to the expert one among the 6 drawn from the coded procedure for tracing the empirical rainfall threshold line.
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Richardson, Keith; Denny, Richard; Hughes, Chris; Skilling, John; Sikora, Jacek; Dadlez, Michał; Manteca, Angel; Jung, Hye Ryung; Jensen, Ole Nørregaard; Redeker, Virginie; Melki, Ronald; Langridge, James I.; Vissers, Johannes P.C.
2013-01-01
A probability-based quantification framework is presented for the calculation of relative peptide and protein abundance in label-free and label-dependent LC-MS proteomics data. The results are accompanied by credible intervals and regulation probabilities. The algorithm takes into account data uncertainties via Poisson statistics modified by a noise contribution that is determined automatically during an initial normalization stage. Protein quantification relies on assignments of component peptides to the acquired data. These assignments are generally of variable reliability and may not be present across all of the experiments comprising an analysis. It is also possible for a peptide to be identified to more than one protein in a given mixture. For these reasons the algorithm accepts a prior probability of peptide assignment for each intensity measurement. The model is constructed in such a way that outliers of any type can be automatically reweighted. Two discrete normalization methods can be employed. The first method is based on a user-defined subset of peptides, while the second method relies on the presence of a dominant background of endogenous peptides for which the concentration is assumed to be unaffected. Normalization is performed using the same computational and statistical procedures employed by the main quantification algorithm. The performance of the algorithm will be illustrated on example data sets, and its utility demonstrated for typical proteomics applications. The quantification algorithm supports relative protein quantification based on precursor and product ion intensities acquired by means of data-dependent methods, originating from all common isotopically-labeled approaches, as well as label-free ion intensity-based data-independent methods. PMID:22871168
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Taguchi Approach to Design Optimization for Quality and Cost: An Overview
NASA Technical Reports Server (NTRS)
Unal, Resit; Dean, Edwin B.
1990-01-01
Calibrations to existing cost of doing business in space indicate that to establish human presence on the Moon and Mars with the Space Exploration Initiative (SEI) will require resources, felt by many, to be more than the national budget can afford. In order for SEI to succeed, we must actually design and build space systems at lower cost this time, even with tremendous increases in quality and performance requirements, such as extremely high reliability. This implies that both government and industry must change the way they do business. Therefore, new philosophy and technology must be employed to design and produce reliable, high quality space systems at low cost. In recognizing the need to reduce cost and improve quality and productivity, Department of Defense (DoD) and National Aeronautics and Space Administration (NASA) have initiated Total Quality Management (TQM). TQM is a revolutionary management strategy in quality assurance and cost reduction. TQM requires complete management commitment, employee involvement, and use of statistical tools. The quality engineering methods of Dr. Taguchi, employing design of experiments (DOE), is one of the most important statistical tools of TQM for designing high quality systems at reduced cost. Taguchi methods provide an efficient and systematic way to optimize designs for performance, quality, and cost. Taguchi methods have been used successfully in Japan and the United States in designing reliable, high quality products at low cost in such areas as automobiles and consumer electronics. However, these methods are just beginning to see application in the aerospace industry. The purpose of this paper is to present an overview of the Taguchi methods for improving quality and reducing cost, describe the current state of applications and its role in identifying cost sensitive design parameters.
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Statistical computation of tolerance limits
NASA Technical Reports Server (NTRS)
Wheeler, J. T.
1993-01-01
Based on a new theory, two computer codes were developed specifically to calculate the exact statistical tolerance limits for normal distributions within unknown means and variances for the one-sided and two-sided cases for the tolerance factor, k. The quantity k is defined equivalently in terms of the noncentral t-distribution by the probability equation. Two of the four mathematical methods employ the theory developed for the numerical simulation. Several algorithms for numerically integrating and iteratively root-solving the working equations are written to augment the program simulation. The program codes generate some tables of k's associated with the varying values of the proportion and sample size for each given probability to show accuracy obtained for small sample sizes.
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Statistics for laminar flamelet modeling
NASA Technical Reports Server (NTRS)
Cant, R. S.; Rutland, C. J.; Trouve, A.
1990-01-01
Statistical information required to support modeling of turbulent premixed combustion by laminar flamelet methods is extracted from a database of the results of Direct Numerical Simulation of turbulent flames. The simulations were carried out previously by Rutland (1989) using a pseudo-spectral code on a three dimensional mesh of 128 points in each direction. One-step Arrhenius chemistry was employed together with small heat release. A framework for the interpretation of the data is provided by the Bray-Moss-Libby model for the mean turbulent reaction rate. Probability density functions are obtained over surfaces of the constant reaction progress variable for the tangential strain rate and the principal curvature. New insights are gained which will greatly aid the development of modeling approaches.
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NASA Astrophysics Data System (ADS)
Huang, C. H.; Chen, Y. I.; Liu, J. Y. G.; Huang, Y. H.
2014-12-01
Statistical evidence of the Seismo-Ionospheric Precursors (SIPs) is reported by statistically investigating the relationship between the Total Electron Content (TEC) in Global Ionosphere Map (GIM) and 56 M≥6.0 earthquakes during 1998-2013 in China. A median-based method and a z test are employed to detect the overall earthquake signatures. It is found that a reduction of positive signatures and an enhancement of negative signatures appear simultaneously on 3-5 days prior to the earthquakes in China. Finally, receiver operating characteristic (ROC) curves are used to measure the power of TEC for predicting M≥6.0 earthquakes in China.
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ERIC Educational Resources Information Center
Florida State Dept. of Labor and Employment Security, Tallahassee.
This report analyzes projected changes in population, labor force, and employment by industry and occupation for Florida between 1995 and 2005. More than 50 charts and graphs provide statistics on the following: Florida's population, labor force 1975-2005; employment 1975-2005; industry employment 1995-2005; occupational employment (general);…
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A Low-Cost Method for Multiple Disease Prediction.
Bayati, Mohsen; Bhaskar, Sonia; Montanari, Andrea
Recently, in response to the rising costs of healthcare services, employers that are financially responsible for the healthcare costs of their workforce have been investing in health improvement programs for their employees. A main objective of these so called "wellness programs" is to reduce the incidence of chronic illnesses such as cardiovascular disease, cancer, diabetes, and obesity, with the goal of reducing future medical costs. The majority of these wellness programs include an annual screening to detect individuals with the highest risk of developing chronic disease. Once these individuals are identified, the company can invest in interventions to reduce the risk of those individuals. However, capturing many biomarkers per employee creates a costly screening procedure. We propose a statistical data-driven method to address this challenge by minimizing the number of biomarkers in the screening procedure while maximizing the predictive power over a broad spectrum of diseases. Our solution uses multi-task learning and group dimensionality reduction from machine learning and statistics. We provide empirical validation of the proposed solution using data from two different electronic medical records systems, with comparisons to a statistical benchmark.
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Design of off-statistics axial-flow fans by means of vortex law optimization
NASA Astrophysics Data System (ADS)
Lazari, Andrea; Cattanei, Andrea
2014-12-01
Off-statistics input data sets are common in axial-flow fans design and may easily result in some violation of the requirements of a good aerodynamic blade design. In order to circumvent this problem, in the present paper, a solution to the radial equilibrium equation is found which minimizes the outlet kinetic energy and fulfills the aerodynamic constraints, thus ensuring that the resulting blade has acceptable aerodynamic performance. The presented method is based on the optimization of a three-parameters vortex law and of the meridional channel size. The aerodynamic quantities to be employed as constraints are individuated and their suitable ranges of variation are proposed. The method is validated by means of a design with critical input data values and CFD analysis. Then, by means of systematic computations with different input data sets, some correlations and charts are obtained which are analogous to classic correlations based on statistical investigations on existing machines. Such new correlations help size a fan of given characteristics as well as study the feasibility of a given design.
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Wanderley, Miriam da Silva; Pereira, Lara Cristina Ribeiro; Santos, Carla Borges; Cunha, Vinícius Santos da; Neves, Mariam Viviane Jovino
2018-04-01
To analyze the association between the indirect methods of evaluating insulin resistance (IR) and blood pressure, anthropometric and biochemical parameters in a population of polycystic ovary syndrome (PCOS) patients. Cross-sectional study performed at the Hospital Universitário de Brasília (HUB, in the Portuguese acronym) involving PCOS patients diagnosed from January 2011 to January 2013. Four indirect methods, namely, fasting blood insulin level, fasting glucose/insulin ratio (G/I), homeostatic model-assessment-insulin resistance (HOMA-IR), and the quantitative insulin sensitivity check index (QUICKI), were used to obtain the IR diagnosis. The data were analyzed using the test of proportions, the Chi-square test, and Fisher exact test, when indicated. Out of the 83 patients assessed, aged 28.79 ± 5.85, IR was found in 51.81-66.2% of them using the G/I ratio and the QUICKI, respectively. The test of proportions did not show a significant difference between the methods analyzed. The proportion of IR diagnoses was statistically higher in obese women than in women with normal body mass index (BMI). We observed a statistically significant association between all the methods for diagnosing IR and BMI, waist circumference (WC) and lipid accumulation product (LAP). With regards to arterial hypertension (AH), we observed a significant association according to three methods, with the exception of the ratio G/I. Insulin resistance prevalence varied according to the diagnostic method employed, with no statistical difference between them. The proportion of IR diagnoses was statistically higher in obese women than in women with normal BMI. We observed a significant association between IR and WC, BMI, LAP, as well as dyslipidemia and AH in a high proportion of patients. Thieme Revinter Publicações Ltda Rio de Janeiro, Brazil.
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Game, Madhuri D.; Gabhane, K. B.; Sakarkar, D. M.
2010-01-01
A simple, accurate and precise spectrophotometric method has been developed for simultaneous estimation of clopidogrel bisulphate and aspirin by employing first order derivative zero crossing method. The first order derivative absorption at 232.5 nm (zero cross point of aspirin) was used for clopidogrel bisulphate and 211.3 nm (zero cross point of clopidogrel bisulphate) for aspirin.Both the drugs obeyed linearity in the concentration range of 5.0 μg/ml to 25.0 μg/ml (correlation coefficient r2<1). No interference was found between both determined constituents and those of matrix. The method was validated statistically and recovery studies were carried out to confirm the accuracy of the method. PMID:21969765
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Nonlinear dynamic analysis of voices before and after surgical excision of vocal polyps
NASA Astrophysics Data System (ADS)
Zhang, Yu; McGilligan, Clancy; Zhou, Liang; Vig, Mark; Jiang, Jack J.
2004-05-01
Phase space reconstruction, correlation dimension, and second-order entropy, methods from nonlinear dynamics, are used to analyze sustained vowels generated by patients before and after surgical excision of vocal polyps. Two conventional acoustic perturbation parameters, jitter and shimmer, are also employed to analyze voices before and after surgery. Presurgical and postsurgical analyses of jitter, shimmer, correlation dimension, and second-order entropy are statistically compared. Correlation dimension and second-order entropy show a statistically significant decrease after surgery, indicating reduced complexity and higher predictability of postsurgical voice dynamics. There is not a significant postsurgical difference in shimmer, although jitter shows a significant postsurgical decrease. The results suggest that jitter and shimmer should be applied to analyze disordered voices with caution; however, nonlinear dynamic methods may be useful for analyzing abnormal vocal function and quantitatively evaluating the effects of surgical excision of vocal polyps.
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Horsetail matching: a flexible approach to optimization under uncertainty
NASA Astrophysics Data System (ADS)
Cook, L. W.; Jarrett, J. P.
2018-04-01
It is important to design engineering systems to be robust with respect to uncertainties in the design process. Often, this is done by considering statistical moments, but over-reliance on statistical moments when formulating a robust optimization can produce designs that are stochastically dominated by other feasible designs. This article instead proposes a formulation for optimization under uncertainty that minimizes the difference between a design's cumulative distribution function and a target. A standard target is proposed that produces stochastically non-dominated designs, but the formulation also offers enough flexibility to recover existing approaches for robust optimization. A numerical implementation is developed that employs kernels to give a differentiable objective function. The method is applied to algebraic test problems and a robust transonic airfoil design problem where it is compared to multi-objective, weighted-sum and density matching approaches to robust optimization; several advantages over these existing methods are demonstrated.
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Mathematical leadership vision.
Hamburger, Y A
2000-11-01
This article is an analysis of a new type of leadership vision, the kind of vision that is becoming increasingly pervasive among leaders in the modern world. This vision appears to offer a new horizon, whereas, in fact it delivers to its target audience a finely tuned version of the already existing ambitions and aspirations of the target audience. The leader, with advisors, has examined the target audience and has used the results of extensive research and statistical methods concerning the group to form a picture of its members' lifestyles and values. On the basis of this information, the leader has built a "vision." The vision is intended to create an impression of a charismatic and transformational leader when, in fact, it is merely a response. The systemic, arithmetic, and statistical methods employed in this operation have led to the coining of the terms mathematical leader and mathematical vision.
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NASA Technical Reports Server (NTRS)
Green, Del L.; Walker, Eric L.; Everhart, Joel L.
2006-01-01
Minimization of uncertainty is essential to extend the usable range of the 15-psid Electronically Scanned Pressure [ESP) transducer measurements to the low free-stream static pressures found in hypersonic wind tunnels. Statistical characterization of environmental error sources inducing much of this uncertainty requires a well defined and controlled calibration method. Employing such a controlled calibration system, several studies were conducted that provide quantitative information detailing the required controls needed to minimize environmental and human induced error sources. Results of temperature, environmental pressure, over-pressurization, and set point randomization studies for the 15-psid transducers are presented along with a comparison of two regression methods using data acquired with both 0.36-psid and 15-psid transducers. Together these results provide insight into procedural and environmental controls required for long term high-accuracy pressure measurements near 0.01 psia in the hypersonic testing environment using 15-psid ESP transducers.
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NASA Technical Reports Server (NTRS)
Green, Del L.; Walker, Eric L.; Everhart, Joel L.
2006-01-01
Minimization of uncertainty is essential to extend the usable range of the 15-psid Electronically Scanned Pressure (ESP) transducer measurements to the low free-stream static pressures found in hypersonic wind tunnels. Statistical characterization of environmental error sources inducing much of this uncertainty requires a well defined and controlled calibration method. Employing such a controlled calibration system, several studies were conducted that provide quantitative information detailing the required controls needed to minimize environmental and human induced error sources. Results of temperature, environmental pressure, over-pressurization, and set point randomization studies for the 15-psid transducers are presented along with a comparison of two regression methods using data acquired with both 0.36-psid and 15-psid transducers. Together these results provide insight into procedural and environmental controls required for long term high-accuracy pressure measurements near 0.01 psia in the hypersonic testing environment using 15-psid ESP transducers.
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Computer Based Instruction in the U.S. Army’s Entry Level Enlisted Training.
1985-03-13
rosters with essential personal data, and graduation rosters with class standings and printed diplomas. The computer also managed the progress of the...discussion is presented in Chapter Three. Methods of Employment Course administration. In 1980 the US Army Research Center for Behaviorial and Social Studies...contained in Appendix C. Data Presentation All responses from the questionaires were coded for use by the Statistical Package for the Social Sciences
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Employment Implications of Informal Cancer Caregiving
de Moor, Janet S.; Dowling, Emily C.; Ekwueme, Donatus U.; Guy, Gery P.; Rodriguez, Juan; Virgo, Katherine S.; Han, Xuesong; Kent, Erin E.; Li, Chunyu; Litzelman, Kristen; McNeel, Timothy S.; Liu, Benmei; Yabroff, K. Robin
2016-01-01
Purpose Previous research describing how informal cancer caregiving impacts employment has been conducted in small samples or a single disease site. This paper provides population-based estimates of the effect of cancer caregiving on employment and characterizes the employment changes made by caregivers. Methods The sample comprised cancer survivors with a friend or family caregiver, participating in either the Medical Expenditure Panel Survey Experiences with Cancer Survivorship Survey (ECSS) (n=458) or the LIVESTRONG 2012 Survey for People Affected by Cancer (SPAC) (n=4,706). Descriptive statistics characterized the sample of survivors and their caregivers’ employment changes. Multivariable logistic regression identified predictors of caregivers’ extended employment changes, comprising time off and changes to hours, duties or employment status. Results Among survivors with an informal caregiver, 25% from the ECSS and 29% from the SPAC reported their caregivers made extended employment changes. Approximately 8% of survivors had caregivers who took time off from work lasting ≥ 2 months. Caregivers who made extended employment changes were more likely to care for survivors treated with chemotherapy or transplant; closer to diagnosis or end of treatment; who experienced functional limitations; and made work changes due to cancer themselves compared to caregivers who did not make extended employment changes. Conclusions Many informal cancer caregivers make employment changes to provide care during survivors’ treatment and recovery. Implications for cancer survivors This study describes cancer caregiving in a prevalent sample of cancer survivors, thereby reflecting the experiences of individuals with many different cancer types and places in the cancer treatment trajectory. PMID:27423439
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Mixture distributions of wind speed in the UAE
NASA Astrophysics Data System (ADS)
Shin, J.; Ouarda, T.; Lee, T. S.
2013-12-01
Wind speed probability distribution is commonly used to estimate potential wind energy. The 2-parameter Weibull distribution has been most widely used to characterize the distribution of wind speed. However, it is unable to properly model wind speed regimes when wind speed distribution presents bimodal and kurtotic shapes. Several studies have concluded that the Weibull distribution should not be used for frequency analysis of wind speed without investigation of wind speed distribution. Due to these mixture distributional characteristics of wind speed data, the application of mixture distributions should be further investigated in the frequency analysis of wind speed. A number of studies have investigated the potential wind energy in different parts of the Arabian Peninsula. Mixture distributional characteristics of wind speed were detected from some of these studies. Nevertheless, mixture distributions have not been employed for wind speed modeling in the Arabian Peninsula. In order to improve our understanding of wind energy potential in Arabian Peninsula, mixture distributions should be tested for the frequency analysis of wind speed. The aim of the current study is to assess the suitability of mixture distributions for the frequency analysis of wind speed in the UAE. Hourly mean wind speed data at 10-m height from 7 stations were used in the current study. The Weibull and Kappa distributions were employed as representatives of the conventional non-mixture distributions. 10 mixture distributions are used and constructed by mixing four probability distributions such as Normal, Gamma, Weibull and Extreme value type-one (EV-1) distributions. Three parameter estimation methods such as Expectation Maximization algorithm, Least Squares method and Meta-Heuristic Maximum Likelihood (MHML) method were employed to estimate the parameters of the mixture distributions. In order to compare the goodness-of-fit of tested distributions and parameter estimation methods for sample wind data, the adjusted coefficient of determination, Bayesian Information Criterion (BIC) and Chi-squared statistics were computed. Results indicate that MHML presents the best performance of parameter estimation for the used mixture distributions. In most of the employed 7 stations, mixture distributions give the best fit. When the wind speed regime shows mixture distributional characteristics, most of these regimes present the kurtotic statistical characteristic. Particularly, applications of mixture distributions for these stations show a significant improvement in explaining the whole wind speed regime. In addition, the Weibull-Weibull mixture distribution presents the best fit for the wind speed data in the UAE.
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Ensemble stacking mitigates biases in inference of synaptic connectivity.
Chambers, Brendan; Levy, Maayan; Dechery, Joseph B; MacLean, Jason N
2018-01-01
A promising alternative to directly measuring the anatomical connections in a neuronal population is inferring the connections from the activity. We employ simulated spiking neuronal networks to compare and contrast commonly used inference methods that identify likely excitatory synaptic connections using statistical regularities in spike timing. We find that simple adjustments to standard algorithms improve inference accuracy: A signing procedure improves the power of unsigned mutual-information-based approaches and a correction that accounts for differences in mean and variance of background timing relationships, such as those expected to be induced by heterogeneous firing rates, increases the sensitivity of frequency-based methods. We also find that different inference methods reveal distinct subsets of the synaptic network and each method exhibits different biases in the accurate detection of reciprocity and local clustering. To correct for errors and biases specific to single inference algorithms, we combine methods into an ensemble. Ensemble predictions, generated as a linear combination of multiple inference algorithms, are more sensitive than the best individual measures alone, and are more faithful to ground-truth statistics of connectivity, mitigating biases specific to single inference methods. These weightings generalize across simulated datasets, emphasizing the potential for the broad utility of ensemble-based approaches.
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NASA Astrophysics Data System (ADS)
Goldsworthy, M. J.
2012-10-01
One of the most useful tools for modelling rarefied hypersonic flows is the Direct Simulation Monte Carlo (DSMC) method. Simulator particle movement and collision calculations are combined with statistical procedures to model thermal non-equilibrium flow-fields described by the Boltzmann equation. The Macroscopic Chemistry Method for DSMC simulations was developed to simplify the inclusion of complex thermal non-equilibrium chemistry. The macroscopic approach uses statistical information which is calculated during the DSMC solution process in the modelling procedures. Here it is shown how inclusion of macroscopic information in models of chemical kinetics, electronic excitation, ionization, and radiation can enhance the capabilities of DSMC to model flow-fields where a range of physical processes occur. The approach is applied to the modelling of a 6.4 km/s nitrogen shock wave and results are compared with those from existing shock-tube experiments and continuum calculations. Reasonable agreement between the methods is obtained. The quality of the comparison is highly dependent on the set of vibrational relaxation and chemical kinetic parameters employed.
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ERIC Educational Resources Information Center
Lewis, Gary
The extent to which occupational staffing patterns change over time was examined in a study focusing on the Food and Kindred Products industry--Standard Industrial Classification (SIC) 20. Data were taken from the 1977 and 1980 Occupational Employment Statistics program coordinated by the United States Department of Labor Statistics. Actual 1980…
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ERIC Educational Resources Information Center
Reshad, Rosalind S.
One of six volumes summarizing through narrative and statistical tables data collected by the Equal Employment Opportunity Commission in its 1974 survey, this fifth volume details nationwide statistics on the employment status of minorities and women working in township governments. Data from 299 actual units of government in fourteen states were…
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ERIC Educational Resources Information Center
Skinner, Alice W.
One of six volumes summarizing through narrative and statistical tables data collected by the Equal Employment Opportunity Commission in its 1974 survey, this fourth volume details the employment status of minorities and women in municipal governments. Based on reports filed by 2,230 municipalities, statistics in this study are designed to…
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Carlier, Bouwine E; Schuring, Merel; Burdorf, Alex
2018-03-01
Purpose To evaluate the influence of an interdisciplinary re-employment programme on labour force participation and perceived health among unemployed persons with common mental health problems. In addition, the influence of entering paid employment on self-rated physical health and mental health was investigated. Methods In this quasi-experimental study with 2 years follow up, 869 persons were enrolled after referral to an interdisciplinary re-employment programme (n = 380) or regular re-employment programme (n = 489). The propensity score technique was used to account for observed differences between the intervention and control group. The intervention programme was provided by an interdisciplinary team, consisting of mental health care professionals as well as employment specialists. Mental health problems were addressed through cognitive counselling and individual tailored job-search support was provided by an employment professional. Primary outcome measures were paid employment and voluntary work. Secondary outcome measures were self-rated mental and physical health, measured by the Short Form 12 Health Survey, and anxiety and depressive symptoms, measured by the Kessler Psychological Distress Scale. Changes in labour force participation and health were examined with repeated-measures logistic regression analyses by the generalized estimating equations method. Results The interdisciplinary re-employment programme did not have a positive influence on entering employment or physical or mental health among unemployed persons with mental health problems. After 2 years, 10% of the participants of the intervention programme worked fulltime, compared to 4% of the participants of the usual programmes (adjusted OR 1.65). The observed differences in labour force participation were not statistically significant. However, among persons who entered paid employment, physical health improved (+16%) and anxiety and depressive symptoms decreased (-15%), whereas health remained unchanged among persons who continued to be unemployed. Conclusions Policies to improve population health should take into account that promoting paid employment may be an effective intervention to improve health. It is recommended to invest in interdisciplinary re-employment programmes with a first place and train approach.
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Recessions and Health: The Impact of Economic Trends on Air Pollution in California
2012-01-01
Objectives. I explored the hypothesis that economic activity has a significant impact on exposure to air pollution and ultimately human health. Methods. I used county-level employment statistics in California (1980–2000), along with major regulatory periods and other controlling factors, to estimate local concentrations of the coefficient of haze, carbon monoxide, and nitrogen dioxide using a mixed regression model approach. Results. The model explained between 33% and 48% of the variability in air pollution levels as estimated by the overall R2 values. The relationship between employment measures and air pollution was statistically significant, suggesting that air quality improves during economic downturns. Additionally, major air quality regulations played a significant role in reducing air pollution levels over the study period. Conclusions. This study provides important evidence of a role for the economy in understanding human exposure to environmental pollution. The evidence further suggests that the impact of environmental regulations are likely to be overstated when they occur during recessionary periods, and understated when they play out during periods of economic growth. PMID:22897522
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Estimation of In Situ Stresses with Hydro-Fracturing Tests and a Statistical Method
NASA Astrophysics Data System (ADS)
Lee, Hikweon; Ong, See Hong
2018-03-01
At great depths, where borehole-based field stress measurements such as hydraulic fracturing are challenging due to difficult downhole conditions or prohibitive costs, in situ stresses can be indirectly estimated using wellbore failures such as borehole breakouts and/or drilling-induced tensile failures detected by an image log. As part of such efforts, a statistical method has been developed in which borehole breakouts detected on an image log are used for this purpose (Song et al. in Proceedings on the 7th international symposium on in situ rock stress, 2016; Song and Chang in J Geophys Res Solid Earth 122:4033-4052, 2017). The method employs a grid-searching algorithm in which the least and maximum horizontal principal stresses ( S h and S H) are varied, and the corresponding simulated depth-related breakout width distribution as a function of the breakout angle ( θ B = 90° - half of breakout width) is compared to that observed along the borehole to determine a set of S h and S H having the lowest misfit between them. An important advantage of the method is that S h and S H can be estimated simultaneously in vertical wells. To validate the statistical approach, the method is applied to a vertical hole where a set of field hydraulic fracturing tests have been carried out. The stress estimations using the proposed method were found to be in good agreement with the results interpreted from the hydraulic fracturing test measurements.
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Confidence interval or p-value?: part 4 of a series on evaluation of scientific publications.
du Prel, Jean-Baptist; Hommel, Gerhard; Röhrig, Bernd; Blettner, Maria
2009-05-01
An understanding of p-values and confidence intervals is necessary for the evaluation of scientific articles. This article will inform the reader of the meaning and interpretation of these two statistical concepts. The uses of these two statistical concepts and the differences between them are discussed on the basis of a selective literature search concerning the methods employed in scientific articles. P-values in scientific studies are used to determine whether a null hypothesis formulated before the performance of the study is to be accepted or rejected. In exploratory studies, p-values enable the recognition of any statistically noteworthy findings. Confidence intervals provide information about a range in which the true value lies with a certain degree of probability, as well as about the direction and strength of the demonstrated effect. This enables conclusions to be drawn about the statistical plausibility and clinical relevance of the study findings. It is often useful for both statistical measures to be reported in scientific articles, because they provide complementary types of information.
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Assessment of environmental impacts part one. Intervention analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hipel, Keith William; Lettenmaier, Dennis P.; McLeod, A. Ian
The use of intervention analysis as a statistical method of gauging the effects of environmental changes is discussed. The Box-Jenkins model, serves as the basis for the intervention analysis methodology. Environmental studies of the Aswan Dam, the South Saskatchewan River, and a forest fire near the Pipers Hole River, Canada, are included as case studies in which intervention analysis was employed. Methods of data collection for intervention analysis are found to have a significant impact on model reliability; effective data collection processes for the Box-Jenkins model are provided. (15 graphs, 27 references, 2 tables)
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Li, Tingting; Cheng, Zhengguo; Zhang, Le
2017-01-01
Since they can provide a natural and flexible description of nonlinear dynamic behavior of complex system, Agent-based models (ABM) have been commonly used for immune system simulation. However, it is crucial for ABM to obtain an appropriate estimation for the key parameters of the model by incorporating experimental data. In this paper, a systematic procedure for immune system simulation by integrating the ABM and regression method under the framework of history matching is developed. A novel parameter estimation method by incorporating the experiment data for the simulator ABM during the procedure is proposed. First, we employ ABM as simulator to simulate the immune system. Then, the dimension-reduced type generalized additive model (GAM) is employed to train a statistical regression model by using the input and output data of ABM and play a role as an emulator during history matching. Next, we reduce the input space of parameters by introducing an implausible measure to discard the implausible input values. At last, the estimation of model parameters is obtained using the particle swarm optimization algorithm (PSO) by fitting the experiment data among the non-implausible input values. The real Influeza A Virus (IAV) data set is employed to demonstrate the performance of our proposed method, and the results show that the proposed method not only has good fitting and predicting accuracy, but it also owns favorable computational efficiency. PMID:29194393
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Li, Tingting; Cheng, Zhengguo; Zhang, Le
2017-12-01
Since they can provide a natural and flexible description of nonlinear dynamic behavior of complex system, Agent-based models (ABM) have been commonly used for immune system simulation. However, it is crucial for ABM to obtain an appropriate estimation for the key parameters of the model by incorporating experimental data. In this paper, a systematic procedure for immune system simulation by integrating the ABM and regression method under the framework of history matching is developed. A novel parameter estimation method by incorporating the experiment data for the simulator ABM during the procedure is proposed. First, we employ ABM as simulator to simulate the immune system. Then, the dimension-reduced type generalized additive model (GAM) is employed to train a statistical regression model by using the input and output data of ABM and play a role as an emulator during history matching. Next, we reduce the input space of parameters by introducing an implausible measure to discard the implausible input values. At last, the estimation of model parameters is obtained using the particle swarm optimization algorithm (PSO) by fitting the experiment data among the non-implausible input values. The real Influeza A Virus (IAV) data set is employed to demonstrate the performance of our proposed method, and the results show that the proposed method not only has good fitting and predicting accuracy, but it also owns favorable computational efficiency.
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The Spiral Arm Segments of the Galaxy within 3 kpc from the Sun: A Statistical Approach
DOE Office of Scientific and Technical Information (OSTI.GOV)
Griv, Evgeny; Jiang, Ing-Guey; Hou, Li-Gang, E-mail: griv@bgu.ac.il
As can be reasonably expected, upcoming large-scale APOGEE, GAIA, GALAH, LAMOST, and WEAVE stellar spectroscopic surveys will yield rather noisy Galactic distributions of stars. In view of the possibility of employing these surveys, our aim is to present a statistical method to extract information about the spiral structure of the Galaxy from currently available data, and to demonstrate the effectiveness of this method. The model differs from previous works studying how objects are distributed in space in its calculation of the statistical significance of the hypothesis that some of the objects are actually concentrated in a spiral. A statistical analysismore » of the distribution of cold dust clumps within molecular clouds, H ii regions, Cepheid stars, and open clusters in the nearby Galactic disk within 3 kpc from the Sun is carried out. As an application of the method, we obtain distances between the Sun and the centers of the neighboring Sagittarius arm segment, the Orion arm segment in which the Sun is located, and the Perseus arm segment. Pitch angles of the logarithmic spiral segments and their widths are also estimated. The hypothesis that the collected objects accidentally form spirals is refuted with almost 100% statistical confidence. We show that these four independent distributions of young objects lead to essentially the same results. We also demonstrate that our newly deduced values of the mean distances and pitch angles for the segments are not too far from those found recently by Reid et al. using VLBI-based trigonometric parallaxes of massive star-forming regions.« less
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Kwon, Deukwoo; Reis, Isildinha M
2015-08-12
When conducting a meta-analysis of a continuous outcome, estimated means and standard deviations from the selected studies are required in order to obtain an overall estimate of the mean effect and its confidence interval. If these quantities are not directly reported in the publications, they must be estimated from other reported summary statistics, such as the median, the minimum, the maximum, and quartiles. We propose a simulation-based estimation approach using the Approximate Bayesian Computation (ABC) technique for estimating mean and standard deviation based on various sets of summary statistics found in published studies. We conduct a simulation study to compare the proposed ABC method with the existing methods of Hozo et al. (2005), Bland (2015), and Wan et al. (2014). In the estimation of the standard deviation, our ABC method performs better than the other methods when data are generated from skewed or heavy-tailed distributions. The corresponding average relative error (ARE) approaches zero as sample size increases. In data generated from the normal distribution, our ABC performs well. However, the Wan et al. method is best for estimating standard deviation under normal distribution. In the estimation of the mean, our ABC method is best regardless of assumed distribution. ABC is a flexible method for estimating the study-specific mean and standard deviation for meta-analysis, especially with underlying skewed or heavy-tailed distributions. The ABC method can be applied using other reported summary statistics such as the posterior mean and 95 % credible interval when Bayesian analysis has been employed.
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Self-Regulated Learning Strategies in Relation with Statistics Anxiety
ERIC Educational Resources Information Center
Kesici, Sahin; Baloglu, Mustafa; Deniz, M. Engin
2011-01-01
Dealing with students' attitudinal problems related to statistics is an important aspect of statistics instruction. Employing the appropriate learning strategies may have a relationship with anxiety during the process of statistics learning. Thus, the present study investigated multivariate relationships between self-regulated learning strategies…
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Hydrologic Landscape Regionalisation Using Deductive Classification and Random Forests
Brown, Stuart C.; Lester, Rebecca E.; Versace, Vincent L.; Fawcett, Jonathon; Laurenson, Laurie
2014-01-01
Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents. PMID:25396410
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Hydrologic landscape regionalisation using deductive classification and random forests.
Brown, Stuart C; Lester, Rebecca E; Versace, Vincent L; Fawcett, Jonathon; Laurenson, Laurie
2014-01-01
Landscape classification and hydrological regionalisation studies are being increasingly used in ecohydrology to aid in the management and research of aquatic resources. We present a methodology for classifying hydrologic landscapes based on spatial environmental variables by employing non-parametric statistics and hybrid image classification. Our approach differed from previous classifications which have required the use of an a priori spatial unit (e.g. a catchment) which necessarily results in the loss of variability that is known to exist within those units. The use of a simple statistical approach to identify an appropriate number of classes eliminated the need for large amounts of post-hoc testing with different number of groups, or the selection and justification of an arbitrary number. Using statistical clustering, we identified 23 distinct groups within our training dataset. The use of a hybrid classification employing random forests extended this statistical clustering to an area of approximately 228,000 km2 of south-eastern Australia without the need to rely on catchments, landscape units or stream sections. This extension resulted in a highly accurate regionalisation at both 30-m and 2.5-km resolution, and a less-accurate 10-km classification that would be more appropriate for use at a continental scale. A smaller case study, of an area covering 27,000 km2, demonstrated that the method preserved the intra- and inter-catchment variability that is known to exist in local hydrology, based on previous research. Preliminary analysis linking the regionalisation to streamflow indices is promising suggesting that the method could be used to predict streamflow behaviour in ungauged catchments. Our work therefore simplifies current classification frameworks that are becoming more popular in ecohydrology, while better retaining small-scale variability in hydrology, thus enabling future attempts to explain and visualise broad-scale hydrologic trends at the scale of catchments and continents.
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van Mierlo, Trevor; Hyatt, Douglas; Ching, Andrew T
2016-01-01
Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality. The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality. Quarterly Gini coefficients were derived from four long-standing DHSNs. The combined data set included 625,736 posts that were generated from 15,181 actors over 18,671 days. The range of actors (8-2323), posts (29-28,684), and Gini coefficients (0.15-0.37) varied. Pearson correlations indicated statistically significant associations between number of actors and number of posts (0.527-0.835, p < .001), and Gini coefficients and number of posts (0.342-0.725, p < .001). However, the association between Gini coefficient and number of actors was only statistically significant for the addiction networks (0.619 and 0.276, p < .036). Linear regression models had positive but mixed R 2 results (0.333-0.527). In all four regression models, the association between Gini coefficient and posts was statistically significant ( t = 3.346-7.381, p < .002). However, unlike the Pearson correlations, the association between Gini coefficient and number of actors was only statistically significant in the two mental health networks ( t = -4.305 and -5.934, p < .000). The Gini coefficient is helpful in measuring shifts in DHSN inequality. However, as a standalone metric, the Gini coefficient does not indicate optimal numbers or ratios of actors to posts, or effective network engagement. Further, mixed-methods research investigating quantitative performance metrics is required.
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Propagation of a Free Flame in a Turbulent Gas Stream
NASA Technical Reports Server (NTRS)
Mickelsen, William R; Ernstein, Norman E
1956-01-01
Effective flame speeds of free turbulent flames were measured by photographic, ionization-gap, and photomultiplier-tube methods, and were found to have a statistical distribution attributed to the nature of the turbulent field. The effective turbulent flame speeds for the free flame were less than those previously measured for flames stabilized on nozzle burners, Bunsen burners, and bluff bodies. The statistical spread of the effective turbulent flame speeds was markedly wider in the lean and rich fuel-air-ratio regions, which might be attributed to the greater sensitivity of laminar flame speed to flame temperature in those regions. Values calculated from the turbulent free-flame-speed analysis proposed by Tucker apparently form upper limits for the statistical spread of free-flame-speed data. Hot-wire anemometer measurements of the longitudinal velocity fluctuation intensity and longitudinal correlation coefficient were made and were employed in the comparison of data and in the theoretical calculation of turbulent flame speed.
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A Multi-Class, Interdisciplinary Project Using Elementary Statistics
ERIC Educational Resources Information Center
Reese, Margaret
2012-01-01
This article describes a multi-class project that employs statistical computing and writing in a statistics class. Three courses, General Ecology, Meteorology, and Introductory Statistics, cooperated on a project for the EPA's Student Design Competition. The continuing investigation has also spawned several undergraduate research projects in…
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Williamson, Graham R
2003-11-01
This paper discusses the theoretical limitations of the use of random sampling and probability theory in the production of a significance level (or P-value) in nursing research. Potential alternatives, in the form of randomization tests, are proposed. Research papers in nursing, medicine and psychology frequently misrepresent their statistical findings, as the P-values reported assume random sampling. In this systematic review of studies published between January 1995 and June 2002 in the Journal of Advanced Nursing, 89 (68%) studies broke this assumption because they used convenience samples or entire populations. As a result, some of the findings may be questionable. The key ideas of random sampling and probability theory for statistical testing (for generating a P-value) are outlined. The result of a systematic review of research papers published in the Journal of Advanced Nursing is then presented, showing how frequently random sampling appears to have been misrepresented. Useful alternative techniques that might overcome these limitations are then discussed. REVIEW LIMITATIONS: This review is limited in scope because it is applied to one journal, and so the findings cannot be generalized to other nursing journals or to nursing research in general. However, it is possible that other nursing journals are also publishing research articles based on the misrepresentation of random sampling. The review is also limited because in several of the articles the sampling method was not completely clearly stated, and in this circumstance a judgment has been made as to the sampling method employed, based on the indications given by author(s). Quantitative researchers in nursing should be very careful that the statistical techniques they use are appropriate for the design and sampling methods of their studies. If the techniques they employ are not appropriate, they run the risk of misinterpreting findings by using inappropriate, unrepresentative and biased samples.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Moses, Alan M.; Chiang, Derek Y.; Pollard, Daniel A.
2004-10-28
We introduce a method (MONKEY) to identify conserved transcription-factor binding sites in multispecies alignments. MONKEY employs probabilistic models of factor specificity and binding site evolution, on which basis we compute the likelihood that putative sites are conserved and assign statistical significance to each hit. Using genomes from the genus Saccharomyces, we illustrate how the significance of real sites increases with evolutionary distance and explore the relationship between conservation and function.
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Graph reconstruction using covariance-based methods.
Sulaimanov, Nurgazy; Koeppl, Heinz
2016-12-01
Methods based on correlation and partial correlation are today employed in the reconstruction of a statistical interaction graph from high-throughput omics data. These dedicated methods work well even for the case when the number of variables exceeds the number of samples. In this study, we investigate how the graphs extracted from covariance and concentration matrix estimates are related by using Neumann series and transitive closure and through discussing concrete small examples. Considering the ideal case where the true graph is available, we also compare correlation and partial correlation methods for large realistic graphs. In particular, we perform the comparisons with optimally selected parameters based on the true underlying graph and with data-driven approaches where the parameters are directly estimated from the data.
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Performance comparison of LUR and OK in PM2.5 concentration mapping: a multidimensional perspective
Zou, Bin; Luo, Yanqing; Wan, Neng; Zheng, Zhong; Sternberg, Troy; Liao, Yilan
2015-01-01
Methods of Land Use Regression (LUR) modeling and Ordinary Kriging (OK) interpolation have been widely used to offset the shortcomings of PM2.5 data observed at sparse monitoring sites. However, traditional point-based performance evaluation strategy for these methods remains stagnant, which could cause unreasonable mapping results. To address this challenge, this study employs ‘information entropy’, an area-based statistic, along with traditional point-based statistics (e.g. error rate, RMSE) to evaluate the performance of LUR model and OK interpolation in mapping PM2.5 concentrations in Houston from a multidimensional perspective. The point-based validation reveals significant differences between LUR and OK at different test sites despite the similar end-result accuracy (e.g. error rate 6.13% vs. 7.01%). Meanwhile, the area-based validation demonstrates that the PM2.5 concentrations simulated by the LUR model exhibits more detailed variations than those interpolated by the OK method (i.e. information entropy, 7.79 vs. 3.63). Results suggest that LUR modeling could better refine the spatial distribution scenario of PM2.5 concentrations compared to OK interpolation. The significance of this study primarily lies in promoting the integration of point- and area-based statistics for model performance evaluation in air pollution mapping. PMID:25731103
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Mortality in the British rubber industry 1946-85.
Sorahan, T; Parkes, H G; Veys, C A; Waterhouse, J A; Straughan, J K; Nutt, A
1989-01-01
The mortality experienced by a cohort of 36,691 rubber workers during 1946-85 has been investigated. These workers were all male operatives first employed in any one of the 13 participating factories in 1946-60; all had worked continuously in the industry for a minimum period of one year. Compared with the general population, statistically significant excesses relating to cancer mortality were found for cancer of the pharynx (E = 20.2, O = 30, SMR = 149), oesophagus (E = 87.6, O = 107, SMR = 122), stomach (E = 316.5, O = 359, SMR = 113), lung (E = 1219.2, O = 1592, SMR = 131), and all neoplasms (E = 2965.6, O = 3344, SMR = 113). Statistically significant deficits were found for cancer of the prostate. (E = 128.2, O = 91, SMR = 71), testis (E = 11.0, O = 4, SMR = 36), and Hodgkin's disease (E = 26.9, O = 16, SMR = 59). Involvement of occupational exposures was assessed by the method of regression models and life tables (RMLT). This method was used to compare the duration of employment in the industry, the duration in "dust exposed" jobs, and the duration in "fume and/or solvent exposed" jobs of those dying from causes of interest with those of all matching survivors. Positive associations (approaching formal levels of statistical significance) were found only for cancers of the stomach and the lung. The results of the RMLT analysis are independent of those from the SMR analysis, and the study continues to provide limited evidence of a causal association between the risks of stomach cancer and dust exposures, and the risks of lung cancer and fume or solvent exposures in the rubber industry during the period under study. PMID:2920137
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Acceptance of illness and satisfaction with life among malaria patients in rivers state, Nigeria
2014-01-01
Background Health condition is one of the basic factors affecting satisfaction with life, and the level of illness acceptance. The purpose of the study was to analyse the level of illness acceptance, the level of satisfaction with life among malaria patients, and the level of trust placed in the physician and the nurse. Methods The study employs the method of diagnostic survey based on standardised AIS and SWLS scales, as well as Anderson and Dedrick’s PPTS and PNTS scales. Results The average AIS level was 12 points, while the average level of SwL at the SWLS scale was 16.5 points. The average level of trust in the physician and the nurse amounted to 50.6 points and 51.4 points, respectively. The correlation between the level of illness acceptance and self-evaluated satisfaction with life was statistically significant, with R = 0.56. The marital status influenced the level of illness acceptance with p < 0.05 and the level of satisfaction with life with p < 0.05. The employment status affected the level of satisfaction with life with p < 0.05 and the level of illness acceptance with p < 0.05. Conclusions The majority of malaria patients did not accept their illness, while the level of satisfaction with life was low. The majority of respondents trusted their physician and nurse. There is a statistically significant correlation between the level of illness acceptance and the self-evaluated satisfaction with life. The marital status had a statistically significant effect on the acceptance of illness and the satisfaction with life. The individuals who had a job demonstrated higher levels of quality of life and illness acceptance. PMID:24885562
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Mujica Ascencio, Saul; Choe, ChunSik; Meinke, Martina C; Müller, Rainer H; Maksimov, George V; Wigger-Alberti, Walter; Lademann, Juergen; Darvin, Maxim E
2016-07-01
Propylene glycol is one of the known substances added in cosmetic formulations as a penetration enhancer. Recently, nanocrystals have been employed also to increase the skin penetration of active components. Caffeine is a component with many applications and its penetration into the epidermis is controversially discussed in the literature. In the present study, the penetration ability of two components - caffeine nanocrystals and propylene glycol, applied topically on porcine ear skin in the form of a gel, was investigated ex vivo using two confocal Raman microscopes operated at different excitation wavelengths (785nm and 633nm). Several depth profiles were acquired in the fingerprint region and different spectral ranges, i.e., 526-600cm(-1) and 810-880cm(-1) were chosen for independent analysis of caffeine and propylene glycol penetration into the skin, respectively. Multivariate statistical methods such as principal component analysis (PCA) and linear discriminant analysis (LDA) combined with Student's t-test were employed to calculate the maximum penetration depths of each substance (caffeine and propylene glycol). The results show that propylene glycol penetrates significantly deeper than caffeine (20.7-22.0μm versus 12.3-13.0μm) without any penetration enhancement effect on caffeine. The results confirm that different substances, even if applied onto the skin as a mixture, can penetrate differently. The penetration depths of caffeine and propylene glycol obtained using two different confocal Raman microscopes are comparable showing that both types of microscopes are well suited for such investigations and that multivariate statistical PCA-LDA methods combined with Student's t-test are very useful for analyzing the penetration of different substances into the skin. Copyright © 2016 Elsevier B.V. All rights reserved.
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A feature refinement approach for statistical interior CT reconstruction
NASA Astrophysics Data System (ADS)
Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong
2016-07-01
Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)—minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.
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A feature refinement approach for statistical interior CT reconstruction.
Hu, Zhanli; Zhang, Yunwan; Liu, Jianbo; Ma, Jianhua; Zheng, Hairong; Liang, Dong
2016-07-21
Interior tomography is clinically desired to reduce the radiation dose rendered to patients. In this work, a new statistical interior tomography approach for computed tomography is proposed. The developed design focuses on taking into account the statistical nature of local projection data and recovering fine structures which are lost in the conventional total-variation (TV)-minimization reconstruction. The proposed method falls within the compressed sensing framework of TV minimization, which only assumes that the interior ROI is piecewise constant or polynomial and does not need any additional prior knowledge. To integrate the statistical distribution property of projection data, the objective function is built under the criteria of penalized weighed least-square (PWLS-TV). In the implementation of the proposed method, the interior projection extrapolation based FBP reconstruction is first used as the initial guess to mitigate truncation artifacts and also provide an extended field-of-view. Moreover, an interior feature refinement step, as an important processing operation is performed after each iteration of PWLS-TV to recover the desired structure information which is lost during the TV minimization. Here, a feature descriptor is specifically designed and employed to distinguish structure from noise and noise-like artifacts. A modified steepest descent algorithm is adopted to minimize the associated objective function. The proposed method is applied to both digital phantom and in vivo Micro-CT datasets, and compared to FBP, ART-TV and PWLS-TV. The reconstruction results demonstrate that the proposed method performs better than other conventional methods in suppressing noise, reducing truncated and streak artifacts, and preserving features. The proposed approach demonstrates its potential usefulness for feature preservation of interior tomography under truncated projection measurements.
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Addeh, Abdoljalil; Khormali, Aminollah; Golilarz, Noorbakhsh Amiri
2018-05-04
The control chart patterns are the most commonly used statistical process control (SPC) tools to monitor process changes. When a control chart produces an out-of-control signal, this means that the process has been changed. In this study, a new method based on optimized radial basis function neural network (RBFNN) is proposed for control chart patterns (CCPs) recognition. The proposed method consists of four main modules: feature extraction, feature selection, classification and learning algorithm. In the feature extraction module, shape and statistical features are used. Recently, various shape and statistical features have been presented for the CCPs recognition. In the feature selection module, the association rules (AR) method has been employed to select the best set of the shape and statistical features. In the classifier section, RBFNN is used and finally, in RBFNN, learning algorithm has a high impact on the network performance. Therefore, a new learning algorithm based on the bees algorithm has been used in the learning module. Most studies have considered only six patterns: Normal, Cyclic, Increasing Trend, Decreasing Trend, Upward Shift and Downward Shift. Since three patterns namely Normal, Stratification, and Systematic are very similar to each other and distinguishing them is very difficult, in most studies Stratification and Systematic have not been considered. Regarding to the continuous monitoring and control over the production process and the exact type detection of the problem encountered during the production process, eight patterns have been investigated in this study. The proposed method is tested on a dataset containing 1600 samples (200 samples from each pattern) and the results showed that the proposed method has a very good performance. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
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An Analysis of the Navy’s Voluntary Education Program
2007-03-01
NAVAL ANALYSIS VOLED STUDY .........11 1. Data .........................................11 2. Statistical Models ...........................12 3...B. EMPLOYER FINANCED GENERAL TRAINING ................31 1. Data .........................................32 2. Statistical Model...37 1. Data .........................................38 2. Statistical Model ............................38 3. Findings
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Gharehbaghi, Arash; Linden, Maria
2017-10-12
This paper presents a novel method for learning the cyclic contents of stochastic time series: the deep time-growing neural network (DTGNN). The DTGNN combines supervised and unsupervised methods in different levels of learning for an enhanced performance. It is employed by a multiscale learning structure to classify cyclic time series (CTS), in which the dynamic contents of the time series are preserved in an efficient manner. This paper suggests a systematic procedure for finding the design parameter of the classification method for a one-versus-multiple class application. A novel validation method is also suggested for evaluating the structural risk, both in a quantitative and a qualitative manner. The effect of the DTGNN on the performance of the classifier is statistically validated through the repeated random subsampling using different sets of CTS, from different medical applications. The validation involves four medical databases, comprised of 108 recordings of the electroencephalogram signal, 90 recordings of the electromyogram signal, 130 recordings of the heart sound signal, and 50 recordings of the respiratory sound signal. Results of the statistical validations show that the DTGNN significantly improves the performance of the classification and also exhibits an optimal structural risk.
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Validity and reliability of a method for assessment of cervical vertebral maturation.
Zhao, Xiao-Guang; Lin, Jiuxiang; Jiang, Jiu-Hui; Wang, Qingzhu; Ng, Sut Hong
2012-03-01
To evaluate the validity and reliability of the cervical vertebral maturation (CVM) method with a longitudinal sample. Eighty-six cephalograms from 18 subjects (5 males and 13 females) were selected from the longitudinal database. Total mandibular length was measured on each film; an increased rate served as the gold standard in examination of the validity of the CVM method. Eleven orthodontists, after receiving intensive training in the CVM method, evaluated all films twice. Kendall's W and the weighted kappa statistic were employed. Kendall's W values were higher than 0.8 at both times, indicating strong interobserver reproducibility, but interobserver agreement was documented twice at less than 50%. A wide range of intraobserver agreement was noted (40.7%-79.1%), and substantial intraobserver reproducibility was proved by kappa values (0.53-0.86). With regard to validity, moderate agreement was reported between the gold standard and observer staging at the initial time (kappa values 0.44-0.61). However, agreement seemed to be unacceptable for clinical use, especially in cervical stage 3 (26.8%). Even though the validity and reliability of the CVM method proved statistically acceptable, we suggest that many other growth indicators should be taken into consideration in evaluating adolescent skeletal maturation.
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Donovan, Carl; Harwood, John; King, Stephanie; Booth, Cormac; Caneco, Bruno; Walker, Cameron
2016-01-01
There are many developments for offshore renewable energy around the United Kingdom whose installation typically produces large amounts of far-reaching noise, potentially disturbing many marine mammals. The potential to affect the favorable conservation status of many species means extensive environmental impact assessment requirements for the licensing of such installation activities. Quantification of such complex risk problems is difficult and much of the key information is not readily available. Expert elicitation methods can be employed in such pressing cases. We describe the methodology used in an expert elicitation study conducted in the United Kingdom for combining expert opinions based on statistical distributions and copula-like methods.
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NASA Astrophysics Data System (ADS)
Riggi, S.; Antonuccio-Delogu, V.; Bandieramonte, M.; Becciani, U.; Costa, A.; La Rocca, P.; Massimino, P.; Petta, C.; Pistagna, C.; Riggi, F.; Sciacca, E.; Vitello, F.
2013-11-01
Muon tomographic visualization techniques try to reconstruct a 3D image as close as possible to the real localization of the objects being probed. Statistical algorithms under test for the reconstruction of muon tomographic images in the Muon Portal Project are discussed here. Autocorrelation analysis and clustering algorithms have been employed within the context of methods based on the Point Of Closest Approach (POCA) reconstruction tool. An iterative method based on the log-likelihood approach was also implemented. Relative merits of all such methods are discussed, with reference to full GEANT4 simulations of different scenarios, incorporating medium and high-Z objects inside a container.
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Analysis of Employment Flow of Landscape Architecture Graduates in Agricultural Universities
ERIC Educational Resources Information Center
Yao, Xia; He, Linchun
2012-01-01
A statistical analysis of employment flow of landscape architecture graduates was conducted on the employment data of graduates major in landscape architecture in 2008 to 2011. The employment flow of graduates was to be admitted to graduate students, industrial direction and regional distribution, etc. Then, the features of talent flow and factors…
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Medical Malpractice Reform and Employer-Sponsored Health Insurance Premiums
Morrisey, Michael A; Kilgore, Meredith L; Nelson, Leonard (Jack)
2008-01-01
Objective Tort reform may affect health insurance premiums both by reducing medical malpractice premiums and by reducing the extent of defensive medicine. The objective of this study is to estimate the effects of noneconomic damage caps on the premiums for employer-sponsored health insurance. Data Sources/Study Setting Employer premium data and plan/establishment characteristics were obtained from the 1999 through 2004 Kaiser/HRET Employer Health Insurance Surveys. Damage caps were obtained and dated based on state annotated codes, statutes, and judicial decisions. Study Design Fixed effects regression models were run to estimate the effects of the size of inflation-adjusted damage caps on the weighted average single premiums. Data Collection/Extraction Methods State tort reform laws were identified using Westlaw, LEXIS, and statutory compilations. Legislative repeal and amendment of statutes and court decisions resulting in the overturning or repealing state statutes were also identified using LEXIS. Principal Findings Using a variety of empirical specifications, there was no statistically significant evidence that noneconomic damage caps exerted any meaningful influence on the cost of employer-sponsored health insurance. Conclusions The findings suggest that tort reforms have not translated into insurance savings. PMID:18522666
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Farnsworth, G.L.; Nichols, J.D.; Sauer, J.R.; Fancy, S.G.; Pollock, K.H.; Shriner, S.A.; Simons, T.R.; Ralph, C. John; Rich, Terrell D.
2005-01-01
Point counts are a standard sampling procedure for many bird species, but lingering concerns still exist about the quality of information produced from the method. It is well known that variation in observer ability and environmental conditions can influence the detection probability of birds in point counts, but many biologists have been reluctant to abandon point counts in favor of more intensive approaches to counting. However, over the past few years a variety of statistical and methodological developments have begun to provide practical ways of overcoming some of the problems with point counts. We describe some of these approaches, and show how they can be integrated into standard point count protocols to greatly enhance the quality of the information. Several tools now exist for estimation of detection probability of birds during counts, including distance sampling, double observer methods, time-depletion (removal) methods, and hybrid methods that combine these approaches. Many counts are conducted in habitats that make auditory detection of birds much more likely than visual detection. As a framework for understanding detection probability during such counts, we propose separating two components of the probability a bird is detected during a count into (1) the probability a bird vocalizes during the count and (2) the probability this vocalization is detected by an observer. In addition, we propose that some measure of the area sampled during a count is necessary for valid inferences about bird populations. This can be done by employing fixed-radius counts or more sophisticated distance-sampling models. We recommend any studies employing point counts be designed to estimate detection probability and to include a measure of the area sampled.
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29 CFR 1614.601 - EEO group statistics.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 29 Labor 4 2010-07-01 2010-07-01 false EEO group statistics. 1614.601 Section 1614.601 Labor... EMPLOYMENT OPPORTUNITY Matters of General Applicability § 1614.601 EEO group statistics. (a) Each agency... provided by an employee is inaccurate, the agency shall advise the employee about the solely statistical...
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Takeyoshi, Masahiro; Sawaki, Masakuni; Yamasaki, Kanji; Kimber, Ian
2003-09-30
The murine local lymph node assay (LLNA) is used for the identification of chemicals that have the potential to cause skin sensitization. However, it requires specific facility and handling procedures to accommodate a radioisotopic (RI) endpoint. We have developed non-radioisotopic (non-RI) endpoint of LLNA based on BrdU incorporation to avoid a use of RI. Although this alternative method appears viable in principle, it is somewhat less sensitive than the standard assay. In this study, we report investigations to determine the use of statistical analysis to improve the sensitivity of a non-RI LLNA procedure with alpha-hexylcinnamic aldehyde (HCA) in two separate experiments. Consequently, the alternative non-RI method required HCA concentrations of greater than 25% to elicit a positive response based on the criterion for classification as a skin sensitizer in the standard LLNA. Nevertheless, dose responses to HCA in the alternative method were consistent in both experiments and we examined whether the use of an endpoint based upon the statistical significance of induced changes in LNC turnover, rather than an SI of 3 or greater, might provide for additional sensitivity. The results reported here demonstrate that with HCA at least significant responses were, in each of two experiments, recorded following exposure of mice to 25% of HCA. These data suggest that this approach may be more satisfactory-at least when BrdU incorporation is measured. However, this modification of the LLNA is rather less sensitive than the standard method if employing statistical endpoint. Taken together the data reported here suggest that a modified LLNA in which BrdU is used in place of radioisotope incorporation shows some promise, but that in its present form, even with the use of a statistical endpoint, lacks some of the sensitivity of the standard method. The challenge is to develop strategies for further refinement of this approach.
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Statistical Learning Analysis in Neuroscience: Aiming for Transparency
Hanke, Michael; Halchenko, Yaroslav O.; Haxby, James V.; Pollmann, Stefan
2009-01-01
Encouraged by a rise of reciprocal interest between the machine learning and neuroscience communities, several recent studies have demonstrated the explanatory power of statistical learning techniques for the analysis of neural data. In order to facilitate a wider adoption of these methods, neuroscientific research needs to ensure a maximum of transparency to allow for comprehensive evaluation of the employed procedures. We argue that such transparency requires “neuroscience-aware” technology for the performance of multivariate pattern analyses of neural data that can be documented in a comprehensive, yet comprehensible way. Recently, we introduced PyMVPA, a specialized Python framework for machine learning based data analysis that addresses this demand. Here, we review its features and applicability to various neural data modalities. PMID:20582270
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Effects of Simplifying Choice Tasks on Estimates of Taste Heterogeneity in Stated-Choice Surveys
Johnson, F. Reed; Ozdemir, Semra; Phillips, Kathryn A
2011-01-01
Researchers usually employ orthogonal arrays or D-optimal designs with little or no attribute overlap in stated-choice surveys. The challenge is to balance statistical efficiency and respondent burden to minimize the overall error in the survey responses. This study examined whether simplifying the choice task, by using a design with more overlap, provides advantages over standard minimum-overlap methods. We administered two designs for eliciting HIV test preferences to split samples. Surveys were undertaken at four HIV testing locations in San Francisco, California. Personal characteristics had different effects on willingness to pay for the two treatments, and gains in statistical efficiency in the minimal-overlap version more than compensated for possible imprecision from increased measurement error. PMID:19880234
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Statistical Analysis of Protein Ensembles
NASA Astrophysics Data System (ADS)
Máté, Gabriell; Heermann, Dieter
2014-04-01
As 3D protein-configuration data is piling up, there is an ever-increasing need for well-defined, mathematically rigorous analysis approaches, especially that the vast majority of the currently available methods rely heavily on heuristics. We propose an analysis framework which stems from topology, the field of mathematics which studies properties preserved under continuous deformations. First, we calculate a barcode representation of the molecules employing computational topology algorithms. Bars in this barcode represent different topological features. Molecules are compared through their barcodes by statistically determining the difference in the set of their topological features. As a proof-of-principle application, we analyze a dataset compiled of ensembles of different proteins, obtained from the Ensemble Protein Database. We demonstrate that our approach correctly detects the different protein groupings.
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Monitoring of bone regeneration process by means of texture analysis
NASA Astrophysics Data System (ADS)
Kokkinou, E.; Boniatis, I.; Costaridou, L.; Saridis, A.; Panagiotopoulos, E.; Panayiotakis, G.
2009-09-01
An image analysis method is proposed for the monitoring of the regeneration of the tibial bone. For this purpose, 130 digitized radiographs of 13 patients, who had undergone tibial lengthening by the Ilizarov method, were studied. For each patient, 10 radiographs, taken at an equal number of postoperative successive time moments, were available. Employing available software, 3 Regions Of Interest (ROIs), corresponding to the: (a) upper, (b) central, and (c) lower aspect of the gap, where bone regeneration was expected to occur, were determined on each radiograph. Employing custom developed algorithms: (i) a number of textural features were generated from each of the ROIs, and (ii) a texture-feature based regression model was designed for the quantitative monitoring of the bone regeneration process. Statistically significant differences (p < 0.05) were derived for the initial and the final textural features values, generated from the first and the last postoperatively obtained radiographs, respectively. A quadratic polynomial regression equation fitted data adequately (r2 = 0.9, p < 0.001). The suggested method may contribute to the monitoring of the tibial bone regeneration process.
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ParallABEL: an R library for generalized parallelization of genome-wide association studies.
Sangket, Unitsa; Mahasirimongkol, Surakameth; Chantratita, Wasun; Tandayya, Pichaya; Aulchenko, Yurii S
2010-04-29
Genome-Wide Association (GWA) analysis is a powerful method for identifying loci associated with complex traits and drug response. Parts of GWA analyses, especially those involving thousands of individuals and consuming hours to months, will benefit from parallel computation. It is arduous acquiring the necessary programming skills to correctly partition and distribute data, control and monitor tasks on clustered computers, and merge output files. Most components of GWA analysis can be divided into four groups based on the types of input data and statistical outputs. The first group contains statistics computed for a particular Single Nucleotide Polymorphism (SNP), or trait, such as SNP characterization statistics or association test statistics. The input data of this group includes the SNPs/traits. The second group concerns statistics characterizing an individual in a study, for example, the summary statistics of genotype quality for each sample. The input data of this group includes individuals. The third group consists of pair-wise statistics derived from analyses between each pair of individuals in the study, for example genome-wide identity-by-state or genomic kinship analyses. The input data of this group includes pairs of SNPs/traits. The final group concerns pair-wise statistics derived for pairs of SNPs, such as the linkage disequilibrium characterisation. The input data of this group includes pairs of individuals. We developed the ParallABEL library, which utilizes the Rmpi library, to parallelize these four types of computations. ParallABEL library is not only aimed at GenABEL, but may also be employed to parallelize various GWA packages in R. The data set from the North American Rheumatoid Arthritis Consortium (NARAC) includes 2,062 individuals with 545,080, SNPs' genotyping, was used to measure ParallABEL performance. Almost perfect speed-up was achieved for many types of analyses. For example, the computing time for the identity-by-state matrix was linearly reduced from approximately eight hours to one hour when ParallABEL employed eight processors. Executing genome-wide association analysis using the ParallABEL library on a computer cluster is an effective way to boost performance, and simplify the parallelization of GWA studies. ParallABEL is a user-friendly parallelization of GenABEL.
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Titrimetric and photometric methods for determination of hypochlorite in commercial bleaches.
Jonnalagadda, Sreekanth B; Gengan, Prabhashini
2010-01-01
Two methods, simple titration and photometric methods for determination of hypochlorite are developed, based its reaction with hydrogen peroxide and titration of the residual peroxide by acidic permanganate. In the titration method, the residual hydrogen peroxide is estimated by titration with standard permanganate solution to estimate the hypochlorite concentration. The photometric method is devised to measure the concentration of remaining permanganate, after the reaction with residual hydrogen peroxide. It employs 4 ranges of calibration curves to enable the determination of hypochlorite accurately. The new photometric method measures hypochlorite in the range 1.90 x 10(-3) to 1.90 x 10(-2) M, with high accuracy and with low variance. The concentrations of hypochlorite in diverse commercial bleach samples and in seawater which is enriched with hypochlorite were estimated using the proposed method and compared with the arsenite method. The statistical analysis validates the superiority of the proposed method.
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Regional analysis of annual maximum rainfall using TL-moments method
NASA Astrophysics Data System (ADS)
Shabri, Ani Bin; Daud, Zalina Mohd; Ariff, Noratiqah Mohd
2011-06-01
Information related to distributions of rainfall amounts are of great importance for designs of water-related structures. One of the concerns of hydrologists and engineers is the probability distribution for modeling of regional data. In this study, a novel approach to regional frequency analysis using L-moments is revisited. Subsequently, an alternative regional frequency analysis using the TL-moments method is employed. The results from both methods were then compared. The analysis was based on daily annual maximum rainfall data from 40 stations in Selangor Malaysia. TL-moments for the generalized extreme value (GEV) and generalized logistic (GLO) distributions were derived and used to develop the regional frequency analysis procedure. TL-moment ratio diagram and Z-test were employed in determining the best-fit distribution. Comparison between the two approaches showed that the L-moments and TL-moments produced equivalent results. GLO and GEV distributions were identified as the most suitable distributions for representing the statistical properties of extreme rainfall in Selangor. Monte Carlo simulation was used for performance evaluation, and it showed that the method of TL-moments was more efficient for lower quantile estimation compared with the L-moments.
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Poppe, L.J.; Eliason, A.H.; Hastings, M.E.
2004-01-01
Measures that describe and summarize sediment grain-size distributions are important to geologists because of the large amount of information contained in textural data sets. Statistical methods are usually employed to simplify the necessary comparisons among samples and quantify the observed differences. The two statistical methods most commonly used by sedimentologists to describe particle distributions are mathematical moments (Krumbein and Pettijohn, 1938) and inclusive graphics (Folk, 1974). The choice of which of these statistical measures to use is typically governed by the amount of data available (Royse, 1970). If the entire distribution is known, the method of moments may be used; if the next to last accumulated percent is greater than 95, inclusive graphics statistics can be generated. Unfortunately, earlier programs designed to describe sediment grain-size distributions statistically do not run in a Windows environment, do not allow extrapolation of the distribution's tails, or do not generate both moment and graphic statistics (Kane and Hubert, 1963; Collias et al., 1963; Schlee and Webster, 1967; Poppe et al., 2000)1.Owing to analytical limitations, electro-resistance multichannel particle-size analyzers, such as Coulter Counters, commonly truncate the tails of the fine-fraction part of grain-size distributions. These devices do not detect fine clay in the 0.6–0.1 μm range (part of the 11-phi and all of the 12-phi and 13-phi fractions). Although size analyses performed down to 0.6 μm microns are adequate for most freshwater and near shore marine sediments, samples from many deeper water marine environments (e.g. rise and abyssal plain) may contain significant material in the fine clay fraction, and these analyses benefit from extrapolation.The program (GSSTAT) described herein generates statistics to characterize sediment grain-size distributions and can extrapolate the fine-grained end of the particle distribution. It is written in Microsoft Visual Basic 6.0 and provides a window to facilitate program execution. The input for the sediment fractions is weight percentages in whole-phi notation (Krumbein, 1934; Inman, 1952), and the program permits the user to select output in either method of moments or inclusive graphics statistics (Fig. 1). Users select options primarily with mouse-click events, or through interactive dialogue boxes.
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Physics Manpower, 1973, Education and Employment Studies.
ERIC Educational Resources Information Center
American Inst. of Physics, New York, NY.
Discussed in this document are the changes within the physics profession, their causes and effect. Detailed statistical data are supplied concerning physics enrollments, the institutions where physics is taught, the faculty in physics departments, and the nonacademic employment of physicists. Other topics include employment, education, minority…
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Bacci, Silvia; Seracini, Marco; Chiavarini, Manuela; Bartolucci, Francesco; Minelli, Liliana
2017-01-01
The aim of this study was to investigate the relationship between employment status (permanent employment, fixed-term employment, unemployment, other) and perceived health status in a sample of the Italian population. Data was obtained from the European Union Statistics on Income and Living Condition (EU-SILC) study during the period 2009 - 2012. The sample consists of 4,848 individuals, each with a complete record of observations during four years for a total of 19,392 observations. The causal relationship between perceived/self-reported health status and employment status was tested using a global logit model (STATA). Our results confirm a significant association between employment status and perceived health, as well as between perceived health status and economic status. Unemployment that was dependent on an actual lack of work opportunities and not from individual disability was found to be the most significant determinant of perceived health status; a higher educational level produces a better perceived health status.
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DATA ON YOUTH, 1967, A STATISTICAL DOCUMENT.
ERIC Educational Resources Information Center
SCHEIDER, GEORGE
THE DATA IN THIS REPORT ARE STATISTICS ON YOUTH THROUGHOUT THE UNITED STATES AND IN NEW YORK STATE. INCLUDED ARE DATA ON POPULATION, SCHOOL STATISTICS, EMPLOYMENT, FAMILY INCOME, JUVENILE DELINQUENCY AND YOUTH CRIME (INCLUDING NEW YORK CITY FIGURES), AND TRAFFIC ACCIDENTS. THE STATISTICS ARE PRESENTED IN THE TEXT AND IN TABLES AND CHARTS. (NH)
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ERIC Educational Resources Information Center
Meletiou-Mavrotheris, Maria
2004-01-01
While technology has become an integral part of introductory statistics courses, the programs typically employed are professional packages designed primarily for data analysis rather than for learning. Findings from several studies suggest that use of such software in the introductory statistics classroom may not be very effective in helping…
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Statistical Approaches Used to Assess the Equity of Access to Food Outlets: A Systematic Review
Lamb, Karen E.; Thornton, Lukar E.; Cerin, Ester; Ball, Kylie
2015-01-01
Background Inequalities in eating behaviours are often linked to the types of food retailers accessible in neighbourhood environments. Numerous studies have aimed to identify if access to healthy and unhealthy food retailers is socioeconomically patterned across neighbourhoods, and thus a potential risk factor for dietary inequalities. Existing reviews have examined differences between methodologies, particularly focussing on neighbourhood and food outlet access measure definitions. However, no review has informatively discussed the suitability of the statistical methodologies employed; a key issue determining the validity of study findings. Our aim was to examine the suitability of statistical approaches adopted in these analyses. Methods Searches were conducted for articles published from 2000–2014. Eligible studies included objective measures of the neighbourhood food environment and neighbourhood-level socio-economic status, with a statistical analysis of the association between food outlet access and socio-economic status. Results Fifty-four papers were included. Outlet accessibility was typically defined as the distance to the nearest outlet from the neighbourhood centroid, or as the number of food outlets within a neighbourhood (or buffer). To assess if these measures were linked to neighbourhood disadvantage, common statistical methods included ANOVA, correlation, and Poisson or negative binomial regression. Although all studies involved spatial data, few considered spatial analysis techniques or spatial autocorrelation. Conclusions With advances in GIS software, sophisticated measures of neighbourhood outlet accessibility can be considered. However, approaches to statistical analysis often appear less sophisticated. Care should be taken to consider assumptions underlying the analysis and the possibility of spatially correlated residuals which could affect the results. PMID:29546115
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Milyo, Jeffrey; Mellor, Jennifer M
2003-01-01
Objective To illustrate the potential sensitivity of ecological associations between mortality and certain socioeconomic factors to different methods of age-adjustment. Data Sources Secondary analysis employing state-level data from several publicly available sources. Crude and age-adjusted mortality rates for 1990 are obtained from the U.S. Centers for Disease Control. The Gini coefficient for family income and percent of persons below the federal poverty line are from the U.S. Bureau of Labor Statistics. Putnam's (2000) Social Capital Index was downloaded from ; the Social Mistrust Index was calculated from responses to the General Social Survey, following the method described in Kawachi et al. (1997). All other covariates are obtained from the U.S. Census Bureau. Study Design We use least squares regression to estimate the effect of several state-level socioeconomic factors on mortality rates. We examine whether these statistical associations are sensitive to the use of alternative methods of accounting for the different age composition of state populations. Following several previous studies, we present results for the case when only mortality rates are age-adjusted. We contrast these results with those obtained from regressions of crude mortality on age variables. Principal Findings Different age-adjustment methods can cause a change in the sign or statistical significance of the association between mortality and various socioeconomic factors. When age variables are included as regressors, we find no significant association between mortality and either income inequality, minority racial concentration, or social capital. Conclusions Ecological associations between certain socioeconomic factors and mortality may be extremely sensitive to different age-adjustment methods. PMID:14727797
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Parametric study of statistical bias in laser Doppler velocimetry
NASA Technical Reports Server (NTRS)
Gould, Richard D.; Stevenson, Warren H.; Thompson, H. Doyle
1989-01-01
Analytical studies have often assumed that LDV velocity bias depends on turbulence intensity in conjunction with one or more characteristic time scales, such as the time between validated signals, the time between data samples, and the integral turbulence time-scale. These parameters are presently varied independently, in an effort to quantify the biasing effect. Neither of the post facto correction methods employed is entirely accurate. The mean velocity bias error is found to be nearly independent of data validation rate.
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Social contagion theory: examining dynamic social networks and human behavior
Christakis, Nicholas A.; Fowler, James H.
2013-01-01
Here, we review the research we have conducted on social contagion. We describe the methods we have employed (and the assumptions they have entailed) to examine several datasets with complementary strengths and weaknesses, including the Framingham Heart Study, the National Longitudinal Study of Adolescent Health, and other observational and experimental datasets that we and others have collected. We describe the regularities that led us to propose that human social networks may exhibit a ‘three degrees of influence’ property, and we review statistical approaches we have used to characterize interpersonal influence with respect to phenomena as diverse as obesity, smoking, cooperation, and happiness. We do not claim that this work is the final word, but we do believe that it provides some novel, informative, and stimulating evidence regarding social contagion in longitudinally followed networks. Along with other scholars, we are working to develop new methods for identifying causal effects using social network data, and we believe that this area is ripe for statistical development as current methods have known and often unavoidable limitations. PMID:22711416
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NASA Astrophysics Data System (ADS)
Bilionis, I.; Koutsourelakis, P. S.
2012-05-01
The present paper proposes an adaptive biasing potential technique for the computation of free energy landscapes. It is motivated by statistical learning arguments and unifies the tasks of biasing the molecular dynamics to escape free energy wells and estimating the free energy function, under the same objective of minimizing the Kullback-Leibler divergence between appropriately selected densities. It offers rigorous convergence diagnostics even though history dependent, non-Markovian dynamics are employed. It makes use of a greedy optimization scheme in order to obtain sparse representations of the free energy function which can be particularly useful in multidimensional cases. It employs embarrassingly parallelizable sampling schemes that are based on adaptive Sequential Monte Carlo and can be readily coupled with legacy molecular dynamics simulators. The sequential nature of the learning and sampling scheme enables the efficient calculation of free energy functions parametrized by the temperature. The characteristics and capabilities of the proposed method are demonstrated in three numerical examples.
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Large-eddy simulation of turbulent cavitating flow in a micro channel
DOE Office of Scientific and Technical Information (OSTI.GOV)
Egerer, Christian P., E-mail: christian.egerer@aer.mw.tum.de; Hickel, Stefan; Schmidt, Steffen J.
2014-08-15
Large-eddy simulations (LES) of cavitating flow of a Diesel-fuel-like fluid in a generic throttle geometry are presented. Two-phase regions are modeled by a parameter-free thermodynamic equilibrium mixture model, and compressibility of the liquid and the liquid-vapor mixture is taken into account. The Adaptive Local Deconvolution Method (ALDM), adapted for cavitating flows, is employed for discretizing the convective terms of the Navier-Stokes equations for the homogeneous mixture. ALDM is a finite-volume-based implicit LES approach that merges physically motivated turbulence modeling and numerical discretization. Validation of the numerical method is performed for a cavitating turbulent mixing layer. Comparisons with experimental data ofmore » the throttle flow at two different operating conditions are presented. The LES with the employed cavitation modeling predicts relevant flow and cavitation features accurately within the uncertainty range of the experiment. The turbulence structure of the flow is further analyzed with an emphasis on the interaction between cavitation and coherent motion, and on the statistically averaged-flow evolution.« less
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Accurate mass measurement: terminology and treatment of data.
Brenton, A Gareth; Godfrey, A Ruth
2010-11-01
High-resolution mass spectrometry has become ever more accessible with improvements in instrumentation, such as modern FT-ICR and Orbitrap mass spectrometers. This has resulted in an increase in the number of articles submitted for publication quoting accurate mass data. There is a plethora of terms related to accurate mass analysis that are in current usage, many employed incorrectly or inconsistently. This article is based on a set of notes prepared by the authors for research students and staff in our laboratories as a guide to the correct terminology and basic statistical procedures to apply in relation to mass measurement, particularly for accurate mass measurement. It elaborates on the editorial by Gross in 1994 regarding the use of accurate masses for structure confirmation. We have presented and defined the main terms in use with reference to the International Union of Pure and Applied Chemistry (IUPAC) recommendations for nomenclature and symbolism for mass spectrometry. The correct use of statistics and treatment of data is illustrated as a guide to new and existing mass spectrometry users with a series of examples as well as statistical methods to compare different experimental methods and datasets. Copyright © 2010. Published by Elsevier Inc.
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Prediction Methods in Solar Sunspots Cycles
Ng, Kim Kwee
2016-01-01
An understanding of the Ohl’s Precursor Method, which is used to predict the upcoming sunspots activity, is presented by employing a simplified movable divided-blocks diagram. Using a new approach, the total number of sunspots in a solar cycle and the maximum averaged monthly sunspots number Rz(max) are both shown to be statistically related to the geomagnetic activity index in the prior solar cycle. The correlation factors are significant and they are respectively found to be 0.91 ± 0.13 and 0.85 ± 0.17. The projected result is consistent with the current observation of solar cycle 24 which appears to have attained at least Rz(max) at 78.7 ± 11.7 in March 2014. Moreover, in a statistical study of the time-delayed solar events, the average time between the peak in the monthly geomagnetic index and the peak in the monthly sunspots numbers in the succeeding ascending phase of the sunspot activity is found to be 57.6 ± 3.1 months. The statistically determined time-delayed interval confirms earlier observational results by others that the Sun’s electromagnetic dipole is moving toward the Sun’s Equator during a solar cycle. PMID:26868269
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NASA Astrophysics Data System (ADS)
Kokkinaki, A.; Sleep, B. E.; Chambers, J. E.; Cirpka, O. A.; Nowak, W.
2010-12-01
Electrical Resistance Tomography (ERT) is a popular method for investigating subsurface heterogeneity. The method relies on measuring electrical potential differences and obtaining, through inverse modeling, the underlying electrical conductivity field, which can be related to hydraulic conductivities. The quality of site characterization strongly depends on the utilized inversion technique. Standard ERT inversion methods, though highly computationally efficient, do not consider spatial correlation of soil properties; as a result, they often underestimate the spatial variability observed in earth materials, thereby producing unrealistic subsurface models. Also, these methods do not quantify the uncertainty of the estimated properties, thus limiting their use in subsequent investigations. Geostatistical inverse methods can be used to overcome both these limitations; however, they are computationally expensive, which has hindered their wide use in practice. In this work, we compare a standard Gauss-Newton smoothness constrained least squares inversion method against the quasi-linear geostatistical approach using the three-dimensional ERT dataset of the SABRe (Source Area Bioremediation) project. The two methods are evaluated for their ability to: a) produce physically realistic electrical conductivity fields that agree with the wide range of data available for the SABRe site while being computationally efficient, and b) provide information on the spatial statistics of other parameters of interest, such as hydraulic conductivity. To explore the trade-off between inversion quality and computational efficiency, we also employ a 2.5-D forward model with corrections for boundary conditions and source singularities. The 2.5-D model accelerates the 3-D geostatistical inversion method. New adjoint equations are developed for the 2.5-D forward model for the efficient calculation of sensitivities. Our work shows that spatial statistics can be incorporated in large-scale ERT inversions to improve the inversion results without making them computationally prohibitive.
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Tang, Jie; Nett, Brian E; Chen, Guang-Hong
2009-10-07
Of all available reconstruction methods, statistical iterative reconstruction algorithms appear particularly promising since they enable accurate physical noise modeling. The newly developed compressive sampling/compressed sensing (CS) algorithm has shown the potential to accurately reconstruct images from highly undersampled data. The CS algorithm can be implemented in the statistical reconstruction framework as well. In this study, we compared the performance of two standard statistical reconstruction algorithms (penalized weighted least squares and q-GGMRF) to the CS algorithm. In assessing the image quality using these iterative reconstructions, it is critical to utilize realistic background anatomy as the reconstruction results are object dependent. A cadaver head was scanned on a Varian Trilogy system at different dose levels. Several figures of merit including the relative root mean square error and a quality factor which accounts for the noise performance and the spatial resolution were introduced to objectively evaluate reconstruction performance. A comparison is presented between the three algorithms for a constant undersampling factor comparing different algorithms at several dose levels. To facilitate this comparison, the original CS method was formulated in the framework of the statistical image reconstruction algorithms. Important conclusions of the measurements from our studies are that (1) for realistic neuro-anatomy, over 100 projections are required to avoid streak artifacts in the reconstructed images even with CS reconstruction, (2) regardless of the algorithm employed, it is beneficial to distribute the total dose to more views as long as each view remains quantum noise limited and (3) the total variation-based CS method is not appropriate for very low dose levels because while it can mitigate streaking artifacts, the images exhibit patchy behavior, which is potentially harmful for medical diagnosis.
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NASA Astrophysics Data System (ADS)
Koparan, Timur
2016-02-01
In this study, the effect on the achievement and attitudes of prospective teachers is examined. With this aim ahead, achievement test, attitude scale for statistics and interviews were used as data collection tools. The achievement test comprises 8 problems based on statistical data, and the attitude scale comprises 13 Likert-type items. The study was carried out in 2014-2015 academic year fall semester at a university in Turkey. The study, which employed the pre-test-post-test control group design of quasi-experimental research method, was carried out on a group of 80 prospective teachers, 40 in the control group and 40 in the experimental group. Both groups had four-hour classes about descriptive statistics. The classes with the control group were carried out through traditional methods while dynamic statistics software was used in the experimental group. Five prospective teachers from the experimental group were interviewed clinically after the application for a deeper examination of their views about application. Qualitative data gained are presented under various themes. At the end of the study, it was found that there is a significant difference in favour of the experimental group in terms of achievement and attitudes, the prospective teachers have affirmative approach to the use of dynamic software and see it as an effective tool to enrich maths classes. In accordance with the findings of the study, it is suggested that dynamic software, which offers unique opportunities, be used in classes by teachers and students.
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Study of multi-dimensional radiative energy transfer in molecular gases
NASA Technical Reports Server (NTRS)
Liu, Jiwen; Tiwari, S. N.
1993-01-01
The Monte Carlo method (MCM) is applied to analyze radiative heat transfer in nongray gases. The nongray model employed is based on the statistical arrow band model with an exponential-tailed inverse intensity distribution. Consideration of spectral correlation results in some distinguishing features of the Monte Carlo formulations. Validation of the Monte Carlo formulations has been conducted by comparing results of this method with other solutions. Extension of a one-dimensional problem to a multi-dimensional problem requires some special treatments in the Monte Carlo analysis. Use of different assumptions results in different sets of Monte Carlo formulations. The nongray narrow band formulations provide the most accurate results.
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Community reporting of ambient air polychlorinated biphenyl concentrations near a Superfund site.
Tomsho, Kathryn S; Basra, Komal; Rubin, Staci M; Miller, Claire B; Juang, Richard; Broude, Sylvia; Martinez, Andres; Hornbuckle, Keri C; Heiger-Bernays, Wendy; Scammell, Madeleine K
2017-10-27
In this manuscript, we describe the process of establishing partnerships for community-based environmental exposure research, the tools and methods implemented for data report-back to community members, and the results of evaluations of these efforts. Data discovery and report-back materials developed by Statistics for Action (SFA) were employed as the framework to communicate the environmental data to community members and workshops. These data communication and research translation efforts are described in detail and evaluated for effectiveness based on feedback provided from community members who attended the workshops. Overall, the methods were mostly effective for the intended data communication.
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Simulation of financial market via nonlinear Ising model
NASA Astrophysics Data System (ADS)
Ko, Bonggyun; Song, Jae Wook; Chang, Woojin
2016-09-01
In this research, we propose a practical method for simulating the financial return series whose distribution has a specific heaviness. We employ the Ising model for generating financial return series to be analogous to those of the real series. The similarity between real financial return series and simulated one is statistically verified based on their stylized facts including the power law behavior of tail distribution. We also suggest the scheme for setting the parameters in order to simulate the financial return series with specific tail behavior. The simulation method introduced in this paper is expected to be applied to the other financial products whose price return distribution is fat-tailed.
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Quantitative estimation of itopride hydrochloride and rabeprazole sodium from capsule formulation.
Pillai, S; Singhvi, I
2008-09-01
Two simple, accurate, economical and reproducible UV spectrophotometric methods and one HPLC method for simultaneous estimation of two component drug mixture of itopride hydrochloride and rabeprazole sodium from combined capsule dosage form have been developed. First developed method involves formation and solving of simultaneous equations using 265.2 nm and 290.8 nm as two wavelengths. Second method is based on two wavelength calculation, wavelengths selected for estimation of itopride hydrochloride was 278.0 nm and 298.8 nm and for rabeprazole sodium 253.6 nm and 275.2 nm. Developed HPLC method is a reverse phase chromatographic method using phenomenex C(18) column and acetonitrile: phosphate buffer (35:65 v/v) pH 7.0 as mobile phase. All developed methods obey Beer's law in concentration range employed for respective methods. Results of analysis were validated statistically and by recovery studies.
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Quantitative Estimation of Itopride Hydrochloride and Rabeprazole Sodium from Capsule Formulation
Pillai, S.; Singhvi, I.
2008-01-01
Two simple, accurate, economical and reproducible UV spectrophotometric methods and one HPLC method for simultaneous estimation of two component drug mixture of itopride hydrochloride and rabeprazole sodium from combined capsule dosage form have been developed. First developed method involves formation and solving of simultaneous equations using 265.2 nm and 290.8 nm as two wavelengths. Second method is based on two wavelength calculation, wavelengths selected for estimation of itopride hydrochloride was 278.0 nm and 298.8 nm and for rabeprazole sodium 253.6 nm and 275.2 nm. Developed HPLC method is a reverse phase chromatographic method using phenomenex C18 column and acetonitrile: phosphate buffer (35:65 v/v) pH 7.0 as mobile phase. All developed methods obey Beer's law in concentration range employed for respective methods. Results of analysis were validated statistically and by recovery studies. PMID:21394269
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Life cycle cost evaluation of the digital opacity compliance system.
McFarland, Michael J; Palmer, Glenn R; Olivas, Arthur C
2010-01-01
The US Environmental Protection Agency (EPA) has established EPA Reference Method 9 (Method 9) as the preferred enforcement approach for verifying compliance with federal visible opacity standards. While Method 9 has an extensive history of successful employment, reliance on human observers to quantify visible emissions is inherently subjective, a characteristic that exposes Method 9 results to claims of inaccuracy, bias and, in some cases, outright fraud. The Digital Opacity Compliance System (DOCS), which employs commercial-off-the-shelf digital photography coupled with simple computer processing, is a new approach for quantifying visible opacity. The DOCS technology has been previously demonstrated to meet and, in many cases, surpass the Method 9 accuracy and reliability standards (McFarland et al., 2006). Beyond its performance relative to Method 9, DOCS provides a permanent visual record of opacity, a vital feature in legal compliance challenges. In recent DOCS field testing, the opacity analysis of two hundred and forty one (241) regulated air emissions from the following industrial processes: 1) industrial scrubbers, 2) emergency generators, 3) asphalt paving, 4) steel production and 5) incineration indicated that Method 9 and DOCS were statistically equivalent at the 99% confidence level. However, a life cycle cost analysis demonstrated that implementation of DOCS could potentially save a facility $15,732 per trained opacity observer compared to utilization of Method 9. Copyright 2009 Elsevier Ltd. All rights reserved.
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Upgrades to the REA method for producing probabilistic climate change projections
NASA Astrophysics Data System (ADS)
Xu, Ying; Gao, Xuejie; Giorgi, Filippo
2010-05-01
We present an augmented version of the Reliability Ensemble Averaging (REA) method designed to generate probabilistic climate change information from ensembles of climate model simulations. Compared to the original version, the augmented one includes consideration of multiple variables and statistics in the calculation of the performance-based weights. In addition, the model convergence criterion previously employed is removed. The method is applied to the calculation of changes in mean and variability for temperature and precipitation over different sub-regions of East Asia based on the recently completed CMIP3 multi-model ensemble. Comparison of the new and old REA methods, along with the simple averaging procedure, and the use of different combinations of performance metrics shows that at fine sub-regional scales the choice of weighting is relevant. This is mostly because the models show a substantial spread in performance for the simulation of precipitation statistics, a result that supports the use of model weighting as a useful option to account for wide ranges of quality of models. The REA method, and in particular the upgraded one, provides a simple and flexible framework for assessing the uncertainty related to the aggregation of results from ensembles of models in order to produce climate change information at the regional scale. KEY WORDS: REA method, Climate change, CMIP3
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ERIC Educational Resources Information Center
General Accounting Office, Washington, DC.
To compile its projections of future employment levels, the Bureau of Labor Statistics (BLS) combines the following five interlinked models in a six-step process: a labor force model, an econometric model of the U.S. economy, an industry activity model, an industry labor demand model, and an occupational labor demand model. The BLS was asked to…
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Measuring Efficiency and Tradeoffs in Attainment of EEO Goals.
1982-02-01
in FY78 and FY79. i.e., T9tese goals Are based on undifferentiated Civilian Labor Force (CLF) ratios required for reporting by the Equal Employment...Lewis and R.J. Niehaus, "Design and Development of Equal Employment Opportunity Human Resources Planning Models," NPDRC TR79--141 (San Diego: Navy...Approach to Analysis of Tradeoffs Among Household Ptoduction Outputs," American Statistical Association 1979 Proceedings of the Social Statistics Section
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Canestaro, W; Vodicka, E; Downing, D; Trussell, J
2017-01-01
Mandatory employer-based insurance coverage of contraception in the US has been a controversial component of the Affordable Care Act (ACA). Prior research has examined the cost-effectiveness of contraception in general; however, no studies have developed a formal decision model in the context of the new ACA provisions. As such, this study aims to estimate the relative cost-effectiveness of insurance coverage of contraception under employer-sponsored insurance coverage taking into consideration newer regulations allowing for religious exemptions. A decision model was developed from the employer perspective to simulate pregnancy costs and outcomes associated with insurance coverage. Method-specific estimates of contraception failure rates, outcomes and costs were derived from the literature. Uptake by marital status and age was drawn from a nationally representative database. Providing no contraception coverage resulted in 33 more unintended pregnancies per 1000 women (95% confidence range: 22.4; 44.0). This subsequently significantly increased the number of unintended births and terminations. Total costs were higher among uninsured women owing to higher costs of pregnancy outcomes. The effect of no insurance was greatest on unmarried women 20-29 years old. Denying female employees' full coverage of contraceptives increases total costs from the employer perspective, as well as the total number of terminations. Insurance coverage was found to be significantly associated with women's choice of contraceptive method in a large nationally representative sample. Using a decision model to extrapolate to pregnancy outcomes, we found a large and statistically significant difference in unintended pregnancy and terminations. Denying women contraception coverage may have significant consequences for pregnancy outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.
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Zhou, Yunyi; Tao, Chenyang; Lu, Wenlian; Feng, Jianfeng
2018-04-20
Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation. A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression. We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods. Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail. In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis. Copyright © 2018. Published by Elsevier B.V.
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Measurement of the relationship between perceived and computed color differences
NASA Astrophysics Data System (ADS)
García, Pedro A.; Huertas, Rafael; Melgosa, Manuel; Cui, Guihua
2007-07-01
Using simulated data sets, we have analyzed some mathematical properties of different statistical measurements that have been employed in previous literature to test the performance of different color-difference formulas. Specifically, the properties of the combined index PF/3 (performance factor obtained as average of three terms), widely employed in current literature, have been considered. A new index named standardized residual sum of squares (STRESS), employed in multidimensional scaling techniques, is recommended. The main difference between PF/3 and STRESS is that the latter is simpler and allows inferences on the statistical significance of two color-difference formulas with respect to a given set of visual data.
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Equal Employment + Equal Pay = Multiple Problems for Colleges and Universities
ERIC Educational Resources Information Center
Steinbach, Sheldon Elliot; Reback, Joyce E.
1974-01-01
Issues involved in government regulation of university employment practices are discussed: confidentiality of records, pregnancy as a disability, alleged discrimination in benefits, tests and other employment criteria, seniority and layoff, reverse discrimination, use of statistics for determination of discrimination, and the Equal Pay Act. (JT)
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SIMPLIFIED PRACTICAL TEST METHOD FOR PORTABLE DOSE METERS USING SEVERAL SEALED RADIOACTIVE SOURCES.
Mikamoto, Takahiro; Yamada, Takahiro; Kurosawa, Tadahiro
2016-09-01
Sealed radioactive sources which have small activity were employed for the determination of response and tests for non-linearity and energy dependence of detector responses. Close source-to-detector geometry (at 0.3 m or less) was employed to practical tests for portable dose meters to accumulate statistically sufficient ionizing currents. Difference between response in the present experimentally studied field and in the reference field complied with ISO 4037 due to non-uniformity of radiation fluence at close geometry was corrected by use of Monte Carlo simulation. As a consequence, corrected results were consistent with the results obtained in the ISO 4037 reference field within their uncertainties. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Graph-based inductive reasoning.
Boumans, Marcel
2016-10-01
This article discusses methods of inductive inferences that are methods of visualizations designed in such a way that the "eye" can be employed as a reliable tool for judgment. The term "eye" is used as a stand-in for visual cognition and perceptual processing. In this paper "meaningfulness" has a particular meaning, namely accuracy, which is closeness to truth. Accuracy consists of precision and unbiasedness. Precision is dealt with by statistical methods, but for unbiasedness one needs expert judgment. The common view at the beginning of the twentieth century was to make the most efficient use of this kind of judgment by representing the data in shapes and forms in such a way that the "eye" can function as a reliable judge to reduce bias. The need for judgment of the "eye" is even more necessary when the background conditions of the observations are heterogeneous. Statistical procedures require a certain minimal level of homogeneity, but the "eye" does not. The "eye" is an adequate tool for assessing topological similarities when, due to heterogeneity of the data, metric assessment is not possible. In fact, graphical assessments precedes measurement, or to put it more forcefully, the graphic method is a necessary prerequisite for measurement. Copyright © 2016 Elsevier Ltd. All rights reserved.
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NASA Technical Reports Server (NTRS)
Rybicki, G. B.; Hummer, D. G.
1991-01-01
A method is presented for solving multilevel transfer problems when nonoverlapping lines and background continuum are present and active continuum transfer is absent. An approximate lambda operator is employed to derive linear, 'preconditioned', statistical-equilibrium equations. A method is described for finding the diagonal elements of the 'true' numerical lambda operator, and therefore for obtaining the coefficients of the equations. Iterations of the preconditioned equations, in conjunction with the transfer equation's formal solution, are used to solve linear equations. Some multilevel problems are considered, including an eleven-level neutral helium atom. Diagonal and tridiagonal approximate lambda operators are utilized in the problems to examine the convergence properties of the method, and it is found to be effective for the line transfer problems.
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[A range of mobbing among female and male nurses employed in the Szczecin hospitals].
Kunecka, Danuta; Kamińska, Magdalena; Karakiewicz, Beata
2008-01-01
Workplace mobbing, a particular type of conflict, has recently been recognized as one of the factors of occupational hazard, resulting from the social environment. Health service workers belong to occupational groups, which are particularly exposed to mobbing. Moreover, changes in the structure of medical labor market make that nurses often work under strong pressure and thus the phenomenon of mobbing becomes even more intensified. The aim of this study was to analyze the incidence of mobbing in the nursing stuff employed in the Szczecin hospitals. The method of diagnostic poll was based on a questionnaire, developed and distributed among 1578 respondents employed in hospitals in Szczecin. Of this number, 1261 correctly completed questionnaires were statistically analyzed. The results showed that the phenomenon of mobbing is actually common in the nursing occupational group (18.6%). The majority (40%) of respondents indicated a superior as a mobber (torturer). The high incidence of mobbing observed in the nursing occupational group may evidence that Human Resource Management (HRM) processes are not perfect.
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ERIC Educational Resources Information Center
Hollenbeck, Kevin
A study examined the effect of education and training on the economy and on employment outcomes. Data collected during a 1982 nationwide telephone survey of 3,500 employers were used as the basis for statistical models of voluntary and involuntary job separations and job promotions. Four major conclusions resulted from the modeling process…
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NASA Astrophysics Data System (ADS)
Senkbeil, J. C.; Brommer, D. M.; Comstock, I. J.; Loyd, T.
2012-07-01
Extratropical cyclones (ETCs) in the southern United States are often overlooked when compared with tropical cyclones in the region and ETCs in the northern United States. Although southern ETCs are significant weather events, there is currently not an operational scheme used for identifying and discussing these nameless storms. In this research, we classified 84 ETCs (1970-2009). We manually identified five distinct formation regions and seven unique ETC types using statistical classification. Statistical classification employed the use of principal components analysis and two methods of cluster analysis. Both manual and statistical storm types generally showed positive (negative) relationships with El Niño (La Niña). Manual storm types displayed precipitation swaths consistent with discrete storm tracks which further legitimizes the existence of multiple modes of southern ETCs. Statistical storm types also displayed unique precipitation intensity swaths, but these swaths were less indicative of track location. It is hoped that by classifying southern ETCs into types, that forecasters, hydrologists, and broadcast meteorologists might be able to better anticipate projected amounts of precipitation at their locations.
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NASA Astrophysics Data System (ADS)
Besic, Nikola; Ventura, Jordi Figueras i.; Grazioli, Jacopo; Gabella, Marco; Germann, Urs; Berne, Alexis
2016-09-01
Polarimetric radar-based hydrometeor classification is the procedure of identifying different types of hydrometeors by exploiting polarimetric radar observations. The main drawback of the existing supervised classification methods, mostly based on fuzzy logic, is a significant dependency on a presumed electromagnetic behaviour of different hydrometeor types. Namely, the results of the classification largely rely upon the quality of scattering simulations. When it comes to the unsupervised approach, it lacks the constraints related to the hydrometeor microphysics. The idea of the proposed method is to compensate for these drawbacks by combining the two approaches in a way that microphysical hypotheses can, to a degree, adjust the content of the classes obtained statistically from the observations. This is done by means of an iterative approach, performed offline, which, in a statistical framework, examines clustered representative polarimetric observations by comparing them to the presumed polarimetric properties of each hydrometeor class. Aside from comparing, a routine alters the content of clusters by encouraging further statistical clustering in case of non-identification. By merging all identified clusters, the multi-dimensional polarimetric signatures of various hydrometeor types are obtained for each of the studied representative datasets, i.e. for each radar system of interest. These are depicted by sets of centroids which are then employed in operational labelling of different hydrometeors. The method has been applied on three C-band datasets, each acquired by different operational radar from the MeteoSwiss Rad4Alp network, as well as on two X-band datasets acquired by two research mobile radars. The results are discussed through a comparative analysis which includes a corresponding supervised and unsupervised approach, emphasising the operational potential of the proposed method.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
al-Saffar, Sinan; Joslyn, Cliff A.; Chappell, Alan R.
As semantic datasets grow to be very large and divergent, there is a need to identify and exploit their inherent semantic structure for discovery and optimization. Towards that end, we present here a novel methodology to identify the semantic structures inherent in an arbitrary semantic graph dataset. We first present the concept of an extant ontology as a statistical description of the semantic relations present amongst the typed entities modeled in the graph. This serves as a model of the underlying semantic structure to aid in discovery and visualization. We then describe a method of ontological scaling in which themore » ontology is employed as a hierarchical scaling filter to infer different resolution levels at which the graph structures are to be viewed or analyzed. We illustrate these methods on three large and publicly available semantic datasets containing more than one billion edges each. Keywords-Semantic Web; Visualization; Ontology; Multi-resolution Data Mining;« less
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Estimating population diversity with CatchAll
Bunge, John; Woodard, Linda; Böhning, Dankmar; Foster, James A.; Connolly, Sean; Allen, Heather K.
2012-01-01
Motivation: The massive data produced by next-generation sequencing require advanced statistical tools. We address estimating the total diversity or species richness in a population. To date, only relatively simple methods have been implemented in available software. There is a need for software employing modern, computationally intensive statistical analyses including error, goodness-of-fit and robustness assessments. Results: We present CatchAll, a fast, easy-to-use, platform-independent program that computes maximum likelihood estimates for finite-mixture models, weighted linear regression-based analyses and coverage-based non-parametric methods, along with outlier diagnostics. Given sample ‘frequency count’ data, CatchAll computes 12 different diversity estimates and applies a model-selection algorithm. CatchAll also derives discounted diversity estimates to adjust for possibly uncertain low-frequency counts. It is accompanied by an Excel-based graphics program. Availability: Free executable downloads for Linux, Windows and Mac OS, with manual and source code, at www.northeastern.edu/catchall. Contact: jab18@cornell.edu PMID:22333246
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Evidence for social learning in wild lemurs (Lemur catta).
Kendal, Rachel L; Custance, Deborah M; Kendal, Jeremy R; Vale, Gillian; Stoinski, Tara S; Rakotomalala, Nirina Lalaina; Rasamimanana, Hantanirina
2010-08-01
Interest in social learning has been fueled by claims of culture in wild animals. These remain controversial because alternative explanations to social learning, such as asocial learning or ecological differences, remain difficult to refute. Compared with laboratory-based research, the study of social learning in natural contexts is in its infancy. Here, for the first time, we apply two new statistical methods, option-bias analysis and network-based diffusion analysis, to data from the wild, complemented by standard inferential statistics. Contrary to common thought regarding the cognitive abilities of prosimian primates, our evidence is consistent with social learning within subgroups in the ring-tailed lemur (Lemur catta), supporting the theory of directed social learning (Coussi-Korbel & Fragaszy, 1995). We also caution that, as the toolbox for capturing social learning in natural contexts grows, care is required in ensuring that the methods employed are appropriate-in particular, regarding social dynamics among study subjects. Supplemental materials for this article may be downloaded from http://lb.psychonomic-journals.org/content/supplemental.
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Malone, Patrick S.; Kertesz, Stefan G.; Wang, Yang; Costanzo, Philip R.
2009-01-01
Objectives. We assessed the relationship between alcohol consumption in young adulthood (ages 18–30 years) and occupational success 15 years later among Blacks and Whites. Methods. We analyzed data from the Coronary Artery Risk Development in Young Adults Study on employment status and occupational prestige at year 15 from baseline. The primary predictor was weekly alcohol use at baseline, after stratification by race and adjustment for socioeconomic factors. Results. We detected racial differences in the relationship between alcohol use in early adulthood and employment status at midlife. Blacks who were very heavy drinkers at baseline were more than 4 times as likely as Blacks who were occasional drinkers to be unemployed at year 15 (odds ratio [OR] = 4.34; 95% confidence interval [CI] = 2.22, 8.47). We found no statistically significant relationship among Whites. Occupational prestige at midlife was negatively related to very heavy drinking, but after adjustment for marital status, active coping, life stress, and educational attainment, this relationship was statistically significant only among Blacks. Conclusions. Heavy drinking during young adulthood was negatively associated with labor market success at midlife, especially among Blacks. PMID:19834006
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Certification Can Count: The Case of Aircraft Mechanics. Issues in Labor Statistics. Summary 02-03.
ERIC Educational Resources Information Center
Bureau of Labor Statistics, Washington, DC.
This document is a summary of aerospace industry technician statistics gathered by the Occupational Employment Statistics Survey for the year 2000 by the Department of Labor, Bureau of Labor Statistics. The data includes the following: (1) a comparison of wages earned by Federal Aviation Administration (FAA) certified and non-FAA certified…
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Code of Federal Regulations, 2010 CFR
2010-10-01
... statistical summaries and other information it maintains? 40.111 Section 40.111 Transportation Office of the... Testing Laboratories § 40.111 When and how must a laboratory disclose statistical summaries and other information it maintains? (a) As a laboratory, you must transmit an aggregate statistical summary, by employer...
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The Functional Relationship between Maternal Employment, Self-Concept; and Family Orientation.
ERIC Educational Resources Information Center
Goodwin, Paul; Newman, Isadore
This study investigated the relationships between maternal employment during three periods in the child's life, the child's self-concept, and family orientation. Variables statistically controlled were intactness of the family, father's employment status, the child's sex, the child's race, and the family's socioeconomic status. It was hypothesized…
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Women and Nontraditional Work.
ERIC Educational Resources Information Center
Mort, Heidi; Reisman, Janet
This fact sheet summarizes labor market statistics on nontraditional jobs for women and public policy, barriers, and strategies regarding such employment. Among the data presented are the following: nontraditional jobs for women are jobs in which 75 percent or more of those employed are men; 9 percent of all working women are employed in…
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From the necessary to the possible: the genesis of the spin-statistics theorem
NASA Astrophysics Data System (ADS)
Blum, Alexander
2014-12-01
The spin-statistics theorem, which relates the intrinsic angular momentum of a single particle to the type of quantum statistics obeyed by a system of many such particles, is one of the central theorems in quantum field theory and the physics of elementary particles. It was first formulated in 1939/40 by Wolfgang Pauli and his assistant Markus Fierz. This paper discusses the developments that led up to this first formulation, starting from early attempts in the late 1920s to explain why charged matter particles obey Fermi-Dirac statistics, while photons obey Bose-Einstein statistics. It is demonstrated how several important developments paved the way from such general philosophical musings to a general (and provable) theorem, most notably the use of quantum field theory, the discovery of new elementary particles, and the generalization of the notion of spin. It is also discussed how the attempts to prove a spin-statistics connection were driven by Pauli from formal to more physical arguments, culminating in Pauli's 1940 proof. This proof was a major success for the beleaguered theory of quantum field theory and the methods Pauli employed proved essential for the renaissance of quantum field theory and the development of renormalization techniques in the late 1940s.
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Zhao, Huiying; Nyholt, Dale R; Yang, Yuanhao; Wang, Jihua; Yang, Yuedong
2017-06-14
Genome-wide association studies (GWAS) have successfully identified single variants associated with diseases. To increase the power of GWAS, gene-based and pathway-based tests are commonly employed to detect more risk factors. However, the gene- and pathway-based association tests may be biased towards genes or pathways containing a large number of single-nucleotide polymorphisms (SNPs) with small P-values caused by high linkage disequilibrium (LD) correlations. To address such bias, numerous pathway-based methods have been developed. Here we propose a novel method, DGAT-path, to divide all SNPs assigned to genes in each pathway into LD blocks, and to sum the chi-square statistics of LD blocks for assessing the significance of the pathway by permutation tests. The method was proven robust with the type I error rate >1.6 times lower than other methods. Meanwhile, the method displays a higher power and is not biased by the pathway size. The applications to the GWAS summary statistics for schizophrenia and breast cancer indicate that the detected top pathways contain more genes close to associated SNPs than other methods. As a result, the method identified 17 and 12 significant pathways containing 20 and 21 novel associated genes, respectively for two diseases. The method is available online by http://sparks-lab.org/server/DGAT-path .
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a Data Field Method for Urban Remotely Sensed Imagery Classification Considering Spatial Correlation
NASA Astrophysics Data System (ADS)
Zhang, Y.; Qin, K.; Zeng, C.; Zhang, E. B.; Yue, M. X.; Tong, X.
2016-06-01
Spatial correlation between pixels is important information for remotely sensed imagery classification. Data field method and spatial autocorrelation statistics have been utilized to describe and model spatial information of local pixels. The original data field method can represent the spatial interactions of neighbourhood pixels effectively. However, its focus on measuring the grey level change between the central pixel and the neighbourhood pixels results in exaggerating the contribution of the central pixel to the whole local window. Besides, Geary's C has also been proven to well characterise and qualify the spatial correlation between each pixel and its neighbourhood pixels. But the extracted object is badly delineated with the distracting salt-and-pepper effect of isolated misclassified pixels. To correct this defect, we introduce the data field method for filtering and noise limitation. Moreover, the original data field method is enhanced by considering each pixel in the window as the central pixel to compute statistical characteristics between it and its neighbourhood pixels. The last step employs a support vector machine (SVM) for the classification of multi-features (e.g. the spectral feature and spatial correlation feature). In order to validate the effectiveness of the developed method, experiments are conducted on different remotely sensed images containing multiple complex object classes inside. The results show that the developed method outperforms the traditional method in terms of classification accuracies.
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Vanderoost, Filip; van der Wielen, Susan; van Nunen, Karolien; Van Hal, Guido
2013-01-01
Background The economic crisis of 2009 led to a wave of corporate reorganisations and bankruptcies, with many dismissals of employees. GPs were confronted with subsequent health consequences. Aim To assess the possible relationship between losing one’s job and having suicidal thoughts. Design and setting A survey of patients aged 18–49 years recruited from GP practices in Belgium in Deurne (Flemish region) and La Louvière (Walloon region) from September to December 2010. Method Anonymous self-administered questionnaire. Results Of all eligible patients (n = 1818), 831 were offered the questionnaire and 377 completed it (45.4%). More than one in five had been confronted with employment loss in the past year (the responder or someone close losing their job). Almost one in ten had lost their job themselves in the past year. More than one in four had experienced suicidal thoughts and 11.7% had seriously considered ending their life in the past year. In the logistic regression analysis, the following characteristics showed a statistically significant relationship with having suicidal thoughts: being single (odds ratio [OR] = 4.8, 95% confidence interval [CI] = 1.7 to 13.8), not having satisfying social contacts (OR = 5.1, 95% CI = 1.6 to 16.2), having depressive complaints (OR = 18.4, 95% CI = 5.8 to 58.4), and having lost one’s employment in the past year (OR = 8.8, 95% CI = 2.0 to 39.3). Conclusion This study points to a statistically significant relationship between losing one’s employment in the past year and having suicidal thoughts. It emphasises the important role of the GP in the continuous and reinforced assessment of suicidal risk in times of recession. PMID:24152484
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Khan, Mohammad Jakir Hossain; Hussain, Mohd Azlan; Mujtaba, Iqbal Mohammed
2014-01-01
Propylene is one type of plastic that is widely used in our everyday life. This study focuses on the identification and justification of the optimum process parameters for polypropylene production in a novel pilot plant based fluidized bed reactor. This first-of-its-kind statistical modeling with experimental validation for the process parameters of polypropylene production was conducted by applying ANNOVA (Analysis of variance) method to Response Surface Methodology (RSM). Three important process variables i.e., reaction temperature, system pressure and hydrogen percentage were considered as the important input factors for the polypropylene production in the analysis performed. In order to examine the effect of process parameters and their interactions, the ANOVA method was utilized among a range of other statistical diagnostic tools such as the correlation between actual and predicted values, the residuals and predicted response, outlier t plot, 3D response surface and contour analysis plots. The statistical analysis showed that the proposed quadratic model had a good fit with the experimental results. At optimum conditions with temperature of 75°C, system pressure of 25 bar and hydrogen percentage of 2%, the highest polypropylene production obtained is 5.82% per pass. Hence it is concluded that the developed experimental design and proposed model can be successfully employed with over a 95% confidence level for optimum polypropylene production in a fluidized bed catalytic reactor (FBCR). PMID:28788576
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NASA Astrophysics Data System (ADS)
Hoell, Simon; Omenzetter, Piotr
2017-04-01
The increasing demand for carbon neutral energy in a challenging economic environment is a driving factor for erecting ever larger wind turbines in harsh environments using novel wind turbine blade (WTBs) designs characterized by high flexibilities and lower buckling capacities. To counteract resulting increasing of operation and maintenance costs, efficient structural health monitoring systems can be employed to prevent dramatic failures and to schedule maintenance actions according to the true structural state. This paper presents a novel methodology for classifying structural damages using vibrational responses from a single sensor. The method is based on statistical classification using Bayes' theorem and an advanced statistic, which allows controlling the performance by varying the number of samples which represent the current state. This is done for multivariate damage sensitive features defined as partial autocorrelation coefficients (PACCs) estimated from vibrational responses and principal component analysis scores from PACCs. Additionally, optimal DSFs are composed not only for damage classification but also for damage detection based on binary statistical hypothesis testing, where features selections are found with a fast forward procedure. The method is applied to laboratory experiments with a small scale WTB with wind-like excitation and non-destructive damage scenarios. The obtained results demonstrate the advantages of the proposed procedure and are promising for future applications of vibration-based structural health monitoring in WTBs.
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Robust Strategy for Rocket Engine Health Monitoring
NASA Technical Reports Server (NTRS)
Santi, L. Michael
2001-01-01
Monitoring the health of rocket engine systems is essentially a two-phase process. The acquisition phase involves sensing physical conditions at selected locations, converting physical inputs to electrical signals, conditioning the signals as appropriate to establish scale or filter interference, and recording results in a form that is easy to interpret. The inference phase involves analysis of results from the acquisition phase, comparison of analysis results to established health measures, and assessment of health indications. A variety of analytical tools may be employed in the inference phase of health monitoring. These tools can be separated into three broad categories: statistical, rule based, and model based. Statistical methods can provide excellent comparative measures of engine operating health. They require well-characterized data from an ensemble of "typical" engines, or "golden" data from a specific test assumed to define the operating norm in order to establish reliable comparative measures. Statistical methods are generally suitable for real-time health monitoring because they do not deal with the physical complexities of engine operation. The utility of statistical methods in rocket engine health monitoring is hindered by practical limits on the quantity and quality of available data. This is due to the difficulty and high cost of data acquisition, the limited number of available test engines, and the problem of simulating flight conditions in ground test facilities. In addition, statistical methods incur a penalty for disregarding flow complexity and are therefore limited in their ability to define performance shift causality. Rule based methods infer the health state of the engine system based on comparison of individual measurements or combinations of measurements with defined health norms or rules. This does not mean that rule based methods are necessarily simple. Although binary yes-no health assessment can sometimes be established by relatively simple rules, the causality assignment needed for refined health monitoring often requires an exceptionally complex rule base involving complicated logical maps. Structuring the rule system to be clear and unambiguous can be difficult, and the expert input required to maintain a large logic network and associated rule base can be prohibitive.
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Yih, W Katherine; Maro, Judith C; Nguyen, Michael; Baker, Meghan A; Balsbaugh, Carolyn; Cole, David V; Dashevsky, Inna; Mba-Jonas, Adamma; Kulldorff, Martin
2018-06-01
The self-controlled tree-temporal scan statistic-a new signal-detection method-can evaluate whether any of a wide variety of health outcomes are temporally associated with receipt of a specific vaccine, while adjusting for multiple testing. Neither health outcomes nor postvaccination potential periods of increased risk need be prespecified. Using US medical claims data in the Food and Drug Administration's Sentinel system, we employed the method to evaluate adverse events occurring after receipt of quadrivalent human papillomavirus vaccine (4vHPV). Incident outcomes recorded in emergency department or inpatient settings within 56 days after first doses of 4vHPV received by 9- through 26.9-year-olds in 2006-2014 were identified using International Classification of Diseases, Ninth Revision, diagnosis codes and analyzed by pairing the new method with a standard hierarchical classification of diagnoses. On scanning diagnoses of 1.9 million 4vHPV recipients, 2 statistically significant categories of adverse events were found: cellulitis on days 2-3 after vaccination and "other complications of surgical and medical procedures" on days 1-3 after vaccination. Cellulitis is a known adverse event. Clinically informed investigation of electronic claims records of the patients with "other complications" did not suggest any previously unknown vaccine safety problem. Considering that thousands of potential short-term adverse events and hundreds of potential risk intervals were evaluated, these findings add significantly to the growing safety record of 4vHPV.
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1987-04-01
of jobs, four types of exclusionary barriers are investigated: "segregated networks" at the candidate stage, "information bias" and " statistical ...constitutional law, and socio-economic theory (for example, Glazer, 1975; Maguire, 1980). Disagreements have been particularly strong about the preferen...will present statistics on current labor market processes that can be used to assess the continuing need for strong policies of equal employment
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Transmit Designs for the MIMO Broadcast Channel With Statistical CSI
NASA Astrophysics Data System (ADS)
Wu, Yongpeng; Jin, Shi; Gao, Xiqi; McKay, Matthew R.; Xiao, Chengshan
2014-09-01
We investigate the multiple-input multiple-output broadcast channel with statistical channel state information available at the transmitter. The so-called linear assignment operation is employed, and necessary conditions are derived for the optimal transmit design under general fading conditions. Based on this, we introduce an iterative algorithm to maximize the linear assignment weighted sum-rate by applying a gradient descent method. To reduce complexity, we derive an upper bound of the linear assignment achievable rate of each receiver, from which a simplified closed-form expression for a near-optimal linear assignment matrix is derived. This reveals an interesting construction analogous to that of dirty-paper coding. In light of this, a low complexity transmission scheme is provided. Numerical examples illustrate the significant performance of the proposed low complexity scheme.
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NASA Astrophysics Data System (ADS)
Buchhave, Preben; Velte, Clara M.
2017-08-01
We present a method for converting a time record of turbulent velocity measured at a point in a flow to a spatial velocity record consisting of consecutive convection elements. The spatial record allows computation of dynamic statistical moments such as turbulent kinetic wavenumber spectra and spatial structure functions in a way that completely bypasses the need for Taylor's hypothesis. The spatial statistics agree with the classical counterparts, such as the total kinetic energy spectrum, at least for spatial extents up to the Taylor microscale. The requirements for applying the method are access to the instantaneous velocity magnitude, in addition to the desired flow quantity, and a high temporal resolution in comparison to the relevant time scales of the flow. We map, without distortion and bias, notoriously difficult developing turbulent high intensity flows using three main aspects that distinguish these measurements from previous work in the field: (1) The measurements are conducted using laser Doppler anemometry and are therefore not contaminated by directional ambiguity (in contrast to, e.g., frequently employed hot-wire anemometers); (2) the measurement data are extracted using a correctly and transparently functioning processor and are analysed using methods derived from first principles to provide unbiased estimates of the velocity statistics; (3) the exact mapping proposed herein has been applied to the high turbulence intensity flows investigated to avoid the significant distortions caused by Taylor's hypothesis. The method is first confirmed to produce the correct statistics using computer simulations and later applied to measurements in some of the most difficult regions of a round turbulent jet—the non-equilibrium developing region and the outermost parts of the developed jet. The proposed mapping is successfully validated using corresponding directly measured spatial statistics in the fully developed jet, even in the difficult outer regions of the jet where the average convection velocity is negligible and turbulence intensities increase dramatically. The measurements in the developing region reveal interesting features of an incomplete Richardson-Kolmogorov cascade under development.
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75 FR 41579 - Submitting Airline Data via the Internet
Federal Register 2010, 2011, 2012, 2013, 2014
2010-07-16
... Airline Information, RTS-42, Bureau of Transportation Statistics, Research and Innovative Technology... Statistics (BTS), must be submitted electronically (e- filing). The new e-filing system is designed to be... November 30, 2010. P-10 Employment Statistics by Labor Category--due February 20, 2011. A Certification...
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75 FR 3926 - Submission for OMB Emergency Review: Comment Request
Federal Register 2010, 2011, 2012, 2013, 2014
2010-01-25
... DEPARTMENT OF LABOR Bureau of Labor Statistics Submission for OMB Emergency Review: Comment.... Agency: Bureau of Labor Statistics. Type of Review: New collection. Title of Collection: Quarterly Census... appropriation tasks the Bureau of Labor Statistics (BLS) Quarterly Census of Employment and Wages (QCEW) program...
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NASA Astrophysics Data System (ADS)
Darvishzadeh, R.; Skidmore, A. K.; Mirzaie, M.; Atzberger, C.; Schlerf, M.
2014-12-01
Accurate estimation of grassland biomass at their peak productivity can provide crucial information regarding the functioning and productivity of the rangelands. Hyperspectral remote sensing has proved to be valuable for estimation of vegetation biophysical parameters such as biomass using different statistical techniques. However, in statistical analysis of hyperspectral data, multicollinearity is a common problem due to large amount of correlated hyper-spectral reflectance measurements. The aim of this study was to examine the prospect of above ground biomass estimation in a heterogeneous Mediterranean rangeland employing multivariate calibration methods. Canopy spectral measurements were made in the field using a GER 3700 spectroradiometer, along with concomitant in situ measurements of above ground biomass for 170 sample plots. Multivariate calibrations including partial least squares regression (PLSR), principal component regression (PCR), and Least-Squared Support Vector Machine (LS-SVM) were used to estimate the above ground biomass. The prediction accuracy of the multivariate calibration methods were assessed using cross validated R2 and RMSE. The best model performance was obtained using LS_SVM and then PLSR both calibrated with first derivative reflectance dataset with R2cv = 0.88 & 0.86 and RMSEcv= 1.15 & 1.07 respectively. The weakest prediction accuracy was appeared when PCR were used (R2cv = 0.31 and RMSEcv= 2.48). The obtained results highlight the importance of multivariate calibration methods for biomass estimation when hyperspectral data are used.
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NASA Astrophysics Data System (ADS)
Ushaq, Muhammad; Fang, Jiancheng
2013-10-01
Integrated navigation systems for various applications, generally employs the centralized Kalman filter (CKF) wherein all measured sensor data are communicated to a single central Kalman filter. The advantage of CKF is that there is a minimal loss of information and high precision under benign conditions. But CKF may suffer computational overloading, and poor fault tolerance. The alternative is the federated Kalman filter (FKF) wherein the local estimates can deliver optimal or suboptimal state estimate as per certain information fusion criterion. FKF has enhanced throughput and multiple level fault detection capability. The Standard CKF or FKF require that the system noise and the measurement noise are zero-mean and Gaussian. Moreover it is assumed that covariance of system and measurement noises remain constant. But if the theoretical and actual statistical features employed in Kalman filter are not compatible, the Kalman filter does not render satisfactory solutions and divergence problems also occur. To resolve such problems, in this paper, an adaptive Kalman filter scheme strengthened with fuzzy inference system (FIS) is employed to adapt the statistical features of contributing sensors, online, in the light of real system dynamics and varying measurement noises. The excessive faults are detected and isolated by employing Chi Square test method. As a case study, the presented scheme has been implemented on Strapdown Inertial Navigation System (SINS) integrated with the Celestial Navigation System (CNS), GPS and Doppler radar using FKF. Collectively the overall system can be termed as SINS/CNS/GPS/Doppler integrated navigation system. The simulation results have validated the effectiveness of the presented scheme with significantly enhanced precision, reliability and fault tolerance. Effectiveness of the scheme has been tested against simulated abnormal errors/noises during different time segments of flight. It is believed that the presented scheme can be applied to the navigation system of aircraft or unmanned aerial vehicle (UAV).
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Comparison of Sample Size by Bootstrap and by Formulas Based on Normal Distribution Assumption.
Wang, Zuozhen
2018-01-01
Bootstrapping technique is distribution-independent, which provides an indirect way to estimate the sample size for a clinical trial based on a relatively smaller sample. In this paper, sample size estimation to compare two parallel-design arms for continuous data by bootstrap procedure are presented for various test types (inequality, non-inferiority, superiority, and equivalence), respectively. Meanwhile, sample size calculation by mathematical formulas (normal distribution assumption) for the identical data are also carried out. Consequently, power difference between the two calculation methods is acceptably small for all the test types. It shows that the bootstrap procedure is a credible technique for sample size estimation. After that, we compared the powers determined using the two methods based on data that violate the normal distribution assumption. To accommodate the feature of the data, the nonparametric statistical method of Wilcoxon test was applied to compare the two groups in the data during the process of bootstrap power estimation. As a result, the power estimated by normal distribution-based formula is far larger than that by bootstrap for each specific sample size per group. Hence, for this type of data, it is preferable that the bootstrap method be applied for sample size calculation at the beginning, and that the same statistical method as used in the subsequent statistical analysis is employed for each bootstrap sample during the course of bootstrap sample size estimation, provided there is historical true data available that can be well representative of the population to which the proposed trial is planning to extrapolate.
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Looking for a Job While Employed. Issues in Labor Statistics. Summary 97-14.
ERIC Educational Resources Information Center
Bureau of Labor Statistics, Washington, DC.
In February 1995, a supplement to the Current Population Survey examined the job search rate among a sample of 108,876 employed persons (except unpaid family workers) who had worked for their employer for at least 3 months were asked if they had looked for others employment since December 1994. Of those surveyed, 6,044 (5.6%) had actively searched…
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Spectroscopic Diagnosis of Arsenic Contamination in Agricultural Soils
Shi, Tiezhu; Liu, Huizeng; Chen, Yiyun; Fei, Teng; Wang, Junjie; Wu, Guofeng
2017-01-01
This study investigated the abilities of pre-processing, feature selection and machine-learning methods for the spectroscopic diagnosis of soil arsenic contamination. The spectral data were pre-processed by using Savitzky-Golay smoothing, first and second derivatives, multiplicative scatter correction, standard normal variate, and mean centering. Principle component analysis (PCA) and the RELIEF algorithm were used to extract spectral features. Machine-learning methods, including random forests (RF), artificial neural network (ANN), radial basis function- and linear function- based support vector machine (RBF- and LF-SVM) were employed for establishing diagnosis models. The model accuracies were evaluated and compared by using overall accuracies (OAs). The statistical significance of the difference between models was evaluated by using McNemar’s test (Z value). The results showed that the OAs varied with the different combinations of pre-processing, feature selection, and classification methods. Feature selection methods could improve the modeling efficiencies and diagnosis accuracies, and RELIEF often outperformed PCA. The optimal models established by RF (OA = 86%), ANN (OA = 89%), RBF- (OA = 89%) and LF-SVM (OA = 87%) had no statistical difference in diagnosis accuracies (Z < 1.96, p < 0.05). These results indicated that it was feasible to diagnose soil arsenic contamination using reflectance spectroscopy. The appropriate combination of multivariate methods was important to improve diagnosis accuracies. PMID:28471412
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Genetic algorithm for the optimization of features and neural networks in ECG signals classification
NASA Astrophysics Data System (ADS)
Li, Hongqiang; Yuan, Danyang; Ma, Xiangdong; Cui, Dianyin; Cao, Lu
2017-01-01
Feature extraction and classification of electrocardiogram (ECG) signals are necessary for the automatic diagnosis of cardiac diseases. In this study, a novel method based on genetic algorithm-back propagation neural network (GA-BPNN) for classifying ECG signals with feature extraction using wavelet packet decomposition (WPD) is proposed. WPD combined with the statistical method is utilized to extract the effective features of ECG signals. The statistical features of the wavelet packet coefficients are calculated as the feature sets. GA is employed to decrease the dimensions of the feature sets and to optimize the weights and biases of the back propagation neural network (BPNN). Thereafter, the optimized BPNN classifier is applied to classify six types of ECG signals. In addition, an experimental platform is constructed for ECG signal acquisition to supply the ECG data for verifying the effectiveness of the proposed method. The GA-BPNN method with the MIT-BIH arrhythmia database achieved a dimension reduction of nearly 50% and produced good classification results with an accuracy of 97.78%. The experimental results based on the established acquisition platform indicated that the GA-BPNN method achieved a high classification accuracy of 99.33% and could be efficiently applied in the automatic identification of cardiac arrhythmias.
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Neighbors, Charles J.; Kuerbis, Alexis; Riordan, Annette; Blanchard, Kimberly A.; McVeigh, Katharine H.; Morgan, Thomas J.; McCrady, Barbara
2009-01-01
Objective. We examined abstinence rates among substance-dependent women receiving Temporary Assistance for Needy Families (TANF) in intensive case management (ICM) over 24 months and whether ICM yielded significantly better employment outcomes compared with a screen-and-refer program (i.e., usual care). Methods. Substance-dependent (n = 302) and non–substance dependent (n = 150) TANF applicants in Essex County, New Jersey, were recruited. We randomly assigned substance-dependent women to ICM or usual care. We interviewed all women at 3, 9, 15, and 24 months. Results. Abstinence rates were higher for the ICM group than for the usual care group through 24 months of follow-up (odds ratio [OR] = 2.11; 95% confidence interval [CI] = 1.36, 3.29). A statistically significant interaction between time and group on number of days employed indicated that the rate of improvement over time in employment was greater for the ICM group than for the usual care group (incidence rate ratio = 1.03; 95% CI = 1.02, 1.04). Additionally, there were greater odds of being employed full time for those in the ICM group (OR = 1.68; 95% CI = 1.12, 2.51). Conclusions. ICM is a promising intervention for managing substance dependence among women receiving TANF and for improving employment rates among this vulnerable population. PMID:19059855
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Bacci, Silvia; Pigini, Claudia; Seracini, Marco; Minelli, Liliana
2017-02-03
Background : The mixed empirical evidence about employment conditions (i.e., permanent vs. temporary job, full-time vs. part-time job) as well as unemployment has motivated the development of conceptual models with the aim of assessing the pathways leading to effects of employment status on health. Alongside physically and psychologically riskier working conditions, one channel stems in the possibly severe economic deprivation faced by temporary workers. We investigate whether economic deprivation is able to partly capture the effect of employment status on Self-evaluated Health Status (SHS). Methods : Our analysis is based on the European Union Statistics on Income and Living Conditions (EU-SILC) survey, for a balanced sample from 26 countries from 2009 to 2012. We estimate a correlated random-effects logit model for the SHS that accounts for the ordered nature of the dependent variable and the longitudinal structure of the data. Results and Discussion : Material deprivation and economic strain are able to partly account for the negative effects on SHS from precarious and part-time employment as well as from unemployment that, however, exhibits a significant independent negative association with SHS. Conclusions : Some of the indicators used to proxy economic deprivation are significant predictors of SHS and their correlation with the employment condition is such that it should not be neglected in empirical analysis, when available and further to the monetary income.
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Bacci, Silvia; Pigini, Claudia; Seracini, Marco; Minelli, Liliana
2017-01-01
Background: The mixed empirical evidence about employment conditions (i.e., permanent vs. temporary job, full-time vs. part-time job) as well as unemployment has motivated the development of conceptual models with the aim of assessing the pathways leading to effects of employment status on health. Alongside physically and psychologically riskier working conditions, one channel stems in the possibly severe economic deprivation faced by temporary workers. We investigate whether economic deprivation is able to partly capture the effect of employment status on Self-evaluated Health Status (SHS). Methods: Our analysis is based on the European Union Statistics on Income and Living Conditions (EU-SILC) survey, for a balanced sample from 26 countries from 2009 to 2012. We estimate a correlated random-effects logit model for the SHS that accounts for the ordered nature of the dependent variable and the longitudinal structure of the data. Results and Discussion: Material deprivation and economic strain are able to partly account for the negative effects on SHS from precarious and part-time employment as well as from unemployment that, however, exhibits a significant independent negative association with SHS. Conclusions: Some of the indicators used to proxy economic deprivation are significant predictors of SHS and their correlation with the employment condition is such that it should not be neglected in empirical analysis, when available and further to the monetary income. PMID:28165375
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NASA Astrophysics Data System (ADS)
Feyen, Luc; Caers, Jef
2006-06-01
In this work, we address the problem of characterizing the heterogeneity and uncertainty of hydraulic properties for complex geological settings. Hereby, we distinguish between two scales of heterogeneity, namely the hydrofacies structure and the intrafacies variability of the hydraulic properties. We employ multiple-point geostatistics to characterize the hydrofacies architecture. The multiple-point statistics are borrowed from a training image that is designed to reflect the prior geological conceptualization. The intrafacies variability of the hydraulic properties is represented using conventional two-point correlation methods, more precisely, spatial covariance models under a multi-Gaussian spatial law. We address the different levels and sources of uncertainty in characterizing the subsurface heterogeneity, and explore their effect on groundwater flow and transport predictions. Typically, uncertainty is assessed by way of many images, termed realizations, of a fixed statistical model. However, in many cases, sampling from a fixed stochastic model does not adequately represent the space of uncertainty. It neglects the uncertainty related to the selection of the stochastic model and the estimation of its input parameters. We acknowledge the uncertainty inherent in the definition of the prior conceptual model of aquifer architecture and in the estimation of global statistics, anisotropy, and correlation scales. Spatial bootstrap is used to assess the uncertainty of the unknown statistical parameters. As an illustrative example, we employ a synthetic field that represents a fluvial setting consisting of an interconnected network of channel sands embedded within finer-grained floodplain material. For this highly non-stationary setting we quantify the groundwater flow and transport model prediction uncertainty for various levels of hydrogeological uncertainty. Results indicate the importance of accurately describing the facies geometry, especially for transport predictions.
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Keith, Jeff; Westbury, Chris; Goldman, James
2015-09-01
Corpus-based semantic space models, which primarily rely on lexical co-occurrence statistics, have proven effective in modeling and predicting human behavior in a number of experimental paradigms that explore semantic memory representation. The most widely studied extant models, however, are strongly influenced by orthographic word frequency (e.g., Shaoul & Westbury, Behavior Research Methods, 38, 190-195, 2006). This has the implication that high-frequency closed-class words can potentially bias co-occurrence statistics. Because these closed-class words are purported to carry primarily syntactic, rather than semantic, information, the performance of corpus-based semantic space models may be improved by excluding closed-class words (using stop lists) from co-occurrence statistics, while retaining their syntactic information through other means (e.g., part-of-speech tagging and/or affixes from inflected word forms). Additionally, very little work has been done to explore the effect of employing morphological decomposition on the inflected forms of words in corpora prior to compiling co-occurrence statistics, despite (controversial) evidence that humans perform early morphological decomposition in semantic processing. In this study, we explored the impact of these factors on corpus-based semantic space models. From this study, morphological decomposition appears to significantly improve performance in word-word co-occurrence semantic space models, providing some support for the claim that sublexical information-specifically, word morphology-plays a role in lexical semantic processing. An overall decrease in performance was observed in models employing stop lists (e.g., excluding closed-class words). Furthermore, we found some evidence that weakens the claim that closed-class words supply primarily syntactic information in word-word co-occurrence semantic space models.
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NASA Astrophysics Data System (ADS)
Eum, H. I.; Cannon, A. J.
2015-12-01
Climate models are a key provider to investigate impacts of projected future climate conditions on regional hydrologic systems. However, there is a considerable mismatch of spatial resolution between GCMs and regional applications, in particular a region characterized by complex terrain such as Korean peninsula. Therefore, a downscaling procedure is an essential to assess regional impacts of climate change. Numerous statistical downscaling methods have been used mainly due to the computational efficiency and simplicity. In this study, four statistical downscaling methods [Bias-Correction/Spatial Disaggregation (BCSD), Bias-Correction/Constructed Analogue (BCCA), Multivariate Adaptive Constructed Analogs (MACA), and Bias-Correction/Climate Imprint (BCCI)] are applied to downscale the latest Climate Forecast System Reanalysis data to stations for precipitation, maximum temperature, and minimum temperature over South Korea. By split sampling scheme, all methods are calibrated with observational station data for 19 years from 1973 to 1991 are and tested for the recent 19 years from 1992 to 2010. To assess skill of the downscaling methods, we construct a comprehensive suite of performance metrics that measure an ability of reproducing temporal correlation, distribution, spatial correlation, and extreme events. In addition, we employ Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify robust statistical downscaling methods based on the performance metrics for each season. The results show that downscaling skill is considerably affected by the skill of CFSR and all methods lead to large improvements in representing all performance metrics. According to seasonal performance metrics evaluated, when TOPSIS is applied, MACA is identified as the most reliable and robust method for all variables and seasons. Note that such result is derived from CFSR output which is recognized as near perfect climate data in climate studies. Therefore, the ranking of this study may be changed when various GCMs are downscaled and evaluated. Nevertheless, it may be informative for end-users (i.e. modelers or water resources managers) to understand and select more suitable downscaling methods corresponding to priorities on regional applications.
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NASA Technical Reports Server (NTRS)
Crowe, D. R.; Henricks, W.
1983-01-01
The combined load statistics are developed by taking the acoustically induced load to be a random population, assumed to be stationary. Each element of this ensemble of acoustically induced loads is assumed to have the same power spectral density (PSD), obtained previously from a random response analysis employing the given acoustic field in the STS cargo bay as a stationary random excitation. The mechanically induced load is treated as either (1) a known deterministic transient, or (2) a nonstationary random variable of known first and second statistical moments which vary with time. A method is then shown for determining the probability that the combined load would, at any time, have a value equal to or less than a certain level. Having obtained a statistical representation of how the acoustic and mechanical loads are expected to combine, an analytical approximation for defining design levels for these loads is presented using the First Passage failure criterion.
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A statistical mechanics model for free-for-all airplane passenger boarding
DOE Office of Scientific and Technical Information (OSTI.GOV)
Steffen, Jason H.; /Fermilab
2008-08-01
I discuss a model for free-for-all passenger boarding which is employed by some discount air carriers. The model is based on the principles of statistical mechanics where each seat in the aircraft has an associated energy which reflects the preferences of travelers. As each passenger enters the airplane they select their seats using Boltzmann statistics, proceed to that location, load their luggage, sit down, and the partition function seen by remaining passengers is modified to reflect this fact. I discuss the various model parameters and make qualitative comparisons of this passenger boarding model with those that involve assigned seats. Themore » model can be used to predict the probability that certain seats will be occupied at different times during the boarding process. These results might provide a useful description of this boarding method. The model is a relatively unusual application of undergraduate level physics and describes a situation familiar to many students and faculty.« less
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Profile Of 'Original Articles' Published In 2016 By The Journal Of Ayub Medical College, Pakistan.
Shaikh, Masood Ali
2018-01-01
Journal of Ayub Medical College (JAMC) is the only Medline indexed biomedical journal of Pakistan that is edited and published by a medical college. Assessing the trends of study designs employed, statistical methods used, and statistical analysis software used in the articles of medical journals help understand the sophistication of research published. The objectives of this descriptive study were to assess all original articles published by JAMC in the year 2016. JAMC published 147 original articles in the year 2016. The most commonly used study design was crosssectional studies, with 64 (43.5%) articles reporting its use. Statistical tests involving bivariate analysis were most common and reported by 73 (49.6%) articles. Use of SPSS software was reported by 109 (74.1%) of articles. Most 138 (93.9%) of the original articles published were based on studies conducted in Pakistan. The number and sophistication of analysis reported in JAMC increased from year 2014 to 2016.
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Cascioli, Vincenzo; Liu, Zhuofu; Heusch, Andrew; McCarthy, Peter W
2016-05-01
This study presents a method for objectively measuring in-chair movement (ICM) that shows correlation with subjective ratings of comfort and discomfort. Employing a cross-over controlled, single blind design, healthy young subjects (n = 21) sat for 18 min on each of the following surfaces: contoured foam, straight foam and wood. Force sensitive resistors attached to the sitting interface measured the relative movements of the subjects during sitting. The purpose of this study was to determine whether ICM could statistically distinguish between each seat material, including two with subtle design differences. In addition, this study investigated methodological considerations, in particular appropriate threshold selection and sitting duration, when analysing objective movement data. ICM appears to be able to statistically distinguish between similar foam surfaces, as long as appropriate ICM thresholds and sufficient sitting durations are present. A relationship between greater ICM and increased discomfort, and lesser ICM and increased comfort was also found. Copyright © 2016. Published by Elsevier Ltd.
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Bruni, Aline Thaís; Velho, Jesus Antonio; Ferreira, Arthur Serra Lopes; Tasso, Maria Júlia; Ferrari, Raíssa Santos; Yoshida, Ricardo Luís; Dias, Marcos Salvador; Leite, Vitor Barbanti Pereira
2014-08-01
This study uses statistical techniques to evaluate reports on suicide scenes; it utilizes 80 reports from different locations in Brazil, randomly collected from both federal and state jurisdictions. We aimed to assess a heterogeneous group of cases in order to obtain an overall perspective of the problem. We evaluated variables regarding the characteristics of the crime scene, such as the detected traces (blood, instruments and clothes) that were found and we addressed the methodology employed by the experts. A qualitative approach using basic statistics revealed a wide distribution as to how the issue was addressed in the documents. We examined a quantitative approach involving an empirical equation and we used multivariate procedures to validate the quantitative methodology proposed for this empirical equation. The methodology successfully identified the main differences in the information presented in the reports, showing that there is no standardized method of analyzing evidences. Copyright © 2014 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.
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Seasonal Drought Prediction: Advances, Challenges, and Future Prospects
NASA Astrophysics Data System (ADS)
Hao, Zengchao; Singh, Vijay P.; Xia, Youlong
2018-03-01
Drought prediction is of critical importance to early warning for drought managements. This review provides a synthesis of drought prediction based on statistical, dynamical, and hybrid methods. Statistical drought prediction is achieved by modeling the relationship between drought indices of interest and a suite of potential predictors, including large-scale climate indices, local climate variables, and land initial conditions. Dynamical meteorological drought prediction relies on seasonal climate forecast from general circulation models (GCMs), which can be employed to drive hydrological models for agricultural and hydrological drought prediction with the predictability determined by both climate forcings and initial conditions. Challenges still exist in drought prediction at long lead time and under a changing environment resulting from natural and anthropogenic factors. Future research prospects to improve drought prediction include, but are not limited to, high-quality data assimilation, improved model development with key processes related to drought occurrence, optimal ensemble forecast to select or weight ensembles, and hybrid drought prediction to merge statistical and dynamical forecasts.
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Lagrangian statistics in compressible isotropic homogeneous turbulence
NASA Astrophysics Data System (ADS)
Yang, Yantao; Wang, Jianchun; Shi, Yipeng; Chen, Shiyi
2011-11-01
In this work we conducted the Direct Numerical Simulation (DNS) of a forced compressible isotropic homogeneous turbulence and investigated the flow statistics from the Lagrangian point of view, namely the statistics is computed following the passive tracers trajectories. The numerical method combined the Eulerian field solver which was developed by Wang et al. (2010, J. Comp. Phys., 229, 5257-5279), and a Lagrangian module for tracking the tracers and recording the data. The Lagrangian probability density functions (p.d.f.'s) have then been calculated for both kinetic and thermodynamic quantities. In order to isolate the shearing part from the compressing part of the flow, we employed the Helmholtz decomposition to decompose the flow field (mainly the velocity field) into the solenoidal and compressive parts. The solenoidal part was compared with the incompressible case, while the compressibility effect showed up in the compressive part. The Lagrangian structure functions and cross-correlation between various quantities will also be discussed. This work was supported in part by the China's Turbulence Program under Grant No.2009CB724101.
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A Seasonal Time-Series Model Based on Gene Expression Programming for Predicting Financial Distress
2018-01-01
The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations. Therefore, this study employed the nonlinear attribute selection method to build a nonlinear financial distress prediction model: that is, this paper proposed a novel seasonal time-series gene expression programming model for predicting the financial distress of companies. The proposed model has several advantages including the following: (i) the proposed model is different from the previous models lacking the concept of time series; (ii) the proposed integrated attribute selection method can find the core attributes and reduce high dimensional data; and (iii) the proposed model can generate the rules and mathematical formulas of financial distress for providing references to the investors and decision makers. The result shows that the proposed method is better than the listing classifiers under three criteria; hence, the proposed model has competitive advantages in predicting the financial distress of companies. PMID:29765399
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A Seasonal Time-Series Model Based on Gene Expression Programming for Predicting Financial Distress.
Cheng, Ching-Hsue; Chan, Chia-Pang; Yang, Jun-He
2018-01-01
The issue of financial distress prediction plays an important and challenging research topic in the financial field. Currently, there have been many methods for predicting firm bankruptcy and financial crisis, including the artificial intelligence and the traditional statistical methods, and the past studies have shown that the prediction result of the artificial intelligence method is better than the traditional statistical method. Financial statements are quarterly reports; hence, the financial crisis of companies is seasonal time-series data, and the attribute data affecting the financial distress of companies is nonlinear and nonstationary time-series data with fluctuations. Therefore, this study employed the nonlinear attribute selection method to build a nonlinear financial distress prediction model: that is, this paper proposed a novel seasonal time-series gene expression programming model for predicting the financial distress of companies. The proposed model has several advantages including the following: (i) the proposed model is different from the previous models lacking the concept of time series; (ii) the proposed integrated attribute selection method can find the core attributes and reduce high dimensional data; and (iii) the proposed model can generate the rules and mathematical formulas of financial distress for providing references to the investors and decision makers. The result shows that the proposed method is better than the listing classifiers under three criteria; hence, the proposed model has competitive advantages in predicting the financial distress of companies.
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A Critique of Divorce Statistics and Their Interpretation.
ERIC Educational Resources Information Center
Crosby, John F.
1980-01-01
Increasingly, appeals to the divorce statistic are employed to substantiate claims that the family is in a state of breakdown and marriage is passe. This article contains a consideration of reasons why the divorce statistics are invalid and/or unreliable as indicators of the present state of marriage and family. (Author)
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Using Statistical Process Control to Make Data-Based Clinical Decisions.
ERIC Educational Resources Information Center
Pfadt, Al; Wheeler, Donald J.
1995-01-01
Statistical process control (SPC), which employs simple statistical tools and problem-solving techniques such as histograms, control charts, flow charts, and Pareto charts to implement continual product improvement procedures, can be incorporated into human service organizations. Examples illustrate use of SPC procedures to analyze behavioral data…
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Handbook of Labor Statistics. Bulletin 2175.
ERIC Educational Resources Information Center
Springsteen, Rosalind, Comp.; Epstein, Rosalie, Comp.
This publication makes available in one volume the major series produced by the Bureau of Labor Statistics. Technical notes preceding each major section contain information on data changes and explain the services. Forty-four tables derived from the Current Population Survey (CPS) provide statistics on labor force and employment status,…
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76 FR 34385 - Program Integrity: Gainful Employment-Debt Measures
Federal Register 2010, 2011, 2012, 2013, 2014
2011-06-13
... postsecondary education at a public institution. National Center for Education Statistics, 2004/2009 Beginning... reliable earnings information, including use of State data, survey data, or Bureau of Labor Statistics (BLS...
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Overworked? An Observation of the Relationship between Student Employment and Academic Performance
ERIC Educational Resources Information Center
Logan, Jennifer; Hughes, Traci; Logan, Brian
2016-01-01
Current observations from the National Center for Education Statistics demonstrate the dramatic increase in college student employment over the past few decades. Not only are more students employed than in previous decades, students are working more hours. This could lead to declines in academic performance as hours worked increase, resulting in…
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The Impact of Social Capital on the Employment of College Graduates
ERIC Educational Resources Information Center
Fengqiao, Yan; Dan, Mao
2015-01-01
This article addresses the impact of social capital on college graduate employment. After reviewing the literature, the authors analyze data collected by Peking University from 34 universities in 2005 and use statistical analysis to clarify the impact of social capital on students' choice of employment or further study, job placement rate,…
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Employment and Unemployment in 1976. Special Labor Force Report 199.
ERIC Educational Resources Information Center
Bednarzik, Robert W.; St. Marie, Stephen M.
Changes in employment and unemployment in 1976, presented through the use of statistical data in tabular and chart forms, is the focus of this report. Protection for the unemployed, labor force trends, and persons of Spanish origin are also discussed under separate minor headings. Under the section on employment, the following subsections are…
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Sex Discrimination in Employment. Research Report No. 171.
ERIC Educational Resources Information Center
Morris, J. David; Wood, Linda B.
This report examines the status of women and the laws that have been enacted to protect women from discrimination in employment. Written in lay language, it examines employment and occupational statistics for women in the United States and in Kentucky. Following an introduction in Chapter 1, the report presents four chapters surveying the problem,…
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The 1988-89 Job Outlook in Brief.
ERIC Educational Resources Information Center
White, Martha C.
1988-01-01
This article summarizes the employment outlook in 225 occupations as projected by the Bureau of Labor Statistics. It provides thumbnail sketches of employment data for each of the occupations in the 1988-89 "Occupational Outlook Handbook," on which it is based. Each entry presents the occupation's title, 1986 employment numbers, the percent change…
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Employers and Child Care: What Roles Do They Play?
ERIC Educational Resources Information Center
Hayghe, Howard V.
1988-01-01
The Bureau of Labor Statistics conducted a nationwide survey of approximately 10,000 businesses and government agencies in 1987. Results show that about 2 percent of employers sponsored day-care centers and 3 percent provide financial assistance toward expenses. However, employers are doing other things to aid employees with growing children. (JOW)
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20 CFR 656.40 - Determination of prevailing wage for labor certification purposes.
Code of Federal Regulations, 2010 CFR
2010-04-01
... Occupational Employment Statistics Survey shall be used to determine the arithmetic mean, unless the employer provides an acceptable survey under paragraph (g) of this section. (3) If the employer provides a survey... education and research entities. In computing the prevailing wage for a job opportunity in an occupational...
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20 CFR 656.40 - Determination of prevailing wage for labor certification purposes.
Code of Federal Regulations, 2013 CFR
2013-04-01
... Occupational Employment Statistics Survey shall be used to determine the arithmetic mean, unless the employer provides an acceptable survey under paragraph (g) of this section. (3) If the employer provides a survey... education and research entities. In computing the prevailing wage for a job opportunity in an occupational...
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20 CFR 656.40 - Determination of prevailing wage for labor certification purposes.
Code of Federal Regulations, 2011 CFR
2011-04-01
... Occupational Employment Statistics Survey shall be used to determine the arithmetic mean, unless the employer provides an acceptable survey under paragraph (g) of this section. (3) If the employer provides a survey... education and research entities. In computing the prevailing wage for a job opportunity in an occupational...
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20 CFR 656.40 - Determination of prevailing wage for labor certification purposes.
Code of Federal Regulations, 2014 CFR
2014-04-01
... Occupational Employment Statistics Survey shall be used to determine the arithmetic mean, unless the employer provides an acceptable survey under paragraph (g) of this section. (3) If the employer provides a survey... education and research entities. In computing the prevailing wage for a job opportunity in an occupational...
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20 CFR 656.40 - Determination of prevailing wage for labor certification purposes.
Code of Federal Regulations, 2012 CFR
2012-04-01
... Occupational Employment Statistics Survey shall be used to determine the arithmetic mean, unless the employer provides an acceptable survey under paragraph (g) of this section. (3) If the employer provides a survey... education and research entities. In computing the prevailing wage for a job opportunity in an occupational...
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Miller, Nathan D; Durham Brooks, Tessa L; Assadi, Amir H; Spalding, Edgar P
2010-10-01
Gene disruption frequently produces no phenotype in the model plant Arabidopsis thaliana, complicating studies of gene function. Functional redundancy between gene family members is one common explanation but inadequate detection methods could also be responsible. Here, newly developed methods for automated capture and processing of time series of images, followed by computational analysis employing modified linear discriminant analysis (LDA) and wavelet-based differentiation, were employed in a study of mutants lacking the Glutamate Receptor-Like 3.3 gene. Root gravitropism was selected as the process to study with high spatiotemporal resolution because the ligand-gated Ca(2+)-permeable channel encoded by GLR3.3 may contribute to the ion fluxes associated with gravity signal transduction in roots. Time series of root tip angles were collected from wild type and two different glr3.3 mutants across a grid of seed-size and seedling-age conditions previously found to be important to gravitropism. Statistical tests of average responses detected no significant difference between populations, but LDA separated both mutant alleles from the wild type. After projecting the data onto LDA solution vectors, glr3.3 mutants displayed greater population variance than the wild type in all four conditions. In three conditions the projection means also differed significantly between mutant and wild type. Wavelet analysis of the raw response curves showed that the LDA-detected phenotypes related to an early deceleration and subsequent slower-bending phase in glr3.3 mutants. These statistically significant, heritable, computation-based phenotypes generated insight into functions of GLR3.3 in gravitropism. The methods could be generally applicable to the study of phenotypes and therefore gene function.
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Miller, Nathan D.; Durham Brooks, Tessa L.; Assadi, Amir H.; Spalding, Edgar P.
2010-01-01
Gene disruption frequently produces no phenotype in the model plant Arabidopsis thaliana, complicating studies of gene function. Functional redundancy between gene family members is one common explanation but inadequate detection methods could also be responsible. Here, newly developed methods for automated capture and processing of time series of images, followed by computational analysis employing modified linear discriminant analysis (LDA) and wavelet-based differentiation, were employed in a study of mutants lacking the Glutamate Receptor-Like 3.3 gene. Root gravitropism was selected as the process to study with high spatiotemporal resolution because the ligand-gated Ca2+-permeable channel encoded by GLR3.3 may contribute to the ion fluxes associated with gravity signal transduction in roots. Time series of root tip angles were collected from wild type and two different glr3.3 mutants across a grid of seed-size and seedling-age conditions previously found to be important to gravitropism. Statistical tests of average responses detected no significant difference between populations, but LDA separated both mutant alleles from the wild type. After projecting the data onto LDA solution vectors, glr3.3 mutants displayed greater population variance than the wild type in all four conditions. In three conditions the projection means also differed significantly between mutant and wild type. Wavelet analysis of the raw response curves showed that the LDA-detected phenotypes related to an early deceleration and subsequent slower-bending phase in glr3.3 mutants. These statistically significant, heritable, computation-based phenotypes generated insight into functions of GLR3.3 in gravitropism. The methods could be generally applicable to the study of phenotypes and therefore gene function. PMID:20647506
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A study on building data warehouse of hospital information system.
Li, Ping; Wu, Tao; Chen, Mu; Zhou, Bin; Xu, Wei-guo
2011-08-01
Existing hospital information systems with simple statistical functions cannot meet current management needs. It is well known that hospital resources are distributed with private property rights among hospitals, such as in the case of the regional coordination of medical services. In this study, to integrate and make full use of medical data effectively, we propose a data warehouse modeling method for the hospital information system. The method can also be employed for a distributed-hospital medical service system. To ensure that hospital information supports the diverse needs of health care, the framework of the hospital information system has three layers: datacenter layer, system-function layer, and user-interface layer. This paper discusses the role of a data warehouse management system in handling hospital information from the establishment of the data theme to the design of a data model to the establishment of a data warehouse. Online analytical processing tools assist user-friendly multidimensional analysis from a number of different angles to extract the required data and information. Use of the data warehouse improves online analytical processing and mitigates deficiencies in the decision support system. The hospital information system based on a data warehouse effectively employs statistical analysis and data mining technology to handle massive quantities of historical data, and summarizes from clinical and hospital information for decision making. This paper proposes the use of a data warehouse for a hospital information system, specifically a data warehouse for the theme of hospital information to determine latitude, modeling and so on. The processing of patient information is given as an example that demonstrates the usefulness of this method in the case of hospital information management. Data warehouse technology is an evolving technology, and more and more decision support information extracted by data mining and with decision-making technology is required for further research.
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ARCOCT: Automatic detection of lumen border in intravascular OCT images.
Cheimariotis, Grigorios-Aris; Chatzizisis, Yiannis S; Koutkias, Vassilis G; Toutouzas, Konstantinos; Giannopoulos, Andreas; Riga, Maria; Chouvarda, Ioanna; Antoniadis, Antonios P; Doulaverakis, Charalambos; Tsamboulatidis, Ioannis; Kompatsiaris, Ioannis; Giannoglou, George D; Maglaveras, Nicos
2017-11-01
Intravascular optical coherence tomography (OCT) is an invaluable tool for the detection of pathological features on the arterial wall and the investigation of post-stenting complications. Computational lumen border detection in OCT images is highly advantageous, since it may support rapid morphometric analysis. However, automatic detection is very challenging, since OCT images typically include various artifacts that impact image clarity, including features such as side branches and intraluminal blood presence. This paper presents ARCOCT, a segmentation method for fully-automatic detection of lumen border in OCT images. ARCOCT relies on multiple, consecutive processing steps, accounting for image preparation, contour extraction and refinement. In particular, for contour extraction ARCOCT employs the transformation of OCT images based on physical characteristics such as reflectivity and absorption of the tissue and, for contour refinement, local regression using weighted linear least squares and a 2nd degree polynomial model is employed to achieve artifact and small-branch correction as well as smoothness of the artery mesh. Our major focus was to achieve accurate contour delineation in the various types of OCT images, i.e., even in challenging cases with branches and artifacts. ARCOCT has been assessed in a dataset of 1812 images (308 from stented and 1504 from native segments) obtained from 20 patients. ARCOCT was compared against ground-truth manual segmentation performed by experts on the basis of various geometric features (e.g. area, perimeter, radius, diameter, centroid, etc.) and closed contour matching indicators (the Dice index, the Hausdorff distance and the undirected average distance), using standard statistical analysis methods. The proposed method was proven very efficient and close to the ground-truth, exhibiting non statistically-significant differences for most of the examined metrics. ARCOCT allows accurate and fully-automated lumen border detection in OCT images. Copyright © 2017 Elsevier B.V. All rights reserved.
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Andersson, Karolina; Carlsten, Anders; Hedenrud, Tove
2009-01-01
Objective To analyse whether prescribing patterns changed after introduction of drug budgets and whether there is an association between drug prescribing patterns and the type of employer and care facility. Methods Data analysed encompassed information on dispensed medicines, by workplaces, prescribed in the Region Västra Götaland, Sweden, for the years 2003 and 2006. Workplaces (n = 969) were categorized according to type of employer and type of care facility. Five prescribing indicators reflecting goals for cost-containing prescribing in Region Västra Götaland were assessed. Changes over time and differences between different types of employer and care facility were analysed by Mann–Whitney tests. Results In 2003, workplaces with a public employer had a significantly higher adherence to three of the prescribing indicators compared with private practitioners. Two of these differences remained in 2006. In 2003, none of the prescribing indicators differed between primary care and other care facilities. Three years later workplaces in primary care had a significantly higher adherence to three of the prescribing indicators than other care facilities. There was a statistically significant difference in change between 2003 and 2006 between primary care and other care facilities; there were no differences in change between workplaces with public and private employers. Conclusions Adherence to three of the prescribing indicators increased after the introduction of decentralized drug budgets. Workplaces with a public employer showed greater adherence to two of the prescribing indicators than private sector workplaces. PMID:19291589
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A system of registration and statistics.
Blayo, C
1993-06-01
In 1971, WHO recommended obligatory reporting to countries preparing to legalize induced abortion, however, there is no registration of abortions in Austria. Greece, Luxembourg, and Portugal, or in Northern Ireland, Ireland, and Malta, where abortion is prohibited, or in Switzerland, where it is limited. Albania is preparing to institute such a provision. Registration is not always complete in Germany, France, Italy, Poland, and Spain, and in the republics of the former USSR, particularly Lithuania. The data gathered are often further impoverished at the stage of the publication of the statistics. Certain estimations, or even results of surveys, make up for these shortcomings. A retrospective survey of a sample representing all women age 15 years or older would allow the reconstruction of statistics on abortions of past years. Systematic registration must be accompanied by the publication of a statistical record. Sterilization appears to be spreading in Europe, but it is only very rarely registered. The proportion of couples sterilized is sometimes obtained by surveys, but there is hardly any information on the characteristics of this group. On the other hand, the practice of contraception can be easily assessed, as in the majority of countries contraceptives are dispensed through pharmacies, public family planning centers, and private practitioners. Family planning centers sometimes are sources of statistical data. In some countries producers' associations make statistics available on the sale of contraceptives. Exact surveys facilitate the characterization of the users and reveal the methods they employ. Many countries carried out such surveys at the end of the 1970s under the aegis of world fertility surveys. It is urgent to invest in data collection suitable for learning the proportion of women who utilize each method of contraception in all the countries of Europe.
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Detection of crossover time scales in multifractal detrended fluctuation analysis
NASA Astrophysics Data System (ADS)
Ge, Erjia; Leung, Yee
2013-04-01
Fractal is employed in this paper as a scale-based method for the identification of the scaling behavior of time series. Many spatial and temporal processes exhibiting complex multi(mono)-scaling behaviors are fractals. One of the important concepts in fractals is crossover time scale(s) that separates distinct regimes having different fractal scaling behaviors. A common method is multifractal detrended fluctuation analysis (MF-DFA). The detection of crossover time scale(s) is, however, relatively subjective since it has been made without rigorous statistical procedures and has generally been determined by eye balling or subjective observation. Crossover time scales such determined may be spurious and problematic. It may not reflect the genuine underlying scaling behavior of a time series. The purpose of this paper is to propose a statistical procedure to model complex fractal scaling behaviors and reliably identify the crossover time scales under MF-DFA. The scaling-identification regression model, grounded on a solid statistical foundation, is first proposed to describe multi-scaling behaviors of fractals. Through the regression analysis and statistical inference, we can (1) identify the crossover time scales that cannot be detected by eye-balling observation, (2) determine the number and locations of the genuine crossover time scales, (3) give confidence intervals for the crossover time scales, and (4) establish the statistically significant regression model depicting the underlying scaling behavior of a time series. To substantive our argument, the regression model is applied to analyze the multi-scaling behaviors of avian-influenza outbreaks, water consumption, daily mean temperature, and rainfall of Hong Kong. Through the proposed model, we can have a deeper understanding of fractals in general and a statistical approach to identify multi-scaling behavior under MF-DFA in particular.
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Liu, Su; Stapleton, David C
2011-01-01
We present longitudinal employment and work-incentive statistics for individuals who began receiving Social Security Disability Insurance (DI) benefits from 1996 through 2006. For the longest-observed cohort, 28 percent returned to work, 6.5 percent had their benefits suspended for work in at least 1 month, and 3.7 percent had their benefits terminated for work. The corresponding percentages are much higher for those who were younger than age 40 when they entered the DI program. Most first suspensions occurred within 5 years after entry. Cross-state variation in outcomes is high, and, to the extent observed, statistics for more recent cohorts are lower.
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Han, Xu; Kim, Jung-jae; Kwoh, Chee Keong
2016-01-01
Biomedical text mining may target various kinds of valuable information embedded in the literature, but a critical obstacle to the extension of the mining targets is the cost of manual construction of labeled data, which are required for state-of-the-art supervised learning systems. Active learning is to choose the most informative documents for the supervised learning in order to reduce the amount of required manual annotations. Previous works of active learning, however, focused on the tasks of entity recognition and protein-protein interactions, but not on event extraction tasks for multiple event types. They also did not consider the evidence of event participants, which might be a clue for the presence of events in unlabeled documents. Moreover, the confidence scores of events produced by event extraction systems are not reliable for ranking documents in terms of informativity for supervised learning. We here propose a novel committee-based active learning method that supports multi-event extraction tasks and employs a new statistical method for informativity estimation instead of using the confidence scores from event extraction systems. Our method is based on a committee of two systems as follows: We first employ an event extraction system to filter potential false negatives among unlabeled documents, from which the system does not extract any event. We then develop a statistical method to rank the potential false negatives of unlabeled documents 1) by using a language model that measures the probabilities of the expression of multiple events in documents and 2) by using a named entity recognition system that locates the named entities that can be event arguments (e.g. proteins). The proposed method further deals with unknown words in test data by using word similarity measures. We also apply our active learning method for the task of named entity recognition. We evaluate the proposed method against the BioNLP Shared Tasks datasets, and show that our method can achieve better performance than such previous methods as entropy and Gibbs error based methods and a conventional committee-based method. We also show that the incorporation of named entity recognition into the active learning for event extraction and the unknown word handling further improve the active learning method. In addition, the adaptation of the active learning method into named entity recognition tasks also improves the document selection for manual annotation of named entities.
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41 CFR 60-2.35 - Compliance status.
Code of Federal Regulations, 2010 CFR
2010-07-01
... workforce (i.e., the employment of minorities or women at a percentage rate below, or above, the goal level... obligations will be determined by analysis of statistical data and other non-statistical information which...
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2010-01-01
Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the detection of moderately irregularly shaped clusters. The multi-objective cohesion scan is most effective for the detection of highly irregularly shaped clusters. PMID:21034451
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2018-01-01
ABSTRACT To assess phenotypic bacterial antimicrobial resistance (AMR) in different strata (e.g., host populations, environmental areas, manure, or sewage effluents) for epidemiological purposes, isolates of target bacteria can be obtained from a stratum using various sample types. Also, different sample processing methods can be applied. The MIC of each target antimicrobial drug for each isolate is measured. Statistical equivalence testing of the MIC data for the isolates allows evaluation of whether different sample types or sample processing methods yield equivalent estimates of the bacterial antimicrobial susceptibility in the stratum. We demonstrate this approach on the antimicrobial susceptibility estimates for (i) nontyphoidal Salmonella spp. from ground or trimmed meat versus cecal content samples of cattle in processing plants in 2013-2014 and (ii) nontyphoidal Salmonella spp. from urine, fecal, and blood human samples in 2015 (U.S. National Antimicrobial Resistance Monitoring System data). We found that the sample types for cattle yielded nonequivalent susceptibility estimates for several antimicrobial drug classes and thus may gauge distinct subpopulations of salmonellae. The quinolone and fluoroquinolone susceptibility estimates for nontyphoidal salmonellae from human blood are nonequivalent to those from urine or feces, conjecturally due to the fluoroquinolone (ciprofloxacin) use to treat infections caused by nontyphoidal salmonellae. We also demonstrate statistical equivalence testing for comparing sample processing methods for fecal samples (culturing one versus multiple aliquots per sample) to assess AMR in fecal Escherichia coli. These methods yield equivalent results, except for tetracyclines. Importantly, statistical equivalence testing provides the MIC difference at which the data from two sample types or sample processing methods differ statistically. Data users (e.g., microbiologists and epidemiologists) may then interpret practical relevance of the difference. IMPORTANCE Bacterial antimicrobial resistance (AMR) needs to be assessed in different populations or strata for the purposes of surveillance and determination of the efficacy of interventions to halt AMR dissemination. To assess phenotypic antimicrobial susceptibility, isolates of target bacteria can be obtained from a stratum using different sample types or employing different sample processing methods in the laboratory. The MIC of each target antimicrobial drug for each of the isolates is measured, yielding the MIC distribution across the isolates from each sample type or sample processing method. We describe statistical equivalence testing for the MIC data for evaluating whether two sample types or sample processing methods yield equivalent estimates of the bacterial phenotypic antimicrobial susceptibility in the stratum. This includes estimating the MIC difference at which the data from the two approaches differ statistically. Data users (e.g., microbiologists, epidemiologists, and public health professionals) can then interpret whether that present difference is practically relevant. PMID:29475868
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Shakeri, Heman; Volkova, Victoriya; Wen, Xuesong; Deters, Andrea; Cull, Charley; Drouillard, James; Müller, Christian; Moradijamei, Behnaz; Jaberi-Douraki, Majid
2018-05-01
To assess phenotypic bacterial antimicrobial resistance (AMR) in different strata (e.g., host populations, environmental areas, manure, or sewage effluents) for epidemiological purposes, isolates of target bacteria can be obtained from a stratum using various sample types. Also, different sample processing methods can be applied. The MIC of each target antimicrobial drug for each isolate is measured. Statistical equivalence testing of the MIC data for the isolates allows evaluation of whether different sample types or sample processing methods yield equivalent estimates of the bacterial antimicrobial susceptibility in the stratum. We demonstrate this approach on the antimicrobial susceptibility estimates for (i) nontyphoidal Salmonella spp. from ground or trimmed meat versus cecal content samples of cattle in processing plants in 2013-2014 and (ii) nontyphoidal Salmonella spp. from urine, fecal, and blood human samples in 2015 (U.S. National Antimicrobial Resistance Monitoring System data). We found that the sample types for cattle yielded nonequivalent susceptibility estimates for several antimicrobial drug classes and thus may gauge distinct subpopulations of salmonellae. The quinolone and fluoroquinolone susceptibility estimates for nontyphoidal salmonellae from human blood are nonequivalent to those from urine or feces, conjecturally due to the fluoroquinolone (ciprofloxacin) use to treat infections caused by nontyphoidal salmonellae. We also demonstrate statistical equivalence testing for comparing sample processing methods for fecal samples (culturing one versus multiple aliquots per sample) to assess AMR in fecal Escherichia coli These methods yield equivalent results, except for tetracyclines. Importantly, statistical equivalence testing provides the MIC difference at which the data from two sample types or sample processing methods differ statistically. Data users (e.g., microbiologists and epidemiologists) may then interpret practical relevance of the difference. IMPORTANCE Bacterial antimicrobial resistance (AMR) needs to be assessed in different populations or strata for the purposes of surveillance and determination of the efficacy of interventions to halt AMR dissemination. To assess phenotypic antimicrobial susceptibility, isolates of target bacteria can be obtained from a stratum using different sample types or employing different sample processing methods in the laboratory. The MIC of each target antimicrobial drug for each of the isolates is measured, yielding the MIC distribution across the isolates from each sample type or sample processing method. We describe statistical equivalence testing for the MIC data for evaluating whether two sample types or sample processing methods yield equivalent estimates of the bacterial phenotypic antimicrobial susceptibility in the stratum. This includes estimating the MIC difference at which the data from the two approaches differ statistically. Data users (e.g., microbiologists, epidemiologists, and public health professionals) can then interpret whether that present difference is practically relevant. Copyright © 2018 Shakeri et al.
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ERIC Educational Resources Information Center
Equal Employment Opportunity Commission, Washington, DC.
The Equal Employment Opportunity Report for 1969 documents the results of job discrimination, based on more than 150,000 reports submitted by 44,000 employers covering more than 28 million workers. These reports provide statistics of employment by sex, race, and national origin in nine standard occupational categories: officials and managers,…
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Investigation of radiative interaction in laminar flows using Monte Carlo simulation
NASA Technical Reports Server (NTRS)
Liu, Jiwen; Tiwari, S. N.
1993-01-01
The Monte Carlo method (MCM) is employed to study the radiative interactions in fully developed laminar flow between two parallel plates. Taking advantage of the characteristics of easy mathematical treatment of the MCM, a general numerical procedure is developed for nongray radiative interaction. The nongray model is based on the statistical narrow band model with an exponential-tailed inverse intensity distribution. To validate the Monte Carlo simulation for nongray radiation problems, the results of radiative dissipation from the MCM are compared with two available solutions for a given temperature profile between two plates. After this validation, the MCM is employed to solve the present physical problem and results for the bulk temperature are compared with available solutions. In general, good agreement is noted and reasons for some discrepancies in certain ranges of parameters are explained.
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Graph-based structural change detection for rotating machinery monitoring
NASA Astrophysics Data System (ADS)
Lu, Guoliang; Liu, Jie; Yan, Peng
2018-01-01
Detection of structural changes is critically important in operational monitoring of a rotating machine. This paper presents a novel framework for this purpose, where a graph model for data modeling is adopted to represent/capture statistical dynamics in machine operations. Meanwhile we develop a numerical method for computing temporal anomalies in the constructed graphs. The martingale-test method is employed for the change detection when making decisions on possible structural changes, where excellent performance is demonstrated outperforming exciting results such as the autoregressive-integrated-moving average (ARIMA) model. Comprehensive experimental results indicate good potentials of the proposed algorithm in various engineering applications. This work is an extension of a recent result (Lu et al., 2017).
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Statistics-based email communication security behavior recognition
NASA Astrophysics Data System (ADS)
Yi, Junkai; Su, Yueyang; Zhao, Xianghui
2017-08-01
With the development of information technology, e-mail has become a popular communication medium. It has great significant to determine the relationship between the two sides of the communication. Firstly, this paper analysed and processed the content and attachment of e-mail using the skill of steganalysis and malware analysis. And it also conducts the following feature extracting and behaviour model establishing which based on Naive Bayesian theory. Then a behaviour analysis method was employed to calculate and evaluate the communication security. Finally, some experiments about the accuracy of the behavioural relationship of communication identifying has been carried out. The result shows that this method has a great effects and correctness as eighty-four percent.
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Branching-ratio approximation for the self-exciting Hawkes process
NASA Astrophysics Data System (ADS)
Hardiman, Stephen J.; Bouchaud, Jean-Philippe
2014-12-01
We introduce a model-independent approximation for the branching ratio of Hawkes self-exciting point processes. Our estimator requires knowing only the mean and variance of the event count in a sufficiently large time window, statistics that are readily obtained from empirical data. The method we propose greatly simplifies the estimation of the Hawkes branching ratio, recently proposed as a proxy for market endogeneity and formerly estimated using numerical likelihood maximization. We employ our method to support recent theoretical and experimental results indicating that the best fitting Hawkes model to describe S&P futures price changes is in fact critical (now and in the recent past) in light of the long memory of financial market activity.
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NASA Astrophysics Data System (ADS)
Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.
2018-03-01
We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.
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On determining absolute entropy without quantum theory or the third law of thermodynamics
NASA Astrophysics Data System (ADS)
Steane, Andrew M.
2016-04-01
We employ classical thermodynamics to gain information about absolute entropy, without recourse to statistical methods, quantum mechanics or the third law of thermodynamics. The Gibbs-Duhem equation yields various simple methods to determine the absolute entropy of a fluid. We also study the entropy of an ideal gas and the ionization of a plasma in thermal equilibrium. A single measurement of the degree of ionization can be used to determine an unknown constant in the entropy equation, and thus determine the absolute entropy of a gas. It follows from all these examples that the value of entropy at absolute zero temperature does not need to be assigned by postulate, but can be deduced empirically.
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NASA Astrophysics Data System (ADS)
Wisniewski, Nicholas Andrew
This dissertation is divided into two parts. First we present an exact solution to a generalization of the Behrens-Fisher problem by embedding the problem in the Riemannian manifold of Normal distributions. From this we construct a geometric hypothesis testing scheme. Secondly we investigate the most commonly used geometric methods employed in tensor field interpolation for DT-MRI analysis and cardiac computer modeling. We computationally investigate a class of physiologically motivated orthogonal tensor invariants, both at the full tensor field scale and at the scale of a single interpolation by doing a decimation/interpolation experiment. We show that Riemannian-based methods give the best results in preserving desirable physiological features.
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Preferred Materials and Methods Employed for Endodontic Treatment by Iranian General Practitioners
Raoof, Maryam; Zeini, Negar; Haghani, Jahangir; Sadr, Saeedeh; Mohammadalizadeh, Sakineh
2015-01-01
Introduction: The aim of this study was to gather information on the materials and methods employed in root canal treatment (RCT) by general dental practitioners (GDPs) in Iran. Methods and Materials: A questionnaire was distributed among 450 dentists who attended the 53th Iranian Dental Association congress. Participants were asked to consider demographic variables and answer the questions regarding the materials and methods commonly used in RCT. Descriptive statistics were given as absolute frequencies and valid percentages. The chi-square test was used to investigate the influence of gender and the years of professional activity for the employed materials and techniques. Results: The response rate was 84.88%. The results showed that 61.5% of the participants did not perform pulp sensitivity tests prior to RCT. Less than half of the general dental practitioners (47.4%) said that they would trace a sinus tract before starting the treatment. Nearly 16% of practitioners preferred the rubber dam isolation method. Over 36% of the practitioners reported using formocresol for pulpotomy. The combined approach of working length (WL) radiographs and electronic apex locators was used by 35.2% of the practitioners. Most of the respondents used K-file hand instruments for canal preparation and the technique of choice was step-back (43.5%), while 40.1% of respondents used NiTi rotary files, mostly ProTaper and RaCe. The most widely used irrigant was normal saline (61.8%). Calcium hydroxide was the most commonly used inter appointment medicament (84.6%). The most popular obturation technique was cold lateral condensation (81.7%) with 51% using zinc oxide-eugenol-based sealers. Conclusions: The majority of Iranian GDPs who participated in the present survey do not comply with quality guidelines of endodontic treatment. PMID:25834595
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A Review of Statistical Disclosure Control Techniques Employed by Web-Based Data Query Systems.
Matthews, Gregory J; Harel, Ofer; Aseltine, Robert H
We systematically reviewed the statistical disclosure control techniques employed for releasing aggregate data in Web-based data query systems listed in the National Association for Public Health Statistics and Information Systems (NAPHSIS). Each Web-based data query system was examined to see whether (1) it employed any type of cell suppression, (2) it used secondary cell suppression, and (3) suppressed cell counts could be calculated. No more than 30 minutes was spent on each system. Of the 35 systems reviewed, no suppression was observed in more than half (n = 18); observed counts below the threshold were observed in 2 sites; and suppressed values were recoverable in 9 sites. Six sites effectively suppressed small counts. This inquiry has revealed substantial weaknesses in the protective measures used in data query systems containing sensitive public health data. Many systems utilized no disclosure control whatsoever, and the vast majority of those that did deployed it inconsistently or inadequately.
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Nazar, Gaurang P.; Lee, John Tayu; Glantz, Stanton A.; Arora, Monika; Pearce, Neil; Millett, Christopher
2014-01-01
Objective To assess whether being employed in a smoke-free workplace is associated with living in a smoke-free home in 15 low and middle income countries (LMICs). Methods Country-specific individual level analyses of cross-sectional Global Adult Tobacco Survey data (2008–2011) from 15 LMICs was conducted using multiple logistic regression. The dependent variable was living in a smoke-free home; the independent variable was being employed in a smoke-free workplace. Analyses were adjusted for age, gender, residence, region, education, occupation, current smoking, current smokeless tobacco use and number of household members. Individual country results were combined in a random effects meta-analysis. Results In each country, the percentage of participants employed in a smoke-free workplace who reported living in a smoke-free home was higher than those employed in a workplace not smoke-free. The adjusted odds ratios (AORs) of living in a smoke-free home among participants employed in a smoke-free workplace (vs. those employed where smoking occurred) were statistically significant in 13 of the 15 countries, ranging from 1.12 [95% CI 0.79–1.58] in Uruguay to 2.29 [1.37–3.83] in China. The pooled AOR was 1.61 [1.46–1.79]. Conclusion In LMICs, employment in a smoke-free workplace is associated with living in a smoke-free home. Accelerated implementation of comprehensive smoke-free policies is likely to result in substantial population health benefits in these settings. PMID:24287123
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Coupling Matched Molecular Pairs with Machine Learning for Virtual Compound Optimization.
Turk, Samo; Merget, Benjamin; Rippmann, Friedrich; Fulle, Simone
2017-12-26
Matched molecular pair (MMP) analyses are widely used in compound optimization projects to gain insights into structure-activity relationships (SAR). The analysis is traditionally done via statistical methods but can also be employed together with machine learning (ML) approaches to extrapolate to novel compounds. The here introduced MMP/ML method combines a fragment-based MMP implementation with different machine learning methods to obtain automated SAR decomposition and prediction. To test the prediction capabilities and model transferability, two different compound optimization scenarios were designed: (1) "new fragments" which occurs when exploring new fragments for a defined compound series and (2) "new static core and transformations" which resembles for instance the identification of a new compound series. Very good results were achieved by all employed machine learning methods especially for the new fragments case, but overall deep neural network models performed best, allowing reliable predictions also for the new static core and transformations scenario, where comprehensive SAR knowledge of the compound series is missing. Furthermore, we show that models trained on all available data have a higher generalizability compared to models trained on focused series and can extend beyond chemical space covered in the training data. Thus, coupling MMP with deep neural networks provides a promising approach to make high quality predictions on various data sets and in different compound optimization scenarios.
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Weighted divergence correction scheme and its fast implementation
NASA Astrophysics Data System (ADS)
Wang, ChengYue; Gao, Qi; Wei, RunJie; Li, Tian; Wang, JinJun
2017-05-01
Forcing the experimental volumetric velocity fields to satisfy mass conversation principles has been proved beneficial for improving the quality of measured data. A number of correction methods including the divergence correction scheme (DCS) have been proposed to remove divergence errors from measurement velocity fields. For tomographic particle image velocimetry (TPIV) data, the measurement uncertainty for the velocity component along the light thickness direction is typically much larger than for the other two components. Such biased measurement errors would weaken the performance of traditional correction methods. The paper proposes a variant for the existing DCS by adding weighting coefficients to the three velocity components, named as the weighting DCS (WDCS). The generalized cross validation (GCV) method is employed to choose the suitable weighting coefficients. A fast algorithm for DCS or WDCS is developed, making the correction process significantly low-cost to implement. WDCS has strong advantages when correcting velocity components with biased noise levels. Numerical tests validate the accuracy and efficiency of the fast algorithm, the effectiveness of GCV method, and the advantages of WDCS. Lastly, DCS and WDCS are employed to process experimental velocity fields from the TPIV measurement of a turbulent boundary layer. This shows that WDCS achieves a better performance than DCS in improving some flow statistics.
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NASA Technical Reports Server (NTRS)
Coggeshall, M. E.; Hoffer, R. M.
1973-01-01
Remote sensing equipment and automatic data processing techniques were employed as aids in the institution of improved forest resource management methods. On the basis of automatically calculated statistics derived from manually selected training samples, the feature selection processor of LARSYS selected, upon consideration of various groups of the four available spectral regions, a series of channel combinations whose automatic classification performances (for six cover types, including both deciduous and coniferous forest) were tested, analyzed, and further compared with automatic classification results obtained from digitized color infrared photography.
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An empirical Bayes approach to analyzing recurring animal surveys
Johnson, D.H.
1989-01-01
Recurring estimates of the size of animal populations are often required by biologists or wildlife managers. Because of cost or other constraints, estimates frequently lack the accuracy desired but cannot readily be improved by additional sampling. This report proposes a statistical method employing empirical Bayes (EB) estimators as alternatives to those customarily used to estimate population size, and evaluates them by a subsampling experiment on waterfowl surveys. EB estimates, especially a simple limited-translation version, were more accurate and provided shorter confidence intervals with greater coverage probabilities than customary estimates.
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Computational tools for multi-linked flexible structures
NASA Technical Reports Server (NTRS)
Lee, Gordon K. F.; Brubaker, Thomas A.; Shults, James R.
1990-01-01
A software module which designs and tests controllers and filters in Kalman Estimator form, based on a polynomial state-space model is discussed. The user-friendly program employs an interactive graphics approach to simplify the design process. A variety of input methods are provided to test the effectiveness of the estimator. Utilities are provided which address important issues in filter design such as graphical analysis, statistical analysis, and calculation time. The program also provides the user with the ability to save filter parameters, inputs, and outputs for future use.
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Statistical Methods for Detecting Differentially Abundant Features in Clinical Metagenomic Samples
White, James Robert; Nagarajan, Niranjan; Pop, Mihai
2009-01-01
Numerous studies are currently underway to characterize the microbial communities inhabiting our world. These studies aim to dramatically expand our understanding of the microbial biosphere and, more importantly, hope to reveal the secrets of the complex symbiotic relationship between us and our commensal bacterial microflora. An important prerequisite for such discoveries are computational tools that are able to rapidly and accurately compare large datasets generated from complex bacterial communities to identify features that distinguish them. We present a statistical method for comparing clinical metagenomic samples from two treatment populations on the basis of count data (e.g. as obtained through sequencing) to detect differentially abundant features. Our method, Metastats, employs the false discovery rate to improve specificity in high-complexity environments, and separately handles sparsely-sampled features using Fisher's exact test. Under a variety of simulations, we show that Metastats performs well compared to previously used methods, and significantly outperforms other methods for features with sparse counts. We demonstrate the utility of our method on several datasets including a 16S rRNA survey of obese and lean human gut microbiomes, COG functional profiles of infant and mature gut microbiomes, and bacterial and viral metabolic subsystem data inferred from random sequencing of 85 metagenomes. The application of our method to the obesity dataset reveals differences between obese and lean subjects not reported in the original study. For the COG and subsystem datasets, we provide the first statistically rigorous assessment of the differences between these populations. The methods described in this paper are the first to address clinical metagenomic datasets comprising samples from multiple subjects. Our methods are robust across datasets of varied complexity and sampling level. While designed for metagenomic applications, our software can also be applied to digital gene expression studies (e.g. SAGE). A web server implementation of our methods and freely available source code can be found at http://metastats.cbcb.umd.edu/. PMID:19360128
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Pursuant to the No Fear Act, a federal agency must post on its public Web site summary statistical data pertaining to complaints of employment discrimination filed by employees, former employees and applicants for employment under 29 CFR part 1614
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Industry is Largest Employer of Scientists
ERIC Educational Resources Information Center
Chemical and Engineering News, 1977
1977-01-01
Cites statistics of a National Science Foundation report on scientists and engineers in 1974. Reports that chemists are better educated, older, have a better chance of being employed, and do more work for industry, than other scientific personnel. (MLH)
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Buunaaisie, C; Manyara, A M; Annett, H; Bird, E L; Bray, I; Ige, J; Jones, M; Orme, J; Pilkington, P; Evans, D
2018-05-08
This article aims to describe the public health career experiences of international graduates of a Master of Science in Public Health (MSc PH) programme and to contribute to developing the evidence base on international public health workforce capacity development. A sequential mixed methods study was conducted between January 2017 and April 2017. Ninety-seven international graduates of one UK university's MSc PH programme were invited to take part in an online survey followed by semistructured interviews, for respondents who consented to be interviewed. We computed the descriptive statistics of the quantitative data obtained, and qualitative data were thematically analysed. The response rate was 48.5%. Most respondents (63%) were employed by various agencies within 1 year after graduation. Others (15%) were at different stages of doctor of philosophy studies. Respondents reported enhanced roles after graduation in areas such as public health policy analysis (74%); planning, implementation and evaluation of public health interventions (74%); leadership roles (72%); and research (70%). The common perceived skills that were relevant to the respondents' present jobs were critical analysis (87%), multidisciplinary thinking (86%), demonstrating public health leadership skills (84%) and research (77%). Almost all respondents (90%) were confident in conducting research. Respondents recommended the provision of longer public health placement opportunities, elective courses on project management and advanced statistics, and 'internationalisation' of the programme's curriculum. The study has revealed the relevance of higher education in public health in developing the career prospects and skills of graduates. International graduates of this MSc PH programme were satisfied with the relevance and impact of the skills they acquired during their studies. The outcomes of this study can be used for curriculum reformation. Employers' perspectives of the capabilities of these graduates, however, need further consideration. Copyright © 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
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The economic impact of Mexico City's smoke-free law.
López, Carlos Manuel Guerrero; Ruiz, Jorge Alberto Jiménez; Shigematsu, Luz Myriam Reynales; Waters, Hugh R
2011-07-01
To evaluate the economic impact of Mexico City's 2008 smoke-free law--The Non-Smokers' Health Protection Law on restaurants, bars and nightclubs. We used the Monthly Services Survey of businesses from January 2005 to April 2009--with revenues, employment and payments to employees as the principal outcomes. The results are estimated using a differences-in-differences regression model with fixed effects. The states of Jalisco, Nuevo León and México, where the law was not in effect, serve as a counterfactual comparison group. In restaurants, after accounting for observable factors and the fixed effects, there was a 24.8% increase in restaurants' revenue associated with the smoke-free law. This difference is not statistically significant but shows that, on average, restaurants did not suffer economically as a result of the law. Total wages increased by 28.2% and employment increased by 16.2%. In nightclubs, bars and taverns there was a decrease of 1.5% in revenues and an increase of 0.1% and 3.0%, respectively, in wages and employment. None of these effects are statistically significant in multivariate analysis. There is no statistically significant evidence that the Mexico City smoke-free law had a negative impact on restaurants' income, employees' wages and levels of employment. On the contrary, the results show a positive, though statistically non-significant, impact of the law on most of these outcomes. Mexico City's experience suggests that smoke-free laws in Mexico and elsewhere will not hurt economic productivity in the restaurant and bar industries.
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Cabrieto, Jedelyn; Tuerlinckx, Francis; Kuppens, Peter; Grassmann, Mariel; Ceulemans, Eva
2017-06-01
Change point detection in multivariate time series is a complex task since next to the mean, the correlation structure of the monitored variables may also alter when change occurs. DeCon was recently developed to detect such changes in mean and\\or correlation by combining a moving windows approach and robust PCA. However, in the literature, several other methods have been proposed that employ other non-parametric tools: E-divisive, Multirank, and KCP. Since these methods use different statistical approaches, two issues need to be tackled. First, applied researchers may find it hard to appraise the differences between the methods. Second, a direct comparison of the relative performance of all these methods for capturing change points signaling correlation changes is still lacking. Therefore, we present the basic principles behind DeCon, E-divisive, Multirank, and KCP and the corresponding algorithms, to make them more accessible to readers. We further compared their performance through extensive simulations using the settings of Bulteel et al. (Biological Psychology, 98 (1), 29-42, 2014) implying changes in mean and in correlation structure and those of Matteson and James (Journal of the American Statistical Association, 109 (505), 334-345, 2014) implying different numbers of (noise) variables. KCP emerged as the best method in almost all settings. However, in case of more than two noise variables, only DeCon performed adequately in detecting correlation changes.
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Combined statistical analysis of landslide release and propagation
NASA Astrophysics Data System (ADS)
Mergili, Martin; Rohmaneo, Mohammad; Chu, Hone-Jay
2016-04-01
Statistical methods - often coupled with stochastic concepts - are commonly employed to relate areas affected by landslides with environmental layers, and to estimate spatial landslide probabilities by applying these relationships. However, such methods only concern the release of landslides, disregarding their motion. Conceptual models for mass flow routing are used for estimating landslide travel distances and possible impact areas. Automated approaches combining release and impact probabilities are rare. The present work attempts to fill this gap by a fully automated procedure combining statistical and stochastic elements, building on the open source GRASS GIS software: (1) The landslide inventory is subset into release and deposition zones. (2) We employ a traditional statistical approach to estimate the spatial release probability of landslides. (3) We back-calculate the probability distribution of the angle of reach of the observed landslides, employing the software tool r.randomwalk. One set of random walks is routed downslope from each pixel defined as release area. Each random walk stops when leaving the observed impact area of the landslide. (4) The cumulative probability function (cdf) derived in (3) is used as input to route a set of random walks downslope from each pixel in the study area through the DEM, assigning the probability gained from the cdf to each pixel along the path (impact probability). The impact probability of a pixel is defined as the average impact probability of all sets of random walks impacting a pixel. Further, the average release probabilities of the release pixels of all sets of random walks impacting a given pixel are stored along with the area of the possible release zone. (5) We compute the zonal release probability by increasing the release probability according to the size of the release zone - the larger the zone, the larger the probability that a landslide will originate from at least one pixel within this zone. We quantify this relationship by a set of empirical curves. (6) Finally, we multiply the zonal release probability with the impact probability in order to estimate the combined impact probability for each pixel. We demonstrate the model with a 167 km² study area in Taiwan, using an inventory of landslides triggered by the typhoon Morakot. Analyzing the model results leads us to a set of key conclusions: (i) The average composite impact probability over the entire study area corresponds well to the density of observed landside pixels. Therefore we conclude that the method is valid in general, even though the concept of the zonal release probability bears some conceptual issues that have to be kept in mind. (ii) The parameters used as predictors cannot fully explain the observed distribution of landslides. The size of the release zone influences the composite impact probability to a larger degree than the pixel-based release probability. (iii) The prediction rate increases considerably when excluding the largest, deep-seated, landslides from the analysis. We conclude that such landslides are mainly related to geological features hardly reflected in the predictor layers used.
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Study of Employment of Women in the Federal Government 1971.
ERIC Educational Resources Information Center
Civil Service Commission, Washington, DC. Manpower Statistics Div.
This study presents statistical information gained from a survey of women employed full-time in Federal civilian collar employment as of October 31, 1971 in the Washington, D.C., metropolitan area, the 50 states and the territories of the U.S., and foreign countries. Excluded from the survey are members and employees of the Congress, employees of…
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Youth Employment in the Hospitality Sector.
ERIC Educational Resources Information Center
Schiller, Bradley R.
A study used data from the National Longitudinal Surveys of Youth to analyze the long-term effects of hospitality industry employment on youth. The subsample extracted for the study included all youth who were aged 16-24 in 1980 and employed in the civilian sector for pay at any time in the year. Statistics indicated the hospitality sector was…
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Labor Trends: Overview of the United States, New York City, and Long Island. Revised Edition.
ERIC Educational Resources Information Center
Goldstein, Cheryl
This document summarizes employment statistics and trends, with a geographic emphasis on areas where Queensborough Community College (New York) students and graduates seek employment. Data are presented on the following: (1) current and projected United States labor force; (2) occupational outlook; (3) employment status of civilian labor force 25…
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ParallABEL: an R library for generalized parallelization of genome-wide association studies
2010-01-01
Background Genome-Wide Association (GWA) analysis is a powerful method for identifying loci associated with complex traits and drug response. Parts of GWA analyses, especially those involving thousands of individuals and consuming hours to months, will benefit from parallel computation. It is arduous acquiring the necessary programming skills to correctly partition and distribute data, control and monitor tasks on clustered computers, and merge output files. Results Most components of GWA analysis can be divided into four groups based on the types of input data and statistical outputs. The first group contains statistics computed for a particular Single Nucleotide Polymorphism (SNP), or trait, such as SNP characterization statistics or association test statistics. The input data of this group includes the SNPs/traits. The second group concerns statistics characterizing an individual in a study, for example, the summary statistics of genotype quality for each sample. The input data of this group includes individuals. The third group consists of pair-wise statistics derived from analyses between each pair of individuals in the study, for example genome-wide identity-by-state or genomic kinship analyses. The input data of this group includes pairs of SNPs/traits. The final group concerns pair-wise statistics derived for pairs of SNPs, such as the linkage disequilibrium characterisation. The input data of this group includes pairs of individuals. We developed the ParallABEL library, which utilizes the Rmpi library, to parallelize these four types of computations. ParallABEL library is not only aimed at GenABEL, but may also be employed to parallelize various GWA packages in R. The data set from the North American Rheumatoid Arthritis Consortium (NARAC) includes 2,062 individuals with 545,080, SNPs' genotyping, was used to measure ParallABEL performance. Almost perfect speed-up was achieved for many types of analyses. For example, the computing time for the identity-by-state matrix was linearly reduced from approximately eight hours to one hour when ParallABEL employed eight processors. Conclusions Executing genome-wide association analysis using the ParallABEL library on a computer cluster is an effective way to boost performance, and simplify the parallelization of GWA studies. ParallABEL is a user-friendly parallelization of GenABEL. PMID:20429914
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Reserve growth of oil and gas fields—Investigations and applications
Cook, Troy A.
2013-01-01
The reserve growth of fields has been a topic for ongoing discussion for over half a century and will continue to be studied well into the future. This is due to the expected size of the volumetric contribution of reserve growth to the future supply of oil and natural gas. Understanding past methods of estimating future volumes based on the data assembly methods that have been used can lead to a better understanding of their applicability. The statistical nature of past methods and the (1) possible high level of dependency on a limited number of fields, (2) assumption of an age-based correlation with effective reserve growth, and (3) assumption of long-lived and more common than not reserve growth, may be improved by employing a more geologically based approach.
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Study on 1H-NMR fingerprinting of Rhodiolae Crenulatae Radix et Rhizoma.
Wen, Shi-yuan; Zhou, Jiang-tao; Chen, Yan-yan; Ding, Li-qin; Jiang, Miao-miao
2015-07-01
Nuclear magnetic resonance (1H-NMR) fingerprint of Rhodiola rosea medicinal materials was established, and used to distinguish the quality of raw materials from different sources. Pulse sequence for water peak inhibition was employed to acquire 1H-NMR spectra with the temperature at 298 K and spectrometer frequency of 400.13 MHz. Through subsection integral method, the obtained NMR data was subjected to similarity analysis and principal component analysis (PCA). 10 batches raw materials of Rhodiola rosea from different origins were successfully distinguished by PCA. The statistical results indicated that rhodiola glucoside, butyl alcohol, maleic acid and alanine were the main differential ingredients. This method provides an auxiliary method of Chinese quality approach to evaluate the quality of Rhodiola crenulata without using natural reference substances.
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Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework.
Zammit-Mangion, Andrew; Rougier, Jonathan; Bamber, Jonathan; Schön, Nana
2014-06-01
Determining the Antarctic contribution to sea-level rise from observational data is a complex problem. The number of physical processes involved (such as ice dynamics and surface climate) exceeds the number of observables, some of which have very poor spatial definition. This has led, in general, to solutions that utilise strong prior assumptions or physically based deterministic models to simplify the problem. Here, we present a new approach for estimating the Antarctic contribution, which only incorporates descriptive aspects of the physically based models in the analysis and in a statistical manner. By combining physical insights with modern spatial statistical modelling techniques, we are able to provide probability distributions on all processes deemed to play a role in both the observed data and the contribution to sea-level rise. Specifically, we use stochastic partial differential equations and their relation to geostatistical fields to capture our physical understanding and employ a Gaussian Markov random field approach for efficient computation. The method, an instantiation of Bayesian hierarchical modelling, naturally incorporates uncertainty in order to reveal credible intervals on all estimated quantities. The estimated sea-level rise contribution using this approach corroborates those found using a statistically independent method. © 2013 The Authors. Environmetrics Published by John Wiley & Sons, Ltd.
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Nursing students’ attitude towards suicide attempters: A study from rural part of Northern India
Nebhinani, Mamta; Nebhinani, Naresh; Tamphasana, L.; Gaikwad, Achla D.
2013-01-01
Context: Majority of health professionals have unfavorable attitudes towards patients presenting with self-harm, which further compromises their willingness and outcome of care. Aims: To assess the nursing students’ attitudes toward suicide attempters. Settings and Design: Cross-sectional study was conducted in two nursing colleges of north India. Material and Methods: Three hundred and eight nursing students were recruited through total enumeration method from May to June 2012. ‘Suicide opinion questionnaire’ was administered to assess their attitudes towards suicide attempters. Statistical Analysis Used: Descriptive statistics was employed with Statistical Package for Social Sciences version 14.0 for Windows. Results: Majority were single females, from urban locality, with the mean age of 20 years. Only minority had previous exposure to suicide prevention programs and management of such cases. Majority of students agreed for mental illness, disturbed family life, and depression as major push to attempt suicide. They held favorable attitude for half of the attitudinal statement, but they were uncertain for rest half of the statements. Conclusions: They generally had favorable attitude towards suicide attempters. Their uncertain response highlights the need for enhancing educational exposure of nursing students and new staff at the earliest opportunity, to carve their favorable attitude towards patients presenting with self-harm. PMID:24347946
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Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework†
Zammit-Mangion, Andrew; Rougier, Jonathan; Bamber, Jonathan; Schön, Nana
2014-01-01
Determining the Antarctic contribution to sea-level rise from observational data is a complex problem. The number of physical processes involved (such as ice dynamics and surface climate) exceeds the number of observables, some of which have very poor spatial definition. This has led, in general, to solutions that utilise strong prior assumptions or physically based deterministic models to simplify the problem. Here, we present a new approach for estimating the Antarctic contribution, which only incorporates descriptive aspects of the physically based models in the analysis and in a statistical manner. By combining physical insights with modern spatial statistical modelling techniques, we are able to provide probability distributions on all processes deemed to play a role in both the observed data and the contribution to sea-level rise. Specifically, we use stochastic partial differential equations and their relation to geostatistical fields to capture our physical understanding and employ a Gaussian Markov random field approach for efficient computation. The method, an instantiation of Bayesian hierarchical modelling, naturally incorporates uncertainty in order to reveal credible intervals on all estimated quantities. The estimated sea-level rise contribution using this approach corroborates those found using a statistically independent method. © 2013 The Authors. Environmetrics Published by John Wiley & Sons, Ltd. PMID:25505370
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Williams, L. Keoki; Buu, Anne
2017-01-01
We propose a multivariate genome-wide association test for mixed continuous, binary, and ordinal phenotypes. A latent response model is used to estimate the correlation between phenotypes with different measurement scales so that the empirical distribution of the Fisher’s combination statistic under the null hypothesis is estimated efficiently. The simulation study shows that our proposed correlation estimation methods have high levels of accuracy. More importantly, our approach conservatively estimates the variance of the test statistic so that the type I error rate is controlled. The simulation also shows that the proposed test maintains the power at the level very close to that of the ideal analysis based on known latent phenotypes while controlling the type I error. In contrast, conventional approaches–dichotomizing all observed phenotypes or treating them as continuous variables–could either reduce the power or employ a linear regression model unfit for the data. Furthermore, the statistical analysis on the database of the Study of Addiction: Genetics and Environment (SAGE) demonstrates that conducting a multivariate test on multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests. The proposed method also offers a new approach to analyzing the Fagerström Test for Nicotine Dependence as multivariate phenotypes in genome-wide association studies. PMID:28081206
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Huber, Stefan; Klein, Elise; Moeller, Korbinian; Willmes, Klaus
2015-10-01
In neuropsychological research, single-cases are often compared with a small control sample. Crawford and colleagues developed inferential methods (i.e., the modified t-test) for such a research design. In the present article, we suggest an extension of the methods of Crawford and colleagues employing linear mixed models (LMM). We first show that a t-test for the significance of a dummy coded predictor variable in a linear regression is equivalent to the modified t-test of Crawford and colleagues. As an extension to this idea, we then generalized the modified t-test to repeated measures data by using LMMs to compare the performance difference in two conditions observed in a single participant to that of a small control group. The performance of LMMs regarding Type I error rates and statistical power were tested based on Monte-Carlo simulations. We found that starting with about 15-20 participants in the control sample Type I error rates were close to the nominal Type I error rate using the Satterthwaite approximation for the degrees of freedom. Moreover, statistical power was acceptable. Therefore, we conclude that LMMs can be applied successfully to statistically evaluate performance differences between a single-case and a control sample. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Hsiao, Chiaowen; Liu, Mengya; Stanton, Rick; McGee, Monnie; Qian, Yu
2015-01-01
Abstract Flow cytometry (FCM) is a fluorescence‐based single‐cell experimental technology that is routinely applied in biomedical research for identifying cellular biomarkers of normal physiological responses and abnormal disease states. While many computational methods have been developed that focus on identifying cell populations in individual FCM samples, very few have addressed how the identified cell populations can be matched across samples for comparative analysis. This article presents FlowMap‐FR, a novel method for cell population mapping across FCM samples. FlowMap‐FR is based on the Friedman–Rafsky nonparametric test statistic (FR statistic), which quantifies the equivalence of multivariate distributions. As applied to FCM data by FlowMap‐FR, the FR statistic objectively quantifies the similarity between cell populations based on the shapes, sizes, and positions of fluorescence data distributions in the multidimensional feature space. To test and evaluate the performance of FlowMap‐FR, we simulated the kinds of biological and technical sample variations that are commonly observed in FCM data. The results show that FlowMap‐FR is able to effectively identify equivalent cell populations between samples under scenarios of proportion differences and modest position shifts. As a statistical test, FlowMap‐FR can be used to determine whether the expression of a cellular marker is statistically different between two cell populations, suggesting candidates for new cellular phenotypes by providing an objective statistical measure. In addition, FlowMap‐FR can indicate situations in which inappropriate splitting or merging of cell populations has occurred during gating procedures. We compared the FR statistic with the symmetric version of Kullback–Leibler divergence measure used in a previous population matching method with both simulated and real data. The FR statistic outperforms the symmetric version of KL‐distance in distinguishing equivalent from nonequivalent cell populations. FlowMap‐FR was also employed as a distance metric to match cell populations delineated by manual gating across 30 FCM samples from a benchmark FlowCAP data set. An F‐measure of 0.88 was obtained, indicating high precision and recall of the FR‐based population matching results. FlowMap‐FR has been implemented as a standalone R/Bioconductor package so that it can be easily incorporated into current FCM data analytical workflows. © 2015 International Society for Advancement of Cytometry PMID:26274018
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Hsiao, Chiaowen; Liu, Mengya; Stanton, Rick; McGee, Monnie; Qian, Yu; Scheuermann, Richard H
2016-01-01
Flow cytometry (FCM) is a fluorescence-based single-cell experimental technology that is routinely applied in biomedical research for identifying cellular biomarkers of normal physiological responses and abnormal disease states. While many computational methods have been developed that focus on identifying cell populations in individual FCM samples, very few have addressed how the identified cell populations can be matched across samples for comparative analysis. This article presents FlowMap-FR, a novel method for cell population mapping across FCM samples. FlowMap-FR is based on the Friedman-Rafsky nonparametric test statistic (FR statistic), which quantifies the equivalence of multivariate distributions. As applied to FCM data by FlowMap-FR, the FR statistic objectively quantifies the similarity between cell populations based on the shapes, sizes, and positions of fluorescence data distributions in the multidimensional feature space. To test and evaluate the performance of FlowMap-FR, we simulated the kinds of biological and technical sample variations that are commonly observed in FCM data. The results show that FlowMap-FR is able to effectively identify equivalent cell populations between samples under scenarios of proportion differences and modest position shifts. As a statistical test, FlowMap-FR can be used to determine whether the expression of a cellular marker is statistically different between two cell populations, suggesting candidates for new cellular phenotypes by providing an objective statistical measure. In addition, FlowMap-FR can indicate situations in which inappropriate splitting or merging of cell populations has occurred during gating procedures. We compared the FR statistic with the symmetric version of Kullback-Leibler divergence measure used in a previous population matching method with both simulated and real data. The FR statistic outperforms the symmetric version of KL-distance in distinguishing equivalent from nonequivalent cell populations. FlowMap-FR was also employed as a distance metric to match cell populations delineated by manual gating across 30 FCM samples from a benchmark FlowCAP data set. An F-measure of 0.88 was obtained, indicating high precision and recall of the FR-based population matching results. FlowMap-FR has been implemented as a standalone R/Bioconductor package so that it can be easily incorporated into current FCM data analytical workflows. © The Authors. Published by Wiley Periodicals, Inc. on behalf of ISAC.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhen, X; Chen, H; Liao, Y
Purpose: To study the feasibility of employing deformable registration methods for accurate rectum dose volume parameters calculation and their potentials in revealing rectum dose-toxicity between complication and non-complication cervical cancer patients with brachytherapy treatment. Method and Materials: Data from 60 patients treated with BT including planning images, treatment plans, and follow-up clinical exam were retrospectively collected. Among them, 12 patients complained about hematochezia were further examined with colonoscopy and scored as Grade 1–3 complication (CP). Meanwhile, another 12 non-complication (NCP) patients were selected as a reference group. To seek for potential gains in rectum toxicity prediction when fractional anatomical deformationsmore » are account for, the rectum dose volume parameters D0.1/1/2cc of the selected patients were retrospectively computed by three different approaches: the simple “worstcase scenario” (WS) addition method, an intensity-based deformable image registration (DIR) algorithm-Demons, and a more accurate, recent developed local topology preserved non-rigid point matching algorithm (TOP). Statistical significance of the differences between rectum doses of the CP group and the NCP group were tested by a two-tailed t-test and results were considered to be statistically significant if p < 0.05. Results: For the D0.1cc, no statistical differences are found between the CP and NCP group in all three methods. For the D1cc, dose difference is not detected by the WS method, however, statistical differences between the two groups are observed by both Demons and TOP, and more evident in TOP. For the D2cc, the CP and NCP cases are statistically significance of the difference for all three methods but more pronounced with TOP. Conclusion: In this study, we calculated the rectum D0.1/1/2cc by simple WS addition and two DIR methods and seek for gains in rectum toxicity prediction. The results favor the claim that accurate dose deformation and summation tend to be more sensitive in unveiling the dose-toxicity relationship. This work is supported in part by grant from VARIAN MEDICAL SYSTEMS INC, the National Natural Science Foundation of China (no 81428019 and no 81301940), the Guangdong Natural Science Foundation (2015A030313302)and the 2015 Pearl River S&T Nova Program of Guangzhou (201506010096).« less
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Kordi, Masoumeh; Erfanian, Fatemeh; Fakari, Farzaneh Rashidi; Dastfan, Fatemeh; Nejad, Keivan Shariati
2017-01-01
INTRODUCTION: Shoulder dystocia is one of the obstetric emergencies that are accompanied to serious risks for mother and fetus. It necessitates making the method of training of shoulder dystocia management more efficient, i.e., better management and giving services with higher quality. Thus, this study was carried out to compare the impact of training by simulation and oral technique on the skill of the employed midwives in obstetric clinics at Mashhad city (Iran) in shoulder dystocia management during 2012. METHODS: The current research is a double-group clinical trial that was conducted on 51 members of the employed midwives in the obstetric clinic at Mashhad city in 2012. The questionnaire of personal specification and awareness about shoulder dystocia and practical examination (objective-structured clinical examination) were employed as tools for data collection. The learners were divided into two groups by randomized allocation. Training was done by the presentation of lecture in the oral content group and a short movie was displayed at the end of it. The shoulder dystocia management technique was simulated in another group and through role-playing of instructor application of moulage (station) training was conducted. The period of the training course (4 h) and content of the educational workshop was identical for both groups. The practical examination was held for the learners before and immediately after training course. The given data were analyzed by means of statistical descriptive tests including Mann–Whitney U-test and Wilcoxon test via SPSS software (version 16). The significance level was considered as (P < 0.05) in all cases. RESULTS: The total mean score was significantly increased for the variable of shoulder dystocia management skill after intervention in both groups (P < 0.0001). Similarly, the results of Mann–Whitney U-test statistical tests indicated that total mean score for the variable of shoulder dystocia management skill after the intervention was significantly greater in simulation group than in an oral group (P = 0.040). CONCLUSION: Training in simulated delivery room by means of role-playing is an efficient method for training shoulder dystocia management skill, so it is recommended to use this program in the training of this skill. PMID:28616417
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Use of the Monte Carlo Method for OECD Principles-Guided QSAR Modeling of SIRT1 Inhibitors.
Kumar, Ashwani; Chauhan, Shilpi
2017-01-01
SIRT1 inhibitors offer therapeutic potential for the treatment of a number of diseases including cancer and human immunodeficiency virus infection. A diverse series of 45 compounds with reported SIRT1 inhibitory activity has been employed for the development of quantitative structure-activity relationship (QSAR) models using the Monte Carlo optimization method. This method makes use of simplified molecular input line entry system notation of the molecular structure. The QSAR models were built up according to OECD principles. Three subsets of three splits were examined and validated by respective external sets. All the three described models have good statistical quality. The best model has the following statistical characteristics: R 2 = 0.8350, Q 2 test = 0.7491 for the test set and R 2 = 0.9655, Q 2 ext = 0.9261 for the validation set. In the mechanistic interpretation, structural attributes responsible for the endpoint increase and decrease are defined. Further, the design of some prospective SIRT1 inhibitors is also presented on the basis of these structural attributes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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[The research protocol III. Study population].
Arias-Gómez, Jesús; Villasís-Keever, Miguel Ángel; Miranda-Novales, María Guadalupe
2016-01-01
The study population is defined as a set of cases, determined, limited, and accessible, that will constitute the subjects for the selection of the sample, and must fulfill several characteristics and distinct criteria. The objectives of this manuscript are focused on specifying each one of the elements required to make the selection of the participants of a research project, during the elaboration of the protocol, including the concepts of study population, sample, selection criteria and sampling methods. After delineating the study population, the researcher must specify the criteria that each participant has to comply. The criteria that include the specific characteristics are denominated selection or eligibility criteria. These criteria are inclusion, exclusion and elimination, and will delineate the eligible population. The sampling methods are divided in two large groups: 1) probabilistic or random sampling and 2) non-probabilistic sampling. The difference lies in the employment of statistical methods to select the subjects. In every research, it is necessary to establish at the beginning the specific number of participants to be included to achieve the objectives of the study. This number is the sample size, and can be calculated or estimated with mathematical formulas and statistic software.
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Bayesian statistical ionospheric tomography improved by incorporating ionosonde measurements
NASA Astrophysics Data System (ADS)
Norberg, Johannes; Virtanen, Ilkka I.; Roininen, Lassi; Vierinen, Juha; Orispää, Mikko; Kauristie, Kirsti; Lehtinen, Markku S.
2016-04-01
We validate two-dimensional ionospheric tomography reconstructions against EISCAT incoherent scatter radar measurements. Our tomography method is based on Bayesian statistical inversion with prior distribution given by its mean and covariance. We employ ionosonde measurements for the choice of the prior mean and covariance parameters and use the Gaussian Markov random fields as a sparse matrix approximation for the numerical computations. This results in a computationally efficient tomographic inversion algorithm with clear probabilistic interpretation. We demonstrate how this method works with simultaneous beacon satellite and ionosonde measurements obtained in northern Scandinavia. The performance is compared with results obtained with a zero-mean prior and with the prior mean taken from the International Reference Ionosphere 2007 model. In validating the results, we use EISCAT ultra-high-frequency incoherent scatter radar measurements as the ground truth for the ionization profile shape. We find that in comparison to the alternative prior information sources, ionosonde measurements improve the reconstruction by adding accurate information about the absolute value and the altitude distribution of electron density. With an ionosonde at continuous disposal, the presented method enhances stand-alone near-real-time ionospheric tomography for the given conditions significantly.
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Makhov, Dmitry V.; Saita, Kenichiro; Martinez, Todd J.; ...
2014-12-11
In this study, we report a detailed computational simulation of the photodissociation of pyrrole using the ab initio Multiple Cloning (AIMC) method implemented within MOLPRO. The efficiency of the AIMC implementation, employing train basis sets, linear approximation for matrix elements, and Ehrenfest configuration cloning, allows us to accumulate significant statistics. We calculate and analyze the total kinetic energy release (TKER) spectrum and Velocity Map Imaging (VMI) of pyrrole and compare the results directly with experimental measurements. Both the TKER spectrum and the structure of the velocity map image (VMI) are well reproduced. Previously, it has been assumed that the isotropicmore » component of the VMI arises from long time statistical dissociation. Instead, our simulations suggest that ultrafast dynamics contributes significantly to both low and high energy portions of the TKER spectrum.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Makhov, Dmitry V.; Saita, Kenichiro; Martinez, Todd J.
In this study, we report a detailed computational simulation of the photodissociation of pyrrole using the ab initio Multiple Cloning (AIMC) method implemented within MOLPRO. The efficiency of the AIMC implementation, employing train basis sets, linear approximation for matrix elements, and Ehrenfest configuration cloning, allows us to accumulate significant statistics. We calculate and analyze the total kinetic energy release (TKER) spectrum and Velocity Map Imaging (VMI) of pyrrole and compare the results directly with experimental measurements. Both the TKER spectrum and the structure of the velocity map image (VMI) are well reproduced. Previously, it has been assumed that the isotropicmore » component of the VMI arises from long time statistical dissociation. Instead, our simulations suggest that ultrafast dynamics contributes significantly to both low and high energy portions of the TKER spectrum.« less
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The effect of different types of employment on quality of life.
Kober, R; Eggleton, I R C
2005-10-01
Despite research that has investigated whether the financial benefits of open employment exceed the costs, there has been scant research as to the effect sheltered and open employment have upon the quality of life of participants. The importance of this research is threefold: it investigates outcomes explicitly in terms of quality of life; the sample size is comparatively large; and it uses an established and validated questionnaire. One hundred and seventeen people with intellectual disability (ID) who were employed in either open or sheltered employment by disability employment agencies were interviewed. Quality of life was assessed using the Quality of Life Questionnaire. After making an initial assessment to see whether the outcomes achieved depended on type of employment, quality of life scores were analyzed controlling for participants' level of functional work ability (assessed via the Functional Assessment Inventory). The results showed that participants placed in open employment reported statistically significant higher quality of life scores. When the sample was split based upon participants' functional work ability, the type of employment had no effect on the reported quality of life for participants with a low functional work ability. However, for those participants with a high functional work ability, those in open employment reported statistically significantly higher quality of life. The results of this study support the placement of people with ID with high functional work ability into open employment. However, a degree of caution needs to be taken in interpreting the results presented given the disparity in income levels between the two types of employment.
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Interpreting Conditions in the Job Market for College Graduates.
ERIC Educational Resources Information Center
Alsalam, Nabeel
1993-01-01
Indicates that occupational and employment statistics would be more beneficial if users had a better understanding of how occupations are changing and how employers are redefining jobs to use the education and skills of their employees. (JOW)
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North American transportation : statistics on Canadian, Mexican, and United States transportation
DOT National Transportation Integrated Search
1994-05-01
North American Transportation: Statistics on Canadian, Mexican, and United States transportation contains extensive data on the size and scope, use, employment, fuel consumption, and economic role of each country's transportation system. It was publi...
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Silva, Arlene S; Brandao, Geovani C; Matos, Geraldo D; Ferreira, Sergio L C
2015-11-01
The present work proposed an analytical method for the direct determination of chromium in infant formulas employing the high-resolution continuum source electrothermal atomic absorption spectrometry combined with the solid sample analysis (SS-HR-CS ET AAS). Sample masses up to 2.0mg were directly weighted on a solid sampling platform and introduced into the graphite tube. In order to minimize the formation of carbonaceous residues and to improve the contact of the modifier solution with the solid sample, a volume of 10 µL of a solution containing 6% (v/v) H2O2, 20% (v/v) ethanol and 1% (v/v) HNO3 was added. The pyrolysis and atomization temperatures established were 1600 and 2400 °C, respectively, using magnesium as chemical modifier. The calibration technique was evaluated by comparing the slopes of calibration curves established using aqueous and solid standards. This test revealed that chromium can be determined employing the external calibration technique using aqueous standards. Under these conditions, the method developed allows the direct determination of chromium with limit of quantification of 11.5 ng g(-1), precision expressed as relative standard deviation (RSD) in the range of 4.0-17.9% (n=3) and a characteristic mass of 1.2 pg of chromium. The accuracy was confirmed by analysis of a certified reference material of tomato leaves furnished by National Institute of Standards and Technology. The method proposed was applied for the determination of chromium in five different infant formula samples. The chromium content found varied in the range of 33.9-58.1 ng g(-1) (n=3). These samples were also analyzed employing ICP-MS. A statistical test demonstrated that there is no significant difference between the results found by two methods. The chromium concentrations achieved are lower than the maximum limit permissible for chromium in foods by Brazilian Legislation. Copyright © 2015. Published by Elsevier B.V.
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Confidence intervals for single-case effect size measures based on randomization test inversion.
Michiels, Bart; Heyvaert, Mieke; Meulders, Ann; Onghena, Patrick
2017-02-01
In the current paper, we present a method to construct nonparametric confidence intervals (CIs) for single-case effect size measures in the context of various single-case designs. We use the relationship between a two-sided statistical hypothesis test at significance level α and a 100 (1 - α) % two-sided CI to construct CIs for any effect size measure θ that contain all point null hypothesis θ values that cannot be rejected by the hypothesis test at significance level α. This method of hypothesis test inversion (HTI) can be employed using a randomization test as the statistical hypothesis test in order to construct a nonparametric CI for θ. We will refer to this procedure as randomization test inversion (RTI). We illustrate RTI in a situation in which θ is the unstandardized and the standardized difference in means between two treatments in a completely randomized single-case design. Additionally, we demonstrate how RTI can be extended to other types of single-case designs. Finally, we discuss a few challenges for RTI as well as possibilities when using the method with other effect size measures, such as rank-based nonoverlap indices. Supplementary to this paper, we provide easy-to-use R code, which allows the user to construct nonparametric CIs according to the proposed method.
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Bakal, Tomas; Janata, Jiri; Sabova, Lenka; Grabic, Roman; Zlabek, Vladimir; Najmanova, Lucie
2018-06-16
A robust and widely applicable method for sampling of aquatic microbial biofilm and further sample processing is presented. The method is based on next-generation sequencing of V4-V5 variable regions of 16S rRNA gene and further statistical analysis of sequencing data, which could be useful not only to investigate taxonomic composition of biofilm bacterial consortia but also to assess aquatic ecosystem health. Five artificial materials commonly used for biofilm growth (glass, stainless steel, aluminum, polypropylene, polyethylene) were tested to determine the one giving most robust and reproducible results. The effect of used sampler material on total microbial composition was not statistically significant; however, the non-plastic materials (glass, metal) gave more stable outputs without irregularities among sample parallels. The bias of the method is assessed with respect to the employment of a non-quantitative step (PCR amplification) to obtain quantitative results (relative abundance of identified taxa). This aspect is often overlooked in ecological and medical studies. We document that sequencing of a mixture of three merged primary PCR reactions for each sample and further evaluation of median values from three technical replicates for each sample enables to overcome this bias and gives robust and repeatable results well distinguishing among sampling localities and seasons.
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NASA Astrophysics Data System (ADS)
Cornaglia, Matteo; Mouchiroud, Laurent; Marette, Alexis; Narasimhan, Shreya; Lehnert, Thomas; Jovaisaite, Virginija; Auwerx, Johan; Gijs, Martin A. M.
2015-05-01
Studies of the real-time dynamics of embryonic development require a gentle embryo handling method, the possibility of long-term live imaging during the complete embryogenesis, as well as of parallelization providing a population’s statistics, while keeping single embryo resolution. We describe an automated approach that fully accomplishes these requirements for embryos of Caenorhabditis elegans, one of the most employed model organisms in biomedical research. We developed a microfluidic platform which makes use of pure passive hydrodynamics to run on-chip worm cultures, from which we obtain synchronized embryo populations, and to immobilize these embryos in incubator microarrays for long-term high-resolution optical imaging. We successfully employ our platform to investigate morphogenesis and mitochondrial biogenesis during the full embryonic development and elucidate the role of the mitochondrial unfolded protein response (UPRmt) within C. elegans embryogenesis. Our method can be generally used for protein expression and developmental studies at the embryonic level, but can also provide clues to understand the aging process and age-related diseases in particular.
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Remaining dischargeable time prediction for lithium-ion batteries using unscented Kalman filter
NASA Astrophysics Data System (ADS)
Dong, Guangzhong; Wei, Jingwen; Chen, Zonghai; Sun, Han; Yu, Xiaowei
2017-10-01
To overcome the range anxiety, one of the important strategies is to accurately predict the range or dischargeable time of the battery system. To accurately predict the remaining dischargeable time (RDT) of a battery, a RDT prediction framework based on accurate battery modeling and state estimation is presented in this paper. Firstly, a simplified linearized equivalent-circuit-model is developed to simulate the dynamic characteristics of a battery. Then, an online recursive least-square-algorithm method and unscented-Kalman-filter are employed to estimate the system matrices and SOC at every prediction point. Besides, a discrete wavelet transform technique is employed to capture the statistical information of past dynamics of input currents, which are utilized to predict the future battery currents. Finally, the RDT can be predicted based on the battery model, SOC estimation results and predicted future battery currents. The performance of the proposed methodology has been verified by a lithium-ion battery cell. Experimental results indicate that the proposed method can provide an accurate SOC and parameter estimation and the predicted RDT can solve the range anxiety issues.
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Wuellner, Sara E; Bonauto, David K
2014-01-01
Background Little empirical data exist to identify the reasons for underreporting in the US Bureau of Labor Statistics (BLS) non-fatal occupational injury and illness data. Methods We interviewed occupational injury and illness record keepers from Washington State establishments that participated in the 2008 BLS Survey of Occupational Injuries and Illnesses (SOII). Qualitative and quantitative methods were used to explore recordkeeping and business practices that may explain SOII's incomplete case capture compared with WC claims data. Results Most participants (90%) did not comply with OSHA recordkeeping regulations. Other factors including using workplace injury data to evaluate supervisors' or SOII respondent's job performance, recording injuries for a worksite that operates multiple shifts, and failing to follow SOII instructions were more common among establishments with unreported WC claims. Conclusion Business practices that incentivize low injury rates, disorganized recordkeeping, and limited communication between BLS and survey respondents are barriers to accurate employer reports of work-related injuries and illnesses. Am. J. Ind. Med. 57:1133–1143, 2014. © 2014 The Authors. American Journal of Industrial Medicine published by Wiley Periodicals, Inc. PMID:25099477
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NASA Astrophysics Data System (ADS)
Eckert, R.; Neyhart, J. T.; Burd, L.; Polikar, R.; Mandayam, S. A.; Tseng, M.
2003-03-01
Mammography is the best method available as a non-invasive technique for the early detection of breast cancer. The radiographic appearance of the female breast consists of radiolucent (dark) regions due to fat and radiodense (light) regions due to connective and epithelial tissue. The amount of radiodense tissue can be used as a marker for predicting breast cancer risk. Previously, we have shown that the use of statistical models is a reliable technique for segmenting radiodense tissue. This paper presents improvements in the model that allow for further development of an automated system for segmentation of radiodense tissue. The segmentation algorithm employs a two-step process. In the first step, segmentation of tissue and non-tissue regions of a digitized X-ray mammogram image are identified using a radial basis function neural network. The second step uses a constrained Neyman-Pearson algorithm, developed especially for this research work, to determine the amount of radiodense tissue. Results obtained using the algorithm have been validated by comparing with estimates provided by a radiologist employing previously established methods.
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Random matrix models, double-time Painlevé equations, and wireless relaying
NASA Astrophysics Data System (ADS)
Chen, Yang; Haq, Nazmus S.; McKay, Matthew R.
2013-06-01
This paper gives an in-depth study of a multiple-antenna wireless communication scenario in which a weak signal received at an intermediate relay station is amplified and then forwarded to the final destination. The key quantity determining system performance is the statistical properties of the signal-to-noise ratio (SNR) γ at the destination. Under certain assumptions on the encoding structure, recent work has characterized the SNR distribution through its moment generating function, in terms of a certain Hankel determinant generated via a deformed Laguerre weight. Here, we employ two different methods to describe the Hankel determinant. First, we make use of ladder operators satisfied by orthogonal polynomials to give an exact characterization in terms of a "double-time" Painlevé differential equation, which reduces to Painlevé V under certain limits. Second, we employ Dyson's Coulomb fluid method to derive a closed form approximation for the Hankel determinant. The two characterizations are used to derive closed-form expressions for the cumulants of γ, and to compute performance quantities of engineering interest.
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NASA Astrophysics Data System (ADS)
Kim, Dae Hoe; Choi, Jae Young; Choi, Seon Hyeong; Ro, Yong Man
2012-03-01
In this study, a novel mammogram enhancement solution is proposed, aiming to improve the quality of subsequent mass segmentation in mammograms. It has been widely accepted that characteristics of masses are usually hyper-dense or uniform density with respect to its background. Also, their core parts are likely to have high-intensity values while the values of intensity tend to be decreased as the distance to core parts increases. Based on the aforementioned observations, we develop a new and effective mammogram enhancement method by combining local statistical measurements and Sliding Band Filtering (SBF). By effectively combining local statistical measurements and SBF, we are able to improve the contrast of the bright and smooth regions (which represent potential mass regions), as well as, at the same time, the regions where their surrounding gradients are converging to the centers of regions of interest. In this study, 89 mammograms were collected from the public MAIS database (DB) to demonstrate the effectiveness of the proposed enhancement solution in terms of improving mass segmentation. As for a segmentation method, widely used contour-based segmentation approach was employed. The contour-based method in conjunction with the proposed enhancement solution achieved overall detection accuracy of 92.4% with a total of 85 correct cases. On the other hand, without using our enhancement solution, overall detection accuracy of the contour-based method was only 78.3%. In addition, experimental results demonstrated the feasibility of our enhancement solution for the purpose of improving detection accuracy on mammograms containing dense parenchymal patterns.
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Weber, Benjamin; Lee, Sau L; Delvadia, Renishkumar; Lionberger, Robert; Li, Bing V; Tsong, Yi; Hochhaus, Guenther
2015-03-01
Equivalence testing of aerodynamic particle size distribution (APSD) through multi-stage cascade impactors (CIs) is important for establishing bioequivalence of orally inhaled drug products. Recent work demonstrated that the median of the modified chi-square ratio statistic (MmCSRS) is a promising metric for APSD equivalence testing of test (T) and reference (R) products as it can be applied to a reduced number of CI sites that are more relevant for lung deposition. This metric is also less sensitive to the increased variability often observed for low-deposition sites. A method to establish critical values for the MmCSRS is described here. This method considers the variability of the R product by employing a reference variance scaling approach that allows definition of critical values as a function of the observed variability of the R product. A stepwise CI equivalence test is proposed that integrates the MmCSRS as a method for comparing the relative shapes of CI profiles and incorporates statistical tests for assessing equivalence of single actuation content and impactor sized mass. This stepwise CI equivalence test was applied to 55 published CI profile scenarios, which were classified as equivalent or inequivalent by members of the Product Quality Research Institute working group (PQRI WG). The results of the stepwise CI equivalence test using a 25% difference in MmCSRS as an acceptance criterion provided the best matching with those of the PQRI WG as decisions of both methods agreed in 75% of the 55 CI profile scenarios.
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Bageshwar, Deepak; Khanvilkar, Vineeta; Kadam, Vilasrao
2011-01-01
A specific, precise and stability indicating high-performance thin-layer chromatographic method for simultaneous estimation of pantoprazole sodium and itopride hydrochloride in pharmaceutical formulations was developed and validated. The method employed TLC aluminium plates precoated with silica gel 60F254 as the stationary phase. The solvent system consisted of methanol:water:ammonium acetate; 4.0:1.0:0.5 (v/v/v). This system was found to give compact and dense spots for both itopride hydrochloride (Rf value of 0.55±0.02) and pantoprazole sodium (Rf value of 0.85±0.04). Densitometric analysis of both drugs was carried out in the reflectance–absorbance mode at 289 nm. The linear regression analysis data for the calibration plots showed a good linear relationship with R2=0.9988±0.0012 in the concentration range of 100–400 ng for pantoprazole sodium. Also, the linear regression analysis data for the calibration plots showed a good linear relationship with R2=0.9990±0.0008 in the concentration range of 200–1200 ng for itopride hydrochloride. The method was validated for specificity, precision, robustness and recovery. Statistical analysis proves that the method is repeatable and selective for the estimation of both the said drugs. As the method could effectively separate the drug from its degradation products, it can be employed as a stability indicating method. PMID:29403710
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Bageshwar, Deepak; Khanvilkar, Vineeta; Kadam, Vilasrao
2011-11-01
A specific, precise and stability indicating high-performance thin-layer chromatographic method for simultaneous estimation of pantoprazole sodium and itopride hydrochloride in pharmaceutical formulations was developed and validated. The method employed TLC aluminium plates precoated with silica gel 60F 254 as the stationary phase. The solvent system consisted of methanol:water:ammonium acetate; 4.0:1.0:0.5 (v/v/v). This system was found to give compact and dense spots for both itopride hydrochloride ( R f value of 0.55±0.02) and pantoprazole sodium ( R f value of 0.85±0.04). Densitometric analysis of both drugs was carried out in the reflectance-absorbance mode at 289 nm. The linear regression analysis data for the calibration plots showed a good linear relationship with R 2 =0.9988±0.0012 in the concentration range of 100-400 ng for pantoprazole sodium. Also, the linear regression analysis data for the calibration plots showed a good linear relationship with R 2 =0.9990±0.0008 in the concentration range of 200-1200 ng for itopride hydrochloride. The method was validated for specificity, precision, robustness and recovery. Statistical analysis proves that the method is repeatable and selective for the estimation of both the said drugs. As the method could effectively separate the drug from its degradation products, it can be employed as a stability indicating method.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Benjamin Langhorst; Thomas M Lillo; Henry S Chu
2014-05-01
A statistics based ballistic test method is presented for use when comparing multiple groups of test articles of unknown relative ballistic perforation resistance. The method is intended to be more efficient than many traditional methods for research and development testing. To establish the validity of the method, it is employed in this study to compare test groups of known relative ballistic performance. Multiple groups of test articles were perforated using consistent projectiles and impact conditions. Test groups were made of rolled homogeneous armor (RHA) plates and differed in thickness. After perforation, each residual projectile was captured behind the target andmore » its mass was measured. The residual masses measured for each test group were analyzed to provide ballistic performance rankings with associated confidence levels. When compared to traditional V50 methods, the residual mass (RM) method was found to require fewer test events and be more tolerant of variations in impact conditions.« less
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High throughput nonparametric probability density estimation.
Farmer, Jenny; Jacobs, Donald
2018-01-01
In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity. Such an automated process for univariate data is implemented to achieve this goal by merging the maximum entropy method with single order statistics and maximum likelihood. The only required properties of the random variables are that they are continuous and that they are, or can be approximated as, independent and identically distributed. A quasi-log-likelihood function based on single order statistics for sampled uniform random data is used to empirically construct a sample size invariant universal scoring function. Then a probability density estimate is determined by iteratively improving trial cumulative distribution functions, where better estimates are quantified by the scoring function that identifies atypical fluctuations. This criterion resists under and over fitting data as an alternative to employing the Bayesian or Akaike information criterion. Multiple estimates for the probability density reflect uncertainties due to statistical fluctuations in random samples. Scaled quantile residual plots are also introduced as an effective diagnostic to visualize the quality of the estimated probability densities. Benchmark tests show that estimates for the probability density function (PDF) converge to the true PDF as sample size increases on particularly difficult test probability densities that include cases with discontinuities, multi-resolution scales, heavy tails, and singularities. These results indicate the method has general applicability for high throughput statistical inference.
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High throughput nonparametric probability density estimation
Farmer, Jenny
2018-01-01
In high throughput applications, such as those found in bioinformatics and finance, it is important to determine accurate probability distribution functions despite only minimal information about data characteristics, and without using human subjectivity. Such an automated process for univariate data is implemented to achieve this goal by merging the maximum entropy method with single order statistics and maximum likelihood. The only required properties of the random variables are that they are continuous and that they are, or can be approximated as, independent and identically distributed. A quasi-log-likelihood function based on single order statistics for sampled uniform random data is used to empirically construct a sample size invariant universal scoring function. Then a probability density estimate is determined by iteratively improving trial cumulative distribution functions, where better estimates are quantified by the scoring function that identifies atypical fluctuations. This criterion resists under and over fitting data as an alternative to employing the Bayesian or Akaike information criterion. Multiple estimates for the probability density reflect uncertainties due to statistical fluctuations in random samples. Scaled quantile residual plots are also introduced as an effective diagnostic to visualize the quality of the estimated probability densities. Benchmark tests show that estimates for the probability density function (PDF) converge to the true PDF as sample size increases on particularly difficult test probability densities that include cases with discontinuities, multi-resolution scales, heavy tails, and singularities. These results indicate the method has general applicability for high throughput statistical inference. PMID:29750803
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Statistical definition of relapse: case of family drug court.
Alemi, Farrokh; Haack, Mary; Nemes, Susanna
2004-06-01
At any point in time, a patient's return to drug use can be seen either as a temporary event or as a return to persistent use. There is no formal standard for distinguishing persistent drug use from an occasional relapse. This lack of standardization persists although the consequences of either interpretation can be life altering. In a drug court or regulatory situation, for example, misinterpreting relapse as return to drug use could lead to incarceration, loss of child custody, or loss of employment. A clinician who mistakes a client's relapse for persistent drug use may fail to adjust treatment intensity to client's needs. An empirical and standardized method for distinguishing relapse from persistent drug use is needed. This paper provides a tool for clinicians and judges to distinguish relapse from persistent use based on statistical analyses of patterns of client's drug use. To accomplish this, a control chart is created for time-in-between relapses. This paper shows how a statistical limit can be calculated by examining either the client's history or other clients in the same program. If client's time-in-between relapse exceeds the statistical limit, then the client has returned to persistent use. Otherwise, the drug use is temporary. To illustrate the method, it is applied to data from three family drug courts. The approach allows the estimation of control limits based on the client's as well as the court's historical patterns. The approach also allows comparison of courts based on recovery rates.
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Huang, Chiung-Yu; Qin, Jing
2013-01-01
The Canadian Study of Health and Aging (CSHA) employed a prevalent cohort design to study survival after onset of dementia, where patients with dementia were sampled and the onset time of dementia was determined retrospectively. The prevalent cohort sampling scheme favors individuals who survive longer. Thus, the observed survival times are subject to length bias. In recent years, there has been a rising interest in developing estimation procedures for prevalent cohort survival data that not only account for length bias but also actually exploit the incidence distribution of the disease to improve efficiency. This article considers semiparametric estimation of the Cox model for the time from dementia onset to death under a stationarity assumption with respect to the disease incidence. Under the stationarity condition, the semiparametric maximum likelihood estimation is expected to be fully efficient yet difficult to perform for statistical practitioners, as the likelihood depends on the baseline hazard function in a complicated way. Moreover, the asymptotic properties of the semiparametric maximum likelihood estimator are not well-studied. Motivated by the composite likelihood method (Besag 1974), we develop a composite partial likelihood method that retains the simplicity of the popular partial likelihood estimator and can be easily performed using standard statistical software. When applied to the CSHA data, the proposed method estimates a significant difference in survival between the vascular dementia group and the possible Alzheimer’s disease group, while the partial likelihood method for left-truncated and right-censored data yields a greater standard error and a 95% confidence interval covering 0, thus highlighting the practical value of employing a more efficient methodology. To check the assumption of stable disease for the CSHA data, we also present new graphical and numerical tests in the article. The R code used to obtain the maximum composite partial likelihood estimator for the CSHA data is available in the online Supplementary Material, posted on the journal web site. PMID:24000265
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Anomalous heat transfer modes of nanofluids: a review based on statistical analysis
NASA Astrophysics Data System (ADS)
Sergis, Antonis; Hardalupas, Yannis
2011-05-01
This paper contains the results of a concise statistical review analysis of a large amount of publications regarding the anomalous heat transfer modes of nanofluids. The application of nanofluids as coolants is a novel practise with no established physical foundations explaining the observed anomalous heat transfer. As a consequence, traditional methods of performing a literature review may not be adequate in presenting objectively the results representing the bulk of the available literature. The current literature review analysis aims to resolve the problems faced by researchers in the past by employing an unbiased statistical analysis to present and reveal the current trends and general belief of the scientific community regarding the anomalous heat transfer modes of nanofluids. The thermal performance analysis indicated that statistically there exists a variable enhancement for conduction, convection/mixed heat transfer, pool boiling heat transfer and critical heat flux modes. The most popular proposed mechanisms in the literature to explain heat transfer in nanofluids are revealed, as well as possible trends between nanofluid properties and thermal performance. The review also suggests future experimentation to provide more conclusive answers to the control mechanisms and influential parameters of heat transfer in nanofluids.
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Anomalous heat transfer modes of nanofluids: a review based on statistical analysis.
Sergis, Antonis; Hardalupas, Yannis
2011-05-19
This paper contains the results of a concise statistical review analysis of a large amount of publications regarding the anomalous heat transfer modes of nanofluids. The application of nanofluids as coolants is a novel practise with no established physical foundations explaining the observed anomalous heat transfer. As a consequence, traditional methods of performing a literature review may not be adequate in presenting objectively the results representing the bulk of the available literature. The current literature review analysis aims to resolve the problems faced by researchers in the past by employing an unbiased statistical analysis to present and reveal the current trends and general belief of the scientific community regarding the anomalous heat transfer modes of nanofluids. The thermal performance analysis indicated that statistically there exists a variable enhancement for conduction, convection/mixed heat transfer, pool boiling heat transfer and critical heat flux modes. The most popular proposed mechanisms in the literature to explain heat transfer in nanofluids are revealed, as well as possible trends between nanofluid properties and thermal performance. The review also suggests future experimentation to provide more conclusive answers to the control mechanisms and influential parameters of heat transfer in nanofluids.
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Avalappampatty Sivasamy, Aneetha; Sundan, Bose
2015-01-01
The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T2 method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T2 statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better. PMID:26357668
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Sivasamy, Aneetha Avalappampatty; Sundan, Bose
2015-01-01
The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T(2) method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T(2) statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better.
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Anomalous heat transfer modes of nanofluids: a review based on statistical analysis
2011-01-01
This paper contains the results of a concise statistical review analysis of a large amount of publications regarding the anomalous heat transfer modes of nanofluids. The application of nanofluids as coolants is a novel practise with no established physical foundations explaining the observed anomalous heat transfer. As a consequence, traditional methods of performing a literature review may not be adequate in presenting objectively the results representing the bulk of the available literature. The current literature review analysis aims to resolve the problems faced by researchers in the past by employing an unbiased statistical analysis to present and reveal the current trends and general belief of the scientific community regarding the anomalous heat transfer modes of nanofluids. The thermal performance analysis indicated that statistically there exists a variable enhancement for conduction, convection/mixed heat transfer, pool boiling heat transfer and critical heat flux modes. The most popular proposed mechanisms in the literature to explain heat transfer in nanofluids are revealed, as well as possible trends between nanofluid properties and thermal performance. The review also suggests future experimentation to provide more conclusive answers to the control mechanisms and influential parameters of heat transfer in nanofluids. PMID:21711932
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Recruitment methods in a clinical trial of provoked vulvodynia: Predictors of enrollment.
Bachour, Candi C; Bachmann, Gloria A; Foster, David C; Wan, Jim Y; Rawlinson, Leslie A; Brown, Candace S
2017-02-01
Successful recruitment in clinical trials for chronic pain conditions is challenging, especially in women with provoked vulvodynia due to reluctance in discussing pain associated with sexual intercourse. The most successful recruitment methods and the characteristics of women reached with these methods are unknown. To compare the effectiveness and efficiency of four recruitment methods and to determine socioeconomic predictors for successful enrollment in a National Institutes of Health-sponsored multicenter clinical trial evaluating a gabapentin intervention in women with provoked vulvodynia. Recruitment methods utilized mass mailing, media, clinician referrals and community outreach. Effectiveness (number of participants enrolled) and efficiency (proportion screened who enrolled) were determined. Socioeconomic variables including race, educational level, annual household income, relationship status, age, menopausal status and employment status were also evaluated regarding which recruitment strategies were best at targeting specific cohorts. Of 868 potential study participants, 219 were enrolled. The most effective recruitment method in enrolling participants was mass mailing ( p < 0.001). There were no statistically significant differences in efficiency between recruitment methods ( p = 0.11). Relative to clinician referral, black women were 13 times as likely to be enrolled through mass mailing (adjusted odds ratio 12.5, 95% confidence interval, 3.6-43.1) as white women. There were no differences in enrollment according to educational level, annual income, relationship status, age, menopausal status, or employment status and recruitment method. In this clinical trial, mass mailing was the most effective recruitment method. Race of participants enrolled in a provoked vulvodynia trial was related to the recruitment method.
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Predicting trauma patient mortality: ICD [or ICD-10-AM] versus AIS based approaches.
Willis, Cameron D; Gabbe, Belinda J; Jolley, Damien; Harrison, James E; Cameron, Peter A
2010-11-01
The International Classification of Diseases Injury Severity Score (ICISS) has been proposed as an International Classification of Diseases (ICD)-10-based alternative to mortality prediction tools that use Abbreviated Injury Scale (AIS) data, including the Trauma and Injury Severity Score (TRISS). To date, studies have not examined the performance of ICISS using Australian trauma registry data. This study aimed to compare the performance of ICISS with other mortality prediction tools in an Australian trauma registry. This was a retrospective review of prospectively collected data from the Victorian State Trauma Registry. A training dataset was created for model development and a validation dataset for evaluation. The multiplicative ICISS model was compared with a worst injury ICISS approach, Victorian TRISS (V-TRISS, using local coefficients), maximum AIS severity and a multivariable model including ICD-10-AM codes as predictors. Models were investigated for discrimination (C-statistic) and calibration (Hosmer-Lemeshow statistic). The multivariable approach had the highest level of discrimination (C-statistic 0.90) and calibration (H-L 7.65, P= 0.468). Worst injury ICISS, V-TRISS and maximum AIS had similar performance. The multiplicative ICISS produced the lowest level of discrimination (C-statistic 0.80) and poorest calibration (H-L 50.23, P < 0.001). The performance of ICISS may be affected by the data used to develop estimates, the ICD version employed, the methods for deriving estimates and the inclusion of covariates. In this analysis, a multivariable approach using ICD-10-AM codes was the best-performing method. A multivariable ICISS approach may therefore be a useful alternative to AIS-based methods and may have comparable predictive performance to locally derived TRISS models. © 2010 The Authors. ANZ Journal of Surgery © 2010 Royal Australasian College of Surgeons.
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A novel measure and significance testing in data analysis of cell image segmentation.
Wu, Jin Chu; Halter, Michael; Kacker, Raghu N; Elliott, John T; Plant, Anne L
2017-03-14
Cell image segmentation (CIS) is an essential part of quantitative imaging of biological cells. Designing a performance measure and conducting significance testing are critical for evaluating and comparing the CIS algorithms for image-based cell assays in cytometry. Many measures and methods have been proposed and implemented to evaluate segmentation methods. However, computing the standard errors (SE) of the measures and their correlation coefficient is not described, and thus the statistical significance of performance differences between CIS algorithms cannot be assessed. We propose the total error rate (TER), a novel performance measure for segmenting all cells in the supervised evaluation. The TER statistically aggregates all misclassification error rates (MER) by taking cell sizes as weights. The MERs are for segmenting each single cell in the population. The TER is fully supported by the pairwise comparisons of MERs using 106 manually segmented ground-truth cells with different sizes and seven CIS algorithms taken from ImageJ. Further, the SE and 95% confidence interval (CI) of TER are computed based on the SE of MER that is calculated using the bootstrap method. An algorithm for computing the correlation coefficient of TERs between two CIS algorithms is also provided. Hence, the 95% CI error bars can be used to classify CIS algorithms. The SEs of TERs and their correlation coefficient can be employed to conduct the hypothesis testing, while the CIs overlap, to determine the statistical significance of the performance differences between CIS algorithms. A novel measure TER of CIS is proposed. The TER's SEs and correlation coefficient are computed. Thereafter, CIS algorithms can be evaluated and compared statistically by conducting the significance testing.
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Shoari, Niloofar; Dubé, Jean-Sébastien; Chenouri, Shoja'eddin
2015-11-01
In environmental studies, concentration measurements frequently fall below detection limits of measuring instruments, resulting in left-censored data. Some studies employ parametric methods such as the maximum likelihood estimator (MLE), robust regression on order statistic (rROS), and gamma regression on order statistic (GROS), while others suggest a non-parametric approach, the Kaplan-Meier method (KM). Using examples of real data from a soil characterization study in Montreal, we highlight the need for additional investigations that aim at unifying the existing literature. A number of studies have examined this issue; however, those considering data skewness and model misspecification are rare. These aspects are investigated in this paper through simulations. Among other findings, results show that for low skewed data, the performance of different statistical methods is comparable, regardless of the censoring percentage and sample size. For highly skewed data, the performance of the MLE method under lognormal and Weibull distributions is questionable; particularly, when the sample size is small or censoring percentage is high. In such conditions, MLE under gamma distribution, rROS, GROS, and KM are less sensitive to skewness. Related to model misspecification, MLE based on lognormal and Weibull distributions provides poor estimates when the true distribution of data is misspecified. However, the methods of rROS, GROS, and MLE under gamma distribution are generally robust to model misspecifications regardless of skewness, sample size, and censoring percentage. Since the characteristics of environmental data (e.g., type of distribution and skewness) are unknown a priori, we suggest using MLE based on gamma distribution, rROS and GROS. Copyright © 2015 Elsevier Ltd. All rights reserved.
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ERIC Educational Resources Information Center
Holland, Bart K.
2006-01-01
A generally-educated individual should have some insight into how decisions are made in the very wide range of fields that employ statistical and probabilistic reasoning. Also, students of introductory probability and statistics are often best motivated by specific applications rather than by theory and mathematical development, because most…
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Huge Increase in Day-Care Workers: A Result of Multiple Societal Changes.
ERIC Educational Resources Information Center
Bureau of Labor Statistics (DOL), Washington, DC.
Using Bureau of Labor Statistics estimates of employment in day-care establishments, this study analyzes changes in day care over the past 20 years. Growth in day-care employment has been much stronger than that of other industries. Since 1972, employment has increased by nearly 250 per cent. Causes of growth includes changing trends in enrollment…
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The Multiplier Effect of the Development of Forest Park Tourism on Employment Creation in China
ERIC Educational Resources Information Center
Shuifa, Ke; Chenguang, Pan; Jiahua, Pan; Yan, Zheng; Ying, Zhang
2011-01-01
The focus of this article was employment creation by developing forest park tourism industries in China. Analysis of the statistical data and an input-output approach showed that 1 direct job opportunity in tourism industries created 1.15 other job opportunities. In the high, middle, and low scenarios, the total predicted employment in forest park…
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ERIC Educational Resources Information Center
Willhide, Robert Jesse
2014-01-01
This report is part of a series of reports that provides information on the structure, function, finances, taxation, employment, and pension systems of the United States' approximately 90,000 state and local governments. This report presents data on state and local government employment and payroll based on information collected by the 2013 Annual…
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ERIC Educational Resources Information Center
Wood, Gaynor
2016-01-01
Graduate employment statistics are receiving considerable attention in UK universities. This paper looks at how a wide range of employability attributes can be developed with students, through the innovative use of the Project Based Learning (PjBL) approach. The case study discussed here involves a group of archaeology students from the University…
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Kim, Il Ho; Khang, Young Ho; Cho, Sung Il; Chun, Heeran; Muntaner, Carles
2011-01-01
We examined gender differential changes in employment-related health inequalities according to occupational position (professional/nonprofessional) in South Korea during the last decade. Data were taken from four rounds of Social Statistical Surveys of South Korea (1995, 1999, 2003, and 2006) from the Korean National Statistics Office. The total study population was 55435 male and 33 913 female employees aged 25-64. Employment arrangements were divided into permanent, fixed-term, and daily employment. After stratification according to occupational position (professional/nonprofessional) and gender, different patterns in employment - related health inequalities were observed. In the professional group, the gaps in absolute and relative employment inequalities for poor self-rated health were more likely to widen following Korea's 1997 economic downturn. In the nonprofessional group, during the study period, graded patterns of employment-related health inequalities were continuously observed in both genders. Absolute health inequalities by employment status, however, decreased among men but increased among women. In addition, a remarkable increase in relative health inequalities was found among female temporary and daily employees (p = 0.009, < 0.001, respectively), but only among male daily employees (p = 0.001). Relative employment-related health inequalities had clearly widened for female daily workers between 2003 and 2006 (p = 0.047). The 1997 Korean economic downturn, in particular, seemingly stimulated a widening gap in employment health inequalities. Our study revealed that whereas absolute health inequalities in relation to employment status increased in the professional group, relative employment-related health inequalities increased in the nonprofessional group, especially among women. In view of the high concentration of female nonstandard employees, further monitoring of inequality should consider gender specific patterns according to employee's occupational and employment status.
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Logistic regression for risk factor modelling in stuttering research.
Reed, Phil; Wu, Yaqionq
2013-06-01
To outline the uses of logistic regression and other statistical methods for risk factor analysis in the context of research on stuttering. The principles underlying the application of a logistic regression are illustrated, and the types of questions to which such a technique has been applied in the stuttering field are outlined. The assumptions and limitations of the technique are discussed with respect to existing stuttering research, and with respect to formulating appropriate research strategies to accommodate these considerations. Finally, some alternatives to the approach are briefly discussed. The way the statistical procedures are employed are demonstrated with some hypothetical data. Research into several practical issues concerning stuttering could benefit if risk factor modelling were used. Important examples are early diagnosis, prognosis (whether a child will recover or persist) and assessment of treatment outcome. After reading this article you will: (a) Summarize the situations in which logistic regression can be applied to a range of issues about stuttering; (b) Follow the steps in performing a logistic regression analysis; (c) Describe the assumptions of the logistic regression technique and the precautions that need to be checked when it is employed; (d) Be able to summarize its advantages over other techniques like estimation of group differences and simple regression. Copyright © 2012 Elsevier Inc. All rights reserved.
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Using complexity metrics with R-R intervals and BPM heart rate measures
Wallot, Sebastian; Fusaroli, Riccardo; Tylén, Kristian; Jegindø, Else-Marie
2013-01-01
Lately, growing attention in the health sciences has been paid to the dynamics of heart rate as indicator of impending failures and for prognoses. Likewise, in social and cognitive sciences, heart rate is increasingly employed as a measure of arousal, emotional engagement and as a marker of interpersonal coordination. However, there is no consensus about which measurements and analytical tools are most appropriate in mapping the temporal dynamics of heart rate and quite different metrics are reported in the literature. As complexity metrics of heart rate variability depend critically on variability of the data, different choices regarding the kind of measures can have a substantial impact on the results. In this article we compare linear and non-linear statistics on two prominent types of heart beat data, beat-to-beat intervals (R-R interval) and beats-per-min (BPM). As a proof-of-concept, we employ a simple rest-exercise-rest task and show that non-linear statistics—fractal (DFA) and recurrence (RQA) analyses—reveal information about heart beat activity above and beyond the simple level of heart rate. Non-linear statistics unveil sustained post-exercise effects on heart rate dynamics, but their power to do so critically depends on the type data that is employed: While R-R intervals are very susceptible to non-linear analyses, the success of non-linear methods for BPM data critically depends on their construction. Generally, “oversampled” BPM time-series can be recommended as they retain most of the information about non-linear aspects of heart beat dynamics. PMID:23964244
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Testing for Mutagens Using Fruit Flies.
ERIC Educational Resources Information Center
Liebl, Eric C.
1998-01-01
Describes a laboratory employed in undergraduate teaching that uses fruit flies to test student-selected compounds for their ability to cause mutations. Requires no prior experience with fruit flies, incorporates a student design component, and employs both rigorous controls and statistical analyses. (DDR)
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Crawford, John R; Garthwaite, Paul H; Denham, Annie K; Chelune, Gordon J
2012-12-01
Regression equations have many useful roles in psychological assessment. Moreover, there is a large reservoir of published data that could be used to build regression equations; these equations could then be employed to test a wide variety of hypotheses concerning the functioning of individual cases. This resource is currently underused because (a) not all psychologists are aware that regression equations can be built not only from raw data but also using only basic summary data for a sample, and (b) the computations involved are tedious and prone to error. In an attempt to overcome these barriers, Crawford and Garthwaite (2007) provided methods to build and apply simple linear regression models using summary statistics as data. In the present study, we extend this work to set out the steps required to build multiple regression models from sample summary statistics and the further steps required to compute the associated statistics for drawing inferences concerning an individual case. We also develop, describe, and make available a computer program that implements these methods. Although there are caveats associated with the use of the methods, these need to be balanced against pragmatic considerations and against the alternative of either entirely ignoring a pertinent data set or using it informally to provide a clinical "guesstimate." Upgraded versions of earlier programs for regression in the single case are also provided; these add the point and interval estimates of effect size developed in the present article.
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Pfeiffer, T.J.; Summerfelt, S.T.; Watten, B.J.
2011-01-01
Many methods are available for the measurement of dissolved carbon dioxide in an aqueous environment. Standard titration is the typical field method for measuring dissolved CO2 in aquaculture systems. However, titrimetric determination of dissolved CO2 in marine water aquaculture systems is unsuitable because of the high dissolved solids, silicates, and other dissolved minerals that interfere with the determination. Other methods used to measure dissolved carbon dioxide in an aquaculture water included use of a wetted CO2 probe analyzer, standard nomographic methods, and calculation by direct measurements of the water's pH, temperature, and alkalinity. The determination of dissolved CO2 in saltwater based on partial pressure measurements and non-dispersive infra-red (NDIR) techniques with a CO2 gas analyzer are widely employed for oceanic surveys of surface ocean CO2 flux and are similar to the techniques employed with the head space unit (HSU) in this study. Dissolved carbon dioxide (DC) determination with the HSU using a infra-red gas analyzer (IRGA) was compared with titrimetric, nomographic, calculated, and probe measurements of CO2 in freshwater and in saltwater with a salinity ranging from 5.0 to 30 ppt, and a CO2 range from 8 to 50 mg/L. Differences in CO2 measurements between duplicate HSUs (0.1–0.2 mg/L) were not statistically significant different. The coefficient of variation for the HSU readings averaged 1.85% which was better than the CO2 probe (4.09%) and that for the titrimetric method (5.84%). In all low, medium and high salinity level trials HSU precision was good, averaging 3.39%. Differences existed between comparison testing of the CO2 probe and HSU measurements with the CO2 probe readings, on average, providing DC estimates that were higher than HSU estimates. Differences between HSU and titration based estimates of DC increased with salinity and reached a maximum at 32.2 ppt. These differences were statistically significant (P < 0.05) at all salinity levels greater than 0.3 ppt. Results indicated reliable replicated results from the head space unit with varying salinity and dissolved carbon dioxide concentrations.
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Paljärvi, Tapio; Martikainen, Pekka; Pensola, Tiina; Leinonen, Taina; Herttua, Kimmo; Mäkelä, Pia
2015-01-01
Background Long-term employment trajectories of young problem drinkers are poorly understood. Methods We constructed retrospective labour market participation histories at ages 18–34 of 64 342 persons born in 1969–1982. Beginning from the year of each subject’s 18th birthday, we extracted information from the records of Statistics Finland on educational attainment, main type of economic activity, months in employment, and months in unemployment for a minimum of seven years (range 7–16 years). We used information on the timing of alcohol-related hospitalizations and deaths in the same period to define problem drinkers with early onset limited course, early onset persistent course, and late onset problem drinking. Results Early onset limited course problem drinkers improved their employment considerably by age, whereas early onset persistent problem drinkers experienced a constant decline in their employment by age. From the age of 18 to 34, early onset persistent problem drinkers were in employment merely 12% of the time, in comparison with 39% among the early onset limited course problem drinkers, and 58% among the general population. Conclusions These results indicate that young adults who were retrospectively defined as having early onset persistent course problem drinking were extensively marginalized from the labour market early on during their life course, and that their employment trajectory was significantly worse compared to other problem drinkers. PMID:25938764
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NASA Astrophysics Data System (ADS)
Nazarzadeh Zare, Mohsen; Dorrani, Kamal; Gholamali Lavasani, Masoud
2012-11-01
Background and purpose : This study examines the views of farmers and extension agents participating in extension education courses in Dezful, Iran, with regard to problems with these courses. It relies upon a descriptive methodology, using a survey as its instrument. Sample : The statistical population consisted of 5060 farmers and 50 extension agents; all extension agents were studied owing to their small population and a sample of 466 farmers was selected based on the stratified ratio sampling method. For the data analysis, statistical procedures including the t-test and factor analysis were used. Results : The results of factor analysis on the views of farmers indicated that these courses have problems such as inadequate use of instructional materials by extension agents, insufficient employment of knowledgeable and experienced extension agents, bad and inconvenient timing of courses for farmers, lack of logical connection between one curriculum and prior ones, negligence in considering the opinions of farmers in arranging the courses, and lack of information about the time of courses. The findings of factor analysis on the views of extension agents indicated that these courses suffer from problems such as use of consistent methods of instruction for teaching curricula, and lack of continuity between courses and their levels and content. Conclusions : Recommendations include: listening to the views of farmers when planning extension courses; providing audiovisual aids, pamphlets and CDs; arranging courses based on convenient timing for farmers; using incentives to encourage participation; and employing extension agents with knowledge of the latest agricultural issues.
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Bazan, Carlos; Hawkins, Trevor; Torres-Barba, David; Blomgren, Peter; Paolini, Paul
2011-08-22
We are exploring the viability of a novel approach to cardiocyte contractility assessment based on biomechanical properties of the cardiac cells, energy conservation principles, and information content measures. We define our measure of cell contraction as being the distance between the shapes of the contracting cell, assessed by the minimum total energy of the domain deformation (warping) of one cell shape into another. To guarantee a meaningful vis-à-vis correspondence between the two shapes, we employ both a data fidelity term and a regularization term. The data fidelity term is based on nonlinear features of the shapes while the regularization term enforces the compatibility between the shape deformations and that of a hyper-elastic material. We tested the proposed approach by assessing the contractile responses in isolated adult rat cardiocytes and contrasted these measurements against two different methods for contractility assessment in the literature. Our results show good qualitative and quantitative agreements with these methods as far as frequency, pacing, and overall behavior of the contractions are concerned. We hypothesize that the proposed methodology, once appropriately developed and customized, can provide a framework for computational cardiac cell biomechanics that can be used to integrate both theory and experiment. For example, besides giving a good assessment of contractile response of the cardiocyte, since the excitation process of the cell is a closed system, this methodology can be employed in an attempt to infer statistically significant model parameters for the constitutive equations of the cardiocytes.