Zonation in the deep benthic megafauna : Application of a general test.

PubMed

Gardiner, Frederick P; Haedrich, Richard L

1978-01-01

A test based on Maxwell-Boltzman statistics, instead of the formerly suggested but inappropriate Bose-Einstein statistics (Pielou and Routledge, 1976), examines the distribution of the boundaries of species' ranges distributed along a gradient, and indicates whether they are random or clustered (zoned). The test is most useful as a preliminary to the application of more instructive but less statistically rigorous methods such as cluster analysis. The test indicates zonation is marked in the deep benthic megafauna living between 200 and 3000 m, but below 3000 m little zonation may be found.

Rigorous Approach in Investigation of Seismic Structure and Source Characteristicsin Northeast Asia: Hierarchical and Trans-dimensional Bayesian Inversion

NASA Astrophysics Data System (ADS)

Mustac, M.; Kim, S.; Tkalcic, H.; Rhie, J.; Chen, Y.; Ford, S. R.; Sebastian, N.

2015-12-01

Conventional approaches to inverse problems suffer from non-linearity and non-uniqueness in estimations of seismic structures and source properties. Estimated results and associated uncertainties are often biased by applied regularizations and additional constraints, which are commonly introduced to solve such problems. Bayesian methods, however, provide statistically meaningful estimations of models and their uncertainties constrained by data information. In addition, hierarchical and trans-dimensional (trans-D) techniques are inherently implemented in the Bayesian framework to account for involved error statistics and model parameterizations, and, in turn, allow more rigorous estimations of the same. Here, we apply Bayesian methods throughout the entire inference process to estimate seismic structures and source properties in Northeast Asia including east China, the Korean peninsula, and the Japanese islands. Ambient noise analysis is first performed to obtain a base three-dimensional (3-D) heterogeneity model using continuous broadband waveforms from more than 300 stations. As for the tomography of surface wave group and phase velocities in the 5-70 s band, we adopt a hierarchical and trans-D Bayesian inversion method using Voronoi partition. The 3-D heterogeneity model is further improved by joint inversions of teleseismic receiver functions and dispersion data using a newly developed high-efficiency Bayesian technique. The obtained model is subsequently used to prepare 3-D structural Green's functions for the source characterization. A hierarchical Bayesian method for point source inversion using regional complete waveform data is applied to selected events from the region. The seismic structure and source characteristics with rigorously estimated uncertainties from the novel Bayesian methods provide enhanced monitoring and discrimination of seismic events in northeast Asia.

Rigorous evaluation of chemical measurement uncertainty: liquid chromatographic analysis methods using detector response factor calibration

NASA Astrophysics Data System (ADS)

Toman, Blaza; Nelson, Michael A.; Bedner, Mary

2017-06-01

Chemical measurement methods are designed to promote accurate knowledge of a measurand or system. As such, these methods often allow elicitation of latent sources of variability and correlation in experimental data. They typically implement measurement equations that support quantification of effects associated with calibration standards and other known or observed parametric variables. Additionally, multiple samples and calibrants are usually analyzed to assess accuracy of the measurement procedure and repeatability by the analyst. Thus, a realistic assessment of uncertainty for most chemical measurement methods is not purely bottom-up (based on the measurement equation) or top-down (based on the experimental design), but inherently contains elements of both. Confidence in results must be rigorously evaluated for the sources of variability in all of the bottom-up and top-down elements. This type of analysis presents unique challenges due to various statistical correlations among the outputs of measurement equations. One approach is to use a Bayesian hierarchical (BH) model which is intrinsically rigorous, thus making it a straightforward method for use with complex experimental designs, particularly when correlations among data are numerous and difficult to elucidate or explicitly quantify. In simpler cases, careful analysis using GUM Supplement 1 (MC) methods augmented with random effects meta analysis yields similar results to a full BH model analysis. In this article we describe both approaches to rigorous uncertainty evaluation using as examples measurements of 25-hydroxyvitamin D3 in solution reference materials via liquid chromatography with UV absorbance detection (LC-UV) and liquid chromatography mass spectrometric detection using isotope dilution (LC-IDMS).

Rigorous Science: a How-To Guide.

PubMed

Casadevall, Arturo; Fang, Ferric C

2016-11-08

Proposals to improve the reproducibility of biomedical research have emphasized scientific rigor. Although the word "rigor" is widely used, there has been little specific discussion as to what it means and how it can be achieved. We suggest that scientific rigor combines elements of mathematics, logic, philosophy, and ethics. We propose a framework for rigor that includes redundant experimental design, sound statistical analysis, recognition of error, avoidance of logical fallacies, and intellectual honesty. These elements lead to five actionable recommendations for research education. Copyright © 2016 Casadevall and Fang.

Time Series Expression Analyses Using RNA-seq: A Statistical Approach

PubMed Central

Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P.

2013-01-01

RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis. PMID:23586021

Time series expression analyses using RNA-seq: a statistical approach.

PubMed

Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P

2013-01-01

RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis.

Interactive visual analysis promotes exploration of long-term ecological data

Treesearch

T.N. Pham; J.A. Jones; R. Metoyer; F.J. Swanson; R.J. Pabst

2013-01-01

Long-term ecological data are crucial in helping ecologists understand ecosystem function and environmental change. Nevertheless, these kinds of data sets are difficult to analyze because they are usually large, multivariate, and spatiotemporal. Although existing analysis tools such as statistical methods and spreadsheet software permit rigorous tests of pre-conceived...

On Improving the Quality and Interpretation of Environmental Assessments using Statistical Analysis and Geographic Information Systems

NASA Astrophysics Data System (ADS)

Karuppiah, R.; Faldi, A.; Laurenzi, I.; Usadi, A.; Venkatesh, A.

2014-12-01

An increasing number of studies are focused on assessing the environmental footprint of different products and processes, especially using life cycle assessment (LCA). This work shows how combining statistical methods and Geographic Information Systems (GIS) with environmental analyses can help improve the quality of results and their interpretation. Most environmental assessments in literature yield single numbers that characterize the environmental impact of a process/product - typically global or country averages, often unchanging in time. In this work, we show how statistical analysis and GIS can help address these limitations. For example, we demonstrate a method to separately quantify uncertainty and variability in the result of LCA models using a power generation case study. This is important for rigorous comparisons between the impacts of different processes. Another challenge is lack of data that can affect the rigor of LCAs. We have developed an approach to estimate environmental impacts of incompletely characterized processes using predictive statistical models. This method is applied to estimate unreported coal power plant emissions in several world regions. There is also a general lack of spatio-temporal characterization of the results in environmental analyses. For instance, studies that focus on water usage do not put in context where and when water is withdrawn. Through the use of hydrological modeling combined with GIS, we quantify water stress on a regional and seasonal basis to understand water supply and demand risks for multiple users. Another example where it is important to consider regional dependency of impacts is when characterizing how agricultural land occupation affects biodiversity in a region. We developed a data-driven methodology used in conjuction with GIS to determine if there is a statistically significant difference between the impacts of growing different crops on different species in various biomes of the world.

Why so many "rigorous" evaluations fail to identify unintended consequences of development programs: How mixed methods can contribute.

PubMed

Bamberger, Michael; Tarsilla, Michele; Hesse-Biber, Sharlene

2016-04-01

Many widely-used impact evaluation designs, including randomized control trials (RCTs) and quasi-experimental designs (QEDs), frequently fail to detect what are often quite serious unintended consequences of development programs. This seems surprising as experienced planners and evaluators are well aware that unintended consequences frequently occur. Most evaluation designs are intended to determine whether there is credible evidence (statistical, theory-based or narrative) that programs have achieved their intended objectives and the logic of many evaluation designs, even those that are considered the most "rigorous," does not permit the identification of outcomes that were not specified in the program design. We take the example of RCTs as they are considered by many to be the most rigorous evaluation designs. We present a numbers of cases to illustrate how infusing RCTs with a mixed-methods approach (sometimes called an "RCT+" design) can strengthen the credibility of these designs and can also capture important unintended consequences. We provide a Mixed Methods Evaluation Framework that identifies 9 ways in which UCs can occur, and we apply this framework to two of the case studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Tensile Properties of Dyneema SK76 Single Fibers at Multiple Loading Rates Using a Direct Gripping Method

DTIC Science & Technology

2014-06-01

lower density compared with aramid fibers such as Kevlar and Twaron. Numerical modeling is used to design more effective fiber-based composite armor...in measuring fibers and doing experiments. vi INTENTIONALLY LEFT BLANK. 1 1. Introduction Aramid fibers such as Kevlar (DuPont) and Twaron...methyl methacrylate blocks. The efficacy of this method to grip Kevlar fibers has been rigorously studied using a variety of statistical methods at

Increased scientific rigor will improve reliability of research and effectiveness of management

USGS Publications Warehouse

Sells, Sarah N.; Bassing, Sarah B.; Barker, Kristin J.; Forshee, Shannon C.; Keever, Allison; Goerz, James W.; Mitchell, Michael S.

2018-01-01

Rigorous science that produces reliable knowledge is critical to wildlife management because it increases accurate understanding of the natural world and informs management decisions effectively. Application of a rigorous scientific method based on hypothesis testing minimizes unreliable knowledge produced by research. To evaluate the prevalence of scientific rigor in wildlife research, we examined 24 issues of the Journal of Wildlife Management from August 2013 through July 2016. We found 43.9% of studies did not state or imply a priori hypotheses, which are necessary to produce reliable knowledge. We posit that this is due, at least in part, to a lack of common understanding of what rigorous science entails, how it produces more reliable knowledge than other forms of interpreting observations, and how research should be designed to maximize inferential strength and usefulness of application. Current primary literature does not provide succinct explanations of the logic behind a rigorous scientific method or readily applicable guidance for employing it, particularly in wildlife biology; we therefore synthesized an overview of the history, philosophy, and logic that define scientific rigor for biological studies. A rigorous scientific method includes 1) generating a research question from theory and prior observations, 2) developing hypotheses (i.e., plausible biological answers to the question), 3) formulating predictions (i.e., facts that must be true if the hypothesis is true), 4) designing and implementing research to collect data potentially consistent with predictions, 5) evaluating whether predictions are consistent with collected data, and 6) drawing inferences based on the evaluation. Explicitly testing a priori hypotheses reduces overall uncertainty by reducing the number of plausible biological explanations to only those that are logically well supported. Such research also draws inferences that are robust to idiosyncratic observations and unavoidable human biases. Offering only post hoc interpretations of statistical patterns (i.e., a posteriorihypotheses) adds to uncertainty because it increases the number of plausible biological explanations without determining which have the greatest support. Further, post hocinterpretations are strongly subject to human biases. Testing hypotheses maximizes the credibility of research findings, makes the strongest contributions to theory and management, and improves reproducibility of research. Management decisions based on rigorous research are most likely to result in effective conservation of wildlife resources. 

Electrical Conductivity of Charged Particle Systems and Zubarev's Nonequilibrium Statistical Operator Method

NASA Astrophysics Data System (ADS)

Röpke, G.

2018-01-01

One of the fundamental problems in physics that are not yet rigorously solved is the statistical mechanics of nonequilibrium processes. An important contribution to describing irreversible behavior starting from reversible Hamiltonian dynamics was given by D. N. Zubarev, who invented the method of the nonequilibrium statistical operator. We discuss this approach, in particular, the extended von Neumann equation, and as an example consider the electrical conductivity of a system of charged particles. We consider the selection of the set of relevant observables. We show the relation between kinetic theory and linear response theory. Using thermodynamic Green's functions, we present a systematic treatment of correlation functions, but the convergence needs investigation. We compare different expressions for the conductivity and list open questions.

Proposal for a biometrics of the cortical surface: a statistical method for relative surface distance metrics

NASA Astrophysics Data System (ADS)

Bookstein, Fred L.

1995-08-01

Recent advances in computational geometry have greatly extended the range of neuroanatomical questions that can be approached by rigorous quantitative methods. One of the major current challenges in this area is to describe the variability of human cortical surface form and its implications for individual differences in neurophysiological functioning. Existing techniques for representation of stochastically invaginated surfaces do not conduce to the necessary parametric statistical summaries. In this paper, following a hint from David Van Essen and Heather Drury, I sketch a statistical method customized for the constraints of this complex data type. Cortical surface form is represented by its Riemannian metric tensor and averaged according to parameters of a smooth averaged surface. Sulci are represented by integral trajectories of the smaller principal strains of this metric, and their statistics follow the statistics of that relative metric. The diagrams visualizing this tensor analysis look like alligator leather but summarize all aspects of cortical surface form in between the principal sulci, the reliable ones; no flattening is required.

Establishing Interventions via a Theory-Driven Single Case Design Research Cycle

ERIC Educational Resources Information Center

Kilgus, Stephen P.; Riley-Tillman, T. Chris; Kratochwill, Thomas R.

2016-01-01

Recent studies have suggested single case design (SCD) intervention research is subject to publication bias, wherein studies are more likely to be published if they possess large or statistically significant effects and use rigorous experimental methods. The nature of SCD and the purposes for which it might be used could suggest that large effects…

Measuring the Unmeasurable: Upholding Rigor in Quantitative Studies of Personal and Social Development in Outdoor Adventure Education

ERIC Educational Resources Information Center

Scrutton, Roger; Beames, Simon

2015-01-01

Outdoor adventure education (OAE) has a long history of being credited with the personal and social development (PSD) of its participants. PSD is notoriously difficult to measure quantitatively, yet stakeholders demand statistical evidence that given approaches to eliciting PSD are effective in their methods. Rightly or wrongly, many stakeholders…

CORSSA: The Community Online Resource for Statistical Seismicity Analysis

USGS Publications Warehouse

Michael, Andrew J.; Wiemer, Stefan

2010-01-01

Statistical seismology is the application of rigorous statistical methods to earthquake science with the goal of improving our knowledge of how the earth works. Within statistical seismology there is a strong emphasis on the analysis of seismicity data in order to improve our scientific understanding of earthquakes and to improve the evaluation and testing of earthquake forecasts, earthquake early warning, and seismic hazards assessments. Given the societal importance of these applications, statistical seismology must be done well. Unfortunately, a lack of educational resources and available software tools make it difficult for students and new practitioners to learn about this discipline. The goal of the Community Online Resource for Statistical Seismicity Analysis (CORSSA) is to promote excellence in statistical seismology by providing the knowledge and resources necessary to understand and implement the best practices, so that the reader can apply these methods to their own research. This introduction describes the motivation for and vision of CORRSA. It also describes its structure and contents.

Rigorous Science: a How-To Guide

PubMed Central

Fang, Ferric C.

2016-01-01

ABSTRACT Proposals to improve the reproducibility of biomedical research have emphasized scientific rigor. Although the word “rigor” is widely used, there has been little specific discussion as to what it means and how it can be achieved. We suggest that scientific rigor combines elements of mathematics, logic, philosophy, and ethics. We propose a framework for rigor that includes redundant experimental design, sound statistical analysis, recognition of error, avoidance of logical fallacies, and intellectual honesty. These elements lead to five actionable recommendations for research education. PMID:27834205

The average receiver operating characteristic curve in multireader multicase imaging studies

PubMed Central

Samuelson, F W

2014-01-01

Objective: In multireader, multicase (MRMC) receiver operating characteristic (ROC) studies for evaluating medical imaging systems, the area under the ROC curve (AUC) is often used as a summary metric. Owing to the limitations of AUC, plotting the average ROC curve to accompany the rigorous statistical inference on AUC is recommended. The objective of this article is to investigate methods for generating the average ROC curve from ROC curves of individual readers. Methods: We present both a non-parametric method and a parametric method for averaging ROC curves that produce a ROC curve, the area under which is equal to the average AUC of individual readers (a property we call area preserving). We use hypothetical examples, simulated data and a real-world imaging data set to illustrate these methods and their properties. Results: We show that our proposed methods are area preserving. We also show that the method of averaging the ROC parameters, either the conventional bi-normal parameters (a, b) or the proper bi-normal parameters (c, da), is generally not area preserving and may produce a ROC curve that is intuitively not an average of multiple curves. Conclusion: Our proposed methods are useful for making plots of average ROC curves in MRMC studies as a companion to the rigorous statistical inference on the AUC end point. The software implementing these methods is freely available from the authors. Advances in knowledge: Methods for generating the average ROC curve in MRMC ROC studies are formally investigated. The area-preserving criterion we defined is useful to evaluate such methods. PMID:24884728

Scaling up to address data science challenges

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wendelberger, Joanne R.

Statistics and Data Science provide a variety of perspectives and technical approaches for exploring and understanding Big Data. Partnerships between scientists from different fields such as statistics, machine learning, computer science, and applied mathematics can lead to innovative approaches for addressing problems involving increasingly large amounts of data in a rigorous and effective manner that takes advantage of advances in computing. Here, this article will explore various challenges in Data Science and will highlight statistical approaches that can facilitate analysis of large-scale data including sampling and data reduction methods, techniques for effective analysis and visualization of large-scale simulations, and algorithmsmore » and procedures for efficient processing.« less

Scaling up to address data science challenges

DOE PAGES

Wendelberger, Joanne R.

2017-04-27

Statistics and Data Science provide a variety of perspectives and technical approaches for exploring and understanding Big Data. Partnerships between scientists from different fields such as statistics, machine learning, computer science, and applied mathematics can lead to innovative approaches for addressing problems involving increasingly large amounts of data in a rigorous and effective manner that takes advantage of advances in computing. Here, this article will explore various challenges in Data Science and will highlight statistical approaches that can facilitate analysis of large-scale data including sampling and data reduction methods, techniques for effective analysis and visualization of large-scale simulations, and algorithmsmore » and procedures for efficient processing.« less

Statistical issues in the design, conduct and analysis of two large safety studies.

PubMed

Gaffney, Michael

2016-10-01

The emergence, post approval, of serious medical events, which may be associated with the use of a particular drug or class of drugs, is an important public health and regulatory issue. The best method to address this issue is through a large, rigorously designed safety study. Therefore, it is important to elucidate the statistical issues involved in these large safety studies. Two such studies are PRECISION and EAGLES. PRECISION is the primary focus of this article. PRECISION is a non-inferiority design with a clinically relevant non-inferiority margin. Statistical issues in the design, conduct and analysis of PRECISION are discussed. Quantitative and clinical aspects of the selection of the composite primary endpoint, the determination and role of the non-inferiority margin in a large safety study and the intent-to-treat and modified intent-to-treat analyses in a non-inferiority safety study are shown. Protocol changes that were necessary during the conduct of PRECISION are discussed from a statistical perspective. Issues regarding the complex analysis and interpretation of the results of PRECISION are outlined. EAGLES is presented as a large, rigorously designed safety study when a non-inferiority margin was not able to be determined by a strong clinical/scientific method. In general, when a non-inferiority margin is not able to be determined, the width of the 95% confidence interval is a way to size the study and to assess the cost-benefit of relative trial size. A non-inferiority margin, when able to be determined by a strong scientific method, should be included in a large safety study. Although these studies could not be called "pragmatic," they are examples of best real-world designs to address safety and regulatory concerns. © The Author(s) 2016.

Academic Rigor and Economic Value: GED[R] and High School Students' Perceptions and Misperceptions of the GED[R] vs. the High School Diploma

ERIC Educational Resources Information Center

Horne, Lela M.; Rachal, John R.; Shelley, Kyna

2012-01-01

A mixed methods framework utilized quantitative and qualitative data to determine whether statistically significant differences existed between high school and GED[R] student perceptions of credential value. An exploratory factor analysis (n=326) extracted four factors and then a MANOVA procedure was performed with a stratified quota sample…

Adult asthma disease management: an analysis of studies, approaches, outcomes, and methods.

PubMed

Maciejewski, Matthew L; Chen, Shih-Yin; Au, David H

2009-07-01

Disease management has been implemented for patients with asthma in various ways. We describe the approaches to and components of adult asthma disease-management interventions, examine the outcomes evaluated, and assess the quality of published studies. We searched the MEDLINE, EMBASE, CINAHL, PsychInfo, and Cochrane databases for studies published in 1986 through 2008, on adult asthma management. With the studies that met our inclusion criteria, we examined the clinical, process, medication, economic, and patient-reported outcomes reported, and the study designs, provider collaboration during the studies, and statistical methods. Twenty-nine articles describing 27 studies satisfied our inclusion criteria. There was great variation in the content, extent of collaboration between physician and non-physician providers responsible for intervention delivery, and outcomes examined across the 27 studies. Because of limitations in the design of 22 of the 27 studies, the differences in outcomes assessed, and the lack of rigorous statistical adjustment, we could not draw definitive conclusions about the effectiveness or cost-effectiveness of the asthma disease-management programs or which approach was most effective. Few well-designed studies with rigorous evaluations have been conducted to evaluate disease-management interventions for adults with asthma. Current evidence is insufficient to recommend any particular intervention.

Statistical Methods Applied to Gamma-ray Spectroscopy Algorithms in Nuclear Security Missions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fagan, Deborah K.; Robinson, Sean M.; Runkle, Robert C.

2012-10-01

In a wide range of nuclear security missions, gamma-ray spectroscopy is a critical research and development priority. One particularly relevant challenge is the interdiction of special nuclear material for which gamma-ray spectroscopy supports the goals of detecting and identifying gamma-ray sources. This manuscript examines the existing set of spectroscopy methods, attempts to categorize them by the statistical methods on which they rely, and identifies methods that have yet to be considered. Our examination shows that current methods effectively estimate the effect of counting uncertainty but in many cases do not address larger sources of decision uncertainty—ones that are significantly moremore » complex. We thus explore the premise that significantly improving algorithm performance requires greater coupling between the problem physics that drives data acquisition and statistical methods that analyze such data. Untapped statistical methods, such as Bayes Modeling Averaging and hierarchical and empirical Bayes methods have the potential to reduce decision uncertainty by more rigorously and comprehensively incorporating all sources of uncertainty. We expect that application of such methods will demonstrate progress in meeting the needs of nuclear security missions by improving on the existing numerical infrastructure for which these analyses have not been conducted.« less

Improved methods for distribution loss evaluation. Volume 1: analytic and evaluative techniques. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Flinn, D.G.; Hall, S.; Morris, J.

This volume describes the background research, the application of the proposed loss evaluation techniques, and the results. The research identified present loss calculation methods as appropriate, provided care was taken to represent the various system elements in sufficient detail. The literature search of past methods and typical data revealed that extreme caution in using typical values (load factor, etc.) should be taken to ensure that all factors were referred to the same time base (daily, weekly, etc.). The performance of the method (and computer program) proposed in this project was determined by comparison of results with a rigorous evaluation ofmore » losses on the Salt River Project system. This rigorous evaluation used statistical modeling of the entire system as well as explicit enumeration of all substation and distribution transformers. Further tests were conducted at Public Service Electric and Gas of New Jersey to check the appropriateness of the methods in a northern environment. Finally sensitivity tests indicated data elements inaccuracy of which would most affect the determination of losses using the method developed in this project.« less

[Adequate application of quantitative and qualitative statistic analytic methods in acupuncture clinical trials].

PubMed

Tan, Ming T; Liu, Jian-ping; Lao, Lixing

2012-08-01

Recently, proper use of the statistical methods in traditional Chinese medicine (TCM) randomized controlled trials (RCTs) has received increased attention. Statistical inference based on hypothesis testing is the foundation of clinical trials and evidence-based medicine. In this article, the authors described the methodological differences between literature published in Chinese and Western journals in the design and analysis of acupuncture RCTs and the application of basic statistical principles. In China, qualitative analysis method has been widely used in acupuncture and TCM clinical trials, while the between-group quantitative analysis methods on clinical symptom scores are commonly used in the West. The evidence for and against these analytical differences were discussed based on the data of RCTs assessing acupuncture for pain relief. The authors concluded that although both methods have their unique advantages, quantitative analysis should be used as the primary analysis while qualitative analysis can be a secondary criterion for analysis. The purpose of this paper is to inspire further discussion of such special issues in clinical research design and thus contribute to the increased scientific rigor of TCM research.

Statistical methods for thermonuclear reaction rates and nucleosynthesis simulations

NASA Astrophysics Data System (ADS)

Iliadis, Christian; Longland, Richard; Coc, Alain; Timmes, F. X.; Champagne, Art E.

2015-03-01

Rigorous statistical methods for estimating thermonuclear reaction rates and nucleosynthesis are becoming increasingly established in nuclear astrophysics. The main challenge being faced is that experimental reaction rates are highly complex quantities derived from a multitude of different measured nuclear parameters (e.g., astrophysical S-factors, resonance energies and strengths, particle and γ-ray partial widths). We discuss the application of the Monte Carlo method to two distinct, but related, questions. First, given a set of measured nuclear parameters, how can one best estimate the resulting thermonuclear reaction rates and associated uncertainties? Second, given a set of appropriate reaction rates, how can one best estimate the abundances from nucleosynthesis (i.e., reaction network) calculations? The techniques described here provide probability density functions that can be used to derive statistically meaningful reaction rates and final abundances for any desired coverage probability. Examples are given for applications to s-process neutron sources, core-collapse supernovae, classical novae, and Big Bang nucleosynthesis.

Methodological rigor and citation frequency in patient compliance literature.

PubMed Central

Bruer, J T

1982-01-01

An exhaustive bibliography which assesses the methodological rigor of the patient compliance literature, and citation data from the Science Citation Index (SCI) are combined to determine if methodologically rigorous papers are used with greater frequency than substandard articles by compliance investigators. There are low, but statistically significant, correlations between methodological rigor and citation indicators for 138 patient compliance papers published in SCI source journals during 1975 and 1976. The correlation is not strong enough to warrant use of citation measures as indicators of rigor on a paper-by-paper basis. The data do suggest that citation measures might be developed as crude indicators of methodological rigor. There is no evidence that randomized trials are cited more frequently than studies that employ other experimental designs. PMID:7114334

Peer Review of EPA's Draft BMDS Document: Exponential ...

EPA Pesticide Factsheets

BMDS is one of the Agency's premier tools for estimating risk assessments, therefore the validity and reliability of its statistical models are of paramount importance. This page provides links to peer review of the BMDS applications and its models as they were developed and eventually released documenting the rigorous review process taken to provide the best science tools available for statistical modeling. This page provides links to peer review of the BMDS applications and its models as they were developed and eventually released documenting the rigorous review process taken to provide the best science tools available for statistical modeling.

Probability bounds analysis for nonlinear population ecology models.

PubMed

Enszer, Joshua A; Andrei Măceș, D; Stadtherr, Mark A

2015-09-01

Mathematical models in population ecology often involve parameters that are empirically determined and inherently uncertain, with probability distributions for the uncertainties not known precisely. Propagating such imprecise uncertainties rigorously through a model to determine their effect on model outputs can be a challenging problem. We illustrate here a method for the direct propagation of uncertainties represented by probability bounds though nonlinear, continuous-time, dynamic models in population ecology. This makes it possible to determine rigorous bounds on the probability that some specified outcome for a population is achieved, which can be a core problem in ecosystem modeling for risk assessment and management. Results can be obtained at a computational cost that is considerably less than that required by statistical sampling methods such as Monte Carlo analysis. The method is demonstrated using three example systems, with focus on a model of an experimental aquatic food web subject to the effects of contamination by ionic liquids, a new class of potentially important industrial chemicals. Copyright © 2015. Published by Elsevier Inc.

Estimation of integral curves from high angular resolution diffusion imaging (HARDI) data.

PubMed

Carmichael, Owen; Sakhanenko, Lyudmila

2015-05-15

We develop statistical methodology for a popular brain imaging technique HARDI based on the high order tensor model by Özarslan and Mareci [10]. We investigate how uncertainty in the imaging procedure propagates through all levels of the model: signals, tensor fields, vector fields, and fibers. We construct asymptotically normal estimators of the integral curves or fibers which allow us to trace the fibers together with confidence ellipsoids. The procedure is computationally intense as it blends linear algebra concepts from high order tensors with asymptotical statistical analysis. The theoretical results are illustrated on simulated and real datasets. This work generalizes the statistical methodology proposed for low angular resolution diffusion tensor imaging by Carmichael and Sakhanenko [3], to several fibers per voxel. It is also a pioneering statistical work on tractography from HARDI data. It avoids all the typical limitations of the deterministic tractography methods and it delivers the same information as probabilistic tractography methods. Our method is computationally cheap and it provides well-founded mathematical and statistical framework where diverse functionals on fibers, directions and tensors can be studied in a systematic and rigorous way.

Estimation of integral curves from high angular resolution diffusion imaging (HARDI) data

PubMed Central

Carmichael, Owen; Sakhanenko, Lyudmila

2015-01-01

We develop statistical methodology for a popular brain imaging technique HARDI based on the high order tensor model by Özarslan and Mareci [10]. We investigate how uncertainty in the imaging procedure propagates through all levels of the model: signals, tensor fields, vector fields, and fibers. We construct asymptotically normal estimators of the integral curves or fibers which allow us to trace the fibers together with confidence ellipsoids. The procedure is computationally intense as it blends linear algebra concepts from high order tensors with asymptotical statistical analysis. The theoretical results are illustrated on simulated and real datasets. This work generalizes the statistical methodology proposed for low angular resolution diffusion tensor imaging by Carmichael and Sakhanenko [3], to several fibers per voxel. It is also a pioneering statistical work on tractography from HARDI data. It avoids all the typical limitations of the deterministic tractography methods and it delivers the same information as probabilistic tractography methods. Our method is computationally cheap and it provides well-founded mathematical and statistical framework where diverse functionals on fibers, directions and tensors can be studied in a systematic and rigorous way. PMID:25937674

Exploring Gender-Specific Trends in Underage Drinking across Adolescent Age Groups and Measures of Drinking: Is Girls' Drinking Catching up with Boys'?

ERIC Educational Resources Information Center

Zhong, Hua; Schwartz, Jennifer

2010-01-01

Underage drinking is among the most serious of public health problems facing adolescents in the United States. Recent concerns have centered on young women, reflected in media reports and arrest statistics on their increasing problematic alcohol use. This study rigorously examined whether girls' alcohol use rose by applying time series methods to…

Bayesian Reconstruction of Disease Outbreaks by Combining Epidemiologic and Genomic Data

PubMed Central

Jombart, Thibaut; Cori, Anne; Didelot, Xavier; Cauchemez, Simon; Fraser, Christophe; Ferguson, Neil

2014-01-01

Recent years have seen progress in the development of statistically rigorous frameworks to infer outbreak transmission trees (“who infected whom”) from epidemiological and genetic data. Making use of pathogen genome sequences in such analyses remains a challenge, however, with a variety of heuristic approaches having been explored to date. We introduce a statistical method exploiting both pathogen sequences and collection dates to unravel the dynamics of densely sampled outbreaks. Our approach identifies likely transmission events and infers dates of infections, unobserved cases and separate introductions of the disease. It also proves useful for inferring numbers of secondary infections and identifying heterogeneous infectivity and super-spreaders. After testing our approach using simulations, we illustrate the method with the analysis of the beginning of the 2003 Singaporean outbreak of Severe Acute Respiratory Syndrome (SARS), providing new insights into the early stage of this epidemic. Our approach is the first tool for disease outbreak reconstruction from genetic data widely available as free software, the R package outbreaker. It is applicable to various densely sampled epidemics, and improves previous approaches by detecting unobserved and imported cases, as well as allowing multiple introductions of the pathogen. Because of its generality, we believe this method will become a tool of choice for the analysis of densely sampled disease outbreaks, and will form a rigorous framework for subsequent methodological developments. PMID:24465202

A Rigorous Statistical Approach to Determine Solar Wind Composition from ACE/SWICS Data, and New Ne/O Ratios

NASA Astrophysics Data System (ADS)

Shearer, P.; Jawed, M. K.; Raines, J. M.; Lepri, S. T.; Gilbert, J. A.; von Steiger, R.; Zurbuchen, T.

2013-12-01

The SWICS instruments aboard ACE and Ulysses have performed in situ measurements of individual solar wind ions for a period spanning over two decades. Solar wind composition is determined by accumulating the measurements into an ion count histogram in which each species appears as a distinct peak. Assigning counts to the appropriate species is a challenging statistical problem because of the limited counts for some species and overlap between some peaks. We show that the most commonly used count assignment methods can suffer from significant bias when a highly abundant species overlaps with a much less abundant one. For ACE/SWICS data, this bias results in an overestimated Ne/O ratio. Bias is greatly reduced by switching to a rigorous maximum likelihood count assignment method, resulting in a 30-50% reduction in the estimated Ne abundance. We will discuss the new Ne/O values and put them in context with the solar system abundances for Ne derived from other techniques, such as in situ collection from Genesis and its heritage instrument, the Solar Foil experiment during the Apollo era. The new count assignment method is currently being applied to reanalyze the archived ACE and Ulysses data and obtain revised abundances of C, N, O, Ne, Mg, Si, S, and Fe, leading to revised datasets that will be made publicly available.

Predicting and downscaling ENSO impacts on intraseasonal precipitation statistics in California: The 1997/98 event

USGS Publications Warehouse

Gershunov, A.; Barnett, T.P.; Cayan, D.R.; Tubbs, T.; Goddard, L.

2000-01-01

Three long-range forecasting methods have been evaluated for prediction and downscaling of seasonal and intraseasonal precipitation statistics in California. Full-statistical, hybrid-dynamical - statistical and full-dynamical approaches have been used to forecast El Nin??o - Southern Oscillation (ENSO) - related total precipitation, daily precipitation frequency, and average intensity anomalies during the January - March season. For El Nin??o winters, the hybrid approach emerges as the best performer, while La Nin??a forecasting skill is poor. The full-statistical forecasting method features reasonable forecasting skill for both La Nin??a and El Nin??o winters. The performance of the full-dynamical approach could not be evaluated as rigorously as that of the other two forecasting schemes. Although the full-dynamical forecasting approach is expected to outperform simpler forecasting schemes in the long run, evidence is presented to conclude that, at present, the full-dynamical forecasting approach is the least viable of the three, at least in California. The authors suggest that operational forecasting of any intraseasonal temperature, precipitation, or streamflow statistic derivable from the available records is possible now for ENSO-extreme years.

External model validation of binary clinical risk prediction models in cardiovascular and thoracic surgery.

PubMed

Hickey, Graeme L; Blackstone, Eugene H

2016-08-01

Clinical risk-prediction models serve an important role in healthcare. They are used for clinical decision-making and measuring the performance of healthcare providers. To establish confidence in a model, external model validation is imperative. When designing such an external model validation study, thought must be given to patient selection, risk factor and outcome definitions, missing data, and the transparent reporting of the analysis. In addition, there are a number of statistical methods available for external model validation. Execution of a rigorous external validation study rests in proper study design, application of suitable statistical methods, and transparent reporting. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Alarms about structural alerts.

PubMed

Alves, Vinicius; Muratov, Eugene; Capuzzi, Stephen; Politi, Regina; Low, Yen; Braga, Rodolpho; Zakharov, Alexey V; Sedykh, Alexander; Mokshyna, Elena; Farag, Sherif; Andrade, Carolina; Kuz'min, Victor; Fourches, Denis; Tropsha, Alexander

2016-08-21

Structural alerts are widely accepted in chemical toxicology and regulatory decision support as a simple and transparent means to flag potential chemical hazards or group compounds into categories for read-across. However, there has been a growing concern that alerts disproportionally flag too many chemicals as toxic, which questions their reliability as toxicity markers. Conversely, the rigorously developed and properly validated statistical QSAR models can accurately and reliably predict the toxicity of a chemical; however, their use in regulatory toxicology has been hampered by the lack of transparency and interpretability. We demonstrate that contrary to the common perception of QSAR models as "black boxes" they can be used to identify statistically significant chemical substructures (QSAR-based alerts) that influence toxicity. We show through several case studies, however, that the mere presence of structural alerts in a chemical, irrespective of the derivation method (expert-based or QSAR-based), should be perceived only as hypotheses of possible toxicological effect. We propose a new approach that synergistically integrates structural alerts and rigorously validated QSAR models for a more transparent and accurate safety assessment of new chemicals.

Uncertainty Analysis of Instrument Calibration and Application

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Experimental aerodynamic researchers require estimated precision and bias uncertainties of measured physical quantities, typically at 95 percent confidence levels. Uncertainties of final computed aerodynamic parameters are obtained by propagation of individual measurement uncertainties through the defining functional expressions. In this paper, rigorous mathematical techniques are extended to determine precision and bias uncertainties of any instrument-sensor system. Through this analysis, instrument uncertainties determined through calibration are now expressed as functions of the corresponding measurement for linear and nonlinear univariate and multivariate processes. Treatment of correlated measurement precision error is developed. During laboratory calibration, calibration standard uncertainties are assumed to be an order of magnitude less than those of the instrument being calibrated. Often calibration standards do not satisfy this assumption. This paper applies rigorous statistical methods for inclusion of calibration standard uncertainty and covariance due to the order of their application. The effects of mathematical modeling error on calibration bias uncertainty are quantified. The effects of experimental design on uncertainty are analyzed. The importance of replication is emphasized, techniques for estimation of both bias and precision uncertainties using replication are developed. Statistical tests for stationarity of calibration parameters over time are obtained.

Statistical comparison of a hybrid approach with approximate and exact inference models for Fusion 2+

NASA Astrophysics Data System (ADS)

Lee, K. David; Wiesenfeld, Eric; Gelfand, Andrew

2007-04-01

One of the greatest challenges in modern combat is maintaining a high level of timely Situational Awareness (SA). In many situations, computational complexity and accuracy considerations make the development and deployment of real-time, high-level inference tools very difficult. An innovative hybrid framework that combines Bayesian inference, in the form of Bayesian Networks, and Possibility Theory, in the form of Fuzzy Logic systems, has recently been introduced to provide a rigorous framework for high-level inference. In previous research, the theoretical basis and benefits of the hybrid approach have been developed. However, lacking is a concrete experimental comparison of the hybrid framework with traditional fusion methods, to demonstrate and quantify this benefit. The goal of this research, therefore, is to provide a statistical analysis on the comparison of the accuracy and performance of hybrid network theory, with pure Bayesian and Fuzzy systems and an inexact Bayesian system approximated using Particle Filtering. To accomplish this task, domain specific models will be developed under these different theoretical approaches and then evaluated, via Monte Carlo Simulation, in comparison to situational ground truth to measure accuracy and fidelity. Following this, a rigorous statistical analysis of the performance results will be performed, to quantify the benefit of hybrid inference to other fusion tools.

Robust Statistical Detection of Power-Law Cross-Correlation.

PubMed

Blythe, Duncan A J; Nikulin, Vadim V; Müller, Klaus-Robert

2016-06-02

We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram.

Robust Statistical Detection of Power-Law Cross-Correlation

PubMed Central

Blythe, Duncan A. J.; Nikulin, Vadim V.; Müller, Klaus-Robert

2016-01-01

We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram. PMID:27250630

Dissolution curve comparisons through the F(2) parameter, a Bayesian extension of the f(2) statistic.

PubMed

Novick, Steven; Shen, Yan; Yang, Harry; Peterson, John; LeBlond, Dave; Altan, Stan

2015-01-01

Dissolution (or in vitro release) studies constitute an important aspect of pharmaceutical drug development. One important use of such studies is for justifying a biowaiver for post-approval changes which requires establishing equivalence between the new and old product. We propose a statistically rigorous modeling approach for this purpose based on the estimation of what we refer to as the F2 parameter, an extension of the commonly used f2 statistic. A Bayesian test procedure is proposed in relation to a set of composite hypotheses that capture the similarity requirement on the absolute mean differences between test and reference dissolution profiles. Several examples are provided to illustrate the application. Results of our simulation study comparing the performance of f2 and the proposed method show that our Bayesian approach is comparable to or in many cases superior to the f2 statistic as a decision rule. Further useful extensions of the method, such as the use of continuous-time dissolution modeling, are considered.

Statistical Model Selection for TID Hardness Assurance

NASA Technical Reports Server (NTRS)

Ladbury, R.; Gorelick, J. L.; McClure, S.

2010-01-01

Radiation Hardness Assurance (RHA) methodologies against Total Ionizing Dose (TID) degradation impose rigorous statistical treatments for data from a part's Radiation Lot Acceptance Test (RLAT) and/or its historical performance. However, no similar methods exist for using "similarity" data - that is, data for similar parts fabricated in the same process as the part under qualification. This is despite the greater difficulty and potential risk in interpreting of similarity data. In this work, we develop methods to disentangle part-to-part, lot-to-lot and part-type-to-part-type variation. The methods we develop apply not just for qualification decisions, but also for quality control and detection of process changes and other "out-of-family" behavior. We begin by discussing the data used in ·the study and the challenges of developing a statistic providing a meaningful measure of degradation across multiple part types, each with its own performance specifications. We then develop analysis techniques and apply them to the different data sets.

On the statistical equivalence of restrained-ensemble simulations with the maximum entropy method

PubMed Central

Roux, Benoît; Weare, Jonathan

2013-01-01

An issue of general interest in computer simulations is to incorporate information from experiments into a structural model. An important caveat in pursuing this goal is to avoid corrupting the resulting model with spurious and arbitrary biases. While the problem of biasing thermodynamic ensembles can be formulated rigorously using the maximum entropy method introduced by Jaynes, the approach can be cumbersome in practical applications with the need to determine multiple unknown coefficients iteratively. A popular alternative strategy to incorporate the information from experiments is to rely on restrained-ensemble molecular dynamics simulations. However, the fundamental validity of this computational strategy remains in question. Here, it is demonstrated that the statistical distribution produced by restrained-ensemble simulations is formally consistent with the maximum entropy method of Jaynes. This clarifies the underlying conditions under which restrained-ensemble simulations will yield results that are consistent with the maximum entropy method. PMID:23464140

Statistical Characterization and Classification of Edge-Localized Plasma Instabilities

NASA Astrophysics Data System (ADS)

Webster, A. J.; Dendy, R. O.

2013-04-01

The statistics of edge-localized plasma instabilities (ELMs) in toroidal magnetically confined fusion plasmas are considered. From first principles, standard experimentally motivated assumptions are shown to determine a specific probability distribution for the waiting times between ELMs: the Weibull distribution. This is confirmed empirically by a statistically rigorous comparison with a large data set from the Joint European Torus. The successful characterization of ELM waiting times enables future work to progress in various ways. Here we present a quantitative classification of ELM types, complementary to phenomenological approaches. It also informs us about the nature of ELM processes, such as whether they are random or deterministic. The methods are extremely general and can be applied to numerous other quasiperiodic intermittent phenomena.

Photons Revisited

NASA Astrophysics Data System (ADS)

Batic, Matej; Begalli, Marcia; Han, Min Cheol; Hauf, Steffen; Hoff, Gabriela; Kim, Chan Hyeong; Kim, Han Sung; Grazia Pia, Maria; Saracco, Paolo; Weidenspointner, Georg

2014-06-01

A systematic review of methods and data for the Monte Carlo simulation of photon interactions is in progress: it concerns a wide set of theoretical modeling approaches and data libraries available for this purpose. Models and data libraries are assessed quantitatively with respect to an extensive collection of experimental measurements documented in the literature to determine their accuracy; this evaluation exploits rigorous statistical analysis methods. The computational performance of the associated modeling algorithms is evaluated as well. An overview of the assessment of photon interaction models and results of the experimental validation are presented.

Closed loop statistical performance analysis of N-K knock controllers

NASA Astrophysics Data System (ADS)

Peyton Jones, James C.; Shayestehmanesh, Saeed; Frey, Jesse

2017-09-01

The closed loop performance of engine knock controllers cannot be rigorously assessed from single experiments or simulations because knock behaves as a random process and therefore the response belongs to a random distribution also. In this work a new method is proposed for computing the distributions and expected values of the closed loop response, both in steady state and in response to disturbances. The method takes as its input the control law, and the knock propensity characteristic of the engine which is mapped from open loop steady state tests. The method is applicable to the 'n-k' class of knock controllers in which the control action is a function only of the number of cycles n since the last control move, and the number k of knock events that have occurred in this time. A Cumulative Summation (CumSum) based controller falls within this category, and the method is used to investigate the performance of the controller in a deeper and more rigorous way than has previously been possible. The results are validated using onerous Monte Carlo simulations, which confirm both the validity of the method and its high computational efficiency.

Using expert knowledge to incorporate uncertainty in cause-of-death assignments for modeling of cause-specific mortality

USGS Publications Warehouse

Walsh, Daniel P.; Norton, Andrew S.; Storm, Daniel J.; Van Deelen, Timothy R.; Heisy, Dennis M.

2018-01-01

Implicit and explicit use of expert knowledge to inform ecological analyses is becoming increasingly common because it often represents the sole source of information in many circumstances. Thus, there is a need to develop statistical methods that explicitly incorporate expert knowledge, and can successfully leverage this information while properly accounting for associated uncertainty during analysis. Studies of cause-specific mortality provide an example of implicit use of expert knowledge when causes-of-death are uncertain and assigned based on the observer's knowledge of the most likely cause. To explicitly incorporate this use of expert knowledge and the associated uncertainty, we developed a statistical model for estimating cause-specific mortality using a data augmentation approach within a Bayesian hierarchical framework. Specifically, for each mortality event, we elicited the observer's belief of cause-of-death by having them specify the probability that the death was due to each potential cause. These probabilities were then used as prior predictive values within our framework. This hierarchical framework permitted a simple and rigorous estimation method that was easily modified to include covariate effects and regularizing terms. Although applied to survival analysis, this method can be extended to any event-time analysis with multiple event types, for which there is uncertainty regarding the true outcome. We conducted simulations to determine how our framework compared to traditional approaches that use expert knowledge implicitly and assume that cause-of-death is specified accurately. Simulation results supported the inclusion of observer uncertainty in cause-of-death assignment in modeling of cause-specific mortality to improve model performance and inference. Finally, we applied the statistical model we developed and a traditional method to cause-specific survival data for white-tailed deer, and compared results. We demonstrate that model selection results changed between the two approaches, and incorporating observer knowledge in cause-of-death increased the variability associated with parameter estimates when compared to the traditional approach. These differences between the two approaches can impact reported results, and therefore, it is critical to explicitly incorporate expert knowledge in statistical methods to ensure rigorous inference.

Statistical ecology comes of age.

PubMed

Gimenez, Olivier; Buckland, Stephen T; Morgan, Byron J T; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

2014-12-01

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1-4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.

Statistical ecology comes of age

PubMed Central

Gimenez, Olivier; Buckland, Stephen T.; Morgan, Byron J. T.; Bez, Nicolas; Bertrand, Sophie; Choquet, Rémi; Dray, Stéphane; Etienne, Marie-Pierre; Fewster, Rachel; Gosselin, Frédéric; Mérigot, Bastien; Monestiez, Pascal; Morales, Juan M.; Mortier, Frédéric; Munoz, François; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M.; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; de Valpine, Perry; Rexstad, Eric

2014-01-01

The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1–4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data. PMID:25540151

All biology is computational biology.

PubMed

Markowetz, Florian

2017-03-01

Here, I argue that computational thinking and techniques are so central to the quest of understanding life that today all biology is computational biology. Computational biology brings order into our understanding of life, it makes biological concepts rigorous and testable, and it provides a reference map that holds together individual insights. The next modern synthesis in biology will be driven by mathematical, statistical, and computational methods being absorbed into mainstream biological training, turning biology into a quantitative science.

Methodological reporting in qualitative, quantitative, and mixed methods health services research articles.

PubMed

Wisdom, Jennifer P; Cavaleri, Mary A; Onwuegbuzie, Anthony J; Green, Carla A

2012-04-01

Methodologically sound mixed methods research can improve our understanding of health services by providing a more comprehensive picture of health services than either method can alone. This study describes the frequency of mixed methods in published health services research and compares the presence of methodological components indicative of rigorous approaches across mixed methods, qualitative, and quantitative articles. All empirical articles (n = 1,651) published between 2003 and 2007 from four top-ranked health services journals. All mixed methods articles (n = 47) and random samples of qualitative and quantitative articles were evaluated to identify reporting of key components indicating rigor for each method, based on accepted standards for evaluating the quality of research reports (e.g., use of p-values in quantitative reports, description of context in qualitative reports, and integration in mixed method reports). We used chi-square tests to evaluate differences between article types for each component. Mixed methods articles comprised 2.85 percent (n = 47) of empirical articles, quantitative articles 90.98 percent (n = 1,502), and qualitative articles 6.18 percent (n = 102). There was a statistically significant difference (χ(2) (1) = 12.20, p = .0005, Cramer's V = 0.09, odds ratio = 1.49 [95% confidence interval = 1,27, 1.74]) in the proportion of quantitative methodological components present in mixed methods compared to quantitative papers (21.94 versus 47.07 percent, respectively) but no statistically significant difference (χ(2) (1) = 0.02, p = .89, Cramer's V = 0.01) in the proportion of qualitative methodological components in mixed methods compared to qualitative papers (21.34 versus 25.47 percent, respectively). Few published health services research articles use mixed methods. The frequency of key methodological components is variable. Suggestions are provided to increase the transparency of mixed methods studies and the presence of key methodological components in published reports. © Health Research and Educational Trust.

Methodological Reporting in Qualitative, Quantitative, and Mixed Methods Health Services Research Articles

PubMed Central

Wisdom, Jennifer P; Cavaleri, Mary A; Onwuegbuzie, Anthony J; Green, Carla A

2012-01-01

Objectives Methodologically sound mixed methods research can improve our understanding of health services by providing a more comprehensive picture of health services than either method can alone. This study describes the frequency of mixed methods in published health services research and compares the presence of methodological components indicative of rigorous approaches across mixed methods, qualitative, and quantitative articles. Data Sources All empirical articles (n = 1,651) published between 2003 and 2007 from four top-ranked health services journals. Study Design All mixed methods articles (n = 47) and random samples of qualitative and quantitative articles were evaluated to identify reporting of key components indicating rigor for each method, based on accepted standards for evaluating the quality of research reports (e.g., use of p-values in quantitative reports, description of context in qualitative reports, and integration in mixed method reports). We used chi-square tests to evaluate differences between article types for each component. Principal Findings Mixed methods articles comprised 2.85 percent (n = 47) of empirical articles, quantitative articles 90.98 percent (n = 1,502), and qualitative articles 6.18 percent (n = 102). There was a statistically significant difference (χ2(1) = 12.20, p = .0005, Cramer's V = 0.09, odds ratio = 1.49 [95% confidence interval = 1,27, 1.74]) in the proportion of quantitative methodological components present in mixed methods compared to quantitative papers (21.94 versus 47.07 percent, respectively) but no statistically significant difference (χ2(1) = 0.02, p = .89, Cramer's V = 0.01) in the proportion of qualitative methodological components in mixed methods compared to qualitative papers (21.34 versus 25.47 percent, respectively). Conclusion Few published health services research articles use mixed methods. The frequency of key methodological components is variable. Suggestions are provided to increase the transparency of mixed methods studies and the presence of key methodological components in published reports. PMID:22092040

Applying Sociocultural Theory to Teaching Statistics for Doctoral Social Work Students

ERIC Educational Resources Information Center

Mogro-Wilson, Cristina; Reeves, Michael G.; Charter, Mollie Lazar

2015-01-01

This article describes the development of two doctoral-level multivariate statistics courses utilizing sociocultural theory, an integrative pedagogical framework. In the first course, the implementation of sociocultural theory helps to support the students through a rigorous introduction to statistics. The second course involves students…

Exploring Student Perceptions of Rigor Online: Toward a Definition of Rigorous Learning

ERIC Educational Resources Information Center

Duncan, Heather E.; Range, Bret; Hvidston, David

2013-01-01

Technological advances in the last decade have impacted delivery methods of university courses. More and more courses are offered in a variety of formats. While academic rigor is a term often used, its definition is less clear. This mixed-methods study explored graduate student conceptions of rigor in the online learning environment embedded…

On the probability density function and characteristic function moments of image steganalysis in the log prediction error wavelet subband

NASA Astrophysics Data System (ADS)

Bao, Zhenkun; Li, Xiaolong; Luo, Xiangyang

2017-01-01

Extracting informative statistic features is the most essential technical issue of steganalysis. Among various steganalysis methods, probability density function (PDF) and characteristic function (CF) moments are two important types of features due to the excellent ability for distinguishing the cover images from the stego ones. The two types of features are quite similar in definition. The only difference is that the PDF moments are computed in the spatial domain, while the CF moments are computed in the Fourier-transformed domain. Then, the comparison between PDF and CF moments is an interesting question of steganalysis. Several theoretical results have been derived, and CF moments are proved better than PDF moments in some cases. However, in the log prediction error wavelet subband of wavelet decomposition, some experiments show that the result is opposite and lacks a rigorous explanation. To solve this problem, a comparison result based on the rigorous proof is presented: the first-order PDF moment is proved better than the CF moment, while the second-order CF moment is better than the PDF moment. It tries to open the theoretical discussion on steganalysis and the question of finding suitable statistical features.

A common base method for analysis of qPCR data and the application of simple blocking in qPCR experiments.

PubMed

Ganger, Michael T; Dietz, Geoffrey D; Ewing, Sarah J

2017-12-01

qPCR has established itself as the technique of choice for the quantification of gene expression. Procedures for conducting qPCR have received significant attention; however, more rigorous approaches to the statistical analysis of qPCR data are needed. Here we develop a mathematical model, termed the Common Base Method, for analysis of qPCR data based on threshold cycle values (C q ) and efficiencies of reactions (E). The Common Base Method keeps all calculations in the logscale as long as possible by working with log 10 (E) ∙ C q , which we call the efficiency-weighted C q value; subsequent statistical analyses are then applied in the logscale. We show how efficiency-weighted C q values may be analyzed using a simple paired or unpaired experimental design and develop blocking methods to help reduce unexplained variation. The Common Base Method has several advantages. It allows for the incorporation of well-specific efficiencies and multiple reference genes. The method does not necessitate the pairing of samples that must be performed using traditional analysis methods in order to calculate relative expression ratios. Our method is also simple enough to be implemented in any spreadsheet or statistical software without additional scripts or proprietary components.

Statistical classification approach to discrimination between weak earthquakes and quarry blasts recorded by the Israel Seismic Network

NASA Astrophysics Data System (ADS)

Kushnir, A. F.; Troitsky, E. V.; Haikin, L. M.; Dainty, A.

1999-06-01

A semi-automatic procedure has been developed to achieve statistically optimum discrimination between earthquakes and explosions at local or regional distances based on a learning set specific to a given region. The method is used for step-by-step testing of candidate discrimination features to find the optimum (combination) subset of features, with the decision taken on a rigorous statistical basis. Linear (LDF) and Quadratic (QDF) Discriminant Functions based on Gaussian distributions of the discrimination features are implemented and statistically grounded; the features may be transformed by the Box-Cox transformation z=(1/ α)( yα-1) to make them more Gaussian. Tests of the method were successfully conducted on seismograms from the Israel Seismic Network using features consisting of spectral ratios between and within phases. Results showed that the QDF was more effective than the LDF and required five features out of 18 candidates for the optimum set. It was found that discrimination improved with increasing distance within the local range, and that eliminating transformation of the features and failing to correct for noise led to degradation of discrimination.

Mass spectrometry-based protein identification with accurate statistical significance assignment.

PubMed

Alves, Gelio; Yu, Yi-Kuo

2015-03-01

Assigning statistical significance accurately has become increasingly important as metadata of many types, often assembled in hierarchies, are constructed and combined for further biological analyses. Statistical inaccuracy of metadata at any level may propagate to downstream analyses, undermining the validity of scientific conclusions thus drawn. From the perspective of mass spectrometry-based proteomics, even though accurate statistics for peptide identification can now be achieved, accurate protein level statistics remain challenging. We have constructed a protein ID method that combines peptide evidences of a candidate protein based on a rigorous formula derived earlier; in this formula the database P-value of every peptide is weighted, prior to the final combination, according to the number of proteins it maps to. We have also shown that this protein ID method provides accurate protein level E-value, eliminating the need of using empirical post-processing methods for type-I error control. Using a known protein mixture, we find that this protein ID method, when combined with the Sorić formula, yields accurate values for the proportion of false discoveries. In terms of retrieval efficacy, the results from our method are comparable with other methods tested. The source code, implemented in C++ on a linux system, is available for download at ftp://ftp.ncbi.nlm.nih.gov/pub/qmbp/qmbp_ms/RAId/RAId_Linux_64Bit. Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

Brightness temperature and attenuation diversity statistics at 20.6 and 31.65 GHz for the Colorado Research Network

NASA Technical Reports Server (NTRS)

Westwater, Ed R.; Falls, M. J.; Fionda, E.

1992-01-01

A limited network of four dual-channel microwave radiometers, with frequencies of 20.6 and 31.65 GHz, was operated in the front range of eastern Colorado from 1985 to 1988. Data, from November 1987 through October 1988 are analyzed to determine both single-station and joint-station brightness temperature and attenuation statistics. Only zenith observations were made. The spatial separations of the stations varied from 50 km to 190 km. Before the statistics were developed, the data were screened by rigorous quality control methods. One such method, that of 20.6 vs. 31.65 GHz scatter plots, is analyzed in detail, and comparisons are made of measured vs calculated data. At 20.6 and 31.65 GHz, vertical attenuations of 5 and 8 dB are exceeded 0.01 percent of the time. For these four stations and at the same 0.01 percent level, diversity gains from 6 to 8 dB are possible with the 50 to 190 km separations.

Demodulation of messages received with low signal to noise ratio

NASA Astrophysics Data System (ADS)

Marguinaud, A.; Quignon, T.; Romann, B.

The implementation of this all-digital demodulator is derived from maximum likelihood considerations applied to an analytical representation of the received signal. Traditional adapted filters and phase lock loops are replaced by minimum variance estimators and hypothesis tests. These statistical tests become very simple when working on phase signal. These methods, combined with rigorous control data representation allow significant computation savings as compared to conventional realizations. Nominal operation has been verified down to energetic signal over noise of -3 dB upon a QPSK demodulator.

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-cloud Aerosols over Ocean Using CALIOP and MODIS Data

NASA Technical Reports Server (NTRS)

Zhang, Z.; Meyer, K.; Platnick, S.; Oreopoulos, L.; Lee, D.; Yu, H.

2013-01-01

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4%. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

NASA Technical Reports Server (NTRS)

Zhang, Z.; Meyer, K.; Platnick, S.; Oreopoulos, L.; Lee, D.; Yu, H.

2014-01-01

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds.

Rigorous Statistical Bounds in Uncertainty Quantification for One-Layer Turbulent Geophysical Flows

NASA Astrophysics Data System (ADS)

Qi, Di; Majda, Andrew J.

2018-04-01

Statistical bounds controlling the total fluctuations in mean and variance about a basic steady-state solution are developed for the truncated barotropic flow over topography. Statistical ensemble prediction is an important topic in weather and climate research. Here, the evolution of an ensemble of trajectories is considered using statistical instability analysis and is compared and contrasted with the classical deterministic instability for the growth of perturbations in one pointwise trajectory. The maximum growth of the total statistics in fluctuations is derived relying on the statistical conservation principle of the pseudo-energy. The saturation bound of the statistical mean fluctuation and variance in the unstable regimes with non-positive-definite pseudo-energy is achieved by linking with a class of stable reference states and minimizing the stable statistical energy. Two cases with dependence on initial statistical uncertainty and on external forcing and dissipation are compared and unified under a consistent statistical stability framework. The flow structures and statistical stability bounds are illustrated and verified by numerical simulations among a wide range of dynamical regimes, where subtle transient statistical instability exists in general with positive short-time exponential growth in the covariance even when the pseudo-energy is positive-definite. Among the various scenarios in this paper, there exist strong forward and backward energy exchanges between different scales which are estimated by the rigorous statistical bounds.

The 1,5-H-shift in 1-butoxy: A case study in the rigorous implementation of transition state theory for a multirotamer system

NASA Astrophysics Data System (ADS)

Vereecken, Luc; Peeters, Jozef

2003-09-01

The rigorous implementation of transition state theory (TST) for a reaction system with multiple reactant rotamers and multiple transition state conformers is discussed by way of a statistical rate analysis of the 1,5-H-shift in 1-butoxy radicals, a prototype reaction for the important class of H-shift reactions in atmospheric chemistry. Several approaches for deriving a multirotamer TST expression are treated: oscillator versus (hindered) internal rotor models; distinguishable versus indistinguishable atoms; and direct count methods versus degeneracy factors calculated by (simplified) direct count methods or from symmetry numbers and number of enantiomers, where applicable. It is shown that the various treatments are fully consistent, even if the TST expressions themselves appear different. The 1-butoxy H-shift reaction is characterized quantum chemically using B3LYP-DFT; the performance of this level of theory is compared to other methods. Rigorous application of the multirotamer TST methodology in an harmonic oscillator approximation based on this data yields a rate coefficient of k(298 K,1 atm)=1.4×105 s-1, and an Arrhenius expression k(T,1 atm)=1.43×1011 exp(-8.17 kcal mol-1/RT) s-1, which both closely match the experimental recommendations in the literature. The T-dependence is substantially influenced by the multirotamer treatment, as well as by the tunneling and fall-off corrections. The present results are compared to those of simplified TST calculations based solely on the properties of the lowest energy 1-butoxy rotamer.

Trends in Study Methods Used in Undergraduate Medical Education Research, 1969–2007

PubMed Central

Baernstein, Amy; Liss, Hillary K.; Carney, Patricia A.; Elmore, Joann G.

2011-01-01

Context Evidence-based medical education requires rigorous studies appraising educational efficacy. Objectives To assess trends over time in methods used to evaluate undergraduate medical education interventions and to identify whether participation of medical education departments or centers is associated with more rigorous methods. Data Sources The PubMed, Cochrane Controlled Trials Registry, Campbell Collaboration, and ERIC databases (January 1966–March 2007) were searched using terms equivalent to students, medical and education, medical crossed with all relevant study designs. Study Selection We selected publications in all languages from every fifth year, plus the most recent 12 months, that evaluated an educational intervention for undergraduate medical students. Four hundred seventy-two publications met criteria for review. Data Extraction Data were abstracted on number of participants; types of comparison groups; whether outcomes assessed were objective, subjective, and/or validated; timing of outcome assessments; funding; and participation of medical education departments and centers. Ten percent of publications were independently abstracted by 2 authors to assess validity of the data abstraction. Results The annual number of publications increased over time from 1 (1969–1970) to 147 (2006–2007). In the most recent year, there was a mean of 145 medical student participants; 9 (6%) recruited participants from multiple institutions; 80 (54%) used comparison groups; 37 (25%) used randomized control groups; 91 (62%) had objective outcomes; 23 (16%) had validated outcomes; 35 (24%) assessed an outcome more than 1 month later; 21 (14%) estimated statistical power; and 66 (45%) reported funding. In 2006–2007, medical education department or center participation, reported in 46 (31%) of the recent publications, was associated only with enrolling more medical student participants (P = .04); for all studies from 1969 to 2007, it was associated only with measuring an objective outcome (P = .048). Between 1969 and 2007, the percentage of publications reporting statistical power and funding increased; percentages did not change for other study features. Conclusions The annual number of published studies of undergraduate medical education interventions demonstrating methodological rigor has been increasing. However, considerable opportunities for improvement remain. PMID:17785648

Efficient kinetic Monte Carlo method for reaction-diffusion problems with spatially varying annihilation rates

NASA Astrophysics Data System (ADS)

Schwarz, Karsten; Rieger, Heiko

2013-03-01

We present an efficient Monte Carlo method to simulate reaction-diffusion processes with spatially varying particle annihilation or transformation rates as it occurs for instance in the context of motor-driven intracellular transport. Like Green's function reaction dynamics and first-passage time methods, our algorithm avoids small diffusive hops by propagating sufficiently distant particles in large hops to the boundaries of protective domains. Since for spatially varying annihilation or transformation rates the single particle diffusion propagator is not known analytically, we present an algorithm that generates efficiently either particle displacements or annihilations with the correct statistics, as we prove rigorously. The numerical efficiency of the algorithm is demonstrated with an illustrative example.

Dealing with missing standard deviation and mean values in meta-analysis of continuous outcomes: a systematic review.

PubMed

Weir, Christopher J; Butcher, Isabella; Assi, Valentina; Lewis, Stephanie C; Murray, Gordon D; Langhorne, Peter; Brady, Marian C

2018-03-07

Rigorous, informative meta-analyses rely on availability of appropriate summary statistics or individual participant data. For continuous outcomes, especially those with naturally skewed distributions, summary information on the mean or variability often goes unreported. While full reporting of original trial data is the ideal, we sought to identify methods for handling unreported mean or variability summary statistics in meta-analysis. We undertook two systematic literature reviews to identify methodological approaches used to deal with missing mean or variability summary statistics. Five electronic databases were searched, in addition to the Cochrane Colloquium abstract books and the Cochrane Statistics Methods Group mailing list archive. We also conducted cited reference searching and emailed topic experts to identify recent methodological developments. Details recorded included the description of the method, the information required to implement the method, any underlying assumptions and whether the method could be readily applied in standard statistical software. We provided a summary description of the methods identified, illustrating selected methods in example meta-analysis scenarios. For missing standard deviations (SDs), following screening of 503 articles, fifteen methods were identified in addition to those reported in a previous review. These included Bayesian hierarchical modelling at the meta-analysis level; summary statistic level imputation based on observed SD values from other trials in the meta-analysis; a practical approximation based on the range; and algebraic estimation of the SD based on other summary statistics. Following screening of 1124 articles for methods estimating the mean, one approximate Bayesian computation approach and three papers based on alternative summary statistics were identified. Illustrative meta-analyses showed that when replacing a missing SD the approximation using the range minimised loss of precision and generally performed better than omitting trials. When estimating missing means, a formula using the median, lower quartile and upper quartile performed best in preserving the precision of the meta-analysis findings, although in some scenarios, omitting trials gave superior results. Methods based on summary statistics (minimum, maximum, lower quartile, upper quartile, median) reported in the literature facilitate more comprehensive inclusion of randomised controlled trials with missing mean or variability summary statistics within meta-analyses.

Orbital State Uncertainty Realism

NASA Astrophysics Data System (ADS)

Horwood, J.; Poore, A. B.

2012-09-01

Fundamental to the success of the space situational awareness (SSA) mission is the rigorous inclusion of uncertainty in the space surveillance network. The *proper characterization of uncertainty* in the orbital state of a space object is a common requirement to many SSA functions including tracking and data association, resolution of uncorrelated tracks (UCTs), conjunction analysis and probability of collision, sensor resource management, and anomaly detection. While tracking environments, such as air and missile defense, make extensive use of Gaussian and local linearity assumptions within algorithms for uncertainty management, space surveillance is inherently different due to long time gaps between updates, high misdetection rates, nonlinear and non-conservative dynamics, and non-Gaussian phenomena. The latter implies that "covariance realism" is not always sufficient. SSA also requires "uncertainty realism"; the proper characterization of both the state and covariance and all non-zero higher-order cumulants. In other words, a proper characterization of a space object's full state *probability density function (PDF)* is required. In order to provide a more statistically rigorous treatment of uncertainty in the space surveillance tracking environment and to better support the aforementioned SSA functions, a new class of multivariate PDFs are formulated which more accurately characterize the uncertainty of a space object's state or orbit. The new distribution contains a parameter set controlling the higher-order cumulants which gives the level sets a distinctive "banana" or "boomerang" shape and degenerates to a Gaussian in a suitable limit. Using the new class of PDFs within the general Bayesian nonlinear filter, the resulting filter prediction step (i.e., uncertainty propagation) is shown to have the *same computational cost as the traditional unscented Kalman filter* with the former able to maintain a proper characterization of the uncertainty for up to *ten times as long* as the latter. The filter correction step also furnishes a statistically rigorous *prediction error* which appears in the likelihood ratios for scoring the association of one report or observation to another. Thus, the new filter can be used to support multi-target tracking within a general multiple hypothesis tracking framework. Additionally, the new distribution admits a distance metric which extends the classical Mahalanobis distance (chi^2 statistic). This metric provides a test for statistical significance and facilitates single-frame data association methods with the potential to easily extend the covariance-based track association algorithm of Hill, Sabol, and Alfriend. The filtering, data fusion, and association methods using the new class of orbital state PDFs are shown to be mathematically tractable and operationally viable.

A methodology for the rigorous verification of plasma simulation codes

NASA Astrophysics Data System (ADS)

Riva, Fabio

2016-10-01

The methodology used to assess the reliability of numerical simulation codes constitutes the Verification and Validation (V&V) procedure. V&V is composed by two separate tasks: the verification, which is a mathematical issue targeted to assess that the physical model is correctly solved, and the validation, which determines the consistency of the code results, and therefore of the physical model, with experimental data. In the present talk we focus our attention on the verification, which in turn is composed by the code verification, targeted to assess that a physical model is correctly implemented in a simulation code, and the solution verification, that quantifies the numerical error affecting a simulation. Bridging the gap between plasma physics and other scientific domains, we introduced for the first time in our domain a rigorous methodology for the code verification, based on the method of manufactured solutions, as well as a solution verification based on the Richardson extrapolation. This methodology was applied to GBS, a three-dimensional fluid code based on a finite difference scheme, used to investigate the plasma turbulence in basic plasma physics experiments and in the tokamak scrape-off layer. Overcoming the difficulty of dealing with a numerical method intrinsically affected by statistical noise, we have now generalized the rigorous verification methodology to simulation codes based on the particle-in-cell algorithm, which are employed to solve Vlasov equation in the investigation of a number of plasma physics phenomena.

Parameter inference in small world network disease models with approximate Bayesian Computational methods

NASA Astrophysics Data System (ADS)

Walker, David M.; Allingham, David; Lee, Heung Wing Joseph; Small, Michael

2010-02-01

Small world network models have been effective in capturing the variable behaviour of reported case data of the SARS coronavirus outbreak in Hong Kong during 2003. Simulations of these models have previously been realized using informed “guesses” of the proposed model parameters and tested for consistency with the reported data by surrogate analysis. In this paper we attempt to provide statistically rigorous parameter distributions using Approximate Bayesian Computation sampling methods. We find that such sampling schemes are a useful framework for fitting parameters of stochastic small world network models where simulation of the system is straightforward but expressing a likelihood is cumbersome.

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.

Big data uncertainties.

PubMed

Maugis, Pierre-André G

2018-07-01

Big data-the idea that an always-larger volume of information is being constantly recorded-suggests that new problems can now be subjected to scientific scrutiny. However, can classical statistical methods be used directly on big data? We analyze the problem by looking at two known pitfalls of big datasets. First, that they are biased, in the sense that they do not offer a complete view of the populations under consideration. Second, that they present a weak but pervasive level of dependence between all their components. In both cases we observe that the uncertainty of the conclusion obtained by statistical methods is increased when used on big data, either because of a systematic error (bias), or because of a larger degree of randomness (increased variance). We argue that the key challenge raised by big data is not only how to use big data to tackle new problems, but to develop tools and methods able to rigorously articulate the new risks therein. Copyright © 2016. Published by Elsevier Ltd.

Improvement of IFNγ ELISPOT Performance Following Overnight Resting of Frozen PBMC Samples Confirmed Through Rigorous Statistical Analysis

PubMed Central

Santos, Radleigh; Buying, Alcinette; Sabri, Nazila; Yu, John; Gringeri, Anthony; Bender, James; Janetzki, Sylvia; Pinilla, Clemencia; Judkowski, Valeria A.

2014-01-01

Immune monitoring of functional responses is a fundamental parameter to establish correlates of protection in clinical trials evaluating vaccines and therapies to boost antigen-specific responses. The IFNγ ELISPOT assay is a well-standardized and validated method for the determination of functional IFNγ-producing T-cells in peripheral blood mononuclear cells (PBMC); however, its performance greatly depends on the quality and integrity of the cryopreserved PBMC. Here, we investigate the effect of overnight (ON) resting of the PBMC on the detection of CD8-restricted peptide-specific responses by IFNγ ELISPOT. The study used PBMC from healthy donors to evaluate the CD8 T-cell response to five pooled or individual HLA-A2 viral peptides. The results were analyzed using a modification of the existing distribution free resampling (DFR) recommended for the analysis of ELISPOT data to ensure the most rigorous possible standard of significance. The results of the study demonstrate that ON resting of PBMC samples prior to IFNγ ELISPOT increases both the magnitude and the statistical significance of the responses. In addition, a comparison of the results with a 13-day preculture of PBMC with the peptides before testing demonstrates that ON resting is sufficient for the efficient evaluation of immune functioning. PMID:25546016

First Monte Carlo analysis of fragmentation functions from single-inclusive e + e - annihilation

DOE PAGES

Sato, Nobuo; Ethier, J. J.; Melnitchouk, W.; ...

2016-12-02

Here, we perform the first iterative Monte Carlo (IMC) analysis of fragmentation functions constrained by all available data from single-inclusive $e^+ e^-$ annihilation into pions and kaons. The IMC method eliminates potential bias in traditional analyses based on single fits introduced by fixing parameters not well contrained by the data, and provides a statistically rigorous determination of uncertainties. Our analysis reveals specific features of fragmentation functions using the new IMC methodology and those obtained from previous analyses, especially for light quarks and for strange quark fragmentation to kaons.

Cancer Imaging Phenomics Software Suite: Application to Brain and Breast Cancer | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

The transition of oncologic imaging from its “industrial era” to it is “information era” demands analytical methods that 1) extract information from this data that is clinically and biologically relevant; 2) integrate imaging, clinical, and genomic data via rigorous statistical and computational methodologies in order to derive models valuable for understanding cancer mechanisms, diagnosis, prognostic assessment, response evaluation, and personalized treatment management; 3) are available to the biomedical community for easy use and application, with the aim of understanding, diagnosing, an

Clopper-Pearson bounds from HEP data cuts

NASA Astrophysics Data System (ADS)

Berg, B. A.

2001-08-01

For the measurement of Ns signals in N events rigorous confidence bounds on the true signal probability pexact were established in a classical paper by Clopper and Pearson [Biometrica 26, 404 (1934)]. Here, their bounds are generalized to the HEP situation where cuts on the data tag signals with probability Ps and background data with likelihood Pb

Developing methods for systematic reviewing in health services delivery and organization: an example from a review of access to health care for people with learning disabilities. Part 2. Evaluation of the literature--a practical guide.

PubMed

Alborz, Alison; McNally, Rosalind

2004-12-01

To develop methods to facilitate the 'systematic' review of evidence from a range of methodologies on diffuse or 'soft' topics, as exemplified by 'access to health care'. Twenty-eight bibliographic databases, research registers, organizational websites or library catalogues. Reference lists from identified studies. Contact with experts and service users. Current awareness and contents alerting services in the area of learning disabilities. Inclusion criteria were English language literature from 1980 onwards, relating to people with learning disabilities of any age and all study designs. The main criteria for assessment was relevance to Guillifords' model of access to health care which was adapted to the circumstances of people with learning disabilities. Selected studies were evaluated for scientific rigour then data was extracted and the results synthesized. Quality assessment was by an initial set of 'generic' quality indicators. This enabled further evidence selection before evaluation of findings according to specific criteria for qualitative, quantitative or mixed-method studies. Eighty-two studies were fully evaluated. Five studies were rated 'highly rigorous', 22 'rigorous', 46 'less rigorous' and nine 'poor' papers were retained as the sole evidence covering aspects of the guiding model. The majority of studies were quantitative but used only descriptive statistics. Most evidence lacked methodological detail, which often lowered final quality ratings. The application of a consistent structure to quality evaluation can facilitate data appraisal, extraction and synthesis across a range of methodologies in diffuse or 'soft' topics. Synthesis can be facilitated further by using software, such as the microsoft 'access' database, for managing information.

irGPU.proton.Net: Irregular strong charge interaction networks of protonatable groups in protein molecules--a GPU solver using the fast multipole method and statistical thermodynamics.

PubMed

Kantardjiev, Alexander A

2015-04-05

A cluster of strongly interacting ionization groups in protein molecules with irregular ionization behavior is suggestive for specific structure-function relationship. However, their computational treatment is unconventional (e.g., lack of convergence in naive self-consistent iterative algorithm). The stringent evaluation requires evaluation of Boltzmann averaged statistical mechanics sums and electrostatic energy estimation for each microstate. irGPU: Irregular strong interactions in proteins--a GPU solver is novel solution to a versatile problem in protein biophysics--atypical protonation behavior of coupled groups. The computational severity of the problem is alleviated by parallelization (via GPU kernels) which is applied for the electrostatic interaction evaluation (including explicit electrostatics via the fast multipole method) as well as statistical mechanics sums (partition function) estimation. Special attention is given to the ease of the service and encapsulation of theoretical details without sacrificing rigor of computational procedures. irGPU is not just a solution-in-principle but a promising practical application with potential to entice community into deeper understanding of principles governing biomolecule mechanisms. © 2015 Wiley Periodicals, Inc.

Double-survey estimates of bald eagle populations in Oregon

USGS Publications Warehouse

Anthony, R.G.; Garrett, Monte G.; Isaacs, F.B.

1999-01-01

The literature on abundance of birds of prey is almost devoid of population estimates with statistical rigor. Therefore, we surveyed bald eagle (Haliaeetus leucocephalus) populations on the Crooked and lower Columbia rivers of Oregon and used the double-survey method to estimate populations and sighting probabilities for different survey methods (aerial, boat, vehicle) and bald eagle ages (adults vs. subadults). Sighting probabilities were consistently 20%. The results revealed variable and negative bias (percent relative bias = -9 to -70%) of direct counts and emphasized the importance of estimating populations where some measure of precision and ability to conduct inference tests are available. We recommend use of the double-survey method to estimate abundance of bald eagle populations and other raptors in open habitats.

Statistical testing and power analysis for brain-wide association study.

PubMed

Gong, Weikang; Wan, Lin; Lu, Wenlian; Ma, Liang; Cheng, Fan; Cheng, Wei; Grünewald, Stefan; Feng, Jianfeng

2018-04-05

The identification of connexel-wise associations, which involves examining functional connectivities between pairwise voxels across the whole brain, is both statistically and computationally challenging. Although such a connexel-wise methodology has recently been adopted by brain-wide association studies (BWAS) to identify connectivity changes in several mental disorders, such as schizophrenia, autism and depression, the multiple correction and power analysis methods designed specifically for connexel-wise analysis are still lacking. Therefore, we herein report the development of a rigorous statistical framework for connexel-wise significance testing based on the Gaussian random field theory. It includes controlling the family-wise error rate (FWER) of multiple hypothesis testings using topological inference methods, and calculating power and sample size for a connexel-wise study. Our theoretical framework can control the false-positive rate accurately, as validated empirically using two resting-state fMRI datasets. Compared with Bonferroni correction and false discovery rate (FDR), it can reduce false-positive rate and increase statistical power by appropriately utilizing the spatial information of fMRI data. Importantly, our method bypasses the need of non-parametric permutation to correct for multiple comparison, thus, it can efficiently tackle large datasets with high resolution fMRI images. The utility of our method is shown in a case-control study. Our approach can identify altered functional connectivities in a major depression disorder dataset, whereas existing methods fail. A software package is available at https://github.com/weikanggong/BWAS. Copyright © 2018 Elsevier B.V. All rights reserved.

Scalable privacy-preserving data sharing methodology for genome-wide association studies.

PubMed

Yu, Fei; Fienberg, Stephen E; Slavković, Aleksandra B; Uhler, Caroline

2014-08-01

The protection of privacy of individual-level information in genome-wide association study (GWAS) databases has been a major concern of researchers following the publication of "an attack" on GWAS data by Homer et al. (2008). Traditional statistical methods for confidentiality and privacy protection of statistical databases do not scale well to deal with GWAS data, especially in terms of guarantees regarding protection from linkage to external information. The more recent concept of differential privacy, introduced by the cryptographic community, is an approach that provides a rigorous definition of privacy with meaningful privacy guarantees in the presence of arbitrary external information, although the guarantees may come at a serious price in terms of data utility. Building on such notions, Uhler et al. (2013) proposed new methods to release aggregate GWAS data without compromising an individual's privacy. We extend the methods developed in Uhler et al. (2013) for releasing differentially-private χ(2)-statistics by allowing for arbitrary number of cases and controls, and for releasing differentially-private allelic test statistics. We also provide a new interpretation by assuming the controls' data are known, which is a realistic assumption because some GWAS use publicly available data as controls. We assess the performance of the proposed methods through a risk-utility analysis on a real data set consisting of DNA samples collected by the Wellcome Trust Case Control Consortium and compare the methods with the differentially-private release mechanism proposed by Johnson and Shmatikov (2013). Copyright © 2014 Elsevier Inc. All rights reserved.

Distinguishing cause from correlation in tokamak experiments to trigger edge-localised plasma instabilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Webster, Anthony J.; CCFE, Culham Science Centre, Abingdon OX14 3DB

2014-11-15

The generic question is considered: How can we determine the probability of an otherwise quasi-random event, having been triggered by an external influence? A specific problem is the quantification of the success of techniques to trigger, and hence control, edge-localised plasma instabilities (ELMs) in magnetically confined fusion (MCF) experiments. The development of such techniques is essential to ensure tolerable heat loads on components in large MCF fusion devices, and is necessary for their development into economically successful power plants. Bayesian probability theory is used to rigorously formulate the problem and to provide a formal solution. Accurate but pragmatic methods aremore » developed to estimate triggering probabilities, and are illustrated with experimental data. These allow results from experiments to be quantitatively assessed, and rigorously quantified conclusions to be formed. Example applications include assessing whether triggering of ELMs is a statistical or deterministic process, and the establishment of thresholds to ensure that ELMs are reliably triggered.« less

Robust source and mask optimization compensating for mask topography effects in computational lithography.

PubMed

Li, Jia; Lam, Edmund Y

2014-04-21

Mask topography effects need to be taken into consideration for a more accurate solution of source mask optimization (SMO) in advanced optical lithography. However, rigorous 3D mask models generally involve intensive computation and conventional SMO fails to manipulate the mask-induced undesired phase errors that degrade the usable depth of focus (uDOF) and process yield. In this work, an optimization approach incorporating pupil wavefront aberrations into SMO procedure is developed as an alternative to maximize the uDOF. We first design the pupil wavefront function by adding primary and secondary spherical aberrations through the coefficients of the Zernike polynomials, and then apply the conjugate gradient method to achieve an optimal source-mask pair under the condition of aberrated pupil. We also use a statistical model to determine the Zernike coefficients for the phase control and adjustment. Rigorous simulations of thick masks show that this approach provides compensation for mask topography effects by improving the pattern fidelity and increasing uDOF.

TREATMENT SWITCHING: STATISTICAL AND DECISION-MAKING CHALLENGES AND APPROACHES.

PubMed

Latimer, Nicholas R; Henshall, Chris; Siebert, Uwe; Bell, Helen

2016-01-01

Treatment switching refers to the situation in a randomized controlled trial where patients switch from their randomly assigned treatment onto an alternative. Often, switching is from the control group onto the experimental treatment. In this instance, a standard intention-to-treat analysis does not identify the true comparative effectiveness of the treatments under investigation. We aim to describe statistical methods for adjusting for treatment switching in a comprehensible way for nonstatisticians, and to summarize views on these methods expressed by stakeholders at the 2014 Adelaide International Workshop on Treatment Switching in Clinical Trials. We describe three statistical methods used to adjust for treatment switching: marginal structural models, two-stage adjustment, and rank preserving structural failure time models. We draw upon discussion heard at the Adelaide International Workshop to explore the views of stakeholders on the acceptability of these methods. Stakeholders noted that adjustment methods are based on assumptions, the validity of which may often be questionable. There was disagreement on the acceptability of adjustment methods, but consensus that when these are used, they should be justified rigorously. The utility of adjustment methods depends upon the decision being made and the processes used by the decision-maker. Treatment switching makes estimating the true comparative effect of a new treatment challenging. However, many decision-makers have reservations with adjustment methods. These, and how they affect the utility of adjustment methods, require further exploration. Further technical work is required to develop adjustment methods to meet real world needs, to enhance their acceptability to decision-makers.

GIA Model Statistics for GRACE Hydrology, Cryosphere, and Ocean Science

NASA Astrophysics Data System (ADS)

Caron, L.; Ivins, E. R.; Larour, E.; Adhikari, S.; Nilsson, J.; Blewitt, G.

2018-03-01

We provide a new analysis of glacial isostatic adjustment (GIA) with the goal of assembling the model uncertainty statistics required for rigorously extracting trends in surface mass from the Gravity Recovery and Climate Experiment (GRACE) mission. Such statistics are essential for deciphering sea level, ocean mass, and hydrological changes because the latter signals can be relatively small (≤2 mm/yr water height equivalent) over very large regions, such as major ocean basins and watersheds. With abundant new >7 year continuous measurements of vertical land motion (VLM) reported by Global Positioning System stations on bedrock and new relative sea level records, our new statistical evaluation of GIA uncertainties incorporates Bayesian methodologies. A unique aspect of the method is that both the ice history and 1-D Earth structure vary through a total of 128,000 forward models. We find that best fit models poorly capture the statistical inferences needed to correctly invert for lower mantle viscosity and that GIA uncertainty exceeds the uncertainty ascribed to trends from 14 years of GRACE data in polar regions.

Designing a mixed methods study in primary care.

PubMed

Creswell, John W; Fetters, Michael D; Ivankova, Nataliya V

2004-01-01

Mixed methods or multimethod research holds potential for rigorous, methodologically sound investigations in primary care. The objective of this study was to use criteria from the literature to evaluate 5 mixed methods studies in primary care and to advance 3 models useful for designing such investigations. We first identified criteria from the social and behavioral sciences to analyze mixed methods studies in primary care research. We then used the criteria to evaluate 5 mixed methods investigations published in primary care research journals. Of the 5 studies analyzed, 3 included a rationale for mixing based on the need to develop a quantitative instrument from qualitative data or to converge information to best understand the research topic. Quantitative data collection involved structured interviews, observational checklists, and chart audits that were analyzed using descriptive and inferential statistical procedures. Qualitative data consisted of semistructured interviews and field observations that were analyzed using coding to develop themes and categories. The studies showed diverse forms of priority: equal priority, qualitative priority, and quantitative priority. Data collection involved quantitative and qualitative data gathered both concurrently and sequentially. The integration of the quantitative and qualitative data in these studies occurred between data analysis from one phase and data collection from a subsequent phase, while analyzing the data, and when reporting the results. We recommend instrument-building, triangulation, and data transformation models for mixed methods designs as useful frameworks to add rigor to investigations in primary care. We also discuss the limitations of our study and the need for future research.

Quality Reporting of Multivariable Regression Models in Observational Studies: Review of a Representative Sample of Articles Published in Biomedical Journals.

PubMed

Real, Jordi; Forné, Carles; Roso-Llorach, Albert; Martínez-Sánchez, Jose M

2016-05-01

Controlling for confounders is a crucial step in analytical observational studies, and multivariable models are widely used as statistical adjustment techniques. However, the validation of the assumptions of the multivariable regression models (MRMs) should be made clear in scientific reporting. The objective of this study is to review the quality of statistical reporting of the most commonly used MRMs (logistic, linear, and Cox regression) that were applied in analytical observational studies published between 2003 and 2014 by journals indexed in MEDLINE.Review of a representative sample of articles indexed in MEDLINE (n = 428) with observational design and use of MRMs (logistic, linear, and Cox regression). We assessed the quality of reporting about: model assumptions and goodness-of-fit, interactions, sensitivity analysis, crude and adjusted effect estimate, and specification of more than 1 adjusted model.The tests of underlying assumptions or goodness-of-fit of the MRMs used were described in 26.2% (95% CI: 22.0-30.3) of the articles and 18.5% (95% CI: 14.8-22.1) reported the interaction analysis. Reporting of all items assessed was higher in articles published in journals with a higher impact factor.A low percentage of articles indexed in MEDLINE that used multivariable techniques provided information demonstrating rigorous application of the model selected as an adjustment method. Given the importance of these methods to the final results and conclusions of observational studies, greater rigor is required in reporting the use of MRMs in the scientific literature.

Statistical Analyses Comparing Prismatic Magnetite Crystals in ALH84001 Carbonate Globules with those from the Terrestrial Magnetotactic Bacteria Strain MV-1

NASA Technical Reports Server (NTRS)

Thomas-Keprta, Kathie L.; Clemett, Simon J.; Bazylinski, Dennis A.; Kirschvink, Joseph L.; McKay, David S.; Wentworth, Susan J.; Vali, H.; Gibson, Everett K.

2000-01-01

Here we use rigorous mathematical modeling to compare ALH84001 prismatic magnetites with those produced by terrestrial magnetotactic bacteria, MV-1. We find that this subset of the Martian magnetites appears to be statistically indistinguishable from those of MV-1.

A CUMULATIVE MIGRATION METHOD FOR COMPUTING RIGOROUS TRANSPORT CROSS SECTIONS AND DIFFUSION COEFFICIENTS FOR LWR LATTICES WITH MONTE CARLO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhaoyuan Liu; Kord Smith; Benoit Forget

2016-05-01

A new method for computing homogenized assembly neutron transport cross sections and dif- fusion coefficients that is both rigorous and computationally efficient is proposed in this paper. In the limit of a homogeneous hydrogen slab, the new method is equivalent to the long-used, and only-recently-published CASMO transport method. The rigorous method is used to demonstrate the sources of inaccuracy in the commonly applied “out-scatter” transport correction. It is also demonstrated that the newly developed method is directly applicable to lattice calculations per- formed by Monte Carlo and is capable of computing rigorous homogenized transport cross sections for arbitrarily heterogeneous lattices.more » Comparisons of several common transport cross section ap- proximations are presented for a simple problem of infinite medium hydrogen. The new method has also been applied in computing 2-group diffusion data for an actual PWR lattice from BEAVRS benchmark.« less

Preserving pre-rigor meat functionality for beef patty production.

PubMed

Claus, J R; Sørheim, O

2006-06-01

Three methods were examined for preserving pre-rigor meat functionality in beef patties. Hot-boned semimembranosus muscles were processed as follows: (1) pre-rigor ground, salted, patties immediately cooked; (2) pre-rigor ground, salted and stored overnight; (3) pre-rigor injected with brine; and (4) post-rigor ground and salted. Raw patties contained 60% lean beef, 19.7% beef fat trim, 1.7% NaCl, 3.6% starch, and 15% water. Pre-rigor processing occurred at 3-3.5h postmortem. Patties made from pre-rigor ground meat had higher pH values; greater protein solubility; firmer, more cohesive, and chewier texture; and substantially lower cooking losses than the other treatments. Addition of salt was sufficient to reduce the rate and extent of glycolysis. Brine injection of intact pre-rigor muscles resulted in some preservation of the functional properties but not as pronounced as with salt addition to pre-rigor ground meat.

Local and global approaches to the problem of Poincaré recurrences. Applications in nonlinear dynamics

NASA Astrophysics Data System (ADS)

Anishchenko, V. S.; Boev, Ya. I.; Semenova, N. I.; Strelkova, G. I.

2015-07-01

We review rigorous and numerical results on the statistics of Poincaré recurrences which are related to the modern development of the Poincaré recurrence problem. We analyze and describe the rigorous results which are achieved both in the classical (local) approach and in the recently developed global approach. These results are illustrated by numerical simulation data for simple chaotic and ergodic systems. It is shown that the basic theoretical laws can be applied to noisy systems if the probability measure is ergodic and stationary. Poincaré recurrences are studied numerically in nonautonomous systems. Statistical characteristics of recurrences are analyzed in the framework of the global approach for the cases of positive and zero topological entropy. We show that for the positive entropy, there is a relationship between the Afraimovich-Pesin dimension, Lyapunov exponents and the Kolmogorov-Sinai entropy either without and in the presence of external noise. The case of zero topological entropy is exemplified by numerical results for the Poincare recurrence statistics in the circle map. We show and prove that the dependence of minimal recurrence times on the return region size demonstrates universal properties for the golden and the silver ratio. The behavior of Poincaré recurrences is analyzed at the critical point of Feigenbaum attractor birth. We explore Poincaré recurrences for an ergodic set which is generated in the stroboscopic section of a nonautonomous oscillator and is similar to a circle shift. Based on the obtained results we show how the Poincaré recurrence statistics can be applied for solving a number of nonlinear dynamics issues. We propose and illustrate alternative methods for diagnosing effects of external and mutual synchronization of chaotic systems in the context of the local and global approaches. The properties of the recurrence time probability density can be used to detect the stochastic resonance phenomenon. We also discuss how the fractal dimension of chaotic attractors can be estimated using the Poincaré recurrence statistics.

Statistical hydrodynamics and related problems in spaces of probability measures

NASA Astrophysics Data System (ADS)

Dostoglou, Stamatios

2017-11-01

A rigorous theory of statistical solutions of the Navier-Stokes equations, suitable for exploring Kolmogorov's ideas, has been developed by M.I. Vishik and A.V. Fursikov, culminating in their monograph "Mathematical problems of Statistical Hydromechanics." We review some progress made in recent years following this approach, with emphasis on problems concerning the correlation of velocities and corresponding questions in the space of probability measures on Hilbert spaces.

Quantum theory of multiscale coarse-graining.

PubMed

Han, Yining; Jin, Jaehyeok; Wagner, Jacob W; Voth, Gregory A

2018-03-14

Coarse-grained (CG) models serve as a powerful tool to simulate molecular systems at much longer temporal and spatial scales. Previously, CG models and methods have been built upon classical statistical mechanics. The present paper develops a theory and numerical methodology for coarse-graining in quantum statistical mechanics, by generalizing the multiscale coarse-graining (MS-CG) method to quantum Boltzmann statistics. A rigorous derivation of the sufficient thermodynamic consistency condition is first presented via imaginary time Feynman path integrals. It identifies the optimal choice of CG action functional and effective quantum CG (qCG) force field to generate a quantum MS-CG (qMS-CG) description of the equilibrium system that is consistent with the quantum fine-grained model projected onto the CG variables. A variational principle then provides a class of algorithms for optimally approximating the qMS-CG force fields. Specifically, a variational method based on force matching, which was also adopted in the classical MS-CG theory, is generalized to quantum Boltzmann statistics. The qMS-CG numerical algorithms and practical issues in implementing this variational minimization procedure are also discussed. Then, two numerical examples are presented to demonstrate the method. Finally, as an alternative strategy, a quasi-classical approximation for the thermal density matrix expressed in the CG variables is derived. This approach provides an interesting physical picture for coarse-graining in quantum Boltzmann statistical mechanics in which the consistency with the quantum particle delocalization is obviously manifest, and it opens up an avenue for using path integral centroid-based effective classical force fields in a coarse-graining methodology.

Tenderness of pre- and post rigor lamb longissimus muscle.

PubMed

Geesink, Geert; Sujang, Sadi; Koohmaraie, Mohammad

2011-08-01

Lamb longissimus muscle (n=6) sections were cooked at different times post mortem (prerigor, at rigor, 1dayp.m., and 7 days p.m.) using two cooking methods. Using a boiling waterbath, samples were either cooked to a core temperature of 70 °C or boiled for 3h. The latter method was meant to reflect the traditional cooking method employed in countries where preparation of prerigor meat is practiced. The time postmortem at which the meat was prepared had a large effect on the tenderness (shear force) of the meat (P<0.01). Cooking prerigor and at rigor meat to 70 °C resulted in higher shear force values than their post rigor counterparts at 1 and 7 days p.m. (9.4 and 9.6 vs. 7.2 and 3.7 kg, respectively). The differences in tenderness between the treatment groups could be largely explained by a difference in contraction status of the meat after cooking and the effect of ageing on tenderness. Cooking pre and at rigor meat resulted in severe muscle contraction as evidenced by the differences in sarcomere length of the cooked samples. Mean sarcomere lengths in the pre and at rigor samples ranged from 1.05 to 1.20 μm. The mean sarcomere length in the post rigor samples was 1.44 μm. Cooking for 3 h at 100 °C did improve the tenderness of pre and at rigor prepared meat as compared to cooking to 70 °C, but not to the extent that ageing did. It is concluded that additional intervention methods are needed to improve the tenderness of prerigor cooked meat. Copyright © 2011 Elsevier B.V. All rights reserved.

Statistical Learning Theory for High Dimensional Prediction: Application to Criterion-Keyed Scale Development

PubMed Central

Chapman, Benjamin P.; Weiss, Alexander; Duberstein, Paul

2016-01-01

Statistical learning theory (SLT) is the statistical formulation of machine learning theory, a body of analytic methods common in “big data” problems. Regression-based SLT algorithms seek to maximize predictive accuracy for some outcome, given a large pool of potential predictors, without overfitting the sample. Research goals in psychology may sometimes call for high dimensional regression. One example is criterion-keyed scale construction, where a scale with maximal predictive validity must be built from a large item pool. Using this as a working example, we first introduce a core principle of SLT methods: minimization of expected prediction error (EPE). Minimizing EPE is fundamentally different than maximizing the within-sample likelihood, and hinges on building a predictive model of sufficient complexity to predict the outcome well, without undue complexity leading to overfitting. We describe how such models are built and refined via cross-validation. We then illustrate how three common SLT algorithms–Supervised Principal Components, Regularization, and Boosting—can be used to construct a criterion-keyed scale predicting all-cause mortality, using a large personality item pool within a population cohort. Each algorithm illustrates a different approach to minimizing EPE. Finally, we consider broader applications of SLT predictive algorithms, both as supportive analytic tools for conventional methods, and as primary analytic tools in discovery phase research. We conclude that despite their differences from the classic null-hypothesis testing approach—or perhaps because of them–SLT methods may hold value as a statistically rigorous approach to exploratory regression. PMID:27454257

Mechanical properties of frog skeletal muscles in iodoacetic acid rigor.

PubMed Central

Mulvany, M J

1975-01-01

1. Methods have been developed for describing the length: tension characteristics of frog skeletal muscles which go into rigor at 4 degrees C following iodoacetic acid poisoning either in the presence of Ca2+ (Ca-rigor) or its absence (Ca-free-rigor). 2. Such rigor muscles showed less resistance to slow stretch (slow rigor resistance) that to fast stretch (fast rigor resistance). The slow and fast rigor resistances of Ca-free-rigor muscles were much lower than those of Ca-rigor muscles. 3. The slow rigor resistance of Ca-rigor muscles was proportional to the amount of overlap between the contractile filaments present when the muscles were put into rigor. 4. Withdrawing Ca2+ from Ca-rigor muscles (induced-Ca-free rigor) reduced their slow and fast rigor resistances. Readdition of Ca2+ (but not Mg2+, Mn2+ or Sr2+) reversed the effect. 5. The slow and fast rigor resistances of Ca-rigor muscles (but not of Ca-free-rigor muscles) decreased with time. 6.The sarcomere structure of Ca-rigor and induced-Ca-free rigor muscles stretched by 0.2lo was destroyed in proportion to the amount of stretch, but the lengths of the remaining intact sarcomeres were essentially unchanged. This suggests that there had been a successive yielding of the weakeast sarcomeres. 7. The difference between the slow and fast rigor resistance and the effect of calcium on these resistances are discussed in relation to possible variations in the strength of crossbridges between the thick and thin filaments. Images Plate 1 Plate 2 PMID:1082023

Experiment Design for Complex VTOL Aircraft with Distributed Propulsion and Tilt Wing

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.; Landman, Drew

2015-01-01

Selected experimental results from a wind tunnel study of a subscale VTOL concept with distributed propulsion and tilt lifting surfaces are presented. The vehicle complexity and automated test facility were ideal for use with a randomized designed experiment. Design of Experiments and Response Surface Methods were invoked to produce run efficient, statistically rigorous regression models with minimized prediction error. Static tests were conducted at the NASA Langley 12-Foot Low-Speed Tunnel to model all six aerodynamic coefficients over a large flight envelope. This work supports investigations at NASA Langley in developing advanced configurations, simulations, and advanced control systems.

Recommendations for research design of telehealth studies.

PubMed

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.

Quantifying falsifiability of scientific theories

NASA Astrophysics Data System (ADS)

Nemenman, Ilya

I argue that the notion of falsifiability, a key concept in defining a valid scientific theory, can be quantified using Bayesian Model Selection, which is a standard tool in modern statistics. This relates falsifiability to the quantitative version of the statistical Occam's razor, and allows transforming some long-running arguments about validity of scientific theories from philosophical discussions to rigorous mathematical calculations.

Effects of Pre and Post-Rigor Marinade Injection on Some Quality Parameters of Longissimus Dorsi Muscles

PubMed Central

Fadıloğlu, Eylem Ezgi; Serdaroğlu, Meltem

2018-01-01

Abstract This study was conducted to evaluate the effects of pre and post-rigor marinade injections on some quality parameters of Longissimus dorsi (LD) muscles. Three marinade formulations were prepared with 2% NaCl, 2% NaCl+0.5 M lactic acid and 2% NaCl+0.5 M sodium lactate. In this study marinade uptake, pH, free water, cooking loss, drip loss and color properties were analyzed. Injection time had significant effect on marinade uptake levels of samples. Regardless of marinate formulation, marinade uptake of pre-rigor samples injected with marinade solutions were higher than post rigor samples. Injection of sodium lactate increased pH values of samples whereas lactic acid injection decreased pH. Marinade treatment and storage period had significant effect on cooking loss. At each evaluation period interaction between marinade treatment and injection time showed different effect on free water content. Storage period and marinade application had significant effect on drip loss values. Drip loss in all samples increased during the storage. During all storage days, lowest CIE L* value was found in pre-rigor samples injected with sodium lactate. Lactic acid injection caused color fade in pre-rigor and post-rigor samples. Interaction between marinade treatment and storage period was found statistically significant (p<0.05). At day 0 and 3, the lowest CIE b* values obtained pre-rigor samples injected with sodium lactate and there were no differences were found in other samples. At day 6, no significant differences were found in CIE b* values of all samples. PMID:29805282

Effects of Pre and Post-Rigor Marinade Injection on Some Quality Parameters of Longissimus Dorsi Muscles.

PubMed

Fadıloğlu, Eylem Ezgi; Serdaroğlu, Meltem

2018-04-01

This study was conducted to evaluate the effects of pre and post-rigor marinade injections on some quality parameters of Longissimus dorsi (LD) muscles. Three marinade formulations were prepared with 2% NaCl, 2% NaCl+0.5 M lactic acid and 2% NaCl+0.5 M sodium lactate. In this study marinade uptake, pH, free water, cooking loss, drip loss and color properties were analyzed. Injection time had significant effect on marinade uptake levels of samples. Regardless of marinate formulation, marinade uptake of pre-rigor samples injected with marinade solutions were higher than post rigor samples. Injection of sodium lactate increased pH values of samples whereas lactic acid injection decreased pH. Marinade treatment and storage period had significant effect on cooking loss. At each evaluation period interaction between marinade treatment and injection time showed different effect on free water content. Storage period and marinade application had significant effect on drip loss values. Drip loss in all samples increased during the storage. During all storage days, lowest CIE L* value was found in pre-rigor samples injected with sodium lactate. Lactic acid injection caused color fade in pre-rigor and post-rigor samples. Interaction between marinade treatment and storage period was found statistically significant ( p <0.05). At day 0 and 3, the lowest CIE b* values obtained pre-rigor samples injected with sodium lactate and there were no differences were found in other samples. At day 6, no significant differences were found in CIE b* values of all samples.

Microfluidic-based mini-metagenomics enables discovery of novel microbial lineages from complex environmental samples.

PubMed

Yu, Feiqiao Brian; Blainey, Paul C; Schulz, Frederik; Woyke, Tanja; Horowitz, Mark A; Quake, Stephen R

2017-07-05

Metagenomics and single-cell genomics have enabled genome discovery from unknown branches of life. However, extracting novel genomes from complex mixtures of metagenomic data can still be challenging and represents an ill-posed problem which is generally approached with ad hoc methods. Here we present a microfluidic-based mini-metagenomic method which offers a statistically rigorous approach to extract novel microbial genomes while preserving single-cell resolution. We used this approach to analyze two hot spring samples from Yellowstone National Park and extracted 29 new genomes, including three deeply branching lineages. The single-cell resolution enabled accurate quantification of genome function and abundance, down to 1% in relative abundance. Our analyses of genome level SNP distributions also revealed low to moderate environmental selection. The scale, resolution, and statistical power of microfluidic-based mini-metagenomics make it a powerful tool to dissect the genomic structure of microbial communities while effectively preserving the fundamental unit of biology, the single cell.

Quantitative structure-activity relationships by neural networks and inductive logic programming. I. The inhibition of dihydrofolate reductase by pyrimidines

NASA Astrophysics Data System (ADS)

Hirst, Jonathan D.; King, Ross D.; Sternberg, Michael J. E.

1994-08-01

Neural networks and inductive logic programming (ILP) have been compared to linear regression for modelling the QSAR of the inhibition of E. coli dihydrofolate reductase (DHFR) by 2,4-diamino-5-(substitured benzyl)pyrimidines, and, in the subsequent paper [Hirst, J.D., King, R.D. and Sternberg, M.J.E., J. Comput.-Aided Mol. Design, 8 (1994) 421], the inhibition of rodent DHFR by 2,4-diamino-6,6-dimethyl-5-phenyl-dihydrotriazines. Cross-validation trials provide a statistically rigorous assessment of the predictive capabilities of the methods, with training and testing data selected randomly and all the methods developed using identical training data. For the ILP analysis, molecules are represented by attributes other than Hansch parameters. Neural networks and ILP perform better than linear regression using the attribute representation, but the difference is not statistically significant. The major benefit from the ILP analysis is the formulation of understandable rules relating the activity of the inhibitors to their chemical structure.

Handwriting Examination: Moving from Art to Science

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jarman, K.H.; Hanlen, R.C.; Manzolillo, P.A.

In this document, we present a method for validating the premises and methodology of forensic handwriting examination. This method is intuitively appealing because it relies on quantitative measurements currently used qualitatively by FDE's in making comparisons, and it is scientifically rigorous because it exploits the power of multivariate statistical analysis. This approach uses measures of both central tendency and variation to construct a profile for a given individual. (Central tendency and variation are important for characterizing an individual's writing and both are currently used by FDE's in comparative analyses). Once constructed, different profiles are then compared for individuality using clustermore » analysis; they are grouped so that profiles within a group cannot be differentiated from one another based on the measured characteristics, whereas profiles between groups can. The cluster analysis procedure used here exploits the power of multivariate hypothesis testing. The result is not only a profile grouping but also an indication of statistical significance of the groups generated.« less

Quantum speedup of Monte Carlo methods.

PubMed

Montanaro, Ashley

2015-09-08

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently.

OR14-V-Uncertainty-PD2La Uncertainty Quantification for Nuclear Safeguards and Nondestructive Assay Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nicholson, Andrew D.; Croft, Stephen; McElroy, Robert Dennis

2017-08-01

The various methods of nondestructive assay (NDA) of special nuclear material (SNM) have applications in nuclear nonproliferation, including detection and identification of illicit SNM at border crossings and quantifying SNM at nuclear facilities for safeguards. No assay method is complete without “error bars,” which provide one way of expressing confidence in the assay result. Consequently, NDA specialists typically provide error bars and also partition total uncertainty into “random” and “systematic” components so that, for example, an error bar can be developed for the total mass estimate in multiple items. Uncertainty Quantification (UQ) for NDA has always been important, but itmore » is recognized that greater rigor is needed and achievable using modern statistical methods.« less

Quantum speedup of Monte Carlo methods

PubMed Central

Montanaro, Ashley

2015-01-01

Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently. PMID:26528079

Designing A Mixed Methods Study In Primary Care

PubMed Central

Creswell, John W.; Fetters, Michael D.; Ivankova, Nataliya V.

2004-01-01

BACKGROUND Mixed methods or multimethod research holds potential for rigorous, methodologically sound investigations in primary care. The objective of this study was to use criteria from the literature to evaluate 5 mixed methods studies in primary care and to advance 3 models useful for designing such investigations. METHODS We first identified criteria from the social and behavioral sciences to analyze mixed methods studies in primary care research. We then used the criteria to evaluate 5 mixed methods investigations published in primary care research journals. RESULTS Of the 5 studies analyzed, 3 included a rationale for mixing based on the need to develop a quantitative instrument from qualitative data or to converge information to best understand the research topic. Quantitative data collection involved structured interviews, observational checklists, and chart audits that were analyzed using descriptive and inferential statistical procedures. Qualitative data consisted of semistructured interviews and field observations that were analyzed using coding to develop themes and categories. The studies showed diverse forms of priority: equal priority, qualitative priority, and quantitative priority. Data collection involved quantitative and qualitative data gathered both concurrently and sequentially. The integration of the quantitative and qualitative data in these studies occurred between data analysis from one phase and data collection from a subsequent phase, while analyzing the data, and when reporting the results. DISCUSSION We recommend instrument-building, triangulation, and data transformation models for mixed methods designs as useful frameworks to add rigor to investigations in primary care. We also discuss the limitations of our study and the need for future research. PMID:15053277

Analyzing Single-Molecule Time Series via Nonparametric Bayesian Inference

PubMed Central

Hines, Keegan E.; Bankston, John R.; Aldrich, Richard W.

2015-01-01

The ability to measure the properties of proteins at the single-molecule level offers an unparalleled glimpse into biological systems at the molecular scale. The interpretation of single-molecule time series has often been rooted in statistical mechanics and the theory of Markov processes. While existing analysis methods have been useful, they are not without significant limitations including problems of model selection and parameter nonidentifiability. To address these challenges, we introduce the use of nonparametric Bayesian inference for the analysis of single-molecule time series. These methods provide a flexible way to extract structure from data instead of assuming models beforehand. We demonstrate these methods with applications to several diverse settings in single-molecule biophysics. This approach provides a well-constrained and rigorously grounded method for determining the number of biophysical states underlying single-molecule data. PMID:25650922

Measurement and calibration of differential Mueller matrix of distributed targets

NASA Technical Reports Server (NTRS)

Sarabandi, Kamal; Oh, Yisok; Ulaby, Fawwaz T.

1992-01-01

A rigorous method for calibrating polarimetric backscatter measurements of distributed targets is presented. By characterizing the radar distortions over the entire mainlobe of the antenna, the differential Mueller matrix is derived from the measured scattering matrices with a high degree of accuracy. It is shown that the radar distortions can be determined by measuring the polarimetric response of a metallic sphere over the main lobe of the antenna. Comparison of results obtained with the new algorithm with the results derived from the old calibration method show that the discrepancy between the two methods is less than 1 dB for the backscattering coefficients. The discrepancy is more drastic for the phase-difference statistics, indicating that removal of the radar distortions from the cross products of the scattering matrix elements cannot be accomplished with the traditional calibration methods.

Continuum radiation from active galactic nuclei: A statistical study

NASA Technical Reports Server (NTRS)

Isobe, T.; Feigelson, E. D.; Singh, K. P.; Kembhavi, A.

1986-01-01

The physics of the continuum spectrum of active galactic nuclei (AGNs) was examined using a large data set and rigorous statistical methods. A data base was constructed for 469 objects which include radio selected quasars, optically selected quasars, X-ray selected AGNs, BL Lac objects, and optically unidentified compact radio sources. Each object has measurements of its radio, optical, X-ray core continuum luminosity, though many of them are upper limits. Since many radio sources have extended components, the core component were carefully selected out from the total radio luminosity. With survival analysis statistical methods, which can treat upper limits correctly, these data can yield better statistical results than those previously obtained. A variety of statistical tests are performed, such as the comparison of the luminosity functions in different subsamples, and linear regressions of luminosities in different bands. Interpretation of the results leads to the following tentative conclusions: the main emission mechanism of optically selected quasars and X-ray selected AGNs is thermal, while that of BL Lac objects is synchrotron; radio selected quasars may have two different emission mechanisms in the X-ray band; BL Lac objects appear to be special cases of the radio selected quasars; some compact radio sources show the possibility of synchrotron self-Compton (SSC) in the optical band; and the spectral index between the optical and the X-ray bands depends on the optical luminosity.

Method for data analysis in different institutions: example of image guidance of prostate cancer patients.

PubMed

Piotrowski, T; Rodrigues, G; Bajon, T; Yartsev, S

2014-03-01

Multi-institutional collaborations allow for more information to be analyzed but the data from different sources may vary in the subgroup sizes and/or conditions of measuring. Rigorous statistical analysis is required for pooling the data in a larger set. Careful comparison of all the components of the data acquisition is indispensable: identical conditions allow for enlargement of the database with improved statistical analysis, clearly defined differences provide opportunity for establishing a better practice. The optimal sequence of required normality, asymptotic normality, and independence tests is proposed. An example of analysis of six subgroups of position corrections in three directions obtained during image guidance procedures for 216 prostate cancer patients from two institutions is presented. Copyright © 2013 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Small sample mediation testing: misplaced confidence in bootstrapped confidence intervals.

PubMed

Koopman, Joel; Howe, Michael; Hollenbeck, John R; Sin, Hock-Peng

2015-01-01

Bootstrapping is an analytical tool commonly used in psychology to test the statistical significance of the indirect effect in mediation models. Bootstrapping proponents have particularly advocated for its use for samples of 20-80 cases. This advocacy has been heeded, especially in the Journal of Applied Psychology, as researchers are increasingly utilizing bootstrapping to test mediation with samples in this range. We discuss reasons to be concerned with this escalation, and in a simulation study focused specifically on this range of sample sizes, we demonstrate not only that bootstrapping has insufficient statistical power to provide a rigorous hypothesis test in most conditions but also that bootstrapping has a tendency to exhibit an inflated Type I error rate. We then extend our simulations to investigate an alternative empirical resampling method as well as a Bayesian approach and demonstrate that they exhibit comparable statistical power to bootstrapping in small samples without the associated inflated Type I error. Implications for researchers testing mediation hypotheses in small samples are presented. For researchers wishing to use these methods in their own research, we have provided R syntax in the online supplemental materials. (c) 2015 APA, all rights reserved.

Decoy-state quantum key distribution with biased basis choice

PubMed Central

Wei, Zhengchao; Wang, Weilong; Zhang, Zhen; Gao, Ming; Ma, Zhi; Ma, Xiongfeng

2013-01-01

We propose a quantum key distribution scheme that combines a biased basis choice with the decoy-state method. In this scheme, Alice sends all signal states in the Z basis and decoy states in the X and Z basis with certain probabilities, and Bob measures received pulses with optimal basis choice. This scheme simplifies the system and reduces the random number consumption. From the simulation result taking into account of statistical fluctuations, we find that in a typical experimental setup, the proposed scheme can increase the key rate by at least 45% comparing to the standard decoy-state scheme. In the postprocessing, we also apply a rigorous method to upper bound the phase error rate of the single-photon components of signal states. PMID:23948999

Deployment of paired pushnets from jet-propelled kayaks to sample ichthyoplankton

USGS Publications Warehouse

Acre, Matthew R.; Grabowski, Timothy B.

2015-01-01

Accessing and effectively sampling the off-channel habitats that are considered crucial for early life stages of freshwater fishes constitute a difficult challenge when common ichthyoplankton survey methods, such as push nets, are used. We describe a new method of deploying push nets from jet-propelled kayaks to enable the sampling of previously inaccessible off-channel habitats. The described rig is also functional in more open and accessible habitats, such as the main channel of rivers or reservoirs. Although further evaluation is necessary to ensure that results are comparable across studies, the described push-net system offers a statistically rigorous methodology that generates replicate samples from a wide range of freshwater habitats that were previously inaccessible to this gear type.

Decoy-state quantum key distribution with biased basis choice.

PubMed

Wei, Zhengchao; Wang, Weilong; Zhang, Zhen; Gao, Ming; Ma, Zhi; Ma, Xiongfeng

2013-01-01

We propose a quantum key distribution scheme that combines a biased basis choice with the decoy-state method. In this scheme, Alice sends all signal states in the Z basis and decoy states in the X and Z basis with certain probabilities, and Bob measures received pulses with optimal basis choice. This scheme simplifies the system and reduces the random number consumption. From the simulation result taking into account of statistical fluctuations, we find that in a typical experimental setup, the proposed scheme can increase the key rate by at least 45% comparing to the standard decoy-state scheme. In the postprocessing, we also apply a rigorous method to upper bound the phase error rate of the single-photon components of signal states.

Rigor in Agricultural Education Research Reporting: Implications for the Discipline

ERIC Educational Resources Information Center

Fuhrman, Nicholas E.; Ladewig, Howard

2008-01-01

Agricultural education has been criticized for publishing research lacking many of the rigorous qualities found in publications of other disciplines. A few agricultural education researchers have suggested strategies for improving the rigor with which agricultural education studies report on methods and findings. The purpose of this study was to…

Experimental evaluation of rigor mortis. VI. Effect of various causes of death on the evolution of rigor mortis.

PubMed

Krompecher, T; Bergerioux, C; Brandt-Casadevall, C; Gujer, H R

1983-07-01

The evolution of rigor mortis was studied in cases of nitrogen asphyxia, drowning and strangulation, as well as in fatal intoxications due to strychnine, carbon monoxide and curariform drugs, using a modified method of measurement. Our experiments demonstrated that: (1) Strychnine intoxication hastens the onset and passing of rigor mortis. (2) CO intoxication delays the resolution of rigor mortis. (3) The intensity of rigor may vary depending upon the cause of death. (4) If the stage of rigidity is to be used to estimate the time of death, it is necessary: (a) to perform a succession of objective measurements of rigor mortis intensity; and (b) to verify the eventual presence of factors that could play a role in the modification of its development.

The Correlation between Rigor and Relevance Using Pedagogical or Andragogical Instructional Methods in American Business Schools

ERIC Educational Resources Information Center

Roldan, Alberto

2010-01-01

The purpose of this study was to examine and document whether there is a correlation between relevance (applicability) focused courses and rigor (scholarly research) focused courses with pedagogical instructional methods or andragogical instructional methods in undergraduate business schools, and how it affects learning behavior and final course…

The MIXED framework: A novel approach to evaluating mixed-methods rigor.

PubMed

Eckhardt, Ann L; DeVon, Holli A

2017-10-01

Evaluation of rigor in mixed-methods (MM) research is a persistent challenge due to the combination of inconsistent philosophical paradigms, the use of multiple research methods which require different skill sets, and the need to combine research at different points in the research process. Researchers have proposed a variety of ways to thoroughly evaluate MM research, but each method fails to provide a framework that is useful for the consumer of research. In contrast, the MIXED framework is meant to bridge the gap between an academic exercise and practical assessment of a published work. The MIXED framework (methods, inference, expertise, evaluation, and design) borrows from previously published frameworks to create a useful tool for the evaluation of a published study. The MIXED framework uses an experimental eight-item scale that allows for comprehensive integrated assessment of MM rigor in published manuscripts. Mixed methods are becoming increasingly prevalent in nursing and healthcare research requiring researchers and consumers to address issues unique to MM such as evaluation of rigor. © 2017 John Wiley & Sons Ltd.

Treatments of Missing Values in Large National Data Affect Conclusions: The Impact of Multiple Imputation on Arthroplasty Research.

PubMed

Ondeck, Nathaniel T; Fu, Michael C; Skrip, Laura A; McLynn, Ryan P; Su, Edwin P; Grauer, Jonathan N

2018-03-01

Despite the advantages of large, national datasets, one continuing concern is missing data values. Complete case analysis, where only cases with complete data are analyzed, is commonly used rather than more statistically rigorous approaches such as multiple imputation. This study characterizes the potential selection bias introduced using complete case analysis and compares the results of common regressions using both techniques following unicompartmental knee arthroplasty. Patients undergoing unicompartmental knee arthroplasty were extracted from the 2005 to 2015 National Surgical Quality Improvement Program. As examples, the demographics of patients with and without missing preoperative albumin and hematocrit values were compared. Missing data were then treated with both complete case analysis and multiple imputation (an approach that reproduces the variation and associations that would have been present in a full dataset) and the conclusions of common regressions for adverse outcomes were compared. A total of 6117 patients were included, of which 56.7% were missing at least one value. Younger, female, and healthier patients were more likely to have missing preoperative albumin and hematocrit values. The use of complete case analysis removed 3467 patients from the study in comparison with multiple imputation which included all 6117 patients. The 2 methods of handling missing values led to differing associations of low preoperative laboratory values with commonly studied adverse outcomes. The use of complete case analysis can introduce selection bias and may lead to different conclusions in comparison with the statistically rigorous multiple imputation approach. Joint surgeons should consider the methods of handling missing values when interpreting arthroplasty research. Copyright © 2017 Elsevier Inc. All rights reserved.

Modeling and prediction of peptide drift times in ion mobility spectrometry using sequence-based and structure-based approaches.

PubMed

Zhang, Yiming; Jin, Quan; Wang, Shuting; Ren, Ren

2011-05-01

The mobile behavior of 1481 peptides in ion mobility spectrometry (IMS), which are generated by protease digestion of the Drosophila melanogaster proteome, is modeled and predicted based on two different types of characterization methods, i.e. sequence-based approach and structure-based approach. In this procedure, the sequence-based approach considers both the amino acid composition of a peptide and the local environment profile of each amino acid in the peptide; the structure-based approach is performed with the CODESSA protocol, which regards a peptide as a common organic compound and generates more than 200 statistically significant variables to characterize the whole structure profile of a peptide molecule. Subsequently, the nonlinear support vector machine (SVM) and Gaussian process (GP) as well as linear partial least squares (PLS) regression is employed to correlate the structural parameters of the characterizations with the IMS drift times of these peptides. The obtained quantitative structure-spectrum relationship (QSSR) models are evaluated rigorously and investigated systematically via both one-deep and two-deep cross-validations as well as the rigorous Monte Carlo cross-validation (MCCV). We also give a comprehensive comparison on the resulting statistics arising from the different combinations of variable types with modeling methods and find that the sequence-based approach can give the QSSR models with better fitting ability and predictive power but worse interpretability than the structure-based approach. In addition, though the QSSR modeling using sequence-based approach is not needed for the preparation of the minimization structures of peptides before the modeling, it would be considerably efficient as compared to that using structure-based approach. Copyright © 2011 Elsevier Ltd. All rights reserved.

Quantitative Imaging Biomarkers: A Review of Statistical Methods for Technical Performance Assessment

PubMed Central

2017-01-01

Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers (QIBs) to measure changes in these features. Critical to the performance of a QIB in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method and metrics used to assess a QIB for clinical use. It is therefore, difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America (RSNA) and the Quantitative Imaging Biomarker Alliance (QIBA) with technical, radiological and statistical experts developed a set of technical performance analysis methods, metrics and study designs that provide terminology, metrics and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of QIB performance studies so that results from multiple studies can be compared, contrasted or combined. PMID:24919831

Graphical Descriptives: A Way to Improve Data Transparency and Methodological Rigor in Psychology.

PubMed

Tay, Louis; Parrigon, Scott; Huang, Qiming; LeBreton, James M

2016-09-01

Several calls have recently been issued to the social sciences for enhanced transparency of research processes and enhanced rigor in the methodological treatment of data and data analytics. We propose the use of graphical descriptives (GDs) as one mechanism for responding to both of these calls. GDs provide a way to visually examine data. They serve as quick and efficient tools for checking data distributions, variable relations, and the potential appropriateness of different statistical analyses (e.g., do data meet the minimum assumptions for a particular analytic method). Consequently, we believe that GDs can promote increased transparency in the journal review process, encourage best practices for data analysis, and promote a more inductive approach to understanding psychological data. We illustrate the value of potentially including GDs as a step in the peer-review process and provide a user-friendly online resource (www.graphicaldescriptives.org) for researchers interested in including data visualizations in their research. We conclude with suggestions on how GDs can be expanded and developed to enhance transparency. © The Author(s) 2016.

[A new formula for the measurement of rigor mortis: the determination of the FRR-index (author's transl)].

PubMed

Forster, B; Ropohl, D; Raule, P

1977-07-05

The manual examination of rigor mortis as currently used and its often subjective evaluation frequently produced highly incorrect deductions. It is therefore desirable that such inaccuracies should be replaced by the objective measuring of rigor mortis at the extremities. To that purpose a method is described which can also be applied in on-the-spot investigations and a new formula for the determination of rigor mortis--indices (FRR) is introduced.

A novel statistical method for quantitative comparison of multiple ChIP-seq datasets.

PubMed

Chen, Li; Wang, Chi; Qin, Zhaohui S; Wu, Hao

2015-06-15

ChIP-seq is a powerful technology to measure the protein binding or histone modification strength in the whole genome scale. Although there are a number of methods available for single ChIP-seq data analysis (e.g. 'peak detection'), rigorous statistical method for quantitative comparison of multiple ChIP-seq datasets with the considerations of data from control experiment, signal to noise ratios, biological variations and multiple-factor experimental designs is under-developed. In this work, we develop a statistical method to perform quantitative comparison of multiple ChIP-seq datasets and detect genomic regions showing differential protein binding or histone modification. We first detect peaks from all datasets and then union them to form a single set of candidate regions. The read counts from IP experiment at the candidate regions are assumed to follow Poisson distribution. The underlying Poisson rates are modeled as an experiment-specific function of artifacts and biological signals. We then obtain the estimated biological signals and compare them through the hypothesis testing procedure in a linear model framework. Simulations and real data analyses demonstrate that the proposed method provides more accurate and robust results compared with existing ones. An R software package ChIPComp is freely available at http://web1.sph.emory.edu/users/hwu30/software/ChIPComp.html. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Statistical learning theory for high dimensional prediction: Application to criterion-keyed scale development.

PubMed

Chapman, Benjamin P; Weiss, Alexander; Duberstein, Paul R

2016-12-01

Statistical learning theory (SLT) is the statistical formulation of machine learning theory, a body of analytic methods common in "big data" problems. Regression-based SLT algorithms seek to maximize predictive accuracy for some outcome, given a large pool of potential predictors, without overfitting the sample. Research goals in psychology may sometimes call for high dimensional regression. One example is criterion-keyed scale construction, where a scale with maximal predictive validity must be built from a large item pool. Using this as a working example, we first introduce a core principle of SLT methods: minimization of expected prediction error (EPE). Minimizing EPE is fundamentally different than maximizing the within-sample likelihood, and hinges on building a predictive model of sufficient complexity to predict the outcome well, without undue complexity leading to overfitting. We describe how such models are built and refined via cross-validation. We then illustrate how 3 common SLT algorithms-supervised principal components, regularization, and boosting-can be used to construct a criterion-keyed scale predicting all-cause mortality, using a large personality item pool within a population cohort. Each algorithm illustrates a different approach to minimizing EPE. Finally, we consider broader applications of SLT predictive algorithms, both as supportive analytic tools for conventional methods, and as primary analytic tools in discovery phase research. We conclude that despite their differences from the classic null-hypothesis testing approach-or perhaps because of them-SLT methods may hold value as a statistically rigorous approach to exploratory regression. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Combined slope ratio analysis and linear-subtraction: An extension of the Pearce ratio method

NASA Astrophysics Data System (ADS)

De Waal, Sybrand A.

1996-07-01

A new technique, called combined slope ratio analysis, has been developed by extending the Pearce element ratio or conserved-denominator method (Pearce, 1968) to its logical conclusions. If two stoichiometric substances are mixed and certain chemical components are uniquely contained in either one of the two mixing substances, then by treating these unique components as conserved, the composition of the substance not containing the relevant component can be accurately calculated within the limits allowed by analytical and geological error. The calculated composition can then be subjected to rigorous statistical testing using the linear-subtraction method recently advanced by Woronow (1994). Application of combined slope ratio analysis to the rocks of the Uwekahuna Laccolith, Hawaii, USA, and the lavas of the 1959-summit eruption of Kilauea Volcano, Hawaii, USA, yields results that are consistent with field observations.

Bioregional monitoring design and occupancy estimation for two Sierra Nevadan amphibian taxa

EPA Science Inventory

Land-management agencies need quantitative, statistically rigorous monitoring data, often at large spatial and temporal scales, to support resource-management decisions. Monitoring designs typically must accommodate multiple ecological, logistical, political, and economic objec...

A spatially informative optic flow model of bee colony with saccadic flight strategy for global optimization.

PubMed

Das, Swagatam; Biswas, Subhodip; Panigrahi, Bijaya K; Kundu, Souvik; Basu, Debabrota

2014-10-01

This paper presents a novel search metaheuristic inspired from the physical interpretation of the optic flow of information in honeybees about the spatial surroundings that help them orient themselves and navigate through search space while foraging. The interpreted behavior combined with the minimal foraging is simulated by the artificial bee colony algorithm to develop a robust search technique that exhibits elevated performance in multidimensional objective space. Through detailed experimental study and rigorous analysis, we highlight the statistical superiority enjoyed by our algorithm over a wide variety of functions as compared to some highly competitive state-of-the-art methods.

Analysis of Well-Clear Boundary Models for the Integration of UAS in the NAS

NASA Technical Reports Server (NTRS)

Upchurch, Jason M.; Munoz, Cesar A.; Narkawicz, Anthony J.; Chamberlain, James P.; Consiglio, Maria C.

2014-01-01

The FAA-sponsored Sense and Avoid Workshop for Unmanned Aircraft Systems (UAS) defnes the concept of sense and avoid for remote pilots as "the capability of a UAS to remain well clear from and avoid collisions with other airborne traffic." Hence, a rigorous definition of well clear is fundamental to any separation assurance concept for the integration of UAS into civil airspace. This paper presents a family of well-clear boundary models based on the TCAS II Resolution Advisory logic. Analytical techniques are used to study the properties and relationships satisfied by the models. Some of these properties are numerically quantifed using statistical methods.

Accuracy and performance of 3D mask models in optical projection lithography

NASA Astrophysics Data System (ADS)

Agudelo, Viviana; Evanschitzky, Peter; Erdmann, Andreas; Fühner, Tim; Shao, Feng; Limmer, Steffen; Fey, Dietmar

2011-04-01

Different mask models have been compared: rigorous electromagnetic field (EMF) modeling, rigorous EMF modeling with decomposition techniques and the thin mask approach (Kirchhoff approach) to simulate optical diffraction from different mask patterns in projection systems for lithography. In addition, each rigorous model was tested for two different formulations for partially coherent imaging: The Hopkins assumption and rigorous simulation of mask diffraction orders for multiple illumination angles. The aim of this work is to closely approximate results of the rigorous EMF method by the thin mask model enhanced with pupil filtering techniques. The validity of this approach for different feature sizes, shapes and illumination conditions is investigated.

The importance of early investigation and publishing in an emergent health and environment crisis.

PubMed

Murase, Kaori

2016-10-01

To minimize the damage resulting from a long-term environmental disaster such as the 2011 Fukushima nuclear accident in Japan, early disclosure of research data by scientists and prompt decision making by government authorities are required in place of careful, time-consuming research and deliberation about the consequences and cause of the accident. A Bayesian approach with flexible statistical modeling helps scientists and encourages government authorities to make decisions based on environmental data available in the early stages of a disaster. It is evident from Fukushima and similar accidents that classical research methods involving statistical methodologies that require rigorous experimental design and complex data sets are too cumbersome and delay important actions that may be critical in the early stages of an environmental disaster. Integr Environ Assess Manag 2016;12:680-682. © 2016 SETAC. © 2016 SETAC.

Space-Time Data fusion for Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Braverman, Amy; Nguyen, H.; Cressie, N.

2011-01-01

NASA has been collecting massive amounts of remote sensing data about Earth's systems for more than a decade. Missions are selected to be complementary in quantities measured, retrieval techniques, and sampling characteristics, so these datasets are highly synergistic. To fully exploit this, a rigorous methodology for combining data with heterogeneous sampling characteristics is required. For scientific purposes, the methodology must also provide quantitative measures of uncertainty that propagate input-data uncertainty appropriately. We view this as a statistical inference problem. The true but notdirectly- observed quantities form a vector-valued field continuous in space and time. Our goal is to infer those true values or some function of them, and provide to uncertainty quantification for those inferences. We use a spatiotemporal statistical model that relates the unobserved quantities of interest at point-level to the spatially aggregated, observed data. We describe and illustrate our method using CO2 data from two NASA data sets.

Statistical significance of combinatorial regulations

PubMed Central

Terada, Aika; Okada-Hatakeyama, Mariko; Tsuda, Koji; Sese, Jun

2013-01-01

More than three transcription factors often work together to enable cells to respond to various signals. The detection of combinatorial regulation by multiple transcription factors, however, is not only computationally nontrivial but also extremely unlikely because of multiple testing correction. The exponential growth in the number of tests forces us to set a strict limit on the maximum arity. Here, we propose an efficient branch-and-bound algorithm called the “limitless arity multiple-testing procedure” (LAMP) to count the exact number of testable combinations and calibrate the Bonferroni factor to the smallest possible value. LAMP lists significant combinations without any limit, whereas the family-wise error rate is rigorously controlled under the threshold. In the human breast cancer transcriptome, LAMP discovered statistically significant combinations of as many as eight binding motifs. This method may contribute to uncover pathways regulated in a coordinated fashion and find hidden associations in heterogeneous data. PMID:23882073

Complexities and potential pitfalls of clinical study design and data analysis in assisted reproduction.

PubMed

Patounakis, George; Hill, Micah J

2018-06-01

The purpose of the current review is to describe the common pitfalls in design and statistical analysis of reproductive medicine studies. It serves to guide both authors and reviewers toward reducing the incidence of spurious statistical results and erroneous conclusions. The large amount of data gathered in IVF cycles leads to problems with multiplicity, multicollinearity, and over fitting of regression models. Furthermore, the use of the word 'trend' to describe nonsignificant results has increased in recent years. Finally, methods to accurately account for female age in infertility research models are becoming more common and necessary. The pitfalls of study design and analysis reviewed provide a framework for authors and reviewers to approach clinical research in the field of reproductive medicine. By providing a more rigorous approach to study design and analysis, the literature in reproductive medicine will have more reliable conclusions that can stand the test of time.

Ice Mass Change in Greenland and Antarctica Between 1993 and 2013 from Satellite Gravity Measurements

NASA Technical Reports Server (NTRS)

Talpe, Matthieu J.; Nerem, R. Steven; Forootan, Ehsan; Schmidt, Michael; Lemoine, Frank G.; Enderlin, Ellyn M.; Landerer, Felix W.

2017-01-01

We construct long-term time series of Greenland and Antarctic ice sheet mass change from satellite gravity measurements. A statistical reconstruction approach is developed based on a principal component analysis (PCA) to combine high-resolution spatial modes from the Gravity Recovery and Climate Experiment (GRACE) mission with the gravity information from conventional satellite tracking data. Uncertainties of this reconstruction are rigorously assessed; they include temporal limitations for short GRACE measurements, spatial limitations for the low-resolution conventional tracking data measurements, and limitations of the estimated statistical relationships between low- and high-degree potential coefficients reflected in the PCA modes. Trends of mass variations in Greenland and Antarctica are assessed against a number of previous studies. The resulting time series for Greenland show a higher rate of mass loss than other methods before 2000, while the Antarctic ice sheet appears heavily influenced by interannual variations.

Digital morphogenesis via Schelling segregation

NASA Astrophysics Data System (ADS)

Barmpalias, George; Elwes, Richard; Lewis-Pye, Andrew

2018-04-01

Schelling’s model of segregation looks to explain the way in which particles or agents of two types may come to arrange themselves spatially into configurations consisting of large homogeneous clusters, i.e. connected regions consisting of only one type. As one of the earliest agent based models studied by economists and perhaps the most famous model of self-organising behaviour, it also has direct links to areas at the interface between computer science and statistical mechanics, such as the Ising model and the study of contagion and cascading phenomena in networks. While the model has been extensively studied it has largely resisted rigorous analysis, prior results from the literature generally pertaining to variants of the model which are tweaked so as to be amenable to standard techniques from statistical mechanics or stochastic evolutionary game theory. In Brandt et al (2012 Proc. 44th Annual ACM Symp. on Theory of Computing) provided the first rigorous analysis of the unperturbed model, for a specific set of input parameters. Here we provide a rigorous analysis of the model’s behaviour much more generally and establish some surprising forms of threshold behaviour, notably the existence of situations where an increased level of intolerance for neighbouring agents of opposite type leads almost certainly to decreased segregation.

Differential gene expression detection and sample classification using penalized linear regression models.

PubMed

Wu, Baolin

2006-02-15

Differential gene expression detection and sample classification using microarray data have received much research interest recently. Owing to the large number of genes p and small number of samples n (p > n), microarray data analysis poses big challenges for statistical analysis. An obvious problem owing to the 'large p small n' is over-fitting. Just by chance, we are likely to find some non-differentially expressed genes that can classify the samples very well. The idea of shrinkage is to regularize the model parameters to reduce the effects of noise and produce reliable inferences. Shrinkage has been successfully applied in the microarray data analysis. The SAM statistics proposed by Tusher et al. and the 'nearest shrunken centroid' proposed by Tibshirani et al. are ad hoc shrinkage methods. Both methods are simple, intuitive and prove to be useful in empirical studies. Recently Wu proposed the penalized t/F-statistics with shrinkage by formally using the (1) penalized linear regression models for two-class microarray data, showing good performance. In this paper we systematically discussed the use of penalized regression models for analyzing microarray data. We generalize the two-class penalized t/F-statistics proposed by Wu to multi-class microarray data. We formally derive the ad hoc shrunken centroid used by Tibshirani et al. using the (1) penalized regression models. And we show that the penalized linear regression models provide a rigorous and unified statistical framework for sample classification and differential gene expression detection.

Student peer assessment in evidence-based medicine (EBM) searching skills training: an experiment

PubMed Central

Eldredge, Jonathan D.; Bear, David G.; Wayne, Sharon J.; Perea, Paul P.

2013-01-01

Background: Student peer assessment (SPA) has been used intermittently in medical education for more than four decades, particularly in connection with skills training. SPA generally has not been rigorously tested, so medical educators have limited evidence about SPA effectiveness. Methods: Experimental design: Seventy-one first-year medical students were stratified by previous test scores into problem-based learning tutorial groups, and then these assigned groups were randomized further into intervention and control groups. All students received evidence-based medicine (EBM) training. Only the intervention group members received SPA training, practice with assessment rubrics, and then application of anonymous SPA to assignments submitted by other members of the intervention group. Results: Students in the intervention group had higher mean scores on the formative test with a potential maximum score of 49 points than did students in the control group, 45.7 and 43.5, respectively (P = 0.06). Conclusions: SPA training and the application of these skills by the intervention group resulted in higher scores on formative tests compared to those in the control group, a difference approaching statistical significance. The extra effort expended by librarians, other personnel, and medical students must be factored into the decision to use SPA in any specific educational context. Implications: SPA has not been rigorously tested, particularly in medical education. Future, similarly rigorous studies could further validate use of SPA so that librarians can optimally make use of limited contact time for information skills training in medical school curricula. PMID:24163593

Can power-law scaling and neuronal avalanches arise from stochastic dynamics?

PubMed

Touboul, Jonathan; Destexhe, Alain

2010-02-11

The presence of self-organized criticality in biology is often evidenced by a power-law scaling of event size distributions, which can be measured by linear regression on logarithmic axes. We show here that such a procedure does not necessarily mean that the system exhibits self-organized criticality. We first provide an analysis of multisite local field potential (LFP) recordings of brain activity and show that event size distributions defined as negative LFP peaks can be close to power-law distributions. However, this result is not robust to change in detection threshold, or when tested using more rigorous statistical analyses such as the Kolmogorov-Smirnov test. Similar power-law scaling is observed for surrogate signals, suggesting that power-law scaling may be a generic property of thresholded stochastic processes. We next investigate this problem analytically, and show that, indeed, stochastic processes can produce spurious power-law scaling without the presence of underlying self-organized criticality. However, this power-law is only apparent in logarithmic representations, and does not survive more rigorous analysis such as the Kolmogorov-Smirnov test. The same analysis was also performed on an artificial network known to display self-organized criticality. In this case, both the graphical representations and the rigorous statistical analysis reveal with no ambiguity that the avalanche size is distributed as a power-law. We conclude that logarithmic representations can lead to spurious power-law scaling induced by the stochastic nature of the phenomenon. This apparent power-law scaling does not constitute a proof of self-organized criticality, which should be demonstrated by more stringent statistical tests.

Identification of dynamic systems, theory and formulation

NASA Technical Reports Server (NTRS)

Maine, R. E.; Iliff, K. W.

1985-01-01

The problem of estimating parameters of dynamic systems is addressed in order to present the theoretical basis of system identification and parameter estimation in a manner that is complete and rigorous, yet understandable with minimal prerequisites. Maximum likelihood and related estimators are highlighted. The approach used requires familiarity with calculus, linear algebra, and probability, but does not require knowledge of stochastic processes or functional analysis. The treatment emphasizes unification of the various areas in estimation in dynamic systems is treated as a direct outgrowth of the static system theory. Topics covered include basic concepts and definitions; numerical optimization methods; probability; statistical estimators; estimation in static systems; stochastic processes; state estimation in dynamic systems; output error, filter error, and equation error methods of parameter estimation in dynamic systems, and the accuracy of the estimates.

A unified statistical approach to non-negative matrix factorization and probabilistic latent semantic indexing

PubMed Central

Wang, Guoli; Ebrahimi, Nader

2014-01-01

Non-negative matrix factorization (NMF) is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into the product of two nonnegative matrices, W and H, such that V ∼ W H. It has been shown to have a parts-based, sparse representation of the data. NMF has been successfully applied in a variety of areas such as natural language processing, neuroscience, information retrieval, image processing, speech recognition and computational biology for the analysis and interpretation of large-scale data. There has also been simultaneous development of a related statistical latent class modeling approach, namely, probabilistic latent semantic indexing (PLSI), for analyzing and interpreting co-occurrence count data arising in natural language processing. In this paper, we present a generalized statistical approach to NMF and PLSI based on Renyi's divergence between two non-negative matrices, stemming from the Poisson likelihood. Our approach unifies various competing models and provides a unique theoretical framework for these methods. We propose a unified algorithm for NMF and provide a rigorous proof of monotonicity of multiplicative updates for W and H. In addition, we generalize the relationship between NMF and PLSI within this framework. We demonstrate the applicability and utility of our approach as well as its superior performance relative to existing methods using real-life and simulated document clustering data. PMID:25821345

A unified statistical approach to non-negative matrix factorization and probabilistic latent semantic indexing.

PubMed

Devarajan, Karthik; Wang, Guoli; Ebrahimi, Nader

2015-04-01

Non-negative matrix factorization (NMF) is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into the product of two nonnegative matrices, W and H , such that V ∼ W H . It has been shown to have a parts-based, sparse representation of the data. NMF has been successfully applied in a variety of areas such as natural language processing, neuroscience, information retrieval, image processing, speech recognition and computational biology for the analysis and interpretation of large-scale data. There has also been simultaneous development of a related statistical latent class modeling approach, namely, probabilistic latent semantic indexing (PLSI), for analyzing and interpreting co-occurrence count data arising in natural language processing. In this paper, we present a generalized statistical approach to NMF and PLSI based on Renyi's divergence between two non-negative matrices, stemming from the Poisson likelihood. Our approach unifies various competing models and provides a unique theoretical framework for these methods. We propose a unified algorithm for NMF and provide a rigorous proof of monotonicity of multiplicative updates for W and H . In addition, we generalize the relationship between NMF and PLSI within this framework. We demonstrate the applicability and utility of our approach as well as its superior performance relative to existing methods using real-life and simulated document clustering data.

Near infrared spectroscopy as an on-line method to quantitatively determine glycogen and predict ultimate pH in pre rigor bovine M. longissimus dorsi.

PubMed

Lomiwes, D; Reis, M M; Wiklund, E; Young, O A; North, M

2010-12-01

The potential of near infrared (NIR) spectroscopy as an on-line method to quantify glycogen and predict ultimate pH (pH(u)) of pre rigor beef M. longissimus dorsi (LD) was assessed. NIR spectra (538 to 1677 nm) of pre rigor LD from steers, cows and bulls were collected early post mortem and measurements were made for pre rigor glycogen concentration and pH(u). Spectral and measured data were combined to develop models to quantify glycogen and predict the pH(u) of pre rigor LD. NIR spectra and pre rigor predicted values obtained from quantitative models were shown to be poorly correlated against glycogen and pH(u) (r(2)=0.23 and 0.20, respectively). Qualitative models developed to categorize each muscle according to their pH(u) were able to correctly categorize 42% of high pH(u) samples. Optimum qualitative and quantitative models derived from NIR spectra found low correlation between predicted values and reference measurements. Copyright © 2010 The American Meat Science Association. Published by Elsevier Ltd.. All rights reserved.

An information-theoretic approach to the modeling and analysis of whole-genome bisulfite sequencing data.

PubMed

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.

Microfluidic-based mini-metagenomics enables discovery of novel microbial lineages from complex environmental samples

PubMed Central

Yu, Feiqiao Brian; Blainey, Paul C; Schulz, Frederik; Woyke, Tanja; Horowitz, Mark A; Quake, Stephen R

2017-01-01

Metagenomics and single-cell genomics have enabled genome discovery from unknown branches of life. However, extracting novel genomes from complex mixtures of metagenomic data can still be challenging and represents an ill-posed problem which is generally approached with ad hoc methods. Here we present a microfluidic-based mini-metagenomic method which offers a statistically rigorous approach to extract novel microbial genomes while preserving single-cell resolution. We used this approach to analyze two hot spring samples from Yellowstone National Park and extracted 29 new genomes, including three deeply branching lineages. The single-cell resolution enabled accurate quantification of genome function and abundance, down to 1% in relative abundance. Our analyses of genome level SNP distributions also revealed low to moderate environmental selection. The scale, resolution, and statistical power of microfluidic-based mini-metagenomics make it a powerful tool to dissect the genomic structure of microbial communities while effectively preserving the fundamental unit of biology, the single cell. DOI: http://dx.doi.org/10.7554/eLife.26580.001 PMID:28678007

Practice-based evidence study design for comparative effectiveness research.

PubMed

Horn, Susan D; Gassaway, Julie

2007-10-01

To describe a new, rigorous, comprehensive practice-based evidence for clinical practice improvement (PBE-CPI) study methodology, and compare its features, advantages, and disadvantages to those of randomized controlled trials and sophisticated statistical methods for comparative effectiveness research. PBE-CPI incorporates natural variation within data from routine clinical practice to determine what works, for whom, when, and at what cost. It uses the knowledge of front-line caregivers, who develop study questions and define variables as part of a transdisciplinary team. Its comprehensive measurement framework provides a basis for analyses of significant bivariate and multivariate associations between treatments and outcomes, controlling for patient differences, such as severity of illness. PBE-CPI studies can uncover better practices more quickly than randomized controlled trials or sophisticated statistical methods, while achieving many of the same advantages. We present examples of actionable findings from PBE-CPI studies in postacute care settings related to comparative effectiveness of medications, nutritional support approaches, incontinence products, physical therapy activities, and other services. Outcomes improved when practices associated with better outcomes in PBE-CPI analyses were adopted in practice.

Revised Planning Methodology For Signalized Intersections And Operational Analysis Of Exclusive Left-Turn Lanes, Part-II: Models And Procedures (Final Report)

DOT National Transportation Integrated Search

1996-04-01

THIS REPORT ALSO DESCRIBES THE PROCEDURES FOR DIRECT ESTIMATION OF INTERSECTION CAPACITY WITH SIMULATION, INCLUDING A SET OF RIGOROUS STATISTICAL TESTS FOR SIMULATION PARAMETER CALIBRATION FROM FIELD DATA.

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)

Experimental evaluation of rigor mortis. III. Comparative study of the evolution of rigor mortis in different sized muscle groups in rats.

PubMed

Krompecher, T; Fryc, O

1978-01-01

The use of new methods and an appropriate apparatus has allowed us to make successive measurements of rigor mortis and a study of its evolution in the rat. By a comparative examination on the front and hind limbs, we have determined the following: (1) The muscular mass of the hind limbs is 2.89 times greater than that of the front limbs. (2) In the initial phase rigor mortis is more pronounced in the front limbs. (3) The front and hind limbs reach maximum rigor mortis at the same time and this state is maintained for 2 hours. (4) Resolution of rigor mortis is accelerated in the front limbs during the initial phase, but both front and hind limbs reach complete resolution at the same time.

Rigor Mortis: Statistical thoroughness in reporting and the making of truth.

PubMed

Tal, Aner

2016-02-01

Should a uniform checklist be adopted for methodological and statistical reporting? The current article discusses this notion, with particular attention to the use of old versus new statistics, and a consideration of the arguments brought up by Von Roten. The article argues that an overly exhaustive checklist that is uniformly applied to all submitted papers may be unsuitable for multidisciplinary work, and would further result in undue clutter and potentially distract reviewers from pertinent considerations in their evaluation of research articles. © The Author(s) 2015.

The slow-scale linear noise approximation: an accurate, reduced stochastic description of biochemical networks under timescale separation conditions

PubMed Central

2012-01-01

Background It is well known that the deterministic dynamics of biochemical reaction networks can be more easily studied if timescale separation conditions are invoked (the quasi-steady-state assumption). In this case the deterministic dynamics of a large network of elementary reactions are well described by the dynamics of a smaller network of effective reactions. Each of the latter represents a group of elementary reactions in the large network and has associated with it an effective macroscopic rate law. A popular method to achieve model reduction in the presence of intrinsic noise consists of using the effective macroscopic rate laws to heuristically deduce effective probabilities for the effective reactions which then enables simulation via the stochastic simulation algorithm (SSA). The validity of this heuristic SSA method is a priori doubtful because the reaction probabilities for the SSA have only been rigorously derived from microscopic physics arguments for elementary reactions. Results We here obtain, by rigorous means and in closed-form, a reduced linear Langevin equation description of the stochastic dynamics of monostable biochemical networks in conditions characterized by small intrinsic noise and timescale separation. The slow-scale linear noise approximation (ssLNA), as the new method is called, is used to calculate the intrinsic noise statistics of enzyme and gene networks. The results agree very well with SSA simulations of the non-reduced network of elementary reactions. In contrast the conventional heuristic SSA is shown to overestimate the size of noise for Michaelis-Menten kinetics, considerably under-estimate the size of noise for Hill-type kinetics and in some cases even miss the prediction of noise-induced oscillations. Conclusions A new general method, the ssLNA, is derived and shown to correctly describe the statistics of intrinsic noise about the macroscopic concentrations under timescale separation conditions. The ssLNA provides a simple and accurate means of performing stochastic model reduction and hence it is expected to be of widespread utility in studying the dynamics of large noisy reaction networks, as is common in computational and systems biology. PMID:22583770

Body size affects the strength of social interactions and spatial organization of a schooling fish (Pseudomugil signifer)

NASA Astrophysics Data System (ADS)

Romenskyy, Maksym; Herbert-Read, James E.; Ward, Ashley J. W.; Sumpter, David J. T.

2017-04-01

While a rich variety of self-propelled particle models propose to explain the collective motion of fish and other animals, rigorous statistical comparison between models and data remains a challenge. Plausible models should be flexible enough to capture changes in the collective behaviour of animal groups at their different developmental stages and group sizes. Here, we analyse the statistical properties of schooling fish (Pseudomugil signifer) through a combination of experiments and simulations. We make novel use of a Boltzmann inversion method, usually applied in molecular dynamics, to identify the effective potential of the mean force of fish interactions. Specifically, we show that larger fish have a larger repulsion zone, but stronger attraction, resulting in greater alignment in their collective motion. We model the collective dynamics of schools using a self-propelled particle model, modified to include varying particle speed and a local repulsion rule. We demonstrate that the statistical properties of the fish schools are reproduced by our model, thereby capturing a number of features of the behaviour and development of schooling fish.

A powerful and flexible statistical framework for testing hypotheses of allele-specific gene expression from RNA-seq data

PubMed Central

Skelly, Daniel A.; Johansson, Marnie; Madeoy, Jennifer; Wakefield, Jon; Akey, Joshua M.

2011-01-01

Variation in gene expression is thought to make a significant contribution to phenotypic diversity among individuals within populations. Although high-throughput cDNA sequencing offers a unique opportunity to delineate the genome-wide architecture of regulatory variation, new statistical methods need to be developed to capitalize on the wealth of information contained in RNA-seq data sets. To this end, we developed a powerful and flexible hierarchical Bayesian model that combines information across loci to allow both global and locus-specific inferences about allele-specific expression (ASE). We applied our methodology to a large RNA-seq data set obtained in a diploid hybrid of two diverse Saccharomyces cerevisiae strains, as well as to RNA-seq data from an individual human genome. Our statistical framework accurately quantifies levels of ASE with specified false-discovery rates, achieving high reproducibility between independent sequencing platforms. We pinpoint loci that show unusual and biologically interesting patterns of ASE, including allele-specific alternative splicing and transcription termination sites. Our methodology provides a rigorous, quantitative, and high-resolution tool for profiling ASE across whole genomes. PMID:21873452

Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment.

PubMed

Raunig, David L; McShane, Lisa M; Pennello, Gene; Gatsonis, Constantine; Carson, Paul L; Voyvodic, James T; Wahl, Richard L; Kurland, Brenda F; Schwarz, Adam J; Gönen, Mithat; Zahlmann, Gudrun; Kondratovich, Marina V; O'Donnell, Kevin; Petrick, Nicholas; Cole, Patricia E; Garra, Brian; Sullivan, Daniel C

2015-02-01

Technological developments and greater rigor in the quantitative measurement of biological features in medical images have given rise to an increased interest in using quantitative imaging biomarkers to measure changes in these features. Critical to the performance of a quantitative imaging biomarker in preclinical or clinical settings are three primary metrology areas of interest: measurement linearity and bias, repeatability, and the ability to consistently reproduce equivalent results when conditions change, as would be expected in any clinical trial. Unfortunately, performance studies to date differ greatly in designs, analysis method, and metrics used to assess a quantitative imaging biomarker for clinical use. It is therefore difficult or not possible to integrate results from different studies or to use reported results to design studies. The Radiological Society of North America and the Quantitative Imaging Biomarker Alliance with technical, radiological, and statistical experts developed a set of technical performance analysis methods, metrics, and study designs that provide terminology, metrics, and methods consistent with widely accepted metrological standards. This document provides a consistent framework for the conduct and evaluation of quantitative imaging biomarker performance studies so that results from multiple studies can be compared, contrasted, or combined. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Optical properties of electrohydrodynamic convection patterns: rigorous and approximate methods.

PubMed

Bohley, Christian; Heuer, Jana; Stannarius, Ralf

2005-12-01

We analyze the optical behavior of two-dimensionally periodic structures that occur in electrohydrodynamic convection (EHC) patterns in nematic sandwich cells. These structures are anisotropic, locally uniaxial, and periodic on the scale of micrometers. For the first time, the optics of these structures is investigated with a rigorous method. The method used for the description of the electromagnetic waves interacting with EHC director patterns is a numerical approach that discretizes directly the Maxwell equations. It works as a space-grid-time-domain method and computes electric and magnetic fields in time steps. This so-called finite-difference-time-domain (FDTD) method is able to generate the fields with arbitrary accuracy. We compare this rigorous method with earlier attempts based on ray-tracing and analytical approximations. Results of optical studies of EHC structures made earlier based on ray-tracing methods are confirmed for thin cells, when the spatial periods of the pattern are sufficiently large. For the treatment of small-scale convection structures, the FDTD method is without alternatives.

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions.

PubMed

Pavlacky, David C; Lukacs, Paul M; Blakesley, Jennifer A; Skorkowsky, Robert C; Klute, David S; Hahn, Beth A; Dreitz, Victoria J; George, T Luke; Hanni, David J

2017-01-01

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer's sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer's sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical design and analyses ensures reliable knowledge about bird populations that is relevant and integral to bird conservation at multiple scales.

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions

PubMed Central

Hahn, Beth A.; Dreitz, Victoria J.; George, T. Luke

2017-01-01

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer’s sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer’s sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical design and analyses ensures reliable knowledge about bird populations that is relevant and integral to bird conservation at multiple scales. PMID:29065128

How to Help Students Conceptualize the Rigorous Definition of the Limit of a Sequence

ERIC Educational Resources Information Center

Roh, Kyeong Hah

2010-01-01

This article suggests an activity, called the epsilon-strip activity, as an instructional method for conceptualization of the rigorous definition of the limit of a sequence via visualization. The article also describes the learning objectives of each instructional step of the activity, and then provides detailed instructional methods to guide…

Scientific rigor through videogames.

PubMed

Treuille, Adrien; Das, Rhiju

2014-11-01

Hypothesis-driven experimentation - the scientific method - can be subverted by fraud, irreproducibility, and lack of rigorous predictive tests. A robust solution to these problems may be the 'massive open laboratory' model, recently embodied in the internet-scale videogame EteRNA. Deploying similar platforms throughout biology could enforce the scientific method more broadly. Copyright © 2014 Elsevier Ltd. All rights reserved.

Rigorous simulations of a helical core fiber by the use of transformation optics formalism.

PubMed

Napiorkowski, Maciej; Urbanczyk, Waclaw

2014-09-22

We report for the first time on rigorous numerical simulations of a helical-core fiber by using a full vectorial method based on the transformation optics formalism. We modeled the dependence of circular birefringence of the fundamental mode on the helix pitch and analyzed the effect of a birefringence increase caused by the mode displacement induced by a core twist. Furthermore, we analyzed the complex field evolution versus the helix pitch in the first order modes, including polarization and intensity distribution. Finally, we show that the use of the rigorous vectorial method allows to better predict the confinement loss of the guided modes compared to approximate methods based on equivalent in-plane bending models.

DESIGNA ND ANALYSIS FOR THEMATIC MAP ACCURACY ASSESSMENT: FUNDAMENTAL PRINCIPLES

EPA Science Inventory

Before being used in scientific investigations and policy decisions, thematic maps constructed from remotely sensed data should be subjected to a statistically rigorous accuracy assessment. The three basic components of an accuracy assessment are: 1) the sampling design used to s...

Perspectives on statistics education: observations from statistical consulting in an academic nursing environment.

PubMed

Hayat, Matthew J; Schmiege, Sarah J; Cook, Paul F

2014-04-01

Statistics knowledge is essential for understanding the nursing and health care literature, as well as for applying rigorous science in nursing research. Statistical consultants providing services to faculty and students in an academic nursing program have the opportunity to identify gaps and challenges in statistics education for nursing students. This information may be useful to curriculum committees and statistics educators. This article aims to provide perspective on statistics education stemming from the experiences of three experienced statistics educators who regularly collaborate and consult with nurse investigators. The authors share their knowledge and express their views about data management, data screening and manipulation, statistical software, types of scientific investigation, and advanced statistical topics not covered in the usual coursework. The suggestions provided promote a call for data to study these topics. Relevant data about statistics education can assist educators in developing comprehensive statistics coursework for nursing students. Copyright 2014, SLACK Incorporated.

Zipf's law holds for phrases, not words.

PubMed

Williams, Jake Ryland; Lessard, Paul R; Desu, Suma; Clark, Eric M; Bagrow, James P; Danforth, Christopher M; Dodds, Peter Sheridan

2015-08-11

With Zipf's law being originally and most famously observed for word frequency, it is surprisingly limited in its applicability to human language, holding over no more than three to four orders of magnitude before hitting a clear break in scaling. Here, building on the simple observation that phrases of one or more words comprise the most coherent units of meaning in language, we show empirically that Zipf's law for phrases extends over as many as nine orders of rank magnitude. In doing so, we develop a principled and scalable statistical mechanical method of random text partitioning, which opens up a rich frontier of rigorous text analysis via a rank ordering of mixed length phrases.

Disciplining Bioethics: Towards a Standard of Methodological Rigor in Bioethics Research

PubMed Central

Adler, Daniel; Shaul, Randi Zlotnik

2012-01-01

Contemporary bioethics research is often described as multi- or interdisciplinary. Disciplines are characterized, in part, by their methods. Thus, when bioethics research draws on a variety of methods, it crosses disciplinary boundaries. Yet each discipline has its own standard of rigor—so when multiple disciplinary perspectives are considered, what constitutes rigor? This question has received inadequate attention, as there is considerable disagreement regarding the disciplinary status of bioethics. This disagreement has presented five challenges to bioethics research. Addressing them requires consideration of the main types of cross-disciplinary research, and consideration of proposals aiming to ensure rigor in bioethics research. PMID:22686634

Curve fitting air sample filter decay curves to estimate transuranic content.

PubMed

Hayes, Robert B; Chiou, Hung Cheng

2004-01-01

By testing industry standard techniques for radon progeny evaluation on air sample filters, a new technique is developed to evaluate transuranic activity on air filters by curve fitting the decay curves. The industry method modified here is simply the use of filter activity measurements at different times to estimate the air concentrations of radon progeny. The primary modification was to not look for specific radon progeny values but rather transuranic activity. By using a method that will provide reasonably conservative estimates of the transuranic activity present on a filter, some credit for the decay curve shape can then be taken. By carrying out rigorous statistical analysis of the curve fits to over 65 samples having no transuranic activity taken over a 10-mo period, an optimization of the fitting function and quality tests for this purpose was attained.

Trends in Mediation Analysis in Nursing Research: Improving Current Practice.

PubMed

Hertzog, Melody

2018-06-01

The purpose of this study was to describe common approaches used by nursing researchers to test mediation models and evaluate them within the context of current methodological advances. MEDLINE was used to locate studies testing a mediation model and published from 2004 to 2015 in nursing journals. Design (experimental/correlation, cross-sectional/longitudinal, model complexity) and analysis (method, inclusion of test of mediated effect, violations/discussion of assumptions, sample size/power) characteristics were coded for 456 studies. General trends were identified using descriptive statistics. Consistent with findings of reviews in other disciplines, evidence was found that nursing researchers may not be aware of the strong assumptions and serious limitations of their analyses. Suggestions for strengthening the rigor of such studies and an overview of current methods for testing more complex models, including longitudinal mediation processes, are presented.

Rigorous Numerical Study of Low-Period Windows for the Quadratic Map

NASA Astrophysics Data System (ADS)

Galias, Zbigniew

An efficient method to find all low-period windows for the quadratic map is proposed. The method is used to obtain very accurate rigorous bounds of positions of all periodic windows with periods p ≤ 32. The contribution of period-doubling windows on the total width of periodic windows is discussed. Properties of periodic windows are studied numerically.

On generic obstructions to recovering correct statistics from climate simulations: Homogenization for deterministic maps and multiplicative noise

NASA Astrophysics Data System (ADS)

Gottwald, Georg; Melbourne, Ian

2013-04-01

Whereas diffusion limits of stochastic multi-scale systems have a long and successful history, the case of constructing stochastic parametrizations of chaotic deterministic systems has been much less studied. We present rigorous results of convergence of a chaotic slow-fast system to a stochastic differential equation with multiplicative noise. Furthermore we present rigorous results for chaotic slow-fast maps, occurring as numerical discretizations of continuous time systems. This raises the issue of how to interpret certain stochastic integrals; surprisingly the resulting integrals of the stochastic limit system are generically neither of Stratonovich nor of Ito type in the case of maps. It is shown that the limit system of a numerical discretisation is different to the associated continuous time system. This has important consequences when interpreting the statistics of long time simulations of multi-scale systems - they may be very different to the one of the original continuous time system which we set out to study.

Using GIS to generate spatially balanced random survey designs for natural resource applications.

PubMed

Theobald, David M; Stevens, Don L; White, Denis; Urquhart, N Scott; Olsen, Anthony R; Norman, John B

2007-07-01

Sampling of a population is frequently required to understand trends and patterns in natural resource management because financial and time constraints preclude a complete census. A rigorous probability-based survey design specifies where to sample so that inferences from the sample apply to the entire population. Probability survey designs should be used in natural resource and environmental management situations because they provide the mathematical foundation for statistical inference. Development of long-term monitoring designs demand survey designs that achieve statistical rigor and are efficient but remain flexible to inevitable logistical or practical constraints during field data collection. Here we describe an approach to probability-based survey design, called the Reversed Randomized Quadrant-Recursive Raster, based on the concept of spatially balanced sampling and implemented in a geographic information system. This provides environmental managers a practical tool to generate flexible and efficient survey designs for natural resource applications. Factors commonly used to modify sampling intensity, such as categories, gradients, or accessibility, can be readily incorporated into the spatially balanced sample design.

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.

Is There a Consensus on Consensus Methodology? Descriptions and Recommendations for Future Consensus Research.

PubMed

Waggoner, Jane; Carline, Jan D; Durning, Steven J

2016-05-01

The authors of this article reviewed the methodology of three common consensus methods: nominal group process, consensus development panels, and the Delphi technique. The authors set out to determine how a majority of researchers are conducting these studies, how they are analyzing results, and subsequently the manner in which they are reporting their findings. The authors conclude with a set of guidelines and suggestions designed to aid researchers who choose to use the consensus methodology in their work.Overall, researchers need to describe their inclusion criteria. In addition to this, on the basis of the current literature the authors found that a panel size of 5 to 11 members was most beneficial across all consensus methods described. Lastly, the authors agreed that the statistical analyses done in consensus method studies should be as rigorous as possible and that the predetermined definition of consensus must be included in the ultimate manuscript. More specific recommendations are given for each of the three consensus methods described in the article.

Dynamic programming algorithms for biological sequence comparison.

PubMed

Pearson, W R; Miller, W

1992-01-01

Efficient dynamic programming algorithms are available for a broad class of protein and DNA sequence comparison problems. These algorithms require computer time proportional to the product of the lengths of the two sequences being compared [O(N2)] but require memory space proportional only to the sum of these lengths [O(N)]. Although the requirement for O(N2) time limits use of the algorithms to the largest computers when searching protein and DNA sequence databases, many other applications of these algorithms, such as calculation of distances for evolutionary trees and comparison of a new sequence to a library of sequence profiles, are well within the capabilities of desktop computers. In particular, the results of library searches with rapid searching programs, such as FASTA or BLAST, should be confirmed by performing a rigorous optimal alignment. Whereas rapid methods do not overlook significant sequence similarities, FASTA limits the number of gaps that can be inserted into an alignment, so that a rigorous alignment may extend the alignment substantially in some cases. BLAST does not allow gaps in the local regions that it reports; a calculation that allows gaps is very likely to extend the alignment substantially. Although a Monte Carlo evaluation of the statistical significance of a similarity score with a rigorous algorithm is much slower than the heuristic approach used by the RDF2 program, the dynamic programming approach should take less than 1 hr on a 386-based PC or desktop Unix workstation. For descriptive purposes, we have limited our discussion to methods for calculating similarity scores and distances that use gap penalties of the form g = rk. Nevertheless, programs for the more general case (g = q+rk) are readily available. Versions of these programs that run either on Unix workstations, IBM-PC class computers, or the Macintosh can be obtained from either of the authors.

A statistical physics perspective on criticality in financial markets

NASA Astrophysics Data System (ADS)

Bury, Thomas

2013-11-01

Stock markets are complex systems exhibiting collective phenomena and particular features such as synchronization, fluctuations distributed as power-laws, non-random structures and similarity to neural networks. Such specific properties suggest that markets operate at a very special point. Financial markets are believed to be critical by analogy to physical systems, but little statistically founded evidence has been given. Through a data-based methodology and comparison to simulations inspired by the statistical physics of complex systems, we show that the Dow Jones and index sets are not rigorously critical. However, financial systems are closer to criticality in the crash neighborhood.

Integration of Technology into the Classroom: Case Studies.

ERIC Educational Resources Information Center

Johnson, D. LaMont, Ed.; Maddux, Cleborne D., Ed.; Liu, Leping, Ed.

This book contains the following case studies on the integration of technology in education: (1) "First Steps toward a Statistically Generated Information Technology Integration Model" (D. LaMont Johnson and Leping Liu); (2) "Case Studies: Are We Rejecting Rigor or Rediscovering Richness?" (Cleborne D. Maddux); (3)…

On Lack of Robustness in Hydrological Model Development Due to Absence of Guidelines for Selecting Calibration and Evaluation Data: Demonstration for Data-Driven Models

NASA Astrophysics Data System (ADS)

Zheng, Feifei; Maier, Holger R.; Wu, Wenyan; Dandy, Graeme C.; Gupta, Hoshin V.; Zhang, Tuqiao

2018-02-01

Hydrological models are used for a wide variety of engineering purposes, including streamflow forecasting and flood-risk estimation. To develop such models, it is common to allocate the available data to calibration and evaluation data subsets. Surprisingly, the issue of how this allocation can affect model evaluation performance has been largely ignored in the research literature. This paper discusses the evaluation performance bias that can arise from how available data are allocated to calibration and evaluation subsets. As a first step to assessing this issue in a statistically rigorous fashion, we present a comprehensive investigation of the influence of data allocation on the development of data-driven artificial neural network (ANN) models of streamflow. Four well-known formal data splitting methods are applied to 754 catchments from Australia and the U.S. to develop 902,483 ANN models. Results clearly show that the choice of the method used for data allocation has a significant impact on model performance, particularly for runoff data that are more highly skewed, highlighting the importance of considering the impact of data splitting when developing hydrological models. The statistical behavior of the data splitting methods investigated is discussed and guidance is offered on the selection of the most appropriate data splitting methods to achieve representative evaluation performance for streamflow data with different statistical properties. Although our results are obtained for data-driven models, they highlight the fact that this issue is likely to have a significant impact on all types of hydrological models, especially conceptual rainfall-runoff models.

The Abdominal Aortic Aneurysm Statistically Corrected Operative Risk Evaluation (AAA SCORE) for predicting mortality after open and endovascular interventions.

PubMed

Ambler, Graeme K; Gohel, Manjit S; Mitchell, David C; Loftus, Ian M; Boyle, Jonathan R

2015-01-01

Accurate adjustment of surgical outcome data for risk is vital in an era of surgeon-level reporting. Current risk prediction models for abdominal aortic aneurysm (AAA) repair are suboptimal. We aimed to develop a reliable risk model for in-hospital mortality after intervention for AAA, using rigorous contemporary statistical techniques to handle missing data. Using data collected during a 15-month period in the United Kingdom National Vascular Database, we applied multiple imputation methodology together with stepwise model selection to generate preoperative and perioperative models of in-hospital mortality after AAA repair, using two thirds of the available data. Model performance was then assessed on the remaining third of the data by receiver operating characteristic curve analysis and compared with existing risk prediction models. Model calibration was assessed by Hosmer-Lemeshow analysis. A total of 8088 AAA repair operations were recorded in the National Vascular Database during the study period, of which 5870 (72.6%) were elective procedures. Both preoperative and perioperative models showed excellent discrimination, with areas under the receiver operating characteristic curve of .89 and .92, respectively. This was significantly better than any of the existing models (area under the receiver operating characteristic curve for best comparator model, .84 and .88; P < .001 and P = .001, respectively). Discrimination remained excellent when only elective procedures were considered. There was no evidence of miscalibration by Hosmer-Lemeshow analysis. We have developed accurate models to assess risk of in-hospital mortality after AAA repair. These models were carefully developed with rigorous statistical methodology and significantly outperform existing methods for both elective cases and overall AAA mortality. These models will be invaluable for both preoperative patient counseling and accurate risk adjustment of published outcome data. Copyright © 2015 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

High-Dimensional Multivariate Repeated Measures Analysis with Unequal Covariance Matrices.

PubMed

Harrar, Solomon W; Kong, Xiaoli

2015-03-01

In this paper, test statistics for repeated measures design are introduced when the dimension is large. By large dimension is meant the number of repeated measures and the total sample size grow together but either one could be larger than the other. Asymptotic distribution of the statistics are derived for the equal as well as unequal covariance cases in the balanced as well as unbalanced cases. The asymptotic framework considered requires proportional growth of the sample sizes and the dimension of the repeated measures in the unequal covariance case. In the equal covariance case, one can grow at much faster rate than the other. The derivations of the asymptotic distributions mimic that of Central Limit Theorem with some important peculiarities addressed with sufficient rigor. Consistent and unbiased estimators of the asymptotic variances, which make efficient use of all the observations, are also derived. Simulation study provides favorable evidence for the accuracy of the asymptotic approximation under the null hypothesis. Power simulations have shown that the new methods have comparable power with a popular method known to work well in low-dimensional situation but the new methods have shown enormous advantage when the dimension is large. Data from Electroencephalograph (EEG) experiment is analyzed to illustrate the application of the results.

High-Dimensional Multivariate Repeated Measures Analysis with Unequal Covariance Matrices

PubMed Central

Harrar, Solomon W.; Kong, Xiaoli

2015-01-01

In this paper, test statistics for repeated measures design are introduced when the dimension is large. By large dimension is meant the number of repeated measures and the total sample size grow together but either one could be larger than the other. Asymptotic distribution of the statistics are derived for the equal as well as unequal covariance cases in the balanced as well as unbalanced cases. The asymptotic framework considered requires proportional growth of the sample sizes and the dimension of the repeated measures in the unequal covariance case. In the equal covariance case, one can grow at much faster rate than the other. The derivations of the asymptotic distributions mimic that of Central Limit Theorem with some important peculiarities addressed with sufficient rigor. Consistent and unbiased estimators of the asymptotic variances, which make efficient use of all the observations, are also derived. Simulation study provides favorable evidence for the accuracy of the asymptotic approximation under the null hypothesis. Power simulations have shown that the new methods have comparable power with a popular method known to work well in low-dimensional situation but the new methods have shown enormous advantage when the dimension is large. Data from Electroencephalograph (EEG) experiment is analyzed to illustrate the application of the results. PMID:26778861

Protein Multiplexed Immunoassay Analysis with R.

PubMed

Breen, Edmond J

2017-01-01

Plasma samples from 177 control and type 2 diabetes patients collected at three Australian hospitals are screened for 14 analytes using six custom-made multiplex kits across 60 96-well plates. In total 354 samples were collected from the patients, representing one baseline and one end point sample from each patient. R methods and source code for analyzing the analyte fluorescence response obtained from these samples by Luminex Bio-Plex ® xMap multiplexed immunoassay technology are disclosed. Techniques and R procedures for reading Bio-Plex ® result files for statistical analysis and data visualization are also presented. The need for technical replicates and the number of technical replicates are addressed as well as plate layout design strategies. Multinomial regression is used to determine plate to sample covariate balance. Methods for matching clinical covariate information to Bio-Plex ® results and vice versa are given. As well as methods for measuring and inspecting the quality of the fluorescence responses are presented. Both fixed and mixed-effect approaches for immunoassay statistical differential analysis are presented and discussed. A random effect approach to outlier analysis and detection is also shown. The bioinformatics R methodology present here provides a foundation for rigorous and reproducible analysis of the fluorescence response obtained from multiplexed immunoassays.

Statistical properties of multi-theta polymer chains

NASA Astrophysics Data System (ADS)

Uehara, Erica; Deguchi, Tetsuo

2018-04-01

We study statistical properties of polymer chains with complex structures whose chemical connectivities are expressed by graphs. The multi-theta curve of m subchains with two branch points connected by them is one of the simplest graphs among those graphs having closed paths, i.e. loops. We denoted it by θm , and for m  =  2 it is given by a ring. We derive analytically the pair distribution function and the scattering function for the θm -shaped polymer chains consisting of m Gaussian random walks of n steps. Surprisingly, it is shown rigorously that the mean-square radius of gyration for the Gaussian θm -shaped polymer chain does not depend on the number m of subchains if each subchain has the same fixed number of steps. For m  =  3 we show the Kratky plot for the theta-shaped polymer chain consisting of hard cylindrical segments by the Monte-Carlo method including reflection at trivalent vertices.

Quantitative Analysis of Venus Radar Backscatter Data in ArcGIS

NASA Technical Reports Server (NTRS)

Long, S. M.; Grosfils, E. B.

2005-01-01

Ongoing mapping of the Ganiki Planitia (V14) quadrangle of Venus and definition of material units has involved an integrated but qualitative analysis of Magellan radar backscatter images and topography using standard geomorphological mapping techniques. However, such analyses do not take full advantage of the quantitative information contained within the images. Analysis of the backscatter coefficient allows a much more rigorous statistical comparison between mapped units, permitting first order selfsimilarity tests of geographically separated materials assigned identical geomorphological labels. Such analyses cannot be performed directly on pixel (DN) values from Magellan backscatter images, because the pixels are scaled to the Muhleman law for radar echoes on Venus and are not corrected for latitudinal variations in incidence angle. Therefore, DN values must be converted based on pixel latitude back to their backscatter coefficient values before accurate statistical analysis can occur. Here we present a method for performing the conversions and analysis of Magellan backscatter data using commonly available ArcGIS software and illustrate the advantages of the process for geological mapping.

Atlantic salmon skin and fillet color changes effected by perimortem handling stress, rigor mortis, and ice storage.

PubMed

Erikson, U; Misimi, E

2008-03-01

The changes in skin and fillet color of anesthetized and exhausted Atlantic salmon were determined immediately after killing, during rigor mortis, and after ice storage for 7 d. Skin color (CIE L*, a*, b*, and related values) was determined by a Minolta Chroma Meter. Roche SalmoFan Lineal and Roche Color Card values were determined by a computer vision method and a sensory panel. Before color assessment, the stress levels of the 2 fish groups were characterized in terms of white muscle parameters (pH, rigor mortis, and core temperature). The results showed that perimortem handling stress initially significantly affected several color parameters of skin and fillets. Significant transient fillet color changes also occurred in the prerigor phase and during the development of rigor mortis. Our results suggested that fillet color was affected by postmortem glycolysis (pH drop, particularly in anesthetized fillets), then by onset and development of rigor mortis. The color change patterns during storage were different for the 2 groups of fish. The computer vision method was considered suitable for automated (online) quality control and grading of salmonid fillets according to color.

Statistically significant relational data mining :

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berry, Jonathan W.; Leung, Vitus Joseph; Phillips, Cynthia Ann

This report summarizes the work performed under the project (3z(BStatitically significant relational data mining.(3y (BThe goal of the project was to add more statistical rigor to the fairly ad hoc area of data mining on graphs. Our goal was to develop better algorithms and better ways to evaluate algorithm quality. We concetrated on algorithms for community detection, approximate pattern matching, and graph similarity measures. Approximate pattern matching involves finding an instance of a relatively small pattern, expressed with tolerance, in a large graph of data observed with uncertainty. This report gathers the abstracts and references for the eight refereed publicationsmore » that have appeared as part of this work. We then archive three pieces of research that have not yet been published. The first is theoretical and experimental evidence that a popular statistical measure for comparison of community assignments favors over-resolved communities over approximations to a ground truth. The second are statistically motivated methods for measuring the quality of an approximate match of a small pattern in a large graph. The third is a new probabilistic random graph model. Statisticians favor these models for graph analysis. The new local structure graph model overcomes some of the issues with popular models such as exponential random graph models and latent variable models.« less

Assessing the Ecological Condition of Streams in a Southeastern Brazilian Basin using a Probabilistic Monitoring Design

EPA Science Inventory

Prompt assessment and management actions are required if we are to reduce the current rapid loss of habitat and biodiversity worldwide. Statistically valid quantification of the biota and habitat condition in water bodies are prerequisites for rigorous assessment of aquatic biodi...

Acquiring data for large aquatic resource surveys: the art of ompromise among science, logistics, and reality

EPA Science Inventory

The US Environmental Protection Agency (EPA) is revising its strategy to obtain the information needed to answer questions pertinent to water-quality management efficiently and rigorously at national scales. One tool of this revised strategy is use of statistically based surveys ...

Exploration of the Maximum Entropy/Optimal Projection Approach to Control Design Synthesis for Large Space Structures.

DTIC Science & Technology

1985-02-01

Energy Analysis , a branch of dynamic modal analysis developed for analyzing acoustic vibration problems, its present stage of development embodies a...Maximum Entropy Stochastic Modelling and Reduced-Order Design Synthesis is a rigorous new approach to this class of problems. Inspired by Statistical

Beyond Composite Scores and Cronbach's Alpha: Advancing Methodological Rigor in Recreation Research

ERIC Educational Resources Information Center

Gagnon, Ryan J.; Stone, Garrett A.; Garst, Barry A.

2017-01-01

Critically examining common statistical approaches and their strengths and weaknesses is an important step in advancing recreation and leisure sciences. To continue this critical examination and to inform methodological decision making, this study compared three approaches to determine how alternative approaches may result in contradictory…

diffHic: a Bioconductor package to detect differential genomic interactions in Hi-C data.

PubMed

Lun, Aaron T L; Smyth, Gordon K

2015-08-19

Chromatin conformation capture with high-throughput sequencing (Hi-C) is a technique that measures the in vivo intensity of interactions between all pairs of loci in the genome. Most conventional analyses of Hi-C data focus on the detection of statistically significant interactions. However, an alternative strategy involves identifying significant changes in the interaction intensity (i.e., differential interactions) between two or more biological conditions. This is more statistically rigorous and may provide more biologically relevant results. Here, we present the diffHic software package for the detection of differential interactions from Hi-C data. diffHic provides methods for read pair alignment and processing, counting into bin pairs, filtering out low-abundance events and normalization of trended or CNV-driven biases. It uses the statistical framework of the edgeR package to model biological variability and to test for significant differences between conditions. Several options for the visualization of results are also included. The use of diffHic is demonstrated with real Hi-C data sets. Performance against existing methods is also evaluated with simulated data. On real data, diffHic is able to successfully detect interactions with significant differences in intensity between biological conditions. It also compares favourably to existing software tools on simulated data sets. These results suggest that diffHic is a viable approach for differential analyses of Hi-C data.

Uncertainty quantification for nuclear density functional theory and information content of new measurements.

PubMed

McDonnell, J D; Schunck, N; Higdon, D; Sarich, J; Wild, S M; Nazarewicz, W

2015-03-27

Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models, to estimate model errors and thereby improve predictive capability, to extrapolate beyond the regions reached by experiment, and to provide meaningful input to applications and planned measurements. To showcase new opportunities offered by such tools, we make a rigorous analysis of theoretical statistical uncertainties in nuclear density functional theory using Bayesian inference methods. By considering the recent mass measurements from the Canadian Penning Trap at Argonne National Laboratory, we demonstrate how the Bayesian analysis and a direct least-squares optimization, combined with high-performance computing, can be used to assess the information content of the new data with respect to a model based on the Skyrme energy density functional approach. Employing the posterior probability distribution computed with a Gaussian process emulator, we apply the Bayesian framework to propagate theoretical statistical uncertainties in predictions of nuclear masses, two-neutron dripline, and fission barriers. Overall, we find that the new mass measurements do not impose a constraint that is strong enough to lead to significant changes in the model parameters. The example discussed in this study sets the stage for quantifying and maximizing the impact of new measurements with respect to current modeling and guiding future experimental efforts, thus enhancing the experiment-theory cycle in the scientific method.

Clinical Trials With Large Numbers of Variables: Important Advantages of Canonical Analysis.

PubMed

Cleophas, Ton J

2016-01-01

Canonical analysis assesses the combined effects of a set of predictor variables on a set of outcome variables, but it is little used in clinical trials despite the omnipresence of multiple variables. The aim of this study was to assess the performance of canonical analysis as compared with traditional multivariate methods using multivariate analysis of covariance (MANCOVA). As an example, a simulated data file with 12 gene expression levels and 4 drug efficacy scores was used. The correlation coefficient between the 12 predictor and 4 outcome variables was 0.87 (P = 0.0001) meaning that 76% of the variability in the outcome variables was explained by the 12 covariates. Repeated testing after the removal of 5 unimportant predictor and 1 outcome variable produced virtually the same overall result. The MANCOVA identified identical unimportant variables, but it was unable to provide overall statistics. (1) Canonical analysis is remarkable, because it can handle many more variables than traditional multivariate methods such as MANCOVA can. (2) At the same time, it accounts for the relative importance of the separate variables, their interactions and differences in units. (3) Canonical analysis provides overall statistics of the effects of sets of variables, whereas traditional multivariate methods only provide the statistics of the separate variables. (4) Unlike other methods for combining the effects of multiple variables such as factor analysis/partial least squares, canonical analysis is scientifically entirely rigorous. (5) Limitations include that it is less flexible than factor analysis/partial least squares, because only 2 sets of variables are used and because multiple solutions instead of one is offered. We do hope that this article will stimulate clinical investigators to start using this remarkable method.

An application of Bayesian statistics to the extragalactic Cepheid distance scale

NASA Astrophysics Data System (ADS)

Barnes, Thomas G., III; Moffett, Thomas J.; Jefferys, W. H.; Forestell, Amy D.

2004-05-01

We have determined quasi-geometric distances to the Magellanic Clouds, M31 and M33. Our analysis uses a Bayesian statistical method to provide mathematically rigorous and objective solutions for individual Cepheids. We combine the individual distances with a hierarchial Bayesian model to determine the galactic distances. We obtain distance moduli 18.87 ± 0.07 mag (LMC, 12 stars), 19.14 ± 0.10 (SMC, 8 stars), 23.83 ± 0.35 mag (M33, 1 star) and 25.2 ± 0.6 mag (M31, 1 star) - all uncorrected for metallicity. The M31 and M33 distances are very preliminary. If the Pl relations of the LMC, SMC, and Galaxy are identical, our results exclude the metallicity effect in the V, (V - R) surface brightness method predicted by Hindsley and Bell (1989) at the 5σ level. Alternately, if Hindsley & Bell's prediction is adopted as true, we find a metallicity effect intrinsic to the Cepheid PL relation requiring a correction Δ(V - Mv) = (0.36 ± 0.07)Δ[A/H] mag. The latter has the opposite sign to other observational estimates of the Cepheid metallicity effect.

Statistical Methods for Detecting Differentially Abundant Features in Clinical Metagenomic Samples

PubMed Central

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

SPRUCE Advanced Molecular Techniques Provide a Rigorous Method for Characterizing Organic Matter Quality in Complex Systems: Supporting Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wilson, Rachel M; Tfaily, Malak M

These data are provided in support of the Commentary, Advanced molecular techniques provide a rigorous method for characterizing organic matter quality in complex systems, Wilson and Tfaily (2018). Measurement results demonstrate that optical characterization of peatland dissolved organic matter (DOM) may not fully capture classically identified chemical characteristics and may, therefore, not be the best measure of organic matter quality.

Statistical Inference for Data Adaptive Target Parameters.

PubMed

Hubbard, Alan E; Kherad-Pajouh, Sara; van der Laan, Mark J

2016-05-01

Consider one observes n i.i.d. copies of a random variable with a probability distribution that is known to be an element of a particular statistical model. In order to define our statistical target we partition the sample in V equal size sub-samples, and use this partitioning to define V splits in an estimation sample (one of the V subsamples) and corresponding complementary parameter-generating sample. For each of the V parameter-generating samples, we apply an algorithm that maps the sample to a statistical target parameter. We define our sample-split data adaptive statistical target parameter as the average of these V-sample specific target parameters. We present an estimator (and corresponding central limit theorem) of this type of data adaptive target parameter. This general methodology for generating data adaptive target parameters is demonstrated with a number of practical examples that highlight new opportunities for statistical learning from data. This new framework provides a rigorous statistical methodology for both exploratory and confirmatory analysis within the same data. Given that more research is becoming "data-driven", the theory developed within this paper provides a new impetus for a greater involvement of statistical inference into problems that are being increasingly addressed by clever, yet ad hoc pattern finding methods. To suggest such potential, and to verify the predictions of the theory, extensive simulation studies, along with a data analysis based on adaptively determined intervention rules are shown and give insight into how to structure such an approach. The results show that the data adaptive target parameter approach provides a general framework and resulting methodology for data-driven science.

Ergodicity of Truncated Stochastic Navier Stokes with Deterministic Forcing and Dispersion

NASA Astrophysics Data System (ADS)

Majda, Andrew J.; Tong, Xin T.

2016-10-01

Turbulence in idealized geophysical flows is a very rich and important topic. The anisotropic effects of explicit deterministic forcing, dispersive effects from rotation due to the β -plane and F-plane, and topography together with random forcing all combine to produce a remarkable number of realistic phenomena. These effects have been studied through careful numerical experiments in the truncated geophysical models. These important results include transitions between coherent jets and vortices, and direct and inverse turbulence cascades as parameters are varied, and it is a contemporary challenge to explain these diverse statistical predictions. Here we contribute to these issues by proving with full mathematical rigor that for any values of the deterministic forcing, the β - and F-plane effects and topography, with minimal stochastic forcing, there is geometric ergodicity for any finite Galerkin truncation. This means that there is a unique smooth invariant measure which attracts all statistical initial data at an exponential rate. In particular, this rigorous statistical theory guarantees that there are no bifurcations to multiple stable and unstable statistical steady states as geophysical parameters are varied in contrast to claims in the applied literature. The proof utilizes a new statistical Lyapunov function to account for enstrophy exchanges between the statistical mean and the variance fluctuations due to the deterministic forcing. It also requires careful proofs of hypoellipticity with geophysical effects and uses geometric control theory to establish reachability. To illustrate the necessity of these conditions, a two-dimensional example is developed which has the square of the Euclidean norm as the Lyapunov function and is hypoelliptic with nonzero noise forcing, yet fails to be reachable or ergodic.

Hypothesis testing of scientific Monte Carlo calculations.

PubMed

Wallerberger, Markus; Gull, Emanuel

2017-11-01

The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and programming bugs. However, the testing paradigms developed for deterministic algorithms have proven to be ill suited for stochastic algorithms. In this paper we demonstrate explicitly how the technique of statistical hypothesis testing, which is in wide use in other fields of science, can be used to devise automatic and reliable tests for Monte Carlo methods, and we show that these tests are able to detect some of the common problems encountered in stochastic scientific simulations. We argue that hypothesis testing should become part of the standard testing toolkit for scientific simulations.

Hypothesis testing of scientific Monte Carlo calculations

NASA Astrophysics Data System (ADS)

Wallerberger, Markus; Gull, Emanuel

2017-11-01

The steadily increasing size of scientific Monte Carlo simulations and the desire for robust, correct, and reproducible results necessitates rigorous testing procedures for scientific simulations in order to detect numerical problems and programming bugs. However, the testing paradigms developed for deterministic algorithms have proven to be ill suited for stochastic algorithms. In this paper we demonstrate explicitly how the technique of statistical hypothesis testing, which is in wide use in other fields of science, can be used to devise automatic and reliable tests for Monte Carlo methods, and we show that these tests are able to detect some of the common problems encountered in stochastic scientific simulations. We argue that hypothesis testing should become part of the standard testing toolkit for scientific simulations.

Objective assessment of image quality. IV. Application to adaptive optics

PubMed Central

Barrett, Harrison H.; Myers, Kyle J.; Devaney, Nicholas; Dainty, Christopher

2008-01-01

The methodology of objective assessment, which defines image quality in terms of the performance of specific observers on specific tasks of interest, is extended to temporal sequences of images with random point spread functions and applied to adaptive imaging in astronomy. The tasks considered include both detection and estimation, and the observers are the optimal linear discriminant (Hotelling observer) and the optimal linear estimator (Wiener). A general theory of first- and second-order spatiotemporal statistics in adaptive optics is developed. It is shown that the covariance matrix can be rigorously decomposed into three terms representing the effect of measurement noise, random point spread function, and random nature of the astronomical scene. Figures of merit are developed, and computational methods are discussed. PMID:17106464

Equilibrium E × B Flows in Nonlinear Gyrofluid Flux-Tube Simulations

NASA Astrophysics Data System (ADS)

Beer, M. A.; Hammett, G. W.

2000-10-01

Comparisons of theory with experiment often indicate levels of sheared E × B flow large enough to significantly suppress turbulence, especially when local transport barriers are formed. We extend our previous simulations by including equilibrium scale sheared E × B flow directly, by introducing a coordinate transformation which shears the simulation domain with the equilibrium E × B flow, while preserving smooth statistical periodicity across the radial domain. This method was used linearly in our previous comparisons with JET [Beer, Budny, Challis, et al., EPS (1999)] and is now applied to nonlinear simulations. This method makes use of some tricks suggested for this problem by Dimits [Int. Conf. on Numerical Simulation of Plasmas (1994)] based on special properties of discrete Fourier transforms. A similar coordinate transformation was previously used successfully by Waltz, et al. [Phys. Plasmas 5, 1784 (1998)], and we confirm their finding that the turbulence is suppressed when the shearing rate, ω_E, is comparable to the maximum linear growth rate in the absence of sheared flow, γ_lin. This is often significantly different than the threshold for linear suppression. With this extension, our simulations are able to address transport barriers from a more rigorous footing. Of particular interest will be the investigation of the expansion or propagation of barriers, where E × B shear suppression is by definition at the marginal point. In addition, our formulation uses general magnetic geometry, so we can rigorously investigate various geometrical effects (e.g. hats, Δ', κ) on the threshold for suppression.

Architecture of marine food webs: To be or not be a 'small-world'.

PubMed

Marina, Tomás Ignacio; Saravia, Leonardo A; Cordone, Georgina; Salinas, Vanesa; Doyle, Santiago R; Momo, Fernando R

2018-01-01

The search for general properties in network structure has been a central issue for food web studies in recent years. One such property is the small-world topology that combines a high clustering and a small distance between nodes of the network. This property may increase food web resilience but make them more sensitive to the extinction of connected species. Food web theory has been developed principally from freshwater and terrestrial ecosystems, largely omitting marine habitats. If theory needs to be modified to accommodate observations from marine ecosystems, based on major differences in several topological characteristics is still on debate. Here we investigated if the small-world topology is a common structural pattern in marine food webs. We developed a novel, simple and statistically rigorous method to examine the largest set of complex marine food webs to date. More than half of the analyzed marine networks exhibited a similar or lower characteristic path length than the random expectation, whereas 39% of the webs presented a significantly higher clustering than its random counterpart. Our method proved that 5 out of 28 networks fulfilled both features of the small-world topology: short path length and high clustering. This work represents the first rigorous analysis of the small-world topology and its associated features in high-quality marine networks. We conclude that such topology is a structural pattern that is not maximized in marine food webs; thus it is probably not an effective model to study robustness, stability and feasibility of marine ecosystems.

MUSiC - Model-independent search for deviations from Standard Model predictions in CMS

NASA Astrophysics Data System (ADS)

Pieta, Holger

2010-02-01

We present an approach for a model independent search in CMS. Systematically scanning the data for deviations from the standard model Monte Carlo expectations, such an analysis can help to understand the detector and tune event generators. By minimizing the theoretical bias the analysis is furthermore sensitive to a wide range of models for new physics, including the uncounted number of models not-yet-thought-of. After sorting the events into classes defined by their particle content (leptons, photons, jets and missing transverse energy), a minimally prejudiced scan is performed on a number of distributions. Advanced statistical methods are used to determine the significance of the deviating regions, rigorously taking systematic uncertainties into account. A number of benchmark scenarios, including common models of new physics and possible detector effects, have been used to gauge the power of such a method. )

Forecasting volatility with neural regression: a contribution to model adequacy.

PubMed

Refenes, A N; Holt, W T

2001-01-01

Neural nets' usefulness for forecasting is limited by problems of overfitting and the lack of rigorous procedures for model identification, selection and adequacy testing. This paper describes a methodology for neural model misspecification testing. We introduce a generalization of the Durbin-Watson statistic for neural regression and discuss the general issues of misspecification testing using residual analysis. We derive a generalized influence matrix for neural estimators which enables us to evaluate the distribution of the statistic. We deploy Monte Carlo simulation to compare the power of the test for neural and linear regressors. While residual testing is not a sufficient condition for model adequacy, it is nevertheless a necessary condition to demonstrate that the model is a good approximation to the data generating process, particularly as neural-network estimation procedures are susceptible to partial convergence. The work is also an important step toward developing rigorous procedures for neural model identification, selection and adequacy testing which have started to appear in the literature. We demonstrate its applicability in the nontrivial problem of forecasting implied volatility innovations using high-frequency stock index options. Each step of the model building process is validated using statistical tests to verify variable significance and model adequacy with the results confirming the presence of nonlinear relationships in implied volatility innovations.

Real-time in Situ Signal-to-noise Ratio Estimation for the Assessment of Operational Communications Links

NASA Technical Reports Server (NTRS)

Manning, Robert M.

2002-01-01

The work presented here formulates the rigorous statistical basis for the correct estimation of communication link SNR of a BPSK, QPSK, and for that matter, any M-ary phase-modulated digital signal from what is known about its statistical behavior at the output of the receiver demodulator. Many methods to accomplish this have been proposed and implemented in the past but all of them are based on tacit and unwarranted assumptions and are thus defective. However, the basic idea is well founded, i.e., the signal at the output of a communications demodulator has convolved within it the prevailing SNR characteristic of the link. The acquisition of the SNR characteristic is of the utmost importance to a communications system that must remain reliable in adverse propagation conditions. This work provides a correct and consistent mathematical basis for the proper statistical 'deconvolution' of the output of a demodulator to yield a measure of the SNR. The use of such techniques will alleviate the need and expense for a separate propagation link to assess the propagation conditions prevailing on the communications link. Furthermore, they are applicable for every situation involving the digital transmission of data over planetary and space communications links.

Connectopic mapping with resting-state fMRI.

PubMed

Haak, Koen V; Marquand, Andre F; Beckmann, Christian F

2018-04-15

Brain regions are often topographically connected: nearby locations within one brain area connect with nearby locations in another area. Mapping these connection topographies, or 'connectopies' in short, is crucial for understanding how information is processed in the brain. Here, we propose principled, fully data-driven methods for mapping connectopies using functional magnetic resonance imaging (fMRI) data acquired at rest by combining spectral embedding of voxel-wise connectivity 'fingerprints' with a novel approach to spatial statistical inference. We apply the approach in human primary motor and visual cortex, and show that it can trace biologically plausible, overlapping connectopies in individual subjects that follow these regions' somatotopic and retinotopic maps. As a generic mechanism to perform inference over connectopies, the new spatial statistics approach enables rigorous statistical testing of hypotheses regarding the fine-grained spatial profile of functional connectivity and whether that profile is different between subjects or between experimental conditions. The combined framework offers a fundamental alternative to existing approaches to investigating functional connectivity in the brain, from voxel- or seed-pair wise characterizations of functional association, towards a full, multivariate characterization of spatial topography. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

ASYMPTOTIC DISTRIBUTION OF ΔAUC, NRIs, AND IDI BASED ON THEORY OF U-STATISTICS

PubMed Central

Demler, Olga V.; Pencina, Michael J.; Cook, Nancy R.; D’Agostino, Ralph B.

2017-01-01

The change in AUC (ΔAUC), the IDI, and NRI are commonly used measures of risk prediction model performance. Some authors have reported good validity of associated methods of estimating their standard errors (SE) and construction of confidence intervals, whereas others have questioned their performance. To address these issues we unite the ΔAUC, IDI, and three versions of the NRI under the umbrella of the U-statistics family. We rigorously show that the asymptotic behavior of ΔAUC, NRIs, and IDI fits the asymptotic distribution theory developed for U-statistics. We prove that the ΔAUC, NRIs, and IDI are asymptotically normal, unless they compare nested models under the null hypothesis. In the latter case, asymptotic normality and existing SE estimates cannot be applied to ΔAUC, NRIs, or IDI. In the former case SE formulas proposed in the literature are equivalent to SE formulas obtained from U-statistics theory if we ignore adjustment for estimated parameters. We use Sukhatme-Randles-deWet condition to determine when adjustment for estimated parameters is necessary. We show that adjustment is not necessary for SEs of the ΔAUC and two versions of the NRI when added predictor variables are significant and normally distributed. The SEs of the IDI and three-category NRI should always be adjusted for estimated parameters. These results allow us to define when existing formulas for SE estimates can be used and when resampling methods such as the bootstrap should be used instead when comparing nested models. We also use the U-statistic theory to develop a new SE estimate of ΔAUC. PMID:28627112

Asymptotic distribution of ∆AUC, NRIs, and IDI based on theory of U-statistics.

PubMed

Demler, Olga V; Pencina, Michael J; Cook, Nancy R; D'Agostino, Ralph B

2017-09-20

The change in area under the curve (∆AUC), the integrated discrimination improvement (IDI), and net reclassification index (NRI) are commonly used measures of risk prediction model performance. Some authors have reported good validity of associated methods of estimating their standard errors (SE) and construction of confidence intervals, whereas others have questioned their performance. To address these issues, we unite the ∆AUC, IDI, and three versions of the NRI under the umbrella of the U-statistics family. We rigorously show that the asymptotic behavior of ∆AUC, NRIs, and IDI fits the asymptotic distribution theory developed for U-statistics. We prove that the ∆AUC, NRIs, and IDI are asymptotically normal, unless they compare nested models under the null hypothesis. In the latter case, asymptotic normality and existing SE estimates cannot be applied to ∆AUC, NRIs, or IDI. In the former case, SE formulas proposed in the literature are equivalent to SE formulas obtained from U-statistics theory if we ignore adjustment for estimated parameters. We use Sukhatme-Randles-deWet condition to determine when adjustment for estimated parameters is necessary. We show that adjustment is not necessary for SEs of the ∆AUC and two versions of the NRI when added predictor variables are significant and normally distributed. The SEs of the IDI and three-category NRI should always be adjusted for estimated parameters. These results allow us to define when existing formulas for SE estimates can be used and when resampling methods such as the bootstrap should be used instead when comparing nested models. We also use the U-statistic theory to develop a new SE estimate of ∆AUC. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

On making cuts for magnetic scalar potentials in multiply connected regions

NASA Astrophysics Data System (ADS)

Kotiuga, P. R.

1987-04-01

The problem of making cuts is of importance to scalar potential formulations of three-dimensional eddy current problems. Its heuristic solution has been known for a century [J. C. Maxwell, A Treatise on Electricity and Magnetism, 3rd ed. (Clarendon, Oxford, 1981), Chap. 1, Article 20] and in the last decade, with the use of finite element methods, a restricted combinatorial variant has been proposed and solved [M. L. Brown, Int. J. Numer. Methods Eng. 20, 665 (1984)]. This problem, in its full generality, has never received a rigorous mathematical formulation. This paper presents such a formulation and outlines a rigorous proof of existence. The technique used in the proof expose the incredible intricacy of the general problem and the restrictive assumptions of Brown [Int. J. Numer. Methods Eng. 20, 665 (1984)]. Finally, the results make rigorous Kotiuga's (Ph. D. Thesis, McGill University, Montreal, 1984) heuristic interpretation of cuts and duality theorems via intersection matrices.

Methodological Issues in Trials of Complementary and Alternative Medicine Interventions

PubMed Central

Sikorskii, Alla; Wyatt, Gwen; Victorson, David; Faulkner, Gwen; Rahbar, Mohammad Hossein

2010-01-01

Background Complementary and alternative medicine (CAM) use is widespread among cancer patients. Information on safety and efficacy of CAM therapies is needed for both patients and health care providers. Well-designed randomized clinical trials (RCTs) of CAM therapy interventions can inform both clinical research and practice. Objectives To review important issues that affect the design of RCTs for CAM interventions. Methods Using the methods component of the Consolidated Standards for Reporting Trials (CONSORT) as a guiding framework, and a National Cancer Institute-funded reflexology study as an exemplar, methodological issues related to participants, intervention, objectives, outcomes, sample size, randomization, blinding, and statistical methods were reviewed. Discussion Trials of CAM interventions designed and implemented according to appropriate methodological standards will facilitate the needed scientific rigor in CAM research. Interventions in CAM can be tested using proposed methodology, and the results of testing will inform nursing practice in providing safe and effective supportive care and improving the well-being of patients. PMID:19918155

Extended maximum likelihood halo-independent analysis of dark matter direct detection data

DOE PAGES

Gelmini, Graciela B.; Georgescu, Andreea; Gondolo, Paolo; ...

2015-11-24

We extend and correct a recently proposed maximum-likelihood halo-independent method to analyze unbinned direct dark matter detection data. Instead of the recoil energy as independent variable we use the minimum speed a dark matter particle must have to impart a given recoil energy to a nucleus. This has the advantage of allowing us to apply the method to any type of target composition and interaction, e.g. with general momentum and velocity dependence, and with elastic or inelastic scattering. We prove the method and provide a rigorous statistical interpretation of the results. As first applications, we find that for dark mattermore » particles with elastic spin-independent interactions and neutron to proton coupling ratio f n/f p=-0.7, the WIMP interpretation of the signal observed by CDMS-II-Si is compatible with the constraints imposed by all other experiments with null results. We also find a similar compatibility for exothermic inelastic spin-independent interactions with f n/f p=-0.8.« less

The impact of rigorous mathematical thinking as learning method toward geometry understanding

NASA Astrophysics Data System (ADS)

Nugraheni, Z.; Budiyono, B.; Slamet, I.

2018-05-01

To reach higher order thinking skill, needed to be mastered the conceptual understanding. RMT is a unique realization of the cognitive conceptual construction approach based on Mediated Learning Experience (MLE) theory by Feurstein and Vygotsky’s sociocultural theory. This was quasi experimental research which was comparing the experimental class that was given Rigorous Mathematical Thinking (RMT) as learning method and control class that was given Direct Learning (DL) as the conventional learning activity. This study examined whether there was different effect of two learning method toward conceptual understanding of Junior High School students. The data was analyzed by using Independent t-test and obtained a significant difference of mean value between experimental and control class on geometry conceptual understanding. Further, by semi-structure interview known that students taught by RMT had deeper conceptual understanding than students who were taught by conventional way. By these result known that Rigorous Mathematical Thinking (RMT) as learning method have positive impact toward Geometry conceptual understanding.

A Generalized Method for the Comparable and Rigorous Calculation of the Polytropic Efficiencies of Turbocompressors

NASA Astrophysics Data System (ADS)

Dimitrakopoulos, Panagiotis

2018-03-01

The calculation of polytropic efficiencies is a very important task, especially during the development of new compression units, like compressor impellers, stages and stage groups. Such calculations are also crucial for the determination of the performance of a whole compressor. As processors and computational capacities have substantially been improved in the last years, the need for a new, rigorous, robust, accurate and at the same time standardized method merged, regarding the computation of the polytropic efficiencies, especially based on thermodynamics of real gases. The proposed method is based on the rigorous definition of the polytropic efficiency. The input consists of pressure and temperature values at the end points of the compression path (suction and discharge), for a given working fluid. The average relative error for the studied cases was 0.536 %. Thus, this high-accuracy method is proposed for efficiency calculations related with turbocompressors and their compression units, especially when they are operating at high power levels, for example in jet engines and high-power plants.

Simulation-Based Probabilistic Tsunami Hazard Analysis: Empirical and Robust Hazard Predictions

NASA Astrophysics Data System (ADS)

De Risi, Raffaele; Goda, Katsuichiro

2017-08-01

Probabilistic tsunami hazard analysis (PTHA) is the prerequisite for rigorous risk assessment and thus for decision-making regarding risk mitigation strategies. This paper proposes a new simulation-based methodology for tsunami hazard assessment for a specific site of an engineering project along the coast, or, more broadly, for a wider tsunami-prone region. The methodology incorporates numerous uncertain parameters that are related to geophysical processes by adopting new scaling relationships for tsunamigenic seismic regions. Through the proposed methodology it is possible to obtain either a tsunami hazard curve for a single location, that is the representation of a tsunami intensity measure (such as inundation depth) versus its mean annual rate of occurrence, or tsunami hazard maps, representing the expected tsunami intensity measures within a geographical area, for a specific probability of occurrence in a given time window. In addition to the conventional tsunami hazard curve that is based on an empirical statistical representation of the simulation-based PTHA results, this study presents a robust tsunami hazard curve, which is based on a Bayesian fitting methodology. The robust approach allows a significant reduction of the number of simulations and, therefore, a reduction of the computational effort. Both methods produce a central estimate of the hazard as well as a confidence interval, facilitating the rigorous quantification of the hazard uncertainties.

Systemic Planning: An Annotated Bibliography and Literature Guide. Exchange Bibliography No. 91.

ERIC Educational Resources Information Center

Catanese, Anthony James

Systemic planning is an operational approach to using scientific rigor and qualitative judgment in a complementary manner. It integrates rigorous techniques and methods from systems analysis, cybernetics, decision theory, and work programing. The annotated reference sources in this bibliography include those works that have been most influential…

Sex Differences in the Response of Children with ADHD to Once-Daily Formulations of Methylphenidate

ERIC Educational Resources Information Center

Sonuga-Barke, J. S.; Coghill, David; Markowitz, John S.; Swanson, James M.; Vandenberghe, Mieke; Hatch, Simon J.

2007-01-01

Objectives: Studies of sex differences in methylphenidate response by children with attention-deficit/hyperactivity disorder have lacked methodological rigor and statistical power. This paper reports an examination of sex differences based on further analysis of data from a comparison of two once-daily methylphenidate formulations (the COMACS…

The Role of Data Analysis Software in Graduate Programs in Education and Post-Graduate Research

ERIC Educational Resources Information Center

Harwell, Michael

2018-01-01

The importance of data analysis software in graduate programs in education and post-graduate educational research is self-evident. However the role of this software in facilitating supererogated statistical practice versus "cookbookery" is unclear. The need to rigorously document the role of data analysis software in students' graduate…

A Study of Statistics through Tootsie Pops

ERIC Educational Resources Information Center

Aaberg, Shelby; Vitosh, Jason; Smith, Wendy

2016-01-01

A classic TV commercial once asked, "How many licks does it take to get to the center of a Tootsie Roll Tootsie Pop?" The narrator claims, "The world may never know" (Tootsie Roll 2012), but an Internet search returns a multitude of answers, some of which include rigorous systematic approaches by academics to address the…

Meeting the needs of an ever-demanding market.

PubMed

Rigby, Richard

2002-04-01

Balancing cost and performance in packaging is critical. This article outlines techniques to assist in this whilst delivering added value and product differentiation. The techniques include a rigorous statistical process capable of delivering cost reduction and improved quality and a computer modelling process that can save time when validating new packaging options.

Exploring the Use of Participatory Information to Improve Monitoring, Mapping and Assessment of Aquatic Ecosystem Services at Landascape Scales

EPA Science Inventory

Traditionally, the EPA has monitored aquatic ecosystems using statistically rigorous sample designs and intensive field efforts which provide high quality datasets. But by their nature they leave many aquatic systems unsampled, follow a top down approach, have a long lag between ...

Critical Examination of Candidates' Diversity Competence: Rigorous and Systematic Assessment of Candidates' Efficacy to Teach Diverse Student Populations

ERIC Educational Resources Information Center

Benton-Borghi, Beatrice Hope; Chang, Young Mi

2011-01-01

The National Center for Educational Statistics (NCES, 2010) continues to report substantial underachievement of diverse student populations in the nation's schools. After decades of focus on diversity and multicultural education, with integrating field and clinical practice, candidates continue to graduate without adequate knowledge, skills and…

State College- and Career-Ready High School Graduation Requirements. Updated

ERIC Educational Resources Information Center

Achieve, Inc., 2013

2013-01-01

Research by Achieve, ACT, and others suggests that for high school graduates to be prepared for success in a wide range of postsecondary settings, they need to take four years of challenging mathematics--covering Advanced Algebra; Geometry; and data, probability, and statistics content--and four years of rigorous English aligned with college- and…

High School Redesign. Diplomas Count, 2016. Education Week. Volume 35, Number 33

ERIC Educational Resources Information Center

Edwards, Virginia B., Ed.

2016-01-01

This year's report focuses on efforts to redesign high schools. Those include incorporating student voice, implementing a rigorous and relevant curriculum, embracing career exploration, and more. The report also includes the latest statistics on the nation's overall, on-time high school graduation rate. Articles include: (1) To Build a Better High…

Drug safety data mining with a tree-based scan statistic.

PubMed

Kulldorff, Martin; Dashevsky, Inna; Avery, Taliser R; Chan, Arnold K; Davis, Robert L; Graham, David; Platt, Richard; Andrade, Susan E; Boudreau, Denise; Gunter, Margaret J; Herrinton, Lisa J; Pawloski, Pamala A; Raebel, Marsha A; Roblin, Douglas; Brown, Jeffrey S

2013-05-01

In post-marketing drug safety surveillance, data mining can potentially detect rare but serious adverse events. Assessing an entire collection of drug-event pairs is traditionally performed on a predefined level of granularity. It is unknown a priori whether a drug causes a very specific or a set of related adverse events, such as mitral valve disorders, all valve disorders, or different types of heart disease. This methodological paper evaluates the tree-based scan statistic data mining method to enhance drug safety surveillance. We use a three-million-member electronic health records database from the HMO Research Network. Using the tree-based scan statistic, we assess the safety of selected antifungal and diabetes drugs, simultaneously evaluating overlapping diagnosis groups at different granularity levels, adjusting for multiple testing. Expected and observed adverse event counts were adjusted for age, sex, and health plan, producing a log likelihood ratio test statistic. Out of 732 evaluated disease groupings, 24 were statistically significant, divided among 10 non-overlapping disease categories. Five of the 10 signals are known adverse effects, four are likely due to confounding by indication, while one may warrant further investigation. The tree-based scan statistic can be successfully applied as a data mining tool in drug safety surveillance using observational data. The total number of statistical signals was modest and does not imply a causal relationship. Rather, data mining results should be used to generate candidate drug-event pairs for rigorous epidemiological studies to evaluate the individual and comparative safety profiles of drugs. Copyright © 2013 John Wiley & Sons, Ltd.

Estimation of the breaking of rigor mortis by myotonometry.

PubMed

Vain, A; Kauppila, R; Vuori, E

1996-05-31

Myotonometry was used to detect breaking of rigor mortis. The myotonometer is a new instrument which measures the decaying oscillations of a muscle after a brief mechanical impact. The method gives two numerical parameters for rigor mortis, namely the period and decrement of the oscillations, both of which depend on the time period elapsed after death. In the case of breaking the rigor mortis by muscle lengthening, both the oscillation period and decrement decreased, whereas, shortening the muscle caused the opposite changes. Fourteen h after breaking the stiffness characteristics of the right and left m. biceps brachii, or oscillation periods, were assimilated. However, the values for decrement of the muscle, reflecting the dissipation of mechanical energy, maintained their differences.

Resemblance profiles as clustering decision criteria: Estimating statistical power, error, and correspondence for a hypothesis test for multivariate structure.

PubMed

Kilborn, Joshua P; Jones, David L; Peebles, Ernst B; Naar, David F

2017-04-01

Clustering data continues to be a highly active area of data analysis, and resemblance profiles are being incorporated into ecological methodologies as a hypothesis testing-based approach to clustering multivariate data. However, these new clustering techniques have not been rigorously tested to determine the performance variability based on the algorithm's assumptions or any underlying data structures. Here, we use simulation studies to estimate the statistical error rates for the hypothesis test for multivariate structure based on dissimilarity profiles (DISPROF). We concurrently tested a widely used algorithm that employs the unweighted pair group method with arithmetic mean (UPGMA) to estimate the proficiency of clustering with DISPROF as a decision criterion. We simulated unstructured multivariate data from different probability distributions with increasing numbers of objects and descriptors, and grouped data with increasing overlap, overdispersion for ecological data, and correlation among descriptors within groups. Using simulated data, we measured the resolution and correspondence of clustering solutions achieved by DISPROF with UPGMA against the reference grouping partitions used to simulate the structured test datasets. Our results highlight the dynamic interactions between dataset dimensionality, group overlap, and the properties of the descriptors within a group (i.e., overdispersion or correlation structure) that are relevant to resemblance profiles as a clustering criterion for multivariate data. These methods are particularly useful for multivariate ecological datasets that benefit from distance-based statistical analyses. We propose guidelines for using DISPROF as a clustering decision tool that will help future users avoid potential pitfalls during the application of methods and the interpretation of results.

Statistically Assessing Time-Averaged and Paleosecular Variation Field Models Against Paleomagnetic Directional Data Sets. Can Likely non-Zonal Features be Detected in a Robust way ?

NASA Astrophysics Data System (ADS)

Hulot, G.; Khokhlov, A.

2007-12-01

We recently introduced a method to rigorously test the statistical compatibility of combined time-averaged (TAF) and paleosecular variation (PSV) field models against any lava flow paleomagnetic database (Khokhlov et al., 2001, 2006). Applying this method to test (TAF+PSV) models against synthetic data produced from those shows that the method is very efficient at discriminating models, and very sensitive, provided those data errors are properly taken into account. This prompted us to test a variety of published combined (TAF+PSV) models against a test Bruhnes stable polarity data set extracted from the Quidelleur et al. (1994) data base. Not surprisingly, ignoring data errors leads all models to be rejected. But taking data errors into account leads to the stimulating conclusion that at least one (TAF+PSV) model appears to be compatible with the selected data set, this model being purely axisymmetric. This result shows that in practice also, and with the data bases currently available, the method can discriminate various candidate models and decide which actually best fits a given data set. But it also shows that likely non-zonal signatures of non-homogeneous boundary conditions imposed by the mantle are difficult to identify as statistically robust from paleomagnetic directional data sets. In the present paper, we will discuss the possibility that such signatures could eventually be identified as robust with the help of more recent data sets (such as the one put together under the collaborative "TAFI" effort, see e.g. Johnson et al. abstract #GP21A-0013, AGU Fall Meeting, 2005) or by taking additional information into account (such as the possible coincidence of non-zonal time-averaged field patterns with analogous patterns in the modern field).

Identifying significant gene‐environment interactions using a combination of screening testing and hierarchical false discovery rate control

PubMed Central

Shen, Li; Saykin, Andrew J.; Williams, Scott M.; Moore, Jason H.

2016-01-01

ABSTRACT Although gene‐environment (G× E) interactions play an important role in many biological systems, detecting these interactions within genome‐wide data can be challenging due to the loss in statistical power incurred by multiple hypothesis correction. To address the challenge of poor power and the limitations of existing multistage methods, we recently developed a screening‐testing approach for G× E interaction detection that combines elastic net penalized regression with joint estimation to support a single omnibus test for the presence of G× E interactions. In our original work on this technique, however, we did not assess type I error control or power and evaluated the method using just a single, small bladder cancer data set. In this paper, we extend the original method in two important directions and provide a more rigorous performance evaluation. First, we introduce a hierarchical false discovery rate approach to formally assess the significance of individual G× E interactions. Second, to support the analysis of truly genome‐wide data sets, we incorporate a score statistic‐based prescreening step to reduce the number of single nucleotide polymorphisms prior to fitting the first stage penalized regression model. To assess the statistical properties of our method, we compare the type I error rate and statistical power of our approach with competing techniques using both simple simulation designs as well as designs based on real disease architectures. Finally, we demonstrate the ability of our approach to identify biologically plausible SNP‐education interactions relative to Alzheimer's disease status using genome‐wide association study data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). PMID:27578615

Performance Comparison of SDN Solutions for Switching Dedicated Long-Haul Connections

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rao, Nageswara S

2016-01-01

We consider scenarios with two sites connected over a dedicated, long-haul connection that must quickly fail-over in response to degradations in host-to-host application performance. We present two methods for path fail-over using OpenFlowenabled switches: (a) a light-weight method that utilizes host scripts to monitor the application performance and dpctl API for switching, and (b) a generic method that uses two OpenDaylight (ODL) controllers and REST interfaces. The restoration dynamics of the application contain significant statistical variations due to the controllers, north interfaces and switches; in addition, the variety of vendor implementations further complicates the choice between different solutions. We presentmore » the impulse-response method to estimate the regressions of performance parameters, which enables a rigorous and objective comparison of different solutions. We describe testing results of the two methods, using TCP throughput and connection rtt as main parameters, over a testbed consisting of HP and Cisco switches connected over longhaul connections emulated in hardware by ANUE devices. The combination of analytical and experimental results demonstrates that dpctl method responds seconds faster than ODL method on average, while both methods restore TCP throughput.« less

Critical evaluation of methods to incorporate entropy loss upon binding in high-throughput docking.

PubMed

Salaniwal, Sumeet; Manas, Eric S; Alvarez, Juan C; Unwalla, Rayomand J

2007-02-01

Proper accounting of the positional/orientational/conformational entropy loss associated with protein-ligand binding is important to obtain reliable predictions of binding affinity. Herein, we critically examine two simplified statistical mechanics-based approaches, namely a constant penalty per rotor method, and a more rigorous method, referred to here as the partition function-based scoring (PFS) method, to account for such entropy losses in high-throughput docking calculations. Our results on the estrogen receptor beta and dihydrofolate reductase proteins demonstrate that, while the constant penalty method over-penalizes molecules for their conformational flexibility, the PFS method behaves in a more "DeltaG-like" manner by penalizing different rotors differently depending on their residual entropy in the bound state. Furthermore, in contrast to no entropic penalty or the constant penalty approximation, the PFS method does not exhibit any bias towards either rigid or flexible molecules in the hit list. Preliminary enrichment studies using a lead-like random molecular database suggest that an accurate representation of the "true" energy landscape of the protein-ligand complex is critical for reliable predictions of relative binding affinities by the PFS method. Copyright 2006 Wiley-Liss, Inc.

A Two-Step Approach to Uncertainty Quantification of Core Simulators

DOE PAGES

Yankov, Artem; Collins, Benjamin; Klein, Markus; ...

2012-01-01

For the multiple sources of error introduced into the standard computational regime for simulating reactor cores, rigorous uncertainty analysis methods are available primarily to quantify the effects of cross section uncertainties. Two methods for propagating cross section uncertainties through core simulators are the XSUSA statistical approach and the “two-step” method. The XSUSA approach, which is based on the SUSA code package, is fundamentally a stochastic sampling method. Alternatively, the two-step method utilizes generalized perturbation theory in the first step and stochastic sampling in the second step. The consistency of these two methods in quantifying uncertainties in the multiplication factor andmore » in the core power distribution was examined in the framework of phase I-3 of the OECD Uncertainty Analysis in Modeling benchmark. With the Three Mile Island Unit 1 core as a base model for analysis, the XSUSA and two-step methods were applied with certain limitations, and the results were compared to those produced by other stochastic sampling-based codes. Based on the uncertainty analysis results, conclusions were drawn as to the method that is currently more viable for computing uncertainties in burnup and transient calculations.« less

Realizing Scientific Methods for Cyber Security

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carroll, Thomas E.; Manz, David O.; Edgar, Thomas W.

There is little doubt among cyber security researchers about the lack of scientic rigor that underlies much of the liter-ature. The issues are manifold and are well documented. Further complicating the problem is insufficient scientic methods to address these issues. Cyber security melds man and machine: we inherit the challenges of computer science, sociology, psychology, and many other elds and create new ones where these elds interface. In this paper we detail a partial list of challenges imposed by rigorous science and survey how other sciences have tackled them, in the hope of applying a similar approach to cyber securitymore » science. This paper is by no means comprehensive: its purpose is to foster discussion in the community on how we can improve rigor in cyber security science.« less

Central nervous system antiretroviral efficacy in HIV infection: a qualitative and quantitative review and implications for future research.

PubMed

Cysique, Lucette A; Waters, Edward K; Brew, Bruce J

2011-11-22

There is conflicting information as to whether antiretroviral drugs with better central nervous system (CNS) penetration (neuroHAART) assist in improving neurocognitive function and suppressing cerebrospinal fluid (CSF) HIV RNA. The current review aims to better synthesise existing literature by using an innovative two-phase review approach (qualitative and quantitative) to overcome methodological differences between studies. Sixteen studies, all observational, were identified using a standard citation search. They fulfilled the following inclusion criteria: conducted in the HAART era; sample size > 10; treatment effect involved more than one antiretroviral and none had a retrospective design. The qualitative phase of review of these studies consisted of (i) a blind assessment rating studies on features such as sample size, statistical methods and definitions of neuroHAART, and (ii) a non-blind assessment of the sensitivity of the neuropsychological methods to HIV-associated neurocognitive disorder (HAND). During quantitative evaluation we assessed the statistical power of studies, which achieved a high rating in the qualitative analysis. The objective of the power analysis was to determine the studies ability to assess their proposed research aims. After studies with at least three limitations were excluded in the qualitative phase, six studies remained. All six found a positive effect of neuroHAART on neurocognitive function or CSF HIV suppression. Of these six studies, only two had statistical power of at least 80%. Studies assessed as using more rigorous methods found that neuroHAART was effective in improving neurocognitive function and decreasing CSF viral load, but only two of those studies were adequately statistically powered. Because all of these studies were observational, they represent a less compelling evidence base than randomised control trials for assessing treatment effect. Therefore, large randomised trials are needed to determine the robustness of any neuroHAART effect. However, such trials must be longitudinal, include the full spectrum of HAND, ideally carefully control for co-morbidities, and be based on optimal neuropsychology methods.

Towards fast, rigorous and efficient conformational sampling of biomolecules: Advances in accelerated molecular dynamics.

PubMed

Doshi, Urmi; Hamelberg, Donald

2015-05-01

Accelerated molecular dynamics (aMD) has been proven to be a powerful biasing method for enhanced sampling of biomolecular conformations on general-purpose computational platforms. Biologically important long timescale events that are beyond the reach of standard molecular dynamics can be accessed without losing the detailed atomistic description of the system in aMD. Over other biasing methods, aMD offers the advantages of tuning the level of acceleration to access the desired timescale without any advance knowledge of the reaction coordinate. Recent advances in the implementation of aMD and its applications to small peptides and biological macromolecules are reviewed here along with a brief account of all the aMD variants introduced in the last decade. In comparison to the original implementation of aMD, the recent variant in which all the rotatable dihedral angles are accelerated (RaMD) exhibits faster convergence rates and significant improvement in statistical accuracy of retrieved thermodynamic properties. RaMD in conjunction with accelerating diffusive degrees of freedom, i.e. dual boosting, has been rigorously tested for the most difficult conformational sampling problem, protein folding. It has been shown that RaMD with dual boosting is capable of efficiently sampling multiple folding and unfolding events in small fast folding proteins. RaMD with the dual boost approach opens exciting possibilities for sampling multiple timescales in biomolecules. While equilibrium properties can be recovered satisfactorily from aMD-based methods, directly obtaining dynamics and kinetic rates for larger systems presents a future challenge. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014 Elsevier B.V. All rights reserved.

Peer Review Documents Related to the Evaluation of ...

EPA Pesticide Factsheets

BMDS is one of the Agency's premier tools for estimating risk assessments, therefore the validity and reliability of its statistical models are of paramount importance. This page provides links to peer review and expert summaries of the BMDS application and its models as they were developed and eventually released documenting the rigorous review process taken to provide the best science tools available for statistical modeling. This page provides links to peer reviews and expert summaries of the BMDS applications and its models as they were developed and eventually released.

Implementation and evaluation of an efficient secure computation system using ‘R’ for healthcare statistics

PubMed Central

Chida, Koji; Morohashi, Gembu; Fuji, Hitoshi; Magata, Fumihiko; Fujimura, Akiko; Hamada, Koki; Ikarashi, Dai; Yamamoto, Ryuichi

2014-01-01

Background and objective While the secondary use of medical data has gained attention, its adoption has been constrained due to protection of patient privacy. Making medical data secure by de-identification can be problematic, especially when the data concerns rare diseases. We require rigorous security management measures. Materials and methods Using secure computation, an approach from cryptography, our system can compute various statistics over encrypted medical records without decrypting them. An issue of secure computation is that the amount of processing time required is immense. We implemented a system that securely computes healthcare statistics from the statistical computing software ‘R’ by effectively combining secret-sharing-based secure computation with original computation. Results Testing confirmed that our system could correctly complete computation of average and unbiased variance of approximately 50 000 records of dummy insurance claim data in a little over a second. Computation including conditional expressions and/or comparison of values, for example, t test and median, could also be correctly completed in several tens of seconds to a few minutes. Discussion If medical records are simply encrypted, the risk of leaks exists because decryption is usually required during statistical analysis. Our system possesses high-level security because medical records remain in encrypted state even during statistical analysis. Also, our system can securely compute some basic statistics with conditional expressions using ‘R’ that works interactively while secure computation protocols generally require a significant amount of processing time. Conclusions We propose a secure statistical analysis system using ‘R’ for medical data that effectively integrates secret-sharing-based secure computation and original computation. PMID:24763677

Systematic review of the quality of prognosis studies in systemic lupus erythematosus.

PubMed

Lim, Lily S H; Lee, Senq J; Feldman, Brian M; Gladman, Dafna D; Pullenayegum, Eleanor; Uleryk, Elizabeth; Silverman, Earl D

2014-10-01

Prognosis studies examine outcomes and/or seek to identify predictors or factors associated with outcomes. Many prognostic factors have been identified in systemic lupus erythematosus (SLE), but few have been consistently found across studies. We hypothesized that this is due to a lack of rigor of study designs. This study aimed to systematically assess the methodologic quality of prognosis studies in SLE. A search of prognosis studies in SLE was performed using MEDLINE and Embase, from January 1990 to June 2011. A representative sample of 150 articles was selected using a random number generator and assessed by 2 reviewers. Each study was assessed by a risk of bias tool according to 6 domains: study participation, study attrition, measurement of prognostic factors, measurement of outcomes, measurement/adjustment for confounders, and appropriateness of statistical analysis. Information about missing data was also collected. A cohort design was used in 71% of studies. High risk of bias was found in 65% of studies for confounders, 57% for study participation, 56% for attrition, 36% for statistical analyses, 20% for prognostic factors, and 18% for outcome. Missing covariate or outcome information was present in half of the studies. Only 6 studies discussed reasons for missing data and 2 imputed missing data. Lack of rigorous study design, especially in addressing confounding, study participation and attrition, and inadequately handled missing data, has limited the quality of prognosis studies in SLE. Future prognosis studies should be designed with consideration of these factors to improve methodologic rigor. Copyright © 2014 by the American College of Rheumatology.

Polynomial probability distribution estimation using the method of moments

PubMed Central

Mattsson, Lars; Rydén, Jesper

2017-01-01

We suggest a procedure for estimating Nth degree polynomial approximations to unknown (or known) probability density functions (PDFs) based on N statistical moments from each distribution. The procedure is based on the method of moments and is setup algorithmically to aid applicability and to ensure rigor in use. In order to show applicability, polynomial PDF approximations are obtained for the distribution families Normal, Log-Normal, Weibull as well as for a bimodal Weibull distribution and a data set of anonymized household electricity use. The results are compared with results for traditional PDF series expansion methods of Gram–Charlier type. It is concluded that this procedure is a comparatively simple procedure that could be used when traditional distribution families are not applicable or when polynomial expansions of probability distributions might be considered useful approximations. In particular this approach is practical for calculating convolutions of distributions, since such operations become integrals of polynomial expressions. Finally, in order to show an advanced applicability of the method, it is shown to be useful for approximating solutions to the Smoluchowski equation. PMID:28394949

Polynomial probability distribution estimation using the method of moments.

PubMed

Munkhammar, Joakim; Mattsson, Lars; Rydén, Jesper

2017-01-01

We suggest a procedure for estimating Nth degree polynomial approximations to unknown (or known) probability density functions (PDFs) based on N statistical moments from each distribution. The procedure is based on the method of moments and is setup algorithmically to aid applicability and to ensure rigor in use. In order to show applicability, polynomial PDF approximations are obtained for the distribution families Normal, Log-Normal, Weibull as well as for a bimodal Weibull distribution and a data set of anonymized household electricity use. The results are compared with results for traditional PDF series expansion methods of Gram-Charlier type. It is concluded that this procedure is a comparatively simple procedure that could be used when traditional distribution families are not applicable or when polynomial expansions of probability distributions might be considered useful approximations. In particular this approach is practical for calculating convolutions of distributions, since such operations become integrals of polynomial expressions. Finally, in order to show an advanced applicability of the method, it is shown to be useful for approximating solutions to the Smoluchowski equation.

Shear Recovery Accuracy in Weak-Lensing Analysis with the Elliptical Gauss-Laguerre Method

NASA Astrophysics Data System (ADS)

Nakajima, Reiko; Bernstein, Gary

2007-04-01

We implement the elliptical Gauss-Laguerre (EGL) galaxy-shape measurement method proposed by Bernstein & Jarvis and quantify the shear recovery accuracy in weak-lensing analysis. This method uses a deconvolution fitting scheme to remove the effects of the point-spread function (PSF). The test simulates >107 noisy galaxy images convolved with anisotropic PSFs and attempts to recover an input shear. The tests are designed to be immune to statistical (random) distributions of shapes, selection biases, and crowding, in order to test more rigorously the effects of detection significance (signal-to-noise ratio [S/N]), PSF, and galaxy resolution. The systematic error in shear recovery is divided into two classes, calibration (multiplicative) and additive, with the latter arising from PSF anisotropy. At S/N > 50, the deconvolution method measures the galaxy shape and input shear to ~1% multiplicative accuracy and suppresses >99% of the PSF anisotropy. These systematic errors increase to ~4% for the worst conditions, with poorly resolved galaxies at S/N simeq 20. The EGL weak-lensing analysis has the best demonstrated accuracy to date, sufficient for the next generation of weak-lensing surveys.

On testing for spatial correspondence between maps of human brain structure and function.

PubMed

Alexander-Bloch, Aaron F; Shou, Haochang; Liu, Siyuan; Satterthwaite, Theodore D; Glahn, David C; Shinohara, Russell T; Vandekar, Simon N; Raznahan, Armin

2018-06-01

A critical issue in many neuroimaging studies is the comparison between brain maps. Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or spatial correspondence between two or more brain maps. This "correspondence problem" affects, for example, the interpretation of comparisons between task-based patterns of functional activation, resting-state networks or modules, and neuroanatomical landmarks. To date, this problem has been addressed with remarkable variability in terms of methodological approaches and statistical rigor. In this paper, we address the correspondence problem using a spatial permutation framework to generate null models of overlap by applying random rotations to spherical representations of the cortical surface, an approach for which we also provide a theoretical statistical foundation. We use this method to derive clusters of cognitive functions that are correlated in terms of their functional neuroatomical substrates. In addition, using publicly available data, we formally demonstrate the correspondence between maps of task-based functional activity, resting-state fMRI networks and gyral-based anatomical landmarks. We provide open-access code to implement the methods presented for two commonly-used tools for surface based cortical analysis (https://www.github.com/spin-test). This spatial permutation approach constitutes a useful advance over widely-used methods for the comparison of cortical maps, thereby opening new possibilities for the integration of diverse neuroimaging data. Copyright © 2018 Elsevier Inc. All rights reserved.

Resolving the problem of trapped water in binding cavities: prediction of host-guest binding free energies in the SAMPL5 challenge by funnel metadynamics

NASA Astrophysics Data System (ADS)

Bhakat, Soumendranath; Söderhjelm, Pär

2017-01-01

The funnel metadynamics method enables rigorous calculation of the potential of mean force along an arbitrary binding path and thereby evaluation of the absolute binding free energy. A problem of such physical paths is that the mechanism characterizing the binding process is not always obvious. In particular, it might involve reorganization of the solvent in the binding site, which is not easily captured with a few geometrically defined collective variables that can be used for biasing. In this paper, we propose and test a simple method to resolve this trapped-water problem by dividing the process into an artificial host-desolvation step and an actual binding step. We show that, under certain circumstances, the contribution from the desolvation step can be calculated without introducing further statistical errors. We apply the method to the problem of predicting host-guest binding free energies in the SAMPL5 blind challenge, using two octa-acid hosts and six guest molecules. For one of the hosts, well-converged results are obtained and the prediction of relative binding free energies is the best among all the SAMPL5 submissions. For the other host, which has a narrower binding pocket, the statistical uncertainties are slightly higher; longer simulations would therefore be needed to obtain conclusive results.

Investigating the feasibility of using partial least squares as a method of extracting salient information for the evaluation of digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Zhang, George Z.; Myers, Kyle J.; Park, Subok

2013-03-01

Digital breast tomosynthesis (DBT) has shown promise for improving the detection of breast cancer, but it has not yet been fully optimized due to a large space of system parameters to explore. A task-based statistical approach1 is a rigorous method for evaluating and optimizing this promising imaging technique with the use of optimal observers such as the Hotelling observer (HO). However, the high data dimensionality found in DBT has been the bottleneck for the use of a task-based approach in DBT evaluation. To reduce data dimensionality while extracting salient information for performing a given task, efficient channels have to be used for the HO. In the past few years, 2D Laguerre-Gauss (LG) channels, which are a complete basis for stationary backgrounds and rotationally symmetric signals, have been utilized for DBT evaluation2, 3 . But since background and signal statistics from DBT data are neither stationary nor rotationally symmetric, LG channels may not be efficient in providing reliable performance trends as a function of system parameters. Recently, partial least squares (PLS) has been shown to generate efficient channels for the Hotelling observer in detection tasks involving random backgrounds and signals.4 In this study, we investigate the use of PLS as a method for extracting salient information from DBT in order to better evaluate such systems.

Sunspot activity and influenza pandemics: a statistical assessment of the purported association.

PubMed

Towers, S

2017-10-01

Since 1978, a series of papers in the literature have claimed to find a significant association between sunspot activity and the timing of influenza pandemics. This paper examines these analyses, and attempts to recreate the three most recent statistical analyses by Ertel (1994), Tapping et al. (2001), and Yeung (2006), which all have purported to find a significant relationship between sunspot numbers and pandemic influenza. As will be discussed, each analysis had errors in the data. In addition, in each analysis arbitrary selections or assumptions were also made, and the authors did not assess the robustness of their analyses to changes in those arbitrary assumptions. Varying the arbitrary assumptions to other, equally valid, assumptions negates the claims of significance. Indeed, an arbitrary selection made in one of the analyses appears to have resulted in almost maximal apparent significance; changing it only slightly yields a null result. This analysis applies statistically rigorous methodology to examine the purported sunspot/pandemic link, using more statistically powerful un-binned analysis methods, rather than relying on arbitrarily binned data. The analyses are repeated using both the Wolf and Group sunspot numbers. In all cases, no statistically significant evidence of any association was found. However, while the focus in this particular analysis was on the purported relationship of influenza pandemics to sunspot activity, the faults found in the past analyses are common pitfalls; inattention to analysis reproducibility and robustness assessment are common problems in the sciences, that are unfortunately not noted often enough in review.

Statistical Approaches to Assess Biosimilarity from Analytical Data.

PubMed

Burdick, Richard; Coffey, Todd; Gutka, Hiten; Gratzl, Gyöngyi; Conlon, Hugh D; Huang, Chi-Ting; Boyne, Michael; Kuehne, Henriette

2017-01-01

Protein therapeutics have unique critical quality attributes (CQAs) that define their purity, potency, and safety. The analytical methods used to assess CQAs must be able to distinguish clinically meaningful differences in comparator products, and the most important CQAs should be evaluated with the most statistical rigor. High-risk CQA measurements assess the most important attributes that directly impact the clinical mechanism of action or have known implications for safety, while the moderate- to low-risk characteristics may have a lower direct impact and thereby may have a broader range to establish similarity. Statistical equivalence testing is applied for high-risk CQA measurements to establish the degree of similarity (e.g., highly similar fingerprint, highly similar, or similar) of selected attributes. Notably, some high-risk CQAs (e.g., primary sequence or disulfide bonding) are qualitative (e.g., the same as the originator or not the same) and therefore not amenable to equivalence testing. For biosimilars, an important step is the acquisition of a sufficient number of unique originator drug product lots to measure the variability in the originator drug manufacturing process and provide sufficient statistical power for the analytical data comparisons. Together, these analytical evaluations, along with PK/PD and safety data (immunogenicity), provide the data necessary to determine if the totality of the evidence warrants a designation of biosimilarity and subsequent licensure for marketing in the USA. In this paper, a case study approach is used to provide examples of analytical similarity exercises and the appropriateness of statistical approaches for the example data.

Launching Effectiveness Research to Guide Practice in Neurosurgery: A National Institute Neurological Disorders and Stroke Workshop Report

PubMed Central

Walicke, Patricia; Abosch, Aviva; Asher, Anthony; Barker, Fred G.; Ghogawala, Zoher; Harbaugh, Robert; Jehi, Lara; Kestle, John; Koroshetz, Walter; Little, Roderick; Rubin, Donald; Valadka, Alex; Wisniewski, Stephen

2017-01-01

Abstract This workshop addressed challenges of clinical research in neurosurgery. Randomized controlled clinical trials (RCTs) have high internal validity, but often insufficiently generalize to real-world practice. Observational studies are inclusive but often lack sufficient rigor. The workshop considered possible solutions, such as (1) statistical methods for demonstrating causality using observational data; (2) characteristics required of a registry supporting effectiveness research; (3) trial designs combining advantages of observational studies and RCTs; and (4) equipoise, an identified challenge for RCTs. In the future, advances in information technology potentially could lead to creation of a massive database where clinical data from all neurosurgeons are integrated and analyzed, ending the separation of clinical research and practice and leading to a new “science of practice.” PMID:28362926

Applications of satellite-derived disturbance information in support of sustainable forest management

Treesearch

Sean Healey; Warren Cohen; Gretchen Moisen

2007-01-01

The need for current information about the effects of fires, harvest, and storms is evident in many areas of sustainable forest management. While there are several potential sources of this information, each source has its limitations. Generally speaking, the statistical rigor associated with traditional forest sampling is an important asset in any monitoring effort....

Preschool Center Care Quality Effects on Academic Achievement: An Instrumental Variables Analysis

ERIC Educational Resources Information Center

Auger, Anamarie; Farkas, George; Burchinal, Margaret R.; Duncan, Greg J.; Vandell, Deborah Lowe

2014-01-01

Much of child care research has focused on the effects of the quality of care in early childhood settings on children's school readiness skills. Although researchers increased the statistical rigor of their approaches over the past 15 years, researchers' ability to draw causal inferences has been limited because the studies are based on…

Statistical linearization for multi-input/multi-output nonlinearities

NASA Technical Reports Server (NTRS)

Lin, Ching-An; Cheng, Victor H. L.

1991-01-01

Formulas are derived for the computation of the random input-describing functions for MIMO nonlinearities; these straightforward and rigorous derivations are based on the optimal mean square linear approximation. The computations involve evaluations of multiple integrals. It is shown that, for certain classes of nonlinearities, multiple-integral evaluations are obviated and the computations are significantly simplified.

Slow off the Mark: Elementary School Teachers and the Crisis in STEM Education

ERIC Educational Resources Information Center

Epstein, Diana; Miller, Raegen T.

2011-01-01

Prospective teachers can typically obtain a license to teach elementary school without taking a rigorous college-level STEM class such as calculus, statistics, or chemistry, and without demonstrating a solid grasp of mathematics knowledge, scientific knowledge, or the nature of scientific inquiry. This is not a recipe for ensuring students have…

Uncertainty quantification for nuclear density functional theory and information content of new measurements

DOE PAGES

McDonnell, J. D.; Schunck, N.; Higdon, D.; ...

2015-03-24

Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models, to estimate model errors and thereby improve predictive capability, to extrapolate beyond the regions reached by experiment, and to provide meaningful input to applications and planned measurements. To showcase new opportunities offered by such tools, we make a rigorous analysis of theoretical statistical uncertainties in nuclear density functional theory using Bayesian inference methods. By considering the recent mass measurements from the Canadian Penning Trap at Argonne National Laboratory, we demonstrate how the Bayesian analysis and a direct least-squaresmore » optimization, combined with high-performance computing, can be used to assess the information content of the new data with respect to a model based on the Skyrme energy density functional approach. Employing the posterior probability distribution computed with a Gaussian process emulator, we apply the Bayesian framework to propagate theoretical statistical uncertainties in predictions of nuclear masses, two-neutron dripline, and fission barriers. Overall, we find that the new mass measurements do not impose a constraint that is strong enough to lead to significant changes in the model parameters. In addition, the example discussed in this study sets the stage for quantifying and maximizing the impact of new measurements with respect to current modeling and guiding future experimental efforts, thus enhancing the experiment-theory cycle in the scientific method.« less

Uncertainty quantification for nuclear density functional theory and information content of new measurements

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDonnell, J. D.; Schunck, N.; Higdon, D.

2015-03-24

Statistical tools of uncertainty quantification can be used to assess the information content of measured observables with respect to present-day theoretical models, to estimate model errors and thereby improve predictive capability, to extrapolate beyond the regions reached by experiment, and to provide meaningful input to applications and planned measurements. To showcase new opportunities offered by such tools, we make a rigorous analysis of theoretical statistical uncertainties in nuclear density functional theory using Bayesian inference methods. By considering the recent mass measurements from the Canadian Penning Trap at Argonne National Laboratory, we demonstrate how the Bayesian analysis and a direct least-squaresmore » optimization, combined with high-performance computing, can be used to assess the information content of the new data with respect to a model based on the Skyrme energy density functional approach. Employing the posterior probability distribution computed with a Gaussian process emulator, we apply the Bayesian framework to propagate theoretical statistical uncertainties in predictions of nuclear masses, two-neutron dripline, and fission barriers. Overall, we find that the new mass measurements do not impose a constraint that is strong enough to lead to significant changes in the model parameters. As a result, the example discussed in this study sets the stage for quantifying and maximizing the impact of new measurements with respect to current modeling and guiding future experimental efforts, thus enhancing the experiment-theory cycle in the scientific method.« less

Unperturbed Schelling Segregation in Two or Three Dimensions

NASA Astrophysics Data System (ADS)

Barmpalias, George; Elwes, Richard; Lewis-Pye, Andrew

2016-09-01

Schelling's models of segregation, first described in 1969 (Am Econ Rev 59:488-493, 1969) are among the best known models of self-organising behaviour. Their original purpose was to identify mechanisms of urban racial segregation. But his models form part of a family which arises in statistical mechanics, neural networks, social science, and beyond, where populations of agents interact on networks. Despite extensive study, unperturbed Schelling models have largely resisted rigorous analysis, prior results generally focusing on variants in which noise is introduced into the dynamics, the resulting system being amenable to standard techniques from statistical mechanics or stochastic evolutionary game theory (Young in Individual strategy and social structure: an evolutionary theory of institutions, Princeton University Press, Princeton, 1998). A series of recent papers (Brandt et al. in: Proceedings of the 44th annual ACM symposium on theory of computing (STOC 2012), 2012); Barmpalias et al. in: 55th annual IEEE symposium on foundations of computer science, Philadelphia, 2014, J Stat Phys 158:806-852, 2015), has seen the first rigorous analyses of 1-dimensional unperturbed Schelling models, in an asymptotic framework largely unknown in statistical mechanics. Here we provide the first such analysis of 2- and 3-dimensional unperturbed models, establishing most of the phase diagram, and answering a challenge from Brandt et al. in: Proceedings of the 44th annual ACM symposium on theory of computing (STOC 2012), 2012).

Box-Counting Dimension Revisited: Presenting an Efficient Method of Minimizing Quantization Error and an Assessment of the Self-Similarity of Structural Root Systems

PubMed Central

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

Treetrimmer: a method for phylogenetic dataset size reduction.

PubMed

Maruyama, Shinichiro; Eveleigh, Robert J M; Archibald, John M

2013-04-12

With rapid advances in genome sequencing and bioinformatics, it is now possible to generate phylogenetic trees containing thousands of operational taxonomic units (OTUs) from a wide range of organisms. However, use of rigorous tree-building methods on such large datasets is prohibitive and manual 'pruning' of sequence alignments is time consuming and raises concerns over reproducibility. There is a need for bioinformatic tools with which to objectively carry out such pruning procedures. Here we present 'TreeTrimmer', a bioinformatics procedure that removes unnecessary redundancy in large phylogenetic datasets, alleviating the size effect on more rigorous downstream analyses. The method identifies and removes user-defined 'redundant' sequences, e.g., orthologous sequences from closely related organisms and 'recently' evolved lineage-specific paralogs. Representative OTUs are retained for more rigorous re-analysis. TreeTrimmer reduces the OTU density of phylogenetic trees without sacrificing taxonomic diversity while retaining the original tree topology, thereby speeding up downstream computer-intensive analyses, e.g., Bayesian and maximum likelihood tree reconstructions, in a reproducible fashion.

Thermostatted delta f

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krommes, J.A.

2000-01-18

The delta f simulation method is revisited. Statistical coarse-graining is used to rigorously derive the equation for the fluctuation delta f in the particle distribution. It is argued that completely collisionless simulation is incompatible with the achievement of true statistically steady states with nonzero turbulent fluxes because the variance of the particle weights w grows with time. To ensure such steady states, it is shown that for dynamically collisionless situations a generalized thermostat or W-stat may be used in lieu of a full collision operator to absorb the flow of entropy to unresolved fine scales in velocity space. The simplestmore » W-stat can be implemented as a self-consistently determined, time-dependent damping applied to w. A precise kinematic analogy to thermostatted nonequilibrium molecular dynamics (NEMD) is pointed out, and the justification of W-stats for simulations of turbulence is discussed. An extrapolation procedure is proposed such that the long-time, steady-state, collisionless flux can be deduced from several short W-statted runs with large effective collisionality, and a numerical demonstration is given.« less

Statistical thermodynamics unveils the dissolution mechanism of cellobiose.

PubMed

Nicol, Thomas W J; Isobe, Noriyuki; Clark, James H; Shimizu, Seishi

2017-08-30

In the study of the cellulose dissolution mechanism opinion is still divided. Here, the solution interaction components of the most prominent hypotheses for the driving force of cellulose dissolution were evaluated quantitatively. Combining a rigorous statistical thermodynamic theory and cellobiose solubility data in the presence of chloride salts, whose cations progress in the Hofmeister series (KCl, NaCl, LiCl and ZnCl 2 ), we have shown that cellobiose solubilization is driven by the preferential accumulation of salts around the solutes which is stronger than cellobiose hydration. Yet contrary to the classical chaotropy hypothesis, increasing salt concentration leads to cellobiose dehydration in the presence of the strongest solubilizer ZnCl 2 . However, thanks to cellobiose dehydration, cellobiose-salt interaction still remains preferential despite weakening salt accumulation. Based on such insights, the previous hypotheses based on hydrophobicity and polymer charging have also been evaluated quantitatively. Thus, our present study successfully paved a way towards identifying the basic driving forces for cellulose solubilization in a quantitative manner for the first time. When combined with unit additivity methods this quantitative information could lead to a full understanding of cellulose solubility.

A graphical user interface for RAId, a knowledge integrated proteomics analysis suite with accurate statistics.

PubMed

Joyce, Brendan; Lee, Danny; Rubio, Alex; Ogurtsov, Aleksey; Alves, Gelio; Yu, Yi-Kuo

2018-03-15

RAId is a software package that has been actively developed for the past 10 years for computationally and visually analyzing MS/MS data. Founded on rigorous statistical methods, RAId's core program computes accurate E-values for peptides and proteins identified during database searches. Making this robust tool readily accessible for the proteomics community by developing a graphical user interface (GUI) is our main goal here. We have constructed a graphical user interface to facilitate the use of RAId on users' local machines. Written in Java, RAId_GUI not only makes easy executions of RAId but also provides tools for data/spectra visualization, MS-product analysis, molecular isotopic distribution analysis, and graphing the retrieval versus the proportion of false discoveries. The results viewer displays and allows the users to download the analyses results. Both the knowledge-integrated organismal databases and the code package (containing source code, the graphical user interface, and a user manual) are available for download at https://www.ncbi.nlm.nih.gov/CBBresearch/Yu/downloads/raid.html .

Statistical tests and identifiability conditions for pooling and analyzing multisite datasets

PubMed Central

Zhou, Hao Henry; Singh, Vikas; Johnson, Sterling C.; Wahba, Grace

2018-01-01

When sample sizes are small, the ability to identify weak (but scientifically interesting) associations between a set of predictors and a response may be enhanced by pooling existing datasets. However, variations in acquisition methods and the distribution of participants or observations between datasets, especially due to the distributional shifts in some predictors, may obfuscate real effects when datasets are combined. We present a rigorous statistical treatment of this problem and identify conditions where we can correct the distributional shift. We also provide an algorithm for the situation where the correction is identifiable. We analyze various properties of the framework for testing model fit, constructing confidence intervals, and evaluating consistency characteristics. Our technical development is motivated by Alzheimer’s disease (AD) studies, and we present empirical results showing that our framework enables harmonizing of protein biomarkers, even when the assays across sites differ. Our contribution may, in part, mitigate a bottleneck that researchers face in clinical research when pooling smaller sized datasets and may offer benefits when the subjects of interest are difficult to recruit or when resources prohibit large single-site studies. PMID:29386387

Increasing rigor in NMR-based metabolomics through validated and open source tools

PubMed Central

Eghbalnia, Hamid R; Romero, Pedro R; Westler, William M; Baskaran, Kumaran; Ulrich, Eldon L; Markley, John L

2016-01-01

The metabolome, the collection of small molecules associated with an organism, is a growing subject of inquiry, with the data utilized for data-intensive systems biology, disease diagnostics, biomarker discovery, and the broader characterization of small molecules in mixtures. Owing to their close proximity to the functional endpoints that govern an organism’s phenotype, metabolites are highly informative about functional states. The field of metabolomics identifies and quantifies endogenous and exogenous metabolites in biological samples. Information acquired from nuclear magnetic spectroscopy (NMR), mass spectrometry (MS), and the published literature, as processed by statistical approaches, are driving increasingly wider applications of metabolomics. This review focuses on the role of databases and software tools in advancing the rigor, robustness, reproducibility, and validation of metabolomics studies. PMID:27643760

Increasing rigor in NMR-based metabolomics through validated and open source tools.

PubMed

Eghbalnia, Hamid R; Romero, Pedro R; Westler, William M; Baskaran, Kumaran; Ulrich, Eldon L; Markley, John L

2017-02-01

The metabolome, the collection of small molecules associated with an organism, is a growing subject of inquiry, with the data utilized for data-intensive systems biology, disease diagnostics, biomarker discovery, and the broader characterization of small molecules in mixtures. Owing to their close proximity to the functional endpoints that govern an organism's phenotype, metabolites are highly informative about functional states. The field of metabolomics identifies and quantifies endogenous and exogenous metabolites in biological samples. Information acquired from nuclear magnetic spectroscopy (NMR), mass spectrometry (MS), and the published literature, as processed by statistical approaches, are driving increasingly wider applications of metabolomics. This review focuses on the role of databases and software tools in advancing the rigor, robustness, reproducibility, and validation of metabolomics studies. Copyright © 2016. Published by Elsevier Ltd.

On statistical inference in time series analysis of the evolution of road safety.

PubMed

Commandeur, Jacques J F; Bijleveld, Frits D; Bergel-Hayat, Ruth; Antoniou, Constantinos; Yannis, George; Papadimitriou, Eleonora

2013-11-01

Data collected for building a road safety observatory usually include observations made sequentially through time. Examples of such data, called time series data, include annual (or monthly) number of road traffic accidents, traffic fatalities or vehicle kilometers driven in a country, as well as the corresponding values of safety performance indicators (e.g., data on speeding, seat belt use, alcohol use, etc.). Some commonly used statistical techniques imply assumptions that are often violated by the special properties of time series data, namely serial dependency among disturbances associated with the observations. The first objective of this paper is to demonstrate the impact of such violations to the applicability of standard methods of statistical inference, which leads to an under or overestimation of the standard error and consequently may produce erroneous inferences. Moreover, having established the adverse consequences of ignoring serial dependency issues, the paper aims to describe rigorous statistical techniques used to overcome them. In particular, appropriate time series analysis techniques of varying complexity are employed to describe the development over time, relating the accident-occurrences to explanatory factors such as exposure measures or safety performance indicators, and forecasting the development into the near future. Traditional regression models (whether they are linear, generalized linear or nonlinear) are shown not to naturally capture the inherent dependencies in time series data. Dedicated time series analysis techniques, such as the ARMA-type and DRAG approaches are discussed next, followed by structural time series models, which are a subclass of state space methods. The paper concludes with general recommendations and practice guidelines for the use of time series models in road safety research. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Recommended Procedure for Estimating the Cosmic-Ray Spectral Parameter of a Simple Power Law With Applications to Detector Design

NASA Technical Reports Server (NTRS)

Howell, L. W.

2001-01-01

A simple power law model consisting of a single spectral index alpha-1 is believed to be an adequate description of the galactic cosmic-ray (GCR) proton flux at energies below 10(exp 13) eV. Two procedures for estimating alpha-1 the method of moments and maximum likelihood (ML), are developed and their statistical performance compared. It is concluded that the ML procedure attains the most desirable statistical properties and is hence the recommended statistical estimation procedure for estimating alpha-1. The ML procedure is then generalized for application to a set of real cosmic-ray data and thereby makes this approach applicable to existing cosmic-ray data sets. Several other important results, such as the relationship between collecting power and detector energy resolution, as well as inclusion of a non-Gaussian detector response function, are presented. These results have many practical benefits in the design phase of a cosmic-ray detector as they permit instrument developers to make important trade studies in design parameters as a function of one of the science objectives. This is particularly important for space-based detectors where physical parameters, such as dimension and weight, impose rigorous practical limits to the design envelope.

Use of FEV1 in Cystic Fibrosis Epidemiologic Studies and Clinical Trials: A Statistical Perspective for the Clinical Researcher

PubMed Central

Szczesniak, Rhonda; Heltshe, Sonya L.; Stanojevic, Sanja; Mayer-Hamblett, Nicole

2017-01-01

Background Forced expiratory volume in 1 second (FEV1) is an established marker of cystic fibrosis (CF) disease progression that is used to capture clinical course and evaluate therapeutic efficacy. The research community has established FEV1 surveillance data through a variety of observational data sources such as patient registries, and there is a growing pipeline of new CF therapies demonstrated to be efficacious in clinical trials by establishing improvements in FEV1. Results In this review, we summarize from a statistical perspective the clinical relevance of FEV1 based on its association with morbidity and mortality in CF, its role in epidemiologic studies of disease progression and comparative effectiveness, and its utility in clinical trials. In addition, we identify opportunities to advance epidemiologic research and the clinical development pipeline through further statistical considerations. Conclusions Our understanding of CF disease course, therapeutics, and clinical care has evolved immensely in the past decades, in large part due to the thoughtful application of rigorous research methods and meaningful clinical endpoints such as FEV1. A continued commitment to conduct research that minimizes the potential for bias, maximizes the limited patient population, and harmonizes approaches to FEV1 analysis while maintaining clinical relevance, will facilitate further opportunities to advance CF care. PMID:28117136

A Solution Space for a System of Null-State Partial Differential Equations: Part 1

NASA Astrophysics Data System (ADS)

Flores, Steven M.; Kleban, Peter

2015-01-01

This article is the first of four that completely and rigorously characterize a solution space for a homogeneous system of 2 N + 3 linear partial differential equations (PDEs) in 2 N variables that arises in conformal field theory (CFT) and multiple Schramm-Löwner evolution (SLE). In CFT, these are null-state equations and conformal Ward identities. They govern partition functions for the continuum limit of a statistical cluster or loop-gas model, such as percolation, or more generally the Potts models and O( n) models, at the statistical mechanical critical point. (SLE partition functions also satisfy these equations.) For such a lattice model in a polygon with its 2 N sides exhibiting a free/fixed side-alternating boundary condition , this partition function is proportional to the CFT correlation function where the w i are the vertices of and where is a one-leg corner operator. (Partition functions for "crossing events" in which clusters join the fixed sides of in some specified connectivity are linear combinations of such correlation functions.) When conformally mapped onto the upper half-plane, methods of CFT show that this correlation function satisfies the system of PDEs that we consider. In this first article, we use methods of analysis to prove that the dimension of this solution space is no more than C N , the Nth Catalan number. While our motivations are based in CFT, our proofs are completely rigorous. This proof is contained entirely within this article, except for the proof of Lemma 14, which constitutes the second article (Flores and Kleban, in Commun Math Phys, arXiv:1404.0035, 2014). In the third article (Flores and Kleban, in Commun Math Phys, arXiv:1303.7182, 2013), we use the results of this article to prove that the solution space of this system of PDEs has dimension C N and is spanned by solutions constructed with the CFT Coulomb gas (contour integral) formalism. In the fourth article (Flores and Kleban, in Commun Math Phys, arXiv:1405.2747, 2014), we prove further CFT-related properties about these solutions, some useful for calculating cluster-crossing probabilities of critical lattice models in polygons.

A Comparison of Alternate Approaches to Creating Indices of Academic Rigor. Research Report 2012-11

ERIC Educational Resources Information Center

Beatty, Adam S.; Sackett, Paul R.; Kuncel, Nathan R.; Kiger, Thomas B.; Rigdon, Jana L.; Shen, Winny; Walmsley, Philip T.

2013-01-01

In recent decades, there has been an increasing emphasis placed on college graduation rates and reducing attrition due to the social and economic benefits, at both the individual and national levels, proposed to accrue from a more highly educated population (Bureau of Labor Statistics, 2011). In the United States in particular, there is a concern…

Comparing the Rigor of Compressed Format Courses to Their Regular Semester Counterparts

ERIC Educational Resources Information Center

Lutes, Lyndell; Davies, Randall

2013-01-01

This study compared workloads of undergraduate courses taught in 16-week and 8-week sessions. A statistically significant difference in workload was found between the two. Based on survey data from approximately 29,000 students, on average students spent about 17 minutes more per credit per week on 16-week courses than on similar 8-week courses.…

Statistical tests and measures for the presence and influence of digit preference

Treesearch

Jay Beaman; Grenier Michel

1998-01-01

Digit preference which is really showing preference for certain numbers has often described as the heaping or rounding of responses to numbers ending in zero or five. Number preference, NP, has been a topic in the social science literature for some years. However, until recently concepts were not adequately rigorously specified to allow, for example, the estimation of...

A new assessment of the alleged link between element 115 and element 117 decay chains

NASA Astrophysics Data System (ADS)

Forsberg, U.; Rudolph, D.; Fahlander, C.; Golubev, P.; Sarmiento, L. G.; Åberg, S.; Block, M.; Düllmann, Ch. E.; Heßberger, F. P.; Kratz, J. V.; Yakushev, A.

2016-09-01

A novel rigorous statistical treatment is applied to available data (May 9, 2016) from search and spectroscopy experiments on the elements with atomic numbers Z = 115 and Z = 117. The present analysis implies that the hitherto proposed cross-reaction link between α-decay chains associated with the isotopes 293117 and 289115 is highly improbable.

Uses of Multivariate Analytical Techniques in Online and Blended Business Education: An Assessment of Current Practice and Recommendations for Future Research

ERIC Educational Resources Information Center

Arbaugh, J. B.; Hwang, Alvin

2013-01-01

Seeking to assess the analytical rigor of empirical research in management education, this article reviews the use of multivariate statistical techniques in 85 studies of online and blended management education over the past decade and compares them with prescriptions offered by both the organization studies and educational research communities.…

Statistical rigor in LiDAR-assisted estimation of aboveground forest biomass

Treesearch

Timothy G. Gregoire; Erik Næsset; Ronald E. McRoberts; Göran Ståhl; Hans Andersen; Terje Gobakken; Liviu Ene; Ross Nelson

2016-01-01

For many decades remotely sensed data have been used as a source of auxiliary information when conducting regional or national surveys of forest resources. In the past decade, airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool for sample surveys aimed at improving estimation of aboveground forest biomass. This technology is now...

The Relationship between the Rigor of a State's Proficiency Standard and Student Achievement in the State

ERIC Educational Resources Information Center

Stoneberg, Bert D.

2015-01-01

The National Center of Education Statistics conducted a mapping study that equated the percentage proficient or above on each state's NCLB reading and mathematics tests in grades 4 and 8 to the NAEP scale. Each "NAEP equivalent score" was labeled according to NAEP's achievement levels and used to compare state proficiency standards and…

Bayesian Inference: with ecological applications

USGS Publications Warehouse

Link, William A.; Barker, Richard J.

2010-01-01

This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational efficiencies and easily accessible software to evaluate complex hierarchical models.

Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Goring, Simon

2017-01-01

Scientific records of temperature and precipitation have been kept for several hundred years, but for many areas, only a shorter record exists. To understand climate change, there is a need for rigorous statistical reconstructions of the paleoclimate using proxy data. Paleoclimate proxy data are often sparse, noisy, indirect measurements of the climate process of interest, making each proxy uniquely challenging to model statistically. We reconstruct spatially explicit temperature surfaces from sparse and noisy measurements recorded at historical United States military forts and other observer stations from 1820 to 1894. One common method for reconstructing the paleoclimate from proxy data is principal component regression (PCR). With PCR, one learns a statistical relationship between the paleoclimate proxy data and a set of climate observations that are used as patterns for potential reconstruction scenarios. We explore PCR in a Bayesian hierarchical framework, extending classical PCR in a variety of ways. First, we model the latent principal components probabilistically, accounting for measurement error in the observational data. Next, we extend our method to better accommodate outliers that occur in the proxy data. Finally, we explore alternatives to the truncation of lower-order principal components using different regularization techniques. One fundamental challenge in paleoclimate reconstruction efforts is the lack of out-of-sample data for predictive validation. Cross-validation is of potential value, but is computationally expensive and potentially sensitive to outliers in sparse data scenarios. To overcome the limitations that a lack of out-of-sample records presents, we test our methods using a simulation study, applying proper scoring rules including a computationally efficient approximation to leave-one-out cross-validation using the log score to validate model performance. The result of our analysis is a spatially explicit reconstruction of spatio-temporal temperature from a very sparse historical record.

A Bayesian nonparametric method for prediction in EST analysis

PubMed Central

Lijoi, Antonio; Mena, Ramsés H; Prünster, Igor

2007-01-01

Background Expressed sequence tags (ESTs) analyses are a fundamental tool for gene identification in organisms. Given a preliminary EST sample from a certain library, several statistical prediction problems arise. In particular, it is of interest to estimate how many new genes can be detected in a future EST sample of given size and also to determine the gene discovery rate: these estimates represent the basis for deciding whether to proceed sequencing the library and, in case of a positive decision, a guideline for selecting the size of the new sample. Such information is also useful for establishing sequencing efficiency in experimental design and for measuring the degree of redundancy of an EST library. Results In this work we propose a Bayesian nonparametric approach for tackling statistical problems related to EST surveys. In particular, we provide estimates for: a) the coverage, defined as the proportion of unique genes in the library represented in the given sample of reads; b) the number of new unique genes to be observed in a future sample; c) the discovery rate of new genes as a function of the future sample size. The Bayesian nonparametric model we adopt conveys, in a statistically rigorous way, the available information into prediction. Our proposal has appealing properties over frequentist nonparametric methods, which become unstable when prediction is required for large future samples. EST libraries, previously studied with frequentist methods, are analyzed in detail. Conclusion The Bayesian nonparametric approach we undertake yields valuable tools for gene capture and prediction in EST libraries. The estimators we obtain do not feature the kind of drawbacks associated with frequentist estimators and are reliable for any size of the additional sample. PMID:17868445

Computer vision-based evaluation of pre- and postrigor changes in size and shape of Atlantic cod (Gadus morhua) and Atlantic salmon (Salmo salar) fillets during rigor mortis and ice storage: effects of perimortem handling stress.

PubMed

Misimi, E; Erikson, U; Digre, H; Skavhaug, A; Mathiassen, J R

2008-03-01

The present study describes the possibilities for using computer vision-based methods for the detection and monitoring of transient 2D and 3D changes in the geometry of a given product. The rigor contractions of unstressed and stressed fillets of Atlantic salmon (Salmo salar) and Atlantic cod (Gadus morhua) were used as a model system. Gradual changes in fillet shape and size (area, length, width, and roundness) were recorded for 7 and 3 d, respectively. Also, changes in fillet area and height (cross-section profiles) were tracked using a laser beam and a 3D digital camera. Another goal was to compare rigor developments of the 2 species of farmed fish, and whether perimortem stress affected the appearance of the fillets. Some significant changes in fillet size and shape were found (length, width, area, roundness, height) between unstressed and stressed fish during the course of rigor mortis as well as after ice storage (postrigor). However, the observed irreversible stress-related changes were small and would hardly mean anything for postrigor fish processors or consumers. The cod were less stressed (as defined by muscle biochemistry) than the salmon after the 2 species had been subjected to similar stress bouts. Consequently, the difference between the rigor courses of unstressed and stressed fish was more extreme in the case of salmon. However, the maximal whole fish rigor strength was judged to be about the same for both species. Moreover, the reductions in fillet area and length, as well as the increases in width, were basically of similar magnitude for both species. In fact, the increases in fillet roundness and cross-section height were larger for the cod. We conclude that the computer vision method can be used effectively for automated monitoring of changes in 2D and 3D shape and size of fish fillets during rigor mortis and ice storage. In addition, it can be used for grading of fillets according to uniformity in size and shape, as well as measurement of fillet yield measured in thickness. The methods are accurate, rapid, nondestructive, and contact-free and can therefore be regarded as suitable for industrial purposes.

Assessing the Rigor of HS Curriculum in Admissions Decisions: A Functional Method, Plus Practical Advising for Prospective Students and High School Counselors

ERIC Educational Resources Information Center

Micceri, Theodore; Brigman, Leellen; Spatig, Robert

2009-01-01

An extensive, internally cross-validated analytical study using nested (within academic disciplines) Multilevel Modeling (MLM) on 4,560 students identified functional criteria for defining high school curriculum rigor and further determined which measures could best be used to help guide decision making for marginal applicants. The key outcome…

Rigorous coupled wave analysis of acousto-optics with relativistic considerations.

PubMed

Xia, Guoqiang; Zheng, Weijian; Lei, Zhenggang; Zhang, Ruolan

2015-09-01

A relativistic analysis of acousto-optics is presented, and a rigorous coupled wave analysis is generalized for the diffraction of the acousto-optical effect. An acoustic wave generates a grating with temporally and spatially modulated permittivity, hindering direct applications of the rigorous coupled wave analysis for the acousto-optical effect. In a reference frame which moves with the acoustic wave, the grating is static, the medium moves, and the coupled wave equations for the static grating may be derived. Floquet's theorem is then applied to cast these equations into an eigenproblem. Using a Lorentz transformation, the electromagnetic fields in the grating region are transformed to the lab frame where the medium is at rest, and relativistic Doppler frequency shifts are introduced into various diffraction orders. In the lab frame, the boundary conditions are considered and the diffraction efficiencies of various orders are determined. This method is rigorous and general, and the plane waves in the resulting expansion satisfy the dispersion relation of the medium and are propagation modes. Properties of various Bragg diffractions are results, rather than preconditions, of this method. Simulations of an acousto-optical tunable filter made by paratellurite, TeO(2), are given as examples.

Estimation of the time since death--reconsidering the re-establishment of rigor mortis.

PubMed

Anders, Sven; Kunz, Michaela; Gehl, Axel; Sehner, Susanne; Raupach, Tobias; Beck-Bornholdt, Hans-Peter

2013-01-01

In forensic medicine, there is an undefined data background for the phenomenon of re-establishment of rigor mortis after mechanical loosening, a method used in establishing time since death in forensic casework that is thought to occur up to 8 h post-mortem. Nevertheless, the method is widely described in textbooks on forensic medicine. We examined 314 joints (elbow and knee) of 79 deceased at defined time points up to 21 h post-mortem (hpm). Data were analysed using a random intercept model. Here, we show that re-establishment occurred in 38.5% of joints at 7.5 to 19 hpm. Therefore, the maximum time span for the re-establishment of rigor mortis appears to be 2.5-fold longer than thought so far. These findings have major impact on the estimation of time since death in forensic casework.

Misclassification of acute respiratory distress syndrome after traumatic injury: The cost of less rigorous approaches.

PubMed

Hendrickson, Carolyn M; Dobbins, Sarah; Redick, Brittney J; Greenberg, Molly D; Calfee, Carolyn S; Cohen, Mitchell Jay

2015-09-01

Adherence to rigorous research protocols for identifying adult respiratory distress syndrome (ARDS) after trauma is variable. To examine how misclassification of ARDS may bias observational studies in trauma populations, we evaluated the agreement of two methods for adjudicating ARDS after trauma: the current gold standard, direct review of chest radiographs and review of dictated radiology reports, a commonly used alternative. This nested cohort study included 123 mechanically ventilated patients between 2005 and 2008, with at least one PaO2/FIO2 less than 300 within the first 8 days of admission. Two blinded physician investigators adjudicated ARDS by two methods. The investigators directly reviewed all chest radiographs to evaluate for bilateral infiltrates. Several months later, blinded to their previous assessments, they adjudicated ARDS using a standardized rubric to classify radiology reports. A κ statistics was calculated. Regression analyses quantified the association between established risk factors as well as important clinical outcomes and ARDS determined by the aforementioned methods as well as hypoxemia as a surrogate marker. The κ was 0.47 for the observed agreement between ARDS adjudicated by direct review of chest radiographs and ARDS adjudicated by review of radiology reports. Both the magnitude and direction of bias on the estimates of association between ARDS and established risk factors as well as clinical outcomes varied by method of adjudication. Classification of ARDS by review of dictated radiology reports had only moderate agreement with the current gold standard, ARDS adjudicated by direct review of chest radiographs. While the misclassification of ARDS had varied effects on the estimates of associations with established risk factors, it tended to weaken the association of ARDS with important clinical outcomes. A standardized approach to ARDS adjudication after trauma by direct review of chest radiographs will minimize misclassification bias in future observational studies. Diagnostic study, level II.

A Novel Estimator for the Rate of Information Transfer by Continuous Signals

PubMed Central

Takalo, Jouni; Ignatova, Irina; Weckström, Matti; Vähäsöyrinki, Mikko

2011-01-01

The information transfer rate provides an objective and rigorous way to quantify how much information is being transmitted through a communications channel whose input and output consist of time-varying signals. However, current estimators of information content in continuous signals are typically based on assumptions about the system's linearity and signal statistics, or they require prohibitive amounts of data. Here we present a novel information rate estimator without these limitations that is also optimized for computational efficiency. We validate the method with a simulated Gaussian information channel and demonstrate its performance with two example applications. Information transfer between the input and output signals of a nonlinear system is analyzed using a sensory receptor neuron as the model system. Then, a climate data set is analyzed to demonstrate that the method can be applied to a system based on two outputs generated by interrelated random processes. These analyses also demonstrate that the new method offers consistent performance in situations where classical methods fail. In addition to these examples, the method is applicable to a wide range of continuous time series commonly observed in the natural sciences, economics and engineering. PMID:21494562

Phototherapy of the newborn: a predictive model for the outcome.

PubMed

Ossamu Osaku, Nelson; Silverio Lopes, Heitor

2005-01-01

Jaundice in one of the most common problems of the newborn. In most cases, jaundice is considered a physiological transient situation, but sometimes it can lead to death or serious injuries for the survivors. For decades, phototherapy has been used as the main method for prevention and treatment of hyperbilirubinaemia of the newborn. This work aims at finding a predictive model for the decrement of blood bilirubin followed conventional phototherapy. Data from 90 patients were collected and used in the multiple regression method. A rigorous statistical analysis was done in order to guarantee a correct and valid model. The obtained model was able to explain 78% of the variation of the dependent variable We found that it is possible to predict the total sugar bilirubin of the patient under phototherapy by knowing its birth weight, bilirubin level at the beginning of treatment, duration of exposition, and irradiance. Besides, it is possible to infer the time necessary for a given decrement of bilirubin, under approximately constant irradiance.

Free energy computations by minimization of Kullback-Leibler divergence: An efficient adaptive biasing potential method for sparse representations

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.

What can comparative effectiveness research, propensity score and registry study bring to Chinese medicine?

PubMed

Liao, Xing; Xie, Yan-ming

2014-10-01

The impact of evidence-based medicine and clinical epidemiology on clinical research has contributed to the development of Chinese medicine in modern times over the past two decades. Many concepts and methods of modern science and technology are emerging in Chinese medicine research, resulting in constant progress. Systematic reviews, randomized controlled trials and other advanced mathematic approaches and statistical analysis methods have brought reform to Chinese medicine. In this new era, Chinese medicine researchers have many opportunities and challenges. On the one hand, Chinese medicine researchers need to dedicate themselves to providing enough evidence to the world through rigorous studies, whilst on the other hand, they also need to keep up with the speed of modern medicine research. For example, recently, real world study, comparative effectiveness research, propensity score techniques and registry study have emerged. This article aims to inspire Chinese medicine researchers to explore new areas by introducing these new ideas and new techniques.

Model-based assessment of estuary ecosystem health using the latent health factor index, with application to the richibucto estuary.

PubMed

Chiu, Grace S; Wu, Margaret A; Lu, Lin

2013-01-01

The ability to quantitatively assess ecological health is of great interest to those tasked with monitoring and conserving ecosystems. For decades, biomonitoring research and policies have relied on multimetric health indices of various forms. Although indices are numbers, many are constructed based on qualitative procedures, thus limiting the quantitative rigor of the practical interpretations of such indices. The statistical modeling approach to construct the latent health factor index (LHFI) was recently developed. With ecological data that otherwise are used to construct conventional multimetric indices, the LHFI framework expresses such data in a rigorous quantitative model, integrating qualitative features of ecosystem health and preconceived ecological relationships among such features. This hierarchical modeling approach allows unified statistical inference of health for observed sites (along with prediction of health for partially observed sites, if desired) and of the relevance of ecological drivers, all accompanied by formal uncertainty statements from a single, integrated analysis. Thus far, the LHFI approach has been demonstrated and validated in a freshwater context. We adapt this approach to modeling estuarine health, and illustrate it on the previously unassessed system in Richibucto in New Brunswick, Canada, where active oyster farming is a potential stressor through its effects on sediment properties. Field data correspond to health metrics that constitute the popular AZTI marine biotic index and the infaunal trophic index, as well as abiotic predictors preconceived to influence biota. Our paper is the first to construct a scientifically sensible model that rigorously identifies the collective explanatory capacity of salinity, distance downstream, channel depth, and silt-clay content-all regarded a priori as qualitatively important abiotic drivers-towards site health in the Richibucto ecosystem. This suggests the potential effectiveness of the LHFI approach for assessing not only freshwater systems but aquatic ecosystems in general.

Optimal correction and design parameter search by modern methods of rigorous global optimization

NASA Astrophysics Data System (ADS)

Makino, K.; Berz, M.

2011-07-01

Frequently the design of schemes for correction of aberrations or the determination of possible operating ranges for beamlines and cells in synchrotrons exhibit multitudes of possibilities for their correction, usually appearing in disconnected regions of parameter space which cannot be directly qualified by analytical means. In such cases, frequently an abundance of optimization runs are carried out, each of which determines a local minimum depending on the specific chosen initial conditions. Practical solutions are then obtained through an often extended interplay of experienced manual adjustment of certain suitable parameters and local searches by varying other parameters. However, in a formal sense this problem can be viewed as a global optimization problem, i.e. the determination of all solutions within a certain range of parameters that lead to a specific optimum. For example, it may be of interest to find all possible settings of multiple quadrupoles that can achieve imaging; or to find ahead of time all possible settings that achieve a particular tune; or to find all possible manners to adjust nonlinear parameters to achieve correction of high order aberrations. These tasks can easily be phrased in terms of such an optimization problem; but while mathematically this formulation is often straightforward, it has been common belief that it is of limited practical value since the resulting optimization problem cannot usually be solved. However, recent significant advances in modern methods of rigorous global optimization make these methods feasible for optics design for the first time. The key ideas of the method lie in an interplay of rigorous local underestimators of the objective functions, and by using the underestimators to rigorously iteratively eliminate regions that lie above already known upper bounds of the minima, in what is commonly known as a branch-and-bound approach. Recent enhancements of the Differential Algebraic methods used in particle optics for the computation of aberrations allow the determination of particularly sharp underestimators for large regions. As a consequence, the subsequent progressive pruning of the allowed search space as part of the optimization progresses is carried out particularly effectively. The end result is the rigorous determination of the single or multiple optimal solutions of the parameter optimization, regardless of their location, their number, and the starting values of optimization. The methods are particularly powerful if executed in interplay with genetic optimizers generating their new populations within the currently active unpruned space. Their current best guess provides rigorous upper bounds of the minima, which can then beneficially be used for better pruning. Examples of the method and its performance will be presented, including the determination of all operating points of desired tunes or chromaticities, etc. in storage ring lattices.

A ground truth based comparative study on clustering of gene expression data.

PubMed

Zhu, Yitan; Wang, Zuyi; Miller, David J; Clarke, Robert; Xuan, Jianhua; Hoffman, Eric P; Wang, Yue

2008-05-01

Given the variety of available clustering methods for gene expression data analysis, it is important to develop an appropriate and rigorous validation scheme to assess the performance and limitations of the most widely used clustering algorithms. In this paper, we present a ground truth based comparative study on the functionality, accuracy, and stability of five data clustering methods, namely hierarchical clustering, K-means clustering, self-organizing maps, standard finite normal mixture fitting, and a caBIG toolkit (VIsual Statistical Data Analyzer--VISDA), tested on sample clustering of seven published microarray gene expression datasets and one synthetic dataset. We examined the performance of these algorithms in both data-sufficient and data-insufficient cases using quantitative performance measures, including cluster number detection accuracy and mean and standard deviation of partition accuracy. The experimental results showed that VISDA, an interactive coarse-to-fine maximum likelihood fitting algorithm, is a solid performer on most of the datasets, while K-means clustering and self-organizing maps optimized by the mean squared compactness criterion generally produce more stable solutions than the other methods.

Job attitudes, job satisfaction, and job affect: A century of continuity and of change.

PubMed

Judge, Timothy A; Weiss, Howard M; Kammeyer-Mueller, John D; Hulin, Charles L

2017-03-01

Over the past 100 years, research on job attitudes has improved in the sophistication of methods and in the productive use of theory as a basis for fundamental research into questions of work psychology. Early research incorporated a diversity of methods for measuring potential predictors and outcomes of job attitudes. Over time, methods for statistically assessing these relationships became more rigorous, but the field also became narrower. In recent years, developments in theory and methodology have reinvigorated research, which now addresses a rich panoply of topics related to the daily flow of affect, the complexity of personal motives and dispositions, and the complex interplay of attitude objects and motivation in shaping behavior. Despite these apparent changes, a review of the concepts and substantive arguments that underpin this literature have remained remarkably consistent. We conclude by discussing how we expect that these major themes will be addressed in the future, emphasizing topics that have proven to be enduring guides for understanding the ways that people construe and react to their appraisals of their work. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

On the assessment of the added value of new predictive biomarkers.

PubMed

Chen, Weijie; Samuelson, Frank W; Gallas, Brandon D; Kang, Le; Sahiner, Berkman; Petrick, Nicholas

2013-07-29

The surge in biomarker development calls for research on statistical evaluation methodology to rigorously assess emerging biomarkers and classification models. Recently, several authors reported the puzzling observation that, in assessing the added value of new biomarkers to existing ones in a logistic regression model, statistical significance of new predictor variables does not necessarily translate into a statistically significant increase in the area under the ROC curve (AUC). Vickers et al. concluded that this inconsistency is because AUC "has vastly inferior statistical properties," i.e., it is extremely conservative. This statement is based on simulations that misuse the DeLong et al. method. Our purpose is to provide a fair comparison of the likelihood ratio (LR) test and the Wald test versus diagnostic accuracy (AUC) tests. We present a test to compare ideal AUCs of nested linear discriminant functions via an F test. We compare it with the LR test and the Wald test for the logistic regression model. The null hypotheses of these three tests are equivalent; however, the F test is an exact test whereas the LR test and the Wald test are asymptotic tests. Our simulation shows that the F test has the nominal type I error even with a small sample size. Our results also indicate that the LR test and the Wald test have inflated type I errors when the sample size is small, while the type I error converges to the nominal value asymptotically with increasing sample size as expected. We further show that the DeLong et al. method tests a different hypothesis and has the nominal type I error when it is used within its designed scope. Finally, we summarize the pros and cons of all four methods we consider in this paper. We show that there is nothing inherently less powerful or disagreeable about ROC analysis for showing the usefulness of new biomarkers or characterizing the performance of classification models. Each statistical method for assessing biomarkers and classification models has its own strengths and weaknesses. Investigators need to choose methods based on the assessment purpose, the biomarker development phase at which the assessment is being performed, the available patient data, and the validity of assumptions behind the methodologies.

Equilibration, thermalisation, and the emergence of statistical mechanics in closed quantum systems

NASA Astrophysics Data System (ADS)

Gogolin, Christian; Eisert, Jens

2016-05-01

We review selected advances in the theoretical understanding of complex quantum many-body systems with regard to emergent notions of quantum statistical mechanics. We cover topics such as equilibration and thermalisation in pure state statistical mechanics, the eigenstate thermalisation hypothesis, the equivalence of ensembles, non-equilibration dynamics following global and local quenches as well as ramps. We also address initial state independence, absence of thermalisation, and many-body localisation. We elucidate the role played by key concepts for these phenomena, such as Lieb-Robinson bounds, entanglement growth, typicality arguments, quantum maximum entropy principles and the generalised Gibbs ensembles, and quantum (non-)integrability. We put emphasis on rigorous approaches and present the most important results in a unified language.

Equilibration, thermalisation, and the emergence of statistical mechanics in closed quantum systems.

PubMed

Gogolin, Christian; Eisert, Jens

2016-05-01

We review selected advances in the theoretical understanding of complex quantum many-body systems with regard to emergent notions of quantum statistical mechanics. We cover topics such as equilibration and thermalisation in pure state statistical mechanics, the eigenstate thermalisation hypothesis, the equivalence of ensembles, non-equilibration dynamics following global and local quenches as well as ramps. We also address initial state independence, absence of thermalisation, and many-body localisation. We elucidate the role played by key concepts for these phenomena, such as Lieb-Robinson bounds, entanglement growth, typicality arguments, quantum maximum entropy principles and the generalised Gibbs ensembles, and quantum (non-)integrability. We put emphasis on rigorous approaches and present the most important results in a unified language.

Statistical Models for Averaging of the Pump–Probe Traces: Example of Denoising in Terahertz Time-Domain Spectroscopy

NASA Astrophysics Data System (ADS)

Skorobogatiy, Maksim; Sadasivan, Jayesh; Guerboukha, Hichem

2018-05-01

In this paper, we first discuss the main types of noise in a typical pump-probe system, and then focus specifically on terahertz time domain spectroscopy (THz-TDS) setups. We then introduce four statistical models for the noisy pulses obtained in such systems, and detail rigorous mathematical algorithms to de-noise such traces, find the proper averages and characterise various types of experimental noise. Finally, we perform a comparative analysis of the performance, advantages and limitations of the algorithms by testing them on the experimental data collected using a particular THz-TDS system available in our laboratories. We conclude that using advanced statistical models for trace averaging results in the fitting errors that are significantly smaller than those obtained when only a simple statistical average is used.

Ensemble forecast of human West Nile virus cases and mosquito infection rates

NASA Astrophysics Data System (ADS)

Defelice, Nicholas B.; Little, Eliza; Campbell, Scott R.; Shaman, Jeffrey

2017-02-01

West Nile virus (WNV) is now endemic in the continental United States; however, our ability to predict spillover transmission risk and human WNV cases remains limited. Here we develop a model depicting WNV transmission dynamics, which we optimize using a data assimilation method and two observed data streams, mosquito infection rates and reported human WNV cases. The coupled model-inference framework is then used to generate retrospective ensemble forecasts of historical WNV outbreaks in Long Island, New York for 2001-2014. Accurate forecasts of mosquito infection rates are generated before peak infection, and >65% of forecasts accurately predict seasonal total human WNV cases up to 9 weeks before the past reported case. This work provides the foundation for implementation of a statistically rigorous system for real-time forecast of seasonal outbreaks of WNV.

Fish-Eye Observing with Phased Array Radio Telescopes

NASA Astrophysics Data System (ADS)

Wijnholds, S. J.

The radio astronomical community is currently developing and building several new radio telescopes based on phased array technology. These telescopes provide a large field-of-view, that may in principle span a full hemisphere. This makes calibration and imaging very challenging tasks due to the complex source structures and direction dependent radio wave propagation effects. In this thesis, calibration and imaging methods are developed based on least squares estimation of instrument and source parameters. Monte Carlo simulations and actual observations with several prototype show that this model based approach provides statistically and computationally efficient solutions. The error analysis provides a rigorous mathematical framework to assess the imaging performance of current and future radio telescopes in terms of the effective noise, which is the combined effect of propagated calibration errors, noise in the data and source confusion.

Ensemble forecast of human West Nile virus cases and mosquito infection rates.

PubMed

DeFelice, Nicholas B; Little, Eliza; Campbell, Scott R; Shaman, Jeffrey

2017-02-24

West Nile virus (WNV) is now endemic in the continental United States; however, our ability to predict spillover transmission risk and human WNV cases remains limited. Here we develop a model depicting WNV transmission dynamics, which we optimize using a data assimilation method and two observed data streams, mosquito infection rates and reported human WNV cases. The coupled model-inference framework is then used to generate retrospective ensemble forecasts of historical WNV outbreaks in Long Island, New York for 2001-2014. Accurate forecasts of mosquito infection rates are generated before peak infection, and >65% of forecasts accurately predict seasonal total human WNV cases up to 9 weeks before the past reported case. This work provides the foundation for implementation of a statistically rigorous system for real-time forecast of seasonal outbreaks of WNV.

Maximum likelihood: Extracting unbiased information from complex networks

NASA Astrophysics Data System (ADS)

Garlaschelli, Diego; Loffredo, Maria I.

2008-07-01

The choice of free parameters in network models is subjective, since it depends on what topological properties are being monitored. However, we show that the maximum likelihood (ML) principle indicates a unique, statistically rigorous parameter choice, associated with a well-defined topological feature. We then find that, if the ML condition is incompatible with the built-in parameter choice, network models turn out to be intrinsically ill defined or biased. To overcome this problem, we construct a class of safely unbiased models. We also propose an extension of these results that leads to the fascinating possibility to extract, only from topological data, the “hidden variables” underlying network organization, making them “no longer hidden.” We test our method on World Trade Web data, where we recover the empirical gross domestic product using only topological information.

Mathematical modelling of tumour volume dynamics in response to stereotactic ablative radiotherapy for non-small cell lung cancer

NASA Astrophysics Data System (ADS)

Tariq, Imran; Humbert-Vidan, Laia; Chen, Tao; South, Christopher P.; Ezhil, Veni; Kirkby, Norman F.; Jena, Rajesh; Nisbet, Andrew

2015-05-01

This paper reports a modelling study of tumour volume dynamics in response to stereotactic ablative radiotherapy (SABR). The main objective was to develop a model that is adequate to describe tumour volume change measured during SABR, and at the same time is not excessively complex as lacking support from clinical data. To this end, various modelling options were explored, and a rigorous statistical method, the Akaike information criterion, was used to help determine a trade-off between model accuracy and complexity. The models were calibrated to the data from 11 non-small cell lung cancer patients treated with SABR. The results showed that it is feasible to model the tumour volume dynamics during SABR, opening up the potential for using such models in a clinical environment in the future.

Comparison of Methods for Characterizing Nonideal Solute Self-Association by Sedimentation Equilibrium

PubMed Central

Scott, David J.; Winzor, Donald J.

2009-01-01

Abstract We have examined in detail analytical solutions of expressions for sedimentation equilibrium in the analytical ultracentrifuge to describe self-association under nonideal conditions. We find that those containing the radial dependence of total solute concentration that incorporate the Adams-Fujita assumption for composition-dependence of activity coefficients reveal potential shortcomings for characterizing such systems. Similar deficiencies are shown in the use of the NONLIN software incorporating the same assumption about the interrelationship between activity coefficients for monomer and polymer species. These difficulties can be overcome by iterative analyses incorporating expressions for the composition-dependence of activity coefficients predicted by excluded volume considerations. A recommendation is therefore made for the replacement of current software packages by programs that incorporate rigorous statistical-mechanical allowance for thermodynamic nonideality in sedimentation equilibrium distributions reflecting solute self-association. PMID:19651047

A psychometric evaluation of the digital logic concept inventory

NASA Astrophysics Data System (ADS)

Herman, Geoffrey L.; Zilles, Craig; Loui, Michael C.

2014-10-01

Concept inventories hold tremendous promise for promoting the rigorous evaluation of teaching methods that might remedy common student misconceptions and promote deep learning. The measurements from concept inventories can be trusted only if the concept inventories are evaluated both by expert feedback and statistical scrutiny (psychometric evaluation). Classical Test Theory and Item Response Theory provide two psychometric frameworks for evaluating the quality of assessment tools. We discuss how these theories can be applied to assessment tools generally and then apply them to the Digital Logic Concept Inventory (DLCI). We demonstrate that the DLCI is sufficiently reliable for research purposes when used in its entirety and as a post-course assessment of students' conceptual understanding of digital logic. The DLCI can also discriminate between students across a wide range of ability levels, providing the most information about weaker students' ability levels.

Compressive Network Analysis

PubMed Central

Jiang, Xiaoye; Yao, Yuan; Liu, Han; Guibas, Leonidas

2014-01-01

Modern data acquisition routinely produces massive amounts of network data. Though many methods and models have been proposed to analyze such data, the research of network data is largely disconnected with the classical theory of statistical learning and signal processing. In this paper, we present a new framework for modeling network data, which connects two seemingly different areas: network data analysis and compressed sensing. From a nonparametric perspective, we model an observed network using a large dictionary. In particular, we consider the network clique detection problem and show connections between our formulation with a new algebraic tool, namely Randon basis pursuit in homogeneous spaces. Such a connection allows us to identify rigorous recovery conditions for clique detection problems. Though this paper is mainly conceptual, we also develop practical approximation algorithms for solving empirical problems and demonstrate their usefulness on real-world datasets. PMID:25620806

A Randomized Study of How Physicians Interpret Research Funding Disclosures

PubMed Central

Kesselheim, Aaron S.; Robertson, Christopher T.; Myers, Jessica A.; Rose, Susannah L.; Gillet, Victoria; Ross, Kathryn M.; Glynn, Robert J.; Joffe, Steven; Avorn, Jerry

2012-01-01

BACKGROUND The effects of clinical-trial funding on the interpretation of trial results are poorly understood. We examined how such support affects physicians’ reactions to trials with a high, medium, or low level of methodologic rigor. METHODS We presented 503 board-certified internists with abstracts that we designed describing clinical trials of three hypothetical drugs. The trials had high, medium, or low methodologic rigor, and each report included one of three support disclosures: funding from a pharmaceutical company, NIH funding, or none. For both factors studied (rigor and funding), one of the three possible variations was randomly selected for inclusion in the abstracts. Follow-up questions assessed the physicians’ impressions of the trials’ rigor, their confidence in the results, and their willingness to prescribe the drugs. RESULTS The 269 respondents (53.5% response rate) perceived the level of study rigor accurately. Physicians reported that they would be less willing to prescribe drugs tested in low-rigor trials than those tested in medium-rigor trials (odds ratio, 0.64; 95% confidence interval [CI], 0.46 to 0.89; P = 0.008) and would be more willing to prescribe drugs tested in high-rigor trials than those tested in medium-rigor trials (odds ratio, 3.07; 95% CI, 2.18 to 4.32; P<0.001). Disclosure of industry funding, as compared with no disclosure of funding, led physicians to downgrade the rigor of a trial (odds ratio, 0.63; 95% CI, 0.46 to 0.87; P = 0.006), their confidence in the results (odds ratio, 0.71; 95% CI, 0.51 to 0.98; P = 0.04), and their willingness to prescribe the hypothetical drugs (odds ratio, 0.68; 95% CI, 0.49 to 0.94; P = 0.02). Physicians were half as willing to prescribe drugs studied in industry-funded trials as they were to prescribe drugs studied in NIH-funded trials (odds ratio, 0.52; 95% CI, 0.37 to 0.71; P<0.001). These effects were consistent across all levels of methodologic rigor. CONCLUSIONS Physicians discriminate among trials of varying degrees of rigor, but industry sponsorship negatively influences their perception of methodologic quality and reduces their willingness to believe and act on trial findings, independently of the trial’s quality. These effects may influence the translation of clinical research into practice. PMID:22992075

How to Map Theory: Reliable Methods Are Fruitless Without Rigorous Theory.

PubMed

Gray, Kurt

2017-09-01

Good science requires both reliable methods and rigorous theory. Theory allows us to build a unified structure of knowledge, to connect the dots of individual studies and reveal the bigger picture. Some have criticized the proliferation of pet "Theories," but generic "theory" is essential to healthy science, because questions of theory are ultimately those of validity. Although reliable methods and rigorous theory are synergistic, Action Identification suggests psychological tension between them: The more we focus on methodological details, the less we notice the broader connections. Therefore, psychology needs to supplement training in methods (how to design studies and analyze data) with training in theory (how to connect studies and synthesize ideas). This article provides a technique for visually outlining theory: theory mapping. Theory mapping contains five elements, which are illustrated with moral judgment and with cars. Also included are 15 additional theory maps provided by experts in emotion, culture, priming, power, stress, ideology, morality, marketing, decision-making, and more (see all at theorymaps.org ). Theory mapping provides both precision and synthesis, which helps to resolve arguments, prevent redundancies, assess the theoretical contribution of papers, and evaluate the likelihood of surprising effects.

Theory of the Decoherence Effect in Finite and Infinite Open Quantum Systems Using the Algebraic Approach

NASA Astrophysics Data System (ADS)

Blanchard, Philippe; Hellmich, Mario; Ługiewicz, Piotr; Olkiewicz, Robert

Quantum mechanics is the greatest revision of our conception of the character of the physical world since Newton. Consequently, David Hilbert was very interested in quantum mechanics. He and John von Neumann discussed it frequently during von Neumann's residence in Göttingen. He published in 1932 his book Mathematical Foundations of Quantum Mechanics. In Hilbert's opinion it was the first exposition of quantum mechanics in a mathematically rigorous way. The pioneers of quantum mechanics, Heisenberg and Dirac, neither had use for rigorous mathematics nor much interest in it. Conceptually, quantum theory as developed by Bohr and Heisenberg is based on the positivism of Mach as it describes only observable quantities. It first emerged as a result of experimental data in the form of statistical observations of quantum noise, the basic concept of quantum probability.

Statistical Analysis of the Processes Controlling Choline and Ethanolamine Glycerophospholipid Molecular Species Composition

PubMed Central

Kiebish, Michael A.; Yang, Kui; Han, Xianlin; Gross, Richard W.; Chuang, Jeffrey

2012-01-01

The regulation and maintenance of the cellular lipidome through biosynthetic, remodeling, and catabolic mechanisms are critical for biological homeostasis during development, health and disease. These complex mechanisms control the architectures of lipid molecular species, which have diverse yet highly regulated fatty acid chains at both the sn1 and sn2 positions. Phosphatidylcholine (PC) and phosphatidylethanolamine (PE) serve as the predominant biophysical scaffolds in membranes, acting as reservoirs for potent lipid signals and regulating numerous enzymatic processes. Here we report the first rigorous computational dissection of the mechanisms influencing PC and PE molecular architectures from high-throughput shotgun lipidomic data. Using novel statistical approaches, we have analyzed multidimensional mass spectrometry-based shotgun lipidomic data from developmental mouse heart and mature mouse heart, lung, brain, and liver tissues. We show that in PC and PE, sn1 and sn2 positions are largely independent, though for low abundance species regulatory processes may interact with both the sn1 and sn2 chain simultaneously, leading to cooperative effects. Chains with similar biochemical properties appear to be remodeled similarly. We also see that sn2 positions are more regulated than sn1, and that PC exhibits stronger cooperative effects than PE. A key aspect of our work is a novel statistically rigorous approach to determine cooperativity based on a modified Fisher's exact test using Markov Chain Monte Carlo sampling. This computational approach provides a novel tool for developing mechanistic insight into lipidomic regulation. PMID:22662143

PCA as a practical indicator of OPLS-DA model reliability.

PubMed

Worley, Bradley; Powers, Robert

Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) are powerful statistical modeling tools that provide insights into separations between experimental groups based on high-dimensional spectral measurements from NMR, MS or other analytical instrumentation. However, when used without validation, these tools may lead investigators to statistically unreliable conclusions. This danger is especially real for Partial Least Squares (PLS) and OPLS, which aggressively force separations between experimental groups. As a result, OPLS-DA is often used as an alternative method when PCA fails to expose group separation, but this practice is highly dangerous. Without rigorous validation, OPLS-DA can easily yield statistically unreliable group separation. A Monte Carlo analysis of PCA group separations and OPLS-DA cross-validation metrics was performed on NMR datasets with statistically significant separations in scores-space. A linearly increasing amount of Gaussian noise was added to each data matrix followed by the construction and validation of PCA and OPLS-DA models. With increasing added noise, the PCA scores-space distance between groups rapidly decreased and the OPLS-DA cross-validation statistics simultaneously deteriorated. A decrease in correlation between the estimated loadings (added noise) and the true (original) loadings was also observed. While the validity of the OPLS-DA model diminished with increasing added noise, the group separation in scores-space remained basically unaffected. Supported by the results of Monte Carlo analyses of PCA group separations and OPLS-DA cross-validation metrics, we provide practical guidelines and cross-validatory recommendations for reliable inference from PCA and OPLS-DA models.

Time Scale Optimization and the Hunt for Astronomical Cycles in Deep Time Strata

NASA Astrophysics Data System (ADS)

Meyers, Stephen R.

2016-04-01

A valuable attribute of astrochronology is the direct link between chronometer and climate change, providing a remarkable opportunity to constrain the evolution of the surficial Earth System. Consequently, the hunt for astronomical cycles in strata has spurred the development of a rich conceptual framework for climatic/oceanographic change, and has allowed exploration of the geologic record with unprecedented temporal resolution. Accompanying these successes, however, has been a persistent skepticism about appropriate astrochronologic testing and circular reasoning: how does one reliably test for astronomical cycles in stratigraphic data, especially when time is poorly constrained? From this perspective, it would seem that the merits and promise of astrochronology (e.g., a geologic time scale measured in ≤400 kyr increments) also serves as its Achilles heel, if the confirmation of such short rhythms defies rigorous statistical testing. To address these statistical challenges in astrochronologic testing, a new approach has been developed that (1) explicitly evaluates time scale uncertainty, (2) is resilient to common problems associated with spectrum confidence level assessment and 'multiple testing', and (3) achieves high statistical power under a wide range of conditions (it can identify astronomical cycles when present in data). Designated TimeOpt (for "time scale optimization"; Meyers 2015), the method employs a probabilistic linear regression model framework to investigate amplitude modulation and frequency ratios (bundling) in stratigraphic data, while simultaneously determining the optimal time scale. This presentation will review the TimeOpt method, and demonstrate how the flexible statistical framework can be further extended to evaluate (and optimize upon) complex sedimentation rate models, enhancing the statistical power of the approach, and addressing the challenge of unsteady sedimentation. Meyers, S. R. (2015), The evaluation of eccentricity-related amplitude modulation and bundling in paleoclimate data: An inverse approach for astrochronologic testing and time scale optimization, Paleoceanography, 30, doi:10.1002/ 2015PA002850.

Decomposition of the Inequality of Income Distribution by Income Types—Application for Romania

NASA Astrophysics Data System (ADS)

Andrei, Tudorel; Oancea, Bogdan; Richmond, Peter; Dhesi, Gurjeet; Herteliu, Claudiu

2017-09-01

This paper identifies the salient factors that characterize the inequality income distribution for Romania. Data analysis is rigorously carried out using sophisticated techniques borrowed from classical statistics (Theil). Decomposition of the inequalities measured by the Theil index is also performed. This study relies on an exhaustive (11.1 million records for 2014) data-set for total personal gross income of Romanian citizens.

Not so Fast My Friend: The Rush to R and the Need for Rigorous Evaluation of Data Analysis and Software in Education

ERIC Educational Resources Information Center

Harwell, Michael

2014-01-01

Commercial data analysis software has been a fixture of quantitative analyses in education for more than three decades. Despite its apparent widespread use there is no formal evidence cataloging what software is used in educational research and educational statistics classes, by whom and for what purpose, and whether some programs should be…

Comparative evaluation of spectroscopic models using different multivariate statistical tools in a multicancer scenario

NASA Astrophysics Data System (ADS)

Ghanate, A. D.; Kothiwale, S.; Singh, S. P.; Bertrand, Dominique; Krishna, C. Murali

2011-02-01

Cancer is now recognized as one of the major causes of morbidity and mortality. Histopathological diagnosis, the gold standard, is shown to be subjective, time consuming, prone to interobserver disagreement, and often fails to predict prognosis. Optical spectroscopic methods are being contemplated as adjuncts or alternatives to conventional cancer diagnostics. The most important aspect of these approaches is their objectivity, and multivariate statistical tools play a major role in realizing it. However, rigorous evaluation of the robustness of spectral models is a prerequisite. The utility of Raman spectroscopy in the diagnosis of cancers has been well established. Until now, the specificity and applicability of spectral models have been evaluated for specific cancer types. In this study, we have evaluated the utility of spectroscopic models representing normal and malignant tissues of the breast, cervix, colon, larynx, and oral cavity in a broader perspective, using different multivariate tests. The limit test, which was used in our earlier study, gave high sensitivity but suffered from poor specificity. The performance of other methods such as factorial discriminant analysis and partial least square discriminant analysis are at par with more complex nonlinear methods such as decision trees, but they provide very little information about the classification model. This comparative study thus demonstrates not just the efficacy of Raman spectroscopic models but also the applicability and limitations of different multivariate tools for discrimination under complex conditions such as the multicancer scenario.

Recommendations for the Design and Analysis of Treatment Trials for Alcohol Use Disorders

PubMed Central

Witkiewitz, Katie; Finney, John W.; Harris, Alex H.S; Kivlahan, Daniel R.; Kranzler, Henry R.

2015-01-01

Background Over the past 60 years the view that “alcoholism” is a disease for which the only acceptable goal of treatment is abstinence has given way to the recognition that alcohol use disorders (AUDs) occur on a continuum of severity, for which a variety of treatment options are appropriate. However, because the available treatments for AUDs are not effective for everyone, more research is needed to develop novel and more efficacious treatments to address the range of AUD severity in diverse populations. Here we offer recommendations for the design and analysis of alcohol treatment trials, with a specific focus on the careful conduct of randomized clinical trials of medications and non-pharmacological interventions for AUDs. Methods Narrative review of the quality of published clinical trials and recommendations for the optimal design and analysis of treatment trials for AUDs. Results Despite considerable improvements in the design of alcohol clinical trials over the past two decades, many studies of AUD treatments have used faulty design features and statistical methods that are known to produce biased estimates of treatment efficacy. Conclusions The published statistical and methodological literatures provide clear guidance on methods to improve clinical trial design and analysis. Consistent use of state-of-the-art design features and analytic approaches will enhance the internal and external validity of treatment trials for AUDs across the spectrum of severity. The ultimate result of this attention to methodological rigor is that better treatment options will be identified for patients with an AUD. PMID:26250333

A novel alignment-free method for detection of lateral genetic transfer based on TF-IDF.

PubMed

Cong, Yingnan; Chan, Yao-Ban; Ragan, Mark A

2016-07-25

Lateral genetic transfer (LGT) plays an important role in the evolution of microbes. Existing computational methods for detecting genomic regions of putative lateral origin scale poorly to large data. Here, we propose a novel method based on TF-IDF (Term Frequency-Inverse Document Frequency) statistics to detect not only regions of lateral origin, but also their origin and direction of transfer, in sets of hierarchically structured nucleotide or protein sequences. This approach is based on the frequency distributions of k-mers in the sequences. If a set of contiguous k-mers appears sufficiently more frequently in another phyletic group than in its own, we infer that they have been transferred from the first group to the second. We performed rigorous tests of TF-IDF using simulated and empirical datasets. With the simulated data, we tested our method under different parameter settings for sequence length, substitution rate between and within groups and post-LGT, deletion rate, length of transferred region and k size, and found that we can detect LGT events with high precision and recall. Our method performs better than an established method, ALFY, which has high recall but low precision. Our method is efficient, with runtime increasing approximately linearly with sequence length.

Electron microscopic quantification of collagen fibril diameters in the rabbit medial collateral ligament: a baseline for comparison.

PubMed

Frank, C; Bray, D; Rademaker, A; Chrusch, C; Sabiston, P; Bodie, D; Rangayyan, R

1989-01-01

To establish a normal baseline for comparison, thirty-one thousand collagen fibril diameters were measured in calibrated transmission electron (TEM) photomicrographs of normal rabbit medial collateral ligaments (MCL's). A new automated method of quantitation was used to compare statistically fibril minimum diameter distributions in one midsubstance location in both MCL's from six animals at 3 months of age (immature) and three animals at 10 months of age (mature). Pooled results demonstrate that rabbit MCL's have statistically different (p less than 0.001) mean minimum diameters at these two ages. Interanimal differences in mean fibril minimum diameters were also significant (p less than 0.001) and varied by 20% to 25% in both mature and immature animals. Finally, there were significant differences (p less than 0.001) in mean diameters and distributions from side-to-side in all animals. These mean left-to-right differences were less than 10% in all mature animals but as much as 62% in some immature animals. Statistical analysis of these data demonstrate that animal-to-animal comparisons using these protocols require a large number of animals with appropriate numbers of fibrils being measured to detect small intergroup differences. With experiments which compare left to right ligaments, far fewer animals are required to detect similarly small differences. These results demonstrate the necessity for rigorous control of sampling, an extensive normal baseline and statistically confirmed experimental designs in any TEM comparisons of collagen fibril diameters.

Comprehensive analysis of yeast metabolite GC x GC-TOFMS data: combining discovery-mode and deconvolution chemometric software.

PubMed

Mohler, Rachel E; Dombek, Kenneth M; Hoggard, Jamin C; Pierce, Karisa M; Young, Elton T; Synovec, Robert E

2007-08-01

The first extensive study of yeast metabolite GC x GC-TOFMS data from cells grown under fermenting, R, and respiring, DR, conditions is reported. In this study, recently developed chemometric software for use with three-dimensional instrumentation data was implemented, using a statistically-based Fisher ratio method. The Fisher ratio method is fully automated and will rapidly reduce the data to pinpoint two-dimensional chromatographic peaks differentiating sample types while utilizing all the mass channels. The effect of lowering the Fisher ratio threshold on peak identification was studied. At the lowest threshold (just above the noise level), 73 metabolite peaks were identified, nearly three-fold greater than the number of previously reported metabolite peaks identified (26). In addition to the 73 identified metabolites, 81 unknown metabolites were also located. A Parallel Factor Analysis graphical user interface (PARAFAC GUI) was applied to selected mass channels to obtain a concentration ratio, for each metabolite under the two growth conditions. Of the 73 known metabolites identified by the Fisher ratio method, 54 were statistically changing to the 95% confidence limit between the DR and R conditions according to the rigorous Student's t-test. PARAFAC determined the concentration ratio and provided a fully-deconvoluted (i.e. mathematically resolved) mass spectrum for each of the metabolites. The combination of the Fisher ratio method with the PARAFAC GUI provides high-throughput software for discovery-based metabolomics research, and is novel for GC x GC-TOFMS data due to the use of the entire data set in the analysis (640 MB x 70 runs, double precision floating point).

Optical methods in nano-biotechnology

NASA Astrophysics Data System (ADS)

Bruno, Luigi; Gentile, Francesco

2016-01-01

A scientific theory is not a mathematical paradigm. It is a framework that explains natural facts and may predict future observations. A scientific theory may be modified, improved, or rejected. Science is less a collection of theories and more the process that brings either to deny some hypothesis, maintain or accept somehow universal beliefs (or disbeliefs), and create new models that may improve or replace precedent theories. This process cannot be entrusted to common sense, personal experiences or anecdotes (many precepts in physics are indeed counterintuitive), but on a rigorous design, observation and rational to statistical analysis of new experiments. Scientific results are always provisional: scientists rarely proclaim an absolute truth or absolute certainty. Uncertainty is inevitable at the frontiers of knowledge. Notably, this is the definition of the scientific method and what we have written in the above echoes the opinion Marcia McNutt who is the Editor of Science 'Science is a method for deciding whether what we choose to believe has a basis in the laws of nature or not'. A new discovery, a new theory that explains that discovery and the scientific method itself need observations, verifications and are susceptible of falsification.

A Model Based Deconvolution Approach for Creating Surface Composition Maps of Irregularly Shaped Bodies from Limited Orbiting Nuclear Spectrometer Measurements

NASA Astrophysics Data System (ADS)

Dallmann, N. A.; Carlsten, B. E.; Stonehill, L. C.

2017-12-01

Orbiting nuclear spectrometers have contributed significantly to our understanding of the composition of solar system bodies. Gamma rays and neutrons are produced within the surfaces of bodies by impacting galactic cosmic rays (GCR) and by intrinsic radionuclide decay. Measuring the flux and energy spectrum of these products at one point in an orbit elucidates the elemental content of the area in view. Deconvolution of measurements from many spatially registered orbit points can produce detailed maps of elemental abundances. In applying these well-established techniques to small and irregularly shaped bodies like Phobos, one encounters unique challenges beyond those of a large spheroid. Polar mapping orbits are not possible for Phobos and quasistatic orbits will realize only modest inclinations unavoidably limiting surface coverage and creating North-South ambiguities in deconvolution. The irregular shape causes self-shadowing both of the body to the spectrometer but also of the body to the incoming GCR. The view angle to the surface normal as well as the distance between the surface and the spectrometer is highly irregular. These characteristics can be synthesized into a complicated and continuously changing measurement system point spread function. We have begun to explore different model-based, statistically rigorous, iterative deconvolution methods to produce elemental abundance maps for a proposed future investigation of Phobos. By incorporating the satellite orbit, the existing high accuracy shape-models of Phobos, and the spectrometer response function, a detailed and accurate system model can be constructed. Many aspects of this model formation are particularly well suited to modern graphics processing techniques and parallel processing. We will present the current status and preliminary visualizations of the Phobos measurement system model. We will also discuss different deconvolution strategies and their relative merit in statistical rigor, stability, achievable resolution, and exploitation of the irregular shape to partially resolve ambiguities. The general applicability of these new approaches to existing data sets from Mars, Mercury, and Lunar investigations will be noted.

Analytic Methods in Investigative Geometry.

ERIC Educational Resources Information Center

Dobbs, David E.

2001-01-01

Suggests an alternative proof by analytic methods, which is more accessible than rigorous proof based on Euclid's Elements, in which students need only apply standard methods of trigonometry to the data without introducing new points or lines. (KHR)

A Critical Review of Methods to Evaluate the Impact of FDA Regulatory Actions

PubMed Central

Briesacher, Becky A.; Soumerai, Stephen B.; Zhang, Fang; Toh, Sengwee; Andrade, Susan E.; Wagner, Joann L.; Shoaibi, Azadeh; Gurwitz, Jerry H.

2013-01-01

Purpose To conduct a synthesis of the literature on methods to evaluate the impacts of FDA regulatory actions, and identify best practices for future evaluations. Methods We searched MEDLINE for manuscripts published between January 1948 and August 2011 that included terms related to FDA, regulatory actions, and empirical evaluation; the review additionally included FDA-identified literature. We used a modified Delphi method to identify preferred methodologies. We included studies with explicit methods to address threats to validity, and identified designs and analytic methods with strong internal validity that have been applied to other policy evaluations. Results We included 18 studies out of 243 abstracts and papers screened. Overall, analytic rigor in prior evaluations of FDA regulatory actions varied considerably; less than a quarter of studies (22%) included control groups. Only 56% assessed changes in the use of substitute products/services, and 11% examined patient health outcomes. Among studies meeting minimal criteria of rigor, 50% found no impact or weak/modest impacts of FDA actions and 33% detected unintended consequences. Among those studies finding significant intended effects of FDA actions, all cited the importance of intensive communication efforts. There are preferred methods with strong internal validity that have yet to be applied to evaluations of FDA regulatory actions. Conclusions Rigorous evaluations of the impact of FDA regulatory actions have been limited and infrequent. Several methods with strong internal validity are available to improve trustworthiness of future evaluations of FDA policies. PMID:23847020

Weak value amplification considered harmful

NASA Astrophysics Data System (ADS)

Ferrie, Christopher; Combes, Joshua

2014-03-01

We show using statistically rigorous arguments that the technique of weak value amplification does not perform better than standard statistical techniques for the tasks of parameter estimation and signal detection. We show that using all data and considering the joint distribution of all measurement outcomes yields the optimal estimator. Moreover, we show estimation using the maximum likelihood technique with weak values as small as possible produces better performance for quantum metrology. In doing so, we identify the optimal experimental arrangement to be the one which reveals the maximal eigenvalue of the square of system observables. We also show these conclusions do not change in the presence of technical noise.

A dose-response model for the conventional phototherapy of the newborn.

PubMed

Osaku, Nelson Ossamu; Lopes, Heitor Silvério

2006-06-01

Jaundice of the newborn is a common problem as a consequence of the rapid increment of blood bilirubin in the first days of live. In most cases, it is considered a physiological transient situation, but unmanaged hyperbilirubinemia can lead to death or serious injuries for the survivors. For decades, phototherapy has been used as the main method for prevention and treatment of hyperbilirubinaemia of the newborn. This work aims at finding a predictive model for the decrement of blood bilirubin for patients submitted to conventional phototherapy. Data from the phototherapy of 90 term newborns were collected and used in a multiple regression method. A rigorous statistical analysis was done in order to guarantee a correct and valid model. The obtained model was able to explain 78% of the variation of the dependent variable. We show that it is possible to predict the total serum bilirubin of the patient under conventional phototherapy by knowing its birth weight, bilirubin level at the beginning of treatment and the radiant energy density (dose). Besides, it is possible to infer the time necessary for a given decrement of bilirubin, under approximately constant irradiance. Statistical analysis of the obtained model shows that it is valid for several ranges of birth weight, initial bilirubin level, and radiant energy density. It is expected that the proposed model can be useful in the clinical management of hyperbilirubinemia of the newborn.

Maximum entropy models as a tool for building precise neural controls.

PubMed

Savin, Cristina; Tkačik, Gašper

2017-10-01

Neural responses are highly structured, with population activity restricted to a small subset of the astronomical range of possible activity patterns. Characterizing these statistical regularities is important for understanding circuit computation, but challenging in practice. Here we review recent approaches based on the maximum entropy principle used for quantifying collective behavior in neural activity. We highlight recent models that capture population-level statistics of neural data, yielding insights into the organization of the neural code and its biological substrate. Furthermore, the MaxEnt framework provides a general recipe for constructing surrogate ensembles that preserve aspects of the data, but are otherwise maximally unstructured. This idea can be used to generate a hierarchy of controls against which rigorous statistical tests are possible. Copyright © 2017 Elsevier Ltd. All rights reserved.

Rigorous high-precision enclosures of fixed points and their invariant manifolds

NASA Astrophysics Data System (ADS)

Wittig, Alexander N.

The well established concept of Taylor Models is introduced, which offer highly accurate C0 enclosures of functional dependencies, combining high-order polynomial approximation of functions and rigorous estimates of the truncation error, performed using verified arithmetic. The focus of this work is on the application of Taylor Models in algorithms for strongly non-linear dynamical systems. A method is proposed to extend the existing implementation of Taylor Models in COSY INFINITY from double precision coefficients to arbitrary precision coefficients. Great care is taken to maintain the highest efficiency possible by adaptively adjusting the precision of higher order coefficients in the polynomial expansion. High precision operations are based on clever combinations of elementary floating point operations yielding exact values for round-off errors. An experimental high precision interval data type is developed and implemented. Algorithms for the verified computation of intrinsic functions based on the High Precision Interval datatype are developed and described in detail. The application of these operations in the implementation of High Precision Taylor Models is discussed. An application of Taylor Model methods to the verification of fixed points is presented by verifying the existence of a period 15 fixed point in a near standard Henon map. Verification is performed using different verified methods such as double precision Taylor Models, High Precision intervals and High Precision Taylor Models. Results and performance of each method are compared. An automated rigorous fixed point finder is implemented, allowing the fully automated search for all fixed points of a function within a given domain. It returns a list of verified enclosures of each fixed point, optionally verifying uniqueness within these enclosures. An application of the fixed point finder to the rigorous analysis of beam transfer maps in accelerator physics is presented. Previous work done by Johannes Grote is extended to compute very accurate polynomial approximations to invariant manifolds of discrete maps of arbitrary dimension around hyperbolic fixed points. The algorithm presented allows for automatic removal of resonances occurring during construction. A method for the rigorous enclosure of invariant manifolds of continuous systems is introduced. Using methods developed for discrete maps, polynomial approximations of invariant manifolds of hyperbolic fixed points of ODEs are obtained. These approximations are outfit with a sharp error bound which is verified to rigorously contain the manifolds. While we focus on the three dimensional case, verification in higher dimensions is possible using similar techniques. Integrating the resulting enclosures using the verified COSY VI integrator, the initial manifold enclosures are expanded to yield sharp enclosures of large parts of the stable and unstable manifolds. To demonstrate the effectiveness of this method, we construct enclosures of the invariant manifolds of the Lorenz system and show pictures of the resulting manifold enclosures. To the best of our knowledge, these enclosures are the largest verified enclosures of manifolds in the Lorenz system in existence.

Sonoelasticity to monitor mechanical changes during rigor and ageing.

PubMed

Ayadi, A; Culioli, J; Abouelkaram, S

2007-06-01

We propose the use of sonoelasticity as a non-destructive method to monitor changes in the resistance of muscle fibres, unaffected by connective tissue. Vibrations were applied at low frequency to induce oscillations in soft tissues and an ultrasound transducer was used to detect the motions. The experiments were carried out on the M. biceps femoris muscles of three beef cattle. In addition to the sonoelasticity measurements, the changes in meat during rigor and ageing were followed by measurements of both the mechanical resistance of myofibres and pH. The variations of mechanical resistance and pH were compared to those of the sonoelastic variables (velocity and attenuation) at two frequencies. The relationships between pH and velocity or attenuation and between the velocity or attenuation and the stress at 20% deformation were highly correlated. We concluded that sonoelasticity is a non-destructive method that can be used to monitor mechanical changes in muscle fibers during rigor-mortis and ageing.

Monitoring Method of Cow Anthrax Based on Gis and Spatial Statistical Analysis

NASA Astrophysics Data System (ADS)

Li, Lin; Yang, Yong; Wang, Hongbin; Dong, Jing; Zhao, Yujun; He, Jianbin; Fan, Honggang

Geographic information system (GIS) is a computer application system, which possesses the ability of manipulating spatial information and has been used in many fields related with the spatial information management. Many methods and models have been established for analyzing animal diseases distribution models and temporal-spatial transmission models. Great benefits have been gained from the application of GIS in animal disease epidemiology. GIS is now a very important tool in animal disease epidemiological research. Spatial analysis function of GIS can be widened and strengthened by using spatial statistical analysis, allowing for the deeper exploration, analysis, manipulation and interpretation of spatial pattern and spatial correlation of the animal disease. In this paper, we analyzed the cow anthrax spatial distribution characteristics in the target district A (due to the secret of epidemic data we call it district A) based on the established GIS of the cow anthrax in this district in combination of spatial statistical analysis and GIS. The Cow anthrax is biogeochemical disease, and its geographical distribution is related closely to the environmental factors of habitats and has some spatial characteristics, and therefore the correct analysis of the spatial distribution of anthrax cow for monitoring and the prevention and control of anthrax has a very important role. However, the application of classic statistical methods in some areas is very difficult because of the pastoral nomadic context. The high mobility of livestock and the lack of enough suitable sampling for the some of the difficulties in monitoring currently make it nearly impossible to apply rigorous random sampling methods. It is thus necessary to develop an alternative sampling method, which could overcome the lack of sampling and meet the requirements for randomness. The GIS computer application software ArcGIS9.1 was used to overcome the lack of data of sampling sites.Using ArcGIS 9.1 and GEODA to analyze the cow anthrax spatial distribution of district A. we gained some conclusions about cow anthrax' density: (1) there is a spatial clustering model. (2) there is an intensely spatial autocorrelation. We established a prediction model to estimate the anthrax distribution based on the spatial characteristic of the density of cow anthrax. Comparing with the true distribution, the prediction model has a well coincidence and is feasible to the application. The method using a GIS tool facilitates can be implemented significantly in the cow anthrax monitoring and investigation, and the space statistics - related prediction model provides a fundamental use for other study on space-related animal diseases.

The Economic Costs of Poverty in the United States: Subsequent Effects of Children Growing Up Poor. Discussion Paper No. 1327-07

ERIC Educational Resources Information Center

Holzer, Harry J.; Schanzenbach, Diane Whitmore; Duncan, Greg J.; Ludwig, Jens

2007-01-01

In this paper, we review a range of rigorous research studies that estimate the average statistical relationships between children growing up in poverty and their earnings, propensity to commit crime, and quality of health later in life. We also review estimates of the costs that crime and poor health per person impose on the economy. Then we…

Enumerating Sparse Organisms in Ships’ Ballast Water: Why Counting to 10 Is Not So Easy

PubMed Central

2011-01-01

To reduce ballast water-borne aquatic invasions worldwide, the International Maritime Organization and United States Coast Guard have each proposed discharge standards specifying maximum concentrations of living biota that may be released in ships’ ballast water (BW), but these regulations still lack guidance for standardized type approval and compliance testing of treatment systems. Verifying whether BW meets a discharge standard poses significant challenges. Properly treated BW will contain extremely sparse numbers of live organisms, and robust estimates of rare events require extensive sampling efforts. A balance of analytical rigor and practicality is essential to determine the volume of BW that can be reasonably sampled and processed, yet yield accurate live counts. We applied statistical modeling to a range of sample volumes, plankton concentrations, and regulatory scenarios (i.e., levels of type I and type II errors), and calculated the statistical power of each combination to detect noncompliant discharge concentrations. The model expressly addresses the roles of sampling error, BW volume, and burden of proof on the detection of noncompliant discharges in order to establish a rigorous lower limit of sampling volume. The potential effects of recovery errors (i.e., incomplete recovery and detection of live biota) in relation to sample volume are also discussed. PMID:21434685

Understanding photon sideband statistics and correlation for determining phonon coherence

NASA Astrophysics Data System (ADS)

Ding, Ding; Yin, Xiaobo; Li, Baowen

2018-01-01

Generating and detecting coherent high-frequency heat-carrying phonons have been topics of great interest in recent years. Although there have been successful attempts in generating and observing coherent phonons, rigorous techniques to characterize and detect phonon coherence in a crystalline material have been lagging compared to what has been achieved for photons. One main challenge is a lack of detailed understanding of how detection signals for phonons can be related to coherence. The quantum theory of photoelectric detection has greatly advanced the ability to characterize photon coherence in the past century, and a similar theory for phonon detection is necessary. Here, we reexamine the optical sideband fluorescence technique that has been used to detect high-frequency phonons in materials with optically active defects. We propose a quantum theory of phonon detection using the sideband technique and found that there are distinct differences in sideband counting statistics between thermal and coherent phonons. We further propose a second-order correlation function unique to sideband signals that allows for a rigorous distinction between thermal and coherent phonons. Our theory is relevant to a correlation measurement with nontrivial response functions at the quantum level and can potentially bridge the gap of experimentally determining phonon coherence to be on par with that of photons.

Enumerating sparse organisms in ships' ballast water: why counting to 10 is not so easy.

PubMed

Miller, A Whitman; Frazier, Melanie; Smith, George E; Perry, Elgin S; Ruiz, Gregory M; Tamburri, Mario N

2011-04-15

To reduce ballast water-borne aquatic invasions worldwide, the International Maritime Organization and United States Coast Guard have each proposed discharge standards specifying maximum concentrations of living biota that may be released in ships' ballast water (BW), but these regulations still lack guidance for standardized type approval and compliance testing of treatment systems. Verifying whether BW meets a discharge standard poses significant challenges. Properly treated BW will contain extremely sparse numbers of live organisms, and robust estimates of rare events require extensive sampling efforts. A balance of analytical rigor and practicality is essential to determine the volume of BW that can be reasonably sampled and processed, yet yield accurate live counts. We applied statistical modeling to a range of sample volumes, plankton concentrations, and regulatory scenarios (i.e., levels of type I and type II errors), and calculated the statistical power of each combination to detect noncompliant discharge concentrations. The model expressly addresses the roles of sampling error, BW volume, and burden of proof on the detection of noncompliant discharges in order to establish a rigorous lower limit of sampling volume. The potential effects of recovery errors (i.e., incomplete recovery and detection of live biota) in relation to sample volume are also discussed.

Estimating pseudocounts and fold changes for digital expression measurements.

PubMed

Erhard, Florian

2018-06-19

Fold changes from count based high-throughput experiments such as RNA-seq suffer from a zero-frequency problem. To circumvent division by zero, so-called pseudocounts are added to make all observed counts strictly positive. The magnitude of pseudocounts for digital expression measurements and on which stage of the analysis they are introduced remained an arbitrary choice. Moreover, in the strict sense, fold changes are not quantities that can be computed. Instead, due to the stochasticity involved in the experiments, they must be estimated by statistical inference. Here, we build on a statistical framework for fold changes, where pseudocounts correspond to the parameters of the prior distribution used for Bayesian inference of the fold change. We show that arbirary and widely used choices for applying pseudocounts can lead to biased results. As a statistical rigorous alternative, we propose and test an empirical Bayes procedure to choose appropriate pseudocounts. Moreover, we introduce the novel estimator Ψ LFC for fold changes showing favorable properties with small counts and smaller deviations from the truth in simulations and real data compared to existing methods. Our results have direct implications for entities with few reads in sequencing experiments, and indirectly also affect results for entities with many reads. Ψ LFC is available as an R package under https://github.com/erhard-lab/lfc (Apache 2.0 license); R scripts to generate all figures are available at zenodo (doi:10.5281/zenodo.1163029).

Statistical issues in signal extraction from microarrays

NASA Astrophysics Data System (ADS)

Bergemann, Tracy; Quiaoit, Filemon; Delrow, Jeffrey J.; Zhao, Lue Ping

2001-06-01

Microarray technologies are increasingly used in biomedical research to study genome-wide expression profiles in the post genomic era. Their popularity is largely due to their high throughput and economical affordability. For example, microarrays have been applied to studies of cell cycle, regulatory circuitry, cancer cell lines, tumor tissues, and drug discoveries. One obstacle facing the continued success of applying microarray technologies, however, is the random variaton present on microarrays: within signal spots, between spots and among chips. In addition, signals extracted by available software packages seem to vary significantly. Despite a variety of software packages, it appears that there are two major approaches to signal extraction. One approach is to focus on the identification of signal regions and hence estimation of signal levels above background levels. The other approach is to use the distribution of intensity values as a way of identifying relevant signals. Building upon both approaches, the objective of our work is to develop a method that is statistically rigorous and also efficient and robust. Statistical issues to be considered here include: (1) how to refine grid alignment so that the overall variation is minimized, (2) how to estimate the signal levels relative to the local background levels as well as the variance of this estimate, and (3) how to integrate red and green channel signals so that the ratio of interest is stable, simultaneously relaxing distributional assumptions.

On Statistical Approaches for Demonstrating Analytical Similarity in the Presence of Correlation.

PubMed

Yang, Harry; Novick, Steven; Burdick, Richard K

Analytical similarity is the foundation for demonstration of biosimilarity between a proposed product and a reference product. For this assessment, currently the U.S. Food and Drug Administration (FDA) recommends a tiered system in which quality attributes are categorized into three tiers commensurate with their risk and approaches of varying statistical rigor are subsequently used for the three-tier quality attributes. Key to the analyses of Tiers 1 and 2 quality attributes is the establishment of equivalence acceptance criterion and quality range. For particular licensure applications, the FDA has provided advice on statistical methods for demonstration of analytical similarity. For example, for Tier 1 assessment, an equivalence test can be used based on an equivalence margin of 1.5 σ R , where σ R is the reference product variability estimated by the sample standard deviation S R from a sample of reference lots. The quality range for demonstrating Tier 2 analytical similarity is of the form X̄ R ± K × σ R where the constant K is appropriately justified. To demonstrate Tier 2 analytical similarity, a large percentage (e.g., 90%) of test product must fall in the quality range. In this paper, through both theoretical derivations and simulations, we show that when the reference drug product lots are correlated, the sample standard deviation S R underestimates the true reference product variability σ R As a result, substituting S R for σ R in the Tier 1 equivalence acceptance criterion and the Tier 2 quality range inappropriately reduces the statistical power and the ability to declare analytical similarity. Also explored is the impact of correlation among drug product lots on Type I error rate and power. Three methods based on generalized pivotal quantities are introduced, and their performance is compared against a two-one-sided tests (TOST) approach. Finally, strategies to mitigate risk of correlation among the reference products lots are discussed. A biosimilar is a generic version of the original biological drug product. A key component of a biosimilar development is the demonstration of analytical similarity between the biosimilar and the reference product. Such demonstration relies on application of statistical methods to establish a similarity margin and appropriate test for equivalence between the two products. This paper discusses statistical issues with demonstration of analytical similarity and provides alternate approaches to potentially mitigate these problems. © PDA, Inc. 2016.

A statistical study of the relationship between surface quality and laser induced damage

NASA Astrophysics Data System (ADS)

Turner, Trey; Turchette, Quentin; Martin, Alex R.

2012-11-01

Laser induced damage of optical components is a concern in many applications in the commercial, scientific and military market sectors. Numerous component manufacturers supply "high laser damage threshold" (HLDT) optics to meet the needs of this market, and consumers pay a premium price for these products. While there's no question that HLDT optics are manufactured to more rigorous standards (and are therefore inherently more expensive) than conventional products, it is not clear how this added expense translates directly into better performance. This is because the standard methods for evaluating laser damage, and the underlying assumptions about the validity of traditional laser damage testing, are flawed. In particular, the surface and coating defects that generally lead to laser damage (in many laserparameter regimes of interest) are widely distributed over the component surface with large spaces in between them. As a result, laser damage testing typically doesn't include enough of these defects to achieve the sample sizes necessary to make its results statistically meaningful. The result is a poor correlation between defect characteristics and damage events. This paper establishes specifically why this is the case, and provides some indication of what might be done to remedy the problem.

Thermostatted {delta}f

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krommes, J.A.

1999-05-01

The {delta}f simulation method is revisited. Statistical coarse graining is used to rigorously derive the equation for the fluctuation {delta}f in the particle distribution. It is argued that completely collisionless simulation is incompatible with the achievement of true statistically steady states with nonzero turbulent fluxes because the variance {ital W} of the particle weights {ital w} grows with time. To ensure such steady states, it is shown that for dynamically collisionless situations a generalized thermostat or {open_quotes}{ital W} stat{close_quotes} may be used in lieu of a full collision operator to absorb the flow of entropy to unresolved fine scales inmore » velocity space. The simplest {ital W} stat can be implemented as a self-consistently determined, time-dependent damping applied to {ital w}. A precise kinematic analogy to thermostatted nonequilibrium molecular dynamics is pointed out, and the justification of {ital W} stats for simulations of turbulence is discussed. An extrapolation procedure is proposed such that the long-time, steady-state, collisionless flux can be deduced from several short {ital W}-statted runs with large effective collisionality, and a numerical demonstration is given. {copyright} {ital 1999 American Institute of Physics.}« less

Statistical tests and identifiability conditions for pooling and analyzing multisite datasets.

PubMed

Zhou, Hao Henry; Singh, Vikas; Johnson, Sterling C; Wahba, Grace

2018-02-13

When sample sizes are small, the ability to identify weak (but scientifically interesting) associations between a set of predictors and a response may be enhanced by pooling existing datasets. However, variations in acquisition methods and the distribution of participants or observations between datasets, especially due to the distributional shifts in some predictors, may obfuscate real effects when datasets are combined. We present a rigorous statistical treatment of this problem and identify conditions where we can correct the distributional shift. We also provide an algorithm for the situation where the correction is identifiable. We analyze various properties of the framework for testing model fit, constructing confidence intervals, and evaluating consistency characteristics. Our technical development is motivated by Alzheimer's disease (AD) studies, and we present empirical results showing that our framework enables harmonizing of protein biomarkers, even when the assays across sites differ. Our contribution may, in part, mitigate a bottleneck that researchers face in clinical research when pooling smaller sized datasets and may offer benefits when the subjects of interest are difficult to recruit or when resources prohibit large single-site studies. Copyright © 2018 the Author(s). Published by PNAS.

A new feedback image encryption scheme based on perturbation with dynamical compound chaotic sequence cipher generator

NASA Astrophysics Data System (ADS)

Tong, Xiaojun; Cui, Minggen; Wang, Zhu

2009-07-01

The design of the new compound two-dimensional chaotic function is presented by exploiting two one-dimensional chaotic functions which switch randomly, and the design is used as a chaotic sequence generator which is proved by Devaney's definition proof of chaos. The properties of compound chaotic functions are also proved rigorously. In order to improve the robustness against difference cryptanalysis and produce avalanche effect, a new feedback image encryption scheme is proposed using the new compound chaos by selecting one of the two one-dimensional chaotic functions randomly and a new image pixels method of permutation and substitution is designed in detail by array row and column random controlling based on the compound chaos. The results from entropy analysis, difference analysis, statistical analysis, sequence randomness analysis, cipher sensitivity analysis depending on key and plaintext have proven that the compound chaotic sequence cipher can resist cryptanalytic, statistical and brute-force attacks, and especially it accelerates encryption speed, and achieves higher level of security. By the dynamical compound chaos and perturbation technology, the paper solves the problem of computer low precision of one-dimensional chaotic function.

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Meyer, Kerry G.; Platnick, Steven; Oreopoulos, Lazaros; Lee, Dongmin; Yu, Hongbin

2014-01-01

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It addresses the overlap of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure while also accounting for subgrid-scale variations of aerosols. The method is computationally efficient because of its use of grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table based on radiative transfer calculations. We verify that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous (approximately 1:30PM local time) shortwave DRE of above cloud aerosol (ACA) that generally agrees with more rigorous pixel-level computation within 4 percent. We also estimate the impact of potential CALIOP aerosol optical depth (AOD) retrieval bias of ACA on DRE. We find that the regional and seasonal mean instantaneous DRE of ACA over southeast Atlantic Ocean would increase, from the original value of 6.4 W m(-2) based on operational CALIOP AOD to 9.6 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 1.5 (Meyer et al., 2013) and further to 30.9 W m(-2) if CALIOP AOD retrieval are biased low by a factor of 5 as suggested in (Jethva et al., 2014). In contrast, the instantaneous ACA radiative forcing efficiency (RFE) remains relatively invariant in all cases at about 53 W m(-2) AOD(-1), suggesting a near linear relation between the instantaneous RFE and AOD. We also compute the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global oceans based on 4 years of CALIOP and MODIS data. We find that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds. While we demonstrate our method using CALIOP and MODIS data, it can also be extended to other satellite data sets, as well as climate model outputs.

Learning from Science and Sport - How we, Safety, "Engage with Rigor"

NASA Astrophysics Data System (ADS)

Herd, A.

2012-01-01

As the world of spaceflight safety is relatively small and potentially inward-looking, we need to be aware of the "outside world". We should then try to remind ourselves to be open to the possibility that data, knowledge or experience from outside of the spaceflight community may provide some constructive alternate perspectives. This paper will assess aspects from two seemingly tangential fields, science and sport, and align these with the world of safety. In doing so some useful insights will be given to the challenges we face and may provide solutions relevant in our everyday (of safety engineering). Sport, particularly a contact sport such as rugby union, requires direct interaction between members of two (opposing) teams. Professional, accurately timed and positioned interaction for a desired outcome. These interactions, whilst an essential part of the game, are however not without their constraints. The rugby scrum has constraints as to the formation and engagement of the two teams. The controlled engagement provides for an interaction between the two teams in a safe manner. The constraints arising from the reality that an incorrect engagement could cause serious injury to members of either team. In academia, scientific rigor is applied to assure that the arguments provided and the conclusions drawn in academic papers presented for publication are valid, legitimate and credible. The scientific goal of the need for rigor may be expressed in the example of achieving a statistically relevant sample size, n, in order to assure analysis validity of the data pool. A failure to apply rigor could then place the entire study at risk of failing to have the respective paper published. This paper will consider the merits of these two different aspects, scientific rigor and sports engagement, and offer a reflective look at how this may provide a "modus operandi" for safety engineers at any level whether at their desks (creating or reviewing safety assessments) or in a safety review meeting (providing a verbal critique of the presented safety case).

Strengthening Causal Estimates for Links Between Spanking and Children's Externalizing Behavior Problems.

PubMed

Gershoff, Elizabeth T; Sattler, Kierra M P; Ansari, Arya

2018-01-01

Establishing causal links when experiments are not feasible is an important challenge for psychology researchers. The question of whether parents' spanking causes children's externalizing behavior problems poses such a challenge because randomized experiments of spanking are unethical, and correlational studies cannot rule out potential selection factors. This study used propensity score matching based on the lifetime prevalence and recent incidence of spanking in a large and nationally representative sample ( N = 12,112) as well as lagged dependent variables to get as close to causal estimates outside an experiment as possible. Whether children were spanked at the age of 5 years predicted increases in externalizing behavior problems by ages 6 and 8, even after the groups based on spanking prevalence or incidence were matched on a range of sociodemographic, family, and cultural characteristics and children's initial behavior problems. These statistically rigorous methods yield the conclusion that spanking predicts a deterioration of children's externalizing behavior over time.

The Application and Future of Big Database Studies in Cardiology: A Single-Center Experience.

PubMed

Lee, Kuang-Tso; Hour, Ai-Ling; Shia, Ben-Chang; Chu, Pao-Hsien

2017-11-01

As medical research techniques and quality have improved, it is apparent that cardiovascular problems could be better resolved by more strict experiment design. In fact, substantial time and resources should be expended to fulfill the requirements of high quality studies. Many worthy ideas and hypotheses were unable to be verified or proven due to ethical or economic limitations. In recent years, new and various applications and uses of databases have received increasing attention. Important information regarding certain issues such as rare cardiovascular diseases, women's heart health, post-marketing analysis of different medications, or a combination of clinical and regional cardiac features could be obtained by the use of rigorous statistical methods. However, there are limitations that exist among all databases. One of the key essentials to creating and correctly addressing this research is through reliable processes of analyzing and interpreting these cardiologic databases.

Introduction to the special issue on recentering science: Replication, robustness, and reproducibility in psychophysiology.

PubMed

Kappenman, Emily S; Keil, Andreas

2017-01-01

In recent years, the psychological and behavioral sciences have increased efforts to strengthen methodological practices and publication standards, with the ultimate goal of enhancing the value and reproducibility of published reports. These issues are especially important in the multidisciplinary field of psychophysiology, which yields rich and complex data sets with a large number of observations. In addition, the technological tools and analysis methods available in the field of psychophysiology are continually evolving, widening the array of techniques and approaches available to researchers. This special issue presents articles detailing rigorous and systematic evaluations of tasks, measures, materials, analysis approaches, and statistical practices in a variety of subdisciplines of psychophysiology. These articles highlight challenges in conducting and interpreting psychophysiological research and provide data-driven, evidence-based recommendations for overcoming those challenges to produce robust, reproducible results in the field of psychophysiology. © 2016 Society for Psychophysiological Research.

DOE Office of Scientific and Technical Information (OSTI.GOV)

English, Shawn A.; Briggs, Timothy M.; Nelson, Stacy M.

Simulations of low velocity impact with a flat cylindrical indenter upon a carbon fiber fabric reinforced polymer laminate are rigorously validated. Comparison of the impact energy absorption between the model and experiment is used as the validation metric. Additionally, non-destructive evaluation, including ultrasonic scans and three-dimensional computed tomography, provide qualitative validation of the models. The simulations include delamination, matrix cracks and fiber breaks. An orthotropic damage and failure constitutive model, capable of predicting progressive damage and failure, is developed in conjunction and described. An ensemble of simulations incorporating model parameter uncertainties is used to predict a response distribution which ismore » then compared to experimental output using appropriate statistical methods. Lastly, the model form errors are exposed and corrected for use in an additional blind validation analysis. The result is a quantifiable confidence in material characterization and model physics when simulating low velocity impact in structures of interest.« less

QTest: Quantitative Testing of Theories of Binary Choice.

PubMed

Regenwetter, Michel; Davis-Stober, Clintin P; Lim, Shiau Hong; Guo, Ying; Popova, Anna; Zwilling, Chris; Cha, Yun-Shil; Messner, William

2014-01-01

The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of "Random Cumulative Prospect Theory." A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences.

Evaluation of endometrial cancer epidemiology in Romania.

PubMed

Bohîlțea, R E; Furtunescu, F; Dosius, M; Cîrstoiu, M; Radoi, V; Baroș, A; Bohîlțea, L C

2015-01-01

Endometrial cancer represents the most frequent gynecological malignant affection in the developed countries, in which the incidence of cervical cancer has significantly decreased due to the rigorous application of screening methods and prophylaxis. According to its frequency, endometrial cancer is situated on the fourth place in the category of women's genital-mammary malignant diseases, after breast, cervical and ovarian cancer in Romania. The incidence and mortality rates due to endometrial cancer have registered an increasing trend worldwide and also in Romania, a significant decrease of the age of appearance for the entire endometrial pathology sphere being noticed. At the national level, the maximum incidence is situated between 60 and 64 years old, the mortality rate of the women under 65 years old being high in Romania. The study evaluates endometrial cancer, from an epidemiologic point of view, at the national level compared to the international statistic data.

Controls of multi-modal wave conditions in a complex coastal setting

USGS Publications Warehouse

Hegermiller, Christie; Rueda, Ana C.; Erikson, Li H.; Barnard, Patrick L.; Antolinez, J.A.A.; Mendez, Fernando J.

2017-01-01

Coastal hazards emerge from the combined effect of wave conditions and sea level anomalies associated with storms or low-frequency atmosphere-ocean oscillations. Rigorous characterization of wave climate is limited by the availability of spectral wave observations, the computational cost of dynamical simulations, and the ability to link wave-generating atmospheric patterns with coastal conditions. We present a hybrid statistical-dynamical approach to simulating nearshore wave climate in complex coastal settings, demonstrated in the Southern California Bight, where waves arriving from distant, disparate locations are refracted over complex bathymetry and shadowed by offshore islands. Contributions of wave families and large-scale atmospheric drivers to nearshore wave energy flux are analyzed. Results highlight the variability of influences controlling wave conditions along neighboring coastlines. The universal method demonstrated here can be applied to complex coastal settings worldwide, facilitating analysis of the effects of climate change on nearshore wave climate.

Controls of Multimodal Wave Conditions in a Complex Coastal Setting

NASA Astrophysics Data System (ADS)

Hegermiller, C. A.; Rueda, A.; Erikson, L. H.; Barnard, P. L.; Antolinez, J. A. A.; Mendez, F. J.

2017-12-01

Coastal hazards emerge from the combined effect of wave conditions and sea level anomalies associated with storms or low-frequency atmosphere-ocean oscillations. Rigorous characterization of wave climate is limited by the availability of spectral wave observations, the computational cost of dynamical simulations, and the ability to link wave-generating atmospheric patterns with coastal conditions. We present a hybrid statistical-dynamical approach to simulating nearshore wave climate in complex coastal settings, demonstrated in the Southern California Bight, where waves arriving from distant, disparate locations are refracted over complex bathymetry and shadowed by offshore islands. Contributions of wave families and large-scale atmospheric drivers to nearshore wave energy flux are analyzed. Results highlight the variability of influences controlling wave conditions along neighboring coastlines. The universal method demonstrated here can be applied to complex coastal settings worldwide, facilitating analysis of the effects of climate change on nearshore wave climate.

Mindfulness Meditation for Chronic Pain: Systematic Review and Meta-analysis.

PubMed

Hilton, Lara; Hempel, Susanne; Ewing, Brett A; Apaydin, Eric; Xenakis, Lea; Newberry, Sydne; Colaiaco, Ben; Maher, Alicia Ruelaz; Shanman, Roberta M; Sorbero, Melony E; Maglione, Margaret A

2017-04-01

Chronic pain patients increasingly seek treatment through mindfulness meditation. This study aims to synthesize evidence on efficacy and safety of mindfulness meditation interventions for the treatment of chronic pain in adults. We conducted a systematic review on randomized controlled trials (RCTs) with meta-analyses using the Hartung-Knapp-Sidik-Jonkman method for random-effects models. Quality of evidence was assessed using the GRADE approach. Outcomes included pain, depression, quality of life, and analgesic use. Thirty-eight RCTs met inclusion criteria; seven reported on safety. We found low-quality evidence that mindfulness meditation is associated with a small decrease in pain compared with all types of controls in 30 RCTs. Statistically significant effects were also found for depression symptoms and quality of life. While mindfulness meditation improves pain and depression symptoms and quality of life, additional well-designed, rigorous, and large-scale RCTs are needed to decisively provide estimates of the efficacy of mindfulness meditation for chronic pain.

Using Temporal Correlations and Full Distributions to Separate Intrinsic and Extrinsic Fluctuations in Biological Systems

NASA Astrophysics Data System (ADS)

Hilfinger, Andreas; Chen, Mark; Paulsson, Johan

2012-12-01

Studies of stochastic biological dynamics typically compare observed fluctuations to theoretically predicted variances, sometimes after separating the intrinsic randomness of the system from the enslaving influence of changing environments. But variances have been shown to discriminate surprisingly poorly between alternative mechanisms, while for other system properties no approaches exist that rigorously disentangle environmental influences from intrinsic effects. Here, we apply the theory of generalized random walks in random environments to derive exact rules for decomposing time series and higher statistics, rather than just variances. We show for which properties and for which classes of systems intrinsic fluctuations can be analyzed without accounting for extrinsic stochasticity and vice versa. We derive two independent experimental methods to measure the separate noise contributions and show how to use the additional information in temporal correlations to detect multiplicative effects in dynamical systems.

Kinetics from Replica Exchange Molecular Dynamics Simulations.

PubMed

Stelzl, Lukas S; Hummer, Gerhard

2017-08-08

Transitions between metastable states govern many fundamental processes in physics, chemistry and biology, from nucleation events in phase transitions to the folding of proteins. The free energy surfaces underlying these processes can be obtained from simulations using enhanced sampling methods. However, their altered dynamics makes kinetic and mechanistic information difficult or impossible to extract. Here, we show that, with replica exchange molecular dynamics (REMD), one can not only sample equilibrium properties but also extract kinetic information. For systems that strictly obey first-order kinetics, the procedure to extract rates is rigorous. For actual molecular systems whose long-time dynamics are captured by kinetic rate models, accurate rate coefficients can be determined from the statistics of the transitions between the metastable states at each replica temperature. We demonstrate the practical applicability of the procedure by constructing master equation (Markov state) models of peptide and RNA folding from REMD simulations.

Quantitative validation of carbon-fiber laminate low velocity impact simulations

DOE PAGES

English, Shawn A.; Briggs, Timothy M.; Nelson, Stacy M.

2015-09-26

Simulations of low velocity impact with a flat cylindrical indenter upon a carbon fiber fabric reinforced polymer laminate are rigorously validated. Comparison of the impact energy absorption between the model and experiment is used as the validation metric. Additionally, non-destructive evaluation, including ultrasonic scans and three-dimensional computed tomography, provide qualitative validation of the models. The simulations include delamination, matrix cracks and fiber breaks. An orthotropic damage and failure constitutive model, capable of predicting progressive damage and failure, is developed in conjunction and described. An ensemble of simulations incorporating model parameter uncertainties is used to predict a response distribution which ismore » then compared to experimental output using appropriate statistical methods. Lastly, the model form errors are exposed and corrected for use in an additional blind validation analysis. The result is a quantifiable confidence in material characterization and model physics when simulating low velocity impact in structures of interest.« less

Precipitation chemistry affected by differences in location of collection sites and storage methods

NASA Astrophysics Data System (ADS)

Mahendrappa, M. K.

An investigation was carried out to evaluate rigorously the possible differences in measured concentrations of hydrogen, nitrate and sulfate ions in 'bulk' precipitation samples that may be caused by variations in location of rain collectors, and duration and temperature of storage. Storage of precipitation samples, up to 1 month, both in the coldroom and in the field resulted in a significant reduction in the concentration of hydrogen ions. Only field storage caused a statistically significant reduction in the concentration of nitrate in the precipitation samples. Levels of sulfate ions were not found to be significantly affected by storage either in the field or in coldrooms. Samples collected from a rain gage located on a building roof were more acidic than those collected in open spaces in forests. Though all samples showed similar seasonal patterns in the concentrations of sulfate and nitrate, the individual values consistently differed from each other.

The art and science of weed mapping

USGS Publications Warehouse

Barnett, David T.; Stohlgren, Thomas J.; Jarnevich, Catherine S.; Chong, Geneva W.; Ericson, Jenny A.; Davern, Tracy R.; Simonson, Sara E.

2007-01-01

Land managers need cost-effective and informative tools for non-native plant species management. Many local, state, and federal agencies adopted mapping systems designed to collect comparable data for the early detection and monitoring of non-native species. We compared mapping information to statistically rigorous, plot-based methods to better understand the benefits and compatibility of the two techniques. Mapping non-native species locations provided a species list, associated species distributions, and infested area for subjectively selected survey sites. The value of this information may be compromised by crude estimates of cover and incomplete or biased estimations of species distributions. Incorporating plot-based assessments guided by a stratified-random sample design provided a less biased description of non-native species distributions and increased the comparability of data over time and across regions for the inventory, monitoring, and management of non-native and native plant species.

A Systematic Review of Strategies for Implementing Empirically Supported Mental Health Interventions

PubMed Central

Powell, Byron J.; Proctor, Enola K.; Glass, Joseph E.

2013-01-01

Objective This systematic review examines experimental studies that test the effectiveness of strategies intended to integrate empirically supported mental health interventions into routine care settings. Our goal was to characterize the state of the literature and to provide direction for future implementation studies. Methods A literature search was conducted using electronic databases and a manual search. Results Eleven studies were identified that tested implementation strategies with a randomized (n = 10) or controlled clinical trial design (n = 1). The wide range of clinical interventions, implementation strategies, and outcomes evaluated precluded meta-analysis. However, the majority of studies (n = 7; 64%) found a statistically significant effect in the hypothesized direction for at least one implementation or clinical outcome. Conclusions There is a clear need for more rigorous research on the effectiveness of implementation strategies, and we provide several suggestions that could improve this research area. PMID:24791131

Skin Bleaching and Dermatologic Health of African and Afro-Caribbean Populations in the US: New Directions for Methodologically Rigorous, Multidisciplinary, and Culturally Sensitive Research.

PubMed

Benn, Emma K T; Alexis, Andrew; Mohamed, Nihal; Wang, Yan-Hong; Khan, Ikhlas A; Liu, Bian

2016-12-01

Skin-bleaching practices, such as using skin creams and soaps to achieve a lighter skin tone, are common throughout the world and are triggered by cosmetic reasons that oftentimes have deep historical, economic, sociocultural, and psychosocial roots. Exposure to chemicals in the bleaching products, notably, mercury (Hg), hydroquinone, and steroids, has been associated with a variety of adverse health effects, such as Hg poisoning and exogenous ochronosis. In New York City (NYC), skin care product use has been identified as an important route of Hg exposure, especially among Caribbean-born blacks and Dominicans. However, surprisingly sparse information is available on the epidemiology of the health impacts of skin-bleaching practices among these populations. We highlight the dearth of large-scale, comprehensive, community-based, clinical, and translational research in this area, especially the limited skin-bleaching-related research among non-White populations in the US. We offer five new research directions, including investigating the known and under-studied health consequences among populations for which the skin bleach practice is newly emerging at an alarming rate using innovative laboratory and statistical methods. We call for conducting methodologically rigorous, multidisciplinary, and culturally sensitive research in order to provide insights into the root and the epidemiological status of the practice and provide evidence of exposure-outcome associations, with an ultimate goal of developing potential intervention strategies to reduce the health burdens of skin-bleaching practice.

Rigorous Photogrammetric Processing of CHANG'E-1 and CHANG'E-2 Stereo Imagery for Lunar Topographic Mapping

NASA Astrophysics Data System (ADS)

Di, K.; Liu, Y.; Liu, B.; Peng, M.

2012-07-01

Chang'E-1(CE-1) and Chang'E-2(CE-2) are the two lunar orbiters of China's lunar exploration program. Topographic mapping using CE-1 and CE-2 images is of great importance for scientific research as well as for preparation of landing and surface operation of Chang'E-3 lunar rover. In this research, we developed rigorous sensor models of CE-1 and CE-2 CCD cameras based on push-broom imaging principle with interior and exterior orientation parameters. Based on the rigorous sensor model, the 3D coordinate of a ground point in lunar body-fixed (LBF) coordinate system can be calculated by space intersection from the image coordinates of con-jugate points in stereo images, and the image coordinates can be calculated from 3D coordinates by back-projection. Due to uncer-tainties of the orbit and the camera, the back-projected image points are different from the measured points. In order to reduce these inconsistencies and improve precision, we proposed two methods to refine the rigorous sensor model: 1) refining EOPs by correcting the attitude angle bias, 2) refining the interior orientation model by calibration of the relative position of the two linear CCD arrays. Experimental results show that the mean back-projection residuals of CE-1 images are reduced to better than 1/100 pixel by method 1 and the mean back-projection residuals of CE-2 images are reduced from over 20 pixels to 0.02 pixel by method 2. Consequently, high precision DEM (Digital Elevation Model) and DOM (Digital Ortho Map) are automatically generated.

Comparison of mid-infrared transmission spectroscopy with biochemical methods for the determination of macronutrients in human milk.

PubMed

Silvestre, Dolores; Fraga, Miriam; Gormaz, María; Torres, Ester; Vento, Máximo

2014-07-01

The variability of human milk (HM) composition renders analysis of its components essential for optimal nutrition of preterm fed either with donor's or own mother's milk. To fulfil this requirement, various analytical instruments have been subjected to scientific and clinical evaluation. The objective of this study was to evaluate the suitability of a rapid method for the analysis of macronutrients in HM as compared with the analytical methods applied by cow's milk industry. Mature milk from 39 donors was analysed using an infrared human milk analyser (HMA) and compared with biochemical reference laboratory methods. The statistical analysis was based on the use of paired data tests. The use of an infrared HMA for the analysis of lipids, proteins and lactose in HM proved satisfactory as regards the rapidity, simplicity and the required sample volume. The instrument afforded good linearity and precision in application to all three nutrients. However, accuracy was not acceptable when compared with the reference methods, with overestimation of the lipid content and underestimation of the amount of proteins and lactose contents. The use of mid-infrared HMA might become the standard for rapid analysis of HM once standardisation and rigorous and systematic calibration is provided. © 2012 John Wiley & Sons Ltd.

Evaluation of physical dimension changes as nondestructive measurements for monitoring rigor mortis development in broiler muscles.

PubMed

Cavitt, L C; Sams, A R

2003-07-01

Studies were conducted to develop a non-destructive method for monitoring the rate of rigor mortis development in poultry and to evaluate the effectiveness of electrical stimulation (ES). In the first study, 36 male broilers in each of two trials were processed at 7 wk of age. After being bled, half of the birds received electrical stimulation (400 to 450 V, 400 to 450 mA, for seven pulses of 2 s on and 1 s off), and the other half were designated as controls. At 0.25 and 1.5 h postmortem (PM), carcasses were evaluated for the angles of the shoulder, elbow, and wing tip and the distance between the elbows. Breast fillets were harvested at 1.5 h PM (after chilling) from all carcasses. Fillet samples were excised and frozen for later measurement of pH and R-value, and the remainder of each fillet was held on ice until 24 h postmortem. Shear value and pH means were significantly lower, but R-value means were higher (P < 0.05) for the ES fillets compared to the controls, suggesting acceleration of rigor mortis by ES. The physical dimensions of the shoulder and elbow changed (P < 0.05) during rigor mortis development and with ES. These results indicate that physical measurements of the wings maybe useful as a nondestructive indicator of rigor development and for monitoring the effectiveness of ES. In the second study, 60 male broilers in each of two trials were processed at 7 wk of age. At 0.25, 1.5, 3.0, and 6.0 h PM, carcasses were evaluated for the distance between the elbows. At each time point, breast fillets were harvested from each carcass. Fillet samples were excised and frozen for later measurement of pH and sacromere length, whereas the remainder of each fillet was held on ice until 24 h PM. Shear value and pH means (P < 0.05) decreased, whereas sarcomere length means (P < 0.05) increased over time, indicating rigor mortis development. Elbow distance decreased (P < 0.05) with rigor development and was correlated (P < 0.01) with shear value (r = 0.2581), sarcomere length (r = -0.3079), and pH (r = 0.6303). These results suggest that elbow distance could be used in conjunction with other detection methods for optically automating measurement of rigor mortis development in broiler carcasses.

Finite-size effects in transcript sequencing count distribution: its power-law correction necessarily precedes downstream normalization and comparative analysis.

PubMed

Wong, Wing-Cheong; Ng, Hong-Kiat; Tantoso, Erwin; Soong, Richie; Eisenhaber, Frank

2018-02-12

Though earlier works on modelling transcript abundance from vertebrates to lower eukaroytes have specifically singled out the Zip's law, the observed distributions often deviate from a single power-law slope. In hindsight, while power-laws of critical phenomena are derived asymptotically under the conditions of infinite observations, real world observations are finite where the finite-size effects will set in to force a power-law distribution into an exponential decay and consequently, manifests as a curvature (i.e., varying exponent values) in a log-log plot. If transcript abundance is truly power-law distributed, the varying exponent signifies changing mathematical moments (e.g., mean, variance) and creates heteroskedasticity which compromises statistical rigor in analysis. The impact of this deviation from the asymptotic power-law on sequencing count data has never truly been examined and quantified. The anecdotal description of transcript abundance being almost Zipf's law-like distributed can be conceptualized as the imperfect mathematical rendition of the Pareto power-law distribution when subjected to the finite-size effects in the real world; This is regardless of the advancement in sequencing technology since sampling is finite in practice. Our conceptualization agrees well with our empirical analysis of two modern day NGS (Next-generation sequencing) datasets: an in-house generated dilution miRNA study of two gastric cancer cell lines (NUGC3 and AGS) and a publicly available spike-in miRNA data; Firstly, the finite-size effects causes the deviations of sequencing count data from Zipf's law and issues of reproducibility in sequencing experiments. Secondly, it manifests as heteroskedasticity among experimental replicates to bring about statistical woes. Surprisingly, a straightforward power-law correction that restores the distribution distortion to a single exponent value can dramatically reduce data heteroskedasticity to invoke an instant increase in signal-to-noise ratio by 50% and the statistical/detection sensitivity by as high as 30% regardless of the downstream mapping and normalization methods. Most importantly, the power-law correction improves concordance in significant calls among different normalization methods of a data series averagely by 22%. When presented with a higher sequence depth (4 times difference), the improvement in concordance is asymmetrical (32% for the higher sequencing depth instance versus 13% for the lower instance) and demonstrates that the simple power-law correction can increase significant detection with higher sequencing depths. Finally, the correction dramatically enhances the statistical conclusions and eludes the metastasis potential of the NUGC3 cell line against AGS of our dilution analysis. The finite-size effects due to undersampling generally plagues transcript count data with reproducibility issues but can be minimized through a simple power-law correction of the count distribution. This distribution correction has direct implication on the biological interpretation of the study and the rigor of the scientific findings. This article was reviewed by Oliviero Carugo, Thomas Dandekar and Sandor Pongor.

A rigorous and simpler method of image charges

NASA Astrophysics Data System (ADS)

Ladera, C. L.; Donoso, G.

2016-07-01

The method of image charges relies on the proven uniqueness of the solution of the Laplace differential equation for an electrostatic potential which satisfies some specified boundary conditions. Granted by that uniqueness, the method of images is rightly described as nothing but shrewdly guessing which and where image charges are to be placed to solve the given electrostatics problem. Here we present an alternative image charges method that is based not on guessing but on rigorous and simpler theoretical grounds, namely the constant potential inside any conductor and the application of powerful geometric symmetries. The aforementioned required uniqueness and, more importantly, guessing are therefore both altogether dispensed with. Our two new theoretical fundaments also allow the image charges method to be introduced in earlier physics courses for engineering and sciences students, instead of its present and usual introduction in electromagnetic theory courses that demand familiarity with the Laplace differential equation and its boundary conditions.

B-ALL minimal residual disease flow cytometry: an application of a novel method for optimization of a single-tube model.

PubMed

Shaver, Aaron C; Greig, Bruce W; Mosse, Claudio A; Seegmiller, Adam C

2015-05-01

Optimizing a clinical flow cytometry panel can be a subjective process dependent on experience. We develop a quantitative method to make this process more rigorous and apply it to B lymphoblastic leukemia/lymphoma (B-ALL) minimal residual disease (MRD) testing. We retrospectively analyzed our existing three-tube, seven-color B-ALL MRD panel and used our novel method to develop an optimized one-tube, eight-color panel, which was tested prospectively. The optimized one-tube, eight-color panel resulted in greater efficiency of time and resources with no loss in diagnostic power. Constructing a flow cytometry panel using a rigorous, objective, quantitative method permits optimization and avoids problems of interdependence and redundancy in a large, multiantigen panel. Copyright© by the American Society for Clinical Pathology.

Exact statistical results for binary mixing and reaction in variable density turbulence

NASA Astrophysics Data System (ADS)

Ristorcelli, J. R.

2017-02-01

We report a number of rigorous statistical results on binary active scalar mixing in variable density turbulence. The study is motivated by mixing between pure fluids with very different densities and whose density intensity is of order unity. Our primary focus is the derivation of exact mathematical results for mixing in variable density turbulence and we do point out the potential fields of application of the results. A binary one step reaction is invoked to derive a metric to asses the state of mixing. The mean reaction rate in variable density turbulent mixing can be expressed, in closed form, using the first order Favre mean variables and the Reynolds averaged density variance, ⟨ρ2⟩ . We show that the normalized density variance, ⟨ρ2⟩ , reflects the reduction of the reaction due to mixing and is a mix metric. The result is mathematically rigorous. The result is the variable density analog, the normalized mass fraction variance ⟨c2⟩ used in constant density turbulent mixing. As a consequence, we demonstrate that use of the analogous normalized Favre variance of the mass fraction, c″ ⁣2˜ , as a mix metric is not theoretically justified in variable density turbulence. We additionally derive expressions relating various second order moments of the mass fraction, specific volume, and density fields. The central role of the density specific volume covariance ⟨ρ v ⟩ is highlighted; it is a key quantity with considerable dynamical significance linking various second order statistics. For laboratory experiments, we have developed exact relations between the Reynolds scalar variance ⟨c2⟩ its Favre analog c″ ⁣2˜ , and various second moments including ⟨ρ v ⟩ . For moment closure models that evolve ⟨ρ v ⟩ and not ⟨ρ2⟩ , we provide a novel expression for ⟨ρ2⟩ in terms of a rational function of ⟨ρ v ⟩ that avoids recourse to Taylor series methods (which do not converge for large density differences). We have derived analytic results relating several other second and third order moments and see coupling between odd and even order moments demonstrating a natural and inherent skewness in the mixing in variable density turbulence. The analytic results have applications in the areas of isothermal material mixing, isobaric thermal mixing, and simple chemical reaction (in progress variable formulation).

Statistical framework for the utilization of simultaneous pupil plane and focal plane telemetry for exoplanet imaging. I. Accounting for aberrations in multiple planes.

PubMed

Frazin, Richard A

2016-04-01

A new generation of telescopes with mirror diameters of 20 m or more, called extremely large telescopes (ELTs), has the potential to provide unprecedented imaging and spectroscopy of exoplanetary systems, if the difficulties in achieving the extremely high dynamic range required to differentiate the planetary signal from the star can be overcome to a sufficient degree. Fully utilizing the potential of ELTs for exoplanet imaging will likely require simultaneous and self-consistent determination of both the planetary image and the unknown aberrations in multiple planes of the optical system, using statistical inference based on the wavefront sensor and science camera data streams. This approach promises to overcome the most important systematic errors inherent in the various schemes based on differential imaging, such as angular differential imaging and spectral differential imaging. This paper is the first in a series on this subject, in which a formalism is established for the exoplanet imaging problem, setting the stage for the statistical inference methods to follow in the future. Every effort has been made to be rigorous and complete, so that validity of approximations to be made later can be assessed. Here, the polarimetric image is expressed in terms of aberrations in the various planes of a polarizing telescope with an adaptive optics system. Further, it is shown that current methods that utilize focal plane sensing to correct the speckle field, e.g., electric field conjugation, rely on the tacit assumption that aberrations on multiple optical surfaces can be represented as aberration on a single optical surface, ultimately limiting their potential effectiveness for ground-based astronomy.

Time-of-flight PET image reconstruction using origin ensembles.

PubMed

Wülker, Christian; Sitek, Arkadiusz; Prevrhal, Sven

2015-03-07

The origin ensemble (OE) algorithm is a novel statistical method for minimum-mean-square-error (MMSE) reconstruction of emission tomography data. This method allows one to perform reconstruction entirely in the image domain, i.e. without the use of forward and backprojection operations. We have investigated the OE algorithm in the context of list-mode (LM) time-of-flight (TOF) PET reconstruction. In this paper, we provide a general introduction to MMSE reconstruction, and a statistically rigorous derivation of the OE algorithm. We show how to efficiently incorporate TOF information into the reconstruction process, and how to correct for random coincidences and scattered events. To examine the feasibility of LM-TOF MMSE reconstruction with the OE algorithm, we applied MMSE-OE and standard maximum-likelihood expectation-maximization (ML-EM) reconstruction to LM-TOF phantom data with a count number typically registered in clinical PET examinations. We analyzed the convergence behavior of the OE algorithm, and compared reconstruction time and image quality to that of the EM algorithm. In summary, during the reconstruction process, MMSE-OE contrast recovery (CRV) remained approximately the same, while background variability (BV) gradually decreased with an increasing number of OE iterations. The final MMSE-OE images exhibited lower BV and a slightly lower CRV than the corresponding ML-EM images. The reconstruction time of the OE algorithm was approximately 1.3 times longer. At the same time, the OE algorithm can inherently provide a comprehensive statistical characterization of the acquired data. This characterization can be utilized for further data processing, e.g. in kinetic analysis and image registration, making the OE algorithm a promising approach in a variety of applications.

Time-of-flight PET image reconstruction using origin ensembles

NASA Astrophysics Data System (ADS)

Wülker, Christian; Sitek, Arkadiusz; Prevrhal, Sven

2015-03-01

The origin ensemble (OE) algorithm is a novel statistical method for minimum-mean-square-error (MMSE) reconstruction of emission tomography data. This method allows one to perform reconstruction entirely in the image domain, i.e. without the use of forward and backprojection operations. We have investigated the OE algorithm in the context of list-mode (LM) time-of-flight (TOF) PET reconstruction. In this paper, we provide a general introduction to MMSE reconstruction, and a statistically rigorous derivation of the OE algorithm. We show how to efficiently incorporate TOF information into the reconstruction process, and how to correct for random coincidences and scattered events. To examine the feasibility of LM-TOF MMSE reconstruction with the OE algorithm, we applied MMSE-OE and standard maximum-likelihood expectation-maximization (ML-EM) reconstruction to LM-TOF phantom data with a count number typically registered in clinical PET examinations. We analyzed the convergence behavior of the OE algorithm, and compared reconstruction time and image quality to that of the EM algorithm. In summary, during the reconstruction process, MMSE-OE contrast recovery (CRV) remained approximately the same, while background variability (BV) gradually decreased with an increasing number of OE iterations. The final MMSE-OE images exhibited lower BV and a slightly lower CRV than the corresponding ML-EM images. The reconstruction time of the OE algorithm was approximately 1.3 times longer. At the same time, the OE algorithm can inherently provide a comprehensive statistical characterization of the acquired data. This characterization can be utilized for further data processing, e.g. in kinetic analysis and image registration, making the OE algorithm a promising approach in a variety of applications.

Thermodynamics of ideal quantum gas with fractional statistics in D dimensions.

PubMed

Potter, Geoffrey G; Müller, Gerhard; Karbach, Michael

2007-06-01

We present exact and explicit results for the thermodynamic properties (isochores, isotherms, isobars, response functions, velocity of sound) of a quantum gas in dimensions D > or = 1 and with fractional exclusion statistics 0 < or = g < or =1 connecting bosons (g=0) and fermions (g=1) . In D=1 the results are equivalent to those of the Calogero-Sutherland model. Emphasis is given to the crossover between bosonlike and fermionlike features, caused by aspects of the statistical interaction that mimic long-range attraction and short-range repulsion. A phase transition along the isobar occurs at a nonzero temperature in all dimensions. The T dependence of the velocity of sound is in simple relation to isochores and isobars. The effects of soft container walls are accounted for rigorously for the case of a pure power-law potential.

Blazar flaring patterns (B-FlaP) classifying blazar candidate of uncertain type in the third Fermi-LAT catalogue by artificial neural networks

NASA Astrophysics Data System (ADS)

Chiaro, G.; Salvetti, D.; La Mura, G.; Giroletti, M.; Thompson, D. J.; Bastieri, D.

2016-11-01

The Fermi-Large Area Telescope (LAT) is currently the most important facility for investigating the GeV γ-ray sky. With Fermi-LAT, more than three thousand γ-ray sources have been discovered so far. 1144 (˜40 per cent) of the sources are active galaxies of the blazar class, and 573 (˜20 per cent) are listed as blazar candidate of uncertain type (BCU), or sources without a conclusive classification. We use the empirical cumulative distribution functions and the artificial neural networks for a fast method of screening and classification for BCUs based on data collected at γ-ray energies only, when rigorous multiwavelength analysis is not available. Based on our method, we classify 342 BCUs as BL Lacs and 154 as flat-spectrum radio quasars, while 77 objects remain uncertain. Moreover, radio analysis and direct observations in ground-based optical observatories are used as counterparts to the statistical classifications to validate the method. This approach is of interest because of the increasing number of unclassified sources in Fermi catalogues and because blazars and in particular their subclass high synchrotron peak objects are the main targets of atmospheric Cherenkov telescopes.

Flexible and scalable methods for quantifying stochastic variability in the era of massive time-domain astronomical data sets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kelly, Brandon C.; Becker, Andrew C.; Sobolewska, Malgosia

2014-06-10

We present the use of continuous-time autoregressive moving average (CARMA) models as a method for estimating the variability features of a light curve, and in particular its power spectral density (PSD). CARMA models fully account for irregular sampling and measurement errors, making them valuable for quantifying variability, forecasting and interpolating light curves, and variability-based classification. We show that the PSD of a CARMA model can be expressed as a sum of Lorentzian functions, which makes them extremely flexible and able to model a broad range of PSDs. We present the likelihood function for light curves sampled from CARMA processes, placingmore » them on a statistically rigorous foundation, and we present a Bayesian method to infer the probability distribution of the PSD given the measured light curve. Because calculation of the likelihood function scales linearly with the number of data points, CARMA modeling scales to current and future massive time-domain data sets. We conclude by applying our CARMA modeling approach to light curves for an X-ray binary, two active galactic nuclei, a long-period variable star, and an RR Lyrae star in order to illustrate their use, applicability, and interpretation.« less

Model Selection in the Analysis of Photoproduction Data

NASA Astrophysics Data System (ADS)

Landay, Justin

2017-01-01

Scattering experiments provide one of the most powerful and useful tools for probing matter to better understand its fundamental properties governed by the strong interaction. As the spectroscopy of the excited states of nucleons enters a new era of precision ushered in by improved experiments at Jefferson Lab and other facilities around the world, traditional partial-wave analysis methods must be adjusted accordingly. In this poster, we present a rigorous set of statistical tools and techniques that we implemented; most notably, the LASSO method, which serves for the selection of the simplest model, allowing us to avoid over fitting. In the case of establishing the spectrum of exited baryons, it avoids overpopulation of the spectrum and thus the occurrence of false-positives. This is a prerequisite to reliably compare theories like lattice QCD or quark models to experiments. Here, we demonstrate the principle by simultaneously fitting three observables in neutral pion photo-production, such as the differential cross section, beam asymmetry and target polarization across thousands of data points. Other authors include Michael Doring, Bin Hu, and Raquel Molina.

From classical to quantum and back: Hamiltonian adaptive resolution path integral, ring polymer, and centroid molecular dynamics

NASA Astrophysics Data System (ADS)

Kreis, Karsten; Kremer, Kurt; Potestio, Raffaello; Tuckerman, Mark E.

2017-12-01

Path integral-based methodologies play a crucial role for the investigation of nuclear quantum effects by means of computer simulations. However, these techniques are significantly more demanding than corresponding classical simulations. To reduce this numerical effort, we recently proposed a method, based on a rigorous Hamiltonian formulation, which restricts the quantum modeling to a small but relevant spatial region within a larger reservoir where particles are treated classically. In this work, we extend this idea and show how it can be implemented along with state-of-the-art path integral simulation techniques, including path-integral molecular dynamics, which allows for the calculation of quantum statistical properties, and ring-polymer and centroid molecular dynamics, which allow the calculation of approximate quantum dynamical properties. To this end, we derive a new integration algorithm that also makes use of multiple time-stepping. The scheme is validated via adaptive classical-path-integral simulations of liquid water. Potential applications of the proposed multiresolution method are diverse and include efficient quantum simulations of interfaces as well as complex biomolecular systems such as membranes and proteins.

Enhancing rigor and practice of scoping reviews in social policy research: considerations from a worked example on the Americans with disabilities act.

PubMed

Harris, Sarah Parker; Gould, Robert; Fujiura, Glenn

2015-01-01

There is increasing theoretical consideration about the use of systematic and scoping reviews of evidence in informing disability and rehabilitation research and practice. Indicative of this trend, this journal published a piece by Rumrill, Fitzgerald and Merchant in 2010 explaining the utility and process for conducting reviews of intervention-based research. There is still need to consider how to apply such rigor when conducting more exploratory reviews of heterogeneous research. This article explores the challenges, benefits, and procedures for conducting rigorous exploratory scoping reviews of diverse evidence. The article expands upon Rumrill, Fitzgerald and Merchant's framework and considers its application to more heterogeneous evidence on the impact of social policy. A worked example of a scoping review of the Americans with Disabilities Act is provided with a procedural framework for conducting scoping reviews on the effects of a social policy. The need for more nuanced techniques for enhancing rigor became apparent during the review process. There are multiple methodological steps that can enhance the utility of exploratory scoping reviews. The potential of systematic consideration during the exploratory review process is shown as a viable method to enhance the rigor in reviewing diverse bodies of evidence.

Knowledge translation and implementation in spinal cord injury: a systematic review

PubMed Central

Noonan, VK; Wolfe, DL; Thorogood, NP; Park, SE; Hsieh, JT; Eng, JJ

2015-01-01

Objective To conduct a systematic review examining the effectiveness of knowledge translation (KT) interventions in changing clinical practice and patient outcomes. Methods MEDLINE/PubMed, CINAHL, EMBASE and PsycINFO were searched for studies published from January 1980 to July 2012 that reported and evaluated an implemented KT intervention in spinal cord injury (SCI) care. We reviewed and summarized results from studies that documented the implemented KT intervention, its impact on changing clinician behavior and patient outcomes as well as the facilitators and barriers encountered during the implementation. Results A total of 13 articles featuring 10 studies were selected and abstracted from 4650 identified articles. KT interventions included developing and implementing patient care protocols, providing clinician education and incorporating outcome measures into clinical practice. The methods (or drivers) to facilitate the implementation included organizing training sessions for clinical staff, introducing computerized reminders and involving organizational leaders. The methodological quality of studies was mostly poor. Only 3 out of 10 studies evaluated the success of the implementation using statistical analyses, and all 3 reported significant behavior change. Out of the 10 studies, 6 evaluated the effect of the implementation on patient outcomes using statistical analyses, with 4 reporting significant improvements. The commonly cited facilitators and barriers were communication and resources, respectively. Conclusion The field of KT in SCI is in its infancy with only a few relevant publications. However, there is some evidence that KT interventions may change clinician behavior and improve patient outcomes. Future studies should ensure rigorous study methods are used to evaluate KT interventions. PMID:24796445

Development of modern human subadult age and sex estimation standards using multi-slice computed tomography images from medical examiner's offices

NASA Astrophysics Data System (ADS)

Stock, Michala K.; Stull, Kyra E.; Garvin, Heather M.; Klales, Alexandra R.

2016-10-01

Forensic anthropologists are routinely asked to estimate a biological profile (i.e., age, sex, ancestry and stature) from a set of unidentified remains. In contrast to the abundance of collections and techniques associated with adult skeletons, there is a paucity of modern, documented subadult skeletal material, which limits the creation and validation of appropriate forensic standards. Many are forced to use antiquated methods derived from small sample sizes, which given documented secular changes in the growth and development of children, are not appropriate for application in the medico-legal setting. Therefore, the aim of this project is to use multi-slice computed tomography (MSCT) data from a large, diverse sample of modern subadults to develop new methods to estimate subadult age and sex for practical forensic applications. The research sample will consist of over 1,500 full-body MSCT scans of modern subadult individuals (aged birth to 20 years) obtained from two U.S. medical examiner's offices. Statistical analysis of epiphyseal union scores, long bone osteometrics, and os coxae landmark data will be used to develop modern subadult age and sex estimation standards. This project will result in a database of information gathered from the MSCT scans, as well as the creation of modern, statistically rigorous standards for skeletal age and sex estimation in subadults. Furthermore, the research and methods developed in this project will be applicable to dry bone specimens, MSCT scans, and radiographic images, thus providing both tools and continued access to data for forensic practitioners in a variety of settings.

Expected values and variances of Bragg peak intensities measured in a nanocrystalline powder diffraction experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Öztürk, Hande; Noyan, I. Cevdet

A rigorous study of sampling and intensity statistics applicable for a powder diffraction experiment as a function of crystallite size is presented. Our analysis yields approximate equations for the expected value, variance and standard deviations for both the number of diffracting grains and the corresponding diffracted intensity for a given Bragg peak. The classical formalism published in 1948 by Alexander, Klug & Kummer [J. Appl. Phys.(1948),19, 742–753] appears as a special case, limited to large crystallite sizes, here. It is observed that both the Lorentz probability expression and the statistics equations used in the classical formalism are inapplicable for nanocrystallinemore » powder samples.« less

Expected values and variances of Bragg peak intensities measured in a nanocrystalline powder diffraction experiment

DOE PAGES

Öztürk, Hande; Noyan, I. Cevdet

2017-08-24

A rigorous study of sampling and intensity statistics applicable for a powder diffraction experiment as a function of crystallite size is presented. Our analysis yields approximate equations for the expected value, variance and standard deviations for both the number of diffracting grains and the corresponding diffracted intensity for a given Bragg peak. The classical formalism published in 1948 by Alexander, Klug & Kummer [J. Appl. Phys.(1948),19, 742–753] appears as a special case, limited to large crystallite sizes, here. It is observed that both the Lorentz probability expression and the statistics equations used in the classical formalism are inapplicable for nanocrystallinemore » powder samples.« less

METHOD OF PREPARING UF$sub 6$

DOEpatents

Davidson, R.; Fried, S.

1959-10-27

A method is described of preparing uraniurn hexafluoride without the use of fluorine gas by reacting uraniurn tetrafluoride with oxygen gas under rigorously anhydrous conditions at 600 to 1300 deg K within a pre-fluorinated nickel vessel.

Cluster-level statistical inference in fMRI datasets: The unexpected behavior of random fields in high dimensions.

PubMed

Bansal, Ravi; Peterson, Bradley S

2018-06-01

Identifying regional effects of interest in MRI datasets usually entails testing a priori hypotheses across many thousands of brain voxels, requiring control for false positive findings in these multiple hypotheses testing. Recent studies have suggested that parametric statistical methods may have incorrectly modeled functional MRI data, thereby leading to higher false positive rates than their nominal rates. Nonparametric methods for statistical inference when conducting multiple statistical tests, in contrast, are thought to produce false positives at the nominal rate, which has thus led to the suggestion that previously reported studies should reanalyze their fMRI data using nonparametric tools. To understand better why parametric methods may yield excessive false positives, we assessed their performance when applied both to simulated datasets of 1D, 2D, and 3D Gaussian Random Fields (GRFs) and to 710 real-world, resting-state fMRI datasets. We showed that both the simulated 2D and 3D GRFs and the real-world data contain a small percentage (<6%) of very large clusters (on average 60 times larger than the average cluster size), which were not present in 1D GRFs. These unexpectedly large clusters were deemed statistically significant using parametric methods, leading to empirical familywise error rates (FWERs) as high as 65%: the high empirical FWERs were not a consequence of parametric methods failing to model spatial smoothness accurately, but rather of these very large clusters that are inherently present in smooth, high-dimensional random fields. In fact, when discounting these very large clusters, the empirical FWER for parametric methods was 3.24%. Furthermore, even an empirical FWER of 65% would yield on average less than one of those very large clusters in each brain-wide analysis. Nonparametric methods, in contrast, estimated distributions from those large clusters, and therefore, by construct rejected the large clusters as false positives at the nominal FWERs. Those rejected clusters were outlying values in the distribution of cluster size but cannot be distinguished from true positive findings without further analyses, including assessing whether fMRI signal in those regions correlates with other clinical, behavioral, or cognitive measures. Rejecting the large clusters, however, significantly reduced the statistical power of nonparametric methods in detecting true findings compared with parametric methods, which would have detected most true findings that are essential for making valid biological inferences in MRI data. Parametric analyses, in contrast, detected most true findings while generating relatively few false positives: on average, less than one of those very large clusters would be deemed a true finding in each brain-wide analysis. We therefore recommend the continued use of parametric methods that model nonstationary smoothness for cluster-level, familywise control of false positives, particularly when using a Cluster Defining Threshold of 2.5 or higher, and subsequently assessing rigorously the biological plausibility of the findings, even for large clusters. Finally, because nonparametric methods yielded a large reduction in statistical power to detect true positive findings, we conclude that the modest reduction in false positive findings that nonparametric analyses afford does not warrant a re-analysis of previously published fMRI studies using nonparametric techniques. Copyright © 2018 Elsevier Inc. All rights reserved.

Model-Based Assessment of Estuary Ecosystem Health Using the Latent Health Factor Index, with Application to the Richibucto Estuary

PubMed Central

Chiu, Grace S.; Wu, Margaret A.; Lu, Lin

2013-01-01

The ability to quantitatively assess ecological health is of great interest to those tasked with monitoring and conserving ecosystems. For decades, biomonitoring research and policies have relied on multimetric health indices of various forms. Although indices are numbers, many are constructed based on qualitative procedures, thus limiting the quantitative rigor of the practical interpretations of such indices. The statistical modeling approach to construct the latent health factor index (LHFI) was recently developed. With ecological data that otherwise are used to construct conventional multimetric indices, the LHFI framework expresses such data in a rigorous quantitative model, integrating qualitative features of ecosystem health and preconceived ecological relationships among such features. This hierarchical modeling approach allows unified statistical inference of health for observed sites (along with prediction of health for partially observed sites, if desired) and of the relevance of ecological drivers, all accompanied by formal uncertainty statements from a single, integrated analysis. Thus far, the LHFI approach has been demonstrated and validated in a freshwater context. We adapt this approach to modeling estuarine health, and illustrate it on the previously unassessed system in Richibucto in New Brunswick, Canada, where active oyster farming is a potential stressor through its effects on sediment properties. Field data correspond to health metrics that constitute the popular AZTI marine biotic index and the infaunal trophic index, as well as abiotic predictors preconceived to influence biota. Our paper is the first to construct a scientifically sensible model that rigorously identifies the collective explanatory capacity of salinity, distance downstream, channel depth, and silt–clay content–all regarded a priori as qualitatively important abiotic drivers–towards site health in the Richibucto ecosystem. This suggests the potential effectiveness of the LHFI approach for assessing not only freshwater systems but aquatic ecosystems in general. PMID:23785443

Hybrid Theory of Electron-Hydrogenic Systems Elastic Scattering

NASA Technical Reports Server (NTRS)

Bhatia, A. K.

2007-01-01

Accurate electron-hydrogen and electron-hydrogenic cross sections are required to interpret fusion experiments, laboratory plasma physics and properties of the solar and astrophysical plasmas. We have developed a method in which the short-range and long-range correlations can be included at the same time in the scattering equations. The phase shifts have rigorous lower bounds and the scattering lengths have rigorous upper bounds. The phase shifts in the resonance region can be used to calculate very accurately the resonance parameters.

Augmented assessment as a means to augmented reality.

PubMed

Bergeron, Bryan

2006-01-01

Rigorous scientific assessment of educational technologies typically lags behind the availability of the technologies by years because of the lack of validated instruments and benchmarks. Even when the appropriate assessment instruments are available, they may not be applied because of time and monetary constraints. Work in augmented reality, instrumented mannequins, serious gaming, and similar promising educational technologies that haven't undergone timely, rigorous evaluation, highlights the need for assessment methodologies that address the limitations of traditional approaches. The most promising augmented assessment solutions incorporate elements of rapid prototyping used in the software industry, simulation-based assessment techniques modeled after methods used in bioinformatics, and object-oriented analysis methods borrowed from object oriented programming.

On analyticity of linear waves scattered by a layered medium

NASA Astrophysics Data System (ADS)

Nicholls, David P.

2017-10-01

The scattering of linear waves by periodic structures is a crucial phenomena in many branches of applied physics and engineering. In this paper we establish rigorous analytic results necessary for the proper numerical analysis of a class of High-Order Perturbation of Surfaces methods for simulating such waves. More specifically, we prove a theorem on existence and uniqueness of solutions to a system of partial differential equations which model the interaction of linear waves with a multiply layered periodic structure in three dimensions. This result provides hypotheses under which a rigorous numerical analysis could be conducted for recent generalizations to the methods of Operator Expansions, Field Expansions, and Transformed Field Expansions.

Guidelines for conducting rigorous health care psychosocial cross-cultural/language qualitative research.

PubMed

Arriaza, Pablo; Nedjat-Haiem, Frances; Lee, Hee Yun; Martin, Shadi S

2015-01-01

The purpose of this article is to synthesize and chronicle the authors' experiences as four bilingual and bicultural researchers, each experienced in conducting cross-cultural/cross-language qualitative research. Through narrative descriptions of experiences with Latinos, Iranians, and Hmong refugees, the authors discuss their rewards, challenges, and methods of enhancing rigor, trustworthiness, and transparency when conducting cross-cultural/cross-language research. The authors discuss and explore how to effectively manage cross-cultural qualitative data, how to effectively use interpreters and translators, how to identify best methods of transcribing data, and the role of creating strong community relationships. The authors provide guidelines for health care professionals to consider when engaging in cross-cultural qualitative research.

On the Response of the Special Sensor Microwave/Imager to the Marine Environment: Implications for Atmospheric Parameter Retrievals. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Petty, Grant W.

1990-01-01

A reasonably rigorous basis for understanding and extracting the physical information content of Special Sensor Microwave/Imager (SSM/I) satellite images of the marine environment is provided. To this end, a comprehensive algebraic parameterization is developed for the response of the SSM/I to a set of nine atmospheric and ocean surface parameters. The brightness temperature model includes a closed-form approximation to microwave radiative transfer in a non-scattering atmosphere and fitted models for surface emission and scattering based on geometric optics calculations for the roughened sea surface. The combined model is empirically tuned using suitable sets of SSM/I data and coincident surface observations. The brightness temperature model is then used to examine the sensitivity of the SSM/I to realistic variations in the scene being observed and to evaluate the theoretical maximum precision of global SSM/I retrievals of integrated water vapor, integrated cloud liquid water, and surface wind speed. A general minimum-variance method for optimally retrieving geophysical parameters from multichannel brightness temperature measurements is outlined, and several global statistical constraints of the type required by this method are computed. Finally, a unified set of efficient statistical and semi-physical algorithms is presented for obtaining fields of surface wind speed, integrated water vapor, cloud liquid water, and precipitation from SSM/I brightness temperature data. Features include: a semi-physical method for retrieving integrated cloud liquid water at 15 km resolution and with rms errors as small as approximately 0.02 kg/sq m; a 3-channel statistical algorithm for integrated water vapor which was constructed so as to have improved linear response to water vapor and reduced sensitivity to precipitation; and two complementary indices of precipitation activity (based on 37 GHz attenuation and 85 GHz scattering, respectively), each of which are relatively insensitive to variations in other environmental parameters.

Analysis of Perfluorinated Chemicals and Their Fluorinated Precursors in Sludge: Method Development and Initial Results

EPA Science Inventory

A rigorous method was developed to maximize the extraction efficacy for perfluorocarboxylic acids (PFCAs), perfluorosulfonates (PFSAs), fluorotelomer alcohols (FTOHs), fluorotelomer acrylates (FTAc), perfluorosulfonamides (FOSAs), and perfluorosulfonamidoethanols (FOSEs) from was...

Adaptive characterization of recrystallization kinetics in IF steel by electron backscatter diffraction.

PubMed

Kim, Dong-Kyu; Park, Won-Woong; Lee, Ho Won; Kang, Seong-Hoon; Im, Yong-Taek

2013-12-01

In this study, a rigorous methodology for quantifying recrystallization kinetics by electron backscatter diffraction is proposed in order to reduce errors associated with the operator's skill. An adaptive criterion to determine adjustable grain orientation spread depending on the recrystallization stage is proposed to better identify the recrystallized grains in the partially recrystallized microstructure. The proposed method was applied in characterizing the microstructure evolution during annealing of interstitial-free steel cold rolled to low and high true strain levels of 0.7 and 1.6, respectively. The recrystallization kinetics determined by the proposed method was found to be consistent with the standard method of Vickers microhardness. The application of the proposed method to the overall recrystallization stages showed that it can be used for the rigorous characterization of progressive microstructure evolution, especially for the severely deformed material. © 2013 The Authors Journal of Microscopy © 2013 Royal Microscopical Society.

Qualitative research methods: key features and insights gained from use in infection prevention research.

PubMed

Forman, Jane; Creswell, John W; Damschroder, Laura; Kowalski, Christine P; Krein, Sarah L

2008-12-01

Infection control professionals and hospital epidemiologists are accustomed to using quantitative research. Although quantitative studies are extremely important in the field of infection control and prevention, often they cannot help us explain why certain factors affect the use of infection control practices and identify the underlying mechanisms through which they do so. Qualitative research methods, which use open-ended techniques, such as interviews, to collect data and nonstatistical techniques to analyze it, provide detailed, diverse insights of individuals, useful quotes that bring a realism to applied research, and information about how different health care settings operate. Qualitative research can illuminate the processes underlying statistical correlations, inform the development of interventions, and show how interventions work to produce observed outcomes. This article describes the key features of qualitative research and the advantages that such features add to existing quantitative research approaches in the study of infection control. We address the goal of qualitative research, the nature of the research process, sampling, data collection and analysis, validity, generalizability of findings, and presentation of findings. Health services researchers are increasingly using qualitative methods to address practical problems by uncovering interacting influences in complex health care environments. Qualitative research methods, applied with expertise and rigor, can contribute important insights to infection prevention efforts.

Re-establishment of rigor mortis: evidence for a considerably longer post-mortem time span.

PubMed

Crostack, Chiara; Sehner, Susanne; Raupach, Tobias; Anders, Sven

2017-07-01

Re-establishment of rigor mortis following mechanical loosening is used as part of the complex method for the forensic estimation of the time since death in human bodies and has formerly been reported to occur up to 8-12 h post-mortem (hpm). We recently described our observation of the phenomenon in up to 19 hpm in cases with in-hospital death. Due to the case selection (preceding illness, immobilisation), transfer of these results to forensic cases might be limited. We therefore examined 67 out-of-hospital cases of sudden death with known time points of death. Re-establishment of rigor mortis was positive in 52.2% of cases and was observed up to 20 hpm. In contrast to the current doctrine that a recurrence of rigor mortis is always of a lesser degree than its first manifestation in a given patient, muscular rigidity at re-establishment equalled or even exceeded the degree observed before dissolving in 21 joints. Furthermore, this is the first study to describe that the phenomenon appears to be independent of body or ambient temperature.

Examining the Statistical Rigor of Test and Evaluation Results in the Live, Virtual and Constructive Environment

DTIC Science & Technology

2011-06-01

Committee Meeting. 23 June 2008. Bjorkman, Eileen A. and Frank B. Gray . “Testing in a Joint Environment 2004-2008: Findings, Conclusions and...the LVC joint test environment to evaluate system performance and joint mission effectiveness (Bjorkman and Gray 2009a). The LVC battlespace...attack (Bjorkman and Gray 2009b). Figure 3 - JTEM Methodology (Bjorkman 2008) A key INTEGRAL FIRE lesson learned was realizing the need for each

An efficient diagnosis system for Parkinson's disease using kernel-based extreme learning machine with subtractive clustering features weighting approach.

PubMed

Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Zhao, Xue-Hua

2014-01-01

A novel hybrid method named SCFW-KELM, which integrates effective subtractive clustering features weighting and a fast classifier kernel-based extreme learning machine (KELM), has been introduced for the diagnosis of PD. In the proposed method, SCFW is used as a data preprocessing tool, which aims at decreasing the variance in features of the PD dataset, in order to further improve the diagnostic accuracy of the KELM classifier. The impact of the type of kernel functions on the performance of KELM has been investigated in detail. The efficiency and effectiveness of the proposed method have been rigorously evaluated against the PD dataset in terms of classification accuracy, sensitivity, specificity, area under the receiver operating characteristic (ROC) curve (AUC), f-measure, and kappa statistics value. Experimental results have demonstrated that the proposed SCFW-KELM significantly outperforms SVM-based, KNN-based, and ELM-based approaches and other methods in the literature and achieved highest classification results reported so far via 10-fold cross validation scheme, with the classification accuracy of 99.49%, the sensitivity of 100%, the specificity of 99.39%, AUC of 99.69%, the f-measure value of 0.9964, and kappa value of 0.9867. Promisingly, the proposed method might serve as a new candidate of powerful methods for the diagnosis of PD with excellent performance.

An Efficient Diagnosis System for Parkinson's Disease Using Kernel-Based Extreme Learning Machine with Subtractive Clustering Features Weighting Approach

PubMed Central

Ma, Chao; Ouyang, Jihong; Chen, Hui-Ling; Zhao, Xue-Hua

2014-01-01

A novel hybrid method named SCFW-KELM, which integrates effective subtractive clustering features weighting and a fast classifier kernel-based extreme learning machine (KELM), has been introduced for the diagnosis of PD. In the proposed method, SCFW is used as a data preprocessing tool, which aims at decreasing the variance in features of the PD dataset, in order to further improve the diagnostic accuracy of the KELM classifier. The impact of the type of kernel functions on the performance of KELM has been investigated in detail. The efficiency and effectiveness of the proposed method have been rigorously evaluated against the PD dataset in terms of classification accuracy, sensitivity, specificity, area under the receiver operating characteristic (ROC) curve (AUC), f-measure, and kappa statistics value. Experimental results have demonstrated that the proposed SCFW-KELM significantly outperforms SVM-based, KNN-based, and ELM-based approaches and other methods in the literature and achieved highest classification results reported so far via 10-fold cross validation scheme, with the classification accuracy of 99.49%, the sensitivity of 100%, the specificity of 99.39%, AUC of 99.69%, the f-measure value of 0.9964, and kappa value of 0.9867. Promisingly, the proposed method might serve as a new candidate of powerful methods for the diagnosis of PD with excellent performance. PMID:25484912

Methods for determining time of death.

PubMed

Madea, Burkhard

2016-12-01

Medicolegal death time estimation must estimate the time since death reliably. Reliability can only be provided empirically by statistical analysis of errors in field studies. Determining the time since death requires the calculation of measurable data along a time-dependent curve back to the starting point. Various methods are used to estimate the time since death. The current gold standard for death time estimation is a previously established nomogram method based on the two-exponential model of body cooling. Great experimental and practical achievements have been realized using this nomogram method. To reduce the margin of error of the nomogram method, a compound method was developed based on electrical and mechanical excitability of skeletal muscle, pharmacological excitability of the iris, rigor mortis, and postmortem lividity. Further increasing the accuracy of death time estimation involves the development of conditional probability distributions for death time estimation based on the compound method. Although many studies have evaluated chemical methods of death time estimation, such methods play a marginal role in daily forensic practice. However, increased precision of death time estimation has recently been achieved by considering various influencing factors (i.e., preexisting diseases, duration of terminal episode, and ambient temperature). Putrefactive changes may be used for death time estimation in water-immersed bodies. Furthermore, recently developed technologies, such as H magnetic resonance spectroscopy, can be used to quantitatively study decompositional changes. This review addresses the gold standard method of death time estimation in forensic practice and promising technological and scientific developments in the field.

Knowledge translation and implementation in spinal cord injury: a systematic review.

PubMed

Noonan, V K; Wolfe, D L; Thorogood, N P; Park, S E; Hsieh, J T; Eng, J J

2014-08-01

To conduct a systematic review examining the effectiveness of knowledge translation (KT) interventions in changing clinical practice and patient outcomes. MEDLINE/PubMed, CINAHL, EMBASE and PsycINFO were searched for studies published from January 1980 to July 2012 that reported and evaluated an implemented KT intervention in spinal cord injury (SCI) care. We reviewed and summarized results from studies that documented the implemented KT intervention, its impact on changing clinician behavior and patient outcomes as well as the facilitators and barriers encountered during the implementation. A total of 13 articles featuring 10 studies were selected and abstracted from 4650 identified articles. KT interventions included developing and implementing patient care protocols, providing clinician education and incorporating outcome measures into clinical practice. The methods (or drivers) to facilitate the implementation included organizing training sessions for clinical staff, introducing computerized reminders and involving organizational leaders. The methodological quality of studies was mostly poor. Only 3 out of 10 studies evaluated the success of the implementation using statistical analyses, and all 3 reported significant behavior change. Out of the 10 studies, 6 evaluated the effect of the implementation on patient outcomes using statistical analyses, with 4 reporting significant improvements. The commonly cited facilitators and barriers were communication and resources, respectively. The field of KT in SCI is in its infancy with only a few relevant publications. However, there is some evidence that KT interventions may change clinician behavior and improve patient outcomes. Future studies should ensure rigorous study methods are used to evaluate KT interventions.

Geometry of behavioral spaces: A computational approach to analysis and understanding of agent based models and agent behaviors

NASA Astrophysics Data System (ADS)

Cenek, Martin; Dahl, Spencer K.

2016-11-01

Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution. Often, a human has to observe an ABM's execution in order to analyze how the ABM functions, identify the emergent processes in the agent's behavior, or study a parameter's effect on the system-wide behavior. This paper introduces a new statistically based framework to automatically analyze agents' behavior, identify common system-wide patterns, and record the probability of agents changing their behavior from one pattern of behavior to another. We use network based techniques to analyze the landscape of common behaviors in an ABM's execution. Finally, we test the proposed framework with a series of experiments featuring increasingly emergent behavior. The proposed framework will allow computational comparison of ABM executions, exploration of a model's parameter configuration space, and identification of the behavioral building blocks in a model's dynamics.

Geometry of behavioral spaces: A computational approach to analysis and understanding of agent based models and agent behaviors.

PubMed

Cenek, Martin; Dahl, Spencer K

2016-11-01

Systems with non-linear dynamics frequently exhibit emergent system behavior, which is important to find and specify rigorously to understand the nature of the modeled phenomena. Through this analysis, it is possible to characterize phenomena such as how systems assemble or dissipate and what behaviors lead to specific final system configurations. Agent Based Modeling (ABM) is one of the modeling techniques used to study the interaction dynamics between a system's agents and its environment. Although the methodology of ABM construction is well understood and practiced, there are no computational, statistically rigorous, comprehensive tools to evaluate an ABM's execution. Often, a human has to observe an ABM's execution in order to analyze how the ABM functions, identify the emergent processes in the agent's behavior, or study a parameter's effect on the system-wide behavior. This paper introduces a new statistically based framework to automatically analyze agents' behavior, identify common system-wide patterns, and record the probability of agents changing their behavior from one pattern of behavior to another. We use network based techniques to analyze the landscape of common behaviors in an ABM's execution. Finally, we test the proposed framework with a series of experiments featuring increasingly emergent behavior. The proposed framework will allow computational comparison of ABM executions, exploration of a model's parameter configuration space, and identification of the behavioral building blocks in a model's dynamics.

Efficient numerical method for analyzing optical bistability in photonic crystal microcavities.

PubMed

Yuan, Lijun; Lu, Ya Yan

2013-05-20

Nonlinear optical effects can be enhanced by photonic crystal microcavities and be used to develop practical ultra-compact optical devices with low power requirements. The finite-difference time-domain method is the standard numerical method for simulating nonlinear optical devices, but it has limitations in terms of accuracy and efficiency. In this paper, a rigorous and efficient frequency-domain numerical method is developed for analyzing nonlinear optical devices where the nonlinear effect is concentrated in the microcavities. The method replaces the linear problem outside the microcavities by a rigorous and numerically computed boundary condition, then solves the nonlinear problem iteratively in a small region around the microcavities. Convergence of the iterative method is much easier to achieve since the size of the problem is significantly reduced. The method is presented for a specific two-dimensional photonic crystal waveguide-cavity system with a Kerr nonlinearity, using numerical methods that can take advantage of the geometric features of the structure. The method is able to calculate multiple solutions exhibiting the optical bistability phenomenon in the strongly nonlinear regime.

Spatial Statistical Data Fusion (SSDF)

NASA Technical Reports Server (NTRS)

Braverman, Amy J.; Nguyen, Hai M.; Cressie, Noel

2013-01-01

As remote sensing for scientific purposes has transitioned from an experimental technology to an operational one, the selection of instruments has become more coordinated, so that the scientific community can exploit complementary measurements. However, tech nological and scientific heterogeneity across devices means that the statistical characteristics of the data they collect are different. The challenge addressed here is how to combine heterogeneous remote sensing data sets in a way that yields optimal statistical estimates of the underlying geophysical field, and provides rigorous uncertainty measures for those estimates. Different remote sensing data sets may have different spatial resolutions, different measurement error biases and variances, and other disparate characteristics. A state-of-the-art spatial statistical model was used to relate the true, but not directly observed, geophysical field to noisy, spatial aggregates observed by remote sensing instruments. The spatial covariances of the true field and the covariances of the true field with the observations were modeled. The observations are spatial averages of the true field values, over pixels, with different measurement noise superimposed. A kriging framework is used to infer optimal (minimum mean squared error and unbiased) estimates of the true field at point locations from pixel-level, noisy observations. A key feature of the spatial statistical model is the spatial mixed effects model that underlies it. The approach models the spatial covariance function of the underlying field using linear combinations of basis functions of fixed size. Approaches based on kriging require the inversion of very large spatial covariance matrices, and this is usually done by making simplifying assumptions about spatial covariance structure that simply do not hold for geophysical variables. In contrast, this method does not require these assumptions, and is also computationally much faster. This method is fundamentally different than other approaches to data fusion for remote sensing data because it is inferential rather than merely descriptive. All approaches combine data in a way that minimizes some specified loss function. Most of these are more or less ad hoc criteria based on what looks good to the eye, or some criteria that relate only to the data at hand.

Output statistics of laser anemometers in sparsely seeded flows

NASA Technical Reports Server (NTRS)

Edwards, R. V.; Jensen, A. S.

1982-01-01

It is noted that until very recently, research on this topic concentrated on the particle arrival statistics and the influence of the optical parameters on them. Little attention has been paid to the influence of subsequent processing on the measurement statistics. There is also controversy over whether the effects of the particle statistics can be measured. It is shown here that some of the confusion derives from a lack of understanding of the experimental parameters that are to be controlled or known. A rigorous framework is presented for examining the measurement statistics of such systems. To provide examples, two problems are then addressed. The first has to do with a sample and hold processor, the second with what is called a saturable processor. The sample and hold processor converts the output to a continuous signal by holding the last reading until a new one is obtained. The saturable system is one where the maximum processable rate is arrived at by the dead time of some unit in the system. At high particle rates, the processed rate is determined through the dead time.

Topological Isomorphisms of Human Brain and Financial Market Networks

PubMed Central

Vértes, Petra E.; Nicol, Ruth M.; Chapman, Sandra C.; Watkins, Nicholas W.; Robertson, Duncan A.; Bullmore, Edward T.

2011-01-01

Although metaphorical and conceptual connections between the human brain and the financial markets have often been drawn, rigorous physical or mathematical underpinnings of this analogy remain largely unexplored. Here, we apply a statistical and graph theoretic approach to the study of two datasets – the time series of 90 stocks from the New York stock exchange over a 3-year period, and the fMRI-derived time series acquired from 90 brain regions over the course of a 10-min-long functional MRI scan of resting brain function in healthy volunteers. Despite the many obvious substantive differences between these two datasets, graphical analysis demonstrated striking commonalities in terms of global network topological properties. Both the human brain and the market networks were non-random, small-world, modular, hierarchical systems with fat-tailed degree distributions indicating the presence of highly connected hubs. These properties could not be trivially explained by the univariate time series statistics of stock price returns. This degree of topological isomorphism suggests that brains and markets can be regarded broadly as members of the same family of networks. The two systems, however, were not topologically identical. The financial market was more efficient and more modular – more highly optimized for information processing – than the brain networks; but also less robust to systemic disintegration as a result of hub deletion. We conclude that the conceptual connections between brains and markets are not merely metaphorical; rather these two information processing systems can be rigorously compared in the same mathematical language and turn out often to share important topological properties in common to some degree. There will be interesting scientific arbitrage opportunities in further work at the graph-theoretically mediated interface between systems neuroscience and the statistical physics of financial markets. PMID:22007161

Student Preferences for Instructional Methods in an Accounting Curriculum

ERIC Educational Resources Information Center

Abeysekera, Indra

2015-01-01

Student preferences among instructional methods are largely unexplored across the accounting curriculum. The algorithmic rigor of courses and the societal culture can influence these preferences. This study explored students' preferences of instructional methods for learning in six courses of the accounting curriculum that differ in algorithmic…

Circular instead of hierarchical: methodological principles for the evaluation of complex interventions

PubMed Central

Walach, Harald; Falkenberg, Torkel; Fønnebø, Vinjar; Lewith, George; Jonas, Wayne B

2006-01-01

Background The reasoning behind evaluating medical interventions is that a hierarchy of methods exists which successively produce improved and therefore more rigorous evidence based medicine upon which to make clinical decisions. At the foundation of this hierarchy are case studies, retrospective and prospective case series, followed by cohort studies with historical and concomitant non-randomized controls. Open-label randomized controlled studies (RCTs), and finally blinded, placebo-controlled RCTs, which offer most internal validity are considered the most reliable evidence. Rigorous RCTs remove bias. Evidence from RCTs forms the basis of meta-analyses and systematic reviews. This hierarchy, founded on a pharmacological model of therapy, is generalized to other interventions which may be complex and non-pharmacological (healing, acupuncture and surgery). Discussion The hierarchical model is valid for limited questions of efficacy, for instance for regulatory purposes and newly devised products and pharmacological preparations. It is inadequate for the evaluation of complex interventions such as physiotherapy, surgery and complementary and alternative medicine (CAM). This has to do with the essential tension between internal validity (rigor and the removal of bias) and external validity (generalizability). Summary Instead of an Evidence Hierarchy, we propose a Circular Model. This would imply a multiplicity of methods, using different designs, counterbalancing their individual strengths and weaknesses to arrive at pragmatic but equally rigorous evidence which would provide significant assistance in clinical and health systems innovation. Such evidence would better inform national health care technology assessment agencies and promote evidence based health reform. PMID:16796762

Forward modelling of global gravity fields with 3D density structures and an application to the high-resolution ( 2 km) gravity fields of the Moon

NASA Astrophysics Data System (ADS)

Šprlák, M.; Han, S.-C.; Featherstone, W. E.

2017-12-01

Rigorous modelling of the spherical gravitational potential spectra from the volumetric density and geometry of an attracting body is discussed. Firstly, we derive mathematical formulas for the spatial analysis of spherical harmonic coefficients. Secondly, we present a numerically efficient algorithm for rigorous forward modelling. We consider the finite-amplitude topographic modelling methods as special cases, with additional postulates on the volumetric density and geometry. Thirdly, we implement our algorithm in the form of computer programs and test their correctness with respect to the finite-amplitude topography routines. For this purpose, synthetic and realistic numerical experiments, applied to the gravitational field and geometry of the Moon, are performed. We also investigate the optimal choice of input parameters for the finite-amplitude modelling methods. Fourth, we exploit the rigorous forward modelling for the determination of the spherical gravitational potential spectra inferred by lunar crustal models with uniform, laterally variable, radially variable, and spatially (3D) variable bulk density. Also, we analyse these four different crustal models in terms of their spectral characteristics and band-limited radial gravitation. We demonstrate applicability of the rigorous forward modelling using currently available computational resources up to degree and order 2519 of the spherical harmonic expansion, which corresponds to a resolution of 2.2 km on the surface of the Moon. Computer codes, a user manual and scripts developed for the purposes of this study are publicly available to potential users.

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries.

PubMed

Wu, Jemma X; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P

2016-07-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries*

PubMed Central

Wu, Jemma X.; Song, Xiaomin; Pascovici, Dana; Zaw, Thiri; Care, Natasha; Krisp, Christoph; Molloy, Mark P.

2016-01-01

The use of data-independent acquisition methods such as SWATH for mass spectrometry based proteomics is usually performed with peptide MS/MS assay libraries which enable identification and quantitation of peptide peak areas. Reference assay libraries can be generated locally through information dependent acquisition, or obtained from community data repositories for commonly studied organisms. However, there have been no studies performed to systematically evaluate how locally generated or repository-based assay libraries affect SWATH performance for proteomic studies. To undertake this analysis, we developed a software workflow, SwathXtend, which generates extended peptide assay libraries by integration with a local seed library and delivers statistical analysis of SWATH-quantitative comparisons. We designed test samples using peptides from a yeast extract spiked into peptides from human K562 cell lysates at three different ratios to simulate protein abundance change comparisons. SWATH-MS performance was assessed using local and external assay libraries of varying complexities and proteome compositions. These experiments demonstrated that local seed libraries integrated with external assay libraries achieve better performance than local assay libraries alone, in terms of the number of identified peptides and proteins and the specificity to detect differentially abundant proteins. Our findings show that the performance of extended assay libraries is influenced by the MS/MS feature similarity of the seed and external libraries, while statistical analysis using multiple testing corrections increases the statistical rigor needed when searching against large extended assay libraries. PMID:27161445

Statistical model of exotic rotational correlations in emergent space-time

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hogan, Craig; Kwon, Ohkyung; Richardson, Jonathan

2017-06-06

A statistical model is formulated to compute exotic rotational correlations that arise as inertial frames and causal structure emerge on large scales from entangled Planck scale quantum systems. Noncommutative quantum dynamics are represented by random transverse displacements that respect causal symmetry. Entanglement is represented by covariance of these displacements in Planck scale intervals defined by future null cones of events on an observer's world line. Light that propagates in a nonradial direction inherits a projected component of the exotic rotational correlation that accumulates as a random walk in phase. A calculation of the projection and accumulation leads to exact predictionsmore » for statistical properties of exotic Planck scale correlations in an interferometer of any configuration. The cross-covariance for two nearly co-located interferometers is shown to depart only slightly from the autocovariance. Specific examples are computed for configurations that approximate realistic experiments, and show that the model can be rigorously tested.« less

The log-periodic-AR(1)-GARCH(1,1) model for financial crashes

NASA Astrophysics Data System (ADS)

Gazola, L.; Fernandes, C.; Pizzinga, A.; Riera, R.

2008-02-01

This paper intends to meet recent claims for the attainment of more rigorous statistical methodology within the econophysics literature. To this end, we consider an econometric approach to investigate the outcomes of the log-periodic model of price movements, which has been largely used to forecast financial crashes. In order to accomplish reliable statistical inference for unknown parameters, we incorporate an autoregressive dynamic and a conditional heteroskedasticity structure in the error term of the original model, yielding the log-periodic-AR(1)-GARCH(1,1) model. Both the original and the extended models are fitted to financial indices of U. S. market, namely S&P500 and NASDAQ. Our analysis reveal two main points: (i) the log-periodic-AR(1)-GARCH(1,1) model has residuals with better statistical properties and (ii) the estimation of the parameter concerning the time of the financial crash has been improved.

SDN solutions for switching dedicated long-haul connections: Measurements and comparative analysis

DOE PAGES

Rao, Nageswara S. V.

2016-01-01

We consider a scenario of two sites connected over a dedicated, long-haul connection that must quickly fail-over in response to degradations in host-to-host application performance. The traditional layer-2/3 hot stand-by fail-over solutions do not adequately address the variety of application degradations, and more recent single controller Software Defined Networks (SDN) solutions are not effective for long-haul connections. We present two methods for such a path fail-over using OpenFlow enabled switches: (a) a light-weight method that utilizes host scripts to monitor application performance and dpctl API for switching, and (b) a generic method that uses two OpenDaylight (ODL) controllers and RESTmore » interfaces. For both methods, the restoration dynamics of applications contain significant statistical variations due to the complexities of controllers, north bound interfaces and switches; they, together with the wide variety of vendor implementations, complicate the choice among such solutions. We develop the impulse-response method based on regression functions of performance parameters to provide a rigorous and objective comparison of different solutions. We describe testing results of the two proposed methods, using TCP throughput and connection rtt as main parameters, over a testbed consisting of HP and Cisco switches connected over longhaul connections emulated in hardware by ANUE devices. Lastly, the combination of analytical and experimental results demonstrate that the dpctl method responds seconds faster than the ODL method on average, even though both methods eventually restore original TCP throughput.« less

Tactics for mechanized reasoning: a commentary on Milner (1984) ‘The use of machines to assist in rigorous proof’

PubMed Central

Gordon, M. J. C.

2015-01-01

Robin Milner's paper, ‘The use of machines to assist in rigorous proof’, introduces methods for automating mathematical reasoning that are a milestone in the development of computer-assisted theorem proving. His ideas, particularly his theory of tactics, revolutionized the architecture of proof assistants. His methodology for automating rigorous proof soundly, particularly his theory of type polymorphism in programing, led to major contributions to the theory and design of programing languages. His citation for the 1991 ACM A.M. Turing award, the most prestigious award in computer science, credits him with, among other achievements, ‘probably the first theoretically based yet practical tool for machine assisted proof construction’. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society. PMID:25750147

Health Promotion in Small Business

PubMed Central

McCoy, Kira; Stinson, Kaylan; Scott, Kenneth; Tenney, Liliana; Newman, Lee S.

2015-01-01

Objective To assess the evidence regarding the adoption and efficacy of worksite health promotion programs (WHPPs) in small businesses. Methods Peer-reviewed research articles were identified from a database search. Included articles were published before July 2013, described a study that used an experimental or quasiexperimental design and either assessed adoption of WHPPs or conducted interventions in businesses with fewer than 500 employees. A review team scored the study’s rigor using the WHO-adapted GRADEprofiler “quality of evidence” criteria. Results Of the 84 retrieved articles, 19 met study inclusion criteria. Of these, only two met criteria for high rigor. Conclusions Fewer small businesses adopt WHPPs compared with large businesses. Two high-rigor studies found that employees were healthier postintervention. Higher quality research is needed to better understand why small businesses rarely adopt wellness programs and to demonstrate the value of such programs. PMID:24905421

Why Open-Ended Survey Questions Are Unlikely to Support Rigorous Qualitative Insights.

PubMed

LaDonna, Kori A; Taylor, Taryn; Lingard, Lorelei

2018-03-01

Health professions education researchers are increasingly relying on a combination of quantitative and qualitative research methods to explore complex questions in the field. This important and necessary development, however, creates new methodological challenges that can affect both the rigor of the research process and the quality of the findings. One example is "qualitatively" analyzing free-text responses to survey or assessment instrument questions. In this Invited Commentary, the authors explain why analysis of such responses rarely meets the bar for rigorous qualitative research. While the authors do not discount the potential for free-text responses to enhance quantitative findings or to inspire new research questions, they caution that these responses rarely produce data rich enough to generate robust, stand-alone insights. The authors consider exemplars from health professions education research and propose strategies for treating free-text responses appropriately.

A Cluster-Randomized Trial of Restorative Practices: An Illustration to Spur High-Quality Research and Evaluation.

PubMed

Acosta, Joie D; Chinman, Matthew; Ebener, Patricia; Phillips, Andrea; Xenakis, Lea; Malone, Patrick S

2016-01-01

Restorative Practices in schools lack rigorous evaluation studies. As an example of rigorous school-based research, this paper describes the first randomized control trial of restorative practices to date, the Study of Restorative Practices. It is a 5-year, cluster-randomized controlled trial (RCT) of the Restorative Practices Intervention (RPI) in 14 middle schools in Maine to assess whether RPI impacts both positive developmental outcomes and problem behaviors and whether the effects persist during the transition from middle to high school. The two-year RPI intervention began in the 2014-2015 school year. The study's rationale and theoretical concerns are discussed along with methodological concerns including teacher professional development. The theoretical rationale and description of the methods from this study may be useful to others conducting rigorous research and evaluation in this area.

Using cancer to make cellular reproduction rigorous and relevant

NASA Astrophysics Data System (ADS)

Duncan, Cynthia F.

The 1983 report Nation at Risk highlighted the fact that test scores of American students were far below that of competing nations and educational standards were being lowered. This trend has continued and studies have also shown that students are not entering college ready for success. This trend can be reversed. Students can better understand and retain biology content expectations if they are taught in a way that is both rigorous and relevant. In the past, students have learned the details of cellular reproduction with little knowledge of why it is important to their everyday lives. This material is learned only for the test. Knowing the details of cellular reproduction is crucial for understanding cancer. Cancer is a topic that will likely affect all of my students at some point in their lives. Students used hands on activities, including simulations, labs, and models to learn about cellular reproduction with cancer as a theme throughout. Students were challenged to learn how to use the rigorous biology content expectations to think about cancer, including stem cell research. Students that will some day be college students, voting citizens, and parents, will become better learners. Students were assessed before and after the completion of the unit to determine if learning occurs. Students did learn the material and became more critical thinkers. Statistical analysis was completed to insure confidence in the results.

The Uphill Battle of Performing Education Scholarship: Barriers Educators and Education Researchers Face.

PubMed

Jordan, Jaime; Coates, Wendy C; Clarke, Samuel; Runde, Daniel; Fowlkes, Emilie; Kurth, Jaqueline; Yarris, Lalena

2018-05-01

Educators and education researchers report that their scholarship is limited by lack of time, funding, mentorship, expertise, and reward. This study aims to evaluate these groups' perceptions regarding barriers to scholarship and potential strategies for success. Core emergency medicine (EM) educators and education researchers completed an online survey consisting of multiple-choice, 10-point Likert scale, and free-response items in 2015. Descriptive statistics were reported. We used qualitative analysis applying a thematic approach to free-response items. A total of 204 educators and 42 education researchers participated. Education researchers were highly productive: 19/42 reported more than 20 peer-reviewed education scholarship publications on their curricula vitae. In contrast, 68/197 educators reported no education publications within five years. Only a minority, 61/197 had formal research training compared to 25/42 education researchers. Barriers to performing research for both groups were lack of time, competing demands, lack of support, lack of funding, and challenges achieving scientifically rigorous methods and publication. The most common motivators identified were dissemination of knowledge, support of evidence-based practices, and promotion. Respondents advised those who seek greater education research involvement to pursue mentorship, formal research training, collaboration, and rigorous methodological standards. The most commonly cited barriers were lack of time and competing demands. Stakeholders were motivated by the desire to disseminate knowledge, support evidence-based practices, and achieve promotion. Suggested strategies for success included formal training, mentorship, and collaboration. This information may inform interventions to support educators in their scholarly pursuits and improve the overall quality of education research in EM.

The Harm Done to Reproducibility by the Culture of Null Hypothesis Significance Testing.

PubMed

Lash, Timothy L

2017-09-15

In the last few years, stakeholders in the scientific community have raised alarms about a perceived lack of reproducibility of scientific results. In reaction, guidelines for journals have been promulgated and grant applicants have been asked to address the rigor and reproducibility of their proposed projects. Neither solution addresses a primary culprit, which is the culture of null hypothesis significance testing that dominates statistical analysis and inference. In an innovative research enterprise, selection of results for further evaluation based on null hypothesis significance testing is doomed to yield a low proportion of reproducible results and a high proportion of effects that are initially overestimated. In addition, the culture of null hypothesis significance testing discourages quantitative adjustments to account for systematic errors and quantitative incorporation of prior information. These strategies would otherwise improve reproducibility and have not been previously proposed in the widely cited literature on this topic. Without discarding the culture of null hypothesis significance testing and implementing these alternative methods for statistical analysis and inference, all other strategies for improving reproducibility will yield marginal gains at best. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Cognitive-behavioral therapy for premenstrual syndrome and premenstrual dysphoric disorder: a systematic review.

PubMed

Lustyk, M Kathleen B; Gerrish, Winslow G; Shaver, Shelley; Keys, Shaunie L

2009-04-01

We systematically reviewed empirical studies that investigated the use of cognitive-behavioral therapy (CBT) for premenstrual syndrome (PMS) or premenstrual dysphoric disorder (PMDD). Our multi-database search identified seven published empirical reports. Three were identified as randomized controlled trials (RCTs). The methods utilized to investigate therapeutic efficacy of CBT in these studies varied widely from case reports to RCTs with pharmacotherapy comparison groups. Initially we provide a brief overview of CBT and justifications for its potential use to treat PMS/PMDD. Next, we provide critical evaluations of the analyses used in each study focusing on the detection of intervention effects assessed by statistically significant time by group interactions. When possible we calculate effect sizes to elucidate the clinical significance of results. Our review revealed a dearth of evidence providing statistically significant CBT intervention effects. Issues such as overall time investment, latency to treatment effects, and complementary and combined therapies are considered. We present a theoretical argument for applying mindfulness- and acceptance-based CBT interventions to PMS/PMDD and suggest future research in this area. In conclusion, to produce the necessary evidence-base support for PMS/PMDD given the limited empirical evidence reported here, researchers are called on to produce methodologically rigorous investigations of psychosocial interventions for PMS/PMDD.

Use of Spatial Epidemiology and Hot Spot Analysis to Target Women Eligible for Prenatal Women, Infants, and Children Services

PubMed Central

Krawczyk, Christopher; Gradziel, Pat; Geraghty, Estella M.

2014-01-01

Objectives. We used a geographic information system and cluster analyses to determine locations in need of enhanced Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) Program services. Methods. We linked documented births in the 2010 California Birth Statistical Master File with the 2010 data from the WIC Integrated Statewide Information System. Analyses focused on the density of pregnant women who were eligible for but not receiving WIC services in California’s 7049 census tracts. We used incremental spatial autocorrelation and hot spot analyses to identify clusters of WIC-eligible nonparticipants. Results. We detected clusters of census tracts with higher-than-expected densities, compared with the state mean density of WIC-eligible nonparticipants, in 21 of 58 (36.2%) California counties (P < .05). In subsequent county-level analyses, we located neighborhood-level clusters of higher-than-expected densities of eligible nonparticipants in Sacramento, San Francisco, Fresno, and Los Angeles Counties (P < .05). Conclusions. Hot spot analyses provided a rigorous and objective approach to determine the locations of statistically significant clusters of WIC-eligible nonparticipants. Results helped inform WIC program and funding decisions, including the opening of new WIC centers, and offered a novel approach for targeting public health services. PMID:24354821

75 FR 13745 - Office of Innovation and Improvement Overview Information; Ready To Teach Program-General...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-23

... on rigorous, scientifically based research methods to assess the effectiveness of a particular... and programs; and (B) Includes research that-- (i) Employs systematic, empirical methods that draw on... hypotheses and justify the general conclusions drawn; (iii) Relies on measurements or observational methods...

75 FR 13515 - Office of Innovation and Improvement (OII); Overview Information; Ready-to-Learn Television...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-22

... on rigorous scientifically based research methods to assess the effectiveness of a particular... activities and programs; and (B) Includes research that-- (i) Employs systematic, empirical methods that draw... or observational methods that provide reliable and valid data across evaluators and observers, across...

Analysis of Perfluorinated Chemicals in Sludge: Method Development and Initial Results

EPA Science Inventory

A fast, rigorous method was developed to maximize the extraction efficacy for ten perfluorocarboxylic acids and perfluorooctanesulfonate from wastewater-treatment sludge and to quantitate using liquid chromatography, tandem-mass spectrometry (LC/MS/MS). First, organic solvents w...

Canonical Drude Weight for Non-integrable Quantum Spin Chains

NASA Astrophysics Data System (ADS)

Mastropietro, Vieri; Porta, Marcello

2018-03-01

The Drude weight is a central quantity for the transport properties of quantum spin chains. The canonical definition of Drude weight is directly related to Kubo formula of conductivity. However, the difficulty in the evaluation of such expression has led to several alternative formulations, accessible to different methods. In particular, the Euclidean, or imaginary-time, Drude weight can be studied via rigorous renormalization group. As a result, in the past years several universality results have been proven for such quantity at zero temperature; remarkably, the proofs work for both integrable and non-integrable quantum spin chains. Here we establish the equivalence of Euclidean and canonical Drude weights at zero temperature. Our proof is based on rigorous renormalization group methods, Ward identities, and complex analytic ideas.

Kinetics versus thermodynamics in materials modeling: The case of the di-vacancy in iron

NASA Astrophysics Data System (ADS)

Djurabekova, F.; Malerba, L.; Pasianot, R. C.; Olsson, P.; Nordlund, K.

2010-07-01

Monte Carlo models are widely used for the study of microstructural and microchemical evolution of materials under irradiation. However, they often link explicitly the relevant activation energies to the energy difference between local equilibrium states. We provide a simple example (di-vacancy migration in iron) in which a rigorous activation energy calculation, by means of both empirical interatomic potentials and density functional theory methods, clearly shows that such a link is not granted, revealing a migration mechanism that a thermodynamics-linked activation energy model cannot predict. Such a mechanism is, however, fully consistent with thermodynamics. This example emphasizes the importance of basing Monte Carlo methods on models where the activation energies are rigorously calculated, rather than deduced from widespread heuristic equations.

Transport of Bacillus thuringiensis var. kurstaki from an outdoor release into buildings: pathways of infiltration and a rapid method to identify contaminated buildings.

PubMed

Van Cuyk, Sheila; Deshpande, Alina; Hollander, Attelia; Franco, David O; Teclemariam, Nerayo P; Layshock, Julie A; Ticknor, Lawrence O; Brown, Michael J; Omberg, Kristin M

2012-06-01

Understanding the fate and transport of biological agents into buildings will be critical to recovery and restoration efforts after a biological attack in an urban area. As part of the Interagency Biological Restoration Demonstration (IBRD), experiments were conducted in Fairfax County, VA, to study whether a biological agent can be expected to infiltrate into buildings following a wide-area release. Bacillus thuringiensis var. kurstaki is a common organic pesticide that has been sprayed in Fairfax County for a number of years to control the gypsy moth. Because the bacterium shares many physical and biological properties with Bacillus anthracis, the results from these studies can be extrapolated to a bioterrorist release. In 2009, samples were collected from inside buildings located immediately adjacent to a spray block. A combined probabilistic and targeted sampling strategy and modeling were conducted to provide insight into likely methods of infiltration. Both the simulations and the experimental results indicate sampling entryways and heating, ventilation, and air conditioning (HVAC) filters are reasonable methods for "ruling in" a building as contaminated. Following a biological attack, this method is likely to provide significant savings in time and labor compared to more rigorous, statistically based characterization. However, this method should never be used to "rule out," or clear, a building.

Image synthesis for SAR system, calibration and processor design

NASA Technical Reports Server (NTRS)

Holtzman, J. C.; Abbott, J. L.; Kaupp, V. H.; Frost, V. S.

1978-01-01

The Point Scattering Method of simulating radar imagery rigorously models all aspects of the imaging radar phenomena. Its computational algorithms operate on a symbolic representation of the terrain test site to calculate such parameters as range, angle of incidence, resolution cell size, etc. Empirical backscatter data and elevation data are utilized to model the terrain. Additionally, the important geometrical/propagation effects such as shadow, foreshortening, layover, and local angle of incidence are rigorously treated. Applications of radar image simulation to a proposed calibrated SAR system are highlighted: soil moisture detection and vegetation discrimination.

Escape rates over potential barriers: variational principles and the Hamilton-Jacobi equation

NASA Astrophysics Data System (ADS)

Cortés, Emilio; Espinosa, Francisco

We describe a rigorous formalism to study some extrema statistics problems, like maximum probability events or escape rate processes, by taking into account that the Hamilton-Jacobi equation completes, in a natural way, the required set of boundary conditions of the Euler-Lagrange equation, for this kind of variational problem. We apply this approach to a one-dimensional stochastic process, driven by colored noise, for a double-parabola potential, where we have one stable and one unstable steady states.

Rapid Creation and Quantitative Monitoring of High Coverage shRNA Libraries

PubMed Central

Bassik, Michael C.; Lebbink, Robert Jan; Churchman, L. Stirling; Ingolia, Nicholas T.; Patena, Weronika; LeProust, Emily M.; Schuldiner, Maya; Weissman, Jonathan S.; McManus, Michael T.

2009-01-01

Short hairpin RNA (shRNA) libraries are limited by the low efficacy of many shRNAs, giving false negatives, and off-target effects, giving false positives. Here we present a strategy for rapidly creating expanded shRNA pools (∼30 shRNAs/gene) that are analyzed by deep-sequencing (EXPAND). This approach enables identification of multiple effective target-specific shRNAs from a complex pool, allowing a rigorous statistical evaluation of whether a gene is a true hit. PMID:19448642

Ray-optical theory of broadband partially coherent emission

NASA Astrophysics Data System (ADS)

Epstein, Ariel; Tessler, Nir; Einziger, Pinchas D.

2013-04-01

We present a rigorous formulation of the effects of spectral broadening on emission of partially coherent source ensembles embedded in multilayered formations with arbitrarily shaped interfaces, provided geometrical optics is valid. The resulting ray-optical theory, applicable to a variety of optical systems from terahertz lenses to photovoltaic cells, quantifies the fundamental interplay between bandwidth and layer dimensions, and sheds light on common practices in optical analysis of statistical fields, e.g., disregarding multiple reflections or neglecting interference cross terms.

A case-control study of malignant melanoma among Lawrence Livermore National Laboratory employees: A critical evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kupper, L.L.; Setzer, R.W.; Schwartzbaum, J.

1987-07-01

This document reports on a reevaluation of data obtained in a previous report on occupational factors associated with the development of malignant melanomas at Lawrence Livermore National Laboratory. The current report reduces the number of these factors from five to three based on a rigorous statistical analysis of the original data. Recommendations include restructuring the original questionnaire and trying to contact more individuals that worked with volatile photographic chemicals. 17 refs., 7 figs., 22 tabs. (TEM)

Contemporary use trends and survival outcomes in patients undergoing radical cystectomy or bladder-preservation therapy for muscle-invasive bladder cancer.

PubMed

Cahn, David B; Handorf, Elizabeth A; Ghiraldi, Eric M; Ristau, Benjamin T; Geynisman, Daniel M; Churilla, Thomas M; Horwitz, Eric M; Sobczak, Mark L; Chen, David Y T; Viterbo, Rosalia; Greenberg, Richard E; Kutikov, Alexander; Uzzo, Robert G; Smaldone, Marc C

2017-11-15

The current study was performed to examine temporal trends and compare overall survival (OS) in patients undergoing radical cystectomy (RC) or bladder-preservation therapy (BPT) for muscle-invasive urothelial carcinoma of the bladder. The authors reviewed the National Cancer Data Base to identify patients with AJCC stage II to III urothelial carcinoma of the bladder from 2004 through 2013. Patients receiving BPT were stratified as having received any external-beam radiotherapy (any XRT), definitive XRT (50-80 grays), and definitive XRT with chemotherapy (CRT). Treatment trends and OS outcomes for the BPT and RC cohorts were evaluated using Cochran-Armitage tests, unadjusted Kaplan-Meier curves, adjusted Cox multivariate regression, and propensity score matching, using increasingly stringent selection criteria. A total of 32,300 patients met the inclusion criteria and were treated with RC (22,680 patients) or BPT (9620 patients). Of the patients treated with BPT, 26.4% (2540 patients) and 15.5% (1489 patients), respectively, were treated with definitive XRT and CRT. Improved OS was observed for RC in all groups. After adjustments with more rigorous statistical models controlling for confounders and with more restrictive BPT cohorts, the magnitude of the OS benefit became attenuated on multivariate (any XRT: hazard ratio [HR], 2.115 [95% confidence interval [95% CI], 2.045-2.188]; definitive XRT: HR, 1.870 [95% CI, 1.773-1.972]; and CRT: HR, 1.578 [95% CI, 1.474-1.691]) and propensity score (any XRT: HR, 2.008 [95% CI, 1.871-2.154]; definitive XRT: HR, 1.606 [95% CI, 1.453-1.776]; and CRT: HR, 1.406 [95% CI, 1.235-1.601]) analyses. In the National Cancer Data Base, receipt of BPT was associated with decreased OS compared with RC in patients with stage II to III urothelial carcinoma. Increasingly stringent definitions of BPT and more rigorous statistical methods adjusting for selection biases attenuated observed survival differences. Cancer 2017;123:4337-45. © 2017 American Cancer Society. © 2017 American Cancer Society.

Development of rigor mortis is not affected by muscle volume.

PubMed

Kobayashi, M; Ikegaya, H; Takase, I; Hatanaka, K; Sakurada, K; Iwase, H

2001-04-01

There is a hypothesis suggesting that rigor mortis progresses more rapidly in small muscles than in large muscles. We measured rigor mortis as tension determined isometrically in rat musculus erector spinae that had been cut into muscle bundles of various volumes. The muscle volume did not influence either the progress or the resolution of rigor mortis, which contradicts the hypothesis. Differences in pre-rigor load on the muscles influenced the onset and resolution of rigor mortis in a few pairs of samples, but did not influence the time taken for rigor mortis to reach its full extent after death. Moreover, the progress of rigor mortis in this muscle was biphasic; this may reflect the early rigor of red muscle fibres and the late rigor of white muscle fibres.

Design Oriented Structural Modeling for Airplane Conceptual Design Optimization

NASA Technical Reports Server (NTRS)

Livne, Eli

1999-01-01

The main goal for research conducted with the support of this grant was to develop design oriented structural optimization methods for the conceptual design of airplanes. Traditionally in conceptual design airframe weight is estimated based on statistical equations developed over years of fitting airplane weight data in data bases of similar existing air- planes. Utilization of such regression equations for the design of new airplanes can be justified only if the new air-planes use structural technology similar to the technology on the airplanes in those weight data bases. If any new structural technology is to be pursued or any new unconventional configurations designed the statistical weight equations cannot be used. In such cases any structural weight estimation must be based on rigorous "physics based" structural analysis and optimization of the airframes under consideration. Work under this grant progressed to explore airframe design-oriented structural optimization techniques along two lines of research: methods based on "fast" design oriented finite element technology and methods based on equivalent plate / equivalent shell models of airframes, in which the vehicle is modelled as an assembly of plate and shell components, each simulating a lifting surface or nacelle / fuselage pieces. Since response to changes in geometry are essential in conceptual design of airplanes, as well as the capability to optimize the shape itself, research supported by this grant sought to develop efficient techniques for parametrization of airplane shape and sensitivity analysis with respect to shape design variables. Towards the end of the grant period a prototype automated structural analysis code designed to work with the NASA Aircraft Synthesis conceptual design code ACS= was delivered to NASA Ames.

A better way to evaluate remote monitoring programs in chronic disease care: receiver operating characteristic analysis.

PubMed

Brown Connolly, Nancy E

2014-12-01

This foundational study applies the process of receiver operating characteristic (ROC) analysis to evaluate utility and predictive value of a disease management (DM) model that uses RM devices for chronic obstructive pulmonary disease (COPD). The literature identifies a need for a more rigorous method to validate and quantify evidence-based value for remote monitoring (RM) systems being used to monitor persons with a chronic disease. ROC analysis is an engineering approach widely applied in medical testing, but that has not been evaluated for its utility in RM. Classifiers (saturated peripheral oxygen [SPO2], blood pressure [BP], and pulse), optimum threshold, and predictive accuracy are evaluated based on patient outcomes. Parametric and nonparametric methods were used. Event-based patient outcomes included inpatient hospitalization, accident and emergency, and home health visits. Statistical analysis tools included Microsoft (Redmond, WA) Excel(®) and MedCalc(®) (MedCalc Software, Ostend, Belgium) version 12 © 1993-2013 to generate ROC curves and statistics. Persons with COPD were monitored a minimum of 183 days, with at least one inpatient hospitalization within 12 months prior to monitoring. Retrospective, de-identified patient data from a United Kingdom National Health System COPD program were used. Datasets included biometric readings, alerts, and resource utilization. SPO2 was identified as a predictive classifier, with an optimal average threshold setting of 85-86%. BP and pulse were failed classifiers, and areas of design were identified that may improve utility and predictive capacity. Cost avoidance methodology was developed. RESULTS can be applied to health services planning decisions. Methods can be applied to system design and evaluation based on patient outcomes. This study validated the use of ROC in RM program evaluation.

Effects of rigor status during high-pressure processing on the physical qualities of farm-raised abalone (Haliotis rufescens).

PubMed

Hughes, Brianna H; Greenberg, Neil J; Yang, Tom C; Skonberg, Denise I

2015-01-01

High-pressure processing (HPP) is used to increase meat safety and shelf-life, with conflicting quality effects depending on rigor status during HPP. In the seafood industry, HPP is used to shuck and pasteurize oysters, but its use on abalones has only been minimally evaluated and the effect of rigor status during HPP on abalone quality has not been reported. Farm-raised abalones (Haliotis rufescens) were divided into 12 HPP treatments and 1 unprocessed control treatment. Treatments were processed pre-rigor or post-rigor at 2 pressures (100 and 300 MPa) and 3 processing times (1, 3, and 5 min). The control was analyzed post-rigor. Uniform plugs were cut from adductor and foot meat for texture profile analysis, shear force, and color analysis. Subsamples were used for scanning electron microscopy of muscle ultrastructure. Texture profile analysis revealed that post-rigor processed abalone was significantly (P < 0.05) less firm and chewy than pre-rigor processed irrespective of muscle type, processing time, or pressure. L values increased with pressure to 68.9 at 300 MPa for pre-rigor processed foot, 73.8 for post-rigor processed foot, 90.9 for pre-rigor processed adductor, and 89.0 for post-rigor processed adductor. Scanning electron microscopy images showed fraying of collagen fibers in processed adductor, but did not show pressure-induced compaction of the foot myofibrils. Post-rigor processed abalone meat was more tender than pre-rigor processed meat, and post-rigor processed foot meat was lighter in color than pre-rigor processed foot meat, suggesting that waiting for rigor to resolve prior to processing abalones may improve consumer perceptions of quality and market value. © 2014 Institute of Food Technologists®

Rigorous analysis of an electric-field-driven liquid crystal lens for 3D displays

NASA Astrophysics Data System (ADS)

Kim, Bong-Sik; Lee, Seung-Chul; Park, Woo-Sang

2014-08-01

We numerically analyzed the optical performance of an electric field driven liquid crystal (ELC) lens adopted for 3-dimensional liquid crystal displays (3D-LCDs) through rigorous ray tracing. For the calculation, we first obtain the director distribution profile of the liquid crystals by using the Erickson-Leslie motional equation; then, we calculate the transmission of light through the ELC lens by using the extended Jones matrix method. The simulation was carried out for a 9view 3D-LCD with a diagonal of 17.1 inches, where the ELC lens was slanted to achieve natural stereoscopic images. The results show that each view exists separately according to the viewing position at an optimum viewing distance of 80 cm. In addition, our simulation results provide a quantitative explanation for the ghost or blurred images between views observed from a 3D-LCD with an ELC lens. The numerical simulations are also shown to be in good agreement with the experimental results. The present simulation method is expected to provide optimum design conditions for obtaining natural 3D images by rigorously analyzing the optical functionalities of an ELC lens.

Rigorous Combination of GNSS and VLBI: How it Improves Earth Orientation and Reference Frames

NASA Astrophysics Data System (ADS)

Lambert, S. B.; Richard, J. Y.; Bizouard, C.; Becker, O.

2017-12-01

Current reference series (C04) of the International Earth Rotation and Reference Systems Service (IERS) are produced by a weighted combination of Earth orientation parameters (EOP) time series built up by combination centers of each technique (VLBI, GNSS, Laser ranging, DORIS). In the future, we plan to derive EOP from a rigorous combination of the normal equation systems of the four techniques.We present here the results of a rigorous combination of VLBI and GNSS pre-reduced, constraint-free, normal equations with the DYNAMO geodetic analysis software package developed and maintained by the French GRGS (Groupe de Recherche en GeÌodeÌsie Spatiale). The used normal equations are those produced separately by the IVS and IGS combination centers to which we apply our own minimal constraints.We address the usefulness of such a method with respect to the classical, a posteriori, combination method, and we show whether EOP determinations are improved.Especially, we implement external validations of the EOP series based on comparison with geophysical excitation and examination of the covariance matrices. Finally, we address the potential of the technique for the next generation celestial reference frames, which are currently determined by VLBI only.

A Cluster-Randomized Trial of Restorative Practices: An Illustration to Spur High-Quality Research and Evaluation

PubMed Central

Acosta, Joie D.; Chinman, Matthew; Ebener, Patricia; Phillips, Andrea; Xenakis, Lea; Malone, Patrick S.

2017-01-01

Restorative Practices in schools lack rigorous evaluation studies. As an example of rigorous school-based research, this paper describes the first randomized control trial of restorative practices to date, the Study of Restorative Practices. It is a 5-year, cluster-randomized controlled trial (RCT) of the Restorative Practices Intervention (RPI) in 14 middle schools in Maine to assess whether RPI impacts both positive developmental outcomes and problem behaviors and whether the effects persist during the transition from middle to high school. The two-year RPI intervention began in the 2014–2015 school year. The study’s rationale and theoretical concerns are discussed along with methodological concerns including teacher professional development. The theoretical rationale and description of the methods from this study may be useful to others conducting rigorous research and evaluation in this area. PMID:28936104

Revisiting the scientific method to improve rigor and reproducibility of immunohistochemistry in reproductive science.

PubMed

Manuel, Sharrón L; Johnson, Brian W; Frevert, Charles W; Duncan, Francesca E

2018-04-21

Immunohistochemistry (IHC) is a robust scientific tool whereby cellular components are visualized within a tissue, and this method has been and continues to be a mainstay for many reproductive biologists. IHC is highly informative if performed and interpreted correctly, but studies have shown that the general use and reporting of appropriate controls in IHC experiments is low. This omission of the scientific method can result in data that lacks rigor and reproducibility. In this editorial, we highlight key concepts in IHC controls and describe an opportunity for our field to partner with the Histochemical Society to adopt their IHC guidelines broadly as researchers, authors, ad hoc reviewers, editorial board members, and editors-in-chief. Such cross-professional society interactions will ensure that we produce the highest quality data as new technologies emerge that still rely upon the foundations of classic histological and immunohistochemical principles.

Rigorous mathematical modelling for a Fast Corrector Power Supply in TPS

NASA Astrophysics Data System (ADS)

Liu, K.-B.; Liu, C.-Y.; Chien, Y.-C.; Wang, B.-S.; Wong, Y. S.

2017-04-01

To enhance the stability of beam orbit, a Fast Orbit Feedback System (FOFB) eliminating undesired disturbances was installed and tested in the 3rd generation synchrotron light source of Taiwan Photon Source (TPS) of National Synchrotron Radiation Research Center (NSRRC). The effectiveness of the FOFB greatly depends on the output performance of Fast Corrector Power Supply (FCPS); therefore, the design and implementation of an accurate FCPS is essential. A rigorous mathematical modelling is very useful to shorten design time and improve design performance of a FCPS. A rigorous mathematical modelling derived by the state-space averaging method for a FCPS in the FOFB of TPS composed of a full-bridge topology is therefore proposed in this paper. The MATLAB/SIMULINK software is used to construct the proposed mathematical modelling and to conduct the simulations of the FCPS. Simulations for the effects of the different resolutions of ADC on the output accuracy of the FCPS are investigated. A FCPS prototype is realized to demonstrate the effectiveness of the proposed rigorous mathematical modelling for the FCPS. Simulation and experimental results show that the proposed mathematical modelling is helpful for selecting the appropriate components to meet the accuracy requirements of a FCPS.

Determining if disease management saves money: an introduction to meta-analysis.

PubMed

Linden, Ariel; Adams, John L

2007-06-01

Disease management (DM) programmes have long been promoted as a major medical cost-saving mechanism, even though the scant research that exists on the topic has provided conflicting results. In a 2004 literature review, the Congressional Budget Office stated that 'there is insufficient evidence to conclude that disease management programs can generally reduce the overall cost of health care services'. To address this question more accurately, a meta-analysis was warranted. Meta-analysis is the quantitative technique used to pool the results of many studies on the same topic and summarize them statistically. This method is also quite suitable for individual DM firms to assess whether their programmes are effective at the aggregate level. This paper describes the elements of a rigorous meta-analytic process and discusses potential biases. A hypothetical DM organization is then evaluated with a specific emphasis on medical cost-savings, simulating a case in which different populations are served, evaluation methodologies are employed, and diseases are managed.

Geoscience Education Research Methods: Thinking About Sample Size

NASA Astrophysics Data System (ADS)

Slater, S. J.; Slater, T. F.; CenterAstronomy; Physics Education Research

2011-12-01

Geoscience education research is at a critical point in which conditions are sufficient to propel our field forward toward meaningful improvements in geosciences education practices. Our field has now reached a point where the outcomes of our research is deemed important to endusers and funding agencies, and where we now have a large number of scientists who are either formally trained in geosciences education research, or who have dedicated themselves to excellence in this domain. At this point we now must collectively work through our epistemology, our rules of what methodologies will be considered sufficiently rigorous, and what data and analysis techniques will be acceptable for constructing evidence. In particular, we have to work out our answer to that most difficult of research questions: "How big should my 'N' be??" This paper presents a very brief answer to that question, addressing both quantitative and qualitative methodologies. Research question/methodology alignment, effect size and statistical power will be discussed, in addition to a defense of the notion that bigger is not always better.

Searching for Unresolved Binary Brown Dwarfs

NASA Astrophysics Data System (ADS)

Albretsen, Jacob; Stephens, Denise

2007-10-01

There are currently L and T brown dwarfs (BDs) with errors in their classification of +/- 1 to 2 spectra types. Metallicity and gravitational differences have accounted for some of these discrepancies, and recent studies have shown unresolved binary BDs may offer some explanation as well. However limitations in technology and resources often make it difficult to clearly resolve an object that may be binary in nature. Stephens and Noll (2006) identified statistically strong binary source candidates from Hubble Space Telescope (HST) images of Trans-Neptunian Objects (TNOs) that were apparently unresolved using model point-spread functions for single and binary sources. The HST archive contains numerous observations of BDs using the Near Infrared Camera and Multi-Object Spectrometer (NICMOS) that have never been rigorously analyzed for binary properties. Using methods developed by Stephens and Noll (2006), BD observations from the HST data archive are being analyzed for possible unresolved binaries. Preliminary results will be presented. This technique will identify potential candidates for future observations to determine orbital information.

The MR-Base platform supports systematic causal inference across the human phenome

PubMed Central

Wade, Kaitlin H; Haberland, Valeriia; Baird, Denis; Laurin, Charles; Burgess, Stephen; Bowden, Jack; Langdon, Ryan; Tan, Vanessa Y; Yarmolinsky, James; Shihab, Hashem A; Timpson, Nicholas J; Evans, David M; Relton, Caroline; Martin, Richard M; Davey Smith, George

2018-01-01

Results from genome-wide association studies (GWAS) can be used to infer causal relationships between phenotypes, using a strategy known as 2-sample Mendelian randomization (2SMR) and bypassing the need for individual-level data. However, 2SMR methods are evolving rapidly and GWAS results are often insufficiently curated, undermining efficient implementation of the approach. We therefore developed MR-Base (http://www.mrbase.org): a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR. The software includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions. The database currently comprises 11 billion single nucleotide polymorphism-trait associations from 1673 GWAS and is updated on a regular basis. Integrating data with software ensures more rigorous application of hypothesis-driven analyses and allows millions of potential causal relationships to be efficiently evaluated in phenome-wide association studies. PMID:29846171

A High Performance Computing Study of a Scalable FISST-Based Approach to Multi-Target, Multi-Sensor Tracking

NASA Astrophysics Data System (ADS)

Hussein, I.; Wilkins, M.; Roscoe, C.; Faber, W.; Chakravorty, S.; Schumacher, P.

2016-09-01

Finite Set Statistics (FISST) is a rigorous Bayesian multi-hypothesis management tool for the joint detection, classification and tracking of multi-sensor, multi-object systems. Implicit within the approach are solutions to the data association and target label-tracking problems. The full FISST filtering equations, however, are intractable. While FISST-based methods such as the PHD and CPHD filters are tractable, they require heavy moment approximations to the full FISST equations that result in a significant loss of information contained in the collected data. In this paper, we review Smart Sampling Markov Chain Monte Carlo (SSMCMC) that enables FISST to be tractable while avoiding moment approximations. We study the effect of tuning key SSMCMC parameters on tracking quality and computation time. The study is performed on a representative space object catalog with varying numbers of RSOs. The solution is implemented in the Scala computing language at the Maui High Performance Computing Center (MHPCC) facility.

Charting the Replica Symmetric Phase

NASA Astrophysics Data System (ADS)

Coja-Oghlan, Amin; Efthymiou, Charilaos; Jaafari, Nor; Kang, Mihyun; Kapetanopoulos, Tobias

2018-02-01

Diluted mean-field models are spin systems whose geometry of interactions is induced by a sparse random graph or hypergraph. Such models play an eminent role in the statistical mechanics of disordered systems as well as in combinatorics and computer science. In a path-breaking paper based on the non-rigorous `cavity method', physicists predicted not only the existence of a replica symmetry breaking phase transition in such models but also sketched a detailed picture of the evolution of the Gibbs measure within the replica symmetric phase and its impact on important problems in combinatorics, computer science and physics (Krzakala et al. in Proc Natl Acad Sci 104:10318-10323, 2007). In this paper we rigorise this picture completely for a broad class of models, encompassing the Potts antiferromagnet on the random graph, the k-XORSAT model and the diluted k-spin model for even k. We also prove a conjecture about the detection problem in the stochastic block model that has received considerable attention (Decelle et al. in Phys Rev E 84:066106, 2011).

An unexpected way forward: towards a more accurate and rigorous protein-protein binding affinity scoring function by eliminating terms from an already simple scoring function.

PubMed

Swanson, Jon; Audie, Joseph

2018-01-01

A fundamental and unsolved problem in biophysical chemistry is the development of a computationally simple, physically intuitive, and generally applicable method for accurately predicting and physically explaining protein-protein binding affinities from protein-protein interaction (PPI) complex coordinates. Here, we propose that the simplification of a previously described six-term PPI scoring function to a four term function results in a simple expression of all physically and statistically meaningful terms that can be used to accurately predict and explain binding affinities for a well-defined subset of PPIs that are characterized by (1) crystallographic coordinates, (2) rigid-body association, (3) normal interface size, and hydrophobicity and hydrophilicity, and (4) high quality experimental binding affinity measurements. We further propose that the four-term scoring function could be regarded as a core expression for future development into a more general PPI scoring function. Our work has clear implications for PPI modeling and structure-based drug design.

Probabilistic risk analysis of building contamination.

PubMed

Bolster, D T; Tartakovsky, D M

2008-10-01

We present a general framework for probabilistic risk assessment (PRA) of building contamination. PRA provides a powerful tool for the rigorous quantification of risk in contamination of building spaces. A typical PRA starts by identifying relevant components of a system (e.g. ventilation system components, potential sources of contaminants, remediation methods) and proceeds by using available information and statistical inference to estimate the probabilities of their failure. These probabilities are then combined by means of fault-tree analyses to yield probabilistic estimates of the risk of system failure (e.g. building contamination). A sensitivity study of PRAs can identify features and potential problems that need to be addressed with the most urgency. Often PRAs are amenable to approximations, which can significantly simplify the approach. All these features of PRA are presented in this paper via a simple illustrative example, which can be built upon in further studies. The tool presented here can be used to design and maintain adequate ventilation systems to minimize exposure of occupants to contaminants.

QTest: Quantitative Testing of Theories of Binary Choice

PubMed Central

Regenwetter, Michel; Davis-Stober, Clintin P.; Lim, Shiau Hong; Guo, Ying; Popova, Anna; Zwilling, Chris; Cha, Yun-Shil; Messner, William

2014-01-01

The goal of this paper is to make modeling and quantitative testing accessible to behavioral decision researchers interested in substantive questions. We provide a novel, rigorous, yet very general, quantitative diagnostic framework for testing theories of binary choice. This permits the nontechnical scholar to proceed far beyond traditionally rather superficial methods of analysis, and it permits the quantitatively savvy scholar to triage theoretical proposals before investing effort into complex and specialized quantitative analyses. Our theoretical framework links static algebraic decision theory with observed variability in behavioral binary choice data. The paper is supplemented with a custom-designed public-domain statistical analysis package, the QTest software. We illustrate our approach with a quantitative analysis using published laboratory data, including tests of novel versions of “Random Cumulative Prospect Theory.” A major asset of the approach is the potential to distinguish decision makers who have a fixed preference and commit errors in observed choices from decision makers who waver in their preferences. PMID:24999495

Separating intrinsic from extrinsic fluctuations in dynamic biological systems

PubMed Central

Paulsson, Johan

2011-01-01

From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems. PMID:21730172

Separating intrinsic from extrinsic fluctuations in dynamic biological systems.

PubMed

Hilfinger, Andreas; Paulsson, Johan

2011-07-19

From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems.

Ethics Training of Law Enforcement Officers: The Optimum Means of Conveyance

ERIC Educational Resources Information Center

Redden, Donald L.

2010-01-01

The current research was designed to furnish an unpretentious but rigorous examination of the subject of ethics education, seeking the most commanding and useful method to deliver the curriculum. A review of the literature revealed several methods currently used to teach ethics. The respondents examined the various methods, noted the positive and…

Comprehensive methods for earlier detection and monitoring of forest decline

Treesearch

Jennifer Pontius; Richard Hallett

2014-01-01

Forested ecosystems are threatened by invasive pests, pathogens, and unusual climatic events brought about by climate change. Earlier detection of incipient forest health problems and a quantitatively rigorous assessment method is increasingly important. Here, we describe a method that is adaptable across tree species and stress agents and practical for use in the...

A Review of Mixed Methods Research on Bullying and Peer Victimization in School

ERIC Educational Resources Information Center

Hong, Jun Sung; Espelage, Dorothy L.

2012-01-01

Recognizing the negative outcomes associated with experiences in bullying at school, educational researchers, school officials, and policy-makers have called for more rigorous research on bullying in school. Research on bullying behavior in school has primarily been examined using quantitative methods. Mixed methods research in the field of…

Practical Bias Correction in Aerial Surveys of Large Mammals: Validation of Hybrid Double-Observer with Sightability Method against Known Abundance of Feral Horse (Equus caballus) Populations

PubMed Central

2016-01-01

Reliably estimating wildlife abundance is fundamental to effective management. Aerial surveys are one of the only spatially robust tools for estimating large mammal populations, but statistical sampling methods are required to address detection biases that affect accuracy and precision of the estimates. Although various methods for correcting aerial survey bias are employed on large mammal species around the world, these have rarely been rigorously validated. Several populations of feral horses (Equus caballus) in the western United States have been intensively studied, resulting in identification of all unique individuals. This provided a rare opportunity to test aerial survey bias correction on populations of known abundance. We hypothesized that a hybrid method combining simultaneous double-observer and sightability bias correction techniques would accurately estimate abundance. We validated this integrated technique on populations of known size and also on a pair of surveys before and after a known number was removed. Our analysis identified several covariates across the surveys that explained and corrected biases in the estimates. All six tests on known populations produced estimates with deviations from the known value ranging from -8.5% to +13.7% and <0.7 standard errors. Precision varied widely, from 6.1% CV to 25.0% CV. In contrast, the pair of surveys conducted around a known management removal produced an estimated change in population between the surveys that was significantly larger than the known reduction. Although the deviation between was only 9.1%, the precision estimate (CV = 1.6%) may have been artificially low. It was apparent that use of a helicopter in those surveys perturbed the horses, introducing detection error and heterogeneity in a manner that could not be corrected by our statistical models. Our results validate the hybrid method, highlight its potentially broad applicability, identify some limitations, and provide insight and guidance for improving survey designs. PMID:27139732

Practical Bias Correction in Aerial Surveys of Large Mammals: Validation of Hybrid Double-Observer with Sightability Method against Known Abundance of Feral Horse (Equus caballus) Populations.

PubMed

Lubow, Bruce C; Ransom, Jason I

2016-01-01

Reliably estimating wildlife abundance is fundamental to effective management. Aerial surveys are one of the only spatially robust tools for estimating large mammal populations, but statistical sampling methods are required to address detection biases that affect accuracy and precision of the estimates. Although various methods for correcting aerial survey bias are employed on large mammal species around the world, these have rarely been rigorously validated. Several populations of feral horses (Equus caballus) in the western United States have been intensively studied, resulting in identification of all unique individuals. This provided a rare opportunity to test aerial survey bias correction on populations of known abundance. We hypothesized that a hybrid method combining simultaneous double-observer and sightability bias correction techniques would accurately estimate abundance. We validated this integrated technique on populations of known size and also on a pair of surveys before and after a known number was removed. Our analysis identified several covariates across the surveys that explained and corrected biases in the estimates. All six tests on known populations produced estimates with deviations from the known value ranging from -8.5% to +13.7% and <0.7 standard errors. Precision varied widely, from 6.1% CV to 25.0% CV. In contrast, the pair of surveys conducted around a known management removal produced an estimated change in population between the surveys that was significantly larger than the known reduction. Although the deviation between was only 9.1%, the precision estimate (CV = 1.6%) may have been artificially low. It was apparent that use of a helicopter in those surveys perturbed the horses, introducing detection error and heterogeneity in a manner that could not be corrected by our statistical models. Our results validate the hybrid method, highlight its potentially broad applicability, identify some limitations, and provide insight and guidance for improving survey designs.

Rigor, vigor, and the study of health disparities

PubMed Central

Adler, Nancy; Bush, Nicole R.; Pantell, Matthew S.

2012-01-01

Health disparities research spans multiple fields and methods and documents strong links between social disadvantage and poor health. Associations between socioeconomic status (SES) and health are often taken as evidence for the causal impact of SES on health, but alternative explanations, including the impact of health on SES, are plausible. Studies showing the influence of parents’ SES on their children’s health provide evidence for a causal pathway from SES to health, but have limitations. Health disparities researchers face tradeoffs between “rigor” and “vigor” in designing studies that demonstrate how social disadvantage becomes biologically embedded and results in poorer health. Rigorous designs aim to maximize precision in the measurement of SES and health outcomes through methods that provide the greatest control over temporal ordering and causal direction. To achieve precision, many studies use a single SES predictor and single disease. However, doing so oversimplifies the multifaceted, entwined nature of social disadvantage and may overestimate the impact of that one variable and underestimate the true impact of social disadvantage on health. In addition, SES effects on overall health and functioning are likely to be greater than effects on any one disease. Vigorous designs aim to capture this complexity and maximize ecological validity through more complete assessment of social disadvantage and health status, but may provide less-compelling evidence of causality. Newer approaches to both measurement and analysis may enable enhanced vigor as well as rigor. Incorporating both rigor and vigor into studies will provide a fuller understanding of the causes of health disparities. PMID:23045672

A study of some non-equilibrium driven models and their contribution to the understanding of molecular motors

NASA Astrophysics Data System (ADS)

Mazilu, Irina; Gonzalez, Joshua

2008-03-01

From the point of view of a physicist, a bio-molecular motor represents an interesting non-equilibrium system and it is directly amenable to an analysis using standard methods of non-equilibrium statistical physics. We conduct a rigorous Monte Carlo study of three different driven lattice gas models that retain the basic behavior of three types of cytoskeletal molecular motors. Our models incorporate novel features such as realistic dynamics rules and complex motor-motor interactions. We are interested to have a deeper understanding of how various parameters influence the macroscopic behavior of these systems, what is the density profile and if the system undergoes a phase transition. On the analytical front, we computed the steady-state probability distributions exactly for the one of the models using the matrix method that was established in 1993 by B. Derrida et al. We also explored the possibilities offered by the ``Bethe ansatz'' method by mapping some well studied spin models into asymmetric simple exclusion models (already analyzed using computer simulations), and to use the results obtained for the spin models in finding an exact solution for our problem. We have exhaustive computational studies of the kinesin and dynein molecular motor models that prove to be very useful in checking our analytical work.

A systematic review on the prevalence and utilization of health care services for reproductive tract infections/sexually transmitted infections: Evidence from India.

PubMed

Nagarkar, Aarti; Mhaskar, Pallavi

2015-01-01

Several studies have reported prevalence rate of reproductive tract infections (RTIs) but very few studies have described health seeking behavior of patients. This paper critically looks at and summarizes the available evidence, systematically. A structured search strategy was used to identify relevant articles, published during years 2000-2012. Forty-one full-text papers discussing prevalence and treatment utilization pattern were included as per PRISMA guidelines. Papers examining prevalence of sexually transmitted diseases used biochemical methods and standard protocol for diagnosis while studies on RTIs used different methods for diagnosis. The prevalence of RTIs has not changed much over the years and found to vary from 11% to 72% in the community-based studies. Stigma, embarrassment, illiteracy, lack of privacy, cost of care found to limit the use of services, but discussion on pathways of nonutilization remains unclear. Lack of methodological rigor, statistical power, specificity in case definitions as well as too little discussion on the limitation of selected method of diagnosis and reliance on observational evidence hampered the quality of studies on RTIs. Raising awareness among women regarding symptoms of RTIs and sexually transmitted infections and also about appropriate treatment has remained largely a neglected area and, therefore, we observed absence of health system studies in this area.

Breast Cancer Status in Iran: Statistical Analysis of 3010 Cases between 1998 and 2014

PubMed Central

Akbari, Mohammad Esmaeil; Sayad, Saed; Khayamzadeh, Maryam; Shojaee, Leila; Shormeji, Zeynab; Amiri, Mojtaba

2017-01-01

Background Breast cancer is the 5th leading cause of cancer death in Iranian women. This study analyzed 3010 women with breast cancer that had been referred to a cancer research center in Tehran between 1998 and 2014. Methods In this retrospective study, we analyzed 3010 breast cancer cases with 32 clinical and paraclinical attributes. We checked the data quality rigorously and removed any invalid values or records. The method was data mining (problem definition, data preparation, data exploration, modeling, evaluation, and deployment). However, only the descriptive analyses' results of the variables are presented in this article. To our knowledge, this is the most comprehensive study on breast cancer status in Iran. Results A typical Iranian breast cancer patient has been a 40–50-year-old married woman with two children, who has a high school diploma and no history of abortion, smoking, or diabetes. Most patients were estrogen and progesterone receptor positive, human epidermal growth factor (HER) negative, and P53 negative. Most cases were detected in stage 2 with intermediate grade. Conclusion This study revealed original findings which can be used in national policymaking to find the best early detection method and improve the care quality and breast cancer prevention in Iran. PMID:29201466

DOE Office of Scientific and Technical Information (OSTI.GOV)

Burr, Tom; Croft, Stephen; Jarman, Kenneth D.

The various methods of nondestructive assay (NDA) of special nuclear material (SNM) have applications in nuclear nonproliferation, including detection and identification of illicit SNM at border crossings, and quantifying SNM at nuclear facilities for safeguards. No assay method is complete without “error bars,” which provide one way of expressing confidence in the assay result. Consequently, NDA specialists typically quantify total uncertainty in terms of “random” and “systematic” components, and then specify error bars for the total mass estimate in multiple items. Uncertainty quantification (UQ) for NDA has always been important, but it is recognized that greater rigor is needed andmore » achievable using modern statistical methods. To this end, we describe the extent to which the guideline for expressing uncertainty in measurements (GUM) can be used for NDA. Also, we propose improvements over GUM for NDA by illustrating UQ challenges that it does not address, including calibration with errors in predictors, model error, and item-specific biases. A case study is presented using low-resolution NaI spectra and applying the enrichment meter principle to estimate the U-235 mass in an item. The case study illustrates how to update the current American Society for Testing and Materials guide for application of the enrichment meter principle using gamma spectra from a NaI detector.« less

Qualitative Methods in Field Research: An Indonesian Experience in Community Based Practice.

ERIC Educational Resources Information Center

Lysack, Catherine L.; Krefting, Laura

1994-01-01

Cross-cultural evaluation of a community-based rehabilitation project in Indonesia used three methods: focus groups, questionnaires, and key informant interviews. A continuous cyclical approach to data collection and concern for cultural sensitivity increased the rigor of the research. (SK)

76 FR 39860 - Proposed Agency Information Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-07

... ``Broad Program Area Categories'' (BPACs) for purposes of conducting the research. For each evaluation... data collection methods than those prescribed for high-rigor. For example, data may be collected by... methods to produce energy savings and outcome estimates. A range of qualitative, quantitative (survey), on...

The Navigation Guide Systematic Review Methodology: A Rigorous and Transparent Method for Translating Environmental Health Science into Better Health Outcomes

PubMed Central

Sutton, Patrice

2014-01-01

Background: Synthesizing what is known about the environmental drivers of health is instrumental to taking prevention-oriented action. Methods of research synthesis commonly used in environmental health lag behind systematic review methods developed in the clinical sciences over the past 20 years. Objectives: We sought to develop a proof of concept of the “Navigation Guide,” a systematic and transparent method of research synthesis in environmental health. Discussion: The Navigation Guide methodology builds on best practices in research synthesis in evidence-based medicine and environmental health. Key points of departure from current methods of expert-based narrative review prevalent in environmental health include a prespecified protocol, standardized and transparent documentation including expert judgment, a comprehensive search strategy, assessment of “risk of bias,” and separation of the science from values and preferences. Key points of departure from evidence-based medicine include assigning a “moderate” quality rating to human observational studies and combining diverse evidence streams. Conclusions: The Navigation Guide methodology is a systematic and rigorous approach to research synthesis that has been developed to reduce bias and maximize transparency in the evaluation of environmental health information. Although novel aspects of the method will require further development and validation, our findings demonstrated that improved methods of research synthesis under development at the National Toxicology Program and under consideration by the U.S. Environmental Protection Agency are fully achievable. The institutionalization of robust methods of systematic and transparent review would provide a concrete mechanism for linking science to timely action to prevent harm. Citation: Woodruff TJ, Sutton P. 2014. The Navigation Guide systematic review methodology: a rigorous and transparent method for translating environmental health science into better health outcomes. Environ Health Perspect 122:1007–1014; http://dx.doi.org/10.1289/ehp.1307175 PMID:24968373

Lattice modeling and application of independent component analysis to high power, long bunch beams in the Los Alamos Proton Storage Ring

NASA Astrophysics Data System (ADS)

Kolski, Jeffrey

The linear lattice properties of the Proton Storage Ring (PSR) at the Los Alamos Neutron Science Center (LANSCE) in Los Alamos, NM were measured and applied to determine a better linear accelerator model. We found that the initial model was deficient in predicting the vertical focusing strength. The additional vertical focusing was located through fundamental understanding of experiment and statistically rigorous analysis. An improved model was constructed and compared against the initial model and measurement at operation set points and set points far away from nominal and was shown to indeed be an enhanced model. Independent component analysis (ICA) is a tool for data mining in many fields of science. Traditionally, ICA is applied to turn-by-turn beam position data as a means to measure the lattice functions of the real machine. Due to the diagnostic setup for the PSR, this method is not applicable. A new application method for ICA is derived, ICA applied along the length of the bunch. The ICA modes represent motions within the beam pulse. Several of the dominate ICA modes are experimentally identified.

Assessing Juvenile Salmonid Passage Through Culverts: Field Research in Support of Protocol Development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Williams, Greg D.; Evans, Nathan R.; Pearson, Walter H.

2001-10-30

The primary goal of our research this spring/ summer was to refine techniques and examine scenarios under which a standardized protocol could be applied to assess juvenile coho salmon (O. kisutch) passage through road culverts. Field evaluations focused on capture-mark- recapture methods that allowed analysis of fish movement patterns, estimates of culvert passability, and potential identification of cues inducing these movements. At this stage, 0+ age coho salmon fry 30 mm to 65 mm long (fork length) were the species and age class of interest. Ultimately, the protocol will provide rapid, statistically rigorous methods for trained personnel to perform standardizedmore » biological assessments of culvert passability to a number of juvenile salmon species. Questions to be addressed by the research include the following: ? Do hydraulic structures such as culverts restrict habitat for juvenile salmonids? ? How do existing culverts and retrofits perform relative to juvenile salmonid passage? ? Do some culvert characteristics and hydraulic conditions provide better passage than others? ? Does the culvert represent a barrier to certain size classes of fish? Recommendations addressed issues of study site selection, initial capture, marking, recapture/observations, and estimating movement.« less

Methods in Symbolic Computation and p-Adic Valuations of Polynomials

NASA Astrophysics Data System (ADS)

Guan, Xiao

Symbolic computation has widely appear in many mathematical fields such as combinatorics, number theory and stochastic processes. The techniques created in the area of experimental mathematics provide us efficient ways of symbolic computing and verification of complicated relations. Part I consists of three problems. The first one focuses on a unimodal sequence derived from a quartic integral. Many of its properties are explored with the help of hypergeometric representations and automatic proofs. The second problem tackles the generating function of the reciprocal of Catalan number. It springs from the closed form given by Mathematica. Furthermore, three methods in special functions are used to justify this result. The third issue addresses the closed form solutions for the moments of products of generalized elliptic integrals , which combines the experimental mathematics and classical analysis. Part II concentrates on the p-adic valuations of polynomials from the perspective of trees. For a given polynomial f( n) indexed in positive integers, the package developed in Mathematica will create certain tree structure following a couple of rules. The evolution of such trees are studied both rigorously and experimentally from the view of field extension, nonparametric statistics and random matrix.

Revealing the face of an ancient Egyptian: synthesis of current and traditional approaches to evidence-based facial approximation.

PubMed

Lindsay, Kaitlin E; Rühli, Frank J; Deleon, Valerie Burke

2015-06-01

The technique of forensic facial approximation, or reconstruction, is one of many facets of the field of mummy studies. Although far from a rigorous scientific technique, evidence-based visualization of antemortem appearance may supplement radiological, chemical, histological, and epidemiological studies of ancient remains. Published guidelines exist for creating facial approximations, but few approximations are published with documentation of the specific process and references used. Additionally, significant new research has taken place in recent years which helps define best practices in the field. This case study records the facial approximation of a 3,000-year-old ancient Egyptian woman using medical imaging data and the digital sculpting program, ZBrush. It represents a synthesis of current published techniques based on the most solid anatomical and/or statistical evidence. Through this study, it was found that although certain improvements have been made in developing repeatable, evidence-based guidelines for facial approximation, there are many proposed methods still awaiting confirmation from comprehensive studies. This study attempts to assist artists, anthropologists, and forensic investigators working in facial approximation by presenting the recommended methods in a chronological and usable format. © 2015 Wiley Periodicals, Inc.

A two-factor error model for quantitative steganalysis

NASA Astrophysics Data System (ADS)

Böhme, Rainer; Ker, Andrew D.

2006-02-01

Quantitative steganalysis refers to the exercise not only of detecting the presence of hidden stego messages in carrier objects, but also of estimating the secret message length. This problem is well studied, with many detectors proposed but only a sparse analysis of errors in the estimators. A deep understanding of the error model, however, is a fundamental requirement for the assessment and comparison of different detection methods. This paper presents a rationale for a two-factor model for sources of error in quantitative steganalysis, and shows evidence from a dedicated large-scale nested experimental set-up with a total of more than 200 million attacks. Apart from general findings about the distribution functions found in both classes of errors, their respective weight is determined, and implications for statistical hypothesis tests in benchmarking scenarios or regression analyses are demonstrated. The results are based on a rigorous comparison of five different detection methods under many different external conditions, such as size of the carrier, previous JPEG compression, and colour channel selection. We include analyses demonstrating the effects of local variance and cover saturation on the different sources of error, as well as presenting the case for a relative bias model for between-image error.

DOE Office of Scientific and Technical Information (OSTI.GOV)

More, R.M.

A new statistical model (the quantum-statistical model (QSM)) was recently introduced by Kalitkin and Kuzmina for the calculation of thermodynamic properties of compressed matter. This paper examines the QSM and gives (i) a numerical QSM calculation of pressure and energy for aluminum and comparison to existing augmented-plane-wave data; (ii) display of separate kinetic, exchange, and quantum pressure terms; (iii) a study of electron density at the nucleus; (iv) a study of the effects of the Kirzhnitz-Weizsacker parameter controlling the gradient terms; (v) an analytic expansion for very high densities; and (vi) rigorous pressure theorems including a general version of themore » virial theorem which applies to an arbitrary microscopic volume. It is concluded that the QSM represents the most accurate and consistent theory of the Thomas-Fermi type.« less

Do climate extreme events foster violent civil conflicts? A coincidence analysis

NASA Astrophysics Data System (ADS)

Schleussner, Carl-Friedrich; Donges, Jonathan F.; Donner, Reik V.

2014-05-01

Civil conflicts promoted by adverse environmental conditions represent one of the most important potential feedbacks in the global socio-environmental nexus. While the role of climate extremes as a triggering factor is often discussed, no consensus is yet reached about the cause-and-effect relation in the observed data record. Here we present results of a rigorous statistical coincidence analysis based on the Munich Re Inc. extreme events database and the Uppsala conflict data program. We report evidence for statistically significant synchronicity between climate extremes with high economic impact and violent conflicts for various regions, although no coherent global signal emerges from our analysis. Our results indicate the importance of regional vulnerability and might aid to identify hot-spot regions for potential climate-triggered violent social conflicts.

Statistical moments of the Strehl ratio

NASA Astrophysics Data System (ADS)

Yaitskova, Natalia; Esselborn, Michael; Gladysz, Szymon

2012-07-01

Knowledge of the statistical characteristics of the Strehl ratio is essential for the performance assessment of the existing and future adaptive optics systems. For full assessment not only the mean value of the Strehl ratio but also higher statistical moments are important. Variance is related to the stability of an image and skewness reflects the chance to have in a set of short exposure images more or less images with the quality exceeding the mean. Skewness is a central parameter in the domain of lucky imaging. We present a rigorous theory for the calculation of the mean value, the variance and the skewness of the Strehl ratio. In our approach we represent the residual wavefront as being formed by independent cells. The level of the adaptive optics correction defines the number of the cells and the variance of the cells, which are the two main parameters of our theory. The deliverables are the values of the three moments as the functions of the correction level. We make no further assumptions except for the statistical independence of the cells.

How Do You Determine Whether The Earth Is Warming Up?

NASA Astrophysics Data System (ADS)

Restrepo, J. M.; Comeau, D.; Flaschka, H.

2012-12-01

How does one determine whether the extreme summer temperatures in the North East of the US, or in Moscow during the summer of 2010, was an extreme weather fluctuation or the result of a systematic global climate warming trend? It is only under exceptional circumstances that one can determine whether an observational climate signal belongs to a particular statistical distribution. In fact, observed climate signals are rarely "statistical" and thus there is usually no way to rigorously obtain enough field data to produce a trend or tendency, based upon data alone. Furthermore, this type of data is often multi-scale. We propose a trend or tendency methodology that does not make use of a parametric or a statistical assumption. The most important feature of this trend strategy is that it is defined in very precise mathematical terms. The tendency is easily understood and practical, and its algorithmic realization is fairly robust. In addition to proposing a trend, the methodology can be adopted to generate surrogate statistical models, useful in reduced filtering schemes of time dependent processes.

Statistical modeling of natural backgrounds in hyperspectral LWIR data

NASA Astrophysics Data System (ADS)

Truslow, Eric; Manolakis, Dimitris; Cooley, Thomas; Meola, Joseph

2016-09-01

Hyperspectral sensors operating in the long wave infrared (LWIR) have a wealth of applications including remote material identification and rare target detection. While statistical models for modeling surface reflectance in visible and near-infrared regimes have been well studied, models for the temperature and emissivity in the LWIR have not been rigorously investigated. In this paper, we investigate modeling hyperspectral LWIR data using a statistical mixture model for the emissivity and surface temperature. Statistical models for the surface parameters can be used to simulate surface radiances and at-sensor radiance which drives the variability of measured radiance and ultimately the performance of signal processing algorithms. Thus, having models that adequately capture data variation is extremely important for studying performance trades. The purpose of this paper is twofold. First, we study the validity of this model using real hyperspectral data, and compare the relative variability of hyperspectral data in the LWIR and visible and near-infrared (VNIR) regimes. Second, we illustrate how materials that are easily distinguished in the VNIR, may be difficult to separate when imaged in the LWIR.

Methods for assessing Phytophthora ramorum chlamydospore germination

Treesearch

Joyce Eberhart; Elilzabeth Stamm; Jennifer Parke

2013-01-01

Germination of chlamydospores is difficult to accurately assess when chlamydospores are attached to remnants of supporting hyphae. We developed two approaches for closely observing and rigorously quantifying the frequency of chlamydospore germination in vitro. The plate marking and scanning method was useful for quantifying germination of large...

Selection of species and sampling areas: The importance of inference

Treesearch

Paul Stephen Corn

2009-01-01

Inductive inference, the process of drawing general conclusions from specific observations, is fundamental to the scientific method. Platt (1964) termed conclusions obtained through rigorous application of the scientific method as "strong inference" and noted the following basic steps: generating alternative hypotheses; devising experiments, the...

Approaching Cauchy's Theorem

ERIC Educational Resources Information Center

Garcia, Stephan Ramon; Ross, William T.

2017-01-01

We hope to initiate a discussion about various methods for introducing Cauchy's Theorem. Although Cauchy's Theorem is the fundamental theorem upon which complex analysis is based, there is no "standard approach." The appropriate choice depends upon the prerequisites for the course and the level of rigor intended. Common methods include…

Statistical Mechanics of Disordered Systems - Series: Cambridge Series in Statistical and Probabilistic Mathematics (No. 18)

NASA Astrophysics Data System (ADS)

Bovier, Anton

2006-06-01

Our mathematical understanding of the statistical mechanics of disordered systems is going through a period of stunning progress. This self-contained book is a graduate-level introduction for mathematicians and for physicists interested in the mathematical foundations of the field, and can be used as a textbook for a two-semester course on mathematical statistical mechanics. It assumes only basic knowledge of classical physics and, on the mathematics side, a good working knowledge of graduate-level probability theory. The book starts with a concise introduction to statistical mechanics, proceeds to disordered lattice spin systems, and concludes with a presentation of the latest developments in the mathematical understanding of mean-field spin glass models. In particular, recent progress towards a rigorous understanding of the replica symmetry-breaking solutions of the Sherrington-Kirkpatrick spin glass models, due to Guerra, Aizenman-Sims-Starr and Talagrand, is reviewed in some detail. Comprehensive introduction to an active and fascinating area of research Clear exposition that builds to the state of the art in the mathematics of spin glasses Written by a well-known and active researcher in the field

Best practices for evaluating single nucleotide variant calling methods for microbial genomics

PubMed Central

Olson, Nathan D.; Lund, Steven P.; Colman, Rebecca E.; Foster, Jeffrey T.; Sahl, Jason W.; Schupp, James M.; Keim, Paul; Morrow, Jayne B.; Salit, Marc L.; Zook, Justin M.

2015-01-01

Innovations in sequencing technologies have allowed biologists to make incredible advances in understanding biological systems. As experience grows, researchers increasingly recognize that analyzing the wealth of data provided by these new sequencing platforms requires careful attention to detail for robust results. Thus far, much of the scientific Communit’s focus for use in bacterial genomics has been on evaluating genome assembly algorithms and rigorously validating assembly program performance. Missing, however, is a focus on critical evaluation of variant callers for these genomes. Variant calling is essential for comparative genomics as it yields insights into nucleotide-level organismal differences. Variant calling is a multistep process with a host of potential error sources that may lead to incorrect variant calls. Identifying and resolving these incorrect calls is critical for bacterial genomics to advance. The goal of this review is to provide guidance on validating algorithms and pipelines used in variant calling for bacterial genomics. First, we will provide an overview of the variant calling procedures and the potential sources of error associated with the methods. We will then identify appropriate datasets for use in evaluating algorithms and describe statistical methods for evaluating algorithm performance. As variant calling moves from basic research to the applied setting, standardized methods for performance evaluation and reporting are required; it is our hope that this review provides the groundwork for the development of these standards. PMID:26217378

The current state of funded NIH grants in implementation science in genomic medicine: a portfolio analysis.

PubMed

Roberts, Megan C; Clyne, Mindy; Kennedy, Amy E; Chambers, David A; Khoury, Muin J

2017-10-26

PurposeImplementation science offers methods to evaluate the translation of genomic medicine research into practice. The extent to which the National Institutes of Health (NIH) human genomics grant portfolio includes implementation science is unknown. This brief report's objective is to describe recently funded implementation science studies in genomic medicine in the NIH grant portfolio, and identify remaining gaps.MethodsWe identified investigator-initiated NIH research grants on implementation science in genomic medicine (funding initiated 2012-2016). A codebook was adapted from the literature, three authors coded grants, and descriptive statistics were calculated for each code.ResultsForty-two grants fit the inclusion criteria (~1.75% of investigator-initiated genomics grants). The majority of included grants proposed qualitative and/or quantitative methods with cross-sectional study designs, and described clinical settings and primarily white, non-Hispanic study populations. Most grants were in oncology and examined genetic testing for risk assessment. Finally, grants lacked the use of implementation science frameworks, and most examined uptake of genomic medicine and/or assessed patient-centeredness.ConclusionWe identified large gaps in implementation science studies in genomic medicine in the funded NIH portfolio over the past 5 years. To move the genomics field forward, investigator-initiated research grants should employ rigorous implementation science methods within diverse settings and populations.Genetics in Medicine advance online publication, 26 October 2017; doi:10.1038/gim.2017.180.

Quantification of uncertainty in aerosol optical thickness retrieval arising from aerosol microphysical model and other sources, applied to Ozone Monitoring Instrument (OMI) measurements

NASA Astrophysics Data System (ADS)

Määttä, A.; Laine, M.; Tamminen, J.; Veefkind, J. P.

2014-05-01

Satellite instruments are nowadays successfully utilised for measuring atmospheric aerosol in many applications as well as in research. Therefore, there is a growing need for rigorous error characterisation of the measurements. Here, we introduce a methodology for quantifying the uncertainty in the retrieval of aerosol optical thickness (AOT). In particular, we concentrate on two aspects: uncertainty due to aerosol microphysical model selection and uncertainty due to imperfect forward modelling. We apply the introduced methodology for aerosol optical thickness retrieval of the Ozone Monitoring Instrument (OMI) on board NASA's Earth Observing System (EOS) Aura satellite, launched in 2004. We apply statistical methodologies that improve the uncertainty estimates of the aerosol optical thickness retrieval by propagating aerosol microphysical model selection and forward model error more realistically. For the microphysical model selection problem, we utilise Bayesian model selection and model averaging methods. Gaussian processes are utilised to characterise the smooth systematic discrepancies between the measured and modelled reflectances (i.e. residuals). The spectral correlation is composed empirically by exploring a set of residuals. The operational OMI multi-wavelength aerosol retrieval algorithm OMAERO is used for cloud-free, over-land pixels of the OMI instrument with the additional Bayesian model selection and model discrepancy techniques introduced here. The method and improved uncertainty characterisation is demonstrated by several examples with different aerosol properties: weakly absorbing aerosols, forest fires over Greece and Russia, and Sahara desert dust. The statistical methodology presented is general; it is not restricted to this particular satellite retrieval application.

Recommendations for the Design and Analysis of Treatment Trials for Alcohol Use Disorders.

PubMed

Witkiewitz, Katie; Finney, John W; Harris, Alex H S; Kivlahan, Daniel R; Kranzler, Henry R

2015-09-01

Over the past 60 years, the view that "alcoholism" is a disease for which the only acceptable goal of treatment is abstinence has given way to the recognition that alcohol use disorders (AUDs) occur on a continuum of severity, for which a variety of treatment options are appropriate. However, because the available treatments for AUDs are not effective for everyone, more research is needed to develop novel and more efficacious treatments to address the range of AUD severity in diverse populations. Here we offer recommendations for the design and analysis of alcohol treatment trials, with a specific focus on the careful conduct of randomized clinical trials of medications and nonpharmacological interventions for AUDs. This paper provides a narrative review of the quality of published clinical trials and recommendations for the optimal design and analysis of treatment trials for AUDs. Despite considerable improvements in the design of alcohol clinical trials over the past 2 decades, many studies of AUD treatments have used faulty design features and statistical methods that are known to produce biased estimates of treatment efficacy. The published statistical and methodological literatures provide clear guidance on methods to improve clinical trial design and analysis. Consistent use of state-of-the-art design features and analytic approaches will enhance the internal and external validity of treatment trials for AUDs across the spectrum of severity. The ultimate result of this attention to methodological rigor is that better treatment options will be identified for patients with an AUD. Copyright © 2015 by the Research Society on Alcoholism.

Identifying and characterizing hepatitis C virus hotspots in Massachusetts: a spatial epidemiological approach.

PubMed

Stopka, Thomas J; Goulart, Michael A; Meyers, David J; Hutcheson, Marga; Barton, Kerri; Onofrey, Shauna; Church, Daniel; Donahue, Ashley; Chui, Kenneth K H

2017-04-20

Hepatitis C virus (HCV) infections have increased during the past decade but little is known about geographic clustering patterns. We used a unique analytical approach, combining geographic information systems (GIS), spatial epidemiology, and statistical modeling to identify and characterize HCV hotspots, statistically significant clusters of census tracts with elevated HCV counts and rates. We compiled sociodemographic and HCV surveillance data (n = 99,780 cases) for Massachusetts census tracts (n = 1464) from 2002 to 2013. We used a five-step spatial epidemiological approach, calculating incremental spatial autocorrelations and Getis-Ord Gi* statistics to identify clusters. We conducted logistic regression analyses to determine factors associated with the HCV hotspots. We identified nine HCV clusters, with the largest in Boston, New Bedford/Fall River, Worcester, and Springfield (p < 0.05). In multivariable analyses, we found that HCV hotspots were independently and positively associated with the percent of the population that was Hispanic (adjusted odds ratio [AOR]: 1.07; 95% confidence interval [CI]: 1.04, 1.09) and the percent of households receiving food stamps (AOR: 1.83; 95% CI: 1.22, 2.74). HCV hotspots were independently and negatively associated with the percent of the population that were high school graduates or higher (AOR: 0.91; 95% CI: 0.89, 0.93) and the percent of the population in the "other" race/ethnicity category (AOR: 0.88; 95% CI: 0.85, 0.91). We identified locations where HCV clusters were a concern, and where enhanced HCV prevention, treatment, and care can help combat the HCV epidemic in Massachusetts. GIS, spatial epidemiological and statistical analyses provided a rigorous approach to identify hotspot clusters of disease, which can inform public health policy and intervention targeting. Further studies that incorporate spatiotemporal cluster analyses, Bayesian spatial and geostatistical models, spatially weighted regression analyses, and assessment of associations between HCV clustering and the built environment are needed to expand upon our combined spatial epidemiological and statistical methods.

A Multiphase Validation of Atlas-Based Automatic and Semiautomatic Segmentation Strategies for Prostate MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martin, Spencer; Rodrigues, George, E-mail: george.rodrigues@lhsc.on.ca; Department of Epidemiology/Biostatistics, University of Western Ontario, London

2013-01-01

Purpose: To perform a rigorous technological assessment and statistical validation of a software technology for anatomic delineations of the prostate on MRI datasets. Methods and Materials: A 3-phase validation strategy was used. Phase I consisted of anatomic atlas building using 100 prostate cancer MRI data sets to provide training data sets for the segmentation algorithms. In phase II, 2 experts contoured 15 new MRI prostate cancer cases using 3 approaches (manual, N points, and region of interest). In phase III, 5 new physicians with variable MRI prostate contouring experience segmented the same 15 phase II datasets using 3 approaches: manual,more » N points with no editing, and full autosegmentation with user editing allowed. Statistical analyses for time and accuracy (using Dice similarity coefficient) endpoints used traditional descriptive statistics, analysis of variance, analysis of covariance, and pooled Student t test. Results: In phase I, average (SD) total and per slice contouring time for the 2 physicians was 228 (75), 17 (3.5), 209 (65), and 15 seconds (3.9), respectively. In phase II, statistically significant differences in physician contouring time were observed based on physician, type of contouring, and case sequence. The N points strategy resulted in superior segmentation accuracy when initial autosegmented contours were compared with final contours. In phase III, statistically significant differences in contouring time were observed based on physician, type of contouring, and case sequence again. The average relative timesaving for N points and autosegmentation were 49% and 27%, respectively, compared with manual contouring. The N points and autosegmentation strategies resulted in average Dice values of 0.89 and 0.88, respectively. Pre- and postedited autosegmented contours demonstrated a higher average Dice similarity coefficient of 0.94. Conclusion: The software provided robust contours with minimal editing required. Observed time savings were seen for all physicians irrespective of experience level and baseline manual contouring speed.« less

Rigorous Electromagnetic Analysis of the Focusing Action of Refractive Cylindrical Microlens

NASA Astrophysics Data System (ADS)

Liu, Juan; Gu, Ben-Yuan; Dong, Bi-Zhen; Yang, Guo-Zhen

The focusing action of refractive cylindrical microlens is investigated based on the rigorous electromagnetic theory with the use of the boundary element method. The focusing behaviors of these refractive microlenses with continuous and multilevel surface-envelope are characterized in terms of total electric-field patterns, the electric-field intensity distributions on the focal plane, and their diffractive efficiencies at the focal spots. The obtained results are also compared with the ones obtained by Kirchhoff's scalar diffraction theory. The present numerical and graphical results may provide useful information for the analysis and design of refractive elements in micro-optics.