Selection of the Maximum Spatial Cluster Size of the Spatial Scan Statistic by Using the Maximum Clustering Set-Proportion Statistic.

PubMed

Ma, Yue; Yin, Fei; Zhang, Tao; Zhou, Xiaohua Andrew; Li, Xiaosong

2016-01-01

Spatial scan statistics are widely used in various fields. The performance of these statistics is influenced by parameters, such as maximum spatial cluster size, and can be improved by parameter selection using performance measures. Current performance measures are based on the presence of clusters and are thus inapplicable to data sets without known clusters. In this work, we propose a novel overall performance measure called maximum clustering set-proportion (MCS-P), which is based on the likelihood of the union of detected clusters and the applied dataset. MCS-P was compared with existing performance measures in a simulation study to select the maximum spatial cluster size. Results of other performance measures, such as sensitivity and misclassification, suggest that the spatial scan statistic achieves accurate results in most scenarios with the maximum spatial cluster sizes selected using MCS-P. Given that previously known clusters are not required in the proposed strategy, selection of the optimal maximum cluster size with MCS-P can improve the performance of the scan statistic in applications without identified clusters.

Selection of the Maximum Spatial Cluster Size of the Spatial Scan Statistic by Using the Maximum Clustering Set-Proportion Statistic

PubMed Central

Ma, Yue; Yin, Fei; Zhang, Tao; Zhou, Xiaohua Andrew; Li, Xiaosong

2016-01-01

Spatial scan statistics are widely used in various fields. The performance of these statistics is influenced by parameters, such as maximum spatial cluster size, and can be improved by parameter selection using performance measures. Current performance measures are based on the presence of clusters and are thus inapplicable to data sets without known clusters. In this work, we propose a novel overall performance measure called maximum clustering set–proportion (MCS-P), which is based on the likelihood of the union of detected clusters and the applied dataset. MCS-P was compared with existing performance measures in a simulation study to select the maximum spatial cluster size. Results of other performance measures, such as sensitivity and misclassification, suggest that the spatial scan statistic achieves accurate results in most scenarios with the maximum spatial cluster sizes selected using MCS-P. Given that previously known clusters are not required in the proposed strategy, selection of the optimal maximum cluster size with MCS-P can improve the performance of the scan statistic in applications without identified clusters. PMID:26820646

Compendium of Methods for Applying Measured Data to Vibration and Acoustic Problems

DTIC Science & Technology

1985-10-01

statistical energy analysis , finite element models, transfer function...Procedures for the Modal Analysis Method .............................................. 8-22 8.4 Summary of the Procedures for the Statistical Energy Analysis Method... statistical energy analysis . 8-1 • o + . . i... "_+,A" L + "+..• •+A ’! i, + +.+ +• o.+ -ore -+. • -..- , .%..% ". • 2 -".-2- ;.-.’, . o . It is helpful

Applications of spatial statistical network models to stream data

Treesearch

Daniel J. Isaak; Erin E. Peterson; Jay M. Ver Hoef; Seth J. Wenger; Jeffrey A. Falke; Christian E. Torgersen; Colin Sowder; E. Ashley Steel; Marie-Josee Fortin; Chris E. Jordan; Aaron S. Ruesch; Nicholas Som; Pascal Monestiez

2014-01-01

Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for...

[The research protocol VI: How to choose the appropriate statistical test. Inferential statistics].

PubMed

Flores-Ruiz, Eric; Miranda-Novales, María Guadalupe; Villasís-Keever, Miguel Ángel

2017-01-01

The statistical analysis can be divided in two main components: descriptive analysis and inferential analysis. An inference is to elaborate conclusions from the tests performed with the data obtained from a sample of a population. Statistical tests are used in order to establish the probability that a conclusion obtained from a sample is applicable to the population from which it was obtained. However, choosing the appropriate statistical test in general poses a challenge for novice researchers. To choose the statistical test it is necessary to take into account three aspects: the research design, the number of measurements and the scale of measurement of the variables. Statistical tests are divided into two sets, parametric and nonparametric. Parametric tests can only be used if the data show a normal distribution. Choosing the right statistical test will make it easier for readers to understand and apply the results.

Analysis of Antarctic Remote-Site Automatic Weather Station Data for Period January 1979 - February 1980.

DTIC Science & Technology

1982-06-01

usefulness to the Untted States Antarctic mission as managed by the National Science Foundation. Various statistical measures were applied to the reported... statistical procedures that would evolve a general meteorological picture of each of these remote sites. Primary texts used as a basis for...processed by station for monthly, seasonal and annual statistics , as appropriate. The following outlines the evaluations completed for both

Characterizations of linear sufficient statistics

NASA Technical Reports Server (NTRS)

Peters, B. C., Jr.; Reoner, R.; Decell, H. P., Jr.

1977-01-01

A surjective bounded linear operator T from a Banach space X to a Banach space Y must be a sufficient statistic for a dominated family of probability measures defined on the Borel sets of X. These results were applied, so that they characterize linear sufficient statistics for families of the exponential type, including as special cases the Wishart and multivariate normal distributions. The latter result was used to establish precisely which procedures for sampling from a normal population had the property that the sample mean was a sufficient statistic.

Uncertainty Analysis of Seebeck Coefficient and Electrical Resistivity Characterization

NASA Technical Reports Server (NTRS)

Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred

2014-01-01

In order to provide a complete description of a materials thermoelectric power factor, in addition to the measured nominal value, an uncertainty interval is required. The uncertainty may contain sources of measurement error including systematic bias error and precision error of a statistical nature. The work focuses specifically on the popular ZEM-3 (Ulvac Technologies) measurement system, but the methods apply to any measurement system. The analysis accounts for sources of systematic error including sample preparation tolerance, measurement probe placement, thermocouple cold-finger effect, and measurement parameters; in addition to including uncertainty of a statistical nature. Complete uncertainty analysis of a measurement system allows for more reliable comparison of measurement data between laboratories.

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

Lewis, John R.; Brooks, Dusty Marie

In pressurized water reactors, the prevention, detection, and repair of cracks within dissimilar metal welds is essential to ensure proper plant functionality and safety. Weld residual stresses, which are difficult to model and cannot be directly measured, contribute to the formation and growth of cracks due to primary water stress corrosion cracking. Additionally, the uncertainty in weld residual stress measurements and modeling predictions is not well understood, further complicating the prediction of crack evolution. The purpose of this document is to develop methodology to quantify the uncertainty associated with weld residual stress that can be applied to modeling predictions andmore » experimental measurements. Ultimately, the results can be used to assess the current state of uncertainty and to build confidence in both modeling and experimental procedures. The methodology consists of statistically modeling the variation in the weld residual stress profiles using functional data analysis techniques. Uncertainty is quantified using statistical bounds (e.g. confidence and tolerance bounds) constructed with a semi-parametric bootstrap procedure. Such bounds describe the range in which quantities of interest, such as means, are expected to lie as evidenced by the data. The methodology is extended to provide direct comparisons between experimental measurements and modeling predictions by constructing statistical confidence bounds for the average difference between the two quantities. The statistical bounds on the average difference can be used to assess the level of agreement between measurements and predictions. The methodology is applied to experimental measurements of residual stress obtained using two strain relief measurement methods and predictions from seven finite element models developed by different organizations during a round robin study.« less

Test Statistics and Confidence Intervals to Establish Noninferiority between Treatments with Ordinal Categorical Data.

PubMed

Zhang, Fanghong; Miyaoka, Etsuo; Huang, Fuping; Tanaka, Yutaka

2015-01-01

The problem for establishing noninferiority is discussed between a new treatment and a standard (control) treatment with ordinal categorical data. A measure of treatment effect is used and a method of specifying noninferiority margin for the measure is provided. Two Z-type test statistics are proposed where the estimation of variance is constructed under the shifted null hypothesis using U-statistics. Furthermore, the confidence interval and the sample size formula are given based on the proposed test statistics. The proposed procedure is applied to a dataset from a clinical trial. A simulation study is conducted to compare the performance of the proposed test statistics with that of the existing ones, and the results show that the proposed test statistics are better in terms of the deviation from nominal level and the power.

A Laboratory Experiment on the Statistical Theory of Nuclear Reactions

ERIC Educational Resources Information Center

Loveland, Walter

1971-01-01

Describes an undergraduate laboratory experiment on the statistical theory of nuclear reactions. The experiment involves measuring the relative cross sections for formation of a nucleus in its meta stable excited state and its ground state by applying gamma-ray spectroscopy to an irradiated sample. Involves 3-4 hours of laboratory time plus…

Statistical Physics in the Era of Big Data

ERIC Educational Resources Information Center

Wang, Dashun

2013-01-01

With the wealth of data provided by a wide range of high-throughout measurement tools and technologies, statistical physics of complex systems is entering a new phase, impacting in a meaningful fashion a wide range of fields, from cell biology to computer science to economics. In this dissertation, by applying tools and techniques developed in…

Conference Report on Youth Unemployment: Its Measurements and Meaning.

ERIC Educational Resources Information Center

Employment and Training Administration (DOL), Washington, DC.

Thirteen papers presented at a conference on employment statistics and youth are contained in this report. Reviewed are the problems of gathering, interpreting, and applying employment and unemployment data relating to youth. The titles of the papers are as follow: "Counting Youth: A Comparison of Youth Labor Force Statistics in the Current…

Uncertainty Analysis of Inertial Model Attitude Sensor Calibration and Application with a Recommended New Calibration Method

NASA Technical Reports Server (NTRS)

Tripp, John S.; Tcheng, Ping

1999-01-01

Statistical tools, previously developed for nonlinear least-squares estimation of multivariate sensor calibration parameters and the associated calibration uncertainty analysis, have been applied to single- and multiple-axis inertial model attitude sensors used in wind tunnel testing to measure angle of attack and roll angle. The analysis provides confidence and prediction intervals of calibrated sensor measurement uncertainty as functions of applied input pitch and roll angles. A comparative performance study of various experimental designs for inertial sensor calibration is presented along with corroborating experimental data. The importance of replicated calibrations over extended time periods has been emphasized; replication provides independent estimates of calibration precision and bias uncertainties, statistical tests for calibration or modeling bias uncertainty, and statistical tests for sensor parameter drift over time. A set of recommendations for a new standardized model attitude sensor calibration method and usage procedures is included. The statistical information provided by these procedures is necessary for the uncertainty analysis of aerospace test results now required by users of industrial wind tunnel test facilities.

[Diversity and frequency of scientific research design and statistical methods in the "Arquivos Brasileiros de Oftalmologia": a systematic review of the "Arquivos Brasileiros de Oftalmologia"--1993-2002].

PubMed

Crosta, Fernando; Nishiwaki-Dantas, Maria Cristina; Silvino, Wilmar; Dantas, Paulo Elias Correa

2005-01-01

To verify the frequency of study design, applied statistical analysis and approval by institutional review offices (Ethics Committee) of articles published in the "Arquivos Brasileiros de Oftalmologia" during a 10-year interval, with later comparative and critical analysis by some of the main international journals in the field of Ophthalmology. Systematic review without metanalysis was performed. Scientific papers published in the "Arquivos Brasileiros de Oftalmologia" between January 1993 and December 2002 were reviewed by two independent reviewers and classified according to the applied study design, statistical analysis and approval by the institutional review offices. To categorize those variables, a descriptive statistical analysis was used. After applying inclusion and exclusion criteria, 584 articles for evaluation of statistical analysis and, 725 articles for evaluation of study design were reviewed. Contingency table (23.10%) was the most frequently applied statistical method, followed by non-parametric tests (18.19%), Student's t test (12.65%), central tendency measures (10.60%) and analysis of variance (9.81%). Of 584 reviewed articles, 291 (49.82%) presented no statistical analysis. Observational case series (26.48%) was the most frequently used type of study design, followed by interventional case series (18.48%), observational case description (13.37%), non-random clinical study (8.96%) and experimental study (8.55%). We found a higher frequency of observational clinical studies, lack of statistical analysis in almost half of the published papers. Increase in studies with approval by institutional review Ethics Committee was noted since it became mandatory in 1996.

Diversity of Poissonian populations.

PubMed

Eliazar, Iddo I; Sokolov, Igor M

2010-01-01

Populations represented by collections of points scattered randomly on the real line are ubiquitous in science and engineering. The statistical modeling of such populations leads naturally to Poissonian populations-Poisson processes on the real line with a distinguished maximal point. Poissonian populations are infinite objects underlying key issues in statistical physics, probability theory, and random fractals. Due to their infiniteness, measuring the diversity of Poissonian populations depends on the lower-bound cut-off applied. This research characterizes the classes of Poissonian populations whose diversities are invariant with respect to the cut-off level applied and establishes an elemental connection between these classes and extreme-value theory. The measures of diversity considered are variance and dispersion, Simpson's index and inverse participation ratio, Shannon's entropy and Rényi's entropy, and Gini's index.

Non-Destructive Measurement Methods (Neutron-, X-ray Radiography, Vibration Diagnostics and Ultrasound) in the Inspection of Helicopter Rotor Blades

DTIC Science & Technology

2005-04-01

the radiography gauging. In addition to the Statistical Energy Analysis (SEA) measurement a small exciter table (BK4810) and impedance head (BK 8000... Statistical Energy Analysis ; 7th Conf. on Vehicle System Dynamics, Identification and Anomalies (VSDIA2000), 6-8 Nov. 2000 Budapest, Proc. pp. 491-493... Energy Analysis (SEA) and Ultrasound Test. (UT) were concurrently applied. These methods collect accessory information on the objects under inspection

Analyzing Randomized Controlled Interventions: Three Notes for Applied Linguists

ERIC Educational Resources Information Center

Vanhove, Jan

2015-01-01

I discuss three common practices that obfuscate or invalidate the statistical analysis of randomized controlled interventions in applied linguistics. These are (a) checking whether randomization produced groups that are balanced on a number of possibly relevant covariates, (b) using repeated measures ANOVA to analyze pretest-posttest designs, and…

Spatial Accessibility and Availability Measures and Statistical Properties in the Food Environment

PubMed Central

Van Meter, E.; Lawson, A.B.; Colabianchi, N.; Nichols, M.; Hibbert, J.; Porter, D.; Liese, A.D.

2010-01-01

Spatial accessibility is of increasing interest in the health sciences. This paper addresses the statistical use of spatial accessibility and availability indices. These measures are evaluated via an extensive simulation based on cluster models for local food outlet density. We derived Monte Carlo critical values for several statistical tests based on the indices. In particular we are interested in the ability to make inferential comparisons between different study areas where indices of accessibility and availability are to be calculated. We derive tests of mean difference as well as tests for differences in Moran's I for spatial correlation for each of the accessibility and availability indices. We also apply these new statistical tests to a data example based on two counties in South Carolina for various accessibility and availability measures calculated for food outlets, stores, and restaurants. PMID:21499528

Survey statistics of automated segmentations applied to optical imaging of mammalian cells.

PubMed

Bajcsy, Peter; Cardone, Antonio; Chalfoun, Joe; Halter, Michael; Juba, Derek; Kociolek, Marcin; Majurski, Michael; Peskin, Adele; Simon, Carl; Simon, Mylene; Vandecreme, Antoine; Brady, Mary

2015-10-15

The goal of this survey paper is to overview cellular measurements using optical microscopy imaging followed by automated image segmentation. The cellular measurements of primary interest are taken from mammalian cells and their components. They are denoted as two- or three-dimensional (2D or 3D) image objects of biological interest. In our applications, such cellular measurements are important for understanding cell phenomena, such as cell counts, cell-scaffold interactions, cell colony growth rates, or cell pluripotency stability, as well as for establishing quality metrics for stem cell therapies. In this context, this survey paper is focused on automated segmentation as a software-based measurement leading to quantitative cellular measurements. We define the scope of this survey and a classification schema first. Next, all found and manually filteredpublications are classified according to the main categories: (1) objects of interests (or objects to be segmented), (2) imaging modalities, (3) digital data axes, (4) segmentation algorithms, (5) segmentation evaluations, (6) computational hardware platforms used for segmentation acceleration, and (7) object (cellular) measurements. Finally, all classified papers are converted programmatically into a set of hyperlinked web pages with occurrence and co-occurrence statistics of assigned categories. The survey paper presents to a reader: (a) the state-of-the-art overview of published papers about automated segmentation applied to optical microscopy imaging of mammalian cells, (b) a classification of segmentation aspects in the context of cell optical imaging, (c) histogram and co-occurrence summary statistics about cellular measurements, segmentations, segmented objects, segmentation evaluations, and the use of computational platforms for accelerating segmentation execution, and (d) open research problems to pursue. The novel contributions of this survey paper are: (1) a new type of classification of cellular measurements and automated segmentation, (2) statistics about the published literature, and (3) a web hyperlinked interface to classification statistics of the surveyed papers at https://isg.nist.gov/deepzoomweb/resources/survey/index.html.

Application of an Entropic Approach to Assessing Systems Integration

DTIC Science & Technology

2012-03-01

two econometrical measures of information efficiency – Shannon entropy and Hurst exponent . Shannon entropy (which is explained in Chapter III) can be...applied to evaluate long-term correlation of time series, while Hurst exponent can be applied to classify the time series in accordance to existence...of trend. Hurst exponent is the statistical measure of time series long-range dependence, and its value falls in the interval [0, 1] – a value in

Speckle reduction in optical coherence tomography by adaptive total variation method

NASA Astrophysics Data System (ADS)

Wu, Tong; Shi, Yaoyao; Liu, Youwen; He, Chongjun

2015-12-01

An adaptive total variation method based on the combination of speckle statistics and total variation restoration is proposed and developed for reducing speckle noise in optical coherence tomography (OCT) images. The statistical distribution of the speckle noise in OCT image is investigated and measured. With the measured parameters such as the mean value and variance of the speckle noise, the OCT image is restored by the adaptive total variation restoration method. The adaptive total variation restoration algorithm was applied to the OCT images of a volunteer's hand skin, which showed effective speckle noise reduction and image quality improvement. For image quality comparison, the commonly used median filtering method was also applied to the same images to reduce the speckle noise. The measured results demonstrate the superior performance of the adaptive total variation restoration method in terms of image signal-to-noise ratio, equivalent number of looks, contrast-to-noise ratio, and mean square error.

Brain tissues volume measurements from 2D MRI using parametric approach

NASA Astrophysics Data System (ADS)

L'vov, A. A.; Toropova, O. A.; Litovka, Yu. V.

2018-04-01

The purpose of the paper is to propose a fully automated method of volume assessment of structures within human brain. Our statistical approach uses maximum interdependency principle for decision making process of measurements consistency and unequal observations. Detecting outliers performed using maximum normalized residual test. We propose a statistical model which utilizes knowledge of tissues distribution in human brain and applies partial data restoration for precision improvement. The approach proposes completed computationally efficient and independent from segmentation algorithm used in the application.

An Interview with David Rindskopf: A Leading Voice on Teaching Statistics and Methodology

ERIC Educational Resources Information Center

Bembenutty, Hefer

2011-01-01

This article presents an interview with David Rindskopf, a Distinguished Professor of Educational Psychology and Psychology at the City University of New York Graduate Center, where he has taught since 1979. His research and teaching are in the area of applied statistics, measurement, and research design. He is a fellow of the American Statistical…

How Does One Assess the Accuracy of Academic Success Predictors? ROC Analysis Applied to University Entrance Factors

ERIC Educational Resources Information Center

Vivo, Juana-Maria; Franco, Manuel

2008-01-01

This article attempts to present a novel application of a method of measuring accuracy for academic success predictors that could be used as a standard. This procedure is known as the receiver operating characteristic (ROC) curve, which comes from statistical decision techniques. The statistical prediction techniques provide predictor models and…

An Empirical Investigation of Methods for Assessing Item Fit for Mixed Format Tests

ERIC Educational Resources Information Center

Chon, Kyong Hee; Lee, Won-Chan; Ansley, Timothy N.

2013-01-01

Empirical information regarding performance of model-fit procedures has been a persistent need in measurement practice. Statistical procedures for evaluating item fit were applied to real test examples that consist of both dichotomously and polytomously scored items. The item fit statistics used in this study included the PARSCALE's G[squared],…

Statistical analysis of global horizontal solar irradiation GHI in Fez city, Morocco

NASA Astrophysics Data System (ADS)

Bounoua, Z.; Mechaqrane, A.

2018-05-01

An accurate knowledge of the solar energy reaching the ground is necessary for sizing and optimizing the performances of solar installations. This paper describes a statistical analysis of the global horizontal solar irradiation (GHI) at Fez city, Morocco. For better reliability, we have first applied a set of check procedures to test the quality of hourly GHI measurements. We then eliminate the erroneous values which are generally due to measurement or the cosine effect errors. Statistical analysis show that the annual mean daily values of GHI is of approximately 5 kWh/m²/day. Daily monthly mean values and other parameter are also calculated.

Assessing the Accuracy and Consistency of Language Proficiency Classification under Competing Measurement Models

ERIC Educational Resources Information Center

Zhang, Bo

2010-01-01

This article investigates how measurement models and statistical procedures can be applied to estimate the accuracy of proficiency classification in language testing. The paper starts with a concise introduction of four measurement models: the classical test theory (CTT) model, the dichotomous item response theory (IRT) model, the testlet response…

Correlation and agreement: overview and clarification of competing concepts and measures.

PubMed

Liu, Jinyuan; Tang, Wan; Chen, Guanqin; Lu, Yin; Feng, Changyong; Tu, Xin M

2016-04-25

Agreement and correlation are widely-used concepts that assess the association between variables. Although similar and related, they represent completely different notions of association. Assessing agreement between variables assumes that the variables measure the same construct, while correlation of variables can be assessed for variables that measure completely different constructs. This conceptual difference requires the use of different statistical methods, and when assessing agreement or correlation, the statistical method may vary depending on the distribution of the data and the interest of the investigator. For example, the Pearson correlation, a popular measure of correlation between continuous variables, is only informative when applied to variables that have linear relationships; it may be non-informative or even misleading when applied to variables that are not linearly related. Likewise, the intraclass correlation, a popular measure of agreement between continuous variables, may not provide sufficient information for investigators if the nature of poor agreement is of interest. This report reviews the concepts of agreement and correlation and discusses differences in the application of several commonly used measures.

Interference detection and correction applied to incoherent-scatter radar power spectrum measurement

NASA Technical Reports Server (NTRS)

Ying, W. P.; Mathews, J. D.; Rastogi, P. K.

1986-01-01

A median filter based interference detection and correction technique is evaluated and the method applied to the Arecibo incoherent scatter radar D-region ionospheric power spectrum is discussed. The method can be extended to other kinds of data when the statistics involved in the process are still valid.

Agreement Analysis: What He Said, She Said Versus You Said.

PubMed

Vetter, Thomas R; Schober, Patrick

2018-06-01

Correlation and agreement are 2 concepts that are widely applied in the medical literature and clinical practice to assess for the presence and strength of an association. However, because correlation and agreement are conceptually distinct, they require the use of different statistics. Agreement is a concept that is closely related to but fundamentally different from and often confused with correlation. The idea of agreement refers to the notion of reproducibility of clinical evaluations or biomedical measurements. The intraclass correlation coefficient is a commonly applied measure of agreement for continuous data. The intraclass correlation coefficient can be validly applied specifically to assess intrarater reliability and interrater reliability. As its name implies, the Lin concordance correlation coefficient is another measure of agreement or concordance. In undertaking a comparison of a new measurement technique with an established one, it is necessary to determine whether they agree sufficiently for the new to replace the old. Bland and Altman demonstrated that using a correlation coefficient is not appropriate for assessing the interchangeability of 2 such measurement methods. They in turn described an alternative approach, the since widely applied graphical Bland-Altman Plot, which is based on a simple estimation of the mean and standard deviation of differences between measurements by the 2 methods. In reading a medical journal article that includes the interpretation of diagnostic tests and application of diagnostic criteria, attention is conventionally focused on aspects like sensitivity, specificity, predictive values, and likelihood ratios. However, if the clinicians who interpret the test cannot agree on its interpretation and resulting typically dichotomous or binary diagnosis, the test results will be of little practical use. Such agreement between observers (interobserver agreement) about a dichotomous or binary variable is often reported as the kappa statistic. Assessing the interrater agreement between observers, in the case of ordinal variables and data, also has important biomedical applicability. Typically, this situation calls for use of the Cohen weighted kappa. Questionnaires, psychometric scales, and diagnostic tests are widespread and increasingly used by not only researchers but also clinicians in their daily practice. It is essential that these questionnaires, scales, and diagnostic tests have a high degree of agreement between observers. It is therefore vital that biomedical researchers and clinicians apply the appropriate statistical measures of agreement to assess the reproducibility and quality of these measurement instruments and decision-making processes.

Phantom Effects in Multilevel Compositional Analysis: Problems and Solutions

ERIC Educational Resources Information Center

Pokropek, Artur

2015-01-01

This article combines statistical and applied research perspective showing problems that might arise when measurement error in multilevel compositional effects analysis is ignored. This article focuses on data where independent variables are constructed measures. Simulation studies are conducted evaluating methods that could overcome the…

Median statistics estimates of Hubble and Newton's constants

NASA Astrophysics Data System (ADS)

Bethapudi, Suryarao; Desai, Shantanu

2017-02-01

Robustness of any statistics depends upon the number of assumptions it makes about the measured data. We point out the advantages of median statistics using toy numerical experiments and demonstrate its robustness, when the number of assumptions we can make about the data are limited. We then apply the median statistics technique to obtain estimates of two constants of nature, Hubble constant (H0) and Newton's gravitational constant ( G , both of which show significant differences between different measurements. For H0, we update the analyses done by Chen and Ratra (2011) and Gott et al. (2001) using 576 measurements. We find after grouping the different results according to their primary type of measurement, the median estimates are given by H0 = 72.5^{+2.5}_{-8} km/sec/Mpc with errors corresponding to 95% c.l. (2 σ) and G=6.674702^{+0.0014}_{-0.0009} × 10^{-11} Nm2kg-2 corresponding to 68% c.l. (1σ).

Development and Initial Validation of a Scale to Measure Instructors' Attitudes toward Concept-Based Teaching of Introductory Statistics in the Health and Behavioral Sciences

ERIC Educational Resources Information Center

Hassad, Rossi; Coxon, APM

2007-01-01

Despite more than a decade of reform efforts, students continue to experience difficulty understanding and applying statistical concepts. The predominant focus of reform has been on content, pedagogy, technology and assessment, with little attention to instructor characteristics. However, there is strong theoretical and empirical evidence that…

Accurate mass measurement: terminology and treatment of data.

PubMed

Brenton, A Gareth; Godfrey, A Ruth

2010-11-01

High-resolution mass spectrometry has become ever more accessible with improvements in instrumentation, such as modern FT-ICR and Orbitrap mass spectrometers. This has resulted in an increase in the number of articles submitted for publication quoting accurate mass data. There is a plethora of terms related to accurate mass analysis that are in current usage, many employed incorrectly or inconsistently. This article is based on a set of notes prepared by the authors for research students and staff in our laboratories as a guide to the correct terminology and basic statistical procedures to apply in relation to mass measurement, particularly for accurate mass measurement. It elaborates on the editorial by Gross in 1994 regarding the use of accurate masses for structure confirmation. We have presented and defined the main terms in use with reference to the International Union of Pure and Applied Chemistry (IUPAC) recommendations for nomenclature and symbolism for mass spectrometry. The correct use of statistics and treatment of data is illustrated as a guide to new and existing mass spectrometry users with a series of examples as well as statistical methods to compare different experimental methods and datasets. Copyright © 2010. Published by Elsevier Inc.

Quantifying the impact of between-study heterogeneity in multivariate meta-analyses

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2012-01-01

Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I2 statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to quantify heterogeneity in the multivariate setting is therefore raised. It is the univariate R2 statistic, the ratio of the variance of the estimated treatment effect under the random and fixed effects models, that generalises most naturally, so this statistic provides our basis. This statistic is then used to derive a multivariate analogue of I2, which we call . We also provide a multivariate H2 statistic, the ratio of a generalisation of Cochran's heterogeneity statistic and its associated degrees of freedom, with an accompanying generalisation of the usual I2 statistic, . Our proposed heterogeneity statistics can be used alongside all the usual estimates and inferential procedures used in multivariate meta-analysis. We apply our methods to some real datasets and show how our statistics are equally appropriate in the context of multivariate meta-regression, where study level covariate effects are included in the model. Our heterogeneity statistics may be used when applying any procedure for fitting the multivariate random effects model. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22763950

MRMC analysis of agreement studies

NASA Astrophysics Data System (ADS)

Gallas, Brandon D.; Anam, Amrita; Chen, Weijie; Wunderlich, Adam; Zhang, Zhiwei

2016-03-01

The purpose of this work is to present and evaluate methods based on U-statistics to compare intra- or inter-reader agreement across different imaging modalities. We apply these methods to multi-reader multi-case (MRMC) studies. We measure reader-averaged agreement and estimate its variance accounting for the variability from readers and cases (an MRMC analysis). In our application, pathologists (readers) evaluate patient tissue mounted on glass slides (cases) in two ways. They evaluate the slides on a microscope (reference modality) and they evaluate digital scans of the slides on a computer display (new modality). In the current work, we consider concordance as the agreement measure, but many of the concepts outlined here apply to other agreement measures. Concordance is the probability that two readers rank two cases in the same order. Concordance can be estimated with a U-statistic and thus it has some nice properties: it is unbiased, asymptotically normal, and its variance is given by an explicit formula. Another property of a U-statistic is that it is symmetric in its inputs; it doesn't matter which reader is listed first or which case is listed first, the result is the same. Using this property and a few tricks while building the U-statistic kernel for concordance, we get a mathematically tractable problem and efficient software. Simulations show that our variance and covariance estimates are unbiased.

SU-E-J-261: Statistical Analysis and Chaotic Dynamics of Respiratory Signal of Patients in BodyFix

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

Michalski, D; Huq, M; Bednarz, G

Purpose: To quantify respiratory signal of patients in BodyFix undergoing 4DCT scan with and without immobilization cover. Methods: 20 pairs of respiratory tracks recorded with RPM system during 4DCT scan were analyzed. Descriptive statistic was applied to selected parameters of exhale-inhale decomposition. Standardized signals were used with the delay method to build orbits in embedded space. Nonlinear behavior was tested with surrogate data. Sample entropy SE, Lempel-Ziv complexity LZC and the largest Lyapunov exponents LLE were compared. Results: Statistical tests show difference between scans for inspiration time and its variability, which is bigger for scans without cover. The same ismore » for variability of the end of exhalation and inhalation. Other parameters fail to show the difference. For both scans respiratory signals show determinism and nonlinear stationarity. Statistical test on surrogate data reveals their nonlinearity. LLEs show signals chaotic nature and its correlation with breathing period and its embedding delay time. SE, LZC and LLE measure respiratory signal complexity. Nonlinear characteristics do not differ between scans. Conclusion: Contrary to expectation cover applied to patients in BodyFix appears to have limited effect on signal parameters. Analysis based on trajectories of delay vectors shows respiratory system nonlinear character and its sensitive dependence on initial conditions. Reproducibility of respiratory signal can be evaluated with measures of signal complexity and its predictability window. Longer respiratory period is conducive for signal reproducibility as shown by these gauges. Statistical independence of the exhale and inhale times is also supported by the magnitude of LLE. The nonlinear parameters seem more appropriate to gauge respiratory signal complexity since its deterministic chaotic nature. It contrasts with measures based on harmonic analysis that are blind for nonlinear features. Dynamics of breathing, so crucial for 4D-based clinical technologies, can be better controlled if nonlinear-based methodology, which reflects respiration characteristic, is applied. Funding provided by Varian Medical Systems via Investigator Initiated Research Project.« less

Comment on Hall et al. (2017), "How to Choose Between Measures of Tinnitus Loudness for Clinical Research? A Report on the Reliability and Validity of an Investigator-Administered Test and a Patient-Reported Measure Using Baseline Data Collected in a Phase IIa Drug Trial".

PubMed

Sabour, Siamak

2018-03-08

The purpose of this letter, in response to Hall, Mehta, and Fackrell (2017), is to provide important knowledge about methodology and statistical issues in assessing the reliability and validity of an audiologist-administered tinnitus loudness matching test and a patient-reported tinnitus loudness rating. The author uses reference textbooks and published articles regarding scientific assessment of the validity and reliability of a clinical test to discuss the statistical test and the methodological approach in assessing validity and reliability in clinical research. Depending on the type of the variable (qualitative or quantitative), well-known statistical tests can be applied to assess reliability and validity. The qualitative variables of sensitivity, specificity, positive predictive value, negative predictive value, false positive and false negative rates, likelihood ratio positive and likelihood ratio negative, as well as odds ratio (i.e., ratio of true to false results), are the most appropriate estimates to evaluate validity of a test compared to a gold standard. In the case of quantitative variables, depending on distribution of the variable, Pearson r or Spearman rho can be applied. Diagnostic accuracy (validity) and diagnostic precision (reliability or agreement) are two completely different methodological issues. Depending on the type of the variable (qualitative or quantitative), well-known statistical tests can be applied to assess validity.

Summary goodness-of-fit statistics for binary generalized linear models with noncanonical link functions.

PubMed

Canary, Jana D; Blizzard, Leigh; Barry, Ronald P; Hosmer, David W; Quinn, Stephen J

2016-05-01

Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) . © 2015 John Wiley & Sons Ltd/London School of Economics.

Performance of Between-Study Heterogeneity Measures in the Cochrane Library.

PubMed

Ma, Xiaoyue; Lin, Lifeng; Qu, Zhiyong; Zhu, Motao; Chu, Haitao

2018-05-29

The growth in comparative effectiveness research and evidence-based medicine has increased attention to systematic reviews and meta-analyses. Meta-analysis synthesizes and contrasts evidence from multiple independent studies to improve statistical efficiency and reduce bias. Assessing heterogeneity is critical for performing a meta-analysis and interpreting results. As a widely used heterogeneity measure, the I statistic quantifies the proportion of total variation across studies that is due to real differences in effect size. The presence of outlying studies can seriously exaggerate the I statistic. Two alternative heterogeneity measures, the Ir and Im, have been recently proposed to reduce the impact of outlying studies. To evaluate these measures' performance empirically, we applied them to 20,599 meta-analyses in the Cochrane Library. We found that the Ir and Im have strong agreement with the I, while they are more robust than the I when outlying studies appear.

Analysis of Sensitivity Experiments - An Expanded Primer

DTIC Science & Technology

2017-03-08

diehard practitioners. The difficulty associated with mastering statistical inference presents a true dilemma. Statistics is an extremely applied...lost, perhaps forever. In other words, when on this safari, you need a guide. This report is designed to be a guide, of sorts. It focuses on analytical...estimated accurately if our analysis is to have real meaning. For this reason, the sensitivity test procedure is designed to concentrate measurements

A statistical assessment of zero-polarization catalogues

NASA Astrophysics Data System (ADS)

Clarke, D.; Naghizadeh-Khouei, J.; Simmons, J. F. L.; Stewart, B. G.

1993-03-01

The statistical behavior associated with polarization measurements is presented. The cumulative distribution function for measurements of unpolarized sources normalized by the measurement error is considered and Kolmogorov tests have been applied to data which might be considered as being representative of assemblies of unpolarized stars. Tinbergen's (1979, 1982) and Piirola's I (1977) catalogs have been examined and reveal shortcomings, the former indicating the presence of uncorrected instrumental polarization in part of the data and both suggesting that the quoted errors are in general slightly underestimated. Citings of these catalogs as providing evidence that middle-type stars in general exhibit weak intrinsic polarizations are shown to be invalid.

Minimal sufficient positive-operator valued measure on a separable Hilbert space

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

Kuramochi, Yui, E-mail: kuramochi.yui.22c@st.kyoto-u.ac.jp

We introduce a concept of a minimal sufficient positive-operator valued measure (POVM), which is the least redundant POVM among the POVMs that have the equivalent information about the measured quantum system. Assuming the system Hilbert space to be separable, we show that for a given POVM, a sufficient statistic called a Lehmann-Scheffé-Bahadur statistic induces a minimal sufficient POVM. We also show that every POVM has an equivalent minimal sufficient POVM and that such a minimal sufficient POVM is unique up to relabeling neglecting null sets. We apply these results to discrete POVMs and information conservation conditions proposed by the author.

A Monte Carlo–Based Bayesian Approach for Measuring Agreement in a Qualitative Scale

PubMed Central

Pérez Sánchez, Carlos Javier

2014-01-01

Agreement analysis has been an active research area whose techniques have been widely applied in psychology and other fields. However, statistical agreement among raters has been mainly considered from a classical statistics point of view. Bayesian methodology is a viable alternative that allows the inclusion of subjective initial information coming from expert opinions, personal judgments, or historical data. A Bayesian approach is proposed by providing a unified Monte Carlo–based framework to estimate all types of measures of agreement in a qualitative scale of response. The approach is conceptually simple and it has a low computational cost. Both informative and non-informative scenarios are considered. In case no initial information is available, the results are in line with the classical methodology, but providing more information on the measures of agreement. For the informative case, some guidelines are presented to elicitate the prior distribution. The approach has been applied to two applications related to schizophrenia diagnosis and sensory analysis. PMID:29881002

An Evaluation of Causal Modeling Applied to Educational Productivity in Mathematics.

ERIC Educational Resources Information Center

Harnisch, Delwyn L.; Dunbar, Stephen B.

To probe a psychological theory of educational productivity, background measures along with mathematics test scores and motivational measures of over 7,000 students (9-, 13- and 17-year olds from National Assessment of Educational Progress samples) were statistically related to each other and to indicators of constructs that prior research shows…

Reliability Estimation for Aggregated Data: Applications for Organizational Research.

ERIC Educational Resources Information Center

Hart, Roland J.; Bradshaw, Stephen C.

This report provides the statistical tools necessary to measure the extent of error that exists in organizational record data and group survey data. It is felt that traditional methods of measuring error are inappropriate or incomplete when applied to organizational groups, especially in studies of organizational change when the same variables are…

Challenge in Enhancing the Teaching and Learning of Variable Measurements in Quantitative Research

ERIC Educational Resources Information Center

Kee, Chang Peng; Osman, Kamisah; Ahmad, Fauziah

2013-01-01

Statistical analysis is one component that cannot be avoided in a quantitative research. Initial observations noted that students in higher education institution faced difficulty analysing quantitative data which were attributed to the confusions of various variable measurements. This paper aims to compare the outcomes of two approaches applied in…

[Evaluation of using statistical methods in selected national medical journals].

PubMed

Sych, Z

1996-01-01

The paper covers the performed evaluation of frequency with which the statistical methods were applied in analyzed works having been published in six selected, national medical journals in the years 1988-1992. For analysis the following journals were chosen, namely: Klinika Oczna, Medycyna Pracy, Pediatria Polska, Polski Tygodnik Lekarski, Roczniki Państwowego Zakładu Higieny, Zdrowie Publiczne. Appropriate number of works up to the average in the remaining medical journals was randomly selected from respective volumes of Pol. Tyg. Lek. The studies did not include works wherein the statistical analysis was not implemented, which referred both to national and international publications. That exemption was also extended to review papers, casuistic ones, reviews of books, handbooks, monographies, reports from scientific congresses, as well as papers on historical topics. The number of works was defined in each volume. Next, analysis was performed to establish the mode of finding out a suitable sample in respective studies, differentiating two categories: random and target selections. Attention was also paid to the presence of control sample in the individual works. In the analysis attention was also focussed on the existence of sample characteristics, setting up three categories: complete, partial and lacking. In evaluating the analyzed works an effort was made to present the results of studies in tables and figures (Tab. 1, 3). Analysis was accomplished with regard to the rate of employing statistical methods in analyzed works in relevant volumes of six selected, national medical journals for the years 1988-1992, simultaneously determining the number of works, in which no statistical methods were used. Concurrently the frequency of applying the individual statistical methods was analyzed in the scrutinized works. Prominence was given to fundamental statistical methods in the field of descriptive statistics (measures of position, measures of dispersion) as well as most important methods of mathematical statistics such as parametric tests of significance, analysis of variance (in single and dual classifications). non-parametric tests of significance, correlation and regression. The works, in which use was made of either multiple correlation or multiple regression or else more complex methods of studying the relationship for two or more numbers of variables, were incorporated into the works whose statistical methods were constituted by correlation and regression as well as other methods, e.g. statistical methods being used in epidemiology (coefficients of incidence and morbidity, standardization of coefficients, survival tables) factor analysis conducted by Jacobi-Hotellng's method, taxonomic methods and others. On the basis of the performed studies it has been established that the frequency of employing statistical methods in the six selected national, medical journals in the years 1988-1992 was 61.1-66.0% of the analyzed works (Tab. 3), and they generally were almost similar to the frequency provided in English language medical journals. On a whole, no significant differences were disclosed in the frequency of applied statistical methods (Tab. 4) as well as in frequency of random tests (Tab. 3) in the analyzed works, appearing in the medical journals in respective years 1988-1992. The most frequently used statistical methods in analyzed works for 1988-1992 were the measures of position 44.2-55.6% and measures of dispersion 32.5-38.5% as well as parametric tests of significance 26.3-33.1% of the works analyzed (Tab. 4). For the purpose of increasing the frequency and reliability of the used statistical methods, the didactics should be widened in the field of biostatistics at medical studies and postgraduation training designed for physicians and scientific-didactic workers.

Applications of spatial statistical network models to stream data

USGS Publications Warehouse

Isaak, Daniel J.; Peterson, Erin E.; Ver Hoef, Jay M.; Wenger, Seth J.; Falke, Jeffrey A.; Torgersen, Christian E.; Sowder, Colin; Steel, E. Ashley; Fortin, Marie-Josée; Jordan, Chris E.; Ruesch, Aaron S.; Som, Nicholas; Monestiez, Pascal

2014-01-01

Streams and rivers host a significant portion of Earth's biodiversity and provide important ecosystem services for human populations. Accurate information regarding the status and trends of stream resources is vital for their effective conservation and management. Most statistical techniques applied to data measured on stream networks were developed for terrestrial applications and are not optimized for streams. A new class of spatial statistical model, based on valid covariance structures for stream networks, can be used with many common types of stream data (e.g., water quality attributes, habitat conditions, biological surveys) through application of appropriate distributions (e.g., Gaussian, binomial, Poisson). The spatial statistical network models account for spatial autocorrelation (i.e., nonindependence) among measurements, which allows their application to databases with clustered measurement locations. Large amounts of stream data exist in many areas where spatial statistical analyses could be used to develop novel insights, improve predictions at unsampled sites, and aid in the design of efficient monitoring strategies at relatively low cost. We review the topic of spatial autocorrelation and its effects on statistical inference, demonstrate the use of spatial statistics with stream datasets relevant to common research and management questions, and discuss additional applications and development potential for spatial statistics on stream networks. Free software for implementing the spatial statistical network models has been developed that enables custom applications with many stream databases.

Methods in pharmacoepidemiology: a review of statistical analyses and data reporting in pediatric drug utilization studies.

PubMed

Sequi, Marco; Campi, Rita; Clavenna, Antonio; Bonati, Maurizio

2013-03-01

To evaluate the quality of data reporting and statistical methods performed in drug utilization studies in the pediatric population. Drug utilization studies evaluating all drug prescriptions to children and adolescents published between January 1994 and December 2011 were retrieved and analyzed. For each study, information on measures of exposure/consumption, the covariates considered, descriptive and inferential analyses, statistical tests, and methods of data reporting was extracted. An overall quality score was created for each study using a 12-item checklist that took into account the presence of outcome measures, covariates of measures, descriptive measures, statistical tests, and graphical representation. A total of 22 studies were reviewed and analyzed. Of these, 20 studies reported at least one descriptive measure. The mean was the most commonly used measure (18 studies), but only five of these also reported the standard deviation. Statistical analyses were performed in 12 studies, with the chi-square test being the most commonly performed test. Graphs were presented in 14 papers. Sixteen papers reported the number of drug prescriptions and/or packages, and ten reported the prevalence of the drug prescription. The mean quality score was 8 (median 9). Only seven of the 22 studies received a score of ≥10, while four studies received a score of <6. Our findings document that only a few of the studies reviewed applied statistical methods and reported data in a satisfactory manner. We therefore conclude that the methodology of drug utilization studies needs to be improved.

High-Throughput Assay Optimization and Statistical Interpolation of Rubella-Specific Neutralizing Antibody Titers

PubMed Central

Lambert, Nathaniel D.; Pankratz, V. Shane; Larrabee, Beth R.; Ogee-Nwankwo, Adaeze; Chen, Min-hsin; Icenogle, Joseph P.

2014-01-01

Rubella remains a social and economic burden due to the high incidence of congenital rubella syndrome (CRS) in some countries. For this reason, an accurate and efficient high-throughput measure of antibody response to vaccination is an important tool. In order to measure rubella-specific neutralizing antibodies in a large cohort of vaccinated individuals, a high-throughput immunocolorimetric system was developed. Statistical interpolation models were applied to the resulting titers to refine quantitative estimates of neutralizing antibody titers relative to the assayed neutralizing antibody dilutions. This assay, including the statistical methods developed, can be used to assess the neutralizing humoral immune response to rubella virus and may be adaptable for assessing the response to other viral vaccines and infectious agents. PMID:24391140

Mapping cell populations in flow cytometry data for cross‐sample comparison using the Friedman–Rafsky test statistic as a distance measure

PubMed Central

Hsiao, Chiaowen; Liu, Mengya; Stanton, Rick; McGee, Monnie; Qian, Yu

2015-01-01

Abstract Flow cytometry (FCM) is a fluorescence‐based single‐cell experimental technology that is routinely applied in biomedical research for identifying cellular biomarkers of normal physiological responses and abnormal disease states. While many computational methods have been developed that focus on identifying cell populations in individual FCM samples, very few have addressed how the identified cell populations can be matched across samples for comparative analysis. This article presents FlowMap‐FR, a novel method for cell population mapping across FCM samples. FlowMap‐FR is based on the Friedman–Rafsky nonparametric test statistic (FR statistic), which quantifies the equivalence of multivariate distributions. As applied to FCM data by FlowMap‐FR, the FR statistic objectively quantifies the similarity between cell populations based on the shapes, sizes, and positions of fluorescence data distributions in the multidimensional feature space. To test and evaluate the performance of FlowMap‐FR, we simulated the kinds of biological and technical sample variations that are commonly observed in FCM data. The results show that FlowMap‐FR is able to effectively identify equivalent cell populations between samples under scenarios of proportion differences and modest position shifts. As a statistical test, FlowMap‐FR can be used to determine whether the expression of a cellular marker is statistically different between two cell populations, suggesting candidates for new cellular phenotypes by providing an objective statistical measure. In addition, FlowMap‐FR can indicate situations in which inappropriate splitting or merging of cell populations has occurred during gating procedures. We compared the FR statistic with the symmetric version of Kullback–Leibler divergence measure used in a previous population matching method with both simulated and real data. The FR statistic outperforms the symmetric version of KL‐distance in distinguishing equivalent from nonequivalent cell populations. FlowMap‐FR was also employed as a distance metric to match cell populations delineated by manual gating across 30 FCM samples from a benchmark FlowCAP data set. An F‐measure of 0.88 was obtained, indicating high precision and recall of the FR‐based population matching results. FlowMap‐FR has been implemented as a standalone R/Bioconductor package so that it can be easily incorporated into current FCM data analytical workflows. © 2015 International Society for Advancement of Cytometry PMID:26274018

Mapping cell populations in flow cytometry data for cross-sample comparison using the Friedman-Rafsky test statistic as a distance measure.

PubMed

Hsiao, Chiaowen; Liu, Mengya; Stanton, Rick; McGee, Monnie; Qian, Yu; Scheuermann, Richard H

2016-01-01

Flow cytometry (FCM) is a fluorescence-based single-cell experimental technology that is routinely applied in biomedical research for identifying cellular biomarkers of normal physiological responses and abnormal disease states. While many computational methods have been developed that focus on identifying cell populations in individual FCM samples, very few have addressed how the identified cell populations can be matched across samples for comparative analysis. This article presents FlowMap-FR, a novel method for cell population mapping across FCM samples. FlowMap-FR is based on the Friedman-Rafsky nonparametric test statistic (FR statistic), which quantifies the equivalence of multivariate distributions. As applied to FCM data by FlowMap-FR, the FR statistic objectively quantifies the similarity between cell populations based on the shapes, sizes, and positions of fluorescence data distributions in the multidimensional feature space. To test and evaluate the performance of FlowMap-FR, we simulated the kinds of biological and technical sample variations that are commonly observed in FCM data. The results show that FlowMap-FR is able to effectively identify equivalent cell populations between samples under scenarios of proportion differences and modest position shifts. As a statistical test, FlowMap-FR can be used to determine whether the expression of a cellular marker is statistically different between two cell populations, suggesting candidates for new cellular phenotypes by providing an objective statistical measure. In addition, FlowMap-FR can indicate situations in which inappropriate splitting or merging of cell populations has occurred during gating procedures. We compared the FR statistic with the symmetric version of Kullback-Leibler divergence measure used in a previous population matching method with both simulated and real data. The FR statistic outperforms the symmetric version of KL-distance in distinguishing equivalent from nonequivalent cell populations. FlowMap-FR was also employed as a distance metric to match cell populations delineated by manual gating across 30 FCM samples from a benchmark FlowCAP data set. An F-measure of 0.88 was obtained, indicating high precision and recall of the FR-based population matching results. FlowMap-FR has been implemented as a standalone R/Bioconductor package so that it can be easily incorporated into current FCM data analytical workflows. © The Authors. Published by Wiley Periodicals, Inc. on behalf of ISAC.

The extension of total gain (TG) statistic in survival models: properties and applications.

PubMed

Choodari-Oskooei, Babak; Royston, Patrick; Parmar, Mahesh K B

2015-07-01

The results of multivariable regression models are usually summarized in the form of parameter estimates for the covariates, goodness-of-fit statistics, and the relevant p-values. These statistics do not inform us about whether covariate information will lead to any substantial improvement in prediction. Predictive ability measures can be used for this purpose since they provide important information about the practical significance of prognostic factors. R (2)-type indices are the most familiar forms of such measures in survival models, but they all have limitations and none is widely used. In this paper, we extend the total gain (TG) measure, proposed for a logistic regression model, to survival models and explore its properties using simulations and real data. TG is based on the binary regression quantile plot, otherwise known as the predictiveness curve. Standardised TG ranges from 0 (no explanatory power) to 1 ('perfect' explanatory power). The results of our simulations show that unlike many of the other R (2)-type predictive ability measures, TG is independent of random censoring. It increases as the effect of a covariate increases and can be applied to different types of survival models, including models with time-dependent covariate effects. We also apply TG to quantify the predictive ability of multivariable prognostic models developed in several disease areas. Overall, TG performs well in our simulation studies and can be recommended as a measure to quantify the predictive ability in survival models.

Experimental Investigations of Non-Stationary Properties In Radiometer Receivers Using Measurements of Multiple Calibration References

NASA Technical Reports Server (NTRS)

Racette, Paul; Lang, Roger; Zhang, Zhao-Nan; Zacharias, David; Krebs, Carolyn A. (Technical Monitor)

2002-01-01

Radiometers must be periodically calibrated because the receiver response fluctuates. Many techniques exist to correct for the time varying response of a radiometer receiver. An analytical technique has been developed that uses generalized least squares regression (LSR) to predict the performance of a wide variety of calibration algorithms. The total measurement uncertainty including the uncertainty of the calibration can be computed using LSR. The uncertainties of the calibration samples used in the regression are based upon treating the receiver fluctuations as non-stationary processes. Signals originating from the different sources of emission are treated as simultaneously existing random processes. Thus, the radiometer output is a series of samples obtained from these random processes. The samples are treated as random variables but because the underlying processes are non-stationary the statistics of the samples are treated as non-stationary. The statistics of the calibration samples depend upon the time for which the samples are to be applied. The statistics of the random variables are equated to the mean statistics of the non-stationary processes over the interval defined by the time of calibration sample and when it is applied. This analysis opens the opportunity for experimental investigation into the underlying properties of receiver non stationarity through the use of multiple calibration references. In this presentation we will discuss the application of LSR to the analysis of various calibration algorithms, requirements for experimental verification of the theory, and preliminary results from analyzing experiment measurements.

Global statistics of liquid water content and effective number concentration of water clouds over ocean derived from combined CALIPSO and MODIS measurements

NASA Astrophysics Data System (ADS)

Hu, Y.; Vaughan, M.; McClain, C.; Behrenfeld, M.; Maring, H.; Anderson, D.; Sun-Mack, S.; Flittner, D.; Huang, J.; Wielicki, B.; Minnis, P.; Weimer, C.; Trepte, C.; Kuehn, R.

2007-06-01

This study presents an empirical relation that links the volume extinction coefficients of water clouds, the layer integrated depolarization ratios measured by lidar, and the effective radii of water clouds derived from collocated passive sensor observations. Based on Monte Carlo simulations of CALIPSO lidar observations, this method combines the cloud effective radius reported by MODIS with the lidar depolarization ratios measured by CALIPSO to estimate both the liquid water content and the effective number concentration of water clouds. The method is applied to collocated CALIPSO and MODIS measurements obtained during July and October of 2006, and January 2007. Global statistics of the cloud liquid water content and effective number concentration are presented.

Control entropy identifies differential changes in complexity of walking and running gait patterns with increasing speed in highly trained runners

NASA Astrophysics Data System (ADS)

McGregor, Stephen J.; Busa, Michael A.; Skufca, Joseph; Yaggie, James A.; Bollt, Erik M.

2009-06-01

Regularity statistics have been previously applied to walking gait measures in the hope of gaining insight into the complexity of gait under different conditions and in different populations. Traditional regularity statistics are subject to the requirement of stationarity, a limitation for examining changes in complexity under dynamic conditions such as exhaustive exercise. Using a novel measure, control entropy (CE), applied to triaxial continuous accelerometry, we report changes in complexity of walking and running during increasing speeds up to exhaustion in highly trained runners. We further apply Karhunen-Loeve analysis in a new and novel way to the patterns of CE responses in each of the three axes to identify dominant modes of CE responses in the vertical, mediolateral, and anterior/posterior planes. The differential CE responses observed between the different axes in this select population provide insight into the constraints of walking and running in those who may have optimized locomotion. Future comparisons between athletes, healthy untrained, and clinical populations using this approach may help elucidate differences between optimized and diseased locomotor control.

Combining censored and uncensored data in a U-statistic: design and sample size implications for cell therapy research.

PubMed

Moyé, Lemuel A; Lai, Dejian; Jing, Kaiyan; Baraniuk, Mary Sarah; Kwak, Minjung; Penn, Marc S; Wu, Colon O

2011-01-01

The assumptions that anchor large clinical trials are rooted in smaller, Phase II studies. In addition to specifying the target population, intervention delivery, and patient follow-up duration, physician-scientists who design these Phase II studies must select the appropriate response variables (endpoints). However, endpoint measures can be problematic. If the endpoint assesses the change in a continuous measure over time, then the occurrence of an intervening significant clinical event (SCE), such as death, can preclude the follow-up measurement. Finally, the ideal continuous endpoint measurement may be contraindicated in a fraction of the study patients, a change that requires a less precise substitution in this subset of participants.A score function that is based on the U-statistic can address these issues of 1) intercurrent SCE's and 2) response variable ascertainments that use different measurements of different precision. The scoring statistic is easy to apply, clinically relevant, and provides flexibility for the investigators' prospective design decisions. Sample size and power formulations for this statistic are provided as functions of clinical event rates and effect size estimates that are easy for investigators to identify and discuss. Examples are provided from current cardiovascular cell therapy research.

Correlation and simple linear regression.

PubMed

Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G

2003-06-01

In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.

Sample Skewness as a Statistical Measurement of Neuronal Tuning Sharpness

PubMed Central

Samonds, Jason M.; Potetz, Brian R.; Lee, Tai Sing

2014-01-01

We propose using the statistical measurement of the sample skewness of the distribution of mean firing rates of a tuning curve to quantify sharpness of tuning. For some features, like binocular disparity, tuning curves are best described by relatively complex and sometimes diverse functions, making it difficult to quantify sharpness with a single function and parameter. Skewness provides a robust nonparametric measure of tuning curve sharpness that is invariant with respect to the mean and variance of the tuning curve and is straightforward to apply to a wide range of tuning, including simple orientation tuning curves and complex object tuning curves that often cannot even be described parametrically. Because skewness does not depend on a specific model or function of tuning, it is especially appealing to cases of sharpening where recurrent interactions among neurons produce sharper tuning curves that deviate in a complex manner from the feedforward function of tuning. Since tuning curves for all neurons are not typically well described by a single parametric function, this model independence additionally allows skewness to be applied to all recorded neurons, maximizing the statistical power of a set of data. We also compare skewness with other nonparametric measures of tuning curve sharpness and selectivity. Compared to these other nonparametric measures tested, skewness is best used for capturing the sharpness of multimodal tuning curves defined by narrow peaks (maximum) and broad valleys (minima). Finally, we provide a more formal definition of sharpness using a shape-based information gain measure and derive and show that skewness is correlated with this definition. PMID:24555451

A statistically derived index for classifying East Coast fever reactions in cattle challenged with Theileria parva under experimental conditions.

PubMed

Rowlands, G J; Musoke, A J; Morzaria, S P; Nagda, S M; Ballingall, K T; McKeever, D J

2000-04-01

A statistically derived disease reaction index based on parasitological, clinical and haematological measurements observed in 309 5 to 8-month-old Boran cattle following laboratory challenge with Theileria parva is described. Principal component analysis was applied to 13 measures including first appearance of schizonts, first appearance of piroplasms and first occurrence of pyrexia, together with the duration and severity of these symptoms, and white blood cell count. The first principal component, which was based on approximately equal contributions of the 13 variables, provided the definition for the disease reaction index, defined on a scale of 0-10. As well as providing a more objective measure of the severity of the reaction, the continuous nature of the index score enables more powerful statistical analysis of the data compared with that which has been previously possible through clinically derived categories of non-, mild, moderate and severe reactions.

BAYESIAN ESTIMATION OF THERMONUCLEAR REACTION RATES

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

Iliadis, C.; Anderson, K. S.; Coc, A.

The problem of estimating non-resonant astrophysical S -factors and thermonuclear reaction rates, based on measured nuclear cross sections, is of major interest for nuclear energy generation, neutrino physics, and element synthesis. Many different methods have been applied to this problem in the past, almost all of them based on traditional statistics. Bayesian methods, on the other hand, are now in widespread use in the physical sciences. In astronomy, for example, Bayesian statistics is applied to the observation of extrasolar planets, gravitational waves, and Type Ia supernovae. However, nuclear physics, in particular, has been slow to adopt Bayesian methods. We presentmore » astrophysical S -factors and reaction rates based on Bayesian statistics. We develop a framework that incorporates robust parameter estimation, systematic effects, and non-Gaussian uncertainties in a consistent manner. The method is applied to the reactions d(p, γ ){sup 3}He, {sup 3}He({sup 3}He,2p){sup 4}He, and {sup 3}He( α , γ ){sup 7}Be, important for deuterium burning, solar neutrinos, and Big Bang nucleosynthesis.« less

Regression modeling of ground-water flow

USGS Publications Warehouse

Cooley, R.L.; Naff, R.L.

1985-01-01

Nonlinear multiple regression methods are developed to model and analyze groundwater flow systems. Complete descriptions of regression methodology as applied to groundwater flow models allow scientists and engineers engaged in flow modeling to apply the methods to a wide range of problems. Organization of the text proceeds from an introduction that discusses the general topic of groundwater flow modeling, to a review of basic statistics necessary to properly apply regression techniques, and then to the main topic: exposition and use of linear and nonlinear regression to model groundwater flow. Statistical procedures are given to analyze and use the regression models. A number of exercises and answers are included to exercise the student on nearly all the methods that are presented for modeling and statistical analysis. Three computer programs implement the more complex methods. These three are a general two-dimensional, steady-state regression model for flow in an anisotropic, heterogeneous porous medium, a program to calculate a measure of model nonlinearity with respect to the regression parameters, and a program to analyze model errors in computed dependent variables such as hydraulic head. (USGS)

A phylogenetic transform enhances analysis of compositional microbiota data.

PubMed

Silverman, Justin D; Washburne, Alex D; Mukherjee, Sayan; David, Lawrence A

2017-02-15

Surveys of microbial communities (microbiota), typically measured as relative abundance of species, have illustrated the importance of these communities in human health and disease. Yet, statistical artifacts commonly plague the analysis of relative abundance data. Here, we introduce the PhILR transform, which incorporates microbial evolutionary models with the isometric log-ratio transform to allow off-the-shelf statistical tools to be safely applied to microbiota surveys. We demonstrate that analyses of community-level structure can be applied to PhILR transformed data with performance on benchmarks rivaling or surpassing standard tools. Additionally, by decomposing distance in the PhILR transformed space, we identified neighboring clades that may have adapted to distinct human body sites. Decomposing variance revealed that covariation of bacterial clades within human body sites increases with phylogenetic relatedness. Together, these findings illustrate how the PhILR transform combines statistical and phylogenetic models to overcome compositional data challenges and enable evolutionary insights relevant to microbial communities.

A statistical comparison of cirrus particle size distributions measured using the 2-D stereo probe during the TC4, SPARTICUS, and MACPEX flight campaigns with historical cirrus datasets

NASA Astrophysics Data System (ADS)

Schwartz, M. Christian

2017-08-01

This paper addresses two straightforward questions. First, how similar are the statistics of cirrus particle size distribution (PSD) datasets collected using the Two-Dimensional Stereo (2D-S) probe to cirrus PSD datasets collected using older Particle Measuring Systems (PMS) 2-D Cloud (2DC) and 2-D Precipitation (2DP) probes? Second, how similar are the datasets when shatter-correcting post-processing is applied to the 2DC datasets? To answer these questions, a database of measured and parameterized cirrus PSDs - constructed from measurements taken during the Small Particles in Cirrus (SPARTICUS); Mid-latitude Airborne Cirrus Properties Experiment (MACPEX); and Tropical Composition, Cloud, and Climate Coupling (TC4) flight campaigns - is used.Bulk cloud quantities are computed from the 2D-S database in three ways: first, directly from the 2D-S data; second, by applying the 2D-S data to ice PSD parameterizations developed using sets of cirrus measurements collected using the older PMS probes; and third, by applying the 2D-S data to a similar parameterization developed using the 2D-S data themselves. This is done so that measurements of the same cloud volumes by parameterized versions of the 2DC and 2D-S can be compared with one another. It is thereby seen - given the same cloud field and given the same assumptions concerning ice crystal cross-sectional area, density, and radar cross section - that the parameterized 2D-S and the parameterized 2DC predict similar distributions of inferred shortwave extinction coefficient, ice water content, and 94 GHz radar reflectivity. However, the parameterization of the 2DC based on uncorrected data predicts a statistically significantly higher number of total ice crystals and a larger ratio of small ice crystals to large ice crystals than does the parameterized 2D-S. The 2DC parameterization based on shatter-corrected data also predicts statistically different numbers of ice crystals than does the parameterized 2D-S, but the comparison between the two is nevertheless more favorable. It is concluded that the older datasets continue to be useful for scientific purposes, with certain caveats, and that continuing field investigations of cirrus with more modern probes is desirable.

Cosmic shear measurements with Dark Energy Survey Science Verification data

DOE PAGES

Becker, M. R.

2016-07-06

Here, we present measurements of weak gravitational lensing cosmic shear two-point statistics using Dark Energy Survey Science Verification data. We demonstrate that our results are robust to the choice of shear measurement pipeline, either ngmix or im3shape, and robust to the choice of two-point statistic, including both real and Fourier-space statistics. Our results pass a suite of null tests including tests for B-mode contamination and direct tests for any dependence of the two-point functions on a set of 16 observing conditions and galaxy properties, such as seeing, airmass, galaxy color, galaxy magnitude, etc. We use a large suite of simulationsmore » to compute the covariance matrix of the cosmic shear measurements and assign statistical significance to our null tests. We find that our covariance matrix is consistent with the halo model prediction, indicating that it has the appropriate level of halo sample variance. We also compare the same jackknife procedure applied to the data and the simulations in order to search for additional sources of noise not captured by the simulations. We find no statistically significant extra sources of noise in the data. The overall detection significance with tomography for our highest source density catalog is 9.7σ. Cosmological constraints from the measurements in this work are presented in a companion paper.« less

Fundamentals of Research Data and Variables: The Devil Is in the Details.

PubMed

Vetter, Thomas R

2017-10-01

Designing, conducting, analyzing, reporting, and interpreting the findings of a research study require an understanding of the types and characteristics of data and variables. Descriptive statistics are typically used simply to calculate, describe, and summarize the collected research data in a logical, meaningful, and efficient way. Inferential statistics allow researchers to make a valid estimate of the association between an intervention and the treatment effect in a specific population, based upon their randomly collected, representative sample data. Categorical data can be either dichotomous or polytomous. Dichotomous data have only 2 categories, and thus are considered binary. Polytomous data have more than 2 categories. Unlike dichotomous and polytomous data, ordinal data are rank ordered, typically based on a numerical scale that is comprised of a small set of discrete classes or integers. Continuous data are measured on a continuum and can have any numeric value over this continuous range. Continuous data can be meaningfully divided into smaller and smaller or finer and finer increments, depending upon the precision of the measurement instrument. Interval data are a form of continuous data in which equal intervals represent equal differences in the property being measured. Ratio data are another form of continuous data, which have the same properties as interval data, plus a true definition of an absolute zero point, and the ratios of the values on the measurement scale make sense. The normal (Gaussian) distribution ("bell-shaped curve") is of the most common statistical distributions. Many applied inferential statistical tests are predicated on the assumption that the analyzed data follow a normal distribution. The histogram and the Q-Q plot are 2 graphical methods to assess if a set of data have a normal distribution (display "normality"). The Shapiro-Wilk test and the Kolmogorov-Smirnov test are 2 well-known and historically widely applied quantitative methods to assess for data normality. Parametric statistical tests make certain assumptions about the characteristics and/or parameters of the underlying population distribution upon which the test is based, whereas nonparametric tests make fewer or less rigorous assumptions. If the normality test concludes that the study data deviate significantly from a Gaussian distribution, rather than applying a less robust nonparametric test, the problem can potentially be remedied by judiciously and openly: (1) performing a data transformation of all the data values; or (2) eliminating any obvious data outlier(s).

Modular Spectral Inference Framework Applied to Young Stars and Brown Dwarfs

NASA Technical Reports Server (NTRS)

Gully-Santiago, Michael A.; Marley, Mark S.

2017-01-01

In practice, synthetic spectral models are imperfect, causing inaccurate estimates of stellar parameters. Using forward modeling and statistical inference, we derive accurate stellar parameters for a given observed spectrum by emulating a grid of precomputed spectra to track uncertainties. Spectral inference as applied to brown dwarfs re: Synthetic spectral models (Marley et al 1996 and 2014) via the newest grid spans a massive multi-dimensional grid applied to IGRINS spectra, improving atmospheric models for JWST. When applied to young stars(10Myr) with large starpots, they can be measured spectroscopically, especially in the near-IR with IGRINS.

A Virtual Study of Grid Resolution on Experiments of a Highly-Resolved Turbulent Plume

NASA Astrophysics Data System (ADS)

Maisto, Pietro M. F.; Marshall, Andre W.; Gollner, Michael J.; Fire Protection Engineering Department Collaboration

2017-11-01

An accurate representation of sub-grid scale turbulent mixing is critical for modeling fire plumes and smoke transport. In this study, PLIF and PIV diagnostics are used with the saltwater modeling technique to provide highly-resolved instantaneous field measurements in unconfined turbulent plumes useful for statistical analysis, physical insight, and model validation. The effect of resolution was investigated employing a virtual interrogation window (of varying size) applied to the high-resolution field measurements. Motivated by LES low-pass filtering concepts, the high-resolution experimental data in this study can be analyzed within the interrogation windows (i.e. statistics at the sub-grid scale) and on interrogation windows (i.e. statistics at the resolved scale). A dimensionless resolution threshold (L/D*) criterion was determined to achieve converged statistics on the filtered measurements. Such a criterion was then used to establish the relative importance between large and small-scale turbulence phenomena while investigating specific scales for the turbulent flow. First order data sets start to collapse at a resolution of 0.3D*, while for second and higher order statistical moments the interrogation window size drops down to 0.2D*.

Neutron/Gamma-ray discrimination through measures of fit

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

Amiri, Moslem; Prenosil, Vaclav; Cvachovec, Frantisek

2015-07-01

Statistical tests and their underlying measures of fit can be utilized to separate neutron/gamma-ray pulses in a mixed radiation field. In this article, first the application of a sample statistical test is explained. Fit measurement-based methods require true pulse shapes to be used as reference for discrimination. This requirement makes practical implementation of these methods difficult; typically another discrimination approach should be employed to capture samples of neutrons and gamma-rays before running the fit-based technique. In this article, we also propose a technique to eliminate this requirement. These approaches are applied to several sets of mixed neutron and gamma-ray pulsesmore » obtained through different digitizers using stilbene scintillator in order to analyze them and measure their discrimination quality. (authors)« less

Application of Allan Deviation to Assessing Uncertainties of Continuous-measurement Instruments, and Optimizing Calibration Schemes

NASA Astrophysics Data System (ADS)

Jacobson, Gloria; Rella, Chris; Farinas, Alejandro

2014-05-01

Technological advancement of instrumentation in atmospheric and other geoscience disciplines over the past decade has lead to a shift from discrete sample analysis to continuous, in-situ monitoring. Standard error analysis used for discrete measurements is not sufficient to assess and compare the error contribution of noise and drift from continuous-measurement instruments, and a different statistical analysis approach should be applied. The Allan standard deviation analysis technique developed for atomic clock stability assessment by David W. Allan [1] can be effectively and gainfully applied to continuous measurement instruments. As an example, P. Werle et al has applied these techniques to look at signal averaging for atmospheric monitoring by Tunable Diode-Laser Absorption Spectroscopy (TDLAS) [2]. This presentation will build on, and translate prior foundational publications to provide contextual definitions and guidelines for the practical application of this analysis technique to continuous scientific measurements. The specific example of a Picarro G2401 Cavity Ringdown Spectroscopy (CRDS) analyzer used for continuous, atmospheric monitoring of CO2, CH4 and CO will be used to define the basics features the Allan deviation, assess factors affecting the analysis, and explore the time-series to Allan deviation plot translation for different types of instrument noise (white noise, linear drift, and interpolated data). In addition, the useful application of using an Allan deviation to optimize and predict the performance of different calibration schemes will be presented. Even though this presentation will use the specific example of the Picarro G2401 CRDS Analyzer for atmospheric monitoring, the objective is to present the information such that it can be successfully applied to other instrument sets and disciplines. [1] D.W. Allan, "Statistics of Atomic Frequency Standards," Proc, IEEE, vol. 54, pp 221-230, Feb 1966 [2] P. Werle, R. Miicke, F. Slemr, "The Limits of Signal Averaging in Atmospheric Trace-Gas Monitoring by Tunable Diode-Laser Absorption Spectroscopy (TDLAS)," Applied Physics, B57, pp 131-139, April 1993

Measurement of Hubble constant: non-Gaussian errors in HST Key Project data

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

Singh, Meghendra; Gupta, Shashikant; Pandey, Ashwini

2016-08-01

Assuming the Central Limit Theorem, experimental uncertainties in any data set are expected to follow the Gaussian distribution with zero mean. We propose an elegant method based on Kolmogorov-Smirnov statistic to test the above; and apply it on the measurement of Hubble constant which determines the expansion rate of the Universe. The measurements were made using Hubble Space Telescope. Our analysis shows that the uncertainties in the above measurement are non-Gaussian.

Statistically advanced, self-similar, radial probability density functions of atmospheric and under-expanded hydrogen jets

NASA Astrophysics Data System (ADS)

Ruggles, Adam J.

2015-11-01

This paper presents improved statistical insight regarding the self-similar scalar mixing process of atmospheric hydrogen jets and the downstream region of under-expanded hydrogen jets. Quantitative planar laser Rayleigh scattering imaging is used to probe both jets. The self-similarity of statistical moments up to the sixth order (beyond the literature established second order) is documented in both cases. This is achieved using a novel self-similar normalization method that facilitated a degree of statistical convergence that is typically limited to continuous, point-based measurements. This demonstrates that image-based measurements of a limited number of samples can be used for self-similar scalar mixing studies. Both jets exhibit the same radial trends of these moments demonstrating that advanced atmospheric self-similarity can be applied in the analysis of under-expanded jets. Self-similar histograms away from the centerline are shown to be the combination of two distributions. The first is attributed to turbulent mixing. The second, a symmetric Poisson-type distribution centered on zero mass fraction, progressively becomes the dominant and eventually sole distribution at the edge of the jet. This distribution is attributed to shot noise-affected pure air measurements, rather than a diffusive superlayer at the jet boundary. This conclusion is reached after a rigorous measurement uncertainty analysis and inspection of pure air data collected with each hydrogen data set. A threshold based upon the measurement noise analysis is used to separate the turbulent and pure air data, and thusly estimate intermittency. Beta-distributions (four parameters) are used to accurately represent the turbulent distribution moments. This combination of measured intermittency and four-parameter beta-distributions constitutes a new, simple approach to model scalar mixing. Comparisons between global moments from the data and moments calculated using the proposed model show excellent agreement. This was attributed to the high quality of the measurements which reduced the width of the correctly identified, noise-affected pure air distribution, with respect to the turbulent mixing distribution. The ignitability of the atmospheric jet is determined using the flammability factor calculated from both kernel density estimated (KDE) PDFs and PDFs generated using the newly proposed model. Agreement between contours from both approaches is excellent. Ignitability of the under-expanded jet is also calculated using KDE PDFs. Contours are compared with those calculated by applying the atmospheric model to the under-expanded jet. Once again, agreement is excellent. This work demonstrates that self-similar scalar mixing statistics and ignitability of atmospheric jets can be accurately described by the proposed model. This description can be applied with confidence to under-expanded jets, which are more realistic of leak and fuel injection scenarios.

3D shape recovery from image focus using gray level co-occurrence matrix

NASA Astrophysics Data System (ADS)

Mahmood, Fahad; Munir, Umair; Mehmood, Fahad; Iqbal, Javaid

2018-04-01

Recovering a precise and accurate 3-D shape of the target object utilizing robust 3-D shape recovery algorithm is an ultimate objective of computer vision community. Focus measure algorithm plays an important role in this architecture which convert the color values of each pixel of the acquired 2-D image dataset into corresponding focus values. After convolving the focus measure filter with the input 2-D image dataset, a 3-D shape recovery approach is applied which will recover the depth map. In this document, we are concerned with proposing Gray Level Co-occurrence Matrix along with its statistical features for computing the focus information of the image dataset. The Gray Level Co-occurrence Matrix quantifies the texture present in the image using statistical features and then applies joint probability distributive function of the gray level pairs of the input image. Finally, we quantify the focus value of the input image using Gaussian Mixture Model. Due to its little computational complexity, sharp focus measure curve, robust to random noise sources and accuracy, it is considered as superior alternative to most of recently proposed 3-D shape recovery approaches. This algorithm is deeply investigated on real image sequences and synthetic image dataset. The efficiency of the proposed scheme is also compared with the state of art 3-D shape recovery approaches. Finally, by means of two global statistical measures, root mean square error and correlation, we claim that this approach -in spite of simplicity generates accurate results.

Scaling of plane-wave functions in statistically optimized near-field acoustic holography.

PubMed

Hald, Jørgen

2014-11-01

Statistically Optimized Near-field Acoustic Holography (SONAH) is a Patch Holography method, meaning that it can be applied in cases where the measurement area covers only part of the source surface. The method performs projections directly in the spatial domain, avoiding the use of spatial discrete Fourier transforms and the associated errors. First, an inverse problem is solved using regularization. For each calculation point a multiplication must then be performed with two transfer vectors--one to get the sound pressure and the other to get the particle velocity. Considering SONAH based on sound pressure measurements, existing derivations consider only pressure reconstruction when setting up the inverse problem, so the evanescent wave amplification associated with the calculation of particle velocity is not taken into account in the regularized solution of the inverse problem. The present paper introduces a scaling of the applied plane wave functions that takes the amplification into account, and it is shown that the previously published virtual source-plane retraction has almost the same effect. The effectiveness of the different solutions is verified through a set of simulated measurements.

Magnetic Field-Vector Measurements in Quiescent Prominences via the Hanle Effect: Analysis of Prominences Observed at Pic-Du-Midi and at Sacramento Peak

NASA Technical Reports Server (NTRS)

Bommier, V.; Leroy, J. L.; Sahal-Brechot, S.

1985-01-01

The Hanle effect method for magnetic field vector diagnostics has now provided results on the magnetic field strength and direction in quiescent prominences, from linear polarization measurements in the He I E sub 3 line, performed at the Pic-du-Midi and at Sacramento Peak. However, there is an inescapable ambiguity in the field vector determination: each polarization measurement provides two field vector solutions symmetrical with respect to the line-of-sight. A statistical analysis capable of solving this ambiguity was applied to the large sample of prominences observed at the Pic-du-Midi (Leroy, et al., 1984); the same method of analysis applied to the prominences observed at Sacramento Peak (Athay, et al., 1983) provides results in agreement on the most probable magnetic structure of prominences; these results are detailed. The statistical results were confirmed on favorable individual cases: for 15 prominences observed at Pic-du-Midi, the two-field vectors are pointing on the same side of the prominence, and the alpha angles are large enough with respect to the measurements and interpretation inaccuracies, so that the field polarity is derived without any ambiguity.

Analysis of Statistical Methods Currently used in Toxicology Journals

PubMed Central

Na, Jihye; Yang, Hyeri

2014-01-01

Statistical methods are frequently used in toxicology, yet it is not clear whether the methods employed by the studies are used consistently and conducted based on sound statistical grounds. The purpose of this paper is to describe statistical methods used in top toxicology journals. More specifically, we sampled 30 papers published in 2014 from Toxicology and Applied Pharmacology, Archives of Toxicology, and Toxicological Science and described methodologies used to provide descriptive and inferential statistics. One hundred thirteen endpoints were observed in those 30 papers, and most studies had sample size less than 10, with the median and the mode being 6 and 3 & 6, respectively. Mean (105/113, 93%) was dominantly used to measure central tendency, and standard error of the mean (64/113, 57%) and standard deviation (39/113, 34%) were used to measure dispersion, while few studies provide justifications regarding why the methods being selected. Inferential statistics were frequently conducted (93/113, 82%), with one-way ANOVA being most popular (52/93, 56%), yet few studies conducted either normality or equal variance test. These results suggest that more consistent and appropriate use of statistical method is necessary which may enhance the role of toxicology in public health. PMID:25343012

Analysis of Statistical Methods Currently used in Toxicology Journals.

PubMed

Na, Jihye; Yang, Hyeri; Bae, SeungJin; Lim, Kyung-Min

2014-09-01

Statistical methods are frequently used in toxicology, yet it is not clear whether the methods employed by the studies are used consistently and conducted based on sound statistical grounds. The purpose of this paper is to describe statistical methods used in top toxicology journals. More specifically, we sampled 30 papers published in 2014 from Toxicology and Applied Pharmacology, Archives of Toxicology, and Toxicological Science and described methodologies used to provide descriptive and inferential statistics. One hundred thirteen endpoints were observed in those 30 papers, and most studies had sample size less than 10, with the median and the mode being 6 and 3 & 6, respectively. Mean (105/113, 93%) was dominantly used to measure central tendency, and standard error of the mean (64/113, 57%) and standard deviation (39/113, 34%) were used to measure dispersion, while few studies provide justifications regarding why the methods being selected. Inferential statistics were frequently conducted (93/113, 82%), with one-way ANOVA being most popular (52/93, 56%), yet few studies conducted either normality or equal variance test. These results suggest that more consistent and appropriate use of statistical method is necessary which may enhance the role of toxicology in public health.

RepExplore: addressing technical replicate variance in proteomics and metabolomics data analysis.

PubMed

Glaab, Enrico; Schneider, Reinhard

2015-07-01

High-throughput omics datasets often contain technical replicates included to account for technical sources of noise in the measurement process. Although summarizing these replicate measurements by using robust averages may help to reduce the influence of noise on downstream data analysis, the information on the variance across the replicate measurements is lost in the averaging process and therefore typically disregarded in subsequent statistical analyses.We introduce RepExplore, a web-service dedicated to exploit the information captured in the technical replicate variance to provide more reliable and informative differential expression and abundance statistics for omics datasets. The software builds on previously published statistical methods, which have been applied successfully to biomedical omics data but are difficult to use without prior experience in programming or scripting. RepExplore facilitates the analysis by providing a fully automated data processing and interactive ranking tables, whisker plot, heat map and principal component analysis visualizations to interpret omics data and derived statistics. Freely available at http://www.repexplore.tk enrico.glaab@uni.lu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

Development and evaluation of statistical shape modeling for principal inner organs on torso CT images.

PubMed

Zhou, Xiangrong; Xu, Rui; Hara, Takeshi; Hirano, Yasushi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Hoshi, Hiroaki; Kido, Shoji; Fujita, Hiroshi

2014-07-01

The shapes of the inner organs are important information for medical image analysis. Statistical shape modeling provides a way of quantifying and measuring shape variations of the inner organs in different patients. In this study, we developed a universal scheme that can be used for building the statistical shape models for different inner organs efficiently. This scheme combines the traditional point distribution modeling with a group-wise optimization method based on a measure called minimum description length to provide a practical means for 3D organ shape modeling. In experiments, the proposed scheme was applied to the building of five statistical shape models for hearts, livers, spleens, and right and left kidneys by use of 50 cases of 3D torso CT images. The performance of these models was evaluated by three measures: model compactness, model generalization, and model specificity. The experimental results showed that the constructed shape models have good "compactness" and satisfied the "generalization" performance for different organ shape representations; however, the "specificity" of these models should be improved in the future.

High order statistical signatures from source-driven measurements of subcritical fissile systems

NASA Astrophysics Data System (ADS)

Mattingly, John Kelly

1998-11-01

This research focuses on the development and application of high order statistical analyses applied to measurements performed with subcritical fissile systems driven by an introduced neutron source. The signatures presented are derived from counting statistics of the introduced source and radiation detectors that observe the response of the fissile system. It is demonstrated that successively higher order counting statistics possess progressively higher sensitivity to reactivity. Consequently, these signatures are more sensitive to changes in the composition, fissile mass, and configuration of the fissile assembly. Furthermore, it is shown that these techniques are capable of distinguishing the response of the fissile system to the introduced source from its response to any internal or inherent sources. This ability combined with the enhanced sensitivity of higher order signatures indicates that these techniques will be of significant utility in a variety of applications. Potential applications include enhanced radiation signature identification of weapons components for nuclear disarmament and safeguards applications and augmented nondestructive analysis of spent nuclear fuel. In general, these techniques expand present capabilities in the analysis of subcritical measurements.

Mapping the Energy Cascade in the North Atlantic Ocean: The Coarse-graining Approach

DOE PAGES

Aluie, Hussein; Hecht, Matthew; Vallis, Geoffrey K.

2017-11-14

A coarse-graining framework is implemented to analyze nonlinear processes, measure energy transfer rates and map out the energy pathways from simulated global ocean data. Traditional tools to measure the energy cascade from turbulence theory, such as spectral flux or spectral transfer rely on the assumption of statistical homogeneity, or at least a large separation between the scales of motion and the scales of statistical inhomogeneity. The coarse-graining framework allows for probing the fully nonlinear dynamics simultaneously in scale and in space, and is not restricted by those assumptions. This study describes how the framework can be applied to ocean flows.

A statistical dynamics approach to the study of human health data: Resolving population scale diurnal variation in laboratory data

NASA Astrophysics Data System (ADS)

Albers, D. J.; Hripcsak, George

2010-02-01

Statistical physics and information theory is applied to the clinical chemistry measurements present in a patient database containing 2.5 million patients' data over a 20-year period. Despite the seemingly naive approach of aggregating all patients over all times (with respect to particular clinical chemistry measurements), both a diurnal signal in the decay of the time-delayed mutual information and the presence of two sub-populations with differing health are detected. This provides a proof in principle that the highly fragmented data in electronic health records has potential for being useful in defining disease and human phenotypes.

Mapping the Energy Cascade in the North Atlantic Ocean: The Coarse-graining Approach

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

Aluie, Hussein; Hecht, Matthew; Vallis, Geoffrey K.

A coarse-graining framework is implemented to analyze nonlinear processes, measure energy transfer rates and map out the energy pathways from simulated global ocean data. Traditional tools to measure the energy cascade from turbulence theory, such as spectral flux or spectral transfer rely on the assumption of statistical homogeneity, or at least a large separation between the scales of motion and the scales of statistical inhomogeneity. The coarse-graining framework allows for probing the fully nonlinear dynamics simultaneously in scale and in space, and is not restricted by those assumptions. This study describes how the framework can be applied to ocean flows.

Relationship between cutoff frequency and accuracy in time-interval photon statistics applied to oscillating signals

NASA Astrophysics Data System (ADS)

Rebolledo, M. A.; Martinez-Betorz, J. A.

1989-04-01

In this paper the accuracy in the determination of the period of an oscillating signal, when obtained from the photon statistics time-interval probability, is studied as a function of the precision (the inverse of the cutoff frequency of the photon counting system) with which time intervals are measured. The results are obtained by means of an experiment with a square-wave signal, where the Fourier or square-wave transforms of the time-interval probability are measured. It is found that for values of the frequency of the signal near the cutoff frequency the errors in the period are small.

Mean phase coherence as a measure for phase synchronization and its application to the EEG of epilepsy patients

NASA Astrophysics Data System (ADS)

Mormann, Florian; Lehnertz, Klaus; David, Peter; E. Elger, Christian

2000-10-01

We apply the concept of phase synchronization of chaotic and/or noisy systems and the statistical distribution of the relative instantaneous phases to electroencephalograms (EEGs) recorded from patients with temporal lobe epilepsy. Using the mean phase coherence as a statistical measure for phase synchronization, we observe characteristic spatial and temporal shifts in synchronization that appear to be strongly related to pathological activity. In particular, we observe distinct differences in the degree of synchronization between recordings from seizure-free intervals and those before an impending seizure, indicating an altered state of brain dynamics prior to seizure activity.

A method for determining electrophoretic and electroosmotic mobilities using AC and DC electric field particle displacements.

PubMed

Oddy, M H; Santiago, J G

2004-01-01

We have developed a method for measuring the electrophoretic mobility of submicrometer, fluorescently labeled particles and the electroosmotic mobility of a microchannel. We derive explicit expressions for the unknown electrophoretic and the electroosmotic mobilities as a function of particle displacements resulting from alternating current (AC) and direct current (DC) applied electric fields. Images of particle displacements are captured using an epifluorescent microscope and a CCD camera. A custom image-processing code was developed to determine image streak lengths associated with AC measurements, and a custom particle tracking velocimetry (PTV) code was devised to determine DC particle displacements. Statistical analysis was applied to relate mobility estimates to measured particle displacement distributions.

"The Two Brothers": Reconciling Perceptual-Cognitive and Statistical Models of Musical Evolution.

PubMed

Jan, Steven

2018-01-01

While the "units, events and dynamics" of memetic evolution have been abstractly theorized (Lynch, 1998), they have not been applied systematically to real corpora in music. Some researchers, convinced of the validity of cultural evolution in more than the metaphorical sense adopted by much musicology, but perhaps skeptical of some or all of the claims of memetics, have attempted statistically based corpus-analysis techniques of music drawn from molecular biology, and these have offered strong evidence in favor of system-level change over time (Savage, 2017). This article argues that such statistical approaches, while illuminating, ignore the psychological realities of music-information grouping, the transmission of such groups with varying degrees of fidelity, their selection according to relative perceptual-cognitive salience, and the power of this Darwinian process to drive the systemic changes (such as the development over time of systems of tonal organization in music) that statistical methodologies measure. It asserts that a synthesis between such statistical approaches to the study of music-cultural change and the theory of memetics as applied to music (Jan, 2007), in particular the latter's perceptual-cognitive elements, would harness the strengths of each approach and deepen understanding of cultural evolution in music.

“The Two Brothers”: Reconciling Perceptual-Cognitive and Statistical Models of Musical Evolution

PubMed Central

Jan, Steven

2018-01-01

While the “units, events and dynamics” of memetic evolution have been abstractly theorized (Lynch, 1998), they have not been applied systematically to real corpora in music. Some researchers, convinced of the validity of cultural evolution in more than the metaphorical sense adopted by much musicology, but perhaps skeptical of some or all of the claims of memetics, have attempted statistically based corpus-analysis techniques of music drawn from molecular biology, and these have offered strong evidence in favor of system-level change over time (Savage, 2017). This article argues that such statistical approaches, while illuminating, ignore the psychological realities of music-information grouping, the transmission of such groups with varying degrees of fidelity, their selection according to relative perceptual-cognitive salience, and the power of this Darwinian process to drive the systemic changes (such as the development over time of systems of tonal organization in music) that statistical methodologies measure. It asserts that a synthesis between such statistical approaches to the study of music-cultural change and the theory of memetics as applied to music (Jan, 2007), in particular the latter's perceptual-cognitive elements, would harness the strengths of each approach and deepen understanding of cultural evolution in music. PMID:29670551

Cosmological Constraints from Galaxy Cluster Velocity Statistics

NASA Astrophysics Data System (ADS)

Bhattacharya, Suman; Kosowsky, Arthur

2007-04-01

Future microwave sky surveys will have the sensitivity to detect the kinematic Sunyaev-Zeldovich signal from moving galaxy clusters, thus providing a direct measurement of their line-of-sight peculiar velocity. We show that cluster peculiar velocity statistics applied to foreseeable surveys will put significant constraints on fundamental cosmological parameters. We consider three statistical quantities that can be constructed from a cluster peculiar velocity catalog: the probability density function, the mean pairwise streaming velocity, and the pairwise velocity dispersion. These quantities are applied to an envisioned data set that measures line-of-sight cluster velocities with normal errors of 100 km s-1 for all clusters with masses larger than 1014 Msolar over a sky area of up to 5000 deg2. A simple Fisher matrix analysis of this survey shows that the normalization of the matter power spectrum and the dark energy equation of state can be constrained to better than 10%, and that the Hubble constant and the primordial power spectrum index can be constrained to a few percent, independent of any other cosmological observations. We also find that the current constraint on the power spectrum normalization can be improved by more than a factor of 2 using data from a 400 deg2 survey and WMAP third-year priors. We also show how the constraints on cosmological parameters change if cluster velocities are measured with normal errors of 300 km s-1.

Blood pressure and heart rate response to posteriorly directed pressure applied to the cervical spine in young, pain-free individuals: a randomized, repeated-measures, double-blind, placebo-controlled study.

PubMed

Yung, Emmanuel; Wong, Michael; Williams, Haddie; Mache, Kyle

2014-08-01

Randomized clinical trial. Objectives To compare the blood pressure (BP) and heart rate (HR) response of healthy volunteers to posteriorly directed (anterior-to-posterior [AP]) pressure applied to the cervical spine versus placebo. Manual therapists employ cervical spine AP mobilizations for various cervical-shoulder pain conditions. However, there is a paucity of literature describing the procedure, cardiovascular response, and safety profile. Thirty-nine (25 female) healthy participants (mean ± SD age, 24.7 ± 1.9 years) were randomly assigned to 1 of 2 groups. Group 1 received a placebo, consisting of light touch applied to the right C6 costal process. Group 2 received AP pressure at the same location. Blood pressure and HR were measured prior to, during, and after the application of AP pressure. One-way analysis of variance and paired-difference statistics were used for data analysis. There was no statistically significant difference between groups for mean systolic BP, mean diastolic BP, and mean HR (P >.05) for all time points. Within-group comparisons indicated statistically significant differences between baseline and post-AP pressure HR (-2.8 bpm; 95% confidence interval: -4.6, -1.1) and between baseline and post-AP pressure systolic BP (-2.4 mmHg; 95% confidence interval: -3.7, -1.0) in the AP group, and between baseline and postplacebo systolic BP (-2.6 mmHg; 95% confidence interval: -4.2, -1.0) in the placebo group. No participants reported any adverse reactions or side effects within 24 hours of testing. AP pressure caused a statistically significant physiologic response that resulted in a minor drop in HR (without causing asystole or vasodepression) after the procedure, whereas this cardiovascular change did not occur for those in the placebo group. Within both groups, there was a small but statistically significant reduction in systolic BP following the procedure.

Could edaravone prevent gentamicin ototoxicity? An experimental study.

PubMed

Turan, M; Ciğer, E; Arslanoğlu, S; Börekci, H; Önal, K

2017-02-01

Clinical application of gentamicin may cause nephrotoxicity and ototoxicity. Our study is the first study to investigate the protective effects of edaravone against the gentamicin-induced ototoxicity. We investigated the protective effect of intraperitoneal (i.p.) edaravone application against gentamicin-induced ototoxicity in guinea pigs. Fourteen guinea pigs were divided into two equal groups consisting of a control group and a study group. One-hundred sixty milligrams per kilogram subcutaneous gentamicin and 0.3 mL i.p. saline were applied simultaneously once daily to seven guinea pigs in the control group (group 1). One-hundred sixty milligrams per kilogram gentamicin was applied subcutaneously and 3 mg/kg edaravone was applied intraperitoneally once daily for 7 days simultaneously to seven guinea pigs in the study group (group 2). Following the drug application, auditory brainstem response measurements were performed for the left ear on the 3rd and 7th days. Hearing threshold values of the group 1 and group 2 measured in the 3rd day of the study were detected as 57.14 ± 4.88 and 82.86 ± 7.56, respectively. This difference was statistically significant ( p < 0.05). Hearing threshold values of the group 1 and group 2 measured in the 7th day of the study were detected as 87.14 ± 4.88 and 62.86 ± 4.88, respectively. This difference was statistically significant ( p < 0.05). A statistically significant difference between the average threshold values of edaravone-administered group 2 and that of group 1 without edaravone was found. These differences show that systemic edaravone administration could diminish ototoxic effects of gentamicin and the severity of the hearing loss.

Estimating discharge measurement uncertainty using the interpolated variance estimator

USGS Publications Warehouse

Cohn, T.; Kiang, J.; Mason, R.

2012-01-01

Methods for quantifying the uncertainty in discharge measurements typically identify various sources of uncertainty and then estimate the uncertainty from each of these sources by applying the results of empirical or laboratory studies. If actual measurement conditions are not consistent with those encountered in the empirical or laboratory studies, these methods may give poor estimates of discharge uncertainty. This paper presents an alternative method for estimating discharge measurement uncertainty that uses statistical techniques and at-site observations. This Interpolated Variance Estimator (IVE) estimates uncertainty based on the data collected during the streamflow measurement and therefore reflects the conditions encountered at the site. The IVE has the additional advantage of capturing all sources of random uncertainty in the velocity and depth measurements. It can be applied to velocity-area discharge measurements that use a velocity meter to measure point velocities at multiple vertical sections in a channel cross section.

Expectation maximization for hard X-ray count modulation profiles

NASA Astrophysics Data System (ADS)

Benvenuto, F.; Schwartz, R.; Piana, M.; Massone, A. M.

2013-07-01

Context. This paper is concerned with the image reconstruction problem when the measured data are solar hard X-ray modulation profiles obtained from the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) instrument. Aims: Our goal is to demonstrate that a statistical iterative method classically applied to the image deconvolution problem is very effective when utilized to analyze count modulation profiles in solar hard X-ray imaging based on rotating modulation collimators. Methods: The algorithm described in this paper solves the maximum likelihood problem iteratively and encodes a positivity constraint into the iterative optimization scheme. The result is therefore a classical expectation maximization method this time applied not to an image deconvolution problem but to image reconstruction from count modulation profiles. The technical reason that makes our implementation particularly effective in this application is the use of a very reliable stopping rule which is able to regularize the solution providing, at the same time, a very satisfactory Cash-statistic (C-statistic). Results: The method is applied to both reproduce synthetic flaring configurations and reconstruct images from experimental data corresponding to three real events. In this second case, the performance of expectation maximization, when compared to Pixon image reconstruction, shows a comparable accuracy and a notably reduced computational burden; when compared to CLEAN, shows a better fidelity with respect to the measurements with a comparable computational effectiveness. Conclusions: If optimally stopped, expectation maximization represents a very reliable method for image reconstruction in the RHESSI context when count modulation profiles are used as input data.

Modeling stimulus variation in three common implicit attitude tasks.

PubMed

Wolsiefer, Katie; Westfall, Jacob; Judd, Charles M

2017-08-01

We explored the consequences of ignoring the sampling variation due to stimuli in the domain of implicit attitudes. A large literature in psycholinguistics has examined the statistical treatment of random stimulus materials, but the recommendations from this literature have not been applied to the social psychological literature on implicit attitudes. This is partly because of inherent complications in applying crossed random-effect models to some of the most common implicit attitude tasks, and partly because no work to date has demonstrated that random stimulus variation is in fact consequential in implicit attitude measurement. We addressed this problem by laying out statistically appropriate and practically feasible crossed random-effect models for three of the most commonly used implicit attitude measures-the Implicit Association Test, affect misattribution procedure, and evaluative priming task-and then applying these models to large datasets (average N = 3,206) that assess participants' implicit attitudes toward race, politics, and self-esteem. We showed that the test statistics from the traditional analyses are substantially (about 60 %) inflated relative to the more-appropriate analyses that incorporate stimulus variation. Because all three tasks used the same stimulus words and faces, we could also meaningfully compare the relative contributions of stimulus variation across the tasks. In an appendix, we give syntax in R, SAS, and SPSS for fitting the recommended crossed random-effects models to data from all three tasks, as well as instructions on how to structure the data file.

Statistical complexity measure of pseudorandom bit generators

NASA Astrophysics Data System (ADS)

González, C. M.; Larrondo, H. A.; Rosso, O. A.

2005-08-01

Pseudorandom number generators (PRNG) are extensively used in Monte Carlo simulations, gambling machines and cryptography as substitutes of ideal random number generators (RNG). Each application imposes different statistical requirements to PRNGs. As L’Ecuyer clearly states “the main goal for Monte Carlo methods is to reproduce the statistical properties on which these methods are based whereas for gambling machines and cryptology, observing the sequence of output values for some time should provide no practical advantage for predicting the forthcoming numbers better than by just guessing at random”. In accordance with different applications several statistical test suites have been developed to analyze the sequences generated by PRNGs. In a recent paper a new statistical complexity measure [Phys. Lett. A 311 (2003) 126] has been defined. Here we propose this measure, as a randomness quantifier of a PRNGs. The test is applied to three very well known and widely tested PRNGs available in the literature. All of them are based on mathematical algorithms. Another PRNGs based on Lorenz 3D chaotic dynamical system is also analyzed. PRNGs based on chaos may be considered as a model for physical noise sources and important new results are recently reported. All the design steps of this PRNG are described, and each stage increase the PRNG randomness using different strategies. It is shown that the MPR statistical complexity measure is capable to quantify this randomness improvement. The PRNG based on the chaotic 3D Lorenz dynamical system is also evaluated using traditional digital signal processing tools for comparison.

Risk Driven Outcome-Based Command and Control (C2) Assessment

DTIC Science & Technology

2000-01-01

shaping the risk ranking scores into more interpretable and statistically sound risk measures. Regression analysis was applied to determine what...Architecture Framework Implementation, AFCEA Coursebook 503J, February 8-11, 2000, San Diego, California. [Morgan and Henrion, 1990] M. Granger Morgan and

UVPROM dosimetry, microdosimetry and applications to SEU and extreme value theory

NASA Astrophysics Data System (ADS)

Scheick, Leif Zebediah

A new method is described for characterizing a device in terms of the statistical distribution of first failures. The method is based on the erasure of a commercial Ultra- Violet erasable Programmable Read Only Memory (UVPROM). The method of readout would be used on a spacecraft or in other restrictive radiation environments. The measurement of the charge remaining on the floating gate is used to determine absorbed dose. The method of determining dose does not require the detector to be destroyed or erased nor does it effect the ability for taking further measurements. This is compared to extreme value theory applied to the statistical distributions that apply to this device. This technique predicts the threshold of Single Event Effects (SEE), like anomalous changes in erasure time in programmable devices due to high microdose energy-deposition events. This technique also allows for advanced non-destructive, screening of a single microelectronic devices for predictable response in a stressful, i.e. radiation, environments.

Minkowski Tensors in Two Dimensions: Probing the Morphology and Isotropy of the Matter and Galaxy Density Fields

NASA Astrophysics Data System (ADS)

Appleby, Stephen; Chingangbam, Pravabati; Park, Changbom; Hong, Sungwook E.; Kim, Juhan; Ganesan, Vidhya

2018-05-01

We apply the Minkowski tensor statistics to two-dimensional slices of the three-dimensional matter density field. The Minkowski tensors are a set of functions that are sensitive to directionally dependent signals in the data and, furthermore, can be used to quantify the mean shape of density fields. We begin by reviewing the definition of Minkowski tensors and introducing a method of calculating them from a discretely sampled field. Focusing on the statistic {W}21,1—a 2 × 2 matrix—we calculate its value for both the entire excursion set and individual connected regions and holes within the set. To study the morphology of structures within the excursion set, we calculate the eigenvalues λ 1, λ 2 for the matrix {W}21,1 of each distinct connected region and hole and measure their mean shape using the ratio β \\equiv < {λ }2/{λ }1> . We compare both {W}21,1 and β for a Gaussian field and a smoothed density field generated from the latest Horizon Run 4 cosmological simulation to study the effect of gravitational collapse on these functions. The global statistic {W}21,1 is essentially independent of gravitational collapse, as the process maintains statistical isotropy. However, β is modified significantly, with overdensities becoming relatively more circular compared to underdensities at low redshifts. When applying the statistics to a redshift-space distorted density field, the matrix {W}21,1 is no longer proportional to the identity matrix, and measurements of its diagonal elements can be used to probe the large-scale velocity field.

A Backscatter-Lidar Forward-Operator

NASA Astrophysics Data System (ADS)

Geisinger, Armin; Behrendt, Andreas; Wulfmeyer, Volker; Vogel, Bernhard; Mattis, Ina; Flentje, Harald; Förstner, Jochen; Potthast, Roland

2015-04-01

We have developed a forward-operator which is capable of calculating virtual lidar profiles from atmospheric state simulations. The operator allows us to compare lidar measurements and model simulations based on the same measurement parameter: the lidar backscatter profile. This method simplifies qualitative comparisons and also makes quantitative comparisons possible, including statistical error quantification. Implemented into an aerosol-capable model system, the operator will act as a component to assimilate backscatter-lidar measurements. As many weather services maintain already networks of backscatter-lidars, such data are acquired already in an operational manner. To estimate and quantify errors due to missing or uncertain aerosol information, we started sensitivity studies about several scattering parameters such as the aerosol size and both the real and imaginary part of the complex index of refraction. Furthermore, quantitative and statistical comparisons between measurements and virtual measurements are shown in this study, i.e. applying the backscatter-lidar forward-operator on model output.

State Estimation Using Dependent Evidence Fusion: Application to Acoustic Resonance-Based Liquid Level Measurement.

PubMed

Xu, Xiaobin; Li, Zhenghui; Li, Guo; Zhou, Zhe

2017-04-21

Estimating the state of a dynamic system via noisy sensor measurement is a common problem in sensor methods and applications. Most state estimation methods assume that measurement noise and state perturbations can be modeled as random variables with known statistical properties. However in some practical applications, engineers can only get the range of noises, instead of the precise statistical distributions. Hence, in the framework of Dempster-Shafer (DS) evidence theory, a novel state estimatation method by fusing dependent evidence generated from state equation, observation equation and the actual observations of the system states considering bounded noises is presented. It can be iteratively implemented to provide state estimation values calculated from fusion results at every time step. Finally, the proposed method is applied to a low-frequency acoustic resonance level gauge to obtain high-accuracy measurement results.

Environmental statistics and optimal regulation

NASA Astrophysics Data System (ADS)

Sivak, David; Thomson, Matt

2015-03-01

The precision with which an organism can detect its environment, and the timescale for and statistics of environmental change, will affect the suitability of different strategies for regulating protein levels in response to environmental inputs. We propose a general framework--here applied to the enzymatic regulation of metabolism in response to changing nutrient concentrations--to predict the optimal regulatory strategy given the statistics of fluctuations in the environment and measurement apparatus, and the costs associated with enzyme production. We find: (i) relative convexity of enzyme expression cost and benefit influences the fitness of thresholding or graded responses; (ii) intermediate levels of measurement uncertainty call for a sophisticated Bayesian decision rule; and (iii) in dynamic contexts, intermediate levels of uncertainty call for retaining memory of the past. Statistical properties of the environment, such as variability and correlation times, set optimal biochemical parameters, such as thresholds and decay rates in signaling pathways. Our framework provides a theoretical basis for interpreting molecular signal processing algorithms and a classification scheme that organizes known regulatory strategies and may help conceptualize heretofore unknown ones.

A power comparison of generalized additive models and the spatial scan statistic in a case-control setting.

PubMed

Young, Robin L; Weinberg, Janice; Vieira, Verónica; Ozonoff, Al; Webster, Thomas F

2010-07-19

A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. The GAM permutation testing methods provide a regression-based alternative to the spatial scan statistic. Across all hypotheses examined in this research, the GAM methods had competing or greater power estimates and sensitivities exceeding that of the spatial scan statistic.

A power comparison of generalized additive models and the spatial scan statistic in a case-control setting

PubMed Central

2010-01-01

Background A common, important problem in spatial epidemiology is measuring and identifying variation in disease risk across a study region. In application of statistical methods, the problem has two parts. First, spatial variation in risk must be detected across the study region and, second, areas of increased or decreased risk must be correctly identified. The location of such areas may give clues to environmental sources of exposure and disease etiology. One statistical method applicable in spatial epidemiologic settings is a generalized additive model (GAM) which can be applied with a bivariate LOESS smoother to account for geographic location as a possible predictor of disease status. A natural hypothesis when applying this method is whether residential location of subjects is associated with the outcome, i.e. is the smoothing term necessary? Permutation tests are a reasonable hypothesis testing method and provide adequate power under a simple alternative hypothesis. These tests have yet to be compared to other spatial statistics. Results This research uses simulated point data generated under three alternative hypotheses to evaluate the properties of the permutation methods and compare them to the popular spatial scan statistic in a case-control setting. Case 1 was a single circular cluster centered in a circular study region. The spatial scan statistic had the highest power though the GAM method estimates did not fall far behind. Case 2 was a single point source located at the center of a circular cluster and Case 3 was a line source at the center of the horizontal axis of a square study region. Each had linearly decreasing logodds with distance from the point. The GAM methods outperformed the scan statistic in Cases 2 and 3. Comparing sensitivity, measured as the proportion of the exposure source correctly identified as high or low risk, the GAM methods outperformed the scan statistic in all three Cases. Conclusions The GAM permutation testing methods provide a regression-based alternative to the spatial scan statistic. Across all hypotheses examined in this research, the GAM methods had competing or greater power estimates and sensitivities exceeding that of the spatial scan statistic. PMID:20642827

Neural network approaches versus statistical methods in classification of multisource remote sensing data

NASA Technical Reports Server (NTRS)

Benediktsson, Jon A.; Swain, Philip H.; Ersoy, Okan K.

1990-01-01

Neural network learning procedures and statistical classificaiton methods are applied and compared empirically in classification of multisource remote sensing and geographic data. Statistical multisource classification by means of a method based on Bayesian classification theory is also investigated and modified. The modifications permit control of the influence of the data sources involved in the classification process. Reliability measures are introduced to rank the quality of the data sources. The data sources are then weighted according to these rankings in the statistical multisource classification. Four data sources are used in experiments: Landsat MSS data and three forms of topographic data (elevation, slope, and aspect). Experimental results show that two different approaches have unique advantages and disadvantages in this classification application.

Statistical methods for conducting agreement (comparison of clinical tests) and precision (repeatability or reproducibility) studies in optometry and ophthalmology.

PubMed

McAlinden, Colm; Khadka, Jyoti; Pesudovs, Konrad

2011-07-01

The ever-expanding choice of ocular metrology and imaging equipment has driven research into the validity of their measurements. Consequently, studies of the agreement between two instruments or clinical tests have proliferated in the ophthalmic literature. It is important that researchers apply the appropriate statistical tests in agreement studies. Correlation coefficients are hazardous and should be avoided. The 'limits of agreement' method originally proposed by Altman and Bland in 1983 is the statistical procedure of choice. Its step-by-step use and practical considerations in relation to optometry and ophthalmology are detailed in addition to sample size considerations and statistical approaches to precision (repeatability or reproducibility) estimates. Ophthalmic & Physiological Optics © 2011 The College of Optometrists.

Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning.

PubMed

Li, Chuan; Sánchez, René-Vinicio; Zurita, Grover; Cerrada, Mariela; Cabrera, Diego

2016-06-17

Fault diagnosis is important for the maintenance of rotating machinery. The detection of faults and fault patterns is a challenging part of machinery fault diagnosis. To tackle this problem, a model for deep statistical feature learning from vibration measurements of rotating machinery is presented in this paper. Vibration sensor signals collected from rotating mechanical systems are represented in the time, frequency, and time-frequency domains, each of which is then used to produce a statistical feature set. For learning statistical features, real-value Gaussian-Bernoulli restricted Boltzmann machines (GRBMs) are stacked to develop a Gaussian-Bernoulli deep Boltzmann machine (GDBM). The suggested approach is applied as a deep statistical feature learning tool for both gearbox and bearing systems. The fault classification performances in experiments using this approach are 95.17% for the gearbox, and 91.75% for the bearing system. The proposed approach is compared to such standard methods as a support vector machine, GRBM and a combination model. In experiments, the best fault classification rate was detected using the proposed model. The results show that deep learning with statistical feature extraction has an essential improvement potential for diagnosing rotating machinery faults.

Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning

PubMed Central

Li, Chuan; Sánchez, René-Vinicio; Zurita, Grover; Cerrada, Mariela; Cabrera, Diego

2016-01-01

Fault diagnosis is important for the maintenance of rotating machinery. The detection of faults and fault patterns is a challenging part of machinery fault diagnosis. To tackle this problem, a model for deep statistical feature learning from vibration measurements of rotating machinery is presented in this paper. Vibration sensor signals collected from rotating mechanical systems are represented in the time, frequency, and time-frequency domains, each of which is then used to produce a statistical feature set. For learning statistical features, real-value Gaussian-Bernoulli restricted Boltzmann machines (GRBMs) are stacked to develop a Gaussian-Bernoulli deep Boltzmann machine (GDBM). The suggested approach is applied as a deep statistical feature learning tool for both gearbox and bearing systems. The fault classification performances in experiments using this approach are 95.17% for the gearbox, and 91.75% for the bearing system. The proposed approach is compared to such standard methods as a support vector machine, GRBM and a combination model. In experiments, the best fault classification rate was detected using the proposed model. The results show that deep learning with statistical feature extraction has an essential improvement potential for diagnosing rotating machinery faults. PMID:27322273

Development of uncertainty-based work injury model using Bayesian structural equation modelling.

PubMed

Chatterjee, Snehamoy

2014-01-01

This paper proposed a Bayesian method-based structural equation model (SEM) of miners' work injury for an underground coal mine in India. The environmental and behavioural variables for work injury were identified and causal relationships were developed. For Bayesian modelling, prior distributions of SEM parameters are necessary to develop the model. In this paper, two approaches were adopted to obtain prior distribution for factor loading parameters and structural parameters of SEM. In the first approach, the prior distributions were considered as a fixed distribution function with specific parameter values, whereas, in the second approach, prior distributions of the parameters were generated from experts' opinions. The posterior distributions of these parameters were obtained by applying Bayesian rule. The Markov Chain Monte Carlo sampling in the form Gibbs sampling was applied for sampling from the posterior distribution. The results revealed that all coefficients of structural and measurement model parameters are statistically significant in experts' opinion-based priors, whereas, two coefficients are not statistically significant when fixed prior-based distributions are applied. The error statistics reveals that Bayesian structural model provides reasonably good fit of work injury with high coefficient of determination (0.91) and less mean squared error as compared to traditional SEM.

R2 effect-size measures for mediation analysis

PubMed Central

Fairchild, Amanda J.; MacKinnon, David P.; Taborga, Marcia P.; Taylor, Aaron B.

2010-01-01

R2 effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data. PMID:19363189

R2 effect-size measures for mediation analysis.

PubMed

Fairchild, Amanda J; Mackinnon, David P; Taborga, Marcia P; Taylor, Aaron B

2009-05-01

R(2) effect-size measures are presented to assess variance accounted for in mediation models. The measures offer a means to evaluate both component paths and the overall mediated effect in mediation models. Statistical simulation results indicate acceptable bias across varying parameter and sample-size combinations. The measures are applied to a real-world example using data from a team-based health promotion program to improve the nutrition and exercise habits of firefighters. SAS and SPSS computer code are also provided for researchers to compute the measures in their own data.

Secular Extragalactic Parallax and Geometric Distances with Gaia Proper Motions

NASA Astrophysics Data System (ADS)

Paine, Jennie; Darling, Jeremiah K.

2018-06-01

The motion of the Solar System with respect to the cosmic microwave background (CMB) rest frame creates a well measured dipole in the CMB, which corresponds to a linear solar velocity of about 78 AU/yr. This motion causes relatively nearby extragalactic objects to appear to move compared to more distant objects, an effect that can be measured in the proper motions of nearby galaxies. An object at 1 Mpc and perpendicular to the CMB apex will exhibit a secular parallax, observed as a proper motion, of 78 µas/yr. The relatively large peculiar motions of galaxies make the detection of secular parallax challenging for individual objects. Instead, a statistical parallax measurement can be made for a sample of objects with proper motions, where the global parallax signal is modeled as an E-mode dipole that diminishes linearly with distance. We present preliminary results of applying this model to a sample of nearby galaxies with Gaia proper motions to detect the statistical secular parallax signal. The statistical measurement can be used to calibrate the canonical cosmological “distance ladder.”

A random-sum Wilcoxon statistic and its application to analysis of ROC and LROC data.

PubMed

Tang, Liansheng Larry; Balakrishnan, N

2011-01-01

The Wilcoxon-Mann-Whitney statistic is commonly used for a distribution-free comparison of two groups. One requirement for its use is that the sample sizes of the two groups are fixed. This is violated in some of the applications such as medical imaging studies and diagnostic marker studies; in the former, the violation occurs since the number of correctly localized abnormal images is random, while in the latter the violation is due to some subjects not having observable measurements. For this reason, we propose here a random-sum Wilcoxon statistic for comparing two groups in the presence of ties, and derive its variance as well as its asymptotic distribution for large sample sizes. The proposed statistic includes the regular Wilcoxon rank-sum statistic. Finally, we apply the proposed statistic for summarizing location response operating characteristic data from a liver computed tomography study, and also for summarizing diagnostic accuracy of biomarker data.

Parameter estimation techniques based on optimizing goodness-of-fit statistics for structural reliability

NASA Technical Reports Server (NTRS)

Starlinger, Alois; Duffy, Stephen F.; Palko, Joseph L.

1993-01-01

New methods are presented that utilize the optimization of goodness-of-fit statistics in order to estimate Weibull parameters from failure data. It is assumed that the underlying population is characterized by a three-parameter Weibull distribution. Goodness-of-fit tests are based on the empirical distribution function (EDF). The EDF is a step function, calculated using failure data, and represents an approximation of the cumulative distribution function for the underlying population. Statistics (such as the Kolmogorov-Smirnov statistic and the Anderson-Darling statistic) measure the discrepancy between the EDF and the cumulative distribution function (CDF). These statistics are minimized with respect to the three Weibull parameters. Due to nonlinearities encountered in the minimization process, Powell's numerical optimization procedure is applied to obtain the optimum value of the EDF. Numerical examples show the applicability of these new estimation methods. The results are compared to the estimates obtained with Cooper's nonlinear regression algorithm.

Approximating Long-Term Statistics Early in the Global Precipitation Measurement Era

NASA Technical Reports Server (NTRS)

Stanley, Thomas; Kirschbaum, Dalia B.; Huffman, George J.; Adler, Robert F.

2017-01-01

Long-term precipitation records are vital to many applications, especially the study of extreme events. The Tropical Rainfall Measuring Mission (TRMM) has served this need, but TRMMs successor mission, Global Precipitation Measurement (GPM), does not yet provide a long-term record. Quantile mapping, the conversion of values across paired empirical distributions, offers a simple, established means to approximate such long-term statistics, but only within appropriately defined domains. This method was applied to a case study in Central America, demonstrating that quantile mapping between TRMM and GPM data maintains the performance of a real-time landslide model. Use of quantile mapping could bring the benefits of the latest satellite-based precipitation dataset to existing user communities such as those for hazard assessment, crop forecasting, numerical weather prediction, and disease tracking.

A comparison of high-frequency cross-correlation measures

NASA Astrophysics Data System (ADS)

Precup, Ovidiu V.; Iori, Giulia

2004-12-01

On a high-frequency scale the time series are not homogeneous, therefore standard correlation measures cannot be directly applied to the raw data. There are two ways to deal with this problem. The time series can be homogenised through an interpolation method (An Introduction to High-Frequency Finance, Academic Press, NY, 2001) (linear or previous tick) and then the Pearson correlation statistic computed. Recently, methods that can handle raw non-synchronous time series have been developed (Int. J. Theor. Appl. Finance 6(1) (2003) 87; J. Empirical Finance 4 (1997) 259). This paper compares two traditional methods that use interpolation with an alternative method applied directly to the actual time series.

Connecting optical and X-ray tracers of galaxy cluster relaxation

NASA Astrophysics Data System (ADS)

Roberts, Ian D.; Parker, Laura C.; Hlavacek-Larrondo, Julie

2018-04-01

Substantial effort has been devoted in determining the ideal proxy for quantifying the morphology of the hot intracluster medium in clusters of galaxies. These proxies, based on X-ray emission, typically require expensive, high-quality X-ray observations making them difficult to apply to large surveys of groups and clusters. Here, we compare optical relaxation proxies with X-ray asymmetries and centroid shifts for a sample of Sloan Digital Sky Survey clusters with high-quality, archival X-ray data from Chandra and XMM-Newton. The three optical relaxation measures considered are the shape of the member-galaxy projected velocity distribution - measured by the Anderson-Darling (AD) statistic, the stellar mass gap between the most-massive and second-most-massive cluster galaxy, and the offset between the most-massive galaxy (MMG) position and the luminosity-weighted cluster centre. The AD statistic and stellar mass gap correlate significantly with X-ray relaxation proxies, with the AD statistic being the stronger correlator. Conversely, we find no evidence for a correlation between X-ray asymmetry or centroid shift and the MMG offset. High-mass clusters (Mhalo > 1014.5 M⊙) in this sample have X-ray asymmetries, centroid shifts, and Anderson-Darling statistics which are systematically larger than for low-mass systems. Finally, considering the dichotomy of Gaussian and non-Gaussian clusters (measured by the AD test), we show that the probability of being a non-Gaussian cluster correlates significantly with X-ray asymmetry but only shows a marginal correlation with centroid shift. These results confirm the shape of the radial velocity distribution as a useful proxy for cluster relaxation, which can then be applied to large redshift surveys lacking extensive X-ray coverage.

A phylogenetic transform enhances analysis of compositional microbiota data

PubMed Central

Silverman, Justin D; Washburne, Alex D; Mukherjee, Sayan; David, Lawrence A

2017-01-01

Surveys of microbial communities (microbiota), typically measured as relative abundance of species, have illustrated the importance of these communities in human health and disease. Yet, statistical artifacts commonly plague the analysis of relative abundance data. Here, we introduce the PhILR transform, which incorporates microbial evolutionary models with the isometric log-ratio transform to allow off-the-shelf statistical tools to be safely applied to microbiota surveys. We demonstrate that analyses of community-level structure can be applied to PhILR transformed data with performance on benchmarks rivaling or surpassing standard tools. Additionally, by decomposing distance in the PhILR transformed space, we identified neighboring clades that may have adapted to distinct human body sites. Decomposing variance revealed that covariation of bacterial clades within human body sites increases with phylogenetic relatedness. Together, these findings illustrate how the PhILR transform combines statistical and phylogenetic models to overcome compositional data challenges and enable evolutionary insights relevant to microbial communities. DOI: http://dx.doi.org/10.7554/eLife.21887.001 PMID:28198697

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.

Comparing a single case to a control group - Applying linear mixed effects models to repeated measures data.

PubMed

Huber, Stefan; Klein, Elise; Moeller, Korbinian; Willmes, Klaus

2015-10-01

In neuropsychological research, single-cases are often compared with a small control sample. Crawford and colleagues developed inferential methods (i.e., the modified t-test) for such a research design. In the present article, we suggest an extension of the methods of Crawford and colleagues employing linear mixed models (LMM). We first show that a t-test for the significance of a dummy coded predictor variable in a linear regression is equivalent to the modified t-test of Crawford and colleagues. As an extension to this idea, we then generalized the modified t-test to repeated measures data by using LMMs to compare the performance difference in two conditions observed in a single participant to that of a small control group. The performance of LMMs regarding Type I error rates and statistical power were tested based on Monte-Carlo simulations. We found that starting with about 15-20 participants in the control sample Type I error rates were close to the nominal Type I error rate using the Satterthwaite approximation for the degrees of freedom. Moreover, statistical power was acceptable. Therefore, we conclude that LMMs can be applied successfully to statistically evaluate performance differences between a single-case and a control sample. Copyright © 2015 Elsevier Ltd. All rights reserved.

Probability distributions of molecular observables computed from Markov models. II. Uncertainties in observables and their time-evolution

NASA Astrophysics Data System (ADS)

Chodera, John D.; Noé, Frank

2010-09-01

Discrete-state Markov (or master equation) models provide a useful simplified representation for characterizing the long-time statistical evolution of biomolecules in a manner that allows direct comparison with experiments as well as the elucidation of mechanistic pathways for an inherently stochastic process. A vital part of meaningful comparison with experiment is the characterization of the statistical uncertainty in the predicted experimental measurement, which may take the form of an equilibrium measurement of some spectroscopic signal, the time-evolution of this signal following a perturbation, or the observation of some statistic (such as the correlation function) of the equilibrium dynamics of a single molecule. Without meaningful error bars (which arise from both approximation and statistical error), there is no way to determine whether the deviations between model and experiment are statistically meaningful. Previous work has demonstrated that a Bayesian method that enforces microscopic reversibility can be used to characterize the statistical component of correlated uncertainties in state-to-state transition probabilities (and functions thereof) for a model inferred from molecular simulation data. Here, we extend this approach to include the uncertainty in observables that are functions of molecular conformation (such as surrogate spectroscopic signals) characterizing each state, permitting the full statistical uncertainty in computed spectroscopic experiments to be assessed. We test the approach in a simple model system to demonstrate that the computed uncertainties provide a useful indicator of statistical variation, and then apply it to the computation of the fluorescence autocorrelation function measured for a dye-labeled peptide previously studied by both experiment and simulation.

Kolmogorov-Smirnov statistical test for analysis of ZAP-70 expression in B-CLL, compared with quantitative PCR and IgV(H) mutation status.

PubMed

Van Bockstaele, Femke; Janssens, Ann; Piette, Anne; Callewaert, Filip; Pede, Valerie; Offner, Fritz; Verhasselt, Bruno; Philippé, Jan

2006-07-15

ZAP-70 has been proposed as a surrogate marker for immunoglobulin heavy-chain variable region (IgV(H)) mutation status, which is known as a prognostic marker in B-cell chronic lymphocytic leukemia (CLL). The flow cytometric analysis of ZAP-70 suffers from difficulties in standardization and interpretation. We applied the Kolmogorov-Smirnov (KS) statistical test to make analysis more straightforward. We examined ZAP-70 expression by flow cytometry in 53 patients with CLL. Analysis was performed as initially described by Crespo et al. (New England J Med 2003; 348:1764-1775) and alternatively by application of the KS statistical test comparing T cells with B cells. Receiver-operating-characteristics (ROC)-curve analyses were performed to determine the optimal cut-off values for ZAP-70 measured by the two approaches. ZAP-70 protein expression was compared with ZAP-70 mRNA expression measured by a quantitative PCR (qPCR) and with the IgV(H) mutation status. Both flow cytometric analyses correlated well with the molecular technique and proved to be of equal value in predicting the IgV(H) mutation status. Applying the KS test is reproducible, simple, straightforward, and overcomes a number of difficulties encountered in the Crespo-method. The KS statistical test is an essential part of the software delivered with modern routine analytical flow cytometers and is well suited for analysis of ZAP-70 expression in CLL. (c) 2006 International Society for Analytical Cytology.

Inequality spectra

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2017-03-01

Inequality indices are widely applied in economics and in the social sciences as quantitative measures of the socioeconomic inequality of human societies. The application of inequality indices extends to size-distributions at large, where these indices can be used as general gauges of statistical heterogeneity. Moreover, as inequality indices are plentiful, arrays of such indices facilitate high-detail quantification of statistical heterogeneity. In this paper we elevate from arrays of inequality indices to inequality spectra: continuums of inequality indices that are parameterized by a single control parameter. We present a general methodology of constructing Lorenz-based inequality spectra, apply the general methodology to establish four sets of inequality spectra, investigate the properties of these sets, and show how these sets generalize known inequality gauges such as: the Gini index, the extended Gini index, the Rényi index, and hill curves.

Applying a Mixed Methods Framework to Differential Item Function Analyses

ERIC Educational Resources Information Center

Hitchcock, John H.; Johanson, George A.

2015-01-01

Understanding the reason(s) for Differential Item Functioning (DIF) in the context of measurement is difficult. Although identifying potential DIF items is typically a statistical endeavor, understanding the reasons for DIF (and item repair or replacement) might require investigations that can be informed by qualitative work. Such work is…

Educational Opportunity. The Concept, Its Measurement, and Application. Highlights. Sponsored Reports Series.

ERIC Educational Resources Information Center

National Center for Education Statistics (DHEW), Washington, DC.

Statistical indicators of inequality of educational opportunity developed through this study were applied to 1970 census information concerning school resources and revenues and pupil characteristics to assess the extent of inequality in elementary and secondary schools. Educational equality is defined as the prevailing view that all students…

Economic Psychology: Its Connections with Research-Oriented Courses

ERIC Educational Resources Information Center

Christopher, Andrew N.; Marek, Pam; Benigno, Joann

2003-01-01

To enhance student interest in research methods, tests and measurement, and statistics classes, we describe how teachers may use resources from economic psychology to illustrate key concepts in these courses. Because of their applied nature and relevance to student experiences, topics covered by these resources may capture student attention and…

24 CFR 570.506 - Records to be maintained.

Code of Federal Regulations, 2011 CFR

2011-04-01

... households (by gender of household head) have applied for, participated in, or benefited from, any program or... attain or maintain any particular statistical measure by race, ethnicity, or gender in covered programs... to all persons regardless of race, color, national origin, sex or handicap in operating units funded...

Robust hypothesis tests for detecting statistical evidence of two-dimensional and three-dimensional interactions in single-molecule measurements

NASA Astrophysics Data System (ADS)

Calderon, Christopher P.; Weiss, Lucien E.; Moerner, W. E.

2014-05-01

Experimental advances have improved the two- (2D) and three-dimensional (3D) spatial resolution that can be extracted from in vivo single-molecule measurements. This enables researchers to quantitatively infer the magnitude and directionality of forces experienced by biomolecules in their native environment. Situations where such force information is relevant range from mitosis to directed transport of protein cargo along cytoskeletal structures. Models commonly applied to quantify single-molecule dynamics assume that effective forces and velocity in the x ,y (or x ,y,z) directions are statistically independent, but this assumption is physically unrealistic in many situations. We present a hypothesis testing approach capable of determining if there is evidence of statistical dependence between positional coordinates in experimentally measured trajectories; if the hypothesis of independence between spatial coordinates is rejected, then a new model accounting for 2D (3D) interactions can and should be considered. Our hypothesis testing technique is robust, meaning it can detect interactions, even if the noise statistics are not well captured by the model. The approach is demonstrated on control simulations and on experimental data (directed transport of intraflagellar transport protein 88 homolog in the primary cilium).

Constructing networks with correlation maximization methods.

PubMed

Mellor, Joseph C; Wu, Jie; Delisi, Charles

2004-01-01

Problems of inference in systems biology are ideally reduced to formulations which can efficiently represent the features of interest. In the case of predicting gene regulation and pathway networks, an important feature which describes connected genes and proteins is the relationship between active and inactive forms, i.e. between the "on" and "off" states of the components. While not optimal at the limits of resolution, these logical relationships between discrete states can often yield good approximations of the behavior in larger complex systems, where exact representation of measurement relationships may be intractable. We explore techniques for extracting binary state variables from measurement of gene expression, and go on to describe robust measures for statistical significance and information that can be applied to many such types of data. We show how statistical strength and information are equivalent criteria in limiting cases, and demonstrate the application of these measures to simple systems of gene regulation.

Spectral Discrete Probability Density Function of Measured Wind Turbine Noise in the Far Field

PubMed Central

Ashtiani, Payam; Denison, Adelaide

2015-01-01

Of interest is the spectral character of wind turbine noise at typical residential set-back distances. In this paper, a spectral statistical analysis has been applied to immission measurements conducted at three locations. This method provides discrete probability density functions for the Turbine ONLY component of the measured noise. This analysis is completed for one-third octave sound levels, at integer wind speeds, and is compared to existing metrics for measuring acoustic comfort as well as previous discussions on low-frequency noise sources. PMID:25905097

Statistical Literacy among Applied Linguists and Second Language Acquisition Researchers

ERIC Educational Resources Information Center

Loewen, Shawn; Lavolette, Elizabeth; Spino, Le Anne; Papi, Mostafa; Schmidtke, Jens; Sterling, Scott; Wolff, Dominik

2014-01-01

The importance of statistical knowledge in applied linguistics and second language acquisition (SLA) research has been emphasized in recent publications. However, the last investigation of the statistical literacy of applied linguists occurred more than 25 years ago (Lazaraton, Riggenbach, & Ediger, 1987). The current study undertook a partial…

Determination of statistics for any rotation of axes of a bivariate normal elliptical distribution. [of wind vector components

NASA Technical Reports Server (NTRS)

Falls, L. W.; Crutcher, H. L.

1976-01-01

Transformation of statistics from a dimensional set to another dimensional set involves linear functions of the original set of statistics. Similarly, linear functions will transform statistics within a dimensional set such that the new statistics are relevant to a new set of coordinate axes. A restricted case of the latter is the rotation of axes in a coordinate system involving any two correlated random variables. A special case is the transformation for horizontal wind distributions. Wind statistics are usually provided in terms of wind speed and direction (measured clockwise from north) or in east-west and north-south components. A direct application of this technique allows the determination of appropriate wind statistics parallel and normal to any preselected flight path of a space vehicle. Among the constraints for launching space vehicles are critical values selected from the distribution of the expected winds parallel to and normal to the flight path. These procedures are applied to space vehicle launches at Cape Kennedy, Florida.

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.

Efficacy of transcutaneous electrical nerve stimulation (tens) for chronic low-back pain in a multiple sclerosis population: a randomized, placebo-controlled clinical trial.

PubMed

Warke, Kim; Al-Smadi, Jamal; Baxter, David; Walsh, Deirdre M; Lowe-Strong, Andrea S

2006-01-01

This study was designed to investigate the hypoalgesic effects of self-applied transcutaneous electrical nerve stimulation (TENS) on chronic low-back pain (LBP) in a multiple sclerosis (MS) population. Ninety participants with probable or definite MS (aged 21 to 78 y) presenting with chronic LBP were recruited and randomized into 3 groups (n=30 per group): (1) low-frequency TENS group (4 Hz, 200 micros); (2) high-frequency TENS group (110 Hz, 200 micros); and (3) placebo TENS. Participants self-applied TENS for 45 minutes, a minimum of twice daily, for 6 weeks. Outcome measures were recorded at weeks 1, 6, 10, and 32. Primary outcome measures included: Visual Analog Scale for average LBP and the McGill Pain Questionnaire. Secondary outcome measures included: Visual Analog Scale for worst and weekly LBP, back and leg spasm; Roland Morris Disability Questionnaire; Barthel Index; Rivermead Mobility Index; Multiple Sclerosis Quality of Life-54 Instrument, and a daily logbook. Data were analyzed blind using parametric and nonparametric tests, as appropriate. Results indicated a statistically significant interactive effect between groups for average LBP (P=0.008); 1-way analysis of covariance did not show any significant effects at any time point once a Bonferonni correction was applied (P>0.05). However, clinically important differences were observed in some of the outcome measures in both active treatment groups during the treatment and follow-up periods. Although not statistically significant, the observed effects may have implications for the clinical prescription and the use of TENS within this population.

Mining a clinical data warehouse to discover disease-finding associations using co-occurrence statistics.

PubMed

Cao, Hui; Markatou, Marianthi; Melton, Genevieve B; Chiang, Michael F; Hripcsak, George

2005-01-01

This paper applies co-occurrence statistics to discover disease-finding associations in a clinical data warehouse. We used two methods, chi2 statistics and the proportion confidence interval (PCI) method, to measure the dependence of pairs of diseases and findings, and then used heuristic cutoff values for association selection. An intrinsic evaluation showed that 94 percent of disease-finding associations obtained by chi2 statistics and 76.8 percent obtained by the PCI method were true associations. The selected associations were used to construct knowledge bases of disease-finding relations (KB-chi2, KB-PCI). An extrinsic evaluation showed that both KB-chi2 and KB-PCI could assist in eliminating clinically non-informative and redundant findings from problem lists generated by our automated problem list summarization system.

Anomaly detection of turbopump vibration in Space Shuttle Main Engine using statistics and neural networks

NASA Technical Reports Server (NTRS)

Lo, C. F.; Wu, K.; Whitehead, B. A.

1993-01-01

The statistical and neural networks methods have been applied to investigate the feasibility in detecting anomalies in turbopump vibration of SSME. The anomalies are detected based on the amplitude of peaks of fundamental and harmonic frequencies in the power spectral density. These data are reduced to the proper format from sensor data measured by strain gauges and accelerometers. Both methods are feasible to detect the vibration anomalies. The statistical method requires sufficient data points to establish a reasonable statistical distribution data bank. This method is applicable for on-line operation. The neural networks method also needs to have enough data basis to train the neural networks. The testing procedure can be utilized at any time so long as the characteristics of components remain unchanged.

Deciphering the Landauer-Büttiker Transmission Function from Single Molecule Break Junction Experiments

NASA Astrophysics Data System (ADS)

Reuter, Matthew; Tschudi, Stephen

When investigating the electrical response properties of molecules, experiments often measure conductance whereas computation predicts transmission probabilities. Although the Landauer-Büttiker theory relates the two in the limit of coherent scattering through the molecule, a direct comparison between experiment and computation can still be difficult. Experimental data (specifically that from break junctions) is statistical and computational results are deterministic. Many studies compare the most probable experimental conductance with computation, but such an analysis discards almost all of the experimental statistics. In this work we develop tools to decipher the Landauer-Büttiker transmission function directly from experimental statistics and then apply them to enable a fairer comparison between experimental and computational results.

Identification of structural damage using wavelet-based data classification

NASA Astrophysics Data System (ADS)

Koh, Bong-Hwan; Jeong, Min-Joong; Jung, Uk

2008-03-01

Predicted time-history responses from a finite-element (FE) model provide a baseline map where damage locations are clustered and classified by extracted damage-sensitive wavelet coefficients such as vertical energy threshold (VET) positions having large silhouette statistics. Likewise, the measured data from damaged structure are also decomposed and rearranged according to the most dominant positions of wavelet coefficients. Having projected the coefficients to the baseline map, the true localization of damage can be identified by investigating the level of closeness between the measurement and predictions. The statistical confidence of baseline map improves as the number of prediction cases increases. The simulation results of damage detection in a truss structure show that the approach proposed in this study can be successfully applied for locating structural damage even in the presence of a considerable amount of process and measurement noise.

Application of econometric and ecology analysis methods in physics software

NASA Astrophysics Data System (ADS)

Han, Min Cheol; Hoff, Gabriela; Kim, Chan Hyeong; Kim, Sung Hun; Grazia Pia, Maria; Ronchieri, Elisabetta; Saracco, Paolo

2017-10-01

Some data analysis methods typically used in econometric studies and in ecology have been evaluated and applied in physics software environments. They concern the evolution of observables through objective identification of change points and trends, and measurements of inequality, diversity and evenness across a data set. Within each analysis area, various statistical tests and measures have been examined. This conference paper summarizes a brief overview of some of these methods.

An Investigation into How Measures of Student Teacher Performance that Indicate Developmentally Informed Practice Are Related to a Measure of Overall Student Teaching Proficiency at a Private Northwest Comprehensive University

ERIC Educational Resources Information Center

Buchanan, Thomas D.

2011-01-01

Indicators of the proficiency of teacher candidates at applying knowledge of child development to teaching and learning were examined to see if they predict the overall success of the candidates full-time student teaching. The assessment instrument, the Full-Time Student Teaching Summary Report (FSTSR), was found statistically reliable and…

A new statistical method for characterizing the atmospheres of extrasolar planets

NASA Astrophysics Data System (ADS)

Henderson, Cassandra S.; Skemer, Andrew J.; Morley, Caroline V.; Fortney, Jonathan J.

2017-10-01

By detecting light from extrasolar planets, we can measure their compositions and bulk physical properties. The technologies used to make these measurements are still in their infancy, and a lack of self-consistency suggests that previous observations have underestimated their systemic errors. We demonstrate a statistical method, newly applied to exoplanet characterization, which uses a Bayesian formalism to account for underestimated errorbars. We use this method to compare photometry of a substellar companion, GJ 758b, with custom atmospheric models. Our method produces a probability distribution of atmospheric model parameters including temperature, gravity, cloud model (fsed) and chemical abundance for GJ 758b. This distribution is less sensitive to highly variant data and appropriately reflects a greater uncertainty on parameter fits.

Diagnosis of students' ability in a statistical course based on Rasch probabilistic outcome

NASA Astrophysics Data System (ADS)

Mahmud, Zamalia; Ramli, Wan Syahira Wan; Sapri, Shamsiah; Ahmad, Sanizah

2017-06-01

Measuring students' ability and performance are important in assessing how well students have learned and mastered the statistical courses. Any improvement in learning will depend on the student's approaches to learning, which are relevant to some factors of learning, namely assessment methods carrying out tasks consisting of quizzes, tests, assignment and final examination. This study has attempted an alternative approach to measure students' ability in an undergraduate statistical course based on the Rasch probabilistic model. Firstly, this study aims to explore the learning outcome patterns of students in a statistics course (Applied Probability and Statistics) based on an Entrance-Exit survey. This is followed by investigating students' perceived learning ability based on four Course Learning Outcomes (CLOs) and students' actual learning ability based on their final examination scores. Rasch analysis revealed that students perceived themselves as lacking the ability to understand about 95% of the statistics concepts at the beginning of the class but eventually they had a good understanding at the end of the 14 weeks class. In terms of students' performance in their final examination, their ability in understanding the topics varies at different probability values given the ability of the students and difficulty of the questions. Majority found the probability and counting rules topic to be the most difficult to learn.

Network Analysis with the Enron Email Corpus

ERIC Educational Resources Information Center

Hardin, J. S.; Sarkis, G.; URC, P. .

2015-01-01

We use the Enron email corpus to study relationships in a network by applying six different measures of centrality. Our results came out of an in-semester undergraduate research seminar. The Enron corpus is well suited to statistical analyses at all levels of undergraduate education. Through this article's focus on centrality, students can explore…

Mathematics Objectives and Measurement Specifications 1986-1990. Exit Level. Texas Educational Assessment of Minimum Skills (TEAMS).

ERIC Educational Resources Information Center

Texas Education Agency, Austin. Div. of Educational Assessment.

This document lists the objectives for the Texas educational assessment program in mathematics. Eighteen objectives for exit level mathematics are listed, by category: number concepts (4); computation (3); applied computation (5); statistical concepts (3); geometric concepts (2); and algebraic concepts (1). Then general specifications are listed…

Large-area forest inventory regression modeling: spatial scale considerations

Treesearch

James A. Westfall

2015-01-01

In many forest inventories, statistical models are employed to predict values for attributes that are difficult and/or time-consuming to measure. In some applications, models are applied across a large geographic area, which assumes the relationship between the response variable and predictors is ubiquitously invariable within the area. The extent to which this...

Outliers: A Potential Data Problem.

ERIC Educational Resources Information Center

Douzenis, Cordelia; Rakow, Ernest A.

Outliers, extreme data values relative to others in a sample, may distort statistics that assume internal levels of measurement and normal distribution. The outlier may be a valid value or an error. Several procedures are available for identifying outliers, and each may be applied to errors of prediction from the regression lines for utility in a…

Subject-enabled analytics model on measurement statistics in health risk expert system for public health informatics.

PubMed

Chung, Chi-Jung; Kuo, Yu-Chen; Hsieh, Yun-Yu; Li, Tsai-Chung; Lin, Cheng-Chieh; Liang, Wen-Miin; Liao, Li-Na; Li, Chia-Ing; Lin, Hsueh-Chun

2017-11-01

This study applied open source technology to establish a subject-enabled analytics model that can enhance measurement statistics of case studies with the public health data in cloud computing. The infrastructure of the proposed model comprises three domains: 1) the health measurement data warehouse (HMDW) for the case study repository, 2) the self-developed modules of online health risk information statistics (HRIStat) for cloud computing, and 3) the prototype of a Web-based process automation system in statistics (PASIS) for the health risk assessment of case studies with subject-enabled evaluation. The system design employed freeware including Java applications, MySQL, and R packages to drive a health risk expert system (HRES). In the design, the HRIStat modules enforce the typical analytics methods for biomedical statistics, and the PASIS interfaces enable process automation of the HRES for cloud computing. The Web-based model supports both modes, step-by-step analysis and auto-computing process, respectively for preliminary evaluation and real time computation. The proposed model was evaluated by computing prior researches in relation to the epidemiological measurement of diseases that were caused by either heavy metal exposures in the environment or clinical complications in hospital. The simulation validity was approved by the commercial statistics software. The model was installed in a stand-alone computer and in a cloud-server workstation to verify computing performance for a data amount of more than 230K sets. Both setups reached efficiency of about 10 5 sets per second. The Web-based PASIS interface can be used for cloud computing, and the HRIStat module can be flexibly expanded with advanced subjects for measurement statistics. The analytics procedure of the HRES prototype is capable of providing assessment criteria prior to estimating the potential risk to public health. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparison of temporal artery, mid-forehead skin and axillary temperature recordings in preterm infants <1500 g of birthweight.

PubMed

Duran, Ridvan; Vatansever, Ulfet; Acunaş, Betül; Süt, Necdet

2009-01-01

Preterm infants are prone to temperature maintenance problems due to immature thermoregulatory mechanism and relatively large body surface area. The objective of the present study was to evaluate the performance of a new non-invasive infrared thermometer applied to the mid-forehead and temporal artery in comparison with axillary temperature recordings by mercury-in-glass thermometer, and to determine the discomfort caused by these procedures in preterm infants on incubator care. The present comparative prospective study was composed of 34 preterm infants <1500 g of birthweight nursed in an incubator. Temperature recording from mid-forehead, temporal artery and axilla were recorded six times a day for 7 days since the end of the first week of life. For pain assessment, the premature infant pain profile (PIPP) was used. The mean mid-forehead, temporal artery and axillary temperatures were 36.72 +/- 0.08, 36.81 +/- 0.09 and 36.71 +/- 0.07 degrees C, respectively. No statistically significant difference was noted between the means of mid-forehead and axillary temperatures. The mean temporal artery temperature was statistically higher than the means of the mid-forehead and axillary temperatures. The PIPP scores of the mid-forehead, temporal artery and axillary temperature measurements were 5.07 +/- 0.36 degrees C, 5.18 +/- 0.43 degrees C and 7.59 +/- 0.84 degrees C, respectively. The mean PIPP score of axillary temperature measurements was statistically higher than the means of mid-forehead and temporal artery measurements. The infrared skin thermometer applied to the mid-forehead is a useful and valid device for easy and less painful measurement of skin temperature in preterm infants <1500 g of birthweight.

Robot Trajectories Comparison: A Statistical Approach

PubMed Central

Ansuategui, A.; Arruti, A.; Susperregi, L.; Yurramendi, Y.; Jauregi, E.; Lazkano, E.; Sierra, B.

2014-01-01

The task of planning a collision-free trajectory from a start to a goal position is fundamental for an autonomous mobile robot. Although path planning has been extensively investigated since the beginning of robotics, there is no agreement on how to measure the performance of a motion algorithm. This paper presents a new approach to perform robot trajectories comparison that could be applied to any kind of trajectories and in both simulated and real environments. Given an initial set of features, it automatically selects the most significant ones and performs a statistical comparison using them. Additionally, a graphical data visualization named polygraph which helps to better understand the obtained results is provided. The proposed method has been applied, as an example, to compare two different motion planners, FM2 and WaveFront, using different environments, robots, and local planners. PMID:25525618

Type Ia Supernova Intrinsic Magnitude Dispersion and the Fitting of Cosmological Parameters

NASA Astrophysics Data System (ADS)

Kim, A. G.

2011-02-01

I present an analysis for fitting cosmological parameters from a Hubble diagram of a standard candle with unknown intrinsic magnitude dispersion. The dispersion is determined from the data, simultaneously with the cosmological parameters. This contrasts with the strategies used to date. The advantages of the presented analysis are that it is done in a single fit (it is not iterative), it provides a statistically founded and unbiased estimate of the intrinsic dispersion, and its cosmological-parameter uncertainties account for the intrinsic-dispersion uncertainty. Applied to Type Ia supernovae, my strategy provides a statistical measure to test for subtypes and assess the significance of any magnitude corrections applied to the calibrated candle. Parameter bias and differences between likelihood distributions produced by the presented and currently used fitters are negligibly small for existing and projected supernova data sets.

Automatic summarization of changes in biological image sequences using algorithmic information theory.

PubMed

Cohen, Andrew R; Bjornsson, Christopher S; Temple, Sally; Banker, Gary; Roysam, Badrinath

2009-08-01

An algorithmic information-theoretic method is presented for object-level summarization of meaningful changes in image sequences. Object extraction and tracking data are represented as an attributed tracking graph (ATG). Time courses of object states are compared using an adaptive information distance measure, aided by a closed-form multidimensional quantization. The notion of meaningful summarization is captured by using the gap statistic to estimate the randomness deficiency from algorithmic statistics. The summary is the clustering result and feature subset that maximize the gap statistic. This approach was validated on four bioimaging applications: 1) It was applied to a synthetic data set containing two populations of cells differing in the rate of growth, for which it correctly identified the two populations and the single feature out of 23 that separated them; 2) it was applied to 59 movies of three types of neuroprosthetic devices being inserted in the brain tissue at three speeds each, for which it correctly identified insertion speed as the primary factor affecting tissue strain; 3) when applied to movies of cultured neural progenitor cells, it correctly distinguished neurons from progenitors without requiring the use of a fixative stain; and 4) when analyzing intracellular molecular transport in cultured neurons undergoing axon specification, it automatically confirmed the role of kinesins in axon specification.

Anomaly detection driven active learning for identifying suspicious tracks and events in WAMI video

NASA Astrophysics Data System (ADS)

Miller, David J.; Natraj, Aditya; Hockenbury, Ryler; Dunn, Katherine; Sheffler, Michael; Sullivan, Kevin

2012-06-01

We describe a comprehensive system for learning to identify suspicious vehicle tracks from wide-area motion (WAMI) video. First, since the road network for the scene of interest is assumed unknown, agglomerative hierarchical clustering is applied to all spatial vehicle measurements, resulting in spatial cells that largely capture individual road segments. Next, for each track, both at the cell (speed, acceleration, azimuth) and track (range, total distance, duration) levels, extreme value feature statistics are both computed and aggregated, to form summary (p-value based) anomaly statistics for each track. Here, to fairly evaluate tracks that travel across different numbers of spatial cells, for each cell-level feature type, a single (most extreme) statistic is chosen, over all cells traveled. Finally, a novel active learning paradigm, applied to a (logistic regression) track classifier, is invoked to learn to distinguish suspicious from merely anomalous tracks, starting from anomaly-ranked track prioritization, with ground-truth labeling by a human operator. This system has been applied to WAMI video data (ARGUS), with the tracks automatically extracted by a system developed in-house at Toyon Research Corporation. Our system gives promising preliminary results in highly ranking as suspicious aerial vehicles, dismounts, and traffic violators, and in learning which features are most indicative of suspicious tracks.

Local image statistics: maximum-entropy constructions and perceptual salience

PubMed Central

Victor, Jonathan D.; Conte, Mary M.

2012-01-01

The space of visual signals is high-dimensional and natural visual images have a highly complex statistical structure. While many studies suggest that only a limited number of image statistics are used for perceptual judgments, a full understanding of visual function requires analysis not only of the impact of individual image statistics, but also, how they interact. In natural images, these statistical elements (luminance distributions, correlations of low and high order, edges, occlusions, etc.) are intermixed, and their effects are difficult to disentangle. Thus, there is a need for construction of stimuli in which one or more statistical elements are introduced in a controlled fashion, so that their individual and joint contributions can be analyzed. With this as motivation, we present algorithms to construct synthetic images in which local image statistics—including luminance distributions, pair-wise correlations, and higher-order correlations—are explicitly specified and all other statistics are determined implicitly by maximum-entropy. We then apply this approach to measure the sensitivity of the human visual system to local image statistics and to sample their interactions. PMID:22751397

Towards the estimation of effect measures in studies using respondent-driven sampling.

PubMed

Rotondi, Michael A

2014-06-01

Respondent-driven sampling (RDS) is an increasingly common sampling technique to recruit hidden populations. Statistical methods for RDS are not straightforward due to the correlation between individual outcomes and subject weighting; thus, analyses are typically limited to estimation of population proportions. This manuscript applies the method of variance estimates recovery (MOVER) to construct confidence intervals for effect measures such as risk difference (difference of proportions) or relative risk in studies using RDS. To illustrate the approach, MOVER is used to construct confidence intervals for differences in the prevalence of demographic characteristics between an RDS study and convenience study of injection drug users. MOVER is then applied to obtain a confidence interval for the relative risk between education levels and HIV seropositivity and current infection with syphilis, respectively. This approach provides a simple method to construct confidence intervals for effect measures in RDS studies. Since it only relies on a proportion and appropriate confidence limits, it can also be applied to previously published manuscripts.

A Statistical Method for Reducing Sidelobe Clutter for the Ku-Band Precipitation Radar on Board the GPM Core Observatory

NASA Technical Reports Server (NTRS)

Kubota, Takuji; Iguchi, Toshio; Kojima, Masahiro; Liao, Liang; Masaki, Takeshi; Hanado, Hiroshi; Meneghini, Robert; Oki, Riko

2016-01-01

A statistical method to reduce the sidelobe clutter of the Ku-band precipitation radar (KuPR) of the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) Core Observatory is described and evaluated using DPR observations. The KuPR sidelobe clutter was much more severe than that of the Precipitation Radar on board the Tropical Rainfall Measuring Mission (TRMM), and it has caused the misidentification of precipitation. The statistical method to reduce sidelobe clutter was constructed by subtracting the estimated sidelobe power, based upon a multiple regression model with explanatory variables of the normalized radar cross section (NRCS) of surface, from the received power of the echo. The saturation of the NRCS at near-nadir angles, resulting from strong surface scattering, was considered in the calculation of the regression coefficients.The method was implemented in the KuPR algorithm and applied to KuPR-observed data. It was found that the received power from sidelobe clutter over the ocean was largely reduced by using the developed method, although some of the received power from the sidelobe clutter still remained. From the statistical results of the evaluations, it was shown that the number of KuPR precipitation events in the clutter region, after the method was applied, was comparable to that in the clutter-free region. This confirms the reasonable performance of the method in removing sidelobe clutter. For further improving the effectiveness of the method, it is necessary to improve the consideration of the NRCS saturation, which will be explored in future work.

Bayesian statistics and Monte Carlo methods

NASA Astrophysics Data System (ADS)

Koch, K. R.

2018-03-01

The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability. If the statements refer to the numerical values of variables, the so-called random variables, univariate and multivariate distributions follow. They lead to the point estimation by which unknown quantities, i.e. unknown parameters, are computed from measurements. The unknown parameters are random variables, they are fixed quantities in traditional statistics which is not founded on Bayes' theorem. Bayesian statistics therefore recommends itself for Monte Carlo methods, which generate random variates from given distributions. Monte Carlo methods, of course, can also be applied in traditional statistics. The unknown parameters, are introduced as functions of the measurements, and the Monte Carlo methods give the covariance matrix and the expectation of these functions. A confidence region is derived where the unknown parameters are situated with a given probability. Following a method of traditional statistics, hypotheses are tested by determining whether a value for an unknown parameter lies inside or outside the confidence region. The error propagation of a random vector by the Monte Carlo methods is presented as an application. If the random vector results from a nonlinearly transformed vector, its covariance matrix and its expectation follow from the Monte Carlo estimate. This saves a considerable amount of derivatives to be computed, and errors of the linearization are avoided. The Monte Carlo method is therefore efficient. If the functions of the measurements are given by a sum of two or more random vectors with different multivariate distributions, the resulting distribution is generally not known. TheMonte Carlo methods are then needed to obtain the covariance matrix and the expectation of the sum.

An intelligent system based on fuzzy probabilities for medical diagnosis– a study in aphasia diagnosis*

PubMed Central

Moshtagh-Khorasani, Majid; Akbarzadeh-T, Mohammad-R; Jahangiri, Nader; Khoobdel, Mehdi

2009-01-01

BACKGROUND: Aphasia diagnosis is particularly challenging due to the linguistic uncertainty and vagueness, inconsistencies in the definition of aphasic syndromes, large number of measurements with imprecision, natural diversity and subjectivity in test objects as well as in opinions of experts who diagnose the disease. METHODS: Fuzzy probability is proposed here as the basic framework for handling the uncertainties in medical diagnosis and particularly aphasia diagnosis. To efficiently construct this fuzzy probabilistic mapping, statistical analysis is performed that constructs input membership functions as well as determines an effective set of input features. RESULTS: Considering the high sensitivity of performance measures to different distribution of testing/training sets, a statistical t-test of significance is applied to compare fuzzy approach results with NN results as well as author's earlier work using fuzzy logic. The proposed fuzzy probability estimator approach clearly provides better diagnosis for both classes of data sets. Specifically, for the first and second type of fuzzy probability classifiers, i.e. spontaneous speech and comprehensive model, P-values are 2.24E-08 and 0.0059, respectively, strongly rejecting the null hypothesis. CONCLUSIONS: The technique is applied and compared on both comprehensive and spontaneous speech test data for diagnosis of four Aphasia types: Anomic, Broca, Global and Wernicke. Statistical analysis confirms that the proposed approach can significantly improve accuracy using fewer Aphasia features. PMID:21772867

Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

Direct Mask Overlay Inspection

NASA Astrophysics Data System (ADS)

Hsia, Liang-Choo; Su, Lo-Soun

1983-11-01

In this paper, we present a mask inspection methodology and procedure that involves direct X-Y measurements. A group of dice is selected for overlay measurement; four measurement targets were laid out in the kerf of each die. The measured coordinates are then fit-ted to either a "historical" grid, which reflects the individual tool bias, or to an ideal grid squares fashion. Measurements are done using a Nikon X-Y laser interferometric measurement system, which provides a reference grid. The stability of the measurement system is essential. We then apply appropriate statistics to the residual after the fit to determine the overlay performance. Statistical methods play an important role in the product disposition. The acceptance criterion is, however, a compromise between the cost for mask making and the final device yield. In order to satisfy the demand on mask houses for quality of masks and high volume, mixing lithographic tools in mask making has become more popular, in particular, mixing optical and E-beam tools. In this paper, we also discuss the inspection procedure for mixing different lithographic tools.

Difficulties in learning and teaching statistics: teacher views

NASA Astrophysics Data System (ADS)

Koparan, Timur

2015-01-01

The purpose of this study is to define teacher views about the difficulties in learning and teaching middle school statistics subjects. To serve this aim, a number of interviews were conducted with 10 middle school maths teachers in 2011-2012 school year in the province of Trabzon. Of the qualitative descriptive research methods, the semi-structured interview technique was applied in the research. In accordance with the aim, teacher opinions about the statistics subjects were examined and analysed. Similar responses from the teachers were grouped and evaluated. The teachers stated that it was positive that middle school statistics subjects were taught gradually in every grade but some difficulties were experienced in the teaching of this subject. The findings are presented in eight themes which are context, sample, data representation, central tendency and dispersion measure, probability, variance, and other difficulties.

Mining a clinical data warehouse to discover disease-finding associations using co-occurrence statistics

PubMed Central

Cao, Hui; Markatou, Marianthi; Melton, Genevieve B.; Chiang, Michael F.; Hripcsak, George

2005-01-01

This paper applies co-occurrence statistics to discover disease-finding associations in a clinical data warehouse. We used two methods, χ2 statistics and the proportion confidence interval (PCI) method, to measure the dependence of pairs of diseases and findings, and then used heuristic cutoff values for association selection. An intrinsic evaluation showed that 94 percent of disease-finding associations obtained by χ2 statistics and 76.8 percent obtained by the PCI method were true associations. The selected associations were used to construct knowledge bases of disease-finding relations (KB-χ2, KB-PCI). An extrinsic evaluation showed that both KB-χ2 and KB-PCI could assist in eliminating clinically non-informative and redundant findings from problem lists generated by our automated problem list summarization system. PMID:16779011

Estimating the Probability of Traditional Copying, Conditional on Answer-Copying Statistics.

PubMed

Allen, Jeff; Ghattas, Andrew

2016-06-01

Statistics for detecting copying on multiple-choice tests produce p values measuring the probability of a value at least as large as that observed, under the null hypothesis of no copying. The posterior probability of copying is arguably more relevant than the p value, but cannot be derived from Bayes' theorem unless the population probability of copying and probability distribution of the answer-copying statistic under copying are known. In this article, the authors develop an estimator for the posterior probability of copying that is based on estimable quantities and can be used with any answer-copying statistic. The performance of the estimator is evaluated via simulation, and the authors demonstrate how to apply the formula using actual data. Potential uses, generalizability to other types of cheating, and limitations of the approach are discussed.

Selected papers in the hydrologic sciences, 1986

USGS Publications Warehouse

Subitzky, Seymour

1987-01-01

Water-quality data from long-term (24 years), fixed- station monitoring at the Cape Fear River at Lock 1 near Kelly, N.C., and various measures of basin development are correlated. Subbasin population, number of acres of cropland in the subbasin, number of people employed in manufacturing, and tons of fertilizer applied in the basin are considered as measures of basinwide development activity. Linear correlations show statistically significant posi- tive relations between both population and manufacturing activity and most of the dissolved constituents considered. Negative correlations were found between the acres of harvested cropland and most of the water-quality measures. The amount of fertilizer sold in the subbasin was not statistically related to the water-quality measures considered in this report. The statistical analysis was limited to several commonly used measures of water quality including specific conductance, pH, dissolved solids, several major dissolved ions, and a few nutrients. The major dissolved ions included in the analysis were calcium, sodium, potassium, magnesium, chloride, sulfate, silica, bicarbonate, and fluoride. The nutrients included were dissolved nitrite plus nitrate nitrogen, dissolved ammonia nitrogen, total nitrogen, dissolved phosphates, and total phosphorus. For the chemicals evaluated, manufacturing and population sources are more closely associated with water quality in the Cape Fear River at Lock 1 than are agricultural variables.

Prediction of local concentration statistics in variably saturated soils: Influence of observation scale and comparison with field data

NASA Astrophysics Data System (ADS)

Graham, Wendy; Destouni, Georgia; Demmy, George; Foussereau, Xavier

1998-07-01

The methodology developed in Destouni and Graham [Destouni, G., Graham, W.D., 1997. The influence of observation method on local concentration statistics in the subsurface. Water Resour. Res. 33 (4) 663-676.] for predicting locally measured concentration statistics for solute transport in heterogeneous porous media under saturated flow conditions is applied to the prediction of conservative nonreactive solute transport in the vadose zone where observations are obtained by soil coring. Exact analytical solutions are developed for both the mean and variance of solute concentrations measured in discrete soil cores using a simplified physical model for vadose-zone flow and solute transport. Theoretical results show that while the ensemble mean concentration is relatively insensitive to the length-scale of the measurement, predictions of the concentration variance are significantly impacted by the sampling interval. Results also show that accounting for vertical heterogeneity in the soil profile results in significantly less spreading in the mean and variance of the measured solute breakthrough curves, indicating that it is important to account for vertical heterogeneity even for relatively small travel distances. Model predictions for both the mean and variance of locally measured solute concentration, based on independently estimated model parameters, agree well with data from a field tracer test conducted in Manatee County, Florida.

The polarization-optical measuring method of linearity of radiant-power characteristic of the laser emission photodetectors

NASA Astrophysics Data System (ADS)

Baranov, M. S.; Khramov, V. N.; Chebanenko, R. A.

2016-04-01

The method of measurement of the power (lux-ampere) characteristic of photodetectors for work with the continuous laser sources of light which radiation has the linear polarization is developed and realized. The way offered in this work is approved on the basis of the FD-24K widespread photo diode. The received results quite correspond to passport data of this kind of photodetectors. Methods of statistical processing of results are applied.

Statistical analysis and interpolation of compositional data in materials science.

PubMed

Pesenson, Misha Z; Suram, Santosh K; Gregoire, John M

2015-02-09

Compositional data are ubiquitous in chemistry and materials science: analysis of elements in multicomponent systems, combinatorial problems, etc., lead to data that are non-negative and sum to a constant (for example, atomic concentrations). The constant sum constraint restricts the sampling space to a simplex instead of the usual Euclidean space. Since statistical measures such as mean and standard deviation are defined for the Euclidean space, traditional correlation studies, multivariate analysis, and hypothesis testing may lead to erroneous dependencies and incorrect inferences when applied to compositional data. Furthermore, composition measurements that are used for data analytics may not include all of the elements contained in the material; that is, the measurements may be subcompositions of a higher-dimensional parent composition. Physically meaningful statistical analysis must yield results that are invariant under the number of composition elements, requiring the application of specialized statistical tools. We present specifics and subtleties of compositional data processing through discussion of illustrative examples. We introduce basic concepts, terminology, and methods required for the analysis of compositional data and utilize them for the spatial interpolation of composition in a sputtered thin film. The results demonstrate the importance of this mathematical framework for compositional data analysis (CDA) in the fields of materials science and chemistry.

Using basic statistics on the individual patient's own numeric data.

PubMed

Hart, John

2012-12-01

This theoretical report gives an example for how coefficient of variation (CV) and quartile analysis (QA) to assess outliers might be able to be used to analyze numeric data in practice for an individual patient. A patient was examined for 8 visits using infrared instrumentation for measurement of mastoid fossa temperature differential (MFTD) readings. The CV and QA were applied to the readings. The participant also completed the Short Form-12 health perception survey on each visit, and these findings were correlated with CV to determine if CV had outcomes support (clinical significance). An outlier MFTD reading was observed on the eighth visit according to QA that coincided with the largest CV value for the MFTDs. Correlations between the Short Form-12 and CV were low to negligible, positive, and statistically nonsignificant. This case provides an example of how basic statistical analyses could possibly be applied to numerical data in chiropractic practice for an individual patient. This might add objectivity to analyzing an individual patient's data in practice, particularly if clinical significance of a clinical numerical finding is unknown.

Quantitative Measures for Software Independent Verification and Validation

NASA Technical Reports Server (NTRS)

Lee, Alice

1996-01-01

As software is maintained or reused, it undergoes an evolution which tends to increase the overall complexity of the code. To understand the effects of this, we brought in statistics experts and leading researchers in software complexity, reliability, and their interrelationships. These experts' project has resulted in our ability to statistically correlate specific code complexity attributes, in orthogonal domains, to errors found over time in the HAL/S flight software which flies in the Space Shuttle. Although only a prototype-tools experiment, the result of this research appears to be extendable to all other NASA software, given appropriate data similar to that logged for the Shuttle onboard software. Our research has demonstrated that a more complete domain coverage can be mathematically demonstrated with the approach we have applied, thereby ensuring full insight into the cause-and-effects relationship between the complexity of a software system and the fault density of that system. By applying the operational profile we can characterize the dynamic effects of software path complexity under this same approach We now have the ability to measure specific attributes which have been statistically demonstrated to correlate to increased error probability, and to know which actions to take, for each complexity domain. Shuttle software verifiers can now monitor the changes in the software complexity, assess the added or decreased risk of software faults in modified code, and determine necessary corrections. The reports, tool documentation, user's guides, and new approach that have resulted from this research effort represent advances in the state of the art of software quality and reliability assurance. Details describing how to apply this technique to other NASA code are contained in this document.

Measurements of the driving forces of bio-motors using the fluctuation theorem

PubMed Central

Hayashi, Kumiko; Tanigawara, Mizue; Kishikawa, Jun-ichi

2012-01-01

The fluctuation theorem (FT), which is a recent achievement in non-equilibrium statistical mechanics, has been suggested to be useful for measuring the driving forces of motor proteins. As an example of this application, we performed single-molecule experiments on F1-ATPase, which is a rotary motor protein, in which we measured its rotary torque by taking advantage of FT. Because fluctuation is inherent nature in biological small systems and because FT is a non-destructive force measurement method using fluctuation, it will be applied to a wide range of biological small systems in future. PMID:27857609

PV cells electrical parameters measurement

NASA Astrophysics Data System (ADS)

Cibira, Gabriel

2017-12-01

When measuring optical parameters of a photovoltaic silicon cell, precise results bring good electrical parameters estimation, applying well-known physical-mathematical models. Nevertheless, considerable re-combination phenomena might occur in both surface and intrinsic thin layers within novel materials. Moreover, rear contact surface parameters may influence close-area re-combination phenomena, too. Therefore, the only precise electrical measurement approach is to prove assumed cell electrical parameters. Based on theoretical approach with respect to experiments, this paper analyses problems within measurement procedures and equipment used for electrical parameters acquisition within a photovoltaic silicon cell, as a case study. Statistical appraisal quality is contributed.

Estimation of road profile variability from measured vehicle responses

NASA Astrophysics Data System (ADS)

Fauriat, W.; Mattrand, C.; Gayton, N.; Beakou, A.; Cembrzynski, T.

2016-05-01

When assessing the statistical variability of fatigue loads acting throughout the life of a vehicle, the question of the variability of road roughness naturally arises, as both quantities are strongly related. For car manufacturers, gathering information on the environment in which vehicles evolve is a long and costly but necessary process to adapt their products to durability requirements. In the present paper, a data processing algorithm is proposed in order to estimate the road profiles covered by a given vehicle, from the dynamic responses measured on this vehicle. The algorithm based on Kalman filtering theory aims at solving a so-called inverse problem, in a stochastic framework. It is validated using experimental data obtained from simulations and real measurements. The proposed method is subsequently applied to extract valuable statistical information on road roughness from an existing load characterisation campaign carried out by Renault within one of its markets.

Applying Rasch model analysis in the development of the cantonese tone identification test (CANTIT).

PubMed

Lee, Kathy Y S; Lam, Joffee H S; Chan, Kit T Y; van Hasselt, Charles Andrew; Tong, Michael C F

2017-01-01

Applying Rasch analysis to evaluate the internal structure of a lexical tone perception test known as the Cantonese Tone Identification Test (CANTIT). A 75-item pool (CANTIT-75) with pictures and sound tracks was developed. Respondents were required to make a four-alternative forced choice on each item. A short version of 30 items (CANTIT-30) was developed based on fit statistics, difficulty estimates, and content evaluation. Internal structure was evaluated by fit statistics and Rasch Factor Analysis (RFA). 200 children with normal hearing and 141 children with hearing impairment were recruited. For CANTIT-75, all infit and 97% of outfit values were < 2.0. RFA revealed 40.1% of total variance was explained by the Rasch measure. The first residual component explained 2.5% of total variance in an eigenvalue of 3.1. For CANTIT-30, all infit and outfit values were < 2.0. The Rasch measure explained 38.8% of total variance, the first residual component explained 3.9% of total variance in an eigenvalue of 1.9. The Rasch model provides excellent guidance for the development of short forms. Both CANTIT-75 and CANTIT-30 possess satisfactory internal structure as a construct validity evidence in measuring the lexical tone identification ability of the Cantonese speakers.

A measure of the signal-to-noise ratio of microarray samples and studies using gene correlations.

PubMed

Venet, David; Detours, Vincent; Bersini, Hugues

2012-01-01

The quality of gene expression data can vary dramatically from platform to platform, study to study, and sample to sample. As reliable statistical analysis rests on reliable data, determining such quality is of the utmost importance. Quality measures to spot problematic samples exist, but they are platform-specific, and cannot be used to compare studies. As a proxy for quality, we propose a signal-to-noise ratio for microarray data, the "Signal-to-Noise Applied to Gene Expression Experiments", or SNAGEE. SNAGEE is based on the consistency of gene-gene correlations. We applied SNAGEE to a compendium of 80 large datasets on 37 platforms, for a total of 24,380 samples, and assessed the signal-to-noise ratio of studies and samples. This allowed us to discover serious issues with three studies. We show that signal-to-noise ratios of both studies and samples are linked to the statistical significance of the biological results. We showed that SNAGEE is an effective way to measure data quality for most types of gene expression studies, and that it often outperforms existing techniques. Furthermore, SNAGEE is platform-independent and does not require raw data files. The SNAGEE R package is available in BioConductor.

Concentration of Calcium, Phosphate and Fluoride Ions in Microbial Plaque and Saliva after Using CPP-ACP Paste in 6-9 year-old Children

PubMed Central

HR, Poureslami; Ra, Hoseinifar; Re, Hoseinifar; H, Sharifi; P, Poureslami

2016-01-01

Statement of Problem: Dental caries is one of the most common chronic diseases in children. The balance between demineralization and remineralization of the decayed teeth depends on the calcium and phosphate content of the tooth surface. Therefore, if a product such as casein phospho peptides - amorphous calcium phosphate (CPP- ACP) which can significantly increase the availability of calcium and phosphate in the plaque and saliva should have an anti-caries protective effect. Objectives: The purpose of this study was to evaluate the concentration of calcium, phosphate and fluoride in the plaque and saliva of children before and after applying the CPP-ACP paste. Materials and Methods: A total of 25 children aged between 6-9 years were selected for this clinical trial study. At first, 1 ml of unstimulated saliva was collected and then 1 mg of the plaque sample was collected from the buccal surfaces of the two first primary molars on the upper jaw. In the next step, CPP-ACP paste (GC Corp, Japan) was applied on the tooth surfaces and then the plaque and saliva sampling was performed after 60 minutes. The amount of calcium ions was measured by Ion meter instrument (Metrohm Co, Swiss) and the amounts of phosphate and fluoride ions were measured by Ion Chromatography instrument (Metrohm Co, Swiss). Data were analyzed using paired t-test at a p < 0.05 level of significance. Results: There were statistically significant differences in the calcium and phosphate concentration of the saliva and plaque before and after applying the CPP-ACP paste. There were also statistically significant differences in the fluoride levels of the plaque before and after applying the CPP-ACP paste. However, there were no statistically significant differences in the fluoride levels of the saliva before and after applying the CPP-ACP paste. Conclusions: In this study, the use of the CPP-ACP paste significantly increased the fluoride levels of the plaque and the calcium and phosphate levels of both saliva and plaque. Hence, CPP-ACP paste can facilitate the remineralization of tooth surfaces and is useful for protecting the primary teeth. PMID:28959745

Volcano plots in analyzing differential expressions with mRNA microarrays.

PubMed

Li, Wentian

2012-12-01

A volcano plot displays unstandardized signal (e.g. log-fold-change) against noise-adjusted/standardized signal (e.g. t-statistic or -log(10)(p-value) from the t-test). We review the basic and interactive use of the volcano plot and its crucial role in understanding the regularized t-statistic. The joint filtering gene selection criterion based on regularized statistics has a curved discriminant line in the volcano plot, as compared to the two perpendicular lines for the "double filtering" criterion. This review attempts to provide a unifying framework for discussions on alternative measures of differential expression, improved methods for estimating variance, and visual display of a microarray analysis result. We also discuss the possibility of applying volcano plots to other fields beyond microarray.

Educational Technology-Related Performance of Teaching Faculty in Higher Education: Implications for eLearning Management

ERIC Educational Resources Information Center

Larbi-Apau, Josephine A.; Guerra-Lopez, Ingrid; Moseley, James L.; Spannaus, Timothy; Yaprak, Attila

2017-01-01

The study examined teaching faculty's educational technology-related performances (ETRP) as a measure for predicting eLearning management in Ghana. A total of valid data (n = 164) were collected and analyzed on applied ISTE-NETS-T Performance Standards using descriptive and ANOVA statistics. Results showed an overall moderate performance with the…

The Performance of Local Dependence Measures with Psychological Data

ERIC Educational Resources Information Center

Houts, Carrie R.; Edwards, Michael C.

2013-01-01

The violation of the assumption of local independence when applying item response theory (IRT) models has been shown to have a negative impact on all estimates obtained from the given model. Numerous indices and statistics have been proposed to aid analysts in the detection of local dependence (LD). A Monte Carlo study was conducted to evaluate…

40 CFR 1048.510 - What transient duty cycles apply for laboratory testing?

Code of Federal Regulations, 2013 CFR

2013-07-01

... model year, measure emissions by testing the engine on a dynamometer with the duty cycle described in Appendix II to determine whether it meets the transient emission standards in § 1048.101(a). (b) Calculate cycle statistics and compare with the established criteria as specified in 40 CFR 1065.514 to confirm...

40 CFR 1048.510 - What transient duty cycles apply for laboratory testing?

Code of Federal Regulations, 2011 CFR

2011-07-01

... model year, measure emissions by testing the engine on a dynamometer with the duty cycle described in Appendix II to determine whether it meets the transient emission standards in § 1048.101(a). (b) Calculate cycle statistics and compare with the established criteria as specified in 40 CFR 1065.514 to confirm...

40 CFR 1048.510 - What transient duty cycles apply for laboratory testing?

Code of Federal Regulations, 2014 CFR

2014-07-01

... model year, measure emissions by testing the engine on a dynamometer with the duty cycle described in Appendix II to determine whether it meets the transient emission standards in § 1048.101(a). (b) Calculate cycle statistics and compare with the established criteria as specified in 40 CFR 1065.514 to confirm...

40 CFR 1048.510 - What transient duty cycles apply for laboratory testing?

Code of Federal Regulations, 2012 CFR

2012-07-01

... model year, measure emissions by testing the engine on a dynamometer with the duty cycle described in Appendix II to determine whether it meets the transient emission standards in § 1048.101(a). (b) Calculate cycle statistics and compare with the established criteria as specified in 40 CFR 1065.514 to confirm...

Financial Literacy of 15-Year-Olds: Results from PISA 2015. Data Point. NCES 2017-086

ERIC Educational Resources Information Center

Gonzales, Patrick; Sen, Anindita

2017-01-01

On May 24, the National Center for Education Statistics released Financial Literacy of 15-year-olds: Results from PISA 2015. The PISA assessment of financial literacy measured students' knowledge and understanding of fundamental elements of the financial world, including financial concepts, products, and risks, and their ability to apply what they…

Propensity Score Techniques and the Assessment of Measured Covariate Balance to Test Causal Associations in Psychological Research

ERIC Educational Resources Information Center

Harder, Valerie S.; Stuart, Elizabeth A.; Anthony, James C.

2010-01-01

There is considerable interest in using propensity score (PS) statistical techniques to address questions of causal inference in psychological research. Many PS techniques exist, yet few guidelines are available to aid applied researchers in their understanding, use, and evaluation. In this study, the authors give an overview of available…

Use of dichotomous choice nonmarket methods to value the whooping crane resource

Treesearch

J. Michael Bowker; John R. Stoll

1985-01-01

A dichotomous choice form of contingent valuation is applied to quantify individuals' economic surplus associated with preservation of the whooping crane resource. Specific issues and limitations of the empirical approach are discussed. The results of this case study reveal that models with similar statistical fits can lead to very disparate measures of economic...

LAND-USE CHANGE AND CARBON FLUX BETWEEN 1970S AND 1990S IN CENTRAL HIGHLANDS OF CHIAPAS, MEXICO

EPA Science Inventory

We present results of a study in an intensively impacted and highly fragmented landscape in which we apply field-measured carbon (C) density values to land-use/land-cover (LU/LC) statistics to estimate the flux of C between terrestrial ecosystems and the atmosphere from the 1970s...

ADHD and Method Variance: A Latent Variable Approach Applied to a Nationally Representative Sample of College Freshmen

ERIC Educational Resources Information Center

Konold, Timothy R.; Glutting, Joseph J.

2008-01-01

This study employed a correlated trait-correlated method application of confirmatory factor analysis to disentangle trait and method variance from measures of attention-deficit/hyperactivity disorder obtained at the college level. The two trait factors were "Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition" ("DSM-IV")…

Ascending Bloom's Pyramid: Fostering Student Creativity and Innovation in Academic Library Spaces

ERIC Educational Resources Information Center

Bieraugel, Mark; Neill, Stern

2017-01-01

Our research examined the degree to which behaviors and learning associated with creativity and innovation were supported in five academic library spaces and three other spaces at a mid-sized university. Based on survey data from 226 students, we apply a number of statistical techniques to measure student perceptions of the types of learning and…

[Statistical process control applied to intensity modulated radiotherapy pretreatment controls with portal dosimetry].

PubMed

Villani, N; Gérard, K; Marchesi, V; Huger, S; François, P; Noël, A

2010-06-01

The first purpose of this study was to illustrate the contribution of statistical process control for a better security in intensity modulated radiotherapy (IMRT) treatments. This improvement is possible by controlling the dose delivery process, characterized by pretreatment quality control results. So, it is necessary to put under control portal dosimetry measurements (currently, the ionisation chamber measurements were already monitored by statistical process control thanks to statistical process control tools). The second objective was to state whether it is possible to substitute ionisation chamber with portal dosimetry in order to optimize time devoted to pretreatment quality control. At Alexis-Vautrin center, pretreatment quality controls in IMRT for prostate and head and neck treatments were performed for each beam of each patient. These controls were made with an ionisation chamber, which is the reference detector for the absolute dose measurement, and with portal dosimetry for the verification of dose distribution. Statistical process control is a statistical analysis method, coming from industry, used to control and improve the studied process quality. It uses graphic tools as control maps to follow-up process, warning the operator in case of failure, and quantitative tools to evaluate the process toward its ability to respect guidelines: this is the capability study. The study was performed on 450 head and neck beams and on 100 prostate beams. Control charts, showing drifts, both slow and weak, and also both strong and fast, of mean and standard deviation have been established and have shown special cause introduced (manual shift of the leaf gap of the multileaf collimator). Correlation between dose measured at one point, given with the EPID and the ionisation chamber has been evaluated at more than 97% and disagreement cases between the two measurements were identified. The study allowed to demonstrate the feasibility to reduce the time devoted to pretreatment controls, by substituting the ionisation chamber's measurements with those performed with EPID, and also that a statistical process control monitoring of data brought security guarantee. 2010 Société française de radiothérapie oncologique (SFRO). Published by Elsevier SAS. All rights reserved.

An instrument to assess the statistical intensity of medical research papers.

PubMed

Nieminen, Pentti; Virtanen, Jorma I; Vähänikkilä, Hannu

2017-01-01

There is widespread evidence that statistical methods play an important role in original research articles, especially in medical research. The evaluation of statistical methods and reporting in journals suffers from a lack of standardized methods for assessing the use of statistics. The objective of this study was to develop and evaluate an instrument to assess the statistical intensity in research articles in a standardized way. A checklist-type measure scale was developed by selecting and refining items from previous reports about the statistical contents of medical journal articles and from published guidelines for statistical reporting. A total of 840 original medical research articles that were published between 2007-2015 in 16 journals were evaluated to test the scoring instrument. The total sum of all items was used to assess the intensity between sub-fields and journals. Inter-rater agreement was examined using a random sample of 40 articles. Four raters read and evaluated the selected articles using the developed instrument. The scale consisted of 66 items. The total summary score adequately discriminated between research articles according to their study design characteristics. The new instrument could also discriminate between journals according to their statistical intensity. The inter-observer agreement measured by the ICC was 0.88 between all four raters. Individual item analysis showed very high agreement between the rater pairs, the percentage agreement ranged from 91.7% to 95.2%. A reliable and applicable instrument for evaluating the statistical intensity in research papers was developed. It is a helpful tool for comparing the statistical intensity between sub-fields and journals. The novel instrument may be applied in manuscript peer review to identify papers in need of additional statistical review.

Factorial analysis of trihalomethanes formation in drinking water.

PubMed

Chowdhury, Shakhawat; Champagne, Pascale; McLellan, P James

2010-06-01

Disinfection of drinking water reduces pathogenic infection, but may pose risks to human health through the formation of disinfection byproducts. The effects of different factors on the formation of trihalomethanes were investigated using a statistically designed experimental program, and a predictive model for trihalomethanes formation was developed. Synthetic water samples with different factor levels were produced, and trihalomethanes concentrations were measured. A replicated fractional factorial design with center points was performed, and significant factors were identified through statistical analysis. A second-order trihalomethanes formation model was developed from 92 experiments, and the statistical adequacy was assessed through appropriate diagnostics. This model was validated using additional data from the Drinking Water Surveillance Program database and was applied to the Smiths Falls water supply system in Ontario, Canada. The model predictions were correlated strongly to the measured trihalomethanes, with correlations of 0.95 and 0.91, respectively. The resulting model can assist in analyzing risk-cost tradeoffs in the design and operation of water supply systems.

Statistical study of air pollutant concentrations via generalized gamma distribution

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

Marani, A.; Lavagnini, I.; Buttazzoni, C.

1986-11-01

This paper deals with modeling observed frequency distributions of air quality data measured in the area of Venice, Italy. The paper discusses the application of the generalized gamma distribution (ggd) which has not been commonly applied to air quality data notwithstanding the fact that it embodies most distribution models used for air quality analyses. The approach yields important simplifications for statistical analyses. A comparison among the ggd and other relevant models (standard gamma, Weibull, lognormal), carried out on daily sulfur dioxide concentrations in the area of Venice underlines the efficiency of ggd models in portraying experimental data.

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

Crowder, Stephen V.

This document outlines a statistical framework for establishing a shelf-life program for components whose performance is measured by the value of a continuous variable such as voltage or function time. The approach applies to both single measurement devices and repeated measurement devices, although additional process control charts may be useful in the case of repeated measurements. The approach is to choose a sample size that protects the margin associated with a particular variable over the life of the component. Deviations from expected performance of the measured variable are detected prior to the complete loss of margin. This ensures the reliabilitymore » of the component over its lifetime.« less

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.

Data-driven sensitivity inference for Thomson scattering electron density measurement systems.

PubMed

Fujii, Keisuke; Yamada, Ichihiro; Hasuo, Masahiro

2017-01-01

We developed a method to infer the calibration parameters of multichannel measurement systems, such as channel variations of sensitivity and noise amplitude, from experimental data. We regard such uncertainties of the calibration parameters as dependent noise. The statistical properties of the dependent noise and that of the latent functions were modeled and implemented in the Gaussian process kernel. Based on their statistical difference, both parameters were inferred from the data. We applied this method to the electron density measurement system by Thomson scattering for the Large Helical Device plasma, which is equipped with 141 spatial channels. Based on the 210 sets of experimental data, we evaluated the correction factor of the sensitivity and noise amplitude for each channel. The correction factor varies by ≈10%, and the random noise amplitude is ≈2%, i.e., the measurement accuracy increases by a factor of 5 after this sensitivity correction. The certainty improvement in the spatial derivative inference was demonstrated.

Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

NASA Astrophysics Data System (ADS)

Quesada-Montano, Beatriz; Westerberg, Ida K.; Fuentes-Andino, Diana; Hidalgo-Leon, Hugo; Halldin, Sven

2017-04-01

Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information - to locally observed discharge - can be used to constrain model parameter uncertainty for ungauged catchments. Climate variability exerts a strong influence on streamflow variability on long and short time scales, in particular in the Central-American region. We therefore explored the use of climate variability knowledge to constrain the simulated discharge uncertainty of a conceptual hydrological model applied to a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty we first rejected parameter relationships that disagreed with our understanding of the system. We then assessed how well climate-based constraints applied at long-term, inter-annual and intra-annual time scales could constrain model uncertainty. Finally, we compared the climate-based constraints to a constraint on low-flow statistics based on information obtained from global maps. We evaluated our method in terms of the ability of the model to reproduce the observed hydrograph and the active catchment processes in terms of two efficiency measures, a statistical consistency measure, a spread measure and 17 hydrological signatures. We found that climate variability knowledge was useful for reducing model uncertainty, in particular, unrealistic representation of deep groundwater processes. The constraints based on global maps of low-flow statistics provided more constraining information than those based on climate variability, but the latter rejected slow rainfall-runoff representations that the low flow statistics did not reject. The use of such knowledge, together with information on low-flow statistics and constraints on parameter relationships showed to be useful to constrain model uncertainty for an - assumed to be - ungauged basin. This shows that our method is promising for reconstructing long-term flow data for ungauged catchments on the Pacific side of Central America, and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.

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.

Empirical investigation into depth-resolution of Magnetotelluric data

NASA Astrophysics Data System (ADS)

Piana Agostinetti, N.; Ogaya, X.

2017-12-01

We investigate the depth-resolution of MT data comparing reconstructed 1D resistivity profiles with measured resistivity and lithostratigraphy from borehole data. Inversion of MT data has been widely used to reconstruct the 1D fine-layered resistivity structure beneath an isolated Magnetotelluric (MT) station. Uncorrelated noise is generally assumed to be associated to MT data. However, wrong assumptions on error statistics have been proved to strongly bias the results obtained in geophysical inversions. In particular the number of resolved layers at depth strongly depends on error statistics. In this study, we applied a trans-dimensional McMC algorithm for reconstructing the 1D resistivity profile near-by the location of a 1500 m-deep borehole, using MT data. We resolve the MT inverse problem imposing different models for the error statistics associated to the MT data. Following a Hierachical Bayes' approach, we also inverted for the hyper-parameters associated to each error statistics model. Preliminary results indicate that assuming un-correlated noise leads to a number of resolved layers larger than expected from the retrieved lithostratigraphy. Moreover, comparing the inversion of synthetic resistivity data obtained from the "true" resistivity stratification measured along the borehole shows that a consistent number of resistivity layers can be obtained using a Gaussian model for the error statistics, with substantial correlation length.

UNITY: Confronting Supernova Cosmology's Statistical and Systematic Uncertainties in a Unified Bayesian Framework

NASA Astrophysics Data System (ADS)

Rubin, D.; Aldering, G.; Barbary, K.; Boone, K.; Chappell, G.; Currie, M.; Deustua, S.; Fagrelius, P.; Fruchter, A.; Hayden, B.; Lidman, C.; Nordin, J.; Perlmutter, S.; Saunders, C.; Sofiatti, C.; Supernova Cosmology Project, The

2015-11-01

While recent supernova (SN) cosmology research has benefited from improved measurements, current analysis approaches are not statistically optimal and will prove insufficient for future surveys. This paper discusses the limitations of current SN cosmological analyses in treating outliers, selection effects, shape- and color-standardization relations, unexplained dispersion, and heterogeneous observations. We present a new Bayesian framework, called UNITY (Unified Nonlinear Inference for Type-Ia cosmologY), that incorporates significant improvements in our ability to confront these effects. We apply the framework to real SN observations and demonstrate smaller statistical and systematic uncertainties. We verify earlier results that SNe Ia require nonlinear shape and color standardizations, but we now include these nonlinear relations in a statistically well-justified way. This analysis was primarily performed blinded, in that the basic framework was first validated on simulated data before transitioning to real data. We also discuss possible extensions of the method.

Quantification and statistical significance analysis of group separation in NMR-based metabonomics studies

PubMed Central

Goodpaster, Aaron M.; Kennedy, Michael A.

2015-01-01

Currently, no standard metrics are used to quantify cluster separation in PCA or PLS-DA scores plots for metabonomics studies or to determine if cluster separation is statistically significant. Lack of such measures makes it virtually impossible to compare independent or inter-laboratory studies and can lead to confusion in the metabonomics literature when authors putatively identify metabolites distinguishing classes of samples based on visual and qualitative inspection of scores plots that exhibit marginal separation. While previous papers have addressed quantification of cluster separation in PCA scores plots, none have advocated routine use of a quantitative measure of separation that is supported by a standard and rigorous assessment of whether or not the cluster separation is statistically significant. Here quantification and statistical significance of separation of group centroids in PCA and PLS-DA scores plots are considered. The Mahalanobis distance is used to quantify the distance between group centroids, and the two-sample Hotelling's T2 test is computed for the data, related to an F-statistic, and then an F-test is applied to determine if the cluster separation is statistically significant. We demonstrate the value of this approach using four datasets containing various degrees of separation, ranging from groups that had no apparent visual cluster separation to groups that had no visual cluster overlap. Widespread adoption of such concrete metrics to quantify and evaluate the statistical significance of PCA and PLS-DA cluster separation would help standardize reporting of metabonomics data. PMID:26246647

Acute Respiratory Distress Syndrome Measurement Error. Potential Effect on Clinical Study Results

PubMed Central

Cooke, Colin R.; Iwashyna, Theodore J.; Hofer, Timothy P.

2016-01-01

Rationale: Identifying patients with acute respiratory distress syndrome (ARDS) is a recognized challenge. Experts often have only moderate agreement when applying the clinical definition of ARDS to patients. However, no study has fully examined the implications of low reliability measurement of ARDS on clinical studies. Objectives: To investigate how the degree of variability in ARDS measurement commonly reported in clinical studies affects study power, the accuracy of treatment effect estimates, and the measured strength of risk factor associations. Methods: We examined the effect of ARDS measurement error in randomized clinical trials (RCTs) of ARDS-specific treatments and cohort studies using simulations. We varied the reliability of ARDS diagnosis, quantified as the interobserver reliability (κ-statistic) between two reviewers. In RCT simulations, patients identified as having ARDS were enrolled, and when measurement error was present, patients without ARDS could be enrolled. In cohort studies, risk factors as potential predictors were analyzed using reviewer-identified ARDS as the outcome variable. Measurements and Main Results: Lower reliability measurement of ARDS during patient enrollment in RCTs seriously degraded study power. Holding effect size constant, the sample size necessary to attain adequate statistical power increased by more than 50% as reliability declined, although the result was sensitive to ARDS prevalence. In a 1,400-patient clinical trial, the sample size necessary to maintain similar statistical power increased to over 1,900 when reliability declined from perfect to substantial (κ = 0.72). Lower reliability measurement diminished the apparent effectiveness of an ARDS-specific treatment from a 15.2% (95% confidence interval, 9.4–20.9%) absolute risk reduction in mortality to 10.9% (95% confidence interval, 4.7–16.2%) when reliability declined to moderate (κ = 0.51). In cohort studies, the effect on risk factor associations was similar. Conclusions: ARDS measurement error can seriously degrade statistical power and effect size estimates of clinical studies. The reliability of ARDS measurement warrants careful attention in future ARDS clinical studies. PMID:27159648

The association of 83 plasma proteins with CHD mortality, BMI, HDL-, and total-cholesterol in men: applying multivariate statistics to identify proteins with prognostic value and biological relevance.

PubMed

Heidema, A Geert; Thissen, Uwe; Boer, Jolanda M A; Bouwman, Freek G; Feskens, Edith J M; Mariman, Edwin C M

2009-06-01

In this study, we applied the multivariate statistical tool Partial Least Squares (PLS) to analyze the relative importance of 83 plasma proteins in relation to coronary heart disease (CHD) mortality and the intermediate end points body mass index, HDL-cholesterol and total cholesterol. From a Dutch monitoring project for cardiovascular disease risk factors, men who died of CHD between initial participation (1987-1991) and end of follow-up (January 1, 2000) (N = 44) and matched controls (N = 44) were selected. Baseline plasma concentrations of proteins were measured by a multiplex immunoassay. With the use of PLS, we identified 15 proteins with prognostic value for CHD mortality and sets of proteins associated with the intermediate end points. Subsequently, sets of proteins and intermediate end points were analyzed together by Principal Components Analysis, indicating that proteins involved in inflammation explained most of the variance, followed by proteins involved in metabolism and proteins associated with total-C. This study is one of the first in which the association of a large number of plasma proteins with CHD mortality and intermediate end points is investigated by applying multivariate statistics, providing insight in the relationships among proteins, intermediate end points and CHD mortality, and a set of proteins with prognostic value.

A Divergence Statistics Extension to VTK for Performance Analysis

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

Pebay, Philippe Pierre; Bennett, Janine Camille

This report follows the series of previous documents ([PT08, BPRT09b, PT09, BPT09, PT10, PB13], where we presented the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k -means, order and auto-correlative statistics engines which we developed within the Visualization Tool Kit ( VTK ) as a scalable, parallel and versatile statistics package. We now report on a new engine which we developed for the calculation of divergence statistics, a concept which we hereafter explain and whose main goal is to quantify the discrepancy, in a stasticial manner akin to measuring a distance, between an observed empirical distribution and a theoretical,more » "ideal" one. The ease of use of the new diverence statistics engine is illustrated by the means of C++ code snippets. Although this new engine does not yet have a parallel implementation, it has already been applied to HPC performance analysis, of which we provide an example.« less

Definition of a simple statistical parameter for the quantification of orientation in two dimensions: application to cells on grooves of nanometric depths.

PubMed

Davidson, P; Bigerelle, M; Bounichane, B; Giazzon, M; Anselme, K

2010-07-01

Contact guidance is generally evaluated by measuring the orientation angle of cells. However, statistical analyses are rarely performed on these parameters. Here we propose a statistical analysis based on a new parameter sigma, the orientation parameter, defined as the dispersion of the distribution of orientation angles. This parameter can be used to obtain a truncated Gaussian distribution that models the distribution of the data between -90 degrees and +90 degrees. We established a threshold value of the orientation parameter below which the data can be considered to be aligned within a 95% confidence interval. Applying our orientation parameter to cells on grooves and using a modelling approach, we established the relationship sigma=alpha(meas)+(52 degrees -alpha(meas))/(1+C(GDE)R) where the parameter C(GDE) represents the sensitivity of cells to groove depth, and R the groove depth. The values of C(GDE) obtained allowed us to compare the contact guidance of human osteoprogenitor (HOP) cells across experiments involving different groove depths, times in culture and inoculation densities. We demonstrate that HOP cells are able to identify and respond to the presence of grooves 30, 100, 200 and 500 nm deep and that the deeper the grooves, the higher the cell orientation. The evolution of the sensitivity (C(GDE)) with culture time is roughly sigmoidal with an asymptote, which is a function of inoculation density. The sigma parameter defined here is a universal parameter that can be applied to all orientation measurements and does not require a mathematical background or knowledge of directional statistics. Copyright 2010 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Image Statistics and the Representation of Material Properties in the Visual Cortex

PubMed Central

Baumgartner, Elisabeth; Gegenfurtner, Karl R.

2016-01-01

We explored perceived material properties (roughness, texturedness, and hardness) with a novel approach that compares perception, image statistics and brain activation, as measured with fMRI. We initially asked participants to rate 84 material images with respect to the above mentioned properties, and then scanned 15 of the participants with fMRI while they viewed the material images. The images were analyzed with a set of image statistics capturing their spatial frequency and texture properties. Linear classifiers were then applied to the image statistics as well as the voxel patterns of visually responsive voxels and early visual areas to discriminate between images with high and low perceptual ratings. Roughness and texturedness could be classified above chance level based on image statistics. Roughness and texturedness could also be classified based on the brain activation patterns in visual cortex, whereas hardness could not. Importantly, the agreement in classification based on image statistics and brain activation was also above chance level. Our results show that information about visual material properties is to a large degree contained in low-level image statistics, and that these image statistics are also partially reflected in brain activity patterns induced by the perception of material images. PMID:27582714

Image Statistics and the Representation of Material Properties in the Visual Cortex.

PubMed

Baumgartner, Elisabeth; Gegenfurtner, Karl R

2016-01-01

We explored perceived material properties (roughness, texturedness, and hardness) with a novel approach that compares perception, image statistics and brain activation, as measured with fMRI. We initially asked participants to rate 84 material images with respect to the above mentioned properties, and then scanned 15 of the participants with fMRI while they viewed the material images. The images were analyzed with a set of image statistics capturing their spatial frequency and texture properties. Linear classifiers were then applied to the image statistics as well as the voxel patterns of visually responsive voxels and early visual areas to discriminate between images with high and low perceptual ratings. Roughness and texturedness could be classified above chance level based on image statistics. Roughness and texturedness could also be classified based on the brain activation patterns in visual cortex, whereas hardness could not. Importantly, the agreement in classification based on image statistics and brain activation was also above chance level. Our results show that information about visual material properties is to a large degree contained in low-level image statistics, and that these image statistics are also partially reflected in brain activity patterns induced by the perception of material images.

Students' Successes and Challenges Applying Data Analysis and Measurement Skills in a Fifth-Grade Integrated STEM Unit

ERIC Educational Resources Information Center

Glancy, Aran W.; Moore, Tamara J.; Guzey, Selcen; Smith, Karl A.

2017-01-01

An understanding of statistics and skills in data analysis are becoming more and more essential, yet research consistently shows that students struggle with these concepts at all levels. This case study documents some of the struggles four groups of fifth-grade students encounter as they collect, organize, and interpret data and then ultimately…

Scattering from Rock and Rock Outcrops

DTIC Science & Technology

2015-09-30

Scattering from Rock and Rock Outcrops Derek R. Olson The Pennsylvania State University Applied Research Laboratory, P.O. Box 30 State...In terms of target detection and classification, scattering from exposed rock on the seafloor, (i.e., individual rocks and rock outcrops) presents...levels, and other statistical measures of acoustic scattering from rocks and rock outcrops is therefore critical. Unfortunately (and curiously

Building Coherent Validation Arguments for the Measurement of Latent Constructs with Unified Statistical Frameworks

ERIC Educational Resources Information Center

Rupp, Andre A.

2012-01-01

In the focus article of this issue, von Davier, Naemi, and Roberts essentially coupled: (1) a short methodological review of structural similarities of latent variable models with discrete and continuous latent variables; and (2) 2 short empirical case studies that show how these models can be applied to real, rather than simulated, large-scale…

Multicausal Systems Ask for Multicausal Approaches: A Network Perspective on Subjective Well-Being in Individuals with Autism Spectrum Disorder

ERIC Educational Resources Information Center

Deserno, Marie K.; Borsboom, Denny; Begeer, Sander; Geurts, Hilde M.

2017-01-01

Given the heterogeneity of autism spectrum disorder, an important limitation of much autism spectrum disorder research is that outcome measures are statistically modeled as separate dependent variables. Often, their multivariate structure is either ignored or treated as a nuisance. This study aims to lift this limitation by applying network…

The Dundee Ready Education Environment Measure (DREEM): a review of its adoption and use.

PubMed

Miles, Susan; Swift, Louise; Leinster, Sam J

2012-01-01

The Dundee Ready Education Environment Measure (DREEM) was published in 1997 as a tool to evaluate educational environments of medical schools and other health training settings and a recent review concluded that it was the most suitable such instrument. This study aimed to review the settings and purposes to which the DREEM has been applied and the approaches used to analyse and report it, with a view to guiding future users towards appropriate methodology. A systematic literature review was conducted using the Web of Knowledge databases of all articles reporting DREEM data between 1997 and 4 January 2011. The review found 40 publications, using data from 20 countries. DREEM is used in evaluation for diagnostic purposes, comparison between different groups and comparison with ideal/expected scores. A variety of non-parametric and parametric statistical methods have been applied, but their use is inconsistent. DREEM has been used internationally for different purposes and is regarded as a useful tool by users. However, reporting and analysis differs between publications. This lack of uniformity makes comparison between institutions difficult. Most users of DREEM are not statisticians and there is a need for informed guidelines on its reporting and statistical analysis.

Segmentation-free statistical image reconstruction for polyenergetic x-ray computed tomography with experimental validation.

PubMed

Idris A, Elbakri; Fessler, Jeffrey A

2003-08-07

This paper describes a statistical image reconstruction method for x-ray CT that is based on a physical model that accounts for the polyenergetic x-ray source spectrum and the measurement nonlinearities caused by energy-dependent attenuation. Unlike our earlier work, the proposed algorithm does not require pre-segmentation of the object into the various tissue classes (e.g., bone and soft tissue) and allows mixed pixels. The attenuation coefficient of each voxel is modelled as the product of its unknown density and a weighted sum of energy-dependent mass attenuation coefficients. We formulate a penalized-likelihood function for this polyenergetic model and develop an iterative algorithm for estimating the unknown density of each voxel. Applying this method to simulated x-ray CT measurements of objects containing both bone and soft tissue yields images with significantly reduced beam hardening artefacts relative to conventional beam hardening correction methods. We also apply the method to real data acquired from a phantom containing various concentrations of potassium phosphate solution. The algorithm reconstructs an image with accurate density values for the different concentrations, demonstrating its potential for quantitative CT applications.

Advanced electrical current measurements of microdischarges: evidence of sub-critical pulses and ion currents in barrier discharge in air

NASA Astrophysics Data System (ADS)

Synek, Petr; Zemánek, Miroslav; Kudrle, Vít; Hoder, Tomáš

2018-04-01

Electrical current measurements in corona or barrier microdischarges are a challenge as they require both high temporal resolution and a large dynamic range of the current probe used. In this article, we apply a simple self-assembled current probe and compare it to commercial ones. An analysis in the time and frequency domain is carried out. Moreover, an improved methodology is presented, enabling both temporal resolution in sub-nanosecond times and current sensitivity in the order of tens of micro-amperes. Combining this methodology with a high-tech oscilloscope and self-developed software, a unique statistical analysis of currents in volume barrier discharge driven in atmospheric-pressure air is made for over 80 consecutive periods of a 15 kHz applied voltage. We reveal the presence of repetitive sub-critical current pulses and conclude that these can be identified with the discharging of surface charge microdomains. Moreover, extremely low, long-lasting microsecond currents were detected which are caused by ion flow, and are analysed in detail. The statistical behaviour presented gives deeper insight into the discharge physics of these usually undetectable current signals.

Multivariate statistical monitoring as applied to clean-in-place (CIP) and steam-in-place (SIP) operations in biopharmaceutical manufacturing.

PubMed

Roy, Kevin; Undey, Cenk; Mistretta, Thomas; Naugle, Gregory; Sodhi, Manbir

2014-01-01

Multivariate statistical process monitoring (MSPM) is becoming increasingly utilized to further enhance process monitoring in the biopharmaceutical industry. MSPM can play a critical role when there are many measurements and these measurements are highly correlated, as is typical for many biopharmaceutical operations. Specifically, for processes such as cleaning-in-place (CIP) and steaming-in-place (SIP, also known as sterilization-in-place), control systems typically oversee the execution of the cycles, and verification of the outcome is based on offline assays. These offline assays add to delays and corrective actions may require additional setup times. Moreover, this conventional approach does not take interactive effects of process variables into account and cycle optimization opportunities as well as salient trends in the process may be missed. Therefore, more proactive and holistic online continued verification approaches are desirable. This article demonstrates the application of real-time MSPM to processes such as CIP and SIP with industrial examples. The proposed approach has significant potential for facilitating enhanced continuous verification, improved process understanding, abnormal situation detection, and predictive monitoring, as applied to CIP and SIP operations. © 2014 American Institute of Chemical Engineers.

Multiple Hypothesis Testing for Experimental Gingivitis Based on Wilcoxon Signed Rank Statistics

PubMed Central

Preisser, John S.; Sen, Pranab K.; Offenbacher, Steven

2011-01-01

Dental research often involves repeated multivariate outcomes on a small number of subjects for which there is interest in identifying outcomes that exhibit change in their levels over time as well as to characterize the nature of that change. In particular, periodontal research often involves the analysis of molecular mediators of inflammation for which multivariate parametric methods are highly sensitive to outliers and deviations from Gaussian assumptions. In such settings, nonparametric methods may be favored over parametric ones. Additionally, there is a need for statistical methods that control an overall error rate for multiple hypothesis testing. We review univariate and multivariate nonparametric hypothesis tests and apply them to longitudinal data to assess changes over time in 31 biomarkers measured from the gingival crevicular fluid in 22 subjects whereby gingivitis was induced by temporarily withholding tooth brushing. To identify biomarkers that can be induced to change, multivariate Wilcoxon signed rank tests for a set of four summary measures based upon area under the curve are applied for each biomarker and compared to their univariate counterparts. Multiple hypothesis testing methods with choice of control of the false discovery rate or strong control of the family-wise error rate are examined. PMID:21984957

In-situ structural integrity evaluation for high-power pulsed spallation neutron source - Effects of cavitation damage on structural vibration

NASA Astrophysics Data System (ADS)

Wan, Tao; Naoe, Takashi; Futakawa, Masatoshi

2016-01-01

A double-wall structure mercury target will be installed at the high-power pulsed spallation neutron source in the Japan Proton Accelerator Research Complex (J-PARC). Cavitation damage on the inner wall is an important factor governing the lifetime of the target-vessel. To monitor the structural integrity of the target vessel, displacement velocity at a point on the outer surface of the target vessel is measured using a laser Doppler vibrometer (LDV). The measured signals can be used for evaluating the damage inside the target vessel because of cyclic loading and cavitation bubble collapse caused by pulsed-beam induced pressure waves. The wavelet differential analysis (WDA) was applied to reveal the effects of the damage on vibrational cycling. To reduce the effects of noise superimposed on the vibration signals on the WDA results, analysis of variance (ANOVA) and analysis of covariance (ANCOVA), statistical methods were applied. Results from laboratory experiments, numerical simulation results with random noise added, and target vessel field data were analyzed by the WDA and the statistical methods. The analyses demonstrated that the established in-situ diagnostic technique can be used to effectively evaluate the structural response of the target vessel.

Statistical Analysis of the Indus Script Using n-Grams

PubMed Central

Yadav, Nisha; Joglekar, Hrishikesh; Rao, Rajesh P. N.; Vahia, Mayank N.; Adhikari, Ronojoy; Mahadevan, Iravatham

2010-01-01

The Indus script is one of the major undeciphered scripts of the ancient world. The small size of the corpus, the absence of bilingual texts, and the lack of definite knowledge of the underlying language has frustrated efforts at decipherment since the discovery of the remains of the Indus civilization. Building on previous statistical approaches, we apply the tools of statistical language processing, specifically n-gram Markov chains, to analyze the syntax of the Indus script. We find that unigrams follow a Zipf-Mandelbrot distribution. Text beginner and ender distributions are unequal, providing internal evidence for syntax. We see clear evidence of strong bigram correlations and extract significant pairs and triplets using a log-likelihood measure of association. Highly frequent pairs and triplets are not always highly significant. The model performance is evaluated using information-theoretic measures and cross-validation. The model can restore doubtfully read texts with an accuracy of about 75%. We find that a quadrigram Markov chain saturates information theoretic measures against a held-out corpus. Our work forms the basis for the development of a stochastic grammar which may be used to explore the syntax of the Indus script in greater detail. PMID:20333254

Statistical methods used in articles published by the Journal of Periodontal and Implant Science.

PubMed

Choi, Eunsil; Lyu, Jiyoung; Park, Jinyoung; Kim, Hae-Young

2014-12-01

The purposes of this study were to assess the trend of use of statistical methods including parametric and nonparametric methods and to evaluate the use of complex statistical methodology in recent periodontal studies. This study analyzed 123 articles published in the Journal of Periodontal & Implant Science (JPIS) between 2010 and 2014. Frequencies and percentages were calculated according to the number of statistical methods used, the type of statistical method applied, and the type of statistical software used. Most of the published articles considered (64.4%) used statistical methods. Since 2011, the percentage of JPIS articles using statistics has increased. On the basis of multiple counting, we found that the percentage of studies in JPIS using parametric methods was 61.1%. Further, complex statistical methods were applied in only 6 of the published studies (5.0%), and nonparametric statistical methods were applied in 77 of the published studies (38.9% of a total of 198 studies considered). We found an increasing trend towards the application of statistical methods and nonparametric methods in recent periodontal studies and thus, concluded that increased use of complex statistical methodology might be preferred by the researchers in the fields of study covered by JPIS.

Systematic review of statistical approaches to quantify, or correct for, measurement error in a continuous exposure in nutritional epidemiology.

PubMed

Bennett, Derrick A; Landry, Denise; Little, Julian; Minelli, Cosetta

2017-09-19

Several statistical approaches have been proposed to assess and correct for exposure measurement error. We aimed to provide a critical overview of the most common approaches used in nutritional epidemiology. MEDLINE, EMBASE, BIOSIS and CINAHL were searched for reports published in English up to May 2016 in order to ascertain studies that described methods aimed to quantify and/or correct for measurement error for a continuous exposure in nutritional epidemiology using a calibration study. We identified 126 studies, 43 of which described statistical methods and 83 that applied any of these methods to a real dataset. The statistical approaches in the eligible studies were grouped into: a) approaches to quantify the relationship between different dietary assessment instruments and "true intake", which were mostly based on correlation analysis and the method of triads; b) approaches to adjust point and interval estimates of diet-disease associations for measurement error, mostly based on regression calibration analysis and its extensions. Two approaches (multiple imputation and moment reconstruction) were identified that can deal with differential measurement error. For regression calibration, the most common approach to correct for measurement error used in nutritional epidemiology, it is crucial to ensure that its assumptions and requirements are fully met. Analyses that investigate the impact of departures from the classical measurement error model on regression calibration estimates can be helpful to researchers in interpreting their findings. With regard to the possible use of alternative methods when regression calibration is not appropriate, the choice of method should depend on the measurement error model assumed, the availability of suitable calibration study data and the potential for bias due to violation of the classical measurement error model assumptions. On the basis of this review, we provide some practical advice for the use of methods to assess and adjust for measurement error in nutritional epidemiology.

Detection of outliers in the response and explanatory variables of the simple circular regression model

NASA Astrophysics Data System (ADS)

Mahmood, Ehab A.; Rana, Sohel; Hussin, Abdul Ghapor; Midi, Habshah

2016-06-01

The circular regression model may contain one or more data points which appear to be peculiar or inconsistent with the main part of the model. This may be occur due to recording errors, sudden short events, sampling under abnormal conditions etc. The existence of these data points "outliers" in the data set cause lot of problems in the research results and the conclusions. Therefore, we should identify them before applying statistical analysis. In this article, we aim to propose a statistic to identify outliers in the both of the response and explanatory variables of the simple circular regression model. Our proposed statistic is robust circular distance RCDxy and it is justified by the three robust measurements such as proportion of detection outliers, masking and swamping rates.

Statistical analysis of subjective preferences for video enhancement

NASA Astrophysics Data System (ADS)

Woods, Russell L.; Satgunam, PremNandhini; Bronstad, P. Matthew; Peli, Eli

2010-02-01

Measuring preferences for moving video quality is harder than for static images due to the fleeting and variable nature of moving video. Subjective preferences for image quality can be tested by observers indicating their preference for one image over another. Such pairwise comparisons can be analyzed using Thurstone scaling (Farrell, 1999). Thurstone (1927) scaling is widely used in applied psychology, marketing, food tasting and advertising research. Thurstone analysis constructs an arbitrary perceptual scale for the items that are compared (e.g. enhancement levels). However, Thurstone scaling does not determine the statistical significance of the differences between items on that perceptual scale. Recent papers have provided inferential statistical methods that produce an outcome similar to Thurstone scaling (Lipovetsky and Conklin, 2004). Here, we demonstrate that binary logistic regression can analyze preferences for enhanced video.

Metrological assessment of the methods for measuring the contents of acids and ion metals responsible for the exchangeable acidity of soils

NASA Astrophysics Data System (ADS)

Vanchikova, E. V.; Shamrikova, E. V.; Bespyatykh, N. V.; Kyz"yurova, E. V.; Kondratenok, B. M.

2015-02-01

Metrological characteristics—precision, trueness, and accuracy—of the results of measurements of the exchangeable acidity and its components by the potentiometric titration method were studied on the basis of multiple analyses of the soil samples with the examination of statistical data for the outliers and their correspondence to the normal distribution. Measurement errors were estimated. The applied method was certified by the Metrological Center of the Uralian Branch of the Russian Academy of Sciences (certificate no. 88-17641-094-2013) and included in the Federal Information Fund on Assurance of Measurements (FR 1.31.2013.16382).

In-situ microscale through-silicon via strain measurements by synchrotron x-ray microdiffraction exploring the physics behind data interpretation

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

Liu, Xi; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332; Thadesar, Paragkumar A.

2014-09-15

In-situ microscale thermomechanical strain measurements have been performed in combination with synchrotron x-ray microdiffraction to understand the fundamental cause of failures in microelectronics devices with through-silicon vias. The physics behind the raster scan and data analysis of the measured strain distribution maps is explored utilizing the energies of indexed reflections from the measured data and applying them for beam intensity analysis and effective penetration depth determination. Moreover, a statistical analysis is performed for the beam intensity and strain distributions along the beam penetration path to account for the factors affecting peak search and strain refinement procedure.

Measuring and improving the quality of postoperative epidural analgesia for major abdominal surgery using statistical process control charts.

PubMed

Duncan, Fiona; Haigh, Carol

2013-10-01

To explore and improve the quality of continuous epidural analgesia for pain relief using Statistical Process Control tools. Measuring the quality of pain management interventions is complex. Intermittent audits do not accurately capture the results of quality improvement initiatives. The failure rate for one intervention, epidural analgesia, is approximately 30% in everyday practice, so it is an important area for improvement. Continuous measurement and analysis are required to understand the multiple factors involved in providing effective pain relief. Process control and quality improvement Routine prospectively acquired data collection started in 2006. Patients were asked about their pain and side effects of treatment. Statistical Process Control methods were applied for continuous data analysis. A multidisciplinary group worked together to identify reasons for variation in the data and instigated ideas for improvement. The key measure for improvement was a reduction in the percentage of patients with an epidural in severe pain. The baseline control charts illustrated the recorded variation in the rate of several processes and outcomes for 293 surgical patients. The mean visual analogue pain score (VNRS) was four. There was no special cause variation when data were stratified by surgeons, clinical area or patients who had experienced pain before surgery. Fifty-seven per cent of patients were hypotensive on the first day after surgery. We were able to demonstrate a significant improvement in the failure rate of epidurals as the project continued with quality improvement interventions. Statistical Process Control is a useful tool for measuring and improving the quality of pain management. The applications of Statistical Process Control methods offer the potential to learn more about the process of change and outcomes in an Acute Pain Service both locally and nationally. We have been able to develop measures for improvement and benchmarking in routine care that has led to the establishment of a national pain registry. © 2013 Blackwell Publishing Ltd.

A concordance index for matched case-control studies with applications in cancer risk.

PubMed

Brentnall, Adam R; Cuzick, Jack; Field, John; Duffy, Stephen W

2015-02-10

In unmatched case-control studies, the area under the receiver operating characteristic (ROC) curve (AUC) may be used to measure how well a variable discriminates between cases and controls. The AUC is sometimes used in matched case-control studies by ignoring matching, but it lacks interpretation because it is not based on an estimate of the ROC for the population of interest. We introduce an alternative measure of discrimination that is the concordance of risk factors conditional on the matching factors. Parametric and non-parametric estimators are given for different matching scenarios, and applied to real data from breast and lung cancer case-control studies. Diagnostic plots to verify the constancy of discrimination over matching factors are demonstrated. The proposed simple measure is easy to use, interpret, more efficient than unmatched AUC statistics and may be applied to compare the conditional discrimination performance of risk factors. Copyright © 2014 John Wiley & Sons, Ltd.

Search for a Permanent Electric Dipole Moment on MERCURY-199 Atoms as a Test of Time Reversal Symmetry

NASA Astrophysics Data System (ADS)

Jacobs, James Patrick

Optically pumped atomic oscillators driven with a modulated light source have been used to measure the Permanent Electric Dipole Moment (PEDM) of the ^{199}Hg atom. A nonzero PEDM on the ground state of ^{199} Hg would be a direct violation of time reversal symmetry. The measurement was obtained by searching for a relative shift in the resonance frequency of the processing nuclear magnetic moments when an externally applied electric field was reversed relative to an externally applied magnetic field. The null result, d(^{199} Hg) = (.3 +/- 5.7 +/- 5.0) times 10 ^{-28} ecdotcm, represents nearly a factor of 15 improvement over previous ^{199}Hg measurements, and a factor of 25 improvement in statistical uncertainty. When combined with theoretical calculations, the result sets stringent limits on possible sources of time reversal symmetry violation in atomic systems.

Non-invasive body temperature measurement of wild chimpanzees using fecal temperature decline.

PubMed

Jensen, Siv Aina; Mundry, Roger; Nunn, Charles L; Boesch, Christophe; Leendertz, Fabian H

2009-04-01

New methods are required to increase our understanding of pathologic processes in wild mammals. We developed a noninvasive field method to estimate the body temperature of wild living chimpanzees habituated to humans, based on statistically fitting temperature decline of feces after defecation. The method was established with the use of control measures of human rectal temperature and subsequent changes in fecal temperature over time. The method was then applied to temperature data collected from wild chimpanzee feces. In humans, we found good correspondence between the temperature estimated by the method and the actual rectal temperature that was measured (maximum deviation 0.22 C). The method was successfully applied and the average estimated temperature of the chimpanzees was 37.2 C. This simple-to-use field method reliably estimates the body temperature of wild chimpanzees and probably also other large mammals.

Statistical Diversions

ERIC Educational Resources Information Center

Petocz, Peter; Sowey, Eric

2012-01-01

The term "data snooping" refers to the practice of choosing which statistical analyses to apply to a set of data after having first looked at those data. Data snooping contradicts a fundamental precept of applied statistics, that the scheme of analysis is to be planned in advance. In this column, the authors shall elucidate the…

The Statistical Interpretation of Classical Thermodynamic Heating and Expansion Processes

ERIC Educational Resources Information Center

Cartier, Stephen F.

2011-01-01

A statistical model has been developed and applied to interpret thermodynamic processes typically presented from the macroscopic, classical perspective. Through this model, students learn and apply the concepts of statistical mechanics, quantum mechanics, and classical thermodynamics in the analysis of the (i) constant volume heating, (ii)…

The Reliability of Panoramic Radiography Versus Cone Beam Computed Tomography when Evaluating the Distance to the Alveolar Nerve in the Site of Lateral Teeth.

PubMed

Česaitienė, Gabrielė; Česaitis, Kęstutis; Junevičius, Jonas; Venskutonis, Tadas

2017-07-04

BACKGROUND The aim of this study was to compare the reliability of panoramic radiography (PR) and cone beam computed tomography (CBCT) in the evaluation of the distance of the roots of lateral teeth to the inferior alveolar nerve canal (IANC). MATERIAL AND METHODS 100 PR and 100 CBCT images that met the selection criteria were selected from the database. In PR images, the distances were measured using an electronic caliper with 0.01 mm accuracy and white light x-ray film reviewer. Actual values of the measurements were calculated taking into consideration the magnification used in PR images (130%). Measurements on CBCT images were performed using i-CAT Vision software. Statistical data analysis was performed using R software and applying Welch's t-test and the Wilcoxon test. RESULTS There was no statistically significant difference in the mean distance from the root of the second premolar and the mesial and distal roots of the first molar to the IANC between PR and CBCT images. The difference in the mean distance from the mesial and distal roots of the second and the third molars to the IANC measured in PR and CBCT images was statistically significant. CONCLUSIONS PR may be uninformative or misleading when measuring the distance from the mesial and distal roots of the second and the third molars to the IANC.

The Reliability of Panoramic Radiography Versus Cone Beam Computed Tomography when Evaluating the Distance to the Alveolar Nerve in the Site of Lateral Teeth

PubMed Central

Česaitienė, Gabrielė; Česaitis, Kęstutis; Junevičius, Jonas; Venskutonis, Tadas

2017-01-01

Background The aim of this study was to compare the reliability of panoramic radiography (PR) and cone beam computed tomography (CBCT) in the evaluation of the distance of the roots of lateral teeth to the inferior alveolar nerve canal (IANC). Material/Methods 100 PR and 100 CBCT images that met the selection criteria were selected from the database. In PR images, the distances were measured using an electronic caliper with 0.01 mm accuracy and white light x-ray film reviewer. Actual values of the measurements were calculated taking into consideration the magnification used in PR images (130%). Measurements on CBCT images were performed using i-CAT Vision software. Statistical data analysis was performed using R software and applying Welch’s t-test and the Wilcoxon test. Results There was no statistically significant difference in the mean distance from the root of the second premolar and the mesial and distal roots of the first molar to the IANC between PR and CBCT images. The difference in the mean distance from the mesial and distal roots of the second and the third molars to the IANC measured in PR and CBCT images was statistically significant. Conclusions PR may be uninformative or misleading when measuring the distance from the mesial and distal roots of the second and the third molars to the IANC. PMID:28674379

Evidence and Clinical Trials.

NASA Astrophysics Data System (ADS)

Goodman, Steven N.

1989-11-01

This dissertation explores the use of a mathematical measure of statistical evidence, the log likelihood ratio, in clinical trials. The methods and thinking behind the use of an evidential measure are contrasted with traditional methods of analyzing data, which depend primarily on a p-value as an estimate of the statistical strength of an observed data pattern. It is contended that neither the behavioral dictates of Neyman-Pearson hypothesis testing methods, nor the coherency dictates of Bayesian methods are realistic models on which to base inference. The use of the likelihood alone is applied to four aspects of trial design or conduct: the calculation of sample size, the monitoring of data, testing for the equivalence of two treatments, and meta-analysis--the combining of results from different trials. Finally, a more general model of statistical inference, using belief functions, is used to see if it is possible to separate the assessment of evidence from our background knowledge. It is shown that traditional and Bayesian methods can be modeled as two ends of a continuum of structured background knowledge, methods which summarize evidence at the point of maximum likelihood assuming no structure, and Bayesian methods assuming complete knowledge. Both schools are seen to be missing a concept of ignorance- -uncommitted belief. This concept provides the key to understanding the problem of sampling to a foregone conclusion and the role of frequency properties in statistical inference. The conclusion is that statistical evidence cannot be defined independently of background knowledge, and that frequency properties of an estimator are an indirect measure of uncommitted belief. Several likelihood summaries need to be used in clinical trials, with the quantitative disparity between summaries being an indirect measure of our ignorance. This conclusion is linked with parallel ideas in the philosophy of science and cognitive psychology.

Treatment effects model for assessing disease management: measuring outcomes and strengthening program management.

PubMed

Wendel, Jeanne; Dumitras, Diana

2005-06-01

This paper describes an analytical methodology for obtaining statistically unbiased outcomes estimates for programs in which participation decisions may be correlated with variables that impact outcomes. This methodology is particularly useful for intraorganizational program evaluations conducted for business purposes. In this situation, data is likely to be available for a population of managed care members who are eligible to participate in a disease management (DM) program, with some electing to participate while others eschew the opportunity. The most pragmatic analytical strategy for in-house evaluation of such programs is likely to be the pre-intervention/post-intervention design in which the control group consists of people who were invited to participate in the DM program, but declined the invitation. Regression estimates of program impacts may be statistically biased if factors that impact participation decisions are correlated with outcomes measures. This paper describes an econometric procedure, the Treatment Effects model, developed to produce statistically unbiased estimates of program impacts in this type of situation. Two equations are estimated to (a) estimate the impacts of patient characteristics on decisions to participate in the program, and then (b) use this information to produce a statistically unbiased estimate of the impact of program participation on outcomes. This methodology is well-established in economics and econometrics, but has not been widely applied in the DM outcomes measurement literature; hence, this paper focuses on one illustrative application.

Study of photon correlation techniques for processing of laser velocimeter signals

NASA Technical Reports Server (NTRS)

Mayo, W. T., Jr.

1977-01-01

The objective was to provide the theory and a system design for a new type of photon counting processor for low level dual scatter laser velocimeter (LV) signals which would be capable of both the first order measurements of mean flow and turbulence intensity and also the second order time statistics: cross correlation auto correlation, and related spectra. A general Poisson process model for low level LV signals and noise which is valid from the photon-resolved regime all the way to the limiting case of nonstationary Gaussian noise was used. Computer simulation algorithms and higher order statistical moment analysis of Poisson processes were derived and applied to the analysis of photon correlation techniques. A system design using a unique dual correlate and subtract frequency discriminator technique is postulated and analyzed. Expectation analysis indicates that the objective measurements are feasible.

Effect of local and global geomagnetic activity on human cardiovascular homeostasis.

PubMed

Dimitrova, Svetla; Stoilova, Irina; Yanev, Toni; Cholakov, Ilia

2004-02-01

The authors investigated the effects of local and planetary geomagnetic activity on human physiology. They collected data in Sofia, Bulgaria, from a group of 86 volunteers during the periods of the autumnal and vernal equinoxes. They used the factors local/planetary geomagnetic activity, day of measurement, gender, and medication use to apply a four-factor multiple analysis of variance. They also used a post hoc analysis to establish the statistical significance of the differences between the average values of the measured physiological parameters in the separate factor levels. In addition, the authors performed correlation analysis between the physiological parameters examined and geophysical factors. The results revealed that geomagnetic changes had a statistically significant influence on arterial blood pressure. Participants expressed this reaction with weak local geomagnetic changes and when major and severe global geomagnetic storms took place.

Statistical Track-Before-Detect Methods Applied to Faint Optical Observations of Resident Space Objects

NASA Astrophysics Data System (ADS)

Fujimoto, K.; Yanagisawa, T.; Uetsuhara, M.

Automated detection and tracking of faint objects in optical, or bearing-only, sensor imagery is a topic of immense interest in space surveillance. Robust methods in this realm will lead to better space situational awareness (SSA) while reducing the cost of sensors and optics. They are especially relevant in the search for high area-to-mass ratio (HAMR) objects, as their apparent brightness can change significantly over time. A track-before-detect (TBD) approach has been shown to be suitable for faint, low signal-to-noise ratio (SNR) images of resident space objects (RSOs). TBD does not rely upon the extraction of feature points within the image based on some thresholding criteria, but rather directly takes as input the intensity information from the image file. Not only is all of the available information from the image used, TBD avoids the computational intractability of the conventional feature-based line detection (i.e., "string of pearls") approach to track detection for low SNR data. Implementation of TBD rooted in finite set statistics (FISST) theory has been proposed recently by Vo, et al. Compared to other TBD methods applied so far to SSA, such as the stacking method or multi-pass multi-period denoising, the FISST approach is statistically rigorous and has been shown to be more computationally efficient, thus paving the path toward on-line processing. In this paper, we intend to apply a multi-Bernoulli filter to actual CCD imagery of RSOs. The multi-Bernoulli filter can explicitly account for the birth and death of multiple targets in a measurement arc. TBD is achieved via a sequential Monte Carlo implementation. Preliminary results with simulated single-target data indicate that a Bernoulli filter can successfully track and detect objects with measurement SNR as low as 2.4. Although the advent of fast-cadence scientific CMOS sensors have made the automation of faint object detection a realistic goal, it is nonetheless a difficult goal, as measurements arcs in space surveillance are often both short and sparse. FISST methodologies have been applied to the general problem of SSA by many authors, but they generally focus on tracking scenarios with long arcs or assume that line detection is tractable. We will instead focus this work on estimating sensor-level kinematics of RSOs for low SNR too-short arc observations. Once said estimate is made available, track association and simultaneous initial orbit determination may be achieved via any number of proposed solutions to the too-short arc problem, such as those incorporating the admissible region. We show that the benefit of combining FISST-based TBD with too-short arc association goes both ways; i.e., the former provides consistent statistics regarding bearing-only measurements, whereas the latter makes better use of the precise dynamical models nominally applicable to RSOs in orbit determination.

Accounting for measurement reliability to improve the quality of inference in dental microhardness research: a worked example.

PubMed

Sever, Ivan; Klaric, Eva; Tarle, Zrinka

2016-07-01

Dental microhardness experiments are influenced by unobserved factors related to the varying tooth characteristics that affect measurement reproducibility. This paper explores the appropriate analytical tools for modeling different sources of unobserved variability to reduce the biases encountered and increase the validity of microhardness studies. The enamel microhardness of human third molars was measured by Vickers diamond. The effects of five bleaching agents-10, 16, and 30 % carbamide peroxide, and 25 and 38 % hydrogen peroxide-were examined, as well as the effect of artificial saliva and amorphous calcium phosphate. To account for both between- and within-tooth heterogeneity in evaluating treatment effects, the statistical analysis was performed in the mixed-effects framework, which also included the appropriate weighting procedure to adjust for confounding. The results were compared to those of the standard ANOVA model usually applied. The weighted mixed-effects model produced the parameter estimates of different magnitude and significance than the standard ANOVA model. The results of the former model were more intuitive, with more precise estimates and better fit. Confounding could seriously bias the study outcomes, highlighting the need for more robust statistical procedures in dental research that account for the measurement reliability. The presented framework is more flexible and informative than existing analytical techniques and may improve the quality of inference in dental research. Reported results could be misleading if underlying heterogeneity of microhardness measurements is not taken into account. The confidence in treatment outcomes could be increased by applying the framework presented.

Characterizing and locating air pollution sources in a complex industrial district using optical remote sensing technology and multivariate statistical modeling.

PubMed

Chang, Pao-Erh Paul; Yang, Jen-Chih Rena; Den, Walter; Wu, Chang-Fu

2014-09-01

Emissions of volatile organic compounds (VOCs) are most frequent environmental nuisance complaints in urban areas, especially where industrial districts are nearby. Unfortunately, identifying the responsible emission sources of VOCs is essentially a difficult task. In this study, we proposed a dynamic approach to gradually confine the location of potential VOC emission sources in an industrial complex, by combining multi-path open-path Fourier transform infrared spectrometry (OP-FTIR) measurement and the statistical method of principal component analysis (PCA). Close-cell FTIR was further used to verify the VOC emission source by measuring emitted VOCs from selected exhaust stacks at factories in the confined areas. Multiple open-path monitoring lines were deployed during a 3-month monitoring campaign in a complex industrial district. The emission patterns were identified and locations of emissions were confined by the wind data collected simultaneously. N,N-Dimethyl formamide (DMF), 2-butanone, toluene, and ethyl acetate with mean concentrations of 80.0 ± 1.8, 34.5 ± 0.8, 103.7 ± 2.8, and 26.6 ± 0.7 ppbv, respectively, were identified as the major VOC mixture at all times of the day around the receptor site. As the toxic air pollutant, the concentrations of DMF in air samples were found exceeding the ambient standard despite the path-average effect of OP-FTIR upon concentration levels. The PCA data identified three major emission sources, including PU coating, chemical packaging, and lithographic printing industries. Applying instrumental measurement and statistical modeling, this study has established a systematic approach for locating emission sources. Statistical modeling (PCA) plays an important role in reducing dimensionality of a large measured dataset and identifying underlying emission sources. Instrumental measurement, however, helps verify the outcomes of the statistical modeling. The field study has demonstrated the feasibility of using multi-path OP-FTIR measurement. The wind data incorporating with the statistical modeling (PCA) may successfully identify the major emission source in a complex industrial district.

Does daily nurse staffing match ward workload variability? Three hospitals' experiences.

PubMed

Gabbay, Uri; Bukchin, Michael

2009-01-01

Nurse shortage and rising healthcare resource burdens mean that appropriate workforce use is imperative. This paper aims to evaluate whether daily nursing staffing meets ward workload needs. Nurse attendance and daily nurses' workload capacity in three hospitals were evaluated. Statistical process control was used to evaluate intra-ward nurse workload capacity and day-to-day variations. Statistical process control is a statistics-based method for process monitoring that uses charts with predefined target measure and control limits. Standardization was performed for inter-ward analysis by converting ward-specific crude measures to ward-specific relative measures by dividing observed/expected. Two charts: acceptable and tolerable daily nurse workload intensity, were defined. Appropriate staffing indicators were defined as those exceeding predefined rates within acceptable and tolerable limits (50 percent and 80 percent respectively). A total of 42 percent of the overall days fell within acceptable control limits and 71 percent within tolerable control limits. Appropriate staffing indicators were met in only 33 percent of wards regarding acceptable nurse workload intensity and in only 45 percent of wards regarding tolerable workloads. The study work did not differentiate crude nurse attendance and it did not take into account patient severity since crude bed occupancy was used. Double statistical process control charts and certain staffing indicators were used, which is open to debate. Wards that met appropriate staffing indicators prove the method's feasibility. Wards that did not meet appropriate staffing indicators prove the importance and the need for process evaluations and monitoring. Methods presented for monitoring daily staffing appropriateness are simple to implement either for intra-ward day-to-day variation by using nurse workload capacity statistical process control charts or for inter-ward evaluation using standardized measure of nurse workload intensity. The real challenge will be to develop planning systems and implement corrective interventions such as dynamic and flexible daily staffing, which will face difficulties and barriers. The paper fulfils the need for workforce utilization evaluation. A simple method using available data for daily staffing appropriateness evaluation, which is easy to implement and operate, is presented. The statistical process control method enables intra-ward evaluation, while standardization by converting crude into relative measures enables inter-ward analysis. The staffing indicator definitions enable performance evaluation. This original study uses statistical process control to develop simple standardization methods and applies straightforward statistical tools. This method is not limited to crude measures, rather it uses weighted workload measures such as nursing acuity or weighted nurse level (i.e. grade/band).

A Ground Flash Fraction Retrieval Algorithm for GLM

NASA Technical Reports Server (NTRS)

Koshak, William J.

2010-01-01

A Bayesian inversion method is introduced for retrieving the fraction of ground flashes in a set of N lightning observed by a satellite lightning imager (such as the Geostationary Lightning Mapper, GLM). An exponential model is applied as a physically reasonable constraint to describe the measured lightning optical parameter distributions. Population statistics (i.e., the mean and variance) are invoked to add additional constraints to the retrieval process. The Maximum A Posteriori (MAP) solution is employed. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The approach is feasible for N greater than 2000, and retrieval errors decrease as N is increased.

Statistical study of generalized nonlinear phase step estimation methods in phase-shifting interferometry.

PubMed

Langoju, Rajesh; Patil, Abhijit; Rastogi, Pramod

2007-11-20

Signal processing methods based on maximum-likelihood theory, discrete chirp Fourier transform, and spectral estimation methods have enabled accurate measurement of phase in phase-shifting interferometry in the presence of nonlinear response of the piezoelectric transducer to the applied voltage. We present the statistical study of these generalized nonlinear phase step estimation methods to identify the best method by deriving the Cramér-Rao bound. We also address important aspects of these methods for implementation in practical applications and compare the performance of the best-identified method with other bench marking algorithms in the presence of harmonics and noise.

Entropy in sound and vibration: towards a new paradigm.

PubMed

Le Bot, A

2017-01-01

This paper describes a discussion on the method and the status of a statistical theory of sound and vibration, called statistical energy analysis (SEA). SEA is a simple theory of sound and vibration in elastic structures that applies when the vibrational energy is diffusely distributed. We show that SEA is a thermodynamical theory of sound and vibration, based on a law of exchange of energy analogous to the Clausius principle. We further investigate the notion of entropy in this context and discuss its meaning. We show that entropy is a measure of information lost in the passage from the classical theory of sound and vibration and SEA, its thermodynamical counterpart.

A comparison of two non-thrust mobilization techniques applied to the C7 segment in patients with restricted and painful cervical rotation.

PubMed

Creighton, Doug; Gruca, Mark; Marsh, Douglas; Murphy, Nancy

2014-11-01

Cervical mobilization and manipulation have been shown to improve cervical range of motion and pain. Rotatory thrust manipulation applied to the lower cervical segments is associated with controversy and the potential for eliciting adverse reactions (AR). The purpose of this clinical trial was to describe two translatory non-thrust mobilization techniques and evaluate their effect on cervical pain, motion restriction, and whether any adverse effects were reported when applied to the C7 segment. This trial included 30 participants with painful and restricted cervical rotation. Participants were randomly assigned to receive one of the two mobilization techniques. Active cervical rotation and pain intensity measurements were recorded pre- and post-intervention. Within group comparisons were determined using the Wilcoxon signed-rank test and between group comparisons were analyzed using the Mann-Whitney U test. Significance was set at P = 0.05. Thirty participants were evaluated immediately after one of the two mobilization techniques was applied. There was a statistically significant difference (improvement) for active cervical rotation after application of the C7 facet distraction technique for both right (P = 0.022) and left (P = 0.022) rotation. Statistically significant improvement was also found for the C7 facet gliding technique for both right (P = 0.022) and left rotation (P = 0.020). Pain reduction was statistically significant for both right and left rotation after application of both techniques. Both mobilization techniques produced similar positive effects and one was not statistically superior to the other. A single application of both C7 mobilization techniques improved active cervical rotation, reduced perceived pain, and did not produce any AR in 30 patients with neck pain and movement limitation. These two non-thrust techniques may offer clinicians an additional safe and effective manual intervention for patients with limited and painful cervical rotation. A more robust experimental design is recommended to further examine these and similar cervical translatory mobilization techniques.

Nonlinear analysis of pupillary dynamics.

PubMed

Onorati, Francesco; Mainardi, Luca Tommaso; Sirca, Fabiola; Russo, Vincenzo; Barbieri, Riccardo

2016-02-01

Pupil size reflects autonomic response to different environmental and behavioral stimuli, and its dynamics have been linked to other autonomic correlates such as cardiac and respiratory rhythms. The aim of this study is to assess the nonlinear characteristics of pupil size of 25 normal subjects who participated in a psychophysiological experimental protocol with four experimental conditions, namely “baseline”, “anger”, “joy”, and “sadness”. Nonlinear measures, such as sample entropy, correlation dimension, and largest Lyapunov exponent, were computed on reconstructed signals of spontaneous fluctuations of pupil dilation. Nonparametric statistical tests were performed on surrogate data to verify that the nonlinear measures are an intrinsic characteristic of the signals. We then developed and applied a piecewise linear regression model to detrended fluctuation analysis (DFA). Two joinpoints and three scaling intervals were identified: slope α0, at slow time scales, represents a persistent nonstationary long-range correlation, whereas α1 and α2, at middle and fast time scales, respectively, represent long-range power-law correlations, similarly to DFA applied to heart rate variability signals. Of the computed complexity measures, α0 showed statistically significant differences among experimental conditions (p<0.001). Our results suggest that (a) pupil size at constant light condition is characterized by nonlinear dynamics, (b) three well-defined and distinct long-memory processes exist at different time scales, and (c) autonomic stimulation is partially reflected in nonlinear dynamics. (c) autonomic stimulation is partially reflected in nonlinear dynamics.

Benchmarking patient improvement in physical therapy with data envelopment analysis.

PubMed

Friesner, Daniel; Neufelder, Donna; Raisor, Janet; Khayum, Mohammed

2005-01-01

The purpose of this article is to present a case study that documents how management science techniques (in particular data envelopment analysis) can be applied to performance improvement initiatives in an inpatient physical therapy setting. The data used in this study consist of patients referred for inpatient physical therapy following total knee replacement surgery (at a medium-sized medical facility in the Midwestern USA) during the fiscal year 2002. Data envelopment analysis (DEA) was applied to determine the efficiency of treatment, as well as to identify benchmarks for potential patient improvement. Statistical trends in the benchmarking and efficiency results were subsequently analyzed using non-parametric and parametric methods. Our analysis indicated that the rehabilitation process was largely effective in terms of providing consistent, quality care, as more than half of the patients in our study achieved the maximum amount of rehabilitation possible given available inputs. Among patients that did not achieve maximum results, most could obtain increases in the degree of flexion gain and reductions in the degree of knee extension. The study is retrospective in nature, and is not based on clinical trial or experimental data. Additionally, DEA results are inherently sensitive to sampling: adding or subtracting individuals from the sample may change the baseline against which efficiency and rehabilitation potential are measured. As such, therapists using this approach must ensure that the sample is representative of the general population, and must not contain significant measurement error. Third, individuals who choose total knee arthroplasty will incur a transient disability. However, this population does not generally fit the World Health Organization International Classification of Functioning, Disability and Health definition of disability if the surgical procedure is successful. Since the study focuses on the outcomes of physical therapy, range of motion measurements and circumferential measurements were chosen as opposed to the more global measures of functional independence such as mobility, transfers and stair climbing. Applying this technique to data on patients with different disabilities (or the same disability with other outcome variables, such as Functional Independence Measure scores) may give dissimilar results. This case study provides an example of how one can apply quantitative management science tools in a manner that is both tractable and intuitive to the practising therapist, who may not have an extensive background in quantitative performance improvement or statistics. DEA has not been applied to rehabilitation, especially in the case where managers have limited data available.

Statistical physics studies of multilayer adsorption isotherm in food materials and pore size distribution

NASA Astrophysics Data System (ADS)

Aouaini, F.; Knani, S.; Ben Yahia, M.; Ben Lamine, A.

2015-08-01

Water sorption isotherms of foodstuffs are very important in different areas of food science engineering such as for design, modeling and optimization of many processes. The equilibrium moisture content is an important parameter in models used to predict changes in the moisture content of a product during storage. A formulation of multilayer model with two energy levels was based on statistical physics and theoretical considerations. Thanks to the grand canonical ensemble in statistical physics. Some physicochemical parameters related to the adsorption process were introduced in the analytical model expression. The data tabulated in literature of water adsorption at different temperatures on: chickpea seeds, lentil seeds, potato and on green peppers were described applying the most popular models applied in food science. We also extend the study to the newest proposed model. It is concluded that among studied models the proposed model seems to be the best for description of data in the whole range of relative humidity. By using our model, we were able to determine the thermodynamic functions. The measurement of desorption isotherms, in particular a gas over a solid porous, allows access to the distribution of pore size PSD.

Predicting future protection of respirator users: Statistical approaches and practical implications.

PubMed

Hu, Chengcheng; Harber, Philip; Su, Jing

2016-01-01

The purpose of this article is to describe a statistical approach for predicting a respirator user's fit factor in the future based upon results from initial tests. A statistical prediction model was developed based upon joint distribution of multiple fit factor measurements over time obtained from linear mixed effect models. The model accounts for within-subject correlation as well as short-term (within one day) and longer-term variability. As an example of applying this approach, model parameters were estimated from a research study in which volunteers were trained by three different modalities to use one of two types of respirators. They underwent two quantitative fit tests at the initial session and two on the same day approximately six months later. The fitted models demonstrated correlation and gave the estimated distribution of future fit test results conditional on past results for an individual worker. This approach can be applied to establishing a criterion value for passing an initial fit test to provide reasonable likelihood that a worker will be adequately protected in the future; and to optimizing the repeat fit factor test intervals individually for each user for cost-effective testing.

Method to measure efficiently rare fluctuations of turbulence intensity for turbulent-laminar transitions in pipe flows

NASA Astrophysics Data System (ADS)

Nemoto, Takahiro; Alexakis, Alexandros

2018-02-01

The fluctuations of turbulence intensity in a pipe flow around the critical Reynolds number is difficult to study but important because they are related to turbulent-laminar transitions. We here propose a rare-event sampling method to study such fluctuations in order to measure the time scale of the transition efficiently. The method is composed of two parts: (i) the measurement of typical fluctuations (the bulk part of an accumulative probability function) and (ii) the measurement of rare fluctuations (the tail part of the probability function) by employing dynamics where a feedback control of the Reynolds number is implemented. We apply this method to a chaotic model of turbulent puffs proposed by Barkley and confirm that the time scale of turbulence decay increases super exponentially even for high Reynolds numbers up to Re =2500 , where getting enough statistics by brute-force calculations is difficult. The method uses a simple procedure of changing Reynolds number that can be applied even to experiments.

Measurements in Transitional Boundary Layers Under High Free-Stream Turbulence and Strong Acceleration Conditions

NASA Technical Reports Server (NTRS)

Volino, Ralph J.; Simon, Terrence W.

1995-01-01

Measurements from transitional, heated boundary layers along a concave-curved test wall are presented and discussed. A boundary layer subject to low free-stream turbulence intensity (FSTI), which contains stationary streamwise (Gortler) vortices, is documented. The low FSTI measurements are followed by measurements in boundary layers subject to high (initially 8%) free-stream turbulence intensity and moderate to strong streamwise acceleration. Conditions were chosen to simulate those present on the downstream half of the pressure side of a gas turbine airfoil. Mean flow characteristics as well as turbulence statistics, including the turbulent shear stress, turbulent heat flux, and turbulent Prandtl number, are documented. A technique called "octant analysis" is introduced and applied to several cases from the literature as well as to data from the present study. Spectral analysis was applied to describe the effects of turbulence scales of different sizes during transition. To the authors'knowledge, this is the first detailed documentation of boundary layer transition under such high free-stream turbulence conditions.

Calibration methodology for proportional counters applied to yield measurements of a neutron burst.

PubMed

Tarifeño-Saldivia, Ariel; Mayer, Roberto E; Pavez, Cristian; Soto, Leopoldo

2014-01-01

This paper introduces a methodology for the yield measurement of a neutron burst using neutron proportional counters. This methodology is to be applied when single neutron events cannot be resolved in time by nuclear standard electronics, or when a continuous current cannot be measured at the output of the counter. The methodology is based on the calibration of the counter in pulse mode, and the use of a statistical model to estimate the number of detected events from the accumulated charge resulting from the detection of the burst of neutrons. The model is developed and presented in full detail. For the measurement of fast neutron yields generated from plasma focus experiments using a moderated proportional counter, the implementation of the methodology is herein discussed. An experimental verification of the accuracy of the methodology is presented. An improvement of more than one order of magnitude in the accuracy of the detection system is obtained by using this methodology with respect to previous calibration methods.

Multivariate statistical data analysis methods for detecting baroclinic wave interactions in the thermally driven rotating annulus

NASA Astrophysics Data System (ADS)

von Larcher, Thomas; Harlander, Uwe; Alexandrov, Kiril; Wang, Yongtai

2010-05-01

Experiments on baroclinic wave instabilities in a rotating cylindrical gap have been long performed, e.g., to unhide regular waves of different zonal wave number, to better understand the transition to the quasi-chaotic regime, and to reveal the underlying dynamical processes of complex wave flows. We present the application of appropriate multivariate data analysis methods on time series data sets acquired by the use of non-intrusive measurement techniques of a quite different nature. While the high accurate Laser-Doppler-Velocimetry (LDV ) is used for measurements of the radial velocity component at equidistant azimuthal positions, a high sensitive thermographic camera measures the surface temperature field. The measurements are performed at particular parameter points, where our former studies show that kinds of complex wave patterns occur [1, 2]. Obviously, the temperature data set has much more information content as the velocity data set due to the particular measurement techniques. Both sets of time series data are analyzed by using multivariate statistical techniques. While the LDV data sets are studied by applying the Multi-Channel Singular Spectrum Analysis (M - SSA), the temperature data sets are analyzed by applying the Empirical Orthogonal Functions (EOF ). Our goal is (a) to verify the results yielded with the analysis of the velocity data and (b) to compare the data analysis methods. Therefor, the temperature data are processed in a way to become comparable to the LDV data, i.e. reducing the size of the data set in such a manner that the temperature measurements would imaginary be performed at equidistant azimuthal positions only. This approach initially results in a great loss of information. But applying the M - SSA to the reduced temperature data sets enable us to compare the methods. [1] Th. von Larcher and C. Egbers, Experiments on transitions of baroclinic waves in a differentially heated rotating annulus, Nonlinear Processes in Geophysics, 2005, 12, 1033-1041, NPG Print: ISSN 1023-5809, NPG Online: ISSN 1607-7946 [2] U. Harlander, Th. von Larcher, Y. Wang and C. Egbers, PIV- and LDV-measurements of baroclinic wave interactions in a thermally driven rotating annulus, Experiments in Fluids, 2009, DOI: 10.1007/s00348-009-0792-5

Applied Behavior Analysis and Statistical Process Control?

ERIC Educational Resources Information Center

Hopkins, B. L.

1995-01-01

Incorporating statistical process control (SPC) methods into applied behavior analysis is discussed. It is claimed that SPC methods would likely reduce applied behavior analysts' intimate contacts with problems and would likely yield poor treatment and research decisions. Cases and data presented by Pfadt and Wheeler (1995) are cited as examples.…

The Application of Statistics Education Research in My Classroom

ERIC Educational Resources Information Center

Jordan, Joy

2007-01-01

A collaborative, statistics education research project (Lovett, 2001) is discussed. Some results of the project were applied in the computer lab sessions of my elementary statistics course. I detail the process of applying these research results, as well as the use of knowledge surveys. Furthermore, I give general suggestions to teachers who want…

Applying Statistical Process Control to Clinical Data: An Illustration.

ERIC Educational Resources Information Center

Pfadt, Al; And Others

1992-01-01

Principles of statistical process control are applied to a clinical setting through the use of control charts to detect changes, as part of treatment planning and clinical decision-making processes. The logic of control chart analysis is derived from principles of statistical inference. Sample charts offer examples of evaluating baselines and…

A Realistic Experimental Design and Statistical Analysis Project

ERIC Educational Resources Information Center

Muske, Kenneth R.; Myers, John A.

2007-01-01

A realistic applied chemical engineering experimental design and statistical analysis project is documented in this article. This project has been implemented as part of the professional development and applied statistics courses at Villanova University over the past five years. The novel aspects of this project are that the students are given a…

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

Understanding growers' decisions to manage invasive pathogens at the farm level.

PubMed

Breukers, Annemarie; van Asseldonk, Marcel; Bremmer, Johan; Beekman, Volkert

2012-06-01

Globalization causes plant production systems to be increasingly threatened by invasive pests and pathogens. Much research is devoted to support management of these risks. Yet, the role of growers' perceptions and behavior in risk management has remained insufficiently analyzed. This article aims to fill this gap by addressing risk management of invasive pathogens from a sociopsychological perspective. An analytical framework based on the Theory of Planned Behavior was used to explain growers' decisions on voluntary risk management measures. Survey information from 303 Dutch horticultural growers was statistically analyzed, including regression and cluster analysis. It appeared that growers were generally willing to apply risk management measures, and that poor risk management was mainly due to perceived barriers, such as high costs and doubts regarding efficacy of management measures. The management measures applied varied considerably among growers, depending on production sector and farm-specific circumstances. Growers' risk perception was found to play a role in their risk management, although the causal relation remained unclear. These results underscore the need to apply a holistic perspective to farm level management of invasive pathogen risk, considering the entire package of management measures and accounting for sector- and farm-specific circumstances. Moreover, they demonstrate that invasive pathogen risk management can benefit from a multidisciplinary approach that incorporates growers' perceptions and behavior.

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…

Assessing Clinical Faculty Understanding of Statistical Terms Used to Measure Treatment Effects and Their Application to Teaching.

PubMed

Hazelton, Lara; Allen, Michael; MacLeod, Tanya; LeBlanc, Constance; Boudreau, Michelle

2016-01-01

Understanding of statistical terms used to measure treatment effect is important for evidence-informed medical teaching and practice. We explored knowledge of these terms among clinical faculty who instruct and mentor a continuum of medical learners to inform medical faculty learning needs. This was a mixed methods study that used a questionnaire to measure a health professional's understanding of measures of treatment effect and a focus group to explore perspectives on learning, applying, and teaching these terms. We analyzed questionnaire data using descriptive statistics and focus group data using thematic analysis. We analyzed responses from clinical faculty who were physicians and completed all sections of the questionnaire (n = 137). Overall, approximately 55% were highly confident in their understanding of statistical terms; self-reported understanding was highest for number needed to treat (77%). Only 26% of respondents correctly responded to all comprehension questions; however, 80% correctly responded to at least one of these questions. There was a significant association among self-reported understanding and ability to correctly calculate terms. A focus group with clinical/medical faculty (n = 4) revealed themes of mentorship, support and resources, and beliefs about the value of statistical literacy. We found that half of clinical faculty members are highly confident in their understanding of relative and absolute terms. Despite the limitations of self-assessment data, our study provides some evidence that self-assessment can be reliable. Recognizing that faculty development is not mandatory for clinical faculty in many centers, and the notion that faculty may benefit from mentorship in critical appraisal topics, it may be appropriate to first engage and support influential clinical faculty rather than using a broad strategy to achieve universal statistical literacy. Second, senior leadership in medical education should support continuous learning by providing paid, protected time for faculty to incorporate evidence in their teaching.

Cosmology constraints from shear peak statistics in Dark Energy Survey Science Verification data

NASA Astrophysics Data System (ADS)

Kacprzak, T.; Kirk, D.; Friedrich, O.; Amara, A.; Refregier, A.; Marian, L.; Dietrich, J. P.; Suchyta, E.; Aleksić, J.; Bacon, D.; Becker, M. R.; Bonnett, C.; Bridle, S. L.; Chang, C.; Eifler, T. F.; Hartley, W. G.; Huff, E. M.; Krause, E.; MacCrann, N.; Melchior, P.; Nicola, A.; Samuroff, S.; Sheldon, E.; Troxel, M. A.; Weller, J.; Zuntz, J.; Abbott, T. M. C.; Abdalla, F. B.; Armstrong, R.; Benoit-Lévy, A.; Bernstein, G. M.; Bernstein, R. A.; Bertin, E.; Brooks, D.; Burke, D. L.; Carnero Rosell, A.; Carrasco Kind, M.; Carretero, J.; Castander, F. J.; Crocce, M.; D'Andrea, C. B.; da Costa, L. N.; Desai, S.; Diehl, H. T.; Evrard, A. E.; Neto, A. Fausti; Flaugher, B.; Fosalba, P.; Frieman, J.; Gerdes, D. W.; Goldstein, D. A.; Gruen, D.; Gruendl, R. A.; Gutierrez, G.; Honscheid, K.; Jain, B.; James, D. J.; Jarvis, M.; Kuehn, K.; Kuropatkin, N.; Lahav, O.; Lima, M.; March, M.; Marshall, J. L.; Martini, P.; Miller, C. J.; Miquel, R.; Mohr, J. J.; Nichol, R. C.; Nord, B.; Plazas, A. A.; Romer, A. K.; Roodman, A.; Rykoff, E. S.; Sanchez, E.; Scarpine, V.; Schubnell, M.; Sevilla-Noarbe, I.; Smith, R. C.; Soares-Santos, M.; Sobreira, F.; Swanson, M. E. C.; Tarle, G.; Thomas, D.; Vikram, V.; Walker, A. R.; Zhang, Y.; DES Collaboration

2016-12-01

Shear peak statistics has gained a lot of attention recently as a practical alternative to the two-point statistics for constraining cosmological parameters. We perform a shear peak statistics analysis of the Dark Energy Survey (DES) Science Verification (SV) data, using weak gravitational lensing measurements from a 139 deg2 field. We measure the abundance of peaks identified in aperture mass maps, as a function of their signal-to-noise ratio, in the signal-to-noise range 04 would require significant corrections, which is why we do not include them in our analysis. We compare our results to the cosmological constraints from the two-point analysis on the SV field and find them to be in good agreement in both the central value and its uncertainty. We discuss prospects for future peak statistics analysis with upcoming DES data.