Some Statistical Properties of Tonality, 1650-1900

ERIC Educational Resources Information Center

White, Christopher Wm.

2013-01-01

This dissertation investigates the statistical properties present within corpora of common practice music, involving a data set of more than 8,000 works spanning from 1650 to 1900, and focusing specifically on the properties of the chord progressions contained therein. In the first chapter, methodologies concerning corpus analysis are presented…

USAF (United States Air Force) Stability and Control DATCOM (Data Compendium)

DTIC Science & Technology

1978-04-01

regression analysis involves the study of a group of variables to determine their effect on a given parameter. Because of the empirical nature of this...regression analysis of mathematical statistics. In general, a regression analysis involves the study of a group of variables to determine their effect on a...Excperiment, OSR TN 58-114, MIT Fluid Dynamics Research Group Rapt. 57-5, 1957. (U) 90. Kennet, H., and Ashley, H.: Review of Unsteady Aerodynamic Studies in

Meta- and statistical analysis of single-case intervention research data: quantitative gifts and a wish list.

PubMed

Kratochwill, Thomas R; Levin, Joel R

2014-04-01

In this commentary, we add to the spirit of the articles appearing in the special series devoted to meta- and statistical analysis of single-case intervention-design data. Following a brief discussion of historical factors leading to our initial involvement in statistical analysis of such data, we discuss: (a) the value added by including statistical-analysis recommendations in the What Works Clearinghouse Standards for single-case intervention designs; (b) the importance of visual analysis in single-case intervention research, along with the distinctive role that could be played by single-case effect-size measures; and (c) the elevated internal validity and statistical-conclusion validity afforded by the incorporation of various forms of randomization into basic single-case design structures. For the future, we envision more widespread application of quantitative analyses, as critical adjuncts to visual analysis, in both primary single-case intervention research studies and literature reviews in the behavioral, educational, and health sciences. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Statistical power and optimal design in experiments in which samples of participants respond to samples of stimuli.

PubMed

Westfall, Jacob; Kenny, David A; Judd, Charles M

2014-10-01

Researchers designing experiments in which a sample of participants responds to a sample of stimuli are faced with difficult questions about optimal study design. The conventional procedures of statistical power analysis fail to provide appropriate answers to these questions because they are based on statistical models in which stimuli are not assumed to be a source of random variation in the data, models that are inappropriate for experiments involving crossed random factors of participants and stimuli. In this article, we present new methods of power analysis for designs with crossed random factors, and we give detailed, practical guidance to psychology researchers planning experiments in which a sample of participants responds to a sample of stimuli. We extensively examine 5 commonly used experimental designs, describe how to estimate statistical power in each, and provide power analysis results based on a reasonable set of default parameter values. We then develop general conclusions and formulate rules of thumb concerning the optimal design of experiments in which a sample of participants responds to a sample of stimuli. We show that in crossed designs, statistical power typically does not approach unity as the number of participants goes to infinity but instead approaches a maximum attainable power value that is possibly small, depending on the stimulus sample. We also consider the statistical merits of designs involving multiple stimulus blocks. Finally, we provide a simple and flexible Web-based power application to aid researchers in planning studies with samples of stimuli.

Examination of two methods for statistical analysis of data with magnitude and direction emphasizing vestibular research applications

NASA Technical Reports Server (NTRS)

Calkins, D. S.

1998-01-01

When the dependent (or response) variable response variable in an experiment has direction and magnitude, one approach that has been used for statistical analysis involves splitting magnitude and direction and applying univariate statistical techniques to the components. However, such treatment of quantities with direction and magnitude is not justifiable mathematically and can lead to incorrect conclusions about relationships among variables and, as a result, to flawed interpretations. This note discusses a problem with that practice and recommends mathematically correct procedures to be used with dependent variables that have direction and magnitude for 1) computation of mean values, 2) statistical contrasts of and confidence intervals for means, and 3) correlation methods.

A statistical analysis of seat belt effectiveness in 1973-1975 model cars involved in towaway crashes. Volume 1

DOT National Transportation Integrated Search

1976-09-01

Standardized injury rates and seat belt effectiveness measures are derived from a probability sample of towaway accidents involving 1973-1975 model cars. The data were collected in five different geographic regions. Weighted sample size available for...

Disordered gambling, type of gambling and gambling involvement in the British Gambling Prevalence Survey 2007

PubMed Central

Nelson, Sarah E.; LaBrie, Richard A.; Shaffer, Howard J.

2011-01-01

Background: The purpose of this study was to examine the relationships between types of gambling and disordered gambling, with and without controlling for gambling involvement (i.e. the number of types of games with which respondents were involved during the past 12 months). Methods: We completed a secondary data analysis of the 2007 British Gambling Prevalence Survey (BGPS), which collected data in England, Scotland and Wales between September 2006 and March 2007. The sample included 9003 residents, aged 16 or older, recruited from 10 144 randomly selected addresses. 5832 households contributed at least one participant. Post-facto weighting to produce a nationally representative sample yielded 8968 observations. The BGPS included four primary types of measures: participation in gambling (during the past 12 months and during the past 7 days), disordered gambling assessments, attitudes toward gambling and descriptive information. Results: Statistically controlling for gambling involvement substantially reduced or eliminated all statistically significant relationships between types of gambling and disordered gambling. Conclusions: Gambling involvement is an important predictor of disordered gambling status. Our analysis indicates that greater gambling involvement better characterizes disordered gambling than does any specific type of gambling. PMID:19892851

Learning and understanding the Kruskal-Wallis one-way analysis-of-variance-by-ranks test for differences among three or more independent groups.

PubMed

Chan, Y; Walmsley, R P

1997-12-01

When several treatment methods are available for the same problem, many clinicians are faced with the task of deciding which treatment to use. Many clinicians may have conducted informal "mini-experiments" on their own to determine which treatment is best suited for the problem. These results are usually not documented or reported in a formal manner because many clinicians feel that they are "statistically challenged." Another reason may be because clinicians do not feel they have controlled enough test conditions to warrant analysis. In this update, a statistic is described that does not involve complicated statistical assumptions, making it a simple and easy-to-use statistical method. This update examines the use of two statistics and does not deal with other issues that could affect clinical research such as issues affecting credibility. For readers who want a more in-depth examination of this topic, references have been provided. The Kruskal-Wallis one-way analysis-of-variance-by-ranks test (or H test) is used to determine whether three or more independent groups are the same or different on some variable of interest when an ordinal level of data or an interval or ratio level of data is available. A hypothetical example will be presented to explain when and how to use this statistic, how to interpret results using the statistic, the advantages and disadvantages of the statistic, and what to look for in a written report. This hypothetical example will involve the use of ratio data to demonstrate how to choose between using the nonparametric H test and the more powerful parametric F test.

The Co-Emergence of Aggregate and Modelling Reasoning

ERIC Educational Resources Information Center

Aridor, Keren; Ben-Zvi, Dani

2017-01-01

This article examines how two processes--reasoning with statistical modelling of a real phenomenon and aggregate reasoning--can co-emerge. We focus in this case study on the emergent reasoning of two fifth graders (aged 10) involved in statistical data analysis, informal inference, and modelling activities using TinkerPlots™. We describe nine…

The prior statistics of object colors.

PubMed

Koenderink, Jan J

2010-02-01

The prior statistics of object colors is of much interest because extensive statistical investigations of reflectance spectra reveal highly non-uniform structure in color space common to several very different databases. This common structure is due to the visual system rather than to the statistics of environmental structure. Analysis involves an investigation of the proper sample space of spectral reflectance factors and of the statistical consequences of the projection of spectral reflectances on the color solid. Even in the case of reflectance statistics that are translationally invariant with respect to the wavelength dimension, the statistics of object colors is highly non-uniform. The qualitative nature of this non-uniformity is due to trichromacy.

Information Technology.

ERIC Educational Resources Information Center

Marcum, Deanna; Boss, Richard

1983-01-01

Relates office automation to its application in libraries, discussing computer software packages for microcomputers performing tasks involved in word processing, accounting, statistical analysis, electronic filing cabinets, and electronic mail systems. (EJS)

Integrating Statistical Mechanics with Experimental Data from the Rotational-Vibrational Spectrum of HCl into the Physical Chemistry Laboratory

ERIC Educational Resources Information Center

Findley, Bret R.; Mylon, Steven E.

2008-01-01

We introduce a computer exercise that bridges spectroscopy and thermodynamics using statistical mechanics and the experimental data taken from the commonly used laboratory exercise involving the rotational-vibrational spectrum of HCl. Based on the results from the analysis of their HCl spectrum, students calculate bulk thermodynamic properties…

Scaling up to address data science challenges

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

Wendelberger, Joanne R.

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

Scaling up to address data science challenges

DOE PAGES

Wendelberger, Joanne R.

2017-04-27

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

Exceedance statistics of accelerations resulting from thruster firings on the Apollo-Soyuz mission

NASA Technical Reports Server (NTRS)

Fichtl, G. H.; Holland, R. L.

1981-01-01

Spacecraft acceleration resulting from firings of vernier control system thrusters is an important consideration in the design, planning, execution and post-flight analysis of laboratory experiments in space. In particular, scientists and technologists involved with the development of experiments to be performed in space in many instances required statistical information on the magnitude and rate of occurrence of spacecraft accelerations. Typically, these accelerations are stochastic in nature, so that it is useful to characterize these accelerations in statistical terms. Statistics of spacecraft accelerations are summarized.

Parricide: An Empirical Analysis of 24 Years of U.S. Data

ERIC Educational Resources Information Center

Heide, Kathleen M.; Petee, Thomas A.

2007-01-01

Empirical analysis of homicides in which children have killed parents has been limited. The most comprehensive statistical analysis involving parents as victims was undertaken by Heide and used Supplementary Homicide Report (SHR) data for the 10-year period 1977 to 1986. This article provides an updated examination of characteristics of victims,…

Analysis of High-Throughput ELISA Microarray Data

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

White, Amanda M.; Daly, Don S.; Zangar, Richard C.

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

The statistical analysis of global climate change studies

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

Hardin, J.W.

1992-01-01

The focus of this work is to contribute to the enhancement of the relationship between climatologists and statisticians. The analysis of global change data has been underway for many years by atmospheric scientists. Much of this analysis includes a heavy reliance on statistics and statistical inference. Some specific climatological analyses are presented and the dependence on statistics is documented before the analysis is undertaken. The first problem presented involves the fluctuation-dissipation theorem and its application to global climate models. This problem has a sound theoretical niche in the literature of both climate modeling and physics, but a statistical analysis inmore » which the data is obtained from the model to show graphically the relationship has not been undertaken. It is under this motivation that the author presents this problem. A second problem concerning the standard errors in estimating global temperatures is purely statistical in nature although very little materials exists for sampling on such a frame. This problem not only has climatological and statistical ramifications, but political ones as well. It is planned to use these results in a further analysis of global warming using actual data collected on the earth. In order to simplify the analysis of these problems, the development of a computer program, MISHA, is presented. This interactive program contains many of the routines, functions, graphics, and map projections needed by the climatologist in order to effectively enter the arena of data visualization.« less

Generalized Factorial Moments

NASA Astrophysics Data System (ADS)

Bialas, A.

2004-02-01

It is shown that the method of eliminating the statistical fluctuations from event-by-event analysis proposed recently by Fu and Liu can be rewritten in a compact form involving the generalized factorial moments.

New Statistical Probe into the Decline of Daily Newspaper Household Penetration.

ERIC Educational Resources Information Center

Alperstein, Gerald

From 1950 to 1970, daily newspaper household penetration (DNHP) levels dropped from 1.24 to 0.99 in the United States. This paper describes some of the variables involved in this decline and outlines a market-by-market statistical analysis of the relationship between the penetration levels of daily newspapers and other forms of mass media. From…

SimHap GUI: an intuitive graphical user interface for genetic association analysis.

PubMed

Carter, Kim W; McCaskie, Pamela A; Palmer, Lyle J

2008-12-25

Researchers wishing to conduct genetic association analysis involving single nucleotide polymorphisms (SNPs) or haplotypes are often confronted with the lack of user-friendly graphical analysis tools, requiring sophisticated statistical and informatics expertise to perform relatively straightforward tasks. Tools, such as the SimHap package for the R statistics language, provide the necessary statistical operations to conduct sophisticated genetic analysis, but lacks a graphical user interface that allows anyone but a professional statistician to effectively utilise the tool. We have developed SimHap GUI, a cross-platform integrated graphical analysis tool for conducting epidemiological, single SNP and haplotype-based association analysis. SimHap GUI features a novel workflow interface that guides the user through each logical step of the analysis process, making it accessible to both novice and advanced users. This tool provides a seamless interface to the SimHap R package, while providing enhanced functionality such as sophisticated data checking, automated data conversion, and real-time estimations of haplotype simulation progress. SimHap GUI provides a novel, easy-to-use, cross-platform solution for conducting a range of genetic and non-genetic association analyses. This provides a free alternative to commercial statistics packages that is specifically designed for genetic association analysis.

A critique of Rasch residual fit statistics.

PubMed

Karabatsos, G

2000-01-01

In test analysis involving the Rasch model, a large degree of importance is placed on the "objective" measurement of individual abilities and item difficulties. The degree to which the objectivity properties are attained, of course, depends on the degree to which the data fit the Rasch model. It is therefore important to utilize fit statistics that accurately and reliably detect the person-item response inconsistencies that threaten the measurement objectivity of persons and items. Given this argument, it is somewhat surprising that there is far more emphasis placed in the objective measurement of person and items than there is in the measurement quality of Rasch fit statistics. This paper provides a critical analysis of the residual fit statistics of the Rasch model, arguably the most often used fit statistics, in an effort to illustrate that the task of Rasch fit analysis is not as simple and straightforward as it appears to be. The faulty statistical properties of the residual fit statistics do not allow either a convenient or a straightforward approach to Rasch fit analysis. For instance, given a residual fit statistic, the use of a single minimum critical value for misfit diagnosis across different testing situations, where the situations vary in sample and test properties, leads to both the overdetection and underdetection of misfit. To improve this situation, it is argued that psychometricians need to implement residual-free Rasch fit statistics that are based on the number of Guttman response errors, or use indices that are statistically optimal in detecting measurement disturbances.

Using Data Analysis to Explore Class Enrollment.

ERIC Educational Resources Information Center

Davis, Gretchen

1990-01-01

Describes classroom activities and shows that statistics is a practical tool for solving real problems. Presents a histogram, a stem plot, and a box plot to compare data involving class enrollments. (YP)

Family Early Literacy Practices Questionnaire: A Validation Study for a Spanish-Speaking Population

ERIC Educational Resources Information Center

Lewis, Kandia

2012-01-01

The purpose of the current study was to evaluate the psychometric validity of a Spanish translated version of a family involvement questionnaire (the FELP) using a mixed-methods design. Thus, statistical analyses (i.e., factor analysis, reliability analysis, and item analysis) and qualitative analyses (i.e., focus group data) were assessed.…

Exceedance statistics of accelerations resulting from thruster firings on the Apollo-Soyuz mission

NASA Technical Reports Server (NTRS)

Fichtl, G. H.; Holland, R. L.

1983-01-01

Spacecraft acceleration resulting from firings of vernier control system thrusters is an important consideration in the design, planning, execution and post-flight analysis of laboratory experiments in space. In particular, scientists and technologists involved with the development of experiments to be performed in space in many instances required statistical information on the magnitude and rate of occurrence of spacecraft accelerations. Typically, these accelerations are stochastic in nature, so that it is useful to characterize these accelerations in statistical terms. Statistics of spacecraft accelerations are summarized. Previously announced in STAR as N82-12127

Robustness of Type I Error and Power in Set Correlation Analysis of Contingency Tables.

ERIC Educational Resources Information Center

Cohen, Jacob; Nee, John C. M.

1990-01-01

The analysis of contingency tables via set correlation allows the assessment of subhypotheses involving contrast functions of the categories of the nominal scales. The robustness of such methods with regard to Type I error and statistical power was studied via a Monte Carlo experiment. (TJH)

How Miniature/Microminiature (2M) Repair Capabilities Can Reduce the Impact of No Evidence of Failure (NEOF) Among Repairables on the Navy’s Operations and Maintenance Account

DTIC Science & Technology

1988-06-01

and PCBs. The pilot program involved screening, testing , and repairing of EMs/PCBs for both COMNAVSEASYSCOM and Commander, Naval Electronic Systems...were chosen from the Support and Test Equipment Engineering Program (STEEP) tests rformed by"IMA San Diego duringl987. A statistical analysis and a Level...were chosen from the Support and Test Equipment Engineering Program (STEEP) tests performed by SIMA San Diego during 1987. A statistical analysis and a

State Alcohol-Impaired-Driving Estimates

MedlinePlus

... For more information on multiple imputation see NHTSA’s Technical Report (DOT HS 809 403, www- nrd. nhtsa. ... involvement); and NHTSA’s National Center for Statistics and Analysis 1200 New Jersey Avenue SE., Washington, DC 20590 ...

Injuries Associated With Hazards Involving Motor Vehicle Power Windows

DOT National Transportation Integrated Search

1997-05-01

National Highway Traffic Safety Administration's (NHTSA) National Center for : Statistics and Analysis (NCSA) recently completed a study of data from the : Consumer Product Safety Commission's (CPSC) National Electronic Injury : Surveillance System (...

An inferentialist perspective on the coordination of actions and reasons involved in making a statistical inference

NASA Astrophysics Data System (ADS)

Bakker, Arthur; Ben-Zvi, Dani; Makar, Katie

2017-12-01

To understand how statistical and other types of reasoning are coordinated with actions to reduce uncertainty, we conducted a case study in vocational education that involved statistical hypothesis testing. We analyzed an intern's research project in a hospital laboratory in which reducing uncertainties was crucial to make a valid statistical inference. In his project, the intern, Sam, investigated whether patients' blood could be sent through pneumatic post without influencing the measurement of particular blood components. We asked, in the process of making a statistical inference, how are reasons and actions coordinated to reduce uncertainty? For the analysis, we used the semantic theory of inferentialism, specifically, the concept of webs of reasons and actions—complexes of interconnected reasons for facts and actions; these reasons include premises and conclusions, inferential relations, implications, motives for action, and utility of tools for specific purposes in a particular context. Analysis of interviews with Sam, his supervisor and teacher as well as video data of Sam in the classroom showed that many of Sam's actions aimed to reduce variability, rule out errors, and thus reduce uncertainties so as to arrive at a valid inference. Interestingly, the decisive factor was not the outcome of a t test but of the reference change value, a clinical chemical measure of analytic and biological variability. With insights from this case study, we expect that students can be better supported in connecting statistics with context and in dealing with uncertainty.

Exploratory Visual Analysis of Statistical Results from Microarray Experiments Comparing High and Low Grade Glioma

PubMed Central

Reif, David M.; Israel, Mark A.; Moore, Jason H.

2007-01-01

The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA) software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a flexible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occuring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profiles of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM) tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specific gene expression patterns having both statistical and biological significance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the flexibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at http://www.epistasis.org. PMID:19390666

Spectral Analysis of B Stars: An Application of Bayesian Statistics

NASA Astrophysics Data System (ADS)

Mugnes, J.-M.; Robert, C.

2012-12-01

To better understand the processes involved in stellar physics, it is necessary to obtain accurate stellar parameters (effective temperature, surface gravity, abundances…). Spectral analysis is a powerful tool for investigating stars, but it is also vital to reduce uncertainties at a decent computational cost. Here we present a spectral analysis method based on a combination of Bayesian statistics and grids of synthetic spectra obtained with TLUSTY. This method simultaneously constrains the stellar parameters by using all the lines accessible in observed spectra and thus greatly reduces uncertainties and improves the overall spectrum fitting. Preliminary results are shown using spectra from the Observatoire du Mont-Mégantic.

An empirical analysis of the distribution of overshoots in a stationary Gaussian stochastic process

NASA Technical Reports Server (NTRS)

Carter, M. C.; Madison, M. W.

1973-01-01

The frequency distribution of overshoots in a stationary Gaussian stochastic process is analyzed. The primary processes involved in this analysis are computer simulation and statistical estimation. Computer simulation is used to simulate stationary Gaussian stochastic processes that have selected autocorrelation functions. An analysis of the simulation results reveals a frequency distribution for overshoots with a functional dependence on the mean and variance of the process. Statistical estimation is then used to estimate the mean and variance of a process. It is shown that for an autocorrelation function, the mean and the variance for the number of overshoots, a frequency distribution for overshoots can be estimated.

On some stochastic formulations and related statistical moments of pharmacokinetic models.

PubMed

Matis, J H; Wehrly, T E; Metzler, C M

1983-02-01

This paper presents the deterministic and stochastic model for a linear compartment system with constant coefficients, and it develops expressions for the mean residence times (MRT) and the variances of the residence times (VRT) for the stochastic model. The expressions are relatively simple computationally, involving primarily matrix inversion, and they are elegant mathematically, in avoiding eigenvalue analysis and the complex domain. The MRT and VRT provide a set of new meaningful response measures for pharmacokinetic analysis and they give added insight into the system kinetics. The new analysis is illustrated with an example involving the cholesterol turnover in rats.

Comments of statistical issue in numerical modeling for underground nuclear test monitoring

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

Nicholson, W.L.; Anderson, K.K.

1993-03-01

The Symposium concluded with prepared summaries by four experts in the involved disciplines. These experts made no mention of statistics and/or the statistical content of issues. The first author contributed an extemporaneous statement at the Symposium because there are important issues associated with conducting and evaluating numerical modeling that are familiar to statisticians and often treated successfully by them. This note expands upon these extemporaneous remarks. Statistical ideas may be helpful in resolving some numerical modeling issues. Specifically, we comment first on the role of statistical design/analysis in the quantification process to answer the question ``what do we know aboutmore » the numerical modeling of underground nuclear tests?`` and second on the peculiar nature of uncertainty analysis for situations involving numerical modeling. The simulations described in the workshop, though associated with topic areas, were basically sets of examples. Each simulation was tuned towards agreeing with either empirical evidence or an expert`s opinion of what empirical evidence would be. While the discussions were reasonable, whether the embellishments were correct or a forced fitting of reality is unclear and illustrates that ``simulation is easy.`` We also suggest that these examples of simulation are typical and the questions concerning the legitimacy and the role of knowing the reality are fair, in general, with respect to simulation. The answers will help us understand why ``prediction is difficult.``« less

Applied statistical training to strengthen analysis and health research capacity in Rwanda.

PubMed

Thomson, Dana R; Semakula, Muhammed; Hirschhorn, Lisa R; Murray, Megan; Ndahindwa, Vedaste; Manzi, Anatole; Mukabutera, Assumpta; Karema, Corine; Condo, Jeanine; Hedt-Gauthier, Bethany

2016-09-29

To guide efficient investment of limited health resources in sub-Saharan Africa, local researchers need to be involved in, and guide, health system and policy research. While extensive survey and census data are available to health researchers and program officers in resource-limited countries, local involvement and leadership in research is limited due to inadequate experience, lack of dedicated research time and weak interagency connections, among other challenges. Many research-strengthening initiatives host prolonged fellowships out-of-country, yet their approaches have not been evaluated for effectiveness in involvement and development of local leadership in research. We developed, implemented and evaluated a multi-month, deliverable-driven, survey analysis training based in Rwanda to strengthen skills of five local research leaders, 15 statisticians, and a PhD candidate. Research leaders applied with a specific research question relevant to country challenges and committed to leading an analysis to publication. Statisticians with prerequisite statistical training and experience with a statistical software applied to participate in class-based trainings and complete an assigned analysis. Both statisticians and research leaders were provided ongoing in-country mentoring for analysis and manuscript writing. Participants reported a high level of skill, knowledge and collaborator development from class-based trainings and out-of-class mentorship that were sustained 1 year later. Five of six manuscripts were authored by multi-institution teams and submitted to international peer-reviewed scientific journals, and three-quarters of the participants mentored others in survey data analysis or conducted an additional survey analysis in the year following the training. Our model was effective in utilizing existing survey data and strengthening skills among full-time working professionals without disrupting ongoing work commitments and using few resources. Critical to our success were a transparent, robust application process and time limited training supplemented by ongoing, in-country mentoring toward manuscript deliverables that were led by Rwanda's health research leaders.

42 CFR 405.1064 - ALJ decisions involving statistical samples.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 42 Public Health 2 2011-10-01 2011-10-01 false ALJ decisions involving statistical samples. 405... Medicare Coverage Policies § 405.1064 ALJ decisions involving statistical samples. When an appeal from the QIC involves an overpayment issue and the QIC used a statistical sample in reaching its...

42 CFR 405.1064 - ALJ decisions involving statistical samples.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 42 Public Health 2 2010-10-01 2010-10-01 false ALJ decisions involving statistical samples. 405... Medicare Coverage Policies § 405.1064 ALJ decisions involving statistical samples. When an appeal from the QIC involves an overpayment issue and the QIC used a statistical sample in reaching its...

A computational framework for estimating statistical power and planning hypothesis-driven experiments involving one-dimensional biomechanical continua.

PubMed

Pataky, Todd C; Robinson, Mark A; Vanrenterghem, Jos

2018-01-03

Statistical power assessment is an important component of hypothesis-driven research but until relatively recently (mid-1990s) no methods were available for assessing power in experiments involving continuum data and in particular those involving one-dimensional (1D) time series. The purpose of this study was to describe how continuum-level power analyses can be used to plan hypothesis-driven biomechanics experiments involving 1D data. In particular, we demonstrate how theory- and pilot-driven 1D effect modeling can be used for sample-size calculations for both single- and multi-subject experiments. For theory-driven power analysis we use the minimum jerk hypothesis and single-subject experiments involving straight-line, planar reaching. For pilot-driven power analysis we use a previously published knee kinematics dataset. Results show that powers on the order of 0.8 can be achieved with relatively small sample sizes, five and ten for within-subject minimum jerk analysis and between-subject knee kinematics, respectively. However, the appropriate sample size depends on a priori justifications of biomechanical meaning and effect size. The main advantage of the proposed technique is that it encourages a priori justification regarding the clinical and/or scientific meaning of particular 1D effects, thereby robustly structuring subsequent experimental inquiry. In short, it shifts focus from a search for significance to a search for non-rejectable hypotheses. Copyright © 2017 Elsevier Ltd. All rights reserved.

Collagen morphology and texture analysis: from statistics to classification

PubMed Central

Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.

2013-01-01

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage. PMID:23846580

A Meta-Analysis of Referential Communication Studies: A Computer Readable Literature Review.

ERIC Educational Resources Information Center

Dickson, W. Patrick; Moskoff, Mary

A computer-assisted analysis of studies on referential communication (giving directions/explanations) located 66 reports involving 80 experiments, 114 referential tasks, and over 6,200 individuals. The studies were entered into a statistical software package system (SPSS) and analyzed for characteristics of the subjects and experimental designs,…

The Analysis of Completely Randomized Factorial Experiments When Observations Are Lost at Random.

ERIC Educational Resources Information Center

Hummel, Thomas J.

An investigation was conducted of the characteristics of two estimation procedures and corresponding test statistics used in the analysis of completely randomized factorial experiments when observations are lost at random. For one estimator, contrast coefficients for cell means did not involve the cell frequencies. For the other, contrast…

New dimensions from statistical graphics for GIS (geographic information system) analysis and interpretation

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

McCord, R.A.; Olson, R.J.

1988-01-01

Environmental research and assessment activities at Oak Ridge National Laboratory (ORNL) include the analysis of spatial and temporal patterns of ecosystem response at a landscape scale. Analysis through use of geographic information system (GIS) involves an interaction between the user and thematic data sets frequently expressed as maps. A portion of GIS analysis has a mathematical or statistical aspect, especially for the analysis of temporal patterns. ARC/INFO is an excellent tool for manipulating GIS data and producing the appropriate map graphics. INFO also has some limited ability to produce statistical tabulation. At ORNL we have extended our capabilities by graphicallymore » interfacing ARC/INFO and SAS/GRAPH to provide a combined mapping and statistical graphics environment. With the data management, statistical, and graphics capabilities of SAS added to ARC/INFO, we have expanded the analytical and graphical dimensions of the GIS environment. Pie or bar charts, frequency curves, hydrographs, or scatter plots as produced by SAS can be added to maps from attribute data associated with ARC/INFO coverages. Numerous, small, simplified graphs can also become a source of complex map ''symbols.'' These additions extend the dimensions of GIS graphics to include time, details of the thematic composition, distribution, and interrelationships. 7 refs., 3 figs.« less

An audit of the statistics and the comparison with the parameter in the population

NASA Astrophysics Data System (ADS)

Bujang, Mohamad Adam; Sa'at, Nadiah; Joys, A. Reena; Ali, Mariana Mohamad

2015-10-01

The sufficient sample size that is needed to closely estimate the statistics for particular parameters are use to be an issue. Although sample size might had been calculated referring to objective of the study, however, it is difficult to confirm whether the statistics are closed with the parameter for a particular population. All these while, guideline that uses a p-value less than 0.05 is widely used as inferential evidence. Therefore, this study had audited results that were analyzed from various sub sample and statistical analyses and had compared the results with the parameters in three different populations. Eight types of statistical analysis and eight sub samples for each statistical analysis were analyzed. Results found that the statistics were consistent and were closed to the parameters when the sample study covered at least 15% to 35% of population. Larger sample size is needed to estimate parameter that involve with categorical variables compared with numerical variables. Sample sizes with 300 to 500 are sufficient to estimate the parameters for medium size of population.

Developing a suitable model for supplier selection based on supply chain risks: an empirical study from Iranian pharmaceutical companies.

PubMed

Mehralian, Gholamhossein; Rajabzadeh Gatari, Ali; Morakabati, Mohadese; Vatanpour, Hossein

2012-01-01

The supply chain represents the critical link between the development of new product and the market in pharmaceutical industry. Over the years, improvements made in supply chain operations have focused largely on ways to reduce cost and gain efficiencies in scale. In addition, powerful regulatory and market forces have provided new incentives for pharmaceutical firms to basically rethink the way they produce and distribute products, and also to re-imagine the role of the supply chain in driving strategic growth, brand differentiation and economic value in the health continuum. The purpose of this paper is to formulate basic factors involved in risk analysis of pharmaceutical industry, and also determine the effective factors involved in suppliers selection and their priorities. This paper is based on the results of literature review, experts' opinion acquisition, statistical analysis and also using MADM models on data gathered from distributed questionnaires. The model consists of the following steps and components: first factors involved in to supply chain risks are determined. Based on them a framework is considered. According the result of statistical analysis and MADM models the risk factors are formulated. The paper determines the main components and influenceial factors involving in the supply chain risks. Results showed that delivery risk can make an important contribution to mitigate the risk of pharmaceutical industry.

Developing a Suitable Model for Supplier Selection Based on Supply Chain Risks: An Empirical Study from Iranian Pharmaceutical Companies

PubMed Central

Mehralian, Gholamhossein; Rajabzadeh Gatari, Ali; Morakabati, Mohadese; Vatanpour, Hossein

2012-01-01

The supply chain represents the critical link between the development of new product and the market in pharmaceutical industry. Over the years, improvements made in supply chain operations have focused largely on ways to reduce cost and gain efficiencies in scale. In addition, powerful regulatory and market forces have provided new incentives for pharmaceutical firms to basically rethink the way they produce and distribute products, and also to re-imagine the role of the supply chain in driving strategic growth, brand differentiation and economic value in the health continuum. The purpose of this paper is to formulate basic factors involved in risk analysis of pharmaceutical industry, and also determine the effective factors involved in suppliers selection and their priorities. This paper is based on the results of literature review, experts’ opinion acquisition, statistical analysis and also using MADM models on data gathered from distributed questionnaires. The model consists of the following steps and components: first factors involved in to supply chain risks are determined. Based on them a framework is considered. According the result of statistical analysis and MADM models the risk factors are formulated. The paper determines the main components and influenceial factors involving in the supply chain risks. Results showed that delivery risk can make an important contribution to mitigate the risk of pharmaceutical industry. PMID:24250442

SimHap GUI: An intuitive graphical user interface for genetic association analysis

PubMed Central

Carter, Kim W; McCaskie, Pamela A; Palmer, Lyle J

2008-01-01

Background Researchers wishing to conduct genetic association analysis involving single nucleotide polymorphisms (SNPs) or haplotypes are often confronted with the lack of user-friendly graphical analysis tools, requiring sophisticated statistical and informatics expertise to perform relatively straightforward tasks. Tools, such as the SimHap package for the R statistics language, provide the necessary statistical operations to conduct sophisticated genetic analysis, but lacks a graphical user interface that allows anyone but a professional statistician to effectively utilise the tool. Results We have developed SimHap GUI, a cross-platform integrated graphical analysis tool for conducting epidemiological, single SNP and haplotype-based association analysis. SimHap GUI features a novel workflow interface that guides the user through each logical step of the analysis process, making it accessible to both novice and advanced users. This tool provides a seamless interface to the SimHap R package, while providing enhanced functionality such as sophisticated data checking, automated data conversion, and real-time estimations of haplotype simulation progress. Conclusion SimHap GUI provides a novel, easy-to-use, cross-platform solution for conducting a range of genetic and non-genetic association analyses. This provides a free alternative to commercial statistics packages that is specifically designed for genetic association analysis. PMID:19109877

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

NASA Technical Reports Server (NTRS)

Djorgovski, George

1993-01-01

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multiparameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resource.

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

NASA Technical Reports Server (NTRS)

Djorgovski, Stanislav

1992-01-01

The existing and forthcoming data bases from NASA missions contain an abundance of information whose complexity cannot be efficiently tapped with simple statistical techniques. Powerful multivariate statistical methods already exist which can be used to harness much of the richness of these data. Automatic classification techniques have been developed to solve the problem of identifying known types of objects in multi parameter data sets, in addition to leading to the discovery of new physical phenomena and classes of objects. We propose an exploratory study and integration of promising techniques in the development of a general and modular classification/analysis system for very large data bases, which would enhance and optimize data management and the use of human research resources.

SAFER, an Analysis Method of Quantitative Proteomic Data, Reveals New Interactors of the C. elegans Autophagic Protein LGG-1.

PubMed

Yi, Zhou; Manil-Ségalen, Marion; Sago, Laila; Glatigny, Annie; Redeker, Virginie; Legouis, Renaud; Mucchielli-Giorgi, Marie-Hélène

2016-05-06

Affinity purifications followed by mass spectrometric analysis are used to identify protein-protein interactions. Because quantitative proteomic data are noisy, it is necessary to develop statistical methods to eliminate false-positives and identify true partners. We present here a novel approach for filtering false interactors, named "SAFER" for mass Spectrometry data Analysis by Filtering of Experimental Replicates, which is based on the reproducibility of the replicates and the fold-change of the protein intensities between bait and control. To identify regulators or targets of autophagy, we characterized the interactors of LGG1, a ubiquitin-like protein involved in autophagosome formation in C. elegans. LGG-1 partners were purified by affinity, analyzed by nanoLC-MS/MS mass spectrometry, and quantified by a label-free proteomic approach based on the mass spectrometric signal intensity of peptide precursor ions. Because the selection of confident interactions depends on the method used for statistical analysis, we compared SAFER with several statistical tests and different scoring algorithms on this set of data. We show that SAFER recovers high-confidence interactors that have been ignored by the other methods and identified new candidates involved in the autophagy process. We further validated our method on a public data set and conclude that SAFER notably improves the identification of protein interactors.

Reproducible research in vadose zone sciences

USDA-ARS?s Scientific Manuscript database

A significant portion of present-day soil and Earth science research is computational, involving complex data analysis pipelines, advanced mathematical and statistical models, and sophisticated computer codes. Opportunities for scientific progress are greatly diminished if reproducing and building o...

Lymph node ratio may predict relapse free survival and overall survival in patients with stage II & III colorectal carcinoma.

PubMed

Zekri, Jamal; Ahmad, Imran; Fawzy, Ehab; Elkhodary, Tawfik R; Al-Gahmi, Aboelkhair; Hassouna, Ashraf; El Sayed, Mohamed E; Ur Rehman, Jalil; Karim, Syed M; Bin Sadiq, Bakr

2015-01-01

Lymph node ratio (LNR) defined as the number of lymph nodes (LNs) involved with metastases divided by number of LNs examined, has been shown to be an independent prognostic factor in breast, stomach and various other solid tumors. Its significance as a prognostic determinant in colorectal cancer (CRC) is still under investigation. This study investigated the prognostic value of LNR in patients with resected CRC. We retrospectively ex- amined 145 patients with stage II & III CRC diagnosed and treated at a single institution during 9 years pe- riod. Patients were grouped according to LNR in three groups. Group 1; LNR < 0.05, Group 2; LNR = 0.05-0.19 & Group 3 > 0.19. Chi square, life table analysis and multivariate Cox regression were used for statistical analysis. On multivariate analysis, number of involved LNs (NILN) (HR = 1.15, 95% CI 1.055-1.245; P = 0.001) and pathological T stage (P = 0.002) were statistically significant predictors of relapse free survival (RFS). LNR as a continuous variable (but not as a categorical variable) was statistically significant predictor of RFS (P = 0.02). LNR was also a statistically significant predictor of overall survival (OS) (P = 0.02). LNR may predict RFS and OS in patients with resected stage II & III CRC. Studies with larger cohorts and longer follow up are needed to further examine and validate theprognostic value of LNR.

Use of Statistical Analyses in the Ophthalmic Literature

PubMed Central

Lisboa, Renato; Meira-Freitas, Daniel; Tatham, Andrew J.; Marvasti, Amir H.; Sharpsten, Lucie; Medeiros, Felipe A.

2014-01-01

Purpose To identify the most commonly used statistical analyses in the ophthalmic literature and to determine the likely gain in comprehension of the literature that readers could expect if they were to sequentially add knowledge of more advanced techniques to their statistical repertoire. Design Cross-sectional study Methods All articles published from January 2012 to December 2012 in Ophthalmology, American Journal of Ophthalmology and Archives of Ophthalmology were reviewed. A total of 780 peer-reviewed articles were included. Two reviewers examined each article and assigned categories to each one depending on the type of statistical analyses used. Discrepancies between reviewers were resolved by consensus. Main Outcome Measures Total number and percentage of articles containing each category of statistical analysis were obtained. Additionally we estimated the accumulated number and percentage of articles that a reader would be expected to be able to interpret depending on their statistical repertoire. Results Readers with little or no statistical knowledge would be expected to be able to interpret the statistical methods presented in only 20.8% of articles. In order to understand more than half (51.4%) of the articles published, readers were expected to be familiar with at least 15 different statistical methods. Knowledge of 21 categories of statistical methods was necessary to comprehend 70.9% of articles, while knowledge of more than 29 categories was necessary to comprehend more than 90% of articles. Articles in retina and glaucoma subspecialties showed a tendency for using more complex analysis when compared to cornea. Conclusions Readers of clinical journals in ophthalmology need to have substantial knowledge of statistical methodology to understand the results of published studies in the literature. The frequency of use of complex statistical analyses also indicates that those involved in the editorial peer-review process must have sound statistical knowledge in order to critically appraise articles submitted for publication. The results of this study could provide guidance to direct the statistical learning of clinical ophthalmologists, researchers and educators involved in the design of courses for residents and medical students. PMID:24612977

DNA sequence-based comparative studies between non-extremophile and extremophile organisms with implications in exobiology

NASA Astrophysics Data System (ADS)

Holden, Todd; Marchese, P.; Tremberger, G., Jr.; Cheung, E.; Subramaniam, R.; Sullivan, R.; Schneider, P.; Flamholz, A.; Lieberman, D.; Cheung, T.

2008-08-01

We have characterized function related DNA sequences of various organisms using informatics techniques, including fractal dimension calculation, nucleotide and multi-nucleotide statistics, and sequence fluctuation analysis. Our analysis shows trends which differentiate extremophile from non-extremophile organisms, which could be reproduced in extraterrestrial life. Among the systems studied are radiation repair genes, genes involved in thermal shocks, and genes involved in drug resistance. We also evaluate sequence level changes that have occurred during short term evolution (several thousand generations) under extreme conditions.

An Overview of Interrater Agreement on Likert Scales for Researchers and Practitioners

PubMed Central

O'Neill, Thomas A.

2017-01-01

Applications of interrater agreement (IRA) statistics for Likert scales are plentiful in research and practice. IRA may be implicated in job analysis, performance appraisal, panel interviews, and any other approach to gathering systematic observations. Any rating system involving subject-matter experts can also benefit from IRA as a measure of consensus. Further, IRA is fundamental to aggregation in multilevel research, which is becoming increasingly common in order to address nesting. Although, several technical descriptions of a few specific IRA statistics exist, this paper aims to provide a tractable orientation to common IRA indices to support application. The introductory overview is written with the intent of facilitating contrasts among IRA statistics by critically reviewing equations, interpretations, strengths, and weaknesses. Statistics considered include rwg, rwg*, r′wg, rwg(p), average deviation (AD), awg, standard deviation (Swg), and the coefficient of variation (CVwg). Equations support quick calculation and contrasting of different agreement indices. The article also includes a “quick reference” table and three figures in order to help readers identify how IRA statistics differ and how interpretations of IRA will depend strongly on the statistic employed. A brief consideration of recommended practices involving statistical and practical cutoff standards is presented, and conclusions are offered in light of the current literature. PMID:28553257

Compression Algorithm Analysis of In-Situ (S)TEM Video: Towards Automatic Event Detection and Characterization

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

Teuton, Jeremy R.; Griswold, Richard L.; Mehdi, Beata L.

Precise analysis of both (S)TEM images and video are time and labor intensive processes. As an example, determining when crystal growth and shrinkage occurs during the dynamic process of Li dendrite deposition and stripping involves manually scanning through each frame in the video to extract a specific set of frames/images. For large numbers of images, this process can be very time consuming, so a fast and accurate automated method is desirable. Given this need, we developed software that uses analysis of video compression statistics for detecting and characterizing events in large data sets. This software works by converting the datamore » into a series of images which it compresses into an MPEG-2 video using the open source “avconv” utility [1]. The software does not use the video itself, but rather analyzes the video statistics from the first pass of the video encoding that avconv records in the log file. This file contains statistics for each frame of the video including the frame quality, intra-texture and predicted texture bits, forward and backward motion vector resolution, among others. In all, avconv records 15 statistics for each frame. By combining different statistics, we have been able to detect events in various types of data. We have developed an interactive tool for exploring the data and the statistics that aids the analyst in selecting useful statistics for each analysis. Going forward, an algorithm for detecting and possibly describing events automatically can be written based on statistic(s) for each data type.« less

Statistical methods for astronomical data with upper limits. I - Univariate distributions

NASA Technical Reports Server (NTRS)

Feigelson, E. D.; Nelson, P. I.

1985-01-01

The statistical treatment of univariate censored data is discussed. A heuristic derivation of the Kaplan-Meier maximum-likelihood estimator from first principles is presented which results in an expression amenable to analytic error analysis. Methods for comparing two or more censored samples are given along with simple computational examples, stressing the fact that most astronomical problems involve upper limits while the standard mathematical methods require lower limits. The application of univariate survival analysis to six data sets in the recent astrophysical literature is described, and various aspects of the use of survival analysis in astronomy, such as the limitations of various two-sample tests and the role of parametric modelling, are discussed.

Protein Sectors: Statistical Coupling Analysis versus Conservation

PubMed Central

Teşileanu, Tiberiu; Colwell, Lucy J.; Leibler, Stanislas

2015-01-01

Statistical coupling analysis (SCA) is a method for analyzing multiple sequence alignments that was used to identify groups of coevolving residues termed “sectors”. The method applies spectral analysis to a matrix obtained by combining correlation information with sequence conservation. It has been asserted that the protein sectors identified by SCA are functionally significant, with different sectors controlling different biochemical properties of the protein. Here we reconsider the available experimental data and note that it involves almost exclusively proteins with a single sector. We show that in this case sequence conservation is the dominating factor in SCA, and can alone be used to make statistically equivalent functional predictions. Therefore, we suggest shifting the experimental focus to proteins for which SCA identifies several sectors. Correlations in protein alignments, which have been shown to be informative in a number of independent studies, would then be less dominated by sequence conservation. PMID:25723535

The analysis of influence of individual and environmental factors on 2-wheeled users' injuries.

PubMed

Marković, Nenad; Pešić, Dalibor R; Antić, Boris; Vujanić, Milan

2016-08-17

Powered 2-wheeled motor vehicles (PTWs) are one of the most vulnerable categories of road users. Bearing that fact in mind, we have researched the effects of individual and environmental factors on the severity and type of injuries of PTW users. The aim was to recognize the circumstances that cause these accidents and take some preventive actions that would improve the level of road safety for PTWs. In the period from 2001 to 2010, an analysis of 139 road accidents involving PTWs was made by the Faculty of Transport and Traffic Engineering in Belgrade. The effects of both individual (age, gender, etc.) and environmental factors (place of an accident, time of day, etc.) on the cause of accidents and severity and type of injuries of PTWs are reported in this article. Analyses of these effects were conducted using logistic regression, chi-square tests, and Pearson's correlation. Factors such as categories of road users, pavement conditions, place of accident, age, and time of day have a statistically significant effect on PTW injuries, whereas other factors (gender, road type; that is, straight or curvy) do not. The article also defines the interdependence of the occurrence of particular injuries at certain speeds. The results show that if PTW users died of a head injury, these were usually concurrent with chest injuries, injuries to internal organs, and limb injuries. It has been shown that there is a high degree of influence of individual factors on the occurrence of accidents involving 2-wheelers (PTWs/bicycles) but with no statistically significant relation. Establishing the existence of such conditionalities enables identifying and defining factors that have an impact on the occurrence of traffic accidents involving bicyclists or PTWs. Such a link between individual factors and the occurrence of accidents makes it possible for system managers to take appropriate actions aimed at certain categories of 2-wheelers in order to reduce casualties in a particular area. The analysis showed that most of the road factors do not have a statistically significant effect on either category of 2-wheeler. Namely, the logistic regression analysis showed that there is a statistically significant effect of the place of accident on the occurrence of accidents involving bicyclists.

Classification Based on Hierarchical Linear Models: The Need for Incorporation of Social Contexts in Classification Analysis

ERIC Educational Resources Information Center

Vaughn, Brandon K.; Wang, Qui

2009-01-01

Many areas in educational and psychological research involve the use of classification statistical analysis. For example, school districts might be interested in attaining variables that provide optimal prediction of school dropouts. In psychology, a researcher might be interested in the classification of a subject into a particular psychological…

A Meta-Analysis of the Effects of Computer Technology on School Students' Mathematics Learning

ERIC Educational Resources Information Center

Li, Qing; Ma, Xin

2010-01-01

This study examines the impact of computer technology (CT) on mathematics education in K-12 classrooms through a systematic review of existing literature. A meta-analysis of 85 independent effect sizes extracted from 46 primary studies involving a total of 36,793 learners indicated statistically significant positive effects of CT on mathematics…

Not the Norm: The Potential of Tree Analysis of Performance Data from Students in a Foundation Mathematics Module

ERIC Educational Resources Information Center

Kirby, Nicola; Dempster, Edith

2015-01-01

Quantitative methods of data analysis usually involve inferential statistics, and are not well known for their ability to reflect the intricacies of a diverse student population. The South African tertiary education sector is characterised by extreme inequality and diversity. Foundation programmes address issues of inequality of access by…

Differences in Temperature Changes in Premature Infants During Invasive Procedures in Incubators and Radiant Warmers.

PubMed

Handhayanti, Ludwy; Rustina, Yeni; Budiati, Tri

Premature infants tend to lose heat quickly. This loss can be aggravated when they have received an invasive procedure involving a venous puncture. This research uses crossover design by conducting 2 intervention tests to compare 2 different treatments on the same sample. This research involved 2 groups with 18 premature infants in each. The process of data analysis used a statistical independent t test. Interventions conducted in an open incubator showed a p value of .001 which statistically related to heat loss in premature infants. In contrast, the radiant warmer p value of .001 statistically referred to a different range of heat gain before and after the venous puncture was given. The radiant warmer saved the premature infant from hypothermia during the invasive procedure. However, it is inadvisable for routine care of newborn infants since it can increase insensible water loss.

Illustrating the practice of statistics

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

Hamada, Christina A; Hamada, Michael S

2009-01-01

The practice of statistics involves analyzing data and planning data collection schemes to answer scientific questions. Issues often arise with the data that must be dealt with and can lead to new procedures. In analyzing data, these issues can sometimes be addressed through the statistical models that are developed. Simulation can also be helpful in evaluating a new procedure. Moreover, simulation coupled with optimization can be used to plan a data collection scheme. The practice of statistics as just described is much more than just using a statistical package. In analyzing the data, it involves understanding the scientific problem andmore » incorporating the scientist's knowledge. In modeling the data, it involves understanding how the data were collected and accounting for limitations of the data where possible. Moreover, the modeling is likely to be iterative by considering a series of models and evaluating the fit of these models. Designing a data collection scheme involves understanding the scientist's goal and staying within hislher budget in terms of time and the available resources. Consequently, a practicing statistician is faced with such tasks and requires skills and tools to do them quickly. We have written this article for students to provide a glimpse of the practice of statistics. To illustrate the practice of statistics, we consider a problem motivated by some precipitation data that our relative, Masaru Hamada, collected some years ago. We describe his rain gauge observational study in Section 2. We describe modeling and an initial analysis of the precipitation data in Section 3. In Section 4, we consider alternative analyses that address potential issues with the precipitation data. In Section 5, we consider the impact of incorporating additional infonnation. We design a data collection scheme to illustrate the use of simulation and optimization in Section 6. We conclude this article in Section 7 with a discussion.« less

Consequences of common data analysis inaccuracies in CNS trauma injury basic research.

PubMed

Burke, Darlene A; Whittemore, Scott R; Magnuson, David S K

2013-05-15

The development of successful treatments for humans after traumatic brain or spinal cord injuries (TBI and SCI, respectively) requires animal research. This effort can be hampered when promising experimental results cannot be replicated because of incorrect data analysis procedures. To identify and hopefully avoid these errors in future studies, the articles in seven journals with the highest number of basic science central nervous system TBI and SCI animal research studies published in 2010 (N=125 articles) were reviewed for their data analysis procedures. After identifying the most common statistical errors, the implications of those findings were demonstrated by reanalyzing previously published data from our laboratories using the identified inappropriate statistical procedures, then comparing the two sets of results. Overall, 70% of the articles contained at least one type of inappropriate statistical procedure. The highest percentage involved incorrect post hoc t-tests (56.4%), followed by inappropriate parametric statistics (analysis of variance and t-test; 37.6%). Repeated Measures analysis was inappropriately missing in 52.0% of all articles and, among those with behavioral assessments, 58% were analyzed incorrectly. Reanalysis of our published data using the most common inappropriate statistical procedures resulted in a 14.1% average increase in significant effects compared to the original results. Specifically, an increase of 15.5% occurred with Independent t-tests and 11.1% after incorrect post hoc t-tests. Utilizing proper statistical procedures can allow more-definitive conclusions, facilitate replicability of research results, and enable more accurate translation of those results to the clinic.

Narrative Review of Statistical Reporting Checklists, Mandatory Statistical Editing, and Rectifying Common Problems in the Reporting of Scientific Articles.

PubMed

Dexter, Franklin; Shafer, Steven L

2017-03-01

Considerable attention has been drawn to poor reproducibility in the biomedical literature. One explanation is inadequate reporting of statistical methods by authors and inadequate assessment of statistical reporting and methods during peer review. In this narrative review, we examine scientific studies of several well-publicized efforts to improve statistical reporting. We also review several retrospective assessments of the impact of these efforts. These studies show that instructions to authors and statistical checklists are not sufficient; no findings suggested that either improves the quality of statistical methods and reporting. Second, even basic statistics, such as power analyses, are frequently missing or incorrectly performed. Third, statistical review is needed for all papers that involve data analysis. A consistent finding in the studies was that nonstatistical reviewers (eg, "scientific reviewers") and journal editors generally poorly assess statistical quality. We finish by discussing our experience with statistical review at Anesthesia & Analgesia from 2006 to 2016.

Knowledge and utilization of computer-software for statistics among Nigerian dentists.

PubMed

Chukwuneke, F N; Anyanechi, C E; Obiakor, A O; Amobi, O; Onyejiaka, N; Alamba, I

2013-01-01

The use of computer soft ware for generation of statistic analysis has transformed health information and data to simplest form in the areas of access, storage, retrieval and analysis in the field of research. This survey therefore was carried out to assess the level of knowledge and utilization of computer software for statistical analysis among dental researchers in eastern Nigeria. Questionnaires on the use of computer software for statistical analysis were randomly distributed to 65 practicing dental surgeons of above 5 years experience in the tertiary academic hospitals in eastern Nigeria. The focus was on: years of clinical experience; research work experience; knowledge and application of computer generated software for data processing and stastistical analysis. Sixty-two (62/65; 95.4%) of these questionnaires were returned anonymously, which were used in our data analysis. Twenty-nine (29/62; 46.8%) respondents fall within those with 5-10 years of clinical experience out of which none has completed the specialist training programme. Practitioners with above 10 years clinical experiences were 33 (33/62; 53.2%) out of which 15 (15/33; 45.5%) are specialists representing 24.2% (15/62) of the total number of respondents. All the 15 specialists are actively involved in research activities and only five (5/15; 33.3%) can utilize software statistical analysis unaided. This study has i dentified poor utilization of computer software for statistic analysis among dental researchers in eastern Nigeria. This is strongly associated with lack of exposure on the use of these software early enough especially during the undergraduate training. This call for introduction of computer training programme in dental curriculum to enable practitioners develops the attitude of using computer software for their research.

Spatially referenced crash data system for application to commercial motor vehicle crashes.

DOT National Transportation Integrated Search

2003-05-01

The Maryland Spatial Analysis of Crashes (MSAC) project involves the design of a : prototype of a geographic information system (GIS) for the State of Maryland that has : the capability of providing online crash information and statistical informatio...

Metabolomic analysis based on 1H-nuclear magnetic resonance spectroscopy metabolic profiles in tuberculous, malignant and transudative pleural effusion

PubMed Central

Wang, Cheng; Peng, Jingjin; Kuang, Yanling; Zhang, Jiaqiang; Dai, Luming

2017-01-01

Pleural effusion is a common clinical manifestation with various causes. Current diagnostic and therapeutic methods have exhibited numerous limitations. By involving the analysis of dynamic changes in low molecular weight catabolites, metabolomics has been widely applied in various types of disease and have provided platforms to distinguish many novel biomarkers. However, to the best of our knowledge, there are few studies regarding the metabolic profiling for pleural effusion. In the current study, 58 pleural effusion samples were collected, among which 20 were malignant pleural effusions, 20 were tuberculous pleural effusions and 18 were transudative pleural effusions. The small molecule metabolite spectrums were obtained by adopting 1H nuclear magnetic resonance technology, and pattern-recognition multi-variable statistical analysis was used to screen out different metabolites. One-way analysis of variance, and Student-Newman-Keuls and the Kruskal-Wallis test were adopted for statistical analysis. Over 400 metabolites were identified in the untargeted metabolomic analysis and 26 metabolites were identified as significantly different among tuberculous, malignant and transudative pleural effusions. These metabolites were predominantly involved in the metabolic pathways of amino acids metabolism, glycometabolism and lipid metabolism. Statistical analysis revealed that eight metabolites contributed to the distinction between the three groups: Tuberculous, malignant and transudative pleural effusion. In the current study, the feasibility of identifying small molecule biochemical profiles in different types of pleural effusion were investigated reveal novel biological insights into the underlying mechanisms. The results provide specific insights into the biology of tubercular, malignant and transudative pleural effusion and may offer novel strategies for the diagnosis and therapy of associated diseases, including tuberculosis, advanced lung cancer and congestive heart failure. PMID:28627685

Effect of citric acid, tetracycline, and doxycycline on instrumented periodontally involved root surfaces: A SEM study

PubMed Central

Chahal, Gurparkash Singh; Chhina, Kamalpreet; Chhabra, Vipin; Bhatnagar, Rakhi; Chahal, Amna

2014-01-01

Background: A surface smear layer consisting of organic and inorganic material is formed on the root surface following mechanical instrumentation and may inhibit the formation of new connective tissue attachment to the root surface. Modification of the tooth surface by root conditioning has resulted in improved connective tissue attachment and has advanced the goal of reconstructive periodontal treatment. Aim: The aim of this study was to compare the effects of citric acid, tetracycline, and doxycycline on the instrumented periodontally involved root surfaces in vitro using a scanning electron microscope. Settings and Design: A total of 45 dentin samples obtained from 15 extracted, scaled, and root planed teeth were divided into three groups. Materials and Methods: The root conditioning agents were applied with cotton pellets using the Passive burnishing technique for 5 minutes. The samples were then examined by the scanning electron microscope. Statistical Analysis Used: The statistical analysis was carried out using Statistical Package for Social Sciences (SPSS Inc., Chicago, IL, version 15.0 for Windows). For all quantitative variables means and standard deviations were calculated and compared. For more than two groups ANOVA was applied. For multiple comparisons post hoc tests with Bonferroni correction was used. Results: Upon statistical analysis the root conditioning agents used in this study were found to be effective in removing the smear layer, uncovering and widening the dentin tubules and unmasking the dentin collagen matrix. Conclusion: Tetracycline HCl was found to be the best root conditioner among the three agents used. PMID:24744541

Ethics Education in University Aviation Management Programs in the US: Part Two B--Statistical Analysis of Current Practice.

ERIC Educational Resources Information Center

Oderman, Dale

2003-01-01

Part Two B of a three-part study examined how 40 universities with baccalaureate programs in aviation management include ethics education in the curricula. Analysis of responses suggests that there is strong support for ethics instruction and that active department head involvement leads to higher levels of planned ethics inclusion. (JOW)

A statistical analysis of the effects of a uniform minimum drinking age

DOT National Transportation Integrated Search

1987-04-01

This report examines the relationship between minimum drinking age (MDA) and : highway fatalities during the 1975-1985 period, when 35 states changed their : MDAs. An econometric model of fatalities involving the 18-20 year-old driver : normalized by...

The Statistical Consulting Center for Astronomy (SCCA)

NASA Technical Reports Server (NTRS)

Akritas, Michael

2001-01-01

The process by which raw astronomical data acquisition is transformed into scientifically meaningful results and interpretation typically involves many statistical steps. Traditional astronomy limits itself to a narrow range of old and familiar statistical methods: means and standard deviations; least-squares methods like chi(sup 2) minimization; and simple nonparametric procedures such as the Kolmogorov-Smirnov tests. These tools are often inadequate for the complex problems and datasets under investigations, and recent years have witnessed an increased usage of maximum-likelihood, survival analysis, multivariate analysis, wavelet and advanced time-series methods. The Statistical Consulting Center for Astronomy (SCCA) assisted astronomers with the use of sophisticated tools, and to match these tools with specific problems. The SCCA operated with two professors of statistics and a professor of astronomy working together. Questions were received by e-mail, and were discussed in detail with the questioner. Summaries of those questions and answers leading to new approaches were posted on the Web (www.state.psu.edu/ mga/SCCA). In addition to serving individual astronomers, the SCCA established a Web site for general use that provides hypertext links to selected on-line public-domain statistical software and services. The StatCodes site (www.astro.psu.edu/statcodes) provides over 200 links in the areas of: Bayesian statistics; censored and truncated data; correlation and regression, density estimation and smoothing, general statistics packages and information; image analysis; interactive Web tools; multivariate analysis; multivariate clustering and classification; nonparametric analysis; software written by astronomers; spatial statistics; statistical distributions; time series analysis; and visualization tools. StatCodes has received a remarkable high and constant hit rate of 250 hits/week (over 10,000/year) since its inception in mid-1997. It is of interest to scientists both within and outside of astronomy. The most popular sections are multivariate techniques, image analysis, and time series analysis. Hundreds of copies of the ASURV, SLOPES and CENS-TAU codes developed by SCCA scientists were also downloaded from the StatCodes site. In addition to formal SCCA duties, SCCA scientists continued a variety of related activities in astrostatistics, including refereeing of statistically oriented papers submitted to the Astrophysical Journal, talks in meetings including Feigelson's talk to science journalists entitled "The reemergence of astrostatistics" at the American Association for the Advancement of Science meeting, and published papers of astrostatistical content.

Risk-benefit analysis and public policy: a bibliography

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

Clark, E.M.; Van Horn, A.J.

1976-11-01

Risk-benefit analysis has been implicitly practiced whenever decision-makers are confronted with decisions involving risks to life, health, or to the environment. Various methodologies have been developed to evaluate relevant criteria and to aid in assessing the impacts of alternative projects. Among these have been cost-benefit analysis, which has been widely used for project evaluation. However, in many cases it has been difficult to assign dollar costs to those criteria involving risks and benefits which are not now assigned explicit monetary values in our economic system. Hence, risk-benefit analysis has evolved to become more than merely an extension of cost-benefit analysis,more » and many methods have been applied to examine the trade-offs between risks and benefits. In addition, new scientific and statistical techniques have been developed for assessing current and future risks. The 950 references included in this bibliography are meant to suggest the breadth of those methodologies which have been applied to decisions involving risk.« less

Relationships of nuclear, architectural and International Federation of Gynecology and Obstetrics grading systems in endometrial cancer.

PubMed

Toptaş, Tayfun; Peştereli, Elif; Bozkurt, Selen; Erdoğan, Gülgün; Şimşek, Tayup

2018-03-01

To examine correlations among nuclear, architectural, and International Federation of Gynecology and Obstetrics (FIGO) grading systems, and their relationships with lymph node (LN) involvement in endometrioid endometrial cancer. Histopathology slides of 135 consecutive patients were reviewed with respect to tumor grade and LN metastasis. Notable nuclear atypia was defined as grade 3 nuclei. FIGO grade was established by raising the architectural grade (AG) by one grade when the tumor was composed of cells with nuclear grade (NG) 3. Correlations between the grading systems were analyzed using Spearman's rank correlation coefficients, and relationships of grading systems with LN involvement were assessed using logistic regression analysis. Correlation analysis revealed a significant and strongly positive relationship between FIGO and architectural grading systems (r=0.885, p=0.001); however, correlations of nuclear grading with the architectural (r=0.535, p=0.165) and FIGO grading systems (r=0.589, p=0.082) were moderate and statistically non-significant. Twenty-five (18.5%) patients had LN metastasis. LN involvement rates differed significantly between tumors with AG 1 and those with AG 2, and tumors with FIGO grade 1 and those with FIGO grade 2. In contrast, although the difference in LN involvement rates failed to reach statistical significance between tumors with NG 1 and those with NG 2, it was significant between NG 2 and NG 3 (p=0.042). Although all three grading systems were associated with LN involvement in univariate analyses, an independent relationship could not be established after adjustment for other confounders in multivariate analysis. Nuclear grading is significantly correlated with neither architectural nor FIGO grading systems. The differences in LN involvement rates in the nuclear grading system reach significance only in the setting of tumor cells with NG 3; however, none of the grading systems was an independent predictor of LN involvement.

Increasing Transparency Through a Multiverse Analysis.

PubMed

Steegen, Sara; Tuerlinckx, Francis; Gelman, Andrew; Vanpaemel, Wolf

2016-09-01

Empirical research inevitably includes constructing a data set by processing raw data into a form ready for statistical analysis. Data processing often involves choices among several reasonable options for excluding, transforming, and coding data. We suggest that instead of performing only one analysis, researchers could perform a multiverse analysis, which involves performing all analyses across the whole set of alternatively processed data sets corresponding to a large set of reasonable scenarios. Using an example focusing on the effect of fertility on religiosity and political attitudes, we show that analyzing a single data set can be misleading and propose a multiverse analysis as an alternative practice. A multiverse analysis offers an idea of how much the conclusions change because of arbitrary choices in data construction and gives pointers as to which choices are most consequential in the fragility of the result. © The Author(s) 2016.

Statistical Analysis of a Round-Robin Measurement Survey of Two Candidate Materials for a Seebeck Coefficient Standard Reference Material

PubMed Central

Lu, Z. Q. J.; Lowhorn, N. D.; Wong-Ng, W.; Zhang, W.; Thomas, E. L.; Otani, M.; Green, M. L.; Tran, T. N.; Caylor, C.; Dilley, N. R.; Downey, A.; Edwards, B.; Elsner, N.; Ghamaty, S.; Hogan, T.; Jie, Q.; Li, Q.; Martin, J.; Nolas, G.; Obara, H.; Sharp, J.; Venkatasubramanian, R.; Willigan, R.; Yang, J.; Tritt, T.

2009-01-01

In an effort to develop a Standard Reference Material (SRM™) for Seebeck coefficient, we have conducted a round-robin measurement survey of two candidate materials—undoped Bi2Te3 and Constantan (55 % Cu and 45 % Ni alloy). Measurements were performed in two rounds by twelve laboratories involved in active thermoelectric research using a number of different commercial and custom-built measurement systems and techniques. In this paper we report the detailed statistical analyses on the interlaboratory measurement results and the statistical methodology for analysis of irregularly sampled measurement curves in the interlaboratory study setting. Based on these results, we have selected Bi2Te3 as the prototype standard material. Once available, this SRM will be useful for future interlaboratory data comparison and instrument calibrations. PMID:27504212

Structure-Specific Statistical Mapping of White Matter Tracts

PubMed Central

Yushkevich, Paul A.; Zhang, Hui; Simon, Tony; Gee, James C.

2008-01-01

We present a new model-based framework for the statistical analysis of diffusion imaging data associated with specific white matter tracts. The framework takes advantage of the fact that several of the major white matter tracts are thin sheet-like structures that can be effectively modeled by medial representations. The approach involves segmenting major tracts and fitting them with deformable geometric medial models. The medial representation makes it possible to average and combine tensor-based features along directions locally perpendicular to the tracts, thus reducing data dimensionality and accounting for errors in normalization. The framework enables the analysis of individual white matter structures, and provides a range of possibilities for computing statistics and visualizing differences between cohorts. The framework is demonstrated in a study of white matter differences in pediatric chromosome 22q11.2 deletion syndrome. PMID:18407524

Statistical analysis of alcohol-related driving trends, 1982-2005

DOT National Transportation Integrated Search

2008-05-01

Overall, the percent of drivers involved in fatal crashes who had consumed alcohol and had blood alcohol concentration (BAC) of .08 or above prior to the crash steadily decreased from 1982 to 1997 and then leveled off (more or less). In an attempt to...

Statistical Discourse Analysis: A Method for Modelling Online Discussion Processes

ERIC Educational Resources Information Center

Chiu, Ming Ming; Fujita, Nobuko

2014-01-01

Online forums (synchronous and asynchronous) offer exciting data opportunities to analyze how people influence one another through their interactions. However, researchers must address several analytic difficulties involving the data (missing values, nested structure [messages within topics], non-sequential messages), outcome variables (discrete…

Evaluating Neurotoxicity of a Mixture of Five OP Pesticides Using a Composite Score

EPA Science Inventory

The evaluation of the cumulative effects of neurotoxic pesticides often involves the analysis of both neurochemical and behavioral endpoints. Multiple statistical tests on many endpoints can greatly inflate Type I error rates. Multiple comparison adjustments are often overly con...

Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

PubMed Central

Thomas, E. V.; Phillippy, K. H.; Brahamsha, B.; Haaland, D. M.; Timlin, J. A.; Elbourne, L. D. H.; Palenik, B.; Paulsen, I. T.

2009-01-01

Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array) was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in part to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition. PMID:19404483

Statistical Analysis of Microarray Data with Replicated Spots: A Case Study with Synechococcus WH8102

DOE PAGES

Thomas, E. V.; Phillippy, K. H.; Brahamsha, B.; ...

2009-01-01

Until recently microarray experiments often involved relatively few arrays with only a single representation of each gene on each array. A complete genome microarray with multiple spots per gene (spread out spatially across the array) was developed in order to compare the gene expression of a marine cyanobacterium and a knockout mutant strain in a defined artificial seawater medium. Statistical methods were developed for analysis in the special situation of this case study where there is gene replication within an array and where relatively few arrays are used, which can be the case with current array technology. Due in partmore » to the replication within an array, it was possible to detect very small changes in the levels of expression between the wild type and mutant strains. One interesting biological outcome of this experiment is the indication of the extent to which the phosphorus regulatory system of this cyanobacterium affects the expression of multiple genes beyond those strictly involved in phosphorus acquisition.« less

[A spatially explicit analysis of traffic accidents involving pedestrians and cyclists in Berlin].

PubMed

Lakes, Tobia

2017-12-01

In many German cities and counties, sustainable mobility concepts that strengthen pedestrian and cyclist traffic are promoted. From the perspectives of urban development, traffic planning and public healthcare, a spatially differentiated analysis of traffic accident data is decisive. 1) The identification of spatial and temporal patterns of the distribution of accidents involving cyclists and pedestrians, 2) the identification of hotspots and exploration of possible underlying causes and 3) the critical discussion of benefits and challenges of the results and the derivation of conclusions. Spatio-temporal distributions of data from accident statistics in Berlin involving pedestrians and cyclists from 2011 to 2015 were analysed with geographic information systems (GIS). While the total number of accidents remains relatively stable for pedestrian and cyclist accidents, the spatial distribution analysis shows, however, that there are significant spatial clusters (hotspots) of traffic accidents with a strong concentration in the inner city area. In a critical discussion, the benefits of geographic concepts are identified, such as spatially explicit health data (in this case traffic accident data), the importance of the integration of other data sources for the evaluation of the health impact of areas (traffic accident statistics of the police), and the possibilities and limitations of spatial-temporal data analysis (spatial point-density analyses) for the derivation of decision-supported recommendations and for the evaluation of policy measures of health prevention and of health-relevant urban development.

Statistical analysis plan of the head position in acute ischemic stroke trial pilot (HEADPOST pilot).

PubMed

Olavarría, Verónica V; Arima, Hisatomi; Anderson, Craig S; Brunser, Alejandro; Muñoz-Venturelli, Paula; Billot, Laurent; Lavados, Pablo M

2017-02-01

Background The HEADPOST Pilot is a proof-of-concept, open, prospective, multicenter, international, cluster randomized, phase IIb controlled trial, with masked outcome assessment. The trial will test if lying flat head position initiated in patients within 12 h of onset of acute ischemic stroke involving the anterior circulation increases cerebral blood flow in the middle cerebral arteries, as measured by transcranial Doppler. The study will also assess the safety and feasibility of patients lying flat for ≥24 h. The trial was conducted in centers in three countries, with ability to perform early transcranial Doppler. A feature of this trial was that patients were randomized to a certain position according to the month of admission to hospital. Objective To outline in detail the predetermined statistical analysis plan for HEADPOST Pilot study. Methods All data collected by participating researchers will be reviewed and formally assessed. Information pertaining to the baseline characteristics of patients, their process of care, and the delivery of treatments will be classified, and for each item, appropriate descriptive statistical analyses are planned with comparisons made between randomized groups. For the outcomes, statistical comparisons to be made between groups are planned and described. Results This statistical analysis plan was developed for the analysis of the results of the HEADPOST Pilot study to be transparent, available, verifiable, and predetermined before data lock. Conclusions We have developed a statistical analysis plan for the HEADPOST Pilot study which is to be followed to avoid analysis bias arising from prior knowledge of the study findings. Trial registration The study is registered under HEADPOST-Pilot, ClinicalTrials.gov Identifier NCT01706094.

Statistical Surrogate Modeling of Atmospheric Dispersion Events Using Bayesian Adaptive Splines

NASA Astrophysics Data System (ADS)

Francom, D.; Sansó, B.; Bulaevskaya, V.; Lucas, D. D.

2016-12-01

Uncertainty in the inputs of complex computer models, including atmospheric dispersion and transport codes, is often assessed via statistical surrogate models. Surrogate models are computationally efficient statistical approximations of expensive computer models that enable uncertainty analysis. We introduce Bayesian adaptive spline methods for producing surrogate models that capture the major spatiotemporal patterns of the parent model, while satisfying all the necessities of flexibility, accuracy and computational feasibility. We present novel methodological and computational approaches motivated by a controlled atmospheric tracer release experiment conducted at the Diablo Canyon nuclear power plant in California. Traditional methods for building statistical surrogate models often do not scale well to experiments with large amounts of data. Our approach is well suited to experiments involving large numbers of model inputs, large numbers of simulations, and functional output for each simulation. Our approach allows us to perform global sensitivity analysis with ease. We also present an approach to calibration of simulators using field data.

The Market Responses to the Government Regulation of Chlorinated Solvents: A Policy Analysis

DTIC Science & Technology

1988-10-01

in the process of statistical estimation of model parameters. The results of the estimation process applied to chlorinated solvent markets show the...93 C.5. Marginal Feedstock Cost Series Estimates for Process Share of Total Production .................................. 94 F.I...poliay context for this research. Section III provides analysis necessary to understand the chemicals involved, their production processes and costs, and

Statistics and bioinformatics in nutritional sciences: analysis of complex data in the era of systems biology⋆

PubMed Central

Fu, Wenjiang J.; Stromberg, Arnold J.; Viele, Kert; Carroll, Raymond J.; Wu, Guoyao

2009-01-01

Over the past two decades, there have been revolutionary developments in life science technologies characterized by high throughput, high efficiency, and rapid computation. Nutritionists now have the advanced methodologies for the analysis of DNA, RNA, protein, low-molecular-weight metabolites, as well as access to bioinformatics databases. Statistics, which can be defined as the process of making scientific inferences from data that contain variability, has historically played an integral role in advancing nutritional sciences. Currently, in the era of systems biology, statistics has become an increasingly important tool to quantitatively analyze information about biological macromolecules. This article describes general terms used in statistical analysis of large, complex experimental data. These terms include experimental design, power analysis, sample size calculation, and experimental errors (type I and II errors) for nutritional studies at population, tissue, cellular, and molecular levels. In addition, we highlighted various sources of experimental variations in studies involving microarray gene expression, real-time polymerase chain reaction, proteomics, and other bioinformatics technologies. Moreover, we provided guidelines for nutritionists and other biomedical scientists to plan and conduct studies and to analyze the complex data. Appropriate statistical analyses are expected to make an important contribution to solving major nutrition-associated problems in humans and animals (including obesity, diabetes, cardiovascular disease, cancer, ageing, and intrauterine fetal retardation). PMID:20233650

Profile Of 'Original Articles' Published In 2016 By The Journal Of Ayub Medical College, Pakistan.

PubMed

Shaikh, Masood Ali

2018-01-01

Journal of Ayub Medical College (JAMC) is the only Medline indexed biomedical journal of Pakistan that is edited and published by a medical college. Assessing the trends of study designs employed, statistical methods used, and statistical analysis software used in the articles of medical journals help understand the sophistication of research published. The objectives of this descriptive study were to assess all original articles published by JAMC in the year 2016. JAMC published 147 original articles in the year 2016. The most commonly used study design was crosssectional studies, with 64 (43.5%) articles reporting its use. Statistical tests involving bivariate analysis were most common and reported by 73 (49.6%) articles. Use of SPSS software was reported by 109 (74.1%) of articles. Most 138 (93.9%) of the original articles published were based on studies conducted in Pakistan. The number and sophistication of analysis reported in JAMC increased from year 2014 to 2016.

AutoBayes Program Synthesis System Users Manual

NASA Technical Reports Server (NTRS)

Schumann, Johann; Jafari, Hamed; Pressburger, Tom; Denney, Ewen; Buntine, Wray; Fischer, Bernd

2008-01-01

Program synthesis is the systematic, automatic construction of efficient executable code from high-level declarative specifications. AutoBayes is a fully automatic program synthesis system for the statistical data analysis domain; in particular, it solves parameter estimation problems. It has seen many successful applications at NASA and is currently being used, for example, to analyze simulation results for Orion. The input to AutoBayes is a concise description of a data analysis problem composed of a parameterized statistical model and a goal that is a probability term involving parameters and input data. The output is optimized and fully documented C/C++ code computing the values for those parameters that maximize the probability term. AutoBayes can solve many subproblems symbolically rather than having to rely on numeric approximation algorithms, thus yielding effective, efficient, and compact code. Statistical analysis is faster and more reliable, because effort can be focused on model development and validation rather than manual development of solution algorithms and code.

Interactive Exploration and Analysis of Large-Scale Simulations Using Topology-Based Data Segmentation.

PubMed

Bremer, Peer-Timo; Weber, Gunther; Tierny, Julien; Pascucci, Valerio; Day, Marcus S; Bell, John B

2011-09-01

Large-scale simulations are increasingly being used to study complex scientific and engineering phenomena. As a result, advanced visualization and data analysis are also becoming an integral part of the scientific process. Often, a key step in extracting insight from these large simulations involves the definition, extraction, and evaluation of features in the space and time coordinates of the solution. However, in many applications, these features involve a range of parameters and decisions that will affect the quality and direction of the analysis. Examples include particular level sets of a specific scalar field, or local inequalities between derived quantities. A critical step in the analysis is to understand how these arbitrary parameters/decisions impact the statistical properties of the features, since such a characterization will help to evaluate the conclusions of the analysis as a whole. We present a new topological framework that in a single-pass extracts and encodes entire families of possible features definitions as well as their statistical properties. For each time step we construct a hierarchical merge tree a highly compact, yet flexible feature representation. While this data structure is more than two orders of magnitude smaller than the raw simulation data it allows us to extract a set of features for any given parameter selection in a postprocessing step. Furthermore, we augment the trees with additional attributes making it possible to gather a large number of useful global, local, as well as conditional statistic that would otherwise be extremely difficult to compile. We also use this representation to create tracking graphs that describe the temporal evolution of the features over time. Our system provides a linked-view interface to explore the time-evolution of the graph interactively alongside the segmentation, thus making it possible to perform extensive data analysis in a very efficient manner. We demonstrate our framework by extracting and analyzing burning cells from a large-scale turbulent combustion simulation. In particular, we show how the statistical analysis enabled by our techniques provides new insight into the combustion process.

Accommodating the Spectrum of Individual Abilities. Clearinghouse Publication 81.

ERIC Educational Resources Information Center

Commission on Civil Rights, Washington, DC.

The monograph addresses legal issues involving discrimination against handicapped persons and the key legal requirement of reasonable accommodation. Four chapters in Part I examine background issues, including definitions and statistical overviews of handicaps; historical attitudes toward handicapped persons and an analysis of the extent of…

Learning Effects of an International Group Competition Project

ERIC Educational Resources Information Center

Akpinar, Murat; del Campo, Cristina; Eryarsoy, Enes

2015-01-01

This study investigates the effects of collaboration and competition on students' learning performance in a course of business statistics. The collaboration involved a simultaneously organised group competition project with analysis of real-life business problems among students. Students from the following schools participated: JAMK University of…

A Novel Genome-Information Content-Based Statistic for Genome-Wide Association Analysis Designed for Next-Generation Sequencing Data

PubMed Central

Luo, Li; Zhu, Yun

2012-01-01

Abstract The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T2, collapsing method, multivariate and collapsing (CMC) method, individual χ2 test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets. PMID:22651812

A novel genome-information content-based statistic for genome-wide association analysis designed for next-generation sequencing data.

PubMed

Luo, Li; Zhu, Yun; Xiong, Momiao

2012-06-01

The genome-wide association studies (GWAS) designed for next-generation sequencing data involve testing association of genomic variants, including common, low frequency, and rare variants. The current strategies for association studies are well developed for identifying association of common variants with the common diseases, but may be ill-suited when large amounts of allelic heterogeneity are present in sequence data. Recently, group tests that analyze their collective frequency differences between cases and controls shift the current variant-by-variant analysis paradigm for GWAS of common variants to the collective test of multiple variants in the association analysis of rare variants. However, group tests ignore differences in genetic effects among SNPs at different genomic locations. As an alternative to group tests, we developed a novel genome-information content-based statistics for testing association of the entire allele frequency spectrum of genomic variation with the diseases. To evaluate the performance of the proposed statistics, we use large-scale simulations based on whole genome low coverage pilot data in the 1000 Genomes Project to calculate the type 1 error rates and power of seven alternative statistics: a genome-information content-based statistic, the generalized T(2), collapsing method, multivariate and collapsing (CMC) method, individual χ(2) test, weighted-sum statistic, and variable threshold statistic. Finally, we apply the seven statistics to published resequencing dataset from ANGPTL3, ANGPTL4, ANGPTL5, and ANGPTL6 genes in the Dallas Heart Study. We report that the genome-information content-based statistic has significantly improved type 1 error rates and higher power than the other six statistics in both simulated and empirical datasets.

Identifiability of PBPK Models with Applications to ...

EPA Pesticide Factsheets

Any statistical model should be identifiable in order for estimates and tests using it to be meaningful. We consider statistical analysis of physiologically-based pharmacokinetic (PBPK) models in which parameters cannot be estimated precisely from available data, and discuss different types of identifiability that occur in PBPK models and give reasons why they occur. We particularly focus on how the mathematical structure of a PBPK model and lack of appropriate data can lead to statistical models in which it is impossible to estimate at least some parameters precisely. Methods are reviewed which can determine whether a purely linear PBPK model is globally identifiable. We propose a theorem which determines when identifiability at a set of finite and specific values of the mathematical PBPK model (global discrete identifiability) implies identifiability of the statistical model. However, we are unable to establish conditions that imply global discrete identifiability, and conclude that the only safe approach to analysis of PBPK models involves Bayesian analysis with truncated priors. Finally, computational issues regarding posterior simulations of PBPK models are discussed. The methodology is very general and can be applied to numerous PBPK models which can be expressed as linear time-invariant systems. A real data set of a PBPK model for exposure to dimethyl arsinic acid (DMA(V)) is presented to illustrate the proposed methodology. We consider statistical analy

Statistical issues in quality control of proteomic analyses: good experimental design and planning.

PubMed

Cairns, David A

2011-03-01

Quality control is becoming increasingly important in proteomic investigations as experiments become more multivariate and quantitative. Quality control applies to all stages of an investigation and statistics can play a key role. In this review, the role of statistical ideas in the design and planning of an investigation is described. This involves the design of unbiased experiments using key concepts from statistical experimental design, the understanding of the biological and analytical variation in a system using variance components analysis and the determination of a required sample size to perform a statistically powerful investigation. These concepts are described through simple examples and an example data set from a 2-D DIGE pilot experiment. Each of these concepts can prove useful in producing better and more reproducible data. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Modelling multiple sources of dissemination bias in meta-analysis.

PubMed

Bowden, Jack; Jackson, Dan; Thompson, Simon G

2010-03-30

Asymmetry in the funnel plot for a meta-analysis suggests the presence of dissemination bias. This may be caused by publication bias through the decisions of journal editors, by selective reporting of research results by authors or by a combination of both. Typically, study results that are statistically significant or have larger estimated effect sizes are more likely to appear in the published literature, hence giving a biased picture of the evidence-base. Previous statistical approaches for addressing dissemination bias have assumed only a single selection mechanism. Here we consider a more realistic scenario in which multiple dissemination processes, involving both the publishing authors and journals, are operating. In practical applications, the methods can be used to provide sensitivity analyses for the potential effects of multiple dissemination biases operating in meta-analysis.

Detecting most influencing courses on students grades using block PCA

NASA Astrophysics Data System (ADS)

Othman, Osama H.; Gebril, Rami Salah

2014-12-01

One of the modern solutions adopted in dealing with the problem of large number of variables in statistical analyses is the Block Principal Component Analysis (Block PCA). This modified technique can be used to reduce the vertical dimension (variables) of the data matrix Xn×p by selecting a smaller number of variables, (say m) containing most of the statistical information. These selected variables can then be employed in further investigations and analyses. Block PCA is an adapted multistage technique of the original PCA. It involves the application of Cluster Analysis (CA) and variable selection throughout sub principal components scores (PC's). The application of Block PCA in this paper is a modified version of the original work of Liu et al (2002). The main objective was to apply PCA on each group of variables, (established using cluster analysis), instead of involving the whole large pack of variables which was proved to be unreliable. In this work, the Block PCA is used to reduce the size of a huge data matrix ((n = 41) × (p = 251)) consisting of Grade Point Average (GPA) of the students in 251 courses (variables) in the faculty of science in Benghazi University. In other words, we are constructing a smaller analytical data matrix of the GPA's of the students with less variables containing most variation (statistical information) in the original database. By applying the Block PCA, (12) courses were found to `absorb' most of the variation or influence from the original data matrix, and hence worth to be keep for future statistical exploring and analytical studies. In addition, the course Independent Study (Math.) was found to be the most influencing course on students GPA among the 12 selected courses.

Characteristics of genomic signatures derived using univariate methods and mechanistically anchored functional descriptors for predicting drug- and xenobiotic-induced nephrotoxicity.

PubMed

Shi, Weiwei; Bugrim, Andrej; Nikolsky, Yuri; Nikolskya, Tatiana; Brennan, Richard J

2008-01-01

ABSTRACT The ideal toxicity biomarker is composed of the properties of prediction (is detected prior to traditional pathological signs of injury), accuracy (high sensitivity and specificity), and mechanistic relationships to the endpoint measured (biological relevance). Gene expression-based toxicity biomarkers ("signatures") have shown good predictive power and accuracy, but are difficult to interpret biologically. We have compared different statistical methods of feature selection with knowledge-based approaches, using GeneGo's database of canonical pathway maps, to generate gene sets for the classification of renal tubule toxicity. The gene set selection algorithms include four univariate analyses: t-statistics, fold-change, B-statistics, and RankProd, and their combination and overlap for the identification of differentially expressed probes. Enrichment analysis following the results of the four univariate analyses, Hotelling T-square test, and, finally out-of-bag selection, a variant of cross-validation, were used to identify canonical pathway maps-sets of genes coordinately involved in key biological processes-with classification power. Differentially expressed genes identified by the different statistical univariate analyses all generated reasonably performing classifiers of tubule toxicity. Maps identified by enrichment analysis or Hotelling T-square had lower classification power, but highlighted perturbed lipid homeostasis as a common discriminator of nephrotoxic treatments. The out-of-bag method yielded the best functionally integrated classifier. The map "ephrins signaling" performed comparably to a classifier derived using sparse linear programming, a machine learning algorithm, and represents a signaling network specifically involved in renal tubule development and integrity. Such functional descriptors of toxicity promise to better integrate predictive toxicogenomics with mechanistic analysis, facilitating the interpretation and risk assessment of predictive genomic investigations.

Tracking problem solving by multivariate pattern analysis and Hidden Markov Model algorithms.

PubMed

Anderson, John R

2012-03-01

Multivariate pattern analysis can be combined with Hidden Markov Model algorithms to track the second-by-second thinking as people solve complex problems. Two applications of this methodology are illustrated with a data set taken from children as they interacted with an intelligent tutoring system for algebra. The first "mind reading" application involves using fMRI activity to track what students are doing as they solve a sequence of algebra problems. The methodology achieves considerable accuracy at determining both what problem-solving step the students are taking and whether they are performing that step correctly. The second "model discovery" application involves using statistical model evaluation to determine how many substates are involved in performing a step of algebraic problem solving. This research indicates that different steps involve different numbers of substates and these substates are associated with different fluency in algebra problem solving. Copyright © 2011 Elsevier Ltd. All rights reserved.

Risk management in inpatient units in the Czech Republic from the point of view of nurses in leadership positions.

PubMed

Prokešová, Radka; Brabcová, Iva; Pokojová, Radka; Bártlová, Sylva

2016-12-01

The goal of this study was to assess specific features of risk management from the point of view of nurses in leadership positions in inpatient units in Czech hospitals. The study was performed using a quantitative research strategy, i.e., a questionnaire. The data sample was analyzed using SPSS v. 23.0. Pearson's chi-square and analysis of adjusted residues were used for identifying the existence associations of nominal and/or ordinal quantities. 315 nurses in leadership positions working in inpatient units of Czech hospitals were included in the sample. The sample was created using random selection by means of quotas. Based on the study results, statistically significant relations between the respondents' education and the utilization of methods to identify risks were identified. Furthermore, statistically significant relationships were found between a nurse's functional role within the system and regular analysis and evaluation of risks and between the type of the healthcare facility and the degree of patient involvement in risk management. The study found statistically significant correlations that can be used to increase the effectiveness of risk management in inpatient units of Czech hospitals. From this perspective, the fact that patient involvement in risk management was only reported by 37.8% of respondents seems to be the most notable problem.

Partial Least Squares Regression Can Aid in Detecting Differential Abundance of Multiple Features in Sets of Metagenomic Samples

PubMed Central

Libiger, Ondrej; Schork, Nicholas J.

2015-01-01

It is now feasible to examine the composition and diversity of microbial communities (i.e., “microbiomes”) that populate different human organs and orifices using DNA sequencing and related technologies. To explore the potential links between changes in microbial communities and various diseases in the human body, it is essential to test associations involving different species within and across microbiomes, environmental settings and disease states. Although a number of statistical techniques exist for carrying out relevant analyses, it is unclear which of these techniques exhibit the greatest statistical power to detect associations given the complexity of most microbiome datasets. We compared the statistical power of principal component regression, partial least squares regression, regularized regression, distance-based regression, Hill's diversity measures, and a modified test implemented in the popular and widely used microbiome analysis methodology “Metastats” across a wide range of simulated scenarios involving changes in feature abundance between two sets of metagenomic samples. For this purpose, simulation studies were used to change the abundance of microbial species in a real dataset from a published study examining human hands. Each technique was applied to the same data, and its ability to detect the simulated change in abundance was assessed. We hypothesized that a small subset of methods would outperform the rest in terms of the statistical power. Indeed, we found that the Metastats technique modified to accommodate multivariate analysis and partial least squares regression yielded high power under the models and data sets we studied. The statistical power of diversity measure-based tests, distance-based regression and regularized regression was significantly lower. Our results provide insight into powerful analysis strategies that utilize information on species counts from large microbiome data sets exhibiting skewed frequency distributions obtained on a small to moderate number of samples. PMID:26734061

Periodontal disease and carotid atherosclerosis: A meta-analysis of 17,330 participants.

PubMed

Zeng, Xian-Tao; Leng, Wei-Dong; Lam, Yat-Yin; Yan, Bryan P; Wei, Xue-Mei; Weng, Hong; Kwong, Joey S W

2016-01-15

The association between periodontal disease and carotid atherosclerosis has been evaluated primarily in single-center studies, and whether periodontal disease is an independent risk factor of carotid atherosclerosis remains uncertain. This meta-analysis aimed to evaluate the association between periodontal disease and carotid atherosclerosis. We searched PubMed and Embase for relevant observational studies up to February 20, 2015. Two authors independently extracted data from included studies, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated for overall and subgroup meta-analyses. Statistical heterogeneity was assessed by the chi-squared test (P<0.1 for statistical significance) and quantified by the I(2) statistic. Data analysis was conducted using the Comprehensive Meta-Analysis (CMA) software. Fifteen observational studies involving 17,330 participants were included in the meta-analysis. The overall pooled result showed that periodontal disease was associated with carotid atherosclerosis (OR: 1.27, 95% CI: 1.14-1.41; P<0.001) but statistical heterogeneity was substantial (I(2)=78.90%). Subgroup analysis of adjusted smoking and diabetes mellitus showed borderline significance (OR: 1.08; 95% CI: 1.00-1.18; P=0.05). Sensitivity and cumulative analyses both indicated that our results were robust. Findings of our meta-analysis indicated that the presence of periodontal disease was associated with carotid atherosclerosis; however, further large-scale, well-conducted clinical studies are needed to explore the precise risk of developing carotid atherosclerosis in patients with periodontal disease. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Gender and Pupil Performance. Interchange 70.

ERIC Educational Resources Information Center

Tinklin, Teresa; Croxford, Linda; Ducklin, Alan; Frame, Barbara

This study examined factors that influence the relative academic attainment of males and females and how good performance by both genders can be achieved. The study involved a review of literature and policy documents, statistical analysis of official data, a questionnaire survey of local authorities, and case studies of six secondary schools in…

Improving Student Retention and Performance in Quantitative Courses Using Clickers

ERIC Educational Resources Information Center

Liu, Wallace C.; Stengel, Donald N.

2011-01-01

Clickers offer instructors of mathematics-related courses an opportunity to involve students actively in class sessions while diminishing the embarrassment of being wrong. This paper reports on the use of clickers in two university-level courses in quantitative analysis and business statistics. Results for student retention and examination…

Method for factor analysis of GC/MS data

DOEpatents

Van Benthem, Mark H; Kotula, Paul G; Keenan, Michael R

2012-09-11

The method of the present invention provides a fast, robust, and automated multivariate statistical analysis of gas chromatography/mass spectroscopy (GC/MS) data sets. The method can involve systematic elimination of undesired, saturated peak masses to yield data that follow a linear, additive model. The cleaned data can then be subjected to a combination of PCA and orthogonal factor rotation followed by refinement with MCR-ALS to yield highly interpretable results.

Comparison of suprapatellar and infrapatellar intramedullary nailing for tibial shaft fractures: a systematic review and meta-analysis.

PubMed

Yang, Liqing; Sun, Yuefeng; Li, Ge

2018-06-14

Optimal surgical approach for tibial shaft fractures remains controversial. We perform a meta-analysis from randomized controlled trials (RCTs) to compare the clinical efficacy and prognosis between infrapatellar and suprapatellar intramedullary nail in the treatment of tibial shaft fractures. PubMed, OVID, Embase, ScienceDirect, and Web of Science were searched up to December 2017 for comparative RCTs involving infrapatellar and suprapatellar intramedullary nail in the treatment of tibial shaft fractures. Primary outcomes were blood loss, visual analog scale (VAS) score, range of motion, Lysholm knee scores, and fluoroscopy times. Secondary outcomes were length of hospital stay and postoperative complications. We assessed statistical heterogeneity for each outcome with the use of a standard χ 2 test and the I 2 statistic. The meta-analysis was undertaken using Stata 14.0. Four RCTs involving 293 participants were included in our study. The present meta-analysis indicated that there were significant differences between infrapatellar and suprapatellar intramedullary nail regarding the total blood loss, VAS scores, Lysholm knee scores, and fluoroscopy times. Suprapatellar intramedullary nailing could significantly reduce total blood loss, postoperative knee pain, and fluoroscopy times compared to infrapatellar approach. Additionally, it was associated with an improved Lysholm knee scores. High-quality RCTs were still required for further investigation.

Factorial validity and internal consistency of the motivational climate in physical education scale.

PubMed

Soini, Markus; Liukkonen, Jarmo; Watt, Anthony; Yli-Piipari, Sami; Jaakkola, Timo

2014-01-01

The aim of the study was to examine the construct validity and internal consistency of the Motivational Climate in Physical Education Scale (MCPES). A key element of the development process of the scale was establishing a theoretical framework that integrated the dimensions of task- and ego involving climates in conjunction with autonomy, and social relatedness supporting climates. These constructs were adopted from the self-determination and achievement goal theories. A sample of Finnish Grade 9 students, comprising 2,594 girls and 1,803 boys, completed the 18-item MCPES during one physical education class. The results of the study demonstrated that participants had highest mean in task-involving climate and the lowest in autonomy climate and ego-involving climate. Additionally, autonomy, social relatedness, and task- involving climates were significantly and strongly correlated with each other, whereas the ego- involving climate had low or negligible correlations with the other climate dimensions.The construct validity of the MCPES was analyzed using confirmatory factor analysis. The statistical fit of the four-factor model consisting of motivational climate factors supporting perceived autonomy, social relatedness, task-involvement, and ego-involvement was satisfactory. The results of the reliability analysis showed acceptable internal consistencies for all four dimensions. The Motivational Climate in Physical Education Scale can be considered as psychometrically valid tool to measure motivational climate in Finnish Grade 9 students. Key PointsThis study developed Motivational Climate in School Physical Education Scale (MCPES). During the development process of the scale, the theoretical framework using dimensions of task- and ego involving as well as autonomy, and social relatedness supporting climates was constructed. These constructs were adopted from the self-determination and achievement goal theories.The statistical fit of the four-factor model of the MCPES consisting of motivational climate factors supporting perceived autonomy, social relatedness, task-involvement, and ego-involvement was satisfactory. Additionally, the results of the reliability analysis showed acceptable internal consistencies for all four dimensions.The results of the study demonstrated that participants had highest mean in task-involving climate and the lowest in autonomy climate.Autonomy, social relatedness, and task climate were significantly and strongly correlated with each other, whereas the ego climate factor had low or negligible correlations with the other three factors.

Factorial Validity and Internal Consistency of the Motivational Climate in Physical Education Scale

PubMed Central

Soini, Markus; Liukkonen, Jarmo; Watt, Anthony; Yli-Piipari, Sami; Jaakkola, Timo

2014-01-01

The aim of the study was to examine the construct validity and internal consistency of the Motivational Climate in Physical Education Scale (MCPES). A key element of the development process of the scale was establishing a theoretical framework that integrated the dimensions of task- and ego involving climates in conjunction with autonomy, and social relatedness supporting climates. These constructs were adopted from the self-determination and achievement goal theories. A sample of Finnish Grade 9 students, comprising 2,594 girls and 1,803 boys, completed the 18-item MCPES during one physical education class. The results of the study demonstrated that participants had highest mean in task-involving climate and the lowest in autonomy climate and ego-involving climate. Additionally, autonomy, social relatedness, and task- involving climates were significantly and strongly correlated with each other, whereas the ego- involving climate had low or negligible correlations with the other climate dimensions.The construct validity of the MCPES was analyzed using confirmatory factor analysis. The statistical fit of the four-factor model consisting of motivational climate factors supporting perceived autonomy, social relatedness, task-involvement, and ego-involvement was satisfactory. The results of the reliability analysis showed acceptable internal consistencies for all four dimensions. The Motivational Climate in Physical Education Scale can be considered as psychometrically valid tool to measure motivational climate in Finnish Grade 9 students. Key Points This study developed Motivational Climate in School Physical Education Scale (MCPES). During the development process of the scale, the theoretical framework using dimensions of task- and ego involving as well as autonomy, and social relatedness supporting climates was constructed. These constructs were adopted from the self-determination and achievement goal theories. The statistical fit of the four-factor model of the MCPES consisting of motivational climate factors supporting perceived autonomy, social relatedness, task-involvement, and ego-involvement was satisfactory. Additionally, the results of the reliability analysis showed acceptable internal consistencies for all four dimensions. The results of the study demonstrated that participants had highest mean in task-involving climate and the lowest in autonomy climate. Autonomy, social relatedness, and task climate were significantly and strongly correlated with each other, whereas the ego climate factor had low or negligible correlations with the other three factors. PMID:24570617

A Statistical Analysis of Brain Morphology Using Wild Bootstrapping

PubMed Central

Ibrahim, Joseph G.; Tang, Niansheng; Rowe, Daniel B.; Hao, Xuejun; Bansal, Ravi; Peterson, Bradley S.

2008-01-01

Methods for the analysis of brain morphology, including voxel-based morphology and surface-based morphometries, have been used to detect associations between brain structure and covariates of interest, such as diagnosis, severity of disease, age, IQ, and genotype. The statistical analysis of morphometric measures usually involves two statistical procedures: 1) invoking a statistical model at each voxel (or point) on the surface of the brain or brain subregion, followed by mapping test statistics (e.g., t test) or their associated p values at each of those voxels; 2) correction for the multiple statistical tests conducted across all voxels on the surface of the brain region under investigation. We propose the use of new statistical methods for each of these procedures. We first use a heteroscedastic linear model to test the associations between the morphological measures at each voxel on the surface of the specified subregion (e.g., cortical or subcortical surfaces) and the covariates of interest. Moreover, we develop a robust test procedure that is based on a resampling method, called wild bootstrapping. This procedure assesses the statistical significance of the associations between a measure of given brain structure and the covariates of interest. The value of this robust test procedure lies in its computationally simplicity and in its applicability to a wide range of imaging data, including data from both anatomical and functional magnetic resonance imaging (fMRI). Simulation studies demonstrate that this robust test procedure can accurately control the family-wise error rate. We demonstrate the application of this robust test procedure to the detection of statistically significant differences in the morphology of the hippocampus over time across gender groups in a large sample of healthy subjects. PMID:17649909

Unlikely Fluctuations and Non-Equilibrium Work Theorems-A Simple Example.

PubMed

Muzikar, Paul

2016-06-30

An exciting development in statistical mechanics has been the elucidation of a series of surprising equalities involving the work done during a nonequilibrium process. Astumian has presented an elegant example of such an equality, involving a colloidal particle undergoing Brownian motion in the presence of gravity. We analyze this example; its simplicity, and its link to geometric Brownian motion, allows us to clarify the inner workings of the equality. Our analysis explicitly shows the important role played by large, unlikely fluctuations.

Statistical Approaches Used to Assess the Equity of Access to Food Outlets: A Systematic Review

PubMed Central

Lamb, Karen E.; Thornton, Lukar E.; Cerin, Ester; Ball, Kylie

2015-01-01

Background Inequalities in eating behaviours are often linked to the types of food retailers accessible in neighbourhood environments. Numerous studies have aimed to identify if access to healthy and unhealthy food retailers is socioeconomically patterned across neighbourhoods, and thus a potential risk factor for dietary inequalities. Existing reviews have examined differences between methodologies, particularly focussing on neighbourhood and food outlet access measure definitions. However, no review has informatively discussed the suitability of the statistical methodologies employed; a key issue determining the validity of study findings. Our aim was to examine the suitability of statistical approaches adopted in these analyses. Methods Searches were conducted for articles published from 2000–2014. Eligible studies included objective measures of the neighbourhood food environment and neighbourhood-level socio-economic status, with a statistical analysis of the association between food outlet access and socio-economic status. Results Fifty-four papers were included. Outlet accessibility was typically defined as the distance to the nearest outlet from the neighbourhood centroid, or as the number of food outlets within a neighbourhood (or buffer). To assess if these measures were linked to neighbourhood disadvantage, common statistical methods included ANOVA, correlation, and Poisson or negative binomial regression. Although all studies involved spatial data, few considered spatial analysis techniques or spatial autocorrelation. Conclusions With advances in GIS software, sophisticated measures of neighbourhood outlet accessibility can be considered. However, approaches to statistical analysis often appear less sophisticated. Care should be taken to consider assumptions underlying the analysis and the possibility of spatially correlated residuals which could affect the results. PMID:29546115

Statistical detection of patterns in unidimensional distributions by continuous wavelet transforms

NASA Astrophysics Data System (ADS)

Baluev, R. V.

2018-04-01

Objective detection of specific patterns in statistical distributions, like groupings or gaps or abrupt transitions between different subsets, is a task with a rich range of applications in astronomy: Milky Way stellar population analysis, investigations of the exoplanets diversity, Solar System minor bodies statistics, extragalactic studies, etc. We adapt the powerful technique of the wavelet transforms to this generalized task, making a strong emphasis on the assessment of the patterns detection significance. Among other things, our method also involves optimal minimum-noise wavelets and minimum-noise reconstruction of the distribution density function. Based on this development, we construct a self-closed algorithmic pipeline aimed to process statistical samples. It is currently applicable to single-dimensional distributions only, but it is flexible enough to undergo further generalizations and development.

Information-dependent enrichment analysis reveals time-dependent transcriptional regulation of the estrogen pathway of toxicity.

PubMed

Pendse, Salil N; Maertens, Alexandra; Rosenberg, Michael; Roy, Dipanwita; Fasani, Rick A; Vantangoli, Marguerite M; Madnick, Samantha J; Boekelheide, Kim; Fornace, Albert J; Odwin, Shelly-Ann; Yager, James D; Hartung, Thomas; Andersen, Melvin E; McMullen, Patrick D

2017-04-01

The twenty-first century vision for toxicology involves a transition away from high-dose animal studies to in vitro and computational models (NRC in Toxicity testing in the 21st century: a vision and a strategy, The National Academies Press, Washington, DC, 2007). This transition requires mapping pathways of toxicity by understanding how in vitro systems respond to chemical perturbation. Uncovering transcription factors/signaling networks responsible for gene expression patterns is essential for defining pathways of toxicity, and ultimately, for determining the chemical modes of action through which a toxicant acts. Traditionally, transcription factor identification is achieved via chromatin immunoprecipitation studies and summarized by calculating which transcription factors are statistically associated with up- and downregulated genes. These lists are commonly determined via statistical or fold-change cutoffs, a procedure that is sensitive to statistical power and may not be as useful for determining transcription factor associations. To move away from an arbitrary statistical or fold-change-based cutoff, we developed, in the context of the Mapping the Human Toxome project, an enrichment paradigm called information-dependent enrichment analysis (IDEA) to guide identification of the transcription factor network. We used a test case of activation in MCF-7 cells by 17β estradiol (E2). Using this new approach, we established a time course for transcriptional and functional responses to E2. ERα and ERβ were associated with short-term transcriptional changes in response to E2. Sustained exposure led to recruitment of additional transcription factors and alteration of cell cycle machinery. TFAP2C and SOX2 were the transcription factors most highly correlated with dose. E2F7, E2F1, and Foxm1, which are involved in cell proliferation, were enriched only at 24 h. IDEA should be useful for identifying candidate pathways of toxicity. IDEA outperforms gene set enrichment analysis (GSEA) and provides similar results to weighted gene correlation network analysis, a platform that helps to identify genes not annotated to pathways.

Test data analysis for concentrating photovoltaic arrays

NASA Astrophysics Data System (ADS)

Maish, A. B.; Cannon, J. E.

A test data analysis approach for use with steady state efficiency measurements taken on concentrating photovoltaic arrays is presented. The analysis procedures can be used to identify based and erroneous data. The steps involved in analyzing the test data are screening the data, developing coefficients for the performance equation, analyzing statistics to ensure adequacy of the regression fit to the data, and plotting the data. In addition, this paper analyzes the sources and magnitudes of precision and bias errors that affect measurement accuracy are analyzed.

Featured Article: Transcriptional landscape analysis identifies differently expressed genes involved in follicle-stimulating hormone induced postmenopausal osteoporosis.

PubMed

Maasalu, Katre; Laius, Ott; Zhytnik, Lidiia; Kõks, Sulev; Prans, Ele; Reimann, Ene; Märtson, Aare

2017-01-01

Osteoporosis is a disorder associated with bone tissue reorganization, bone mass, and mineral density. Osteoporosis can severely affect postmenopausal women, causing bone fragility and osteoporotic fractures. The aim of the current study was to compare blood mRNA profiles of postmenopausal women with and without osteoporosis, with the aim of finding different gene expressions and thus targets for future osteoporosis biomarker studies. Our study consisted of transcriptome analysis of whole blood serum from 12 elderly female osteoporotic patients and 12 non-osteoporotic elderly female controls. The transcriptome analysis was performed with RNA sequencing technology. For data analysis, the edgeR package of R Bioconductor was used. Two hundred and fourteen genes were expressed differently in osteoporotic compared with non-osteoporotic patients. Statistical analysis revealed 20 differently expressed genes with a false discovery rate of less than 1.47 × 10 -4 among osteoporotic patients. The expression of 10 genes were up-regulated and 10 down-regulated. Further statistical analysis identified a potential osteoporosis mRNA biomarker pattern consisting of six genes: CACNA1G, ALG13, SBK1, GGT7, MBNL3, and RIOK3. Functional ingenuity pathway analysis identified the strongest candidate genes with regard to potential involvement in a follicle-stimulating hormone activated network of increased osteoclast activity and hypogonadal bone loss. The differentially expressed genes identified in this study may contribute to future research of postmenopausal osteoporosis blood biomarkers.

Which Type of Risk Information to Use for Whom? Moderating Role of Outcome-Relevant Involvement in the Effects of Statistical and Exemplified Risk Information on Risk Perceptions.

PubMed

So, Jiyeon; Jeong, Se-Hoon; Hwang, Yoori

2017-04-01

The extant empirical research examining the effectiveness of statistical and exemplar-based health information is largely inconsistent. Under the premise that the inconsistency may be due to an unacknowledged moderator (O'Keefe, 2002), this study examined a moderating role of outcome-relevant involvement (Johnson & Eagly, 1989) in the effects of statistical and exemplified risk information on risk perception. Consistent with predictions based on elaboration likelihood model (Petty & Cacioppo, 1984), findings from an experiment (N = 237) concerning alcohol consumption risks showed that statistical risk information predicted risk perceptions of individuals with high, rather than low, involvement, while exemplified risk information predicted risk perceptions of those with low, rather than high, involvement. Moreover, statistical risk information contributed to negative attitude toward drinking via increased risk perception only for highly involved individuals, while exemplified risk information influenced the attitude through the same mechanism only for individuals with low involvement. Theoretical and practical implications for health risk communication are discussed.

STATISTICAL ANALYSIS OF SPECTROPHOTOMETRIC DETERMINATIONS OF BORON; Estudo Estatistico de Determinacoes Espectrofotometricas de Boro

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

Lima, F.W.; Pagano, C.; Schneiderman, B.

1959-07-01

Boron can be determined quantitatively by absorption spectrophotometry of solutions of the red compound formed by the reaction of boric acid with curcumin. This reaction is affected by various factors, some of which can be detected easily in the data interpretation. Others, however, provide more difficulty. The application of modern statistical method to the study of the influence of these factors on the quantitative determination of boron is presented. These methods provide objective ways of establishing significant effects of the factors involved. (auth)

DARHT Multi-intelligence Seismic and Acoustic Data Analysis

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

Stevens, Garrison Nicole; Van Buren, Kendra Lu; Hemez, Francois M.

The purpose of this report is to document the analysis of seismic and acoustic data collected at the Dual-Axis Radiographic Hydrodynamic Test (DARHT) facility at Los Alamos National Laboratory for robust, multi-intelligence decision making. The data utilized herein is obtained from two tri-axial seismic sensors and three acoustic sensors, resulting in a total of nine data channels. The goal of this analysis is to develop a generalized, automated framework to determine internal operations at DARHT using informative features extracted from measurements collected external of the facility. Our framework involves four components: (1) feature extraction, (2) data fusion, (3) classification, andmore » finally (4) robustness analysis. Two approaches are taken for extracting features from the data. The first of these, generic feature extraction, involves extraction of statistical features from the nine data channels. The second approach, event detection, identifies specific events relevant to traffic entering and leaving the facility as well as explosive activities at DARHT and nearby explosive testing sites. Event detection is completed using a two stage method, first utilizing signatures in the frequency domain to identify outliers and second extracting short duration events of interest among these outliers by evaluating residuals of an autoregressive exogenous time series model. Features extracted from each data set are then fused to perform analysis with a multi-intelligence paradigm, where information from multiple data sets are combined to generate more information than available through analysis of each independently. The fused feature set is used to train a statistical classifier and predict the state of operations to inform a decision maker. We demonstrate this classification using both generic statistical features and event detection and provide a comparison of the two methods. Finally, the concept of decision robustness is presented through a preliminary analysis where uncertainty is added to the system through noise in the measurements.« less

Statistical analysis plan for the Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART). A randomized controlled trial

PubMed Central

Damiani, Lucas Petri; Berwanger, Otavio; Paisani, Denise; Laranjeira, Ligia Nasi; Suzumura, Erica Aranha; Amato, Marcelo Britto Passos; Carvalho, Carlos Roberto Ribeiro; Cavalcanti, Alexandre Biasi

2017-01-01

Background The Alveolar Recruitment for Acute Respiratory Distress Syndrome Trial (ART) is an international multicenter randomized pragmatic controlled trial with allocation concealment involving 120 intensive care units in Brazil, Argentina, Colombia, Italy, Poland, Portugal, Malaysia, Spain, and Uruguay. The primary objective of ART is to determine whether maximum stepwise alveolar recruitment associated with PEEP titration, adjusted according to the static compliance of the respiratory system (ART strategy), is able to increase 28-day survival in patients with acute respiratory distress syndrome compared to conventional treatment (ARDSNet strategy). Objective To describe the data management process and statistical analysis plan. Methods The statistical analysis plan was designed by the trial executive committee and reviewed and approved by the trial steering committee. We provide an overview of the trial design with a special focus on describing the primary (28-day survival) and secondary outcomes. We describe our data management process, data monitoring committee, interim analyses, and sample size calculation. We describe our planned statistical analyses for primary and secondary outcomes as well as pre-specified subgroup analyses. We also provide details for presenting results, including mock tables for baseline characteristics, adherence to the protocol and effect on clinical outcomes. Conclusion According to best trial practice, we report our statistical analysis plan and data management plan prior to locking the database and beginning analyses. We anticipate that this document will prevent analysis bias and enhance the utility of the reported results. Trial registration ClinicalTrials.gov number, NCT01374022. PMID:28977255

Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis.

PubMed

Blasco, H; Błaszczyński, J; Billaut, J C; Nadal-Desbarats, L; Pradat, P F; Devos, D; Moreau, C; Andres, C R; Emond, P; Corcia, P; Słowiński, R

2015-02-01

Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients. Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA) allowed satisfactory discrimination (72.7%) between ALS and non-ALS patients. Some discriminant metabolites were identified: acetate, acetone, pyruvate and glutamine. The concentrations of acetate and pyruvate were also identified by univariate analysis as significantly different between ALS and non-ALS patients. DRSA correctly classified 68.7% of the cases and established rules involving some of the metabolites highlighted by OPLS-DA (acetate and acetone). Some rules identified potential biomarkers not revealed by OPLS-DA (beta-hydroxybutyrate). We also found a large number of common discriminating metabolites after Bayesian confirmation measures, particularly acetate, pyruvate, acetone and ascorbate, consistent with the pathophysiological pathways involved in ALS. DRSA provides a complementary method for improving the predictive performance of the multivariate data analysis usually used in metabolomics. This method could help in the identification of metabolites involved in disease pathogenesis. Interestingly, these different strategies mostly identified the same metabolites as being discriminant. The selection of strong decision rules with high value of Bayesian confirmation provides useful information about relevant condition-decision relationships not otherwise revealed in metabolomics data. Copyright © 2014 Elsevier Inc. All rights reserved.

Robust Strategy for Rocket Engine Health Monitoring

NASA Technical Reports Server (NTRS)

Santi, L. Michael

2001-01-01

Monitoring the health of rocket engine systems is essentially a two-phase process. The acquisition phase involves sensing physical conditions at selected locations, converting physical inputs to electrical signals, conditioning the signals as appropriate to establish scale or filter interference, and recording results in a form that is easy to interpret. The inference phase involves analysis of results from the acquisition phase, comparison of analysis results to established health measures, and assessment of health indications. A variety of analytical tools may be employed in the inference phase of health monitoring. These tools can be separated into three broad categories: statistical, rule based, and model based. Statistical methods can provide excellent comparative measures of engine operating health. They require well-characterized data from an ensemble of "typical" engines, or "golden" data from a specific test assumed to define the operating norm in order to establish reliable comparative measures. Statistical methods are generally suitable for real-time health monitoring because they do not deal with the physical complexities of engine operation. The utility of statistical methods in rocket engine health monitoring is hindered by practical limits on the quantity and quality of available data. This is due to the difficulty and high cost of data acquisition, the limited number of available test engines, and the problem of simulating flight conditions in ground test facilities. In addition, statistical methods incur a penalty for disregarding flow complexity and are therefore limited in their ability to define performance shift causality. Rule based methods infer the health state of the engine system based on comparison of individual measurements or combinations of measurements with defined health norms or rules. This does not mean that rule based methods are necessarily simple. Although binary yes-no health assessment can sometimes be established by relatively simple rules, the causality assignment needed for refined health monitoring often requires an exceptionally complex rule base involving complicated logical maps. Structuring the rule system to be clear and unambiguous can be difficult, and the expert input required to maintain a large logic network and associated rule base can be prohibitive.

[Organizational climate and burnout syndrome].

PubMed

Lubrańska, Anna

2011-01-01

The paper addresses the issue of organizational climate and burnout syndrome. It has been assumed that burnout syndrome is dependent on work climate (organizational climate), therefore, two concepts were analyzed: by D. Kolb (organizational climate) and by Ch. Maslach (burnout syndrome). The research involved 239 persons (122 woman, 117 men), aged 21-66. In the study Maslach Burnout Inventory (MBI) and Inventory of Organizational Climate were used. The results of statistical methods (correlation analysis, one-variable analysis of variance and regression analysis) evidenced a strong relationship between organizational climate and burnout dimension. As depicted by the results, there are important differences in the level of burnout between the study participants who work in different types of organizational climate. The results of the statistical analyses indicate that the organizational climate determines burnout syndrome. Therefore, creating supportive conditions at the workplace might reduce the risk of burnout.

Using the MCNP Taylor series perturbation feature (efficiently) for shielding problems

NASA Astrophysics Data System (ADS)

Favorite, Jeffrey

2017-09-01

The Taylor series or differential operator perturbation method, implemented in MCNP and invoked using the PERT card, can be used for efficient parameter studies in shielding problems. This paper shows how only two PERT cards are needed to generate an entire parameter study, including statistical uncertainty estimates (an additional three PERT cards can be used to give exact statistical uncertainties). One realistic example problem involves a detailed helium-3 neutron detector model and its efficiency as a function of the density of its high-density polyethylene moderator. The MCNP differential operator perturbation capability is extremely accurate for this problem. A second problem involves the density of the polyethylene reflector of the BeRP ball and is an example of first-order sensitivity analysis using the PERT capability. A third problem is an analytic verification of the PERT capability.

FADTTSter: accelerating hypothesis testing with functional analysis of diffusion tensor tract statistics

NASA Astrophysics Data System (ADS)

Noel, Jean; Prieto, Juan C.; Styner, Martin

2017-03-01

Functional Analysis of Diffusion Tensor Tract Statistics (FADTTS) is a toolbox for analysis of white matter (WM) fiber tracts. It allows associating diffusion properties along major WM bundles with a set of covariates of interest, such as age, diagnostic status and gender, and the structure of the variability of these WM tract properties. However, to use this toolbox, a user must have an intermediate knowledge in scripting languages (MATLAB). FADTTSter was created to overcome this issue and make the statistical analysis accessible to any non-technical researcher. FADTTSter is actively being used by researchers at the University of North Carolina. FADTTSter guides non-technical users through a series of steps including quality control of subjects and fibers in order to setup the necessary parameters to run FADTTS. Additionally, FADTTSter implements interactive charts for FADTTS' outputs. This interactive chart enhances the researcher experience and facilitates the analysis of the results. FADTTSter's motivation is to improve usability and provide a new analysis tool to the community that complements FADTTS. Ultimately, by enabling FADTTS to a broader audience, FADTTSter seeks to accelerate hypothesis testing in neuroimaging studies involving heterogeneous clinical data and diffusion tensor imaging. This work is submitted to the Biomedical Applications in Molecular, Structural, and Functional Imaging conference. The source code of this application is available in NITRC.

Laterality Differences in Child Stutterers: Heterogeneity, Severity Levels, and Statistical Treatments.

ERIC Educational Resources Information Center

Blood, Gordon W.

1985-01-01

Results of a study involving 76 stutterers and 76 nonstutterers (seven to 15 years old) included (1) a right- ear preference for both groups; (2) differences in dichotic stuttering and nonstuttering Ss; and (3) a relationship between stuttering severity and hemispheric dominance dependency on manner of data analysis. (Author/CL)

The Acquisition of Gender Labels in Infancy: Implications for Gender-Typed Play

ERIC Educational Resources Information Center

Zosuls, Kristina M.; Ruble, Diane N.; Tamis-LeMonda, Catherine S.; Shrout, Patrick E.; Bornstein, Marc H.; Greulich, Faith K.

2009-01-01

Two aspects of children's early gender development--the spontaneous production of gender labels and gender-typed play--were examined longitudinally in a sample of 82 children. Survival analysis, a statistical technique well suited to questions involving developmental transitions, was used to investigate the timing of the onset of children's gender…

Adolescent Pregnancy in an Urban Environment: Issues, Programs, and Evaluation.

ERIC Educational Resources Information Center

Hardy, Janet B.; Zabin, Laurie Schwab

An in-depth discussion of national and local statistics regarding teenage and adolescent pregnancy and the developmental issues involved opens this analysis. Problems and adverse consequences of adolescent pregnancy in an urban setting are explored using a city-wide random sample of adolescent births. A model pregnancy and parenting program and…

Students' Initial Knowledge State and Test Design: Towards a Valid and Reliable Test Instrument

ERIC Educational Resources Information Center

CoPo, Antonio Roland I.

2015-01-01

Designing a good test instrument involves specifications, test construction, validation, try-out, analysis and revision. The initial knowledge state of forty (40) tertiary students enrolled in Business Statistics course was determined and the same test instrument undergoes validation. The designed test instrument did not only reveal the baseline…

Parent Expectations and Planning for College. Statistical Analysis Report. NCES 2008-079

ERIC Educational Resources Information Center

Lippman, Laura; Guzman, Lina; Keith, Julie Dombrowski; Kinukawa, Akemi; Shwalb, Rebecca; Tice, Peter

2008-01-01

This report uses data from the 2003 National Household Education Surveys Program (NHES) Parent and Family Involvement Survey (PFI) to examine the characteristics associated with the educational expectations parents had for their children and the postsecondary education planning practices families and schools engaged in. The results presented in…

75 FR 47592 - Final Test Guideline; Product Performance of Skin-applied Insect Repellents of Insect and Other...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-06

... considerations affecting the design and conduct of repellent studies when human subjects are involved. Any... recommendations for the design and execution of studies to evaluate the performance of pesticide products intended... recommends appropriate study designs and methods for selecting subjects, statistical analysis, and reporting...

Editorial: Introduction to the Special Section on Causal Inference in Cross Sectional and Longitudinal Mediational Models

PubMed Central

West, Stephen G.

2016-01-01

Psychologists have long had interest in the processes through which antecedent variables produce their effects on the outcomes of ultimate interest (e.g., Wood-worth's Stimulus-Organism-Response model). Models involving such meditational processes have characterized many of the important psychological theories of the 20th century and continue to the present day. However, it was not until Judd and Kenny (1981) and Baron and Kenny (1986) combined ideas from experimental design and structural equation modeling that statistical methods for directly testing such models, now known as mediation analysis, began to be developed. Methodologists have improved these statistical methods, developing new, more efficient estimators for mediated effects. They have also extended mediation analysis to multilevel data structures, models involving multiple mediators, models in which interactions occur, and an array of noncontinuous outcome measures (see MacKinnon, 2008). This work nicely maps on to key questions of applied researchers and has led to an outpouring of research testing meditational models (As of August, 2011, Baron and Kenny's article has had over 24,000 citations according to Google Scholar). PMID:26736046

Data integration aids understanding of butterfly-host plant networks

NASA Astrophysics Data System (ADS)

Muto-Fujita, Ai; Takemoto, Kazuhiro; Kanaya, Shigehiko; Nakazato, Takeru; Tokimatsu, Toshiaki; Matsumoto, Natsushi; Kono, Mayo; Chubachi, Yuko; Ozaki, Katsuhisa; Kotera, Masaaki

2017-03-01

Although host-plant selection is a central topic in ecology, its general underpinnings are poorly understood. Here, we performed a case study focusing on the publicly available data on Japanese butterflies. A combined statistical analysis of plant-herbivore relationships and taxonomy revealed that some butterfly subfamilies in different families feed on the same plant families, and the occurrence of this phenomenon more than just by chance, thus indicating the independent acquisition of adaptive phenotypes to the same hosts. We consequently integrated plant-herbivore and plant-compound relationship data and conducted a statistical analysis to identify compounds unique to host plants of specific butterfly families. Some of the identified plant compounds are known to attract certain butterfly groups while repelling others. The additional incorporation of insect-compound relationship data revealed potential metabolic processes that are related to host plant selection. Our results demonstrate that data integration enables the computational detection of compounds putatively involved in particular interspecies interactions and that further data enrichment and integration of genomic and transcriptomic data facilitates the unveiling of the molecular mechanisms involved in host plant selection.

Data integration aids understanding of butterfly–host plant networks

PubMed Central

Muto-Fujita, Ai; Takemoto, Kazuhiro; Kanaya, Shigehiko; Nakazato, Takeru; Tokimatsu, Toshiaki; Matsumoto, Natsushi; Kono, Mayo; Chubachi, Yuko; Ozaki, Katsuhisa; Kotera, Masaaki

2017-01-01

Although host-plant selection is a central topic in ecology, its general underpinnings are poorly understood. Here, we performed a case study focusing on the publicly available data on Japanese butterflies. A combined statistical analysis of plant–herbivore relationships and taxonomy revealed that some butterfly subfamilies in different families feed on the same plant families, and the occurrence of this phenomenon more than just by chance, thus indicating the independent acquisition of adaptive phenotypes to the same hosts. We consequently integrated plant–herbivore and plant–compound relationship data and conducted a statistical analysis to identify compounds unique to host plants of specific butterfly families. Some of the identified plant compounds are known to attract certain butterfly groups while repelling others. The additional incorporation of insect–compound relationship data revealed potential metabolic processes that are related to host plant selection. Our results demonstrate that data integration enables the computational detection of compounds putatively involved in particular interspecies interactions and that further data enrichment and integration of genomic and transcriptomic data facilitates the unveiling of the molecular mechanisms involved in host plant selection. PMID:28262809

Trucks involved in fatal accidents factbook 2007.

DOT National Transportation Integrated Search

2010-01-01

This document presents aggregate statistics on trucks involved in traffic accidents in 2007. The : statistics are derived from the Trucks Involved in Fatal Accidents (TIFA) file, compiled by the : University of Michigan Transportation Research Instit...

Buses involved in fatal accidents factbook 2007

DOT National Transportation Integrated Search

2010-03-01

This document presents aggregate statistics on buses involved in traffic accidents in 2007. The : statistics are derived from the Buses Involved in Fatal Accidents (BIFA) file, compiled by the : University of Michigan Transportation Research Institut...

Trucks involved in fatal accidents factbook 2008.

DOT National Transportation Integrated Search

2011-03-01

This document presents aggregate statistics on trucks involved in traffic accidents in 2008. The : statistics are derived from the Trucks Involved in Fatal Accidents (TIFA) file, compiled by the : University of Michigan Transportation Research Instit...

New U.S. Geological Survey Method for the Assessment of Reserve Growth

USGS Publications Warehouse

Klett, Timothy R.; Attanasi, E.D.; Charpentier, Ronald R.; Cook, Troy A.; Freeman, P.A.; Gautier, Donald L.; Le, Phuong A.; Ryder, Robert T.; Schenk, Christopher J.; Tennyson, Marilyn E.; Verma, Mahendra K.

2011-01-01

Reserve growth is defined as the estimated increases in quantities of crude oil, natural gas, and natural gas liquids that have the potential to be added to remaining reserves in discovered accumulations through extension, revision, improved recovery efficiency, and additions of new pools or reservoirs. A new U.S. Geological Survey method was developed to assess the reserve-growth potential of technically recoverable crude oil and natural gas to be added to reserves under proven technology currently in practice within the trend or play, or which reasonably can be extrapolated from geologically similar trends or plays. This method currently is in use to assess potential additions to reserves in discovered fields of the United States. The new approach involves (1) individual analysis of selected large accumulations that contribute most to reserve growth, and (2) conventional statistical modeling of reserve growth in remaining accumulations. This report will focus on the individual accumulation analysis. In the past, the U.S. Geological Survey estimated reserve growth by statistical methods using historical recoverable-quantity data. Those statistical methods were based on growth rates averaged by the number of years since accumulation discovery. Accumulations in mature petroleum provinces with volumetrically significant reserve growth, however, bias statistical models of the data; therefore, accumulations with significant reserve growth are best analyzed separately from those with less significant reserve growth. Large (greater than 500 million barrels) and older (with respect to year of discovery) oil accumulations increase in size at greater rates late in their development history in contrast to more recently discovered accumulations that achieve most growth early in their development history. Such differences greatly affect the statistical methods commonly used to forecast reserve growth. The individual accumulation-analysis method involves estimating the in-place petroleum quantity and its uncertainty, as well as the estimated (forecasted) recoverability and its respective uncertainty. These variables are assigned probabilistic distributions and are combined statistically to provide probabilistic estimates of ultimate recoverable quantities. Cumulative production and remaining reserves are then subtracted from the estimated ultimate recoverable quantities to provide potential reserve growth. In practice, results of the two methods are aggregated to various scales, the highest of which includes an entire country or the world total. The aggregated results are reported along with the statistically appropriate uncertainties.

Statistics of Delta v magnitude for a trajectory correction maneuver containing deterministic and random components

NASA Technical Reports Server (NTRS)

Bollman, W. E.; Chadwick, C.

1982-01-01

A number of interplanetary missions now being planned involve placing deterministic maneuvers along the flight path to alter the trajectory. Lee and Boain (1973) examined the statistics of trajectory correction maneuver (TCM) magnitude with no deterministic ('bias') component. The Delta v vector magnitude statistics were generated for several values of random Delta v standard deviations using expansions in terms of infinite hypergeometric series. The present investigation uses a different technique (Monte Carlo simulation) to generate Delta v magnitude statistics for a wider selection of random Delta v standard deviations and also extends the analysis to the case of nonzero deterministic Delta v's. These Delta v magnitude statistics are plotted parametrically. The plots are useful in assisting the analyst in quickly answering questions about the statistics of Delta v magnitude for single TCM's consisting of both a deterministic and a random component. The plots provide quick insight into the nature of the Delta v magnitude distribution for the TCM.

Quantitative Analysis of Venus Radar Backscatter Data in ArcGIS

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

Sources of Safety Data and Statistical Strategies for Design and Analysis: Clinical Trials.

PubMed

Zink, Richard C; Marchenko, Olga; Sanchez-Kam, Matilde; Ma, Haijun; Jiang, Qi

2018-03-01

There has been an increased emphasis on the proactive and comprehensive evaluation of safety endpoints to ensure patient well-being throughout the medical product life cycle. In fact, depending on the severity of the underlying disease, it is important to plan for a comprehensive safety evaluation at the start of any development program. Statisticians should be intimately involved in this process and contribute their expertise to study design, safety data collection, analysis, reporting (including data visualization), and interpretation. In this manuscript, we review the challenges associated with the analysis of safety endpoints and describe the safety data that are available to influence the design and analysis of premarket clinical trials. We share our recommendations for the statistical and graphical methodologies necessary to appropriately analyze, report, and interpret safety outcomes, and we discuss the advantages and disadvantages of safety data obtained from clinical trials compared to other sources. Clinical trials are an important source of safety data that contribute to the totality of safety information available to generate evidence for regulators, sponsors, payers, physicians, and patients. This work is a result of the efforts of the American Statistical Association Biopharmaceutical Section Safety Working Group.

Measurements and analysis in imaging for biomedical applications

NASA Astrophysics Data System (ADS)

Hoeller, Timothy L.

2009-02-01

A Total Quality Management (TQM) approach can be used to analyze data from biomedical optical and imaging platforms of tissues. A shift from individuals to teams, partnerships, and total participation are necessary from health care groups for improved prognostics using measurement analysis. Proprietary measurement analysis software is available for calibrated, pixel-to-pixel measurements of angles and distances in digital images. Feature size, count, and color are determinable on an absolute and comparative basis. Although changes in images of histomics are based on complex and numerous factors, the variation of changes in imaging analysis to correlations of time, extent, and progression of illness can be derived. Statistical methods are preferred. Applications of the proprietary measurement software are available for any imaging platform. Quantification of results provides improved categorization of illness towards better health. As health care practitioners try to use quantified measurement data for patient diagnosis, the techniques reported can be used to track and isolate causes better. Comparisons, norms, and trends are available from processing of measurement data which is obtained easily and quickly from Scientific Software and methods. Example results for the class actions of Preventative and Corrective Care in Ophthalmology and Dermatology, respectively, are provided. Improved and quantified diagnosis can lead to better health and lower costs associated with health care. Systems support improvements towards Lean and Six Sigma affecting all branches of biology and medicine. As an example for use of statistics, the major types of variation involving a study of Bone Mineral Density (BMD) are examined. Typically, special causes in medicine relate to illness and activities; whereas, common causes are known to be associated with gender, race, size, and genetic make-up. Such a strategy of Continuous Process Improvement (CPI) involves comparison of patient results to baseline data using F-statistics. Self-parings over time are also useful. Special and common causes are identified apart from aging in applying the statistical methods. In the future, implementation of imaging measurement methods by research staff, doctors, and concerned patient partners result in improved health diagnosis, reporting, and cause determination. The long-term prospects for quantified measurements are better quality in imaging analysis with applications of higher utility for heath care providers.

Searching for molecular markers in head and neck squamous cell carcinomas (HNSCC) by statistical and bioinformatic analysis of larynx-derived SAGE libraries

PubMed Central

Silveira, Nelson JF; Varuzza, Leonardo; Machado-Lima, Ariane; Lauretto, Marcelo S; Pinheiro, Daniel G; Rodrigues, Rodrigo V; Severino, Patrícia; Nobrega, Francisco G; Silva, Wilson A; de B Pereira, Carlos A; Tajara, Eloiza H

2008-01-01

Background Head and neck squamous cell carcinoma (HNSCC) is one of the most common malignancies in humans. The average 5-year survival rate is one of the lowest among aggressive cancers, showing no significant improvement in recent years. When detected early, HNSCC has a good prognosis, but most patients present metastatic disease at the time of diagnosis, which significantly reduces survival rate. Despite extensive research, no molecular markers are currently available for diagnostic or prognostic purposes. Methods Aiming to identify differentially-expressed genes involved in laryngeal squamous cell carcinoma (LSCC) development and progression, we generated individual Serial Analysis of Gene Expression (SAGE) libraries from a metastatic and non-metastatic larynx carcinoma, as well as from a normal larynx mucosa sample. Approximately 54,000 unique tags were sequenced in three libraries. Results Statistical data analysis identified a subset of 1,216 differentially expressed tags between tumor and normal libraries, and 894 differentially expressed tags between metastatic and non-metastatic carcinomas. Three genes displaying differential regulation, one down-regulated (KRT31) and two up-regulated (BST2, MFAP2), as well as one with a non-significant differential expression pattern (GNA15) in our SAGE data were selected for real-time polymerase chain reaction (PCR) in a set of HNSCC samples. Consistent with our statistical analysis, quantitative PCR confirmed the upregulation of BST2 and MFAP2 and the downregulation of KRT31 when samples of HNSCC were compared to tumor-free surgical margins. As expected, GNA15 presented a non-significant differential expression pattern when tumor samples were compared to normal tissues. Conclusion To the best of our knowledge, this is the first study reporting SAGE data in head and neck squamous cell tumors. Statistical analysis was effective in identifying differentially expressed genes reportedly involved in cancer development. The differential expression of a subset of genes was confirmed in additional larynx carcinoma samples and in carcinomas from a distinct head and neck subsite. This result suggests the existence of potential common biomarkers for prognosis and targeted-therapy development in this heterogeneous type of tumor. PMID:19014460

High efficiency family shuffling based on multi-step PCR and in vivo DNA recombination in yeast: statistical and functional analysis of a combinatorial library between human cytochrome P450 1A1 and 1A2.

PubMed

Abécassis, V; Pompon, D; Truan, G

2000-10-15

The design of a family shuffling strategy (CLERY: Combinatorial Libraries Enhanced by Recombination in Yeast) associating PCR-based and in vivo recombination and expression in yeast is described. This strategy was tested using human cytochrome P450 CYP1A1 and CYP1A2 as templates, which share 74% nucleotide sequence identity. Construction of highly shuffled libraries of mosaic structures and reduction of parental gene contamination were two major goals. Library characterization involved multiprobe hybridization on DNA macro-arrays. The statistical analysis of randomly selected clones revealed a high proportion of chimeric genes (86%) and a homogeneous representation of the parental contribution among the sequences (55.8 +/- 2.5% for parental sequence 1A2). A microtiter plate screening system was designed to achieve colorimetric detection of polycyclic hydrocarbon hydroxylation by transformed yeast cells. Full sequences of five randomly picked and five functionally selected clones were analyzed. Results confirmed the shuffling efficiency and allowed calculation of the average length of sequence exchange and mutation rates. The efficient and statistically representative generation of mosaic structures by this type of family shuffling in a yeast expression system constitutes a novel and promising tool for structure-function studies and tuning enzymatic activities of multicomponent eucaryote complexes involving non-soluble enzymes.

Mild cognitive impairment and fMRI studies of brain functional connectivity: the state of the art

PubMed Central

Farràs-Permanyer, Laia; Guàrdia-Olmos, Joan; Peró-Cebollero, Maribel

2015-01-01

In the last 15 years, many articles have studied brain connectivity in Mild Cognitive Impairment patients with fMRI techniques, seemingly using different connectivity statistical models in each investigation to identify complex connectivity structures so as to recognize typical behavior in this type of patient. This diversity in statistical approaches may cause problems in results comparison. This paper seeks to describe how researchers approached the study of brain connectivity in MCI patients using fMRI techniques from 2002 to 2014. The focus is on the statistical analysis proposed by each research group in reference to the limitations and possibilities of those techniques to identify some recommendations to improve the study of functional connectivity. The included articles came from a search of Web of Science and PsycINFO using the following keywords: f MRI, MCI, and functional connectivity. Eighty-one papers were found, but two of them were discarded because of the lack of statistical analysis. Accordingly, 79 articles were included in this review. We summarized some parts of the articles, including the goal of every investigation, the cognitive paradigm and methods used, brain regions involved, use of ROI analysis and statistical analysis, emphasizing on the connectivity estimation model used in each investigation. The present analysis allowed us to confirm the remarkable variability of the statistical analysis methods found. Additionally, the study of brain connectivity in this type of population is not providing, at the moment, any significant information or results related to clinical aspects relevant for prediction and treatment. We propose to follow guidelines for publishing fMRI data that would be a good solution to the problem of study replication. The latter aspect could be important for future publications because a higher homogeneity would benefit the comparison between publications and the generalization of results. PMID:26300802

Statistical identification of stimulus-activated network nodes in multi-neuron voltage-sensitive dye optical recordings.

PubMed

Fathiazar, Elham; Anemuller, Jorn; Kretzberg, Jutta

2016-08-01

Voltage-Sensitive Dye (VSD) imaging is an optical imaging method that allows measuring the graded voltage changes of multiple neurons simultaneously. In neuroscience, this method is used to reveal networks of neurons involved in certain tasks. However, the recorded relative dye fluorescence changes are usually low and signals are superimposed by noise and artifacts. Therefore, establishing a reliable method to identify which cells are activated by specific stimulus conditions is the first step to identify functional networks. In this paper, we present a statistical method to identify stimulus-activated network nodes as cells, whose activities during sensory network stimulation differ significantly from the un-stimulated control condition. This method is demonstrated based on voltage-sensitive dye recordings from up to 100 neurons in a ganglion of the medicinal leech responding to tactile skin stimulation. Without relying on any prior physiological knowledge, the network nodes identified by our statistical analysis were found to match well with published cell types involved in tactile stimulus processing and to be consistent across stimulus conditions and preparations.

Gene expression profiling of Japanese psoriatic skin reveals an increased activity in molecular stress and immune response signals.

PubMed

Kulski, Jerzy K; Kenworthy, William; Bellgard, Matthew; Taplin, Ross; Okamoto, Koichi; Oka, Akira; Mabuchi, Tomotaka; Ozawa, Akira; Tamiya, Gen; Inoko, Hidetoshi

2005-12-01

Gene expression profiling was performed on biopsies of affected and unaffected psoriatic skin and normal skin from seven Japanese patients to obtain insights into the pathways that control this disease. HUG95A Affymetrix DNA chips that contained oligonucleotide arrays of approximately 12,000 well-characterized human genes were used in the study. The statistical analysis of the Affymetrix data, based on the ranking of the Student t-test statistic, revealed a complex regulation of molecular stress and immune gene responses. The majority of the 266 induced genes in affected and unaffected psoriatic skin were involved with interferon mediation, immunity, cell adhesion, cytoskeleton restructuring, protein trafficking and degradation, RNA regulation and degradation, signalling transduction, apoptosis and atypical epidermal cellular proliferation and differentiation. The disturbances in the normal protein degradation equilibrium of skin were reflected by the significant increase in the gene expression of various protease inhibitors and proteinases, including the induced components of the ATP/ubiquitin-dependent non-lysosomal proteolytic pathway that is involved with peptide processing and presentation to T cells. Some of the up-regulated genes, such as TGM1, IVL, FABP5, CSTA and SPRR, are well-known psoriatic markers involved in atypical epidermal cellular organization and differentiation. In the comparison between the affected and unaffected psoriatic skin, the transcription factor JUNB was found at the top of the statistical rankings for the up-regulated genes in affected skin, suggesting that it has an important but as yet undefined role in psoriasis. Our gene expression data and analysis suggest that psoriasis is a chronic interferon- and T-cell-mediated immune disease of the skin where the imbalance in epidermal cellular structure, growth and differentiation arises from the molecular antiviral stress signals initiating inappropriate immune responses.

An updated and expanded meta-analysis of nonresident fathering and child well-being.

PubMed

Adamsons, Kari; Johnson, Sara K

2013-08-01

Since Amato and Gilbreth's (1999) meta-analysis of nonresident father involvement and child well-being, nonmarital childbirths and nonresident father involvement both have increased. The unknown implications of such changes motivated the present study, a meta-analytic review of 52 studies of nonresident father involvement and child well-being. Consistent with Amato and Gilbreth, we found that positive forms of involvement were associated with benefits for children, with a small but statistically significant effect size. Amounts of father-child contact and financial provision, however, were not associated with child well-being. Going beyond Amato and Gilbreth, we analyzed the associations between different types of fathering and overall child well-being, and between overall father involvement and different types of child well-being. We found that nonresident father involvement was most strongly associated with children's social well-being and also was associated with children's emotional well-being, academic achievement, and behavioral adjustment. The forms of father involvement most strongly associated with child well-being were involvement in child-related activities, having positive father-child relationships, and engaging in multiple forms of involvement. Moderator analyses demonstrated variation in effect sizes based on both study characteristics and demographic variables. We discuss the implications of these findings for policy and practice. © 2013 American Psychological Association

Design and analysis of multiple diseases genome-wide association studies without controls.

PubMed

Chen, Zhongxue; Huang, Hanwen; Ng, Hon Keung Tony

2012-11-15

In genome-wide association studies (GWAS), multiple diseases with shared controls is one of the case-control study designs. If data obtained from these studies are appropriately analyzed, this design can have several advantages such as improving statistical power in detecting associations and reducing the time and cost in the data collection process. In this paper, we propose a study design for GWAS which involves multiple diseases but without controls. We also propose corresponding statistical data analysis strategy for GWAS with multiple diseases but no controls. Through a simulation study, we show that the statistical association test with the proposed study design is more powerful than the test with single disease sharing common controls, and it has comparable power to the overall test based on the whole dataset including the controls. We also apply the proposed method to a real GWAS dataset to illustrate the methodologies and the advantages of the proposed design. Some possible limitations of this study design and testing method and their solutions are also discussed. Our findings indicate that the proposed study design and statistical analysis strategy could be more efficient than the usual case-control GWAS as well as those with shared controls. Copyright © 2012 Elsevier B.V. All rights reserved.

Trend analysis of body weight parameters, mortality, and incidence of spontaneous tumors in Tg.rasH2 mice.

PubMed

Paranjpe, Madhav G; Denton, Melissa D; Vidmar, Tom; Elbekai, Reem H

2014-01-01

Carcinogenicity studies have been performed in conventional 2-year rodent studies for at least 3 decades, whereas the short-term carcinogenicity studies in transgenic mice, such as Tg.rasH2, have only been performed over the last decade. In the 2-year conventional rodent studies, interlinked problems, such as increasing trends in the initial body weights, increased body weight gains, high incidence of spontaneous tumors, and low survival, that complicate the interpretation of findings have been well established. However, these end points have not been evaluated in the short-term carcinogenicity studies involving the Tg.rasH2 mice. In this article, we present retrospective analysis of data obtained from control groups in 26-week carcinogenicity studies conducted in Tg.rasH2 mice since 2004. Our analysis showed statistically significant decreasing trends in initial body weights of both sexes. Although the terminal body weights did not show any significant trends, there was a statistically significant increasing trend toward body weight gains, more so in males than in females, which correlated with increasing trends in the food consumption. There were no statistically significant alterations in mortality trends. In addition, the incidence of all common spontaneous tumors remained fairly constant with no statistically significant differences in trends. © The Author(s) 2014.

Proteomic analysis of early phase of conidia germination in Aspergillus nidulans.

PubMed

Oh, Young Taek; Ahn, Chun-Seob; Kim, Jeong Geun; Ro, Hyeon-Su; Lee, Chang-Won; Kim, Jae Won

2010-03-01

In order to investigate proteins involved in early phase of conidia germination, proteomic analysis was performed using two-dimensional gel electrophoresis (2D-GE) in conjunction with MALDI-TOF mass spectrometry (MS). The expression levels of 241 proteins varied quantitatively with statistical significance (P<0.05) at the early phase of the germination stage. Out of these 57 were identified by MALDI-TOF MS. Through classification of physiological functions from Conserved Domain Database analysis, among the identified proteins, 21, 13, and 6 proteins were associated with energy metabolism, protein synthesis, and protein folding process, respectively. Interestingly, eight proteins, which are involved in detoxification of reactive oxygen species (ROS) including catalase A, thioredoxin reductase, and mitochondrial peroxiredoxin, were also identified. The expression levels of the genes were further confirmed using Northern blot and reverse transcriptase (RT)-PCR analyses. This study represents the first proteomic analysis of early phase of conidia germination and will contribute to a better understanding of the molecular events involved in conidia germination process. Copyright (c) 2009 Elsevier Inc. All rights reserved.

THE DAMAGING EFFECTS OF ALCOHOL: CHRONIC AND PATTERN ALCOHOL USE EXPLAIN WHY SEXUAL ASSAULT FIGURES HAVE NOT SIGNIFICANTLY DROPPED IN THE UNITED STATES MILITARY

DTIC Science & Technology

2015-10-01

Recommendations ······················································ 7 The Significance of Statistics ...further analysis and documentation in metrics in future surveys. This statistic , alone, in a public military report is enough to warrant an inquiry into...3 It is unknown how many of the total reported sexual assaults involved alcohol use. Other statistical reports indicate 32% of males in the

Constructing and Modifying Sequence Statistics for relevent Using informR in 𝖱

PubMed Central

Marcum, Christopher Steven; Butts, Carter T.

2015-01-01

The informR package greatly simplifies the analysis of complex event histories in 𝖱 by providing user friendly tools to build sufficient statistics for the relevent package. Historically, building sufficient statistics to model event sequences (of the form a→b) using the egocentric generalization of Butts’ (2008) relational event framework for modeling social action has been cumbersome. The informR package simplifies the construction of the complex list of arrays needed by the rem() model fitting for a variety of cases involving egocentric event data, multiple event types, and/or support constraints. This paper introduces these tools using examples from real data extracted from the American Time Use Survey. PMID:26185488

TERT rs2736098 polymorphism and cancer risk: results of a meta-analysis.

PubMed

Qi, Hao-Yu; Zou, Peng; Zhao, Lin; Zhu, Jue; Gu, Ai-Hua

2012-01-01

Several studies have demonstrated associations between the TERT rs2736098 single nucleotide polymorphisms (SNPs) and susceptibility to cancer development. However, there are conflicting results. A systematic meta-analysis was therefore performed to establish the cancer risk associated with the polymorphism. In this meta-analysis, a total of 6 case-control studies, including 5,567 cases and 6,191 controls, were included. Crude odds ratios with 95% confidence intervals were used to assess the strength of associations in several genetic models. Our results showed no association reaching the level of statistical significance for overall risk. Interestingly, in the stratified analyses (subdivided by ethnicity), significantly increased risks were found in the Asian subgroup which indicates the TERT rs2736098 polymorphism may have controversial involvement in cancer susceptibility. Overall, this meta-analysis indicates that the TERT rs2736098 polymorphism may have little involvement in cancer susceptibility.

Power flow as a complement to statistical energy analysis and finite element analysis

NASA Technical Reports Server (NTRS)

Cuschieri, J. M.

1987-01-01

Present methods of analysis of the structural response and the structure-borne transmission of vibrational energy use either finite element (FE) techniques or statistical energy analysis (SEA) methods. The FE methods are a very useful tool at low frequencies where the number of resonances involved in the analysis is rather small. On the other hand SEA methods can predict with acceptable accuracy the response and energy transmission between coupled structures at relatively high frequencies where the structural modal density is high and a statistical approach is the appropriate solution. In the mid-frequency range, a relatively large number of resonances exist which make finite element method too costly. On the other hand SEA methods can only predict an average level form. In this mid-frequency range a possible alternative is to use power flow techniques, where the input and flow of vibrational energy to excited and coupled structural components can be expressed in terms of input and transfer mobilities. This power flow technique can be extended from low to high frequencies and this can be integrated with established FE models at low frequencies and SEA models at high frequencies to form a verification of the method. This method of structural analysis using power flo and mobility methods, and its integration with SEA and FE analysis is applied to the case of two thin beams joined together at right angles.

A novel complete-case analysis to determine statistical significance between treatments in an intention-to-treat population of randomized clinical trials involving missing data.

PubMed

Liu, Wei; Ding, Jinhui

2018-04-01

The application of the principle of the intention-to-treat (ITT) to the analysis of clinical trials is challenged in the presence of missing outcome data. The consequences of stopping an assigned treatment in a withdrawn subject are unknown. It is difficult to make a single assumption about missing mechanisms for all clinical trials because there are complicated reactions in the human body to drugs due to the presence of complex biological networks, leading to data missing randomly or non-randomly. Currently there is no statistical method that can tell whether a difference between two treatments in the ITT population of a randomized clinical trial with missing data is significant at a pre-specified level. Making no assumptions about the missing mechanisms, we propose a generalized complete-case (GCC) analysis based on the data of completers. An evaluation of the impact of missing data on the ITT analysis reveals that a statistically significant GCC result implies a significant treatment effect in the ITT population at a pre-specified significance level unless, relative to the comparator, the test drug is poisonous to the non-completers as documented in their medical records. Applications of the GCC analysis are illustrated using literature data, and its properties and limits are discussed.

Analysis of longitudinal data from animals with missing values using SPSS.

PubMed

Duricki, Denise A; Soleman, Sara; Moon, Lawrence D F

2016-06-01

Testing of therapies for disease or injury often involves the analysis of longitudinal data from animals. Modern analytical methods have advantages over conventional methods (particularly when some data are missing), yet they are not used widely by preclinical researchers. Here we provide an easy-to-use protocol for the analysis of longitudinal data from animals, and we present a click-by-click guide for performing suitable analyses using the statistical package IBM SPSS Statistics software (SPSS). We guide readers through the analysis of a real-life data set obtained when testing a therapy for brain injury (stroke) in elderly rats. If a few data points are missing, as in this example data set (for example, because of animal dropout), repeated-measures analysis of covariance may fail to detect a treatment effect. An alternative analysis method, such as the use of linear models (with various covariance structures), and analysis using restricted maximum likelihood estimation (to include all available data) can be used to better detect treatment effects. This protocol takes 2 h to carry out.

An experiment on the impact of a neonicotinoid pesticide on honeybees: the value of a formal analysis of the data.

PubMed

Schick, Robert S; Greenwood, Jeremy J D; Buckland, Stephen T

2017-01-01

We assess the analysis of the data resulting from a field experiment conducted by Pilling et al. (PLoS ONE. doi: 10.1371/journal.pone.0077193, 5) on the potential effects of thiamethoxam on honeybees. The experiment had low levels of replication, so Pilling et al. concluded that formal statistical analysis would be misleading. This would be true if such an analysis merely comprised tests of statistical significance and if the investigators concluded that lack of significance meant little or no effect. However, an analysis that includes estimation of the size of any effects-with confidence limits-allows one to reach conclusions that are not misleading and that produce useful insights. For the data of Pilling et al., we use straightforward statistical analysis to show that the confidence limits are generally so wide that any effects of thiamethoxam could have been large without being statistically significant. Instead of formal analysis, Pilling et al. simply inspected the data and concluded that they provided no evidence of detrimental effects and from this that thiamethoxam poses a "low risk" to bees. Conclusions derived from the inspection of the data were not just misleading in this case but also are unacceptable in principle, for if data are inadequate for a formal analysis (or only good enough to provide estimates with wide confidence intervals), then they are bound to be inadequate as a basis for reaching any sound conclusions. Given that the data in this case are largely uninformative with respect to the treatment effect, any conclusions reached from such informal approaches can do little more than reflect the prior beliefs of those involved.

Video Games as a Context for Numeracy Development

ERIC Educational Resources Information Center

Thomas, Troy A.; Wiest, Lynda R.

2013-01-01

Troy Thomas and Lynda Wiest share an engaging lesson on statistics involving analysis of real-world data on the top ten video game sales in the United States during a one-week period. Three upper-primary classes completed the lesson, providing insight into the lesson's effectiveness. The lesson description includes attention to the manner in which…

A Pedagogical Approach to the Boltzmann Factor through Experiments and Simulations

ERIC Educational Resources Information Center

Battaglia, O. R.; Bonura, A.; Sperandeo-Mineo, R. M.

2009-01-01

The Boltzmann factor is the basis of a huge amount of thermodynamic and statistical physics, both classical and quantum. It governs the behaviour of all systems in nature that are exchanging energy with their environment. To understand why the expression has this specific form involves a deep mathematical analysis, whose flow of logic is hard to…

Fourier Descriptor Analysis and Unification of Voice Range Profile Contours: Method and Applications

ERIC Educational Resources Information Center

Pabon, Peter; Ternstrom, Sten; Lamarche, Anick

2011-01-01

Purpose: To describe a method for unified description, statistical modeling, and comparison of voice range profile (VRP) contours, even from diverse sources. Method: A morphologic modeling technique, which is based on Fourier descriptors (FDs), is applied to the VRP contour. The technique, which essentially involves resampling of the curve of the…

Tolerancing aspheres based on manufacturing statistics

NASA Astrophysics Data System (ADS)

Wickenhagen, S.; Möhl, A.; Fuchs, U.

2017-11-01

A standard way of tolerancing optical elements or systems is to perform a Monte Carlo based analysis within a common optical design software package. Although, different weightings and distributions are assumed they are all counting on statistics, which usually means several hundreds or thousands of systems for reliable results. Thus, employing these methods for small batch sizes is unreliable, especially when aspheric surfaces are involved. The huge database of asphericon was used to investigate the correlation between the given tolerance values and measured data sets. The resulting probability distributions of these measured data were analyzed aiming for a robust optical tolerancing process.

Extending Working Life: Which Competencies are Crucial in Near-Retirement Age?

PubMed

Wiktorowicz, Justyna

2018-01-01

Nowadays, one of the most important economic and social phenomena is population ageing. Due to the low activity rate of older people, one of the most important challenges is to take various actions involving active ageing, which is supposed to extending working life, and along with it-improve the competencies of older people. The aim of this paper is to evaluate the relevance of different competencies for extending working life, with limiting the analysis for Poland. The paper also assesses the competencies of mature Polish people (aged 50+, but still in working age). In the statistical analysis, I used logistic regression, as well as descriptive statistics and appropriate statistical tests. The results show that among the actions aimed at extending working life, the most important are those related to lifelong learning, targeted at improving the competencies of the older generation. The competencies (both soft and hard) of people aged 50+ are more important than their formal education.

Compound-Specific Isotope Analysis of Diesel Fuels in a Forensic Investigation

NASA Astrophysics Data System (ADS)

Muhammad, Syahidah; Frew, Russell; Hayman, Alan

2015-02-01

Compound-specific isotope analysis (CSIA) offers great potential as a tool to provide chemical evidence in a forensic investigation. Many attempts to trace environmental oil spills were successful where isotopic values were particularly distinct. However, difficulties arise when a large data set is analyzed and the isotopic differences between samples are subtle. In the present study, discrimination of diesel oils involved in a diesel theft case was carried out to infer the relatedness of the samples to potential source samples. This discriminatory analysis used a suite of hydrocarbon diagnostic indices, alkanes, to generate carbon and hydrogen isotopic data of the compositions of the compounds which were then processed using multivariate statistical analyses to infer the relatedness of the data set. The results from this analysis were put into context by comparing the data with the δ13C and δ2H of alkanes in commercial diesel samples obtained from various locations in the South Island of New Zealand. Based on the isotopic character of the alkanes, it is suggested that diesel fuels involved in the diesel theft case were distinguishable. This manuscript shows that CSIA when used in tandem with multivariate statistical analysis provide a defensible means to differentiate and source-apportion qualitatively similar oils at the molecular level. This approach was able to overcome confounding challenges posed by the near single-point source of origin i.e. the very subtle differences in isotopic values between the samples.

The multiple imputation method: a case study involving secondary data analysis.

PubMed

Walani, Salimah R; Cleland, Charles M

2015-05-01

To illustrate with the example of a secondary data analysis study the use of the multiple imputation method to replace missing data. Most large public datasets have missing data, which need to be handled by researchers conducting secondary data analysis studies. Multiple imputation is a technique widely used to replace missing values while preserving the sample size and sampling variability of the data. The 2004 National Sample Survey of Registered Nurses. The authors created a model to impute missing values using the chained equation method. They used imputation diagnostics procedures and conducted regression analysis of imputed data to determine the differences between the log hourly wages of internationally educated and US-educated registered nurses. The authors used multiple imputation procedures to replace missing values in a large dataset with 29,059 observations. Five multiple imputed datasets were created. Imputation diagnostics using time series and density plots showed that imputation was successful. The authors also present an example of the use of multiple imputed datasets to conduct regression analysis to answer a substantive research question. Multiple imputation is a powerful technique for imputing missing values in large datasets while preserving the sample size and variance of the data. Even though the chained equation method involves complex statistical computations, recent innovations in software and computation have made it possible for researchers to conduct this technique on large datasets. The authors recommend nurse researchers use multiple imputation methods for handling missing data to improve the statistical power and external validity of their studies.

Limbic and corpus callosum aberrations in adolescents with bipolar disorder: a tract-based spatial statistics analysis.

PubMed

Barnea-Goraly, Naama; Chang, Kiki D; Karchemskiy, Asya; Howe, Meghan E; Reiss, Allan L

2009-08-01

Bipolar disorder (BD) is a common and debilitating condition, often beginning in adolescence. Converging evidence from genetic and neuroimaging studies indicates that white matter abnormalities may be involved in BD. In this study, we investigated white matter structure in adolescents with familial bipolar disorder using diffusion tensor imaging (DTI) and a whole brain analysis. We analyzed DTI images using tract-based spatial statistics (TBSS), a whole-brain voxel-by-voxel analysis, to investigate white matter structure in 21 adolescents with BD, who also were offspring of at least one parent with BD, and 18 age- and IQ-matched control subjects. Fractional anisotropy (FA; a measure of diffusion anisotropy), trace values (average diffusivity), and apparent diffusion coefficient (ADC; a measure of overall diffusivity) were used as variables in this analysis. In a post hoc analysis, we correlated between FA values, behavioral measures, and medication exposure. Adolescents with BD had lower FA values than control subjects in the fornix, the left mid-posterior cingulate gyrus, throughout the corpus callosum, in fibers extending from the fornix to the thalamus, and in parietal and occipital corona radiata bilaterally. There were no significant between-group differences in trace or ADC values and no significant correlation between behavioral measures, medication exposure, and FA values. Significant white matter tract alterations in adolescents with BD were observed in regions involved in emotional, behavioral, and cognitive regulation. These results suggest that alterations in white matter are present early in the course of disease in familial BD.

Compound-specific isotope analysis of diesel fuels in a forensic investigation

PubMed Central

Muhammad, Syahidah A.; Frew, Russell D.; Hayman, Alan R.

2015-01-01

Compound-specific isotope analysis (CSIA) offers great potential as a tool to provide chemical evidence in a forensic investigation. Many attempts to trace environmental oil spills were successful where isotopic values were particularly distinct. However, difficulties arise when a large data set is analyzed and the isotopic differences between samples are subtle. In the present study, discrimination of diesel oils involved in a diesel theft case was carried out to infer the relatedness of the samples to potential source samples. This discriminatory analysis used a suite of hydrocarbon diagnostic indices, alkanes, to generate carbon and hydrogen isotopic data of the compositions of the compounds which were then processed using multivariate statistical analyses to infer the relatedness of the data set. The results from this analysis were put into context by comparing the data with the δ13C and δ2H of alkanes in commercial diesel samples obtained from various locations in the South Island of New Zealand. Based on the isotopic character of the alkanes, it is suggested that diesel fuels involved in the diesel theft case were distinguishable. This manuscript shows that CSIA when used in tandem with multivariate statistical analysis provide a defensible means to differentiate and source-apportion qualitatively similar oils at the molecular level. This approach was able to overcome confounding challenges posed by the near single-point source of origin, i.e., the very subtle differences in isotopic values between the samples. PMID:25774366

Evaluation of Time Spent by Pharmacists and Nurses Based on the Location of Pharmacist Involvement in Medication History Collection.

PubMed

Chhabra, Anmol; Quinn, Andrea; Ries, Amanda

2018-01-01

Accurate history collection is integral to medication reconciliation. Studies support pharmacy involvement in the process, but assessment of global time spent is limited. The authors hypothesized the location of a medication-focused interview would impact time spent. The objective was to compare time spent by pharmacists and nurses based on the location of a medication-focused interview. Time spent by the interviewing pharmacist, admitting nurse, and centralized pharmacist verifying admission orders was collected. Patient groups were based on whether the interview was conducted in the emergency department (ED) or medical floor. The primary end point was a composite of the 3 time points. Secondary end points were individual time components and number and types of transcription discrepancies identified during medical floor interviews. Pharmacists and nurses spent an average of ten fewer minutes per ED patient versus a medical floor patient ( P = .028). Secondary end points were not statistically significant. Transcription discrepancies were identified at a rate of 1 in 4 medications. Post hoc analysis revealed the time spent by pharmacists and nurses was 2.4 minutes shorter per medication when interviewed in the ED ( P < .001). The primary outcome was statistically and clinically significant. Limitations included inability to blind and lack of cost-saving analysis. Pharmacist involvement in ED medication reconciliation leads to time savings during the admission process.

Assessing signal-to-noise in quantitative proteomics: multivariate statistical analysis in DIGE experiments.

PubMed

Friedman, David B

2012-01-01

All quantitative proteomics experiments measure variation between samples. When performing large-scale experiments that involve multiple conditions or treatments, the experimental design should include the appropriate number of individual biological replicates from each condition to enable the distinction between a relevant biological signal from technical noise. Multivariate statistical analyses, such as principal component analysis (PCA), provide a global perspective on experimental variation, thereby enabling the assessment of whether the variation describes the expected biological signal or the unanticipated technical/biological noise inherent in the system. Examples will be shown from high-resolution multivariable DIGE experiments where PCA was instrumental in demonstrating biologically significant variation as well as sample outliers, fouled samples, and overriding technical variation that would not be readily observed using standard univariate tests.

Analysis and design of randomised clinical trials involving competing risks endpoints.

PubMed

Tai, Bee-Choo; Wee, Joseph; Machin, David

2011-05-19

In randomised clinical trials involving time-to-event outcomes, the failures concerned may be events of an entirely different nature and as such define a classical competing risks framework. In designing and analysing clinical trials involving such endpoints, it is important to account for the competing events, and evaluate how each contributes to the overall failure. An appropriate choice of statistical model is important for adequate determination of sample size. We describe how competing events may be summarised in such trials using cumulative incidence functions and Gray's test. The statistical modelling of competing events using proportional cause-specific and subdistribution hazard functions, and the corresponding procedures for sample size estimation are outlined. These are illustrated using data from a randomised clinical trial (SQNP01) of patients with advanced (non-metastatic) nasopharyngeal cancer. In this trial, treatment has no effect on the competing event of loco-regional recurrence. Thus the effects of treatment on the hazard of distant metastasis were similar via both the cause-specific (unadjusted csHR = 0.43, 95% CI 0.25 - 0.72) and subdistribution (unadjusted subHR 0.43; 95% CI 0.25 - 0.76) hazard analyses, in favour of concurrent chemo-radiotherapy followed by adjuvant chemotherapy. Adjusting for nodal status and tumour size did not alter the results. The results of the logrank test (p = 0.002) comparing the cause-specific hazards and the Gray's test (p = 0.003) comparing the cumulative incidences also led to the same conclusion. However, the subdistribution hazard analysis requires many more subjects than the cause-specific hazard analysis to detect the same magnitude of effect. The cause-specific hazard analysis is appropriate for analysing competing risks outcomes when treatment has no effect on the cause-specific hazard of the competing event. It requires fewer subjects than the subdistribution hazard analysis for a similar effect size. However, if the main and competing events are influenced in opposing directions by an intervention, a subdistribution hazard analysis may be warranted.

Representation of Probability Density Functions from Orbit Determination using the Particle Filter

NASA Technical Reports Server (NTRS)

Mashiku, Alinda K.; Garrison, James; Carpenter, J. Russell

2012-01-01

Statistical orbit determination enables us to obtain estimates of the state and the statistical information of its region of uncertainty. In order to obtain an accurate representation of the probability density function (PDF) that incorporates higher order statistical information, we propose the use of nonlinear estimation methods such as the Particle Filter. The Particle Filter (PF) is capable of providing a PDF representation of the state estimates whose accuracy is dependent on the number of particles or samples used. For this method to be applicable to real case scenarios, we need a way of accurately representing the PDF in a compressed manner with little information loss. Hence we propose using the Independent Component Analysis (ICA) as a non-Gaussian dimensional reduction method that is capable of maintaining higher order statistical information obtained using the PF. Methods such as the Principal Component Analysis (PCA) are based on utilizing up to second order statistics, hence will not suffice in maintaining maximum information content. Both the PCA and the ICA are applied to two scenarios that involve a highly eccentric orbit with a lower apriori uncertainty covariance and a less eccentric orbit with a higher a priori uncertainty covariance, to illustrate the capability of the ICA in relation to the PCA.

Multivariate meta-analysis: a robust approach based on the theory of U-statistic.

PubMed

Ma, Yan; Mazumdar, Madhu

2011-10-30

Meta-analysis is the methodology for combining findings from similar research studies asking the same question. When the question of interest involves multiple outcomes, multivariate meta-analysis is used to synthesize the outcomes simultaneously taking into account the correlation between the outcomes. Likelihood-based approaches, in particular restricted maximum likelihood (REML) method, are commonly utilized in this context. REML assumes a multivariate normal distribution for the random-effects model. This assumption is difficult to verify, especially for meta-analysis with small number of component studies. The use of REML also requires iterative estimation between parameters, needing moderately high computation time, especially when the dimension of outcomes is large. A multivariate method of moments (MMM) is available and is shown to perform equally well to REML. However, there is a lack of information on the performance of these two methods when the true data distribution is far from normality. In this paper, we propose a new nonparametric and non-iterative method for multivariate meta-analysis on the basis of the theory of U-statistic and compare the properties of these three procedures under both normal and skewed data through simulation studies. It is shown that the effect on estimates from REML because of non-normal data distribution is marginal and that the estimates from MMM and U-statistic-based approaches are very similar. Therefore, we conclude that for performing multivariate meta-analysis, the U-statistic estimation procedure is a viable alternative to REML and MMM. Easy implementation of all three methods are illustrated by their application to data from two published meta-analysis from the fields of hip fracture and periodontal disease. We discuss ideas for future research based on U-statistic for testing significance of between-study heterogeneity and for extending the work to meta-regression setting. Copyright © 2011 John Wiley & Sons, Ltd.

Pig immune response to general stimulus and to porcine reproductive and respiratory syndrome virus infection: a meta-analysis approach

PubMed Central

2013-01-01

Background The availability of gene expression data that corresponds to pig immune response challenges provides compelling material for the understanding of the host immune system. Meta-analysis offers the opportunity to confirm and expand our knowledge by combining and studying at one time a vast set of independent studies creating large datasets with increased statistical power. In this study, we performed two meta-analyses of porcine transcriptomic data: i) scrutinized the global immune response to different challenges, and ii) determined the specific response to Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) infection. To gain an in-depth knowledge of the pig response to PRRSV infection, we used an original approach comparing and eliminating the common genes from both meta-analyses in order to identify genes and pathways specifically involved in the PRRSV immune response. The software Pointillist was used to cope with the highly disparate data, circumventing the biases generated by the specific responses linked to single studies. Next, we used the Ingenuity Pathways Analysis (IPA) software to survey the canonical pathways, biological functions and transcription factors found to be significantly involved in the pig immune response. We used 779 chips corresponding to 29 datasets for the pig global immune response and 279 chips obtained from 6 datasets for the pig response to PRRSV infection, respectively. Results The pig global immune response analysis showed interconnected canonical pathways involved in the regulation of translation and mitochondrial energy metabolism. Biological functions revealed in this meta-analysis were centred around translation regulation, which included protein synthesis, RNA-post transcriptional gene expression and cellular growth and proliferation. Furthermore, the oxidative phosphorylation and mitochondria dysfunctions, associated with stress signalling, were highly regulated. Transcription factors such as MYCN, MYC and NFE2L2 were found in this analysis to be potentially involved in the regulation of the immune response. The host specific response to PRRSV infection engendered the activation of well-defined canonical pathways in response to pathogen challenge such as TREM1, toll-like receptor and hyper-cytokinemia/ hyper-chemokinemia signalling. Furthermore, this analysis brought forth the central role of the crosstalk between innate and adaptive immune response and the regulation of anti-inflammatory response. The most significant transcription factor potentially involved in this analysis was HMGB1, which is required for the innate recognition of viral nucleic acids. Other transcription factors like interferon regulatory factors IRF1, IRF3, IRF5 and IRF8 were also involved in the pig specific response to PRRSV infection. Conclusions This work reveals key genes, canonical pathways and biological functions involved in the pig global immune response to diverse challenges, including PRRSV infection. The powerful statistical approach led us to consolidate previous findings as well as to gain new insights into the pig immune response either to common stimuli or specifically to PRRSV infection. PMID:23552196

Application of the Linux cluster for exhaustive window haplotype analysis using the FBAT and Unphased programs.

PubMed

Mishima, Hiroyuki; Lidral, Andrew C; Ni, Jun

2008-05-28

Genetic association studies have been used to map disease-causing genes. A newly introduced statistical method, called exhaustive haplotype association study, analyzes genetic information consisting of different numbers and combinations of DNA sequence variations along a chromosome. Such studies involve a large number of statistical calculations and subsequently high computing power. It is possible to develop parallel algorithms and codes to perform the calculations on a high performance computing (HPC) system. However, most existing commonly-used statistic packages for genetic studies are non-parallel versions. Alternatively, one may use the cutting-edge technology of grid computing and its packages to conduct non-parallel genetic statistical packages on a centralized HPC system or distributed computing systems. In this paper, we report the utilization of a queuing scheduler built on the Grid Engine and run on a Rocks Linux cluster for our genetic statistical studies. Analysis of both consecutive and combinational window haplotypes was conducted by the FBAT (Laird et al., 2000) and Unphased (Dudbridge, 2003) programs. The dataset consisted of 26 loci from 277 extended families (1484 persons). Using the Rocks Linux cluster with 22 compute-nodes, FBAT jobs performed about 14.4-15.9 times faster, while Unphased jobs performed 1.1-18.6 times faster compared to the accumulated computation duration. Execution of exhaustive haplotype analysis using non-parallel software packages on a Linux-based system is an effective and efficient approach in terms of cost and performance.

Application of the Linux cluster for exhaustive window haplotype analysis using the FBAT and Unphased programs

PubMed Central

Mishima, Hiroyuki; Lidral, Andrew C; Ni, Jun

2008-01-01

Background Genetic association studies have been used to map disease-causing genes. A newly introduced statistical method, called exhaustive haplotype association study, analyzes genetic information consisting of different numbers and combinations of DNA sequence variations along a chromosome. Such studies involve a large number of statistical calculations and subsequently high computing power. It is possible to develop parallel algorithms and codes to perform the calculations on a high performance computing (HPC) system. However, most existing commonly-used statistic packages for genetic studies are non-parallel versions. Alternatively, one may use the cutting-edge technology of grid computing and its packages to conduct non-parallel genetic statistical packages on a centralized HPC system or distributed computing systems. In this paper, we report the utilization of a queuing scheduler built on the Grid Engine and run on a Rocks Linux cluster for our genetic statistical studies. Results Analysis of both consecutive and combinational window haplotypes was conducted by the FBAT (Laird et al., 2000) and Unphased (Dudbridge, 2003) programs. The dataset consisted of 26 loci from 277 extended families (1484 persons). Using the Rocks Linux cluster with 22 compute-nodes, FBAT jobs performed about 14.4–15.9 times faster, while Unphased jobs performed 1.1–18.6 times faster compared to the accumulated computation duration. Conclusion Execution of exhaustive haplotype analysis using non-parallel software packages on a Linux-based system is an effective and efficient approach in terms of cost and performance. PMID:18541045

[Assessment of psychometric properties of the academic involvement questionnaire, expectations version].

PubMed

Pérez V, Cristhian; Ortiz M, Liliana; Fasce H, Eduardo; Parra P, Paula; Matus B, Olga; McColl C, Peter; Torres A, Graciela; Meyer K, Andrea; Márquez U, Carolina; Ortega B, Javiera

2015-11-01

Academic Involvement Questionnaire, Expectations version (CIA-A), assesses the expectations of involvement in studies. It is a relevant predictor of student success. However, the evidence of its validity and reliability in Chile is low, and in the case of Medical students, there is no evidence at all. To evaluate the factorial structure and internal consistency of the CIA-A in Chilean Medical school freshmen. The survey was applied to 340 Medicine freshmen, chosen by non-probability quota sampling. They answered a back-translated version of CIA-A from Portuguese to Spanish, plus a sociodemographic questionnaire. For psychometric analysis of the CIA-A, an exploratory factor analysis was carried on, the reliability of the factors was calculated, a descriptive analysis was conducted and their correlation was assessed. Five factors were identified: vocational, institutional and social involvement, use of resources and student participation. Their reliabilities ranged between Cronbach's alpha values of 0.71 to 0.87. Factors also showed statistically significant correlations between each other. Identified factor structure is theoretically consistent with the structure of original version. It just disagrees in one factor. In addition, the factors' internal consistency were adequate for using them in research. This supports the construct validity and reliability of the CIA-A to assess involvement expectations in medical school freshmen.

Evaluating Structural Equation Models for Categorical Outcomes: A New Test Statistic and a Practical Challenge of Interpretation.

PubMed

Monroe, Scott; Cai, Li

2015-01-01

This research is concerned with two topics in assessing model fit for categorical data analysis. The first topic involves the application of a limited-information overall test, introduced in the item response theory literature, to structural equation modeling (SEM) of categorical outcome variables. Most popular SEM test statistics assess how well the model reproduces estimated polychoric correlations. In contrast, limited-information test statistics assess how well the underlying categorical data are reproduced. Here, the recently introduced C2 statistic of Cai and Monroe (2014) is applied. The second topic concerns how the root mean square error of approximation (RMSEA) fit index can be affected by the number of categories in the outcome variable. This relationship creates challenges for interpreting RMSEA. While the two topics initially appear unrelated, they may conveniently be studied in tandem since RMSEA is based on an overall test statistic, such as C2. The results are illustrated with an empirical application to data from a large-scale educational survey.

Quantitative 3D analysis of bone in hip osteoarthritis using clinical computed tomography.

PubMed

Turmezei, Tom D; Treece, Graham M; Gee, Andrew H; Fotiadou, Anastasia F; Poole, Kenneth E S

2016-07-01

To assess the relationship between proximal femoral cortical bone thickness and radiological hip osteoarthritis using quantitative 3D analysis of clinical computed tomography (CT) data. Image analysis was performed on clinical CT imaging data from 203 female volunteers with a technique called cortical bone mapping (CBM). Colour thickness maps were created for each proximal femur. Statistical parametric mapping was performed to identify statistically significant differences in cortical bone thickness that corresponded with the severity of radiological hip osteoarthritis. Kellgren and Lawrence (K&L) grade, minimum joint space width (JSW) and a novel CT-based osteophyte score were also blindly assessed from the CT data. For each increase in K&L grade, cortical thickness increased by up to 25 % in distinct areas of the superolateral femoral head-neck junction and superior subchondral bone plate. For increasing severity of CT osteophytes, the increase in cortical thickness was more circumferential, involving a wider portion of the head-neck junction, with up to a 7 % increase in cortical thickness per increment in score. Results were not significant for minimum JSW. These findings indicate that quantitative 3D analysis of the proximal femur can identify changes in cortical bone thickness relevant to structural hip osteoarthritis. • CT is being increasingly used to assess bony involvement in osteoarthritis • CBM provides accurate and reliable quantitative analysis of cortical bone thickness • Cortical bone is thicker at the superior femoral head-neck with worse osteoarthritis • Regions of increased thickness co-locate with impingement and osteophyte formation • Quantitative 3D bone analysis could enable clinical disease prediction and therapy development.

Effect of virtual reality distraction on pain among patients with hand injury undergoing dressing change.

PubMed

Guo, Chunlan; Deng, Hongyan; Yang, Jian

2015-01-01

To assess the effect of virtual reality distraction on pain among patients with a hand injury undergoing a dressing change. Virtual reality distraction can effectively alleviate pain among patients undergoing a dressing change. Clinical research has not addressed pain control during a dressing change. A randomised controlled trial was performed. In the first dressing change sequence, 98 patients were randomly divided into an experimental group and a control group, with 49 cases in each group. Pain levels were compared between the two groups before and after the dressing change using a visual analog scale. The sense of involvement in virtual environments was measured using the Pearson correlation coefficient analysis, which determined the relationship between the sense of involvement and pain level. The difference in visual analog scale scores between the two groups before the dressing change was not statistically significant (t = 0·196, p > 0·05), but the scores became statistically significant after the dressing change (t = -30·792, p < 0·01). The correlation between the sense of involvement in a virtual environment and pain level during the dressing was statistically significant (R(2) = 0·5538, p < 0·05). Virtual reality distraction can effectively alleviate pain among patients with a hand injury undergoing a dressing change. Better results can be obtained by increasing the sense of involvement in a virtual environment. Virtual reality distraction can effectively relieve pain without side effects and is not reliant on a doctor's prescription. This tool is convenient for nurses to use, especially when analgesics are unavailable. © 2014 John Wiley & Sons Ltd.

Statistical Inference for Data Adaptive Target Parameters.

PubMed

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

2016-05-01

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

Evaluation of Cranio-cervical Posture in Children with Bruxism Before and After Bite Plate Therapy: A Pilot Project.

PubMed

Bortoletto, Carolina Carvalho; Cordeiro da Silva, Fernanda; Silva, Paula Fernanda da Costa; Leal de Godoy, Camila Haddad; Albertini, Regiane; Motta, Lara J; Mesquita-Ferrari, Raquel Agnelli; Fernandes, Kristianne Porta Santos; Romano, Renata; Bussadori, Sandra Kalil

2014-07-01

[Purpose] The aim of the present study was to evaluate the effect of a biteplate on the cranio-cervical posture of children with bruxism. [Subjects and Methods] Twelve male and female children aged six to 10 years with a diagnosis of bruxism participated in this study. The children used a biteplate during sleep for 30 days and were submitted to three postural evaluations: initial, immediately following placement of the biteplate, and at the end of treatment. Posture analysis was performed with the aid of the Alcimagem(®) 2.1 program. Data analysis (IBM SPSS Statistics 2.0) involved descriptive statistics and the Student's t-test. [Results] A statistically significant difference was found between the initial cranio-cervical angle and the angle immediately following placement of the biteplate. However, no statistically significant difference was found between the initial angle and the angle after one month of biteplate usage. [Conclusion] No significant change in the cranio-cervical posture of the children was found one month of biteplate usage. However, a reduction occurred in the cranio-cervical angle when the biteplate was in position.

Statistical Analyses of Scatterplots to Identify Important Factors in Large-Scale Simulations

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

Kleijnen, J.P.C.; Helton, J.C.

1999-04-01

The robustness of procedures for identifying patterns in scatterplots generated in Monte Carlo sensitivity analyses is investigated. These procedures are based on attempts to detect increasingly complex patterns in the scatterplots under consideration and involve the identification of (1) linear relationships with correlation coefficients, (2) monotonic relationships with rank correlation coefficients, (3) trends in central tendency as defined by means, medians and the Kruskal-Wallis statistic, (4) trends in variability as defined by variances and interquartile ranges, and (5) deviations from randomness as defined by the chi-square statistic. The following two topics related to the robustness of these procedures are consideredmore » for a sequence of example analyses with a large model for two-phase fluid flow: the presence of Type I and Type II errors, and the stability of results obtained with independent Latin hypercube samples. Observations from analysis include: (1) Type I errors are unavoidable, (2) Type II errors can occur when inappropriate analysis procedures are used, (3) physical explanations should always be sought for why statistical procedures identify variables as being important, and (4) the identification of important variables tends to be stable for independent Latin hypercube samples.« less

Adaptive filtering in biological signal processing.

PubMed

Iyer, V K; Ploysongsang, Y; Ramamoorthy, P A

1990-01-01

The high dependence of conventional optimal filtering methods on the a priori knowledge of the signal and noise statistics render them ineffective in dealing with signals whose statistics cannot be predetermined accurately. Adaptive filtering methods offer a better alternative, since the a priori knowledge of statistics is less critical, real time processing is possible, and the computations are less expensive for this approach. Adaptive filtering methods compute the filter coefficients "on-line", converging to the optimal values in the least-mean square (LMS) error sense. Adaptive filtering is therefore apt for dealing with the "unknown" statistics situation and has been applied extensively in areas like communication, speech, radar, sonar, seismology, and biological signal processing and analysis for channel equalization, interference and echo canceling, line enhancement, signal detection, system identification, spectral analysis, beamforming, modeling, control, etc. In this review article adaptive filtering in the context of biological signals is reviewed. An intuitive approach to the underlying theory of adaptive filters and its applicability are presented. Applications of the principles in biological signal processing are discussed in a manner that brings out the key ideas involved. Current and potential future directions in adaptive biological signal processing are also discussed.

Post-operative diffusion weighted imaging as a predictor of posterior fossa syndrome permanence in paediatric medulloblastoma.

PubMed

Chua, Felicia H Z; Thien, Ady; Ng, Lee Ping; Seow, Wan Tew; Low, David C Y; Chang, Kenneth T E; Lian, Derrick W Q; Loh, Eva; Low, Sharon Y Y

2017-03-01

Posterior fossa syndrome (PFS) is a serious complication faced by neurosurgeons and their patients, especially in paediatric medulloblastoma patients. The uncertain aetiology of PFS, myriad of cited risk factors and therapeutic challenges make this phenomenon an elusive entity. The primary objective of this study was to identify associative factors related to the development of PFS in medulloblastoma patient post-tumour resection. This is a retrospective study based at a single institution. Patient data and all related information were collected from the hospital records, in accordance to a list of possible risk factors associated with PFS. These included pre-operative tumour volume, hydrocephalus, age, gender, extent of resection, metastasis, ventriculoperitoneal shunt insertion, post-operative meningitis and radiological changes in MRI. Additional variables included molecular and histological subtypes of each patient's medulloblastoma tumour. Statistical analysis was employed to determine evidence of each variable's significance in PFS permanence. A total of 19 patients with appropriately complete data was identified. Initial univariate analysis did not show any statistical significance. However, multivariate analysis for MRI-specific changes reported bilateral DWI restricted diffusion changes involving both right and left sides of the surgical cavity was of statistical significance for PFS permanence. The authors performed a clinical study that evaluated possible risk factors for permanent PFS in paediatric medulloblastoma patients. Analysis of collated results found that post-operative DWI restriction in bilateral regions within the surgical cavity demonstrated statistical significance as a predictor of PFS permanence-a novel finding in the current literature.

Evaluation of scheduling techniques for payload activity planning

NASA Technical Reports Server (NTRS)

Bullington, Stanley F.

1991-01-01

Two tasks related to payload activity planning and scheduling were performed. The first task involved making a comparison of space mission activity scheduling problems with production scheduling problems. The second task consisted of a statistical analysis of the output of runs of the Experiment Scheduling Program (ESP). Details of the work which was performed on these two tasks are presented.

Factors influencing storm-generated suspended-sediment concentrations and loads in four basins of contrasting land use, humid-tropical Puerto Rico

Treesearch

A. C. Gellis; NO-VALUE

2013-01-01

The significant characteristics controlling the variability in storm-generated suspended-sediment loads and concentrations were analyzed for four basins of differing land use (forest, pasture, cropland, and urbanizing) in humid-tropical Puerto Rico. Statistical analysis involved stepwise regression on factor scores. The explanatory variables were attributes of flow,...

Bayesian inference for joint modelling of longitudinal continuous, binary and ordinal events.

PubMed

Li, Qiuju; Pan, Jianxin; Belcher, John

2016-12-01

In medical studies, repeated measurements of continuous, binary and ordinal outcomes are routinely collected from the same patient. Instead of modelling each outcome separately, in this study we propose to jointly model the trivariate longitudinal responses, so as to take account of the inherent association between the different outcomes and thus improve statistical inferences. This work is motivated by a large cohort study in the North West of England, involving trivariate responses from each patient: Body Mass Index, Depression (Yes/No) ascertained with cut-off score not less than 8 at the Hospital Anxiety and Depression Scale, and Pain Interference generated from the Medical Outcomes Study 36-item short-form health survey with values returned on an ordinal scale 1-5. There are some well-established methods for combined continuous and binary, or even continuous and ordinal responses, but little work was done on the joint analysis of continuous, binary and ordinal responses. We propose conditional joint random-effects models, which take into account the inherent association between the continuous, binary and ordinal outcomes. Bayesian analysis methods are used to make statistical inferences. Simulation studies show that, by jointly modelling the trivariate outcomes, standard deviations of the estimates of parameters in the models are smaller and much more stable, leading to more efficient parameter estimates and reliable statistical inferences. In the real data analysis, the proposed joint analysis yields a much smaller deviance information criterion value than the separate analysis, and shows other good statistical properties too. © The Author(s) 2014.

A graph theory approach to identify resonant and non-resonant transmission paths in statistical modal energy distribution analysis

NASA Astrophysics Data System (ADS)

Aragonès, Àngels; Maxit, Laurent; Guasch, Oriol

2015-08-01

Statistical modal energy distribution analysis (SmEdA) extends classical statistical energy analysis (SEA) to the mid frequency range by establishing power balance equations between modes in different subsystems. This circumvents the SEA requirement of modal energy equipartition and enables applying SmEdA to the cases of low modal overlap, locally excited subsystems and to deal with complex heterogeneous subsystems as well. Yet, widening the range of application of SEA is done at a price with large models because the number of modes per subsystem can become considerable when the frequency increases. Therefore, it would be worthwhile to have at one's disposal tools for a quick identification and ranking of the resonant and non-resonant paths involved in modal energy transmission between subsystems. It will be shown that previously developed graph theory algorithms for transmission path analysis (TPA) in SEA can be adapted to SmEdA and prove useful for that purpose. The case of airborne transmission between two cavities separated apart by homogeneous and ribbed plates will be first addressed to illustrate the potential of the graph approach. A more complex case representing transmission between non-contiguous cavities in a shipbuilding structure will be also presented.

A large-scale perspective on stress-induced alterations in resting-state networks

NASA Astrophysics Data System (ADS)

Maron-Katz, Adi; Vaisvaser, Sharon; Lin, Tamar; Hendler, Talma; Shamir, Ron

2016-02-01

Stress is known to induce large-scale neural modulations. However, its neural effect once the stressor is removed and how it relates to subjective experience are not fully understood. Here we used a statistically sound data-driven approach to investigate alterations in large-scale resting-state functional connectivity (rsFC) induced by acute social stress. We compared rsfMRI profiles of 57 healthy male subjects before and after stress induction. Using a parcellation-based univariate statistical analysis, we identified a large-scale rsFC change, involving 490 parcel-pairs. Aiming to characterize this change, we employed statistical enrichment analysis, identifying anatomic structures that were significantly interconnected by these pairs. This analysis revealed strengthening of thalamo-cortical connectivity and weakening of cross-hemispheral parieto-temporal connectivity. These alterations were further found to be associated with change in subjective stress reports. Integrating report-based information on stress sustainment 20 minutes post induction, revealed a single significant rsFC change between the right amygdala and the precuneus, which inversely correlated with the level of subjective recovery. Our study demonstrates the value of enrichment analysis for exploring large-scale network reorganization patterns, and provides new insight on stress-induced neural modulations and their relation to subjective experience.

Statistical deprojection of galaxy pairs

NASA Astrophysics Data System (ADS)

Nottale, Laurent; Chamaraux, Pierre

2018-06-01

Aims: The purpose of the present paper is to provide methods of statistical analysis of the physical properties of galaxy pairs. We perform this study to apply it later to catalogs of isolated pairs of galaxies, especially two new catalogs we recently constructed that contain ≈1000 and ≈13 000 pairs, respectively. We are particularly interested by the dynamics of those pairs, including the determination of their masses. Methods: We could not compute the dynamical parameters directly since the necessary data are incomplete. Indeed, we only have at our disposal one component of the intervelocity between the members, namely along the line of sight, and two components of their interdistance, i.e., the projection on the sky-plane. Moreover, we know only one point of each galaxy orbit. Hence we need statistical methods to find the probability distribution of 3D interdistances and 3D intervelocities from their projections; we designed those methods under the term deprojection. Results: We proceed in two steps to determine and use the deprojection methods. First we derive the probability distributions expected for the various relevant projected quantities, namely intervelocity vz, interdistance rp, their ratio, and the product rp v_z^2, which is involved in mass determination. In a second step, we propose various methods of deprojection of those parameters based on the previous analysis. We start from a histogram of the projected data and we apply inversion formulae to obtain the deprojected distributions; lastly, we test the methods by numerical simulations, which also allow us to determine the uncertainties involved.

Methods for calculating confidence and credible intervals for the residual between-study variance in random effects meta-regression models

PubMed Central

2014-01-01

Background Meta-regression is becoming increasingly used to model study level covariate effects. However this type of statistical analysis presents many difficulties and challenges. Here two methods for calculating confidence intervals for the magnitude of the residual between-study variance in random effects meta-regression models are developed. A further suggestion for calculating credible intervals using informative prior distributions for the residual between-study variance is presented. Methods Two recently proposed and, under the assumptions of the random effects model, exact methods for constructing confidence intervals for the between-study variance in random effects meta-analyses are extended to the meta-regression setting. The use of Generalised Cochran heterogeneity statistics is extended to the meta-regression setting and a Newton-Raphson procedure is developed to implement the Q profile method for meta-analysis and meta-regression. WinBUGS is used to implement informative priors for the residual between-study variance in the context of Bayesian meta-regressions. Results Results are obtained for two contrasting examples, where the first example involves a binary covariate and the second involves a continuous covariate. Intervals for the residual between-study variance are wide for both examples. Conclusions Statistical methods, and R computer software, are available to compute exact confidence intervals for the residual between-study variance under the random effects model for meta-regression. These frequentist methods are almost as easily implemented as their established counterparts for meta-analysis. Bayesian meta-regressions are also easily performed by analysts who are comfortable using WinBUGS. Estimates of the residual between-study variance in random effects meta-regressions should be routinely reported and accompanied by some measure of their uncertainty. Confidence and/or credible intervals are well-suited to this purpose. PMID:25196829

Reflectance of vegetation, soil, and water

NASA Technical Reports Server (NTRS)

Wiegand, C. L. (Principal Investigator)

1973-01-01

There are no author-identified significant results in this report. This report deals with the selection of the best channels from the 24-channel aircraft data to represent crop and soil conditions. A three-step procedure has been developed that involves using univariate statistics and an F-ratio test to indicate the best 14 channels. From the 14, the 10 best channels are selected by a multivariate stochastic process. The third step involves the pattern recognition procedures developed in the data analysis plan. Indications are that the procedures in use are satsifactory and will extract the desired information from the data.

A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae

PubMed Central

Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol; Scalcinati, Gionata; Fagerberg, Linn; Uhlén, Matthias; Nielsen, Jens

2012-01-01

RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated with the Illumina platform, and to perform a cross-platform comparison based on the results obtained through Affymetrix microarray. As a case study for our work we, used the Saccharomyces cerevisiae strain CEN.PK 113-7D, grown under two different conditions (batch and chemostat). Here, we asses the influence of genetic variation on the estimation of gene expression level using three different aligners for read-mapping (Gsnap, Stampy and TopHat) on S288c genome, the capabilities of five different statistical methods to detect differential gene expression (baySeq, Cuffdiff, DESeq, edgeR and NOISeq) and we explored the consistency between RNA-seq analysis using reference genome and de novo assembly approach. High reproducibility among biological replicates (correlation ≥0.99) and high consistency between the two platforms for analysis of gene expression levels (correlation ≥0.91) are reported. The results from differential gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays) for gene expression analysis and addresses the contribution of the different steps involved in the analysis of RNA-seq data. PMID:22965124

[Injuries: preventive approach and progress of injuries in the construction of the line B1 of the underground of Rome].

PubMed

Saggio, G; Conti, E; Valentini, F; De Sio, L; Capano, M Perrone

2010-01-01

The line B1 is a branch of the existing Metro line B in Rome. The route is long about 5 km, is completely underground and involves the construction of four new stations: Annibaliano, Libia /Gondar, Conca d'Oro and Jonio. The line will have a capacity of transport of 24,000 people/hour in each direction. The works started in 2006 involve about 500 workers. The report provides a statistical analysis of the events that occurred in the period 2005/2010 and aims to introduce the starting and management of this study, also on the basis of the "Operating procedures" issued by the acquisition of OSHAS 18001 certification from the agent of Metro B) / R.I.M.A.T.I. This analysis aims to provide to supervisors, to social security institutions and to workers, a usefull analysis tool in the prevention of the monitored events.

Emerging and recurrent issues in drug development.

PubMed

Anello, C

This paper reviews several emerging and recurrent issues relating to the drug development process. These emerging issues include changes to the FDA regulatory environment, internationalization of drug development, advances in computer technology and visualization tools, and efforts to incorporate meta-analysis methodology. Recurrent issues include: renewed interest in statistical methods for handling subgroups in the design and analysis of clinical trials; renewed interest in alternatives to the 'intention-to-treat' analysis in the presence of non-compliance in randomized clinical trials; renewed interest in methodology to address the multiplicities resulting from a variety of sources inherent in the drug development process, and renewed interest in methods to assure data integrity. These emerging and recurrent issues provide a continuing challenge to the international community of statisticians involved in drug development. Moreover, the involvement of statisticians with different perspectives continues to enrich the field and contributes to improvement in the public health.

Protecting Privacy of Shared Epidemiologic Data without Compromising Analysis Potential

DOE PAGES

Cologne, John; Grant, Eric J.; Nakashima, Eiji; ...

2012-01-01

Objective . Ensuring privacy of research subjects when epidemiologic data are shared with outside collaborators involves masking (modifying) the data, but overmasking can compromise utility (analysis potential). Methods of statistical disclosure control for protecting privacy may be impractical for individual researchers involved in small-scale collaborations. Methods . We investigated a simple approach based on measures of disclosure risk and analytical utility that are straightforward for epidemiologic researchers to derive. The method is illustrated using data from the Japanese Atomic-bomb Survivor population. Results . Masking by modest rounding did not adequately enhance security but rounding to remove several digits of relativemore » accuracy effectively reduced the risk of identification without substantially reducing utility. Grouping or adding random noise led to noticeable bias. Conclusions . When sharing epidemiologic data, it is recommended that masking be performed using rounding. Specific treatment should be determined separately in individual situations after consideration of the disclosure risks and analysis needs.« less

Protecting Privacy of Shared Epidemiologic Data without Compromising Analysis Potential

PubMed Central

Cologne, John; Grant, Eric J.; Nakashima, Eiji; Chen, Yun; Funamoto, Sachiyo; Katayama, Hiroaki

2012-01-01

Objective. Ensuring privacy of research subjects when epidemiologic data are shared with outside collaborators involves masking (modifying) the data, but overmasking can compromise utility (analysis potential). Methods of statistical disclosure control for protecting privacy may be impractical for individual researchers involved in small-scale collaborations. Methods. We investigated a simple approach based on measures of disclosure risk and analytical utility that are straightforward for epidemiologic researchers to derive. The method is illustrated using data from the Japanese Atomic-bomb Survivor population. Results. Masking by modest rounding did not adequately enhance security but rounding to remove several digits of relative accuracy effectively reduced the risk of identification without substantially reducing utility. Grouping or adding random noise led to noticeable bias. Conclusions. When sharing epidemiologic data, it is recommended that masking be performed using rounding. Specific treatment should be determined separately in individual situations after consideration of the disclosure risks and analysis needs. PMID:22505949

Protecting privacy of shared epidemiologic data without compromising analysis potential.

PubMed

Cologne, John; Grant, Eric J; Nakashima, Eiji; Chen, Yun; Funamoto, Sachiyo; Katayama, Hiroaki

2012-01-01

Ensuring privacy of research subjects when epidemiologic data are shared with outside collaborators involves masking (modifying) the data, but overmasking can compromise utility (analysis potential). Methods of statistical disclosure control for protecting privacy may be impractical for individual researchers involved in small-scale collaborations. We investigated a simple approach based on measures of disclosure risk and analytical utility that are straightforward for epidemiologic researchers to derive. The method is illustrated using data from the Japanese Atomic-bomb Survivor population. Masking by modest rounding did not adequately enhance security but rounding to remove several digits of relative accuracy effectively reduced the risk of identification without substantially reducing utility. Grouping or adding random noise led to noticeable bias. When sharing epidemiologic data, it is recommended that masking be performed using rounding. Specific treatment should be determined separately in individual situations after consideration of the disclosure risks and analysis needs.

Parent involvement and student academic performance: a multiple mediational analysis.

PubMed

Topor, David R; Keane, Susan P; Shelton, Terri L; Calkins, Susan D

2010-01-01

Parent involvement in a child's education is consistently found to be positively associated with a child's academic performance. However, there has been little investigation of the mechanisms that explain this association. The present study examines two potential mechanisms of this association: the child's perception of cognitive competence and the quality of the student-teacher relationship. This study used a sample of 158 seven-year-old participants, their mothers, and their teachers. Results indicated a statistically significant association between parent involvement and a child's academic performance, over and above the impact of the child's intelligence. A multiple mediation model indicated that the child's perception of cognitive competence fully mediated the relation between parent involvement and the child's performance on a standardized achievement test. The quality of the student-teacher relationship fully mediated the relation between parent involvement and teacher ratings of the child's classroom academic performance. Limitations, future research directions, and implications for public policy initiatives are discussed.

The vestibular evoked myogenic potentials (VEMP) score: a promising tool for evaluation of brainstem involvement in multiple sclerosis.

PubMed

Gabelić, T; Krbot Skorić, M; Adamec, I; Barun, B; Zadro, I; Habek, M

2015-02-01

Concerning the great importance of brainstem involvement in multiple sclerosis (MS), the aim of this study was to explore the role of the newly developed vestibular evoked myogenic potentials (VEMP) score as a possible marker of brainstem involvement in MS patients. This was a prospective case-control study which included 100 MS patients divided into two groups (without and with clinical signs of brainstem involvement) and 50 healthy controls. Ocular VEMP (oVEMP) and cervical VEMP (cVEMP) measurements were performed in all participants and analyzed for latencies, conduction block and amplitude asymmetry ratio. Based on this the VEMP score was calculated and compared with Expanded Disability Status Scale (EDSS), disease duration and magnetic resonance imaging data. Multiple sclerosis patients with clinical signs of brainstem involvement (group 2) had a statistically significant higher percentage of VEMP conduction blocks compared with patients without clinical signs of brainstem involvement (group 1) and healthy controls (P = 0.027 and P < 0.0001, respectively). Similarly, the VEMP score was significantly higher in group 2 compared with group 1 (P = 0.018) and correlated with EDSS and disease duration (P = 0.011 and P = 0.032, respectively). Multivariate linear regression analysis showed that the VEMP score has a statistically significant influence on the EDSS score (P < 0.001, R(2) = 0.239). Interpretation of the oVEMP and cVEMP results in the form of the VEMP score enables better evaluation of brainstem involvement than either of these evoked potentials alone and correlates well with disability. © 2014 EAN.

An Inferentialist Perspective on the Coordination of Actions and Reasons Involved in Making a Statistical Inference

ERIC Educational Resources Information Center

Bakker, Arthur; Ben-Zvi, Dani; Makar, Katie

2017-01-01

To understand how statistical and other types of reasoning are coordinated with actions to reduce uncertainty, we conducted a case study in vocational education that involved statistical hypothesis testing. We analyzed an intern's research project in a hospital laboratory in which reducing uncertainties was crucial to make a valid statistical…

Meta-analysis of the technical performance of an imaging procedure: guidelines and statistical methodology.

PubMed

Huang, Erich P; Wang, Xiao-Feng; Choudhury, Kingshuk Roy; McShane, Lisa M; Gönen, Mithat; Ye, Jingjing; Buckler, Andrew J; Kinahan, Paul E; Reeves, Anthony P; Jackson, Edward F; Guimaraes, Alexander R; Zahlmann, Gudrun

2015-02-01

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test-retest repeatability data for illustrative purposes. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Meta-analysis of the technical performance of an imaging procedure: Guidelines and statistical methodology

PubMed Central

Huang, Erich P; Wang, Xiao-Feng; Choudhury, Kingshuk Roy; McShane, Lisa M; Gönen, Mithat; Ye, Jingjing; Buckler, Andrew J; Kinahan, Paul E; Reeves, Anthony P; Jackson, Edward F; Guimaraes, Alexander R; Zahlmann, Gudrun

2017-01-01

Medical imaging serves many roles in patient care and the drug approval process, including assessing treatment response and guiding treatment decisions. These roles often involve a quantitative imaging biomarker, an objectively measured characteristic of the underlying anatomic structure or biochemical process derived from medical images. Before a quantitative imaging biomarker is accepted for use in such roles, the imaging procedure to acquire it must undergo evaluation of its technical performance, which entails assessment of performance metrics such as repeatability and reproducibility of the quantitative imaging biomarker. Ideally, this evaluation will involve quantitative summaries of results from multiple studies to overcome limitations due to the typically small sample sizes of technical performance studies and/or to include a broader range of clinical settings and patient populations. This paper is a review of meta-analysis procedures for such an evaluation, including identification of suitable studies, statistical methodology to evaluate and summarize the performance metrics, and complete and transparent reporting of the results. This review addresses challenges typical of meta-analyses of technical performance, particularly small study sizes, which often causes violations of assumptions underlying standard meta-analysis techniques. Alternative approaches to address these difficulties are also presented; simulation studies indicate that they outperform standard techniques when some studies are small. The meta-analysis procedures presented are also applied to actual [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) test–retest repeatability data for illustrative purposes. PMID:24872353

[Pitfalls in informed consent: a statistical analysis of malpractice law suits].

PubMed

Echigo, Junko

2014-05-01

In medical malpractice law suits, the notion of informed consent is often relevant in assessing whether negligence can be attributed to the medical practitioner who has caused injury to a patient. Furthermore, it is not rare that courts award damages for a lack of appropriate informed consent alone. In this study, two results were arrived at from a statistical analysis of medical malpractice law suits. One, unexpectedly, was that the severity of a patient's illness made no significant difference to whether damages were awarded. The other was that cases of typical medical treatment that national medical insurance does not cover were involved significantly more often than insured treatment cases. In cases where damages were awarded, the courts required more disclosure and written documents of information by medical practitioners, especially about complications and adverse effects that the patient might suffer.

Statistical geometric affinity in human brain electric activity

NASA Astrophysics Data System (ADS)

Chornet-Lurbe, A.; Oteo, J. A.; Ros, J.

2007-05-01

The representation of the human electroencephalogram (EEG) records by neurophysiologists demands standardized time-amplitude scales for their correct conventional interpretation. In a suite of graphical experiments involving scaling affine transformations we have been able to convert electroencephalogram samples corresponding to any particular sleep phase and relaxed wakefulness into each other. We propound a statistical explanation for that finding in terms of data collapse. As a sequel, we determine characteristic time and amplitude scales and outline a possible physical interpretation. An analysis for characteristic times based on lacunarity is also carried out as well as a study of the synchrony between left and right EEG channels.

Statistical hadronization with exclusive channels in e +e - annihilation

DOE PAGES

Ferroni, L.; Becattini, F.

2012-01-01

We present a systematic analysis of exclusive hadronic channels in e +e - collisions at centre-of-mass energies between 2.1 and 2.6 GeV within the statistical hadronization model. Because of the low multiplicities involved, calculations have been carried out in the full microcanonical ensemble, including conservation of energy-momentum, angular momentum, parity, isospin, and all relevant charges. We show that the data is in an overall good agreement with the model for an energy density of about 0.5 GeV/fm 3 and an extra strangeness suppression parameter γ S 0:7, essentially the same values found with fits to inclusive multiplicities at higher energy.

Mathematic model analysis of Gaussian beam propagation through an arbitrary thickness random phase screen.

PubMed

Tian, Yuzhen; Guo, Jin; Wang, Rui; Wang, Tingfeng

2011-09-12

In order to research the statistical properties of Gaussian beam propagation through an arbitrary thickness random phase screen for adaptive optics and laser communication application in the laboratory, we establish mathematic models of statistical quantities, which are based on the Rytov method and the thin phase screen model, involved in the propagation process. And the analytic results are developed for an arbitrary thickness phase screen based on the Kolmogorov power spectrum. The comparison between the arbitrary thickness phase screen and the thin phase screen shows that it is more suitable for our results to describe the generalized case, especially the scintillation index.

Directions for new developments on statistical design and analysis of small population group trials.

PubMed

Hilgers, Ralf-Dieter; Roes, Kit; Stallard, Nigel

2016-06-14

Most statistical design and analysis methods for clinical trials have been developed and evaluated where at least several hundreds of patients could be recruited. These methods may not be suitable to evaluate therapies if the sample size is unavoidably small, which is usually termed by small populations. The specific sample size cut off, where the standard methods fail, needs to be investigated. In this paper, the authors present their view on new developments for design and analysis of clinical trials in small population groups, where conventional statistical methods may be inappropriate, e.g., because of lack of power or poor adherence to asymptotic approximations due to sample size restrictions. Following the EMA/CHMP guideline on clinical trials in small populations, we consider directions for new developments in the area of statistical methodology for design and analysis of small population clinical trials. We relate the findings to the research activities of three projects, Asterix, IDeAl, and InSPiRe, which have received funding since 2013 within the FP7-HEALTH-2013-INNOVATION-1 framework of the EU. As not all aspects of the wide research area of small population clinical trials can be addressed, we focus on areas where we feel advances are needed and feasible. The general framework of the EMA/CHMP guideline on small population clinical trials stimulates a number of research areas. These serve as the basis for the three projects, Asterix, IDeAl, and InSPiRe, which use various approaches to develop new statistical methodology for design and analysis of small population clinical trials. Small population clinical trials refer to trials with a limited number of patients. Small populations may result form rare diseases or specific subtypes of more common diseases. New statistical methodology needs to be tailored to these specific situations. The main results from the three projects will constitute a useful toolbox for improved design and analysis of small population clinical trials. They address various challenges presented by the EMA/CHMP guideline as well as recent discussions about extrapolation. There is a need for involvement of the patients' perspective in the planning and conduct of small population clinical trials for a successful therapy evaluation.

Reducing the Complexity of an Agent-Based Local Heroin Market Model

PubMed Central

Heard, Daniel; Bobashev, Georgiy V.; Morris, Robert J.

2014-01-01

This project explores techniques for reducing the complexity of an agent-based model (ABM). The analysis involved a model developed from the ethnographic research of Dr. Lee Hoffer in the Larimer area heroin market, which involved drug users, drug sellers, homeless individuals and police. The authors used statistical techniques to create a reduced version of the original model which maintained simulation fidelity while reducing computational complexity. This involved identifying key summary quantities of individual customer behavior as well as overall market activity and replacing some agents with probability distributions and regressions. The model was then extended to allow external market interventions in the form of police busts. Extensions of this research perspective, as well as its strengths and limitations, are discussed. PMID:25025132

Black stains in the mixed dentition: a PCR microbiological study of the etiopathogenic bacteria.

PubMed

Saba, C; Solidani, M; Berlutti, F; Vestri, A; Ottolenghi, L; Polimeni, A

2006-01-01

The aim of this work is to emphasize that particular stains on the third cervical of the buccal and lingual surfaces in mixed dentition, called "black stain." Previous research showed the microbiological etiology of this discoloration by chromogen bacterias. Our study shows bacteria spp involved in stains by means of PCR process and electrophoresis gel on the agarose medium. Sample was formed by 100 subject with black stain and 100 control subjects stain-free. A statistical analysis (SPSS 10.0) using X2 was performed in this study. Porphyromonas gingivalis and Prevotella melaninogenica, were not involved in both in black stain subjects and in the control. On the contrary, Actinomyces could be involved in the pigmentation process.

Prognostic impact of number of resected and involved lymph nodes at complete resection on survival in non-small cell lung cancer.

PubMed

Saji, Hisashi; Tsuboi, Masahiro; Yoshida, Koichi; Kato, Yasufumi; Nomura, Masaharu; Matsubayashi, Jun; Nagao, Toshitaka; Kakihana, Masatoshi; Usuda, Jitsuo; Kajiwara, Naohiro; Ohira, Tatsuo; Ikeda, Norihiko

2011-11-01

Lymph node (LN) status is a major determinant of stage and survival in patients with lung cancer. In the 7th edition of the TNM Classification of Malignant Tumors, the number of involved LNs is included in the definition of pN factors in breast, stomach, esophageal, and colorectal cancer, and the pN status significantly correlates with prognosis. We retrospectively investigated the prognostic impact of the number of resected LNs (RLNs) and involved LNs in the context of other established clinical prognostic factors, in a series of 928 consecutive patients with non-small cell lung cancer (NSCLC) who underwent complete resection at our institution between 2000 and 2007. The mean number of RLNs was 15. There was a significant difference in the total number of RLNs categorized between less than 10 and ≥10 (p = 0.0129). Although the incidence of LN involvement was statistically associated with poor prognosis, the largest statistically significant increase in overall survival was observed between 0 to 3 and ≥4 involved LNs (hazard ratio = 7.680; 95% confidence interval = 5.051-11.655, p < 0.0001). On multivariate analysis, we used the ratio between the number of involved LNs and RLNs. The number of RLNs was found to be a strong independent prognostic factor for NSCLC (hazard ratio = 6.803; 95% confidence interval = 4.137-11.186, p < 0.0001). Complete resection including 10 or more LNs influenced survival at complete NSCLC resection. Four involved LNs seemed to be a benchmark for NSCLC prognosis. The number of involved LNs is a strong independent prognostic factor in NSCLC, and the results of this study may provide new information for determining the N category in the next tumor, node, metastasis classification.

Network theory inspired analysis of time-resolved expression data reveals key players guiding P. patens stem cell development.

PubMed

Busch, Hauke; Boerries, Melanie; Bao, Jie; Hanke, Sebastian T; Hiss, Manuel; Tiko, Theodhor; Rensing, Stefan A

2013-01-01

Transcription factors (TFs) often trigger developmental decisions, yet, their transcripts are often only moderately regulated and thus not easily detected by conventional statistics on expression data. Here we present a method that allows to determine such genes based on trajectory analysis of time-resolved transcriptome data. As a proof of principle, we have analysed apical stem cells of filamentous moss (P. patens) protonemata that develop from leaflets upon their detachment from the plant. By our novel correlation analysis of the post detachment transcriptome kinetics we predict five out of 1,058 TFs to be involved in the signaling leading to the establishment of pluripotency. Among the predicted regulators is the basic helix loop helix TF PpRSL1, which we show to be involved in the establishment of apical stem cells in P. patens. Our methodology is expected to aid analysis of key players of developmental decisions in complex plant and animal systems.

Ames Research Center SR&T program and earth observations

NASA Technical Reports Server (NTRS)

Poppoff, I. G.

1972-01-01

An overview is presented of the research activities in earth observations at Ames Research Center. Most of the tasks involve the use of research aircraft platforms. The program is also directed toward the use of the Illiac 4 computer for statistical analysis. Most tasks are weighted toward Pacific coast and Pacific basin problems with emphasis on water applications, air applications, animal migration studies, and geophysics.

A-Scan Ultrasound Measurement of Ocular Changes during Accommodation.

DTIC Science & Technology

1987-04-01

r.I.FMt# I. F’riUECT TASK AREA & WORK UNIT NUMBERSAF [T S’LUt)I’ENT AT: Pacific University SI.- ITP )LtIG oF FICE NAME AND ADDRESS 12. REPORT DATE A1FIT...analysis of the distribution made. This involved writing a program on the IBM PCAT which would generate, and statistically analyze three findings grouped in

[Prevalence of weapons possession and associated factors and involvement in physical aggression among adolescents 15 to 18 years of age: a population-based study].

PubMed

Silva, Ricardo Azevedo da; Jansen, Karen; Godoy, Russélia Vanila; Souza, Luciano Dias Mattos; Horta, Bernardo Lessa; Pinheiro, Ricardo Tavares

2009-12-01

This cross-sectional, population-based study aimed to evaluate the prevalence of weapons possession and associated factors and involvement in physical aggression among adolescents 15 to 18 years of age (n = 960) in the city of Pelotas, Rio Grande do Sul State, Brazil. Ninety of the city's 448 census tracts were selected, and 86 houses in each tract were visited. The statistical analysis used Poisson regression. Prevalence rates in the sample were 22.8% for involvement in fights with physical aggression and 9.6% for weapons possession in the previous 12 months. The study concluded that young males that use alcohol and/or illegal drugs and present minor psychiatric disorders show a higher probability of weapons possession and involvement in physical fights.

Enhancing the Equating of Item Difficulty Metrics: Estimation of Reference Distribution. Research Report. ETS RR-14-07

ERIC Educational Resources Information Center

Ali, Usama S.; Walker, Michael E.

2014-01-01

Two methods are currently in use at Educational Testing Service (ETS) for equating observed item difficulty statistics. The first method involves the linear equating of item statistics in an observed sample to reference statistics on the same items. The second method, or the item response curve (IRC) method, involves the summation of conditional…

Preparing systems engineering and computing science students in disciplined methods, quantitative, and advanced statistical techniques to improve process performance

NASA Astrophysics Data System (ADS)

McCray, Wilmon Wil L., Jr.

The research was prompted by a need to conduct a study that assesses process improvement, quality management and analytical techniques taught to students in U.S. colleges and universities undergraduate and graduate systems engineering and the computing science discipline (e.g., software engineering, computer science, and information technology) degree programs during their academic training that can be applied to quantitatively manage processes for performance. Everyone involved in executing repeatable processes in the software and systems development lifecycle processes needs to become familiar with the concepts of quantitative management, statistical thinking, process improvement methods and how they relate to process-performance. Organizations are starting to embrace the de facto Software Engineering Institute (SEI) Capability Maturity Model Integration (CMMI RTM) Models as process improvement frameworks to improve business processes performance. High maturity process areas in the CMMI model imply the use of analytical, statistical, quantitative management techniques, and process performance modeling to identify and eliminate sources of variation, continually improve process-performance; reduce cost and predict future outcomes. The research study identifies and provides a detail discussion of the gap analysis findings of process improvement and quantitative analysis techniques taught in U.S. universities systems engineering and computing science degree programs, gaps that exist in the literature, and a comparison analysis which identifies the gaps that exist between the SEI's "healthy ingredients " of a process performance model and courses taught in U.S. universities degree program. The research also heightens awareness that academicians have conducted little research on applicable statistics and quantitative techniques that can be used to demonstrate high maturity as implied in the CMMI models. The research also includes a Monte Carlo simulation optimization model and dashboard that demonstrates the use of statistical methods, statistical process control, sensitivity analysis, quantitative and optimization techniques to establish a baseline and predict future customer satisfaction index scores (outcomes). The American Customer Satisfaction Index (ACSI) model and industry benchmarks were used as a framework for the simulation model.

Experimental analysis of computer system dependability

NASA Technical Reports Server (NTRS)

Iyer, Ravishankar, K.; Tang, Dong

1993-01-01

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance.

SEM-PLS Analysis of Inhibiting Factors of Cost Performance for Large Construction Projects in Malaysia: Perspective of Clients and Consultants

PubMed Central

Memon, Aftab Hameed; Rahman, Ismail Abdul

2014-01-01

This study uncovered inhibiting factors to cost performance in large construction projects of Malaysia. Questionnaire survey was conducted among clients and consultants involved in large construction projects. In the questionnaire, a total of 35 inhibiting factors grouped in 7 categories were presented to the respondents for rating significant level of each factor. A total of 300 questionnaire forms were distributed. Only 144 completed sets were received and analysed using advanced multivariate statistical software of Structural Equation Modelling (SmartPLS v2). The analysis involved three iteration processes where several of the factors were deleted in order to make the model acceptable. The result of the analysis found that R 2 value of the model is 0.422 which indicates that the developed model has a substantial impact on cost performance. Based on the final form of the model, contractor's site management category is the most prominent in exhibiting effect on cost performance of large construction projects. This finding is validated using advanced techniques of power analysis. This vigorous multivariate analysis has explicitly found the significant category which consists of several causative factors to poor cost performance in large construction projects. This will benefit all parties involved in construction projects for controlling cost overrun. PMID:24693227

SEM-PLS analysis of inhibiting factors of cost performance for large construction projects in Malaysia: perspective of clients and consultants.

PubMed

Memon, Aftab Hameed; Rahman, Ismail Abdul

2014-01-01

This study uncovered inhibiting factors to cost performance in large construction projects of Malaysia. Questionnaire survey was conducted among clients and consultants involved in large construction projects. In the questionnaire, a total of 35 inhibiting factors grouped in 7 categories were presented to the respondents for rating significant level of each factor. A total of 300 questionnaire forms were distributed. Only 144 completed sets were received and analysed using advanced multivariate statistical software of Structural Equation Modelling (SmartPLS v2). The analysis involved three iteration processes where several of the factors were deleted in order to make the model acceptable. The result of the analysis found that R(2) value of the model is 0.422 which indicates that the developed model has a substantial impact on cost performance. Based on the final form of the model, contractor's site management category is the most prominent in exhibiting effect on cost performance of large construction projects. This finding is validated using advanced techniques of power analysis. This vigorous multivariate analysis has explicitly found the significant category which consists of several causative factors to poor cost performance in large construction projects. This will benefit all parties involved in construction projects for controlling cost overrun.

Detecting disease-predisposing variants: the haplotype method.

PubMed Central

Valdes, A M; Thomson, G

1997-01-01

For many HLA-associated diseases, multiple alleles-- and, in some cases, multiple loci--have been suggested as the causative agents. The haplotype method for identifying disease-predisposing amino acids in a genetic region is a stratification analysis. We show that, for each haplotype combination containing all the amino acid sites involved in the disease process, the relative frequencies of amino acid variants at sites not involved in disease but in linkage disequilibrium with the disease-predisposing sites are expected to be the same in patients and controls. The haplotype method is robust to mode of inheritance and penetrance of the disease and can be used to determine unequivocally whether all amino acid sites involved in the disease have not been identified. Using a resampling technique, we developed a statistical test that takes account of the nonindependence of the sites sampled. Further, when multiple sites in the genetic region are involved in disease, the test statistic gives a closer fit to the null expectation when some--compared with none--of the true predisposing factors are included in the haplotype analysis. Although the haplotype method cannot distinguish between very highly correlated sites in one population, ethnic comparisons may help identify the true predisposing factors. The haplotype method was applied to insulin-dependent diabetes mellitus (IDDM) HLA class II DQA1-DQB1 data from Caucasian, African, and Japanese populations. Our results indicate that the combination DQA1#52 (Arg predisposing) DQB1#57 (Asp protective), which has been proposed as an important IDDM agent, does not include all the predisposing elements. With rheumatoid arthritis HLA class II DRB1 data, the results were consistent with the shared-epitope hypothesis. PMID:9042931

Uncertainties in obtaining high reliability from stress-strength models

NASA Technical Reports Server (NTRS)

Neal, Donald M.; Matthews, William T.; Vangel, Mark G.

1992-01-01

There has been a recent interest in determining high statistical reliability in risk assessment of aircraft components. The potential consequences are identified of incorrectly assuming a particular statistical distribution for stress or strength data used in obtaining the high reliability values. The computation of the reliability is defined as the probability of the strength being greater than the stress over the range of stress values. This method is often referred to as the stress-strength model. A sensitivity analysis was performed involving a comparison of reliability results in order to evaluate the effects of assuming specific statistical distributions. Both known population distributions, and those that differed slightly from the known, were considered. Results showed substantial differences in reliability estimates even for almost nondetectable differences in the assumed distributions. These differences represent a potential problem in using the stress-strength model for high reliability computations, since in practice it is impossible to ever know the exact (population) distribution. An alternative reliability computation procedure is examined involving determination of a lower bound on the reliability values using extreme value distributions. This procedure reduces the possibility of obtaining nonconservative reliability estimates. Results indicated the method can provide conservative bounds when computing high reliability. An alternative reliability computation procedure is examined involving determination of a lower bound on the reliability values using extreme value distributions. This procedure reduces the possibility of obtaining nonconservative reliability estimates. Results indicated the method can provide conservative bounds when computing high reliability.

PEPA test: fast and powerful differential analysis from relative quantitative proteomics data using shared peptides.

PubMed

Jacob, Laurent; Combes, Florence; Burger, Thomas

2018-06-18

We propose a new hypothesis test for the differential abundance of proteins in mass-spectrometry based relative quantification. An important feature of this type of high-throughput analyses is that it involves an enzymatic digestion of the sample proteins into peptides prior to identification and quantification. Due to numerous homology sequences, different proteins can lead to peptides with identical amino acid chains, so that their parent protein is ambiguous. These so-called shared peptides make the protein-level statistical analysis a challenge and are often not accounted for. In this article, we use a linear model describing peptide-protein relationships to build a likelihood ratio test of differential abundance for proteins. We show that the likelihood ratio statistic can be computed in linear time with the number of peptides. We also provide the asymptotic null distribution of a regularized version of our statistic. Experiments on both real and simulated datasets show that our procedures outperforms state-of-the-art methods. The procedures are available via the pepa.test function of the DAPAR Bioconductor R package.

Results of a transparent expert consultation on patient and public involvement in palliative care research.

PubMed

Daveson, Barbara A; de Wolf-Linder, Susanne; Witt, Jana; Newson, Kirstie; Morris, Carolyn; Higginson, Irene J; Evans, Catherine J

2015-12-01

Support and evidence for patient, unpaid caregiver and public involvement in research (user involvement) are growing. Consensus on how best to involve users in palliative care research is lacking. To determine an optimal user-involvement model for palliative care research. We hosted a consultation workshop using expert presentations, discussion and nominal group technique to generate recommendations and consensus on agreement of importance. A total of 35 users and 32 researchers were approached to attend the workshop, which included break-out groups and a ranking exercise. Descriptive statistical analysis to establish consensus and highlight divergence was applied. Qualitative analysis of discussions was completed to aid interpretation of findings. Participants involved in palliative care research were invited to a global research institute, UK. A total of 12 users and 5 researchers participated. Users wanted their involvement to be more visible, including during dissemination, with a greater emphasis on the difference their involvement makes. Researchers wanted to improve productivity, relevance and quality through involvement. Users and researchers agreed that an optimal model should consist of (a) early involvement to ensure meaningful involvement and impact and (b) diverse virtual and face-to-face involvement methods to ensure flexibility. For involvement in palliative care research to succeed, early and flexible involvement is required. Researchers should advertise opportunities for involvement and promote impact of involvement via dissemination plans. Users should prioritise adding value to research through enhancing productivity, quality and relevance. More research is needed not only to inform implementation and ensure effectiveness but also to investigate the cost-effectiveness of involvement in palliative care research. © The Author(s) 2015.

Results of a transparent expert consultation on patient and public involvement in palliative care research

PubMed Central

Daveson, Barbara A; de Wolf-Linder, Susanne; Witt, Jana; Newson, Kirstie; Morris, Carolyn; Higginson, Irene J; Evans, Catherine J

2015-01-01

Background: Support and evidence for patient, unpaid caregiver and public involvement in research (user involvement) are growing. Consensus on how best to involve users in palliative care research is lacking. Aim: To determine an optimal user-involvement model for palliative care research. Design: We hosted a consultation workshop using expert presentations, discussion and nominal group technique to generate recommendations and consensus on agreement of importance. A total of 35 users and 32 researchers were approached to attend the workshop, which included break-out groups and a ranking exercise. Descriptive statistical analysis to establish consensus and highlight divergence was applied. Qualitative analysis of discussions was completed to aid interpretation of findings. Setting/participants: Participants involved in palliative care research were invited to a global research institute, UK. Results: A total of 12 users and 5 researchers participated. Users wanted their involvement to be more visible, including during dissemination, with a greater emphasis on the difference their involvement makes. Researchers wanted to improve productivity, relevance and quality through involvement. Users and researchers agreed that an optimal model should consist of (a) early involvement to ensure meaningful involvement and impact and (b) diverse virtual and face-to-face involvement methods to ensure flexibility. Conclusion: For involvement in palliative care research to succeed, early and flexible involvement is required. Researchers should advertise opportunities for involvement and promote impact of involvement via dissemination plans. Users should prioritise adding value to research through enhancing productivity, quality and relevance. More research is needed not only to inform implementation and ensure effectiveness but also to investigate the cost-effectiveness of involvement in palliative care research. PMID:25931336

Multiple testing and power calculations in genetic association studies.

PubMed

So, Hon-Cheong; Sham, Pak C

2011-01-01

Modern genetic association studies typically involve multiple single-nucleotide polymorphisms (SNPs) and/or multiple genes. With the development of high-throughput genotyping technologies and the reduction in genotyping cost, investigators can now assay up to a million SNPs for direct or indirect association with disease phenotypes. In addition, some studies involve multiple disease or related phenotypes and use multiple methods of statistical analysis. The combination of multiple genetic loci, multiple phenotypes, and multiple methods of evaluating associations between genotype and phenotype means that modern genetic studies often involve the testing of an enormous number of hypotheses. When multiple hypothesis tests are performed in a study, there is a risk of inflation of the type I error rate (i.e., the chance of falsely claiming an association when there is none). Several methods for multiple-testing correction are in popular use, and they all have strengths and weaknesses. Because no single method is universally adopted or always appropriate, it is important to understand the principles, strengths, and weaknesses of the methods so that they can be applied appropriately in practice. In this article, we review the three principle methods for multiple-testing correction and provide guidance for calculating statistical power.

Borrowing of strength and study weights in multivariate and network meta-analysis.

PubMed

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2017-12-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of 'borrowing of strength'. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis).

Borrowing of strength and study weights in multivariate and network meta-analysis

PubMed Central

Jackson, Dan; White, Ian R; Price, Malcolm; Copas, John; Riley, Richard D

2016-01-01

Multivariate and network meta-analysis have the potential for the estimated mean of one effect to borrow strength from the data on other effects of interest. The extent of this borrowing of strength is usually assessed informally. We present new mathematical definitions of ‘borrowing of strength’. Our main proposal is based on a decomposition of the score statistic, which we show can be interpreted as comparing the precision of estimates from the multivariate and univariate models. Our definition of borrowing of strength therefore emulates the usual informal assessment. We also derive a method for calculating study weights, which we embed into the same framework as our borrowing of strength statistics, so that percentage study weights can accompany the results from multivariate and network meta-analyses as they do in conventional univariate meta-analyses. Our proposals are illustrated using three meta-analyses involving correlated effects for multiple outcomes, multiple risk factor associations and multiple treatments (network meta-analysis). PMID:26546254

Statistical methods and neural network approaches for classification of data from multiple sources

NASA Technical Reports Server (NTRS)

Benediktsson, Jon Atli; Swain, Philip H.

1990-01-01

Statistical methods for classification of data from multiple data sources are investigated and compared to neural network models. A problem with using conventional multivariate statistical approaches for classification of data of multiple types is in general that a multivariate distribution cannot be assumed for the classes in the data sources. Another common problem with statistical classification methods is that the data sources are not equally reliable. This means that the data sources need to be weighted according to their reliability but most statistical classification methods do not have a mechanism for this. This research focuses on statistical methods which can overcome these problems: a method of statistical multisource analysis and consensus theory. Reliability measures for weighting the data sources in these methods are suggested and investigated. Secondly, this research focuses on neural network models. The neural networks are distribution free since no prior knowledge of the statistical distribution of the data is needed. This is an obvious advantage over most statistical classification methods. The neural networks also automatically take care of the problem involving how much weight each data source should have. On the other hand, their training process is iterative and can take a very long time. Methods to speed up the training procedure are introduced and investigated. Experimental results of classification using both neural network models and statistical methods are given, and the approaches are compared based on these results.

The involvement of girls and boys with bullying: an analysis of gender differences.

PubMed

Silva, Marta Angélica Iossi; Pereira, Beatriz; Mendonça, Denisa; Nunes, Berta; de Oliveira, Wanderlei Abadio

2013-12-05

This exploratory and cross-sectional study aimed to identify the prevalence of bullying in a group of students and analyze the data regarding the gender of those involved in the violence. A questionnaire adapted from Olweus was applied in seven elementary education schools in Portugal. The sample consisted of 387 students between 7 and 14 years old. Data are presented in terms of descriptive statistics and differences between proportions were analyzed using chi-square tests. The gender analysis of victimization and aggression shows that boys and girls are both victims and aggressors, and there are significant differences in involvement in bullying between genders and the roles played. Boys are victims more often when considering different types of bullying, although significant differences were only found for physical aggression. Strategies that include gender roles are a priority for prevention and careful attention to this phenomenon in the school context. The questions addressed contribute to a broader understanding of the phenomenon, emphasizing the differential participation of boys and girls in bullying.

Early interventions involving parents to improve neurodevelopmental outcomes of premature infants: a meta-analysis.

PubMed

Vanderveen, J A; Bassler, D; Robertson, C M T; Kirpalani, H

2009-05-01

To determine in a systematic review, whether interventions for infant development that involve parents, improve neurodevelopment at 12 months corrected age or older. Randomized trials were identified where an infant intervention was aimed to improve development and involved parents of preterms; and long-term neurodevelopment using standardized tests at 12 months (or longer) was reported. Identified studies (n=25) used a variety of interventions including parent education, infant stimulation, home visits or individualized developmental care. Meta-analysis at 12 months (N=2198 infants) found significantly higher mental (N=2198) and physical (N=1319) performance scores favoring the intervention group. At 24 months, the mental (N=1490) performance scores were improved, but physical (N=1025) performance scores were not statistically significant. The improvement in neurodevelopmental outcome was not sustained at 36 months (N=961) and 5 years (N=1017). Positive clinically meaningful effects (>5 points) are seen to an age of 36 months, but are no longer present at 5 years.

The Involvement of Girls and Boys with Bullying: An Analysis of Gender Differences

PubMed Central

Silva, Marta Angélica Iossi; Pereira, Beatriz; Mendonça, Denisa; Nunes, Berta; de Oliveira, Wanderlei Abadio

2013-01-01

This exploratory and cross-sectional study aimed to identify the prevalence of bullying in a group of students and analyze the data regarding the gender of those involved in the violence. A questionnaire adapted from Olweus was applied in seven elementary education schools in Portugal. The sample consisted of 387 students between 7 and 14 years old. Data are presented in terms of descriptive statistics and differences between proportions were analyzed using chi-square tests. The gender analysis of victimization and aggression shows that boys and girls are both victims and aggressors, and there are significant differences in involvement in bullying between genders and the roles played. Boys are victims more often when considering different types of bullying, although significant differences were only found for physical aggression. Strategies that include gender roles are a priority for prevention and careful attention to this phenomenon in the school context. The questions addressed contribute to a broader understanding of the phenomenon, emphasizing the differential participation of boys and girls in bullying. PMID:24317387

The application of satellite data in monitoring strip mines

NASA Technical Reports Server (NTRS)

Sharber, L. A.; Shahrokhi, F.

1977-01-01

Strip mines in the New River Drainage Basin of Tennessee were studied through use of Landsat-1 imagery and aircraft photography. A multilevel analysis, involving conventional photo interpretation techniques, densitometric methods, multispectral analysis and statistical testing was applied to the data. The Landsat imagery proved adequate for monitoring large-scale change resulting from active mining and land-reclamation projects. However, the spatial resolution of the satellite imagery rendered it inadequate for assessment of many smaller strip mines, in the region which may be as small as a few hectares.

Factors predicting survival in amyotrophic lateral sclerosis patients on non-invasive ventilation.

PubMed

Gonzalez Calzada, Nuria; Prats Soro, Enric; Mateu Gomez, Lluis; Giro Bulta, Esther; Cordoba Izquierdo, Ana; Povedano Panades, Monica; Dorca Sargatal, Jordi; Farrero Muñoz, Eva

2016-01-01

Non invasive ventilation (NIV) improves quality of life and extends survival in amyotrophic lateral sclerosis (ALS) patients. However, few data exist about the factors related to survival. We intended to assess the predictive factors that influence survival in patients after NIV initiation. Patients who started NIV from 2000 to 2014 and were tolerant (compliance ≥ 4 hours) were included; demographic, disease related and respiratory variables at NIV initiation were analysed. Statistical analysis was performed using the Kaplan-Meier test and Cox proportional hazard models. 213 patients were included with median survival from NIV initiation of 13.5 months. In univariate analysis, the identified risk factors for mortality were severity of bulbar involvement (HR 2), Forced Vital Capacity (FVC) % (HR 0.99) and ALSFRS-R (HR 0.97). Multivariate analysis showed that bulbar involvement (HR 1.92) and ALSFRS-R (HR 0.97) were independent predictive factors of survival in patients on NIV. In our study, the two prognostic factors in ALS patients following NIV were the severity of bulbar involvement and ALSFRS-R at the time on NIV initiation. A better assessment of bulbar involvement, including evaluation of the upper airway, and a careful titration on NIV are necessary to optimize treatment efficacy.

Efficacy of Pharmacist Based Diabetes Educational Interventions on Clinical Outcomes of Adults With Type 2 Diabetes Mellitus: A Network Meta-Analysis.

PubMed

Bukhsh, Allah; Khan, Tahir M; Lee, Shaun W H; Lee, Learn-Han; Chan, Kok-Gan; Goh, Bey-Hing

2018-01-01

Background: Comparative efficacy of different pharmacist based interventions on glycemic control of type 2 diabetes patients is unclear. This review aimed to evaluate and compare the efficacy of different pharmacist based interventions on clinical outcomes of type 2 diabetes patients. Methods: A systematic search was conducted across five databases from date of database inception to September 2017. All randomized clinical trials evaluating the efficacy of pharmacist based interventions on type 2 diabetes patients were included for network meta-analysis (NMA). The protocol is available with PROSPERO (CRD42017078854). Results: A total of 43 studies, involving 6259 type 2 diabetes patients, were included. NMA demonstrated that all interventions significantly lowered glycosylated hemoglobin (HbA1c) levels compared to usual care, but there was no statistical evidence from this study that one intervention was significantly better than the other for reducing HbA1c levels. Pharmacist based diabetes education plus pharmaceutical care showed maximum efficacy for reducing HbA1c levels [-0.86, 95% CI -0.983, -0.727; p < 0.001]. Pharmacist based diabetes education plus pharmaceutical care was observed to be statistically significant in lowering levels of systolic blood pressure [-4.94; 95%CI -8.65, -1.23] and triglycerides levels [-0.26, 95%CI -0.51, -0.01], as compared to the interventions which involved diabetes education by pharmacist, and for body mass index (BMI) [-0.57; 95%CI -1.25, -0.12] in comparison to diabetes education by health care team involving pharmacist as member. Conclusion: The findings of this review demonstrate that all interventions had a significantly positive effect on HbA1c, but there was no statistical evidence from this study that one intervention was significantly better than the other for achieving glycemic control.Pharmacist based diabetes education plus pharmaceutical care showed maximum efficacy on HbA1c and rest of the clinical outcomes.

Predictive value of bone scintigraphy for the detection of joint involvement in Behçet's disease: Dermatologists' perspectives.

PubMed

Seo, Jimyung; Lee, Minseok; Choi, Min Ju; Zheng, Zhenlong; Cho, Arthur; Bang, Dongsik; Kim, Do Young

2015-01-01

Behçet's disease (BD) is a multisystemic inflammatory disease with articular involvement. Non-specific arthralgia without objective signs of arthritis, such as swelling or effusion, is common in such patients. Thus, an accurate diagnosis of joint involvement may be challenging for dermatologists. To evaluate the validity of (99m)Tc-methylene diphosphonate (Tc-99m-MDP) bone scintigraphy for joint involvement assessment in patients with BD. In 211 patients with BD who had scintigraphic evaluations due to joint symptoms, agreement between bone scintigraphy findings and clinically evaluated joint complaints was retrospectively assessed using Cohen's kappa (κ) statistic. A patient subset (n = 104) showing agreement between joint complaints and scintigraphy results was re-evaluated by a rheumatologist to determine the level of diagnostic specificity attained by combining bone scintigraphy with clinical examinations of dermatologists. The total kappa value (211 patients) was 0.604, indicating fair agreement between joint complaints and scintigraphy results. Individual analysis of eleven joint categories revealed statistically significant correlations for wrist (κ = 0.677), shoulder (κ = 0.661), and foot joints (κ = 0.618). Of the 104 referrals to a rheumatologist, 95 (91.34%) were confirmed as having BD-associated articular involvement. Joint acral areas (e.g., foot, hand, wrist and shoulder) that had the highest kappa value correlations also ranked highest in diagnostic specificity. Bone scintigraphy presents a simple and useful option for dermatologists to assess joint involvement in BD patients, especially for specific anatomic sites.

Non sentinel node involvement prediction for sentinel node micrometastases in breast cancer: nomogram validation and comparison with other models.

PubMed

Houvenaeghel, Gilles; Bannier, Marie; Nos, Claude; Giard, Sylvia; Mignotte, Herve; Jacquemier, Jocelyne; Martino, Marc; Esterni, Benjamin; Belichard, Catherine; Classe, Jean-Marc; Tunon de Lara, Christine; Cohen, Monique; Payan, Raoul; Blanchot, Jerome; Rouanet, Philippe; Penault-Llorca, Frederique; Bonnier, Pascal; Fournet, Sandrine; Agostini, Aubert; Marchal, Frederique; Garbay, Jean-Remi

2012-04-01

The risk of non sentinel node (NSN) involvement varies in function of the characteristics of sentinel nodes (SN) and primary tumor. Our aim was to determine and validate a statistical tool (a nomogram) able to predict the risk of NSN involvement in case of SN micro or sub-micrometastasis of breast cancer. We have compared this monogram with other models described in the literature. We have collected data on 905 patients, then 484 other patients, to build and validate the nomogram and compare it with other published scores and nomograms. Multivariate analysis conducted on the data of the first cohort allowed us to define a nomogram based on 5 criteria: the method of SN detection (immunohistochemistry or by standard coloration with HES); the ratio of positive SN out of total removed SN; the pathologic size of the tumor; the histological type; and the presence (or not) of lympho-vascular invasion. The nomogram developed here is the only one dedicated to micrometastasis and developed on the basis of two large cohorts. The results of this statistical tool in the calculation of the risk of NSN involvement is similar to those of the MSKCC (the similarly more effective nomogram according to the literature), with a lower rate of false negatives. this nomogram is dedicated specifically to cases of SN involvement by metastasis lower or equal to 2 mm. It could be used in clinical practice in the way to omit ALND when the risk of NSN involvement is low. Copyright © 2011 Elsevier Ltd. All rights reserved.

Statistical mapping of zones of focused groundwater/surface-water exchange using fiber-optic distributed temperature sensing

USGS Publications Warehouse

Mwakanyamale, Kisa; Day-Lewis, Frederick D.; Slater, Lee D.

2013-01-01

Fiber-optic distributed temperature sensing (FO-DTS) increasingly is used to map zones of focused groundwater/surface-water exchange (GWSWE). Previous studies of GWSWE using FO-DTS involved identification of zones of focused GWSWE based on arbitrary cutoffs of FO-DTS time-series statistics (e.g., variance, cross-correlation between temperature and stage, or spectral power). New approaches are needed to extract more quantitative information from large, complex FO-DTS data sets while concurrently providing an assessment of uncertainty associated with mapping zones of focused GSWSE. Toward this end, we present a strategy combining discriminant analysis (DA) and spectral analysis (SA). We demonstrate the approach using field experimental data from a reach of the Columbia River adjacent to the Hanford 300 Area site. Results of the combined SA/DA approach are shown to be superior to previous results from qualitative interpretation of FO-DTS spectra alone.

Assessment and prediction of inter-joint upper limb movement correlations based on kinematic analysis and statistical regression

NASA Astrophysics Data System (ADS)

Toth-Tascau, Mirela; Balanean, Flavia; Krepelka, Mircea

2013-10-01

Musculoskeletal impairment of the upper limb can cause difficulties in performing basic daily activities. Three dimensional motion analyses can provide valuable data of arm movement in order to precisely determine arm movement and inter-joint coordination. The purpose of this study was to develop a method to evaluate the degree of impairment based on the influence of shoulder movements in the amplitude of elbow flexion and extension based on the assumption that a lack of motion of the elbow joint will be compensated by an increased shoulder activity. In order to develop and validate a statistical model, one healthy young volunteer has been involved in the study. The activity of choice simulated blowing the nose, starting from a slight flexion of the elbow and raising the hand until the middle finger touches the tip of the nose and return to the start position. Inter-joint coordination between the elbow and shoulder movements showed significant correlation. Statistical regression was used to fit an equation model describing the influence of shoulder movements on the elbow mobility. The study provides a brief description of the kinematic analysis protocol and statistical models that may be useful in describing the relation between inter-joint movements of daily activities.

The effects of compensatory workplace exercises to reduce work-related stress and musculoskeletal pain1

PubMed Central

de Freitas-Swerts, Fabiana Cristina Taubert; Robazzi, Maria Lúcia do Carmo Cruz

2014-01-01

OBJECTIVES: to assess the effect of a compensatory workplace exercise program on workers with the purpose of reducing work-related stress and musculoskeletal pain. METHOD: quasi-experimental research with quantitative analysis of the data, involving 30 administrative workers from a Higher Education Public Institution. For data collection, questionnaires were used to characterize the workers, as well as the Workplace Stress Scale and the Corlett Diagram. The research took place in three stages: first: pre-test with the application of the questionnaires to the subjects; second: Workplace Exercise taking place twice a week, for 15 minutes, during a period of 10 weeks; third: post-test in which the subjects answered the questionnaires again. For data analysis, the descriptive statistics and non-parametric statistics were used through the Wilcoxon Test. RESULTS: work-related stress was present in the assessed workers, but there was no statistically significant reduction in the scores after undergoing Workplace Exercise. However, there was a statistically significant pain reduction in the neck, cervical, upper, middle and lower back, right thigh, left leg, right ankle and feet. CONCLUSION: the Workplace Exercise promoted a significant pain reduction in the spine, but did not result in a significant reduction in the levels of work-related stress. PMID:25296147

[A study of behavior patterns between smokers and nonsmokers].

PubMed

Kim, H S

1990-04-01

Clinical and epidemiologic studies of coronary heart disease (CHD) have from time to time over the last three decades found associations between prevalence of CHD and behavioral attributes and cigarette smoking. The main purpose of this study is reduced to major risk factor of coronary heart disease through prohibition of smoking and control of behavior pattern. The subjects consisted of 120 smokers and 90 nonsmokers who were married men older than 30 years working in officers. The officers were surveyed by means of questionnaire September 26 through October 6, 1989. The Instruments used for this study was a self-administered measurement tool composed of 59 items was made through modifications of Jenkuns Activity Survey (JAS). The Data were analysed by SAS (Statistical Analysis System) program personal computer. The statistical technique used for this study were Frequency, chi 2-test, t-test, ANOVA, Pearson Correlation Coefficient. The 15 items were chosen with items above 0.3 of the factor loading in the factor analysis. In the first factor analysis 19 factors were extracted and accounted for 86% of the total variance. However when the number of factors were limited to 3 in order to derive Jenkins classification, three factors were derived. There names are Job-Involvement, Speed & Impatience, Hard-Driving. Each of them includes 21 items, 21 and 9, respectively. The results of this study were as follow: 1. The score of the smoker group and non-smoker group in Job-Involvement (t = 5.7147, p less than 0.0001), Speed & Impatience (t = 4.6756, p less than .0001), Hard-Driving (t = 8.0822, p less than .0001) and total type A behavior pattern showed statistically significant differences (t = 8.1224, p less than .0001). 2. The score of type A behavior pattern by number of cigarettes smoked daily were not statistically significant differences. 3. The score of type A behavior pattern by duration of smoking were not significant differences. It was concluded that the relationship between smokers and non-smokers of type A behavior pattern was statistically significant difference but number of cigarettes smoked daily and duration of smoking were not significant differences. Therefore this study is needed to adequate nursing intervention of type A behavior pattern in order to elevated to educational effect for prohibition of cigarette smoking.

A new statistical methodology predicting chip failure probability considering electromigration

NASA Astrophysics Data System (ADS)

Sun, Ted

In this research thesis, we present a new approach to analyze chip reliability subject to electromigration (EM) whose fundamental causes and EM phenomenon happened in different materials are presented in this thesis. This new approach utilizes the statistical nature of EM failure in order to assess overall EM risk. It includes within-die temperature variations from the chip's temperature map extracted by an Electronic Design Automation (EDA) tool to estimate the failure probability of a design. Both the power estimation and thermal analysis are performed in the EDA flow. We first used the traditional EM approach to analyze the design with a single temperature across the entire chip that involves 6 metal and 5 via layers. Next, we used the same traditional approach but with a realistic temperature map. The traditional EM analysis approach and that coupled with a temperature map and the comparison between the results of considering and not considering temperature map are presented in in this research. A comparison between these two results confirms that using a temperature map yields a less pessimistic estimation of the chip's EM risk. Finally, we employed the statistical methodology we developed considering a temperature map and different use-condition voltages and frequencies to estimate the overall failure probability of the chip. The statistical model established considers the scaling work with the usage of traditional Black equation and four major conditions. The statistical result comparisons are within our expectations. The results of this statistical analysis confirm that the chip level failure probability is higher i) at higher use-condition frequencies for all use-condition voltages, and ii) when a single temperature instead of a temperature map across the chip is considered. In this thesis, I start with an overall review on current design types, common flows, and necessary verifications and reliability checking steps used in this IC design industry. Furthermore, the important concepts about "Scripting Automation" which is used in all the integration of using diversified EDA tools in this research work are also described in detail with several examples and my completed coding works are also put in the appendix for your reference. Hopefully, this construction of my thesis will give readers a thorough understanding about my research work from the automation of EDA tools to the statistical data generation, from the nature of EM to the statistical model construction, and the comparisons among the traditional EM analysis and the statistical EM analysis approaches.

Multiscale hidden Markov models for photon-limited imaging

NASA Astrophysics Data System (ADS)

Nowak, Robert D.

1999-06-01

Photon-limited image analysis is often hindered by low signal-to-noise ratios. A novel Bayesian multiscale modeling and analysis method is developed in this paper to assist in these challenging situations. In addition to providing a very natural and useful framework for modeling an d processing images, Bayesian multiscale analysis is often much less computationally demanding compared to classical Markov random field models. This paper focuses on a probabilistic graph model called the multiscale hidden Markov model (MHMM), which captures the key inter-scale dependencies present in natural image intensities. The MHMM framework presented here is specifically designed for photon-limited imagin applications involving Poisson statistics, and applications to image intensity analysis are examined.

Treatment of missing data in follow-up studies of randomised controlled trials: A systematic review of the literature.

PubMed

Sullivan, Thomas R; Yelland, Lisa N; Lee, Katherine J; Ryan, Philip; Salter, Amy B

2017-08-01

After completion of a randomised controlled trial, an extended follow-up period may be initiated to learn about longer term impacts of the intervention. Since extended follow-up studies often involve additional eligibility restrictions and consent processes for participation, and a longer duration of follow-up entails a greater risk of participant attrition, missing data can be a considerable threat in this setting. As a potential source of bias, it is critical that missing data are appropriately handled in the statistical analysis, yet little is known about the treatment of missing data in extended follow-up studies. The aims of this review were to summarise the extent of missing data in extended follow-up studies and the use of statistical approaches to address this potentially serious problem. We performed a systematic literature search in PubMed to identify extended follow-up studies published from January to June 2015. Studies were eligible for inclusion if the original randomised controlled trial results were also published and if the main objective of extended follow-up was to compare the original randomised groups. We recorded information on the extent of missing data and the approach used to treat missing data in the statistical analysis of the primary outcome of the extended follow-up study. Of the 81 studies included in the review, 36 (44%) reported additional eligibility restrictions and 24 (30%) consent processes for entry into extended follow-up. Data were collected at a median of 7 years after randomisation. Excluding 28 studies with a time to event primary outcome, 51/53 studies (96%) reported missing data on the primary outcome. The median percentage of randomised participants with complete data on the primary outcome was just 66% in these studies. The most common statistical approach to address missing data was complete case analysis (51% of studies), while likelihood-based analyses were also well represented (25%). Sensitivity analyses around the missing data mechanism were rarely performed (25% of studies), and when they were, they often involved unrealistic assumptions about the mechanism. Despite missing data being a serious problem in extended follow-up studies, statistical approaches to addressing missing data were often inadequate. We recommend researchers clearly specify all sources of missing data in follow-up studies and use statistical methods that are valid under a plausible assumption about the missing data mechanism. Sensitivity analyses should also be undertaken to assess the robustness of findings to assumptions about the missing data mechanism.

Whole-tumour diffusion kurtosis MR imaging histogram analysis of rectal adenocarcinoma: Correlation with clinical pathologic prognostic factors.

PubMed

Cui, Yanfen; Yang, Xiaotang; Du, Xiaosong; Zhuo, Zhizheng; Xin, Lei; Cheng, Xintao

2018-04-01

To investigate potential relationships between diffusion kurtosis imaging (DKI)-derived parameters using whole-tumour volume histogram analysis and clinicopathological prognostic factors in patients with rectal adenocarcinoma. 79 consecutive patients who underwent MRI examination with rectal adenocarcinoma were retrospectively evaluated. Parameters D, K and conventional ADC were measured using whole-tumour volume histogram analysis. Student's t-test or Mann-Whitney U-test, receiver operating characteristic curves and Spearman's correlation were used for statistical analysis. Almost all the percentile metrics of K were correlated positively with nodal involvement, higher histological grades, the presence of lymphangiovascular invasion (LVI) and circumferential margin (CRM) (p<0.05), with the exception of between K 10th , K 90th and histological grades. In contrast, significant negative correlations were observed between 25th, 50th percentiles and mean values of ADC and D, as well as ADC 10th , with tumour T stages (p< 0.05). Meanwhile, lower 75th and 90th percentiles of ADC and D values were also correlated inversely with nodal involvement (p< 0.05). K mean showed a relatively higher area under the curve (AUC) and higher specificity than other percentiles for differentiation of lesions with nodal involvement. DKI metrics with whole-tumour volume histogram analysis, especially K parameters, were associated with important prognostic factors of rectal cancer. • K correlated positively with some important prognostic factors of rectal cancer. • K mean showed higher AUC and specificity for differentiation of nodal involvement. • DKI metrics with whole-tumour volume histogram analysis depicted tumour heterogeneity.

Analysis of Nonequivalent Assessments across Different Linguistic Groups Using a Mixed Methods Approach: Understanding the Causes of Differential Item Functioning by Cognitive Interviewing

ERIC Educational Resources Information Center

Benítez, Isabel; Padilla, José-Luis

2014-01-01

Differential item functioning (DIF) can undermine the validity of cross-lingual comparisons. While a lot of efficient statistics for detecting DIF are available, few general findings have been found to explain DIF results. The objective of the article was to study DIF sources by using a mixed method design. The design involves a quantitative phase…

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

Nose, Y.

Methods were developed for generating an integrated, statistical model of the anatomical structures within the human thorax relevant to radioisotope powered artificial heart implantation. These methods involve measurement and analysis of anatomy in four areas: chest wall, pericardium, vascular connections, and great vessels. A model for the prediction of thorax outline from radiograms was finalized. These models were combined with 100 radiograms to arrive at a size distribution representing the adult male and female populations. (CH)

Statistical Models and Inference Procedures for Structural and Materials Reliability

DTIC Science & Technology

1990-12-01

as an official Department of the Army positio~n, policy, or decision, unless sD designated by other documentazion. 12a. DISTRIBUTION /AVAILABILITY...Some general stress-strength models were also developed and applied to the failure of systems subject to cyclic loading. Involved in the failure of...process control ideas and sequential design and analysis methods. Finally, smooth nonparametric quantile .wJ function estimators were studied. All of

Thermoelastic Stress Analysis: The Mean Stress Effect in Metallic Alloys

NASA Technical Reports Server (NTRS)

Gyekenyesi, Andrew L.; Baaklini, George Y.

1999-01-01

The primary objective of this study involved the utilization of the thermoelastic stress analysis (TSA) method to demonstrate the mean stress dependence of the thermoelastic constant. Titanium and nickel base alloys, commonly employed in aerospace gas turbines, were the materials of interest. The repeatability of the results was studied through a statistical analysis of the data. Although the mean stress dependence was well established, the ability to confidently quantify it was diminished by the experimental variations. If calibration of the thermoelastic response to mean stress can be successfully implemented, it is feasible to use the relationship to determine a structure's residual stress state.

Texture analysis of pulmonary parenchyma in normal and emphysematous lung

NASA Astrophysics Data System (ADS)

Uppaluri, Renuka; Mitsa, Theophano; Hoffman, Eric A.; McLennan, Geoffrey; Sonka, Milan

1996-04-01

Tissue characterization using texture analysis is gaining increasing importance in medical imaging. We present a completely automated method for discriminating between normal and emphysematous regions from CT images. This method involves extracting seventeen features which are based on statistical, hybrid and fractal texture models. The best subset of features is derived from the training set using the divergence technique. A minimum distance classifier is used to classify the samples into one of the two classes--normal and emphysema. Sensitivity and specificity and accuracy values achieved were 80% or greater in most cases proving that texture analysis holds great promise in identifying emphysema.

Medical history and epidemiology: their contribution to the development of public health nursing.

PubMed

Earl, Catherine E

2009-01-01

The nursing profession historically has been involved in data collection in research efforts notably from the time of the Framingham Tuberculosis Project (1914-1923). Over the past century, nurses have become more sophisticated in their abilities to design, conduct, and analyze data. This article discusses the contributions of medicine and epidemiology to the development of public health nursing and the use of statistical methods by nurses in the United States in the 19th and 20th centuries. Knowledge acquired from this article will inform educators and researchers about the importance of using quantitative analysis, evidenced-based knowledge, and statistical methods when teaching students in all health professions.

APOD Data Release of Social Network Footprint for 2015

NASA Astrophysics Data System (ADS)

Nemiroff, Robert J.; Russell, David; Allen, Alice; Connelly, Paul; Lowe, Stuart R.; Petz, Sydney; Haring, Ralf; Bonnell, Jerry T.; APOD Team

2017-01-01

APOD data for 2015 are being made freely available for download and analysis. The data includes page view statistics for the main NASA APOD website at https://apod.nasa.gov, as well as for APOD's social media sites on Facebook, Instagram, Google Plus, and Twitter. General APOD-specific demographic information for each site is included. Popularity statistics that have been archived including Page Views, Likes, Shares, Hearts, and Retweets. The downloadable Excel-type spreadsheet also includes the APOD title and (unlinked) explanation. This data is released not to highlight APOD's popularity but to encourage analyses, with potential examples involving which astronomy topics trend the best and whether popularity is social group dependent.

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

PubMed

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

2018-04-05

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

Identification of key micro-organisms involved in Douchi fermentation by statistical analysis and their use in an experimental fermentation.

PubMed

Chen, C; Xiang, J Y; Hu, W; Xie, Y B; Wang, T J; Cui, J W; Xu, Y; Liu, Z; Xiang, H; Xie, Q

2015-11-01

To screen and identify safe micro-organisms used during Douchi fermentation, and verify the feasibility of producing high-quality Douchi using these identified micro-organisms. PCR-denaturing gradient gel electrophoresis (DGGE) and automatic amino-acid analyser were used to investigate the microbial diversity and free amino acids (FAAs) content of 10 commercial Douchi samples. The correlations between microbial communities and FAAs were analysed by statistical analysis. Ten strains with significant positive correlation were identified. Then an experiment on Douchi fermentation by identified strains was carried out, and the nutritional composition in Douchi was analysed. Results showed that FAAs and relative content of isoflavone aglycones in verification Douchi samples were generally higher than those in commercial Douchi samples. Our study indicated that fungi, yeasts, Bacillus and lactic acid bacteria were the key players in Douchi fermentation, and with identified probiotic micro-organisms participating in fermentation, a higher quality Douchi product was produced. This is the first report to analyse and confirm the key micro-organisms during Douchi fermentation by statistical analysis. This work proves fermentation micro-organisms to be the key influencing factor of Douchi quality, and demonstrates the feasibility of fermenting Douchi using identified starter micro-organisms. © 2015 The Society for Applied Microbiology.

A wavelet-based statistical analysis of FMRI data: I. motivation and data distribution modeling.

PubMed

Dinov, Ivo D; Boscardin, John W; Mega, Michael S; Sowell, Elizabeth L; Toga, Arthur W

2005-01-01

We propose a new method for statistical analysis of functional magnetic resonance imaging (fMRI) data. The discrete wavelet transformation is employed as a tool for efficient and robust signal representation. We use structural magnetic resonance imaging (MRI) and fMRI to empirically estimate the distribution of the wavelet coefficients of the data both across individuals and spatial locations. An anatomical subvolume probabilistic atlas is used to tessellate the structural and functional signals into smaller regions each of which is processed separately. A frequency-adaptive wavelet shrinkage scheme is employed to obtain essentially optimal estimations of the signals in the wavelet space. The empirical distributions of the signals on all the regions are computed in a compressed wavelet space. These are modeled by heavy-tail distributions because their histograms exhibit slower tail decay than the Gaussian. We discovered that the Cauchy, Bessel K Forms, and Pareto distributions provide the most accurate asymptotic models for the distribution of the wavelet coefficients of the data. Finally, we propose a new model for statistical analysis of functional MRI data using this atlas-based wavelet space representation. In the second part of our investigation, we will apply this technique to analyze a large fMRI dataset involving repeated presentation of sensory-motor response stimuli in young, elderly, and demented subjects.

Incorporating Information of microRNAs into Pathway Analysis in a Genome-Wide Association Study of Bipolar Disorder

PubMed Central

Shih, Wei-Liang; Kao, Chung-Feng; Chuang, Li-Chung; Kuo, Po-Hsiu

2012-01-01

MicroRNAs (miRNAs) are known to be important post-transcriptional regulators that are involved in the etiology of complex psychiatric traits. The present study aimed to incorporate miRNAs information into pathway analysis using a genome-wide association dataset to identify relevant biological pathways for bipolar disorder (BPD). We selected psychiatric- and neurological-associated miRNAs (N = 157) from PhenomiR database. The miRNA target genes (miTG) predictions were obtained from microRNA.org. Canonical pathways (N = 4,051) were downloaded from the Molecule Signature Database. We employed a novel weighting scheme for miTGs in pathway analysis using methods of gene set enrichment analysis and sum-statistic. Under four statistical scenarios, 38 significantly enriched pathways (P-value < 0.01 after multiple testing correction) were identified for the risk of developing BPD, including pathways of ion channels associated (e.g., gated channel activity, ion transmembrane transporter activity, and ion channel activity) and nervous related biological processes (e.g., nervous system development, cytoskeleton, and neuroactive ligand receptor interaction). Among them, 19 were identified only when the weighting scheme was applied. Many miRNA-targeted genes were functionally related to ion channels, collagen, and axonal growth and guidance that have been suggested to be associated with BPD previously. Some of these genes are linked to the regulation of miRNA machinery in the literature. Our findings provide support for the potential involvement of miRNAs in the psychopathology of BPD. Further investigations to elucidate the functions and mechanisms of identified candidate pathways are needed. PMID:23264780

Protein Interaction Networks Reveal Novel Autism Risk Genes within GWAS Statistical Noise

PubMed Central

Correia, Catarina; Oliveira, Guiomar; Vicente, Astrid M.

2014-01-01

Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical “noise” that warrant further analysis for causal variants. PMID:25409314

Protein interaction networks reveal novel autism risk genes within GWAS statistical noise.

PubMed

Correia, Catarina; Oliveira, Guiomar; Vicente, Astrid M

2014-01-01

Genome-wide association studies (GWAS) for Autism Spectrum Disorder (ASD) thus far met limited success in the identification of common risk variants, consistent with the notion that variants with small individual effects cannot be detected individually in single SNP analysis. To further capture disease risk gene information from ASD association studies, we applied a network-based strategy to the Autism Genome Project (AGP) and the Autism Genetics Resource Exchange GWAS datasets, combining family-based association data with Human Protein-Protein interaction (PPI) data. Our analysis showed that autism-associated proteins at higher than conventional levels of significance (P<0.1) directly interact more than random expectation and are involved in a limited number of interconnected biological processes, indicating that they are functionally related. The functionally coherent networks generated by this approach contain ASD-relevant disease biology, as demonstrated by an improved positive predictive value and sensitivity in retrieving known ASD candidate genes relative to the top associated genes from either GWAS, as well as a higher gene overlap between the two ASD datasets. Analysis of the intersection between the networks obtained from the two ASD GWAS and six unrelated disease datasets identified fourteen genes exclusively present in the ASD networks. These are mostly novel genes involved in abnormal nervous system phenotypes in animal models, and in fundamental biological processes previously implicated in ASD, such as axon guidance, cell adhesion or cytoskeleton organization. Overall, our results highlighted novel susceptibility genes previously hidden within GWAS statistical "noise" that warrant further analysis for causal variants.

Statistical Inference at Work: Statistical Process Control as an Example

ERIC Educational Resources Information Center

Bakker, Arthur; Kent, Phillip; Derry, Jan; Noss, Richard; Hoyles, Celia

2008-01-01

To characterise statistical inference in the workplace this paper compares a prototypical type of statistical inference at work, statistical process control (SPC), with a type of statistical inference that is better known in educational settings, hypothesis testing. Although there are some similarities between the reasoning structure involved in…

Revealing representational content with pattern-information fMRI--an introductory guide.

PubMed

Mur, Marieke; Bandettini, Peter A; Kriegeskorte, Nikolaus

2009-03-01

Conventional statistical analysis methods for functional magnetic resonance imaging (fMRI) data are very successful at detecting brain regions that are activated as a whole during specific mental activities. The overall activation of a region is usually taken to indicate involvement of the region in the task. However, such activation analysis does not consider the multivoxel patterns of activity within a brain region. These patterns of activity, which are thought to reflect neuronal population codes, can be investigated by pattern-information analysis. In this framework, a region's multivariate pattern information is taken to indicate representational content. This tutorial introduction motivates pattern-information analysis, explains its underlying assumptions, introduces the most widespread methods in an intuitive way, and outlines the basic sequence of analysis steps.

Statistical Sources for Health Science Librarians.

ERIC Educational Resources Information Center

Weise, Frieda

This continuing education course syllabus presents information on the collection of vital and health statistics, lists of agencies or organizations involved in statistical collection and/or dissemination, annotated bibliographies of statistical sources, and guidelines for accessing statistical information. Topics covered include: (1) the reporting…

Low-Level Contrast Statistics of Natural Images Can Modulate the Frequency of Event-Related Potentials (ERP) in Humans.

PubMed

Ghodrati, Masoud; Ghodousi, Mahrad; Yoonessi, Ali

2016-01-01

Humans are fast and accurate in categorizing complex natural images. It is, however, unclear what features of visual information are exploited by brain to perceive the images with such speed and accuracy. It has been shown that low-level contrast statistics of natural scenes can explain the variance of amplitude of event-related potentials (ERP) in response to rapidly presented images. In this study, we investigated the effect of these statistics on frequency content of ERPs. We recorded ERPs from human subjects, while they viewed natural images each presented for 70 ms. Our results showed that Weibull contrast statistics, as a biologically plausible model, explained the variance of ERPs the best, compared to other image statistics that we assessed. Our time-frequency analysis revealed a significant correlation between these statistics and ERPs' power within theta frequency band (~3-7 Hz). This is interesting, as theta band is believed to be involved in context updating and semantic encoding. This correlation became significant at ~110 ms after stimulus onset, and peaked at 138 ms. Our results show that not only the amplitude but also the frequency of neural responses can be modulated with low-level contrast statistics of natural images and highlights their potential role in scene perception.

Low-Level Contrast Statistics of Natural Images Can Modulate the Frequency of Event-Related Potentials (ERP) in Humans

PubMed Central

Ghodrati, Masoud; Ghodousi, Mahrad; Yoonessi, Ali

2016-01-01

Humans are fast and accurate in categorizing complex natural images. It is, however, unclear what features of visual information are exploited by brain to perceive the images with such speed and accuracy. It has been shown that low-level contrast statistics of natural scenes can explain the variance of amplitude of event-related potentials (ERP) in response to rapidly presented images. In this study, we investigated the effect of these statistics on frequency content of ERPs. We recorded ERPs from human subjects, while they viewed natural images each presented for 70 ms. Our results showed that Weibull contrast statistics, as a biologically plausible model, explained the variance of ERPs the best, compared to other image statistics that we assessed. Our time-frequency analysis revealed a significant correlation between these statistics and ERPs' power within theta frequency band (~3–7 Hz). This is interesting, as theta band is believed to be involved in context updating and semantic encoding. This correlation became significant at ~110 ms after stimulus onset, and peaked at 138 ms. Our results show that not only the amplitude but also the frequency of neural responses can be modulated with low-level contrast statistics of natural images and highlights their potential role in scene perception. PMID:28018197

Los Alamos National Laboratory W76 Pit Tube Lifetime Study

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

Abeln, Terri G.

2012-04-25

A metallurgical study was requested as part of the Los Alamos National Laboratory (LANL) W76-1 life-extension program (LEP) involving a lifetime analysis of type 304 stainless steel pit tubes subject to repeat bending loads during assembly and disassembly operations at BWXT/Pantex. This initial test phase was completed during the calendar years of 2004-2006 and the report not issued until additional recommended tests could be performed. These tests have not been funded to this date and therefore this report is considered final. Tubes were reportedly fabricated according to Rocky Flats specification P14548 - Seamless Type 304 VIM/VAR Stainless Steel Tubing. Tubemore » diameter was specified as 0.125 inches and wall thickness as 0.028 inches. A heat treat condition is not specified and the hardness range specification can be characteristic of both 1/8 and 1/4 hard conditions. Properties of all tubes tested were within specification. Metallographic analysis could not conclusively determine a specified limit to number of bends allowable. A statistical analysis suggests a range of 5-7 bends with a 99.95% confidence limit. See the 'Statistical Analysis' section of this report. The initial phase of this study involved two separate sets of test specimens. The first group was part of an investigation originating in the ESA-GTS [now Gas Transfer Systems (W-7) Group]. After the bend cycle test parameters were chosen (all three required bends subjected to the same amount of bend cycles) and the tubes bent, the investigation was transferred to Terri Abeln (Metallurgical Science and Engineering) for analysis. Subsequently, another limited quantity of tubes became available for testing and were cycled with the same bending fixture, but with different test parameters determined by T. Abeln.« less

Effect of birth ball on labor pain relief: A systematic review and meta-analysis.

PubMed

Makvandi, Somayeh; Latifnejad Roudsari, Robab; Sadeghi, Ramin; Karimi, Leila

2015-11-01

To critically evaluate the available evidence related to the impact of using a birth ball on labor pain relief. The Cochrane library, Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE/PubMed and Scopus were searched from their inception to January 2015 using keywords: (Birth* OR Swiss OR Swedish OR balance OR fitness OR gym* OR Pezzi OR sport* OR stability) AND (ball*) AND (labor OR labour OR Obstetric). All available randomized controlled trials involving women using a birth ball for pain relief during labor were considered. The search resulted in 341 titles and abstracts, which were narrowed down to eight potentially relevant articles. Of these, four studies met the inclusion criteria. Pain intensity on a 10 cm visual analogue scale was used as the main outcome measure. Risk of bias was assessed using the Cochrane Risk of Bias tool. Comprehensive Meta-Analysis Version 2 was used for statistical analysis. Four RCTs involving 220 women were included in the systematic review. One study was excluded from the meta-analysis because of heterogeneous interventions and a lack of mean and standard deviation results of labor pain score. The meta-analysis showed that birth ball exercises provided statistically significant improvements to labor pain (pooled mean difference -0.921; 95% confidence interval -1.28, -0.56; P = 0.0000005; I(2)  = 33.7%). The clinical implementation of a birth ball exercise could be an effective tool for parturient women to reduce labor pain. However, rigorous RCTs are needed to evaluate the effect of the birth ball on labor pain relief. © 2015 Japan Society of Obstetrics and Gynecology.

Diagnostic accuracy of the clinical and CT findings for differentiating Kikuchi's disease and tuberculous lymphadenitis presenting with cervical lymphadenopathy.

PubMed

Baek, Hye Jin; Lee, Jeong Hyun; Lim, Hyun Kyung; Lee, Ha Young; Baek, Jung Hwan

2014-11-01

To determine the optimal clinical and CT findings for differentiating Kikuchi's disease (KD) and tuberculous lymphadenitis (TB) in patients presenting with cervical lymphadenopathy. From 2006 to 2010, 87 consecutive patients who were finally diagnosed with KD or TB were enrolled. Two radiologists performed independent analysis of contrast-enhanced neck CT images with regard to the involvement pattern, nodal or perinodal changes, and evidence of the previous infection. Significant clinical and CT findings of KD were determined by statistical analyses. Of the 87 patients, 27 (31%) were classified as having KD and 60 (69%) as having TB. Statistically significant findings of KD patients were younger age, presence of fever, involvement of ≥5 nodal levels or the bilateral neck, no or minimal nodal necrosis, marked perinodal infiltration, and no evidence of upper lung lesion or mediastinal lymphadenopathy. The presence of four or more statistically significant clinical and CT findings of KD had the largest area under the receiver-operating characteristic curve (A z = 0.861; 95% confidence intervals 0.801, 0.909), with a sensitivity of 89% and specificity of 83%. CT can be a helpful tool for differentiating KD from TB, especially when it is combined with the clinical findings.

Early Father Involvement and Subsequent Child Behaviour at Ages 3, 5 and 7 Years: Prospective Analysis of the UK Millennium Cohort Study.

PubMed

Kroll, Mary E; Carson, Claire; Redshaw, Maggie; Quigley, Maria A

Fathers are increasingly involved in care of their babies and young children. We assessed the association of resident fathers' involvement with subsequent behaviour of their children, examining boys and girls separately. We used longitudinal data from the UK Millennium Cohort Study for children born in 2000-2001, divided into three separate analysis periods: ages 9 months to 3 years, 3 to 5 years, and 5 to 7 years. By exploratory factor analysis of self-reported attitudes and engagement in caring activities, we derived composite measures of various types of father involvement at 9 months, 3 and 5 years. Where possible we created equivalent measures of mother involvement. Child behaviour was assessed by the Strengths and Difficulties Questionnaire (SDQ), which was completed by the mother when the child was aged 3, 5 and 7 years. We estimated gender-specific odds ratios for behaviour problems per quintile of father involvement, using separate logistic regression models for boys and girls in each analysis period. We controlled for a wide range of potential confounders: characteristics of the child (temperament and development at 9 months, and illness and exact age at outcome), equivalent mother involvement where appropriate, and factors related to socioeconomic status, household change, and parental well-being, where statistically significant. Paternal positive parenting beliefs at age 9 months and increased frequency of creative play at age 5 years were significantly associated with lower risk of subsequent behaviour problems (SDQ total difficulties) in both boys and girls (p<0.05), odds ratios ranging between 0.81 and 0.89 per quintile of involvement. No associations were observed for other composite measures of caring activity by the father at 9 months, 3 years or 5 years. Quality of parenting, rather than the division of routine care between parents, was associated with child behavioural outcomes.

Water Polo Game-Related Statistics in Women’s International Championships: Differences and Discriminatory Power

PubMed Central

Escalante, Yolanda; Saavedra, Jose M.; Tella, Victor; Mansilla, Mirella; García-Hermoso, Antonio; Dominguez, Ana M.

2012-01-01

The aims of this study were (i) to compare women’s water polo game-related statistics by match outcome (winning and losing teams) and phase (preliminary, classificatory, and semi-final/bronze medal/gold medal), and (ii) identify characteristics that discriminate performances for each phase. The game-related statistics of the 124 women’s matches played in five International Championships (World and European Championships) were analyzed. Differences between winning and losing teams in each phase were determined using the chi-squared. A discriminant analysis was then performed according to context in each of the three phases. It was found that the game-related statistics differentiate the winning from the losing teams in each phase of an international championship. The differentiating variables were both offensive (centre goals, power-play goals, counterattack goal, assists, offensive fouls, steals, blocked shots, and won sprints) and defensive (goalkeeper-blocked shots, goalkeeper-blocked inferiority shots, and goalkeeper-blocked 5-m shots). The discriminant analysis showed the game-related statistics to discriminate performance in all phases: preliminary, classificatory, and final phases (92%, 90%, and 83%, respectively). Two variables were discriminatory by match outcome (winning or losing teams) in all three phases: goals and goalkeeper-blocked shots. Key pointsThe preliminary phase that more than one variable was involved in this differentiation, including both offensive and defensive aspects of the game.The game-related statistics were found to have a high discriminatory power in predicting the result of matches with shots and goalkeeper-blocked shots being discriminatory variables in all three phases.Knowledge of the characteristics of women’s water polo game-related statistics of the winning teams and their power to predict match outcomes will allow coaches to take these characteristics into account when planning training and match preparation. PMID:24149356

STRengthening analytical thinking for observational studies: the STRATOS initiative.

PubMed

Sauerbrei, Willi; Abrahamowicz, Michal; Altman, Douglas G; le Cessie, Saskia; Carpenter, James

2014-12-30

The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even 'standard' analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests. In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved. © 2014 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd.

Substantial increase in concurrent droughts and heatwaves in the United States

PubMed Central

Mazdiyasni, Omid; AghaKouchak, Amir

2015-01-01

A combination of climate events (e.g., low precipitation and high temperatures) may cause a significant impact on the ecosystem and society, although individual events involved may not be severe extremes themselves. Analyzing historical changes in concurrent climate extremes is critical to preparing for and mitigating the negative effects of climatic change and variability. This study focuses on the changes in concurrences of heatwaves and meteorological droughts from 1960 to 2010. Despite an apparent hiatus in rising temperature and no significant trend in droughts, we show a substantial increase in concurrent droughts and heatwaves across most parts of the United States, and a statistically significant shift in the distribution of concurrent extremes. Although commonly used trend analysis methods do not show any trend in concurrent droughts and heatwaves, a unique statistical approach discussed in this study exhibits a statistically significant change in the distribution of the data. PMID:26324927

Substantial increase in concurrent droughts and heatwaves in the United States.

PubMed

Mazdiyasni, Omid; AghaKouchak, Amir

2015-09-15

A combination of climate events (e.g., low precipitation and high temperatures) may cause a significant impact on the ecosystem and society, although individual events involved may not be severe extremes themselves. Analyzing historical changes in concurrent climate extremes is critical to preparing for and mitigating the negative effects of climatic change and variability. This study focuses on the changes in concurrences of heatwaves and meteorological droughts from 1960 to 2010. Despite an apparent hiatus in rising temperature and no significant trend in droughts, we show a substantial increase in concurrent droughts and heatwaves across most parts of the United States, and a statistically significant shift in the distribution of concurrent extremes. Although commonly used trend analysis methods do not show any trend in concurrent droughts and heatwaves, a unique statistical approach discussed in this study exhibits a statistically significant change in the distribution of the data.

Evaluation of Different Normalization and Analysis Procedures for Illumina Gene Expression Microarray Data Involving Small Changes

PubMed Central

Johnstone, Daniel M.; Riveros, Carlos; Heidari, Moones; Graham, Ross M.; Trinder, Debbie; Berretta, Regina; Olynyk, John K.; Scott, Rodney J.; Moscato, Pablo; Milward, Elizabeth A.

2013-01-01

While Illumina microarrays can be used successfully for detecting small gene expression changes due to their high degree of technical replicability, there is little information on how different normalization and differential expression analysis strategies affect outcomes. To evaluate this, we assessed concordance across gene lists generated by applying different combinations of normalization strategy and analytical approach to two Illumina datasets with modest expression changes. In addition to using traditional statistical approaches, we also tested an approach based on combinatorial optimization. We found that the choice of both normalization strategy and analytical approach considerably affected outcomes, in some cases leading to substantial differences in gene lists and subsequent pathway analysis results. Our findings suggest that important biological phenomena may be overlooked when there is a routine practice of using only one approach to investigate all microarray datasets. Analytical artefacts of this kind are likely to be especially relevant for datasets involving small fold changes, where inherent technical variation—if not adequately minimized by effective normalization—may overshadow true biological variation. This report provides some basic guidelines for optimizing outcomes when working with Illumina datasets involving small expression changes. PMID:27605185

White matter volume loss in amyotrophic lateral sclerosis: A meta-analysis of voxel-based morphometry studies.

PubMed

Chen, Guangxiang; Zhou, Baiwan; Zhu, Hongyan; Kuang, Weihong; Bi, Feng; Ai, Hua; Gu, Zhongwei; Huang, Xiaoqi; Lui, Su; Gong, Qiyong

2018-04-20

Structural neuroimaging studies of white matter (WM) volume in amyotrophic lateral sclerosis (ALS) using voxel-based morphometry (VBM) have yielded inconsistent findings. This study aimed to perform a quantitative voxel-based meta-analysis using effect-size signed differential mapping (ES-SDM) to establish a statistical consensus between published studies for WM volume alterations in ALS. The pooled meta-analysis revealed significant WM volume losses in the bilateral supplementary motor areas (SMAs), bilateral precentral gyri (PGs), left middle cerebellar peduncle and right cerebellum in patients with ALS, involving the corticospinal tract (CST), interhemispheric fibers, subcortical arcuate fibers, projection fibers to the striatum and cortico-ponto-cerebellar tract. The meta-regression showed that the ALS functional rating scale-revised (ALSFRS-R) was positively correlated with decreased WM volume in the bilateral SMAs, whereas illness duration was negatively correlated with WM volume reduction in the right SMA. This study provides a thorough profile of WM volume loss in ALS and robust evidence that ALS is a multisystem neurodegenerative disease that involves a variety of subcortical WM tracts extending beyond motor cortex involvement. Copyright © 2018 Elsevier Inc. All rights reserved.

Cyber Risk Management for Critical Infrastructure: A Risk Analysis Model and Three Case Studies.

PubMed

Paté-Cornell, M-Elisabeth; Kuypers, Marshall; Smith, Matthew; Keller, Philip

2018-02-01

Managing cyber security in an organization involves allocating the protection budget across a spectrum of possible options. This requires assessing the benefits and the costs of these options. The risk analyses presented here are statistical when relevant data are available, and system-based for high-consequence events that have not happened yet. This article presents, first, a general probabilistic risk analysis framework for cyber security in an organization to be specified. It then describes three examples of forward-looking analyses motivated by recent cyber attacks. The first one is the statistical analysis of an actual database, extended at the upper end of the loss distribution by a Bayesian analysis of possible, high-consequence attack scenarios that may happen in the future. The second is a systems analysis of cyber risks for a smart, connected electric grid, showing that there is an optimal level of connectivity. The third is an analysis of sequential decisions to upgrade the software of an existing cyber security system or to adopt a new one to stay ahead of adversaries trying to find their way in. The results are distributions of losses to cyber attacks, with and without some considered countermeasures in support of risk management decisions based both on past data and anticipated incidents. © 2017 Society for Risk Analysis.

Does Topical Ozone Therapy Improve Patient Comfort After Surgical Removal of Impacted Mandibular Third Molar? A Randomized Controlled Trial.

PubMed

Sivalingam, Varun P; Panneerselvam, Elavenil; Raja, Krishnakumar V B; Gopi, Gayathri

2017-01-01

To assess the influence of topical ozone administration on patient comfort after third molar surgery. A single-blinded randomized controlled clinical trial was designed involving patients who required removal of bilateral impacted mandibular third molars. The predictor variable was the postoperative medication used after third molar surgery. Using the split-mouth design, the study group received topical ozone without postoperative systemic antibiotics, whereas the control group did not receive ozone but only systemic antibiotics. The 2 groups were prescribed analgesics for 2 days. The assessing surgeon was blinded to treatment assignment. The primary outcome variables were postoperative mouth opening, pain, and swelling. The secondary outcome variable was the number of analgesic doses required by each group on postoperative days 3 to 5. Data analysis involved descriptive statistics, paired t tests, and 2-way analysis of variance with repeated measures (P < .05). SPSS 20.0 was used for data analysis. The study sample included 33 patients (n = 33 in each group). The study group showed statistically relevant decreases in postoperative pain, swelling, and trismus. Further, the number of analgesics required was smaller than in the control group. No adverse effects of ozone gel were observed in any patient. Ozone gel was found to be an effective topical agent that considerably improves patient comfort postoperatively and can be considered a substitute of postoperative systemic antibiotics. Copyright © 2016 American Association of Oral and Maxillofacial Surgeons. Published by Elsevier Inc. All rights reserved.

On "black swans" and "perfect storms": risk analysis and management when statistics are not enough.

PubMed

Paté-Cornell, Elisabeth

2012-11-01

Two images, "black swans" and "perfect storms," have struck the public's imagination and are used--at times indiscriminately--to describe the unthinkable or the extremely unlikely. These metaphors have been used as excuses to wait for an accident to happen before taking risk management measures, both in industry and government. These two images represent two distinct types of uncertainties (epistemic and aleatory). Existing statistics are often insufficient to support risk management because the sample may be too small and the system may have changed. Rationality as defined by the von Neumann axioms leads to a combination of both types of uncertainties into a single probability measure--Bayesian probability--and accounts only for risk aversion. Yet, the decisionmaker may also want to be ambiguity averse. This article presents an engineering risk analysis perspective on the problem, using all available information in support of proactive risk management decisions and considering both types of uncertainty. These measures involve monitoring of signals, precursors, and near-misses, as well as reinforcement of the system and a thoughtful response strategy. It also involves careful examination of organizational factors such as the incentive system, which shape human performance and affect the risk of errors. In all cases, including rare events, risk quantification does not allow "prediction" of accidents and catastrophes. Instead, it is meant to support effective risk management rather than simply reacting to the latest events and headlines. © 2012 Society for Risk Analysis.

Statistical aspects of carbon fiber risk assessment modeling. [fire accidents involving aircraft

NASA Technical Reports Server (NTRS)

Gross, D.; Miller, D. R.; Soland, R. M.

1980-01-01

The probabilistic and statistical aspects of the carbon fiber risk assessment modeling of fire accidents involving commercial aircraft are examined. Three major sources of uncertainty in the modeling effort are identified. These are: (1) imprecise knowledge in establishing the model; (2) parameter estimation; and (3)Monte Carlo sampling error. All three sources of uncertainty are treated and statistical procedures are utilized and/or developed to control them wherever possible.

Parent involvement and student academic performance: A multiple mediational analysis

PubMed Central

Topor, David R.; Keane, Susan P.; Shelton, Terri L.; Calkins, Susan D.

2011-01-01

Parent involvement in a child's education is consistently found to be positively associated with a child's academic performance. However, there has been little investigation of the mechanisms that explain this association. The present study examines two potential mechanisms of this association: the child's perception of cognitive competence and the quality of the student-teacher relationship. This study used a sample of 158 seven-year old participants, their mothers, and their teachers. Results indicated a statistically significant association between parent involvement and a child's academic performance, over and above the impact of the child's intelligence. A multiple mediation model indicated that the child's perception of cognitive competence fully mediated the relation between parent involvement and the child's performance on a standardized achievement test. The quality of the student-teacher relationship fully mediated the relation between parent involvement and teacher ratings of the child's classroom academic performance. Limitations, future research directions, and implications for public policy initiatives were discussed. PMID:20603757

Integrating Data From the UK National Reporting and Learning System With Work Domain Analysis to Understand Patient Safety Incidents in Community Pharmacy.

PubMed

Phipps, Denham L; Tam, W Vanessa; Ashcroft, Darren M

2017-03-01

To explore the combined use of a critical incident database and work domain analysis to understand patient safety issues in a health-care setting. A retrospective review was conducted of incidents reported to the UK National Reporting and Learning System (NRLS) that involved community pharmacy between April 2005 and August 2010. A work domain analysis of community pharmacy was constructed using observational data from 5 community pharmacies, technical documentation, and a focus group with 6 pharmacists. Reports from the NRLS were mapped onto the model generated by the work domain analysis. Approximately 14,709 incident reports meeting the selection criteria were retrieved from the NRLS. Descriptive statistical analysis of these reports found that almost all of the incidents involved medication and that the most frequently occurring error types were dose/strength errors, incorrect medication, and incorrect formulation. The work domain analysis identified 4 overall purposes for community pharmacy: business viability, health promotion and clinical services, provision of medication, and use of medication. These purposes were served by lower-order characteristics of the work system (such as the functions, processes and objects). The tasks most frequently implicated in the incident reports were those involving medication storage, assembly, or patient medication records. Combining the insights from different analytical methods improves understanding of patient safety problems. Incident reporting data can be used to identify general patterns, whereas the work domain analysis can generate information about the contextual factors that surround a critical task.

Comparative analysis of a nontraditional general chemistry textbook and selected traditional textbooks used in Texas community colleges

NASA Astrophysics Data System (ADS)

Salvato, Steven Walter

The purpose of this study was to analyze questions within the chapters of a nontraditional general chemistry textbook and the four general chemistry textbooks most widely used by Texas community colleges in order to determine if the questions require higher- or lower-order thinking according to Bloom's taxonomy. The study employed quantitative methods. Bloom's taxonomy (Bloom, Engelhart, Furst, Hill, & Krathwohl, 1956) was utilized as the main instrument in the study. Additional tools were used to help classify the questions into the proper category of the taxonomy (McBeath, 1992; Metfessel, Michael, & Kirsner, 1969). The top four general chemistry textbooks used in Texas community colleges and Chemistry: A Project of the American Chemical Society (Bell et al., 2005) were analyzed during the fall semester of 2010 in order to categorize the questions within the chapters into one of the six levels of Bloom's taxonomy. Two coders were used to assess reliability. The data were analyzed using descriptive and inferential methods. The descriptive method involved calculation of the frequencies and percentages of coded questions from the books as belonging to the six categories of the taxonomy. Questions were dichotomized into higher- and lower-order thinking questions. The inferential methods involved chi-square tests of association to determine if there were statistically significant differences among the four traditional college general chemistry textbooks in the proportions of higher- and lower-order questions and if there were statistically significant differences between the nontraditional chemistry textbook and the four traditional general chemistry textbooks. Findings indicated statistically significant differences among the four textbooks frequently used in Texas community colleges in the number of higher- and lower-level questions. Statistically significant differences were also found among the four textbooks and the nontraditional textbook. After the analysis of the data, conclusions were drawn, implications for practice were delineated, and recommendations for future research were given.

STRengthening Analytical Thinking for Observational Studies: the STRATOS initiative

PubMed Central

Sauerbrei, Willi; Abrahamowicz, Michal; Altman, Douglas G; le Cessie, Saskia; Carpenter, James

2014-01-01

The validity and practical utility of observational medical research depends critically on good study design, excellent data quality, appropriate statistical methods and accurate interpretation of results. Statistical methodology has seen substantial development in recent times. Unfortunately, many of these methodological developments are ignored in practice. Consequently, design and analysis of observational studies often exhibit serious weaknesses. The lack of guidance on vital practical issues discourages many applied researchers from using more sophisticated and possibly more appropriate methods when analyzing observational studies. Furthermore, many analyses are conducted by researchers with a relatively weak statistical background and limited experience in using statistical methodology and software. Consequently, even ‘standard’ analyses reported in the medical literature are often flawed, casting doubt on their results and conclusions. An efficient way to help researchers to keep up with recent methodological developments is to develop guidance documents that are spread to the research community at large. These observations led to the initiation of the strengthening analytical thinking for observational studies (STRATOS) initiative, a large collaboration of experts in many different areas of biostatistical research. The objective of STRATOS is to provide accessible and accurate guidance in the design and analysis of observational studies. The guidance is intended for applied statisticians and other data analysts with varying levels of statistical education, experience and interests. In this article, we introduce the STRATOS initiative and its main aims, present the need for guidance documents and outline the planned approach and progress so far. We encourage other biostatisticians to become involved. PMID:25074480

Senior Computational Scientist | Center for Cancer Research

Cancer.gov

The Basic Science Program (BSP) pursues independent, multidisciplinary research in basic and applied molecular biology, immunology, retrovirology, cancer biology, and human genetics. Research efforts and support are an integral part of the Center for Cancer Research (CCR) at the Frederick National Laboratory for Cancer Research (FNLCR). The Cancer & Inflammation Program (CIP), Basic Science Program, HLA Immunogenetics Section, under the leadership of Dr. Mary Carrington, studies the influence of human leukocyte antigens (HLA) and specific KIR/HLA genotypes on risk of and outcomes to infection, cancer, autoimmune disease, and maternal-fetal disease. Recent studies have focused on the impact of HLA gene expression in disease, the molecular mechanism regulating expression levels, and the functional basis for the effect of differential expression on disease outcome. The lab’s further focus is on the genetic basis for resistance/susceptibility to disease conferred by immunogenetic variation. KEY ROLES/RESPONSIBILITIES The Senior Computational Scientist will provide research support to the CIP-BSP-HLA Immunogenetics Section performing bio-statistical design, analysis and reporting of research projects conducted in the lab. This individual will be involved in the implementation of statistical models and data preparation. Successful candidate should have 5 or more years of competent, innovative biostatistics/bioinformatics research experience, beyond doctoral training Considerable experience with statistical software, such as SAS, R and S-Plus Sound knowledge, and demonstrated experience of theoretical and applied statistics Write program code to analyze data using statistical analysis software Contribute to the interpretation and publication of research results

ParallABEL: an R library for generalized parallelization of genome-wide association studies.

PubMed

Sangket, Unitsa; Mahasirimongkol, Surakameth; Chantratita, Wasun; Tandayya, Pichaya; Aulchenko, Yurii S

2010-04-29

Genome-Wide Association (GWA) analysis is a powerful method for identifying loci associated with complex traits and drug response. Parts of GWA analyses, especially those involving thousands of individuals and consuming hours to months, will benefit from parallel computation. It is arduous acquiring the necessary programming skills to correctly partition and distribute data, control and monitor tasks on clustered computers, and merge output files. Most components of GWA analysis can be divided into four groups based on the types of input data and statistical outputs. The first group contains statistics computed for a particular Single Nucleotide Polymorphism (SNP), or trait, such as SNP characterization statistics or association test statistics. The input data of this group includes the SNPs/traits. The second group concerns statistics characterizing an individual in a study, for example, the summary statistics of genotype quality for each sample. The input data of this group includes individuals. The third group consists of pair-wise statistics derived from analyses between each pair of individuals in the study, for example genome-wide identity-by-state or genomic kinship analyses. The input data of this group includes pairs of SNPs/traits. The final group concerns pair-wise statistics derived for pairs of SNPs, such as the linkage disequilibrium characterisation. The input data of this group includes pairs of individuals. We developed the ParallABEL library, which utilizes the Rmpi library, to parallelize these four types of computations. ParallABEL library is not only aimed at GenABEL, but may also be employed to parallelize various GWA packages in R. The data set from the North American Rheumatoid Arthritis Consortium (NARAC) includes 2,062 individuals with 545,080, SNPs' genotyping, was used to measure ParallABEL performance. Almost perfect speed-up was achieved for many types of analyses. For example, the computing time for the identity-by-state matrix was linearly reduced from approximately eight hours to one hour when ParallABEL employed eight processors. Executing genome-wide association analysis using the ParallABEL library on a computer cluster is an effective way to boost performance, and simplify the parallelization of GWA studies. ParallABEL is a user-friendly parallelization of GenABEL.

[The problem of abortions and enhancement of analysis of reproductive behavior of women].

PubMed

Maksimova, T M; Belov, V B; Lushkina, N P; Nikitina, S Iu; Redina, M A

2012-01-01

The article deals with the study of actual rate of abortions in Russia. It is established that multi-aspect statistical information is needed to compare with the data of international organizations. The regular monitoring is important to control the different characteristics of population reproductive behavior abortion prevalence and the all-inclusive participation in the reporting activity of all medical institutions involved independently of property forms and sectorial membership.

Methods of Single Station and Limited Data Analysis and Forecasting

DTIC Science & Technology

1985-08-15

example using real data. Discusses modifications of SSA technique in certain climatological regimes and describes some statistical tech- niques for SSA of... caster has access to radar or satellite observations, or any computer products during the period of his isolation. Where calculations are involved, it is...chapters of the text will deal with special topics such as modifications of the SSA technique that must be considered for certain clima- tological regimes

Guidelines for the design and statistical analysis of experiments in papers submitted to ATLA.

PubMed

Festing, M F

2001-01-01

In vitro experiments need to be well designed and correctly analysed if they are to achieve their full potential to replace the use of animals in research. An "experiment" is a procedure for collecting scientific data in order to answer a hypothesis, or to provide material for generating new hypotheses, and differs from a survey because the scientist has control over the treatments that can be applied. Most experiments can be classified into one of a few formal designs, the most common being completely randomised, and randomised block designs. These are quite common with in vitro experiments, which are often replicated in time. Some experiments involve a single independent (treatment) variable, while other "factorial" designs simultaneously vary two or more independent variables, such as drug treatment and cell line. Factorial designs often provide additional information at little extra cost. Experiments need to be carefully planned to avoid bias, be powerful yet simple, provide for a valid statistical analysis and, in some cases, have a wide range of applicability. Virtually all experiments need some sort of statistical analysis in order to take account of biological variation among the experimental subjects. Parametric methods using the t test or analysis of variance are usually more powerful than non-parametric methods, provided the underlying assumptions of normality of the residuals and equal variances are approximately valid. The statistical analyses of data from a completely randomised design, and from a randomised-block design are demonstrated in Appendices 1 and 2, and methods of determining sample size are discussed in Appendix 3. Appendix 4 gives a checklist for authors submitting papers to ATLA.

Low-cost digital image processing at the University of Oklahoma

NASA Technical Reports Server (NTRS)

Harrington, J. A., Jr.

1981-01-01

Computer assisted instruction in remote sensing at the University of Oklahoma involves two separate approaches and is dependent upon initial preprocessing of a LANDSAT computer compatible tape using software developed for an IBM 370/158 computer. In-house generated preprocessing algorithms permits students or researchers to select a subset of a LANDSAT scene for subsequent analysis using either general purpose statistical packages or color graphic image processing software developed for Apple II microcomputers. Procedures for preprocessing the data and image analysis using either of the two approaches for low-cost LANDSAT data processing are described.

Immunohistochemical evaluation of inducible nitric oxide synthase in the epithelial lining of odontogenic cysts: A qualitative and quantitative analysis

PubMed Central

Akshatha, B K; Karuppiah, Karpagaselvi; Manjunath, G S; Kumarswamy, Jayalakshmi; Papaiah, Lokesh; Rao, Jyothi

2017-01-01

Introduction: The three common odontogenic cysts include radicular cysts (RCs), dentigerous cysts (DCs), and odontogenic keratocysts (OKCs). Among these 3 cysts, OKC is recently been classified as benign keratocystic odontogenic tumor attributing to its aggressive behavior, recurrence rate, and malignant potential. The present study involved qualitative and quantitative analysis of inducible nitric oxide synthase (iNOS) expression in epithelial lining of RCs, DCs, and OKCs, compare iNOS expression in epithelial linings of all the 3 cysts and determined overexpression of iNOS in OKCs which might contribute to its aggressive behavior and malignant potential. Aims: The present study is to investigate the role of iNOS in the pathogenesis of OKCs, DCs, and RCs by evaluating the iNOS expression in the epithelial lining of these cysts. Subjects and Methods: Analysis of iNOS expression in epithelial lining cells of 20 RCs, 20 DCs, and 20 OKCs using immunohistochemistry done. Statistical Analysis Used: The percentage of positive cells and intensity of stain was assessed and compared among all the 3 cysts using contingency coefficient. Kappa statistics for the two observers were computed for finding interobserver agreement. Results: The percentage of iNOS-positive cells was found to be remarkably high in OKCs (12/20) –57.1% as compared to RCs (6/20) – 28.6% and DCs (3/20) – 14.3%. The interobserver agreement for iNOS-positive percentage cells was arrived with kappa values with OKCs → Statistically significant (P > 0.000), RCs → statistically significant (P > 0.001) with no significant values for DCs. No statistical difference exists among 3 study samples in regard to the intensity of staining with iNOS. Conclusions: Increased iNOS expression in OKCs may contribute to bone resorption and accumulation of wild-type p53, hence, making OKCs more aggressive. PMID:29391711

A Simple Test of Class-Level Genetic Association Can Reveal Novel Cardiometabolic Trait Loci.

PubMed

Qian, Jing; Nunez, Sara; Reed, Eric; Reilly, Muredach P; Foulkes, Andrea S

2016-01-01

Characterizing the genetic determinants of complex diseases can be further augmented by incorporating knowledge of underlying structure or classifications of the genome, such as newly developed mappings of protein-coding genes, epigenetic marks, enhancer elements and non-coding RNAs. We apply a simple class-level testing framework, termed Genetic Class Association Testing (GenCAT), to identify protein-coding gene association with 14 cardiometabolic (CMD) related traits across 6 publicly available genome wide association (GWA) meta-analysis data resources. GenCAT uses SNP-level meta-analysis test statistics across all SNPs within a class of elements, as well as the size of the class and its unique correlation structure, to determine if the class is statistically meaningful. The novelty of findings is evaluated through investigation of regional signals. A subset of findings are validated using recently updated, larger meta-analysis resources. A simulation study is presented to characterize overall performance with respect to power, control of family-wise error and computational efficiency. All analysis is performed using the GenCAT package, R version 3.2.1. We demonstrate that class-level testing complements the common first stage minP approach that involves individual SNP-level testing followed by post-hoc ascribing of statistically significant SNPs to genes and loci. GenCAT suggests 54 protein-coding genes at 41 distinct loci for the 13 CMD traits investigated in the discovery analysis, that are beyond the discoveries of minP alone. An additional application to biological pathways demonstrates flexibility in defining genetic classes. We conclude that it would be prudent to include class-level testing as standard practice in GWA analysis. GenCAT, for example, can be used as a simple, complementary and efficient strategy for class-level testing that leverages existing data resources, requires only summary level data in the form of test statistics, and adds significant value with respect to its potential for identifying multiple novel and clinically relevant trait associations.

Conceptual Models of Depression in Primary Care Patients: A Comparative Study

PubMed Central

Karasz, Alison; Garcia, Nerina; Ferri, Lucia

2009-01-01

Conventional psychiatric treatment models are based on a biopsychiatric model of depression. A plausible explanation for low rates of depression treatment utilization among ethnic minorities and the poor is that members of these communities do not share the cultural assumptions underlying the biopsychiatric model. The study examined conceptual models of depression among depressed patients from various ethnic groups, focusing on the degree to which patients’ conceptual models ‘matched’ a biopsychiatric model of depression. The sample included 74 primary care patients from three ethnic groups screening positive for depression. We administered qualitative interviews assessing patients’ conceptual representations of depression. The analysis proceeded in two phases. The first phase involved a strategy called ‘quantitizing’ the qualitative data. A rating scheme was developed and applied to the data by a rater blind to study hypotheses. The data was subjected to statistical analyses. The second phase of the analysis involved the analysis of thematic data using standard qualitative techniques. Study hypotheses were largely supported. The qualitative analysis provided a detailed picture of primary care patients’ conceptual models of depression and suggested interesting directions for future research. PMID:20182550

RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

NASA Astrophysics Data System (ADS)

Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

2005-10-01

Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and spatial statistics. The tool also includes some fundamental spatial and non-spatial database in regional population and environment, which can be updated by external database via CD or network. Utilizing this data mining and exploratory analytical tool, the users can easily and quickly analyse the huge mount of the interrelated regional data, and better understand the spatial patterns and trends of the regional development, so as to make a credible and scientific decision. Moreover, it can be used as an educational tool for spatial data analysis and environmental studies. In this paper, we also present a case study on Poyang Lake Basin as an application of the tool and spatial data mining in complex environmental studies. At last, several concluding remarks are discussed.

Cost-effectiveness research in cancer therapy: a systematic review of literature trends, methods and the influence of funding

PubMed Central

Al-Badriyeh, Daoud; Alameri, Marwah; Al-Okka, Randa

2017-01-01

Objective To perform a first-time analysis of the cost-effectiveness (CE) literature on chemotherapies, of all types, in cancer, in terms of trends and change over time, including the influence of industry funding. Design Systematic review. Setting A wide range of cancer-related research settings within healthcare, including health systems, hospitals and medical centres. Participants All literature comparative CE research of drug-based cancer therapies in the period 1986 to 2015. Primary and secondary outcome measures Primary outcomes are the literature trends in relation to journal subject category, authorship, research design, data sources, funds and consultation involvement. An additional outcome measure is the association between industry funding and study outcomes. Analysis Descriptive statistics and the χ2, Fisher exact or Somer's D tests were used to perform non-parametric statistics, with a p value of <0.05 as the statistical significance measure. Results Total 574 publications were analysed. The drug-related CE literature expands over time, with increased publishing in the healthcare sciences and services journal subject category (p<0.001). The retrospective data collection in studies increased over time (p<0.001). The usage of prospective data, however, has been decreasing (p<0.001) in relation to randomised clinical trials (RCTs), but is unchanging for non-RCT studies. The industry-sponsored CE studies have especially been increasing (p<0.001), in contrast to those sponsored by other sources. While paid consultation involvement grew throughout the years, the declaration of funding for this is relatively limited. Importantly, there is evidence that industry funding is associated with favourable result to the sponsor (p<0.001). Conclusions This analysis demonstrates clear trends in how the CE cancer research is presented to the practicing community, including in relation to journals, study designs, authorship and consultation, together with increased financial sponsorship by pharmaceutical industries, which may be more influencing study outcomes than other funding sources. PMID:28131999

Influence of science and technology magnet middle schools on students' motivation and achievement in science

NASA Astrophysics Data System (ADS)

Allen, David

Some informal discussions among educators regarding motivation of students and academic performance have included the topic of magnet schools. The premise is that a focused theme, such as an aspect of science, positively affects student motivation and academic achievement. However, there is limited research involving magnet schools and their influence on student motivation and academic performance. This study provides empirical data for the discussion about magnet schools influence on motivation and academic ability. This study utilized path analysis in a structural equation modeling framework to simultaneously investigate the relationships between demographic exogenous independent variables, the independent variable of attending a science or technology magnet middle school, and the dependent variables of motivation to learn science and academic achievement in science. Due to the categorical nature of the variables, Bayesian statistical analysis was used to calculate the path coefficients and the standardized effects for each relationship in the model. The coefficients of determination were calculated to determine the amount of variance each path explained. Only five of 21 paths had statistical significance. Only one of the five statistically significant paths (Attended Magnet School to Motivation to Learn Science) explained a noteworthy amount (45.8%) of the variance.

Quality quandaries: Statistical detective work to understand the isotopic ratios in Drum 68660 and the radioactive release at WIPP

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

Kelly, Elizabeth J.; Weaver, Brian Phillip; Veirs, Douglas Kirk

An incident at the Department of Energy's Waste Isolation Pilot Plant (WIPP) in 2014 resulted in the release of radioactive material into the environment. Initially, it was known that at least one drum in WIPP, identified as drum 68660, was involved. However, questions remained. Could the air-monitor isotopic ratios measured in WIPP at the time of the release be explained by materials in drum 68660 or were other drums involved? Could internal conditions in drum 68660 have caused the breach? What were the implications for 68660's sister drum? These questions needed to be answered as quickly as possible. Here, thismore » analysis, which was completed in three weeks, combined combinatorics and uncertainty analysis to provide scientists with the timely evidence they needed to either answer these important questions or to design experiments to answer them.« less

Quality quandaries: Statistical detective work to understand the isotopic ratios in Drum 68660 and the radioactive release at WIPP

DOE PAGES

Kelly, Elizabeth J.; Weaver, Brian Phillip; Veirs, Douglas Kirk

2017-08-09

An incident at the Department of Energy's Waste Isolation Pilot Plant (WIPP) in 2014 resulted in the release of radioactive material into the environment. Initially, it was known that at least one drum in WIPP, identified as drum 68660, was involved. However, questions remained. Could the air-monitor isotopic ratios measured in WIPP at the time of the release be explained by materials in drum 68660 or were other drums involved? Could internal conditions in drum 68660 have caused the breach? What were the implications for 68660's sister drum? These questions needed to be answered as quickly as possible. Here, thismore » analysis, which was completed in three weeks, combined combinatorics and uncertainty analysis to provide scientists with the timely evidence they needed to either answer these important questions or to design experiments to answer them.« less

An advanced probabilistic structural analysis method for implicit performance functions

NASA Technical Reports Server (NTRS)

Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.

1989-01-01

In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

Are drivers with CVD more at risk for motor vehicle crashes? Study of men aged 45 to 70.

PubMed Central

Guibert, R.; Potvin, L.; Ciampi, A.; Loiselle, J.; Philibert, L.; Franco, E. D.

1998-01-01

OBJECTIVE: To examine whether male drivers aged 45 to 70 years suffering from cardiovascular disease (CVD) are more likely to be involved in motor vehicle crashes (MVC) that are reported to the police. DESIGN: Population-based case-control study. SETTING: Data on drivers' ages and medical conditions were compiled from the Societé de l'assurance automobile du Québec's (SAAQ) computerized files. A questionnaire was mailed to all subjects to collect additional information on annual distances driven and various driving behaviours. PARTICIPANTS: Age-stratified population-based random sample. Subjects were 2504 drivers involved in MVCs during a 6-month period; controls were 2520 drivers not involved in crashes. MAIN OUTCOME MEASURES: Proportion of drivers with CVD involved in MVCs. RESULTS: Response rate to the questionnaire was 35.5%. Analysis of the SAAQ files' entire sample of 5024 drivers showed that drivers suffering from CVD were less likely to be involved in MVCs (odds ratio [OR] 0.82, 95% confidence interval [CI] 0.67 to 0.99) than drivers without CVD. Although the estimate of risk remains unchanged when adjusted for age, it becomes statistically insignificant. It also remains unchanged and statistically insignificant when adjusted for yearly distance driven and driver behaviour, as shown by responses to the questionnaire. Drivers suffering from CVD drove significantly less each year (8900 km) than drivers without medical conditions (13,000 km). CONCLUSION: This study shows no increased risk of motor vehicle crashes for drivers suffering from CVD. PMID:9585850

Radiologic science students' perceptions of parental involvement.

PubMed

DuBose, Cheryl; Barymon, Deanna; Vanderford, Virginia; Hensley, Chad; Shaver, Gary

2014-01-01

A new generation of students is in the classroom, and they are not always alone. Helicopter parents, those who hover around the student and attempt to ease life's challenges, are accompanying the students to radiologic science programs across the nation. To determine radiologic science students' perception regarding their parents' level of involvement in their lives. A survey focused on student perceptions of parental involvement inside and outside of the academic setting was completed by 121 radiologic science students at 4 institutional settings. The analysis demonstrates statistically significant relationships between student sex, age, marital status, and perceived level of parental involvement. In addition, as financial support increases, students' perception of the level of parental involvement also increases. Radiologic science students want their parents to be involved in their higher education decisions. Research indicates that students with involved parents are more successful, and faculty should be prepared for increased parental involvement in the future. Radiologic science students perceive their parents to be involved in their academic careers. Ninety-five percent of respondents believe that the financial support of their parent or parents contributes to their academic success. Sixty-five percent of participants are content with their parents' current level of involvement, while 11% wish their parents were more involved in their academic careers.

fMRI paradigm designing and post-processing tools

PubMed Central

James, Jija S; Rajesh, PG; Chandran, Anuvitha VS; Kesavadas, Chandrasekharan

2014-01-01

In this article, we first review some aspects of functional magnetic resonance imaging (fMRI) paradigm designing for major cognitive functions by using stimulus delivery systems like Cogent, E-Prime, Presentation, etc., along with their technical aspects. We also review the stimulus presentation possibilities (block, event-related) for visual or auditory paradigms and their advantage in both clinical and research setting. The second part mainly focus on various fMRI data post-processing tools such as Statistical Parametric Mapping (SPM) and Brain Voyager, and discuss the particulars of various preprocessing steps involved (realignment, co-registration, normalization, smoothing) in these software and also the statistical analysis principles of General Linear Modeling for final interpretation of a functional activation result. PMID:24851001

The resolving power of in vitro genotoxicity assays for cigarette smoke particulate matter.

PubMed

Scott, K; Saul, J; Crooks, I; Camacho, O M; Dillon, D; Meredith, C

2013-06-01

In vitro genotoxicity assays are often used to compare tobacco smoke particulate matter (PM) from different cigarettes. The quantitative aspect of the comparisons requires appropriate statistical methods and replication levels, to support the interpretation in terms of power and significance. This paper recommends a uniform statistical analysis for the Ames test, mouse lymphoma mammalian cell mutation assay (MLA) and the in vitro micronucleus test (IVMNT); involving a hierarchical decision process with respect to slope, fixed effect and single dose comparisons. With these methods, replication levels of 5 (Ames test TA98), 4 (Ames test TA100), 10 (Ames test TA1537), 6 (MLA) and 4 (IVMNT) resolved a 30% difference in PM genotoxicity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Properties of different selection signature statistics and a new strategy for combining them.

PubMed

Ma, Y; Ding, X; Qanbari, S; Weigend, S; Zhang, Q; Simianer, H

2015-11-01

Identifying signatures of recent or ongoing selection is of high relevance in livestock population genomics. From a statistical perspective, determining a proper testing procedure and combining various test statistics is challenging. On the basis of extensive simulations in this study, we discuss the statistical properties of eight different established selection signature statistics. In the considered scenario, we show that a reasonable power to detect selection signatures is achieved with high marker density (>1 SNP/kb) as obtained from sequencing, while rather small sample sizes (~15 diploid individuals) appear to be sufficient. Most selection signature statistics such as composite likelihood ratio and cross population extended haplotype homozogysity have the highest power when fixation of the selected allele is reached, while integrated haplotype score has the highest power when selection is ongoing. We suggest a novel strategy, called de-correlated composite of multiple signals (DCMS) to combine different statistics for detecting selection signatures while accounting for the correlation between the different selection signature statistics. When examined with simulated data, DCMS consistently has a higher power than most of the single statistics and shows a reliable positional resolution. We illustrate the new statistic to the established selective sweep around the lactase gene in human HapMap data providing further evidence of the reliability of this new statistic. Then, we apply it to scan selection signatures in two chicken samples with diverse skin color. Our analysis suggests that a set of well-known genes such as BCO2, MC1R, ASIP and TYR were involved in the divergent selection for this trait.

Urine β2-microglobulin is associated with clinical disease activity and renal involvement in female patients with systemic lupus erythematosus.

PubMed

Choe, J-Y; Park, S-H; Kim, S-K

2014-12-01

We investigated the association of serum and urine β2-microglobulin (β2MG) with renal involvement and clinical disease activity in systemic lupus erythematosus (SLE). Sixty-four female patients with SLE were enrolled. We assessed SLE disease activity (SLEDAI)-2K and measured serum and urine β2MG levels, as well as complement (C3 and C4) and anti-dsDNA levels. According to the SLEDAI scores, two groups were categorized: low (0-5 of SLEDAI) and high (6-19 of SLEDAI) disease activity groups. The presence of renal involvement was determined by renal SLEDAI score. Statistical analysis was performed using Spearman's correlation analysis, Mann-Whitney U test, multivariate regression analysis, and logistic regression analysis. Urine β2MG levels were significantly different between low and high SLEDAI groups (p = 0.001), but not for serum β2MG levels (p = 0.579). Patients with renal involvement showed higher urine β2MG levels compared to those without renal involvement (p < 0.001), but again there was not a difference in serum β2MG levels (p = 0.228). Urine β2MG was closely associated with SLEDAI (r = 0.363, p = 0.003), renal SLEDAI (r = 0.479, p < 0.001), urine protein/Cr (r = 0.416, p = 0.001), and ESR (r = 0.347, p = 0.006), but not serum β2MG (r = 0.245, p = 0.051). Urine β2MG level was identified as a surrogate for renal involvement (p = 0.009, OR = 1.017, 95% CI 1.004-1.030) and overall disease activity (p = 0.009, OR = 1.020, 95% CI 1.005-1.036). We demonstrated that urine β2MG levels are associated with renal involvement and overall clinical disease activity in SLE. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Designing for auto safety

NASA Technical Reports Server (NTRS)

Driver, E. T.

1971-01-01

Safety design features in the motor vehicle and highway construction fields result from systems analysis approach to prevent or lessen death, injury, and property damage results. Systems analysis considers the prevention of crashes, increased survivability in crashes, and prompt medical attention to injuries as well as other postcrash salvage measures. The interface of these system elements with the driver, the vehicle, and the environment shows that action on the vehicle system produces the greatest safety payoff through design modifications. New and amended safety standards developed through hazard analysis technique improved accident statistics in the 70'; these regulations include driver qualifications and countermeasures to identify the chronic drunken driver who is involved in more than two-thirds of all auto deaths.

Inferring Instantaneous, Multivariate and Nonlinear Sensitivities for the Analysis of Feedback Processes in a Dynamical System: Lorenz Model Case Study

NASA Technical Reports Server (NTRS)

Aires, Filipe; Rossow, William B.; Hansen, James E. (Technical Monitor)

2001-01-01

A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.

Protein mass spectra data analysis for clinical biomarker discovery: a global review.

PubMed

Roy, Pascal; Truntzer, Caroline; Maucort-Boulch, Delphine; Jouve, Thomas; Molinari, Nicolas

2011-03-01

The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. In recent years there has been a growing interest in using high throughput technologies for the detection of such biomarkers. In particular, mass spectrometry appears as an exciting tool with great potential. However, to extract any benefit from the massive potential of clinical proteomic studies, appropriate methods, improvement and validation are required. To better understand the key statistical points involved with such studies, this review presents the main data analysis steps of protein mass spectra data analysis, from the pre-processing of the data to the identification and validation of biomarkers.

[Microvascular descompression for trigeminal neuralgia: prognostic [corrected] factors].

PubMed

Alberione, F; Arena, A; Matera, R

2008-06-01

We describe our experience of the MVD in the typical trigeminal neuralgia and identify the prognostic factors. A retrospective studio of 89 cases between 1995-2005 was used. The prognostic significant data evaluated were demographics data; duration of neuralgia; the affected divisions involved; surgical findings; used material for the decompression. The data analysis was made with the chi(2) test. We have found an excellent outcome in 77% one year later. The age and the antecedent of hypertension disease were not statistically significant. A poor outcome was observed for: female sex, neuralgia lasting longer than two years, the three divisions involved, venous compression and the muscle used as surgical material. The MVD is an effective and reliable technique. The use of muscle is not recommended. When the three trigeminal divisions are involved we should choose another technique.

Size and shape measurement in contemporary cephalometrics.

PubMed

McIntyre, Grant T; Mossey, Peter A

2003-06-01

The traditional method of analysing cephalograms--conventional cephalometric analysis (CCA)--involves the calculation of linear distance measurements, angular measurements, area measurements, and ratios. Because shape information cannot be determined from these 'size-based' measurements, an increasing number of studies employ geometric morphometric tools in the cephalometric analysis of craniofacial morphology. Most of the discussions surrounding the appropriateness of CCA, Procrustes superimposition, Euclidean distance matrix analysis (EDMA), thin-plate spline analysis (TPS), finite element morphometry (FEM), elliptical Fourier functions (EFF), and medial axis analysis (MAA) have centred upon mathematical and statistical arguments. Surprisingly, little information is available to assist the orthodontist in the clinical relevance of each technique. This article evaluates the advantages and limitations of the above methods currently used to analyse the craniofacial morphology on cephalograms and investigates their clinical relevance and possible applications.

Variations in clinicopathologic characteristics of thyroid cancer among racial ethnic groups: analysis of a large public city hospital and the SEER database.

PubMed

Moo-Young, Tricia A; Panergo, Jessel; Wang, Chih E; Patel, Subhash; Duh, Hong Yan; Winchester, David J; Prinz, Richard A; Fogelfeld, Leon

2013-11-01

Clinicopathologic variables influence the treatment and prognosis of patients with thyroid cancer. A retrospective analysis of public hospital thyroid cancer database and the Surveillance, Epidemiology and End Results 17 database was conducted. Demographic, clinical, and pathologic data were compared across ethnic groups. Within the public hospital database, Hispanics versus non-Hispanic whites were younger and had more lymph node involvement (34% vs 17%, P < .001). Median tumor size was not statistically different across ethnic groups. Similar findings were demonstrated within the Surveillance, Epidemiology and End Results database. African Americans aged <45 years had the largest tumors but were least likely to have lymph node involvement. Asians had the most stage IV disease despite having no differences in tumor size, lymph node involvement, and capsular invasion. There is considerable variability in the clinical presentation of thyroid cancer across ethnic groups. Such disparities persist within an equal-access health care system. These findings suggest that factors beyond socioeconomics may contribute to such differences. Copyright © 2013 Elsevier Inc. All rights reserved.

Statistical process management: An essential element of quality improvement

NASA Astrophysics Data System (ADS)

Buckner, M. R.

Successful quality improvement requires a balanced program involving the three elements that control quality: organization, people and technology. The focus of the SPC/SPM User's Group is to advance the technology component of Total Quality by networking within the Group and by providing an outreach within Westinghouse to foster the appropriate use of statistic techniques to achieve Total Quality. SPM encompasses the disciplines by which a process is measured against its intrinsic design capability, in the face of measurement noise and other obscuring variability. SPM tools facilitate decisions about the process that generated the data. SPM deals typically with manufacturing processes, but with some flexibility of definition and technique it accommodates many administrative processes as well. The techniques of SPM are those of Statistical Process Control, Statistical Quality Control, Measurement Control, and Experimental Design. In addition, techniques such as job and task analysis, and concurrent engineering are important elements of systematic planning and analysis that are needed early in the design process to ensure success. The SPC/SPM User's Group is endeavoring to achieve its objectives by sharing successes that have occurred within the member's own Westinghouse department as well as within other US and foreign industry. In addition, failures are reviewed to establish lessons learned in order to improve future applications. In broader terms, the Group is interested in making SPM the accepted way of doing business within Westinghouse.

Is there a relationship between periodontal disease and causes of death? A cross sectional study.

PubMed

Natto, Zuhair S; Aladmawy, Majdi; Alasqah, Mohammed; Papas, Athena

2015-01-01

The aim of this study was to evaluate whether there is any correlation between periodontal disease and mortality contributing factors, such as cardiovascular disease and diabetes mellitus in the elderly population. A dental evaluation was performed by a single examiner at Tufts University dental clinics for 284 patients. Periodontal assessments were performed by probing with a manual UNC-15 periodontal probe to measure pocket depth and clinical attachment level (CAL) at 6 sites. Causes of death abstracted from death certificate. Statistical analysis involved ANOVA, chi-square and multivariate logistic regression analysis. The demographics of the population sample indicated that, most were females (except for diabetes mellitus), white, married, completed 13 years of education and were 83 years old on average. CAL (continuous or dichotomous) and marital status attained statistical significance (p<0.05) in contingency table analysis (Chi-square for independence). Individuals with increased CAL were 2.16 times more likely (OR=2.16, 95% CI=1.47-3.17) to die due to CVD and this effect persisted even after control for age, marital status, gender, race, years of education (OR=2.03, 95% CI=1.35-3.03). CAL (continuous or dichotomous) was much higher among those who died due to diabetes mellitus or out of state of Massachusetts. However, these results were not statistically significant. The same pattern was observed with pocket depth (continuous or dichotomous), but these results were not statistically significant either. CAL seems to be more sensitive to chronic diseases than pocket depth. Among those conditions, cardiovascular disease has the strongest effect.

Integrating statistical and clinical research elements in intervention-related grant applications: summary from an NIMH workshop.

PubMed

Sherrill, Joel T; Sommers, David I; Nierenberg, Andrew A; Leon, Andrew C; Arndt, Stephan; Bandeen-Roche, Karen; Greenhouse, Joel; Guthrie, Donald; Normand, Sharon-Lise; Phillips, Katharine A; Shear, M Katherine; Woolson, Robert

2009-01-01

The authors summarize points for consideration generated in a National Institute of Mental Health (NIMH) workshop convened to provide an opportunity for reviewers from different disciplines-specifically clinical researchers and statisticians-to discuss how their differing and complementary expertise can be well integrated in the review of intervention-related grant applications. A 1-day workshop was convened in October, 2004. The workshop featured panel presentations on key topics followed by interactive discussion. This article summarizes the workshop and subsequent discussions, which centered on topics including weighting the statistics/data analysis elements of an application in the assessment of the application's overall merit; the level of statistical sophistication appropriate to different stages of research and for different funding mechanisms; some key considerations in the design and analysis portions of applications; appropriate statistical methods for addressing essential questions posed by an application; and the role of the statistician in the application's development, study conduct, and interpretation and dissemination of results. A number of key elements crucial to the construction and review of grant applications were identified. It was acknowledged that intervention-related studies unavoidably involve trade-offs. Reviewers are helped when applications acknowledge such trade-offs and provide good rationale for their choices. Clear linkage among the design, aims, hypotheses, and data analysis plan and avoidance of disconnections among these elements also strengthens applications. The authors identify multiple points to consider when constructing intervention-related grant applications. The points are presented here as questions and do not reflect institute policy or comprise a list of best practices, but rather represent points for consideration.

On the accuracy of the interdiffusion coefficient measurements of high-temperature binary mixtures under ISS conditions

NASA Astrophysics Data System (ADS)

Saez, Núria; Ruiz, Xavier; Pallarés, Jordi; Shevtsova, Valentina

2013-04-01

An accelerometric record from the IVIDIL experiment (ESA Columbus module) has exhaustively been studied. The analysis involved the determination of basic statistical properties as, for instance, the auto-correlation and the power spectrum (second-order statistical analyses). Also, and taking into account the shape of the associated histograms, we address another important question, the non-Gaussian nature of the time series using the bispectrum and the bicoherence of the signals. Extrapolating the above-mentioned results, a computational model of a high-temperature shear cell has been performed. A scalar indicator has been used to quantify the accuracy of the diffusion coefficient measurements in the case of binary mixtures involving photovoltaic silicon or liquid Al-Cu binary alloys. Three different initial arrangements have been considered, the so-called interdiffusion, centred thick layer and the lateral thick layer. Results allow us to conclude that, under the conditions of the present work, the diffusion coefficient is insensitive to the environmental conditions, that is to say, accelerometric disturbances and initial shear cell arrangement.

Interpretation of Statistical Data: The Importance of Affective Expressions

ERIC Educational Resources Information Center

Queiroz, Tamires; Monteiro, Carlos; Carvalho, Liliane; François, Karen

2017-01-01

In recent years, research on teaching and learning of statistics emphasized that the interpretation of data is a complex process that involves cognitive and technical aspects. However, it is a human activity that involves also contextual and affective aspects. This view is in line with research on affectivity and cognition. While the affective…

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…

Evidence, temperature, and the laws of thermodynamics.

PubMed

Vieland, Veronica J

2014-01-01

A primary purpose of statistical analysis in genetics is the measurement of the strength of evidence for or against hypotheses. As with any type of measurement, a properly calibrated measurement scale is necessary if we want to be able to meaningfully compare degrees of evidence across genetic data sets, across different types of genetic studies and/or across distinct experimental modalities. In previous papers in this journal and elsewhere, my colleagues and I have argued that geneticists ought to care about the scale on which statistical evidence is measured, and we have proposed the Kelvin temperature scale as a template for a context-independent measurement scale for statistical evidence. Moreover, we have claimed that, mathematically speaking, evidence and temperature may be one and the same thing. On first blush, this might seem absurd. Temperature is a property of systems following certain laws of nature (in particular, the 1st and 2nd Law of Thermodynamics) involving very physical quantities (e.g., energy) and processes (e.g., mechanical work). But what do the laws of thermodynamics have to do with statistical systems? Here I address that question. © 2014 S. Karger AG, Basel.

Approximations to the distribution of a test statistic in covariance structure analysis: A comprehensive study.

PubMed

Wu, Hao

2018-05-01

In structural equation modelling (SEM), a robust adjustment to the test statistic or to its reference distribution is needed when its null distribution deviates from a χ 2 distribution, which usually arises when data do not follow a multivariate normal distribution. Unfortunately, existing studies on this issue typically focus on only a few methods and neglect the majority of alternative methods in statistics. Existing simulation studies typically consider only non-normal distributions of data that either satisfy asymptotic robustness or lead to an asymptotic scaled χ 2 distribution. In this work we conduct a comprehensive study that involves both typical methods in SEM and less well-known methods from the statistics literature. We also propose the use of several novel non-normal data distributions that are qualitatively different from the non-normal distributions widely used in existing studies. We found that several under-studied methods give the best performance under specific conditions, but the Satorra-Bentler method remains the most viable method for most situations. © 2017 The British Psychological Society.

Testing homogeneity of proportion ratios for stratified correlated bilateral data in two-arm randomized clinical trials.

PubMed

Pei, Yanbo; Tian, Guo-Liang; Tang, Man-Lai

2014-11-10

Stratified data analysis is an important research topic in many biomedical studies and clinical trials. In this article, we develop five test statistics for testing the homogeneity of proportion ratios for stratified correlated bilateral binary data based on an equal correlation model assumption. Bootstrap procedures based on these test statistics are also considered. To evaluate the performance of these statistics and procedures, we conduct Monte Carlo simulations to study their empirical sizes and powers under various scenarios. Our results suggest that the procedure based on score statistic performs well generally and is highly recommended. When the sample size is large, procedures based on the commonly used weighted least square estimate and logarithmic transformation with Mantel-Haenszel estimate are recommended as they do not involve any computation of maximum likelihood estimates requiring iterative algorithms. We also derive approximate sample size formulas based on the recommended test procedures. Finally, we apply the proposed methods to analyze a multi-center randomized clinical trial for scleroderma patients. Copyright © 2014 John Wiley & Sons, Ltd.

A statistical approach to optimizing concrete mixture design.

PubMed

Ahmad, Shamsad; Alghamdi, Saeid A

2014-01-01

A step-by-step statistical approach is proposed to obtain optimum proportioning of concrete mixtures using the data obtained through a statistically planned experimental program. The utility of the proposed approach for optimizing the design of concrete mixture is illustrated considering a typical case in which trial mixtures were considered according to a full factorial experiment design involving three factors and their three levels (3(3)). A total of 27 concrete mixtures with three replicates (81 specimens) were considered by varying the levels of key factors affecting compressive strength of concrete, namely, water/cementitious materials ratio (0.38, 0.43, and 0.48), cementitious materials content (350, 375, and 400 kg/m(3)), and fine/total aggregate ratio (0.35, 0.40, and 0.45). The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for compressive strength in terms of the three design factors considered in this study. The developed statistical model was used to show how optimization of concrete mixtures can be carried out with different possible options.

A Statistical Approach to Optimizing Concrete Mixture Design

PubMed Central

Alghamdi, Saeid A.

2014-01-01

A step-by-step statistical approach is proposed to obtain optimum proportioning of concrete mixtures using the data obtained through a statistically planned experimental program. The utility of the proposed approach for optimizing the design of concrete mixture is illustrated considering a typical case in which trial mixtures were considered according to a full factorial experiment design involving three factors and their three levels (33). A total of 27 concrete mixtures with three replicates (81 specimens) were considered by varying the levels of key factors affecting compressive strength of concrete, namely, water/cementitious materials ratio (0.38, 0.43, and 0.48), cementitious materials content (350, 375, and 400 kg/m3), and fine/total aggregate ratio (0.35, 0.40, and 0.45). The experimental data were utilized to carry out analysis of variance (ANOVA) and to develop a polynomial regression model for compressive strength in terms of the three design factors considered in this study. The developed statistical model was used to show how optimization of concrete mixtures can be carried out with different possible options. PMID:24688405

A Generalized Approach for the Interpretation of Geophysical Well Logs in Ground-Water Studies - Theory and Application

USGS Publications Warehouse

Paillet, Frederick L.; Crowder, R.E.

1996-01-01

Quantitative analysis of geophysical logs in ground-water studies often involves at least as broad a range of applications and variation in lithology as is typically encountered in petroleum exploration, making such logs difficult to calibrate and complicating inversion problem formulation. At the same time, data inversion and analysis depend on inversion model formulation and refinement, so that log interpretation cannot be deferred to a geophysical log specialist unless active involvement with interpretation can be maintained by such an expert over the lifetime of the project. We propose a generalized log-interpretation procedure designed to guide hydrogeologists in the interpretation of geophysical logs, and in the integration of log data into ground-water models that may be systematically refined and improved in an iterative way. The procedure is designed to maximize the effective use of three primary contributions from geophysical logs: (1) The continuous depth scale of the measurements along the well bore; (2) The in situ measurement of lithologic properties and the correlation with hydraulic properties of the formations over a finite sample volume; and (3) Multiple independent measurements that can potentially be inverted for multiple physical or hydraulic properties of interest. The approach is formulated in the context of geophysical inversion theory, and is designed to be interfaced with surface geophysical soundings and conventional hydraulic testing. The step-by-step procedures given in our generalized interpretation and inversion technique are based on both qualitative analysis designed to assist formulation of the interpretation model, and quantitative analysis used to assign numerical values to model parameters. The approach bases a decision as to whether quantitative inversion is statistically warranted by formulating an over-determined inversion. If no such inversion is consistent with the inversion model, quantitative inversion is judged not possible with the given data set. Additional statistical criteria such as the statistical significance of regressions are used to guide the subsequent calibration of geophysical data in terms of hydraulic variables in those situations where quantitative data inversion is considered appropriate.

Improved sample preparation of glyphosate and methylphosphonic acid by EPA method 6800A and time-of-flight mass spectrometry using novel solid-phase extraction.

PubMed

Wagner, Rebecca; Wetzel, Stephanie J; Kern, John; Kingston, H M Skip

2012-02-01

The employment of chemical weapons by rogue states and/or terrorist organizations is an ongoing concern in the United States. The quantitative analysis of nerve agents must be rapid and reliable for use in the private and public sectors. Current methods describe a tedious and time-consuming derivatization for gas chromatography-mass spectrometry and liquid chromatography in tandem with mass spectrometry. Two solid-phase extraction (SPE) techniques for the analysis of glyphosate and methylphosphonic acid are described with the utilization of isotopically enriched analytes for quantitation via atmospheric pressure chemical ionization-quadrupole time-of-flight mass spectrometry (APCI-Q-TOF-MS) that does not require derivatization. Solid-phase extraction-isotope dilution mass spectrometry (SPE-IDMS) involves pre-equilibration of a naturally occurring sample with an isotopically enriched standard. The second extraction method, i-Spike, involves loading an isotopically enriched standard onto the SPE column before the naturally occurring sample. The sample and the spike are then co-eluted from the column enabling precise and accurate quantitation via IDMS. The SPE methods in conjunction with IDMS eliminate concerns of incomplete elution, matrix and sorbent effects, and MS drift. For accurate quantitation with IDMS, the isotopic contribution of all atoms in the target molecule must be statistically taken into account. This paper describes two newly developed sample preparation techniques for the analysis of nerve agent surrogates in drinking water as well as statistical probability analysis for proper molecular IDMS. The methods described in this paper demonstrate accurate molecular IDMS using APCI-Q-TOF-MS with limits of quantitation as low as 0.400 mg/kg for glyphosate and 0.031 mg/kg for methylphosphonic acid. Copyright © 2012 John Wiley & Sons, Ltd.

Daily remote monitoring of implantable cardioverter-defibrillators: insights from the pooled patient-level data from three randomized controlled trials (IN-TIME, ECOST, TRUST).

PubMed

Hindricks, Gerhard; Varma, Niraj; Kacet, Salem; Lewalter, Thorsten; Søgaard, Peter; Guédon-Moreau, Laurence; Proff, Jochen; Gerds, Thomas A; Anker, Stefan D; Torp-Pedersen, Christian

2017-06-07

Remote monitoring of implantable cardioverter-defibrillators may improve clinical outcome. A recent meta-analysis of three randomized controlled trials (TRUST, ECOST, IN-TIME) using a specific remote monitoring system with daily transmissions [Biotronik Home Monitoring (HM)] demonstrated improved survival. We performed a patient-level analysis to verify this result with appropriate time-to-event statistics and to investigate further clinical endpoints. Individual data of the TRUST, ECOST, and IN-TIME patients were pooled to calculate absolute risks of endpoints at 1-year follow-up for HM vs. conventional follow-up. All-cause mortality analysis involved all three trials (2405 patients). Other endpoints involved two trials, ECOST and IN-TIME (1078 patients), in which an independent blinded endpoint committee adjudicated the underlying causes of hospitalizations and deaths. The absolute risk of death at 1 year was reduced by 1.9% in the HM group (95% CI: 0.1-3.8%; P = 0.037), equivalent to a risk ratio of 0.62. Also the combined endpoint of all-cause mortality or hospitalization for worsening heart failure (WHF) was significantly reduced (by 5.6%; P = 0.007; risk ratio 0.64). The composite endpoint of all-cause mortality or cardiovascular (CV) hospitalization tended to be reduced by a similar degree (4.1%; P = 0.13; risk ratio 0.85) but without statistical significance. In a pooled analysis of the three trials, HM reduced all-cause mortality and the composite endpoint of all-cause mortality or WHF hospitalization. The similar magnitudes of absolute risk reductions for WHF and CV endpoints suggest that the benefit of HM is driven by the prevention of heart failure exacerbation.

Teachers' Training and Involvement in School Health Programme in Oyo State, Southwest Nigeria.

PubMed

Adebayo, A M; Makinde, G I; Omode, P K

2018-02-01

School Health Programme (SHP) currently lacks effective implementation in Nigeria. Lack of training/orientation of teachers in the programme may have contributed to this. Developing an appropriate training intervention may require prior situation analysis to know teachers' current level of training and involvement in the programme, as there is paucity of information on such study in Oyo State. Thus, this study was carried out to assess primary school teachers' training and involvement in the SHP in Oyo state, Nigeria. A descriptive cross-sectional study was conducted using a 2-stage cluster sampling method to select 2 out of the 33 Local Government Areas (LGAs) in Oyo State. A semi-structured self-administered questionnaire was used to obtain information on respondents' characteristics and previous training and involvement in the SHP. The major variable for assessing teachers' involvement in the SHP was "ever been involved in health inspection of pupils". Level of involvement was categorized into "never, "once", "occasionally", "frequently", and "very regularly". These options were further re-categorized into "never", "infrequently" (once and occasionally) and "frequently" (frequently and very regularly) for the purpose of inferential statistics. Data were analyzed using descriptive statistics and Chi-square test at p=0.05. A total of 811 respondents participated in the study. Twenty-eight percent of the respondents reported previous training in the SHP out of whom 44.7% received the training on-the-job. Forty-seven percent were regularly involved in health inspection of pupils. Teachers who taught health education (92.3%) were involved in health inspection of pupils compared with counterparts who did not (74.4%) (p<0.001). Similarly, 85.3% of teachers trained on-the-job were frequently involved in the SHP compared with 73.6% of those trained during undergraduate years (p=0.026). Training and involvement of public primary school teachers in the SHP in Oyo State were suboptimal. Efforts at building the capacity of teachers through on-the-job training in SHP may be necessary to improving the current level of implementation in the State.

Ethics in Statistics

ERIC Educational Resources Information Center

Lenard, Christopher; McCarthy, Sally; Mills, Terence

2014-01-01

There are many different aspects of statistics. Statistics involves mathematics, computing, and applications to almost every field of endeavour. Each aspect provides an opportunity to spark someone's interest in the subject. In this paper we discuss some ethical aspects of statistics, and describe how an introduction to ethics has been…

Photographic and photometric enhancement of Lunar Orbiter products, projects A, B and C

NASA Technical Reports Server (NTRS)

1972-01-01

A detailed discussion is presented of the framelet joining, photometric data improvement, and statistical error analysis. The Lunar Orbiter film handling system, readout system, and the digitization are described, along with the technique of joining adjacent framelets by a using a digital computer. Time and cost estimates are given. The problems and techniques involved in improving the digitized data are discussed. It was found that spectacular improvements are possible. Program documentations are included.

Neural network representation and learning of mappings and their derivatives

NASA Technical Reports Server (NTRS)

White, Halbert; Hornik, Kurt; Stinchcombe, Maxwell; Gallant, A. Ronald

1991-01-01

Discussed here are recent theorems proving that artificial neural networks are capable of approximating an arbitrary mapping and its derivatives as accurately as desired. This fact forms the basis for further results establishing the learnability of the desired approximations, using results from non-parametric statistics. These results have potential applications in robotics, chaotic dynamics, control, and sensitivity analysis. An example involving learning the transfer function and its derivatives for a chaotic map is discussed.

Statistical Analysis of Physiological Signals

NASA Astrophysics Data System (ADS)

Ruiz, María G.; Pérez, Leticia

2003-07-01

In spite of two hundred years of clinical practice, Homeopathy still lacks of scientific basis. Its fundamental laws, similia principle and the activity of the denominated ultra-high dilutions are controversial issues that do not fit into the mainstream medicine or current physical-chemistry field as well. Aside its clinical efficacy, the identification of physical - chemistry parameters, as markers of the homeopathic effect, would allow to construct mathematic models [1], which in turn, could provide clues regarding the involved mechanism.

A strategy for involving on-campus and distance students in a nursing research course.

PubMed

Shuster, George F; Learn, Cheryl Demerth; Duncan, Robert

2003-01-01

Teaching research at the undergraduate level can be a challenge. This is particularly true for distance education courses, in which students often feel isolated from each other and from faculty. Faculty teaching on-campus and distance education research courses designed a student research project and a method for bringing distance and on-campus students together to present their research findings. By actively engaging students in the research process and providing an on-campus research day for the presentation of student posters (Year 1) and research papers (Year 2), course faculty were able to achieve their two goals of directly involving students in the nursing research process and creating a greater student sense of belonging within the college learning community. Statistical analysis of an evaluation survey among on-site and off-site registered nurse to bachelor of science in nursing students indicated both groups ranked the Year 1 poster research day as good to very good. Students attending the Year 2 research day, where they presented papers, ranked the day as good. Statistical analysis indicated a significant difference between the two research days, with a clear student preference for posters. Students valued their active participation in the research process and the opportunity to get together and present their work. However, students clearly preferred a poster presentation format to presenting their findings as a research paper.

Elephantiasis nostras verrucosa: an institutional analysis of 21 cases.

PubMed

Dean, Steven M; Zirwas, Matthew J; Horst, Anthony Vander

2011-06-01

Previous reports regarding elephantiasis nostras verrucosa (ENV) have been typically limited to 3 or fewer patients. We sought to statistically ascertain what demographic features and clinical variables are associated with ENV. A retrospective chart review of 21 patients with ENV from 2006 to 2008 was performed and statistically analyzed. All 21 patients were obese (morbid obesity in 91%) with a mean body mass index of 55.8. The average maximal calf circumference was 63.7 cm. Concurrent chronic venous insufficiency was identified in 15 patients (71%). ENV was predominantly bilateral (86%) and typically involved the calves (81%). Proximal cutaneous involvement (thighs 19%/abdomen 9.5%) was less common. Eighteen (86%) related a history of lower extremity cellulitis/lymphangitis and/or manifested soft-tissue infection upon presentation. Multisegmental ENV was statistically more likely in setting of a higher body mass index (P = .02), larger calf circumference (P = .01), multiple lymphedema risk factors (P = .05), ulcerations (P < .001), and nodules (P < .001). Calf circumference was significantly and proportionally linked to developing lower extremity ulcerations (P = .02). Ulcerations and nodules were significantly prone to occur concomitantly (P = .05). Nodules appeared more likely to exist in the presence of a higher body mass index (P = .06) and multiple lymphedema risk factors (P = .06). The statistical conclusions were potentially inhibited by the relatively small cohort. The study was retrospective. Our data confirm the association among obesity, soft-tissue infection, and ENV. Chronic venous insufficiency may be an underappreciated risk factor in the genesis of ENV. Copyright © 2010 American Academy of Dermatology, Inc. Published by Mosby, Inc. All rights reserved.

Systematic review of restraint interventions for challenging behaviour among persons with intellectual disabilities: focus on effectiveness in single-case experiments.

PubMed

Heyvaert, Mieke; Saenen, Lore; Maes, Bea; Onghena, Patrick

2014-11-01

This article is the first in a two-part series: we focus on the effectiveness of restraint interventions (RIs) for reducing challenging behaviour (CB) among persons with intellectual disabilities in this first article. In the second article, we focus on experiences with RIs for CB among people with intellectual disabilities. A mixed-methods research synthesis involving statistical meta-analysis and qualitative meta-synthesis techniques was applied to synthesize 76 retrieved articles. This first article reports on the meta-analysis of 59 single-case experiments (SCEs) on effectiveness of RIs for CB among people with intellectual disabilities. The RIs reported on in the SCEs were on average highly effective in reducing CB for people with intellectual disabilities, and this reduction in CB was statistically significant. However, the effects vary significantly over the included participants, and the published data and reported outcomes are rather unrepresentative of the everyday use of RIs among persons with intellectual disabilities. © 2014 John Wiley & Sons Ltd.

Convolutionless Nakajima-Zwanzig equations for stochastic analysis in nonlinear dynamical systems.

PubMed

Venturi, D; Karniadakis, G E

2014-06-08

Determining the statistical properties of stochastic nonlinear systems is of major interest across many disciplines. Currently, there are no general efficient methods to deal with this challenging problem that involves high dimensionality, low regularity and random frequencies. We propose a framework for stochastic analysis in nonlinear dynamical systems based on goal-oriented probability density function (PDF) methods. The key idea stems from techniques of irreversible statistical mechanics, and it relies on deriving evolution equations for the PDF of quantities of interest, e.g. functionals of the solution to systems of stochastic ordinary and partial differential equations. Such quantities could be low-dimensional objects in infinite dimensional phase spaces. We develop the goal-oriented PDF method in the context of the time-convolutionless Nakajima-Zwanzig-Mori formalism. We address the question of approximation of reduced-order density equations by multi-level coarse graining, perturbation series and operator cumulant resummation. Numerical examples are presented for stochastic resonance and stochastic advection-reaction problems.

Cracking the Neural Code for Sensory Perception by Combining Statistics, Intervention, and Behavior.

PubMed

Panzeri, Stefano; Harvey, Christopher D; Piasini, Eugenio; Latham, Peter E; Fellin, Tommaso

2017-02-08

The two basic processes underlying perceptual decisions-how neural responses encode stimuli, and how they inform behavioral choices-have mainly been studied separately. Thus, although many spatiotemporal features of neural population activity, or "neural codes," have been shown to carry sensory information, it is often unknown whether the brain uses these features for perception. To address this issue, we propose a new framework centered on redefining the neural code as the neural features that carry sensory information used by the animal to drive appropriate behavior; that is, the features that have an intersection between sensory and choice information. We show how this framework leads to a new statistical analysis of neural activity recorded during behavior that can identify such neural codes, and we discuss how to combine intersection-based analysis of neural recordings with intervention on neural activity to determine definitively whether specific neural activity features are involved in a task. Copyright © 2017 Elsevier Inc. All rights reserved.

Carbohydrate Structure Database: tools for statistical analysis of bacterial, plant and fungal glycomes

PubMed Central

Egorova, K.S.; Kondakova, A.N.; Toukach, Ph.V.

2015-01-01

Carbohydrates are biological blocks participating in diverse and crucial processes both at cellular and organism levels. They protect individual cells, establish intracellular interactions, take part in the immune reaction and participate in many other processes. Glycosylation is considered as one of the most important modifications of proteins and other biologically active molecules. Still, the data on the enzymatic machinery involved in the carbohydrate synthesis and processing are scattered, and the advance on its study is hindered by the vast bulk of accumulated genetic information not supported by any experimental evidences for functions of proteins that are encoded by these genes. In this article, we present novel instruments for statistical analysis of glycomes in taxa. These tools may be helpful for investigating carbohydrate-related enzymatic activities in various groups of organisms and for comparison of their carbohydrate content. The instruments are developed on the Carbohydrate Structure Database (CSDB) platform and are available freely on the CSDB web-site at http://csdb.glycoscience.ru. Database URL: http://csdb.glycoscience.ru PMID:26337239

Effective Thermal Inactivation of the Spores of Bacillus cereus Biofilms Using Microwave.

PubMed

Park, Hyong Seok; Yang, Jungwoo; Choi, Hee Jung; Kim, Kyoung Heon

2017-07-28

Microwave sterilization was performed to inactivate the spores of biofilms of Bacillus cereus involved in foodborne illness. The sterilization conditions, such as the amount of water and the operating temperature and treatment time, were optimized using statistical analysis based on 15 runs of experimental results designed by the Box-Behnken method. Statistical analysis showed that the optimal conditions for the inactivation of B. cereus biofilms were 14 ml of water, 108°C of temperature, and 15 min of treatment time. Interestingly, response surface plots showed that the amount of water is the most important factor for microwave sterilization under the present conditions. Complete inactivation by microwaves was achieved in 5 min, and the inactivation efficiency by microwave was obviously higher than that by conventional steam autoclave. Finally, confocal laser scanning microscopy images showed that the principal effect of microwave treatment was cell membrane disruption. Thus, this study can contribute to the development of a process to control food-associated pathogens.

Convolutionless Nakajima–Zwanzig equations for stochastic analysis in nonlinear dynamical systems

PubMed Central

Venturi, D.; Karniadakis, G. E.

2014-01-01

Determining the statistical properties of stochastic nonlinear systems is of major interest across many disciplines. Currently, there are no general efficient methods to deal with this challenging problem that involves high dimensionality, low regularity and random frequencies. We propose a framework for stochastic analysis in nonlinear dynamical systems based on goal-oriented probability density function (PDF) methods. The key idea stems from techniques of irreversible statistical mechanics, and it relies on deriving evolution equations for the PDF of quantities of interest, e.g. functionals of the solution to systems of stochastic ordinary and partial differential equations. Such quantities could be low-dimensional objects in infinite dimensional phase spaces. We develop the goal-oriented PDF method in the context of the time-convolutionless Nakajima–Zwanzig–Mori formalism. We address the question of approximation of reduced-order density equations by multi-level coarse graining, perturbation series and operator cumulant resummation. Numerical examples are presented for stochastic resonance and stochastic advection–reaction problems. PMID:24910519

Revealing time bunching effect in single-molecule enzyme conformational dynamics.

PubMed

Lu, H Peter

2011-04-21

In this perspective, we focus our discussion on how the single-molecule spectroscopy and statistical analysis are able to reveal enzyme hidden properties, taking the study of T4 lysozyme as an example. Protein conformational fluctuations and dynamics play a crucial role in biomolecular functions, such as in enzymatic reactions. Single-molecule spectroscopy is a powerful approach to analyze protein conformational dynamics under physiological conditions, providing dynamic perspectives on a molecular-level understanding of protein structure-function mechanisms. Using single-molecule fluorescence spectroscopy, we have probed T4 lysozyme conformational motions under the hydrolysis reaction of a polysaccharide of E. coli B cell walls by monitoring the fluorescence resonant energy transfer (FRET) between a donor-acceptor probe pair tethered to T4 lysozyme domains involving open-close hinge-bending motions. Based on the single-molecule spectroscopic results, molecular dynamics simulation, a random walk model analysis, and a novel 2D statistical correlation analysis, we have revealed a time bunching effect in protein conformational motion dynamics that is critical to enzymatic functions. Bunching effect implies that conformational motion times tend to bunch in a finite and narrow time window. We show that convoluted multiple Poisson rate processes give rise to the bunching effect in the enzymatic reaction dynamics. Evidently, the bunching effect is likely common in protein conformational dynamics involving in conformation-gated protein functions. In this perspective, we will also discuss a new approach of 2D regional correlation analysis capable of analyzing fluctuation dynamics of complex multiple correlated and anti-correlated fluctuations under a non-correlated noise background. Using this new method, we are able to map out any defined segments along the fluctuation trajectories and determine whether they are correlated, anti-correlated, or non-correlated; after which, a cross correlation analysis can be applied for each specific segment to obtain a detailed fluctuation dynamics analysis.

High-throughput process development: I. Process chromatography.

PubMed

Rathore, Anurag S; Bhambure, Rahul

2014-01-01

Chromatographic separation serves as "a workhorse" for downstream process development and plays a key role in removal of product-related, host cell-related, and process-related impurities. Complex and poorly characterized raw materials and feed material, low feed concentration, product instability, and poor mechanistic understanding of the processes are some of the critical challenges that are faced during development of a chromatographic step. Traditional process development is performed as trial-and-error-based evaluation and often leads to a suboptimal process. High-throughput process development (HTPD) platform involves an integration of miniaturization, automation, and parallelization and provides a systematic approach for time- and resource-efficient chromatography process development. Creation of such platforms requires integration of mechanistic knowledge of the process with various statistical tools for data analysis. The relevance of such a platform is high in view of the constraints with respect to time and resources that the biopharma industry faces today. This protocol describes the steps involved in performing HTPD of process chromatography step. It described operation of a commercially available device (PreDictor™ plates from GE Healthcare). This device is available in 96-well format with 2 or 6 μL well size. We also discuss the challenges that one faces when performing such experiments as well as possible solutions to alleviate them. Besides describing the operation of the device, the protocol also presents an approach for statistical analysis of the data that is gathered from such a platform. A case study involving use of the protocol for examining ion-exchange chromatography of granulocyte colony-stimulating factor (GCSF), a therapeutic product, is briefly discussed. This is intended to demonstrate the usefulness of this protocol in generating data that is representative of the data obtained at the traditional lab scale. The agreement in the data is indeed very significant (regression coefficient 0.93). We think that this protocol will be of significant value to those involved in performing high-throughput process development of process chromatography.

Stakeholders' views of the introduction of assistive technology in the classroom: How family-centred is Australian practice for students with cerebral palsy?

PubMed

Karlsson, P; Johnston, C; Barker, K

2017-07-01

With family-centred care widely recognized as a cornerstone for effective assistive technology service provision, the current study was undertaken to investigate to what extent such approaches were used by schools when assistive technology assessments and implementation occurred in the classroom. In this cross-sectional study, we compare survey results from parents (n = 76), school staff (n = 33) and allied health professionals (n = 65) with experience in the use of high-tech assistive technology. Demographic characteristics and the stakeholders' perceived helpfulness and frequency attending assessment and set-up sessions were captured. To evaluate how family-centred the assistive technology services were perceived to be, the parents filled out the Measure of Processes of Care for Caregivers, and the professionals completed the Measure of Processes of Care for Service Providers. Descriptive statistics and one-way analysis of variance were used to conduct the data analysis. Findings show that parents are more involved during the assessment stage than during the implementation and that classroom teachers are often not involved in the initial stage. Speech pathologists in particular are seen to be to a great extent helpful when implementing assistive technology in the classroom. This study found that family-centred service is not yet fully achieved in schools despite being endorsed in early intervention and disability services for over 20 years. No statistically significant differences were found with respect to school staff and allied health professionals' roles, their years of experience working with students with cerebral palsy and the scales in the Measure of Processes of Care for Service Providers. To enhance the way technology is matched to the student and successfully implemented, classroom teachers need to be fully involved in the whole assistive technology process. The findings also point to the significance of parents' involvement, with the support of allied health professionals, in the process of selecting and implementing assistive technology in the classroom. © 2017 John Wiley & Sons Ltd.

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.

Multivariate Statistical Analysis of Water Quality data in Indian River Lagoon, Florida

NASA Astrophysics Data System (ADS)

Sayemuzzaman, M.; Ye, M.

2015-12-01

The Indian River Lagoon, is part of the longest barrier island complex in the United States, is a region of particular concern to the environmental scientist because of the rapid rate of human development throughout the region and the geographical position in between the colder temperate zone and warmer sub-tropical zone. Thus, the surface water quality analysis in this region always brings the newer information. In this present study, multivariate statistical procedures were applied to analyze the spatial and temporal water quality in the Indian River Lagoon over the period 1998-2013. Twelve parameters have been analyzed on twelve key water monitoring stations in and beside the lagoon on monthly datasets (total of 27,648 observations). The dataset was treated using cluster analysis (CA), principle component analysis (PCA) and non-parametric trend analysis. The CA was used to cluster twelve monitoring stations into four groups, with stations on the similar surrounding characteristics being in the same group. The PCA was then applied to the similar groups to find the important water quality parameters. The principal components (PCs), PC1 to PC5 was considered based on the explained cumulative variances 75% to 85% in each cluster groups. Nutrient species (phosphorus and nitrogen), salinity, specific conductivity and erosion factors (TSS, Turbidity) were major variables involved in the construction of the PCs. Statistical significant positive or negative trends and the abrupt trend shift were detected applying Mann-Kendall trend test and Sequential Mann-Kendall (SQMK), for each individual stations for the important water quality parameters. Land use land cover change pattern, local anthropogenic activities and extreme climate such as drought might be associated with these trends. This study presents the multivariate statistical assessment in order to get better information about the quality of surface water. Thus, effective pollution control/management of the surface waters can be undertaken.

Gene fusion analysis in the battle against the African endemic sleeping sickness.

PubMed

Trimpalis, Philip; Koumandou, Vassiliki Lila; Pliakou, Evangelia; Anagnou, Nicholas P; Kossida, Sophia

2013-01-01

The protozoan Trypanosoma brucei causes African Trypanosomiasis or sleeping sickness in humans, which can be lethal if untreated. Most available pharmacological treatments for the disease have severe side-effects. The purpose of this analysis was to detect novel protein-protein interactions (PPIs), vital for the parasite, which could lead to the development of drugs against this disease to block the specific interactions. In this work, the Domain Fusion Analysis (Rosetta Stone method) was used to identify novel PPIs, by comparing T. brucei to 19 organisms covering all major lineages of the tree of life. Overall, 49 possible protein-protein interactions were detected, and classified based on (a) statistical significance (BLAST e-value, domain length etc.), (b) their involvement in crucial metabolic pathways, and (c) their evolutionary history, particularly focusing on whether a protein pair is split in T. brucei and fused in the human host. We also evaluated fusion events including hypothetical proteins, and suggest a possible molecular function or involvement in a certain biological process. This work has produced valuable results which could be further studied through structural biology or other experimental approaches so as to validate the protein-protein interactions proposed here. The evolutionary analysis of the proteins involved showed that, gene fusion or gene fission events can happen in all organisms, while some protein domains are more prone to fusion and fission events and present complex evolutionary patterns.

Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses

PubMed Central

Liu, Ruijie; Holik, Aliaksei Z.; Su, Shian; Jansz, Natasha; Chen, Kelan; Leong, Huei San; Blewitt, Marnie E.; Asselin-Labat, Marie-Liesse; Smyth, Gordon K.; Ritchie, Matthew E.

2015-01-01

Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean–variance relationship of the log-counts-per-million using ‘voom’. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source ‘limma’ package. PMID:25925576

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Ghent, D.; Rayner, N. A.

2017-12-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-2018, https://www.eustaceproject.eu) we have developed an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. This includes developing new "Big Data" analysis methods as the data volumes involved are considerable. We will present recent progress along this road in the EUSTACE project, i.e.: • identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; • estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; • using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

Use of a statistical model of the whole femur in a large scale, multi-model study of femoral neck fracture risk.

PubMed

Bryan, Rebecca; Nair, Prasanth B; Taylor, Mark

2009-09-18

Interpatient variability is often overlooked in orthopaedic computational studies due to the substantial challenges involved in sourcing and generating large numbers of bone models. A statistical model of the whole femur incorporating both geometric and material property variation was developed as a potential solution to this problem. The statistical model was constructed using principal component analysis, applied to 21 individual computer tomography scans. To test the ability of the statistical model to generate realistic, unique, finite element (FE) femur models it was used as a source of 1000 femurs to drive a study on femoral neck fracture risk. The study simulated the impact of an oblique fall to the side, a scenario known to account for a large proportion of hip fractures in the elderly and have a lower fracture load than alternative loading approaches. FE model generation, application of subject specific loading and boundary conditions, FE processing and post processing of the solutions were completed automatically. The generated models were within the bounds of the training data used to create the statistical model with a high mesh quality, able to be used directly by the FE solver without remeshing. The results indicated that 28 of the 1000 femurs were at highest risk of fracture. Closer analysis revealed the percentage of cortical bone in the proximal femur to be a crucial differentiator between the failed and non-failed groups. The likely fracture location was indicated to be intertrochantic. Comparison to previous computational, clinical and experimental work revealed support for these findings.

Introductory Statistics Students' Conceptual Understanding of Study Design and Conclusions

NASA Astrophysics Data System (ADS)

Fry, Elizabeth Brondos

Recommended learning goals for students in introductory statistics courses include the ability to recognize and explain the key role of randomness in designing studies and in drawing conclusions from those studies involving generalizations to a population or causal claims (GAISE College Report ASA Revision Committee, 2016). The purpose of this study was to explore introductory statistics students' understanding of the distinct roles that random sampling and random assignment play in study design and the conclusions that can be made from each. A study design unit lasting two and a half weeks was designed and implemented in four sections of an undergraduate introductory statistics course based on modeling and simulation. The research question that this study attempted to answer is: How does introductory statistics students' conceptual understanding of study design and conclusions (in particular, unbiased estimation and establishing causation) change after participating in a learning intervention designed to promote conceptual change in these areas? In order to answer this research question, a forced-choice assessment called the Inferences from Design Assessment (IDEA) was developed as a pretest and posttest, along with two open-ended assignments, a group quiz and a lab assignment. Quantitative analysis of IDEA results and qualitative analysis of the group quiz and lab assignment revealed that overall, students' mastery of study design concepts significantly increased after the unit, and the great majority of students successfully made the appropriate connections between random sampling and generalization, and between random assignment and causal claims. However, a small, but noticeable portion of students continued to demonstrate misunderstandings, such as confusion between random sampling and random assignment.

Seeking a Balance between the Statistical and Scientific Elements in Psychometrics

ERIC Educational Resources Information Center

Wilson, Mark

2013-01-01

In this paper, I will review some aspects of psychometric projects that I have been involved in, emphasizing the nature of the work of the psychometricians involved, especially the balance between the statistical and scientific elements of that work. The intent is to seek to understand where psychometrics, as a discipline, has been and where it…

MicroRNA Expression Analysis in Serum of Patients with Congenital Hemochromatosis and Age-Related Macular Degeneration (AMD)

PubMed Central

Szemraj, Maciej; Oszajca, Katarzyna; Szemraj, Janusz; Jurowski, Piotr

2017-01-01

Background Congenital hemochromatosis is a disorder caused by mutations of genes involved in iron metabolism, leading to increased levels of iron concentration in tissues and serum. High concentrations of iron can lead to the development of AMD. The aim of this study was to analyze circulating miRNAs in the serum of congenital hemochromatosis patients with AMD and their correlation with the expression of genes involved in iron metabolism. Material/Methods Peripheral blood monolayer cells and serum were obtained from patients with congenital hemochromatosis, congenital hemochromatosis and AMD, AMD patients without congenital hemochromatosis, and healthy controls. Serum miRNAs expressions were analyzed by RT-PCR (qRT-PCR) using TaqMan MicroRNA probes, and proteins levels were measured by ELSA kits. Gene polymorphisms in TF and TFRC genes were determined using the TaqMan discrimination assay. Results Statistical analysis of the miRNAs expressions selected for further study the miR-31, miR-133a, miR-141, miR-145, miR-149, and miR-182, which are involved in the posttranscriptional expression of iron-related genes: TF, TFRI, DMT1, FTL, and FPN1. It was discovered that the observed changes in the expressions of the miRNAs was correlated with the level of protein in the serum of the analyzed genes. There were no statistically significant differences in the distribution of genotype and allele frequencies in TF and TFRC genes between analyzed groups of patients. Conclusions The differences studied in the miRNA serum profile, in conjunction with the changes in the analyzed protein levels, may be useful in the early detection of congenital hemochromatosis in patients who may develop AMD disease. PMID:28827515

Characteristics of worker accidents on NYSDOT construction projects.

PubMed

Mohan, Satish; Zech, Wesley C

2005-01-01

This paper aims at providing cost-effective safety measures to protect construction workers in highway work zones, based on real data. Two types of accidents that occur in work zones were: (a) construction work area accidents, and (b) traffic accidents involving construction worker(s). A detailed analysis of work zone accidents involving 36 fatalities and 3,055 severe injuries to construction workers on New York State Department of Transportation (NYSDOT) construction projects from 1990 to 2001 established that five accident types: (a) Struck/Pinned by Large Equipment, (b) Trip or Fall (elevated), (c) Contact w/Electrical or Gas Utility, (d) Struck-by Moving/Falling Load, and (e) Crane/Lift Device Failure accounted for nearly 96% of the fatal accidents, nearly 63% of the hospital-level injury accidents, and nearly 91% of the total costs. These construction work area accidents had a total cost of $133.8 million. Traffic accidents that involve contractors' employees were also examined. Statistical analyses of the traffic accidents established that five traffic accident types: (a) Work Space Intrusion, (b) Worker Struck-by Vehicle Inside Work Space, (c) Flagger Struck-by Vehicle, (d) Worker Struck-by Vehicle Entering/Exiting Work Space, and (e) Construction Equipment Struck-by Vehicle Inside Work Space accounted for nearly 86% of the fatal, nearly 70% of the hospital-level injury and minor injury traffic accidents, and $45.4 million (79.4%) of the total traffic accident costs. The results of this paper provide real statistics on construction worker related accidents reported on construction work zones. Potential preventions based on real statistics have also been suggested. The ranking of accident types, both within the work area as well as in traffic, will guide the heavy highway contractor and owner agencies in identifying the most cost effective safety preventions.

Comparative Evaluation of Cone-beam Computed Tomography versus Direct Surgical Measurements in the Diagnosis of Mandibular Molar Furcation Involvement

PubMed Central

Padmanabhan, Shyam; Dommy, Ahila; Guru, Sanjeela R.; Joseph, Ajesh

2017-01-01

Aim: Periodontists frequently experience inconvenience in accurate assessment and treatment of furcation areas affected by periodontal disease. Furcation involvement (FI) most commonly affects the mandibular molars. Diagnosis of furcation-involved teeth is mainly by the assessment of probing pocket depth, clinical attachment level, furcation entrance probing, and intraoral periapical radiographs. Three-dimensional imaging has provided advantage to the clinician in assessment of bone morphology. Thus, the present study aimed to compare the diagnostic efficacy of cone-beam computed tomography (CBCT) as against direct intrasurgical measurements of furcation defects in mandibular molars. Subjects and Methods: Study population included 14 patients with 25 mandibular molar furcation sites. CBCT was performed to measure height, width, and depth of furcation defects of mandibular molars with Grade II and Grade III FI. Intrasurgical measurements of the FI were assessed during periodontal flap surgery in indicated teeth which were compared with CBCT measurements. Statistical analysis was done using paired t-test and Bland–Altman plot. Results: The CBCT versus intrasurgical furcation measurements were 2.18 ± 0.86 mm and 2.30 ± 0.89 mm for furcation height, 1.87 ± 0.52 mm and 1.84 ± 0.49 mm for furcation width, and 3.81 ± 1.37 mm and 4.05 ± 1.49 mm for furcation depth, respectively. Results showed that there was no statistical significance between the measured parameters, indicating that the two methods were statistically similar. Conclusion: Accuracy of assessment of mandibular molar FI by CBCT was comparable to that of direct surgical measurements. These findings indicate that CBCT is an excellent adjunctive diagnostic tool in periodontal treatment planning. PMID:29042732

Dependence of prevalence of contiguous pathways in proteins on structural complexity.

PubMed

Thayer, Kelly M; Galganov, Jesse C; Stein, Avram J

2017-01-01

Allostery is a regulatory mechanism in proteins where an effector molecule binds distal from an active site to modulate its activity. Allosteric signaling may occur via a continuous path of residues linking the active and allosteric sites, which has been suggested by large conformational changes evident in crystal structures. An alternate possibility is that the signal occurs in the realm of ensemble dynamics via an energy landscape change. While the latter was first proposed on theoretical grounds, increasing evidence suggests that such a control mechanism is plausible. A major difficulty for testing the two methods is the ability to definitively determine that a residue is directly involved in allosteric signal transduction. Statistical Coupling Analysis (SCA) is a method that has been successful at predicting pathways, and experimental tests involving mutagenesis or domain substitution provide the best available evidence of signaling pathways. However, ascertaining energetic pathways which need not be contiguous is far more difficult. To date, simple estimates of the statistical significance of a pathway in a protein remain to be established. The focus of this work is to estimate such benchmarks for the statistical significance of contiguous pathways for the null model of selecting residues at random. We found that when 20% of residues in proteins are randomly selected, contiguous pathways at the 6 Å cutoff level were found with success rates of 51% in PDZ, 30% in p53, and 3% in MutS. The results suggest that the significance of pathways may have system specific factors involved. Furthermore, the possible existence of false positives for contiguous pathways implies that signaling could be occurring via alternate routes including those consistent with the energetic landscape model.

Selection of Valid Reference Genes for Reverse Transcription Quantitative PCR Analysis in Heliconius numata (Lepidoptera: Nymphalidae)

PubMed Central

Chouteau, Mathieu; Whibley, Annabel; Joron, Mathieu; Llaurens, Violaine

2016-01-01

Identifying the genetic basis of adaptive variation is challenging in non-model organisms and quantitative real time PCR. is a useful tool for validating predictions regarding the expression of candidate genes. However, comparing expression levels in different conditions requires rigorous experimental design and statistical analyses. Here, we focused on the neotropical passion-vine butterflies Heliconius, non-model species studied in evolutionary biology for their adaptive variation in wing color patterns involved in mimicry and in the signaling of their toxicity to predators. We aimed at selecting stable reference genes to be used for normalization of gene expression data in RT-qPCR analyses from developing wing discs according to the minimal guidelines described in Minimum Information for publication of Quantitative Real-Time PCR Experiments (MIQE). To design internal RT-qPCR controls, we studied the stability of expression of nine candidate reference genes (actin, annexin, eF1α, FK506BP, PolyABP, PolyUBQ, RpL3, RPS3A, and tubulin) at two developmental stages (prepupal and pupal) using three widely used programs (GeNorm, NormFinder and BestKeeper). Results showed that, despite differences in statistical methods, genes RpL3, eF1α, polyABP, and annexin were stably expressed in wing discs in late larval and pupal stages of Heliconius numata. This combination of genes may be used as a reference for a reliable study of differential expression in wings for instance for genes involved in important phenotypic variation, such as wing color pattern variation. Through this example, we provide general useful technical recommendations as well as relevant statistical strategies for evolutionary biologists aiming to identify candidate-genes involved adaptive variation in non-model organisms. PMID:27271971

Could the clinical interpretability of subgroups detected using clustering methods be improved by using a novel two-stage approach?

PubMed

Kent, Peter; Stochkendahl, Mette Jensen; Christensen, Henrik Wulff; Kongsted, Alice

2015-01-01

Recognition of homogeneous subgroups of patients can usefully improve prediction of their outcomes and the targeting of treatment. There are a number of research approaches that have been used to recognise homogeneity in such subgroups and to test their implications. One approach is to use statistical clustering techniques, such as Cluster Analysis or Latent Class Analysis, to detect latent relationships between patient characteristics. Influential patient characteristics can come from diverse domains of health, such as pain, activity limitation, physical impairment, social role participation, psychological factors, biomarkers and imaging. However, such 'whole person' research may result in data-driven subgroups that are complex, difficult to interpret and challenging to recognise clinically. This paper describes a novel approach to applying statistical clustering techniques that may improve the clinical interpretability of derived subgroups and reduce sample size requirements. This approach involves clustering in two sequential stages. The first stage involves clustering within health domains and therefore requires creating as many clustering models as there are health domains in the available data. This first stage produces scoring patterns within each domain. The second stage involves clustering using the scoring patterns from each health domain (from the first stage) to identify subgroups across all domains. We illustrate this using chest pain data from the baseline presentation of 580 patients. The new two-stage clustering resulted in two subgroups that approximated the classic textbook descriptions of musculoskeletal chest pain and atypical angina chest pain. The traditional single-stage clustering resulted in five clusters that were also clinically recognisable but displayed less distinct differences. In this paper, a new approach to using clustering techniques to identify clinically useful subgroups of patients is suggested. Research designs, statistical methods and outcome metrics suitable for performing that testing are also described. This approach has potential benefits but requires broad testing, in multiple patient samples, to determine its clinical value. The usefulness of the approach is likely to be context-specific, depending on the characteristics of the available data and the research question being asked of it.

Efficacy of Pharmacist Based Diabetes Educational Interventions on Clinical Outcomes of Adults With Type 2 Diabetes Mellitus: A Network Meta-Analysis

PubMed Central

Bukhsh, Allah; Khan, Tahir M.; Lee, Shaun W. H.; Lee, Learn-Han; Chan, Kok-Gan; Goh, Bey-Hing

2018-01-01

Background: Comparative efficacy of different pharmacist based interventions on glycemic control of type 2 diabetes patients is unclear. This review aimed to evaluate and compare the efficacy of different pharmacist based interventions on clinical outcomes of type 2 diabetes patients. Methods: A systematic search was conducted across five databases from date of database inception to September 2017. All randomized clinical trials evaluating the efficacy of pharmacist based interventions on type 2 diabetes patients were included for network meta-analysis (NMA). The protocol is available with PROSPERO (CRD42017078854). Results: A total of 43 studies, involving 6259 type 2 diabetes patients, were included. NMA demonstrated that all interventions significantly lowered glycosylated hemoglobin (HbA1c) levels compared to usual care, but there was no statistical evidence from this study that one intervention was significantly better than the other for reducing HbA1c levels. Pharmacist based diabetes education plus pharmaceutical care showed maximum efficacy for reducing HbA1c levels [−0.86, 95% CI −0.983, −0.727; p < 0.001]. Pharmacist based diabetes education plus pharmaceutical care was observed to be statistically significant in lowering levels of systolic blood pressure [−4.94; 95%CI −8.65, −1.23] and triglycerides levels [−0.26, 95%CI −0.51, −0.01], as compared to the interventions which involved diabetes education by pharmacist, and for body mass index (BMI) [−0.57; 95%CI −1.25, −0.12] in comparison to diabetes education by health care team involving pharmacist as member. Conclusion: The findings of this review demonstrate that all interventions had a significantly positive effect on HbA1c, but there was no statistical evidence from this study that one intervention was significantly better than the other for achieving glycemic control.Pharmacist based diabetes education plus pharmaceutical care showed maximum efficacy on HbA1c and rest of the clinical outcomes. PMID:29692730

Location of skin lesions in Henoch-Schönlein purpura and its association with significant renal involvement.

PubMed

St John, Jessica; Vedak, Priyanka; Garza-Mayers, Anna Cristina; Hoang, Mai P; Nigwekar, Sagar U; Kroshinsky, Daniela

2018-01-01

Henoch-Schönlein purpura (HSP) is a small vessel IgA-predominant vasculitis. To describe adult patients with HSP and determine if the distribution of skin lesions (ie, purpura above the waist or purpura below the waist only), is a predictor of significant renal involvement at the time of the skin biopsy and the months following. A retrospective study on renal function from 72 adult patients with skin-biopsy proven HSP. Longitudinal renal data were analyzed after HSP diagnosis by using baseline renal function for comparison. Statistical analysis adjusted for sex, age, and baseline creatinine revealed a trend between HSP lesions only on the upper and lower extremities and long-term renal involvement (4.767, P = .067). Moreover, in another analysis adjusted for age and baseline creatinine, lesions located only on the upper and lower extremities significantly increased the odds of having long-term significant renal involvement (6.55, P = .049) in men. This retrospective study used patient information that was subject to selection bias. In patients with HSP, skin lesion distribution on the extremities might be predictive of significant long-term renal involvement and might be critical for risk stratification and development of personalized diagnostics and therapeutics. Copyright © 2017 American Academy of Dermatology, Inc. Published by Elsevier Inc. All rights reserved.

Landsat Thematic Mapper studies of land cover spatial variability related to hydrology

NASA Technical Reports Server (NTRS)

Wharton, S.; Ormsby, J.; Salomonson, V.; Mulligan, P.

1984-01-01

Past accomplishments involving remote sensing based land-cover analysis for hydrologic applications are reviewed. Ongoing research in exploiting the increased spatial, radiometric, and spectral capabilities afforded by the TM on Landsats 4 and 5 is considered. Specific studies to compare MSS and TM for urbanizing watersheds, wetlands, and floodplain mapping situations show that only a modest improvement in classification accuracy is achieved via statistical per pixel multispectral classifiers. The limitations of current approaches to multispectral classification are illustrated. The objectives, background, and progress in the development of an alternative analysis approach for defining inputs to urban hydrologic models using TM are discussed.

STS-121/Discovery: Imagery Quick-Look Briefing

NASA Technical Reports Server (NTRS)

2006-01-01

Kyle Herring (NASA Public Affairs) introduced Wayne Hale (Space Shuttle Program Manager) who stated that the imagery for the Space shuttle external tank showed the tank performed very well. Image analysis showed small pieces of foam falling off the rocket booster and external tank. There was no risk involved in these minor incidents. Statistical models were built to assist in risk analysis. The orbiter performed excellently. Wayne also provided some close-up pictures of small pieces of foam separating from the external tank during launching. He said the crew will also perform a 100% inspection of the heat shield. This flight showed great improvement over previous flights.

Development of computer-assisted instruction application for statistical data analysis android platform as learning resource

NASA Astrophysics Data System (ADS)

Hendikawati, P.; Arifudin, R.; Zahid, M. Z.

2018-03-01

This study aims to design an android Statistics Data Analysis application that can be accessed through mobile devices to making it easier for users to access. The Statistics Data Analysis application includes various topics of basic statistical along with a parametric statistics data analysis application. The output of this application system is parametric statistics data analysis that can be used for students, lecturers, and users who need the results of statistical calculations quickly and easily understood. Android application development is created using Java programming language. The server programming language uses PHP with the Code Igniter framework, and the database used MySQL. The system development methodology used is the Waterfall methodology with the stages of analysis, design, coding, testing, and implementation and system maintenance. This statistical data analysis application is expected to support statistical lecturing activities and make students easier to understand the statistical analysis of mobile devices.

Report to DHS on Summer Internship 2006

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

Beckwith, R H

2006-07-26

This summer I worked at Lawrence Livermore National Laboratory in a bioforensics collection and extraction research group under David Camp. The group is involved with researching efficiencies of various methods for collecting bioforensic evidence from crime scenes. The different methods under examination are a wipe, swab, HVAC filter and a vacuum. The vacuum is something that has particularly gone uncharacterized. My time was spent mostly on modeling and calculations work, but at the end of the summer I completed my internship with a few experiments to supplement my calculations. I had two major projects this summer. My first major projectmore » this summer involved fluid mechanics modeling of collection and extraction situations. This work examines different fluid dynamic models for the case of a micron spore attached to a fiber. The second project I was involved with was a statistical analysis of the different sampling techniques.« less

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.

Regulatory considerations in the design of comparative observational studies using propensity scores.

PubMed

Yue, Lilly Q

2012-01-01

In the evaluation of medical products, including drugs, biological products, and medical devices, comparative observational studies could play an important role when properly conducted randomized, well-controlled clinical trials are infeasible due to ethical or practical reasons. However, various biases could be introduced at every stage and into every aspect of the observational study, and consequently the interpretation of the resulting statistical inference would be of concern. While there do exist statistical techniques for addressing some of the challenging issues, often based on propensity score methodology, these statistical tools probably have not been as widely employed in prospectively designing observational studies as they should be. There are also times when they are implemented in an unscientific manner, such as performing propensity score model selection for a dataset involving outcome data in the same dataset, so that the integrity of observational study design and the interpretability of outcome analysis results could be compromised. In this paper, regulatory considerations on prospective study design using propensity scores are shared and illustrated with hypothetical examples.

GenomeGraphs: integrated genomic data visualization with R.

PubMed

Durinck, Steffen; Bullard, James; Spellman, Paul T; Dudoit, Sandrine

2009-01-06

Biological studies involve a growing number of distinct high-throughput experiments to characterize samples of interest. There is a lack of methods to visualize these different genomic datasets in a versatile manner. In addition, genomic data analysis requires integrated visualization of experimental data along with constantly changing genomic annotation and statistical analyses. We developed GenomeGraphs, as an add-on software package for the statistical programming environment R, to facilitate integrated visualization of genomic datasets. GenomeGraphs uses the biomaRt package to perform on-line annotation queries to Ensembl and translates these to gene/transcript structures in viewports of the grid graphics package. This allows genomic annotation to be plotted together with experimental data. GenomeGraphs can also be used to plot custom annotation tracks in combination with different experimental data types together in one plot using the same genomic coordinate system. GenomeGraphs is a flexible and extensible software package which can be used to visualize a multitude of genomic datasets within the statistical programming environment R.

Multivariate statistical model for 3D image segmentation with application to medical images.

PubMed

John, Nigel M; Kabuka, Mansur R; Ibrahim, Mohamed O

2003-12-01

In this article we describe a statistical model that was developed to segment brain magnetic resonance images. The statistical segmentation algorithm was applied after a pre-processing stage involving the use of a 3D anisotropic filter along with histogram equalization techniques. The segmentation algorithm makes use of prior knowledge and a probability-based multivariate model designed to semi-automate the process of segmentation. The algorithm was applied to images obtained from the Center for Morphometric Analysis at Massachusetts General Hospital as part of the Internet Brain Segmentation Repository (IBSR). The developed algorithm showed improved accuracy over the k-means, adaptive Maximum Apriori Probability (MAP), biased MAP, and other algorithms. Experimental results showing the segmentation and the results of comparisons with other algorithms are provided. Results are based on an overlap criterion against expertly segmented images from the IBSR. The algorithm produced average results of approximately 80% overlap with the expertly segmented images (compared with 85% for manual segmentation and 55% for other algorithms).

Analysis of the procedures used to evaluate suicide crime scenes in Brazil: a statistical approach to interpret reports.

PubMed

Bruni, Aline Thaís; Velho, Jesus Antonio; Ferreira, Arthur Serra Lopes; Tasso, Maria Júlia; Ferrari, Raíssa Santos; Yoshida, Ricardo Luís; Dias, Marcos Salvador; Leite, Vitor Barbanti Pereira

2014-08-01

This study uses statistical techniques to evaluate reports on suicide scenes; it utilizes 80 reports from different locations in Brazil, randomly collected from both federal and state jurisdictions. We aimed to assess a heterogeneous group of cases in order to obtain an overall perspective of the problem. We evaluated variables regarding the characteristics of the crime scene, such as the detected traces (blood, instruments and clothes) that were found and we addressed the methodology employed by the experts. A qualitative approach using basic statistics revealed a wide distribution as to how the issue was addressed in the documents. We examined a quantitative approach involving an empirical equation and we used multivariate procedures to validate the quantitative methodology proposed for this empirical equation. The methodology successfully identified the main differences in the information presented in the reports, showing that there is no standardized method of analyzing evidences. Copyright © 2014 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Efficient Blockwise Permutation Tests Preserving Exchangeability

PubMed Central

Zhou, Chunxiao; Zwilling, Chris E.; Calhoun, Vince D.; Wang, Michelle Y.

2014-01-01

In this paper, we present a new blockwise permutation test approach based on the moments of the test statistic. The method is of importance to neuroimaging studies. In order to preserve the exchangeability condition required in permutation tests, we divide the entire set of data into certain exchangeability blocks. In addition, computationally efficient moments-based permutation tests are performed by approximating the permutation distribution of the test statistic with the Pearson distribution series. This involves the calculation of the first four moments of the permutation distribution within each block and then over the entire set of data. The accuracy and efficiency of the proposed method are demonstrated through simulated experiment on the magnetic resonance imaging (MRI) brain data, specifically the multi-site voxel-based morphometry analysis from structural MRI (sMRI). PMID:25289113

New advances in the statistical parton distributions approach

NASA Astrophysics Data System (ADS)

Soffer, Jacques; Bourrely, Claude

2016-03-01

The quantum statistical parton distributions approach proposed more than one decade ago is revisited by considering a larger set of recent and accurate Deep Inelastic Scattering experimental results. It enables us to improve the description of the data by means of a new determination of the parton distributions. This global next-to-leading order QCD analysis leads to a good description of several structure functions, involving unpolarized parton distributions and helicity distributions, in terms of a rather small number of free parameters. There are many serious challenging issues. The predictions of this theoretical approach will be tested for single-jet production and charge asymmetry in W± production in p¯p and pp collisions up to LHC energies, using recent data and also for forthcoming experimental results. Presented by J. So.er at POETIC 2015

Phase error statistics of a phase-locked loop synchronized direct detection optical PPM communication system

NASA Technical Reports Server (NTRS)

Natarajan, Suresh; Gardner, C. S.

1987-01-01

Receiver timing synchronization of an optical Pulse-Position Modulation (PPM) communication system can be achieved using a phased-locked loop (PLL), provided the photodetector output is suitably processed. The magnitude of the PLL phase error is a good indicator of the timing error at the receiver decoder. The statistics of the phase error are investigated while varying several key system parameters such as PPM order, signal and background strengths, and PPL bandwidth. A practical optical communication system utilizing a laser diode transmitter and an avalanche photodiode in the receiver is described, and the sampled phase error data are presented. A linear regression analysis is applied to the data to obtain estimates of the relational constants involving the phase error variance and incident signal power.

Integrated data management for clinical studies: automatic transformation of data models with semantic annotations for principal investigators, data managers and statisticians.

PubMed

Dugas, Martin; Dugas-Breit, Susanne

2014-01-01

Design, execution and analysis of clinical studies involves several stakeholders with different professional backgrounds. Typically, principle investigators are familiar with standard office tools, data managers apply electronic data capture (EDC) systems and statisticians work with statistics software. Case report forms (CRFs) specify the data model of study subjects, evolve over time and consist of hundreds to thousands of data items per study. To avoid erroneous manual transformation work, a converting tool for different representations of study data models was designed. It can convert between office format, EDC and statistics format. In addition, it supports semantic annotations, which enable precise definitions for data items. A reference implementation is available as open source package ODMconverter at http://cran.r-project.org.

Statistical Analysis of Complexity Generators for Cost Estimation

NASA Technical Reports Server (NTRS)

Rowell, Ginger Holmes

1999-01-01

Predicting the cost of cutting edge new technologies involved with spacecraft hardware can be quite complicated. A new feature of the NASA Air Force Cost Model (NAFCOM), called the Complexity Generator, is being developed to model the complexity factors that drive the cost of space hardware. This parametric approach is also designed to account for the differences in cost, based on factors that are unique to each system and subsystem. The cost driver categories included in this model are weight, inheritance from previous missions, technical complexity, and management factors. This paper explains the Complexity Generator framework, the statistical methods used to select the best model within this framework, and the procedures used to find the region of predictability and the prediction intervals for the cost of a mission.

40 CFR Appendix IV to Part 265 - Tests for Significance

Code of Federal Regulations, 2010 CFR

2010-07-01

... introductory statistics texts. ... student's t-test involves calculation of the value of a t-statistic for each comparison of the mean... parameter with its initial background concentration or value. The calculated value of the t-statistic must...

ITA, a portable program for the interactive analysis of data from tracer experiments

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

Wootton, R.; Ashley, K.

ITA is a portable program for analyzing data from tracer experiments, most of the mathematical and graphical work being carried out by subroutines from the NAG and DASL libraries. The program can be used in batch or interactive mode, commands being typed in an English-like language, in free format. Data can be entered from a terminal keyboard or read from a file, and can be validated by printing or plotting them. Erroneous values can be corrected by appropriate editing. Analysis can involve elementary statistics, multiple-isotope crossover corrections, convolution or deconvolution, polyexponential curve-fitting, spline interpolation and/or compartmental analysis. On those installationsmore » with the appropriate hardware, high-resolution graphs can be drawn.« less

Utilizing formative evaluation to enhance the understanding of chemistry and the methods and procedures of science

NASA Astrophysics Data System (ADS)

Pizzini, Edward L.; Treagust, David F.; Cody, John

The purpose of this study was to determine whether or not formative evaluation could facilitate goal attainment in a biochemistry course and produce desired learning outcomes consistently by altering course materials and/or instruction. Formative evaluation procedures included the administration of the Inorganic-Organic-Biological Chemistry Test Form 1974 and the Methods and Procedures of Science test to course participants over three consecutive years. A one group pretest-post-test design was used. The statistical analysis involved the use of the Wilcoxon matched-pairs signed-ranks test. The study involved 64 participants. The findings indicate that the use of formative evaluation can be effective in producing desired learning outcomes to facilitate goal attainment.

Time-series analysis of the transcriptome and proteome of Escherichia coli upon glucose repression.

PubMed

Borirak, Orawan; Rolfe, Matthew D; de Koning, Leo J; Hoefsloot, Huub C J; Bekker, Martijn; Dekker, Henk L; Roseboom, Winfried; Green, Jeffrey; de Koster, Chris G; Hellingwerf, Klaas J

2015-10-01

Time-series transcript- and protein-profiles were measured upon initiation of carbon catabolite repression in Escherichia coli, in order to investigate the extent of post-transcriptional control in this prototypical response. A glucose-limited chemostat culture was used as the CCR-free reference condition. Stopping the pump and simultaneously adding a pulse of glucose, that saturated the cells for at least 1h, was used to initiate the glucose response. Samples were collected and subjected to quantitative time-series analysis of both the transcriptome (using microarray analysis) and the proteome (through a combination of 15N-metabolic labeling and mass spectrometry). Changes in the transcriptome and corresponding proteome were analyzed using statistical procedures designed specifically for time-series data. By comparison of the two sets of data, a total of 96 genes were identified that are post-transcriptionally regulated. This gene list provides candidates for future in-depth investigation of the molecular mechanisms involved in post-transcriptional regulation during carbon catabolite repression in E. coli, like the involvement of small RNAs. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

KNIME for reproducible cross-domain analysis of life science data.

PubMed

Fillbrunn, Alexander; Dietz, Christian; Pfeuffer, Julianus; Rahn, René; Landrum, Gregory A; Berthold, Michael R

2017-11-10

Experiments in the life sciences often involve tools from a variety of domains such as mass spectrometry, next generation sequencing, or image processing. Passing the data between those tools often involves complex scripts for controlling data flow, data transformation, and statistical analysis. Such scripts are not only prone to be platform dependent, they also tend to grow as the experiment progresses and are seldomly well documented, a fact that hinders the reproducibility of the experiment. Workflow systems such as KNIME Analytics Platform aim to solve these problems by providing a platform for connecting tools graphically and guaranteeing the same results on different operating systems. As an open source software, KNIME allows scientists and programmers to provide their own extensions to the scientific community. In this review paper we present selected extensions from the life sciences that simplify data exploration, analysis, and visualization and are interoperable due to KNIME's unified data model. Additionally, we name other workflow systems that are commonly used in the life sciences and highlight their similarities and differences to KNIME. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Proteome analysis of yeast response to various nutrient limitations

PubMed Central

Kolkman, Annemieke; Daran-Lapujade, Pascale; Fullaondo, Asier; Olsthoorn, Maurien M A; Pronk, Jack T; Slijper, Monique; Heck, Albert J R

2006-01-01

We compared the response of Saccharomyces cerevisiae to carbon (glucose) and nitrogen (ammonia) limitation in chemostat cultivation at the proteome level. Protein levels were differentially quantified using unlabeled and 15N metabolically labeled yeast cultures. A total of 928 proteins covering a wide range of isoelectric points, molecular weights and subcellular localizations were identified. Stringent statistical analysis identified 51 proteins upregulated in response to glucose limitation and 51 upregulated in response to ammonia limitation. Under glucose limitation, typical glucose-repressed genes encoding proteins involved in alternative carbon source utilization, fatty acids β-oxidation and oxidative phosphorylation displayed an increased protein level. Proteins upregulated in response to nitrogen limitation were mostly involved in scavenging of alternative nitrogen sources and protein degradation. Comparison of transcript and protein levels clearly showed that upregulation in response to glucose limitation was mainly transcriptionally controlled, whereas upregulation in response to nitrogen limitation was essentially controlled at the post-transcriptional level by increased translational efficiency and/or decreased protein degradation. These observations underline the need for multilevel analysis in yeast systems biology. PMID:16738570

ParallABEL: an R library for generalized parallelization of genome-wide association studies

PubMed Central

2010-01-01

Background Genome-Wide Association (GWA) analysis is a powerful method for identifying loci associated with complex traits and drug response. Parts of GWA analyses, especially those involving thousands of individuals and consuming hours to months, will benefit from parallel computation. It is arduous acquiring the necessary programming skills to correctly partition and distribute data, control and monitor tasks on clustered computers, and merge output files. Results Most components of GWA analysis can be divided into four groups based on the types of input data and statistical outputs. The first group contains statistics computed for a particular Single Nucleotide Polymorphism (SNP), or trait, such as SNP characterization statistics or association test statistics. The input data of this group includes the SNPs/traits. The second group concerns statistics characterizing an individual in a study, for example, the summary statistics of genotype quality for each sample. The input data of this group includes individuals. The third group consists of pair-wise statistics derived from analyses between each pair of individuals in the study, for example genome-wide identity-by-state or genomic kinship analyses. The input data of this group includes pairs of SNPs/traits. The final group concerns pair-wise statistics derived for pairs of SNPs, such as the linkage disequilibrium characterisation. The input data of this group includes pairs of individuals. We developed the ParallABEL library, which utilizes the Rmpi library, to parallelize these four types of computations. ParallABEL library is not only aimed at GenABEL, but may also be employed to parallelize various GWA packages in R. The data set from the North American Rheumatoid Arthritis Consortium (NARAC) includes 2,062 individuals with 545,080, SNPs' genotyping, was used to measure ParallABEL performance. Almost perfect speed-up was achieved for many types of analyses. For example, the computing time for the identity-by-state matrix was linearly reduced from approximately eight hours to one hour when ParallABEL employed eight processors. Conclusions Executing genome-wide association analysis using the ParallABEL library on a computer cluster is an effective way to boost performance, and simplify the parallelization of GWA studies. ParallABEL is a user-friendly parallelization of GenABEL. PMID:20429914

A brief understanding of process optimisation in microwave-assisted extraction of botanical materials: options and opportunities with chemometric tools.

PubMed

Das, Anup Kumar; Mandal, Vivekananda; Mandal, Subhash C

2014-01-01

Extraction forms the very basic step in research on natural products for drug discovery. A poorly optimised and planned extraction methodology can jeopardise the entire mission. To provide a vivid picture of different chemometric tools and planning for process optimisation and method development in extraction of botanical material, with emphasis on microwave-assisted extraction (MAE) of botanical material. A review of studies involving the application of chemometric tools in combination with MAE of botanical materials was undertaken in order to discover what the significant extraction factors were. Optimising a response by fine-tuning those factors, experimental design or statistical design of experiment (DoE), which is a core area of study in chemometrics, was then used for statistical analysis and interpretations. In this review a brief explanation of the different aspects and methodologies related to MAE of botanical materials that were subjected to experimental design, along with some general chemometric tools and the steps involved in the practice of MAE, are presented. A detailed study on various factors and responses involved in the optimisation is also presented. This article will assist in obtaining a better insight into the chemometric strategies of process optimisation and method development, which will in turn improve the decision-making process in selecting influential extraction parameters. Copyright © 2013 John Wiley & Sons, Ltd.

Immunohistochemical evaluation of inducible nitric oxide synthase in the epithelial lining of odontogenic cysts: A qualitative and quantitative analysis.

PubMed

Akshatha, B K; Karuppiah, Karpagaselvi; Manjunath, G S; Kumarswamy, Jayalakshmi; Papaiah, Lokesh; Rao, Jyothi

2017-01-01

The three common odontogenic cysts include radicular cysts (RCs), dentigerous cysts (DCs), and odontogenic keratocysts (OKCs). Among these 3 cysts, OKC is recently been classified as benign keratocystic odontogenic tumor attributing to its aggressive behavior, recurrence rate, and malignant potential. The present study involved qualitative and quantitative analysis of inducible nitric oxide synthase (iNOS) expression in epithelial lining of RCs, DCs, and OKCs, compare iNOS expression in epithelial linings of all the 3 cysts and determined overexpression of iNOS in OKCs which might contribute to its aggressive behavior and malignant potential. The present study is to investigate the role of iNOS in the pathogenesis of OKCs, DCs, and RCs by evaluating the iNOS expression in the epithelial lining of these cysts. Analysis of iNOS expression in epithelial lining cells of 20 RCs, 20 DCs, and 20 OKCs using immunohistochemistry done. The percentage of positive cells and intensity of stain was assessed and compared among all the 3 cysts using contingency coefficient. Kappa statistics for the two observers were computed for finding interobserver agreement. The percentage of iNOS-positive cells was found to be remarkably high in OKCs (12/20) -57.1% as compared to RCs (6/20) - 28.6% and DCs (3/20) - 14.3%. The interobserver agreement for iNOS-positive percentage cells was arrived with kappa values with OKCs → Statistically significant ( P > 0.000), RCs → statistically significant ( P > 0.001) with no significant values for DCs. No statistical difference exists among 3 study samples in regard to the intensity of staining with iNOS. Increased iNOS expression in OKCs may contribute to bone resorption and accumulation of wild-type p53, hence, making OKCs more aggressive.

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

PubMed

Gaffney, Michael

2016-10-01

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

Effectiveness of perioperative antiepileptic drug prophylaxis for early and late seizures following oncologic neurosurgery: a meta-analysis.

PubMed

Joiner, Evan F; Youngerman, Brett E; Hudson, Taylor S; Yang, Jingyan; Welch, Mary R; McKhann, Guy M; Neugut, Alfred I; Bruce, Jeffrey N

2018-04-27

OBJECTIVE The purpose of this meta-analysis was to evaluate the impact of perioperative antiepileptic drug (AED) prophylaxis on short- and long-term seizure incidence among patients undergoing brain tumor surgery. It is the first meta-analysis to focus exclusively on perioperative AED prophylaxis among patients undergoing brain tumor surgery. METHODS The authors searched PubMed/MEDLINE, Embase, Cochrane Central Register of Controlled Trials, clinicaltrials.gov, and the System for Information on Gray Literature in Europe for records related to perioperative AED prophylaxis for patients with brain tumors. Risk of bias in the included studies was assessed using the Cochrane risk of bias tool. Incidence rates for early seizures (within the first postoperative week) and total seizures were estimated based on data from randomized controlled trials. A Mantel-Haenszel random-effects model was used to analyze pooled relative risk (RR) of early seizures (within the first postoperative week) and total seizures associated with perioperative AED prophylaxis versus control. RESULTS Four RCTs involving 352 patients met the criteria of inclusion. The results demonstrated that perioperative AED prophylaxis for patients undergoing brain tumor surgery provides a statistically significant reduction in risk of early postoperative seizures compared with control (RR = 0.352, 95% confidence interval 0.130-0.949, p = 0.039). AED prophylaxis had no statistically significant effect on the total (combined short- and long-term) incidence of seizures. CONCLUSIONS This meta-analysis demonstrates for the first time that perioperative AED prophylaxis for brain tumor surgery provides a statistically significant reduction in early postoperative seizure risk.

Exploring the validity and statistical utility of a racism scale among Black men who have sex with men: a pilot study.

PubMed

Smith, William Pastor

2013-09-01

The primary purpose of this two-phased study was to examine the structural validity and statistical utility of a racism scale specific to Black men who have sex with men (MSM) who resided in the Washington, DC, metropolitan area and Baltimore, Maryland. Phase I involved pretesting a 10-item racism measure with 20 Black MSM. Based on pretest findings, the scale was adapted into a 21-item racism scale for use in collecting data on 166 respondents in Phase II. Exploratory factor analysis of the 21-item racism scale resulted in a 19-item, two-factor solution. The two factors or subscales were the following: General Racism and Relationships and Racism. Confirmatory factor analysis was used in testing construct validity of the factored racism scale. Specifically, the two racism factors were combined with three homophobia factors into a confirmatory factor analysis model. Based on a summary of the fit indices, both comparative and incremental were equal to .90, suggesting an adequate convergence of the racism and homophobia dimensions into a single social oppression construct. Statistical utility of the two racism subscales was demonstrated when regression analysis revealed that the gay-identified men versus bisexual-identified men in the sample were more likely to experience increased racism within the context of intimate relationships and less likely to be exposed to repeated experiences of general racism. Overall, the findings in this study highlight the importance of continuing to explore the psychometric properties of a racism scale that accounts for the unique psychosocial concerns experienced by Black MSM.

Analysis of laparoscopic port site complications: A descriptive study

PubMed Central

Karthik, Somu; Augustine, Alfred Joseph; Shibumon, Mundunadackal Madhavan; Pai, Manohar Varadaraya

2013-01-01

CONTEXT: The rate of port site complications following conventional laparoscopic surgery is about 21 per 100,000 cases. It has shown a proportional rise with increase in the size of the port site incision and trocar. Although rare, complications that occur at the port site include infection, bleeding, and port site hernia. AIMS: To determine the morbidity associated with ports at the site of their insertion in laparoscopic surgery and to identify risk factors for complications. SETTINGS AND DESIGN: Prospective descriptive study. MATERIALS AND METHODS: In the present descriptive study, a total of 570 patients who underwent laparoscopic surgeries for various ailments between August 2009 and July 2011 at our institute were observed for port site complications prospectively and the complications were reviewed. STATISTICAL ANALYSIS USED: Descriptive statistical analysis was carried out in the present study. The statistical software, namely, SPSS 15.0 was used for the analysis of the data. RESULTS: Of the 570 patients undergoing laparoscopic surgery, 17 (3%) had developed complications specifically related to the port site during a minimum follow-up of three months; port site infection (PSI) was the most frequent (n = 10, 1.8%), followed by port site bleeding (n = 4, 0.7%), omentum-related complications (n = 2; 0.35%), and port site metastasis (n = 1, 0.175%). CONCLUSIONS: Laparoscopic surgeries are associated with minimal port site complications. Complications are related to the increased number of ports. Umbilical port involvement is the commonest. Most complications are manageable with minimal morbidity, and can be further minimized with meticulous surgical technique during entry and exit. PMID:23741110

Direction dependence analysis: A framework to test the direction of effects in linear models with an implementation in SPSS.

PubMed

Wiedermann, Wolfgang; Li, Xintong

2018-04-16

In nonexperimental data, at least three possible explanations exist for the association of two variables x and y: (1) x is the cause of y, (2) y is the cause of x, or (3) an unmeasured confounder is present. Statistical tests that identify which of the three explanatory models fits best would be a useful adjunct to the use of theory alone. The present article introduces one such statistical method, direction dependence analysis (DDA), which assesses the relative plausibility of the three explanatory models on the basis of higher-moment information about the variables (i.e., skewness and kurtosis). DDA involves the evaluation of three properties of the data: (1) the observed distributions of the variables, (2) the residual distributions of the competing models, and (3) the independence properties of the predictors and residuals of the competing models. When the observed variables are nonnormally distributed, we show that DDA components can be used to uniquely identify each explanatory model. Statistical inference methods for model selection are presented, and macros to implement DDA in SPSS are provided. An empirical example is given to illustrate the approach. Conceptual and empirical considerations are discussed for best-practice applications in psychological data, and sample size recommendations based on previous simulation studies are provided.

Forecasts of non-Gaussian parameter spaces using Box-Cox transformations

NASA Astrophysics Data System (ADS)

Joachimi, B.; Taylor, A. N.

2011-09-01

Forecasts of statistical constraints on model parameters using the Fisher matrix abound in many fields of astrophysics. The Fisher matrix formalism involves the assumption of Gaussianity in parameter space and hence fails to predict complex features of posterior probability distributions. Combining the standard Fisher matrix with Box-Cox transformations, we propose a novel method that accurately predicts arbitrary posterior shapes. The Box-Cox transformations are applied to parameter space to render it approximately multivariate Gaussian, performing the Fisher matrix calculation on the transformed parameters. We demonstrate that, after the Box-Cox parameters have been determined from an initial likelihood evaluation, the method correctly predicts changes in the posterior when varying various parameters of the experimental setup and the data analysis, with marginally higher computational cost than a standard Fisher matrix calculation. We apply the Box-Cox-Fisher formalism to forecast cosmological parameter constraints by future weak gravitational lensing surveys. The characteristic non-linear degeneracy between matter density parameter and normalization of matter density fluctuations is reproduced for several cases, and the capabilities of breaking this degeneracy by weak-lensing three-point statistics is investigated. Possible applications of Box-Cox transformations of posterior distributions are discussed, including the prospects for performing statistical data analysis steps in the transformed Gaussianized parameter space.

[Medication rule for treatment of functional dyspepsia: an analysis of traditional Chinese medicine literature based on China National Knowledge Internet].

PubMed

Xiao, Hong-ling; Wu, Yuan-jie; Wang, Xiang; Li, Yi-fang; Fang, Zheng-qing

2015-10-01

By retrieving the clinical research literature of treatment functional dyspepsia by traditional Chinese medicine (TCM) from January 2004 to December 2014 based on China National Knowledge Internet (CNKI), we would establish a TCM decoction database for treating functional dyspepsia in this study. One hundred and sixty-four literature were included, involving 159 prescriptions, 377 medicines, in a total of 1 990 herbs. These herbs can be divided into 18 categories according to the effectiveness; and qi-regulating herbs, blood circulation herbs, and antipyretic herbs ranked top three ones according to the frequency of usage of the herbs, whose medicine usage frequency accounted for 51.81%. Usage frequency of 16 herbs was over 30, and Atractylodes, Radix, Poriaranked top three according to the usage frequency. Medicinal properties were divided into 9 kinds according to the frequency statistics, and the top three were warm, flat, and cold. Taste frequency statistics were classifiedinto 9 kinds, and the top three were acrid, sweet, and bitter. In frequency statistics of the meridian tropism of herbs, it was classifiedinto 11 kinds, and the top three were spleen, stomach, lung. The analysis can provide a reference for treatment and study of TCM of functional dyspepsia.

Statistical variation in progressive scrambling

NASA Astrophysics Data System (ADS)

Clark, Robert D.; Fox, Peter C.

2004-07-01

The two methods most often used to evaluate the robustness and predictivity of partial least squares (PLS) models are cross-validation and response randomization. Both methods may be overly optimistic for data sets that contain redundant observations, however. The kinds of perturbation analysis widely used for evaluating model stability in the context of ordinary least squares regression are only applicable when the descriptors are independent of each other and errors are independent and normally distributed; neither assumption holds for QSAR in general and for PLS in particular. Progressive scrambling is a novel, non-parametric approach to perturbing models in the response space in a way that does not disturb the underlying covariance structure of the data. Here, we introduce adjustments for two of the characteristic values produced by a progressive scrambling analysis - the deprecated predictivity (Q_s^{ast^2}) and standard error of prediction (SDEP s * ) - that correct for the effect of introduced perturbation. We also explore the statistical behavior of the adjusted values (Q_0^{ast^2} and SDEP 0 * ) and the sensitivity to perturbation (d q 2/d r yy ' 2). It is shown that the three statistics are all robust for stable PLS models, in terms of the stochastic component of their determination and of their variation due to sampling effects involved in training set selection.

OPLS statistical model versus linear regression to assess sonographic predictors of stroke prognosis.

PubMed

Vajargah, Kianoush Fathi; Sadeghi-Bazargani, Homayoun; Mehdizadeh-Esfanjani, Robab; Savadi-Oskouei, Daryoush; Farhoudi, Mehdi

2012-01-01

The objective of the present study was to assess the comparable applicability of orthogonal projections to latent structures (OPLS) statistical model vs traditional linear regression in order to investigate the role of trans cranial doppler (TCD) sonography in predicting ischemic stroke prognosis. The study was conducted on 116 ischemic stroke patients admitted to a specialty neurology ward. The Unified Neurological Stroke Scale was used once for clinical evaluation on the first week of admission and again six months later. All data was primarily analyzed using simple linear regression and later considered for multivariate analysis using PLS/OPLS models through the SIMCA P+12 statistical software package. The linear regression analysis results used for the identification of TCD predictors of stroke prognosis were confirmed through the OPLS modeling technique. Moreover, in comparison to linear regression, the OPLS model appeared to have higher sensitivity in detecting the predictors of ischemic stroke prognosis and detected several more predictors. Applying the OPLS model made it possible to use both single TCD measures/indicators and arbitrarily dichotomized measures of TCD single vessel involvement as well as the overall TCD result. In conclusion, the authors recommend PLS/OPLS methods as complementary rather than alternative to the available classical regression models such as linear regression.

Integrative pathway analysis of a genome-wide association study of V̇o2max response to exercise training

PubMed Central

Vivar, Juan C.; Sarzynski, Mark A.; Sung, Yun Ju; Timmons, James A.; Bouchard, Claude; Rankinen, Tuomo

2013-01-01

We previously reported the findings from a genome-wide association study of the response of maximal oxygen uptake (V̇o2max) to an exercise program. Here we follow up on these results to generate hypotheses on genes, pathways, and systems involved in the ability to respond to exercise training. A systems biology approach can help us better establish a comprehensive physiological description of what underlies V̇o2maxtrainability. The primary material for this exploration was the individual single-nucleotide polymorphism (SNP), SNP-gene mapping, and statistical significance levels. We aimed to generate novel hypotheses through analyses that go beyond statistical association of single-locus markers. This was accomplished through three complementary approaches: 1) building de novo evidence of gene candidacy through informatics-driven literature mining; 2) aggregating evidence from statistical associations to link variant enrichment in biological pathways to V̇o2max trainability; and 3) predicting possible consequences of variants residing in the pathways of interest. We started with candidate gene prioritization followed by pathway analysis focused on overrepresentation analysis and gene set enrichment analysis. Subsequently, leads were followed using in silico analysis of predicted SNP functions. Pathways related to cellular energetics (pantothenate and CoA biosynthesis; PPAR signaling) and immune functions (complement and coagulation cascades) had the highest levels of SNP burden. In particular, long-chain fatty acid transport and fatty acid oxidation genes and sequence variants were found to influence differences in V̇o2max trainability. Together, these methods allow for the hypothesis-driven ranking and prioritization of genes and pathways for future experimental testing and validation. PMID:23990238

Use of statistical tools to evaluate the reductive dechlorination of high levels of TCE in microcosm studies.

PubMed

Harkness, Mark; Fisher, Angela; Lee, Michael D; Mack, E Erin; Payne, Jo Ann; Dworatzek, Sandra; Roberts, Jeff; Acheson, Carolyn; Herrmann, Ronald; Possolo, Antonio

2012-04-01

A large, multi-laboratory microcosm study was performed to select amendments for supporting reductive dechlorination of high levels of trichloroethylene (TCE) found at an industrial site in the United Kingdom (UK) containing dense non-aqueous phase liquid (DNAPL) TCE. The study was designed as a fractional factorial experiment involving 177 bottles distributed between four industrial laboratories and was used to assess the impact of six electron donors, bioaugmentation, addition of supplemental nutrients, and two TCE levels (0.57 and 1.90 mM or 75 and 250 mg/L in the aqueous phase) on TCE dechlorination. Performance was assessed based on the concentration changes of TCE and reductive dechlorination degradation products. The chemical data was evaluated using analysis of variance (ANOVA) and survival analysis techniques to determine both main effects and important interactions for all the experimental variables during the 203-day study. The statistically based design and analysis provided powerful tools that aided decision-making for field application of this technology. The analysis showed that emulsified vegetable oil (EVO), lactate, and methanol were the most effective electron donors, promoting rapid and complete dechlorination of TCE to ethene. Bioaugmentation and nutrient addition also had a statistically significant positive impact on TCE dechlorination. In addition, the microbial community was measured using phospholipid fatty acid analysis (PLFA) for quantification of total biomass and characterization of the community structure and quantitative polymerase chain reaction (qPCR) for enumeration of Dehalococcoides organisms (Dhc) and the vinyl chloride reductase (vcrA) gene. The highest increase in levels of total biomass and Dhc was observed in the EVO microcosms, which correlated well with the dechlorination results. Copyright © 2012 Elsevier B.V. All rights reserved.

Experimental design matters for statistical analysis: how to handle blocking.

PubMed

Jensen, Signe M; Schaarschmidt, Frank; Onofri, Andrea; Ritz, Christian

2018-03-01

Nowadays, evaluation of the effects of pesticides often relies on experimental designs that involve multiple concentrations of the pesticide of interest or multiple pesticides at specific comparable concentrations and, possibly, secondary factors of interest. Unfortunately, the experimental design is often more or less neglected when analysing data. Two data examples were analysed using different modelling strategies. First, in a randomized complete block design, mean heights of maize treated with a herbicide and one of several adjuvants were compared. Second, translocation of an insecticide applied to maize as a seed treatment was evaluated using incomplete data from an unbalanced design with several layers of hierarchical sampling. Extensive simulations were carried out to further substantiate the effects of different modelling strategies. It was shown that results from suboptimal approaches (two-sample t-tests and ordinary ANOVA assuming independent observations) may be both quantitatively and qualitatively different from the results obtained using an appropriate linear mixed model. The simulations demonstrated that the different approaches may lead to differences in coverage percentages of confidence intervals and type 1 error rates, confirming that misleading conclusions can easily happen when an inappropriate statistical approach is chosen. To ensure that experimental data are summarized appropriately, avoiding misleading conclusions, the experimental design should duly be reflected in the choice of statistical approaches and models. We recommend that author guidelines should explicitly point out that authors need to indicate how the statistical analysis reflects the experimental design. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

The extended statistical analysis of toxicity tests using standardised effect sizes (SESs): a comparison of nine published papers.

PubMed

Festing, Michael F W

2014-01-01

The safety of chemicals, drugs, novel foods and genetically modified crops is often tested using repeat-dose sub-acute toxicity tests in rats or mice. It is important to avoid misinterpretations of the results as these tests are used to help determine safe exposure levels in humans. Treated and control groups are compared for a range of haematological, biochemical and other biomarkers which may indicate tissue damage or other adverse effects. However, the statistical analysis and presentation of such data poses problems due to the large number of statistical tests which are involved. Often, it is not clear whether a "statistically significant" effect is real or a false positive (type I error) due to sampling variation. The author's conclusions appear to be reached somewhat subjectively by the pattern of statistical significances, discounting those which they judge to be type I errors and ignoring any biomarker where the p-value is greater than p = 0.05. However, by using standardised effect sizes (SESs) a range of graphical methods and an over-all assessment of the mean absolute response can be made. The approach is an extension, not a replacement of existing methods. It is intended to assist toxicologists and regulators in the interpretation of the results. Here, the SES analysis has been applied to data from nine published sub-acute toxicity tests in order to compare the findings with those of the author's. Line plots, box plots and bar plots show the pattern of response. Dose-response relationships are easily seen. A "bootstrap" test compares the mean absolute differences across dose groups. In four out of seven papers where the no observed adverse effect level (NOAEL) was estimated by the authors, it was set too high according to the bootstrap test, suggesting that possible toxicity is under-estimated.

Online and offline tools for head movement compensation in MEG.

PubMed

Stolk, Arjen; Todorovic, Ana; Schoffelen, Jan-Mathijs; Oostenveld, Robert

2013-03-01

Magnetoencephalography (MEG) is measured above the head, which makes it sensitive to variations of the head position with respect to the sensors. Head movements blur the topography of the neuronal sources of the MEG signal, increase localization errors, and reduce statistical sensitivity. Here we describe two novel and readily applicable methods that compensate for the detrimental effects of head motion on the statistical sensitivity of MEG experiments. First, we introduce an online procedure that continuously monitors head position. Second, we describe an offline analysis method that takes into account the head position time-series. We quantify the performance of these methods in the context of three different experimental settings, involving somatosensory, visual and auditory stimuli, assessing both individual and group-level statistics. The online head localization procedure allowed for optimal repositioning of the subjects over multiple sessions, resulting in a 28% reduction of the variance in dipole position and an improvement of up to 15% in statistical sensitivity. Offline incorporation of the head position time-series into the general linear model resulted in improvements of group-level statistical sensitivity between 15% and 29%. These tools can substantially reduce the influence of head movement within and between sessions, increasing the sensitivity of many cognitive neuroscience experiments. Copyright © 2012 Elsevier Inc. All rights reserved.

Functional brain networks for learning predictive statistics.

PubMed

Giorgio, Joseph; Karlaftis, Vasilis M; Wang, Rui; Shen, Yuan; Tino, Peter; Welchman, Andrew; Kourtzi, Zoe

2017-08-18

Making predictions about future events relies on interpreting streams of information that may initially appear incomprehensible. This skill relies on extracting regular patterns in space and time by mere exposure to the environment (i.e., without explicit feedback). Yet, we know little about the functional brain networks that mediate this type of statistical learning. Here, we test whether changes in the processing and connectivity of functional brain networks due to training relate to our ability to learn temporal regularities. By combining behavioral training and functional brain connectivity analysis, we demonstrate that individuals adapt to the environment's statistics as they change over time from simple repetition to probabilistic combinations. Further, we show that individual learning of temporal structures relates to decision strategy. Our fMRI results demonstrate that learning-dependent changes in fMRI activation within and functional connectivity between brain networks relate to individual variability in strategy. In particular, extracting the exact sequence statistics (i.e., matching) relates to changes in brain networks known to be involved in memory and stimulus-response associations, while selecting the most probable outcomes in a given context (i.e., maximizing) relates to changes in frontal and striatal networks. Thus, our findings provide evidence that dissociable brain networks mediate individual ability in learning behaviorally-relevant statistics. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

The potential for meta-analysis to support decision analysis in ecology.

PubMed

Mengersen, Kerrie; MacNeil, M Aaron; Caley, M Julian

2015-06-01

Meta-analysis and decision analysis are underpinned by well-developed methods that are commonly applied to a variety of problems and disciplines. While these two fields have been closely linked in some disciplines such as medicine, comparatively little attention has been paid to the potential benefits of linking them in ecology, despite reasonable expectations that benefits would be derived from doing so. Meta-analysis combines information from multiple studies to provide more accurate parameter estimates and to reduce the uncertainty surrounding them. Decision analysis involves selecting among alternative choices using statistical information that helps to shed light on the uncertainties involved. By linking meta-analysis to decision analysis, improved decisions can be made, with quantification of the costs and benefits of alternate decisions supported by a greater density of information. Here, we briefly review concepts of both meta-analysis and decision analysis, illustrating the natural linkage between them and the benefits from explicitly linking one to the other. We discuss some examples in which this linkage has been exploited in the medical arena and how improvements in precision and reduction of structural uncertainty inherent in a meta-analysis can provide substantive improvements to decision analysis outcomes by reducing uncertainty in expected loss and maximising information from across studies. We then argue that these significant benefits could be translated to ecology, in particular to the problem of making optimal ecological decisions in the face of uncertainty. Copyright © 2013 John Wiley & Sons, Ltd.

Gene variations in sex hormone pathways and the risk of testicular germ cell tumour: a case-parent triad study in a Norwegian-Swedish population.

PubMed

Kristiansen, W; Andreassen, K E; Karlsson, R; Aschim, E L; Bremnes, R M; Dahl, O; Fosså, S D; Klepp, O; Langberg, C W; Solberg, A; Tretli, S; Adami, H-O; Wiklund, F; Grotmol, T; Haugen, T B

2012-05-01

Testicular germ cell tumour (TGCT) is the most common cancer in young men, and an imbalance between the estrogen and androgen levels in utero is hypothesized to influence TGCT risk. Thus, polymorphisms in genes involved in the action of sex hormones may contribute to variability in an individual's susceptibility to TGCT. We conducted a Norwegian-Swedish case-parent study. A total of 105 single-nucleotide polymorphisms (SNPs) in 20 sex hormone pathway genes were genotyped using Sequenom MassArray iPLEX Gold, in 831 complete triads and 474 dyads. To increase the statistical power, the analysis was expanded to include 712 case singletons and 3922 Swedish controls, thus including triads, dyads and the case-control samples in a single test for association. Analysis for allelic associations was performed with the UNPHASED program, using a likelihood-based association test for nuclear families with missing data, and odds ratios (ORs) and 95% confidence intervals (CIs) were calculated. False discovery rate (FDR) was used to adjust for multiple testing. Five genetic variants across the ESR2 gene [encoding estrogen receptor beta (ERβ)] were statistically significantly associated with the risk of TGCT. In the case-parent analysis, the markers rs12434245 and rs10137185 were associated with a reduced risk of TGCT (OR = 0.66 and 0.72, respectively; both FDRs <5%), whereas rs2978381 and rs12435857 were associated with an increased risk of TGCT (OR = 1.21 and 1.19, respectively; both FDRs <5%). In the combined case-parent/case-control analysis, rs12435857 and rs10146204 were associated with an increased risk of TGCT (OR = 1.15 and 1.13, respectively; both FDRs <5%), whereas rs10137185 was associated with a reduced risk of TGCT (OR = 0.79, FDR <5%). In addition, we found that three genetic variants in CYP19A1 (encoding aromatase) were statistically significantly associated with the risk of TGCT in the case-parent analysis. The T alleles of the rs2414099, rs8025374 and rs3751592 SNPs were associated with an increased risk of TGCT (OR = 1.30, 1.30 and 1.21, respectively; all FDRs <5%). We found no statistically significant differences in allelic effect estimates between parental inherited genetic variation in the sex hormone pathways and TGCT risk in the offspring, and no evidence of heterogeneity between seminomas and non-seminomas, or between the Norwegian and the Swedish population, in any of the SNPs examined. Our findings provide support for ERβ and aromatase being implicated in the aetiology of TGCT. Exploring the functional role of the TGCT risk-associated SNPs will further elucidate the biological mechanisms involved.

Descriptive data analysis.

PubMed

Thompson, Cheryl Bagley

2009-01-01

This 13th article of the Basics of Research series is first in a short series on statistical analysis. These articles will discuss creating your statistical analysis plan, levels of measurement, descriptive statistics, probability theory, inferential statistics, and general considerations for interpretation of the results of a statistical analysis.

A SURVEY OF LABORATORY AND STATISTICAL ISSUES RELATED TO FARMWORKER EXPOSURE STUDIES

EPA Science Inventory

Developing internally valid, and perhaps generalizable, farmworker exposure studies is a complex process that involves many statistical and laboratory considerations. Statistics are an integral component of each study beginning with the design stage and continuing to the final da...

P-Value Club: Teaching Significance Level on the Dance Floor

ERIC Educational Resources Information Center

Gray, Jennifer

2010-01-01

Courses: Beginning research methods and statistics courses, as well as advanced communication courses that require reading research articles and completing research projects involving statistics. Objective: Students will understand the difference between significant and nonsignificant statistical results based on p-value.

Segment and fit thresholding: a new method for image analysis applied to microarray and immunofluorescence data.

PubMed

Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E; Allen, Peter J; Sempere, Lorenzo F; Haab, Brian B

2015-10-06

Experiments involving the high-throughput quantification of image data require algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multicolor, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu's method for selected images. SFT promises to advance the goal of full automation in image analysis.

The relationship between budget allocated and budget utilized of faculties in an academic institution

NASA Astrophysics Data System (ADS)

Aziz, Wan Noor Hayatie Wan Abdul; Aziz, Rossidah Wan Abdul; Shuib, Adibah; Razi, Nor Faezah Mohamad

2014-06-01

Budget planning enables an organization to set priorities towards achieving certain goals and to identify the highest priorities to be accomplished with the available funds, thus allowing allocation of resources according to the set priorities and constraints. On the other hand, budget execution and monitoring enables allocated funds or resources to be utilized as planned. Our study concerns with investigating the relationship between budget allocation and budget utilization of faculties in a public university in Malaysia. The focus is on the university's operations management financial allocation and utilization based on five categories which are emolument expenditure, academic or services and supplies expenditure, maintenance expenditure, student expenditure and others expenditure. The analysis on financial allocation and utilization is performed based on yearly quarters. Data collected include three years faculties' budget allocation and budget utilization performance involving a sample of ten selected faculties of a public university in Malaysia. Results show that there are positive correlation and significant relationship between quarterly budget allocation and quarterly budget utilization. This study found that emolument give the highest contribution to the total allocation and total utilization for all quarters. This paper presents some findings based on statistical analysis conducted which include descriptive statistics and correlation analysis.

Segment and Fit Thresholding: A New Method for Image Analysis Applied to Microarray and Immunofluorescence Data

PubMed Central

Ensink, Elliot; Sinha, Jessica; Sinha, Arkadeep; Tang, Huiyuan; Calderone, Heather M.; Hostetter, Galen; Winter, Jordan; Cherba, David; Brand, Randall E.; Allen, Peter J.; Sempere, Lorenzo F.; Haab, Brian B.

2016-01-01

Certain experiments involve the high-throughput quantification of image data, thus requiring algorithms for automation. A challenge in the development of such algorithms is to properly interpret signals over a broad range of image characteristics, without the need for manual adjustment of parameters. Here we present a new approach for locating signals in image data, called Segment and Fit Thresholding (SFT). The method assesses statistical characteristics of small segments of the image and determines the best-fit trends between the statistics. Based on the relationships, SFT identifies segments belonging to background regions; analyzes the background to determine optimal thresholds; and analyzes all segments to identify signal pixels. We optimized the initial settings for locating background and signal in antibody microarray and immunofluorescence data and found that SFT performed well over multiple, diverse image characteristics without readjustment of settings. When used for the automated analysis of multi-color, tissue-microarray images, SFT correctly found the overlap of markers with known subcellular localization, and it performed better than a fixed threshold and Otsu’s method for selected images. SFT promises to advance the goal of full automation in image analysis. PMID:26339978

Enhancement of CFD validation exercise along the roof profile of a low-rise building

NASA Astrophysics Data System (ADS)

Deraman, S. N. C.; Majid, T. A.; Zaini, S. S.; Yahya, W. N. W.; Abdullah, J.; Ismail, M. A.

2018-04-01

The aim of this study is to enhance the validation of CFD exercise along the roof profile of a low-rise building. An isolated gabled-roof house having 26.6° roof pitch was simulated to obtain the pressure coefficient around the house. Validation of CFD analysis with experimental data requires many input parameters. This study performed CFD simulation based on the data from a previous study. Where the input parameters were not clearly stated, new input parameters were established from the open literatures. The numerical simulations were performed in FLUENT 14.0 by applying the Computational Fluid Dynamics (CFD) approach based on steady RANS equation together with RNG k-ɛ model. Hence, the result from CFD was analysed by using quantitative test (statistical analysis) and compared with CFD results from the previous study. The statistical analysis results from ANOVA test and error measure showed that the CFD results from the current study produced good agreement and exhibited the closest error compared to the previous study. All the input data used in this study can be extended to other types of CFD simulation involving wind flow over an isolated single storey house.

Fourier descriptor analysis and unification of voice range profile contours: method and applications.

PubMed

Pabon, Peter; Ternström, Sten; Lamarche, Anick

2011-06-01

To describe a method for unified description, statistical modeling, and comparison of voice range profile (VRP) contours, even from diverse sources. A morphologic modeling technique, which is based on Fourier descriptors (FDs), is applied to the VRP contour. The technique, which essentially involves resampling of the curve of the contour, is assessed and also is compared to density-based VRP averaging methods that use the overlap count. VRP contours can be usefully described and compared using FDs. The method also permits the visualization of the local covariation along the contour average. For example, the FD-based analysis shows that the population variance for ensembles of VRP contours is usually smallest at the upper left part of the VRP. To illustrate the method's advantages and possible further application, graphs are given that compare the averaged contours from different authors and recording devices--for normal, trained, and untrained male and female voices as well as for child voices. The proposed technique allows any VRP shape to be brought to the same uniform base. On this uniform base, VRP contours or contour elements coming from a variety of sources may be placed within the same graph for comparison and for statistical analysis.

Assessment of pleiotropic transcriptome perturbations in Arabidopsis engineered for indirect insect defence.

PubMed

Houshyani, Benyamin; van der Krol, Alexander R; Bino, Raoul J; Bouwmeester, Harro J

2014-06-19

Molecular characterization is an essential step of risk/safety assessment of genetically modified (GM) crops. Holistic approaches for molecular characterization using omics platforms can be used to confirm the intended impact of the genetic engineering, but can also reveal the unintended changes at the omics level as a first assessment of potential risks. The potential of omics platforms for risk assessment of GM crops has rarely been used for this purpose because of the lack of a consensus reference and statistical methods to judge the significance or importance of the pleiotropic changes in GM plants. Here we propose a meta data analysis approach to the analysis of GM plants, by measuring the transcriptome distance to untransformed wild-types. In the statistical analysis of the transcriptome distance between GM and wild-type plants, values are compared with naturally occurring transcriptome distances in non-GM counterparts obtained from a database. Using this approach we show that the pleiotropic effect of genes involved in indirect insect defence traits is substantially equivalent to the variation in gene expression occurring naturally in Arabidopsis. Transcriptome distance is a useful screening method to obtain insight in the pleiotropic effects of genetic modification.

Analysis of promoter polymorphism in monoamine oxidase A (MAOA) gene in completed suicide on Slovenian population.

PubMed

Uršič, Katarina; Zupanc, Tomaž; Paska, Alja Videtič

2018-04-23

Suicide is a well-defined public health problem and is a complex phenomenon influenced by a number of different risk factors, including genetic ones. Numerous studies have examined serotonin system genes. Monoamine oxidase A (MAO-A) is an outer mitochondrial membrane enzyme which is involved in the metabolic pathway of serotonin degradation. Upstream variable number of tandem repeats (uVNTR) in the promoter region of MAOA gene affects the activity of transcription. In the present study we genotyped MAOA-uVNTR polymorphism in 266 suicide victims and 191 control subjects of Slovenian population, which ranks among the European and world populations with the highest suicide rate. Genotyping was performed with polymerase chain reaction and agarose gel electrophoresis. Using a separate statistical analysis for female and male subjects we determined the differences in genotype distributions of MAOA-uVNTR polymorphism between the studied groups. Statistical analysis showed a trend towards 3R allele and suicide, and associated 3R allele with non-violent suicide method on stratified data (20 suicide victims). This is the first study associating highly suicidal Slovenian population with MAOA-uVNTR polymorphism. Copyright © 2018 Elsevier B.V. All rights reserved.

Using the gene ontology for microarray data mining: a comparison of methods and application to age effects in human prefrontal cortex.

PubMed

Pavlidis, Paul; Qin, Jie; Arango, Victoria; Mann, John J; Sibille, Etienne

2004-06-01

One of the challenges in the analysis of gene expression data is placing the results in the context of other data available about genes and their relationships to each other. Here, we approach this problem in the study of gene expression changes associated with age in two areas of the human prefrontal cortex, comparing two computational methods. The first method, "overrepresentation analysis" (ORA), is based on statistically evaluating the fraction of genes in a particular gene ontology class found among the set of genes showing age-related changes in expression. The second method, "functional class scoring" (FCS), examines the statistical distribution of individual gene scores among all genes in the gene ontology class and does not involve an initial gene selection step. We find that FCS yields more consistent results than ORA, and the results of ORA depended strongly on the gene selection threshold. Our findings highlight the utility of functional class scoring for the analysis of complex expression data sets and emphasize the advantage of considering all available genomic information rather than sets of genes that pass a predetermined "threshold of significance."

Principal Component Analysis in the Spectral Analysis of the Dynamic Laser Speckle Patterns

NASA Astrophysics Data System (ADS)

Ribeiro, K. M.; Braga, R. A., Jr.; Horgan, G. W.; Ferreira, D. D.; Safadi, T.

2014-02-01

Dynamic laser speckle is a phenomenon that interprets an optical patterns formed by illuminating a surface under changes with coherent light. Therefore, the dynamic change of the speckle patterns caused by biological material is known as biospeckle. Usually, these patterns of optical interference evolving in time are analyzed by graphical or numerical methods, and the analysis in frequency domain has also been an option, however involving large computational requirements which demands new approaches to filter the images in time. Principal component analysis (PCA) works with the statistical decorrelation of data and it can be used as a data filtering. In this context, the present work evaluated the PCA technique to filter in time the data from the biospeckle images aiming the reduction of time computer consuming and improving the robustness of the filtering. It was used 64 images of biospeckle in time observed in a maize seed. The images were arranged in a data matrix and statistically uncorrelated by PCA technique, and the reconstructed signals were analyzed using the routine graphical and numerical methods to analyze the biospeckle. Results showed the potential of the PCA tool in filtering the dynamic laser speckle data, with the definition of markers of principal components related to the biological phenomena and with the advantage of fast computational processing.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

PubMed

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

Association of bladder sensation measures and bladder diary in patients with urinary incontinence.

PubMed

King, Ashley B; Wolters, Jeff P; Klausner, Adam P; Rapp, David E

2012-04-01

Investigation suggests the involvement of afferent actions in the pathophysiology of urinary incontinence. Current diagnostic modalities do not allow for the accurate identification of sensory dysfunction. We previously reported urodynamic derivatives that may be useful in assessing bladder sensation. We sought to further investigate these derivatives by assessing for a relationship with 3-day bladder diary. Subset analysis was performed in patients without stress urinary incontinence (SUI) attempting to isolate patients with urgency symptoms. No association was demonstrated between bladder diary parameters and urodynamic derivatives (r coefficient range (-0.06 to 0.08)(p > 0.05)). However, subset analysis demonstrated an association between detrusor overactivity (DO) and bladder urgency velocity (BUV), with a lower BUV identified in patients without DO. Subset analysis of patients with isolated urgency/urge incontinence identified weak associations between voiding frequency and FSR (r = 0.39) and between daily incontinence episodes and BUV (r = 0.35). However, these associations failed to demonstrate statistical significance. No statistical association was seen between bladder diary and urodynamic derivatives. This is not unexpected, given that bladder diary parameters may reflect numerous pathologies including not only sensory dysfunction but also SUI and DO. However, weak associations were identified in patients without SUI and, further, a statistical relationship between DO and BUV was seen. Additional research is needed to assess the utility of FSR/BUV in characterizing sensory dysfunction, especially in patients without concurrent pathology (e.g. SUI, DO).

Adaptation of Lorke's method to determine and compare ED50 values: the cases of two anticonvulsants drugs.

PubMed

Garrido-Acosta, Osvaldo; Meza-Toledo, Sergio Enrique; Anguiano-Robledo, Liliana; Valencia-Hernández, Ignacio; Chamorro-Cevallos, Germán

2014-01-01

We determined the median effective dose (ED50) values for the anticonvulsants phenobarbital and sodium valproate using a modification of Lorke's method. This modification allowed appropriate statistical analysis and the use of a smaller number of mice per compound tested. The anticonvulsant activities of phenobarbital and sodium valproate were evaluated in male CD1 mice by maximal electroshock (MES) and intraperitoneal administration of pentylenetetrazole (PTZ). The anticonvulsant ED50 values were obtained through modifications of Lorke's method that involved changes in the selection of the three first doses in the initial test and the fourth dose in the second test. Furthermore, a test was added to evaluate the ED50 calculated by the modified Lorke's method, allowing statistical analysis of the data and determination of the confidence limits for ED50. The ED50 for phenobarbital against MES- and PTZ-induced seizures was 16.3mg/kg and 12.7mg/kg, respectively. The sodium valproate values were 261.2mg/kg and 159.7mg/kg, respectively. These results are similar to those found using the traditional methods of finding ED50, suggesting that the modifications made to Lorke's method generate equal results using fewer mice while increasing confidence in the statistical analysis. This adaptation of Lorke's method can be used to determine median letal dose (LD50) or ED50 for compounds with other pharmacological activities. Copyright © 2014 Elsevier Inc. All rights reserved.

Development and Validation of an Instrument to Measure Indonesian Pre-Service Teachers' Conceptions of Statistics

ERIC Educational Resources Information Center

Idris, Khairiani; Yang, Kai-Lin

2017-01-01

This article reports the results of a mixed-methods approach to develop and validate an instrument to measure Indonesian pre-service teachers' conceptions of statistics. First, a phenomenographic study involving a sample of 44 participants uncovered six categories of conceptions of statistics. Second, an instrument of conceptions of statistics was…

Genetics of PCOS: A systematic bioinformatics approach to unveil the proteins responsible for PCOS.

PubMed

Panda, Pritam Kumar; Rane, Riya; Ravichandran, Rahul; Singh, Shrinkhla; Panchal, Hetalkumar

2016-06-01

Polycystic ovary syndrome (PCOS) is a hormonal imbalance in women, which causes problems during menstrual cycle and in pregnancy that sometimes results in fatality. Though the genetics of PCOS is not fully understood, early diagnosis and treatment can prevent long-term effects. In this study, we have studied the proteins involved in PCOS and the structural aspects of the proteins that are taken into consideration using computational tools. The proteins involved are modeled using Modeller 9v14 and Ab-initio programs. All the 43 proteins responsible for PCOS were subjected to phylogenetic analysis to identify the relatedness of the proteins. Further, microarray data analysis of PCOS datasets was analyzed that was downloaded from GEO datasets to find the significant protein-coding genes responsible for PCOS, which is an addition to the reported protein-coding genes. Various statistical analyses were done using R programming to get an insight into the structural aspects of PCOS that can be used as drug targets to treat PCOS and other related reproductive diseases.

Prospects of studies on violence, adolescence and cortisol: a systematic literature review.

PubMed

Lugarinho, Leonardo Planel; Avanci, Joviana Quintes; Pinto, Liana Wernersbach

2017-04-01

Violence has a negative impact on adolescents and affects their quality of life. It causes stress and requires the victim's adaptive capacity, which can cause psychological and biological changes. Hormone cortisol levels have been used as stress biomarker in several studies. This paper aims to perform a systematic literature review of publications on cortisol and violence involving teenagers from 2000 to 2013. Descriptors "cortisol", "violence" and "adolescent" were used in both English and Portuguese in this review, which included bibliographic databases PubMed/Medline, Lilacs, BVS and SciELO. Twelve papers were analyzed. Most studies involve participants from the United States, of both genders and without a control group. Different types of violence are studied, especially family violence, victimization or testimony. All studies used saliva to measure cortisol and no standard methodology was used for the analysis. Most studies (83.3%) found a statistically significant association between cortisol levels and exposure to violence. Results regarding gender, type of violence, socioeconomic status or cortisol analysis methods are not yet uniform.

Extended method of moments for deterministic analysis of stochastic multistable neurodynamical systems

NASA Astrophysics Data System (ADS)

Deco, Gustavo; Martí, Daniel

2007-03-01

The analysis of transitions in stochastic neurodynamical systems is essential to understand the computational principles that underlie those perceptual and cognitive processes involving multistable phenomena, like decision making and bistable perception. To investigate the role of noise in a multistable neurodynamical system described by coupled differential equations, one usually considers numerical simulations, which are time consuming because of the need for sufficiently many trials to capture the statistics of the influence of the fluctuations on that system. An alternative analytical approach involves the derivation of deterministic differential equations for the moments of the distribution of the activity of the neuronal populations. However, the application of the method of moments is restricted by the assumption that the distribution of the state variables of the system takes on a unimodal Gaussian shape. We extend in this paper the classical moments method to the case of bimodal distribution of the state variables, such that a reduced system of deterministic coupled differential equations can be derived for the desired regime of multistability.

Managing heteroscedasticity in general linear models.

PubMed

Rosopa, Patrick J; Schaffer, Meline M; Schroeder, Amber N

2013-09-01

Heteroscedasticity refers to a phenomenon where data violate a statistical assumption. This assumption is known as homoscedasticity. When the homoscedasticity assumption is violated, this can lead to increased Type I error rates or decreased statistical power. Because this can adversely affect substantive conclusions, the failure to detect and manage heteroscedasticity could have serious implications for theory, research, and practice. In addition, heteroscedasticity is not uncommon in the behavioral and social sciences. Thus, in the current article, we synthesize extant literature in applied psychology, econometrics, quantitative psychology, and statistics, and we offer recommendations for researchers and practitioners regarding available procedures for detecting heteroscedasticity and mitigating its effects. In addition to discussing the strengths and weaknesses of various procedures and comparing them in terms of existing simulation results, we describe a 3-step data-analytic process for detecting and managing heteroscedasticity: (a) fitting a model based on theory and saving residuals, (b) the analysis of residuals, and (c) statistical inferences (e.g., hypothesis tests and confidence intervals) involving parameter estimates. We also demonstrate this data-analytic process using an illustrative example. Overall, detecting violations of the homoscedasticity assumption and mitigating its biasing effects can strengthen the validity of inferences from behavioral and social science data.

Evaluating sufficient similarity for drinking-water disinfection by-product (DBP) mixtures with bootstrap hypothesis test procedures.

PubMed

Feder, Paul I; Ma, Zhenxu J; Bull, Richard J; Teuschler, Linda K; Rice, Glenn

2009-01-01

In chemical mixtures risk assessment, the use of dose-response data developed for one mixture to estimate risk posed by a second mixture depends on whether the two mixtures are sufficiently similar. While evaluations of similarity may be made using qualitative judgments, this article uses nonparametric statistical methods based on the "bootstrap" resampling technique to address the question of similarity among mixtures of chemical disinfectant by-products (DBP) in drinking water. The bootstrap resampling technique is a general-purpose, computer-intensive approach to statistical inference that substitutes empirical sampling for theoretically based parametric mathematical modeling. Nonparametric, bootstrap-based inference involves fewer assumptions than parametric normal theory based inference. The bootstrap procedure is appropriate, at least in an asymptotic sense, whether or not the parametric, distributional assumptions hold, even approximately. The statistical analysis procedures in this article are initially illustrated with data from 5 water treatment plants (Schenck et al., 2009), and then extended using data developed from a study of 35 drinking-water utilities (U.S. EPA/AMWA, 1989), which permits inclusion of a greater number of water constituents and increased structure in the statistical models.

Shoulder strength value differences between genders and age groups.

PubMed

Balcells-Diaz, Eudald; Daunis-I-Estadella, Pepus

2018-03-01

The strength of a normal shoulder differs according to gender and decreases with age. Therefore, the Constant score, which is a shoulder function measurement tool that allocates 25% of the final score to strength, differs from the absolute values but likely reflects a normal shoulder. To compare group results, a normalized Constant score is needed, and the first step to achieving normalization involves statistically establishing the gender differences and age-related decline. In this investigation, we sought to verify the gender difference and age-related decline in strength. We obtained a randomized representative sample of the general population in a small to medium-sized Spanish city. We then invited this population to participate in our study, and we measured their shoulder strength. We performed a statistical analysis with a power of 80% and a P value < .05. We observed a statistically significant difference between the genders and a statistically significant decline with age. To the best of our knowledge, this is the first investigation to study a representative sample of the general population from which conclusions can be drawn regarding Constant score normalization. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Statistical downscaling of GCM simulations to streamflow using relevance vector machine

NASA Astrophysics Data System (ADS)

Ghosh, Subimal; Mujumdar, P. P.

2008-01-01

General circulation models (GCMs), the climate models often used in assessing the impact of climate change, operate on a coarse scale and thus the simulation results obtained from GCMs are not particularly useful in a comparatively smaller river basin scale hydrology. The article presents a methodology of statistical downscaling based on sparse Bayesian learning and Relevance Vector Machine (RVM) to model streamflow at river basin scale for monsoon period (June, July, August, September) using GCM simulated climatic variables. NCEP/NCAR reanalysis data have been used for training the model to establish a statistical relationship between streamflow and climatic variables. The relationship thus obtained is used to project the future streamflow from GCM simulations. The statistical methodology involves principal component analysis, fuzzy clustering and RVM. Different kernel functions are used for comparison purpose. The model is applied to Mahanadi river basin in India. The results obtained using RVM are compared with those of state-of-the-art Support Vector Machine (SVM) to present the advantages of RVMs over SVMs. A decreasing trend is observed for monsoon streamflow of Mahanadi due to high surface warming in future, with the CCSR/NIES GCM and B2 scenario.

Combining Shapley value and statistics to the analysis of gene expression data in children exposed to air pollution

PubMed Central

Moretti, Stefano; van Leeuwen, Danitsja; Gmuender, Hans; Bonassi, Stefano; van Delft, Joost; Kleinjans, Jos; Patrone, Fioravante; Merlo, Domenico Franco

2008-01-01

Background In gene expression analysis, statistical tests for differential gene expression provide lists of candidate genes having, individually, a sufficiently low p-value. However, the interpretation of each single p-value within complex systems involving several interacting genes is problematic. In parallel, in the last sixty years, game theory has been applied to political and social problems to assess the power of interacting agents in forcing a decision and, more recently, to represent the relevance of genes in response to certain conditions. Results In this paper we introduce a Bootstrap procedure to test the null hypothesis that each gene has the same relevance between two conditions, where the relevance is represented by the Shapley value of a particular coalitional game defined on a microarray data-set. This method, which is called Comparative Analysis of Shapley value (shortly, CASh), is applied to data concerning the gene expression in children differentially exposed to air pollution. The results provided by CASh are compared with the results from a parametric statistical test for testing differential gene expression. Both lists of genes provided by CASh and t-test are informative enough to discriminate exposed subjects on the basis of their gene expression profiles. While many genes are selected in common by CASh and the parametric test, it turns out that the biological interpretation of the differences between these two selections is more interesting, suggesting a different interpretation of the main biological pathways in gene expression regulation for exposed individuals. A simulation study suggests that CASh offers more power than t-test for the detection of differential gene expression variability. Conclusion CASh is successfully applied to gene expression analysis of a data-set where the joint expression behavior of genes may be critical to characterize the expression response to air pollution. We demonstrate a synergistic effect between coalitional games and statistics that resulted in a selection of genes with a potential impact in the regulation of complex pathways. PMID:18764936

Clinical Characteristics of Patients With Renal Cell Carcinoma and Metastasis to the Thyroid Gland.

PubMed

Jackson, Gregory; Fino, Nora; Bitting, Rhonda L

2017-01-01

Renal cell carcinoma (RCC) is the most common malignancy to metastasize to the thyroid gland. The aims of this study are as follows: (1) to analyze the clinical characteristics of patients with thyroid involvement of RCC and (2) in patients with RCC thyroid metastasis, to determine whether RCC metastasis to glandular organs only portends a better prognosis compared with other patterns of RCC metastasis. Patients from Wake Forest Baptist Medical Center (WFBMC) diagnosed with thyroid metastasis from RCC were identified and medical records retrospectively examined. A systematic review of the literature for cases of RCC involving the thyroid gland was also performed. The clinical characteristics of the institutional cohort and the cases from the literature review were compared. Descriptive statistical analysis was performed, and overall survival (OS) was summarized using Kaplan-Meier methods. The median OS for the WFBMC cohort was 56.4 months. In the literature review cohort, OS of patients with RCC thyroid metastasis was 213.6 months, and there was no statistically significant survival difference based on the site of metastasis. Median survival after thyroid metastasis from RCC for the WFBMC and literature cohort was 21.6 and 45.6 months, respectively. Metastatic RCC should be included in the differential of a new thyroid mass. Treatment directed at the thyroid metastasis results in prolonged survival in some cases. Further analysis into the genomic differences and mechanisms of thyroid metastasis is warranted.

Two-year quality of life after free flap reconstruction in tumor-site discrepancy among Taiwanese with moderately advanced oral squamous cell carcinoma.

PubMed

Chang, Kao-Ping; Lai, Chung-Sheng; Hsieh, Tung-Ying; Wu, Yi-Chia; Chang, Chih-Hau

2012-07-13

This study describes 2-year impact on quality of life (QOL) in relation to the anatomical discrepancy among T4a oral cancer patients after free flap reconstruction in Taiwan. Thirty-two patients who underwent tumor ablation with simultaneous microvascular free flap transfer at 2-year follow-up were recruited. They were divided into six subgroups, according to the resected area, consisting of: (1) buccal/retromolar trigone; (2) cheek; (3) commissure; (4) lip; (5) mandible; and (6) tongue. Functional disturbances and daily activity were analyzed using the Version-1 UW QOL Questionnaire with one more specific category: 'Drooling'. Kruskal-Wallis rank sums analysis was used to test differences in average QOL scores between these subgroups. Post-hoc analysis was applied to assess influence of dominant categories between subgroups. The category 'Pain' revealed the highest average score and reached significant statistical difference (P = 0.019) among all the categories, however, the category 'Employment' averaged the lowest score. Regarding 'Pain', there existed a statistical significance (P = 0.0032) between the commissure- and cheek-involved groups, which described the former showed poorer pain quality of life. The commissure-involved group had the lowest average score, which might imply the worst QOL in our study, especially for the categories 'Pain' and 'Drooling'. This present study of T4a patients was the first carried out in Taiwan implementing the QOL questionnaire, and its results may serve for future reference.

Copy number variation in ALOX5 and PTGER1 is associated with NSAIDs-induced urticaria and/or angioedema.

PubMed

Plaza-Serón, María Del Carmen; Ayuso, Pedro; Pérez-Sánchez, Natalia; Doña, Inmaculada; Blanca-Lopez, Natalia; Flores, Carlos; Galindo, Luisa; Molina, Ana; Perkins, James R; Cornejo-García, Jose A; Agúndez, Jose A; García-Martín, Elena; Campo, Paloma; Canto, Gabriela; Blanca, Miguel

2016-06-01

Cross-intolerance to NSAIDs is a class of drug hypersensitivity reaction, of which NSAIDs-induced urticaria and/or angioedema (NIUA) are the most frequent clinical entities. They are considered to involve dysregulation of the arachidonic acid pathway; however, this mechanism has not been confirmed for NIUA. In this work, we assessed copy number variations (CNVs) in eight of the main genes involved in the arachidonic acid pathway and their possible genetic association with NIUA. CNVs in ALOX5, LTC4S, PTGS1, PTGS2, PTGER1, PTGER2, PTGER3, and PTGER4 were analyzed using TaqMan copy number assays. Genotyping was carried out by real-time quantitative PCR. Individual genotypes were assigned using the CopyCaller Software. Statistical analysis was carried out using GraphPad prism 5, PLINK, EPIDAT, and R version 3.1.2. A total of 151 cases and 139 controls were analyzed during the discovery phase and 148 cases and 140 controls were used for replication. CNVs in open reading frames were found for ALOX5, PTGER1, PTGER3, and PTGER4. Statistically significant differences in the CNV frequency between NIUA and controls were found for ALOX5 (Pc=0.017) and PTGER1 (Pc=1.22E-04). This study represents the first analysis showing an association between CNVs in exonic regions of ALOX5 and PTGER1 and NIUA. This suggests a role of CNVs in this pathology that should be explored further.

Formalized Conflicts Detection Based on the Analysis of Multiple Emails: An Approach Combining Statistics and Ontologies

NASA Astrophysics Data System (ADS)

Zakaria, Chahnez; Curé, Olivier; Salzano, Gabriella; Smaïli, Kamel

In Computer Supported Cooperative Work (CSCW), it is crucial for project leaders to detect conflicting situations as early as possible. Generally, this task is performed manually by studying a set of documents exchanged between team members. In this paper, we propose a full-fledged automatic solution that identifies documents, subjects and actors involved in relational conflicts. Our approach detects conflicts in emails, probably the most popular type of documents in CSCW, but the methods used can handle other text-based documents. These methods rely on the combination of statistical and ontological operations. The proposed solution is decomposed in several steps: (i) we enrich a simple negative emotion ontology with terms occuring in the corpus of emails, (ii) we categorize each conflicting email according to the concepts of this ontology and (iii) we identify emails, subjects and team members involved in conflicting emails using possibilistic description logic and a set of proposed measures. Each of these steps are evaluated and validated on concrete examples. Moreover, this approach's framework is generic and can be easily adapted to domains other than conflicts, e.g. security issues, and extended with operations making use of our proposed set of measures.

Lexical statistics of competition in L2 versus L1 listening

NASA Astrophysics Data System (ADS)

Cutler, Anne

2005-09-01

Spoken-word recognition involves multiple activation of alternative word candidates and competition between these alternatives. Phonemic confusions in L2 listening increase the number of potentially active words, thus slowing word recognition by adding competitors. This study used a 70,000-word English lexicon backed by frequency statistics from a 17,900,000-word corpus to assess the competition increase resulting from two representative phonemic confusions, one vocalic (ae/E) and one consonantal (r/l), in L2 versus L1 listening. The first analysis involved word embedding. Embedded words (cat in cattle, rib in ribbon) cause competition, which phonemic confusion can increase (cat in kettle, rib in liberty). The average increase in number of embedded words was 59.6 and 48.3 temporary ambiguity. Even when no embeddings are present, multiple alternatives are possible: para- can become parrot, paradise, etc., but also pallet, palace given /r/-/l/ confusion. Phoneme confusions (vowel or consonant) in first or second position in the word approximately doubled the number of activated candidates; confusions later in the word increased activation by on average 53 third, 42 confusions significantly increase competition for L2 compared with L1 listeners.

Relationship of nurses' intrapersonal characteristics with work performance and caring behaviors: A cross-sectional study.

PubMed

Geyer, Nelouise-Marié; Coetzee, Siedine K; Ellis, Suria M; Uys, Leana R

2018-02-28

This study aimed to describe intrapersonal characteristics (professional values, personality, empathy, and job involvement), work performance as perceived by nurses, and caring behaviors as perceived by patients, and to examine the relationships among these variables. A cross-sectional design was employed. A sample was recruited of 218 nurses and 116 patients in four private hospitals and four public hospitals. Data were collected using self-report measures. Data analysis included descriptive statistics, exploratory and confirmatory factor analyses, hierarchical linear modelling, correlations, and structural equation modeling. Nurses perceived their work performance to be of high quality. Among the intrapersonal characteristics, nurses had high scores for professional values, and moderately high scores for personality, empathy and job involvement. Patients perceived nurses' caring behaviors as moderately high. Professional values of nurses were the only selected intrapersonal characteristic with a statistically significant positive relationship, of practical importance, with work performance as perceived by nurses and with caring behaviors as perceived by patients at ward level. Managers can enhance nurses' work performance and caring behaviors through provision of in-service training that focuses on development of professional values. © 2018 John Wiley & Sons Australia, Ltd.

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

Analysis of longitudinal "time series" data in toxicology.

PubMed

Cox, C; Cory-Slechta, D A

1987-02-01

Studies focusing on chronic toxicity or on the time course of toxicant effect often involve repeated measurements or longitudinal observations of endpoints of interest. Experimental design considerations frequently necessitate between-group comparisons of the resulting trends. Typically, procedures such as the repeated-measures analysis of variance have been used for statistical analysis, even though the required assumptions may not be satisfied in some circumstances. This paper describes an alternative analytical approach which summarizes curvilinear trends by fitting cubic orthogonal polynomials to individual profiles of effect. The resulting regression coefficients serve as quantitative descriptors which can be subjected to group significance testing. Randomization tests based on medians are proposed to provide a comparison of treatment and control groups. Examples from the behavioral toxicology literature are considered, and the results are compared to more traditional approaches, such as repeated-measures analysis of variance.

A meta-analysis of aneurysm formation in laser assisted vascular anastomosis (LAVA)

NASA Astrophysics Data System (ADS)

Chen, Chen; Peng, Fei; Xu, Dahai; Cheng, Qinghua

2009-08-01

Laser assisted vascular anastomosis (LAVA) is looked as a particularly promising non-suture method in future. However, aneurysm formation is one of the main reasons delay the clinical application of LAVA. Some scientists investigated the incidence of aneurysms in animal model. To systematically analyze the literature on reported incidence of aneurysm formation in LAVA therapy, we performed a meta-analysis comparing LAVA with conventional suture anastomosis (CSA) in animal model. Data were systematically retrieved and selected from PUBMED. In total, 23 studies were retrieved. 18 studies were excluded, and 5 studies involving 647 animals were included. Analysis suggested no statistically significant difference between LAVA and CSA (OR 1.24, 95%CI 0.66-2.32, P=0.51). Result of meta analysis shows that the technology of LAVA is very close to clinical application.

Statistical principle and methodology in the NISAN system.

PubMed Central

Asano, C

1979-01-01

The NISAN system is a new interactive statistical analysis program package constructed by an organization of Japanese statisticans. The package is widely available for both statistical situations, confirmatory analysis and exploratory analysis, and is planned to obtain statistical wisdom and to choose optimal process of statistical analysis for senior statisticians. PMID:540594

Intramedullary nailing versus plating for distal tibia fractures without articular involvement: a meta-analysis.

PubMed

Mao, Zhi; Wang, Guoqi; Zhang, Lihai; Zhang, Licheng; Chen, Shuo; Du, Hailong; Zhao, Yanpeng; Tang, Peifu

2015-06-16

The choice between intramedullary (IM) nailing or plating of distal tibia fractures without articular involvement remains controversial. A meta-analysis of randomized controlled trials (RCTs) and observational studies was performed to compare IM nailing with plating for distal tibia fractures without articular involvement and to determine the dominant strategy. The PubMed, Embase, Cochrane Library databases, Chinese Wan-Fang Database, and China National Knowledge Infrastructure were searched. Twenty-eight studies, which included 1863 fractures, met the eligible criteria. The meta-analysis did not identify a statistically significant difference between the two treatments in terms of the rate of deep infection, delayed union, removal of instrumentation, or secondary procedures either in the RCT or retrospective subgroups. IM nailing was associated with significantly more malunion events and a higher incidence of knee pain in the retrospective subgroup and across all the studies, but not significantly in the RCT subgroup, and a lower rate of delayed wound healing and superficial infection both in the RCT and retrospective subgroups relative to plating. A meta-analysis of the functional scores or questionnaires was not possible because of the considerable variation among the included studies, and no significant differences were observed. Evidence suggests that both IM nailing and plating are appropriate treatments as IM nailing shows lower rate of delayed wound healing and superficial infection and plating may avoid malunion and knee pain. These findings should be interpreted with caution, however, because of the heterogeneity of the study designs. Large, rigorous RCTs are required.

Design of a Web-tool for diagnostic clinical trials handling medical imaging research.

PubMed

Baltasar Sánchez, Alicia; González-Sistal, Angel

2011-04-01

New clinical studies in medicine are based on patients and controls using different imaging diagnostic modalities. Medical information systems are not designed for clinical trials employing clinical imaging. Although commercial software and communication systems focus on storage of image data, they are not suitable for storage and mining of new types of quantitative data. We sought to design a Web-tool to support diagnostic clinical trials involving different experts and hospitals or research centres. The image analysis of this project is based on skeletal X-ray imaging. It involves a computerised image method using quantitative analysis of regions of interest in healthy bone and skeletal metastases. The database is implemented with ASP.NET 3.5 and C# technologies for our Web-based application. For data storage, we chose MySQL v.5.0, one of the most popular open source databases. User logins were necessary, and access to patient data was logged for auditing. For security, all data transmissions were carried over encrypted connections. This Web-tool is available to users scattered at different locations; it allows an efficient organisation and storage of data (case report form) and images and allows each user to know precisely what his task is. The advantages of our Web-tool are as follows: (1) sustainability is guaranteed; (2) network locations for collection of data are secured; (3) all clinical information is stored together with the original images and the results derived from processed images and statistical analysis that enable us to perform retrospective studies; (4) changes are easily incorporated because of the modular architecture; and (5) assessment of trial data collected at different sites is centralised to reduce statistical variance.

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Rayner, Nick

2017-04-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-June 2018, https://www.eustaceproject.eu) we are developing an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. As the data volumes involved are considerable, such work needs to include development of new "Big Data" analysis methods. We will present recent progress along this road in the EUSTACE project: 1. providing new, consistent, multi-component estimates of uncertainty in surface skin temperature retrievals from satellites; 2. identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; 3. estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; 4. using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Ghent, D.; Rayner, N. A.

2016-12-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-June 2018, https://www.eustaceproject.eu) we are developing an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. As the data volumes involved are considerable, such work needs to include development of new "Big Data" analysis methods. We will present recent progress along this road in the EUSTACE project, i.e.: • providing new, consistent, multi-component estimates of uncertainty in surface skin temperature retrievals from satellites; • identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; • estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; • using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

Structural equation modeling assessing relationship between mathematics beliefs, teachers' attitudes and teaching practices among novice teachers in Malaysia

NASA Astrophysics Data System (ADS)

Borhan, Noziati; Zakaria, Effandi

2017-05-01

This quantitative study was conducted to investigate the perception level of novice teachers about mathematics belief, teachers' attitude towards mathematics and teaching practices of mathematics in the classroom. In addition, it also aims to identify whether there is a correspondence model with the data obtained and to identify the relationship between the variables of beliefs, attitudes and practices among novice teachers in Malaysia. A total of 263 primary novice teachers throughout the country were involved in this study were selected randomly. Respondents are required to provide a response to the questionnaire of 66 items related to mathematics beliefs, attitudes and practices of the teaching mathematics. There are ten sub-factors which have been established in this instrument for three major constructs using a Likert scale rating of five points. The items of the constructs undergo the exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) procedure involve of unidimensionality test, convergent validity, construct validity and discriminant validity. Descriptive statistics were used to describe the frequency, percentage, the mean and standard deviation for completing some research questions that have been expressed. As for inferential statistical analysis, the researchers used structural equation modeling (SEM) to answer the question of correspondents model and the relationship between these three variables. The results of the study were found that there exist a correspondence measurement and structural model with the data obtained. While the relationship between variable found that mathematics beliefs have a significant influence on teachers' attitudes towards mathematics as well as the relationship between the attitudes with teaching practices. Meanwhile, mathematics belief had no significant relationship with mathematics teaching practices among novice teachers in Malaysia.

Time-Domain Microfluidic Fluorescence Lifetime Flow Cytometry for High-Throughput Förster Resonance Energy Transfer Screening

PubMed Central

Nedbal, Jakub; Visitkul, Viput; Ortiz-Zapater, Elena; Weitsman, Gregory; Chana, Prabhjoat; Matthews, Daniel R; Ng, Tony; Ameer-Beg, Simon M

2015-01-01

Sensing ion or ligand concentrations, physico-chemical conditions, and molecular dimerization or conformation change is possible by assays involving fluorescent lifetime imaging. The inherent low throughput of imaging impedes rigorous statistical data analysis on large cell numbers. We address this limitation by developing a fluorescence lifetime-measuring flow cytometer for fast fluorescence lifetime quantification in living or fixed cell populations. The instrument combines a time-correlated single photon counting epifluorescent microscope with microfluidics cell-handling system. The associated computer software performs burst integrated fluorescence lifetime analysis to assign fluorescence lifetime, intensity, and burst duration to each passing cell. The maximum safe throughput of the instrument reaches 3,000 particles per minute. Living cells expressing spectroscopic rulers of varying peptide lengths were distinguishable by Förster resonant energy transfer measured by donor fluorescence lifetime. An epidermal growth factor (EGF)-stimulation assay demonstrated the technique's capacity to selectively quantify EGF receptor phosphorylation in cells, which was impossible by measuring sensitized emission on a standard flow cytometer. Dual-color fluorescence lifetime detection and cell-specific chemical environment sensing were exemplified using di-4-ANEPPDHQ, a lipophilic environmentally sensitive dye that exhibits changes in its fluorescence lifetime as a function of membrane lipid order. To our knowledge, this instrument opens new applications in flow cytometry which were unavailable due to technological limitations of previously reported fluorescent lifetime flow cytometers. The presented technique is sensitive to lifetimes of most popular fluorophores in the 0.5–5 ns range including fluorescent proteins and is capable of detecting multi-exponential fluorescence lifetime decays. This instrument vastly enhances the throughput of experiments involving fluorescence lifetime measurements, thereby providing statistically significant quantitative data for analysis of large cell populations. © 2014 International Society for Advancement of Cytometry PMID:25523156

A meta-analysis of experimental studies of diversion programs for juvenile offenders.

PubMed

Schwalbe, Craig S; Gearing, Robin E; MacKenzie, Michael J; Brewer, Kathryne B; Ibrahim, Rawan

2012-02-01

Research to establish an evidence-base for the treatment of conduct problems and delinquency in adolescence is well established; however, an evidence-base for interventions with offenders who are diverted from the juvenile justice system has yet to be synthesized. The purpose of this study was to conduct a meta-analysis of experimental studies testing juvenile diversion programs and to examine the moderating effect of program type and implementation quality. A literature search using PsycINFO, Web of Science, and the National Criminal Justice Reference Service data-bases and research institute websites yielded 28 eligible studies involving 57 experimental comparisons and 19,301 youths. Recidivism was the most common outcome reported across all studies. Overall, the effect of diversion programs on recidivism was non-significant (k=45, OR=0.83, 95%CI=0.43-1.58). Of the five program types identified, including case management (k=18, OR=0.78), individual treatment (k=11, OR=0.83), family treatment (k=4, OR=0.57), youth court (k=6, OR=0.93), and restorative justice (k=6, OR=0.87), only family treatment led to a statistically significant reduction in recidivism. Restorative justice studies that were implemented with active involvement of researchers led to statistically significant reductions in recidivism (k=3, OR=0.69). Other outcomes, including frequency of offending, truancy, and psycho-social problems were reported infrequently and were not subjected to meta-analysis. High levels of heterogeneity characterize diversion research. Results of this study recommend against implementation of programs limited to case management and highlight the promise of family interventions and restorative justice. Copyright © 2011 Elsevier Ltd. All rights reserved.

Psychopathological Symptoms and Psychological Wellbeing in Mexican Undergraduate Students

PubMed Central

Contreras, Mariel; de León, Ana Mariela; Martínez, Estela; Peña, Elsa Melissa; Marques, Luana; Gallegos, Julia

2017-01-01

College life involves a process of adaptation to changes that have an impact on the psycho-emotional development of students. Successful adaptation to this stage involves the balance between managing personal resources and potential stressors that generate distress. This epidemiological descriptive and transversal study estimates the prevalence of psychopathological symptomatology and psychological well-being among 516 college students, 378 (73.26%) women and 138 (26.74%) men, ages between 17 and 24, from the city of Monterrey in Mexico. It describes the relationship between psychopathological symptomatology and psychological well-being, and explores gender differences. For data collection, two measures were used: The Symptom Checklist Revised and the Scale of Psychological Well-being. Statistical analyses used were t test for independent samples, Pearson’s r and regression analysis with the Statistical Package for the Social Sciences (SPSS v21.0). Statistical analyses showed that the prevalence of psychopathological symptoms was 10–13%, being Aggression the highest. The dimension of psychological well-being with the lowest scores was Environmental Mastery. Participants with a higher level of psychological well-being had a lower level of psychopathological symptoms, which shows the importance of early identification and prevention. Gender differences were found on some subscales of the psychopathological symptomatology and of the psychological well-being measures. This study provides a basis for future research and development of resources to promote the psychological well-being and quality of life of university students. PMID:29104876

Clinical and histopathologic independent prognostic factors in oral squamous cell carcinoma: a retrospective study of 334 cases.

PubMed

Arduino, Paolo G; Carrozzo, Marco; Chiecchio, Andrea; Broccoletti, Roberto; Tirone, Federico; Borra, Eleonora; Bertolusso, Giorgio; Gandolfo, Sergio

2008-08-01

This retrospective hospital-based study reviewed and evaluated the outcome of patients with oral squamous cell carcinoma (OSCC) with the aim of identifying factors affecting the clinical course and survival rate. Patients with a follow-up of at least 12 months were included. The data collected were statistically analyzed for the presence of factors valuable for prognosis; survival curves were processed in accordance with the Kaplan-Meier method. Differences in the expression of variables in different grading levels were investigated. Cox's proportional hazard model for Z(i) covariates (grading, age, T, N) also was calculated. Mean patient age was 67.7 years in women (n = 152) and 62.4 years in men (n = 182). A total of 98 patients were identified with Broder's/World Health Organization grade 1 histology, 176 with grade 2, and 55 with grade 3; 5 patients were identified as grade 4 (carcinoma in situ). Gender and risk factors seemed to be unrelated to prognosis, whereas a significant increase in mortality was seen in patients over age 70. Histological grading, tumor size, and neck involvement were related, as independent factors, in predicting survival in patients with OSCC (QM-H > 3.9). Gender, age, and risk factors had no statistical relationship with cancer histological differentiation. Our analysis reveals a statistically significant relationship among histological Broder's grading of malignancy, tumor size, locoregional involvement, and survival rates, underscoring the utility of tumor differentiation in predicting the clinical course and outcome of OSCC.

Face recognition using an enhanced independent component analysis approach.

PubMed

Kwak, Keun-Chang; Pedrycz, Witold

2007-03-01

This paper is concerned with an enhanced independent component analysis (ICA) and its application to face recognition. Typically, face representations obtained by ICA involve unsupervised learning and high-order statistics. In this paper, we develop an enhancement of the generic ICA by augmenting this method by the Fisher linear discriminant analysis (LDA); hence, its abbreviation, FICA. The FICA is systematically developed and presented along with its underlying architecture. A comparative analysis explores four distance metrics, as well as classification with support vector machines (SVMs). We demonstrate that the FICA approach leads to the formation of well-separated classes in low-dimension subspace and is endowed with a great deal of insensitivity to large variation in illumination and facial expression. The comprehensive experiments are completed for the facial-recognition technology (FERET) face database; a comparative analysis demonstrates that FICA comes with improved classification rates when compared with some other conventional approaches such as eigenface, fisherface, and the ICA itself.

A Bayesian approach to meta-analysis of plant pathology studies.

PubMed

Mila, A L; Ngugi, H K

2011-01-01

Bayesian statistical methods are used for meta-analysis in many disciplines, including medicine, molecular biology, and engineering, but have not yet been applied for quantitative synthesis of plant pathology studies. In this paper, we illustrate the key concepts of Bayesian statistics and outline the differences between Bayesian and classical (frequentist) methods in the way parameters describing population attributes are considered. We then describe a Bayesian approach to meta-analysis and present a plant pathological example based on studies evaluating the efficacy of plant protection products that induce systemic acquired resistance for the management of fire blight of apple. In a simple random-effects model assuming a normal distribution of effect sizes and no prior information (i.e., a noninformative prior), the results of the Bayesian meta-analysis are similar to those obtained with classical methods. Implementing the same model with a Student's t distribution and a noninformative prior for the effect sizes, instead of a normal distribution, yields similar results for all but acibenzolar-S-methyl (Actigard) which was evaluated only in seven studies in this example. Whereas both the classical (P = 0.28) and the Bayesian analysis with a noninformative prior (95% credibility interval [CRI] for the log response ratio: -0.63 to 0.08) indicate a nonsignificant effect for Actigard, specifying a t distribution resulted in a significant, albeit variable, effect for this product (CRI: -0.73 to -0.10). These results confirm the sensitivity of the analytical outcome (i.e., the posterior distribution) to the choice of prior in Bayesian meta-analyses involving a limited number of studies. We review some pertinent literature on more advanced topics, including modeling of among-study heterogeneity, publication bias, analyses involving a limited number of studies, and methods for dealing with missing data, and show how these issues can be approached in a Bayesian framework. Bayesian meta-analysis can readily include information not easily incorporated in classical methods, and allow for a full evaluation of competing models. Given the power and flexibility of Bayesian methods, we expect them to become widely adopted for meta-analysis of plant pathology studies.

Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses.

PubMed

Liu, Ruijie; Holik, Aliaksei Z; Su, Shian; Jansz, Natasha; Chen, Kelan; Leong, Huei San; Blewitt, Marnie E; Asselin-Labat, Marie-Liesse; Smyth, Gordon K; Ritchie, Matthew E

2015-09-03

Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean-variance relationship of the log-counts-per-million using 'voom'. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source 'limma' package. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Statistical analysis of native contact formation in the folding of designed model proteins

NASA Astrophysics Data System (ADS)

Tiana, Guido; Broglia, Ricardo A.

2001-02-01

The time evolution of the formation probability of native bonds has been studied for designed sequences which fold fast into the native conformation. From this analysis a clear hierarchy of bonds emerge: (a) local, fast forming highly stable native bonds built by some of the most strongly interacting amino acids of the protein; (b) nonlocal bonds formed late in the folding process, in coincidence with the folding nucleus, and involving essentially the same strongly interacting amino acids already participating in the fast bonds; (c) the rest of the native bonds whose behavior is subordinated, to a large extent, to that of the strong local and nonlocal native contacts.

Inactivation disinfection property of Moringa Oleifera seed extract: optimization and kinetic studies

NASA Astrophysics Data System (ADS)

Idris, M. A.; Jami, M. S.; Hammed, A. M.

2017-05-01

This paper presents the statistical optimization study of disinfection inactivation parameters of defatted Moringa oleifera seed extract on Pseudomonas aeruginosa bacterial cells. Three level factorial design was used to estimate the optimum range and the kinetics of the inactivation process was also carried. The inactivation process involved comparing different disinfection models of Chicks-Watson, Collins-Selleck and Homs models. The results from analysis of variance (ANOVA) of the statistical optimization process revealed that only contact time was significant. The optimum disinfection range of the seed extract was 125 mg/L, 30 minutes and 120rpm agitation. At the optimum dose, the inactivation kinetics followed the Collin-Selleck model with coefficient of determination (R2) of 0.6320. This study is the first of its kind in determining the inactivation kinetics of pseudomonas aeruginosa using the defatted seed extract.

Usefulness and limitations of various guinea-pig test methods in detecting human skin sensitizers-validation of guinea-pig tests for skin hypersensitivity.

PubMed

Marzulli, F; Maguire, H C

1982-02-01

Several guinea-pig predictive test methods were evaluated by comparison of results with those obtained with human predictive tests, using ten compounds that have been used in cosmetics. The method involves the statistical analysis of the frequency with which guinea-pig tests agree with the findings of tests in humans. In addition, the frequencies of false positive and false negative predictive findings are considered and statistically analysed. The results clearly demonstrate the superiority of adjuvant tests (complete Freund's adjuvant) in determining skin sensitizers and the overall superiority of the guinea-pig maximization test in providing results similar to those obtained by human testing. A procedure is suggested for utilizing adjuvant and non-adjuvant test methods for characterizing compounds as of weak, moderate or strong sensitizing potential.

Clinical competence of Guatemalan and Mexican physicians for family dysfunction management.

PubMed

Cabrera-Pivaral, Carlos Enrique; Orozco-Valerio, María de Jesús; Celis-de la Rosa, Alfredo; Covarrubias-Bermúdez, María de Los Ángeles; Zavala-González, Marco Antonio

2017-01-01

To evaluate the clinical competence of Mexican and Guatemalan physicians to management the family dysfunction. Cross comparative study in four care units first in Guadalajara, Mexico, and four in Guatemala, Guatemala, based on a purposeful sampling, involving 117 and 100 physicians, respectively. Clinical competence evaluated by validated instrument integrated for 187 items. Non-parametric descriptive and inferential statistical analysis was performed. The percentage of Mexican physicians with high clinical competence was 13.7%, medium 53%, low 24.8% and defined by random 8.5%. For the Guatemalan physicians'14% was high, average 63%, and 23% defined by random. There were no statistically significant differences between healthcare country units, but between the medium of Mexicans (0.55) and Guatemalans (0.55) (p = 0.02). The proportion of the high clinical competency of Mexican physicians' was as Guatemalans.

RCT: Module 2.03, Counting Errors and Statistics, Course 8768

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

Hillmer, Kurt T.

2017-04-01

Radiological sample analysis involves the observation of a random process that may or may not occur and an estimation of the amount of radioactive material present based on that observation. Across the country, radiological control personnel are using the activity measurements to make decisions that may affect the health and safety of workers at those facilities and their surrounding environments. This course will present an overview of measurement processes, a statistical evaluation of both measurements and equipment performance, and some actions to take to minimize the sources of error in count room operations. This course will prepare the student withmore » the skills necessary for radiological control technician (RCT) qualification by passing quizzes, tests, and the RCT Comprehensive Phase 1, Unit 2 Examination (TEST 27566) and by providing in the field skills.« less

Applying Sociocultural Theory to Teaching Statistics for Doctoral Social Work Students

ERIC Educational Resources Information Center

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

2015-01-01

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

Wavelet Transform Based Higher Order Statistical Analysis of Wind and Wave Time Histories

NASA Astrophysics Data System (ADS)

Habib Huseni, Gulamhusenwala; Balaji, Ramakrishnan

2017-10-01

Wind, blowing on the surface of the ocean, imparts the energy to generate the waves. Understanding the wind-wave interactions is essential for an oceanographer. This study involves higher order spectral analyses of wind speeds and significant wave height time histories, extracted from European Centre for Medium-Range Weather Forecast database at an offshore location off Mumbai coast, through continuous wavelet transform. The time histories were divided by the seasons; pre-monsoon, monsoon, post-monsoon and winter and the analysis were carried out to the individual data sets, to assess the effect of various seasons on the wind-wave interactions. The analysis revealed that the frequency coupling of wind speeds and wave heights of various seasons. The details of data, analysing technique and results are presented in this paper.

Thrust imbalance of solid rocket motor pairs on Space Shuttle flights

NASA Technical Reports Server (NTRS)

Foster, W. A., Jr.; Shu, P. H.; Sforzini, R. H.

1986-01-01

This analysis extends the investigation presented at the 17th Joint Propulsion Conference in 1981 to include fifteen sets of Space Shuttle flight data. The previous report dealt only with static test data and the first flight pair. The objective is to compare the authors' previous theoretical analysis of thrust imbalance with actual Space Shuttle performance. The theoretical prediction method, which involves a Monte Carlo technique, is reviewed briefly as are salient features of the flight instrumentation system and the statistical analysis. A scheme for smoothing flight data is discussed. The effects of changes in design parameters are discussed with special emphasis on the filament wound motor case being developed to replace the steel case. Good agreement between the predictions and the flight data is demonstrated.

White matter involvement in sporadic Creutzfeldt-Jakob disease

PubMed Central

Mandelli, Maria Luisa; DeArmond, Stephen J.; Hess, Christopher P.; Vitali, Paolo; Papinutto, Nico; Oehler, Abby; Miller, Bruce L.; Lobach, Irina V.; Bastianello, Stefano; Geschwind, Michael D.; Henry, Roland G.

2014-01-01

Sporadic Creutzfeldt-Jakob disease is considered primarily a disease of grey matter, although the extent of white matter involvement has not been well described. We used diffusion tensor imaging to study the white matter in sporadic Creutzfeldt-Jakob disease compared to healthy control subjects and to correlated magnetic resonance imaging findings with histopathology. Twenty-six patients with sporadic Creutzfeldt-Jakob disease and nine age- and gender-matched healthy control subjects underwent volumetric T1-weighted and diffusion tensor imaging. Six patients had post-mortem brain analysis available for assessment of neuropathological findings associated with prion disease. Parcellation of the subcortical white matter was performed on 3D T1-weighted volumes using Freesurfer. Diffusion tensor imaging maps were calculated and transformed to the 3D-T1 space; the average value for each diffusion metric was calculated in the total white matter and in regional volumes of interest. Tract-based spatial statistics analysis was also performed to investigate the deeper white matter tracts. There was a significant reduction of mean (P = 0.002), axial (P = 0.0003) and radial (P = 0.0134) diffusivities in the total white matter in sporadic Creutzfeldt-Jakob disease. Mean diffusivity was significantly lower in most white matter volumes of interest (P < 0.05, corrected for multiple comparisons), with a generally symmetric pattern of involvement in sporadic Creutzfeldt-Jakob disease. Mean diffusivity reduction reflected concomitant decrease of both axial and radial diffusivity, without appreciable changes in white matter anisotropy. Tract-based spatial statistics analysis showed significant reductions of mean diffusivity within the white matter of patients with sporadic Creutzfeldt-Jakob disease, mainly in the left hemisphere, with a strong trend (P = 0.06) towards reduced mean diffusivity in most of the white matter bilaterally. In contrast, by visual assessment there was no white matter abnormality either on T2-weighted or diffusion-weighted images. Widespread reduction in white matter mean diffusivity, however, was apparent visibly on the quantitative attenuation coefficient maps compared to healthy control subjects. Neuropathological analysis showed diffuse astrocytic gliosis and activated microglia in the white matter, rare prion deposition and subtle subcortical microvacuolization, and patchy foci of demyelination with no evident white matter axonal degeneration. Decreased mean diffusivity on attenuation coefficient maps might be associated with astrocytic gliosis. We show for the first time significant global reduced mean diffusivity within the white matter in sporadic Creutzfeldt-Jakob disease, suggesting possible primary involvement of the white matter, rather than changes secondary to neuronal degeneration/loss. PMID:25367029

Sensitivity analysis of limit state functions for probability-based plastic design

NASA Technical Reports Server (NTRS)

Frangopol, D. M.

1984-01-01

The evaluation of the total probability of a plastic collapse failure P sub f for a highly redundant structure of random interdependent plastic moments acted on by random interdepedent loads is a difficult and computationally very costly process. The evaluation of reasonable bounds to this probability requires the use of second moment algebra which involves man statistical parameters. A computer program which selects the best strategy for minimizing the interval between upper and lower bounds of P sub f is now in its final stage of development. The relative importance of various uncertainties involved in the computational process on the resulting bounds of P sub f, sensitivity is analyzed. Response sensitivities for both mode and system reliability of an ideal plastic portal frame are shown.

Automated Statistical Forecast Method to 36-48H ahead of Storm Wind and Dangerous Precipitation at the Mediterranean Region

NASA Astrophysics Data System (ADS)

Perekhodtseva, E. V.

2009-09-01

Development of successful method of forecast of storm winds, including squalls and tornadoes and heavy rainfalls, that often result in human and material losses, could allow one to take proper measures against destruction of buildings and to protect people. Well-in-advance successful forecast (from 12 hours to 48 hour) makes possible to reduce the losses. Prediction of the phenomena involved is a very difficult problem for synoptic till recently. The existing graphic and calculation methods still depend on subjective decision of an operator. Nowadays in Russia there is no hydrodynamic model for forecast of the maximal precipitation and wind velocity V> 25m/c, hence the main tools of objective forecast are statistical methods using the dependence of the phenomena involved on a number of atmospheric parameters (predictors). Statistical decisive rule of the alternative and probability forecast of these events was obtained in accordance with the concept of "perfect prognosis" using the data of objective analysis. For this purpose the different teaching samples of present and absent of this storm wind and rainfalls were automatically arranged that include the values of forty physically substantiated potential predictors. Then the empirical statistical method was used that involved diagonalization of the mean correlation matrix R of the predictors and extraction of diagonal blocks of strongly correlated predictors. Thus for these phenomena the most informative predictors were selected without loosing information. The statistical decisive rules for diagnosis and prognosis of the phenomena involved U(X) were calculated for choosing informative vector-predictor. We used the criterion of distance of Mahalanobis and criterion of minimum of entropy by Vapnik-Chervonenkis for the selection predictors. Successful development of hydrodynamic models for short-term forecast and improvement of 36-48h forecasts of pressure, temperature and others parameters allowed us to use the prognostic fields of those models for calculations of the discriminant functions in the nodes of the grid 150x150km and the values of probabilities P of dangerous wind and thus to get fully automated forecasts. In order to change to the alternative forecast the author proposes the empirical threshold values specified for this phenomenon and advance period 36 hours. In the accordance to the Pirsey-Obukhov criterion (T), the success of these automated statistical methods of forecast of squalls and tornadoes to 36 -48 hours ahead and heavy rainfalls in the warm season for the territory of Italy, Spain and Balkan countries is T = 1-a-b=0,54: 0,78 after author experiments. A lot of examples of very successful forecasts of summer storm wind and heavy rainfalls over the Italy and Spain territory are submitted at this report. The same decisive rules were applied to the forecast of these phenomena during cold period in this year too. This winter heavy snowfalls in Spain and in Italy and storm wind at this territory were observed very often. And our forecasts are successful.

Conducting indirect-treatment-comparison and network-meta-analysis studies: report of the ISPOR Task Force on Indirect Treatment Comparisons Good Research Practices: part 2.

PubMed

Hoaglin, David C; Hawkins, Neil; Jansen, Jeroen P; Scott, David A; Itzler, Robbin; Cappelleri, Joseph C; Boersma, Cornelis; Thompson, David; Larholt, Kay M; Diaz, Mireya; Barrett, Annabel

2011-06-01

Evidence-based health care decision making requires comparison of all relevant competing interventions. In the absence of randomized controlled trials involving a direct comparison of all treatments of interest, indirect treatment comparisons and network meta-analysis provide useful evidence for judiciously selecting the best treatment(s). Mixed treatment comparisons, a special case of network meta-analysis, combine direct evidence and indirect evidence for particular pairwise comparisons, thereby synthesizing a greater share of the available evidence than traditional meta-analysis. This report from the International Society for Pharmacoeconomics and Outcomes Research Indirect Treatment Comparisons Good Research Practices Task Force provides guidance on technical aspects of conducting network meta-analyses (our use of this term includes most methods that involve meta-analysis in the context of a network of evidence). We start with a discussion of strategies for developing networks of evidence. Next we briefly review assumptions of network meta-analysis. Then we focus on the statistical analysis of the data: objectives, models (fixed-effects and random-effects), frequentist versus Bayesian approaches, and model validation. A checklist highlights key components of network meta-analysis, and substantial examples illustrate indirect treatment comparisons (both frequentist and Bayesian approaches) and network meta-analysis. A further section discusses eight key areas for future research. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Moderate evidence to recommend submucosal injection of dexamethasone in reducing post-operative oedema and pain after third molar extraction.

PubMed

Freda, Nicolas M; Keenan, Analia Veitz

2016-06-01

Data sourcesThe electronic databases searched included: PubMed/MEDLINE, Cochrane Central Register of Controlled Trials (Central) and Web of Science until June 2015. There was no restriction to language and the reference lists from relevant studies were searched for further articles.Study selectionRandomised and prospective controlled trials that compared the effect of submucosal injection of dexamethasone with that of placebo after impacted third molar surgery in humans. Studies involving volunteers with decompensated metabolic disease were excluded.Data extraction and synthesisStudy selection, data extraction and quality assessment (risk of bias) were assessed by two reviewers. All disagreements were resolved through discussion. A meta-analysis was performed for all continuous variables (oedema, pain and trismus) when at least two of the studies analysed the same data type.ResultsEight studies involving a total of 476 patients of which six were included in the meta-analysis. All of the surgical procedures were performed on the lower molars, submucosal injections of dexamethasone were used in concentrations of 4 mg, 8 mg, or 10 mg, and saline was used as a control. Antibiotic medications were administered prophylactically before surgery or by continuous use after the procedure. Seven of the eight studies identified the impactions according to the Pell and Gregory Classification. Oedema was measured using facial contours of pre-established reference points. The meta-analysis presented a mean difference (MD) of -2.20 (95% CI -2.70 to -1.70), with a statistically significant difference favouring dexamethasone (P< 0.00001). Trismus (assessed using inter-incisal distance upon maximum opening) had a MD of -2.92 (95% CI -7.13 to 1.29) and showed no statistically significant difference between groups. Pain was assessed using both visual analogue scales and number of analgesic taken; however, only studies including a VAS were used for meta-analysis. Pain presented with a MD of -1.79 (95% CI -3.28 to -0.30) and showed a statistically significant difference favouring dexamethasone.ConclusionsThe review found moderate quality evidence that submucosal injections of dexamethasone reduced post-operative oedema and pain compared to a placebo following impacted third molar surgery. There was no significant difference, in regards to trismus, between placebo and dexamethasone.

Standardized Effect Sizes for Moderated Conditional Fixed Effects with Continuous Moderator Variables

PubMed Central

Bodner, Todd E.

2017-01-01

Wilkinson and Task Force on Statistical Inference (1999) recommended that researchers include information on the practical magnitude of effects (e.g., using standardized effect sizes) to distinguish between the statistical and practical significance of research results. To date, however, researchers have not widely incorporated this recommendation into the interpretation and communication of the conditional effects and differences in conditional effects underlying statistical interactions involving a continuous moderator variable where at least one of the involved variables has an arbitrary metric. This article presents a descriptive approach to investigate two-way statistical interactions involving continuous moderator variables where the conditional effects underlying these interactions are expressed in standardized effect size metrics (i.e., standardized mean differences and semi-partial correlations). This approach permits researchers to evaluate and communicate the practical magnitude of particular conditional effects and differences in conditional effects using conventional and proposed guidelines, respectively, for the standardized effect size and therefore provides the researcher important supplementary information lacking under current approaches. The utility of this approach is demonstrated with two real data examples and important assumptions underlying the standardization process are highlighted. PMID:28484404

Statistical Analysis of Research Data | Center for Cancer Research

Cancer.gov

Recent advances in cancer biology have resulted in the need for increased statistical analysis of research data. The Statistical Analysis of Research Data (SARD) course will be held on April 5-6, 2018 from 9 a.m.-5 p.m. at the National Institutes of Health's Natcher Conference Center, Balcony C on the Bethesda Campus. SARD is designed to provide an overview on the general principles of statistical analysis of research data.  The first day will feature univariate data analysis, including descriptive statistics, probability distributions, one- and two-sample inferential statistics.

Success rates of a skeletal anchorage system in orthodontics: A retrospective analysis.

PubMed

Lam, Raymond; Goonewardene, Mithran S; Allan, Brent P; Sugawara, Junji

2018-01-01

To evaluate the premise that skeletal anchorage with SAS miniplates are highly successful and predictable for a range of complex orthodontic movements. This retrospective cross-sectional analysis consisted of 421 bone plates placed by one clinician in 163 patients (95 female, 68 male, mean age 29.4 years ± 12.02). Simple descriptive statistics were performed for a wide range of malocclusions and desired movements to obtain success, complication, and failure rates. The success rate of skeletal anchorage system miniplates was 98.6%, where approximately 40% of cases experienced mild complications. The most common complication was soft tissue inflammation, which was amenable to focused oral hygiene and antiseptic rinses. Infection occurred in approximately 15% of patients where there was a statistically significant correlation with poor oral hygiene. The most common movements were distalization and intrusion of teeth. More than a third of the cases involved complex movements in more than one plane of space. The success rate of skeletal anchorage system miniplates is high and predictable for a wide range of complex orthodontic movements.

Nuclear magnetic resonance (NMR)-based metabolomics for cancer research.

PubMed

Ranjan, Renuka; Sinha, Neeraj

2018-05-07

Nuclear magnetic resonance (NMR) has emerged as an effective tool in various spheres of biomedical research, amongst which metabolomics is an important method for the study of various types of disease. Metabolomics has proved its stronghold in cancer research by the development of different NMR methods over time for the study of metabolites, thus identifying key players in the aetiology of cancer. A plethora of one-dimensional and two-dimensional NMR experiments (in solids, semi-solids and solution phases) are utilized to obtain metabolic profiles of biofluids, cell extracts and tissue biopsy samples, which can further be subjected to statistical analysis. Any alteration in the assigned metabolite peaks gives an indication of changes in metabolic pathways. These defined changes demonstrate the utility of NMR in the early diagnosis of cancer and provide further measures to combat malignancy and its progression. This review provides a snapshot of the trending NMR techniques and the statistical analysis involved in the metabolomics of diseases, with emphasis on advances in NMR methodology developed for cancer research. Copyright © 2018 John Wiley & Sons, Ltd.

Statistical analysis of atom probe data: detecting the early stages of solute clustering and/or co-segregation.

PubMed

Hyde, J M; Cerezo, A; Williams, T J

2009-04-01

Statistical analysis of atom probe data has improved dramatically in the last decade and it is now possible to determine the size, the number density and the composition of individual clusters or precipitates such as those formed in reactor pressure vessel (RPV) steels during irradiation. However, the characterisation of the onset of clustering or co-segregation is more difficult and has traditionally focused on the use of composition frequency distributions (for detecting clustering) and contingency tables (for detecting co-segregation). In this work, the authors investigate the possibility of directly examining the neighbourhood of each individual solute atom as a means of identifying the onset of solute clustering and/or co-segregation. The methodology involves comparing the mean observed composition around a particular type of solute with that expected from the overall composition of the material. The methodology has been applied to atom probe data obtained from several irradiated RPV steels. The results show that the new approach is more sensitive to fine scale clustering and co-segregation than that achievable using composition frequency distribution and contingency table analyses.

Introduction to Bayesian statistical approaches to compositional analyses of transgenic crops 1. Model validation and setting the stage.

PubMed

Harrison, Jay M; Breeze, Matthew L; Harrigan, George G

2011-08-01

Statistical comparisons of compositional data generated on genetically modified (GM) crops and their near-isogenic conventional (non-GM) counterparts typically rely on classical significance testing. This manuscript presents an introduction to Bayesian methods for compositional analysis along with recommendations for model validation. The approach is illustrated using protein and fat data from two herbicide tolerant GM soybeans (MON87708 and MON87708×MON89788) and a conventional comparator grown in the US in 2008 and 2009. Guidelines recommended by the US Food and Drug Administration (FDA) in conducting Bayesian analyses of clinical studies on medical devices were followed. This study is the first Bayesian approach to GM and non-GM compositional comparisons. The evaluation presented here supports a conclusion that a Bayesian approach to analyzing compositional data can provide meaningful and interpretable results. We further describe the importance of method validation and approaches to model checking if Bayesian approaches to compositional data analysis are to be considered viable by scientists involved in GM research and regulation. Copyright © 2011 Elsevier Inc. All rights reserved.

Bayesian Estimation of Thermonuclear Reaction Rates for Deuterium+Deuterium Reactions

NASA Astrophysics Data System (ADS)

Gómez Iñesta, Á.; Iliadis, C.; Coc, A.

2017-11-01

The study of d+d reactions is of major interest since their reaction rates affect the predicted abundances of D, 3He, and 7Li. In particular, recent measurements of primordial D/H ratios call for reduced uncertainties in the theoretical abundances predicted by Big Bang nucleosynthesis (BBN). Different authors have studied reactions involved in BBN by incorporating new experimental data and a careful treatment of systematic and probabilistic uncertainties. To analyze the experimental data, Coc et al. used results of ab initio models for the theoretical calculation of the energy dependence of S-factors in conjunction with traditional statistical methods based on χ 2 minimization. Bayesian methods have now spread to many scientific fields and provide numerous advantages in data analysis. Astrophysical S-factors and reaction rates using Bayesian statistics were calculated by Iliadis et al. Here we present a similar analysis for two d+d reactions, d(d, n)3He and d(d, p)3H, that has been translated into a total decrease of the predicted D/H value by 0.16%.

Study designs, use of statistical tests, and statistical analysis software choice in 2015: Results from two Pakistani monthly Medline indexed journals.

PubMed

Shaikh, Masood Ali

2017-09-01

Assessment of research articles in terms of study designs used, statistical tests applied and the use of statistical analysis programmes help determine research activity profile and trends in the country. In this descriptive study, all original articles published by Journal of Pakistan Medical Association (JPMA) and Journal of the College of Physicians and Surgeons Pakistan (JCPSP), in the year 2015 were reviewed in terms of study designs used, application of statistical tests, and the use of statistical analysis programmes. JPMA and JCPSP published 192 and 128 original articles, respectively, in the year 2015. Results of this study indicate that cross-sectional study design, bivariate inferential statistical analysis entailing comparison between two variables/groups, and use of statistical software programme SPSS to be the most common study design, inferential statistical analysis, and statistical analysis software programmes, respectively. These results echo previously published assessment of these two journals for the year 2014.

Improving Statistical Skills through Students' Participation in the Development of Resources

ERIC Educational Resources Information Center

Biza, Irene; Vande Hey, Eugénie

2015-01-01

This paper summarizes the evaluation of a project that involved undergraduate mathematics students in the development of teaching and learning resources for statistics modules taught in various departments of a university. This evaluation regards students' participation in the project and its impact on their learning of statistics, as…

Statistical Cost Estimation in Higher Education: Some Alternatives.

ERIC Educational Resources Information Center

Brinkman, Paul T.; Niwa, Shelley

Recent developments in econometrics that are relevant to the task of estimating costs in higher education are reviewed. The relative effectiveness of alternative statistical procedures for estimating costs are also tested. Statistical cost estimation involves three basic parts: a model, a data set, and an estimation procedure. Actual data are used…

A wavelet-based technique to predict treatment outcome for Major Depressive Disorder.

PubMed

Mumtaz, Wajid; Xia, Likun; Mohd Yasin, Mohd Azhar; Azhar Ali, Syed Saad; Malik, Aamir Saeed

2017-01-01

Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant's treatment outcome may help during antidepressant's selection and ultimately improve the quality of life for MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such predictions for Selective Serotonin Reuptake Inhibitor (SSRIs). For this purpose, the acquisition of experimental data involved 34 MDD patients and 30 healthy controls. Consequently, a feature matrix was constructed involving time-frequency decomposition of EEG data based on wavelet transform (WT) analysis, termed as EEG data matrix. However, the resultant EEG data matrix had high dimensionality. Therefore, dimension reduction was performed based on a rank-based feature selection method according to a criterion, i.e., receiver operating characteristic (ROC). As a result, the most significant features were identified and further be utilized during the training and testing of a classification model, i.e., the logistic regression (LR) classifier. Finally, the LR model was validated with 100 iterations of 10-fold cross-validation (10-CV). The classification results were compared with short-time Fourier transform (STFT) analysis, and empirical mode decompositions (EMD). The wavelet features extracted from frontal and temporal EEG data were found statistically significant. In comparison with other time-frequency approaches such as the STFT and EMD, the WT analysis has shown highest classification accuracy, i.e., accuracy = 87.5%, sensitivity = 95%, and specificity = 80%. In conclusion, significant wavelet coefficients extracted from frontal and temporal pre-treatment EEG data involving delta and theta frequency bands may predict antidepressant's treatment outcome for the MDD patients.

Statistical Methods for Proteomic Biomarker Discovery based on Feature Extraction or Functional Modeling Approaches.

PubMed

Morris, Jeffrey S

2012-01-01

In recent years, developments in molecular biotechnology have led to the increased promise of detecting and validating biomarkers, or molecular markers that relate to various biological or medical outcomes. Proteomics, the direct study of proteins in biological samples, plays an important role in the biomarker discovery process. These technologies produce complex, high dimensional functional and image data that present many analytical challenges that must be addressed properly for effective comparative proteomics studies that can yield potential biomarkers. Specific challenges include experimental design, preprocessing, feature extraction, and statistical analysis accounting for the inherent multiple testing issues. This paper reviews various computational aspects of comparative proteomic studies, and summarizes contributions I along with numerous collaborators have made. First, there is an overview of comparative proteomics technologies, followed by a discussion of important experimental design and preprocessing issues that must be considered before statistical analysis can be done. Next, the two key approaches to analyzing proteomics data, feature extraction and functional modeling, are described. Feature extraction involves detection and quantification of discrete features like peaks or spots that theoretically correspond to different proteins in the sample. After an overview of the feature extraction approach, specific methods for mass spectrometry ( Cromwell ) and 2D gel electrophoresis ( Pinnacle ) are described. The functional modeling approach involves modeling the proteomic data in their entirety as functions or images. A general discussion of the approach is followed by the presentation of a specific method that can be applied, wavelet-based functional mixed models, and its extensions. All methods are illustrated by application to two example proteomic data sets, one from mass spectrometry and one from 2D gel electrophoresis. While the specific methods presented are applied to two specific proteomic technologies, MALDI-TOF and 2D gel electrophoresis, these methods and the other principles discussed in the paper apply much more broadly to other expression proteomics technologies.

District nurses' involvement in mental health: an exploratory survey.

PubMed

Lee, Soo; Knight, Denise

2006-04-01

This article reports on a survey of district nurses' involvement in mental health interventions in one county. Seventy-nine questionnaires were sent and 46 were returned. Descriptive analysis was carried out using statistical software. The DNs reported encountering a wide range of mental health issues and interventions in practice: dementia, anxiety and depression featured highly. Over half (55%) of the respondents reported involvement in bereavement counselling, and 28% and 23% of respondents reported encountering anxiety management, and problem solving and alcohol advice respectively. A large proportion, however, reported no involvement in mental health interventions. Among the psychiatric professionals, district nurses tended to have most frequent contacts with social workers. GPs were the most likely person to whom DNs made referrals, followed by community psychiatric nurses. Despite the apparent awareness of the values of psychosocial interventions, DNs were equally influenced by the medical model of treatment. In order to realize the potential contribution of district nurses in mental health interventions, there is a need for primary care teams to foster a closer working relationship with mental health specialist services.

The use of imputed sibling genotypes in sibship-based association analysis: on modeling alternatives, power and model misspecification.

PubMed

Minică, Camelia C; Dolan, Conor V; Hottenga, Jouke-Jan; Willemsen, Gonneke; Vink, Jacqueline M; Boomsma, Dorret I

2013-05-01

When phenotypic, but no genotypic data are available for relatives of participants in genetic association studies, previous research has shown that family-based imputed genotypes can boost the statistical power when included in such studies. Here, using simulations, we compared the performance of two statistical approaches suitable to model imputed genotype data: the mixture approach, which involves the full distribution of the imputed genotypes and the dosage approach, where the mean of the conditional distribution features as the imputed genotype. Simulations were run by varying sibship size, size of the phenotypic correlations among siblings, imputation accuracy and minor allele frequency of the causal SNP. Furthermore, as imputing sibling data and extending the model to include sibships of size two or greater requires modeling the familial covariance matrix, we inquired whether model misspecification affects power. Finally, the results obtained via simulations were empirically verified in two datasets with continuous phenotype data (height) and with a dichotomous phenotype (smoking initiation). Across the settings considered, the mixture and the dosage approach are equally powerful and both produce unbiased parameter estimates. In addition, the likelihood-ratio test in the linear mixed model appears to be robust to the considered misspecification in the background covariance structure, given low to moderate phenotypic correlations among siblings. Empirical results show that the inclusion in association analysis of imputed sibling genotypes does not always result in larger test statistic. The actual test statistic may drop in value due to small effect sizes. That is, if the power benefit is small, that the change in distribution of the test statistic under the alternative is relatively small, the probability is greater of obtaining a smaller test statistic. As the genetic effects are typically hypothesized to be small, in practice, the decision on whether family-based imputation could be used as a means to increase power should be informed by prior power calculations and by the consideration of the background correlation.

Improving Logistics Realism in Command Post Exercises Involving the KC-135A/E/R Aircraft Using a Historical Aircraft Maintenance Database Model

DTIC Science & Technology

1990-09-01

exper[ ence in u.sings both the KC-13iA/E/R d ,aboase model and other mat.hematival models. A staListical analysis of survey oz;ai,.,arons, will be...statistic. Consequently, differ- ences of opinion among respondents will be amplified. Summary The research methodology provide5 a sequential set of...Cost Accounting Direc- torate (AFLC/ACC). Though used for cost accounting pur- poses, the VAMOSC system has the capability of cross refer- encing a WUC

Patient Populations, Clinical Associations, and System Efficiency in Healthcare Delivery System

NASA Astrophysics Data System (ADS)

Liu, Yazhuo

The efforts to improve health care delivery usually involve studies and analysis of patient populations and healthcare systems. In this dissertation, I present the research conducted in the following areas: identifying patient groups, improving treatments for specific conditions by using statistical as well as data mining techniques, and developing new operation research models to increase system efficiency from the health institutes' perspective. The results provide better understanding of high risk patient groups, more accuracy in detecting disease' correlations and practical scheduling tools that consider uncertain operation durations and real-life constraints.

A metabonomic investigation on the biochemical perturbation in post-stroke patients with depressive disorder (PSD).

PubMed

Ding, Xinghua; Liu, Ruoxu; Li, Wenkai; Ni, Hengjia; Liu, Yong; Wu, Dandan; Yang, Shuguang; Liu, Jing; Xiao, Bo; Liu, Shaojun

2016-04-01

A metabonomics study based on GC/MS and multivariate statistical analysis was performed involving 28 post stroke depressed (PSD) patients, 27 post-stroke non-depressed (PSND) patients and 33 healthy subjects to investigate the biochemical perturbation in their plasma samples. The outcome of this study showed that there was distinctive metabolic profile for PSD patients. Seven sentinel metabolites showed marked perturbations in PSD patients' blood. The introduction of metabonomics approach may provide a novel metabonomic insight about PSD and the sentinel metabolites for classifying PSD.

Organic food consumption in Taiwan: Motives, involvement, and purchase intention under the moderating role of uncertainty.

PubMed

Teng, Chih-Ching; Lu, Chi-Heng

2016-10-01

Despite the progressive development of the organic food sector in Taiwan, little is known about how consumers' consumption motives will influence organic food decision through various degrees of involvement and whether or not consumers with various degrees of uncertainty will vary in their intention to buy organic foods. The current study aims to examine the effect of consumption motives on behavioral intention related to organic food consumption under the mediating role of involvement as well as the moderating role of uncertainty. Research data were collected from organic food consumers in Taiwan via a questionnaire survey, eventually obtaining 457 valid questionnaires for analysis. This study tested the overall model fit and hypotheses through structural equation modeling method (SEM). The results show that consumer involvement significantly mediates the effects of health consciousness and ecological motives on organic food purchase intention, but not applied to food safety concern. Moreover, the moderating effect of uncertainty is statistical significance, indicating that the relationship between involvement and purchase intention becomes weaker in the condition of consumers with higher degree of uncertainty. Several implications and suggestions are also discussed for organic food providers and marketers. Copyright © 2016. Published by Elsevier Ltd.

CTLA-4 gene polymorphisms and their influence on predisposition to autoimmune thyroid diseases (Graves’ disease and Hashimoto's thyroiditis)

PubMed Central

Pastuszak-Lewandoska, Dorota; Sewerynek, Ewa; Domańska, Daria; Gładyś, Aleksandra; Skrzypczak, Renata

2012-01-01

Introduction Autoimmune thyroid disease (AITD) is associated with both genetic and environmental factors which lead to the overactivity of immune system. Cytotoxic T-Lymphocyte Antigen 4 (CTLA-4) gene polymorphisms belong to the main genetic factors determining the susceptibility to AITD (Hashimoto's thyroiditis, HT and Graves' disease, GD) development. The aim of the study was to evaluate the relationship between CTLA-4 polymorphisms (A49G, 1822 C/T and CT60 A/G) and HT and/or GD in Polish patients. Material and methods Molecular analysis involved AITD group, consisting of HT (n=28) and GD (n=14) patients, and a control group of healthy persons (n=20). Genomic DNA was isolated from peripheral blood and CTLA-4 polymorphisms were assessed by polymerase chain reaction-restriction fragment length polymorphism method, using three restriction enzymes: Fnu4HI (A49G), BsmAI (1822 C/T) and BsaAI (CT60 A/G). Results Statistical analysis (χ2 test) confirmed significant differences between the studied groups concerning CTLA-4 A49G genotypes. CTLA-4 A/G genotype was significantly more frequent in AITD group and OR analysis suggested that it might increase the susceptibility to HT. In GD patients, OR analysis revealed statistically significant relationship with the presence of G allele. In controls, CTLA-4 A/A genotype frequency was significantly increased suggesting a protective effect. There were no statistically significant differences regarding frequencies of other genotypes and polymorphic alleles of the CTLA-4 gene (1822 C/T and CT60 A/G) between the studied groups. Conclusions CTLA-4 A49G polymorphism seems to be an important genetic determinant of the risk of HT and GD in Polish patients. PMID:22851994

CTLA-4 gene polymorphisms and their influence on predisposition to autoimmune thyroid diseases (Graves' disease and Hashimoto's thyroiditis).

PubMed

Pastuszak-Lewandoska, Dorota; Sewerynek, Ewa; Domańska, Daria; Gładyś, Aleksandra; Skrzypczak, Renata; Brzeziańska, Ewa

2012-07-04

Autoimmune thyroid disease (AITD) is associated with both genetic and environmental factors which lead to the overactivity of immune system. Cytotoxic T-Lymphocyte Antigen 4 (CTLA-4) gene polymorphisms belong to the main genetic factors determining the susceptibility to AITD (Hashimoto's thyroiditis, HT and Graves' disease, GD) development. The aim of the study was to evaluate the relationship between CTLA-4 polymorphisms (A49G, 1822 C/T and CT60 A/G) and HT and/or GD in Polish patients. Molecular analysis involved AITD group, consisting of HT (n=28) and GD (n=14) patients, and a control group of healthy persons (n=20). Genomic DNA was isolated from peripheral blood and CTLA-4 polymorphisms were assessed by polymerase chain reaction-restriction fragment length polymorphism method, using three restriction enzymes: Fnu4HI (A49G), BsmAI (1822 C/T) and BsaAI (CT60 A/G). Statistical analysis (χ(2) test) confirmed significant differences between the studied groups concerning CTLA-4 A49G genotypes. CTLA-4 A/G genotype was significantly more frequent in AITD group and OR analysis suggested that it might increase the susceptibility to HT. In GD patients, OR analysis revealed statistically significant relationship with the presence of G allele. In controls, CTLA-4 A/A genotype frequency was significantly increased suggesting a protective effect. There were no statistically significant differences regarding frequencies of other genotypes and polymorphic alleles of the CTLA-4 gene (1822 C/T and CT60 A/G) between the studied groups. CTLA-4 A49G polymorphism seems to be an important genetic determinant of the risk of HT and GD in Polish patients.

Job involvement of primary healthcare employees: does a service provision model play a role?

PubMed

Koponen, Anne M; Laamanen, Ritva; Simonsen-Rehn, Nina; Sundell, Jari; Brommels, Mats; Suominen, Sakari

2010-05-01

To investigate whether the development of job involvement of primary healthcare (PHC) employees in Southern Municipality (SM), where PHC services were outsourced to an independent non-profit organisation, differed from that in the three comparison municipalities (M1, M2, M3) with municipal service providers. Also, the associations of job involvement with factors describing the psychosocial work environment were investigated. A panel mail survey 2000-02 in Finland (n=369, response rates 73% and 60%). The data were analysed by descriptive statistics and multivariate linear regression analysis. Despite the favourable development in the psychosocial work environment, job involvement decreased most in SM, which faced the biggest organisational changes. Job involvement decreased also in M3, where the psychosocial work environment deteriorated most. Job involvement in 2002 was best predicted by high baseline level of interactional justice and work control, positive change in interactional justice, and higher age. Also other factors, such as organisational stability, seemed to play a role; after controlling for the effect of the psychosocial work characteristics, job involvement was higher in M3 than in SM. Outsourcing of PHC services may decrease job involvement at least during the first years. A particular service provision model is better than the others only if it is superior in providing a favourable and stable psychosocial work environment.

Beyond P Values and Hypothesis Testing: Using the Minimum Bayes Factor to Teach Statistical Inference in Undergraduate Introductory Statistics Courses

ERIC Educational Resources Information Center

Page, Robert; Satake, Eiki

2017-01-01

While interest in Bayesian statistics has been growing in statistics education, the treatment of the topic is still inadequate in both textbooks and the classroom. Because so many fields of study lead to careers that involve a decision-making process requiring an understanding of Bayesian methods, it is becoming increasingly clear that Bayesian…

Urine metabolic fingerprinting using LC-MS and GC-MS reveals metabolite changes in prostate cancer: A pilot study.

PubMed

Struck-Lewicka, Wiktoria; Kordalewska, Marta; Bujak, Renata; Yumba Mpanga, Arlette; Markuszewski, Marcin; Jacyna, Julia; Matuszewski, Marcin; Kaliszan, Roman; Markuszewski, Michał J

2015-01-01

Prostate cancer (CaP) is a leading cause of cancer deaths in men worldwide. The alarming statistics, the currently applied biomarkers are still not enough specific and selective. In addition, pathogenesis of CaP development is not totally understood. Therefore, in the present work, metabolomics study related to urinary metabolic fingerprinting analyses has been performed in order to scrutinize potential biomarkers that could help in explaining the pathomechanism of the disease and be potentially useful in its diagnosis and prognosis. Urine samples from CaP patients and healthy volunteers were analyzed with the use of high performance liquid chromatography coupled with time of flight mass spectrometry detection (HPLC-TOF/MS) in positive and negative polarity as well as gas chromatography hyphenated with triple quadruple mass spectrometry detection (GC-QqQ/MS) in a scan mode. The obtained data sets were statistically analyzed using univariate and multivariate statistical analyses. The Principal Component Analysis (PCA) was used to check systems' stability and possible outliers, whereas Partial Least Squares Discriminant Analysis (PLS-DA) was performed for evaluation of quality of the model as well as its predictive ability using statistically significant metabolites. The subsequent identification of selected metabolites using NIST library and commonly available databases allows for creation of a list of putative biomarkers and related biochemical pathways they are involved in. The selected pathways, like urea and tricarboxylic acid cycle, amino acid and purine metabolism, can play crucial role in pathogenesis of prostate cancer disease. Copyright © 2014 Elsevier B.V. All rights reserved.

Applying quantitative adiposity feature analysis models to predict benefit of bevacizumab-based chemotherapy in ovarian cancer patients

NASA Astrophysics Data System (ADS)

Wang, Yunzhi; Qiu, Yuchen; Thai, Theresa; More, Kathleen; Ding, Kai; Liu, Hong; Zheng, Bin

2016-03-01

How to rationally identify epithelial ovarian cancer (EOC) patients who will benefit from bevacizumab or other antiangiogenic therapies is a critical issue in EOC treatments. The motivation of this study is to quantitatively measure adiposity features from CT images and investigate the feasibility of predicting potential benefit of EOC patients with or without receiving bevacizumab-based chemotherapy treatment using multivariate statistical models built based on quantitative adiposity image features. A dataset involving CT images from 59 advanced EOC patients were included. Among them, 32 patients received maintenance bevacizumab after primary chemotherapy and the remaining 27 patients did not. We developed a computer-aided detection (CAD) scheme to automatically segment subcutaneous fat areas (VFA) and visceral fat areas (SFA) and then extracted 7 adiposity-related quantitative features. Three multivariate data analysis models (linear regression, logistic regression and Cox proportional hazards regression) were performed respectively to investigate the potential association between the model-generated prediction results and the patients' progression-free survival (PFS) and overall survival (OS). The results show that using all 3 statistical models, a statistically significant association was detected between the model-generated results and both of the two clinical outcomes in the group of patients receiving maintenance bevacizumab (p<0.01), while there were no significant association for both PFS and OS in the group of patients without receiving maintenance bevacizumab. Therefore, this study demonstrated the feasibility of using quantitative adiposity-related CT image features based statistical prediction models to generate a new clinical marker and predict the clinical outcome of EOC patients receiving maintenance bevacizumab-based chemotherapy.

A meta-analysis of trials using the intention to treat principle for glutamine supplementation in critically ill patients with burn.

PubMed

Lin, Jiun-Jie; Chung, Xiu-Juan; Yang, Chung-Yih; Lau, Hui-Ling

2013-06-01

During critical illness, the demand for glutamine may exceed that which can be mobilized from muscle stores. Infections increase mortality, morbidity, length-of-stay, antibiotic usage and the cost of care. This is a major health care issue. RCTs were identified from the electronic databases: the Cochrane Library, MEDLINE, PubMed web of knowledge and hand searching journals. The trials compared the supplementation with glutamine and non-supplementation in burn. Statistical analysis was performed using RevMan5.1 software, from Cochrane Collaboration. 216 papers showed a match, in the keyword search. Upon screening the title, reading the abstract and the entire article, only four RCTs, involving 155 patients, were included. For both the glutamine group and control group, total burn surface area (TBSA) (MD=2.02, 95% CI -2.17, 6.21, p=0.34) was similar. Glutamine supplementation was associated with a statistically significant decrease in the number of patients with gram-negative bacteremia (OR 0.27, 95% CI 0.08-0.92, p=0.04) and hospital mortality (OR=0.13, 95% CI 0.03, 0.51, p=0.004), however, no statistical difference was noted between groups, for the other results. Glutamine supplemented nutrition can be associated with a reduction in mortality in hospital, complications due to gram-negative bacteremia in burn patients. Further larger and better quality trials are required, in order to determine whether any differences are statistically and clinically important. Copyright © 2012 Elsevier Ltd and ISBI. All rights reserved.

[Acetabular anteversion angle of the hip in the Mexican adult population measured with computed tomography].

PubMed

Rubalcava, J; Gómez-García, F; Ríos-Reina, J L

2012-01-01

Knowledge of the radiogrametric characteristics of a specific skeletal segment in a healthy population is of the utmost clinical importance. The main justification for this study is that there is no published description of the radiogrametric parameter of acetabular anteversion in a healthy Mexican adult population. A prospective, descriptive and cross-sectional study was conducted. Individuals of both genders older than 18 years and orthopedically healthy were included. They underwent a two-dimensional axial tomographic study of both hips to measure the acetabular anteversion angles. The statistical analysis consisted of obtaining central trend and scatter measurements. A multivariate analysis of variance (ANOVA) and statistical significance were performed. 118 individuals were studied, 60 males and 58 females, with a mean age of 47.7 +/- 16.7, and a range of 18-85 years. The anteversion of the entire group was 18.6 degrees + 4.1 degrees. Anteversion in males was 17.3 degrees +/- 3.5 degrees (10 degrees - 25 degrees) and in females 19.8 degrees +/- 4.7 degrees (10 degrees - 31 degrees). There were no statistically significant differences (p < or = 0.05) in right and left anteversion in the entire group. However, there were statistically significant differences (p > or = 0.005) both in the right and left sides when males and females were compared. Our study showed that there are great variations in the anteversion ranges of a healthy population. When our results are compared with those published by other authors the mean of most measurements exceeds 15 degrees. This should be useful to make therapeutic decisions that involve acetabular anteversion.