Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images.

PubMed

Gutmann, Michael U; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús

2014-01-01

Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation.

A quadratically regularized functional canonical correlation analysis for identifying the global structure of pleiotropy with NGS data

PubMed Central

Zhu, Yun; Fan, Ruzong; Xiong, Momiao

2017-01-01

Investigating the pleiotropic effects of genetic variants can increase statistical power, provide important information to achieve deep understanding of the complex genetic structures of disease, and offer powerful tools for designing effective treatments with fewer side effects. However, the current multiple phenotype association analysis paradigm lacks breadth (number of phenotypes and genetic variants jointly analyzed at the same time) and depth (hierarchical structure of phenotype and genotypes). A key issue for high dimensional pleiotropic analysis is to effectively extract informative internal representation and features from high dimensional genotype and phenotype data. To explore correlation information of genetic variants, effectively reduce data dimensions, and overcome critical barriers in advancing the development of novel statistical methods and computational algorithms for genetic pleiotropic analysis, we proposed a new statistic method referred to as a quadratically regularized functional CCA (QRFCCA) for association analysis which combines three approaches: (1) quadratically regularized matrix factorization, (2) functional data analysis and (3) canonical correlation analysis (CCA). Large-scale simulations show that the QRFCCA has a much higher power than that of the ten competing statistics while retaining the appropriate type 1 errors. To further evaluate performance, the QRFCCA and ten other statistics are applied to the whole genome sequencing dataset from the TwinsUK study. We identify a total of 79 genes with rare variants and 67 genes with common variants significantly associated with the 46 traits using QRFCCA. The results show that the QRFCCA substantially outperforms the ten other statistics. PMID:29040274

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Biological Parametric Mapping: A Statistical Toolbox for Multi-Modality Brain Image Analysis

PubMed Central

Casanova, Ramon; Ryali, Srikanth; Baer, Aaron; Laurienti, Paul J.; Burdette, Jonathan H.; Hayasaka, Satoru; Flowers, Lynn; Wood, Frank; Maldjian, Joseph A.

2006-01-01

In recent years multiple brain MR imaging modalities have emerged; however, analysis methodologies have mainly remained modality specific. In addition, when comparing across imaging modalities, most researchers have been forced to rely on simple region-of-interest type analyses, which do not allow the voxel-by-voxel comparisons necessary to answer more sophisticated neuroscience questions. To overcome these limitations, we developed a toolbox for multimodal image analysis called biological parametric mapping (BPM), based on a voxel-wise use of the general linear model. The BPM toolbox incorporates information obtained from other modalities as regressors in a voxel-wise analysis, thereby permitting investigation of more sophisticated hypotheses. The BPM toolbox has been developed in MATLAB with a user friendly interface for performing analyses, including voxel-wise multimodal correlation, ANCOVA, and multiple regression. It has a high degree of integration with the SPM (statistical parametric mapping) software relying on it for visualization and statistical inference. Furthermore, statistical inference for a correlation field, rather than a widely-used T-field, has been implemented in the correlation analysis for more accurate results. An example with in-vivo data is presented demonstrating the potential of the BPM methodology as a tool for multimodal image analysis. PMID:17070709

IUTAM Symposium on Statistical Energy Analysis, 8-11 July 1997, Programme

DTIC Science & Technology

1997-01-01

distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (Maximum200 words) This was the first international scientific gathering devoted...energy flow, continuum dynamics, vibrational energy, statistical energy analysis (SEA) 15. NUMBER OF PAGES 16. PRICE CODE INSECURITY... correlation v=V(ɘ ’• • determination of the correlation n^, =11^, (<?). When harmonic motion and time-average are considered, the following I

Applications of statistics to medical science, III. Correlation and regression.

PubMed

Watanabe, Hiroshi

2012-01-01

In this third part of a series surveying medical statistics, the concepts of correlation and regression are reviewed. In particular, methods of linear regression and logistic regression are discussed. Arguments related to survival analysis will be made in a subsequent paper.

Statistical methods for astronomical data with upper limits. II - Correlation and regression

NASA Technical Reports Server (NTRS)

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

1986-01-01

Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

Statistical Analysis For Nucleus/Nucleus Collisions

NASA Technical Reports Server (NTRS)

Mcguire, Stephen C.

1989-01-01

Report describes use of several statistical techniques to charactertize angular distributions of secondary particles emitted in collisions of atomic nuclei in energy range of 24 to 61 GeV per nucleon. Purpose of statistical analysis to determine correlations between intensities of emitted particles and angles comfirming existence of quark/gluon plasma.

A study of correlations between crude oil spot and futures markets: A rolling sample test

NASA Astrophysics Data System (ADS)

Liu, Li; Wan, Jieqiu

2011-10-01

In this article, we investigate the asymmetries of exceedance correlations and cross-correlations between West Texas Intermediate (WTI) spot and futures markets. First, employing the test statistic proposed by Hong et al. [Asymmetries in stock returns: statistical tests and economic evaluation, Review of Financial Studies 20 (2007) 1547-1581], we find that the exceedance correlations were overall symmetric. However, the results from rolling windows show that some occasional events could induce the significant asymmetries of the exceedance correlations. Second, employing the test statistic proposed by Podobnik et al. [Quantifying cross-correlations using local and global detrending approaches, European Physics Journal B 71 (2009) 243-250], we find that the cross-correlations were significant even for large lagged orders. Using the detrended cross-correlation analysis proposed by Podobnik and Stanley [Detrended cross-correlation analysis: a new method for analyzing two nonstationary time series, Physics Review Letters 100 (2008) 084102], we find that the cross-correlations were weakly persistent and were stronger between spot and futures contract with larger maturity. Our results from rolling sample test also show the apparent effects of the exogenous events. Additionally, we have some relevant discussions on the obtained evidence.

Interpretation of correlations in clinical research.

PubMed

Hung, Man; Bounsanga, Jerry; Voss, Maren Wright

2017-11-01

Critically analyzing research is a key skill in evidence-based practice and requires knowledge of research methods, results interpretation, and applications, all of which rely on a foundation based in statistics. Evidence-based practice makes high demands on trained medical professionals to interpret an ever-expanding array of research evidence. As clinical training emphasizes medical care rather than statistics, it is useful to review the basics of statistical methods and what they mean for interpreting clinical studies. We reviewed the basic concepts of correlational associations, violations of normality, unobserved variable bias, sample size, and alpha inflation. The foundations of causal inference were discussed and sound statistical analyses were examined. We discuss four ways in which correlational analysis is misused, including causal inference overreach, over-reliance on significance, alpha inflation, and sample size bias. Recent published studies in the medical field provide evidence of causal assertion overreach drawn from correlational findings. The findings present a primer on the assumptions and nature of correlational methods of analysis and urge clinicians to exercise appropriate caution as they critically analyze the evidence before them and evaluate evidence that supports practice. Critically analyzing new evidence requires statistical knowledge in addition to clinical knowledge. Studies can overstate relationships, expressing causal assertions when only correlational evidence is available. Failure to account for the effect of sample size in the analyses tends to overstate the importance of predictive variables. It is important not to overemphasize the statistical significance without consideration of effect size and whether differences could be considered clinically meaningful.

Study of photon correlation techniques for processing of laser velocimeter signals

NASA Technical Reports Server (NTRS)

Mayo, W. T., Jr.

1977-01-01

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

A Frequency Domain Approach to Pretest Analysis Model Correlation and Model Updating for the Mid-Frequency Range

DTIC Science & Technology

2009-02-01

range of modal analysis and the high frequency region of statistical energy analysis , is referred to as the mid-frequency range. The corresponding...frequency range of modal analysis and the high frequency region of statistical energy analysis , is referred to as the mid-frequency range. The...predictions. The averaging process is consistent with the averaging done in statistical energy analysis for stochastic systems. The FEM will always

Detrended cross-correlation analysis on RMB exchange rate and Hang Seng China Enterprises Index

NASA Astrophysics Data System (ADS)

Ruan, Qingsong; Yang, Bingchan; Ma, Guofeng

2017-02-01

In this paper, we investigate the cross-correlations between the Hang Seng China Enterprises Index and RMB exchange markets on the basis of a cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). MF-DCCA has, at best, serious limitations for most of the signals describing complex natural processes and often indicates multifractal cross-correlations when there are none. In order to prevent these false multifractal cross-correlations, we apply MFCCA to verify the cross-correlations. Qualitatively, we find that the return series of the Hang Seng China Enterprises Index and RMB exchange markets were, overall, significantly cross-correlated based on the statistical analysis. Quantitatively, we find that the cross-correlations between the stock index and RMB exchange markets were strongly multifractal, and the multifractal degree of the onshore RMB exchange markets was somewhat larger than the offshore RMB exchange markets. Moreover, we use the absolute return series to investigate and confirm the fact of multifractality. The results from the rolling windows show that the short-term cross-correlations between volatility series remain high.

A hybrid correlation analysis with application to imaging genetics

NASA Astrophysics Data System (ADS)

Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

2018-03-01

Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding the correlation between brain imaging and genomic data.

Structural Analysis of Covariance and Correlation Matrices.

ERIC Educational Resources Information Center

Joreskog, Karl G.

1978-01-01

A general approach to analysis of covariance structures is considered, in which the variances and covariances or correlations of the observed variables are directly expressed in terms of the parameters of interest. The statistical problems of identification, estimation and testing of such covariance or correlation structures are discussed.…

Detailed Analysis of the Interoccurrence Time Statistics in Seismic Activity

NASA Astrophysics Data System (ADS)

Tanaka, Hiroki; Aizawa, Yoji

2017-02-01

The interoccurrence time statistics of seismiciry is studied theoretically as well as numerically by taking into account the conditional probability and the correlations among many earthquakes in different magnitude levels. It is known so far that the interoccurrence time statistics is well approximated by the Weibull distribution, but the more detailed information about the interoccurrence times can be obtained from the analysis of the conditional probability. Firstly, we propose the Embedding Equation Theory (EET), where the conditional probability is described by two kinds of correlation coefficients; one is the magnitude correlation and the other is the inter-event time correlation. Furthermore, the scaling law of each correlation coefficient is clearly determined from the numerical data-analysis carrying out with the Preliminary Determination of Epicenter (PDE) Catalog and the Japan Meteorological Agency (JMA) Catalog. Secondly, the EET is examined to derive the magnitude dependence of the interoccurrence time statistics and the multi-fractal relation is successfully formulated. Theoretically we cannot prove the universality of the multi-fractal relation in seismic activity; nevertheless, the theoretical results well reproduce all numerical data in our analysis, where several common features or the invariant aspects are clearly observed. Especially in the case of stationary ensembles the multi-fractal relation seems to obey an invariant curve, furthermore in the case of non-stationary (moving time) ensembles for the aftershock regime the multi-fractal relation seems to satisfy a certain invariant curve at any moving times. It is emphasized that the multi-fractal relation plays an important role to unify the statistical laws of seismicity: actually the Gutenberg-Richter law and the Weibull distribution are unified in the multi-fractal relation, and some universality conjectures regarding the seismicity are briefly discussed.

Multiple Phenotype Association Tests Using Summary Statistics in Genome-Wide Association Studies

PubMed Central

Liu, Zhonghua; Lin, Xihong

2017-01-01

Summary We study in this paper jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. PMID:28653391

Multiple phenotype association tests using summary statistics in genome-wide association studies.

PubMed

Liu, Zhonghua; Lin, Xihong

2018-03-01

We study in this article jointly testing the associations of a genetic variant with correlated multiple phenotypes using the summary statistics of individual phenotype analysis from Genome-Wide Association Studies (GWASs). We estimated the between-phenotype correlation matrix using the summary statistics of individual phenotype GWAS analyses, and developed genetic association tests for multiple phenotypes by accounting for between-phenotype correlation without the need to access individual-level data. Since genetic variants often affect multiple phenotypes differently across the genome and the between-phenotype correlation can be arbitrary, we proposed robust and powerful multiple phenotype testing procedures by jointly testing a common mean and a variance component in linear mixed models for summary statistics. We computed the p-values of the proposed tests analytically. This computational advantage makes our methods practically appealing in large-scale GWASs. We performed simulation studies to show that the proposed tests maintained correct type I error rates, and to compare their powers in various settings with the existing methods. We applied the proposed tests to a GWAS Global Lipids Genetics Consortium summary statistics data set and identified additional genetic variants that were missed by the original single-trait analysis. © 2017, The International Biometric Society.

Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study.

PubMed

Egbewale, Bolaji E; Lewis, Martyn; Sim, Julius

2014-04-09

Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. 126 hypothetical trial scenarios were evaluated (126,000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power.

Bias, precision and statistical power of analysis of covariance in the analysis of randomized trials with baseline imbalance: a simulation study

PubMed Central

2014-01-01

Background Analysis of variance (ANOVA), change-score analysis (CSA) and analysis of covariance (ANCOVA) respond differently to baseline imbalance in randomized controlled trials. However, no empirical studies appear to have quantified the differential bias and precision of estimates derived from these methods of analysis, and their relative statistical power, in relation to combinations of levels of key trial characteristics. This simulation study therefore examined the relative bias, precision and statistical power of these three analyses using simulated trial data. Methods 126 hypothetical trial scenarios were evaluated (126 000 datasets), each with continuous data simulated by using a combination of levels of: treatment effect; pretest-posttest correlation; direction and magnitude of baseline imbalance. The bias, precision and power of each method of analysis were calculated for each scenario. Results Compared to the unbiased estimates produced by ANCOVA, both ANOVA and CSA are subject to bias, in relation to pretest-posttest correlation and the direction of baseline imbalance. Additionally, ANOVA and CSA are less precise than ANCOVA, especially when pretest-posttest correlation ≥ 0.3. When groups are balanced at baseline, ANCOVA is at least as powerful as the other analyses. Apparently greater power of ANOVA and CSA at certain imbalances is achieved in respect of a biased treatment effect. Conclusions Across a range of correlations between pre- and post-treatment scores and at varying levels and direction of baseline imbalance, ANCOVA remains the optimum statistical method for the analysis of continuous outcomes in RCTs, in terms of bias, precision and statistical power. PMID:24712304

Use of statistical study methods for the analysis of the results of the imitation modeling of radiation transfer

NASA Astrophysics Data System (ADS)

Alekseenko, M. A.; Gendrina, I. Yu.

2017-11-01

Recently, due to the abundance of various types of observational data in the systems of vision through the atmosphere and the need for their processing, the use of various methods of statistical research in the study of such systems as correlation-regression analysis, dynamic series, variance analysis, etc. is actual. We have attempted to apply elements of correlation-regression analysis for the study and subsequent prediction of the patterns of radiation transfer in these systems same as in the construction of radiation models of the atmosphere. In this paper, we present some results of statistical processing of the results of numerical simulation of the characteristics of vision systems through the atmosphere obtained with the help of a special software package.1

An Analysis of Research Methods and Statistical Techniques Used by Doctoral Dissertation at the Education Sciences in Turkey

ERIC Educational Resources Information Center

Karadag, Engin

2010-01-01

To assess research methods and analysis of statistical techniques employed by educational researchers, this study surveyed unpublished doctoral dissertation from 2003 to 2007. Frequently used research methods consisted of experimental research; a survey; a correlational study; and a case study. Descriptive statistics, t-test, ANOVA, factor…

Analysis of thrips distribution: application of spatial statistics and Kriging

Treesearch

John Aleong; Bruce L. Parker; Margaret Skinner; Diantha Howard

1991-01-01

Kriging is a statistical technique that provides predictions for spatially and temporally correlated data. Observations of thrips distribution and density in Vermont soils are made in both space and time. Traditional statistical analysis of such data assumes that the counts taken over space and time are independent, which is not necessarily true. Therefore, to analyze...

Do Deregulated Cas Proteins Induce Genomic Instability in Early-Stage Ovarian Cancer

DTIC Science & Technology

2006-12-01

use Western blot analysis of tumor lysates to correlate expression of HEF1, p130Cas, Aurora A, and phospho-Aurora A. This analysis is in progress. In...and importantly, evaluated a number of different detection/image analysis systems to ensure reproducible quantitative results. We have used a pilot...reproducible Interestingly, preliminary statistical analysis using Spearman and Pearson correlation indicates at least one striking correlation

Statistical properties of DNA sequences

NASA Technical Reports Server (NTRS)

Peng, C. K.; Buldyrev, S. V.; Goldberger, A. L.; Havlin, S.; Mantegna, R. N.; Simons, M.; Stanley, H. E.

1995-01-01

We review evidence supporting the idea that the DNA sequence in genes containing non-coding regions is correlated, and that the correlation is remarkably long range--indeed, nucleotides thousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene. We resolve the problem of the "non-stationarity" feature of the sequence of base pairs by applying a new algorithm called detrended fluctuation analysis (DFA). We address the claim of Voss that there is no difference in the statistical properties of coding and non-coding regions of DNA by systematically applying the DFA algorithm, as well as standard FFT analysis, to every DNA sequence (33301 coding and 29453 non-coding) in the entire GenBank database. Finally, we describe briefly some recent work showing that the non-coding sequences have certain statistical features in common with natural and artificial languages. Specifically, we adapt to DNA the Zipf approach to analyzing linguistic texts. These statistical properties of non-coding sequences support the possibility that non-coding regions of DNA may carry biological information.

Wavelet analysis of polarization maps of polycrystalline biological fluids networks

NASA Astrophysics Data System (ADS)

Ushenko, Y. A.

2011-12-01

The optical model of human joints synovial fluid is proposed. The statistic (statistic moments), correlation (autocorrelation function) and self-similar (Log-Log dependencies of power spectrum) structure of polarization two-dimensional distributions (polarization maps) of synovial fluid has been analyzed. It has been shown that differentiation of polarization maps of joint synovial fluid with different physiological state samples is expected of scale-discriminative analysis. To mark out of small-scale domain structure of synovial fluid polarization maps, the wavelet analysis has been used. The set of parameters, which characterize statistic, correlation and self-similar structure of wavelet coefficients' distributions of different scales of polarization domains for diagnostics and differentiation of polycrystalline network transformation connected with the pathological processes, has been determined.

Analysis of Doppler radar windshear data

NASA Technical Reports Server (NTRS)

Williams, F.; Mckinney, P.; Ozmen, F.

1989-01-01

The objective of this analysis is to process Lincoln Laboratory Doppler radar data obtained during FLOWS testing at Huntsville, Alabama, in the summer of 1986, to characterize windshear events. The processing includes plotting velocity and F-factor profiles, histogram analysis to summarize statistics, and correlation analysis to demonstrate any correlation between different data fields.

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

PubMed

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

Separate-channel analysis of two-channel microarrays: recovering inter-spot information.

PubMed

Smyth, Gordon K; Altman, Naomi S

2013-05-26

Two-channel (or two-color) microarrays are cost-effective platforms for comparative analysis of gene expression. They are traditionally analysed in terms of the log-ratios (M-values) of the two channel intensities at each spot, but this analysis does not use all the information available in the separate channel observations. Mixed models have been proposed to analyse intensities from the two channels as separate observations, but such models can be complex to use and the gain in efficiency over the log-ratio analysis is difficult to quantify. Mixed models yield test statistics for the null distributions can be specified only approximately, and some approaches do not borrow strength between genes. This article reformulates the mixed model to clarify the relationship with the traditional log-ratio analysis, to facilitate information borrowing between genes, and to obtain an exact distributional theory for the resulting test statistics. The mixed model is transformed to operate on the M-values and A-values (average log-expression for each spot) instead of on the log-expression values. The log-ratio analysis is shown to ignore information contained in the A-values. The relative efficiency of the log-ratio analysis is shown to depend on the size of the intraspot correlation. A new separate channel analysis method is proposed that assumes a constant intra-spot correlation coefficient across all genes. This approach permits the mixed model to be transformed into an ordinary linear model, allowing the data analysis to use a well-understood empirical Bayes analysis pipeline for linear modeling of microarray data. This yields statistically powerful test statistics that have an exact distributional theory. The log-ratio, mixed model and common correlation methods are compared using three case studies. The results show that separate channel analyses that borrow strength between genes are more powerful than log-ratio analyses. The common correlation analysis is the most powerful of all. The common correlation method proposed in this article for separate-channel analysis of two-channel microarray data is no more difficult to apply in practice than the traditional log-ratio analysis. It provides an intuitive and powerful means to conduct analyses and make comparisons that might otherwise not be possible.

Extreme value statistics analysis of fracture strengths of a sintered silicon nitride failing from pores

NASA Technical Reports Server (NTRS)

Chao, Luen-Yuan; Shetty, Dinesh K.

1992-01-01

Statistical analysis and correlation between pore-size distribution and fracture strength distribution using the theory of extreme-value statistics is presented for a sintered silicon nitride. The pore-size distribution on a polished surface of this material was characterized, using an automatic optical image analyzer. The distribution measured on the two-dimensional plane surface was transformed to a population (volume) distribution, using the Schwartz-Saltykov diameter method. The population pore-size distribution and the distribution of the pore size at the fracture origin were correllated by extreme-value statistics. Fracture strength distribution was then predicted from the extreme-value pore-size distribution, usin a linear elastic fracture mechanics model of annular crack around pore and the fracture toughness of the ceramic. The predicted strength distribution was in good agreement with strength measurements in bending. In particular, the extreme-value statistics analysis explained the nonlinear trend in the linearized Weibull plot of measured strengths without postulating a lower-bound strength.

Comparing Methods for Item Analysis: The Impact of Different Item-Selection Statistics on Test Difficulty

ERIC Educational Resources Information Center

Jones, Andrew T.

2011-01-01

Practitioners often depend on item analysis to select items for exam forms and have a variety of options available to them. These include the point-biserial correlation, the agreement statistic, the B index, and the phi coefficient. Although research has demonstrated that these statistics can be useful for item selection, no research as of yet has…

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression.

PubMed

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson's statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran's index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China's regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test.

STATISTICAL METHODOLOGY FOR THE SIMULTANEOUS ANALYSIS OF MULTIPLE TYPES OF OUTCOMES IN NONLINEAR THRESHOLD MODELS.

EPA Science Inventory

Multiple outcomes are often measured on each experimental unit in toxicology experiments. These multiple observations typically imply the existence of correlation between endpoints, and a statistical analysis that incorporates it may result in improved inference. When both disc...

Local sensitivity analysis for inverse problems solved by singular value decomposition

USGS Publications Warehouse

Hill, M.C.; Nolan, B.T.

2010-01-01

Local sensitivity analysis provides computationally frugal ways to evaluate models commonly used for resource management, risk assessment, and so on. This includes diagnosing inverse model convergence problems caused by parameter insensitivity and(or) parameter interdependence (correlation), understanding what aspects of the model and data contribute to measures of uncertainty, and identifying new data likely to reduce model uncertainty. Here, we consider sensitivity statistics relevant to models in which the process model parameters are transformed using singular value decomposition (SVD) to create SVD parameters for model calibration. The statistics considered include the PEST identifiability statistic, and combined use of the process-model parameter statistics composite scaled sensitivities and parameter correlation coefficients (CSS and PCC). The statistics are complimentary in that the identifiability statistic integrates the effects of parameter sensitivity and interdependence, while CSS and PCC provide individual measures of sensitivity and interdependence. PCC quantifies correlations between pairs or larger sets of parameters; when a set of parameters is intercorrelated, the absolute value of PCC is close to 1.00 for all pairs in the set. The number of singular vectors to include in the calculation of the identifiability statistic is somewhat subjective and influences the statistic. To demonstrate the statistics, we use the USDA’s Root Zone Water Quality Model to simulate nitrogen fate and transport in the unsaturated zone of the Merced River Basin, CA. There are 16 log-transformed process-model parameters, including water content at field capacity (WFC) and bulk density (BD) for each of five soil layers. Calibration data consisted of 1,670 observations comprising soil moisture, soil water tension, aqueous nitrate and bromide concentrations, soil nitrate concentration, and organic matter content. All 16 of the SVD parameters could be estimated by regression based on the range of singular values. Identifiability statistic results varied based on the number of SVD parameters included. Identifiability statistics calculated for four SVD parameters indicate the same three most important process-model parameters as CSS/PCC (WFC1, WFC2, and BD2), but the order differed. Additionally, the identifiability statistic showed that BD1 was almost as dominant as WFC1. The CSS/PCC analysis showed that this results from its high correlation with WCF1 (-0.94), and not its individual sensitivity. Such distinctions, combined with analysis of how high correlations and(or) sensitivities result from the constructed model, can produce important insights into, for example, the use of sensitivity analysis to design monitoring networks. In conclusion, the statistics considered identified similar important parameters. They differ because (1) with CSS/PCC can be more awkward because sensitivity and interdependence are considered separately and (2) identifiability requires consideration of how many SVD parameters to include. A continuing challenge is to understand how these computationally efficient methods compare with computationally demanding global methods like Markov-Chain Monte Carlo given common nonlinear processes and the often even more nonlinear models.

The relationship between procrastination, learning strategies and statistics anxiety among Iranian college students: a canonical correlation analysis.

PubMed

Vahedi, Shahrum; Farrokhi, Farahman; Gahramani, Farahnaz; Issazadegan, Ali

2012-01-01

Approximately 66-80%of graduate students experience statistics anxiety and some researchers propose that many students identify statistics courses as the most anxiety-inducing courses in their academic curriculums. As such, it is likely that statistics anxiety is, in part, responsible for many students delaying enrollment in these courses for as long as possible. This paper proposes a canonical model by treating academic procrastination (AP), learning strategies (LS) as predictor variables and statistics anxiety (SA) as explained variables. A questionnaire survey was used for data collection and 246-college female student participated in this study. To examine the mutually independent relations between procrastination, learning strategies and statistics anxiety variables, a canonical correlation analysis was computed. Findings show that two canonical functions were statistically significant. The set of variables (metacognitive self-regulation, source management, preparing homework, preparing for test and preparing term papers) helped predict changes of statistics anxiety with respect to fearful behavior, Attitude towards math and class, Performance, but not Anxiety. These findings could be used in educational and psychological interventions in the context of statistics anxiety reduction.

Statistical Development of Flood Frequency and Magnitude Equations for the Cosumnes and Mokelumne River Drainage Basins, Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Burns, R. G.; Meyer, R. W.; Cornwell, K.

2003-12-01

In-basin statistical relations allow for development of regional flood frequency and magnitude equations in the Cosumnes River and Mokelumne River drainage basins. Current equations were derived from data collected through 1975, and do not reflect newer data with some significant flooding. Physical basin characteristics (area, mean basin elevation, slope of longest reach, and mean annual precipitation) were correlated against predicted flood discharges for each of the 5, 10, 25, 50, 100, 200, and 500-year recurrence intervals in a multivariate analysis. Predicted maximum instantaneous flood discharges were determined using the PEAKFQ program with default settings, for 24 stream gages within the study area presumed not affected by flow management practices. For numerical comparisons, GIS-based methods using Spatial Analyst and the Arc Hydro Tools extension were applied to derive physical basin characteristics as predictor variables from a 30m digital elevation model (DEM) and a mean annual precipitation raster (PRISM). In a bivariate analysis, examination of Pearson correlation coefficients, F-statistic, and t & p thresholds show good correlation between area and flood discharges. Similar analyses show poor correlation for mean basin elevation, slope and precipitation, with flood discharge. Bivariate analysis suggests slope may not be an appropriate predictor term for use in the multivariate analysis. Precipitation and elevation correlate very well, demonstrating possible orographic effects. From the multivariate analysis, less than 6% of the variability in the correlation is not explained for flood recurrences up to 25 years. Longer term predictions up to 500 years accrue greater uncertainty with as much as 15% of the variability in the correlation left unexplained.

The mediating effect of calling on the relationship between medical school students' academic burnout and empathy.

PubMed

Chae, Su Jin; Jeong, So Mi; Chung, Yoon-Sok

2017-09-01

This study is aimed at identifying the relationships between medical school students' academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students' empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. This result demonstrates that calling is a key variable that mediates the relationship between medical students' academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students' empathy skills.

Solar granulation and statistical crystallography: A modeling approach using size-shape relations

NASA Technical Reports Server (NTRS)

Noever, D. A.

1994-01-01

The irregular polygonal pattern of solar granulation is analyzed for size-shape relations using statistical crystallography. In contrast to previous work which has assumed perfectly hexagonal patterns for granulation, more realistic accounting of cell (granule) shapes reveals a broader basis for quantitative analysis. Several features emerge as noteworthy: (1) a linear correlation between number of cell-sides and neighboring shapes (called Aboav-Weaire's law); (2) a linear correlation between both average cell area and perimeter and the number of cell-sides (called Lewis's law and a perimeter law, respectively) and (3) a linear correlation between cell area and squared perimeter (called convolution index). This statistical picture of granulation is consistent with a finding of no correlation in cell shapes beyond nearest neighbors. A comparative calculation between existing model predictions taken from luminosity data and the present analysis shows substantial agreements for cell-size distributions. A model for understanding grain lifetimes is proposed which links convective times to cell shape using crystallographic results.

Statistical correlations of crime with arrests

NASA Astrophysics Data System (ADS)

Kuelling, Albert C.

1997-01-01

Regression analysis shows that the overall crime rate correlates with the overall arrest rate. Violent crime only weakly correlates with the violent arrest rate, but strongly correlates with the property arrest rate. Contrary to common impressions, increasing arrest rates do not significantly increase loading on incarceration facilities.

Determining the Statistical Significance of Relative Weights

ERIC Educational Resources Information Center

Tonidandel, Scott; LeBreton, James M.; Johnson, Jeff W.

2009-01-01

Relative weight analysis is a procedure for estimating the relative importance of correlated predictors in a regression equation. Because the sampling distribution of relative weights is unknown, researchers using relative weight analysis are unable to make judgments regarding the statistical significance of the relative weights. J. W. Johnson…

Relationship between teacher preparedness and inquiry-based instructional practices to students' science achievement: Evidence from TIMSS 2007

NASA Astrophysics Data System (ADS)

Martin, Lynn A.

The purpose of this study was to examine the relationship between teachers' self-reported preparedness for teaching science content and their instructional practices to the science achievement of eighth grade science students in the United States as demonstrated by TIMSS 2007. Six hundred eighty-seven eighth grade science teachers in the United States representing 7,377 students responded to the TIMSS 2007 questionnaire about their instructional preparedness and their instructional practices. Quantitative data were reported. Through correlation analysis, the researcher found statistically significant positive relationships emerge between eighth grade science teachers' main area of study and their self-reported beliefs about their preparedness to teach that same content area. Another correlation analysis found a statistically significant negative relationship existed between teachers' self-reported use of inquiry-based instruction and preparedness to teach chemistry, physics and earth science. Another correlation analysis discovered a statistically significant positive relationship existed between physics preparedness and student science achievement. Finally, a correlation analysis found a statistically significant positive relationship existed between science teachers' self-reported implementation of inquiry-based instructional practices and student achievement. The data findings support the conclusion that teachers who have feelings of preparedness to teach science content and implement more inquiry-based instruction and less didactic instruction produce high achieving science students. As science teachers obtain the appropriate knowledge in science content and pedagogy, science teachers will feel prepared and will implement inquiry-based instruction in science classrooms.

On the analysis of very small samples of Gaussian repeated measurements: an alternative approach.

PubMed

Westgate, Philip M; Burchett, Woodrow W

2017-03-15

The analysis of very small samples of Gaussian repeated measurements can be challenging. First, due to a very small number of independent subjects contributing outcomes over time, statistical power can be quite small. Second, nuisance covariance parameters must be appropriately accounted for in the analysis in order to maintain the nominal test size. However, available statistical strategies that ensure valid statistical inference may lack power, whereas more powerful methods may have the potential for inflated test sizes. Therefore, we explore an alternative approach to the analysis of very small samples of Gaussian repeated measurements, with the goal of maintaining valid inference while also improving statistical power relative to other valid methods. This approach uses generalized estimating equations with a bias-corrected empirical covariance matrix that accounts for all small-sample aspects of nuisance correlation parameter estimation in order to maintain valid inference. Furthermore, the approach utilizes correlation selection strategies with the goal of choosing the working structure that will result in the greatest power. In our study, we show that when accurate modeling of the nuisance correlation structure impacts the efficiency of regression parameter estimation, this method can improve power relative to existing methods that yield valid inference. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Prison Radicalization: The New Extremist Training Grounds?

DTIC Science & Technology

2007-09-01

distributing and collecting survey data , and the data analysis. The analytical methodology includes descriptive and inferential statistical methods, in... statistical analysis of the responses to identify significant correlations and relationships. B. SURVEY DATA COLLECTION To effectively access a...Q18, Q19, Q20, and Q21. Due to the exploratory nature of this small survey, data analyses were confined mostly to descriptive statistics and

Is math anxiety in the secondary classroom limiting physics mastery? A study of math anxiety and physics performance

NASA Astrophysics Data System (ADS)

Mercer, Gary J.

This quantitative study examined the relationship between secondary students with math anxiety and physics performance in an inquiry-based constructivist classroom. The Revised Math Anxiety Rating Scale was used to evaluate math anxiety levels. The results were then compared to the performance on a physics standardized final examination. A simple correlation was performed, followed by a multivariate regression analysis to examine effects based on gender and prior math background. The correlation showed statistical significance between math anxiety and physics performance. The regression analysis showed statistical significance for math anxiety, physics performance, and prior math background, but did not show statistical significance for math anxiety, physics performance, and gender.

Can Money Buy Happiness? A Statistical Analysis of Predictors for User Satisfaction

ERIC Educational Resources Information Center

Hunter, Ben; Perret, Robert

2011-01-01

2007 data from LibQUAL+[TM] and the ACRL Library Trends and Statistics database were analyzed to determine if there is a statistically significant correlation between library expenditures and usage statistics and library patron satisfaction across 73 universities. The results show that users of larger, better funded libraries have higher…

78 FR 34101 - Agency Information Collection Activities: Proposed Collection; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-06

... and basic descriptive statistics on the quantity and type of consumer-reported patient safety events... conduct correlations, cross tabulations of responses and other statistical analysis. Estimated Annual...

Mathematical and Statistical Software Index.

DTIC Science & Technology

1986-08-01

geometric) mean HMEAN - harmonic mean MEDIAN - median MODE - mode QUANT - quantiles OGIVE - distribution curve IQRNG - interpercentile range RANGE ... range mutliphase pivoting algorithm cross-classification multiple discriminant analysis cross-tabul ation mul tipl e-objecti ve model curve fitting...Statistics). .. .. .... ...... ..... ...... ..... .. 21 *RANGEX (Correct Correlations for Curtailment of Range ). .. .. .... ...... ... 21 *RUMMAGE II (Analysis

Examples of Data Analysis with SPSS-X.

ERIC Educational Resources Information Center

MacFarland, Thomas W.

Intended for classroom use only, these unpublished notes contain computer lessons on descriptive statistics using SPSS-X Release 3.0 for VAX/UNIX. Statistical measures covered include Chi-square analysis; Spearman's rank correlation coefficient; Student's t-test with two independent samples; Student's t-test with a paired sample; One-way analysis…

Security of statistical data bases: invasion of privacy through attribute correlational modeling

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

Palley, M.A.

This study develops, defines, and applies a statistical technique for the compromise of confidential information in a statistical data base. Attribute Correlational Modeling (ACM) recognizes that the information contained in a statistical data base represents real world statistical phenomena. As such, ACM assumes correlational behavior among the database attributes. ACM proceeds to compromise confidential information through creation of a regression model, where the confidential attribute is treated as the dependent variable. The typical statistical data base may preclude the direct application of regression. In this scenario, the research introduces the notion of a synthetic data base, created through legitimate queriesmore » of the actual data base, and through proportional random variation of responses to these queries. The synthetic data base is constructed to resemble the actual data base as closely as possible in a statistical sense. ACM then applies regression analysis to the synthetic data base, and utilizes the derived model to estimate confidential information in the actual database.« less

Concordance correlation for model performance assessment: An example with reference evapotranspiration

USDA-ARS?s Scientific Manuscript database

Procedures for assessing model performance in agronomy are often arbitrary and not always helpful. An omnibus analysis statistic, concordance correlation, is widely known and used in many other sciences. An illustrative example is presented here. The analysis assumes the exact relationship “observat...

Correlation spectrometer for filtering of (quasi) elastic neutron scattering with variable resolution

NASA Astrophysics Data System (ADS)

Magazù, Salvatore; Mezei, Ferenc; Migliardo, Federica

2018-05-01

In a variety of applications of inelastic neutron scattering spectroscopy the goal is to single out the elastic scattering contribution from the total scattered spectrum as a function of momentum transfer and sample environment parameters. The elastic part of the spectrum is defined in such a case by the energy resolution of the spectrometer. Variable elastic energy resolution offers a way to distinguish between elastic and quasi-elastic intensities. Correlation spectroscopy lends itself as an efficient, high intensity approach for accomplishing this both at continuous and pulsed neutron sources. On the one hand, in beam modulation methods the Liouville theorem coupling between intensity and resolution is relaxed and time-of-flight velocity analysis of the neutron velocity distribution can be performed with 50 % duty factor exposure for all available resolutions. On the other hand, the (quasi)elastic part of the spectrum generally contains the major part of the integrated intensity at a given detector, and thus correlation spectroscopy can be applied with most favorable signal to statistical noise ratio. The novel spectrometer CORELLI at SNS is an example for this type of application of the correlation technique at a pulsed source. On a continuous neutron source a statistical chopper can be used for quasi-random time dependent beam modulation and the total time-of-flight of the neutron from the statistical chopper to detection is determined by the analysis of the correlation between the temporal fluctuation of the neutron detection rate and the statistical chopper beam modulation pattern. The correlation analysis can either be used for the determination of the incoming neutron velocity or for the scattered neutron velocity, depending of the position of the statistical chopper along the neutron trajectory. These two options are considered together with an evaluation of spectrometer performance compared to conventional spectroscopy, in particular for variable resolution elastic neutron scattering (RENS) studies of relaxation processes and the evolution of mean square displacements. A particular focus of our analysis is the unique feature of correlation spectroscopy of delivering high and resolution independent beam intensity, thus the same statistical chopper scan contains both high intensity and high resolution information at the same time, and can be evaluated both ways. This flexibility for variable resolution data handling represents an additional asset for correlation spectroscopy in variable resolution work. Changing the beam width for the same statistical chopper allows us to additionally trade resolution for intensity in two different experimental runs, similarly for conventional single slit chopper spectroscopy. The combination of these two approaches is a capability of particular value in neutron spectroscopy studies requiring variable energy resolution, such as the systematic study of quasi-elastic scattering and mean square displacement. Furthermore the statistical chopper approach is particularly advantageous for studying samples with low scattering intensity in the presence of a high, sample independent background.

Performance of Modified Test Statistics in Covariance and Correlation Structure Analysis under Conditions of Multivariate Nonnormality.

ERIC Educational Resources Information Center

Fouladi, Rachel T.

2000-01-01

Provides an overview of standard and modified normal theory and asymptotically distribution-free covariance and correlation structure analysis techniques and details Monte Carlo simulation results on Type I and Type II error control. Demonstrates through the simulation that robustness and nonrobustness of structure analysis techniques vary as a…

A generalization of random matrix theory and its application to statistical physics.

PubMed

Wang, Duan; Zhang, Xin; Horvatic, Davor; Podobnik, Boris; Eugene Stanley, H

2017-02-01

To study the statistical structure of crosscorrelations in empirical data, we generalize random matrix theory and propose a new method of cross-correlation analysis, known as autoregressive random matrix theory (ARRMT). ARRMT takes into account the influence of auto-correlations in the study of cross-correlations in multiple time series. We first analytically and numerically determine how auto-correlations affect the eigenvalue distribution of the correlation matrix. Then we introduce ARRMT with a detailed procedure of how to implement the method. Finally, we illustrate the method using two examples taken from inflation rates for air pressure data for 95 US cities.

The Malpractice of Statistical Interpretation

ERIC Educational Resources Information Center

Fraas, John W.; Newman, Isadore

1978-01-01

Problems associated with the use of gain scores, analysis of covariance, multicollinearity, part and partial correlation, and the lack of rectilinearity in regression are discussed. Particular attention is paid to the misuse of statistical techniques. (JKS)

Statistical correlation analysis for comparing vibration data from test and analysis

NASA Technical Reports Server (NTRS)

Butler, T. G.; Strang, R. F.; Purves, L. R.; Hershfeld, D. J.

1986-01-01

A theory was developed to compare vibration modes obtained by NASTRAN analysis with those obtained experimentally. Because many more analytical modes can be obtained than experimental modes, the analytical set was treated as expansion functions for putting both sources in comparative form. The dimensional symmetry was developed for three general cases: nonsymmetric whole model compared with a nonsymmetric whole structural test, symmetric analytical portion compared with a symmetric experimental portion, and analytical symmetric portion with a whole experimental test. The theory was coded and a statistical correlation program was installed as a utility. The theory is established with small classical structures.

Spatial Autocorrelation Approaches to Testing Residuals from Least Squares Regression

PubMed Central

Chen, Yanguang

2016-01-01

In geo-statistics, the Durbin-Watson test is frequently employed to detect the presence of residual serial correlation from least squares regression analyses. However, the Durbin-Watson statistic is only suitable for ordered time or spatial series. If the variables comprise cross-sectional data coming from spatial random sampling, the test will be ineffectual because the value of Durbin-Watson’s statistic depends on the sequence of data points. This paper develops two new statistics for testing serial correlation of residuals from least squares regression based on spatial samples. By analogy with the new form of Moran’s index, an autocorrelation coefficient is defined with a standardized residual vector and a normalized spatial weight matrix. Then by analogy with the Durbin-Watson statistic, two types of new serial correlation indices are constructed. As a case study, the two newly presented statistics are applied to a spatial sample of 29 China’s regions. These results show that the new spatial autocorrelation models can be used to test the serial correlation of residuals from regression analysis. In practice, the new statistics can make up for the deficiencies of the Durbin-Watson test. PMID:26800271

Statistical analysis of co-occurrence patterns in microbial presence-absence datasets.

PubMed

Mainali, Kumar P; Bewick, Sharon; Thielen, Peter; Mehoke, Thomas; Breitwieser, Florian P; Paudel, Shishir; Adhikari, Arjun; Wolfe, Joshua; Slud, Eric V; Karig, David; Fagan, William F

2017-01-01

Drawing on a long history in macroecology, correlation analysis of microbiome datasets is becoming a common practice for identifying relationships or shared ecological niches among bacterial taxa. However, many of the statistical issues that plague such analyses in macroscale communities remain unresolved for microbial communities. Here, we discuss problems in the analysis of microbial species correlations based on presence-absence data. We focus on presence-absence data because this information is more readily obtainable from sequencing studies, especially for whole-genome sequencing, where abundance estimation is still in its infancy. First, we show how Pearson's correlation coefficient (r) and Jaccard's index (J)-two of the most common metrics for correlation analysis of presence-absence data-can contradict each other when applied to a typical microbiome dataset. In our dataset, for example, 14% of species-pairs predicted to be significantly correlated by r were not predicted to be significantly correlated using J, while 37.4% of species-pairs predicted to be significantly correlated by J were not predicted to be significantly correlated using r. Mismatch was particularly common among species-pairs with at least one rare species (<10% prevalence), explaining why r and J might differ more strongly in microbiome datasets, where there are large numbers of rare taxa. Indeed 74% of all species-pairs in our study had at least one rare species. Next, we show how Pearson's correlation coefficient can result in artificial inflation of positive taxon relationships and how this is a particular problem for microbiome studies. We then illustrate how Jaccard's index of similarity (J) can yield improvements over Pearson's correlation coefficient. However, the standard null model for Jaccard's index is flawed, and thus introduces its own set of spurious conclusions. We thus identify a better null model based on a hypergeometric distribution, which appropriately corrects for species prevalence. This model is available from recent statistics literature, and can be used for evaluating the significance of any value of an empirically observed Jaccard's index. The resulting simple, yet effective method for handling correlation analysis of microbial presence-absence datasets provides a robust means of testing and finding relationships and/or shared environmental responses among microbial taxa.

A note on generalized Genome Scan Meta-Analysis statistics

PubMed Central

Koziol, James A; Feng, Anne C

2005-01-01

Background Wise et al. introduced a rank-based statistical technique for meta-analysis of genome scans, the Genome Scan Meta-Analysis (GSMA) method. Levinson et al. recently described two generalizations of the GSMA statistic: (i) a weighted version of the GSMA statistic, so that different studies could be ascribed different weights for analysis; and (ii) an order statistic approach, reflecting the fact that a GSMA statistic can be computed for each chromosomal region or bin width across the various genome scan studies. Results We provide an Edgeworth approximation to the null distribution of the weighted GSMA statistic, and, we examine the limiting distribution of the GSMA statistics under the order statistic formulation, and quantify the relevance of the pairwise correlations of the GSMA statistics across different bins on this limiting distribution. We also remark on aggregate criteria and multiple testing for determining significance of GSMA results. Conclusion Theoretical considerations detailed herein can lead to clarification and simplification of testing criteria for generalizations of the GSMA statistic. PMID:15717930

Which statistics should tropical biologists learn?

PubMed

Loaiza Velásquez, Natalia; González Lutz, María Isabel; Monge-Nájera, Julián

2011-09-01

Tropical biologists study the richest and most endangered biodiversity in the planet, and in these times of climate change and mega-extinctions, the need for efficient, good quality research is more pressing than in the past. However, the statistical component in research published by tropical authors sometimes suffers from poor quality in data collection; mediocre or bad experimental design and a rigid and outdated view of data analysis. To suggest improvements in their statistical education, we listed all the statistical tests and other quantitative analyses used in two leading tropical journals, the Revista de Biología Tropical and Biotropica, during a year. The 12 most frequent tests in the articles were: Analysis of Variance (ANOVA), Chi-Square Test, Student's T Test, Linear Regression, Pearson's Correlation Coefficient, Mann-Whitney U Test, Kruskal-Wallis Test, Shannon's Diversity Index, Tukey's Test, Cluster Analysis, Spearman's Rank Correlation Test and Principal Component Analysis. We conclude that statistical education for tropical biologists must abandon the old syllabus based on the mathematical side of statistics and concentrate on the correct selection of these and other procedures and tests, on their biological interpretation and on the use of reliable and friendly freeware. We think that their time will be better spent understanding and protecting tropical ecosystems than trying to learn the mathematical foundations of statistics: in most cases, a well designed one-semester course should be enough for their basic requirements.

Re-Evaluation of Event Correlations in Virtual California Using Statistical Analysis

NASA Astrophysics Data System (ADS)

Glasscoe, M. T.; Heflin, M. B.; Granat, R. A.; Yikilmaz, M. B.; Heien, E.; Rundle, J.; Donnellan, A.

2010-12-01

Fusing the results of simulation tools with statistical analysis methods has contributed to our better understanding of the earthquake process. In a previous study, we used a statistical method to investigate emergent phenomena in data produced by the Virtual California earthquake simulator. The analysis indicated that there were some interesting fault interactions and possible triggering and quiescence relationships between events. We have converted the original code from Matlab to python/C++ and are now evaluating data from the most recent version of Virtual California in order to analyze and compare any new behavior exhibited by the model. The Virtual California earthquake simulator can be used to study fault and stress interaction scenarios for realistic California earthquakes. The simulation generates a synthetic earthquake catalog of events with a minimum size of ~M 5.8 that can be evaluated using statistical analysis methods. Virtual California utilizes realistic fault geometries and a simple Amontons - Coulomb stick and slip friction law in order to drive the earthquake process by means of a back-slip model where loading of each segment occurs due to the accumulation of a slip deficit at the prescribed slip rate of the segment. Like any complex system, Virtual California may generate emergent phenomena unexpected even by its designers. In order to investigate this, we have developed a statistical method that analyzes the interaction between Virtual California fault elements and thereby determine whether events on any given fault elements show correlated behavior. Our method examines events on one fault element and then determines whether there is an associated event within a specified time window on a second fault element. Note that an event in our analysis is defined as any time an element slips, rather than any particular “earthquake” along the entire fault length. Results are then tabulated and then differenced with an expected correlation, calculated by assuming a uniform distribution of events in time. We generate a correlation score matrix, which indicates how weakly or strongly correlated each fault element is to every other in the course of the VC simulation. We calculate correlation scores by summing the difference between the actual and expected correlations over all time window lengths and normalizing by the time window size. The correlation score matrix can focus attention on the most interesting areas for more in-depth analysis of event correlation vs. time. The previous study included 59 faults (639 elements) in the model, which included all the faults save the creeping section of the San Andreas. The analysis spanned 40,000 yrs of Virtual California-generated earthquake data. The newly revised VC model includes 70 faults, 8720 fault elements, and spans 110,000 years. Due to computational considerations, we will evaluate the elements comprising the southern California region, which our previous study indicated showed interesting fault interaction and event triggering/quiescence relationships.

Search for correlation between geomagnetic disturbances and mortality

NASA Technical Reports Server (NTRS)

Lipa, B. J.; Sturrock, P. A.; Rogot, F.

1976-01-01

A search is conducted for a possible correlation between solar activity and myocardial infarction and stroke in the United States. A statistical analysis is performed using data on geomagnetic activity and the daily U.S. mortality due to coronary heart disease and stroke for the years 1962 through 1966. None of the results are found to yield any evidence of a correlation. It is concluded that correlations claimed by Soviet workers between geomagnetic activity and the incidence of various human diseases are probably not statistically significant or probably are not due to a causal relation between geomagnetic activity and disease.

Correlation and simple linear regression.

PubMed

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

2003-06-01

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

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)

The Relationship Between Procrastination, Learning Strategies and Statistics Anxiety Among Iranian College Students: A Canonical Correlation Analysis

PubMed Central

Vahedi, Shahrum; Farrokhi, Farahman; Gahramani, Farahnaz; Issazadegan, Ali

2012-01-01

Objective: Approximately 66-80%of graduate students experience statistics anxiety and some researchers propose that many students identify statistics courses as the most anxiety-inducing courses in their academic curriculums. As such, it is likely that statistics anxiety is, in part, responsible for many students delaying enrollment in these courses for as long as possible. This paper proposes a canonical model by treating academic procrastination (AP), learning strategies (LS) as predictor variables and statistics anxiety (SA) as explained variables. Methods: A questionnaire survey was used for data collection and 246-college female student participated in this study. To examine the mutually independent relations between procrastination, learning strategies and statistics anxiety variables, a canonical correlation analysis was computed. Results: Findings show that two canonical functions were statistically significant. The set of variables (metacognitive self-regulation, source management, preparing homework, preparing for test and preparing term papers) helped predict changes of statistics anxiety with respect to fearful behavior, Attitude towards math and class, Performance, but not Anxiety. Conclusion: These findings could be used in educational and psychological interventions in the context of statistics anxiety reduction. PMID:24644468

Accurate Structural Correlations from Maximum Likelihood Superpositions

PubMed Central

Theobald, Douglas L; Wuttke, Deborah S

2008-01-01

The cores of globular proteins are densely packed, resulting in complicated networks of structural interactions. These interactions in turn give rise to dynamic structural correlations over a wide range of time scales. Accurate analysis of these complex correlations is crucial for understanding biomolecular mechanisms and for relating structure to function. Here we report a highly accurate technique for inferring the major modes of structural correlation in macromolecules using likelihood-based statistical analysis of sets of structures. This method is generally applicable to any ensemble of related molecules, including families of nuclear magnetic resonance (NMR) models, different crystal forms of a protein, and structural alignments of homologous proteins, as well as molecular dynamics trajectories. Dominant modes of structural correlation are determined using principal components analysis (PCA) of the maximum likelihood estimate of the correlation matrix. The correlations we identify are inherently independent of the statistical uncertainty and dynamic heterogeneity associated with the structural coordinates. We additionally present an easily interpretable method (“PCA plots”) for displaying these positional correlations by color-coding them onto a macromolecular structure. Maximum likelihood PCA of structural superpositions, and the structural PCA plots that illustrate the results, will facilitate the accurate determination of dynamic structural correlations analyzed in diverse fields of structural biology. PMID:18282091

Correlative weighted stacking for seismic data in the wavelet domain

USGS Publications Warehouse

Zhang, S.; Xu, Y.; Xia, J.; ,

2004-01-01

Horizontal stacking plays a crucial role for modern seismic data processing, for it not only compresses random noise and multiple reflections, but also provides a foundational data for subsequent migration and inversion. However, a number of examples showed that random noise in adjacent traces exhibits correlation and coherence. The average stacking and weighted stacking based on the conventional correlative function all result in false events, which are caused by noise. Wavelet transform and high order statistics are very useful methods for modern signal processing. The multiresolution analysis in wavelet theory can decompose signal on difference scales, and high order correlative function can inhibit correlative noise, for which the conventional correlative function is of no use. Based on the theory of wavelet transform and high order statistics, high order correlative weighted stacking (HOCWS) technique is presented in this paper. Its essence is to stack common midpoint gathers after the normal moveout correction by weight that is calculated through high order correlative statistics in the wavelet domain. Synthetic examples demonstrate its advantages in improving the signal to noise (S/N) ration and compressing the correlative random noise.

The mediating effect of calling on the relationship between medical school students’ academic burnout and empathy

PubMed Central

2017-01-01

Purpose This study is aimed at identifying the relationships between medical school students’ academic burnout, empathy, and calling, and determining whether their calling has a mediating effect on the relationship between academic burnout and empathy. Methods A mixed method study was conducted. One hundred twenty-seven medical students completed a survey. Scales measuring academic burnout, medical students’ empathy, and calling were utilized. For statistical analysis, correlation analysis, descriptive statistics analysis, and hierarchical multiple regression analyses were conducted. For qualitative approach, eight medical students participated in a focus group interview. Results The study found that empathy has a statistically significant, negative correlation with academic burnout, while having a significant, positive correlation with calling. Sense of calling proved to be an effective mediator of the relationship between academic burnout and empathy. Conclusion This result demonstrates that calling is a key variable that mediates the relationship between medical students’ academic burnout and empathy. As such, this study provides baseline data for an education that could improve medical students’ empathy skills. PMID:28870019

Uses and Misuses of the Correlation Coefficient.

ERIC Educational Resources Information Center

Onwuegbuzie, Anthony J.; Daniel, Larry G.

The purpose of this paper is to provide an in-depth critical analysis of the use and misuse of correlation coefficients. Various analytical and interpretational misconceptions are reviewed, beginning with the egregious assumption that correlational statistics may be useful in inferring causality. Additional misconceptions, stemming from…

Sexual Harassment Retaliation Climate DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

exploratory factor analysis, and bivariate correlations (sample 1) 2) To determine the factor structure of the remaining (final) questions via...statistics, reliability analysis, exploratory factor analysis, and bivariate correlations of the prospective Sexual Harassment Retaliation Climate...reported by the survey requester). For information regarding the composition of sample, refer to Table 1. Table 1. Sample 1 Demographics n

CorSig: a general framework for estimating statistical significance of correlation and its application to gene co-expression analysis.

PubMed

Wang, Hong-Qiang; Tsai, Chung-Jui

2013-01-01

With the rapid increase of omics data, correlation analysis has become an indispensable tool for inferring meaningful associations from a large number of observations. Pearson correlation coefficient (PCC) and its variants are widely used for such purposes. However, it remains challenging to test whether an observed association is reliable both statistically and biologically. We present here a new method, CorSig, for statistical inference of correlation significance. CorSig is based on a biology-informed null hypothesis, i.e., testing whether the true PCC (ρ) between two variables is statistically larger than a user-specified PCC cutoff (τ), as opposed to the simple null hypothesis of ρ = 0 in existing methods, i.e., testing whether an association can be declared without a threshold. CorSig incorporates Fisher's Z transformation of the observed PCC (r), which facilitates use of standard techniques for p-value computation and multiple testing corrections. We compared CorSig against two methods: one uses a minimum PCC cutoff while the other (Zhu's procedure) controls correlation strength and statistical significance in two discrete steps. CorSig consistently outperformed these methods in various simulation data scenarios by balancing between false positives and false negatives. When tested on real-world Populus microarray data, CorSig effectively identified co-expressed genes in the flavonoid pathway, and discriminated between closely related gene family members for their differential association with flavonoid and lignin pathways. The p-values obtained by CorSig can be used as a stand-alone parameter for stratification of co-expressed genes according to their correlation strength in lieu of an arbitrary cutoff. CorSig requires one single tunable parameter, and can be readily extended to other correlation measures. Thus, CorSig should be useful for a wide range of applications, particularly for network analysis of high-dimensional genomic data. A web server for CorSig is provided at http://202.127.200.1:8080/probeWeb. R code for CorSig is freely available for non-commercial use at http://aspendb.uga.edu/downloads.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis.

PubMed

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-07-01

A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness.Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Code is available at https://github.com/aalto-ics-kepaco anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

metaCCA: summary statistics-based multivariate meta-analysis of genome-wide association studies using canonical correlation analysis

PubMed Central

Cichonska, Anna; Rousu, Juho; Marttinen, Pekka; Kangas, Antti J.; Soininen, Pasi; Lehtimäki, Terho; Raitakari, Olli T.; Järvelin, Marjo-Riitta; Salomaa, Veikko; Ala-Korpela, Mika; Ripatti, Samuli; Pirinen, Matti

2016-01-01

Motivation: A dominant approach to genetic association studies is to perform univariate tests between genotype-phenotype pairs. However, analyzing related traits together increases statistical power, and certain complex associations become detectable only when several variants are tested jointly. Currently, modest sample sizes of individual cohorts, and restricted availability of individual-level genotype-phenotype data across the cohorts limit conducting multivariate tests. Results: We introduce metaCCA, a computational framework for summary statistics-based analysis of a single or multiple studies that allows multivariate representation of both genotype and phenotype. It extends the statistical technique of canonical correlation analysis to the setting where original individual-level records are not available, and employs a covariance shrinkage algorithm to achieve robustness. Multivariate meta-analysis of two Finnish studies of nuclear magnetic resonance metabolomics by metaCCA, using standard univariate output from the program SNPTEST, shows an excellent agreement with the pooled individual-level analysis of original data. Motivated by strong multivariate signals in the lipid genes tested, we envision that multivariate association testing using metaCCA has a great potential to provide novel insights from already published summary statistics from high-throughput phenotyping technologies. Availability and implementation: Code is available at https://github.com/aalto-ics-kepaco Contacts: anna.cichonska@helsinki.fi or matti.pirinen@helsinki.fi Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153689

A powerful score-based test statistic for detecting gene-gene co-association.

PubMed

Xu, Jing; Yuan, Zhongshang; Ji, Jiadong; Zhang, Xiaoshuai; Li, Hongkai; Wu, Xuesen; Xue, Fuzhong; Liu, Yanxun

2016-01-29

The genetic variants identified by Genome-wide association study (GWAS) can only account for a small proportion of the total heritability for complex disease. The existence of gene-gene joint effects which contains the main effects and their co-association is one of the possible explanations for the "missing heritability" problems. Gene-gene co-association refers to the extent to which the joint effects of two genes differ from the main effects, not only due to the traditional interaction under nearly independent condition but the correlation between genes. Generally, genes tend to work collaboratively within specific pathway or network contributing to the disease and the specific disease-associated locus will often be highly correlated (e.g. single nucleotide polymorphisms (SNPs) in linkage disequilibrium). Therefore, we proposed a novel score-based statistic (SBS) as a gene-based method for detecting gene-gene co-association. Various simulations illustrate that, under different sample sizes, marginal effects of causal SNPs and co-association levels, the proposed SBS has the better performance than other existed methods including single SNP-based and principle component analysis (PCA)-based logistic regression model, the statistics based on canonical correlations (CCU), kernel canonical correlation analysis (KCCU), partial least squares path modeling (PLSPM) and delta-square (δ (2)) statistic. The real data analysis of rheumatoid arthritis (RA) further confirmed its advantages in practice. SBS is a powerful and efficient gene-based method for detecting gene-gene co-association.

Statistical tests for power-law cross-correlated processes

NASA Astrophysics Data System (ADS)

Podobnik, Boris; Jiang, Zhi-Qiang; Zhou, Wei-Xing; Stanley, H. Eugene

2011-12-01

For stationary time series, the cross-covariance and the cross-correlation as functions of time lag n serve to quantify the similarity of two time series. The latter measure is also used to assess whether the cross-correlations are statistically significant. For nonstationary time series, the analogous measures are detrended cross-correlations analysis (DCCA) and the recently proposed detrended cross-correlation coefficient, ρDCCA(T,n), where T is the total length of the time series and n the window size. For ρDCCA(T,n), we numerically calculated the Cauchy inequality -1≤ρDCCA(T,n)≤1. Here we derive -1≤ρDCCA(T,n)≤1 for a standard variance-covariance approach and for a detrending approach. For overlapping windows, we find the range of ρDCCA within which the cross-correlations become statistically significant. For overlapping windows we numerically determine—and for nonoverlapping windows we derive—that the standard deviation of ρDCCA(T,n) tends with increasing T to 1/T. Using ρDCCA(T,n) we show that the Chinese financial market's tendency to follow the U.S. market is extremely weak. We also propose an additional statistical test that can be used to quantify the existence of cross-correlations between two power-law correlated time series.

Large-angle correlations in the cosmic microwave background

NASA Astrophysics Data System (ADS)

Efstathiou, George; Ma, Yin-Zhe; Hanson, Duncan

2010-10-01

It has been argued recently by Copi et al. 2009 that the lack of large angular correlations of the CMB temperature field provides strong evidence against the standard, statistically isotropic, inflationary Lambda cold dark matter (ΛCDM) cosmology. We compare various estimators of the temperature correlation function showing how they depend on assumptions of statistical isotropy and how they perform on the Wilkinson Microwave Anisotropy Probe (WMAP) 5-yr Internal Linear Combination (ILC) maps with and without a sky cut. We show that the low multipole harmonics that determine the large-scale features of the temperature correlation function can be reconstructed accurately from the data that lie outside the sky cuts. The reconstructions are only weakly dependent on the assumed statistical properties of the temperature field. The temperature correlation functions computed from these reconstructions are in good agreement with those computed from the ILC map over the whole sky. We conclude that the large-scale angular correlation function for our realization of the sky is well determined. A Bayesian analysis of the large-scale correlations is presented, which shows that the data cannot exclude the standard ΛCDM model. We discuss the differences between our results and those of Copi et al. Either there exists a violation of statistical isotropy as claimed by Copi et al., or these authors have overestimated the significance of the discrepancy because of a posteriori choices of estimator, statistic and sky cut.

Importance of the Correlation between Width and Length in the Shape Analysis of Nanorods: Use of a 2D Size Plot To Probe Such a Correlation.

PubMed

Zhao, Zhihua; Zheng, Zhiqin; Roux, Clément; Delmas, Céline; Marty, Jean-Daniel; Kahn, Myrtil L; Mingotaud, Christophe

2016-08-22

Analysis of nanoparticle size through a simple 2D plot is proposed in order to extract the correlation between length and width in a collection or a mixture of anisotropic particles. Compared to the usual statistics on the length associated with a second and independent statistical analysis of the width, this simple plot easily points out the various types of nanoparticles and their (an)isotropy. For each class of nano-objects, the relationship between width and length (i.e., the strong or weak correlations between these two parameters) may suggest information concerning the nucleation/growth processes. It allows one to follow the effect on the shape and size distribution of physical or chemical processes such as simple ripening. Various electron microscopy pictures from the literature or from the authors' own syntheses are used as examples to demonstrate the efficiency and simplicity of the proposed 2D plot combined with a multivariate analysis. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Vibration Response Models of a Stiffened Aluminum Plate Excited by a Shaker

NASA Technical Reports Server (NTRS)

Cabell, Randolph H.

2008-01-01

Numerical models of structural-acoustic interactions are of interest to aircraft designers and the space program. This paper describes a comparison between two energy finite element codes, a statistical energy analysis code, a structural finite element code, and the experimentally measured response of a stiffened aluminum plate excited by a shaker. Different methods for modeling the stiffeners and the power input from the shaker are discussed. The results show that the energy codes (energy finite element and statistical energy analysis) accurately predicted the measured mean square velocity of the plate. In addition, predictions from an energy finite element code had the best spatial correlation with measured velocities. However, predictions from a considerably simpler, single subsystem, statistical energy analysis model also correlated well with the spatial velocity distribution. The results highlight a need for further work to understand the relationship between modeling assumptions and the prediction results.

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

Factors affecting the inter-annual to centennial timescale variability of Indian summer monsoon rainfall

NASA Astrophysics Data System (ADS)

Malik, Abdul; Brönnimann, Stefan

2017-09-01

The Modes of Ocean Variability (MOV) namely Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), and El Niño Southern Oscillation (ENSO) can have significant impacts on Indian Summer Monsoon Rainfall (ISMR) on different timescales. The timescales at which these MOV interacts with ISMR and the factors which may perturb their relationship with ISMR need to be investigated. We employ De-trended Cross-Correlation Analysis (DCCA), and De-trended Partial-Cross-Correlation Analysis (DPCCA) to study the timescales of interaction of ISMR with AMO, PDO, and ENSO using observational dataset (AD 1854-1999), and atmosphere-ocean-chemistry climate model simulations with SOCOL-MPIOM (AD 1600-1999). Further, this study uses De-trended Semi-Partial Cross-Correlation Analysis (DSPCCA) to address the relation between solar variability and the ISMR. We find statistically significant evidence of intrinsic correlations of ISMR with AMO, PDO, and ENSO on different timescales, consistent between model simulations and observations. However, the model fails to capture modulation in intrinsic relationship between ISRM and MOV due to external signals. Our analysis indicates that AMO is a potential source of non-stationary relationship between ISMR and ENSO. Furthermore, the pattern of correlation between ISMR and Total Solar Irradiance (TSI) is inconsistent between observations and model simulations. The observational dataset indicates statistically insignificant negative intrinsic correlation between ISMR and TSI on decadal-to-centennial timescales. This statistically insignificant negative intrinsic correlation is transformed to statistically significant positive extrinsic by AMO on 61-86-year timescale. We propose a new mechanism for Sun-monsoon connection which operates through AMO by changes in summer (June-September; JJAS) meridional gradient of tropospheric temperatures (ΔTTJJAS). There is a negative (positive) intrinsic correlation between ΔTTJJAS (AMO) and TSI. The negative intrinsic correlation between ΔTTJJAS and TSI indicates that high (low) solar activity weakens (strengthens) the meridional gradient of tropospheric temperature during the summer monsoon season and subsequently the weak (strong) ΔTTJJAS decreases (increases) the ISMR. However, the presence of AMO transforms the negative intrinsic relation between ΔTTJJAS and TSI into positive extrinsic and strengthens the ISMR. We conclude that the positive relation between ISMR and solar activity, as found by other authors, is mainly due to the effect of AMO on ISMR.

Factors affecting the inter-annual to centennial timescale variability of Indian summer monsoon rainfall

NASA Astrophysics Data System (ADS)

Malik, Abdul; Brönnimann, Stefan

2018-06-01

The Modes of Ocean Variability (MOV) namely Atlantic Multidecadal Oscillation (AMO), Pacific Decadal Oscillation (PDO), and El Niño Southern Oscillation (ENSO) can have significant impacts on Indian Summer Monsoon Rainfall (ISMR) on different timescales. The timescales at which these MOV interacts with ISMR and the factors which may perturb their relationship with ISMR need to be investigated. We employ De-trended Cross-Correlation Analysis (DCCA), and De-trended Partial-Cross-Correlation Analysis (DPCCA) to study the timescales of interaction of ISMR with AMO, PDO, and ENSO using observational dataset (AD 1854-1999), and atmosphere-ocean-chemistry climate model simulations with SOCOL-MPIOM (AD 1600-1999). Further, this study uses De-trended Semi-Partial Cross-Correlation Analysis (DSPCCA) to address the relation between solar variability and the ISMR. We find statistically significant evidence of intrinsic correlations of ISMR with AMO, PDO, and ENSO on different timescales, consistent between model simulations and observations. However, the model fails to capture modulation in intrinsic relationship between ISRM and MOV due to external signals. Our analysis indicates that AMO is a potential source of non-stationary relationship between ISMR and ENSO. Furthermore, the pattern of correlation between ISMR and Total Solar Irradiance (TSI) is inconsistent between observations and model simulations. The observational dataset indicates statistically insignificant negative intrinsic correlation between ISMR and TSI on decadal-to-centennial timescales. This statistically insignificant negative intrinsic correlation is transformed to statistically significant positive extrinsic by AMO on 61-86-year timescale. We propose a new mechanism for Sun-monsoon connection which operates through AMO by changes in summer (June-September; JJAS) meridional gradient of tropospheric temperatures (ΔTTJJAS). There is a negative (positive) intrinsic correlation between ΔTTJJAS (AMO) and TSI. The negative intrinsic correlation between ΔTTJJAS and TSI indicates that high (low) solar activity weakens (strengthens) the meridional gradient of tropospheric temperature during the summer monsoon season and subsequently the weak (strong) ΔTTJJAS decreases (increases) the ISMR. However, the presence of AMO transforms the negative intrinsic relation between ΔTTJJAS and TSI into positive extrinsic and strengthens the ISMR. We conclude that the positive relation between ISMR and solar activity, as found by other authors, is mainly due to the effect of AMO on ISMR.

Statistics for People Who (Think They) Hate Statistics. Third Edition

ERIC Educational Resources Information Center

Salkind, Neil J.

2007-01-01

This text teaches an often intimidating and difficult subject in a way that is informative, personable, and clear. The author takes students through various statistical procedures, beginning with correlation and graphical representation of data and ending with inferential techniques and analysis of variance. In addition, the text covers SPSS, and…

Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.

PubMed

Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg

2009-11-01

G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.

Neuronal Correlation Parameter and the Idea of Thermodynamic Entropy of an N-Body Gravitationally Bounded System.

PubMed

Haranas, Ioannis; Gkigkitzis, Ioannis; Kotsireas, Ilias; Austerlitz, Carlos

2017-01-01

Understanding how the brain encodes information and performs computation requires statistical and functional analysis. Given the complexity of the human brain, simple methods that facilitate the interpretation of statistical correlations among different brain regions can be very useful. In this report we introduce a numerical correlation measure that may serve the interpretation of correlational neuronal data, and may assist in the evaluation of different brain states. The description of the dynamical brain system, through a global numerical measure may indicate the presence of an action principle which may facilitate a application of physics principles in the study of the human brain and cognition.

Statistical functions and relevant correlation coefficients of clearness index

NASA Astrophysics Data System (ADS)

Pavanello, Diego; Zaaiman, Willem; Colli, Alessandra; Heiser, John; Smith, Scott

2015-08-01

This article presents a statistical analysis of the sky conditions, during years from 2010 to 2012, for three different locations: the Joint Research Centre site in Ispra (Italy, European Solar Test Installation - ESTI laboratories), the site of National Renewable Energy Laboratory in Golden (Colorado, USA) and the site of Brookhaven National Laboratories in Upton (New York, USA). The key parameter is the clearness index kT, a dimensionless expression of the global irradiance impinging upon a horizontal surface at a given instant of time. In the first part, the sky conditions are characterized using daily averages, giving a general overview of the three sites. In the second part the analysis is performed using data sets with a short-term resolution of 1 sample per minute, demonstrating remarkable properties of the statistical distributions of the clearness index, reinforced by a proof using fuzzy logic methods. Successively some time-dependent correlations between different meteorological variables are presented in terms of Pearson and Spearman correlation coefficients, and introducing a new one.

Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates.

PubMed

Xia, Li C; Steele, Joshua A; Cram, Jacob A; Cardon, Zoe G; Simmons, Sheri L; Vallino, Joseph J; Fuhrman, Jed A; Sun, Fengzhu

2011-01-01

The increasing availability of time series microbial community data from metagenomics and other molecular biological studies has enabled the analysis of large-scale microbial co-occurrence and association networks. Among the many analytical techniques available, the Local Similarity Analysis (LSA) method is unique in that it captures local and potentially time-delayed co-occurrence and association patterns in time series data that cannot otherwise be identified by ordinary correlation analysis. However LSA, as originally developed, does not consider time series data with replicates, which hinders the full exploitation of available information. With replicates, it is possible to understand the variability of local similarity (LS) score and to obtain its confidence interval. We extended our LSA technique to time series data with replicates and termed it extended LSA, or eLSA. Simulations showed the capability of eLSA to capture subinterval and time-delayed associations. We implemented the eLSA technique into an easy-to-use analytic software package. The software pipeline integrates data normalization, statistical correlation calculation, statistical significance evaluation, and association network construction steps. We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified. The extended LSA analysis technique was demonstrated to reveal statistically significant local and potentially time-delayed association patterns in replicated time series data beyond that of ordinary correlation analysis. These statistically significant associations can provide insights to the real dynamics of biological systems. The newly designed eLSA software efficiently streamlines the analysis and is freely available from the eLSA homepage, which can be accessed at http://meta.usc.edu/softs/lsa.

Extended local similarity analysis (eLSA) of microbial community and other time series data with replicates

PubMed Central

2011-01-01

Background The increasing availability of time series microbial community data from metagenomics and other molecular biological studies has enabled the analysis of large-scale microbial co-occurrence and association networks. Among the many analytical techniques available, the Local Similarity Analysis (LSA) method is unique in that it captures local and potentially time-delayed co-occurrence and association patterns in time series data that cannot otherwise be identified by ordinary correlation analysis. However LSA, as originally developed, does not consider time series data with replicates, which hinders the full exploitation of available information. With replicates, it is possible to understand the variability of local similarity (LS) score and to obtain its confidence interval. Results We extended our LSA technique to time series data with replicates and termed it extended LSA, or eLSA. Simulations showed the capability of eLSA to capture subinterval and time-delayed associations. We implemented the eLSA technique into an easy-to-use analytic software package. The software pipeline integrates data normalization, statistical correlation calculation, statistical significance evaluation, and association network construction steps. We applied the eLSA technique to microbial community and gene expression datasets, where unique time-dependent associations were identified. Conclusions The extended LSA analysis technique was demonstrated to reveal statistically significant local and potentially time-delayed association patterns in replicated time series data beyond that of ordinary correlation analysis. These statistically significant associations can provide insights to the real dynamics of biological systems. The newly designed eLSA software efficiently streamlines the analysis and is freely available from the eLSA homepage, which can be accessed at http://meta.usc.edu/softs/lsa. PMID:22784572

Signatures of criticality arise from random subsampling in simple population models.

PubMed

Nonnenmacher, Marcel; Behrens, Christian; Berens, Philipp; Bethge, Matthias; Macke, Jakob H

2017-10-01

The rise of large-scale recordings of neuronal activity has fueled the hope to gain new insights into the collective activity of neural ensembles. How can one link the statistics of neural population activity to underlying principles and theories? One attempt to interpret such data builds upon analogies to the behaviour of collective systems in statistical physics. Divergence of the specific heat-a measure of population statistics derived from thermodynamics-has been used to suggest that neural populations are optimized to operate at a "critical point". However, these findings have been challenged by theoretical studies which have shown that common inputs can lead to diverging specific heat. Here, we connect "signatures of criticality", and in particular the divergence of specific heat, back to statistics of neural population activity commonly studied in neural coding: firing rates and pairwise correlations. We show that the specific heat diverges whenever the average correlation strength does not depend on population size. This is necessarily true when data with correlations is randomly subsampled during the analysis process, irrespective of the detailed structure or origin of correlations. We also show how the characteristic shape of specific heat capacity curves depends on firing rates and correlations, using both analytically tractable models and numerical simulations of a canonical feed-forward population model. To analyze these simulations, we develop efficient methods for characterizing large-scale neural population activity with maximum entropy models. We find that, consistent with experimental findings, increases in firing rates and correlation directly lead to more pronounced signatures. Thus, previous reports of thermodynamical criticality in neural populations based on the analysis of specific heat can be explained by average firing rates and correlations, and are not indicative of an optimized coding strategy. We conclude that a reliable interpretation of statistical tests for theories of neural coding is possible only in reference to relevant ground-truth models.

A statistical analysis of the impact of advertising signs on road safety.

PubMed

Yannis, George; Papadimitriou, Eleonora; Papantoniou, Panagiotis; Voulgari, Chrisoula

2013-01-01

This research aims to investigate the impact of advertising signs on road safety. An exhaustive review of international literature was carried out on the effect of advertising signs on driver behaviour and safety. Moreover, a before-and-after statistical analysis with control groups was applied on several road sites with different characteristics in the Athens metropolitan area, in Greece, in order to investigate the correlation between the placement or removal of advertising signs and the related occurrence of road accidents. Road accident data for the 'before' and 'after' periods on the test sites and the control sites were extracted from the database of the Hellenic Statistical Authority, and the selected 'before' and 'after' periods vary from 2.5 to 6 years. The statistical analysis shows no statistical correlation between road accidents and advertising signs in none of the nine sites examined, as the confidence intervals of the estimated safety effects are non-significant at 95% confidence level. This can be explained by the fact that, in the examined road sites, drivers are overloaded with information (traffic signs, directions signs, labels of shops, pedestrians and other vehicles, etc.) so that the additional information load from advertising signs may not further distract them.

Quantitative analysis of spatial variability of geotechnical parameters

NASA Astrophysics Data System (ADS)

Fang, Xing

2018-04-01

Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

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

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

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

Comparative Analysis of Serum (Anti)oxidative Status Parameters in Healthy Persons

PubMed Central

Jansen, Eugène HJM; Ruskovska, Tatjana

2013-01-01

Five antioxidant and two oxidative stress assays were applied to serum samples of 43 healthy males. The antioxidant tests showed different inter-assay correlations. A very good correlation of 0.807 was observed between the ferric reducing ability of plasma (FRAP) and total antioxidant status (TAS) assay and also a fair correlation of 0.501 between the biological antioxidant potential (BAP) and TAS assay. There was no statistically significant correlation between the BAP and FRAP assay. The anti-oxidant assays have a high correlation with uric acid, especially the TAS (0.922) and FRAP assay (0.869). The BAP assay has a much lower and no statistically significant correlation with uric acid (0.302), which makes BAP more suitable for the antioxidant status. The total thiol assay showed no statistically significant correlation with uric acid (0.114). The total thiol assay, which is based on a completely different principle, showed a good and statistically significant correlation with the BAP assay (0.510) and also to the TAS assay, but to a lower and not significant extent (0.279) and not with the FRAP assay (−0.008). The oxy-adsorbent test (OXY) assay has no correlation with any of the other assays tested. The oxidative stress assays, reactive oxygen metabolites (ROM) and total oxidant status (TOS), based on a different principle, do not show a statistically significant correlation with the serum samples in this study. Both assays showed a negative, but not significant, correlation with the antioxidant assays. In conclusion, the ROM, TOS, BAP and TTP assays are based on different principles and will have an additional value when a combination of these assays will be applied in large-scale population studies. PMID:23507749

Pelvic floor muscle strength of women consulting at the gynecology outpatient clinics and its correlation with sexual dysfunction: A cross-sectional study.

PubMed

Ozdemir, Filiz Ciledag; Pehlivan, Erkan; Melekoglu, Rauf

2017-01-01

To investigate the pelvic floor muscle strength of the women andevaluateits possible correlation with sexual dysfunction. In this cross-sectional type study, stratified clusters were used for the sampling method. Index of Female Sexual Function (IFSF) worksheetwere used for questions on sexual function. The pelvic floor muscle strength of subjects was assessed byperineometer. The chi-squared test, logistic regression and Pearson's correlation analysis were used for the statistical analysis. Four hundred thirty primiparous women, mean age 38.5 participated in this study. The average pelvic floor muscle strength value was found 31.4±9.6 cm H 2 O and the average Index of Female Sexual Function (IFSF) score was found 26.5±6.9. Parity (odds ratio OR=5.546) and age 40 or higher (OR=3.484) were found correlated with pelvic floor muscle weakness (p<0.05). The factors directly correlated with sexual dysfunction were found being overweight (OR=2.105) and age 40 or higher (OR=2.451) (p<0.05). Pearson's correlation analysis showed that there was a statistically significantlinear correlation between the muscular strength of the pelvic floor and sexual function (p=0.001). The results suggested subjects with decreased pelvic floor muscle strength value had higher frequency of sexual dysfunction.

Comparative analysis of perceptual evaluation, acoustic analysis and indirect laryngoscopy for vocal assessment of a population with vocal complaint.

PubMed

Nemr, Kátia; Amar, Ali; Abrahão, Marcio; Leite, Grazielle Capatto de Almeida; Köhle, Juliana; Santos, Alexandra de O; Correa, Luiz Artur Costa

2005-01-01

As a result of technology evolution and development, methods of voice evaluation have changed both in medical and speech and language pathology practice. To relate the results of perceptual evaluation, acoustic analysis and medical evaluation in the diagnosis of vocal and/or laryngeal affections of the population with vocal complaint. Clinical prospective. 29 people that attended vocal health protection campaign were evaluated. They were submitted to perceptual evaluation (AFPA), acoustic analysis (AA), indirect laryngoscopy (LI) and telelaryngoscopy (TL). Correlations between medical and speech language pathology evaluation methods were established, verifying possible statistical signification with the application of Fischer Exact Test. There were statistically significant results in the correlation between AFPA and LI, AFPA and TL, LI and TL. This research study conducted in a vocal health protection campaign presented correlations between speech language pathology evaluation and perceptual evaluation and clinical evaluation, as well as between vocal affection and/or laryngeal medical exams.

Understanding the Relationship between School-Based Management, Emotional Intelligence and Performance of Religious Upper Secondary School Principals in Banten Province

ERIC Educational Resources Information Center

Muslihah, Oleh Eneng

2015-01-01

The research examines the correlation between the understanding of school-based management, emotional intelligences and headmaster performance. Data was collected, using quantitative methods. The statistical analysis used was the Pearson Correlation, and multivariate regression analysis. The results of this research suggest firstly that there is…

The Problem of Auto-Correlation in Parasitology

PubMed Central

Pollitt, Laura C.; Reece, Sarah E.; Mideo, Nicole; Nussey, Daniel H.; Colegrave, Nick

2012-01-01

Explaining the contribution of host and pathogen factors in driving infection dynamics is a major ambition in parasitology. There is increasing recognition that analyses based on single summary measures of an infection (e.g., peak parasitaemia) do not adequately capture infection dynamics and so, the appropriate use of statistical techniques to analyse dynamics is necessary to understand infections and, ultimately, control parasites. However, the complexities of within-host environments mean that tracking and analysing pathogen dynamics within infections and among hosts poses considerable statistical challenges. Simple statistical models make assumptions that will rarely be satisfied in data collected on host and parasite parameters. In particular, model residuals (unexplained variance in the data) should not be correlated in time or space. Here we demonstrate how failure to account for such correlations can result in incorrect biological inference from statistical analysis. We then show how mixed effects models can be used as a powerful tool to analyse such repeated measures data in the hope that this will encourage better statistical practices in parasitology. PMID:22511865

Statistical analysis of co-occurrence patterns in microbial presence-absence datasets

PubMed Central

Bewick, Sharon; Thielen, Peter; Mehoke, Thomas; Breitwieser, Florian P.; Paudel, Shishir; Adhikari, Arjun; Wolfe, Joshua; Slud, Eric V.; Karig, David; Fagan, William F.

2017-01-01

Drawing on a long history in macroecology, correlation analysis of microbiome datasets is becoming a common practice for identifying relationships or shared ecological niches among bacterial taxa. However, many of the statistical issues that plague such analyses in macroscale communities remain unresolved for microbial communities. Here, we discuss problems in the analysis of microbial species correlations based on presence-absence data. We focus on presence-absence data because this information is more readily obtainable from sequencing studies, especially for whole-genome sequencing, where abundance estimation is still in its infancy. First, we show how Pearson’s correlation coefficient (r) and Jaccard’s index (J)–two of the most common metrics for correlation analysis of presence-absence data–can contradict each other when applied to a typical microbiome dataset. In our dataset, for example, 14% of species-pairs predicted to be significantly correlated by r were not predicted to be significantly correlated using J, while 37.4% of species-pairs predicted to be significantly correlated by J were not predicted to be significantly correlated using r. Mismatch was particularly common among species-pairs with at least one rare species (<10% prevalence), explaining why r and J might differ more strongly in microbiome datasets, where there are large numbers of rare taxa. Indeed 74% of all species-pairs in our study had at least one rare species. Next, we show how Pearson’s correlation coefficient can result in artificial inflation of positive taxon relationships and how this is a particular problem for microbiome studies. We then illustrate how Jaccard’s index of similarity (J) can yield improvements over Pearson’s correlation coefficient. However, the standard null model for Jaccard’s index is flawed, and thus introduces its own set of spurious conclusions. We thus identify a better null model based on a hypergeometric distribution, which appropriately corrects for species prevalence. This model is available from recent statistics literature, and can be used for evaluating the significance of any value of an empirically observed Jaccard’s index. The resulting simple, yet effective method for handling correlation analysis of microbial presence-absence datasets provides a robust means of testing and finding relationships and/or shared environmental responses among microbial taxa. PMID:29145425

Statistical analysis of 4 types of neck whiplash injuries based on classical meridian theory.

PubMed

Chen, Yemeng; Zhao, Yan; Xue, Xiaolin; Li, Hui; Wu, Xiuyan; Zhang, Qunce; Zheng, Xin; Wang, Tianfang

2015-01-01

As one component of the Chinese medicine meridian system, the meridian sinew (Jingjin, (see text), tendino-musculo) is specially described as being for acupuncture treatment of the musculoskeletal system because of its dynamic attributes and tender point correlations. In recent decades, the therapeutic importance of the sinew meridian has become revalued in clinical application. Based on this theory, the authors have established therapeutic strategies of acupuncture treatment in Whiplash-Associated Disorders (WAD) by categorizing four types of neck symptom presentations. The advantage of this new system is to make it much easier for the clinician to find effective acupuncture points. This study attempts to prove the significance of the proposed therapeutic strategies by analyzing data collected from a clinical survey of various WAD using non-supervised statistical methods, such as correlation analysis, factor analysis, and cluster analysis. The clinical survey data have successfully verified discrete characteristics of four neck syndromes, based upon the range of motion (ROM) and tender point location findings. A summary of the relationships among the symptoms of the four neck syndromes has shown the correlation coefficient as having a statistical significance (P < 0.01 or P < 0.05), especially with regard to ROM. Furthermore, factor and cluster analyses resulted in a total of 11 categories of general symptoms, which implies syndrome factors are more related to the Liver, as originally described in classical theory. The hypothesis of meridian sinew syndromes in WAD is clearly supported by the statistical analysis of the clinical trials. This new discovery should be beneficial in improving therapeutic outcomes.

Theory of Financial Risk and Derivative Pricing

NASA Astrophysics Data System (ADS)

Bouchaud, Jean-Philippe; Potters, Marc

2009-01-01

Foreword; Preface; 1. Probability theory: basic notions; 2. Maximum and addition of random variables; 3. Continuous time limit, Ito calculus and path integrals; 4. Analysis of empirical data; 5. Financial products and financial markets; 6. Statistics of real prices: basic results; 7. Non-linear correlations and volatility fluctuations; 8. Skewness and price-volatility correlations; 9. Cross-correlations; 10. Risk measures; 11. Extreme correlations and variety; 12. Optimal portfolios; 13. Futures and options: fundamental concepts; 14. Options: hedging and residual risk; 15. Options: the role of drift and correlations; 16. Options: the Black and Scholes model; 17. Options: some more specific problems; 18. Options: minimum variance Monte-Carlo; 19. The yield curve; 20. Simple mechanisms for anomalous price statistics; Index of most important symbols; Index.

Theory of Financial Risk and Derivative Pricing - 2nd Edition

NASA Astrophysics Data System (ADS)

Bouchaud, Jean-Philippe; Potters, Marc

2003-12-01

Foreword; Preface; 1. Probability theory: basic notions; 2. Maximum and addition of random variables; 3. Continuous time limit, Ito calculus and path integrals; 4. Analysis of empirical data; 5. Financial products and financial markets; 6. Statistics of real prices: basic results; 7. Non-linear correlations and volatility fluctuations; 8. Skewness and price-volatility correlations; 9. Cross-correlations; 10. Risk measures; 11. Extreme correlations and variety; 12. Optimal portfolios; 13. Futures and options: fundamental concepts; 14. Options: hedging and residual risk; 15. Options: the role of drift and correlations; 16. Options: the Black and Scholes model; 17. Options: some more specific problems; 18. Options: minimum variance Monte-Carlo; 19. The yield curve; 20. Simple mechanisms for anomalous price statistics; Index of most important symbols; Index.

Statistics Anxiety and Worry: The Roles of Worry Beliefs, Negative Problem Orientation, and Cognitive Avoidance

ERIC Educational Resources Information Center

Williams, Amanda S.

2015-01-01

Statistics anxiety is a common problem for graduate students. This study explores the multivariate relationship between a set of worry-related variables and six types of statistics anxiety. Canonical correlation analysis indicates a significant relationship between the two sets of variables. Findings suggest that students who are more intolerant…

One Hundred Ways to be Non-Fickian - A Rigorous Multi-Variate Statistical Analysis of Pore-Scale Transport

NASA Astrophysics Data System (ADS)

Most, Sebastian; Nowak, Wolfgang; Bijeljic, Branko

2015-04-01

Fickian transport in groundwater flow is the exception rather than the rule. Transport in porous media is frequently simulated via particle methods (i.e. particle tracking random walk (PTRW) or continuous time random walk (CTRW)). These methods formulate transport as a stochastic process of particle position increments. At the pore scale, geometry and micro-heterogeneities prohibit the commonly made assumption of independent and normally distributed increments to represent dispersion. Many recent particle methods seek to loosen this assumption. Hence, it is important to get a better understanding of the processes at pore scale. For our analysis we track the positions of 10.000 particles migrating through the pore space over time. The data we use come from micro CT scans of a homogeneous sandstone and encompass about 10 grain sizes. Based on those images we discretize the pore structure and simulate flow at the pore scale based on the Navier-Stokes equation. This flow field realistically describes flow inside the pore space and we do not need to add artificial dispersion during the transport simulation. Next, we use particle tracking random walk and simulate pore-scale transport. Finally, we use the obtained particle trajectories to do a multivariate statistical analysis of the particle motion at the pore scale. Our analysis is based on copulas. Every multivariate joint distribution is a combination of its univariate marginal distributions. The copula represents the dependence structure of those univariate marginals and is therefore useful to observe correlation and non-Gaussian interactions (i.e. non-Fickian transport). The first goal of this analysis is to better understand the validity regions of commonly made assumptions. We are investigating three different transport distances: 1) The distance where the statistical dependence between particle increments can be modelled as an order-one Markov process. This would be the Markovian distance for the process, where the validity of yet-unexplored non-Gaussian-but-Markovian random walks start. 2) The distance where bivariate statistical dependence simplifies to a multi-Gaussian dependence based on simple linear correlation (validity of correlated PTRW/CTRW). 3) The distance of complete statistical independence (validity of classical PTRW/CTRW). The second objective is to reveal characteristic dependencies influencing transport the most. Those dependencies can be very complex. Copulas are highly capable of representing linear dependence as well as non-linear dependence. With that tool we are able to detect persistent characteristics dominating transport even across different scales. The results derived from our experimental data set suggest that there are many more non-Fickian aspects of pore-scale transport than the univariate statistics of longitudinal displacements. Non-Fickianity can also be found in transverse displacements, and in the relations between increments at different time steps. Also, the found dependence is non-linear (i.e. beyond simple correlation) and persists over long distances. Thus, our results strongly support the further refinement of techniques like correlated PTRW or correlated CTRW towards non-linear statistical relations.

Advanced Statistics for Exotic Animal Practitioners.

PubMed

Hodsoll, John; Hellier, Jennifer M; Ryan, Elizabeth G

2017-09-01

Correlation and regression assess the association between 2 or more variables. This article reviews the core knowledge needed to understand these analyses, moving from visual analysis in scatter plots through correlation, simple and multiple linear regression, and logistic regression. Correlation estimates the strength and direction of a relationship between 2 variables. Regression can be considered more general and quantifies the numerical relationships between an outcome and 1 or multiple variables in terms of a best-fit line, allowing predictions to be made. Each technique is discussed with examples and the statistical assumptions underlying their correct application. Copyright © 2017 Elsevier Inc. All rights reserved.

MWASTools: an R/bioconductor package for metabolome-wide association studies.

PubMed

Rodriguez-Martinez, Andrea; Posma, Joram M; Ayala, Rafael; Neves, Ana L; Anwar, Maryam; Petretto, Enrico; Emanueli, Costanza; Gauguier, Dominique; Nicholson, Jeremy K; Dumas, Marc-Emmanuel

2018-03-01

MWASTools is an R package designed to provide an integrated pipeline to analyse metabonomic data in large-scale epidemiological studies. Key functionalities of our package include: quality control analysis; metabolome-wide association analysis using various models (partial correlations, generalized linear models); visualization of statistical outcomes; metabolite assignment using statistical total correlation spectroscopy (STOCSY); and biological interpretation of metabolome-wide association studies results. The MWASTools R package is implemented in R (version  > =3.4) and is available from Bioconductor: https://bioconductor.org/packages/MWASTools/. m.dumas@imperial.ac.uk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

The Relationship Between Surface Curvature and Abdominal Aortic Aneurysm Wall Stress.

PubMed

de Galarreta, Sergio Ruiz; Cazón, Aitor; Antón, Raúl; Finol, Ender A

2017-08-01

The maximum diameter (MD) criterion is the most important factor when predicting risk of rupture of abdominal aortic aneurysms (AAAs). An elevated wall stress has also been linked to a high risk of aneurysm rupture, yet is an uncommon clinical practice to compute AAA wall stress. The purpose of this study is to assess whether other characteristics of the AAA geometry are statistically correlated with wall stress. Using in-house segmentation and meshing algorithms, 30 patient-specific AAA models were generated for finite element analysis (FEA). These models were subsequently used to estimate wall stress and maximum diameter and to evaluate the spatial distributions of wall thickness, cross-sectional diameter, mean curvature, and Gaussian curvature. Data analysis consisted of statistical correlations of the aforementioned geometry metrics with wall stress for the 30 AAA inner and outer wall surfaces. In addition, a linear regression analysis was performed with all the AAA wall surfaces to quantify the relationship of the geometric indices with wall stress. These analyses indicated that while all the geometry metrics have statistically significant correlations with wall stress, the local mean curvature (LMC) exhibits the highest average Pearson's correlation coefficient for both inner and outer wall surfaces. The linear regression analysis revealed coefficients of determination for the outer and inner wall surfaces of 0.712 and 0.516, respectively, with LMC having the largest effect on the linear regression equation with wall stress. This work underscores the importance of evaluating AAA mean wall curvature as a potential surrogate for wall stress.

Soil erosion assessment and its correlation with landslide events using remote sensing data and GIS: a case study at Penang Island, Malaysia.

PubMed

Pradhan, Biswajeet; Chaudhari, Amruta; Adinarayana, J; Buchroithner, Manfred F

2012-01-01

In this paper, an attempt has been made to assess, prognosis and observe dynamism of soil erosion by universal soil loss equation (USLE) method at Penang Island, Malaysia. Multi-source (map-, space- and ground-based) datasets were used to obtain both static and dynamic factors of USLE, and an integrated analysis was carried out in raster format of GIS. A landslide location map was generated on the basis of image elements interpretation from aerial photos, satellite data and field observations and was used to validate soil erosion intensity in the study area. Further, a statistical-based frequency ratio analysis was carried out in the study area for correlation purposes. The results of the statistical correlation showed a satisfactory agreement between the prepared USLE-based soil erosion map and landslide events/locations, and are directly proportional to each other. Prognosis analysis on soil erosion helps the user agencies/decision makers to design proper conservation planning program to reduce soil erosion. Temporal statistics on soil erosion in these dynamic and rapid developments in Penang Island indicate the co-existence and balance of ecosystem.

Correlation between quantitative traits and correlation between corresponding LOD scores: detection of pleiotropic effects.

PubMed

Ulgen, Ayse; Han, Zhihua; Li, Wentian

2003-12-31

We address the question of whether statistical correlations among quantitative traits lead to correlation of linkage results of these traits. Five measured quantitative traits (total cholesterol, fasting glucose, HDL cholesterol, blood pressure, and triglycerides), and one derived quantitative trait (total cholesterol divided by the HDL cholesterol) are used for phenotype correlation studies. Four of them are used for linkage analysis. We show that although correlation among phenotypes partially reflects the correlation among linkage analysis results, the LOD-score correlations are on average low. The most significant peaks found by using different traits do not often overlap. Studying covariances at specific locations in LOD scores may provide clues for further bivariate linkage analyses.

A correlational analysis of the effects of changing environmental conditions on the NR atomic hydrogen maser

NASA Technical Reports Server (NTRS)

Dragonette, Richard A.; Suter, Joseph J.

1992-01-01

An extensive statistical analysis has been undertaken to determine if a correlation exists between changes in an NR atomic hydrogen maser's frequency offset and changes in environmental conditions. Correlation analyses have been performed comparing barometric pressure, humidity, and temperature with maser frequency offset as a function of time for periods ranging from 5.5 to 17 days. Semipartial correlation coefficients as large as -0.9 have been found between barometric pressure and maser frequency offset. Correlation between maser frequency offset and humidity was small compared to barometric pressure and unpredictable. Analysis of temperature data indicates that in the most current design, temperature does not significantly affect maser frequency offset.

Choroidal Thickness Analysis in Patients with Usher Syndrome Type 2 Using EDI OCT.

PubMed

Colombo, L; Sala, B; Montesano, G; Pierrottet, C; De Cillà, S; Maltese, P; Bertelli, M; Rossetti, L

2015-01-01

To portray Usher Syndrome type 2, analyzing choroidal thickness and comparing data reported in published literature on RP and healthy subjects. Methods. 20 eyes of 10 patients with clinical signs and genetic diagnosis of Usher Syndrome type 2. Each patient underwent a complete ophthalmologic examination including Best Corrected Visual Acuity (BCVA), intraocular pressure (IOP), axial length (AL), automated visual field (VF), and EDI OCT. Both retinal and choroidal measures were measured. Statistical analysis was performed to correlate choroidal thickness with age, BCVA, IOP, AL, VF, and RT. Comparison with data about healthy people and nonsyndromic RP patients was performed. Results. Mean subfoveal choroidal thickness (SFCT) was 248.21 ± 79.88 microns. SFCT was statistically significant correlated with age (correlation coefficient -0.7248179, p < 0.01). No statistically significant correlation was found between SFCT and BCVA, IOP, AL, VF, and RT. SFCT was reduced if compared to healthy subjects (p < 0.01). No difference was found when compared to choroidal thickness from nonsyndromic RP patients (p = 0.2138). Conclusions. Our study demonstrated in vivo choroidal thickness reduction in patients with Usher Syndrome type 2. These data are important for the comprehension of mechanisms of disease and for the evaluation of therapeutic approaches.

Correlation of gingival thickness with gingival width, probing depth, and papillary fill in maxillary anterior teeth in students of a dental college in Navi Mumbai

PubMed Central

Singh, Jyotsna; Rathod, Varsha J.; Rao, Prajakta R.; Patil, Aardra A.; Langade, Deepak G.; Singh, Roshan K.

2016-01-01

Context: The gingival biotype is of utmost importance for esthetics and biologic function. Anatomical characteristic of periodontium such as gingival thickness (GT), width of keratinized gingiva, and alveolar bone morphology will determine the behavior of periodontium when subjected to physical, chemical, or bacterial insult or during therapeutic procedure. Aims: The aim of this study was to correlate the GT with gingival width (GW), probing depth (PD), and papillary fill (PF) in relation to maxillary anterior region. Settings and Design: Undergraduate dental students and interns from a dental college in Navi Mumbai were enrolled in the study according to the inclusion criteria. Six teeth per subject were assessed; a total of 2178 maxillary anterior teeth were examined. Subjects and Methods: Subjects were examined clinically for GT, width of keratinized gingiva, pocket depth, and interdental PF. The data obtained was tabulated and subjected to statistical analysis. Statistical Analysis Used: Spearman's correlation analysis test was performed to find the correlation of GT with GW, PD, and PF. Results: Positive correlation was found between GT and GW (r = 0.241). No significant correlation could be found between GT and PD; and between GT and PF. Conclusions: The present study confirmed a positive correlation between GT and GW. A weak negative correlation was found between GT and PD. PMID:27994424

Sympathetic Nerve Injury in Thyroid Cancer.

PubMed

Diamantis, Evangelos; Farmaki, Paraskevi; Savvanis, Spyridon; Athanasiadis, Georgios; Troupis, Theodoros; Damaskos, Christos

The double innervation of the thyroid comes from the sympathetic and parasympathetic nervous system. Injury rates during surgery are at 30% but can be minimized by upwardly preparing the thyroid vessels at the level of thyroid capsule. Several factors have been accused of increasing the risk of injury including age and tumor size. Our aim was to investigate of there is indeed any possible correlations between these factors and a possible increase in injury rates following thyroidectomy. Seven studies were included in the meta-analysis. Statistical correlation was observed for a positive relationship between injury of the sympathetic nerve and thyroid malignancy surgery (p 2 = 74%) No statistical correlations were observed for a negative or positive relationship between injury of the sympathetic nerve and tumor size. There was also no statistically significant value observed for the correlation of the patients' age with the risk of sympathetic nerve injury (p = 0.388). Lack of significant correlation reported could be due to the small number of studies and great heterogeneity between them.

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation

PubMed Central

Wang, Yikai; Kang, Jian; Kemmer, Phebe B.; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package “DensParcorr” can be downloaded from CRAN for implementing the proposed statistical methods. PMID:27242395

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.

PubMed

Wang, Yikai; Kang, Jian; Kemmer, Phebe B; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package "DensParcorr" can be downloaded from CRAN for implementing the proposed statistical methods.

[Relativity among starch quantity, polysaccharides content and total alkaloid content of Dendrobium loddigesii].

PubMed

Zhu, Hua; Teng, Jianbei; Cai, Yi; Liang, Jie; Zhu, Yilin; Wei, Tao

2011-12-01

To find out the relativity among starch quantity, polysaccharides content and total alkaloid content of Dendrobium loddigesii. Microscopy-counting process was applied to starch quantity statistics, sulfuric acid-anthrone colorimetry was used to assay polysaccharides content and bromocresol green colorimetry was used to assay alkaloid content. Pearson product moment correlation analysis, Kendall's rank correlation analysis and Spearman's concordance coefficient analysis were applied to study their relativity. Extremely significant positive correlation was found between starch quantity and polysaccharides content, and significant negative correlation between alkaloid content and starch quantity was discovered, as well was between alkaloid content and polysaccharides content.

A note on the correlation between circular and linear variables with an application to wind direction and air temperature data in a Mediterranean climate

NASA Astrophysics Data System (ADS)

Lototzis, M.; Papadopoulos, G. K.; Droulia, F.; Tseliou, A.; Tsiros, I. X.

2018-04-01

There are several cases where a circular variable is associated with a linear one. A typical example is wind direction that is often associated with linear quantities such as air temperature and air humidity. The analysis of a statistical relationship of this kind can be tested by the use of parametric and non-parametric methods, each of which has its own advantages and drawbacks. This work deals with correlation analysis using both the parametric and the non-parametric procedure on a small set of meteorological data of air temperature and wind direction during a summer period in a Mediterranean climate. Correlations were examined between hourly, daily and maximum-prevailing values, under typical and non-typical meteorological conditions. Both tests indicated a strong correlation between mean hourly wind directions and mean hourly air temperature, whereas mean daily wind direction and mean daily air temperature do not seem to be correlated. In some cases, however, the two procedures were found to give quite dissimilar levels of significance on the rejection or not of the null hypothesis of no correlation. The simple statistical analysis presented in this study, appropriately extended in large sets of meteorological data, may be a useful tool for estimating effects of wind on local climate studies.

On the diffuse fraction of daily and monthly global radiation for the island of Cyprus

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

Jacovides, C.P.; Hadjioannou, L.; Pashiardis, S.

1996-06-01

Six years of hourly global and diffuse irradiation measurements on a horizontal surface performed at Athalassa, Cyprus, are used to establish a relationship between the daily diffuse fraction and the daily clearness index. Two types of correlations - yearly and seasonal - have been developed. These correlations, of first and third order in the clearness index are compared to the various correlations established by Collares-Pereira and Rabl (1979), Newland (1989), Erbs et al. (1982), Rao et al. (1984), Page (1961), Liu and Jordan (1960) and Lalas et al. (1987). The comparison has been performed in terms of the widely usedmore » statistical indicators (MBE) and (RMSE) errors; and additional statistical indicator, the t-statistic, combining the earlier indicators, is introduced. The results indicate that the proposed yearly correlation matches the earlier correlations quite closely and all correlations examined yield results that are statistically significant. For large K{sub t} > 0.60 values, most of the earlier correlations exhibit a slight tendency to systematically overestimate the diffuse fraction. This marginal disagreement between the earlier correlations and the proposed model is probably significantly affected by the clear sky conditions that prevail over Cyprus for most of the time as well as atmospheric humidity content. It is clear that the standard correlations examined in this analysis appear to be location-independent models for diffuse irradiation predictions, at least for the Cyprus case. 13 refs., 5 figs., 4 tabs.« less

Quantification and Correlation of Angiogenesis with Macrophages by Histomorphometric Method in Central and Peripheral Giant Cell Granuloma: An Immunohistochemical Analysis.

PubMed

Kumar, Varsha Vimal; Krishanappa, Savita Jangal; Prakash, Smitha Gowdra; Channabasaviah, Girish Hemdal; Murgod, Sanjay; Pujari, Ravikumar; Kamat, Mamata Sharad

2016-03-01

Angiogenesis is a fundamental process that affects physiologic reactions and pathological processes such as tumour development and metastasis. It is the process of formation of new microvessel from the preexisting vessels. The purpose of this study was to evaluate angiogenesis, macrophage index and correlate the impact of macrophages on angiogenesis in the central and peripheral giant cell granulomas by evaluating immunohistochemically microvessel density, microvessel perimeter and macrophage index. Immunohistochemical analysis was carried on 20 cases of central and peripheral giant cell granulomas each for CD34 and CD68 proteins expression. Inferential statistical analysis was performed using Independent student t-test to assess the microvessel density, microvessel perimeter and macrophage index on continuous scale between Group I and Group II. Level of significance was determined at 5%. Further bivariate analysis using Pearson correlation test was carried out to see the relationship between microvessel density and macrophage index in each group. Microvessel density, micro vessel perimeter and macrophage index was higher in central giant cell granuloma compared to that of peripheral giant cell granuloma. Correlation between microvessel density and macrophage index among these two lesions was statistically insignificant. Angiogenesis as well as the number of macrophages appeared to increase in Central Giant Cell Granuloma in present study. These findings suggest that macrophages may up regulate the angiogenesis in these giant cell granulomas and angiogenesis do have a role in clinical behaviour. However, we could not establish a positive correlation between microvessel density and macrophage index as the values were statistically insignificant. This insignificance may be presumed due to fewer samples taken for study.

On computations of variance, covariance and correlation for interval data

NASA Astrophysics Data System (ADS)

Kishida, Masako

2017-02-01

In many practical situations, the data on which statistical analysis is to be performed is only known with interval uncertainty. Different combinations of values from the interval data usually lead to different values of variance, covariance, and correlation. Hence, it is desirable to compute the endpoints of possible values of these statistics. This problem is, however, NP-hard in general. This paper shows that the problem of computing the endpoints of possible values of these statistics can be rewritten as the problem of computing skewed structured singular values ν, for which there exist feasible (polynomial-time) algorithms that compute reasonably tight bounds in most practical cases. This allows one to find tight intervals of the aforementioned statistics for interval data.

A primer on the study of transitory dynamics in ecological series using the scale-dependent correlation analysis.

PubMed

Rodríguez-Arias, Miquel Angel; Rodó, Xavier

2004-03-01

Here we describe a practical, step-by-step primer to scale-dependent correlation (SDC) analysis. The analysis of transitory processes is an important but often neglected topic in ecological studies because only a few statistical techniques appear to detect temporary features accurately enough. We introduce here the SDC analysis, a statistical and graphical method to study transitory processes at any temporal or spatial scale. SDC analysis, thanks to the combination of conventional procedures and simple well-known statistical techniques, becomes an improved time-domain analogue of wavelet analysis. We use several simple synthetic series to describe the method, a more complex example, full of transitory features, to compare SDC and wavelet analysis, and finally we analyze some selected ecological series to illustrate the methodology. The SDC analysis of time series of copepod abundances in the North Sea indicates that ENSO primarily is the main climatic driver of short-term changes in population dynamics. SDC also uncovers some long-term, unexpected features in the population. Similarly, the SDC analysis of Nicholson's blowflies data locates where the proposed models fail and provides new insights about the mechanism that drives the apparent vanishing of the population cycle during the second half of the series.

Meta-analysis of correlated traits via summary statistics from GWASs with an application in hypertension.

PubMed

Zhu, Xiaofeng; Feng, Tao; Tayo, Bamidele O; Liang, Jingjing; Young, J Hunter; Franceschini, Nora; Smith, Jennifer A; Yanek, Lisa R; Sun, Yan V; Edwards, Todd L; Chen, Wei; Nalls, Mike; Fox, Ervin; Sale, Michele; Bottinger, Erwin; Rotimi, Charles; Liu, Yongmei; McKnight, Barbara; Liu, Kiang; Arnett, Donna K; Chakravati, Aravinda; Cooper, Richard S; Redline, Susan

2015-01-08

Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple-even distinct-traits. Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10(-8)) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10(-7)) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Selected nutrients and pesticides in streams of the eastern Iowa basins, 1970-95

USGS Publications Warehouse

Schnoebelen, Douglas J.; Becher, Kent D.; Bobier, Matthew W.; Wilton, Thomas

1999-01-01

 The statistical analysis of the nutrient data typically indicated a strong positive correlation of nitrate with streamflow. Total phosphorus concentrations with streamflow showed greater variability than nitrate, perhaps reflecting the greater potential of transport of phosphorus on sediment rather than in the dissolved phase as with nitrate. Ammonia and ammonia plus organic nitrogen showed no correlation with streamflow or a weak positive correlation. Seasonal variations and the relations of nutrients and pesticides to streamflow generally corresponded with nonpoint‑source loadings, although possible point sources for nutrients were indicated by the data at selected monitoring sites. Statistical trend tests for concentrations and loads were computed for nitrate, ammonia, and total phosphorus. Trend analysis indicated decreases for ammonia and total phosphorus concentrations at several sites and increases for nitrate concentrations at other sites in the study unit.

Statistical physics in foreign exchange currency and stock markets

NASA Astrophysics Data System (ADS)

Ausloos, M.

2000-09-01

Problems in economy and finance have attracted the interest of statistical physicists all over the world. Fundamental problems pertain to the existence or not of long-, medium- or/and short-range power-law correlations in various economic systems, to the presence of financial cycles and on economic considerations, including economic policy. A method like the detrended fluctuation analysis is recalled emphasizing its value in sorting out correlation ranges, thereby leading to predictability at short horizon. The ( m, k)-Zipf method is presented for sorting out short-range correlations in the sign and amplitude of the fluctuations. A well-known financial analysis technique, the so-called moving average, is shown to raise questions to physicists about fractional Brownian motion properties. Among spectacular results, the possibility of crash predictions has been demonstrated through the log-periodicity of financial index oscillations.

Data Analysis Techniques for Physical Scientists

NASA Astrophysics Data System (ADS)

Pruneau, Claude A.

2017-10-01

Preface; How to read this book; 1. The scientific method; Part I. Foundation in Probability and Statistics: 2. Probability; 3. Probability models; 4. Classical inference I: estimators; 5. Classical inference II: optimization; 6. Classical inference III: confidence intervals and statistical tests; 7. Bayesian inference; Part II. Measurement Techniques: 8. Basic measurements; 9. Event reconstruction; 10. Correlation functions; 11. The multiple facets of correlation functions; 12. Data correction methods; Part III. Simulation Techniques: 13. Monte Carlo methods; 14. Collision and detector modeling; List of references; Index.

Reporting quality of statistical methods in surgical observational studies: protocol for systematic review.

PubMed

Wu, Robert; Glen, Peter; Ramsay, Tim; Martel, Guillaume

2014-06-28

Observational studies dominate the surgical literature. Statistical adjustment is an important strategy to account for confounders in observational studies. Research has shown that published articles are often poor in statistical quality, which may jeopardize their conclusions. The Statistical Analyses and Methods in the Published Literature (SAMPL) guidelines have been published to help establish standards for statistical reporting.This study will seek to determine whether the quality of statistical adjustment and the reporting of these methods are adequate in surgical observational studies. We hypothesize that incomplete reporting will be found in all surgical observational studies, and that the quality and reporting of these methods will be of lower quality in surgical journals when compared with medical journals. Finally, this work will seek to identify predictors of high-quality reporting. This work will examine the top five general surgical and medical journals, based on a 5-year impact factor (2007-2012). All observational studies investigating an intervention related to an essential component area of general surgery (defined by the American Board of Surgery), with an exposure, outcome, and comparator, will be included in this systematic review. Essential elements related to statistical reporting and quality were extracted from the SAMPL guidelines and include domains such as intent of analysis, primary analysis, multiple comparisons, numbers and descriptive statistics, association and correlation analyses, linear regression, logistic regression, Cox proportional hazard analysis, analysis of variance, survival analysis, propensity analysis, and independent and correlated analyses. Each article will be scored as a proportion based on fulfilling criteria in relevant analyses used in the study. A logistic regression model will be built to identify variables associated with high-quality reporting. A comparison will be made between the scores of surgical observational studies published in medical versus surgical journals. Secondary outcomes will pertain to individual domains of analysis. Sensitivity analyses will be conducted. This study will explore the reporting and quality of statistical analyses in surgical observational studies published in the most referenced surgical and medical journals in 2013 and examine whether variables (including the type of journal) can predict high-quality reporting.

Novel Assessment of Interstitial Lung Disease Using the "Computer-Aided Lung Informatics for Pathology Evaluation and Rating" (CALIPER) Software System in Idiopathic Inflammatory Myopathies.

PubMed

Ungprasert, Patompong; Wilton, Katelynn M; Ernste, Floranne C; Kalra, Sanjay; Crowson, Cynthia S; Rajagopalan, Srinivasan; Bartholmai, Brian J

2017-10-01

To evaluate the correlation between measurements from quantitative thoracic high-resolution CT (HRCT) analysis with "Computer-Aided Lung Informatics for Pathology Evaluation and Rating" (CALIPER) software and measurements from pulmonary function tests (PFTs) in patients with idiopathic inflammatory myopathies (IIM)-associated interstitial lung disease (ILD). A cohort of patients with IIM-associated ILD seen at Mayo Clinic was identified from medical record review. Retrospective analysis of HRCT data and PFTs at baseline and 1 year was performed. The abnormalities in HRCT were quantified using CALIPER software. A total of 110 patients were identified. At baseline, total interstitial abnormalities as measured by CALIPER, both by absolute volume and by percentage of total lung volume, had a significant negative correlation with diffusing capacity for carbon monoxide (DLCO), total lung capacity (TLC), and oxygen saturation. Analysis by subtype of interstitial abnormality revealed significant negative correlations between ground glass opacities (GGO) and reticular density (RD) with DLCO and TLC. At one year, changes of total interstitial abnormalities compared with baseline had a significant negative correlation with changes of TLC and oxygen saturation. A negative correlation between changes of total interstitial abnormalities and DLCO was also observed, but it was not statistically significant. Analysis by subtype of interstitial abnormality revealed negative correlations between changes of GGO and RD and changes of DLCO, TLC, and oxygen saturation, but most of the correlations did not achieve statistical significance. CALIPER measurements correlate well with functional measurements in patients with IIM-associated ILD.

Complex Analysis of Combat in Afghanistan

DTIC Science & Technology

2014-12-01

analysis we have β−ffE ~)( where β= 2H - 1 = 1 - γ, with H being the Hurst exponent , related to the correlation exponent γ. Usually, real-world data are...statistical nature. In every instance we found strong power law correlations in the data, and were able to extract accurate scaling exponents . On the... exponents , α. The case αɘ.5 corresponds to long-term anti-correlations, meaning that large values are most likely to be followed by small values and

A Statistical Analysis of Langmuir Wave-Electron Correlations Observed by the CHARM II Auroral Sounding Rocket

NASA Astrophysics Data System (ADS)

Dombrowski, M. P.; Labelle, J. W.; Kletzing, C.; Bounds, S. R.; Kaeppler, S. R.

2014-12-01

Langmuir-mode electron plasma waves are frequently observed by spacecraft in active plasma environments such as the ionosphere. Ionospheric Langmuir waves may be excited by the bump-on-tail instability generated by impinging beams of electrons traveling parallel to the background magnetic field (B). The Correlation of High-frequencies and Auroral Roar Measurement (CHARM II) sounding rocket was launched into a substorm at 9:49 UT on 17 February 2010, from the Poker Flat Research Range in Alaska. The primary instruments included the University of Iowa Wave-Particle Correlator (WPC), the Dartmouth High-Frequency Experiment (HFE), several charged particle detectors, low-frequency wave instruments, and a magnetometer. The HFE is a receiver system which effectively yields continuous (100% duty cycle) electric-field waveform measurements from 100 kHz to 5 MHz, and which had its detection axis aligned nominally parallel to B. The HFE output was fed on-payload to the WPC, which uses a phase-locked loop to track the incoming wave frequency with the most power, then sorting incoming electrons at eight energy levels into sixteen wave-phase bins. CHARM II encountered several regions of strong Langmuir wave activity throughout its 15-minute flight, and the WPC showed wave-lock and statistically significant particle correlation distributions during several time periods. We show results of an in-depth analysis of the CHARM II WPC data for the entire flight, including statistical analysis of correlations which show evidence of direct interaction with the Langmuir waves, indicating (at various times) trapping of particles and both driving and damping of Langmuir waves by particles. In particular, the sign of the gradient in particle flux appears to correlate with the phase relation between the electrons and the wave field, with possible implications for the wave physics.

ASURV: Astronomical SURVival Statistics

NASA Astrophysics Data System (ADS)

Feigelson, E. D.; Nelson, P. I.; Isobe, T.; LaValley, M.

2014-06-01

ASURV (Astronomical SURVival Statistics) provides astronomy survival analysis for right- and left-censored data including the maximum-likelihood Kaplan-Meier estimator and several univariate two-sample tests, bivariate correlation measures, and linear regressions. ASURV is written in FORTRAN 77, and is stand-alone and does not call any specialized libraries.

Analysis of in vivo corrosion of 316L stainless steel posterior thoracolumbar plate systems: a retrieval study.

PubMed

Majid, Kamran; Crowder, Terence; Baker, Erin; Baker, Kevin; Koueiter, Denise; Shields, Edward; Herkowitz, Harry N

2011-12-01

One hundred eighteen patients retrieved 316L stainless steel thoracolumbar plates, of 3 different designs, used for fusion in 60 patients were examined for evidence of corrosion. A medical record review and statistical analysis were also carried out. This study aims to identify types of corrosion and examine preferential metal ion release and the possibility of statistical correlation to clinical effects. Earlier studies have found that stainless steel spine devices showed evidence of mild-to-severe corrosion; fretting and crevice corrosion were the most commonly reported types. Studies have also shown the toxicity of metal ions released from stainless steel corrosion and how the ions may adversely affect bone formation and/or induce granulomatous foreign body responses. The retrieved plates were visually inspected and graded based on the degree of corrosion. The plates were then analyzed with optical microscopy, scanning electron microscopy, and energy dispersive x-ray spectroscopy. A retrospective medical record review was performed and statistical analysis was carried out to determine any correlations between experimental findings and patient data. More than 70% of the plates exhibited some degree of corrosion. Both fretting and crevice corrosion mechanisms were observed, primarily at the screw plate interface. Energy dispersive x-ray spectroscopy analysis indicated reductions in nickel content in corroded areas, suggestive of nickel ion release to the surrounding biological environment. The incidence and severity of corrosion was significantly correlated with the design of the implant. Stainless steel thoracolumbar plates show a high incidence of corrosion, with statistical dependence on device design.

Individualism: a valid and important dimension of cultural differences between nations.

PubMed

Schimmack, Ulrich; Oishi, Shigehiro; Diener, Ed

2005-01-01

Oyserman, Coon, and Kemmelmeier's (2002) meta-analysis suggested problems in the measurement of individualism and collectivism. Studies using Hofstede's individualism scores show little convergent validity with more recent measures of individualism and collectivism. We propose that the lack of convergent validity is due to national differences in response styles. Whereas Hofstede statistically controlled for response styles, Oyserman et al.'s meta-analysis relied on uncorrected ratings. Data from an international student survey demonstrated convergent validity between Hofstede's individualism dimension and horizontal individualism when response styles were statistically controlled, whereas uncorrected scores correlated highly with the individualism scores in Oyserman et al.'s meta-analysis. Uncorrected horizontal individualism scores and meta-analytic individualism scores did not correlate significantly with nations' development, whereas corrected horizontal individualism scores and Hofstede's individualism dimension were significantly correlated with development. This pattern of results suggests that individualism is a valid construct for cross-cultural comparisons, but that the measurement of this construct needs improvement.

The Interaction between Leadership, Climate, and Satisfaction in a Professional Organization

DTIC Science & Technology

1974-12-01

DESCRIPTIVE STATISTICS 3^ B. IDENTIFICATION OF LEADERSHIP STYLES 35 C. FACTOR ANALYSIS ^0 D. CORRELATION ANALYSIS k2 E. PARTIAL CORRELATION...different definitions of supervisor behaviors of leadership styles in the comparisons with satis- faction, these studies have generally concluded that...Several norms, or recognized leadership styles , have been described in management; theory literature. It would not be beneficial to discuss or even

Current State and Development Trends of Education Policy Research in China in the Last Decade (2004-2013): A Statistical Analysis of Papers from Eight Core Chinese Journals

ERIC Educational Resources Information Center

Ling, Guo

2017-01-01

The author conducted sampling and statistical analysis of papers on education policy research collected by the China National Knowledge Infrastructure in the period from the years 2004--2013. Under the current state of education policy research in China, the number of papers correlates positively with the year; the papers are concentrated in…

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.

Comprehensive analysis of correlation coefficients estimated from pooling heterogeneous microarray data

PubMed Central

2013-01-01

Background The synthesis of information across microarray studies has been performed by combining statistical results of individual studies (as in a mosaic), or by combining data from multiple studies into a large pool to be analyzed as a single data set (as in a melting pot of data). Specific issues relating to data heterogeneity across microarray studies, such as differences within and between labs or differences among experimental conditions, could lead to equivocal results in a melting pot approach. Results We applied statistical theory to determine the specific effect of different means and heteroskedasticity across 19 groups of microarray data on the sign and magnitude of gene-to-gene Pearson correlation coefficients obtained from the pool of 19 groups. We quantified the biases of the pooled coefficients and compared them to the biases of correlations estimated by an effect-size model. Mean differences across the 19 groups were the main factor determining the magnitude and sign of the pooled coefficients, which showed largest values of bias as they approached ±1. Only heteroskedasticity across the pool of 19 groups resulted in less efficient estimations of correlations than did a classical meta-analysis approach of combining correlation coefficients. These results were corroborated by simulation studies involving either mean differences or heteroskedasticity across a pool of N > 2 groups. Conclusions The combination of statistical results is best suited for synthesizing the correlation between expression profiles of a gene pair across several microarray studies. PMID:23822712

Correlation between hospital-level antibiotic consumption and incident health care facility-onset Clostridium difficile infection.

PubMed

Crew, Page E; Rhodes, Nathaniel J; O'Donnell, J Nicholas; Miglis, Cristina; Gilbert, Elise M; Zembower, Teresa R; Qi, Chao; Silkaitis, Christina; Sutton, Sarah H; Scheetz, Marc H

2018-03-01

The purpose of this single-center, ecologic study is to characterize the relationship between facility-wide (FacWide) antibiotic consumption and incident health care facility-onset Clostridium difficile infection (HO-CDI). FacWide antibiotic consumption and incident HO-CDI were tallied on a monthly basis and standardized, from January 2013 through April 2015. Spearman rank-order correlation coefficients were calculated using matched-months analysis and a 1-month delay. Regression analyses were performed, with P < .05 considered statistically significant. FacWide analysis identified a matched-months correlation between ceftriaxone and HO-CDI (ρ = 0.44, P = .018). A unit of stem cell transplant recipients did not have significant correlation between carbapenems and HO-CDI in matched months (ρ = 0.37, P = .098), but a significant correlation was observed when a 1-month lag was applied (ρ = 0.54, P = .014). Three statistically significant lag associations were observed between FacWide/unit-level antibiotic consumption and HO-CDI, and 1 statistically significant nonlagged association was observed FacWide. Antibiotic consumption may convey extended ward-level risk for incident CDI. Consumption of antibiotic agents may have immediate and prolonged influence on incident CDI. Additional studies are needed to investigate the immediate and delayed associations between antibiotic consumption and C difficile colonization, infection, and transmission at the hospital level. Published by Elsevier Inc.

Statistical and linguistic features of DNA sequences

NASA Technical Reports Server (NTRS)

Havlin, S.; Buldyrev, S. V.; Goldberger, A. L.; Mantegna, R. N.; Peng, C. K.; Simons, M.; Stanley, H. E.

1995-01-01

We present evidence supporting the idea that the DNA sequence in genes containing noncoding regions is correlated, and that the correlation is remarkably long range--indeed, base pairs thousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene. We resolve the problem of the "non-stationary" feature of the sequence of base pairs by applying a new algorithm called Detrended Fluctuation Analysis (DFA). We address the claim of Voss that there is no difference in the statistical properties of coding and noncoding regions of DNA by systematically applying the DFA algorithm, as well as standard FFT analysis, to all eukaryotic DNA sequences (33 301 coding and 29 453 noncoding) in the entire GenBank database. We describe a simple model to account for the presence of long-range power-law correlations which is based upon a generalization of the classic Levy walk. Finally, we describe briefly some recent work showing that the noncoding sequences have certain statistical features in common with natural languages. Specifically, we adapt to DNA the Zipf approach to analyzing linguistic texts, and the Shannon approach to quantifying the "redundancy" of a linguistic text in terms of a measurable entropy function. We suggest that noncoding regions in plants and invertebrates may display a smaller entropy and larger redundancy than coding regions, further supporting the possibility that noncoding regions of DNA may carry biological information.

Quantification of integrated HIV DNA by repetitive-sampling Alu-HIV PCR on the basis of poisson statistics.

PubMed

De Spiegelaere, Ward; Malatinkova, Eva; Lynch, Lindsay; Van Nieuwerburgh, Filip; Messiaen, Peter; O'Doherty, Una; Vandekerckhove, Linos

2014-06-01

Quantification of integrated proviral HIV DNA by repetitive-sampling Alu-HIV PCR is a candidate virological tool to monitor the HIV reservoir in patients. However, the experimental procedures and data analysis of the assay are complex and hinder its widespread use. Here, we provide an improved and simplified data analysis method by adopting binomial and Poisson statistics. A modified analysis method on the basis of Poisson statistics was used to analyze the binomial data of positive and negative reactions from a 42-replicate Alu-HIV PCR by use of dilutions of an integration standard and on samples of 57 HIV-infected patients. Results were compared with the quantitative output of the previously described Alu-HIV PCR method. Poisson-based quantification of the Alu-HIV PCR was linearly correlated with the standard dilution series, indicating that absolute quantification with the Poisson method is a valid alternative for data analysis of repetitive-sampling Alu-HIV PCR data. Quantitative outputs of patient samples assessed by the Poisson method correlated with the previously described Alu-HIV PCR analysis, indicating that this method is a valid alternative for quantifying integrated HIV DNA. Poisson-based analysis of the Alu-HIV PCR data enables absolute quantification without the need of a standard dilution curve. Implementation of the CI estimation permits improved qualitative analysis of the data and provides a statistical basis for the required minimal number of technical replicates. © 2014 The American Association for Clinical Chemistry.

A PLSPM-Based Test Statistic for Detecting Gene-Gene Co-Association in Genome-Wide Association Study with Case-Control Design

PubMed Central

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods. PMID:23620809

Laser diagnostics of native cervix dabs with human papilloma virus in high carcinogenic risk

NASA Astrophysics Data System (ADS)

Peresunko, O. P.; Karpenko, Ju. G.; Burkovets, D. N.; Ivashko, P. V.; Nikorych, A. V.; Yermolenko, S. B.; Gruia, Ion; Gruia, M. J.

2015-11-01

The results of experimental studies of coordinate distributions of Mueller matrix elements of the following types of cervical scraping tissue are presented: rate- low-grade - highly differentiated dysplasia (CIN1-CIN3) - adenocarcinoma of high, medium and low levels of differentiation (G1-G3). The rationale for the choice of statistical points 1-4 orders polarized coherent radiation field, transformed as a result of interaction with the oncologic modified biological layers "epithelium-stroma" as a quantitative criterion of polarimetric optical differentiation state of human biological tissues are shown here. The analysis of the obtained Mueller matrix elements and statistical correlation methods, the systematized by types studied tissues is accomplished. The results of research images of Mueller matrix elements m34 for this type of pathology as low-grade dysplasia (CIN2), the results of its statistical and correlation analysis are presented.

A PLSPM-based test statistic for detecting gene-gene co-association in genome-wide association study with case-control design.

PubMed

Zhang, Xiaoshuai; Yang, Xiaowei; Yuan, Zhongshang; Liu, Yanxun; Li, Fangyu; Peng, Bin; Zhu, Dianwen; Zhao, Jinghua; Xue, Fuzhong

2013-01-01

For genome-wide association data analysis, two genes in any pathway, two SNPs in the two linked gene regions respectively or in the two linked exons respectively within one gene are often correlated with each other. We therefore proposed the concept of gene-gene co-association, which refers to the effects not only due to the traditional interaction under nearly independent condition but the correlation between two genes. Furthermore, we constructed a novel statistic for detecting gene-gene co-association based on Partial Least Squares Path Modeling (PLSPM). Through simulation, the relationship between traditional interaction and co-association was highlighted under three different types of co-association. Both simulation and real data analysis demonstrated that the proposed PLSPM-based statistic has better performance than single SNP-based logistic model, PCA-based logistic model, and other gene-based methods.

Macular Thickness Assessment in Patients with Glaucoma and Its Correlation with Visual Fields

PubMed Central

Vaz, Fernando T; Ramalho, Mário; Pedrosa, Catarina; Lisboa, Maria; Kaku, Paulo; Esperancinha, Florindo

2016-01-01

Aim To determine the relationship between macular thickness (MT) and visual field (VF) parameters, as well as with changes in the retinal nerve fiber layer (RNFL) thickness in patients with glaucoma and ocular hypertension (OH). Materials and methods Cross-sectional statistical analysis of spectral domain optical coherence tomography (SD-OCT) compared with several VF parameters (mean defect - MD and loss variance - LV), in a nonrandom sample of 70 eyes from patients with glaucoma or OH. Statistical analysis was performed using Statistical Package for Social Sciences®. The correlation coefficient used was determined by Spearman correlation and the value of p < 0.05 was considered statistically significant. Results A significant correlation was seen between VF parameters and decrease in MT (MD: r = –0.363, p = 0.002; LV: r=–0.378, p = 0.001). The results were more significant when we compared the LV in the group with average MT 270 to 300 μm (r = –0.413, p = 0.015). Asymmetry between the superior macula and inferior macula correlated with LV (r = 0.432, p = 0.019) in the group with MT < 270 μm. There was also a significant correlation between thinning of superior-temporal and inferior-temporal RNFL and the decrease of the superior and inferior MT respectively (p < 0.001). Conclusion Spectral domain optical coherence tomography measurements of retinal thickness in the macula correlate with VF parameters and RNFL parameters in glaucoma patients. This relationship was first demonstrated with static computerized perimetry made with Octopus 101®. These results can be a valuable aid for evaluating and monitoring of glaucoma patients, establishing a correlation between structure and function. Measurements of retinal thickness in the macula may be an additional instrument for early detection of structural changes and its correlation with functional defects. How to cite this article Mota M, Vaz FT, Ramalho M, Pedrosa C, Lisboa M, Kaku P, Esperancinha F. Macular Thickness Assessment in Patients with Glaucoma and Its Correlation with Visual Fields. J Curr Glaucoma Pract 2016;10(3):85-90. PMID:27857487

Statistical interpretation of chromatic indicators in correlation to phytochemical profile of a sulfur dioxide-free mulberry (Morus nigra) wine submitted to non-thermal maturation processes.

PubMed

Tchabo, William; Ma, Yongkun; Kwaw, Emmanuel; Zhang, Haining; Xiao, Lulu; Apaliya, Maurice T

2018-01-15

The four different methods of color measurement of wine proposed by Boulton, Giusti, Glories and Commission International de l'Eclairage (CIE) were applied to assess the statistical relationship between the phytochemical profile and chromatic characteristics of sulfur dioxide-free mulberry (Morus nigra) wine submitted to non-thermal maturation processes. The alteration in chromatic properties and phenolic composition of non-thermal aged mulberry wine were examined, aided by the used of Pearson correlation, cluster and principal component analysis. The results revealed a positive effect of non-thermal processes on phytochemical families of wines. From Pearson correlation analysis relationships between chromatic indexes and flavonols as well as anthocyanins were established. Cluster analysis highlighted similarities between Boulton and Giusti parameters, as well as Glories and CIE parameters in the assessment of chromatic properties of wines. Finally, principal component analysis was able to discriminate wines subjected to different maturation techniques on the basis of their chromatic and phenolics characteristics. Copyright © 2017. Published by Elsevier Ltd.

Common pitfalls in statistical analysis: Measures of agreement.

PubMed

Ranganathan, Priya; Pramesh, C S; Aggarwal, Rakesh

2017-01-01

Agreement between measurements refers to the degree of concordance between two (or more) sets of measurements. Statistical methods to test agreement are used to assess inter-rater variability or to decide whether one technique for measuring a variable can substitute another. In this article, we look at statistical measures of agreement for different types of data and discuss the differences between these and those for assessing correlation.

Electrophysiological evidence of heterogeneity in visual statistical learning in young children with ASD.

PubMed

Jeste, Shafali S; Kirkham, Natasha; Senturk, Damla; Hasenstab, Kyle; Sugar, Catherine; Kupelian, Chloe; Baker, Elizabeth; Sanders, Andrew J; Shimizu, Christina; Norona, Amanda; Paparella, Tanya; Freeman, Stephanny F N; Johnson, Scott P

2015-01-01

Statistical learning is characterized by detection of regularities in one's environment without an awareness or intention to learn, and it may play a critical role in language and social behavior. Accordingly, in this study we investigated the electrophysiological correlates of visual statistical learning in young children with autism spectrum disorder (ASD) using an event-related potential shape learning paradigm, and we examined the relation between visual statistical learning and cognitive function. Compared to typically developing (TD) controls, the ASD group as a whole showed reduced evidence of learning as defined by N1 (early visual discrimination) and P300 (attention to novelty) components. Upon further analysis, in the ASD group there was a positive correlation between N1 amplitude difference and non-verbal IQ, and a positive correlation between P300 amplitude difference and adaptive social function. Children with ASD and a high non-verbal IQ and high adaptive social function demonstrated a distinctive pattern of learning. This is the first study to identify electrophysiological markers of visual statistical learning in children with ASD. Through this work we have demonstrated heterogeneity in statistical learning in ASD that maps onto non-verbal cognition and adaptive social function. © 2014 John Wiley & Sons Ltd.

Analysis/forecast experiments with a flow-dependent correlation function using FGGE data

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Carus, H.; Nestler, M. S.

1986-01-01

The use of a flow-dependent correlation function to improve the accuracy of an optimum interpolation (OI) scheme is examined. The development of the correlation function for the OI analysis scheme used for numerical weather prediction is described. The scheme uses a multivariate surface analysis over the oceans to model the pressure-wind error cross-correlation and it has the ability to use an error correlation function that is flow- and geographically-dependent. A series of four-day data assimilation experiments, conducted from January 5-9, 1979, were used to investigate the effect of the different features of the OI scheme (error correlation) on forecast skill for the barotropic lows and highs. The skill of the OI was compared with that of a successive correlation method (SCM) of analysis. It is observed that the largest difference in the correlation statistics occurred in barotropic and baroclinic lows and highs. The comparison reveals that the OI forecasts were more accurate than the SCM forecasts.

Leadership in nursing and patient satisfaction in hospital context.

PubMed

Nunes, Elisabete Maria Garcia Teles; Gaspar, Maria Filomena Mendes

2016-06-01

Objectives to know the quality of the leadership relationship from the perspective of a chief nurse and nurse, patient satisfaction, the relationship between the quality of the relationship perceived for both and patient satisfaction. Methods a quantitative, transverse and correlational approach. Non-probabilistic convenience sample consists of 15 chief nurses, 342 nurses, 273 patients. Data collected at the Central Lisbon Hospital Center, between January and March 2013, through the LMX-7, CLMX-7 and SUCEH21 scales. Statistical analysis was performed through SPSS ® Statistics 19. Results the chief nurse considers the quality of the leadership relationship good, the nurses consider it satisfactory, patients are considered to be satisfied with nursing care; there is a statistically significant correlation between the quality of the leadership relationship from the perspective of chief nurses and patient satisfaction, there is no statistically significant correlation between the quality of the leadership relationship in the nurse's perspective and satisfaction. Conclusion the chief nurse has a major role in patient satisfaction.

Statistical approaches in published ophthalmic clinical science papers: a comparison to statistical practice two decades ago.

PubMed

Zhang, Harrison G; Ying, Gui-Shuang

2018-02-09

The aim of this study is to evaluate the current practice of statistical analysis of eye data in clinical science papers published in British Journal of Ophthalmology ( BJO ) and to determine whether the practice of statistical analysis has improved in the past two decades. All clinical science papers (n=125) published in BJO in January-June 2017 were reviewed for their statistical analysis approaches for analysing primary ocular measure. We compared our findings to the results from a previous paper that reviewed BJO papers in 1995. Of 112 papers eligible for analysis, half of the studies analysed the data at an individual level because of the nature of observation, 16 (14%) studies analysed data from one eye only, 36 (32%) studies analysed data from both eyes at ocular level, one study (1%) analysed the overall summary of ocular finding per individual and three (3%) studies used the paired comparison. Among studies with data available from both eyes, 50 (89%) of 56 papers in 2017 did not analyse data from both eyes or ignored the intereye correlation, as compared with in 60 (90%) of 67 papers in 1995 (P=0.96). Among studies that analysed data from both eyes at an ocular level, 33 (92%) of 36 studies completely ignored the intereye correlation in 2017, as compared with in 16 (89%) of 18 studies in 1995 (P=0.40). A majority of studies did not analyse the data properly when data from both eyes were available. The practice of statistical analysis did not improve in the past two decades. Collaborative efforts should be made in the vision research community to improve the practice of statistical analysis for ocular data. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Intrabolus pressure on high-resolution manometry distinguishes fibrostenotic and inflammatory phenotypes of eosinophilic esophagitis.

PubMed

Colizzo, J M; Clayton, S B; Richter, J E

2016-08-01

The aim of this investigation was to determine the motility patterns of inflammatory and fibrostenotic phenotypes of eosinophilic esophagitis (EoE) utilizing high-resolution manometry (HRM). Twenty-nine patients with a confirmed diagnosis of EoE according to clinicopathological criteria currently being managed at the Joy McCann Culverhouse Swallowing Center at the University of South Florida were included in the retrospective analysis. Only patients who completed HRM studies were included in the analysis. Patients were classified into inflammatory or fibrostenotic subtypes based on baseline endoscopic evidence. Their baseline HRM studies prior to therapy were analyzed. Manometric data including distal contractile integral, integrated relaxation pressure, and intrabolus pressure (IBP) values were recorded. HRM results were interpreted according to the Chicago Classification system. Statistical analysis was performed with SPSS software (Version 22, IBM Co., Armonk, NY, USA). Data were compared utilizing Student's t-test, χ(2) test, Pearson correlation, and Spearman correlation tests. Statistical significance was set at P < 0.05. A total of 29 patients with EoE were included into the retrospective analysis. The overall average age among patients was 40 years. Male patients comprised 62% of the overall population. Both groups were similar in age, gender, and overall clinical presentation. Seventeen patients (58%) had fibrostenotic disease, and 12 (42%) displayed inflammatory disease. The average IBP for the fibrostenotic and inflammatory groups were 18.6 ± 6.0 mmHg and 12.6 ± 3.5 mmHg, respectively (P < 0.05). Strictures were only seen in the fibrostenotic group. Of the fibrostenotic group, 6 (35%) demonstrated proximal esophageal strictures, 7 (41%) had distal strictures, 3 (18%) had mid-esophageal strictures, and 1 (6%) patient had pan-esophageal strictures. There was no statistically significant correlation between the level of esophageal stricture and degree of IBP. Integrated relaxation pressure, distal contractile integral, and other HRM metrics did not demonstrate statistical significance between the two subtypes. There also appeared no statistically significant correlation between patient demographics and esophageal metrics. Patients with the fibrostenotic phenotype of EoE demonstrated an IBP that was significantly higher than that of the inflammatory group. © 2015 International Society for Diseases of the Esophagus.

Analysis of the sleep quality of elderly people using biomedical signals.

PubMed

Moreno-Alsasua, L; Garcia-Zapirain, B; Mendez-Zorrilla, A

2015-01-01

This paper presents a technical solution that analyses sleep signals captured by biomedical sensors to find possible disorders during rest. Specifically, the method evaluates electrooculogram (EOG) signals, skin conductance (GSR), air flow (AS), and body temperature. Next, a quantitative sleep quality analysis determines significant changes in the biological signals, and any similarities between them in a given time period. Filtering techniques such as the Fourier transform method and IIR filters process the signal and identify significant variations. Once these changes have been identified, all significant data is compared and a quantitative and statistical analysis is carried out to determine the level of a person's rest. To evaluate the correlation and significant differences, a statistical analysis has been calculated showing correlation between EOG and AS signals (p=0,005), EOG, and GSR signals (p=0,037) and, finally, the EOG and Body temperature (p=0,04). Doctors could use this information to monitor changes within a patient.

Analysis/forecast experiments with a multivariate statistical analysis scheme using FGGE data

NASA Technical Reports Server (NTRS)

Baker, W. E.; Bloom, S. C.; Nestler, M. S.

1985-01-01

A three-dimensional, multivariate, statistical analysis method, optimal interpolation (OI) is described for modeling meteorological data from widely dispersed sites. The model was developed to analyze FGGE data at the NASA-Goddard Laboratory of Atmospherics. The model features a multivariate surface analysis over the oceans, including maintenance of the Ekman balance and a geographically dependent correlation function. Preliminary comparisons are made between the OI model and similar schemes employed at the European Center for Medium Range Weather Forecasts and the National Meteorological Center. The OI scheme is used to provide input to a GCM, and model error correlations are calculated for forecasts of 500 mb vertical water mixing ratios and the wind profiles. Comparisons are made between the predictions and measured data. The model is shown to be as accurate as a successive corrections model out to 4.5 days.

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

EEG Correlates of Fluctuation in Cognitive Performance in an Air Traffic Control Task

DTIC Science & Technology

2014-11-01

using non-parametric statistical analysis to identify neurophysiological patterns due to the time-on-task effect. Significant changes in EEG power...EEG, Cognitive Performance, Power Spectral Analysis , Non-Parametric Analysis Document is available to the public through the Internet...3 Performance Data Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 EEG

Atmospheric pollution measurement by optical cross correlation methods - A concept

NASA Technical Reports Server (NTRS)

Fisher, M. J.; Krause, F. R.

1971-01-01

Method combines standard spectroscopy with statistical cross correlation analysis of two narrow light beams for remote sensing to detect foreign matter of given particulate size and consistency. Method is applicable in studies of generation and motion of clouds, nuclear debris, ozone, and radiation belts.

Influence of solar activity on fibrinolysis and fibrinogenolysis. [statistical correlation between solar flare and blood coagulation indices

NASA Technical Reports Server (NTRS)

Marchenko, V. I.

1974-01-01

During periods of high solar activity fibrinolysis and fibrinogenolysis are increased. A direct correlative relationship is established between the indices of fibrinolysis, fibrinogenolysis and solar flares which were recorded two days before the blood was collected for analysis.

Electricity supply efficiency and organizational growth and profitability in Lagos, Nigeria

NASA Astrophysics Data System (ADS)

Adeleke, Adedeji Tajudeen

A modern and efficient infrastructure is a basic necessity for economic development and integration into the global economy. The specific problem was the inadequate and unreliable supply of electricity to manufacturing corporations in Lagos, Nigeria. The purpose of the current quantitative correlational research study was to examine if there was a correlation between electricity supply efficiency and organizational growth and profitability in manufacturing corporations in Lagos, Nigeria. The population of the current correlational research study involved 28 out of 34 manufacturing corporations from various industrial sectors in Lagos, Nigeria, that are listed and traded on the Nigerian Stock Exchange. Spearman rho correlations were used to assess the relationships between independent variables of electricity supply efficiency levels and the dependent variables of organizational growth and profitability. The result of the correlational analysis of the data revealed that there was a statistically significant, strong positive correlation between the Average Gross Income (1998-2007) and Average Actual Electricity supply efficiency level (1998-2007), rho = 0.57; p = 0.002. A statistically significant, strong positive correlation was found between the Average Balance Sheet Size (1998-2007) and Average Actual Electricity Supply Efficiency Level (1998-2007), rho = 0.54; p = 0.003. A statistically significant, strong positive correlation between the Average Profit After Tax (1998-2007) and Average Actual Electricity Supply Efficiency Level (1998-2007), rho = 0.60; p = 0.001, was found. No statistically significant correlation between the Average Return on Investment (1998-2007) and Average Actual Electricity supply efficiency level (1998-2007), rho = 0.19; p = 0.33, was discovered.

Correlation between Post-LASIK Starburst Symptom and Ocular Wavefront Aberrations

NASA Astrophysics Data System (ADS)

Liu, Yong-Ji; Mu, Guo-Guang; Wang, Zhao-Qi; Wang-Yan

2006-06-01

Monochromatic aberrations in post laser in-situ keratomileusis (LASIK) eyes are measured. The data are categorized into reference group and starburst group according to the visual symptoms. Statistic analysis has been made to find the correlation between the ocular wavefront aberrations and the starburst symptom. The rms aberrations of the 3rd and 4th orders for the starburst group are significantly larger than those for the reference group. The starburst symptom shows a strong correlation with vertical coma, total coma, spherical aberrations. For 3-mm pupil size and 5.8-mm pupil size, the modulation transfer function (MTF) of the starburst group are lower than those of the reference group, but their visual acuities are close. MTF and PSF analyses are made for two groups, and the results are consistent with the statistical analysis, which means the difference between the two groups is mainly due to the third- and fourth-order Zernike aberrations.

Topological signatures of interstellar magnetic fields - I. Betti numbers and persistence diagrams

NASA Astrophysics Data System (ADS)

Makarenko, Irina; Shukurov, Anvar; Henderson, Robin; Rodrigues, Luiz F. S.; Bushby, Paul; Fletcher, Andrew

2018-04-01

The interstellar medium (ISM) is a magnetized system in which transonic or supersonic turbulence is driven by supernova explosions. This leads to the production of intermittent, filamentary structures in the ISM gas density, whilst the associated dynamo action also produces intermittent magnetic fields. The traditional theory of random functions, restricted to second-order statistical moments (or power spectra), does not adequately describe such systems. We apply topological data analysis (TDA), sensitive to all statistical moments and independent of the assumption of Gaussian statistics, to the gas density fluctuations in a magnetohydrodynamic simulation of the multiphase ISM. This simulation admits dynamo action, so produces physically realistic magnetic fields. The topology of the gas distribution, with and without magnetic fields, is quantified in terms of Betti numbers and persistence diagrams. Like the more standard correlation analysis, TDA shows that the ISM gas density is sensitive to the presence of magnetic fields. However, TDA gives us important additional information that cannot be obtained from correlation functions. In particular, the Betti numbers per correlation cell are shown to be physically informative. Magnetic fields make the ISM more homogeneous, reducing the abundance of both isolated gas clouds and cavities, with a stronger effect on the cavities. Remarkably, the modification of the gas distribution by magnetic fields is captured by the Betti numbers even in regions more than 300 pc from the mid-plane, where the magnetic field is weaker and correlation analysis fails to detect any signatures of magnetic effects.

Implication of correlations among some common stability statistics - a Monte Carlo simulations.

PubMed

Piepho, H P

1995-03-01

Stability analysis of multilocation trials is often based on a mixed two-way model. Two stability measures in frequent use are the environmental variance (S i (2) )and the ecovalence (W i). Under the two-way model the rank orders of the expected values of these two statistics are identical for a given set of genotypes. By contrast, empirical rank correlations among these measures are consistently low. This suggests that the two-way mixed model may not be appropriate for describing real data. To check this hypothesis, a Monte Carlo simulation was conducted. It revealed that the low empirical rank correlation amongS i (2) and W i is most likely due to sampling errors. It is concluded that the observed low rank correlation does not invalidate the two-way model. The paper also discusses tests for homogeneity of S i (2) as well as implications of the two-way model for the classification of stability statistics.

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

PubMed

Sych, Z

1996-01-01

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

Common pitfalls in statistical analysis: Linear regression analysis

PubMed Central

Aggarwal, Rakesh; Ranganathan, Priya

2017-01-01

In a previous article in this series, we explained correlation analysis which describes the strength of relationship between two continuous variables. In this article, we deal with linear regression analysis which predicts the value of one continuous variable from another. We also discuss the assumptions and pitfalls associated with this analysis. PMID:28447022

Statistical Association Criteria in Forensic Psychiatry–A criminological evaluation of casuistry

PubMed Central

Gheorghiu, V; Buda, O; Popescu, I; Trandafir, MS

2011-01-01

Purpose. Identification of potential shared primary psychoprophylaxis and crime prevention is measured by analyzing the rate of commitments for patients–subjects to forensic examination. Material and method. The statistic trial is a retrospective, document–based study. The statistical lot consists of 770 initial examination reports performed and completed during the whole year 2007, primarily analyzed in order to summarize the data within the National Institute of Forensic Medicine, Bucharest, Romania (INML), with one of the group variables being ‘particularities of the psychiatric patient history’, containing the items ‘forensic onset’, ‘commitments within the last year prior to the examination’ and ‘absence of commitments within the last year prior to the examination’. The method used was the Kendall bivariate correlation. For this study, the authors separately analyze only the two items regarding commitments by other correlation alternatives and by modern, elaborate statistical analyses, i.e. recording of the standard case study variables, Kendall bivariate correlation, cross tabulation, factor analysis and hierarchical cluster analysis. Results. The results are varied, from theoretically presumed clinical nosography (such as schizophrenia or manic depression), to non–presumed (conduct disorders) or unexpected behavioral acts, and therefore difficult to interpret. Conclusions. One took into consideration the features of the batch as well as the results of the previous standard correlation of the whole statistical lot. The authors emphasize the role of medical security measures that are actually applied in the therapeutic management in general and in risk and second offence management in particular, as well as the role of forensic psychiatric examinations in the detection of certain aspects related to the monitoring of mental patients. PMID:21505571

Dental and Chronological Ages as Determinants of Peak Growth Period and Its Relationship with Dental Calcification Stages

PubMed Central

Litsas, George; Lucchese, Alessandra

2016-01-01

Purpose: To investigate the relationship between dental, chronological, and cervical vertebral maturation growth in the peak growth period, as well as to study the association between the dental calcification phases and the skeletal maturity stages during the same growth period. Methods: Subjects were selected from orthodontic pre-treatment cohorts consisting of 420 subjects where 255 were identified and enrolled into the study, comprising 145 girls and 110 boys. The lateral cephalometric and panoramic radiographs were examined from the archives of the Department of Orthodontics, Aristotle University of Thessaloniki, Greece. Dental age was assessed according to the method of Demirjian, and skeletal maturation according to the Cervical Vertebral Maturation Method. Statistical elaboration included Spearman Brown formula, descriptive statistics, Pearson’s correlation coefficient and regression analysis, paired samples t-test, and Spearman’s rho correlation coefficient. Results: Chronological and dental age showed a high correlation for both gender(r =0.741 for boys, r = 0.770 for girls, p<0.001). The strongest correlation was for the CVM Stage IV for both males (r=0.554) and females (r=0.68). The lowest correlation was for the CVM Stage III in males (r=0.433, p<0.001) and for the CVM Stage II in females (r=0.393, p>0.001). The t-test revealed statistically significant differences between these variables (p<0.001) during the peak period. A statistically significant correlation (p<0.001) between tooth calcification and CVM stages was determined. The second molars showed the highest correlation with CVM stages (CVMS) (r= 0.65 for boys, r = 0.72 for girls). Conclusion: Dental age was more advanced than chronological for both boys and girls for all CVMS. During the peak period these differences were more pronounced. Moreover, all correlations between skeletal and dental stages were statistically significant. The second molars showed the highest correlation whereas the canines showed the lowest correlation for both gender. PMID:27335610

Estimation of positive semidefinite correlation matrices by using convex quadratic semidefinite programming.

PubMed

Fushiki, Tadayoshi

2009-07-01

The correlation matrix is a fundamental statistic that is used in many fields. For example, GroupLens, a collaborative filtering system, uses the correlation between users for predictive purposes. Since the correlation is a natural similarity measure between users, the correlation matrix may be used in the Gram matrix in kernel methods. However, the estimated correlation matrix sometimes has a serious defect: although the correlation matrix is originally positive semidefinite, the estimated one may not be positive semidefinite when not all ratings are observed. To obtain a positive semidefinite correlation matrix, the nearest correlation matrix problem has recently been studied in the fields of numerical analysis and optimization. However, statistical properties are not explicitly used in such studies. To obtain a positive semidefinite correlation matrix, we assume the approximate model. By using the model, an estimate is obtained as the optimal point of an optimization problem formulated with information on the variances of the estimated correlation coefficients. The problem is solved by a convex quadratic semidefinite program. A penalized likelihood approach is also examined. The MovieLens data set is used to test our approach.

Statistical analysis and digital processing of the Mössbauer spectra

NASA Astrophysics Data System (ADS)

Prochazka, Roman; Tucek, Pavel; Tucek, Jiri; Marek, Jaroslav; Mashlan, Miroslav; Pechousek, Jiri

2010-02-01

This work is focused on using the statistical methods and development of the filtration procedures for signal processing in Mössbauer spectroscopy. Statistical tools for noise filtering in the measured spectra are used in many scientific areas. The use of a pure statistical approach in accumulated Mössbauer spectra filtration is described. In Mössbauer spectroscopy, the noise can be considered as a Poisson statistical process with a Gaussian distribution for high numbers of observations. This noise is a superposition of the non-resonant photons counting with electronic noise (from γ-ray detection and discrimination units), and the velocity system quality that can be characterized by the velocity nonlinearities. The possibility of a noise-reducing process using a new design of statistical filter procedure is described. This mathematical procedure improves the signal-to-noise ratio and thus makes it easier to determine the hyperfine parameters of the given Mössbauer spectra. The filter procedure is based on a periodogram method that makes it possible to assign the statistically important components in the spectral domain. The significance level for these components is then feedback-controlled using the correlation coefficient test results. The estimation of the theoretical correlation coefficient level which corresponds to the spectrum resolution is performed. Correlation coefficient test is based on comparison of the theoretical and the experimental correlation coefficients given by the Spearman method. The correctness of this solution was analyzed by a series of statistical tests and confirmed by many spectra measured with increasing statistical quality for a given sample (absorber). The effect of this filter procedure depends on the signal-to-noise ratio and the applicability of this method has binding conditions.

Long-range correlation in cosmic microwave background radiation.

PubMed

Movahed, M Sadegh; Ghasemi, F; Rahvar, Sohrab; Tabar, M Reza Rahimi

2011-08-01

We investigate the statistical anisotropy and gaussianity of temperature fluctuations of Cosmic Microwave Background (CMB) radiation data from the Wilkinson Microwave Anisotropy Probe survey, using the Multifractal Detrended Fluctuation Analysis, Rescaled Range, and Scaled Windowed Variance methods. Multifractal Detrended Fluctuation Analysis shows that CMB fluctuations has a long-range correlation function with a multifractal behavior. By comparing the shuffled and surrogate series of CMB data, we conclude that the multifractality nature of the temperature fluctuation of CMB radiation is mainly due to the long-range correlations, and the map is consistent with a gaussian distribution.

Local image statistics: maximum-entropy constructions and perceptual salience

PubMed Central

Victor, Jonathan D.; Conte, Mary M.

2012-01-01

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

Linearised and non-linearised isotherm models optimization analysis by error functions and statistical means

PubMed Central

2014-01-01

In adsorption study, to describe sorption process and evaluation of best-fitting isotherm model is a key analysis to investigate the theoretical hypothesis. Hence, numerous statistically analysis have been extensively used to estimate validity of the experimental equilibrium adsorption values with the predicted equilibrium values. Several statistical error analysis were carried out. In the present study, the following statistical analysis were carried out to evaluate the adsorption isotherm model fitness, like the Pearson correlation, the coefficient of determination and the Chi-square test, have been used. The ANOVA test was carried out for evaluating significance of various error functions and also coefficient of dispersion were evaluated for linearised and non-linearised models. The adsorption of phenol onto natural soil (Local name Kalathur soil) was carried out, in batch mode at 30 ± 20 C. For estimating the isotherm parameters, to get a holistic view of the analysis the models were compared between linear and non-linear isotherm models. The result reveled that, among above mentioned error functions and statistical functions were designed to determine the best fitting isotherm. PMID:25018878

Statistical and Economic Techniques for Site-specific Nematode Management.

PubMed

Liu, Zheng; Griffin, Terry; Kirkpatrick, Terrence L

2014-03-01

Recent advances in precision agriculture technologies and spatial statistics allow realistic, site-specific estimation of nematode damage to field crops and provide a platform for the site-specific delivery of nematicides within individual fields. This paper reviews the spatial statistical techniques that model correlations among neighboring observations and develop a spatial economic analysis to determine the potential of site-specific nematicide application. The spatial econometric methodology applied in the context of site-specific crop yield response contributes to closing the gap between data analysis and realistic site-specific nematicide recommendations and helps to provide a practical method of site-specifically controlling nematodes.

Knowledge-Sharing Intention among Information Professionals in Nigeria: A Statistical Analysis

ERIC Educational Resources Information Center

Tella, Adeyinka

2016-01-01

In this study, the researcher administered a survey and developed and tested a statistical model to examine the factors that determine the intention of information professionals in Nigeria to share knowledge with their colleagues. The result revealed correlations between the overall score for intending to share knowledge and other…

Critical discussion of evaluation parameters for inter-observer variability in target definition for radiation therapy.

PubMed

Fotina, I; Lütgendorf-Caucig, C; Stock, M; Pötter, R; Georg, D

2012-02-01

Inter-observer studies represent a valid method for the evaluation of target definition uncertainties and contouring guidelines. However, data from the literature do not yet give clear guidelines for reporting contouring variability. Thus, the purpose of this work was to compare and discuss various methods to determine variability on the basis of clinical cases and a literature review. In this study, 7 prostate and 8 lung cases were contoured on CT images by 8 experienced observers. Analysis of variability included descriptive statistics, calculation of overlap measures, and statistical measures of agreement. Cross tables with ratios and correlations were established for overlap parameters. It was shown that the minimal set of parameters to be reported should include at least one of three volume overlap measures (i.e., generalized conformity index, Jaccard coefficient, or conformation number). High correlation between these parameters and scatter of the results was observed. A combination of descriptive statistics, overlap measure, and statistical measure of agreement or reliability analysis is required to fully report the interrater variability in delineation.

[Study on correlation between ITS sequence of Arctium lappa and quality of Fructus Arctii].

PubMed

Xu, Liang; Dou, Deqiang; Wang, Bing; Yang, Yanyun; Kang, Tingguo

2011-07-01

To study the correlation between ITS sequence of Arctium lappa and Fructus Arctii quality of different origin. The samples of Fructu arctii materials were collected from 26 different producing areas. Their ITS sequence were determined after polymerase chain reaction (PCR) and quality were evaluated through the determination of arctiin content by HPLC. Genetic diversity, genotype and correlation were analyzed by ClustalX (1.81), Mage 4.0, SPSS 13.0 statistical software. ITS sequence of A. was obtained from 26 samples, and was registered in the GenBank. Corresponding arctiin content of Fructus arctii and 1000-grain weight were determined. A. lappa genotype correlated with Fructus arctii quality by statistical analysis. The research provided a foundation for revealing the molecular mechanism of Fructus arctii geoherbs.

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.

Assessment of trace elements levels in patients with Type 2 diabetes using multivariate statistical analysis.

PubMed

Badran, M; Morsy, R; Soliman, H; Elnimr, T

2016-01-01

The trace elements metabolism has been reported to possess specific roles in the pathogenesis and progress of diabetes mellitus. Due to the continuous increase in the population of patients with Type 2 diabetes (T2D), this study aims to assess the levels and inter-relationships of fast blood glucose (FBG) and serum trace elements in Type 2 diabetic patients. This study was conducted on 40 Egyptian Type 2 diabetic patients and 36 healthy volunteers (Hospital of Tanta University, Tanta, Egypt). The blood serum was digested and then used to determine the levels of 24 trace elements using an inductive coupled plasma mass spectroscopy (ICP-MS). Multivariate statistical analysis depended on correlation coefficient, cluster analysis (CA) and principal component analysis (PCA), were used to analysis the data. The results exhibited significant changes in FBG and eight of trace elements, Zn, Cu, Se, Fe, Mn, Cr, Mg, and As, levels in the blood serum of Type 2 diabetic patients relative to those of healthy controls. The statistical analyses using multivariate statistical techniques were obvious in the reduction of the experimental variables, and grouping the trace elements in patients into three clusters. The application of PCA revealed a distinct difference in associations of trace elements and their clustering patterns in control and patients group in particular for Mg, Fe, Cu, and Zn that appeared to be the most crucial factors which related with Type 2 diabetes. Therefore, on the basis of this study, the contributors of trace elements content in Type 2 diabetic patients can be determine and specify with correlation relationship and multivariate statistical analysis, which confirm that the alteration of some essential trace metals may play a role in the development of diabetes mellitus. Copyright © 2015 Elsevier GmbH. All rights reserved.

Gaussian statistics of the cosmic microwave background: Correlation of temperature extrema in the COBE DMR two-year sky maps

NASA Technical Reports Server (NTRS)

Kogut, A.; Banday, A. J.; Bennett, C. L.; Hinshaw, G.; Lubin, P. M.; Smoot, G. F.

1995-01-01

We use the two-point correlation function of the extrema points (peaks and valleys) in the Cosmic Background Explorer (COBE) Differential Microwave Radiometers (DMR) 2 year sky maps as a test for non-Gaussian temperature distribution in the cosmic microwave background anisotropy. A maximum-likelihood analysis compares the DMR data to n = 1 toy models whose random-phase spherical harmonic components a(sub lm) are drawn from either Gaussian, chi-square, or log-normal parent populations. The likelihood of the 53 GHz (A+B)/2 data is greatest for the exact Gaussian model. There is less than 10% chance that the non-Gaussian models tested describe the DMR data, limited primarily by type II errors in the statistical inference. The extrema correlation function is a stronger test for this class of non-Gaussian models than topological statistics such as the genus.

Descriptive statistics and correlation analysis of agronomic traits in a maize recombinant inbred line population.

PubMed

Zhang, H M; Hui, G Q; Luo, Q; Sun, Y; Liu, X H

2014-01-21

Maize (Zea mays L.) is one of the most important crops in the world. In this study, 13 agronomic traits of a recombinant inbred line population that was derived from the cross between Mo17 and Huangzao4 were investigated in maize: ear diameter, ear length, ear axis diameter, ear weight, plant height, ear height, days to pollen shed (DPS), days to silking (DS), the interval between DPS and DS, 100-kernel weight, kernel test weight, ear kernel weight, and kernel rate. Furthermore, the descriptive statistics and correlation analysis of the 13 traits were performed using the SPSS 11.5 software. The results providing the phenotypic data here are needed for the quantitative trait locus mapping of these agronomic traits.

Non-parametric correlative uncertainty quantification and sensitivity analysis: Application to a Langmuir bimolecular adsorption model

NASA Astrophysics Data System (ADS)

Feng, Jinchao; Lansford, Joshua; Mironenko, Alexander; Pourkargar, Davood Babaei; Vlachos, Dionisios G.; Katsoulakis, Markos A.

2018-03-01

We propose non-parametric methods for both local and global sensitivity analysis of chemical reaction models with correlated parameter dependencies. The developed mathematical and statistical tools are applied to a benchmark Langmuir competitive adsorption model on a close packed platinum surface, whose parameters, estimated from quantum-scale computations, are correlated and are limited in size (small data). The proposed mathematical methodology employs gradient-based methods to compute sensitivity indices. We observe that ranking influential parameters depends critically on whether or not correlations between parameters are taken into account. The impact of uncertainty in the correlation and the necessity of the proposed non-parametric perspective are demonstrated.

Correlation of Visual Prostate Symptom Score with International Prostate Symptom Score and Uroflowmetry Parameters in Nepalese Male Patients with Lower Urinary Tract Symptoms.

PubMed

Bhomi, K K; Subedi, N; Panta, P P

2017-01-01

International prostate symptom score is a validated questionnaire used to evaluate the lower urinary tract symptoms in benign prostatic hyperplasia. Visual prostate symptom score is a new simplified symptom score with pictograms to evaluate the same. We evaluated the correlation of visual prostate symptom score with international prostate symptom score and uroflowmetry parameters in Nepalese male patients with lower urinary tract symptoms. Male patients aged ≥40 years attending the Urology clinic were enrolled in the study. They were given international prostate symptom score and visual prostate symptom score questionnaires to complete providing assistance whenever needed. Demographic data, examination findings and uroflowmetry parameters were noted. Correlation and regression analysis was used to identify correlation of the two scoring systems and uroflowmetry parameters. Among the 66 patients enrolled, only 10 (15.15%) patients were able to understand English language. There was a statistically significant correlation between total visual prostate symptom score and international prostate symptom score (r= 0.822; P<0.01). The correlations between individual scores of the two scoring systems related to force of urinary stream, frequency, nocturia and quality of life were also statistically significant. There was also a statistically significant correlation of both scores with maximum flow rate and average flow rate. There is a statistically significant correlation of visual prostate symptom score with international prostate symptom score and uroflowmetry parameters. IPSS can be replaced with simple VPSS in evaluation of lower urinary tract symptoms in elderly male patients.

Assessing correlations between the spatial distribution of the dose to the rectal wall and late rectal toxicity after prostate radiotherapy: an analysis of data from the MRC RT01 trial (ISRCTN 47772397)

NASA Astrophysics Data System (ADS)

Buettner, Florian; Gulliford, Sarah L.; Webb, Steve; Sydes, Matthew R.; Dearnaley, David P.; Partridge, Mike

2009-11-01

Many studies have been performed to assess correlations between measures derived from dose-volume histograms and late rectal toxicities for radiotherapy of prostate cancer. The purpose of this study was to quantify correlations between measures describing the shape and location of the dose distribution and different outcomes. The dose to the rectal wall was projected on a two-dimensional map. In order to characterize the dose distribution, its centre of mass, longitudinal and lateral extent, and eccentricity were calculated at different dose levels. Furthermore, the dose-surface histogram (DSH) was determined. Correlations between these measures and seven clinically relevant rectal-toxicity endpoints were quantified by maximally selected standardized Wilcoxon rank statistics. The analysis was performed using data from the RT01 prostate radiotherapy trial. For some endpoints, the shape of the dose distribution is more strongly correlated with the outcome than simple DSHs. Rectal bleeding was most strongly correlated with the lateral extent of the dose distribution. For loose stools, the strongest correlations were found for longitudinal extent; proctitis was most strongly correlated with DSH. For the other endpoints no statistically significant correlations could be found. The strengths of the correlations between the shape of the dose distribution and outcome differed considerably between the different endpoints. Due to these significant correlations, it is desirable to use shape-based tools in order to assess the quality of a dose distribution.

Statistical analysis of the calibration procedure for personnel radiation measurement instruments

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

Bush, W.J.; Bengston, S.J.; Kalbeitzer, F.L.

1980-11-01

Thermoluminescent analyzer (TLA) calibration procedures were used to estimate personnel radiation exposure levels at the Idaho National Engineering Laboratory (INEL). A statistical analysis is presented herein based on data collected over a six month period in 1979 on four TLA's located in the Department of Energy (DOE) Radiological and Environmental Sciences Laboratory at the INEL. The data were collected according to the day-to-day procedure in effect at that time. Both gamma and beta radiation models are developed. Observed TLA readings of thermoluminescent dosimeters are correlated with known radiation levels. This correlation is then used to predict unknown radiation doses frommore » future analyzer readings of personnel thermoluminescent dosimeters. The statistical techniques applied in this analysis include weighted linear regression, estimation of systematic and random error variances, prediction interval estimation using Scheffe's theory of calibration, the estimation of the ratio of the means of two normal bivariate distributed random variables and their corresponding confidence limits according to Kendall and Stuart, tests of normality, experimental design, a comparison between instruments, and quality control.« less

A hint of Poincaré dodecahedral topology in the WMAP first year sky map

NASA Astrophysics Data System (ADS)

Roukema, B. F.; Lew, B.; Cechowska, M.; Marecki, A.; Bajtlik, S.

2004-09-01

It has recently been suggested by Luminet et al. (\\cite{LumNat03}) that the WMAP data are better matched by a geometry in which the topology is that of a Poincaré dodecahedral model and the curvature is ``slightly'' spherical, rather than by an (effectively) infinite flat model. A general back-to-back matched circles analysis by Cornish et al. (\\cite{CSSK03}) for angular radii in the range 25-90 °, using a correlation statistic for signal detection, failed to support this. In this paper, a matched circles analysis specifically designed to detect dodecahedral patterns of matched circles is performed over angular radii in the range 1-40\\ddeg on the one-year WMAP data. Signal detection is attempted via a correlation statistic and an rms difference statistic. Extreme value distributions of these statistics are calculated for one orientation of the 36\\ddeg ``screw motion'' (Clifford translation) when matching circles, for the opposite screw motion, and for a zero (unphysical) rotation. The most correlated circles appear for circle radii of \\alpha =11 ± 1 \\ddeg, for the left-handed screw motion, but not for the right-handed one, nor for the zero rotation. The favoured six dodecahedral face centres in galactic coordinates are (\\lII,\\bII) ≈ (252\\ddeg,+65\\ddeg), (51\\ddeg,+51\\ddeg), (144\\ddeg,+38\\ddeg), (207\\ddeg,+10\\ddeg), (271\\ddeg,+3\\ddeg), (332\\ddeg,+25\\ddeg) and their opposites. The six pairs of circles independently each favour a circle angular radius of 11 ± 1\\ddeg. The temperature fluctuations along the matched circles are plotted and are clearly highly correlated. Whether or not these six circle pairs centred on dodecahedral faces match via a 36\\ddeg rotation only due to unexpected statistical properties of the WMAP ILC map, or whether they match due to global geometry, it is clear that the WMAP ILC map has some unusual statistical properties which mimic a potentially interesting cosmological signal.

Analysis of Magnitude Correlations in a Self-Similar model of Seismicity

NASA Astrophysics Data System (ADS)

Zambrano, A.; Joern, D.

2017-12-01

A recent model of seismicity that incorporates a self-similar Omori-Utsu relation, which is used to describe the temporal evolution of earthquake triggering, has been shown to provide a more accurate description of seismicity in Southern California when compared to epidemic type aftershock sequence models. Forecasting of earthquakes is an active research area where one of the debated points is whether magnitude correlations of earthquakes exist within real world seismic data. Prior to this work, the analysis of magnitude correlations of the aforementioned self-similar model had not been addressed. Here we present statistical properties of the magnitude correlations for the self-similar model along with an analytical analysis of the branching ratio and criticality parameters.

Efficient Coding and Statistically Optimal Weighting of Covariance among Acoustic Attributes in Novel Sounds

PubMed Central

Stilp, Christian E.; Kluender, Keith R.

2012-01-01

To the extent that sensorineural systems are efficient, redundancy should be extracted to optimize transmission of information, but perceptual evidence for this has been limited. Stilp and colleagues recently reported efficient coding of robust correlation (r = .97) among complex acoustic attributes (attack/decay, spectral shape) in novel sounds. Discrimination of sounds orthogonal to the correlation was initially inferior but later comparable to that of sounds obeying the correlation. These effects were attenuated for less-correlated stimuli (r = .54) for reasons that are unclear. Here, statistical properties of correlation among acoustic attributes essential for perceptual organization are investigated. Overall, simple strength of the principal correlation is inadequate to predict listener performance. Initial superiority of discrimination for statistically consistent sound pairs was relatively insensitive to decreased physical acoustic/psychoacoustic range of evidence supporting the correlation, and to more frequent presentations of the same orthogonal test pairs. However, increased range supporting an orthogonal dimension has substantial effects upon perceptual organization. Connectionist simulations and Eigenvalues from closed-form calculations of principal components analysis (PCA) reveal that perceptual organization is near-optimally weighted to shared versus unshared covariance in experienced sound distributions. Implications of reduced perceptual dimensionality for speech perception and plausible neural substrates are discussed. PMID:22292057

[A cross-correlational analysis of the background neuronal pulse trains in surviving slices of the guinea pig neocortex].

PubMed

Bortnik, A T; Iakupova, L P

1991-01-01

Cross-correlation analysis of interdependence of the background spike activity was carried out for pairs of adjacent neurons simultaneously recorded in the incubated slices of the neocortex of guinea-pig. Statistical correlation of spike discharges was detected in 16 out of 26 recorded pairs of the neurons. Significant correlation was observed mainly in the range of +/- 100 ms from the null point. Cross-correlation had symmetric or asymmetric maxima up to 150 ms long and negative shifts up to 200 ms long. More complex positive-negative types of cross-correlations were also obtained. The data were compared to those known from other authors for the intact brain. The contribution of intrinsic intracortical interactions and extrinsic afferent influences in these correlations of activity is discussed.

Identifying Node Role in Social Network Based on Multiple Indicators

PubMed Central

Huang, Shaobin; Lv, Tianyang; Zhang, Xizhe; Yang, Yange; Zheng, Weimin; Wen, Chao

2014-01-01

It is a classic topic of social network analysis to evaluate the importance of nodes and identify the node that takes on the role of core or bridge in a network. Because a single indicator is not sufficient to analyze multiple characteristics of a node, it is a natural solution to apply multiple indicators that should be selected carefully. An intuitive idea is to select some indicators with weak correlations to efficiently assess different characteristics of a node. However, this paper shows that it is much better to select the indicators with strong correlations. Because indicator correlation is based on the statistical analysis of a large number of nodes, the particularity of an important node will be outlined if its indicator relationship doesn't comply with the statistical correlation. Therefore, the paper selects the multiple indicators including degree, ego-betweenness centrality and eigenvector centrality to evaluate the importance and the role of a node. The importance of a node is equal to the normalized sum of its three indicators. A candidate for core or bridge is selected from the great degree nodes or the nodes with great ego-betweenness centrality respectively. Then, the role of a candidate is determined according to the difference between its indicators' relationship with the statistical correlation of the overall network. Based on 18 real networks and 3 kinds of model networks, the experimental results show that the proposed methods perform quite well in evaluating the importance of nodes and in identifying the node role. PMID:25089823

Statistics of baryon correlation functions in lattice QCD

NASA Astrophysics Data System (ADS)

Wagman, Michael L.; Savage, Martin J.; Nplqcd Collaboration

2017-12-01

A systematic analysis of the structure of single-baryon correlation functions calculated with lattice QCD is performed, with a particular focus on characterizing the structure of the noise associated with quantum fluctuations. The signal-to-noise problem in these correlation functions is shown, as long suspected, to result from a sign problem. The log-magnitude and complex phase are found to be approximately described by normal and wrapped normal distributions respectively. Properties of circular statistics are used to understand the emergence of a large time noise region where standard energy measurements are unreliable. Power-law tails in the distribution of baryon correlation functions, associated with stable distributions and "Lévy flights," are found to play a central role in their time evolution. A new method of analyzing correlation functions is considered for which the signal-to-noise ratio of energy measurements is constant, rather than exponentially degrading, with increasing source-sink separation time. This new method includes an additional systematic uncertainty that can be removed by performing an extrapolation, and the signal-to-noise problem reemerges in the statistics of this extrapolation. It is demonstrated that this new method allows accurate results for the nucleon mass to be extracted from the large-time noise region inaccessible to standard methods. The observations presented here are expected to apply to quantum Monte Carlo calculations more generally. Similar methods to those introduced here may lead to practical improvements in analysis of noisier systems.

"TNOs are Cool": A survey of the trans-Neptunian region. XIII. Statistical analysis of multiple trans-Neptunian objects observed with Herschel Space Observatory

NASA Astrophysics Data System (ADS)

Kovalenko, I. D.; Doressoundiram, A.; Lellouch, E.; Vilenius, E.; Müller, T.; Stansberry, J.

2017-11-01

Context. Gravitationally bound multiple systems provide an opportunity to estimate the mean bulk density of the objects, whereas this characteristic is not available for single objects. Being a primitive population of the outer solar system, binary and multiple trans-Neptunian objects (TNOs) provide unique information about bulk density and internal structure, improving our understanding of their formation and evolution. Aims: The goal of this work is to analyse parameters of multiple trans-Neptunian systems, observed with Herschel and Spitzer space telescopes. Particularly, statistical analysis is done for radiometric size and geometric albedo, obtained from photometric observations, and for estimated bulk density. Methods: We use Monte Carlo simulation to estimate the real size distribution of TNOs. For this purpose, we expand the dataset of diameters by adopting the Minor Planet Center database list with available values of the absolute magnitude therein, and the albedo distribution derived from Herschel radiometric measurements. We use the 2-sample Anderson-Darling non-parametric statistical method for testing whether two samples of diameters, for binary and single TNOs, come from the same distribution. Additionally, we use the Spearman's coefficient as a measure of rank correlations between parameters. Uncertainties of estimated parameters together with lack of data are taken into account. Conclusions about correlations between parameters are based on statistical hypothesis testing. Results: We have found that the difference in size distributions of multiple and single TNOs is biased by small objects. The test on correlations between parameters shows that the effective diameter of binary TNOs strongly correlates with heliocentric orbital inclination and with magnitude difference between components of binary system. The correlation between diameter and magnitude difference implies that small and large binaries are formed by different mechanisms. Furthermore, the statistical test indicates, although not significant with the sample size, that a moderately strong correlation exists between diameter and bulk density. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.

Complex polarization-phase and spatial-frequency selections of laser images of blood-plasma films in diagnostics of changes in their polycrystalline structure

NASA Astrophysics Data System (ADS)

Ushenko, Yu. A.; Angelskii, P. O.; Dubolazov, A. V.; Karachevtsev, A. O.; Sidor, M. I.; Mintser, O. P.; Oleinichenko, B. P.; Bizer, L. I.

2013-10-01

We present a theoretical formalism of correlation phase analysis of laser images of human blood plasma with spatial-frequency selection of manifestations of mechanisms of linear and circular birefringence of albumin and globulin polycrystalline networks. Comparative results of the measurement of coordinate distributions of the correlation parameter—the modulus of the degree of local correlation of amplitudes—of laser images of blood plasma taken from patients of three groups—healthy patients (donors), rheumatoid-arthritis patients, and breast-cancer patients—are presented. We investigate values and ranges of change of statistical (the first to fourth statistical moments), correlation (excess of autocorrelation functions), and fractal (slopes of approximating curves and dispersion of extrema of logarithmic dependences of power spectra) parameters of coordinate distributions of the degree of local correlation of amplitudes. Objective criteria for diagnostics of occurrence and differentiation of inflammatory and oncological states are determined.

Histogram analysis parameters identify multiple associations between DWI and DCE MRI in head and neck squamous cell carcinoma.

PubMed

Meyer, Hans Jonas; Leifels, Leonard; Schob, Stefan; Garnov, Nikita; Surov, Alexey

2018-01-01

Nowadays, multiparametric investigations of head and neck squamous cell carcinoma (HNSCC) are established. These approaches can better characterize tumor biology and behavior. Diffusion weighted imaging (DWI) can by means of apparent diffusion coefficient (ADC) quantitatively characterize different tissue compartments. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) reflects perfusion and vascularization of tissues. Recently, a novel approach of data acquisition, namely histogram analysis of different images is a novel diagnostic approach, which can provide more information of tissue heterogeneity. The purpose of this study was to analyze possible associations between DWI, and DCE parameters derived from histogram analysis in patients with HNSCC. Overall, 34 patients, 9 women and 25 men, mean age, 56.7±10.2years, with different HNSCC were involved in the study. DWI was obtained by using of an axial echo planar imaging sequence with b-values of 0 and 800s/mm 2 . Dynamic T1w DCE sequence after intravenous application of contrast medium was performed for estimation of the following perfusion parameters: volume transfer constant (K trans ), volume of the extravascular extracellular leakage space (Ve), and diffusion of contrast medium from the extravascular extracellular leakage space back to the plasma (Kep). Both ADC and perfusion parameters maps were processed offline in DICOM format with custom-made Matlab-based application. Thereafter, polygonal ROIs were manually drawn on the transferred maps on each slice. For every parameter, mean, maximal, minimal, and median values, as well percentiles 10th, 25th, 75th, 90th, kurtosis, skewness, and entropy were estimated. Сorrelation analysis identified multiple statistically significant correlations between the investigated parameters. Ve related parameters correlated well with different ADC values. Especially, percentiles 10 and 75, mode, and median values showed stronger correlations in comparison to other parameters. Thereby, the calculated correlation coefficients ranged from 0.62 to 0.69. Furthermore, K trans related parameters showed multiple slightly to moderate significant correlations with different ADC values. Strongest correlations were identified between ADC P75 and K trans min (p=0.58, P=0.0007), and ADC P75 and K trans P10 (p=0.56, P=0.001). Only four K ep related parameters correlated statistically significant with ADC fractions. Strongest correlation was found between K ep max and ADC mode (p=-0.47, P=0.008). Multiple statistically significant correlations between, DWI and DCE MRI parameters derived from histogram analysis were identified in HNSCC. Copyright © 2017 Elsevier Inc. All rights reserved.

Generalized Majority Logic Criterion to Analyze the Statistical Strength of S-Boxes

NASA Astrophysics Data System (ADS)

Hussain, Iqtadar; Shah, Tariq; Gondal, Muhammad Asif; Mahmood, Hasan

2012-05-01

The majority logic criterion is applicable in the evaluation process of substitution boxes used in the advanced encryption standard (AES). The performance of modified or advanced substitution boxes is predicted by processing the results of statistical analysis by the majority logic criteria. In this paper, we use the majority logic criteria to analyze some popular and prevailing substitution boxes used in encryption processes. In particular, the majority logic criterion is applied to AES, affine power affine (APA), Gray, Lui J, residue prime, S8 AES, Skipjack, and Xyi substitution boxes. The majority logic criterion is further extended into a generalized majority logic criterion which has a broader spectrum of analyzing the effectiveness of substitution boxes in image encryption applications. The integral components of the statistical analyses used for the generalized majority logic criterion are derived from results of entropy analysis, contrast analysis, correlation analysis, homogeneity analysis, energy analysis, and mean of absolute deviation (MAD) analysis.

SMALL COLOUR VISION VARIATIONS AND THEIR EFFECT IN VISUAL COLORIMETRY,

DTIC Science & Technology

COLOR VISION, PERFORMANCE(HUMAN), TEST EQUIPMENT, PERFORMANCE(HUMAN), CORRELATION TECHNIQUES, STATISTICAL PROCESSES, COLORS, ANALYSIS OF VARIANCE, AGING(MATERIALS), COLORIMETRY , BRIGHTNESS, ANOMALIES, PLASTICS, UNITED KINGDOM.

THE MEASUREMENT OF BONE QUALITY USING GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURAL FEATURES.

PubMed

Shirvaikar, Mukul; Huang, Ning; Dong, Xuanliang Neil

2016-10-01

In this paper, statistical methods for the estimation of bone quality to predict the risk of fracture are reported. Bone mineral density and bone architecture properties are the main contributors of bone quality. Dual-energy X-ray Absorptiometry (DXA) is the traditional clinical measurement technique for bone mineral density, but does not include architectural information to enhance the prediction of bone fragility. Other modalities are not practical due to cost and access considerations. This study investigates statistical parameters based on the Gray Level Co-occurrence Matrix (GLCM) extracted from two-dimensional projection images and explores links with architectural properties and bone mechanics. Data analysis was conducted on Micro-CT images of 13 trabecular bones (with an in-plane spatial resolution of about 50μm). Ground truth data for bone volume fraction (BV/TV), bone strength and modulus were available based on complex 3D analysis and mechanical tests. Correlation between the statistical parameters and biomechanical test results was studied using regression analysis. The results showed Cluster-Shade was strongly correlated with the microarchitecture of the trabecular bone and related to mechanical properties. Once the principle thesis of utilizing second-order statistics is established, it can be extended to other modalities, providing cost and convenience advantages for patients and doctors.

THE MEASUREMENT OF BONE QUALITY USING GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURAL FEATURES

PubMed Central

Shirvaikar, Mukul; Huang, Ning; Dong, Xuanliang Neil

2016-01-01

In this paper, statistical methods for the estimation of bone quality to predict the risk of fracture are reported. Bone mineral density and bone architecture properties are the main contributors of bone quality. Dual-energy X-ray Absorptiometry (DXA) is the traditional clinical measurement technique for bone mineral density, but does not include architectural information to enhance the prediction of bone fragility. Other modalities are not practical due to cost and access considerations. This study investigates statistical parameters based on the Gray Level Co-occurrence Matrix (GLCM) extracted from two-dimensional projection images and explores links with architectural properties and bone mechanics. Data analysis was conducted on Micro-CT images of 13 trabecular bones (with an in-plane spatial resolution of about 50μm). Ground truth data for bone volume fraction (BV/TV), bone strength and modulus were available based on complex 3D analysis and mechanical tests. Correlation between the statistical parameters and biomechanical test results was studied using regression analysis. The results showed Cluster-Shade was strongly correlated with the microarchitecture of the trabecular bone and related to mechanical properties. Once the principle thesis of utilizing second-order statistics is established, it can be extended to other modalities, providing cost and convenience advantages for patients and doctors. PMID:28042512

Texture analysis of apparent diffusion coefficient maps for treatment response assessment in prostate cancer bone metastases-A pilot study.

PubMed

Reischauer, Carolin; Patzwahl, René; Koh, Dow-Mu; Froehlich, Johannes M; Gutzeit, Andreas

2018-04-01

To evaluate whole-lesion volumetric texture analysis of apparent diffusion coefficient (ADC) maps for assessing treatment response in prostate cancer bone metastases. Texture analysis is performed in 12 treatment-naïve patients with 34 metastases before treatment and at one, two, and three months after the initiation of androgen deprivation therapy. Four first-order and 19 second-order statistical texture features are computed on the ADC maps in each lesion at every time point. Repeatability, inter-patient variability, and changes in the feature values under therapy are investigated. Spearman rank's correlation coefficients are calculated across time to demonstrate the relationship between the texture features and the serum prostate specific antigen (PSA) levels. With few exceptions, the texture features exhibited moderate to high precision. At the same time, Friedman's tests revealed that all first-order and second-order statistical texture features changed significantly in response to therapy. Thereby, the majority of texture features showed significant changes in their values at all post-treatment time points relative to baseline. Bivariate analysis detected significant correlations between the great majority of texture features and the serum PSA levels. Thereby, three first-order and six second-order statistical features showed strong correlations with the serum PSA levels across time. The findings in the present work indicate that whole-tumor volumetric texture analysis may be utilized for response assessment in prostate cancer bone metastases. The approach may be used as a complementary measure for treatment monitoring in conjunction with averaged ADC values. Copyright © 2018 Elsevier B.V. All rights reserved.

Random matrix theory analysis of cross-correlations in the US stock market: Evidence from Pearson’s correlation coefficient and detrended cross-correlation coefficient

NASA Astrophysics Data System (ADS)

Wang, Gang-Jin; Xie, Chi; Chen, Shou; Yang, Jiao-Jiao; Yang, Ming-Yan

2013-09-01

In this study, we first build two empirical cross-correlation matrices in the US stock market by two different methods, namely the Pearson’s correlation coefficient and the detrended cross-correlation coefficient (DCCA coefficient). Then, combining the two matrices with the method of random matrix theory (RMT), we mainly investigate the statistical properties of cross-correlations in the US stock market. We choose the daily closing prices of 462 constituent stocks of S&P 500 index as the research objects and select the sample data from January 3, 2005 to August 31, 2012. In the empirical analysis, we examine the statistical properties of cross-correlation coefficients, the distribution of eigenvalues, the distribution of eigenvector components, and the inverse participation ratio. From the two methods, we find some new results of the cross-correlations in the US stock market in our study, which are different from the conclusions reached by previous studies. The empirical cross-correlation matrices constructed by the DCCA coefficient show several interesting properties at different time scales in the US stock market, which are useful to the risk management and optimal portfolio selection, especially to the diversity of the asset portfolio. It will be an interesting and meaningful work to find the theoretical eigenvalue distribution of a completely random matrix R for the DCCA coefficient because it does not obey the Marčenko-Pastur distribution.

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

PubMed

Jenkinson, Garrett; Abante, Jordi; Feinberg, Andrew P; Goutsias, John

2018-03-07

DNA methylation is a stable form of epigenetic memory used by cells to control gene expression. Whole genome bisulfite sequencing (WGBS) has emerged as a gold-standard experimental technique for studying DNA methylation by producing high resolution genome-wide methylation profiles. Statistical modeling and analysis is employed to computationally extract and quantify information from these profiles in an effort to identify regions of the genome that demonstrate crucial or aberrant epigenetic behavior. However, the performance of most currently available methods for methylation analysis is hampered by their inability to directly account for statistical dependencies between neighboring methylation sites, thus ignoring significant information available in WGBS reads. We present a powerful information-theoretic approach for genome-wide modeling and analysis of WGBS data based on the 1D Ising model of statistical physics. This approach takes into account correlations in methylation by utilizing a joint probability model that encapsulates all information available in WGBS methylation reads and produces accurate results even when applied on single WGBS samples with low coverage. Using the Shannon entropy, our approach provides a rigorous quantification of methylation stochasticity in individual WGBS samples genome-wide. Furthermore, it utilizes the Jensen-Shannon distance to evaluate differences in methylation distributions between a test and a reference sample. Differential performance assessment using simulated and real human lung normal/cancer data demonstrate a clear superiority of our approach over DSS, a recently proposed method for WGBS data analysis. Critically, these results demonstrate that marginal methods become statistically invalid when correlations are present in the data. This contribution demonstrates clear benefits and the necessity of modeling joint probability distributions of methylation using the 1D Ising model of statistical physics and of quantifying methylation stochasticity using concepts from information theory. By employing this methodology, substantial improvement of DNA methylation analysis can be achieved by effectively taking into account the massive amount of statistical information available in WGBS data, which is largely ignored by existing methods.

Statistics 101 for Radiologists.

PubMed

Anvari, Arash; Halpern, Elkan F; Samir, Anthony E

2015-10-01

Diagnostic tests have wide clinical applications, including screening, diagnosis, measuring treatment effect, and determining prognosis. Interpreting diagnostic test results requires an understanding of key statistical concepts used to evaluate test efficacy. This review explains descriptive statistics and discusses probability, including mutually exclusive and independent events and conditional probability. In the inferential statistics section, a statistical perspective on study design is provided, together with an explanation of how to select appropriate statistical tests. Key concepts in recruiting study samples are discussed, including representativeness and random sampling. Variable types are defined, including predictor, outcome, and covariate variables, and the relationship of these variables to one another. In the hypothesis testing section, we explain how to determine if observed differences between groups are likely to be due to chance. We explain type I and II errors, statistical significance, and study power, followed by an explanation of effect sizes and how confidence intervals can be used to generalize observed effect sizes to the larger population. Statistical tests are explained in four categories: t tests and analysis of variance, proportion analysis tests, nonparametric tests, and regression techniques. We discuss sensitivity, specificity, accuracy, receiver operating characteristic analysis, and likelihood ratios. Measures of reliability and agreement, including κ statistics, intraclass correlation coefficients, and Bland-Altman graphs and analysis, are introduced. © RSNA, 2015.

[Study on ecological suitability regionalization of Eucommia ulmoides in Guizhou].

PubMed

Kang, Chuan-Zhi; Wang, Qing-Qing; Zhou, Tao; Jiang, Wei-Ke; Xiao, Cheng-Hong; Xie, Yu

2014-05-01

To study the ecological suitability regionalization of Eucommia ulmoides, for selecting artificial planting base and high-quality industrial raw material purchase area of the herb in Guizhou. Based on the investigation of 14 Eucommia ulmoides producing areas, pinoresinol diglucoside content and ecological factors were obtained. Using spatial analysis method to carry on ecological suitability regionalization. Meanwhile, combining pinoresinol diglucoside content, the correlation of major active components and environmental factors were analyzed by statistical analysis. The most suitability planting area of Eucommia ulmoides was the northwest of Guizhou. The distribution of Eucommia ulmoides was mainly affected by the type and pH value of soil, and monthly precipitation. The spatial structure of major active components in Eucommia ulmoides were randomly distributed in global space, but had only one aggregation point which had a high positive correlation in local space. The major active components of Eucommia ulmoides had no correlation with altitude, longitude or latitude. Using the spatial analysis method and statistical analysis method, based on environmental factor and pinoresinol diglucoside content, the ecological suitability regionalization of Eucommia ulmoides can provide reference for the selection of suitable planting area, artificial planting base and directing production layout.

Theory and simulations of covariance mapping in multiple dimensions for data analysis in high-event-rate experiments

NASA Astrophysics Data System (ADS)

Zhaunerchyk, V.; Frasinski, L. J.; Eland, J. H. D.; Feifel, R.

2014-05-01

Multidimensional covariance analysis and its validity for correlation of processes leading to multiple products are investigated from a theoretical point of view. The need to correct for false correlations induced by experimental parameters which fluctuate from shot to shot, such as the intensity of self-amplified spontaneous emission x-ray free-electron laser pulses, is emphasized. Threefold covariance analysis based on simple extension of the two-variable formulation is shown to be valid for variables exhibiting Poisson statistics. In this case, false correlations arising from fluctuations in an unstable experimental parameter that scale linearly with signals can be eliminated by threefold partial covariance analysis, as defined here. Fourfold covariance based on the same simple extension is found to be invalid in general. Where fluctuations in an unstable parameter induce nonlinear signal variations, a technique of contingent covariance analysis is proposed here to suppress false correlations. In this paper we also show a method to eliminate false correlations associated with fluctuations of several unstable experimental parameters.

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.

Automated Cognitive Health Assessment From Smart Home-Based Behavior Data.

PubMed

Dawadi, Prafulla Nath; Cook, Diane Joyce; Schmitter-Edgecombe, Maureen

2016-07-01

Smart home technologies offer potential benefits for assisting clinicians by automating health monitoring and well-being assessment. In this paper, we examine the actual benefits of smart home-based analysis by monitoring daily behavior in the home and predicting clinical scores of the residents. To accomplish this goal, we propose a clinical assessment using activity behavior (CAAB) approach to model a smart home resident's daily behavior and predict the corresponding clinical scores. CAAB uses statistical features that describe characteristics of a resident's daily activity performance to train machine learning algorithms that predict the clinical scores. We evaluate the performance of CAAB utilizing smart home sensor data collected from 18 smart homes over two years. We obtain a statistically significant correlation ( r=0.72) between CAAB-predicted and clinician-provided cognitive scores and a statistically significant correlation ( r=0.45) between CAAB-predicted and clinician-provided mobility scores. These prediction results suggest that it is feasible to predict clinical scores using smart home sensor data and learning-based data analysis.

Peculiarities of the statistics of spectrally selected fluorescence radiation in laser-pumped dye-doped random media

NASA Astrophysics Data System (ADS)

Yuvchenko, S. A.; Ushakova, E. V.; Pavlova, M. V.; Alonova, M. V.; Zimnyakov, D. A.

2018-04-01

We consider the practical realization of a new optical probe method of the random media which is defined as the reference-free path length interferometry with the intensity moments analysis. A peculiarity in the statistics of the spectrally selected fluorescence radiation in laser-pumped dye-doped random medium is discussed. Previously established correlations between the second- and the third-order moments of the intensity fluctuations in the random interference patterns, the coherence function of the probe radiation, and the path difference probability density for the interfering partial waves in the medium are confirmed. The correlations were verified using the statistical analysis of the spectrally selected fluorescence radiation emitted by a laser-pumped dye-doped random medium. Water solution of Rhodamine 6G was applied as the doping fluorescent agent for the ensembles of the densely packed silica grains, which were pumped by the 532 nm radiation of a solid state laser. The spectrum of the mean path length for a random medium was reconstructed.

Factorial analysis of trihalomethanes formation in drinking water.

PubMed

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

2010-06-01

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

A national streamflow network gap analysis

USGS Publications Warehouse

Kiang, Julie E.; Stewart, David W.; Archfield, Stacey A.; Osborne, Emily B.; Eng, Ken

2013-01-01

The U.S. Geological Survey (USGS) conducted a gap analysis to evaluate how well the USGS streamgage network meets a variety of needs, focusing on the ability to calculate various statistics at locations that have streamgages (gaged) and that do not have streamgages (ungaged). This report presents the results of analysis to determine where there are gaps in the network of gaged locations, how accurately desired statistics can be calculated with a given length of record, and whether the current network allows for estimation of these statistics at ungaged locations. The analysis indicated that there is variability across the Nation’s streamflow data-collection network in terms of the spatial and temporal coverage of streamgages. In general, the Eastern United States has better coverage than the Western United States. The arid Southwestern United States, Alaska, and Hawaii were observed to have the poorest spatial coverage, using the dataset assembled for this study. Except in Hawaii, these areas also tended to have short streamflow records. Differences in hydrology lead to differences in the uncertainty of statistics calculated in different regions of the country. Arid and semiarid areas of the Central and Southwestern United States generally exhibited the highest levels of interannual variability in flow, leading to larger uncertainty in flow statistics. At ungaged locations, information can be transferred from nearby streamgages if there is sufficient similarity between the gaged watersheds and the ungaged watersheds of interest. Areas where streamgages exhibit high correlation are most likely to be suitable for this type of information transfer. The areas with the most highly correlated streamgages appear to coincide with mountainous areas of the United States. Lower correlations are found in the Central United States and coastal areas of the Southeastern United States. Information transfer from gaged basins to ungaged basins is also most likely to be successful when basin attributes show high similarity. At the scale of the analysis completed in this study, the attributes of basins upstream of USGS streamgages cover the full range of basin attributes observed at potential locations of interest fairly well. Some exceptions included very high or very low elevation areas and very arid areas.

Cross-correlations between crude oil and exchange markets for selected oil rich economies

NASA Astrophysics Data System (ADS)

Li, Jianfeng; Lu, Xinsheng; Zhou, Ying

2016-07-01

Using multifractal detrended cross-correlation analysis (MF-DCCA), this paper studies the cross-correlation behavior between crude oil market and five selected exchange rate markets. The dataset covers the period of January 1,1996-December 31,2014, and contains 4,633 observations for each of the series, including daily closing prices of crude oil, Australian Dollars, Canadian Dollars, Mexican Pesos, Russian Rubles, and South African Rand. Our empirical results obtained from cross-correlation statistic and cross-correlation coefficient have confirmed the existence of cross-correlations, and the MF-DCCA results have demonstrated a strong multifractality between cross-correlated crude oil market and exchange rate markets in both short term and long term. Using rolling window analysis, we have also found the persistent cross-correlations between the exchange rates and crude oil returns, and the cross-correlation scaling exponents exhibit volatility during some time periods due to its sensitivity to sudden events.

Identification of stress responsive genes by studying specific relationships between mRNA and protein abundance.

PubMed

Morimoto, Shimpei; Yahara, Koji

2018-03-01

Protein expression is regulated by the production and degradation of mRNAs and proteins but the specifics of their relationship are controversial. Although technological advances have enabled genome-wide and time-series surveys of mRNA and protein abundance, recent studies have shown paradoxical results, with most statistical analyses being limited to linear correlation, or analysis of variance applied separately to mRNA and protein datasets. Here, using recently analyzed genome-wide time-series data, we have developed a statistical analysis framework for identifying which types of genes or biological gene groups have significant correlation between mRNA and protein abundance after accounting for potential time delays. Our framework stratifies all genes in terms of the extent of time delay, conducts gene clustering in each stratum, and performs a non-parametric statistical test of the correlation between mRNA and protein abundance in a gene cluster. Consequently, we revealed stronger correlations than previously reported between mRNA and protein abundance in two metabolic pathways. Moreover, we identified a pair of stress responsive genes ( ADC17 and KIN1 ) that showed a highly similar time series of mRNA and protein abundance. Furthermore, we confirmed robustness of the analysis framework by applying it to another genome-wide time-series data and identifying a cytoskeleton-related gene cluster (keratin 18, keratin 17, and mitotic spindle positioning) that shows similar correlation. The significant correlation and highly similar changes of mRNA and protein abundance suggests a concerted role of these genes in cellular stress response, which we consider provides an answer to the question of the specific relationships between mRNA and protein in a cell. In addition, our framework for studying the relationship between mRNAs and proteins in a cell will provide a basis for studying specific relationships between mRNA and protein abundance after accounting for potential time delays.

A Guerilla Guide to Common Problems in ‘Neurostatistics’: Essential Statistical Topics in Neuroscience

PubMed Central

Smith, Paul F.

2017-01-01

Effective inferential statistical analysis is essential for high quality studies in neuroscience. However, recently, neuroscience has been criticised for the poor use of experimental design and statistical analysis. Many of the statistical issues confronting neuroscience are similar to other areas of biology; however, there are some that occur more regularly in neuroscience studies. This review attempts to provide a succinct overview of some of the major issues that arise commonly in the analyses of neuroscience data. These include: the non-normal distribution of the data; inequality of variance between groups; extensive correlation in data for repeated measurements across time or space; excessive multiple testing; inadequate statistical power due to small sample sizes; pseudo-replication; and an over-emphasis on binary conclusions about statistical significance as opposed to effect sizes. Statistical analysis should be viewed as just another neuroscience tool, which is critical to the final outcome of the study. Therefore, it needs to be done well and it is a good idea to be proactive and seek help early, preferably before the study even begins. PMID:29371855

A Guerilla Guide to Common Problems in 'Neurostatistics': Essential Statistical Topics in Neuroscience.

PubMed

Smith, Paul F

2017-01-01

Effective inferential statistical analysis is essential for high quality studies in neuroscience. However, recently, neuroscience has been criticised for the poor use of experimental design and statistical analysis. Many of the statistical issues confronting neuroscience are similar to other areas of biology; however, there are some that occur more regularly in neuroscience studies. This review attempts to provide a succinct overview of some of the major issues that arise commonly in the analyses of neuroscience data. These include: the non-normal distribution of the data; inequality of variance between groups; extensive correlation in data for repeated measurements across time or space; excessive multiple testing; inadequate statistical power due to small sample sizes; pseudo-replication; and an over-emphasis on binary conclusions about statistical significance as opposed to effect sizes. Statistical analysis should be viewed as just another neuroscience tool, which is critical to the final outcome of the study. Therefore, it needs to be done well and it is a good idea to be proactive and seek help early, preferably before the study even begins.

Correlating tephras and cryptotephras using glass compositional analyses and numerical and statistical methods: Review and evaluation

NASA Astrophysics Data System (ADS)

Lowe, David J.; Pearce, Nicholas J. G.; Jorgensen, Murray A.; Kuehn, Stephen C.; Tryon, Christian A.; Hayward, Chris L.

2017-11-01

We define tephras and cryptotephras and their components (mainly ash-sized particles of glass ± crystals in distal deposits) and summarize the basis of tephrochronology as a chronostratigraphic correlational and dating tool for palaeoenvironmental, geological, and archaeological research. We then document and appraise recent advances in analytical methods used to determine the major, minor, and trace elements of individual glass shards from tephra or cryptotephra deposits to aid their correlation and application. Protocols developed recently for the electron probe microanalysis of major elements in individual glass shards help to improve data quality and standardize reporting procedures. A narrow electron beam (diameter ∼3-5 μm) can now be used to analyze smaller glass shards than previously attainable. Reliable analyses of 'microshards' (defined here as glass shards <32 μm in diameter) using narrow beams are useful for fine-grained samples from distal or ultra-distal geographic locations, and for vesicular or microlite-rich glass shards or small melt inclusions. Caveats apply, however, in the microprobe analysis of very small microshards (≤∼5 μm in diameter), where particle geometry becomes important, and of microlite-rich glass shards where the potential problem of secondary fluorescence across phase boundaries needs to be recognised. Trace element analyses of individual glass shards using laser ablation inductively coupled plasma-mass spectrometry (LA-ICP-MS), with crater diameters of 20 μm and 10 μm, are now effectively routine, giving detection limits well below 1 ppm. Smaller ablation craters (<10 μm) can be subject to significant element fractionation during analysis, but the systematic relationship of such fractionation with glass composition suggests that analyses for some elements at these resolutions may be quantifiable. In undertaking analyses, either by microprobe or LA-ICP-MS, reference material data acquired using the same procedure, and preferably from the same analytical session, should be presented alongside new analytical data. In part 2 of the review, we describe, critically assess, and recommend ways in which tephras or cryptotephras can be correlated (in conjunction with other information) using numerical or statistical analyses of compositional data. Statistical methods provide a less subjective means of dealing with analytical data pertaining to tephra components (usually glass or crystals/phenocrysts) than heuristic alternatives. They enable a better understanding of relationships among the data from multiple viewpoints to be developed and help quantify the degree of uncertainty in establishing correlations. In common with other scientific hypothesis testing, it is easier to infer using such analysis that two or more tephras are different rather than the same. Adding stratigraphic, chronological, spatial, or palaeoenvironmental data (i.e. multiple criteria) is usually necessary and allows for more robust correlations to be made. A two-stage approach is useful, the first focussed on differences in the mean composition of samples, or their range, which can be visualised graphically via scatterplot matrices or bivariate plots coupled with the use of statistical tools such as distance measures, similarity coefficients, hierarchical cluster analysis (informed by distance measures or similarity or cophenetic coefficients), and principal components analysis (PCA). Some statistical methods (cluster analysis, discriminant analysis) are referred to as 'machine learning' in the computing literature. The second stage examines sample variance and the degree of compositional similarity so that sample equivalence or otherwise can be established on a statistical basis. This stage may involve discriminant function analysis (DFA), support vector machines (SVMs), canonical variates analysis (CVA), and ANOVA or MANOVA (or its two-sample special case, the Hotelling two-sample T2 test). Randomization tests can be used where distributional assumptions such as multivariate normality underlying parametric tests are doubtful. Compositional data may be transformed and scaled before being subjected to multivariate statistical procedures including calculation of distance matrices, hierarchical cluster analysis, and PCA. Such transformations may make the assumption of multivariate normality more appropriate. A sequential procedure using Mahalanobis distance and the Hotelling two-sample T2 test is illustrated using glass major element data from trachytic to phonolitic Kenyan tephras. All these methods require a broad range of high-quality compositional data which can be used to compare 'unknowns' with reference (training) sets that are sufficiently complete to account for all possible correlatives, including tephras with heterogeneous glasses that contain multiple compositional groups. Currently, incomplete databases are tending to limit correlation efficacy. The development of an open, online global database to facilitate progress towards integrated, high-quality tephrostratigraphic frameworks for different regions is encouraged.

Statistical properties of Galactic CMB foregrounds: dust and synchrotron

NASA Astrophysics Data System (ADS)

Kandel, D.; Lazarian, A.; Pogosyan, D.

2018-07-01

Recent Planck observations have revealed some of the important statistical properties of synchrotron and dust polarization, namely, the B to E mode power and temperature-E (TE) mode cross-correlation. In this paper, we extend our analysis in Kandel et al. that studied the B to E mode power ratio for polarized dust emission to include TE cross-correlation and develop an analogous formalism for synchrotron signal, all using a realistic model of magnetohydrodynamical turbulence. Our results suggest that the Planck results for both synchrotron and dust polarization can be understood if the turbulence in the Galaxy is sufficiently sub-Alfvénic. Making use of the observed poor magnetic field-density correlation, we show that the observed positive TE correlation for dust corresponds to our theoretical expectations. We also show how the B to E ratio as well as the TE cross-correlation can be used to study media magnetization, compressibility, and level of density-magnetic field correlation.

An exploration of counterfeit medicine surveillance strategies guided by geospatial analysis: lessons learned from counterfeit Avastin detection in the US drug supply chain.

PubMed

Cuomo, Raphael E; Mackey, Tim K

2014-12-02

To explore healthcare policy and system improvements that would more proactively respond to future penetration of counterfeit cancer medications in the USA drug supply chain using geospatial analysis. A statistical and geospatial analysis of areas that received notices from the Food and Drug Administration (FDA) about the possibility of counterfeit Avastin penetrating the US drug supply chain. Data from FDA warning notices were compared to data from 44 demographic variables available from the US Census Bureau via correlation, means testing and geospatial visualisation. Results were interpreted in light of existing literature in order to recommend improvements to surveillance of counterfeit medicines. This study analysed 791 distinct healthcare provider addresses that received FDA warning notices across 30,431 zip codes in the USA. Statistical outputs were Pearson's correlation coefficients and t values. Geospatial outputs were cartographic visualisations. These data were used to generate the overarching study outcome, which was a recommendation for a strategy for drug safety surveillance congruent with existing literature on counterfeit medication. Zip codes with greater numbers of individuals age 65+ and greater numbers of ethnic white individuals were most correlated with receipt of a counterfeit Avastin notice. Geospatial visualisations designed in conjunction with statistical analysis of demographic variables appeared more capable of suggesting areas and populations that may be at risk for undetected counterfeit Avastin penetration. This study suggests that dual incorporation of statistical and geospatial analysis in surveillance of counterfeit medicine may be helpful in guiding efforts to prevent, detect and visualise counterfeit medicines penetrations in the US drug supply chain and other settings. Importantly, the information generated by these analyses could be utilised to identify at-risk populations associated with demographic characteristics. Stakeholders should explore these results as another tool to improve on counterfeit medicine surveillance. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

A comparison of correlation-length estimation methods for the objective analysis of surface pollutants at Environment and Climate Change Canada.

PubMed

Ménard, Richard; Deshaies-Jacques, Martin; Gasset, Nicolas

2016-09-01

An objective analysis is one of the main components of data assimilation. By combining observations with the output of a predictive model we combine the best features of each source of information: the complete spatial and temporal coverage provided by models, with a close representation of the truth provided by observations. The process of combining observations with a model output is called an analysis. To produce an analysis requires the knowledge of observation and model errors, as well as its spatial correlation. This paper is devoted to the development of methods of estimation of these error variances and the characteristic length-scale of the model error correlation for its operational use in the Canadian objective analysis system. We first argue in favor of using compact support correlation functions, and then introduce three estimation methods: the Hollingsworth-Lönnberg (HL) method in local and global form, the maximum likelihood method (ML), and the [Formula: see text] diagnostic method. We perform one-dimensional (1D) simulation studies where the error variance and true correlation length are known, and perform an estimation of both error variances and correlation length where both are non-uniform. We show that a local version of the HL method can capture accurately the error variances and correlation length at each observation site, provided that spatial variability is not too strong. However, the operational objective analysis requires only a single and globally valid correlation length. We examine whether any statistics of the local HL correlation lengths could be a useful estimate, or whether other global estimation methods such as by the global HL, ML, or [Formula: see text] should be used. We found in both 1D simulation and using real data that the ML method is able to capture physically significant aspects of the correlation length, while most other estimates give unphysical and larger length-scale values. This paper describes a proposed improvement of the objective analysis of surface pollutants at Environment and Climate Change Canada (formerly known as Environment Canada). Objective analyses are essentially surface maps of air pollutants that are obtained by combining observations with an air quality model output, and are thought to provide a complete and more accurate representation of the air quality. The highlight of this study is an analysis of methods to estimate the model (or background) error correlation length-scale. The error statistics are an important and critical component to the analysis scheme.

Toward a perceptual image quality assessment of color quantized images

NASA Astrophysics Data System (ADS)

Frackiewicz, Mariusz; Palus, Henryk

2018-04-01

Color image quantization is an important operation in the field of color image processing. In this paper, we consider new perceptual image quality metrics for assessment of quantized images. These types of metrics, e.g. DSCSI, MDSIs, MDSIm and HPSI achieve the highest correlation coefficients with MOS during tests on the six publicly available image databases. Research was limited to images distorted by two types of compression: JPG and JPG2K. Statistical analysis of correlation coefficients based on the Friedman test and post-hoc procedures showed that the differences between the four new perceptual metrics are not statistically significant.

Nonlinear Analysis of Time Series in Genome-Wide Linkage Disequilibrium Data

NASA Astrophysics Data System (ADS)

Hernández-Lemus, Enrique; Estrada-Gil, Jesús K.; Silva-Zolezzi, Irma; Fernández-López, J. Carlos; Hidalgo-Miranda, Alfredo; Jiménez-Sánchez, Gerardo

2008-02-01

The statistical study of large scale genomic data has turned out to be a very important tool in population genetics. Quantitative methods are essential to understand and implement association studies in the biomedical and health sciences. Nevertheless, the characterization of recently admixed populations has been an elusive problem due to the presence of a number of complex phenomena. For example, linkage disequilibrium structures are thought to be more complex than their non-recently admixed population counterparts, presenting the so-called ancestry blocks, admixed regions that are not yet smoothed by the effect of genetic recombination. In order to distinguish characteristic features for various populations we have implemented several methods, some of them borrowed or adapted from the analysis of nonlinear time series in statistical physics and quantitative physiology. We calculate the main fractal dimensions (Kolmogorov's capacity, information dimension and correlation dimension, usually named, D0, D1 and D2). We also have made detrended fluctuation analysis and information based similarity index calculations for the probability distribution of correlations of linkage disequilibrium coefficient of six recently admixed (mestizo) populations within the Mexican Genome Diversity Project [1] and for the non-recently admixed populations in the International HapMap Project [2]. Nonlinear correlations showed up as a consequence of internal structure within the haplotype distributions. The analysis of these correlations as well as the scope and limitations of these procedures within the biomedical sciences are discussed.

New Statistics for Testing Differential Expression of Pathways from Microarray Data

NASA Astrophysics Data System (ADS)

Siu, Hoicheong; Dong, Hua; Jin, Li; Xiong, Momiao

Exploring biological meaning from microarray data is very important but remains a great challenge. Here, we developed three new statistics: linear combination test, quadratic test and de-correlation test to identify differentially expressed pathways from gene expression profile. We apply our statistics to two rheumatoid arthritis datasets. Notably, our results reveal three significant pathways and 275 genes in common in two datasets. The pathways we found are meaningful to uncover the disease mechanisms of rheumatoid arthritis, which implies that our statistics are a powerful tool in functional analysis of gene expression data.

Kernel canonical-correlation Granger causality for multiple time series

NASA Astrophysics Data System (ADS)

Wu, Guorong; Duan, Xujun; Liao, Wei; Gao, Qing; Chen, Huafu

2011-04-01

Canonical-correlation analysis as a multivariate statistical technique has been applied to multivariate Granger causality analysis to infer information flow in complex systems. It shows unique appeal and great superiority over the traditional vector autoregressive method, due to the simplified procedure that detects causal interaction between multiple time series, and the avoidance of potential model estimation problems. However, it is limited to the linear case. Here, we extend the framework of canonical correlation to include the estimation of multivariate nonlinear Granger causality for drawing inference about directed interaction. Its feasibility and effectiveness are verified on simulated data.

Micro-heterogeneity versus clustering in binary mixtures of ethanol with water or alkanes.

PubMed

Požar, Martina; Lovrinčević, Bernarda; Zoranić, Larisa; Primorać, Tomislav; Sokolić, Franjo; Perera, Aurélien

2016-08-24

Ethanol is a hydrogen bonding liquid. When mixed in small concentrations with water or alkanes, it forms aggregate structures reminiscent of, respectively, the direct and inverse micellar aggregates found in emulsions, albeit at much smaller sizes. At higher concentrations, micro-heterogeneous mixing with segregated domains is found. We examine how different statistical methods, namely correlation function analysis, structure factor analysis and cluster distribution analysis, can describe efficiently these morphological changes in these mixtures. In particular, we explain how the neat alcohol pre-peak of the structure factor evolves into the domain pre-peak under mixing conditions, and how this evolution differs whether the co-solvent is water or alkane. This study clearly establishes the heuristic superiority of the correlation function/structure factor analysis to study the micro-heterogeneity, since cluster distribution analysis is insensitive to domain segregation. Correlation functions detect the domains, with a clear structure factor pre-peak signature, while the cluster techniques detect the cluster hierarchy within domains. The main conclusion is that, in micro-segregated mixtures, the domain structure is a more fundamental statistical entity than the underlying cluster structures. These findings could help better understand comparatively the radiation scattering experiments, which are sensitive to domains, versus the spectroscopy-NMR experiments, which are sensitive to clusters.

Statistical characteristics of the sequential detection of signals in correlated noise

NASA Astrophysics Data System (ADS)

Averochkin, V. A.; Baranov, P. E.

1985-10-01

A solution is given to the problem of determining the distribution of the duration of the sequential two-threshold Wald rule for the time-discrete detection of determinate and Gaussian correlated signals on a background of Gaussian correlated noise. Expressions are obtained for the joint probability densities of the likelihood ratio logarithms, and an analysis is made of the effect of correlation and SNR on the duration distribution and the detection efficiency. Comparison is made with Neumann-Pearson detection.

Do scores on three commonly used measures of critical thinking correlate with academic success of health professions trainees? A systematic review and meta-analysis.

PubMed

Ross, David; Loeffler, Kim; Schipper, Shirley; Vandermeer, Ben; Allan, G Michael

2013-05-01

To determine whether the three commonly used measures of critical thinking correlate with academic success of medical professionals in training. The search for English-language articles (from 1980 to 2011) used Medline, Embase, Scopus, Cochrane Library on Ovid, Proquest Dissertations, Health and Psychosocial Instruments, PsychINFO, and references of included articles. Studies comparing critical thinking with academic success among medical professionals were included. Two authors performed study selection independently, with disagreement resolved by consensus. Two authors independently abstracted data on study characteristics, quality, and outcomes, with disagreement resolved by a third author. Critical thinking tests studied were the California Critical Thinking Skills Test (CCTST), California Critical Thinking Disposition Inventory (CCTDI), and Watson-Glaser Critical Thinking Appraisal. Correlation coefficients were pooled in meta-analysis. The search identified 557 studies: 52 met inclusion for systematic review, 41 of which were meta-analyzed. Critical thinking was positively correlated with academic success, r=0.31 (95% confidence intervals [CI] 0.26, 0.35), with a moderate statistical heterogeneity (I=67%). In subgroup analysis, only student type had statistical significance for correlation, although bias was likely due to low numbers for some student types. In direct comparison, using studies that employed two critical thinking tests, the CCTDI (r=0.23, 95% CI 0.15, 0.30) was significantly inferior (P<.001) to the CCTST (r=0.39, 95% CI 0.33, 0.45). Critical thinking was moderately correlated with academic success of medical professionals in training. The CCTDI was inferior to the CCTST in correlating with academic success.

Effect of the image resolution on the statistical descriptors of heterogeneous media.

PubMed

Ledesma-Alonso, René; Barbosa, Romeli; Ortegón, Jaime

2018-02-01

The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by scanning electron microscopy or other microscopy techniques. Among them, binarization and decimation are critical in order to compute the correlation functions that characterize the microstructure of the above-mentioned materials. In this study, we present a theoretical analysis of the effects of the image-size reduction, due to the progressive and sequential decimation of the original image. Three different decimation procedures (random, bilinear, and bicubic) were implemented and their consequences on the discrete correlation functions (two-point, line-path, and pore-size distribution) and the coarseness (derived from the local volume fraction) are reported and analyzed. The chosen statistical descriptors (correlation functions and coarseness) are typically employed to characterize and reconstruct heterogeneous materials. A normalization for each of the correlation functions has been performed. When the loss of statistical information has not been significant for a decimated image, its normalized correlation function is forecast by the trend of the original image (reference function). In contrast, when the decimated image does not hold statistical evidence of the original one, the normalized correlation function diverts from the reference function. Moreover, the equally weighted sum of the average of the squared difference, between the discrete correlation functions of the decimated images and the reference functions, leads to a definition of an overall error. During the first stages of the gradual decimation, the error remains relatively small and independent of the decimation procedure. Above a threshold defined by the correlation length of the reference function, the error becomes a function of the number of decimation steps. At this stage, some statistical information is lost and the error becomes dependent on the decimation procedure. These results may help us to restrict the amount of information that one can afford to lose during a decimation process, in order to reduce the computational and memory cost, when one aims to diminish the time consumed by a characterization or reconstruction technique, yet maintaining the statistical quality of the digitized sample.

Effect of the image resolution on the statistical descriptors of heterogeneous media

NASA Astrophysics Data System (ADS)

Ledesma-Alonso, René; Barbosa, Romeli; Ortegón, Jaime

2018-02-01

The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by scanning electron microscopy or other microscopy techniques. Among them, binarization and decimation are critical in order to compute the correlation functions that characterize the microstructure of the above-mentioned materials. In this study, we present a theoretical analysis of the effects of the image-size reduction, due to the progressive and sequential decimation of the original image. Three different decimation procedures (random, bilinear, and bicubic) were implemented and their consequences on the discrete correlation functions (two-point, line-path, and pore-size distribution) and the coarseness (derived from the local volume fraction) are reported and analyzed. The chosen statistical descriptors (correlation functions and coarseness) are typically employed to characterize and reconstruct heterogeneous materials. A normalization for each of the correlation functions has been performed. When the loss of statistical information has not been significant for a decimated image, its normalized correlation function is forecast by the trend of the original image (reference function). In contrast, when the decimated image does not hold statistical evidence of the original one, the normalized correlation function diverts from the reference function. Moreover, the equally weighted sum of the average of the squared difference, between the discrete correlation functions of the decimated images and the reference functions, leads to a definition of an overall error. During the first stages of the gradual decimation, the error remains relatively small and independent of the decimation procedure. Above a threshold defined by the correlation length of the reference function, the error becomes a function of the number of decimation steps. At this stage, some statistical information is lost and the error becomes dependent on the decimation procedure. These results may help us to restrict the amount of information that one can afford to lose during a decimation process, in order to reduce the computational and memory cost, when one aims to diminish the time consumed by a characterization or reconstruction technique, yet maintaining the statistical quality of the digitized sample.

To Identify the Important Soil Properties Affecting Dinoseb Adsorption with Statistical Analysis

PubMed Central

Guan, Yiqing; Wei, Jianhui; Zhang, Danrong; Zu, Mingjuan; Zhang, Liru

2013-01-01

Investigating the influences of soil characteristic factors on dinoseb adsorption parameter with different statistical methods would be valuable to explicitly figure out the extent of these influences. The correlation coefficients and the direct, indirect effects of soil characteristic factors on dinoseb adsorption parameter were analyzed through bivariate correlation analysis, and path analysis. With stepwise regression analysis the factors which had little influence on the adsorption parameter were excluded. Results indicate that pH and CEC had moderate relationship and lower direct effect on dinoseb adsorption parameter due to the multicollinearity with other soil factors, and organic carbon and clay contents were found to be the most significant soil factors which affect the dinoseb adsorption process. A regression is thereby set up to explore the relationship between the dinoseb adsorption parameter and the two soil factors: the soil organic carbon and clay contents. A 92% of the variation of dinoseb sorption coefficient could be attributed to the variation of the soil organic carbon and clay contents. PMID:23737715

Dynamic heterogeneity and non-Gaussian statistics for acetylcholine receptors on live cell membrane

NASA Astrophysics Data System (ADS)

He, W.; Song, H.; Su, Y.; Geng, L.; Ackerson, B. J.; Peng, H. B.; Tong, P.

2016-05-01

The Brownian motion of molecules at thermal equilibrium usually has a finite correlation time and will eventually be randomized after a long delay time, so that their displacement follows the Gaussian statistics. This is true even when the molecules have experienced a complex environment with a finite correlation time. Here, we report that the lateral motion of the acetylcholine receptors on live muscle cell membranes does not follow the Gaussian statistics for normal Brownian diffusion. From a careful analysis of a large volume of the protein trajectories obtained over a wide range of sampling rates and long durations, we find that the normalized histogram of the protein displacements shows an exponential tail, which is robust and universal for cells under different conditions. The experiment indicates that the observed non-Gaussian statistics and dynamic heterogeneity are inherently linked to the slow-active remodelling of the underlying cortical actin network.

Handling incomplete correlated continuous and binary outcomes in meta-analysis of individual participant data.

PubMed

Gomes, Manuel; Hatfield, Laura; Normand, Sharon-Lise

2016-09-20

Meta-analysis of individual participant data (IPD) is increasingly utilised to improve the estimation of treatment effects, particularly among different participant subgroups. An important concern in IPD meta-analysis relates to partially or completely missing outcomes for some studies, a problem exacerbated when interest is on multiple discrete and continuous outcomes. When leveraging information from incomplete correlated outcomes across studies, the fully observed outcomes may provide important information about the incompleteness of the other outcomes. In this paper, we compare two models for handling incomplete continuous and binary outcomes in IPD meta-analysis: a joint hierarchical model and a sequence of full conditional mixed models. We illustrate how these approaches incorporate the correlation across the multiple outcomes and the between-study heterogeneity when addressing the missing data. Simulations characterise the performance of the methods across a range of scenarios which differ according to the proportion and type of missingness, strength of correlation between outcomes and the number of studies. The joint model provided confidence interval coverage consistently closer to nominal levels and lower mean squared error compared with the fully conditional approach across the scenarios considered. Methods are illustrated in a meta-analysis of randomised controlled trials comparing the effectiveness of implantable cardioverter-defibrillator devices alone to implantable cardioverter-defibrillator combined with cardiac resynchronisation therapy for treating patients with chronic heart failure. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Changes in patellofemoral alignment do not cause clinical impact after open-wedge high tibial osteotomy.

PubMed

Lee, Yong Seuk; Lee, Sang Bok; Oh, Won Seok; Kwon, Yong Eok; Lee, Beom Koo

2016-01-01

The objectives of this study were (1) to evaluate the clinical and radiologic outcomes of open-wedge high tibial osteotomy focusing on patellofemoral alignment and (2) to search for correlation between variables and patellofemoral malalignment. A total of 46 knees (46 patients) from 32 females and 14 males who underwent open-wedge high tibial osteotomy were included in this retrospective case series. Outcomes were evaluated using clinical scales and radiologic parameters at the last follow-up. Pre-operative and final follow-up values were compared for the outcome analysis. For the focused analysis of the patellofemoral joint, correlation analyses between patellofemoral variables and pre- and post-operative weight-bearing line (WBL), clinical score, posterior slope, Blackburn Peel ratio, lateral patellar tilt, lateral patellar shift, and congruence angle were performed. The minimum follow-up period was 2 years and median follow-up period was 44 months (range 24-88 months). The percentage of weight-bearing line was shifted from 17.2 ± 11.1 to 56.7 ± 12.7%, and it was statistically significant (p < 0.01). Regarding the clinical results, statistical significance was observed using all scores (p < 0.01). In the radiologic evaluation, patellar descent was observed with statistical significance (p < 0.01). Last follow-up lateral patellar tilt was decreased with statistical significance (p < 0.01). In correlation analysis between variables of patellofemoral malalignment, the pre-operative weight-bearing line showed an association with the change in lateral patellar tilt and lateral patellar shift (correlation coefficient: 0.3). After open-wedge high tibial osteotomy, clinical results showed improvement, compared to pre-operative values. The patellar tilt and lateral patellar shift were not changed; however, descent of the patella was observed. Therefore, mild patellofemoral problems should not be a contraindication of the open-wedge high tibial osteotomy. Case series, Level IV.

Digital Correlation Microwave Polarimetry: Analysis and Demonstration

NASA Technical Reports Server (NTRS)

Piepmeier, J. R.; Gasiewski, A. J.; Krebs, Carolyn A. (Technical Monitor)

2000-01-01

The design, analysis, and demonstration of a digital-correlation microwave polarimeter for use in earth remote sensing is presented. We begin with an analysis of three-level digital correlation and develop the correlator transfer function and radiometric sensitivity. A fifth-order polynomial regression is derived for inverting the digital correlation coefficient into the analog statistic. In addition, the effects of quantizer threshold asymmetry and hysteresis are discussed. A two-look unpolarized calibration scheme is developed for identifying correlation offsets. The developed theory and calibration method are verified using a 10.7 GHz and a 37.0 GHz polarimeter. The polarimeters are based upon 1-GS/s three-level digital correlators and measure the first three Stokes parameters. Through experiment, the radiometric sensitivity is shown to approach the theoretical as derived earlier in the paper and the two-look unpolarized calibration method is successfully compared with results using a polarimetric scheme. Finally, sample data from an aircraft experiment demonstrates that the polarimeter is highly-useful for ocean wind-vector measurement.

Data analytics using canonical correlation analysis and Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Rickman, Jeffrey M.; Wang, Yan; Rollett, Anthony D.; Harmer, Martin P.; Compson, Charles

2017-07-01

A canonical correlation analysis is a generic parametric model used in the statistical analysis of data involving interrelated or interdependent input and output variables. It is especially useful in data analytics as a dimensional reduction strategy that simplifies a complex, multidimensional parameter space by identifying a relatively few combinations of variables that are maximally correlated. One shortcoming of the canonical correlation analysis, however, is that it provides only a linear combination of variables that maximizes these correlations. With this in mind, we describe here a versatile, Monte-Carlo based methodology that is useful in identifying non-linear functions of the variables that lead to strong input/output correlations. We demonstrate that our approach leads to a substantial enhancement of correlations, as illustrated by two experimental applications of substantial interest to the materials science community, namely: (1) determining the interdependence of processing and microstructural variables associated with doped polycrystalline aluminas, and (2) relating microstructural decriptors to the electrical and optoelectronic properties of thin-film solar cells based on CuInSe2 absorbers. Finally, we describe how this approach facilitates experimental planning and process control.

Correlation between X-ray flux and rotational acceleration in Vela X-1

NASA Technical Reports Server (NTRS)

Deeter, J. E.; Boynton, P. E.; Shibazaki, N.; Hayakawa, S.; Nagase, F.

1989-01-01

The results of a search for correlations between X-ray flux and angular acceleration for the accreting binary pulsar Vela X-1 are presented. Results are based on data obtained with the Hakucho satellite during the interval 1982 to 1984. In undertaking this correlation analysis, it was necessary to modify the usual statistical method to deal with conditions imposed by generally unavoidable satellite observing constraints, most notably a mismatch in sampling between the two variables. The results are suggestive of a correlation between flux and the absolute value of the angular acceleration, at a significance level of 96 percent. The implications of the methods and results for future observations and analysis are discussed.

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

ERIC Educational Resources Information Center

Konold, Timothy R.; Glutting, Joseph J.

2008-01-01

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

Health inequality in Slovenia.

PubMed

Artnik, B; Premik, M

2001-01-01

The aim of this study was to correlate some socio-economic factors (gender, income, education, social position) with some health indicators (life expectancy, death rate by selected causes of death, self-evaluation of one's own health, absence from work due to illness or injuries) with a purpose to define the ineqaulity in health across Slovenian municipalities. In our study two sources of data for the population of Slovenia in 1996 were used: from the Statistical Office of the Republic of Slovenia (aggregated data across Slovenian municipalities) and Public Opinion Research (individual data). Statistical analysis was performed by correlation and factor analysis. The correlation coefficient between education and life expectancy is 0.712. The correlation between income base and life expectancy is also significant (0.707). In the eastern part of the country (mostly rural population) women in average live 2 years and men 3 years less than their counterparts in the western part of the country. Five causes of death across Slovenian municipalities are significantly related to the population's education and incomes, of which only death due to neoplasm is positively correlated to income while all other causes are negatively correlated not only with income but also with education. Health (self-evaluation) is closely related to an individual's education and social position. The factor analysis of pressures at work showed groups of two factors as being the most significant: pressures related to leadership positions (positive correlation with health), and physical labour or work in inferior positions (negative correlation with health). We can conclude that the results of our study showed the crucial effect of investigated socio-economic factors on people's health across Slovenian municipalities. During the present socio-economic transition period we are trying to establish new sources of data and looking for possibilities to connect and refine them for further investigation.

Feature-Based Statistical Analysis of Combustion Simulation Data

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

Bennett, J; Krishnamoorthy, V; Liu, S

2011-11-18

We present a new framework for feature-based statistical analysis of large-scale scientific data and demonstrate its effectiveness by analyzing features from Direct Numerical Simulations (DNS) of turbulent combustion. Turbulent flows are ubiquitous and account for transport and mixing processes in combustion, astrophysics, fusion, and climate modeling among other disciplines. They are also characterized by coherent structure or organized motion, i.e. nonlocal entities whose geometrical features can directly impact molecular mixing and reactive processes. While traditional multi-point statistics provide correlative information, they lack nonlocal structural information, and hence, fail to provide mechanistic causality information between organized fluid motion and mixing andmore » reactive processes. Hence, it is of great interest to capture and track flow features and their statistics together with their correlation with relevant scalar quantities, e.g. temperature or species concentrations. In our approach we encode the set of all possible flow features by pre-computing merge trees augmented with attributes, such as statistical moments of various scalar fields, e.g. temperature, as well as length-scales computed via spectral analysis. The computation is performed in an efficient streaming manner in a pre-processing step and results in a collection of meta-data that is orders of magnitude smaller than the original simulation data. This meta-data is sufficient to support a fully flexible and interactive analysis of the features, allowing for arbitrary thresholds, providing per-feature statistics, and creating various global diagnostics such as Cumulative Density Functions (CDFs), histograms, or time-series. We combine the analysis with a rendering of the features in a linked-view browser that enables scientists to interactively explore, visualize, and analyze the equivalent of one terabyte of simulation data. We highlight the utility of this new framework for combustion science; however, it is applicable to many other science domains.« less

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

The Correlation between Insertion Depth of Prodisc-C Artificial Disc and Postoperative Kyphotic Deformity: Clinical Importance of Insertion Depth of Artificial Disc.

PubMed

Lee, Do-Youl; Kim, Se-Hoon; Suh, Jung-Keun; Cho, Tai-Hyoung; Chung, Yong-Gu

2012-09-01

This study was designed to investigate the correlation between insertion depth of artificial disc and postoperative kyphotic deformity after Prodisc-C total disc replacement surgery, and the range of artificial disc insertion depth which is effective in preventing postoperative whole cervical or segmental kyphotic deformity. A retrospective radiological analysis was performed in 50 patients who had undergone single level total disc replacement surgery. Records were reviewed to obtain demographic data. Preoperative and postoperative radiographs were assessed to determine C2-7 Cobb's angle and segmental angle and to investigate postoperative kyphotic deformity. A formula was introduced to calculate insertion depth of Prodisc-C artificial disc. Statistical analysis was performed to search the correlation between insertion depth of Prodisc-C artificial disc and postoperative kyphotic deformity, and to estimate insertion depth of Prodisc-C artificial disc to prevent postoperative kyphotic deformity. In this study no significant statistical correlation was observed between insertion depth of Prodisc-C artificial disc and postoperative kyphotic deformity regarding C2-7 Cobb's angle. Statistical correlation between insertion depth of Prodisc-C artificial disc and postoperative kyphotic deformity was observed regarding segmental angle (p<0.05). It failed to estimate proper insertion depth of Prodisc-C artificial disc effective in preventing postoperative kyphotic deformity. Postoperative segmental kyphotic deformity is associated with insertion depth of Prodisc-C artificial disc. Anterior located artificial disc leads to lordotic segmental angle and posterior located artificial disc leads to kyphotic segmental angle postoperatively. But C2-7 Cobb's angle is not affected by artificial disc location after the surgery.

The use of copula functions for predictive analysis of correlations between extreme storm tides

NASA Astrophysics Data System (ADS)

Domino, Krzysztof; Błachowicz, Tomasz; Ciupak, Maurycy

2014-11-01

In this paper we present a method used in quantitative description of weakly predictable hydrological, extreme events at inland sea. Investigations for correlations between variations of individual measuring points, employing combined statistical methods, were carried out. As a main tool for this analysis we used a two-dimensional copula function sensitive for correlated extreme effects. Additionally, a new proposed methodology, based on Detrended Fluctuations Analysis (DFA) and Anomalous Diffusion (AD), was used for the prediction of negative and positive auto-correlations and associated optimum choice of copula functions. As a practical example we analysed maximum storm tides data recorded at five spatially separated places at the Baltic Sea. For the analysis we used Gumbel, Clayton, and Frank copula functions and introduced the reversed Clayton copula. The application of our research model is associated with modelling the risk of high storm tides and possible storm flooding.

Combined magnetic and gravity analysis

NASA Technical Reports Server (NTRS)

Hinze, W. J.; Braile, L. W.; Chandler, V. W.; Mazella, F. E.

1975-01-01

Efforts are made to identify methods of decreasing magnetic interpretation ambiguity by combined gravity and magnetic analysis, to evaluate these techniques in a preliminary manner, to consider the geologic and geophysical implications of correlation, and to recommend a course of action to evaluate methods of correlating gravity and magnetic anomalies. The major thrust of the study was a search and review of the literature. The literature of geophysics, geology, geography, and statistics was searched for articles dealing with spatial correlation of independent variables. An annotated bibliography referencing the Germane articles and books is presented. The methods of combined gravity and magnetic analysis techniques are identified and reviewed. A more comprehensive evaluation of two types of techniques is presented. Internal correspondence of anomaly amplitudes is examined and a combined analysis is done utilizing Poisson's theorem. The geologic and geophysical implications of gravity and magnetic correlation based on both theoretical and empirical relationships are discussed.

General Nature of Multicollinearity in Multiple Regression Analysis.

ERIC Educational Resources Information Center

Liu, Richard

1981-01-01

Discusses multiple regression, a very popular statistical technique in the field of education. One of the basic assumptions in regression analysis requires that independent variables in the equation should not be highly correlated. The problem of multicollinearity and some of the solutions to it are discussed. (Author)

Geochemical prospecting for Cu mineralization in an arid terrain-central Iran

NASA Astrophysics Data System (ADS)

Mokhtari, Ahmad Reza; Roshani Rodsari, Parisa; Fatehi, Moslem; Shahrestani, Shahed; Pournik, Peyman

2014-12-01

Geochemical sampling and data processing were implemented for prospecting Cu mineralization through catchment basin approach in central Iran, Yazd province, over drainage systems in order to determine areas of interest for the detailed exploration program. The target zone, inside an area called Kalout-e-Ashrafa in Yazd province-Iran, was characterized by the collection of 107 stream sediment samples. Catchment basin modeling was conducted based on digital elevation model (DEM) and geological map of the study area. Samples were studied by univariate and multivariate statistical techniques of exploratory data analysis, classical statistical analysis and cluster analysis. The results showed that only Cu had anomalous behavior and it did not exhibit a considerable correlation with other elements. Geochemical maps were prepared for Cu and anomalous zones and separated for potential copper mineralization. It was concluded that due to especial geomorphological and geographical characteristics (smooth topography, negligible annual precipitation and insufficient thickness of silicified Cu-bearing outcrops of the area), low concentrations of Cu would be expected for the delineation of promising zones in similar trains. Using cluster analysis showed that there was a strong correlation between Ag, Sr and S. Calcium and Pb present moderate correlation with Cu. Additionally, there was a strong correlation between Zn and Li, thereby indicating a meaningful correlation with Fe, P, Ti and Mg. Aluminum, Sc and V had a correlation with Be and K. Applying threshold value according to MAD (median absolute deviation) helped us to distinguish anomalous catchments more properly. Finally, there was a significant kind of conformity among anomalous catchment basins and silicified veins and veinlets (as validating index) at the central part of the area.

New insights into time series analysis. II - Non-correlated observations

NASA Astrophysics Data System (ADS)

Ferreira Lopes, C. E.; Cross, N. J. G.

2017-08-01

Context. Statistical parameters are used to draw conclusions in a vast number of fields such as finance, weather, industrial, and science. These parameters are also used to identify variability patterns on photometric data to select non-stochastic variations that are indicative of astrophysical effects. New, more efficient, selection methods are mandatory to analyze the huge amount of astronomical data. Aims: We seek to improve the current methods used to select non-stochastic variations on non-correlated data. Methods: We used standard and new data-mining parameters to analyze non-correlated data to find the best way to discriminate between stochastic and non-stochastic variations. A new approach that includes a modified Strateva function was performed to select non-stochastic variations. Monte Carlo simulations and public time-domain data were used to estimate its accuracy and performance. Results: We introduce 16 modified statistical parameters covering different features of statistical distribution such as average, dispersion, and shape parameters. Many dispersion and shape parameters are unbound parameters, I.e. equations that do not require the calculation of average. Unbound parameters are computed with single loop and hence decreasing running time. Moreover, the majority of these parameters have lower errors than previous parameters, which is mainly observed for distributions with few measurements. A set of non-correlated variability indices, sample size corrections, and a new noise model along with tests of different apertures and cut-offs on the data (BAS approach) are introduced. The number of mis-selections are reduced by about 520% using a single waveband and 1200% combining all wavebands. On the other hand, the even-mean also improves the correlated indices introduced in Paper I. The mis-selection rate is reduced by about 18% if the even-mean is used instead of the mean to compute the correlated indices in the WFCAM database. Even-statistics allows us to improve the effectiveness of both correlated and non-correlated indices. Conclusions: The selection of non-stochastic variations is improved by non-correlated indices. The even-averages provide a better estimation of mean and median for almost all statistical distributions analyzed. The correlated variability indices, which are proposed in the first paper of this series, are also improved if the even-mean is used. The even-parameters will also be useful for classifying light curves in the last step of this project. We consider that the first step of this project, where we set new techniques and methods that provide a huge improvement on the efficiency of selection of variable stars, is now complete. Many of these techniques may be useful for a large number of fields. Next, we will commence a new step of this project regarding the analysis of period search methods.

Testing alternative ground water models using cross-validation and other methods

USGS Publications Warehouse

Foglia, L.; Mehl, S.W.; Hill, M.C.; Perona, P.; Burlando, P.

2007-01-01

Many methods can be used to test alternative ground water models. Of concern in this work are methods able to (1) rank alternative models (also called model discrimination) and (2) identify observations important to parameter estimates and predictions (equivalent to the purpose served by some types of sensitivity analysis). Some of the measures investigated are computationally efficient; others are computationally demanding. The latter are generally needed to account for model nonlinearity. The efficient model discrimination methods investigated include the information criteria: the corrected Akaike information criterion, Bayesian information criterion, and generalized cross-validation. The efficient sensitivity analysis measures used are dimensionless scaled sensitivity (DSS), composite scaled sensitivity, and parameter correlation coefficient (PCC); the other statistics are DFBETAS, Cook's D, and observation-prediction statistic. Acronyms are explained in the introduction. Cross-validation (CV) is a computationally intensive nonlinear method that is used for both model discrimination and sensitivity analysis. The methods are tested using up to five alternative parsimoniously constructed models of the ground water system of the Maggia Valley in southern Switzerland. The alternative models differ in their representation of hydraulic conductivity. A new method for graphically representing CV and sensitivity analysis results for complex models is presented and used to evaluate the utility of the efficient statistics. The results indicate that for model selection, the information criteria produce similar results at much smaller computational cost than CV. For identifying important observations, the only obviously inferior linear measure is DSS; the poor performance was expected because DSS does not include the effects of parameter correlation and PCC reveals large parameter correlations. ?? 2007 National Ground Water Association.

A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis.

PubMed

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρDXA, contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

Whole-brain diffusion tensor imaging in correlation to visual-evoked potentials in multiple sclerosis: a tract-based spatial statistics analysis.

PubMed

Lobsien, D; Ettrich, B; Sotiriou, K; Classen, J; Then Bergh, F; Hoffmann, K-T

2014-01-01

Functional correlates of microstructural damage of the brain affected by MS are incompletely understood. The purpose of this study was to evaluate correlations of visual-evoked potentials with microstructural brain changes as determined by DTI in patients with demyelinating central nervous disease. Sixty-one patients with clinically isolated syndrome or MS were prospectively recruited. The mean P100 visual-evoked potential latencies of the right and left eyes of each patient were calculated and used for the analysis. For DTI acquisition, a single-shot echo-planar imaging pulse sequence with 80 diffusion directions was performed at 3T. Fractional anisotropy, radial diffusivity, and axial diffusivity were calculated and correlated with mean P100 visual-evoked potentials by tract-based spatial statistics. Significant negative correlations between mean P100 visual-evoked potentials and fractional anisotropy and significant positive correlations between mean P100 visual-evoked potentials and radial diffusivity were found widespread over the whole brain. The highest significance was found in the optic radiation, frontoparietal white matter, and corpus callosum. Significant positive correlations between mean P100 visual-evoked potentials and axial diffusivity were less widespread, notably sparing the optic radiation. Microstructural changes of the whole brain correlated significantly with mean P100 visual-evoked potentials. The distribution of the correlations showed clear differences among axial diffusivity, fractional anisotropy, and radial diffusivity, notably in the optic radiation. This finding suggests a stronger correlation of mean P100 visual-evoked potentials to demyelination than to axonal damage. © 2014 by American Journal of Neuroradiology.

Statistical analysis of major ion and trace element geochemistry of water, 1986-2006, at seven wells transecting the freshwater/saline-water interface of the Edwards Aquifer, San Antonio, Texas

USGS Publications Warehouse

Mahler, Barbara J.

2008-01-01

The statistical analyses taken together indicate that the geochemistry at the freshwater-zone wells is more variable than that at the transition-zone wells. The geochemical variability at the freshwater-zone wells might result from dilution of ground water by meteoric water. This is indicated by relatively constant major ion molar ratios; a preponderance of positive correlations between SC, major ions, and trace elements; and a principal components analysis in which the major ions are strongly loaded on the first principal component. Much of the variability at three of the four transition-zone wells might result from the use of different laboratory analytical methods or reporting procedures during the period of sampling. This is reflected by a lack of correlation between SC and major ion concentrations at the transition-zone wells and by a principal components analysis in which the variability is fairly evenly distributed across several principal components. The statistical analyses further indicate that, although the transition-zone wells are less well connected to surficial hydrologic conditions than the freshwater-zone wells, there is some connection but the response time is longer. 

Systematic Review and Meta-Analysis of Studies Evaluating Diagnostic Test Accuracy: A Practical Review for Clinical Researchers-Part II. Statistical Methods of Meta-Analysis

PubMed Central

Lee, Juneyoung; Kim, Kyung Won; Choi, Sang Hyun; Huh, Jimi

2015-01-01

Meta-analysis of diagnostic test accuracy studies differs from the usual meta-analysis of therapeutic/interventional studies in that, it is required to simultaneously analyze a pair of two outcome measures such as sensitivity and specificity, instead of a single outcome. Since sensitivity and specificity are generally inversely correlated and could be affected by a threshold effect, more sophisticated statistical methods are required for the meta-analysis of diagnostic test accuracy. Hierarchical models including the bivariate model and the hierarchical summary receiver operating characteristic model are increasingly being accepted as standard methods for meta-analysis of diagnostic test accuracy studies. We provide a conceptual review of statistical methods currently used and recommended for meta-analysis of diagnostic test accuracy studies. This article could serve as a methodological reference for those who perform systematic review and meta-analysis of diagnostic test accuracy studies. PMID:26576107

The neuronal correlates of intranasal trigeminal function – An ALE meta-analysis of human functional brain imaging data

PubMed Central

Albrecht, Jessica; Kopietz, Rainer; Frasnelli, Johannes; Wiesmann, Martin; Hummel, Thomas; Lundström, Johan N.

2009-01-01

Almost every odor we encounter in daily life has the capacity to produce a trigeminal sensation. Surprisingly, few functional imaging studies exploring human neuronal correlates of intranasal trigeminal function exist, and results are to some degree inconsistent. We utilized activation likelihood estimation (ALE), a quantitative voxel-based meta-analysis tool, to analyze functional imaging data (fMRI/PET) following intranasal trigeminal stimulation with carbon dioxide (CO2), a stimulus known to exclusively activate the trigeminal system. Meta-analysis tools are able to identify activations common across studies, thereby enabling activation mapping with higher certainty. Activation foci of nine studies utilizing trigeminal stimulation were included in the meta-analysis. We found significant ALE scores, thus indicating consistent activation across studies, in the brainstem, ventrolateral posterior thalamic nucleus, anterior cingulate cortex, insula, precentral gyrus, as well as in primary and secondary somatosensory cortices – a network known for the processing of intranasal nociceptive stimuli. Significant ALE values were also observed in the piriform cortex, insula, and the orbitofrontal cortex, areas known to process chemosensory stimuli, and in association cortices. Additionally, the trigeminal ALE statistics were directly compared with ALE statistics originating from olfactory stimulation, demonstrating considerable overlap in activation. In conclusion, the results of this meta-analysis map the human neuronal correlates of intranasal trigeminal stimulation with high statistical certainty and demonstrate that the cortical areas recruited during the processing of intranasal CO2 stimuli include those outside traditional trigeminal areas. Moreover, through illustrations of the considerable overlap between brain areas that process trigeminal and olfactory information; these results demonstrate the interconnectivity of flavor processing. PMID:19913573

Selected papers in the hydrologic sciences, 1986

USGS Publications Warehouse

Subitzky, Seymour

1987-01-01

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

Acoustic correlates of Japanese expressions associated with voice quality of male adults

NASA Astrophysics Data System (ADS)

Kido, Hiroshi; Kasuya, Hideki

2004-05-01

Japanese expressions associated with the voice quality of male adults were extracted by a series of questionnaire surveys and statistical multivariate analysis. One hundred and thirty-seven Japanese expressions were collected through the first questionnaire and careful investigations of well-established Japanese dictionaries and articles. From the second questionnaire about familiarity with each of the expressions and synonymity that were addressed to 249 subjects, 25 expressions were extracted. The third questionnaire was about an evaluation of their own voice quality. By applying a statistical clustering method and a correlation analysis to the results of the questionnaires, eight bipolar expressions and one unipolar expression were obtained. They constituted high-pitched/low-pitched, masculine/feminine, hoarse/clear, calm/excited, powerful/weak, youthful/elderly, thick/thin, tense/lax, and nasal, respectively. Acoustic correlates of each of the eight bipolar expressions were extracted by means of perceptual evaluation experiments that were made with sentence utterances of 36 males and by a statistical decision tree method. They included an average of the fundamental frequency (F0) of the utterance, speaking rate, spectral tilt, formant frequency parameter, standard deviation of F0 values, and glottal noise, when SPL of each of the stimuli was maintained identical in the perceptual experiments.

Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis.

PubMed

Buldyrev, S V; Goldberger, A L; Havlin, S; Mantegna, R N; Matsa, M E; Peng, C K; Simons, M; Stanley, H E

1995-05-01

An open question in computational molecular biology is whether long-range correlations are present in both coding and noncoding DNA or only in the latter. To answer this question, we consider all 33301 coding and all 29453 noncoding eukaryotic sequences--each of length larger than 512 base pairs (bp)--in the present release of the GenBank to dtermine whether there is any statistically significant distinction in their long-range correlation properties. Standard fast Fourier transform (FFT) analysis indicates that coding sequences have practically no correlations in the range from 10 bp to 100 bp (spectral exponent beta=0.00 +/- 0.04, where the uncertainty is two standard deviations). In contrast, for noncoding sequences, the average value of the spectral exponent beta is positive (0.16 +/- 0.05) which unambiguously shows the presence of long-range correlations. We also separately analyze the 874 coding and the 1157 noncoding sequences that have more than 4096 bp and find a larger region of power-law behavior. We calculate the probability that these two data sets (coding and noncoding) were drawn from the same distribution and we find that it is less than 10(-10). We obtain independent confirmation of these findings using the method of detrended fluctuation analysis (DFA), which is designed to treat sequences with statistical heterogeneity, such as DNA's known mosaic structure ("patchiness") arising from the nonstationarity of nucleotide concentration. The near-perfect agreement between the two independent analysis methods, FFT and DFA, increases the confidence in the reliability of our conclusion.

Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis

NASA Technical Reports Server (NTRS)

Buldyrev, S. V.; Goldberger, A. L.; Havlin, S.; Mantegna, R. N.; Matsa, M. E.; Peng, C. K.; Simons, M.; Stanley, H. E.

1995-01-01

An open question in computational molecular biology is whether long-range correlations are present in both coding and noncoding DNA or only in the latter. To answer this question, we consider all 33301 coding and all 29453 noncoding eukaryotic sequences--each of length larger than 512 base pairs (bp)--in the present release of the GenBank to dtermine whether there is any statistically significant distinction in their long-range correlation properties. Standard fast Fourier transform (FFT) analysis indicates that coding sequences have practically no correlations in the range from 10 bp to 100 bp (spectral exponent beta=0.00 +/- 0.04, where the uncertainty is two standard deviations). In contrast, for noncoding sequences, the average value of the spectral exponent beta is positive (0.16 +/- 0.05) which unambiguously shows the presence of long-range correlations. We also separately analyze the 874 coding and the 1157 noncoding sequences that have more than 4096 bp and find a larger region of power-law behavior. We calculate the probability that these two data sets (coding and noncoding) were drawn from the same distribution and we find that it is less than 10(-10). We obtain independent confirmation of these findings using the method of detrended fluctuation analysis (DFA), which is designed to treat sequences with statistical heterogeneity, such as DNA's known mosaic structure ("patchiness") arising from the nonstationarity of nucleotide concentration. The near-perfect agreement between the two independent analysis methods, FFT and DFA, increases the confidence in the reliability of our conclusion.

[A Review on the Use of Effect Size in Nursing Research].

PubMed

Kang, Hyuncheol; Yeon, Kyupil; Han, Sang Tae

2015-10-01

The purpose of this study was to introduce the main concepts of statistical testing and effect size and to provide researchers in nursing science with guidance on how to calculate the effect size for the statistical analysis methods mainly used in nursing. For t-test, analysis of variance, correlation analysis, regression analysis which are used frequently in nursing research, the generally accepted definitions of the effect size were explained. Some formulae for calculating the effect size are described with several examples in nursing research. Furthermore, the authors present the required minimum sample size for each example utilizing G*Power 3 software that is the most widely used program for calculating sample size. It is noted that statistical significance testing and effect size measurement serve different purposes, and the reliance on only one side may be misleading. Some practical guidelines are recommended for combining statistical significance testing and effect size measure in order to make more balanced decisions in quantitative analyses.

On an additive partial correlation operator and nonparametric estimation of graphical models.

PubMed

Lee, Kuang-Yao; Li, Bing; Zhao, Hongyu

2016-09-01

We introduce an additive partial correlation operator as an extension of partial correlation to the nonlinear setting, and use it to develop a new estimator for nonparametric graphical models. Our graphical models are based on additive conditional independence, a statistical relation that captures the spirit of conditional independence without having to resort to high-dimensional kernels for its estimation. The additive partial correlation operator completely characterizes additive conditional independence, and has the additional advantage of putting marginal variation on appropriate scales when evaluating interdependence, which leads to more accurate statistical inference. We establish the consistency of the proposed estimator. Through simulation experiments and analysis of the DREAM4 Challenge dataset, we demonstrate that our method performs better than existing methods in cases where the Gaussian or copula Gaussian assumption does not hold, and that a more appropriate scaling for our method further enhances its performance.

On an additive partial correlation operator and nonparametric estimation of graphical models

PubMed Central

Li, Bing; Zhao, Hongyu

2016-01-01

Abstract We introduce an additive partial correlation operator as an extension of partial correlation to the nonlinear setting, and use it to develop a new estimator for nonparametric graphical models. Our graphical models are based on additive conditional independence, a statistical relation that captures the spirit of conditional independence without having to resort to high-dimensional kernels for its estimation. The additive partial correlation operator completely characterizes additive conditional independence, and has the additional advantage of putting marginal variation on appropriate scales when evaluating interdependence, which leads to more accurate statistical inference. We establish the consistency of the proposed estimator. Through simulation experiments and analysis of the DREAM4 Challenge dataset, we demonstrate that our method performs better than existing methods in cases where the Gaussian or copula Gaussian assumption does not hold, and that a more appropriate scaling for our method further enhances its performance. PMID:29422689

Predicting Success in Psychological Statistics Courses.

PubMed

Lester, David

2016-06-01

Many students perform poorly in courses on psychological statistics, and it is useful to be able to predict which students will have difficulties. In a study of 93 undergraduates enrolled in Statistical Methods (18 men, 75 women; M age = 22.0 years, SD = 5.1), performance was significantly associated with sex (female students performed better) and proficiency in algebra in a linear regression analysis. Anxiety about statistics was not associated with course performance, indicating that basic mathematical skills are the best correlate for performance in statistics courses and can usefully be used to stream students into classes by ability. © The Author(s) 2016.

Morphological texture assessment of oral bone as a screening tool for osteoporosis

NASA Astrophysics Data System (ADS)

Analoui, Mostafa; Eggertsson, Hafsteinn; Eckert, George

2001-07-01

Three classes of texture analysis approaches have been employed to assess the textural characteristic of oral bone. A set of linear structuring elements was used to compute granulometric features of trabecular bone. Multifractal analysis was also used to compute the fractal dimension of the corresponding tissues. In addition, some statistical features and histomorphometric parameters were computed. To assess the proposed approach we acquired digital intraoral radiographs of 47 subjects (14 males and 33 females). All radiographs were captured at 12 bits/pixel. Images were converted to binary form through a sliding locally adaptive thresholding approach. Each subject was scanned by DEXA for bone dosimetry. Subject were classified into one of the following three categories according World Health Organization (WHO) standard (1) healthy, (2) with osteopenia and (3) osteoporosis. In this study fractal dimension showed very low correlation with bone mineral density (BMD) measurements, which did not reach a level of statistical significance (p<0.5). However, entropy of pattern spectrum (EPS), along with statistical features and histomorphometric parameters, has shown correlation coefficients ranging from low to high, with statistical significance for both males and females. The results of this study indicate the utility of this approach for bone texture analysis. It is conjectured that designing a 2-D structuring element, specially tuned to trabecular bone texture, will increase the efficacy of the proposed method.

The GEOS Ozone Data Assimilation System: Specification of Error Statistics

NASA Technical Reports Server (NTRS)

Stajner, Ivanka; Riishojgaard, Lars Peter; Rood, Richard B.

2000-01-01

A global three-dimensional ozone data assimilation system has been developed at the Data Assimilation Office of the NASA/Goddard Space Flight Center. The Total Ozone Mapping Spectrometer (TOMS) total ozone and the Solar Backscatter Ultraviolet (SBUV) or (SBUV/2) partial ozone profile observations are assimilated. The assimilation, into an off-line ozone transport model, is done using the global Physical-space Statistical Analysis Scheme (PSAS). This system became operational in December 1999. A detailed description of the statistical analysis scheme, and in particular, the forecast and observation error covariance models is given. A new global anisotropic horizontal forecast error correlation model accounts for a varying distribution of observations with latitude. Correlations are largest in the zonal direction in the tropics where data is sparse. Forecast error variance model is proportional to the ozone field. The forecast error covariance parameters were determined by maximum likelihood estimation. The error covariance models are validated using x squared statistics. The analyzed ozone fields in the winter 1992 are validated against independent observations from ozone sondes and HALOE. There is better than 10% agreement between mean Halogen Occultation Experiment (HALOE) and analysis fields between 70 and 0.2 hPa. The global root-mean-square (RMS) difference between TOMS observed and forecast values is less than 4%. The global RMS difference between SBUV observed and analyzed ozone between 50 and 3 hPa is less than 15%.

Comparison of diagnostic capability of macular ganglion cell complex and retinal nerve fiber layer among primary open angle glaucoma, ocular hypertension, and normal population using Fourier-domain optical coherence tomography and determining their functional correlation in Indian population

PubMed Central

Barua, Nabanita; Sitaraman, Chitra; Goel, Sonu; Chakraborti, Chandana; Mukherjee, Sonai; Parashar, Hemandra

2016-01-01

Context: Analysis of diagnostic ability of macular ganglionic cell complex and retinal nerve fiber layer (RNFL) in glaucoma. Aim: To correlate functional and structural parameters and comparing predictive value of each of the structural parameters using Fourier-domain (FD) optical coherence tomography (OCT) among primary open angle glaucoma (POAG) and ocular hypertension (OHT) versus normal population. Setting and Design: Single centric, cross-sectional study done in 234 eyes. Materials and Methods: Patients were enrolled in three groups: POAG, ocular hypertensive and normal (40 patients in each group). After comprehensive ophthalmological examination, patients underwent standard automated perimetry and FD-OCT scan in optic nerve head and ganglion cell mode. The relationship was assessed by correlating ganglion cell complex (GCC) parameters with mean deviation. Results were compared with RNFL parameters. Statistical Analysis: Data were analyzed with SPSS, analysis of variance, t-test, Pearson's coefficient, and receiver operating curve. Results: All parameters showed strong correlation with visual field (P < 0.001). Inferior GCC had highest area under curve (AUC) for detecting glaucoma (0.827) in POAG from normal population. However, the difference was not statistically significant (P > 0.5) when compared with other parameters. None of the parameters showed significant diagnostic capability to detect OHT from normal population. In diagnosing early glaucoma from OHT and normal population, only inferior GCC had statistically significant AUC value (0.715). Conclusion: In this study, GCC and RNFL parameters showed equal predictive capability in perimetric versus normal group. In early stage, inferior GCC was the best parameter. In OHT population, single day cross-sectional imaging was not valuable. PMID:27221682

Statistical relationships between journal use and research output at academic institutions in South Korea.

PubMed

Jung, Youngim; Kim, Jayhoon; So, Minho; Kim, Hwanmin

In this study, we analysed the statistical association between e-journal use and research output at the institution level in South Korea by performing comparative and diachronic analyses, as well as the analysis by field. The datasets were compiled from four different sources: national reports on research output indicators in science fields, two statistics databases on higher education institutions open to the public, and e-journal usage statistics generated by 47 major publishers. Due to the different data sources utilized, a considerable number of missing values appeared in our datasets and various mapping issues required corrections prior to the analysis. Two techniques for handling missing data were applied and the impact of each technique was discussed. In order to compile the institutional data by field, journals were first mapped, and then the statistics were summarized according to subject field. We observed that e-journal use exhibited stronger correlations with the number of publications and the times cited, in contrast to the number of undergraduates, graduates, faculty members and the amount of research funds, and this was the case regardless of the NA handling method or author type. The difference between the maximum correlation for the amount of external research funding with two average indicators and that of the correlation for e-journal use were not significant. Statistically, the accountability of e-journal use for the average times cited per article and the average JIF was quite similar with external research funds. It was found that the number of e-journal articles used had a strong positive correlation (Pearson's correlation coefficients of r  > 0.9, p  < 0.05) with the number of articles published in SCI(E) journals and the times cited regardless of the author type, NA handling method or time period. We also observed that the top-five institutions in South Korea, with respect to the number of publications in SCI(E) journals, were generally across a balanced range of academic activities, while producing significant research output and using published material. Finally, we confirmed that the association of e-journal use with the two quantitative research indicators is strongly positive, even for the analyses by field, with the exception of the Arts and Humanities.

Correlation of RNA secondary structure statistics with thermodynamic stability and applications to folding.

PubMed

Wu, Johnny C; Gardner, David P; Ozer, Stuart; Gutell, Robin R; Ren, Pengyu

2009-08-28

The accurate prediction of the secondary and tertiary structure of an RNA with different folding algorithms is dependent on several factors, including the energy functions. However, an RNA higher-order structure cannot be predicted accurately from its sequence based on a limited set of energy parameters. The inter- and intramolecular forces between this RNA and other small molecules and macromolecules, in addition to other factors in the cell such as pH, ionic strength, and temperature, influence the complex dynamics associated with transition of a single stranded RNA to its secondary and tertiary structure. Since all of the factors that affect the formation of an RNAs 3D structure cannot be determined experimentally, statistically derived potential energy has been used in the prediction of protein structure. In the current work, we evaluate the statistical free energy of various secondary structure motifs, including base-pair stacks, hairpin loops, and internal loops, using their statistical frequency obtained from the comparative analysis of more than 50,000 RNA sequences stored in the RNA Comparative Analysis Database (rCAD) at the Comparative RNA Web (CRW) Site. Statistical energy was computed from the structural statistics for several datasets. While the statistical energy for a base-pair stack correlates with experimentally derived free energy values, suggesting a Boltzmann-like distribution, variation is observed between different molecules and their location on the phylogenetic tree of life. Our statistical energy values calculated for several structural elements were utilized in the Mfold RNA-folding algorithm. The combined statistical energy values for base-pair stacks, hairpins and internal loop flanks result in a significant improvement in the accuracy of secondary structure prediction; the hairpin flanks contribute the most.

The overnight effect on the Taiwan stock market

NASA Astrophysics Data System (ADS)

Tsai, Kuo-Ting; Lih, Jiann-Shing; Ko, Jing-Yuan

2012-12-01

This study examines statistical regularities among three components of stocks and indices: daytime (trading hour) return, overnight (off-hour session) return, and total (close-to-close) return. Owing to the fact that the Taiwan Stock Exchange (TWSE) has the longest non-trading periods among major markets, the TWSE is selected to explore the correlation among the three components and compare it with major markets such as the New York Stock Exchange (NYSE) and the National Association of Securities Dealers Automated Quotation (NASDAQ). Analysis results indicate a negative cross correlation between the sign of daytime return and the sign of overnight return; possibly explaining why most stocks feature a negative cross correlation between daytime return and overnight return [F. Wang, S.-J. Shieh, S. Havlin, H.E. Stanley, Statistical analysis of the overnight and daytime return, Phys. Rev. E 79 (2009) 056109]. Additionally, the cross correlation between the magnitude of returns is analyzed. According to those results, a larger magnitude of overnight return implies a higher probability that the sign of the following daytime return is the opposite of the sign of overnight return. Namely, the predictability of daytime return might be improved when a stock undergoes a large magnitude of overnight return. Furthermore, the cross correlations of 29 indices of worldwide markets are discussed.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies.

PubMed

Koerner, Tess K; Zhang, Yang

2017-02-27

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers.

Identifying the impact of social determinants of health on disease rates using correlation analysis of area-based summary information.

PubMed

Song, Ruiguang; Hall, H Irene; Harrison, Kathleen McDavid; Sharpe, Tanya Telfair; Lin, Lillian S; Dean, Hazel D

2011-01-01

We developed a statistical tool that brings together standard, accessible, and well-understood analytic approaches and uses area-based information and other publicly available data to identify social determinants of health (SDH) that significantly affect the morbidity of a specific disease. We specified AIDS as the disease of interest and used data from the American Community Survey and the National HIV Surveillance System. Morbidity and socioeconomic variables in the two data systems were linked through geographic areas that can be identified in both systems. Correlation and partial correlation coefficients were used to measure the impact of socioeconomic factors on AIDS diagnosis rates in certain geographic areas. We developed an easily explained approach that can be used by a data analyst with access to publicly available datasets and standard statistical software to identify the impact of SDH. We found that the AIDS diagnosis rate was highly correlated with the distribution of race/ethnicity, population density, and marital status in an area. The impact of poverty, education level, and unemployment depended on other SDH variables. Area-based measures of socioeconomic variables can be used to identify risk factors associated with a disease of interest. When correlation analysis is used to identify risk factors, potential confounding from other variables must be taken into account.

Methods for trend analysis: Examples with problem/failure data

NASA Technical Reports Server (NTRS)

Church, Curtis K.

1989-01-01

Statistics are emphasized as an important role in quality control and reliability. Consequently, Trend Analysis Techniques recommended a variety of statistical methodologies that could be applied to time series data. The major goal of the working handbook, using data from the MSFC Problem Assessment System, is to illustrate some of the techniques in the NASA standard, some different techniques, and to notice patterns of data. Techniques for trend estimation used are: regression (exponential, power, reciprocal, straight line) and Kendall's rank correlation coefficient. The important details of a statistical strategy for estimating a trend component are covered in the examples. However, careful analysis and interpretation is necessary because of small samples and frequent zero problem reports in a given time period. Further investigations to deal with these issues are being conducted.

Characterizing chaotic melodies in automatic music composition

NASA Astrophysics Data System (ADS)

Coca, Andrés E.; Tost, Gerard O.; Zhao, Liang

2010-09-01

In this paper, we initially present an algorithm for automatic composition of melodies using chaotic dynamical systems. Afterward, we characterize chaotic music in a comprehensive way as comprising three perspectives: musical discrimination, dynamical influence on musical features, and musical perception. With respect to the first perspective, the coherence between generated chaotic melodies (continuous as well as discrete chaotic melodies) and a set of classical reference melodies is characterized by statistical descriptors and melodic measures. The significant differences among the three types of melodies are determined by discriminant analysis. Regarding the second perspective, the influence of dynamical features of chaotic attractors, e.g., Lyapunov exponent, Hurst coefficient, and correlation dimension, on melodic features is determined by canonical correlation analysis. The last perspective is related to perception of originality, complexity, and degree of melodiousness (Euler's gradus suavitatis) of chaotic and classical melodies by nonparametric statistical tests.

Quantifying predictability in a model with statistical features of the atmosphere

PubMed Central

Kleeman, Richard; Majda, Andrew J.; Timofeyev, Ilya

2002-01-01

The Galerkin truncated inviscid Burgers equation has recently been shown by the authors to be a simple model with many degrees of freedom, with many statistical properties similar to those occurring in dynamical systems relevant to the atmosphere. These properties include long time-correlated, large-scale modes of low frequency variability and short time-correlated “weather modes” at smaller scales. The correlation scaling in the model extends over several decades and may be explained by a simple theory. Here a thorough analysis of the nature of predictability in the idealized system is developed by using a theoretical framework developed by R.K. This analysis is based on a relative entropy functional that has been shown elsewhere by one of the authors to measure the utility of statistical predictions precisely. The analysis is facilitated by the fact that most relevant probability distributions are approximately Gaussian if the initial conditions are assumed to be so. Rather surprisingly this holds for both the equilibrium (climatological) and nonequilibrium (prediction) distributions. We find that in most cases the absolute difference in the first moments of these two distributions (the “signal” component) is the main determinant of predictive utility variations. Contrary to conventional belief in the ensemble prediction area, the dispersion of prediction ensembles is generally of secondary importance in accounting for variations in utility associated with different initial conditions. This conclusion has potentially important implications for practical weather prediction, where traditionally most attention has focused on dispersion and its variability. PMID:12429863

Cytomegalovirus (CMV) Enzyme-Linked Immunosorbent Spot Assay but Not CMV QuantiFERON Assay Is a Novel Biomarker To Determine Risk of Congenital CMV Infection in Pregnant Women

PubMed Central

Forner, Gabriella; Saldan, Alda; Mengoli, Carlo; Gussetti, Nadia; Palù, Giorgio

2016-01-01

Cytomegalovirus (CMV) enzyme-linked immunosorbent spot (ELISPOT) and CMV QuantiFERON assays were examined as potential biomarkers predictive of congenital CMV (cCMV) transmission. Fifty-seven pregnant women with primary CMV infection and 23 with nonprimary CMV infection were recruited in the study. Maternal age, CMV IgG avidity, viremia, and viruria were also included among the potential predictors. Spearman's statistical correlation analysis revealed a positive correlation between the CMV ELISPOT and CMV QuantiFERON assay results (P < 0.001), but only the CMV ELISPOT assay correlated with cCMV (P < 0.001). cCMV was positively correlated with maternal viremia and viruria (P < 0.05) and negatively correlated with CMV IgG avidity (P < 0.01). Maternal age and CMV QuantiFERON assay results were not statistically associated with cCMV. CMV-specific cell-mediated immunity detected by the CMV ELISPOT assay plays a critical role in cCMV. PMID:27280418

Correlation analysis between 2D and quasi-3D gamma evaluations for both intensity-modulated radiation therapy and volumetric modulated arc therapy

PubMed Central

Kim, Jung-in; Choi, Chang Heon; Wu, Hong-Gyun; Kim, Jin Ho; Kim, Kyubo; Park, Jong Min

2017-01-01

The aim of this work was to investigate correlations between 2D and quasi-3D gamma passing rates. A total of 20 patients (10 prostate cases and 10 head and neck cases, H&N) were retrospectively selected. For each patient, both intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) plans were generated. For each plan, 2D gamma evaluation with radiochromic films and quasi-3D gamma evaluation with fluence measurements were performed with both 2%/2 mm and 3%/3 mm criteria. Gamma passing rates were grouped together according to delivery techniques and treatment sites. Statistical analyses were performed to examine the correlation between 2D and quasi-3D gamma evaluations. Statistically significant difference was observed between delivery techniques only in the quasi-3D gamma passing rates with 2%/2 mm. Statistically significant differences were observed between treatment sites in the 2D gamma passing rates (differences of less than 8%). No statistically significant correlations were observed between 2D and quasi-3D gamma passing rates except the VMAT group and the group including both IMRT and VMAT with 3%/3 mm (r = 0.564 with p = 0.012 for theVMAT group and r = 0.372 with p = 0.020 for the group including both IMRT and VMAT), however, those were not strong. No strong correlations were observed between 2D and quasi-3D gamma evaluations. PMID:27690300

More efficient parameter estimates for factor analysis of ordinal variables by ridge generalized least squares.

PubMed

Yuan, Ke-Hai; Jiang, Ge; Cheng, Ying

2017-11-01

Data in psychology are often collected using Likert-type scales, and it has been shown that factor analysis of Likert-type data is better performed on the polychoric correlation matrix than on the product-moment covariance matrix, especially when the distributions of the observed variables are skewed. In theory, factor analysis of the polychoric correlation matrix is best conducted using generalized least squares with an asymptotically correct weight matrix (AGLS). However, simulation studies showed that both least squares (LS) and diagonally weighted least squares (DWLS) perform better than AGLS, and thus LS or DWLS is routinely used in practice. In either LS or DWLS, the associations among the polychoric correlation coefficients are completely ignored. To mend such a gap between statistical theory and empirical work, this paper proposes new methods, called ridge GLS, for factor analysis of ordinal data. Monte Carlo results show that, for a wide range of sample sizes, ridge GLS methods yield uniformly more accurate parameter estimates than existing methods (LS, DWLS, AGLS). A real-data example indicates that estimates by ridge GLS are 9-20% more efficient than those by existing methods. Rescaled and adjusted test statistics as well as sandwich-type standard errors following the ridge GLS methods also perform reasonably well. © 2017 The British Psychological Society.

Interdisciplinary evaluation of dysphagia: clinical swallowing evaluation and videoendoscopy of swallowing.

PubMed

Sordi, Marina de; Mourão, Lucia Figueiredo; Silva, Ariovaldo Armando da; Flosi, Luciana Claudia Leite

2009-01-01

Patients with dysphagia have impairments in many aspects, and an interdisciplinary approach is fundamental to define diagnosis and treatment. A joint approach in the clinical and videoendoscopy evaluation is paramount. To study the correlation between the clinical assessment (ACD) and the videoendoscopic (VED) assessment of swallowing by classifying the degree of severity and the qualitative/descriptive analyses of the procedures. cross-sectional, descriptive and comparative. held from March to December of 2006, at the Otolaryngology/Dysphagia ward of a hospital in the country side of São Paulo. 30 dysphagic patients with different disorders were assessed by ACD and VED. The data was classified by means of severity scales and qualitative/ descriptive analysis. the correlation between severity ACD and VED scales pointed to a statistically significant low agreement (KAPA = 0.4) (p=0,006). The correlation between the qualitative/descriptive analysis pointed to an excellent and statistically significant agreement (KAPA=0.962) (p<0.001) concerning the entire sample. the low agreement between the severity scales point to a need to perform both procedures, reinforcing VED as a doable procedure. The descriptive qualitative analysis pointed to an excellent agreement, and such data reinforces our need to understand swallowing as a process.

Utilization of an Enhanced Canonical Correlation Analysis (ECCA) to Predict Daily Precipitation and Temperature in a Semi-Arid Environment

NASA Astrophysics Data System (ADS)

Lopez, S. R.; Hogue, T. S.

2011-12-01

Global climate models (GCMs) are primarily used to generate historical and future large-scale circulation patterns at a coarse resolution (typical order of 50,000 km2) and fail to capture climate variability at the ground level due to localized surface influences (i.e topography, marine, layer, land cover, etc). Their inability to accurately resolve these processes has led to the development of numerous 'downscaling' techniques. The goal of this study is to enhance statistical downscaling of daily precipitation and temperature for regions with heterogeneous land cover and topography. Our analysis was divided into two periods, historical (1961-2000) and contemporary (1980-2000), and tested using sixteen predictand combinations from four GCMs (GFDL CM2.0, GFDL CM2.1, CNRM-CM3 and MRI-CGCM2 3.2a. The Southern California area was separated into five county regions: Santa Barbara, Ventura, Los Angeles, Orange and San Diego. Principle component analysis (PCA) was performed on ground-based observations in order to (1) reduce the number of redundant gauges and minimize dimensionality and (2) cluster gauges that behave statistically similarly for post-analysis. Post-PCA analysis included extensive testing of predictor-predictand relationships using an enhanced canonical correlation analysis (ECCA). The ECCA includes obtaining the optimal predictand sets for all models within each spatial domain (county) as governed by daily and monthly overall statistics. Results show all models maintain mean annual and monthly behavior within each county and daily statistics are improved. The level of improvement highly depends on the vegetation extent within each county and the land-to-ocean ratio within the GCM spatial grid. The utilization of the entire historical period also leads to better statistical representation of observed daily precipitation. The validated ECCA technique is being applied to future climate scenarios distributed by the IPCC in order to provide forcing data for regional hydrologic models and assess future water resources in the Southern California region.

Statistical analysis for understanding and predicting battery degradations in real-life electric vehicle use

NASA Astrophysics Data System (ADS)

Barré, Anthony; Suard, Frédéric; Gérard, Mathias; Montaru, Maxime; Riu, Delphine

2014-01-01

This paper describes the statistical analysis of recorded data parameters of electrical battery ageing during electric vehicle use. These data permit traditional battery ageing investigation based on the evolution of the capacity fade and resistance raise. The measured variables are examined in order to explain the correlation between battery ageing and operating conditions during experiments. Such study enables us to identify the main ageing factors. Then, detailed statistical dependency explorations present the responsible factors on battery ageing phenomena. Predictive battery ageing models are built from this approach. Thereby results demonstrate and quantify a relationship between variables and battery ageing global observations, and also allow accurate battery ageing diagnosis through predictive models.

[The effect of the iontophoretic administration of glutamate on the organization of interneuronal interactions in the rabbit motor cortex].

PubMed

Khokhlova, V N

1999-01-01

The multiunit activity of neurons in the motor cortex was recorded in 6 rabbits during glutamate (or physiological saline) iontophoretic application. Interaction between the neighboring neurons was evaluated by means of statistical cross-correlation analysis of spike trains. It was found that glutamate did not produce significant changes in cross-correlations.

Statistical studies in stellar rotation 2: A method of analyzing rotational coupling in double stars and an introduction to its applications

NASA Technical Reports Server (NTRS)

Bernacca, P. L.

1971-01-01

The correlation between the equatorial velocities of the components of double stars is studied from a statistical standpoint. A theory of rotational correlation is developed and discussed with regard to its applicability to existing observations. The theory is then applied to a sample of visual binaries which are the least studied for rotational coupling. Consideration of eclipsing systems and spectroscopic binaries is limited to show how the degrees of freedom in the spin parallelism problem can be reduced. The analysis lends support to the existence of synchronism in closely spaced binaries.

The correlation between proprioception and handwriting legibility in children

PubMed Central

Hong, So Young; Jung, Nam-Hae; Kim, Kyeong Mi

2016-01-01

[Purpose] This study investigated the association between proprioception, including joint position sense and kinetic sense, and handwriting legibility in healthy children. [Subjects and Methods] Assessment of joint position sense, kinetic sense, and handwriting legibility was conducted for 19 healthy children. Joint position sense was assessed by asking the children to flex their right elbow between 30° to 110° while blindfolded. The range of elbow movement was analyzed with Compact Measuring System 10 for 3D motion Analysis. Kinetic sense was assessed using the Sensory Integration and Praxis Test. The children were directed to write 30 words from the Korean alphabet, and the legibility of their handwriting was scored for form, alignment, space, size, and shape. To analyze the data, descriptive statistics and Spearman correlation analysis were conducted using IBM SPSS Statistics 20.0. [Results] There was significant negative correlation between handwriting legibility and Kinetic sense. A significant correlation between handwriting legibility and Joint position sense was not found. [Conclusion] This study showed that a higher Kinetic sense was associated with better legibility of handwriting. Further work is needed to determine the association of handwriting legibility and speed with Joint position sense of the elbow, wrist, and fingers. PMID:27821948

On Determining the Rise, Size, and Duration Classes of a Sunspot Cycle

NASA Astrophysics Data System (ADS)

Wilson, Robert M.; Hathaway, David H.; Reichmann, Edwin J.

1996-09-01

The behavior of ascent duration, maximum amplitude, and period for cycles 1 to 21 suggests that they are not mutually independent. Analysis of the resultant three-dimensional contingency table for cycles divided according to rise time (ascent duration), size (maximum amplitude), and duration (period) yields a chi-square statistic (= 18.59) that is larger than the test statistic (= 9.49 for 4 degrees-of-freedom at the 5-percent level of significance), thereby, inferring that the null hypothesis (mutual independence) can be rejected. Analysis of individual 2 by 2 contingency tables (based on Fisher's exact test) for these parameters shows that, while ascent duration is strongly related to maximum amplitude in the negative sense (inverse correlation) - the Waldmeier effect, it also is related (marginally) to period, but in the positive sense (direct correlation). No significant (or marginally significant) correlation is found between period and maximum amplitude. Using cycle 22 as a test case, we show that by the 12th month following conventional onset, cycle 22 appeared highly likely to be a fast-rising, larger-than-average-size cycle. Because of the inferred correlation between ascent duration and period, it also seems likely that it will have a period shorter than average length.

On Determining the Rise, Size, and Duration Classes of a Sunspot Cycle

NASA Technical Reports Server (NTRS)

Wilson, Robert M.; Hathaway, David H.; Reichmann, Edwin J.

1996-01-01

The behavior of ascent duration, maximum amplitude, and period for cycles 1 to 21 suggests that they are not mutually independent. Analysis of the resultant three-dimensional contingency table for cycles divided according to rise time (ascent duration), size (maximum amplitude), and duration (period) yields a chi-square statistic (= 18.59) that is larger than the test statistic (= 9.49 for 4 degrees-of-freedom at the 5-percent level of significance), thereby, inferring that the null hypothesis (mutual independence) can be rejected. Analysis of individual 2 by 2 contingency tables (based on Fisher's exact test) for these parameters shows that, while ascent duration is strongly related to maximum amplitude in the negative sense (inverse correlation) - the Waldmeier effect, it also is related (marginally) to period, but in the positive sense (direct correlation). No significant (or marginally significant) correlation is found between period and maximum amplitude. Using cycle 22 as a test case, we show that by the 12th month following conventional onset, cycle 22 appeared highly likely to be a fast-rising, larger-than-average-size cycle. Because of the inferred correlation between ascent duration and period, it also seems likely that it will have a period shorter than average length.

Lower incisor inclination regarding different reference planes.

PubMed

Zataráin, Brenda; Avila, Josué; Moyaho, Angeles; Carrasco, Rosendo; Velasco, Carmen

2016-09-01

The purpose of this study was to assess the degree of lower incisor inclination with respect to different reference planes. It was an observational, analytical, longitudinal, prospective study conducted on 100 lateral cephalograms which were corrected according to the photograph in natural head position in order to draw the true vertical plane (TVP). The incisor mandibular plane angle (IMPA) was compensated to eliminate the variation of the mandibular plane growth type with the formula "FMApx.- 25 (FMA) + IMPApx. = compensated IMPA (IMPACOM)". As the data followed normal distribution determined by the KolmogorovSmirnov test, parametric tests were used for the statistical analysis, Ttest, ANOVA and Pearson coefficient correlation test. Statistical analysis was performed using a statistical significance of p <0.05. There is correlation between TVP and NB line (NB) (0.8614), Frankfort mandibular incisor angle (FMIA) (0.8894), IMPA (0.6351), Apo line (Apo) (0.609), IMPACOM (0.8895) and McHorris angle (MH) (0.7769). ANOVA showed statistically significant differences between the means for the 7 variables with 95% confidence level, P=0.0001. The multiple range test showed no significant difference among means: APoNB (0.88), IMPAMH (0.36), IMPANB (0.65), FMIAIMPACOM (0.01), FMIATVP (0.18), TVPIMPACOM (0.17). There was correlation among all reference planes. There were statistically significant differences among the means of the planes measured, except for IMPACOM, FMIA and TVP. The IMPA differed significantly from the IMPACOM. The compensated IMPA and the FMIA did not differ significantly from the TVP. The true horizontal plane was mismatched with Frankfort plane in 84% of the sample with a range of 19°. The true vertical plane is adequate for measuring lower incisor inclination. Sociedad Argentina de Investigación Odontológica.

Analysis models for the estimation of oceanic fields

NASA Technical Reports Server (NTRS)

Carter, E. F.; Robinson, A. R.

1987-01-01

A general model for statistically optimal estimates is presented for dealing with scalar, vector and multivariate datasets. The method deals with anisotropic fields and treats space and time dependence equivalently. Problems addressed include the analysis, or the production of synoptic time series of regularly gridded fields from irregular and gappy datasets, and the estimate of fields by compositing observations from several different instruments and sampling schemes. Technical issues are discussed, including the convergence of statistical estimates, the choice of representation of the correlations, the influential domain of an observation, and the efficiency of numerical computations.

Statistical modeling of space shuttle environmental data

NASA Technical Reports Server (NTRS)

Tubbs, J. D.; Brewer, D. W.

1983-01-01

Statistical models which use a class of bivariate gamma distribution are examined. Topics discussed include: (1) the ratio of positively correlated gamma varieties; (2) a method to determine if unequal shape parameters are necessary in bivariate gamma distribution; (3) differential equations for modal location of a family of bivariate gamma distribution; and (4) analysis of some wind gust data using the analytical results developed for modeling application.

Hierarchical multivariate covariance analysis of metabolic connectivity.

PubMed

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-12-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI).

Coherent light depolarization by multiple scattering media and tissues: some fundamentals and applications

NASA Astrophysics Data System (ADS)

Zimnyakov, Dmitry A.; Tuchin, Valery V.; Yodh, Arjun G.; Mishin, Alexey A.; Peretochkin, Igor S.

1998-04-01

Relationships between decorrelation and depolarization of coherent light scattered by disordered media are examined by using the conception of the photon paths distribution functions. Analysis of behavior of the autocorrelation functions of the scattered field fluctuations and their polarization properties allows us to introduce generalized parameter of scattering media such as specific correlation time. Determination of specific correlation time has been carried out for phantom scattering media (water suspensions of polystyrene spheres). Results of statistical, correlation and polarization analysis of static and dynamic speckle patterns carried out in the experiments with human sclera with artificially controlled optical transmittance are presented. Some possibilities of applications of such polarization- correlation technique for monitoring and visualization of non- single scattering tissue structures are discussed.

Fast Metabolite Identification in Nuclear Magnetic Resonance Metabolomic Studies: Statistical Peak Sorting and Peak Overlap Detection for More Reliable Database Queries.

PubMed

Hoijemberg, Pablo A; Pelczer, István

2018-01-05

A lot of time is spent by researchers in the identification of metabolites in NMR-based metabolomic studies. The usual metabolite identification starts employing public or commercial databases to match chemical shifts thought to belong to a given compound. Statistical total correlation spectroscopy (STOCSY), in use for more than a decade, speeds the process by finding statistical correlations among peaks, being able to create a better peak list as input for the database query. However, the (normally not automated) analysis becomes challenging due to the intrinsic issue of peak overlap, where correlations of more than one compound appear in the STOCSY trace. Here we present a fully automated methodology that analyzes all STOCSY traces at once (every peak is chosen as driver peak) and overcomes the peak overlap obstacle. Peak overlap detection by clustering analysis and sorting of traces (POD-CAST) first creates an overlap matrix from the STOCSY traces, then clusters the overlap traces based on their similarity and finally calculates a cumulative overlap index (COI) to account for both strong and intermediate correlations. This information is gathered in one plot to help the user identify the groups of peaks that would belong to a single molecule and perform a more reliable database query. The simultaneous examination of all traces reduces the time of analysis, compared to viewing STOCSY traces by pairs or small groups, and condenses the redundant information in the 2D STOCSY matrix into bands containing similar traces. The COI helps in the detection of overlapping peaks, which can be added to the peak list from another cross-correlated band. POD-CAST overcomes the generally overlooked and underestimated presence of overlapping peaks and it detects them to include them in the search of all compounds contributing to the peak overlap, enabling the user to accelerate the metabolite identification process with more successful database queries and searching all tentative compounds in the sample set.

Utility of Gram stain for the microbiological analysis of burn wound surfaces.

PubMed

Elsayed, Sameer; Gregson, Daniel B; Lloyd, Tracie; Crichton, Marilyn; Church, Deirdre L

2003-11-01

Surface swab cultures have attracted attention as a potential alternative to biopsy histology or quantitative culture methods for microbiological burn wound monitoring. To our knowledge, the utility of adding a Gram-stained slide in this context has not been evaluated previously. To determine the degree of correlation of Gram stain with culture for the microbiological analysis of burn wound surfaces. Prospective laboratory analysis. Urban health region/centralized diagnostic microbiology laboratory. Burn patients hospitalized in any Calgary Health Region burn center from November 2000 to September 2001. Gram stain plus culture of burn wound surface swab specimens obtained during routine dressing changes or based on clinical signs of infection. Degree of correlation (complete, high, partial, none), including weighted kappa statistic (kappa(w)), of Gram stain with culture based on quantitative microscopy and degree of culture growth. A total of 375 specimens from 50 burn patients were evaluated. Of these, 239 were negative by culture and Gram stain, 7 were positive by Gram stain only, 89 were positive by culture only, and 40 were positive by both methods. The degree of complete, high, partial, and no correlation of Gram stain with culture was 70.9% (266/375), 1.1% (4/375), 2.4% (9/375), and 25.6% (96/375), respectively. The degree of correlation for all 375 specimens, as expressed by the weighted kappa statistic, was found to be fair (kappa(w) = 0.32).Conclusion.-The Gram stain is not suitable for the microbiological analysis of burn wound surfaces.

Experiments with a three-dimensional statistical objective analysis scheme using FGGE data

NASA Technical Reports Server (NTRS)

Baker, Wayman E.; Bloom, Stephen C.; Woollen, John S.; Nestler, Mark S.; Brin, Eugenia

1987-01-01

A three-dimensional (3D), multivariate, statistical objective analysis scheme (referred to as optimum interpolation or OI) has been developed for use in numerical weather prediction studies with the FGGE data. Some novel aspects of the present scheme include: (1) a multivariate surface analysis over the oceans, which employs an Ekman balance instead of the usual geostrophic relationship, to model the pressure-wind error cross correlations, and (2) the capability to use an error correlation function which is geographically dependent. A series of 4-day data assimilation experiments are conducted to examine the importance of some of the key features of the OI in terms of their effects on forecast skill, as well as to compare the forecast skill using the OI with that utilizing a successive correction method (SCM) of analysis developed earlier. For the three cases examined, the forecast skill is found to be rather insensitive to varying the error correlation function geographically. However, significant differences are noted between forecasts from a two-dimensional (2D) version of the OI and those from the 3D OI, with the 3D OI forecasts exhibiting better forecast skill. The 3D OI forecasts are also more accurate than those from the SCM initial conditions. The 3D OI with the multivariate oceanic surface analysis was found to produce forecasts which were slightly more accurate, on the average, than a univariate version.

Statistical analysis of atmospheric turbulence about a simulated block building

NASA Technical Reports Server (NTRS)

Steely, S. L., Jr.

1981-01-01

An array of towers instrumented to measure the three components of wind speed was used to study atmospheric flow about a simulated block building. Two-point spacetime correlations of the longitudinal velocity component were computed along with two-point spatial correlations. These correlations are in good agreement with fundamental concepts of fluid mechanics. The two-point spatial correlations computed directly were compared with correlations predicted by Taylor's hypothesis and excellent agreement was obtained at the higher levels which were out of the building influence. The correlations fall off significantly in the building wake but recover beyond the wake to essentially the same values in the undisturbed, higher regions.

Statistical Approaches to Adjusting Weights for Dependent Arms in Network Meta-analysis.

PubMed

Su, Yu-Xuan; Tu, Yu-Kang

2018-05-22

Network meta-analysis compares multiple treatments in terms of their efficacy and harm by including evidence from randomized controlled trials. Most clinical trials use parallel design, where patients are randomly allocated to different treatments and receive only one treatment. However, some trials use within person designs such as split-body, split-mouth and cross-over designs, where each patient may receive more than one treatment. Data from treatment arms within these trials are no longer independent, so the correlations between dependent arms need to be accounted for within the statistical analyses. Ignoring these correlations may result in incorrect conclusions. The main objective of this study is to develop statistical approaches to adjusting weights for dependent arms within special design trials. In this study, we demonstrate the following three approaches: the data augmentation approach, the adjusting variance approach, and the reducing weight approach. These three methods could be perfectly applied in current statistic tools such as R and STATA. An example of periodontal regeneration was used to demonstrate how these approaches could be undertaken and implemented within statistical software packages, and to compare results from different approaches. The adjusting variance approach can be implemented within the network package in STATA, while reducing weight approach requires computer software programming to set up the within-study variance-covariance matrix. This article is protected by copyright. All rights reserved.

Application of histogram analysis for the evaluation of vascular permeability in glioma by the K2 parameter obtained with the dynamic susceptibility contrast method: Comparisons with Ktrans obtained with the dynamic contrast enhance method and cerebral blood volume.

PubMed

Taoka, Toshiaki; Kawai, Hisashi; Nakane, Toshiki; Hori, Saeka; Ochi, Tomoko; Miyasaka, Toshiteru; Sakamoto, Masahiko; Kichikawa, Kimihiko; Naganawa, Shinji

2016-09-01

The "K2" value is a factor that represents the vascular permeability of tumors and can be calculated from datasets obtained with the dynamic susceptibility contrast (DSC) method. The purpose of the current study was to correlate K2 with Ktrans, which is a well-established permeability parameter obtained with the dynamic contrast enhance (DCE) method, and determine the usefulness of K2 for glioma grading with histogram analysis. The subjects were 22 glioma patients (Grade II: 5, III: 6, IV: 11) who underwent DSC studies, including eight patients in which both DSC and DCE studies were performed on separate days within 10days. We performed histogram analysis of regions of interest of the tumors and acquired 20th percentile values for leakage-corrected cerebral blood volume (rCBV20%ile), K2 (K220%ile), and for patients who underwent a DCE study, Ktrans (Ktrans20%ile). We evaluated the correlation between K220%ile and Ktrans20%ile and the statistical difference between rCBV20%ile and K220%ile. We found a statistically significant correlation between K220%ile and Ktrans20%ile (r=0.717, p<0.05). rCBV20%ile showed a significant difference between Grades II and III and between Grades II and IV, whereas K220%ile showed a statistically significant (p<0.05) difference between Grades II and IV and between Grades III and IV. The K2 value calculated from the DSC dataset, which can be obtained with a short acquisition time, showed a correlation with Ktrans obtained with the DCE method and may be useful for glioma grading when analyzed with histogram analysis. Copyright © 2016 Elsevier Inc. All rights reserved.

Correlation of FCGRT genomic structure with serum immunoglobulin, albumin and farletuzumab pharmacokinetics in patients with first relapsed ovarian cancer.

PubMed

O'Shannessy, Daniel J; Bendas, Katie; Schweizer, Charles; Wang, Wenquan; Albone, Earl; Somers, Elizabeth B; Weil, Susan; Meredith, Rhonda K; Wustner, Jason; Grasso, Luigi; Landers, Mark; Nicolaides, Nicholas C

2017-07-01

Farletuzumab (FAR) is a humanized monoclonal antibody (mAb) that binds to folate receptor alpha. A Ph3 trial in ovarian cancer patients treated with carboplatin/taxane plus FAR or placebo did not meet the primary statistical endpoint. Subgroup analysis demonstrated that subjects with high FAR exposure levels (Cmin>57.6μg/mL) showed statistically significant improvements in PFS and OS. The neonatal Fc receptor (fcgrt) plays a central role in albumin/IgG stasis and mAb pharmacokinetics (PK). Here we evaluated fcgrt sequence and association of its promoter variable number tandem repeats (VNTR) and coding single nucleotide variants (SNV) with albumin/IgG levels and FAR PK in the Ph3 patients. A statistical correlation existed between high FAR Cmin and AUC in patients with the highest quartile of albumin and lowest quartile of IgG1. Analysis of fcgrt identified 5 different VNTRs in the promoter region and 9 SNVs within the coding region, 4 which are novel. Copyright © 2017. Published by Elsevier Inc.

Review and statistical analysis of the use of ultrasonic velocity for estimating the porosity fraction in polycrystalline materials

NASA Technical Reports Server (NTRS)

Roth, D. J.; Swickard, S. M.; Stang, D. B.; Deguire, M. R.

1991-01-01

A review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials is presented. Initially, a semiempirical model is developed showing the origin of the linear relationship between ultrasonic velocity and porosity fraction. Then, from a compilation of data produced by many researchers, scatter plots of velocity versus percent porosity data are shown for Al2O3, MgO, porcelain-based ceramics, PZT, SiC, Si3N4, steel, tungsten, UO2,(U0.30Pu0.70)C, and YBa2Cu3O(7-x). Linear regression analysis produces predicted slope, intercept, correlation coefficient, level of significance, and confidence interval statistics for the data. Velocity values predicted from regression analysis of fully-dense materials are in good agreement with those calculated from elastic properties.

Review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials

NASA Technical Reports Server (NTRS)

Roth, D. J.; Swickard, S. M.; Stang, D. B.; Deguire, M. R.

1990-01-01

A review and statistical analysis of the ultrasonic velocity method for estimating the porosity fraction in polycrystalline materials is presented. Initially, a semi-empirical model is developed showing the origin of the linear relationship between ultrasonic velocity and porosity fraction. Then, from a compilation of data produced by many researchers, scatter plots of velocity versus percent porosity data are shown for Al2O3, MgO, porcelain-based ceramics, PZT, SiC, Si3N4, steel, tungsten, UO2,(U0.30Pu0.70)C, and YBa2Cu3O(7-x). Linear regression analysis produced predicted slope, intercept, correlation coefficient, level of significance, and confidence interval statistics for the data. Velocity values predicted from regression analysis for fully-dense materials are in good agreement with those calculated from elastic properties.

Analysis of the Einstein sample of early-type galaxies

NASA Technical Reports Server (NTRS)

Eskridge, Paul B.; Fabbiano, Giuseppina

1993-01-01

The EINSTEIN galaxy catalog contains x-ray data for 148 early-type (E and SO) galaxies. A detailed analysis of the global properties of this sample are studied. By comparing the x-ray properties with other tracers of the ISM, as well as with observables related to the stellar dynamics and populations of the sample, we expect to determine more clearly the physical relationships that determine the evolution of early-type galaxies. Previous studies with smaller samples have explored the relationships between x-ray luminosity (L(sub x)) and luminosities in other bands. Using our larger sample and the statistical techniques of survival analysis, a number of these earlier analyses were repeated. For our full sample, a strong statistical correlation is found between L(sub X) and L(sub B) (the probability that the null hypothesis is upheld is P less than 10(exp -4) from a variety of rank correlation tests. Regressions with several algorithms yield consistent results.

Psychometric properties of the Portuguese version of place attachment scale for youth in residential care.

PubMed

Magalhães, Eunice; Calheiros, María M

2015-01-01

Although the significant scientific advances on place attachment literature, no instruments exist specifically developed or adapted to residential care. 410 adolescents (11 - 18 years old) participated in this study. The place attachment scale evaluates five dimensions: Place identity, Place dependence, Institutional bonding, Caregivers bonding and Friend bonding. Data analysis included descriptive statistics, content validity, construct validity (Confirmatory Factor Analysis), concurrent validity with correlations with satisfaction with life and with institution, and reliability evidences. The relationship with individual characteristics and placement length was also verified. Content validity analysis revealed that more than half of the panellists perceive all the items as relevant to assess the construct in residential care. The structure with five dimensions revealed good fit statistics and concurrent validity evidences were found, with significant correlations with satisfaction with life and with the institution. Acceptable values of internal consistence and specific gender differences were found. The preliminary psychometric properties of this scale suggest it potential to be used with youth in care.

Model-based reconstruction of synthetic promoter library in Corynebacterium glutamicum.

PubMed

Zhang, Shuanghong; Liu, Dingyu; Mao, Zhitao; Mao, Yufeng; Ma, Hongwu; Chen, Tao; Zhao, Xueming; Wang, Zhiwen

2018-05-01

To develop an efficient synthetic promoter library for fine-tuned expression of target genes in Corynebacterium glutamicum. A synthetic promoter library for C. glutamicum was developed based on conserved sequences of the - 10 and - 35 regions. The synthetic promoter library covered a wide range of strengths, ranging from 1 to 193% of the tac promoter. 68 promoters were selected and sequenced for correlation analysis between promoter sequence and strength with a statistical model. A new promoter library was further reconstructed with improved promoter strength and coverage based on the results of correlation analysis. Tandem promoter P70 was finally constructed with increased strength by 121% over the tac promoter. The promoter library developed in this study showed a great potential for applications in metabolic engineering and synthetic biology for the optimization of metabolic networks. To the best of our knowledge, this is the first reconstruction of synthetic promoter library based on statistical analysis of C. glutamicum.

HydroClimATe: hydrologic and climatic analysis toolkit

USGS Publications Warehouse

Dickinson, Jesse; Hanson, Randall T.; Predmore, Steven K.

2014-01-01

The potential consequences of climate variability and climate change have been identified as major issues for the sustainability and availability of the worldwide water resources. Unlike global climate change, climate variability represents deviations from the long-term state of the climate over periods of a few years to several decades. Currently, rich hydrologic time-series data are available, but the combination of data preparation and statistical methods developed by the U.S. Geological Survey as part of the Groundwater Resources Program is relatively unavailable to hydrologists and engineers who could benefit from estimates of climate variability and its effects on periodic recharge and water-resource availability. This report documents HydroClimATe, a computer program for assessing the relations between variable climatic and hydrologic time-series data. HydroClimATe was developed for a Windows operating system. The software includes statistical tools for (1) time-series preprocessing, (2) spectral analysis, (3) spatial and temporal analysis, (4) correlation analysis, and (5) projections. The time-series preprocessing tools include spline fitting, standardization using a normal or gamma distribution, and transformation by a cumulative departure. The spectral analysis tools include discrete Fourier transform, maximum entropy method, and singular spectrum analysis. The spatial and temporal analysis tool is empirical orthogonal function analysis. The correlation analysis tools are linear regression and lag correlation. The projection tools include autoregressive time-series modeling and generation of many realizations. These tools are demonstrated in four examples that use stream-flow discharge data, groundwater-level records, gridded time series of precipitation data, and the Multivariate ENSO Index.

A LISREL Model for the Analysis of Repeated Measures with a Patterned Covariance Matrix.

ERIC Educational Resources Information Center

Rovine, Michael J.; Molenaar, Peter C. M.

1998-01-01

Presents a LISREL model for the estimation of the repeated measures analysis of variance (ANOVA) with a patterned covariance matrix. The model is demonstrated for a 5 x 2 (Time x Group) ANOVA in which the data are assumed to be serially correlated. Similarities with the Statistical Analysis System PROC MIXED model are discussed. (SLD)

Noise induced hearing loss of forest workers in Turkey.

PubMed

Tunay, M; Melemez, K

2008-09-01

In this study, a total number of 114 workers who were in 3 different groups in terms of age and work underwent audiometric analysis. In order to determine whether there was a statistically significant difference between the hearing loss levels of the workers who were included in the study, variance analysis was applied with the help of the data obtained as a result of the evaluation. Correlation and regression analysis were applied in order to determine the relations between hearing loss and their age and their time of work. As a result of the variance analysis, statistically significant differences were found at 500, 2000 and 4000 Hz frequencies. The most specific difference was observed among chainsaw machine operators at 4000 Hz frequency, which was determined by the variance analysis. As a result of the correlation analysis, significant relations were found between time of work and hearing loss in 0.01 confidence level and between age and hearing loss in 0.05 confidence level. Forest workers using chainsaw machines should be informed, they should wear or use protective materials and less noising chainsaw machines should be used if possible and workers should undergo audiometric tests when they start work and once a year.

Rasch analysis of three dry eye questionnaires and correlates with objective clinical tests.

PubMed

McAlinden, Colm; Gao, Rongrong; Wang, Qinmei; Zhu, Senmiao; Yang, Jing; Yu, Ayong; Bron, Anthony J; Huang, Jinhai

2017-04-01

To assess the psychometric properties of Chinese versions of the Ocular Comfort Index (OCI), Ocular Surface Disease Index (OSDI) and McMonnies questionnaires. Further, to assess the correlation between questionnaire scores and objective dry eye disease (DED) clinical tests. Translated versions of the OCI, OSDI and McMonnies questionnaires were completed in a random order by 238 participants with DED. Objective clinical tests included visual acuity (VA), fluorescein tear film break-up time (TBUT), corneal fluorescein staining, Schirmer I testing and meibomian gland grading. Rasch analysis was used to assess questionnaire psychometrics and spearman rank for correlations. For the OCI, the person separation was 2.31, item infit and outfit statistics ranged from 0.74-1.14 and 0.75-1.32, respectively, and targeting 1.54 logits. For the OSDI, person separation was 0.94. None of the three subscales provided valid measurements based on Rasch analysis. For the McMonnies questionnaire, person separation was 1.17, item infit and outfit statistics ranged from 0.7 to 1.21 and 0.51-3.49, respectively. There were weak correlations between questionnaire scores and clinical tests. There were weak correlations between OSDI scores and VA, fluorescein TBUT, Schirmer I testing and corneal fluorescein staining. There were weak correlations between McMonnies scores and VA, fluorescein TBUT, Schirmer I testing, and corneal fluorescein staining and meibomian gland grading. The OCI questionnaire was the only questionnaire that provided valid measurement on the basis of Rasch analysis, although slight multidimensionality was found. There were weak correlations between OCI scores and fluorescein TBUT, Schirmer I testing, and corneal fluorescein staining. Due to this paradoxical disconnect between symptoms and signs and the repeatability of tests, the use of both subjective and objective markers in the clinical management of patients or as endpoints in clinical trials would appear prudent. Copyright © 2017 Elsevier Inc. All rights reserved.

Orthotopic bladder substitution in men revisited: identification of continence predictors.

PubMed

Koraitim, M M; Atta, M A; Foda, M K

2006-11-01

We determined the impact of the functional characteristics of the neobladder and urethral sphincter on continence results, and determined the most significant predictors of continence. A total of 88 male patients 29 to 70 years old underwent orthotopic bladder substitution with tubularized ileocecal segment (40) and detubularized sigmoid (25) or ileum (23). Uroflowmetry, cystometry and urethral pressure profilometry were performed at 13 to 36 months (mean 19) postoperatively. The correlation between urinary continence and 28 urodynamic variables was assessed. Parameters that correlated significantly with continence were entered into a multivariate analysis using a logistic regression model to determine the most significant predictors of continence. Maximum urethral closure pressure was the only parameter that showed a statistically significant correlation with diurnal continence. Nocturnal continence had not only a statistically significant positive correlation with maximum urethral closure pressure, but also statistically significant negative correlations with maximum contraction amplitude, and baseline pressure at mid and maximum capacity. Three of these 4 parameters, including maximum urethral closure pressure, maximum contraction amplitude and baseline pressure at mid capacity, proved to be significant predictors of continence on multivariate analysis. While daytime continence is determined by maximum urethral closure pressure, during the night it is the net result of 2 forces that have about equal influence but in opposite directions, that is maximum urethral closure pressure vs maximum contraction amplitude plus baseline pressure at mid capacity. Two equations were derived from the logistic regression model to predict the probability of continence after orthotopic bladder substitution, including Z1 (diurnal) = 0.605 + 0.0085 maximum urethral closure pressure and Z2 (nocturnal) = 0.841 + 0.01 [maximum urethral closure pressure - (maximum contraction amplitude + baseline pressure at mid capacity)].

Distributed lags time series analysis versus linear correlation analysis (Pearson's r) in identifying the relationship between antipseudomonal antibiotic consumption and the susceptibility of Pseudomonas aeruginosa isolates in a single Intensive Care Unit of a tertiary hospital.

PubMed

Erdeljić, Viktorija; Francetić, Igor; Bošnjak, Zrinka; Budimir, Ana; Kalenić, Smilja; Bielen, Luka; Makar-Aušperger, Ksenija; Likić, Robert

2011-05-01

The relationship between antibiotic consumption and selection of resistant strains has been studied mainly by employing conventional statistical methods. A time delay in effect must be anticipated and this has rarely been taken into account in previous studies. Therefore, distributed lags time series analysis and simple linear correlation were compared in their ability to evaluate this relationship. Data on monthly antibiotic consumption for ciprofloxacin, piperacillin/tazobactam, carbapenems and cefepime as well as Pseudomonas aeruginosa susceptibility were retrospectively collected for the period April 2006 to July 2007. Using distributed lags analysis, a significant temporal relationship was identified between ciprofloxacin, meropenem and cefepime consumption and the resistance rates of P. aeruginosa isolates to these antibiotics. This effect was lagged for ciprofloxacin and cefepime [1 month (R=0.827, P=0.039) and 2 months (R=0.962, P=0.001), respectively] and was simultaneous for meropenem (lag 0, R=0.876, P=0.002). Furthermore, a significant concomitant effect of meropenem consumption on the appearance of multidrug-resistant P. aeruginosa strains (resistant to three or more representatives of classes of antibiotics) was identified (lag 0, R=0.992, P<0.001). This effect was not delayed and it was therefore identified both by distributed lags analysis and the Pearson's correlation coefficient. Correlation coefficient analysis was not able to identify relationships between antibiotic consumption and bacterial resistance when the effect was delayed. These results indicate that the use of diverse statistical methods can yield significantly different results, thus leading to the introduction of possibly inappropriate infection control measures. Copyright © 2010 Elsevier B.V. and the International Society of Chemotherapy. All rights reserved.

Analysis of Superintendent Longevity in Large School Districts: A Qualitative Study

ERIC Educational Resources Information Center

Mouton, Nikki Golar

2013-01-01

School district leadership matters, as evidenced by a meta-analysis of 27 reports and 1,210 districts conducted by Waters and Marzano (2006) which highlights a statistically significant correlation between district leadership and student achievement. Because this relationship is significant, it is important for school districts to have effective…

Statistical analysis of dynamic fibrils observed from NST/BBSO observations

NASA Astrophysics Data System (ADS)

Gopalan Priya, Thambaje; Su, Jiang-Tao; Chen, Jie; Deng, Yuan-Yong; Prasad Choudhury, Debi

2018-02-01

We present the results obtained from the analysis of dynamic fibrils in NOAA active region (AR) 12132, using high resolution Hα observations from the New Solar Telescope operating at Big Bear Solar Observatory. The dynamic fibrils are seen to be moving up and down, and most of these dynamic fibrils are periodic and have a jet-like appearance. We found from our observations that the fibrils follow almost perfect parabolic paths in many cases. A statistical analysis on the properties of the parabolic paths showing an analysis on deceleration, maximum velocity, duration and kinetic energy of these fibrils is presented here. We found the average maximum velocity to be around 15 kms‑1 and mean deceleration to be around 100 ms‑2. The observed deceleration appears to be a fraction of gravity of the Sun and is not compatible with the path of ballistic motion due to gravity of the Sun. We found a positive correlation between deceleration and maximum velocity. This correlation is consistent with simulations done earlier on magnetoacoustic shock waves propagating upward.

Evaluating measurement models in clinical research: covariance structure analysis of latent variable models of self-conception.

PubMed

Hoyle, R H

1991-02-01

Indirect measures of psychological constructs are vital to clinical research. On occasion, however, the meaning of indirect measures of psychological constructs is obfuscated by statistical procedures that do not account for the complex relations between items and latent variables and among latent variables. Covariance structure analysis (CSA) is a statistical procedure for testing hypotheses about the relations among items that indirectly measure a psychological construct and relations among psychological constructs. This article introduces clinical researchers to the strengths and limitations of CSA as a statistical procedure for conceiving and testing structural hypotheses that are not tested adequately with other statistical procedures. The article is organized around two empirical examples that illustrate the use of CSA for evaluating measurement models with correlated error terms, higher-order factors, and measured and latent variables.

A novel coefficient for detecting and quantifying asymmetry of California electricity market based on asymmetric detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Wang, Fang

2016-06-01

In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρ D X A , contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.

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.

A five year review of paediatric burns and social deprivation: Is there a link?

PubMed

Richards, Helen; Kokocinska, Maria; Lewis, Darren

2017-09-01

To establish if there is a correlation between burn incidence and social deprivation in order to formulate a more effective burns prevention strategy. A quantitative retrospective review of International Burn Injury Database (IBID) was carried out over a period from 2006 to 2011 to obtain data for children referred to our burns centre in West Midlands. Social deprivation scores for geographical areas were obtained from Office of National Statistics (ONS). Statistical analysis was carried out using Graphpad Prism. 1688 children were reviewed at our burns centre. Statistical analysis using Pearson correlation coefficient showed a slight association between social deprivation and increasing burn incidence r 2 =0.1268, 95% confidence interval 0.018-0.219, p value<0.0001. There was a slight male preponderance (58%). The most common mechanism of injury was scalding (61%). The most commonly affected age group were 1-2 year olds (38%). There were statistically significant differences in the ethnicity of children with significantly more children from Asian and African backgrounds being referred compared to Caucasian children. We found that appropriate first aid was administered in 67% of cases overall. We did not find a statistically significant link between first aid provision and social deprivation score. There was only a slight positive correlation between social deprivation and burn incidence. However, there did not seem to be any change in mechanism of burn in the most deprived groups compared to overall pattern, nor was there a significant difference in appropriate first aid provision. It would seem that dissemination of burn prevention strategies and first aid advice need to be improved across all geographical areas as this was uniformly lacking and the increased burn incidence in more socially deprived groups, although present, was not statistically significant. Copyright © 2017 Elsevier Ltd and ISBI. All rights reserved.

Statistical analysis of aerosol species, trace gasses, and meteorology in Chicago.

PubMed

Binaku, Katrina; O'Brien, Timothy; Schmeling, Martina; Fosco, Tinamarie

2013-09-01

Both canonical correlation analysis (CCA) and principal component analysis (PCA) were applied to atmospheric aerosol and trace gas concentrations and meteorological data collected in Chicago during the summer months of 2002, 2003, and 2004. Concentrations of ammonium, calcium, nitrate, sulfate, and oxalate particulate matter, as well as, meteorological parameters temperature, wind speed, wind direction, and humidity were subjected to CCA and PCA. Ozone and nitrogen oxide mixing ratios were also included in the data set. The purpose of statistical analysis was to determine the extent of existing linear relationship(s), or lack thereof, between meteorological parameters and pollutant concentrations in addition to reducing dimensionality of the original data to determine sources of pollutants. In CCA, the first three canonical variate pairs derived were statistically significant at the 0.05 level. Canonical correlation between the first canonical variate pair was 0.821, while correlations of the second and third canonical variate pairs were 0.562 and 0.461, respectively. The first canonical variate pair indicated that increasing temperatures resulted in high ozone mixing ratios, while the second canonical variate pair showed wind speed and humidity's influence on local ammonium concentrations. No new information was uncovered in the third variate pair. Canonical loadings were also interpreted for information regarding relationships between data sets. Four principal components (PCs), expressing 77.0 % of original data variance, were derived in PCA. Interpretation of PCs suggested significant production and/or transport of secondary aerosols in the region (PC1). Furthermore, photochemical production of ozone and wind speed's influence on pollutants were expressed (PC2) along with overall measure of local meteorology (PC3). In summary, CCA and PCA results combined were successful in uncovering linear relationships between meteorology and air pollutants in Chicago and aided in determining possible pollutant sources.

Prevalence of upper airway obstruction in patients with apparently asymptomatic euthyroid multi nodular goitre

PubMed Central

Menon, Sunil K.; Jagtap, Varsha S.; Sarathi, Vijaya; Lila, Anurag R.; Bandgar, Tushar R.; Menon, Padmavathy S; Shah, Nalini S.

2011-01-01

Aims: To study the prevalence of upper airway obstruction (UAO) in “apparently asymptomatic” patients with euthyroid multinodular goitre (MNG) and find correlation between clinical features, UAO on pulmonary function test (PFT) and tracheal narrowing on computerised tomography (CT). Materials and Methods: Consecutive patients with apparently asymptomatic euthyroid MNG attending thyroid clinic in a tertiary centre underwent clinical examination to elicit features of UAO, PFT, and CT of neck and chest. Statistical Analysis Used: Statistical analysis was done with SPSS version 11.5 using paired t-test, Chi square test, and Fisher's exact test. P value of <0.05 was considered to be significant. Results: Fifty-six patients (52 females and four males) were studied. The prevalence of UAO (PFT) and significant tracheal narrowing (CT) was 14.3%. and 9.3%, respectively. Clinical features failed to predict UAO or significant tracheal narrowing. Tracheal narrowing (CT) did not correlate with UAO (PFT). Volume of goitre significantly correlated with degree of tracheal narrowing. Conclusions: Clinical features do not predict UAO on PFT or tracheal narrowing on CT in apparently asymptomatic patients with euthyroid MNG. PMID:21966649

A quantitative study of factors influencing quality of life in rural Mexican women diagnosed with HIV.

PubMed

Holtz, Carol; Sowell, Richard; VanBrackle, Lewis; Velasquez, Gabriela; Hernandez-Alonso, Virginia

2014-01-01

This quantitative study explored the level of Quality of Life (QoL) in indigenous Mexican women and identified psychosocial factors that significantly influenced their QoL, using face-to-face interviews with 101 women accessing care in an HIV clinic in Oaxaca, Mexico. Variables included demographic characteristics, levels of depression, coping style, family functioning, HIV-related beliefs, and QoL. Descriptive statistics were used to analyze participant characteristics, and women's scores on data collection instruments. Pearson's R correlational statistics were used to determine the level of significance between study variables. Multiple regression analysis examined all variables that were significantly related to QoL. Pearson's correlational analysis of relationships between Spirituality, Educating Self about HIV, Family Functioning, Emotional Support, Physical Care, and Staying Positive demonstrated positive correlation to QoL. Stigma, depression, and avoidance coping were significantly and negatively associated with QoL. The final regression model indicated that depression and avoidance coping were the best predictor variables for QoL. Copyright © 2014 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

An Analysis LANDSAT-4 Thematic Mapper Geometric Properties

NASA Technical Reports Server (NTRS)

Walker, R. E.; Zobrist, A. L.; Bryant, N. A.; Gokhman, B.; Friedman, S. Z.; Logan, T. L.

1984-01-01

LANDSAT Thematic Mapper P-data of Washington, D. C., Harrisburg, PA, and Salton Sea, CA are analyzed to determine magnitudes and causes of error in the geometric conformity of the data to known Earth surface geometry. Several tests of data geometry are performed. Intraband and interband correlation and registration are investigated, exclusive of map based ground truth. The magnitudes and statistical trends of pixel offsets between a single band's mirror scans (due to processing procedures) are computed, and the inter-band integrity of registration is analyzed. A line to line correlation analysis is included.

Cross ranking of cities and regions: population versus income

NASA Astrophysics Data System (ADS)

Cerqueti, Roy; Ausloos, Marcel

2015-07-01

This paper explores the relationship between the inner economical structure of communities and their population distribution through a rank-rank analysis of official data, along statistical physics ideas within two techniques. The data is taken on Italian cities. The analysis is performed both at a global (national) and at a more local (regional) level in order to distinguish ‘macro’ and ‘micro’ aspects. First, the rank-size rule is found not to be a standard power law, as in many other studies, but a doubly decreasing power law. Next, the Kendall τ and the Spearman ρ rank correlation coefficients which measure pair concordance and the correlation between fluctuations in two rankings, respectively,—as a correlation function does in thermodynamics, are calculated for finding rank correlation (if any) between demography and wealth. Results show non only global disparities for the whole (country) set, but also (regional) disparities, when comparing the number of cities in regions, the number of inhabitants in cities and that in regions, as well as when comparing the aggregated tax income of the cities and that of regions. Different outliers are pointed out and justified. Interestingly, two classes of cities in the country and two classes of regions in the country are found. ‘Common sense’ social, political, and economic considerations sustain the findings. More importantly, the methods show that they allow to distinguish communities, very clearly, when specific criteria are numerically sound. A specific modeling for the findings is presented, i.e. for the doubly decreasing power law and the two phase system, based on statistics theory, e.g. urn filling. The model ideas can be expected to hold when similar rank relationship features are observed in fields. It is emphasized that the analysis makes more sense than one through a Pearson Π value-value correlation analysis

A model for predicting sulcus-to-sulcus diameter in posterior chamber phakic intraocular lens candidates: correlation between ocular biometric parameters.

PubMed

Ghoreishi, Mohammad; Abdi-Shahshahani, Mehdi; Peyman, Alireza; Pourazizi, Mohsen

2018-02-21

The aim of this study was to determine the correlation between ocular biometric parameters and sulcus-to-sulcus (STS) diameter. This was a cross-sectional study of preoperative ocular biometry data of patients who were candidates for phakic intraocular lens (IOL) surgery. Subjects underwent ocular biometry analysis, including refraction error evaluation using an autorefractor and Orbscan topography for white-to-white (WTW) corneal diameter and measurement. Pentacam was used to perform WTW corneal diameter and measurements of minimum and maximum keratometry (K). Measurements of STS and angle-to-angle (ATA) were obtained using a 50-MHz B-mode ultrasound device. Anterior optical coherence tomography was performed for anterior chamber depth measurement. Pearson's correlation test and stepwise linear regression analysis were used to find a model to predict STS. Fifty-eight eyes of 58 patients were enrolled. Mean age ± standard deviation of sample was 28.95 ± 6.04 years. The Pearson's correlation coefficient between STS with WTW, ATA, mean K was 0.383, 0.492, and - 0.353, respectively, which was statistically significant (all P < 0.001). Using stepwise linear regression analysis, there is a statistically significant association between STS with WTW (P = 0.011) and mean K (P = 0.025). The standardized coefficient was 0.323 and - 0.284 for WTW and mean K, respectively. The stepwise linear regression analysis equation was: (STS = 9.549 + 0.518 WTW - 0.083 mean K). Based on our result, given the correlation of STS with WTW and mean K and potential of direct and essay measurement of WTW and mean K, it seems that current IOL sizing protocols could be estimating with WTW and mean K.

A systematic review of statistical methods used to test for reliability of medical instruments measuring continuous variables.

PubMed

Zaki, Rafdzah; Bulgiba, Awang; Nordin, Noorhaire; Azina Ismail, Noor

2013-06-01

Reliability measures precision or the extent to which test results can be replicated. This is the first ever systematic review to identify statistical methods used to measure reliability of equipment measuring continuous variables. This studyalso aims to highlight the inappropriate statistical method used in the reliability analysis and its implication in the medical practice. In 2010, five electronic databases were searched between 2007 and 2009 to look for reliability studies. A total of 5,795 titles were initially identified. Only 282 titles were potentially related, and finally 42 fitted the inclusion criteria. The Intra-class Correlation Coefficient (ICC) is the most popular method with 25 (60%) studies having used this method followed by the comparing means (8 or 19%). Out of 25 studies using the ICC, only 7 (28%) reported the confidence intervals and types of ICC used. Most studies (71%) also tested the agreement of instruments. This study finds that the Intra-class Correlation Coefficient is the most popular method used to assess the reliability of medical instruments measuring continuous outcomes. There are also inappropriate applications and interpretations of statistical methods in some studies. It is important for medical researchers to be aware of this issue, and be able to correctly perform analysis in reliability studies.

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.

Multivariate two-part statistics for analysis of correlated mass spectrometry data from multiple biological specimens.

PubMed

Taylor, Sandra L; Ruhaak, L Renee; Weiss, Robert H; Kelly, Karen; Kim, Kyoungmi

2017-01-01

High through-put mass spectrometry (MS) is now being used to profile small molecular compounds across multiple biological sample types from the same subjects with the goal of leveraging information across biospecimens. Multivariate statistical methods that combine information from all biospecimens could be more powerful than the usual univariate analyses. However, missing values are common in MS data and imputation can impact between-biospecimen correlation and multivariate analysis results. We propose two multivariate two-part statistics that accommodate missing values and combine data from all biospecimens to identify differentially regulated compounds. Statistical significance is determined using a multivariate permutation null distribution. Relative to univariate tests, the multivariate procedures detected more significant compounds in three biological datasets. In a simulation study, we showed that multi-biospecimen testing procedures were more powerful than single-biospecimen methods when compounds are differentially regulated in multiple biospecimens but univariate methods can be more powerful if compounds are differentially regulated in only one biospecimen. We provide R functions to implement and illustrate our method as supplementary information CONTACT: sltaylor@ucdavis.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Exploring the Replicability of a Study's Results: Bootstrap Statistics for the Multivariate Case.

ERIC Educational Resources Information Center

Thompson, Bruce

1995-01-01

Use of the bootstrap method in a canonical correlation analysis to evaluate the replicability of a study's results is illustrated. More confidence may be vested in research results that replicate. (SLD)

Is There a Critical Distance for Fickian Transport? - a Statistical Approach to Sub-Fickian Transport Modelling in Porous Media

NASA Astrophysics Data System (ADS)

Most, S.; Nowak, W.; Bijeljic, B.

2014-12-01

Transport processes in porous media are frequently simulated as particle movement. This process can be formulated as a stochastic process of particle position increments. At the pore scale, the geometry and micro-heterogeneities prohibit the commonly made assumption of independent and normally distributed increments to represent dispersion. Many recent particle methods seek to loosen this assumption. Recent experimental data suggest that we have not yet reached the end of the need to generalize, because particle increments show statistical dependency beyond linear correlation and over many time steps. The goal of this work is to better understand the validity regions of commonly made assumptions. We are investigating after what transport distances can we observe: A statistical dependence between increments, that can be modelled as an order-k Markov process, boils down to order 1. This would be the Markovian distance for the process, where the validity of yet-unexplored non-Gaussian-but-Markovian random walks would start. A bivariate statistical dependence that simplifies to a multi-Gaussian dependence based on simple linear correlation (validity of correlated PTRW). Complete absence of statistical dependence (validity of classical PTRW/CTRW). The approach is to derive a statistical model for pore-scale transport from a powerful experimental data set via copula analysis. The model is formulated as a non-Gaussian, mutually dependent Markov process of higher order, which allows us to investigate the validity ranges of simpler models.

Statistical properties of the radiation belt seed population

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

Boyd, A. J.; Spence, H. E.; Huang, C. -L.

Here, we present a statistical analysis of phase space density data from the first 26 months of the Van Allen Probes mission. In particular, we investigate the relationship between the tens and hundreds of keV seed electrons and >1 MeV core radiation belt electron population. Using a cross-correlation analysis, we find that the seed and core populations are well correlated with a coefficient of ≈0.73 with a time lag of 10–15 h. We present evidence of a seed population threshold that is necessary for subsequent acceleration. The depth of penetration of the seed population determines the inner boundary of themore » acceleration process. However, we show that an enhanced seed population alone is not enough to produce acceleration in the higher energies, implying that the seed population of hundreds of keV electrons is only one of several conditions required for MeV electron radiation belt acceleration.« less

Statistical properties of the radiation belt seed population

DOE PAGES

Boyd, A. J.; Spence, H. E.; Huang, C. -L.; ...

2016-07-25

Here, we present a statistical analysis of phase space density data from the first 26 months of the Van Allen Probes mission. In particular, we investigate the relationship between the tens and hundreds of keV seed electrons and >1 MeV core radiation belt electron population. Using a cross-correlation analysis, we find that the seed and core populations are well correlated with a coefficient of ≈0.73 with a time lag of 10–15 h. We present evidence of a seed population threshold that is necessary for subsequent acceleration. The depth of penetration of the seed population determines the inner boundary of themore » acceleration process. However, we show that an enhanced seed population alone is not enough to produce acceleration in the higher energies, implying that the seed population of hundreds of keV electrons is only one of several conditions required for MeV electron radiation belt acceleration.« less

Smoking-Related Knowledge, Attitudes, Behaviors, Smoking Cessation Idea and Education Level among Young Adult Male Smokers in Chongqing, China

PubMed Central

Xu, Xianglong; Liu, Lingli; Sharma, Manoj; Zhao, Yong

2015-01-01

Introduction: In 2012 in China, 52.9% of men were reported to smoke while only 2.4% of women smoked. This study explored the smoking-related Knowledge, Attitudes and Practices (KAP) among young adult male smokers. Methods: A cross-sectional study was conducted in four municipal areas of Chongqing using a questionnaire administered to 536 natives young male smokers aged 18–45 years old. Results: The total score of smoking cognition, the total score of smoking attitude and the total score of positive behavior to quit smoking was significantly different among the three groups by education. Besides, 30.97% of male smokers never seriously thought about quitting smoking. Logistic regression analysis found smoking-related knowledge, attitudes, behaviors and sociodemographic factors affect having smoking cessation idea. But no statistically significant correlation was observed between smoking cognition and positive behavior to quit smoking in a sample of higher education. No statistically significant correlation was observed between smoking cognition and positive behavior to quit smoking (Pearson correlation coefficient = 0.03012, p = 0.6811), and also no statistically significant correlation was observed between smoking cognition and positive behavior to quit smoking (Pearson correlation coefficient = 0.08869, p = 0.2364)  in the sample of higher education young adult males Conclusions: Young adult males with higher education have a better knowledge of smoking hazards and a more positive attitude toward smoking, however, this knowledge and attitude do not necessarily translate into health behavioral outcomes such as not smoking. Overall the present findings indicate that no statistically significant correlation between the education level and quitting smoking idea exists among young adult male smokers in China. This survey gives a snapshot of the impact of education on smoking-related KAP among young adults male smokers. PMID:25689992

Smoking-related knowledge, attitudes, behaviors, smoking cessation idea and education level among young adult male smokers in Chongqing, China.

PubMed

Xu, Xianglong; Liu, Lingli; Sharma, Manoj; Zhao, Yong

2015-02-16

In 2012 in China, 52.9% of men were reported to smoke while only 2.4% of women smoked. This study explored the smoking-related Knowledge, Attitudes and Practices (KAP) among young adult male smokers. A cross-sectional study was conducted in four municipal areas of Chongqing using a questionnaire administered to 536 natives young male smokers aged 18-45 years old. The total score of smoking cognition, the total score of smoking attitude and the total score of positive behavior to quit smoking was significantly different among the three groups by education. Besides, 30.97% of male smokers never seriously thought about quitting smoking. Logistic regression analysis found smoking-related knowledge, attitudes, behaviors and sociodemographic factors affect having smoking cessation idea. But no statistically significant correlation was observed between smoking cognition and positive behavior to quit smoking in a sample of higher education. No statistically significant correlation was observed between smoking cognition and positive behavior to quit smoking (Pearson correlation coefficient = 0.03012, p = 0.6811), and also no statistically significant correlation was observed between smoking cognition and positive behavior to quit smoking (Pearson correlation coefficient = 0.08869, p = 0.2364) in the sample of higher education young adult males Young adult males with higher education have a better knowledge of smoking hazards and a more positive attitude toward smoking, however, this knowledge and attitude do not necessarily translate into health behavioral outcomes such as not smoking. Overall the present findings indicate that no statistically significant correlation between the education level and quitting smoking idea exists among young adult male smokers in China. This survey gives a snapshot of the impact of education on smoking-related KAP among young adults male smokers.

The Fusion of Financial Analysis and Seismology: Statistical Methods from Financial Market Analysis Applied to Earthquake Data

NASA Astrophysics Data System (ADS)

Ohyanagi, S.; Dileonardo, C.

2013-12-01

As a natural phenomenon earthquake occurrence is difficult to predict. Statistical analysis of earthquake data was performed using candlestick chart and Bollinger Band methods. These statistical methods, commonly used in the financial world to analyze market trends were tested against earthquake data. Earthquakes above Mw 4.0 located on shore of Sanriku (37.75°N ~ 41.00°N, 143.00°E ~ 144.50°E) from February 1973 to May 2013 were selected for analysis. Two specific patterns in earthquake occurrence were recognized through the analysis. One is a spread of candlestick prior to the occurrence of events greater than Mw 6.0. A second pattern shows convergence in the Bollinger Band, which implies a positive or negative change in the trend of earthquakes. Both patterns match general models for the buildup and release of strain through the earthquake cycle, and agree with both the characteristics of the candlestick chart and Bollinger Band analysis. These results show there is a high correlation between patterns in earthquake occurrence and trend analysis by these two statistical methods. The results of this study agree with the appropriateness of the application of these financial analysis methods to the analysis of earthquake occurrence.

Statistical inference of dynamic resting-state functional connectivity using hierarchical observation modeling.

PubMed

Sojoudi, Alireza; Goodyear, Bradley G

2016-12-01

Spontaneous fluctuations of blood-oxygenation level-dependent functional magnetic resonance imaging (BOLD fMRI) signals are highly synchronous between brain regions that serve similar functions. This provides a means to investigate functional networks; however, most analysis techniques assume functional connections are constant over time. This may be problematic in the case of neurological disease, where functional connections may be highly variable. Recently, several methods have been proposed to determine moment-to-moment changes in the strength of functional connections over an imaging session (so called dynamic connectivity). Here a novel analysis framework based on a hierarchical observation modeling approach was proposed, to permit statistical inference of the presence of dynamic connectivity. A two-level linear model composed of overlapping sliding windows of fMRI signals, incorporating the fact that overlapping windows are not independent was described. To test this approach, datasets were synthesized whereby functional connectivity was either constant (significant or insignificant) or modulated by an external input. The method successfully determines the statistical significance of a functional connection in phase with the modulation, and it exhibits greater sensitivity and specificity in detecting regions with variable connectivity, when compared with sliding-window correlation analysis. For real data, this technique possesses greater reproducibility and provides a more discriminative estimate of dynamic connectivity than sliding-window correlation analysis. Hum Brain Mapp 37:4566-4580, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Long-Range Temporal Correlations, Multifractality, and the Causal Relation between Neural Inputs and Movements

PubMed Central

Hu, Jing; Zheng, Yi; Gao, Jianbo

2013-01-01

Understanding the causal relation between neural inputs and movements is very important for the success of brain-machine interfaces (BMIs). In this study, we analyze 104 neurons’ firings using statistical, information theoretic, and fractal analysis. The latter include Fano factor analysis, multifractal adaptive fractal analysis (MF-AFA), and wavelet multifractal analysis. We find neuronal firings are highly non-stationary, and Fano factor analysis always indicates long-range correlations in neuronal firings, irrespective of whether those firings are correlated with movement trajectory or not, and thus does not reveal any actual correlations between neural inputs and movements. On the other hand, MF-AFA and wavelet multifractal analysis clearly indicate that when neuronal firings are not well correlated with movement trajectory, they do not have or only have weak temporal correlations. When neuronal firings are well correlated with movements, they are characterized by very strong temporal correlations, up to a time scale comparable to the average time between two successive reaching tasks. This suggests that neurons well correlated with hand trajectory experienced a “re-setting” effect at the start of each reaching task, in the sense that within the movement correlated neurons the spike trains’ long-range dependences persisted about the length of time the monkey used to switch between task executions. A new task execution re-sets their activity, making them only weakly correlated with their prior activities on longer time scales. We further discuss the significance of the coalition of those important neurons in executing cortical control of prostheses. PMID:24130549

Statistical Determination of Rainfall-Runoff Erosivity Indices for Single Storms in the Chinese Loess Plateau

PubMed Central

Zheng, Mingguo; Chen, Xiaoan

2015-01-01

Correlation analysis is popular in erosion- or earth-related studies, however, few studies compare correlations on a basis of statistical testing, which should be conducted to determine the statistical significance of the observed sample difference. This study aims to statistically determine the erosivity index of single storms, which requires comparison of a large number of dependent correlations between rainfall-runoff factors and soil loss, in the Chinese Loess Plateau. Data observed at four gauging stations and five runoff experimental plots were presented. Based on the Meng’s tests, which is widely used for comparing correlations between a dependent variable and a set of independent variables, two methods were proposed. The first method removes factors that are poorly correlated with soil loss from consideration in a stepwise way, while the second method performs pairwise comparisons that are adjusted using the Bonferroni correction. Among 12 rainfall factors, I 30 (the maximum 30-minute rainfall intensity) has been suggested for use as the rainfall erosivity index, although I 30 is equally correlated with soil loss as factors of I 20, EI 10 (the product of the rainfall kinetic energy, E, and I 10), EI 20 and EI 30 are. Runoff depth (total runoff volume normalized to drainage area) is more correlated with soil loss than all other examined rainfall-runoff factors, including I 30, peak discharge and many combined factors. Moreover, sediment concentrations of major sediment-producing events are independent of all examined rainfall-runoff factors. As a result, introducing additional factors adds little to the prediction accuracy of the single factor of runoff depth. Hence, runoff depth should be the best erosivity index at scales from plots to watersheds. Our findings can facilitate predictions of soil erosion in the Loess Plateau. Our methods provide a valuable tool while determining the predictor among a number of variables in terms of correlations. PMID:25781173

Statistical determination of rainfall-runoff erosivity indices for single storms in the Chinese Loess Plateau.

PubMed

Zheng, Mingguo; Chen, Xiaoan

2015-01-01

Correlation analysis is popular in erosion- or earth-related studies, however, few studies compare correlations on a basis of statistical testing, which should be conducted to determine the statistical significance of the observed sample difference. This study aims to statistically determine the erosivity index of single storms, which requires comparison of a large number of dependent correlations between rainfall-runoff factors and soil loss, in the Chinese Loess Plateau. Data observed at four gauging stations and five runoff experimental plots were presented. Based on the Meng's tests, which is widely used for comparing correlations between a dependent variable and a set of independent variables, two methods were proposed. The first method removes factors that are poorly correlated with soil loss from consideration in a stepwise way, while the second method performs pairwise comparisons that are adjusted using the Bonferroni correction. Among 12 rainfall factors, I30 (the maximum 30-minute rainfall intensity) has been suggested for use as the rainfall erosivity index, although I30 is equally correlated with soil loss as factors of I20, EI10 (the product of the rainfall kinetic energy, E, and I10), EI20 and EI30 are. Runoff depth (total runoff volume normalized to drainage area) is more correlated with soil loss than all other examined rainfall-runoff factors, including I30, peak discharge and many combined factors. Moreover, sediment concentrations of major sediment-producing events are independent of all examined rainfall-runoff factors. As a result, introducing additional factors adds little to the prediction accuracy of the single factor of runoff depth. Hence, runoff depth should be the best erosivity index at scales from plots to watersheds. Our findings can facilitate predictions of soil erosion in the Loess Plateau. Our methods provide a valuable tool while determining the predictor among a number of variables in terms of correlations.

GOEAST: a web-based software toolkit for Gene Ontology enrichment analysis.

PubMed

Zheng, Qi; Wang, Xiu-Jie

2008-07-01

Gene Ontology (GO) analysis has become a commonly used approach for functional studies of large-scale genomic or transcriptomic data. Although there have been a lot of software with GO-related analysis functions, new tools are still needed to meet the requirements for data generated by newly developed technologies or for advanced analysis purpose. Here, we present a Gene Ontology Enrichment Analysis Software Toolkit (GOEAST), an easy-to-use web-based toolkit that identifies statistically overrepresented GO terms within given gene sets. Compared with available GO analysis tools, GOEAST has the following improved features: (i) GOEAST displays enriched GO terms in graphical format according to their relationships in the hierarchical tree of each GO category (biological process, molecular function and cellular component), therefore, provides better understanding of the correlations among enriched GO terms; (ii) GOEAST supports analysis for data from various sources (probe or probe set IDs of Affymetrix, Illumina, Agilent or customized microarrays, as well as different gene identifiers) and multiple species (about 60 prokaryote and eukaryote species); (iii) One unique feature of GOEAST is to allow cross comparison of the GO enrichment status of multiple experiments to identify functional correlations among them. GOEAST also provides rigorous statistical tests to enhance the reliability of analysis results. GOEAST is freely accessible at http://omicslab.genetics.ac.cn/GOEAST/

Cross-correlation earthquake precursors in the hydrogeochemical and geoacoustic signals for the Kamchatka peninsula

NASA Astrophysics Data System (ADS)

Ryabinin, Gennadiy; Gavrilov, Valeriy; Polyakov, Yuriy; Timashev, Serge

2012-06-01

We propose a new type of earthquake precursor based on the analysis of correlation dynamics between geophysical signals of different nature. The precursor is found using a two-parameter cross-correlation function introduced within the framework of flicker-noise spectroscopy, a general statistical physics approach to the analysis of time series. We consider an example of cross-correlation analysis for water salinity time series, an integral characteristic of the chemical composition of groundwater, and geoacoustic emissions recorded at the G-1 borehole on the Kamchatka peninsula in the time frame from 2001 to 2003, which is characterized by a sequence of three groups of significant seismic events. We found that cross-correlation precursors took place 27, 31, and 35 days ahead of the strongest earthquakes for each group of seismic events, respectively. At the same time, precursory anomalies in the signals themselves were observed only in the geoacoustic emissions for one group of earthquakes.

Tests of Mediation: Paradoxical Decline in Statistical Power as a Function of Mediator Collinearity

PubMed Central

Beasley, T. Mark

2013-01-01

Increasing the correlation between the independent variable and the mediator (a coefficient) increases the effect size (ab) for mediation analysis; however, increasing a by definition increases collinearity in mediation models. As a result, the standard error of product tests increase. The variance inflation due to increases in a at some point outweighs the increase of the effect size (ab) and results in a loss of statistical power. This phenomenon also occurs with nonparametric bootstrapping approaches because the variance of the bootstrap distribution of ab approximates the variance expected from normal theory. Both variances increase dramatically when a exceeds the b coefficient, thus explaining the power decline with increases in a. Implications for statistical analysis and applied researchers are discussed. PMID:24954952

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.

Analysis strategies for longitudinal attachment loss data.

PubMed

Beck, J D; Elter, J R

2000-02-01

The purpose of this invited review is to describe and discuss methods currently in use to quantify the progression of attachment loss in epidemiological studies of periodontal disease, and to make recommendations for specific analytic methods based upon the particular design of the study and structure of the data. The review concentrates on the definition of incident attachment loss (ALOSS) and its component parts; measurement issues including thresholds and regression to the mean; methods of accounting for longitudinal change, including changes in means, changes in proportions of affected sites, incidence density, the effect of tooth loss and reversals, and repeated events; statistical models of longitudinal change, including the incorporation of the time element, use of linear, logistic or Poisson regression or survival analysis, and statistical tests; site vs person level of analysis, including statistical adjustment for correlated data; the strengths and limitations of ALOSS data. Examples from the Piedmont 65+ Dental Study are used to illustrate specific concepts. We conclude that incidence density is the preferred methodology to use for periodontal studies with more than one period of follow-up and that the use of studies not employing methods for dealing with complex samples, correlated data, and repeated measures does not take advantage of our current understanding of the site- and person-level variables important in periodontal disease and may generate biased results.

Statistical analysis of magnetically soft particles in magnetorheological elastomers

NASA Astrophysics Data System (ADS)

Gundermann, T.; Cremer, P.; Löwen, H.; Menzel, A. M.; Odenbach, S.

2017-04-01

The physical properties of magnetorheological elastomers (MRE) are a complex issue and can be influenced and controlled in many ways, e.g. by applying a magnetic field, by external mechanical stimuli, or by an electric potential. In general, the response of MRE materials to these stimuli is crucially dependent on the distribution of the magnetic particles inside the elastomer. Specific knowledge of the interactions between particles or particle clusters is of high relevance for understanding the macroscopic rheological properties and provides an important input for theoretical calculations. In order to gain a better insight into the correlation between the macroscopic effects and microstructure and to generate a database for theoretical analysis, x-ray micro-computed tomography (X-μCT) investigations as a base for a statistical analysis of the particle configurations were carried out. Different MREs with quantities of 2-15 wt% (0.27-2.3 vol%) of iron powder and different allocations of the particles inside the matrix were prepared. The X-μCT results were edited by an image processing software regarding the geometrical properties of the particles with and without the influence of an external magnetic field. Pair correlation functions for the positions of the particles inside the elastomer were calculated to statistically characterize the distributions of the particles in the samples.

Relationship between Hounsfield unit in CT scan and gray scale in CBCT

NASA Astrophysics Data System (ADS)

Kamaruddin, Noorshaida; Rajion, Zainul Ahmad; Yusof, Asilah; Aziz, Mohd Ezane

2016-12-01

Cone-beam computed tomography (CBCT) is an imaging system which has advantages over computed tomography (CT). Recently, CBCT has become widely used for oral and maxillofacial imaging. In CT scan, Hounsfield Unit (HU) is proportional to the degree of x-ray attenuation by the tissue. In CBCT, the degree of x-ray attenuation is shown by gray scale (voxel value). The aim of the present (in vitro) study was to investigate the relationship between gray scale in CBCT and HU in CT scan. In this descriptive study, the anthropomorphic head phantom was scanned with CBCT and CT scanner. Gray scales and HUs were detected on images at the crown of the teeth, trabecular and cortical bone of mandible. The images were analyzed to obtain the gray scale value and HU value. The obtained value then used to investigate the relationship between CBCT gray scales and HUs. For the statistical analysis, t-test, Pearson's correlation and regression analysis were used. The differences between the gray scale of CBCT and HU of CT were statistically not significant, whereas the Pearson's correlation coefficients demonstrated a statistically significant correlation between gray scale of CBCT and HU of CT values. Considering the fact that gray scale in CBCT is important in pre assessment evaluation of bone density before implant treatments, it is recommended because of the lower dose and cost compared to CT scan.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis.

PubMed

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-04

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c  = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

Relationship between climatic variables and the variation in bulk tank milk composition using canonical correlation analysis

NASA Astrophysics Data System (ADS)

Stürmer, Morgana; Busanello, Marcos; Velho, João Pedro; Heck, Vanessa Isabel; Haygert-Velho, Ione Maria Pereira

2018-06-01

A number of studies have addressed the relations between climatic variables and milk composition, but these works used univariate statistical approaches. In our study, we used a multivariate approach (canonical correlation) to study the impact of climatic variables on milk composition, price, and monthly milk production at a dairy farm using bulk tank milk data. Data on milk composition, price, and monthly milk production were obtained from a dairy company that purchased the milk from the farm, while climatic variable data were obtained from the National Institute of Meteorology (INMET). The data are from January 2014 to December 2016. Univariate correlation analysis and canonical correlation analysis were performed. Few correlations between the climatic variables and milk composition were found using a univariate approach. However, using canonical correlation analysis, we found a strong and significant correlation (r c = 0.95, p value = 0.0029). Lactose, ambient temperature measures (mean, minimum, and maximum), and temperature-humidity index (THI) were found to be the most important variables for the canonical correlation. Our study indicated that 10.2% of the variation in milk composition, pricing, and monthly milk production can be explained by climatic variables. Ambient temperature variables, together with THI, seem to have the most influence on variation in milk composition.

A report on the clinical-pathological correlations of 788 gingival lesion

PubMed Central

Carbone, Mario; Broccoletti, Roberto; Carcieri, Paola; Conrotto, Davide; Carrozzo, Marco; Arduino, Paolo G.

2017-01-01

Background The diagnosis and treatment of a variety of non-plaque related gingival diseases have become an integrated aspect of everyday dentistry. The aim of this study was to analyse the relationship between clinical appearance and histopathological features of gingival lesions in a large Northern Italian population. Material and Methods A retrospective study of 788 cases of gingival and alveolar mucosal biopsies was set up. Statistical analysis was performed by calculating the odds ratio and 95% confidence interval (C.I.), in order to assess the degree of association between the clinical parameters considered (primary lesions) and the single pathologies, statistically evaluated by Mantel-Haenszel tests. The correlation between clinical and histological diagnosis was classified as follow: 1) expected data (ED): provisional clinical diagnosis; 2) real data (RD): final histopathology diagnosis; 3) concordant data (CD): correspondence between the expected data and real data. The correlation was calculated as follow: CC (complete concordance) = CD x 100 / ED, this expressing the percentage in which the clinical and the histological diagnosis overlapped. Results The most frequently observed and biopsied primary lesions resulted to be exophytic, followed by mucosal colour changes and finally by losses of substance. The statistically significant association between primary lesion and their manifestation in gingival pathologies was reported. Volume increases, for instance, were positively correlated to plasma cell epulis, pyogenic granuloma, fibrous reactive hyperplasia and hemangioma. Verrucous-papillary lesions were most often seen in verrucous carcinoma, verrucous leukoplakia and mild dysplasia. White lesion resulted to be related to leukoplakia or oral lichen planus. Red lesions resulted to be related only oral lichen planus. Erosive vesicle-bullous lesions were linked to disimmune pathologies. Ulcerative lesions were positively associated to oral squamous cell cancer. Finally, potentially malignant disorders have the most percentage high concordance. Among the malignant lesions, the correlation increased up to the squamous cell carcinoma and leukaemia. Conclusions This article presented the frequency and the clinico-pathological concordance of all primary lesions and the histopathological diagnosis of gingival lesions. For every primary lesion, it is possible to correlate a specific histopathological diagnosis in a statistical manner. This can be a valuable aid for not specialist clinicians who daily observe mucosae and have the opportunity to intercept major diseases. Key words:Gingival lesions; clinical appearance; histological analysis; clinico-pathological correlation. PMID:29053652

The Minnesota Grading System Using Fundus Autofluorescence of Eye Bank Eyes: A Correlation To Age-Related Macular Degeneration (An AOS Thesis)

PubMed Central

Olsen, Timothy W.

2008-01-01

Purpose To establish a grading system of eye bank eyes using fundus autofluorescence (FAF) and identify a methodology that correlates FAF to age-related macular degeneration (AMD) with clinical correlation to the Age-Related Eye Disease Study (AREDS). Methods Two hundred sixty-two eye bank eyes were evaluated using a standardized analysis of FAF. Measurements were taken with the confocal scanning laser ophthalmoscope (cSLO). First, high-resolution, digital, stereoscopic, color images were obtained and graded according to AREDS criteria. With the neurosensory retina removed, mean FAF values were obtained from cSLO images using software analysis that excludes areas of atrophy and other artifact, generating an FAF value from a grading template. Age and AMD grade were compared to FAF values. An internal fluorescence reference standard was tested. Results Standardization of the cSLO machine demonstrated that reliable data could be acquired after a 1-hour warm-up. Images obtained prior to 1 hour had falsely elevated levels of FAF. In this initial analysis, there was no statistical correlation of age to mean FAF. There was a statistically significant decrease in FAF from AREDS grade 1, 2 to 3, 4 (P < .0001). An internal fluorescent standard may serve as a quantitative reference. Conclusions The Minnesota Grading System (MGS) of FAF (MGS-FAF) establishes a standardized methodology for grading eye bank tissue to quantify FAF compounds in the retinal pigment epithelium and correlate these findings to the AREDS. Future studies could then correlate specific FAF to the aging process, histopathology AMD phenotypes, and other maculopathies, as well as to analyze the biochemistry of autofluorescent fluorophores. PMID:19277247

The Minnesota Grading System using fundus autofluorescence of eye bank eyes: a correlation to age-related macular degeneration (an AOS thesis).

PubMed

Olsen, Timothy W

2008-01-01

To establish a grading system of eye bank eyes using fundus autofluorescence (FAF) and identify a methodology that correlates FAF to age-related macular degeneration (AMD) with clinical correlation to the Age-Related Eye Disease Study (AREDS). Two hundred sixty-two eye bank eyes were evaluated using a standardized analysis of FAF. Measurements were taken with the confocal scanning laser ophthalmoscope (cSLO). First, high-resolution, digital, stereoscopic, color images were obtained and graded according to AREDS criteria. With the neurosensory retina removed, mean FAF values were obtained from cSLO images using software analysis that excludes areas of atrophy and other artifact, generating an FAF value from a grading template. Age and AMD grade were compared to FAF values. An internal fluorescence reference standard was tested. Standardization of the cSLO machine demonstrated that reliable data could be acquired after a 1-hour warm-up. Images obtained prior to 1 hour had falsely elevated levels of FAF. In this initial analysis, there was no statistical correlation of age to mean FAF. There was a statistically significant decrease in FAF from AREDS grade 1, 2 to 3, 4 (P < .0001). An internal fluorescent standard may serve as a quantitative reference. The Minnesota Grading System (MGS) of FAF (MGS-FAF) establishes a standardized methodology for grading eye bank tissue to quantify FAF compounds in the retinal pigment epithelium and correlate these findings to the AREDS. Future studies could then correlate specific FAF to the aging process, histopathology AMD phenotypes, and other maculopathies, as well as to analyze the biochemistry of autofluorescent fluorophores.

[Expressions of EMMPRIN and its ligand CyPA in gingival crevicular fluid of chronic periodontitis patients].

PubMed

He, Yan-ping; Xie, Ming; Jiao, Ting

2016-02-01

To detect the expressions of EMMPRIN and its ligand CyPA in gingival crevicular fluid (GCF) of chronic periodontitis (CP) patients and explore their possible relation to the status of periodontal inflammation. GCF of CP patients (group CP) and periodontitis-free patients with intact dentition (the control group) were collected and assayed for EMMPRIN and CyPA expressions by ELISA. The clinical periodontal status of these patients were examined. Statistical analysis was performed by use of SPSS 17.0 software package. Spearman's correlation analysis was utilized to determine the relationships between the expressions of EMMPRIN and CyPA in GCF and the clinical parameters. In addition, analysis of variance (ANOVA) was used for comparing the difference between group CP and the control group. In group CP, GCF volume was positively correlated with EMMPRIN total amount, CyPA total amount and some clinical periodontal indexes (GI,SBI,AL). EMMPRIN total amount was positively correlated with GCF volume, CyPA total amount and some of clinical periodontal indexes (GI,SBI,AL), but it was negatively correlated with smoking status (P<0.05). Moreover, CyPA total amount was positively correlated with GCF volume, EMMPRIN total amount and some of clinical periodontal indexes (GI,SBI,AL). In the control group,there were significant positive correlations among GCF volume, EMMPRIN total amount and CyPA total amount. The difference of GCF, EMMPRIN and CyPA between the 2 groups were statistically significant (P<0.05). EMMPRIN and its ligand CyPA in GCF of periodontitis-free patients with intact dentition and CP patients were all detected. As the progress of periodontal inflammation, GCF secretion increases, as well as the expressions of EMMPRIN and CyPA in GCF.

[A correlational study on uncertainty, mastery and appraisal of uncertainty in hospitalized children's mothers].

PubMed

Yoo, Kyung Hee

2007-06-01

This study was conducted to investigate the correlation among uncertainty, mastery and appraisal of uncertainty in hospitalized children's mothers. Self report questionnaires were used to measure the variables. Variables were uncertainty, mastery and appraisal of uncertainty. In data analysis, the SPSSWIN 12.0 program was utilized for descriptive statistics, Pearson's correlation coefficients, and regression analysis. Reliability of the instruments was cronbach's alpha=.84~.94. Mastery negatively correlated with uncertainty(r=-.444, p=.000) and danger appraisal of uncertainty(r=-.514, p=.000). In regression of danger appraisal of uncertainty, uncertainty and mastery were significant predictors explaining 39.9%. Mastery was a significant mediating factor between uncertainty and danger appraisal of uncertainty in hospitalized children's mothers. Therefore, nursing interventions which improve mastery must be developed for hospitalized children's mothers.

Quantitative analysis of the correlations in the Boltzmann-Grad limit for hard spheres

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

Pulvirenti, M.

2014-12-09

In this contribution I consider the problem of the validity of the Boltzmann equation for a system of hard spheres in the Boltzmann-Grad limit. I briefly review the results available nowadays with a particular emphasis on the celebrated Lanford’s validity theorem. Finally I present some recent results, obtained in collaboration with S. Simonella, concerning a quantitative analysis of the propagation of chaos. More precisely we introduce a quantity (the correlation error) measuring how close a j-particle rescaled correlation function at time t (sufficiently small) is far from the full statistical independence. Roughly speaking, a correlation error of order k, measuresmore » (in the context of the BBKGY hierarchy) the event in which k tagged particles form a recolliding group.« less

ADC histogram analysis of muscle lymphoma - Correlation with histopathology in a rare entity.

PubMed

Meyer, Hans-Jonas; Pazaitis, Nikolaos; Surov, Alexey

2018-06-21

Diffusion weighted imaging (DWI) is able to reflect histopathology architecture. A novel imaging approach, namely histogram analysis, is used to further characterize lesion on MRI. The purpose of this study is to correlate histogram parameters derived from apparent diffusion coefficient- (ADC) maps with histopathology parameters in muscle lymphoma. Eight patients (mean age 64.8 years, range 45-72 years) with histopathologically confirmed muscle lymphoma were retrospectively identified. Cell count, total nucleic and average nucleic areas were estimated using ImageJ. Additionally, Ki67-index was calculated. DWI was obtained on a 1.5T scanner by using the b values of 0 and 1000 s/mm2. Histogram analysis was performed as a whole lesion measurement by using a custom-made Matlabbased application. The correlation analysis revealed statistically significant correlation between cell count and ADCmean (p=-0.76, P=0.03) as well with ADCp75 (p=-0.79, P=0.02). Kurtosis and entropy correlated with average nucleic area (p=-0.81, P=0.02, p=0.88, P=0.007, respectively). None of the analyzed ADC parameters correlated with total nucleic area and with Ki67-index. This study identified significant correlations between cellularity and histogram parameters derived from ADC maps in muscle lymphoma. Thus, histogram analysis parameters reflect histopathology in muscle tumors. Advances in knowledge: Whole lesion ADC histogram analysis is able to reflect histopathology parameters in muscle lymphomas.

Statistical study of the correlation of hard X-ray and type 3 radio bursts in solar flares

NASA Technical Reports Server (NTRS)

Hamilton, Russell J.; Petrosian, Vahe

1989-01-01

A large number of hard X-ray events which were recorded by the Hard X-Ray Burst Spectrometer (HXRBS) on the Solar Maximum Mission (SMM) during the maximum of the 21st solar cycle (circa 1980) are analyzed in order to study their statistical correlation with type 3 bursts. The earlier finding by Kane (1981) are confirmed qualitatively that flares with stronger hard X-ray emission, especially those with harder spectra, are more likely to produce a type 3 burst. The observed distribution of hard X-ray and type 3 events and their correlations are shown to be satisfactorily described by a bivariate distribution consistent with the assumption of statistical linear dependence of X-ray and radio burst intensities. From this analysis it was determined that the distribution of the ratio of X-ray intensity (in counts/s) to type 3 intensity (in solar flux units) which has a wide range and a typical value for this ratio of about 10. The implications of the results for impulsive phase models are discussed.

Design of off-statistics axial-flow fans by means of vortex law optimization

NASA Astrophysics Data System (ADS)

Lazari, Andrea; Cattanei, Andrea

2014-12-01

Off-statistics input data sets are common in axial-flow fans design and may easily result in some violation of the requirements of a good aerodynamic blade design. In order to circumvent this problem, in the present paper, a solution to the radial equilibrium equation is found which minimizes the outlet kinetic energy and fulfills the aerodynamic constraints, thus ensuring that the resulting blade has acceptable aerodynamic performance. The presented method is based on the optimization of a three-parameters vortex law and of the meridional channel size. The aerodynamic quantities to be employed as constraints are individuated and their suitable ranges of variation are proposed. The method is validated by means of a design with critical input data values and CFD analysis. Then, by means of systematic computations with different input data sets, some correlations and charts are obtained which are analogous to classic correlations based on statistical investigations on existing machines. Such new correlations help size a fan of given characteristics as well as study the feasibility of a given design.

Evaluation of standardized and applied variables in predicting treatment outcomes of polytrauma patients.

PubMed

Aksamija, Goran; Mulabdic, Adi; Rasic, Ismar; Muhovic, Samir; Gavric, Igor

2011-01-01

Polytrauma is defined as an injury where they are affected by at least two different organ systems or body, with at least one life-threatening injuries. Given the multilevel model care of polytrauma patients within KCUS are inevitable weaknesses in the management of this category of patients. To determine the dynamics of existing procedures in treatment of polytrauma patients on admission to KCUS, and based on statistical analysis of variables applied to determine and define the factors that influence the final outcome of treatment, and determine their mutual relationship, which may result in eliminating the flaws in the approach to the problem. The study was based on 263 polytrauma patients. Parametric and non-parametric statistical methods were used. Basic statistics were calculated, based on the calculated parameters for the final achievement of research objectives, multicoleration analysis, image analysis, discriminant analysis and multifactorial analysis were used. From the universe of variables for this study we selected sample of n = 25 variables, of which the first two modular, others belong to the common measurement space (n = 23) and in this paper defined as a system variable methods, procedures and assessments of polytrauma patients. After the multicoleration analysis, since the image analysis gave a reliable measurement results, we started the analysis of eigenvalues, that is defining the factors upon which they obtain information about the system solve the problem of the existing model and its correlation with treatment outcome. The study singled out the essential factors that determine the current organizational model of care, which may affect the treatment and better outcome of polytrauma patients. This analysis has shown the maximum correlative relationships between these practices and contributed to development guidelines that are defined by isolated factors.

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

Correlation of sweat chloride and percent predicted FEV1 in cystic fibrosis patients treated with ivacaftor.

PubMed

Fidler, Meredith C; Beusmans, Jack; Panorchan, Paul; Van Goor, Fredrick

2017-01-01

Ivacaftor, a CFTR potentiator that enhances chloride transport by acting directly on CFTR to increase its channel gating activity, has been evaluated in patients with different CFTR mutations. Several previous analyses have reported no statistical correlation between change from baseline in ppFEV 1 and reduction in sweat chloride levels for individuals treated with ivacaftor. The objective of the post hoc analysis described here was to expand upon previous analyses and evaluate the correlation between sweat chloride levels and absolute ppFEV 1 changes across multiple cohorts of patients with different CF-causing mutations who were treated with ivacaftor. The goal of the analysis was to help define the potential value of sweat chloride as a pharmacodynamic biomarker for use in CFTR modulator trials. For any given study, reductions in sweat chloride levels and improvements in absolute ppFEV 1 were not correlated for individual patients. However, when the data from all studies were combined, a statistically significant correlation between sweat chloride levels and ppFEV 1 changes was observed (p<0.0001). Thus, sweat chloride level changes in response to potentiation of the CFTR protein by ivacaftor appear to be a predictive pharmacodynamic biomarker of lung function changes on a population basis but are unsuitable for the prediction of treatment benefits for individuals. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Report on 3 and 4-point correlation statistics in the COBE DMR anisotrophy maps

NASA Technical Reports Server (NTRS)

Hinshaw, Gary (Principal Investigator); Gorski, Krzystof M.; Banday, Anthony J.; Bennett, Charles L.

1996-01-01

As part of the work performed under NASA contract # NAS5-32648, we have computed the 3-point and 4-point correlation functions of the COBE-DNIR 2-year and 4-year anisotropy maps. The motivation for this study was to search for evidence of non-Gaussian statistical fluctuations in the temperature maps: skewness or asymmetry in the case of the 3-point function, kurtosis in the case of the 4-point function. Such behavior would have very significant implications for our understanding of the processes of galaxy formation, because our current models of galaxy formation predict that non-Gaussian features should not be present in the DMR maps. The results of our work showed that the 3-point correlation function is consistent with zero and that the 4-point function is not a very sensitive probe of non-Gaussian behavior in the COBE-DMR data. Our computation and analysis of 3-point correlations in the 2-year DMR maps was published in the Astrophysical Journal Letters, volume 446, page L67, 1995. Our computation and analysis of 3-point correlations in the 4-year DMR maps will be published, together with some additional tests, in the June 10, 1996 issue of the Astrophysical Journal Letters. Copies of both of these papers are attached as an appendix to this report.

Application of Linear Mixed-Effects Models in Human Neuroscience Research: A Comparison with Pearson Correlation in Two Auditory Electrophysiology Studies

PubMed Central

Koerner, Tess K.; Zhang, Yang

2017-01-01

Neurophysiological studies are often designed to examine relationships between measures from different testing conditions, time points, or analysis techniques within the same group of participants. Appropriate statistical techniques that can take into account repeated measures and multivariate predictor variables are integral and essential to successful data analysis and interpretation. This work implements and compares conventional Pearson correlations and linear mixed-effects (LME) regression models using data from two recently published auditory electrophysiology studies. For the specific research questions in both studies, the Pearson correlation test is inappropriate for determining strengths between the behavioral responses for speech-in-noise recognition and the multiple neurophysiological measures as the neural responses across listening conditions were simply treated as independent measures. In contrast, the LME models allow a systematic approach to incorporate both fixed-effect and random-effect terms to deal with the categorical grouping factor of listening conditions, between-subject baseline differences in the multiple measures, and the correlational structure among the predictor variables. Together, the comparative data demonstrate the advantages as well as the necessity to apply mixed-effects models to properly account for the built-in relationships among the multiple predictor variables, which has important implications for proper statistical modeling and interpretation of human behavior in terms of neural correlates and biomarkers. PMID:28264422

Regionally variant collagen alignment correlates with viscoelastic properties of the disc of the human temporomandibular joint.

PubMed

Gutman, Shawn; Kim, Daniel; Tarafder, Solaiman; Velez, Sergio; Jeong, Julia; Lee, Chang H

2018-02-01

To determine the regionally variant quality of collagen alignment in human TMJ discs and its statistical correlation with viscoelastic properties. For quantitative analysis of the quality of collagen alignment, horizontal sections of human TMJ discs with Pricrosirius Red staining were imaged under circularly polarized microscopy. Mean angle and angular deviation of collagen fibers in each region were analyzed using a well-established automated image-processing for angular gradient. Instantaneous and relaxation moduli of each disc region were measured under stress-relaxation test both in tensile and compression. Then Spearman correlation analysis was performed between the angular deviation and the moduli. To understand the effect of glycosaminoglycans on the correlation, TMJ disc samples were treated by chondroitinase ABC (C-ABC). Our imaging processing analysis showed the region-variant direction of collagen alignment, consistently with previous findings. Interestingly, the quality of collagen alignment, not only the directions, was significantly different in between the regions. The angular deviation of fiber alignment in the anterior and intermediate regions were significantly smaller than the posterior region. Medial and lateral regions showed significantly bigger angular deviation than all the other regions. The regionally variant angular deviation values showed statistically significant correlation with the tensile instantaneous modulus and the relaxation modulus, partially dependent on C-ABC treatment. Our findings suggest the region-variant degree of collagen fiber alignment is likely attributed to the heterogeneous viscoelastic properties of TMJ disc that may have significant implications in development of regenerative therapy for TMJ disc. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of pH, lactate, hematocrit and potassium level on the accuracy of continuous glucose monitoring (CGM) in pediatric intensive care unit.

PubMed

Marics, Gábor; Koncz, Levente; Eitler, Katalin; Vatai, Barbara; Szénási, Boglárka; Zakariás, David; Mikos, Borbála; Körner, Anna; Tóth-Heyn, Péter

2015-03-19

Continuous glucose monitoring (CGM) originally was developed for diabetic patients and it may be a useful tool for monitoring glucose changes in pediatric intensive care unit (PICU). Its use is, however, limited by the lack of sufficient data on its reliability at insufficient peripheral perfusion. We aimed to correlate the accuracy of CGM with laboratory markers relevant to disturbed tissue perfusion. In 38 pediatric patients (age range, 0-18 years) requiring intensive care we tested the effect of pH, lactate, hematocrit and serum potassium on the difference between CGM and meter glucose measurements. Guardian® (Medtronic®) CGM results were compared to GEM 3000 (Instrumentation laboratory®) and point-of-care measurements. The clinical accuracy of CGM was evaluated by Clarke Error Grid -, Bland-Altman analysis and Pearson's correlation. We used Friedman test for statistical analysis (statistical significance was established as a p < 0.05). CGM values exhibited a considerable variability without any correlation with the examined laboratory parameters. Clarke, Bland-Altman analysis and Pearson's correlation coefficient demonstrated a good clinical accuracy of CGM (zone A and B = 96%; the mean difference between reference and CGM glucose was 1,3 mg/dL, 48 from the 780 calibration pairs overrunning the 2 standard deviation; Pearson's correlation coefficient: 0.83). The accuracy of CGM measurements is independent of laboratory parameters relevant to tissue hypoperfusion. CGM may prove a reliable tool for continuous monitoring of glucose changes in PICUs, not much influenced by tissue perfusion, but still not appropriate for being the base for clinical decisions.

THESEUS: maximum likelihood superpositioning and analysis of macromolecular structures

PubMed Central

Theobald, Douglas L.; Wuttke, Deborah S.

2008-01-01

Summary THESEUS is a command line program for performing maximum likelihood (ML) superpositions and analysis of macromolecular structures. While conventional superpositioning methods use ordinary least-squares (LS) as the optimization criterion, ML superpositions provide substantially improved accuracy by down-weighting variable structural regions and by correcting for correlations among atoms. ML superpositioning is robust and insensitive to the specific atoms included in the analysis, and thus it does not require subjective pruning of selected variable atomic coordinates. Output includes both likelihood-based and frequentist statistics for accurate evaluation of the adequacy of a superposition and for reliable analysis of structural similarities and differences. THESEUS performs principal components analysis for analyzing the complex correlations found among atoms within a structural ensemble. PMID:16777907

The Importance of Medical Students' Attitudes Regarding Cognitive Competence for Teaching Applied Statistics: Multi-Site Study and Meta-Analysis

PubMed Central

Milic, Natasa M.; Masic, Srdjan; Milin-Lazovic, Jelena; Trajkovic, Goran; Bukumiric, Zoran; Savic, Marko; Milic, Nikola V.; Cirkovic, Andja; Gajic, Milan; Kostic, Mirjana; Ilic, Aleksandra; Stanisavljevic, Dejana

2016-01-01

Background The scientific community increasingly is recognizing the need to bolster standards of data analysis given the widespread concern that basic mistakes in data analysis are contributing to the irreproducibility of many published research findings. The aim of this study was to investigate students’ attitudes towards statistics within a multi-site medical educational context, monitor their changes and impact on student achievement. In addition, we performed a systematic review to better support our future pedagogical decisions in teaching applied statistics to medical students. Methods A validated Serbian Survey of Attitudes Towards Statistics (SATS-36) questionnaire was administered to medical students attending obligatory introductory courses in biostatistics from three medical universities in the Western Balkans. A systematic review of peer-reviewed publications was performed through searches of Scopus, Web of Science, Science Direct, Medline, and APA databases through 1994. A meta-analysis was performed for the correlation coefficients between SATS component scores and statistics achievement. Pooled estimates were calculated using random effects models. Results SATS-36 was completed by 461 medical students. Most of the students held positive attitudes towards statistics. Ability in mathematics and grade point average were associated in a multivariate regression model with the Cognitive Competence score, after adjusting for age, gender and computer ability. The results of 90 paired data showed that Affect, Cognitive Competence, and Effort scores demonstrated significant positive changes. The Cognitive Competence score showed the largest increase (M = 0.48, SD = 0.95). The positive correlation found between the Cognitive Competence score and students’ achievement (r = 0.41; p<0.001), was also shown in the meta-analysis (r = 0.37; 95% CI 0.32–0.41). Conclusion Students' subjective attitudes regarding Cognitive Competence at the beginning of the biostatistics course, which were directly linked to mathematical knowledge, affected their attitudes at the end of the course that, in turn, influenced students' performance. This indicates the importance of positively changing not only students’ cognitive competency, but also their perceptions of gained competency during the biostatistics course. PMID:27764123

The Importance of Medical Students' Attitudes Regarding Cognitive Competence for Teaching Applied Statistics: Multi-Site Study and Meta-Analysis.

PubMed

Milic, Natasa M; Masic, Srdjan; Milin-Lazovic, Jelena; Trajkovic, Goran; Bukumiric, Zoran; Savic, Marko; Milic, Nikola V; Cirkovic, Andja; Gajic, Milan; Kostic, Mirjana; Ilic, Aleksandra; Stanisavljevic, Dejana

2016-01-01

The scientific community increasingly is recognizing the need to bolster standards of data analysis given the widespread concern that basic mistakes in data analysis are contributing to the irreproducibility of many published research findings. The aim of this study was to investigate students' attitudes towards statistics within a multi-site medical educational context, monitor their changes and impact on student achievement. In addition, we performed a systematic review to better support our future pedagogical decisions in teaching applied statistics to medical students. A validated Serbian Survey of Attitudes Towards Statistics (SATS-36) questionnaire was administered to medical students attending obligatory introductory courses in biostatistics from three medical universities in the Western Balkans. A systematic review of peer-reviewed publications was performed through searches of Scopus, Web of Science, Science Direct, Medline, and APA databases through 1994. A meta-analysis was performed for the correlation coefficients between SATS component scores and statistics achievement. Pooled estimates were calculated using random effects models. SATS-36 was completed by 461 medical students. Most of the students held positive attitudes towards statistics. Ability in mathematics and grade point average were associated in a multivariate regression model with the Cognitive Competence score, after adjusting for age, gender and computer ability. The results of 90 paired data showed that Affect, Cognitive Competence, and Effort scores demonstrated significant positive changes. The Cognitive Competence score showed the largest increase (M = 0.48, SD = 0.95). The positive correlation found between the Cognitive Competence score and students' achievement (r = 0.41; p<0.001), was also shown in the meta-analysis (r = 0.37; 95% CI 0.32-0.41). Students' subjective attitudes regarding Cognitive Competence at the beginning of the biostatistics course, which were directly linked to mathematical knowledge, affected their attitudes at the end of the course that, in turn, influenced students' performance. This indicates the importance of positively changing not only students' cognitive competency, but also their perceptions of gained competency during the biostatistics course.

An Exploratory Data Analysis System for Support in Medical Decision-Making

PubMed Central

Copeland, J. A.; Hamel, B.; Bourne, J. R.

1979-01-01

An experimental system was developed to allow retrieval and analysis of data collected during a study of neurobehavioral correlates of renal disease. After retrieving data organized in a relational data base, simple bivariate statistics of parametric and nonparametric nature could be conducted. An “exploratory” mode in which the system provided guidance in selection of appropriate statistical analyses was also available to the user. The system traversed a decision tree using the inherent qualities of the data (e.g., the identity and number of patients, tests, and time epochs) to search for the appropriate analyses to employ.

Statistical analysis of experimental data for mathematical modeling of physical processes in the atmosphere

NASA Astrophysics Data System (ADS)

Karpushin, P. A.; Popov, Yu B.; Popova, A. I.; Popova, K. Yu; Krasnenko, N. P.; Lavrinenko, A. V.

2017-11-01

In this paper, the probabilities of faultless operation of aerologic stations are analyzed, the hypothesis of normality of the empirical data required for using the Kalman filter algorithms is tested, and the spatial correlation functions of distributions of meteorological parameters are determined. The results of a statistical analysis of two-term (0, 12 GMT) radiosonde observations of the temperature and wind velocity components at some preset altitude ranges in the troposphere in 2001-2016 are presented. These data can be used in mathematical modeling of physical processes in the atmosphere.

Statistical Analysis of Large Scale Structure by the Discrete Wavelet Transform

NASA Astrophysics Data System (ADS)

Pando, Jesus

1997-10-01

The discrete wavelet transform (DWT) is developed as a general statistical tool for the study of large scale structures (LSS) in astrophysics. The DWT is used in all aspects of structure identification including cluster analysis, spectrum and two-point correlation studies, scale-scale correlation analysis and to measure deviations from Gaussian behavior. The techniques developed are demonstrated on 'academic' signals, on simulated models of the Lymanα (Lyα) forests, and on observational data of the Lyα forests. This technique can detect clustering in the Ly-α clouds where traditional techniques such as the two-point correlation function have failed. The position and strength of these clusters in both real and simulated data is determined and it is shown that clusters exist on scales as large as at least 20 h-1 Mpc at significance levels of 2-4 σ. Furthermore, it is found that the strength distribution of the clusters can be used to distinguish between real data and simulated samples even where other traditional methods have failed to detect differences. Second, a method for measuring the power spectrum of a density field using the DWT is developed. All common features determined by the usual Fourier power spectrum can be calculated by the DWT. These features, such as the index of a power law or typical scales, can be detected even when the samples are geometrically complex, the samples are incomplete, or the mean density on larger scales is not known (the infrared uncertainty). Using this method the spectra of Ly-α forests in both simulated and real samples is calculated. Third, a method for measuring hierarchical clustering is introduced. Because hierarchical evolution is characterized by a set of rules of how larger dark matter halos are formed by the merging of smaller halos, scale-scale correlations of the density field should be one of the most sensitive quantities in determining the merging history. We show that these correlations can be completely determined by the correlations between discrete wavelet coefficients on adjacent scales and at nearly the same spatial position, Cj,j+12/cdot2. Scale-scale correlations on two samples of the QSO Ly-α forests absorption spectra are computed. Lastly, higher order statistics are developed to detect deviations from Gaussian behavior. These higher order statistics are necessary to fully characterize the Ly-α forests because the usual 2nd order statistics, such as the two-point correlation function or power spectrum, give inconclusive results. It is shown how this technique takes advantage of the locality of the DWT to circumvent the central limit theorem. A non-Gaussian spectrum is defined and this spectrum reveals not only the magnitude, but the scales of non-Gaussianity. When applied to simulated and observational samples of the Ly-α clouds, it is found that different popular models of structure formation have different spectra while two, independent observational data sets, have the same spectra. Moreover, the non-Gaussian spectra of real data sets are significantly different from the spectra of various possible random samples. (Abstract shortened by UMI.)

Intratumoral heterogeneity analysis reveals hidden associations between protein expression losses and patient survival in clear cell renal cell carcinoma

PubMed Central

Devarajan, Karthik; Parsons, Theodore; Wang, Qiong; O'Neill, Raymond; Solomides, Charalambos; Peiper, Stephen C.; Testa, Joseph R.; Uzzo, Robert; Yang, Haifeng

2017-01-01

Intratumoral heterogeneity (ITH) is a prominent feature of kidney cancer. It is not known whether it has utility in finding associations between protein expression and clinical parameters. We used ITH that is detected by immunohistochemistry (IHC) to aid the association analysis between the loss of SWI/SNF components and clinical parameters.160 ccRCC tumors (40 per tumor stage) were used to generate tissue microarray (TMA). Four foci from different regions of each tumor were selected. IHC was performed against PBRM1, ARID1A, SETD2, SMARCA4, and SMARCA2. Statistical analyses were performed to correlate biomarker losses with patho-clinical parameters. Categorical variables were compared between groups using Fisher's exact tests. Univariate and multivariable analyses were used to correlate biomarker changes and patient survivals. Multivariable analyses were performed by constructing decision trees using the classification and regression trees (CART) methodology. IHC detected widespread ITH in ccRCC tumors. The statistical analysis of the “Truncal loss” (root loss) found additional correlations between biomarker losses and tumor stages than the traditional “Loss in tumor (total)”. Losses of SMARCA4 or SMARCA2 significantly improved prognosis for overall survival (OS). Losses of PBRM1, ARID1A or SETD2 had the opposite effect. Thus “Truncal Loss” analysis revealed hidden links between protein losses and patient survival in ccRCC. PMID:28445125

Lack of large-angle TT correlations persists in WMAP and Planck

NASA Astrophysics Data System (ADS)

Copi, Craig J.; Huterer, Dragan; Schwarz, Dominik J.; Starkman, Glenn D.

2015-08-01

The lack of large-angle correlations in the observed microwave background temperature fluctuations persists in the final-year maps from Wilkinson Microwave Anisotropy Probe (WMAP) and the first cosmological data release from Planck. We find a statistically robust and significant result: p-values for the missing correlations lying below 0.24 per cent (i.e. evidence at more than 3σ) for foreground cleaned maps, in complete agreement with previous analyses based upon earlier WMAP data. A cut-sky analysis of the Planck HFI 100 GHz frequency band, the `cleanest CMB channel' of this instrument, returns a p-value as small as 0.03 per cent, based on the conservative mask defined by WMAP. These findings are in stark contrast to expectations from the inflationary Lambda cold dark matter model and still lack a convincing explanation. If this lack of large-angle correlations is a true feature of our Universe, and not just a statistical fluke, then the cosmological dipole must be considerably smaller than that predicted in the best-fitting model.

Streamwise evolution of statistical events and the triple correlation in a model wind turbine array

NASA Astrophysics Data System (ADS)

Viestenz, Kyle; Cal, Raúl Bayoán

2013-11-01

Hot-wire anemometry data, obtained from a wind tunnel experiment containing a 3 × 3 wind turbine array, are used to conditionally average the Reynolds stresses. Nine profiles at the centerline behind the array are analyzed to characterize the turbulent velocity statistics of the wake flow. Quadrant analysis yields statistical events occurring in the wake of the wind farm, where quadrants 2 and 4 produce ejections and sweeps, respectively. A balance between these quadrants is expressed via the ΔSo parameter, which attains a maximum value at the bottom tip and changes sign near the top tip of the rotor. These are then associated to the triple correlation term present in the turbulent kinetic energy equation of the fluctuations. The development of these various quantities is assessed in light of wake remediation, energy transport and possess significance in closure models. National Science Foundation: ECCS-1032647.

Improved Statistics for Genome-Wide Interaction Analysis

PubMed Central

Ueki, Masao; Cordell, Heather J.

2012-01-01

Recently, Wu and colleagues [1] proposed two novel statistics for genome-wide interaction analysis using case/control or case-only data. In computer simulations, their proposed case/control statistic outperformed competing approaches, including the fast-epistasis option in PLINK and logistic regression analysis under the correct model; however, reasons for its superior performance were not fully explored. Here we investigate the theoretical properties and performance of Wu et al.'s proposed statistics and explain why, in some circumstances, they outperform competing approaches. Unfortunately, we find minor errors in the formulae for their statistics, resulting in tests that have higher than nominal type 1 error. We also find minor errors in PLINK's fast-epistasis and case-only statistics, although theory and simulations suggest that these errors have only negligible effect on type 1 error. We propose adjusted versions of all four statistics that, both theoretically and in computer simulations, maintain correct type 1 error rates under the null hypothesis. We also investigate statistics based on correlation coefficients that maintain similar control of type 1 error. Although designed to test specifically for interaction, we show that some of these previously-proposed statistics can, in fact, be sensitive to main effects at one or both loci, particularly in the presence of linkage disequilibrium. We propose two new “joint effects” statistics that, provided the disease is rare, are sensitive only to genuine interaction effects. In computer simulations we find, in most situations considered, that highest power is achieved by analysis under the correct genetic model. Such an analysis is unachievable in practice, as we do not know this model. However, generally high power over a wide range of scenarios is exhibited by our joint effects and adjusted Wu statistics. We recommend use of these alternative or adjusted statistics and urge caution when using Wu et al.'s originally-proposed statistics, on account of the inflated error rate that can result. PMID:22496670

On the insufficiency of arbitrarily precise covariance matrices: non-Gaussian weak-lensing likelihoods

NASA Astrophysics Data System (ADS)

Sellentin, Elena; Heavens, Alan F.

2018-01-01

We investigate whether a Gaussian likelihood, as routinely assumed in the analysis of cosmological data, is supported by simulated survey data. We define test statistics, based on a novel method that first destroys Gaussian correlations in a data set, and then measures the non-Gaussian correlations that remain. This procedure flags pairs of data points that depend on each other in a non-Gaussian fashion, and thereby identifies where the assumption of a Gaussian likelihood breaks down. Using this diagnosis, we find that non-Gaussian correlations in the CFHTLenS cosmic shear correlation functions are significant. With a simple exclusion of the most contaminated data points, the posterior for s8 is shifted without broadening, but we find no significant reduction in the tension with s8 derived from Planck cosmic microwave background data. However, we also show that the one-point distributions of the correlation statistics are noticeably skewed, such that sound weak-lensing data sets are intrinsically likely to lead to a systematically low lensing amplitude being inferred. The detected non-Gaussianities get larger with increasing angular scale such that for future wide-angle surveys such as Euclid or LSST, with their very small statistical errors, the large-scale modes are expected to be increasingly affected. The shifts in posteriors may then not be negligible and we recommend that these diagnostic tests be run as part of future analyses.

From Principal Component to Direct Coupling Analysis of Coevolution in Proteins: Low-Eigenvalue Modes are Needed for Structure Prediction

PubMed Central

Cocco, Simona; Monasson, Remi; Weigt, Martin

2013-01-01

Various approaches have explored the covariation of residues in multiple-sequence alignments of homologous proteins to extract functional and structural information. Among those are principal component analysis (PCA), which identifies the most correlated groups of residues, and direct coupling analysis (DCA), a global inference method based on the maximum entropy principle, which aims at predicting residue-residue contacts. In this paper, inspired by the statistical physics of disordered systems, we introduce the Hopfield-Potts model to naturally interpolate between these two approaches. The Hopfield-Potts model allows us to identify relevant ‘patterns’ of residues from the knowledge of the eigenmodes and eigenvalues of the residue-residue correlation matrix. We show how the computation of such statistical patterns makes it possible to accurately predict residue-residue contacts with a much smaller number of parameters than DCA. This dimensional reduction allows us to avoid overfitting and to extract contact information from multiple-sequence alignments of reduced size. In addition, we show that low-eigenvalue correlation modes, discarded by PCA, are important to recover structural information: the corresponding patterns are highly localized, that is, they are concentrated in few sites, which we find to be in close contact in the three-dimensional protein fold. PMID:23990764

Re-Analysis Report: Daylighting in Schools, Additional Analysis. Tasks 2.2.1 through 2.2.5.

ERIC Educational Resources Information Center

Heschong, Lisa; Elzeyadi, Ihab; Knecht, Carey

This study expands and validates previous research that found a statistical correlation between the amount of daylight in elementary school classrooms and the performance of students on standardized math and reading tests. The researchers reanalyzed the 19971998 school year student performance data from the Capistrano Unified School District…

An exploratory investigation of weight estimation techniques for hypersonic flight vehicles

NASA Technical Reports Server (NTRS)

Cook, E. L.

1981-01-01

The three basic methods of weight prediction (fixed-fraction, statistical correlation, and point stress analysis) and some of the computer programs that have been developed to implement them are discussed. A modified version of the WAATS (Weights Analysis of Advanced Transportation Systems) program is presented, along with input data forms and an example problem.

Analysis of high-resolution foreign exchange data of USD-JPY for 13 years

NASA Astrophysics Data System (ADS)

Mizuno, Takayuki; Kurihara, Shoko; Takayasu, Misako; Takayasu, Hideki

2003-06-01

We analyze high-resolution foreign exchange data consisting of 20 million data points of USD-JPY for 13 years to report firm statistical laws in distributions and correlations of exchange rate fluctuations. A conditional probability density analysis clearly shows the existence of trend-following movements at time scale of 8-ticks, about 1 min.

Color Shade Instrumentation Correlation Study: Statistical Analysis. Revision

DTIC Science & Technology

2011-03-01

L* a* b* Alpha Desert Sand 503 Beta Chi Army Green 491 Delta Epsilon Iota Kappa Lambda Mu Desert Sand 503...Desert Sand 503 Epsilon Army Green 491 Iota Kappa Lambda Desert Sand 503 Mu Omega Omicron Desert Sand 503 Psi Rho...Color Tiles Figure 3-3. Correlation Matrix for a* Means of Color Tiles Alpha Beta Chi Delta Epsilon Iota Kappa Lambda Mu Omega Omicron Psi Rho

A twelve-year profile of students' SAT scores, GPAs, and MCAT scores from a small university's premedical program.

PubMed

Montague, J R; Frei, J K

1993-04-01

To determine whether significant correlations existed among quantitative and qualitative predictors of students' academic success and quantitative outcomes of such success over a 12-year period in a small university's premedical program. A database was assembled from information on the 199 graduates who earned BS degrees in biology from Barry University's School of Natural and Health Sciences from 1980 through 1991. The quantitative variables were year of BS degree, total score on the Scholastic Aptitude Test (SAT), various measures of undergraduate grade-point averages (GPAs), and total score on the Medical College Admission Test (MCAT); and the qualitative variables were minority (54% of the students) or majority status and transfer (about one-third of the students) or nontransfer status. The statistical methods were multiple analysis of variance and stepwise multiple regression. Statistically significant positive correlations were found among SAT total scores, final GPAs, biology GPAs versus nonbiology GPAs, and MCAT total scores. These correlations held for transfer versus nontransfer students and for minority versus majority students. Over the 12-year period there were significant fluctuations in mean MCAT scores. The students' SAT scores and GPAs proved to be statistically reliable predictors of MCAT scores, but the minority or majority status and the transfer or nontransfer status of the students were statistically insignificant.

Quantitative Analysis of the Interdisciplinarity of Applied Mathematics.

PubMed

Xie, Zheng; Duan, Xiaojun; Ouyang, Zhenzheng; Zhang, Pengyuan

2015-01-01

The increasing use of mathematical techniques in scientific research leads to the interdisciplinarity of applied mathematics. This viewpoint is validated quantitatively here by statistical and network analysis on the corpus PNAS 1999-2013. A network describing the interdisciplinary relationships between disciplines in a panoramic view is built based on the corpus. Specific network indicators show the hub role of applied mathematics in interdisciplinary research. The statistical analysis on the corpus content finds that algorithms, a primary topic of applied mathematics, positively correlates, increasingly co-occurs, and has an equilibrium relationship in the long-run with certain typical research paradigms and methodologies. The finding can be understood as an intrinsic cause of the interdisciplinarity of applied mathematics.

NIRS-SPM: statistical parametric mapping for near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Tak, Sungho; Jang, Kwang Eun; Jung, Jinwook; Jang, Jaeduck; Jeong, Yong; Ye, Jong Chul

2008-02-01

Even though there exists a powerful statistical parametric mapping (SPM) tool for fMRI, similar public domain tools are not available for near infrared spectroscopy (NIRS). In this paper, we describe a new public domain statistical toolbox called NIRS-SPM for quantitative analysis of NIRS signals. Specifically, NIRS-SPM statistically analyzes the NIRS data using GLM and makes inference as the excursion probability which comes from the random field that are interpolated from the sparse measurement. In order to obtain correct inference, NIRS-SPM offers the pre-coloring and pre-whitening method for temporal correlation estimation. For simultaneous recording NIRS signal with fMRI, the spatial mapping between fMRI image and real coordinate in 3-D digitizer is estimated using Horn's algorithm. These powerful tools allows us the super-resolution localization of the brain activation which is not possible using the conventional NIRS analysis tools.

Statistical Analysis of Spectral Properties and Prosodic Parameters of Emotional Speech

NASA Astrophysics Data System (ADS)

Přibil, J.; Přibilová, A.

2009-01-01

The paper addresses reflection of microintonation and spectral properties in male and female acted emotional speech. Microintonation component of speech melody is analyzed regarding its spectral and statistical parameters. According to psychological research of emotional speech, different emotions are accompanied by different spectral noise. We control its amount by spectral flatness according to which the high frequency noise is mixed in voiced frames during cepstral speech synthesis. Our experiments are aimed at statistical analysis of cepstral coefficient values and ranges of spectral flatness in three emotions (joy, sadness, anger), and a neutral state for comparison. Calculated histograms of spectral flatness distribution are visually compared and modelled by Gamma probability distribution. Histograms of cepstral coefficient distribution are evaluated and compared using skewness and kurtosis. Achieved statistical results show good correlation comparing male and female voices for all emotional states portrayed by several Czech and Slovak professional actors.

Statistical analysis of Geopotential Height (GH) timeseries based on Tsallis non-extensive statistical mechanics

NASA Astrophysics Data System (ADS)

Karakatsanis, L. P.; Iliopoulos, A. C.; Pavlos, E. G.; Pavlos, G. P.

2018-02-01

In this paper, we perform statistical analysis of time series deriving from Earth's climate. The time series are concerned with Geopotential Height (GH) and correspond to temporal and spatial components of the global distribution of month average values, during the period (1948-2012). The analysis is based on Tsallis non-extensive statistical mechanics and in particular on the estimation of Tsallis' q-triplet, namely {qstat, qsens, qrel}, the reconstructed phase space and the estimation of correlation dimension and the Hurst exponent of rescaled range analysis (R/S). The deviation of Tsallis q-triplet from unity indicates non-Gaussian (Tsallis q-Gaussian) non-extensive character with heavy tails probability density functions (PDFs), multifractal behavior and long range dependences for all timeseries considered. Also noticeable differences of the q-triplet estimation found in the timeseries at distinct local or temporal regions. Moreover, in the reconstructive phase space revealed a lower-dimensional fractal set in the GH dynamical phase space (strong self-organization) and the estimation of Hurst exponent indicated multifractality, non-Gaussianity and persistence. The analysis is giving significant information identifying and characterizing the dynamical characteristics of the earth's climate.

Hierarchical multivariate covariance analysis of metabolic connectivity

PubMed Central

Carbonell, Felix; Charil, Arnaud; Zijdenbos, Alex P; Evans, Alan C; Bedell, Barry J

2014-01-01

Conventional brain connectivity analysis is typically based on the assessment of interregional correlations. Given that correlation coefficients are derived from both covariance and variance, group differences in covariance may be obscured by differences in the variance terms. To facilitate a comprehensive assessment of connectivity, we propose a unified statistical framework that interrogates the individual terms of the correlation coefficient. We have evaluated the utility of this method for metabolic connectivity analysis using [18F]2-fluoro-2-deoxyglucose (FDG) positron emission tomography (PET) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. As an illustrative example of the utility of this approach, we examined metabolic connectivity in angular gyrus and precuneus seed regions of mild cognitive impairment (MCI) subjects with low and high β-amyloid burdens. This new multivariate method allowed us to identify alterations in the metabolic connectome, which would not have been detected using classic seed-based correlation analysis. Ultimately, this novel approach should be extensible to brain network analysis and broadly applicable to other imaging modalities, such as functional magnetic resonance imaging (MRI). PMID:25294129

Statistical analysis of fNIRS data: a comprehensive review.

PubMed

Tak, Sungho; Ye, Jong Chul

2014-01-15

Functional near-infrared spectroscopy (fNIRS) is a non-invasive method to measure brain activities using the changes of optical absorption in the brain through the intact skull. fNIRS has many advantages over other neuroimaging modalities such as positron emission tomography (PET), functional magnetic resonance imaging (fMRI), or magnetoencephalography (MEG), since it can directly measure blood oxygenation level changes related to neural activation with high temporal resolution. However, fNIRS signals are highly corrupted by measurement noises and physiology-based systemic interference. Careful statistical analyses are therefore required to extract neuronal activity-related signals from fNIRS data. In this paper, we provide an extensive review of historical developments of statistical analyses of fNIRS signal, which include motion artifact correction, short source-detector separation correction, principal component analysis (PCA)/independent component analysis (ICA), false discovery rate (FDR), serially-correlated errors, as well as inference techniques such as the standard t-test, F-test, analysis of variance (ANOVA), and statistical parameter mapping (SPM) framework. In addition, to provide a unified view of various existing inference techniques, we explain a linear mixed effect model with restricted maximum likelihood (ReML) variance estimation, and show that most of the existing inference methods for fNIRS analysis can be derived as special cases. Some of the open issues in statistical analysis are also described. Copyright © 2013 Elsevier Inc. All rights reserved.

Challenges of Big Data Analysis.

PubMed

Fan, Jianqing; Han, Fang; Liu, Han

2014-06-01

Big Data bring new opportunities to modern society and challenges to data scientists. On one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity, and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This article gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogeneous assumptions in most statistical methods for Big Data can not be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions.

Challenges of Big Data Analysis

PubMed Central

Fan, Jianqing; Han, Fang; Liu, Han

2014-01-01

Big Data bring new opportunities to modern society and challenges to data scientists. On one hand, Big Data hold great promises for discovering subtle population patterns and heterogeneities that are not possible with small-scale data. On the other hand, the massive sample size and high dimensionality of Big Data introduce unique computational and statistical challenges, including scalability and storage bottleneck, noise accumulation, spurious correlation, incidental endogeneity, and measurement errors. These challenges are distinguished and require new computational and statistical paradigm. This article gives overviews on the salient features of Big Data and how these features impact on paradigm change on statistical and computational methods as well as computing architectures. We also provide various new perspectives on the Big Data analysis and computation. In particular, we emphasize on the viability of the sparsest solution in high-confidence set and point out that exogeneous assumptions in most statistical methods for Big Data can not be validated due to incidental endogeneity. They can lead to wrong statistical inferences and consequently wrong scientific conclusions. PMID:25419469

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

Xiang, N. B.; Kong, D. F., E-mail: nanbin@ynao.ac.cn

The Physikalisch Meteorologisches Observatorium Davos total solar irradiance (TSI), Active Cavity Radiometer Irradiance Monitoring TSI, and Royal Meteorological Institute of Belgium TSI are three typical TSI composites. Magnetic Plage Strength Index (MPSI) and Mount Wilson Sunspot Index (MWSI) should indicate the weak and strong magnetic field activity on the solar full disk, respectively. Cross-correlation (CC) analysis of MWSI with three TSI composites shows that TSI should be weakly correlated with MWSI, and not be in phase with MWSI at timescales of solar cycles. The wavelet coherence (WTC) and partial wavelet coherence (PWC) of TSI with MWSI indicate that the inter-solar-cyclemore » variation of TSI is also not related to solar strong magnetic field activity, which is represented by MWSI. However, CC analysis of MPSI with three TSI composites indicates that TSI should be moderately correlated and accurately in phase with MPSI at timescales of solar cycles, and that the statistical significance test indicates that the correlation coefficient of three TSI composites with MPSI is statistically significantly higher than that of three TSI composites with MWSI. Furthermore, the cross wavelet transform (XWT) and WTC of TSI with MPSI show that the TSI is highly related and actually in phase with MPSI at a timescale of a solar cycle as well. Consequently, the CC analysis, XWT, and WTC indicate that the solar weak magnetic activity on the full disk, which is represented by MPSI, dominates the inter-solar-cycle variation of TSI.« less

Voice Tremor in Parkinson's Disease: An Acoustic Study.

PubMed

Gillivan-Murphy, Patricia; Miller, Nick; Carding, Paul

2018-01-30

Voice tremor associated with Parkinson disease (PD) has not been characterized. Its relationship with voice disability and disease variables is unknown. This study aimed to evaluate voice tremor in people with PD (pwPD) and a matched control group using acoustic analysis, and to examine correlations with voice disability and disease variables. Acoustic voice tremor analysis was completed on 30 pwPD and 28 age-gender matched controls. Voice disability (Voice Handicap Index), and disease variables of disease duration, Activities of Daily Living (Unified Parkinson's Disease Rating Scale [UPDRS II]), and motor symptoms related to PD (UPDRS III) were examined for relationship with voice tremor measures. Voice tremor was detected acoustically in pwPD and controls with similar frequency. PwPD had a statistically significantly higher rate of amplitude tremor (Hz) than controls (P = 0.001). Rate of amplitude tremor was negatively and significantly correlated with UPDRS III total score (rho -0.509). For pwPD, the magnitude and periodicity of acoustic tremor was higher than for controls without statistical significance. The magnitude of frequency tremor (Mftr%) was positively and significantly correlated with disease duration (rho 0.463). PwPD had higher Voice Handicap Index total, functional, emotional, and physical subscale scores than matched controls (P < 0.001). Voice disability did not correlate significantly with acoustic voice tremor measures. Acoustic analysis enhances understanding of PD voice tremor characteristics, its pathophysiology, and its relationship with voice disability and disease symptomatology. Copyright © 2018 The Voice Foundation. All rights reserved.

Turkish Version of Kolcaba's Immobilization Comfort Questionnaire: A Validity and Reliability Study.

PubMed

Tosun, Betül; Aslan, Özlem; Tunay, Servet; Akyüz, Aygül; Özkan, Hüseyin; Bek, Doğan; Açıksöz, Semra

2015-12-01

The purpose of this study was to determine the validity and reliability of the Turkish version of the Immobilization Comfort Questionnaire (ICQ). The sample used in this methodological study consisted of 121 patients undergoing lower extremity arthroscopy in a training and research hospital. The validity study of the questionnaire assessed language validity, structural validity and criterion validity. Structural validity was evaluated via exploratory factor analysis. Criterion validity was evaluated by assessing the correlation between the visual analog scale (VAS) scores (i.e., the comfort and pain VAS scores) and the ICQ scores using Spearman's correlation test. The Kaiser-Meyer-Olkin coefficient and Bartlett's test of sphericity were used to determine the suitability of the data for factor analysis. Internal consistency was evaluated to determine reliability. The data were analyzed with SPSS version 15.00 for Windows. Descriptive statistics were presented as frequencies, percentages, means and standard deviations. A p value ≤ .05 was considered statistically significant. A moderate positive correlation was found between the ICQ scores and the VAS comfort scores; a moderate negative correlation was found between the ICQ and the VAS pain measures in the criterion validity analysis. Cronbach α values of .75 and .82 were found for the first and second measurements, respectively. The findings of this study reveal that the ICQ is a valid and reliable tool for assessing the comfort of patients in Turkey who are immobilized because of lower extremity orthopedic problems. Copyright © 2015. Published by Elsevier B.V.

Nonlinear dynamic analysis of voices before and after surgical excision of vocal polyps

NASA Astrophysics Data System (ADS)

Zhang, Yu; McGilligan, Clancy; Zhou, Liang; Vig, Mark; Jiang, Jack J.

2004-05-01

Phase space reconstruction, correlation dimension, and second-order entropy, methods from nonlinear dynamics, are used to analyze sustained vowels generated by patients before and after surgical excision of vocal polyps. Two conventional acoustic perturbation parameters, jitter and shimmer, are also employed to analyze voices before and after surgery. Presurgical and postsurgical analyses of jitter, shimmer, correlation dimension, and second-order entropy are statistically compared. Correlation dimension and second-order entropy show a statistically significant decrease after surgery, indicating reduced complexity and higher predictability of postsurgical voice dynamics. There is not a significant postsurgical difference in shimmer, although jitter shows a significant postsurgical decrease. The results suggest that jitter and shimmer should be applied to analyze disordered voices with caution; however, nonlinear dynamic methods may be useful for analyzing abnormal vocal function and quantitatively evaluating the effects of surgical excision of vocal polyps.

Nurses' perception of ethical climate and organizational commitment.

PubMed

Borhani, Fariba; Jalali, Tayebe; Abbaszadeh, Abbas; Haghdoost, Aliakbar

2014-05-01

The high turnover of nurses has become a universal issue. The manner in which nurses view their organization's ethical climate has direct bearing on their organizational commitment. The aim of this study was to determine the correlation between nurses' perception of ethical climate and organizational commitment in teaching hospitals in the southeastern region of Iran. A descriptive analytical design was used in this study. The sample consisted of 275 nurses working in four teaching hospitals in the southeastern region of Iran. The instruments used in this study included a demographic questionnaire, Ethical Climate Questionnaire, and Organizational Commitment Questionnaire. Data analysis was carried out using Pearson's correlation, t-test, and descriptive statistic through Statistical Package for Social Science, version 16. The result of this research indicated a positive correlation among professionalism, caring, rules, independence climate, and organizational commitment. Therefore, findings of this study are a guideline for researchers and managers alike who endeavor to improve organizational commitment.

An asymptotic theory for cross-correlation between auto-correlated sequences and its application on neuroimaging data.

PubMed

Zhou, Yunyi; Tao, Chenyang; Lu, Wenlian; Feng, Jianfeng

2018-04-20

Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation. A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression. We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods. Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail. In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis. Copyright © 2018. Published by Elsevier B.V.

Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study.

PubMed

Meyer, Hans Jonas; Höhn, Annekathrin; Surov, Alexey

2018-04-06

Functional imaging modalities like Diffusion-weighted imaging are increasingly used to predict tumor behavior like cellularity and vascularity in different tumors. Histogram analysis is an emergent imaging analysis, in which every voxel is used to obtain a histogram and therefore statistically information about tumors can be provided. The purpose of this study was to elucidate possible associations between ADC histogram parameters and several immunhistochemical features in rectal cancer. Overall, 11 patients with histologically proven rectal cancer were included into the study. There were 2 (18.18%) females and 9 males with a mean age of 67.1 years. KI 67-index, expression of p53, EGFR, VEGF, and Hif1-alpha were semiautomatically estimated. The tumors were divided into PD1-positive and PD1-negative lesions. ADC histogram analysis was performed as a whole lesion measurement using an in-house matlab application. Spearman's correlation analysis revealed a strong correlation between EGFR expression and ADCmax (p=0.72, P=0.02). None of the vascular parameters (VEGF, Hif1-alpha) correlated with ADC parameters. Kurtosis and skewness correlated inversely with p53 expression (p=-0.64, P=0.03 and p=-0.81, P=0.002, respectively). ADCmedian and ADCmode correlated with Ki67 (p=-0.62, P=0.04 and p=-0.65, P=0.03, respectively). PD1-positive tumors showed statistically significant lower ADCmax values in comparison to PD1-negative tumors, 1.93 ± 0.36 vs 2.32 ± 0.47×10 -3 mm 2 /s, p=0.04. Several associations were identified between histogram parameter derived from ADC maps and EGFR, KI 67 and p53 expression in rectal cancer. Furthermore, ADCmax was different between PD1 positive and PD1 negative tumors indicating an important role of ADC parameters for possible future treatment prediction.

Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study

PubMed Central

Meyer, Hans Jonas; Höhn, Annekathrin; Surov, Alexey

2018-01-01

Functional imaging modalities like Diffusion-weighted imaging are increasingly used to predict tumor behavior like cellularity and vascularity in different tumors. Histogram analysis is an emergent imaging analysis, in which every voxel is used to obtain a histogram and therefore statistically information about tumors can be provided. The purpose of this study was to elucidate possible associations between ADC histogram parameters and several immunhistochemical features in rectal cancer. Overall, 11 patients with histologically proven rectal cancer were included into the study. There were 2 (18.18%) females and 9 males with a mean age of 67.1 years. KI 67-index, expression of p53, EGFR, VEGF, and Hif1-alpha were semiautomatically estimated. The tumors were divided into PD1-positive and PD1-negative lesions. ADC histogram analysis was performed as a whole lesion measurement using an in-house matlab application. Spearman's correlation analysis revealed a strong correlation between EGFR expression and ADCmax (p=0.72, P=0.02). None of the vascular parameters (VEGF, Hif1-alpha) correlated with ADC parameters. Kurtosis and skewness correlated inversely with p53 expression (p=-0.64, P=0.03 and p=-0.81, P=0.002, respectively). ADCmedian and ADCmode correlated with Ki67 (p=-0.62, P=0.04 and p=-0.65, P=0.03, respectively). PD1-positive tumors showed statistically significant lower ADCmax values in comparison to PD1-negative tumors, 1.93 ± 0.36 vs 2.32 ± 0.47×10−3mm2/s, p=0.04. Several associations were identified between histogram parameter derived from ADC maps and EGFR, KI 67 and p53 expression in rectal cancer. Furthermore, ADCmax was different between PD1 positive and PD1 negative tumors indicating an important role of ADC parameters for possible future treatment prediction. PMID:29719621

Non-enzymatic antioxidant capacity (NEAC) estimated by two different dietary assessment methods and its relationship with NEAC plasma levels.

PubMed

Carrión-García, Cayetano Javier; Guerra-Hernández, Eduardo J; García-Villanova, Belén; Molina-Montes, Esther

2017-06-01

We aimed to quantify and compare dietary non-enzymatic antioxidant capacity (NEAC), estimated using two dietary assessment methods, and to explore its relationship with plasma NEAC. Fifty healthy subjects volunteer to participate in this study. Two dietary assessment methods [a food frequency questionnaire (FFQ) and a 24-hour recall (24-HR)] were used to collect dietary information. Dietary NEAC, including oxygen radical absorbance capacity (ORAC), total polyphenols, ferric-reducing antioxidant power (FRAP) and trolox equivalent antioxidant capacity, was estimated using several data sources of NEAC content in food. NEAC status was measured in fasting blood samples using the same assays. We performed nonparametric Spearman's correlation analysis between pairs of dietary NEAC (FFQ and 24-HR) and diet-plasma NEAC, with and without the contribution of coffee's NEAC. Partial correlation analysis was used to estimate correlations regardless of variables potentially influencing these relationships. FFQ-based NEAC and 24-HR-based NEAC were moderately correlated, with correlation coefficients ranging from 0.54 to 0.71, after controlling for energy intake, age and sex. Statistically significant positive correlations were found for dietary FRAP, either derived from the FFQ or the 24-HR, with plasma FRAP (r ~ 0.30). This weak, albeit statistically significant, correlation for FRAP was mostly present in the fruits and vegetables food groups. Plasma ORAC without proteins and 24-HR-based total ORAC were also positively correlated (r = 0.35). The relationship between dietary NEAC and plasma FRAP and ORAC suggests the dietary NEAC may reflect antioxidant status despite its weak in vivo potential, supporting further its use in oxidative stress-related disease epidemiology.

Long- and short-time analysis of heartbeat sequences: correlation with mortality risk in congestive heart failure patients.

PubMed

Allegrini, P; Balocchi, R; Chillemi, S; Grigolini, P; Hamilton, P; Maestri, R; Palatella, L; Raffaelli, G

2003-06-01

We analyze RR heartbeat sequences with a dynamic model that satisfactorily reproduces both the long- and the short-time statistical properties of heart beating. These properties are expressed quantitatively by means of two significant parameters, the scaling delta concerning the asymptotic effects of long-range correlation, and the quantity 1-pi establishing the amount of uncorrelated fluctuations. We find a correlation between the position in the phase space (delta, pi) of patients with congestive heart failure and their mortality risk.

THE RADIO/GAMMA-RAY CONNECTION IN ACTIVE GALACTIC NUCLEI IN THE ERA OF THE FERMI LARGE AREA TELESCOPE

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

Ackermann, M.; Ajello, M.; Allafort, A.

We present a detailed statistical analysis of the correlation between radio and gamma-ray emission of the active galactic nuclei (AGNs) detected by Fermi during its first year of operation, with the largest data sets ever used for this purpose. We use both archival interferometric 8.4 GHz data (from the Very Large Array and ATCA, for the full sample of 599 sources) and concurrent single-dish 15 GHz measurements from the Owens Valley Radio Observatory (OVRO, for a sub sample of 199 objects). Our unprecedentedly large sample permits us to assess with high accuracy the statistical significance of the correlation, using amore » surrogate data method designed to simultaneously account for common-distance bias and the effect of a limited dynamical range in the observed quantities. We find that the statistical significance of a positive correlation between the centimeter radio and the broadband (E > 100 MeV) gamma-ray energy flux is very high for the whole AGN sample, with a probability of <10{sup -7} for the correlation appearing by chance. Using the OVRO data, we find that concurrent data improve the significance of the correlation from 1.6 x 10{sup -6} to 9.0 x 10{sup -8}. Our large sample size allows us to study the dependence of correlation strength and significance on specific source types and gamma-ray energy band. We find that the correlation is very significant (chance probability < 10{sup -7}) for both flat spectrum radio quasars and BL Lac objects separately; a dependence of the correlation strength on the considered gamma-ray energy band is also present, but additional data will be necessary to constrain its significance.« less

The radio/gamma-ray connection in active galactic nuclei in the era of the Fermi Large Area Telescope

DOE PAGES

Ackermann, M.; Ajello, M.; Allafort, A.; ...

2011-10-12

We present a detailed statistical analysis of the correlation between radio and gamma-ray emission of the active galactic nuclei (AGNs) detected by Fermi during its first year of operation, with the largest data sets ever used for this purpose. We use both archival interferometric 8.4 GHz data (from the Very Large Array and ATCA, for the full sample of 599 sources) and concurrent single-dish 15 GHz measurements from the Owens Valley Radio Observatory (OVRO, for a sub sample of 199 objects). Our unprecedentedly large sample permits us to assess with high accuracy the statistical significance of the correlation, using amore » surrogate data method designed to simultaneously account for common-distance bias and the effect of a limited dynamical range in the observed quantities. We find that the statistical significance of a positive correlation between the centimeter radio and the broadband (E > 100 MeV) gamma-ray energy flux is very high for the whole AGN sample, with a probability of <10 –7 for the correlation appearing by chance. Using the OVRO data, we find that concurrent data improve the significance of the correlation from 1.6 × 10 –6 to 9.0 × 10 –8. Our large sample size allows us to study the dependence of correlation strength and significance on specific source types and gamma-ray energy band. As a result, we find that the correlation is very significant (chance probability < 10 –7) for both flat spectrum radio quasars and BL Lac objects separately; a dependence of the correlation strength on the considered gamma-ray energy band is also present, but additional data will be necessary to constrain its significance.« less

The Radio/Gamma-Ray Connection in Active Galactic Nuclei in the Era of the Fermi Large Area Telescope

NASA Technical Reports Server (NTRS)

Ackermann, M.; Ajello, M.; Allafort, A.; Angelakis, E.; Axelsson, M.; Baldini, L.; Ballet, J.; Barbiellini, G.; Bastieri, D.; Bellazzini, R.;

Extending local canonical correlation analysis to handle general linear contrasts for FMRI data.

PubMed

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic.

Extending Local Canonical Correlation Analysis to Handle General Linear Contrasts for fMRI Data

PubMed Central

Jin, Mingwu; Nandy, Rajesh; Curran, Tim; Cordes, Dietmar

2012-01-01

Local canonical correlation analysis (CCA) is a multivariate method that has been proposed to more accurately determine activation patterns in fMRI data. In its conventional formulation, CCA has several drawbacks that limit its usefulness in fMRI. A major drawback is that, unlike the general linear model (GLM), a test of general linear contrasts of the temporal regressors has not been incorporated into the CCA formalism. To overcome this drawback, a novel directional test statistic was derived using the equivalence of multivariate multiple regression (MVMR) and CCA. This extension will allow CCA to be used for inference of general linear contrasts in more complicated fMRI designs without reparameterization of the design matrix and without reestimating the CCA solutions for each particular contrast of interest. With the proper constraints on the spatial coefficients of CCA, this test statistic can yield a more powerful test on the inference of evoked brain regional activations from noisy fMRI data than the conventional t-test in the GLM. The quantitative results from simulated and pseudoreal data and activation maps from fMRI data were used to demonstrate the advantage of this novel test statistic. PMID:22461786

Histogram analysis parameters of apparent diffusion coefficient reflect tumor cellularity and proliferation activity in head and neck squamous cell carcinoma

PubMed Central

Winter, Karsten; Richter, Cindy; Hoehn, Anna-Kathrin

2018-01-01

Our purpose was to analyze associations between apparent diffusion coefficient (ADC) histogram analysis parameters and histopathologicalfeatures in head and neck squamous cell carcinoma (HNSCC). The study involved 32 patients with primary HNSCC. For every tumor, the following histogram analysis parameters were calculated: ADCmean, ADCmax, ADCmin, ADCmedian, ADCmode, P10, P25, P75, P90, kurtosis, skewness, and entropy. Furthermore, proliferation index KI 67, cell count, total and average nucleic areas were estimated. Spearman's correlation coefficient (p) was used to analyze associations between investigated parameters. In overall sample, all ADC values showed moderate inverse correlations with KI 67. All ADC values except ADCmax correlated inversely with tumor cellularity. Slightly correlations were identified between total/average nucleic area and ADCmean, ADCmin, ADCmedian, and P25. In G1/2 tumors, only ADCmode correlated well with Ki67. No statistically significant correlations between ADC parameters and cellularity were found. In G3 tumors, Ki 67 correlated with all ADC parameters except ADCmode. Cell count correlated well with all ADC parameters except ADCmax. Total nucleic area correlated inversely with ADCmean, ADCmin, ADCmedian, P25, and P90. ADC histogram parameters reflect proliferation potential and cellularity in HNSCC. The associations between histopathology and imaging depend on tumor grading. PMID:29805759

Mesopic pupil size in a refractive surgery population (13,959 eyes).

PubMed

Linke, Stephan J; Baviera, Julio; Munzer, Gur; Fricke, Otto H; Richard, Gisbert; Katz, Toam

2012-08-01

To evaluate factors that may affect mesopic pupil size in refractive surgery candidates. Medical records of 13,959 eyes of 13,959 refractive surgery candidates were reviewed, and one eye per subject was selected randomly for statistical analysis. Detailed ophthalmological examination data were obtained from medical records. Preoperative measurements included uncorrected distance visual acuity, corrected distance visual acuity, manifest and cycloplegic refraction, topography, slit lamp examination, and funduscopy. Mesopic pupil size measurements were performed with Colvard pupillometer. Relationship between mesopic pupil size and age, gender, refractive state, average keratometry, and pachymetry (thinnest point) were analyzed by means of ANOVA (+ANCOVA) and multivariate regression analyses. Overall mesopic pupil size was 6.45 ± 0.82 mm, and mean age was 36.07 years. Mesopic pupil size was 5.96 ± 0.8 mm in hyperopic astigmatism, 6.36 ± 0.83 mm in high astigmatism, and 6.51 ± 0.8 mm in myopic astigmatism. The difference in mesopic pupil size between all refractive subgroups was statistically significant (p < 0.001). Age revealed the strongest correlation (r = -0.405, p < 0.001) with mesopic pupil size. Spherical equivalent showed a moderate correlation (r = -0.136), whereas keratometry (r = -0.064) and pachymetry (r = -0.057) had a weak correlation with mesopic pupil size. No statistically significant difference in mesopic pupil size was noted regarding gender and ocular side. The sum of all analyzed factors (age, refractive state, keratometry, and pachymetry) can only predict the expected pupil size in <20% (R = 0.179, p < 0.001). Our analysis confirmed that age and refractive state are determinative factors on mesopic pupil size. Average keratometry and minimal pachymetry exhibited a statistically significant, but clinically insignificant, impact on mesopic pupil size.

Statistical Analysis of Human Body Movement and Group Interactions in Response to Music

NASA Astrophysics Data System (ADS)

Desmet, Frank; Leman, Marc; Lesaffre, Micheline; de Bruyn, Leen

Quantification of time series that relate to physiological data is challenging for empirical music research. Up to now, most studies have focused on time-dependent responses of individual subjects in controlled environments. However, little is known about time-dependent responses of between-subject interactions in an ecological context. This paper provides new findings on the statistical analysis of group synchronicity in response to musical stimuli. Different statistical techniques were applied to time-dependent data obtained from an experiment on embodied listening in individual and group settings. Analysis of inter group synchronicity are described. Dynamic Time Warping (DTW) and Cross Correlation Function (CCF) were found to be valid methods to estimate group coherence of the resulting movements. It was found that synchronicity of movements between individuals (human-human interactions) increases significantly in the social context. Moreover, Analysis of Variance (ANOVA) revealed that the type of music is the predominant factor in both the individual and the social context.

Length bias correction in gene ontology enrichment analysis using logistic regression.

PubMed

Mi, Gu; Di, Yanming; Emerson, Sarah; Cumbie, Jason S; Chang, Jeff H

2012-01-01

When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called "length bias", will influence subsequent analyses such as Gene Ontology enrichment analysis. In the presence of length bias, Gene Ontology categories that include longer genes are more likely to be identified as enriched. These categories, however, are not necessarily biologically more relevant. We show that one can effectively adjust for length bias in Gene Ontology analysis by including transcript length as a covariate in a logistic regression model. The logistic regression model makes the statistical issue underlying length bias more transparent: transcript length becomes a confounding factor when it correlates with both the Gene Ontology membership and the significance of the differential expression test. The inclusion of the transcript length as a covariate allows one to investigate the direct correlation between the Gene Ontology membership and the significance of testing differential expression, conditional on the transcript length. We present both real and simulated data examples to show that the logistic regression approach is simple, effective, and flexible.

Monitoring the metering performance of an electronic voltage transformer on-line based on cyber-physics correlation analysis

NASA Astrophysics Data System (ADS)

Zhang, Zhu; Li, Hongbin; Tang, Dengping; Hu, Chen; Jiao, Yang

2017-10-01

Metering performance is the key parameter of an electronic voltage transformer (EVT), and it requires high accuracy. The conventional off-line calibration method using a standard voltage transformer is not suitable for the key equipment in a smart substation, which needs on-line monitoring. In this article, we propose a method for monitoring the metering performance of an EVT on-line based on cyber-physics correlation analysis. By the electrical and physical properties of a substation running in three-phase symmetry, the principal component analysis method is used to separate the metering deviation caused by the primary fluctuation and the EVT anomaly. The characteristic statistics of the measured data during operation are extracted, and the metering performance of the EVT is evaluated by analyzing the change in statistics. The experimental results show that the method successfully monitors the metering deviation of a Class 0.2 EVT accurately. The method demonstrates the accurate evaluation of on-line monitoring of the metering performance on an EVT without a standard voltage transformer.

Sieve analysis in HIV-1 vaccine efficacy trials

PubMed Central

Edlefsen, Paul T.; Gilbert, Peter B.; Rolland, Morgane

2013-01-01

Purpose of review The genetic characterization of HIV-1 breakthrough infections in vaccine and placebo recipients offers new ways to assess vaccine efficacy trials. Statistical and sequence analysis methods provide opportunities to mine the mechanisms behind the effect of an HIV vaccine. Recent findings The release of results from two HIV-1 vaccine efficacy trials, Step/HVTN-502 and RV144, led to numerous studies in the last five years, including efforts to sequence HIV-1 breakthrough infections and compare viral characteristics between the vaccine and placebo groups. Novel genetic and statistical analysis methods uncovered features that distinguished founder viruses isolated from vaccinees from those isolated from placebo recipients, and identified HIV-1 genetic targets of vaccine-induced immune responses. Summary Studies of HIV-1 breakthrough infections in vaccine efficacy trials can provide an independent confirmation to correlates of risk studies, as they take advantage of vaccine/placebo comparisons while correlates of risk analyses are limited to vaccine recipients. Through the identification of viral determinants impacted by vaccine-mediated host immune responses, sieve analyses can shed light on potential mechanisms of vaccine protection. PMID:23719202

Sieve analysis in HIV-1 vaccine efficacy trials.

PubMed

Edlefsen, Paul T; Gilbert, Peter B; Rolland, Morgane

2013-09-01

The genetic characterization of HIV-1 breakthrough infections in vaccine and placebo recipients offers new ways to assess vaccine efficacy trials. Statistical and sequence analysis methods provide opportunities to mine the mechanisms behind the effect of an HIV vaccine. The release of results from two HIV-1 vaccine efficacy trials, Step/HVTN-502 (HIV Vaccine Trials Network-502) and RV144, led to numerous studies in the last 5 years, including efforts to sequence HIV-1 breakthrough infections and compare viral characteristics between the vaccine and placebo groups. Novel genetic and statistical analysis methods uncovered features that distinguished founder viruses isolated from vaccinees from those isolated from placebo recipients, and identified HIV-1 genetic targets of vaccine-induced immune responses. Studies of HIV-1 breakthrough infections in vaccine efficacy trials can provide an independent confirmation to correlates of risk studies, as they take advantage of vaccine/placebo comparisons, whereas correlates of risk analyses are limited to vaccine recipients. Through the identification of viral determinants impacted by vaccine-mediated host immune responses, sieve analyses can shed light on potential mechanisms of vaccine protection.

Fractal mechanisms and heart rate dynamics. Long-range correlations and their breakdown with disease

NASA Technical Reports Server (NTRS)

Peng, C. K.; Havlin, S.; Hausdorff, J. M.; Mietus, J. E.; Stanley, H. E.; Goldberger, A. L.

1995-01-01

Under healthy conditions, the normal cardiac (sinus) interbeat interval fluctuates in a complex manner. Quantitative analysis using techniques adapted from statistical physics reveals the presence of long-range power-law correlations extending over thousands of heartbeats. This scale-invariant (fractal) behavior suggests that the regulatory system generating these fluctuations is operating far from equilibrium. In contrast, it is found that for subjects at high risk of sudden death (e.g., congestive heart failure patients), these long-range correlations break down. Application of fractal scaling analysis and related techniques provides new approaches to assessing cardiac risk and forecasting sudden cardiac death, as well as motivating development of novel physiologic models of systems that appear to be heterodynamic rather than homeostatic.

A Statistical Study of Eiscat Electron and Ion Temperature Measurements In The E-region

NASA Astrophysics Data System (ADS)

Hussey, G.; Haldoupis, C.; Schlegel, K.; Bösinger, T.

Motivated by the large EISCAT data base, which covers over 15 years of common programme operation, and previous statistical work with EISCAT data (e.g., C. Hal- doupis, K. Schlegel, and G. Hussey, Auroral E-region electron density gradients mea- sured with EISCAT, Ann. Geopshysicae, 18, 1172-1181, 2000), a detailed statistical analysis of electron and ion EISCAT temperature measurements has been undertaken. This study was specifically concerned with the statistical dependence of heating events with other ambient parameters such as the electric field and electron density. The re- sults showed previously reported dependences such as the electron temperature being directly correlated with the ambient electric field and inversely related to the electron density. However, these correlations were found to be also dependent upon altitude. There was also evidence of the so called "Schlegel effect" (K. Schlegel, Reduced effective recombination coefficient in the disturbed polar E-region, J. Atmos. Terr. Phys., 44, 183-185, 1982); that is, the heated electron gas leads to increases in elec- tron density through a reduction in the recombination rate. This paper will present the statistical heating results and attempt to offer physical explanations and interpretations of the findings.

Statistical properties of the radiation from SASE FEL operating in the linear regime

NASA Astrophysics Data System (ADS)

Saldin, E. L.; Schneidmiller, E. A.; Yurkov, M. V.

1998-02-01

The paper presents comprehensive analysis of statistical properties of the radiation from self amplified spontaneous emission (SASE) free electron laser operating in linear mode. The investigation has been performed in a one-dimensional approximation, assuming the electron pulse length to be much larger than a coherence length of the radiation. The following statistical properties of the SASE FEL radiation have been studied: field correlations, distribution of the radiation energy after monochromator installed at the FEL amplifier exit and photoelectric counting statistics of SASE FEL radiation. It is shown that the radiation from SASE FEL operating in linear regime possesses all the features corresponding to completely chaotic polarized radiation.

Statistical link between external climate forcings and modes of ocean variability

NASA Astrophysics Data System (ADS)

Malik, Abdul; Brönnimann, Stefan; Perona, Paolo

2017-07-01

In this study we investigate statistical link between external climate forcings and modes of ocean variability on inter-annual (3-year) to centennial (100-year) timescales using de-trended semi-partial-cross-correlation analysis technique. To investigate this link we employ observations (AD 1854-1999), climate proxies (AD 1600-1999), and coupled Atmosphere-Ocean-Chemistry Climate Model simulations with SOCOL-MPIOM (AD 1600-1999). We find robust statistical evidence that Atlantic multi-decadal oscillation (AMO) has intrinsic positive correlation with solar activity in all datasets employed. The strength of the relationship between AMO and solar activity is modulated by volcanic eruptions and complex interaction among modes of ocean variability. The observational dataset reveals that El Niño southern oscillation (ENSO) has statistically significant negative intrinsic correlation with solar activity on decadal to multi-decadal timescales (16-27-year) whereas there is no evidence of a link on a typical ENSO timescale (2-7-year). In the observational dataset, the volcanic eruptions do not have a link with AMO on a typical AMO timescale (55-80-year) however the long-term datasets (proxies and SOCOL-MPIOM output) show that volcanic eruptions have intrinsic negative correlation with AMO on inter-annual to multi-decadal timescales. The Pacific decadal oscillation has no link with solar activity, however, it has positive intrinsic correlation with volcanic eruptions on multi-decadal timescales (47-54-year) in reconstruction and decadal to multi-decadal timescales (16-32-year) in climate model simulations. We also find evidence of a link between volcanic eruptions and ENSO, however, the sign of relationship is not consistent between observations/proxies and climate model simulations.

[Correlation of adverse childhood experiences with psychiatric disorders and aggressiveness in adulthood].

PubMed

Samardzić, Ljiljana; Nikolić, Gordana; Grbesa, Grozdanko; Simonović, Maja; Milenković, Tatjana

2010-08-01

Consequences of individual adverse childhood experiences for adult mental health have been precisely studied during past decades. The focus of past research was mainly on childhood maltreatment and neglect. The aim of this paper was to determine association between multiple adverse childhood experiences and psychiatric disorders, as well as their correlation to the degree and type of aggressiveness in adult psychiatric patients. One hundred and thirteen psychiatric outpatients were divided into three diagnostic groups: psychotics, non-psychotics and alcoholics and compared with fourty healthy individuals. Adverse childhood experiences data were gathered retrospectively, using the Adverse childhood experiences questionnaire and explanatory interview. Aggressiveness was assessed using Buss-Perry Aggression Questionnaire. The Student's t test, ANOVA and correlational analysis were used for evaluation of statistical significance of differences among the groups. A value p < 0.05 was considered statistically significant. Our results showed that the mean number of adverse childhood experiences in each group of psychiatric patients, as well as in the whole group of patients, was statistically significantly higher than in the group of healthy individuals (p < 0.001); there was a statistically significant difference in score of physical aggressiveness between the patients exposed to adverse childhood experiences and those who were not exposed to them (p < 0.05); scores of physical aggressiveness were in positive correlation with the number of adverse childhood experiences (p < 0.05). The highest mean score of adverse childhood experiences was evidenced in the group of patients with psychotic disorders. Multiple adverse childhood experiences are significantly associated with psychotic disorders, nonpsychotic disorders and alcohol dependence in adulthood and their presence is important morbidity risk factor for psychiatric disorders. They are in positive correlation with physical aggressiveness of the patients from these diagnostic groups.

Autocorrel I: A Neural Network Based Network Event Correlation Approach

DTIC Science & Technology

2005-05-01

which concern any component of the network. 2.1.1 Existing Intrusion Detection Systems EMERALD [8] is a distributed, scalable, hierarchal, customizable...writing this paper, the updaters of this system had not released their correlation unit to the public. EMERALD ex- plicitly divides statistical analysis... EMERALD , NetSTAT is scalable and composi- ble. QuidSCOR [12] is an open-source IDS, though it requires a subscription from its publisher, Qualys Inc

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.

Multispectral determination of soil moisture-2. [Guymon, Oklahoma and Dalhart, Texas

NASA Technical Reports Server (NTRS)

Estes, J. E.; Simonett, D. S. (Principal Investigator); Hajic, E. J.; Hilton, B. M.; Lees, R. D.

1982-01-01

Soil moisture data obtained using scatterometers, modular multispectral scanners and passive microwave radiometers were revised and grouped into four field cover types for statistical anaysis. Guymon data are grouped as alfalfa, bare, milo with rows perpendicular to the field view, and milo viewed parallel to the field of view. Dalhart data are grouped as bare combo, stubble, disked stubble, and corn field. Summary graphs combine selected analyses to compare the effects of field cover. The analysis for each of the cover types is presented in tables and graphs. Other tables show elementary statistics, correlation matrices, and single variable regressions. Selected eigenvectors and factor analyses are included and the highest correlating sensor typs for each location are summarized.

Reassessment of the relationship between M-protein decrement and survival in multiple myeloma.

PubMed

Palmer, M; Belch, A; Hanson, J; Brox, L

1989-01-01

The relationship between percentage M-protein decrement and survival is assessed in 134 multiple myeloma patients. The correlation did not achieve statistical significance (P = 0.069). Multivariate analysis using the Cox proportional hazards model, including a number of previously recognised prognostic factors, showed only percentage M-protein decrement, creatinine and haemoglobin to be significantly correlated with survival. However, the R'-statistic for each of these variables was low, indicating that their prognostic power is weak. We conclude that neither the percentage M-protein decrement nor the response derived from it can be used as an accurate means of assessing the efficacy of treatment in myeloma. Mature survival data alone should be used for this purpose.

Reassessment of the relationship between M-protein decrement and survival in multiple myeloma.

PubMed Central

Palmer, M.; Belch, A.; Hanson, J.; Brox, L.

1989-01-01

The relationship between percentage M-protein decrement and survival is assessed in 134 multiple myeloma patients. The correlation did not achieve statistical significance (P = 0.069). Multivariate analysis using the Cox proportional hazards model, including a number of previously recognised prognostic factors, showed only percentage M-protein decrement, creatinine and haemoglobin to be significantly correlated with survival. However, the R'-statistic for each of these variables was low, indicating that their prognostic power is weak. We conclude that neither the percentage M-protein decrement nor the response derived from it can be used as an accurate means of assessing the efficacy of treatment in myeloma. Mature survival data alone should be used for this purpose. PMID:2757916

Non Kolmogorov Probability Models Outside Quantum Mechanics

NASA Astrophysics Data System (ADS)

Accardi, Luigi

2009-03-01

This paper is devoted to analysis of main conceptual problems in the interpretation of QM: reality, locality, determinism, physical state, Heisenberg principle, "deterministic" and "exact" theories, laws of chance, notion of event, statistical invariants, adaptive realism, EPR correlations and, finally, the EPR-chameleon experiment.

Correlation analysis of respiratory signals by using parallel coordinate plots.

PubMed

Saatci, Esra

2018-01-01

The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data. In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP. The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals. It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data. Copyright © 2017 Elsevier B.V. All rights reserved.

Statistical analysis and interpolation of compositional data in materials science.

PubMed

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

2015-02-09

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

An Evaluation of the Psychometric Properties of Three Different Forms of Daly and Miller's Writing Apprehension Test through Rasch Analysis

ERIC Educational Resources Information Center

Güler, Nese; Ilhan, Mustafa; Güneyli, Ahmet; Demir, Süleyman

2017-01-01

This study evaluates the psychometric properties of three different forms of the Writing Apprehension Test (WAT; Daly & Miller, 1975) through Rasch analysis. For this purpose, the fit statistics and correlation coefficients, and the reliability, separation ratio, and chi-square values for the facets of item and person calculated for the…

Effectiveness of Quantitative Real Time PCR in Long-Term Follow-up of Chronic Myeloid Leukemia Patients.

PubMed

Savasoglu, Kaan; Payzin, Kadriye Bahriye; Ozdemirkiran, Fusun; Berber, Belgin

2015-08-01

To determine the use of the Quantitative Real Time PCR (RQ-PCR) assay follow-up with Chronic Myeloid Leukemia (CML) patients. Cross-sectional observational. Izmir Ataturk Education and Research Hospital, Izmir, Turkey, from 2009 to 2013. Cytogenetic, FISH, RQ-PCR test results from 177 CMLpatients' materials selected between 2009 - 2013 years was set up for comparison analysis. Statistical analysis was performed to compare between FISH, karyotype and RQ-PCR results of the patients. Karyotyping and FISH specificity and sensitivity rates determined by ROC analysis compared with RQ-PCR results. Chi-square test was used to compare test failure rates. Sensitivity and specificity values were determined for karyotyping 17.6 - 98% (p=0.118, p > 0.05) and for FISH 22.5 - 96% (p=0.064, p > 0.05) respectively. FISH sensitivity was slightly higher than karyotyping but there was calculated a strong correlation between them (p < 0.001). RQ-PCR test failure rate did not correlate with other two tests (p > 0.05); however, karyotyping and FISH test failure rate was statistically significant (p < 0.001). Besides, the situation needed for karyotype analysis, RQ-PCR assay can be used alone in the follow-up of CMLdisease.

Image encryption based on a delayed fractional-order chaotic logistic system

NASA Astrophysics Data System (ADS)

Wang, Zhen; Huang, Xia; Li, Ning; Song, Xiao-Na

2012-05-01

A new image encryption scheme is proposed based on a delayed fractional-order chaotic logistic system. In the process of generating a key stream, the time-varying delay and fractional derivative are embedded in the proposed scheme to improve the security. Such a scheme is described in detail with security analyses including correlation analysis, information entropy analysis, run statistic analysis, mean-variance gray value analysis, and key sensitivity analysis. Experimental results show that the newly proposed image encryption scheme possesses high security.

Influence of eye biometrics and corneal micro-structure on noncontact tonometry.

PubMed

Jesus, Danilo A; Majewska, Małgorzata; Krzyżanowska-Berkowska, Patrycja; Iskander, D Robert

2017-01-01

Tonometry is widely used as the main screening tool supporting glaucoma diagnosis. Still, its accuracy could be improved if full knowledge about the variation of the corneal biomechanical properties was available. In this study, Optical Coherence Tomography (OCT) speckle statistics are used to infer the organisation of the corneal micro-structure and hence, to analyse its influence on intraocular pressure (IOP) measurements. Fifty-six subjects were recruited for this prospective study. Macro and micro-structural corneal parameters as well as subject age were considered. Macro-structural analysis included the parameters that are associated with the ocular anatomy, such as central corneal thickness (CCT), corneal radius, axial length, anterior chamber depth and white-to-white corneal diameter. Micro-structural parameters which included OCT speckle statistics were related to the internal organisation of the corneal tissue and its physiological changes during lifetime. The corneal speckle obtained from OCT was modelled with the Generalised Gamma (GG) distribution that is characterised with a scale parameter and two shape parameters. In macro-structure analysis, only CCT showed a statistically significant correlation with IOP (R2 = 0.25, p<0.001). The scale parameter and the ratio of the shape parameters of GG distribution showed statistically significant correlation with IOP (R2 = 0.19, p<0.001 and R2 = 0.17, p<0.001, respectively). For the studied group, a weak, although significant correlation was found between age and IOP (R2 = 0.053, p = 0.04). Forward stepwise regression showed that CCT and the scale parameter of the Generalised Gamma distribution can be combined in a regression model (R2 = 0.39, p<0.001) to study the role of the corneal structure on IOP. We show, for the first time, that corneal micro-structure influences the IOP measurements obtained from noncontact tonometry. OCT speckle statistics can be employed to learn about the corneal micro-structure and hence, to further calibrate the IOP measurements.

Esthetic evaluation of maxillary single-tooth implants in the esthetic zone

PubMed Central

Cho, Hae-Lyung; Lee, Jae-Kwan; Um, Heung-Sik

2010-01-01

Purpose The aim of this study is to assess the influence exerted by the observer's dental specialization and compare patients' opinion with observers' opinion of the esthetics of maxillary single-tooth implants in the esthetic zone. Methods Forty-one adult patients, who were treated with a single implant in the esthetic zone, were enrolled in this study. Eight observers (2 periodontists, 2 prosthodontists, 2 orthodontists and 2 senior dental students) applied the pink esthetic score (PES)/white esthetic score (WES) to 41 implant-supported single restorations twice with an interval of 4 weeks. We used a visual analog scale (VAS) to assess the patient's satisfaction with the treatment outcome from an esthetic point of view. Results In the PES/WES, very good and moderate intraobserver agreements were noted between the first and second rating. The mean total PES/WES was 11.19 ± 3.59. The mean PES was 5.17 ± 2.29 and mean WES was 6.02 ± 1.96. In the total PES/WES, the difference between the groups was not significant. However, in the WES, the difference between the groups was significant and prosthodontists were found to have assigned poorer ratings than the other groups. Periodontists gave higher ratings than prosthodontists and senior dental students. Orthodontists were clearly more critical than the other observers. The statistical analysis revealed statistically significant correlation between patients' esthetic perception and dentists' perception of the anterior tooth. However, the correlation between the total PES/WES and the VAS score for the first premolar was not statistically significant. Conclusions The PES/WES is an objective tool in rating the esthetics of implant supported single crowns and adjacent soft tissues. Orthodontists were the most critical observers, while periodontists were more generous than other observers. The statistical analysis revealed a statistically significant correlation between patients' esthetic perception and dentists' perception of the anterior tooth. PMID:20827328

Influence of eye biometrics and corneal micro-structure on noncontact tonometry

PubMed Central

Majewska, Małgorzata; Krzyżanowska-Berkowska, Patrycja; Iskander, D. Robert

2017-01-01

Purpose Tonometry is widely used as the main screening tool supporting glaucoma diagnosis. Still, its accuracy could be improved if full knowledge about the variation of the corneal biomechanical properties was available. In this study, Optical Coherence Tomography (OCT) speckle statistics are used to infer the organisation of the corneal micro-structure and hence, to analyse its influence on intraocular pressure (IOP) measurements. Methods Fifty-six subjects were recruited for this prospective study. Macro and micro-structural corneal parameters as well as subject age were considered. Macro-structural analysis included the parameters that are associated with the ocular anatomy, such as central corneal thickness (CCT), corneal radius, axial length, anterior chamber depth and white-to-white corneal diameter. Micro-structural parameters which included OCT speckle statistics were related to the internal organisation of the corneal tissue and its physiological changes during lifetime. The corneal speckle obtained from OCT was modelled with the Generalised Gamma (GG) distribution that is characterised with a scale parameter and two shape parameters. Results In macro-structure analysis, only CCT showed a statistically significant correlation with IOP (R2 = 0.25, p<0.001). The scale parameter and the ratio of the shape parameters of GG distribution showed statistically significant correlation with IOP (R2 = 0.19, p<0.001 and R2 = 0.17, p<0.001, respectively). For the studied group, a weak, although significant correlation was found between age and IOP (R2 = 0.053, p = 0.04). Forward stepwise regression showed that CCT and the scale parameter of the Generalised Gamma distribution can be combined in a regression model (R2 = 0.39, p<0.001) to study the role of the corneal structure on IOP. Conclusions We show, for the first time, that corneal micro-structure influences the IOP measurements obtained from noncontact tonometry. OCT speckle statistics can be employed to learn about the corneal micro-structure and hence, to further calibrate the IOP measurements. PMID:28472178

Creation of a virtual cutaneous tissue bank

NASA Astrophysics Data System (ADS)

LaFramboise, William A.; Shah, Sujal; Hoy, R. W.; Letbetter, D.; Petrosko, P.; Vennare, R.; Johnson, Peter C.

2000-04-01

Cellular and non-cellular constituents of skin contain fundamental morphometric features and structural patterns that correlate with tissue function. High resolution digital image acquisitions performed using an automated system and proprietary software to assemble adjacent images and create a contiguous, lossless, digital representation of individual microscope slide specimens. Serial extraction, evaluation and statistical analysis of cutaneous feature is performed utilizing an automated analysis system, to derive normal cutaneous parameters comprising essential structural skin components. Automated digital cutaneous analysis allows for fast extraction of microanatomic dat with accuracy approximating manual measurement. The process provides rapid assessment of feature both within individual specimens and across sample populations. The images, component data, and statistical analysis comprise a bioinformatics database to serve as an architectural blueprint for skin tissue engineering and as a diagnostic standard of comparison for pathologic specimens.

Phenotypic mapping of metabolic profiles using self-organizing maps of high-dimensional mass spectrometry data.

PubMed

Goodwin, Cody R; Sherrod, Stacy D; Marasco, Christina C; Bachmann, Brian O; Schramm-Sapyta, Nicole; Wikswo, John P; McLean, John A

2014-07-01

A metabolic system is composed of inherently interconnected metabolic precursors, intermediates, and products. The analysis of untargeted metabolomics data has conventionally been performed through the use of comparative statistics or multivariate statistical analysis-based approaches; however, each falls short in representing the related nature of metabolic perturbations. Herein, we describe a complementary method for the analysis of large metabolite inventories using a data-driven approach based upon a self-organizing map algorithm. This workflow allows for the unsupervised clustering, and subsequent prioritization of, correlated features through Gestalt comparisons of metabolic heat maps. We describe this methodology in detail, including a comparison to conventional metabolomics approaches, and demonstrate the application of this method to the analysis of the metabolic repercussions of prolonged cocaine exposure in rat sera profiles.

Validation of a food frequency questionnaire for Japanese pregnant women with and without nausea and vomiting in early pregnancy.

PubMed

Ogawa, Kohei; Jwa, Seung-Chik; Kobayashi, Minatsu; Morisaki, Naho; Sago, Haruhiko; Fujiwara, Takeo

2017-05-01

No previous study has shown the validity of a food frequency questionnaire (FFQ) in early pregnancy with consideration of nausea and vomiting during pregnancy (NVP). The aim of this study was to evaluate the validity of a FFQ in early pregnancy for Japanese pregnant women. We included 188 women before 15 weeks of gestation and compared estimated nutrient intake and food group intake based on a modified FFQ with that based on 3-day dietary records (DRs). Spearman's rank correlation coefficients, adjusting energy intake and attenuating within-person error, were calculated. Subgroup analysis for those with and without NVP was conducted. We also examined the degree of appropriate classification across categories between FFQ and DRs through division of consumption of nutrients and food groups into quintiles. Crude Spearman's correlation coefficients of nutrients ranged from 0.098 (sodium) to 0.401 (vitamin C), and all of the 36 nutrients were statistically significant. In 27 food groups, correlation coefficients ranged from -0.015 (alcohol) to 0.572 (yogurt), and 81% were statistically significant. In subgroup analysis, correlation coefficients in 89% of nutrients and 70% of food groups in women with NVP and 97% of nutrients and 74% of food groups in women without NVP were statistically significant. On average, 63.7% of nutrients and 60.4% of food groups were classified into same or adjacent quintiles according to the FFQ and DRs. The FFQ is a useful instrument, regardless of NVP, for assessing the diet of women in early pregnancy in Japan. Copyright © 2016 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Multiple regression and Artificial Neural Network for long-term rainfall forecasting using large scale climate modes

NASA Astrophysics Data System (ADS)

Mekanik, F.; Imteaz, M. A.; Gato-Trinidad, S.; Elmahdi, A.

2013-10-01

In this study, the application of Artificial Neural Networks (ANN) and Multiple regression analysis (MR) to forecast long-term seasonal spring rainfall in Victoria, Australia was investigated using lagged El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) as potential predictors. The use of dual (combined lagged ENSO-IOD) input sets for calibrating and validating ANN and MR Models is proposed to investigate the simultaneous effect of past values of these two major climate modes on long-term spring rainfall prediction. The MR models that did not violate the limits of statistical significance and multicollinearity were selected for future spring rainfall forecast. The ANN was developed in the form of multilayer perceptron using Levenberg-Marquardt algorithm. Both MR and ANN modelling were assessed statistically using mean square error (MSE), mean absolute error (MAE), Pearson correlation (r) and Willmott index of agreement (d). The developed MR and ANN models were tested on out-of-sample test sets; the MR models showed very poor generalisation ability for east Victoria with correlation coefficients of -0.99 to -0.90 compared to ANN with correlation coefficients of 0.42-0.93; ANN models also showed better generalisation ability for central and west Victoria with correlation coefficients of 0.68-0.85 and 0.58-0.97 respectively. The ability of multiple regression models to forecast out-of-sample sets is compatible with ANN for Daylesford in central Victoria and Kaniva in west Victoria (r = 0.92 and 0.67 respectively). The errors of the testing sets for ANN models are generally lower compared to multiple regression models. The statistical analysis suggest the potential of ANN over MR models for rainfall forecasting using large scale climate modes.

Serum concentrations of soluble (s)L- and (s)P-selectins in women with ovarian cancer.

PubMed

Majchrzak-Baczmańska, Dominika B; Głowacka, Ewa; Wilczyński, Miłosz; Malinowski, Andrzej

2018-03-01

The aim of the study was to compare serum concentration of soluble L- and P-selectins in women with ovarian cancer (OC) and healthy controls, and to investigate sL- and sP-selectin levels with regard to clinical and pathological parameters. Correlation analysis was used to measure the following: sL- and sP-selectin concentration and Ca125; sP-selectin and platelet concentrations; and sL-selectin and serum leukocyte levels in women with OC. The study included 29 patients with OC and 23 healthy controls. Serum concentrations of sL- and sP-selectins were measured in all subjects. Routine diagnostic tests: CBC and USG (both groups) and Ca125 (study group) were performed. Significantly higher serum concentrations of sL- and sP-selectins were found in the study group as compared to controls. Lower levels of serum sL-selectin were observed in women with poorly-differentiated OC (G3) and advanced stages of the disease (FIGO III, IV), but the results were statistically insignificant. No statistically significant relationship was detected between sP-selectin serum concentration in women with OC and tumour differentiation, histological type, and stage of the disease. No significant correlation was found between sL- and sP-selectins and Ca125 levels. A weak correlation was found between serum concentration of sP-selectin in women with OC and platelet count. No statistically significant correlation was observed between sL-selectin concentration and serum leukocyte levels in women with OC. The analysis of sL- and sP-selectin concentrations may be a useful tool in the diagnosis of OC. The levels of sL-selectin decrease with disease progression.

Human movement stochastic variability leads to diagnostic biomarkers In Autism Spectrum Disorders (ASD)

NASA Astrophysics Data System (ADS)

Wu, Di; Torres, Elizabeth B.; Jose, Jorge V.

2015-03-01

ASD is a spectrum of neurodevelopmental disorders. The high heterogeneity of the symptoms associated with the disorder impedes efficient diagnoses based on human observations. Recent advances with high-resolution MEM wearable sensors enable accurate movement measurements that may escape the naked eye. It calls for objective metrics to extract physiological relevant information from the rapidly accumulating data. In this talk we'll discuss the statistical analysis of movement data continuously collected with high-resolution sensors at 240Hz. We calculated statistical properties of speed fluctuations within the millisecond time range that closely correlate with the subjects' cognitive abilities. We computed the periodicity and synchronicity of the speed fluctuations' from their power spectrum and ensemble averaged two-point cross-correlation function. We built a two-parameter phase space from the temporal statistical analyses of the nearest neighbor fluctuations that provided a quantitative biomarker for ASD and adult normal subjects and further classified ASD severity. We also found age related developmental statistical signatures and potential ASD parental links in our movement dynamical studies. Our results may have direct clinical applications.

Correlation of MRI Visual Scales with Neuropsychological Profile in Mild Cognitive Impairment of Parkinson's Disease.

PubMed

Vasconcellos, Luiz Felipe; Pereira, João Santos; Adachi, Marcelo; Greca, Denise; Cruz, Manuela; Malak, Ana Lara; Charchat-Fichman, Helenice; Spitz, Mariana

2017-01-01

Few studies have evaluated magnetic resonance imaging (MRI) visual scales in Parkinson's disease-Mild Cognitive Impairment (PD-MCI). We selected 79 PD patients and 92 controls (CO) to perform neurologic and neuropsychological evaluation. Brain MRI was performed to evaluate the following scales: Global Cortical Atrophy (GCA), Fazekas, and medial temporal atrophy (MTA). The analysis revealed that both PD groups (amnestic and nonamnestic) showed worse performance on several tests when compared to CO. Memory, executive function, and attention impairment were more severe in amnestic PD-MCI group. Overall analysis of frequency of MRI visual scales by MCI subtype did not reveal any statistically significant result. Statistically significant inverse correlation was observed between GCA scale and Mini-Mental Status Examination (MMSE), Montreal Cognitive Assessment (MoCA), semantic verbal fluency, Stroop test, figure memory test, trail making test (TMT) B, and Rey Auditory Verbal Learning Test (RAVLT). The MTA scale correlated with Stroop test and Fazekas scale with figure memory test, digit span, and Stroop test according to the subgroup evaluated. Visual scales by MRI in MCI should be evaluated by cognitive domain and might be more useful in more severely impaired MCI or dementia patients.

Antenna systems for base station diversity in urban small and micro cells

NASA Astrophysics Data System (ADS)

Eggers, Patrick C. F.; Toftgard, Jorn; Oprea, Alex M.

1993-09-01

This paper describes cross-correlation properties for compact urban base station antenna configurations, nearly all resulting in very low envelope cross-correlation coefficients of about 0.1 to 0.3. A focus is set on polarization diversity systems for their potential in improving link quality when hand-held terminals are involved. An expression is given for the correlation function of compound space and polarization diversity systems. Dispersion and envelope dynamic statistics are presented for the measured environments. For microcell applications, it is found that systems such as GSM having a bandwidth of 200 MHz or less can use narrowband cross-correlation analysis directly.

Gas detection by correlation spectroscopy employing a multimode diode laser.

PubMed

Lou, Xiutao; Somesfalean, Gabriel; Zhang, Zhiguo

2008-05-01

A gas sensor based on the gas-correlation technique has been developed using a multimode diode laser (MDL) in a dual-beam detection scheme. Measurement of CO(2) mixed with CO as an interfering gas is successfully demonstrated using a 1570 nm tunable MDL. Despite overlapping absorption spectra and occasional mode hops, the interfering signals can be effectively excluded by a statistical procedure including correlation analysis and outlier identification. The gas concentration is retrieved from several pair-correlated signals by a linear-regression scheme, yielding a reliable and accurate measurement. This demonstrates the utility of the unsophisticated MDLs as novel light sources for gas detection applications.

Chronic atrophic gastritis in association with hair mercury level.

PubMed

Xue, Zeyun; Xue, Huiping; Jiang, Jianlan; Lin, Bing; Zeng, Si; Huang, Xiaoyun; An, Jianfu

2014-11-01

The objective of this study was to explore hair mercury level in association with chronic atrophic gastritis, a precancerous stage of gastric cancer (GC), and thus provide a brand new angle of view on the timely intervention of precancerous stage of GC. We recruited 149 healthy volunteers as controls and 152 patients suffering from chronic gastritis as cases. The controls denied upper gastrointestinal discomforts, and the cases were diagnosed as chronic superficial gastritis (n=68) or chronic atrophic gastritis (n=84). We utilized Mercury Automated Analyzer (NIC MA-3000) to detect hair mercury level of both healthy controls and cases of chronic gastritis. The statistic of measurement data was expressed as mean ± standard deviation, which was analyzed using Levene variance equality test and t test. Pearson correlation analysis was employed to determine associated factors affecting hair mercury levels, and multiple stepwise regression analysis was performed to deduce regression equations. Statistical significance is considered if p value is less than 0.05. The overall hair mercury level was 0.908949 ± 0.8844490 ng/g [mean ± standard deviation (SD)] in gastritis cases and 0.460198 ± 0.2712187 ng/g (mean±SD) in healthy controls; the former level was significantly higher than the latter one (p=0.000<0.01). The hair mercury level in chronic atrophic gastritis subgroup was 1.155220 ± 0.9470246 ng/g (mean ± SD) and that in chronic superficial gastritis subgroup was 0.604732 ± 0.6942509 ng/g (mean ± SD); the former level was significantly higher than the latter level (p<0.01). The hair mercury level in chronic superficial gastritis cases was significantly higher than that in healthy controls (p<0.05). The hair mercury level in chronic atrophic gastritis cases was significantly higher than that in healthy controls (p<0.01). Stratified analysis indicated that the hair mercury level in healthy controls with eating seafood was significantly higher than that in healthy controls without eating seafood (p<0.01) and that the hair mercury level in chronic atrophic gastritis cases was significantly higher than that in chronic superficial gastritis cases (p<0.01). Pearson correlation analysis indicated that eating seafood was most correlated with hair mercury level and positively correlated in the healthy controls and that the severity of gastritis was most correlated with hair mercury level and positively correlated in the gastritis cases. Multiple stepwise regression analysis indicated that the regression equation of hair mercury level in controls could be expressed as 0.262 multiplied the value of eating seafood plus 0.434, the model that was statistically significant (p<0.01). Multiple stepwise regression analysis also indicated that the regression equation of hair mercury level in gastritis cases could be expressed as 0.305 multiplied the severity of gastritis, the model that was also statistically significant (p<0.01). The graphs of regression standardized residual for both controls and cases conformed to normal distribution. The main positively correlated factor affecting the hair mercury level is eating seafood in healthy people whereas the predominant positively correlated factor affecting the hair mercury level is the severity of gastritis in chronic gastritis patients. That is to say, the severity of chronic gastritis is positively correlated with the level of hair mercury. The incessantly increased level of hair mercury possibly reflects the development of gastritis from normal stomach to superficial gastritis and to atrophic gastritis. The detection of hair mercury is potentially a means to predict the severity of chronic gastritis and possibly to insinuate the environmental mercury threat to human health in terms of gastritis or even carcinogenesis.

Civil construction work: The unseen contributor to the occupational and global disease burden

PubMed Central

Sitalakshmi, R.; Saikumar, P.; Jeyachandran, P.; Manoharan; Thangavel; Thomas, Jayakar

2016-01-01

Background: Construction industry is the second largest employment giving industry in India with many semi-skilled or unskilled workers taking up the occupation for livelihood without any training and proper guidance. Aim: To evaluate the pathogenic association of cement exposure to occupational contact dermatoses as evidenced by immune markers and to correlate their pulmonary functions with years of exposure to cement. Setting and Design: This was a cross-sectional study conducted among randomly selected cement workers. Methods and material: Evaluation of socioeconomic status (SES) and years of exposure of cement workers was done using a questionnaire. Clinical examination of skin lesions and strip patch test with application of potassium dichromate on unexposed skin was performed. Results were interpreted after 48 hours. Absolute eosinophil count (AEC) and IgE levels measured, and spirometric evaluation was performed. Statistical Analysis: Analysis of variance and Pearson's correlation test were used for data analysis. P < 0.05 was considered to be statistically significant. Results: Clinically, skin lesions were noticed in 51%, elevated AEC in 47%, and raised Anti IgE in 73%. Two participants developed positive reactions to the skin strip patch test. Duration of exposure to cement and SES were compared with clinical skin lesions. Spirometry result was normal in 81%, obstruction in 8%, restriction in 10%, and mixed pattern in 1%. Forced expiratory volume at 1.0 second, forced expiratory flow (25–75%), and  (PEFR) Peak Expiratory Flow Rate were markedly reduced with years of exposure. Workers who had greater skin lesions and with increase in exposure had increased AEC and IgE levels, although statistically not significant. Conclusions: Exposure to cement and poor SES is strongly correlated to increased prevalence of skin lesions and reduced pulmonary functions. PMID:28194084

Machine learning classifier using abnormal brain network topological metrics in major depressive disorder.

PubMed

Guo, Hao; Cao, Xiaohua; Liu, Zhifen; Li, Haifang; Chen, Junjie; Zhang, Kerang

2012-12-05

Resting state functional brain networks have been widely studied in brain disease research. However, it is currently unclear whether abnormal resting state functional brain network metrics can be used with machine learning for the classification of brain diseases. Resting state functional brain networks were constructed for 28 healthy controls and 38 major depressive disorder patients by thresholding partial correlation matrices of 90 regions. Three nodal metrics were calculated using graph theory-based approaches. Nonparametric permutation tests were then used for group comparisons of topological metrics, which were used as classified features in six different algorithms. We used statistical significance as the threshold for selecting features and measured the accuracies of six classifiers with different number of features. A sensitivity analysis method was used to evaluate the importance of different features. The result indicated that some of the regions exhibited significantly abnormal nodal centralities, including the limbic system, basal ganglia, medial temporal, and prefrontal regions. Support vector machine with radial basis kernel function algorithm and neural network algorithm exhibited the highest average accuracy (79.27 and 78.22%, respectively) with 28 features (P<0.05). Correlation analysis between feature importance and the statistical significance of metrics was investigated, and the results revealed a strong positive correlation between them. Overall, the current study demonstrated that major depressive disorder is associated with abnormal functional brain network topological metrics and statistically significant nodal metrics can be successfully used for feature selection in classification algorithms.

Study on the relationship between the methylation of the MMP-9 gene promoter region and diabetic nephropathy.

PubMed

Yang, Xiao-Hui; Feng, Shi-Ya; Yu, Yang; Liang, Zhou

2018-01-01

This study aims to explore the relationship between the methylation of matrix metalloproteinase (MMP)-9 gene promoter region and diabetic nephropathy (DN) through the detection of the methylation level of MMP-9 gene promoter region in the peripheral blood of patients with DN in different periods and serum MMP-9 concentration. The methylation level of the MMP-9 gene promoter region was detected by methylation-specific polymerase chain reaction (MSP), and the content of MMP-9 in serum was determined by enzyme-linked immunosorbent assay (ELISA). Results of the statistical analysis revealed that serum MMP-9 protein expression levels gradually increased in patients in the simple diabetic group, early diabetic nephropathy group and clinical diabetic nephropathy group, compared with the control group; and the difference was statistically significant (P < 0.05). Compared with the control group, the methylation levels of MMP-9 gene promoter regions gradually decreased in patients in the simple diabetic group, early diabetic nephropathy group, and clinical diabetic nephropathy group; and the difference was statistically significant (P < 0.05). Furthermore, correlation analysis results indicated that the demethylation levels of the MMP-9 gene promoter region was positively correlated with serum protein levels, urinary albumin to creatinine ratio (UACR), urea and creatinine; and was negatively correlated with GFR. The demethylation of the MMP-9 gene promoter region may be involved in the occurrence and development of diabetic nephropathy by regulating the expression of MMP-9 protein in serum.

Maternal factors predicting cognitive and behavioral characteristics of children with fetal alcohol spectrum disorders.

PubMed

May, Philip A; Tabachnick, Barbara G; Gossage, J Phillip; Kalberg, Wendy O; Marais, Anna-Susan; Robinson, Luther K; Manning, Melanie A; Blankenship, Jason; Buckley, David; Hoyme, H Eugene; Adnams, Colleen M

2013-06-01

To provide an analysis of multiple predictors of cognitive and behavioral traits for children with fetal alcohol spectrum disorders (FASDs). Multivariate correlation techniques were used with maternal and child data from epidemiologic studies in a community in South Africa. Data on 561 first-grade children with fetal alcohol syndrome (FAS), partial FAS (PFAS), and not FASD and their mothers were analyzed by grouping 19 maternal variables into categories (physical, demographic, childbearing, and drinking) and used in structural equation models (SEMs) to assess correlates of child intelligence (verbal and nonverbal) and behavior. A first SEM using only 7 maternal alcohol use variables to predict cognitive/behavioral traits was statistically significant (B = 3.10, p < .05) but explained only 17.3% of the variance. The second model incorporated multiple maternal variables and was statistically significant explaining 55.3% of the variance. Significantly correlated with low intelligence and problem behavior were demographic (B = 3.83, p < .05) (low maternal education, low socioeconomic status [SES], and rural residence) and maternal physical characteristics (B = 2.70, p < .05) (short stature, small head circumference, and low weight). Childbearing history and alcohol use composites were not statistically significant in the final complex model and were overpowered by SES and maternal physical traits. Although other analytic techniques have amply demonstrated the negative effects of maternal drinking on intelligence and behavior, this highly controlled analysis of multiple maternal influences reveals that maternal demographics and physical traits make a significant enabling or disabling contribution to child functioning in FASD.

No direct correlation between rotavirus diarrhea and breast feeding: A meta-analysis.

PubMed

Shen, Jian; Zhang, Bi-Meng; Zhu, Sheng-Guo; Chen, Jian-Jie

2018-04-01

Some studies indicated that children with exclusive breast feeding had a reduction in the prevalence of rotavirus diarrhea, while some others held the opposite views. In this study, we aimed to systematically find the associations between rotavirus diarrhea and breast feeding. A literature search up to June 2016 in electronic literature databases, including PubMed and Embase, was performed. The Newcastle-Ottawa Scale was used to conduct the quality assessment of all the selected studies. Statistical analyses were performed using the R package version 3.12 (R Foundation for Statistical Computing, Beijing1, China, meta package), and odds ratio (OR) and 95% confidence interval (CI) were used to assess the strength of the association. The heterogeneity was assessed by Cochran's Q-statistic and I 2 test, and the sensitivity analysis was performed by trimming one study at a time. A total of 17 articles, which included 10,841 participants, were investigated in the present meta-analysis. There was no significant difference between the case group and control group (OR, 0.59 95% CI 0.33-1.07) in the meta-analysis of exclusive breast feeding, and no significant difference was found between the case group and the control group (OR, 0.86; 95% CI 0.63-1.16) in the meta-analysis of breast feeding. No significant difference was found between the case group and control group (OR, 0.78 95% CI 0.59-1.04) for all quantitative data. There may be no direct correlation between rotavirus diarrhea and breast feeding. Copyright © 2017. Published by Elsevier B.V.

Analysis of cerebral vessels dynamics using experimental data with missed segments

NASA Astrophysics Data System (ADS)

Pavlova, O. N.; Abdurashitov, A. S.; Ulanova, M. V.; Shihalov, G. M.; Semyachkina-Glushkovskaya, O. V.; Pavlov, A. N.

2018-04-01

Physiological signals often contain various bad segments that occur due to artifacts, failures of the recording equipment or varying experimental conditions. The related experimental data need to be preprocessed to avoid such parts of recordings. In the case of few bad segments, they can simply be removed from the signal and its analysis is further performed. However, when there are many extracted segments, the internal structure of the analyzed physiological process may be destroyed, and it is unclear whether such signal can be used in diagnostic-related studies. In this paper we address this problem for the case of cerebral vessels dynamics. We perform analysis of simulated data in order to reveal general features of quantifying scaling features of complex signals with distinct correlation properties and show that the effects of data loss are significantly different for experimental data with long-range correlations and anti-correlations. We conclude that the cerebral vessels dynamics is significantly less sensitive to missed data fragments as compared with signals with anti-correlated statistics.

Comparison and correlation of pelvic parameters between low-grade and high-grade spondylolisthesis.

PubMed

Min, Woo-Kie; Lee, Chang-Hwa

2014-05-01

This study was retrospectively conducted on 51 patients with L5-S1 spondylolisthesis. This study was conducted to compare a total of 11 pelvic parameters, such as the level of displacement by Meyerding method, lumbar lordosis, sacral inclination, lumbosacral angle, slip angle, S2 inclination, pelvic incidence (PI), L5 inclination, L5 slope, pelvic tilt (PT), and sacral slope (SS) between low-grade and high-grade spondylolisthesis, and to investigate a correlation of the level of displacement by Meyerding method with other pelvic parameters. Pelvic parameters were measured using preoperational erect lateral spinal simple radiographs. The patients were divided into 39 patients with low-grade spondylolisthesis and 12 patients with high-grade spondylolisthesis before analysis. In all patients of both groups, 11 radiographic measurements including the level of displacement by Meyerding method, lumbar lordosis, sacral inclination, lumbosacral angle, slip angle, S2 inclination, PI, L5 inclination, L5 slope, PT, and SS were performed. T test and Pearson correlation analysis were conducted to compare and analyze each measurement. As for the comparison between the 2 groups, a statistically great significance in the level of displacement by Meyerding method, lumbosacral angle, slip angle, L5 incidence, PI, and L5 slope (P≤0.001) was shown. Meanwhile, a statistical significance in the sacral inclination and PT (P<0.05) was also shown. However, no statistical significance in the S2 incidence and SS was shown. A correlation of the level of displacement by Meyerding method with each parameter was analyzed in the both the groups. A high correlation was observed in the lumbar lordosis, lumbosacral angle, slip angle, L5 incidence, and L5 slope (Pearson correlation coefficient, P=0.01), as well as the sacral inclination, PI, and PT (Pearson correlation coefficient, P=0.05). Meanwhile, no correlation was shown in the S2 incidence and SS. A significant difference in the lumbosacral angle, slip angle, L5 incidence, PI, L5 slope, sacral inclination, and PT was shown between the patients with high-grade spondylolisthesis and patients with low-grade spondylolisthesis. Among the aforementioned measurements, the PI showed a significant difference between the 2 groups and also had a significant correlation with the dislocation level in all the patients.

Quantitative analysis of tympanic membrane perforation: a simple and reliable method.

PubMed

Ibekwe, T S; Adeosun, A A; Nwaorgu, O G

2009-01-01

Accurate assessment of the features of tympanic membrane perforation, especially size, site, duration and aetiology, is important, as it enables optimum management. To describe a simple, cheap and effective method of quantitatively analysing tympanic membrane perforations. The system described comprises a video-otoscope (capable of generating still and video images of the tympanic membrane), adapted via a universal serial bus box to a computer screen, with images analysed using the Image J geometrical analysis software package. The reproducibility of results and their correlation with conventional otoscopic methods of estimation were tested statistically with the paired t-test and correlational tests, using the Statistical Package for the Social Sciences version 11 software. The following equation was generated: P/T x 100 per cent = percentage perforation, where P is the area (in pixels2) of the tympanic membrane perforation and T is the total area (in pixels2) for the entire tympanic membrane (including the perforation). Illustrations are shown. Comparison of blinded data on tympanic membrane perforation area obtained independently from assessments by two trained otologists, of comparative years of experience, using the video-otoscopy system described, showed similar findings, with strong correlations devoid of inter-observer error (p = 0.000, r = 1). Comparison with conventional otoscopic assessment also indicated significant correlation, comparing results for two trained otologists, but some inter-observer variation was present (p = 0.000, r = 0.896). Correlation between the two methods for each of the otologists was also highly significant (p = 0.000). A computer-adapted video-otoscope, with images analysed by Image J software, represents a cheap, reliable, technology-driven, clinical method of quantitative analysis of tympanic membrane perforations and injuries.

Statistics of SU(5) D-brane models on a type II orientifold

NASA Astrophysics Data System (ADS)

Gmeiner, Florian; Stein, Maren

2006-06-01

We perform a statistical analysis of models with SU(5) and flipped SU(5) gauge group in a type II orientifold setup. We investigate the distribution and correlation of properties of these models, including the number of generations and the hidden sector gauge group. Compared to the recent analysis [F. Gmeiner, R. Blumenhagen, G. Honecker, D. Lüst, and T. Weigand, J. High Energy Phys.JHEPFG1029-8479 01 (2006) 004; F. Gmeiner, Fortschr. Phys.FPYKA60015-8208 54, 391 (2006).10.1088/1126-6708/2006/01/004] of models with a standard model-like gauge group, we find very similar results.

Explorations in Statistics: Correlation

ERIC Educational Resources Information Center

Curran-Everett, Douglas

2010-01-01

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This sixth installment of "Explorations in Statistics" explores correlation, a familiar technique that estimates the magnitude of a straight-line relationship between two variables. Correlation is meaningful only when the…

Selenium Speciation in the Fountain Creek Watershed (Colorado, USA) Correlates with Water Hardness, Ca and Mg Levels.

PubMed

Carsella, James S; Sánchez-Lombardo, Irma; Bonetti, Sandra J; Crans, Debbie C

2017-04-30

The environmental levels of selenium (Se) are regulated and strictly enforced by the Environmental Protection Agency (EPA) because of the toxicity that Se can exert at high levels. However, speciation plays an important role in the overall toxicity of Se, and only when speciation analysis has been conducted will a detailed understanding of the system be possible. In the following, we carried out the speciation analysis of the creek waters in three of the main tributaries-Upper Fountain Creek, Monument Creek and Lower Fountain Creek-located in the Fountain Creek Watershed (Colorado, USA). There are statistically significant differences between the Se, Ca and Mg, levels in each of the tributaries and seasonal swings in Se, Ca and Mg levels have been observed. There are also statistically significant differences between the Se levels when grouped by Pierre Shale type. These factors are considered when determining the forms of Se present and analyzing their chemistry using the reported thermodynamic relationships considering Ca 2+ , Mg 2+ , SeO₄ 2- , SeO₃ 2- and carbonates. This analysis demonstrated that the correlation between Se and water hardness can be explained in terms of formation of soluble CaSeO₄. The speciation analysis demonstrated that for the Fountain Creek waters, the Ca 2+ ion may be mainly responsible for the observed correlation with the Se level. Considering that the Mg 2+ level is also correlating linearly with the Se levels it is important to recognize that without Mg 2+ the Ca 2+ would be significantly reduced. The major role of Mg 2+ is thus to raise the Ca 2+ levels despite the equilibria with carbonate and other anions that would otherwise decrease Ca 2+ levels.

Simultaneous measurement of cerebral blood flow and mRNA signals: pixel-based inter-modality correlational analysis.

PubMed

Zhao, W; Busto, R; Truettner, J; Ginsberg, M D

2001-07-30

The analysis of pixel-based relationships between local cerebral blood flow (LCBF) and mRNA expression can reveal important insights into brain function. Traditionally, LCBF and in situ hybridization studies for genes of interest have been analyzed in separate series. To overcome this limitation and to increase the power of statistical analysis, this study focused on developing a double-label method to measure local cerebral blood flow (LCBF) and gene expressions simultaneously by means of a dual-autoradiography procedure. A 14C-iodoantipyrine autoradiographic LCBF study was first performed. Serial brain sections (12 in this study) were obtained at multiple coronal levels and were processed in the conventional manner to yield quantitative LCBF images. Two replicate sections at each bregma level were then used for in situ hybridization. To eliminate the 14C-iodoantipyrine from these sections, a chloroform-washout procedure was first performed. The sections were then processed for in situ hybridization autoradiography for the probes of interest. This method was tested in Wistar rats subjected to 12 min of global forebrain ischemia by two-vessel occlusion plus hypotension, followed by 2 or 6 h of reperfusion (n=4-6 per group). LCBF and in situ hybridization images for heat shock protein 70 (HSP70) were generated for each rat, aligned by disparity analysis, and analyzed on a pixel-by-pixel basis. This method yielded detailed inter-modality correlation between LCBF and HSP70 mRNA expressions. The advantages of this method include reducing the number of experimental animals by one-half; and providing accurate pixel-based correlations between different modalities in the same animals, thus enabling paired statistical analyses. This method can be extended to permit correlation of LCBF with the expression of multiple genes of interest.

Flexion and extension gaps created by the navigation-assisted gap technique show small acceptable mismatches and close mutual correlations.

PubMed

Lee, Dae-Hee; Shin, Young-Soo; Jeon, Jin-Ho; Suh, Dong-Won; Han, Seung-Beom

2014-08-01

The aim of this study was to investigate the mechanism underlying the development of gap differences in total knee arthroplasty using the navigation-assisted gap technique and to assess whether these gap differences have statistical significance. Ninety-two patients (105 knees) implanted with cruciate-retaining prostheses using the navigation-assisted gap balancing technique were prospectively analysed. Medial extension and flexion gaps and lateral extension and flexion gaps were measured at full extension and at 90° of flexion. Repeated measures analysis of variance was used to compare the mean values of these four gaps. The correlation coefficient between each pair of gaps was assessed using Pearson's correlation analysis. Mean intra-operative medial and lateral extension gaps were 20.6 ± 2.1 and 21.7 ± 2.2 mm, respectively, and mean intra-operative medial and lateral flexion gaps were 21.6 ± 2.7 and 22.1 ± 2.5 mm, respectively. The pairs of gaps differed significantly (P < 0.05 each), except for the difference between the medial flexion and lateral extension gaps (n.s.). All four gaps were significantly correlated with each other, with the highest correlation between the medial and lateral flexion gaps (r = 0.890, P < 0.001) and the lowest between the medial flexion and lateral extension gaps (r = 0.701, P < 0.001). Medial and lateral flexion and extension gaps created using the navigation-assisted gap technique differed significantly, although the differences between them were <2 mm, and the gaps were closely correlated. These narrow ranges of statistically acceptable gap differences and the strong correlations between gaps should be considered by surgeons, as should the risks of soft tissue over-release or unintentional increases in extension or flexion gap after preparation of the other gap.

Quantized correlation coefficient for measuring reproducibility of ChIP-chip data.

PubMed

Peng, Shouyong; Kuroda, Mitzi I; Park, Peter J

2010-07-27

Chromatin immunoprecipitation followed by microarray hybridization (ChIP-chip) is used to study protein-DNA interactions and histone modifications on a genome-scale. To ensure data quality, these experiments are usually performed in replicates, and a correlation coefficient between replicates is used often to assess reproducibility. However, the correlation coefficient can be misleading because it is affected not only by the reproducibility of the signal but also by the amount of binding signal present in the data. We develop the Quantized correlation coefficient (QCC) that is much less dependent on the amount of signal. This involves discretization of data into set of quantiles (quantization), a merging procedure to group the background probes, and recalculation of the Pearson correlation coefficient. This procedure reduces the influence of the background noise on the statistic, which then properly focuses more on the reproducibility of the signal. The performance of this procedure is tested in both simulated and real ChIP-chip data. For replicates with different levels of enrichment over background and coverage, we find that QCC reflects reproducibility more accurately and is more robust than the standard Pearson or Spearman correlation coefficients. The quantization and the merging procedure can also suggest a proper quantile threshold for separating signal from background for further analysis. To measure reproducibility of ChIP-chip data correctly, a correlation coefficient that is robust to the amount of signal present should be used. QCC is one such measure. The QCC statistic can also be applied in a variety of other contexts for measuring reproducibility, including analysis of array CGH data for DNA copy number and gene expression data.

Can statistical linkage of missing variables reduce bias in treatment effect estimates in comparative effectiveness research studies?

PubMed

Crown, William; Chang, Jessica; Olson, Melvin; Kahler, Kristijan; Swindle, Jason; Buzinec, Paul; Shah, Nilay; Borah, Bijan

2015-09-01

Missing data, particularly missing variables, can create serious analytic challenges in observational comparative effectiveness research studies. Statistical linkage of datasets is a potential method for incorporating missing variables. Prior studies have focused upon the bias introduced by imperfect linkage. This analysis uses a case study of hepatitis C patients to estimate the net effect of statistical linkage on bias, also accounting for the potential reduction in missing variable bias. The results show that statistical linkage can reduce bias while also enabling parameter estimates to be obtained for the formerly missing variables. The usefulness of statistical linkage will vary depending upon the strength of the correlations of the missing variables with the treatment variable, as well as the outcome variable of interest.

Grouping of Bulgarian wines according to grape variety by using statistical methods

NASA Astrophysics Data System (ADS)

Milev, M.; Nikolova, Kr.; Ivanova, Ir.; Minkova, St.; Evtimov, T.; Krustev, St.

2017-12-01

68 different types of Bulgarian wines were studied in accordance with 9 optical parameters as follows: color parameters in XYZ and SIE Lab color systems, lightness, Hue angle, chroma, fluorescence intensity and emission wavelength. The main objective of this research is using hierarchical cluster analysis to evaluate the similarity and the distance between examined different types of Bulgarian wines and their grouping based on physical parameters. We have found that wines are grouped in clusters on the base of the degree of identity between them. There are two main clusters each one with two subclusters. The first one contains white wines and Sira, the second contains red wines and rose. The results from cluster analysis are presented graphically by a dendrogram. The other statistical technique used is factor analysis performed by the Method of Principal Components (PCA). The aim is to reduce the large number of variables to a few factors by grouping the correlated variables into one factor and subdividing the noncorrelated variables into different factors. Moreover the factor analysis provided the possibility to determine the parameters with the greatest influence over the distribution of samples in different clusters. In our study after the rotation of the factors with Varimax method the parameters were combined into two factors, which explain about 80 % of the total variation. The first one explains the 61.49% and correlates with color characteristics, the second one explains 18.34% from the variation and correlates with the parameters connected with fluorescence spectroscopy.

Unpredictability of fighter pilots' g duration tolerance by anthropometric and physiological characteristics.

PubMed

Park, Myunghwan; Yoo, Seunghoon; Seol, Hyeongju; Kim, Cheonyoung; Hong, Youngseok

2015-04-01

While the factors affecting fighter pilots' G level tolerance have been widely accepted, the factors affecting fighter pilots' G duration tolerance have not been well understood. Thirty-eight subjects wearing anti-G suits were exposed to sustained high G forces using a centrifuge. The subjects exerted AGSM and decelerated the centrifuge when they reached the point of loss of peripheral vision. The G profile consisted of a +2.3 G onset rate, +7.3 G single plateau, and -1.6 G offset rate. Each subject's G tolerance time was recorded and the relationship between the tolerance time and the subject's anthropometric and physiological factors were analyzed. The mean tolerance time of the 38 subjects was 31.6 s, and the min and max tolerance times were 20 s and 58 s, respectively. The correlation analysis indicated that none of the factors had statistically significant correlations with the subjects' G duration tolerance. Stepwise multiple regression analysis showed that G duration tolerance was not dependent on any personal factors of the subjects. After the values of personal factors were simplified into 0 or 1, the t-test analysis showed that subjects' heights were inversely correlated with G duration tolerance at a statistically significant level. However, a logistic regression analysis suggested that the effect of the height factor to a pilot's G duration tolerance was too weak to be used as a predictor of a pilot's G tolerance. Fighter pilots' G duration tolerance could not be predicted by pilots' anthropometric and physiological factors.

Cheiloscopy and dactyloscopy: Do they dictate personality patterns?

PubMed Central

Abidullah, Mohammed; Kumar, M. Naveen; Bhorgonde, Kavita D.; Reddy, D. Shyam Prasad

2015-01-01

Context: Cheiloscopy and dactyloscopy, both are well-established forensic tools used in individual identification in any scenario be it a crime scene or civil cause. Like finger prints, lip prints are unique and distinguishable for every individual. But their relationship to personality types has not been established excepting the hypothesis stating that finger prints could explain these personality patterns. Aims: The study was aimed to record and correlate the lip and finger prints with that of character/personality of a person. Settings and Design: The lip and finger prints and character of a person were recorded and the data obtained was subjected for statistical analysis, especially for Pearson's Chi-square test and correlation/association between the groups was also studied. Materials and Methods: The study sample comprised of 200 subjects, 100 males and 100 females, aged between 18 and 30 years. For recording lip prints, brown/pink-colored lipstick was applied on the lips and the subjects were asked to spread uniformly over the lips. Lip prints were traced in the normal rest position on a plain white bond paper. For recording the finger prints, imprints of the fingers were taken on a plain white bond paper using ink pad. The collected prints were visualized using magnifying lens. To record the character of person, a pro forma manual for multivariable personality inventory by Dr. BC Muthayya was used. Statistical Analysis Used: Data obtained was subjected for statistical analysis, especially for Pearson's Chi-square test and correlation/association between the groups was also studied. Results: In males, predominant lip pattern recorded was Type I with whorls-type finger pattern and the character being ego ideal, pessimism, introvert, and dogmatic; whereas in females, predominant lip pattern recorded was Type II with loops-type finger pattern and the character being neurotic, need achievers, and dominant. Conclusion: Many studies on lip pattern, finger pattern, palatal rugae, etc., for individual identification and gender determination exist, but correlative studies are scanty. This is the first study done on correlating patterns, that is, lip and finger pattern with the character of a person. With this study we conclude that this correlation can be used as an adjunct in the investigatory process in forensic sciences. PMID:26005299

Empirical analysis of online human dynamics

NASA Astrophysics Data System (ADS)

Zhao, Zhi-Dan; Zhou, Tao

2012-06-01

Patterns of human activities have attracted increasing academic interests, since the quantitative understanding of human behavior is helpful to uncover the origins of many socioeconomic phenomena. This paper focuses on behaviors of Internet users. Six large-scale systems are studied in our experiments, including the movie-watching in Netflix and MovieLens, the transaction in Ebay, the bookmark-collecting in Delicious, and the posting in FreindFeed and Twitter. Empirical analysis reveals some common statistical features of online human behavior: (1) The total number of user's actions, the user's activity, and the interevent time all follow heavy-tailed distributions. (2) There exists a strongly positive correlation between user's activity and the total number of user's actions, and a significantly negative correlation between the user's activity and the width of the interevent time distribution. We further study the rescaling method and show that this method could to some extent eliminate the different statistics among users caused by the different activities, yet the effectiveness depends on the data sets.

Upside/Downside statistical mechanics of nonequilibrium Brownian motion. I. Distributions, moments, and correlation functions of a free particle.

PubMed

Craven, Galen T; Nitzan, Abraham

2018-01-28

Statistical properties of Brownian motion that arise by analyzing, separately, trajectories over which the system energy increases (upside) or decreases (downside) with respect to a threshold energy level are derived. This selective analysis is applied to examine transport properties of a nonequilibrium Brownian process that is coupled to multiple thermal sources characterized by different temperatures. Distributions, moments, and correlation functions of a free particle that occur during upside and downside events are investigated for energy activation and energy relaxation processes and also for positive and negative energy fluctuations from the average energy. The presented results are sufficiently general and can be applied without modification to the standard Brownian motion. This article focuses on the mathematical basis of this selective analysis. In subsequent articles in this series, we apply this general formalism to processes in which heat transfer between thermal reservoirs is mediated by activated rate processes that take place in a system bridging them.

Upside/Downside statistical mechanics of nonequilibrium Brownian motion. I. Distributions, moments, and correlation functions of a free particle

NASA Astrophysics Data System (ADS)

Craven, Galen T.; Nitzan, Abraham

2018-01-01

Statistical properties of Brownian motion that arise by analyzing, separately, trajectories over which the system energy increases (upside) or decreases (downside) with respect to a threshold energy level are derived. This selective analysis is applied to examine transport properties of a nonequilibrium Brownian process that is coupled to multiple thermal sources characterized by different temperatures. Distributions, moments, and correlation functions of a free particle that occur during upside and downside events are investigated for energy activation and energy relaxation processes and also for positive and negative energy fluctuations from the average energy. The presented results are sufficiently general and can be applied without modification to the standard Brownian motion. This article focuses on the mathematical basis of this selective analysis. In subsequent articles in this series, we apply this general formalism to processes in which heat transfer between thermal reservoirs is mediated by activated rate processes that take place in a system bridging them.

Multivariate fault isolation of batch processes via variable selection in partial least squares discriminant analysis.

PubMed

Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan

2017-09-01

In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Analysis and generation of groundwater concentration time series

NASA Astrophysics Data System (ADS)

Crăciun, Maria; Vamoş, Călin; Suciu, Nicolae

2018-01-01

Concentration time series are provided by simulated concentrations of a nonreactive solute transported in groundwater, integrated over the transverse direction of a two-dimensional computational domain and recorded at the plume center of mass. The analysis of a statistical ensemble of time series reveals subtle features that are not captured by the first two moments which characterize the approximate Gaussian distribution of the two-dimensional concentration fields. The concentration time series exhibit a complex preasymptotic behavior driven by a nonstationary trend and correlated fluctuations with time-variable amplitude. Time series with almost the same statistics are generated by successively adding to a time-dependent trend a sum of linear regression terms, accounting for correlations between fluctuations around the trend and their increments in time, and terms of an amplitude modulated autoregressive noise of order one with time-varying parameter. The algorithm generalizes mixing models used in probability density function approaches. The well-known interaction by exchange with the mean mixing model is a special case consisting of a linear regression with constant coefficients.

Weak-value amplification and optimal parameter estimation in the presence of correlated noise

NASA Astrophysics Data System (ADS)

Sinclair, Josiah; Hallaji, Matin; Steinberg, Aephraim M.; Tollaksen, Jeff; Jordan, Andrew N.

2017-11-01

We analytically and numerically investigate the performance of weak-value amplification (WVA) and related parameter estimation methods in the presence of temporally correlated noise. WVA is a special instance of a general measurement strategy that involves sorting data into separate subsets based on the outcome of a second "partitioning" measurement. Using a simplified correlated noise model that can be analyzed exactly together with optimal statistical estimators, we compare WVA to a conventional measurement method. We find that WVA indeed yields a much lower variance of the parameter of interest than the conventional technique does, optimized in the absence of any partitioning measurements. In contrast, a statistically optimal analysis that employs partitioning measurements, incorporating all partitioned results and their known correlations, is found to yield an improvement—typically slight—over the noise reduction achieved by WVA. This result occurs because the simple WVA technique is not tailored to any specific noise environment and therefore does not make use of correlations between the different partitions. We also compare WVA to traditional background subtraction, a familiar technique where measurement outcomes are partitioned to eliminate unknown offsets or errors in calibration. Surprisingly, for the cases we consider, background subtraction turns out to be a special case of the optimal partitioning approach, possessing a similar typically slight advantage over WVA. These results give deeper insight into the role of partitioning measurements (with or without postselection) in enhancing measurement precision, which some have found puzzling. They also resolve previously made conflicting claims about the usefulness of weak-value amplification to precision measurement in the presence of correlated noise. We finish by presenting numerical results to model a more realistic laboratory situation of time-decaying correlations, showing that our conclusions hold for a wide range of statistical models.

Factors associated with frailty in chronically ill older adults.

PubMed

Hackstaff, Lynn

2009-01-01

An ex post facto analysis of a secondary dataset examined relationships between physical frailty, depression, and the self-perceived domains of health status and quality-of-life in older adults. The randomized sample included 992 community-dwelling, chronically ill, and functionally impaired adults age 65 and older who received care from a Southern California Kaiser Permanente medical center between 1998 and 2002. Physical frailty represents a level of physiologic vulnerability and functional loss that results in dependence on others for basic, daily living needs (Fried et al., 2001). The purpose of the study was to identify possible intervention junctures related to self-efficacy of older adults in order to help optimize their functionality. Multivariate correlation analyses showed statistically significant positive correlations between frailty level and depression (r = .18; p = < .05), number of medical conditions (r = .09; p = < .05), and self-rated quality-of-life (r = .24; p = < .05). Frailty level showed a statistically significant negative correlation with self-perceived health status (r = -.25; p = < .05). Notably, no statistically significant correlation was found between age and frailty level (r = -.03; p = < .05). In linear regression, self-perceived health status had a partial variance with frailty level (part r = -.18). The significant correlations found support further research to identify interventions to help vulnerable, older adults challenge self-perceived capabilities so that they may achieve optimum functionality through increased physical activity earlier on, and increased self-efficacy to support successful adaptation to aging-related losses.

A Cross-Correlational Analysis between Electroencephalographic and End-Tidal Carbon Dioxide Signals: Methodological Issues in the Presence of Missing Data and Real Data Results

PubMed Central

Morelli, Maria Sole; Giannoni, Alberto; Passino, Claudio; Landini, Luigi; Emdin, Michele; Vanello, Nicola

2016-01-01

Electroencephalographic (EEG) irreducible artifacts are common and the removal of corrupted segments from the analysis may be required. The present study aims at exploring the effects of different EEG Missing Data Segment (MDS) distributions on cross-correlation analysis, involving EEG and physiological signals. The reliability of cross-correlation analysis both at single subject and at group level as a function of missing data statistics was evaluated using dedicated simulations. Moreover, a Bayesian-based approach for combining the single subject results at group level by considering each subject’s reliability was introduced. Starting from the above considerations, the cross-correlation function between EEG Global Field Power (GFP) in delta band and end-tidal CO2 (PETCO2) during rest and voluntary breath-hold was evaluated in six healthy subjects. The analysis of simulated data results at single subject level revealed a worsening of precision and accuracy in the cross-correlation analysis in the presence of MDS. At the group level, a large improvement in the results’ reliability with respect to single subject analysis was observed. The proposed Bayesian approach showed a slight improvement with respect to simple average results. Real data results were discussed in light of the simulated data tests and of the current physiological findings. PMID:27809243

The skeletal maturation status estimated by statistical shape analysis: axial images of Japanese cervical vertebra.

PubMed

Shin, S M; Kim, Y-I; Choi, Y-S; Yamaguchi, T; Maki, K; Cho, B-H; Park, S-B

2015-01-01

To evaluate axial cervical vertebral (ACV) shape quantitatively and to build a prediction model for skeletal maturation level using statistical shape analysis for Japanese individuals. The sample included 24 female and 19 male patients with hand-wrist radiographs and CBCT images. Through generalized Procrustes analysis and principal components (PCs) analysis, the meaningful PCs were extracted from each ACV shape and analysed for the estimation regression model. Each ACV shape had meaningful PCs, except for the second axial cervical vertebra. Based on these models, the smallest prediction intervals (PIs) were from the combination of the shape space PCs, age and gender. Overall, the PIs of the male group were smaller than those of the female group. There was no significant correlation between centroid size as a size factor and skeletal maturation level. Our findings suggest that the ACV maturation method, which was applied by statistical shape analysis, could confirm information about skeletal maturation in Japanese individuals as an available quantifier of skeletal maturation and could be as useful a quantitative method as the skeletal maturation index.

The skeletal maturation status estimated by statistical shape analysis: axial images of Japanese cervical vertebra

PubMed Central

Shin, S M; Choi, Y-S; Yamaguchi, T; Maki, K; Cho, B-H; Park, S-B

2015-01-01

Objectives: To evaluate axial cervical vertebral (ACV) shape quantitatively and to build a prediction model for skeletal maturation level using statistical shape analysis for Japanese individuals. Methods: The sample included 24 female and 19 male patients with hand–wrist radiographs and CBCT images. Through generalized Procrustes analysis and principal components (PCs) analysis, the meaningful PCs were extracted from each ACV shape and analysed for the estimation regression model. Results: Each ACV shape had meaningful PCs, except for the second axial cervical vertebra. Based on these models, the smallest prediction intervals (PIs) were from the combination of the shape space PCs, age and gender. Overall, the PIs of the male group were smaller than those of the female group. There was no significant correlation between centroid size as a size factor and skeletal maturation level. Conclusions: Our findings suggest that the ACV maturation method, which was applied by statistical shape analysis, could confirm information about skeletal maturation in Japanese individuals as an available quantifier of skeletal maturation and could be as useful a quantitative method as the skeletal maturation index. PMID:25411713

Testing the Difference of Correlated Agreement Coefficients for Statistical Significance

ERIC Educational Resources Information Center

Gwet, Kilem L.

2016-01-01

This article addresses the problem of testing the difference between two correlated agreement coefficients for statistical significance. A number of authors have proposed methods for testing the difference between two correlated kappa coefficients, which require either the use of resampling methods or the use of advanced statistical modeling…

Co-occurrence correlations of heavy metals in sediments revealed using network analysis.

PubMed

Liu, Lili; Wang, Zhiping; Ju, Feng; Zhang, Tong

2015-01-01

In this study, the correlation-based study was used to identify the co-occurrence correlations among metals in marine sediment of Hong Kong, based on the long-term (from 1991 to 2011) temporal and spatial monitoring data. 14 stations out of the total 45 marine sediment monitoring stations were selected from three representative areas, including Deep Bay, Victoria Harbour and Mirs Bay. Firstly, Spearman's rank correlation-based network analysis was conducted as the first step to identify the co-occurrence correlations of metals from raw metadata, and then for further analysis using the normalized metadata. The correlations patterns obtained by network were consistent with those obtained by the other statistic normalization methods, including annual ratios, R-squared coefficient and Pearson correlation coefficient. Both Deep Bay and Victoria Harbour have been polluted by heavy metals, especially for Pb and Cu, which showed strong co-occurrence with other heavy metals (e.g. Cr, Ni, Zn and etc.) and little correlations with the reference parameters (Fe or Al). For Mirs Bay, which has better marine sediment quality compared with Deep Bay and Victoria Harbour, the co-occurrence patterns revealed by network analysis indicated that the metals in sediment dominantly followed the natural geography process. Besides the wide applications in biology, sociology and informatics, it is the first time to apply network analysis in the researches of environment pollutions. This study demonstrated its powerful application for revealing the co-occurrence correlations among heavy metals in marine sediments, which could be further applied for other pollutants in various environment systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Multivariate analysis of fears in dental phobic patients according to a reduced FSS-II scale.

PubMed

Hakeberg, M; Gustafsson, J E; Berggren, U; Carlsson, S G

1995-10-01

This study analyzed and assessed dimensions of a questionnaire developed to measure general fears and phobias. A previous factor analysis among 109 dental phobics had revealed a five-factor structure with 22 items and an explained total variance of 54%. The present study analyzed the same material using a multivariate statistical procedure (LISREL) to reveal structural latent variables. The LISREL analysis, based on the correlation matrix, yielded a chi-square of 216.6 with 195 degrees of freedom (P = 0.138) and showed a model with seven latent variables. One was a general fear factor correlated to all 22 items. The other six factors concerned "Illness & Death" (5 items), "Failures & Embarrassment" (5 items), "Social situations" (5 items), "Physical injuries" (4 items), "Animals & Natural phenomena" (4 items). One item (opposite sex) was included in both "Failures & Embarrassment" and "Social situations". The last factor, "Social interaction", combined all the items in "Failures & Embarrassment" and "Social situations" (9 items). In conclusion, this multivariate statistical analysis (LISREL) revealed and confirmed a factor structure similar to our previous study, but added two important dimensions not shown with a traditional factor analysis. This reduced FSS-II version measures general fears and phobias and may be used on a routine clinical basis as well as in dental phobia research.

Proper joint analysis of summary association statistics requires the adjustment of heterogeneity in SNP coverage pattern.

PubMed

Zhang, Han; Wheeler, William; Song, Lei; Yu, Kai

2017-07-07

As meta-analysis results published by consortia of genome-wide association studies (GWASs) become increasingly available, many association summary statistics-based multi-locus tests have been developed to jointly evaluate multiple single-nucleotide polymorphisms (SNPs) to reveal novel genetic architectures of various complex traits. The validity of these approaches relies on the accurate estimate of z-score correlations at considered SNPs, which in turn requires knowledge on the set of SNPs assessed by each study participating in the meta-analysis. However, this exact SNP coverage information is usually unavailable from the meta-analysis results published by GWAS consortia. In the absence of the coverage information, researchers typically estimate the z-score correlations by making oversimplified coverage assumptions. We show through real studies that such a practice can generate highly inflated type I errors, and we demonstrate the proper way to incorporate correct coverage information into multi-locus analyses. We advocate that consortia should make SNP coverage information available when posting their meta-analysis results, and that investigators who develop analytic tools for joint analyses based on summary data should pay attention to the variation in SNP coverage and adjust for it appropriately. Published by Oxford University Press 2017. This work is written by US Government employees and is in the public domain in the US.

Anthropometric Study of the Piriformis Muscle and Sciatic Nerve: A Morphological Analysis in a Polish Population

PubMed Central

Haładaj, Robert; Pingot, Mariusz; Polguj, Michał; Wysiadecki, Grzegorz; Topol, Mirosław

2015-01-01

Background The aim of this study was to determine relationships between piriformis muscle (PM) and sciatic nerve (SN) with reference to sex and anatomical variations. Material/Methods Deep dissection of the gluteal region was performed on 30 randomized, formalin-fixed human lower limbs of adults of both sexes of the Polish population. Anthropometric measurements were taken and then statistically analyzed. Results The conducted research revealed that, apart from the typical structure of the piriformis muscle, the most common variation was division of the piriformis muscle into two heads, with the common peroneal nerve running between them (20%). The group with anatomical variations of the sciatic nerve course displayed greater diversity of morphometric measurement results. There was a statistically significant correlation between the lower limb length and the distance from the sciatic nerve to the greater trochanter in the male specimens. On the other hand, in the female specimens, a statistically significant correlation was observed between the lower limb length and the distance from the sciatic nerve to the ischial tuberosity. The shortest distance from the sciatic nerve to the greater trochanter measured at the level of the inferior edge of the piriformis was 21 mm, while the shortest distance to the ischial tuberosity was 63 mm. Such correlations should be taken into account during invasive medical procedures performed in the gluteal region. Conclusions It is possible to distinguish several anatomical variations of the sciatic nerve course within the deep gluteal region. The statistically significant correlations between some anthropometric measurements were only present within particular groups of male and female limbs. PMID:26629744

Attempting to physically explain space-time correlation of extremes

NASA Astrophysics Data System (ADS)

Bernardara, Pietro; Gailhard, Joel

2010-05-01

Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.

Correlative bacteriologic and micro-computed tomographic analysis of mandibular molar mesial canals prepared by self-adjusting file, reciproc, and twisted file systems.

PubMed

Siqueira, José F; Alves, Flávio R F; Versiani, Marco A; Rôças, Isabela N; Almeida, Bernardo M; Neves, Mônica A S; Sousa-Neto, Manoel D

2013-08-01

This ex vivo study evaluated the disinfecting and shaping ability of 3 protocols used in the preparation of mesial root canals of mandibular molars by means of correlative bacteriologic and micro-computed tomographic (μμCT) analysis. The mesial canals of extracted mandibular molars were contaminated with Enterococcus faecalis for 30 days and assigned to 3 groups based on their anatomic configuration as determined by μCT analysis according to the preparation technique (Self-Adjusting File [ReDent-Nova, Ra'anana, Israel], Reciproc [VDW, Munich, Germany], and Twisted File [SybronEndo, Orange, CA]). In all groups, 2.5% NaOCl was the irrigant. Canal samples were taken before (S1) and after instrumentation (S2), and bacterial quantification was performed using culture. Next, mesial roots were subjected to additional μCT analysis in order to evaluate shaping of the canals. All instrumentation protocols promoted a highly significant intracanal bacterial reduction (P < .001). Intergroup quantitative and qualitative comparisons disclosed no significant differences between groups (P > .05). As for shaping, no statistical difference was observed between the techniques regarding the mean percentage of volume increase, the surface area increase, the unprepared surface area, and the relative unprepared surface area (P > .05). Correlative analysis showed no statistically significant relationship between bacterial reduction and the mean percentage increase of the analyzed parameters (P > .05). The 3 instrumentation systems have similar disinfecting and shaping performance in the preparation of mesial canals of mandibular molars. Copyright © 2013 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

An uncertainty analysis of the flood-stage upstream from a bridge.

PubMed

Sowiński, M

2006-01-01

The paper begins with the formulation of the problem in the form of a general performance function. Next the Latin hypercube sampling (LHS) technique--a modified version of the Monte Carlo method is briefly described. The essential uncertainty analysis of the flood-stage upstream from a bridge starts with a description of the hydraulic model. This model concept is based on the HEC-RAS model developed for subcritical flow under a bridge without piers in which the energy equation is applied. The next section contains the characteristic of the basic variables including a specification of their statistics (means and variances). Next the problem of correlated variables is discussed and assumptions concerning correlation among basic variables are formulated. The analysis of results is based on LHS ranking lists obtained from the computer package UNCSAM. Results fot two examples are given: one for independent and the other for correlated variables.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

PubMed

Hu, Yi-Juan; Berndt, Sonja I; Gustafsson, Stefan; Ganna, Andrea; Hirschhorn, Joel; North, Kari E; Ingelsson, Erik; Lin, Dan-Yu

2013-08-08

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available. Copyright © 2013 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

[Study on the factors impacting on early cochlear implantation between the eastern and western region of China].

PubMed

Xiao, Hanqiong; Li, Wei; Ma, Ruixia; Gong, Zhengpeng; Shi, Haibo; Li, Huawei; Chen, Bing; Jiang, Ye; Dai, Chunfu

2015-06-01

To describe tne regional different factors which impact on early cochlear implantation in prelingual deaf children between eastern and western regions of China. The charts of 113 children who received the cochlear implantation after 24 months old were reviewed and analyzed. Forty-five of them came from the eastern region (Jiangsu, Zhejiang or Shanghai) while 68 of them came from the western region (Ningxia or Guizhou). Parental interviews were conducted to collect information regarding the factors that impact on early cochlear implantation. Result:Based on the univariate logistic regression analysis, the odds ratio (OR) value of universal newborn hearing screening (UNHS) was 5. 481, which indicated the correlation of UNHS with early cochlear implantation is significant. There was statistical difference between the 2 groups (P<0. 01). For the financial burden, the OR value was 3. 521(strong correlation) and there was statistical difference between the 2 groups (P<0. 01). For the communication barriers and community location, the OR value was 0. 566 and 1. 128 respectively, and there was no statistical difference between the 2 groups (P>0. 05). The multivariate analysis indicated that the UNHS and financial burden are statistically different between the eastern and western regions (P=0. 00 and 0. 040 respectively). The UNHS and financial burden are statistically different between the eastern reinforced in the western region. In addition, the government and society should provide powerful policy and more financial support in the western region of China. The innovation of management system is also helpful to the early cochlear implantation.

Student failures on first-year medical basic science courses and the USMLE step 1: a retrospective study over a 20-year period.

PubMed

Burns, E Robert; Garrett, Judy

2015-01-01

Correlates of achievement in the basic science years in medical school and on the Step 1 of the United States Medical Licensing Examination® (USMLE®), (Step 1) in relation to preadmission variables have been the subject of considerable study. Preadmissions variables such as the undergraduate grade point average (uGPA) and Medical College Admission Test® (MCAT®) scores, solely or in combination, have previously been found to be predictors of achievement in the basic science years and/or on the Step 1. The purposes of this retrospective study were to: (1) determine if our statistical analysis confirmed previously published relationships between preadmission variables (MCAT, uGPA, and applicant pool size), and (2) study correlates of the number of failures in five M1 courses with those preadmission variables and failures on Step 1. Statistical analysis confirmed previously published relationships between all preadmission variables. Only one course, Microscopic Anatomy, demonstrated significant correlations with all variables studied including the Step 1 failures. Physiology correlated with three of the four variables studied, but not with the Step 1 failures. Analyses such as these provide a tool by which administrators will be able to identify what courses are or are not responding in appropriate ways to changes in the preadmissions variables that signal student performance on the Step 1. © 2014 American Association of Anatomists.

Nonlinear analysis of pupillary dynamics.

PubMed

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

2016-02-01

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

Socio-economic factors of bacillary dysentery based on spatial correlation analysis in Guangxi Province, China.

PubMed

Nie, Chengjing; Li, Hairong; Yang, Linsheng; Zhong, Gemei; Zhang, Lan

2014-01-01

In the past decade, bacillary dysentery was still a big public health problem in China, especially in Guangxi Province, where thousands of severe diarrhea cases occur every year. Reported bacillary dysentery cases in Guangxi Province were obtained from local Centers for Diseases Prevention and Control. The 14 socio-economic indexes were selected as potential explanatory variables for the study. The spatial correlation analysis was used to explore the associations between the selected factors and bacillary dysentery incidence at county level, which was based on the software of ArcGIS10.2 and GeoDA 0.9.5i. The proportion of primary industry, the proportion of younger than 5-year-old children in total population, the number of hospitals per thousand persons and the rates of bacillary dysentery incidence show statistically significant positive correlation. But the proportion of secondary industry, per capital GDP, per capital government revenue, rural population proportion, popularization rate of tap water in rural area, access rate to the sanitation toilets in rural, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons and the rate of bacillary dysentery incidence show statistically significant negative correlation. The socio-economic factors can be divided into four aspects, including economic development, health development, medical development and human own condition. The four aspects were not isolated from each other, but interacted with each other.

Evaluation of the Correlation of Ramus Height, Gonial Angle, and Dental Height with Different Facial Forms in Individuals with Deep Bite Disorders

PubMed Central

Ahila, SC; Sasikala, C; Kumar, B Muthu; Tah, Rajdeep; Abinaya, K

2016-01-01

Background: Restoring the vertical dimension is a critical procedure in prosthetic dentistry. Anterior facial height has a significant impact on the length of the ramus. Patients with deep bite will exhibit a shorter lower facial height; hence, restoring the vertical dimension esthetically without altering the facial form is highly challenging. Aim: To evaluate the relationship of gonial angle, ramus height, and dental height with different facial forms. Subjects and Methods: A total of 51 subjects in all facial form aged between 20 and 40 with deep bite were randomly selected. Lateral cephalograms and facial photographs were made for each patient. Ramus height was measured on lateral cephalogram by measuring the distance from articulare to gonion. The gonial angles were calculated and anterior and posterior dental height were measured from cephalogram. Facial forms were evaluated using patient's photographs. Results: The obtained measurements were evaluated, and compared statistically with one way analysis of variance and regression correlation test. Statistical analysis revealed that there was no correlation found between the gonial angle and ramus height. Conclusion: Correlation found between the ramus height and anterior and posterior dental height in patients with deep bite disorders. The ramus height can be calculated using the formulas 46.42 + (0.095 × AD height), 46.046+ (0.123 × PD height). PMID:28480098

Correlations between trans-membrane pressure (TMP) and sludge properties in submerged membrane electro-bioreactor (SMEBR) and conventional membrane bioreactor (MBR).

PubMed

Hasan, Shadi W; Elektorowicz, Maria; Oleszkiewicz, Jan A

2012-09-01

The influence of sludge properties in SMEBR and conventional MBR pilot systems on membrane fouling was investigated. Generated data were analyzed using statistical analysis Pearson's product momentum correlation coefficient (r(p)). Analysis showed that TMP had strong direct (r(p)=0.9182) and inverse (r(p)=-0.9205) correlations to mean particle size diameter in MBR and SMEBR, respectively. TMP in SMEBR had a strong direct correlation to the sludge mixed liquor suspended solids concentration (MLSS) (r(p)=0.7757) while a weak direct correlation (r(p)=0.1940) was observed in MBR. SMEBR showed a moderate inverse correlation (r(p)=-0.6118) between TMP and soluble carbohydrates (EPS(c)) and a very weak direct correlation (r(p)=0.3448) to soluble proteins (EPS(p)). Conversely, EPS(p) in MBR had more significant impact (r(p)=0.4856) on membrane fouling than EPS(c) (r(p)=0.3051). The results provide insight into optimization of operational conditions in SMEBR system to overcome membrane fouling. Copyright © 2012 Elsevier Ltd. All rights reserved.

SER Analysis of MPPM-Coded MIMO-FSO System over Uncorrelated and Correlated Gamma-Gamma Atmospheric Turbulence Channels

NASA Astrophysics Data System (ADS)

Khallaf, Haitham S.; Garrido-Balsells, José M.; Shalaby, Hossam M. H.; Sampei, Seiichi

2015-12-01

The performance of multiple-input multiple-output free space optical (MIMO-FSO) communication systems, that adopt multipulse pulse position modulation (MPPM) techniques, is analyzed. Both exact and approximate symbol-error rates (SERs) are derived for both cases of uncorrelated and correlated channels. The effects of background noise, receiver shot-noise, and atmospheric turbulence are taken into consideration in our analysis. The random fluctuations of the received optical irradiance, produced by the atmospheric turbulence, is modeled by the widely used gamma-gamma statistical distribution. Uncorrelated MIMO channels are modeled by the α-μ distribution. A closed-form expression for the probability density function of the optical received irradiance is derived for the case of correlated MIMO channels. Using our analytical expressions, the degradation of the system performance with the increment of the correlation coefficients between MIMO channels is corroborated.

Estimation and correlation of salivary thiocyanate levels in periodontally healthy subjects, smokers, nonsmokers, and gutka-chewers with chronic periodontitis.

PubMed

Hegde, Shashikanth; Chatterjee, Elashri; Rajesh, K S; Kumar, M S Arun

2016-01-01

This study was conducted to estimate and correlate salivary thiocyanate (SCN) levels in periodontally healthy subjects, smokers, nonsmokers, and gutka-chewers with chronic periodontitis. The study population consisted of 40 systemically healthy subjects in the age group of 18-55 years that was further divided into four groups: Control, smokers, nonsmokers, and gutka-chewers with chronic periodontitis. Gingival index (GI) (Loe and Silness-1963), probing depth (PD), clinical attachment loss was assessed. Estimation of SCN was performed by ultraviolet spectrophotometer at 447 nm wavelength. Statistical analysis was performed using the one-way ANOVAs Welch test and Pearson's correlation test using SPSS version 17 software. Results showed statistically significant increase in SCN levels in smokers as compared to gutka-chewers with chronic periodontitis, control, and nonsmokers with chronic periodontitis subjects. Significantly higher PD and loss of attachment were seen in smokers group compared with other groups. A negative correlation observed between the GI and thiocyanate levels. The present study revealed a significant increase in SCN levels in smokers with periodontitis as compared to nonsmokers.

Impact of work environment and work-related stress on turnover intention in physical therapists.

PubMed

Lee, Byoung-Kwon; Seo, Dong-Kwon; Lee, Jang-Tae; Lee, A-Ram; Jeon, Ha-Neul; Han, Dong-Uk

2016-08-01

[Purpose] This study was conducted to provide basic data for solutions to reduce the turnover rate of physical therapists. It should help create efficient personnel and organization management by exploring the impact of the work environment and work-related stress on turnover intention and analyzing the correlation between them. [Subjects and Methods] A survey was conducted with 236 physical therapists working at medical institutions in the Daejeon and Chungcheong areas. For the analysis on the collected data, correlational and linear regression analyses were conducted using the SPSS 18.0 program and Cronbach's alpha coefficient. [Results] The results showed a statistically significant positive correlation between turnover intention and work-related stress but a statistically significant negative correlation respectively between turnover intention and work environment. Work-related stress (β=0.415) had a significant positive impact on turnover intention and work environment (β=-0.387) had a significant negative impact on turnover intention. [Conclusion] To increase satisfaction level with the profession as well as the workplace for physical therapists, improvement of the work environment was the most necessary primary improvement.

Impact of work environment and work-related stress on turnover intention in physical therapists

PubMed Central

Lee, Byoung-kwon; Seo, Dong-kwon; Lee, Jang-Tae; Lee, A-Ram; Jeon, Ha-Neul; Han, Dong-Uk

2016-01-01

[Purpose] This study was conducted to provide basic data for solutions to reduce the turnover rate of physical therapists. It should help create efficient personnel and organization management by exploring the impact of the work environment and work-related stress on turnover intention and analyzing the correlation between them. [Subjects and Methods] A survey was conducted with 236 physical therapists working at medical institutions in the Daejeon and Chungcheong areas. For the analysis on the collected data, correlational and linear regression analyses were conducted using the SPSS 18.0 program and Cronbach’s alpha coefficient. [Results] The results showed a statistically significant positive correlation between turnover intention and work-related stress but a statistically significant negative correlation respectively between turnover intention and work environment. Work-related stress (β=0.415) had a significant positive impact on turnover intention and work environment (β=−0.387) had a significant negative impact on turnover intention. [Conclusion] To increase satisfaction level with the profession as well as the workplace for physical therapists, improvement of the work environment was the most necessary primary improvement. PMID:27630432

Understanding the Heterogeneity of BPD Symptoms through Latent Class Analysis: Initial Results and Clinical Correlates among Inner-City Substance Users

ERIC Educational Resources Information Center

Bornovalova, Marina A.; Levy, Roy; Gratz, Kim L.; Lejuez, C. W.

2010-01-01

The current study investigated the heterogeneity of borderline personality disorder (BPD) symptoms in a sample of 382 inner-city, predominantly African American male substance users through the use of latent class analysis. A 4-class model was statistically preferred, with 1 class interpreted to be a baseline class, 1 class interpreted to be a…

Central depression in nucleonic densities: Trend analysis in the nuclear density functional theory approach

NASA Astrophysics Data System (ADS)

Schuetrumpf, B.; Nazarewicz, W.; Reinhard, P.-G.

2017-08-01

Background: The central depression of nucleonic density, i.e., a reduction of density in the nuclear interior, has been attributed to many factors. For instance, bubble structures in superheavy nuclei are believed to be due to the electrostatic repulsion. In light nuclei, the mechanism behind the density reduction in the interior has been discussed in terms of shell effects associated with occupations of s orbits. Purpose: The main objective of this work is to reveal mechanisms behind the formation of central depression in nucleonic densities in light and heavy nuclei. To this end, we introduce several measures of the internal nucleonic density. Through the statistical analysis, we study the information content of these measures with respect to nuclear matter properties. Method: We apply nuclear density functional theory with Skyrme functionals. Using the statistical tools of linear least square regression, we inspect correlations between various measures of central depression and model parameters, including nuclear matter properties. We study bivariate correlations with selected quantities as well as multiple correlations with groups of parameters. Detailed correlation analysis is carried out for 34Si for which a bubble structure has been reported recently, 48Ca, and N =82 , 126, and 184 isotonic chains. Results: We show that the central depression in medium-mass nuclei is very sensitive to shell effects, whereas for superheavy systems it is firmly driven by the electrostatic repulsion. An appreciable semibubble structure in proton density is predicted for 294Og, which is currently the heaviest nucleus known experimentally. Conclusion: Our correlation analysis reveals that the central density indicators in nuclei below 208Pb carry little information on parameters of nuclear matter; they are predominantly driven by shell structure. On the other hand, in the superheavy nuclei there exists a clear relationship between the central nucleonic density and symmetry energy.

Applied immuno-epidemiological research: an approach for integrating existing knowledge into the statistical analysis of multiple immune markers.

PubMed

Genser, Bernd; Fischer, Joachim E; Figueiredo, Camila A; Alcântara-Neves, Neuza; Barreto, Mauricio L; Cooper, Philip J; Amorim, Leila D; Saemann, Marcus D; Weichhart, Thomas; Rodrigues, Laura C

2016-05-20

Immunologists often measure several correlated immunological markers, such as concentrations of different cytokines produced by different immune cells and/or measured under different conditions, to draw insights from complex immunological mechanisms. Although there have been recent methodological efforts to improve the statistical analysis of immunological data, a framework is still needed for the simultaneous analysis of multiple, often correlated, immune markers. This framework would allow the immunologists' hypotheses about the underlying biological mechanisms to be integrated. We present an analytical approach for statistical analysis of correlated immune markers, such as those commonly collected in modern immuno-epidemiological studies. We demonstrate i) how to deal with interdependencies among multiple measurements of the same immune marker, ii) how to analyse association patterns among different markers, iii) how to aggregate different measures and/or markers to immunological summary scores, iv) how to model the inter-relationships among these scores, and v) how to use these scores in epidemiological association analyses. We illustrate the application of our approach to multiple cytokine measurements from 818 children enrolled in a large immuno-epidemiological study (SCAALA Salvador), which aimed to quantify the major immunological mechanisms underlying atopic diseases or asthma. We demonstrate how to aggregate systematically the information captured in multiple cytokine measurements to immunological summary scores aimed at reflecting the presumed underlying immunological mechanisms (Th1/Th2 balance and immune regulatory network). We show how these aggregated immune scores can be used as predictors in regression models with outcomes of immunological studies (e.g. specific IgE) and compare the results to those obtained by a traditional multivariate regression approach. The proposed analytical approach may be especially useful to quantify complex immune responses in immuno-epidemiological studies, where investigators examine the relationship among epidemiological patterns, immune response, and disease outcomes.

Relating N2O emissions during biological nitrogen removal with operating conditions using multivariate statistical techniques.

PubMed

Vasilaki, V; Volcke, E I P; Nandi, A K; van Loosdrecht, M C M; Katsou, E

2018-04-26

Multivariate statistical analysis was applied to investigate the dependencies and underlying patterns between N 2 O emissions and online operational variables (dissolved oxygen and nitrogen component concentrations, temperature and influent flow-rate) during biological nitrogen removal from wastewater. The system under study was a full-scale reactor, for which hourly sensor data were available. The 15-month long monitoring campaign was divided into 10 sub-periods based on the profile of N 2 O emissions, using Binary Segmentation. The dependencies between operating variables and N 2 O emissions fluctuated according to Spearman's rank correlation. The correlation between N 2 O emissions and nitrite concentrations ranged between 0.51 and 0.78. Correlation >0.7 between N 2 O emissions and nitrate concentrations was observed at sub-periods with average temperature lower than 12 °C. Hierarchical k-means clustering and principal component analysis linked N 2 O emission peaks with precipitation events and ammonium concentrations higher than 2 mg/L, especially in sub-periods characterized by low N 2 O fluxes. Additionally, the highest ranges of measured N 2 O fluxes belonged to clusters corresponding with NO 3 -N concentration less than 1 mg/L in the upstream plug-flow reactor (middle of oxic zone), indicating slow nitrification rates. The results showed that the range of N 2 O emissions partially depends on the prior behavior of the system. The principal component analysis validated the findings from the clustering analysis and showed that ammonium, nitrate, nitrite and temperature explained a considerable percentage of the variance in the system for the majority of the sub-periods. The applied statistical methods, linked the different ranges of emissions with the system variables, provided insights on the effect of operating conditions on N 2 O emissions in each sub-period and can be integrated into N 2 O emissions data processing at wastewater treatment plants. Copyright © 2018. Published by Elsevier Ltd.

Depression and anxiety levels increase chronic musculoskeletal pain in patients with Alzheimer's disease.

PubMed

Tsatali, Marianna; Papaliagkas, Vasileios; Damigos, Dimitrios; Mavreas, Venetsanos; Gouva, Maria; Tsolaki, Magda

2014-01-01

During the next decades a rapid increase is expected in the number of patients with dementia suffering from pain who often take less medication compared to normal elderly, due to several diagnostic barriers. Comorbid mood disorders result in great difficulties in pain assessment and further treatment. Twenty five patients with Alzheimer's disease, comorbid mood disorders, and chronic musculoskeletal pain (experimental group) and thirty one patients with Alzheimer's disease and chronic musculoskeletal pain without comorbid mood disorders (control group) were examined. The assessment tools used were Geriatric Pain Measure, Patient Health Questionnaire, Pain Assessment in Advanced Dementia, Mini Mental State Examination and Pain Anxiety Symptom Scale. Statistical analysis was performed by SPSS v17.0, using the Pearson correlation and the multiple linear regression analysis. The correlation between mood disorders and levels of pain intensity in the experimental group was found to be statistically higher than that in the control group (p<.001). Among all quantitative variables, highly significant correlation (p<.001) was observed between stress and depression symptomatology (r =.550, p<.001) in the experimental group. Normal regression analysis was used to assess possible differences between demographic data and PASS scores. Scores in fearful thinking and physiological responses scales of PASS were higher in female than male (p=.014), whereas scores in the cognitive anxiety scale of PASS have shown a highly significant positive correlation with years of education (p<.001). It seems that depression and anxiety are associated with chronic musculoskeletal pain intensity in dementia, thus need to be taken into consideration by health professionals for patient's management.

Detection methods for non-Gaussian gravitational wave stochastic backgrounds

NASA Astrophysics Data System (ADS)

Drasco, Steve; Flanagan, Éanna É.

2003-04-01

A gravitational wave stochastic background can be produced by a collection of independent gravitational wave events. There are two classes of such backgrounds, one for which the ratio of the average time between events to the average duration of an event is small (i.e., many events are on at once), and one for which the ratio is large. In the first case the signal is continuous, sounds something like a constant hiss, and has a Gaussian probability distribution. In the second case, the discontinuous or intermittent signal sounds something like popcorn popping, and is described by a non-Gaussian probability distribution. In this paper we address the issue of finding an optimal detection method for such a non-Gaussian background. As a first step, we examine the idealized situation in which the event durations are short compared to the detector sampling time, so that the time structure of the events cannot be resolved, and we assume white, Gaussian noise in two collocated, aligned detectors. For this situation we derive an appropriate version of the maximum likelihood detection statistic. We compare the performance of this statistic to that of the standard cross-correlation statistic both analytically and with Monte Carlo simulations. In general the maximum likelihood statistic performs better than the cross-correlation statistic when the stochastic background is sufficiently non-Gaussian, resulting in a gain factor in the minimum gravitational-wave energy density necessary for detection. This gain factor ranges roughly between 1 and 3, depending on the duty cycle of the background, for realistic observing times and signal strengths for both ground and space based detectors. The computational cost of the statistic, although significantly greater than that of the cross-correlation statistic, is not unreasonable. Before the statistic can be used in practice with real detector data, further work is required to generalize our analysis to accommodate separated, misaligned detectors with realistic, colored, non-Gaussian noise.

The Attenuation of Correlation Coefficients: A Statistical Literacy Issue

ERIC Educational Resources Information Center

Trafimow, David

2016-01-01

Much of the science reported in the media depends on correlation coefficients. But the size of correlation coefficients depends, in part, on the reliability with which the correlated variables are measured. Understanding this is a statistical literacy issue.

Statistical indicators of collective behavior and functional clusters in gene networks of yeast

NASA Astrophysics Data System (ADS)

Živković, J.; Tadić, B.; Wick, N.; Thurner, S.

2006-03-01

We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.

The Use of Citation Counting to Identify Research Trends

ERIC Educational Resources Information Center

Rothman, Harry; Woodhead, Michael

1971-01-01

The analysis and application of manpower statistics to identify some long-term international research trends in economic entomology and pest conrol are described. Movements in research interests, particularly towards biological methods of control, correlations between these sectors, and the difficulties encountered in the construction of a…

Reading Ability as a Predictor of Academic Procrastination among African American Graduate Students

ERIC Educational Resources Information Center

Collins, Kathleen M. T.; Onwuegbuzie, Anthony J.; Jiao, Qun G.

2008-01-01

The present study examined the relationship between reading ability (i.e., reading comprehension and reading vocabulary) and academic procrastination among 120 African American graduate students. A canonical correlation analysis revealed statistically significant and practically significant multivariate relationships between these two reading…