Correlation analysis of the physiological factors controlling fundamental voice frequency.

PubMed

Atkinson, J E

1978-01-01

A technique has been developed to obtain a quantitative measure of correlation between electromyographic (EMG) activity of various laryngeal muscles, subglottal air pressure, and the fundamental frequency of vibration of the vocal folds (Fo). Data were collected and analyzed on one subject, a native speaker of American English. The results show that an analysis of this type can provide a useful measure of correlation between the physiological and acoustical events in speech and, furthermore, can yield detailed insights into the organization and nature of the speech production process. In particular, based on these results, a model is suggested of Fo control involving laryngeal state functions that seems to agree with present knowledge of laryngeal control and experimental evidence.

Quantitative gene expression deregulation in mantle-cell lymphoma: correlation with clinical and biologic factors.

PubMed

Kienle, Dirk; Katzenberger, Tiemo; Ott, German; Saupe, Doreen; Benner, Axel; Kohlhammer, Holger; Barth, Thomas F E; Höller, Sylvia; Kalla, Jörg; Rosenwald, Andreas; Müller-Hermelink, Hans Konrad; Möller, Peter; Lichter, Peter; Döhner, Hartmut; Stilgenbauer, Stephan

2007-07-01

There is evidence for a direct role of quantitative gene expression deregulation in mantle-cell lymphoma (MCL) pathogenesis. Our aim was to investigate gene expression associations with other pathogenic factors and the significance of gene expression in a multivariate survival analysis. Quantitative expression of 20 genes of potential relevance for MCL prognosis and pathogenesis were analyzed using real-time reverse transcriptase polymerase chain reaction and correlated with clinical and genetic factors, tumor morphology, and Ki-67 index in 65 MCL samples. Genomic losses at the loci of TP53, RB1, and P16 were associated with reduced transcript levels of the respective genes, indicating a gene-dosage effect as the pathomechanism. Analysis of gene expression correlations between the candidate genes revealed a separation into two clusters, one dominated by proliferation activators, another by proliferation inhibitors and regulators of apoptosis. Whereas only weak associations were identified between gene expression and clinical parameters or blastoid morphology, several genes were correlated closely with the Ki-67 index, including the short CCND1 variant (positive correlation) and RB1, ATM, P27, and BMI (negative correlation). In multivariate survival analysis, expression levels of MYC, MDM2, EZH2, and CCND1 were the strongest prognostic factors independently of tumor proliferation and clinical factors. These results indicate a pathogenic contribution of several gene transcript levels to the biology and clinical course of MCL. Genes can be differentiated into factors contributing to proliferation deregulation, either by enhancement or loss of inhibition, and proliferation-independent factors potentially contributing to MCL pathogenesis by apoptosis impairment.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.

PubMed

Faltermeier, Rupert; Proescholdt, Martin A; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology

PubMed Central

Faltermeier, Rupert; Proescholdt, Martin A.; Bele, Sylvia; Brawanski, Alexander

2015-01-01

Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses. PMID:26693250

[Correlation research on contents of podophyllotoxin and total lignans in Sinopodophyllum hexandrum and ecological factors].

PubMed

Li, Min; Zhong, Guo-yue; Wu, Ao-lin; Zhang, Shou-wen; Jiang, Wei; Liang, Jian

2015-05-01

To explore the correlation between the ecological factors and the contents of podophyllotoxin and total lignans in root and rhizome of Sinopodophyllum hexandrum, podophyllotoxin in 87 samples (from 5 provinces) was determined by HPLC and total lignans by UV. A correlation and regression analysis was made by software SPSS 16.0 in combination with ecological factors (terrain, soil and climate). The content determination results showed a great difference between podophyllotoxin and total lignans, attaining 1.001%-6.230% and 5.350%-16.34%, respective. The correlation and regression analysis by SPSS showed a positive linear correlation between their contents, strong positive correlation between their contents, latitude and annual average rainfall within the sampling area, weak negative correlation with pH value and organic material in soil, weaker and stronger positive correlations with soil potassium, weak negative correlation with slope and annual average temperature and weaker positive correlation between the podophyllotoxin content and soil potassium.

Correlative SEM SERS for quantitative analysis of dimer nanoparticles.

PubMed

Timmermans, F J; Lenferink, A T M; van Wolferen, H A G M; Otto, C

2016-11-14

A Raman microscope integrated with a scanning electron microscope was used to investigate plasmonic structures by correlative SEM-SERS analysis. The integrated Raman-SEM microscope combines high-resolution electron microscopy information with SERS signal enhancement from selected nanostructures with adsorbed Raman reporter molecules. Correlative analysis is performed for dimers of two gold nanospheres. Dimers were selected on the basis of SEM images from multi aggregate samples. The effect of the orientation of the dimer with respect to the polarization state of the laser light and the effect of the particle gap size on the Raman signal intensity is observed. Additionally, calculations are performed to simulate the electric near field enhancement. These simulations are based on the morphologies observed by electron microscopy. In this way the experiments are compared with the enhancement factor calculated with near field simulations and are subsequently used to quantify the SERS enhancement factor. Large differences between experimentally observed and calculated enhancement factors are regularly detected, a phenomenon caused by nanoscale differences between the real and 'simplified' simulated structures. Quantitative SERS experiments reveal the structure induced enhancement factor, ranging from ∼200 to ∼20 000, averaged over the full nanostructure surface. The results demonstrate correlative Raman-SEM microscopy for the quantitative analysis of plasmonic particles and structures, thus enabling a new analytical method in the field of SERS and plasmonics.

Estimation and Testing of Partial Covariances, Correlations, and Regression Weights Using Maximum Likelihood Factor Analysis.

ERIC Educational Resources Information Center

And Others; Werts, Charles E.

1979-01-01

It is shown how partial covariance, part and partial correlation, and regression weights can be estimated and tested for significance by means of a factor analytic model. Comparable partial covariance, correlations, and regression weights have identical significance tests. (Author)

Dynamical behavior of the correlation between meteorological factors

NASA Astrophysics Data System (ADS)

You, Cheol-Hwan; Chang, Ki-Ho; Lee, Jun-Ho; Kim, Kyungsik

2017-12-01

We study the temporal and spatial variation characteristics of meteorological factors (temperature, humidity, and wind velocity) at a meteorological tower located on Bosung-gun of South Korea. We employ the detrended cross-correlation analysis (DCCA) method to extract the overall tendency of the hourly variation from data of meteorological factors. The relationships between meteorological factors are identified and quantified by using DCCA coefficients. From our results, we ascertain that the DCCA coefficient between temperature and humidity at time lag m = 24 has the smallest value at the height of 10 m of the measuring tower. Particularly, the DCCA coefficient between temperature and wind speed at time lag m = 24 has the largest value at a height of 10 m of the measuring tower

Correlation of causal factors that influence construction safety performance: A model.

PubMed

Rodrigues, F; Coutinho, A; Cardoso, C

2015-01-01

The construction sector has presented positive development regarding the decrease in occupational accident rates in recent years. Regardless, the construction sector stands out systematically from other industries due to its high number of fatalities. The aim of this paper is to deeply understand the causality of construction accidents from the early design phase through a model. This study reviewed several research papers presenting various analytical models that correlate the contributing factors to occupational accidents in this sector. This study also analysed different construction projects and conducted a survey of design and site supervision teams. This paper proposes a model developed from the analysis of existing ones, which correlates the causal factors through all the construction phases. It was concluded that effective risk prevention can only be achieved by a global correlation of causal factors including not only production ones but also client requirements, financial climate, design team competence, project and risk management, financial capacity, health and safety policy and early planning. Accordingly, a model is proposed.

Multicollinearity in canonical correlation analysis in maize.

PubMed

Alves, B M; Cargnelutti Filho, A; Burin, C

2017-03-30

The objective of this study was to evaluate the effects of multicollinearity under two methods of canonical correlation analysis (with and without elimination of variables) in maize (Zea mays L.) crop. Seventy-six maize genotypes were evaluated in three experiments, conducted in a randomized block design with three replications, during the 2009/2010 crop season. Eleven agronomic variables (number of days from sowing until female flowering, number of days from sowing until male flowering, plant height, ear insertion height, ear placement, number of plants, number of ears, ear index, ear weight, grain yield, and one thousand grain weight), 12 protein-nutritional variables (crude protein, lysine, methionine, cysteine, threonine, tryptophan, valine, isoleucine, leucine, phenylalanine, histidine, and arginine), and 6 energetic-nutritional variables (apparent metabolizable energy, apparent metabolizable energy corrected for nitrogen, ether extract, crude fiber, starch, and amylose) were measured. A phenotypic correlation matrix was first generated among the 29 variables for each of the experiments. A multicollinearity diagnosis was later performed within each group of variables using methodologies such as variance inflation factor and condition number. Canonical correlation analysis was then performed, with and without the elimination of variables, among groups of agronomic and protein-nutritional, and agronomic and energetic-nutritional variables. The canonical correlation analysis in the presence of multicollinearity (without elimination of variables) overestimates the variability of canonical coefficients. The elimination of variables is an efficient method to circumvent multicollinearity in canonical correlation analysis.

Bone mineral density and correlation factor analysis in normal Taiwanese children.

PubMed

Shu, San-Ging

2007-01-01

Our aim was to establish reference data and linear regression equations for lumbar bone mineral density (BMD) in normal Taiwanese children. Several influencing factors of lumbar BMD were investigated. Two hundred fifty-seven healthy children were recruited from schools, 136 boys and 121 girls, aged 4-18 years were enrolled on a voluntary basis with written consent. Their height, weight, blood pressure, puberty stage, bone age and lumbar BMD (L2-4) by dual energy x-ray absorptiometry (DEXA) were measured. Data were analyzed using Pearson correlation and stepwise regression tests. All measurements increased with age. Prior to age 8, there was no gender difference. Parameters such as height, weight, and bone age (BA) in girls surpassed boys between ages 8-13 without statistical significance (p> or =0.05). This was reversed subsequently after age 14 in height (p<0.05). BMD difference had the same trend but was not statistically significant either. The influencing power of puberty stage and bone age over BMD was almost equal to or higher than that of height and weight. All the other factors correlated with BMD to variable powers. Multiple linear regression equations for boys and girls were formulated. BMD reference data is provided and can be used to monitor childhood pathological conditions. However, BMD in those with abnormal bone age or pubertal development could need modifications to ensure accuracy.

[Correlation analysis on normalized difference vegetation index (NDVI) of different vegetations and climatic factors in Southwest China].

PubMed

Zhang, Yuan-Dong; Zhang, Xiao-He; Liu, Shi-Rong

2011-02-01

Based on the 1982-2006 NDVI remote sensing data and meteorological data of Southwest China, and by using GIS technology, this paper interpolated and extracted the mean annual temperature, annual precipitation, and drought index in the region, and analyzed the correlations of the annual variation of NDVI in different vegetation types (marsh, shrub, bush, grassland, meadow, coniferous forest, broad-leaved forest, alpine vegetation, and cultural vegetation) with corresponding climatic factors. In 1982-2006, the NDVI, mean annual temperature, and annual precipitation had an overall increasing trend, and the drought index decreased. Particularly, the upward trend of mean annual temperature was statistically significant. Among the nine vegetation types, the NDVI of bush and mash decreased, and the downward trend was significant for bush. The NDVI of the other seven vegetation types increased, and the upward trend was significant for coniferous forest, meadow, and alpine vegetation, and extremely significant for shrub. The mean annual temperature in the areas with all the nine vegetation types increased significantly, while the annual precipitation had no significant change. The drought index in the areas with marsh, bush, and cultural vegetation presented an increasing trend, that in the areas with meadow and alpine vegetation decreased significantly, and this index in the areas with other four vegetation types had an unobvious decreasing trend. The NDVI of shrub and coniferous forest had a significantly positive correlation with mean annual temperature, and that of shrub and meadow had significantly negative correlation with drought index. Under the conditions of the other two climatic factors unchanged, the NDVI of coniferous forest, broad-leaved forest, and alpine vegetation showed the strongest correlation with mean annual temperature, that of grass showed the strongest correlation with annual precipitation, and the NDVI of mash, shrub, grass, meadow, and cultural

Forecasted trends in vaccination coverage and correlations with socioeconomic factors: a global time-series analysis over 30 years.

PubMed

de Figueiredo, Alexandre; Johnston, Iain G; Smith, David M D; Agarwal, Sumeet; Larson, Heidi J; Jones, Nick S

2016-10-01

Incomplete immunisation coverage causes preventable illness and death in both developing and developed countries. Identification of factors that might modulate coverage could inform effective immunisation programmes and policies. We constructed a performance indicator that could quantitatively approximate measures of the susceptibility of immunisation programmes to coverage losses, with an aim to identify correlations between trends in vaccine coverage and socioeconomic factors. We undertook a data-driven time-series analysis to examine trends in coverage of diphtheria, tetanus, and pertussis (DTP) vaccination across 190 countries over the past 30 years. We grouped countries into six world regions according to WHO classifications. We used Gaussian process regression to forecast future coverage rates and provide a vaccine performance index: a summary measure of the strength of immunisation coverage in a country. Overall vaccine coverage increased in all six world regions between 1980 and 2010, with variation in volatility and trends. Our vaccine performance index identified that 53 countries had more than a 50% chance of missing the Global Vaccine Action Plan (GVAP) target of 90% worldwide coverage with three doses of DTP (DTP3) by 2015. These countries were mostly in sub-Saharan Africa and south Asia, but Austria and Ukraine also featured. Factors associated with DTP3 immunisation coverage varied by world region: personal income (Spearman's ρ=0·66, p=0·0011) and government health spending (0·66, p<0·0001) were informative of immunisation coverage in the Eastern Mediterranean between 1980 and 2010, whereas primary school completion was informative of coverage in Africa (0·56, p<0·0001) over the same period. The proportion of births attended by skilled health staff correlated significantly with immunisation coverage across many world regions. Our vaccine performance index highlighted countries at risk of failing to achieve the GVAP target of 90% coverage by

HIV incidence and CDC's HIV prevention budget: an exploratory correlational analysis.

PubMed

Holtgrave, David R; Kates, Jennifer

2007-01-01

The central evaluative question about a national HIV prevention program is whether that program affects HIV incidence. Numerous factors may influence incidence, including public investment in HIV prevention. Few studies, however, have examined the relationship between public investment and the HIV epidemic in the United States. This 2006 exploratory analysis examined the period from 1978 through 2006 using a quantitative, lagged, correlational analysis to capture the relationship between national HIV incidence and Centers for Disease Control and Prevention's HIV prevention budget in the United States over time. The analyses suggest that early HIV incidence rose in advance of the nation's HIV prevention investment until the mid-1980s (1-year lag correlation, r=0.972, df=2, p <0.05). From that point on, it appears that the nation's investment in HIV prevention became a strong correlate of HIV incidence (1-year lag correlation, r=-0.905, df=18, p <0.05). This exploratory study provides correlational evidence of a relationship between U.S. HIV incidence and the federal HIV prevention budget over time, and calls for further analysis of the role of funding and other factors that may influence the direction of a nation's HIV epidemic.

Using BMDP and SPSS for a Q factor analysis.

PubMed

Tanner, B A; Koning, S M

1980-12-01

While Euclidean distances and Q factor analysis may sometimes be preferred to correlation coefficients and cluster analysis for developing a typology, commercially available software does not always facilitate their use. Commands are provided for using BMDP and SPSS in a Q factor analysis with Euclidean distances.

Clinical correlates of resilience factors in geriatric depression.

PubMed

Laird, Kelsey T; Lavretsky, Helen; Paholpak, Pattharee; Vlasova, Roza M; Roman, Michael; St Cyr, Natalie; Siddarth, Prabha

2018-01-16

Traditional perspectives conceptualize resilience as a trait and depression as resulting from resilience deficiency. However, research indicates that resilience varies substantially even among adults who are clinically depressed, as well as across the lifespan of an individual. Few studies have investigated resilience in depression, and even fewer have examined resilience in depressed older adults. Three hundred thirty-seven adults ≥60 years with major depressive disorder completed the Connor-Davidson Resilience Scale (CD-RISC) and measures of mental health, quality of life (QOL), and medical comorbidity. Exploratory factor analysis was used to explore the factor structure of the CD-RISC. Correlations and general linear models were used to examine associations between resilience and other variables. The rotated component matrix indicated a four-factor model. Sorting of items by highest factor loading revealed constructs associated with (1) grit, (2) active coping self-efficacy, (3) accommodative coping self-efficacy, and (4) spirituality. Resilience was significantly correlated with increased age, lower cognitive functioning, greater cerebrovascular risk, and greater medical comorbidity. Resilience was negatively associated with mental health symptoms (depression, apathy, and anxiety) and positively associated with QOL. The final optimal model identified less depression, less apathy, greater medical comorbidity, higher QOL, and minority (non-White) race as factors that significantly explained variability in resilience. Resilience was significantly associated with a range of mental health constructs in a sample of older adults with depression. Future clinical trials and dismantling studies may help determine whether interventions targeting grit, active coping, accommodative coping, and spirituality can increase resilience and help prevent and treat depression in older adults.

Accuracy of the Parallel Analysis Procedure with Polychoric Correlations

ERIC Educational Resources Information Center

Cho, Sun-Joo; Li, Feiming; Bandalos, Deborah

2009-01-01

The purpose of this study was to investigate the application of the parallel analysis (PA) method for choosing the number of factors in component analysis for situations in which data are dichotomous or ordinal. Although polychoric correlations are sometimes used as input for component analyses, the random data matrices generated for use in PA…

Bayesian Correlation Analysis for Sequence Count Data

PubMed Central

Lau, Nelson; Perkins, Theodore J.

2016-01-01

Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities’ measurements based on high-throughput sequencing data. These entities could be different genes or miRNAs whose expression is measured by RNA-seq, different transcription factors or histone marks whose expression is measured by ChIP-seq, or even combinations of different types of entities. Our Bayesian formulation accounts for both measured signal levels and uncertainty in those levels, due to varying sequencing depth in different experiments and to varying absolute levels of individual entities, both of which affect the precision of the measurements. In comparison with a traditional Pearson correlation analysis, we show that our Bayesian correlation analysis retains high correlations when measurement confidence is high, but suppresses correlations when measurement confidence is low—especially for entities with low signal levels. In addition, we consider the influence of priors on the Bayesian correlation estimate. Perhaps surprisingly, we show that naive, uniform priors on entities’ signal levels can lead to highly biased correlation estimates, particularly when different experiments have widely varying sequencing depths. However, we propose two alternative priors that provably mitigate this problem. We also prove that, like traditional Pearson correlation, our Bayesian correlation calculation constitutes a kernel in the machine learning sense, and thus can be used as a similarity measure in any kernel-based machine learning algorithm. We demonstrate our approach on two RNA-seq datasets and one miRNA-seq dataset. PMID:27701449

Correlation analysis for the attack of bacillary dysentery and meteorological factors based on the Chinese medicine theory of Yunqi and the medical-meteorological forecast model.

PubMed

Ma, Shi-Lei; Tang, Qiao-Ling; Liu, Hong-Wei; He, Juan; Gao, Si-Hua

2013-03-01

To explore the impact of meteorological factors on the outbreak of bacillary dysentery, so as to provide suggestions for disease prevention. Based on the Chinese medicine theory of Yunqi, the descriptive statistics, single-factor correlation analysis and back-propagation artificial neural net-work were conducted using data on five basic meteorological factors and data on incidence of bacillary dysentery in Beijing, China, for the period 1970-2004. The incidence of bacillary dysentery showed significant positive correlation relationship with the precipitation, relative humidity, vapor pressure, and temperature, respectively. The incidence of bacillary dysentery showed a negatively correlated relationship with the wind speed and the change trend of average wind speed. The results of medical-meteorological forecast model showed a relatively high accuracy rate. There is a close relationship between the meteorological factors and the incidence of bacillary dysentery, but the contributions of which to the onset of bacillary dysentery are different to each other.

Psychological Factors and Conditioned Pain Modulation: A Meta-Analysis.

PubMed

Nahman-Averbuch, Hadas; Nir, Rony-Reuven; Sprecher, Elliot; Yarnitsky, David

2016-06-01

Conditioned pain modulation (CPM) responses may be affected by psychological factors such as anxiety, depression, and pain catastrophizing; however, most studies on CPM do not address these relations as their primary outcome. The aim of this meta-analysis was to analyze the findings regarding the associations between CPM responses and psychological factors in both pain-free individuals and pain patients. After a comprehensive PubMed search, 37 articles were found to be suitable for inclusion. Analyses used DerSimonian and Laird's random-effects model on Fisher's z-transforms of correlations; potential publication bias was tested using funnel plots and Egger's regression test for funnel plot asymmetry. Six meta-analyses were performed examining the correlations between anxiety, depression, and pain catastrophizing, and CPM responses in healthy individuals and pain patients. No significant correlations between CPM responses and any of the examined psychological factors were found. However, a secondary analysis, comparing modality-specific CPM responses and psychological factors in healthy individuals, revealed the following: (1) pressure-based CPM responses were correlated with anxiety (grand mean correlation in original units r=-0.1087; 95% confidence limits, -0.1752 to -0.0411); (2) heat-based CPM was correlated with depression (r=0.2443; 95% confidence limits, 0.0150 to 0.4492); and (3) electrical-based CPM was correlated with pain catastrophizing levels (r=-0.1501; 95% confidence limits, -0.2403 to -0.0574). Certain psychological factors seem to be associated with modality-specific CPM responses in healthy individuals. This potentially supports the notion that CPM paradigms evoked by different stimulation modalities represent different underlying mechanisms.

Regularized Generalized Canonical Correlation Analysis

ERIC Educational Resources Information Center

Tenenhaus, Arthur; Tenenhaus, Michel

2011-01-01

Regularized generalized canonical correlation analysis (RGCCA) is a generalization of regularized canonical correlation analysis to three or more sets of variables. It constitutes a general framework for many multi-block data analysis methods. It combines the power of multi-block data analysis methods (maximization of well identified criteria) and…

Analysis of the correlative factors for velopharyngeal closure of patients with cleft palate after primary repair.

PubMed

Chen, Qi; Li, Yang; Shi, Bing; Yin, Heng; Zheng, Guang-Ning; Zheng, Qian

2013-12-01

The objective of this study was to analyze the correlative factors for velopharyngeal closure of patients with cleft palate after primary repair. Ninety-five nonsyndromic patients with cleft palate were enrolled. Two surgical techniques were applied in the patients: simple palatoplasty and combined palatoplasty with pharyngoplasty. All patients were assessed 6 months after the operation. The postoperative velopharyngeal closure (VPC) rate was compared by χ(2) test and the correlative factors were analyzed with logistic regression model. The postoperative VPC rate of young patients was higher than that of old patients, the group with incomplete cleft palate was higher than the group with complete cleft palate, and combined palatoplasty with pharyngoplasty was higher than simple palatoplasty. Operative age, cleft type, and surgical technique were the contributing factors for postoperative VPC rate. Operative age, cleft type, and surgical technique were significant factors influencing postoperative VPC rate of patients with cleft palate. Copyright © 2013 Elsevier Inc. All rights reserved.

The Eysenckian personality factors and their correlations with academic performance.

PubMed

Poropat, Arthur E

2011-03-01

BACKGROUND. The relationship between personality and academic performance has long been explored, and a recent meta-analysis established that measures of the five-factor model (FFM) dimension of Conscientiousness have similar validity to intelligence measures. Although currently dominant, the FFM is only one of the currently accepted models of personality, and has limited theoretical support. In contrast, the Eysenckian personality model was developed to assess a specific theoretical model and is still commonly used in educational settings and research. AIMS. This meta-analysis assessed the validity of the Eysenckian personality measures for predicting academic performance. SAMPLE. Statistics were obtained for correlations with Psychoticism, Extraversion, and Neuroticism (20-23 samples; N from 8,013 to 9,191), with smaller aggregates for the Lie scale (7 samples; N= 3,910). METHODS. The Hunter-Schmidt random effects method was used to estimate population correlations between the Eysenckian personality measures and academic performance. Moderating effects were tested using weighted least squares regression. RESULTS. Significant but modest validities were reported for each scale. Neuroticism and Extraversion had relationships with academic performance that were consistent with previous findings, while Psychoticism appears to be linked to academic performance because of its association with FFM Conscientiousness. Age and educational level moderated correlations with Neuroticism and Extraversion, and gender had no moderating effect. Correlations varied significantly based on the measurement instrument used. CONCLUSIONS. The Eysenckian scales do not add to the prediction of academic performance beyond that provided by FFM scales. Several measurement problems afflict the Eysenckian scales, including low to poor internal reliability and complex factor structures. In particular, the measurement and validity problems of Psychoticism mean its continued use in academic

Functional Multiple-Set Canonical Correlation Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Jung, Kwanghee; Takane, Yoshio; Woodward, Todd S.

2012-01-01

We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the…

Examination of fungi in domestic interiors by using factor analysis: Correlations and associations with home factors. [Cladosporium, Alternaria, Epicoccum, Aureobasidium, Aspergillus; Penicillium

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

Su, H.J.; Rotnitzky, A.; Spengler, J.D.

1992-01-01

Factor analysis was utilized to investigate correlations among airborne microorganisms collected with Andersen samplers from homes in Topeka, Kans., during the winter of 1987 to 1988. The factors derived were used to relate microbial concentrations with categorical, questionnaire-derived descriptions of housing conditions. This approach successfully identified groups of common aboveground decay fungi including Cladosporium, Alternaria, Epicoccum, and Aureobasidium spp. The common soil fungi Aspergillus and Penicillium spp. were also separated as a group. These previously known ecological groupings were confirmed with air sampling data by a quantitative evaluation technique. The above ground decay fungi sampled indoors in winter were presentmore » at relatively high concentrations in homes with gas stoves for cooking, suggesting a possible association between these fungi and increased humidity from the combustion process. Elevated concentrations of the soil fungi were significantly associated with the dirt floor, crawl-space type of basement. Elevated concentrations of water-requiring fungi, such as Fusarium spp., were shown to be associated with water collection in domestic interiors. Also, elevated mean concentrations for the group of fungi including Cladosporium, Epicoccum, Aureobasidium, and yeast spp. were found to be associated with symptoms reported on a health questionnaire. This finding was consistent with the authors previous study of associations between respiratory health and airborne microorganisms by univariate logistic regression analysis.« less

Fuzzy correlation analysis with realization

NASA Astrophysics Data System (ADS)

Tang, Yue Y.; Fan, Xinrui; Zheng, Ying N.

1998-10-01

The fundamental concept of fuzzy correlation is briefly discussed. Based on the correlation coefficient of classic correlation, polarity correlation and fuzzy correlation, the relationship between the correlations are analyzed. A fuzzy correlation analysis has the merits of both rapidity and accuracy as some amplitude information of random signals has been utilized. It has broad prospects for application. The form of fuzzy correlative analyzer with NLX 112 fuzzy data correlator and single-chip microcomputer is introduced.

A generalized view of the correlation factor in solid-state diffusion

NASA Astrophysics Data System (ADS)

Akbar, Sheikh A.

1994-03-01

The correlation factor is commonly used to determine the mechanism of diffusion in solids. Although originally thought to be associated only with tracer diffusion, the concept of the correlation factor has broadened considerably over the last couple of decades. In light of these developments, it is important to generalize the concept. This article attempts to present a simple picture of an integrated view of the correlation factor in a way accessible to a wider audience. Some areas where the generalized correlation factor plays important roles are also highlighted.

Scale-Free Nonparametric Factor Analysis: A User-Friendly Introduction with Concrete Heuristic Examples.

ERIC Educational Resources Information Center

Mittag, Kathleen Cage

Most researchers using factor analysis extract factors from a matrix of Pearson product-moment correlation coefficients. A method is presented for extracting factors in a non-parametric way, by extracting factors from a matrix of Spearman rho (rank correlation) coefficients. It is possible to factor analyze a matrix of association such that…

Allowing for Correlations between Correlations in Random-Effects Meta-Analysis of Correlation Matrices

ERIC Educational Resources Information Center

Prevost, A. Toby; Mason, Dan; Griffin, Simon; Kinmonth, Ann-Louise; Sutton, Stephen; Spiegelhalter, David

2007-01-01

Practical meta-analysis of correlation matrices generally ignores covariances (and hence correlations) between correlation estimates. The authors consider various methods for allowing for covariances, including generalized least squares, maximum marginal likelihood, and Bayesian approaches, illustrated using a 6-dimensional response in a series of…

Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

PubMed

Stankov, L

1979-07-01

The procedure for hierarchical factoring suggested by Schmid and Leiman (1957) is applied within the framework of image analysis and orthoblique rotational procedures. It is shown that this approach necessarily leads to correlated higher order factors. Also, one can obtain a smaller number of factors than produced by typical hierarchical procedures.

Two speed factors of visual recognition independently correlated with fluid intelligence.

PubMed

Tachibana, Ryosuke; Namba, Yuri; Noguchi, Yasuki

2014-01-01

Growing evidence indicates a moderate but significant relationship between processing speed in visuo-cognitive tasks and general intelligence. On the other hand, findings from neuroscience proposed that the primate visual system consists of two major pathways, the ventral pathway for objects recognition and the dorsal pathway for spatial processing and attentive analysis. Previous studies seeking for visuo-cognitive factors of human intelligence indicated a significant correlation between fluid intelligence and the inspection time (IT), an index for a speed of object recognition performed in the ventral pathway. We thus presently examined a possibility that neural processing speed in the dorsal pathway also represented a factor of intelligence. Specifically, we used the mental rotation (MR) task, a popular psychometric measure for mental speed of spatial processing in the dorsal pathway. We found that the speed of MR was significantly correlated with intelligence scores, while it had no correlation with one's IT (recognition speed of visual objects). Our results support the new possibility that intelligence could be explained by two types of mental speed, one related to object recognition (IT) and another for manipulation of mental images (MR).

Two Speed Factors of Visual Recognition Independently Correlated with Fluid Intelligence

PubMed Central

Tachibana, Ryosuke; Namba, Yuri; Noguchi, Yasuki

2014-01-01

Growing evidence indicates a moderate but significant relationship between processing speed in visuo-cognitive tasks and general intelligence. On the other hand, findings from neuroscience proposed that the primate visual system consists of two major pathways, the ventral pathway for objects recognition and the dorsal pathway for spatial processing and attentive analysis. Previous studies seeking for visuo-cognitive factors of human intelligence indicated a significant correlation between fluid intelligence and the inspection time (IT), an index for a speed of object recognition performed in the ventral pathway. We thus presently examined a possibility that neural processing speed in the dorsal pathway also represented a factor of intelligence. Specifically, we used the mental rotation (MR) task, a popular psychometric measure for mental speed of spatial processing in the dorsal pathway. We found that the speed of MR was significantly correlated with intelligence scores, while it had no correlation with one’s IT (recognition speed of visual objects). Our results support the new possibility that intelligence could be explained by two types of mental speed, one related to object recognition (IT) and another for manipulation of mental images (MR). PMID:24825574

Factor analysis and multiple regression between topography and precipitation on Jeju Island, Korea

NASA Astrophysics Data System (ADS)

Um, Myoung-Jin; Yun, Hyeseon; Jeong, Chang-Sam; Heo, Jun-Haeng

2011-11-01

SummaryIn this study, new factors that influence precipitation were extracted from geographic variables using factor analysis, which allow for an accurate estimation of orographic precipitation. Correlation analysis was also used to examine the relationship between nine topographic variables from digital elevation models (DEMs) and the precipitation in Jeju Island. In addition, a spatial analysis was performed in order to verify the validity of the regression model. From the results of the correlation analysis, it was found that all of the topographic variables had a positive correlation with the precipitation. The relations between the variables also changed in accordance with a change in the precipitation duration. However, upon examining the correlation matrix, no significant relationship between the latitude and the aspect was found. According to the factor analysis, eight topographic variables (latitude being the exception) were found to have a direct influence on the precipitation. Three factors were then extracted from the eight topographic variables. By directly comparing the multiple regression model with the factors (model 1) to the multiple regression model with the topographic variables (model 3), it was found that model 1 did not violate the limits of statistical significance and multicollinearity. As such, model 1 was considered to be appropriate for estimating the precipitation when taking into account the topography. In the study of model 1, the multiple regression model using factor analysis was found to be the best method for estimating the orographic precipitation on Jeju Island.

Canonical correlation analysis of synchronous neural interactions and cognitive deficits in Alzheimer's dementia

NASA Astrophysics Data System (ADS)

Karageorgiou, Elissaios; Lewis, Scott M.; Riley McCarten, J.; Leuthold, Arthur C.; Hemmy, Laura S.; McPherson, Susan E.; Rottunda, Susan J.; Rubins, David M.; Georgopoulos, Apostolos P.

2012-10-01

In previous work (Georgopoulos et al 2007 J. Neural Eng. 4 349-55) we reported on the use of magnetoencephalographic (MEG) synchronous neural interactions (SNI) as a functional biomarker in Alzheimer's dementia (AD) diagnosis. Here we report on the application of canonical correlation analysis to investigate the relations between SNI and cognitive neuropsychological (NP) domains in AD patients. First, we performed individual correlations between each SNI and each NP, which provided an initial link between SNI and specific cognitive tests. Next, we performed factor analysis on each set, followed by a canonical correlation analysis between the derived SNI and NP factors. This last analysis optimally associated the entire MEG signal with cognitive function. The results revealed that SNI as a whole were mostly associated with memory and language, and, slightly less, executive function, processing speed and visuospatial abilities, thus differentiating functions subserved by the frontoparietal and the temporal cortices. These findings provide a direct interpretation of the information carried by the SNI and set the basis for identifying specific neural disease phenotypes according to cognitive deficits.

Analysis of HIV Correlated Factors in Chinese and Vietnamese Female Sex Workers in Hekou, Yunnan Province, a Chinese Border Region

PubMed Central

Wang, Junjie; Ding, Guowei; Zhu, Zhibin; Zhou, Chunlian; Wang, Ning

2015-01-01

Objectives To assess the prevalence and correlated factors of HIV-1 among Chinese and Vietnamese female sex workers (FSW) in the border county of Hekou, Yunnan province, China. Methods A cross-sectional survey was conducted collecting information on demographics, sexual behavior, medical history, and drug use. Blood samples were obtained to test for HIV/STIs. Multivariate logistic regression model was used to examine associations between factors and HIV-1 infection. Results Of 345 FSWs who participated in this study, 112 (32.5%) were Chinese and 233 (67.5) were Vietnamese. Vietnamese FSWs were significantly more likely to be HIV-1 positive (7.7%) compared with Chinese FSWs (0.9%) (p = 0.009). In multivariate analysis, sexual debut at age≤16 (OR 3.8: 95% CI: 1.4, 10.6), last client’s payment <150 RMB ($22 USD) (OR: 5.2, 95% CI; 1.7, 16.6), and HSV-2 (OR: 12.3; 95% CI: 1.6, 94.8) were significant for HIV-1 infection. Conclusions Differences in HIV prevalence in Vietnamese and Chinese FSWs may be indicative of differential risk. It is important to characterize the nature of trans-border transmission in order to gain a better understanding of the potential impact on the international HIV epidemic. Understanding the correlated factors for HIV in Vietnamese and Chinese FSWs is important for designing interventions for this vulnerable population. PMID:26053040

Analysis of Factors Influencing Creative Personality of Elementary School Students

ERIC Educational Resources Information Center

Park, Jongman; Kim, Minkee; Jang, Shinho

2017-01-01

This quantitative research examined factors that affect elementary students' creativity and how those factors correlate. Aiming to identify significant factors that affect creativity and to clarify the relationship between these factors by path analysis, this research was designed to be a stepping stone for creativity enhancement studies. Data…

Bayesian Factor Analysis When Only a Sample Covariance Matrix Is Available

ERIC Educational Resources Information Center

Hayashi, Kentaro; Arav, Marina

2006-01-01

In traditional factor analysis, the variance-covariance matrix or the correlation matrix has often been a form of inputting data. In contrast, in Bayesian factor analysis, the entire data set is typically required to compute the posterior estimates, such as Bayes factor loadings and Bayes unique variances. We propose a simple method for computing…

Clustering of risk factors for noncommunicable diseases in Brazilian adolescents: prevalence and correlates.

PubMed

Cureau, Felipe Vogt; Duarte, Paola; dos Santos, Daniela Lopes; Reichert, Felipe Fossati

2014-07-01

Few studies have investigated the prevalence and correlates of risk factors for noncommunicable diseases among Brazilian adolescents. We evaluated the clustering of risk factors and their associations with sociodemographic variables. We used a cross-sectional study carried out in 2011 comprising 1132 students aged 14-19 years from Santa Maria, Brazil. The cluster index was created as the sum of the risk factors. For the correlates analysis, a multinomial logistic regression was used. Furthermore, the observed/expected ratio was calculated. Prevalence of individual risk factors studied was as follows: 85.8% unhealthy diets, 53.5% physical inactivity, 31.3% elevated blood pressure, 23.9% overweight, 22.3% excessive drinking alcohol, and 8.6% smoking. Only 2.8% of the adolescents did not present any risk factor, while 21.7%, 40.9%, 23.1%, and 11.5% presented 1, 2, 3, and 4 or more risk factors, respectively. The most prevalent combination was between unhealthy diets and physical inactivity (observed/expected ratio =1.32; 95% CI: 1.16-1.49). Clustering of risk factors was directly associated with age and inversely associated with socioeconomic status. Clustering of risk factors for noncommunicable diseases is high in Brazilian adolescents. Preventive strategies are more likely to be successful if focusing on multiple risk factors, instead of a single one.

Factors that influence disease-specific quality of life or health status in patients with COPD: a review and meta-analysis of Pearson correlations.

PubMed

Tsiligianni, Ioanna; Kocks, Janwillem; Tzanakis, Nikolaos; Siafakas, Nikolaos; van der Molen, Thys

2011-09-01

A major goal in the management of chronic obstructive pulmonary disease (COPD) is to ensure that the burden of the disease for patients with COPD is limited and that patients will have the best possible quality of life. To explore all the possible factors that could influence disease-specific quality of life and health status in patients with COPD. A systematic review of the literature and a meta-analysis were performed to explore the factors that could have a positive or negative effect on quality of life and/or health status in patients with COPD. Quality of life and health status are determined by certain factors included gender, disease severity indices, lung function parameters, body mass index, smoking, symptoms, co-morbidity, depression, anxiety, and exacerbations. Factors such as dyspnoea, depression, anxiety and exercise tolerance were found to be more correlated with health status than the widely used spirometric values. Forced expiratory volume in one second had a weak to modest Pearson weighted correlation coefficient which ranged from -0.110 to -0.510 depending on the questionnaire used. The broad range of determining factors suggests that, in order to reach the management goals, health status should be measured in addition to lung function in patients with COPD.

[Correlation analysis of major agronomic characters and the polysaccharide contents in Dendrobium officinale].

PubMed

Zhang, Lei; Zheng, Xi-Long; Qiu, Dao-Shou; Cai, Shi-Ke; Luo, Huan-Ming; Deng, Rui-Yun; Liu, Xiao-Jin

2013-10-01

In order to provide theoretical and technological basis for the germplasm innovation and variety breeding in Dendrobium officinale, a study of the correlation between polysaccharide content and agronomic characters was conducted. Based on the polysaccharide content determination and the agronomic characters investigation of 30 copies (110 individual plants) of Dendrobium officinale germplasm resources, the correlation between polysaccharide content and agronomic characters was analyzed via path and correlation analysis. Correlation analysis results showed that there was a significant negative correlation between average spacing and polysaccharide content, the correlation coefficient was -0.695. And the blade thickness was positively correlated with the polysaccharide content, but the correlation was not significant. The path analysis results showed that the stem length was the maximum influence factor to the polysaccharide, and it was positive effect, the direct path coefficient was 1.568. According to thess results, the polysaccharide content can be easily and intuitively estimated by the agronomic characters investigating data in the germpalsm resources screening and variety breeding. Therefore, it is a visual and practical technology guidance in quality variety breeding of Dendrobium officinale.

Phylogenetic Factor Analysis.

PubMed

Tolkoff, Max R; Alfaro, Michael E; Baele, Guy; Lemey, Philippe; Suchard, Marc A

2018-05-01

Phylogenetic comparative methods explore the relationships between quantitative traits adjusting for shared evolutionary history. This adjustment often occurs through a Brownian diffusion process along the branches of the phylogeny that generates model residuals or the traits themselves. For high-dimensional traits, inferring all pair-wise correlations within the multivariate diffusion is limiting. To circumvent this problem, we propose phylogenetic factor analysis (PFA) that assumes a small unknown number of independent evolutionary factors arise along the phylogeny and these factors generate clusters of dependent traits. Set in a Bayesian framework, PFA provides measures of uncertainty on the factor number and groupings, combines both continuous and discrete traits, integrates over missing measurements and incorporates phylogenetic uncertainty with the help of molecular sequences. We develop Gibbs samplers based on dynamic programming to estimate the PFA posterior distribution, over 3-fold faster than for multivariate diffusion and a further order-of-magnitude more efficiently in the presence of latent traits. We further propose a novel marginal likelihood estimator for previously impractical models with discrete data and find that PFA also provides a better fit than multivariate diffusion in evolutionary questions in columbine flower development, placental reproduction transitions and triggerfish fin morphometry.

Detrended partial cross-correlation analysis of two nonstationary time series influenced by common external forces

NASA Astrophysics Data System (ADS)

Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene

2015-06-01

When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.

Confirmatory factor analysis of the Child Oral Health Impact Profile (Korean version).

PubMed

Cho, Young Il; Lee, Soonmook; Patton, Lauren L; Kim, Hae-Young

2016-04-01

Empirical support for the factor structure of the Child Oral Health Impact Profile (COHIP) has not been fully established. The purposes of this study were to evaluate the factor structure of the Korean version of the COHIP (COHIP-K) empirically using confirmatory factor analysis (CFA) based on the theoretical framework and then to assess whether any of the factors in the structure could be grouped into a simpler single second-order factor. Data were collected through self-reported COHIP-K responses from a representative community sample of 2,236 Korean children, 8-15 yr of age. Because a large inter-factor correlation of 0.92 was estimated in the original five-factor structure, the two strongly correlated factors were combined into one factor, resulting in a four-factor structure. The revised four-factor model showed a reasonable fit with appropriate inter-factor correlations. Additionally, the second-order model with four sub-factors was reasonable with sufficient fit and showed equal fit to the revised four-factor model. A cross-validation procedure confirmed the appropriateness of the findings. Our analysis empirically supported a four-factor structure of COHIP-K, a summarized second-order model, and the use of an integrated summary COHIP score. © 2016 Eur J Oral Sci.

The Quality of Life of Hemodialysis Patients Is Affected Not Only by Medical but also Psychosocial Factors: a Canonical Correlation Study.

PubMed

Kim, Kyungmin; Kang, Gun Woo; Woo, Jungmin

2018-04-02

The quality of life (QoL) of patients with end-stage renal disease (ESRD) is very poor, plausibly due to both psychosocial and medical factors. This study aimed to determine the relationship among psychosocial factors, medical factors, and QoL in patients with ESRD undergoing hemodialysis (HD). In total, 55 male and 47 female patients were evaluated (mean age, 57.1 ± 12.0 years). The QoL was evaluated using the Korean version of World Health Organization Quality of Life Scale-Abbreviated Version. The psychosocial factors were evaluated using the Hospital Anxiety and Depression Scale, Multidimensional Scale of Perceived Social Support, Montreal Cognitive Assessment, Pittsburgh Sleep Quality Index, and Zarit Burden Interview. The medical factors were assessed using laboratory examinations. Correlation and canonical correlation analyses were performed to investigate the association patterns. The QoL was significantly correlated with the psychosocial factors, and to a lesser extent with the medical factors. The medical and psychosocial factors were also correlated. The canonical correlation analysis indicated a correlation between QoL and psychosocial factors (1st canonical correlation = 0.696, P < 0.001; 2nd canonical correlation = 0.421, P = 0.191), but not medical factors (1st canonical correlation = 0.478, P = 0.475; 2nd canonical correlation = 0.419, P = 0.751). The medical and psychosocial factors were also correlated (1st canonical correlation = 0.689, P < 0.001; 2nd canonical correlation = 0.603, P = 0.009). Psychosocial factors influence QoL in patients with ESRD, and should thus be carefully considered when caring for these patients in clinical practice. © 2018 The Korean Academy of Medical Sciences.

Exploratory factor analysis of the Oral Health Impact Profile.

PubMed

John, M T; Reissmann, D R; Feuerstahler, L; Waller, N; Baba, K; Larsson, P; Celebić, A; Szabo, G; Rener-Sitar, K

2014-09-01

Although oral health-related quality of life (OHRQoL) as measured by the Oral Health Impact Profile (OHIP) is thought to be multidimensional, the nature of these dimensions is not known. The aim of this report was to explore the dimensionality of the OHIP using the Dimensions of OHRQoL (DOQ) Project, an international study of general population subjects and prosthodontic patients. Using the project's Learning Sample (n = 5173), we conducted an exploratory factor analysis on the 46 OHIP items not specifically referring to dentures for 5146 subjects with sufficiently complete data. The first eigenvalue (27·0) of the polychoric correlation matrix was more than ten times larger than the second eigenvalue (2·6), suggesting the presence of a dominant, higher-order general factor. Follow-up analyses with Horn's parallel analysis revealed a viable second-order, four-factor solution. An oblique rotation of this solution revealed four highly correlated factors that we named Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact. These four dimensions and the strong general factor are two viable hypotheses for the factor structure of the OHIP. © 2014 John Wiley & Sons Ltd.

[The epidemiological characteristics and correlated factors of daily hassles for thermal power plant workers].

PubMed

Wu, Hui; Yu, Shan-fa; Zhou, Wen-hui; Gu, Gui-zhen

2012-07-01

This study aimed to investigate the epidemiological characteristics and correlated factors of daily hassles among thermal power plant workers. A mass screening of daily hassles and correlated factors was conducted on 498 workers from a thermal power plant in Zhengzhou in July, 2008. The questionnaires included Daily Hassles Questionnaires, Work Roles Questionnaires, Job Content Questionnaires (Chinese version), Effort-Reward Imbalance (Chinese version), Work Locus of Control Scale and Type A Behavior Scale, with content covering demographic characters and occupational stress correlated factors among subjects. The daily hassles was divided into lower level and higher level according to scores, and the epidemiological characteristics and correlated factors of daily hassles were analyzed. A total of 446 qualified questionnaires were obtained, effective response rate was 89.6% (446/498). For respondents, the age was (36.96 ± 6.49) years old, working length of the current job was (12.05 ± 7.54) years, the daily hassles scores was (9.01 ± 2.50), and the prevalence rate of the higher level of daily hassles was 34.1% (152/446). The multiple non-conditional logistic regression analysis showed 5-14 years' working length of current job (OR = 0.451, 95%CI: 0.225 - 0.904), average income > 3000 yuan(OR = 0.372, 95%CI: 0.202 - 0.684), reward (OR = 0.557, 95%CI: 0.325 - 0.954) and coping strategy (OR = 0.552, 95%CI: 0.330 - 0.925) were negatively correlated with daily hassles, and shift-work (OR = 1.887, 95%CI: 1.108 - 3.215), effort (OR = 2.053, 95%CI: 1.198 - 3.519), psychological demand (OR = 1.797, 95%CI: 1.049 - 3.078), negative affectivity (OR = 3.421, 95%CI: 2.065 - 5.668) were positively correlated with daily hassles. The prevalence rate of the higher level of daily hassles was considerable high for thermal power plant workers. Its negative correlated factors included 5 - 14 years' working length of the current job, average income > 3000 yuan, reward and coping

Time Correlations of Lightning Flash Sequences in Thunderstorms Revealed by Fractal Analysis

NASA Astrophysics Data System (ADS)

Gou, Xueqiang; Chen, Mingli; Zhang, Guangshu

2018-01-01

By using the data of lightning detection and ranging system at the Kennedy Space Center, the temporal fractal and correlation of interevent time series of lightning flash sequences in thunderstorms have been investigated with Allan factor (AF), Fano factor (FF), and detrended fluctuation analysis (DFA) methods. AF, FF, and DFA methods are powerful tools to detect the time-scaling structures and correlations in point processes. Totally 40 thunderstorms with distinguishing features of a single-cell storm and apparent increase and decrease in the total flash rate were selected for the analysis. It is found that the time-scaling exponents for AF (αAF) and FF (αFF) analyses are 1.62 and 0.95 in average, respectively, indicating a strong time correlation of the lightning flash sequences. DFA analysis shows that there is a crossover phenomenon—a crossover timescale (τc) ranging from 54 to 195 s with an average of 114 s. The occurrence of a lightning flash in a thunderstorm behaves randomly at timescales <τc but shows strong time correlation at scales >τc. Physically, these may imply that the establishment of an extensive strong electric field necessary for the occurrence of a lightning flash needs a timescale >τc, which behaves strongly time correlated. But the initiation of a lightning flash within a well-established extensive strong electric field may involve the heterogeneities of the electric field at a timescale <τc, which behave randomly.

[Correlations between climate change-related infectious diseases and meteorological factors in Korea].

PubMed

Kim, Si Heon; Jang, Jae Yeon

2010-09-01

Infectious diseases are known to be affected by climate change. We investigated if the infectious diseases were related to meteorological factors in Korea. Scrub typhus, hemorrhagic fever with renal syndrome (HFRS), leptospirosis, malaria and Vibrio vulnificus sepsis among the National Notifiable Infectious Diseases were selected as the climate change-related infectious diseases. Temperature, relative humidity and precipitation were used as meteorological factors. The study period was from 2001 through 2008. We examined the seasonality of the diseases and those correlations with meteorological factors. We also analyzed the correlations between the incidences of the diseases during the outbreak periods and monthly meteorological factors in the hyper-endemic regions. All of the investigated diseases showed strong seasonality; malaria and V. vulnificus sepsis were prevalent in summer and scrub typhus, HFRS and leptospirosis were prevalent in the autumn. There were significant correlations between the monthly numbers of cases and all the meteorological factors for malaria and V. vulnificus sepsis, but there were no correlation for the other diseases. However, the incidence of scrub typhus in hyper-endemic region during the outbreak period was positively correlated with temperature and humidity during the summer. The incidences of HFRS and leptospirosis had positive correlations with precipitation in November and temperature and humidity in February, respectively. V. vulnificus sepsis showed positive correlations with precipitation in April/May/July. In Korea, the incidences of the infectious diseases were correlated with meteorological factors, and this implies that the incidences could be influenced by climate change.

A new methodology of spatial cross-correlation analysis.

PubMed

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

Orthopositronium decay form factors and two-photon correlations

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

Adkins, Gregory S.; Droz, Daniel R.; Rastawicki, Dominik

2010-04-15

We give results for the orthopositronium decay form factors through one-loop order. We use the form factors to calculate momentum correlations of the final-state photons and , including one-loop corrections, for ensembles of initial orthopositronium atoms having arbitrary polarization.

Correlations between environmental factors and wild bee behavior on alfalfa (Medicago sativa) in northwestern China.

PubMed

Wang, Xiaojuan; Liu, Hongping; Li, Xiaoxia; Song, Yu; Chen, Li; Jin, Liang

2009-10-01

To discover the effect of environmental factors on pollinator visitation to flowering Medicago sativa, several field experiments were designed to examine the diurnal movement patterns of wild bee species in the Hexi Corridor of northwestern China. Our study results showed that Megachile abluta, M. spissula, and Xylocopa valga showed unimodal diurnal foraging behavior, whereas Andrena parvula and Anthophora melanognatha showed bimodal diurnal foraging behavior. Correlation analysis indicated that diurnal foraging activities of pollinators were significantly correlated with environmental factors. Correlations of foraging activities versus environmental factors for M. abluta, M. spissula, and X. valga best fit a linear model, whereas those of A. parvula and A. melanognatha best fit a parallel quadratic model. Results of this study indicated that solitary wild bees such as M. abluta, M. spissula, X. valga, A. parvula, and A. melanognatha are potential alfalfa pollinators in the Hexi Corridor. An understanding of the environmental factors that affect the behaviors of different wild bees foraging in alfalfa are basic to the utilization of solitary wild bees in a practical way for increased, or more consistent, pollination of alfalfa for seed production.

A Canonical Correlation Analysis of AIDS Restriction Genes and Metabolic Pathways Identifies Purine Metabolism as a Key Cooperator.

PubMed

Ye, Hanhui; Yuan, Jinjin; Wang, Zhengwu; Huang, Aiqiong; Liu, Xiaolong; Han, Xiao; Chen, Yahong

2016-01-01

Human immunodeficiency virus causes a severe disease in humans, referred to as immune deficiency syndrome. Studies on the interaction between host genetic factors and the virus have revealed dozens of genes that impact diverse processes in the AIDS disease. To resolve more genetic factors related to AIDS, a canonical correlation analysis was used to determine the correlation between AIDS restriction and metabolic pathway gene expression. The results show that HIV-1 postentry cellular viral cofactors from AIDS restriction genes are coexpressed in human transcriptome microarray datasets. Further, the purine metabolism pathway comprises novel host factors that are coexpressed with AIDS restriction genes. Using a canonical correlation analysis for expression is a reliable approach to exploring the mechanism underlying AIDS.

A New Methodology of Spatial Cross-Correlation Analysis

PubMed Central

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

Correlation between Self-Citation and Impact Factor in Iranian English Medical Journals in WoS and ISC: A Comparative Approach.

PubMed

Ghazi Mirsaeid, Seyed Javad; Motamedi, Nadia; Ramezan Ghorbani, Nahid

2015-09-01

In this study, the impact of self-citation (Journal and Author) on impact factor of Iranian English Medical journals in two international citation databases, Web of Science (WoS) and Islamic world science citation center (ISC), were compared by citation analysis. Twelve journals in WoS and 26 journals in ISC databases indexed between the years (2006-2009) were selected and compared. For comparison of self-citation rate in two databases, we used Wilcoxon and Mann-whitney tests. We used Pearson test for correlation of self-citation and IF in WoS, and the Spearman's correlation coefficient for the ISC database. Covariance analysis was used for comparison of two correlation tests. P. value was 0.05 in all of tests. There was no significant difference between self-citation rates in two databases (P>0.05). Findings also showed no significant difference between the correlation of Journal self-citation and impact factor in two databases (P=0.526) however, there was significant difference between the author's self-citation and impact factor in these databases (P<0.001). The impact of Author's self-citation in the Impact Factor of WoS was higher than the ISC.

Systematic correlation of environmental exposure and physiological and self-reported behaviour factors with leukocyte telomere length.

PubMed

Patel, Chirag J; Manrai, Arjun K; Corona, Erik; Kohane, Isaac S

2017-02-01

It is hypothesized that environmental exposures and behaviour influence telomere length, an indicator of cellular ageing. We systematically associated 461 indicators of environmental exposures, physiology and self-reported behaviour with telomere length in data from the US National Health and Nutrition Examination Survey (NHANES) in 1999-2002. Further, we tested whether factors identified in the NHANES participants are also correlated with gene expression of telomere length modifying genes. We correlated 461 environmental exposures, behaviours and clinical variables with telomere length, using survey-weighted linear regression, adjusting for sex, age, age squared, race/ethnicity, poverty level, education and born outside the USA, and estimated the false discovery rate to adjust for multiple hypotheses. We conducted a secondary analysis to investigate the correlation between identified environmental variables and gene expression levels of telomere-associated genes in publicly available gene expression samples. After correlating 461 variables with telomere length, we found 22 variables significantly associated with telomere length after adjustment for multiple hypotheses. Of these varaibales, 14 were associated with longer telomeres, including biomarkers of polychlorinated biphenyls([PCBs; 0.1 to 0.2 standard deviation (SD) increase for 1 SD increase in PCB level, P  < 0.002] and a form of vitamin A, retinyl stearate. Eight variables associated with shorter telomeres, including biomarkers of cadmium, C-reactive protein and lack of physical activity. We could not conclude that PCBs are correlated with gene expression of telomere-associated genes. Both environmental exposures and chronic disease-related risk factors may play a role in telomere length. Our secondary analysis found no evidence of association between PCBs/smoking and gene expression of telomere-associated genes. All correlations between exposures, behaviours and clinical factors and changes in

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data.

PubMed

Ying, Gui-Shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-04-01

To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field in the elderly. When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI -0.03 to 0.32D, p = 0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, p = 0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller p-values, while analysis of the worse eye provided larger p-values than mixed effects models and marginal models. In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision.

Stereochemical control factors in the Hantzsch thiazole synthesis: a Hammett substitution correlation analysis.

PubMed

Qiao, Q; So, S S; Goodnow, R A

2001-11-15

[reaction--see text] It is possible to correlate the distribution of stereochemical products produced during a Hantzsch thiazole synthesis according to the Hammett free-energy equation. This analysis confirms the presumed control of the rate of epimerization during thiazole formation due to stabilization of a cationic transition state intermediate during dehydration of the thiazoline ring system. In the chemical system under study, the stereochemical outcome of the reaction also appears to occur according to a kinetically controlled protonation of a thiazoline tautomer.

Inflammatory Markers and Plasma Lipids in HIV Patients: A Correlation Analysis Study

PubMed Central

Muswe, Rudo; Oktedalen, Olav; Zhou, Danai T.; Zinyando, Enita; Shawarira-Bote, Sandra; Stray-Pedersen, Babill; Siziba, Atipa; Gomo, Zvenyika A.R.

2017-01-01

Background: Recent evidence suggests that HIV infection, even with treatment, increases the risk of coronary heart disease (CHD) and that both chronic inflammation and traditional risk factors play key roles in HIV-associated CHD. Subjects and Methods: Patients (N=152), attending Harare HIV clinic, 26% of them male and 82% of them on antiretroviral therapy (ART), were studied. Inflammatory markers comprising of cytokines such as pro-inflammatory tumor necrosis factor-α, (TNF-α), anti-inflammatory interleukin 10, (IL-10) and highly sensitive C reactive protein (hsCRP) together with lipids were assayed using enzyme linked immunosorbent assay (ELISA), immuno-turbidimetric and enzymatic assays, respectively. Correlation analysis of inflammatory markers versus lipid profiles was carried out using bivariate regression analysis. Results: Anti-inflammatory cytokine IL-10 and inflammatory hsCRP levels were elevated when measured in all the HIV positive patients, while TNF-α and lipid levels were within normal ranges. Pro-inflammatory TNF-α was significantly higher in ART-naive patients than ART-experienced patients, whereas the reverse was observed for anti-inflammatory IL-10 and anti-atherogenic HDL-C. Correlation analysis indicated a significant positive linear association between IL-10 and total cholesterol (TC) levels but no other correlations were found. Conclusion: High cytokine ratio (TNF-α/IL-10) indicates higher CHD risk in ART-naive patients compared to the ART-exposed. The CHD risk could be further strengthened by interplay between inflammatory markers and high prevalence of low HDL-C. Lack of correlation between pro-inflammatory markers (hsCRP and TNF-α) with lipid fractions and correlation between anti-inflammatory IL-10 with artherogenic TC were unexpected findings, necessitating further studies in future. PMID:29387269

Correlates of Unwanted Births in Bangladesh: A Study through Path Analysis.

PubMed

Roy, Tapan Kumar; Singh, Brijesh P

2016-01-01

Unwanted birth is an important public health concern due to its negative association with adverse outcomes of mothers and children as well as socioeconomic development of a country. Although a number of studies have been investigated the determinants of unwanted births through logistic regression analysis, an extensive assessment using path model is lacking. In the current study, we applied path analysis to know the important covariates for unwanted births in Bangladesh. The study used data extracted from Bangladesh Demographic and Health Survey (BDHS) 2011. It considered sub-sample consisted of 7,972 women who had given most recent births five years preceding the date of interview or who were currently pregnant at survey time. Correlation analysis was used to find out the significant association with unwanted births. This study provided the factors affecting unwanted births in Bangladesh. The path model was used to determine the direct, indirect and total effects of socio-demographic factors on unwanted births. The result exhibited that more than one-tenth of the recent births were unwanted in Bangladesh. The differentials of unwanted births were women's age, education, age at marriage, religion, socioeconomic status, exposure of mass-media and use of family planning. In correlation analysis, it showed that unwanted births were positively correlated with women age and place of residence and these relationships were significant. On the contrary, unwanted births were inversely significantly correlated with education and social status. The total effects of endogenous variables such as women age, place of residence and use of family planning methods had favorable effect on unwanted births. Policymakers and program planners need to design programs and services carefully to reduce unwanted births in Bangladesh, especially, service should focus on helping those groups of women who were identified in the analysis as being at increased risks of unwanted births- older women

FDG-PET/CT and diffusion-weighted imaging for resected lung cancer: correlation of maximum standardized uptake value and apparent diffusion coefficient value with prognostic factors.

PubMed

Usuda, Katsuo; Funasaki, Aika; Sekimura, Atsushi; Motono, Nozomu; Matoba, Munetaka; Doai, Mariko; Yamada, Sohsuke; Ueda, Yoshimichi; Uramoto, Hidetaka

2018-04-09

Diffusion-weighted magnetic resonance imaging (DWI) is useful for detecting malignant tumors and the assessment of lymph nodes, as FDG-PET/CT is. But it is not clear how DWI influences the prognosis of lung cancer patients. The focus of this study is to evaluate the correlations between maximum standardized uptake value (SUVmax) of FDG-PET/CT and apparent diffusion coefficient (ADC) value of DWI with known prognostic factors in resected lung cancer. A total of 227 patients with resected lung cancers were enrolled in this study. FEG-PET/CT and DWI were performed in each patient before surgery. There were 168 patients with adenocarcinoma, 44 patients with squamous cell carcinoma, and 15 patients with other cell types. SUVmax was a factor that was correlated to T factor, N factor, or cell differentiation. ADC of lung cancer was a factor that was not correlated to T factor, or N factor. There was a significantly weak inverse relationship between SUVmax and ADC (Correlation coefficient r = - 0.227). In analysis of survival, there were significant differences between the categories of sex, age, pT factor, pN factor, cell differentiation, cell type, and SUVmax. Univariate analysis revealed that SUVmax, pN factor, age, cell differentiation, cell type, sex, and pT factor were significant factors. Multivariate analysis revealed that SUVmax and pN factor were independent significant prognostic factors. SUVmax was a significant prognostic factor that is correlated to T factor, N factor, or cell differentiation, but ADC was not. SUVmax may be more useful for predicting the prognosis of lung cancer than ADC values.

A new approach for SSVEP detection using PARAFAC and canonical correlation analysis.

PubMed

Tello, Richard; Pouryazdian, Saeed; Ferreira, Andre; Beheshti, Soosan; Krishnan, Sridhar; Bastos, Teodiano

2015-01-01

This paper presents a new way for automatic detection of SSVEPs through correlation analysis between tensor models. 3-way EEG tensor of channel × frequency × time is decomposed into constituting factor matrices using PARAFAC model. PARAFAC analysis of EEG tensor enables us to decompose multichannel EEG into constituting temporal, spectral and spatial signatures. SSVEPs characterized with localized spectral and spatial signatures are then detected exploiting a correlation analysis between extracted signatures of the EEG tensor and the corresponding simulated signatures of all target SSVEP signals. The SSVEP that has the highest correlation is selected as the intended target. Two flickers blinking at 8 and 13 Hz were used as visual stimuli and the detection was performed based on data packets of 1 second without overlapping. Five subjects participated in the experiments and the highest classification rate of 83.34% was achieved, leading to the Information Transfer Rate (ITR) of 21.01 bits/min.

Rotation Criteria and Hypothesis Testing for Exploratory Factor Analysis: Implications for Factor Pattern Loadings and Interfactor Correlations

ERIC Educational Resources Information Center

Schmitt, Thomas A.; Sass, Daniel A.

2011-01-01

Exploratory factor analysis (EFA) has long been used in the social sciences to depict the relationships between variables/items and latent traits. Researchers face many choices when using EFA, including the choice of rotation criterion, which can be difficult given that few research articles have discussed and/or demonstrated their differences.…

Higher HOMA-IR index and correlated factors of insulin resistance in patients with IgA nephropathy.

PubMed

Yang, Yue; Wei, Ri-Bao; Wang, Yuan-da; Zhang, Xue-Guang; Rong, Na; Tang, Li; Chen, Xiang-Mei

2012-11-01

To investigate the index of homeostasis model of insulin resistance (HOMA-IR) in IgA nephropathy (IgAN) patients, and to explore the possible correlated factors contributing to insulin resistance (IR) within these patients. There were 255 IgAN patients and 45 membranous nephropathy (MN) patients in our database. We identified 89 IgAN subjects and 21 MN subjects without diabetes and undergoing glucocorticoid therapy for at least 6 months. Data regarding physical examination, blood chemistry and renal pathology were collected from 89 IgAN subjects and 21 MN subjects. Then 62 IgAN patients and 19 MN patients with chronic kidney disease (CKD) Stage 1 - 2 were selected for the comparison of HOMA-IR index, 89 IgAN patients were selected for multiple regression analysis to test for correlated factors of HOMA-IR index with IgAN patients. Comparison between IgAN and MN show that HOMA-IR index was significantly higher in IgAN patients with CKD Stage 1 - 2. After logarithmic transformation with urine protein (UPr), Ln(UPr) (b = 0.186, p = 0.008), eGFR (b = -0.005, p = 0.014), > 50% of glomeruli with mesangial hypercellularity (b = 0.285, p = 0.027) and body mass index (BMI) (b = 0.039, p = 0.008) were correlated factors of HOMA-IR index in the multiple regression analysis. IgAN patients had higher HOMA-IR index compared with MN in the stages of CKD 1 - 2. For IgAN patients, more UPr, lower eGFR, > 50% of glomeruli with mesangial hypercellularity and higher BMI were correlated with IR.

Biological risk factors for suicidal behaviors: a meta-analysis

PubMed Central

Chang, B P; Franklin, J C; Ribeiro, J D; Fox, K R; Bentley, K H; Kleiman, E M; Nock, M K

2016-01-01

Prior studies have proposed a wide range of potential biological risk factors for future suicidal behaviors. Although strong evidence exists for biological correlates of suicidal behaviors, it remains unclear if these correlates are also risk factors for suicidal behaviors. We performed a meta-analysis to integrate the existing literature on biological risk factors for suicidal behaviors and to determine their statistical significance. We conducted a systematic search of PubMed, PsycInfo and Google Scholar for studies that used a biological factor to predict either suicide attempt or death by suicide. Inclusion criteria included studies with at least one longitudinal analysis using a biological factor to predict either of these outcomes in any population through 2015. From an initial screen of 2541 studies we identified 94 cases. Random effects models were used for both meta-analyses and meta-regression. The combined effect of biological factors produced statistically significant but relatively weak prediction of suicide attempts (weighted mean odds ratio (wOR)=1.41; CI: 1.09–1.81) and suicide death (wOR=1.28; CI: 1.13–1.45). After accounting for publication bias, prediction was nonsignificant for both suicide attempts and suicide death. Only two factors remained significant after accounting for publication bias—cytokines (wOR=2.87; CI: 1.40–5.93) and low levels of fish oil nutrients (wOR=1.09; CI: 1.01–1.19). Our meta-analysis revealed that currently known biological factors are weak predictors of future suicidal behaviors. This conclusion should be interpreted within the context of the limitations of the existing literature, including long follow-up intervals and a lack of tests of interactions with other risk factors. Future studies addressing these limitations may more effectively test for potential biological risk factors. PMID:27622931

Tutorial on Biostatistics: Linear Regression Analysis of Continuous Correlated Eye Data

PubMed Central

Ying, Gui-shuang; Maguire, Maureen G; Glynn, Robert; Rosner, Bernard

2017-01-01

Purpose To describe and demonstrate appropriate linear regression methods for analyzing correlated continuous eye data. Methods We describe several approaches to regression analysis involving both eyes, including mixed effects and marginal models under various covariance structures to account for inter-eye correlation. We demonstrate, with SAS statistical software, applications in a study comparing baseline refractive error between one eye with choroidal neovascularization (CNV) and the unaffected fellow eye, and in a study determining factors associated with visual field data in the elderly. Results When refractive error from both eyes were analyzed with standard linear regression without accounting for inter-eye correlation (adjusting for demographic and ocular covariates), the difference between eyes with CNV and fellow eyes was 0.15 diopters (D; 95% confidence interval, CI −0.03 to 0.32D, P=0.10). Using a mixed effects model or a marginal model, the estimated difference was the same but with narrower 95% CI (0.01 to 0.28D, P=0.03). Standard regression for visual field data from both eyes provided biased estimates of standard error (generally underestimated) and smaller P-values, while analysis of the worse eye provided larger P-values than mixed effects models and marginal models. Conclusion In research involving both eyes, ignoring inter-eye correlation can lead to invalid inferences. Analysis using only right or left eyes is valid, but decreases power. Worse-eye analysis can provide less power and biased estimates of effect. Mixed effects or marginal models using the eye as the unit of analysis should be used to appropriately account for inter-eye correlation and maximize power and precision. PMID:28102741

Correlation between Self-Citation and Impact Factor in Iranian English Medical Journals in WoS and ISC: A Comparative Approach

PubMed Central

GHAZI MIRSAEID, Seyed Javad; MOTAMEDI, Nadia; RAMEZAN GHORBANI, Nahid

2015-01-01

Background: In this study, the impact of self-citation (Journal and Author) on impact factor of Iranian English Medical journals in two international citation databases, Web of Science (WoS) and Islamic world science citation center (ISC), were compared by citation analysis. Methods: Twelve journals in WoS and 26 journals in ISC databases indexed between the years (2006–2009) were selected and compared. For comparison of self-citation rate in two databases, we used Wilcoxon and Mann-whitney tests. We used Pearson test for correlation of self-citation and IF in WoS, and the Spearman’s correlation coefficient for the ISC database. Covariance analysis was used for comparison of two correlation tests. P. value was 0.05 in all of tests. Results: There was no significant difference between self-citation rates in two databases (P>0.05). Findings also showed no significant difference between the correlation of Journal self-citation and impact factor in two databases (P=0.526) however, there was significant difference between the author’s self-citation and impact factor in these databases (P<0.001). Conclusion: The impact of Author’s self-citation in the Impact Factor of WoS was higher than the ISC. PMID:26587498

Quantitative analysis of titanium-induced artifacts and correlated factors during micro-CT scanning.

PubMed

Li, Jun Yuan; Pow, Edmond Ho Nang; Zheng, Li Wu; Ma, Li; Kwong, Dora Lai Wan; Cheung, Lim Kwong

2014-04-01

To investigate the impact of cover screw, resin embedment, and implant angulation on artifact of microcomputed tomography (micro-CT) scanning for implant. A total of twelve implants were randomly divided into 4 groups: (i) implant only; (ii) implant with cover screw; (iii) implant with resin embedment; and (iv) implants with cover screw and resin embedment. Implants angulation at 0°, 45°, and 90° were scanned by micro-CT. Images were assessed, and the ratio of artifact volume to total volume (AV/TV) was calculated. A multiple regression analysis in stepwise model was used to determine the significance of different factors. One-way ANOVA was performed to identify which combination of factors could minimize the artifact. In the regression analysis, implant angulation was identified as the best predictor for artifact among the factors (P < 0.001). Resin embedment also had significant effect on artifact volume (P = 0.028), while cover screw had not (P > 0.05). Non-embedded implants with the axis parallel to X-ray source of micro-CT produced minimal artifact. Implant angulation and resin embedment affected the artifact volume of micro-CT scanning for implant, while cover screw did not. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Increased and correlated expression of connective tissue growth factor and transforming growth factor beta 1 in surgically removed periodontal tissues with chronic periodontitis.

PubMed

Mize, T W; Sundararaj, K P; Leite, R S; Huang, Y

2015-06-01

Both gingival tissue destruction and regeneration are associated with chronic periodontitis, although the former overwhelms the latter. Studies have shown that transforming growth factor beta 1 (TGF-β1), a growth factor largely involved in tissue regeneration and remodeling, is upregulated in chronic periodontitis. However, the gingival expression of connective tissue growth factor (CTGF or CCN2), a TGF-β1-upregulated gene, in patients with periodontitis remains undetermined. Although both CTGF/CCN2 and TGF-b1 increase the production of extracellular matrix, they have many different biological functions. Therefore, it is important to delineate the impact of periodontitis on gingival CTGF/CCN2 expression. Periodontal tissue specimens were collected from seven individuals without periodontitis (group 1) and from 14 with periodontitis (group 2). The expression of CTGF and TGFβ1 mRNAs were quantified using real-time PCR. Analysis using the nonparametric Mann-Whitney U-test showed that the levels of expression of both CTGF/CCN2 and TGFβ1 mRNAs were significantly increased in individuals with periodontitis compared with individuals without periodontitis. Furthermore, analysis using a nonparametric correlation (Spearman r) test showed a positive correlation between TGFβ1 and CTGF/CCN2 mRNAs. The gingival expression levels of CTGF/CCN2 and TGFβ1 mRNAs in individuals with periodontitis are upregulated and correlated. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Auto-correlation of journal impact factor for consensus research reporting statements: a cohort study.

PubMed

Shanahan, Daniel R

2016-01-01

Background. The Journal Citation Reports journal impact factors (JIFs) are widely used to rank and evaluate journals, standing as a proxy for the relative importance of a journal within its field. However, numerous criticisms have been made of use of a JIF to evaluate importance. This problem is exacerbated when the use of JIFs is extended to evaluate not only the journals, but the papers therein. The purpose of this study was therefore to investigate the relationship between the number of citations and journal IF for identical articles published simultaneously in multiple journals. Methods. Eligible articles were consensus research reporting statements listed on the EQUATOR Network website that were published simultaneously in three or more journals. The correlation between the citation count for each article and the median journal JIF over the published period, and between the citation count and number of article accesses was calculated for each reporting statement. Results. Nine research reporting statements were included in this analysis, representing 85 articles published across 58 journals in biomedicine. The number of citations was strongly correlated to the JIF for six of the nine reporting guidelines, with moderate correlation shown for the remaining three guidelines (median r = 0.66, 95% CI [0.45-0.90]). There was also a strong positive correlation between the number of citations and the number of article accesses (median r = 0.71, 95% CI [0.5-0.8]), although the number of data points for this analysis were limited. When adjusted for the individual reporting guidelines, each logarithm unit of JIF predicted a median increase of 0.8 logarithm units of citation counts (95% CI [-0.4-5.2]), and each logarithm unit of article accesses predicted a median increase of 0.1 logarithm units of citation counts (95% CI [-0.9-1.4]). This model explained 26% of the variance in citations (median adjusted r (2) = 0.26, range 0.18-1.0). Conclusion. The impact factor of the

Factors That Attenuate the Correlation Coefficient and Its Analogs.

ERIC Educational Resources Information Center

Dolenz, Beverly

The correlation coefficient is an integral part of many other statistical techniques (analysis of variance, t-tests, etc.), since all analytic methods are actually correlational (G. V. Glass and K. D. Hopkins, 1984). The correlation coefficient is a statistical summary that represents the degree and direction of relationship between two variables.…

A Comparison of Distribution Free and Non-Distribution Free Factor Analysis Methods

ERIC Educational Resources Information Center

Ritter, Nicola L.

2012-01-01

Many researchers recognize that factor analysis can be conducted on both correlation matrices and variance-covariance matrices. Although most researchers extract factors from non-distribution free or parametric methods, researchers can also extract factors from distribution free or non-parametric methods. The nature of the data dictates the method…

The Manifest Association Structure of the Single-Factor Model: Insights from Partial Correlations

ERIC Educational Resources Information Center

Salgueiro, Maria de Fatima; Smith, Peter W. F.; McDonald, John W.

2008-01-01

The association structure between manifest variables arising from the single-factor model is investigated using partial correlations. The additional insights to the practitioner provided by partial correlations for detecting a single-factor model are discussed. The parameter space for the partial correlations is presented, as are the patterns of…

The factors that have correlation with student behavior to dispose liquid waste

NASA Astrophysics Data System (ADS)

Kusmawaningtyas, Rieneke; Darmajanti, Linda; Soesilo, Tri Edhi Budhi

2017-03-01

Students majoring in chemistry could produce toxic liquid waste in their laboratory practices. They are not allowed to dispose of hazardous laboratory liquid into the environment. The formulation of problem in this study is that not all students have good behavior to dispose liquid waste properly according to their type and chemical properties while it is expected that all students have good behavior to dispose liquid waste with the type and chemical properties in container vessel, even though all students are expected to have behavior to dispose waste in the container vessel with the support of the predisposing factors, enabling factors, and driving factors. The aim of this study is to analyze the type and chemical properties of liquid waste and the relationship between three factors forming behavior with student behavior. The relationship between three factors forming behavior with student behavior was analyzed by correlative analysis. Type and chemical properties known through observation and qualitative analysis. The results of this research is found that enabling factors and driving behavior have a weak relation with student behavior. Nevertheless, predisposing factors has no relation with student behavior. The result of analysis of waste laboratory are known that laboratory liquid waste contains Cu, Fe, and methylene blue which potentially pollute the environment. The findings show that although generally the laboratory use chemicals in small quantities, but the total quantity of laboratory liquid waste produced from all laboratories in some regions must be considered. Moreover, the impact of the big quantity of liquid waste to environment must be taken into account. Thus, it is recommended that students should raise awareness of the risks associated with laboratory liquid waste and, we should provide proper management for a laboratory and policy makers.

Factor analysis of the Hamilton Depression Rating Scale in Parkinson's disease.

PubMed

Broen, M P G; Moonen, A J H; Kuijf, M L; Dujardin, K; Marsh, L; Richard, I H; Starkstein, S E; Martinez-Martin, P; Leentjens, A F G

2015-02-01

Several studies have validated the Hamilton Depression Rating Scale (HAMD) in patients with Parkinson's disease (PD), and reported adequate reliability and construct validity. However, the factorial validity of the HAMD has not yet been investigated. The aim of our analysis was to explore the factor structure of the HAMD in a large sample of PD patients. A principal component analysis of the 17-item HAMD was performed on data of 341 PD patients, available from a previous cross sectional study on anxiety. An eigenvalue ≥1 was used to determine the number of factors. Factor loadings ≥0.4 in combination with oblique rotations were used to identify which variables made up the factors. Kaiser-Meyer-Olkin measure (KMO), Cronbach's alpha, Bartlett's test, communality, percentage of non-redundant residuals and the component correlation matrix were computed to assess factor validity. KMO verified the sample's adequacy for factor analysis and Cronbach's alpha indicated a good internal consistency of the total scale. Six factors had eigenvalues ≥1 and together explained 59.19% of the variance. The number of items per factor varied from 1 to 6. Inter-item correlations within each component were low. There was a high percentage of non-redundant residuals and low communality. This analysis demonstrates that the factorial validity of the HAMD in PD is unsatisfactory. This implies that the scale is not appropriate for studying specific symptom domains of depression based on factorial structure in a PD population. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysis of the Factors Affecting the Interval between Blood Donations Using Log-Normal Hazard Model with Gamma Correlated Frailties.

PubMed

Tavakol, Najmeh; Kheiri, Soleiman; Sedehi, Morteza

2016-01-01

Time to donating blood plays a major role in a regular donor to becoming continues one. The aim of this study was to determine the effective factors on the interval between the blood donations. In a longitudinal study in 2008, 864 samples of first-time donors in Shahrekord Blood Transfusion Center,  capital city of Chaharmahal and Bakhtiari Province, Iran were selected by a systematic sampling and were followed up for five years. Among these samples, a subset of 424 donors who had at least two successful blood donations were chosen for this study and the time intervals between their donations were measured as response variable. Sex, body weight, age, marital status, education, stay and job were recorded as independent variables. Data analysis was performed based on log-normal hazard model with gamma correlated frailty. In this model, the frailties are sum of two independent components assumed a gamma distribution. The analysis was done via Bayesian approach using Markov Chain Monte Carlo algorithm by OpenBUGS. Convergence was checked via Gelman-Rubin criteria using BOA program in R. Age, job and education were significant on chance to donate blood (P<0.05). The chances of blood donation for the higher-aged donors, clericals, workers, free job, students and educated donors were higher and in return, time intervals between their blood donations were shorter. Due to the significance effect of some variables in the log-normal correlated frailty model, it is necessary to plan educational and cultural program to encourage the people with longer inter-donation intervals to donate more frequently.

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

Exploratory factor analysis of signalment and conformational measurements in Thoroughbred horses with and without recurrent laryngeal neuropathy.

PubMed

McGivney, C L; Gough, K F; McGivney, B A; Farries, G; Hill, E W; Katz, L M

2018-06-23

Conflicting results have been reported for risk factors for recurrent laryngeal neuropathy (RLN) based on resting endoscopic evaluation and comparison of single conformation traits, with many traits correlated to one another. To simplify identification of signalment and conformation traits (i.e. variables) associated with RLN cases and controls diagnosed with exercising overground endoscopy (OGE) using exploratory factor analysis (EFA). Prospective cohort. Pearson's rank correlation was used to establish significance and association between variables collected from n = 188 Thoroughbreds from one stable by observers blinded to OGE results. Exploratory factor analysis was conducted on 9 variables for cases and controls; common elements between variables developed a factor, with variables grouped into 3 factors for cases and controls, respectively. Correlation (loading) between each variable and factor was calculated to rank relationships between variables and cases/controls, with factors retrospectively named based on their underlying correlations with variables. Numerous inter-correlations were present between variables. Most strongly correlated in cases were wither height with body weight (r = 0.70) and ventral neck length (r = 0.68) and in controls body weight with rostral neck circumference (r = 0.58). Wither height (r = 0.61) significantly loaded the top-ranked factor for cases ('height RLN '), explaining 25% of conformational variance. Ventral neck length (r = 0.69) and age (r = 0.57) significantly loaded the second-ranked factor for cases ('neck length RLN '), explaining 16% of conformational variance. Rostral neck circumference (r = 0.86) and body weight (r = 0.6) significantly loaded the top-ranked factor for controls ('body size CON '), explaining 19% of the variance. Wither height (r = 0.84) significantly loaded the second-ranked factor for controls ('height CON '), explaining 13% of the variance. Horses had not reached skeletal maturity. Exploratory

An Exploratory Analysis of Factors Affecting Participation in Air Force Knowledge Now Communities of Practice

DTIC Science & Technology

2004-03-01

reliability coefficients are presented in chapter four in the factor analysis section. Along with Crobach’s Alpha coefficients, the Kaiser - Meyer - Olkin ...the pattern of correlation coefficients > 0.300 in the correlation matrix • Kaiser - Meyer - Olkin Measure of Sampling Adequacy (MSA) > 0.700 • Bartlett’s...exploratory factor analysis. The Kaiser - Meyer - Olkin measure of sampling adequacy yielded a value of .790, and Bartlett’s test of sphericity yielded a

Confirmatory factor analysis of posttraumatic stress symptoms in sexually harassed women.

PubMed

Palmieri, Patrick A; Fitzgerald, Louise F

2005-12-01

Posttraumatic stress disorder (PTSD) factor analytic research to date has not provided a clear consensus on the structure of posttraumatic stress symptoms. Seven hypothesized factor structures were evaluated using confirmatory factor analysis of the Posttraumatic Stress Disorder Checklist, a paper-and-pencil measure of posttraumatic stress symptom severity, in a sample of 1,218 women who experienced a broad range of workplace sexual harassment. The model specifying correlated re-experiencing, effortful avoidance, emotional numbing, and hyperarousal factors provided the best fit to the data. Virtually no support was obtained for the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV; American Psychiatric Association, 1994) three-factor model of re-experiencing, avoidance, and hyperarousal factors. Different patterns of correlations with external variables were found for the avoidance and emotional numbing factors, providing further validation of the supported model.

Replica Analysis for Portfolio Optimization with Single-Factor Model

NASA Astrophysics Data System (ADS)

Shinzato, Takashi

2017-06-01

In this paper, we use replica analysis to investigate the influence of correlation among the return rates of assets on the solution of the portfolio optimization problem. We consider the behavior of an optimal solution for the case where the return rate is described with a single-factor model and compare the findings obtained from our proposed methods with correlated return rates with those obtained with independent return rates. We then analytically assess the increase in the investment risk when correlation is included. Furthermore, we also compare our approach with analytical procedures for minimizing the investment risk from operations research.

On the Genetic and Environmental Correlations between Trait Emotional Intelligence and Vocational Interest Factors.

PubMed

Schermer, Julie Aitken; Petrides, Konstantinos V; Vernon, Philip A

2015-04-01

The phenotypic (observed), genetic, and environmental correlations were examined in a sample of adult twins between the four factors and global score of the trait emotional intelligence questionnaire (TEIQue) and the seven vocational interest factors of the Jackson Career Explorer (JCE). Multiple significant correlations were found involving the work style vocational interest factor (consisting of job security, stamina, accountability, planfulness, and interpersonal confidence) and the social vocational interest factor (which included interests in the social sciences, personal services, teaching, social services, and elementary education), both of which correlated significantly with all of the TEIQue variables (well-being, self-control, emotionality, sociability, and global trait EI). Following bivariate genetic analyses, most of the significant phenotypic correlations were found to also have significant genetic correlations as well as significant non-shared (unique) environmental correlations.

A meta-analysis of factors affecting trust in human-robot interaction.

PubMed

Hancock, Peter A; Billings, Deborah R; Schaefer, Kristin E; Chen, Jessie Y C; de Visser, Ewart J; Parasuraman, Raja

2011-10-01

We evaluate and quantify the effects of human, robot, and environmental factors on perceived trust in human-robot interaction (HRI). To date, reviews of trust in HRI have been qualitative or descriptive. Our quantitative review provides a fundamental empirical foundation to advance both theory and practice. Meta-analytic methods were applied to the available literature on trust and HRI. A total of 29 empirical studies were collected, of which 10 met the selection criteria for correlational analysis and 11 for experimental analysis. These studies provided 69 correlational and 47 experimental effect sizes. The overall correlational effect size for trust was r = +0.26,with an experimental effect size of d = +0.71. The effects of human, robot, and environmental characteristics were examined with an especial evaluation of the robot dimensions of performance and attribute-based factors. The robot performance and attributes were the largest contributors to the development of trust in HRI. Environmental factors played only a moderate role. Factors related to the robot itself, specifically, its performance, had the greatest current association with trust, and environmental factors were moderately associated. There was little evidence for effects of human-related factors. The findings provide quantitative estimates of human, robot, and environmental factors influencing HRI trust. Specifically, the current summary provides effect size estimates that are useful in establishing design and training guidelines with reference to robot-related factors of HRI trust. Furthermore, results indicate that improper trust calibration may be mitigated by the manipulation of robot design. However, many future research needs are identified.

Interuser Interference Analysis for Direct-Sequence Spread-Spectrum Systems Part I: Partial-Period Cross-Correlation

NASA Technical Reports Server (NTRS)

Ni, Jianjun (David)

2012-01-01

This presentation discusses an analysis approach to evaluate the interuser interference for Direct-Sequence Spread-Spectrum (DSSS) Systems for Space Network (SN) Users. Part I of this analysis shows that the correlation property of pseudo noise (PN) sequences is the critical factor which determines the interuser interference performance of the DSSS system. For non-standard DSSS systems in which PN sequence s period is much larger than one data symbol duration, it is the partial-period cross-correlation that determines the system performance. This study reveals through an example that a well-designed PN sequence set (e.g. Gold Sequence, in which the cross-correlation for a whole-period is well controlled) may have non-controlled partial-period cross-correlation which could cause severe interuser interference for a DSSS system. Since the analytical derivation of performance metric (bit error rate or signal-to-noise ratio) based on partial-period cross-correlation is prohibitive, the performance degradation due to partial-period cross-correlation will be evaluated using simulation in Part II of this analysis in the future.

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

PubMed

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

Ground-state factorization and correlations with broken symmetry

NASA Astrophysics Data System (ADS)

Tomasello, B.; Rossini, D.; Hamma, A.; Amico, L.

2011-10-01

We show how the phenomenon of factorization in a quantum many-body system is of collective nature. To this aim we study the quantum discord Q in the one-dimensional XY model in a transverse field. We analyze the behavior of Q at both the critical point and at the non-critical factorizing field. The factorization is found to be governed by an exponential scaling law for Q. We also address the thermal effects fanning out from the anomalies occurring at zero temperature. Close to the quantum phase transition, Q exhibits a finite-temperature crossover with universal scaling behavior, while the factorization phenomenon results in a non-trivial pattern of correlations present at low temperature.

Analysis of Performance Factors for Accounting and Finance Related Business Courses in a Distance Education Environment

ERIC Educational Resources Information Center

Benligiray, Serdar; Onay, Ahmet

2017-01-01

The objective of this study is to explore business courses performance factors with a focus on accounting and finance. Course score interrelations are assumed to represent interpretable constructs of these factors. Factor analysis is proposed to identify the constructs that explain the correlations. Factor analysis results identify three…

Principal-component analysis of two-particle azimuthal correlations in PbPb and pPb collisions at CMS

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

Sirunyan, Albert M; et al.

2017-08-23

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from sqrt(s[NN]) = 2.76 TeV PbPb and sqrt(s[NN]) = 5.02 TeV pPb collisions collected by the CMS experiment at the LHC. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it has been shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on the breakdown ofmore » flow factorization in heavy ion collisions. The first two modes ("leading" and "subleading") of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and pPb collisions as a function of pt over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique has also been applied to multiplicity fluctuations. These also show a subleading mode. The connection of these new results to previous studies of factorization is discussed.« less

Principal-component analysis of two-particle azimuthal correlations in PbPb and p Pb collisions at CMS

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

Sirunyan, A. M.; Tumasyan, A.; Adam, W.

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from √ sNN = 2.76TeV PbPb and √ sNN = 5.02TeV pPb collisions collected by the CMS experiment at the CERN Large Hadron Collider. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it was shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on themore » breakdown of flow factorization in heavy ion collisions. The first two modes (“leading” and “subleading”) of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and pPb collisions as a function of p T over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique was also applied to multiplicity fluctuations. These also show a subleading mode. As a result, the connection of these new results to previous studies of factorization is discussed.« less

Principal-component analysis of two-particle azimuthal correlations in PbPb and p Pb collisions at CMS

NASA Astrophysics Data System (ADS)

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; Rabady, D.; Rad, N.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Spanring, M.; Spitzbart, D.; Strauss, J.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Suarez Gonzalez, J.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Roskas, C.; Salva, S.; Tytgat, M.; Verbeke, W.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Jafari, A.; Komm, M.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Quertenmont, L.; Vidal Marono, M.; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Melo De Almeida, M.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Tomei, T. R. Fernandez Perez; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Misheva, M.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Jiang, C. H.; Leggat, D.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Susa, T.; Ather, M. W.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; Abdelalim, A. A.; Mohammed, Y.; Salama, E.; Dewanjee, R. K.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. Ã.-.; Titov, M.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Lobanov, A.; Martin Blanco, J.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Stahl Leiton, A. G.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Jansová, M.; Le Bihan, A.-C.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Finco, L.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sordini, V.; Vander Donckt, M.; Viret, S.; Toriashvili, T.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Verlage, T.; Albert, A.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Teyssier, D.; Thüer, S.; Flügge, G.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Müller, T.; Nehrkorn, A.; Nowack, A.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bin Anuar, A. A.; Borras, K.; Botta, V.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; Grohsjean, A.; Gunnellini, P.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Lenz, T.; Leonard, J.; Lipka, K.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Roland, B.; Savitskyi, M.; Saxena, P.; Shevchenko, R.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wen, Y.; Wichmann, K.; Wissing, C.; Zenaiev, O.; Bein, S.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hoffmann, M.; Junkes, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Kurz, S.; Lapsien, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Sonneveld, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baur, S.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Freund, B.; Friese, R.; Giffels, M.; Gilbert, A.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Kassel, F.; Kudella, S.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Evangelou, I.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Triantis, F. A.; Csanad, M.; Filipovic, N.; Pasztor, G.; Bencze, G.; Hajdu, C.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Choudhury, S.; Komaragiri, J. R.; Bahinipati, S.; Bhowmik, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Bhawandeep, U.; Chawla, R.; Dhingra, N.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Kumari, P.; Mehta, A.; Mittal, M.; Singh, J. B.; Walia, G.; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A.; Chauhan, S.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Sharma, V.; Bhardwaj, R.; Bhattacharya, R.; Bhattacharya, S.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhattacharya, S.; Chatterjee, S.; Das, P.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Pandey, S.; Rane, A.; Sharma, S.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Errico, F.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Guiducci, L.; Marcellini, S.; Masetti, G.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Chatterjee, K.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Lenzi, P.; Meschini, M.; Paoletti, S.; Russo, L.; Sguazzoni, G.; Strom, D.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Robutti, E.; Tosi, S.; Brianza, L.; Brivio, F.; Ciriolo, V.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malberti, M.; Malvezzi, S.; Manzoni, R. A.; Menasce, D.; Moroni, L.; Paganoni, M.; Pauwels, K.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; Di Guida, S.; Fabozzi, F.; Fienga, F.; Iorio, A. O. M.; Khan, W. A.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Michelotto, M.; Montecassiano, F.; Pantano, D.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zumerle, G.; Braghieri, A.; Fallavollita, F.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Mantovani, G.; Mariani, V.; Menichelli, M.; Saha, A.; Santocchia, A.; Spiga, D.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Borrello, L.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Fedi, G.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; Daci, N.; Del Re, D.; Diemoz, M.; Gelli, S.; Longo, E.; Margaroli, F.; Marzocchi, B.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Biino, C.; Cartiglia, N.; Cenna, F.; Costa, M.; Covarelli, R.; Degano, A.; Demaria, N.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Monteno, M.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, J.; Lee, S.; Lee, S. W.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Lee, A.; Kim, H.; Moon, D. H.; Oh, G.; Brochero Cifuentes, J. A.; Goh, J.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Kim, J. S.; Lee, H.; Lee, K.; Nam, K.; Oh, S. B.; Radburn-Smith, B. C.; Seo, S. h.; Yang, U. K.; Yoo, H. D.; Yu, G. B.; Choi, M.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Ryu, G.; Choi, Y.; Hwang, C.; Lee, J.; Yu, I.; Dudenas, V.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Md Ali, M. A. B.; Mohamad Idris, F.; Wan Abdullah, W. A. T.; Yusli, M. N.; Zolkapli, Z.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Lopez-Fernandez, R.; Mejia Guisao, J.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Oropeza Barrera, C.; Vazquez Valencia, F.; Pedraza, I.; Salazar Ibarguen, H. A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Saddique, A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Pyskir, A.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Calpas, B.; Di Francesco, A.; Faccioli, P.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. 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P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Álvarez Fernández, A.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Cuevas, J.; Erice, C.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Suárez Andrés, I.; Vischia, P.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Chazin Quero, B.; Curras, E.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Martinez Ruiz del Arbol, P.; Matorras, F.; Piedra Gomez, J.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Baillon, P.; Ball, A. 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T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Rossini, M.; Schönenberger, M.; Shchutska, L.; Starodumov, A.; Tavolaro, V. R.; Theofilatos, K.; Vesterbacka Olsson, M. L.; Wallny, R.; Zagozdzinska, A.; Zhu, D. H.; Aarrestad, T. K.; Amsler, C.; Caminada, L.; Canelli, M. F.; De Cosa, A.; Donato, S.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Ngadiuba, J.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Seitz, C.; Zucchetta, A.; Candelise, V.; Doan, T. H.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chao, Y.; Chen, K. F.; Chen, P. H.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Paganis, E.; Psallidas, A.; Tsai, J. f.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Adiguzel, A.; Bakirci, M. N.; Boran, F.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. 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R.; Williams, T.; Baber, M.; Bainbridge, R.; Breeze, S.; Buchmuller, O.; Bundock, A.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Dunne, P.; Elwood, A.; Futyan, D.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Matsushita, T.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Scott, E.; Seez, C.; Shtipliyski, A.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Winterbottom, D.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Pazzini, J.; Piperov, S.; Sagir, S.; Syarif, R.; Yu, D.; Band, R.; Brainerd, C.; Burns, D.; Calderon De La Barca Sanchez, M.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Squires, M.; Stolp, D.; Tos, K.; Tripathi, M.; Wang, Z.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Shrinivas, A.; Si, W.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Hashemi, B.; Holzner, A.; Klein, D.; Kole, G.; Krutelyov, V.; Letts, J.; Macneill, I.; Masciovecchio, M.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Franco Sevilla, M.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Mullin, S. D.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bendavid, J.; Bornheim, A.; Lawhorn, J. M.; Newman, H. B.; Nguyen, T.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhang, Z.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Mudholkar, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. 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M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; Evdokimov, O.; Gerber, C. E.; Hangal, D. A.; Hofman, D. J.; Jung, K.; Kamin, J.; Sandoval Gonzalez, I. D.; Tonjes, M. B.; Trauger, H.; Varelas, N.; Wang, H.; Wu, Z.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Castle, J.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Royon, C.; Sanders, S.; Schmitz, E.; Stringer, R.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Azzolini, V.; Barbieri, R.; Baty, A.; Bi, R.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Kalafut, S.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Alyari, M.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Loukas, N.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Benaglia, A.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Lange, D.; Luo, J.; Marlow, D.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Svyatkovskiy, A.; Tully, C.; Malik, S.; Norberg, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Schulte, J. F.; Sun, J.; Wang, F.; Xie, W.; Cheng, T.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Ciesielski, R.; Goulianos, K.; Mesropian, C.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Sturdy, J.; Zaleski, S.; Buchanan, J.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.; CMS Collaboration

2017-12-01

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from √{sNN}=2.76 TeV PbPb and √{sNN}=5.02 TeV p Pb collisions collected by the CMS experiment at the CERN Large Hadron Collider. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it was shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on the breakdown of flow factorization in heavy ion collisions. The first two modes ("leading" and "subleading") of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and p Pb collisions as a function of pT over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique was also applied to multiplicity fluctuations. These also show a subleading mode. The connection of these new results to previous studies of factorization is discussed.

Principal-component analysis of two-particle azimuthal correlations in PbPb and p Pb collisions at CMS

DOE PAGES

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; ...

2017-12-05

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from √ sNN = 2.76TeV PbPb and √ sNN = 5.02TeV pPb collisions collected by the CMS experiment at the CERN Large Hadron Collider. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it was shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on themore » breakdown of flow factorization in heavy ion collisions. The first two modes (“leading” and “subleading”) of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and pPb collisions as a function of p T over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique was also applied to multiplicity fluctuations. These also show a subleading mode. As a result, the connection of these new results to previous studies of factorization is discussed.« less

B-cell subset alterations and correlated factors in HIV-1 infection.

PubMed

Pensieroso, Simone; Galli, Laura; Nozza, Silvia; Ruffin, Nicolas; Castagna, Antonella; Tambussi, Giuseppe; Hejdeman, Bo; Misciagna, Donatella; Riva, Agostino; Malnati, Mauro; Chiodi, Francesca; Scarlatti, Gabriella

2013-05-15

During HIV-1 infection, the development, phenotype, and functionality of B cells are impaired. Transitional B cells and aberrant B-cell populations arise in blood, whereas a declined percentage of resting memory B cells is detected. Our study aimed at pinpointing the demographic, immunological, and viral factors driving these pathological findings, and the role of antiretroviral therapy in reverting these alterations. B-cell phenotype and correlating factors were evaluated. Variations in B-cell subsets were evaluated by flow cytometry in HIV-1-infected individuals naive to therapy, elite controllers, and patients treated with antiretroviral drugs (virological control or failure). Multivariable analysis was performed to identify variables independently associated with the B-cell alterations. Significant differences were observed among patients' groups in relation to all B-cell subsets. Resting memory B cells were preserved in patients naive to therapy and elite controllers, but reduced in treated patients. Individuals naive to therapy and experiencing multidrug failure, as well as elite controllers, had significantly higher levels of activated memory B cells compared to healthy controls. In the multivariate analysis, plasma viral load and nadir CD4 T cells independently correlated with major B-cell alterations. Coinfection with hepatitis C but not hepatitis B virus also showed an impact on specific B-cell subsets. Successful protracted antiretroviral treatment led to normalization of all B-cell subsets with exception of resting memory B cells. Our results indicate that viremia and nadir CD4 T cells are important prognostic markers of B-cell perturbations and provide evidence that resting memory B-cell depletion during chronic infection is not reverted upon successful antiretroviral therapy.

Common factor analysis versus principal component analysis: choice for symptom cluster research.

PubMed

Kim, Hee-Ju

2008-03-01

The purpose of this paper is to examine differences between two factor analytical methods and their relevance for symptom cluster research: common factor analysis (CFA) versus principal component analysis (PCA). Literature was critically reviewed to elucidate the differences between CFA and PCA. A secondary analysis (N = 84) was utilized to show the actual result differences from the two methods. CFA analyzes only the reliable common variance of data, while PCA analyzes all the variance of data. An underlying hypothetical process or construct is involved in CFA but not in PCA. PCA tends to increase factor loadings especially in a study with a small number of variables and/or low estimated communality. Thus, PCA is not appropriate for examining the structure of data. If the study purpose is to explain correlations among variables and to examine the structure of the data (this is usual for most cases in symptom cluster research), CFA provides a more accurate result. If the purpose of a study is to summarize data with a smaller number of variables, PCA is the choice. PCA can also be used as an initial step in CFA because it provides information regarding the maximum number and nature of factors. In using factor analysis for symptom cluster research, several issues need to be considered, including subjectivity of solution, sample size, symptom selection, and level of measure.

Correlates of early pregnancy serum brain-derived neurotrophic factor in a Peruvian population.

PubMed

Yang, Na; Levey, Elizabeth; Gelaye, Bizu; Zhong, Qiu-Yue; Rondon, Marta B; Sanchez, Sixto E; Williams, Michelle A

2017-12-01

Knowledge about factors that influence serum brain-derived neurotrophic factor (BDNF) concentrations during early pregnancy is lacking. The aim of the study is to examine the correlates of early pregnancy serum BDNF concentrations. A total of 982 women attending prenatal care clinics in Lima, Peru, were recruited in early pregnancy. Pearson's correlation coefficient was calculated to evaluate the relation between BDNF concentrations and continuous covariates. Analysis of variance and generalized linear models were used to compare the unadjusted and adjusted BDNF concentrations according to categorical variables. Multivariable linear regression models were applied to determine the factors that influence early pregnancy serum BDNF concentrations. In bivariate analysis, early pregnancy serum BDNF concentrations were positively associated with maternal age (r = 0.16, P < 0.001) and early pregnancy body mass index (BMI) (r = 0.17, P < 0.001), but inversely correlated with gestational age at sample collection (r = -0.21, P < 0.001) and C-reactive protein (CRP) concentrations (r = -0.07, P < 0.05). In the multivariable linear regression model, maternal age (β = 0.11, P = 0.001), early pregnancy BMI (β = 1.58, P < 0.001), gestational age at blood collection (β = -0.33, P < 0.001), and serum CRP concentrations (β = -0.57, P = 0.002) were significantly associated with early pregnancy serum BDNF concentrations. Participants with moderate antepartum depressive symptoms (Patient Health Questionnaire-9 (PHQ-9) score ≥ 10) had lower serum BDNF concentrations compared with participants with no/mild antepartum depressive symptoms (PHQ-9 score < 10). Maternal age, early pregnancy BMI, gestational age, and the presence of moderate antepartum depressive symptoms were statistically significantly associated with early pregnancy serum BDNF concentrations in low-income Peruvian women. Biological changes of CRP during pregnancy may affect serum

The prevalence, risk factors and clinical correlates of obesity in Chinese patients with schizophrenia.

PubMed

Li, Qiongzhen; Du, Xiangdong; Zhang, Yingyang; Yin, Guangzhong; Zhang, Guangya; Walss-Bass, Consuelo; Quevedo, João; Soares, Jair C; Xia, Haishen; Li, Xiaosi; Zheng, Yingjun; Ning, Yuping; Zhang, Xiang Yang

2017-05-01

Obesity is a common comorbidity in schizophrenia. Few studies have addressed obesity in Chinese schizophrenia patients. The aims of this current study were to evaluate the prevalence, risk factors and clinical correlates of obesity in Chinese patients with schizophrenia. A total of 206 patients were recruited from a hospital in Beijing. Their clinical and anthropometric data together with plasma glucose and lipid parameters were collected. Positive and Negative Syndrome Scale (PANSS) was rated for all patients. Overall, 43 (20.9%) patients were obese and 67 (32.5%) were overweight. The obese patients had significantly higher glucose levels, triglyceride levels than non-obese patients. Females and patients with type 2 diabetes mellitus had increased risk for obesity. Correlation analysis showed that BMI was associated with sex, education levels, negative symptoms, total PANSS score, triglyceride levels and type 2 diabetes mellitus. Further stepwise regression analysis showed that sex, type 2 diabetes, education level, triglyceride and amount of smoking/day were significant predictors for obesity. Our study showed that the prevalence of obesity in Chinese patients with schizophrenia is higher than that in the general population. Some demographic and clinical variables are risk factors for obesity in schizophrenia. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Developing Multidimensional Likert Scales Using Item Factor Analysis: The Case of Four-Point Items

ERIC Educational Resources Information Center

Asún, Rodrigo A.; Rdz-Navarro, Karina; Alvarado, Jesús M.

2016-01-01

This study compares the performance of two approaches in analysing four-point Likert rating scales with a factorial model: the classical factor analysis (FA) and the item factor analysis (IFA). For FA, maximum likelihood and weighted least squares estimations using Pearson correlation matrices among items are compared. For IFA, diagonally weighted…

Factor analysis of some socio-economic and demographic variables for Bangladesh.

PubMed

Islam, S M

1986-01-01

The author carries out an exploratory factor analysis of some socioeconomic and demographic variables for Bangladesh using the classical or common factor approach with the varimax rotation method. The socioeconomic and demographic indicators used in this study include literacy, rate of growth, female employment, economic development, urbanization, population density, childlessness, sex ratio, proportion of women ever married, and fertility. The 18 administrative districts of Bangladesh constitute the unit of analysis. 3 common factors--modernization, fertility, and social progress--are identified in this study to explain the correlations among the set of selected socioeconomic and demographic variables.

[Retrospective analysis of correlative factors between digestive system injury and anticoagulant or antiplatelet-agents].

PubMed

Cui, Ning; Luo, Hesheng

2014-05-27

To explore the correlative factors and clinical characteristics of digestive system injury during the treatment of anticoagulant and (or) antiplatelet-agents. A total of 1 443 hospitalized patients on anticoagulant and (or) antiplatelet-agents from January 2010 to December 2013 at Renmin Hospital of Wuhan University were analyzed retrospectively. Their length of hospital stay was from 5 to 27 days. Most of them were elderly males (n = 880, 61.0%) with an average age of (62 ± 6) years. 1 138 patients (78.9%) were farmers, workers or someone without a specific occupation. During the treatment of anticoagulant/antiplatelet-agents, statistical difference existed (P = 0.01) between positively and negatively previous digestive disease groups for actively newly occurring digestive system injury (16.0% (41/256) vs 15.9% (189/1 187)). After the dosing of anticoagulant and (or) antiplatelet-agents, 57 (66.3%, 57/86) patients were complicated by hemorrhage of digestive tract, taking 62.9% (61/97) of all positive result patients for Helicobacter pylori test. Comparing preventive PPI group with no PPI group, there was no marked statistical differences (P = 2.67) for digestive system complication (including hemorrhage of digestive tract) while receiving anticoagulant and (or) antiplatelet-agents (13.9% (74/533) vs 17.1% (156/910)). During anticoagulant and/or antiplatelet-agent therapy, 185 patients (12.8%) were complicated by peptic ulcer or peptic ulcer with bleeding, 40 patients (2.8%) had erosive gastritis and 5 (0.3%) developed acute gastric mucosal lesions. And 42 of 76 patients complicated by hemorrhage of digestive tract underwent endoscopic hemostasis while 2 patients were operated. Ninety-seven patients (6.7%) died, including 61 (62.9%, 61/97) from hemorrhage of digestive tract. The remainder became cured, improved and discharged. Moreover, no significant statistical differences existed (P = 2.29) among three combination group (aspirin, clopidogrel, warfarin), two

The correlation analysis of tumor necrosis factor-alpha-308G/A polymorphism and venous thromboembolism risk: A meta-analysis.

PubMed

Gao, Quangen; Zhang, Peijin; Wang, Wei; Ma, He; Tong, Yue; Zhang, Jing; Lu, Zhaojun

2016-10-01

Venous thromboembolism is a common complex disorder, being the resultant of gene-gene and gene-environment interactions. Tumor necrosis factor-alpha is a proinflammatory cytokine which has been implicated in venous thromboembolism risk. A promoter 308G/A polymorphism in the tumor necrosis factor-alpha gene has been suggested to modulate the risk for venous thromboembolism. However, the published findings remain inconsistent. In this study, we conducted a meta-analysis of all available data regarding this issue. Eligible studies were identified through search of Pubmed, EBSCO Medline, Web of Science, and China National Knowledge Infrastructure (CNKI, Chinese) databases up to June 2014. Pooled Odd ratios (ORs) with 95% confidence intervals were applied to estimating the strength of the genetic association in the random-effects model or fixed-effects model. A total of 10 studies involving 1999 venous thromboembolism cases and 2166 controls were included in this meta-analysis to evaluate the association between tumor necrosis factor-alpha-308G/A polymorphism and venous thromboembolism risk. Overall, no significantly increased risk venous thromboembolism was observed in all comparison models when all studies were pooled into the meta-analysis. However, in stratified analyses by ethnicity, there was a pronounced association with venous thromboembolism risk among West Asians in three genetic models (A vs. G: OR = 1.82, 95%CI = 1.13-2.94; GA vs. GG: OR = 1.82, 95%CI = 1.08-3.06; AA/GA vs. GG: OR = 1.88, 95%CI = 1.12-3.16). When stratifying by source of controls, no significant result was detected in all genetic models. This meta-analysis demonstrates that tumor necrosis factor-alpha 308G/A polymorphism may contribute to susceptibility to venous thromboembolism among West Asians. Studies are needed to ascertain these findings in larger samples and different racial groups. © The Author(s) 2015.

Correlating Detergent Fiber Analysis and Dietary Fiber Analysis Data for Corn Stover

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

Wolfrum, E. J.; Lorenz, A. J.; deLeon, N.

There exist large amounts of detergent fiber analysis data [neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL)] for many different potential cellulosic ethanol feedstocks, since these techniques are widely used for the analysis of forages. Researchers working in the area of cellulosic ethanol are interested in the structural carbohydrates in a feedstock (principally glucan and xylan), which are typically determined by acid hydrolysis of the structural fraction after multiple extractions of the biomass. These so-called dietary fiber analysis methods are significantly more involved than detergent fiber analysis methods. The purpose of this study was to determinemore » whether it is feasible to correlate detergent fiber analysis values to glucan and xylan content determined by dietary fiber analysis methods for corn stover. In the detergent fiber analysis literature cellulose is often estimated as the difference between ADF and ADL, while hemicellulose is often estimated as the difference between NDF and ADF. Examination of a corn stover dataset containing both detergent fiber analysis data and dietary fiber analysis data predicted using near infrared spectroscopy shows that correlations between structural glucan measured using dietary fiber techniques and cellulose estimated using detergent techniques, and between structural xylan measured using dietary fiber techniques and hemicellulose estimated using detergent techniques are high, but are driven largely by the underlying correlation between total extractives measured by fiber analysis and NDF/ADF. That is, detergent analysis data is correlated to dietary fiber analysis data for structural carbohydrates, but only indirectly; the main correlation is between detergent analysis data and solvent extraction data produced during the dietary fiber analysis procedure.« less

Ligand-Independent Epidermal Growth Factor Receptor Overexpression Correlates with Poor Prognosis in Colorectal Cancer.

PubMed

Yun, Sumi; Kwak, Yoonjin; Nam, Soo Kyung; Seo, An Na; Oh, Heung-Kwon; Kim, Duck-Woo; Kang, Sung-Bum; Lee, Hye Seung

2018-01-17

Molecular treatments targeting epidermal growth factor receptors (EGFRs) are important strategies for advanced colorectal cancer (CRC). However, clinicopathologic implications of EGFRs and EGFR ligand signaling have not been fully evaluated. We evaluated the expression of EGFR ligands and correlation with their receptors, clinicopathologic factors, and patients' survival with CRC. The expression of EGFR ligands, including heparin binding epidermal growth factor like growth factor (HBEGF), transforming growth factor (TGF), betacellulin, and epidermal growth factor (EGF), were evaluated in 331 consecutive CRC samples using mRNA in situ hybridization (ISH). We also evaluated the expression status of EGFR, human epidermal growth factor receptor 2 (HER2), HER3, and HER4 using immunohistochemistry and/or silver ISH. Unlike low incidences of TGF (38.1%), betacellulin (7.9%), and EGF (2.1%), HBEGF expression was noted in 62.2% of CRC samples. However, the expression of each EGFR ligand did not reveal significant correlations with survival. The combined analyses of EGFR ligands and EGFR expression indicated that the ligands‒/EGFR+ group showed a significant association with the worst disease-free survival (DFS, p=0.018) and overall survival (OS, p=0.005). It was also an independent, unfavorable prognostic factor for DFS (p=0.026) and OS (p=0.007). Additionally, HER4 nuclear expression, regardless of ligand expression, was an independent, favorable prognostic factor for DFS (p=0.034) and OS (p=0.049), by multivariate analysis. Ligand-independent EGFR overexpression was suggested to have a significant prognostic impact; thus, the expression status of EGFR ligands, in addition to EGFR, might be necessary for predicting patients' outcome in CRC.

Factor Analysis via Components Analysis

ERIC Educational Resources Information Center

Bentler, Peter M.; de Leeuw, Jan

2011-01-01

When the factor analysis model holds, component loadings are linear combinations of factor loadings, and vice versa. This interrelation permits us to define new optimization criteria and estimation methods for exploratory factor analysis. Although this article is primarily conceptual in nature, an illustrative example and a small simulation show…

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution.

PubMed

Han, Fang; Liu, Han

2017-02-01

Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.

Principal-component analysis of two-particle azimuthal correlations in PbPb and $$p\\text{Pb}$$ collisions at CMS

DOE PAGES

Sirunyan, A.M.; et al.

2017-12-05

For the first time a principle-component analysis is used to separate out different orthogonal modes of the two-particle correlation matrix from heavy ion collisions. The analysis uses data from sNN=2.76TeV PbPb and sNN=5.02TeV pPb collisions collected by the CMS experiment at the CERN Large Hadron Collider. Two-particle azimuthal correlations have been extensively used to study hydrodynamic flow in heavy ion collisions. Recently it was shown that the expected factorization of two-particle results into a product of the constituent single-particle anisotropies is broken. The new information provided by these modes may shed light on the breakdown of flow factorization in heavymore » ion collisions. The first two modes (“leading” and “subleading”) of two-particle correlations are presented for elliptical and triangular anisotropies in PbPb and pPb collisions as a function of pT over a wide range of event activity. The leading mode is found to be essentially equivalent to the anisotropy harmonic previously extracted from two-particle correlation methods. The subleading mode represents a new experimental observable and is shown to account for a large fraction of the factorization breaking recently observed at high transverse momentum. The principle-component analysis technique was also applied to multiplicity fluctuations. These also show a subleading mode. The connection of these new results to previous studies of factorization is discussed.« less

Spinal appearance questionnaire: factor analysis, scoring, reliability, and validity testing.

PubMed

Carreon, Leah Y; Sanders, James O; Polly, David W; Sucato, Daniel J; Parent, Stefan; Roy-Beaudry, Marjolaine; Hopkins, Jeffrey; McClung, Anna; Bratcher, Kelly R; Diamond, Beverly E

2011-08-15

Cross sectional. This study presents the factor analysis of the Spinal Appearance Questionnaire (SAQ) and its psychometric properties. Although the SAQ has been administered to a large sample of patients with adolescent idiopathic scoliosis (AIS) treated surgically, its psychometric properties have not been fully evaluated. This study presents the factor analysis and scoring of the SAQ and evaluates its psychometric properties. The SAQ and the Scoliosis Research Society-22 (SRS-22) were administered to AIS patients who were being observed, braced or scheduled for surgery. Standard demographic data and radiographic measures including Lenke type and curve magnitude were also collected. Of the 1802 patients, 83% were female; with a mean age of 14.8 years and mean initial Cobb angle of 55.8° (range, 0°-123°). From the 32 items of the SAQ, 15 loaded on two factors with consistent and significant correlations across all Lenke types. There is an Appearance (items 1-10) and an Expectations factor (items 12-15). Responses are summed giving a range of 5 to 50 for the Appearance domain and 5 to 20 for the Expectations domain. The Cronbach's α was 0.88 for both domains and Total score with a test-retest reliability of 0.81 for Appearance and 0.91 for Expectations. Correlations with major curve magnitude were higher for the SAQ Appearance and SAQ Total scores compared to correlations between the SRS Appearance and SRS Total scores. The SAQ and SRS-22 Scores were statistically significantly different in patients who were scheduled for surgery compared to those who were observed or braced. The SAQ is a valid measure of self-image in patients with AIS with greater correlation to curve magnitude than SRS Appearance and Total score. It also discriminates between patients who require surgery from those who do not.

Personality Correlates of Midlife Cardiometabolic Risk: The Explanatory Role of Higher-Order Factors of the Five Factor Model

PubMed Central

Dermody, Sarah S.; Wright, Aidan G.C.; Cheong, JeeWon; Miller, Karissa G.; Muldoon, Matthew F.; Flory, Janine D.; Gianaros, Peter J.; Marsland, Anna L.; Manuck, Stephen B.

2015-01-01

Objective Varying associations are reported between Five Factor Model (FFM) personality traits and cardiovascular diseaabolic risk within a hierarchical model of personality that posits higherse risk. Here, we further examine dispositional correlates of cardiomet -order traits of Stability (shared variance of Agreeableness, Conscientiousness, inverse Neuroticism) and Plasticity (Extraversion, Openness), and test hypothesized mediation via biological and behavioral factors. Method In an observational study of 856 community volunteers aged 30–54 years (46% male, 86% Caucasian), latent variable FFM traits (using multiple-informant reports) and aggregated cardiometabolic risk (indicators: insulin resistance, dyslipidemia, blood pressure, adiposity) were estimated using confirmatory factor analysis (CFA). The cardiometabolic factor was regressed on each personality factor or higher-order trait. Cross-sectional indirect effects via systemic inflammation, cardiac autonomic control, and physical activity were tested. Results CFA models confirmed the Stability “meta-trait,” but not Plasticity. Lower Stability was associated with heightened cardiometabolic risk. This association was accounted for by inflammation, autonomic function, and physical activity. Among FFM traits, only Openness was associated with risk over and above Stability and, unlike Stablity, this relationship was unexplained by the intervening variables. Conclusions A Stability meta-trait covaries with midlife cardiometabolic risk, and this association is accounted for by three candidate biological and behavioral factors. PMID:26249259

[Anemia status and correlation factors in rural regions of Hebei province].

PubMed

Wang, Yue-jin; Li, Jian-guo; Xu, Wei-ling; Wang, Xiao-bo; Liu, Yan-li; Jiang, Hong

2008-05-01

To investigate anemia status and correlation infection factors in rural regions of Hebei province and to find out evidence for preventing and controlling anemia. A random-sampling survey was conducted among 3367 houses in Hebei rural areas. The investigation involved economic levels, ages, education levels and occupations of 11,627 questionnaire. The hemoprotein and serum iron were measured. Unconditional logistic regression was performed. The anemia prevalence rate was shown up to 8.4% in rural regions of Hebei province, and in men and women was 5.5% and 11.0%, respectively;mainly in infant (< 2 years old, 27.2%) child bearing age women, the anemia prevalence rate was 11.0%-16.0%. The analysis showed that the main risk factors of anemia were sex and serum iron. The anemia prevalence is highest in infant and child bearing age women;supplying of iron should be an important measure for preventing and controlling anemia.

Factor Rotation and Standard Errors in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Preacher, Kristopher J.

2015-01-01

In this article, we report a surprising phenomenon: Oblique CF-varimax and oblique CF-quartimax rotation produced similar point estimates for rotated factor loadings and factor correlations but different standard error estimates in an empirical example. Influences of factor rotation on asymptotic standard errors are investigated using a numerical…

Thermal form-factor approach to dynamical correlation functions of integrable lattice models

NASA Astrophysics Data System (ADS)

Göhmann, Frank; Karbach, Michael; Klümper, Andreas; Kozlowski, Karol K.; Suzuki, Junji

2017-11-01

We propose a method for calculating dynamical correlation functions at finite temperature in integrable lattice models of Yang-Baxter type. The method is based on an expansion of the correlation functions as a series over matrix elements of a time-dependent quantum transfer matrix rather than the Hamiltonian. In the infinite Trotter-number limit the matrix elements become time independent and turn into the thermal form factors studied previously in the context of static correlation functions. We make this explicit with the example of the XXZ model. We show how the form factors can be summed utilizing certain auxiliary functions solving finite sets of nonlinear integral equations. The case of the XX model is worked out in more detail leading to a novel form-factor series representation of the dynamical transverse two-point function.

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.

Old and New Ideas for Data Screening and Assumption Testing for Exploratory and Confirmatory Factor Analysis

PubMed Central

Flora, David B.; LaBrish, Cathy; Chalmers, R. Philip

2011-01-01

We provide a basic review of the data screening and assumption testing issues relevant to exploratory and confirmatory factor analysis along with practical advice for conducting analyses that are sensitive to these concerns. Historically, factor analysis was developed for explaining the relationships among many continuous test scores, which led to the expression of the common factor model as a multivariate linear regression model with observed, continuous variables serving as dependent variables, and unobserved factors as the independent, explanatory variables. Thus, we begin our paper with a review of the assumptions for the common factor model and data screening issues as they pertain to the factor analysis of continuous observed variables. In particular, we describe how principles from regression diagnostics also apply to factor analysis. Next, because modern applications of factor analysis frequently involve the analysis of the individual items from a single test or questionnaire, an important focus of this paper is the factor analysis of items. Although the traditional linear factor model is well-suited to the analysis of continuously distributed variables, commonly used item types, including Likert-type items, almost always produce dichotomous or ordered categorical variables. We describe how relationships among such items are often not well described by product-moment correlations, which has clear ramifications for the traditional linear factor analysis. An alternative, non-linear factor analysis using polychoric correlations has become more readily available to applied researchers and thus more popular. Consequently, we also review the assumptions and data-screening issues involved in this method. Throughout the paper, we demonstrate these procedures using an historic data set of nine cognitive ability variables. PMID:22403561

Dynamic test/analysis correlation using reduced analytical models

NASA Technical Reports Server (NTRS)

Mcgowan, Paul E.; Angelucci, A. Filippo; Javeed, Mehzad

1992-01-01

Test/analysis correlation is an important aspect of the verification of analysis models which are used to predict on-orbit response characteristics of large space structures. This paper presents results of a study using reduced analysis models for performing dynamic test/analysis correlation. The reduced test-analysis model (TAM) has the same number and orientation of DOF as the test measurements. Two reduction methods, static (Guyan) reduction and the Improved Reduced System (IRS) reduction, are applied to the test/analysis correlation of a laboratory truss structure. Simulated test results and modal test data are used to examine the performance of each method. It is shown that selection of DOF to be retained in the TAM is critical when large structural masses are involved. In addition, the use of modal test results may provide difficulties in TAM accuracy even if a large number of DOF are retained in the TAM.

Correlates of perceived stigma for people living with epilepsy: A meta-analysis.

PubMed

Shi, Ying; Wang, Shouqi; Ying, Jie; Zhang, Meiling; Liu, Pengcheng; Zhang, Huanhuan; Sun, Jiao

2017-05-01

Epilepsy, one of the most common, serious chronic neurological diseases, is accompanied by different levels of perceived stigma that affects people in almost all age groups. This stigma can negatively impact the physical and mental health of people living with epilepsy (PLWE). Good knowledge of perceived stigma for PLWE is important. In this study, we conducted a meta-analysis to identify the correlates of perceived stigma for PLWE. Studies on factors associated with perceived stigma for PLWE, including sociodemographic, psychosocial, and disease-related variables, were searched in PubMed, PsychINFO, EMBASE, and Web of Science. Nineteen variables (k>1) were included in the meta-analysis. For sociodemographic characteristics, findings revealed that the significant weighted mean correlation (R) for "residence" and "poor financial status" were 0.177 and 0.286, respectively. For disease-related characteristics, all variables of significance, including "seizure severity," "seizure frequency," "number of medicines," and "adverse event" (R ranging from 0.190 to 0.362), were positively correlated with perceived stigma. For psychosocial characteristics, "depression" and "anxiety" with R values of 0.414 and 0.369 were significantly associated with perceived stigma. In addition, "social support," "quality of life (QOLIE-31,89)," "knowledge," and "attitude," with R values ranging from -0.444 to -0.200 indicating negative correlation with perceived stigma. The current meta-analysis evaluated the correlates of perceived stigma for PLWE. Results can serve as a basis for policymakers and healthcare professionals for formulating health promotion and prevention strategies. Copyright © 2017 Elsevier Inc. All rights reserved.

Correlational Analysis of Ordinal Data: From Pearson's "r" to Bayesian Polychoric Correlation

ERIC Educational Resources Information Center

Choi, Jaehwa; Peters, Michelle; Mueller, Ralph O.

2010-01-01

Correlational analyses are one of the most popular quantitative methods, yet also one of the mostly frequently misused methods in social and behavioral research, especially when analyzing ordinal data from Likert or other rating scales. Although several correlational analysis options have been developed for ordinal data, there seems to be a lack…

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

PubMed Central

Han, Fang; Liu, Han

2016-01-01

Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson’s sample correlation matrix. Although Pearson’s sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall’s tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall’s tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall’s tau correlation matrix and the latent Pearson’s correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of “effective rank” in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a “sign subgaussian condition” which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition. PMID:28337068

[Wave-type time series variation of the correlation between NDVI and climatic factors].

PubMed

Bi, Xiaoli; Wang, Hui; Ge, Jianping

2005-02-01

Based on the 1992-1996 data of 1 km monthly NDVI and those of the monthly precipitation and mean temperature collected by 400 standard meteorological stations in China, this paper analyzed the temporal and spatial dynamic changes of the correlation between NDVI and climatic factors in different climate districts of this country. The results showed that there was a significant correlation between monthly precipitations and NDVI. The wave-type time series model could simulate well the temporal dynamic changes of the correlation between NDVI and climatic factors, and the simulated results of the correlation between NDVI and precipitation was better than that between NDVI and temperature. The correlation coefficients (R2) were 0.91 and 0.86, respectively for the whole country.

Analysis of quality of life and influencing factors in 197 Chinese patients with port-wine stains

PubMed Central

Wang, Juan; Zhu, Yu-you; Wang, Zhong-ying; Yao, Xiu-hua; Zhang, Lan-fang; Lv, Hong; Zhang, Si-ping; Hu, Bai

2017-01-01

Abstract Port-wine stains (PWS) are congenital capillary malformations, usually occurring on the face, neck, and other exposed parts of the skin, that have serious psychological and social impact on the patient. Most researchers focus on the treatment of PWS, but the quality of life (QoL) of PWS patients is seldom researched. The objective of this study is to evaluate the QoL of patients with PWS on exposed parts and explore the factors influencing the QoL of PWS patients. The QoL of 197 cases with PWS on exposed parts were prospectively studied using the Dermatology Life Quality Index questionnaire (DLQI), and the factors influencing the patients’ QoL were analyzed by single-factor analysis and multiple-factor logistic regression analysis. The reliability and validity of the QoL of PWS patients were then assessed by DLQI. A total of 197 valid questionnaires were collected. The DLQI scores in PWS cases ranged from 2 to 16, with 2 to 5 in 52.29% (103/197), 6 to 10 in 42.13% (83/197), and 11 to 20 in 5.58% (11/197). The main score elements of the DLQI focused on symptoms and feelings, daily activities, and social entertainment. Single-factor analysis and multiple-factor logistic regression analysis showed that the main influencing factors were female sex, skin hypertrophy, and lesion area >30 cm2. The inter-item correlation averaged 47.46% and the Cronbach α was 0.740, indicating high internal consistency. Correlation of the 6 dimensions of the DLQI questionnaires with the total scores showed that the Spearman correlation coefficient r ranged from 0.550 to 0.782 (P < .001), with symptoms and feelings having a correlation coefficient of 0.782 and a high correlation with total scores. This study shows that PWS has mild to moderate influence on the QoL of most patients, mainly on daily activities, social entertainment, and feelings. PMID:29390578

[Correlation between polymorphisms in the coagulation factor VII gene hypervariable region 4 site and the risk of coronary heart disease in population with different ethnic backgrounds: a Meta-analysis].

PubMed

Wang, Li-li; Ma, Bin; Qian, Dun; Pang, Jun; Yao, Ya-li

2013-12-01

To assess the correlation between polymorphisms in the coagulation factor VII (F VII)gene hypervariable region 4 (HVR4)site and risk related to coronary heart disease (CHD)in different ethnic populations, especially the Asian populations. Publications up to April 2013, from CBM, CNKI, Wanfang Database,VIP, PubMed, Cochrane Library and Embase were searched to collect data from case-control studies related to F VII gene HVR4 site and CHD in populations from different ethnicities. Quality of studies was evaluated, available data extracted and both RevMan 5.1 and Stata 11.0 softwares were used for Meta-analysis. Fifteen case-control studies were included, involving 3167 cases with CHD group and 3168 cases in the control group. on this Meta-analysis showed that:a)polymorphism of the F VII gene HVR4 site H7/H6+H5 and CHD, b)H7H7/H6H6 + H7H6 and CHD were both slightly correlated between people with different ethnic backgrounds. However, the H6 allele versus H7+H5 allele and CHD showed different results-a high correlation seen in different ethnic groups. H5 allele versus H6+H7 allele and CHD did not appear significant difference(OR = 1.20, 95%CI:0.76-1.90, P = 0.43). Both F VII gene HVR4 polymorphisms H7 allele and the H7H7 genotype might have served as protective factors for CHD in different ethnic groups, H6 allele might serve as a risk factor for CHD, but H5 allele was likely not to be associated with CHD in different ethnic groups.

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

PubMed

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

Generic expansion of the Jastrow correlation factor in polynomials satisfying symmetry and cusp conditions

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

Lüchow, Arne, E-mail: luechow@rwth-aachen.de; Jülich Aachen Research Alliance; Sturm, Alexander

2015-02-28

Jastrow correlation factors play an important role in quantum Monte Carlo calculations. Together with an orbital based antisymmetric function, they allow the construction of highly accurate correlation wave functions. In this paper, a generic expansion of the Jastrow correlation function in terms of polynomials that satisfy both the electron exchange symmetry constraint and the cusp conditions is presented. In particular, an expansion of the three-body electron-electron-nucleus contribution in terms of cuspless homogeneous symmetric polynomials is proposed. The polynomials can be expressed in fairly arbitrary scaling function allowing a generic implementation of the Jastrow factor. It is demonstrated with a fewmore » examples that the new Jastrow factor achieves 85%–90% of the total correlation energy in a variational quantum Monte Carlo calculation and more than 90% of the diffusion Monte Carlo correlation energy.« less

Correlation between polar values and vector analysis.

PubMed

Naeser, K; Behrens, J K

1997-01-01

To evaluate the possible correlation between polar value and vector analysis assessment of surgically induced astigmatism. Department of Ophthalmology, Aalborg Sygehus Syd, Denmark. The correlation between polar values and vector analysis was evaluated by simple mathematical and optical methods using accepted principles of trigonometry and first-order optics. Vector analysis and polar values report different aspects of surgically induced astigmatism. Vector analysis describes the total astigmatic change, characterized by both astigmatic magnitude and direction, while the polar value method produces a single, reduced figure that reports flattening or steepening in preselected directions, usually the plane of the surgical meridian. There is a simple Pythagorean correlation between vector analysis and two polar values separated by an arch of 45 degrees. The polar value calculated in the surgical meridian indicates the power or the efficacy of the surgical procedure. The polar value calculated in a plane inclined 45 degrees to the surgical meridian indicates the degree of cylinder rotation induced by surgery. These two polar values can be used to obtain other relevant data such as magnitude, direction, and sphere of an induced cylinder. Consistent use of these methods will enable surgeons to control and in many cases reduce preoperative astigmatism.

WGCNA: an R package for weighted correlation network analysis

PubMed Central

Langfelder, Peter; Horvath, Steve

2008-01-01

Background Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. Results The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. Conclusion The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at . PMID:19114008

Sensitivity analysis of a sound absorption model with correlated inputs

NASA Astrophysics Data System (ADS)

Chai, W.; Christen, J.-L.; Zine, A.-M.; Ichchou, M.

2017-04-01

Sound absorption in porous media is a complex phenomenon, which is usually addressed with homogenized models, depending on macroscopic parameters. Since these parameters emerge from the structure at microscopic scale, they may be correlated. This paper deals with sensitivity analysis methods of a sound absorption model with correlated inputs. Specifically, the Johnson-Champoux-Allard model (JCA) is chosen as the objective model with correlation effects generated by a secondary micro-macro semi-empirical model. To deal with this case, a relatively new sensitivity analysis method Fourier Amplitude Sensitivity Test with Correlation design (FASTC), based on Iman's transform, is taken into application. This method requires a priori information such as variables' marginal distribution functions and their correlation matrix. The results are compared to the Correlation Ratio Method (CRM) for reference and validation. The distribution of the macroscopic variables arising from the microstructure, as well as their correlation matrix are studied. Finally the results of tests shows that the correlation has a very important impact on the results of sensitivity analysis. Assessment of correlation strength among input variables on the sensitivity analysis is also achieved.

WGCNA: an R package for weighted correlation network analysis.

PubMed

Langfelder, Peter; Horvath, Steve

2008-12-29

Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.

Genomic Analysis of Circadian Clock-, Light-, and Growth-Correlated Genes Reveals PHYTOCHROME-INTERACTING FACTOR5 as a Modulator of Auxin Signaling in Arabidopsis1[C][W][OA

PubMed Central

Nozue, Kazunari; Harmer, Stacey L.; Maloof, Julin N.

2011-01-01

Plants exhibit daily rhythms in their growth, providing an ideal system for the study of interactions between environmental stimuli such as light and internal regulators such as the circadian clock. We previously found that two basic loop-helix-loop transcription factors, PHYTOCHROME-INTERACTING FACTOR4 (PIF4) and PIF5, integrate light and circadian clock signaling to generate rhythmic plant growth in Arabidopsis (Arabidopsis thaliana). Here, we use expression profiling and real-time growth assays to identify growth regulatory networks downstream of PIF4 and PIF5. Genome-wide analysis of light-, clock-, or growth-correlated genes showed significant overlap between the transcriptomes of clock-, light-, and growth-related pathways. Overrepresentation analysis of growth-correlated genes predicted that the auxin and gibberellic acid (GA) hormone pathways both contribute to diurnal growth control. Indeed, lesions of GA biosynthesis genes retarded rhythmic growth. Surprisingly, GA-responsive genes are not enriched among genes regulated by PIF4 and PIF5, whereas auxin pathway and response genes are. Consistent with this finding, the auxin response is more severely affected than the GA response in pif4 pif5 double mutants and in PIF5-overexpressing lines. We conclude that at least two downstream modules participate in diurnal rhythmic hypocotyl growth: PIF4 and/or PIF5 modulation of auxin-related pathways and PIF-independent regulation of the GA pathway. PMID:21430186

Multifractal detrended cross-correlation analysis in the MENA area

NASA Astrophysics Data System (ADS)

El Alaoui, Marwane; Benbachir, Saâd

2013-12-01

In this paper, we investigated multifractal cross-correlations qualitatively and quantitatively using a cross-correlation test and the Multifractal detrended cross-correlation analysis method (MF-DCCA) for markets in the MENA area. We used cross-correlation coefficients to measure the level of this correlation. The analysis concerns four stock market indices of Morocco, Tunisia, Egypt and Jordan. The countries chosen are signatory of the Agadir agreement concerning the establishment of a free trade area comprising Arab Mediterranean countries. We computed the bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively the cross-correlations. By analyzing the results, we found the existence of multifractal cross-correlations between all of these markets. We compared the spectrum width of these indices; we also found which pair of indices has a strong multifractal cross-correlation.

Systematic evaluation of environmental factors: persistent pollutants and nutrients correlated with serum lipid levels

PubMed Central

Patel, Chirag J; Cullen, Mark R; Ioannidis, John PA; Butte, Atul J

2012-01-01

Background Both genetic and environmental factors contribute to triglyceride, low-density lipoprotein-cholesterol (LDL-C), and high-density lipoprotein-cholesterol (HDL-C) levels. Although genome-wide association studies are currently testing the genetic factors systematically, testing and reporting one or a few factors at a time can lead to fragmented literature for environmental chemical factors. We screened for correlation between environmental factors and lipid levels, utilizing four independent surveys with information on 188 environmental factors from the Centers of Disease Control, National Health and Nutrition Examination Survey, collected between 1999 and 2006. Methods We used linear regression to correlate each environmental chemical factor to triglycerides, LDL-C and HDL-C adjusting for age, age2, sex, ethnicity, socio-economic status and body mass index. Final estimates were adjusted for waist circumference, diabetes status, blood pressure and survey. Multiple comparisons were controlled for by estimating the false discovery rate and significant findings were tentatively validated in an independent survey. Results We identified and validated 29, 9 and 17 environmental factors correlated with triglycerides, LDL-C and HDL-C levels, respectively. Findings include hydrocarbons and nicotine associated with lower HDL-C and vitamin E (γ-tocopherol) associated with unfavourable lipid levels. Higher triglycerides and lower HDL-C were correlated with higher levels of fat-soluble contaminants (e.g. polychlorinated biphenyls and dibenzofurans). Nutrients and vitamin markers (e.g. vitamins B, D and carotenes), were associated with favourable triglyceride and HDL-C levels. Conclusions Our systematic association study has enabled us to postulate about broad environmental correlation to lipid levels. Although subject to confounding and reverse causality bias, these findings merit evaluation in additional cohorts. PMID:22421054

The proportion of dyslipidemia in systemic lupus erythematosus patient and distribution of correlated factors.

PubMed

Wijaya, Linda K; Kasjmir, Yoga Iwanoff; Sukmana, Nanang; Subekti, Imam; Prihartono, Joedo

2005-01-01

To understand the proportion of dyslipidemia in systemic lupus erythematosus (SLE) patients and the influencing factors of dyslipidemia. AN observational, cross-sectional study was conducted on new and longstanding SLE patients who had been diagnosed based on ARA criteria 1982 with 1997 revision. They had been hospitalized and treated at Department of Internal Medicine, Cipto Mangunkusumo National Central General Hospital and the other private Hospitals in Jakarta, i.e. Kramat Hospital in July - November 2003. The sample was selected by non probability sampling method with consecutive sampling technique. Every participant underwent history taking, physical and laboratory examination. There were 77 patients satisfying the inclusion criteria. The proportion of dyslipidemia in this study was 75.3%. By confidence interval of 95%, the dyslipidemia in SLE patient was 65.3% - 84.6%. The distribution of lipid profile in sample population were 43% with total cholesterol > or = 200 mg/dL, 26% with HDL cholesterol level < 40 mg/dL, 26.4% with LDL cholesterol level > or = 130 mg/dl and 44.2% with triglycerides serum level > or = 150 mg/dL. The characteristics of influencing factors in dyslipidemia prevalence for sample population consisted of 24.7% with renal involvement, 53.2% with > or = 3 years illness periods, 26% had received > or = 30 mg/day prednisone, 94.8% had not received chloroquines, and 58.4% had illness activity of Mex-SLEDAI > or = 2. By bivariate analysis, we found that illness period < 3 years tends to affect dyslipidemia with OR value of 12.04 (CI 95%, 2.54-57.05, p = 0.001). After conducting multivariate analysis by backward methods, it appears that only one significant influencing factor of dyslipidemia prevalence in SLE patient i.e. Illness period od < 3 years with OR value 12.04 (CI 95% 2.54 - 57.05, p = 0.001). Illness period of 3 years is represent a significant correlative factor for dyslipedemia prevalence. Prednisone > or = 30 mg/dL is the

Runaway youths and correlating factors, study in Thailand.

PubMed

Techakasem, Pisarn; Kolkijkovin, Varuna

2006-02-01

To study differences between runaways and non-runaways in a mental health clinic and to study differences between runaways in a mental health clinic and legal / shelter system. Psychiatric records of runaways and non-runaways from Vajira Hospital were collected from June 1994 to October 2003. 21 cases in each group were studied in various factors. 21 runaway cases who were in child and adolescent shelters were interviewed by the researchers. Neglect, sexual abuse, rejection, poverty and truancy were more common in the runaway group. The runaway group had more conduct disorder and substance abuse. Physical abuse, authoritarian and being in custody were more common in runaways in shelters. Various factors correlate with running away. These factors lie beneath long before runaway has taken place and understanding and managing them help in preventing and prompt treatment.

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.…

Analysis on factors affecting household customers decision in using electricity at peak time and its correlation towards saving electricity

NASA Astrophysics Data System (ADS)

Pasasa, Linus; Marbun, Parlin; Mariza, Ita

2015-09-01

The purpose of this paper is to study and analyse the factors affecting customer decisions in using electricity at peak-load hours (between 17.00 to 22.00 WIB) and their behaviors towards electricity conservation in Indonesian household. The underlying rationale is to influence a reduction in energy consumption by stimulating energy saving behaviors, thereby reducing the impact of energy use on the environment. How is the correlation between the decisions in using electricity during peak load hours with the household customer's behavior towards saving electricity? The primary data is obtained by distributing questionnaires to customers of PT. PLN Jakarta Raya and Tangerang Distribution from Household segment. The data is analysed using the Structural Equation Model (SEM) and AMOS Software. The research is finding that all factors (Personal, Social, PLN Services, Psychological, and Cultural) are positively influence customer decision in using electricity at peak load hours. There is a correlation between the decisions in using electricity during peak load hours with the household customer's behavior towards saving electricity.

Correlation of quantitative histopathological morphology and quantitative radiological analysis during aseptic loosening of hip endoprostheses.

PubMed

Bertz, S; Kriegsmann, J; Eckardt, A; Delank, K-S; Drees, P; Hansen, T; Otto, M

2006-01-01

Aseptic hip prosthesis loosening is the most important long-term complication in total hip arthroplasty. Polyethylene (PE) wear is the dominant etiologic factor in aseptic loosening, which together with other factors induces mechanisms resulting in bone loss, and finally in implant loosening. The single-shot radiograph analysis (EBRA, abbreviation for the German term "Einzel-Bild-Röntgenanalyse") is a computerized method for early radiological prediction of aseptic loosening. In this study, EBRA parameters were correlated with histomorphological parameters of the periprosthetic membrane. Periprosthetic membranes obtained from 19 patients during revision surgery of loosened ABG I-type total hip pros-theses were analyzed histologically and morphometrically. The pre-existing EBRA parameters, the thickness of the PE debris lay-er and the dimension of inclination and anteversion, were compared with the density of macrophages and giant cells. Addi-tionally, the semiquantitatively determined density of lymphocytes, plasma cells, giant cells and the size of the necrotic areas were correlated with the EBRA results. All periprosthetic membranes were classified as debris-induced type membranes. We found a positive correlation between the number of giant cells and the thickness of the PE debris layer. There was no significant correlation between the number of macrophages or all semiquantitative parameters and EBRA parameters. The number of giant cells decreased with implant duration. The morphometrically measured number of foreign body giant cells more closely reflects the results of the EBRA. The semiquantitative estimation of giant cell density could not substitute for the morphometrical analysis. The density of macrophages, lymphocytes, plasma cells and the size of necrotic areas did not correlate with the EBRA parameters, indicating that there is no correlation with aseptic loosening.

Rotational Uniqueness Conditions under Oblique Factor Correlation Metric

ERIC Educational Resources Information Center

Peeters, Carel F. W.

2012-01-01

In an addendum to his seminal 1969 article Joreskog stated two sets of conditions for rotational identification of the oblique factor solution under utilization of fixed zero elements in the factor loadings matrix (Joreskog in "Advances in factor analysis and structural equation models," pp. 40-43, 1979). These condition sets, formulated under…

Correlation between spontaneous apoptosis and the expression of angiogenic factors in advanced gastric adenocarcinoma.

PubMed

Ikeguchi, M; Cai, J; Fukuda, K; Oka, S; Katano, K; Tsujitani, S; Maeta, M; Kaibara, N

2001-06-01

The aim of this study was to investigate whether angiogenic factors influence the occurrence of spontaneous apoptosis in advanced gastric cancer. The apoptotic indices (AIs) of 97 tumors from 97 patients with advanced gastric cancer (pT3, pN0, pM0, Stage II) were analyzed by the terminal deoxynucleotidyl transferase-mediated deoxyuridine triphosphate biotin nick end labeling (TUNEL) method. Intratumoral microvessel densities (IMVDs) of tumors stained with anti-CD34 monoclonal antibody were quantified under x 200 magnification using computer-assisted image analysis. The expressions of angiogenic factors, such as vascular endothelial growth factor (VEGF), thymidine phosphorylase (dThdPase), transforming growth factor-alpha (TGF-alpha), and p53 were analyzed immunohistochemically and compared with IMVDs and AIs. The mean IMVD of the 97 tumors was 365/mm2 (range 147-990/mm2). The mean AI of tumors was 2.1% (range 0-11.3%). A significant inverse correlation between the AIs and the IMVDs was shown (p = -0.278, P = 0.0064). The mean IMVDs of tumors with high expressions of dThdPase, TGF-alpha, or p53 were significantly higher than those of tumors with low expressions of these factors. The mean AI of tumors with high expressions of dThdPase was significantly lower than that of tumors with low expressions of dThdPase (P = 0.023). However, no significant correlations were detected between AIs and the expression levels of VEGF, TGF-alpha, or p53. In gastric cancer, dThdPase may play an important role in tumor progression by increasing microvessels and by suppressing apoptosis of cancer cells.

Validation of the Adolescent Concerns Measure (ACM): Evidence from Exploratory and Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Ang, Rebecca P.; Chong, Wan Har; Huan, Vivien S.; Yeo, Lay See

2007-01-01

This article reports the development and initial validation of scores obtained from the Adolescent Concerns Measure (ACM), a scale which assesses concerns of Asian adolescent students. In Study 1, findings from exploratory factor analysis using 619 adolescents suggested a 24-item scale with four correlated factors--Family Concerns (9 items), Peer…

[Factors correlated with low-income diabetic patients' quality of life in Bogota].

PubMed

Muñoz, Diana I; Gómez, Olga L; Ballesteros, Luz Carime

2014-01-01

Identifying the factors correlated with health-related quality of life (QOL) amongst low-income diabetic patients attending two public hospitals in Bogotá. This was a cross-sectional study involving 153 type 2 diabetic patients. The variables studied were socio-demographic characteristics, social support, lifestyle and clinical measurements (HbA1c, BMI, and cholesterol). The SF-8 health survey (8-item short form) was used for assessing health-related QOL. Overall physical score was 41.4 (SE 8.5) and overall mental score 46.5 (SE 7.3); the scores never exceeded 50 points. The factors correlated with lower QOL regarding the physical domain were occupation, social support, physical activity and fat intake and age, occupation, social support, and smoking status regarding the mental domain. The patients surveyed here had a poor QOL. The factors correlated with health-related QOL included socio-demographic characteristics, social support and lifestyle. These findings should be taken into account when formulating public health policy to readdress the current healthcare model for controlling diabetes.

Factors affecting quality of life in adults with epilepsy in Taiwan: A cross-sectional, correlational study.

PubMed

Chen, Hsiu-Fang; Tsai, Yun-Fang; Hsi, Mo-Song; Chen, Jui-Chen

2016-05-01

The purpose of this study was to assess eight factors considered important for quality of life in persons with epilepsy in order to determine which of these components affect quality of life in adults with epilepsy in Taiwan. A cross-sectional, correlational study using structured questionnaires assessed 260 patients with epilepsy purposively sampled from a medical center in Northern Taiwan. Health-related quality of life (HRQoL) was evaluated with the Quality of Life in Epilepsy-31 (QOLIE-31) questionnaire. Data also included personal and health-related characteristics, knowledge of epilepsy, efficacy in the self-management of epilepsy, and social support. Scores for the QOLIE-31 were correlated with the following factors: (1) demographic characteristics of age, gender, and income; (2) sleep quality; (3) symptoms of anxiety and depression; (4) epilepsy-specific variables: seizure frequency; types, number, and frequency of antiepileptic drugs (AEDs); and adverse events of AEDs; and (5) social support. Stepwise regression analysis showed that seven factors were predictive for quality of life: anxiety, depression, adverse events of AEDs, social support, seizure frequency of at least once in three months, household income of NT$ 40,001-100,000, and male gender. These factors accounted for 58.2% of the variance of quality of life. Our study assessed multiple factors in an examination of relationships and predictive factors for quality of life in adults with epilepsy in Taiwan. Knowledge of these contributing factors can assist health-care providers when evaluating patients with epilepsy to help target interventions for improving quality of life. Copyright © 2016 Elsevier Inc. All rights reserved.

Factors influencing parenting efficacy of Asian immigrant, first-time mothers: A cross-sectional, correlational survey.

PubMed

Roh, Eun Ha; Ahn, Jeong-Ah; Park, Somi; Song, Ju-Eun

2017-12-01

In this study, we determined the factors influencing parenting efficacy of Asian immigrant, first-time mothers. The research design was a cross-sectional, correlational study. The study included 125 first-time mothers who immigrated and married Korean men, and were living in Korea. Data were collected using translated questionnaires, and analyzed for descriptive statistics, Pearson correlation, and multiple regression analysis. The major finding was that the parenting efficacy of immigrant women was influenced by childcare support from their husbands, maternal identity, and original nationality. The findings suggest that customized programs be developed and used to enhance parenting efficacy for Asian immigrant, first-time mothers. In developing such programs, the advantages of maternal identity, social support from the husband, and women's cultural context should be considered. © 2017 John Wiley & Sons Australia, Ltd.

[Mathematic analysis of risk factors influence on occupational respiratory diseases development].

PubMed

Budkar', L N; Bugaeva, I V; Obukhova, T Iu; Tereshina, L G; Karpova, E A; Shmonina, O G

2010-01-01

Analysis covered 1348 case histories of workers exposed to industrial dust in Urals region. The analysis applied mathematical processing of survival theory and correlation analysis. The authors studied influence of various factors: dust concentration, connective tissue dysplasia, smoking habits--on duration for diseases caused by dust to appear. Findings are that occupational diseases develop reliably faster with higher ambient dust concentrations and with connective tissue dysplasia syndrome. Smoking habits do not alter duration of pneumoconiosis development, but reliably increases development of occupational dust bronchitis.

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.

Dependence of structure factor and correlation energy on the width of electron wires

NASA Astrophysics Data System (ADS)

Ashokan, Vinod; Bala, Renu; Morawetz, Klaus; Pathak, Kare Narain

2018-02-01

The structure factor and correlation energy of a quantum wire of thickness b ≪ a B are studied in random phase approximation (RPA) and for the less investigated region r s < 1. Using the single-loop approximation, analytical expressions of the structure factor are obtained. The exact expressions for the exchange energy are also derived for a cylindrical and harmonic wire. The correlation energy in RPA is found to be represented by ɛ c ( b, r s ) = α( r s )/ b + β( r s ) ln( b) + η( r s ), for small b and high densities. For a pragmatic width of the wire, the correlation energy is in agreement with the quantum Monte Carlo simulation data.

Multiscale Detrended Cross-Correlation Analysis of STOCK Markets

NASA Astrophysics Data System (ADS)

Yin, Yi; Shang, Pengjian

2014-06-01

In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and

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.

Research on the factors of return on equity: empirical analysis in Chinese port industries from 2000-2008

NASA Astrophysics Data System (ADS)

Li, Wei

2012-01-01

Port industries are the basic industries in the national economy. The industries have become the most modernized departments in every country. The development of the port industry is not only advantageous to promote the optimizing arrangement of social resources, but also to promote the growth of foreign trade volume through enhancing the transportation functions. Return on equity (ROE) is a direct indicator related to the maximization of company's wealth. It makes up the shortcomings of earnings per share (EPS). The aim of this paper is to prove the correlation between ROE and other financial indicators by choosing the listed port companies as the research objectives and selecting the data of these companies from 2000 to 2008 as empirical sample data with statistical analysis of the chartered figure and coefficient. The detailed analysis method used in the paper is the combination of trend analysis, comparative analysis and the ratio of the factor analysis method. This paper analyzes and compares all these factors and draws the conclusions as follows: Firstly, ROE has a positive correlation with total assets turnover, main profit margin and fixed asset ratio, while has a negative correlation with assets liabilities ratio, total assets growth rate and DOL. Secondly, main profit margin has the greatest positive effect on ROE among all these factors. The second greatest factor is total assets turnover, which shows the operation capacity is also an important indicator after the profitability. Thirdly, assets liabilities ratio has the greatest negative effect on ROE among all these factors.

Research on the factors of return on equity: empirical analysis in Chinese port industries from 2000-2008

NASA Astrophysics Data System (ADS)

Li, Wei

2011-12-01

Port industries are the basic industries in the national economy. The industries have become the most modernized departments in every country. The development of the port industry is not only advantageous to promote the optimizing arrangement of social resources, but also to promote the growth of foreign trade volume through enhancing the transportation functions. Return on equity (ROE) is a direct indicator related to the maximization of company's wealth. It makes up the shortcomings of earnings per share (EPS). The aim of this paper is to prove the correlation between ROE and other financial indicators by choosing the listed port companies as the research objectives and selecting the data of these companies from 2000 to 2008 as empirical sample data with statistical analysis of the chartered figure and coefficient. The detailed analysis method used in the paper is the combination of trend analysis, comparative analysis and the ratio of the factor analysis method. This paper analyzes and compares all these factors and draws the conclusions as follows: Firstly, ROE has a positive correlation with total assets turnover, main profit margin and fixed asset ratio, while has a negative correlation with assets liabilities ratio, total assets growth rate and DOL. Secondly, main profit margin has the greatest positive effect on ROE among all these factors. The second greatest factor is total assets turnover, which shows the operation capacity is also an important indicator after the profitability. Thirdly, assets liabilities ratio has the greatest negative effect on ROE among all these factors.

20 Meter Solar Sail Analysis and Correlation

NASA Technical Reports Server (NTRS)

Taleghani, B.; Lively, P.; Banik, J.; Murphy, D.; Trautt, T.

2005-01-01

This presentation discusses studies conducted to determine the element type and size that best represents a 20-meter solar sail under ground-test load conditions, the performance of test/Analysis correlation by using Static Shape Optimization Method for Q4 sail, and system dynamic. TRIA3 elements better represent wrinkle patterns than do QUAD3 elements Baseline, ten-inch elements are small enough to accurately represent sail shape, and baseline TRIA3 mesh requires a reasonable computation time of 8 min. 21 sec. In the test/analysis correlation by using Static shape optimization method for Q4 sail, ten parameters were chosen and varied during optimization. 300 sail models were created with random parameters. A response surfaces for each targets which were created based on the varied parameters. Parameters were optimized based on response surface. Deflection shape comparison for 0 and 22.5 degrees yielded a 4.3% and 2.1% error respectively. For the system dynamic study testing was done on the booms without the sails attached. The nominal boom properties produced a good correlation to test data the frequencies were within 10%. Boom dominated analysis frequencies and modes compared well with the test results.

Using Horn's Parallel Analysis Method in Exploratory Factor Analysis for Determining the Number of Factors

ERIC Educational Resources Information Center

Çokluk, Ömay; Koçak, Duygu

2016-01-01

In this study, the number of factors obtained from parallel analysis, a method used for determining the number of factors in exploratory factor analysis, was compared to that of the factors obtained from eigenvalue and scree plot--two traditional methods for determining the number of factors--in terms of consistency. Parallel analysis is based on…

Factor Analysis of Linear Type Traits and Their Relation with Longevity in Brazilian Holstein Cattle

PubMed Central

Kern, Elisandra Lurdes; Cobuci, Jaime Araújo; Costa, Cláudio Napolis; Pimentel, Concepta Margaret McManus

2014-01-01

In this study we aimed to evaluate the reduction in dimensionality of 20 linear type traits and more final score in 14,943 Holstein cows in Brazil using factor analysis, and indicate their relationship with longevity and 305 d first lactation milk production. Low partial correlations (−0.19 to 0.38), the medium to high Kaiser sampling mean (0.79) and the significance of the Bartlett sphericity test (p<0.001), indicated correlations between type traits and the suitability of these data for a factor analysis, after the elimination of seven traits. Two factors had autovalues greater than one. The first included width and height of posterior udder, udder texture, udder cleft, loin strength, bone quality and final score. The second included stature, top line, chest width, body depth, fore udder attachment, angularity and final score. The linear regression of the factors on several measures of longevity and 305 d milk production showed that selection considering only the first factor should lead to improvements in longevity and 305 milk production. PMID:25050015

Factor Covariance Analysis in Subgroups.

ERIC Educational Resources Information Center

Pennell, Roger

The problem considered is that of an investigator sampling two or more correlation matrices and desiring to fit a model where a factor pattern matrix is assumed to be identical across samples and we need to estimate only the factor covariance matrix and the unique variance for each sample. A flexible, least squares solution is worked out and…

Cross-correlation detection and analysis for California's electricity market based on analogous multifractal analysis

NASA Astrophysics Data System (ADS)

Wang, Fang; Liao, Gui-ping; Li, Jian-hui; Zou, Rui-biao; Shi, Wen

2013-03-01

A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF -XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF -XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.

Cross-correlation detection and analysis for California's electricity market based on analogous multifractal analysis.

PubMed

Wang, Fang; Liao, Gui-ping; Li, Jian-hui; Zou, Rui-biao; Shi, Wen

2013-03-01

A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF-XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF-XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.

Combining Correlation Matrices: Simulation Analysis of Improved Fixed-Effects Methods

ERIC Educational Resources Information Center

Hafdahl, Adam R.

2007-01-01

The originally proposed multivariate meta-analysis approach for correlation matrices--analyze Pearson correlations, with each study's observed correlations replacing their population counterparts in its conditional-covariance matrix--performs poorly. Two refinements are considered: Analyze Fisher Z-transformed correlations, and substitute better…

HR-MAS MR Spectroscopy of Breast Cancer Tissue Obtained with Core Needle Biopsy: Correlation with Prognostic Factors

PubMed Central

Choi, Ji Soo; Baek, Hyeon-Man; Kim, Suhkmann; Kim, Min Jung; Youk, Ji Hyun; Moon, Hee Jung; Kim, Eun-Kyung; Han, Kyung Hwa; Kim, Dong-hyun; Kim, Seung Il; Koo, Ja Seung

2012-01-01

The purpose of this study was to examine the correlation between high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopy using core needle biopsy (CNB) specimens and histologic prognostic factors currently used in breast cancer patients. After institutional review board approval and informed consent were obtained for this study, CNB specimens were collected from 36 malignant lesions in 34 patients. Concentrations and metabolic ratios of various choline metabolites were estimated by HR-MAS MR spectroscopy using CNB specimens. HR-MAS spectroscopic values were compared according to histopathologic variables [tumor size, lymph node metastasis, histologic grade, status of estrogens receptor (ER), progesterone receptor (PR), HER2 (a receptor for human epidermal growth factor), and Ki-67, and triple negativity]. Multivariate analysis was performed with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA). HR-MAS MR spectroscopy quantified and discriminated choline metabolites in all CNB specimens of the 36 breast cancers. Several metabolite markers [free choline (Cho), phosphocholine (PC), creatine (Cr), taurine, myo-inositol, scyllo-inositol, total choline (tCho), glycine, Cho/Cr, tCho/Cr, PC/Cr] on HR-MAS MR spectroscopy were found to correlate with histologic prognostic factors [ER, PR, HER2, histologic grade, triple negativity, Ki-67, poor prognosis]. OPLS-DA multivariate models were generally able to discriminate the status of histologic prognostic factors (ER, PR, HER2, Ki-67) and prognosis groups. Our study suggests that HR-MAS MR spectroscopy using CNB specimens can predict tumor aggressiveness prior to surgery in breast cancer patients. In addition, it may be helpful in the detection of reliable markers for breast cancer characterization. PMID:23272149

Cluster structure of EU-15 countries derived from the correlation matrix analysis of macroeconomic index fluctuations

NASA Astrophysics Data System (ADS)

Gligor, M.; Ausloos, M.

2007-05-01

The statistical distances between countries, calculated for various moving average time windows, are mapped into the ultrametric subdominant space as in classical Minimal Spanning Tree methods. The Moving Average Minimal Length Path (MAMLP) algorithm allows a decoupling of fluctuations with respect to the mass center of the system from the movement of the mass center itself. A Hamiltonian representation given by a factor graph is used and plays the role of cost function. The present analysis pertains to 11 macroeconomic (ME) indicators, namely the GDP (x1), Final Consumption Expenditure (x2), Gross Capital Formation (x3), Net Exports (x4), Consumer Price Index (y1), Rates of Interest of the Central Banks (y2), Labour Force (z1), Unemployment (z2), GDP/hour worked (z3), GDP/capita (w1) and Gini coefficient (w2). The target group of countries is composed of 15 EU countries, data taken between 1995 and 2004. By two different methods (the Bipartite Factor Graph Analysis and the Correlation Matrix Eigensystem Analysis) it is found that the strongly correlated countries with respect to the macroeconomic indicators fluctuations can be partitioned into stable clusters.

Determining the Number of Factors in P-Technique Factor Analysis

ERIC Educational Resources Information Center

Lo, Lawrence L.; Molenaar, Peter C. M.; Rovine, Michael

2017-01-01

Determining the number of factors is a critical first step in exploratory factor analysis. Although various criteria and methods for determining the number of factors have been evaluated in the usual between-subjects R-technique factor analysis, there is still question of how these methods perform in within-subjects P-technique factor analysis. A…

A canonical correlation analysis based EMG classification algorithm for eliminating electrode shift effect.

PubMed

Zhe Fan; Zhong Wang; Guanglin Li; Ruomei Wang

2016-08-01

Motion classification system based on surface Electromyography (sEMG) pattern recognition has achieved good results in experimental condition. But it is still a challenge for clinical implement and practical application. Many factors contribute to the difficulty of clinical use of the EMG based dexterous control. The most obvious and important is the noise in the EMG signal caused by electrode shift, muscle fatigue, motion artifact, inherent instability of signal and biological signals such as Electrocardiogram. In this paper, a novel method based on Canonical Correlation Analysis (CCA) was developed to eliminate the reduction of classification accuracy caused by electrode shift. The average classification accuracy of our method were above 95% for the healthy subjects. In the process, we validated the influence of electrode shift on motion classification accuracy and discovered the strong correlation with correlation coefficient of >0.9 between shift position data and normal position data.

Fatality analysis reporting system and roadway inventory correlation.

DOT National Transportation Integrated Search

2013-01-01

In this project, we developed an integrated database to provide new analysis capabilities : for discovering correlations between roadway characteristics and the occurrence of : fatality collisions. Specifically, the aim of this data analysis project ...

Correlation between reactive oxygen metabolites & atherosclerotic risk factors in patients with type 2 diabetes mellitus.

PubMed

Kotani, Kazuhiko; Tsuzaki, Kokoro; Taniguchi, Nobuyuki; Sakane, Naoki

2013-04-01

Oxidative stress plays important roles in the pathophysiology of type 2 diabetes mellitus (T2DM). The diacron reactive oxygen metabolites (d-ROMs) test has been used in the clinics. The present study was aimed to investigate the correlation of the oxidative stress status, as evaluated by the d-ROMs, with atherosclerotic risk factors in T2DM patients, in comparison to controls. The study included 200 subjects (100 patients with T2DM and 100 controls; 86 males/114 females; mean age 59.0 yr). Clinical variables including the body mass index, blood pressure (BP), glucose and lipid panels, in addition to the d-ROMs, were measured. Patients with T2DM showed significantly higher d-ROMs levels than controls (322 ± 60 vs. 345 ± 64 U. Carr., P<0.05). A multiple linear regression analysis revealed that systolic BP (β=0.26, P<0.05) and high-density lipoprotein cholesterol (HDL-C: β= -0.30, P<0.05) were independently and significantly correlated with the d-ROMs levels in patients with T2DM, although these correlations were not significant in the controls. The gender-based analysis showed that systolic BP (β = 0.44, P<0.05) and HDL-C (β = -0.36, P<0.05) were independently and significantly correlated with the d-ROMs levels in females with T2DM, while there was a marginally significant correlation between HDL-C and the d-ROMs levels (β = -0.36, P=0.06) in males with T2DM. The present findings may reinforce the importance of BP control in female patients with T2DM, as well as the management of HDL-C in male and female patients with T2DM, under the linkage between oxidative stress and atherosclerosis.

Correlation between reactive oxygen metabolites & atherosclerotic risk factors in patients with type 2 diabetes mellitus

PubMed Central

Kotani, Kazuhiko; Tsuzaki, Kokoro; Taniguchi, Nobuyuki; Sakane, Naoki

2013-01-01

Background & objectives: Oxidative stress plays important roles in the pathophysiology of type 2 diabetes mellitus (T2DM). The diacron reactive oxygen metabolites (d-ROMs) test has been used in the clinics. The present study was aimed to investigate the correlation of the oxidative stress status, as evaluated by the d-ROMs, with atherosclerotic risk factors in T2DM patients, in comparison to controls. Methods: The study included 200 subjects (100 patients with T2DM and 100 controls; 86 males/114 females; mean age 59.0 yr). Clinical variables including the body mass index, blood pressure (BP), glucose and lipid panels, in addition to the d-ROMs, were measured. Results: Patients with T2DM showed significantly higher d-ROMs levels than controls (322 ± 60 vs. 345 ± 64 U. Carr., P<0.05). A multiple linear regression analysis revealed that systolic BP (β=0.26, P<0.05) and high-density lipoprotein cholesterol (HDL-C: β= -0.30, P<0.05) were independently and significantly correlated with the d-ROMs levels in patients with T2DM, although these correlations were not significant in the controls. The gender-based analysis showed that systolic BP (β = 0.44, P<0.05) and HDL-C (β = -0.36, P<0.05) were independently and significantly correlated with the d-ROMs levels in females with T2DM, while there was a marginally significant correlation between HDL-C and the d-ROMs levels (β = -0.36, P=0.06) in males with T2DM. Interpretation & conclusions: The present findings may reinforce the importance of BP control in female patients with T2DM, as well as the management of HDL-C in male and female patients with T2DM, under the linkage between oxidative stress and atherosclerosis. PMID:23703342

International Space Station Model Correlation Analysis

NASA Technical Reports Server (NTRS)

Laible, Michael R.; Fitzpatrick, Kristin; Hodge, Jennifer; Grygier, Michael

2018-01-01

This paper summarizes the on-orbit structural dynamic data and the related modal analysis, model validation and correlation performed for the International Space Station (ISS) configuration ISS Stage ULF7, 2015 Dedicated Thruster Firing (DTF). The objective of this analysis is to validate and correlate the analytical models used to calculate the ISS internal dynamic loads and compare the 2015 DTF with previous tests. During the ISS configurations under consideration, on-orbit dynamic measurements were collected using the three main ISS instrumentation systems; Internal Wireless Instrumentation System (IWIS), External Wireless Instrumentation System (EWIS) and the Structural Dynamic Measurement System (SDMS). The measurements were recorded during several nominal on-orbit DTF tests on August 18, 2015. Experimental modal analyses were performed on the measured data to extract modal parameters including frequency, damping, and mode shape information. Correlation and comparisons between test and analytical frequencies and mode shapes were performed to assess the accuracy of the analytical models for the configurations under consideration. These mode shapes were also compared to earlier tests. Based on the frequency comparisons, the accuracy of the mathematical models is assessed and model refinement recommendations are given. In particular, results of the first fundamental mode will be discussed, nonlinear results will be shown, and accelerometer placement will be assessed.

Exploratory and confirmatory factor analyses and demographic correlate models of the strategies for weight management measure for overweight or obese adults.

PubMed

Kolodziejczyk, Julia K; Norman, Gregory J; Roesch, Scott C; Rock, Cheryl L; Arredondo, Elva M; Madanat, Hala; Patrick, Kevin

2015-01-01

There is a need for a self-report measure that assesses use of recommended strategies related to weight management. Cross-sectional analysis. Universities, community. Exploratory factor analysis (EFA) involved data from 404 overweight/obese young adults (mean age = 22 years, 48% non-Hispanic white, 68% ethnic minority). Confirmatory factor analysis (CFA) involved data from 236 overweight/obese adults (mean age = 42 years, 63% non-Hispanic white, 84% ethnic minority). The Strategies for Weight Management (SWM) measure is a 35-item questionnaire that assesses use of recommended behavioral strategies for reducing energy intake and increasing energy expenditure in overweight/obese adults. EFA and CFA were conducted on the SWM. Correlate models assessed the associations between SWM factor/total scores and demographics by using linear regressions. EFA suggested a four-factor model: strategies categorized as targeting (1) energy intake, (2) energy expenditure, (3) self-monitoring, and (4) self-regulation. CFA indicated good model fit (χ(2)/df = 2.0, comparative fit index = .90, standardized root mean square residual = .06, and root mean square error of approximation = .07, confidence interval = .06-.08, R(2) = .11-.74). The fourth factor had the lowest loadings, possibly because the items cover a wide domain. The final model included 20 items. Correlate models revealed weak associations between the SWM scores and age, gender, Hispanic ethnicity, and relationship status in both samples, with the models explaining only 1% to 8% of the variance (betas = -.04 to .29, p < .05). The SWM has promising psychometric qualities in two diverse samples.

Detrended Partial-Cross-Correlation Analysis: A New Method for Analyzing Correlations in Complex System

PubMed Central

Yuan, Naiming; Fu, Zuntao; Zhang, Huan; Piao, Lin; Xoplaki, Elena; Luterbacher, Juerg

2015-01-01

In this paper, a new method, detrended partial-cross-correlation analysis (DPCCA), is proposed. Based on detrended cross-correlation analysis (DCCA), this method is improved by including partial-correlation technique, which can be applied to quantify the relations of two non-stationary signals (with influences of other signals removed) on different time scales. We illustrate the advantages of this method by performing two numerical tests. Test I shows the advantages of DPCCA in handling non-stationary signals, while Test II reveals the “intrinsic” relations between two considered time series with potential influences of other unconsidered signals removed. To further show the utility of DPCCA in natural complex systems, we provide new evidence on the winter-time Pacific Decadal Oscillation (PDO) and the winter-time Nino3 Sea Surface Temperature Anomaly (Nino3-SSTA) affecting the Summer Rainfall over the middle-lower reaches of the Yangtze River (SRYR). By applying DPCCA, better significant correlations between SRYR and Nino3-SSTA on time scales of 6 ~ 8 years are found over the period 1951 ~ 2012, while significant correlations between SRYR and PDO on time scales of 35 years arise. With these physically explainable results, we have confidence that DPCCA is an useful method in addressing complex systems. PMID:25634341

Defeat and entrapment: more than meets the eye? Applying network analysis to estimate dimensions of highly correlated constructs.

PubMed

Forkmann, Thomas; Teismann, Tobias; Stenzel, Jana-Sophie; Glaesmer, Heide; de Beurs, Derek

2018-01-25

Defeat and entrapment have been shown to be of central relevance to the development of different disorders. However, it remains unclear whether they represent two distinct constructs or one overall latent variable. One reason for the unclarity is that traditional factor analytic techniques have trouble estimating the right number of clusters in highly correlated data. In this study, we applied a novel approach based on network analysis that can deal with correlated data to establish whether defeat and entrapment are best thought of as one or multiple constructs. Explanatory graph analysis was used to estimate the number of dimensions within the 32 items that make up the defeat and entrapment scales in two samples: an online community sample of 480 participants, and a clinical sample of 147 inpatients admitted to a psychiatric hospital after a suicidal attempt or severe suicidal crisis. Confirmatory Factor analysis (CFA) was used to test whether the proposed structure fits the data. In both samples, bootstrapped exploratory graph analysis suggested that the defeat and entrapment items belonged to different dimensions. Within the entrapment items, two separate dimensions were detected, labelled internal and external entrapment. Defeat appeared to be multifaceted only in the online sample. When comparing the CFA outcomes of the one, two, three and four factor models, the one factor model was preferred. Defeat and entrapment can be viewed as distinct, yet, highly associated constructs. Thus, although replication is needed, results are in line with theories differentiating between these two constructs.

Early Retirement: A Meta-Analysis of Its Antecedent and Subsequent Correlates

PubMed Central

Topa, Gabriela; Depolo, Marco; Alcover, Carlos-Maria

2018-01-01

Early or voluntary retirement (ER) can be defined as the full exit from an organizational job or career path of long duration, decided by individuals of a certain age at the mid or late career before mandatory retirement age, with the aim of reducing their attachment to work and closing a process of gradual psychological disengagement from working life. Given the swinging movements that characterize employment policies, the potential effects of ER—both for individuals and society—are still controversial. This meta-analysis examined the relationships between ER and its antecedent and subsequent correlates. Our review of the literature was generated with 151 empirical studies, containing a total number of 706,937 participants, with a wide range of sample sizes (from N = 27 to N = 127,384 participants) and 380 independent effect sizes (ESs), which included 171 independent samples. A negligible ES value for antecedent correlates of early retirement (family pull, job stress, job satisfaction, and income) was obtained (which ranged from r = −0.13 to 0.19), while a fair ES was obtained for workplace timing for retirement, organizational pressures, financial security, and poor physical and mental health, (ranging from r = 0.28 to 0.25). Regarding ER subsequent correlates, poor ESs were obtained, ranging from r = 0.08 to 0.18 for the relationships with subsequent correlates, and fair ESs only for social engagement (r = −0.25). Examination of the potential moderator variables has been conducted. Only a reduced percentage of variability of primary studies has been explained by moderators. Although potential moderator factors were examined, there are several unknown or not measurable factors which contribute to ER and about which there are very little data available. The discussion is aimed to offer theoretical and empirical implications suggestion in order to improve employee's well-being. PMID:29354075

Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis.

PubMed

Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

2016-08-18

The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

Four- and five-factor models of the WAIS-IV in a clinical sample: Variations in indicator configuration and factor correlational structure.

PubMed

Staffaroni, Adam M; Eng, Megan E; Moses, James A; Zeiner, Harriet Katz; Wickham, Robert E

2018-05-01

A growing body of research supports the validity of 5-factor models for interpreting the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV). The majority of these studies have utilized the WAIS-IV normative or clinical sample, the latter of which differs in its diagnostic composition from the referrals seen at outpatient neuropsychology clinics. To address this concern, 2 related studies were conducted on a sample of 322 American military Veterans who were referred for outpatient neuropsychological assessment. In Study 1, 4 hierarchical models with varying indicator configurations were evaluated: 3 extant 5-factor models from the literature and the traditional 4-factor model. In Study 2, we evaluated 3 variations in correlation structure in the models from Study 1: indirect hierarchical (i.e., higher-order g), bifactor (direct hierarchical), and oblique models. The results from Study 1 suggested that both 4- and 5-factor models showed acceptable fit. The results from Study 2 showed that bifactor and oblique models offer improved fit over the typically specified indirect hierarchical model, and the oblique models outperformed the orthogonal bifactor models. An exploratory analysis found improved fit when bifactor models were specified with oblique rather than orthogonal latent factors. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

Analytic uncertainty and sensitivity analysis of models with input correlations

NASA Astrophysics Data System (ADS)

Zhu, Yueying; Wang, Qiuping A.; Li, Wei; Cai, Xu

2018-03-01

Probabilistic uncertainty analysis is a common means of evaluating mathematical models. In mathematical modeling, the uncertainty in input variables is specified through distribution laws. Its contribution to the uncertainty in model response is usually analyzed by assuming that input variables are independent of each other. However, correlated parameters are often happened in practical applications. In the present paper, an analytic method is built for the uncertainty and sensitivity analysis of models in the presence of input correlations. With the method, it is straightforward to identify the importance of the independence and correlations of input variables in determining the model response. This allows one to decide whether or not the input correlations should be considered in practice. Numerical examples suggest the effectiveness and validation of our analytic method in the analysis of general models. A practical application of the method is also proposed to the uncertainty and sensitivity analysis of a deterministic HIV model.

Application of the Gini correlation coefficient to infer regulatory relationships in transcriptome analysis.

PubMed

Ma, Chuang; Wang, Xiangfeng

2012-09-01

One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey's biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses.

[Correlation analysis of bone marrow edema degree and serum inflammatory factors change with knee joint pain symptoms in patients with bone contusion around the knee joint].

PubMed

Li, Songiun; An, Rongze; Wang, Zhaojie; Kuang, Lipeng; Tan, Weiyuan; Fang, Cunxun

2014-05-01

To explore the correlation between the degree of bone marrow edema (BME) and the content change of tumor necrosis factor alpha (TNF-alpha) and matrix metalloproteinase 3 (MMP-3) and the knee pain symptoms in patients with bone contusion around the knee joint. Thirty patients (30 knees) of bone contusion around the knee joint were chosen as the trial group between October 2009 and April 2012. According to visual analogue scale (VAS), 30 patients were divided into mild group (10 cases), moderate group (10 cases), and severe group (10 cases); according to MRI morphological changes, the patients were divided into type I group (12 cases), type II group (11 cases), and type III group (7 cases). Ten patients (10 knees) with soft tissue injury of the knee were chosen as control group. No significant difference was found (P > 0.05) in gender, age, causes, side, and admission time after injury between 2 groups. The serum contents of MMP-3 and TNF-alpha were detected and statistically analysed between different degrees of pain groups and between different degrees of BME groups. Correlation was analysed between BME and inflammatory factor changes and VAS score. The MMP-3 and TNF-alpha contents in trial group [(29.580 +/- 6.870) (microg/L and (23.750 +/- 7.096) ng/L] were significantly higher than those in control group [(8.219 +/- 1.355) microg/L and (6.485 +/- 1.168) ng/L] (t = 9.686, P = 0.000; t = 7.596, P =0.000). The MMP-3 and TNF-alpha contents in patients with different degrees of pain and BME were significantly higher than those in patients of control group (P < 0.05), and significant difference was found between patients with different degrees of pain (P < 0.05), but no significant difference between patients with different degrees of BME (P > 0.05). Multiple linear regression analysis showed that TNF-alpha content was significantly correlated with VAS score (P = 0.000). Knee pain symptoms are not related to the degree of BME in patients with bone contusion around the

Weighted network analysis of high-frequency cross-correlation measures

NASA Astrophysics Data System (ADS)

Iori, Giulia; Precup, Ovidiu V.

2007-03-01

In this paper we implement a Fourier method to estimate high-frequency correlation matrices from small data sets. The Fourier estimates are shown to be considerably less noisy than the standard Pearson correlation measures and thus capable of detecting subtle changes in correlation matrices with just a month of data. The evolution of correlation at different time scales is analyzed from the full correlation matrix and its minimum spanning tree representation. The analysis is performed by implementing measures from the theory of random weighted networks.

[Correlation factors of 127 times pre-crisis state in patients with myasthenia gravis].

PubMed

Ou, C Y; Ran, H; Qiu, L; Huang, Z D; Lin, Z Z; Deng, J; Liu, W B

2017-10-10

Objective: To investigate the clinical features of the Pre-Crisis State and analyze the correlated risk factors of Pre-Crisis State of myasthenia crisis. Methods: We included 93 patients with myasthenia gravis (MG) who experienced 127 times Pre-Crisis State between October 2007 and July 2016. Those patients were hospitalized in the MG specialize center, Department of Neurological Science, first Affiliated Hospital of Sun Yat-sen University. The information of the general situation, the clinical manifestations and the blood gas analysis in those patients were collected using our innovated clinical research form. Statistic methods were applied including descriptive analysis, univariate logistic analysis, multivariate correlation logistic analysis, etc. Results: (1)The typical features of MG Pre-Crisis State included: dyspnea (127 times, 100% not requiring intubation or non-invasive ventilation), bulbar-muscle weakness (121 times, 95.28%), the increased blood partial pressure of carbon dioxide (PCO(2)) (94 times, 85.45%), expectoration weakness (99 times, 77.95%), sleep disorders (107 times, 84.25%) and the infection (99 times, 77.95%). The occurrence of dyspnea in combination with bulbar-muscle weakness ( P =0.002) or the increased blood PCO(2) ( P =0.042) often indicated the tendency of crisis. (2) The MG symptoms which were proportion to the occurrence of crisis includes: bulbar-muscle weakness ( P =0.028), fever ( P =0.028), malnutrition ( P =0.066), complications ( P =0.071), excess oropharyngeal secretions ( P =0.005) and the increased blood PCO(2) ( P =0.007). The perioperative period of thymectomy would not increase the risk of crisis. Conclusions: Dyspnea indicates the occurrence of the Pre-Crisis State of MG. In order to significantly reduce the morbidity of myasthenia crisis, the bulbar-muscle weakness, the increased blood PCO(2), expectoration weakness, sleep disorders, infection & fever and excess oropharyngeal secretions should be treated timely.

University student depression inventory (USDI): confirmatory factor analysis and review of psychometric properties.

PubMed

Romaniuk, Madeline; Khawaja, Nigar G

2013-09-25

The 30-item USDI is a self-report measure that assesses depressive symptoms among university students. It consists of three correlated three factors: lethargy, cognitive-emotional and academic motivation. The current research used confirmatory factor analysis to asses construct validity and determine whether the original factor structure would be replicated in a different sample. Psychometric properties were also examined. Participants were 1148 students (mean age 22.84 years, SD=6.85) across all faculties from a large Australian metropolitan university. Students completed a questionnaire comprising of the USDI, the depression anxiety stress scale (DASS) and Life Satisfaction Scale (LSS). The three correlated factor model was shown to be an acceptable fit to the data, indicating sound construct validity. Internal consistency of the scale was also demonstrated to be sound, with high Cronbach alpha values. Temporal stability of the scale was also shown to be strong through test-retest analysis. Finally, concurrent and discriminant validity was examined with correlations between the USDI and DASS subscales as well as the LSS, with sound results further supporting the construct validity of the scale. Cut-off points were also developed to aid total score interpretation. Response rates are unclear. In addition, the representativeness of the sample could be improved potentially through targeted recruitment (i.e. reviewing the online sample statistics during data collection, examining the representativeness trends and addressing particular faculties within the university that were underrepresented). The USDI provides a valid and reliable method of assessing depressive symptoms found among university students. © 2013 Elsevier B.V. All rights reserved.

Quantitative immunohistochemistry of factor VIII-related antigen in breast carcinoma: a comparison of computer-assisted image analysis with established counting methods.

PubMed

Kohlberger, P D; Obermair, A; Sliutz, G; Heinzl, H; Koelbl, H; Breitenecker, G; Gitsch, G; Kainz, C

1996-06-01

Microvessel density in the area of the most intense neovascularization in invasive breast carcinoma is reported to be an independent prognostic factor. The established method of enumeration of microvessel density is to count the vessels using an ocular raster (counted microvessel density [CMVD]). The vessels were detected by staining endothelial cells using Factor VIII-related antigen. The aim of the study was to compare the CMVD results with the percentage of factor VIII-related antigen-stained area using computer-assisted image analysis. A true color red-green-blue (RGB) image analyzer based on a morphologically reduced instruction set computer processor was used to evaluate the area of stained endothelial cells. Sixty invasive breast carcinomas were included in the analysis. There was no significant correlation between the CMVD and the percentage of factor VIII-related antigen-stained area (Spearman correlation coefficient = 0.24, confidence interval = 0.02-0.46). Although high CMVD was significantly correlated with poorer recurrence free survival (P = .024), percentage of factor VIII-related antigen-stained area showed no prognostic value. Counted microvessel density and percentage of factor VIII-related antigen-stained area showed a highly significant correlation with vessel invasion (P = .0001 and P = .02, respectively). There was no correlation between CMVD and percentage of factor VIII-related antigen-stained area with other prognostic factors. In contrast to the CMVD within malignant tissue, the percentage of factor VIII-related antigen-stained area is not suitable as an indicator of prognosis in breast cancer patients.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Complex-valued time-series correlation increases sensitivity in FMRI analysis.

PubMed

Kociuba, Mary C; Rowe, Daniel B

2016-07-01

To develop a linear matrix representation of correlation between complex-valued (CV) time-series in the temporal Fourier frequency domain, and demonstrate its increased sensitivity over correlation between magnitude-only (MO) time-series in functional MRI (fMRI) analysis. The standard in fMRI is to discard the phase before the statistical analysis of the data, despite evidence of task related change in the phase time-series. With a real-valued isomorphism representation of Fourier reconstruction, correlation is computed in the temporal frequency domain with CV time-series data, rather than with the standard of MO data. A MATLAB simulation compares the Fisher-z transform of MO and CV correlations for varying degrees of task related magnitude and phase amplitude change in the time-series. The increased sensitivity of the complex-valued Fourier representation of correlation is also demonstrated with experimental human data. Since the correlation description in the temporal frequency domain is represented as a summation of second order temporal frequencies, the correlation is easily divided into experimentally relevant frequency bands for each voxel's temporal frequency spectrum. The MO and CV correlations for the experimental human data are analyzed for four voxels of interest (VOIs) to show the framework with high and low contrast-to-noise ratios in the motor cortex and the supplementary motor cortex. The simulation demonstrates the increased strength of CV correlations over MO correlations for low magnitude contrast-to-noise time-series. In the experimental human data, the MO correlation maps are noisier than the CV maps, and it is more difficult to distinguish the motor cortex in the MO correlation maps after spatial processing. Including both magnitude and phase in the spatial correlation computations more accurately defines the correlated left and right motor cortices. Sensitivity in correlation analysis is important to preserve the signal of interest in f

Orbital angiogenesis and lymphangiogenesis in thyroid eye disease: an analysis of vascular growth factors with clinical correlation

PubMed Central

Wong, Lindsay L.; Lee, Nahyoung Grace; Amarnani, Dhanesh; Choi, Catherine J.; Bielenberg, Diane R.; Freitag, Suzanne K.; D’Amore, Patricia A.; Kim, Leo A.

2017-01-01

Purpose The human orbit is an environment that is vulnerable to inflammation and edema in the setting of autoimmune thyroid disease. Our study investigated the tenet that orbital adipose tissue lacks lymphatic vessels and analyzed the clinicopathologic differences between patients with acute and chronic thyroid eye disease (TED). The underlying molecular mediators of blood and lymphatic vessel formation within the orbital fat were also evaluated. Design Retrospective cohort study Participants The study included fat specimens from 26 orbits of 15 patients with TED undergoing orbital decompression. Orbital fat specimens from patients without TED as well as cadaveric orbital fat served as controls. Methods Tissue specimens were processed as formalin-fixed paraffin-embedded sections (FFPE) or frozen cryosections for immunohistochemistry. Total RNA was extracted and analyzed via quantitative (real-time) reverse transcription polymerase chain reaction (qRT-PCR). Clinicopathological correlation was made by determining the Clinical Activity Score (CAS) of each patient with TED. Main Outcome Measures Samples were examined for vascular and lymphatic markers including podoplanin, LYVE-1, and CD31 by immunohistochemistry, as well as for mRNA levels of VEGF, VEGF receptors, SEMA-3F, NRP-1, NRP-2, podoplanin and LYVE-1 by qRT-PCR. Results Clinicopathological correlation revealed increased staining of CD31-positive blood vessels in patients with acute TED with CAS > 4, as well as rare staining of podoplanin-positive lymphatic vessels within acutely inflamed orbital fat tissue. Additionally, qRT-PCR analysis demonstrated increased expression of vascular endothelial growth factor receptor 2 (VEGFR-2) as well as VEGF signaling molecules: VEGF-A, VEGF-C, and VEGF-D. Conclusions In acute TED, compared to chronic TED and control orbital fat, there is increased blood vessel density suggesting neovascularization and rare lymphatic vessels suggestive of limited lymphangiogenesis. This pro

Exploring the Factors Contributing to Sibling Correlations in BMI: A Study Using the Panel Study of Income Dynamics

PubMed Central

Brown, Heather W.; Roberts, Jennifer

2012-01-01

Understanding the mechanisms contributing to correlated BMI outcomes in a social network such as siblings will help policy makers reduce the burden of disease associated with obesity. There are two potential mechanisms explaining correlated BMI outcomes in a biologically related social network: (i) time constant factors such as genetic heritability and habits formed during childhood and (ii) factors that change over time some of which are dependent on the frequency of interactions between the social network, for example, social norms shaped by the social network's shifting attitudes towards weight and behaviors related to weight, or environmental factors like opportunities for exercise. This study aims to distinguish between time constant factors from factors that are likely to change over time to gain a better understanding of the mechanisms explaining the correlation in sibling BMI. We exploit data from the Panel Study of Income Dynamics (PSID) over 1999–2007 estimating the correlation in BMI for adult siblings who currently live in separate households but grew-up in the same household and adolescent siblings currently living in the same household to isolate the influence of factors that change over time. The findings indicate that time constant factors explain some of the overall correlation in sibling BMI for both cohorts of siblings. Factors that change over time only significantly impact on the overall correlation in BMI for adolescent siblings suggesting if there is a social network influence on correlations in BMI this is facilitated by sharing the same household. PMID:22173572

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.

Multifractal detrending moving-average cross-correlation analysis

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Zhou, Wei-Xing

2011-07-01

There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross correlations. The multifractal detrended cross-correlation analysis (MFDCCA) approaches can be used to quantify such cross correlations, such as the MFDCCA based on the detrended fluctuation analysis (MFXDFA) method. We develop in this work a class of MFDCCA algorithms based on the detrending moving-average analysis, called MFXDMA. The performances of the proposed MFXDMA algorithms are compared with the MFXDFA method by extensive numerical experiments on pairs of time series generated from bivariate fractional Brownian motions, two-component autoregressive fractionally integrated moving-average processes, and binomial measures, which have theoretical expressions of the multifractal nature. In all cases, the scaling exponents hxy extracted from the MFXDMA and MFXDFA algorithms are very close to the theoretical values. For bivariate fractional Brownian motions, the scaling exponent of the cross correlation is independent of the cross-correlation coefficient between two time series, and the MFXDFA and centered MFXDMA algorithms have comparative performances, which outperform the forward and backward MFXDMA algorithms. For two-component autoregressive fractionally integrated moving-average processes, we also find that the MFXDFA and centered MFXDMA algorithms have comparative performances, while the forward and backward MFXDMA algorithms perform slightly worse. For binomial measures, the forward MFXDMA algorithm exhibits the best performance, the centered MFXDMA algorithms performs worst, and the backward MFXDMA algorithm outperforms the MFXDFA algorithm when the moment order q<0 and underperforms when q>0. We apply these algorithms to the return time series of two stock market indexes and to their volatilities. For the returns, the centered MFXDMA algorithm gives the best estimates of hxy(q) since its hxy(2) is closest to 0

Medical University admission test: a confirmatory factor analysis of the results.

PubMed

Luschin-Ebengreuth, Marion; Dimai, Hans P; Ithaler, Daniel; Neges, Heide M; Reibnegger, Gilbert

2016-05-01

The Graz Admission Test has been applied since the academic year 2006/2007. The validity of the Test was demonstrated by a significant improvement of study success and a significant reduction of dropout rate. The purpose of this study was a detailed analysis of the internal correlation structure of the various components of the Graz Admission Test. In particular, the question investigated was whether or not the various test parts constitute a suitable construct which might be designated as "Basic Knowledge in Natural Science." This study is an observational investigation, analyzing the results of the Graz Admission Test for the study of human medicine and dentistry. A total of 4741 applicants were included in the analysis. Principal component factor analysis (PCFA) as well as techniques from structural equation modeling, specifically confirmatory factor analysis (CFA), were employed to detect potential underlying latent variables governing the behavior of the measured variables. PCFA showed good clustering of the science test parts, including also text comprehension. A putative latent variable "Basic Knowledge in Natural Science," investigated by CFA, was indeed shown to govern the response behavior of the applicants in biology, chemistry, physics, and mathematics as well as text comprehension. The analysis of the correlation structure of the various test parts confirmed that the science test parts together with text comprehension constitute a satisfactory instrument for measuring a latent construct variable "Basic Knowledge in Natural Science." The present results suggest the fundamental importance of basic science knowledge for results obtained in the framework of the admission process for medical universities.

Effects of different correlation metrics and preprocessing factors on small-world brain functional networks: a resting-state functional MRI study.

PubMed

Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

2012-01-01

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01-0.027 Hz) versus slow-4 (0.027-0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the "best" network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027-0.073 Hz band exhibited greater reliability than those in the 0.01-0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics and specific

Effects of Different Correlation Metrics and Preprocessing Factors on Small-World Brain Functional Networks: A Resting-State Functional MRI Study

PubMed Central

Liang, Xia; Wang, Jinhui; Yan, Chaogan; Shu, Ni; Xu, Ke; Gong, Gaolang; He, Yong

2012-01-01

Graph theoretical analysis of brain networks based on resting-state functional MRI (R-fMRI) has attracted a great deal of attention in recent years. These analyses often involve the selection of correlation metrics and specific preprocessing steps. However, the influence of these factors on the topological properties of functional brain networks has not been systematically examined. Here, we investigated the influences of correlation metric choice (Pearson's correlation versus partial correlation), global signal presence (regressed or not) and frequency band selection [slow-5 (0.01–0.027 Hz) versus slow-4 (0.027–0.073 Hz)] on the topological properties of both binary and weighted brain networks derived from them, and we employed test-retest (TRT) analyses for further guidance on how to choose the “best” network modeling strategy from the reliability perspective. Our results show significant differences in global network metrics associated with both correlation metrics and global signals. Analysis of nodal degree revealed differing hub distributions for brain networks derived from Pearson's correlation versus partial correlation. TRT analysis revealed that the reliability of both global and local topological properties are modulated by correlation metrics and the global signal, with the highest reliability observed for Pearson's-correlation-based brain networks without global signal removal (WOGR-PEAR). The nodal reliability exhibited a spatially heterogeneous distribution wherein regions in association and limbic/paralimbic cortices showed moderate TRT reliability in Pearson's-correlation-based brain networks. Moreover, we found that there were significant frequency-related differences in topological properties of WOGR-PEAR networks, and brain networks derived in the 0.027–0.073 Hz band exhibited greater reliability than those in the 0.01–0.027 Hz band. Taken together, our results provide direct evidence regarding the influences of correlation metrics

DGCA: A comprehensive R package for Differential Gene Correlation Analysis.

PubMed

McKenzie, Andrew T; Katsyv, Igor; Song, Won-Min; Wang, Minghui; Zhang, Bin

2016-11-15

Dissecting the regulatory relationships between genes is a critical step towards building accurate predictive models of biological systems. A powerful approach towards this end is to systematically study the differences in correlation between gene pairs in more than one distinct condition. In this study we develop an R package, DGCA (for Differential Gene Correlation Analysis), which offers a suite of tools for computing and analyzing differential correlations between gene pairs across multiple conditions. To minimize parametric assumptions, DGCA computes empirical p-values via permutation testing. To understand differential correlations at a systems level, DGCA performs higher-order analyses such as measuring the average difference in correlation and multiscale clustering analysis of differential correlation networks. Through a simulation study, we show that the straightforward z-score based method that DGCA employs significantly outperforms the existing alternative methods for calculating differential correlation. Application of DGCA to the TCGA RNA-seq data in breast cancer not only identifies key changes in the regulatory relationships between TP53 and PTEN and their target genes in the presence of inactivating mutations, but also reveals an immune-related differential correlation module that is specific to triple negative breast cancer (TNBC). DGCA is an R package for systematically assessing the difference in gene-gene regulatory relationships under different conditions. This user-friendly, effective, and comprehensive software tool will greatly facilitate the application of differential correlation analysis in many biological studies and thus will help identification of novel signaling pathways, biomarkers, and targets in complex biological systems and diseases.

Motivational Basis of Personality Traits: A Meta-Analysis of Value-Personality Correlations.

PubMed

Fischer, Ronald; Boer, Diana

2015-10-01

We investigated the relationships between personality traits and basic value dimensions. Furthermore, we developed novel country-level hypotheses predicting that contextual threat moderates value-personality trait relationships. We conducted a three-level v-known meta-analysis of correlations between Big Five traits and Schwartz's (1992) 10 values involving 9,935 participants from 14 countries. Variations in contextual threat (measured as resource threat, ecological threat, and restrictive social institutions) were used as country-level moderator variables. We found systematic relationships between Big Five traits and human values that varied across contexts. Overall, correlations between Openness traits and the Conservation value dimension and Agreeableness traits and the Transcendence value dimension were strongest across all samples. Correlations between values and all personality traits (except Extraversion) were weaker in contexts with greater financial, ecological, and social threats. In contrast, stronger personality-value links are typically found in contexts with low financial and ecological threats and more democratic institutions and permissive social context. These effects explained on average more than 10% of the variability in value-personality correlations. Our results provide strong support for systematic linkages between personality and broad value dimensions, but they also point out that these relations are shaped by contextual factors. © 2014 Wiley Periodicals, Inc.

Correlation of transforming growth factor-β1 and tumour necrosis factor levels with left ventricular function in Chagas disease.

PubMed

Curvo, Eduardo Ov; Ferreira, Roberto R; Madeira, Fabiana S; Alves, Gabriel F; Chambela, Mayara C; Mendes, Veronica G; Sangenis, Luiz Henrique C; Waghabi, Mariana C; Saraiva, Roberto M

2018-02-19

Transforming growth factor β1 (TGF-β1) and tumour necrosis factor (TNF) have been implicated in Chagas disease pathophysiology and may correlate with left ventricular (LV) function. We determined whether TGF-β1 and TNF serum levels correlate with LV systolic and diastolic functions and brain natriuretic peptide (BNP) serum levels in chronic Chagas disease. This cross-sectional study included 152 patients with Chagas disease (43% men; 57 ± 12 years old), classified as 53 patients with indeterminate form and 99 patients with cardiac form (stage A: 24, stage B: 25, stage C: 44, stage D: 6). TGF-β1, TNF, and BNP were determined by enzyme-linked immunosorbent assay ELISA. Echocardiogram was used to determine left atrial and LV diameters, as well as LV ejection fraction and diastolic function. TGF-b1 serum levels were lower in stages B, C, and D, while TNF serum levels were higher in stages C and D of the cardiac form. TGF-β1 presented a weak correlation with LV diastolic function and LV ejection fraction. TNF presented a weak correlation with left atrial and LV diameters and LV ejection fraction. TNF is increased, while TGF-β1 is decreased in the cardiac form of chronic Chagas disease. TNF and TGF-β1 serum levels present a weak correlation with LV systolic and diastolic function in Chagas disease patients.

Familial aggregation and linkage analysis with covariates for metabolic syndrome risk factors.

PubMed

Naseri, Parisa; Khodakarim, Soheila; Guity, Kamran; Daneshpour, Maryam S

2018-06-15

Mechanisms of metabolic syndrome (MetS) causation are complex, genetic and environmental factors are important factors for the pathogenesis of MetS In this study, we aimed to evaluate familial and genetic influences on metabolic syndrome risk factor and also assess association between FTO (rs1558902 and rs7202116) and CETP(rs1864163) genes' single nucleotide polymorphisms (SNP) with low HDL_C in the Tehran Lipid and Glucose Study (TLGS). The design was a cross-sectional study of 1776 members of 227 randomly-ascertained families. Selected families contained at least one affected metabolic syndrome and at least two members of the family had suffered a loss of HDL_C according to ATP III criteria. In this study, after confirming the familial aggregation with intra-trait correlation coefficients (ICC) of Metabolic syndrome (MetS) and the quantitative lipid traits, the genetic linkage analysis of HDL_C was performed using conditional logistic method with adjusted sex and age. The results of the aggregation analysis revealed a higher correlation between siblings than between parent-offspring pairs representing the role of genetic factors in MetS. In addition, the conditional logistic model with covariates showed that the linkage results between HDL_C and three marker, rs1558902, rs7202116 and rs1864163 were significant. In summary, a high risk of MetS was found in siblings confirming the genetic influences of metabolic syndrome risk factor. Moreover, the power to detect linkage increases in the one parameter conditional logistic model regarding the use of age and sex as covariates. Copyright © 2018. Published by Elsevier B.V.

Clinical correlation to differences in ranibizumab and aflibercept vascular endothelial growth factor suppression times.

PubMed

Fauser, Sascha; Muether, Philipp S

2016-11-01

To determine clinical correlations to intraocular vascular endothelial growth factor A (VEGF-A) suppression times (VSTs) on the treatment of neovascular age-related macular degeneration (nAMD) with ranibizumab (Lucentis) or aflibercept (Eylea). Seven of 89 treatment-naïve nAMD eyes showed persistent choroidal neovascular membrane (CNV) activity throughout a spectral domain optical coherence tomography (SD-OCT)-driven pro re nata (PRN) regimen of intravitreal ranibizumab injections over 28±4 months. The treatment was switched to PRN aflibercept injections and patients were followed for another 15±2 months. A total of 160 aqueous humour specimens were collected before the intravitreal injections, and their VEGF-A concentrations were assayed by Luminex multiplex bead analysis (Luminex, Austin, Texas, USA). Intraocular VEGF-A concentrations were correlated to CNV activity shown by SD-OCT. The mean duration of suppression of VEGF-A concentrations in aqueous humour below the lower limit of quantification of our assay was 34±5 (26-69) days for ranibizumab and 67±14 (49-89) days for aflibercept (p<0.001). The percentual reduction of central retinal volume (CRV) 6 weeks after injection was higher for aflibercept compared with ranibizumab (p=0.009). The time point of clinical re-activity occurred about 50% earlier than the respective VST for each ranibizumab and aflibercept. The VST under aflibercept treatment exceeded that under ranibizumab treatment by a factor of 2. This difference correlated with differential clinical CRV reduction 6 weeks after the respective injection. For both medications, clinical activity was found at a time point as early as 50% of the individual VST. NCT01213667, post-results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Within-Subject Correlation Analysis to Detect Functional Areas Associated With Response Inhibition.

PubMed

Yamasaki, Tomoko; Ogawa, Akitoshi; Osada, Takahiro; Jimura, Koji; Konishi, Seiki

2018-01-01

Functional areas in fMRI studies are often detected by brain-behavior correlation, calculating across-subject correlation between the behavioral index and the brain activity related to a function of interest. Within-subject correlation analysis is also employed in a single subject level, which utilizes cognitive fluctuations in a shorter time period by correlating the behavioral index with the brain activity across trials. In the present study, the within-subject analysis was applied to the stop-signal task, a standard task to probe response inhibition, where efficiency of response inhibition can be evaluated by the stop-signal reaction time (SSRT). Since the SSRT is estimated, by definition, not in a trial basis but from pooled trials, the correlation across runs was calculated between the SSRT and the brain activity related to response inhibition. The within-subject correlation revealed negative correlations in the anterior cingulate cortex and the cerebellum. Moreover, the dissociation pattern was observed in the within-subject analysis when earlier vs. later parts of the runs were analyzed: negative correlation was dominant in earlier runs, whereas positive correlation was dominant in later runs. Regions of interest analyses revealed that the negative correlation in the anterior cingulate cortex, but not in the cerebellum, was dominant in earlier runs, suggesting multiple mechanisms associated with inhibitory processes that fluctuate on a run-by-run basis. These results indicate that the within-subject analysis compliments the across-subject analysis by highlighting different aspects of cognitive/affective processes related to response inhibition.

Factor analysis of the contextual fine motor questionnaire in children.

PubMed

Lin, Chin-Kai; Meng, Ling-Fu; Yu, Ya-Wen; Chen, Che-Kuo; Li, Kuan-Hua

2014-02-01

Most studies treat fine motor as one subscale in a developmental test, hence, further factor analysis of fine motor has not been conducted. In fact, fine motor has been treated as a multi-dimensional domain from both clinical and theoretical perspectives, and therefore to know its factors would be valuable. The aim of this study is to analyze the internal consistency and factor validity of the Contextual Fine Motor Questionnaire (CFMQ). Based on the ecological observation and literature, the Contextual Fine Motor Questionnaire (CFMQ) was developed and includes 5 subscales: Pen Control, Tool Use During Handicraft Activities, the Use of Dining Utensils, Connecting and Separating during Dressing and Undressing, and Opening Containers. The main purpose of this study is to establish the factorial validity of the CFMQ through conducting this factor analysis study. Among 1208 questionnaires, 904 were successfully completed. Data from the children's CFMQ submitted by primary care providers was analyzed, including 485 females (53.6%) and 419 males (46.4%) from grades 1 to 5, ranging in age from 82 to 167 months (M=113.9, SD=16.3). Cronbach's alpha was used to measure internal consistency and explorative factor analysis was applied to test the five factor structures within the CFMQ. Results showed that Cronbach's alpha coefficient of the CFMQ for 5 subscales ranged from .77 to .92 and all item-total correlations with corresponding subscales were larger than .4 except one item. The factor loading of almost all items classified to their factor was larger than .5 except 3 items. There were five factors, explaining a total of 62.59% variance for the CFMQ. In conclusion, the remaining 24 items in the 5 subscales of the CFMQ had appropriate internal consistency, test-retest reliability and construct validity. Copyright © 2013 Elsevier Ltd. All rights reserved.

Combined target factor analysis and Bayesian soft-classification of interference-contaminated samples: forensic fire debris analysis.

PubMed

Williams, Mary R; Sigman, Michael E; Lewis, Jennifer; Pitan, Kelly McHugh

2012-10-10

A bayesian soft classification method combined with target factor analysis (TFA) is described and tested for the analysis of fire debris data. The method relies on analysis of the average mass spectrum across the chromatographic profile (i.e., the total ion spectrum, TIS) from multiple samples taken from a single fire scene. A library of TIS from reference ignitable liquids with assigned ASTM classification is used as the target factors in TFA. The class-conditional distributions of correlations between the target and predicted factors for each ASTM class are represented by kernel functions and analyzed by bayesian decision theory. The soft classification approach assists in assessing the probability that ignitable liquid residue from a specific ASTM E1618 class, is present in a set of samples from a single fire scene, even in the presence of unspecified background contributions from pyrolysis products. The method is demonstrated with sample data sets and then tested on laboratory-scale burn data and large-scale field test burns. The overall performance achieved in laboratory and field test of the method is approximately 80% correct classification of fire debris samples. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Examining the correlates of the coldheartedness factor of the Psychopathic Personality Inventory-Revised.

PubMed

Berg, Joanna M; Hecht, Lisa K; Latzman, Robert D; Lilienfeld, Scott O

2015-12-01

Coldheartedness is a subscale of the Psychopathic Personality Inventory-Revised (PPI-R) that does not load onto either of the PPI-R's two traditional higher order factors (Fearless Dominance [FD] and Self-Centered Impulsivity [SCI]). As a result, it has been omitted from analyses in many studies. However, owing to Coldheartedness's associations with lack of empathy, guilt, and deep-seated social emotions, this subscale may be highly relevant to the construct of psychopathy. In a sample of 1,158 undergraduates, we attempted to clarify Coldheartedness's correlates within the context of a nomological network of psychopathology and personality; in addition, we examined Coldheartedness's contributions to psychopathy above and beyond FD and SCI. Coldheartedness demonstrated negative correlations with the Big Five personality factors, mixed correlations with indices of impulsivity, and largely negative correlations with measures of depression and anxiety. Regressions suggested that Coldheartedness displays substantial overlap with both FD and SCI but also contains psychologically important unique variance. Although the nature of this variance requires clarification, further research and perhaps an expansion of the Coldheartedness subscale may move the field toward a clearer understanding of the construct assessed by this measure. (c) 2015 APA, all rights reserved).

Connections between Graphical Gaussian Models and Factor Analysis

ERIC Educational Resources Information Center

Salgueiro, M. Fatima; Smith, Peter W. F.; McDonald, John W.

2010-01-01

Connections between graphical Gaussian models and classical single-factor models are obtained by parameterizing the single-factor model as a graphical Gaussian model. Models are represented by independence graphs, and associations between each manifest variable and the latent factor are measured by factor partial correlations. Power calculations…

Temporal Stability, Correlates, and Longitudinal Outcomes of Career Indecision Factors

ERIC Educational Resources Information Center

Nauta, Margaret M.

2012-01-01

A confirmatory factor analysis (CFA) tested the fit of Kelly and Lee's six-factor model of career decision problems among 188 college students. The six-factor model did not fit the data well, but a five-factor (Lack of Information, Need for Information, Trait Indecision, Disagreement with Others, and Choice Anxiety) model did provide a good fit.…

Correlation of adiposity indices with cardiovascular disease risk factors in healthy adults of Singapore: a cross-sectional study.

PubMed

Bi, Xinyan; Tey, Siew Ling; Leong, Claudia; Quek, Rina; Loo, Yi Ting; Henry, Christiani Jeyakumar

2016-01-01

Obesity has long been highlighted for its association with increased incidence of cardiovascular disease (CVD). Nonetheless, the best adiposity indices to evaluate the CVD risk factors remain contentious and few studies have been performed in Asian populations. In the present study, we compared the association strength of percent body fat (PBF) to indirect anthropometric measures of general adiposity (body mass index (BMI) and body adiposity index (BAI)) and central adiposity (waist circumference (WC), and waist-to-hip ratio (WHR)) for the prediction of CVD risk factors in healthy men and women living in Singapore. A total of 125 individuals (63 men and 62 women) took part in this study. PBF was measured by using three different techniques, including bioelectrical impedance analysis (BIA), BOD POD, and dual-energy X-ray absorptiometry (DEXA). Anthropometric measurements (WC, hip circumference (HC), height, and weight), fasting blood glucose (FBG), fasting serum insulin (FSI), and lipid profiles were determined according to standard protocols. Correlations of anthropometric measurements and PBF with CVD risk factors were compared. Irrespective of the measuring techniques, PBF showed strong positive correlations with FSI, HOMA-IR, TC/HDL, TG/HDL, and LDL/HDL in both genders. While PBF was highly correlated with FBG, SBP, and DBP in females, no significant relationships were observed in males. Amongst the five anthropometric measures of adiposity, BAI was the best predictor for CVD risk factors in female participants (r = 0.593 for HOMA-IR, r = 0.542 for TG/HDL, r = 0.474 for SBP, and r = 0.448 for DBP). For males, the combination of WC (r = 0.629 for HOMA-IR, and r = 0.446 for TG/HDL) and WHR (r = 0.352 for SBP, and r = 0.366 for DBP) had the best correlation with CVD risk factors. Measurement of PBF does not outperform the simple anthropometric measurements of obesity, i.e. BAI, WC, and WHR, in the prediction of CVD risk factors in

[Correlation analysis between residual displacement and hip function after reconstruction of acetabular fractures].

PubMed

Ma, Kunlong; Fang, Yue; Luan, Fujun; Tu, Chongqi; Yang, Tianfu

2012-03-01

To investigate the relationships between residual displacement of weight-bearing and non weight-bearing zones (gap displacement and step displacement) and hip function by analyzing the CT images after reconstruction of acetabular fractures. The CT measures and clinical outcome were retrospectively analyzed from 48 patients with displaced acetabular fracture between June 2004 and June 2009. All patients were treated by open reduction and internal fixation, and were followed up 24 to 72 months (mean, 36 months); all fractures healed after operation. The residual displacement involved the weight-bearing zone in 30 cases (weight-bearing group), and involved the non weight-bearing zone in 18 cases (non weight-bearing group). The clinical outcomes were evaluated by Merle d'Aubigné-Postel criteria, and the reduction of articular surface by CT images, including the maximums of two indexes (gap displacement and step displacement). All the data were analyzed in accordance with the Spearman rank correlation coefficient analysis. There was strong negative correlation between the hip function and the residual displacement values in weight-bearing group (r(s) = -0.722, P = 0.001). But there was no correlation between the hip function and the residual displacement values in non weight-bearing group (r(s) = 0.481, P = 0.059). The results of clinical follow-up were similar to the correlation analysis results. In weight-bearing group, the hip function had strong negative correlation with step displacement (r(s) = 0.825, P = 0.002), but it had no correlation with gap displacement (r(s) = 0.577, P = 0.134). In patients with acetabular fracture, the hip function has correlation not only with the extent of the residual displacement but also with the location of the residual displacement, so the residual displacement of weight-bearing zone is a key factor to affect the hip function. In patients with residual displacement in weight-bearing zone, the bigger the step displacement is, the

Risky Business: Factor Analysis of Survey Data – Assessing the Probability of Incorrect Dimensionalisation

PubMed Central

van der Eijk, Cees; Rose, Jonathan

2015-01-01

This paper undertakes a systematic assessment of the extent to which factor analysis the correct number of latent dimensions (factors) when applied to ordered-categorical survey items (so-called Likert items). We simulate 2400 data sets of uni-dimensional Likert items that vary systematically over a range of conditions such as the underlying population distribution, the number of items, the level of random error, and characteristics of items and item-sets. Each of these datasets is factor analysed in a variety of ways that are frequently used in the extant literature, or that are recommended in current methodological texts. These include exploratory factor retention heuristics such as Kaiser’s criterion, Parallel Analysis and a non-graphical scree test, and (for exploratory and confirmatory analyses) evaluations of model fit. These analyses are conducted on the basis of Pearson and polychoric correlations. We find that, irrespective of the particular mode of analysis, factor analysis applied to ordered-categorical survey data very often leads to over-dimensionalisation. The magnitude of this risk depends on the specific way in which factor analysis is conducted, the number of items, the properties of the set of items, and the underlying population distribution. The paper concludes with a discussion of the consequences of over-dimensionalisation, and a brief mention of alternative modes of analysis that are much less prone to such problems. PMID:25789992

Factor analysis and cluster analysis applied to assess the water quality of middle and lower Han River in Central China

NASA Astrophysics Data System (ADS)

Kuo, Yi-Ming; Liu, Wen-Wen

2015-04-01

The Han River basin is one of the most important industrial and grain production bases in the central China. A lot of factories and towns have been established along the river where large farmlands are located nearby. In the last few decades the water quality of the Han River, specifically in middle and lower reaches, has gradually declined. The agricultural nonpoint pollution and municipal and industrial point pollution significantly degrade the water quality of the Han River. Factor analysis can be applied to reduce the dimensionality of a data set consisting of a large number of inter-related variables. Cluster analysis can classify the samples according to their similar characters. In this study, factor analysis is used to identify major pollution indicators, and cluster analysis is employed to classify the samples based on the sample locations and hydrochemical variables. Water samples were collected from 12 sample sites collected from Xiangyang City (middle Han River) to Wuhan City (lower Han River). Correlations among 25 hydrochemical variables are statistically examined. The important pollutants are determined by factor analysis. A three-factor model is determined and explains over 85% of the total river water quality variation. Factor 1, including SS, Chl-a, TN and TP, can be considered as the nonpoint source pollution. Factor 2, including Cl-, Br-, SO42-, Ca2+, Mg2+, K+, Fe2+ and PO43-, can be treated as the industrial pollutant pollution. Factor 3, including F- and NO3-, reflects the influence of the groundwater or self-purification capability of the river water. The various land uses along the Han River correlate well with the pollution types. In addition, the result showed that the water quality of Han River deteriorated gradually from middle to lower Han River. Some tributaries have been seriously polluted and significantly influence the mainstream water quality of the Han River. Finally, the result showed that the nonpoint pollution and the point

Correlated factors in amphibian decline: Exotic species and habitat change in western Washington

USGS Publications Warehouse

Adams, Michael J.

1999-01-01

Amphibian declines may frequently be associated with multiple, correlated factors. In western North America, exotic species and hydrological changes are often correlated and are considered 2 of the greatest threats to freshwater systems. Bullfrog (Rana catesbeiana) introductions are frequently cited as a threat to lentic-breeding anurans native to western North America and are a suspected factor in the decline of red-legged frogs (Rana aurora) in California. Introduced fish and habitat change are cited less frequently but are equally viable hypotheses. I examined the relation among introduced species, habitat, and the distribution and abundance of red-legged frogs in western Washington. Red-legged frog occurrence in the Puget Lowlands was more closely associated with habitat structure and the presence of exotic fish than with the presence of bull-frogs. The spread of exotics is correlated with a shift toward greater permanence in wetland habitats regionally. Conservation of more ephemeral wetland habitats may have direct benefits for some native amphibians and may also reduce the threat of exotic fish and bullfrogs, both of which were associated with permanent wetlands. Research and conservation efforts for lowland anurans in the West should emphasize the complexities of multiple contributing factors to amphibian losses.

Correlation of transforming growth factor-β1 and tumour necrosis factor levels with left ventricular function in Chagas disease

PubMed Central

Curvo, Eduardo OV; Ferreira, Roberto R; Madeira, Fabiana S; Alves, Gabriel F; Chambela, Mayara C; Mendes, Veronica G; Sangenis, Luiz Henrique C; Waghabi, Mariana C; Saraiva, Roberto M

2018-01-01

BACKGROUND Transforming growth factor β1 (TGF-β1) and tumour necrosis factor (TNF) have been implicated in Chagas disease pathophysiology and may correlate with left ventricular (LV) function. OBJECTIVES We determined whether TGF-β1 and TNF serum levels correlate with LV systolic and diastolic functions and brain natriuretic peptide (BNP) serum levels in chronic Chagas disease. METHODS This cross-sectional study included 152 patients with Chagas disease (43% men; 57 ± 12 years old), classified as 53 patients with indeterminate form and 99 patients with cardiac form (stage A: 24, stage B: 25, stage C: 44, stage D: 6). TGF-β1, TNF, and BNP were determined by enzyme-linked immunosorbent assay ELISA. Echocardiogram was used to determine left atrial and LV diameters, as well as LV ejection fraction and diastolic function. FINDINGS TGF-b1 serum levels were lower in stages B, C, and D, while TNF serum levels were higher in stages C and D of the cardiac form. TGF-β1 presented a weak correlation with LV diastolic function and LV ejection fraction. TNF presented a weak correlation with left atrial and LV diameters and LV ejection fraction. CONCLUSIONS TNF is increased, while TGF-β1 is decreased in the cardiac form of chronic Chagas disease. TNF and TGF-β1 serum levels present a weak correlation with LV systolic and diastolic function in Chagas disease patients. PMID:29513876

Mother-daughter correlation of central obesity and other noncommunicable disease risk factors: Tehran Lipid and Glucose Study.

PubMed

Heidari, Zahra; Hosseinpanah, Farhad; Barzin, Maryam; Safarkhani, Maryam; Azizi, Fereidoun

2015-03-01

This study aimed to investigate the mother-daughter correlation for central obesity and other noncommunicable disease risk factors. The authors used metabolic and anthropometric data from the Tehran Lipid and Glucose Study, enrolling 1041 mother-daughter pairs for the current study. Three age strata were defined: 3 to 9 years for childhood (146 mother-daughter pairs), 10 to 17 years for adolescence (395 mother-daughter pairs), and 18 to 25 years for early adulthood (500 mother-daughter pairs). Familial associations for central obesity and other noncommunicable disease risk factors were assessed. The prevalence of central obesity was 44.7% in mothers and 11.2% in daughters (6.2% in the 3-9, 19.2% in the 10-17, and 6.4% in the 18-25 years groups). Mothers with central obesity were more likely than nonobese mothers to have daughters with central obesity (10.5% and 1.7%, respectively; P = .0001). Central obesity indices among daughters were positively correlated with those of their mothers in all 3 age strata. Correlations for other noncommunicable disease risk factors were analyzed before and after adjusting the risk factor levels for mothers' and daughters' waist circumferences (WCs) within each group to determine whether risk factor correlations were, in part, a result of the central obesity correlations. After the non-communicable disease risk factor levels of participants were adjusted for their WCs, the mother-daughter correlations remained significant. The consistent association of central obesity between mothers and daughters may indicate the key role that could be played by the mother in the primary prevention of central obesity, particularly in high-risk families. © 2012 APJPH.

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.

Longitudinal Study of Bad Dreams in Preschool-Aged Children: Prevalence, Demographic Correlates, Risk and Protective Factors

PubMed Central

Simard, Valérie; Nielsen, Tore A.; Tremblay, Richard E.; Boivin, Michel; Montplaisir, Jacques Y.

2008-01-01

Study objectives: To (1) clarify the epidemiology of bad dreams in children and investigate risk and protective factors related to (2) the child's sleep, (3) parental sleep-enabling practices, and (4) the child's temperament. Design: Longitudinal with 6 time points from 5 months to 6 years. Setting: Subjects' homes. Participants: Representative sample of 987 children in the Province of Quebec. Interventions: None. Measurements and Results: Longitudinal logistic regression analysis models with primary endpoints of presence or absence of parent-rated bad dreams at 29 months, 41 months, 50 months, 5 years, and 6 years and predictor variables of demographic characteristics, parent ratings of child's sleep characteristics, parental sleep-enabling practices (e.g., cosleeping), and child's psychological characteristics at 5 and 17 months (anxiousness, temperament). Mothers' ratings indicated lower than expected prevalence of frequent bad dreams (1.3% to 3.9%). Demographic correlates of bad dreams were high family income, absence of siblings at 29 months, and a non-immigrant mother. The best predictor at 41 and 50 months was the presence of bad dreams the preceding year, whereas at 5 and 6 years, it was their earlier presence at 29 months. Early protective factors were parental practices favoring emotional nurturance after night awakenings (29 and 41 months); early risk factors were sleep-onset emotional nurturance (29 months), difficult temperament (5 months), and anxiousness (17 months). Conclusions: Bad dreams in preschoolers are less prevalent than thought but, when present, are trait-like in nature and associated with personality characteristics measured as early as 5 months. A stress-diathesis model may best account for the observed pattern of predictive factors. Citation: Simard V; Nielsen TA; Tremblay RE; Boivin M; Montplaisir JY. Longitudinal study of bad dreams in preschool-aged children: prevalence, demographic correlates, risk and protective factors. SLEEP 2008

Factors affecting construction performance: exploratory factor analysis

NASA Astrophysics Data System (ADS)

Soewin, E.; Chinda, T.

2018-04-01

The present work attempts to develop a multidimensional performance evaluation framework for a construction company by considering all relevant measures of performance. Based on the previous studies, this study hypothesizes nine key factors, with a total of 57 associated items. The hypothesized factors, with their associated items, are then used to develop questionnaire survey to gather data. The exploratory factor analysis (EFA) was applied to the collected data which gave rise 10 factors with 57 items affecting construction performance. The findings further reveal that the items constituting ten key performance factors (KPIs) namely; 1) Time, 2) Cost, 3) Quality, 4) Safety & Health, 5) Internal Stakeholder, 6) External Stakeholder, 7) Client Satisfaction, 8) Financial Performance, 9) Environment, and 10) Information, Technology & Innovation. The analysis helps to develop multi-dimensional performance evaluation framework for an effective measurement of the construction performance. The 10 key performance factors can be broadly categorized into economic aspect, social aspect, environmental aspect, and technology aspects. It is important to understand a multi-dimension performance evaluation framework by including all key factors affecting the construction performance of a company, so that the management level can effectively plan to implement an effective performance development plan to match with the mission and vision of the company.

Orbital Angiogenesis and Lymphangiogenesis in Thyroid Eye Disease: An Analysis of Vascular Growth Factors with Clinical Correlation.

PubMed

Wong, Lindsay L; Lee, Nahyoung Grace; Amarnani, Dhanesh; Choi, Catherine J; Bielenberg, Diane R; Freitag, Suzanne K; D'Amore, Patricia A; Kim, Leo A

2016-09-01

The human orbit is an environment that is vulnerable to inflammation and edema in the setting of autoimmune thyroid disease. Our study investigated the tenet that orbital adipose tissue lacks lymphatic vessels and analyzed the clinicopathologic differences between patients with acute and chronic thyroid eye disease (TED). The underlying molecular mediators of blood and lymphatic vessel formation within the orbital fat also were evaluated. Retrospective cohort study. The study included fat specimens from 26 orbits of 15 patients with TED undergoing orbital decompression. Orbital fat specimens from patients without TED as well as cadaveric orbital fat served as controls. Tissue specimens were processed as formalin-fixed, paraffin-embedded sections or frozen cryosections for immunohistochemistry. Total RNA was extracted and analyzed via quantitative (real-time) reverse-transcription polymerase chain reaction. Clinicopathologic correlation was made by determining the clinical activity score (CAS) of each patient with TED. Samples were examined for vascular and lymphatic markers including podoplanin, lymphatic vessel endothelial hyaluronan receptor 1 (LYVE-1), and cluster of differentiation 31 (CD31) by immunohistochemistry, as well as for mRNA levels of vascular endothelial growth factor (VEGF), VEGF receptors, semaphorin 3F, neuropilin 1, neuropilin 2, podoplanin, and LYVE-1 by quantitative (real-time) reverse-transcription polymerase chain reaction. Clinicopathologic correlation revealed increased staining of CD31-positive blood vessels in patients with acute TED with a CAS more than 4, as well as rare staining of podoplanin-positive lymphatic vessels within acutely inflamed orbital fat tissue. Additionally, quantitative (real-time) reverse-transcription polymerase chain reaction analysis demonstrated increased expression of VEGF receptor (VEGFR) 2 as well as VEGF signaling molecules VEGF-A, VEGF-C, and VEGF-D. In acute TED, compared with chronic TED and control

Multifractal detrended cross-correlation analysis for two nonstationary signals.

PubMed

Zhou, Wei-Xing

2008-06-01

We propose a method called multifractal detrended cross-correlation analysis to investigate the multifractal behaviors in the power-law cross-correlations between two time series or higher-dimensional quantities recorded simultaneously, which can be applied to diverse complex systems such as turbulence, finance, ecology, physiology, geophysics, and so on. The method is validated with cross-correlated one- and two-dimensional binomial measures and multifractal random walks. As an example, we illustrate the method by analyzing two financial time series.

Correlation Between Posttraumatic Growth and Posttraumatic Stress Disorder Symptoms Based on Pearson Correlation Coefficient: A Meta-Analysis.

PubMed

Liu, An-Nuo; Wang, Lu-Lu; Li, Hui-Ping; Gong, Juan; Liu, Xiao-Hong

2017-05-01

The literature on posttraumatic growth (PTG) is burgeoning, with the inconsistencies in the literature of the relationship between PTG and posttraumatic stress disorder (PTSD) symptoms becoming a focal point of attention. Thus, this meta-analysis aims to explore the relationship between PTG and PTSD symptoms through the Pearson correlation coefficient. A systematic search of the literature from January 1996 to November 2015 was completed. We retrieved reports on 63 studies that involved 26,951 patients. The weighted correlation coefficient revealed an effect size of 0.22 with a 95% confidence interval of 0.18 to 0.25. Meta-analysis provides evidence that PTG may be positively correlated with PTSD symptoms and that this correlation may be modified by age, trauma type, and time since trauma. Accordingly, people with high levels of PTG should not be ignored, but rather, they should continue to receive help to alleviate their PTSD symptoms.

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

Is Valuing Happiness Associated With Lower Well-Being? A Factor-Level Analysis using the Valuing Happiness Scale

PubMed Central

Luhmann, Maike; Necka, Elizabeth A.; Schönbrodt, Felix D.; Hawkley, Louise C.

2015-01-01

Recent studies suggest that valuing happiness is negatively associated with well-being. Most of these studies used the Valuing Happiness Scale (Mauss, Tamir, et al., 2011). In the present paper, we examined the factor structure of this scale using data pooled from six independent samples (Ntotal = 938). Exploratory and confirmatory factor analysis showed that the Valuing Happiness Scale is not unidimensional and that only one of its three factors correlates negatively with various indicators of well-being, whereas non-significant or positive correlations were found for the other factors. These findings indicate that valuing happiness may not necessarily be bad for one’s well-being, and call for a better definition, theoretical foundation, and operationalization of this construct. PMID:26778865

Personality and patient adherence: correlates of the five-factor model in renal dialysis.

PubMed

Christensen, A J; Smith, T W

1995-06-01

The five-factor taxonomy of personality traits has received increasing attention in the literature regarding personality correlates of health outcomes and behaviors. We examined the association of the five NEO Five-Factor Inventory dimensions to medical regimen adherence in a sample of 72 renal dialysis patients. Results indicated that Conscientiousness (Dimension III) is a five-factor trait significantly associated with adherence to the medication regimen. No other NEO-FFI dimension was significantly associated with patient adherence.

Calculation of the orientational linear and nonlinear correlation factors of polar liquids from the rotational Dean-Kawasaki equation.

PubMed

Déjardin, P M; Cornaton, Y; Ghesquière, P; Caliot, C; Brouzet, R

2018-01-28

A calculation of the Kirkwood and Piekara-Kielich correlation factors of polar liquids is presented using the forced rotational diffusion theory of Cugliandolo et al. [Phys. Rev. E 91, 032139 (2015)]. These correlation factors are obtained as a function of density and temperature. Our results compare reasonably well with the experimental temperature dependence of the linear dielectric constant of some simple polar liquids across a wide temperature range. A comparison of our results for the linear dielectric constant and the Kirkwood correlation factor with relevant numerical simulations of liquid water and methanol is given.

Confirmatory Factor Analysis of the Finnish Job Content Questionnaire (JCQ) in 590 Professional Musicians.

PubMed

Vastamäki, Heidi; Vastamäki, Martti; Laimi, Katri; Saltychev, Michail

2017-07-01

Poorly functioning work environments may lead to dissatisfaction for the employees and financial loss for the employers. The Job Content Questionnaire (JCQ) was designed to measure social and psychological characteristics of work environments. To investigate the factor construct of the Finnish 14-item version of JCQ when applied to professional orchestra musicians. In a cross-sectional survey, the questionnaire was sent by mail to 1550 orchestra musicians and students. 630 responses were received. Full data were available for 590 respondents (response rate 38%).The questionnaire also contained questions on demographics, job satisfaction, health status, health behaviors, and intensity of playing music. Confirmatory factor analysis of the 2-factor model of JCQ was conducted. Of the 5 estimates, JCQ items in the "job demand" construct, the "conflicting demands" (question 5) explained most of the total variance in this construct (79%) demonstrating almost perfect correlation of 0.63. In the construct of "job control," "opinions influential" (question 10) demonstrated a perfect correlation index of 0.84 and the items "little decision freedom" (question 14) and "allows own decisions" (question 6) showed substantial correlations of 0.77 and 0.65. The 2-factor model of the Finnish 14-item version of JCQ proposed in this study fitted well into the observed data. The "conflicting demands," "opinions influential," "little decision freedom," and "allows own decisions" items demonstrated the strongest correlations with latent factors suggesting that in a population similar to the studied one, especially these items should be taken into account when observed in the response of a population.

Development of Test-Analysis Models (TAM) for correlation of dynamic test and analysis results

NASA Technical Reports Server (NTRS)

Angelucci, Filippo; Javeed, Mehzad; Mcgowan, Paul

1992-01-01

The primary objective of structural analysis of aerospace applications is to obtain a verified finite element model (FEM). The verified FEM can be used for loads analysis, evaluate structural modifications, or design control systems. Verification of the FEM is generally obtained as the result of correlating test and FEM models. A test analysis model (TAM) is very useful in the correlation process. A TAM is essentially a FEM reduced to the size of the test model, which attempts to preserve the dynamic characteristics of the original FEM in the analysis range of interest. Numerous methods for generating TAMs have been developed in the literature. The major emphasis of this paper is a description of the procedures necessary for creation of the TAM and the correlation of the reduced models with the FEM or the test results. Herein, three methods are discussed, namely Guyan, Improved Reduced System (IRS), and Hybrid. Also included are the procedures for performing these analyses using MSC/NASTRAN. Finally, application of the TAM process is demonstrated with an experimental test configuration of a ten bay cantilevered truss structure.

Individual and Work-Related Factors Influencing Burnout of Mental Health Professionals: A Meta-Analysis

ERIC Educational Resources Information Center

Lim, Nayoung; Kim, Eun Kyoung; Kim, Hyunjung; Yang, Eunjoo; Lee, Sang Min

2010-01-01

The current study identifies and assesses individual and work-related factors as correlates of burnout among mental health professionals. Results of a meta-analysis indicate that age and work setting variables are the most significant indicators of emotional exhaustion and depersonalization. In terms of level of personal accomplishment, the age…

Paternal postnatal depression in Japan: an investigation of correlated factors including relationship with a partner.

PubMed

Nishimura, Akiko; Fujita, Yuichi; Katsuta, Mayumi; Ishihara, Aya; Ohashi, Kazutomo

2015-05-31

A negative effect of paternal depression on child development has been revealed in several previous studies. The aims of this study were to examine the prevalence and relevant factors associated with paternal postnatal depression at four months postpartum, including age, part-time work or unemployment, experience of visiting a medical institution due to a mental health problem, economic anxiety, unexpected pregnancy, pregnancy with infertility treatment, first child, partner's depression, and lower marital relationship satisfaction. We distributed 2032 self-report questionnaires to couples (one mother and one father) with a 4-month old infant between January and April 2013. Data from 807 couples (39.7 %) were analyzed. Depressive symptoms were measured with the Edinburgh Postnatal Depression Scale (EPDS). In order to clarify the factors related with paternal depression, a logistic regression analysis was conducted. One hundred and ten fathers (13.6 %) and 83 mothers (10.3 %) were depressed. According to the logistic regression analysis, paternal depression was positively associated with partner's depression (adjusted odds ratio (AOR) 1.91, 95 % confidence interval (CI) 1.05-3.47), and negatively with marital relationship satisfaction (AOR 0.83, 95 % CI 0.77-0.89). History of infertility treatment (AOR 2.37, 95 % CI 1.32-4.24), experience of visiting a medical institution due to a mental health problem (AOR 4.56, 95 % CI 2.06-10.08), and economic anxiety (AOR 2.15, 95 % CI 1.34-3.45) were also correlated with paternal depression. This study showed that the prevalence of paternal depression at four months after childbirth was 13.6 % in Japan. The presence of partner's depression and low marital relationship satisfaction were significantly correlated with paternal postpartum depression, suggesting that health professionals need to pay attention to the mental status of both fathers and mothers, and to their relationship.

PCAN: Probabilistic Correlation Analysis of Two Non-normal Data Sets

PubMed Central

Zoh, Roger S.; Mallick, Bani; Ivanov, Ivan; Baladandayuthapani, Veera; Manyam, Ganiraju; Chapkin, Robert S.; Lampe, Johanna W.; Carroll, Raymond J.

2016-01-01

Summary Most cancer research now involves one or more assays profiling various biological molecules, e.g., messenger RNA and micro RNA, in samples collected on the same individuals. The main interest with these genomic data sets lies in the identification of a subset of features that are active in explaining the dependence between platforms. To quantify the strength of the dependency between two variables, correlation is often preferred. However, expression data obtained from next-generation sequencing platforms are integer with very low counts for some important features. In this case, the sample Pearson correlation is not a valid estimate of the true correlation matrix, because the sample correlation estimate between two features/variables with low counts will often be close to zero, even when the natural parameters of the Poisson distribution are, in actuality, highly correlated. We propose a model-based approach to correlation estimation between two non-normal data sets, via a method we call Probabilistic Correlations ANalysis, or PCAN. PCAN takes into consideration the distributional assumption about both data sets and suggests that correlations estimated at the model natural parameter level are more appropriate than correlations estimated directly on the observed data. We demonstrate through a simulation study that PCAN outperforms other standard approaches in estimating the true correlation between the natural parameters. We then apply PCAN to the joint analysis of a microRNA (miRNA) and a messenger RNA (mRNA) expression data set from a squamous cell lung cancer study, finding a large number of negative correlation pairs when compared to the standard approaches. PMID:27037601

Analysis of risk factors in the development of retinopathy of prematurity.

PubMed

Knezević, Sanja; Stojanović, Nadezda; Oros, Ana; Savić, Dragana; Simović, Aleksandra; Knezević, Jasmina

2011-01-01

Retinopathy of prematurity (ROP) is a multifactorial disease that occurs most frequently in very small and very sick preterm infants, and it has been identified as the major cause of childhood blindness. The aim of this study was to evaluate ROP incidence and risk factors associated with varying degrees of illness. The study was conducted at the Centre for Neonatology, Paediatric Clinic of the Clinical Centre Kragujevac, Serbia, in the period from June 2006 to December 2008. Ophthalmologic screening was performed in all children with body weight lower than 2000 g or gestational age lower than 36 weeks. We analyzed eighteen postnatal and six perinatal risk factors and the group correlations for each of the risk factors. Out of 317 children that were screened, 56 (17.7%) developed a mild form of ROP, while 68 (21.5%) developed a severe form. Univariate analysis revealed a large number of statistically significant risk factors for the development of ROP, especially the severe form. Multivariate logistical analysis further separated two independent risk factors: small birth weight (p = 0.001) and damage of central nervous system (p = 0.01). Independent risk factors for transition from mild to severe forms of ROP were identified as: small birth weight (p = 0.05) and perinatal risk factors (p = 0.02). Small birth weight and central nervous system damage were risk factors for the development of ROP, perinatal risk factors were identified as significant for transition from mild to severe form of ROP.

International Space Station Future Correlation Analysis Improvements

NASA Technical Reports Server (NTRS)

Laible, Michael R.; Pinnamaneni, Murthy; Sugavanam, Sujatha; Grygier, Michael

2018-01-01

Ongoing modal analyses and model correlation are performed on different configurations of the International Space Station (ISS). These analyses utilize on-orbit dynamic measurements collected using four main ISS instrumentation systems: External Wireless Instrumentation System (EWIS), Internal Wireless Instrumentation System (IWIS), Space Acceleration Measurement System (SAMS), and Structural Dynamic Measurement System (SDMS). Remote Sensor Units (RSUs) are network relay stations that acquire flight data from sensors. Measured data is stored in the Remote Sensor Unit (RSU) until it receives a command to download data via RF to the Network Control Unit (NCU). Since each RSU has its own clock, it is necessary to synchronize measurements before analysis. Imprecise synchronization impacts analysis results. A study was performed to evaluate three different synchronization techniques: (i) measurements visually aligned to analytical time-response data using model comparison, (ii) Frequency Domain Decomposition (FDD), and (iii) lag from cross-correlation to align measurements. This paper presents the results of this study.

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.

Standardized uptake value and apparent diffusion coefficient of endometrial cancer evaluated with integrated whole-body PET/MR: Correlation with pathological prognostic factors.

PubMed

Shih, I-Lun; Yen, Ruoh-Fang; Chen, Chi-An; Chen, Bang-Bin; Wei, Shwu-Yuan; Chang, Wen-Chun; Sheu, Bor-Ching; Cheng, Wen-Fang; Tseng, Yao-Hui; Chen, Xin-Jia; Chen, Chi-Hau; Wei, Lin-Hung; Chiang, Ying-Cheng; Torng, Pao-Ling; Yen, Men-Luh; Shih, Tiffany Ting-Fang

2015-12-01

To evaluate the correlation between maximum standardized uptake value (SUVmax ) and minimum apparent diffusion coefficient (ADCmin ) of endometrial cancer derived from an integrated positron emission tomography / magnetic resonance (PET/MR) system and to determine their correlation with pathological prognostic factors. This prospective study was approved by the Institutional Review Board of the hospital, and informed consent was obtained. Between April and December 2014, 47 consecutive patients with endometrial cancer were enrolled and underwent simultaneous PET/MR examinations before surgery. Thirty-six patients with measurable tumors on PET/MR were included for image analysis. Pearson's correlation coefficient was used to evaluate the correlation between SUVmax and ADCmin of the tumors. The Mann-Whitney U-test was utilized to evaluate relationships between these two imaging biomarkers and pathological prognostic factors. The mean SUVmax and ADCmin were 14.7 ± 7.1 and 0.48 ± 0.13 × 10(-3) mm(2) /s, respectively. A significant inverse correlation was found between SUVmax and ADCmin (r = -0.53; P = 0.001). SUVmax was significantly higher in tumors with advanced stage, deep myometrial invasion, cervical invasion, lymphovascular space involvement, and lymph node metastasis (P < 0.05). ADCmin was lower in tumors with higher grade, advanced stage, and cervical invasion (P < 0.05). The ratio of SUVmax to ADCmin was higher in tumors with higher grade, advanced stage, deep myometrial invasion, cervical invasion, lymphovascular space involvement, and lymph node metastasis (P < 0.05). SUVmax and ADCmin of endometrial cancer derived from integrated PET/MR are inversely correlated and are associated with pathological prognostic factors. © 2015 Wiley Periodicals, Inc.

Analysis of significant factors for dengue fever incidence prediction.

PubMed

Siriyasatien, Padet; Phumee, Atchara; Ongruk, Phatsavee; Jampachaisri, Katechan; Kesorn, Kraisak

2016-04-16

Many popular dengue forecasting techniques have been used by several researchers to extrapolate dengue incidence rates, including the K-H model, support vector machines (SVM), and artificial neural networks (ANN). The time series analysis methodology, particularly ARIMA and SARIMA, has been increasingly applied to the field of epidemiological research for dengue fever, dengue hemorrhagic fever, and other infectious diseases. The main drawback of these methods is that they do not consider other variables that are associated with the dependent variable. Additionally, new factors correlated to the disease are needed to enhance the prediction accuracy of the model when it is applied to areas of similar climates, where weather factors such as temperature, total rainfall, and humidity are not substantially different. Such drawbacks may consequently lower the predictive power for the outbreak. The predictive power of the forecasting model-assessed by Akaike's information criterion (AIC), Bayesian information criterion (BIC), and the mean absolute percentage error (MAPE)-is improved by including the new parameters for dengue outbreak prediction. This study's selected model outperforms all three other competing models with the lowest AIC, the lowest BIC, and a small MAPE value. The exclusive use of climate factors from similar locations decreases a model's prediction power. The multivariate Poisson regression, however, effectively forecasts even when climate variables are slightly different. Female mosquitoes and seasons were strongly correlated with dengue cases. Therefore, the dengue incidence trends provided by this model will assist the optimization of dengue prevention. The present work demonstrates the important roles of female mosquito infection rates from the previous season and climate factors (represented as seasons) in dengue outbreaks. Incorporating these two factors in the model significantly improves the predictive power of dengue hemorrhagic fever forecasting

Meta-analysis of the predictive factors of postpartum fatigue.

PubMed

Badr, Hanan A; Zauszniewski, Jaclene A

2017-08-01

Nearly 64% of new mothers are affected by fatigue during the postpartum period, making it the most common problem that a woman faces as she adapts to motherhood. Postpartum fatigue can lead to serious negative effects on the mother's health and the newborn's development and interfere with mother-infant interaction. The aim of this meta-analysis was to identify predictive factors of postpartum fatigue and to document the magnitude of their effects using effect sizes. We used two search engines, PubMed and Google Scholar, to identify studies that met three inclusion criteria: (a) the article was written in English, (b) the article studied the predictive factors of postpartum fatigue, and (c) the article included information about the validity and reliability of the instruments used in the research. Nine articles met these inclusion criteria. The direction and strength of correlation coefficients between predictive factors and postpartum fatigue were examined across the studies to determine their effect sizes. Measurement of predictor variables occurred from 3days to 6months postpartum. Correlations reported between predictive factors and postpartum fatigue were as follows: small effect size (r range =0.10 to 0.29) for education level, age, postpartum hemorrhage, infection, and child care difficulties; medium effect size (r range =0.30 to 0.49) for physiological illness, low ferritin level, low hemoglobin level, sleeping problems, stress and anxiety, and breastfeeding problems; and large effect size (r range =0.50+) for depression. Postpartum fatigue is a common condition that can lead to serious health problems for a new mother and her newborn. Therefore, increased knowledge concerning factors that influence the onset of postpartum fatigue is needed for early identification of new mothers who may be at risk. Appropriate treatments, interventions, information, and support can then be initiated to prevent or minimize the postpartum fatigue. Copyright © 2017 Elsevier

Subjective wellbeing, suicide and socioeconomic factors: an ecological analysis in Hong Kong.

PubMed

Hsu, C-Y; Chang, S-S; Yip, P S F

2018-04-10

There has recently been an increased interest in mental health indicators for the monitoring of population wellbeing, which is among the targets of Sustainable Development Goals adopted by the United Nations. Levels of subjective wellbeing and suicide rates have been proposed as indicators of population mental health, but prior research is limited. Data on individual happiness and life satisfaction were sourced from a population-based survey in Hong Kong (2011). Suicide data were extracted from Coroner's Court files (2005-2013). Area characteristic variables included local poverty rate and four factors derived from a factor analysis of 21 variables extracted from the 2011 census. The associations between mean happiness and life satisfaction scores and suicide rates were assessed using Pearson correlation coefficient at two area levels: 18 districts and 30 quantiles of large street blocks (LSBs; n = 1620). LSB is a small area unit with a higher level of within-unit homogeneity compared with districts. Partial correlations were used to control for area characteristics. Happiness and life satisfaction demonstrated weak inverse associations with suicide rate at the district level (r = -0.32 and -0.36, respectively) but very strong associations at the LSB quantile level (r = -0.83 and -0.84, respectively). There were generally very weak or weak negative correlations across sex/age groups at the district level but generally moderate to strong correlations at the LSB quantile level. The associations were markedly attenuated or became null after controlling for area characteristics. Subjective wellbeing is strongly associated with suicide at a small area level; socioeconomic factors can largely explain this association. Socioeconomic factors could play an important role in determining the wellbeing of the population, and this could inform policies aimed at enhancing population wellbeing.

Confirmatory factor analysis of the Oral Health Impact Profile.

PubMed

John, M T; Feuerstahler, L; Waller, N; Baba, K; Larsson, P; Celebić, A; Kende, D; Rener-Sitar, K; Reissmann, D R

2014-09-01

Previous exploratory analyses suggest that the Oral Health Impact Profile (OHIP) consists of four correlated dimensions and that individual differences in OHIP total scores reflect an underlying higher-order factor. The aim of this report is to corroborate these findings in the Dimensions of Oral Health-Related Quality of Life (DOQ) Project, an international study of general population subjects and prosthodontic patients. Using the project's Validation Sample (n = 5022), we conducted confirmatory factor analyses in a sample of 4993 subjects with sufficiently complete data. In particular, we compared the psychometric performance of three models: a unidimensional model, a four-factor model and a bifactor model that included one general factor and four group factors. Using model-fit criteria and factor interpretability as guides, the four-factor model was deemed best in terms of strong item loadings, model fit (RMSEA = 0·05, CFI = 0·99) and interpretability. These results corroborate our previous findings that four highly correlated factors - which we have named Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact - can be reliably extracted from the OHIP item pool. However, the good fit of the unidimensional model and the high interfactor correlations in the four-factor solution suggest that OHRQoL can also be sufficiently described with one score. © 2014 John Wiley & Sons Ltd.

Spatio-Chromatic Adaptation via Higher-Order Canonical Correlation Analysis of Natural Images

PubMed Central

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. PMID:24533049

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.

FACTOR ANALYSIS OF A SOCIAL SKILLS SCALE FOR HIGH SCHOOL STUDENTS.

PubMed

Wang, H-Y; Lin, C-K

2015-10-01

The objective of this study was to develop a social skills scale for high school students in Taiwan. This study adopted stratified random sampling. A total of 1,729 high school students were included. The students ranged in age from 16 to 18 years. A Social Skills Scale was developed for this study and was designed for classroom teachers to fill out. The test-retest reliability of this scale was tested by Pearson's correlation coefficient. Exploratory factor analysis was used to determine construct validity. The Social Skills Scale had good overall test-retest reliability of .92, and the internal consistency of the five subscales was above .90. The results of the factor analysis showed that the Social Skills Scale covered the five domains of classroom learning skills, communication skills, individual initiative skills, interaction skills, and job-related social skills, and the five factors explained 68.34% of the variance. Thus, the Social Skills Scale had good reliability and validity and would be applicable to and could be promoted for use in schools.

Residential Greenness and Birth Outcomes: Evaluating the Influence of Spatially Correlated Built-Environment Factors

PubMed Central

Davies, Hugh W.; Frank, Lawrence; Van Loon, Josh; Gehring, Ulrike; Tamburic, Lillian; Brauer, Michael

2014-01-01

Background: Half the world’s population lives in urban areas. It is therefore important to identify characteristics of the built environment that are beneficial to human health. Urban greenness has been associated with improvements in a diverse range of health conditions, including birth outcomes; however, few studies have attempted to distinguish potential effects of greenness from those of other spatially correlated exposures related to the built environment. Objectives: We aimed to investigate associations between residential greenness and birth outcomes and evaluate the influence of spatially correlated built environment factors on these associations. Methods: We examined associations between residential greenness [measured using satellite-derived Normalized Difference Vegetation Index (NDVI) within 100 m of study participants’ homes] and birth outcomes in a cohort of 64,705 singleton births (from 1999–2002) in Vancouver, British Columbia, Canada. We also evaluated associations after adjusting for spatially correlated built environmental factors that may influence birth outcomes, including exposure to air pollution and noise, neighborhood walkability, and distance to the nearest park. Results: An interquartile increase in greenness (0.1 in residential NDVI) was associated with higher term birth weight (20.6 g; 95% CI: 16.5, 24.7) and decreases in the likelihood of small for gestational age, very preterm (< 30 weeks), and moderately preterm (30–36 weeks) birth. Associations were robust to adjustment for air pollution and noise exposures, neighborhood walkability, and park proximity. Conclusions: Increased residential greenness was associated with beneficial birth outcomes in this population-based cohort. These associations did not change after adjusting for other spatially correlated built environment factors, suggesting that alternative pathways (e.g., psychosocial and psychological mechanisms) may underlie associations between residential greenness and

A CRITERION FACTOR ANALYSIS OF THE SIXTEEN PERSONALITY FACTOR QUESTIONNAIRE.

ERIC Educational Resources Information Center

MAZER, GILBERT E.

THE CORRELATION OF REPORTED VARIATIONS IN COUNSELOR PRACTICES WITH WELL-IDENTIFIED PERSONALITY TRAITS WAS STUDIED. THE SIXTEEN PERSONALITY FACTOR QUESTIONNAIRE (WHICH MEASURES 15 PERSONALITY TRAITS AND INTELLIGENCE) AND THE INVENTORY OF COUNSELING PRACTICES (WHICH EVALUATES 75 COUNSELING PRACTICES) WERE GIVEN TO 120 GRADUATE GUIDANCE STUDENTS AT…

Path analysis of risk factors leading to premature birth.

PubMed

Fields, S J; Livshits, G; Sirotta, L; Merlob, P

1996-01-01

The present study tested whether various sociodemographic, anthropometric, behavioral, and medical/physiological factors act in a direct or indirect manner on the risk of prematurity using path analysis on a sample of Israeli births. The path model shows that medical complications, primarily toxemia, chorioammionitis, and a previous low birth weight delivery directly and significantly act on the risk of prematurity as do low maternal pregnancy weight gain and ethnicity. Other medical complications, including chronic hypertension, preclampsia, and placental abruption, although significantly correlated with prematurity, act indirectly on prematurity through toxemia. The model further shows that the commonly accepted sociodemographic, anthropometric, and behavioral risk factors act by modifying the development of medical complications that lead to prematurity as opposed to having a direct effect on premature delivery. © 1996 Wiley-Liss, Inc. Copyright © 1996 Wiley-Liss, Inc.

A Graphical Modelling Approach to the Dissection of Highly Correlated Transcription Factor Binding Site Profiles

PubMed Central

Stojnic, Robert; Fu, Audrey Qiuyan; Adryan, Boris

2012-01-01

Inferring the combinatorial regulatory code of transcription factors (TFs) from genome-wide TF binding profiles is challenging. A major reason is that TF binding profiles significantly overlap and are therefore highly correlated. Clustered occurrence of multiple TFs at genomic sites may arise from chromatin accessibility and local cooperation between TFs, or binding sites may simply appear clustered if the profiles are generated from diverse cell populations. Overlaps in TF binding profiles may also result from measurements taken at closely related time intervals. It is thus of great interest to distinguish TFs that directly regulate gene expression from those that are indirectly associated with gene expression. Graphical models, in particular Bayesian networks, provide a powerful mathematical framework to infer different types of dependencies. However, existing methods do not perform well when the features (here: TF binding profiles) are highly correlated, when their association with the biological outcome is weak, and when the sample size is small. Here, we develop a novel computational method, the Neighbourhood Consistent PC (NCPC) algorithms, which deal with these scenarios much more effectively than existing methods do. We further present a novel graphical representation, the Direct Dependence Graph (DDGraph), to better display the complex interactions among variables. NCPC and DDGraph can also be applied to other problems involving highly correlated biological features. Both methods are implemented in the R package ddgraph, available as part of Bioconductor (http://bioconductor.org/packages/2.11/bioc/html/ddgraph.html). Applied to real data, our method identified TFs that specify different classes of cis-regulatory modules (CRMs) in Drosophila mesoderm differentiation. Our analysis also found depletion of the early transcription factor Twist binding at the CRMs regulating expression in visceral and somatic muscle cells at later stages, which suggests a CRM

Performance of prioritized activities is not correlated with functional factors after grip reconstruction in tetraplegia.

PubMed

Wangdell, Johanna; Fridén, Jan

2011-06-01

To investigate the correlation between perceived performance in prioritized activities and physical conditions related to grip reconstruction. Retrospective clinical outcome study. Forty-seven individuals with tetraplegia were included in the study. Each participant underwent tendon transfer surgery in the hand between November 2002 and April 2009 and had a complete 1-year follow-up. Functional characteristics and performance data were collected from our database and medical records. Patients' perceived performances in prioritized activities were recorded using the Canadian Occupational Performance Measurement. Preoperative data included age at surgery, time since injury, severity of injury, sensibility and hand dominance. At 1-year follow-up, grip strength, key pinch strength, finger pulp-to-palm distance, distance between thumb and index finger and wrist flexion were measured. Correlation rank coefficient was used to test the possible relationship between physical data and activity performance. There were improvements in both functional factors and in rated performance of prioritized activities after surgery. There was no correlation between performance change and any of the physical functions, the factors known before surgery, or the functional outcome factors. No correlation exists between a single functional outcome parameter and the patients' perceived performance of their prioritized goals in reconstructive hand surgery in tetraplegia.

PCAN: Probabilistic correlation analysis of two non-normal data sets.

PubMed

Zoh, Roger S; Mallick, Bani; Ivanov, Ivan; Baladandayuthapani, Veera; Manyam, Ganiraju; Chapkin, Robert S; Lampe, Johanna W; Carroll, Raymond J

2016-12-01

Most cancer research now involves one or more assays profiling various biological molecules, e.g., messenger RNA and micro RNA, in samples collected on the same individuals. The main interest with these genomic data sets lies in the identification of a subset of features that are active in explaining the dependence between platforms. To quantify the strength of the dependency between two variables, correlation is often preferred. However, expression data obtained from next-generation sequencing platforms are integer with very low counts for some important features. In this case, the sample Pearson correlation is not a valid estimate of the true correlation matrix, because the sample correlation estimate between two features/variables with low counts will often be close to zero, even when the natural parameters of the Poisson distribution are, in actuality, highly correlated. We propose a model-based approach to correlation estimation between two non-normal data sets, via a method we call Probabilistic Correlations ANalysis, or PCAN. PCAN takes into consideration the distributional assumption about both data sets and suggests that correlations estimated at the model natural parameter level are more appropriate than correlations estimated directly on the observed data. We demonstrate through a simulation study that PCAN outperforms other standard approaches in estimating the true correlation between the natural parameters. We then apply PCAN to the joint analysis of a microRNA (miRNA) and a messenger RNA (mRNA) expression data set from a squamous cell lung cancer study, finding a large number of negative correlation pairs when compared to the standard approaches. © 2016, The International Biometric Society.

Inter-correlations between Cloninger's temperament dimensions-- a meta-analysis.

PubMed

Miettunen, Jouko; Lauronen, Erika; Kantojärvi, Liisa; Veijola, Juha; Joukamaa, Matti

2008-07-15

The Temperament and Character Inventory (TCI) was developed to measure the following temperament dimensions: novelty seeking (NS), harm avoidance (HA), reward dependence (RD) and persistence (P). These four dimensions of temperament were originally proposed to be independent of one another. In this study the inter-relationships between the dimensions were studied with meta-analytic techniques. We also studied the effects of sociodemographic factors (location of the study, mean age and gender distribution) on correlations between temperament dimensions. We searched studies on healthy (non-clinical) populations that used the TCI (version 9), and that had a required sample size of at least 100. The search resulted in 16 articles. The resulted pooled correlation coefficient was medium level between NS and HA (-0.27). Correlations were small for HA-P (-0.20), NS-P (-0.14), NS-RD (0.10), RD-P (0.05) and HA-RD (0.04). In meta-regression, the correlation NS-P was significantly affected by the location of the study (Asian/other) and by the gender distribution of the sample. In the HA-P correlation, the mean age of the sample affected the correlation. In conclusion, we found a medium level negative correlation between NS and HA; other correlations between the dimensions were small. These findings mainly support Cloninger's theory of independent dimensions.

Factor Analysis of the Autism Spectrum Screening Questionnaire

ERIC Educational Resources Information Center

Posserud, Britt; Lundervold, Astri J.; Steijnen, Maaike C.; Verhoeven, Sophie; Stormark, Kjell Morten; Gillberg, Christopher

2008-01-01

The present study investigated the factor structure of parent and teacher Autism Spectrum Screening Questionnaire (ASSQ) in a population of 7-9 years old children. For validation purposes, factors derived were correlated with results on the Strengths and Difficulties Questionnaire (SDQ). A three-factor solution was identified on both parent and…

Re-analysis of correlations among four impulsivity scales.

PubMed

Gallardo-Pujol, David; Andrés-Pueyo, Antonio

2006-08-01

Impulsivity plays a key role in normal and pathological behavior. Although there is some consensus about its conceptualization, there have been many attempts to build a multidimensional tool due to the lack of agreement in how to measure it. A recent study claimed support for a three-dimensional structure of impulsivity, however with weak empirical support. By re-analysing those data, a four-factor structure was found to describe the correlation matrix much better. The debate remains open and further research is needed to clarify the factor structure. The desirability of constructing new measures, perhaps analogously to the Wechsler Intelligence Scale, is emphasized.

Application of the Gini Correlation Coefficient to Infer Regulatory Relationships in Transcriptome Analysis[W][OA

PubMed Central

Ma, Chuang; Wang, Xiangfeng

2012-01-01

One of the computational challenges in plant systems biology is to accurately infer transcriptional regulation relationships based on correlation analyses of gene expression patterns. Despite several correlation methods that are applied in biology to analyze microarray data, concerns regarding the compatibility of these methods with the gene expression data profiled by high-throughput RNA transcriptome sequencing (RNA-Seq) technology have been raised. These concerns are mainly due to the fact that the distribution of read counts in RNA-Seq experiments is different from that of fluorescence intensities in microarray experiments. Therefore, a comprehensive evaluation of the existing correlation methods and, if necessary, introduction of novel methods into biology is appropriate. In this study, we compared four existing correlation methods used in microarray analysis and one novel method called the Gini correlation coefficient on previously published microarray-based and sequencing-based gene expression data in Arabidopsis (Arabidopsis thaliana) and maize (Zea mays). The comparisons were performed on more than 11,000 regulatory relationships in Arabidopsis, including 8,929 pairs of transcription factors and target genes. Our analyses pinpointed the strengths and weaknesses of each method and indicated that the Gini correlation can compensate for the shortcomings of the Pearson correlation, the Spearman correlation, the Kendall correlation, and the Tukey’s biweight correlation. The Gini correlation method, with the other four evaluated methods in this study, was implemented as an R package named rsgcc that can be utilized as an alternative option for biologists to perform clustering analyses of gene expression patterns or transcriptional network analyses. PMID:22797655

Comparison of mixed-mode stress-intensity factors obtained through displacement correlation, J-integral formulation, and modified crack-closure integral

NASA Astrophysics Data System (ADS)

Bittencourt, Tulio N.; Barry, Ahmabou; Ingraffea, Anthony R.

This paper presents a comparison among stress-intensity factors for mixed-mode two-dimensional problems obtained through three different approaches: displacement correlation, J-integral, and modified crack-closure integral. All mentioned procedures involve only one analysis step and are incorporated in the post-processor page of a finite element computer code for fracture mechanics analysis (FRANC). Results are presented for a closed-form solution problem under mixed-mode conditions. The accuracy of these described methods then is discussed and analyzed in the framework of their numerical results. The influence of the differences among the three methods on the predicted crack trajectory of general problems is also discussed.

Confirmatory factor analysis of the female sexual function index.

PubMed

Opperman, Emily A; Benson, Lindsay E; Milhausen, Robin R

2013-01-01

The Female Sexual Functioning Index (Rosen et al., 2000 ) was designed to assess the key dimensions of female sexual functioning using six domains: desire, arousal, lubrication, orgasm, satisfaction, and pain. A full-scale score was proposed to represent women's overall sexual function. The fifth revision to the Diagnostic and Statistical Manual (DSM) is currently underway and includes a proposal to combine desire and arousal problems. The objective of this article was to evaluate and compare four models of the Female Sexual Functioning Index: (a) single-factor model, (b) six-factor model, (c) second-order factor model, and (4) five-factor model combining the desire and arousal subscales. Cross-sectional and observational data from 85 women were used to conduct a confirmatory factor analysis on the Female Sexual Functioning Index. Local and global goodness-of-fit measures, the chi-square test of differences, squared multiple correlations, and regression weights were used. The single-factor model fit was not acceptable. The original six-factor model was confirmed, and good model fit was found for the second-order and five-factor models. Delta chi-square tests of differences supported best fit for the six-factor model validating usage of the six domains. However, when revisions are made to the DSM-5, the Female Sexual Functioning Index can adapt to reflect these changes and remain a valid assessment tool for women's sexual functioning, as the five-factor structure was also supported.

[Correlation analysis between effectiveness of element in rhizonsphere soil and quality of Danshen (Salvia miltiorrhiza)].

PubMed

Shen, Xiao-Feng; Zhang, Qi; Yan, Zhu-Yun; Yang, Xin-Jie; Guo, Xiao-Heng; Chen, Xin; Wan, De-Guang

2016-04-01

In order to investigate the content and distribution of available element in the rhizonsphere soil of the growing areas of Salvia miltiorrhiza Bunge, the contents of available element (N,P,K,B,Cu,Zn,Fe,Mn) in 26 soil samples were tested and evaluated. The results showed that the contents of available P and Fe were very plentiful, available K, Cu and Zn were rich, available N and Mn were deficient, available B was extremely deficient in all growing areas of S. miltiorrhiza of eight provinces in China. The correlation analysis showed that the contents of eight kinds of available elements were varying degree correlation. The stepwise regression analysis between the contents of available elements of rhizonsphere soil and ten kinds of active ingredients of Danshen (Salviae Miltiorrhizae Radix et Rhizoma) were researched. The results showed that the rates of contribution of available N,B,Mn and Fe to quality of Danshen were relatively large and they were the significant factors, and the other factors did not show statistical significance. The recommended fertilizing strategies is that the usage of N,B and Mn fertilizers should be controlled according to different stages of growth of S. miltiorrhiza, and P fertilizer should be reduced in all growing areas of S. miltiorrhiza. Copyright© by the Chinese Pharmaceutical Association.

Imbalance between vascular endothelial growth factor and endostatin correlates with the prognosis of operable non-small cell lung cancer.

PubMed

Hu, Y; Hu, M-m; Shi, G-L; Han, Y; Li, B-L

2014-09-01

Angiogenesis is regulated by a balance of pro-angiogenic and anti-angiogenic factors. Vascular endothelial growth factor (VEGF) and endostatin respectively represents a frequent component of inducers and inhibitors in the process of angiogenesis. The ratio of VEGF/endostatin may reflect the balance of angiogenic switch. This study aimed to determine whether an imbalance between VEGF/endostatin exists in operable non-small cell lung cancer (NSCLC) patients and to assess the correlation, if any, between the imbalance and the prognosis. Preoperative serum levels of VEGF and endostatin were simultaneously determined by quantitiative enzyme-linked immunosorbent assay (ELISA) and the ratio of them was calculated among 98 NSCLC patients and 51 healthy controls. The relationship between these factors and clinicopathological features, including prognosis, was examined. The ratio of VEGF/endostatin levels was significantly higher in operable NSCLC patients [median, 10.4; interquartile range (IQR), 5.9-19.8] than in normal controls [median, 5.1; IQR, 3.3-9.7] (P = 0.002). While the ratio in patients who were still alive for more than 60 months was 8.3 (IQR, 4.3-17.9), the ratio in those who died was 12.9 (IQR, 8.0-22.1) (p = 0.017). In subgroup analysis of patients with pathological stage N0, there was a statistically significant increase of the survival time in the group with a lower ratio than in the group with a higher ratio (p = 0.032). Multivariate analysis confirmed that the VEGF/endostatin ratio was an independent prognostic factor (p = 0.018). There was an imbalance between VEGF and endostatin in serum of operable NSCLC patients. The imbalance correlated with the prognosis of operable NSCLC. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Collinear Latent Variables in Multilevel Confirmatory Factor Analysis

PubMed Central

van de Schoot, Rens; Hox, Joop

2014-01-01

Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation coefficient (ICC) and estimation method; maximum likelihood estimation with robust chi-squares and standard errors and Bayesian estimation, on the convergence rate are investigated. The other variables of interest were rate of inadmissible solutions and the relative parameter and standard error bias on the between level. The results showed that inadmissible solutions were obtained when there was between level collinearity and the estimation method was maximum likelihood. In the within level multicollinearity condition, all of the solutions were admissible but the bias values were higher compared with the between level collinearity condition. Bayesian estimation appeared to be robust in obtaining admissible parameters but the relative bias was higher than for maximum likelihood estimation. Finally, as expected, high ICC produced less biased results compared to medium ICC conditions. PMID:29795827

Probing transcription factor diffusion dynamics in the living mammalian embryo with photoactivatable fluorescence correlation spectroscopy.

PubMed

Kaur, Gurpreet; Costa, Mauro W; Nefzger, Christian M; Silva, Juan; Fierro-González, Juan Carlos; Polo, Jose M; Bell, Toby D M; Plachta, Nicolas

2013-01-01

Transcription factors use diffusion to search the DNA, yet the mechanisms controlling transcription factor diffusion during mammalian development remain poorly understood. Here we combine photoactivation and fluorescence correlation spectroscopy to study transcription factor diffusion in developing mouse embryos. We show that the pluripotency-associated transcription factor Oct4 displays both fast and Brownian and slower subdiffusive behaviours that are controlled by DNA interactions. Following cell lineage specification, the slower DNA-interacting diffusion fraction distinguishes pluripotent from extraembryonic cell nuclei. Similar to Oct4, Sox2 shows slower diffusion in pluripotent cells while Cdx2 displays opposite dynamics, suggesting that slow diffusion may represent a general feature of transcription factors in lineages where they are essential. Slow Oct4 subdiffusive behaviours are conserved in embryonic stem cells and induced pluripotent stem cells (iPS cells), and lost during differentiation. We also show that Oct4 diffusion depends on its interaction with ERG-associated protein with SET domain. Photoactivation and fluorescence correlation spectroscopy provides a new intravital approach to study transcription factor diffusion in complex in vivo systems.

Network analysis reveals seasonal variation of co-occurrence correlations between Cyanobacteria and other bacterioplankton.

PubMed

Zhao, Dayong; Shen, Feng; Zeng, Jin; Huang, Rui; Yu, Zhongbo; Wu, Qinglong L

2016-12-15

Association network approaches have recently been proposed as a means for exploring the associations between bacterial communities. In the present study, high-throughput sequencing was employed to investigate the seasonal variations in the composition of bacterioplankton communities in six eutrophic urban lakes of Nanjing City, China. Over 150,000 16S rRNA sequences were derived from 52 water samples, and correlation-based network analyses were conducted. Our results demonstrated that the architecture of the co-occurrence networks varied in different seasons. Cyanobacteria played various roles in the ecological networks during different seasons. Co-occurrence patterns revealed that members of Cyanobacteria shared a very similar niche and they had weak positive correlations with other phyla in summer. To explore the effect of environmental factors on species-species co-occurrence networks and to determine the most influential environmental factors, the original positive network was simplified by module partitioning and by calculating module eigengenes. Module eigengene analysis indicated that temperature only affected some Cyanobacteria; the rest were mainly affected by nitrogen associated factors throughout the year. Cyanobacteria were dominant in summer which may result from strong co-occurrence patterns and suitable living conditions. Overall, this study has improved our understanding of the roles of Cyanobacteria and other bacterioplankton in ecological networks. Copyright © 2016 Elsevier B.V. All rights reserved.

[A multilevel model analysis of correlation between population characteristics and work ability of employees].

PubMed

Zhang, Lei; Huang, Chunping; Lan, Yajia; Wang, Mianzhen

2015-12-01

To analyze the correlation between population characteristics and work ability of employees with a multilevel model, to investigate the important influencing factors for work ability, and to provide a basis for improvement in work ability. Work ability index (WAI)was applied to measure the work ability of 1686 subjects from different companies (n=6). MLwi N2.0 software was applied for two-level variance component model fitting. The WAI of employees showed differences between various companies (χ2=3.378 6, P=0.0660); working years was negatively correlated with WAI (χ2=38.229 2, P=0.0001), and the WAI of the employees with 20 or more working years was 1.63 lower than that of the employees with less than 20 working years; the work ability of manual workers was lower than that of mental-manual workers (χ2=8.2726, P=0.0040), and the work ability showed no significant difference between mental workers and mental-manual workers (χ2=2.086 0, P=0.148 7). From the perspective of probability, the multilevel model analysis reveals the differences in work ability of employees between different companies, and suggests that company, work type, and working years are the important influencing factors for work ability of employees. These factors should be improved and adjusted to protect or enhance the work ability of employees.

Validation of the Adolescent Concerns Measure (ACM): evidence from exploratory and confirmatory factor analysis.

PubMed

Ang, Rebecca P; Chong, Wan Har; Huan, Vivien S; Yeo, Lay See

2007-01-01

This article reports the development and initial validation of scores obtained from the Adolescent Concerns Measure (ACM), a scale which assesses concerns of Asian adolescent students. In Study 1, findings from exploratory factor analysis using 619 adolescents suggested a 24-item scale with four correlated factors--Family Concerns (9 items), Peer Concerns (5 items), Personal Concerns (6 items), and School Concerns (4 items). Initial estimates of convergent validity for ACM scores were also reported. The four-factor structure of ACM scores derived from Study 1 was confirmed via confirmatory factor analysis in Study 2 using a two-fold cross-validation procedure with a separate sample of 811 adolescents. Support was found for both the multidimensional and hierarchical models of adolescent concerns using the ACM. Internal consistency and test-retest reliability estimates were adequate for research purposes. ACM scores show promise as a reliable and potentially valid measure of Asian adolescents' concerns.

Factor Analysis with EM Algorithm Never Gives Improper Solutions when Sample Covariance and Initial Parameter Matrices Are Proper

ERIC Educational Resources Information Center

Adachi, Kohei

2013-01-01

Rubin and Thayer ("Psychometrika," 47:69-76, 1982) proposed the EM algorithm for exploratory and confirmatory maximum likelihood factor analysis. In this paper, we prove the following fact: the EM algorithm always gives a proper solution with positive unique variances and factor correlations with absolute values that do not exceed one,…

Development problem analysis of correlation leak detector’s software

NASA Astrophysics Data System (ADS)

Faerman, V. A.; Avramchuk, V. S.; Marukyan, V. M.

2018-05-01

In the article, the practical application and the structure of the correlation leak detectors’ software is studied and the task of its designing is analyzed. In the first part of the research paper, the expediency of the facilities development of correlation leak detectors for the following operating efficiency of public utilities exploitation is shown. The analysis of the functional structure of correlation leak detectors is conducted and its program software tasks are defined. In the second part of the research paper some development steps of the software package – requirement forming, program structure definition and software concept creation – are examined in the context of the usage experience of the hardware-software prototype of correlation leak detector.

An Ecological Analysis of Environmental Correlates of Active Commuting in Urban U.S.

PubMed Central

Fan, Jessie X.; Wen, Ming; Kowaleski-Jones, Lori

2014-01-01

We conduct a cross-sectional ecological analysis to examine environmental correlates of active commuting in 39,660 urban tracts using data from the 2010 Census, 2007-2011 American Community Survey, and other sources. The five-year average (2007-2011) prevalence is 3.05% for walking, 0.63% for biking, and 7.28% for public transportation to work, with higher prevalence for all modes in lower-income tracts. Environmental factors account for more variances in public transportation to work but economic and demographic factors account for more variances in walking and biking to work. Population density, median housing age, street connectivity, tree canopy, distance to parks, air quality, and county sprawl index are associated with active commuting, but the association can vary in size and direction for different transportation mode and for higher-income and lower-income tracts. PMID:25460907

20 Meter Solar Sail Analysis and Correlation

NASA Technical Reports Server (NTRS)

Taleghani, B. K.; Lively, P. S.; Banik, J.; Murphy, D. M.; Trautt, T. A.

2005-01-01

This paper describes finite element analyses and correlation studies to predict deformations and vibration modes/frequencies of a 20-meter solar sail system developed by ATK Space Systems. Under the programmatic leadership of NASA Marshall Space Flight Center's In-Space Propulsion activity, the 20-meter solar sail program objectives were to verify the design, to assess structural responses of the sail system, to implement lessons learned from a previous 10-meter quadrant system analysis and test program, and to mature solar sail technology to a technology readiness level (TRL) of 5. For this 20 meter sail system, static and ground vibration tests were conducted in NASA Glenn Research Center's 100 meter diameter vacuum chamber at Plum Brook station. Prior to testing, a preliminary analysis was performed to evaluate test conditions and to determine sensor and actuator locations. After testing was completed, an analysis of each test configuration was performed. Post-test model refinements included updated properties to account for the mass of sensors, wiring, and other components used for testing. This paper describes the development of finite element models (FEM) for sail membranes and masts in each of four quadrants at both the component and system levels, as well as an optimization procedure for the static test/analyses correlation.

Study of risk factors for gastric cancer by populational databases analysis

PubMed Central

Ferrari, Fangio; Reis, Marco Antonio Moura

2013-01-01

AIM: To study the association between the incidence of gastric cancer and populational exposure to risk/protective factors through an analysis of international databases. METHODS: Open-access global databases concerning the incidence of gastric cancer and its risk/protective factors were identified through an extensive search on the Web. As its distribution was neither normal nor symmetric, the cancer incidence of each country was categorized according to ranges of percentile distribution. The association of each risk/protective factor with exposure was measured between the extreme ranges of the incidence of gastric cancer (under the 25th percentile and above the 75th percentile) by the use of the Mann-Whitney test, considering a significance level of 0.05. RESULTS: A variable amount of data omission was observed among all of the factors under study. A weak or nonexistent correlation between the incidence of gastric cancer and the study variables was shown by a visual analysis of scatterplot dispersion. In contrast, an analysis of categorized incidence revealed that the countries with the highest human development index (HDI) values had the highest rates of obesity in males and the highest consumption of alcohol, tobacco, fruits, vegetables and meat, which were associated with higher incidences of gastric cancer. There was no significant difference for the risk factors of obesity in females and fish consumption. CONCLUSION: Higher HDI values, coupled with a higher prevalence of male obesity and a higher per capita consumption of alcohol, tobacco, fruits, vegetables and meat, are associated with a higher incidence of gastric cancer based on an analysis of populational global data. PMID:24409066

Noninvasive deep Raman detection with 2D correlation analysis

NASA Astrophysics Data System (ADS)

Kim, Hyung Min; Park, Hyo Sun; Cho, Youngho; Jin, Seung Min; Lee, Kang Taek; Jung, Young Mee; Suh, Yung Doug

2014-07-01

The detection of poisonous chemicals enclosed in daily necessaries is prerequisite essential for homeland security with the increasing threat of terrorism. For the detection of toxic chemicals, we combined a sensitive deep Raman spectroscopic method with 2D correlation analysis. We obtained the Raman spectra from concealed chemicals employing spatially offset Raman spectroscopy in which incident line-shaped light experiences multiple scatterings before being delivered to inner component and yielding deep Raman signal. Furthermore, we restored the pure Raman spectrum of each component using 2D correlation spectroscopic analysis with chemical inspection. Using this method, we could elucidate subsurface component under thick powder and packed contents in a bottle.

Estimation of stature from sternal lengths. A correlation meta-analysis.

PubMed

Yammine, Kaissar; Assi, Chahine

2017-01-01

Methods based on the positive linear relationship existing between stature and long bones are most commonly used to estimate living stature in forensic anthropology. The length of the sternum and its parts has been advanced as a plausible alternative to estimate stature when such long bones are missing or damaged. This meta-analysis aims to quantify evidence on the correlation between the sternum/sternal parts length and stature. Nine studies were included with 1118 sternal bones. Analyses showed that the length of the meso-sternum (manubrium + body) yielded the best correlation with stature; 53.5% and 55.42% for men and women, respectively. The second best variable is the total sternal length with correlations of 44.3% and 55% for men and women, respectively. Subgroup analysis of autopsy studies demonstrated even a higher correlation of 58.2% for the meso-sternal length. Manubrium and body lengths showed the least correlation values. Except for the body length, females exhibit a better correlation than man between all other sternal lengths and stature. While the meso-sternal length is found to be the most correlated variable with stature, all sternal lengths are to be considered with caution when estimating stature. The relatively low values of the weighted correlation results should raise the question of reliability and limit the use of sternal length when long bones are available. Future research using larger samples from different populations and taking into account the fusion status of the sternum are needed.

Correlates of Parental Differential Treatment: Parental and Contextual Factors during Middle Childhood

ERIC Educational Resources Information Center

Atzaba-Poria, Naama; Pike, Alison

2008-01-01

The current study examined whether parental and contextual risk factors contribute to mothers' and fathers' differential treatment (MDT/FDT) when accounting for sibling dyad characteristics. Also explored was whether family type (single mothers vs. 2 parents) moderated the links between the parental and contextual correlates and MDT. One hundred…

Factors affecting energy and nitrogen efficiency of dairy cows: a meta-analysis.

PubMed

Phuong, H N; Friggens, N C; de Boer, I J M; Schmidely, P

2013-01-01

A meta-analysis was performed to explore the correlation between energy and nitrogen efficiency of dairy cows, and to study nutritional and animal factors that influence these efficiencies, as well as their relationship. Treatment mean values were extracted from 68 peer-reviewed studies, including 306 feeding trials. The main criterion for inclusion of a study in the meta-analysis was that it reported, or permitted calculation of, energy efficiency (Eeff; energy in milk/digestible energy intake) and nitrogen efficiency (Neff; nitrogen in milk/digestible nitrogen intake) at the digestible level (digestible energy or digestible protein). The effect of nutritional and animal variables, including neutral detergent fiber, acid detergent fiber (ADF), digestible energy, digestible protein, proportion of concentrate (PCO), dry matter intake, milk yield, days in milk, and body weight, on Eeff, Neff, and the Neff:Eeff ratio was analyzed using mixed models. The interstudy correlation between Eeff and Neff was 0.62, whereas the intrastudy correlation was 0.30. The higher interstudy correlation was partly due to milk yield and dry matter intake being present in both Eeff and Neff. We, therefore, also explored the Neff:Eeff ratio. Energy efficiency was negatively associated with ADF and PCO, whereas Neff was negatively associated with ADF and digestible energy. The Neff:Eeff ratio was affected by ADF and PCO only. In conclusion, the results indicate a possibility to maximize feed efficiency in terms of both energy and nitrogen at the same time. In other words, an improvement in Eeff would also mean an improvement in Neff. The current study also shows that these types of transverse data are not sufficient to study the effect of animal factors, such as days in milk, on feed efficiency. Longitudinal measurements per animal would probably be more appropriate. Copyright © 2013 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Exploratory Bi-factor Analysis: The Oblique Case.

PubMed

Jennrich, Robert I; Bentler, Peter M

2012-07-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford (Psychometrika 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler (Psychometrika 76:537-549, 2011) introduced an exploratory form of bi-factor analysis that does not require one to provide an explicit bi-factor structure a priori. They use exploratory factor analysis and a bifactor rotation criterion designed to produce a rotated loading matrix that has an approximate bi-factor structure. Among other things this can be used as an aid in finding an explicit bi-factor structure for use in a confirmatory bi-factor analysis. They considered only orthogonal rotation. The purpose of this paper is to consider oblique rotation and to compare it to orthogonal rotation. Because there are many more oblique rotations of an initial loading matrix than orthogonal rotations, one expects the oblique results to approximate a bi-factor structure better than orthogonal rotations and this is indeed the case. A surprising result arises when oblique bi-factor rotation methods are applied to ideal data.

Analysis of noise-induced temporal correlations in neuronal spike sequences

NASA Astrophysics Data System (ADS)

Reinoso, José A.; Torrent, M. C.; Masoller, Cristina

2016-11-01

We investigate temporal correlations in sequences of noise-induced neuronal spikes, using a symbolic method of time-series analysis. We focus on the sequence of time-intervals between consecutive spikes (inter-spike-intervals, ISIs). The analysis method, known as ordinal analysis, transforms the ISI sequence into a sequence of ordinal patterns (OPs), which are defined in terms of the relative ordering of consecutive ISIs. The ISI sequences are obtained from extensive simulations of two neuron models (FitzHugh-Nagumo, FHN, and integrate-and-fire, IF), with correlated noise. We find that, as the noise strength increases, temporal order gradually emerges, revealed by the existence of more frequent ordinal patterns in the ISI sequence. While in the FHN model the most frequent OP depends on the noise strength, in the IF model it is independent of the noise strength. In both models, the correlation time of the noise affects the OP probabilities but does not modify the most probable pattern.

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.

Factors that determine self-reported immunosuppressant adherence in kidney transplant recipients: a correlational study.

PubMed

Weng, Li-Chueh; Yang, Ya-Chen; Huang, Hsiu-Li; Chiang, Yang-Jen; Tsai, Yu-Hsia

2017-01-01

To determine the factors related to immunosuppressant therapy adherence in kidney transplant recipients in Taiwan. Adherence to immunosuppressant treatment is critical after kidney transplantation. Thus, the factors associated with self-reported medication adherence in kidney transplant recipients warrant investigation. The study used a cross-sectional and correlation design. A convenience sample of 145 kidney transplant recipients was included. Structured questionnaires were used to collect data during 2012-2013. Multivariate linear regression was used to examine the factors related to immunosuppressant therapy adherence. Over half of the participants were female (54·5%), mean age was 45·5 years, and mean year after transplant was 7·4. The mean score for medication adherence was 29·73 (possible score range 7-35). The results of the multivariate linear regression analysis showed that gender (male), low income with a high school or college education, years after transplantation and concerns about medication taking were negatively associated with adherence. Medication self-efficacy was positively associated with adherence. Therapy-related factors, partnerships with healthcare professionals and having private healthcare insurance did not significantly relate to immunosuppressant therapy adherence. Kidney transplant recipients demonstrated a high level of adherence. Strategies to enhance patients' self-efficacy and alleviate concerns about medication may promote medication adherence. Male patients, those with a lower income and those with a higher education level, should be a focus of efforts to maintain adherence to the medication regimen. © 2016 John Wiley & Sons Ltd.

Pantoea ananatis Genetic Diversity Analysis Reveals Limited Genomic Diversity as Well as Accessory Genes Correlated with Onion Pathogenicity.

PubMed

Stice, Shaun P; Stumpf, Spencer D; Gitaitis, Ron D; Kvitko, Brian H; Dutta, Bhabesh

2018-01-01

Pantoea ananatis is a member of the family Enterobacteriaceae and an enigmatic plant pathogen with a broad host range. Although P. ananatis strains can be aggressive on onion causing foliar necrosis and onion center rot, previous genomic analysis has shown that P. ananatis lacks the primary virulence secretion systems associated with other plant pathogens. We assessed a collection of fifty P. ananatis strains collected from Georgia over three decades to determine genetic factors that correlated with onion pathogenic potential. Previous genetic analysis studies have compared strains isolated from different hosts with varying diseases potential and isolation sources. Strains varied greatly in their pathogenic potential and aggressiveness on different cultivated Allium species like onion, leek, shallot, and chive. Using multi-locus sequence analysis (MLSA) and repetitive extragenic palindrome repeat (rep)-PCR techniques, we did not observe any correlation between onion pathogenic potential and genetic diversity among strains. Whole genome sequencing and pan-genomic analysis of a sub-set of 10 strains aided in the identification of a novel series of genetic regions, likely plasmid borne, and correlating with onion pathogenicity observed on single contigs of the genetic assemblies. We named these loci Onion Virulence Regions (OVR) A-D. The OVR loci contain genes involved in redox regulation as well as pectate lyase and rhamnogalacturonase genes. Previous studies have not identified distinct genetic loci or plasmids correlating with onion foliar pathogenicity or pathogenicity on a single host pathosystem. The lack of focus on a single host system for this phytopathgenic disease necessitates the pan-genomic analysis performed in this study.

Pantoea ananatis Genetic Diversity Analysis Reveals Limited Genomic Diversity as Well as Accessory Genes Correlated with Onion Pathogenicity

PubMed Central

Stice, Shaun P.; Stumpf, Spencer D.; Gitaitis, Ron D.; Kvitko, Brian H.; Dutta, Bhabesh

2018-01-01

Pantoea ananatis is a member of the family Enterobacteriaceae and an enigmatic plant pathogen with a broad host range. Although P. ananatis strains can be aggressive on onion causing foliar necrosis and onion center rot, previous genomic analysis has shown that P. ananatis lacks the primary virulence secretion systems associated with other plant pathogens. We assessed a collection of fifty P. ananatis strains collected from Georgia over three decades to determine genetic factors that correlated with onion pathogenic potential. Previous genetic analysis studies have compared strains isolated from different hosts with varying diseases potential and isolation sources. Strains varied greatly in their pathogenic potential and aggressiveness on different cultivated Allium species like onion, leek, shallot, and chive. Using multi-locus sequence analysis (MLSA) and repetitive extragenic palindrome repeat (rep)-PCR techniques, we did not observe any correlation between onion pathogenic potential and genetic diversity among strains. Whole genome sequencing and pan-genomic analysis of a sub-set of 10 strains aided in the identification of a novel series of genetic regions, likely plasmid borne, and correlating with onion pathogenicity observed on single contigs of the genetic assemblies. We named these loci Onion Virulence Regions (OVR) A-D. The OVR loci contain genes involved in redox regulation as well as pectate lyase and rhamnogalacturonase genes. Previous studies have not identified distinct genetic loci or plasmids correlating with onion foliar pathogenicity or pathogenicity on a single host pathosystem. The lack of focus on a single host system for this phytopathgenic disease necessitates the pan-genomic analysis performed in this study. PMID:29491851

Prevalence and correlates of hypertension in Maharashtra, India: A multilevel analysis

PubMed Central

Bhise, Mahadev D.

2018-01-01

Background and aim In the last few decades, the prevalence of hypertension has been drastically increased in India. The present study estimates the current prevalence of hypertension and its correlates in the state of Maharashtra. The variation in the prevalence of hypertension associated with individual-level characteristics is explained at the community and district level. Methods Data is used from the recent round of District Level Household & Facility Survey (DLHS-4), 2012–13. The DLHS-4 has used the nationally representative sample, collected through multistage stratified sampling procedure. A similar sampling frame, used in NSSO-2007-08, has been followed. The chi-square test is used to show the significance level of the association between the estimated prevalence of hypertension and its correlates. Multilevel regression analysis is carried out to investigate the effects of individual and community level factors on the prevalence of hypertension. Results The overall prevalence of hypertension is 25% in Maharashtra, and a huge variation in the prevalence of hypertension is found across the districts. Dhule, Gadchiroli (with a low HDI rank), Mumbai and Satara (with higher HDI rank) are the districts with the higher (above 30%) prevalence of high blood pressure. The prevalence also significantly varies according to different correlates. The prevalence of high blood pressure is higher among elderly population (40%), among males (28%), in the urban areas (27%) and in the richest wealth quintile (28%). The prevalence is also higher among cigarette smokers (31%), alcohol consumers (30%) and people with obesity (38%) as compared to their counterparts. The results of the multilevel analysis show that the older and obese persons are at four-time higher risk of hypertension. Again, age, sex, marital status, place of residence, wealth status, unhealthy habits (i.e. smoking and alcohol consumption) and BMI are significantly associated with hypertension. The results of

Prevalence and correlates of hypertension in Maharashtra, India: A multilevel analysis.

PubMed

Bhise, Mahadev D; Patra, Shraboni

2018-01-01

In the last few decades, the prevalence of hypertension has been drastically increased in India. The present study estimates the current prevalence of hypertension and its correlates in the state of Maharashtra. The variation in the prevalence of hypertension associated with individual-level characteristics is explained at the community and district level. Data is used from the recent round of District Level Household & Facility Survey (DLHS-4), 2012-13. The DLHS-4 has used the nationally representative sample, collected through multistage stratified sampling procedure. A similar sampling frame, used in NSSO-2007-08, has been followed. The chi-square test is used to show the significance level of the association between the estimated prevalence of hypertension and its correlates. Multilevel regression analysis is carried out to investigate the effects of individual and community level factors on the prevalence of hypertension. The overall prevalence of hypertension is 25% in Maharashtra, and a huge variation in the prevalence of hypertension is found across the districts. Dhule, Gadchiroli (with a low HDI rank), Mumbai and Satara (with higher HDI rank) are the districts with the higher (above 30%) prevalence of high blood pressure. The prevalence also significantly varies according to different correlates. The prevalence of high blood pressure is higher among elderly population (40%), among males (28%), in the urban areas (27%) and in the richest wealth quintile (28%). The prevalence is also higher among cigarette smokers (31%), alcohol consumers (30%) and people with obesity (38%) as compared to their counterparts. The results of the multilevel analysis show that the older and obese persons are at four-time higher risk of hypertension. Again, age, sex, marital status, place of residence, wealth status, unhealthy habits (i.e. smoking and alcohol consumption) and BMI are significantly associated with hypertension. The results of VPC statistics show that 14% of

Television Time among Brazilian Adolescents: Correlated Factors are Different between Boys and Girls

PubMed Central

Tremblay, Mark Stephen; Gonçalves, Eliane Cristina de Andrade; Silva, Roberto Jerônimo dos Santos

2014-01-01

Objective. The aim of this study was to identify the prevalence of excess television time and verify correlated factors in adolescent males and females. Methods. This cross-sectional study included 2,105 adolescents aged from 13 to 18 years from the city of Aracaju, Northeastern Brazil. Television time was self-reported, corresponding to the time spent watching television in a typical week. Several correlates were examined including age, skin color, socioeconomic status, parent education, physical activity level, consumption of fruits and vegetables, smoking status, alcohol use, and sports team participation. Results. The prevalence excess television time (≥2 hours/day) in girls and boys was 70.9% and 66.2%, respectively. Girls with low socioeconomic status or inadequate consumption of fruits and vegetables were more likely to have excess television time. Among boys, those >16 years of age or with black skin color were more likely to have excess television time. Conclusions. Excess television time was observed in more than two-thirds of adolescents, being more evident in girls. Correlated factors differed according to sex. Efforts to reduce television time among Brazilian adolescents, and replace with more active pursuits, may yield desirable public health benefits. PMID:24723826

Influencing factors of NT-proBNP level inheart failure patients with different cardiacfunctions and correlation with prognosis.

PubMed

Xu, Liang; Chen, Yanchun; Ji, Yanni; Yang, Song

2018-06-01

Factors influencing N-terminal pro-brain natriuretic peptide (NT-proBNP) level in heart failure patients with different cardiac functions were identified to explore the correlations with prognosis. Eighty heart failure patients with different cardiac functions treated in Yixing People's Hospital from January 2016 to June 2017 were selected, and divided into two groups (group with cardiac function in class II and below and group with cardiac function in class III and above), according to the cardiac function classification established by New York Heart Association (NYHA). Blood biochemical test and outcome analysis were conducted to measure serum NT-proBNP and matrix metalloproteinase-9 (MMP-9) levels in patients with different cardiac functions, and correlations between levels of NT-proBNP and MMP-9 and left ventricular ejection fraction (LVEF) level were analyzed in patients with different cardiac functions at the same time. In addition, risk factors for heart failure in patients with different cardiac functions were analyzed. Compared with the group with cardiac function in class III and above, the group with cardiac function in class II and below had significantly lower serum NT-proBNP and MMP-9 levels (p<0.05). For echocardiogram indexes, left ventricular end-diastolic diameter (LVEDD) and left ventricular end-systolic diameter (LVESD) in the group with cardiac function in class II and below were obviously lower than those in the group with cardiac function in class III and above (p<0.05), while LVEF was higher in group with cardiac function in class II and below than that in group with cardiac function in class III and above (p<0.05). NT-proBNP and MMP-9 levels were negatively correlated with LVEF level [r=-0.8517 and -0.8517, respectively, p<0.001 (<0.05)]. Cardiac function in class III and above, increased NT-proBNP, increased MMP-9 and decreased LVEF were relevant risk factors and independent risk factors for heart failure in patients with different cardiac

Factor analysis and psychometric properties of the Mother-Adolescent Sexual Communication (MASC) instrument for sexual risk behavior.

PubMed

Cox, Mary Foster; Fasolino, Tracy K; Tavakoli, Abbas S

2008-01-01

Sexual risk behavior is a public health problem among adolescents living at or below poverty level. Approximately 1 million pregnancies and 3 million cases of sexually transmitted infections (STIs) are reported yearly. Parenting plays a significant role in adolescent behavior, with mother-adolescent sexual communication correlated with absent or delayed sexual behavior. This study developed an instrument examining constructs of mother-adolescent communication, the Mother-Adolescent Sexual Communication (MASC) instrument. A convenience sample of 99 mothers of middle school children completed the self-administered questionnaires. The original 34-item MASC was reduced to 18 items. Exploratory factor analysis was conducted on the 18-item scale, which resulted in four factors explaining 84.63% of the total variance. Internal consistency analysis produced Cronbach alpha coefficients of .87, .90, .82, and .71 for the four factors, respectively. Convergent validity via hypothesis testing was supported by significant correlations with several subscales of the Parent-Child Relationship Questionnaire (PCRQ) with MASC factors, that is, content and style factors with warmth, personal relationships and disciplinary warmth subscales of the PCRQ, the context factor with personal relationships, and the timing factor with warmth. In light of these findings, the psychometric characteristics and multidimensional perspective of the MASC instrument show evidence of usefulness for measuring and advancing knowledge of mother and adolescent sexual communication techniques.

Exploratory factor analysis of the Dizziness Handicap Inventory (German version).

PubMed

Kurre, Annette; Bastiaenen, Caroline Hg; van Gool, Christel Jaw; Gloor-Juzi, Thomas; de Bruin, Eling D; Straumann, Dominik

2010-03-15

The Dizziness Handicap Inventory (DHI) is a validated, self-report questionnaire which is widely used as an outcome measure. Previous studies supported the multidimensionality of the DHI, but not the original subscale structure. The objectives of this survey were to explore the dimensions of the Dizziness Handicap Inventory - German version, and to investigate the associations of the retained factors with items assessing functional disability and the Hospital Anxiety and Depression Scale (HADS). Secondly we aimed to explore the retained factors according to the International Classification of Functioning, Disability and Health (ICF). Patients were recruited from a tertiary centre for vertigo, dizziness or balance disorders. They filled in two questionnaires: (1) The DHI assesses precipitating physical factors associated with dizziness/unsteadiness and functional/emotional consequences of symptoms. (2) The HADS assesses non-somatic symptoms of anxiety and depression. In addition, patients answered the third question of the University of California Los Angeles-Dizziness Questionnaire which covers the impact of dizziness and unsteadiness on everyday activities. Principal component analysis (PCA) was performed to explore the dimensions of the DHI. Associations were estimated by Spearman correlation coefficients. One hundred ninety-four patients with dizziness or unsteadiness associated with a vestibular disorder, mean age (standard deviation) of 50.6 (13.6) years, participated. Based on eigenvalues greater one respectively the scree plot we analysed diverse factor solutions. The 3-factor solution seems to be reliable, clinically relevant and can partly be explained with the ICF. It explains 49.2% of the variance. Factor 1 comprises the effect of dizziness and unsteadiness on emotion and participation, factor 2 informs about specific activities or effort provoking dizziness and unsteadiness, and factor 3 focuses on self-perceived walking ability in relation to

Exploratory factor analysis of the Dizziness Handicap Inventory (German version)

PubMed Central

2010-01-01

Background The Dizziness Handicap Inventory (DHI) is a validated, self-report questionnaire which is widely used as an outcome measure. Previous studies supported the multidimensionality of the DHI, but not the original subscale structure. The objectives of this survey were to explore the dimensions of the Dizziness Handicap Inventory - German version, and to investigate the associations of the retained factors with items assessing functional disability and the Hospital Anxiety and Depression Scale (HADS). Secondly we aimed to explore the retained factors according to the International Classification of Functioning, Disability and Health (ICF). Methods Patients were recruited from a tertiary centre for vertigo, dizziness or balance disorders. They filled in two questionnaires: (1) The DHI assesses precipitating physical factors associated with dizziness/unsteadiness and functional/emotional consequences of symptoms. (2) The HADS assesses non-somatic symptoms of anxiety and depression. In addition, patients answered the third question of the University of California Los Angeles-Dizziness Questionnaire which covers the impact of dizziness and unsteadiness on everyday activities. Principal component analysis (PCA) was performed to explore the dimensions of the DHI. Associations were estimated by Spearman correlation coefficients. Results One hundred ninety-four patients with dizziness or unsteadiness associated with a vestibular disorder, mean age (standard deviation) of 50.6 (13.6) years, participated. Based on eigenvalues greater one respectively the scree plot we analysed diverse factor solutions. The 3-factor solution seems to be reliable, clinically relevant and can partly be explained with the ICF. It explains 49.2% of the variance. Factor 1 comprises the effect of dizziness and unsteadiness on emotion and participation, factor 2 informs about specific activities or effort provoking dizziness and unsteadiness, and factor 3 focuses on self-perceived walking

Chaotic Brillouin optical correlation-domain analysis

NASA Astrophysics Data System (ADS)

Zhang, Jianzhong; Zhang, Mingtao; Zhang, Mingjiang; Liu, Yi; Feng, Changkun; Wang, Yahui; Wang, Yuncai

2018-04-01

We propose and experimentally demonstrate a chaotic Brillouin optical correlation-domain analysis (BOCDA) system for distributed fiber sensing. The utilization of the chaotic laser with low coherent state ensures high spatial resolution. The experimental results demonstrate a 3.92-cm spatial resolution over a 906-m measurement range. The uncertainty in the measurement of the local Brillouin frequency shift is 1.2MHz. The measurement signal-to-noise ratio is given, which is agreement with the theoretical value.

Analyzing the Cross-Correlation Between Onshore and Offshore RMB Exchange Rates Based on Multifractal Detrended Cross-Correlation Analysis (MF-DCCA)

NASA Astrophysics Data System (ADS)

Xie, Chi; Zhou, Yingying; Wang, Gangjin; Yan, Xinguo

We use the multifractal detrended cross-correlation analysis (MF-DCCA) method to explore the multifractal behavior of the cross-correlation between exchange rates of onshore RMB (CNY) and offshore RMB (CNH) against US dollar (USD). The empirical data are daily prices of CNY/USD and CNH/USD from May 1, 2012 to February 29, 2016. The results demonstrate that: (i) the cross-correlation between CNY/USD and CNH/USD is persistent and its fluctuation is smaller when the order of fluctuation function is negative than that when the order is positive; (ii) the multifractal behavior of the cross-correlation between CNY/USD and CNH/USD is significant during the sample period; (iii) the dynamic Hurst exponents obtained by the rolling windows analysis show that the cross-correlation is stable when the global economic situation is good and volatile in bad situation; and (iv) the non-normal distribution of original data has a greater effect on the multifractality of the cross-correlation between CNY/USD and CNH/USD than the temporary correlation.

The Interest Checklist: a factor analysis.

PubMed

Klyczek, J P; Bauer-Yox, N; Fiedler, R C

1997-01-01

The purpose of this study was to determine whether the 80 items on the Interest Checklist empirically cluster into the five categories of interests described by Matsutsuyu, the developer of the tool. The Interest Checklist was administered to 367 subjects classified in three subgroups: students, working adults, and retired elderly persons. An 80-item correlation matrix was formed from the responses to the Interest Checklist for each subgroup and then used in a factor analysis model to identify the underlying structure or domains of interest. Results indicated that the Social Recreation theoretical category was empirically independent for all three subgroups; the Physical Sports and Cultural/Educational theoretical categories were empirically independent for only the college students and working adults; and the Manual Skills theoretical category was empirically independent for only the working adults. Although therapists should continue to be cautious in their interpretation of patients' Interest Checklist scores, the tool is useful for identifying patients' interests in order to choose meaningful activities for therapy.

The combined use of dynamic factor analysis and wavelet analysis to evaluate latent factors controlling complex groundwater level fluctuations in a riverside alluvial aquifer

NASA Astrophysics Data System (ADS)

Oh, Yun-Yeong; Yun, Seong-Taek; Yu, Soonyoung; Hamm, Se-Yeong

2017-12-01

To identify and quantitatively evaluate complex latent factors controlling groundwater level (GWL) fluctuations in a riverside alluvial aquifer influenced by barrage construction, we developed the combined use of dynamic factor analysis (DFA) and wavelet analysis (WA). Time series data of GWL, river water level and precipitation were collected for 3 years (July 2012 to June 2015) from an alluvial aquifer underneath an agricultural area of the Nakdong river basin, South Korea. Based on the wavelet coefficients of the final approximation, the GWL data was clustered into three groups (WCG1 to WCG3). Two dynamic factors (DFs) were then extracted using DFA for each group; thus, six major factors were extracted. Next, the time-frequency variability of the extracted DFs was examined using multiresolution cross-correlation analysis (MRCCA) with the following steps: 1) major driving forces and their scales in GWL fluctuations were identified by comparing maximum correlation coefficients (rmax) between DFs and the GWL time series and 2) the results were supplemented using the wavelet transformed coherence (WTC) analysis between DFs and the hydrological time series. Finally, relative contributions of six major DFs to the GWL fluctuations could be quantitatively assessed by calculating the effective dynamic efficiency (Def). The characteristics and relevant process of the identified six DFs are: 1) WCG1DF4,1 as an indicative of seasonal agricultural pumping (scales = 64-128 days; rmax = 0.68-0.89; Def ≤ 23.1%); 2) WCG1DF4,4 representing the cycle of regional groundwater recharge (scales = 64-128 days; rmax = 0.98-1.00; Def ≤ 11.1%); 3) WCG2DF4,1 indicating the complex interaction between the episodes of precipitation and direct runoff (scales = 2-8 days; rmax = 0.82-0.91; Def ≤ 35.3%) and seasonal GW-RW interaction (scales = 64-128 days; rmax = 0.76-0.91; Def ≤ 14.2%); 4) WCG2DF4,4 reflecting the complex effects of seasonal pervasive pumping and the local recharge

Correlations between metabolic syndrome, serologic factors, and gallstones

PubMed Central

Sang, Jae Hong; Ki, Nam Kyun; Cho, Jae Hwan; Ahn, Jae Ouk; Sunwoo, Jae Gun

2016-01-01

[Purpose] This study investigated the serologic factors associated with metabolic syndrome and gallstones. [Subjects and Methods] The study evaluated subjects who visited a health promotion center in Seoul from March 2, 2013 to February 28, 2014, and had undergone abdominal ultrasonography. Height, weight, and blood pressure were measured. Blood sampling was performed for high-density lipoprotein cholesterol, triglyceride, fasting blood glucose, total bilirubin, direct bilirubin, indirect bilirubin, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, uric acid, total cholesterol, low-density lipoprotein cholesterol, thyroid stimulating hormone, and red and white blood cell counts. We conducted logistic regression analysis to assess the risk factors associated with metabolic syndrome. [Results] The risk factors for metabolic syndrome in men, in order of decreasing weight, were red blood cell count, body mass index, maximum size of gallstones, white blood cell count, waist circumference, and uric acid level. The factors in women, in order of decreasing weight, were red blood cell count, presence/absence of gallstones, uric acid level, body mass index, fasting blood glucose, and waist circumference. [Conclusion] Most serum biochemical factors and gallstone occurrence could be used to indicate the presence or absence of metabolic syndrome, independent of gender. PMID:27630427

Multifractal detrended Cross Correlation Analysis of Foreign Exchange and SENSEX fluctuation in Indian perspective

NASA Astrophysics Data System (ADS)

Dutta, Srimonti; Ghosh, Dipak; Chatterjee, Sucharita

2016-12-01

The manuscript studies autocorrelation and cross correlation of SENSEX fluctuations and Forex Exchange Rate in respect to Indian scenario. Multifractal detrended fluctuation analysis (MFDFA) and multifractal detrended cross correlation analysis (MFDXA) were employed to study the correlation between the two series. It was observed that the two series are strongly cross correlated. The change of degree of cross correlation with time was studied and the results are interpreted qualitatively.

Analysis of spectra using correlation functions

NASA Technical Reports Server (NTRS)

Beer, Reinhard; Norton, Robert H.

1988-01-01

A novel method is presented for the quantitative analysis of spectra based on the properties of the cross correlation between a real spectrum and either a numerical synthesis or laboratory simulation. A new goodness-of-fit criterion called the heteromorphic coefficient H is proposed that has the property of being zero when a fit is achieved and varying smoothly through zero as the iteration proceeds, providing a powerful tool for automatic or near-automatic analysis. It is also shown that H can be rendered substantially noise-immune, permitting the analysis of very weak spectra well below the apparent noise level and, as a byproduct, providing Doppler shift and radial velocity information with excellent precision. The technique is in regular use in the Atmospheric Trace Molecule Spectroscopy (ATMOS) project and operates in an interactive, realtime computing environment with turn-around times of a few seconds or less.

Mobility and Balance and Their Correlation with Physiological Factors in Elderly with Different Foot Postures

PubMed Central

Mohd Said, Aisyah; Bukry, Saiful Adli

2015-01-01

This study determines (1) the correlation between mobility and balance performances with physiological factors and (2) the relationship between foot postures with anthropometric characteristics and lower limb characteristics among elderly with neutral, pronated, and supinated foot. A cross-sectional observational study was conducted in community-dwelling elderly (age: 69.86 ± 5.62 years). Participants were grouped into neutral (n = 16), pronated (n = 14), and supinated (n = 14) foot based on the foot posture index classification. Anthropometric data (height, weight, and BMI), lower limb strength (5-STS) and endurance (30 s chair rise test), mobility (TUG), and balance (FSST) were determined. Data were analyzed using Spearman's correlation coefficient. Body weight was negatively and moderately correlated (r s = −0.552, P < 0.05) with mobility in supinated foot; moderate-to-high positive linear rank correlation was found between lower limb strength and mobility (r s = 0.551 to 0.804, P < 0.05) for pronated and neutral foot. Lower limb endurance was negatively and linearly correlated with mobility in pronated (r s = −0.699) and neutral (r s = −0.573) foot. No correlation was observed in balance performance with physiological factors in any of the foot postures. We can conclude that muscle function may be the most important feature to make movement possible in older persons regardless of the type of foot postures. PMID:26583104

Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations

NASA Astrophysics Data System (ADS)

Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław

2015-11-01

The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.

Spatial econometric analysis of factors influencing regional energy efficiency in China.

PubMed

Song, Malin; Chen, Yu; An, Qingxian

2018-05-01

Increased environmental pollution and energy consumption caused by the country's rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model-data envelopment analysis (SBM-DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson's maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000-2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China's energy efficiency and regional coordinated development.

Information-Pooling Bias in Collaborative Security Incident Correlation Analysis.

PubMed

Rajivan, Prashanth; Cooke, Nancy J

2018-03-01

Incident correlation is a vital step in the cybersecurity threat detection process. This article presents research on the effect of group-level information-pooling bias on collaborative incident correlation analysis in a synthetic task environment. Past research has shown that uneven information distribution biases people to share information that is known to most team members and prevents them from sharing any unique information available with them. The effect of such biases on security team collaborations are largely unknown. Thirty 3-person teams performed two threat detection missions involving information sharing and correlating security incidents. Incidents were predistributed to each person in the team based on the hidden profile paradigm. Participant teams, randomly assigned to three experimental groups, used different collaboration aids during Mission 2. Communication analysis revealed that participant teams were 3 times more likely to discuss security incidents commonly known to the majority. Unaided team collaboration was inefficient in finding associations between security incidents uniquely available to each member of the team. Visualizations that augment perceptual processing and recognition memory were found to mitigate the bias. The data suggest that (a) security analyst teams, when conducting collaborative correlation analysis, could be inefficient in pooling unique information from their peers; (b) employing off-the-shelf collaboration tools in cybersecurity defense environments is inadequate; and (c) collaborative security visualization tools developed considering the human cognitive limitations of security analysts is necessary. Potential applications of this research include development of team training procedures and collaboration tool development for security analysts.

Analysis of correlation factors and pregnancy outcomes of hypertensive disorders of pregnancy - a secondary analysis of a random sampling in Beijing, China.

PubMed

Zhu, Yu-Chun; Yang, Hui-Xia; Wei, Yu-Mei; Zhu, Wei-Wei; Meng, Wen-Ying; Wang, Yong-Qing; Shang, Li-Xin; Cai, Zhen-Yu; Ji, Li-Ping; Wang, Yun-Feng; Sun, Ying; Liu, Jia-Xiu; Wei, Li; Sun, Yu-Feng; Zhang, Xue-Ying; Luo, Tian-Xia; Chen, Hai-Xia; Yu, Li-Jun

2017-03-01

We aimed to assess the prevalence and risk factors for hypertensive disorders and to study the main pregnancy outcomes in the Beijing area of China. This study randomly sampled 15 hospitals in Beijing from Jun 2013 to Nov 2013 and evaluated 15 194 deliveries. Logistic regression analysis was used to study the association between risk factors and hypertensive disorders. Pregnancy outcomes included preterm birth, cesarean delivery and small for gestational age (SGA). The prevalence of hypertensive disorders, preeclampsia (PE) and severe PE was 4.4, 2.7 and 1.8%, respectively. The risk factors for hypertensive disorders and severe PE were maternal body mass index before pregnancy, gestational weight gain (GWG), gestational diabetes and pre-gestational diabetes, and third trimester cholesterol (CHOL) levels. First trimester high-density lipoprotein was a protective factor for severe PE. The incidence of hypertensive disorders increased with maternal age. Preterm delivery, cesarean delivery and small infant size for gestational age were more prevalent in the severe PE group compared with the non-hypertensive group. In the Beijing area of China, maternal body mass index before pregnancy, GWG, maternal complications of gestational diabetes and pre-gestational diabetes, and third trimester CHOL levels are risk factors for both hypertensive disorders of pregnancy and severe PE. First trimester high-density lipoprotein is a protective factor for severe PE. Severe preeclampsia leads to a higher incidence of preterm delivery, cesarean delivery and SGA infants.

Confirmatory factor analysis of the Chinese version of the Pediatric Quality-of-Life Inventory Cancer Module.

PubMed

Li, Ho Cheung William; Williams, Phoebe D; Williams, Arthur R; Chung, Joyce O K; Chiu, Sau Ying; Lopez, Violeta

2013-01-01

Before the Chinese version of the Pediatric Quality-of-Life Inventory Cancer Module can be used to assess the multidimensional construct of quality of life among Hong Kong Chinese pediatric patients with cancer, its psychometric properties need to be further empirically tested. The objectives of the study were to establish the construct validity, including hypothesis testing and a confirmatory factor analysis of factor structure, of the Chinese version of the Pediatric Quality-of-Life Inventory Cancer Module. A cross-sectional study was used; 200 children hospitalized with cancer (9- to 16-year-olds) were recruited. Participants were asked to respond to the Chinese version of the Cancer Module, Therapy-Related Symptom Checklist, and Rosenberg's Self-esteem Scale. The results showed that there was a strong positive correlation between children's self-esteem and quality of life (r = 0.50) and a strong negative correlation between children's therapy-related symptoms and quality of life (r = -0.65). Confirmatory factor analysis indicated that there were 7 factors underlying the Chinese version of the Cancer Module. The study added further evidence of the construct validity of the Chinese version of the Cancer Module, patient version. The Cancer Module can be used to assess and evaluate psychological interventions directed toward promoting the quality of life of children hospitalized with cancer.

Correlations between brain structure and symptom dimensions of psychosis in schizophrenia, schizoaffective, and psychotic bipolar I disorders.

PubMed

Padmanabhan, Jaya L; Tandon, Neeraj; Haller, Chiara S; Mathew, Ian T; Eack, Shaun M; Clementz, Brett A; Pearlson, Godfrey D; Sweeney, John A; Tamminga, Carol A; Keshavan, Matcheri S

2015-01-01

Structural alterations may correlate with symptom severity in psychotic disorders, but the existing literature on this issue is heterogeneous. In addition, it is not known how cortical thickness and cortical surface area correlate with symptom dimensions of psychosis. Subjects included 455 individuals with schizophrenia, schizoaffective, or bipolar I disorders. Data were obtained as part of the Bipolar Schizophrenia Network for Intermediate Phenotypes study. Diagnosis was made through the Structured Clinical Interview for DSM-IV. Positive and negative symptom subscales were assessed using the Positive and Negative Syndrome Scale. Structural brain measurements were extracted from T1-weight structural MRIs using FreeSurfer v5.1 and were correlated with symptom subscales using partial correlations. Exploratory factor analysis was also used to identify factors among those regions correlating with symptom subscales. The positive symptom subscale correlated inversely with gray matter volume (GMV) and cortical thickness in frontal and temporal regions, whereas the negative symptom subscale correlated inversely with right frontal cortical surface area. Among regions correlating with the positive subscale, factor analysis identified four factors, including a temporal cortical thickness factor and frontal GMV factor. Among regions correlating with the negative subscale, factor analysis identified a frontal GMV-cortical surface area factor. There was no significant diagnosis by structure interactions with symptom severity. Structural measures correlate with positive and negative symptom severity in psychotic disorders. Cortical thickness demonstrated more associations with psychopathology than cortical surface area. © The Author 2014. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

KIT mutations correlate with adverse survival in children with core-binding factor acute myeloid leukemia.

PubMed

Chen, Xi; Dou, Hu; Wang, Xingjuan; Huang, Yi; Lu, Ling; Bin, Junqing; Su, Yongchun; Zou, Lin; Yu, Jie; Bao, Liming

2018-04-01

The prevalence and clinical relevance of KIT mutations in childhood core-binding factor (CBF) acute myeloid leukemia (AML) have not been well characterized. In this study, a total of 212 children with de novo AML were enrolled from a Chinese population and 50 (23.5%) of the patients were deemed CBF-AML. KIT mutations were identified in 30% of the CBF-AML cohort. The KIT mutations were clustered in exon 17 and exon 8, and KIT mutations in exons 8 and 17 were correlated with a shorter overall survival (OS) (5-year OS: 30.0 ± 14.5% vs. 73.0 ± 8.5%, p = .007) and event-free survival (EFS) (5-year EFS: 30.0 ± 14.5% vs. 73.0 ± 8.5%, p = .003). Multivariate analysis revealed KIT mutations as an independent risk factor in CBF-AML. Our results suggest that KIT mutations are a molecular marker for an inferior prognosis in pediatric CBF-AML.

Correlates of Successful Aging: Are They Universal?

ERIC Educational Resources Information Center

Litwin, Howard

2005-01-01

The analysis compared differing correlates of life satisfaction among three diverse population groups in Israel, examining background and health status variables, social environment factors, and activity indicators. Multiple regression analysis revealed that veteran Jewish-Israelis (n = 2,043) had the largest set of predictors, the strongest of…

Integrative analysis of gene expression and copy number alterations using canonical correlation analysis.

PubMed

Soneson, Charlotte; Lilljebjörn, Henrik; Fioretos, Thoas; Fontes, Magnus

2010-04-15

With the rapid development of new genetic measurement methods, several types of genetic alterations can be quantified in a high-throughput manner. While the initial focus has been on investigating each data set separately, there is an increasing interest in studying the correlation structure between two or more data sets. Multivariate methods based on Canonical Correlation Analysis (CCA) have been proposed for integrating paired genetic data sets. The high dimensionality of microarray data imposes computational difficulties, which have been addressed for instance by studying the covariance structure of the data, or by reducing the number of variables prior to applying the CCA. In this work, we propose a new method for analyzing high-dimensional paired genetic data sets, which mainly emphasizes the correlation structure and still permits efficient application to very large data sets. The method is implemented by translating a regularized CCA to its dual form, where the computational complexity depends mainly on the number of samples instead of the number of variables. The optimal regularization parameters are chosen by cross-validation. We apply the regularized dual CCA, as well as a classical CCA preceded by a dimension-reducing Principal Components Analysis (PCA), to a paired data set of gene expression changes and copy number alterations in leukemia. Using the correlation-maximizing methods, regularized dual CCA and PCA+CCA, we show that without pre-selection of known disease-relevant genes, and without using information about clinical class membership, an exploratory analysis singles out two patient groups, corresponding to well-known leukemia subtypes. Furthermore, the variables showing the highest relevance to the extracted features agree with previous biological knowledge concerning copy number alterations and gene expression changes in these subtypes. Finally, the correlation-maximizing methods are shown to yield results which are more biologically

Quantitative study of the correlation between cerebellar retraction factors and hearing loss following microvascular decompression for hemifacial spasm.

PubMed

Li, Ning; Zhao, Wei-Guo; Pu, Chun-Hua; Yang, Wen-Lei

2018-01-01

This prospective study quantitatively measured the cerebellar retraction factors, including retraction distance, depth and duration, and evaluated their potential relationship to the development of hearing loss after microvascular decompression (MVD) for hemifacial spasm (HFS). One hundred ten patients with primary HFS who underwent MVD in our department were included into this study. The cerebellar retraction factors were quantitatively measured on preoperative MR and timed during MVD. Associations of cerebellar retraction and other factors to postoperative hearing loss were analyzed. Eleven (10%) patients developed hearing loss after MVD. Compared with the group without hearing loss, the cerebellar retraction distance, depth and duration of the group with hearing loss were significantly greater (p < 0.05). Multivariate regression analysis showed that greater cerebellar retraction depth and longer retraction duration were significantly associated with a higher incidence of postoperative hearing impairment (p < 0.05). This study strongly suggested a correlation between the cerebellar retraction factors, especially retraction depth and duration, and possibility of hearing loss following MVD for HFS.

Exploratory Bi-Factor Analysis: The Oblique Case

ERIC Educational Resources Information Center

Jennrich, Robert I.; Bentler, Peter M.

2012-01-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford ("Psychometrika" 47:41-54, 1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler ("Psychometrika" 76:537-549, 2011) introduced an exploratory form of bi-factor…

An ecological analysis of environmental correlates of active commuting in urban U.S.

PubMed

Fan, Jessie X; Wen, Ming; Kowaleski-Jones, Lori

2014-11-01

We conduct a cross-sectional ecological analysis to examine environmental correlates of active commuting in 39,660 urban tracts using data from the 2010 Census, 2007-2011 American Community Survey, and other sources. The five-year average (2007-2011) prevalence is 3.05% for walking, 0.63% for biking, and 7.28% for public transportation to work, with higher prevalence for all modes in lower-income tracts. Environmental factors account for more variances in public transportation to work but economic and demographic factors account for more variances in walking and biking to work. Population density, median housing age, street connectivity, tree canopy, distance to parks, air quality, and county sprawl index are associated with active commuting, but the association can vary in size and direction for different transportation mode and for higher-income and lower-income tracts. Copyright © 2014 Elsevier Ltd. All rights reserved.

Bayesian Exploratory Factor Analysis

PubMed Central

Conti, Gabriella; Frühwirth-Schnatter, Sylvia; Heckman, James J.; Piatek, Rémi

2014-01-01

This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings. Classical identification criteria are applied and integrated into our Bayesian procedure to generate models that are stable and clearly interpretable. A Monte Carlo study confirms the validity of the approach. The method is used to produce interpretable low dimensional aggregates from a high dimensional set of psychological measurements. PMID:25431517

L2 Reading Comprehension and Its Correlates: A Meta-Analysis

ERIC Educational Resources Information Center

Jeon, Eun Hee; Yamashita, Junko

2014-01-01

The present meta-analysis examined the overall average correlation (weighted for sample size and corrected for measurement error) between passage-level second language (L2) reading comprehension and 10 key reading component variables investigated in the research domain. Four high-evidence correlates (with 18 or more accumulated effect sizes: L2…

Factor structure and clinical correlates of the 61-item Wender Utah Rating Scale (WURS).

PubMed

Calamia, Matthew; Hill, Benjamin D; Musso, Mandi W; Pella, Russell D; Gouvier, Wm Drew

2018-02-09

The objective of this study was to assess the factor structure and clinical correlates of a 61-item version of the Wender Utah Rating Scale (WURS), a self-report retrospective measure of childhood problems, experiences, and behavior used in ADHD assessment. Given the currently mostly widely used form of the WURS was derived via a criterion-keyed approach, the study aimed to use latent variable modeling of the 61-item WURS to potentially identify more and more homogeneous set of items reflecting current conceptualizations of ADHD symptoms. Exploratory structural equation modeling was used to generate factor scores which were then correlated with neuropsychological measures of intelligence and executive attention as well as a broad measure of personality and emotional functioning. Support for a modified five-factor model was found: ADHD, disruptive mood and behavior, negative affectivity, social confidence, and academic problems. The ADHD factor differed somewhat from the traditional 25-item WURS short form largely through weaker associations with several measures of personality and psychopathology. This study identified a factor more aligned with DSM-5 conceptualization of ADHD as well as measures of other types of childhood characteristics and symptoms which may prove useful for both research and clinical practice.

Factor analysis of the Mayo-Portland Adaptability Inventory: structure and validity.

PubMed

Bohac, D L; Malec, J F; Moessner, A M

1997-07-01

Principal-components (PC) factor analysis of the Mayo-Portland Adaptability Inventory (MPAI) was conducted using a sample of outpatients (n = 189) with acquired brain injury (ABI) to evaluate whether outcome after ABI is multifactorial or unifactorial in nature. An eight-factor model was derived which explained 64-4% of the total variance. The eight factors were interpreted as representing Activities of Daily Living, Social Initiation, Cognition, Impaired-Self-awareness/Distress, Social Skills/ Support, Independence, Visuoperceptual, and Psychiatric, respectively. Validation of the Cognition factor was supported when factor scores were correlated with various neuropsychological measures. In addition, 117 patient self-rating total scores were used to evaluate the Impaired Self-awareness/Distress factor. An inverse relationship was observed, supporting this factor's ability to capture the two-dimensional phenomena of diminished self-awareness or enhanced emotional distress. A new subscale structure is suggested, that may allow greater clinical utility in understanding how ABI manifests in patients, and may provide clinicians with a better structure for implementing treatment strategies to address specific areas of impairment and disability for specific patients. Additionally, more precise measurement of treatment outcomes may be afforded by this reorganization.

A MAD Explanation for the Correlation between Bulk Lorentz Factor and Minimum Variability Timescale

NASA Astrophysics Data System (ADS)

Lloyd-Ronning, Nicole; Lei, Wei-hua; Xie, Wei

2018-04-01

We offer an explanation for the anti-correlation between the minimum variability timescale (MTS) in the prompt emission light curve of gamma-ray bursts (GRBs) and the estimated bulk Lorentz factor of these GRBs, in the context of a magnetically arrested disk (MAD) model. In particular, we show that previously derived limits on the maximum available energy per baryon in a Blandford-Znajek jet leads to a relationship between the characteristic MAD timescale in GRBs and the maximum bulk Lorentz factor: tMAD∝Γ-6, somewhat steeper than (although within the error bars of) the fitted relationship found in the GRB data. Similarly, the MAD model also naturally accounts for the observed anti-correlation between MTS and gamma-ray luminosity L in the GRB data, and we estimate the accretion rates of the GRB disk (given these luminosities) in the context of this model. Both of these correlations (MTS - Γ and MTS - L) are also observed in the AGN data, and we discuss the implications of our results in the context of both GRB and blazar systems.

Expression and significance of Tie-1 and Tie-2 receptors, and angiopoietins-1, 2 and 4 in colorectal adenocarcinoma: Immunohistochemical analysis and correlation with clinicopathological factors

PubMed Central

Nakayama, Toshiyuki; Hatachi, Go; Wen, Chun-Yang; Yoshizaki, Ayumi; Yamazumi, Kazuyuki; Niino, Daisuke; Sekine, Ichiro

2005-01-01

AIM: There is strong evidence that tyrosine kinases are involved in the regulation of tumor progression, cellular growth and differentiation. Recently, many kinds of tyrosine kinase receptors have been reported, among them Tie-1 and Tie-2 receptors constitute a major class. Angiopoietin (Ang)-1 is known as a ligand of Tie-2 tyrosine kinase receptor. The objective of this study was to establish a comprehensive Tie-1 and Tie-2 and Ang-1, 2 and 4 expression profile in human colorectal adenocarcinomas. METHODS: We examined 96 cases of surgically resected human colorectal adenocarcinoma by immunohistochemistry and investigated the statistical correlation between the expressions of Ties and Angs and clinicopathological factors. RESULTS: Among the 96 cases of adenocarcinoma, 87 (90.6%), 92 (95.8%), 83 (86.5%), 89 (92.7%), and 76 cases (79.2%) showed positive staining in the cytoplasm of carcinoma cells for the Tie-1 and Tie-2 and Ang-1, 2 and 4 proteins, respectively. Histologically, the expressions of Ties and Angs were variable. The expressions of Ties and Angs were correlated with several clinicopathological factors, but did not correlate with the presence of lymph node metastasis. Ties and Angs were highly expressed in human colorectal adenocarcinoma cells. CONCLUSION: These findings suggest that the Tie-Ang receptor-ligand complex is one of the factors involved in the cellular differentiation and progression of human colorectal adenocarcinoma. PMID:15742397

Endoscopic carpal tunnel release: a prospective analysis of factors associated with unsatisfactory results.

PubMed

Straub, T A

1999-04-01

The first 100 consecutive cases of endoscopic carpal tunnel release (ECTR) performed by the author were studied prospectively during 6 to 24 months follow-up. Various preoperative and postoperative factors were subjected to statistical analysis to determine possible associations with unsatisfactory results. Overall, 92% of hands had a satisfactory result from ECTR, although not all were rendered symptom-free. There were no significant complications. Preoperative factors associated with an increased likelihood of unsatisfactory results included hands with preoperative weakness, widened two-point discrimination, myofascial pain syndrome or fibromyalgia, involvement in litigation, multiple compressive neuropathies, or the presence of abnormal psychological factors. A trend to less satisfactory results was present in Workers' Compensation cases and patients with normal motor latencies on nerve conduction studies. Multiple postoperative factors correlated with unsatisfactory results.

Joint Blind Source Separation by Multi-set Canonical Correlation Analysis

PubMed Central

Li, Yi-Ou; Adalı, Tülay; Wang, Wei; Calhoun, Vince D

2009-01-01

In this work, we introduce a simple and effective scheme to achieve joint blind source separation (BSS) of multiple datasets using multi-set canonical correlation analysis (M-CCA) [1]. We first propose a generative model of joint BSS based on the correlation of latent sources within and between datasets. We specify source separability conditions, and show that, when the conditions are satisfied, the group of corresponding sources from each dataset can be jointly extracted by M-CCA through maximization of correlation among the extracted sources. We compare source separation performance of the M-CCA scheme with other joint BSS methods and demonstrate the superior performance of the M-CCA scheme in achieving joint BSS for a large number of datasets, group of corresponding sources with heterogeneous correlation values, and complex-valued sources with circular and non-circular distributions. We apply M-CCA to analysis of functional magnetic resonance imaging (fMRI) data from multiple subjects and show its utility in estimating meaningful brain activations from a visuomotor task. PMID:20221319

Multiscale multifractal detrended cross-correlation analysis of financial time series

NASA Astrophysics Data System (ADS)

Shi, Wenbin; Shang, Pengjian; Wang, Jing; Lin, Aijing

2014-06-01

In this paper, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). The method allows us to extend the description of the cross-correlation properties between two time series. MM-DCCA may provide new ways of measuring the nonlinearity of two signals, and it helps to present much richer information than multifractal detrended cross-correlation analysis (MF-DCCA) by sweeping all the range of scale at which the multifractal structures of complex system are discussed. Moreover, to illustrate the advantages of this approach we make use of the MM-DCCA to analyze the cross-correlation properties between financial time series. We show that this new method can be adapted to investigate stock markets under investigation. It can provide a more faithful and more interpretable description of the dynamic mechanism between financial time series than traditional MF-DCCA. We also propose to reduce the scale ranges to analyze short time series, and some inherent properties which remain hidden when a wide range is used may exhibit perfectly in this way.

Image-defined Risk Factors Correlate with Surgical Radicality and Local Recurrence in Patients with Neuroblastoma.

PubMed

Pohl, A; Erichsen, M; Stehr, M; Hubertus, J; Bergmann, F; Kammer, B; von Schweinitz, D

2016-04-01

Neuroblastoma is the second most common solid pediatric tumor and the most common cancer to be detected in children younger than 12 months of age. To date, 2 different staging systems describe the extent of the disease: the International Neuroblastoma Staging System (INSS) and the International Neuroblastoma Risk Group Staging System (INRGSS). The INRGSS-system is characterized by the presence or absence of so called image-defined risk factors (IDRFs), which are described as surgical risk factors. We hypothesized that IDRFs correlate with surgical complications, surgical radicality, local recurrence and overall survival (OS). Between 2003 and 2010, 102 patients had neuroblastoma surgery performed in our department. We analyzed medical records for IDRF-status and above named data. 16 patients were IDRF-negative, whereas 86 patients showed one or more IDRF. Intra- or postoperative complications have been reported in 21 patients (21%). 19 of them showed one or more IDRF and 2 patients were IDRF-negative (p=n.s.). Patients who suffered from intra- or postoperative complications demonstrated a decreased OS (p=0.011). Statistical analysis revealed an inverse correlation between the extent of macroscopical removal and IDRF-status (p=0.001). Furthermore, the number of IDRFs were associated with a decreased likelihood of radical tumor resection (p<0.001). 19 patients had local recurrence; all of them were IDRF-positive (p=0.037). Pediatric surgeons should consider IDRFs as a useful tool for risk assessment and therefore planning for neuroblastoma surgery. © Georg Thieme Verlag KG Stuttgart · New York.

Nuclear factor-kappaB activation correlates with better prognosis and Akt activation in human gastric cancer.

PubMed

Lee, Byung Lan; Lee, Hye Seung; Jung, Jieun; Cho, Sung Jin; Chung, Hee-Yong; Kim, Woo Ho; Jin, Young-Woo; Kim, Chong Soon; Nam, Seon Young

2005-04-01

Because the biological significance of constitutive nuclear factor-kappaB (NF-kappaB) activation in human gastric cancer is unclear, we undertook this study to clarify the regulatory mechanism of NF-kappaB activation and its clinical significance. Immunohistochemistry for NF-kappaB/RelA was done on 290 human gastric carcinoma specimens placed on tissue array slides. The correlations between NF-kappaB activation and clinicopathologic features, prognosis, Akt activation, tumor suppressor gene expression, or Bcl-2 expression were analyzed. We also did luciferase reporter assay, Western blot analysis, and reverse transcription-PCR using the SNU-216 human gastric cancer cell line transduced with retroviral vectors containing constitutively active Akt or the NF-kappaB repressor mutant of IkappaBalpha. Nuclear expression of RelA was found in 18% of the gastric carcinomas and was higher in early-stage pathologic tumor-node-metastasis (P = 0.019). A negative correlation was observed between NF-kappaB activation and lymphatic invasion (P = 0.034) and a positive correlation between NF-kappaB activation and overall survival rate of gastric cancer patients (P = 0.0228). In addition, NF-kappaB activation was positively correlated with pAkt (P = 0.047), p16 (P = 0.004), adenomatous polyposis coli (P < 0.001), Smad4 (P = 0.002), and kangai 1 (P < 0.001) expression. An in vitro study showed that NF-kappaB activity in gastric cancer cells is controlled by and controls Akt. NF-kappaB activation was frequently observed in early-stage gastric carcinoma and was significantly correlated with better prognosis and Akt activation. These findings suggest that NF-kappaB activation is a valuable prognostic variable in gastric carcinoma.

Correlation between increasing tissue ischemia and circulating levels of angiogenic growth factors in peripheral artery disease.

PubMed

Jalkanen, Juho; Hautero, Olli; Maksimow, Mikael; Jalkanen, Sirpa; Hakovirta, Harri

2018-04-21

The aim of the present study was to assess the circulating levels of vascular endothelial growth factor (VEGF) and other suggested therapeutic growth factors with the degree of ischemia in patients with different clinical manifestations of peripheral arterial disease (PAD) according to the Rutherford grades. The study cohort consists of 226 consecutive patients admitted to a Department of Vascular Surgery for elective invasive procedures. PAD patients were grouped according to the Rutherford grades after a clinical assessment. Ankle-brachial pressure indices (ABI) and absolute toe pressure (TP) values were measured. Serum levels of circulating VEGF, hepatocyte growth factor (HGF), basic fibroblast growth factor (bFGF), and platelet derived growth factor (PDGF) were measured from serum and analysed against Rutherford grades and peripheral hemodynamic measurements. The levels of VEGF (P = 0.009) and HGF (P < 0.001) increased significantly as the ischaemic burden became more severe according to the Rutherford grades. PDGF behaved in opposite manner and declined along increasing Rutherford grades (P = 0.004). A significant, inverse correlations between Rutherford grades was detected as follows; VEGF (Pearson's correlation = 0.183, P = 0.004), HGF (Pearson's correlation = 0.253, P < 0.001), bFGF (Pearson's correlation = 0.169, P = 0.008) and PDGF (Pearson's correlation = 0.296, P < 0.001). In addition, VEGF had a clear direct negative correlation with ABI (Pearson's correlation -0.19, P = 0.009) and TP (Pearson's correlation -0.20, P = 0.005) measurements. Our present observations show that the circulating levels of VEGF and other suggested therapeutic growth factors are significantly increased along with increasing ischemia. These findings present a new perspective to anticipated positive effects of gene therapies utilizing VEGF, HGF, and bFGF, because the levels of these growth factors are endogenously high in end

Factor analysis shows association between family activity environment and children's health behaviour.

PubMed

Hendrie, Gilly A; Coveney, John; Cox, David N

2011-12-01

To characterise the family activity environment in a questionnaire format, assess the questionnaire's reliability and describe its predictive ability by examining the relationships between the family activity environment and children's health behaviours - physical activity, screen time and fruit and vegetable intake. This paper describes the creation of a tool, based on previously validated scales, adapted from the food domain. Data are from 106 children and their parents (Adelaide, South Australia). Factor analysis was used to characterise factors within the family activity environment. Pearson-Product Moment correlations between the family environment and child outcomes, controlling for demographic variation, were examined. Three factors described the family activity environment - parental activity involvement, opportunity for role modelling and parental support for physical activity - and explained 37.6% of the variance. Controlling for demographic factors, the scale was significantly correlated with children's health behaviour - physical activity (r=0.27), screen time (r=-0.24) and fruit and vegetable intake (r=0.34). The family activity environment questionnaire shows high internal consistency and moderate predictive ability. This study has built on previous research by taking a more comprehensive approach to measuring the family activity environment. This research suggests the family activity environment should be considered in family-based health promotion interventions. © 2011 The Authors. ANZJPH © 2011 Public Health Association of Australia.

Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and Bayesian Estimations

ERIC Educational Resources Information Center

Can, Seda; van de Schoot, Rens; Hox, Joop

2015-01-01

Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation…

Physical and Cognitive-Affective Factors Associated with Fatigue in Individuals with Fibromyalgia: A Multiple Regression Analysis

ERIC Educational Resources Information Center

Muller, Veronica; Brooks, Jessica; Tu, Wei-Mo; Moser, Erin; Lo, Chu-Ling; Chan, Fong

2015-01-01

Purpose: The main objective of this study was to determine the extent to which physical and cognitive-affective factors are associated with fibromyalgia (FM) fatigue. Method: A quantitative descriptive design using correlation techniques and multiple regression analysis. The participants consisted of 302 members of the National Fibromyalgia &…

Residential greenness and birth outcomes: evaluating the influence of spatially correlated built-environment factors.

PubMed

Hystad, Perry; Davies, Hugh W; Frank, Lawrence; Van Loon, Josh; Gehring, Ulrike; Tamburic, Lillian; Brauer, Michael

2014-10-01

Half the world's population lives in urban areas. It is therefore important to identify characteristics of the built environment that are beneficial to human health. Urban greenness has been associated with improvements in a diverse range of health conditions, including birth outcomes; however, few studies have attempted to distinguish potential effects of greenness from those of other spatially correlated exposures related to the built environment. We aimed to investigate associations between residential greenness and birth outcomes and evaluate the influence of spatially correlated built environment factors on these associations. We examined associations between residential greenness [measured using satellite-derived Normalized Difference Vegetation Index (NDVI) within 100 m of study participants' homes] and birth outcomes in a cohort of 64,705 singleton births (from 1999-2002) in Vancouver, British Columbia, Canada. We also evaluated associations after adjusting for spatially correlated built environmental factors that may influence birth outcomes, including exposure to air pollution and noise, neighborhood walkability, and distance to the nearest park. An interquartile increase in greenness (0.1 in residential NDVI) was associated with higher term birth weight (20.6 g; 95% CI: 16.5, 24.7) and decreases in the likelihood of small for gestational age, very preterm (< 30 weeks), and moderately preterm (30-36 weeks) birth. Associations were robust to adjustment for air pollution and noise exposures, neighborhood walkability, and park proximity. Increased residential greenness was associated with beneficial birth outcomes in this population-based cohort. These associations did not change after adjusting for other spatially correlated built environment factors, suggesting that alternative pathways (e.g., psychosocial and psychological mechanisms) may underlie associations between residential greenness and birth outcomes.

Correlation between 18F-FDG Positron-Emission Tomography 18F-FDG Uptake Levels at Diagnosis and Histopathologic and Immunohistochemical Factors in Patients with Breast Cancer

PubMed Central

Uğurluer, Gamze; Yavuz, Sinan; Çalıkuşu, Züleyha; Seyrek, Ertuğrul; Kibar, Mustafa; Serin, Meltem; Ersöz, Canan; Demircan, Orhan

2016-01-01

Objective In this study, we aimed to determine the correlation between pretreatment-staging 18F-FDG total body positron-emission tomography/computed tomography (PET/CT) maximum standardized uptake value (SUVmax) levels and histopathologic and immunohistochemical predictive and prognostic factors in patients with breast cancer. Materials and Methods One hundred thirty-nine women with breast cancer who were treated between 2009 and 2015 at our hospital and who had pretreatment-staging PET/CT were included in the study. SUVmax levels and histopathologic and immunohistochemical results were compared. Results The median age was 48 years (range, 29–79 years). The mean tumor diameter was 33.4 mm (range, 7–120 mm). The histology was invasive ductal carcinoma in 80.6% of the patients. In the univariate analysis, SUVmax levels were significantly higher in patients with invasive ductal carcinoma; in patients with a maximum tumor diameter more than 2 cm; patients who were estrogen, progesterone, and combined hormone receptor-negative, triple-negative patients, and in tumors with higher grades (p<0.05). In HER2-positive patients, SUVmax levels were higher even if it was not statistically significant. There was no correlation between lymph node metastases and pathologic stage. In multivariate analysis, tumor diameter was an independent factor. Conclusion SUVmax levels are correlated with known histopathologic and immunohistochemical prognostic factors. PET/CT could be useful in preoperative evaluation of patients with breast cancer to predict biologic characteristics of tumors and prognosis. PMID:28331746

Functional network connectivity analysis based on partial correlation in Alzheimer's disease

NASA Astrophysics Data System (ADS)

Zhang, Nan; Guan, Xiaoting; Zhang, Yumei; Li, Jingjing; Chen, Hongyan; Chen, Kewei; Fleisher, Adam; Yao, Li; Wu, Xia

2009-02-01

Functional network connectivity (FNC) measures the temporal dependency among the time courses of functional networks. However, the marginal correlation between two networks used in the classic FNC analysis approach doesn't separate the FNC from the direct/indirect effects of other networks. In this study, we proposed an alternative approach based on partial correlation to evaluate the FNC, since partial correlation based FNC can reveal the direct interaction between a pair of networks, removing dependencies or influences from others. Previous studies have demonstrated less task-specific activation and less rest-state activity in Alzheimer's disease (AD). We applied present approach to contrast FNC differences of resting state network (RSN) between AD and normal controls (NC). The fMRI data under resting condition were collected from 15 AD and 16 NC. FNC was calculated for each pair of six RSNs identified using Group ICA, thus resulting in 15 (2 out of 6) pairs for each subject. Partial correlation based FNC analysis indicated 6 pairs significant differences between groups, while marginal correlation only revealed 2 pairs (involved in the partial correlation results). Additionally, patients showed lower correlation than controls among most of the FNC differences. Our results provide new evidences for the disconnection hypothesis in AD.

Comparison of Penalty Functions for Sparse Canonical Correlation Analysis

PubMed Central

Chalise, Prabhakar; Fridley, Brooke L.

2011-01-01

Canonical correlation analysis (CCA) is a widely used multivariate method for assessing the association between two sets of variables. However, when the number of variables far exceeds the number of subjects, such in the case of large-scale genomic studies, the traditional CCA method is not appropriate. In addition, when the variables are highly correlated the sample covariance matrices become unstable or undefined. To overcome these two issues, sparse canonical correlation analysis (SCCA) for multiple data sets has been proposed using a Lasso type of penalty. However, these methods do not have direct control over sparsity of solution. An additional step that uses Bayesian Information Criterion (BIC) has also been suggested to further filter out unimportant features. In this paper, a comparison of four penalty functions (Lasso, Elastic-net, SCAD and Hard-threshold) for SCCA with and without the BIC filtering step have been carried out using both real and simulated genotypic and mRNA expression data. This study indicates that the SCAD penalty with BIC filter would be a preferable penalty function for application of SCCA to genomic data. PMID:21984855

Data for factor analysis of hydro-geochemical characteristics of groundwater resources in Iranshahr.

PubMed

Biglari, Hamed; Saeidi, Mehdi; Karimyan, Kamaleddin; Narooie, Mohammad Reza; Sharafi, Hooshmand

2018-08-01

Detection of Hydrogeological and Hydro-geochemical changes affecting the quality of aquifer water is very important. The aim of this study was to determine the factor analysis of the hydro-geochemical characteristics of Iranshahr underground water resources during the warm and cool seasons. In this study, 248 samples (two-time repetitions) of ground water resources were provided at first by cluster-random sampling method during 2017 in the villages of Iranshahr city. After transferring the samples to the laboratory, concentrations of 13 important chemical parameters in those samples were determined according to o water and wastewater standard methods. The results of this study indicated that 45.45% and 55.55% of the correlation between parameters has had a significant decrease and increase, respectively with the transition from warm seasons to cold seasons. According to the factor analysis method, three factors of land hydro-geochemical processes, supplying resources by surface water and sewage as well as human activities have been identified as influential on the chemical composition of these resources.The highest growth rate of 0.37 was observed between phosphate and nitrate ions while the lowest trend of - 0.33 was seen between fluoride ion and calcium as well as chloride ions. Also, a significant increase in the correlation between magnesium ion and nitrate ion from warm seasons to cold seasons indicates the high seasonal impact of the relation between these two parameters.

Risk factors in laparoscopic cholecystectomy: a multivariate analysis.

PubMed

Kanakala, Venkatesh; Borowski, David W; Pellen, Michael G C; Dronamraju, Shridhar S; Woodcock, Sean A A; Seymour, Keith; Attwood, Stephen E A; Horgan, Liam F

2011-01-01

Laparoscopic cholecystectomy (LC) is the operation of choice in the treatment of symptomatic gallstone disease. The aim of this study is to identify risk factors for LC, outcomes include operating time, length of stay, conversion rate, morbidity and mortality. All patients undergoing LC between 1998 and 2007 in a single district general hospital. Risk factors were examined using uni- and multivariate analysis. 2117 patients underwent LC, with 1706 (80.6%) patients operated on electively. Male patients were older, had more co-morbidity and more emergency surgery than females. The median post-operative hospital stay was one day, and was positively correlated with the complexity of surgery. Conversion rates were higher in male patients (OR 1.47, p = 0.047) than in females, and increased with co-morbidity. Emergency surgery (OR 1.75, p = 0.005), male gender (OR 1.68, p = 0.005), increasing co-morbidity and complexity of surgery were all positively associated with the incidence of complications (153/2117 [7.2%]), whereas only male gender was significantly associated with mortality (OR 5.71, p = 0.025). Adverse outcome from LC is particularly associated with male gender, but also the patient's co-morbidity, complexity and urgency of surgery. Risk-adjusted outcome analysis is desirable to ensure an informed consent process. Copyright © 2011 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

Evaluation of breast cancer using intravoxel incoherent motion (IVIM) histogram analysis: comparison with malignant status, histological subtype, and molecular prognostic factors.

PubMed

Cho, Gene Young; Moy, Linda; Kim, Sungheon G; Baete, Steven H; Moccaldi, Melanie; Babb, James S; Sodickson, Daniel K; Sigmund, Eric E

2016-08-01

To examine heterogeneous breast cancer through intravoxel incoherent motion (IVIM) histogram analysis. This HIPAA-compliant, IRB-approved retrospective study included 62 patients (age 48.44 ± 11.14 years, 50 malignant lesions and 12 benign) who underwent contrast-enhanced 3 T breast MRI and diffusion-weighted imaging. Apparent diffusion coefficient (ADC) and IVIM biomarkers of tissue diffusivity (Dt), perfusion fraction (fp), and pseudo-diffusivity (Dp) were calculated using voxel-based analysis for the whole lesion volume. Histogram analysis was performed to quantify tumour heterogeneity. Comparisons were made using Mann-Whitney tests between benign/malignant status, histological subtype, and molecular prognostic factor status while Spearman's rank correlation was used to characterize the association between imaging biomarkers and prognostic factor expression. The average values of the ADC and IVIM biomarkers, Dt and fp, showed significant differences between benign and malignant lesions. Additional significant differences were found in the histogram parameters among tumour subtypes and molecular prognostic factor status. IVIM histogram metrics, particularly fp and Dp, showed significant correlation with hormonal factor expression. Advanced diffusion imaging biomarkers show relationships with molecular prognostic factors and breast cancer malignancy. This analysis reveals novel diagnostic metrics that may explain some of the observed variability in treatment response among breast cancer patients. • Novel IVIM biomarkers characterize heterogeneous breast cancer. • Histogram analysis enables quantification of tumour heterogeneity. • IVIM biomarkers show relationships with breast cancer malignancy and molecular prognostic factors.

Process Correlation Analysis Model for Process Improvement Identification

PubMed Central

Park, Sooyong

2014-01-01

Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data. PMID:24977170

Process correlation analysis model for process improvement identification.

PubMed

Choi, Su-jin; Kim, Dae-Kyoo; Park, Sooyong

2014-01-01

Software process improvement aims at improving the development process of software systems. It is initiated by process assessment identifying strengths and weaknesses and based on the findings, improvement plans are developed. In general, a process reference model (e.g., CMMI) is used throughout the process of software process improvement as the base. CMMI defines a set of process areas involved in software development and what to be carried out in process areas in terms of goals and practices. Process areas and their elements (goals and practices) are often correlated due to the iterative nature of software development process. However, in the current practice, correlations of process elements are often overlooked in the development of an improvement plan, which diminishes the efficiency of the plan. This is mainly attributed to significant efforts and the lack of required expertise. In this paper, we present a process correlation analysis model that helps identify correlations of process elements from the results of process assessment. This model is defined based on CMMI and empirical data of improvement practices. We evaluate the model using industrial data.

On the mode I fracture analysis of cracked Brazilian disc using a digital image correlation method

NASA Astrophysics Data System (ADS)

Abshirini, Mohammad; Soltani, Nasser; Marashizadeh, Parisa

2016-03-01

Mode I of fracture of centrally cracked Brazilian disc was investigated experimentally using a digital image correlation (DIC) method. Experiments were performed on PMMA polymers subjected to diametric-compression load. The displacement fields were determined by a correlation between the reference and the deformed images captured before and during loading. The stress intensity factors were calculated by displacement fields using William's equation and the least square algorithm. The parameters involved in the accuracy of SIF calculation such as number of terms in William's equation and the region of analysis around the crack were discussed. The DIC results were compared with the numerical results available in literature and a very good agreement between them was observed. By extending the tests up to the critical state, mode I fracture toughness was determined by analyzing the image of specimen captured at the moment before fracture. The results showed that the digital image correlation was a reliable technique for the calculation of the fracture toughness of brittle materials.

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.

Expression of pigment epithelium-derived factor and tumor necrosis factor-α is correlated in bladder tumor and is related to tumor angiogenesis.

PubMed

Feng, Chen-Chen; Wang, Pao-Hsun; Ding, Qiang; Guan, Ming; Zhang, Yuan-Fang; Jiang, Hao-Wen; Wen, Hui; Wu, Zhong

2013-02-01

Angiogenesis is a pivotal process on which solid tumor growth is substantially dependent. Pigment epithelium-derived factor (PEDF) is the most potent natural anti-angiogenic factor, which has seldom been studied in bladder tumor, and whose functioning pathway remains unclear. We have thus investigated PEDF expression in relation to tumor necrosis factor-α (TNF-α) and microvessel density (MVD) with immunohistochemistry. Antibodies of PEDF and TNF-α were examined by Western blotting before immunohistochemistry. Sixty-four urothelial tumor sections and 23 normal controls were stained and expression of PEDF, TNF-α, and MVD were studied. Decreased PEDF expression and increased TNF-α expression was noticed in tumorous tissue compared with healthy urothelium. Lower PEDF expression was related to higher tumor grade but stage. Increased TNF-α expression was noticed in recurrent, larger tumors as well as in tumors with progression in grade and stage. Expression of PEDF and TNF-α was correlated in bladder tumor. PEDF or TNF-α was correlated with MVD negatively or positively, respectively, in cancerous tissue and tumorous grouping without correlation in papillary urothelial neoplasm of low malignant potential. Expressional change of PEDF and TNF-α is in relation to angiogenesis of bladder tumor, especially in bladder cancer development. Copyright © 2013 Elsevier Inc. All rights reserved.

[Correlation Among Soil Organic Carbon, Soil Inorganic Carbon and the Environmental Factors in a Typical Oasis in the Southern Edge of the Tarim Basin].

PubMed

Gong, Lu; Zhu, Mei-ling; Liu, Zeng-yuan; Zhang, Xue-ni; Xie, Li-na

2016-04-15

We analyzed the differentiation among the environmental factors and soil organic/inorganic carbon contents of irrigated desert soil, brown desert soil, saline soil and aeolian sandy soil by classical statistics methods, and studied the correlation between soil carbon contents and the environmental factor by redundancy analysis (RDA) in a typical oasis of Yutian in the southern edge of the Tarim Basin. The results showed that the average contents of soil organic carbon and soil inorganic carbon were 2.51 g · kg⁻¹ and 25.63 g · kg⁻¹ respectively. The soil organic carbon content of the irrigated desert soil was significantly higher than those of brown desert soil, saline soil and aeolian sandy soil, while the inorganic carbon content of aeolian sandy soil was significantly higher than those of other soil types. The soil moisture and nutrient content were the highest in the irrigated desert soil and the lowest in the aeolian sandy sail. All soil types had high degree of salinization except the irrigated desert soil. The RDA results showed that the impacts of environmental factors on soil carbon contents ranked in order of importance were total nitrogen > available phosphorus > soil moisture > ground water depth > available potassium > pH > total salt. The soil carbon contents correlated extremely significantly with total nitrogen, available phosphorus, soil moisture and ground water depth (P < 0.01), and it correlated significantly with available potassium and pH (P < 0.05). There was no significant correlation between soil carbon contents and other environmental factors (P > 0.05).

Correlation and path analysis of biomass sorghum production.

PubMed

Vendruscolo, T P S; Barelli, M A A; Castrillon, M A S; da Silva, R S; de Oliveira, F T; Corrêa, C L; Zago, B W; Tardin, F D

2016-12-23

Sorghum biomass is an interesting raw material for bioenergy production due to its versatility, potential of being a renewable energy source, and low-cost of production. The objective of this study was to evaluate the genetic variability of biomass sorghum genotypes and to estimate genotypic, phenotypic, and environmental correlations, and direct and indirect effects of seven agronomic traits through path analysis. Thirty-four biomass sorghum genotypes and two forage sorghum genotypes were cultivated in a randomized block design with three replicates. The following morpho-agronomic traits were evaluated: flowering date, stem diameter, number of stems, plant height, number of leaves, green mass production, and dry matter production. There were significant differences at the 1% level for all traits. The highest genotypic correlation was found between the traits green mass production and dry matter production. The path analysis demonstrated that green mass production and number of leaves can assist in the selection of dry matter production.

Use of exploratory factor analysis to ascertain the correlation between the activities of rheumatoid arthritis and infection by human parvovirus B19.

PubMed

Kakurina, Natalja; Kadisa, Anda; Lejnieks, Aivars; Mikazane, Helena; Kozireva, Svetlana; Murovska, Modra

2015-01-01

We evaluated a possible correlation between the clinical activities of rheumatoid arthritis (RA) and human parvovirus B19 (B19) infection using exploratory factor analysis (EFA). RA patients were organized into two groups: 100 patients in the main group and 97 in the RA(DAS28) group. Four subgroups were defined from the main group according to the presence or absence of certain infection-specific markers: group I comprised 43 patients who had IgG antibodies against B19; group II, 25 patients with active B19 infection (B19-specific IgM antibodies and/or plasma viremia); group III, 19 patients with latent/persistent B19 infection (virus-specific sequences in peripheral blood leukocytes' DNA with or without B19-specific IgG antibodies), and group IV, 13 patients without infection markers. The RA(DAS28) group was divided into four subgroups similarly to the main group: group I, 35; group II, 31; group III, 19; and group IV, 12 patients. Disease-specific clinical values in both groups were analyzed employing EFA, and the RA(DAS28) group was additionally assessed using Disease Activity Score (DAS)28. RA activity was higher in patients who had markers of B19 infection. The highest activity of RA in both study groups was in patients with latent/persistent infection. In the RA(DAS28) group, according to DAS28, the highest activity of RA was in patients with active B19 infection. Using EFA and DAS28, a correlation between the clinical activity of RA and B19 infection was confirmed. These data suggest that EFA is applicable for medico-biological studies. Copyright © 2015 Lithuanian University of Health Sciences. Production and hosting by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Exploratory factor analysis of self-reported symptoms in a large, population-based military cohort

PubMed Central

2010-01-01

Background US military engagements have consistently raised concern over the array of health outcomes experienced by service members postdeployment. Exploratory factor analysis has been used in studies of 1991 Gulf War-related illnesses, and may increase understanding of symptoms and health outcomes associated with current military conflicts in Iraq and Afghanistan. The objective of this study was to use exploratory factor analysis to describe the correlations among numerous physical and psychological symptoms in terms of a smaller number of unobserved variables or factors. Methods The Millennium Cohort Study collects extensive self-reported health data from a large, population-based military cohort, providing a unique opportunity to investigate the interrelationships of numerous physical and psychological symptoms among US military personnel. This study used data from the Millennium Cohort Study, a large, population-based military cohort. Exploratory factor analysis was used to examine the covariance structure of symptoms reported by approximately 50,000 cohort members during 2004-2006. Analyses incorporated 89 symptoms, including responses to several validated instruments embedded in the questionnaire. Techniques accommodated the categorical and sometimes incomplete nature of the survey data. Results A 14-factor model accounted for 60 percent of the total variance in symptoms data and included factors related to several physical, psychological, and behavioral constructs. A notable finding was that many factors appeared to load in accordance with symptom co-location within the survey instrument, highlighting the difficulty in disassociating the effects of question content, location, and response format on factor structure. Conclusions This study demonstrates the potential strengths and weaknesses of exploratory factor analysis to heighten understanding of the complex associations among symptoms. Further research is needed to investigate the relationship between

Analysis of factors influencing safety management for metro construction in China.

PubMed

Yu, Q Z; Ding, L Y; Zhou, C; Luo, H B

2014-07-01

With the rapid development of urbanization in China, the number and size of metro construction projects are increasing quickly. At the same time, and increasing number of accidents in metro construction make it a disturbing focus of social attention. In order to improve safety management in metro construction, an investigation of the participants' perspectives on safety factors in China metro construction has been conducted to identify the key safety factors, and their ranking consistency among the main participants, including clients, consultants, designers, contractors and supervisors. The result of factor analysis indicates that there are five key factors which influence the safety of metro construction including safety attitude, construction site safety, government supervision, market restrictions and task unpredictability. In addition, ANOVA and Spearman rank correlation coefficients were performed to test the consistency of the means rating and the ranking of safety factors. The results indicated that the main participants have significant disagreement about the importance of safety factors on more than half of the items. Suggestions and recommendations on practical countermeasures to improve metro construction safety management in China are proposed. Copyright © 2013 Elsevier Ltd. All rights reserved.

Factor Analysis of Intern Effectiveness

ERIC Educational Resources Information Center

Womack, Sid T.; Hannah, Shellie Louise; Bell, Columbus David

2012-01-01

Four factors in teaching intern effectiveness, as measured by a Praxis III-similar instrument, were found among observational data of teaching interns during the 2010 spring semester. Those factors were lesson planning, teacher/student reflection, fairness & safe environment, and professionalism/efficacy. This factor analysis was as much of a…

Beyond Correlates: A Review of Risk and Protective Factors for Adolescent Dating Violence Perpetration

PubMed Central

Vagi, Kevin J.; Rothman, Emily; Latzman, Natasha E.; Tharp, Andra Teten; Hall, Diane M.; Breiding, Matthew J.

2013-01-01

Dating violence is a serious public health problem. In recent years, the U.S. Centers for Disease Control and Prevention (CDC) and other entities have made funding available to community based agencies for dating violence prevention. Practitioners who are tasked with developing dating violence prevention strategies should pay particular attention to risk and protective factors for dating violence perpetration that have been established in longitudinal studies. This has been challenging to date because the scientific literature on the etiology of dating violence is somewhat limited, and because there have been no comprehensive reviews of the literature that clearly distinguish correlates of dating violence perpetration from risk or protective factors that have been established through longitudinal research. This is problematic because prevention programs may then target factors that are merely correlated with dating violence perpetration, and have no causal influence, which could potentially limit the effectiveness of the programs. In this article, we review the literature on risk and protective factors for adolescent dating violence perpetration and highlight those factors for which temporal precedence has been established by one or more studies. This review is intended as a guide for researchers and practitioners as they formulate prevention programs. We reviewed articles published between 2000–2010 that reported on adolescent dating violence perpetration using samples from the United States or Canada. In total, 53 risk factors and six protective factors were identified from 20 studies. Next steps for etiological research in adolescent dating violence are discussed, as well as future directions for prevention program developers. PMID:23385616

Kernel-aligned multi-view canonical correlation analysis for image recognition

NASA Astrophysics Data System (ADS)

Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

2016-09-01

Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

Using beta coefficients to impute missing correlations in meta-analysis research: Reasons for caution.

PubMed

Roth, Philip L; Le, Huy; Oh, In-Sue; Van Iddekinge, Chad H; Bobko, Philip

2018-06-01

Meta-analysis has become a well-accepted method for synthesizing empirical research about a given phenomenon. Many meta-analyses focus on synthesizing correlations across primary studies, but some primary studies do not report correlations. Peterson and Brown (2005) suggested that researchers could use standardized regression weights (i.e., beta coefficients) to impute missing correlations. Indeed, their beta estimation procedures (BEPs) have been used in meta-analyses in a wide variety of fields. In this study, the authors evaluated the accuracy of BEPs in meta-analysis. We first examined how use of BEPs might affect results from a published meta-analysis. We then developed a series of Monte Carlo simulations that systematically compared the use of existing correlations (that were not missing) to data sets that incorporated BEPs (that impute missing correlations from corresponding beta coefficients). These simulations estimated ρ̄ (mean population correlation) and SDρ (true standard deviation) across a variety of meta-analytic conditions. Results from both the existing meta-analysis and the Monte Carlo simulations revealed that BEPs were associated with potentially large biases when estimating ρ̄ and even larger biases when estimating SDρ. Using only existing correlations often substantially outperformed use of BEPs and virtually never performed worse than BEPs. Overall, the authors urge a return to the standard practice of using only existing correlations in meta-analysis. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Factors controlling degree of correlation between ISEE 1 and ISEE 3 interplanetary magnetic field measurements

NASA Technical Reports Server (NTRS)

Crooker, N. U.; Siscoe, G. L.; Russell, C. T.; Smith, E. J.

1982-01-01

Correlation variability between ISEE 1 and 3 IMF measurements is investigated, and factors governing the variability are discussed. About 200 two-hour periods when correlation was good, and 200 when correlation was poor, are examined, and both IMF variance and spacecraft separation distance in the plane perpendicular to the earth-sun line exert substantial control. The scale size of magnetic features is larger when variance is high, and abrupt changes in the correlation coefficient from poor to good or good to poor in adjacent two-hour intervals appear to be governed by the sense of change of IMF variance and vice versa. During periods of low variance, good correlations are most likely to occur when the distance between ISEE 1 and 3 perpendicular to the IMF is less than 20 earth radii.

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.

Learning Bayesian Networks from Correlated Data

NASA Astrophysics Data System (ADS)

Bae, Harold; Monti, Stefano; Montano, Monty; Steinberg, Martin H.; Perls, Thomas T.; Sebastiani, Paola

2016-05-01

Bayesian networks are probabilistic models that represent complex distributions in a modular way and have become very popular in many fields. There are many methods to build Bayesian networks from a random sample of independent and identically distributed observations. However, many observational studies are designed using some form of clustered sampling that introduces correlations between observations within the same cluster and ignoring this correlation typically inflates the rate of false positive associations. We describe a novel parameterization of Bayesian networks that uses random effects to model the correlation within sample units and can be used for structure and parameter learning from correlated data without inflating the Type I error rate. We compare different learning metrics using simulations and illustrate the method in two real examples: an analysis of genetic and non-genetic factors associated with human longevity from a family-based study, and an example of risk factors for complications of sickle cell anemia from a longitudinal study with repeated measures.

Strong anticipation and long-range cross-correlation: Application of detrended cross-correlation analysis to human behavioral data

NASA Astrophysics Data System (ADS)

Delignières, Didier; Marmelat, Vivien

2014-01-01

In this paper, we analyze empirical data, accounting for coordination processes between complex systems (bimanual coordination, interpersonal coordination, and synchronization with a fractal metronome), by using a recently proposed method: detrended cross-correlation analysis (DCCA). This work is motivated by the strong anticipation hypothesis, which supposes that coordination between complex systems is not achieved on the basis of local adaptations (i.e., correction, predictions), but results from a more global matching of complexity properties. Indeed, recent experiments have evidenced a very close correlation between the scaling properties of the series produced by two coordinated systems, despite a quite weak local synchronization. We hypothesized that strong anticipation should result in the presence of long-range cross-correlations between the series produced by the two systems. Results allow a detailed analysis of the effects of coordination on the fluctuations of the series produced by the two systems. In the long term, series tend to present similar scaling properties, with clear evidence of long-range cross-correlation. Short-term results strongly depend on the nature of the task. Simulation studies allow disentangling the respective effects of noise and short-term coupling processes on DCCA results, and suggest that the matching of long-term fluctuations could be the result of short-term coupling processes.

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

Robust Bayesian Factor Analysis

ERIC Educational Resources Information Center

Hayashi, Kentaro; Yuan, Ke-Hai

2003-01-01

Bayesian factor analysis (BFA) assumes the normal distribution of the current sample conditional on the parameters. Practical data in social and behavioral sciences typically have significant skewness and kurtosis. If the normality assumption is not attainable, the posterior analysis will be inaccurate, although the BFA depends less on the current…

Application of factor analysis of infrared spectra for quantitative determination of beta-tricalcium phosphate in calcium hydroxylapatite.

PubMed

Arsenyev, P A; Trezvov, V V; Saratovskaya, N V

1997-01-01

This work represents a method, which allows to determine phase composition of calcium hydroxylapatite basing on its infrared spectrum. The method uses factor analysis of the spectral data of calibration set of samples to determine minimal number of factors required to reproduce the spectra within experimental error. Multiple linear regression is applied to establish correlation between factor scores of calibration standards and their properties. The regression equations can be used to predict the property value of unknown sample. The regression model was built for determination of beta-tricalcium phosphate content in hydroxylapatite. Statistical estimation of quality of the model was carried out. Application of the factor analysis on spectral data allows to increase accuracy of beta-tricalcium phosphate determination and expand the range of determination towards its less concentration. Reproducibility of results is retained.

Separable projection integrals for higher-order correlators of the cosmic microwave sky: Acceleration by factors exceeding 100

NASA Astrophysics Data System (ADS)

Briggs, J. P.; Pennycook, S. J.; Fergusson, J. R.; Jäykkä, J.; Shellard, E. P. S.

2016-04-01

We present a case study describing efforts to optimise and modernise "Modal", the simulation and analysis pipeline used by the Planck satellite experiment for constraining general non-Gaussian models of the early universe via the bispectrum (or three-point correlator) of the cosmic microwave background radiation. We focus on one particular element of the code: the projection of bispectra from the end of inflation to the spherical shell at decoupling, which defines the CMB we observe today. This code involves a three-dimensional inner product between two functions, one of which requires an integral, on a non-rectangular domain containing a sparse grid. We show that by employing separable methods this calculation can be reduced to a one-dimensional summation plus two integrations, reducing the overall dimensionality from four to three. The introduction of separable functions also solves the issue of the non-rectangular sparse grid. This separable method can become unstable in certain scenarios and so the slower non-separable integral must be calculated instead. We present a discussion of the optimisation of both approaches. We demonstrate significant speed-ups of ≈100×, arising from a combination of algorithmic improvements and architecture-aware optimisations targeted at improving thread and vectorisation behaviour. The resulting MPI/OpenMP hybrid code is capable of executing on clusters containing processors and/or coprocessors, with strong-scaling efficiency of 98.6% on up to 16 nodes. We find that a single coprocessor outperforms two processor sockets by a factor of 1.3× and that running the same code across a combination of both microarchitectures improves performance-per-node by a factor of 3.38×. By making bispectrum calculations competitive with those for the power spectrum (or two-point correlator) we are now able to consider joint analysis for cosmological science exploitation of new data.

Multifactorial analysis of factors affecting recurrence of stroke in Japan.

PubMed

Omori, Toyonori; Kawagoe, Masahiro; Moriyama, Michiko; Yasuda, Takeshi; Ito, Yasuhiro; Hyakuta, Takeshi; Nagatsuka, Kazuyuki; Matsumoto, Masayasu

2015-03-01

Data on factors affecting stroke recurrence are relatively limited. The authors examined potential factors affecting stroke recurrence, retrospectively. The study participants were 1087 patients who were admitted to stroke centers suffering from first-ever ischemic stroke and returned questionnaires with usable information after discharge. The authors analyzed the association between clinical parameters of the patients and their prognosis. Recurrence rate of during an average of 2 years after discharge was 21.3%, and there were differences among stroke subtypes. It was found that the disability level of the patients after discharge correlated well with the level at discharge (r s = 0.66). Multivariate logistic regression analysis of the data shows that modified Rankin Scale score, National Institute of Health Stroke Scale score, gender, age, and family history had statistically significant impacts on stroke recurrence, and the impact was different depending on subtypes. These findings suggest that aggressive and persistent health education for poststroke patients and management of risk factors are essential to reduce stroke recurrence. © 2012 APJPH.

Correlative factors for the location of tracheobronchial foreign bodies in infants and children.

PubMed

Xu, Ying; Feng, Rui-Ling; Jiang, Lan; Ren, Hong-Bo; Li, Qi

2018-02-01

This study aims to analyze factors related to the location of tracheobronchial foreign bodies in infants and children, and provide help in the assessment of the disease, surgical risk and prognosis. The clinical data of 1,060 pediatric patients with tracheobronchial foreign bodies diagnosed from January 2015 to December 2015 were retrospectively studied, the association of the location of the foreign bodies with age, gender, granulation formation, chest computed tomography and 3D reconstruction results, preoperative complications, operation time, and hospital stay was analyzed. The location of foreign bodies was not correlated with age, gender, operation time and length of hospital stay, but was correlated to granulation formation, chest computed tomography and 3D reconstruction results, and preoperative complications. The location of foreign bodies was correlated to granulation formation, the location of foreign bodies displayed by chest computed tomography, and preoperative complications.

Suicide during Perinatal Period: Epidemiology, Risk Factors, and Clinical Correlates

PubMed Central

Orsolini, Laura; Valchera, Alessandro; Vecchiotti, Roberta; Tomasetti, Carmine; Iasevoli, Felice; Fornaro, Michele; De Berardis, Domenico; Perna, Giampaolo; Pompili, Maurizio; Bellantuono, Cesario

2016-01-01

Perinatal period may pose a great challenge for the clinical management and treatment of psychiatric disorders in women. In fact, several mental illnesses can arise during pregnancy and/or following childbirth. Suicide has been considered a relatively rare event during the perinatal period. However, in some mental disorders (i.e., postpartum depression, bipolar disorder, postpartum psychosis, etc.) have been reported a higher risk of suicidal ideation, suicide attempt, or suicide. Therefore, a complete screening of mothers’ mental health should also take into account thoughts of suicide and thoughts about harming infants as well. Clinicians should carefully monitor and early identify related clinical manifestations, potential risk factors, and alarm symptoms related to suicide. The present paper aims at providing a focused review about epidemiological data, risk factors, and an overview about the main clinical correlates associated with the suicidal behavior during the pregnancy and postpartum period. Practical recommendations have been provided as well. PMID:27570512

Suicide during Perinatal Period: Epidemiology, Risk Factors, and Clinical Correlates.

PubMed

Orsolini, Laura; Valchera, Alessandro; Vecchiotti, Roberta; Tomasetti, Carmine; Iasevoli, Felice; Fornaro, Michele; De Berardis, Domenico; Perna, Giampaolo; Pompili, Maurizio; Bellantuono, Cesario

2016-01-01

Perinatal period may pose a great challenge for the clinical management and treatment of psychiatric disorders in women. In fact, several mental illnesses can arise during pregnancy and/or following childbirth. Suicide has been considered a relatively rare event during the perinatal period. However, in some mental disorders (i.e., postpartum depression, bipolar disorder, postpartum psychosis, etc.) have been reported a higher risk of suicidal ideation, suicide attempt, or suicide. Therefore, a complete screening of mothers' mental health should also take into account thoughts of suicide and thoughts about harming infants as well. Clinicians should carefully monitor and early identify related clinical manifestations, potential risk factors, and alarm symptoms related to suicide. The present paper aims at providing a focused review about epidemiological data, risk factors, and an overview about the main clinical correlates associated with the suicidal behavior during the pregnancy and postpartum period. Practical recommendations have been provided as well.

Correlation between polymerization shrinkage stress and C-factor depends upon cavity compliance.

PubMed

Wang, Zhengzhi; Chiang, Martin Y M

2016-03-01

The literature reports inconsistent results regarding using configuration factor (C-factor) as an indicator to reflect the generation of polymerization shrinkage stress (PS) from dental restorative composites due to the constraint of cavity configuration. The current study aimed at unraveling the complex effects of C-factor on PS based on analytical and experimental approaches together, such that the reported inconsistency can be explained and a significance of C-factor in clinic can be comprehensively provided. Analytical models based on linear elasticity were established to predict PS measured in instruments (testing systems) with different compliances, and complex effects of C-factor on PS were derived. The analyses were validated by experiments using a cantilever beam-based instrument and systematic variation of instrumental compliance. For a general trend, PS decreased with increasing C-factor when measured by instruments with high compliance. However, this trend gradually diminished and eventually reversed (PS became increased with increasing C-factor) by decreasing the system compliance. Our study indicates that the correlation between PS and C-factor are highly dependent on the compliance of testing instrument for PS measurement. This suggests that the current concept on the role of C-factor in the stress development and transmission to tooth structures, higher C-factor produces higher PS due to reduced flow capacity of more confined materials, can be misleading. Thus, the compliance of the prepared tooth (cavity) structure should also be considered in the effect of C-factor on PS. Published by Elsevier Ltd.

Comparative expression analysis of immune-related factors in the sea cucumber Apostichopus japonicus.

PubMed

Jiang, Jingwei; Zhou, Zunchun; Dong, Ying; Zhao, Zelong; Sun, Hongjuan; Wang, Bai; Jiang, Bei; Chen, Zhong; Gao, Shan

2018-01-01

In order to preliminarily explore the joint involvement of different immune-related factors during the same immune process in Apostichopus japonicus, the transcriptional expression of Cu/Zn superoxide dismutase (Cu/Zn-SOD), catalase (CAT), c-type lysozyme (c-LYZ), i-type lysozyme (i-LYZ), cathepsin D, melanotransferrin (MTF), Toll, c-type lectin (c-LCT) and complement 3 (C3) during the development from fertilized eggs to juveniles and after challenging the juveniles with Vibrio splendidus, Pseudoalteromonas nigrifaciens, Shewanella baltica and Bacillus cereus, respectively, was measured using the method of quantitative real-time PCR (qRT-PCR), and then the correlations among different immune-related factors were analyzed. The results showed that the selected immune-related factors were expressed at all of the determined developmental stages and significantly up-regulated at doliolaria stage, suggesting the selected factors are indispensable immune components and the immune system might be broadly activated at doliolaria stage in A. japonicus. After challenged with four pathogenic bacteria, Cu/Zn-SOD, CAT, i-LYZ, cathepsin D, MTF, Toll, C3 were all significantly down-regulated at 4 h, indicating that some components of A. japonicus immune system might be inhibited at the beginning of pathogenic bacteria invasion. The immune-responsive analysis also showed that the significant regulation in Toll after challenged with four tested bacteria, that in MTF after challenged with S. baltica and that in C3 after challenged with P. nigrifaciens were all minus, suggesting Toll, MTF and C3 are probably the primary targets of pathogenic bacteria attack. Furthermore, the correlation analysis indicated that, all of the selected immune-related factors except cathepsin D might be in the same immune regulatory network during A. japonicus development, while all of the selected immune-related factors except c-LYZ might be in the same responsive regulatory network after challenged with

Ultrasound measurement of peripheral endothelial dysfunction in type 2 diabetic patients: correlation with risk factors

PubMed Central

Bosevski, Marijan; Georgievska-Ismail, Ljubica

2010-01-01

The purpose of the study was to assess the endothelial dysfunction (ED) in type 2 diabetic patients ultrasonographicaly and estimate the correlation of ED with glycemia and other cardio-metabolic risk factors. 171 patient (age 60,0 + 8,5 years) with diagnosed type 2 diabetes and coronary artery disease (CAD) were randomly included in a cross sectional study. B-mode ultrasound system with a linear transducer of 7.5 MHz was used for evaluation of flow-mediated vasodilation in brachial artery (FMV). FMV was presented as a change of brachial artery diameter at rest and after limb ischemia, previously provoked by cuff inflation. Peripheral ED was found in 77,2% (132 patients). Multivariate logistic regression model defined: age (OR 1,071, 95% CI 1,003 1,143) and plasma cholesterol (OR 4,083 95%CI 1,080 17,017) as determinants for ED. Linear multivariate analysis presented duration of diabetes (Beta 0,173, Sig 0,024), and glycemia (Beta 0,132, Sig 0,044) to be associated independently with FMV value. Estimated factors influencing FMV might be potential therapeutic targets for presented endothelial dysfunction in type 2 diabetic patients with coronary artery disease. PMID:20507285

Correlates of Gross Motor Competence in Children and Adolescents: A Systematic Review and Meta-Analysis.

PubMed

Barnett, Lisa M; Lai, Samuel K; Veldman, Sanne L C; Hardy, Louise L; Cliff, Dylan P; Morgan, Philip J; Zask, Avigdor; Lubans, David R; Shultz, Sarah P; Ridgers, Nicola D; Rush, Elaine; Brown, Helen L; Okely, Anthony D

2016-11-01

Gross motor competence confers health benefits, but levels in children and adolescents are low. While interventions can improve gross motor competence, it remains unclear which correlates should be targeted to ensure interventions are most effective, and for whom targeted and tailored interventions should be developed. The aim of this systematic review was to identify the potential correlates of gross motor competence in typically developing children and adolescents (aged 3-18 years) using an ecological approach. Motor competence was defined as gross motor skill competency, encompassing fundamental movement skills and motor coordination, but excluding motor fitness. Studies needed to assess a summary score of at least one aspect of motor competence (i.e., object control, locomotor, stability, or motor coordination). A structured electronic literature search was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Six electronic databases (CINAHL Complete, ERIC, MEDLINE Complete, PsycINFO ® , Scopus and SPORTDiscus with Full Text) were searched from 1994 to 5 August 2014. Meta-analyses were conducted to determine the relationship between potential correlates and motor competency if at least three individual studies investigated the same correlate and also reported standardized regression coefficients. A total of 59 studies were identified from 22 different countries, published between 1995 and 2014. Studies reflected the full range of age groups. The most examined correlates were biological and demographic factors. Age (increasing) was a correlate of children's motor competence. Weight status (healthy), sex (male) and socioeconomic background (higher) were consistent correlates for certain aspects of motor competence only. Physical activity and sport participation constituted the majority of investigations in the behavioral attributes and skills category. Whilst we found physical activity to be a positive

Analysis of risk factors for central venous port failure in cancer patients

PubMed Central

Hsieh, Ching-Chuan; Weng, Hsu-Huei; Huang, Wen-Shih; Wang, Wen-Ke; Kao, Chiung-Lun; Lu, Ming-Shian; Wang, Chia-Siu

2009-01-01

AIM: To analyze the risk factors for central port failure in cancer patients administered chemotherapy, using univariate and multivariate analyses. METHODS: A total of 1348 totally implantable venous access devices (TIVADs) were implanted into 1280 cancer patients in this cohort study. A Cox proportional hazard model was applied to analyze risk factors for failure of TIVADs. Log-rank test was used to compare actuarial survival rates. Infection, thrombosis, and surgical complication rates (χ2 test or Fisher’s exact test) were compared in relation to the risk factors. RESULTS: Increasing age, male gender and open-ended catheter use were significant risk factors reducing survival of TIVADs as determined by univariate and multivariate analyses. Hematogenous malignancy decreased the survival time of TIVADs; this reduction was not statistically significant by univariate analysis [hazard ratio (HR) = 1.336, 95% CI: 0.966-1.849, P = 0.080)]. However, it became a significant risk factor by multivariate analysis (HR = 1.499, 95% CI: 1.079-2.083, P = 0.016) when correlated with variables of age, sex and catheter type. Close-ended (Groshong) catheters had a lower thrombosis rate than open-ended catheters (2.5% vs 5%, P = 0.015). Hematogenous malignancy had higher infection rates than solid malignancy (10.5% vs 2.5%, P < 0.001). CONCLUSION: Increasing age, male gender, open-ended catheters and hematogenous malignancy were risk factors for TIVAD failure. Close-ended catheters had lower thrombosis rates and hematogenous malignancy had higher infection rates. PMID:19787834

Protein structure similarity from Principle Component Correlation analysis.

PubMed

Zhou, Xiaobo; Chou, James; Wong, Stephen T C

2006-01-25

Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD) in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities. We measure structural similarity between proteins by correlating the principle components of their secondary structure interaction matrix. In our approach, the Principle Component Correlation (PCC) analysis, a symmetric interaction matrix for a protein structure is constructed with relationship parameters between secondary elements that can take the form of distance, orientation, or other relevant structural invariants. When using a distance-based construction in the presence or absence of encoded N to C terminal sense, there are strong correlations between the principle components of interaction matrices of structurally or topologically similar proteins. The PCC method is extensively tested for protein structures that belong to the same topological class but are significantly different by RMSD measure. The PCC analysis can also differentiate proteins having similar shapes but different topological arrangements. Additionally, we demonstrate that when using two independently defined interaction matrices, comparison of their maximum eigenvalues can be highly effective in clustering structurally or

Effects of Correlated Errors on the Analysis of Space Geodetic Data

NASA Technical Reports Server (NTRS)

Romero-Wolf, Andres; Jacobs, C. S.

2011-01-01

As thermal errors are reduced instrumental and troposphere correlated errors will increasingly become more important. Work in progress shows that troposphere covariance error models improve data analysis results. We expect to see stronger effects with higher data rates. Temperature modeling of delay errors may further reduce temporal correlations in the data.

Modal Test/Analysis Correlation of Space Station Structures Using Nonlinear Sensitivity

NASA Technical Reports Server (NTRS)

Gupta, Viney K.; Newell, James F.; Berke, Laszlo; Armand, Sasan

1992-01-01

The modal correlation problem is formulated as a constrained optimization problem for validation of finite element models (FEM's). For large-scale structural applications, a pragmatic procedure for substructuring, model verification, and system integration is described to achieve effective modal correlation. The space station substructure FEM's are reduced using Lanczos vectors and integrated into a system FEM using Craig-Bampton component modal synthesis. The optimization code is interfaced with MSC/NASTRAN to solve the problem of modal test/analysis correlation; that is, the problem of validating FEM's for launch and on-orbit coupled loads analysis against experimentally observed frequencies and mode shapes. An iterative perturbation algorithm is derived and implemented to update nonlinear sensitivity (derivatives of eigenvalues and eigenvectors) during optimizer iterations, which reduced the number of finite element analyses.

Modal test/analysis correlation of Space Station structures using nonlinear sensitivity

NASA Technical Reports Server (NTRS)

Gupta, Viney K.; Newell, James F.; Berke, Laszlo; Armand, Sasan

1992-01-01

The modal correlation problem is formulated as a constrained optimization problem for validation of finite element models (FEM's). For large-scale structural applications, a pragmatic procedure for substructuring, model verification, and system integration is described to achieve effective modal correlations. The space station substructure FEM's are reduced using Lanczos vectors and integrated into a system FEM using Craig-Bampton component modal synthesis. The optimization code is interfaced with MSC/NASTRAN to solve the problem of modal test/analysis correlation; that is, the problem of validating FEM's for launch and on-orbit coupled loads analysis against experimentally observed frequencies and mode shapes. An iterative perturbation algorithm is derived and implemented to update nonlinear sensitivity (derivatives of eigenvalues and eigenvectors) during optimizer iterations, which reduced the number of finite element analyses.

The association between meteorological factors and road traffic injuries: a case analysis from Shantou city, China

PubMed Central

Gao, Jinghong; Chen, Xiaojun; Woodward, Alistair; Liu, Xiaobo; Wu, Haixia; Lu, Yaogui; Li, Liping; Liu, Qiyong

2016-01-01

Few studies examined the associations of meteorological factors with road traffic injuries (RTIs). The purpose of the present study was to quantify the contributions of meteorological factors to RTI cases treated at a tertiary level hospital in Shantou city, China. A time-series diagram was employed to illustrate the time trends and seasonal variation of RTIs, and correlation analysis and multiple linear regression analysis were conducted to investigate the relationships between meteorological parameters and RTIs. RTIs followed a seasonal pattern as more cases occurred during summer and winter months. RTIs are positively correlated with temperature and sunshine duration, while negatively associated with wind speed. Temperature, sunshine hour and wind speed were included in the final linear model with regression coefficients of 0.65 (t = 2.36, P = 0.019), 2.23 (t = 2.72, P = 0.007) and −27.66 (t = −5.67, P < 0.001), respectively, accounting for 19.93% of the total variation of RTI cases. The findings can help us better understand the associations between meteorological factors and RTIs, and with potential contributions to the development and implementation of regional level evidence-based weather-responsive traffic management system in the future. PMID:27853316

Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis

PubMed Central

Wang, Shijun; Yao, Jianhua; Liu, Jiamin; Petrick, Nicholas; Van Uitert, Robert L.; Periaswamy, Senthil; Summers, Ronald M.

2009-01-01

Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice—Once supine and once prone—to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined by the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27±52.97 to 14.98 mm±11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline. PMID:20095272

Registration of prone and supine CT colonography scans using correlation optimized warping and canonical correlation analysis

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

Wang Shijun; Yao Jianhua; Liu Jiamin

Purpose: In computed tomographic colonography (CTC), a patient will be scanned twice--Once supine and once prone--to improve the sensitivity for polyp detection. To assist radiologists in CTC reading, in this paper we propose an automated method for colon registration from supine and prone CTC scans. Methods: We propose a new colon centerline registration method for prone and supine CTC scans using correlation optimized warping (COW) and canonical correlation analysis (CCA) based on the anatomical structure of the colon. Four anatomical salient points on the colon are first automatically distinguished. Then correlation optimized warping is applied to the segments defined bymore » the anatomical landmarks to improve the global registration based on local correlation of segments. The COW method was modified by embedding canonical correlation analysis to allow multiple features along the colon centerline to be used in our implementation. Results: We tested the COW algorithm on a CTC data set of 39 patients with 39 polyps (19 training and 20 test cases) to verify the effectiveness of the proposed COW registration method. Experimental results on the test set show that the COW method significantly reduces the average estimation error in a polyp location between supine and prone scans by 67.6%, from 46.27{+-}52.97 to 14.98 mm{+-}11.41 mm, compared to the normalized distance along the colon centerline algorithm (p<0.01). Conclusions: The proposed COW algorithm is more accurate for the colon centerline registration compared to the normalized distance along the colon centerline method and the dynamic time warping method. Comparison results showed that the feature combination of z-coordinate and curvature achieved lowest registration error compared to the other feature combinations used by COW. The proposed method is tolerant to centerline errors because anatomical landmarks help prevent the propagation of errors across the entire colon centerline.« less

Correlation of regional cardiovascular disease mortality in India with lifestyle and nutritional factors.

PubMed

Gupta, Rajeev; Misra, Anoop; Pais, Prem; Rastogi, Priyanka; Gupta, V P

2006-04-14

There is a wide disparity in prevalence and cardiovascular disease mortality in different Indian states. To determine significance of various nutritional factors and other lifestyle variables in explaining this difference in cardiovascular disease mortality we performed an analysis. Mortality data were obtained from the Registrar General of India. In 1998 the annual death rate for India was 840/100,000 population. Cardiovascular diseases contribute to 27% of these deaths and its crude mortality rate was 227/100,000. Major differences in cardiovascular disease mortality rates in different Indian states were reported varying from 75-100 in sub-Himalayan states of Nagaland, Meghalaya, Himachal Pradesh and Sikkim to a high of 360-430 in Andhra Pradesh, Tamil Nadu, Punjab and Goa. Lifestyle data were obtained from national surveys conducted by the government of India. The second National Family Health Survey (26 states, 92,447 households, 301,984 adults) conducted in 1998-1999 reported on various demographic and lifestyle variables and India Nutrition Profile Study reported dietary intake of 177,841 adults (18 states, 75,229 men, 102,612 women). Cardiovascular disease mortality rates were correlated with smoking, literacy levels, prevalence of stunted growth at 3-years (as marker of fetal undernutrition), adult mean body mass index, prevalence of overweight and obesity, dietary consumption of calories, cereals and pulses, green leafy vegetables, roots, tubers and other vegetables, milk and milk products, fats and oils, and sugar and jaggery. As a major confounder in different states is poverty, all the partial correlation coefficients were adjusted for illiteracy, fertility rate and infant mortality rate. There was a significant positive correlation of cardiovascular disease mortality with prevalence of obesity (R=0.37) and dietary consumption of fats (R=0.67), milk and its products (R=0.27) and sugars (R=0.51) and negative correlation with green leafy vegetable intake

Factors influencing medication adherence in patients with gout: A descriptive correlational study.

PubMed

Chua, Xin Hui Jasmine; Lim, Siriwan; Lim, Fui Ping; Lim, Yee Nah Anita; He, Hong-Gu; Teng, Gim Gee

2018-01-01

To examine the factors influencing adherence to urate-lowering therapy in patients with gout in Singapore. Gout is the most common type of chronic inflammatory arthritis. Urate-lowering therapy is used to treat gout by reducing serum uric acid levels. However, adherence to urate-lowering therapy among patients remains poor. To date, there have been no available studies based on a conceptual framework that examined factors influencing medication adherence in patients with gout. Cross-sectional, descriptive correlational study. A convenience sample of outpatients (n = 108) was recruited between October 2014-January 2015 from a tertiary hospital in Singapore. Outcomes were measured by relevant valid and reliable instruments. Descriptive statistics and parametric tests including multiple linear regression were used to analyse the data. Although 44.4% of the participants were high adherers to urate-lowering therapy, the mean adherence level was moderate. Significant differences in medication adherence scores were found among the subgroups of gender, ethnicity, marital status, employment status and presence of comorbidity. Medication adherence was positively significantly correlated with age, number of comorbidities and beliefs about medicines. Linear regression showed that higher level of beliefs about medicines, presence of comorbidity and being married were factors positively influencing medication adherence. This study revealed moderate adherence to urate-lowering therapy in patients with gout in Singapore, indicating the need for strategies to improve adherence by considering its main influencing factors. Future research should be conducted to develop interventions targeted at modifying patients' beliefs about medicines in order to improve medication adherence. Findings from this study allow healthcare providers to quickly and easily identify patients who may have low adherence. Nurses should take the lead in educating patients on the mechanism of urate

Factor Retention in Exploratory Factor Analysis: A Comparison of Alternative Methods.

ERIC Educational Resources Information Center

Mumford, Karen R.; Ferron, John M.; Hines, Constance V.; Hogarty, Kristine Y.; Kromrey, Jeffery D.

This study compared the effectiveness of 10 methods of determining the number of factors to retain in exploratory common factor analysis. The 10 methods included the Kaiser rule and a modified Kaiser criterion, 3 variations of parallel analysis, 4 regression-based variations of the scree procedure, and the minimum average partial procedure. The…

Social cognition in schizophrenia: factor structure, clinical and functional correlates.

PubMed

Buck, Benjamin E; Healey, Kristin M; Gagen, Emily C; Roberts, David L; Penn, David L

2016-08-01

Social cognition is consistently impaired in people with schizophrenia, separable from general neurocognition, predictive of real-world functioning and amenable to psychosocial treatment. Few studies have empirically examined its underlying factor structure. This study (1) examines the factor structure of social cognition in both a sample of individuals with schizophrenia-spectrum disorders and non-clinical controls and (2) explores relationships of factors to neurocognition, symptoms and functioning. A factor analysis was conducted on social cognition measures in a sample of 65 individuals with schizophrenia or schizoaffective disorder, and 50 control participants. The resulting factors were examined for their relationships to symptoms and functioning. Results suggested a two-factor structure in the schizophrenia sample (social cognition skill and hostile attributional style) and a three-factor structure in the non-clinical sample (hostile attributional style, higher-level inferential processing and lower-level cue detection). In the schizophrenia sample, the social cognition skill factor was significantly related to negative symptoms and social functioning, whereas hostile attributional style predicted positive and general psychopathology symptoms. The factor structure of social cognition in schizophrenia separates hostile attributional style and social cognition skill, and each show differential relationships to relevant clinical variables in schizophrenia.

Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

PubMed

Roberson, Richard B; Elliott, Timothy R; Chang, Jessica E; Hill, Jessica N

2014-11-01

Our objective was to examine the use and quality of exploratory factor analysis (EFA) in articles published in Rehabilitation Psychology. Trained raters examined 66 separate exploratory factor analyses in 47 articles published between 1999 and April 2014. The raters recorded the aim of the EFAs, the distributional statistics, sample size, factor retention method(s), extraction and rotation method(s), and whether the pattern coefficients, structure coefficients, and the matrix of association were reported. The primary use of the EFAs was scale development, but the most widely used extraction and rotation method was principle component analysis, with varimax rotation. When determining how many factors to retain, multiple methods (e.g., scree plot, parallel analysis) were used most often. Many articles did not report enough information to allow for the duplication of their results. EFA relies on authors' choices (e.g., factor retention rules extraction, rotation methods), and few articles adhered to all of the best practices. The current findings are compared to other empirical investigations into the use of EFA in published research. Recommendations for improving EFA reporting practices in rehabilitation psychology research are provided.

A new method for correlation analysis of compositional (environmental) data - a worked example.

PubMed

Reimann, C; Filzmoser, P; Hron, K; Kynčlová, P; Garrett, R G

2017-12-31