A Confirmatory Factor Analysis of the Structure of Statistics Anxiety Measure: An examination of four alternative models

PubMed Central

Vahedi, Shahram; Farrokhi, Farahman

2011-01-01

Objective The aim of this study is to explore the confirmatory factor analysis results of the Persian adaptation of Statistics Anxiety Measure (SAM), proposed by Earp. Method The validity and reliability assessments of the scale were performed on 298 college students chosen randomly from Tabriz University in Iran. Confirmatory factor analysis (CFA) was carried out to determine the factor structures of the Persian adaptation of SAM. Results As expected, the second order model provided a better fit to the data than the three alternative models. Conclusions Hence, SAM provides an equally valid measure for use among college students. The study both expands and adds support to the existing body of math anxiety literature. PMID:22952530

Toward Reflective Judgment in Exploratory Factor Analysis Decisions: Determining the Extraction Method and Number of Factors To Retain.

ERIC Educational Resources Information Center

Knight, Jennifer L.

This paper considers some decisions that must be made by the researcher conducting an exploratory factor analysis. The primary purpose is to aid the researcher in making informed decisions during the factor analysis instead of relying on defaults in statistical programs or traditions of previous researchers. Three decision areas are addressed.…

Model Fit and Item Factor Analysis: Overfactoring, Underfactoring, and a Program to Guide Interpretation.

PubMed

Clark, D Angus; Bowles, Ryan P

2018-04-23

In exploratory item factor analysis (IFA), researchers may use model fit statistics and commonly invoked fit thresholds to help determine the dimensionality of an assessment. However, these indices and thresholds may mislead as they were developed in a confirmatory framework for models with continuous, not categorical, indicators. The present study used Monte Carlo simulation methods to investigate the ability of popular model fit statistics (chi-square, root mean square error of approximation, the comparative fit index, and the Tucker-Lewis index) and their standard cutoff values to detect the optimal number of latent dimensions underlying sets of dichotomous items. Models were fit to data generated from three-factor population structures that varied in factor loading magnitude, factor intercorrelation magnitude, number of indicators, and whether cross loadings or minor factors were included. The effectiveness of the thresholds varied across fit statistics, and was conditional on many features of the underlying model. Together, results suggest that conventional fit thresholds offer questionable utility in the context of IFA.

An Analysis of Effects of Variable Factors on Weapon Performance

DTIC Science & Technology

1993-03-01

ALTERNATIVE ANALYSIS A. CATEGORICAL DATA ANALYSIS Statistical methodology for categorical data analysis traces its roots to the work of Francis Galton in the...choice of statistical tests . This thesis examines an analysis performed by Surface Warfare Development Group (SWDG). The SWDG analysis is shown to be...incorrect due to the misapplication of testing methods. A corrected analysis is presented and recommendations suggested for changes to the testing

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

PubMed Central

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

2013-01-01

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

The Shock and Vibration Digest. Volume 15, Number 7

DTIC Science & Technology

1983-07-01

systems noise -- for tant analytical tool, the statistical energy analysis example, from a specific metal, chain driven, con- method, has been the subject...34Experimental Determination of Vibration Parameters Re- ~~~quired in the Statistical Energy Analysis Meth- .,i. 31. Dubowsky, S. and Morris, T.L., "An...34Coupling Loss Factors for 55. Upton, R., "Sound Intensity -. A Powerful New Statistical Energy Analysis of Sound Trans- Measurement Tool," S/V, Sound

Selecting the "Best" Factor Structure and Moving Measurement Validation Forward: An Illustration.

PubMed

Schmitt, Thomas A; Sass, Daniel A; Chappelle, Wayne; Thompson, William

2018-04-09

Despite the broad literature base on factor analysis best practices, research seeking to evaluate a measure's psychometric properties frequently fails to consider or follow these recommendations. This leads to incorrect factor structures, numerous and often overly complex competing factor models and, perhaps most harmful, biased model results. Our goal is to demonstrate a practical and actionable process for factor analysis through (a) an overview of six statistical and psychometric issues and approaches to be aware of, investigate, and report when engaging in factor structure validation, along with a flowchart for recommended procedures to understand latent factor structures; (b) demonstrating these issues to provide a summary of the updated Posttraumatic Stress Disorder Checklist (PCL-5) factor models and a rationale for validation; and (c) conducting a comprehensive statistical and psychometric validation of the PCL-5 factor structure to demonstrate all the issues we described earlier. Considering previous research, the PCL-5 was evaluated using a sample of 1,403 U.S. Air Force remotely piloted aircraft operators with high levels of battlefield exposure. Previously proposed PCL-5 factor structures were not supported by the data, but instead a bifactor model is arguably more statistically appropriate.

Transforming Graph Data for Statistical Relational Learning

DTIC Science & Technology

2012-10-01

Jordan, 2003), PLSA (Hofmann, 1999), ? Classification via RMN (Taskar et al., 2003) or SVM (Hasan, Chaoji, Salem , & Zaki, 2006) ? Hierarchical...dimensionality reduction methods such as Principal 407 Rossi, McDowell, Aha, & Neville Component Analysis (PCA), Principal Factor Analysis ( PFA ), and...clustering algorithm. Journal of the Royal Statistical Society. Series C, Applied statistics, 28, 100–108. Hasan, M. A., Chaoji, V., Salem , S., & Zaki, M

A Bootstrap Generalization of Modified Parallel Analysis for IRT Dimensionality Assessment

ERIC Educational Resources Information Center

Finch, Holmes; Monahan, Patrick

2008-01-01

This article introduces a bootstrap generalization to the Modified Parallel Analysis (MPA) method of test dimensionality assessment using factor analysis. This methodology, based on the use of Marginal Maximum Likelihood nonlinear factor analysis, provides for the calculation of a test statistic based on a parametric bootstrap using the MPA…

Sexual Harassment Retaliation Climate DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

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

Applied Statistics: From Bivariate through Multivariate Techniques [with CD-ROM

ERIC Educational Resources Information Center

Warner, Rebecca M.

2007-01-01

This book provides a clear introduction to widely used topics in bivariate and multivariate statistics, including multiple regression, discriminant analysis, MANOVA, factor analysis, and binary logistic regression. The approach is applied and does not require formal mathematics; equations are accompanied by verbal explanations. Students are asked…

The "S.W.A.T." Concept.

ERIC Educational Resources Information Center

Williamson, Bob; And Others

1985-01-01

Describes Statistical Work Analysis Teams (S.W.A.T.), which marry the two factors necessary for successful statistical analysis with the personal nature of attribute data into a single effort. Discusses S.W.A.T. project guidelines, implementation of the first S.W.A.T. projects, team training, and project completion. (CT)

An Analysis of Attitudes toward Statistics: Gender Differences among Advertising Majors.

ERIC Educational Resources Information Center

Fullerton, Jami A.; Umphrey, Don

This study measures advertising students' attitudes toward statistics. Subjects, 275 undergraduate advertising students from two southwestern United States universities, completed a questionnaire used to gauge students' attitudes toward statistics by measuring 6 underlying factors: (1) students' interest and future applicability; (2) relationship…

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

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

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

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

PubMed

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

2004-02-01

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

How Attitudes towards Statistics Courses and the Field of Statistics Predicts Statistics Anxiety among Undergraduate Social Science Majors: A Validation of the Statistical Anxiety Scale

ERIC Educational Resources Information Center

O'Bryant, Monique J.

2017-01-01

The aim of this study was to validate an instrument that can be used by instructors or social scientist who are interested in evaluating statistics anxiety. The psychometric properties of the English version of the Statistical Anxiety Scale (SAS) was examined through a confirmatory factor analysis of scores from a sample of 323 undergraduate…

Students' Perception of Frequent Assessments and Its Relation to Motivation and Grades in a Statistics Course: A Pilot Study

ERIC Educational Resources Information Center

Vaessen, Bram E.; van den Beemt, Antoine; van de Watering, Gerard; van Meeuwen, Ludo W.; Lemmens, Lex; den Brok, Perry

2017-01-01

This pilot study measures university students' perceptions of graded frequent assessments in an obligatory statistics course using a novel questionnaire. Relations between perceptions of frequent assessments, intrinsic motivation and grades were also investigated. A factor analysis of the questionnaire revealed four factors, which were labelled…

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

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

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

PubMed

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

2017-03-01

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

Exploring the validity and statistical utility of a racism scale among Black men who have sex with men: a pilot study.

PubMed

Smith, William Pastor

2013-09-01

The primary purpose of this two-phased study was to examine the structural validity and statistical utility of a racism scale specific to Black men who have sex with men (MSM) who resided in the Washington, DC, metropolitan area and Baltimore, Maryland. Phase I involved pretesting a 10-item racism measure with 20 Black MSM. Based on pretest findings, the scale was adapted into a 21-item racism scale for use in collecting data on 166 respondents in Phase II. Exploratory factor analysis of the 21-item racism scale resulted in a 19-item, two-factor solution. The two factors or subscales were the following: General Racism and Relationships and Racism. Confirmatory factor analysis was used in testing construct validity of the factored racism scale. Specifically, the two racism factors were combined with three homophobia factors into a confirmatory factor analysis model. Based on a summary of the fit indices, both comparative and incremental were equal to .90, suggesting an adequate convergence of the racism and homophobia dimensions into a single social oppression construct. Statistical utility of the two racism subscales was demonstrated when regression analysis revealed that the gay-identified men versus bisexual-identified men in the sample were more likely to experience increased racism within the context of intimate relationships and less likely to be exposed to repeated experiences of general racism. Overall, the findings in this study highlight the importance of continuing to explore the psychometric properties of a racism scale that accounts for the unique psychosocial concerns experienced by Black MSM.

A factor analysis of the SSQ (Speech, Spatial, and Qualities of Hearing Scale).

PubMed

Akeroyd, Michael A; Guy, Fiona H; Harrison, Dawn L; Suller, Sharon L

2014-02-01

The speech, spatial, and qualities of hearing questionnaire (SSQ) is a self-report test of auditory disability. The 49 items ask how well a listener would do in many complex listening situations illustrative of real life. The scores on the items are often combined into the three main sections or into 10 pragmatic subscales. We report here a factor analysis of the SSQ that we conducted to further investigate its statistical properties and to determine its structure. Statistical factor analysis of questionnaire data, using parallel analysis to determine the number of factors to retain, oblique rotation of factors, and a bootstrap method to estimate the confidence intervals. 1220 people who have attended MRC IHR over the last decade. We found three clear factors, essentially corresponding to the three main sections of the SSQ. They are termed "speech understanding", "spatial perception", and "clarity, separation, and identification". Thirty-five of the SSQ questions were included in the three factors. There was partial evidence for a fourth factor, "effort and concentration", representing two more questions. These results aid in the interpretation and application of the SSQ and indicate potential methods for generating average scores.

Agriculture, population growth, and statistical analysis of the radiocarbon record.

PubMed

Zahid, H Jabran; Robinson, Erick; Kelly, Robert L

2016-01-26

The human population has grown significantly since the onset of the Holocene about 12,000 y ago. Despite decades of research, the factors determining prehistoric population growth remain uncertain. Here, we examine measurements of the rate of growth of the prehistoric human population based on statistical analysis of the radiocarbon record. We find that, during most of the Holocene, human populations worldwide grew at a long-term annual rate of 0.04%. Statistical analysis of the radiocarbon record shows that transitioning farming societies experienced the same rate of growth as contemporaneous foraging societies. The same rate of growth measured for populations dwelling in a range of environments and practicing a variety of subsistence strategies suggests that the global climate and/or endogenous biological factors, not adaptability to local environment or subsistence practices, regulated the long-term growth of the human population during most of the Holocene. Our results demonstrate that statistical analyses of large ensembles of radiocarbon dates are robust and valuable for quantitatively investigating the demography of prehistoric human populations worldwide.

Ranking and validation of spallation models for isotopic production cross sections of heavy residua

NASA Astrophysics Data System (ADS)

Sharma, Sushil K.; Kamys, Bogusław; Goldenbaum, Frank; Filges, Detlef

2017-07-01

The production cross sections of isotopically identified residual nuclei of spallation reactions induced by 136Xe projectiles at 500AMeV on hydrogen target were analyzed in a two-step model. The first stage of the reaction was described by the INCL4.6 model of an intranuclear cascade of nucleon-nucleon and pion-nucleon collisions whereas the second stage was analyzed by means of four different models; ABLA07, GEM2, GEMINI++ and SMM. The quality of the data description was judged quantitatively using two statistical deviation factors; the H-factor and the M-factor. It was found that the present analysis leads to a different ranking of models as compared to that obtained from the qualitative inspection of the data reproduction. The disagreement was caused by sensitivity of the deviation factors to large statistical errors present in some of the data. A new deviation factor, the A factor, was proposed, that is not sensitive to the statistical errors of the cross sections. The quantitative ranking of models performed using the A-factor agreed well with the qualitative analysis of the data. It was concluded that using the deviation factors weighted by statistical errors may lead to erroneous conclusions in the case when the data cover a large range of values. The quality of data reproduction by the theoretical models is discussed. Some systematic deviations of the theoretical predictions from the experimental results are observed.

Analyzing the Validity of the Adult-Adolescent Parenting Inventory for Low-Income Populations

ERIC Educational Resources Information Center

Lawson, Michael A.; Alameda-Lawson, Tania; Byrnes, Edward

2017-01-01

Objectives: The purpose of this study was to examine the construct and predictive validity of the Adult-Adolescent Parenting Inventory (AAPI-2). Methods: The validity of the AAPI-2 was evaluated using multiple statistical methods, including exploratory factor analysis, confirmatory factor analysis, and latent class analysis. These analyses were…

Development of Consistency between Marketing and Planning.

ERIC Educational Resources Information Center

Williford, A. Michael

1986-01-01

Examined descriptive information about marketing, enrollment management, institutional planning and factors affecting them. A factor analysis of statistically appropriate variables identified factors associated with a state of symbiosis between marketing and institutional planning. (Author/BL)

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

PubMed

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

2017-04-01

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

Statistical analysis of the electrocatalytic activity of Pt nanoparticles supported on novel functionalized reduced graphene oxide-chitosan for methanol electrooxidation

NASA Astrophysics Data System (ADS)

Ekrami-Kakhki, Mehri-Saddat; Abbasi, Sedigheh; Farzaneh, Nahid

2018-01-01

The purpose of this study is to statistically analyze the anodic current density and peak potential of methanol oxidation at Pt nanoparticles supported on functionalized reduced graphene oxide (RGO), using design of experiments methodology. RGO is functionalized with methyl viologen (MV) and chitosan (CH). The novel Pt/MV-RGO-CH catalyst is successfully prepared and characterized with transmission electron microscopy (TEM) image. The electrocatalytic activity of Pt/MV-RGOCH catalyst is experimentally evaluated for methanol oxidation. The effects of methanol concentration and scan rate factors are also investigated experimentally and statistically. The effects of these two main factors and their interactions are investigated, using analysis of variance test, Duncan's multiple range test and response surface method. The results of the analysis of variance show that all the main factors and their interactions have a significant effect on anodic current density and peak potential of methanol oxidation at α = 0.05. The suggested models which encompass significant factors can predict the variation of the anodic current density and peak potential of methanol oxidation. The results of Duncan's multiple range test confirmed that there is a significant difference between the studied levels of the main factors. [Figure not available: see fulltext.

Multivariate analysis of fears in dental phobic patients according to a reduced FSS-II scale.

PubMed

Hakeberg, M; Gustafsson, J E; Berggren, U; Carlsson, S G

1995-10-01

This study analyzed and assessed dimensions of a questionnaire developed to measure general fears and phobias. A previous factor analysis among 109 dental phobics had revealed a five-factor structure with 22 items and an explained total variance of 54%. The present study analyzed the same material using a multivariate statistical procedure (LISREL) to reveal structural latent variables. The LISREL analysis, based on the correlation matrix, yielded a chi-square of 216.6 with 195 degrees of freedom (P = 0.138) and showed a model with seven latent variables. One was a general fear factor correlated to all 22 items. The other six factors concerned "Illness & Death" (5 items), "Failures & Embarrassment" (5 items), "Social situations" (5 items), "Physical injuries" (4 items), "Animals & Natural phenomena" (4 items). One item (opposite sex) was included in both "Failures & Embarrassment" and "Social situations". The last factor, "Social interaction", combined all the items in "Failures & Embarrassment" and "Social situations" (9 items). In conclusion, this multivariate statistical analysis (LISREL) revealed and confirmed a factor structure similar to our previous study, but added two important dimensions not shown with a traditional factor analysis. This reduced FSS-II version measures general fears and phobias and may be used on a routine clinical basis as well as in dental phobia research.

Individual risk factors for deep infection and compromised fracture healing after intramedullary nailing of tibial shaft fractures: a single centre experience of 480 patients.

PubMed

Metsemakers, W-J; Handojo, K; Reynders, P; Sermon, A; Vanderschot, P; Nijs, S

2015-04-01

Despite modern advances in the treatment of tibial shaft fractures, complications including nonunion, malunion, and infection remain relatively frequent. A better understanding of these injuries and its complications could lead to prevention rather than treatment strategies. A retrospective study was performed to identify risk factors for deep infection and compromised fracture healing after intramedullary nailing (IMN) of tibial shaft fractures. Between January 2000 and January 2012, 480 consecutive patients with 486 tibial shaft fractures were enrolled in the study. Statistical analysis was performed to determine predictors of deep infection and compromised fracture healing. Compromised fracture healing was subdivided in delayed union and nonunion. The following independent variables were selected for analysis: age, sex, smoking, obesity, diabetes, American Society of Anaesthesiologists (ASA) classification, polytrauma, fracture type, open fractures, Gustilo type, primary external fixation (EF), time to nailing (TTN) and reaming. As primary statistical evaluation we performed a univariate analysis, followed by a multiple logistic regression model. Univariate regression analysis revealed similar risk factors for delayed union and nonunion, including fracture type, open fractures and Gustilo type. Factors affecting the occurrence of deep infection in this model were primary EF, a prolonged TTN, open fractures and Gustilo type. Multiple logistic regression analysis revealed polytrauma as the single risk factor for nonunion. With respect to delayed union, no risk factors could be identified. In the same statistical model, deep infection was correlated with primary EF. The purpose of this study was to evaluate risk factors of poor outcome after IMN of tibial shaft fractures. The univariate regression analysis showed that the nature of complications after tibial shaft nailing could be multifactorial. This was not confirmed in a multiple logistic regression model, which only revealed polytrauma and primary EF as risk factors for nonunion and deep infection, respectively. Future strategies should focus on prevention in high-risk populations such as polytrauma patients treated with EF. Copyright © 2014 Elsevier Ltd. All rights reserved.

Water quality analysis of the Rapur area, Andhra Pradesh, South India using multivariate techniques

NASA Astrophysics Data System (ADS)

Nagaraju, A.; Sreedhar, Y.; Thejaswi, A.; Sayadi, Mohammad Hossein

2017-10-01

The groundwater samples from Rapur area were collected from different sites to evaluate the major ion chemistry. The large number of data can lead to difficulties in the integration, interpretation, and representation of the results. Two multivariate statistical methods, hierarchical cluster analysis (HCA) and factor analysis (FA), were applied to evaluate their usefulness to classify and identify geochemical processes controlling groundwater geochemistry. Four statistically significant clusters were obtained from 30 sampling stations. This has resulted two important clusters viz., cluster 1 (pH, Si, CO3, Mg, SO4, Ca, K, HCO3, alkalinity, Na, Na + K, Cl, and hardness) and cluster 2 (EC and TDS) which are released to the study area from different sources. The application of different multivariate statistical techniques, such as principal component analysis (PCA), assists in the interpretation of complex data matrices for a better understanding of water quality of a study area. From PCA, it is clear that the first factor (factor 1), accounted for 36.2% of the total variance, was high positive loading in EC, Mg, Cl, TDS, and hardness. Based on the PCA scores, four significant cluster groups of sampling locations were detected on the basis of similarity of their water quality.

STATISTICAL ANALYSIS OF SNAP 10A THERMOELECTRIC CONVERTER ELEMENT PROCESS DEVELOPMENT VARIABLES

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

Fitch, S.H.; Morris, J.W.

1962-12-15

Statistical analysis, primarily analysis of variance, was applied to evaluate several factors involved in the development of suitable fabrication and processing techniques for the production of lead telluride thermoelectric elements for the SNAP 10A energy conversion system. The analysis methods are described as to their application for determining the effects of various processing steps, estabIishing the value of individual operations, and evaluating the significance of test results. The elimination of unnecessary or detrimental processing steps was accomplished and the number of required tests was substantially reduced by application of these statistical methods to the SNAP 10A production development effort. (auth)

A factor analysis of the SSQ (Speech, Spatial, and Qualities of Hearing Scale)

PubMed Central

2014-01-01

Objective The speech, spatial, and qualities of hearing questionnaire (SSQ) is a self-report test of auditory disability. The 49 items ask how well a listener would do in many complex listening situations illustrative of real life. The scores on the items are often combined into the three main sections or into 10 pragmatic subscales. We report here a factor analysis of the SSQ that we conducted to further investigate its statistical properties and to determine its structure. Design Statistical factor analysis of questionnaire data, using parallel analysis to determine the number of factors to retain, oblique rotation of factors, and a bootstrap method to estimate the confidence intervals. Study sample 1220 people who have attended MRC IHR over the last decade. Results We found three clear factors, essentially corresponding to the three main sections of the SSQ. They are termed “speech understanding”, “spatial perception”, and “clarity, separation, and identification”. Thirty-five of the SSQ questions were included in the three factors. There was partial evidence for a fourth factor, “effort and concentration”, representing two more questions. Conclusions These results aid in the interpretation and application of the SSQ and indicate potential methods for generating average scores. PMID:24417459

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

PubMed

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

2011-01-01

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

Validating Future Force Performance Measures (Army Class): Concluding Analyses

DTIC Science & Technology

2016-06-01

32 Table 3.10. Descriptive Statistics and Intercorrelations for LV Final Predictor Factor Scores...55 Table 4.7. Descriptive Statistics for Analysis Criteria...Soldier attrition and performance: Dependability (Non- Delinquency ), Adjustment, Physical Conditioning, Leadership, Work Orientation, and Agreeableness

Acoustic fill factors for a 120 inch diameter fairing

NASA Technical Reports Server (NTRS)

Lee, Y. Albert

1992-01-01

Data from the acoustic test of a 120-inch diameter payload fairing were collected and an analysis of acoustic fill factors were performed. Correction factors for obtaining a weighted spatial average of the interior sound pressure level (SPL) were derived based on this database and a normalized 200-inch diameter fairing database. The weighted fill factors were determined and compared with statistical energy analysis (VAPEPS code) derived fill factors. The comparison is found to be reasonable.

Statistical analysis of arthroplasty data

PubMed Central

2011-01-01

It is envisaged that guidelines for statistical analysis and presentation of results will improve the quality and value of research. The Nordic Arthroplasty Register Association (NARA) has therefore developed guidelines for the statistical analysis of arthroplasty register data. The guidelines are divided into two parts, one with an introduction and a discussion of the background to the guidelines (Ranstam et al. 2011a, see pages x-y in this issue), and this one with a more technical statistical discussion on how specific problems can be handled. This second part contains (1) recommendations for the interpretation of methods used to calculate survival, (2) recommendations on howto deal with bilateral observations, and (3) a discussion of problems and pitfalls associated with analysis of factors that influence survival or comparisons between outcomes extracted from different hospitals. PMID:21619500

Dimensionality of Community Satisfaction.

ERIC Educational Resources Information Center

Williams, R. Gary; Knop, Edward

Using factor analysis (both principal factor solutions and rotated factor solutions) to search for underlying statistical commonality among 12 indicators of community satisfaction in 6 Colorado communities, the research explores various dimensions of community satisfaction that may be important across different communities. The communities under…

Job Satisfaction DEOCS 4.1 Construct Validity Summary

DTIC Science & Technology

2017-08-01

focuses more specifically on satisfaction with the job. Included is a review of the 4.0 description and items, followed by the proposed modifications to...the factor. The DEOCS 4.0 description provided for job satisfaction is “the perception of personal fulfillment in a specific vocation, and sense of...piloting items on the DEOCS; (4) examining the descriptive statistics, exploratory factor analysis results, and aggregation statistics; and (5

Assessing Attitudes towards Statistics among Medical Students: Psychometric Properties of the Serbian Version of the Survey of Attitudes Towards Statistics (SATS)

PubMed Central

Stanisavljevic, Dejana; Trajkovic, Goran; Marinkovic, Jelena; Bukumiric, Zoran; Cirkovic, Andja; Milic, Natasa

2014-01-01

Background Medical statistics has become important and relevant for future doctors, enabling them to practice evidence based medicine. Recent studies report that students’ attitudes towards statistics play an important role in their statistics achievements. The aim of the study was to test the psychometric properties of the Serbian version of the Survey of Attitudes Towards Statistics (SATS) in order to acquire a valid instrument to measure attitudes inside the Serbian educational context. Methods The validation study was performed on a cohort of 417 medical students who were enrolled in an obligatory introductory statistics course. The SATS adaptation was based on an internationally accepted methodology for translation and cultural adaptation. Psychometric properties of the Serbian version of the SATS were analyzed through the examination of factorial structure and internal consistency. Results Most medical students held positive attitudes towards statistics. The average total SATS score was above neutral (4.3±0.8), and varied from 1.9 to 6.2. Confirmatory factor analysis validated the six-factor structure of the questionnaire (Affect, Cognitive Competence, Value, Difficulty, Interest and Effort). Values for fit indices TLI (0.940) and CFI (0.961) were above the cut-off of ≥0.90. The RMSEA value of 0.064 (0.051–0.078) was below the suggested value of ≤0.08. Cronbach’s alpha of the entire scale was 0.90, indicating scale reliability. In a multivariate regression model, self-rating of ability in mathematics and current grade point average were significantly associated with the total SATS score after adjusting for age and gender. Conclusion Present study provided the evidence for the appropriate metric properties of the Serbian version of SATS. Confirmatory factor analysis validated the six-factor structure of the scale. The SATS might be reliable and a valid instrument for identifying medical students’ attitudes towards statistics in the Serbian educational context. PMID:25405489

Assessing attitudes towards statistics among medical students: psychometric properties of the Serbian version of the Survey of Attitudes Towards Statistics (SATS).

PubMed

Stanisavljevic, Dejana; Trajkovic, Goran; Marinkovic, Jelena; Bukumiric, Zoran; Cirkovic, Andja; Milic, Natasa

2014-01-01

Medical statistics has become important and relevant for future doctors, enabling them to practice evidence based medicine. Recent studies report that students' attitudes towards statistics play an important role in their statistics achievements. The aim of the study was to test the psychometric properties of the Serbian version of the Survey of Attitudes Towards Statistics (SATS) in order to acquire a valid instrument to measure attitudes inside the Serbian educational context. The validation study was performed on a cohort of 417 medical students who were enrolled in an obligatory introductory statistics course. The SATS adaptation was based on an internationally accepted methodology for translation and cultural adaptation. Psychometric properties of the Serbian version of the SATS were analyzed through the examination of factorial structure and internal consistency. Most medical students held positive attitudes towards statistics. The average total SATS score was above neutral (4.3±0.8), and varied from 1.9 to 6.2. Confirmatory factor analysis validated the six-factor structure of the questionnaire (Affect, Cognitive Competence, Value, Difficulty, Interest and Effort). Values for fit indices TLI (0.940) and CFI (0.961) were above the cut-off of ≥0.90. The RMSEA value of 0.064 (0.051-0.078) was below the suggested value of ≤0.08. Cronbach's alpha of the entire scale was 0.90, indicating scale reliability. In a multivariate regression model, self-rating of ability in mathematics and current grade point average were significantly associated with the total SATS score after adjusting for age and gender. Present study provided the evidence for the appropriate metric properties of the Serbian version of SATS. Confirmatory factor analysis validated the six-factor structure of the scale. The SATS might be reliable and a valid instrument for identifying medical students' attitudes towards statistics in the Serbian educational context.

Multivariate analysis of heavy metal contamination using river sediment cores of Nankan River, northern Taiwan

NASA Astrophysics Data System (ADS)

Lee, An-Sheng; Lu, Wei-Li; Huang, Jyh-Jaan; Chang, Queenie; Wei, Kuo-Yen; Lin, Chin-Jung; Liou, Sofia Ya Hsuan

2016-04-01

Through the geology and climate characteristic in Taiwan, generally rivers carry a lot of suspended particles. After these particles settled, they become sediments which are good sorbent for heavy metals in river system. Consequently, sediments can be found recording contamination footprint at low flow energy region, such as estuary. Seven sediment cores were collected along Nankan River, northern Taiwan, which is seriously contaminated by factory, household and agriculture input. Physico-chemical properties of these cores were derived from Itrax-XRF Core Scanner and grain size analysis. In order to interpret these complex data matrices, the multivariate statistical techniques (cluster analysis, factor analysis and discriminant analysis) were introduced to this study. Through the statistical determination, the result indicates four types of sediment. One of them represents contamination event which shows high concentration of Cu, Zn, Pb, Ni and Fe, and low concentration of Si and Zr. Furthermore, three possible contamination sources of this type of sediment were revealed by Factor Analysis. The combination of sediment analysis and multivariate statistical techniques used provides new insights into the contamination depositional history of Nankan River and could be similarly applied to other river systems to determine the scale of anthropogenic contamination.

Modelling and analysis of FMS productivity variables by ISM, SEM and GTMA approach

NASA Astrophysics Data System (ADS)

Jain, Vineet; Raj, Tilak

2014-09-01

Productivity has often been cited as a key factor in a flexible manufacturing system (FMS) performance, and actions to increase it are said to improve profitability and the wage earning capacity of employees. Improving productivity is seen as a key issue for survival and success in the long term of a manufacturing system. The purpose of this paper is to make a model and analysis of the productivity variables of FMS. This study was performed by different approaches viz. interpretive structural modelling (ISM), structural equation modelling (SEM), graph theory and matrix approach (GTMA) and a cross-sectional survey within manufacturing firms in India. ISM has been used to develop a model of productivity variables, and then it has been analyzed. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) are powerful statistical techniques. CFA is carried by SEM. EFA is applied to extract the factors in FMS by the statistical package for social sciences (SPSS 20) software and confirming these factors by CFA through analysis of moment structures (AMOS 20) software. The twenty productivity variables are identified through literature and four factors extracted, which involves the productivity of FMS. The four factors are people, quality, machine and flexibility. SEM using AMOS 20 was used to perform the first order four-factor structures. GTMA is a multiple attribute decision making (MADM) methodology used to find intensity/quantification of productivity variables in an organization. The FMS productivity index has purposed to intensify the factors which affect FMS.

Statistical model to perform error analysis of curve fits of wind tunnel test data using the techniques of analysis of variance and regression analysis

NASA Technical Reports Server (NTRS)

Alston, D. W.

1981-01-01

The considered research had the objective to design a statistical model that could perform an error analysis of curve fits of wind tunnel test data using analysis of variance and regression analysis techniques. Four related subproblems were defined, and by solving each of these a solution to the general research problem was obtained. The capabilities of the evolved true statistical model are considered. The least squares fit is used to determine the nature of the force, moment, and pressure data. The order of the curve fit is increased in order to delete the quadratic effect in the residuals. The analysis of variance is used to determine the magnitude and effect of the error factor associated with the experimental data.

Statistical analysis of the factors that influenced the mechanical properties improvement of cassava starch films

NASA Astrophysics Data System (ADS)

Monteiro, Mayra; Oliveira, Victor; Santos, Francisco; Barros Neto, Eduardo; Silva, Karyn; Silva, Rayane; Henrique, João; Chibério, Abimaelle

2017-08-01

In order to obtain cassava starch films with improved mechanical properties in relation to the synthetic polymer in the packaging production, a complete factorial design 23 was carried out in order to investigate which factor significantly influences the tensile strength of the biofilm. The factors to be investigated were cassava starch, glycerol and modified clay contents. Modified bentonite clay was used as a filling material of the biofilm. Glycerol was the plasticizer used to thermoplastify cassava starch. The factorial analysis suggested a regression model capable of predicting the optimal mechanical property of the cassava starch film from the maximization of the tensile strength. The reliability of the regression model was tested by the correlation established with the experimental data through the following statistical analyse: Pareto graph. The modified clay was the factor of greater statistical significance on the observed response variable, being the factor that contributed most to the improvement of the mechanical property of the starch film. The factorial experiments showed that the interaction of glycerol with both modified clay and cassava starch was significant for the reduction of biofilm ductility. Modified clay and cassava starch contributed to the maximization of biofilm ductility, while glycerol contributed to the minimization.

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

PubMed

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

2015-01-01

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

A Comparison of Imputation Methods for Bayesian Factor Analysis Models

ERIC Educational Resources Information Center

Merkle, Edgar C.

2011-01-01

Imputation methods are popular for the handling of missing data in psychology. The methods generally consist of predicting missing data based on observed data, yielding a complete data set that is amiable to standard statistical analyses. In the context of Bayesian factor analysis, this article compares imputation under an unrestricted…

Multilevel Factor Analysis by Model Segregation: New Applications for Robust Test Statistics

ERIC Educational Resources Information Center

Schweig, Jonathan

2014-01-01

Measures of classroom environments have become central to policy efforts that assess school and teacher quality. This has sparked a wide interest in using multilevel factor analysis to test measurement hypotheses about classroom-level variables. One approach partitions the total covariance matrix and tests models separately on the…

Modular Open-Source Software for Item Factor Analysis

ERIC Educational Resources Information Center

Pritikin, Joshua N.; Hunter, Micheal D.; Boker, Steven M.

2015-01-01

This article introduces an item factor analysis (IFA) module for "OpenMx," a free, open-source, and modular statistical modeling package that runs within the R programming environment on GNU/Linux, Mac OS X, and Microsoft Windows. The IFA module offers a novel model specification language that is well suited to programmatic generation…

Factor analysis in optimization of formulation of high content uniformity tablets containing low dose active substance.

PubMed

Lukášová, Ivana; Muselík, Jan; Franc, Aleš; Goněc, Roman; Mika, Filip; Vetchý, David

2017-11-15

Warfarin is intensively discussed drug with narrow therapeutic range. There have been cases of bleeding attributed to varying content or altered quality of the active substance. Factor analysis is useful for finding suitable technological parameters leading to high content uniformity of tablets containing low amount of active substance. The composition of tabletting blend and technological procedure were set with respect to factor analysis of previously published results. The correctness of set parameters was checked by manufacturing and evaluation of tablets containing 1-10mg of warfarin sodium. The robustness of suggested technology was checked by using "worst case scenario" and statistical evaluation of European Pharmacopoeia (EP) content uniformity limits with respect to Bergum division and process capability index (Cpk). To evaluate the quality of active substance and tablets, dissolution method was developed (water; EP apparatus II; 25rpm), allowing for statistical comparison of dissolution profiles. Obtained results prove the suitability of factor analysis to optimize the composition with respect to batches manufactured previously and thus the use of metaanalysis under industrial conditions is feasible. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed

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

2009-08-28

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

Factorial analysis of trihalomethanes formation in drinking water.

PubMed

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

2010-06-01

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

Statistical analysis on the factors affecting agricultural landowners’ willingness to enroll in a tree planting program

Treesearch

Taeyoung Kim; Christian Langpap

2015-01-01

This report provides a statistical analysis of the data collected from two survey regions of the United States, the Pacific Northwest and the Southeast. The survey asked about individual agricultural landowners’ characteristics, characteristics of their land, and the landowners’ willingness to enroll in a tree planting program under incentive payments for carbon...

Identifying the hydrochemical characteristics of rivers and groundwater by multivariate statistical analysis in the Sanjiang Plain, China

NASA Astrophysics Data System (ADS)

Cao, Yingjie; Tang, Changyuan; Song, Xianfang; Liu, Changming; Zhang, Yinghua

2016-06-01

Two multivariate statistical technologies, factor analysis (FA) and discriminant analysis (DA), are applied to study the river and groundwater hydrochemistry and its controlling processes in the Sanjiang Plain of the northeast China. Factor analysis identifies five factors which account for 79.65 % of the total variance in the dataset. Four factors bearing specific meanings as the river and groundwater hydrochemistry controlling processes are divided into two groups, the "natural hydrochemistry evolution" group and the "pollution" group. The "natural hydrochemistry evolution" group includes the salinity factor (factor 1) caused by rock weathering and the residence time factor (factor 2) reflecting the groundwater traveling time. The "pollution" group represents the groundwater quality deterioration due to geogenic pollution caused by elevated Fe and Mn (factor 3) and elevated nitrate (NO3 -) introduced by human activities such as agriculture exploitations (factor 5). The hydrochemical difference and hydraulic connection among rivers (surface water, SW), shallow groundwater (SG) and deep groundwater (DG) group are evaluated by the factor scores obtained from FA and DA (Fisher's method). It is showed that the river water is characterized as low salinity and slight pollution, and the shallow groundwater has the highest salinity and severe pollution. The SW is well separated from SG and DG by Fisher's discriminant function, but the SG and DG can not be well separated showing their hydrochemical similarities, and emphasize hydraulic connections between SG and DG.

Prognostic and survival analysis of 837 Chinese colorectal cancer patients.

PubMed

Yuan, Ying; Li, Mo-Dan; Hu, Han-Guang; Dong, Cai-Xia; Chen, Jia-Qi; Li, Xiao-Fen; Li, Jing-Jing; Shen, Hong

2013-05-07

To develop a prognostic model to predict survival of patients with colorectal cancer (CRC). Survival data of 837 CRC patients undergoing surgery between 1996 and 2006 were collected and analyzed by univariate analysis and Cox proportional hazard regression model to reveal the prognostic factors for CRC. All data were recorded using a standard data form and analyzed using SPSS version 18.0 (SPSS, Chicago, IL, United States). Survival curves were calculated by the Kaplan-Meier method. The log rank test was used to assess differences in survival. Univariate hazard ratios and significant and independent predictors of disease-specific survival and were identified by Cox proportional hazard analysis. The stepwise procedure was set to a threshold of 0.05. Statistical significance was defined as P < 0.05. The survival rate was 74% at 3 years and 68% at 5 years. The results of univariate analysis suggested age, preoperative obstruction, serum carcinoembryonic antigen level at diagnosis, status of resection, tumor size, histological grade, pathological type, lymphovascular invasion, invasion of adjacent organs, and tumor node metastasis (TNM) staging were positive prognostic factors (P < 0.05). Lymph node ratio (LNR) was also a strong prognostic factor in stage III CRC (P < 0.0001). We divided 341 stage III patients into three groups according to LNR values (LNR1, LNR ≤ 0.33, n = 211; LNR2, LNR 0.34-0.66, n = 76; and LNR3, LNR ≥ 0.67, n = 54). Univariate analysis showed a significant statistical difference in 3-year survival among these groups: LNR1, 73%; LNR2, 55%; and LNR3, 42% (P < 0.0001). The multivariate analysis results showed that histological grade, depth of bowel wall invasion, and number of metastatic lymph nodes were the most important prognostic factors for CRC if we did not consider the interaction of the TNM staging system (P < 0.05). When the TNM staging was taken into account, histological grade lost its statistical significance, while the specific TNM staging system showed a statistically significant difference (P < 0.0001). The overall survival of CRC patients has improved between 1996 and 2006. LNR is a powerful factor for estimating the survival of stage III CRC patients.

Evolution of statistical properties for a nonlinearly propagating sinusoid.

PubMed

Shepherd, Micah R; Gee, Kent L; Hanford, Amanda D

2011-07-01

The nonlinear propagation of a pure sinusoid is considered using time domain statistics. The probability density function, standard deviation, skewness, kurtosis, and crest factor are computed for both the amplitude and amplitude time derivatives as a function of distance. The amplitude statistics vary only in the postshock realm, while the amplitude derivative statistics vary rapidly in the preshock realm. The statistical analysis also suggests that the sawtooth onset distance can be considered to be earlier than previously realized. © 2011 Acoustical Society of America

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

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

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

1959-07-01

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

A Statistical Analysis Plan to Support the Joint Forward Area Air Defense Test.

DTIC Science & Technology

1984-08-02

hy estahlishing a specific significance level prior to performing the statistical test (traditionally a levels are set at .01 or .05). What is often...undesirable increase in 8. For constant a levels , the power (I - 8) of a statistical test can he increased by Increasing the sample size of the test. fRef...ANOVA Iparison Test on MOP I=--ferences Exist AmongF "Upon MOP "A" Factor I "A" Factor I 1MOP " A " Levels ? I . I I I _ _ ________ IPerform k-Sample Com- I

Augmenting Latent Dirichlet Allocation and Rank Threshold Detection with Ontologies

DTIC Science & Technology

2010-03-01

Probabilistic Latent Semantic Indexing (PLSI) is an automated indexing information retrieval model [20]. It is based on a statistical latent class model which is...uses a statistical foundation that is more accurate in finding hidden semantic relationships [20]. The model uses factor analysis of count data, number...principle of statistical infer- ence which asserts that all of the information in a sample is contained in the likelihood function [20]. The statistical

Meta-analysis of neutropenia or leukopenia as a prognostic factor in patients with malignant disease undergoing chemotherapy.

PubMed

Shitara, Kohei; Matsuo, Keitaro; Oze, Isao; Mizota, Ayako; Kondo, Chihiro; Nomura, Motoo; Yokota, Tomoya; Takahari, Daisuke; Ura, Takashi; Muro, Kei

2011-08-01

We performed a systematic review and meta-analysis to determine the impact of neutropenia or leukopenia experienced during chemotherapy on survival. Eligible studies included prospective or retrospective analyses that evaluated neutropenia or leukopenia as a prognostic factor for overall survival or disease-free survival. Statistical analyses were conducted to calculate a summary hazard ratio and 95% confidence interval (CI) using random-effects or fixed-effects models based on the heterogeneity of the included studies. Thirteen trials were selected for the meta-analysis, with a total of 9,528 patients. The hazard ratio of death was 0.69 (95% CI, 0.64-0.75) for patients with higher-grade neutropenia or leukopenia compared to patients with lower-grade or lack of cytopenia. Our analysis was also stratified by statistical method (any statistical method to decrease lead-time bias; time-varying analysis or landmark analysis), but no differences were observed. Our results indicate that neutropenia or leukopenia experienced during chemotherapy is associated with improved survival in patients with advanced cancer or hematological malignancies undergoing chemotherapy. Future prospective analyses designed to investigate the potential impact of chemotherapy dose adjustment coupled with monitoring of neutropenia or leukopenia on survival are warranted.

Classification Techniques for Multivariate Data Analysis.

DTIC Science & Technology

1980-03-28

analysis among biologists, botanists, and ecologists, while some social scientists may refer "typology". Other frequently encountered terms are pattern...the determinantal equation: lB -XW 0 (42) 49 The solutions X. are the eigenvalues of the matrix W-1 B 1 as in discriminant analysis. There are t non...Statistical Package for Social Sciences (SPSS) (14) subprogram FACTOR was used for the principal components analysis. It is designed both for the factor

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

PubMed

Kratochwill, Thomas R; Levin, Joel R

2014-04-01

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

Social inequalities in alcohol consumption in the Czech Republic: a multilevel analysis.

PubMed

Dzúrová, Dagmara; Spilková, Jana; Pikhart, Hynek

2010-05-01

Czech Republic traditionally ranks among the countries with the highest alcohol, consumption. This paper examines both risk and protective factors for frequent of alcohol, consumption in the Czech population using multilevel analysis. Risk factors were measured at the, individual level and at the area level. The individual-level data were obtained from a survey for a, sample of 3526 respondents aged 18-64 years. The area-level data were obtained from the Czech, Statistical Office. The group most inclinable to risk alcohol consumption and binge drinking are mainly, men, who live as single, with low education and also unemployed. Only the variable for divorce rate, showed statistical significance at both levels, thus the individual and the aggregated one. No cross-level interactions were found to be statistically significant. Copyright 2010 Elsevier Ltd. All rights reserved.

Combine bivariate statistics analysis and multivariate statistics analysis to assess landslide susceptibility in Chen-Yu-Lan watershed, Nantou, Taiwan.

NASA Astrophysics Data System (ADS)

Ngan Nguyen, Thi To; Liu, Cheng-Chien

2013-04-01

How landslides occurred and which factors triggered and sped up landslide occurrences were usually asked by researchers in the past decades. Many investigations carried out in many places in the world to finding out methods that predict and prevent damages from landslides phenomena. Chen-Yu-Lan River watershed is reputed as a 'hot pot' of landslide researches in Taiwan by its complicated geological structures with the significant tectonic fault systems and steeply mountainous terrain. Beside annual high precipitation concentration and the abrupt slopes, some natural disaster, as typhoons (Sinlaku-2008, Kalmaegi-2008, and Marakot-2009) and earthquake (Chi-Chi earthquake-1999) are also the triggered factors cause landslides with serious damages in this place. This research expresses the quantitative approaches to generate landslide susceptible map for Chen-Yu-Lan watershed, a mountainous area in the central Taiwan. Landslide inventories data, which were detected from the Formosat-2 imageries for eight years from 2004 to 2011, were applied to carry out landslide susceptibility mapping. Bivariate statistics analysis and multivariate statistics analysis would be applied to calculate susceptible index of landslides. The weights of parameters were computed based on landslide data for eight years from 2004 to 2011. To validate effective levels of factors to landslide occurrences, this method built some multivariate algorithms and compared these results with real landslide occurrences. Besides this method, the historical data of landslides were also used to assess and classify landslide susceptibility levels. From long-term landslide data, relation between landslide susceptibility levels and landslide repetition was assigned. The results demonstrated differently effective levels of potential factors, such as, slope gradient, drainage density, lithology and land use to landslide phenomena. The results also showed logical relationship between weights and characteristics of factors' classes. Depending on these results be able to help planning managers localize the high risk areas of landslide or safely areas by building and human activities.

Association factor analysis between osteoporosis with cerebral artery disease: The STROBE study.

PubMed

Jin, Eun-Sun; Jeong, Je Hoon; Lee, Bora; Im, Soo Bin

2017-03-01

The purpose of this study was to determine the clinical association factors between osteoporosis and cerebral artery disease in Korean population. Two hundred nineteen postmenopausal women and men undergoing cerebral computed tomography angiography were enrolled in this study to evaluate the cerebral artery disease by cross-sectional study. Cerebral artery disease was diagnosed if there was narrowing of 50% higher diameter in one or more cerebral vessel artery or presence of vascular calcification. History of osteoporotic fracture was assessed using medical record, and radiographic data such as simple radiography, MRI, and bone scan. Bone mineral density was checked by dual-energy x-ray absorptiometry. We reviewed clinical characteristics in all patients and also performed subgroup analysis for total or extracranial/ intracranial cerebral artery disease group retrospectively. We performed statistical analysis by means of chi-square test or Fisher's exact test for categorical variables and Student's t-test or Wilcoxon's rank sum test for continuous variables. We also used univariate and multivariate logistic regression analyses were conducted to assess the factors associated with the prevalence of cerebral artery disease. A two-tailed p-value of less than 0.05 was considered as statistically significant. All statistical analyses were performed using R (version 3.1.3; The R Foundation for Statistical Computing, Vienna, Austria) and SPSS (version 14.0; SPSS, Inc, Chicago, Ill, USA). Of the 219 patients, 142 had cerebral artery disease. All vertebral fracture was observed in 29 (13.24%) patients. There was significant difference in hip fracture according to the presence or absence of cerebral artery disease. In logistic regression analysis, osteoporotic hip fracture was significantly associated with extracranial cerebral artery disease after adjusting for multiple risk factors. Females with osteoporotic hip fracture were associated with total calcified cerebral artery disease. Some clinical factors such as age, hypertension, and osteoporotic hip fracture, smoking history and anti-osteoporosis drug use were associated with cerebral artery disease.

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

PubMed

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

2016-08-17

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

Chemometrics.

ERIC Educational Resources Information Center

Delaney, Michael F.

1984-01-01

This literature review on chemometrics (covering December 1981 to December 1983) is organized under these headings: personal supermicrocomputers; education and books; statistics; modeling and parameter estimation; resolution; calibration; signal processing; image analysis; factor analysis; pattern recognition; optimization; artificial…

The Design and Analysis of Transposon-Insertion Sequencing Experiments

PubMed Central

Chao, Michael C.; Abel, Sören; Davis, Brigid M.; Waldor, Matthew K.

2016-01-01

Preface Transposon-insertion sequencing (TIS) is a powerful approach that can be widely applied to genome-wide definition of loci that are required for growth in diverse conditions. However, experimental design choices and stochastic biological processes can heavily influence the results of TIS experiments and affect downstream statistical analysis. Here, we discuss TIS experimental parameters and how these factors relate to the benefits and limitations of the various statistical frameworks that can be applied to computational analysis of TIS data. PMID:26775926

Outbreak of resistant Acinetobacter baumannii- measures and proposal for prevention and control.

PubMed

Romanelli, Roberta Maia de Castro; Jesus, Lenize Adriana de; Clemente, Wanessa Trindade; Lima, Stella Sala Soares; Rezende, Edna Maria; Coutinho, Rosane Luiza; Moreira, Ricardo Luiz Fontes; Neves, Francelli Aparecida Cordeiro; Brás, Nelma de Jesus

2009-10-01

Acinetobacter baumannii colonization and infection, frequent in Intensive Care Unit (ICU) patients, is commonly associated with high morbimortality. Several outbreaks due to multidrug-resistant (MDR) A. baumanii have been reported but few of them in Brazil. This study aimed to identify risk factors associated with colonization and infection by MDR and carbapenem-resistant A. baumannii strains isolated from patients admitted to the adult ICU at HC/UFMG. A case-control study was performed from January 2007 to June 2008. Cases were defined as patients colonized or infected by MDR/carbapenem-resistant A. baumannii, and controls were patients without MDR/carbapenem-resistant A. baumannii isolation, in a 1:2 proportion. For statistical analysis, due to changes in infection control guidelines, infection criteria and the notification process, this study was divided into two periods. During the first period analyzed, from January to December 2007, colonization or infection by MDR/carbapenem-resistant A. baumannii was associated with prior infection, invasive device utilization, prior carbapenem use and clinical severity. In the multivariate analysis, prior infection and mechanical ventilation proved to be statistically significant risk factors. Carbapenem use showed a tendency towards a statistical association. During the second study period, from January to June 2008, variables with a significant association with MDR/carbapenem-resistant A. baumannii colonization/infection were catheter utilization, carbapenem and third-generation cephalosporin use, hepatic transplantation, and clinical severity. In the multivariate analysis, only CVC use showed a statistical difference. Carbapenem and third-generation cephalosporin use displayed a tendency to be risk factors. Risk factors must be focused on infection control and prevention measures considering A. baumanni dissemination.

Groundwater flow and hydrogeochemical evolution in the Jianghan Plain, central China

NASA Astrophysics Data System (ADS)

Gan, Yiqun; Zhao, Ke; Deng, Yamin; Liang, Xing; Ma, Teng; Wang, Yanxin

2018-05-01

Hydrogeochemical analysis and multivariate statistics were applied to identify flow patterns and major processes controlling the hydrogeochemistry of groundwater in the Jianghan Plain, which is located in central Yangtze River Basin (central China) and characterized by intensive surface-water/groundwater interaction. Although HCO3-Ca-(Mg) type water predominated in the study area, the 457 (21 surface water and 436 groundwater) samples were effectively classified into five clusters by hierarchical cluster analysis. The hydrochemical variations among these clusters were governed by three factors from factor analysis. Major components (e.g., Ca, Mg and HCO3) in surface water and groundwater originated from carbonate and silicate weathering (factor 1). Redox conditions (factor 2) influenced the geogenic Fe and As contamination in shallow confined groundwater. Anthropogenic activities (factor 3) primarily caused high levels of Cl and SO4 in surface water and phreatic groundwater. Furthermore, the factor score 1 of samples in the shallow confined aquifer gradually increased along the flow paths. This study demonstrates that enhanced information on hydrochemistry in complex groundwater flow systems, by multivariate statistical methods, improves the understanding of groundwater flow and hydrogeochemical evolution due to natural and anthropogenic impacts.

Confirmatory Factor Analysis of Persian Adaptation of Multidimensional Students' Life Satisfaction Scale (MSLSS)

ERIC Educational Resources Information Center

Hatami, Gissou; Motamed, Niloofar; Ashrafzadeh, Mahshid

2010-01-01

Validity and reliability of Persian adaptation of MSLSS in the 12-18 years, middle and high school students (430 students in grades 6-12 in Bushehr port, Iran) using confirmatory factor analysis by means of LISREL statistical package were checked. Internal consistency reliability estimates (Cronbach's coefficient [alpha]) were all above the…

An Analysis of Construction Contractor Performance Evaluation System

DTIC Science & Technology

2009-03-01

65 8. Summary of Determinant and KMO Values for Finalized...principle component analysis output is the KMO and Bartlett‘s Test. KMO or Kaiser-Meyer-Olkin measure of sampling adequacy is used to identify if a...set of variables, when factored together, yield distinct and reliable factors (Field, 2005). KMO statistics vary between values of 0 to 1. Kaiser

The Effect of Missing Data Handling Methods on Goodness of Fit Indices in Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Köse, Alper

2014-01-01

The primary objective of this study was to examine the effect of missing data on goodness of fit statistics in confirmatory factor analysis (CFA). For this aim, four missing data handling methods; listwise deletion, full information maximum likelihood, regression imputation and expectation maximization (EM) imputation were examined in terms of…

Factors Affecting the Mental Development of Very Low Birthweight Infants: An Evaluation Based Primarily on Covariance Structure Analysis.

ERIC Educational Resources Information Center

Honjo, Shuji; And Others

1998-01-01

Evaluated statistically the effect of intranatal and early postnatal period factors on mental development of very low-birth-weight infants. Covariance structure analysis revealed direct influence of birth weight and gestational age in weeks on mental development at age 1, and of opthalmological aberrations and respirator disorder on mental…

Using Multi-Group Confirmatory Factor Analysis to Evaluate Cross-Cultural Research: Identifying and Understanding Non-Invariance

ERIC Educational Resources Information Center

Brown, Gavin T. L.; Harris, Lois R.; O'Quin, Chrissie; Lane, Kenneth E.

2017-01-01

Multi-group confirmatory factor analysis (MGCFA) allows researchers to determine whether a research inventory elicits similar response patterns across samples. If statistical equivalence in responding is found, then scale score comparisons become possible and samples can be said to be from the same population. This paper illustrates the use of…

Crash analysis, statistics & information notebook 2008

DOT National Transportation Integrated Search

2008-01-01

Traditionally crash data is often presented as single fact sheets highlighting a single factor such as Vehicle Type or Road Type. This document will try to show how the risk factors interrelate to produce a crash. Complete detailed analys...

Investigation of trends in flooding in the Tug Fork basin of Kentucky, Virginia, and West Virginia

USGS Publications Warehouse

Hirsch, Robert M.; Scott, Arthur G.; Wyant, Timothy

1982-01-01

Statistical analysis indicates that the average size of annual-flood peaks of the Tug Fork (Ky., Va., and W. Va.) has been increasing. However, additional statistical analysis does not indicate that the flood levels that were exceeded typically once or twice a year in the period 1947-79 are any more likely to be exceeded now than in 1947. Possible trends in streamchannel size also are investigated at three locations. No discernible trends in channel size are noted. Further statistical analysis of the trend in the size of annual-flood peaks shows that much of the annual variation is related to local rainfall and to the 'natural' hydrologic response in a relatively undisturbed subbasin. However, some statistical indication of trend persists after accounting for these natural factors, though it is of borderline statistical significance. Further study in the basin may relate flood magnitudes to both rainfall and to land use.

Multiple Statistical Models Based Analysis of Causative Factors and Loess Landslides in Tianshui City, China

NASA Astrophysics Data System (ADS)

Su, Xing; Meng, Xingmin; Ye, Weilin; Wu, Weijiang; Liu, Xingrong; Wei, Wanhong

2018-03-01

Tianshui City is one of the mountainous cities that are threatened by severe geo-hazards in Gansu Province, China. Statistical probability models have been widely used in analyzing and evaluating geo-hazards such as landslide. In this research, three approaches (Certainty Factor Method, Weight of Evidence Method and Information Quantity Method) were adopted to quantitively analyze the relationship between the causative factors and the landslides, respectively. The source data used in this study are including the SRTM DEM and local geological maps in the scale of 1:200,000. 12 causative factors (i.e., altitude, slope, aspect, curvature, plan curvature, profile curvature, roughness, relief amplitude, and distance to rivers, distance to faults, distance to roads, and the stratum lithology) were selected to do correlation analysis after thorough investigation of geological conditions and historical landslides. The results indicate that the outcomes of the three models are fairly consistent.

Tools for Basic Statistical Analysis

NASA Technical Reports Server (NTRS)

Luz, Paul L.

2005-01-01

Statistical Analysis Toolset is a collection of eight Microsoft Excel spreadsheet programs, each of which performs calculations pertaining to an aspect of statistical analysis. These programs present input and output data in user-friendly, menu-driven formats, with automatic execution. The following types of calculations are performed: Descriptive statistics are computed for a set of data x(i) (i = 1, 2, 3 . . . ) entered by the user. Normal Distribution Estimates will calculate the statistical value that corresponds to cumulative probability values, given a sample mean and standard deviation of the normal distribution. Normal Distribution from two Data Points will extend and generate a cumulative normal distribution for the user, given two data points and their associated probability values. Two programs perform two-way analysis of variance (ANOVA) with no replication or generalized ANOVA for two factors with four levels and three repetitions. Linear Regression-ANOVA will curvefit data to the linear equation y=f(x) and will do an ANOVA to check its significance.

The Warning System in Disaster Situations: A Selective Analysis.

DTIC Science & Technology

DISASTERS, *WARNING SYSTEMS), CIVIL DEFENSE, SOCIAL PSYCHOLOGY, REACTION(PSYCHOLOGY), FACTOR ANALYSIS, CLASSIFICATION, STATISTICAL DATA, TIME ... MANAGEMENT PLANNING AND CONTROL, DAMAGE, CONTROL SYSTEMS, THREAT EVALUATION, DECISION MAKING, DATA PROCESSING, COMMUNICATION SYSTEMS, NUCLEAR EXPLOSIONS

Statistical tables and charts showing geochemical variation in the Mesoproterozoic Big Creek, Apple Creek, and Gunsight formations, Lemhi group, Salmon River Mountains and Lemhi Range, central Idaho

USGS Publications Warehouse

Lindsey, David A.; Tysdal, Russell G.; Taggart, Joseph E.

2002-01-01

The principal purpose of this report is to provide a reference archive for results of a statistical analysis of geochemical data for metasedimentary rocks of Mesoproterozoic age of the Salmon River Mountains and Lemhi Range, central Idaho. Descriptions of geochemical data sets, statistical methods, rationale for interpretations, and references to the literature are provided. Three methods of analysis are used: R-mode factor analysis of major oxide and trace element data for identifying petrochemical processes, analysis of variance for effects of rock type and stratigraphic position on chemical composition, and major-oxide ratio plots for comparison with the chemical composition of common clastic sedimentary rocks.

GIS and statistical analysis for landslide susceptibility mapping in the Daunia area, Italy

NASA Astrophysics Data System (ADS)

Mancini, F.; Ceppi, C.; Ritrovato, G.

2010-09-01

This study focuses on landslide susceptibility mapping in the Daunia area (Apulian Apennines, Italy) and achieves this by using a multivariate statistical method and data processing in a Geographical Information System (GIS). The Logistic Regression (hereafter LR) method was chosen to produce a susceptibility map over an area of 130 000 ha where small settlements are historically threatened by landslide phenomena. By means of LR analysis, the tendency to landslide occurrences was, therefore, assessed by relating a landslide inventory (dependent variable) to a series of causal factors (independent variables) which were managed in the GIS, while the statistical analyses were performed by means of the SPSS (Statistical Package for the Social Sciences) software. The LR analysis produced a reliable susceptibility map of the investigated area and the probability level of landslide occurrence was ranked in four classes. The overall performance achieved by the LR analysis was assessed by local comparison between the expected susceptibility and an independent dataset extrapolated from the landslide inventory. Of the samples classified as susceptible to landslide occurrences, 85% correspond to areas where landslide phenomena have actually occurred. In addition, the consideration of the regression coefficients provided by the analysis demonstrated that a major role is played by the "land cover" and "lithology" causal factors in determining the occurrence and distribution of landslide phenomena in the Apulian Apennines.

Using Quality Management Tools to Enhance Feedback from Student Evaluations

ERIC Educational Resources Information Center

Jensen, John B.; Artz, Nancy

2005-01-01

Statistical tools found in the service quality assessment literature--the "T"[superscript 2] statistic combined with factor analysis--can enhance the feedback instructors receive from student ratings. "T"[superscript 2] examines variability across multiple sets of ratings to isolate individual respondents with aberrant response…

Analysis of Developmental Data: Comparison Among Alternative Methods

ERIC Educational Resources Information Center

Wilson, Ronald S.

1975-01-01

To examine the ability of the correction factor epsilon to counteract statistical bias in univariate analysis, an analysis of variance (adjusted by epsilon) and a multivariate analysis of variance were performed on the same data. The results indicated that univariate analysis is a fully protected design when used with epsilon. (JMB)

Clusters in the distribution of pulsars in period, pulse-width, and age. [statistical analysis/statistical distributions

NASA Technical Reports Server (NTRS)

Baker, K. B.; Sturrock, P. A.

1975-01-01

The question of whether pulsars form a single group or whether pulsars come in two or more different groups is discussed. It is proposed that such groups might be related to several factors such as the initial creation of the neutron star, or the orientation of the magnetic field axis with the spin axis. Various statistical models are examined.

Statistical analysis of microgravity experiment performance using the degrees of success scale

NASA Technical Reports Server (NTRS)

Upshaw, Bernadette; Liou, Ying-Hsin Andrew; Morilak, Daniel P.

1994-01-01

This paper describes an approach to identify factors that significantly influence microgravity experiment performance. Investigators developed the 'degrees of success' scale to provide a numerical representation of success. A degree of success was assigned to 293 microgravity experiments. Experiment information including the degree of success rankings and factors for analysis was compiled into a database. Through an analysis of variance, nine significant factors in microgravity experiment performance were identified. The frequencies of these factors are presented along with the average degree of success at each level. A preliminary discussion of the relationship between the significant factors and the degree of success is presented.

Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis.

PubMed

Flores, X; Comas, J; Roda, I R; Jiménez, L; Gernaey, K V

2007-01-01

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.

Statistical Analysis of Zebrafish Locomotor Response.

PubMed

Liu, Yiwen; Carmer, Robert; Zhang, Gaonan; Venkatraman, Prahatha; Brown, Skye Ashton; Pang, Chi-Pui; Zhang, Mingzhi; Ma, Ping; Leung, Yuk Fai

2015-01-01

Zebrafish larvae display rich locomotor behaviour upon external stimulation. The movement can be simultaneously tracked from many larvae arranged in multi-well plates. The resulting time-series locomotor data have been used to reveal new insights into neurobiology and pharmacology. However, the data are of large scale, and the corresponding locomotor behavior is affected by multiple factors. These issues pose a statistical challenge for comparing larval activities. To address this gap, this study has analyzed a visually-driven locomotor behaviour named the visual motor response (VMR) by the Hotelling's T-squared test. This test is congruent with comparing locomotor profiles from a time period. Different wild-type (WT) strains were compared using the test, which shows that they responded differently to light change at different developmental stages. The performance of this test was evaluated by a power analysis, which shows that the test was sensitive for detecting differences between experimental groups with sample numbers that were commonly used in various studies. In addition, this study investigated the effects of various factors that might affect the VMR by multivariate analysis of variance (MANOVA). The results indicate that the larval activity was generally affected by stage, light stimulus, their interaction, and location in the plate. Nonetheless, different factors affected larval activity differently over time, as indicated by a dynamical analysis of the activity at each second. Intriguingly, this analysis also shows that biological and technical repeats had negligible effect on larval activity. This finding is consistent with that from the Hotelling's T-squared test, and suggests that experimental repeats can be combined to enhance statistical power. Together, these investigations have established a statistical framework for analyzing VMR data, a framework that should be generally applicable to other locomotor data with similar structure.

Statistical Analysis of Zebrafish Locomotor Response

PubMed Central

Zhang, Gaonan; Venkatraman, Prahatha; Brown, Skye Ashton; Pang, Chi-Pui; Zhang, Mingzhi; Ma, Ping; Leung, Yuk Fai

2015-01-01

Zebrafish larvae display rich locomotor behaviour upon external stimulation. The movement can be simultaneously tracked from many larvae arranged in multi-well plates. The resulting time-series locomotor data have been used to reveal new insights into neurobiology and pharmacology. However, the data are of large scale, and the corresponding locomotor behavior is affected by multiple factors. These issues pose a statistical challenge for comparing larval activities. To address this gap, this study has analyzed a visually-driven locomotor behaviour named the visual motor response (VMR) by the Hotelling’s T-squared test. This test is congruent with comparing locomotor profiles from a time period. Different wild-type (WT) strains were compared using the test, which shows that they responded differently to light change at different developmental stages. The performance of this test was evaluated by a power analysis, which shows that the test was sensitive for detecting differences between experimental groups with sample numbers that were commonly used in various studies. In addition, this study investigated the effects of various factors that might affect the VMR by multivariate analysis of variance (MANOVA). The results indicate that the larval activity was generally affected by stage, light stimulus, their interaction, and location in the plate. Nonetheless, different factors affected larval activity differently over time, as indicated by a dynamical analysis of the activity at each second. Intriguingly, this analysis also shows that biological and technical repeats had negligible effect on larval activity. This finding is consistent with that from the Hotelling’s T-squared test, and suggests that experimental repeats can be combined to enhance statistical power. Together, these investigations have established a statistical framework for analyzing VMR data, a framework that should be generally applicable to other locomotor data with similar structure. PMID:26437184

Statistically derived factors of varied importance to audiologists when making a hearing aid brand preference decision.

PubMed

Johnson, Earl E; Mueller, H Gustav; Ricketts, Todd A

2009-01-01

To determine the amount of importance audiologists place on various items related to their selection of a preferred hearing aid brand manufacturer. Three hundred forty-three hearing aid-dispensing audiologists rated a total of 32 randomized items by survey methodology. Principle component analysis identified seven orthogonal statistical factors of importance. In rank order, these factors were Aptitude of the Brand, Image, Cost, Sales and Speed of Delivery, Exposure, Colleague Recommendations, and Contracts and Incentives. While it was hypothesized that differences among audiologists in the importance ratings of these factors would dictate their preference for a given brand, that was not our finding. Specifically, mean ratings for the six most important factors did not differ among audiologists preferring different brands. A statistically significant difference among audiologists preferring different brands was present, however, for one factor: Contracts and Incentives. Its assigned importance, though, was always lower than that for the other six factors. Although most audiologists have a preferred hearing aid brand, differences in the perceived importance of common factors attributed to brands do not largely determine preference for a particular brand.

[Statistical analysis of German radiologic periodicals: developmental trends in the last 10 years].

PubMed

Golder, W

1999-09-01

To identify which statistical tests are applied in German radiological publications, to what extent their use has changed during the last decade, and which factors might be responsible for this development. The major articles published in "ROFO" and "DER RADIOLOGE" during 1988, 1993 and 1998 were reviewed for statistical content. The contributions were classified by principal focus and radiological subspecialty. The methods used were assigned to descriptive, basal and advanced statistics. Sample size, significance level and power were established. The use of experts' assistance was monitored. Finally, we calculated the so-called cumulative accessibility of the publications. 525 contributions were found to be eligible. In 1988, 87% used descriptive statistics only, 12.5% basal, and 0.5% advanced statistics. The corresponding figures in 1993 and 1998 are 62 and 49%, 32 and 41%, and 6 and 10%, respectively. Statistical techniques were most likely to be used in research on musculoskeletal imaging and articles dedicated to MRI. Six basic categories of statistical methods account for the complete statistical analysis appearing in 90% of the articles. ROC analysis is the single most common advanced technique. Authors make increasingly use of statistical experts' opinion and programs. During the last decade, the use of statistical methods in German radiological journals has fundamentally improved, both quantitatively and qualitatively. Presently, advanced techniques account for 20% of the pertinent statistical tests. This development seems to be promoted by the increasing availability of statistical analysis software.

Digital immunohistochemistry platform for the staining variation monitoring based on integration of image and statistical analyses with laboratory information system.

PubMed

Laurinaviciene, Aida; Plancoulaine, Benoit; Baltrusaityte, Indra; Meskauskas, Raimundas; Besusparis, Justinas; Lesciute-Krilaviciene, Daiva; Raudeliunas, Darius; Iqbal, Yasir; Herlin, Paulette; Laurinavicius, Arvydas

2014-01-01

Digital immunohistochemistry (IHC) is one of the most promising applications brought by new generation image analysis (IA). While conventional IHC staining quality is monitored by semi-quantitative visual evaluation of tissue controls, IA may require more sensitive measurement. We designed an automated system to digitally monitor IHC multi-tissue controls, based on SQL-level integration of laboratory information system with image and statistical analysis tools. Consecutive sections of TMA containing 10 cores of breast cancer tissue were used as tissue controls in routine Ki67 IHC testing. Ventana slide label barcode ID was sent to the LIS to register the serial section sequence. The slides were stained and scanned (Aperio ScanScope XT), IA was performed by the Aperio/Leica Colocalization and Genie Classifier/Nuclear algorithms. SQL-based integration ensured automated statistical analysis of the IA data by the SAS Enterprise Guide project. Factor analysis and plot visualizations were performed to explore slide-to-slide variation of the Ki67 IHC staining results in the control tissue. Slide-to-slide intra-core IHC staining analysis revealed rather significant variation of the variables reflecting the sample size, while Brown and Blue Intensity were relatively stable. To further investigate this variation, the IA results from the 10 cores were aggregated to minimize tissue-related variance. Factor analysis revealed association between the variables reflecting the sample size detected by IA and Blue Intensity. Since the main feature to be extracted from the tissue controls was staining intensity, we further explored the variation of the intensity variables in the individual cores. MeanBrownBlue Intensity ((Brown+Blue)/2) and DiffBrownBlue Intensity (Brown-Blue) were introduced to better contrast the absolute intensity and the colour balance variation in each core; relevant factor scores were extracted. Finally, tissue-related factors of IHC staining variance were explored in the individual tissue cores. Our solution enabled to monitor staining of IHC multi-tissue controls by the means of IA, followed by automated statistical analysis, integrated into the laboratory workflow. We found that, even in consecutive serial tissue sections, tissue-related factors affected the IHC IA results; meanwhile, less intense blue counterstain was associated with less amount of tissue, detected by the IA tools.

Digital immunohistochemistry platform for the staining variation monitoring based on integration of image and statistical analyses with laboratory information system

PubMed Central

2014-01-01

Background Digital immunohistochemistry (IHC) is one of the most promising applications brought by new generation image analysis (IA). While conventional IHC staining quality is monitored by semi-quantitative visual evaluation of tissue controls, IA may require more sensitive measurement. We designed an automated system to digitally monitor IHC multi-tissue controls, based on SQL-level integration of laboratory information system with image and statistical analysis tools. Methods Consecutive sections of TMA containing 10 cores of breast cancer tissue were used as tissue controls in routine Ki67 IHC testing. Ventana slide label barcode ID was sent to the LIS to register the serial section sequence. The slides were stained and scanned (Aperio ScanScope XT), IA was performed by the Aperio/Leica Colocalization and Genie Classifier/Nuclear algorithms. SQL-based integration ensured automated statistical analysis of the IA data by the SAS Enterprise Guide project. Factor analysis and plot visualizations were performed to explore slide-to-slide variation of the Ki67 IHC staining results in the control tissue. Results Slide-to-slide intra-core IHC staining analysis revealed rather significant variation of the variables reflecting the sample size, while Brown and Blue Intensity were relatively stable. To further investigate this variation, the IA results from the 10 cores were aggregated to minimize tissue-related variance. Factor analysis revealed association between the variables reflecting the sample size detected by IA and Blue Intensity. Since the main feature to be extracted from the tissue controls was staining intensity, we further explored the variation of the intensity variables in the individual cores. MeanBrownBlue Intensity ((Brown+Blue)/2) and DiffBrownBlue Intensity (Brown-Blue) were introduced to better contrast the absolute intensity and the colour balance variation in each core; relevant factor scores were extracted. Finally, tissue-related factors of IHC staining variance were explored in the individual tissue cores. Conclusions Our solution enabled to monitor staining of IHC multi-tissue controls by the means of IA, followed by automated statistical analysis, integrated into the laboratory workflow. We found that, even in consecutive serial tissue sections, tissue-related factors affected the IHC IA results; meanwhile, less intense blue counterstain was associated with less amount of tissue, detected by the IA tools. PMID:25565007

Oral cancer associated with chronic mechanical irritation of the oral mucosa.

PubMed

Piemonte, E; Lazos, J; Belardinelli, P; Secchi, D; Brunotto, M; Lanfranchi-Tizeira, H

2018-03-01

Most of the studies dealing with Chronic Mechanical Irritation (CMI) and Oral Cancer (OC) only considered prosthetic and dental variables separately, and CMI functional factors are not registered. Thus, the aim of this study was to assess OC risk in individuals with dental, prosthetic and functional CMI. Also, we examined CMI presence in relation to tumor size. A case-control study was carried out from 2009 to 2013. Study group were squamous cell carcinoma cases; control group was patients seeking dental treatment in the same institution. 153 patients were studied (Study group n=53, Control group n=100). CMI reproducibility displayed a correlation coefficient of 1 (p<0.0001). Bivariate analysis showed statistically significant associations for all variables (age, gender, tobacco and alcohol consumption and CMI). Multivariate analysis exhibited statistical significance for age, alcohol, and CMI, but not for gender or tobacco. Relationship of CMI with tumor size showed no statistically significant differences. CMI could be regarded as a risk factor for oral cancer. In individuals with other OC risk factors, proper treatment of the mechanical injuring factors (dental, prosthetic and functional) could be an important measure to reduce the risk of oral cancer.

Spatial diffusion of influenza outbreak-related climate factors in Chiang Mai Province, Thailand.

PubMed

Nakapan, Supachai; Tripathi, Nitin Kumar; Tipdecho, Taravudh; Souris, Marc

2012-10-24

Influenza is one of the most important leading causes of respiratory illness in the countries located in the tropical areas of South East Asia and Thailand. In this study the climate factors associated with influenza incidence in Chiang Mai Province, Northern Thailand, were investigated. Identification of factors responsible for influenza outbreaks and the mapping of potential risk areas in Chiang Mai are long overdue. This work examines the association between yearly climate patterns between 2001 and 2008 and influenza outbreaks in the Chiang Mai Province. The climatic factors included the amount of rainfall, percent of rainy days, relative humidity, maximum, minimum temperatures and temperature difference. The study develops a statistical analysis to quantitatively assess the relationship between climate and influenza outbreaks and then evaluate its suitability for predicting influenza outbreaks. A multiple linear regression technique was used to fit the statistical model. The Inverse Distance Weighted (IDW) interpolation and Geographic Information System (GIS) techniques were used in mapping the spatial diffusion of influenza risk zones. The results show that there is a significance correlation between influenza outbreaks and climate factors for the majority of the studied area. A statistical analysis was conducted to assess the validity of the model comparing model outputs and actual outbreaks.

Confirmatory factor analytic structure and measurement invariance of quantitative autistic traits measured by the social responsiveness scale-2.

PubMed

Frazier, Thomas W; Ratliff, Kristin R; Gruber, Chris; Zhang, Yi; Law, Paul A; Constantino, John N

2014-01-01

Understanding the factor structure of autistic symptomatology is critical to the discovery and interpretation of causal mechanisms in autism spectrum disorder. We applied confirmatory factor analysis and assessment of measurement invariance to a large (N = 9635) accumulated collection of reports on quantitative autistic traits using the Social Responsiveness Scale, representing a broad diversity of age, severity, and reporter type. A two-factor structure (corresponding to social communication impairment and restricted, repetitive behavior) as elaborated in the updated Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5) criteria for autism spectrum disorder exhibited acceptable model fit in confirmatory factor analysis. Measurement invariance was appreciable across age, sex, and reporter (self vs other), but somewhat less apparent between clinical and nonclinical populations in this sample comprised of both familial and sporadic autism spectrum disorders. The statistical power afforded by this large sample allowed relative differentiation of three factors among items encompassing social communication impairment (emotion recognition, social avoidance, and interpersonal relatedness) and two factors among items encompassing restricted, repetitive behavior (insistence on sameness and repetitive mannerisms). Cross-trait correlations remained extremely high, that is, on the order of 0.66-0.92. These data clarify domains of statistically significant factoral separation that may relate to partially-but not completely-overlapping biological mechanisms, contributing to variation in human social competency. Given such robust intercorrelations among symptom domains, understanding their co-emergence remains a high priority in conceptualizing common neural mechanisms underlying autistic syndromes.

Perceived Nurse-Physician Communication in Patient Care and Associated Factors in Public Hospitals of Jimma Zone, South West Ethiopia: Cross Sectional Study.

PubMed

Hailu, Fikadu Balcha; Kassahun, Chanyalew Worku; Kerie, Mirkuzie Woldie

2016-01-01

Nurse-physician communication has been shown to have a significant impact on the job satisfaction and retention of staff. In areas where it has been studied, communication failure between nurses and physicians was found to be one of the leading causes of preventable patient injuries, complications, death and medical malpractice claims. The objective of this study is to determine perception of nurses and physicians towards nurse-physician communication in patient care and associated factors in public hospitals of Jimma zone, southwest Ethiopia. Institution based cross-sectional survey was conducted from March 10 to April 16, 2014 among 341 nurses and 168 physicians working in public hospitals in Jimma zone. Data was collected using a pre-tested self-administered questionnaire; entered into EpiData version 3.1 and exported to Statistical Package for Social Sciences (SPSS) version 16.0 for analysis. Factor analysis was carried out. Descriptive statistics, independent sample t-test, linear regression and one way analysis of variance were used. Variables with P-value < 0.05 were considered as statistically significant. The response rate of the study was 91.55%. The mean perceived nurse-physician communication scores were 50.88±19.7% for perceived professional respect and satisfaction, and 48.52±19.7% for perceived openness and sharing of patient information on nurse-physician communication. Age, salary and organizational factors were statistically significant predictors for perceived respect and satisfaction. Whereas sex, working hospital, work attitude individual factors and organizational factors were significant predictors of perceived openness and sharing of patient information in nurse-physician communication during patient care. Perceived level of nurse-physician communication mean score was low among nurses than physicians and it is attention seeking gap. Hence, the finding of our study suggests the need for developing and implementing nurse-physician communication improvement strategies to solve communication mishaps in patient care.

Perceived Nurse—Physician Communication in Patient Care and Associated Factors in Public Hospitals of Jimma Zone, South West Ethiopia: Cross Sectional Study

PubMed Central

Hailu, Fikadu Balcha; Kassahun, Chanyalew Worku; Kerie, Mirkuzie Woldie

2016-01-01

Background Nurse–physician communication has been shown to have a significant impact on the job satisfaction and retention of staff. In areas where it has been studied, communication failure between nurses and physicians was found to be one of the leading causes of preventable patient injuries, complications, death and medical malpractice claims. Objective The objective of this study is to determine perception of nurses and physicians towards nurse-physician communication in patient care and associated factors in public hospitals of Jimma zone, southwest Ethiopia. Methods Institution based cross-sectional survey was conducted from March 10 to April 16, 2014 among 341 nurses and 168 physicians working in public hospitals in Jimma zone. Data was collected using a pre-tested self-administered questionnaire; entered into EpiData version 3.1 and exported to Statistical Package for Social Sciences (SPSS) version 16.0 for analysis. Factor analysis was carried out. Descriptive statistics, independent sample t-test, linear regression and one way analysis of variance were used. Variables with P-value < 0.05 were considered as statistically significant. Results The response rate of the study was 91.55%. The mean perceived nurse-physician communication scores were 50.88±19.7% for perceived professional respect and satisfaction, and 48.52±19.7% for perceived openness and sharing of patient information on nurse-physician communication. Age, salary and organizational factors were statistically significant predictors for perceived respect and satisfaction. Whereas sex, working hospital, work attitude individual factors and organizational factors were significant predictors of perceived openness and sharing of patient information in nurse-physician communication during patient care. Conclusion Perceived level of nurse-physician communication mean score was low among nurses than physicians and it is attention seeking gap. Hence, the finding of our study suggests the need for developing and implementing nurse-physician communication improvement strategies to solve communication mishaps in patient care. PMID:27632162

The Content of Statistical Requirements for Authors in Biomedical Research Journals

PubMed Central

Liu, Tian-Yi; Cai, Si-Yu; Nie, Xiao-Lu; Lyu, Ya-Qi; Peng, Xiao-Xia; Feng, Guo-Shuang

2016-01-01

Background: Robust statistical designing, sound statistical analysis, and standardized presentation are important to enhance the quality and transparency of biomedical research. This systematic review was conducted to summarize the statistical reporting requirements introduced by biomedical research journals with an impact factor of 10 or above so that researchers are able to give statistical issues’ serious considerations not only at the stage of data analysis but also at the stage of methodological design. Methods: Detailed statistical instructions for authors were downloaded from the homepage of each of the included journals or obtained from the editors directly via email. Then, we described the types and numbers of statistical guidelines introduced by different press groups. Items of statistical reporting guideline as well as particular requirements were summarized in frequency, which were grouped into design, method of analysis, and presentation, respectively. Finally, updated statistical guidelines and particular requirements for improvement were summed up. Results: Totally, 21 of 23 press groups introduced at least one statistical guideline. More than half of press groups can update their statistical instruction for authors gradually relative to issues of new statistical reporting guidelines. In addition, 16 press groups, covering 44 journals, address particular statistical requirements. The most of the particular requirements focused on the performance of statistical analysis and transparency in statistical reporting, including “address issues relevant to research design, including participant flow diagram, eligibility criteria, and sample size estimation,” and “statistical methods and the reasons.” Conclusions: Statistical requirements for authors are becoming increasingly perfected. Statistical requirements for authors remind researchers that they should make sufficient consideration not only in regards to statistical methods during the research design, but also standardized statistical reporting, which would be beneficial in providing stronger evidence and making a greater critical appraisal of evidence more accessible. PMID:27748343

The Content of Statistical Requirements for Authors in Biomedical Research Journals.

PubMed

Liu, Tian-Yi; Cai, Si-Yu; Nie, Xiao-Lu; Lyu, Ya-Qi; Peng, Xiao-Xia; Feng, Guo-Shuang

2016-10-20

Robust statistical designing, sound statistical analysis, and standardized presentation are important to enhance the quality and transparency of biomedical research. This systematic review was conducted to summarize the statistical reporting requirements introduced by biomedical research journals with an impact factor of 10 or above so that researchers are able to give statistical issues' serious considerations not only at the stage of data analysis but also at the stage of methodological design. Detailed statistical instructions for authors were downloaded from the homepage of each of the included journals or obtained from the editors directly via email. Then, we described the types and numbers of statistical guidelines introduced by different press groups. Items of statistical reporting guideline as well as particular requirements were summarized in frequency, which were grouped into design, method of analysis, and presentation, respectively. Finally, updated statistical guidelines and particular requirements for improvement were summed up. Totally, 21 of 23 press groups introduced at least one statistical guideline. More than half of press groups can update their statistical instruction for authors gradually relative to issues of new statistical reporting guidelines. In addition, 16 press groups, covering 44 journals, address particular statistical requirements. The most of the particular requirements focused on the performance of statistical analysis and transparency in statistical reporting, including "address issues relevant to research design, including participant flow diagram, eligibility criteria, and sample size estimation," and "statistical methods and the reasons." Statistical requirements for authors are becoming increasingly perfected. Statistical requirements for authors remind researchers that they should make sufficient consideration not only in regards to statistical methods during the research design, but also standardized statistical reporting, which would be beneficial in providing stronger evidence and making a greater critical appraisal of evidence more accessible.

OASIS 2: online application for survival analysis 2 with features for the analysis of maximal lifespan and healthspan in aging research.

PubMed

Han, Seong Kyu; Lee, Dongyeop; Lee, Heetak; Kim, Donghyo; Son, Heehwa G; Yang, Jae-Seong; Lee, Seung-Jae V; Kim, Sanguk

2016-08-30

Online application for survival analysis (OASIS) has served as a popular and convenient platform for the statistical analysis of various survival data, particularly in the field of aging research. With the recent advances in the fields of aging research that deal with complex survival data, we noticed a need for updates to the current version of OASIS. Here, we report OASIS 2 (http://sbi.postech.ac.kr/oasis2), which provides extended statistical tools for survival data and an enhanced user interface. In particular, OASIS 2 enables the statistical comparison of maximal lifespans, which is potentially useful for determining key factors that limit the lifespan of a population. Furthermore, OASIS 2 provides statistical and graphical tools that compare values in different conditions and times. That feature is useful for comparing age-associated changes in physiological activities, which can be used as indicators of "healthspan." We believe that OASIS 2 will serve as a standard platform for survival analysis with advanced and user-friendly statistical tools for experimental biologists in the field of aging research.

Statistical power in parallel group point exposure studies with time-to-event outcomes: an empirical comparison of the performance of randomized controlled trials and the inverse probability of treatment weighting (IPTW) approach.

PubMed

Austin, Peter C; Schuster, Tibor; Platt, Robert W

2015-10-15

Estimating statistical power is an important component of the design of both randomized controlled trials (RCTs) and observational studies. Methods for estimating statistical power in RCTs have been well described and can be implemented simply. In observational studies, statistical methods must be used to remove the effects of confounding that can occur due to non-random treatment assignment. Inverse probability of treatment weighting (IPTW) using the propensity score is an attractive method for estimating the effects of treatment using observational data. However, sample size and power calculations have not been adequately described for these methods. We used an extensive series of Monte Carlo simulations to compare the statistical power of an IPTW analysis of an observational study with time-to-event outcomes with that of an analysis of a similarly-structured RCT. We examined the impact of four factors on the statistical power function: number of observed events, prevalence of treatment, the marginal hazard ratio, and the strength of the treatment-selection process. We found that, on average, an IPTW analysis had lower statistical power compared to an analysis of a similarly-structured RCT. The difference in statistical power increased as the magnitude of the treatment-selection model increased. The statistical power of an IPTW analysis tended to be lower than the statistical power of a similarly-structured RCT.

Robust Detection of Examinees with Aberrant Answer Changes

ERIC Educational Resources Information Center

Belov, Dmitry I.

2015-01-01

The statistical analysis of answer changes (ACs) has uncovered multiple testing irregularities on large-scale assessments and is now routinely performed at testing organizations. However, AC data has an uncertainty caused by technological or human factors. Therefore, existing statistics (e.g., number of wrong-to-right ACs) used to detect examinees…

Some Statistics for Assessing Person-Fit Based on Continuous-Response Models

ERIC Educational Resources Information Center

Ferrando, Pere Joan

2010-01-01

This article proposes several statistics for assessing individual fit based on two unidimensional models for continuous responses: linear factor analysis and Samejima's continuous response model. Both models are approached using a common framework based on underlying response variables and are formulated at the individual level as fixed regression…

Does the IQ God Exist?

ERIC Educational Resources Information Center

Siegel, Linda S.

1995-01-01

Responds to "The Bell Curve" by arguing that IQ is merely a statistical fiction, an artificial construct not corresponding to any real entity. Discusses the "seductive statistical trap of factor analysis" as it relates to IQ tests, multiple intelligences, content and bias of IQ tests, lack of validity of IQ tests for individual…

Vibroacoustic optimization using a statistical energy analysis model

NASA Astrophysics Data System (ADS)

Culla, Antonio; D`Ambrogio, Walter; Fregolent, Annalisa; Milana, Silvia

2016-08-01

In this paper, an optimization technique for medium-high frequency dynamic problems based on Statistical Energy Analysis (SEA) method is presented. Using a SEA model, the subsystem energies are controlled by internal loss factors (ILF) and coupling loss factors (CLF), which in turn depend on the physical parameters of the subsystems. A preliminary sensitivity analysis of subsystem energy to CLF's is performed to select CLF's that are most effective on subsystem energies. Since the injected power depends not only on the external loads but on the physical parameters of the subsystems as well, it must be taken into account under certain conditions. This is accomplished in the optimization procedure, where approximate relationships between CLF's, injected power and physical parameters are derived. The approach is applied on a typical aeronautical structure: the cabin of a helicopter.

The use of analysis of variance procedures in biological studies

USGS Publications Warehouse

Williams, B.K.

1987-01-01

The analysis of variance (ANOVA) is widely used in biological studies, yet there remains considerable confusion among researchers about the interpretation of hypotheses being tested. Ambiguities arise when statistical designs are unbalanced, and in particular when not all combinations of design factors are represented in the data. This paper clarifies the relationship among hypothesis testing, statistical modelling and computing procedures in ANOVA for unbalanced data. A simple two-factor fixed effects design is used to illustrate three common parametrizations for ANOVA models, and some associations among these parametrizations are developed. Biologically meaningful hypotheses for main effects and interactions are given in terms of each parametrization, and procedures for testing the hypotheses are described. The standard statistical computing procedures in ANOVA are given along with their corresponding hypotheses. Throughout the development unbalanced designs are assumed and attention is given to problems that arise with missing cells.

Factors that influence career choice in primary care among medical students starting social service in Honduras.

PubMed

Puertas, E Benjamín; Rivera, Tamara Y

2016-11-01

To 1) describe patterns of specialty choice; 2) investigate relationships between career selection and selected demographic indicators; and 3) identify salary perception, factors that influence career choice in primary care, and factors that influence desired location of future medical practice. The study used a mixed-methods approach that included a cross-sectional questionnaire survey applied to 234 last-year medical students in Honduras (September 2014), and semi-structured interviews with eight key informants (October 2014). Statistical analysis included chi-square and factor analysis. An alpha level of 0.05 was used to determine significance. In the qualitative analysis, several codes were associated with each other, and five major themes emerged. Primary care careers were the preferred choice for 8.1% of students, who preferred urban settings for future practice location. The perceived salary of specialties other than primary care was significantly higher than those of general practitioners, family practitioners, and pediatricians (P < 0.001). Participants considered "making a difference," income, teaching, prestige, and challenging work the most important factors influencing career choice. Practice in ambulatory settings was significantly associated with a preference for primary care specialties (P = < 0.05). Logistic regression analysis found that factors related to patient-based care were statistically significant for selecting primary care (P = 0.006). The qualitative analysis further endorsed the survey findings, identifying additional factors that influence career choice (future work option; availability of residency positions; and social factors, including violence). Rationales behind preference of a specialty appeared to be based on a combination of ambition and prestige, and on personal and altruistic considerations. Most factors that influence primary care career choice are similar to those found in the literature. There are several factors distinctive to medical students in Honduras-most of them barriers to primary care career choice.

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

PubMed

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

2014-10-01

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

Equivalent statistics and data interpretation.

PubMed

Francis, Gregory

2017-08-01

Recent reform efforts in psychological science have led to a plethora of choices for scientists to analyze their data. A scientist making an inference about their data must now decide whether to report a p value, summarize the data with a standardized effect size and its confidence interval, report a Bayes Factor, or use other model comparison methods. To make good choices among these options, it is necessary for researchers to understand the characteristics of the various statistics used by the different analysis frameworks. Toward that end, this paper makes two contributions. First, it shows that for the case of a two-sample t test with known sample sizes, many different summary statistics are mathematically equivalent in the sense that they are based on the very same information in the data set. When the sample sizes are known, the p value provides as much information about a data set as the confidence interval of Cohen's d or a JZS Bayes factor. Second, this equivalence means that different analysis methods differ only in their interpretation of the empirical data. At first glance, it might seem that mathematical equivalence of the statistics suggests that it does not matter much which statistic is reported, but the opposite is true because the appropriateness of a reported statistic is relative to the inference it promotes. Accordingly, scientists should choose an analysis method appropriate for their scientific investigation. A direct comparison of the different inferential frameworks provides some guidance for scientists to make good choices and improve scientific practice.

Unpredictability of fighter pilots' g duration tolerance by anthropometric and physiological characteristics.

PubMed

Park, Myunghwan; Yoo, Seunghoon; Seol, Hyeongju; Kim, Cheonyoung; Hong, Youngseok

2015-04-01

While the factors affecting fighter pilots' G level tolerance have been widely accepted, the factors affecting fighter pilots' G duration tolerance have not been well understood. Thirty-eight subjects wearing anti-G suits were exposed to sustained high G forces using a centrifuge. The subjects exerted AGSM and decelerated the centrifuge when they reached the point of loss of peripheral vision. The G profile consisted of a +2.3 G onset rate, +7.3 G single plateau, and -1.6 G offset rate. Each subject's G tolerance time was recorded and the relationship between the tolerance time and the subject's anthropometric and physiological factors were analyzed. The mean tolerance time of the 38 subjects was 31.6 s, and the min and max tolerance times were 20 s and 58 s, respectively. The correlation analysis indicated that none of the factors had statistically significant correlations with the subjects' G duration tolerance. Stepwise multiple regression analysis showed that G duration tolerance was not dependent on any personal factors of the subjects. After the values of personal factors were simplified into 0 or 1, the t-test analysis showed that subjects' heights were inversely correlated with G duration tolerance at a statistically significant level. However, a logistic regression analysis suggested that the effect of the height factor to a pilot's G duration tolerance was too weak to be used as a predictor of a pilot's G tolerance. Fighter pilots' G duration tolerance could not be predicted by pilots' anthropometric and physiological factors.

Sound transmission loss of composite sandwich panels

NASA Astrophysics Data System (ADS)

Zhou, Ran

Light composite sandwich panels are increasingly used in automobiles, ships and aircraft, because of the advantages they offer of high strength-to-weight ratios. However, the acoustical properties of these light and stiff structures can be less desirable than those of equivalent metal panels. These undesirable properties can lead to high interior noise levels. A number of researchers have studied the acoustical properties of honeycomb and foam sandwich panels. Not much work, however, has been carried out on foam-filled honeycomb sandwich panels. In this dissertation, governing equations for the forced vibration of asymmetric sandwich panels are developed. An analytical expression for modal densities of symmetric sandwich panels is derived from a sixth-order governing equation. A boundary element analysis model for the sound transmission loss of symmetric sandwich panels is proposed. Measurements of the modal density, total loss factor, radiation loss factor, and sound transmission loss of foam-filled honeycomb sandwich panels with different configurations and thicknesses are presented. Comparisons between the predicted sound transmission loss values obtained from wave impedance analysis, statistical energy analysis, boundary element analysis, and experimental values are presented. The wave impedance analysis model provides accurate predictions of sound transmission loss for the thin foam-filled honeycomb sandwich panels at frequencies above their first resonance frequencies. The predictions from the statistical energy analysis model are in better agreement with the experimental transmission loss values of the sandwich panels when the measured radiation loss factor values near coincidence are used instead of the theoretical values for single-layer panels. The proposed boundary element analysis model provides more accurate predictions of sound transmission loss for the thick foam-filled honeycomb sandwich panels than either the wave impedance analysis model or the statistical energy analysis model.

The prior statistics of object colors.

PubMed

Koenderink, Jan J

2010-02-01

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

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

PubMed

Kim, H S

1990-04-01

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

Assessing risk factors for periodontitis using regression

NASA Astrophysics Data System (ADS)

Lobo Pereira, J. A.; Ferreira, Maria Cristina; Oliveira, Teresa

2013-10-01

Multivariate statistical analysis is indispensable to assess the associations and interactions between different factors and the risk of periodontitis. Among others, regression analysis is a statistical technique widely used in healthcare to investigate and model the relationship between variables. In our work we study the impact of socio-demographic, medical and behavioral factors on periodontal health. Using regression, linear and logistic models, we can assess the relevance, as risk factors for periodontitis disease, of the following independent variables (IVs): Age, Gender, Diabetic Status, Education, Smoking status and Plaque Index. The multiple linear regression analysis model was built to evaluate the influence of IVs on mean Attachment Loss (AL). Thus, the regression coefficients along with respective p-values will be obtained as well as the respective p-values from the significance tests. The classification of a case (individual) adopted in the logistic model was the extent of the destruction of periodontal tissues defined by an Attachment Loss greater than or equal to 4 mm in 25% (AL≥4mm/≥25%) of sites surveyed. The association measures include the Odds Ratios together with the correspondent 95% confidence intervals.

Statistical t Analysis for the Solution of Prediction Trash Management in Dusun Tanjung Sari Kec. Ngaglik Kab Sleman, Yogyakarta

NASA Astrophysics Data System (ADS)

Salmahaminati; Husnaqilati, Atina; Yahya, Amri

2017-01-01

Trash management is one of the society participation to have a good hygiene for each area or nationally. Trash is known as the remainder of regular consumption that should be disposed to do waste processing which will be beneficial and improve the hygiene. The way to do is by sorting plastic which is processed into goods in accordance with the waste. In this study, we will know what are the factors that affect the desire of citizens to process the waste. The factors would have the identity and the state of being of each resident, having known of these factors will be the education about waste management, so it can be compared how the results of the extension by using preliminary data prior to the extension and the final data after extension. The analysis uses multiple logistic regression is the identify factors that influence people’s to desire the waste while the comparison results using t analysis. Data is derived from statistical instrument in the form of a questionnaire.

Factors affecting job satisfaction in nurse faculty: a meta-analysis.

PubMed

Gormley, Denise K

2003-04-01

Evidence in the literature suggests job satisfaction can make a difference in keeping qualified workers on the job, but little research has been conducted focusing specifically on nursing faculty. Several studies have examined nurse faculty satisfaction in relationship to one or two influencing factors. These factors include professional autonomy, leader role expectations, organizational climate, perceived role conflict and role ambiguity, leadership behaviors, and organizational characteristics. This meta-analysis attempts to synthesize the various studies conducted on job satisfaction in nursing faculty and analyze which influencing factors have the greatest effect. The procedure used for this meta-analysis consisted of reviewing studies to identify factors influencing job satisfaction, research questions, sample size reported, instruments used for measurement of job satisfaction and influencing factors, and results of statistical analysis.

The influence of the interactions between anthropogenic activities and multiple ecological factors on land surface temperatures of urban forests

NASA Astrophysics Data System (ADS)

Ren, Y.

2017-12-01

Context Land surface temperatures (LSTs) spatio-temporal distribution pattern of urban forests are influenced by many ecological factors; the identification of interaction between these factors can improve simulations and predictions of spatial patterns of urban cold islands. This quantitative research requires an integrated method that combines multiple sources data with spatial statistical analysis. Objectives The purpose of this study was to clarify urban forest LST influence interaction between anthropogenic activities and multiple ecological factors using cluster analysis of hot and cold spots and Geogdetector model. We introduced the hypothesis that anthropogenic activity interacts with certain ecological factors, and their combination influences urban forests LST. We also assumed that spatio-temporal distributions of urban forest LST should be similar to those of ecological factors and can be represented quantitatively. Methods We used Jinjiang as a representative city in China as a case study. Population density was employed to represent anthropogenic activity. We built up a multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) on a unified urban scale to support urban forest LST influence interaction research. Through a combination of spatial statistical analysis results, multi-source spatial data, and Geogdetector model, the interaction mechanisms of urban forest LST were revealed. Results Although different ecological factors have different influences on forest LST, in two periods with different hot spots and cold spots, the patch area and dominant tree species were the main factors contributing to LST clustering in urban forests. The interaction between anthropogenic activity and multiple ecological factors increased LST in urban forest stands, linearly and nonlinearly. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. Conclusions In conclusion, a combination of spatial statistics and GeogDetector models should be effective for quantitatively evaluating interactive relationships among ecological factors, anthropogenic activity and LST.

Ultrasound-enhanced bioscouring of greige cotton: regression analysis of process factors

USDA-ARS?s Scientific Manuscript database

Ultrasound-enhanced bioscouring process factors for greige cotton fabric are examined using custom experimental design utilizing statistical principles. An equation is presented which predicts bioscouring performance based upon percent reflectance values obtained from UV-Vis measurements of rutheniu...

A spatial cluster analysis of tractor overturns in Kentucky from 1960 to 2002

USGS Publications Warehouse

Saman, D.M.; Cole, H.P.; Odoi, A.; Myers, M.L.; Carey, D.I.; Westneat, S.C.

2012-01-01

Background: Agricultural tractor overturns without rollover protective structures are the leading cause of farm fatalities in the United States. To our knowledge, no studies have incorporated the spatial scan statistic in identifying high-risk areas for tractor overturns. The aim of this study was to determine whether tractor overturns cluster in certain parts of Kentucky and identify factors associated with tractor overturns. Methods: A spatial statistical analysis using Kulldorff's spatial scan statistic was performed to identify county clusters at greatest risk for tractor overturns. A regression analysis was then performed to identify factors associated with tractor overturns. Results: The spatial analysis revealed a cluster of higher than expected tractor overturns in four counties in northern Kentucky (RR = 2.55) and 10 counties in eastern Kentucky (RR = 1.97). Higher rates of tractor overturns were associated with steeper average percent slope of pasture land by county (p = 0.0002) and a greater percent of total tractors with less than 40 horsepower by county (p<0.0001). Conclusions: This study reveals that geographic hotspots of tractor overturns exist in Kentucky and identifies factors associated with overturns. This study provides policymakers a guide to targeted county-level interventions (e.g., roll-over protective structures promotion interventions) with the intention of reducing tractor overturns in the highest risk counties in Kentucky. ?? 2012 Saman et al.

[Factor Analysis: Principles to Evaluate Measurement Tools for Mental Health].

PubMed

Campo-Arias, Adalberto; Herazo, Edwin; Oviedo, Heidi Celina

2012-09-01

The validation of a measurement tool in mental health is a complex process that usually starts by estimating reliability, to later approach its validity. Factor analysis is a way to know the number of dimensions, domains or factors of a measuring tool, generally related to the construct validity of the scale. The analysis could be exploratory or confirmatory, and helps in the selection of the items with better performance. For an acceptable factor analysis, it is necessary to follow some steps and recommendations, conduct some statistical tests, and rely on a proper sample of participants. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

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

PubMed

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

2016-08-24

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

Linear regression analysis: part 14 of a series on evaluation of scientific publications.

PubMed

Schneider, Astrid; Hommel, Gerhard; Blettner, Maria

2010-11-01

Regression analysis is an important statistical method for the analysis of medical data. It enables the identification and characterization of relationships among multiple factors. It also enables the identification of prognostically relevant risk factors and the calculation of risk scores for individual prognostication. This article is based on selected textbooks of statistics, a selective review of the literature, and our own experience. After a brief introduction of the uni- and multivariable regression models, illustrative examples are given to explain what the important considerations are before a regression analysis is performed, and how the results should be interpreted. The reader should then be able to judge whether the method has been used correctly and interpret the results appropriately. The performance and interpretation of linear regression analysis are subject to a variety of pitfalls, which are discussed here in detail. The reader is made aware of common errors of interpretation through practical examples. Both the opportunities for applying linear regression analysis and its limitations are presented.

Climate drivers on malaria transmission in Arunachal Pradesh, India.

PubMed

Upadhyayula, Suryanaryana Murty; Mutheneni, Srinivasa Rao; Chenna, Sumana; Parasaram, Vaideesh; Kadiri, Madhusudhan Rao

2015-01-01

The present study was conducted during the years 2006 to 2012 and provides information on prevalence of malaria and its regulation with effect to various climatic factors in East Siang district of Arunachal Pradesh, India. Correlation analysis, Principal Component Analysis and Hotelling's T² statistics models are adopted to understand the effect of weather variables on malaria transmission. The epidemiological study shows that the prevalence of malaria is mostly caused by the parasite Plasmodium vivax followed by Plasmodium falciparum. It is noted that, the intensity of malaria cases declined gradually from the year 2006 to 2012. The transmission of malaria observed was more during the rainy season, as compared to summer and winter seasons. Further, the data analysis study with Principal Component Analysis and Hotelling's T² statistic has revealed that the climatic variables such as temperature and rainfall are the most influencing factors for the high rate of malaria transmission in East Siang district of Arunachal Pradesh.

Factor Scores, Structure and Communality Coefficients: A Primer

ERIC Educational Resources Information Center

Odum, Mary

2011-01-01

(Purpose) The purpose of this paper is to present an easy-to-understand primer on three important concepts of factor analysis: Factor scores, structure coefficients, and communality coefficients. Given that statistical analyses are a part of a global general linear model (GLM), and utilize weights as an integral part of analyses (Thompson, 2006;…

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.…

Advance Report of Final Mortality Statistics, 1985.

ERIC Educational Resources Information Center

Monthly Vital Statistics Report, 1987

1987-01-01

This document presents mortality statistics for 1985 for the entire United States. Data analysis and discussion of these factors is included: death and death rates; death rates by age, sex, and race; expectation of life at birth and at specified ages; causes of death; infant mortality; and maternal mortality. Highlights reported include: (1) the…

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

ERIC Educational Resources Information Center

Tella, Adeyinka

2016-01-01

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

Geographical Environment Factors and Risk Assessment of Tick-Borne Encephalitis in Hulunbuir, Northeastern China.

PubMed

Li, Yifan; Wang, Juanle; Gao, Mengxu; Fang, Liqun; Liu, Changhua; Lyu, Xin; Bai, Yongqing; Zhao, Qiang; Li, Hairong; Yu, Hongjie; Cao, Wuchun; Feng, Liqiang; Wang, Yanjun; Zhang, Bin

2017-05-26

Tick-borne encephalitis (TBE) is one of natural foci diseases transmitted by ticks. Its distribution and transmission are closely related to geographic and environmental factors. Identification of environmental determinates of TBE is of great importance to understanding the general distribution of existing and potential TBE natural foci. Hulunbuir, one of the most severe endemic areas of the disease, is selected as the study area. Statistical analysis, global and local spatial autocorrelation analysis, and regression methods were applied to detect the spatiotemporal characteristics, compare the impact degree of associated factors, and model the risk distribution using the heterogeneity. The statistical analysis of gridded geographic and environmental factors and TBE incidence show that the TBE patients mainly occurred during spring and summer and that there is a significant positive spatial autocorrelation between the distribution of TBE cases and environmental characteristics. The impact degree of these factors on TBE risks has the following descending order: temperature, relative humidity, vegetation coverage, precipitation and topography. A high-risk area with a triangle shape was determined in the central part of Hulunbuir; the low-risk area is located in the two belts next to the outside edge of the central triangle. The TBE risk distribution revealed that the impact of the geographic factors changed depending on the heterogeneity.

Prognostic factors for risk stratification of adult cancer patients with chemotherapy-induced febrile neutropenia: a systematic review and meta-analysis.

PubMed

Lee, Yee Mei; Lang, Dora; Lockwood, Craig

Increasing numbers of studies identify new prognostic factors for categorising chemotherapy-induced febrile neutropenia adult cancer patients into high- or low-risk groups for adverse outcomes. These groupings are used to tailor therapy according to level of risk. However many emerging factors with prognostic significance remain controversial, being based on single studies only. A systematic review was conducted to determine the strength of association of all identified factors associated with the outcomes of chemotherapy-induced febrile neutropenia patients. The participants included were adults of 15 years old and above, with a cancer diagnosis and who underwent cancer treatment.The review focused on clinical factors and their association with the outcomes of cancer patients with chemotherapy-induced febrile neutropenia at presentation of fever.All quantitative studies published in English which investigated clinical factors for risk stratification of adult cancer patients with chemotherapy-induced febrile neutropenia were considered.The primary outcome of interest was to identify the clinical factors for risk stratification of adult cancer patients with chemotherapy-induced febrile neutropenia. Electronic databases searched from their respective inception date up to December 2011 include MEDLINE, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science, Science-Direct, Scopus and Mednar. The quality of the included studies was subjected to assessment by two independent reviewers. The standardised critical appraisal tool from the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI-MAStARI) was used to assess the following criteria: representativeness of study population; clearly defined prognostic factors and outcomes; whether potential confounders were addressed and appropriate statistical analysis was undertaken for the study design. Data extraction was performed using a modified version of the standardised extraction tool from the JBI-MAStARI. Prognostic factors and the accompanying odds ratio reported for the significance of these factors that were identified by multivariate regression, were extracted from each included study. Studies results were pooled in statistical meta-analysis using Review Manager 5.1. Where statistical pooling was not possible, the findings were presented in narrative form. Seven studies (four prospective cohort and three retrospective cohort) investigating 22 factors in total were included. Fixed effects meta-analysis showed: hypotension [OR=1.66, 95%CI, 1.14-2.41, p=0.008] and thrombocytopenia [OR=3.92, 95%CI, 2.19-7.01, p<0.00001)] were associated with high-risk of adverse outcomes for febrile neutropenia. Other factors that were statistically significant from single studies included: age of patients, clinical presentation at fever onset, presence or absence of co-morbidities, infections, duration and severity of neutropenia state. Five prognostic factors failed to demonstrate an association between the variables and the outcomes measured and they include: presence of pneumonia, total febrile days, median days to fever, recovery from neutropenia and presence of moderate clinical symptoms in association with Gram-negative bacteraemia. Despite the overall limitations identified in the included studies, this review has provided a synthesis of the best available evidence for the prognostic factors used in risk stratification of febrile neutropenia patients. However, the dynamic aspects of prognostic model development, validation and utilisation have not been addressed adequately thus far. Given the findings of this review, it is timely to address these issues and improve the utilisation of prognostic models in the management of febrile neutropenia patients. The identified factors are similar to the factors in current prognostic models. However, additional factors that were reported to be statistically significant in this review (thrombocytopenia, presence of central venous catheter, and duration and severity of neutropenia) have not previously been included in prognostic models. This review has found these factors may improve the performance of current models by adding or replacing some of the factors. The role of risk stratification of chemotherapy-induced febrile neutropenia patients continues to evolve as the practice of risk-based therapy has been demonstrated to be beneficial to patients, clinicians and health care organisations. Further research to identify new factors /markers is needed to develop a new model which is reliable and accurate for these patients, regardless of cancer types. A robust and well-validated prognostic model is the key to enhance patient safety in the risk-based management of cancer patients with chemotherapy-induced febrile neutropenia.

Grouping of Bulgarian wines according to grape variety by using statistical methods

NASA Astrophysics Data System (ADS)

Milev, M.; Nikolova, Kr.; Ivanova, Ir.; Minkova, St.; Evtimov, T.; Krustev, St.

2017-12-01

68 different types of Bulgarian wines were studied in accordance with 9 optical parameters as follows: color parameters in XYZ and SIE Lab color systems, lightness, Hue angle, chroma, fluorescence intensity and emission wavelength. The main objective of this research is using hierarchical cluster analysis to evaluate the similarity and the distance between examined different types of Bulgarian wines and their grouping based on physical parameters. We have found that wines are grouped in clusters on the base of the degree of identity between them. There are two main clusters each one with two subclusters. The first one contains white wines and Sira, the second contains red wines and rose. The results from cluster analysis are presented graphically by a dendrogram. The other statistical technique used is factor analysis performed by the Method of Principal Components (PCA). The aim is to reduce the large number of variables to a few factors by grouping the correlated variables into one factor and subdividing the noncorrelated variables into different factors. Moreover the factor analysis provided the possibility to determine the parameters with the greatest influence over the distribution of samples in different clusters. In our study after the rotation of the factors with Varimax method the parameters were combined into two factors, which explain about 80 % of the total variation. The first one explains the 61.49% and correlates with color characteristics, the second one explains 18.34% from the variation and correlates with the parameters connected with fluorescence spectroscopy.

Diagnosis checking of statistical analysis in RCTs indexed in PubMed.

PubMed

Lee, Paul H; Tse, Andy C Y

2017-11-01

Statistical analysis is essential for reporting of the results of randomized controlled trials (RCTs), as well as evaluating their effectiveness. However, the validity of a statistical analysis also depends on whether the assumptions of that analysis are valid. To review all RCTs published in journals indexed in PubMed during December 2014 to provide a complete picture of how RCTs handle assumptions of statistical analysis. We reviewed all RCTs published in December 2014 that appeared in journals indexed in PubMed using the Cochrane highly sensitive search strategy. The 2014 impact factors of the journals were used as proxies for their quality. The type of statistical analysis used and whether the assumptions of the analysis were tested were reviewed. In total, 451 papers were included. Of the 278 papers that reported a crude analysis for the primary outcomes, 31 (27·2%) reported whether the outcome was normally distributed. Of the 172 papers that reported an adjusted analysis for the primary outcomes, diagnosis checking was rarely conducted, with only 20%, 8·6% and 7% checked for generalized linear model, Cox proportional hazard model and multilevel model, respectively. Study characteristics (study type, drug trial, funding sources, journal type and endorsement of CONSORT guidelines) were not associated with the reporting of diagnosis checking. The diagnosis of statistical analyses in RCTs published in PubMed-indexed journals was usually absent. Journals should provide guidelines about the reporting of a diagnosis of assumptions. © 2017 Stichting European Society for Clinical Investigation Journal Foundation.

Forecasting daily source air quality using multivariate statistical analysis and radial basis function networks.

PubMed

Sun, Gang; Hoff, Steven J; Zelle, Brian C; Nelson, Minda A

2008-12-01

It is vital to forecast gas and particle matter concentrations and emission rates (GPCER) from livestock production facilities to assess the impact of airborne pollutants on human health, ecological environment, and global warming. Modeling source air quality is a complex process because of abundant nonlinear interactions between GPCER and other factors. The objective of this study was to introduce statistical methods and radial basis function (RBF) neural network to predict daily source air quality in Iowa swine deep-pit finishing buildings. The results show that four variables (outdoor and indoor temperature, animal units, and ventilation rates) were identified as relative important model inputs using statistical methods. It can be further demonstrated that only two factors, the environment factor and the animal factor, were capable of explaining more than 94% of the total variability after performing principal component analysis. The introduction of fewer uncorrelated variables to the neural network would result in the reduction of the model structure complexity, minimize computation cost, and eliminate model overfitting problems. The obtained results of RBF network prediction were in good agreement with the actual measurements, with values of the correlation coefficient between 0.741 and 0.995 and very low values of systemic performance indexes for all the models. The good results indicated the RBF network could be trained to model these highly nonlinear relationships. Thus, the RBF neural network technology combined with multivariate statistical methods is a promising tool for air pollutant emissions modeling.

The use of multicomponent statistical analysis in hydrogeological environmental research.

PubMed

Lambrakis, Nicolaos; Antonakos, Andreas; Panagopoulos, George

2004-04-01

The present article examines the possibilities of investigating NO(3)(-) spread in aquifers by applying multicomponent statistical methods (factor, cluster and discriminant analysis) on hydrogeological, hydrochemical, and environmental parameters. A 4-R-Mode factor model determined from the analysis showed its useful role in investigating hydrogeological parameters affecting NO(3)(-) concentration, such as its dilution by upcoming groundwater of the recharge areas. The relationship between NO(3)(-) concentration and agricultural activities can be determined sufficiently by the first factor which relies on NO(3)(-) and SO(4)(2-) of the same origin-that of agricultural fertilizers. The other three factors of R-Mode analysis are not connected directly to the NO(3)(-) problem. They do however, by extracting the role of the unsaturated zone, show an interesting relationship between organic matter content, thickness and saturated hydraulic conductivity. The application of Hirerarchical Cluster Analysis, based on all possible combinations of classification method, showed two main groups of samples. The first group comprises samples from the edges and the second from the central part of the study area. By the application of Discriminant Analysis it was shown that NO(3)(-) and SO(4)(2-) ions are the most significant variables in the discriminant function. Therefore, the first group is considered to comprise all samples from areas not influenced by fertilizers lying on the edges of contaminating activities such as crop cultivation, while the second comprises all the other samples.

Statistical analysis of RHIC beam position monitors performance

NASA Astrophysics Data System (ADS)

Calaga, R.; Tomás, R.

2004-04-01

A detailed statistical analysis of beam position monitors (BPM) performance at RHIC is a critical factor in improving regular operations and future runs. Robust identification of malfunctioning BPMs plays an important role in any orbit or turn-by-turn analysis. Singular value decomposition and Fourier transform methods, which have evolved as powerful numerical techniques in signal processing, will aid in such identification from BPM data. This is the first attempt at RHIC to use a large set of data to statistically enhance the capability of these two techniques and determine BPM performance. A comparison from run 2003 data shows striking agreement between the two methods and hence can be used to improve BPM functioning at RHIC and possibly other accelerators.

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

Analysis of Doppler radar windshear data

NASA Technical Reports Server (NTRS)

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

1989-01-01

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

Multivariate statistical analysis to characterize/discriminate between anthropogenic and geogenic trace elements occurrence in the Campania Plain, Southern Italy.

PubMed

Busico, Gianluigi; Cuoco, Emilio; Kazakis, Nerantzis; Colombani, Nicolò; Mastrocicco, Micòl; Tedesco, Dario; Voudouris, Konstantinos

2018-03-01

Shallow aquifers are the most accessible reservoirs of potable groundwater; nevertheless, they are also prone to various sources of pollution and it is usually difficult to distinguish between human and natural sources at the watershed scale. The area chosen for this study (the Campania Plain) is characterized by high spatial heterogeneities both in geochemical features and in hydraulic properties. Groundwater mineralization is driven by many processes such as, geothermal activity, weathering of volcanic products and intense human activities. In such a landscape, multivariate statistical analysis has been used to differentiate among the main hydrochemical processes occurring in the area, using three different approaches of factor analysis: (i) major elements, (ii) trace elements, (iii) both major and trace elements. The elaboration of the factor analysis approaches has revealed seven distinct hydrogeochemical processes: i) Salinization (Cl - , Na + ); ii) Carbonate rocks dissolution; iii) Anthropogenic inputs (NO 3 - , SO 4 2- , U, V); iv) Reducing conditions (Fe 2+ , Mn 2+ ); v) Heavy metals contamination (Cr and Ni); vi) Geothermal fluids influence (Li + ); and vii) Volcanic products contribution (As, Rb). Results from this study highlight the need to separately apply factor analysis when a large data set of trace elements is available. In fact, the impact of geothermal fluids in the shallow aquifer was identified from the application of the factor analysis using only trace elements. This study also reveals that the factor analysis of major and trace elements can differentiate between anthropogenic and geogenic sources of pollution in intensively exploited aquifers. Copyright © 2017 Elsevier Ltd. All rights reserved.

CSFII Analysis of Food Intake Distributions (2003)

EPA Science Inventory

The National Center for Environmental Assessment (NCEA) of the Office of Research and Development published the Exposure Factors Handbook in 1997 (EPA/600/P-95/002Fa-c). The Handbook provides a summary of the available statistical data on various factors used in assessing human ...

Psychosocial Factors and Community College Student Success: A Meta-Analytic Investigation

ERIC Educational Resources Information Center

Fong, Carlton J.; Davis, Coreen W.; Kim, Yughi; Kim, Young Won; Marriott, Lauren; Kim, SooYeon

2017-01-01

This meta-analysis examined the relationship between psychosocial factors and community college student success. Informed by college persistence models and motivational theory, we statistically integrated past research on five psychosocial categories (motivation, self-perceptions, attributions, self-regulation, and anxiety), examining their…

Statistical analysis for improving data precision in the SPME GC-MS analysis of blackberry (Rubus ulmifolius Schott) volatiles.

PubMed

D'Agostino, M F; Sanz, J; Martínez-Castro, I; Giuffrè, A M; Sicari, V; Soria, A C

2014-07-01

Statistical analysis has been used for the first time to evaluate the dispersion of quantitative data in the solid-phase microextraction (SPME) followed by gas chromatography-mass spectrometry (GC-MS) analysis of blackberry (Rubus ulmifolius Schott) volatiles with the aim of improving their precision. Experimental and randomly simulated data were compared using different statistical parameters (correlation coefficients, Principal Component Analysis loadings and eigenvalues). Non-random factors were shown to significantly contribute to total dispersion; groups of volatile compounds could be associated with these factors. A significant improvement of precision was achieved when considering percent concentration ratios, rather than percent values, among those blackberry volatiles with a similar dispersion behavior. As novelty over previous references, and to complement this main objective, the presence of non-random dispersion trends in data from simple blackberry model systems was evidenced. Although the influence of the type of matrix on data precision was proved, the possibility of a better understanding of the dispersion patterns in real samples was not possible from model systems. The approach here used was validated for the first time through the multicomponent characterization of Italian blackberries from different harvest years. Copyright © 2014 Elsevier B.V. All rights reserved.

Analysis of variance to assess statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes.

PubMed

Makeyev, Oleksandr; Joe, Cody; Lee, Colin; Besio, Walter G

2017-07-01

Concentric ring electrodes have shown promise in non-invasive electrophysiological measurement demonstrating their superiority to conventional disc electrodes, in particular, in accuracy of Laplacian estimation. Recently, we have proposed novel variable inter-ring distances concentric ring electrodes. Analytic and finite element method modeling results for linearly increasing distances electrode configurations suggested they may decrease the truncation error resulting in more accurate Laplacian estimates compared to currently used constant inter-ring distances configurations. This study assesses statistical significance of Laplacian estimation accuracy improvement due to novel variable inter-ring distances concentric ring electrodes. Full factorial design of analysis of variance was used with one categorical and two numerical factors: the inter-ring distances, the electrode diameter, and the number of concentric rings in the electrode. The response variables were the Relative Error and the Maximum Error of Laplacian estimation computed using a finite element method model for each of the combinations of levels of three factors. Effects of the main factors and their interactions on Relative Error and Maximum Error were assessed and the obtained results suggest that all three factors have statistically significant effects in the model confirming the potential of using inter-ring distances as a means of improving accuracy of Laplacian estimation.

Fatal falls in the US construction industry, 1990 to 1999.

PubMed

Derr, J; Forst, L; Chen, H Y; Conroy, L

2001-10-01

The Occupational Safety and Health Administration's (OSHA's) Integrated Management Information System (IMIS) database allows for the detailed analysis of risk factors surrounding fatal occupational events. This study used IMIS data to (1) perform a risk factor analysis of fatal construction falls, and (2) assess the impact of the February 1995 29 CFR Part 1926 Subpart M OSHA fall protection regulations for construction by calculating trends in fatal fall rates. In addition, IMIS data on fatal construction falls were compared with data from other occupational fatality surveillance systems. For falls in construction, the study identified several demographic factors that may indicate increased risk. A statistically significant downward trend in fatal falls was evident in all construction and within several construction categories during the decade. Although the study failed to show a statistically significant intervention effect from the new OSHA regulations, it may have lacked the power to do so.

Problem area descriptions : motor vehicle crashes - data analysis and IVI program analysis

DOT National Transportation Integrated Search

In general, the IVI program focuses on the more significant safety problem categories as : indicated by statistical analyses of crash data. However, other factors were considered in setting : program priorities and schedules. For some problem areas, ...

Assessing the specificity of posttraumatic stress disorder's dysphoric items within the dysphoria model.

PubMed

Armour, Cherie; Shevlin, Mark

2013-10-01

The factor structure of posttraumatic stress disorder (PTSD) currently used by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), has received limited support. A four-factor dysphoria model is widely supported. However, the dysphoria factor of this model has been hailed as a nonspecific factor of PTSD. The present study investigated the specificity of the dysphoria factor within the dysphoria model by conducting a confirmatory factor analysis while statistically controlling for the variance attributable to depression. The sample consisted of 429 individuals who met the diagnostic criteria for PTSD in the National Comorbidity Survey. The results concluded that there was no significant attenuation in any of the PTSD items. This finding is pertinent given several proposals for the removal of dysphoric items from the diagnostic criteria set of PTSD in the upcoming DSM-5.

Medial Tibial Stress Syndrome in Active Individuals: A Systematic Review and Meta-analysis of Risk Factors

PubMed Central

Reinking, Mark F.; Austin, Tricia M.; Richter, Randy R.; Krieger, Mary M.

2016-01-01

Context: Medial tibial stress syndrome (MTSS) is a common condition in active individuals and presents as diffuse pain along the posteromedial border of the tibia. Objective: To use cross-sectional, case-control, and cohort studies to identify significant MTSS risk factors. Data Sources: Bibliographic databases (PubMed, Scopus, CINAHL, SPORTDiscus, EMBASE, EBM Reviews, PEDRo), grey literature, electronic search of full text of journals, manual review of reference lists, and automatically executed PubMed MTSS searches were utilized. All searches were conducted between 2011 and 2015. Study Selection: Inclusion criteria were determined a priori and included original research with participants’ pain diffuse, located in the posterior medial tibial region, and activity related. Study Design: Systematic review with meta-analysis. Level of evidence: Level 4. Data Extraction: Titles and abstracts were reviewed to eliminate citations that did not meet the criteria for inclusion. Study characteristics identified a priori were extracted for data analysis. Statistical heterogeneity was examined using the I2 index and Cochran Q test, and a random-effects model was used to calculate the meta-analysis when 2 or more studies examined a risk factor. Two authors independently assessed study quality. Results: Eighty-three articles met the inclusion criteria, and 22 articles included risk factor data. Of the 27 risk factors that were in 2 or more studies, 5 risk factors showed a significant pooled effect and low statistical heterogeneity, including female sex (odds ratio [OR], 2.35; CI, 1.58-3.50), increased weight (standardized mean difference [SMD], 0.24; CI, 0.03-0.45), higher navicular drop (SMD, 0.44; CI, 0.21-0.67), previous running injury (OR, 2.18; CI, 1.00-4.72), and greater hip external rotation with the hip in flexion (SMD, 0.44; CI, 0.23-0.65). The remaining risk factors had a nonsignificant pooled effect or significant pooled effect with high statistical heterogeneity. Conclusion: Female sex, increased weight, higher navicular drop, previous running injury, and greater hip external rotation with the hip in flexion are risk factors for the development of MTSS. PMID:27729482

Using multi-level data to estimate the effect of an 'alcogenic' environment on hazardous alcohol consumption in the former Soviet Union.

PubMed

Murphy, Adrianna; Roberts, Bayard; Ploubidis, George B; Stickley, Andrew; McKee, Martin

2014-05-01

The purpose of this study was to assess whether alcohol-related community characteristics act collectively to influence individual-level alcohol consumption in the former Soviet Union (fSU). Using multi-level data from nine countries in the fSU we conducted a factor analysis of seven alcohol-related community characteristics. The association between any latent factors underlying these characteristics and two measures of hazardous alcohol consumption was then analysed using a population average regression modelling approach. Our factor analysis produced one factor with an eigenvalue >1 (EV=1.28), which explained 94% of the variance. This factor was statistically significantly associated with increased odds of CAGE problem drinking (OR=1.40 (1.08-1.82)). The estimated association with EHD was not statistically significant (OR=1.10 (0.85-1.44)). Our findings suggest that a high number of beer, wine and spirit advertisements and high alcohol outlet density may work together to create an 'alcogenic' environment that encourages hazardous alcohol consumption in the fSU. Copyright © 2014 Elsevier Ltd. All rights reserved.

Workshop on Functional and Structural Relationships and Factor Analysis (1983). Summary of Research Interests of Participants.

DTIC Science & Technology

1983-01-01

J. Amer. Statist. Assoc. 75, 687-692. Dahm, P. F., Helton, B. and Fuller, W. A. (1983), Generalized least squares estimation of the genotypic ...with applications to -"insect development times". Austral. J. Statist. 23, 204-213. [2] Angus , J.F., R. Morton and C. Schafer. (1981). "Phasic

Finding P-Values for F Tests of Hypothesis on a Spreadsheet.

ERIC Educational Resources Information Center

Rochowicz, John A., Jr.

The calculation of the F statistic for a one-factor analysis of variance (ANOVA) and the construction of an ANOVA tables are easily implemented on a spreadsheet. This paper describes how to compute the p-value (observed significance level) for a particular F statistic on a spreadsheet. Decision making on a spreadsheet and applications to the…

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

ERIC Educational Resources Information Center

Vivo, Juana-Maria; Franco, Manuel

2008-01-01

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

Measuring the Effects of Peer Learning on Students' Academic Achievement in First-Year Business Statistics

ERIC Educational Resources Information Center

Dancer, Diane; Morrison, Kellie; Tarr, Garth

2015-01-01

Peer-assisted study session (PASS) programs have been shown to positively affect students' grades in a majority of studies. This study extends that analysis in two ways: controlling for ability and other factors, with focus on international students, and by presenting results for PASS in business statistics. Ordinary least squares, random effects…

Salutogenic factors for mental health promotion in work settings and organizations.

PubMed

Graeser, Silke

2011-12-01

Accompanied by an increasing awareness of companies and organizations for mental health conditions in work settings and organizations, the salutogenic perspective provides a promising approach to identify supportive factors and resources of organizations to promote mental health. Based on the sense of coherence (SOC) - usually treated as an individual and personality trait concept - an organization-based SOC scale was developed to identify potential salutogenic factors of a university as an organization and work place. Based on results of two samples of employees (n = 362, n = 204), factors associated with the organization-based SOC were evaluated. Statistical analysis yielded significant correlations between mental health and the setting-based SOC as well as the three factors of the SOC yielded by factor analysis yielded three factors comprehensibility, manageability and meaningfulness. Significant statistic results of bivariate and multivariate analyses emphasize the significance of aspects such as participation and comprehensibility referring to the organization, social cohesion and social climate on the social level, and recognition on the individual level for an organization-based SOC. Potential approaches for the further development of interventions for work-place health promotion based on salutogenic factors and resources on the individual, social and organization level are elaborated and the transcultural dimensions of these factors discussed.

Duration on unemployment: geographic mobility and selectivity bias.

PubMed

Goss, E P; Paul, C; Wilhite, A

1994-01-01

Modeling the factors affecting the duration of unemployment was found to be influenced by the inclusion of migration factors. Traditional models which did not control for migration factors were found to underestimate movers' probability of finding an acceptable job. The empirical test of the theory, based on the analysis of data on US household heads unemployed in 1982 and employed in 1982 and 1983, found that the cumulative probability of reemployment in the traditional model was .422 and in the migration selectivity model was .624 after 30 weeks of searching. In addition, controlling for selectivity eliminated the significance of the relationship between race and job search duration in the model. The relationship between search duration and the county unemployment rate in 1982 became statistically significant, and the relationship between search duration and 1980 population per square mile in the 1982 county of residence became statistically insignificant. The finding that non-Whites have a longer duration of unemployment can better be understood as non-Whites' lower geographic mobility and lack of greater job contacts. The statistical significance of a high unemployment rate in the home labor market reducing the probability of finding employment was more in keeping with expectations. The findings assumed that the duration of employment accurately reflected the length of job search. The sample was redrawn to exclude discouraged workers and the analysis was repeated. The findings were similar to the full sample, with the coefficient for migration variable being negative and statistically significant and the coefficient for alpha remaining positive and statistically significant. Race in the selectivity model remained statistically insignificant. The findings supported the Schwartz model hypothesizing that the expansion of the radius of the search would reduce the duration of unemployment. The exclusion of the migration factor misspecified the equation for unemployment duration. Policy should be directed to the problems of geographic mobility, particularly among non-Whites.

Method for factor analysis of GC/MS data

DOEpatents

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

2012-09-11

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

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.

A longitudinal analysis of bibliometric and impact factor trends among the core international journals of nursing, 1977-2008.

PubMed

Smith, Derek R

2010-12-01

Although bibliometric analysis affords significant insight into the progression and distribution of information within a particular research field, detailed longitudinal studies of this type are rare within the field of nursing. This study aimed to investigate, from a bibliometric perspective, the progression and trends of core international nursing journals over the longest possible time period. A detailed bibliometric analysis was undertaken among 7 core international nursing periodicals using custom historical data sourced from the Thomson Reuters Journal Citation Reports®. In the 32 years between 1977 and 2008, the number of citations received by these 7 journals increased over 700%. A sustained and statistically significant (p<0.001) 3-fold increase was also observed in the average impact factor score during this period. Statistical analysis revealed that all periodicals experienced significant (p<0.001) improvements in their impact factors over time, with gains ranging from approximately 2- to 78-fold. Overall, this study provides one of the most comprehensive, longitudinal bibliometric analyses ever conducted in the field of nursing. Impressive and continual impact factor gains suggest that published nursing research is being increasingly seen, heard and cited in the international academic community. Copyright © 2010 Elsevier Ltd. All rights reserved.

Demographics as predictors of suicidal thoughts and behaviors: A meta-analysis

PubMed Central

Huang, Xieyining; Ribeiro, Jessica D.; Musacchio, Katherine M.; Franklin, Joseph C.

2017-01-01

Background Certain demographic factors have long been cited to confer risk or protection for suicidal thoughts and behaviors. However, many studies have found weak or non-significant effects. Determining the effect strength and clinical utility of demographics as predictors is crucial for suicide risk assessment and theory development. As such, we conducted a meta-analysis to determine the effect strength and clinical utility of demographics as predictors. Methods We searched PsycInfo, PubMed, and GoogleScholar for studies published before January 1st, 2015. Inclusion criteria required that studies use at least one demographic factor to longitudinally predict suicide ideation, attempt, or death. The initial search yielded 2,541 studies, 159 of which were eligible. A total of 752 unique statistical tests were included in analysis. Results Suicide death was the most commonly studied outcome, followed by attempt and ideation. The average follow-up length was 9.4 years. The overall effects of demographic factors studied in the field as risk factors were significant but weak, and that of demographic factors studied as protective factors were non-significant. Adjusting for publication bias further reduced effect estimates. No specific demographic factors appeared to be strong predictors. The effects were consistent across multiple moderators. Conclusions At least within the narrow methodological constraints of the existing literature, demographic factors were statistically significant risk factors, but not protective factors. Even as risk factors, demographics offer very little improvement in predictive accuracy. Future studies that go beyond the limitations of the existing literature are needed to further understand the effects of demographics. PMID:28700728

Quantifying the influences of various ecological factors on land surface temperature of urban forests.

PubMed

Ren, Yin; Deng, Lu-Ying; Zuo, Shu-Di; Song, Xiao-Dong; Liao, Yi-Lan; Xu, Cheng-Dong; Chen, Qi; Hua, Li-Zhong; Li, Zheng-Wei

2016-09-01

Identifying factors that influence the land surface temperature (LST) of urban forests can help improve simulations and predictions of spatial patterns of urban cool islands. This requires a quantitative analytical method that combines spatial statistical analysis with multi-source observational data. The purpose of this study was to reveal how human activities and ecological factors jointly influence LST in clustering regions (hot or cool spots) of urban forests. Using Xiamen City, China from 1996 to 2006 as a case study, we explored the interactions between human activities and ecological factors, as well as their influences on urban forest LST. Population density was selected as a proxy for human activity. We integrated multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) to develop a database on a unified urban scale. The driving mechanism of urban forest LST was revealed through a combination of multi-source spatial data and spatial statistical analysis of clustering regions. The results showed that the main factors contributing to urban forest LST were dominant tree species and elevation. The interactions between human activity and specific ecological factors linearly or nonlinearly increased LST in urban forests. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. In conclusion, quantitative studies based on spatial statistics and GeogDetector models should be conducted in urban areas to reveal interactions between human activities, ecological factors, and LST. Copyright © 2016 Elsevier Ltd. All rights reserved.

The analysis of morphometric data on rocky mountain wolves and artic wolves using statistical method

NASA Astrophysics Data System (ADS)

Ammar Shafi, Muhammad; Saifullah Rusiman, Mohd; Hamzah, Nor Shamsidah Amir; Nor, Maria Elena; Ahmad, Noor’ani; Azia Hazida Mohamad Azmi, Nur; Latip, Muhammad Faez Ab; Hilmi Azman, Ahmad

2018-04-01

Morphometrics is a quantitative analysis depending on the shape and size of several specimens. Morphometric quantitative analyses are commonly used to analyse fossil record, shape and size of specimens and others. The aim of the study is to find the differences between rocky mountain wolves and arctic wolves based on gender. The sample utilised secondary data which included seven variables as independent variables and two dependent variables. Statistical modelling was used in the analysis such was the analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). The results showed there exist differentiating results between arctic wolves and rocky mountain wolves based on independent factors and gender.

[Influence of demographic and socioeconomic characteristics on the quality of life].

PubMed

Grbić, Gordana; Djokić, Dragoljub; Kocić, Sanja; Mitrašinović, Dejan; Rakić, Ljiljana; Prelević, Rade; Krivokapić, Žarko; Miljković, Snežana

2011-01-01

The quality of life is a multidimensional concept, which is best expressed by the subjective well-being. Evaluation of the quality of life is the basis for measuring the well-being, and the determination of factors that determine the quality of life quality is the basis for its improvement. To evaluate and assess the determinants of the perceived quality of life of group distinguishing features which characterize demographic and socioeconomic factors. This was a cross-sectional study of a representative sample of the population in Serbia aged over 20 years (9479 examinees). The quality of life was expressed by the perception of well-being (pleasure of life). Data on the examinees (demographic and socioeconomic characteristics) were collected by using a questionnaire for adults of each household. To process, analyze and present the data, we used the methods of parametric descriptive statistics (mean value, standard deviation, coefficient of variation), variance analysis and factor analysis. Although men evaluated the quality of life with a slightly higher grading, there was no statistically significant difference in the evaluation of the quality of life in relation to the examinee's gender (p > 0.005). Among the examinees there was a high statistically significant difference in grading the quality of life depending on age, level of education, marital status and type of job (p < 0.001). In relation to the number of children, there was no statistically significant difference in he grading of the quality of life (p > 0.005). The quality of life is influenced by numerous factors that characterize each person (demographic and socioeconomic characteristics of individual). Determining factors of the quality of life are numerous and diverse, and the manner and the strength of their influence are variable.

Angiogenesis and lymphangiogenesis as prognostic factors after therapy in patients with cervical cancer

PubMed Central

Makarewicz, Roman; Kopczyńska, Ewa; Marszałek, Andrzej; Goralewska, Alina; Kardymowicz, Hanna

2012-01-01

Aim of the study This retrospective study attempts to evaluate the influence of serum vascular endothelial growth factor C (VEGF-C), microvessel density (MVD) and lymphatic vessel density (LMVD) on the result of tumour treatment in women with cervical cancer. Material and methods The research was carried out in a group of 58 patients scheduled for brachytherapy for cervical cancer. All women were patients of the Department and University Hospital of Oncology and Brachytherapy, Collegium Medicum in Bydgoszcz of Nicolaus Copernicus University in Toruń. VEGF-C was determined by means of a quantitative sandwich enzyme immunoassay using a human antibody VEGF-C ELISA produced by Bender MedSystem, enzyme-linked immunosorbent detecting the activity of human VEGF-C in body fluids. The measure for the intensity of angiogenesis and lymphangiogenesis in immunohistochemical reactions is the number of blood vessels within the tumour. Statistical analysis was done using Statistica 6.0 software (StatSoft, Inc. 2001). The Cox proportional hazards model was used for univariate and multivariate analyses. Univariate analysis of overall survival was performed as outlined by Kaplan and Meier. In all statistical analyses p < 0.05 (marked red) was taken as significant. Results In 51 patients who showed up for follow-up examination, the influence of the factors of angiogenesis, lymphangiogenesis, patients’ age and the level of haemoglobin at the end of treatment were assessed. Selected variables, such as patients’ age, lymph vessel density (LMVD), microvessel density (MVD) and the level of haemoglobin (Hb) before treatment were analysed by means of Cox logical regression as potential prognostic factors for lymph node invasion. The observed differences were statistically significant for haemoglobin level before treatment and the platelet number after treatment. The study revealed the following prognostic factors: lymph node status, FIGO stage, and kind of treatment. No statistically significant influence of angiogenic and lymphangiogenic factors on the prognosis was found. Conclusion Angiogenic and lymphangiogenic factors have no value in predicting response to radiotherapy in cervical cancer patients. PMID:23788848

Predicting Esophagitis After Chemoradiation Therapy for Non-Small Cell Lung Cancer: An Individual Patient Data Meta-Analysis

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

Palma, David A., E-mail: david.palma@uwo.ca; Senan, Suresh; Oberije, Cary

Purpose: Concurrent chemoradiation therapy (CCRT) improves survival compared with sequential treatment for locally advanced non-small cell lung cancer, but it increases toxicity, particularly radiation esophagitis (RE). Validated predictors of RE for clinical use are lacking. We performed an individual-patient-data meta-analysis to determine factors predictive of clinically significant RE. Methods and Materials: After a systematic review of the literature, data were obtained on 1082 patients who underwent CCRT, including patients from Europe, North America, Asia, and Australia. Patients were randomly divided into training and validation sets (2/3 vs 1/3 of patients). Factors predictive of RE (grade ≥2 and grade ≥3) weremore » assessed using logistic modeling, with the concordance statistic (c statistic) used to evaluate the performance of each model. Results: The median radiation therapy dose delivered was 65 Gy, and the median follow-up time was 2.1 years. Most patients (91%) received platinum-containing CCRT regimens. The development of RE was common, scored as grade 2 in 348 patients (32.2%), grade 3 in 185 (17.1%), and grade 4 in 10 (0.9%). There were no RE-related deaths. On univariable analysis using the training set, several baseline factors were statistically predictive of RE (P<.05), but only dosimetric factors had good discrimination scores (c > .60). On multivariable analysis, the esophageal volume receiving ≥60 Gy (V60) alone emerged as the best predictor of grade ≥2 and grade ≥3 RE, with good calibration and discrimination. Recursive partitioning identified 3 risk groups: low (V60 <0.07%), intermediate (V60 0.07% to 16.99%), and high (V60 ≥17%). With use of the validation set, the predictive model performed inferiorly for the grade ≥2 endpoint (c = .58) but performed well for the grade ≥3 endpoint (c = .66). Conclusions: Clinically significant RE is common, but life-threatening complications occur in <1% of patients. Although several factors are statistically predictive of RE, the V60 alone provides the best predictive ability. Efforts to reduce the V60 should be prioritized, with further research needed to identify and validate new predictive factors.« less

Text mining factor analysis (TFA) in green tea patent data

NASA Astrophysics Data System (ADS)

Rahmawati, Sela; Suprijadi, Jadi; Zulhanif

2017-03-01

Factor analysis has become one of the most widely used multivariate statistical procedures in applied research endeavors across a multitude of domains. There are two main types of analyses based on factor analysis: Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA). Both EFA and CFA aim to observed relationships among a group of indicators with a latent variable, but they differ fundamentally, a priori and restrictions made to the factor model. This method will be applied to patent data technology sector green tea to determine the development technology of green tea in the world. Patent analysis is useful in identifying the future technological trends in a specific field of technology. Database patent are obtained from agency European Patent Organization (EPO). In this paper, CFA model will be applied to the nominal data, which obtain from the presence absence matrix. While doing processing, analysis CFA for nominal data analysis was based on Tetrachoric matrix. Meanwhile, EFA model will be applied on a title from sector technology dominant. Title will be pre-processing first using text mining analysis.

Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, paranoid personality disorder diagnosis: a unitary or a two-dimensional construct?

PubMed

Falkum, Erik; Pedersen, Geir; Karterud, Sigmund

2009-01-01

This article examines reliability and validity aspects of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) paranoid personality disorder (PPD) diagnosis. Patients with personality disorders (n = 930) from the Norwegian network of psychotherapeutic day hospitals, of which 114 had PPD, were included in the study. Frequency distribution, chi(2), correlations, reliability statistics, exploratory, and confirmatory factor analyses were performed. The distribution of PPD criteria revealed no distinct boundary between patients with and without PPD. Diagnostic category membership was obtained in 37 of 64 theoretically possible ways. The PPD criteria formed a separate factor in a principal component analysis, whereas a confirmatory factor analysis indicated that the DSM-IV PPD construct consists of 2 separate dimensions as follows: suspiciousness and hostility. The reliability of the unitary PPD scale was only 0.70, probably partly due to the apparent 2-dimensionality of the construct. Persistent unwarranted doubts about the loyalty of friends had the highest diagnostic efficiency, whereas unwarranted accusations of infidelity of partner had particularly poor indicator properties. The reliability and validity of the unitary PPD construct may be questioned. The 2-dimensional PPD model should be further explored.

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

PubMed Central

Zhu, Yun; Fan, Ruzong; Xiong, Momiao

2017-01-01

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

Impact of Damping Uncertainty on SEA Model Response Variance

NASA Technical Reports Server (NTRS)

Schiller, Noah; Cabell, Randolph; Grosveld, Ferdinand

2010-01-01

Statistical Energy Analysis (SEA) is commonly used to predict high-frequency vibroacoustic levels. This statistical approach provides the mean response over an ensemble of random subsystems that share the same gross system properties such as density, size, and damping. Recently, techniques have been developed to predict the ensemble variance as well as the mean response. However these techniques do not account for uncertainties in the system properties. In the present paper uncertainty in the damping loss factor is propagated through SEA to obtain more realistic prediction bounds that account for both ensemble and damping variance. The analysis is performed on a floor-equipped cylindrical test article that resembles an aircraft fuselage. Realistic bounds on the damping loss factor are determined from measurements acquired on the sidewall of the test article. The analysis demonstrates that uncertainties in damping have the potential to significantly impact the mean and variance of the predicted response.

Contextualizing Obesity and Diabetes Policy: Exploring a Nested Statistical and Constructivist Approach at the Cross-National and Subnational Government Level in the United States and Brazil

PubMed Central

Gómez, Eduardo J.

2017-01-01

Background: This article conducts a comparative national and subnational government analysis of the political, economic, and ideational constructivist contextual factors facilitating the adoption of obesity and diabetes policy. Methods: We adopt a nested analytical approach to policy analysis, which combines cross-national statistical analysis with subnational case study comparisons to examine theoretical prepositions and discover alternative contextual factors; this was combined with an ideational constructivist approach to policy-making. Results: Contrary to the existing literature, we found that with the exception of cross-national statistical differences in access to healthcare infrastructural resources, the growing burden of obesity and diabetes, rising healthcare costs and increased citizens’ knowledge had no predictive affect on the adoption of obesity and diabetes policy. We then turned to a subnational comparative analysis of the states of Mississippi in the United States and Rio Grande do Norte in Brazil to further assess the importance of infrastructural resources, at two units of analysis: the state governments versus rural municipal governments. Qualitative evidence suggests that differences in subnational healthcare infrastructural resources were insufficient for explaining policy reform processes, highlighting instead other potentially important factors, such as state-civil societal relationships and policy diffusion in Mississippi, federal policy intervention in Rio Grande do Norte, and politicians’ social construction of obesity and the resulting differences in policy roles assigned to the central government. Conclusion: We conclude by underscoring the complexity of subnational policy responses to obesity and diabetes, the importance of combining resource and constructivist analysis for better understanding the context of policy reform, while underscoring the potential lessons that the United States can learn from Brazil. PMID:29179290

Factors Influencing Stress, Burnout, and Retention of Secondary Teachers

ERIC Educational Resources Information Center

Fisher, Molly H.

2011-01-01

This study examines the stress, burnout, satisfaction, and preventive coping skills of nearly 400 secondary teachers to determine variables contributing to these major factors influencing teachers. Analysis of Variance (ANOVA) statistics were conducted that found the burnout levels between new and experienced teachers are significantly different,…

Verbal Neuropsychological Functions in Aphasia: An Integrative Model

ERIC Educational Resources Information Center

Vigliecca, Nora Silvana; Báez, Sandra

2015-01-01

A theoretical framework which considers the verbal functions of the brain under a multivariate and comprehensive cognitive model was statistically analyzed. A confirmatory factor analysis was performed to verify whether some recognized aphasia constructs can be hierarchically integrated as latent factors from a homogenously verbal test. The Brief…

Non-Cognitive Factor Relationships to Hybrid Doctoral Student Self-Efficacy

ERIC Educational Resources Information Center

Egbert, Jessica Dalby; Gomez, Frank; Li, Wenling; Pennington, Sandra L.

2015-01-01

Statistical analysis of data gathered from 139 healthcare doctoral students revealed three key findings regarding non-cognitive factor relationships to hybrid doctoral student self-efficacy between online (web-based) and on-campus course components. First, student experiences significantly differed between online and on-campus course components…

Should I Stay or Should I Go? A Comparison Study of Intention to Leave among Public Child Welfare Systems with High and Low Turnover Rates

ERIC Educational Resources Information Center

Strolin-Goltzman, Jessica

2008-01-01

This comparison study analyzes the commonalties, similarities, and differences on supervisory and organizational factors between a group of high turnover systems and a group of low turnover systems. Significant differences on organizational factors, but not on supervisory factors, emerged from the statistical analysis. Additionally, this study…

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

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

Determinants of health care expenditures and the contribution of associated factors: 16 cities and provinces in Korea, 2003-2010.

PubMed

Han, Kimyoung; Cho, Minho; Chun, Kihong

2013-11-01

The purpose of this study was to classify determinants of cost increases into two categories, negotiable factors and non-negotiable factors, in order to identify the determinants of health care expenditure increases and to clarify the contribution of associated factors selected based on a literature review. The data in this analysis was from the statistical yearbooks of National Health Insurance Service, the Economic Index from Statistics Korea and regional statistical yearbooks. The unit of analysis was the annual growth rate of variables of 16 cities and provinces from 2003 to 2010. First, multiple regression was used to identify the determinants of health care expenditures. We then used hierarchical multiple regression to calculate the contribution of associated factors. The changes of coefficients (R(2)) of predictors, which were entered into this analysis step by step based on the empirical evidence of the investigator could explain the contribution of predictors to increased medical cost. Health spending was mainly associated with the proportion of the elderly population, but the Medicare Economic Index (MEI) showed an inverse association. The contribution of predictors was as follows: the proportion of elderly in the population (22.4%), gross domestic product (GDP) per capita (4.5%), MEI (-12%), and other predictors (less than 1%). As Baby Boomers enter retirement, an increasing proportion of the population aged 65 and over and the GDP will continue to increase, thus accelerating the inflation of health care expenditures and precipitating a crisis in the health insurance system. Policy makers should consider providing comprehensive health services by an accountable care organization to achieve cost savings while ensuring high-quality care.

Exploring item and higher order factor structure with the Schmid-Leiman solution: syntax codes for SPSS and SAS.

PubMed

Wolff, Hans-Georg; Preising, Katja

2005-02-01

To ease the interpretation of higher order factor analysis, the direct relationships between variables and higher order factors may be calculated by the Schmid-Leiman solution (SLS; Schmid & Leiman, 1957). This simple transformation of higher order factor analysis orthogonalizes first-order and higher order factors and thereby allows the interpretation of the relative impact of factor levels on variables. The Schmid-Leiman solution may also be used to facilitate theorizing and scale development. The rationale for the procedure is presented, supplemented by syntax codes for SPSS and SAS, since the transformation is not part of most statistical programs. Syntax codes may also be downloaded from www.psychonomic.org/archive/.

Career Issues in HRD.

ERIC Educational Resources Information Center

1999

This document contains four symposium papers on career issues in human resource development (HRD). "Are Careers What They Used To Be: A Factor Analysis of Schein's Career Orientations Inventory" (Gerri Mukri, Sharon Confessore) is a statistical analysis of Schein's Career Orientations Inventory that finds the inventory to be a…

[Study on the factors impacting on early cochlear implantation between the eastern and western region of China].

PubMed

Xiao, Hanqiong; Li, Wei; Ma, Ruixia; Gong, Zhengpeng; Shi, Haibo; Li, Huawei; Chen, Bing; Jiang, Ye; Dai, Chunfu

2015-06-01

To describe tne regional different factors which impact on early cochlear implantation in prelingual deaf children between eastern and western regions of China. The charts of 113 children who received the cochlear implantation after 24 months old were reviewed and analyzed. Forty-five of them came from the eastern region (Jiangsu, Zhejiang or Shanghai) while 68 of them came from the western region (Ningxia or Guizhou). Parental interviews were conducted to collect information regarding the factors that impact on early cochlear implantation. Result:Based on the univariate logistic regression analysis, the odds ratio (OR) value of universal newborn hearing screening (UNHS) was 5. 481, which indicated the correlation of UNHS with early cochlear implantation is significant. There was statistical difference between the 2 groups (P<0. 01). For the financial burden, the OR value was 3. 521(strong correlation) and there was statistical difference between the 2 groups (P<0. 01). For the communication barriers and community location, the OR value was 0. 566 and 1. 128 respectively, and there was no statistical difference between the 2 groups (P>0. 05). The multivariate analysis indicated that the UNHS and financial burden are statistically different between the eastern and western regions (P=0. 00 and 0. 040 respectively). The UNHS and financial burden are statistically different between the eastern reinforced in the western region. In addition, the government and society should provide powerful policy and more financial support in the western region of China. The innovation of management system is also helpful to the early cochlear implantation.

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

PubMed

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

2014-05-01

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

Detailed Uncertainty Analysis of the ZEM-3 Measurement System

NASA Technical Reports Server (NTRS)

Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred

2014-01-01

The measurement of Seebeck coefficient and electrical resistivity are critical to the investigation of all thermoelectric systems. Therefore, it stands that the measurement uncertainty must be well understood to report ZT values which are accurate and trustworthy. A detailed uncertainty analysis of the ZEM-3 measurement system has been performed. The uncertainty analysis calculates error in the electrical resistivity measurement as a result of sample geometry tolerance, probe geometry tolerance, statistical error, and multi-meter uncertainty. The uncertainty on Seebeck coefficient includes probe wire correction factors, statistical error, multi-meter uncertainty, and most importantly the cold-finger effect. The cold-finger effect plagues all potentiometric (four-probe) Seebeck measurement systems, as heat parasitically transfers through thermocouple probes. The effect leads to an asymmetric over-estimation of the Seebeck coefficient. A thermal finite element analysis allows for quantification of the phenomenon, and provides an estimate on the uncertainty of the Seebeck coefficient. The thermoelectric power factor has been found to have an uncertainty of +9-14 at high temperature and 9 near room temperature.

Clinical features and risk factor analysis for lower extremity deep venous thrombosis in Chinese neurosurgical patients

PubMed Central

Guo, Fuyou; Shashikiran, Tagilapalli; Chen, Xi; Yang, Lei; Liu, Xianzhi; Song, Laijun

2015-01-01

Background: Deep venous thrombosis (DVT) contributes significantly to the morbidity and mortality of neurosurgical patients; however, no data regarding lower extremity DVT in postoperative Chinese neurosurgical patients have been reported. Materials and Methods: From January 2012 to December 2013, 196 patients without preoperative DVT who underwent neurosurgical operations were evaluated by color Doppler ultrasonography and D-dimer level measurements on the 3rd, 7th, and 14th days after surgery. Follow-up clinical data were recorded to determine the incidence of lower extremity DVT in postoperative neurosurgical patients and to analyze related clinical features. First, a single factor analysis, Chi-square test, was used to select statistically significant factors. Then, a multivariate analysis, binary logistic regression analysis, was used to determine risk factors for lower extremity DVT in postoperative neurosurgical patients. Results: Lower extremity DVT occurred in 61 patients, and the incidence of DVT was 31.1% in the enrolled Chinese neurosurgical patients. The common symptoms of DVT were limb swelling and lower extremity pain as well as increased soft tissue tension. The common sites of venous involvement were the calf muscle and peroneal and posterior tibial veins. The single factor analysis showed statistically significant differences in DVT risk factors, including age, hypertension, smoking status, operation time, a bedridden or paralyzed state, the presence of a tumor, postoperative dehydration, and glucocorticoid treatment, between the two groups (P < 0.05). The binary logistic regression analysis showed that an age greater than 50 years, hypertension, a bedridden or paralyzed state, the presence of a tumor, and postoperative dehydration were risk factors for lower extremity DVT in postoperative neurosurgical patients. Conclusions: Lower extremity DVT was a common complication following craniotomy in the enrolled Chinese neurosurgical patients. Multiple factors were identified as predictive of DVT in neurosurgical patients, including the presence of a tumor, an age greater than 50 years, hypertension, and immobility. PMID:26752303

Influencing factors of alexithymia in Chinese medical students: a cross-sectional study.

PubMed

Zhu, Yaxin; Luo, Ting; Liu, Jie; Qu, Bo

2017-04-04

A much higher prevalence of alexithymia has been reported in medical students compared with the general population, and alexithymia is a risk factor that increases vulnerability to mental disorders. Our aim was to evaluate the level of alexithymia in Chinese medical students and to explore its influencing factors. A cross-sectional study of 1,950 medical students at Shenyang Medical College was conducted in May 2014 to evaluate alexithymia in medical students using the Chinese version of the 20-item Toronto Alexithymia Scale (TAS-20). The reliability of the questionnaire was assessed by Cronbach's α coefficient and mean inter-item correlations. Confirmatory factor analysis (CFA) was used to evaluate construct validity. The relationships between alexithymia and influencing factors were examined using Student's t-test, analysis of variance, and multiple linear regression analysis. Statistical analysis was performed using SPSS 21.0. Of the 1,950 medical students, 1,886 (96.7%) completed questionnaires. Overall, Cronbach's α coefficient of the TAS-20 questionnaire was 0.868. The results of CFA showed that the original three-factor structure produced an acceptable fit to the data. By univariate analysis, gender, grade (academic year of study), smoking behavior, alcohol use, physical activity, history of living with parents during childhood, and childhood trauma were influencing factors of TAS-20 scores (p < 0.05). Multiple linear regression analysis showed that gender, physical activity, grade, living with parents, and childhood trauma also had statistically significant association with total TAS-20 score (p < 0.05). Gender, physical activity, grade, history of living with parents during childhood, and childhood trauma were all factors determining the level of alexithymia. To prevent alexithymia, it will be advisable to promote adequate physical activity and pay greater attention to male medical students and those who are in the final year of training.

A General Procedure to Assess the Internal Structure of a Noncognitive Measure--The Student360 Insight Program (S360) Time Management Scale. Research Report. ETS RR-11-42

ERIC Educational Resources Information Center

Ling, Guangming; Rijmen, Frank

2011-01-01

The factorial structure of the Time Management (TM) scale of the Student 360: Insight Program (S360) was evaluated based on a national sample. A general procedure with a variety of methods was introduced and implemented, including the computation of descriptive statistics, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA).…

An issue of literacy on pediatric arterial hypertension

NASA Astrophysics Data System (ADS)

Teodoro, M. Filomena; Romana, Andreia; Simão, Carla

2017-11-01

Arterial hypertension in pediatric age is a public health problem, whose prevalence has increased significantly over time. Pediatric arterial hypertension (PAH) is under-diagnosed in most cases, a highly prevalent disease, appears without notice with multiple consequences on the children's health and future adults. Children caregivers and close family must know the PAH existence, the negative consequences associated with it, the risk factors and, finally, must do prevention. In [12, 13] can be found a statistical data analysis using a simpler questionnaire introduced in [4] under the aim of a preliminary study about PAH caregivers acquaintance. A continuation of such analysis is detailed in [14]. An extension of such questionnaire was built and applied to a distinct population and it was filled online. The statistical approach is partially reproduced in the present work. Some statistical models were estimated using several approaches, namely multivariate analysis (factorial analysis), also adequate methods to analyze the kind of data in study.

Using structural equation modeling for network meta-analysis.

PubMed

Tu, Yu-Kang; Wu, Yun-Chun

2017-07-14

Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison. SEM provides a very flexible framework for univariate and multivariate meta-analysis, and its potential as a powerful tool for advanced meta-analysis is still to be explored.

Multivariate statistical analysis of heavy metal concentration in soils of Yelagiri Hills, Tamilnadu, India--spectroscopical approach.

PubMed

Chandrasekaran, A; Ravisankar, R; Harikrishnan, N; Satapathy, K K; Prasad, M V R; Kanagasabapathy, K V

2015-02-25

Anthropogenic activities increase the accumulation of heavy metals in the soil environment. Soil pollution significantly reduces environmental quality and affects the human health. In the present study soil samples were collected at different locations of Yelagiri Hills, Tamilnadu, India for heavy metal analysis. The samples were analyzed for twelve selected heavy metals (Mg, Al, K, Ca, Ti, Fe, V, Cr, Mn, Co, Ni and Zn) using energy dispersive X-ray fluorescence (EDXRF) spectroscopy. Heavy metals concentration in soil were investigated using enrichment factor (EF), geo-accumulation index (Igeo), contamination factor (CF) and pollution load index (PLI) to determine metal accumulation, distribution and its pollution status. Heavy metal toxicity risk was assessed using soil quality guidelines (SQGs) given by target and intervention values of Dutch soil standards. The concentration of Ni, Co, Zn, Cr, Mn, Fe, Ti, K, Al, Mg were mainly controlled by natural sources. Multivariate statistical methods such as correlation matrix, principal component analysis and cluster analysis were applied for the identification of heavy metal sources (anthropogenic/natural origin). Geo-statistical methods such as kirging identified hot spots of metal contamination in road areas influenced mainly by presence of natural rocks. Copyright © 2014 Elsevier B.V. All rights reserved.

Theoretical analysis of photon statistics on excited number of modes and dopant concentration in Er3+:Ti:LiNbO, waveguide amplifiers

NASA Astrophysics Data System (ADS)

Ducariu, A.; Constantin, G. C.; Puscas, N. N.

2005-08-01

In the small gain approximation and the unsaturated regime in this paper we report some original results concerning the evaluation of the Fano factor, statistical fluctuation and spontaneous emission factor which characterize the photon statistics on the number of excited modes, dopant concentration and power pumping in the single and double pass Er3+ - doped LiNbO, straight waveguide amplifiers pumped near 1484 nm using erfc, Gaussian and constant profile of the Er3+ ions in LiNbO, crystal. We demonstrated that for 50 mW input pump power the Poisson photon statistics are maintained in the above mentioned amplifiers for concentrations of the Er ions smaller than l026 m-3 and also high gains and low noise figures are achievable. The obtained results can be used for the design of optoelectronic integrated circuits.

Breast cancer lymphoscintigraphy: Factors associated with sentinel lymph node non visualization.

PubMed

Vaz, S C; Silva, Â; Sousa, R; Ferreira, T C; Esteves, S; Carvalho, I P; Ratão, P; Daniel, A; Salgado, L

2015-01-01

To evaluate factors associated with non identification of the sentinel lymph node (SLN) in lymphoscintigraphy of breast cancer patients and analyze the relationship with SLN metastases. A single-center, cross-sectional and retrospective study was performed. Forty patients with lymphoscintigraphy without sentinel lymph node identification (negative lymphoscintigraphy - NL) were enrolled. The control group included 184 patients with SLN identification (positive lymphoscintigraphy - PL). Evaluated factors were age, body mass index (BMI), tumor size, histology, localization, preoperative breast lesion hookwire (harpoon) marking and SLN metastases. The statistical analysis was performed with uni- and multivariate logistic regression models and matched-pairs analysis. Age (p=0.036) or having BMI (p=0.047) were the only factors significantly associated with NL. Being ≥60 years with a BMI ≥30 increased the odds of having a NL 2 and 3.8 times, respectively. Marking with hookwire seems to increase the likelihood of NL, but demonstrated statistical significance is lacking (p=0.087). The other tested variables did not affect the examination result. When controlling for age, BMI and marking with the harpoon, a significant association between lymph node metastization and NL was not found (p=0.565). The most important factors related with non identification of SLN in the patients were age, BMI and marking with hook wire. However, only the first two had statistical importance. When these variables were controlled, no association was found between NL and axillary metastases. Copyright © 2015 Elsevier España, S.L.U. and SEMNIM. All rights reserved.

Lungworm Infections in German Dairy Cattle Herds — Seroprevalence and GIS-Supported Risk Factor Analysis

PubMed Central

Schunn, Anne-Marie; Conraths, Franz J.; Staubach, Christoph; Fröhlich, Andreas; Forbes, Andrew; Strube, Christina

2013-01-01

In November 2008, a total of 19,910 bulk tank milk (BTM) samples were obtained from dairy farms from all over Germany, corresponding to about 20% of all German dairy herds, and analysed for antibodies against the bovine lungworm Dictyocaulus viviparus by use of the recombinant MSP-ELISA. A total number of 3,397 (17.1%; n = 19,910) BTM samples tested seropositive. The prevalences in individual German federal states varied between 0.0% and 31.2% positive herds. A geospatial map was drawn to show the distribution of seropositive and seronegative herds per postal code area. ELISA results were further analysed for associations with land-use and climate data. Bivariate statistical analysis was used to identify potential spatial risk factors for dictyocaulosis. Statistically significant positive associations were found between lungworm seropositive herds and the proportion of water bodies and grassed area per postal code area. Variables that showed a statistically significant association with a positive BTM test were included in a logistic regression model, which was further refined by controlled stepwise selection of variables. The low Pseudo R2 values (0.08 for the full model and 0.06 for the final model) and further evaluation of the model by ROC analysis indicate that additional, unrecorded factors (e.g. management factors) or random effects may substantially contribute to lungworm infections in dairy cows. Veterinarians should include lungworms in the differential diagnosis of respiratory disease in dairy cattle, particularly those at pasture. Monitoring of herds through BTM screening for antibodies can help farmers and veterinarians plan and implement appropriate control measures. PMID:24040243

A retrospective analysis on patients at high-risk for obstructive sleep apnea undergoing ear, nose, and throat surgeries.

PubMed

Woodling, Karina; Fiorda-Diaz, Juan; Otto, Bradley A; Barnes, Christie A; Uribe, Alberto A; Bergese, Sergio D; Yildiz, Vedat; Stoicea, Nicoleta; Guertin, Michael G

2018-02-01

Obstructive sleep apnea (OSA) may be related to episodes of oxygen de-saturation, hypercapnia, cardiovascular dysfunction, cor-pulmonale, and pulmonary hypertension. STOP-BANG is an acronym for eight specific questions used to assess the likelihood of OSA. If the individual exhibits three or more of these indicators, he/she should be considered to be at high risk for OSA complications. Therefore, the decision of proceeding with inpatient versus outpatient ENT surgery still remains controversial. The primary objective of the study was to identify and correlate desaturation (SPO2 <90%) episodes and risk factors. We conducted a single-center retrospective study between October 1, 2011 and August 31, 2014 in order to identify postoperative complications during the first 24 hours that justify postoperative monitoring and hospital admission. A total of 292 subjects were included for data analysis. Patients were divided into two groups based on the number of OSA risk factors: group A with 3-4 risk factors (n = 166), and group B with ≥5 risk factors (n = 126). The following information was collected: demographics, ASA, preoperative STOP-BANG score, length of surgery, intraoperative complications, opioid consumption, post anesthesia care unit (PACU) and overall length of stay, supplemental oxygen requirement, oxygen desaturation, and postoperative opioid consumption. No statistically significant difference was found when comparing demographic variables between both groups. All STOP-BANG variables showed statistical significance. PACU and inpatient variables were similar among both groups, with the exception of length of hospital stay (longer stay in group B when compared to group A [ p  = 0.003]). Desaturation differences between both groups during PACU were statistically significant ( p  = 0.008). A post-hoc analysis showed a 0% incidence of overall desaturation in the group with three STOP-BANG indicators. Our retrospective analysis concluded that patients diagnosed with three STOP-BANG risk factors did not experience postoperative complications and hospital admission was not justified. 4.

A statistical approach to optimizing concrete mixture design.

PubMed

Ahmad, Shamsad; Alghamdi, Saeid A

2014-01-01

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

A Statistical Approach to Optimizing Concrete Mixture Design

PubMed Central

Alghamdi, Saeid A.

2014-01-01

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

Latent structure of the Wisconsin Card Sorting Test: a confirmatory factor analytic study.

PubMed

Greve, Kevin W; Stickle, Timothy R; Love, Jeffrey M; Bianchini, Kevin J; Stanford, Matthew S

2005-05-01

The present study represents the first large scale confirmatory factor analysis of the Wisconsin Card Sorting Test (WCST). The results generally support the three factor solutions reported in the exploratory factor analysis literature. However, only the first factor, which reflects general executive functioning, is statistically sound. The secondary factors, while likely reflecting meaningful cognitive abilities, are less stable except when all subjects complete all 128 cards. It is likely that having two discontinuation rules for the WCST has contributed to the varied factor analytic solutions reported in the literature and early discontinuation may result in some loss of useful information. Continued multivariate research will be necessary to better clarify the processes underlying WCST performance and their relationships to one another.

Development and validity of a scale to measure workplace culture of health.

PubMed

Kwon, Youngbum; Marzec, Mary L; Edington, Dee W

2015-05-01

To describe the development of and test the validity and reliability of the Workplace Culture of Health (COH) scale. Exploratory factor analysis and confirmatory factor analysis were performed on data from a health care organization (N = 627). To verify the factor structure, confirmatory factor analysis was performed on a second data set from a medical equipment manufacturer (N = 226). The COH scale included a structure of five orthogonal factors: senior leadership and polices, programs and rewards, quality assurance, supervisor support, and coworker support. With regard to construct validity (convergent and discriminant) and reliability, two different US companies showed the same factorial structure, satisfactory fit statistics, and suitable internal and external consistency. The COH scale represents a reliable and valid scale to assess the workplace environment and culture for supporting health.

Application of statistical experimental design to study the formulation variables influencing the coating process of lidocaine liposomes.

PubMed

González-Rodríguez, M L; Barros, L B; Palma, J; González-Rodríguez, P L; Rabasco, A M

2007-06-07

In this paper, we have used statistical experimental design to investigate the effect of several factors in coating process of lidocaine hydrochloride (LID) liposomes by a biodegradable polymer (chitosan, CH). These variables were the concentration of CH coating solution, the dripping rate of this solution on the liposome colloidal dispersion, the stirring rate, the time since the liposome production to the liposome coating and finally the amount of drug entrapped into liposomes. The selected response variables were drug encapsulation efficiency (EE, %), coating efficiency (CE, %) and zeta potential. Liposomes were obtained by thin-layer evaporation method. They were subsequently coated with CH according the experimental plan provided by a fractional factorial (2(5-1)) screening matrix. We have used spectroscopic methods to determine the zeta potential values. The EE (%) assay was carried out in dialysis bags and the brilliant red probe was used to determine CE (%) due to its property of forming molecular complexes with CH. The graphic analysis of the effects allowed the identification of the main formulation and technological factors by the analysis of the selected responses and permitted the determination of the proper level of these factors for the response improvement. Moreover, fractional design allowed quantifying the interactions between the factors, which will consider in next experiments. The results obtained pointed out that LID amount was the predominant factor that increased the drug entrapment capacity (EE). The CE (%) response was mainly affected by the concentration of the CH solution and the stirring rate, although all the interactions between the main factors have statistical significance.

[Analysis on influencing factor of the complications of percutaneous dilational tracheotomy].

PubMed

Zhai, Xiang; Zhang, Jinling; Hang, Wei; Wang, Ming; Shi, Zhan; Mi, Yue; Hu, Yunlei; Liu, Gang

2015-01-01

To Analyze the influence factors on the complications of percutaneous dilational tracheotomy. Between August 2008 and February 2014, there were 3 450 patients with the indications of tracheotomy accepted percutaneous dilational tracheostomy, mainly using percutaneous dilational and percutaneous guide wire forceps in these cases. Statistical analysis was performed by SPSS 19.0 software on postoperative complications, the possible influence factors including age, gender, etiology, preoperative hypoxia, obesity, preoperative pulmonary infection, state of consciousness, operation method, operation doctor and whether with tracheal intubation. Among 3 450 patients, there were 164 cases with intraoperative or postoperative complications, including postoperative bleeding in 74 cases (2.14%), subcutaneous emphysema in 54 cases (1.57%), wound infection in 16 cases (0.46%), pneumothorax in 6 cases (0.17%), mediastinal emphysema in 5 cases (0.14%), operation failed and change to conventional incision in 4 cases (0.12%), tracheoesophageal fistula in 2 cases (0.06%), death in 3 cases(0.09%).Obesity, etiology, preoperative hypoxia, preoperative pulmonary infection, state of consciousness and operation method were the main influence factors, with significant statistical difference (χ(2) value was 0.010, 0.000, 0.002, 0.000, 0.000, 0.000, all P < 0.05). Gender, age, operation doctor and whether there was the endotracheal intubation were not the main influence factors. There was no significant statistical difference (P > 0.05). Although percutaneous dilational tracheostomy is safe, but the complications can also happen. In order to reduce the complications, it is need to pay attention to the factors of obesity, etiology, preoperative hypoxia, preoperative pulmonary infection, state of consciousness and operation method.

A risk-based approach to management of leachables utilizing statistical analysis of extractables.

PubMed

Stults, Cheryl L M; Mikl, Jaromir; Whelehan, Oliver; Morrical, Bradley; Duffield, William; Nagao, Lee M

2015-04-01

To incorporate quality by design concepts into the management of leachables, an emphasis is often put on understanding the extractable profile for the materials of construction for manufacturing disposables, container-closure, or delivery systems. Component manufacturing processes may also impact the extractable profile. An approach was developed to (1) identify critical components that may be sources of leachables, (2) enable an understanding of manufacturing process factors that affect extractable profiles, (3) determine if quantitative models can be developed that predict the effect of those key factors, and (4) evaluate the practical impact of the key factors on the product. A risk evaluation for an inhalation product identified injection molding as a key process. Designed experiments were performed to evaluate the impact of molding process parameters on the extractable profile from an ABS inhaler component. Statistical analysis of the resulting GC chromatographic profiles identified processing factors that were correlated with peak levels in the extractable profiles. The combination of statistically significant molding process parameters was different for different types of extractable compounds. ANOVA models were used to obtain optimal process settings and predict extractable levels for a selected number of compounds. The proposed paradigm may be applied to evaluate the impact of material composition and processing parameters on extractable profiles and utilized to manage product leachables early in the development process and throughout the product lifecycle.

SOME CHARACTERISTICS OF THE ORAL CAVITY AND TEETH OF COSMONAUTS ON MISSIONS TO THE INTERNATIONAL SPACE STATION.

PubMed

Ilyin, V K; Shumilina, G A; Solovieva, Z O; Nosovsky, A M; Kaminskaya, E V

Earlier studies were furthered by examination of parodentium anaerobic microbiota and investigation of gingival liquid immunological factors in space flight. Immunoglobulins were measured using the .enzyme immunoassay (EM). The qualitative content of keya parodentium pathogens is determined with state-of-the-art molecular biology technologies such as the polymerase chain reaction. Statistical data processing was performed using the principle component analysis and ensuing standard statistical analysis. Thereupon, recommendations on cosmonaut's oral and dental hygiene during space mission were developed.

Lower education level is a major risk factor for peritonitis incidence in chronic peritoneal dialysis patients: a retrospective cohort study with 12-year follow-up.

PubMed

Chern, Yahn-Bor; Ho, Pei-Shan; Kuo, Li-Chueh; Chen, Jin-Bor

2013-01-01

Peritoneal dialysis (PD)-related peritonitis remains an important complication in PD patients, potentially causing technique failure and influencing patient outcome. To date, no comprehensive study in the Taiwanese PD population has used a time-dependent statistical method to analyze the factors associated with PD-related peritonitis. Our single-center retrospective cohort study, conducted in southern Taiwan between February 1999 and July 2010, used time-dependent statistical methods to analyze the factors associated with PD-related peritonitis. The study recruited 404 PD patients for analysis, 150 of whom experienced at least 1 episode of peritonitis during the follow-up period. The incidence rate of peritonitis was highest during the first 6 months after PD start. A comparison of patients in the two groups (peritonitis vs null-peritonitis) by univariate analysis showed that the peritonitis group included fewer men (p = 0.048) and more patients of older age (≥65 years, p = 0.049). In addition, patients who had never received compulsory education showed a statistically higher incidence of PD-related peritonitis in the univariate analysis (p = 0.04). A proportional hazards model identified education level (less than elementary school vs any higher education level) as having an independent association with PD-related peritonitis [hazard ratio (HR): 1.45; 95% confidence interval (CI): 1.01 to 2.06; p = 0.045). Comorbidities measured using the Charlson comorbidity index (score >2 vs ≤2) showed borderline statistical significance (HR: 1.44; 95% CI: 1.00 to 2.13; p = 0.053). A lower education level is a major risk factor for PD-related peritonitis independent of age, sex, hypoalbuminemia, and comorbidities. Our study emphasizes that a comprehensive PD education program is crucial for PD patients with a lower education level.

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

PubMed

Hoyle, R H

1991-02-01

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

Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures

PubMed Central

Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.

2016-01-01

Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology. PMID:27014147

Teaching Research Methods and Statistics in eLearning Environments: Pedagogy, Practical Examples, and Possible Futures.

PubMed

Rock, Adam J; Coventry, William L; Morgan, Methuen I; Loi, Natasha M

2016-01-01

Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology.

Weighing of risk factors for penetrating keratoplasty graft failure: application of Risk Score System.

PubMed

Tourkmani, Abdo Karim; Sánchez-Huerta, Valeria; De Wit, Guillermo; Martínez, Jaime D; Mingo, David; Mahillo-Fernández, Ignacio; Jiménez-Alfaro, Ignacio

2017-01-01

To analyze the relationship between the score obtained in the Risk Score System (RSS) proposed by Hicks et al with penetrating keratoplasty (PKP) graft failure at 1y postoperatively and among each factor in the RSS with the risk of PKP graft failure using univariate and multivariate analysis. The retrospective cohort study had 152 PKPs from 152 patients. Eighteen cases were excluded from our study due to primary failure (10 cases), incomplete medical notes (5 cases) and follow-up less than 1y (3 cases). We included 134 PKPs from 134 patients stratified by preoperative risk score. Spearman coefficient was calculated for the relationship between the score obtained and risk of failure at 1y. Univariate and multivariate analysis were calculated for the impact of every single risk factor included in the RSS over graft failure at 1y. Spearman coefficient showed statistically significant correlation between the score in the RSS and graft failure ( P <0.05). Multivariate logistic regression analysis showed no statistically significant relationship ( P >0.05) between diagnosis and lens status with graft failure. The relationship between the other risk factors studied and graft failure was significant ( P <0.05), although the results for previous grafts and graft failure was unreliable. None of our patients had previous blood transfusion, thus, it had no impact. After the application of multivariate analysis techniques, some risk factors do not show the expected impact over graft failure at 1y.

Weighing of risk factors for penetrating keratoplasty graft failure: application of Risk Score System

PubMed Central

Tourkmani, Abdo Karim; Sánchez-Huerta, Valeria; De Wit, Guillermo; Martínez, Jaime D.; Mingo, David; Mahillo-Fernández, Ignacio; Jiménez-Alfaro, Ignacio

2017-01-01

AIM To analyze the relationship between the score obtained in the Risk Score System (RSS) proposed by Hicks et al with penetrating keratoplasty (PKP) graft failure at 1y postoperatively and among each factor in the RSS with the risk of PKP graft failure using univariate and multivariate analysis. METHODS The retrospective cohort study had 152 PKPs from 152 patients. Eighteen cases were excluded from our study due to primary failure (10 cases), incomplete medical notes (5 cases) and follow-up less than 1y (3 cases). We included 134 PKPs from 134 patients stratified by preoperative risk score. Spearman coefficient was calculated for the relationship between the score obtained and risk of failure at 1y. Univariate and multivariate analysis were calculated for the impact of every single risk factor included in the RSS over graft failure at 1y. RESULTS Spearman coefficient showed statistically significant correlation between the score in the RSS and graft failure (P<0.05). Multivariate logistic regression analysis showed no statistically significant relationship (P>0.05) between diagnosis and lens status with graft failure. The relationship between the other risk factors studied and graft failure was significant (P<0.05), although the results for previous grafts and graft failure was unreliable. None of our patients had previous blood transfusion, thus, it had no impact. CONCLUSION After the application of multivariate analysis techniques, some risk factors do not show the expected impact over graft failure at 1y. PMID:28393027

Rasch Based Analysis of Oral Proficiency Test Data.

ERIC Educational Resources Information Center

Nakamura, Yuji

2001-01-01

This paper examines the rating scale data of oral proficiency tests analyzed by a Rasch Analysis focusing on an item map and factor analysis. In discussing the item map, the difficulty order of six items and students' answering patterns are analyzed using descriptive statistics and measures of central tendency of test scores. The data ranks the…

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

ERIC Educational Resources Information Center

Lewis, Kandia

2012-01-01

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

Review of U.S. Army Unmanned Aerial Systems Accident Reports: Analysis of Human Error Contributions

DTIC Science & Technology

2018-03-20

USAARL Report No. 2018-08 Review of U.S. Army Unmanned Aerial Systems Accident Reports: Analysis of Human Error Contributions By Kathryn A...3 Statistical Analysis Approach ..............................................................................................3 Results...1 Introduction The success of unmanned aerial systems (UAS) operations relies upon a variety of factors, including, but not limited to

Putting the "But" Back in Meta-Analysis: Issues Affecting the Validity of Quantitative Reviews.

ERIC Educational Resources Information Center

L'Hommedieu, Randi; And Others

Some of the frustrations inherent in trying to incorporate qualifications of statistical results into meta-analysis are reviewed, and some solutions are proposed to prevent the loss of information in meta-analytic reports. The validity of a meta-analysis depends on several factors, including the: thoroughness of the literature search; selection of…

Acceptability of Dative Argument Structure in Spanish: Assessing Semantic and Usage-Based Factors

ERIC Educational Resources Information Center

Reali, Florencia

2017-01-01

Multiple constraints, including semantic, lexical, and usage-based factors, have been shown to influence dative alternation across different languages. This work explores whether fine-grained statistics and semantic properties of the verb affect the acceptability of dative constructions in Spanish. First, a corpus analysis reveals that verbs of…

The Five-Factor Model of Personality Traits and Organizational Citizenship Behaviors: A Meta-Analysis

ERIC Educational Resources Information Center

Chiaburu, Dan S.; Oh, In-Sue; Berry, Christopher M.; Li, Ning; Gardner, Richard G.

2011-01-01

Using meta-analytic tests based on 87 statistically independent samples, we investigated the relationships between the five-factor model (FFM) of personality traits and organizational citizenship behaviors in both the aggregate and specific forms, including individual-directed, organization-directed, and change-oriented citizenship. We found that…

The Importance of Physical Fitness versus Physical Activity for Coronary Artery Disease Risk Factors: A Cross-Sectional Analysis.

ERIC Educational Resources Information Center

Young, Deborah Rohm; Steinhardt, Mary A.

1993-01-01

This cross-sectional study examined relationships among physical fitness, physical activity, and risk factors for coronary artery disease (CAD) in male police officers. Data from screenings and physical fitness assessments indicated physical activity must be sufficient to influence fitness before obtaining statistically significant risk-reducing…

Near-exact distributions for the block equicorrelation and equivariance likelihood ratio test statistic

NASA Astrophysics Data System (ADS)

Coelho, Carlos A.; Marques, Filipe J.

2013-09-01

In this paper the authors combine the equicorrelation and equivariance test introduced by Wilks [13] with the likelihood ratio test (l.r.t.) for independence of groups of variables to obtain the l.r.t. of block equicorrelation and equivariance. This test or its single block version may find applications in many areas as in psychology, education, medicine, genetics and they are important "in many tests of multivariate analysis, e.g. in MANOVA, Profile Analysis, Growth Curve analysis, etc" [12, 9]. By decomposing the overall hypothesis into the hypotheses of independence of groups of variables and the hypothesis of equicorrelation and equivariance we are able to obtain the expressions for the overall l.r.t. statistic and its moments. From these we obtain a suitable factorization of the characteristic function (c.f.) of the logarithm of the l.r.t. statistic, which enables us to develop highly manageable and precise near-exact distributions for the test statistic.

Software for Data Analysis with Graphical Models

NASA Technical Reports Server (NTRS)

Buntine, Wray L.; Roy, H. Scott

1994-01-01

Probabilistic graphical models are being used widely in artificial intelligence and statistics, for instance, in diagnosis and expert systems, as a framework for representing and reasoning with probabilities and independencies. They come with corresponding algorithms for performing statistical inference. This offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper illustrates the framework with an example and then presents some basic techniques for the task: problem decomposition and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.

Newly Graduated Nurses' Competence and Individual and Organizational Factors: A Multivariate Analysis.

PubMed

Numminen, Olivia; Leino-Kilpi, Helena; Isoaho, Hannu; Meretoja, Riitta

2015-09-01

To study the relationships between newly graduated nurses' (NGNs') perceptions of their professional competence, and individual and organizational work-related factors. A multivariate, quantitative, descriptive, correlation design was applied. Data collection took place in November 2012 with a national convenience sample of 318 NGNs representing all main healthcare settings in Finland. Five instruments measured NGNs' perceptions of their professional competence, occupational commitment, empowerment, practice environment, and its ethical climate, with additional questions on turnover intentions, job satisfaction, and demographics. Descriptive statistics summarized the demographic data, and inferential statistics multivariate path analysis modeling estimated the relationships between the variables. The strongest relationship was found between professional competence and empowerment, competence explaining 20% of the variance of empowerment. The explanatory power of competence regarding practice environment, ethical climate of the work unit, and occupational commitment, and competence's associations with turnover intentions, job satisfaction, and age, were statistically significant but considerably weaker. Higher competence and satisfaction with quality of care were associated with more positive perceptions of practice environment and its ethical climate as well as higher empowerment and occupational commitment. Apart from its association with empowerment, competence seems to be a rather independent factor in relation to the measured work-related factors. Further exploration would deepen the knowledge of this relationship, providing support for planning educational and developmental programs. Research on other individual and organizational factors is warranted to shed light on factors associated with professional competence in providing high-quality and safe care as well as retaining new nurses in the workforce. The study sheds light on the strength and direction of the significantly associated work-related factors. Nursing professional bodies, managers, and supervisors can use the findings in planning orientation programs and other occupational interventions for NGNs. © 2015 Sigma Theta Tau International.

Risk behaviours among early adolescents: risk and protective factors.

PubMed

Wang, Ruey-Hsia; Hsu, Hsiu-Yueh; Lin, Shu-Yuan; Cheng, Chung-Ping; Lee, Shu-Li

2010-02-01

This paper is a report of a study conducted to examine the influence of risk/protective factors on risk behaviours of early adolescents and whether protective factors moderate their impact. An understanding of how risk and protective factors operate to influence risk behaviours of early adolescents will better prepare nurses to perform interventions appropriately to reduce risk behaviours of early adolescents. A cross-sectional study was carried out, based on a sample of public junior high schools (from 7th to 9th grades) in one city and one county in Taiwan. An anonymous questionnaire designed to measure five risk factors, six protective factors and risk behaviours was administered from October 2006 to March 2007. Data from 878 students were used for the present analysis. Pearson's correlations, anova with random effect models, and generalized linear models were used to analyse the statistically significant explanatory variables for risk behaviours. Gender, perceived father's risk behaviour, perceived mother's risk behaviour, health self-efficacy, interaction of health self-efficacy and perceived peers' risk behaviour, and interaction of emotional regulation and perceived peers' risk behaviour were statistically significant explanatory variables of risk behaviours. Health self-efficacy and emotional regulation moderated the negative effects of peers' perceived risk behaviour on risk behaviours. All protective factors were negative statistically correlated with risk behaviours, and all risk factors positively statistically correlated with risk behaviours. Male adolescents should be considered an at-risk group for risk behaviour intervention. Nurses could provide early adolescents with training regarding health self-efficacy improvement, self-esteem enhancement, emotional regulation skills to reduce their risk behaviours.

Dual Level Statistical Investigation of Equilibrium Solubility in Simulated Fasted and Fed Intestinal Fluid

PubMed Central

2017-01-01

The oral route is the preferred option for drug administration but contains the inherent issue of drug absorption from the gastro-intestinal tract (GIT) in order to elicit systemic activity. A prerequisite for absorption is drug dissolution, which is dependent upon drug solubility in the variable milieu of GIT fluid, with poorly soluble drugs presenting a formulation and biopharmaceutical challenge. Multiple factors within GIT fluid influence solubility ranging from pH to the concentration and ratio of amphiphilic substances, such as phospholipid, bile salt, monoglyceride, and cholesterol. To aid in vitro investigation simulated intestinal fluids (SIF) covering the fasted and fed state have been developed. SIF media is complex and statistical design of experiment (DoE) investigations have revealed the range of solubility values possible within each state due to physiological variability along with the media factors and factor interactions which influence solubility. However, these studies require large numbers of experiments (>60) and are not feasible or sensible within a drug development setting. In the current study a smaller dual level, reduced experimental number (20) DoE providing three arms covering the fasted and fed states along with a combined analysis has been investigated. The results indicate that this small scale investigation is feasible and provides solubility ranges that encompass published data in human and simulated fasted and fed fluids. The measured fasted and fed solubility ranges are in agreement with published large scale DoE results in around half of the cases, with the differences due to changes in media composition between studies. Indicating that drug specific behaviors are being determined and that careful media factor and concentration level selection is required in order to determine a physiologically relevant solubility range. The study also correctly identifies the major single factor or factors which influence solubility but it is evident that lower significance factors (for example bile salt) are not picked up due to the lower sample number employed. A similar issue is present with factor interactions with only a limited number available for study and generally not determined to have a significant solubility impact due to the lower statistical power of the study. The study indicates that a reduced experimental number DoE is feasible, will provide solubility range results with identification of major solubility factors however statistical limitations restrict the analysis. The approach therefore represents a useful initial screening tool that can guide further in depth analysis of a drug’s behavior in gastrointestinal fluids. PMID:29072917

A study on phenomenology of Dhat syndrome in men in a general medical setting

PubMed Central

Prakash, Sathya; Sharan, Pratap; Sood, Mamta

2016-01-01

Background: “Dhat syndrome” is believed to be a culture-bound syndrome of the Indian subcontinent. Although many studies have been performed, many have methodological limitations and there is a lack of agreement in many areas. Aims: The aim is to study the phenomenology of “Dhat syndrome” in men and to explore the possibility of subtypes within this entity. Settings and Design: It is a cross-sectional descriptive study conducted at a sex and marriage counseling clinic of a tertiary care teaching hospital in Northern India. Materials and Methods: An operational definition and assessment instrument for “Dhat syndrome” was developed after taking all concerned stakeholders into account and review of literature. It was applied on 100 patients along with socio-demographic profile, Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale, Mini International Neuropsychiatric Interview, and Postgraduate Institute Neuroticism Scale. Statistical Analysis: For statistical analysis, descriptive statistics, group comparisons, and Pearson's product moment correlations were carried out. Factor analysis and cluster analysis were done to determine the factor structure and subtypes of “Dhat syndrome.” Results: A diagnostic and assessment instrument for “Dhat syndrome” has been developed and the phenomenology in 100 patients has been described. Both the health beliefs scale and associated symptoms scale demonstrated a three-factor structure. The patients with “Dhat syndrome” could be categorized into three clusters based on severity. Conclusions: There appears to be a significant agreement among various stakeholders on the phenomenology of “Dhat syndrome” although some differences exist. “Dhat syndrome” could be subtyped into three clusters based on severity. PMID:27385844

Contribution of artificial intelligence to the knowledge of prognostic factors in Hodgkin's lymphoma.

PubMed

Buciński, Adam; Marszałł, Michał Piotr; Krysiński, Jerzy; Lemieszek, Andrzej; Załuski, Jerzy

2010-07-01

Hodgkin's lymphoma is one of the most curable malignancies and most patients achieve a lasting complete remission. In this study, artificial neural network (ANN) analysis was shown to provide significant factors with regard to 5-year recurrence after lymphoma treatment. Data from 114 patients treated for Hodgkin's disease were available for evaluation and comparison. A total of 31 variables were subjected to ANN analysis. The ANN approach as an advanced multivariate data processing method was shown to provide objective prognostic data. Some of these prognostic factors are consistent or even identical to the factors evaluated earlier by other statistical methods.

An Application of M[subscript 2] Statistic to Evaluate the Fit of Cognitive Diagnostic Models

ERIC Educational Resources Information Center

Liu, Yanlou; Tian, Wei; Xin, Tao

2016-01-01

The fit of cognitive diagnostic models (CDMs) to response data needs to be evaluated, since CDMs might yield misleading results when they do not fit the data well. Limited-information statistic M[subscript 2] and the associated root mean square error of approximation (RMSEA[subscript 2]) in item factor analysis were extended to evaluate the fit of…

RANDOMIZATION PROCEDURES FOR THE ANALYSIS OF EDUCATIONAL EXPERIMENTS.

ERIC Educational Resources Information Center

COLLIER, RAYMOND O.

CERTAIN SPECIFIC ASPECTS OF HYPOTHESIS TESTS USED FOR ANALYSIS OF RESULTS IN RANDOMIZED EXPERIMENTS WERE STUDIED--(1) THE DEVELOPMENT OF THE THEORETICAL FACTOR, THAT OF PROVIDING INFORMATION ON STATISTICAL TESTS FOR CERTAIN EXPERIMENTAL DESIGNS AND (2) THE DEVELOPMENT OF THE APPLIED ELEMENT, THAT OF SUPPLYING THE EXPERIMENTER WITH MACHINERY FOR…

Logistic regression applied to natural hazards: rare event logistic regression with replications

NASA Astrophysics Data System (ADS)

Guns, M.; Vanacker, V.

2012-06-01

Statistical analysis of natural hazards needs particular attention, as most of these phenomena are rare events. This study shows that the ordinary rare event logistic regression, as it is now commonly used in geomorphologic studies, does not always lead to a robust detection of controlling factors, as the results can be strongly sample-dependent. In this paper, we introduce some concepts of Monte Carlo simulations in rare event logistic regression. This technique, so-called rare event logistic regression with replications, combines the strength of probabilistic and statistical methods, and allows overcoming some of the limitations of previous developments through robust variable selection. This technique was here developed for the analyses of landslide controlling factors, but the concept is widely applicable for statistical analyses of natural hazards.

[Methods of the multivariate statistical analysis of so-called polyetiological diseases using the example of coronary heart disease].

PubMed

Lifshits, A M

1979-01-01

General characteristics of the multivariate statistical analysis (MSA) is given. Methodical premises and criteria for the selection of an adequate MSA method applicable to pathoanatomic investigations of the epidemiology of multicausal diseases are presented. The experience of using MSA with computors and standard computing programs in studies of coronary arteries aterosclerosis on the materials of 2060 autopsies is described. The combined use of 4 MSA methods: sequential, correlational, regressional, and discriminant permitted to quantitate the contribution of each of the 8 examined risk factors in the development of aterosclerosis. The most important factors were found to be the age, arterial hypertension, and heredity. Occupational hypodynamia and increased fatness were more important in men, whereas diabetes melitus--in women. The registration of this combination of risk factors by MSA methods provides for more reliable prognosis of the likelihood of coronary heart disease with a fatal outcome than prognosis of the degree of coronary aterosclerosis.

Comparing statistical and machine learning classifiers: alternatives for predictive modeling in human factors research.

PubMed

Carnahan, Brian; Meyer, Gérard; Kuntz, Lois-Ann

2003-01-01

Multivariate classification models play an increasingly important role in human factors research. In the past, these models have been based primarily on discriminant analysis and logistic regression. Models developed from machine learning research offer the human factors professional a viable alternative to these traditional statistical classification methods. To illustrate this point, two machine learning approaches--genetic programming and decision tree induction--were used to construct classification models designed to predict whether or not a student truck driver would pass his or her commercial driver license (CDL) examination. The models were developed and validated using the curriculum scores and CDL exam performances of 37 student truck drivers who had completed a 320-hr driver training course. Results indicated that the machine learning classification models were superior to discriminant analysis and logistic regression in terms of predictive accuracy. Actual or potential applications of this research include the creation of models that more accurately predict human performance outcomes.

Factors determining access to oral health services among children aged less than 12 years in Peru.

PubMed

Azañedo, Diego; Hernández-Vásquez, Akram; Casas-Bendezú, Mixsi; Gutiérrez, César; Agudelo-Suárez, Andrés A; Cortés, Sandra

2017-01-01

Background: Understanding problems of access to oral health services requires knowledge of factors that determine access. This study aimed to evaluate factors that determine access to oral health services among children aged <12 years in Peru between 2014 and 2015. Methods: We performed a secondary data analysis of 71,614 Peruvian children aged <12 years and their caregivers. Data were obtained from the Survey on Demography and Family Health 2014-2015 (Encuesta Demográfica y de Salud Familiar - ENDES). Children's access to oral health services within the previous 6 months was used as the dependent variable (i.e. Yes/No), and the Andersen and col model was used to select independent variables. Predisposing (e.g., language spoken by  tutor or guardian, wealth level, caregivers' educational level, area of residence, natural region of residence, age, and sex) and enabling factors (e.g. type of health insurance) were considered. Descriptive statistics were calculated, and multivariate analysis was performed using generalized linear models (Poisson family). Results: Of all the children, 51% were males, 56% were aged <5 years, and 62.6% lived in urban areas. The most common type of health insurance was Integral Health Insurance (57.8%), and most respondents were in the first quintile of wealth (31.6%). Regarding caregivers, the most common educational level was high school (43.02%) and the most frequently spoken language was Spanish (88.4%). Univariate analysis revealed that all variables, except sex and primary educational level, were statistically significant. After adjustment, sex, area of residence, and language were insignificant, whereas the remaining variables were statistically significant. Conclusions: Wealth index, caregivers' education level, natural region of residence, age, and type of health insurance are factors that determine access to oral health services among children aged <12 years in Peru. These factors should be considered when devising strategies to mitigate against inequities in access to oral health services.

Factors determining access to oral health services among children aged less than 12 years in Peru

PubMed Central

Azañedo, Diego; Hernández-Vásquez, Akram; Casas-Bendezú, Mixsi; Gutiérrez, César; Agudelo-Suárez, Andrés A.; Cortés, Sandra

2017-01-01

Background: Understanding problems of access to oral health services requires knowledge of factors that determine access. This study aimed to evaluate factors that determine access to oral health services among children aged <12 years in Peru between 2014 and 2015. Methods: We performed a secondary data analysis of 71,614 Peruvian children aged <12 years and their caregivers. Data were obtained from the Survey on Demography and Family Health 2014-2015 (Encuesta Demográfica y de Salud Familiar - ENDES). Children’s access to oral health services within the previous 6 months was used as the dependent variable (i.e. Yes/No), and the Andersen and col model was used to select independent variables. Predisposing (e.g., language spoken by  tutor or guardian, wealth level, caregivers’ educational level, area of residence, natural region of residence, age, and sex) and enabling factors (e.g. type of health insurance) were considered. Descriptive statistics were calculated, and multivariate analysis was performed using generalized linear models (Poisson family). Results: Of all the children, 51% were males, 56% were aged <5 years, and 62.6% lived in urban areas. The most common type of health insurance was Integral Health Insurance (57.8%), and most respondents were in the first quintile of wealth (31.6%). Regarding caregivers, the most common educational level was high school (43.02%) and the most frequently spoken language was Spanish (88.4%). Univariate analysis revealed that all variables, except sex and primary educational level, were statistically significant. After adjustment, sex, area of residence, and language were insignificant, whereas the remaining variables were statistically significant. Conclusions: Wealth index, caregivers’ education level, natural region of residence, age, and type of health insurance are factors that determine access to oral health services among children aged <12 years in Peru. These factors should be considered when devising strategies to mitigate against inequities in access to oral health services. PMID:29527289

Reliability and validity of the workplace harassment questionnaire for Korean finance and service workers.

PubMed

Lee, Myeongjun; Kim, Hyunjung; Shin, Donghee; Lee, Sangyun

2016-01-01

Harassment means systemic and repeated unethical acts. Research on workplace harassment have been conducted widely and the NAQ-R has been widely used for the researches. But this tool, however the limitations in revealing differended in sub-factors depending on the culture and in reflecting that unique characteristics of the Koren society. So, The workplace harassment questionnaire for Korean finace and service workers has been developed to assess the level of personal harassment at work. This study aims to develop a tool to assess the level of personal harassment at work and to test its validity and reliability while examining specific characteristics of workplace harassment against finance and service workers in Korea. The framework of survey was established based on literature review, focused-group interview for the Korean finance and service workers. To verify its reliability, Cronbach's alpha coefficient was calculated; and to verify its validity, items and factors of the tool were analyzed. The correlation matrix analysis was examined to verify the tool's convergent validity and discriminant validity. Structural validity was verified by checking statistical significance in relation to the BDI-K. Cronbach's alpha coefficient of this survey was 0.93, which indicates a quite high level of reliability. To verify the appropriateness of this survey tool, its construct validity was examined through factor analysis. As a result of the factor analysis, 3 factors were extracted, explaining 56.5 % of the total variance. The loading values and communalities of the 20 items were 0.85 to 0.48 and 0.71 to 0.46. The convergent validity and discriminant validity were analyzed and rate of item discriminant validity was 100 %. Finally, for the concurrent validity, We examined the relationship between the WHI-KFSW and pschosocial stress by examining the correlation with the BDI-K. The results of chi-square test and multiple logistic analysis indicated that the correlation with the BDI-K was satatisctically significant. Workplace harassment in actual workplaces were investigated based on interviews, and the statistical analysis contributed to systematizing the types of actual workplace harassment. By statistical method, we developed the questionare, 20 items of 3 categories.

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

PubMed

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

2012-01-01

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

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

PubMed Central

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

2012-01-01

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

Using factor analysis to identify neuromuscular synergies during treadmill walking

NASA Technical Reports Server (NTRS)

Merkle, L. A.; Layne, C. S.; Bloomberg, J. J.; Zhang, J. J.

1998-01-01

Neuroscientists are often interested in grouping variables to facilitate understanding of a particular phenomenon. Factor analysis is a powerful statistical technique that groups variables into conceptually meaningful clusters, but remains underutilized by neuroscience researchers presumably due to its complicated concepts and procedures. This paper illustrates an application of factor analysis to identify coordinated patterns of whole-body muscle activation during treadmill walking. Ten male subjects walked on a treadmill (6.4 km/h) for 20 s during which surface electromyographic (EMG) activity was obtained from the left side sternocleidomastoid, neck extensors, erector spinae, and right side biceps femoris, rectus femoris, tibialis anterior, and medial gastrocnemius. Factor analysis revealed 65% of the variance of seven muscles sampled aligned with two orthogonal factors, labeled 'transition control' and 'loading'. These two factors describe coordinated patterns of muscular activity across body segments that would not be evident by evaluating individual muscle patterns. The results show that factor analysis can be effectively used to explore relationships among muscle patterns across all body segments to increase understanding of the complex coordination necessary for smooth and efficient locomotion. We encourage neuroscientists to consider using factor analysis to identify coordinated patterns of neuromuscular activation that would be obscured using more traditional EMG analyses.

Stress perception and social indicators for low back, shoulder and joint pains in Japan: national surveys in 1995 and 2001.

PubMed

Takeuchi, Takeaki; Nakao, Mutsuhiro; Nishikitani, Mariko; Yano, Eiji

2004-07-01

This study aims to clarify the effects of stress perception and related social indicators on three major musculoskeletal symptoms: low back, shoulder, and joint pains in a Japanese population. Twenty health-related variables (stress perception and 19 social indicators) and the three symptoms were obtained from the following Japanese national surveys: the Comprehensive Survey of Living Condition of the People on Health and Welfare, the System of Social and Demographic Statistics of Japan, and the Statistical Report on Health Administration Services. The results were compared among 46 Japanese prefectures in 1995 and 2001. By factor analysis, the 19 indicators were classified into three factors of urbanization, aging and life-regularity, and individualization. The prevalence of stress perception was significantly correlated to the 8 indicators of urbanization factor. Although simple correlation analysis revealed a significant relationship of stress perception only to shoulder pain (in both years) and low back pain (in 2001), the results of multiple regression analysis showed that stress perception and some urbanization factors were significantly associated with all the three symptoms in both years exclusive of joint pain in 1995. Taking the effects of urbanization into consideration, stress perception seems to be closely related to the complaints of musculoskeletal symptoms in Japan.

Coupling strength assumption in statistical energy analysis

PubMed Central

Lafont, T.; Totaro, N.

2017-01-01

This paper is a discussion of the hypothesis of weak coupling in statistical energy analysis (SEA). The examples of coupled oscillators and statistical ensembles of coupled plates excited by broadband random forces are discussed. In each case, a reference calculation is compared with the SEA calculation. First, it is shown that the main SEA relation, the coupling power proportionality, is always valid for two oscillators irrespective of the coupling strength. But the case of three subsystems, consisting of oscillators or ensembles of plates, indicates that the coupling power proportionality fails when the coupling is strong. Strong coupling leads to non-zero indirect coupling loss factors and, sometimes, even to a reversal of the energy flow direction from low to high vibrational temperature. PMID:28484335

Evaluation of Facility Management by Multivariate Statistics - Factor Analysis

NASA Astrophysics Data System (ADS)

Singovszki, Miloš; Vranayová, Zuzana

2013-06-01

Facility management is evolving, there is no exact than other sciences, although its development is fast forward. The knowledge and practical skills in facility management is not replaced, on the contrary, they complement each other. The existing low utilization of science in the field of facility management is mainly caused by the management of support activities are many variables and prevailing immediate reaction to the extraordinary situation arising from motives of those who have substantial experience and years of proven experience. Facility management is looking for a system that uses organized knowledge and will form the basis, which grows from a wide range of disciplines. Significant influence on its formation as a scientific discipline is the "structure, which follows strategy". The paper deals evaluate technology building as part of an facility management by multivariate statistic - factor analysis.

Forecasting obesity prevalence in Korean adults for the years 2020 and 2030 by the analysis of contributing factors.

PubMed

Baik, Inkyung

2018-06-01

There are few studies that forecast the future prevalence of obesity based on the predicted prevalence model including contributing factors. The present study aimed to identify factors associated with obesity and construct forecasting models including significant contributing factors to estimate the 2020 and 2030 prevalence of obesity and abdominal obesity. Panel data from the Korea National Health and Nutrition Examination Survey and national statistics from the Korean Statistical Information Service were used for the analysis. The study subjects were 17,685 male and 24,899 female adults aged 19 years or older. The outcome variables were the prevalence of obesity (body mass index ≥ 25 kg/m 2 ) and abdominal obesity (waist circumference ≥ 90 cm for men and ≥ 85 cm for women). Stepwise logistic regression analysis was used to select significant variables from potential exposures. The survey year, age, marital status, job status, income status, smoking, alcohol consumption, sleep duration, psychological factors, dietary intake, and fertility rate were found to contribute to the prevalence of obesity and abdominal obesity. Based on the forecasting models including these variables, the 2020 and 2030 estimates for obesity prevalence were 47% and 62% for men and 32% and 37% for women, respectively. The present study suggested an increased prevalence of obesity and abdominal obesity in 2020 and 2030. Lifestyle factors were found to be significantly associated with the increasing trend in obesity prevalence and, therefore, they may require modification to prevent the rising trend.

Vocational students' learning preferences: the interpretability of ipsative data.

PubMed

Smith, P J

2000-02-01

A number of researchers have argued that ipsative data are not suitable for statistical procedures designed for normative data. Others have argued that the interpretability of such analyses of ipsative data are little affected where the number of variables and the sample size are sufficiently large. The research reported here represents a factor analysis of the scores on the Canfield Learning Styles Inventory for 1,252 students in vocational education. The results of the factor analysis of these ipsative data were examined in a context of existing theory and research on vocational students and lend support to the argument that the factor analysis of ipsative data can provide sensibly interpretable results.

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.

Associated factors of radiation pneumonitis induced by precise radiotherapy in 186 elderly patients with esophageal cancer.

PubMed

Cui, Zhen; Tian, Ye; He, Bin; Li, Hongwei; Li, Duojie; Liu, Jingjing; Cai, Hanfei; Lou, Jianjun; Jiang, Hao; Shen, Xueming; Peng, Kaigui

2015-01-01

Radiation pneumonitis is one of the most severe complications of esophageal cancer. To explore the factors correlated to radiation pneumonitis induced by precise radiotherapy for elderly patients with esophageal cancer. The retrospective analysis was used to collect clinical data from 186 elderly patients with esophageal cancer. The incidence of radiation pneumonitis was observed, followed by statistical analysis through ANVON or multiple regression analysis. 27 in 186 cases of esophageal cancer suffered from radiation pneumonitis, with incidence of 14.52%. The single factor analysis showed that, Karnofsky performance status (KPS) score, chronic obstructive pulmonary disease, concurrent chemoradiotherapy, gross tumor volume (GTV) dose, lung V20, mean lung dose (MLD) and planning target volume (PTV) were associated with radiation pneumonitis. The logistic regression analysis indicated that, concurrent chemoradiotherapy, GTV dose, lung V20 and PTV were the independent factors of radiation pneumonitis. The concurrent chemoradiotherapy, GTV dose, lung V20, MLD and PTV are the major risk factors of radiation pneumonitis for elderly patients with esophageal cancer.

Temporal scaling and spatial statistical analyses of groundwater level fluctuations

NASA Astrophysics Data System (ADS)

Sun, H.; Yuan, L., Sr.; Zhang, Y.

2017-12-01

Natural dynamics such as groundwater level fluctuations can exhibit multifractionality and/or multifractality due likely to multi-scale aquifer heterogeneity and controlling factors, whose statistics requires efficient quantification methods. This study explores multifractionality and non-Gaussian properties in groundwater dynamics expressed by time series of daily level fluctuation at three wells located in the lower Mississippi valley, after removing the seasonal cycle in the temporal scaling and spatial statistical analysis. First, using the time-scale multifractional analysis, a systematic statistical method is developed to analyze groundwater level fluctuations quantified by the time-scale local Hurst exponent (TS-LHE). Results show that the TS-LHE does not remain constant, implying the fractal-scaling behavior changing with time and location. Hence, we can distinguish the potentially location-dependent scaling feature, which may characterize the hydrology dynamic system. Second, spatial statistical analysis shows that the increment of groundwater level fluctuations exhibits a heavy tailed, non-Gaussian distribution, which can be better quantified by a Lévy stable distribution. Monte Carlo simulations of the fluctuation process also show that the linear fractional stable motion model can well depict the transient dynamics (i.e., fractal non-Gaussian property) of groundwater level, while fractional Brownian motion is inadequate to describe natural processes with anomalous dynamics. Analysis of temporal scaling and spatial statistics therefore may provide useful information and quantification to understand further the nature of complex dynamics in hydrology.

[Risk factors associated with dystocic delivery].

PubMed

Romero Gutiérrez, Gustavo; Ríos López, Juan Carlos; Cortés Salim, Patricia; Ponce Ponce de León, Ana Lilia

2007-09-01

the dystocic delivery is a frequent complication and its perinatal repercussions vary from minor lesions to severe brain damage. It has been reported diverse factors associated with this medical complication. to identify the risk factors with significant association with dystocic delivery. a case-control study was carried out. There were included 750 patients, divided into 250 women with dystocic deliveries (cases) and 500 women with eutocic deliveries (controls). Demographic and clinical variables were registered. The statistical analysis was performed with percentages, arithmetic media, standard deviation, Student t test, chi2 and logistic regression analysis. An alpha value was set at 0.05. the factors with statistical significance were: advanced age (p < 0.001), major patient's height (p < 0.001), major new born's weight (p = 0.009), lower parity (p < 0.001), and prolonged duration of labor (p = 0.04). Other variables such as number of pregnancies, previous cesarean sections, spontaneous abortions, weight of the patient, weight earned during pregnancy, number of medical appointments during antenatal care, previous dystocic delivery, and premature rupture of the membranes, were not significant. there are clinical and demographic risk factors associated with dystocic delivery. To identify this risk factors during the antenatal care could diminish the frequency of dystocic deliveries and therefore to avoid the associated maternal-fetal complications.

[Risk factors for infection in total knee artrhoplasty, including previously unreported intraoperative fracture and deep venous thrombosis].

PubMed

de Dios, M; Cordero-Ampuero, J

2015-01-01

To carry out a statistical analysis on the significant risk factors for deep late infection (prosthetic joint infection, PJI) in patients with a knee arthroplasty (TKA). A retrospective observational case-control study was conducted on a case series of 32 consecutive knee infections, using an analysis of all the risk factors reported in the literature. A control series of 100 randomly selected patients operated in the same Department of a University General Hospital during the same period of time, with no sign of deep infection in their knee arthroplasty during follow-up. Statistical comparisons were made using Pearson for qualitative and ANOVA for quantitative variables. The significant (p>0.05) factors found in the series were: Preoperative previous knee surgery, glucocorticoids, immunosuppressants, inflammatory arthritis. prolonged surgical time, inadequate antibiotic prophylaxis, intraoperative fractures. Postoperative secretion of the wound longer than 10 days, deep palpable haematoma, need for a new surgery, and deep venous thrombosis in lower limbs. Distant infections cutaneous, generalized sepsis, urinary tract, pneumonia, abdominal. This is the first report of intraoperative fractures and deep venous thrombosis as significantly more frequent factors in infected TKAs. Other previously described risk factors for TKA PJI are also confirmed. Copyright © 2014 SECOT. Published by Elsevier Espana. All rights reserved.

[Lake eutrophication modeling in considering climatic factors change: a review].

PubMed

Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

2012-11-01

Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

Two-sample statistics for testing the equality of survival functions against improper semi-parametric accelerated failure time alternatives: an application to the analysis of a breast cancer clinical trial.

PubMed

Broët, Philippe; Tsodikov, Alexander; De Rycke, Yann; Moreau, Thierry

2004-06-01

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests.

Antarctica Meta-Analysis: Psychosocial Factors Related to Long Duration Isolation and Confinement

NASA Technical Reports Server (NTRS)

Leveton, Lauren; Shea, Camille; Slack, Kelley J.; Keeton, Kathryn E.; Palinkas, Lawrence A.

2009-01-01

This meta-analysis is examining the psychological effects of wintering-over in Antarctica. As an isolated, confined, and extreme (ICE) environment, Antarctica provides invaluable opportunities to experience stressors more common to spaceflight than to the average person s everyday life. Increased prevalence of psychological symptoms, syndromes, and psychiatric disorders, as well as positive effects, are expected to be associated with various demographic and environmental factors. Implications for spaceflight are discussed. Findings from statistical review of the Antarctic articles will be shared.

Scores on the 16 Personality Factor Test and Success in College Calculus 1.

ERIC Educational Resources Information Center

Shaughnessy, Michael F.; And Others

This study explored personality variables measured by the 16 Personality Factor (16PF) test and their relevance to success, as defined by the final course grade, in college calculus courses with 94 students. Two personality variables were significant predictors of success as determined by the final course grade. A Statistical Analysis System…

A Pedagogical Approach to the Boltzmann Factor through Experiments and Simulations

ERIC Educational Resources Information Center

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

2009-01-01

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

School Performance, Cultural, Social and Personality Factors and Their Relationships with Majoring in Foreign and First Languages

ERIC Educational Resources Information Center

Khodadady, Ebrahim; Zabihi, Reza

2011-01-01

This study reports the performance of 419 undergraduate and graduate students on three questionnaires addressing their biodata, social and cultural capitals and personality factors. The statistical analysis of the students' diploma Grade Point Averages (GPAs) and monthly family income (MFI) showed that the GPAs and MFIs of students majoring in…

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

ERIC Educational Resources Information Center

Konold, Timothy R.; Glutting, Joseph J.

2008-01-01

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

Data-Mining Techniques in Detecting Factors Linked to Academic Achievement

ERIC Educational Resources Information Center

Martínez Abad, Fernando; Chaparro Caso López, Alicia A.

2017-01-01

In light of the emergence of statistical analysis techniques based on data mining in education sciences, and the potential they offer to detect non-trivial information in large databases, this paper presents a procedure used to detect factors linked to academic achievement in large-scale assessments. The study is based on a non-experimental,…

Design and statistical problems in prevention.

PubMed

Gullberg, B

1996-01-01

Clinical and epidemiological research in osteoporosis can benefit from using the methods and techniques established in the area of chronic disease epidemiology. However, attention has to be given to the special characteristics such as the multifactorial nature and the fact that the subjects usually are of high ages. In order to evaluate prevention it is of course first necessary to detect and confirm reversible risk factors. The advantage and disadvantage of different design (cross-sectional, cohort and case-control) are well known. The effects of avoidable biases, e.g. selection, observation and confounding have to be balanced against practical conveniences like time, expenses, recruitment etc. The translation of relative risks into population attributable risks (etiologic fractions, prevented fractions) are complex and are usually performed under unrealistic, simplified assumptions. The consequences of interactions (synergy) between risk factors are often neglected. The multifactorial structure requires application of more advanced multi-level statistical techniques. The common strategy in prevention to target a cluster of risk factors in order to avoid the multifactorial nature implies that in the end it is impossible to separate each unique factor. Experimental designs for evaluating prevention like clinical trials and intervention have to take into account the distinction between explanatory and pragmatic studies. An explanatory approach is similar to an idealized laboratory trial while the pragmatic design is more realistic, practical and has a general public health perspective. The statistical techniques to be used in osteoporosis research are implemented in easy available computer-packages like SAS, SPSS, BMDP and GLIM. In addition to the traditional logistic regression methods like Cox analysis and Poisson regression also analysis of repeated measurement and cluster analysis are relevant.

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

PubMed

Cleophas, Ton J

2016-01-01

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

Motivating factors among Iranian nurses

PubMed Central

Negarandeh, Reza; Dehghan-Nayeri, Nahid; Ghasemi, Elham

2015-01-01

Background: One of the most important challenges of Iranian health care system is “quality of care,” and it is assumed that motivated nurses are more ready to provide better care. There are limited studies investigating Iranian nurses’ motivations; however, factors which motivate them have not been studied yet. Identifying the motivating factors enables nurse managers to inspire nurses for continuous quality improvement. The aim of this study was to identify motivating factors for Iranian hospital nurses. Materials and Methods: This is a cross-sectional descriptive study in which 310 nurses working at 14 hospitals of Tehran University of Medical Sciences were selected by proportionate stratified random sampling. Data were collected in 2010 by a researcher-developed questionnaire. Descriptive statistics and independent t-test, analysis of variance, Tukey post-hoc test, Chi-Square and Fisher's exact test were used for statistical analysis by Statistical Package for Social Sciences (SPSS) version 16. Results: The mean score of motivation was 90.53 ± 10.76 (range: 59–121). Four motivating factors including “career development” (22.63 ± 5.66), “job characteristics” (34.29 ± 4), “job authority” (18.48 ± 2.79), and “recognition” (15.12 ± 2.5) were recognized. The least mean of the motivation score, considering the number of items, was 3.23 for career development, while the highest mean was 3.81 for job characteristics. Conclusions: The findings showed that motivation of nurses was at a medium level, which calls for improvement. The factors that have the greatest potential to motivate nurses were identified in this study and they can help managers to achieve the goal of continuous quality improvement. PMID:26257797

MUC4: a novel prognostic factor of oral squamous cell carcinoma.

PubMed

Hamada, Tomofumi; Wakamatsu, Tsunenobu; Miyahara, Mayumi; Nagata, Satoshi; Nomura, Masahiro; Kamikawa, Yoshiaki; Yamada, Norishige; Batra, Surinder K; Yonezawa, Suguru; Sugihara, Kazumasa

2012-04-15

MUC4 mucin is now known to be expressed in various normal and cancer tissues. We have previously reported that MUC4 expression is a novel prognostic factor in several malignant tumors; however, it has not been investigated in oral squamous cell carcinoma (OSCC). The aim of our study is to evaluate the prognostic significance of MUC4 expression in OSCC. We examined the expression profile of MUC4 in OSCC tissues from 150 patients using immunohistochemistry. Its prognostic significance in OSCC was statistically analyzed. MUC4 was expressed in 61 of the 150 patients with OSCC. MUC4 expression was significantly correlated with higher T classification (p = 0.0004), positive nodal metastasis (p = 0.049), advanced tumor stage (p = 0.002), diffuse invasion of cancer cells (p = 0.004) and patient's death (p = 0.004) in OSCC. Multivariate analysis showed that MUC4 expression (p = 0.011), tumor location (p = 0.032) and diffuse invasion (p = 0.009) were statistically significant risk factors. Backward stepwise multivariate analysis demonstrated MUC4 expression (p = 0.0015) and diffuse invasion (p = 0.018) to be statistically significant independent risk factors of poor survival in OSCC. The disease-free and overall survival of patients with MUC4 expression was significantly worse than those without MUC4 expression (p < 0.0001 and p = 0.0001). In addition, the MUC4 expression was a significant risk factor for local recurrence and subsequent nodal metastasis in OSCC (p = 0.017 and p = 0.0001). We first report MUC4 overexpression is an independent factor for poor prognosis of patients with OSCC; therefore, patients with OSCC showing positive MUC4 expression should be followed up carefully. Copyright © 2011 UICC.

Protein Sectors: Statistical Coupling Analysis versus Conservation

PubMed Central

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

2015-01-01

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

Space station software reliability analysis based on failures observed during testing at the multisystem integration facility

NASA Technical Reports Server (NTRS)

Tamayo, Tak Chai

1987-01-01

Quality of software not only is vital to the successful operation of the space station, it is also an important factor in establishing testing requirements, time needed for software verification and integration as well as launching schedules for the space station. Defense of management decisions can be greatly strengthened by combining engineering judgments with statistical analysis. Unlike hardware, software has the characteristics of no wearout and costly redundancies, thus making traditional statistical analysis not suitable in evaluating reliability of software. A statistical model was developed to provide a representation of the number as well as types of failures occur during software testing and verification. From this model, quantitative measure of software reliability based on failure history during testing are derived. Criteria to terminate testing based on reliability objectives and methods to estimate the expected number of fixings required are also presented.

Identifying drought response of semi-arid aeolian systems using near-surface luminescence profiles and changepoint analysis, Nebraska Sandhills.

NASA Astrophysics Data System (ADS)

Buckland, Catherine; Bailey, Richard; Thomas, David

2017-04-01

Two billion people living in drylands are affected by land degradation. Sediment erosion by wind and water removes fertile soil and destabilises landscapes. Vegetation disturbance is a key driver of dryland erosion caused by both natural and human forcings: drought, fire, land use, grazing pressure. A quantified understanding of vegetation cover sensitivities and resultant surface change to forcing factors is needed if the vegetation and landscape response to future climate change and human pressure are to be better predicted. Using quartz luminescence dating and statistical changepoint analysis (Killick & Eckley, 2014) this study demonstrates the ability to identify step-changes in depositional age of near-surface sediments. Lx/Tx luminescence profiles coupled with statistical analysis show the use of near-surface sediments in providing a high-resolution record of recent system response and aeolian system thresholds. This research determines how the environment has recorded and retained sedimentary evidence of drought response and land use disturbances over the last two hundred years across both individual landforms and the wider Nebraska Sandhills. Identifying surface deposition and comparing with records of climate, fire and land use changes allows us to assess the sensitivity and stability of the surface sediment to a range of forcing factors. Killick, R and Eckley, IA. (2014) "changepoint: An R Package for Changepoint Analysis." Journal of Statistical Software, (58) 1-19.

An Overview of Equal Educational Opportunities in Turkey: A Spatial Analysis of Classrooms in Rural and Urban Primary Schools

ERIC Educational Resources Information Center

Gökçe, Nazli; Kaya, Erdogan; Aktas, Semra Günay; Kantar, Yeliz Mert

2017-01-01

The number of students in a class is a primary factor affecting the quality of education. Therefore, this study examines the distribution of the number of students per class in rural and urban primary schools in Turkey, and efforts have been made to specify classroom needs. Statistical data was obtained from the Turkish Institute of Statistics and…

An exploratory factor analysis of nutritional biomarkers associated with major depression in pregnancy.

PubMed

Bodnar, Lisa M; Wisner, Katherine L; Luther, James F; Powers, Robert W; Evans, Rhobert W; Gallaher, Marcia J; Newby, P K

2012-06-01

Major depressive disorder (MDD) during pregnancy increases the risk of adverse maternal and infant outcomes. Maternal nutritional status may be a modifiable risk factor for antenatal depression. We evaluated the association between patterns in mid-pregnancy nutritional biomarkers and MDD. Prospective cohort study. Pittsburgh, Pennsylvania, USA. Women who enrolled at ≤20 weeks' gestation and had a diagnosis of MDD made with the Structured Clinical Interview for DSM-IV (Diagnostic and Statistical Manual of Mental Disorders, 4th edition) at 20-, 30- and 36-week study visits. A total of 135 women contributed 345 person-visits. Non-fasting blood drawn at enrolment was assayed for red cell essential fatty acids, plasma folate, homocysteine and ascorbic acid; serum 25-hydroxyvitamin D, retinol, vitamin E, carotenoids, ferritin and soluble transferrin receptors. Nutritional biomarkers were entered into principal components analysis. Three factors emerged: Factor 1, Essential Fatty Acids; Factor 2, Micronutrients; and Factor 3, Carotenoids. MDD was prevalent in 21·5 % of women. In longitudinal multivariable logistic models, there was no association between the Essential Fatty Acids or Micronutrients pattern and MDD either before or after adjustment for employment, education or pre-pregnancy BMI. In unadjusted analysis, women with factor scores for Carotenoids in the middle and upper tertiles were 60 % less likely than women in the bottom tertile to have MDD during pregnancy, but after adjustment for confounders the associations were no longer statistically significant. While meaningful patterns were derived using nutritional biomarkers, significant associations with MDD were not observed in multivariable adjusted analyses. Larger, more diverse samples are needed to understand nutrition-depression relationships during pregnancy.

Geographical distribution patterns of iodine in drinking-water and its associations with geological factors in Shandong Province, China.

PubMed

Gao, Jie; Zhang, Zhijie; Hu, Yi; Bian, Jianchao; Jiang, Wen; Wang, Xiaoming; Sun, Liqian; Jiang, Qingwu

2014-05-19

County-based spatial distribution characteristics and the related geological factors for iodine in drinking-water were studied in Shandong Province (China). Spatial autocorrelation analysis and spatial scan statistic were applied to analyze the spatial characteristics. Generalized linear models (GLMs) and geographically weighted regression (GWR) studies were conducted to explore the relationship between water iodine level and its related geological factors. The spatial distribution of iodine in drinking-water was significantly heterogeneous in Shandong Province (Moran's I = 0.52, Z = 7.4, p < 0.001). Two clusters for high iodine in drinking-water were identified in the south-western and north-western parts of Shandong Province by the purely spatial scan statistic approach. Both GLMs and GWR indicated a significantly global association between iodine in drinking-water and geological factors. Furthermore, GWR showed obviously spatial variability across the study region. Soil type and distance to Yellow River were statistically significant at most areas of Shandong Province, confirming the hypothesis that the Yellow River causes iodine deposits in Shandong Province. Our results suggested that the more effective regional monitoring plan and water improvement strategies should be strengthened targeting at the cluster areas based on the characteristics of geological factors and the spatial variability of local relationships between iodine in drinking-water and geological factors.

Prognostic value of inflammation-based scores in patients with osteosarcoma

PubMed Central

Liu, Bangjian; Huang, Yujing; Sun, Yuanjue; Zhang, Jianjun; Yao, Yang; Shen, Zan; Xiang, Dongxi; He, Aina

2016-01-01

Systemic inflammation responses have been associated with cancer development and progression. C-reactive protein (CRP), Glasgow prognostic score (GPS), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), and neutrophil-platelet score (NPS) have been shown to be independent risk factors in various types of malignant tumors. This retrospective analysis of 162 osteosarcoma cases was performed to estimate their predictive value of survival in osteosarcoma. All statistical analyses were performed by SPSS statistical software. Receiver operating characteristic (ROC) analysis was generated to set optimal thresholds; area under the curve (AUC) was used to show the discriminatory abilities of inflammation-based scores; Kaplan-Meier analysis was performed to plot the survival curve; cox regression models were employed to determine the independent prognostic factors. The optimal cut-off points of NLR, PLR, and LMR were 2.57, 123.5 and 4.73, respectively. GPS and NLR had a markedly larger AUC than CRP, PLR and LMR. High levels of CRP, GPS, NLR, PLR, and low level of LMR were significantly associated with adverse prognosis (P < 0.05). Multivariate Cox regression analyses revealed that GPS, NLR, and occurrence of metastasis were top risk factors associated with death of osteosarcoma patients. PMID:28008988

Recipient area folliculitis after follicular-unit transplantation: characterization of clinical features and analysis of associated factors.

PubMed

Bunagan, M J Kristine S; Pathomvanich, Damkerng; Laorwong, Kongkiat

2010-07-01

Postoperative recipient-area folliculitis may be a cause of less or delayed growth of transplanted hair and an obvious cause of distress to the patient. No study has been done to elaborate on its clinical features and assess possible factors that may correlate with its occurrence. To study the clinical features and possible factors that may be associated with the development of recipient-area folliculitis after follicular-unit transplantation (FUT). Retrospective analysis of 27 patients who developed folliculitis after FUT and 28 patients without such complication. Lesion onset ranged from 2 days to 6 months after FUT (mean 1.44 months). Lesions were mostly pustules that resolved without sequela. Statistical analysis showed that, in terms of patient characteristics (e.g., hair features, scalp condition) and the number of grafts transplanted, there was no statistically significant difference in assessed parameters between those with and without folliculitis (p<.05). Main clinical features of postoperative folliculitis consist mostly of few to moderate self-limited pustules. In this study, regardless of management, lesions healed without scarring and without affecting graft growth. Neither patient characteristics nor number of grafts transplanted was associated with this complication.

Intrinsic gait-related risk factors for Achilles tendinopathy in novice runners: a prospective study.

PubMed

Van Ginckel, Ans; Thijs, Youri; Hesar, Narmin Ghani Zadeh; Mahieu, Nele; De Clercq, Dirk; Roosen, Philip; Witvrouw, Erik

2009-04-01

The purpose of this prospective cohort study was to identify dynamic gait-related risk factors for Achilles tendinopathy (AT) in a population of novice runners. Prior to a 10-week running program, force distribution patterns underneath the feet of 129 subjects were registered using a footscan pressure plate while the subjects jogged barefoot at a comfortable self-selected pace. Throughout the program 10 subjects sustained Achilles tendinopathy of which three reported bilateral complaints. Sixty-six subjects were excluded from the statistical analysis. Therefore the statistical analysis was performed on the remaining sample of 63 subjects. Logistic regression analysis revealed a significant decrease in the total posterior-anterior displacement of the Centre Of Force (COF) (P=0.015) and a laterally directed force distribution underneath the forefoot at 'forefoot flat' (P=0.016) as intrinsic gait-related risk factors for Achilles tendinopathy in novice runners. These results suggest that, in contrast to the frequently described functional hyperpronation following a more inverted touchdown, a lateral foot roll-over following heel strike and diminished forward force transfer underneath the foot should be considered in the prevention of Achilles tendinopathy.

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.

Forest fires in Pennsylvania.

Treesearch

Donald A. Haines; William A. Main; Eugene F. McNamara

1978-01-01

Describes factors that contribute to forest fires in Pennsylvania. Includes an analysis of basic statistics; distribution of fires during normal, drought, and wet years; fire cause, fire activity by day-of-week; multiple-fire day; and fire climatology.

Railroad Classification Yard Technology Manual. Volume III. Freight Car Rollability

DOT National Transportation Integrated Search

1981-07-01

The report presents a survey of rolling resistance research, histograms of rolling resistance from five yards, a statistical regression analysis of causal factors affecting rolling resistance, procedures for constructing a rolling resistance histogra...

Prototype demonstration of a geographic information system application for seasonal analysis of traffic data : development of seasonal factors and seasonal adjustment of roadways

DOT National Transportation Integrated Search

1999-08-15

The Traffic Survey Unit plans to establish a methodology in which it can assign each Portable Traffic Counter (PTC) station a seasonal group profile through a means of statistical and geographical analysis. An ArcView Geographic Information Systems a...

Open Access Publishing Trend Analysis: Statistics beyond the Perception

ERIC Educational Resources Information Center

Poltronieri, Elisabetta; Bravo, Elena; Curti, Moreno; Maurizio Ferri,; Mancini, Cristina

2016-01-01

Introduction: The purpose of this analysis was twofold: to track the number of open access journals acquiring impact factor, and to investigate the distribution of subject categories pertaining to these journals. As a case study, journals in which the researchers of the National Institute of Health (Istituto Superiore di Sanità) in Italy have…

Multilevel Structural Equation Models for the Analysis of Comparative Data on Educational Performance

ERIC Educational Resources Information Center

Goldstein, Harvey; Bonnet, Gerard; Rocher, Thierry

2007-01-01

The Programme for International Student Assessment comparative study of reading performance among 15-year-olds is reanalyzed using statistical procedures that allow the full complexity of the data structures to be explored. The article extends existing multilevel factor analysis and structural equation models and shows how this can extract richer…

Arthrodesis following failed total knee arthroplasty: comprehensive review and meta-analysis of recent literature.

PubMed

Damron, T A; McBeath, A A

1995-04-01

With the increasing duration of follow up on total knee arthroplasties, more revision arthroplasties are being performed. When revision is not advisable, a salvage procedure such as arthrodesis or resection arthroplasty is indicated. This article provides a comprehensive review of the literature regarding arthrodesis following failed total knee arthroplasty. In addition, a statistical meta-analysis of five studies using modern arthrodesis techniques is presented. A statistically significant greater fusion rate with intramedullary nail arthrodesis compared to external fixation is documented. Gram negative and mixed infections are found to be significant risk factors for failure of arthrodesis.

An Investigation of the Overlap Between the Statistical Discrete Gust and the Power Spectral Density Analysis Methods

NASA Technical Reports Server (NTRS)

Perry, Boyd, III; Pototzky, Anthony S.; Woods, Jessica A.

1989-01-01

The results of a NASA investigation of a claimed Overlap between two gust response analysis methods: the Statistical Discrete Gust (SDG) Method and the Power Spectral Density (PSD) Method are presented. The claim is that the ratio of an SDG response to the corresponding PSD response is 10.4. Analytical results presented for several different airplanes at several different flight conditions indicate that such an Overlap does appear to exist. However, the claim was not met precisely: a scatter of up to about 10 percent about the 10.4 factor can be expected.

Lower back pain and absenteeism among professional public transport drivers.

PubMed

Kresal, Friderika; Roblek, Vasja; Jerman, Andrej; Meško, Maja

2015-01-01

Drivers in public transport are subjected to lower back pain. The reason for the pain is associated with the characteristics of the physical position imposed on the worker while performing the job. Lower back pain is the main cause of absenteeism among drivers. The present study includes 145 public transport drivers employed as professional drivers for an average of 14.14 years. Analysis of the data obtained in the study includes the basic descriptive statistics, χ(2) test and multiple regression analysis. Analysis of the incidence of lower back pain showed that the majority of our sample population suffered from pain in the lower back. We found that there are no statistically significant differences between the groups formed by the length of service as a professional driver and incidence of lower back pain; we were also interested in whether or not the risk factors of lower back pain affects the absenteeism of city bus drivers. Analysis of the data has shown that the risk factors of pain in the lower part of the spine do affect the absenteeism of city bus drivers.

Analyzing the effect of selected control policy measures and sociodemographic factors on alcoholic beverage consumption in Europe within the AMPHORA project: statistical methods.

PubMed

Baccini, Michela; Carreras, Giulia

2014-10-01

This paper describes the methods used to investigate variations in total alcoholic beverage consumption as related to selected control intervention policies and other socioeconomic factors (unplanned factors) within 12 European countries involved in the AMPHORA project. The analysis presented several critical points: presence of missing values, strong correlation among the unplanned factors, long-term waves or trends in both the time series of alcohol consumption and the time series of the main explanatory variables. These difficulties were addressed by implementing a multiple imputation procedure for filling in missing values, then specifying for each country a multiple regression model which accounted for time trend, policy measures and a limited set of unplanned factors, selected in advance on the basis of sociological and statistical considerations are addressed. This approach allowed estimating the "net" effect of the selected control policies on alcohol consumption, but not the association between each unplanned factor and the outcome.

Uncertainty Analysis of Seebeck Coefficient and Electrical Resistivity Characterization

NASA Technical Reports Server (NTRS)

Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred

2014-01-01

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

Statistical Analysis of Human Body Movement and Group Interactions in Response to Music

NASA Astrophysics Data System (ADS)

Desmet, Frank; Leman, Marc; Lesaffre, Micheline; de Bruyn, Leen

Quantification of time series that relate to physiological data is challenging for empirical music research. Up to now, most studies have focused on time-dependent responses of individual subjects in controlled environments. However, little is known about time-dependent responses of between-subject interactions in an ecological context. This paper provides new findings on the statistical analysis of group synchronicity in response to musical stimuli. Different statistical techniques were applied to time-dependent data obtained from an experiment on embodied listening in individual and group settings. Analysis of inter group synchronicity are described. Dynamic Time Warping (DTW) and Cross Correlation Function (CCF) were found to be valid methods to estimate group coherence of the resulting movements. It was found that synchronicity of movements between individuals (human-human interactions) increases significantly in the social context. Moreover, Analysis of Variance (ANOVA) revealed that the type of music is the predominant factor in both the individual and the social context.

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.

Statistical validation and an empirical model of hydrogen production enhancement found by utilizing passive flow disturbance in the steam-reformation process

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

Erickson, Paul A.; Liao, Chang-hsien

2007-11-15

A passive flow disturbance has been proven to enhance the conversion of fuel in a methanol-steam reformer. This study presents a statistical validation of the experiment based on a standard 2{sup k} factorial experiment design and the resulting empirical model of the enhanced hydrogen producing process. A factorial experiment design was used to statistically analyze the effects and interactions of various input factors in the experiment. Three input factors, including the number of flow disturbers, catalyst size, and reactant flow rate were investigated for their effects on the fuel conversion in the steam-reformation process. Based on the experimental results, anmore » empirical model was developed and further evaluated with an uncertainty analysis and interior point data. (author)« less

[On measuring of factors influencing the complex need for cultural entertainments of the inhabitants in geriatric nursing homes (3rd information) (author's transl)].

PubMed

Kuhlmey, J; Lautsch, E

1980-01-01

In our 2. information on the investigation of the need for cultural entertainments of inhabitants in geriatric nursing homes we tested the influence of the factors age, sex, kind of work and during of stay in the geriatric nursing home singly and successively for each single indicator of this complex need. In this 3. information the influence of this four factors was investigated in these contradictory dependency on the indicators under synchronous consideration of their contradictory dependency. The contradictory dependency of the factors was presented by typisation (cluster analysis). As a result of the cluster analysis same classes arose--similar disposed inhabitants belong to same classes. The average coinage in this classes was obtained and differences were analysed by statistical methods multidimensional analysis of variance and analysis of discriminance).

Demographic and health situation of children in conditions of economic destabilization in the Ukraine.

PubMed

Pantyley, Viktoriya

2014-01-01

In new conditions of socio-economic development in the Ukraine, the health of the population of children is considered as the most reliable indicator of socio-economic development of the country. The primary goal of the study was analysis of the effect of contemporary socio-economic transformations, their scope, and strength of effect on the demographic and social situation of children in various regions of the Ukraine. The methodological objectives of the study were as follows: development of a synthetic measure of the state of health of the population of children, based on the Hellwig's method, and selection of districts in the Ukraine according to the present health-demographic situation of children. The study was based on statistical data from the State Statistics Service of Ukraine, Centre of Medical Statistics in Kiev, Ukrainian Ministry of Defence, as well as Ministry of Education and Science, Youth and Sports of Ukraine. The following research methods were used: analysis of literature and Internet sources, selection and analysis of statistical materials, cartographic and statistical methods. Basic indices of the demographic and health situation of the population of children were analyzed, as well as factors of a socio-economic nature which affect this situation. A set of variables was developed for the synthetic evaluation of the state of health of the population of children. The typology of the Ukrainian districts was performed according to the state of health of the child population, based on the Hellwig's taxonomic method. Deterioration was observed of selected quality parameters, as well as a change in the strength and directions of effect of factors of organizational-institutional, socioeconomic, historical and cultural nature on the population of children potential.

Versatility of Cooperative Transcriptional Activation: A Thermodynamical Modeling Analysis for Greater-Than-Additive and Less-Than-Additive Effects

PubMed Central

Frank, Till D.; Carmody, Aimée M.; Kholodenko, Boris N.

2012-01-01

We derive a statistical model of transcriptional activation using equilibrium thermodynamics of chemical reactions. We examine to what extent this statistical model predicts synergy effects of cooperative activation of gene expression. We determine parameter domains in which greater-than-additive and less-than-additive effects are predicted for cooperative regulation by two activators. We show that the statistical approach can be used to identify different causes of synergistic greater-than-additive effects: nonlinearities of the thermostatistical transcriptional machinery and three-body interactions between RNA polymerase and two activators. In particular, our model-based analysis suggests that at low transcription factor concentrations cooperative activation cannot yield synergistic greater-than-additive effects, i.e., DNA transcription can only exhibit less-than-additive effects. Accordingly, transcriptional activity turns from synergistic greater-than-additive responses at relatively high transcription factor concentrations into less-than-additive responses at relatively low concentrations. In addition, two types of re-entrant phenomena are predicted. First, our analysis predicts that under particular circumstances transcriptional activity will feature a sequence of less-than-additive, greater-than-additive, and eventually less-than-additive effects when for fixed activator concentrations the regulatory impact of activators on the binding of RNA polymerase to the promoter increases from weak, to moderate, to strong. Second, for appropriate promoter conditions when activator concentrations are increased then the aforementioned re-entrant sequence of less-than-additive, greater-than-additive, and less-than-additive effects is predicted as well. Finally, our model-based analysis suggests that even for weak activators that individually induce only negligible increases in promoter activity, promoter activity can exhibit greater-than-additive responses when transcription factors and RNA polymerase interact by means of three-body interactions. Overall, we show that versatility of transcriptional activation is brought about by nonlinearities of transcriptional response functions and interactions between transcription factors, RNA polymerase and DNA. PMID:22506020

Statistical Analysis of Complexity Generators for Cost Estimation

NASA Technical Reports Server (NTRS)

Rowell, Ginger Holmes

1999-01-01

Predicting the cost of cutting edge new technologies involved with spacecraft hardware can be quite complicated. A new feature of the NASA Air Force Cost Model (NAFCOM), called the Complexity Generator, is being developed to model the complexity factors that drive the cost of space hardware. This parametric approach is also designed to account for the differences in cost, based on factors that are unique to each system and subsystem. The cost driver categories included in this model are weight, inheritance from previous missions, technical complexity, and management factors. This paper explains the Complexity Generator framework, the statistical methods used to select the best model within this framework, and the procedures used to find the region of predictability and the prediction intervals for the cost of a mission.

The Effects of industrial workers' food choice attribute on sugar intake pattern and job satisfaction with Structural Equcation Model

PubMed Central

Park, Young Il

2016-01-01

BACKGROUND/OBJECTIVES This research analyzes the effects of the food choices of industrial workers according to their sugar intake pattern on their job satisfaction through the construction of a model on the relationship between sugar intake pattern and job satisfaction. SUBJECTS/METHODS Surveys were collected from May to July 2015. A statistical analysis of the 775 surveys from Kyungsangnam-do was conducted using SPSS13.0 for Windows and SEM was performed using the AMOS 5.0 statistics package. RESULTS The reliability of the data was confirmed by an exploratory factor analysis through a Cronbach's alpha coefficient, and the measurement model was proven to be appropriate by a confirmatory factor analysis in conjunction with AMOS. The results of factor analysis on food choice, sugar intake pattern and job satisfaction were categorized into five categories. The reliability of these findings was supported by a Cronbach's alpha coefficient of 0.6 and higher for all factors except confection (0.516) and dairy products (0.570). The multicollinearity results did not indicate a problem between the variables since the highest correlation coefficient was 0.494 (P < 0.01). In an attempt to study the sugar intake pattern in accordance with the food choices and job satisfaction of industrial workers, a structural equation model was constructed and analyzed. CONCLUSIONS All tests confirmed that the model satisfied the recommended levels for the goodness of fit index, and thus, the overall research model was proven to be appropriate. PMID:27478555

Comparative Analysis of Academic Grades in Compulsory Secondary Education in Spain Using Statistical Techniques

ERIC Educational Resources Information Center

Veas, Alejandro; Gilar, Raquel; Miñano, Pablo; Castejón, Juan Luis

2017-01-01

The present study, based on the construct comparability approach, performs a comparative analysis of general points average for seven courses, using exploratory factor analysis (EFA) and the Partial Credit model (PCM) with a sample of 1398 student subjects (M = 12.5, SD = 0.67) from 8 schools in the province of Alicante (Spain). EFA confirmed a…

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

PubMed

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

2014-06-28

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

Source Evaluation and Trace Metal Contamination in Benthic Sediments from Equatorial Ecosystems Using Multivariate Statistical Techniques

PubMed Central

Benson, Nsikak U.; Asuquo, Francis E.; Williams, Akan B.; Essien, Joseph P.; Ekong, Cyril I.; Akpabio, Otobong; Olajire, Abaas A.

2016-01-01

Trace metals (Cd, Cr, Cu, Ni and Pb) concentrations in benthic sediments were analyzed through multi-step fractionation scheme to assess the levels and sources of contamination in estuarine, riverine and freshwater ecosystems in Niger Delta (Nigeria). The degree of contamination was assessed using the individual contamination factors (ICF) and global contamination factor (GCF). Multivariate statistical approaches including principal component analysis (PCA), cluster analysis and correlation test were employed to evaluate the interrelationships and associated sources of contamination. The spatial distribution of metal concentrations followed the pattern Pb>Cu>Cr>Cd>Ni. Ecological risk index by ICF showed significant potential mobility and bioavailability for Cu, Cu and Ni. The ICF contamination trend in the benthic sediments at all studied sites was Cu>Cr>Ni>Cd>Pb. The principal component and agglomerative clustering analyses indicate that trace metals contamination in the ecosystems was influenced by multiple pollution sources. PMID:27257934

Raising the bar for reproducible science at the U.S. Environmental Protection Agency Office of Research and Development.

PubMed

George, Barbara Jane; Sobus, Jon R; Phelps, Lara P; Rashleigh, Brenda; Simmons, Jane Ellen; Hines, Ronald N

2015-05-01

Considerable concern has been raised regarding research reproducibility both within and outside the scientific community. Several factors possibly contribute to a lack of reproducibility, including a failure to adequately employ statistical considerations during study design, bias in sample selection or subject recruitment, errors in developing data inclusion/exclusion criteria, and flawed statistical analysis. To address some of these issues, several publishers have developed checklists that authors must complete. Others have either enhanced statistical expertise on existing editorial boards, or formed distinct statistics editorial boards. Although the U.S. Environmental Protection Agency, Office of Research and Development, already has a strong Quality Assurance Program, an initiative was undertaken to further strengthen statistics consideration and other factors in study design and also to ensure these same factors are evaluated during the review and approval of study protocols. To raise awareness of the importance of statistical issues and provide a forum for robust discussion, a Community of Practice for Statistics was formed in January 2014. In addition, three working groups were established to develop a series of questions or criteria that should be considered when designing or reviewing experimental, observational, or modeling focused research. This article describes the process used to develop these study design guidance documents, their contents, how they are being employed by the Agency's research enterprise, and expected benefits to Agency science. The process and guidance documents presented here may be of utility for any research enterprise interested in enhancing the reproducibility of its science. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology.

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

Treesearch

A. C. Gellis; NO-VALUE

2013-01-01

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

Part 1--Factors Associated with School Nurse Ratios: An Analysis of State Data

ERIC Educational Resources Information Center

Maughan, Erin

2009-01-01

Despite the recognized importance of school nurses, the ratios of nurse to pupil are insufficient in many states across the country. The purpose of this study was to describe school nurse-to-pupil ratios by state and to statistically identify factors that may influence these ratios. Funding per pupil unit in general and support services and laws…

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

ERIC Educational Resources Information Center

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

2012-01-01

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

Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography.

PubMed

Lee, Jang-Eun; Lee, Bum-Jin; Chung, Jin-Oh; Kim, Hak-Nam; Kim, Eun-Hee; Jung, Sungheuk; Lee, Hyosang; Lee, Sang-Jun; Hong, Young-Shick

2015-05-01

Numerous factors such as geographical origin, cultivar, climate, cultural practices, and manufacturing processes influence the chemical compositions of tea, in the same way as growing conditions and grape variety affect wine quality. However, the relationships between these factors and tea chemical compositions are not well understood. In this study, a new approach for non-targeted or global analysis, i.e., metabolomics, which is highly reproducible and statistically effective in analysing a diverse range of compounds, was used to better understand the metabolome of Camellia sinensis and determine the influence of environmental factors, including geography, climate, and cultural practices, on tea-making. We found a strong correlation between environmental factors and the metabolome of green, white, and oolong teas from China, Japan, and South Korea. In particular, multivariate statistical analysis revealed strong inter-country and inter-city relationships in the levels of theanine and catechin derivatives found in green and white teas. This information might be useful for assessing tea quality or producing distinct tea products across different locations, and highlights simultaneous identification of diverse tea metabolites through an NMR-based metabolomics approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

Measuring determinants of career satisfaction of anesthesiologists: validation of a survey instrument.

PubMed

Afonso, Anoushka M; Diaz, James H; Scher, Corey S; Beyl, Robbie A; Nair, Singh R; Kaye, Alan David

2013-06-01

To measure the parameter of job satisfaction among anesthesiologists. Survey instrument. Academic anesthesiology departments in the United States. 320 anesthesiologists who attended the annual meeting of the ASA in 2009 (95% response rate). The anonymous 50-item survey collected information on 26 independent demographic variables and 24 dependent ranked variables of career satisfaction among practicing anesthesiologists. Mean survey scores were calculated for each demographic variable and tested for statistically significant differences by analysis of variance. Questions within each domain that were internally consistent with each other within domains were identified by Cronbach's alpha ≥ 0.7. P-values ≤ 0.05 were considered statistically significant. Cronbach's alpha analysis showed strong internal consistency for 10 dependent outcome questions in the practice factor-related domain (α = 0.72), 6 dependent outcome questions in the peer factor-related domain (α = 0.71), and 8 dependent outcome questions in the personal factor-related domain (α = 0.81). Although age was not a variable, full-time status, early satisfaction within the first 5 years of practice, working with respected peers, and personal choice factors were all significantly associated with anesthesiologist job satisfaction. Improvements in factors related to job satisfaction among anesthesiologists may lead to higher early and current career satisfaction. Copyright © 2013 Elsevier Inc. All rights reserved.

Genomic analysis of regulatory network dynamics reveals large topological changes

NASA Astrophysics Data System (ADS)

Luscombe, Nicholas M.; Madan Babu, M.; Yu, Haiyuan; Snyder, Michael; Teichmann, Sarah A.; Gerstein, Mark

2004-09-01

Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information and gene-expression data for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here-particularly the large-scale topological changes and hub transience-will apply to other biological networks, including complex sub-systems in higher eukaryotes.

The skeletal maturation status estimated by statistical shape analysis: axial images of Japanese cervical vertebra.

PubMed

Shin, S M; Kim, Y-I; Choi, Y-S; Yamaguchi, T; Maki, K; Cho, B-H; Park, S-B

2015-01-01

To evaluate axial cervical vertebral (ACV) shape quantitatively and to build a prediction model for skeletal maturation level using statistical shape analysis for Japanese individuals. The sample included 24 female and 19 male patients with hand-wrist radiographs and CBCT images. Through generalized Procrustes analysis and principal components (PCs) analysis, the meaningful PCs were extracted from each ACV shape and analysed for the estimation regression model. Each ACV shape had meaningful PCs, except for the second axial cervical vertebra. Based on these models, the smallest prediction intervals (PIs) were from the combination of the shape space PCs, age and gender. Overall, the PIs of the male group were smaller than those of the female group. There was no significant correlation between centroid size as a size factor and skeletal maturation level. Our findings suggest that the ACV maturation method, which was applied by statistical shape analysis, could confirm information about skeletal maturation in Japanese individuals as an available quantifier of skeletal maturation and could be as useful a quantitative method as the skeletal maturation index.

The skeletal maturation status estimated by statistical shape analysis: axial images of Japanese cervical vertebra

PubMed Central

Shin, S M; Choi, Y-S; Yamaguchi, T; Maki, K; Cho, B-H; Park, S-B

2015-01-01

Objectives: To evaluate axial cervical vertebral (ACV) shape quantitatively and to build a prediction model for skeletal maturation level using statistical shape analysis for Japanese individuals. Methods: The sample included 24 female and 19 male patients with hand–wrist radiographs and CBCT images. Through generalized Procrustes analysis and principal components (PCs) analysis, the meaningful PCs were extracted from each ACV shape and analysed for the estimation regression model. Results: Each ACV shape had meaningful PCs, except for the second axial cervical vertebra. Based on these models, the smallest prediction intervals (PIs) were from the combination of the shape space PCs, age and gender. Overall, the PIs of the male group were smaller than those of the female group. There was no significant correlation between centroid size as a size factor and skeletal maturation level. Conclusions: Our findings suggest that the ACV maturation method, which was applied by statistical shape analysis, could confirm information about skeletal maturation in Japanese individuals as an available quantifier of skeletal maturation and could be as useful a quantitative method as the skeletal maturation index. PMID:25411713

A scaling procedure for the response of an isolated system with high modal overlap factor

NASA Astrophysics Data System (ADS)

De Rosa, S.; Franco, F.

2008-10-01

The paper deals with a numerical approach that reduces some physical sizes of the solution domain to compute the dynamic response of an isolated system: it has been named Asymptotical Scaled Modal Analysis (ASMA). The proposed numerical procedure alters the input data needed to obtain the classic modal responses to increase the frequency band of validity of the discrete or continuous coordinates model through the definition of a proper scaling coefficient. It is demonstrated that the computational cost remains acceptable while the frequency range of analysis increases. Moreover, with reference to the flexural vibrations of a rectangular plate, the paper discusses the ASMA vs. the statistical energy analysis and the energy distribution approach. Some insights are also given about the limits of the scaling coefficient. Finally it is shown that the linear dynamic response, predicted with the scaling procedure, has the same quality and characteristics of the statistical energy analysis, but it can be useful when the system cannot be solved appropriately by the standard Statistical Energy Analysis (SEA).

Experience with multiple control groups in a large population-based case-control study on genetic and environmental risk factors.

PubMed

Pomp, E R; Van Stralen, K J; Le Cessie, S; Vandenbroucke, J P; Rosendaal, F R; Doggen, C J M

2010-07-01

We discuss the analytic and practical considerations in a large case-control study that had two control groups; the first control group consisting of partners of patients and the second obtained by random digit dialling (RDD). As an example of the evaluation of a general lifestyle factor, we present body mass index (BMI). Both control groups had lower BMIs than the patients. The distribution in the partner controls was closer to that of the patients, likely due to similar lifestyles. A statistical approach was used to pool the results of both analyses, wherein partners were analyzed with a matched analysis, while RDDs were analyzed without matching. Even with a matched analysis, the odds ratio with partner controls remained closer to unity than with RDD controls, which is probably due to unmeasured confounders in the comparison with the random controls as well as intermediary factors. However, when studying injuries as a risk factor, the odds ratio remained higher with partner control subjects than with RRD control subjects, even after taking the matching into account. Finally we used factor V Leiden as an example of a genetic risk factor. The frequencies of factor V Leiden were identical in both control groups, indicating that for the analyses of this genetic risk factor the two control groups could be combined in a single unmatched analysis. In conclusion, the effect measures with the two control groups were in the same direction, and of the same order of magnitude. Moreover, it was not always the same control group that produced the higher or lower estimates, and a matched analysis did not remedy the differences. Our experience with the intricacies of dealing with two control groups may be useful to others when thinking about an optimal research design or the best statistical approach.

Two-Sample Statistics for Testing the Equality of Survival Functions Against Improper Semi-parametric Accelerated Failure Time Alternatives: An Application to the Analysis of a Breast Cancer Clinical Trial

PubMed Central

BROËT, PHILIPPE; TSODIKOV, ALEXANDER; DE RYCKE, YANN; MOREAU, THIERRY

2010-01-01

This paper presents two-sample statistics suited for testing equality of survival functions against improper semi-parametric accelerated failure time alternatives. These tests are designed for comparing either the short- or the long-term effect of a prognostic factor, or both. These statistics are obtained as partial likelihood score statistics from a time-dependent Cox model. As a consequence, the proposed tests can be very easily implemented using widely available software. A breast cancer clinical trial is presented as an example to demonstrate the utility of the proposed tests. PMID:15293627

The Investigation of Construct Validity of Diagnostic and Statistical Manual of Mental Disorder-5 Personality Traits on Iranian sample with Antisocial and Borderline Personality Disorders.

PubMed

Amini, Mehdi; Pourshahbaz, Abbas; Mohammadkhani, Parvaneh; Ardakani, Mohammad-Reza Khodaie; Lotfi, Mozhgan

2014-12-01

The goal of this study was to examine the construct validity of the diagnostic and statistical manual of mental disorder-5 (DSM-5) conceptual model of antisocial and borderline personality disorders (PDs). More specifically, the aim was to determine whether the DSM-5 five-factor structure of pathological personality trait domains replicated in an independently collected sample that differs culturally from the derivation sample. This study was on a sample of 346 individuals with antisocial (n = 122) and borderline PD (n = 130), and nonclinical subjects (n = 94). Participants randomly selected from prisoners, out-patient, and in-patient clients. Participants were recruited from Tehran prisoners, and clinical psychology and psychiatry clinics of Razi and Taleghani Hospital, Tehran, Iran. The SCID-II-PQ, SCID-II, DSM-5 Personality Trait Rating Form (Clinician's PTRF) were used to diagnosis of PD and to assessment of pathological traits. The data were analyzed by exploratory factor analysis. Factor analysis revealed a 5-factor solution for DSM-5 personality traits. Results showed that DSM-5 has adequate construct validity in Iranian sample with antisocial and borderline PDs. Factors similar in number with the other studies, but different in the content. Exploratory factor analysis revealed five homogeneous components of antisocial and borderline PDs. That may represent personality, behavioral, and affective features central to the disorder. Furthermore, the present study helps understand the adequacy of DSM-5 dimensional approach to evaluation of personality pathology, specifically on Iranian sample.

Evaluation of psychometric properties of the malay version perceived stress scale in two occupational settings in malaysia.

PubMed

Al-Dubai, Sar; Ganasegeran, K; Barua, A; Rizal, Am; Rampal, Kg

2014-07-01

The 10-item version of Perceived Stress Scale (PSS-10) is a widely used tool to measure stress. The Malay version of the PSS-10 has been validated among Malaysian Medical Students. However, studies have not been conducted to assess its validity in occupational settings. The aim of this study is to assess the psychometric properties of the Malay version of the PSS-10 in two occupational setting in Malaysia. This study was conducted among 191 medical residents and 513 railway workers. An exploratory factor analysis was performed using the principal component method with varimax rotation. Correlation analyses, Kaiser-Meyer-Olkin, Bartlett's test of Sphericity and Cronbach's alpha were obtained. Statistical analysis was carried out using statistical package for the social sciences version 16 (SPSS, Chicago, IL, USA) software. Analysis yielded two factor structure of the Malay version of PSS-10 in both occupational groups. The two factors accounted for 59.2% and 64.8% of the variance in the medical residents and the railway workers respectively. Factor loadings were greater than 0.59 in both occupational groups. Cronbach's alpha co-efficient was 0.70 for medical residents and 0.71 for railway workers. The Malay version of PSS-10 had adequate psychometric properties and can be used to measure stress among occupational settings in Malaysia.

Evaluation of Psychometric Properties of the Malay Version Perceived Stress Scale in Two Occupational Settings In Malaysia

PubMed Central

Al-Dubai, SAR; Ganasegeran, K; Barua, A; Rizal, AM; Rampal, KG

2014-01-01

Background: The 10-item version of Perceived Stress Scale (PSS-10) is a widely used tool to measure stress. The Malay version of the PSS-10 has been validated among Malaysian Medical Students. However, studies have not been conducted to assess its validity in occupational settings. Aim: The aim of this study is to assess the psychometric properties of the Malay version of the PSS-10 in two occupational setting in Malaysia. Subjects and Methods: This study was conducted among 191 medical residents and 513 railway workers. An exploratory factor analysis was performed using the principal component method with varimax rotation. Correlation analyses, Kaiser-Meyer-Olkin, Bartlett's test of Sphericity and Cronbach's alpha were obtained. Statistical analysis was carried out using statistical package for the social sciences version 16 (SPSS, Chicago, IL, USA) software. Results: Analysis yielded two factor structure of the Malay version of PSS-10 in both occupational groups. The two factors accounted for 59.2% and 64.8% of the variance in the medical residents and the railway workers respectively. Factor loadings were greater than 0.59 in both occupational groups. Cronbach's alpha co-efficient was 0.70 for medical residents and 0.71 for railway workers. Conclusion: The Malay version of PSS-10 had adequate psychometric properties and can be used to measure stress among occupational settings in Malaysia. PMID:25184074

Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Do, Cuong Manh; Nguyen, Trung Hieu; Dinh, Tuan Anh Diep

2015-05-01

The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70% of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH₃ are the discriminating parameters in space, affording 67% correct assignation in spatial analysis; pH and NO₂ are the discriminating parameters according to season, assigning approximately 60% of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.

A systematic literature review of PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders: DSM-IV to DSM-5.

PubMed

Armour, Cherie; Műllerová, Jana; Elhai, Jon D

2016-03-01

The factor structure of posttraumatic stress disorder (PTSD) has been widely researched, but consensus regarding the exact number and nature of factors is yet to be reached. The aim of the current study was to systematically review the extant literature on PTSD's latent structure in the Diagnostic and Statistical Manual of Mental Disorders (DSM) in order to identify the best-fitting model. One hundred and twelve research papers published after 1994 using confirmatory factor analysis and DSM-based measures of PTSD were included in the review. In the DSM-IV literature, four-factor models received substantial support, but the five-factor Dysphoric arousal model demonstrated the best fit, regardless of gender, measurement instrument or trauma type. The recently proposed DSM-5 PTSD model was found to be a good representation of PTSD's latent structure, but studies analysing the six- and seven-factor models suggest that the DSM-5 PTSD factor structure may need further alterations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Similarity in temperament between mother and offspring rhesus monkeys: Sex differences and the role of monoamine oxidase-A and serotonin transporter promoter polymorphism genotypes

PubMed Central

Sullivan, Erin C.; Mendoza, Sally P.; Capitanio, John P.

2011-01-01

Temperament is usually considered biologically based and largely inherited, however the environment can shape the development of temperament. Allelic variation may confer differential sensitivity to early environment resulting in variations in temperament. Here we explore the relationship between measures of temperament in mothers and their first-born offspring and the role of genetic sensitivity in establishing the strength of these associations. Temperament ratings were conducted on 3-4 month old rhesus monkeys after a 25-hour biobehavioral assessment. Factor analysis revealed a four factor structure of temperament. Females assessed as infants have reproduced and their offspring have also been evaluated through the standardized testing paradigm. Canonical correlation analysis revealed statistically significant associations between factor scores of mothers and sons, but not mothers and daughters. Further, offspring possessing the high activity, “low risk”, alleles of the rhMAOA-LPR or rh5-HTTLPR showed statistically significant canonical correlations, whereas those possessing other alleles did not, suggesting differential genetic sensitivity to the normative early experience of maternal temperament. PMID:21866539

Síndrome metabólico y otros factores asociados a gonartrosis.

PubMed

Charles-Lozoya, Sergio; Treviño-Báez, Joaquín Darío; Ramos-Rivera, Jesús Alejandro; Rangel-Flores, Jesús María; Tamez-Montes, Juan Carlos; Brizuela-Ventura, Jesús Miguel

2017-01-01

To evaluate whether an association exists between gonarthrosis and metabolic syndrome X (MS) as well as other potential risk factors. Comparative cross-sectional study of 310 patients evaluated by pathology of knee grouped in patients with gonarthrosis and without it. Sociodemographic, anthropometric and laboratory data was obtained. Gonarthrosis was defined as a ≥ 2 score in Kellgren-Lawrence radiological scale, and MS was assessed using the International Diabetes Federation criteria. Odds ratio and logistic regression were used for bivariate and multivariate analysis respectively. The prevalence of MS in patients who had gonarthrosis was 79.9%, statistically higher than in patients without gonarthrosis (p = 0.001). Other factors that had a statistically higher frequency in this group included diabetes mellitus (p = 0.02) and hypertension (p = 0.02). Multivariate analysis revealed MS had an association with a higher prevalence of gonarthrosis (p = 0.003), while high density lipoproteins (p = 0.02) was associated with a lower prevalence. MS and its related alterations are associated to gonarthrosis; their adequate control could prevent patients from developing the disease. Copyright: © 2017 SecretarÍa de Salud

The citation impact of hydrology journals

NASA Astrophysics Data System (ADS)

Clark, Martyn P.; Hanson, R. Brooks

2017-06-01

We examine a suite of journal-level productivity and citation statistics for six leading hydrology journals in order to help authors understand the robustness and meaning of journal impact factors. The main results are (1) the probability distribution of citations is remarkably homogenous across hydrology journals; (2) hydrology papers tend to have a long-lasting impact, with a large fraction of papers cited after the 2 year window used to calculate the journal impact factor; and (3) journal impact factors are characterized by substantial year-to-year variability (especially for smaller journals), primarily because a small number of highly cited papers have a large influence on the journal impact factor. Consequently, the ranking of hydrology journals with respect to the journal impact factor in a given year does not have much information content. These results highlight problems in using citation data to evaluate hydrologic science. We hope that this analysis helps authors better understand journal-level citation statistics, and also helps improve research assessments in institutions and funding agencies.

The need for conducting forensic analysis of decommissioned bridges.

DOT National Transportation Integrated Search

2014-01-01

A limiting factor in current bridge management programs is a lack of detailed knowledge of bridge deterioration : mechanisms and processes. The current state of the art is to predict future condition using statistical forecasting : models based upon ...

14 CFR 23.621 - Casting factors.

Code of Federal Regulations, 2013 CFR

2013-01-01

... either magnetic particle, penetrant or other approved equivalent non-destructive inspection method; or... percent approved non-destructive inspection. When an approved quality control procedure is established and an acceptable statistical analysis supports reduction, non-destructive inspection may be reduced from...

14 CFR 23.621 - Casting factors.

Code of Federal Regulations, 2012 CFR

2012-01-01

... either magnetic particle, penetrant or other approved equivalent non-destructive inspection method; or... percent approved non-destructive inspection. When an approved quality control procedure is established and an acceptable statistical analysis supports reduction, non-destructive inspection may be reduced from...

14 CFR 23.621 - Casting factors.

Code of Federal Regulations, 2014 CFR

2014-01-01

... either magnetic particle, penetrant or other approved equivalent non-destructive inspection method; or... percent approved non-destructive inspection. When an approved quality control procedure is established and an acceptable statistical analysis supports reduction, non-destructive inspection may be reduced from...

14 CFR 23.621 - Casting factors.

Code of Federal Regulations, 2010 CFR

2010-01-01

... either magnetic particle, penetrant or other approved equivalent non-destructive inspection method; or... percent approved non-destructive inspection. When an approved quality control procedure is established and an acceptable statistical analysis supports reduction, non-destructive inspection may be reduced from...

Development and evaluation of the Internalized Racism in Asian Americans Scale (IRAAS).

PubMed

Choi, Andrew Young; Israel, Tania; Maeda, Hotaka

2017-01-01

This article presents the development and psychometric evaluation of the Internalized Racism in Asian Americans Scale (IRAAS), which was designed to measure the degree to which Asian Americans internalized hostile attitudes and negative messages targeted toward their racial identity. Items were developed on basis of prior literature, vetted through expert feedback and cognitive interviews, and administered to 655 Asian American participants through Amazon Mechanical Turk. Exploratory factor analysis with a random subsample (n = 324) yielded a psychometrically robust preliminary measurement model consisting of 3 factors: Self-Negativity, Weakness Stereotypes, and Appearance Bias. Confirmatory factor analysis with a separate subsample (n = 331) indicated that the proposed correlated factors model was strongly consistent with the observed data. Factor determinacies were high and demonstrated that the specified items adequately measured their intended factors. Bifactor modeling further indicated that this multidimensionality could be univocally represented for the purpose of measurement, including the use of a mean total score representing a single continuum of internalized racism on which individuals vary. The IRAAS statistically predicted depressive symptoms, and demonstrated statistically significant correlations in theoretically expected directions with four dimensions of collective self-esteem. These results provide initial validity evidence supporting the use of the IRAAS to measure aspects of internalized racism in this population. Limitations and research implications are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

MetaComp: comprehensive analysis software for comparative meta-omics including comparative metagenomics.

PubMed

Zhai, Peng; Yang, Longshu; Guo, Xiao; Wang, Zhe; Guo, Jiangtao; Wang, Xiaoqi; Zhu, Huaiqiu

2017-10-02

During the past decade, the development of high throughput nucleic sequencing and mass spectrometry analysis techniques have enabled the characterization of microbial communities through metagenomics, metatranscriptomics, metaproteomics and metabolomics data. To reveal the diversity of microbial communities and interactions between living conditions and microbes, it is necessary to introduce comparative analysis based upon integration of all four types of data mentioned above. Comparative meta-omics, especially comparative metageomics, has been established as a routine process to highlight the significant differences in taxon composition and functional gene abundance among microbiota samples. Meanwhile, biologists are increasingly concerning about the correlations between meta-omics features and environmental factors, which may further decipher the adaptation strategy of a microbial community. We developed a graphical comprehensive analysis software named MetaComp comprising a series of statistical analysis approaches with visualized results for metagenomics and other meta-omics data comparison. This software is capable to read files generated by a variety of upstream programs. After data loading, analyses such as multivariate statistics, hypothesis testing of two-sample, multi-sample as well as two-group sample and a novel function-regression analysis of environmental factors are offered. Here, regression analysis regards meta-omic features as independent variable and environmental factors as dependent variables. Moreover, MetaComp is capable to automatically choose an appropriate two-group sample test based upon the traits of input abundance profiles. We further evaluate the performance of its choice, and exhibit applications for metagenomics, metaproteomics and metabolomics samples. MetaComp, an integrative software capable for applying to all meta-omics data, originally distills the influence of living environment on microbial community by regression analysis. Moreover, since the automatically chosen two-group sample test is verified to be outperformed, MetaComp is friendly to users without adequate statistical training. These improvements are aiming to overcome the new challenges under big data era for all meta-omics data. MetaComp is available at: http://cqb.pku.edu.cn/ZhuLab/MetaComp/ and https://github.com/pzhaipku/MetaComp/ .

[Suicide risk factors in the professional military personnel in the Army of Serbia].

PubMed

Dedić, Gordana; Panić, Milivoje

2010-04-01

Recognition of suicide risk factors is important in taking adequate suicide preventive measures, Suicide Prevention Program for Professional Military Personnel (PMP) implemented in the Army of Serbia in 2003. The aim of our study was to establish suicide risk factors in PMP of the Army of Serbia. Analysis of suicide risk factors in PMP was carried out on the basis of data obtained by psychological suicide autopsy. The controls were demographically similar psychiatric outpatients with no history of suicidal behaviour. A descriptive statistics method was used for risk factors analysis. The t-test was used for testing statistical hypotheses. A total of 30 PMP, aged 22-49 years (30.53 +/- 6.24 on average) committed suicide within the period 1998-2007. Distal suicide risk factors in PMP were considered to be not being married, psychiatric heredity, having no outpatient psychiatric treatment, gambling, regular physical practice (bodybuilding), less transfer to a different post, low motivation for military service (p < 0.001), not having children, parental loss in early childhood, alcohol abuse (p < 0.005), low salary (p < 0.01) uncompleted military school, debts in the family (p < 0.05). The commonest proximal suicide risk factors were: actual family problems (36.6%), actual mental problems (13.3%), burnout (13.3%), negative balance of accounts (13.3%), professional problems (6.7%), behavioral model while for 10.0% PMP suicide risk factors could not be established. According to the presence of multiple suicide risk factors, Suicide Prevention Program for PMP in the Army of Serbia is directed to the prevention of both proximal and distal suicide risk factors.

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.

Analysis of nasopharyngeal carcinoma risk factors with Bayesian networks.

PubMed

Aussem, Alex; de Morais, Sérgio Rodrigues; Corbex, Marilys

2012-01-01

We propose a new graphical framework for extracting the relevant dietary, social and environmental risk factors that are associated with an increased risk of nasopharyngeal carcinoma (NPC) on a case-control epidemiologic study that consists of 1289 subjects and 150 risk factors. This framework builds on the use of Bayesian networks (BNs) for representing statistical dependencies between the random variables. We discuss a novel constraint-based procedure, called Hybrid Parents and Children (HPC), that builds recursively a local graph that includes all the relevant features statistically associated to the NPC, without having to find the whole BN first. The local graph is afterwards directed by the domain expert according to his knowledge. It provides a statistical profile of the recruited population, and meanwhile helps identify the risk factors associated to NPC. Extensive experiments on synthetic data sampled from known BNs show that the HPC outperforms state-of-the-art algorithms that appeared in the recent literature. From a biological perspective, the present study confirms that chemical products, pesticides and domestic fume intake from incomplete combustion of coal and wood are significantly associated with NPC risk. These results suggest that industrial workers are often exposed to noxious chemicals and poisonous substances that are used in the course of manufacturing. This study also supports previous findings that the consumption of a number of preserved food items, like house made proteins and sheep fat, are a major risk factor for NPC. BNs are valuable data mining tools for the analysis of epidemiologic data. They can explicitly combine both expert knowledge from the field and information inferred from the data. These techniques therefore merit consideration as valuable alternatives to traditional multivariate regression techniques in epidemiologic studies. Copyright © 2011 Elsevier B.V. All rights reserved.

Factors influencing initiation and duration of breast feeding in Ireland.

PubMed

Leahy-Warren, Patricia; Mulcahy, Helen; Phelan, Agnes; Corcoran, Paul

2014-03-01

The aim of this research was to identify factors associated with mothers breast feeding and to identify, for those who breast fed, factors associated with breast feeding for as long as planned. breast feeding rates in Ireland are amongst the lowest in Europe. Research evidence indicates that in order for mothers to be successful at breast feeding, multiplicities of supports are necessary for both initiation and duration. The nature of these supports in tandem with other influencing factors requires analysis from an Irish perspective. cross-sectional study involving public health nurses and mothers in Ireland. This paper presents the results of the mothers' evaluation. mothers (n=1715) with children less than three years were offered a choice of completing the self-report questionnaires online or by mail. Data were analysed and reported using descriptive and inferential statistics. four in every five participants breast fed their infant and two thirds of them breast fed as long as planned. The multivariate logistic regression analysis identified that third level education, being a first time mother or previously having breast fed, participating online, having more than two public health nurse visits, and having a positive infant feeding attitude were independently and statistically significantly associated with breast feeding. Among mothers who breast fed, being aged at least 35 years, participating online, having a positive infant feeding attitude and high breast feeding self-efficacy were independently and statistically significantly associated with breast feeding for as long as planned. findings from this study reinforce health inequalities therefore there needs to be a renewed commitment to reducing health inequalities in relation to breast feeding. this study has identified factors associated with initiation and duration of breast feeding that are potentially modifiable through public health interventions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Ground-Based Telescope Parametric Cost Model

NASA Technical Reports Server (NTRS)

Stahl, H. Philip; Rowell, Ginger Holmes

2004-01-01

A parametric cost model for ground-based telescopes is developed using multi-variable statistical analysis, The model includes both engineering and performance parameters. While diameter continues to be the dominant cost driver, other significant factors include primary mirror radius of curvature and diffraction limited wavelength. The model includes an explicit factor for primary mirror segmentation and/or duplication (i.e.. multi-telescope phased-array systems). Additionally, single variable models based on aperture diameter are derived. This analysis indicates that recent mirror technology advances have indeed reduced the historical telescope cost curve.

Modelling runway incursion severity.

PubMed

Wilke, Sabine; Majumdar, Arnab; Ochieng, Washington Y

2015-06-01

Analysis of the causes underlying runway incursions is fundamental for the development of effective mitigation measures. However, there are significant weaknesses in the current methods to model these factors. This paper proposes a structured framework for modelling causal factors and their relationship to severity, which includes a description of the airport surface system architecture, establishment of terminological definitions, the determination and collection of appropriate data, the analysis of occurrences for severity and causes, and the execution of a statistical analysis framework. It is implemented in the context of U.S. airports, enabling the identification of a number of priority interventions, including the need for better investigation and causal factor capture, recommendations for airfield design, operating scenarios and technologies, and better training for human operators in the system. The framework is recommended for the analysis of runway incursions to support safety improvements and the methodology is transferable to other areas of aviation safety risk analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

When Does Neoadjuvant Chemotherapy Really Avoid Radiotherapy? Clinical Predictors of Adjuvant Radiotherapy in Cervical Cancer.

PubMed

Papadia, Andrea; Bellati, Filippo; Bogani, Giorgio; Ditto, Antonino; Martinelli, Fabio; Lorusso, Domenica; Donfrancesco, Cristina; Gasparri, Maria Luisa; Raspagliesi, Francesco

2015-12-01

The aim of this study was to identify clinical variables that may predict the need for adjuvant radiotherapy after neoadjuvant chemotherapy (NACT) and radical surgery in locally advanced cervical cancer patients. A retrospective series of cervical cancer patients with International Federation of Gynecology and Obstetrics (FIGO) stages IB2-IIB treated with NACT followed by radical surgery was analyzed. Clinical predictors of persistence of intermediate- and/or high-risk factors at final pathological analysis were investigated. Statistical analysis was performed using univariate and multivariate analysis and using a model based on artificial intelligence known as artificial neuronal network (ANN) analysis. Overall, 101 patients were available for the analyses. Fifty-two (51 %) patients were considered at high risk secondary to parametrial, resection margin and/or lymph node involvement. When disease was confined to the cervix, four (4 %) patients were considered at intermediate risk. At univariate analysis, FIGO grade 3, stage IIB disease at diagnosis and the presence of enlarged nodes before NACT predicted the presence of intermediate- and/or high-risk factors at final pathological analysis. At multivariate analysis, only FIGO grade 3 and tumor diameter maintained statistical significance. The specificity of ANN models in evaluating predictive variables was slightly superior to conventional multivariable models. FIGO grade, stage, tumor diameter, and histology are associated with persistence of pathological intermediate- and/or high-risk factors after NACT and radical surgery. This information is useful in counseling patients at the time of treatment planning with regard to the probability of being subjected to pelvic radiotherapy after completion of the initially planned treatment.

Concentration of Elements in Food: How Can It Reflect Impact of Environmental and Other Influencing Factors?

NASA Astrophysics Data System (ADS)

Vincevica-Gaile, Zane; Klavins, Maris

2013-12-01

Element content of food is variable and can be influenced by different factors. The aim of the present study was to discover the linkage between macro- and microelement concentrations in food produced in Latvia, and possible impacts of environmental factors. More than 300 fresh food samples such as eggs, cottage cheese, honey, root vegetables, apple juice, apple wine were collected in the time period from 2009 to 2011. Samples were mineralised or analysed directly by appropriate method of quantitative analysis: atomic absorption spectrometry, inductively coupled plasma mass spectrometry or total reflection X-ray fluorescence spectrometry. Statistical analysis of data revealed that food elemental content can be influenced by sitespecific factors such as geographical origin, seasonality, environmental pollution.

Application of radioisotope XRF and thermoluminescence (TL) dating in investigation of pottery from Tell AL-Kasra archaeological site, Syria.

PubMed

Abboud, R; Issa, H; Abed-Allah, Y D; Bakraji, E H

2015-11-01

Statistical analysis based on chemical composition, using radioisotope X-ray fluorescence, have been applied on 39 ancient pottery fragments coming from the excavation at Tell Al-Kasra archaeological site, Syria. Three groups were defined by applying Cluster and Factor analysis statistical methods. Thermoluminescence (TL) dating was investigated on three sherds taken from the bathroom (hammam) on the site. Multiple aliquot additive dose (MAAD) was used to estimate the paleodose value, and the gamma spectrometry was used to estimate the dose rate. The average age was found to be 715±36 year. Copyright © 2015 Elsevier Ltd. All rights reserved.

An investigation of the 'Overlap' between the Statistical-Discrete-Gust and the Power-Spectral-Density analysis methods

NASA Technical Reports Server (NTRS)

Perry, Boyd, III; Pototzky, Anthony S.; Woods, Jessica A.

1989-01-01

This paper presents the results of a NASA investigation of a claimed 'Overlap' between two gust response analysis methods: the Statistical Discrete Gust (SDG) method and the Power Spectral Density (PSD) method. The claim is that the ratio of an SDG response to the corresponding PSD response is 10.4. Analytical results presented in this paper for several different airplanes at several different flight conditions indicate that such an 'Overlap' does appear to exist. However, the claim was not met precisely: a scatter of up to about 10 percent about the 10.4 factor can be expected.

Characterization and classification of oral tissues using excitation and emission matrix: a statistical modeling approach

NASA Astrophysics Data System (ADS)

Kanniyappan, Udayakumar; Gnanatheepaminstein, Einstein; Prakasarao, Aruna; Dornadula, Koteeswaran; Singaravelu, Ganesan

2017-02-01

Cancer is one of the most common human threats around the world and diagnosis based on optical spectroscopy especially fluorescence technique has been established as the standard approach among scientist to explore the biochemical and morphological changes in tissues. In this regard, the present work aims to extract spectral signatures of the various fluorophores present in oral tissues using parallel factor analysis (PARAFAC). Subsequently, the statistical analysis also to be performed to show its diagnostic potential in distinguishing malignant, premalignant from normal oral tissues. Hence, the present study may lead to the possible and/or alternative tool for oral cancer diagnosis.

Spatio-temporal patterns of Barmah Forest virus disease in Queensland, Australia.

PubMed

Naish, Suchithra; Hu, Wenbiao; Mengersen, Kerrie; Tong, Shilu

2011-01-01

Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ(2) = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.

Geographical Distribution Patterns of Iodine in Drinking-Water and Its Associations with Geological Factors in Shandong Province, China

PubMed Central

Gao, Jie; Zhang, Zhijie; Hu, Yi; Bian, Jianchao; Jiang, Wen; Wang, Xiaoming; Sun, Liqian; Jiang, Qingwu

2014-01-01

County-based spatial distribution characteristics and the related geological factors for iodine in drinking-water were studied in Shandong Province (China). Spatial autocorrelation analysis and spatial scan statistic were applied to analyze the spatial characteristics. Generalized linear models (GLMs) and geographically weighted regression (GWR) studies were conducted to explore the relationship between water iodine level and its related geological factors. The spatial distribution of iodine in drinking-water was significantly heterogeneous in Shandong Province (Moran’s I = 0.52, Z = 7.4, p < 0.001). Two clusters for high iodine in drinking-water were identified in the south-western and north-western parts of Shandong Province by the purely spatial scan statistic approach. Both GLMs and GWR indicated a significantly global association between iodine in drinking-water and geological factors. Furthermore, GWR showed obviously spatial variability across the study region. Soil type and distance to Yellow River were statistically significant at most areas of Shandong Province, confirming the hypothesis that the Yellow River causes iodine deposits in Shandong Province. Our results suggested that the more effective regional monitoring plan and water improvement strategies should be strengthened targeting at the cluster areas based on the characteristics of geological factors and the spatial variability of local relationships between iodine in drinking-water and geological factors. PMID:24852390

A three-step approach for the derivation and validation of high-performing predictive models using an operational dataset: congestive heart failure readmission case study.

PubMed

AbdelRahman, Samir E; Zhang, Mingyuan; Bray, Bruce E; Kawamoto, Kensaku

2014-05-27

The aim of this study was to propose an analytical approach to develop high-performing predictive models for congestive heart failure (CHF) readmission using an operational dataset with incomplete records and changing data over time. Our analytical approach involves three steps: pre-processing, systematic model development, and risk factor analysis. For pre-processing, variables that were absent in >50% of records were removed. Moreover, the dataset was divided into a validation dataset and derivation datasets which were separated into three temporal subsets based on changes to the data over time. For systematic model development, using the different temporal datasets and the remaining explanatory variables, the models were developed by combining the use of various (i) statistical analyses to explore the relationships between the validation and the derivation datasets; (ii) adjustment methods for handling missing values; (iii) classifiers; (iv) feature selection methods; and (iv) discretization methods. We then selected the best derivation dataset and the models with the highest predictive performance. For risk factor analysis, factors in the highest-performing predictive models were analyzed and ranked using (i) statistical analyses of the best derivation dataset, (ii) feature rankers, and (iii) a newly developed algorithm to categorize risk factors as being strong, regular, or weak. The analysis dataset consisted of 2,787 CHF hospitalizations at University of Utah Health Care from January 2003 to June 2013. In this study, we used the complete-case analysis and mean-based imputation adjustment methods; the wrapper subset feature selection method; and four ranking strategies based on information gain, gain ratio, symmetrical uncertainty, and wrapper subset feature evaluators. The best-performing models resulted from the use of a complete-case analysis derivation dataset combined with the Class-Attribute Contingency Coefficient discretization method and a voting classifier which averaged the results of multi-nominal logistic regression and voting feature intervals classifiers. Of 42 final model risk factors, discharge disposition, discretized age, and indicators of anemia were the most significant. This model achieved a c-statistic of 86.8%. The proposed three-step analytical approach enhanced predictive model performance for CHF readmissions. It could potentially be leveraged to improve predictive model performance in other areas of clinical medicine.

Variability Analysis of MOS Differential Amplifier

NASA Astrophysics Data System (ADS)

Aoki, Masakazu; Seto, Kenji; Yamawaki, Taizo; Tanaka, Satoshi

Variation characteristics in MOS differential amplifier are evaluated by using the concise statistical model parameters for SPICE simulation. We find that the variation in the differential-mode gain, Adm, induced by the current factor variation, Δβ0, in the Id-variation of the differential MOS transistors is more than one order of magnitude larger than that induced by the threshold voltage variation, ΔVth, which has been regarded as a major factor for circuit variations in SoC's (2). The results obtained by the Monte Carlo simulations are verified by the theoretical analysis combined with the sensitivity analysis which clarifies the specific device parameter dependences of the variation in Adm.

Risk factors for superficial surgical site infection after elective rectal cancer resection: a multivariate analysis of 8880 patients from the American College of Surgeons National Surgical Quality Improvement Program database.

PubMed

Sutton, Elie; Miyagaki, Hiromichi; Bellini, Geoffrey; Shantha Kumara, H M C; Yan, Xiaohong; Howe, Brett; Feigel, Amanda; Whelan, Richard L

2017-01-01

Superficial surgical site infection (sSSI) is one of the most common complications after colorectal resection. The goal of this study was to determine the comorbidities and operative characteristics that place patients at risk for sSSI in patients who underwent rectal cancer resection. The American College of Surgeons National Surgical Quality Improvement Program database was queried (via diagnosis and Current Procedural Terminology codes) for patients with rectal cancer who underwent elective resection between 2005 and 2012. Patients for whom data concerning 27 demographic factors, comorbidities, and operative characteristics were available were eligible. A univariate and multivariate analysis was performed to identify possible risk factors for sSSI. A total of 8880 patients met the entry criteria and were included. sSSIs were diagnosed in 861 (9.7%) patients. Univariate analysis found 14 patients statistically significant risk factors for sSSI. Multivariate analysis revealed the following risk factors: male gender, body mass index (BMI) >30, current smoking, history of chronic obstructive pulmonary disease (COPD), American Society of Anesthesiologists III/IV, abdominoperineal resection (APR), stoma formation, open surgery (versus laparoscopic), and operative time >217 min. The greatest difference in sSSI rates was noted in patients with COPD (18.9 versus 9.5%). Of note, 54.2% of sSSIs was noted after hospital discharge. With regard to the timing of presentation, univariate analysis revealed a statistically significant delay in sSSI presentation in patients with the following factors and/or characteristics: BMI <30, previous radiation therapy (RT), APR, minimally invasive surgery, and stoma formation. Multivariate analysis suggested that only laparoscopic surgery (versus open) and preoperative RT were risk factors for delay. Rectal cancer resections are associated with a high incidence of sSSIs, over half of which are noted after discharge. Nine patient and operative characteristics, including smoking, BMI, COPD, APR, and open surgery were found to be significant risk factors for SSI on multivariate analysis. Furthermore, sSSI presentation in patients who had laparoscopic surgery and those who had preoperative RT is significantly delayed for unclear reasons. Copyright © 2016 Elsevier Inc. All rights reserved.

Executive Order 12898 and Social, Economic, and Sociopolitical Factors Influencing Toxic Release Inventory Facility Location in EPA Region 6: A Multi-Scale Spatial Assessment of Environmental Justice

ERIC Educational Resources Information Center

Moore, Andrea Lisa

2013-01-01

Toxic Release Inventory facilities are among the many environmental hazards shown to create environmental inequities in the United States. This project examined four factors associated with Toxic Release Inventory, specifically, manufacturing facility location at multiple spatial scales using spatial analysis techniques (i.e., O-ring statistic and…

Quantitative investigation of inappropriate regression model construction and the importance of medical statistics experts in observational medical research: a cross-sectional study.

PubMed

Nojima, Masanori; Tokunaga, Mutsumi; Nagamura, Fumitaka

2018-05-05

To investigate under what circumstances inappropriate use of 'multivariate analysis' is likely to occur and to identify the population that needs more support with medical statistics. The frequency of inappropriate regression model construction in multivariate analysis and related factors were investigated in observational medical research publications. The inappropriate algorithm of using only variables that were significant in univariate analysis was estimated to occur at 6.4% (95% CI 4.8% to 8.5%). This was observed in 1.1% of the publications with a medical statistics expert (hereinafter 'expert') as the first author, 3.5% if an expert was included as coauthor and in 12.2% if experts were not involved. In the publications where the number of cases was 50 or less and the study did not include experts, inappropriate algorithm usage was observed with a high proportion of 20.2%. The OR of the involvement of experts for this outcome was 0.28 (95% CI 0.15 to 0.53). A further, nation-level, analysis showed that the involvement of experts and the implementation of unfavourable multivariate analysis are associated at the nation-level analysis (R=-0.652). Based on the results of this study, the benefit of participation of medical statistics experts is obvious. Experts should be involved for proper confounding adjustment and interpretation of statistical models. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Preoperative Carcinoembryonic Antigen and Prognosis of Colorectal Cancer. An Independent Prognostic Factor Still Reliable

PubMed Central

Li Destri, Giovanni; Rubino, Antonio Salvatore; Latino, Rosalia; Giannone, Fabio; Lanteri, Raffaele; Scilletta, Beniamino; Di Cataldo, Antonio

2015-01-01

To evaluate whether, in a sample of patients radically treated for colorectal carcinoma, the preoperative determination of the carcinoembryonic antigen (p-CEA) may have a prognostic value and constitute an independent risk factor in relation to disease-free survival. The preoperative CEA seems to be related both to the staging of colorectal neoplasia and to the patient's prognosis, although this—to date—has not been conclusively demonstrated and is still a matter of intense debate in the scientific community. This is a retrospective analysis of prospectively collected data. A total of 395 patients were radically treated for colorectal carcinoma. The preoperative CEA was statistically compared with the 2010 American Joint Committee on Cancer (AJCC) staging, the T and N parameters, and grading. All parameters recorded in our database were tested for an association with disease-free survival (DFS). Only factors significantly associated (P < 0.05) with the DFS were used to build multivariate stepwise forward logistic regression models to establish their independent predictors. A statistically significant relationship was found between p-CEA and tumor staging (P < 0.001), T (P < 0.001) and N parameters (P = 0.006). In a multivariate analysis, the independent prognostic factors found were: p-CEA, stages N1 and N2 according to AJCC, and G3 grading (grade). A statistically significant difference (P < 0.001) was evident between the DFS of patients with normal and high p-CEA levels. Preoperative CEA makes a pre-operative selection possible of those patients for whom it is likely to be able to predict a more advanced staging. PMID:25875542

Preoperative carcinoembryonic antigen and prognosis of colorectal cancer. An independent prognostic factor still reliable.

PubMed

Li Destri, Giovanni; Rubino, Antonio Salvatore; Latino, Rosalia; Giannone, Fabio; Lanteri, Raffaele; Scilletta, Beniamino; Di Cataldo, Antonio

2015-04-01

To evaluate whether, in a sample of patients radically treated for colorectal carcinoma, the preoperative determination of the carcinoembryonic antigen (p-CEA) may have a prognostic value and constitute an independent risk factor in relation to disease-free survival. The preoperative CEA seems to be related both to the staging of colorectal neoplasia and to the patient's prognosis, although this-to date-has not been conclusively demonstrated and is still a matter of intense debate in the scientific community. This is a retrospective analysis of prospectively collected data. A total of 395 patients were radically treated for colorectal carcinoma. The preoperative CEA was statistically compared with the 2010 American Joint Committee on Cancer (AJCC) staging, the T and N parameters, and grading. All parameters recorded in our database were tested for an association with disease-free survival (DFS). Only factors significantly associated (P < 0.05) with the DFS were used to build multivariate stepwise forward logistic regression models to establish their independent predictors. A statistically significant relationship was found between p-CEA and tumor staging (P < 0.001), T (P < 0.001) and N parameters (P = 0.006). In a multivariate analysis, the independent prognostic factors found were: p-CEA, stages N1 and N2 according to AJCC, and G3 grading (grade). A statistically significant difference (P < 0.001) was evident between the DFS of patients with normal and high p-CEA levels. Preoperative CEA makes a pre-operative selection possible of those patients for whom it is likely to be able to predict a more advanced staging.

Quantitative topographic differentiation of the neonatal EEG.

PubMed

Paul, Karel; Krajca, Vladimír; Roth, Zdenek; Melichar, Jan; Petránek, Svojmil

2006-09-01

To test the discriminatory topographic potential of a new method of the automatic EEG analysis in neonates. A quantitative description of the neonatal EEG can contribute to the objective assessment of the functional state of the brain, and may improve the precision of diagnosing cerebral dysfunctions manifested by 'disorganization', 'dysrhythmia' or 'dysmaturity'. 21 healthy, full-term newborns were examined polygraphically during sleep (EEG-8 referential derivations, respiration, ECG, EOG, EMG). From each EEG record, two 5-min samples (one from the middle of quiet sleep, the other from the middle of active sleep) were subject to subsequent automatic analysis and were described by 13 variables: spectral features and features describing shape and variability of the signal. The data from individual infants were averaged and the number of variables was reduced by factor analysis. All factors identified by factor analysis were statistically significantly influenced by the location of derivation. A large number of statistically significant differences were also established when comparing the effects of individual derivations on each of the 13 measured variables. Both spectral features and features describing shape and variability of the signal are largely accountable for the topographic differentiation of the neonatal EEG. The presented method of the automatic EEG analysis is capable to assess the topographic characteristics of the neonatal EEG, and it is adequately sensitive and describes the neonatal electroencephalogram with sufficient precision. The discriminatory capability of the used method represents a promise for their application in the clinical practice.

Bayesian hypothesis testing for human threat conditioning research: an introduction and the condir R package

PubMed Central

Krypotos, Angelos-Miltiadis; Klugkist, Irene; Engelhard, Iris M.

2017-01-01

ABSTRACT Threat conditioning procedures have allowed the experimental investigation of the pathogenesis of Post-Traumatic Stress Disorder. The findings of these procedures have also provided stable foundations for the development of relevant intervention programs (e.g. exposure therapy). Statistical inference of threat conditioning procedures is commonly based on p-values and Null Hypothesis Significance Testing (NHST). Nowadays, however, there is a growing concern about this statistical approach, as many scientists point to the various limitations of p-values and NHST. As an alternative, the use of Bayes factors and Bayesian hypothesis testing has been suggested. In this article, we apply this statistical approach to threat conditioning data. In order to enable the easy computation of Bayes factors for threat conditioning data we present a new R package named condir, which can be used either via the R console or via a Shiny application. This article provides both a non-technical introduction to Bayesian analysis for researchers using the threat conditioning paradigm, and the necessary tools for computing Bayes factors easily. PMID:29038683

Integrated ITS capabilities in transit vehicles : human factors research needs : summary report

DOT National Transportation Integrated Search

2005-08-30

This synthesis reviews statistics and activities of public private partnership activities in transportation around the world between 1985 and 2004. The data used for the analysis is from the 2004 International Public Works Financing Projects Database...

Diffuse nutrient losses and the impact factors determining their regional differences in four catchments from North to South China

NASA Astrophysics Data System (ADS)

Zhang, Yongyong; Zhou, Yujian; Shao, Quanxi; Liu, Hongbin; Lei, Qiuliang; Zhai, Xiaoyan; Wang, Xuelei

2016-12-01

Diffuse nutrient loss mechanism is complicated and shows remarkably regional differences due to spatial heterogeneities of underlying surface conditions, climate and agricultural practices. Moreover, current available observations are still hard to support the identification of impact factors due to different time or space steps. In this study, an integrated water system model (HEQM) was adopted to obtain the simulated loads of diffuse components (carriers: runoff and sediment; nutrient: total nitrogen (TN) and total phosphorous (TP)) with synchronous scales. Multivariable statistical analysis approaches (Analysis of Similarity and redundancy analysis) were used to assess the regional differences, and to identify impact factors as well as their contributions. Four catchments were selected as our study areas, i.e., Xiahui and Zhangjiafen Catchments of Miyun Basin in North China, Yuliang and Tunxi Catchments of Xin'anjiang Basin in South China. Results showed that the model performances of monthly processes were very good for runoff and good for sediment, TN and TP. The annual average coefficients of all the diffuse components in Xin'anjiang Basin were much greater than those in Miyun Basin, and showed significantly regional differences. All the selected impact factors interpreted 72.87-82.16% of the regional differences of carriers, and 62.72-71.62% of those of nutrient coefficients, respectively. For individual impact factor categories, the critical category was geography, followed by land-use/cover, carriers, climate, as well as soil and agricultural practices in Miyun Basin, or agricultural practices and soil in Xin'anjiang Basin. For individual factors, the critical factors were locations for the carrier regional differences, and carriers or chemical fertilizer for the nutrient regional differences. This study is expected to promote further applications of integrated water system model and multivariable statistical analysis in the diffuse nutrient studies, and provide a scientific support for the diffuse pollution control and management in China.

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

PubMed Central

Zheng, Mingguo; Chen, Xiaoan

2015-01-01

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

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

PubMed

Zheng, Mingguo; Chen, Xiaoan

2015-01-01

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

Enhancing efficiency and quality of statistical estimation of immunogenicity assay cut points through standardization and automation.

PubMed

Su, Cheng; Zhou, Lei; Hu, Zheng; Weng, Winnie; Subramani, Jayanthi; Tadkod, Vineet; Hamilton, Kortney; Bautista, Ami; Wu, Yu; Chirmule, Narendra; Zhong, Zhandong Don

2015-10-01

Biotherapeutics can elicit immune responses, which can alter the exposure, safety, and efficacy of the therapeutics. A well-designed and robust bioanalytical method is critical for the detection and characterization of relevant anti-drug antibody (ADA) and the success of an immunogenicity study. As a fundamental criterion in immunogenicity testing, assay cut points need to be statistically established with a risk-based approach to reduce subjectivity. This manuscript describes the development of a validated, web-based, multi-tier customized assay statistical tool (CAST) for assessing cut points of ADA assays. The tool provides an intuitive web interface that allows users to import experimental data generated from a standardized experimental design, select the assay factors, run the standardized analysis algorithms, and generate tables, figures, and listings (TFL). It allows bioanalytical scientists to perform complex statistical analysis at a click of the button to produce reliable assay parameters in support of immunogenicity studies. Copyright © 2015 Elsevier B.V. All rights reserved.

High-order fuzzy time-series based on multi-period adaptation model for forecasting stock markets

NASA Astrophysics Data System (ADS)

Chen, Tai-Liang; Cheng, Ching-Hsue; Teoh, Hia-Jong

2008-02-01

Stock investors usually make their short-term investment decisions according to recent stock information such as the late market news, technical analysis reports, and price fluctuations. To reflect these short-term factors which impact stock price, this paper proposes a comprehensive fuzzy time-series, which factors linear relationships between recent periods of stock prices and fuzzy logical relationships (nonlinear relationships) mined from time-series into forecasting processes. In empirical analysis, the TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) and HSI (Heng Seng Index) are employed as experimental datasets, and four recent fuzzy time-series models, Chen’s (1996), Yu’s (2005), Cheng’s (2006) and Chen’s (2007), are used as comparison models. Besides, to compare with conventional statistic method, the method of least squares is utilized to estimate the auto-regressive models of the testing periods within the databases. From analysis results, the performance comparisons indicate that the multi-period adaptation model, proposed in this paper, can effectively improve the forecasting performance of conventional fuzzy time-series models which only factor fuzzy logical relationships in forecasting processes. From the empirical study, the traditional statistic method and the proposed model both reveal that stock price patterns in the Taiwan stock and Hong Kong stock markets are short-term.

Integrated Application of Multivariate Statistical Methods to Source Apportionment of Watercourses in the Liao River Basin, Northeast China

PubMed Central

Chen, Jiabo; Li, Fayun; Fan, Zhiping; Wang, Yanjie

2016-01-01

Source apportionment of river water pollution is critical in water resource management and aquatic conservation. Comprehensive application of various GIS-based multivariate statistical methods was performed to analyze datasets (2009–2011) on water quality in the Liao River system (China). Cluster analysis (CA) classified the 12 months of the year into three groups (May–October, February–April and November–January) and the 66 sampling sites into three groups (groups A, B and C) based on similarities in water quality characteristics. Discriminant analysis (DA) determined that temperature, dissolved oxygen (DO), pH, chemical oxygen demand (CODMn), 5-day biochemical oxygen demand (BOD5), NH4+–N, total phosphorus (TP) and volatile phenols were significant variables affecting temporal variations, with 81.2% correct assignments. Principal component analysis (PCA) and positive matrix factorization (PMF) identified eight potential pollution factors for each part of the data structure, explaining more than 61% of the total variance. Oxygen-consuming organics from cropland and woodland runoff were the main latent pollution factor for group A. For group B, the main pollutants were oxygen-consuming organics, oil, nutrients and fecal matter. For group C, the evaluated pollutants primarily included oxygen-consuming organics, oil and toxic organics. PMID:27775679

Bayesian Factor Analysis as a Variable Selection Problem: Alternative Priors and Consequences

PubMed Central

Lu, Zhao-Hua; Chow, Sy-Miin; Loken, Eric

2016-01-01

Factor analysis is a popular statistical technique for multivariate data analysis. Developments in the structural equation modeling framework have enabled the use of hybrid confirmatory/exploratory approaches in which factor loading structures can be explored relatively flexibly within a confirmatory factor analysis (CFA) framework. Recently, a Bayesian structural equation modeling (BSEM) approach (Muthén & Asparouhov, 2012) has been proposed as a way to explore the presence of cross-loadings in CFA models. We show that the issue of determining factor loading patterns may be formulated as a Bayesian variable selection problem in which Muthén and Asparouhov’s approach can be regarded as a BSEM approach with ridge regression prior (BSEM-RP). We propose another Bayesian approach, denoted herein as the Bayesian structural equation modeling with spike and slab prior (BSEM-SSP), which serves as a one-stage alternative to the BSEM-RP. We review the theoretical advantages and disadvantages of both approaches and compare their empirical performance relative to two modification indices-based approaches and exploratory factor analysis with target rotation. A teacher stress scale data set (Byrne, 2012; Pettegrew & Wolf, 1982) is used to demonstrate our approach. PMID:27314566

Metal and physico-chemical variations at a hydroelectric reservoir analyzed by Multivariate Analyses and Artificial Neural Networks: environmental management and policy/decision-making tools.

PubMed

Cavalcante, Y L; Hauser-Davis, R A; Saraiva, A C F; Brandão, I L S; Oliveira, T F; Silveira, A M

2013-01-01

This paper compared and evaluated seasonal variations in physico-chemical parameters and metals at a hydroelectric power station reservoir by applying Multivariate Analyses and Artificial Neural Networks (ANN) statistical techniques. A Factor Analysis was used to reduce the number of variables: the first factor was composed of elements Ca, K, Mg and Na, and the second by Chemical Oxygen Demand. The ANN showed 100% correct classifications in training and validation samples. Physico-chemical analyses showed that water pH values were not statistically different between the dry and rainy seasons, while temperature, conductivity, alkalinity, ammonia and DO were higher in the dry period. TSS, hardness and COD, on the other hand, were higher during the rainy season. The statistical analyses showed that Ca, K, Mg and Na are directly connected to the Chemical Oxygen Demand, which indicates a possibility of their input into the reservoir system by domestic sewage and agricultural run-offs. These statistical applications, thus, are also relevant in cases of environmental management and policy decision-making processes, to identify which factors should be further studied and/or modified to recover degraded or contaminated water bodies. Copyright © 2012 Elsevier B.V. All rights reserved.

To Nap, Perchance to DREAM: A Factor Analysis of College Students' Self-Reported Reasons for Napping.

PubMed

Duggan, Katherine A; McDevitt, Elizabeth A; Whitehurst, Lauren N; Mednick, Sara C

2018-01-01

Although napping has received attention because of its associations with health and use as a method to understand the function of sleep, to our knowledge no study has systematically and statistically assessed reasons for napping. Using factor analysis, we determined the underlying structure of reasons for napping in diverse undergraduates (N = 430, 59% female) and examined their relationships with self-reported sleep, psychological health, and physical health. The five reasons for napping can be summarized using the acronym DREAM (Dysregulative, Restorative, Emotional, Appetitive, and Mindful). Only Emotional reasons for napping were uniformly related to lower well-being. The use of factor analysis raises possibilities for future research, including examining the stability, structure, and psychological and physical health processes related to napping throughout the lifespan.

To nap, perchance to DREAM: A factor analysis of college students’ self-reported reasons for napping

PubMed Central

Duggan, Katherine A.; McDevitt, Elizabeth A.; Whitehurst, Lauren N.; Mednick, Sara C.

2017-01-01

Although napping has received attention because of its associations with health and use as a method to understand the function of sleep, to our knowledge no study has systematically and statistically assessed reasons for napping. Using factor analysis, we determined the underlying structure of reasons for napping in diverse undergraduates (N=430, 59% female) and examined their relationships with self-reported sleep, psychological, and physical health. The 5 reasons for napping can be summarized using the acronym DREAM (Dysregulative, Restorative, Emotional, Appetitive, and Mindful). Only Emotional reasons for napping were uniformly related to lower well-being. The use of factor analysis raises possibilities for future research, including examining the stability, structure, and psychological and physical health processes related to napping throughout the lifespan. PMID:27347727

Implementation of quality by design principles in the development of microsponges as drug delivery carriers: Identification and optimization of critical factors using multivariate statistical analyses and design of experiments studies.

PubMed

Simonoska Crcarevska, Maja; Dimitrovska, Aneta; Sibinovska, Nadica; Mladenovska, Kristina; Slavevska Raicki, Renata; Glavas Dodov, Marija

2015-07-15

Microsponges drug delivery system (MDDC) was prepared by double emulsion-solvent-diffusion technique using rotor-stator homogenization. Quality by design (QbD) concept was implemented for the development of MDDC with potential to be incorporated into semisolid dosage form (gel). Quality target product profile (QTPP) and critical quality attributes (CQA) were defined and identified, accordingly. Critical material attributes (CMA) and Critical process parameters (CPP) were identified using quality risk management (QRM) tool, failure mode, effects and criticality analysis (FMECA). CMA and CPP were identified based on results obtained from principal component analysis (PCA-X&Y) and partial least squares (PLS) statistical analysis along with literature data, product and process knowledge and understanding. FMECA identified amount of ethylcellulose, chitosan, acetone, dichloromethane, span 80, tween 80 and water ratio in primary/multiple emulsions as CMA and rotation speed and stirrer type used for organic solvent removal as CPP. The relationship between identified CPP and particle size as CQA was described in the design space using design of experiments - one-factor response surface method. Obtained results from statistically designed experiments enabled establishment of mathematical models and equations that were used for detailed characterization of influence of identified CPP upon MDDC particle size and particle size distribution and their subsequent optimization. Copyright © 2015 Elsevier B.V. All rights reserved.

Prevalence, cause, and location of palatal fistula in operated complete unilateral cleft lip and palate: retrospective study.

PubMed

de Agostino Biella Passos, Vivian; de Carvalho Carrara, Cleide Felício; da Silva Dalben, Gisele; Costa, Beatriz; Gomide, Marcia Ribeiro

2014-03-01

To evaluate the prevalence of fistulas after palate repair and analyze their location and association with possible causal factors. Retrospective analysis of patient records and evaluation of preoperative initial photographs. Tertiary craniofacial center. Five hundred eighty-nine individuals with complete unilateral cleft lip and palate that underwent palate repair at the age of 12 to 36 months by the von Langenbeck technique, in a single stage, by the plastic surgery team of the hospital, from January 2003 to July 2007. The cleft width was visually classified by a single examiner as narrow, regular, or wide. The following regions of the palate were considered for the location: anterior, medium, transition (between hard and soft palate), and soft palate. Descriptive statistics and analysis of association between the occurrence of fistula and the different parameters were evaluated. Palatal fistulas were observed in 27% of the sample, with a greater proportion at the anterior region (37.11%). The chi-square statistical test revealed statistically significant association (P ≤ .05) between the fistulas and initial cleft width (P = .0003), intraoperative problems (P = .0037), and postoperative problems (P = .00002). The prevalence of palatal fistula was similar to mean values reported in the literature. Analysis of causal factors showed a positive association between palatal fistulas with wide and regular initial cleft width and intraoperative and postoperative problems. The anterior region presented the greatest occurrence of fistulas.

Wave energy resource of Brazil: An analysis from 35 years of ERA-Interim reanalysis data

PubMed Central

Araújo, Alex Maurício

2017-01-01

This paper presents a characterization of the wave power resource and an analysis of the wave power output for three (AquaBuoy, Pelamis and Wave Dragon) different wave energy converters (WEC) over the Brazilian offshore. To do so it used a 35 years reanalysis database from the ERA-Interim project. Annual and seasonal statistical analyzes of significant height and energy period were performed, and the directional variability of the incident waves were evaluated. The wave power resource was characterized in terms of the statistical parameters of mean, maximum, 95th percentile and standard deviation, and in terms of the temporal variability coefficients COV, SV e MV. From these analyses, the total annual wave power resource available over the Brazilian offshore was estimated in 89.97 GW, with largest mean wave power of 20.63 kW/m in the southernmost part of the study area. The analysis of the three WEC was based in the annual wave energy output and in the capacity factor. The higher capacity factor was 21.85% for Pelamis device at the southern region of the study area. PMID:28817731

Wave energy resource of Brazil: An analysis from 35 years of ERA-Interim reanalysis data.

PubMed

Espindola, Rafael Luz; Araújo, Alex Maurício

2017-01-01

This paper presents a characterization of the wave power resource and an analysis of the wave power output for three (AquaBuoy, Pelamis and Wave Dragon) different wave energy converters (WEC) over the Brazilian offshore. To do so it used a 35 years reanalysis database from the ERA-Interim project. Annual and seasonal statistical analyzes of significant height and energy period were performed, and the directional variability of the incident waves were evaluated. The wave power resource was characterized in terms of the statistical parameters of mean, maximum, 95th percentile and standard deviation, and in terms of the temporal variability coefficients COV, SV e MV. From these analyses, the total annual wave power resource available over the Brazilian offshore was estimated in 89.97 GW, with largest mean wave power of 20.63 kW/m in the southernmost part of the study area. The analysis of the three WEC was based in the annual wave energy output and in the capacity factor. The higher capacity factor was 21.85% for Pelamis device at the southern region of the study area.

Traumatic injury among drywall installers, 1992 to 1995.

PubMed

Chiou, S S; Pan, C S; Keane, P

2000-11-01

This study examined the traumatic-injury characteristics associated with one of the high-risk occupations in the construction industry--drywall installers--through an analysis of the traumatic-injury data obtained from the Bureau of Labor Statistics. An additional objective was to demonstrate a feasible and economic approach to identify risk factors associated with a specific occupation by using an existing database. An analysis of nonfatal traumatic injuries with days away from work among wage-and-salary drywall installers was performed for 1992 through 1995 using the Occupational Injury and Illness Survey conducted by the Bureau of Labor Statistics. Results from this study indicate that drywall installers are at a high risk of overexertion and falls to a lower level. More than 40% of the injured drywall installers suffered sprains, strains, and/or tears. The most frequently injured body part was the trunk. More than one-third of the trunk injuries occurred while handling solid building materials, mainly drywall. In addition, the database analysis used in this study is valid in identifying overall risk factors for specific occupations.

Statistical approaches to account for missing values in accelerometer data: Applications to modeling physical activity.

PubMed

Yue Xu, Selene; Nelson, Sandahl; Kerr, Jacqueline; Godbole, Suneeta; Patterson, Ruth; Merchant, Gina; Abramson, Ian; Staudenmayer, John; Natarajan, Loki

2018-04-01

Physical inactivity is a recognized risk factor for many chronic diseases. Accelerometers are increasingly used as an objective means to measure daily physical activity. One challenge in using these devices is missing data due to device nonwear. We used a well-characterized cohort of 333 overweight postmenopausal breast cancer survivors to examine missing data patterns of accelerometer outputs over the day. Based on these observed missingness patterns, we created psuedo-simulated datasets with realistic missing data patterns. We developed statistical methods to design imputation and variance weighting algorithms to account for missing data effects when fitting regression models. Bias and precision of each method were evaluated and compared. Our results indicated that not accounting for missing data in the analysis yielded unstable estimates in the regression analysis. Incorporating variance weights and/or subject-level imputation improved precision by >50%, compared to ignoring missing data. We recommend that these simple easy-to-implement statistical tools be used to improve analysis of accelerometer data.

Circularly-symmetric complex normal ratio distribution for scalar transmissibility functions. Part III: Application to statistical modal analysis

NASA Astrophysics Data System (ADS)

Yan, Wang-Ji; Ren, Wei-Xin

2018-01-01

This study applies the theoretical findings of circularly-symmetric complex normal ratio distribution Yan and Ren (2016) [1,2] to transmissibility-based modal analysis from a statistical viewpoint. A probabilistic model of transmissibility function in the vicinity of the resonant frequency is formulated in modal domain, while some insightful comments are offered. It theoretically reveals that the statistics of transmissibility function around the resonant frequency is solely dependent on 'noise-to-signal' ratio and mode shapes. As a sequel to the development of the probabilistic model of transmissibility function in modal domain, this study poses the process of modal identification in the context of Bayesian framework by borrowing a novel paradigm. Implementation issues unique to the proposed approach are resolved by Lagrange multiplier approach. Also, this study explores the possibility of applying Bayesian analysis in distinguishing harmonic components and structural ones. The approaches are verified through simulated data and experimentally testing data. The uncertainty behavior due to variation of different factors is also discussed in detail.

Factors affecting the prevalence of chronic diseases in Palestinian people: an analysis of data from the Palestinian Central Bureau of Statistics.

PubMed

Abukhdeir, H F; Caplan, L S; Reese, L; Alema-Mensah, E

2013-04-01

This study determined whether there are significant differences in the prevalence of diabetes, hypertension, cardiovascular disease (CVD) and cancer among Palestinians with respect to different demographic variables using secondary data from the Palestinian Central Bureau of Statistics. Living in the Gaza Strip was a protective factor, with this group being 21% less likely to have diabetes, 35% less likely to have hypertension, and 48% less likely to have CVD than those living in the West Bank. No significant difference was found for cancer. Being a refugee was a significant risk factor for diabetes and CVD while being married/engaged or divorced/ separated/widowed was a risk factor for diabetes and hypertension. Gender was a risk factor for hypertension with females being 60% more likely to have hypertension than males. Living in a rural setting was protective against hypertension. As expected, age was a risk factor for diabetes, hypertension and CVD; the magnitude of this increased risk was alarming, 36 to 434 times greater in those aged 40-65 years compared with those aged 0-19 years.

EVALUATION OF FACTORS IN THE ELUTION OF HYDROCORTISONE FROM PAPER CHROMATOGRAMS

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

Ganis, F.M.; Hendrickson, M.W.; Giunta, P.D.

An assessment was made of a number of variable factors which affect the recovery of hydrocortisone from eluted filter paper chromatographic fractions. Factors tested included time of elution, sample concentration, rinsing of eluting fractions and pre-washing of the filter paper. It was noted that a 50 mu g sample could be quantitatively recovered after a 15-minute elution time from a pre-washed filter paper fraction. The results were subjected to a statistical analysis and were found to be highly significant. (auth)

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

PubMed

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

2016-01-15

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

Postpartum screening practices, progression to abnormal glucose tolerance and its related risk factors in Asian women with a known history of gestational diabetes: A systematic review and meta-analysis.

PubMed

Nouhjah, Sedigheh; Shahbazian, Hajieh; Amoori, Neda; Jahanfar, Shayesteh; Shahbazian, Nahid; Jahanshahi, Alireza; Cheraghian, Bahman

2017-12-01

Rate of postpartum screening and progression to glucose intolerance (diabetes and/or pre-diabetes) in Asian women with prior GDM and risk factors of diversion to abnormal glucose tolerance were reviewed. We searched Pub Med, Cochrane Library, Web of Science, EMBASE, and Ovid data base. About 1300 studies were screened and 27 articles were selected. Meta-analysis using Comprehensive Meta -Analysis software was conducted. All results were reported at the pooled ORs and 95% CI. Quantitative heterogeneity (I 2 ) was assessed. To estimate the variances between studies, the statistical method "tau-squared" was applied. Statistical models like fixed effect or Mantel-Haenszel, and random effect (REM) or Dersimonian-laird were used for the analysis and integration of results. Rate of glucose testing ranged from 13.1% to 81.9%. Prevalence of pre-diabetes was 3.9%-50.9%. Diabetes was reported in 2.8%-58% of women with history of gestational diabetes based on length of follow-up. Factor associated with postpartum diabetes mellitus included family History of diabetes mellitus, gestational age at diagnosis of GDM, insulin use during pregnancy and pre-pregnancy BMI. Rate of postpartum screening in most of the Asian countries population is sub-optimal, in spite of high rate of glucose intolerance in this high risk group of women. Risk factors of progression to pre-diabetes and diabetes are similar to previous reported in developed countries. Copyright © 2017 Diabetes India. All rights reserved.

Factors influencing health professions students' use of computers for data analysis at three Ugandan public medical schools: a cross-sectional survey.

PubMed

Munabi, Ian G; Buwembo, William; Bajunirwe, Francis; Kitara, David Lagoro; Joseph, Ruberwa; Peter, Kawungezi; Obua, Celestino; Quinn, John; Mwaka, Erisa S

2015-02-25

Effective utilization of computers and their applications in medical education and research is of paramount importance to students. The objective of this study was to determine the association between owning a computer and use of computers for research data analysis and the other factors influencing health professions students' computer use for data analysis. We conducted a cross sectional study among undergraduate health professions students at three public universities in Uganda using a self-administered questionnaire. The questionnaire was composed of questions on participant demographics, students' participation in research, computer ownership, and use of computers for data analysis. Descriptive and inferential statistics (uni-variable and multi- level logistic regression analysis) were used to analyse data. The level of significance was set at 0.05. Six hundred (600) of 668 questionnaires were completed and returned (response rate 89.8%). A majority of respondents were male (68.8%) and 75.3% reported owning computers. Overall, 63.7% of respondents reported that they had ever done computer based data analysis. The following factors were significant predictors of having ever done computer based data analysis: ownership of a computer (adj. OR 1.80, p = 0.02), recently completed course in statistics (Adj. OR 1.48, p =0.04), and participation in research (Adj. OR 2.64, p <0.01). Owning a computer, participation in research and undertaking courses in research methods influence undergraduate students' use of computers for research data analysis. Students are increasingly participating in research, and thus need to have competencies for the successful conduct of research. Medical training institutions should encourage both curricular and extra-curricular efforts to enhance research capacity in line with the modern theories of adult learning.

Mesopic pupil size in a refractive surgery population (13,959 eyes).

PubMed

Linke, Stephan J; Baviera, Julio; Munzer, Gur; Fricke, Otto H; Richard, Gisbert; Katz, Toam

2012-08-01

To evaluate factors that may affect mesopic pupil size in refractive surgery candidates. Medical records of 13,959 eyes of 13,959 refractive surgery candidates were reviewed, and one eye per subject was selected randomly for statistical analysis. Detailed ophthalmological examination data were obtained from medical records. Preoperative measurements included uncorrected distance visual acuity, corrected distance visual acuity, manifest and cycloplegic refraction, topography, slit lamp examination, and funduscopy. Mesopic pupil size measurements were performed with Colvard pupillometer. Relationship between mesopic pupil size and age, gender, refractive state, average keratometry, and pachymetry (thinnest point) were analyzed by means of ANOVA (+ANCOVA) and multivariate regression analyses. Overall mesopic pupil size was 6.45 ± 0.82 mm, and mean age was 36.07 years. Mesopic pupil size was 5.96 ± 0.8 mm in hyperopic astigmatism, 6.36 ± 0.83 mm in high astigmatism, and 6.51 ± 0.8 mm in myopic astigmatism. The difference in mesopic pupil size between all refractive subgroups was statistically significant (p < 0.001). Age revealed the strongest correlation (r = -0.405, p < 0.001) with mesopic pupil size. Spherical equivalent showed a moderate correlation (r = -0.136), whereas keratometry (r = -0.064) and pachymetry (r = -0.057) had a weak correlation with mesopic pupil size. No statistically significant difference in mesopic pupil size was noted regarding gender and ocular side. The sum of all analyzed factors (age, refractive state, keratometry, and pachymetry) can only predict the expected pupil size in <20% (R = 0.179, p < 0.001). Our analysis confirmed that age and refractive state are determinative factors on mesopic pupil size. Average keratometry and minimal pachymetry exhibited a statistically significant, but clinically insignificant, impact on mesopic pupil size.

The volume-mortality relation for radical cystectomy in England: retrospective analysis of hospital episode statistics

PubMed Central

Bottle, Alex; Darzi, Ara W; Athanasiou, Thanos; Vale, Justin A

2010-01-01

Objectives To investigate the relation between volume and mortality after adjustment for case mix for radical cystectomy in the English healthcare setting using improved statistical methodology, taking into account the institutional and surgeon volume effects and institutional structural and process of care factors. Design Retrospective analysis of hospital episode statistics using multilevel modelling. Setting English hospitals carrying out radical cystectomy in the seven financial years 2000/1 to 2006/7. Participants Patients with a primary diagnosis of cancer undergoing an inpatient elective cystectomy. Main outcome measure Mortality within 30 days of cystectomy. Results Compared with low volume institutions, medium volume ones had a significantly higher odds of in-hospital and total mortality: odds ratio 1.72 (95% confidence interval 1.00 to 2.98, P=0.05) and 1.82 (1.08 to 3.06, P=0.02). This was only seen in the final model, which included adjustment for structural and processes of care factors. The surgeon volume-mortality relation showed weak evidence of reduced odds of in-hospital mortality (by 35%) for the high volume surgeons, although this did not reach statistical significance at the 5% level. Conclusions The relation between case volume and mortality after radical cystectomy for bladder cancer became evident only after adjustment for structural and process of care factors, including staffing levels of nurses and junior doctors, in addition to case mix. At least for this relatively uncommon procedure, adjusting for these confounders when examining the volume-outcome relation is critical before considering centralisation of care to a few specialist institutions. Outcomes other than mortality, such as functional morbidity and disease recurrence may ultimately influence towards centralising care. PMID:20305302

Chemistry of surface water at a volcanic summit area, Norikura, central Japan: multivariate statistical approach.

PubMed

Anazaw, K; Ohmori, L H

2001-11-01

Many hydrochemical studies on chemical formation of shallow ground water have been reported as results of water-rock interaction, and contamination of paleo-brine or human activities, whereas the preliminary formation of precipitation source in the recharged region has not been established yet. The purpose of this research work is to clarify the geochemical process of water formation from a water source unpolluted by seawater or human activity. Norikura volcano, located in western part of central Japan provided a suitable source for this research purpose, and hence chemical compositions of water samples from the summit and the mountainside area of Norikura volcano were determined. Most samples in the summit area showed very low electrical conductivity, and lower than 12 microS/cm. On the basis of the chemical compositions, principal component analysis (PCA) and factor analysis (FA), such as kinds of multivariate statistical techniques were used to extract geochemical factors affecting hydrochemical process. As a result, three factors were extracted. The first factor showed high loading on K+, Ca2+, SO2 and SiO2, and this factor was interpreted due to influence of the chemical interaction between acidic precipitated water and rocks. The second factor showed high loading on Na+ and Cl-, and it was assumed to be an influence of seawater salt. The third factor showed loading on NO3-, and it was interpreted to be caused by biochemical effect of vegetation. The proportionate contributions of these factors to the evolution of water chemical composition were found to be 45%, 20%, and 10% for factors 1, 2 and 3, respectively. The same exploration at the mountainside of Norikura volcano revealed that the chemical variances of the non-geothermal water samples were highly influenced by water-rock interactions. The silicate dissolution showed 45% contribution for all chemical variances, while the adsorption of Ca2+ and Mg2+ by precipitation or ion exchange showed 20% contribution. The seawater salt influence or biochemical effect was statistically negligible in this area. The clear differentiation of geochemical process on water formation was found between the summit area and the mountainside area.

Factor Xa inhibitors versus vitamin K antagonists for preventing cerebral or systemic embolism in patients with atrial fibrillation.

PubMed

Bruins Slot, Karsten Mh; Berge, Eivind

2018-03-06

Factor Xa inhibitors and vitamin K antagonists (VKAs) are now recommended in treatment guidelines for preventing stroke and systemic embolic events in people with atrial fibrillation (AF). This is an update of a Cochrane review previously published in 2013. To assess the effectiveness and safety of treatment with factor Xa inhibitors versus VKAs for preventing cerebral or systemic embolic events in people with AF. We searched the trials registers of the Cochrane Stroke Group and the Cochrane Heart Group (September 2016), the Cochrane Central Register of Controlled Trials (CENTRAL) (August 2017), MEDLINE (1950 to April 2017), and Embase (1980 to April 2017). We also contacted pharmaceutical companies, authors and sponsors of relevant published trials. We used outcome data from marketing authorisation applications of apixaban, edoxaban and rivaroxaban that were submitted to regulatory authorities in Europe and the USA. We included randomised controlled trials (RCTs) that directly compared the effects of long-term treatment (lasting more than four weeks) with factor Xa inhibitors versus VKAs for preventing cerebral and systemic embolism in people with AF. The primary efficacy outcome was the composite endpoint of all strokes and systemic embolic events. Two review authors independently extracted data, and assessed the quality of the trials and the risk of bias. We calculated a weighted estimate of the typical treatment effect across trials using the odds ratio (OR) with 95% confidence interval (CI) by means of a fixed-effect model. In case of moderate or high heterogeneity of treatment effects, we used a random-effects model to compare the overall treatment effects. We also performed a pre-specified sensitivity analysis excluding any open-label studies. We included data from 67,688 participants randomised into 13 RCTs. The included trials directly compared dose-adjusted warfarin with either apixaban, betrixaban, darexaban, edoxaban, idraparinux, idrabiotaparinux, or rivaroxaban. The majority of the included data (approximately 90%) was from apixaban, edoxaban, and rivaroxaban.The composite primary efficacy endpoint of all strokes (both ischaemic and haemorrhagic) and non-central nervous systemic embolic events was reported in all of the included studies. Treatment with a factor Xa inhibitor significantly decreased the number of strokes and systemic embolic events compared with dose-adjusted warfarin in participants with AF (OR 0.89, 95% CI 0.82 to 0.97; 13 studies; 67,477 participants; high-quality evidence).Treatment with a factor Xa inhibitor significantly reduced the number of major bleedings compared with warfarin (OR 0.78, 95% CI 0.73 to 0.84; 13 studies; 67,396 participants; moderate-quality evidence). There was, however, statistically significant and high heterogeneity (I 2 = 83%). When we repeated this analysis using a random-effects model, it did not show a statistically significant decrease in the number of major bleedings (OR 0.88, 95% CI 0.66 to 1.17). A pre-specified sensitivity analysis excluding all open-label studies showed that treatment with a factor Xa inhibitor significantly reduced the number of major bleedings compared with warfarin (OR 0.75, 95% CI 0.69 to 0.81), but high heterogeneity was also observed in this analysis (I 2 = 72%). The same sensitivity analysis using a random-effects model also showed a statistically significant decrease in the number of major bleedings in participants treated with factor Xa inhibitors (OR 0.76, 95% CI 0.60 to 0.96).Treatment with a factor Xa inhibitor significantly reduced the risk of intracranial haemorrhages (ICHs) compared with warfarin (OR 0.50, 95% CI 0.42 to 0.59; 12 studies; 66,259 participants; high-quality evidence). We observed moderate, but statistically significant heterogeneity (I 2 = 55%). The pre-specified sensitivity analysis excluding open-label studies showed that treatment with a factor Xa inhibitor significantly reduced the number of ICHs compared with warfarin (OR 0.47, 95% CI 0.40 to 0.56), with low, non-statistically significant heterogeneity (I 2 = 27%).Treatment with a factor Xa inhibitor also significantly reduced the number of all-cause deaths compared with warfarin (OR 0.89, 95% 0.83 to 0.95; 10 studies; 65,624 participants; moderate-quality evidence). Treatment with factor Xa inhibitors significantly reduced the number of strokes and systemic embolic events compared with warfarin in people with AF. The absolute effect of factor Xa inhibitors compared with warfarin treatment was, however, rather small. Factor Xa inhibitors also reduced the number of ICHs, all-cause deaths and major bleedings compared with warfarin, although the evidence for a reduction in the latter is less robust.

Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization.

PubMed

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.

Directional Variance Adjustment: Bias Reduction in Covariance Matrices Based on Factor Analysis with an Application to Portfolio Optimization

PubMed Central

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W.; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation. PMID:23844016

Factors Influencing Cecal Intubation Time during Retrograde Approach Single-Balloon Enteroscopy

PubMed Central

Chen, Peng-Jen; Shih, Yu-Lueng; Huang, Hsin-Hung; Hsieh, Tsai-Yuan

2014-01-01

Background and Aim. The predisposing factors for prolonged cecal intubation time (CIT) during colonoscopy have been well identified. However, the factors influencing CIT during retrograde SBE have not been addressed. The aim of this study was to determine the factors influencing CIT during retrograde SBE. Methods. We investigated patients who underwent retrograde SBE at a medical center from January 2011 to March 2014. The medical charts and SBE reports were reviewed. The patients' characteristics and procedure-associated data were recorded. These data were analyzed with univariate analysis as well as multivariate logistic regression analysis to identify the possible predisposing factors. Results. We enrolled 66 patients into this study. The median CIT was 17.4 minutes. With univariate analysis, there was no statistical difference in age, sex, BMI, or history of abdominal surgery, except for bowel preparation (P = 0.021). Multivariate logistic regression analysis showed that inadequate bowel preparation (odds ratio 30.2, 95% confidence interval 4.63–196.54; P < 0.001) was the independent predisposing factors for prolonged CIT during retrograde SBE. Conclusions. For experienced endoscopist, inadequate bowel preparation was the independent predisposing factor for prolonged CIT during retrograde SBE. PMID:25505904

EVALUATION OF A NEW MEAN SCALED AND MOMENT ADJUSTED TEST STATISTIC FOR SEM.

PubMed

Tong, Xiaoxiao; Bentler, Peter M

2013-01-01

Recently a new mean scaled and skewness adjusted test statistic was developed for evaluating structural equation models in small samples and with potentially nonnormal data, but this statistic has received only limited evaluation. The performance of this statistic is compared to normal theory maximum likelihood and two well-known robust test statistics. A modification to the Satorra-Bentler scaled statistic is developed for the condition that sample size is smaller than degrees of freedom. The behavior of the four test statistics is evaluated with a Monte Carlo confirmatory factor analysis study that varies seven sample sizes and three distributional conditions obtained using Headrick's fifth-order transformation to nonnormality. The new statistic performs badly in most conditions except under the normal distribution. The goodness-of-fit χ(2) test based on maximum-likelihood estimation performed well under normal distributions as well as under a condition of asymptotic robustness. The Satorra-Bentler scaled test statistic performed best overall, while the mean scaled and variance adjusted test statistic outperformed the others at small and moderate sample sizes under certain distributional conditions.

STATISTICAL METHOD FOR DETECTION OF A TREND IN ATMOSPHERIC SULFATE

EPA Science Inventory

Daily atmospheric concentrations of sulfate collected in northeastern Pennsylvania are regressed against meteorological factors, ozone, and time in order to determine if a significant trend in sulfate can be detected. he data used in this analysis were collected during the Sulfat...

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

PubMed Central

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

2015-01-01

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

Do Program Implementation Factors or Fidelity Affect Chronic Disease Self-Management Education Programs' Outcomes?

PubMed

Brady, Teresa J; Murphy, Louise B; O'Colmain, Benita J; Hobson, Reeti Desai

2017-09-01

To evaluate whether implementation factors or fidelity moderate chronic disease self-management education program outcomes. Meta-analysis of 34 Arthritis Self-Management Program and Chronic Disease Self-Management Program studies. Community. N = 10 792. Twelve implementation factors: program delivery fidelity and setting and leader and participant characteristics. Eighteen program outcomes: self-reported health behaviors, physical health status, psychological health status, and health-care utilization. Meta-analysis using pooled effect sizes. Modest to moderate statistically significant differences for 4 of 6 implementation factors; these findings were counterintuitive with better outcomes when leaders and participants were unpaid, leaders had less than minimum training, and implementation did not meet fidelity requirements. Exploratory study findings suggest that these interventions tolerate some variability in implementation factors. Further work is needed to identify key elements where fidelity is essential for intervention effectiveness.

Routes to failure: analysis of 41 civil aviation accidents from the Republic of China using the human factors analysis and classification system.

PubMed

Li, Wen-Chin; Harris, Don; Yu, Chung-San

2008-03-01

The human factors analysis and classification system (HFACS) is based upon Reason's organizational model of human error. HFACS was developed as an analytical framework for the investigation of the role of human error in aviation accidents, however, there is little empirical work formally describing the relationship between the components in the model. This research analyses 41 civil aviation accidents occurring to aircraft registered in the Republic of China (ROC) between 1999 and 2006 using the HFACS framework. The results show statistically significant relationships between errors at the operational level and organizational inadequacies at both the immediately adjacent level (preconditions for unsafe acts) and higher levels in the organization (unsafe supervision and organizational influences). The pattern of the 'routes to failure' observed in the data from this analysis of civil aircraft accidents show great similarities to that observed in the analysis of military accidents. This research lends further support to Reason's model that suggests that active failures are promoted by latent conditions in the organization. Statistical relationships linking fallible decisions in upper management levels were found to directly affect supervisory practices, thereby creating the psychological preconditions for unsafe acts and hence indirectly impairing the performance of pilots, ultimately leading to accidents.

[Behavioral phenotypes of autism spectrum disorder patients and their parents].

PubMed

Situ, Mingjing; Hu, Xiao; Cai, Jia; Guo, Kuifang; Huang, Yi

2015-12-01

To explore the relationship between the behavior phenotypes of patients with autism spectrum disorder (ASD) and their parents through family study. Forty-five core families with ASD and 30 control families from Chengdu area were examined using Autism Spectrum Quotient (AQ). Descriptive statistical analysis, correlation analysis, and Logistic regression analysis were used to investigate the effect of various factors, especially genetic factors that may affect the pathogenesis of ASD. The social skills factor and communication factor of the father's AQ scale, as well as the mother's age of childbearing and AQ social skills factor are related to whether children with ASD (R were 0.46, 0.39, 0.39 and 0.36, P<0.05). The communication factor of the parents' AQ and mother's attention to detail factor are related to whether children will show developmental anomaly before the age of 36 months (R were 0.55, 0.51 and 0.54, P<0.05). The social skill problems of parents and father's communication problems are risk factors for children with autism. ASD may be influenced by both genetic and environmental factors. The autistic behavior phenotype of parents is a risk factor for ASD and is associated with developmental anomalies of early childhood.

Perception on obesity among university students: A case study using factor analysis

NASA Astrophysics Data System (ADS)

Hassan, Suriani; Rahman, Nur Amira Abdol; Ghazali, Khadizah; Ismail, Norlita; Budin, Kamsia

2014-07-01

The purpose of this study was to examine the university students' perceptions on obesity and to compare the difference in mean scores factor based on demographic factors. Data was collected randomly using questionnaires. There were 321 university students participated in this study. Descriptive statistics, factor analysis, normality test, independent t test, one-way ANOVA and non-parametric tests were used in this study. Factor analysis results managed to retrieve three new factors namely impact of the health, impact of the physical appearance and personal factors. The study found that Science students have higher awareness and perceptions than Art students on Factor 1, impact of the health towards overweight problems and obesity. The findings of the study showed students, whose family background has obesity problem have higher awareness and perceptions than students' whose family background has no obesity problem on Factor 1, impact of the health towards overweight problems and obesity. The study also found that students' whose father with primary school level had the lowest awareness and perceptions on Factor 2, impact of the physical appearance towards overweight problems and obesity than other students whose father with higher academic level.

Analysis of a Single Hemodialysis on Phosphate Removal of the Internal Fistula Patients by Mathematical and Statistical Methods

PubMed Central

Yu, Qiyao; Bai, Yaling; Zhang, Junxia; Cui, Liwen; Zhang, Huiran; Xu, Jinsheng; Gao, Chao

2013-01-01

Chronic kidney disease related mineral and bone disease (CKD-MBD) is a worldwide challenge in hemodialysis patients. In china, the number of dialysis patients is growing but few data are available about their bone disorders. In the current study, we aimed to evaluate the effect of clinical factors on the serum phosphorus clearance in the 80 maintenance hemodialysis (MHD) patients. Six clinical factors were identified for their association with the serum phosphorus clearance using the analysis of Spearman's single linear correlation, including predialysis serum phosphate level, CRR, membrane surface area of the dialyzer, effective blood flow rate, the blood chamber volume, and hematocrit. In an overall multivariate analysis, pre-P, CRR, membrane SA, and Qb were identified as independent risk factors associated with the serum phosphorus clearance. In conclusion, HD could effectively clear serum phosphorus. The analysis of CRR might help to estimate serum phosphorus reduction ratio. PMID:24454542

Factor structure and dimensionality of the two depression scales in STAR*D using level 1 datasets.

PubMed

Bech, P; Fava, M; Trivedi, M H; Wisniewski, S R; Rush, A J

2011-08-01

The factor structure and dimensionality of the HAM-D(17) and the IDS-C(30) are as yet uncertain, because psychometric analyses of these scales have been performed without a clear separation between factor structure profile and dimensionality (total scores being a sufficient statistic). The first treatment step (Level 1) in the STAR*D study provided a dataset of 4041 outpatients with DSM-IV nonpsychotic major depression. The HAM-D(17) and IDS-C(30) were evaluated by principal component analysis (PCA) without rotation. Mokken analysis tested the unidimensionality of the IDS-C(6), which corresponds to the unidimensional HAM-D(6.) For both the HAM-D(17) and IDS-C(30), PCA identified a bi-directional factor contrasting the depressive symptoms versus the neurovegetative symptoms. The HAM-D(6) and the corresponding IDS-C(6) symptoms all emerged in the depression factor. Both the HAM-D(6) and IDS-C(6) were found to be unidimensional scales, i.e., their total scores are each a sufficient statistic for the measurement of depressive states. STAR*D used only one medication in Level 1. The unidimensional HAM-D(6) and IDS-C(6) should be used when evaluating the pure clinical effect of antidepressive treatment, whereas the multidimensional HAM-D(17) and IDS-C(30) should be considered when selecting antidepressant treatment. Copyright © 2011 Elsevier B.V. All rights reserved.

ABO blood grouping: A potential risk factor for early childhood caries - A cross-sectional study.

PubMed

Govindaraju, Lavanya; Jeevanandan, Ganesh; Subramanian, E M G

2018-01-01

The paradigm of etiology of early childhood caries (ECC) is shifting toward genetics. Of various inherited factors, blood group of an individual is genetically determined. The aim of the study is to determine if blood group of an individual will serve as a potential risk factor in the development of ECC. A cross-sectional study was conducted in Chennai. Blood samples were collected from a total of 500 children <71 months of age for determination of the blood group. Of which 96 children (24 per blood group) were randomly selected and were included in the study. Oral screening of the selected children was done by a pediatric dentist who was blinded to the blood group of the children. Decayed, extracted, and filling index was noted. Details on other associated factors for the development of ECC such as the socioeconomic status, oral hygiene measures, diet, and feeding practices were collected by directly interviewing the parents through a questionnaire. Statistical analysis was done using Chi-square and Kruskal-Wallis test and post hoc Tukey test with significance level set at 0.05. Intergroup analysis of the associated factors showed no significant differences between the children of different blood groups. A statistically significant relation was noted between the blood groups and development of ECC (P = 0.025). Blood group is a potential risk indicator for the development of ECC.

Spatial patterns of heavy metals in soil under different geological structures and land uses for assessing metal enrichments.

PubMed

Krami, Loghman Khoda; Amiri, Fazel; Sefiyanian, Alireza; Shariff, Abdul Rashid B Mohamed; Tabatabaie, Tayebeh; Pradhan, Biswajeet

2013-12-01

One hundred and thirty composite soil samples were collected from Hamedan county, Iran to characterize the spatial distribution and trace the sources of heavy metals including As, Cd, Co, Cr, Cu, Ni, Pb, V, Zn, and Fe. The multivariate gap statistical analysis was used; for interrelation of spatial patterns of pollution, the disjunctive kriging and geoenrichment factor (EF(G)) techniques were applied. Heavy metals and soil properties were grouped using agglomerative hierarchical clustering and gap statistic. Principal component analysis was used for identification of the source of metals in a set of data. Geostatistics was used for the geospatial data processing. Based on the comparison between the original data and background values of the ten metals, the disjunctive kriging and EF(G) techniques were used to quantify their geospatial patterns and assess the contamination levels of the heavy metals. The spatial distribution map combined with the statistical analysis showed that the main source of Cr, Co, Ni, Zn, Pb, and V in group A land use (agriculture, rocky, and urban) was geogenic; the origin of As, Cd, and Cu was industrial and agricultural activities (anthropogenic sources). In group B land use (rangeland and orchards), the origin of metals (Cr, Co, Ni, Zn, and V) was mainly controlled by natural factors and As, Cd, Cu, and Pb had been added by organic factors. In group C land use (water), the origin of most heavy metals is natural without anthropogenic sources. The Cd and As pollution was relatively more serious in different land use. The EF(G) technique used confirmed the anthropogenic influence of heavy metal pollution. All metals showed concentrations substantially higher than their background values, suggesting anthropogenic pollution.

Assessing risk factors for dental caries: a statistical modeling approach.

PubMed

Trottini, Mario; Bossù, Maurizio; Corridore, Denise; Ierardo, Gaetano; Luzzi, Valeria; Saccucci, Matteo; Polimeni, Antonella

2015-01-01

The problem of identifying potential determinants and predictors of dental caries is of key importance in caries research and it has received considerable attention in the scientific literature. From the methodological side, a broad range of statistical models is currently available to analyze dental caries indices (DMFT, dmfs, etc.). These models have been applied in several studies to investigate the impact of different risk factors on the cumulative severity of dental caries experience. However, in most of the cases (i) these studies focus on a very specific subset of risk factors; and (ii) in the statistical modeling only few candidate models are considered and model selection is at best only marginally addressed. As a result, our understanding of the robustness of the statistical inferences with respect to the choice of the model is very limited; the richness of the set of statistical models available for analysis in only marginally exploited; and inferences could be biased due the omission of potentially important confounding variables in the model's specification. In this paper we argue that these limitations can be overcome considering a general class of candidate models and carefully exploring the model space using standard model selection criteria and measures of global fit and predictive performance of the candidate models. Strengths and limitations of the proposed approach are illustrated with a real data set. In our illustration the model space contains more than 2.6 million models, which require inferences to be adjusted for 'optimism'.

The Mindful Attention Awareness Scale: Further Examination of Dimensionality, Reliability, and Concurrent Validity Estimates.

PubMed

Osman, Augustine; Lamis, Dorian A; Bagge, Courtney L; Freedenthal, Stacey; Barnes, Sean M

2016-01-01

We examined the factor structure and psychometric properties of the Mindful Attention Awareness Scale (MAAS) in a sample of 810 undergraduate students. Using common exploratory factor analysis (EFA), we obtained evidence for a 1-factor solution (41.84% common variance). To confirm unidimensionality of the 15-item MAAS, we conducted a 1-factor confirmatory factor analysis (CFA). Results of the EFA and CFA, respectively, provided support for a unidimensional model. Using differential item functioning analysis methods within item response theory modeling (IRT-based DIF), we found that individuals with high and low levels of nonattachment responded similarly to the MAAS items. Following a detailed item analysis, we proposed a 5-item short version of the instrument and present descriptive statistics and composite score reliability for the short and full versions of the MAAS. Finally, correlation analyses showed that scores on the full and short versions of the MAAS were associated with measures assessing related constructs. The 5-item MAAS is as useful as the original MAAS in enhancing our understanding of the mindfulness construct.

Data exploration, quality control and statistical analysis of ChIP-exo/nexus experiments

PubMed Central

Welch, Rene; Chung, Dongjun; Grass, Jeffrey; Landick, Robert

2017-01-01

Abstract ChIP-exo/nexus experiments rely on innovative modifications of the commonly used ChIP-seq protocol for high resolution mapping of transcription factor binding sites. Although many aspects of the ChIP-exo data analysis are similar to those of ChIP-seq, these high throughput experiments pose a number of unique quality control and analysis challenges. We develop a novel statistical quality control pipeline and accompanying R/Bioconductor package, ChIPexoQual, to enable exploration and analysis of ChIP-exo and related experiments. ChIPexoQual evaluates a number of key issues including strand imbalance, library complexity, and signal enrichment of data. Assessment of these features are facilitated through diagnostic plots and summary statistics computed over regions of the genome with varying levels of coverage. We evaluated our QC pipeline with both large collections of public ChIP-exo/nexus data and multiple, new ChIP-exo datasets from Escherichia coli. ChIPexoQual analysis of these datasets resulted in guidelines for using these QC metrics across a wide range of sequencing depths and provided further insights for modelling ChIP-exo data. PMID:28911122

Data exploration, quality control and statistical analysis of ChIP-exo/nexus experiments.

PubMed

Welch, Rene; Chung, Dongjun; Grass, Jeffrey; Landick, Robert; Keles, Sündüz

2017-09-06

ChIP-exo/nexus experiments rely on innovative modifications of the commonly used ChIP-seq protocol for high resolution mapping of transcription factor binding sites. Although many aspects of the ChIP-exo data analysis are similar to those of ChIP-seq, these high throughput experiments pose a number of unique quality control and analysis challenges. We develop a novel statistical quality control pipeline and accompanying R/Bioconductor package, ChIPexoQual, to enable exploration and analysis of ChIP-exo and related experiments. ChIPexoQual evaluates a number of key issues including strand imbalance, library complexity, and signal enrichment of data. Assessment of these features are facilitated through diagnostic plots and summary statistics computed over regions of the genome with varying levels of coverage. We evaluated our QC pipeline with both large collections of public ChIP-exo/nexus data and multiple, new ChIP-exo datasets from Escherichia coli. ChIPexoQual analysis of these datasets resulted in guidelines for using these QC metrics across a wide range of sequencing depths and provided further insights for modelling ChIP-exo data. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Recent advances in statistical energy analysis

NASA Technical Reports Server (NTRS)

Heron, K. H.

1992-01-01

Statistical Energy Analysis (SEA) has traditionally been developed using modal summation and averaging approach, and has led to the need for many restrictive SEA assumptions. The assumption of 'weak coupling' is particularly unacceptable when attempts are made to apply SEA to structural coupling. It is now believed that this assumption is more a function of the modal formulation rather than a necessary formulation of SEA. The present analysis ignores this restriction and describes a wave approach to the calculation of plate-plate coupling loss factors. Predictions based on this method are compared with results obtained from experiments using point excitation on one side of an irregular six-sided box structure. Conclusions show that the use and calculation of infinite transmission coefficients is the way forward for the development of a purely predictive SEA code.

Processes and subdivisions in diogenites, a multivariate statistical analysis

NASA Technical Reports Server (NTRS)

Harriott, T. A.; Hewins, R. H.

1984-01-01

Multivariate statistical techniques used on diogenite orthopyroxene analyses show the relationships that occur within diogenites and the two orthopyroxenite components (class I and II) in the polymict diogenite Garland. Cluster analysis shows that only Peckelsheim is similar to Garland class I (Fe-rich) and the other diogenites resemble Garland class II. The unique diogenite Y 75032 may be related to type I by fractionation. Factor analysis confirms the subdivision and shows that Fe does not correlate with the weakly incompatible elements across the entire pyroxene composition range, indicating that igneous fractionation is not the process controlling total diogenite composition variation. The occurrence of two groups of diogenites is interpreted as the result of sampling or mixing of two main sequences of orthopyroxene cumulates with slightly different compositions.

Do climate extreme events foster violent civil conflicts? A coincidence analysis

NASA Astrophysics Data System (ADS)

Schleussner, Carl-Friedrich; Donges, Jonathan F.; Donner, Reik V.

2014-05-01

Civil conflicts promoted by adverse environmental conditions represent one of the most important potential feedbacks in the global socio-environmental nexus. While the role of climate extremes as a triggering factor is often discussed, no consensus is yet reached about the cause-and-effect relation in the observed data record. Here we present results of a rigorous statistical coincidence analysis based on the Munich Re Inc. extreme events database and the Uppsala conflict data program. We report evidence for statistically significant synchronicity between climate extremes with high economic impact and violent conflicts for various regions, although no coherent global signal emerges from our analysis. Our results indicate the importance of regional vulnerability and might aid to identify hot-spot regions for potential climate-triggered violent social conflicts.

Factors influencing health information system adoption in American hospitals.

PubMed

Wang, Bill B; Wan, Thomas T H; Burke, Darrell E; Bazzoli, Gloria J; Lin, Blossom Y J

2005-01-01

To study the number of health information systems (HISs), applicable to administrative, clinical, and executive decision support functionalities, adopted by acute care hospitals and to examine how hospital market, organizational, and financial factors influence HIS adoption. A cross-sectional analysis was performed with 1441 hospitals selected from metropolitan statistical areas in the United States. Multiple data sources were merged. Six hypotheses were empirically tested by multiple regression analysis. HIS adoption was influenced by the hospital market, organizational, and financial factors. Larger, system-affiliated, and for-profit hospitals with more preferred provider organization contracts are more likely to adopt managerial information systems than their counterparts. Operating revenue is positively associated with HIS adoption. The study concludes that hospital organizational and financial factors influence on hospitals' strategic adoption of clinical, administrative, and managerial information systems.

Principal component analysis of normalized full spectrum mass spectrometry data in multiMS-toolbox: An effective tool to identify important factors for classification of different metabolic patterns and bacterial strains.

PubMed

Cejnar, Pavel; Kuckova, Stepanka; Prochazka, Ales; Karamonova, Ludmila; Svobodova, Barbora

2018-06-15

Explorative statistical analysis of mass spectrometry data is still a time-consuming step. We analyzed critical factors for application of principal component analysis (PCA) in mass spectrometry and focused on two whole spectrum based normalization techniques and their application in the analysis of registered peak data and, in comparison, in full spectrum data analysis. We used this technique to identify different metabolic patterns in the bacterial culture of Cronobacter sakazakii, an important foodborne pathogen. Two software utilities, the ms-alone, a python-based utility for mass spectrometry data preprocessing and peak extraction, and the multiMS-toolbox, an R software tool for advanced peak registration and detailed explorative statistical analysis, were implemented. The bacterial culture of Cronobacter sakazakii was cultivated on Enterobacter sakazakii Isolation Agar, Blood Agar Base and Tryptone Soya Agar for 24 h and 48 h and applied by the smear method on an Autoflex speed MALDI-TOF mass spectrometer. For three tested cultivation media only two different metabolic patterns of Cronobacter sakazakii were identified using PCA applied on data normalized by two different normalization techniques. Results from matched peak data and subsequent detailed full spectrum analysis identified only two different metabolic patterns - a cultivation on Enterobacter sakazakii Isolation Agar showed significant differences to the cultivation on the other two tested media. The metabolic patterns for all tested cultivation media also proved the dependence on cultivation time. Both whole spectrum based normalization techniques together with the full spectrum PCA allow identification of important discriminative factors in experiments with several variable condition factors avoiding any problems with improper identification of peaks or emphasis on bellow threshold peak data. The amounts of processed data remain still manageable. Both implemented software utilities are available free of charge from http://uprt.vscht.cz/ms. Copyright © 2018 John Wiley & Sons, Ltd.

Exploratory factor analysis of borderline personality disorder criteria in hospitalized adolescents.

PubMed

Becker, Daniel F; McGlashan, Thomas H; Grilo, Carlos M

2006-01-01

The authors examined the factor structure of borderline personality disorder (BPD) in hospitalized adolescents and also sought to add to the theoretical and clinical understanding of any homogeneous components by determining whether they may be related to specific forms of Axis I pathology. Subjects were 123 adolescent inpatients, who were reliably assessed with structured diagnostic interviews for Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition Axes I and II disorders. Exploratory factor analysis identified BPD components, and logistic regression analyses tested whether these components were predictive of specific Axis I disorders. Factor analysis revealed a 4-factor solution that accounted for 67.0% of the variance. Factor 1 ("suicidal threats or gestures" and "emptiness or boredom") predicted depressive disorders and alcohol use disorders. Factor 2 ("affective instability," "uncontrolled anger," and "identity disturbance") predicted anxiety disorders and oppositional defiant disorder. Factor 3 ("unstable relationships" and "abandonment fears") predicted only anxiety disorders. Factor 4 ("impulsiveness" and "identity disturbance") predicted conduct disorder and substance use disorders. Exploratory factor analysis of BPD criteria in adolescent inpatients revealed 4 BPD factors that appear to differ from those reported for similar studies of adults. The factors represent components of self-negation, irritability, poorly modulated relationships, and impulsivity--each of which is associated with characteristic Axis I pathology. These findings shed light on the nature of BPD in adolescents and may also have implications for treatment.

Functional genomics annotation of a statistical epistasis network associated with bladder cancer susceptibility.

PubMed

Hu, Ting; Pan, Qinxin; Andrew, Angeline S; Langer, Jillian M; Cole, Michael D; Tomlinson, Craig R; Karagas, Margaret R; Moore, Jason H

2014-04-11

Several different genetic and environmental factors have been identified as independent risk factors for bladder cancer in population-based studies. Recent studies have turned to understanding the role of gene-gene and gene-environment interactions in determining risk. We previously developed the bioinformatics framework of statistical epistasis networks (SEN) to characterize the global structure of interacting genetic factors associated with a particular disease or clinical outcome. By applying SEN to a population-based study of bladder cancer among Caucasians in New Hampshire, we were able to identify a set of connected genetic factors with strong and significant interaction effects on bladder cancer susceptibility. To support our statistical findings using networks, in the present study, we performed pathway enrichment analyses on the set of genes identified using SEN, and found that they are associated with the carcinogen benzo[a]pyrene, a component of tobacco smoke. We further carried out an mRNA expression microarray experiment to validate statistical genetic interactions, and to determine if the set of genes identified in the SEN were differentially expressed in a normal bladder cell line and a bladder cancer cell line in the presence or absence of benzo[a]pyrene. Significant nonrandom sets of genes from the SEN were found to be differentially expressed in response to benzo[a]pyrene in both the normal bladder cells and the bladder cancer cells. In addition, the patterns of gene expression were significantly different between these two cell types. The enrichment analyses and the gene expression microarray results support the idea that SEN analysis of bladder in population-based studies is able to identify biologically meaningful statistical patterns. These results bring us a step closer to a systems genetic approach to understanding cancer susceptibility that integrates population and laboratory-based studies.

Evaluation of damping loss factor of flat laminates by sound transmission

NASA Astrophysics Data System (ADS)

Parrinello, A.; Ghiringhelli, G. L.

2018-06-01

A novel approach to investigate and evaluate the damping loss factor of a planar multilayered structure is presented. A statistical analysis reveals the connection between the damping properties of the structure and the transmission of sound through the thickness of its laterally infinite counterpart. The obtained expression for the panel loss factor involves all the derivatives of the transmission and reflection coefficients of the layered structure with respect each layer damping. The properties of the fluid for which the sound transmission is evaluated are chosen to fulfil the hypotheses on the basis of the statistical formulation. A transfer matrix approach is used to compute the required transmission and reflection coefficients, making it possible to deal with structures having arbitrary stratifications of different layers and also granting high efficiency in a wide frequency range. Comparison with alternative formulations and measurements demonstrates the effectiveness of the proposed methodology.

A pedagogical approach to the Boltzmann factor through experiments and simulations

NASA Astrophysics Data System (ADS)

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

2009-09-01

The Boltzmann factor is the basis of a huge amount of thermodynamic and statistical physics, both classical and quantum. It governs the behaviour of all systems in nature that are exchanging energy with their environment. To understand why the expression has this specific form involves a deep mathematical analysis, whose flow of logic is hard to see and is not at the level of high school or college students' preparation. We here present some experiments and simulations aimed at directly deriving its mathematical expression and illustrating the fundamental concepts on which it is grounded. Experiments use easily available apparatuses, and simulations are developed in the Net-Logo environment that, besides having a user-friendly interface, allows an easy interaction with the algorithm. The approach supplies pedagogical support for the introduction of the Boltzmann factor at the undergraduate level to students without a background in statistical mechanics.

A statistical approach to the interpretation of aliphatic hydrocarbon distributions in marine sediments

USGS Publications Warehouse

Rapp, J.B.

1991-01-01

Q-mode factor analysis was used to quantitate the distribution of the major aliphatic hydrocarbon (n-alkanes, pristane, phytane) systems in sediments from a variety of marine environments. The compositions of the pure end members of the systems were obtained from factor scores and the distribution of the systems within each sample was obtained from factor loadings. All the data, from the diverse environments sampled (estuarine (San Francisco Bay), fresh-water (San Francisco Peninsula), polar-marine (Antarctica) and geothermal-marine (Gorda Ridge) sediments), were reduced to three major systems: a terrestrial system (mostly high molecular weight aliphatics with odd-numbered-carbon predominance), a mature system (mostly low molecular weight aliphatics without predominance) and a system containing mostly high molecular weight aliphatics with even-numbered-carbon predominance. With this statistical approach, it is possible to assign the percentage contribution from various sources to the observed distribution of aliphatic hydrocarbons in each sediment sample. ?? 1991.

Clinical Validation of the "Sedentary Lifestyle" Nursing Diagnosis in Secondary School Students.

PubMed

de Oliveira, Marcos Renato; da Silva, Viviane Martins; Guedes, Nirla Gomes; de Oliveira Lopes, Marcos Venícios

2016-06-01

This study clinically validated the nursing diagnosis of "sedentary lifestyle" (SL) among 564 Brazilian adolescents. Measures of diagnostic accuracy were calculated for defining characteristics, and Mantel-Haenszel analysis was used to identify related factors. The measures of diagnostic accuracy showed that the following defining characteristics were statistically significant: "average daily physical activity less than recommended for gender and age," "preference for activity low in physical activity," "nonengagement in leisure time physical activities," and "diminished respiratory capacity." An SL showed statistically significant associations with the following related factors: insufficient motivation for physical activity; insufficient interest in physical activity; insufficient resources for physical activity; insufficient social support for physical activity; attitudes, beliefs, and health habits that hinder physical activity; and insufficient confidence for practicing physical exercises. The study highlighted the four defining characteristics and six related factors for making decisions related to SL among adolescents. © The Author(s) 2015.

Increasing Army Supply Chain Performance: Using an Integrated End to End Metrics System

DTIC Science & Technology

2017-01-01

Sched Deliver Sched Delinquent Contracts Current Metrics PQDR/SDRs Forecasting Accuracy Reliability Demand Management Asset Mgmt Strategies Pipeline...are identified and characterized by statistical analysis. The study proposed a framework and tool for inventory management based on factors such as

Statistical Analysis to Assess Effectiveness of Rumble Stripes on Highway Safety

DOT National Transportation Integrated Search

2011-01-01

Although traffic deaths are caused by an array of factors, in the United States more than half of all roadway fatalities are caused by roadway departures [FHWA 2006]. In 2003, there were 25,562 roadway departure fatalities, accounting for 55 percent ...

Evaluation of psychiatric and genetic risk factors among primary relatives of suicide completers in Delhi NCR region, India.

PubMed

Pasi, Shivani; Singh, Piyoosh Kumar; Pandey, Rajeev Kumar; Dikshit, P C; Jiloha, R C; Rao, V R

2015-10-30

Suicide as a public health problem is studied worldwide and association of psychiatric and genetic risk factors for suicidal behavior are the point of discussion in studies across different ethnic groups. The present study is aimed at evaluating psychiatric and genetic traits among primary relatives of suicide completer families in an urban Indian population. Bi-variate analysis shows significant increase in major depression (PHQ and Hamilton), stress, panic disorder, somatoform disorder and suicide attemptamong primary compared to other relatives. Sib pair correlations also reveal significant results for major depression (Hamilton), stress, suicide attempt, intensity of suicide ideation and other anxiety syndrome. 5-HTTLPR, 5-HTT (Stin2) and COMT risk alleles are higher among primary relatives, though statistically insignificant. Backward conditional logistic regression analysis show only independent variable, Depression (Hamilton) made a unique statistically significant contribution to the model in primary relatives. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Nurses' autonomy level in teaching hospitals and its relationship with the underlying factors.

PubMed

Amini, Kourosh; Negarandeh, Reza; Ramezani-Badr, Farhad; Moosaeifard, Mahdi; Fallah, Ramezan

2015-02-01

This study aimed to determine the autonomy level of nurses in hospitals affiliated to Zanjan University of Medical Sciences, Iran. In this descriptive cross-sectional study, 252 subjects were recruited using systematic random sampling method. The data were collected using questionnaire including Dempster Practice Behavior Scale. For data analysis, descriptive statistics and to compare the overall score and its subscales according to the demographic variables, t-test and analysis of variance test were used. The nurses in this study had medium professional autonomy. Statistical tests showed significant differences in the research sample according to age, gender, work experience, working position and place of work. The results of this study revealed that most of the nurses who participated in the study compared with western societies have lower professional autonomy. More studies are needed to determine the factors related to this difference and how we can promote Iranian nurses' autonomy. © 2013 Wiley Publishing Asia Pty Ltd.

Confirmatory Factor Analysis of the Malay Version of the Confusion, Hubbub and Order Scale (CHAOS-6) among Myocardial Infarction Survivors in a Malaysian Cardiac Healthcare Facility.

PubMed

Ganasegeran, Kurubaran; Selvaraj, Kamaraj; Rashid, Abdul

2017-08-01

The six item Confusion, Hubbub and Order Scale (CHAOS-6) has been validated as a reliable tool to measure levels of household disorder. We aimed to investigate the goodness of fit and reliability of a new Malay version of the CHAOS-6. The original English version of the CHAOS-6 underwent forward-backward translation into the Malay language. The finalised Malay version was administered to 105 myocardial infarction survivors in a Malaysian cardiac health facility. We performed confirmatory factor analyses (CFAs) using structural equation modelling. A path diagram and fit statistics were yielded to determine the Malay version's validity. Composite reliability was tested to determine the scale's reliability. All 105 myocardial infarction survivors participated in the study. The CFA yielded a six-item, one-factor model with excellent fit statistics. Composite reliability for the single factor CHAOS-6 was 0.65, confirming that the scale is reliable for Malay speakers. The Malay version of the CHAOS-6 was reliable and showed the best fit statistics for our study sample. We thus offer a simple, brief, validated, reliable and novel instrument to measure chaos, the Skala Kecelaruan, Keriuhan & Tertib Terubahsuai (CHAOS-6) , for the Malaysian population.

Confirmatory Factor Analysis of the Malay Version of the Confusion, Hubbub and Order Scale (CHAOS-6) among Myocardial Infarction Survivors in a Malaysian Cardiac Healthcare Facility

PubMed Central

Ganasegeran, Kurubaran; Selvaraj, Kamaraj; Rashid, Abdul

2017-01-01

Background The six item Confusion, Hubbub and Order Scale (CHAOS-6) has been validated as a reliable tool to measure levels of household disorder. We aimed to investigate the goodness of fit and reliability of a new Malay version of the CHAOS-6. Methods The original English version of the CHAOS-6 underwent forward-backward translation into the Malay language. The finalised Malay version was administered to 105 myocardial infarction survivors in a Malaysian cardiac health facility. We performed confirmatory factor analyses (CFAs) using structural equation modelling. A path diagram and fit statistics were yielded to determine the Malay version’s validity. Composite reliability was tested to determine the scale’s reliability. Results All 105 myocardial infarction survivors participated in the study. The CFA yielded a six-item, one-factor model with excellent fit statistics. Composite reliability for the single factor CHAOS-6 was 0.65, confirming that the scale is reliable for Malay speakers. Conclusion The Malay version of the CHAOS-6 was reliable and showed the best fit statistics for our study sample. We thus offer a simple, brief, validated, reliable and novel instrument to measure chaos, the Skala Kecelaruan, Keriuhan & Tertib Terubahsuai (CHAOS-6), for the Malaysian population. PMID:28951688

Time from Prior Chemotherapy Enhances Prognostic Risk Grouping in the Second-line Setting of Advanced Urothelial Carcinoma: A Retrospective Analysis of Pooled, Prospective Phase 2 Trials

PubMed Central

Sonpavde, Guru; Pond, Gregory R.; Fougeray, Ronan; Choueiri, Toni K.; Qu, Angela Q.; Vaughn, David J.; Niegisch, Guenter; Albers, Peter; James, Nicholas D.; Wong, Yu-Ning; Ko, Yoo-Joung; Sridhar, Srikala S.; Galsky, Matthew D.; Petrylak, Daniel P.; Vaishampayan, Ulka N.; Khan, Awais; Vogelzang, Nicholas J.; Beer, Tomasz M.; Stadler, Walter M.; O’Donnell, Peter H.; Sternberg, Cora N.; Rosenberg, Jonathan E.; Bellmunt, Joaquim

2014-01-01

Background Outcomes for patients in the second-line setting of advanced urothelial carcinoma (UC) are dismal. The recognized prognostic factors in this context are Eastern Cooperative Oncology Group (ECOG) performance status (PS) >0, hemoglobin level (Hb) <10 g/dl, and liver metastasis (LM). Objectives The purpose of this retrospective study of prospective trials was to investigate the prognostic value of time from prior chemotherapy (TFPC) independent of known prognostic factors. Design, setting, and participants: Data from patients from seven prospective trials with available baseline TFPC, Hb, PS, and LM values were used for retrospective analysis (n = 570). External validation was conducted in a second-line phase 3 trial comparing best supportive care (BSC) versus vinflunine plus BSC (n = 352). Outcome measurements and statistical analysis Cox proportional hazards regression was used to evaluate the association of factors, with overall survival (OS) and progression-free survival (PFS) being the respective primary and secondary outcome measures. Results and limitations ECOG-PS >0, LM, Hb <10 g/dl, and shorter TFPC were significant prognostic factors for OS and PFS on multivariable analysis. Patients with zero, one, two, and three to four factors demonstrated median OS of 12.2, 6.7, 5.1, and 3.0 mo, respectively (concordance statistic = 0.638). Setting of prior chemotherapy (metastatic disease vs perioperative) and prior platinum agent (cisplatin or carboplatin) were not prognostic factors. External validation demonstrated a significant association of TFPC with PFS on univariable and most multivariable analyses, and with OS on univariable analyses. Limitations of retrospective analyses are applicable. Conclusions Shorter TFPC enhances prognostic classification independent of ECOG-PS>0, Hb<10 g/ dl, and LM in the setting of second-line therapy for advanced UC. These data may facilitate drug development and interpretation of trials. PMID:23206856

Standardization of the NEO-PI-3 in the Greek general population.

PubMed

Fountoulakis, Konstantinos N; Siamouli, Melina; Moysidou, Stefania; Pantoula, Eleonora; Moutou, Katerina; Panagiotidis, Panagiotis; Kemeridou, Marina; Mavridou, Eirini; Loli, Efimia; Batsiari, Elena; Preti, Antonio; Tondo, Leonardo; Gonda, Xenia; Mobayed, Nisreen; Akiskal, Kareen; Akiskal, Hagop; Costa, Paul; McCrae, Robert

2014-01-01

The revised NEO Personality Inventory (NEO-PI-3) includes 240 items corresponding to the Big Five personality traits (Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness to Experience) and subordinate dimensions (facets). It is suitable for use with adolescents and adults (12 years or older). The aim of the current study was to validate the Greek translation of the NEO-PI-3 in the general Greek population. The study sample included 734 subjects from the general Greek population of whom 59.4% were females and 40.6% males aged 40.80 ± 11.48. The NEO-PI-3 was translated into Greek and back-translated into English, and the accuracy of the translation was confirmed and established. The statistical analysis included descriptive statistics, confirmatory factorial analysis (CFA), the calculation of Cronbach's alpha, and the calculation of Pearson product-moment correlations. Sociodemographics groups were compared by ANOVA. Most facets had Cronbach's alpha above 0.60. Confirmatory factor analysis showed acceptable loading of the facets on their own hypothesized factors and very good estimations of Cronbach's alphas for the hypothesized factors, so it was partially supportive of the five-factor structure of the NEO-PI-3.The factors extracted with Procrustes rotation analysis can be considered reasonably homologous to the factors of the American normative sample. Correlations between dimensions were as expected and similar to those reported in the literature. The literature suggests that overall, the psychometric properties of NEO-PI-3 scales have been found to generalize across ages, cultures, and methods of measurement. In accord with this, the results of the current study confirm the reliability of the Greek translation and adaptation of the NEO-PI-3. The inventory has comparable psychometric properties in its Greek version in comparison to the original and other national translations, and it is suitable for clinical as well as research use.

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

DTIC Science & Technology

1974-12-01

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

The microcomputer scientific software series 3: general linear model--analysis of variance.

Treesearch

Harold M. Rauscher

1985-01-01

A BASIC language set of programs, designed for use on microcomputers, is presented. This set of programs will perform the analysis of variance for any statistical model describing either balanced or unbalanced designs. The program computes and displays the degrees of freedom, Type I sum of squares, and the mean square for the overall model, the error, and each factor...

Indicators of economic security of the region: a risk-based approach to assessing and rating

NASA Astrophysics Data System (ADS)

Karanina, Elena; Loginov, Dmitri

2017-10-01

The article presents the results of research of theoretical and methodical problems of strategy development for economic security of a particular region, justified by the composition of risk factors. The analysis of those risk factors is performed. The threshold values of indicators of economic security of regions were determined using the methods of socioeconomic statistics. The authors concluded that in modern Russian conditions it is necessary to pay great attention to the analysis of the composition and level of indicators of economic security of the region and, based on the materials of this analysis, to formulate more accurate decisions concerning the strategy of socio-economic development.

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

PubMed

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

2016-01-01

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

Study design and statistical analysis of data in human population studies with the micronucleus assay.

PubMed

Ceppi, Marcello; Gallo, Fabio; Bonassi, Stefano

2011-01-01

The most common study design performed in population studies based on the micronucleus (MN) assay, is the cross-sectional study, which is largely performed to evaluate the DNA damaging effects of exposure to genotoxic agents in the workplace, in the environment, as well as from diet or lifestyle factors. Sample size is still a critical issue in the design of MN studies since most recent studies considering gene-environment interaction, often require a sample size of several hundred subjects, which is in many cases difficult to achieve. The control of confounding is another major threat to the validity of causal inference. The most popular confounders considered in population studies using MN are age, gender and smoking habit. Extensive attention is given to the assessment of effect modification, given the increasing inclusion of biomarkers of genetic susceptibility in the study design. Selected issues concerning the statistical treatment of data have been addressed in this mini-review, starting from data description, which is a critical step of statistical analysis, since it allows to detect possible errors in the dataset to be analysed and to check the validity of assumptions required for more complex analyses. Basic issues dealing with statistical analysis of biomarkers are extensively evaluated, including methods to explore the dose-response relationship among two continuous variables and inferential analysis. A critical approach to the use of parametric and non-parametric methods is presented, before addressing the issue of most suitable multivariate models to fit MN data. In the last decade, the quality of statistical analysis of MN data has certainly evolved, although even nowadays only a small number of studies apply the Poisson model, which is the most suitable method for the analysis of MN data.

Using Statistics and Data Mining Approaches to Analyze Male Sexual Behaviors and Use of Erectile Dysfunction Drugs Based on Large Questionnaire Data.

PubMed

Qiao, Zhi; Li, Xiang; Liu, Haifeng; Zhang, Lei; Cao, Junyang; Xie, Guotong; Qin, Nan; Jiang, Hui; Lin, Haocheng

2017-01-01

The prevalence of erectile dysfunction (ED) has been extensively studied worldwide. Erectile dysfunction drugs has shown great efficacy in preventing male erectile dysfunction. In order to help doctors know drug taken preference of patients and better prescribe, it is crucial to analyze who actually take erectile dysfunction drugs and the relation between sexual behaviors and drug use. Existing clinical studies usually used descriptive statistics and regression analysis based on small volume of data. In this paper, based on big volume of data (48,630 questionnaires), we use data mining approaches besides statistics and regression analysis to comprehensively analyze the relation between male sexual behaviors and use of erectile dysfunction drugs for unravelling the characteristic of patients who take erectile dysfunction drugs. We firstly analyze the impact of multiple sexual behavior factors on whether to use the erectile dysfunction drugs. Then, we explore to mine the Decision Rules for Stratification to discover patients who are more likely to take drugs. Based on the decision rules, the patients can be partitioned into four potential groups for use of erectile dysfunction: high potential group, intermediate potential-1 group, intermediate potential-2 group and low potential group. Experimental results show 1) the sexual behavior factors, erectile hardness and time length to prepare (how long to prepares for sexual behaviors ahead of time), have bigger impacts both in correlation analysis and potential drug taking patients discovering; 2) odds ratio between patients identified as low potential and high potential was 6.098 (95% confidence interval, 5.159-7.209) with statistically significant differences in taking drug potential detected between all potential groups.

Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia

PubMed Central

Naish, Suchithra; Hu, Wenbiao; Mengersen, Kerrie; Tong, Shilu

2011-01-01

Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland. PMID:22022430

Symptom Clusters in Advanced Cancer Patients: An Empirical Comparison of Statistical Methods and the Impact on Quality of Life.

PubMed

Dong, Skye T; Costa, Daniel S J; Butow, Phyllis N; Lovell, Melanie R; Agar, Meera; Velikova, Galina; Teckle, Paulos; Tong, Allison; Tebbutt, Niall C; Clarke, Stephen J; van der Hoek, Kim; King, Madeleine T; Fayers, Peter M

2016-01-01

Symptom clusters in advanced cancer can influence patient outcomes. There is large heterogeneity in the methods used to identify symptom clusters. To investigate the consistency of symptom cluster composition in advanced cancer patients using different statistical methodologies for all patients across five primary cancer sites, and to examine which clusters predict functional status, a global assessment of health and global quality of life. Principal component analysis and exploratory factor analysis (with different rotation and factor selection methods) and hierarchical cluster analysis (with different linkage and similarity measures) were used on a data set of 1562 advanced cancer patients who completed the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire-Core 30. Four clusters consistently formed for many of the methods and cancer sites: tense-worry-irritable-depressed (emotional cluster), fatigue-pain, nausea-vomiting, and concentration-memory (cognitive cluster). The emotional cluster was a stronger predictor of overall quality of life than the other clusters. Fatigue-pain was a stronger predictor of overall health than the other clusters. The cognitive cluster and fatigue-pain predicted physical functioning, role functioning, and social functioning. The four identified symptom clusters were consistent across statistical methods and cancer types, although there were some noteworthy differences. Statistical derivation of symptom clusters is in need of greater methodological guidance. A psychosocial pathway in the management of symptom clusters may improve quality of life. Biological mechanisms underpinning symptom clusters need to be delineated by future research. A framework for evidence-based screening, assessment, treatment, and follow-up of symptom clusters in advanced cancer is essential. Copyright © 2016 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Clinical and histopathologic independent prognostic factors in oral squamous cell carcinoma: a retrospective study of 334 cases.

PubMed

Arduino, Paolo G; Carrozzo, Marco; Chiecchio, Andrea; Broccoletti, Roberto; Tirone, Federico; Borra, Eleonora; Bertolusso, Giorgio; Gandolfo, Sergio

2008-08-01

This retrospective hospital-based study reviewed and evaluated the outcome of patients with oral squamous cell carcinoma (OSCC) with the aim of identifying factors affecting the clinical course and survival rate. Patients with a follow-up of at least 12 months were included. The data collected were statistically analyzed for the presence of factors valuable for prognosis; survival curves were processed in accordance with the Kaplan-Meier method. Differences in the expression of variables in different grading levels were investigated. Cox's proportional hazard model for Z(i) covariates (grading, age, T, N) also was calculated. Mean patient age was 67.7 years in women (n = 152) and 62.4 years in men (n = 182). A total of 98 patients were identified with Broder's/World Health Organization grade 1 histology, 176 with grade 2, and 55 with grade 3; 5 patients were identified as grade 4 (carcinoma in situ). Gender and risk factors seemed to be unrelated to prognosis, whereas a significant increase in mortality was seen in patients over age 70. Histological grading, tumor size, and neck involvement were related, as independent factors, in predicting survival in patients with OSCC (QM-H > 3.9). Gender, age, and risk factors had no statistical relationship with cancer histological differentiation. Our analysis reveals a statistically significant relationship among histological Broder's grading of malignancy, tumor size, locoregional involvement, and survival rates, underscoring the utility of tumor differentiation in predicting the clinical course and outcome of OSCC.

Risk factors for granuloma formation in children induced by tracheobronchial foreign bodies.

PubMed

Huang, Zhenghua; Zhou, Ai; Zhang, Jianya; Xie, Lisheng; Li, Qi

2015-12-01

The aim of this study was to analyze the risk factors for granuloma formation caused by plant-based tracheobronchial foreign bodies in children, and investigate the underlying pathogenesis. In this retrospective analysis of 153 cases with tracheobronchial foreign bodies (peanuts and watermelon seeds), 35 cases of granuloma formation as granulation group (G), and 118 cases of no granuloma formation as non-granulation group (NG) were studied. Clinical data pertaining to sex (S), age (A), foreign body surface smoothness (SF), foreign body shape (SH), foreign body oil release state (O), the location of foreign bodies (L), and foreign body retention time (T) were collected for statistical analysis. Univariate analysis showed no significant difference between the two groups (G and NG) with respect to S, A, SH and L. Significant factors based on univariate analysis included SF, O and T. Multivariate logistic regression analysis revealed that SF and T were independent risk factors associated with development of granuloma. SF, O and T had relationship with the granuloma formation. Local trauma caused by an irregular and sharp foreign body, and extended period of time represent the main factors causing granuloma formation. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Assessment of water quality parameters using multivariate analysis for Klang River basin, Malaysia.

PubMed

Mohamed, Ibrahim; Othman, Faridah; Ibrahim, Adriana I N; Alaa-Eldin, M E; Yunus, Rossita M

2015-01-01

This case study uses several univariate and multivariate statistical techniques to evaluate and interpret a water quality data set obtained from the Klang River basin located within the state of Selangor and the Federal Territory of Kuala Lumpur, Malaysia. The river drains an area of 1,288 km(2), from the steep mountain rainforests of the main Central Range along Peninsular Malaysia to the river mouth in Port Klang, into the Straits of Malacca. Water quality was monitored at 20 stations, nine of which are situated along the main river and 11 along six tributaries. Data was collected from 1997 to 2007 for seven parameters used to evaluate the status of the water quality, namely dissolved oxygen, biochemical oxygen demand, chemical oxygen demand, suspended solids, ammoniacal nitrogen, pH, and temperature. The data were first investigated using descriptive statistical tools, followed by two practical multivariate analyses that reduced the data dimensions for better interpretation. The analyses employed were factor analysis and principal component analysis, which explain 60 and 81.6% of the total variation in the data, respectively. We found that the resulting latent variables from the factor analysis are interpretable and beneficial for describing the water quality in the Klang River. This study presents the usefulness of several statistical methods in evaluating and interpreting water quality data for the purpose of monitoring the effectiveness of water resource management. The results should provide more straightforward data interpretation as well as valuable insight for managers to conceive optimum action plans for controlling pollution in river water.

Morphometric assessment of the red stripe weevils, Rhynchophorus vulneratus (Coleoptera: Curculionidae) from several localities in Malaysia

NASA Astrophysics Data System (ADS)

Sazali, Siti Nurlydia; Hazmi, Izfa Riza; Rahim, Faszly; Abang, Fatimah; Jemain, Abdul Aziz

2018-04-01

The recognition of intraspecific variation could enhance knowledge and understanding on the population divergence that might be resulted from different geographical areas. To study the possible effect derived from different locations, a morphometric study of the red stripe weevils, Rhynchophorus vulneratus from different localities in Malaysia was conducted using field and voucher specimens. A total of twenty-three morphological characters were examined from 108 individuals of R. vulneratus representing population of Kota Samarahan, Mukah and central of Peninsular Malaysia. The data were subjected to univariate one-way single factor analysis of variance (ANOVA) and analysed in factor analysis using SPSS version 22.0 software. Univariate ANOVA showed that all tested variables were significantly different (p<0.05) except for mesocoxal distance (MSD), meanwhile from the factor analysis, the first three factors with eigenvalues greater than 1.0 were successfully extracted, resulting in a high variation of 82.687%. For factor 1, 39.213% of total variation was recorded, factor 2 accounted for 34.096% and factor 3 contributing to 9.377%, respectively. The mixed plotting among the twenty-three morphological characters suggests a strong correlation among the parameters examined and further statistical analysis should be conducted to include environmental factors such as habitat types, food availability and predation effect.

A Heat Vulnerability Index and Adaptation Solutions for Pittsburgh, Pennsylvania.

PubMed

Bradford, Kathryn; Abrahams, Leslie; Hegglin, Miriam; Klima, Kelly

2015-10-06

With increasing evidence of global warming, many cities have focused attention on response plans to address their populations' vulnerabilities. Despite expected increased frequency and intensity of heat waves, the health impacts of such events in urban areas can be minimized with careful policy and economic investments. We focus on Pittsburgh, Pennsylvania and ask two questions. First, what are the top factors contributing to heat vulnerability and how do these characteristics manifest geospatially throughout Pittsburgh? Second, assuming the City wishes to deploy additional cooling centers, what placement will optimally address the vulnerability of the at risk populations? We use national census data, ArcGIS geospatial modeling, and statistical analysis to determine a range of heat vulnerability indices and optimal cooling center placement. We find that while different studies use different data and statistical calculations, all methods tested locate additional cooling centers at the confluence of the three rivers (Downtown), the northeast side of Pittsburgh (Shadyside/Highland Park), and the southeast side of Pittsburgh (Squirrel Hill). This suggests that for Pittsburgh, a researcher could apply the same factor analysis procedure to compare data sets for different locations and times; factor analyses for heat vulnerability are more robust than previously thought.

Groundwater nitrate contamination: Factors and indicators

PubMed Central

Wick, Katharina; Heumesser, Christine; Schmid, Erwin

2012-01-01

Identifying significant determinants of groundwater nitrate contamination is critical in order to define sensible agri-environmental indicators that support the design, enforcement, and monitoring of regulatory policies. We use data from approximately 1200 Austrian municipalities to provide a detailed statistical analysis of (1) the factors influencing groundwater nitrate contamination and (2) the predictive capacity of the Gross Nitrogen Balance, one of the most commonly used agri-environmental indicators. We find that the percentage of cropland in a given region correlates positively with nitrate concentration in groundwater. Additionally, environmental characteristics such as temperature and precipitation are important co-factors. Higher average temperatures result in lower nitrate contamination of groundwater, possibly due to increased evapotranspiration. Higher average precipitation dilutes nitrates in the soil, further reducing groundwater nitrate concentration. Finally, we assess whether the Gross Nitrogen Balance is a valid predictor of groundwater nitrate contamination. Our regression analysis reveals that the Gross Nitrogen Balance is a statistically significant predictor for nitrate contamination. We also show that its predictive power can be improved if we account for average regional precipitation. The Gross Nitrogen Balance predicts nitrate contamination in groundwater more precisely in regions with higher average precipitation. PMID:22906701

Job satisfaction of nurses with master of nursing degrees in Poland: quantitative and qualitative analysis.

PubMed

Brayer, Aneta; Marcinowicz, Ludmila

2018-04-03

Understanding the issue of job satisfaction of nurses with master of nursing degrees may help develop organisational changes necessary for better functioning of health care institutions. This study aimed to evaluate the level of job satisfaction among holders of Masters of Nursing degrees employed at health care institutions and to ascertain its determinants. The cross-sectional study was carried out in randomly selected health care institutions in Poland using the Misener Nurse Practitioner Job Satisfaction Survey and an original survey questionnaire with two open-ended questions. Quantitative data were analysed using descriptive and summary statistics. The participants gave highest satisfaction ratings to their relationships with direct superiors and other nurses, as well as their social contacts at work. The lowest ratings were given to the pension scheme and factors connected with remuneration. A highly statistically significant relationship was found between the job classification and the level of professional satisfaction (p < 0.001). Qualitative analysis of responses to the two open-ended questions supported Herzberg's Two-Factor theory: internal factors promoted satisfaction, whilst external ones caused dissatisfaction. Managers of nurses should strengthen the areas that contribute to higher employee satisfaction, particularly interpersonal relationships, by commendation and recognition of work effects.

Investigation of machinability characteristics on EN47 steel for cutting force and tool wear using optimization technique

NASA Astrophysics Data System (ADS)

M, Vasu; Shivananda Nayaka, H.

2018-06-01

In this experimental work dry turning process carried out on EN47 spring steel with coated tungsten carbide tool insert with 0.8 mm nose radius are optimized by using statistical technique. Experiments were conducted at three different cutting speeds (625, 796 and 1250 rpm) with three different feed rates (0.046, 0.062 and 0.093 mm/rev) and depth of cuts (0.2, 0.3 and 0.4 mm). Experiments are conducted based on full factorial design (FFD) 33 three factors and three levels. Analysis of variance is used to identify significant factor for each output response. The result reveals that feed rate is the most significant factor influencing on cutting force followed by depth of cut and cutting speed having less significance. Optimum machining condition for cutting force obtained from the statistical technique. Tool wear measurements are performed with optimum condition of Vc = 796 rpm, ap = 0.2 mm, f = 0.046 mm/rev. The minimum tool wear observed as 0.086 mm with 5 min machining. Analysis of tool wear was done by confocal microscope it was observed that tool wear increases with increasing cutting time.

Social relationships and risk of dementia: A systematic review and meta-analysis of longitudinal cohort studies.

PubMed

Kuiper, Jisca S; Zuidersma, Marij; Oude Voshaar, Richard C; Zuidema, Sytse U; van den Heuvel, Edwin R; Stolk, Ronald P; Smidt, Nynke

2015-07-01

It is unclear to what extent poor social relationships are related to the development of dementia. A comprehensive systematic literature search identified 19 longitudinal cohort studies investigating the association between various social relationship factors and incident dementia in the general population. Relative risks (RRs) with 95% confidence intervals (CIs) were pooled using random-effects meta-analysis. Low social participation (RR: 1.41 (95% CI: 1.13-1.75)), less frequent social contact (RR: 1.57 (95% CI: 1.32-1.85)), and more loneliness (RR: 1.58 (95% CI: 1.19-2.09)) were statistically significant associated with incident dementia. The results of the association between social network size and dementia were inconsistent. No statistically significant association was found for low satisfaction with social network and the onset of dementia (RR: 1.25 (95% CI: 0.96-1.62). We conclude that social relationship factors that represent a lack of social interaction are associated with incident dementia. The strength of the associations between poor social interaction and incident dementia is comparable with other well-established risk factors for dementia, including low education attainment, physical inactivity, and late-life depression. Copyright © 2015 Elsevier B.V. All rights reserved.

Second primary malignancies after treatment for malignant lymphoma

PubMed Central

Okines, A; Thomson, C S; Radstone, C R; Horsman, J M; Hancock, B W

2005-01-01

To determine the incidence and possible causes of second primary malignancies after treatment for Hodgkin's and Non-Hodgkin's lymphoma (HL and NHL). A cohort of 3764 consecutive patients diagnosed with HL or NHL between January 1970 and July 2001 was identified using the Sheffield Lymphoma Group database. A search was undertaken for all patients diagnosed with a subsequent primary malignancy. Two matched controls were identified for each case. Odds ratios were calculated to detect and quantify any risk factors in the cases compared to their matched controls. Mean follow-up for the cohort was 5.2 years. A total of 68 patients who developed second cancers at least 6 months after their primary diagnosis were identified, giving a crude incidence of 1.89% overall: 3.21% among the patients treated for HL, 1.32% in those treated for NHL. Most common were bronchial, breast, colorectal and haematological malignancies. High stage at diagnosis almost reached statistical significance in the analysis of just the NHL patients (odds ratio=3.48; P=0.068) after adjustment for other factors. Treatment modality was not statistically significant in any analysis. High stage at diagnosis of NHL may be a risk factor for developing a second primary cancer. PMID:16106249

A Heat Vulnerability Index and Adaptation Solutions for Pittsburgh, Pennsylvania

NASA Astrophysics Data System (ADS)

Klima, K.; Abrahams, L.; Bradford, K.; Hegglin, M.

2015-12-01

With increasing evidence of global warming, many cities have focused attention on response plans to address their populations' vulnerabilities. Despite expected increased frequency and intensity of heat waves, the health impacts of such events in urban areas can be minimized with careful policy and economic investments. We focus on Pittsburgh, Pennsylvania and ask two questions. First, what are the top factors contributing to heat vulnerability and how do these characteristics manifest geospatially throughout Pittsburgh? Second, assuming the City wishes to deploy additional cooling centers, what placement will optimally address the vulnerability of the at risk populations? We use national census data, ArcGIS geospatial modeling, and statistical analysis to determine a range of heat vulnerability indices and optimal cooling center placement. We find that while different studies use different data and statistical calculations, all methods tested locate additional cooling centers at the confluence of the three rivers (Downtown), the northeast side of Pittsburgh (Shadyside/ Highland Park), and the southeast side of Pittsburgh (Squirrel Hill). This suggests that for Pittsburgh, a researcher could apply the same factor analysis procedure to compare datasets for different locations and times; factor analyses for heat vulnerability are more robust than previously thought.

Assessment of stigma associated with tuberculosis in Mexico.

PubMed

Moya, E M; Biswas, A; Chávez Baray, S M; Martínez, O; Lomeli, B

2014-12-21

Stigma is a major barrier to health care access and impacts the quality of life for individuals affected by tuberculosis (TB). Assessing TB stigma is essential to addressing health disparities. However, no such instrument was available in Mexico at the time of our study. This study examined the adaptability of the TB and human immunodeficiency virus (HIV) stigma scales previously used in Thailand. The original scale, developed in English, was linguistically adapted to Spanish and administered to 217 individuals affected by TB in five states in Mexico. The TB-HIV stigma subscales were designed to assess individual and community perspectives. Additional data collected included general information and socio-demographics. Assessment of psychometric properties included basic statistical tests, evaluation of Cronbach's alpha and factor analysis. We found no significant statistical differences associated with higher stigma scores by location, age, marital status, education and stigma scores. Factor analysis did not create any new factors. Internal consistency reliability coefficients were satisfactory (Cronbach α = 0.876-0.912). The use of the stigma scales has implications for 1) health improvements, 2) research on stigma and health disparities, and 3) TB and HIV stigma interventions. Further research is needed to examine transferability among larger and randomly selected Spanish-speaking populations.

Young Vs Old Colorectal Cancer in Indian Subcontinent: a Tertiary Care Center Experience.

PubMed

Pokharkar, Ashish B; Bhandare, Manish; Patil, Prachi; Mehta, Shaesta; Engineer, Reena; Saklani, Avanish P

2017-12-01

This study aims to compare patient, tumor, treatment-related factors and survival between young (<45 years) and old (>45 years) Indian colorectal cancer (CRC) patients. Total 778 patients of CRC were registered at tertiary cancer center in India between 1 August 2013 and 31 July 2014. Patients were followed up for median period of 27.73 months. Data regarding patient, tumor, treatment and survival-related factors were collected. Patients were divided in young (≤45 years) and old (>45 years) age groups. Statistical analysis was done with SPSS software version 23. Young age group patients presented more commonly with poor histology, node-positive disease, and rectal site. Younger age group patients received multiple lines of neoadjuvant treatment. There was no significant overall survival difference in both groups of patients. On stratified stage-wise analysis, no significant overall survival (OS) difference was found between two groups (young vs old-1- and 3-year OS: 85.2 and 61.5% vs 81.5 and 64.5%, respectively; P  = 0.881). On univariate analysis, gender, performance status, site, stage, differentiation, TRG, CRM status, signet ring type, and CEA level were significant prognostic factors. In disease-free survival (DFS) analysis, it is found that there is statistically significant difference in DFS (young vs old: 1 and 3 years; 77.6 and 62.8% vs 85.8 and 74.1%, respectively; P value, 0.02), but when OS was analyzed for same group of patient, there was no statistical difference ( P  = 0.302). This study confirms the high incidence rates of CRC in young Indian patients. There is no OS difference between two age groups. In operated group of patients, there is higher DFS in older patients but no OS advantage at 3 years follow-up. Further long-term follow-up is required to see any OS difference.

Vibration-based structural health monitoring using adaptive statistical method under varying environmental condition

NASA Astrophysics Data System (ADS)

Jin, Seung-Seop; Jung, Hyung-Jo

2014-03-01

It is well known that the dynamic properties of a structure such as natural frequencies depend not only on damage but also on environmental condition (e.g., temperature). The variation in dynamic characteristics of a structure due to environmental condition may mask damage of the structure. Without taking the change of environmental condition into account, false-positive or false-negative damage diagnosis may occur so that structural health monitoring becomes unreliable. In order to address this problem, an approach to construct a regression model based on structural responses considering environmental factors has been usually used by many researchers. The key to success of this approach is the formulation between the input and output variables of the regression model to take into account the environmental variations. However, it is quite challenging to determine proper environmental variables and measurement locations in advance for fully representing the relationship between the structural responses and the environmental variations. One alternative (i.e., novelty detection) is to remove the variations caused by environmental factors from the structural responses by using multivariate statistical analysis (e.g., principal component analysis (PCA), factor analysis, etc.). The success of this method is deeply depending on the accuracy of the description of normal condition. Generally, there is no prior information on normal condition during data acquisition, so that the normal condition is determined by subjective perspective with human-intervention. The proposed method is a novel adaptive multivariate statistical analysis for monitoring of structural damage detection under environmental change. One advantage of this method is the ability of a generative learning to capture the intrinsic characteristics of the normal condition. The proposed method is tested on numerically simulated data for a range of noise in measurement under environmental variation. A comparative study with conventional methods (i.e., fixed reference scheme) demonstrates the superior performance of the proposed method for structural damage detection.

Evaluation of a Partial Genome Screening of Two Asthma Susceptibility Regions Using Bayesian Network Based Bayesian Multilevel Analysis of Relevance

PubMed Central

Antal, Péter; Kiszel, Petra Sz.; Gézsi, András; Hadadi, Éva; Virág, Viktor; Hajós, Gergely; Millinghoffer, András; Nagy, Adrienne; Kiss, András; Semsei, Ágnes F.; Temesi, Gergely; Melegh, Béla; Kisfali, Péter; Széll, Márta; Bikov, András; Gálffy, Gabriella; Tamási, Lilla; Falus, András; Szalai, Csaba

2012-01-01

Genetic studies indicate high number of potential factors related to asthma. Based on earlier linkage analyses we selected the 11q13 and 14q22 asthma susceptibility regions, for which we designed a partial genome screening study using 145 SNPs in 1201 individuals (436 asthmatic children and 765 controls). The results were evaluated with traditional frequentist methods and we applied a new statistical method, called Bayesian network based Bayesian multilevel analysis of relevance (BN-BMLA). This method uses Bayesian network representation to provide detailed characterization of the relevance of factors, such as joint significance, the type of dependency, and multi-target aspects. We estimated posteriors for these relations within the Bayesian statistical framework, in order to estimate the posteriors whether a variable is directly relevant or its association is only mediated. With frequentist methods one SNP (rs3751464 in the FRMD6 gene) provided evidence for an association with asthma (OR = 1.43(1.2–1.8); p = 3×10−4). The possible role of the FRMD6 gene in asthma was also confirmed in an animal model and human asthmatics. In the BN-BMLA analysis altogether 5 SNPs in 4 genes were found relevant in connection with asthma phenotype: PRPF19 on chromosome 11, and FRMD6, PTGER2 and PTGDR on chromosome 14. In a subsequent step a partial dataset containing rhinitis and further clinical parameters was used, which allowed the analysis of relevance of SNPs for asthma and multiple targets. These analyses suggested that SNPs in the AHNAK and MS4A2 genes were indirectly associated with asthma. This paper indicates that BN-BMLA explores the relevant factors more comprehensively than traditional statistical methods and extends the scope of strong relevance based methods to include partial relevance, global characterization of relevance and multi-target relevance. PMID:22432035

Early rectal stenosis following stapled rectal mucosectomy for hemorrhoids

PubMed Central

Petersen, Sven; Hellmich, Gunter; Schumann, Dietrich; Schuster, Anja; Ludwig, Klaus

2004-01-01

Background Within the last years, stapled rectal mucosectomy (SRM) has become a widely accepted procedure for second and third degree hemorrhoids. One of the delayed complications is a stenosis of the lower rectum. In order to evaluate the specific problem of rectal stenosis following SRM we reviewed our data with special respect to potential predictive factors or stenotic events. Methods A retrospective analysis of 419 consecutive patients, which underwent SRM from December 1998 to August 2003 was performed. Only patients with at least one follow-up check were evaluated, thus the analysis includes 289 patients with a mean follow-up of 281 days (±18 days). For statistic analysis the groups with and without stenosis were evaluated using the Chi-Square Test, using the Kaplan-Meier statistic the actuarial incidence for rectal stenosis was plotted. Results Rectal stenosis was observed in 9 patients (3.1%), eight of these stenoses were detected within the first 100 days after surgery; the median time to stenosis was 95 days. Only one patient had a rectal stenosis after more than one year. 8 of the 9 patients had no obstructive symptoms, however the remaining patients complained of obstructive defecation and underwent surgery for transanal strictureplasty with electrocautery. A statistical analysis revealed that patients with stenosis had significantly more often prior treatment for hemorrhoids (p < 0.01). According to the SRM only severe postoperative pain was significantly associated with stenoses (p < 0.01). Other factors, such as gender (p = 0.11), surgical technique (p = 0.25), revision (p = 0.79) or histological evidence of squamous skin (p = 0.69) showed no significance. Conclusion Rectal stenosis is an uncommon event after SRM. Early stenosis will occur within the first three months after surgery. The majority of the stenoses are without clinical relevance. Only one of nine patients had to undergo surgery for a relevant stenosis. The predictive factor for stenosis in the patient-characteristics is previous interventions for hemorrhoids, severe postoperative pain might also predict rectal stenosis. PMID:15153248

Risk factors for hydrocephalus and neurological deficit in children born with an encephalocele.

PubMed

Da Silva, Stephanie L; Jeelani, Yasser; Dang, Ha; Krieger, Mark D; McComb, J Gordon

2015-04-01

There is a known association of hydrocephalus with encephaloceles. Risk factors for hydrocephalus and neurological deficit were ascertained in a series of patients born with an encephalocele. A retrospective analysis was undertaken of patients treated for encephaloceles at Children's Hospital Los Angeles between 1994 and 2012. The following factors were evaluated for their prognostic value: age at presentation, sex, location of encephalocele, size, contents, microcephaly, presence of hydrocephalus, CSF leak, associated cranial anomalies, and neurological outcome. Seventy children were identified, including 38 girls and 32 boys. The median age at presentation was 2 months. The mean follow-up duration was 3.7 years. Encephalocele location was classified as anterior (n = 14) or posterior (n = 56) to the coronal suture. The average maximum encephalocele diameter was 4 cm (range 0.5-23 cm). Forty-seven encephaloceles contained neural tissue. Eight infants presented at birth with CSF leaking from the encephalocele, with 1 being infected. Six patients presented with hydrocephalus, while 11 developed progressive hydrocephalus postoperatively. On univariate analysis, the presence of neural tissue, cranial anomalies, encephalocele size of at least 2 cm, seizure disorder, and microcephaly were each positively associated with hydrocephalus. On multivariate logistic regression modeling, the single prognostic factor for hydrocephalus of borderline statistical significance was the presence of neural tissue (odds ratio [OR] = 5.8, 95% confidence interval [CI] = 0.8-74.0). Fourteen patients had severe developmental delay, 28 had mild/moderate delay, and 28 were neurologically normal. On univariate analysis, the presence of cranial anomalies, larger size of encephalocele, hydrocephalus, and microcephaly were positively associated with neurological deficit. In the multivariable model, the only statistically significant prognostic factor for neurological deficit was presence of hydrocephalus (OR 17.2, 95% CI 1.7-infinity). In multivariate models, the presence of neural tissue was borderline significantly associated with hydrocephalus and the presence of hydrocephalus was significantly associated with neurological deficit. The location of the encephalocele did not have a statistically significant association with incidence of hydrocephalus or neurological deficit. In contrast to modestly good/fair neurological outcome in children with an encephalocele without hydrocephalus, the presence of hydrocephalus resulted in a far worse neurological outcome.

Incorporating covariates into fisheries stock assessment models with application to Pacific herring.

PubMed

Deriso, Richard B; Maunder, Mark N; Pearson, Walter H

2008-07-01

We present a framework for evaluating the cause of fishery declines by integrating covariates into a fisheries stock assessment model. This allows the evaluation of fisheries' effects vs. natural and other human impacts. The analyses presented are based on integrating ecological science and statistics and form the basis for environmental decision-making advice. Hypothesis tests are described to rank hypotheses and determine the size of a multiple covariate model. We extend recent developments in integrated analysis and use novel methods to produce effect size estimates that are relevant to policy makers and include estimates of uncertainty. Results can be directly applied to evaluate trade-offs among alternative management decisions. The methods and results are also broadly applicable outside fisheries stock assessment. We show that multiple factors influence populations and that analysis of factors in isolation can be misleading. We illustrate the framework by applying it to Pacific herring of Prince William Sound, Alaska (USA). The Pacific herring stock that spawns in Prince William Sound is a stock that has collapsed, but there are several competing or alternative hypotheses to account for the initial collapse and subsequent lack of recovery. Factors failing the initial screening tests for statistical significance included indicators of the 1989 Exxon Valdez oil spill, coho salmon predation, sea lion predation, Pacific Decadal Oscillation, Northern Oscillation Index, and effects of containment in the herring egg-on-kelp pound fishery. The overall results indicate that the most statistically significant factors related to the lack of recovery of the herring stock involve competition or predation by juvenile hatchery pink salmon on herring juveniles. Secondary factors identified in the analysis were poor nutrition in the winter, ocean (Gulf of Alaska) temperature in the winter, the viral hemorrhagic septicemia virus, and the pathogen Ichthyophonus hoferi. The implication of this result to fisheries management in Prince William Sound is that it may well be difficult to simultaneously increase the production of pink salmon and maintain a viable Pacific herring fishery. The impact can be extended to other commercially important fisheries, and a whole ecosystem approach may be needed to evaluate the costs and benefits of salmon hatcheries.

Development of a Self-Report Physical Function Instrument for Disability Assessment: Item Pool Construction and Factor Analysis

PubMed Central

McDonough, Christine M.; Jette, Alan M.; Ni, Pengsheng; Bogusz, Kara; Marfeo, Elizabeth E; Brandt, Diane E; Chan, Leighton; Meterko, Mark; Haley, Stephen M.; Rasch, Elizabeth K.

2014-01-01

Objectives To build a comprehensive item pool representing work-relevant physical functioning and to test the factor structure of the item pool. These developmental steps represent initial outcomes of a broader project to develop instruments for the assessment of function within the context of Social Security Administration (SSA) disability programs. Design Comprehensive literature review; gap analysis; item generation with expert panel input; stakeholder interviews; cognitive interviews; cross-sectional survey administration; and exploratory and confirmatory factor analyses to assess item pool structure. Setting In-person and semi-structured interviews; internet and telephone surveys. Participants A sample of 1,017 SSA claimants, and a normative sample of 999 adults from the US general population. Interventions Not Applicable. Main Outcome Measure Model fit statistics Results The final item pool consisted of 139 items. Within the claimant sample 58.7% were white; 31.8% were black; 46.6% were female; and the mean age was 49.7 years. Initial factor analyses revealed a 4-factor solution which included more items and allowed separate characterization of: 1) Changing and Maintaining Body Position, 2) Whole Body Mobility, 3) Upper Body Function and 4) Upper Extremity Fine Motor. The final 4-factor model included 91 items. Confirmatory factor analyses for the 4-factor models for the claimant and the normative samples demonstrated very good fit. Fit statistics for claimant and normative samples respectively were: Comparative Fit Index = 0.93 and 0.98; Tucker-Lewis Index = 0.92 and 0.98; Root Mean Square Error Approximation = 0.05 and 0.04. Conclusions The factor structure of the Physical Function item pool closely resembled the hypothesized content model. The four scales relevant to work activities offer promise for providing reliable information about claimant physical functioning relevant to work disability. PMID:23542402

Development of a self-report physical function instrument for disability assessment: item pool construction and factor analysis.

PubMed

McDonough, Christine M; Jette, Alan M; Ni, Pengsheng; Bogusz, Kara; Marfeo, Elizabeth E; Brandt, Diane E; Chan, Leighton; Meterko, Mark; Haley, Stephen M; Rasch, Elizabeth K

2013-09-01

To build a comprehensive item pool representing work-relevant physical functioning and to test the factor structure of the item pool. These developmental steps represent initial outcomes of a broader project to develop instruments for the assessment of function within the context of Social Security Administration (SSA) disability programs. Comprehensive literature review; gap analysis; item generation with expert panel input; stakeholder interviews; cognitive interviews; cross-sectional survey administration; and exploratory and confirmatory factor analyses to assess item pool structure. In-person and semistructured interviews and Internet and telephone surveys. Sample of SSA claimants (n=1017) and a normative sample of adults from the U.S. general population (n=999). Not applicable. Model fit statistics. The final item pool consisted of 139 items. Within the claimant sample, 58.7% were white; 31.8% were black; 46.6% were women; and the mean age was 49.7 years. Initial factor analyses revealed a 4-factor solution, which included more items and allowed separate characterization of: (1) changing and maintaining body position, (2) whole body mobility, (3) upper body function, and (4) upper extremity fine motor. The final 4-factor model included 91 items. Confirmatory factor analyses for the 4-factor models for the claimant and the normative samples demonstrated very good fit. Fit statistics for claimant and normative samples, respectively, were: Comparative Fit Index=.93 and .98; Tucker-Lewis Index=.92 and .98; and root mean square error approximation=.05 and .04. The factor structure of the physical function item pool closely resembled the hypothesized content model. The 4 scales relevant to work activities offer promise for providing reliable information about claimant physical functioning relevant to work disability. Copyright © 2013 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Factors associated with student learning processes in primary health care units: a questionnaire study.

PubMed

Bos, Elisabeth; Alinaghizadeh, Hassan; Saarikoski, Mikko; Kaila, Päivi

2015-01-01

Clinical placement plays a key role in education intended to develop nursing and caregiving skills. Studies of nursing students' clinical learning experiences show that these dimensions affect learning processes: (i) supervisory relationship, (ii) pedagogical atmosphere, (iii) management leadership style, (iv) premises of nursing care on the ward, and (v) nursing teachers' roles. Few empirical studies address the probability of an association between these dimensions and factors such as student (a) motivation, (b) satisfaction with clinical placement, and (c) experiences with professional role models. The study aimed to investigate factors associated with the five dimensions in clinical learning environments within primary health care units. The Swedish version of Clinical Learning Environment, Supervision and Teacher, a validated evaluation scale, was administered to 356 graduating nursing students after four or five weeks clinical placement in primary health care units. Response rate was 84%. Multivariate analysis of variance is determined if the five dimensions are associated with factors a, b, and c above. The analysis revealed a statistically significant association with the five dimensions and two factors: students' motivation and experiences with professional role models. The satisfaction factor had a statistically significant association (effect size was high) with all dimensions; this clearly indicates that students experienced satisfaction. These questionnaire results show that a good clinical learning experience constitutes a complex whole (totality) that involves several interacting factors. Supervisory relationship and pedagogical atmosphere particularly influenced students' satisfaction and motivation. These results provide valuable decision-support material for clinical education planning, implementation, and management. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysis of a Rocket Based Combined Cycle Engine during Rocket Only Operation

NASA Technical Reports Server (NTRS)

Smith, T. D.; Steffen, C. J., Jr.; Yungster, S.; Keller, D. J.

1998-01-01

The all rocket mode of operation is a critical factor in the overall performance of a rocket based combined cycle (RBCC) vehicle. However, outside of performing experiments or a full three dimensional analysis, there are no first order parametric models to estimate performance. As a result, an axisymmetric RBCC engine was used to analytically determine specific impulse efficiency values based upon both full flow and gas generator configurations. Design of experiments methodology was used to construct a test matrix and statistical regression analysis was used to build parametric models. The main parameters investigated in this study were: rocket chamber pressure, rocket exit area ratio, percent of injected secondary flow, mixer-ejector inlet area, mixer-ejector area ratio, and mixer-ejector length-to-inject diameter ratio. A perfect gas computational fluid dynamics analysis was performed to obtain values of vacuum specific impulse. Statistical regression analysis was performed based on both full flow and gas generator engine cycles. Results were also found to be dependent upon the entire cycle assumptions. The statistical regression analysis determined that there were five significant linear effects, six interactions, and one second-order effect. Two parametric models were created to provide performance assessments of an RBCC engine in the all rocket mode of operation.

[Insect cholinesterases and irreversible inhibitors. Statistical treatment of the data].

PubMed

Moralev, S N

2010-01-01

The data on sensitivity of cholinesterases (ChE) of different insects to reversible inhibitors, as well as the data on physico-chemical parameters of amino acids constituting their active centers, were treated by factor analysis and juxtaposed. It is shown that both these characteristics are related to taxonomical belonging of insects. It is revealed the "material substrate" of the factors determining inhibitor action specificity, which are specific sites in ChE active center.

Sunnier European countries have lower melanoma mortality.

PubMed

Shipman, A R; Clark, A B; Levell, N J

2011-07-01

Doubt has been cast on sunlight as the major causative factor for malignant melanoma. We performed statistical analysis of the average annual sunlight hours in 36 European capital cities compared with the country's melanoma mortality rate. A significant inverse proportionality was identified in both men and women, indicating that sun exposure is unlikely to be the strongest factor affecting mortality from malignant melanoma. © The Author(s). CED © 2011 British Association of Dermatologists.

Which sociodemographic factors are important on smoking behaviour of high school students? The contribution of classification and regression tree methodology in a broad epidemiological survey.

PubMed

Ozge, C; Toros, F; Bayramkaya, E; Camdeviren, H; Sasmaz, T

2006-08-01

The purpose of this study is to evaluate the most important sociodemographic factors on smoking status of high school students using a broad randomised epidemiological survey. Using in-class, self administered questionnaire about their sociodemographic variables and smoking behaviour, a representative sample of total 3304 students of preparatory, 9th, 10th, and 11th grades, from 22 randomly selected schools of Mersin, were evaluated and discriminative factors have been determined using appropriate statistics. In addition to binary logistic regression analysis, the study evaluated combined effects of these factors using classification and regression tree methodology, as a new statistical method. The data showed that 38% of the students reported lifetime smoking and 16.9% of them reported current smoking with a male predominancy and increasing prevalence by age. Second hand smoking was reported at a 74.3% frequency with father predominance (56.6%). The significantly important factors that affect current smoking in these age groups were increased by household size, late birth rank, certain school types, low academic performance, increased second hand smoking, and stress (especially reported as separation from a close friend or because of violence at home). Classification and regression tree methodology showed the importance of some neglected sociodemographic factors with a good classification capacity. It was concluded that, as closely related with sociocultural factors, smoking was a common problem in this young population, generating important academic and social burden in youth life and with increasing data about this behaviour and using new statistical methods, effective coping strategies could be composed.

Title VII and the Male/Female Earnings Gap: An Economic Analysis.

ERIC Educational Resources Information Center

Beller, Andrea

1978-01-01

After controlling statistically for the effects of other factors that affect earnings, it was found that enforcement of sex discrimination charges under Title VII increased the relative demand for women and thus decreased the male/female earnings differential between 1967 and 1974. (Author)

School Readiness Factor Analyzed.

ERIC Educational Resources Information Center

Brenner, Anton; Scott, Leland H.

This paper is an empirical statistical analysis and interpretation of data relating to school readiness previously examined and reported on a theoretical basis. A total of 118 white, middle class children from six consecutive kindergarten groups in Dearborn, Michigan were tested with seven instruments, evaluated in terms of achievement, ability,…

Optimization of fermentation medium for the production of atrazine degrading strain Acinetobacter sp. DNS(32) by statistical analysis system.

PubMed

Zhang, Ying; Wang, Yang; Wang, Zhi-Gang; Wang, Xi; Guo, Huo-Sheng; Meng, Dong-Fang; Wong, Po-Keung

2012-01-01

Statistical experimental designs provided by statistical analysis system (SAS) software were applied to optimize the fermentation medium composition for the production of atrazine-degrading Acinetobacter sp. DNS(32) in shake-flask cultures. A "Plackett-Burman Design" was employed to evaluate the effects of different components in the medium. The concentrations of corn flour, soybean flour, and K(2)HPO(4) were found to significantly influence Acinetobacter sp. DNS(32) production. The steepest ascent method was employed to determine the optimal regions of these three significant factors. Then, these three factors were optimized using central composite design of "response surface methodology." The optimized fermentation medium composition was composed as follows (g/L): corn flour 39.49, soybean flour 25.64, CaCO(3) 3, K(2)HPO(4) 3.27, MgSO(4)·7H(2)O 0.2, and NaCl 0.2. The predicted and verifiable values in the medium with optimized concentration of components in shake flasks experiments were 7.079 × 10(8) CFU/mL and 7.194 × 10(8) CFU/mL, respectively. The validated model can precisely predict the growth of atrazine-degraing bacterium, Acinetobacter sp. DNS(32).

Related factors of dental caries and molar incisor hypomineralisation in a group of children with cystic fibrosis.

PubMed

Peker, S; Mete, S; Gokdemir, Y; Karadag, B; Kargul, B

2014-08-01

To investigate dental caries and molar incisor hypomineralisation (MIH)-related factors such as treatment, diet, brushing and salivary factors in children with cystic fibrosis (CF) compared with healthy peers. A cohort study was performed. This study was performed on 30 CF children comprising patients at the Faculty of Medicine and 30 control children recruited from the Dental School. Salivary factors, dental caries, MIH, daily diet, brushing habits were analysed. Statistical analysis was calculated by SPSS for Windows. Decay missing filled teeth (DMF-T) score was 4.6 ± 4.0 in CF and 7.7 ± 2.7 in control (p = 0.001). 43% of CF children with MIH were found to use antibiotics, but no significant difference in the caries experience was found with antibiotic usage (p > 0.05). DMF-T of CF adolescents (23%) who use Tobramycin was 7 ± 3.5. DMF-T of CF children (20%) who take other antibiotics was 2.5 ± 3.5, but no statistical difference was found (p = 0.054). Saliva pH, salivary flow rate, and buffering capacity were not found statistically significant (p > 0.05). Percentage arithmetic mean value, standard deviation, independent sample t test, Fisher's exact test, Chi-square test and Mann-Whitney U test were used, while a p value of <0.05 was considered statistically significant. Medication and diet could be considered as a risk factor for dental caries and factors such as salivary pH, good oral hygiene could play a protective role for oral health CF children. MIH frequency and lower caries experience seen in CF children could be due to salivary factors or pharmacological treatment they take. The multidisciplinary approach team would be advantageous in the management of children with CF and oral health should be under control during early years of life by paediatric dentists.

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

PubMed Central

Memon, Aftab Hameed; Rahman, Ismail Abdul

2014-01-01

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

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

PubMed

Memon, Aftab Hameed; Rahman, Ismail Abdul

2014-01-01

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

Does angiotensin-converting enzyme-1 (ACE-1) gene polymorphism lead to chronic kidney disease among hypertensive patients?

PubMed

Sarkar, Taposh; Singh, Narinder Pal; Kar, Premashish; Husain, Syed Akhtar; Kapoor, Seema; Pollipalli, Sunil Kumar; Kumar, Anish; Garg, Neena

2016-06-01

Hypertension is one of the important contributing factors linked with both causation and development of kidney disease. It is a multifactorial, polygenic, and complex disorder due to interaction of several risk genes with environmental factors. The present study was aimed to explore genetic polymorphism in ACE-1 gene as a risk factor for CKD among hypertensive patients. Three hundred patients were enrolled in the study. Ninety were hypertensive patients with CKD taken as cases, whereas 210 hypertensive patients without CKD were taken as controls. Demographic data including age, sex, Body mass index (BMI), and other risk factors were also recorded. DNA was extracted from blood by salting out method. Genotyping of ACE gene was done by PCR technique. All the statistical analysis was done by using Epi Info and SPSS version 16 software (SPSS Inc., Chicago, IL). Mean age was higher in the control group (p < 0.05). Variables among two groups were compared out of which age, BMI, hemoglobin (Hb) was found to be statistically significant whereas other variables like systolic blood pressure, triglyceride and low-density lipoprotein were not. Blood urea and serum creatinine levels were statistically significant in the two genotypes (p < 0.05). Total and HDL cholesterol were statistically significant for DD genotype of ACE gene (OR = 1.42, 95% CI = 0.72-2.81). Similarly, the risk for CKD among hypertensive patients was also associated with D allele of ACE gene (OR = 1.25, 95% CI = 0.86-1.79). It is concluded that ACE-DD genotype may be a risk factor for the causation and development of chronic kidney failure among hypertensive patients.

Adjuvant cytostatic therapy of breast cancer as an important factor in the postponing of a relapse and longer survival period.

PubMed

Stula, N

1992-01-01

This prospective clinical study shows the results of the adjuvant cytostatic therapy (ACT) in breast cancer applied to patients in the premenopausal age. Cyclophosphamide, methotrexate, 5-fluorouracil (CMF) group (70 patients): after operative and radiotherapeutic treatment the ACT is applied over the period of six months (six cycles). Control group (71 patients): only operative and radiotherapeutic treatment. Protocol of the ACT: cyclophosphamide, methotrexate, 5-fluorouracil (CMF) over 5 days with a 4-week break. Total 6 cycles. Control period: 10 years. Stratification of patients was made on the basis of the following risk factors: size of the tumour, number of positive lymph nodes of ipsilateral axilla, grade of the differentiation of the tumour, hormonal dependence of the tumour. Statistical method of analysis: actuary calculation, the Hi square test. The results show that the application of the ACT is statistically significant (P < 0.05) in regard to the disease-free interval. However, concerning the survival, the usefulness of its application is present but not statistically significant on the significance level of 5%. The usefulness of the ACT application as regards high risk factors (T3, T4 > or = 4 lymph nodes, grade of differentiation II, III, ER-PR-) is statistically significant (P < 0.05) both in regard to the DFI and survival. Regarding low risk factors the ACT application adversely influenced the results in the control group. This is probably the result of the ACT toxicity. The patients have a favourable prognosis in this subgroup in regard to the staging and biological nature of the tumour. The ACT in the premenopausal age of patients with high risk factors gives a significantly better results concerning the procrastination of relapse and the length of the survival period.

Stationary statistical theory of two-surface multipactor regarding all impacts for efficient threshold analysis

NASA Astrophysics Data System (ADS)

Lin, Shu; Wang, Rui; Xia, Ning; Li, Yongdong; Liu, Chunliang

2018-01-01

Statistical multipactor theories are critical prediction approaches for multipactor breakdown determination. However, these approaches still require a negotiation between the calculation efficiency and accuracy. This paper presents an improved stationary statistical theory for efficient threshold analysis of two-surface multipactor. A general integral equation over the distribution function of the electron emission phase with both the single-sided and double-sided impacts considered is formulated. The modeling results indicate that the improved stationary statistical theory can not only obtain equally good accuracy of multipactor threshold calculation as the nonstationary statistical theory, but also achieve high calculation efficiency concurrently. By using this improved stationary statistical theory, the total time consumption in calculating full multipactor susceptibility zones of parallel plates can be decreased by as much as a factor of four relative to the nonstationary statistical theory. It also shows that the effect of single-sided impacts is indispensable for accurate multipactor prediction of coaxial lines and also more significant for the high order multipactor. Finally, the influence of secondary emission yield (SEY) properties on the multipactor threshold is further investigated. It is observed that the first cross energy and the energy range between the first cross and the SEY maximum both play a significant role in determining the multipactor threshold, which agrees with the numerical simulation results in the literature.

Lifestyle Factors in U.S. Residential Electricity Consumption

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

Sanquist, Thomas F.; Orr, Heather M.; Shui, Bin

2012-03-30

A multivariate statistical approach to lifestyle analysis of residential electricity consumption is described and illustrated. Factor analysis of selected variables from the 2005 U.S. Residential Energy Consumption Survey (RECS) identified five lifestyle factors reflecting social and behavioral choices associated with air conditioning, laundry usage, personal computer usage, climate zone of residence, and TV use. These factors were also estimated for 2001 RECS data. Multiple regression analysis using the lifestyle factors yields solutions accounting for approximately 40% of the variance in electricity consumption for both years. By adding the associated household and market characteristics of income, local electricity price and accessmore » to natural gas, variance accounted for is increased to approximately 54%. Income contributed only {approx}1% unique variance to the 2005 and 2001 models, indicating that lifestyle factors reflecting social and behavioral choices better account for consumption differences than income. This was not surprising given the 4-fold range of energy use at differing income levels. Geographic segmentation of factor scores is illustrated, and shows distinct clusters of consumption and lifestyle factors, particularly in suburban locations. The implications for tailored policy and planning interventions are discussed in relation to lifestyle issues.« less

The effect of baryons in the cosmological lensing PDFs

NASA Astrophysics Data System (ADS)

Castro, Tiago; Quartin, Miguel; Giocoli, Carlo; Borgani, Stefano; Dolag, Klaus

2018-07-01

Observational cosmology is passing through a unique moment of grandeur with the amount of quality data growing fast. However, in order to better take advantage of this moment, data analysis tools have to keep up the pace. Understanding the effect of baryonic matter on the large-scale structure is one of the challenges to be faced in cosmology. In this work, we have thoroughly studied the effect of baryonic physics on different lensing statistics. Making use of the Magneticum Pathfinder suite of simulations, we show that the influence of luminous matter on the 1-point lensing statistics of point sources is significant, enhancing the probability of magnified objects with μ > 3 by a factor of 2 and the occurrence of multiple images by a factor of 5-500, depending on the source redshift and size. We also discuss the dependence of the lensing statistics on the angular resolution of sources. Our results and methodology were carefully tested to guarantee that our uncertainties are much smaller than the effects here presented.

Sympathetic Nerve Injury in Thyroid Cancer.

PubMed

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

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

The effect of baryons in the cosmological lensing PDFs

NASA Astrophysics Data System (ADS)

Castro, Tiago; Quartin, Miguel; Giocoli, Carlo; Borgani, Stefano; Dolag, Klaus

2018-05-01

Observational cosmology is passing through a unique moment of grandeur with the amount of quality data growing fast. However, in order to better take advantage of this moment, data analysis tools have to keep up the pace. Understanding the effect of baryonic matter on the large-scale structure is one of the challenges to be faced in cosmology. In this work, we have thoroughly studied the effect of baryonic physics on different lensing statistics. Making use of the Magneticum Pathfinder suite of simulations we show that the influence of luminous matter on the 1-point lensing statistics of point sources is significant, enhancing the probability of magnified objects with μ > 3 by a factor of 2 and the occurrence of multiple-images by a factor 5 - 500 depending on the source redshift and size. We also discuss the dependence of the lensing statistics on the angular resolution of sources. Our results and methodology were carefully tested in order to guarantee that our uncertainties are much smaller than the effects here presented.

Statistical analysis of the photodegradation of imazethapyr on the surface of extracted soybean (Glycine max) and corn (Zea mays) epicuticular waxes.

PubMed

Anderson, Scott C; Christiansen, Amy; Peterson, Alexa; Beukelman, Logan; Nienow, Amanda M

2016-10-12

The photodegradation rate of the herbicide imazethapyr on epicuticular waxes of soybean and corn plants was investigated. Plant age, relative humidity, temperature, and number of light banks were varied during plant growth, analyzed statistically, and examined to determine if these factors had an effect on the photodegradation of imazethapyr. Through ultraviolet/visible (UV-Vis) and fluorescence spectroscopy, epicuticular wax characteristics of soybean and corn plants were explored, were used to confirm observations determined statistically, and explain correlations between the rate constants and the composition of the epicuticular waxes. Plant age, the interaction between plant age and light, and the quadratic dependence on temperature were all determined to have a significant impact on the photodegradation rate of imazethapyr on the epicuticular waxes of soybean plants. As for the photodegradation rate on the epicuticular waxes of corn plants, the number of light banks used during growing and temperature were significant factors.

Development and Validation of the Caring Loneliness Scale.

PubMed

Karhe, Liisa; Kaunonen, Marja; Koivisto, Anna-Maija

2016-12-01

The Caring Loneliness Scale (CARLOS) includes 5 categories derived from earlier qualitative research. This article assesses the reliability and construct validity of a scale designed to measure patient experiences of loneliness in a professional caring relationship. Statistical analysis with 4 different sample sizes included Cronbach's alpha and exploratory factor analysis with principal axis factoring extraction. The sample size of 250 gave the most useful and comprehensible structure, but all 4 samples yielded underlying content of loneliness experiences. The initial 5 categories were reduced to 4 factors with 24 items and Cronbach's alpha ranging from .77 to .90. The findings support the reliability and validity of CARLOS for the assessment of Finnish breast cancer and heart surgery patients' experiences but as all instruments, further validation is needed.

[Labour factors associated with post-traumatic stress in uniformed workers in Medellín].

PubMed

González-Penagos, Catalina; Moreno-Bedoya, Juan P; Berbesi-Fernández, Dedsy Y; Segura-Cardona, Angela M

2013-01-01

Determining the labor factors associated with post-traumatic stress in uniformed workers in Medellin. A cross-sectional study was made of 124 uniformed workers aged 20 to 48 years-old. A survey was made using an adults' post-traumatic stress instrument which had been validated in Medellin. Statistical analysis was carried out. Post-traumatic stress disorder risk prevalence was 52.2 %. Multivariate analysis showed that the highest risk situations were those related to previous mental health diagnosis (PR=7.67), working schedule (4.24), violent episodes (PR=3.59) and community relationships (PR=2.73). A person's current labor situation seemed to be a risk factor for developing post-traumatic stress in the target population.

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.

fMRI reliability: influences of task and experimental design.

PubMed

Bennett, Craig M; Miller, Michael B

2013-12-01

As scientists, it is imperative that we understand not only the power of our research tools to yield results, but also their ability to obtain similar results over time. This study is an investigation into how common decisions made during the design and analysis of a functional magnetic resonance imaging (fMRI) study can influence the reliability of the statistical results. To that end, we gathered back-to-back test-retest fMRI data during an experiment involving multiple cognitive tasks (episodic recognition and two-back working memory) and multiple fMRI experimental designs (block, event-related genetic sequence, and event-related m-sequence). Using these data, we were able to investigate the relative influences of task, design, statistical contrast (task vs. rest, target vs. nontarget), and statistical thresholding (unthresholded, thresholded) on fMRI reliability, as measured by the intraclass correlation (ICC) coefficient. We also utilized data from a second study to investigate test-retest reliability after an extended, six-month interval. We found that all of the factors above were statistically significant, but that they had varying levels of influence on the observed ICC values. We also found that these factors could interact, increasing or decreasing the relative reliability of certain Task × Design combinations. The results suggest that fMRI reliability is a complex construct whose value may be increased or decreased by specific combinations of factors.

The Analysis of Factors Causing the High Prevalence of Child Obesity in Jeju Island.

PubMed

Park, Eun Hye; Oh, Min-Su; Kim, Sorina; Lee, Juyeon; Kang, Ki Soo

2018-04-01

For 3 consecutive years from 2012-2014, we analyzed the causative factors for why the Jeju Island had the highest obesity prevalences of school children among the 15 provinces in Korea. From our analysis of 28,026 elementary school children with obesity or normal weight in the 15 provinces, we analyzed 12 factors related to eating habits, exercise habits, lifestyle, and mental health. The differences between the obese and normal weight children were researched. Finally, Jeju was compared with Seoul, which has the lowest obesity prevalence in school age children. Statistical analysis was performed using the chi square test of PASW Statistics ver. 18.0. Compared to the normal weight group, the obese group had significantly higher rates of consuming soft drinks ( p <0.001), fast food intake ( p =0.019), skipping breakfast ( p <0.001), insufficient sleep ( p <0.001), bullying experiences ( p =0.001) and runaway impulses ( p =0.012). Compared to Seoul, Jeju Island had significantly higher rates of Ramen intake (3.4% vs. 5.4%, p =0.021) and meat intake (46.0% vs. 52.9%, p =0.003). On the other hand, Jeju Island was significantly lower than was Seoul in their fruit intake (83.4% vs. 67.1%, p <0.001), vegetable intake (71.4% vs. 64.2%, p =0.001), and intense physical activity (63.4% vs. 47.7%, p <0.001). Meanwhile, insufficient sleep (15.4% vs. 9.6%, p <0.001) and runaway impulses (5.6% vs. 3.3%, p =0.027) in children were significantly lower in Jeju Island than in Seoul. The results of the obesity factor analysis of elementary school students in Jeju Island can be used as useful educational material for lowering the obesity prevalence in Jeju community.

Lack of findings for the association between obesity risk and usual sugar-sweetened beverage consumption in adults--a primary analysis of databases of CSFII-1989-1991, CSFII-1994-1998, NHANES III, and combined NHANES 1999-2002.

PubMed

Sun, Sam Z; Empie, Mark W

2007-08-01

The relationship between obesity risk and sugar-sweetened beverage (SSB) consumption was examined together with multiple lifestyle factors. Statistical analysis was performed using population dietary survey databases of USDA CSFII 1989-1991, CSFII 1994-1996, CDC NHANES III, and combined NHANES 1999-2002. Totally, 38,409 individuals, ages 20-74 years, with accompanying data of dietary intake, lifestyle factors, and anthropometrics were included in the descriptive statistics and risk analysis. Analytical results indicate that obesity risk was significantly and positively associated with gender, age, daily TV/screen watching hours and dietary fat content, and negatively associated with smoking habit, education and physical activity; obesity risk was not significantly associated with SSB consumption pattern, dietary saturated fat content and total calorie intake. No elevated BMI values or increased obesity rates were observed in populations frequently consuming SSB compared to populations infrequently consuming SSB. Additionally, one-day food consumption data was found to overestimate SSB usual intake by up to 38.9% compared to the data of multiple survey days. multiple lifestyle factors and higher dietary fat intake were significantly associated with obesity risk. Populations who frequently consumed SSB, primarily HFCS sweetened beverages, did not have a higher obesity rate or increased obesity risk than that of populations which consumed SSB infrequently.

A 3-Year Study of Predictive Factors for Positive and Negative Appendicectomies.

PubMed

Chang, Dwayne T S; Maluda, Melissa; Lee, Lisa; Premaratne, Chandrasiri; Khamhing, Srisongham

2018-03-06

Early and accurate identification or exclusion of acute appendicitis is the key to avoid the morbidity of delayed treatment for true appendicitis or unnecessary appendicectomy, respectively. We aim (i) to identify potential predictive factors for positive and negative appendicectomies; and (ii) to analyse the use of ultrasound scans (US) and computed tomography (CT) scans for acute appendicitis. All appendicectomies that took place at our hospital from the 1st of January 2013 to the 31st of December 2015 were retrospectively recorded. Test results of potential predictive factors of acute appendicitis were recorded. Statistical analysis was performed using Fisher exact test, logistic regression analysis, sensitivity, specificity, and positive and negative predictive values calculation. 208 patients were included in this study. 184 patients had histologically proven acute appendicitis. The other 24 patients had either nonappendicitis pathology or normal appendix. Logistic regression analysis showed statistically significant associations between appendicitis and white cell count, neutrophil count, C-reactive protein, and bilirubin. Neutrophil count was the test with the highest sensitivity and negative predictive values, whereas bilirubin was the test with the highest specificity and positive predictive values (PPV). US and CT scans had high sensitivity and PPV for diagnosing appendicitis. No single test was sufficient to diagnose or exclude acute appendicitis by itself. Combining tests with high sensitivity (abnormal neutrophil count, and US and CT scans) and high specificity (raised bilirubin) may predict acute appendicitis more accurately.

[PASS neurocognitive dysfunction in attention deficit].

PubMed

Pérez-Alvarez, F; Timoneda-Gallart, C

Attention deficit disorder shows both cognitive and behavioral patterns. To determine a particular PASS (planning, attention, successive and simultaneous) pattern in order to early diagnosis and remediation according to PASS theory. 80 patients were selected from the neuropediatric attendance, aged 6 to 12 years old, 55 boys and 25 girls. Inclusion criteria were inattention (80 cases) and inattention with hyperactive symptoms (40 cases) according to the Diagnostic and Statistical Manual (DSM-IV). Exclusion criteria were the criteria of phonologic awareness previously reported, considered useful to diagnose dyslexia. A control group of 300 individuals, aged 5 to 12 years old, was used, criteria above mentioned being controlled. DN:CAS (Das-Naglieri Cognitive Assessment System) battery, translated to native language, was given to assess PASS cognitive processes. Results were analyzed with cluster analysis and t-Student test. Statistical factor analysis of the control group had previously identified the four PASS processes: planning, attention, successive and simultaneous. The dendrogram of the cluster analysis discriminated three categories of attention deficit disorder: 1. The most frequent, with planning deficit; 2. Without planning deficit but with deficit in other processes, and 3. Just only a few cases, without cognitive processing deficit. Cognitive deficiency in terms of means of scores was statistically significant when compared to control group (p = 0.001). According to PASS pattern, planning deficiency is a relevant factor. Neurological planning is not exactly the same than neurological executive function. The behavioral pattern is mainly linked to planning deficiency, but also to other PASS processing deficits and even to no processing deficit.

Using Genome-Wide Expression Profiling to Define Gene Networks Relevant to the Study of Complex Traits: From RNA Integrity to Network Topology

PubMed Central

O'Brien, M.A.; Costin, B.N.; Miles, M.F.

2014-01-01

Postgenomic studies of the function of genes and their role in disease have now become an area of intense study since efforts to define the raw sequence material of the genome have largely been completed. The use of whole-genome approaches such as microarray expression profiling and, more recently, RNA-sequence analysis of transcript abundance has allowed an unprecedented look at the workings of the genome. However, the accurate derivation of such high-throughput data and their analysis in terms of biological function has been critical to truly leveraging the postgenomic revolution. This chapter will describe an approach that focuses on the use of gene networks to both organize and interpret genomic expression data. Such networks, derived from statistical analysis of large genomic datasets and the application of multiple bioinformatics data resources, poten-tially allow the identification of key control elements for networks associated with human disease, and thus may lead to derivation of novel therapeutic approaches. However, as discussed in this chapter, the leveraging of such networks cannot occur without a thorough understanding of the technical and statistical factors influencing the derivation of genomic expression data. Thus, while the catch phrase may be “it's the network … stupid,” the understanding of factors extending from RNA isolation to genomic profiling technique, multivariate statistics, and bioinformatics are all critical to defining fully useful gene networks for study of complex biology. PMID:23195313

Outcome predictors in the management of intramedullary classic ependymoma: An integrative survival analysis.

PubMed

Wang, Yinqing; Cai, Ranze; Wang, Rui; Wang, Chunhua; Chen, Chunmei

2018-06-01

This is a retrospective study.The aim of this study was to illustrate the survival outcomes of patients with classic ependymoma (CE) and identify potential prognostic factors.CE is the most common category of spinal ependymomas, but few published studies have discussed predictors of the survival outcome.A Boolean search of the PubMed, Embase, and OVID databases was conducted by 2 investigators independently. The objects were intramedullary grade II ependymoma according to 2007 WHO classification. Univariate Kaplan-Meier analysis and Log-Rank tests were performed to identify variables associated with progression-free survival (PFS) or overall survival (OS). Multivariate Cox regression was performed to assess hazard ratios (HRs) with 95% confidence intervals (95% CIs). Statistical analysis was performed by SPSS version 23.0 (IBM Corp.) with statistical significance defined as P < .05.A total of 35 studies were identified, including 169 cases of CE. The mean follow-up time across cases was 64.2 ± 51.5 months. Univariate analysis showed that patients who had undergone total resection (TR) had better PFS and OS than those with subtotal resection (STR) and biopsy (P = .002, P = .004, respectively). Within either univariate or multivariate analysis (P = .000, P = .07, respectively), histological type was an independent prognostic factor for PFS of CE [papillary type: HR 0.002, 95% CI (0.000-0.073), P = .001, tanycytic type: HR 0.010, 95% CI (0.000-0.218), P = .003].It was the first integrative analysis of CE to elucidate the correlation between kinds of factors and prognostic outcomes. Definite histological type and safely TR were foundation of CE's management. 4.

Spatio-temporal dependencies between hospital beds, physicians and health expenditure using visual variables and data classification in statistical table

NASA Astrophysics Data System (ADS)

Medyńska-Gulij, Beata; Cybulski, Paweł

2016-06-01

This paper analyses the use of table visual variables of statistical data of hospital beds as an important tool for revealing spatio-temporal dependencies. It is argued that some of conclusions from the data about public health and public expenditure on health have a spatio-temporal reference. Different from previous studies, this article adopts combination of cartographic pragmatics and spatial visualization with previous conclusions made in public health literature. While the significant conclusions about health care and economic factors has been highlighted in research papers, this article is the first to apply visual analysis to statistical table together with maps which is called previsualisation.

Considering Horn's Parallel Analysis from a Random Matrix Theory Point of View.

PubMed

Saccenti, Edoardo; Timmerman, Marieke E

2017-03-01

Horn's parallel analysis is a widely used method for assessing the number of principal components and common factors. We discuss the theoretical foundations of parallel analysis for principal components based on a covariance matrix by making use of arguments from random matrix theory. In particular, we show that (i) for the first component, parallel analysis is an inferential method equivalent to the Tracy-Widom test, (ii) its use to test high-order eigenvalues is equivalent to the use of the joint distribution of the eigenvalues, and thus should be discouraged, and (iii) a formal test for higher-order components can be obtained based on a Tracy-Widom approximation. We illustrate the performance of the two testing procedures using simulated data generated under both a principal component model and a common factors model. For the principal component model, the Tracy-Widom test performs consistently in all conditions, while parallel analysis shows unpredictable behavior for higher-order components. For the common factor model, including major and minor factors, both procedures are heuristic approaches, with variable performance. We conclude that the Tracy-Widom procedure is preferred over parallel analysis for statistically testing the number of principal components based on a covariance matrix.

Microbial Keratitis in Kingdom of Bahrain: Clinical and Microbiology Study

PubMed Central

Al-Yousuf, Nada

2009-01-01

Background: Microbial keratitis is a potentially vision threatening condition worldwide. Knowing the predisposing factors and etiologic microorganism can help control and prevent this problem. This is the first study of its kind in Kingdom of Bahrain. Objective: To study the profile of microbial keratitis in Bahrain with special focus on risk factors, clinical outcome and microbilogical results. Methods: A retrospective analysis of all patients admitted in Salmaniya Medical Complex over a period of three years from January 2005 to January 2007 was performed. A total of 285 patients with keratitis were analysed. Non infectious corneal ulceration were excluded. Data collected from medical records were demographic features, predisposing factors, history of corneal trauma, associated ocular conditions, visual acuity at the time of presentation and the clinical course. Predisposing risk factors measured were contact lens use, presence of blepharitis, diabetes, lid abnormalities, dry eyes, keratoplasty and refractive surgery. For contact lens wearers any contact lens related risk factors that can lead to keratitis were measured. Pearson's chi-square test was used to carry out statistical analysis wherever required. Results: Contact lens wear, as a risk factor for microbial keratitis, formed 40% of the total study population. Other risk factors identified were dry eyes 24 cases (8%), 10 blepharitis (3%), 22 trauma (8%), abnormal lid position 14 cases (5%). 6 patients keratitis in a graft (2%), 3 had refractive surgery (1%). The most common causative organism isolated was pseudomonas aeroginosa (54%) followed by streptococcus 12%, staph 10%, other organisms 6%. 95% of contact lens wearers had pseudomonas Aeroginosa. This was statistically significant (p< 0.0001). The vast majority, 92% healed with scarring. 1% needed therapeutic keratoplasty and 7% lost to follow up. Risk factors in contact lens wearers were; 41 patients (36%) slept with the contact lenses. 12 (8%) had contact lens related trauma and 8 (7%) had poor hygiene. Sleeping with the contact lenses was statistically significant (p< 0.0001). Conclusion & Recommendation: Contact lens wear is the major risk factor for microbial keratitis in Bahrain. Pseudomonas aeroginosa was the commonest bacteria isolated. Sleeping with the contact lenses is the major risk factor among contact lens wearers. Majority of keratitis patients resulted in permanent scarring on the cornea. Educating the public, especially on contact lens care and precaution, can help reduce this visual morbidity. PMID:20142952

Polypropylene Production Optimization in Fluidized Bed Catalytic Reactor (FBCR): Statistical Modeling and Pilot Scale Experimental Validation

PubMed Central

Khan, Mohammad Jakir Hossain; Hussain, Mohd Azlan; Mujtaba, Iqbal Mohammed

2014-01-01

Propylene is one type of plastic that is widely used in our everyday life. This study focuses on the identification and justification of the optimum process parameters for polypropylene production in a novel pilot plant based fluidized bed reactor. This first-of-its-kind statistical modeling with experimental validation for the process parameters of polypropylene production was conducted by applying ANNOVA (Analysis of variance) method to Response Surface Methodology (RSM). Three important process variables i.e., reaction temperature, system pressure and hydrogen percentage were considered as the important input factors for the polypropylene production in the analysis performed. In order to examine the effect of process parameters and their interactions, the ANOVA method was utilized among a range of other statistical diagnostic tools such as the correlation between actual and predicted values, the residuals and predicted response, outlier t plot, 3D response surface and contour analysis plots. The statistical analysis showed that the proposed quadratic model had a good fit with the experimental results. At optimum conditions with temperature of 75°C, system pressure of 25 bar and hydrogen percentage of 2%, the highest polypropylene production obtained is 5.82% per pass. Hence it is concluded that the developed experimental design and proposed model can be successfully employed with over a 95% confidence level for optimum polypropylene production in a fluidized bed catalytic reactor (FBCR). PMID:28788576

Discrete geometric analysis of message passing algorithm on graphs

NASA Astrophysics Data System (ADS)

Watanabe, Yusuke

2010-04-01

We often encounter probability distributions given as unnormalized products of non-negative functions. The factorization structures are represented by hypergraphs called factor graphs. Such distributions appear in various fields, including statistics, artificial intelligence, statistical physics, error correcting codes, etc. Given such a distribution, computations of marginal distributions and the normalization constant are often required. However, they are computationally intractable because of their computational costs. One successful approximation method is Loopy Belief Propagation (LBP) algorithm. The focus of this thesis is an analysis of the LBP algorithm. If the factor graph is a tree, i.e. having no cycle, the algorithm gives the exact quantities. If the factor graph has cycles, however, the LBP algorithm does not give exact results and possibly exhibits oscillatory and non-convergent behaviors. The thematic question of this thesis is "How the behaviors of the LBP algorithm are affected by the discrete geometry of the factor graph?" The primary contribution of this thesis is the discovery of a formula that establishes the relation between the LBP, the Bethe free energy and the graph zeta function. This formula provides new techniques for analysis of the LBP algorithm, connecting properties of the graph and of the LBP and the Bethe free energy. We demonstrate applications of the techniques to several problems including (non) convexity of the Bethe free energy, the uniqueness and stability of the LBP fixed point. We also discuss the loop series initiated by Chertkov and Chernyak. The loop series is a subgraph expansion of the normalization constant, or partition function, and reflects the graph geometry. We investigate theoretical natures of the series. Moreover, we show a partial connection between the loop series and the graph zeta function.

Bacterial Community Dynamics in Full-Scale Activated Sludge Bioreactors: Operational and Ecological Factors Driving Community Assembly and Performance

PubMed Central

Valentín-Vargas, Alexis; Toro-Labrador, Gladys; Massol-Deyá, Arturo A.

2012-01-01

The assembling of bacterial communities in conventional activated sludge (CAS) bioreactors was thought, until recently, to be chaotic and mostly unpredictable. Studies done over the last decade have shown that specific, and often, predictable random and non-random factors could be responsible for that process. These studies have also motivated a “structure–function” paradigm that is yet to be resolved. Thus, elucidating the factors that affect community assembly in the bioreactors is necessary for predicting fluctuations in community structure and function. For this study activated sludge samples were collected during a one-year period from two geographically distant CAS bioreactors of different size. Combining community fingerprinting analysis and operational parameters data with a robust statistical analysis, we aimed to identify relevant links between system performance and bacterial community diversity and dynamics. In addition to revealing a significant β-diversity between the bioreactors’ communities, results showed that the largest bioreactor had a less dynamic but more efficient and diverse bacterial community throughout the study. The statistical analysis also suggests that deterministic factors, as opposed to stochastic factors, may have a bigger impact on the community structure in the largest bioreactor. Furthermore, the community seems to rely mainly on mechanisms of resistance and functional redundancy to maintain functional stability. We suggest that the ecological theories behind the Island Biogeography model and the species-area relationship were appropriate to predict the assembly of bacterial communities in these CAS bioreactors. These results are of great importance for engineers and ecologists as they reveal critical aspects of CAS systems that could be applied towards improving bioreactor design and operation. PMID:22880016

Health inequality in Slovenia.

PubMed

Artnik, B; Premik, M

2001-01-01

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

Factors influencing utilization of hospital services by adult sickle cell disease patients: a systematic review.

PubMed

Benenson, Irina; Jadotte, Yuri; Echevarria, Mercedes

2017-03-01

Painful vaso-occlusive crisis is a hallmark of sickle cell disease (SCD) that commonly results in utilization of hospital services. Recurrent use of hospital services by SCD patients is associated with high healthcare costs and adverse clinical outcomes. Understanding the factors influencing the pattern of utilization is a first step in improving medical care of this patient population while reducing healthcare expenditures. The primary objective of this systematic review was to determine what modifiable and non-modifiable factors influence utilization of hospital services by adult SCD patients. Adult SCD patients of both sexes who utilized hospital services for acute or emergency care. Non-modifiable and modifiable factors influencing utilization of hospital services. Prospective and retrospective cohort studies, case-control and analytical cross-sectional studies. The primary outcome of interest was high utilization of hospital services by adult SCD patients based on non-modifiable and modifiable factors measured as an odds ratio (analytical outcome). The secondary outcome was the prevalence of non-modifiable and modifiable factors among SCD patients who utilized hospital services measured as an event rate (descriptive outcome). A comprehensive multi-step search was undertaken to find both published and unpublished studies. Only studies published in the English language were included. The search was not limited by year of publication. Retrieved papers were assessed for methodological quality using standardized critical appraisal instruments from the Joanna Briggs Institute Meta Analysis of Statistics Assessment and Review Instrument. Data were extracted using a researcher-developed tool. Included studies were combined in a statistical meta-analysis. The meta-analysis was based on a random effect model. For studies that did not allow statistical pooling, the findings have been presented in a narrative form. Fourteen studies were included in this review. The analysis demonstrated that male patients accounted for 40.8% (95% confidence interval [CI] 0.370-0.447) of all utilizing patients. Sickle cell disease patients who were publically insured accounted for 76.5% (95% CI 0.632-0.861) of all patients who had hospital encounters. Patients aged 25-35 years had the highest rate of utilization, and the rate of utilization declined in patients older than 50 years. High utilizing patients had more diagnoses of acute chest syndrome and sepsis than patients who were moderate or low utilizers. The majority of SCD patients who utilized hospital services were women, young people and publically insured individuals. Patients with particularly high level of utilization had more frequent diagnoses of acute chest syndrome and sepsis.

[The impact of social and hygienic lifestyle factors on health status of students].

PubMed

Sakharova, O B; Kiku, P F; Gorborukova, T V

2012-01-01

The complex estimation of the impact of socio-hygienic lifestyle factors on the health of students has been performed. In the work the data of sociological analysis (questionnaire), the methods of multivariate statistics (correlation, regression analysis, method of correlation pleiades by P. V. Terentiev) were used. Among the analyzed components the average monthly income was found to make the greatest contribution of the health state and physical capacity of the studied contingent of students. The influence of this factor is most pronounced in a group of students with an average wealth. The quality of nutrition and the mode of life depend on the level of material well-being of students. Students with a deficiency or excess body weight are more susceptible to the effects of such lifestyle factors such as nutrition, physical activity, bad habits and prosperity.

Factor analysis as a tool for spectral line component separation 21cm emission in the direction of L1780

NASA Technical Reports Server (NTRS)

Toth, L. V.; Mattila, K.; Haikala, L.; Balazs, L. G.

1992-01-01

The spectra of the 21cm HI radiation from the direction of L1780, a small high-galactic latitude dark/molecular cloud, were analyzed by multivariate methods. Factor analysis was performed on HI (21cm) spectra in order to separate the different components responsible for the spectral features. The rotated, orthogonal factors explain the spectra as a sum of radiation from the background (an extended HI emission layer), and from the L1780 dark cloud. The coefficients of the cloud-indicator factors were used to locate the HI 'halo' of the molecular cloud. Our statistically derived 'background' and 'cloud' spectral profiles, as well as the spatial distribution of the HI halo emission distribution were compared to the results of a previous study which used conventional methods analyzing nearly the same data set.

Calypso: a user-friendly web-server for mining and visualizing microbiome-environment interactions.

PubMed

Zakrzewski, Martha; Proietti, Carla; Ellis, Jonathan J; Hasan, Shihab; Brion, Marie-Jo; Berger, Bernard; Krause, Lutz

2017-03-01

Calypso is an easy-to-use online software suite that allows non-expert users to mine, interpret and compare taxonomic information from metagenomic or 16S rDNA datasets. Calypso has a focus on multivariate statistical approaches that can identify complex environment-microbiome associations. The software enables quantitative visualizations, statistical testing, multivariate analysis, supervised learning, factor analysis, multivariable regression, network analysis and diversity estimates. Comprehensive help pages, tutorials and videos are provided via a wiki page. The web-interface is accessible via http://cgenome.net/calypso/ . The software is programmed in Java, PERL and R and the source code is available from Zenodo ( https://zenodo.org/record/50931 ). The software is freely available for non-commercial users. l.krause@uq.edu.au. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Disutility analysis of oil spills: graphs and trends.

PubMed

Ventikos, Nikolaos P; Sotiropoulos, Foivos S

2014-04-15

This paper reports the results of an analysis of oil spill cost data assembled from a worldwide pollution database that mainly includes data from the International Oil Pollution Compensation Fund. The purpose of the study is to analyze the conditions of marine pollution accidents and the factors that impact the costs of oil spills worldwide. The accidents are classified into categories based on their characteristics, and the cases are compared using charts to show how the costs are affected under all conditions. This study can be used as a helpful reference for developing a detailed statistical model that is capable of reliably and realistically estimating the total costs of oil spills. To illustrate the differences identified by this statistical analysis, the results are compared with the results of previous studies, and the findings are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Water quality and non-point sources of risk: the Jiulong River Watershed, P. R. of China.

PubMed

Zhang, Jingjing; Zhang, Luoping; Ricci, Paolo F

2012-01-01

Retrospective water quality assessment plays an essential role in identifying trends and causal associations between exposures and risks, thus it can be a guide for water resources management. We have developed empirical relationships between several time-varying social and economic factors of economic development, water quality variables such as nitrate-nitrogen, COD(Mn), BOD(5), and DO, in the Jiulong River Watershed and its main tributary, the West River. Our analyses used alternative statistical methods to reduce the dimensionality of the analysis first and then strengthen the study's causal associations. The statistical methods included: factor analysis (FA), trend analysis, Monte Carlo/bootstrap simulations, robust regressions and a coupled equations model, integrated into a framework that allows an investigation and resolution of the issues that may affect the estimated results. After resolving these, we found that the concentrations of nitrogen compounds increased over time in the West River region, and that fertilizer used in agricultural fruit crops was the main risk with regard to nitrogen pollution. The relationships we developed can identify hazards and explain the impact of sources of different types of pollution, such as urbanization, and agriculture.

Comparative inter-institutional study of stress among dentists.

PubMed

Pozos-Radillo, Blanca E; Galván-Ramírez, Ma Luz; Pando, Manuel; Carrión, Ma De los Angeles; González, Guillermo J

2010-01-01

Dentistry is considered to be a stressful profession due to different factors caused by work, representing a threat to dentists'health. The objectives of this work were to identify and compare chronic stress in dentists among the different health institutions and the association of stress with risk factors. The study in question is observational, transversal and comparative; 256 dentists were included, distributed among five public health institutions in the city of Guadalajara, Jalisco, Mexico, namely: the Mexican Institute of Social Security (IMSS), the Ministry of Health (SS), the Integral Development of the Family (DIF), the Social Security Services Institute for the Workers (ISSSTE) and the University of Guadalajara (U. de G) Data were obtained by means of the census technique. Stress was identified using the Stress Symptoms Inventory and the statistical analysis was performed using the Odds Ratio (O.R.) and the chi-square statistic. From the total population studied, 219 subjects presented high levels of chronic stress and 37, low levels. In the results of comparative analysis, significant differences were found between IMSS and U. de G and likewise between IMSS and SS. However, in the analysis of association, only U. de G was found to be associated with the high level of chronic stress.

The analysis of factors of management of safety of critical information infrastructure with use of dynamic models

NASA Astrophysics Data System (ADS)

Trostyansky, S. N.; Kalach, A. V.; Lavlinsky, V. V.; Lankin, O. V.

2018-03-01

Based on the analysis of the dynamic model of panel data by region, including fire statistics for surveillance sites and statistics of a set of regional socio-economic indicators, as well as the time of rapid response of the state fire service to fires, the probability of fires in the surveillance sites and the risk of human death in The result of such fires from the values of the corresponding indicators for the previous year, a set of regional social-economics factors, as well as regional indicators time rapid response of the state fire service in the fire. The results obtained are consistent with the results of the application to the fire risks of the model of a rational offender. Estimation of the economic equivalent of human life from data on surveillance objects for Russia, calculated on the basis of the analysis of the presented dynamic model of fire risks, correctly agrees with the known literary data. The results obtained on the basis of the econometric approach to fire risks allow us to forecast fire risks at the supervisory sites in the regions of Russia and to develop management solutions to minimize such risks.

Oregon ground-water quality and its relation to hydrogeological factors; a statistical approach

USGS Publications Warehouse

Miller, T.L.; Gonthier, J.B.

1984-01-01

An appraisal of Oregon ground-water quality was made using existing data accessible through the U.S. Geological Survey computer system. The data available for about 1,000 sites were separated by aquifer units and hydrologic units. Selected statistical moments were described for 19 constituents including major ions. About 96 percent of all sites in the data base were sampled only once. The sample data were classified by aquifer unit and hydrologic unit and analysis of variance was run to determine if significant differences exist between the units within each of these two classifications for the same 19 constituents on which statistical moments were determined. Results of the analysis of variance indicated both classification variables performed about the same, but aquifer unit did provide more separation for some constituents. Samples from the Rogue River basin were classified by location within the flow system and type of flow system. The samples were then analyzed using analysis of variance on 14 constituents to determine if there were significant differences between subsets classified by flow path. Results of this analysis were not definitive, but classification as to the type of flow system did indicate potential for segregating water-quality data into distinct subsets. (USGS)

A statistical analysis of the distribution of a larval nematode (Anisakis sp.) in the musculature of chum salmon (Oncorhynchus keta - Walbaum)

USGS Publications Warehouse

Novotny, A.J.

1960-01-01

The one factor which probably contributes the greatest effect on distributional patterns of Anisakis within chum salmon musculature is the total intensity of infection (or population density of Anisakis) in each fish.

Using Symbolic-Logic Matrices To Improve Confirmatory Factor Analysis Techniques.

ERIC Educational Resources Information Center

Creighton, Theodore B.; Coleman, Donald G.; Adams, R. C.

A continuing and vexing problem associated with survey instrument development is the creation of items, initially, that correlate favorably a posteriori with constructs being measured. This study tests the use of symbolic-logic matrices developed by D. G. Coleman (1979) in creating factorially "pure" statistically discrete constructs in…

Illinois Teacher Supply and Demand, 1984-1985.

ERIC Educational Resources Information Center

Bartolini, Leandro

Statistics are presented on the current status of teacher supply and demand trends in Illinois. This report reviews and discusses the factors affecting teacher supply and demand, changes in student enrollment, teacher retirements, changes in state mandates, and opportunity for employment. An analysis of the data collected on teacher employment…

Investigating Academic Success Factors for Undergraduate Business Students

ERIC Educational Resources Information Center

Kaighobadi, Mehdi; Allen, Marcus T.

2008-01-01

Student academic performance is of major interest to all stakeholders of higher education institutions. This study questions whether or not statistical analysis of information that is readily available in most universities' official records system can be used to predict overall academic success. In particular, this study is an attempt to…

The Learning Organization Model across Vocational and Academic Teacher Groups

ERIC Educational Resources Information Center

Park, Joo Ho; Rojewski, Jay W.

2006-01-01

Multiple-group confirmatory factor analysis was used to investigate factorial invariance between vocational and academic teacher groups on a measure of the learning organization concept. Participants were 488 full-time teachers of public trade industry-technical and business schools located within Seoul, South Korea. Statistically significant…

Gender and Pupil Performance. Interchange 70.

ERIC Educational Resources Information Center

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

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

AQAK: A Library Anxiety Scale for Undergraduate Students

ERIC Educational Resources Information Center

Anwar, Mumtaz A.; Al-Qallaf, Charlene L.; Al-Kandari, Noriah M.; Al-Ansari, Husain A.

2012-01-01

The library environment has drastically changed since 1992 when Bostick's Library Anxiety Scale was developed. This project aimed to develop a scale specifically for undergraduate students. A three-stage study was conducted, using students of Kuwait University. A variety of statistical measures, including factor analysis, were used to process the…

Identifying the Factors That Influence Change in SEBD Using Logistic Regression Analysis

ERIC Educational Resources Information Center

Camilleri, Liberato; Cefai, Carmel

2013-01-01

Multiple linear regression and ANOVA models are widely used in applications since they provide effective statistical tools for assessing the relationship between a continuous dependent variable and several predictors. However these models rely heavily on linearity and normality assumptions and they do not accommodate categorical dependent…

Contributions to Statistical Problems Related to Microarray Data

ERIC Educational Resources Information Center

Hong, Feng

2009-01-01

Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we…

Cross-National Differences in Special Education Coverage: An Empirical Analysis

ERIC Educational Resources Information Center

Anastasiou, Dimitris; Keller, Clayton E.

2014-01-01

This study investigated the role of educational and socioeconomic factors in explaining differences in national special education coverage. Data were derived from several international and governmental sources, targeting the year 2008 and covering 143 countries. Descriptive statistics revealed huge disparities in access to special education among…

EVALUATION OF THE EXTRACELLULAR MATRIX OF INJURED SUPRASPINATUS IN RATS

PubMed Central

Almeida, Luiz Henrique Oliveira; Ikemoto, Roberto; Mader, Ana Maria; Pinhal, Maria Aparecida Silva; Munhoz, Bruna; Murachovsky, Joel

2016-01-01

ABSTRACT Objective: To evaluate the evolution of injuries of the supraspinatus muscle by immunohistochemistry (IHC) and anatomopathological analysis in animal model (Wistar rats). Methods: Twenty-five Wistar rats were submitted to complete injury of the supraspinatus tendon, then subsequently sacrificed in groups of five animals at the following periods: immediately after the injury, 24h after the injury, 48h after, 30 days after and three months after the injury. All groups underwent histological and IHC analysis. Results: Regarding vascular proliferation and inflammatory infiltrate, we found a statistically significant difference between groups 1(control group) and 2 (24h after injury). IHC analysis showed that expression of vascular endothelial growth factor (VEGF) showed a statistically significant difference between groups 1 and 2, and collagen type 1 (Col-1) evaluation presented a statistically significant difference between groups 1 and 4. Conclusion: We observed changes in the extracellular matrix components compatible with remodeling and healing. Remodeling is more intense 24h after injury. However, VEGF and Col-1 are substantially increased at 24h and 30 days after the injury, respectively. Level of Evidence I, Experimental Study. PMID:26997907

Are studies reporting significant results more likely to be published?

PubMed

Koletsi, Despina; Karagianni, Anthi; Pandis, Nikolaos; Makou, Margarita; Polychronopoulou, Argy; Eliades, Theodore

2009-11-01

Our objective was to assess the hypothesis that there are variations of the proportion of articles reporting a significant effect, with a higher percentage of those articles published in journals with impact factors. The contents of 5 orthodontic journals (American Journal of Orthodontics and Dentofacial Orthopedics, Angle Orthodontist, European Journal of Orthodontics, Journal of Orthodontics, and Orthodontics and Craniofacial Research), published between 2004 and 2008, were hand-searched. Articles with statistical analysis of data were included in the study and classified into 4 categories: behavior and psychology, biomaterials and biomechanics, diagnostic procedures and treatment, and craniofacial growth, morphology, and genetics. In total, 2622 articles were examined, with 1785 included in the analysis. Univariate and multivariate logistic regression analyses were applied with statistical significance as the dependent variable, and whether the journal had an impact factor, the subject, and the year were the independent predictors. A higher percentage of articles showed significant results relative to those without significant associations (on average, 88% vs 12%) for those journals. Overall, these journals published significantly more studies with significant results, ranging from 75% to 90% (P = 0.02). Multivariate modeling showed that journals with impact factors had a 100% increased probability of publishing a statistically significant result compared with journals with no impact factor (odds ratio [OR], 1.99; 95% CI, 1.19-3.31). Compared with articles on biomaterials and biomechanics, all other subject categories showed lower probabilities of significant results. Nonsignificant findings in behavior and psychology and diagnosis and treatment were 1.8 (OR, 1.75; 95% CI, 1.51-2.67) and 3.5 (OR, 3.50; 95% CI, 2.27-5.37) times more likely to be published, respectively. Journals seem to prefer reporting significant results; this might be because of authors' perceptions of the importance of their findings and editors' and reviewers' preferences for significant results. The implication of this factor in the reliability of systematic reviews is discussed.

The Society of Thoracic Surgeons Congenital Heart Surgery Database Mortality Risk Model: Part 1—Statistical Methodology

PubMed Central

O’Brien, Sean M.; Jacobs, Jeffrey P.; Pasquali, Sara K.; Gaynor, J. William; Karamlou, Tara; Welke, Karl F.; Filardo, Giovanni; Han, Jane M.; Kim, Sunghee; Shahian, David M.; Jacobs, Marshall L.

2016-01-01

Background This study’s objective was to develop a risk model incorporating procedure type and patient factors to be used for case-mix adjustment in the analysis of hospital-specific operative mortality rates after congenital cardiac operations. Methods Included were patients of all ages undergoing cardiac operations, with or without cardiopulmonary bypass, at centers participating in The Society of Thoracic Surgeons Congenital Heart Surgery Database during January 1, 2010, to December 31, 2013. Excluded were isolated patent ductus arteriosus closures in patients weighing less than or equal to 2.5 kg, centers with more than 10% missing data, and patients with missing data for key variables. Data from the first 3.5 years were used for model development, and data from the last 0.5 year were used for assessing model discrimination and calibration. Potential risk factors were proposed based on expert consensus and selected after empirically comparing a variety of modeling options. Results The study cohort included 52,224 patients from 86 centers with 1,931 deaths (3.7%). Covariates included in the model were primary procedure, age, weight, and 11 additional patient factors reflecting acuity status and comorbidities. The C statistic in the validation sample was 0.858. Plots of observed-vs-expected mortality rates revealed good calibration overall and within subgroups, except for a slight overestimation of risk in the highest decile of predicted risk. Removing patient preoperative factors from the model reduced the C statistic to 0.831 and affected the performance classification for 12 of 86 hospitals. Conclusions The risk model is well suited to adjust for case mix in the analysis and reporting of hospital-specific mortality for congenital heart operations. Inclusion of patient factors added useful discriminatory power and reduced bias in the calculation of hospital-specific mortality metrics. PMID:26245502

Investigation of the Dominant Factors Influencing the ERA15 Temperature Increments at the Subtropical and Temperate Belts with a Focus over the Eastern Mediterranean Region

NASA Astrophysics Data System (ADS)

Alpert, Pinhas; Hirsch-Eshkol, Tali; Baharad, Anat

2015-04-01

A Stepwise Multi Regression-based statistics was employed for prioritizing the influence of several factors, both anthropogenic and natural, on the ERA15 temperature increments. The 5 factors which are defined as predictors are;topography, aerosol index (TOMS-AI), atmospheric vertical velocity along with two anthropogenic factors population density and land use changes (LUCI and NDVI trends). The seismic hazard assessment factor was also chosen as the "dummy variable", for validity. Special focus was given to the land use change factor, which was based on two different data sets; HITE data of historical land use/ land cover data and of NDVI trends during 1982- 1991. The Increment Analysis Updates of temperature (IAU(T)), the predicted data, was obtained from the ERA15 (1979-1993) reanalysis. The research consists of both spatial and vertical analyses as well as potential synergies of the selected variables. The spatial geographic analysis is divided into three categories; (a) Coarse region (b) Sub regions analysis and (c) A "small cell" of 4°X4° analysis. It is shown that the following three factors;Topography, TOMS-AI and NDVI are statistically significant (at p<0.05 level) in being the most effective predictors of IAU(T), especially at the 700mb level during March - June. In contrast, the 850mb presents the weakest contribution to IAU(T)probably due to contradictive influence of the various variables at this level. The land use as expressed by the NDVI trends factor, shows a very clear dependency with height, i.e. decreasing, and is one of the most influential factors over the Eastern Mediterranean, which explains up to 20% of the temperature increments in January at 700mb. Moreover, its influence is significant (p<0.05) through all research stages and the different combinations of the multiple regression runs. A major finding not quantified earlier. Reference: T. Hirsch-Eshkol, A. Baharad and P. Alpert, "Investigation of the dominant factors influencing the ERA15 temperature increments at the subtropical and temperate belts with a focus over the Eastern Mediterranean region", Land, 3, 1015-1036; doi:10.3390/land3031015, 2014.

Factors affecting aggression in South Korean middle school students.

PubMed

Park, MiJeong; Choi, Jihea; Lim, Seung-Joo

2014-12-01

The study was undertaken to assess levels of aggression, and to determine factors affecting aggression among South Korean middle school students. A descriptive study was conducted using self-report questionnaires. The participants were 340 girls and boys from two middle schools and 302 questionnaires were used for the final data analysis. Aggression, academic stress, depression, self esteem, decision-making competency, and happiness were measured. Data were analyzed using descriptive statistics including t tests, one-way analysis of variance, Pearson's correlation coefficients and multiple regressions. Aggression had significant correlations with academic stress (r = .21, p < .001), depression (r = .43, p < .001), self esteem (r = -.25, p < .001), decision-making competency (r = -.25, p < .001), and happiness (r = -.21, p < .001). Mean score for aggression was 2.49 out of 5. Significant explanatory variables for aggression were grade (t = 4.39, p < .001), academic stress (t = 2.78, p = .006), and depression (t = 5.03, p < .001). The explanatory power of these factors was 26.9%, and this was statistically significant (F = 16.06, p < .001). Findings indicate that depression, academic stress, and grade (second grade) influence aggression. To decrease aggressive behavior, it is necessary to provide systematic and political programs in schools and local communities that can ameliorate negative emotional factors like depression and academic stress. Additionally, development of positive factors such as self esteem, decision-making skills, and happiness in middle school students is important to reduce aggression. Copyright © 2014. Published by Elsevier B.V.