Noise removal using factor analysis of dynamic structures: application to cardiac gated studies.

Science.gov (United States)

Bruyant, P P; Sau, J; Mallet, J J

1999-10-01

Factor analysis of dynamic structures (FADS) facilitates the extraction of relevant data, usually with physiologic meaning, from a dynamic set of images. The result of this process is a set of factor images and curves plus some residual activity. The set of factor images and curves can be used to retrieve the original data with reduced noise using an inverse factor analysis process (iFADS). This improvement in image quality is expected because the inverse process does not use the residual activity, assumed to be made of noise. The goal of this work is to quantitate and assess the efficiency of this method on gated cardiac images. A computer simulation of a planar cardiac gated study was performed. The simulated images were added with noise and processed by the FADS-iFADS program. The signal-to-noise ratios (SNRs) were compared between original and processed data. Planar gated cardiac studies from 10 patients were tested. The data processed by FADS-iFADS were subtracted to the original data. The result of the substraction was studied to evaluate its noisy nature. The SNR is about five times greater after the FADS-iFADS process. The difference between original and processed data is noise only, i.e., processed data equals original data minus some white noise. The FADS-iFADS process is successful in the removal of an important part of the noise and therefore is a tool to improve the image quality of cardiac images. This tool does not decrease the spatial resolution (compared with smoothing filters) and does not lose details (compared with frequential filters). Once the number of factors is chosen, this method is not operator dependent.

Comparing 3 dietary pattern methods--cluster analysis, factor analysis, and index analysis--With colorectal cancer risk: The NIH-AARP Diet and Health Study.

Science.gov (United States)

Reedy, Jill; Wirfält, Elisabet; Flood, Andrew; Mitrou, Panagiota N; Krebs-Smith, Susan M; Kipnis, Victor; Midthune, Douglas; Leitzmann, Michael; Hollenbeck, Albert; Schatzkin, Arthur; Subar, Amy F

2010-02-15

The authors compared dietary pattern methods-cluster analysis, factor analysis, and index analysis-with colorectal cancer risk in the National Institutes of Health (NIH)-AARP Diet and Health Study (n = 492,306). Data from a 124-item food frequency questionnaire (1995-1996) were used to identify 4 clusters for men (3 clusters for women), 3 factors, and 4 indexes. Comparisons were made with adjusted relative risks and 95% confidence intervals, distributions of individuals in clusters by quintile of factor and index scores, and health behavior characteristics. During 5 years of follow-up through 2000, 3,110 colorectal cancer cases were ascertained. In men, the vegetables and fruits cluster, the fruits and vegetables factor, the fat-reduced/diet foods factor, and all indexes were associated with reduced risk; the meat and potatoes factor was associated with increased risk. In women, reduced risk was found with the Healthy Eating Index-2005 and increased risk with the meat and potatoes factor. For men, beneficial health characteristics were seen with all fruit/vegetable patterns, diet foods patterns, and indexes, while poorer health characteristics were found with meat patterns. For women, findings were similar except that poorer health characteristics were seen with diet foods patterns. Similarities were found across methods, suggesting basic qualities of healthy diets. Nonetheless, findings vary because each method answers a different question.

A factor analysis to find critical success factors in retail brand

Directory of Open Access Journals (Sweden)

Naser Azad

2013-03-01

Full Text Available The present exploratory study aims to find critical components of retail brand among some retail stores. The study seeks to build a brand name in retail level and looks to find important factors affecting it. Customer behavior is largely influenced when the first retail customer experience is formed. These factors have direct impacts on customer experience and satisfaction in retail industry. The proposed study performs an empirical investigation on two well-known retain stores located in city of Tehran, Iran. Using a sample of 265 people from regular customers, the study uses factor analysis and extracts four main factors including related brand, product benefits, customer welfare strategy and corporate profits using the existing 31 factors in the literature.

Determining the Number of Factors in P-Technique Factor Analysis

Science.gov (United States)

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

2017-01-01

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

A Beginner’s Guide to Factor Analysis: Focusing on Exploratory Factor Analysis

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An Gie Yong

2013-10-01

Full Text Available The following paper discusses exploratory factor analysis and gives an overview of the statistical technique and how it is used in various research designs and applications. A basic outline of how the technique works and its criteria, including its main assumptions are discussed as well as when it should be used. Mathematical theories are explored to enlighten students on how exploratory factor analysis works, an example of how to run an exploratory factor analysis on SPSS is given, and finally a section on how to write up the results is provided. This will allow readers to develop a better understanding of when to employ factor analysis and how to interpret the tables and graphs in the output.

Traditional cardiovascular risk factors and coronary collateral circulation: Protocol for a systematic review and meta-analysis of case-control studies.

Science.gov (United States)

Xing, Zhenhua; Pei, Junyu; Tang, Liang; Hu, Xinqun

2018-04-01

Well-developed coronary collateral circulation usually results in fewer infarct size, improved cardiac function, and fewer mortality. Traditional coronary risk factors (diabetes, hypertension, and smoking) have some effects on coronary collateral circulation. However, the association between these risk factors and coronary collateral circulation are controversial. Given the confusing evidences regarding traditional cardiovascular risk factors on coronary collateral circulation, we performed this meta-analysis protocol to investigate the relationship between traditional risk factors of coronary artery disease and coronary collateral circulation. MEDINE, EMBASE, and Science Citation Index will be searched to identify relevant studies. The primary outcomes of this meta-analysis are well-developed coronary collateral circulation. Meta-analysis was performed to calculate the odds ratio (OR) and 95% confidence interval (CI) of traditional coronary risk factors (diabetes, smoking, hypertriton). Pooled ORs were computed as the Mantel-Haenszel-weighted average of the ORs for all included studies. Sensitivity analysis, quality assessment, publication bias analysis, and the Grading of Recommendations Assessment, Development and Evaluation approach (GRADE) will be performed to ensure the reliability of our results. This study will provide a high-quality synthesis of current evidence of traditional risk factors on collateral circulation. This conclusion of our systematic review and meta-analysis will provide evidence to judge whether traditional risk factors affects coronary collateral circulation.Ethics and dissemination: Ethical approval is not required because our systematic review and meta-analysis will be based on published data without interventions on patients. The findings of this study will be published in a peer-reviewed journal.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies

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Hero Alfred

2010-11-01

Full Text Available Abstract Background Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP, the Indian Buffet Process (IBP, and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB analysis. Results Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV, Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD, closely related non-Bayesian approaches. Conclusions Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

Science.gov (United States)

Chen, Bo; Chen, Minhua; Paisley, John; Zaas, Aimee; Woods, Christopher; Ginsburg, Geoffrey S; Hero, Alfred; Lucas, Joseph; Dunson, David; Carin, Lawrence

2010-11-09

Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

An easy guide to factor analysis

CERN Document Server

Kline, Paul

2014-01-01

Factor analysis is a statistical technique widely used in psychology and the social sciences. With the advent of powerful computers, factor analysis and other multivariate methods are now available to many more people. An Easy Guide to Factor Analysis presents and explains factor analysis as clearly and simply as possible. The author, Paul Kline, carefully defines all statistical terms and demonstrates step-by-step how to work out a simple example of principal components analysis and rotation. He further explains other methods of factor analysis, including confirmatory and path analysis, a

Factor Economic Analysis at Forestry Enterprises

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M.Yu. Chik

2018-03-01

Full Text Available The article studies the importance of economic analysis according to the results of research of scientific works of domestic and foreign scientists. The calculation of the influence of factors on the change in the cost of harvesting timber products by cost items has been performed. The results of the calculation of the influence of factors on the change of costs on 1 UAH are determined using the full cost of sold products. The variable and fixed costs and their distribution are allocated that influences the calculation of the impact of factors on cost changes on 1 UAH of sold products. The paper singles out the general results of calculating the influence of factors on cost changes on 1 UAH of sold products. According to the results of the analysis, the list of reserves for reducing the cost of production at forest enterprises was proposed. The main sources of reserves for reducing the prime cost of forest products at forest enterprises are investigated based on the conducted factor analysis.

Application of factor analysis in psychological diagnostics (sample: study of students’ social safety

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Pavel Aleksandrovich Kislyakov

2015-10-01

Our recommendations for the use of factor analysis, with necessary restrictions and clear reasons of a possible ambiguity of solutions, will be useful to everyone interested in mastering an adequate mathematical tool for solving problems pertaining to the humanities, in particular, those of practical psychology. As a practical example is presented the research of the psychological factors which provide students’ social safety. With the help of the factor analysis relevant personal and professional qualities of a teacher were revealed which are the subjective factors of students’ social safety, namely: social anticipation, socio-psychological stress resistance, social tolerance, professional orientation, responsibility, communication skills.

Physics Metacognition Inventory Part II: Confirmatory factor analysis and Rasch analysis

Science.gov (United States)

Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

2015-11-01

The Physics Metacognition Inventory was developed to measure physics students' metacognition for problem solving. In one of our earlier studies, an exploratory factor analysis provided evidence of preliminary construct validity, revealing six components of students' metacognition when solving physics problems including knowledge of cognition, planning, monitoring, evaluation, debugging, and information management. The college students' scores on the inventory were found to be reliable and related to students' physics motivation and physics grade. However, the results of the exploratory factor analysis indicated that the questionnaire could be revised to improve its construct validity. The goal of this study was to revise the questionnaire and establish its construct validity through a confirmatory factor analysis. In addition, a Rasch analysis was applied to the data to better understand the psychometric properties of the inventory and to further evaluate the construct validity. Results indicated that the final, revised inventory is a valid, reliable, and efficient tool for assessing student metacognition for physics problem solving.

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

Science.gov (United States)

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.

Analysis of mineral phases in coal utilizing factor analysis

International Nuclear Information System (INIS)

Roscoe, B.A.; Hopke, P.K.

1982-01-01

The mineral phase inclusions of coal are discussed. The contribution of these to a coal sample are determined utilizing several techniques. Neutron activation analysis in conjunction with coal washability studies have produced some information on the general trends of elemental variation in the mineral phases. These results have been enhanced by the use of various statistical techniques. The target transformation factor analysis is specifically discussed and shown to be able to produce elemental profiles of the mineral phases in coal. A data set consisting of physically fractionated coal samples was generated. These samples were analyzed by neutron activation analysis and then their elemental concentrations examined using TTFA. Information concerning the mineral phases in coal can thus be acquired from factor analysis even with limited data. Additional data may permit the resolution of additional mineral phases as well as refinement of theose already identified

Factor analysis

CERN Document Server

Gorsuch, Richard L

2013-01-01

Comprehensive and comprehensible, this classic covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. Emphasizing the usefulness of the techniques, it presents sufficient mathematical background for understanding and sufficient discussion of applications for effective use. This includes not only theory but also the empirical evaluations of the importance of mathematical distinctions for applied scientific analysis.

Exploratory Analysis of the Factors Affecting Consumer Choice in E-Commerce: Conjoint Analysis

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Elena Mazurova

2017-05-01

Full Text Available According to previous studies of online consumer behaviour, three factors are the most influential on purchasing behavior - brand, colour and position of the product on the screen. However, a simultaneous influence of these three factors on the consumer decision making process has not been investigated previously. In this particular work we aim to execute a comprehensive study of the influence of these three factors. In order to answer our main research questions, we conducted an experiment with 96 different combinations of the three attributes, and using statistical analysis, such as conjoint analysis, t-test analysis and Kendall analysis we identified that the most influential factor to the online consumer decision making process is brand, the second most important attribute is the colour, which was estimated half as important as brand, and the least important attribute is the position on the screen. Additionally, we identified the main differences regarding consumers stated and revealed preferences regarding these three attributes.

Analysis of the Risk Factors for Aerobic Vaginitis: A Case-Control Study.

Science.gov (United States)

Geng, Nv; Wu, Wenjuan; Fan, Aiping; Han, Cha; Wang, Chen; Wang, Yingmei; Xue, Fengxia

2015-06-09

Aerobic vaginitis (AV) is a newly defined clinical entity which may interfere with women's reproductive health and have negative effects on pregnancy. This study was to identify the risk factors for AV. Participants in this case-control study included healthy women and women with AV. All participants completed a standardized questionnaire covering sociodemographic factors, sexual behaviors, personal hygiene habits and health behaviors. Uni- and multivariate logistic regression analyses were used for statistical evaluation. A total of 290 women of reproductive age were enrolled. In the multivariate analysis, unmarried status (odds ratio [OR] 2.606, 95% confidence interval [CI] 1.257-5.402), use of an intrauterine device (OR 4.989, 95% CI 1.922-12.952), long-term use of antibiotics (OR 11.176, 95% CI 1.363-91.666) and frequent vaginal douching (OR 4.689, 95% CI 1.363-16.135) were independent risk factors for AV. On the contrary, consistent condom use (OR 0.546, 95% CI 0.301-0.991) and college-level education or above (OR 0.255, 95% CI 0.131-0.497) were independent protective factors. Measures that may be considered to prevent AV include enhancing education to improve women's knowledge related to reproductive health, especially unmarried women, encouraging them to consistently use condoms as a contraceptive method, to avoid long-term use of antibiotics and to stop frequent vaginal douching. © 2015 S. Karger AG, Basel.

Assessment of children with suspected auditory processing disorder: a factor analysis study.

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Ahmmed, Ansar U; Ahmmed, Afsara A; Bath, Julie R; Ferguson, Melanie A; Plack, Christopher J; Moore, David R

2014-01-01

To identify the factors that may underlie the deficits in children with listening difficulties, despite normal pure-tone audiograms. These children may have auditory processing disorder (APD), but there is no universally agreed consensus as to what constitutes APD. The authors therefore refer to these children as children with suspected APD (susAPD) and aim to clarify the role of attention, cognition, memory, sensorimotor processing speed, speech, and nonspeech auditory processing in susAPD. It was expected that a factor analysis would show how nonauditory and supramodal factors relate to auditory behavioral measures in such children with susAPD. This would facilitate greater understanding of the nature of listening difficulties, thus further helping with characterizing APD and designing multimodal test batteries to diagnose APD. Factor analysis of outcomes from 110 children (68 male, 42 female; aged 6 to 11 years) with susAPD on a widely used clinical test battery (SCAN-C) and a research test battery (MRC Institute of Hearing Research Multi-center Auditory Processing "IMAP"), that have age-based normative data. The IMAP included backward masking, simultaneous masking, frequency discrimination, nonverbal intelligence, working memory, reading, alerting attention and motor reaction times to auditory and visual stimuli. SCAN-C included monaural low-redundancy speech (auditory closure and speech in noise) and dichotic listening tests (competing words and competing sentences) that assess divided auditory attention and hence executive attention. Three factors were extracted: "general auditory processing," "working memory and executive attention," and "processing speed and alerting attention." Frequency discrimination, backward masking, simultaneous masking, and monaural low-redundancy speech tests represented the "general auditory processing" factor. Dichotic listening and the IMAP cognitive tests (apart from nonverbal intelligence) were represented in the "working

Exploratory Bi-factor Analysis: The Oblique Case

OpenAIRE

Jennrich, Robert L.; Bentler, Peter M.

2011-01-01

Bi-factor analysis is a form of confirmatory factor analysis originally introduced by Holzinger and Swineford (1937). The bi-factor model has a general factor, a number of group factors, and an explicit bi-factor structure. Jennrich and Bentler (2011) introduced an exploratory form of bi-factor analysis that does not require one to provide an explicit bi-factor structure a priori. They use exploratory factor analysis and a bi-factor rotation criterion designed to produce a rotated loading mat...

Factor analysis improves the selection of prescribing indicators

DEFF Research Database (Denmark)

Rasmussen, Hanne Marie Skyggedal; Søndergaard, Jens; Sokolowski, Ineta

2006-01-01

OBJECTIVE: To test a method for improving the selection of indicators of general practitioners' prescribing. METHODS: We conducted a prescription database study including all 180 general practices in the County of Funen, Denmark, approximately 472,000 inhabitants. Principal factor analysis was us...... appropriate and inappropriate prescribing, as revealed by the correlation of the indicators in the first factor. CONCLUSION: Correlation and factor analysis is a feasible method that assists the selection of indicators and gives better insight into prescribing patterns....

Factor analysis of multivariate data

Digital Repository Service at National Institute of Oceanography (India)

Fernandes, A.A.; Mahadevan, R.

A brief introduction to factor analysis is presented. A FORTRAN program, which can perform the Q-mode and R-mode factor analysis and the singular value decomposition of a given data matrix is presented in Appendix B. This computer program, uses...

Factor Analysis for Clustered Observations.

Science.gov (United States)

Longford, N. T.; Muthen, B. O.

1992-01-01

A two-level model for factor analysis is defined, and formulas for a scoring algorithm for this model are derived. A simple noniterative method based on decomposition of total sums of the squares and cross-products is discussed and illustrated with simulated data and data from the Second International Mathematics Study. (SLD)

Interactions between toxic chemicals and natural environmental factors--a meta-analysis and case studies.

Science.gov (United States)

Laskowski, Ryszard; Bednarska, Agnieszka J; Kramarz, Paulina E; Loureiro, Susana; Scheil, Volker; Kudłek, Joanna; Holmstrup, Martin

2010-08-15

The paper addresses problems arising from effects of natural environmental factors on toxicity of pollutants to organisms. Most studies on interactions between toxicants and natural factors, including those completed in the EU project NoMiracle (Novel Methods for Integrated Risk Assessment of Cumulative Stressors in Europe) described herein, showed that effects of toxic chemicals on organisms can differ vastly depending purely on external conditions. We compiled data from 61 studies on effects of temperature, moisture and dissolved oxygen on toxicity of a range of chemicals representing pesticides, polycyclic aromatic hydrocarbons, plant protection products of bacterial origin and trace metals. In 62.3% cases significant interactions (pnatural factors and chemicals were found, reaching 100% for the effect of dissolved oxygen on toxicity of waterborne chemicals. The meta-analysis of the 61 studies showed that the null hypothesis assuming no interactions between toxic chemicals and natural environmental factors should be rejected at p=2.7 x 10(-82) (truncated product method probability). In a few cases of more complex experimental designs, also second-order interactions were found, indicating that natural factors can modify interactions among chemicals. Such data emphasize the necessity of including information on natural factors and their variation in time and across geographic regions in ecological risk assessment. This can be done only if appropriate ecotoxicological test designs are used, in which test organisms are exposed to toxicants at a range of environmental conditions. We advocate designing such tests for the second-tier ecological risk assessment procedures. Copyright 2010 Elsevier B.V. All rights reserved.

Risk factors for violence in psychosis: systematic review and meta-regression analysis of 110 studies.

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Katrina Witt

Full Text Available Previous reviews on risk and protective factors for violence in psychosis have produced contrasting findings. There is therefore a need to clarify the direction and strength of association of risk and protective factors for violent outcomes in individuals with psychosis.We conducted a systematic review and meta-analysis using 6 electronic databases (CINAHL, EBSCO, EMBASE, Global Health, PsycINFO, PUBMED and Google Scholar. Studies were identified that reported factors associated with violence in adults diagnosed, using DSM or ICD criteria, with schizophrenia and other psychoses. We considered non-English language studies and dissertations. Risk and protective factors were meta-analysed if reported in three or more primary studies. Meta-regression examined sources of heterogeneity. A novel meta-epidemiological approach was used to group similar risk factors into one of 10 domains. Sub-group analyses were then used to investigate whether risk domains differed for studies reporting severe violence (rather than aggression or hostility and studies based in inpatient (rather than outpatient settings.There were 110 eligible studies reporting on 45,533 individuals, 8,439 (18.5% of whom were violent. A total of 39,995 (87.8% were diagnosed with schizophrenia, 209 (0.4% were diagnosed with bipolar disorder, and 5,329 (11.8% were diagnosed with other psychoses. Dynamic (or modifiable risk factors included hostile behaviour, recent drug misuse, non-adherence with psychological therapies (p values<0.001, higher poor impulse control scores, recent substance misuse, recent alcohol misuse (p values<0.01, and non-adherence with medication (p value <0.05. We also examined a number of static factors, the strongest of which were criminal history factors. When restricting outcomes to severe violence, these associations did not change materially. In studies investigating inpatient violence, associations differed in strength but not direction.Certain dynamic risk

Bacteriuria and urinary tract infection after female urodynamic studies: risk factors and microbiological analysis.

Science.gov (United States)

Nóbrega, Mônica Martins; Auge, Antonio Pedro Flores; de Toledo, Luis Gustavo Morato; da Silva Carramão, Sílvia; Frade, Armando Brites; Salles, Mauro José Costa

2015-10-01

This study was conducted to determine risk factors for infectious complications after urodynamic study (UDS) in women, which can assist clinicians in identifying high-risk subjects who would benefit from antibiotic prophylaxis before UDS. In this prospective cohort study, we studied 232 women who underwent UDS at Santa Casa de São Paulo School of Medical Sciences between June 2013 and June 2014. Women ranging in age from 26 to 84 years who had urinary incontinence, pelvic organ prolapse, or voiding dysfunction were required to collect urine samples at 7 days before, on the day of, and 3-5 days after UDS. Urine cultures with >100,000 CFU/mL were considered positive. Risk factors associated with bacteriuria and urinary tract infection (UTI) after UDS were evaluated using multivariate analysis with multiple logistic regression. Two hundred thirty-two out of 257 women were subjected to further analysis. The incidence of bacteriuria, transient bacteriuria, and UTI after UDS was 11.6%, 7.3%, and 4.3%, respectively. On multivariate analysis, hypothyroidism (P = .04), body mass index (BMI) >30 (P = .025), and advanced pelvic organ prolapse (P = .021) were associated with a significantly increased risk of bacteriuria; however, only BMI >30 (P = .02) was associated with an increased risk for UTI. The rate of infectious complications after UDS was low, and advanced pelvic organ prolapse and hypothyroidism increased the risk for bacteriuria. However, only BMI >30 was associated with bacteriuria and UTI after UDS. Copyright © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

A Factor Analysis of the BSRI and the PAQ.

Science.gov (United States)

Edwards, Teresa A.; And Others

Factor analysis of the Bem Sex Role Inventory (BSRI) and the Personality Attributes Questionnaire (PAQ) was undertaken to study the independence of the masculine and feminine scales within each instrument. Both instruments were administered to undergraduate education majors. Analysis of primary first and second order factors of the BSRI indicated…

Transforming Rubrics Using Factor Analysis

Science.gov (United States)

Baryla, Ed; Shelley, Gary; Trainor, William

2012-01-01

Student learning and program effectiveness is often assessed using rubrics. While much time and effort may go into their creation, it is equally important to assess how effective and efficient the rubrics actually are in terms of measuring competencies over a number of criteria. This study demonstrates the use of common factor analysis to identify…

Prevalence and associated factors for early interruption of exclusive breastfeeding: meta-analysis on Brazilian epidemiological studies

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Marcos Pereira-Santos

Full Text Available Abstract Objectives: to summarize Brazilian studies that analyzed the risk factors for Exclusive Breastfeeding (EBF interruption before the child's six months of life. Methods: systematic review and meta-analysis indexed articles from Bireme, Scielo and Pubmed databases published in the period of January 2000 to December 2015. Results: 22 articles were included in the meta-analysis. The factors related to newborns were observed, such as birth weight (OR= 1.17; CI 95%: 1.05-1.29, female gender (OR= 1,09; CI 95%: 1.04-1.13 and the use of pacifier (OR= 2.29; CI 95%: 1.68-2.91 were the main factors responsible for the increase in the occurrence of EBF interruption. The factors were related to the mother, maternal age below twenty years old (OR= 1.22; CI 95%: 1.12-1.33 low schooling level (OR=1.28; CI 95%: 1.11-1.45, primiparity (OR= 1.17; CI 95%: 1.02-1.32 maternal employment during the postpartum period (OR= 1.26; CI 95%: 1.11-1.41, and low family income (OR= 1.22; CI 95%: 1.08-1.37 contributed significantly to the EBF interruption . Conclusions: the meta-analysis of Brazilian epidemiological studies demonstrated evidences to conclude that below the age of twenty, low schooling, primiparity, maternal employment in the postpartum period and low family income are associated to the interruption of exclusive breastfeeding until 6 months of age. Children with low birth weight, female gender and used a pacifier had greater vulnerability to not be exclusively breastfed. In conclusion, most of these factors can be modified through appropriate public policies throughout the adequate prenatal period to promote exclusive breastfeeding.

Ranking insurance firms using AHP and Factor Analysis

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Mohammad Khodaei Valahzaghard

2013-03-01

Full Text Available Insurance industry includes a significant part of economy and it is important to learn more about the capabilities of different firms, which are active in this industry. In this paper, we present an empirical study to rank the insurance firms using analytical hierarchy process as well as factor analysis. The study considers four criteria including capital adequacy, quality of earning, quality of cash flow and quality of firms’ assets. The results of the implementation of factor analysis (FA have been verified using Kaiser-Meyer-Olkin (KMO=0.573 and Bartlett's Chi-Square (443.267 P-value=0.000 tests. According to the results FA, the first important factor, capital adequacy, represents 21.557% of total variance, the second factor, quality of income, represents 20.958% of total variance. In addition, the third factor, quality of cash flow, represents 19.417% of total variance and the last factor, quality of assets, represents 18.641% of total variance. The study has also used analytical hierarchy process (AHP to rank insurance firms. The results of our survey indicate that capital adequacy (0.559 is accounted as the most important factor followed by quality of income (0.235, quality of cash flow (0.144 and quality of assets (0.061. The results of AHP are consistent with the results of FA, which somewhat validates the overall study.

Applications of factor analysis to electron and ion beam surface techniques

International Nuclear Information System (INIS)

Solomon, J.S.

1987-01-01

Factor analysis, a mathematical technique for extracting chemical information from matrices of data, is used to enhance Auger electron spectroscopy (AES), core level electron energy loss spectroscopy (EELS), ion scattering spectroscopy (ISS), and secondary ion mass spectroscopy (SIMS) in studies of interfaces, thin films, and surfaces. Several examples of factor analysis enhancement of chemical bonding variations in thin films and at interfaces studied with AES and SIMS are presented. Factor analysis is also shown to be of great benefit in quantifying electron and ion beam doses required to induce surface damage. Finally, examples are presented of the use of factor analysis to reconstruct elemental profiles when peaks of interest overlap each other during the course of depth profile analysis. (author)

Meta-Analysis of Human Factors Engineering Studies Comparing Individual Differences, Practice Effects and Equipment Design Variations.

Science.gov (United States)

1985-02-21

Approvoid foT public 90Ieleol, 2* . tJni7nited " - . - o . - ’--. * . -... . 1 UNCLASSIFIED S, E CURITY CLASSIFICATION OF THIS PAGE-" REPORT DOCUMENTATION...ACCESSION NO. 11. TITLE (Include Security Classification) . Veta -Analysis of Human Factors Engineering Studies Comparing Individual Differences, Practice...Background C Opportunity D Significance E History III. PHASE I FINAL REPORT A Literature Review B Formal Analysis C Results D Implications for Phase II IV

Risk factors for re-bleeding of aneurysmal subarachnoid hemorrhage: meta-analysis of observational studies.

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Alfotih, Gobran Taha Ahmed; Li, FangCheng; Xu, XinKe; Zhang, ShangYi

2014-01-01

The mortality of re-bleeding following aneurysmal subarachnoid hemorrhage is high, and surviving patients often have poor clinical condition and worse outcome than patients with a single bleed. In this study, we performed an updated systematic review and meta-analysis to determine the most common risk factors for re-bleeding in this patient population, with the goal of providing neurologists, neurosurgeons, neuro-interventionalists with a simple and fast method to evaluate the re-bleeding risk for aneurysmal subarachnoid hemorrhage. We conducted a thorough meta-analysis of the risk factors associated with re-bleeding or re-rupture of intracranial aneurysms in cases published between 2000 and 2013. Pooled mean difference was calculated for the continuous variables (age), and pooled odds ratio (OR) was calculated for categorical factors. If heterogeneity was significant (pbleeding, resulting in a weighted average rate of re-bleeding of 11.3% with 95% confidence interval [CI]: 10.1-12.6. In this population, sex (OR 1.46; 95% CI: 1.11-1.92), high systolic blood pressure [SBP] (OR 2.52; 95% CI: 1.40-4.53), aneurysm size (OR 3.00; 95% CI: 2.06-4.37), clinical condition (Hunt & Hess) (OR 4.94; 95% CI: 2.29,10.68), and Fisher grade (OR 2.29; 95% CI: 1.45, 3.61) were statistically significant risk factors for re-bleeding. Sex, high SBP, high Fisher grade, aneurysm size larger than 10mm, and poor clinical condition were independent risk factors for aneurysmal re-bleeding. The importance of early aneurysm intervention and careful consideration of patient risk factors should be emphasized to eliminate the risk of re-bleeding and poor outcome. Copyright © 2014 Polish Neurological Society. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Situational Factors in Focus Group Studies: A Systematic Review

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Arne Orvik MPolSc

2013-02-01

Full Text Available The aim of this study was to see how contextual factors are expressed, used, and analyzed in data collected in focus group discussions (FGDs. The study includes an assessment of how the methodological reporting of contextual factors might influence and improve the trustworthiness of articles. Articles reporting workplace health, stress, and coping among health professionals were identified in a systematic review and used in the analysis. By using Vicsek's framework of situational factors for analysis of focus group results as a starting point, we found that contextual factors were most frequently described in the method sections and less frequently in the results and discussion sections. Vicsek's framework for the analysis of focus group results covers six contextual and methodological dimensions: interactional factors, personal characteristics of the participants, the moderator, the environment, time factors, and the content of FGDs. We found that the framework does not include a consideration of psychological safety, ethical issues, or organizational information. To deepen the analysis of focus group results, we argue that contextual factors should be analyzed as methodological dimensions and be considered as a sensitizing concept. Credibility, confirmability, dependability, and transferability can be strengthened by using, reporting, and discussing contextual factors in detail. The study contributes to elucidating how reporting of contextual data may enrich the analysis of focus group results and strengthen the trustworthiness. Future research should focus on clear reporting of contextual factors as well as further develop Vicsek's model to enhance reporting accuracy and transferability.

Depression as a risk factor for dementia and mild cognitive impairment: a meta-analysis of longitudinal studies.

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Gao, Yuan; Huang, Changquan; Zhao, Kexiang; Ma, Louyan; Qiu, Xuan; Zhang, Lei; Xiu, Yun; Chen, Lin; Lu, Wei; Huang, Chunxia; Tang, Yong; Xiao, Qian

2013-05-01

This study examined whether depression was a risk factor for onset of dementia including Alzheimer's disease (AD), vascular dementia (VD) and any dementia, and mild cognitive impairment (MCI) by using a quantitative meta-analysis of longitudinal studies. EMBASE and MEDLINE were searched for articles published up to February 2011. All studies that examined the relationship between depression and the onset of dementia or MCI were included. Pooled relative risk was calculated using fixed-effects models. Twelve studies met our inclusion criteria for this meta-analysis. All subjects were without dementia or MCI at baseline. Four, two, five, and four studies compared the incidence of AD, VD, any dementia, and MCI between subjects with or without depression, respectively. After pooling all the studies, subjects with depression had higher incidence of AD (relative risk (RR):1.66, 95% confidence interval (CI): 1.29-2.14), VD (RR: 1.89, 95% CI: 1.19-3.01), any dementia (RR: 1.55, 95% CI: 1.31-2.83), and MCI (RR: 1.97, 95% CI: 1.53-2.54) than those without depression. The quantitative meta-analysis showed that depression was a major risk factor for incidence of dementia (including AD, VD, and any dementia) and MCI. Copyright © 2012 John Wiley & Sons, Ltd.

Using exploratory factor analysis in personality research: Best-practice recommendations

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Sumaya Laher

2010-11-01

Research purpose: This article presents more objective methods to determine the number of factors, most notably parallel analysis and Velicer’s minimum average partial (MAP. The benefits of rotation are also discussed. The article argues for more consistent use of Procrustes rotation and congruence coefficients in factor analytic studies. Motivation for the study: Exploratory factor analysis is often criticised for not being rigorous and objective enough in terms of the methods used to determine the number of factors, the rotations to be used and ultimately the validity of the factor structure. Research design, approach and method: The article adopts a theoretical stance to discuss the best-practice recommendations for factor analytic research in the field of psychology. Following this, an example located within personality assessment and using the NEO-PI-R specifically is presented. A total of 425 students at the University of the Witwatersrand completed the NEO-PI-R. These responses were subjected to a principal components analysis using varimax rotation. The rotated solution was subjected to a Procrustes rotation with Costa and McCrae’s (1992 matrix as the target matrix. Congruence coefficients were also computed. Main findings: The example indicates the use of the methods recommended in the article and demonstrates an objective way of determining the number of factors. It also provides an example of Procrustes rotation with coefficients of agreement as an indication of how factor analytic results may be presented more rigorously in local research. Practical/managerial implications: It is hoped that the recommendations in this article will have best-practice implications for both researchers and practitioners in the field who employ factor analysis regularly. Contribution/value-add: This article will prove useful to all researchers employing factor analysis and has the potential to set the trend for better use of factor analysis in the South African context.

A retrospective content analysis of studies on factors constraining the implementation of health sector reform in Ghana.

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Sakyi, E Kojo

2008-01-01

Ghana has undertaken many public service management reforms in the past two decades. But the implementation of the reforms has been constrained by many factors. This paper undertakes a retrospective study of research works on the challenges to the implementation of reforms in the public health sector. It points out that most of the studies identified: (1) centralised, weak and fragmented management system; (2) poor implementation strategy; (3) lack of motivation; (4) weak institutional framework; (5) lack of financial and human resources and (6) staff attitude and behaviour as the major causes of ineffective reform implementation. The analysis further revealed that quite a number of crucial factors obstructing reform implementation which are particularly internal to the health system have either not been thoroughly studied or overlooked. The analysis identified lack of leadership; weak communication and consultation; lack of stakeholder participation, corruption and unethical professional behaviour as some of the missing variables in the literature. The study, therefore, indicated that there are gaps in the literature that needed to be filled through rigorous reform evaluation based on empirical research particularly at district, sub-district and community levels. It further suggested that future research should be concerned with the effects of both systems and structures and behavioural factors on reform implementation.

Exploratory Bi-Factor Analysis: The Oblique Case

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Jennrich, Robert I.; Bentler, Peter M.

2012-01-01

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

Risk factors for Clonorchis sinensis infection transmission in humans in northern Vietnam: A descriptive and social network analysis study.

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Vinh, Hoang Quang; Phimpraphai, Waraphon; Tangkawattana, Sirikachorn; Smith, John F; Kaewkes, Sasithorn; Dung, Do Trung; Duong, Tran Thanh; Sripa, Banchob

2017-04-01

Clonorchis sinensis is major fish-borne trematode, endemic in North Vietnam. Risk factors described so far include individual eating behaviors and environmental factors. Here, additional to conventional risk factors, we report on socially influenced liver fluke transmission in endemic communities. A cross-sectional study on risk factors and fish sharing networks was conducted in 4 villages of Gia Thinh Commune, Ninh Binh Province. A total of 510 residents in 272 households were recruited for risk factor analysis while 220 households, 28 fishermen and 10 fish-sellers were enrolled for social network study. Fecal examination for C. sinensis eggs was performed. Average C. sinensis infection rate at Gia Thinh commune was 16.5% (range 2% to 34.4%). Higher infection rates were significantly associated with males, lower educational levels, eating raw fish, and location of the villages. Social network analysis (SNA) showed a strong positive correlation between ego network size (number of households in fish sharing network) and quantity of raw fish consumed (r=0.603, Psinensis infection transmission in northern Vietnam. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Using confirmatory factor analysis to explore associated factors of intimate partner violence in a sample of Chinese rural women: a cross-sectional study.

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Hou, Fengsu; Cerulli, Catherine; Wittink, Marsha N; Caine, Eric D; Qiu, Peiyuan

2018-02-02

To estimate the prevalence of intimate partner violence (IPV) among a sample of rural Chinese women and to explore associated factors. Cross-sectional study. Rural areas of Guangyuan City, Sichuan, China. We recruited 1501 women, aged 16 years and older, who had been living locally for at least 2 years and reported being married or in a relationship during the past 12 months. They were among a sample of 1898 potential participants from our larger parent study on the prevalence of depressive-distress symptoms. Participants completed demographic and social economic measures, the Short Form of the Revised Conflict Tactics Scale and the Duke Social Support Index. We applied χ 2 test, analysis of variance and confirmatory factor analysis for analysis. The overall prevalence of IPV in the past 12 months was 29.05%; the prevalence of physical, psychological and sexual violence was 7.66%, 26.58% and 3.20%, respectively. The overall prevalence was highest among women aged 16-29 years, and was more common among those without a high school diploma and who saw their family's financial status as very poor or stagnant. Women who were not victims of IPV had higher levels of social support. Confirmatory factor analysis showed that the total effects of social support on physical, psychological and sexual violence were -0.12, -0.35 and -0.12, respectively. The indirect effects of objective economic status on physical, psychological and sexual violence were -0.047, -0.014 and -0.047, respectively, but the total effect was not significant. The indirect effect of education on psychological violence was -0.056. IPV is common in rural Guangyuan. Our data are comparable with the findings from north-west of China. Social support is an important protective factor. Future work is needed to develop, test and later disseminate potential IPV interventions, with a focus on building actual and perceived supportive social networks. © Article author(s) (or their employer(s) unless otherwise

Sensitivity Analysis of b-factor in Microwave Emission Model for Soil Moisture Retrieval: A Case Study for SMAP Mission

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Dugwon Seo

2010-05-01

Full Text Available Sensitivity analysis is critically needed to better understand the microwave emission model for soil moisture retrieval using passive microwave remote sensing data. The vegetation b-factor along with vegetation water content and surface characteristics has significant impact in model prediction. This study evaluates the sensitivity of the b-factor, which is function of vegetation type. The analysis is carried out using Passive and Active L and S-band airborne sensor (PALS and measured field soil moisture from Southern Great Plains experiment (SGP99. The results show that the relative sensitivity of the b-factor is 86% in wet soil condition and 88% in high vegetated condition compared to the sensitivity of the soil moisture. Apparently, the b-factor is found to be more sensitive than the vegetation water content, surface roughness and surface temperature; therefore, the effect of the b-factor is fairly large to the microwave emission in certain conditions. Understanding the dependence of the b-factor on the soil and vegetation is important in studying the soil moisture retrieval algorithm, which can lead to potential improvements in model development for the Soil Moisture Active-Passive (SMAP mission.

Item-level factor analysis of the Self-Efficacy Scale.

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Bunketorp Käll, Lina

2014-03-01

This study explores the internal structure of the Self-Efficacy Scale (SES) using item response analysis. The SES was previously translated into Swedish and modified to encompass all types of pain, not exclusively back pain. Data on perceived self-efficacy in 47 patients with subacute whiplash-associated disorders were derived from a previously conducted randomized-controlled trial. The item-level factor analysis was carried out using a six-step procedure. To further study the item inter-relationships and to determine the underlying structure empirically, the 20 items of the SES were also subjected to principal component analysis with varimax rotation. The analyses showed two underlying factors, named 'social activities' and 'physical activities', with seven items loading on each factor. The remaining six items of the SES appeared to measure somewhat different constructs and need to be analysed further.

Factor analysis for exercise stress radionuclide ventriculography

International Nuclear Information System (INIS)

Hirota, Kazuyoshi; Yasuda, Mitsutaka; Oku, Hisao; Ikuno, Yoshiyasu; Takeuchi, Kazuhide; Takeda, Tadanao; Ochi, Hironobu

1987-01-01

Using factor analysis, a new image processing in exercise stress radionuclide ventriculography, changes in factors associated with exercise were evaluated in 14 patients with angina pectoris or old myocardial infarction. The patients were imaged in the left anterior oblique projection, and three factor images were presented on a color coded scale. Abnormal factors (AF) were observed in 6 patients before exercise, 13 during exercise, and 4 after exercise. In 7 patients, the occurrence of AF was associated with exercise. Five of them became free from AF after exercise. Three patients showing AF before exercise had aggravation of AF during exercise. Overall, the occurrence or aggravation of AF was associated with exercise in ten (71 %) of the patients. The other three patients, however, had disappearance of AF during exercise. In the last patient, none of the AF was observed throughout the study. In view of a high incidence of AF associated with exercise, the factor analysis may have the potential in evaluating cardiac reverse from the viewpoint of left ventricular wall motion abnormality. (Namekawa, K.)

Logistic regression analysis of risk factors for postoperative recurrence of spinal tumors and analysis of prognostic factors.

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Zhang, Shanyong; Yang, Lili; Peng, Chuangang; Wu, Minfei

2018-02-01

The aim of the present study was to investigate the risk factors for postoperative recurrence of spinal tumors by logistic regression analysis and analysis of prognostic factors. In total, 77 male and 48 female patients with spinal tumor were selected in our hospital from January, 2010 to December, 2015 and divided into the benign (n=76) and malignant groups (n=49). All the patients underwent microsurgical resection of spinal tumors and were reviewed regularly 3 months after operation. The McCormick grading system was used to evaluate the postoperative spinal cord function. Data were subjected to statistical analysis. Of the 125 cases, 63 cases showed improvement after operation, 50 cases were stable, and deterioration was found in 12 cases. The improvement rate of patients with cervical spine tumor, which reached 56.3%, was the highest. Fifty-two cases of sensory disturbance, 34 cases of pain, 30 cases of inability to exercise, 26 cases of ataxia, and 12 cases of sphincter disorders were found after operation. Seventy-two cases (57.6%) underwent total resection, 18 cases (14.4%) received subtotal resection, 23 cases (18.4%) received partial resection, and 12 cases (9.6%) were only treated with biopsy/decompression. Postoperative recurrence was found in 57 cases (45.6%). The mean recurrence time of patients in the malignant group was 27.49±6.09 months, and the mean recurrence time of patients in the benign group was 40.62±4.34. The results were significantly different (Pregression analysis of total resection-related factors showed that total resection should be the preferred treatment for patients with benign tumors, thoracic and lumbosacral tumors, and lower McCormick grade, as well as patients without syringomyelia and intramedullary tumors. Logistic regression analysis of recurrence-related factors revealed that the recurrence rate was relatively higher in patients with malignant, cervical, thoracic and lumbosacral, intramedullary tumors, and higher Mc

Factor analysis of symptom profile in early onset and late onset OCD.

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Grover, Sandeep; Sarkar, Siddharth; Gupta, Gourav; Kate, Natasha; Ghosh, Abhishek; Chakrabarti, Subho; Avasthi, Ajit

2018-04-01

This study aimed to assess the factor structure of early and late onset OCD. Additionally, cluster analysis was conducted in the same sample to assess the applicability of the factors. 345 participants were assessed with Yale Brown Obsessive Compulsive Scale symptom checklist. Patients were classified as early onset (onset of symptoms at age ≤ 18 years) and late onset (onset at age > 18 years) OCD depending upon the age of onset of the symptoms. Factor analysis and cluster analysis of early-onset and late-onset OCD was conducted. The study sample comprised of 91 early onset and 245 late onset OCD subjects. Males were more common in the early onset group. Differences in the frequency of phenomenology related to contamination related, checking, repeating, counting and ordering/arranging compulsions were present across the early and late onset groups. Factor analysis of YBOCS revealed a 3 factor solution for both the groups, which largely concurred with each other. These factors were named as hoarding and symmetry (factor-1), contamination (factor-2) and aggressive, sexual and religious factor (factor-3). To conclude this study shows that factor structure of symptoms of OCD seems to be similar between early-onset and late-onset OCD. Copyright © 2017 Elsevier B.V. All rights reserved.

Deterministic factor analysis: methods of integro-differentiation of non-integral order

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Valentina V. Tarasova

2016-12-01

Full Text Available Objective to summarize the methods of deterministic factor economic analysis namely the differential calculus and the integral method. nbsp Methods mathematical methods for integrodifferentiation of nonintegral order the theory of derivatives and integrals of fractional nonintegral order. Results the basic concepts are formulated and the new methods are developed that take into account the memory and nonlocality effects in the quantitative description of the influence of individual factors on the change in the effective economic indicator. Two methods are proposed for integrodifferentiation of nonintegral order for the deterministic factor analysis of economic processes with memory and nonlocality. It is shown that the method of integrodifferentiation of nonintegral order can give more accurate results compared with standard methods method of differentiation using the first order derivatives and the integral method using the integration of the first order for a wide class of functions describing effective economic indicators. Scientific novelty the new methods of deterministic factor analysis are proposed the method of differential calculus of nonintegral order and the integral method of nonintegral order. Practical significance the basic concepts and formulas of the article can be used in scientific and analytical activity for factor analysis of economic processes. The proposed method for integrodifferentiation of nonintegral order extends the capabilities of the determined factorial economic analysis. The new quantitative method of deterministic factor analysis may become the beginning of quantitative studies of economic agents behavior with memory hereditarity and spatial nonlocality. The proposed methods of deterministic factor analysis can be used in the study of economic processes which follow the exponential law in which the indicators endogenous variables are power functions of the factors exogenous variables including the processes

A human factor analysis of a radiotherapy accident

International Nuclear Information System (INIS)

Thellier, S.

2009-01-01

Since September 2005, I.R.S.N. studies activities of radiotherapy treatment from the angle of the human and organizational factors to improve the reliability of treatment in radiotherapy. Experienced in nuclear industry incidents analysis, I.R.S.N. analysed and diffused in March 2008, for the first time in France, the detailed study of a radiotherapy accident from the angle of the human and organizational factors. The method used for analysis is based on interviews and documents kept by the hospital. This analysis aimed at identifying the causes of the difference recorded between the dose prescribed by the radiotherapist and the dose effectively received by the patient. Neither verbal nor written communication (intra-service meetings and protocols of treatment) allowed information to be transmitted correctly in order to permit radiographers to adjust the irradiation zones correctly. This analysis highlighted the fact that during the preparation and the carrying out of the treatment, various factors led planned controls to not be performed. Finally, this analysis highlighted the fact that unsolved areas persist in the report over this accident. This is due to a lack of traceability of a certain number of key actions. The article concluded that there must be improvement in three areas: cooperation between the practitioners, control of the actions and traceability of the actions. (author)

Risk factors for radiation-induced hypothyroidism: A Literature-Based Meta-Analysis

DEFF Research Database (Denmark)

Vogelius, Ivan R; Bentzen, Søren; Maraldo, Maja V

2011-01-01

BACKGROUND: A systematic overview and meta-analysis of studies reporting data on hypothyroidism (HT) after radiation therapy was conducted to identify risk factors for development of HT. METHODS: Published studies were identified from the PubMed and Embase databases and by hand-searching published...... reviews. Studies allowing the extraction of odds ratios (OR) for HT in 1 or more of several candidate clinical risk groups were included. A meta-analysis of the OR for development of HT with or without each of the candidate risk factors was performed. Furthermore, studies allowing the extraction......% risk of HT at a dose of 45 Gy but with considerable variation in the dose response between studies. Chemotherapy and age were not associated with risk of HT in this analysis. CONCLUSIONS: Several clinical risk factors for HT were identified. The risk of HT increases with increasing radiation dose...

Effective factors in providing holistic care: a qualitative study.

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Zamanzadeh, Vahid; Jasemi, Madineh; Valizadeh, Leila; Keogh, Brian; Taleghani, Fariba

2015-01-01

Holistic care is a comprehensive model of caring. Previous studies have shown that most nurses do not apply this method. Examining the effective factors in nurses' provision of holistic care can help with enhancing it. Studying these factors from the point of view of nurses will generate real and meaningful concepts and can help to extend this method of caring. A qualitative study was used to identify effective factors in holistic care provision. Data gathered by interviewing 14 nurses from university hospitals in Iran were analyzed with a conventional qualitative content analysis method and by using MAXQDA (professional software for qualitative and mixed methods data analysis) software. Analysis of data revealed three main themes as effective factors in providing holistic care: The structure of educational system, professional environment, and personality traits. Establishing appropriate educational, management systems, and promoting religiousness and encouragement will induce nurses to provide holistic care and ultimately improve the quality of their caring.

Effective factors in providing holistic care: A qualitative study

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Vahid Zamanzadeh

2015-01-01

Full Text Available Background: Holistic care is a comprehensive model of caring. Previous studies have shown that most nurses do not apply this method. Examining the effective factors in nurses′ provision of holistic care can help with enhancing it. Studying these factors from the point of view of nurses will generate real and meaningful concepts and can help to extend this method of caring. Materials and Methods: A qualitative study was used to identify effective factors in holistic care provision. Data gathered by interviewing 14 nurses from university hospitals in Iran were analyzed with a conventional qualitative content analysis method and by using MAXQDA (professional software for qualitative and mixed methods data analysis software. Results: Analysis of data revealed three main themes as effective factors in providing holistic care: The structure of educational system, professional environment, and personality traits. Conclusion: Establishing appropriate educational, management systems, and promoting religiousness and encouragement will induce nurses to provide holistic care and ultimately improve the quality of their caring.

Capital Cost Optimization for Prefabrication: A Factor Analysis Evaluation Model

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Hong Xue

2018-01-01

Full Text Available High capital cost is a significant hindrance to the promotion of prefabrication. In order to optimize cost management and reduce capital cost, this study aims to explore the latent factors and factor analysis evaluation model. Semi-structured interviews were conducted to explore potential variables and then questionnaire survey was employed to collect professionals’ views on their effects. After data collection, exploratory factor analysis was adopted to explore the latent factors. Seven latent factors were identified, including “Management Index”, “Construction Dissipation Index”, “Productivity Index”, “Design Efficiency Index”, “Transport Dissipation Index”, “Material increment Index” and “Depreciation amortization Index”. With these latent factors, a factor analysis evaluation model (FAEM, divided into factor analysis model (FAM and comprehensive evaluation model (CEM, was established. The FAM was used to explore the effect of observed variables on the high capital cost of prefabrication, while the CEM was used to evaluate comprehensive cost management level on prefabrication projects. Case studies were conducted to verify the models. The results revealed that collaborative management had a positive effect on capital cost of prefabrication. Material increment costs and labor costs had significant impacts on production cost. This study demonstrated the potential of on-site management and standardization design to reduce capital cost. Hence, collaborative management is necessary for cost management of prefabrication. Innovation and detailed design were needed to improve cost performance. The new form of precast component factories can be explored to reduce transportation cost. Meanwhile, targeted strategies can be adopted for different prefabrication projects. The findings optimized the capital cost and improved the cost performance through providing an evaluation and optimization model, which helps managers to

Confirmatory Factor Analysis of IT-based Competency Questionnaire in Information Science & Knowledge Studies, Based on Job Market Analysis

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Rahim Shahbazi

2016-03-01

Full Text Available The main purpose of the present research is to evaluate the validity of an IT-based competency questionnaire in Information Science & Knowledge Studies. The Survey method has been used in the present research. A data collection tool has been a researcher-made questionnaire. Statistic samples, which are 315 people, have been chosen purposefully from among Iranian faculty members, Ph.D. students, and information center employees. The findings showed that by eliminating 17 items from the whole questionnaire and Confirmatory Factor Analysis of the rest and rotating findings using the Varimax method, 8 Factors were revealed. The resulting components and also the items which had a high load factor with these components were considerably consistent with the classifications in the questionnaire and partly consistent with the findings of other researchers. 76 competency indicators (knowledge, skills, and attitudes were validated and grouped under 8 main categories: 1. “Computer Basics” 2. “Database Operating, Collection Development of Digital Resources, & Digital Library Management” 3. “Basics of Computer Networking” 4. “Basics of Programming & Database Designing” 5. “Web Designing & Web Content Analysis” 6. “Library Software & Computerized Organizing” 7. Archive of Digital Resources and 8. Attitudes.

ANALYSIS OF FACTORS WHICH AFFECTING THE ECONOMIC GROWTH

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Suparna Wijaya

2017-03-01

Full Text Available High economic growth and sustainable process are main conditions for sustainability of economic country development. They are also become measures of the success of the country's economy. Factors which tested in this study are economic and non-economic factors which impacting economic development. This study has a goal to explain the factors that influence on macroeconomic Indonesia. It used linear regression modeling approach. The analysis result showed that Tax Amnesty, Exchange Rate, Inflation, and interest rate, they jointly can bring effect which amounted to 77.6% on economic growth whereas the remaining 22.4% is the influenced by other variables which not observed in this study. Keywords: tax amnesty, exchange rates, inflation, SBI and economic growth

The Infinitesimal Jackknife with Exploratory Factor Analysis

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Zhang, Guangjian; Preacher, Kristopher J.; Jennrich, Robert I.

2012-01-01

The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both…

Necessary steps in factor analysis : Enhancing validation studies of educational instruments. The PHEEM applied to clerks as an example

NARCIS (Netherlands)

Schonrock-Adema, Johanna; Heijne-Penninga, Marjolein; van Hell, Elisabeth A.; Cohen-Schotanus, Janke

2009-01-01

Background: The validation of educational instruments, in particular the employment of factor analysis, can be improved in many instances. Aims: To demonstrate the superiority of a sophisticated method of factor analysis, implying an integration of recommendations described in the factor analysis

Left ventricular wall motion abnormalities evaluated by factor analysis as compared with Fourier analysis

International Nuclear Information System (INIS)

Hirota, Kazuyoshi; Ikuno, Yoshiyasu; Nishikimi, Toshio

1986-01-01

Factor analysis was applied to multigated cardiac pool scintigraphy to evaluate its ability to detect left ventricular wall motion abnormalities in 35 patients with old myocardial infarction (MI), and in 12 control cases with normal left ventriculography. All cases were also evaluated by conventional Fourier analysis. In most cases with normal left ventriculography, the ventricular and atrial factors were extracted by factor analysis. In cases with MI, the third factor was obtained in the left ventricle corresponding to wall motion abnormality. Each case was scored according to the coincidence of findings of ventriculography and those of factor analysis or Fourier analysis. Scores were recorded for three items; the existence, location, and degree of asynergy. In cases of MI, the detection rate of asynergy was 94 % by factor analysis, 83 % by Fourier analysis, and the agreement in respect to location was 71 % and 66 %, respectively. Factor analysis had higher scores than Fourier analysis, but this was not significant. The interobserver error of factor analysis was less than that of Fourier analysis. Factor analysis can display locations and dynamic motion curves of asynergy, and it is regarded as a useful method for detecting and evaluating left ventricular wall motion abnormalities. (author)

Factor analysis of the contextual fine motor questionnaire in children.

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

2014-02-01

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

Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

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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.

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

Science.gov (United States)

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

2015-02-01

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

Lithuanian Population Aging Factors Analysis

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Agnė Garlauskaitė

2015-05-01

Full Text Available The aim of this article is to identify the factors that determine aging of Lithuania’s population and to assess the influence of these factors. The article shows Lithuanian population aging factors analysis, which consists of two main parts: the first describes the aging of the population and its characteristics in theoretical terms. Second part is dedicated to the assessment of trends that influence the aging population and demographic factors and also to analyse the determinants of the aging of the population of Lithuania. After analysis it is concluded in the article that the decline in the birth rate and increase in the number of emigrants compared to immigrants have the greatest impact on aging of the population, so in order to show the aging of the population, a lot of attention should be paid to management of these demographic processes.

An Evaluation on Factors Influencing Decision making for Malaysia Disaster Management: The Confirmatory Factor Analysis Approach

Science.gov (United States)

Zubir, S. N. A.; Thiruchelvam, S.; Mustapha, K. N. M.; Che Muda, Z.; Ghazali, A.; Hakimie, H.

2017-12-01

For the past few years, natural disaster has been the subject of debate in disaster management especially in flood disaster. Each year, natural disaster results in significant loss of life, destruction of homes and public infrastructure, and economic hardship. Hence, an effective and efficient flood disaster management would assure non-futile efforts for life saving. The aim of this article is to examine the relationship between approach, decision maker, influence factor, result, and ethic to decision making for flood disaster management in Malaysia. The key elements of decision making in the disaster management were studied based on the literature. Questionnaire surveys were administered among lead agencies at East Coast of Malaysia in the state of Kelantan and Pahang. A total of 307 valid responses had been obtained for further analysis. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were carried out to analyse the measurement model involved in the study. The CFA for second-order reflective and first-order reflective measurement model indicates that approach, decision maker, influence factor, result, and ethic have a significant and direct effect on decision making during disaster. The results from this study showed that decision- making during disaster is an important element for disaster management to necessitate a successful collaborative decision making. The measurement model is accepted to proceed with further analysis known as Structural Equation Modeling (SEM) and can be assessed for the future research.

Sustainable Manufacturing Practices in Malaysian Automotive Industry: Confirmatory Factor Analysis

OpenAIRE

Habidin, Nurul Fadly; Zubir, Anis Fadzlin Mohd; Fuz, Nursyazwani Mohd; Latip, Nor Azrin Md; Azman, Mohamed Nor Azhari

2015-01-01

Sustainable manufacturing practices (SMPs) have received enormous attention in current years as an effective solution to support the continuous growth and expansion of the automotive manufacturing industry. This reported study was conducted to examine confirmatory factor analysis for SMP such as manufacturing process, supply chain management, social responsibility, and environmental management based on automotive manufacturing industry. The results of confirmatory factor analysis show that fo...

A Case-Control Study and Meta-Analysis Reveal BDNF Val66Met Is a Possible Risk Factor for PTSD

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Dagmar Bruenig

2016-01-01

Full Text Available Posttraumatic stress disorder (PTSD is a debilitating condition that develops in some people after exposure to a traumatic event. Brain-derived neurotrophic factor (BDNF is highly expressed in the mammalian brain and is thought to be involved in learning and memory processes. A nonsynonymous polymorphism in the BDNF gene, rs6265 (Val66Met, has been hypothesised to be associated with PTSD. Association studies examining the Val66Met polymorphism and PTSD have been inconclusive, likely due to the variability in type of trauma exposure analysed. Vietnam veterans (n=257 screened for PTSD and controlled for trauma exposure were genotyped for BDNF Val66Met. The association was not significant so we incorporated our data into a meta-analysis to obtain greater statistical power. A comprehensive search of more than 1237 articles revealed eight additional studies suitable for meta-analysis (n=3625. A random-effects meta-analysis observed a potential protective factor of the Val/Val genotype. After removing two studies with violation of Hardy-Weinberg equilibrium, findings for the Val/Val genotype reached significance. Subgroup analyses confirmed a trend for this finding. Limitations of some studies that inform this meta-analysis include poorly screened controls and a lack of examination of population stratification. Effectively designed studies should inform this line of research in the future.

Understanding Older Adults' Perceptions of Internet Use: An Exploratory Factor Analysis

Science.gov (United States)

Zheng, Robert; Spears, Jeffrey; Luptak, Marilyn; Wilby, Frances

2015-01-01

The current study examined factors related to older adults' perceptions of Internet use. Three hundred ninety five older adults participated in the study. The factor analysis revealed four factors perceived by older adults as critical to their Internet use: social connection, self-efficacy, the need to seek financial information, and the need to…

An exploration study on factors influencing green marketing

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Mojtaba Esmaeeli

2013-05-01

Full Text Available These days, there have been tremendous efforts on offering products, which are environment friendly. Green marketing plays an important role for attracting new customer and customer retention. This paper presents an empirical investigation based on the implementation of factor analysis to locate important factors influencing green marketing planning and strategies. building market oriented business units. The study designs a questionnaire including 23 questions and the questionnaire was distributed among 200 people who were visiting organic product exhibition. Cronbach alpha was calculated as 0.845, which is well above the minimum acceptable limit and validates the results. The results of factor analysis reveal four major factors including green labeling, compatibility, product value and marketing component and size.

Clinicopathological Analysis of Factors Related to Colorectal Tumor Perforation

OpenAIRE

Medina-Arana, Vicente; Martínez-Riera, Antonio; Delgado-Plasencia, Luciano; Rodríguez-González, Diana; Bravo-Gutiérrez, Alberto; Álvarez-Argüelles, Hugo; Alarcó-Hernández, Antonio; Salido-Ruiz, Eduardo; Fernández-Peralta, Antonia M.; González-Aguilera, Juan J.

2015-01-01

Abstract Colorectal tumor perforation is a life-threatening complication of this disease. However, little is known about the anatomopathological factors or pathophysiologic mechanisms involved. Pathological and immunohistochemical analysis of factors related with tumoral neo-angiogenesis, which could influence tumor perforation are assessed in this study. A retrospective study of patients with perforated colon tumors (Group P) and T4a nonperforated (controls) was conducted between 2001 and 20...

An Analysis of Construction Accident Factors Based on Bayesian Network

OpenAIRE

Yunsheng Zhao; Jinyong Pei

2013-01-01

In this study, we have an analysis of construction accident factors based on bayesian network. Firstly, accidents cases are analyzed to build Fault Tree method, which is available to find all the factors causing the accidents, then qualitatively and quantitatively analyzes the factors with Bayesian network method, finally determines the safety management program to guide the safety operations. The results of this study show that bad condition of geological environment has the largest posterio...

First course in factor analysis

CERN Document Server

Comrey, Andrew L

2013-01-01

The goal of this book is to foster a basic understanding of factor analytic techniques so that readers can use them in their own research and critically evaluate their use by other researchers. Both the underlying theory and correct application are emphasized. The theory is presented through the mathematical basis of the most common factor analytic models and several methods used in factor analysis. On the application side, considerable attention is given to the extraction problem, the rotation problem, and the interpretation of factor analytic results. Hence, readers are given a background of

Structural studies of formic acid using partial form-factor analysis

International Nuclear Information System (INIS)

Swan, G.; Dore, J.C.; Bellissent-Funel, M.C.

1993-01-01

Neutron diffraction measurements have been made of liquid formic acid using H/D isotopic substitution. Data are recorded for samples of DCOOD, HCOOD and a (H/D)COOD mixture (α D =0.36). A first-order difference method is used to determine the intra-molecular contribution through the introduction of a partial form-factor analysis technique incorporating a hydrogen-bond term. The method improves the sensitivity of the parameters defining the molecular geometry and avoids some of the ambiguities arising from terms involving spatial overlap of inter- and intra-molecular features. The possible application to other systems is briefly reviewed. (authors). 8 figs., 2 tabs., 8 refs

Study on Performance Shaping Factors (PSFs) Quantification Method in Human Reliability Analysis (HRA)

International Nuclear Information System (INIS)

Kim, Ar Ryum; Jang, Inseok Jang; Seong, Poong Hyun; Park, Jinkyun; Kim, Jong Hyun

2015-01-01

The purpose of HRA implementation is 1) to achieve the human factor engineering (HFE) design goal of providing operator interfaces that will minimize personnel errors and 2) to conduct an integrated activity to support probabilistic risk assessment (PRA). For these purposes, various HRA methods have been developed such as technique for human error rate prediction (THERP), simplified plant analysis risk human reliability assessment (SPAR-H), cognitive reliability and error analysis method (CREAM) and so on. In performing HRA, such conditions that influence human performances have been represented via several context factors called performance shaping factors (PSFs). PSFs are aspects of the human's individual characteristics, environment, organization, or task that specifically decrements or improves human performance, thus respectively increasing or decreasing the likelihood of human errors. Most HRA methods evaluate the weightings of PSFs by expert judgment and explicit guidance for evaluating the weighting is not provided. It has been widely known that the performance of the human operator is one of the critical factors to determine the safe operation of NPPs. HRA methods have been developed to identify the possibility and mechanism of human errors. In performing HRA methods, the effect of PSFs which may increase or decrease human error should be investigated. However, the effect of PSFs were estimated by expert judgment so far. Accordingly, in order to estimate the effect of PSFs objectively, the quantitative framework to estimate PSFs by using PSF profiles is introduced in this paper

Quantitative EDXS analysis of organic materials using the ζ-factor method

International Nuclear Information System (INIS)

Fladischer, Stefanie; Grogger, Werner

2014-01-01

In this study we successfully applied the ζ-factor method to perform quantitative X-ray analysis of organic thin films consisting of light elements. With its ability to intrinsically correct for X-ray absorption, this method significantly improved the quality of the quantification as well as the accuracy of the results compared to conventional techniques in particular regarding the quantification of light elements. We describe in detail the process of determining sensitivity factors (ζ-factors) using a single standard specimen and the involved parameter optimization for the estimation of ζ-factors for elements not contained in the standard. The ζ-factor method was then applied to perform quantitative analysis of organic semiconducting materials frequently used in organic electronics. Finally, the results were verified and discussed concerning validity and accuracy. - Highlights: • The ζ-factor method is used for quantitative EDXS analysis of light elements. • We describe the process of determining ζ-factors from a single standard in detail. • Organic semiconducting materials are successfully quantified

Multiplication factor versus regression analysis in stature estimation from hand and foot dimensions.

Science.gov (United States)

Krishan, Kewal; Kanchan, Tanuj; Sharma, Abhilasha

2012-05-01

Estimation of stature is an important parameter in identification of human remains in forensic examinations. The present study is aimed to compare the reliability and accuracy of stature estimation and to demonstrate the variability in estimated stature and actual stature using multiplication factor and regression analysis methods. The study is based on a sample of 246 subjects (123 males and 123 females) from North India aged between 17 and 20 years. Four anthropometric measurements; hand length, hand breadth, foot length and foot breadth taken on the left side in each subject were included in the study. Stature was measured using standard anthropometric techniques. Multiplication factors were calculated and linear regression models were derived for estimation of stature from hand and foot dimensions. Derived multiplication factors and regression formula were applied to the hand and foot measurements in the study sample. The estimated stature from the multiplication factors and regression analysis was compared with the actual stature to find the error in estimated stature. The results indicate that the range of error in estimation of stature from regression analysis method is less than that of multiplication factor method thus, confirming that the regression analysis method is better than multiplication factor analysis in stature estimation. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Risk and protective factors of internet addiction: a meta-analysis of empirical studies in Korea.

Science.gov (United States)

Koo, Hoon Jung; Kwon, Jung-Hye

2014-11-01

A meta-analysis of empirical studies performed in Korea was conducted to systematically investigate the associations between the indices of Internet addiction (IA) and psychosocial variables. Systematic literature searches were carried out using the Korean Studies Information Service System, Research Information Sharing Service, Science Direct, Google Scholar, and references in review articles. The key words were Internet addiction, (Internet) game addiction, and pathological, problematic, and excessive Internet use. Only original research papers using Korean samples published from 1999 to 2012 and officially reviewed by peers were included for analysis. Ninety-five studies meeting the inclusion criteria were identified. The magnitude of the overall effect size of the intrapersonal variables associated with internet addiction was significantly higher than that of interpersonal variables. Specifically, IA demonstrated a medium to strong association with "escape from self" and "self-identity" as self-related variables. "Attention problem", "self-control", and "emotional regulation" as control and regulation-relation variables; "addiction and absorption traits" as temperament variables; "anger" and "aggression" as emotion and mood and variables; "negative stress coping" as coping variables were also associated with comparably larger effect sizes. Contrary to our expectation, the magnitude of the correlations between relational ability and quality, parental relationships and family functionality, and IA were found to be small. The strength of the association between IA and the risk and protective factors was found to be higher in younger age groups. The findings highlight a need for closer examination of psychosocial factors, especially intrapersonal variables when assessing high-risk individuals and designing intervention strategies for both general IA and Internet game addiction.

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale

Science.gov (United States)

Sediyama, Cristina Y. N.; Moura, Ricardo; Garcia, Marina S.; da Silva, Antonio G.; Soraggi, Carolina; Neves, Fernando S.; Albuquerque, Maicon R.; Whiteside, Setephen P.; Malloy-Diniz, Leandro F.

2017-01-01

Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale. Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a) urgency, (b) lack of premeditation; (c) lack of perseverance; (d) sensation seeking. In the present study 384 participants (278 women and 106 men), who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis. Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years) scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach’s alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory. Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS. PMID:28484414

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale

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Leandro F. Malloy-Diniz

2017-04-01

Full Text Available Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale.Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a urgency, (b lack of premeditation; (c lack of perseverance; (d sensation seeking. In the present study 384 participants (278 women and 106 men, who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis.Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach’s alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory.Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS.

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale.

Science.gov (United States)

Sediyama, Cristina Y N; Moura, Ricardo; Garcia, Marina S; da Silva, Antonio G; Soraggi, Carolina; Neves, Fernando S; Albuquerque, Maicon R; Whiteside, Setephen P; Malloy-Diniz, Leandro F

2017-01-01

Objective: To examine the internal consistency and factor structure of the Brazilian adaptation of the UPPS Impulsive Behavior Scale. Methods: UPPS is a self-report scale composed by 40 items assessing four factors of impulsivity: (a) urgency, (b) lack of premeditation; (c) lack of perseverance; (d) sensation seeking. In the present study 384 participants (278 women and 106 men), who were recruited from schools, universities, leisure centers and workplaces fulfilled the UPPS scale. An exploratory factor analysis was performed by using Varimax factor rotation and Kaiser Normalization, and we also conducted two confirmatory analyses to test the independency of the UPPS components found in previous analysis. Results: Results showed a decrease in mean UPPS total scores with age and this analysis showed that the youngest participants (below 30 years) scored significantly higher than the other groups over 30 years. No difference in gender was found. Cronbach's alpha, results indicated satisfactory values for all subscales, with similar high values for the subscales and confirmatory factor analysis indexes also indicated a poor model fit. The results of two exploratory factor analysis were satisfactory. Conclusion: Our results showed that the Portuguese version has the same four-factor structure of the original and previous translations of the UPPS.

Meta-Analysis of Comparing Personal and Environmental Factors Effective in Addiction Relapse (Iran, 2004 -2012

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s Safari

2014-12-01

Full Text Available Objective: This As a meta-analysis, this study aimed to integrate different studies and investigate the impact of individual and environmental factors on the reappearance of addiction in quitted people. Method: This study is a meta-analysis which uses Hunter and Schmidt approach. For this purpose, 28 out of 42 studies enjoying acceptable methodologies were selected, upon which the meta-analysis was conducted. A meta-analysis checklist was the research instrument. Using summary of the study results, the researcher manually calculated effect size and interpreted it based on the meta-analysis approach and Cohen’s table. Findings: Results revealed that the effect size of environmental factors on addiction relapse was 0.64 while it was obtained 0.41 for individual factors on addiction relapse. Conclusion: According to Cohen’s table, the effect sizes are evaluated as moderate and high for individual factors and environmental factors on addiction relapse, respectively.

Multiple factor analysis by example using R

CERN Document Server

Pagès, Jérôme

2014-01-01

Multiple factor analysis (MFA) enables users to analyze tables of individuals and variables in which the variables are structured into quantitative, qualitative, or mixed groups. Written by the co-developer of this methodology, Multiple Factor Analysis by Example Using R brings together the theoretical and methodological aspects of MFA. It also includes examples of applications and details of how to implement MFA using an R package (FactoMineR).The first two chapters cover the basic factorial analysis methods of principal component analysis (PCA) and multiple correspondence analysis (MCA). The

A multivariate statistical study with a factor analysis of recent planktonic foraminiferal distribution in the Coromandel Coast of India

Digital Repository Service at National Institute of Oceanography (India)

Jayalakshmy, K.V.; Rao, K.K.

A study of planktonic foraminiferal assemblages from 19 stations in the neritic and oceanic regions off the Coromandel Coast, Bay of Bengal has been made using a multivariate statistical method termed as factor analysis. On the basis of abundance...

A Monte Carlo study comparing PIV, ULS and DWLS in the estimation of dichotomous confirmatory factor analysis.

Science.gov (United States)

Nestler, Steffen

2013-02-01

We conducted a Monte Carlo study to investigate the performance of the polychoric instrumental variable estimator (PIV) in comparison to unweighted least squares (ULS) and diagonally weighted least squares (DWLS) in the estimation of a confirmatory factor analysis model with dichotomous indicators. The simulation involved 144 conditions (1,000 replications per condition) that were defined by a combination of (a) two types of latent factor models, (b) four sample sizes (100, 250, 500, 1,000), (c) three factor loadings (low, moderate, strong), (d) three levels of non-normality (normal, moderately, and extremely non-normal), and (e) whether the factor model was correctly specified or misspecified. The results showed that when the model was correctly specified, PIV produced estimates that were as accurate as ULS and DWLS. Furthermore, the simulation showed that PIV was more robust to structural misspecifications than ULS and DWLS. © 2012 The British Psychological Society.

[A factor analysis method for contingency table data with unlimited multiple choice questions].

Science.gov (United States)

Toyoda, Hideki; Haiden, Reina; Kubo, Saori; Ikehara, Kazuya; Isobe, Yurie

2016-02-01

The purpose of this study is to propose a method of factor analysis for analyzing contingency tables developed from the data of unlimited multiple-choice questions. This method assumes that the element of each cell of the contingency table has a binominal distribution and a factor analysis model is applied to the logit of the selection probability. Scree plot and WAIC are used to decide the number of factors, and the standardized residual, the standardized difference between the sample, and the proportion ratio, is used to select items. The proposed method was applied to real product impression research data on advertised chips and energy drinks. Since the results of the analysis showed that this method could be used in conjunction with conventional factor analysis model, and extracted factors were fully interpretable, and suggests the usefulness of the proposed method in the study of psychology using unlimited multiple-choice questions.

Determinants of job stress in chemical process industry: A factor analysis approach.

Science.gov (United States)

Menon, Balagopal G; Praveensal, C J; Madhu, G

2015-01-01

Job stress is one of the active research domains in industrial safety research. The job stress can result in accidents and health related issues in workers in chemical process industries. Hence it is important to measure the level of job stress in workers so as to mitigate the same to avoid the worker's safety related problems in the industries. The objective of this study is to determine the job stress factors in the chemical process industry in Kerala state, India. This study also aims to propose a comprehensive model and an instrument framework for measuring job stress levels in the chemical process industries in Kerala, India. The data is collected through a questionnaire survey conducted in chemical process industries in Kerala. The collected data out of 1197 surveys is subjected to principal component and confirmatory factor analysis to develop the job stress factor structure. The factor analysis revealed 8 factors that influence the job stress in process industries. It is also found that the job stress in employees is most influenced by role ambiguity and the least by work environment. The study has developed an instrument framework towards measuring job stress utilizing exploratory factor analysis and structural equation modeling.

Factors that affect risk for pancreatic disease in the general population: a systematic review and meta-analysis of prospective cohort studies.

Science.gov (United States)

Alsamarrai, Ammar; Das, Stephanie L M; Windsor, John A; Petrov, Maxim S

2014-10-01

Pancreatic diseases place significant burdens on health care systems worldwide. However, there is lack of agreement about which factors increase or reduce risk for pancreatic disease. We reviewed high-quality studies of factors that affect risk for pancreatic diseases in the general population. We searched 3 databases (Medline, Embase, and Scopus) for prospective cohort studies of modifiable risk and/or protective factors for acute pancreatitis, chronic pancreatitis, and pancreatic cancer in adult populations. Factors that were investigated in 2 or more studies were assessed by meta-analysis if the required data were available. Subgroup analyses were performed when appropriate. Outcome measures were relative risk (RR) and 95% confidence interval (CI). Our analysis included 51 population-based studies with more than 3 million individuals and nearly 11,000 patients with pancreatic diseases. A total of 31 different factors were investigated. Current tobacco use was the single most important risk factor for pancreatic diseases (RR, 1.87; 95% CI, 1.54-2.27), followed by obesity (RR, 1.48; 95% CI, 1.15-1.92) and heavy use of alcohol (RR, 1.37; 95% CI, 1.19-1.58). Tobacco and heavy use of alcohol had bigger effects on risk of acute pancreatitis and chronic pancreatitis than pancreatic cancer. Vegetable consumption (RR, 0.71; 95% CI, 0.57-0.88) and fruit consumption (RR, 0.73; 95% CI, 0.60-0.90) provided the greatest degree of protection against pancreatic diseases on the basis of meta-analyses. Vegetable consumption had stronger association with protection against acute pancreatitis and fruit consumption with protection against pancreatic cancer. On the basis of systematic review and meta-analysis, current tobacco use, obesity, and heavy use of alcohol are associated with significant increases in risk for pancreatic diseases. Vegetables and fruit consumption are associated with reduced risk for pancreatic diseases. Prevention strategies for acute pancreatitis, chronic

An exploration study on factors influencing Iranian food industry

OpenAIRE

Arash Hosseinzadeh; Seyed Mohsen Seyedaliakbar; Naser Azad; Ashkan Arabi

2013-01-01

The proposed study of this paper present an empirical investigation to detect important factors impacting on food market using factor analysis. The proposed study designed a questionnaire, distributed among 207 customers who were regular customers of two food chains in city of Tehran, Iran named Shahrvand and Hyperstar. The results of our survey indicate that six major factors including brand loyalty, physical characteristics, pricing effects, performance characteristics, brand relationship a...

Gene-by-Psychosocial Factor Interactions Influence Diastolic Blood Pressure in European and African Ancestry Populations: Meta-Analysis of Four Cohort Studies

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Jennifer A. Smith

2017-12-01

Full Text Available Inter-individual variability in blood pressure (BP is influenced by both genetic and non-genetic factors including socioeconomic and psychosocial stressors. A deeper understanding of the gene-by-socioeconomic/psychosocial factor interactions on BP may help to identify individuals that are genetically susceptible to high BP in specific social contexts. In this study, we used a genomic region-based method for longitudinal analysis, Longitudinal Gene-Environment-Wide Interaction Studies (LGEWIS, to evaluate the effects of interactions between known socioeconomic/psychosocial and genetic risk factors on systolic and diastolic BP in four large epidemiologic cohorts of European and/or African ancestry. After correction for multiple testing, two interactions were significantly associated with diastolic BP. In European ancestry participants, outward/trait anger score had a significant interaction with the C10orf107 genomic region (p = 0.0019. In African ancestry participants, depressive symptom score had a significant interaction with the HFE genomic region (p = 0.0048. This study provides a foundation for using genomic region-based longitudinal analysis to identify subgroups of the population that may be at greater risk of elevated BP due to the combined influence of genetic and socioeconomic/psychosocial risk factors.

A Comparative Study of the Application of Fluorescence Excitation-Emission Matrices Combined with Parallel Factor Analysis and Nonnegative Matrix Factorization in the Analysis of Zn Complexation by Humic Acids

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Patrycja Boguta

2016-10-01

Full Text Available The main aim of this study was the application of excitation-emission fluorescence matrices (EEMs combined with two decomposition methods: parallel factor analysis (PARAFAC and nonnegative matrix factorization (NMF to study the interaction mechanisms between humic acids (HAs and Zn(II over a wide concentration range (0–50 mg·dm−3. The influence of HA properties on Zn(II complexation was also investigated. Stability constants, quenching degree and complexation capacity were estimated for binding sites found in raw EEM, EEM-PARAFAC and EEM-NMF data using mathematical models. A combination of EEM fluorescence analysis with one of the proposed decomposition methods enabled separation of overlapping binding sites and yielded more accurate calculations of the binding parameters. PARAFAC and NMF processing allowed finding binding sites invisible in a few raw EEM datasets as well as finding totally new maxima attributed to structures of the lowest humification. Decomposed data showed an increase in Zn complexation with an increase in humification, aromaticity and molecular weight of HAs. EEM-PARAFAC analysis also revealed that the most stable compounds were formed by structures containing the highest amounts of nitrogen. The content of oxygen-functional groups did not influence the binding parameters, mainly due to fact of higher competition of metal cation with protons. EEM spectra coupled with NMF and especially PARAFAC processing gave more adequate assessments of interactions as compared to raw EEM data and should be especially recommended for modeling of complexation processes where the fluorescence intensities (FI changes are weak or where the processes are interfered with by the presence of other fluorophores.

Multivariate factor analysis of Girgentana goat milk composition

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Pietro Giaccone

2010-01-01

Full Text Available The interpretation of the several variables that contribute to defining milk quality is difficult due to the high degree of  correlation among them. In this case, one of the best methods of statistical processing is factor analysis, which belongs  to the multivariate groups; for our study this particular statistical approach was employed.  A total of 1485 individual goat milk samples from 117 Girgentana goats, were collected fortnightly from January to July,  and analysed for physical and chemical composition, and clotting properties. Milk pH and tritable acidity were within the  normal range for fresh goat milk. Morning milk yield resulted 704 ± 323 g with 3.93 ± 1.23% and 3.48±0.38% for fat  and protein percentages, respectively. The milk urea content was 43.70 ± 8.28 mg/dl. The clotting ability of Girgentana  milk was quite good, with a renneting time equal to 16.96 ± 3.08 minutes, a rate of curd formation of 2.01 ± 1.63 min-  utes and a curd firmness of 25.08 ± 7.67 millimetres.  Factor analysis was performed by applying axis orthogonal rotation (rotation type VARIMAX; the analysis grouped the  milk components into three latent or common factors. The first, which explained 51.2% of the total covariance, was  defined as “slow milks”, because it was linked to r and pH. The second latent factor, which explained 36.2% of the total  covariance, was defined as “milk yield”, because it is positively correlated to the morning milk yield and to the urea con-  tent, whilst negatively correlated to the fat percentage. The third latent factor, which explained 12.6% of the total covari-  ance, was defined as “curd firmness,” because it is linked to protein percentage, a30 and titatrable acidity. With the aim  of evaluating the influence of environmental effects (stage of kidding, parity and type of kidding, factor scores were anal-  ysed with the mixed linear model. Results showed significant effects of the season of

Common Factor Analysis Versus Principal Component Analysis: Choice for Symptom Cluster Research

Directory of Open Access Journals (Sweden)

Hee-Ju Kim, PhD, RN

2008-03-01

Conclusion: If the study purpose is to explain correlations among variables and to examine the structure of the data (this is usual for most cases in symptom cluster research, CFA provides a more accurate result. If the purpose of a study is to summarize data with a smaller number of variables, PCA is the choice. PCA can also be used as an initial step in CFA because it provides information regarding the maximum number and nature of factors. In using factor analysis for symptom cluster research, several issues need to be considered, including subjectivity of solution, sample size, symptom selection, and level of measure.

Situational Factors in Focus Group Studies: A Systematic Review

OpenAIRE

Arne Orvik MPolSc; Lillebeth Larun PhD; Astrid Berland MSc; Karin C. Ringsberg PhD

2013-01-01

The aim of this study was to see how contextual factors are expressed, used, and analyzed in data collected in focus group discussions (FGDs). The study includes an assessment of how the methodological reporting of contextual factors might influence and improve the trustworthiness of articles. Articles reporting workplace health, stress, and coping among health professionals were identified in a systematic review and used in the analysis. By using Vicsek's framework of situational factors for...

Risk and Protective Factors of Internet Addiction: A Meta-Analysis of Empirical Studies in Korea

Science.gov (United States)

Koo, Hoon Jung

2014-01-01

Purpose A meta-analysis of empirical studies performed in Korea was conducted to systematically investigate the associations between the indices of Internet addiction (IA) and psychosocial variables. Materials and Methods Systematic literature searches were carried out using the Korean Studies Information Service System, Research Information Sharing Service, Science Direct, Google Scholar, and references in review articles. The key words were Internet addiction, (Internet) game addiction, and pathological, problematic, and excessive Internet use. Only original research papers using Korean samples published from 1999 to 2012 and officially reviewed by peers were included for analysis. Ninety-five studies meeting the inclusion criteria were identified. Results The magnitude of the overall effect size of the intrapersonal variables associated with internet addiction was significantly higher than that of interpersonal variables. Specifically, IA demonstrated a medium to strong association with "escape from self" and "self-identity" as self-related variables. "Attention problem", "self-control", and "emotional regulation" as control and regulation-relation variables; "addiction and absorption traits" as temperament variables; "anger" and "aggression" as emotion and mood and variables; "negative stress coping" as coping variables were also associated with comparably larger effect sizes. Contrary to our expectation, the magnitude of the correlations between relational ability and quality, parental relationships and family functionality, and IA were found to be small. The strength of the association between IA and the risk and protective factors was found to be higher in younger age groups. Conclusion The findings highlight a need for closer examination of psychosocial factors, especially intrapersonal variables when assessing high-risk individuals and designing intervention strategies for both general IA and Internet game addiction. PMID:25323910

Risk Factor Analysis for AKI Including Laboratory Indicators: a Nationwide Multicenter Study of Hospitalized Patients

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Sasa Nie

2017-10-01

Full Text Available Background/Aims: Risk factor studies for acute kidney injury (AKI in China are lacking, especially those regarding non-traditional risk factors, such as laboratory indicators. Methods: All adult patients admitted to 38 tertiary and 22 secondary hospitals in China in any one month between July and December 2014 were surveyed. AKI patients were screened according to the Kidney Disease: Improving Global Outcomes’ definition of AKI. Logistic regression was used to analyze the risk factors for AKI, and Cox regression was used to analyze the risk of in-hospital mortality for AKI patients; additionally, a propensity score analysis was used to reconfirm the risk factors among laboratory indicators for mortality. Results: The morbidity of AKI was 0.97%. Independent risk factors for AKI were advancing age, male gender, hypertension, and chronic kidney disease. All-cause mortality was 16.5%. The predictors of mortality in AKI patients were advancing age, tumor, higher uric acid level and increases in Acute Physiologic Assessment and Chronic Health Evaluation II and Sequential Organ Failure Assessment scores. The hazard ratio (HR for mortality with uric acid levels > 9.1 mg/dl compared with ≤ 5.2 mg/dl was 1.78 (95% CI: 1.23 to 2.58 for the AKI patients as a group, and was 1.73 (95% CI: 1.24 to 2.42 for a propensity score-matched set. Conclusion: In addition to traditional risk factors, uric acid level is an independent predictor of all-cause mortality after AKI.

Risk factors for cataract: A case control study

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Ughade Suresh

1998-01-01

Full Text Available The present study was designed as a hospital-based, group-matched, case-control investigation into the risk factors associated with age-related cataract in central India. The study included 262 cases of age-related cataract and an equal number of controls. A total of 21 risk factors were evaluated: namely, low socioeconomic status (SES, illiteracy, marital status, history of diarrhoea, history of diabetes, glaucoma, use of cholinesterase inhibitors, steroids, spironolactone, nifedipine, analgesics, myopia early in life, renal failure, heavy smoking, heavy alcohol consumption, hypertension, low body mass index (BMI, use of cheaper cooking fuel, working in direct sunlight, family history of cataract, and occupational exposure. In univariate analysis, except marital status, low BMI, renal failure, use of steroids, spironolactone, analgesics, and occupational exposure, all 14 other risk factors were found significantly associated with age-related cataract. Unconditional multiple logistic regression analysis confirmed the significance of low SES, illiteracy, history of diarrhoea, diabetes, glaucoma, myopia, smoking, hypertension and cheap cooking fuel. The etiological role of these risk factors in the outcome of cataract is confirmed by the estimates of attributable risk proportion. The estimates of population attributable risk proportion for these factors highlight the impact of elimination of these risk factors on the reduction of cataract in this population.

Analysis of related risk factors for pancreatic fistula after pancreaticoduodenectomy

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Qi-Song Yu

2016-08-01

Full Text Available Objective: To explore the related risk factors for pancreatic fistula after pancreaticoduodenectomy to provide a theoretical evidence for effectively preventing the occurrence of pancreatic fistula. Methods: A total of 100 patients who were admitted in our hospital from January, 2012 to January, 2015 and had performed pancreaticoduodenectomy were included in the study. The related risk factors for developing pancreatic fistula were collected for single factor and Logistic multi-factor analysis. Results: Among the included patients, 16 had pancreatic fistula, and the total occurrence rate was 16% (16/100. The single-factor analysis showed that the upper abdominal operation history, preoperative bilirubin, pancreatic texture, pancreatic duct diameter, intraoperative amount of bleeding, postoperative hemoglobin, and application of somatostatin after operation were the risk factors for developing pancreatic fistula (P<0.05. The multi-factor analysis showed that the upper abdominal operation history, the soft pancreatic texture, small pancreatic duct diameter, and low postoperative hemoglobin were the dependent risk factors for developing pancreatic fistula (OR=4.162, 6.104, 5.613, 4.034, P<0.05. Conclusions: The occurrence of pancreatic fistula after pancreaticoduodenectomy is closely associated with the upper abdominal operation history, the soft pancreatic texture, small pancreatic duct diameter, and low postoperative hemoglobin; therefore, effective measures should be taken to reduce the occurrence of pancreatic fistula according to the patients’ own conditions.

Study of Sesame (Sesame indicum L. Cultivars based on Morphological Characteristics Under Water Deficit Stress Condition Using Factor Analysis

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A Asghari

2014-03-01

Full Text Available In order to evaluation sesame cultivars based on morphological characteristics under water deficit stress condition using factor analysis, an experiment was conducted as a split plot based on randomized complete block design with three replications during 2009 in Research Center of Agriculture and Natural Resources in Parsabad. In this experiment, irrigation as the main factor at three levels (50, 75 and 100 percent of crop water requirement and ten sesame cultivars as the sub-factor were studied. The water requirement of sesame was calculated using CROPWAT software (Penman-Monteith method according to FAO-56. Results showed significant differences between the cultivars and the irrigation levels for all studied traits. Interaction between cultivars and irrigation levels was significant for some of traits. Comparisons of means showed that in water deficit condition, yield and all of traits reduced. In all traits the greatest amounts observed in complete irrigation treatment. In 50 percent of water requirement treatment, amount of leaf chlorophyll, root length, root branches and root length/plant height ratio were greater than other treatments. The Karaj1, Ultan, Naze and IS cultivars were better than other cultivars in stress and non stress condition. In factor analysis 5 and 4 first factors in non stress and stress condition explained 91.36 and 89.52 percent of trait variance, respectively. Grouping of sesame cultivars based on first and second factors in non stress conditions showed that Karaj1, Ultan and Naze cultivars were better than other cultivars. Also, in stress conditions Karaj1 and Ultan cultivars grouped as water deficit stress and better cultivars.

Is chronic toxoplasmosis a risk factor for diabetes mellitus? A systematic review and meta-analysis of case–control studies

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Hamidreza Majidiani

2016-11-01

Conclusion: Despite the limitations such as low number of studies, this meta-analysis suggests chronic toxoplasmosis as a possible risk factor for type 2 DM. However, based on random effects model no statistically significant association was observed between T. gondii and type 1 DM. It is highly recommended for researchers to carry out more accurate studies aiming to better understand this association.

Exploratory Factor Analysis of SCL90-R Symptoms Relevant to Psychosis

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Javad Amini

2011-10-01

Full Text Available "nObjective: Inconsistent results have been reported regarding the symptom dimensions relevant to psychosis in symptoms check list revised (SCL90-R, i.e., "psychoticism" and "paranoid ideation". Therefore, some studies have suggested different factor structures for questions of these two dimensions, and proposed two newly defined dimensions of "schizotypal signs" and "schizophrenia nuclear symptoms". We conducted an exploratory factor analysis on the items of these two dimensions in a general population sample in Iran. "nMethod: A total of 2158 subjects residing in Southern Tehran (capital of Iran were interviewed using the psychoticism and paranoid ideation questions in SCL90-R to assess severity of these symptom dimensions. Factor analysis was done through SAS 9.1.3 PROC FACTOR using Promax rotation (power=3 on the matrix of "polychoric correlations among variables" as the input data. "nResults: Two factors were retained by the proportion criterion. Considering loadings >= 0.5 as minimum criteria for factor loadings, 7 out of 10 questions  from psychoticism ,and 3 out of 6 questions from paranoid ideation were retained, and others were eliminated. The factor labels proposed by the questionnaire suited the extracted factors and were retained. Internal consistency for each of the dimensions was acceptable (Cronbach's alpha 0.7 and 0.74 for paranoid ideation and psychoticism respectively. Composite scores showed a half-normal distribution for both dimensions which is predictable for instruments that detect psychotic symptoms. "nConclusion: Results were in contrast with similar studies, and questioned them by suggesting a different factor structure obtained from a statistically large population. The population in a developing nation (Iran in this study and the socio-cultural differences in developed settings are the potential sources for discrepancies between this analysis and previous reports.

Landscape of dietary factors associated with risk of gastric cancer: A systematic review and dose-response meta-analysis of prospective cohort studies.

Science.gov (United States)

Fang, Xuexian; Wei, Jiayu; He, Xuyan; An, Peng; Wang, Hao; Jiang, Li; Shao, Dandan; Liang, Han; Li, Yi; Wang, Fudi; Min, Junxia

2015-12-01

The associations between dietary factors and gastric cancer risk have been analysed by many studies, but with inconclusive results. We conducted a meta-analysis of prospective studies to systematically investigate the associations. Relevant studies were identified through searching Medline, Embase, and Web of Science up to June 30, 2015. We included prospective cohort studies of intake of dietary factors with risk estimates and 95% confidence intervals for gastric cancer. Seventy-six prospective cohort studies were eligible and included in the analysis. We ascertained 32,758 gastric cancer cases out of 6,316,385 participants in relations to intake of 67 dietary factors, covering a wide ranging of vegetables, fruit, meat, fish, salt, alcohol, tea, coffee, and nutrients, during 3.3 to 30 years of follow-up. Evidence from this study indicates that consumption of total fruit and white vegetables, but not total vegetables, was inversely associated with gastric cancer risk. Both fruit and white vegetables are rich sources of vitamin C, which showed significant protective effect against gastric cancer by our analysis too. Furthermore, we found concordant positive associations between high-salt foods and gastric cancer risk. In addition, a strong effect of alcohol consumption, particularly beer and liquor but not wine, on gastric cancer risk was observed compared with nondrinkers. Dose-response analysis indicated that risk of gastric cancer was increased by 12% per 5 g/day increment of dietary salt intake or 5% per 10 g/day increment of alcohol consumption, and that a 100 g/day increment of fruit consumption was inversely associated with 5% reduction of risk. This study provides comprehensive and strong evidence that there are a number of protective and risk factors for gastric cancer in diet. Our findings may have significant public health implications with regard to prevention of gastric cancer and provide insights into future cohort studies and the design of related

Workplace Innovation: Exploratory and Confirmatory Factor Analysis for Construct Validation

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Wipulanusat Warit

2017-06-01

Full Text Available Workplace innovation enables the development and improvement of products, processes and services leading simultaneously to improvement in organisational performance. This study has the purpose of examining the factor structure of workplace innovation. Survey data, extracted from the 2014 APS employee census, comprising 3,125 engineering professionals in the Commonwealth of Australia’s departments were analysed using exploratory factor analysis (EFA and confirmatory factor analysis (CFA. EFA returned a two-factor structure explaining 69.1% of the variance of the construct. CFA revealed that a two-factor structure was indicated as a validated model (GFI = 0.98, AGFI = 0.95, RMSEA = 0.08, RMR = 0.02, IFI = 0.98, NFI = 0.98, CFI = 0.98, and TLI = 0.96. Both factors showed good reliability of the scale (Individual creativity: α = 0.83, CR = 0.86, and AVE = 0.62; Team Innovation: α = 0.82, CR = 0.88, and AVE = 0.61. These results confirm that the two factors extracted for characterising workplace innovation included individual creativity and team innovation.

Risk Factors for Post-stroke Depression: A Meta-analysis

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Yu Shi

2017-07-01

Full Text Available Background: Stroke not only impacts patients physically but also economically. Post-stroke depression (PSD, as a common complication of stroke, always obstructs the process of stroke rehabilitation. Accordingly, defining the risk factors associated with PSD has extraordinary importance. Although there have been many studies investigating the risk factors for PSD, the results are inconsistent.Objectives: The objectives of this study were to identify the risk factors for PSD by evidence-based medicine.Data sources: A systematic and comprehensive database search was performed of PubMed, Medline, CENTRAL, EMBASE.com, the Cochrane library and Web of Science for Literature, covering publications from January 1, 1998 to November 19, 2016.Study Selection: Studies on risk factors for PSD were identified, according to inclusion and exclusion criteria. The risk of bias tool, described in the Cochrane Handbook version 5.1.0, was used to assess the quality of each study. Meta-analysis was performed using RevMan 5.3 software.Results: Thirty-six studies were included for review. A history of mental illness was the highest ranking modifiable risk factor; other risk factors for PSD were female gender, age (<70 years, neuroticism, family history, severity of stroke, and level of handicap. Social support was a protective factor for PSD.Conclusion: There are many factors that have effects on PSD. The severity of stroke is an important factor in the occurrence of PSD. Mental history is a possible predictor of PSD. Prevention of PSD requires social and family participation.

Combining analysis of variance and three‐way factor analysis methods for studying additive and multiplicative effects in sensory panel data

DEFF Research Database (Denmark)

Romano, Rosaria; Næs, Tormod; Brockhoff, Per Bruun

2015-01-01

Data from descriptive sensory analysis are essentially three‐way data with assessors, samples and attributes as the three ways in the data set. Because of this, there are several ways that the data can be analysed. The paper focuses on the analysis of sensory characteristics of products while...... in the use of the scale with reference to the existing structure of relationships between sensory descriptors. The multivariate assessor model will be tested on a data set from milk. Relations between the proposed model and other multiplicative models like parallel factor analysis and analysis of variance...

Ranking factors of an investment in cogeneration: sensitivity analysis ranking the technical and economical factors

International Nuclear Information System (INIS)

Sundberg, Gunnel

2001-01-01

A deregulation of the electricity market in Europe will result in increased competition among the power-producing companies. They will therefore carefully estimate the financial risk in an investment in new power-producing capability. One part of the risk assessment is to perform a sensitivity analysis. This paper presents a sensitivity analysis using factorial design, resulting in an assessment of the most important technical and economical factors affecting an investment in gas turbine combined cycle and a steam cycle fired by wood chips. The study is performed using a simulation model that optimises the operation of existing power plants and potential new investments to fulfil the desired heat demand. The local utility system analysed is a Swedish district heating system with 655 GWh y -1 heat demand. The conclusion is that to understand which of the technical and economical factors affect the investment, it is not sufficient to investigate the parameters of the studied plant, but also the parameters related to the competing plants. Both the individual effects of the factors and the effect of their interaction should be investigated. For the energy system studied the price of natural gas, price of wood chips and investment cost have the major influence on the profitability of the investment. (Author)

Risk factors for chronic and recurrent otitis media-a meta-analysis.

Science.gov (United States)

Zhang, Yan; Xu, Min; Zhang, Jin; Zeng, Lingxia; Wang, Yanfei; Zheng, Qing Yin

2014-01-01

Risk factors associated with chronic otitis media (COM) and recurrent otitis media (ROM) have been investigated in previous studies. The objective of this study was to integrate the findings and determine the possible risk factors for COM/ROM based on our meta-analysis. A comprehensive search of electronic bibliographic databases (PubMed, Embase, CNKI and Wanfang database) from 1964 to Dec 2012, as well as a manual search of references of articles, was performed. A total of 2971 articles were searched, and 198 full-text articles were assessed for eligibility; 24 studies were eligible for this meta-analysis. Regarding risk factors for COM/ROM, there were two to nine different studies from which the odds ratios (ORs) could be pooled. The presence of allergy or atopy increased the risk of COM/ROM (OR, 1.36; 95% CI, 1.13-1.64; P = 0.001). An upper respiratory tract infection (URTI) significantly increased the risk of COM/ROM (OR, 6.59; 95% CI, 3.13-13.89; Pmedia (AOM)/ROM increased the risk of COM/ROM (OR, 11.13; 95% CI, 1.06-116.44; P = 0.04). Passive smoke significantly increased the risk of COM/ROM (OR, 1.39; 95% CI, 1.02-1.89 P = 0.04). Low social status appeared to be a risk factor for COM/ROM (OR, 3.82; 95% CI, 1.11-13.15; P = 0.03). Our meta-analysis identified reliable conclusions that allergy/atopy, URTI, snoring, previous history of AOM/ROM, Second-hand smoke and low social status are important risk factors for COM/ROM. Other unidentified risk factors need to be identified in further studies with critical criteria.

Factor Analysis on the Factors that Influencing Rural Environmental Pollution in the Hilly Area of Sichuan Province,China

Institute of Scientific and Technical Information of China (English)

2011-01-01

By using factor analysis method and establishing analysis indicator system from four aspects including crop production,poultry farming,rural life and township enterprises,the difference,features,and types of factors influencing the rural environmental pollution in the hilly area in Sichuan Province,China.Results prove that the major factor influencing rural environmental pollution in the study area is livestock and poultry breeding,flowed by crop planting,rural life,and township enterprises.Hence future pollution prevention and control should set about from livestock and poultry breeding.Meanwhile,attention should be paid to the prevention and control of rural environmental pollution caused by rural life and township enterprise production.

Environmental Performance in Countries Worldwide: Determinant Factors and Multivariate Analysis

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Isabel Gallego-Alvarez

2014-11-01

Full Text Available The aim of this study is to analyze the environmental performance of countries and the variables that can influence it. At the same time, we performed a multivariate analysis using the HJ-biplot, an exploratory method that looks for hidden patterns in the data, obtained from the usual singular value decomposition (SVD of the data matrix, to contextualize the countries grouped by geographical areas and the variables relating to environmental indicators included in the environmental performance index. The sample used comprises 149 countries of different geographic areas. The findings obtained from the empirical analysis emphasize that socioeconomic factors, such as economic wealth and education, as well as institutional factors represented by the style of public administration, in particular control of corruption, are determinant factors of environmental performance in the countries analyzed. In contrast, no effect on environmental performance was found for factors relating to the internal characteristics of a country or political factors.

EXPLORATORY FACTOR ANALYSIS (EFA IN CONSUMER BEHAVIOR AND MARKETING RESEARCH

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Marcos Pascual Soler

2012-06-01

Full Text Available Exploratory Factor Analysis (EFA is one of the most widely used statistical procedures in social research. The main objective of this work is to describe the most common practices used by researchers in the consumer behavior and marketing area. Through a literature review methodology the practices of AFE in five consumer behavior and marketing journals(2000-2010 were analyzed. Then, the choices made by the researchers concerning factor model, retention criteria, rotation, factors interpretation and other relevant issues to factor analysis were analized. The results suggest that researchers routinely conduct analyses using such questionable methods. Suggestions for improving the use of factor analysis and the reporting of results are presented and a checklist (Exploratory Factor Analysis Checklist, EFAC is provided to help editors, reviewers, and authors improve reporting exploratory factor analysis.

A Confirmatory Factor Analysis of the Structure of Abbreviated Math Anxiety Scale

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Farahman Farrokhi

2011-06-01

Full Text Available "nObjective: The aim of this study is to explore the confirmatory factor analysis results of the Persian adaptation of Abbreviated Math Anxiety Scale (AMAS, proposed by Hopko, Mahadevan, Bare & Hunt. "nMethod: The validity and reliability assessments of the scale were performed on 298 college students chosen randomly from Tabriz University in Iran. The confirmatory factor analysis (CFA was carried out to determine the factor structures of the Persian version of AMAS. "nResults: As expected, the two-factor solution provided a better fit to the data than a single factor. Moreover, multi-group analyses showed that this two-factor structure was invariant across sex. Hence, AMAS provides an equally valid measure for use among college students. "nConclusions:  Brief AMAS demonstrates adequate reliability and validity. The AMAS scores can be used to compare symptoms of math anxiety between male and female students. The study both expands and adds support to the existing body of math anxiety literature.

Exploratory Factor Analysis With Small Samples and Missing Data.

Science.gov (United States)

McNeish, Daniel

2017-01-01

Exploratory factor analysis (EFA) is an extremely popular method for determining the underlying factor structure for a set of variables. Due to its exploratory nature, EFA is notorious for being conducted with small sample sizes, and recent reviews of psychological research have reported that between 40% and 60% of applied studies have 200 or fewer observations. Recent methodological studies have addressed small size requirements for EFA models; however, these models have only considered complete data, which are the exception rather than the rule in psychology. Furthermore, the extant literature on missing data techniques with small samples is scant, and nearly all existing studies focus on topics that are not of primary interest to EFA models. Therefore, this article presents a simulation to assess the performance of various missing data techniques for EFA models with both small samples and missing data. Results show that deletion methods do not extract the proper number of factors and estimate the factor loadings with severe bias, even when data are missing completely at random. Predictive mean matching is the best method overall when considering extracting the correct number of factors and estimating factor loadings without bias, although 2-stage estimation was a close second.

A factor analysis of the Kirton Adaption-Innovation Inventory using an alcoholic population.

Science.gov (United States)

Robertson, E D; Fournet, G P; Zelhart, P F; Estes, R E

1988-04-01

The present study reports a factor analysis of the Kirton Adaption-Innovation Inventory using 103 alcoholic men. Kirton in 1976 and we in an unpublished work in 1986 noted identical factor structures when responses from nonalcoholic populations to the inventory were factor analyzed. Recent reviews regarding personality characteristics of alcoholics suggest characteristics similar to the adaption-innovation concepts of Kirton. This factor analysis for an alcoholic sample supports the validity of the inventory as a measure of problem-solving style of alcoholics.

A human factors needs assessment and planning study

International Nuclear Information System (INIS)

Price, H.E.; Van Cott, H.P.

1982-06-01

A study was done to assess the need for human factors research, development, and regulatory action in the Atomic Energy Control Board. Further study or development in nine human factors areas is proposed. The urgency, schedule, and resources judged to be necessary for the proposed efforts are estimated. Special emphasis is placed on the need for task analysis information, for the evaluation of control room and maintenance human engineering, and for the development of an improved human error reporting system

Confirmatory factor analysis applied to the Force Concept Inventory

Science.gov (United States)

Eaton, Philip; Willoughby, Shannon D.

2018-06-01

In 1995, Huffman and Heller used exploratory factor analysis to draw into question the factors of the Force Concept Inventory (FCI). Since then several papers have been published examining the factors of the FCI on larger sets of student responses and understandable factors were extracted as a result. However, none of these proposed factor models have been verified to not be unique to their original sample through the use of independent sets of data. This paper seeks to confirm the factor models proposed by Scott et al. in 2012, and Hestenes et al. in 1992, as well as another expert model proposed within this study through the use of confirmatory factor analysis (CFA) and a sample of 20 822 postinstruction student responses to the FCI. Upon application of CFA using the full sample, all three models were found to fit the data with acceptable global fit statistics. However, when CFA was performed using these models on smaller sample sizes the models proposed by Scott et al. and Eaton and Willoughby were found to be far more stable than the model proposed by Hestenes et al. The goodness of fit of these models to the data suggests that the FCI can be scored on factors that are not unique to a single class. These scores could then be used to comment on how instruction methods effect the performance of students along a single factor and more in-depth analyses of curriculum changes may be possible as a result.

Risk factors for chronic and recurrent otitis media-a meta-analysis.

Directory of Open Access Journals (Sweden)

Yan Zhang

Full Text Available Risk factors associated with chronic otitis media (COM and recurrent otitis media (ROM have been investigated in previous studies. The objective of this study was to integrate the findings and determine the possible risk factors for COM/ROM based on our meta-analysis. A comprehensive search of electronic bibliographic databases (PubMed, Embase, CNKI and Wanfang database from 1964 to Dec 2012, as well as a manual search of references of articles, was performed. A total of 2971 articles were searched, and 198 full-text articles were assessed for eligibility; 24 studies were eligible for this meta-analysis. Regarding risk factors for COM/ROM, there were two to nine different studies from which the odds ratios (ORs could be pooled. The presence of allergy or atopy increased the risk of COM/ROM (OR, 1.36; 95% CI, 1.13-1.64; P = 0.001. An upper respiratory tract infection (URTI significantly increased the risk of COM/ROM (OR, 6.59; 95% CI, 3.13-13.89; P<0.00001. Snoring appeared to be a significant risk factor for COM/ROM (OR, 1.96; 95% CI, 1.78-2.16; P<0.00001. A patient history of acute otitis media (AOM/ROM increased the risk of COM/ROM (OR, 11.13; 95% CI, 1.06-116.44; P = 0.04. Passive smoke significantly increased the risk of COM/ROM (OR, 1.39; 95% CI, 1.02-1.89 P = 0.04. Low social status appeared to be a risk factor for COM/ROM (OR, 3.82; 95% CI, 1.11-13.15; P = 0.03. Our meta-analysis identified reliable conclusions that allergy/atopy, URTI, snoring, previous history of AOM/ROM, Second-hand smoke and low social status are important risk factors for COM/ROM. Other unidentified risk factors need to be identified in further studies with critical criteria.

An exploration study on factors influencing Iranian food industry

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Arash Hosseinzadeh

2013-05-01

Full Text Available The proposed study of this paper present an empirical investigation to detect important factors impacting on food market using factor analysis. The proposed study designed a questionnaire, distributed among 207 customers who were regular customers of two food chains in city of Tehran, Iran named Shahrvand and Hyperstar. The results of our survey indicate that six major factors including brand loyalty, physical characteristics, pricing effects, performance characteristics, brand relationship and brand position influence food industry, significantly. In terms of the first factor, brand loyalty, “Trust”, “Packaging design characteristics”, “Competitive pricing strategy”, “Stability in quality”, “External relationships” and “Meeting expectations” are important factors in different categories.

Classification analysis of organization factors related to system safety

International Nuclear Information System (INIS)

Liu Huizhen; Zhang Li; Zhang Yuling; Guan Shihua

2009-01-01

This paper analyzes the different types of organization factors which influence the system safety. The organization factor can be divided into the interior organization factor and exterior organization factor. The latter includes the factors of political, economical, technical, law, social culture and geographical, and the relationships among different interest groups. The former includes organization culture, communication, decision, training, process, supervision and management and organization structure. This paper focuses on the description of the organization factors. The classification analysis of the organization factors is the early work of quantitative analysis. (authors)

Seismic analysis response factors and design margins of piping systems

International Nuclear Information System (INIS)

Shieh, L.C.; Tsai, N.C.; Yang, M.S.; Wong, W.L.

1985-01-01

The objective of the simplified methods project of the Seismic Safety Margins Research Program is to develop a simplified seismic risk methodology for general use. The goal is to reduce seismic PRA costs to roughly 60 man-months over a 6 to 8 month period, without compromising the quality of the product. To achieve the goal, it is necessary to simplify the calculational procedure of the seismic response. The response factor approach serves this purpose. The response factor relates the median level response to the design data. Through a literature survey, we identified the various seismic analysis methods adopted in the U.S. nuclear industry for the piping system. A series of seismic response calculations was performed. The response factors and their variabilities for each method of analysis were computed. A sensitivity study of the effect of piping damping, in-structure response spectra envelop method, and analysis method was conducted. In addition, design margins, which relate the best-estimate response to the design data, are also presented

Time Series Factor Analysis with an Application to Measuring Money

NARCIS (Netherlands)

Gilbert, Paul D.; Meijer, Erik

2005-01-01

Time series factor analysis (TSFA) and its associated statistical theory is developed. Unlike dynamic factor analysis (DFA), TSFA obviates the need for explicitly modeling the process dynamics of the underlying phenomena. It also differs from standard factor analysis (FA) in important respects: the

An Analysis of Peer-Reviewed Scores and Impact Factors with Different Citation Time Windows: A Case Study of 28 Ophthalmologic Journals.

Science.gov (United States)

Liu, Xue-Li; Gai, Shuang-Shuang; Zhang, Shi-Le; Wang, Pu

2015-01-01

An important attribute of the traditional impact factor was the controversial 2-year citation window. So far, several scholars have proposed using different citation time windows for evaluating journals. However, there is no confirmation whether a longer citation time window would be better. How did the journal evaluation effects of 3IF, 4IF, and 6IF comparing with 2IF and 5IF? In order to understand these questions, we made a comparative study of impact factors with different citation time windows with the peer-reviewed scores of ophthalmologic journals indexed by Science Citation Index Expanded (SCIE) database. The peer-reviewed scores of 28 ophthalmologic journals were obtained through a self-designed survey questionnaire. Impact factors with different citation time windows (including 2IF, 3IF, 4IF, 5IF, and 6IF) of 28 ophthalmologic journals were computed and compared in accordance with each impact factor's definition and formula, using the citation analysis function of the Web of Science (WoS) database. An analysis of the correlation between impact factors with different citation time windows and peer-reviewed scores was carried out. Although impact factor values with different citation time windows were different, there was a high level of correlation between them when it came to evaluating journals. In the current study, for ophthalmologic journals' impact factors with different time windows in 2013, 3IF and 4IF seemed the ideal ranges for comparison, when assessed in relation to peer-reviewed scores. In addition, the 3-year and 4-year windows were quite consistent with the cited peak age of documents published by ophthalmologic journals. Our study is based on ophthalmology journals and we only analyze the impact factors with different citation time window in 2013, so it has yet to be ascertained whether other disciplines (especially those with a later cited peak) or other years would follow the same or similar patterns. We designed the survey questionnaire

Genome wide analysis of stress responsive WRKY transcription factors in Arabidopsis thaliana

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Shaiq Sultan

2016-04-01

Full Text Available WRKY transcription factors are a class of DNA-binding proteins that bind with a specific sequence C/TTGACT/C known as W-Box found in promoters of genes which are regulated by these WRKYs. From previous studies, 43 different stress responsive WRKY transcription factors in Arabidopsis thaliana, identified and then categorized in three groups viz., abiotic, biotic and both of these stresses. A comprehensive genome wide analysis including chromosomal localization, gene structure analysis, multiple sequence alignment, phylogenetic analysis and promoter analysis of these WRKY genes was carried out in this study to determine the functional homology in Arabidopsis. This analysis led to the classification of these WRKY family members into 3 major groups and subgroups and showed evolutionary relationship among these groups on the base of their functional WRKY domain, chromosomal localization and intron/exon structure. The proposed groups of these stress responsive WRKY genes and annotation based on their position on chromosomes can also be explored to determine their functional homology in other plant species in relation to different stresses. The result of the present study provides indispensable genomic information for the stress responsive WRKY transcription factors in Arabidopsis and will pave the way to explain the precise role of various AtWRKYs in plant growth and development under stressed conditions.

A Confirmatory Factor Analysis of Reilly's Role Overload Scale

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Thiagarajan, Palaniappan; Chakrabarty, Subhra; Taylor, Ronald D.

2006-01-01

In 1982, Reilly developed a 13-item scale to measure role overload. This scale has been widely used, but most studies did not assess the unidimensionality of the scale. Given the significance of unidimensionality in scale development, the current study reports a confirmatory factor analysis of the 13-item scale in two samples. Based on the…

Worry About Caregiving Performance: A Confirmatory Factor Analysis

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Ruijie Li

2018-03-01

Full Text Available Recent studies on the Zarit Burden Interview (ZBI support the existence of a unique factor, worry about caregiving performance (WaP, beyond role and personal strain. Our current study aims to confirm the existence of WaP within the multidimensionality of ZBI and to determine if predictors of WaP differ from the role and personal strain. We performed confirmatory factor analysis (CFA on 466 caregiver-patient dyads to compare between one-factor (total score, two-factor (role/personal strain, three-factor (role/personal strain and WaP, and four-factor models (role strain split into two factors. We conducted linear regression analyses to explore the relationships between different ZBI factors with socio-demographic and disease characteristics, and investigated the stage-dependent differences between WaP with role and personal strain by dyadic relationship. The four-factor structure that incorporated WaP and split role strain into two factors yielded the best fit. Linear regression analyses reveal that different variables significantly predict WaP (adult child caregiver and Neuropsychiatric Inventory Questionnaire (NPI-Q severity from role/personal strain (adult child caregiver, instrumental activities of daily living, and NPI-Q distress. Unlike other factors, WaP was significantly endorsed in early cognitive impairment. Among spouses, WaP remained low across Clinical Dementia Rating (CDR stages until a sharp rise in CDR 3; adult child and sibling caregivers experience a gradual rise throughout the stages. Our results affirm the existence of WaP as a unique factor. Future research should explore the potential of WaP as a possible intervention target to improve self-efficacy in the milder stages of burden.

Neutron activation analysis of copper traces: a study for sodium correction factor

International Nuclear Information System (INIS)

Tripathi, A.B.R.; Bhadkambekar, C.A.; Basu, A.K.; Chattopadhyay, N.

2007-01-01

Peak ratio correction factors for accurate quantitative determination of copper by NAA via 64 Cu radioisotope in presence of high 24 Na radioactivities has been established. Copper is the principal element as a marker of bullet residues on targets in connection to forensic ballistics cases. Reliable and precise estimation of copper by NAA either via non-destructive way or by resorting to radiochemical separation is of importance in forensic analysis for arriving at definitive inferences. However, majority of samples originating from wearing apparels, paper, leather, skin, glass or any other metal exhibit matrices contain high levels of sodium. The NAA scheme for determination of copper rests on measurements of net counts at 511 KeV which is the positron annihilation peak of 64 Cu. 24 Na also contributes significantly exactly at 511 KeV of gamma energy albeit by different mechanism i.e., by pair production. Therefore, total signal at 511 KeV is contributed by both. The easiest approach for correct estimation of copper traces has been established by the peak ratio correction factor. This has significance as both 64 Cu and 24 Na have comparable half lives, hence, as such time gap measurements cannot improve the situation. The consistency of peak ratio correction factor could be established for a particular geometry. (author)

Symptoms of delirium: an exploratory factor analytic study among referred patients.

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Jain, Gaurav; Chakrabarti, Subho; Kulhara, Parmanand

2011-01-01

Factor analytic studies of delirium symptoms among patients referred through consultation-liaison psychiatric services are rare. We examined the factor structure of delirium symptoms in referred patients and determined whether combining items from several delirium rating scales influenced the factor structure of delirium symptoms. Eighty-six patients with delirium (Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision) referred though the consultation-liaison services were assessed with structured rating scales. Nineteen symptom items extracted from the Delirium Rating Scale-Revised-98 (DRS-R-98), the Memorial Delirium Assessment Scale and the Confusional State Evaluation Scale were subjected to an exploratory (principal component) factor analysis. A second such analysis was conducted on 15 items of the DRS-R-98 for comparison. Compared with prior studies, patients were younger and the majority had hyperactive delirium. Principal components analysis identified two factors: (1) a "cognitive" factor comprising of disturbances in language, thought processes, orientation, attention, short- and long-term memory, visuospatial ability, consciousness (awareness) and perseveration accounted for 28.9% of the variance and (2) a "behavioral" factor consisting of sleep-wake cycle disturbances, delusions, perceptual disturbances, motor agitation, affect-lability, distractibility, irritability and temporal onset accounted for 18.9% of the variance. An identical factor structure was obtained with the DRS-R-98 items. Similar to previous factor analytic studies, the present study supported the existence of two principal dimensions of delirium, cognitive and behavioral. Additionally, it extended the results of earlier investigations to a wider group of patients with delirium, suggesting that these dimensions might provide important clues to the neurobiology of delirium. Copyright © 2011 Elsevier Inc. All rights reserved.

Using BMDP and SPSS for a Q factor analysis.

Science.gov (United States)

Tanner, B A; Koning, S M

1980-12-01

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

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

Science.gov (United States)

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

2017-01-01

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

Studies on thermal neutron perturbation factor needed for bulk sample activation analysis

CERN Document Server

Csikai, J; Sanami, T; Michikawa, T

2002-01-01

The spatial distribution of thermal neutrons produced by an Am-Be source in a graphite pile was measured via the activation foil method. The results obtained agree well with calculated data using the MCNP-4B code. A previous method used for the determination of the average neutron flux within thin absorbing samples has been improved and extended for a graphite moderator. A procedure developed for the determination of the flux perturbation factor renders the thermal neutron activation analysis of bulky samples of unknown composition possible both in hydrogenous and graphite moderators.

Exploring Technostress: Results of a Large Sample Factor Analysis

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Steponas Jonušauskas

2016-06-01

Full Text Available With reference to the results of a large sample factor analysis, the article aims to propose the frame examining technostress in a population. The survey and principal component analysis of the sample consisting of 1013 individuals who use ICT in their everyday work was implemented in the research. 13 factors combine 68 questions and explain 59.13 per cent of the answers dispersion. Based on the factor analysis, questionnaire was reframed and prepared to reasonably analyze the respondents’ answers, revealing technostress causes and consequences as well as technostress prevalence in the population in a statistically validated pattern. A key elements of technostress based on factor analysis can serve for the construction of technostress measurement scales in further research.

Exploring Technostress: Results of a Large Sample Factor Analysis

OpenAIRE

Jonušauskas, Steponas; Raišienė, Agota Giedrė

2016-01-01

With reference to the results of a large sample factor analysis, the article aims to propose the frame examining technostress in a population. The survey and principal component analysis of the sample consisting of 1013 individuals who use ICT in their everyday work was implemented in the research. 13 factors combine 68 questions and explain 59.13 per cent of the answers dispersion. Based on the factor analysis, questionnaire was reframed and prepared to reasonably analyze the respondents’ an...

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

Science.gov (United States)

Benligiray, Serdar; Onay, Ahmet

2017-01-01

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

Analysis of factors affecting failure of glass cermet tunnel restorations in a multi-center study.

Science.gov (United States)

Pilebro, C E; van Dijken, J W

2001-06-01

The aim of this study was to analyze factors influencing the failures of tunnel restorations performed with a glass cermet cement (Ketac Silver). Caries activity, lesion size, tunnel cavity opening size, partial or total tunnel, composite lamination or operating time showed no significant correlation to failure rate. Twelve dentists in eight clinics clinically experienced and familiar with the tunnel technique placed 374 restorations. The occlusal sections of fifty percent of the restorations were laminated with hybrid resin composite. The results of the yearly clinical and radiographic evaluations over the course of 3 years were correlated to factors that could influence the failure rate using logistic regression analysis. At the 3-year recall a cumulative number of 305 restorations were available. The cumulative replacement rate was 20%. The main reasons for replacement were marginal ridge fracture (14%) and dentin caries (3%). Another 7% of the restorations which had not been replaced were classified as failures because of untreated dentin caries. The only significant variable observed was the individual failure rate of the participating dentists varying between 9 and 50% (p=0.013).

The Analysis of Factors Influencing Effectivenes of Property Taxes in Karanganyar Regency

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Endang Brotojoyo

2018-03-01

Full Text Available The purpose of this study was to test empirically Effect of Compensation, Motivation and External Factors To Performance Officer With Property Taxes Voting in the District Effectiveness Matesih Karanganyar. The analysis technique used is using validity and reliability test, linearity test, regression analysis, path analysis, t test, F test, test the coefficient of determination and correlation analysis. Compensation Hypothesis Test Results significantly influence the effectiveness of tax collection. Motivation significantly influences the effectiveness of tax collection. External factors do not significant effect on effectiveness of tax collection. Compensation significant effect on the performance of Officers. Motivation significant effect on the performance of the Property Taxes polling clerk. External factors do not significant effect on the performance of Officers. Effectiveness of tax collection clerk significant effects on performance. F test results can be concluded jointly variable compensation, motivation, and external factors affecting the effectiveness of tax collection performance. The R2 total of 0,974 means that the performance of the Property Taxes in the district polling officer Matesih Karanganyar explained by the variable compensation, motivation, external factors and the effectiveness of tax collection amounted to 97.4%. The results of path analysis showed that the effective compensation and motivation through a direct path, while external factors are not effective for direct and indirect pathways.

Factors Affecting Surgical Decision-making—A Qualitative Study

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Caroline Gunaratnam

2018-01-01

Full Text Available Background Guidelines and Class 1 evidence are strong factors that help guide surgeons’ decision-making, but dilemmas exist in selecting the best surgical option, usually without the benefit of guidelines or Class 1 evidence. A few studies have discussed the variability of surgical treatment options that are currently available, but no study has examined surgeons’ views on the influential factors that encourage them to choose one surgical treatment over another. This study examines the influential factors and the thought process that encourage surgeons to make these decisions in such circumstances. Methods Semi-structured face-to-face interviews were conducted with 32 senior consultant surgeons, surgical fellows, and senior surgical residents at the University of Toronto teaching hospitals. An e-mail was sent out for volunteers, and interviews were audio-recorded, transcribed verbatim, and subjected to thematic analysis using open and axial coding. Results Broadly speaking there are five groups of factors affecting surgeons’ decision-making: medical condition, information, institutional, patient, and surgeon factors. When information factors such as guidelines and Class 1 evidence are lacking, the other four groups of factors—medical condition, institutional, patient, and surgeon factors (the last-mentioned likely being the most powerful—play a significant role in guiding surgical decision-making. Conclusions This study is the first qualitative study on surgeons’ perspectives on the influential factors that help them choose one surgical treatment option over another for their patients.

Work Disability among Employees with Diabetes: Latent Class Analysis of Risk Factors in Three Prospective Cohort Studies.

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Marianna Virtanen

Full Text Available Studies of work disability in diabetes have examined diabetes as a homogeneous disease. We sought to identify subgroups among persons with diabetes based on potential risk factors for work disability.Participants were 2,445 employees with diabetes from three prospective cohorts (the Finnish Public Sector study, the GAZEL study, and the Whitehall II study. Work disability was ascertained via linkage to registers of sickness absence and disability pensions during a follow-up of 4 years. Study-specific latent class analysis was used to identify subgroups according to prevalent comorbid disease and health-risk behaviours. Study-specific associations with work disability at follow-up were pooled using fixed-effects meta-analysis.Separate latent class analyses for men and women in each cohort supported a two-class solution with one subgroup (total n = 1,086; 44.4% having high prevalence of chronic somatic diseases, psychological symptoms, obesity, physical inactivity and abstinence from alcohol and the other subgroup (total n = 1,359; 55.6% low prevalence of these factors. In the adjusted meta-analyses, participants in the 'high-risk' group had more work disability days (pooled rate ratio = 1.66, 95% CI 1.38-1.99 and more work disability episodes (pooled rate ratio = 1.33, 95% CI 1.21-1.46. These associations were similar in men and women, younger and older participants, and across occupational groups.Diabetes is not a homogeneous disease in terms of work disability risk. Approximately half of people with diabetes are assigned to a subgroup characterised by clustering of comorbid health conditions, obesity, physical inactivity, abstinence of alcohol, and associated high risk of work disability; the other half to a subgroup characterised by a more favourable risk profile.

Bayes factor design analysis: Planning for compelling evidence.

Science.gov (United States)

Schönbrodt, Felix D; Wagenmakers, Eric-Jan

2018-02-01

A sizeable literature exists on the use of frequentist power analysis in the null-hypothesis significance testing (NHST) paradigm to facilitate the design of informative experiments. In contrast, there is almost no literature that discusses the design of experiments when Bayes factors (BFs) are used as a measure of evidence. Here we explore Bayes Factor Design Analysis (BFDA) as a useful tool to design studies for maximum efficiency and informativeness. We elaborate on three possible BF designs, (a) a fixed-n design, (b) an open-ended Sequential Bayes Factor (SBF) design, where researchers can test after each participant and can stop data collection whenever there is strong evidence for either [Formula: see text] or [Formula: see text], and (c) a modified SBF design that defines a maximal sample size where data collection is stopped regardless of the current state of evidence. We demonstrate how the properties of each design (i.e., expected strength of evidence, expected sample size, expected probability of misleading evidence, expected probability of weak evidence) can be evaluated using Monte Carlo simulations and equip researchers with the necessary information to compute their own Bayesian design analyses.

Risk Factors For Ectopic Pregnancy : A Case Control Study

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Deshmukh J.S

1999-01-01

Full Text Available Research question: Which are the risk factors for ectopic pregnancy . Objective: To study the strength of association between hypothesised risk factors and ectopic pregnancy. Study design: Unmatched case- control study. Setting: Government Medical College, Hospital, Nagpur. Participants: 133 cases of ectopic pregnancy and equal number of controls (non pregnant women admitted to study hospital. Study variables : Pelvic inflammatory diseases, sexually transmitted diseases, IUD use at conception , past use of IUD, prior ectopic pregnancy, OC pills use at the time of conception, past use of OC pills, induced abortion, spontaneous abortion, infertility and pelvic and abdominal surgery. Statistical analysis: Odds ratios & their 95% CI, Pearson’s chi square test, unconditional logistic regression analysis and population attributable risk proportion. Results : Use of IUD at conception, prior ectopic pregnancy , pelvic inflammatory disease, sexually transmitted diseases, infertility, OC pills use at the time of conception, past use of IUD and induced abortion were found to be significantly associated with ectopic pregnancy. Conclusion: Identification of these risk factors for etopic pregnancy shall help in early detection and appropriate management in an individual case and it may help in devising a comprehensive preventive strategy for ectopic pregnancy

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

Science.gov (United States)

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

2011-01-01

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

Using Factor Analysis to Identify Topic Preferences Within MBA Courses

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Earl Chrysler

2003-02-01

Full Text Available This study demonstrates the role of a principal components factor analysis in conducting a gap analysis as to the desired characteristics of business alumni. Typically, gap analyses merely compare the emphases that should be given to areas of inquiry with perceptions of actual emphases. As a result, the focus is upon depth of coverage. A neglected area in need of investigation is the breadth of topic dimensions and their differences between the normative (should offer and the descriptive (actually offer. The implications of factor structures, as well as traditional gap analyses, are developed and discussed in the context of outcomes assessment.

The Columbia Impairment Scale: Factor Analysis Using a Community Mental Health Sample

Science.gov (United States)

Singer, Jonathan B.; Eack, Shaun M.; Greeno, Catherine M.

2011-01-01

Objective: The objective of this study was to test the factor structure of the parent version of the Columbia Impairment Scale (CIS) in a sample of mothers who brought their children for community mental health (CMH) services (n = 280). Method: Confirmatory factor analysis (CFA) was used to test the fit of the hypothesized four-factor structure…

Risk factors associated with lipomyelomeningocele: a case-control study.

Science.gov (United States)

Esmaeili, Arash; Hanaei, Sara; Fadakar, Kaveh; Dadkhah, Sahar; Arjipour, Mahdi; Habibi, Zohreh; Nejat, Farideh; El Khashab, Mostafa

2013-01-01

In general, it seems that both genetic and environmental factors play important roles in the induction of neural tube defects. Lipomyelomeningocele (LipoMMC) is a rather common type of closed neural tube defect, but only limited studies have investigated the potential risk factors of this anomaly. Therefore, the purpose of this case-control study was to investigate the risk factors involved in LipoMMC formation. Various risk factors were evaluated in 35 children between 1 month and 10 years of age with LipoMMC in a hospital-based case-control study. The 2 control arms consisted of 35 children with myelomeningocele (MMC group) and 35 children with congenital anomalies other than central nervous system problems (control group). All groups were matched for age and visited the same hospital. A structured questionnaire was used for the collection of all data, including the mothers' weight and height during pregnancy, education, reproductive history, previous abortions, and socioeconomic status, as well as the parents' consanguinity and family history of the same anomalies. Univariate analysis of the children with LipoMMC compared to the control group showed that the use of periconceptional folic acid supplementation was significantly lower in the MMC and LipoMMC groups compared to the control group. In addition, comparison of the MMC and control groups revealed statistically significant differences regarding the use of folic acid and maternal obesity. In multivariate analysis, use of folic acid in the periconceptional period and during the first trimester was an independent risk factor for LipoMMC and MMC. Furthermore, maternal obesity was a significantly positive risk factor for MMC. The probable risk factors for LipoMMC were investigated in this case-control study. Consumption of folic acid in the periconceptional period and during the first trimester is an independent protective factor against LipoMMC. It seems that larger studies are needed to examine other possible

Human factors analysis of incident/accident report

International Nuclear Information System (INIS)

Kuroda, Isao

1992-01-01

Human factors analysis of accident/incident has different kinds of difficulties in not only technical, but also psychosocial background. This report introduces some experiments of 'Variation diagram method' which is able to extend to operational and managemental factors. (author)

Logistic Regression and Path Analysis Method to Analyze Factors influencing Students’ Achievement

Science.gov (United States)

Noeryanti, N.; Suryowati, K.; Setyawan, Y.; Aulia, R. R.

2018-04-01

Students' academic achievement cannot be separated from the influence of two factors namely internal and external factors. The first factors of the student (internal factors) consist of intelligence (X1), health (X2), interest (X3), and motivation of students (X4). The external factors consist of family environment (X5), school environment (X6), and society environment (X7). The objects of this research are eighth grade students of the school year 2016/2017 at SMPN 1 Jiwan Madiun sampled by using simple random sampling. Primary data are obtained by distributing questionnaires. The method used in this study is binary logistic regression analysis that aims to identify internal and external factors that affect student’s achievement and how the trends of them. Path Analysis was used to determine the factors that influence directly, indirectly or totally on student’s achievement. Based on the results of binary logistic regression, variables that affect student’s achievement are interest and motivation. And based on the results obtained by path analysis, factors that have a direct impact on student’s achievement are students’ interest (59%) and students’ motivation (27%). While the factors that have indirect influences on students’ achievement, are family environment (97%) and school environment (37).

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

Science.gov (United States)

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.

A study on critical success factors on building IT based flat organization: A case study of Mellat Bank

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Farajollah Rahnavard

2014-07-01

Full Text Available A flat organization is a firm that has an organizational structure with few or no levels of middle management between employee and executives. The idea is to take advantage of well-trained workers when they are more directly involved in the decision making process, rather than closely supervised by various layers of management. This paper presents an empirical investigation to determine critical success factors on building information technology (IT based flat organization in a case study of banking industry. Using principal component analysis, the study applies factor analysis for two internal and external factors. In terms of internal factors, there are three factors including Processes and the electronic decision making, Teaching and Electronic Learning and Work in IT. In addition, the study has detected four factors including Electronic Supply, IT structure, Appropriate IT usage and Electronic Communication.

Nominal Performance Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M.A. Wasiolek

2005-01-01

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standards. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis'' (Figure 1-1). The objectives of this analysis are to develop BDCFs for the

Confirmatory Factor Analysis in the study of the Structure and Stability of Assessment Instruments: An example with the Self-Esteem Questionnaire (CA-14

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Juan Herrero

2010-12-01

Full Text Available This research presents a study of the factor structure and temporal stability of the Self-Esteem Questionnaire (CA-14 using Confirmatory Factor Analysis (CFA techniques. The paper pretends to offer a potential guide to researchers, paying special attention to data requirements, estimation methods suggested in the literature, recommended fit indices and other circumstances that need to be taken into account when estimating CFA models. Also, various methodological strategies are shown during the implementation of CFA models: correlated errors, use of parameter constraints, multigroup analysis, etc.

Sustainability Perceptions in Romanian Non-Profit Organizations: An Exploratory Study Using Success Factor Analysis

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Sebastian Ion Ceptureanu

2018-01-01

Full Text Available This paper analyses sustainability perceptions in Romanian non-profits by investigating 81 non-profits managers and board members. Using a multidimensional sustainability measurement framework, Success Factor Analysis, as a conceptual model, we measured perceptions on 5 critical sustainability factors: People, Business Model, Operations, Strategy and Culture and concluded that there are significant differences in the perceptions of sustainability depending on respondents’ previous failure experiences. While those which previously experienced failure adopt a long-term approach based on marketization, clear accountability standards and rely on strategy, while the others prefer a short-term approach, focused more on non-profits operations and focus on human resources.

Analysis of technological, institutional and socioeconomic factors ...

African Journals Online (AJOL)

Analysis of technological, institutional and socioeconomic factors that influences poor reading culture among secondary school students in Nigeria. ... Proliferation and availability of smart phones, chatting culture and social media were identified as technological factors influencing poor reading culture among secondary ...

Studying risk factors associated with Human Leptospirosis

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Ramachandra Kamath

2014-01-01

Full Text Available Background: Leptospirosis is one of the most under diagnosed and underreported disease in both developed and developing countries including India. It is established that environmental conditions and occupational habit of the individuals put them at risk of acquiring disease, which varies from community to community. Various seroprevalence studies across the world have documented emerging situation of this neglected tropical disease, but limited have probed to identify the risk factors, especially in India. Objectives: The objective of this study was to identify the environmental and occupational risk factors associated with the disease in Udupi District. Materials and Methods: This population-based case-control study was carried out in Udupi, a District in Southern India from April 2012 until August 2012. Udupi is considered to be endemic for Leptospirosis and reported 116 confirmed cases in the year 2011. Seventy of 116 laboratory confirmed cases and 140 sex matched neighborhood healthy controls participated in the study. A predesigned, semi-structured and validated questionnaire was used for data collection through house to house visit and observations were noted about environmental conditions. Univariate analysis followed by multivariate analysis (back ward conditional logistic regression was performed by using STATA version 9.2 (StataCorp, College Station, TX, USA to identify potential risk factors. Results: Occupational factors such as outdoor activities (matched odds ratio [OR] of 3.95, 95% confidence interval [CI]: 1.19-13.0, presence of cut or wound at body parts during work (matched OR: 4.88, CI: 1.83-13.02 and environmental factors such as contact with rodents through using the food materials ate by rat (matched OR: 4.29, CI: 1.45-12.73 and contact with soil or water contaminated with urine of rat (matched OR: 4.58, CI: 1.43-14.67 were the risk factors identified to be associated with disease. Conclusion: Leptospirosis is still

Case Study on Influence Factor Trend Analysis of the Accidents and Events of Nuclear Power Plants by applying Nuclear Safety Culture Framework

International Nuclear Information System (INIS)

Park, J. Y.; Park, Y. W.; Park, H.G.

2016-01-01

This study 1) established the standard based on frameworks of safety culture principles that show safety culture promotion goals, 2) analyzed the linkages with the frameworks that were established by analyzing each incident cause and weak point from selected 268 cases(rating over INES grade 1) among 4,088 cases (as of April 1, 2015). The 4,088 cases were selected as a result of database analysis from 702 accidents recorded in accident and rating evaluation reports that were published in the National Nuclear Safety Commission and overseas IRS (International Reporting System for operating Experience), and 3) finally conducted a trend analysis studies with these comprehensive results. From the investigations, followings were concluded. 1) In order to analyze the safety culture, analysis methodology is required. 2) Analytical methodology for building sustainable safety culture promoting a virtuous cycle system was developed 3) Among variety of process input data, 970 domestic and overseas incidents were selected as targets and 502 accidents were classified as safety culture related events by utilizing screen filter of IAEA GS-G-3.5 Appendix I and Framework (Nuclear Safety Culture Base Frame) developed by BEES, Inc. for safety culture analysis method. 4) As a result, complex safety culture influence factors for the one reason which was difficult to separate by conventional methods was able to be analyzed. 5) The cumulative data through the system was results of virtuous trend analysis rather than temporary results. Thus, it could be unique cultural factors of the domestic industry and could derive trend differences for domestic safety culture factors accordingly

Case Study on Influence Factor Trend Analysis of the Accidents and Events of Nuclear Power Plants by applying Nuclear Safety Culture Framework

Energy Technology Data Exchange (ETDEWEB)

Park, J. Y.; Park, Y. W.; Park, H.G. [KAIST, Daejeon (Korea, Republic of)

2016-05-15

This study 1) established the standard based on frameworks of safety culture principles that show safety culture promotion goals, 2) analyzed the linkages with the frameworks that were established by analyzing each incident cause and weak point from selected 268 cases(rating over INES grade 1) among 4,088 cases (as of April 1, 2015). The 4,088 cases were selected as a result of database analysis from 702 accidents recorded in accident and rating evaluation reports that were published in the National Nuclear Safety Commission and overseas IRS (International Reporting System for operating Experience), and 3) finally conducted a trend analysis studies with these comprehensive results. From the investigations, followings were concluded. 1) In order to analyze the safety culture, analysis methodology is required. 2) Analytical methodology for building sustainable safety culture promoting a virtuous cycle system was developed 3) Among variety of process input data, 970 domestic and overseas incidents were selected as targets and 502 accidents were classified as safety culture related events by utilizing screen filter of IAEA GS-G-3.5 Appendix I and Framework (Nuclear Safety Culture Base Frame) developed by BEES, Inc. for safety culture analysis method. 4) As a result, complex safety culture influence factors for the one reason which was difficult to separate by conventional methods was able to be analyzed. 5) The cumulative data through the system was results of virtuous trend analysis rather than temporary results. Thus, it could be unique cultural factors of the domestic industry and could derive trend differences for domestic safety culture factors accordingly.

Parallel factor analysis PARAFAC of process affected water

Energy Technology Data Exchange (ETDEWEB)

Ewanchuk, A.M.; Ulrich, A.C.; Sego, D. [Alberta Univ., Edmonton, AB (Canada). Dept. of Civil and Environmental Engineering; Alostaz, M. [Thurber Engineering Ltd., Calgary, AB (Canada)

2010-07-01

A parallel factor analysis (PARAFAC) of oil sands process-affected water was presented. Naphthenic acids (NA) are traditionally described as monobasic carboxylic acids. Research has indicated that oil sands NA do not fit classical definitions of NA. Oil sands organic acids have toxic and corrosive properties. When analyzed by fluorescence technology, oil sands process-affected water displays a characteristic peak at 290 nm excitation and approximately 346 nm emission. In this study, a parallel factor analysis (PARAFAC) was used to decompose process-affected water multi-way data into components representing analytes, chemical compounds, and groups of compounds. Water samples from various oil sands operations were analyzed in order to obtain EEMs. The EEMs were then arranged into a large matrix in decreasing process-affected water content for PARAFAC. Data were divided into 5 components. A comparison with commercially prepared NA samples suggested that oil sands NA is fundamentally different. Further research is needed to determine what each of the 5 components represent. tabs., figs.

The driving factors behind coal demand in China from 1997 to 2012: An empirical study of input-output structural decomposition analysis

International Nuclear Information System (INIS)

Wu, Ya; Zhang, Wanying

2016-01-01

With the rapid development of economy, especially the constant progress in industrialisation and urbanisation, China's energy consumption has increased annually. Coal consumption, which accounts for about 70% of total energy consumption, is of particular concern. Hence, it is crucial to study the driving factors behind coal demand in China. This work uses an input-output structural decomposition analysis (I-O SDA) model to decompose the increments of coal demand in China from 1997 to 2012 into the sum of the weighted average for eight driving factors from three aspects, including: domestic demand, foreign trade and industrial upgrading. Results show that: during the research period, the demand for coal increases by 153.3%, which is increased by 185.4% and 76.4% respectively due to the driving forces of domestic demand and foreign trade; in addition, industrial upgrading can effectively restrain the growth in coal demand with a contribution rate of −108.6%. On this basis, we mainly studied the driving factors of coal demand in six high energy-consuming industries, namely the electrical power, energy processing, metals, mining, building materials and chemical industries. Finally, we proposed targeted policy suggestions for the realisation of energy conservation and emissions reduction in China. - Highlights: •The driving factors behind coal demand in China from 1997 to 2012 are studied. •An input-output structural decomposition analysis is developed. •A fresh perspective of domestic demand, foreign trade, and industrial upgrading is employed. •The influences of these affecting factors on China's coal demand from six high energy-consuming industries are investigated. •Targeted policy suggestions for energy conservation and emissions reduction are suggested.

Genomewide analysis of TCP transcription factor gene family in ...

Indian Academy of Sciences (India)

Home; Journals; Journal of Genetics; Volume 93; Issue 3. Genomewide ... Teosinte branched1/cycloidea/proliferating cell factor1 (TCP) proteins are a large family of transcriptional regulators in angiosperms. They are ... To the best of our knowledge, this is the first study of a genomewide analysis of apple TCP gene family.

Assessment of modern methods of human factor reliability analysis in PSA studies

International Nuclear Information System (INIS)

Holy, J.

2001-12-01

The report is structured as follows: Classical terms and objects (Probabilistic safety assessment as a framework for human reliability assessment; Human failure within the PSA model; Basic types of operator failure modelled in a PSA study and analyzed by HRA methods; Qualitative analysis of human reliability; Quantitative analysis of human reliability used; Process of analysis of nuclear reactor operator reliability in a PSA study); New terms and objects (Analysis of dependences; Errors of omission; Errors of commission; Error forcing context); and Overview and brief assessment of human reliability analysis (Basic characteristics of the methods; Assets and drawbacks of the use of each of HRA method; History and prospects of the use of the methods). (P.A.)

Teaching Confirmatory Factor Analysis to Non-Statisticians: A Case Study for Estimating Composite Reliability of Psychometric Instruments

Science.gov (United States)

Gajewski, Byron J.; Jiang, Yu; Yeh, Hung-Wen; Engelman, Kimberly; Teel, Cynthia; Choi, Won S.; Greiner, K. Allen; Daley, Christine Makosky

2013-01-01

Texts and software that we are currently using for teaching multivariate analysis to non-statisticians lack in the delivery of confirmatory factor analysis (CFA). The purpose of this paper is to provide educators with a complement to these resources that includes CFA and its computation. We focus on how to use CFA to estimate a “composite reliability” of a psychometric instrument. This paper provides guidance for introducing, via a case-study, the non-statistician to CFA. As a complement to our instruction about the more traditional SPSS, we successfully piloted the software R for estimating CFA on nine non-statisticians. This approach can be used with healthcare graduate students taking a multivariate course, as well as modified for community stakeholders of our Center for American Indian Community Health (e.g. community advisory boards, summer interns, & research team members). The placement of CFA at the end of the class is strategic and gives us an opportunity to do some innovative teaching: (1) build ideas for understanding the case study using previous course work (such as ANOVA); (2) incorporate multi-dimensional scaling (that students already learned) into the selection of a factor structure (new concept); (3) use interactive data from the students (active learning); (4) review matrix algebra and its importance to psychometric evaluation; (5) show students how to do the calculation on their own; and (6) give students access to an actual recent research project. PMID:24772373

Nominal Performance Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M.A. Wasiolek

2003-07-25

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports (BSC 2003 [DIRS 160964]; BSC 2003 [DIRS 160965]; BSC 2003 [DIRS 160976]; BSC 2003 [DIRS 161239]; BSC 2003 [DIRS 161241]) contain detailed description of the model input parameters. This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs and conversion factors for the TSPA. The BDCFs will be used in performance assessment for calculating annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle activity in groundwater and the annual dose from beta- and photon-emitting radionuclides.

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

Science.gov (United States)

Wang, H-Y; Lin, C-K

2015-10-01

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

Salivary SPECT and factor analysis in Sjoegren's syndrome

International Nuclear Information System (INIS)

Nakamura, T.; Oshiumi, Y.; Yonetsu, K.; Muranaka, T.; Sakai, K.; Kanda, S.; National Fukuoka Central Hospital

1991-01-01

Salivary SPECT and factor analysis in Sjoegren's syndrome were performed in 17 patients and 6 volunteers as controls. The ability of SPECT to detect small differences in the level of uptake can be used to separate glands from background even when uptake is reduced as in the patients with Sjoegren's syndrome. In control and probable Sjoegren's syndrome groups the uptake ratio of the submandibular gland to parotid gland on salivary SPECT (S/P ratio) was less than 1.0. However, in the definite Sjoergren's syndrome group, the ratio was more than 1.0. Moreover, the ratio in all patients with sialectasia, which is characteristic of Sjoegren's syndrome, was more than 1.0. Salivary factor analysis of normal parotid glands showed slowly increasing patterns of uptake and normal submandibular glands had rapidly increasing patterns of uptake. However, in the definite Sjoegren's syndrome group, the factor analysis patterns were altered, with slowly increasing patterns dominating both in the parotid and submandibular glands. These results suggest that the S/P ratio in salivary SPECT and salivary factor analysis provide additional radiologic criteria in diagnosing Sjoegren's syndrome. (orig.)

Analysis of risk factors in the development of retinopathy of prematurity

Directory of Open Access Journals (Sweden)

Knežević Sanja

2011-01-01

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

Analysis of the Factors Affecting Resistance to Changes in Management Accounting Systems

Directory of Open Access Journals (Sweden)

Rodrigo Angonese

2014-12-01

Full Text Available Despite changes in the environment and management accounting practices, studies indicate that management accounting systems do not change or change at a much slower rate than expected. The stability of the management accounting systems used by companies may relate to resistance to changing these systems. This study analyzes the factors that contribute to resistance to implementing an integrated management system from the perspective of institutional theory, grounded in the old institutional economics. Methodologically, this study provides a qualitative assessment of the problem and a descriptive analysis of the resistance factors through a case-study approach. The data were collected using semi-structured interviews and analyzed through content analysis. Two companies were selected for this study due to their differing characteristics. The following seven factors were analyzed for resistance to implementing integrated management systems: institutional power, ontological insecurity, trust, inertia, lack of knowledge, acceptance of routines and decoupling. However, there was no evidence to characterize hierarchical power. The research findings indicate that changing management accounting systems, through the implementation of an integrated management system, faces internal resistance in these organizations. Each factor varies in intensity but is permanently present in these companies, such as ontological insecurity, trust, inertia, lack of knowledge, acceptance of routines and decoupling. These factors are awakened when the change process begins and, if they gather enough force, can stop the change.

A study on effective factors on employee motivation

Directory of Open Access Journals (Sweden)

Hassan Ghodrati

2013-06-01

Full Text Available Management is often considered as collaboration with others and this requires knowing about employers' behavior and the factors influencing their behaviors to motivate them for obtaining some predicted aims. This paper presents a study to detect important factors influencing motivation of some employees who work for a public offices in city of Kashan, Iran. The study designs a questionnaire in Likert scale and distributes it among 160 randomly selected participants. The questions are divided into two groups of management performance and motivational factors. To evaluate the effect of demographic factors on the quality of respondents' statements, a rating analysis based on Kruskal–Wallis test is used. To measure the effective vote, the motivation levels are divided into three groups of highly motivated, motivated and not motivated and they are analyzed based on rating mean variance with freedman scale. The results indicate that interesting job, job security, good salary and benefits and promotions, etc. are important factors to impact on the employers' motivation. For the newly – employed personal, job security is the most important motivation factor and for old – established employees, job attractive and sense of being considered is the most effective factor.

Confirmatory factor analysis of the neck disability index in a whiplash population indicates a one-factor model is viable

OpenAIRE

Gabel, Charles P.; Cuesta-Vargas, Antonio I.; Barr, Sebastian; Winkeljohn Black, Stephanie; Osborne, Jason W.; Melloh, Markus

2016-01-01

Purpose The neck disability index (NDI) as a 10-item patient reported outcome (PRO) measure is the most commonly used whiplash associated disorders (WAD) assessment tool. However, statistical rigor and factor structure are not definitive. To date, confirmatory factor analysis (CFA) has not examined whether the factor structure generalizes across different groups (e.g., WAD versus non-WAD). This study aimed to determine the psychometric properties of the NDI in these population groups.

Analysis Of The Social-Economic Factors Affecting Output Of Nihort ...

African Journals Online (AJOL)

Analysis Of The Social-Economic Factors Affecting Output Of Nihort Fruit Adoptors And ... A moderate family size of 6-7 family members are in adopters and ... Extension agents presence is necessary in the study area so as to organise training ...

A risk factor analysis of healthcare-associated fungal infections in an intensive care unit: a retrospective cohort study

Directory of Open Access Journals (Sweden)

Yang Su-Pen

2013-01-01

Full Text Available Abstract Background The incidence of fungal healthcare-associated infection (HAI has increased in a major teaching hospital in the northern part of Taiwan over the past decade, especially in the intensive care units (ICUs. The purpose of this study was to determine the factors that were responsible for the outbreak and trend in the ICU. Methods Surveillance fungal cultures were obtained from “sterile” objects, antiseptic solutions, environment of infected patients and hands of medical personnel. Risk factors for comparison included age, gender, admission service, and total length of stay in the ICU, Acute Physiology and Chronic Health Evaluation (APACHE II scores at admission to the ICU, main diagnosis on ICU admission, use of invasive devices, receipt of hemodialysis, total parenteral nutrition (TPN use, history of antibiotic therapy before HAI or during ICU stay in no HAI group, and ICU discharge status (ie, dead or alive. Univariable analysis followed by multiple logistic regression analysis was performed to identify the independent risk factors for ICU fungal HAIs and ICU mortality. Results There was a significant trend in ICU fungal HAIs from 1998 to 2009 (P Candida albicans (27.3%, Candida tropicalis (6.6%, Candida glabrata (6.6%, Candida parapsilosis (1.9%, Candida species (0.8%, and other fungi (1.9%. Candida albicans accounted for 63% of all Candida species. Yeasts were found in the environment of more heavily infected patients. The independent risk factors (P P  Conclusions There was a secular trend of an increasing number of fungal HAIs in our ICU over the past decade. Patients with ICU fungal HAIs had a significantly higher mortality rate than did patients without ICU HAIs. Total parenteral nutrition was a significant risk factor for all types of ICU fungal HAIs, and its use should be monitored closely.

An exploratory study to identify critical factors of innovation culture in organizations

Directory of Open Access Journals (Sweden)

Hamed Asgari

2013-07-01

Full Text Available During the past two decades, there has been a growing trend on knowledge-based organizations. Innovation, on the other hand, plays essential role on building competitive business units. In this paper, we present an exploratory study to identify critical factors of innovation culture in organizations. We detect important factors influencing innovation culture in construction industry based on the implementation of factor analysis. The proposed study designs a questionnaire and distributes it among 400 experts who are involved in construction industry. Cronbach alpha has been calculated as 0.779, which validates the overall questionnaire. The results of factor analysis have indicated that six factors of building cultural infrastructures, education, organizational vision, established culture, strategic culture and flexible culture are the most important items influencing innovation culture.

Nominal Performance Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M.A. Wasiolek

2005-04-28

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standards. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis

Applying total interpretive structural modeling to study factors affecting construction labour productivity

Directory of Open Access Journals (Sweden)

Sayali Shrikrishna Sandbhor

2014-03-01

Full Text Available Construction sector has always been dependent on manpower. Most of the activities carried out on any construction site are labour intensive. Since productivity of any project depends directly on productivity of labour, it is a prime responsibility of the employer to enhance labour productivity. Measures to improve the same depend on analysis of positive and negative factors affecting productivity. Major attention should be given to factors that decrease the productivity of labour. Factor analysis thus is an integral part of any study aiming to improve productivity.  Interpretive structural modeling is a methodology for identifying and summarizing relationships among factors which define an issue or problem. It provides a means to arrange the factors in an order as per their complexity. This study attempts to use the latest version of interpretive structural modeling i.e. total interpretive structural modeling to analyze factors negatively affecting construction labour productivity. It establishes interpretive relationship among these factors facilitating improvement in the overall productivity of construction site.

Analysis of Learning Environment Factors Based on Maslow’s Hierarchy of Needs

Directory of Open Access Journals (Sweden)

Košir Katja

2013-09-01

Full Text Available This paper provides a new analysis of some learning environment factors from the point of view of one of the most established motivational models, i.e. Maslow’s hierarchy of needs. For a teacher, this model can represent a meaningful tool for the analysis of the potential factors of pupils’ inadequate school adjustment. Some psychological constructs that can be conceptualized as learning environment factors are presented at specific levels of needs. As regards the level of physiological needs, this paper provides an overview of research studies on ergonomic factors of learning environment. As for safety needs, the paper outlines the concepts of classroom management and peer-to-peer violence, and presents some main research findings in both fields. The analysis regarding the level of love and belonging includes aspects of positive classroom climate and the concept of pupils’ social acceptance. Contemporary findings about the development of pupil’s academic self-concept are presented within the self-esteem and achievements needs. Flow is considered to be one of key factors that help teacher satisfy the self-actualization needs and stimulate pupils’ personal development. On the basis of this analysis, some implications and recommendations are given to help teachers efficiently encourage an integrated approach to pupil development.

The General Factor of Personality: A meta-analysis of Big Five intercorrelations and a criterion-related validity study

NARCIS (Netherlands)

van der Linden, D.; te Nijenhuis, J.; Bakker, A.B.

2010-01-01

Recently, it has been proposed that a General Factor of Personality (GFP) occupies the top of the hierarchical personality structure. We present a meta-analysis (K = 212, total N = 144,117) on the intercorrelations among the Big Five personality factors (Openness, Conscientiousness, Extraversion,

Analysis about factors affecting the degree of damage of buildings in earthquake

International Nuclear Information System (INIS)

Jia, Jing; Yan, Jinghong

2015-01-01

Earthquakes have been affecting human's safety through human's history. Previous studies on earthquake, mostly, focused on the performance of buildings or evaluating damages. This paper, however, compares different factors that have influence on the damage of buildings with a case study in Wenchuan earthquake, using multiple linear regression methodology, so as to identify to what extend this factors influence the buildings’ damages, then give the rank of importance of these factors. In this process, authors take the type of structure as a dummy variable to compare the degree of damages caused by different types of structure, which were barely studied before. Besides, Factor Analysis Methodology(FA) will be adapted to classify factors, the results of which will simplify later study. The outcome of this study would make a big difference in optimizing the seismic design and improving residential seismic quality. (paper)

A Study on Factors Affecting Strength of Solidified Peat through XRD and FESEM Analysis

Science.gov (United States)

Rahman, J. A.; Napia, A. M. A.; Nazri, M. A. A.; Mohamed, R. M. S. R.; Al-Geethi, A. S.

2018-04-01

Peat is soft soil that often causes multiple problems to construction. Peat has low shear strength and high deformation characteristics. Thus, peat soil needs to be stabilized or treated. Study on peat stabilization has been conducted for decades with various admixtures and mixing formulations. This project intends to provide an overview of the solidification of peat soil and the factors that affecting the strength of solidified peat soil. Three types of peats which are fabric, hemic and sapric were used in this study to understand the differences on the effect. The understanding of the factors affecting strength of solidified peat in this study is limited to XRD and FESEM analysis only. Peat samples were collected at Pontian, Johor and Parit Raja, Johor. Peat soil was solidified using fly ash, bottom ash and Portland cement with two mixing formulation following literature review. The solidified peat were cured for 7 days, 14 days, 28 days and 56 days. All samples were tested using Unconfined Compressive Strength Test (UCS), X-ray diffraction (XRD) and Field Emission Scanning Electron Microscope (FESEM). The compressive strength test of solidified peat had shown consistently increase of sheer strength, qu for Mixing 1 while decrease of its compressive strength value for Mixing 2. All samples were tested and compared for each curing days. Through XRD, it is found that all solidified peat are dominated with pargasite and richterite. The highest qu is Fabric Mixing 1(FM1) with the value of 105.94 kPa. This sample were proven contain pargasite. Samples with high qu were observed to be having fly ash and bottom ash bound together with the help of pargasite. Sample with decreasing strength showed less amount of pargasite in it. In can be concluded that XRD and FESEM findings are in line with UCS values.

INTRINSIC FACTORS AND FIRM FINANCIAL ANALYSIS WITH TRIPPLE BOTTOM LINES AS INTERVENING VARIABLE AGAINST FIRM VALUE Empirical Studies on Property and Real Estate Companies Year 2010-2013

Directory of Open Access Journals (Sweden)

Mia Andika Sari

2016-09-01

Full Text Available This research conducted to examine the influence of intrinsic factors which being peroxided with Capital Structure, Firm Size, Firm Age and Financial factors that being peroxided with liquidity, profitability also with another activities using triple bottom lines as Intervening Variable against Firm Value of Property Industries. The data that being used in this study were obtained from published financial statements during the period 2010 to 2013, as well as annual reports that can be accessed through the IDX website. Data analysis technique used in this study is a regression with panel data and path analysis. The results of this research showed that intrinsic factors and financial variables have a significant influence on the firm value, as well as intrinsic factors and financial variables have a significant influence on the triple bottom lines. From the results of path analysis demonstrated that the indirect effect using the triple bottom lines as a intervening variable was greater than the direct effect.

Beyond factor analysis: Multidimensionality and the Parkinson's Disease Sleep Scale-Revised.

Directory of Open Access Journals (Sweden)

Maria E Pushpanathan

Full Text Available Many studies have sought to describe the relationship between sleep disturbance and cognition in Parkinson's disease (PD. The Parkinson's Disease Sleep Scale (PDSS and its variants (the Parkinson's disease Sleep Scale-Revised; PDSS-R, and the Parkinson's Disease Sleep Scale-2; PDSS-2 quantify a range of symptoms impacting sleep in only 15 items. However, data from these scales may be problematic as included items have considerable conceptual breadth, and there may be overlap in the constructs assessed. Multidimensional measurement models, accounting for the tendency for items to measure multiple constructs, may be useful more accurately to model variance than traditional confirmatory factor analysis. In the present study, we tested the hypothesis that a multidimensional model (a bifactor model is more appropriate than traditional factor analysis for data generated by these types of scales, using data collected using the PDSS-R as an exemplar. 166 participants diagnosed with idiopathic PD participated in this study. Using PDSS-R data, we compared three models: a unidimensional model; a 3-factor model consisting of sub-factors measuring insomnia, motor symptoms and obstructive sleep apnoea (OSA and REM sleep behaviour disorder (RBD symptoms; and, a confirmatory bifactor model with both a general factor and the same three sub-factors. Only the confirmatory bifactor model achieved satisfactory model fit, suggesting that PDSS-R data are multidimensional. There were differential associations between factor scores and patient characteristics, suggesting that some PDSS-R items, but not others, are influenced by mood and personality in addition to sleep symptoms. Multidimensional measurement models may also be a helpful tool in the PDSS and the PDSS-2 scales and may improve the sensitivity of these instruments.

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

Science.gov (United States)

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

2011-10-01

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

An empirical study on key factors for purchasing strategy on project based organizations: A case study of gas field development projects

Directory of Open Access Journals (Sweden)

Aboulfazl Kazazi

2012-08-01

Full Text Available One of the primary concerns in development of oil and gas resources is to find the critical success factors associated with different important projects. Purchasing and procurement plays a key role in these projects. There is no doubt that in history of similar studies, there are not much studies to determine key factors. The proposed study of this paper presents an empirical study to find these factors in one of the most important gas filed in Iran is now South Pars Gas Field. The study distributes a questionnaire consists of various questions associated with purchasing activities. We investigate the feedbacks gathered from decision makers using factor analysis. The results of our survey reveal that there are three categories of organizational strategy, the relative importance of strategy and risk according to factor analysis. Each factor consists of many other factors and the relative importance of all factors are investigated.

PATH ANALYSIS OF RECORDING SYSTEM INNOVATION FACTORS AFFECTING ADOPTION OF GOAT FARMERS

Directory of Open Access Journals (Sweden)

S. Okkyla

2014-09-01

Full Text Available The objective of this study was to evaluate the path analysis of recording system innovation factorsaffecting adoption of goat farmers. This study was conducted from January to February 2014 inPringapus District, Semarang Regency by using survey method. For determining the location, this studyused purposive sampling method. The amount of respondents were determined by quota samplingmethod. Total respondents randomly chosed were 146 farmers. The data were descriptively andquantitatively analyzed by using path analysis of statistical package for the social science (SPSS 16.Independent variables in this study were internal factor, motivation, innovation characteristics,information source, and dependent variable was adoption. Analysis of linear regression showed thatthere was no significant effect of internal factor on adoption, so that it was important to use the trimmingmethod in path analysis. The result of path analysis showed that the influence of motivation, innovationcharacteristics and information source on adoption were 0.168; 0.720 and 0.09, respectively. Innovationcharacteristics were the greatest effect on adoption. In conclusion, by improving innovationcharacteristics of respondent through motivation and information source may significantly increase theadoption of recording system in goat farmers.

A Rasch and factor analysis of the Functional Assessment of Cancer Therapy-General (FACT-G

Directory of Open Access Journals (Sweden)

Selby Peter J

2007-04-01

Full Text Available Abstract Background Although the Functional Assessment of Cancer Therapy – General questionnaire (FACT-G has been validated few studies have explored the factor structure of the instrument, in particular using non-sample dependent measurement techniques, such as Rasch Models. Furthermore, few studies have explored the relationship between item fit to the Rasch Model and clinical utility. The aim of this study was to investigate the dimensionality and measurement properties of the FACT-G with Rasch Models and Factor analysis. Methods A factor analysis and Rasch analysis (Partial Credit Model was carried out on the FACT-G completed by a heterogeneous sample of cancer patients (n = 465. For the Rasch analysis item fit (infit mean squares ≥ 1.30, dimensionality and item invariance were assessed. The impact of removing misfitting items on the clinical utility of the subscales and FACT-G total scale was also assessed. Results The factor analysis demonstrated a four factor structure of the FACT-G which broadly corresponded to the four subscales of the instrument. Internal consistency for these four scales was very good (Cronbach's alpha 0.72 – 0.85. The Rasch analysis demonstrated that each of the subscales and the FACT-G total scale had misfitting items (infit means square ≥ 1.30. All these scales with the exception of the Social & Family Well-being Scale (SFWB were unidimensional. When misfitting items were removed, the effect sizes and the clinical utility of the instrument were maintained for the subscales and the total FACT-G scores. Conclusion The results of the traditional factor analysis and Rasch analysis of the FACT-G broadly agreed. Caution should be exercised when utilising the Social & Family Well-being scale and further work is required to determine whether this scale is best represented by two factors. Additionally, removing misfitting items from scales should be performed alongside an assessment of the impact on clinical utility.

Validity of a four-factor modelunderlying the physical fitness in adults with intellectual disabilities a confirmatory factor analysis

OpenAIRE

Cuesta-Vargas, Antonio; Solera Martinez, M; Rodriguez Moya, Alejandro; Perez, Y; Martinez Vizcaino, V

2011-01-01

Purpose: To use confirmatory factor analysis to test whether a four factor might explain the clustering of the components of the physical fitness in adults with intellectual disabilities (FID). Relevance: Individuals with intellectual disabilities (ID) are significantly weaker than individuals without ID at all stages of life. These subjects might be particularly susceptible to loss of basic function because of poor physical fitness. Participants: We studied 267 adults with intellectual...

Analysis and optimization of the TWINKLE factoring device

NARCIS (Netherlands)

Lenstra, A.K.; Shamir, A.; Preneel, B.

2000-01-01

We describe an enhanced version of the TWINKLE factoring device and analyse to what extent it can be expected to speed up the sieving step of the Quadratic Sieve and Number Field Sieve factoring al- gorithms. The bottom line of our analysis is that the TWINKLE-assisted factorization of 768-bit

Nominal Performance Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2004-09-08

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs for the groundwater exposure scenario for the three climate states considered in the TSPA-LA as well as conversion factors for evaluating compliance with the groundwater protection standard. The BDCFs will be used in performance assessment for calculating all-pathway annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle

Nominal Performance Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the Total System Performance Assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the groundwater exposure scenario, and the development of conversion factors for assessing compliance with the groundwater protection standard. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA-LA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the ''Biosphere Model Report'' in Figure 1-1, contain detailed description of the model input parameters, their development, and the relationship between the parameters and specific features events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the groundwater exposure scenario. The objectives of this analysis are to develop BDCFs for the groundwater exposure scenario for the three climate states considered in the TSPA-LA as well as conversion factors for evaluating compliance with the groundwater protection standard. The BDCFs will be used in performance assessment for calculating all-pathway annual doses for a given concentration of radionuclides in groundwater. The conversion factors will be used for calculating gross alpha particle activity in groundwater and the annual dose

Critical Success Factors of Mobile Application Development Projects: A Qualitative Study

Directory of Open Access Journals (Sweden)

Hamza Khastar

2016-07-01

Full Text Available This study seeks to identify the critical success factors of teams in the application-development project. To achieve this goal, a qualitative approach and content analysis was utilized. Semi-structured interviews with 14 developers and experts was performed for data collection. A systematic review of previous research shows that after 9 critical success factors. With the analysis interviews, the CSf's raised to 12; including user experience, strategy and project management, support and promotion, business models, planning and goal setting, financial and budgeting, marketing and customer needs, infrastructure, technical issues and design, contextual factors, teamwork and staffing. The results show that the customer experience, teamwork and contextual factors are core categories in the research paradigm model.

Risk factor analysis of equine strongyle resistance to anthelmintics

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G. Sallé

2017-12-01

Full Text Available Intestinal strongyles are the most problematic endoparasites of equids as a result of their wide distribution and the spread of resistant isolates throughout the world. While abundant literature can be found on the extent of anthelmintic resistance across continents, empirical knowledge about associated risk factors is missing. This study brought together results from anthelmintic efficacy testing and risk factor analysis to provide evidence-based guidelines in the field. It involved 688 horses from 39 French horse farms and riding schools to both estimate Faecal Egg Count Reduction (FECR after anthelmintic treatment and to interview farm and riding school managers about their practices. Risk factors associated with reduced anthelmintic efficacy in equine strongyles were estimated across drugs using a marginal modelling approach. Results demonstrated ivermectin efficacy (96.3% ± 14.5% FECR, the inefficacy of fenbendazole (42.8% ± 33.4% FECR and an intermediate profile for pyrantel (90.3% ± 19.6% FECR. Risk factor analysis provided support to advocate for FEC-based treatment regimens combined with individual anthelmintic dosage and the enforcement of tighter biosecurity around horse introduction. The combination of these measures resulted in a decreased risk of drug resistance (relative risk of 0.57, p = 0.02. Premises falling under this typology also relied more on their veterinarians suggesting practitionners play an important role in the sustainability of anthelmintic usage. Similarly, drug resistance risk was halved in premises with frequent pasture rotation and with stocking rate below five horses/ha (relative risk of 0.53, p < 0.01. This is the first empirical risk factor analysis for anthelmintic resistance in equids. Our findings should guide the implementation of more sustained strongyle management in the field. Keywords: Horse, Nematode, Anthelmintic resistance, Strongyle, Cyathostomin

Strategic Decision-Making: Research Mapping from Exploratory Factor Analysis and Multidimensional Scaling

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Ivano Ribeiro

2017-04-01

Full Text Available To understand the connection between authors, concepts and theories that address strategic decision-making, in this article the citations and co-citations of works published up to 2014 were analyzed. The sample consists of 489 articles published in international periodicals included in the Web of Science-ISI Web of Knowledge database. The search was conducted using key words that enabled the identification of the highest possible number of articles on the subject in question. Through Multidimensional Scaling (MDS and Exploratory Factor Analysis (EFA, the conceptual and theoretical relationships involved in these studies were identified. The results show that from 1980 to 2014 three different factors are highlighted: the first has to do with studies on conflict; the second factor is the Top Management Team (TMT and decision-making; and the third is related to processes. More recently (2013-2014, studies on strategic decision-making are converging towards analysis of conflict and process, composition and control, with Upper Echelon Theory being maintained as the central theory in these studies. This finding is the main contribution of this article.

An exploration study to detect important factors influencing insurance firms

OpenAIRE

Farzaneh Soleimani; Fattaneh Alizadeh Meshkani; Abdullah Naami

2013-01-01

The recent trend on competition among insurance firms has increased motivation to look for important factors influencing this industry. In this paper, we present an empirical investigation to find important factors shaping this industry. The proposed study designs a questionnaire in Likert scale and, using principal component analysis, detects important factors on the success of this industry. Cronbach alpha is calculated as 0.849, and Kaiser-Meyer-Olkin and Bartlett's Test are calculated as ...

Influencing Factors of Catering and Food Service Industry Based on Principal Component Analysis

OpenAIRE

Zi Tang

2014-01-01

Scientific analysis of influencing factors is of great importance for the healthy development of catering and food service industry. This study attempts to present a set of critical indicators for evaluating the contribution of influencing factors to catering and food service industry in the particular context of Harbin City, Northeast China. Ten indicators that correlate closely with catering and food service industry were identified and performed by the principal component analysis method u...

A study to determine influential factors on implementation of management information system

Directory of Open Access Journals (Sweden)

Naser Azad

2013-08-01

Full Text Available Management information system (MIS plays an important role on sharing necessary information within organization. In this paper, we study to find out important factors influencing the implementation of MIS in banking industry. The study designs a questionnaire in Likert scale and distributes it among 253 randomly selected people. Cronbach alpha has been calculated as 0.82, which is within an acceptable limit. The study uses factor analysis to find important factors and detects six important factors including fear of technology, organizational instability, informal groups, cultural factors, organizational development and understanding that change is always good.

Identification of noise in linear data sets by factor analysis

International Nuclear Information System (INIS)

Roscoe, B.A.; Hopke, Ph.K.

1982-01-01

A technique which has the ability to identify bad data points, after the data has been generated, is classical factor analysis. The ability of classical factor analysis to identify two different types of data errors make it ideally suited for scanning large data sets. Since the results yielded by factor analysis indicate correlations between parameters, one must know something about the nature of the data set and the analytical techniques used to obtain it to confidentially isolate errors. (author)

A pragmatic approach to estimate alpha factors for common cause failure analysis

International Nuclear Information System (INIS)

Hassija, Varun; Senthil Kumar, C.; Velusamy, K.

2014-01-01

Highlights: • Estimation of coefficients in alpha factor model for common cause analysis. • A derivation of plant specific alpha factors is demonstrated. • We examine sensitivity of common cause contribution to total system failure. • We compare beta factor and alpha factor models for various redundant configurations. • The use of alpha factors is preferable, especially for large redundant systems. - Abstract: Most of the modern technological systems are deployed with high redundancy but still they fail mainly on account of common cause failures (CCF). Various models such as Beta Factor, Multiple Greek Letter, Binomial Failure Rate and Alpha Factor exists for estimation of risk from common cause failures. Amongst all, alpha factor model is considered most suitable for high redundant systems as it arrives at common cause failure probabilities from a set of ratios of failures and the total component failure probability Q T . In the present study, alpha factor model is applied for the assessment of CCF of safety systems deployed at two nuclear power plants. A method to overcome the difficulties in estimation of the coefficients viz., alpha factors in the model, importance of deriving plant specific alpha factors and sensitivity of common cause contribution to the total system failure probability with respect to hazard imposed by various CCF events is highlighted. An approach described in NUREG/CR-5500 is extended in this study to provide more explicit guidance for a statistical approach to derive plant specific coefficients for CCF analysis especially for high redundant systems. The procedure is expected to aid regulators for independent safety assessment

Human factors in resuscitation: Lessons learned from simulator studies

Directory of Open Access Journals (Sweden)

Hunziker S

2010-01-01

Full Text Available Medical algorithms, technical skills, and repeated training are the classical cornerstones for successful cardiopulmonary resuscitation (CPR. Increasing evidence suggests that human factors, including team interaction, communication, and leadership, also influence the performance of CPR. Guidelines, however, do not yet include these human factors, partly because of the difficulties of their measurement in real-life cardiac arrest. Recently, clinical studies of cardiac arrest scenarios with high-fidelity video-assisted simulations have provided opportunities to better delineate the influence of human factors on resuscitation team performance. This review focuses on evidence from simulator studies that focus on human factors and their influence on the performance of resuscitation teams. Similar to studies in real patients, simulated cardiac arrest scenarios revealed many unnecessary interruptions of CPR as well as significant delays in defibrillation. These studies also showed that human factors play a major role in these shortcomings and that the medical performance depends on the quality of leadership and team-structuring. Moreover, simulated video-taped medical emergencies revealed that a substantial part of information transfer during communication is erroneous. Understanding the impact of human factors on the performance of a complex medical intervention like resuscitation requires detailed, second-by-second, analysis of factors involving the patient, resuscitative equipment such as the defibrillator, and all team members. Thus, high-fidelity simulator studies provide an important research method in this challenging field.

Application of classification algorithms for analysis of road safety risk factor dependencies.

Science.gov (United States)

Kwon, Oh Hoon; Rhee, Wonjong; Yoon, Yoonjin

2015-02-01

Transportation continues to be an integral part of modern life, and the importance of road traffic safety cannot be overstated. Consequently, recent road traffic safety studies have focused on analysis of risk factors that impact fatality and injury level (severity) of traffic accidents. While some of the risk factors, such as drug use and drinking, are widely known to affect severity, an accurate modeling of their influences is still an open research topic. Furthermore, there are innumerable risk factors that are waiting to be discovered or analyzed. A promising approach is to investigate historical traffic accident data that have been collected in the past decades. This study inspects traffic accident reports that have been accumulated by the California Highway Patrol (CHP) since 1973 for which each accident report contains around 100 data fields. Among them, we investigate 25 fields between 2004 and 2010 that are most relevant to car accidents. Using two classification methods, the Naive Bayes classifier and the decision tree classifier, the relative importance of the data fields, i.e., risk factors, is revealed with respect to the resulting severity level. Performances of the classifiers are compared to each other and a binary logistic regression model is used as the basis for the comparisons. Some of the high-ranking risk factors are found to be strongly dependent on each other, and their incremental gains on estimating or modeling severity level are evaluated quantitatively. The analysis shows that only a handful of the risk factors in the data dominate the severity level and that dependency among the top risk factors is an imperative trait to consider for an accurate analysis. Copyright © 2014 Elsevier Ltd. All rights reserved.

Factor analysis of Wechsler Adult Intelligence Scale-Revised in developmentally disabled persons.

Science.gov (United States)

Di Nuovo, Santo F; Buono, Serafino

2006-12-01

The results of previous studies on the factorial structure of Wechsler Intelligence Scales are somewhat inconsistent across normal and pathological samples. To study specific clinical groups, such as developmentally disabled persons, it is useful to examine the factor structure in appropriate samples. A factor analysis was carried out using the principal component method and the Varimax orthogonal rotation on the Wechsler Adult Intelligence Scale (WAIS-R) in a sample of 203 developmentally disabled persons, with a mean age of 25 years 4 months. Developmental disability ranged from mild to moderate. Partially contrasting with previous studies on normal samples, results found a two-factor solution. Wechsler's traditional Verbal and Performance scales seems to be more appropriate for this sample than the alternative three-factor solution.

"Factor Analysis Using ""R"""

Directory of Open Access Journals (Sweden)

A. Alexander Beaujean

2013-02-01

Full Text Available R (R Development Core Team, 2011 is a very powerful tool to analyze data, that is gaining in popularity due to its costs (its free and flexibility (its open-source. This article gives a general introduction to using R (i.e., loading the program, using functions, importing data. Then, using data from Canivez, Konold, Collins, and Wilson (2009, this article walks the user through how to use the program to conduct factor analysis, from both an exploratory and confirmatory approach.

The provenance study of Chinese ancient color glaze from Shanxi by INAA and factor analysis

International Nuclear Information System (INIS)

Cheng, L.; Ding, X.L.; Feng, S.L.; Feng, X.Q.; Lu, Z.R.

2005-01-01

This paper reports the results of the provenance study of Chinese ancient color glaze in Shanxi. The minor and trace elements of body of color glaze in different dynasty from Xiyue temper kiln and that of Lidipo kiln in Ming Dynasty determined by INAA, some of ancient porcelain from Lidipo kiln were measured, also. The factor analysis showed that provenances of the ancient color glazes from Xiyue Temple that were produced during Song Dynasty to the early Qing Dynasty were in the place of the Xiyue kiln, and body material of ancient color have little been changed, on the other hand, that of Later Qing Dynasty were-produced from Lidipo kiln. Different color glazes were measured by SRXRF and it proved the colored elements were Fe and Cu.

Effect of abiotic and biotic stress factors analysis using machine learning methods in zebrafish.

Science.gov (United States)

Gutha, Rajasekar; Yarrappagaari, Suresh; Thopireddy, Lavanya; Reddy, Kesireddy Sathyavelu; Saddala, Rajeswara Reddy

2018-03-01

In order to understand the mechanisms underlying stress responses, meta-analysis of transcriptome is made to identify differentially expressed genes (DEGs) and their biological, molecular and cellular mechanisms in response to stressors. The present study is aimed at identifying the effect of abiotic and biotic stress factors, and it is found that several stress responsive genes are common for both abiotic and biotic stress factors in zebrafish. The meta-analysis of micro-array studies revealed that almost 4.7% i.e., 108 common DEGs are differentially regulated between abiotic and biotic stresses. This shows that there is a global coordination and fine-tuning of gene regulation in response to these two types of challenges. We also performed dimension reduction methods, principal component analysis, and partial least squares discriminant analysis which are able to segregate abiotic and biotic stresses into separate entities. The supervised machine learning model, recursive-support vector machine, could classify abiotic and biotic stresses with 100% accuracy using a subset of DEGs. Beside these methods, the random forests decision tree model classified five out of 8 stress conditions with high accuracy. Finally, Functional enrichment analysis revealed the different gene ontology terms, transcription factors and miRNAs factors in the regulation of stress responses. Copyright © 2017 Elsevier Inc. All rights reserved.

Determination of Important Topographic Factors for Landslide Mapping Analysis Using MLP Network

Directory of Open Access Journals (Sweden)

Mutasem Sh. Alkhasawneh

2013-01-01

Full Text Available Landslide is one of the natural disasters that occur in Malaysia. Topographic factors such as elevation, slope angle, slope aspect, general curvature, plan curvature, and profile curvature are considered as the main causes of landslides. In order to determine the dominant topographic factors in landslide mapping analysis, a study was conducted and presented in this paper. There are three main stages involved in this study. The first stage is the extraction of extra topographic factors. Previous landslide studies had identified mainly six topographic factors. Seven new additional factors have been proposed in this study. They are longitude curvature, tangential curvature, cross section curvature, surface area, diagonal line length, surface roughness, and rugosity. The second stage is the specification of the weight of each factor using two methods. The methods are multilayer perceptron (MLP network classification accuracy and Zhou's algorithm. At the third stage, the factors with higher weights were used to improve the MLP performance. Out of the thirteen factors, eight factors were considered as important factors, which are surface area, longitude curvature, diagonal length, slope angle, elevation, slope aspect, rugosity, and profile curvature. The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors.

An exploration study to detect important factors influencing insurance firms

Directory of Open Access Journals (Sweden)

Farzaneh Soleimani

2013-11-01

Full Text Available The recent trend on competition among insurance firms has increased motivation to look for important factors influencing this industry. In this paper, we present an empirical investigation to find important factors shaping this industry. The proposed study designs a questionnaire in Likert scale and, using principal component analysis, detects important factors on the success of this industry. Cronbach alpha is calculated as 0.849, and Kaiser-Meyer-Olkin and Bartlett's Test are calculated as 0.873 and 12744 with (Sig. =0.000, respectively. The study has detected four important factors including quality of service casualties, sales improvement and advertisement, quality of issuance of insurance policies and quality of work force.

Factor Analysis Affecting The Audit Quality Study On Inspectorate In Riau Province

Directory of Open Access Journals (Sweden)

Nur Azlina

2017-07-01

Full Text Available This study aims to determine 1 the influence of integrity on audit quality 2 the influence of objectivity on audit quality 3 the effect of work experience on audit quality 4 the influence of knowledge on financial management on audit quality and 5 Motivation to audit quality. The sample of this study is the auditor who works in inspectorate in Riau Province precisely in Inspectorate of Bengkalis Siak Pelalawan Kuantan Singingi and Pekanbaru City. Data were analyzed by using multiple regression method using SPSS version 21. The data used is primary data by using questionnaire. The analytical technique used to perform the hypothesis is random sampling. The results showed that integrity work experience knowledge of local financial management and motivation had no effect on audit quality while objectivity had an effect on audit quality. Adjusted R Square of 0.626. This shows that the quality of audit on Inspectorate in Riau Province can be influenced by factors studied by 62.6 and 37.4 influenced by factors not observed in this study.

The Recoverability of P-Technique Factor Analysis

Science.gov (United States)

Molenaar, Peter C. M.; Nesselroade, John R.

2009-01-01

It seems that just when we are about to lay P-technique factor analysis finally to rest as obsolete because of newer, more sophisticated multivariate time-series models using latent variables--dynamic factor models--it rears its head to inform us that an obituary may be premature. We present the results of some simulations demonstrating that even…

Minerals sampling: sensibility analysis and correction factors for Pierre Gy's equation

International Nuclear Information System (INIS)

Vallebuona, G.; Niedbalski, F.

2005-01-01

Pierre Gy's equation is widely used in ore sampling. This equation is based in four parameters: shape factor, size distribution factor, mineralogical factor and liberation factor. The usual practice is to consider fixed values for the shape and size distribution factors. This practice does not represent well several important ores. The mineralogical factor considers only one specie of interest and the gangue, leaving out other cases such as polymetallic ores where there are more than one species of interest. A sensibility analysis to the Gy's equation factors was done and a procedure to determine specific values for them was developed and presented in this work. mean ore characteristics, associated with an insecure use of the actual procedure, were determined. finally, for a case study, the effects of using each alternative were evaluated. (Author) 4 refs

Study on Influencing Factor Analysis and Application of Consumer Mobile Commerce Acceptance

Science.gov (United States)

Li, Gaoguang; Lv, Tingjie

Mobile commerce (MC) refers to e-commerce activities carried out using a mobile device such as a phone or PDA. With new technology, MC will be rapidly growing in the near future. At the present time, what factors making consumer accept MC and what MC applications are acceptable by consumers are two of hot issues both for MC providers and f or MC researchers. This study presents a proposed MC acceptance model that integrates perceived playfulness, perceived risk and cost into the TAM to study which factors affect consumer MC acceptance. The proposed model includes five variables, namely perceived risk, cost, perceived usefulness, perceived playfulness, perceived ease of use, perceived playfulness. Then, using analytic hierarchy process (AHP) to calculate weight of criteria involved in proposed model. Finally, the study utilizes fuzzy comprehensive evaluation method to evaluate MC applications accepted possibility, and then a MC application is empirically tested using data collected from a survey of MC consumers.

Human factor analysis and preventive countermeasures in nuclear power plant

International Nuclear Information System (INIS)

Li Ye

2010-01-01

Based on the human error analysis theory and the characteristics of maintenance in a nuclear power plant, human factors of maintenance in NPP are divided into three different areas: human, technology, and organization. Which is defined as individual factors, including psychological factors, physiological characteristics, health status, level of knowledge and interpersonal skills; The technical factors including technology, equipment, tools, working order, etc.; The organizational factors including management, information exchange, education, working environment, team building and leadership management,etc The analysis found that organizational factors can directly or indirectly affect the behavior of staff and technical factors, is the most basic human error factor. Based on this nuclear power plant to reduce human error and measures the response. (authors)

Studying Driving Risk Factors using Multi-Source Mobile Computing Data

Directory of Open Access Journals (Sweden)

Xianbiao Hu

2015-09-01

In this paper, the overall research framework used in this research is presented, which mainly includes data collection, data processing, calibration and analysis methodology. A preliminary case study — including data summary statistics and correlation analysis — is also presented. The results of our study will further existing knowledge about driving exposure factors that are closely linked to crash risk, and provide the foundation for advanced forms of Usage Based Insurance.

A study on important factors influencing customers’ impulsive buying behavior: A case study of Shahrvand food chain

Directory of Open Access Journals (Sweden)

Hamed Asgari

2013-05-01

Full Text Available Customer purchasing behavior plays an essential role on marketing planning in today’s competitive environment. Immediate purchasing behavior is one of the most important components of purchasing behavior. In this paper, we use factor analysis to extract important factors influencing immediate purchasing behavior.The proposed study of this paper designs a questionnaire including 35 questions and through basic investigation, the questions are reduced to 21 ones. The questionnaire is distributed among 200 regular customers and 149 questionnaires have been collected. Cronbach alpha has been calculated as 0.804, which is well above the minimum desirable level of 0.7. The survey is conducted among regular customers who normally make purchases from Shahrvand food chains in city of Tehran, Iran. The results of factor analysis reveals four major factors including intelligence pricing strategy, involvement, promotion margin and consumer behavior. The proposed study of this paper considers “intelligence pricing strategy” for the first time as an important factor in consumer’s purchasing behavior.

Analysis of the socio-economic factors associated with gum Arabic ...

African Journals Online (AJOL)

The study is an analysis of the socio-economic factors associated with gum arabic collectors in Northern Guinea Savanna Zone of Adamawa State, Nigeria through a questionnaire survey on a sample of 100 respondents obtained through a multi stage sampling technique. Data collected were analyzed using descriptive ...

The development of human factors technologies -The development of human behaviour analysis techniques-

Energy Technology Data Exchange (ETDEWEB)

Lee, Jung Woon; Lee, Yong Heui; Park, Keun Ok; Chun, Se Woo; Suh, Sang Moon; Park, Jae Chang [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1995-07-01

In order to contribute to human error reduction through the studies on human-machine interaction in nuclear power plants, this project has objectives to develop SACOM(Simulation Analyzer with a Cognitive Operator Model) and techniques for human error analysis and application. In this year, we studied the followings: (1) Site investigation of operator tasks, (2) Development of operator task micro structure and revision of micro structure, (3) Development of knowledge representation software and SACOM prototype, (4) Development of performance assessment methodologies in task simulation and analysis of the effects of performance shaping factors. analysis and application techniques> (1) Classification of error shaping factors(ESFs) and development of software for ESF evaluation, (2) Analysis of human error occurrences and revision of analysis procedure, (3) Experiment for human error data collection using a compact nuclear simulator, (4) Development of a prototype data base system of the analyzed information on trip cases. 55 figs, 23 tabs, 33 refs. (Author).

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

Science.gov (United States)

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

2016-10-01

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

Research on the relationship between the elements and pharmacological activities in velvet antler using factor analysis and cluster analysis

Science.gov (United States)

Zhou, Libing

2017-04-01

Velvet antler has certain effect on improving the body's immune cells and the regulation of immune system function, nervous system, anti-stress, anti-aging and osteoporosis. It has medicinal applications to treat a wide range of diseases such as tissue wound healing, anti-tumor, cardiovascular disease, et al. Therefore, the research on the relationship between pharmacological activities and elements in velvet antler is of great significance. The objective of this study was to comprehensively evaluate 15 kinds of elements in different varieties of velvet antlers and study on the relationship between the elements and traditional Chinese medicine efficacy for the human. The factor analysis and the factor cluster analysis methods were used to analyze the data of elements in the sika velvet antler, cervus elaphus linnaeus, flower horse hybrid velvet antler, apiti (elk) velvet antler, male reindeer velvet antler and find out the relationship between 15 kinds of elements including Ca, P, Mg, Na, K, Fe, Cu, Mn, Al, Ba, Co, Sr, Cr, Zn and Ni. Combining with MATLAB2010 and SPSS software, the chemometrics methods were made on the relationship between the elements in velvet antler and the pharmacological activities. The first commonality factor F1 had greater load on the indexes of Ca, P, Mg, Co, Sr and Ni, and the second commonality factor F2 had greater load on the indexes of K, Mn, Zn and Cr, and the third commonality factor F3 had greater load on the indexes of Na, Cu and Ba, and the fourth commonality factor F4 had greater load on the indexes of Fe and Al. 15 kinds of elements in velvet antler in the order were elk velvet antler>flower horse hybrid velvet antler>cervus elaphus linnaeus>sika velvet antler>male reindeer velvet antler. Based on the factor analysis and the factor cluster analysis, a model for evaluating traditional Chinese medicine quality was constructed. These studies provide the scientific base and theoretical foundation for the future large-scale rational

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

OpenAIRE

BENLIGIRAY, Serdar; ONAY, Ahmet

2017-01-01

The objective of this study is to explore business courses performance factors with a focus on accounting and finance. Course score interrelations are assumed to represent interpretable constructs of these factors. Factor analysis is proposed to identify the constructs that explain the correlations. Factor analysis results identify three sub-groups of business core courses. The first group is labeled as management-oriented courses. Accounting, finance and economics courses are separated in tw...

A Factor Analytic Study of the Internet Usage Scale

Science.gov (United States)

Monetti, David M.; Whatley, Mark A.; Hinkle, Kerry T.; Cunningham, Kerry T.; Breneiser, Jennifer E.; Kisling, Rhea

2011-01-01

This study developed an Internet Usage Scale (IUS) for use with adolescent populations. The IUS is a 26-item scale that measures participants' beliefs about how their Internet usage impacts their behavior. The sample for this study consisted of 947 middle school students. An exploratory factor analysis with varimax rotation was conducted on the…

Integrating human factors into process hazard analysis

International Nuclear Information System (INIS)

Kariuki, S.G.; Loewe, K.

2007-01-01

A comprehensive process hazard analysis (PHA) needs to address human factors. This paper describes an approach that systematically identifies human error in process design and the human factors that influence its production and propagation. It is deductive in nature and therefore considers human error as a top event. The combinations of different factors that may lead to this top event are analysed. It is qualitative in nature and is used in combination with other PHA methods. The method has an advantage because it does not look at the operator error as the sole contributor to the human failure within a system but a combination of all underlying factors

Potential barriers to the application of multi-factor portfolio analysis in public hospitals: evidence from a pilot study in the Netherlands.

Science.gov (United States)

Pavlova, Milena; Tsiachristas, Apostolos; Vermaeten, Gerhard; Groot, Wim

2009-01-01

Portfolio analysis is a business management tool that can assist health care managers to develop new organizational strategies. The application of portfolio analysis to US hospital settings has been frequently reported. In Europe however, the application of this technique has received little attention, especially concerning public hospitals. Therefore, this paper examines the peculiarities of portfolio analysis and its applicability to the strategic management of European public hospitals. The analysis is based on a pilot application of a multi-factor portfolio analysis in a Dutch university hospital. The nature of portfolio analysis and the steps in a multi-factor portfolio analysis are reviewed along with the characteristics of the research setting. Based on these data, a multi-factor portfolio model is developed and operationalized. The portfolio model is applied in a pilot investigation to analyze the market attractiveness and hospital strengths with regard to the provision of three orthopedic services: knee surgery, hip surgery, and arthroscopy. The pilot portfolio analysis is discussed to draw conclusions about potential barriers to the overall adoption of portfolio analysis in the management of a public hospital. Copyright (c) 2008 John Wiley & Sons, Ltd.

Functional analysis of jasmonate-responsive transcription factors in Arabidopsis thaliana

NARCIS (Netherlands)

Zarei, Adel

2007-01-01

The aim of the studies described in this thesis was the functional analysis of JA-responsive transcription factors in Arabidopsis with an emphasis on the interaction with the promoters of their target genes. In short, the following new results were obtained. The promoter of the PDF1.2 gene contains

Prognostic Factors of Patients with Gastric Gastrointestinal Stromal Tumor after Curative Resection: A Retrospective Analysis of 406 Consecutive Cases in a Multicenter Study.

Science.gov (United States)

Kim, In-Hwan; Kwak, Sang-Gyu; Chae, Hyun-Dong

2015-01-01

Gastric gastrointestinal stromal tumors (GISTs) have a highly variable clinical course, and recurrent disease sometimes develops despite curative surgery. This study was undertaken to investigate the surgical role in treating gastric GISTs and evaluate the clinicopathological features of a large series of patients who underwent curative resection for gastric GISTs to clarify which features were independent prognostic factors. The clinicopathological data of 406 patients with gastric GISTs who underwent curative resection at 4 university hospitals in Daegu, South Korea, from March 1998 to March 2012 were reviewed. All cases were confirmed as gastric GISTs by immunohistochemical staining, in which CD117 or CD34 was positive. Clinical follow-up was performed periodically, and disease-free survival rates were retrospectively investigated using the medical records. The mean follow-up period was 42.9 months (range: 2-166). There were 11 recurrent patients (2.7%). Due to the small number of recurrences, age, sex and location were controlled using propensity score matching before performing any statistical analysis. Tumor size, mitotic count, NIH classification, and cellularity were judged to be independent prognostic factors for recurrence by univariate analysis. In a multivariate analysis, tumor size and mitotic count were significantly and independently related to recurrence, and tumor size was determined to be the most important prognostic factor for recurrence after curative resection (hazard ratio: 1.204; p < 0.01). The results of this multicenter study demonstrate that disease-free survival rates are good. Tumor size was disclosed as the most important factor for recurrence in gastric GIST patients who underwent radical resection. 2015 S. Karger AG, Basel.

A Confirmatory Factor Analysis on the Attitude Scale of Constructivist Approach for Science Teachers

Directory of Open Access Journals (Sweden)

E. Evrekli

2010-11-01

Full Text Available Underlining the importance of teachers for the constructivist approach, the present study attempts to develop “Attitude Scale of Construc¬tivist Approach for Science Teachers (ASCAST”. The pre-applications of the scale were administered to a total of 210 science teachers; however, the data obtained from 5 teachers were excluded from the analysis. As a result of the analysis of the data obtained from the pre-applications, it was found that the scale could have a single factor structure, which was tested using the confir¬matory factor analysis. As a result of the initial confirmatory factor analysis, the values of fit were examined and found to be low. Subsequently, by exam¬ining the modification indices, error covariance was added between items 23 and 24 and the model was tested once again. The added error covariance led to a significant improvement in the model, producing values of fit suitable for limit values. Thus, it was concluded that the scale could be employed with a single factor. The explained variance value for the scale developed with a sin¬gle factor structure was calculated to be 50.43% and its reliability was found to be .93. The results obtained suggest that the scale possesses reliable-valid characteristics and could be used in further studies.

RISK FACTOR ASSESSMENT AND CLINICOPATHOLOGICAL ANALYSIS OF BREAST DISEASES IN A TERTIARY CENTER- A PROSPECTIVE STUDY

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Abhishek Jina

2017-08-01

Full Text Available BACKGROUND Breast is modified sebaceous gland. It is an organ of female beauty and pride. From puberty to death, the breast is subjected to constant physical and physiological alterations that are related to menses, pregnancy and menopause. The breast problem could be as simple as breast abscess to as ominous as cancer. Both benign and malignant diseases occur in men and women of all ages but benign lesion tend to occur more commonly at younger age than cancer. Benign breast diseases (BBD are common with estimate of over half of the female population at some times in life seeking medical advice for breast problem. This prospective study was done on patients attending OPD for breast complaints in 1 year period, to do the risk factors assessment & clinical analysis of patients presented with breast complaints. MATERIALS AND METHODS Total 200 patients who have attended OPD with breast related complaints and given consent for study, were studied in a period of 1 year duration from at Nehru Hospital, B.R.D Medical College, Gorakhpur. RESULTS Benign breast diseases are more common in the population than malignant one, Fibroadenoma, Breast abscesses and Fibrocystic disease and ANDI are the most common cause of mass seen in middle ages. Malignant lesion of the breast is major concern and the second most commonly diagnosed cancer in our region as seen in study. Incidence is high in western industrialized countries and relatively low in developing countries in Asia and other parts of the world, predisposing factors for BBD are age, sex, race, inverted nipple, retracted nipple, cracked nipple, improper feeding due to lack of knowledge about breast-feeding and endogenous hormonal factors. CONCLUSION BBD is the most frequent type of lesion found in the present study in surgery OPD in BRD medical college, Gorakhpur. Among BBD, fibroadenoma was the commonest, followed by breast abscess, ANDI and gynecomastia. In this study, breast abscess was second most

Qualitative analysis of factors leading to clinical incidents.

Science.gov (United States)

Smith, Matthew D; Birch, Julian D; Renshaw, Mark; Ottewill, Melanie

2013-01-01

The purpose of this paper is to evaluate the common themes leading or contributing to clinical incidents in a UK teaching hospital. A root-cause analysis was conducted on patient safety incidents. Commonly occurring root causes and contributing factors were collected and correlated with incident timing and severity. In total, 65 root-cause analyses were reviewed, highlighting 202 factors implicated in the clinical incidents and 69 categories were identified. The 14 most commonly occurring causes (encountered in four incidents or more) were examined as a key-root or contributory cause. Incident timing was also analysed; common factors were encountered more frequently during out-hours--occurring as contributory rather than a key-root cause. In total, 14 commonly occurring factors were identified to direct interventions that could prevent many clinical incidents. From these, an "Organisational Safety Checklist" was developed to involve departmental level clinicians to monitor practice. This study demonstrates that comprehensively investigating incidents highlights common factors that can be addressed at a local level. Resilience against clinical incidents is low during out-of-hours periods, where factors such as lower staffing levels and poor service provision allows problems to escalate and become clinical incidents, which adds to the literature regarding out-of-hours care provision and should prove useful to those organising hospital services at departmental and management levels.

An SPSSR -Menu for Ordinal Factor Analysis

Directory of Open Access Journals (Sweden)

Mario Basto

2012-01-01

Full Text Available Exploratory factor analysis is a widely used statistical technique in the social sciences. It attempts to identify underlying factors that explain the pattern of correlations within a set of observed variables. A statistical software package is needed to perform the calculations. However, there are some limitations with popular statistical software packages, like SPSS. The R programming language is a free software package for statistical and graphical computing. It offers many packages written by contributors from all over the world and programming resources that allow it to overcome the dialog limitations of SPSS. This paper offers an SPSS dialog written in theR programming language with the help of some packages, so that researchers with little or no knowledge in programming, or those who are accustomed to making their calculations based on statistical dialogs, have more options when applying factor analysis to their data and hence can adopt a better approach when dealing with ordinal, Likert-type data.

Modeling of Iranian Cheetah Habitat using Ecological Niche Factor Analysis (Case Study: Dare Anjir Wildlife Refuge

Directory of Open Access Journals (Sweden)

N. Zamani

2016-03-01

Full Text Available Evaluation of habitat sustainability indexes is essential in wildlife management and conservation of rare species. Suitable habitats are required in wildlife managements and conservation also, they increase reproduction and survival rate of species. In this study in order to mapping habitat sustainability and recognizing habitat requirements of Iranian Cheetah (Acinonyx jubatus venaticus, field data from Dare Anjir  wildlife refuge were collected since autumn 2009 until summer 2011. Ecological Niche Factor Analysis approach has been used to develop habitat suitability model. In this method primary maps of  habitat variables including elevation, slope, aspect, vegetation cover, distance from water sources and environmental monitoring stations have been produced by Idrisi and Biomapper software and imported in Biomapper. The output scores obtained from the analysis showed that Iranian cheetah tends to mountain areas where has more topographical features for camouflage in order to hunting, and northern aspects which have more humidity, denser vegetation cover and more preys . Our result showed that the Iranian cheetah has medium niche width and prefer marginal habitats.

A computational intelligent approach to multi-factor analysis of violent crime information system

Science.gov (United States)

Liu, Hongbo; Yang, Chao; Zhang, Meng; McLoone, Seán; Sun, Yeqing

2017-02-01

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.

Cancer risk factors in Korean news media: a content analysis.

Science.gov (United States)

Kye, Su Yeon; Kwon, Jeong Hyun; Kim, Yong-Chan; Shim, Minsun; Kim, Jee Hyun; Cho, Hyunsoon; Jung, Kyu Won; Park, Keeho

2015-01-01

Little is known about the news coverage of cancer risk factors in Korea. This study aimed to examine how the news media encompasses a wide array of content regarding cancer risk factors and related cancer sites, and investigate whether news coverage of cancer risk factors is congruent with the actual prevalence of the disease. A content analysis was conducted on 1,138 news stories covered during a 5-year period between 2008 and 2012. The news stories were selected from nationally representative media in Korea. Information was collected about cancer risk factors and cancer sites. Of various cancer risk factors, occupational and environmental exposures appeared most frequently in the news. Breast cancer was mentioned the most in relation to cancer sites. Breast, cervical, prostate, and skin cancer were overrepresented in the media in comparison to incidence and mortality cases, whereas lung, thyroid, liver, and stomach cancer were underrepresented. To our knowledge, this research is the first investigation dealing with news coverage about cancer risk factors in Korea. The study findings show occupational and environmental exposures are emphasized more than personal lifestyle factors; further, more prevalent cancers in developed countries have greater media coverage, not reflecting the realities of the disease. The findings may help health journalists and other health storytellers to develop effective ways to communicate cancer risk factors.

Analysis Of Factors Causing Delays On Harun Nafsi - Hm Rifadin Street In Samarinda East Kalimantan Maintenance Project

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Fadli

2017-12-01

Full Text Available This study aims to identify analyze and describe the factors that affect the project maintenance delay on Harun Nafsi - HM. Rifadin Street in Samarinda East Kalimantan. This research uses qualitative research method by utilizing questionnaires. The 30 participating respondents consist of 14 project implementers and 16 field implementers. The data are analyzed by descriptive statistical technique factor analysis and linear regression analysis. The results show that the factors influencing the delay of maintenance project of Harun Nafis - HM Rifadin Street include 1 time factor and workmanship factor 2 human resources and natural factors 3 geographical conditions late approval plans change and labor strikes and 4 non-optimal working levels and changes in the scope of the project during the work are still ongoing. Based on multiple linear regression analysis coefficient of determination value of 0.824 is obtained. It means that the four factors studied affect 82.4 of project delays and the rest of 27.6 is influenced by other variables out of this study. The results of this study also indicate that the dominant factor for road maintenance project delays is the fourth factor of the factors mentioned. The effort that the contractor needs to undertake is not to expand the employment contract if the project is underway or the contractor does not have the capability to complete another project.

Analysis of Factors That Affects the Investors in Conducting Business in Indonesia

Directory of Open Access Journals (Sweden)

Rini Kurnia Sari

2015-10-01

Full Text Available Investment is needed in the development of the economy. With the decentralization of investment is expected to evolve as a whole in every province in Indonesia. Local governments need to improve the quality of economic (GDP / Capita, social (HDI and the infrastructure to attract domestic and foreign investors. Fromthe test results showed that factors affecting investors conducting business in Indonesia is still influenced by GDP/capita, HDI and Infrastructure instead of natural resources.This study uses descriptive analysis and correlation analysis methods to look at the correlation factors that affect investors doing business in Indonesia.

Myocardial infarction (heart attack) and its risk factors: a statistical study

International Nuclear Information System (INIS)

Salahuddin; Alamgir

2005-01-01

A Statistical technique of odds ratio analysis was performed to look at the association of Myocardial Infarction with sex, smoking, hypertension, cholesterol, diabetes, family history, number of dependents, household income and residence. For this purpose a total of 506 patients were examined and their personal and medical data were collected. For each patient, the phenomenon of myocardial infarction was studied in relation to different risk factors. The analysis suggests that smoking, hypertension, cholesterol level, diabetes, family history are important risk factors for the occurrence of MI. (author)

Factoral analysis of the cost of preparing oil

Energy Technology Data Exchange (ETDEWEB)

Avdeyeva, L A; Kudoyarov, G Sh; Shmatova, M F

1979-01-01

Mathematical statistics methods (basically correlational and regression analysis) are used to study the factors which form the level of cost of preparing oil with consideration of the mutual influence of the factors. Selected as the claims for inclusion into a mathematical model was a group of five a priori justified factors: the water level of the oil being extracted (%); the specific expenditure of deemulsifiers; the volume of oil preparation; the quality of oil preparation (the salt content) and the level of use of the installations' capacities (%). To construct an economic and mathematical model of the cost of the technical preparation (SPP) of the oil, all the unions which make up the Ministry of the Oil Industry were divided into two comparable totalities. The first group included unions in which the oil SPP was lower than the branch average and the second, unions in which the SPP was higher than the branch wide cost. Using the coefficients of regression, special elasticity coefficients and the fluctuation indicators, the basic factors were finally identified which have the greatest influence on the formation of the oil SPP level separately for the first and second groups of unions.

Disruptive Event Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M. A. Wasiolek

2003-07-21

This analysis report, ''Disruptive Event Biosphere Dose Conversion Factor Analysis'', is one of the technical reports containing documentation of the ERMYN (Environmental Radiation Model for Yucca Mountain Nevada) biosphere model for the geologic repository at Yucca Mountain, its input parameters, and the application of the model to perform the dose assessment for the repository. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of the two reports that develop biosphere dose conversion factors (BDCFs), which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the conceptual model as well as the mathematical model and lists its input parameters. Model input parameters are developed and described in detail in five analysis report (BSC 2003 [DIRS 160964], BSC 2003 [DIRS 160965], BSC 2003 [DIRS 160976], BSC 2003 [DIRS 161239], and BSC 2003 [DIRS 161241]). The objective of this analysis was to develop the BDCFs for the volcanic ash exposure scenario and the dose factors (DFs) for calculating inhalation doses during volcanic eruption (eruption phase of the volcanic event). The volcanic ash exposure scenario is hereafter referred to as the volcanic ash scenario. For the volcanic ash scenario, the mode of radionuclide release into the biosphere is a volcanic eruption through the repository with the resulting entrainment of contaminated waste in the tephra and the subsequent atmospheric transport and dispersion of contaminated material in

Disruptive Event Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M. A. Wasiolek

2003-01-01

This analysis report, ''Disruptive Event Biosphere Dose Conversion Factor Analysis'', is one of the technical reports containing documentation of the ERMYN (Environmental Radiation Model for Yucca Mountain Nevada) biosphere model for the geologic repository at Yucca Mountain, its input parameters, and the application of the model to perform the dose assessment for the repository. The biosphere model is one of a series of process models supporting the Total System Performance Assessment (TSPA) for the Yucca Mountain repository. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of the two reports that develop biosphere dose conversion factors (BDCFs), which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2003 [DIRS 164186]) describes in detail the conceptual model as well as the mathematical model and lists its input parameters. Model input parameters are developed and described in detail in five analysis report (BSC 2003 [DIRS 160964], BSC 2003 [DIRS 160965], BSC 2003 [DIRS 160976], BSC 2003 [DIRS 161239], and BSC 2003 [DIRS 161241]). The objective of this analysis was to develop the BDCFs for the volcanic ash exposure scenario and the dose factors (DFs) for calculating inhalation doses during volcanic eruption (eruption phase of the volcanic event). The volcanic ash exposure scenario is hereafter referred to as the volcanic ash scenario. For the volcanic ash scenario, the mode of radionuclide release into the biosphere is a volcanic eruption through the repository with the resulting entrainment of contaminated waste in the tephra and the subsequent atmospheric transport and dispersion of contaminated material in the biosphere. The biosphere process

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

NARCIS (Netherlands)

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

2013-01-01

A meta-analysis was performed to explore the correlation between energy and nitrogen efficiency of dairy cows, and to study nutritional and animal factors that influence these efficiencies, as well as their relationship. Treatment mean values were extracted from 68 peer-reviewed studies, including

Defining critical success factors in TOD implementation using rough set analysis

NARCIS (Netherlands)

Thomas, R.; Bertolini, L.

2017-01-01

This paper defines critical success conditions in transit-oriented development (TOD), evaluating the impact of practices, policies, and governance models on implementation. As part of a meta-analysis of 11 international case studies, 16 critical success factors were developed and validated using

A study of environmental polluting factors by neutron activation method

International Nuclear Information System (INIS)

Paunoiu, C.; Doca, C.

2004-01-01

The paper presents: a) some importance factors of the environmental pollution; b) the theoretical aspects of the Neutron Activation Analysis (NAA) used in the study of the environmental pollution; c) the NAA specific hardware and software facilities existing at the Institute for Nuclear Research; d) a direct application of the NAA method in the study of the environmental pollution for Pitesti city by the analysis of some ground and vegetation samples; e) results and conclusions. (authors)

A replication of a factor analysis of motivations for trapping

Science.gov (United States)

Schroeder, Susan; Fulton, David C.

2015-01-01

Using a 2013 sample of Minnesota trappers, we employed confirmatory factor analysis to replicate an exploratory factor analysis of trapping motivations conducted by Daigle, Muth, Zwick, and Glass (1998).  We employed the same 25 items used by Daigle et al. and tested the same five-factor structure using a recent sample of Minnesota trappers. We also compared motivations in our sample to those reported by Daigle et el.

The Five-Factor Model personality traits in schizophrenia: A meta-analysis.

Science.gov (United States)

Ohi, Kazutaka; Shimada, Takamitsu; Nitta, Yusuke; Kihara, Hiroaki; Okubo, Hiroaki; Uehara, Takashi; Kawasaki, Yasuhiro

2016-06-30

Personality is one of important factors in the pathogenesis of schizophrenia because it affects patients' symptoms, cognition and social functioning. Several studies have reported specific personality traits in patients with schizophrenia compared with healthy subjects. However, the results were inconsistent among studies. The NEO Five-Factor Inventory (NEO-FFI) measures five personality traits: Neuroticism (N), Extraversion (E), Openness (O), Agreeableness (A) and Conscientiousness (C). Here, we performed a meta-analysis of these personality traits assessed by the NEO-FFI in 460 patients with schizophrenia and 486 healthy subjects from the published literature and investigated possible associations between schizophrenia and these traits. There was no publication bias for any traits. Because we found evidence of significant heterogeneity in all traits among the studies, we applied a random-effect model to perform the meta-analysis. Patients with schizophrenia showed a higher score for N and lower scores for E, O, A and C compared with healthy subjects. The effect sizes of these personality traits ranged from moderate to large. These differences were not affected by possible moderator factors, such as gender distribution and mean age in each study, expect for gender effect for A. These findings suggest that patients with schizophrenia have a different personality profile compared with healthy subjects. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Factor analysis for imperfect maintenance planning at nuclear power plants by cognitive task analysis

International Nuclear Information System (INIS)

Takagawa, Kenichi; Iida, Hiroyasu

2011-01-01

Imperfect maintenance planning was frequently identified in domestic nuclear power plants. To prevent such an event, we analyzed causal factors in maintenance planning stages and showed the directionality of countermeasures in this study. There is a pragmatic limit in finding the causal factors from the items based on report descriptions. Therefore, the idea of the systemic accident model, which is used to monitor the performance variability in normal circumstances, is taken as a new concept instead of investigating negative factors. As an actual method for analyzing usual activities, cognitive task analysis (CTA) was applied. Persons who experienced various maintenance activities at one electric power company were interviewed about sources related to decision making during maintenance planning, and then usual factors affecting planning were extracted as performance variability factors. The tendency of domestic events was analyzed using the classification item of those factors, and the directionality of countermeasures was shown. The following are critical for preventing imperfect maintenance planning: the persons in charge should fully understand the situation of the equipment for which they are responsible in the work planning and maintenance evaluation stages, and they should definitely understand, for example, the maintenance bases of that equipment. (author)

Dietary patterns derived using exploratory and confirmatory factor analysis are stable and generalizable across race, region, and gender subgroups in the REGARDS study

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Suzanne E Judd

2015-01-01

Full Text Available Background: Examining diet as a whole using dietary patterns as exposures is a complementary method to using single food or nutrients in studies of diet and disease, but the generalizability of patterns across race, region, and gender in the United States has not been established. Objective: To employ rigorous statistical analysis to empirically derive dietary patterns in a large bi-racial, geographically diverse population and examine whether results are stable across population subgroups.Design: The present analysis utilized data from 21,636 participants in the Reasons for Geographic and Racial Differences in Stroke (REGARDS study who completed the Block98 food frequency questionnaire. We employed exploratory factor analysis and confirmatory factor analyses on 56 different food groups iteratively and examined differences by race, region, sex to determine the optimal factor solution in our sample. Results: Five dietary patterns emerged: the Convenience pattern was characterized by mixed dishes; the Plant-based pattern by fruits, vegetables, and fish; the Sweets/Fats pattern by sweet snacks, desserts, and fats and oils; the Southern pattern by fried foods, organ meat, and sweetened beverages; and the Alcohol/Salads pattern by beer, wine, liquor, and salads. Differences were most pronounced in the Southern pattern with black participants, those residing in the Southeast, and participants not completing high school having the highest scores. Conclusions: Five meaningful dietary patterns emerged in the REGARDS study and showed strong congruence across race, sex and region. Future research will examine associations between these patterns and health outcomes to better understand racial disparities in disease and inform prevention efforts.

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

Science.gov (United States)

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

2018-06-15

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

The development of human factors technologies -The development of human behaviour analysis techniques-

International Nuclear Information System (INIS)

Lee, Jung Woon; Lee, Yong Heui; Park, Keun Ok; Chun, Se Woo; Suh, Sang Moon; Park, Jae Chang

1995-07-01

In order to contribute to human error reduction through the studies on human-machine interaction in nuclear power plants, this project has objectives to develop SACOM(Simulation Analyzer with a Cognitive Operator Model) and techniques for human error analysis and application. In this year, we studied the followings: 1) Site investigation of operator tasks, 2) Development of operator task micro structure and revision of micro structure, 3) Development of knowledge representation software and SACOM prototype, 4) Development of performance assessment methodologies in task simulation and analysis of the effects of performance shaping factors. 1) Classification of error shaping factors(ESFs) and development of software for ESF evaluation, 2) Analysis of human error occurrences and revision of analysis procedure, 3) Experiment for human error data collection using a compact nuclear simulator, 4) Development of a prototype data base system of the analyzed information on trip cases. 55 figs, 23 tabs, 33 refs. (Author)

Factors Influencing Fast-Food Consumption Among Adolescents in Tehran: A Qualitative Study.

Science.gov (United States)

Askari Majabadi, Hesamedin; Solhi, Mahnaz; Montazeri, Ali; Shojaeizadeh, Davoud; Nejat, Saharnaz; Khalajabadi Farahani, Farideh; Djazayeri, Abolghasem

2016-03-01

The consumption of different types of fast food is increasingly growing in all parts of the world, both in developed and developing countries. Because of the changes and transitions in the lifestyle and dietary habits of people, an increasing number of people from different age groups, particularly adolescents and young adults, are inclined toward consuming fast food. The objective of this study was to investigate the factors influencing fast-food consumption among adolescents in Tehran, Iran. The present qualitative study was conducted in 2012 - 2013 in Tehran, the capital of Iran. To achieve the objective of this study, 42 adolescents were enrolled in this study through a purposive sampling method, and the required data was collected via individual semi-structured in-depth interviews. Data collection and analysis were carried out simultaneously, and the collected data was analyzed via a thematic content analysis and using MAXQDA 10 software. In this study after coding the transcribed interviews, the findings were categorized into three main themes as follows: personal views, social factors, and family factors. Each theme included several categories and subcategories, and the coded sentences and phrases were placed under each category and subcategory. The results of this study showed that the number of factors promoting fast-food consumption appeared to be more than the inhibiting factors and that the diverse factors at the individual and social level influenced fast-food consumption among adolescents.

Risk factors for deep infection after total knee arthroplasty: a meta-analysis.

Science.gov (United States)

Chen, Jie; Cui, Yunying; Li, Xin; Miao, Xiangwan; Wen, Zhanpeng; Xue, Yan; Tian, Jing

2013-05-01

Estimated the risk factors for postoperative infection after total knee arthroplasty (TKA) to prevent its occurrence. The meta-analysis collected twelve cohorts or case-control studies which included 548 infected persons in 57,223 general cases. Review Manager 5.0 was operated to assess the heterogeneity and to give an overall estimate of the association of factors with postoperative infection after TKA. The main factors distinctly associated with infection after TKA were BMI (BMI >30: OR = 2.53, 95 % CI 1.25, 5.13; BMI >40: OR = 4.00, 95 % CI 1.23, 12.98), diabetes mellitus (OR = 3.72, 95 % CI 2.30, 6.01), hypertension (OR = 2.53, 95 % CI 1.07, 5.99), steroid therapy (OR = 2.04, 95 % CI 1.11, 3.74), and rheumatoid arthritis (OR = 1.83; 95 % CI 1.42, 2.36). It had no sufficient evidences to reveal that gender could lead to infection after TKA. Osteoarthritis appeared to have a moderately protective effect. Statistical analysis revealed no correlation between urinary tract infection, fixation method, ASA, bilateral operation, age, transfusion, antibiotics, bone graft, and infection. There were positive evidences for some certain factors which could be targeted for prevention of the onset of infection, but more studies are needed to define the association of some other controversial factors in infection, like osteoarthritis, gender and so on. The quality of studies also needs to be improved.

Factors affecting the HIV/AIDS epidemic: An ecological analysis of ...

African Journals Online (AJOL)

Factors affecting the HIV/AIDS epidemic: An ecological analysis of global data. ... Backward multiple linear regression analysis identified the proportion of Muslims, physicians density, and adolescent fertility rate are as the three most prominent factors linked with the national HIV epidemic. Conclusions: The findings support ...

Analysis of Economic Factors Affecting Stock Market

OpenAIRE

Xie, Linyin

2010-01-01

This dissertation concentrates on analysis of economic factors affecting Chinese stock market through examining relationship between stock market index and economic factors. Six economic variables are examined: industrial production, money supply 1, money supply 2, exchange rate, long-term government bond yield and real estate total value. Stock market comprises fixed interest stocks and equities shares. In this dissertation, stock market is restricted to equity market. The stock price in thi...

Multiple Linear Regression Analysis of Factors Affecting Real Property Price Index From Case Study Research In Istanbul/Turkey

Science.gov (United States)

Denli, H. H.; Koc, Z.

2015-12-01

Estimation of real properties depending on standards is difficult to apply in time and location. Regression analysis construct mathematical models which describe or explain relationships that may exist between variables. The problem of identifying price differences of properties to obtain a price index can be converted into a regression problem, and standard techniques of regression analysis can be used to estimate the index. Considering regression analysis for real estate valuation, which are presented in real marketing process with its current characteristics and quantifiers, the method will help us to find the effective factors or variables in the formation of the value. In this study, prices of housing for sale in Zeytinburnu, a district in Istanbul, are associated with its characteristics to find a price index, based on information received from a real estate web page. The associated variables used for the analysis are age, size in m2, number of floors having the house, floor number of the estate and number of rooms. The price of the estate represents the dependent variable, whereas the rest are independent variables. Prices from 60 real estates have been used for the analysis. Same price valued locations have been found and plotted on the map and equivalence curves have been drawn identifying the same valued zones as lines.

A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation

International Nuclear Information System (INIS)

Trucco, P.; Cagno, E.; Ruggeri, F.; Grande, O.

2008-01-01

The paper presents an innovative approach to integrate Human and Organisational Factors (HOF) into risk analysis. The approach has been developed and applied to a case study in the maritime industry, but it can also be utilised in other sectors. A Bayesian Belief Network (BBN) has been developed to model the Maritime Transport System (MTS), by taking into account its different actors (i.e., ship-owner, shipyard, port and regulator) and their mutual influences. The latter have been modelled by means of a set of dependent variables whose combinations express the relevant functions performed by each actor. The BBN model of the MTS has been used in a case study for the quantification of HOF in the risk analysis carried out at the preliminary design stage of High Speed Craft (HSC). The study has focused on a collision in open sea hazard carried out by means of an original method of integration of a Fault Tree Analysis (FTA) of technical elements with a BBN model of the influences of organisational functions and regulations, as suggested by the International Maritime Organisation's (IMO) Guidelines for Formal Safety Assessment (FSA). The approach has allowed the identification of probabilistic correlations between the basic events of a collision accident and the BBN model of the operational and organisational conditions. The linkage can be exploited in different ways, especially to support identification and evaluation of risk control options also at the organisational level. Conditional probabilities for the BBN have been estimated by means of experts' judgments, collected from an international panel of different European countries. Finally, a sensitivity analysis has been carried out over the model to identify configurations of the MTS leading to a significant reduction of accident probability during the operation of the HSC

Driven Factors Analysis of China’s Irrigation Water Use Efficiency by Stepwise Regression and Principal Component Analysis

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Renfu Jia

2016-01-01

Full Text Available This paper introduces an integrated approach to find out the major factors influencing efficiency of irrigation water use in China. It combines multiple stepwise regression (MSR and principal component analysis (PCA to obtain more realistic results. In real world case studies, classical linear regression model often involves too many explanatory variables and the linear correlation issue among variables cannot be eliminated. Linearly correlated variables will cause the invalidity of the factor analysis results. To overcome this issue and reduce the number of the variables, PCA technique has been used combining with MSR. As such, the irrigation water use status in China was analyzed to find out the five major factors that have significant impacts on irrigation water use efficiency. To illustrate the performance of the proposed approach, the calculation based on real data was conducted and the results were shown in this paper.

Modification and analysis of engineering hot spot factor of HFETR

International Nuclear Information System (INIS)

Hu Yuechun; Deng Caiyu; Li Haitao; Xu Taozhong; Mo Zhengyu

2014-01-01

This paper presents the modification and analysis of engineering hot spot factors of HFETR. The new factors are applied in the fuel temperature analysis and the estimated value of the safety allowable operating power of HFETR. The result shows the maximum cladding temperature of the fuel is lower when the new factor are in utilization, and the safety allowable operating power of HFETR if higher, thus providing the economical efficiency of HFETR. (authors)

Factor analysis and Mokken scaling of the Organizational Commitment Questionnaire in nurses.

Science.gov (United States)

Al-Yami, M; Galdas, P; Watson, R

2018-03-22

To generate an Arabic version of the Organizational Commitment Questionnaire that would be easily understood by Arabic speakers and would be sensitive to Arabic culture. The nursing workforce in Saudi Arabia is undergoing a process of Saudization but there is a need to understand the factors that will help to retain this workforce. No organizational commitment tools exist in Arabic that are specifically designed for health organizations. An Arabic version of the organizational commitment tool could aid Arabic speaking employers to understand their employees' perceptions of their organizations. Translation and back-translation followed by factor analysis (principal components analysis and confirmatory factor analysis) to test the factorial validity and item response theory (Mokken scaling). A two-factor structure was obtained for the Organizational Commitment Questionnaire comprising Factor 1: Value commitment; and Factor 2: Commitment to stay with acceptable reliability measured by internal consistency. A Mokken scale was obtained including items from both factors showing a hierarchy of items running from commitment to the organization and commitment to self. This study shows that the Arabic version of the OCQ retained the established two-factor structure of the original English-language version. Although the two factors - 'value commitment' and 'commitment to stay' - repudiate the original developers' single factor claim. A useful insight into the structure of the Organizational Commitment Questionnaire has been obtained with the novel addition of a hierarchical scale. The Organizational Commitment Questionnaire is now ready to be used with nurses in the Arab speaking world and could be used a tool to measure the contemporary commitment of nursing employees and in future interventions aimed at increasing commitment and retention of valuable nursing staff. © 2018 International Council of Nurses.

Intrinsic Risk Factors of Lateral Ankle Sprain: A Systematic Review and Meta-analysis.

Science.gov (United States)

Kobayashi, Takumi; Tanaka, Masashi; Shida, Masahiro

2016-01-01

Lateral ankle ligamentous sprain (LAS) is one of the most common injuries in recreational activities and competitive sports. Many studies have attempted to determine whether there are certain intrinsic factors that can predict LAS. However, no consensus has been reached on the predictive intrinsic factors. To identify the intrinsic risk factors of LAS by meta-analysis from data in randomized control trials and prospective cohort studies. A systematic computerized literature search of MEDLINE, CINAHL, ScienceDirect, SPORTDiscus, and Cochrane Register of Clinical Trials was performed. A computerized literature search from inception to January 2015 resulted in 1133 studies of the LAS intrinsic risk factors written in English. Systematic review. Level 4. The modified quality index was used to assess the quality of the design of the papers and the standardized mean difference was used as an index to pool included study outcomes. Eight articles were included in this systematic review. Meta-analysis results showed that body mass index, slow eccentric inversion strength, fast concentric plantar flexion strength, passive inversion joint position sense, and peroneus brevis reaction time correlated with LAS. Body mass index, slow eccentric inversion strength, fast concentric plantar flexion strength, passive inversion joint position sense, and the reaction time of the peroneus brevis were associated with significantly increased risk of LAS.

Non-negative factor analysis supporting the interpretation of elemental distribution images acquired by XRF

International Nuclear Information System (INIS)

Alfeld, Matthias; Falkenberg, Gerald; Wahabzada, Mirwaes; Bauckhage, Christian; Kersting, Kristian; Wellenreuther, Gerd

2014-01-01

Stacks of elemental distribution images acquired by XRF can be difficult to interpret, if they contain high degrees of redundancy and components differing in their quantitative but not qualitative elemental composition. Factor analysis, mainly in the form of Principal Component Analysis (PCA), has been used to reduce the level of redundancy and highlight correlations. PCA, however, does not yield physically meaningful representations as they often contain negative values. This limitation can be overcome, by employing factor analysis that is restricted to non-negativity. In this paper we present the first application of the Python Matrix Factorization Module (pymf) on XRF data. This is done in a case study on the painting Saul and David from the studio of Rembrandt van Rijn. We show how the discrimination between two different Co containing compounds with minimum user intervention and a priori knowledge is supported by Non-Negative Matrix Factorization (NMF).

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

Science.gov (United States)

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.

Supervised Cross-Modal Factor Analysis for Multiple Modal Data Classification

KAUST Repository

Wang, Jingbin

2015-10-09

In this paper we study the problem of learning from multiple modal data for purpose of document classification. In this problem, each document is composed two different modals of data, i.e., An image and a text. Cross-modal factor analysis (CFA) has been proposed to project the two different modals of data to a shared data space, so that the classification of a image or a text can be performed directly in this space. A disadvantage of CFA is that it has ignored the supervision information. In this paper, we improve CFA by incorporating the supervision information to represent and classify both image and text modals of documents. We project both image and text data to a shared data space by factor analysis, and then train a class label predictor in the shared space to use the class label information. The factor analysis parameter and the predictor parameter are learned jointly by solving one single objective function. With this objective function, we minimize the distance between the projections of image and text of the same document, and the classification error of the projection measured by hinge loss function. The objective function is optimized by an alternate optimization strategy in an iterative algorithm. Experiments in two different multiple modal document data sets show the advantage of the proposed algorithm over other CFA methods.

Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

Science.gov (United States)

Stankov, L

1979-07-01

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

Factor analysis of the Zarit Burden Interview in family caregivers of patients with amyotrophic lateral sclerosis.

Science.gov (United States)

Oh, Juyeon; Kim, Jung A

2018-02-01

The Zarit Burden Interview has been used in many studies to assess caregiver burden in family caregivers of patients with amyotrophic lateral sclerosis, but the factor structure of the Zarit Burden Interview in the caregivers of amyotrophic lateral sclerosis patients is unknown. The aim of this study was to explore the factor structure of the Zarit Burden Interview in family caregivers of amyotrophic lateral sclerosis patients using exploratory factor analysis. The exploratory factor analysis was performed using generalized least squares with oblique rotation in a sample of 202 family caregivers. Three factors had an eigenvalue greater than 1 and accounted for 60.33% of the total variance. The three factors were named as follows: (factor 1) "Social restrictions" (items 2, 3, and 10-15); (factor 2) "Self-criticism" (items 20-21); and (factor 3) "Anger and frustration" (items 1, 4-6, 9, and 16-19). The correlation between factors 1 and 3 was much higher (r = 0.79) than that between factors 1 and 2 (r = 0.14) or factors 2 and 3 (r = 0.15). The findings of this study enriched our understanding of several meaningful dimensions of the caregiving burden in caregivers of an amyotrophic lateral sclerosis population and provided opportunities for future intervention.

Contextual factors affecting autonomy for patients in Iranian hospitals: A qualitative study.

Science.gov (United States)

Ebrahimi, Hossein; Sadeghian, Efat; Seyedfatemi, Naeimeh; Mohammadi, Eesa; Crowley, Maureen

2016-01-01

Consideration of patient autonomy is an essential element in individualized, patient-centered, ethical care. Internal and external factors associated with patient autonomy are related to culture and it is not clear what they are in Iran. The aim of this study was to explore contextual factors affecting the autonomy of patients in Iranian hospitals. This was a qualitative study using conventional content analysis methods. Thirty-four participants (23 patients, 9 nurses, and 2 doctors) from three Iranian teaching hospitals, selected using purposive sampling, participated in semi-structured interviews. Unstructured observation and filed notes were other methods for data collection. The data were subjected to qualitative content analysis and analyzed using the MAXQDA-10 software. Five categories and sixteen subcategories were identified. The five main categories related to patient autonomy were: Intrapersonal factors, physical health status, supportive family and friends, communication style, and organizational constraints. In summary, this study uncovered contextual factors that the care team, managers, and planners in the health field should target in order to improve patient autonomy in Iranian hospitals.

Contextual factors affecting autonomy for patients in Iranian hospitals: A qualitative study

Science.gov (United States)

Ebrahimi, Hossein; Sadeghian, Efat; Seyedfatemi, Naeimeh; Mohammadi, Eesa; Crowley, Maureen

2016-01-01

Background: Consideration of patient autonomy is an essential element in individualized, patient-centered, ethical care. Internal and external factors associated with patient autonomy are related to culture and it is not clear what they are in Iran. The aim of this study was to explore contextual factors affecting the autonomy of patients in Iranian hospitals. Materials and Methods: This was a qualitative study using conventional content analysis methods. Thirty-four participants (23 patients, 9 nurses, and 2 doctors) from three Iranian teaching hospitals, selected using purposive sampling, participated in semi-structured interviews. Unstructured observation and filed notes were other methods for data collection. The data were subjected to qualitative content analysis and analyzed using the MAXQDA-10 software. Results: Five categories and sixteen subcategories were identified. The five main categories related to patient autonomy were: Intrapersonal factors, physical health status, supportive family and friends, communication style, and organizational constraints. Conclusions: In summary, this study uncovered contextual factors that the care team, managers, and planners in the health field should target in order to improve patient autonomy in Iranian hospitals. PMID:27186203

ANALYSIS OF THE FACTORS AFFECTING THE AVERAGE

Directory of Open Access Journals (Sweden)

Carmen BOGHEAN

2013-12-01

Full Text Available Productivity in agriculture most relevantly and concisely expresses the economic efficiency of using the factors of production. Labour productivity is affected by a considerable number of variables (including the relationship system and interdependence between factors, which differ in each economic sector and influence it, giving rise to a series of technical, economic and organizational idiosyncrasies. The purpose of this paper is to analyse the underlying factors of the average work productivity in agriculture, forestry and fishing. The analysis will take into account the data concerning the economically active population and the gross added value in agriculture, forestry and fishing in Romania during 2008-2011. The distribution of the average work productivity per factors affecting it is conducted by means of the u-substitution method.

Meta-analysis of greenhouse gas displacement factors of wood product substitution

International Nuclear Information System (INIS)

Sathre, Roger; O'Connor, Jennifer

2010-01-01

A displacement factor can express the efficiency of using biomass to reduce net greenhouse gas (GHG) emission, by quantifying the amount of emission reduction achieved per unit of wood use. Here we integrate data from 21 different international studies in a meta-analysis of the displacement factors of wood products substituted in place of non-wood materials. We calculate the displacement factors in consistent units of tons of carbon (tC) of emission reduction per tC in wood product. The displacement factors range from a low of -2.3 to a high of 15, with most lying in the range of 1.0 to 3.0. The average displacement factor value is 2.1, meaning that for each tC in wood products substituted in place of non-wood products, there occurs an average GHG emission reduction of approximately 2.1 tC. Expressed in other units, this value corresponds to roughly 3.9 t CO 2 eq emission reduction per ton of dry wood used. The few cases of negative displacement factors are the result of worst-case scenarios that are unrealistic in current practice. This meta-analysis quantifies the range of GHG benefits of wood substitution, and provides a clear climate rationale for increasing wood substitution in place of other products, provided that forests are sustainably managed and that wood residues are used responsibly.

Meta-analysis of greenhouse gas displacement factors of wood product substitution

Energy Technology Data Exchange (ETDEWEB)

Sathre, Roger [Ecotechnology, Mid Sweden University, 83125 Ostersund (Sweden); O' Connor, Jennifer [FPInnovations-Forintek, Vancouver, BC, Canada V6T 1W5 (Canada)

2010-04-15

A displacement factor can express the efficiency of using biomass to reduce net greenhouse gas (GHG) emission, by quantifying the amount of emission reduction achieved per unit of wood use. Here we integrate data from 21 different international studies in a meta-analysis of the displacement factors of wood products substituted in place of non-wood materials. We calculate the displacement factors in consistent units of tons of carbon (tC) of emission reduction per tC in wood product. The displacement factors range from a low of -2.3 to a high of 15, with most lying in the range of 1.0 to 3.0. The average displacement factor value is 2.1, meaning that for each tC in wood products substituted in place of non-wood products, there occurs an average GHG emission reduction of approximately 2.1 tC. Expressed in other units, this value corresponds to roughly 3.9 t CO{sub 2} eq emission reduction per ton of dry wood used. The few cases of negative displacement factors are the result of worst-case scenarios that are unrealistic in current practice. This meta-analysis quantifies the range of GHG benefits of wood substitution, and provides a clear climate rationale for increasing wood substitution in place of other products, provided that forests are sustainably managed and that wood residues are used responsibly.

Factors on green service industry: Case study at AirAsia

Science.gov (United States)

Abdullah, Muhammad-Azfar; Chew, Boon-Cheong; Hamid, Syaiful-Rizal

2017-03-01

Presently service organizations are challenged by fierce global competition, new technology and changing customer demands. These trends force service sectors to adapt environmental factors and places innovation at the core of their competitive strategy. On the other hand, service sectors challenge to deliver value memorable experiences and complete "service solutions" while lowering costs and keep sustainable. Despite, many studies have attempted to explore the factors that help toward environmental sustainability in the manufacturing sector, the service sector has not yet received a considerable attention in all world countries generally and in developing countries particularly. Thus, this paper aims to explore the factors that help to attain environmental sustainability in the service sector. A qualitative case study through semi-structured interview conducted with twenty managers from AirAsia to explore the factors that are related to environmental sustainability and green services. Besides, secondary data from document analysis was reviewed to gain more comprehensive understanding and triangulate the interview data. The finding of this paper emphasizes to three important factors namely institutional factors, process factors and result factors that each factor contain sustainability and innovations to promote competitive green service in the marketplace.

An Analysis of the Influencing Factors of Customer Retention in Tourism Resort Industry: A Case Study of Lingnan Impression Park, Guangzhou, China

Directory of Open Access Journals (Sweden)

Li Li

2014-09-01

Full Text Available The customer retention is an important factor in today’s increasingly tourism competitive markets which should be concerned seriously. At present, many academic customer retention researches mostly focused on the business market research in the hotel industry. In view of the tourism resort, especially the urban cultural themes attraction, analyzing the influencing factors of customer retention in such resort has its special significance. The aim of this study is to empirically explore the relationship among the cultural attractive, attraction operation, promotion strategy and tourist costs on customer retention in the urban cultural themes attraction. A quantitative research method was adopted to collect empirical data from the case study of Lingnan Impression Park, Guangzhou, China and the analysis of the influencing factors base on the integrated research approach for the urban cultural themes resort. The results indicate what extent these individual factors can have an impact on customer retention is beneficial for the resort marketing practices and several strategies are suggested about improving the degree of the customer retention to the urban cultural themes resorts in China.

Confirmatory Factor Analysis of the ISB - Burnout Syndrome Inventory

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Ana Maria T. Benevides-Pereira

2017-05-01

Full Text Available AimBurnout is a dysfunctional reaction to chronic occupational stress. The present study analysis the psychometric qualities of the Burnout Syndrome Inventory (ISB through Confirmatory Factor Analysis (CFA.MethodEmpirical study in a multi-centre and multi-occupational sample (n = 701 using the ISB. The Part I assesses antecedent factors: Positive Organizational Conditions (PC and Negative Organizational Conditions (NC. The Part II assesses the syndrome: Emotional Exhaustion (EE, Dehumanization (DE, Emotional Distancing (ED and Personal Accomplishment (PA.ResultsThe highest means occurred in the positive scales CP (M = 23.29, SD = 5.89 and PA (M = 14.84, SD = 4.71. Negative conditions showed the greatest variability (SD = 6.03. Reliability indexes were reasonable, with the lowest rate at .77 for DE and the highest rate .91 for PA. The CFA revealed RMSEA = .057 and CFI = .90 with all scales regressions showing significant values (β = .73 until β = .92.ConclusionThe ISB showed a plausible instrument to evaluate burnout. The two sectors maintained the initial model and confirmed the theoretical presupposition. This instrument makes possible a more comprehensive idea of the labour context, and one or another part may be used separately according to the needs and the aims of the assessor.

Factor analysis with a priori knowledge - application in dynamic cardiac SPECT

Energy Technology Data Exchange (ETDEWEB)

Sitek, A.; Di Bella, E.V.R.; Gullberg, G.T. [Medical Imaging Research Laboratory, Department of Radiology, University of Utah, CAMT, 729 Arapeen Drive, Salt Lake City, UT 84108-1218 (United States)

2000-09-01

Two factor analysis of dynamic structures (FADS) methods for the extraction of time-activity curves (TACs) from cardiac dynamic SPECT data sequences were investigated. One method was based on a least squares (LS) approach which was subject to positivity constraints. The other method was the well known apex-seeking (AS) method. A post-processing step utilizing a priori information was employed to correct for the non-uniqueness of the FADS solution. These methods were used to extract {sup 99m}Tc-teboroxime TACs from computer simulations and from experimental canine and patient studies. In computer simulations, the LS and AS methods, which are completely different algorithms, yielded very similar and accurate results after application of the correction for non-uniqueness. FADS-obtained blood curves correlated well with curves derived from region of interest (ROI) measurements in the experimental studies. The results indicate that the factor analysis techniques can be used for semi-automatic estimation of activity curves derived from cardiac dynamic SPECT images, and that they can be used for separation of physiologically different regions in dynamic cardiac SPECT studies. (author)

Dispersion-theoretical analysis of the nucleon electromagnetic form factors

Energy Technology Data Exchange (ETDEWEB)

Belushkin, M.

2007-09-29

The structure of the proton and the neutron is of fundamental importance for the study of the strong interaction dynamics over a wide range of momentum transfers. The nucleon form factors encode information on the internal structure of the nucleon as probed by the electromagnetic interaction, and, to a certain extent, reflect the charge and magnetisation distributions within the proton and the neutron. In this thesis we report on our investigation of the electromagnetic form factors of the proton and the neutron with dispersion relation techniques, including known experimental input on the {pi}{pi}, K anti K and the {rho}{pi} continua and perturbative QCD constraints. We include new experimental data on the pion form factor and the nucleon form factors in our simultaneous analysis of all four form factors in both the space- and the timelike regions for all momentum transfers, and perform Monte- Carlo sampling in order to obtain theoretical uncertainty bands. Finally, we discuss the implications of our results on the pion cloud of the nucleon, the nucleon radii and the Okubo-Zweig-Iizuka rule, and present our results of a model-independent approach to estimating two-photon effects in elastic electron-proton scattering. (orig.)

Dispersion-theoretical analysis of the nucleon electromagnetic form factors

International Nuclear Information System (INIS)

Belushkin, M.

2007-01-01

The structure of the proton and the neutron is of fundamental importance for the study of the strong interaction dynamics over a wide range of momentum transfers. The nucleon form factors encode information on the internal structure of the nucleon as probed by the electromagnetic interaction, and, to a certain extent, reflect the charge and magnetisation distributions within the proton and the neutron. In this thesis we report on our investigation of the electromagnetic form factors of the proton and the neutron with dispersion relation techniques, including known experimental input on the ππ, K anti K and the ρπ continua and perturbative QCD constraints. We include new experimental data on the pion form factor and the nucleon form factors in our simultaneous analysis of all four form factors in both the space- and the timelike regions for all momentum transfers, and perform Monte- Carlo sampling in order to obtain theoretical uncertainty bands. Finally, we discuss the implications of our results on the pion cloud of the nucleon, the nucleon radii and the Okubo-Zweig-Iizuka rule, and present our results of a model-independent approach to estimating two-photon effects in elastic electron-proton scattering. (orig.)

Evaluation of Parallel Analysis Methods for Determining the Number of Factors

Science.gov (United States)

Crawford, Aaron V.; Green, Samuel B.; Levy, Roy; Lo, Wen-Juo; Scott, Lietta; Svetina, Dubravka; Thompson, Marilyn S.

2010-01-01

Population and sample simulation approaches were used to compare the performance of parallel analysis using principal component analysis (PA-PCA) and parallel analysis using principal axis factoring (PA-PAF) to identify the number of underlying factors. Additionally, the accuracies of the mean eigenvalue and the 95th percentile eigenvalue criteria…

The mathematical pathogenetic factors analysis of acute inflammatory diseases development of bronchopulmonary system among infants

Directory of Open Access Journals (Sweden)

G. O. Lezhenko

2017-10-01

Full Text Available The purpose. To study the factor structure and to establish the associative interaction of pathogenetic links of acute diseases development of the bronchopulmonary system in infants.Materials and methods. The examination group consisted of 59 infants (average age 13.8 ± 1.4 months sick with acute inflammatory bronchopulmonary diseases. Also we tested the level of 25-hydroxyvitamin D (25(ОНD, vitamin D-binding protein, hBPI, cathelicidin LL-37, ß1-defensins, lactoferrin in blood serum with the help of immunoenzymometric analysis. Selection of prognostically important pathogenetic factors of acute bronchopulmonary disease among infants was conducted using ROC-analysis. The procedure for classifying objects was carried out using Hierarchical Cluster Analysis by the method of Centroid-based clustering. Results. Based on the results of the ROC-analysis were selected 15 potential predictors of the development of acute inflammatory diseases of the bronchopulmonary system among infants. The factor analysis made it possible to determine the 6 main components . The biggest influence in the development of the disease was made by "the anemia factor", "the factor of inflammation", "the maternal factor", "the vitamin D supply factor", "the immune factor" and "the phosphorus-calcium exchange factor” with a factor load of more than 0.6. The performed procedure of hierarchical cluster analysis confirmed the initial role of immuno-inflammatory components. The conclusions. The highlighted factors allowed to define a group of parameters, that must be influenced to achieve a maximum effect in carrying out preventive and therapeutic measures. First of all, it is necessary to influence the "the anemia factor" and "the calcium exchange factor", as well as the "the vitamin D supply factor". In other words, to correct vitamin D deficiency and carry out measures aimed at preventing the development of anemia. The prevention and treatment of the pathological course of

Sea level rise and the geoid: factor analysis approach

Directory of Open Access Journals (Sweden)

Alexey Sadovski

2013-08-01

Full Text Available Sea levels are rising around the world, and this is a particular concern along most of the coasts of the United States. A 1989 EPA report shows that sea levels rose 5-6 inches more than the global average along the Mid-Atlantic and Gulf Coasts in the last century. The main reason for this is coastal land subsidence. This sea level rise is considered more as relative sea level rise than global sea level rise. Thus, instead of studying sea level rise globally, this paper describes a statistical approach by using factor analysis of regional sea level rates of change. Unlike physical models and semi-empirical models that attempt to approach how much and how fast sea levels are changing, this methodology allows for a discussion of the factor(s that statistically affects sea level rates of change, and seeks patterns to explain spatial correlations.

An exploration study to find important factors influencing on expert systems

Directory of Open Access Journals (Sweden)

Naser Azad

2013-09-01

Full Text Available Knowledge management plays an important role in modern management systems since many existing systems move towards learning organizations. Expert systems, on the other hand, are considered as the most popular techniques for adapting recent developments on knowledge management. This paper presents an empirical investigation to find important factors influencing adaptation of expert systems. The proposed study designs a questionnaire in Likert scale consists of 25 questions, distributes it among 258 people who have recently graduated from computer science and they are familiar with implementation of expert systems. Cronbach alpha is calculated as 0.730 and Kaiser-Meyer-Olkin Measure of Sampling Adequacy and Approx. Chi-Square are 0.748 and 1377.397, respectively. The study has implemented principal component analysis and the results have indicated that there were four factors influencing expert systems including systems management, intelligence systems, system analysis and specialized analysis.

Disruptive Event Biosphere Dose Conversion Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

M. Wasiolek

2004-09-08

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2004 [DIRS 169671]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis''. The objective of this

Disruptive Event Biosphere Dose Conversion Factor Analysis

International Nuclear Information System (INIS)

M. Wasiolek

2004-01-01

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2004 [DIRS 169671]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis''. The objective of this analysis was to develop the BDCFs for the volcanic ash

Prognostic factors in pediatric pulmonary arterial hypertension: A systematic review and meta-analysis.

Science.gov (United States)

Ploegstra, Mark-Jan; Zijlstra, Willemijn M H; Douwes, Johannes M; Hillege, Hans L; Berger, Rolf M F

2015-04-01

Despite the introduction of targeted therapies in pediatric pulmonary arterial hypertension (PAH), prognosis remains poor. For the definition of treatment strategies and guidelines, there is a high need for an evidence-based recapitulation of prognostic factors. The aim of this study was to identify and evaluate prognostic factors in pediatric PAH by a systematic review of the literature and to summarize the prognostic value of currently reported prognostic factors using meta-analysis. Medline, EMBASE and Cochrane Library were searched on April 1st 2014 to identify original studies that described predictors of mortality or lung-transplantation exclusively in children with PAH. 1053 citations were identified, of which 25 were included for further analysis. Hazard ratios (HR) and 95% confidence intervals were extracted from the papers. For variables studied in at least three non-overlapping cohorts, a combined HR was calculated using random-effects meta-analysis. WHO functional class (WHO-FC, HR 2.7), (N-terminal pro-) brain natriuretic peptide ([NT-pro]BNP, HR 3.2), mean right atrial pressure (mRAP, HR 1.1), cardiac index (HR 0.7), indexed pulmonary vascular resistance (PVRi, HR 1.3) and acute vasodilator response (HR 0.3) were identified as significant prognostic factors (p ≤ 0.001). This systematic review combined with separate meta-analyses shows that WHO-FC, (NT-pro)BNP, mRAP, PVRi, cardiac index and acute vasodilator response are consistently reported prognostic factors for outcome in pediatric PAH. These variables are useful clinical tools to assess prognosis and should be incorporated in treatment strategies and guidelines for children with PAH. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

An inter-battery factor analysis of the comrey personality scales and the 16 personality factor questionnaire

OpenAIRE

Gideon P. de Bruin

2000-01-01

The scores of 700 Afrikaans-speaking university students on the Comrey Personality Scales and the 16 Personality Factor Questionnaire were subjected to an inter-battery factor analysis. This technique uses only the correlations between two sets of variables and reveals only the factors that they have in common. Three of the Big Five personality factors were revealed, namely Extroversion, Neuroticism and Conscientiousness. However, the Conscientiousness factor contained a relatively strong uns...

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

Science.gov (United States)

Song, Malin; Chen, Yu; An, Qingxian

2018-05-01

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

Multi-Scale Factor Analysis of High-Dimensional Brain Signals

KAUST Repository

Ting, Chee-Ming

2017-05-18

In this paper, we develop an approach to modeling high-dimensional networks with a large number of nodes arranged in a hierarchical and modular structure. We propose a novel multi-scale factor analysis (MSFA) model which partitions the massive spatio-temporal data defined over the complex networks into a finite set of regional clusters. To achieve further dimension reduction, we represent the signals in each cluster by a small number of latent factors. The correlation matrix for all nodes in the network are approximated by lower-dimensional sub-structures derived from the cluster-specific factors. To estimate regional connectivity between numerous nodes (within each cluster), we apply principal components analysis (PCA) to produce factors which are derived as the optimal reconstruction of the observed signals under the squared loss. Then, we estimate global connectivity (between clusters or sub-networks) based on the factors across regions using the RV-coefficient as the cross-dependence measure. This gives a reliable and computationally efficient multi-scale analysis of both regional and global dependencies of the large networks. The proposed novel approach is applied to estimate brain connectivity networks using functional magnetic resonance imaging (fMRI) data. Results on resting-state fMRI reveal interesting modular and hierarchical organization of human brain networks during rest.

The recovery factors analysis of the human errors for research reactors

International Nuclear Information System (INIS)

Farcasiu, M.; Nitoi, M.; Apostol, M.; Turcu, I.; Florescu, Ghe.

2006-01-01

The results of many Probabilistic Safety Assessment (PSA) studies show a very significant contribution of human errors to systems unavailability of the nuclear installations. The treatment of human interactions is considered one of the major limitations in the context of PSA. To identify those human actions that can have an effect on system reliability or availability applying the Human Reliability Analysis (HRA) is necessary. The recovery factors analysis of the human action is an important step in HRA. This paper presents how can be reduced the human errors probabilities (HEP) using those elements that have the capacity to recovery human error. The recovery factors modeling is marked to identify error likelihood situations or situations that conduct at development of the accident. This analysis is realized by THERP method. The necessary information was obtained from the operating experience of the research reactor TRIGA of the INR Pitesti. The required data were obtained from generic databases. (authors)

PRINCIPAL COMPONENT ANALYSIS OF FACTORS DETERMINING PHOSPHATE ROCK DISSOLUTION ON ACID SOILS

Directory of Open Access Journals (Sweden)

Yusdar Hilman

2016-10-01

Full Text Available Many of the agricultural soils in Indonesia are acidic and low in both total and available phosphorus which severely limits their potential for crops production. These problems can be corrected by application of chemical fertilizers. However, these fertilizers are expensive, and cheaper alternatives such as phosphate rock (PR have been considered. Several soil factors may influence the dissolution of PR in soils, including both chemical and physical properties. The study aimed to identify PR dissolution factors and evaluate their relative magnitude. The experiment was conducted in Soil Chemical Laboratory, Universiti Putra Malaysia and Indonesian Center for Agricultural Land Resources Research and Development from January to April 2002. The principal component analysis (PCA was used to characterize acid soils in an incubation system into a number of factors that may affect PR dissolution. Three major factors selected were soil texture, soil acidity, and fertilization. Using the scores of individual factors as independent variables, stepwise regression analysis was performed to derive a PR dissolution function. The factors influencing PR dissolution in order of importance were soil texture, soil acidity, then fertilization. Soil texture factors including clay content and organic C, and soil acidity factor such as P retention capacity interacted positively with P dissolution and promoted PR dissolution effectively. Soil texture factors, such as sand and silt content, soil acidity factors such as pH, and exchangeable Ca decreased PR dissolution.

Cardiometabolic risk clustering in spinal cord injury: results of exploratory factor analysis.

Science.gov (United States)

Libin, Alexander; Tinsley, Emily A; Nash, Mark S; Mendez, Armando J; Burns, Patricia; Elrod, Matt; Hamm, Larry F; Groah, Suzanne L

2013-01-01

Evidence suggests an elevated prevalence of cardiometabolic risks among persons with spinal cord injury (SCI); however, the unique clustering of risk factors in this population has not been fully explored. The purpose of this study was to describe unique clustering of cardiometabolic risk factors differentiated by level of injury. One hundred twenty-one subjects (mean 37 ± 12 years; range, 18-73) with chronic C5 to T12 motor complete SCI were studied. Assessments included medical histories, anthropometrics and blood pressure, and fasting serum lipids, glucose, insulin, and hemoglobin A1c (HbA1c). The most common cardiometabolic risk factors were overweight/obesity, high levels of low-density lipoprotein (LDL-C), and low levels of high-density lipoprotein (HDL-C). Risk clustering was found in 76.9% of the population. Exploratory principal component factor analysis using varimax rotation revealed a 3-factor model in persons with paraplegia (65.4% variance) and a 4-factor solution in persons with tetraplegia (73.3% variance). The differences between groups were emphasized by the varied composition of the extracted factors: Lipid Profile A (total cholesterol [TC] and LDL-C), Body Mass-Hypertension Profile (body mass index [BMI], systolic blood pressure [SBP], and fasting insulin [FI]); Glycemic Profile (fasting glucose and HbA1c), and Lipid Profile B (TG and HDL-C). BMI and SBP formed a separate factor only in persons with tetraplegia. Although the majority of the population with SCI has risk clustering, the composition of the risk clusters may be dependent on level of injury, based on a factor analysis group comparison. This is clinically plausible and relevant as tetraplegics tend to be hypo- to normotensive and more sedentary, resulting in lower HDL-C and a greater propensity toward impaired carbohydrate metabolism.

Reliability Analysis of a Composite Wind Turbine Blade Section Using the Model Correction Factor Method: Numerical Study and Validation

DEFF Research Database (Denmark)

Dimitrov, Nikolay Krasimirov; Friis-Hansen, Peter; Berggreen, Christian

2013-01-01

by the composite failure criteria. Each failure mode has been considered in a separate component reliability analysis, followed by a system analysis which gives the total probability of failure of the structure. The Model Correction Factor method used in connection with FORM (First-Order Reliability Method) proved...

Assessing Saudi medical students learning approach using the revised two-factor study process questionnaire.

Science.gov (United States)

Shaik, Shaffi Ahamed; Almarzuqi, Ahmed; Almogheer, Rakan; Alharbi, Omar; Jalal, Abdulaziz; Alorainy, Majed

2017-08-17

To assess learning approaches of 1st, 2nd, and 3rd-year medical students by using revised two-factor study process questionnaire, and to assess reliability and validity of the questionnaire. This cross-sectional study was conducted at the College of Medicine, Riyadh, Saudi Arabia in 2014. The revised two-factor study process questionnaire (R-SPQ-2F) was completed by 610 medical students of both genders, from foundation (first year), central nervous system (second year), medicine and surgery (third year) courses. The study process was evaluated by computing mean scores of two research study approaches (deep & surface) using student's t-test and one-way analysis of variance. The internal consistency and construct validity of the questionnaire were assessed using Cronbach's α and factor analysis. The mean score of deep approach was significantly higher than the surface approach among participants(t (770) =7.83, p= 0.000) for the four courses. The mean scores of deep approach were significantly higher among participants with higher grade point average (F (2,768) =13.31, p=0.001) along with more number of study hours by participants (F (2,768) =20.08, p=0.001). The Cronbach's α-values of items at 0.70 indicate the good internal consistency of questionnaire used. Factor analysis confirms two factors (deep and surface approaches) of R-SPQ-2F. The deep approach to learning was the primary approach among 1st, 2nd and 3rd-year King Saud University medical students. This study confirms reliability and validity of the revised two-factor study process questionnaire. Medical educators could use the results of such studies to make required changes in the curriculum.

Bayesian Sensitivity Analysis of a Nonlinear Dynamic Factor Analysis Model with Nonparametric Prior and Possible Nonignorable Missingness.

Science.gov (United States)

Tang, Niansheng; Chow, Sy-Miin; Ibrahim, Joseph G; Zhu, Hongtu

2017-12-01

Many psychological concepts are unobserved and usually represented as latent factors apprehended through multiple observed indicators. When multiple-subject multivariate time series data are available, dynamic factor analysis models with random effects offer one way of modeling patterns of within- and between-person variations by combining factor analysis and time series analysis at the factor level. Using the Dirichlet process (DP) as a nonparametric prior for individual-specific time series parameters further allows the distributional forms of these parameters to deviate from commonly imposed (e.g., normal or other symmetric) functional forms, arising as a result of these parameters' restricted ranges. Given the complexity of such models, a thorough sensitivity analysis is critical but computationally prohibitive. We propose a Bayesian local influence method that allows for simultaneous sensitivity analysis of multiple modeling components within a single fitting of the model of choice. Five illustrations and an empirical example are provided to demonstrate the utility of the proposed approach in facilitating the detection of outlying cases and common sources of misspecification in dynamic factor analysis models, as well as identification of modeling components that are sensitive to changes in the DP prior specification.

Dietary Patterns Derived Using Exploratory and Confirmatory Factor Analysis are Stable and Generalizable Across Race, Region, and Gender Subgroups in the REGARDS Study

Science.gov (United States)

Judd, Suzanne E.; Letter, Abraham J.; Shikany, James M.; Roth, David L.; Newby, P. K.

2015-01-01

Background: Examining diet as a whole using dietary patterns as exposures is a complementary method to using single food or nutrients in studies of diet and disease, but the generalizability of intake patterns across race, region, and gender in the United States has not been established. Objective: To employ rigorous statistical analysis to empirically derive dietary patterns in a large bi-racial, geographically diverse population and examine whether results are stable across population subgroups. Design: The present analysis utilized data from 21,636 participants in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study who completed the Block 98 food frequency questionnaire. We employed exploratory factor analysis and confirmatory factor analyses on 56 different food groups iteratively and examined differences by race, region, and sex to determine the optimal factor solution in our sample. Results: Five dietary patterns emerged: the “Convenience” pattern was characterized by mixed dishes; the “Plant-based” pattern by fruits, vegetables, and fish; the “Sweets/Fats” pattern by sweet snacks, desserts, and fats and oils; the “Southern” pattern by fried foods, organ meat, and sweetened beverages; and the “Alcohol/Salads” pattern by beer, wine, liquor, and salads. Differences were most pronounced in the Southern pattern with black participants, those residing in the Southeast, and participants not completing high school having the highest scores. Conclusion: Five meaningful dietary patterns emerged in the REGARDS study and showed strong congruence across race, sex, and region. Future research will examine associations between these patterns and health outcomes to better understand racial disparities in disease and inform prevention efforts. PMID:25988129

Quinn’s Leadership Roles: A Confirmatory Factor Analysis Study in Portuguese Health Services

Directory of Open Access Journals (Sweden)

Pedro Parreira

2015-08-01

Full Text Available Purpose: To assess the psychometric properties of Quinn’s leadership questionnaire (CFV questionnaire; 1988 in Portuguese health services. Design: Cross-sectional study, using Quinn’s leadership questionnaire, administered to registered nurses and physicians in Portuguese health services (N = 687. Method: Self-administered survey applied to two samples. In the first sample (convenience; N = 249 Portuguese health professionals, exploratory factor and reliability analyses were performed to the CFV questionnaire. In the second sample (stratified; N = 50 surgical units of 33 Portuguese hospitals, confirmatory factor analyses were performed using LISREL 8.80. Findings: In the first sample, an eight-factor solution emerged accounting for 65.46% of the total variance, in an interpretable factor structure (loadings> .50, with Cronbach’s α greater than .79. This factor structure, replicated in the second sample, showed reasonable goodness-of-fit of the model to each of the leadership roles, that is, to the eight quadrants and global model. Overall, the models showed nomological validity, with scores between good and acceptable (.235 < x2/df < 2.055 and .00 < RMSEA < .077. Conclusions: Quinn’s leadership questionnaire showed good reliability and validity for the eight leadership roles, proving to be suitable for use in health care/hospital settings.

Risk factors for suicide behaviors in the observational schizophrenia outpatient health outcomes (SOHO study

Directory of Open Access Journals (Sweden)

Brugnoli Roberto

2012-07-01

Full Text Available Abstract Background To identify risk factors for suicide using data from a large, 3-year, multinational follow-up study of schizophrenia (SOHO study. Methods Baseline characteristics of 8,871 adult patients with schizophrenia were included in a logistic regression post-hoc analysis comparing patients who attempted and/or committed suicide during the study with those who did not. Results 384 (4.3% patients attempted or committed suicide. Completed suicides were 27 (0.3%. The significant risk factors for suicide behaviors were previous suicidality, depressive symptoms, prolactin-related adverse events, male gender and history of hospitalization for schizophrenia. Conclusions In view of the observational design of the study and the post-hoc nature of the analysis, the identified risk factors should be confirmed by ad-hoc specifically designed studies.

Multiple timescale analysis and factor analysis of energy ecological footprint growth in China 1953-2006

International Nuclear Information System (INIS)

Chen Chengzhong; Lin Zhenshan

2008-01-01

Scientific analysis of energy consumption and its influencing factors is of great importance for energy strategy and policy planning. The energy consumption in China 1953-2006 is estimated by applying the energy ecological footprint (EEF) method, and the fluctuation periods of annual China's per capita EEF (EEF cpc ) growth rate are analyzed with the empirical mode decomposition (EMD) method in this paper. EEF intensity is analyzed to depict energy efficiency in China. The main timescales of the 37 factors that affect the annual growth rate of EEF cpc are also discussed based on EMD and factor analysis methods. Results show three obvious undulation cycles of the annual growth rate of EEF cpc , i.e., 4.6, 14.4 and 34.2 years over the last 53 years. The analysis findings from the common synthesized factors of IMF1, IMF2 and IMF3 timescales of the 37 factors suggest that China's energy policy-makers should attach more importance to stabilizing economic growth, optimizing industrial structure, regulating domestic petroleum exploitation and improving transportation efficiency

Hybrid PV/diesel solar power system design using multi-level factor analysis optimization

Science.gov (United States)

Drake, Joshua P.

Solar power systems represent a large area of interest across a spectrum of organizations at a global level. It was determined that a clear understanding of current state of the art software and design methods, as well as optimization methods, could be used to improve the design methodology. Solar power design literature was researched for an in depth understanding of solar power system design methods and algorithms. Multiple software packages for the design and optimization of solar power systems were analyzed for a critical understanding of their design workflow. In addition, several methods of optimization were studied, including brute force, Pareto analysis, Monte Carlo, linear and nonlinear programming, and multi-way factor analysis. Factor analysis was selected as the most efficient optimization method for engineering design as it applied to solar power system design. The solar power design algorithms, software work flow analysis, and factor analysis optimization were combined to develop a solar power system design optimization software package called FireDrake. This software was used for the design of multiple solar power systems in conjunction with an energy audit case study performed in seven Tibetan refugee camps located in Mainpat, India. A report of solar system designs for the camps, as well as a proposed schedule for future installations was generated. It was determined that there were several improvements that could be made to the state of the art in modern solar power system design, though the complexity of current applications is significant.

Factors affecting public prejudice and social distance on mental illness: analysis of contextual effect by multi-level analysis.

Science.gov (United States)

Jang, Hyeongap; Lim, Jun-Tae; Oh, Juhwan; Lee, Seon-Young; Kim, Yong-Ik; Lee, Jin-Seok

2012-03-01

While there have been many quantitative studies on the public's attitude towards mental illnesses, it is hard to find quantitative study which focused on the contextual effect on the public's attitude. The purpose of this study was to identify factors that affect the public's beliefs and attitudes including contextual effects. We analyzed survey on the public's beliefs and attitudes towards mental illness in Korea with multi-level analysis. We analyzed the public's beliefs and attitudes in terms of prejudice as an intermediate outcome and social distance as a final outcome. Then, we focused on the associations of factors, which were individual and regional socio-economic factors, familiarity, and knowledge based on the comparison of the intermediate and final outcomes. Prejudice was not explained by regional variables but was only correlated with individual factors. Prejudice increased with age and decreased by high education level. However, social distance controlling for prejudice increased in females, in people with a high education level, and in regions with a high education level and a high proportion of the old. Therefore, social distance without controlling for prejudice increased in females, in the elderly, in highly educated people, and in regions with a high education and aged community. The result of the multi-level analysis for the regional variables suggests that social distance for mental illness are not only determined by individual factors but also influenced by the surroundings so that it could be tackled sufficiently with appropriate considering of the relevant regional context with individual characteristics.

Pediatric nurses' perception of factors associated with caring self-efficacy: A qualitative content analysis.

Science.gov (United States)

Alavi, Azam; Bahrami, Masoud; Zargham-Boroujeni, Ali; Yousefy, Alireza

2015-01-01

Nurses, who are considered to form the largest group of professional healthcare providers, face the challenge of maintaining, promoting, and providing quality nursing care and to prepare themselves to function confidently and to care effectively. Among the factors affecting nursing performance, self-efficacy has been expected to have the greatest influence. However, the concept of caring self-efficacy was not considered and no research has been done in this field in Iran. This study was conducted to explore and identify the factors described by pediatric nurses as related to caring self-efficacy. This is a qualitative study conducted through content analysis in 2013 in Iran. Twenty-four participants were selected through purposive sampling method from pediatric nurses and educators. Data were collected through semi-structured interviews. Data were analyzed using conventional content analysis method. The analysis of the interviews in this study led to the development of four main themes: (1) Professional knowledge of children caring, (2) experience, (3) caring motivation, and (4) efficient educational system as the factors influencing caring self-efficacy perception of pediatric nurses. This article presents the factors associated with the perception of caring self-efficacy in pediatric nurses' perspective. This finding can be used by nursing administrators and instructors, especially in the area of pediatric caring, to enhance nursing professional practice and the quality of pediatric caring.

A confirmatory factor analysis of the Utrecht Work Engagement Scale for Students in a Chinese sample.

Science.gov (United States)

Meng, Lina; Jin, Yi

2017-02-01

Educational institutions play an important role in encouraging students' engagement with course work. Educators are finding instruments to measure students' engagement in order to develop strategies to improve it. Little is known about the factor structure of the Utrecht Work Engagement Scale for Students among Chinese nursing students. The aim of this research was to examine the factor structure of the Utrecht Work Engagement Scale for Students via confirmatory factor analysis. The study used a cross-sectional design. A sample of 480 students from a nursing school in one Chinese university completed the Utrecht Work Engagement Scale for Students. Factor analysis was used to analyze the resulting data. The overall results of internal consistency reliability and confirmatory factor analysis provided evidence supporting the reliability and three-factor structure of the Utrecht Work Engagement Scale for Students. The total internal consistency reliability coefficients were 0.91. Model comparison tests indicated that an oblique factors model that permitted correlations between pairs of error terms fitted the data better than other first-order models. In addition, due to the three strongly intercorrelated factors, a second-order model was found to fit the data well, providing support for the factorial structure of the Utrecht Work Engagement Scale for Students. The findings of confirmatory factor analysis provided evidence supporting the reliability and three-factor structure of the Utrecht Work Engagement Scale for Students when evaluated with a Chinese nursing student sample in this study. Thus, it is appropriate to use The Utrecht Work Engagement Scale for Students in for assessing the engagement among Chinese nursing students. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis of 'human element related trip case book in Korean NPPs' using organizational factors

International Nuclear Information System (INIS)

Kim, S. Y.; Kim, Y. I.; Lee, Y. S.; Kim, C. S.; Jung, C. H.; Jung, W. D.

2002-01-01

There have been no studies appling organizational factors to data analysis in Korean NPPs. In this paper, data in 'human element related trip case book in Korean NPPs' are analyzed and categorized by the 20 organizational factors of NRC-BNL according to the cause of reactor trip. These inform us how organizational factors affected on the safety of Korean NPPs. Consequently important organizational factor are identified through which it is known that NPP organization would have a tendency

Two Expectation-Maximization Algorithms for Boolean Factor Analysis

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Húsek, Dušan; Polyakov, P.Y.

2014-01-01

Roč. 130, 23 April (2014), s. 83-97 ISSN 0925-2312 R&D Projects: GA ČR GAP202/10/0262 Grant - others:GA MŠk(CZ) ED1.1.00/02.0070; GA MŠk(CZ) EE.2.3.20.0073 Program:ED Institutional research plan: CEZ:AV0Z10300504 Keywords : Boolean Factor analysis * Binary Matrix factorization * Neural networks * Binary data model * Dimension reduction * Bars problem Subject RIV: IN - Informatics, Computer Science Impact factor: 2.083, year: 2014

Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

Energy Technology Data Exchange (ETDEWEB)

Stevens, Andrew J.; Pu, Yunchen; Sun, Yannan; Spell, Gregory; Carin, Lawrence

2017-04-20

We introduce new dictionary learning methods for tensor-variate data of any order. We represent each data item as a sum of Kruskal decomposed dictionary atoms within the framework of beta-process factor analysis (BPFA). Our model is nonparametric and can infer the tensor-rank of each dictionary atom. This Kruskal-Factor Analysis (KFA) is a natural generalization of BPFA. We also extend KFA to a deep convolutional setting and develop online learning methods. We test our approach on image processing and classification tasks achieving state of the art results for 2D & 3D inpainting and Caltech 101. The experiments also show that atom-rank impacts both overcompleteness and sparsity.

Factors Influencing the Organizational Stress among Teachers Working in Higher Education Sector in Kerala: An Empirical Analysis

Science.gov (United States)

Areekkuzhiyil, Santhosh

2014-01-01

The study aims to explore the various factors that influence the organizational stress of teachers working in higher education sector in the state of Kerala. The data required for the study has been conveniently collected from 200 teachers working in higher education sector. Exploratory factor analysis revealed nine factors, which significantly…

Confirmatory factor analysis using Microsoft Excel.

Science.gov (United States)

Miles, Jeremy N V

2005-11-01

This article presents a method for using Microsoft (MS) Excel for confirmatory factor analysis (CFA). CFA is often seen as an impenetrable technique, and thus, when it is taught, there is frequently little explanation of the mechanisms or underlying calculations. The aim of this article is to demonstrate that this is not the case; it is relatively straightforward to produce a spreadsheet in MS Excel that can carry out simple CFA. It is possible, with few or no programming skills, to effectively program a CFA analysis and, thus, to gain insight into the workings of the procedure.

Seizure Self-Efficacy Scale for Children with Epilepsy: Confirmatory and Exploratory Factor Analysis

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Şerife Tutar Güven

2017-12-01

Full Text Available Aim: In the past few years, the concept of self-efficacy in children with epilepsy has become increasingly important. This study aimed to analyze the psychometric aspects of the Turkish version of the Seizure Self-Efficacy Scale for Children. Materials and Methods: This is a cross-sectional survey. The study data were collected using the Seizure Self-Efficacy Scale for Children and Child Introduction Form. The study sample included 166 children who were between 9 and 17 years of age. The authors assessed the reliability and construct validity of the study data using exploratory and confirmatory factor analyses (CFA. Results: The original model was not confirmed by the CFA. The analysis tool included 15 items in two factors. Reliability analysis showed that the two factors were acceptable and valid. The tool was valid and reliable for measuring the self-efficacy of epileptic children. The factor structure was derived from and confirmed by the original tool. It was found that the Turkish version of the modified Seizure Self-Efficacy Scale for Children had excellent satisfactory psychometric aspects for a Turkish population. Conclusion: Health professionals can present a more effective drug process and nursing care by identifying and assessing seizure self-efficacy levels in children with epilepsy, and they can make a positive contribution to disease management and the way the child deals with the disease.

Boolean Factor Analysis by Attractor Neural Network

Czech Academy of Sciences Publication Activity Database

Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.

2007-01-01

Roč. 18, č. 3 (2007), s. 698-707 ISSN 1045-9227 R&D Projects: GA AV ČR 1ET100300419; GA ČR GA201/05/0079 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * dimensionality reduction * features clustering * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.769, year: 2007

Psychometric properties of the revised Malay version Medical Outcome Study Social Support Survey using confirmatory factor analysis among postpartum mothers.

Science.gov (United States)

Norhayati, Mohd Noor; Aniza, Abd Aziz; Nik Hazlina, Nik Hussain; Azman, Mohd Yacob

2015-12-01

Social support is an essential component for the physical and emotional well-being of postpartum mothers. The objective of this study is to determine the psychometric properties of the revised Malay version Medical Outcome Study (MOS) Social Support Survey using a confirmatory validity approach. A cross-sectional study was conducted involving 144 postpartum mothers attending Obstetric and Gynecology Clinic, Universiti Sains Malaysia Hospital. Construct validity and internal consistency assessment was performed after the translation, content validity and face validity process. The data were analyzed using SPSS 20.0 (SPSS Inc., Chicago, IL, USA) and AMOS 20.0 (SPSS Inc., Chicago, IL, USA). The original questionnaire consists of four domains (emotional/informational support, tangible support, affectionate support and positive social interaction) and 19 items. Affectionate support domain with three items only was treated as a separate construct and was not included in the factor analysis. The final confirmatory model with three constructs and 13 items demonstrated acceptable factor loadings, domain to domain correlation and best fit; (χ2[df]=1.665 [61]; P-value=0.001; Tucker-Lewis Index=0.944; comparative fit index=0.956; root mean square error of approximation=0.068). Composite reliability, average variance extracted and Cronbach's α of the domains ranged from 0.649 to 0.903; 0.390 to 0.699; 0.616 to 0.902, respectively. The study suggested that the four-factor model with 16 items (including one separate factor of affectionate) of the revised Malay version MOS Social Support Survey was acceptable to be used to measure social support after childbirth because it is valid, reliable and simple. © 2015 Wiley Publishing Asia Pty Ltd.

MOOC Success Factors: Proposal of an Analysis Framework

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Margarida M. Marques

2017-10-01

Full Text Available Aim/Purpose: From an idea of lifelong-learning-for-all to a phenomenon affecting higher education, Massive Open Online Courses (MOOCs can be the next step to a truly universal education. Indeed, MOOC enrolment rates can be astoundingly high; still, their completion rates are frequently disappointingly low. Nevertheless, as courses, the participants’ enrolment and learning within the MOOCs must be considered when assessing their success. In this paper, the authors’ aim is to reflect on what makes a MOOC successful to propose an analysis framework of MOOC success factors. Background: A literature review was conducted to identify reported MOOC success factors and to propose an analysis framework. Methodology: This literature-based framework was tested against data of a specific MOOC and refined, within a qualitative interpretivist methodology. The data were collected from the ‘As alterações climáticas nos média escolares - Clima@EduMedia’ course, which was developed by the project Clima@EduMedia and was submitted to content analysis. This MOOC aimed to support science and school media teachers in the use of media to teach climate change Contribution: By proposing a MOOC success factors framework the authors are attempting to contribute to fill in a literature gap regarding what concerns criteria to consider a specific MOOC successful. Findings: This work major finding is a literature-based and empirically-refined MOOC success factors analysis framework. Recommendations for Practitioners: The proposed framework is also a set of best practices relevant to MOOC developers, particularly when targeting teachers as potential participants. Recommendation for Researchers: This work’s relevance is also based on its contribution to increasing empirical research on MOOCs. Impact on Society: By providing a proposal of a framework on factors to make a MOOC successful, the authors hope to contribute to the quality of MOOCs. Future Research: Future

Study of the critical success factors of emblematic hotels through the analysis of content of online opinions: The case of the Spanish Tourist Paradors

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M. Lilibeth Fuentes-Medina

2018-03-01

Full Text Available Purpose - The purpose of this paper is to identify the critical success factors of emblematic hotels from the perspective of the guest, by analysing the direct activities that make up the value chain of these types of establishments. Design/methodology/approach - The authors use the case study methodology to derive conclusions that contribute to the development of a theory about the success factors of emblematic hotels. The case selected is the Spanish Tourist Parador chain. The authors carried out over a period of two years a data mining analysis of the online comments posted by its guests. Findings - The results indicate that the attributes of location and facilities are critical success factors expected a priori given the nature of the business of such establishments, based on the singular nature of the buildings. Another critical success factor is personnel, which seems to indicate that the Paradors support their business model by employing highly qualified staff, but give less attention to restaurant services or the room, according to guest perceptions. Originality/value - The paper provides required evidence on the critical success factors of emblematic hotels adapting Porter’s value chain, for the tourism accommodation sector, through the analysis of direct value chain activities. In addition, the existing literature is broadened by taking a perspective scarcely studied, the guest perception of hotel establishments, online content posted by the user on the establishment’s website, rather than simply considering the traditional views of the experts/managers, through structures questionnaires. Besides, the results provide practical and useful implications for the managements of the emblematic hotels under study.

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

Science.gov (United States)

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

2007-01-01

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

Exploratory Factor Analysis as a Construct Validation Tool: (Mis)applications in Applied Linguistics Research

Science.gov (United States)

Karami, Hossein

2015-01-01

Factor analysis has been frequently exploited in applied research to provide evidence about the underlying factors in various measurement instruments. A close inspection of a large number of studies published in leading applied linguistic journals shows that there is a misconception among applied linguists as to the relative merits of exploratory…

Periodontal disease as a risk factor for adverse pregnancy outcomes: a systematic review and meta-analysis of case-control studies.

Science.gov (United States)

Corbella, Stefano; Taschieri, Silvio; Francetti, Luca; De Siena, Francesca; Del Fabbro, Massimo

2012-07-01

Periodontal disease is a highly prevalent group of illnesses of microbial etiology, whose consequence is a severe breakdown of tooth-supporting structures. A link between periodontal infection and several systemic conditions, among which adverse pregnancy outcomes, has been suggested in the recent years. The aim of this review based on case-control studies was to evaluate if periodontal disease could be considered as a risk factor for preterm birth, low birth-weight and preterm low birth-weight. An electronic search (via Pubmed) was performed for case-control studies investigating the relationship between periodontal disease and adverse pregnancy outcomes. From the initially retrieved 417 articles, 17 case-control studies, accounting for a total of 10,148 patients, were included in the review and in the meta-analysis. The estimated odds ratio was 1.78 (CI 95%: 1.58, 2.01) for preterm birth, 1.82 (CI 95%: 1.51, 1.20) for low birth-weight and 3.00 (CI 95%: 1.93, 4.68) for preterm low birth-weight. Despite the results of the analysis of pooled data suggested a link between periodontal diseases and adverse pregnancy outcomes, the presence of important confounders, whose effect could not be addressed, prevents a validation of the meta-analysis outcomes. Further more accurate investigations based on individual data analysis could give a better insight into the topic of the present review.

Analysis of radiation and chemical factors which define the ecological situation of environment

International Nuclear Information System (INIS)

Trofimenko, A.P.

1996-01-01

A new method of large information set statistical analysis is proposed. It permits to define the main directions of work in a given field in the world or in a particular country, to find the most important investigated problems and to evaluate the role each of them quantitatively, as well as to study the dynamics of work development in time, the methods of research used, the centres in which this research is mostly developed, authors of publications etc. Statistical analysis may be supplemented with subject analysis of selected publications. Main factors which influence on different environment components and on public health are presented as an example of this method use, and the role of radiation and chemical factors is evaluated. 18 refs., 6 tab

Gene expression meta-analysis identifies metastatic pathways and transcription factors in breast cancer

International Nuclear Information System (INIS)

Thomassen, Mads; Tan, Qihua; Kruse, Torben A

2008-01-01

Metastasis is believed to progress in several steps including different pathways but the determination and understanding of these mechanisms is still fragmentary. Microarray analysis of gene expression patterns in breast tumors has been used to predict outcome in recent studies. Besides classification of outcome, these global expression patterns may reflect biological mechanisms involved in metastasis of breast cancer. Our purpose has been to investigate pathways and transcription factors involved in metastasis by use of gene expression data sets. We have analyzed 8 publicly available gene expression data sets. A global approach, 'gene set enrichment analysis' as well as an approach focusing on a subset of significantly differently regulated genes, GenMAPP, has been applied to rank pathway gene sets according to differential regulation in metastasizing tumors compared to non-metastasizing tumors. Meta-analysis has been used to determine overrepresentation of pathways and transcription factors targets, concordant deregulated in metastasizing breast tumors, in several data sets. The major findings are up-regulation of cell cycle pathways and a metabolic shift towards glucose metabolism reflected in several pathways in metastasizing tumors. Growth factor pathways seem to play dual roles; EGF and PDGF pathways are decreased, while VEGF and sex-hormone pathways are increased in tumors that metastasize. Furthermore, migration, proteasome, immune system, angiogenesis, DNA repair and several signal transduction pathways are associated to metastasis. Finally several transcription factors e.g. E2F, NFY, and YY1 are identified as being involved in metastasis. By pathway meta-analysis many biological mechanisms beyond major characteristics such as proliferation are identified. Transcription factor analysis identifies a number of key factors that support central pathways. Several previously proposed treatment targets are identified and several new pathways that may

A Retrospective Analysis of Factors Affecting Early Stoma Complications.

Science.gov (United States)

Koc, Umit; Karaman, Kerem; Gomceli, Ismail; Dalgic, Tahsin; Ozer, Ilter; Ulas, Murat; Ercan, Metin; Bostanci, Erdal; Akoglu, Musa

2017-01-01

Despite advances in surgical techniques and products for stoma care, stoma-related complications are still common. A retrospective analysis was performed of the medical records of 462 consecutive patients (295 [63.9%] female, 167 [36.1 %] male, mean age 55.5 ± 15.1 years, mean body mass index [BMI] 25.1 ± 5.2) who had undergone stoma creation at the Gastroenterological Surgery Clinic of Turkiye Yuksek İhtisas Teaching and Research Hospital between January 2008 and December 2012 to examine the incidence of early (ie, within 30 days after surgery) stoma complications and identify potential risk factors. Variables abstracted included gender, age, and BMI; existence of malignant disease; comorbidities (diabetes mellitus, hypertension, coronary artery disease, chronic respiratory disease); use of neoadjuvant chemoradiotherapy; permanent or temporary stoma; type of stoma (loop/end stoma); stoma localization; and the use of preoperative marking of the stoma site. Data were entered and analyzed using statistical software. Descriptive statistics, chi-squared, and Mann-Whitney U tests were used to describe and analyze all variables, and logistic regression analysis was used to determine independent risk factors for stoma complications. Ostomy-related complications developed in 131 patients (28.4%) Of these, superficial mucocutaneous separation was the most frequent complication (90 patients, 19.5%), followed by stoma retraction (15 patients, 3.2%). In univariate analysis, malignant disease (P = .025), creation of a colostomy (P = .002), and left lower quadrant stoma location (P toma complication. Only stoma location was an independent risk factor for the development of a stoma complication (P = .044). The rate of stoma complications was not significantly different between patients who underwent nonemergent surgery (30% in patients preoperatively sited versus 28.4% not sited) and patients who underwent emergency surgery (27.1%). Early stoma complication rates were higher

DISRUPTIVE EVENT BIOSPHERE DOSE CONVERSION FACTOR ANALYSIS

International Nuclear Information System (INIS)

M.A. Wasiolek

2005-01-01

This analysis report is one of the technical reports containing documentation of the Environmental Radiation Model for Yucca Mountain, Nevada (ERMYN), a biosphere model supporting the total system performance assessment (TSPA) for the license application (LA) for the Yucca Mountain repository. This analysis report describes the development of biosphere dose conversion factors (BDCFs) for the volcanic ash exposure scenario, and the development of dose factors for calculating inhalation dose during volcanic eruption. A graphical representation of the documentation hierarchy for the ERMYN is presented in Figure 1-1. This figure shows the interrelationships among the products (i.e., analysis and model reports) developed for biosphere modeling and provides an understanding of how this analysis report contributes to biosphere modeling. This report is one of two reports that develop biosphere BDCFs, which are input parameters for the TSPA model. The Biosphere Model Report (BSC 2004 [DIRS 169460]) describes in detail the ERMYN conceptual model and mathematical model. The input parameter reports, shown to the right of the Biosphere Model Report in Figure 1-1, contain detailed descriptions of the model input parameters, their development and the relationship between the parameters and specific features, events and processes (FEPs). This report describes biosphere model calculations and their output, the BDCFs, for the volcanic ash exposure scenario. This analysis receives direct input from the outputs of the ''Biosphere Model Report'' (BSC 2004 [DIRS 169460]) and from the five analyses that develop parameter values for the biosphere model (BSC 2005 [DIRS 172827]; BSC 2004 [DIRS 169672]; BSC 2004 [DIRS 169673]; BSC 2004 [DIRS 169458]; and BSC 2004 [DIRS 169459]). The results of this report are further analyzed in the ''Biosphere Dose Conversion Factor Importance and Sensitivity Analysis'' (Figure 1-1). The objective of this analysis was to develop the BDCFs for the volcanic

Environmental Risk Factors in Han and Uyghur Children with Dyslexia: A Comparative Study.

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Hua Zhao

Full Text Available Several studies have been conducted to explore risk factors for dyslexia. However, most studies examining dyslexia have been skewed toward Western countries, and few have considered two nationalities simultaneously. This study focused on differences in dyslexia prevalence and potential environmental risk factors between Han and Uyghur children.A cross-sectional study was conducted in Kashgar and Aksu, cities in Xinjiang province, China. A two-stage sampling strategy was used to recruit 2,854 students in grades 3-6 from 5 primary schools in 5 districts; 2,348 valid student questionnaires were included in the analysis. Dyslexia checklists for Chinese and Uyghur children and pupil rating scales were used to identify children with dyslexia. Questions related to the home literacy environment and reading ability were used to evaluate potential environmental risk factors. Single factor analysis and multivariate logistic regression were used to examine prevalence and risk factors for dyslexia.Dyslexia prevalence differed significantly between Han (3.9% and Uyghur (7.0% children (P < 0.05, and the boy-to-girl diagnosis ratio was almost 2:1. Multiple logistic regression analysis showed that ethnic differences in dyslexia prevalence between Han and Uyghur children could have occurred because of factors such as mother's occupation (P = 0.02, OR = 0.04, 95% CI = 0.01-0.68 and the frequency with which parents told stories (P = 0.00, OR = 4.50, 95% CI = 1.67-12.11.The prevalence of dyslexia was high in all children, particularly those in the Uyghur group. Environmental factors could have been responsible for some of the differences observed. The results contribute to the early identification and management of dyslexia in children from these two groups and research examining developmental dyslexia and differences in racial genetics.

Patient Safety Culture Survey in Pediatric Complex Care Settings: A Factor Analysis.

Science.gov (United States)

Hessels, Amanda J; Murray, Meghan; Cohen, Bevin; Larson, Elaine L

2017-04-19

Children with complex medical needs are increasing in number and demanding the services of pediatric long-term care facilities (pLTC), which require a focus on patient safety culture (PSC). However, no tool to measure PSC has been tested in this unique hybrid acute care-residential setting. The objective of this study was to evaluate the psychometric properties of the Nursing Home Survey on Patient Safety Culture tool slightly modified for use in the pLTC setting. Factor analyses were performed on data collected from 239 staff at 3 pLTC in 2012. Items were screened by principal axis factoring, and the original structure was tested using confirmatory factor analysis. Exploratory factor analysis was conducted to identify the best model fit for the pLTC data, and factor reliability was assessed by Cronbach alpha. The extracted, rotated factor solution suggested items in 4 (staffing, nonpunitive response to mistakes, communication openness, and organizational learning) of the original 12 dimensions may not be a good fit for this population. Nevertheless, in the pLTC setting, both the original and the modified factor solutions demonstrated similar reliabilities to the published consistencies of the survey when tested in adult nursing homes and the items factored nearly identically as theorized. This study demonstrates that the Nursing Home Survey on Patient Safety Culture with minimal modification may be an appropriate instrument to measure PSC in pLTC settings. Additional psychometric testing is recommended to further validate the use of this instrument in this setting, including examining the relationship to safety outcomes. Increased use will yield data for benchmarking purposes across these specialized settings to inform frontline workers and organizational leaders of areas of strength and opportunity for improvement.

Factors and competitiveness analysis in rare earth mining, new methodology: case study from Brazil.

Science.gov (United States)

Silva, Gustavo A; Petter, Carlos O; Albuquerque, Nelson R

2018-03-01

Rare earths are increasingly being applied in high-tech industries, such as green energy (e.g. wind power), hybrid cars, electric cars, permanent high-performance magnets, superconductors, luminophores and many other industrial sectors involved in modern technologies. Given that China dominates this market and imposes restrictions on production and exports whenever opportunities arise, it is becoming more and more challenging to develop business ventures in this sector. Several initiatives were taken to prospect new resources and develop the production chain, including the mining of these mineral assets around the world, but some factors of uncertainties, including current low prices, increased the challenge of transforming the current resources into deposits or productive mines. Thus, analyzing the competitiveness of advanced projects becomes indispensable. This work has the objective of introducing a new methodology of competitiveness analysis, where some variables are considered as main factors that can contribute strongly to make unfeasible a mining enterprise for the use of rare earth elements (REE) with this methodology, which is quite practical and reproducible, it was possible to verify some real facts, such as: the fact that the Lynas Mount Weld CLD (AUS) Project is resilient to the uncertainties of the RE sector, at the same time as the Molycorp Project is facing major financial difficulties (under judicial reorganization). It was also possible to verify that the Araxá Project of CBMM in Brazil is one of the most competitive in this country. Thus, we contribute to the existing literature, providing a new methodology for competitiveness analysis in rare earth mining.

Conversion from laparoscopic to open cholecystectomy: Multivariate analysis of preoperative risk factors

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Khan M

2005-01-01

Full Text Available BACKGROUND: Laparoscopic cholecystectomy has become the gold standard in the treatment of symptomatic cholelithiasis. Some patients require conversion to open surgery and several preoperative variables have been identified as risk factors that are helpful in predicting the probability of conversion. However, there is a need to devise a risk-scoring system based on the identified risk factors to (a predict the risk of conversion preoperatively for selected patients, (b prepare the patient psychologically, (c arrange operating schedules accordingly, and (d minimize the procedure-related cost and help overcome financial constraints, which is a significant problem in developing countries. AIM: This study was aimed to evaluate preoperative risk factors for conversion from laparoscopic to open cholecystectomy in our setting. SETTINGS AND DESIGNS: A case control study of patients who underwent laparoscopic surgery from January 1997 to December 2001 was conducted at the Aga Khan University Hospital, Karachi, Pakistan. MATERIALS AND METHODS: All those patients who were converted to open surgery (n = 73 were enrolled as cases. Two controls who had successful laparoscopic surgery (n = 146 were matched with each case for operating surgeon and closest date of surgery. STATISTICAL ANALYSIS USED: Descriptive statistics were computed and, univariate and multivariate analysis was done through multiple logistic regression. RESULTS: The final multivariate model identified two risk factors for conversion: ultrasonographic signs of inflammation (adjusted odds ratio [aOR] = 8.5; 95% confidence interval [CI]: 3.3, 21.9 and age > 60 years (aOR = 8.1; 95% CI: 2.9, 22.2 after adjusting for physical signs, alkaline phosphatase and BMI levels. CONCLUSION: Preoperative risk factors evaluated by the present study confirm the likelihood of conversion. Recognition of these factors is important for understanding the characteristics of patients at a higher risk of conversion.

A study to determine influential factors on data security

Directory of Open Access Journals (Sweden)

Naser Azad

2014-01-01

Full Text Available During the past few years, there has been increasing interest in making online transaction. As people become more interested in using internet for their daily business activities such as regular communications, financial transactions, etc., there will be more concerns on security of available data. In fact, data security is the primary concern in today’s online activities. This paper performs an empirical investigation to find important factors influencing data security in Municipality is city of Tehran, Iran. The survey uses factor analysis to find important factors using a questionnaire consist of 29 variables, which were reduced to 22 questions after considering skewness statistics. Cronbach alpha is calculated as 0.86, which validates the questionnaire. The survey detects six factors influencing feasibility study, organizational learning, management strategy, enterprise resource management, process approach and the acceptance.

Risk factors for breast cancer-related upper extremity lymphedema: a meta-analysis

International Nuclear Information System (INIS)

Xie Yuhuan; Guo Qi; Liu Fenghua; Zhu Yaqun; Tian Ye

2014-01-01

Objective: To systematically evaluate the risk factors for upper extremity lymphedema after breast cancer treatment and the strength of their associations. Methods: PubMed, Ovid, EMbase, and the Cochrane Library were searched to identify clinical trials published up to December 2012. The quality of included studies was assessed by the Newcastle-Ottawa Scale;data analysis was performed by Stata 10.0 and RevMan 5.2; the strength of associations between risk factors and breast cancer-related upper extremity lymphedema was described as odds ratio (OR) and 95% confidence intervals (CI). Results: Twenty-two studies involving 10106 patients were included in the meta-analysis. The risk factors for upper extremity lymphedema after breast cancer treatment mainly included axillary lymph node dissection (OR=2.72, 95% CI=1.06-6.99, P=0.038), hypertension (OR=1.84, 95% CI=1.38-2.44, P=0.000), body mass index (OR=1.68, 95% CI=1.22-2.32, P=0.001), and radiotherapy (OR=1.65, 95% CI=1.20-2.25, P=0.002), while no significant associations were found for such factors as chemotherapy, age, number of positive lymph nodes, and number of dissected lymph nodes. Conclusions: The incidence of upper extremity lymphedema is high among patients with breast cancer after treatment, and axillary lymph node dissection, hypertension,body mass index, and radiotherapy are the main risk factors for lymphedema after breast cancer treatment. (authors)

An analysis of the factors affecting the level of fertilizer use in crop production. A case study of Tokat - Turkey

International Nuclear Information System (INIS)

Karkacier, O.; Sayili, M.; Akca, H.; Gulse, H.S.

1999-01-01

In this study, socio-economic factors (size of land, number of irrigation, age of farmers, educational level of farmers, soil analysis, and extension services) to be effected to the level of fertilizer use have been investigated. It has been determined that socio-economic factors have an important effect on fertilizer use in tomatoes growing. However, their effects on fertilization in wheat and sugar beet growing is limited due to traditional and contract farming. And also, there is no effect of extension services in the region on the level of fertilizer use in all crops. The quantity of fertilizer used was 51.64 kg/da in sugar beet, 18.20 kg/da in wheat (dry), 19.03 kg/da in wheat (irrigated) and 73.77 kg/da in tomatoes growing. Refs. 5 (author)

Testing all six person-oriented principles in dynamic factor analysis.

Science.gov (United States)

Molenaar, Peter C M

2010-05-01

All six person-oriented principles identified by Sterba and Bauer's Keynote Article can be tested by means of dynamic factor analysis in its current form. In particular, it is shown how complex interactions and interindividual differences/intraindividual change can be tested in this way. In addition, the necessity to use single-subject methods in the analysis of developmental processes is emphasized, and attention is drawn to the possibility to optimally treat developmental psychopathology by means of new computational techniques that can be integrated with dynamic factor analysis.

Exploratory factor analysis and reliability analysis with missing data: A simple method for SPSS users

Directory of Open Access Journals (Sweden)

Bruce Weaver

2014-09-01

Full Text Available Missing data is a frequent problem for researchers conducting exploratory factor analysis (EFA or reliability analysis. The SPSS FACTOR procedure allows users to select listwise deletion, pairwise deletion or mean substitution as a method for dealing with missing data. The shortcomings of these methods are well-known. Graham (2009 argues that a much better way to deal with missing data in this context is to use a matrix of expectation maximization (EM covariances(or correlations as input for the analysis. SPSS users who have the Missing Values Analysis add-on module can obtain vectors ofEM means and standard deviations plus EM correlation and covariance matrices via the MVA procedure. But unfortunately, MVA has no /MATRIX subcommand, and therefore cannot write the EM correlations directly to a matrix dataset of the type needed as input to the FACTOR and RELIABILITY procedures. We describe two macros that (in conjunction with an intervening MVA command carry out the data management steps needed to create two matrix datasets, one containing EM correlations and the other EM covariances. Either of those matrix datasets can then be used asinput to the FACTOR procedure, and the EM correlations can also be used as input to RELIABILITY. We provide an example that illustrates the use of the two macros to generate the matrix datasets and how to use those datasets as input to the FACTOR and RELIABILITY procedures. We hope that this simple method for handling missing data will prove useful to both students andresearchers who are conducting EFA or reliability analysis.

Factor Analysis of Drawings: Application to college student models of the greenhouse effect

Science.gov (United States)

Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

2015-09-01

Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance, suggesting that 4 archetype models of the greenhouse effect dominate thinking within this population. Factor scores, indicating the extent to which each student's drawing aligned with representative models, were compared to performance on conceptual understanding and attitudes measures, demographics, and non-cognitive features of drawings. Student drawings were also compared to drawings made by scientists to ascertain the extent to which models reflect more sophisticated and accurate models. Results indicate that student and scientist drawings share some similarities, most notably the presence of some features of the most sophisticated non-scientific model held among the study population. Prior knowledge, prior attitudes, gender, and non-cognitive components are also predictive of an individual student's model. This work presents a new technique for analyzing drawings, with general implications for the use of drawings in investigating student conceptions.

Likelihood-based Dynamic Factor Analysis for Measurement and Forecasting

NARCIS (Netherlands)

Jungbacker, B.M.J.P.; Koopman, S.J.

2015-01-01

We present new results for the likelihood-based analysis of the dynamic factor model. The latent factors are modelled by linear dynamic stochastic processes. The idiosyncratic disturbance series are specified as autoregressive processes with mutually correlated innovations. The new results lead to

Risk Factors for Suicide Ideation Among Adolescents: Five-Year National Data Analysis.

Science.gov (United States)

Im, Yeojin; Oh, Won-Oak; Suk, Minhyun

2017-06-01

This study identified risk factors for suicide ideation among adolescents through a secondary analysis using data collected over five years from the 5th-9th Korea Youth Risk Behavior Survey. We analyzed 370,568 students' responses to questions about suicidality. The risk factors for suicide ideation included demographic characteristics, such as gender (girls), low grades, low economic status, and not living with one or both parents. Behavioral and mental health risk factors affecting suicide ideation were depression, low sleep satisfaction, high stress, alcohol consumption, smoking, and sexual activity. Health care providers should particularly target adolescents manifesting the above risk factors when developing suicide prevention programs for them. Copyright © 2017 Elsevier Inc. All rights reserved.

Confirmatory Factor Analysis of the Bases of Leader Power: First-Order Factor Model and Its Invariance Across Groups.

Science.gov (United States)

Rahim, M A; Magner, N R

1996-10-01

Confirmatory factor analyses of data (from five samples: N = 308 accountants and finance professionals, N = 578 management and non-management employees, and N = 588 employed management students in the U.S.; N = 728 management and non-management employees in S. Korea, N = 250 management and non-management bank employees in Bangladesh) on the 29 items of the Rahim Leader Power Inventory were performed with LISREL 7. The results provided support for the convergent and discriminant validities of the subscales measuring the five bases of leader power (coercive, reward, legitimate, expert, and referent), and the invariance of factor pattern and factor loadings across organizational levels and the three American samples. Additional analysis indicated that leader power profiles differed across the three national cultures represented in the study.

In-depth analysis of the causal factors of incidents reported in the Greek petrochemical industry

Energy Technology Data Exchange (ETDEWEB)

Konstandinidou, Myrto [Institute of Nuclear Technology-Radiation Protection, National Center for Scientific Research ' Demokritos' , Aghia Paraskevi 15310 (Greece); Nivolianitou, Zoe, E-mail: zoe@ipta.demokritos.gr [Institute of Nuclear Technology-Radiation Protection, National Center for Scientific Research ' Demokritos' , Aghia Paraskevi 15310 (Greece); Kefalogianni, Eirini; Caroni, Chrys [School of Applied Mathematical and Physical Sciences, National Technical University of Athens, 9 Iroon Polytexneiou Str., Zografou Campus, 157 80 Athens (Greece)

2011-11-15

This paper presents a statistical analysis of all reported incidents in the Greek petrochemical industry from 1997 to 2003. A comprehensive database has been developed to include industrial accidents (fires, explosions and substance releases), occupational accidents, incidents without significant consequences and near misses. The study concentrates on identifying and analyzing the causal factors related to different consequences of incidents, in particular, injury, absence from work and material damage. Methods of analysis include logistic regression with one of these consequences as dependent variable. The causal factors that are considered cover four major categories related to organizational issues, equipment malfunctions, human errors (of commission or omission) and external causes. Further analyses aim to confirm the value of recording near misses by comparing their causal factors with those of more serious incidents. The statistical analysis highlights the connection between the human factor and the underlying causes of accidents or incidents. - Highlights: > The research work is original, based on field data collected directly from the petrochemical industry. > It deals with the in-depth statistical analysis of accident data on human-organizational causes. > It researches underlying causes of accidents and the parameters affecting them. > The causal factors that are considered cover four big taxonomies. > Near misses are worth recording for comparing their causal factors with more serious incidents.

Factors influencing the satisfaction of rural physician assistants: a cross-sectional study.

Science.gov (United States)

Filipova, Anna A

2014-01-01

The purpose of the study was to determine factors that attract physician assistants (PAs) to rural settings, and what they found satisfying about their practice and community. A cross-sectional survey design was used. All PAs who were practicing in both nonmetropolitan counties and rural communities in metropolitan counties, in a single midwestern US state, served as the population for the study. A total of 414 usable questionnaires were returned of the 1,072 distributed, a 39% response rate. Factor analysis, descriptive statistics, Pearson's correlation analysis, and robust regression analyses were used. Statistical models were tested to identify antecedents of four job satisfaction factors (satisfaction with professional respect, satisfaction with supervising physician, satisfaction with authority/ autonomy, and satisfaction with workload/salary). The strongest predictor of all four job satisfaction factors was community satisfaction, followed by importance of job practice. Additionally, the four job satisfaction factors had some significant associations with importance of socialization, community importance, practice attributes (years of practice, years in current location, specialty, and facility type), job responsibilities (percentage of patient load not discussed with physician, weekly hours as PA, inpatient visits), and demographics (marital status, race, age, education).

Determining The Factors Affecting Fruit Hardness of Different Peach Types with Meta Analysis

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Hande Küçükönder

2014-09-01

Full Text Available The aim of this study is to determine the factor effective in determining the hardness of Caterina, Suidring, Royal Glory and Tirrenia peach types using meta analysis. In the study, the impact force (Fi and the contact time (tc were detected and the impulse values (I that are expressed as independent variable in the area under the curve were calculated in the measurements performed using the technique of a low-mass lateral impactor multiplicated with peach. Using the theory of elasticity, the independent variables were determined as Fmax (maximum impact force, contact time (tmax, Fmax/tmax, 1/tmax, 1/tmax2,5, Fmax/tmax 1.25 and Fmax2.5 parameters. The correlation coefficient values showing the relationship between these parameters and the dependent variable Magness-Taylor force (MT were calculated and were combined with meta-analysis by using the Hunter-Schmid and Fisher’s Z methods. The Cohen’s classification criterion was used in evaluating the resulting mean effect size (combined correlation value and in determining its direction. As a result of the meta-analysis, the mean effect size according to Hunter-Schmid method was found 0.436 (0.371-0.497 positively directed in 95% confidence interval, while it was found 0.468 (0.390-0.545 according to Fisher’s Z method. The effect sizes in both methods were determined “mid-level” according to the Cohen’s classification. When the significance level of the studies was analyzed with the Z test, all of the ones that taken into the meta analysis has been found statistically significant. As a result of the meta analysis in this study evaluating the relationship of peach types with the fruit hardness, the mean effect size has been found to reach “strong level”. Consequently, “maximum shock acceleration” was found to be a more effective factor comparing to the other factors in determining the the fruit hardness according to the results of meta analysis applied in both methods.

A Study of the Factors Associated with Risk for Development of Pressure Ulcers: A Longitudinal Analysis.

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Thomas, Elizebeth; Vinodkumar, Sudhaya; Mathew, Silvia; Setia, Maninder Singh

2015-01-01

Pressure ulcers (PUs) are prevalent in hospitalized patients; they may cause clinical, psychological, and economic problems in these patients. Previous studies are cross-sectional, have used pooled data, or cox-regression models to assess the risk for developing PU. However, PU risk scores change over time and models that account for time varying variables are useful for cohort analysis of data. The present longitudinal study was conducted to compare the risk of PU between surgical and nonsurgical patients, and to evaluate the factors associated with the development of these ulcers over a period of time. We evaluated 290 hospitalized patients over a 4 months period. The main outcomes for our analysis were: (1) Score on the pressure risk assessment scale; and (2) the proportion of individuals who were at severe risk for developing PUs. We used random effects models for longitudinal analysis of the data. The mean PU score was significantly higher in the nonsurgical patients compared with surgical patients at baseline (15.23 [3.86] vs. 9.33 [4.57]; P 20 at baseline and were considered as being at high-risk for PU; the proportion was significantly higher among the nonsurgical patients compared with the surgical patients (14% vs. 4%, P = 0.003). In the adjusted models, there was no difference for severe risk for PU between surgical and nonsurgical patients (odds ratios [ORs]: 0.37, 95% confidence interval [CI]: 0.01-12.80). An additional day in the ward was associated with a significantly higher likelihood of being at high-risk for PU (OR: 1.47, 95% CI: 1.16-1.86). There were no significant differences between patients who were admitted for surgery compared with those who were not. An additional day in the ward, however, is important for developing a high-risk score for PU on the monitoring scale, and these patients require active interventions.

Training department's role in human factor analysis during post-trip reviews

International Nuclear Information System (INIS)

Goodman, D.

1987-01-01

Provide training is a frequent corrective action specified in a post-trip review report. This corrective action is most often decided upon by technical and operational staff, not training staff, without a detailed analysis of whether training can resolve the immediate problem or enhance employees' future performance. A more specific human factor or performance problem analysis would often reveal that training cannot impact or resolve the concern to avoid future occurrences. This human factor analysis is similar to Thomas Gilbert's Behavior Engineering Model (Human Competence, McGraw-Hill, 1978) or Robert Mager's/Peter Pipe's Performance Analysis (Analyzing Performance Problems, Pitman Learning, 1984). At Palo Verde Nuclear Generating Station, training analysts participate in post-trip reviews in order to conduct or provide input to this type of human factor and performance problem analysis. Their goal is to keep provide training out of corrective action statements unless training can in fact impact or resolve the problem. The analysts follow a plant specific logic diagram to identify human factors and to identify whether changes to the environment or to the person would best resolve the concern

Exploring leadership styles for innovation: an exploratory factor analysis

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Wipulanusat Warit

2017-03-01

Full Text Available Leadership plays a vital role in building the process, structures, and climate for an organisation to become innovative and to motivate team expectations toward innovations. This study explores the leadership styles that engineers regard as significant for innovation in the public sector. Exploratory factor analysis (EFA was conducted to identify the principal leadership styles influencing innovation in the Australian Public Service (APS, using survey data extracted from the 2014 APS employee census comprising 3 125 engineering professionals in Commonwealth of Australia departments. EFA returned a two-factor structure explaining 77.6% of the variance of the leadership for innovation construct. In this study, the results from the EFA provided a clear estimation of the factor structure of the measures for leadership for innovation. From the results, the two factors extracted were transformational leadership and consideration leadership. In transformational leadership, a leader values organisational objectives, inspires subordinates to perform, and motivates followers beyond expected levels of work standards. Consideration leadership refers to the degree to which a leader shows concern and expressions of support for subordinates, takes care of their welfare, treats members as equals, and displays warmth and approachability. These findings highlight the role of leadership as the most critical predictor when considering the degree to which subordinates strive for creativity and innovation. Both transformational and consideration leadership styles are recommended to be incorporated into management training and development programs. This study also recommends that Commonwealth departments recruit supervisors who have both of these leadership styles before implementing innovative projects.

Internal Structure of Mini-CEX Scores for Internal Medicine Residents: Factor Analysis and Generalizability

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Cook, David A.; Beckman, Thomas J.; Mandrekar, Jayawant N.; Pankratz, V. Shane

2010-01-01

The mini-CEX is widely used to rate directly observed resident-patient encounters. Although several studies have explored the reliability of mini-CEX scores, the dimensionality of mini-CEX scores is incompletely understood. Objective: Explore the dimensionality of mini-CEX scores through factor analysis and generalizability analysis. Design:…

Profile and Risk Factor Analysis of Unintentional Injuries in Children.

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Bhamkar, Rahul; Seth, Bageshree; Setia, Maninder Singh

2016-10-01

To study the profile and various risk factors associated with unintentional injuries in children. The study is a cross sectional analysis of data collected from 351 children presenting with unintentional injury to a tertiary care hospital in Navi Mumbai, India. Data were collected about variables based on Haddon Phase Factor Matrix - host, environment and agent factors. Proportions for categorical variables across various groups were compared using Chi square test or Fisher's exact test. Logistic regression model was used to evaluate the factors. Falls (36 %) were the most common injuries followed by bites (23 %). Majority of children were school going children (38 %) followed by preschool children (29 %). Forty-seven percent were from lower socioeconomic class. Commonest place of injury was home (48 %) and the commonest time was evening (49 %). Though there was male predominance in injuries, the difference across gender did not vary significantly (p = 0.15). Poisonings were significantly more common in infants and toddlers and in rural population (p risk of bites compared to urban (p Profile of injuries varies widely as per the variations in agent, host and environmental factors. Socio-environmental, economic conditions and infancy-toddler age groups are predisposing risk factors for bites and poisoning. Although rural areas and lower socioeconomic class population are more vulnerable to serious types of injuries, they still lack essential basic medical care.

Factor Analysis of Drawings: Application to College Student Models of the Greenhouse Effect

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Libarkin, Julie C.; Thomas, Stephen R.; Ording, Gabriel

2015-01-01

Exploratory factor analysis was used to identify models underlying drawings of the greenhouse effect made by over 200 entering university freshmen. Initial content analysis allowed deconstruction of drawings into salient features, with grouping of these features via factor analysis. A resulting 4-factor solution explains 62% of the data variance,…

Research and development studies on human factors: new trends

International Nuclear Information System (INIS)

Llory, M.; Larchier-Boulanger, J.

1988-01-01

This paper is aimed at describing where the research work on human factors undertaken at EDF stands in relation to this European trend and to define the problematics of cognitive phenomena in relation to all (non cognitive) human phenomena, on the one hand, and to individual aspects as compared to collective and organizational aspects, on the other. Some important trends in the research and development studies will thus be examined one lay one: - analysis of operators' activity; - analysis of the activity cognitive aspects; - problem of the impact of non-cognitive aspects

Risk factors for new onset diabetes mellitus after liver transplantation: A meta-analysis.

Science.gov (United States)

Li, Da-Wei; Lu, Tian-Fei; Hua, Xiang-Wei; Dai, Hui-Juan; Cui, Xiao-Lan; Zhang, Jian-Jian; Xia, Qiang

2015-05-28

To determine the risk factors for new-onset diabetes mellitus (NODM) after liver transplantation by conducting a systematic review and meta-analysis. We electronically searched the databases of MEDLINE, EMBASE and the Cochrane Library from January 1980 to December 2013 to identify relevant studies reporting risk factors for NODM after liver transplantation. Two authors independently assessed the trials for inclusion and extracted the data. Discrepancies were resolved in consultation with a third reviewer. All statistical analyses were performed with the RevMan5.0 software (The Cochrane Collaboration, Oxford, United Kingdom). Pooled odds ratios (OR) or weighted mean differences (WMD) with 95% confidence intervals (CIs) were calculated using either a fixed effects or a random effects model, based on the presence (I (2) 50%) of significant heterogeneity. Twenty studies with 4580 patients were included in the meta-analysis, all of which were retrospective. The meta-analysis identified the following significant risk factors: hepatitis C virus (HCV) infection (OR = 2.68; 95%CI: 1.92-3.72); a family history of diabetes (OR = 1.69, 95%CI: 1.09-2.63, P diabetes (OR = 1.69; 95%CI: 1.09-2.63; P = 0.02); use of tacrolimus (OR = 1.34; 95%CI: 1.03-1.76; P = 0.03) and body mass index (BMI)(WMD = 1.19, 95%CI: 0.69-1.68, P diabetes, male gender, tacrolimus and BMI are risk factors for NODM after liver transplantation.

Analyzing Mathematics Beliefs of Pre-Service Teachers Using Confirmatory Factor Analysis

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Mazlini Adnan

2011-12-01

Full Text Available Mathematics beliefs play an important role in enhancing the quality and the effectiveness of teaching and learning. This study analyzes the mathematics beliefs of 317 pre-service teachers from six Higher Education Institutions (HEIs (Government Public Universities who were randomly selected to participate in this study. Questionnaires consisting of twenty three items were given to the respondents during the data collection process. The validation of the items was done by using confirmatory factor analysis (CFA. In order to obtain a model fit for the measurement model of mathematics beliefs, several fit index tests such as CMINDF, GFI, AGFI, IFI, NFI, CFI, TLI and RMSEA were used. Constructivist beliefs and traditional beliefs were identified as the contributing factors in the model. The analysis also revealed that mathematics beliefs consist of structures of two hidden variables. The correlation between the two variables (constructivist beliefs and traditional beliefs is at a moderate level. Hence, pre-service teachers should be able to recognize their type of mathematics beliefs in order to become effective mathematics teachers.

Prognostic Factors of Uterine Serous Carcinoma-A Multicenter Study.

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Zhong, Xiaozhu; Wang, Jianliu; Kaku, Tengen; Wang, Zhiqi; Li, Xiaoping; Wei, Lihui

2018-04-04

The prognostic factors of uterine serous carcinoma (USC) vary among studies, and there is no report of Chinese USC patients. The aim of this study was to investigate the clinicopathological characteristics and prognostic factors in Chinese patients with USC. Patients with USC from 13 authoritative university hospitals in China and treated between 2004 and 2014 were retrospectively reviewed. Three-year disease-free survival rate (DFSR), cumulative recurrence, and cumulative mortality were estimated by Kaplan-Meier analyses and log-rank tests. Multivariate Cox regression analysis was used to model the association of potential prognostic factors with clinical outcomes. Data of a total of 241 patients were reviewed. The median follow-up was 26 months (range, 1-128 months). Median age was 60 years (range, 39-84 years), and 58.0% had stages I-II disease. The 3-year DFSR and cumulative recurrence were 46.8% and 27.7%. Advanced stage (III and IV) (P = 0.004), myometrial invasion (P = 0.001), adnexal involvement (P USC. Prospective studies are needed to confirm these results.

Introductory analysis of sustainable consumption and production : Factors of corporate social responsibility management in Japan

OpenAIRE

八木, 迪幸; 國部, 克彦

2017-01-01

As an introductory analysis of sustainable consumption and production, this paper examines what factors influence corporate social responsibility management in Japan. Following some underlying theories (management control system; the neo-institutional theory; performance measurement systems; the stakeholder theory; the resource dependence theory), this paper conducts empirical studies using firm-level data. The first three studies examine what factors encourage corporate social responsibility...

Meta-analysis of the predictive factors of postpartum fatigue.

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Badr, Hanan A; Zauszniewski, Jaclene A

2017-08-01

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

Statictical Analysis Of The Conditioning Factors Of Urban Electric Consumption

International Nuclear Information System (INIS)

Segura D'Rouville, Juan Joel; Suárez Carreño, Franyelit María

2017-01-01

This research work presents the analysis of the most important factors that condition the urban residential electricity consumption. This study shows the quantitative parameters conditioning the electricity consumption. This sector of analysis has been chosen because there is disaggregated information of which are the main social and technological factors that determine its behavior, growth, with the objective of elaborating policies in the management of the electric consumption. The electrical demand considered as the sum of the powers of all the equipment that are used in each of the instants of a full day, is related to the electrical consumption, which is not but the value of the power demanded by a determined consumer Multiplied by the time in which said demand is maintained. In this report we propose the design of a probabilistic model of prediction of electricity consumption, taking into account mainly influential social and technological factors. The statistical process of this database is done through the Stat Graphics software version 4.1, for its extensive didactic in the accomplishment of calculations and associated methods. Finally, the correlation of the variables was performed to classify the determinants in a specific way and thus to determine the consumption of the dwellings. (author)

Critical Factors Analysis for Offshore Software Development Success by Structural Equation Modeling

Science.gov (United States)

Wada, Yoshihisa; Tsuji, Hiroshi

In order to analyze the success/failure factors in offshore software development service by the structural equation modeling, this paper proposes to follow two approaches together; domain knowledge based heuristic analysis and factor analysis based rational analysis. The former works for generating and verifying of hypothesis to find factors and causalities. The latter works for verifying factors introduced by theory to build the model without heuristics. Following the proposed combined approaches for the responses from skilled project managers of the questionnaire, this paper found that the vendor property has high causality for the success compared to software property and project property.

Confirmatory Factor Analysis of the Structure of Statistics Anxiety Measure: An Examination of Four Alternative Models

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Hossein Bevrani, PhD

2011-09-01

Full Text Available 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.

Design and analysis of biomedical studies

DEFF Research Database (Denmark)

Hansen, Merete Kjær

been allocated this field. It is utterly important to utilize these ressources responsibly and efficiently by constantly striving to ensure high-quality biomedical studies. This involves the use of a sound statistical methodology regarding both the design and analysis of biomedical studies. The focus...... have conducted a literature study strongly indicating that this structure commonly is neglected in the statistical analysis. Based on this closed-form expressions for the approximate type I error rate are formulated. The type I error rates are assessed for a number of factor combinations as they appear...... in practice and in all cases the type I error rates are demonstrated to be severely inflated. Prior to conducting a study it is important to perform power and sample size determinations to ensure that reliable conclusions can be drawn from the statistical analysis. We have formulated closed-form expressions...

An empirical study on identifying critical success factors on chaos management

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Naser Azad

2012-08-01

Full Text Available Chaos management is one of the most necessary efforts on managing business units. Many organizations fail to cope with undesirable circumstances, which may happen without any prior notice and as a result, they may face with significant financial losses. In this paper, we present an empirical study to determine critical success factors, which could help handle any possible chaos in organizations. The proposed study of this paper is implemented for a set of travel agencies located in Tehran, Iran. Chronbach alpha is calculated as 0.821, which is well above the minimum desirable level. In addition, we have also performed factor analysis, which yields a KMO value of 0.576 with the level of significance of 0.000. The results indicate that there are six important factors including effective management strategy, internal environmental factors, creative and innovative attitudes, external environmental factors and top level management thoughts.

Using exploratory factor analysis of FFQ data to identify dietary patterns among Yup'ik people.

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Ryman, Tove K; Austin, Melissa A; Hopkins, Scarlett; Philip, Jacques; O'Brien, Diane; Thummel, Kenneth; Boyer, Bert B

2014-03-01

An FFQ developed by the Center for Alaska Native Health Research for studies in Yup'ik people includes market foods and subsistence foods such as moose, seal, waterfowl and salmon that may be related to disease risk. Because the FFQ contains >100 food items, we sought to characterize dietary patterns more simply for use in ongoing pharmacogenomics studies. Exploratory factor analysis was used to derive a small number of 'factors' that explain a substantial amount of the variation in the Yup'ik diet. We estimated factor scores and measured associations with demographic characteristics and biomarkers. South-west Alaska, USA. Yup'ik people (n 358) aged ≥18 years. We identified three factors that each accounted for ≥10 % of the common variance: the first characterized by 'processed foods' (e.g. salty snacks, sweetened cereals); the second by 'fruits and vegetables' (e.g. fresh citrus, potato salad); and the third by 'subsistence foods' (seal or walrus soup, non-oily fish). Participants from coastal communities had higher values for the 'subsistence' factor, whereas participants from inland communities had higher values for the 'fruits and vegetables' factor. A biomarker of marine intake, δ 15N, was correlated with the 'subsistence' factor, whereas a biomarker of corn- and sugarcane-based market food intake, δ 13C, was correlated with 'processed foods'. The exploratory factor analysis identified three factors that appeared to reflect dietary patterns among Yup'ik based on associations with participant characteristics and biomarkers. These factors will be useful for chronic disease studies in this population.

Cement Leakage in Percutaneous Vertebral Augmentation for Osteoporotic Vertebral Compression Fractures: Analysis of Risk Factors.

Science.gov (United States)

Xie, Weixing; Jin, Daxiang; Ma, Hui; Ding, Jinyong; Xu, Jixi; Zhang, Shuncong; Liang, De

2016-05-01

The risk factors for cement leakage were retrospectively reviewed in 192 patients who underwent percutaneous vertebral augmentation (PVA). To discuss the factors related to the cement leakage in PVA procedure for the treatment of osteoporotic vertebral compression fractures. PVA is widely applied for the treatment of osteoporotic vertebral fractures. Cement leakage is a major complication of this procedure. The risk factors for cement leakage were controversial. A retrospective review of 192 patients who underwent PVA was conducted. The following data were recorded: age, sex, bone density, number of fractured vertebrae before surgery, number of treated vertebrae, severity of the treated vertebrae, operative approach, volume of injected bone cement, preoperative vertebral compression ratio, preoperative local kyphosis angle, intraosseous clefts, preoperative vertebral cortical bone defect, and ratio and type of cement leakage. To study the correlation between each factor and cement leakage ratio, bivariate regression analysis was employed to perform univariate analysis, whereas multivariate linear regression analysis was employed to perform multivariate analysis. The study included 192 patients (282 treated vertebrae), and cement leakage occurred in 100 vertebrae (35.46%). The vertebrae with preoperative cortical bone defects generally exhibited higher cement leakage ratio, and the leakage is typically type C. Vertebrae with intact cortical bones before the procedure tend to experience type S leakage. Univariate analysis showed that patient age, bone density, number of fractured vertebrae before surgery, and vertebral cortical bone were associated with cement leakage ratio (Pcement leakage are bone density and vertebral cortical bone defect, with standardized partial regression coefficients of -0.085 and 0.144, respectively. High bone density and vertebral cortical bone defect are independent risk factors associated with bone cement leakage.

Double Shell Tank (DST) Human Factors Study

International Nuclear Information System (INIS)

CHAFFEE, G.A.

1994-01-01

This report documents the data collection and analyses that were performed in development of material to be used in the Human Factors chapter for the upgrade to the Safety Analysis Report (SAR) for the Double-Shell Tank Farms (DSTF). This study was conducted to collect the data that is necessary to prepare the Human Factors chapter for the upgrade of the SAR for the DSTF. Requirements for the HF chapter of the SAR generally dictate that the facility management describe how the consideration of operator capabilities and limitations and operating experience are used in ensuring the safe and effective operation of the facility. Additionally, analysis to indicate the contribution of human error to the safety basis accidents or events must be reported. Since the DSTF is a mature operating facility and the requirement to prepare a HF chapter is new, it was not expected that the consideration of HF principles would be an explicit part of DSTF operations. It can be expected, however, that the programs that guide the daily operations at the DSTF contain provisions for the consideration of the needs of their operating personnel and lessons learned from prior experience. Consideration of both the SAR requirements and the nature of the DSTF operations led to the following objectives being defined for the study: (1) to identify the programs at the OSTF where human performance may be considered; (2) to describe how HF principles and operating experience are used to ensure safe and reliable human performance at the DSTF; (3) to describe how HF principles and operating experience are considered as modifications or improvements are made at the DSTF; and (4) to perform task analysis sufficient to understand the potential for human error in OSTF operations

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

Science.gov (United States)

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

2011-08-15

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

A Second-Order Confirmatory Factor Analysis of the Moral Distress Scale-Revised for Nurses.

Science.gov (United States)

Sharif Nia, Hamid; Shafipour, Vida; Allen, Kelly-Ann; Heidari, Mohammad Reza; Yazdani-Charati, Jamshid; Zareiyan, Armin

2017-01-01

Moral distress is a growing problem for healthcare professionals that may lead to dissatisfaction, resignation, or occupational burnout if left unattended, and nurses experience different levels of this phenomenon. This study aims to investigate the factor structure of the Persian version of the Moral Distress Scale-Revised in intensive care and general nurses. This methodological research was conducted with 771 nurses from eight hospitals in the Mazandaran Province of Iran in 2017. Participants completed the Moral Distress Scale-Revised, data collected, and factor structure assessed using the construct, convergent, and divergent validity methods. The reliability of the scale was assessed using internal consistency (Cronbach's alpha, Theta, and McDonald's omega coefficients) and construct reliability. Ethical considerations: This study was approved by the Ethics Committee of Mazandaran University of Medical Sciences. The exploratory factor analysis ( N = 380) showed that the Moral Distress Scale-Revised has five factors: lack of professional competence at work, ignoring ethical issues and patient conditions, futile care, carrying out the physician's orders without question and unsafe care, and providing care under personal and organizational pressures, which explained 56.62% of the overall variance. The confirmatory factor analysis ( N = 391) supported the five-factor solution and the second-order latent factor model. The first-order model did not show a favorable convergent and divergent validity. Ultimately, the Moral Distress Scale-Revised was found to have a favorable internal consistency and construct reliability. The Moral Distress Scale-Revised was found to be a multidimensional construct. The data obtained confirmed the hypothesis of the factor structure model with a latent second-order variable. Since the convergent and divergent validity of the scale were not confirmed in this study, further assessment is necessary in future studies.

Analysis of IFR driver fuel hot channel factors

International Nuclear Information System (INIS)

Ku, J.Y.; Chang, L.K.; Mohr, D.

1994-01-01

Thermal-hydraulic uncertainty factors for Integral Fast Reactor (IFR) driver fuels have been determined based primarily on the database obtained from the predecessor fuels used in the IFR prototype, Experimental Breeder Reactor II. The uncertainty factors were applied to the channel factors (HCFs) analyses to obtain separate overall HCFs for fuel and cladding for steady-state analyses. A ''semistatistical horizontal method'' was used in the HCFs analyses. The uncertainty factor of the fuel thermal conductivity dominates the effects considered in the HCFs analysis; the uncertainty in fuel thermal conductivity will be reduced as more data are obtained to expand the currently limited database for the IFR ternary metal fuel (U-20Pu-10Zr). A set of uncertainty factors to be used for transient analyses has also been derived

Analysis of IFR driver fuel hot channel factors

International Nuclear Information System (INIS)

Ku, J.Y.; Chang, L.K.; Mohr, D.

2004-01-01

Thermal-hydraulic uncertainty factors for Integral Fast Reactor (IFR) driver fuels have been determined based primarily on the database obtained from the predecessor fuels used in the IFR prototype. Experimental Breeder Reactor II. The uncertainty factors were applied to the hot channel factors (HCFs) analyses to obtain separate overall HCFs for fuel and cladding for steady-state analyses. A 'semistatistical horizontal method' was used in the HCFs analyses. The uncertainty factor of the fuel thermal conductivity dominates the effects considered in the HCFs analysis; the uncertainty in fuel thermal conductivity will be reduced as more data are obtained to expand the currently limited database for the IFR ternary metal fuel (U-20Pu-10Zr). A set of uncertainty factors to be used for transient analyses has also been derived. (author)

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