Decision Tree Analysis of Traditional Risk Factors of Carotid Atherosclerosis and a Cutpoint-Based Prevention Strategy

PubMed Central

Lv, Lihong; Xiao, Yufei; Tu, Jiangfeng; Tao, Lisha; Wu, Jiaqi; Tang, Xiaoxiao; Pan, Wensheng

2014-01-01

Background Reducing the exposure to risk factors for the prevention of cardio-cerebral vascular disease is a crucial issue. Few reports have described practical interventions for preventing cardiovascular disease in different genders and age groups, particularly detailed and specific cutpoint-based prevention strategies. Methods We collected the health examination data of 5822 subjects between 20 and 80 years of age. The administration of medical questionnaires and physical examinations and the measurement of blood pressure, fasting plasma glucose (FPG) and blood lipids [total cholesterol (TC), triglycerides (TG), high density lipoprotein–cholesterol (HDL-C), and low density lipoprotein-cholesterol (LDL-C)] were performed by physicians. Carotid ultrasound was performed to examine the carotid intima-media thickness (CIMT), which was defined as carotid atherosclerosis when CIMT ≥0.9 mm. Decision tree analysis was used to screen for the most important risk factors for carotid atherosclerosis and to identify the relevant cutpoints. Results In the study population, the incidence of carotid atherosclerosis was 12.20% (men: 14.10%, women: 9.20%). The statistical analysis showed significant differences in carotid atherosclerosis incidence between different genders (P<0.0001) and age groups (P<0.001). The decision tree analysis showed that in men, the most important traditional risk factors for carotid atherosclerosis were TC (cutpoint [CP]: 6.31 mmol/L) between the ages of 20–40 and FPG (CP: 5.79 mmol/L) between the ages of 41–59. By comparison, LDL-C (CP: 4.27 mmol/L) became the major risk factor when FPG ≤5.79 mmol/L. FPG (CP: 5.52 mmol/L) and TG (CP: 1.51 mmol/L) were the most important traditional risk factors for women between 20–40 and 41–59 years of age, respectively. Conclusion Traditional risk factors and relevant cutpoints were not identical in different genders and age groups. A specific gender and age group-based cutpoint strategy might contribute

Inheritance of dermatoglyphic asymmetry and diversity traits in twins based on factor: variance decomposition analysis.

PubMed

Karmakar, Bibha; Malkin, Ida; Kobyliansky, Eugene

2013-06-01

Dermatoglyphic asymmetry and diversity traits from a large number of twins (MZ and DZ) were analyzed based on principal factors to evaluate genetic effects and common familial environmental influences on twin data by the use of maximum likelihood-based Variance decomposition analysis. Sample consists of monozygotic (MZ) twins of two sexes (102 male pairs and 138 female pairs) and 120 pairs of dizygotic (DZ) female twins. All asymmetry (DA and FA) and diversity of dermatoglyphic traits were clearly separated into factors. These are perfectly corroborated with the earlier studies in different ethnic populations, which indicate a common biological validity perhaps exists of the underlying component structures of dermatoglyphic characters. Our heritability result in twins clearly showed that DA_F2 is inherited mostly in dominant type (28.0%) and FA_F1 is additive (60.7%), but no significant difference in sexes was observed for these factors. Inheritance is also very prominent in diversity Factor 1, which is exactly corroborated with our previous findings. The present results are similar with the earlier results of finger ridge count diversity in twin data, which suggested that finger ridge count diversity is under genetic control.

Factor Analysis and Counseling Research

ERIC Educational Resources Information Center

Weiss, David J.

1970-01-01

Topics discussed include factor analysis versus cluster analysis, analysis of Q correlation matrices, ipsativity and factor analysis, and tests for the significance of a correlation matrix prior to application of factor analytic techniques. Techniques for factor extraction discussed include principal components, canonical factor analysis, alpha…

A Comparison of Rule-based Analysis with Regression Methods in Understanding the Risk Factors for Study Withdrawal in a Pediatric Study.

PubMed

Haghighi, Mona; Johnson, Suzanne Bennett; Qian, Xiaoning; Lynch, Kristian F; Vehik, Kendra; Huang, Shuai

2016-08-26

Regression models are extensively used in many epidemiological studies to understand the linkage between specific outcomes of interest and their risk factors. However, regression models in general examine the average effects of the risk factors and ignore subgroups with different risk profiles. As a result, interventions are often geared towards the average member of the population, without consideration of the special health needs of different subgroups within the population. This paper demonstrates the value of using rule-based analysis methods that can identify subgroups with heterogeneous risk profiles in a population without imposing assumptions on the subgroups or method. The rules define the risk pattern of subsets of individuals by not only considering the interactions between the risk factors but also their ranges. We compared the rule-based analysis results with the results from a logistic regression model in The Environmental Determinants of Diabetes in the Young (TEDDY) study. Both methods detected a similar suite of risk factors, but the rule-based analysis was superior at detecting multiple interactions between the risk factors that characterize the subgroups. A further investigation of the particular characteristics of each subgroup may detect the special health needs of the subgroup and lead to tailored interventions.

Factor Analysis for Clustered Observations.

ERIC Educational Resources Information Center

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)

Phylogenetic Factor Analysis.

PubMed

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

2018-05-01

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

Bootstrap Confidence Intervals for Ordinary Least Squares Factor Loadings and Correlations in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Preacher, Kristopher J.; Luo, Shanhong

2010-01-01

This article is concerned with using the bootstrap to assign confidence intervals for rotated factor loadings and factor correlations in ordinary least squares exploratory factor analysis. Coverage performances of "SE"-based intervals, percentile intervals, bias-corrected percentile intervals, bias-corrected accelerated percentile…

The joint return period analysis of natural disasters based on monitoring and statistical modeling of multidimensional hazard factors.

PubMed

Liu, Xueqin; Li, Ning; Yuan, Shuai; Xu, Ning; Shi, Wenqin; Chen, Weibin

2015-12-15

As a random event, a natural disaster has the complex occurrence mechanism. The comprehensive analysis of multiple hazard factors is important in disaster risk assessment. In order to improve the accuracy of risk analysis and forecasting, the formation mechanism of a disaster should be considered in the analysis and calculation of multi-factors. Based on the consideration of the importance and deficiencies of multivariate analysis of dust storm disasters, 91 severe dust storm disasters in Inner Mongolia from 1990 to 2013 were selected as study cases in the paper. Main hazard factors from 500-hPa atmospheric circulation system, near-surface meteorological system, and underlying surface conditions were selected to simulate and calculate the multidimensional joint return periods. After comparing the simulation results with actual dust storm events in 54years, we found that the two-dimensional Frank Copula function showed the better fitting results at the lower tail of hazard factors and that three-dimensional Frank Copula function displayed the better fitting results at the middle and upper tails of hazard factors. However, for dust storm disasters with the short return period, three-dimensional joint return period simulation shows no obvious advantage. If the return period is longer than 10years, it shows significant advantages in extreme value fitting. Therefore, we suggest the multivariate analysis method may be adopted in forecasting and risk analysis of serious disasters with the longer return period, such as earthquake and tsunami. Furthermore, the exploration of this method laid the foundation for the prediction and warning of other nature disasters. Copyright © 2015 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

Analysis of Factors Influencing Hydration Site Prediction Based on Molecular Dynamics Simulations

PubMed Central

2015-01-01

Water contributes significantly to the binding of small molecules to proteins in biochemical systems. Molecular dynamics (MD) simulation based programs such as WaterMap and WATsite have been used to probe the locations and thermodynamic properties of hydration sites at the surface or in the binding site of proteins generating important information for structure-based drug design. However, questions associated with the influence of the simulation protocol on hydration site analysis remain. In this study, we use WATsite to investigate the influence of factors such as simulation length and variations in initial protein conformations on hydration site prediction. We find that 4 ns MD simulation is appropriate to obtain a reliable prediction of the locations and thermodynamic properties of hydration sites. In addition, hydration site prediction can be largely affected by the initial protein conformations used for MD simulations. Here, we provide a first quantification of this effect and further indicate that similar conformations of binding site residues (RMSD < 0.5 Å) are required to obtain consistent hydration site predictions. PMID:25252619

Analysis of factors influencing hydration site prediction based on molecular dynamics simulations.

PubMed

Yang, Ying; Hu, Bingjie; Lill, Markus A

2014-10-27

Water contributes significantly to the binding of small molecules to proteins in biochemical systems. Molecular dynamics (MD) simulation based programs such as WaterMap and WATsite have been used to probe the locations and thermodynamic properties of hydration sites at the surface or in the binding site of proteins generating important information for structure-based drug design. However, questions associated with the influence of the simulation protocol on hydration site analysis remain. In this study, we use WATsite to investigate the influence of factors such as simulation length and variations in initial protein conformations on hydration site prediction. We find that 4 ns MD simulation is appropriate to obtain a reliable prediction of the locations and thermodynamic properties of hydration sites. In addition, hydration site prediction can be largely affected by the initial protein conformations used for MD simulations. Here, we provide a first quantification of this effect and further indicate that similar conformations of binding site residues (RMSD < 0.5 Å) are required to obtain consistent hydration site predictions.

Classification and identification of molecules through factor analysis method based on terahertz spectroscopy

NASA Astrophysics Data System (ADS)

Huang, Jianglou; Liu, Jinsong; Wang, Kejia; Yang, Zhengang; Liu, Xiaming

2018-06-01

By means of factor analysis approach, a method of molecule classification is built based on the measured terahertz absorption spectra of the molecules. A data matrix can be obtained by sampling the absorption spectra at different frequency points. The data matrix is then decomposed into the product of two matrices: a weight matrix and a characteristic matrix. By using the K-means clustering to deal with the weight matrix, these molecules can be classified. A group of samples (spirobenzopyran, indole, styrene derivatives and inorganic salts) has been prepared, and measured via a terahertz time-domain spectrometer. These samples are classified with 75% accuracy compared to that directly classified via their molecular formulas.

Determining the Number of Factors in P-Technique Factor Analysis

ERIC Educational Resources Information Center

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

2017-01-01

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

Analysis of factors that inhibiting implementation of Information Security Management System (ISMS) based on ISO 27001

NASA Astrophysics Data System (ADS)

Tatiara, R.; Fajar, A. N.; Siregar, B.; Gunawan, W.

2018-03-01

The purpose of this research is to determine multi factors that inhibiting the implementation of the ISMS based on ISO 2700. It is also to propose a follow-up recommendation on the factors that inhibit the implementation of the ISMS. Data collection is derived from questionnaires to 182 respondents from users in data center operation (DCO) at bca, Indonesian telecommunication international (telin), and data centre division at Indonesian Ministry of Health. We analysing data collection with multiple linear regression analysis and paired t-test. The results are multiple factors which inhibiting the implementation of the ISMS from the three organizations which has implement and operate the ISMS, ISMS documentation management, and continual improvement. From this research, we concluded that the processes of implementation in ISMS is the necessity of the role of all parties in succeeding the implementation of the ISMS continuously.

Factor investing based on Musharakah principle

NASA Astrophysics Data System (ADS)

Simon, Shahril; Omar, Mohd; Lazam, Norazliani Md; Amin, Mohd Nazrul Mohd

2015-10-01

Shariah stock investing has become a widely discussed topic in financial industry as part of today's investment strategy. The strategy primarily applies market capitalization allocations. However, some researchers have argued that market capitalization weighting is inherently flawed and have advocated replacing market capitalization allocations with factor allocations. In this paper, we discuss the rationale for factor investing based on Musharakah principle. The essential elements or factors of Musharakah principle such as business sector, management capability, profitability growth and capital efficiency are embedded in the Shariah-compliant stock. We then transform these factors into indexation for better analysis and performance measurement. Investment universe for this research covers Malaysian stocks for the period of January 2009 to December 2013. We found out that these factor indexes have historically earned excess returns over market capitalization weighted indexes and experienced higher Sharpe Ratios.

Analysis on influencing factors of EV charging station planning based on AHP

NASA Astrophysics Data System (ADS)

Yan, F.; Ma, X. F.

2016-08-01

As a new means of transport, electric vehicle (EV) is of great significance to alleviate the energy crisis. EV charging station planning has a far-reaching significance for the development of EV industry. This paper analyzes the impact factors of EV charging station planning, and then uses the analytic hierarchy process (AHP) to carry on the further analysis to the influencing factors, finally it gets the weight of each influence factor, and provides the basis for the evaluation scheme of the planning of charging stations for EV.

Framework Design and Influencing Factor Analysis of a Water Environmental Functional Zone-Based Effluent Trading System.

PubMed

Chen, Lei; Han, Zhaoxing; Li, Shuang; Shen, Zhenyao

2016-10-01

The efficacy of traditional effluent trading systems is questionable due to their neglect of seasonal hydrological variation and the creation of upstream hot spots within a watershed. Besides, few studies have been conducted to distinguish the impacts of each influencing factor on effluent trading systems outputs. In this study, a water environmental functional zone-based effluent trading systems framework was configured and a comprehensive analysis of its influencing factors was conducted. This proposed water environmental functional zone-based effluent trading systems was then applied for the control of chemical oxygen demand in the Beiyun River watershed, Beijing, China. Optimal trading results highlighted the integration of water quality constraints and different hydrological seasons, especially for downstream dischargers. The optimal trading of each discharger, in terms of pollutant reduction load and abatement cost, is greatly influenced by environmental and political factors such as background water quality, the location of river assessment points, and tradable discharge permits. In addition, the initial permit allowance has little influence on the market as a whole but does impact the individual discharger. These results provide information that is critical to understanding the impact of policy design on the functionality of an effluent trading systems.

Framework Design and Influencing Factor Analysis of a Water Environmental Functional Zone-Based Effluent Trading System

NASA Astrophysics Data System (ADS)

Chen, Lei; Han, Zhaoxing; Li, Shuang; Shen, Zhenyao

2016-10-01

The efficacy of traditional effluent trading systems is questionable due to their neglect of seasonal hydrological variation and the creation of upstream hot spots within a watershed. Besides, few studies have been conducted to distinguish the impacts of each influencing factor on effluent trading systems outputs. In this study, a water environmental functional zone-based effluent trading systems framework was configured and a comprehensive analysis of its influencing factors was conducted. This proposed water environmental functional zone-based effluent trading systems was then applied for the control of chemical oxygen demand in the Beiyun River watershed, Beijing, China. Optimal trading results highlighted the integration of water quality constraints and different hydrological seasons, especially for downstream dischargers. The optimal trading of each discharger, in terms of pollutant reduction load and abatement cost, is greatly influenced by environmental and political factors such as background water quality, the location of river assessment points, and tradable discharge permits. In addition, the initial permit allowance has little influence on the market as a whole but does impact the individual discharger. These results provide information that is critical to understanding the impact of policy design on the functionality of an effluent trading systems.

An Analysis of Multiple Factors Affecting Retention in Web-Based Community College Courses

ERIC Educational Resources Information Center

Doherty, William

2006-01-01

The current study examined four factors affecting retention in Web-based community college courses. Analyses were conducted on student demographics, student learning styles, course communication and external factors. The results suggest that Web-based courses are more attractive to busy students who are also more likely to fail or drop the course.…

Factors affecting medication adherence in community-managed patients with hypertension based on the principal component analysis: evidence from Xinjiang, China.

PubMed

Zhang, Yuji; Li, Xiaoju; Mao, Lu; Zhang, Mei; Li, Ke; Zheng, Yinxia; Cui, Wangfei; Yin, Hongpo; He, Yanli; Jing, Mingxia

2018-01-01

The analysis of factors affecting the nonadherence to antihypertensive medications is important in the control of blood pressure among patients with hypertension. The purpose of this study was to assess the relationship between factors and medication adherence in Xinjiang community-managed patients with hypertension based on the principal component analysis. A total of 1,916 community-managed patients with hypertension, selected randomly through a multi-stage sampling, participated in the survey. Self-designed questionnaires were used to classify the participants as either adherent or nonadherent to their medication regimen. A principal component analysis was used in order to eliminate the correlation between factors. Factors related to nonadherence were analyzed by using a χ 2 -test and a binary logistic regression model. This study extracted nine common factors, with a cumulative variance contribution rate of 63.6%. Further analysis revealed that the following variables were significantly related to nonadherence: severity of disease, community management, diabetes, and taking traditional medications. Community management plays an important role in improving the patients' medication-taking behavior. Regular medication regimen instruction and better community management services through community-level have the potential to reduce nonadherence. Mild hypertensive patients should be monitored by community health care providers.

[Habitat factor analysis for Torreya grandis cv. Merrillii based on spatial information technology].

PubMed

Wang, Xiao-ming; Wang, Ke; Ao, Wei-jiu; Deng, Jin-song; Han, Ning; Zhu, Xiao-yun

2008-11-01

Torreya grandis cv. Merrillii, a tertiary survival plant, is a rare tree species of significant economic value and expands rapidly in China. Its special habitat factor analysis has the potential value to provide guide information for its planting, management, and sustainable development, because the suitable growth conditions for this tree species are special and strict. In this paper, the special habitat factors for T. grandis cv. Merrillii in its core region, i.e., in seven villages of Zhuji City, Zhejiang Province were analyzed with Principal Component Analysis (PCA) and a series of data, such as IKONOS image, Digital Elevation Model (DEM), and field survey data supported by the spatial information technology. The results showed that T. grandis cv. Merrillii exhibited high selectivity of environmental factors such as elevation, slope, and aspect. 96.22% of T. grandis cv. Merrillii trees were located at the elevation from 300 to 600 m, 97.52% of them were found to present on the areas whose slope was less than 300, and 74.43% of them distributed on sunny and half-sunny slopes. The results of PCA analysis indicated that the main environmental factors affecting the habitat of T. grandis cv. Merrillii were moisture, heat, and soil nutrients, and moisture might be one of the most important ecological factors for T. grandis cv. Merrillii due to the unique biological and ecological characteristics of the tree species.

Nonlinear bulging factor based on R-curve data

NASA Technical Reports Server (NTRS)

Jeong, David Y.; Tong, Pin

1994-01-01

In this paper, a nonlinear bulging factor is derived using a strain energy approach combined with dimensional analysis. The functional form of the bulging factor contains an empirical constant that is determined using R-curve data from unstiffened flat and curved panel tests. The determination of this empirical constant is based on the assumption that the R-curve is the same for both flat and curved panels.

Health-Related Lifestyle Factors and Sexual Dysfunction: A Meta-Analysis of Population-Based Research.

PubMed

Allen, Mark S; Walter, Emma E

2018-04-01

-adjusted models and tests of potential moderators using meta-regression. Limitations include low statistical power in models testing diet, caffeine, and cannabis use as risk factors. Results provide compelling evidence that cigarette smoking, alcohol, and physical activity are important for sexual dysfunction. Insufficient research was available to draw conclusions regarding risk factors for premature ejaculation or for cannabis use as a risk factor. These findings should be of interest to clinicians treating men and women with complaints relating to symptoms of sexual dysfunction. Allen MS, Walter EE. Health-Related Lifestyle Factors and Sexual Dysfunction: A Meta-Analysis of Population-Based Research. J Sex Med 2018;15:458-475. Copyright © 2018 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Human Factors Vehicle Displacement Analysis: Engineering In Motion

NASA Technical Reports Server (NTRS)

Atencio, Laura Ashley; Reynolds, David; Robertson, Clay

2010-01-01

While positioned on the launch pad at the Kennedy Space Center, tall stacked launch vehicles are exposed to the natural environment. Varying directional winds and vortex shedding causes the vehicle to sway in an oscillating motion. The Human Factors team recognizes that vehicle sway may hinder ground crew operation, impact the ground system designs, and ultimately affect launch availability . The objective of this study is to physically simulate predicted oscillation envelopes identified by analysis. and conduct a Human Factors Analysis to assess the ability to carry out essential Upper Stage (US) ground operator tasks based on predicted vehicle motion.

Multivariate analysis of prognostic factors in synovial sarcoma.

PubMed

Koh, Kyoung Hwan; Cho, Eun Yoon; Kim, Dong Wook; Seo, Sung Wook

2009-11-01

Many studies have described the diversity of synovial sarcoma in terms of its biological characteristics and clinical features. Moreover, much effort has been expended on the identification of prognostic factors because of unpredictable behaviors of synovial sarcomas. However, with the exception of tumor size, published results have been inconsistent. We attempted to identify independent risk factors using survival analysis. Forty-one consecutive patients with synovial sarcoma were prospectively followed from January 1997 to March 2008. Overall and progression-free survival for age, sex, tumor size, tumor location, metastasis at presentation, histologic subtype, chemotherapy, radiation therapy, and resection margin were analyzed, and standard multivariate Cox proportional hazard regression analysis was used to evaluate potential prognostic factors. Tumor size (>5 cm), nonlimb-based tumors, metastasis at presentation, and a monophasic subtype were associated with poorer overall survival. Multivariate analysis showed metastasis at presentation and monophasic tumor subtype affected overall survival. For the progression-free survival, monophasic subtype was found to be only 1 prognostic factor. The study confirmed that histologic subtype is the single most important independent prognostic factors of synovial sarcoma regardless of tumor stage.

Testing of technology readiness index model based on exploratory factor analysis approach

NASA Astrophysics Data System (ADS)

Ariani, AF; Napitupulu, D.; Jati, RK; Kadar, JA; Syafrullah, M.

2018-04-01

SMEs readiness in using ICT will determine the adoption of ICT in the future. This study aims to evaluate the model of technology readiness in order to apply the technology on SMEs. The model is tested to find if TRI model is relevant to measure ICT adoption, especially for SMEs in Indonesia. The research method used in this paper is survey to a group of SMEs in South Tangerang. The survey measures the readiness to adopt ICT based on four variables which is Optimism, Innovativeness, Discomfort, and Insecurity. Each variable contains several indicators to make sure the variable is measured thoroughly. The data collected through survey is analysed using factor analysis methodwith the help of SPSS software. The result of this study shows that TRI model gives more descendants on some indicators and variables. This result can be caused by SMEs owners’ knowledge is not homogeneous about either the technology that they are used, knowledge or the type of their business.

Directional variance adjustment: bias reduction in covariance matrices based on factor analysis with an application to portfolio optimization.

PubMed

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation.

Analysis and Design of Power Factor Pre-Regulator Based on a Symmetrical Charge Pump Circuit Applied to Electronic Ballast

NASA Astrophysics Data System (ADS)

Lazcano Olea, Miguel; Ramos Astudillo, Reynaldo; Sanhueza Robles, René; Rodriguez Rubke, Leopoldo; Ruiz-Caballero, Domingo Antonio

This paper presents the analysis and design of a power factor pre-regulator based on a symmetrical charge pump circuit applied to electronic ballast. The operation stages of the circuit are analyzed and its main design equations are obtained. Simulation and experimental results are presented in order to show the design methodology feasibility.

Comparison of cardiovascular risk factors in maintenance hemodialysis patients based on phase angle of bioimpedance analysis

NASA Astrophysics Data System (ADS)

Muzasti, R. A.; Lubis, H. R.

2018-03-01

Mortality and morbidity rate, especially from cardiovascular disease in hemodialysis patients in Indonesia is still quite high. One of indicator to assess the predictive value of mortality is the phase angle (PhA) of bioimpedance analysis (BIA) scan examination. Determining the comparison of BMI and laboratory data as cardiovascular risk factors in hemodialysis patients based on PhA.A cross-sectional analytical study was done on 155 outpatientsin RasyidaRenal Hospital, Medan in 2016. Patients were two groups, namely PhA<4 group and ≥ 4 group. The comparison of BMI and laboratory data based on PhA were by analyzingthe independent T-test. A P-value <0.05 was considered statistically significant. Most of thepatients are male (56.7%), obese (39.4%), with age 40-59 years (56.1%). Based on PhA, 56.7% patients have PhA ≥4. There are differences in the profile of age (p: 0.01), BMI (p: 0.028) and hemoglobin (p: 0.00) between two groups, but not in the profile of albumin (p: 0.071), total cholesterol (p: 0.65), HDL (p: 0.06), LDL (p: 0.07), triglyceride (p: 0.87), calcium (p: 0.59) and phosphorus (p: 0.17).Based onPhA, the cardiovascular risk factors of hemodialysis patients were determined by age, BMI, and hemoglobin.

Success Probability Analysis for Shuttle Based Microgravity Experiments

NASA Technical Reports Server (NTRS)

Liou, Ying-Hsin Andrew

1996-01-01

Presented in this report are the results of data analysis of shuttle-based microgravity flight experiments. Potential factors were identified in the previous grant period, and in this period 26 factors were selected for data analysis. In this project, the degree of success was developed and used as the performance measure. 293 of the 391 experiments in Lewis Research Center Microgravity Database were assigned degrees of success. The frequency analysis and the analysis of variance were conducted to determine the significance of the factors that effect the experiment success.

Extension Procedures for Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Nagy, Gabriel; Brunner, Martin; Lüdtke, Oliver; Greiff, Samuel

2017-01-01

We present factor extension procedures for confirmatory factor analysis that provide estimates of the relations of common and unique factors with external variables that do not undergo factor analysis. We present identification strategies that build upon restrictions of the pattern of correlations between unique factors and external variables. The…

Donor retention in health care in Iran: a factor analysis

PubMed Central

Aghababa, Sara; Nasiripour, Amir Ashkan; Maleki, Mohammadreza; Gohari, Mahmoodreza

2017-01-01

Background: Long-term financial support is essential for the survival of a charitable organization. Health charities need to identify the effective factors influencing donor retention. Methods: In the present study, the items of a questionnaire were derived from both literature review and semi-structured interviews related to donor retention. Using a purposive sampling, 300 academic and executive practitioners were selected. After the follow- up, a total of 243 usable questionnaires were prepared for factor analysis. The questionnaire was validated based on the face and content validity and reliability through Cronbach’s α-coefficient. Results: The results of exploratory factor analysis extracted 2 factors for retention: donor factor (variance = 33.841%; Cronbach’s α-coefficient = 90.2) and charity factor (variance = 29.038%; Cronbach’s α-coefficient = 82.8), respectively. Subsequently, confirmatory factor analysis was applied to support the overall reasonable fit. Conclusions: In this study, it was found that repeated monetary donations are supplied to the charitable organizations when both aspects of donor factor (retention factor and charity factor) for retention are taken into consideration. This model could provide a perspective for making sustainable donations and charitable giving PMID:28955663

Subgroups of Dutch homeless young adults based on risk- and protective factors for quality of life: Results of a latent class analysis.

PubMed

Altena, Astrid M; Beijersbergen, Mariëlle D; Vermunt, Jeroen K; Wolf, Judith R L M

2018-04-17

It is important to gain more insight into specific subgroups of homeless young adults (HYA) to enable the development of tailored interventions that adequately meet their diverse needs and to improve their quality of life. Within a heterogeneous sample of HYA, we investigated whether subgroups are distinguishable based on risk- and protective factors for quality of life. In addition, differences between subgroups were examined regarding the socio-demographic characteristics, the use of cognitive coping strategies and quality of life. A total of 393 HYA using shelter facilities in the Netherlands were approached to participate, between December 2011 and March 2013. Structured face-to-face interviews were administered approximately 2 weeks after shelter admission by trained research assistants. A latent class analysis was conducted to empirically distinguish 251 HYA in subgroups based on common risk factors (former abuse, victimisation, psychological symptoms and substance use) and protective factors (resilience, family and social support and perceived health status). Additional analysis of variance and chi-square tests were used to compare subgroups on socio-demographic characteristics, the use of cognitive coping strategies and quality of life. The latent class analysis yielded four highly interpretable subgroups: the at-risk subgroup, the high-risk and least protected subgroup, the low-risk subgroup and the higher functioning and protected subgroup. Subgroups of HYA with lower scores in risk factors showed higher scores in protective factors, the adaptive cognitive coping strategies and quality of life. Our findings confirm the need for targeted and tailored interventions for specific subgroups of HYA. Social workers need to be attentive to the pattern of risk- and protective factors in each individual to determine which risk factors are prominent and need to be targeted and which protective factors need to be enhanced to improve the quality of life of HYA. �

Directional Variance Adjustment: Bias Reduction in Covariance Matrices Based on Factor Analysis with an Application to Portfolio Optimization

PubMed Central

Bartz, Daniel; Hatrick, Kerr; Hesse, Christian W.; Müller, Klaus-Robert; Lemm, Steven

2013-01-01

Robust and reliable covariance estimates play a decisive role in financial and many other applications. An important class of estimators is based on factor models. Here, we show by extensive Monte Carlo simulations that covariance matrices derived from the statistical Factor Analysis model exhibit a systematic error, which is similar to the well-known systematic error of the spectrum of the sample covariance matrix. Moreover, we introduce the Directional Variance Adjustment (DVA) algorithm, which diminishes the systematic error. In a thorough empirical study for the US, European, and Hong Kong stock market we show that our proposed method leads to improved portfolio allocation. PMID:23844016

Deep Learning with Hierarchical Convolutional Factor Analysis

PubMed Central

Chen, Bo; Polatkan, Gungor; Sapiro, Guillermo; Blei, David; Dunson, David; Carin, Lawrence

2013-01-01

Unsupervised multi-layered (“deep”) models are considered for general data, with a particular focus on imagery. The model is represented using a hierarchical convolutional factor-analysis construction, with sparse factor loadings and scores. The computation of layer-dependent model parameters is implemented within a Bayesian setting, employing a Gibbs sampler and variational Bayesian (VB) analysis, that explicitly exploit the convolutional nature of the expansion. In order to address large-scale and streaming data, an online version of VB is also developed. The number of basis functions or dictionary elements at each layer is inferred from the data, based on a beta-Bernoulli implementation of the Indian buffet process. Example results are presented for several image-processing applications, with comparisons to related models in the literature. PMID:23787342

Determinants of Standard Errors of MLEs in Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Cheng, Ying; Zhang, Wei

2010-01-01

This paper studies changes of standard errors (SE) of the normal-distribution-based maximum likelihood estimates (MLE) for confirmatory factor models as model parameters vary. Using logical analysis, simplified formulas and numerical verification, monotonic relationships between SEs and factor loadings as well as unique variances are found.…

Background recovery via motion-based robust principal component analysis with matrix factorization

NASA Astrophysics Data System (ADS)

Pan, Peng; Wang, Yongli; Zhou, Mingyuan; Sun, Zhipeng; He, Guoping

2018-03-01

Background recovery is a key technique in video analysis, but it still suffers from many challenges, such as camouflage, lighting changes, and diverse types of image noise. Robust principal component analysis (RPCA), which aims to recover a low-rank matrix and a sparse matrix, is a general framework for background recovery. The nuclear norm is widely used as a convex surrogate for the rank function in RPCA, which requires computing the singular value decomposition (SVD), a task that is increasingly costly as matrix sizes and ranks increase. However, matrix factorization greatly reduces the dimension of the matrix for which the SVD must be computed. Motion information has been shown to improve low-rank matrix recovery in RPCA, but this method still finds it difficult to handle original video data sets because of its batch-mode formulation and implementation. Hence, in this paper, we propose a motion-assisted RPCA model with matrix factorization (FM-RPCA) for background recovery. Moreover, an efficient linear alternating direction method of multipliers with a matrix factorization (FL-ADM) algorithm is designed for solving the proposed FM-RPCA model. Experimental results illustrate that the method provides stable results and is more efficient than the current state-of-the-art algorithms.

Factor Analysis of the Minnesota Infant Development Inventory Based on a Hispanic Migrant Population.

ERIC Educational Resources Information Center

Reilly, Amysue; Eaves, Ronald C.

2000-01-01

Completed the Minnesota Infant Development Inventory (MIDI), a parental report instrument, for 168 infants of Hispanic migrant workers and performed factor analysis of the MIDI scores. Results suggest that the one-factor solution is best for infants from Hispanic migrant families until future research supports other practices. (SLD)

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

NASA Astrophysics Data System (ADS)

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).

Evaluating voice characteristics of first-year acting students in Israel: factor analysis.

PubMed

Amir, Ofer; Primov-Fever, Adi; Kushnir, Tami; Kandelshine-Waldman, Osnat; Wolf, Michael

2013-01-01

Acting students require diverse, high-quality, and high-intensity vocal performance from early stages of their training. Demanding vocal activities, before developing the appropriate vocal skills, put them in high risk for developing vocal problems. A retrospective analysis of voice characteristics of first-year acting students using several voice evaluation tools. A total of 79 first-year acting students (55 women and 24 men) were assigned into two study groups: laryngeal findings (LFs) and no laryngeal findings, based on stroboscopic findings. Their voice characteristics were evaluated using acoustic analysis, aerodynamic examination, perceptual scales, and self-report questionnaires. Results obtained from each set of measures were examined using a factor analysis approach. Significant differences between the two groups were found for a single fundamental frequency (F(0))-Regularity factor; a single Grade, Roughness, Breathiness, Asthenia, Strain perceptual factor; and the three self-evaluation factors. Gender differences were found for two acoustic analysis factors, which were based on F(0) and its derivatives, namely an aerodynamic factor that represents expiratory volume measurements and a single self-evaluation factor that represents the tendency to seek therapy. Approximately 50% of the first-year acting students had LFs. These students differed from their peers in the control group in a single acoustic analysis factor, as well as perceptual and self-report factors. No group differences, however, were found for the aerodynamic factors. Early laryngeal examination and voice evaluation of future professional voice users could provide a valuable individual baseline, to which later examinations could be compared, and assist in providing personally tailored treatment. Copyright © 2013 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Risk factors for financial hardship in patients receiving adjuvant chemotherapy for colon cancer: a population-based exploratory analysis.

PubMed

Shankaran, Veena; Jolly, Sanjay; Blough, David; Ramsey, Scott D

2012-05-10

Characteristics that predispose patients to financial hardship during cancer treatment are poorly understood. We therefore conducted a population-based exploratory analysis of potential factors associated with financial hardship and treatment nonadherence during and following adjuvant chemotherapy for colon cancer. Patients diagnosed with stage III colon cancer between 2008 and 2010 were identified from a population-based cancer registry representing 13 counties in Washington state. Patients were asked to complete a comprehensive survey on treatment-related costs. Patients were considered to have experienced financial hardship if they accrued debt, sold or refinanced their home, borrowed money from friends or family, or experienced a 20% or greater decline in their annual income as a result of treatment-related expenses. Logistic regression analysis was used to investigate factors associated with financial hardship and treatment nonadherence. A total of 284 responses were obtained from 555 eligible patients (response rate, 51.2%). Nearly all patients in the final sample were insured during treatment. In this sample, 38% of patients reported one or more financial hardships as a result of treatment. The factors most closely associated with treatment-related financial hardship were younger age and lower annual household income. Younger age, lower income, and unemployment or disability (which occurred in most instances following diagnosis) were most closely associated with treatment nonadherence. A significant proportion of patients undergoing adjuvant chemotherapy for stage III colon cancer may experience financial hardship, despite having health insurance coverage. Interventions to help at-risk patients early on during therapy may prevent long-term financial adverse effects.

Analysis of the influencing factors of global energy interconnection development

NASA Astrophysics Data System (ADS)

Zhang, Yi; He, Yongxiu; Ge, Sifan; Liu, Lin

2018-04-01

Under the background of building global energy interconnection and achieving green and low-carbon development, this paper grasps a new round of energy restructuring and the trend of energy technology change, based on the present situation of global and China's global energy interconnection development, established the index system of the impact of global energy interconnection development factors. A subjective and objective weight analysis of the factors affecting the development of the global energy interconnection was conducted separately by network level analysis and entropy method, and the weights are summed up by the method of additive integration, which gives the comprehensive weight of the influencing factors and the ranking of their influence.

Affective Outcomes of Schooling: Full-Information Item Factor Analysis of a Student Questionnaire.

ERIC Educational Resources Information Center

Muraki, Eiji; Engelhard, George, Jr.

Recent developments in dichotomous factor analysis based on multidimensional item response models (Bock and Aitkin, 1981; Muthen, 1978) provide an effective method for exploring the dimensionality of questionnaire items. Implemented in the TESTFACT program, this "full information" item factor analysis accounts not only for the pairwise joint…

Exploratory Bi-factor Analysis: The Oblique Case.

PubMed

Jennrich, Robert I; Bentler, Peter M

2012-07-01

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

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

PubMed

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

2016-06-01

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

Factorization-based texture segmentation

DOE PAGES

Yuan, Jiangye; Wang, Deliang; Cheriyadat, Anil M.

2015-06-17

This study introduces a factorization-based approach that efficiently segments textured images. We use local spectral histograms as features, and construct an M × N feature matrix using M-dimensional feature vectors in an N-pixel image. Based on the observation that each feature can be approximated by a linear combination of several representative features, we factor the feature matrix into two matrices-one consisting of the representative features and the other containing the weights of representative features at each pixel used for linear combination. The factorization method is based on singular value decomposition and nonnegative matrix factorization. The method uses local spectral histogramsmore » to discriminate region appearances in a computationally efficient way and at the same time accurately localizes region boundaries. Finally, the experiments conducted on public segmentation data sets show the promise of this simple yet powerful approach.« less

Subphenotypes of mild-to-moderate COPD by factor and cluster analysis of pulmonary function, CT imaging and breathomics in a population-based survey.

PubMed

Fens, Niki; van Rossum, Annelot G J; Zanen, Pieter; van Ginneken, Bram; van Klaveren, Rob J; Zwinderman, Aeilko H; Sterk, Peter J

2013-06-01

Classification of COPD is currently based on the presence and severity of airways obstruction. However, this may not fully reflect the phenotypic heterogeneity of COPD in the (ex-) smoking community. We hypothesized that factor analysis followed by cluster analysis of functional, clinical, radiological and exhaled breath metabolomic features identifies subphenotypes of COPD in a community-based population of heavy (ex-) smokers. Adults between 50-75 years with a smoking history of at least 15 pack-years derived from a random population-based survey as part of the NELSON study underwent detailed assessment of pulmonary function, chest CT scanning, questionnaires and exhaled breath molecular profiling using an electronic nose. Factor and cluster analyses were performed on the subgroup of subjects fulfilling the GOLD criteria for COPD (post-BD FEV1/FVC < 0.70). Three hundred subjects were recruited, of which 157 fulfilled the criteria for COPD and were included in the factor and cluster analysis. Four clusters were identified: cluster 1 (n = 35; 22%): mild COPD, limited symptoms and good quality of life. Cluster 2 (n = 48; 31%): low lung function, combined emphysema and chronic bronchitis and a distinct breath molecular profile. Cluster 3 (n = 60; 38%): emphysema predominant COPD with preserved lung function. Cluster 4 (n = 14; 9%): highly symptomatic COPD with mildly impaired lung function. In a leave-one-out validation analysis an accuracy of 97.4% was reached. This unbiased taxonomy for mild to moderate COPD reinforces clusters found in previous studies and thereby allows better phenotyping of COPD in the general (ex-) smoking population.

Image-derived input function with factor analysis and a-priori information.

PubMed

Simončič, Urban; Zanotti-Fregonara, Paolo

2015-02-01

Quantitative PET studies often require the cumbersome and invasive procedure of arterial cannulation to measure the input function. This study sought to minimize the number of necessary blood samples by developing a factor-analysis-based image-derived input function (IDIF) methodology for dynamic PET brain studies. IDIF estimation was performed as follows: (a) carotid and background regions were segmented manually on an early PET time frame; (b) blood-weighted and tissue-weighted time-activity curves (TACs) were extracted with factor analysis; (c) factor analysis results were denoised and scaled using the voxels with the highest blood signal; (d) using population data and one blood sample at 40 min, whole-blood TAC was estimated from postprocessed factor analysis results; and (e) the parent concentration was finally estimated by correcting the whole-blood curve with measured radiometabolite concentrations. The methodology was tested using data from 10 healthy individuals imaged with [(11)C](R)-rolipram. The accuracy of IDIFs was assessed against full arterial sampling by comparing the area under the curve of the input functions and by calculating the total distribution volume (VT). The shape of the image-derived whole-blood TAC matched the reference arterial curves well, and the whole-blood area under the curves were accurately estimated (mean error 1.0±4.3%). The relative Logan-V(T) error was -4.1±6.4%. Compartmental modeling and spectral analysis gave less accurate V(T) results compared with Logan. A factor-analysis-based IDIF for [(11)C](R)-rolipram brain PET studies that relies on a single blood sample and population data can be used for accurate quantification of Logan-V(T) values.

Exploratory Bi-Factor Analysis: The Oblique Case

ERIC Educational Resources Information Center

Jennrich, Robert I.; Bentler, Peter M.

2012-01-01

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

Bayesian Exploratory Factor Analysis

PubMed Central

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

2014-01-01

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

Human factors in mental healthcare: A work system analysis of a community-based program for older adults with depression and dementia.

PubMed

Heiden, Siobhan M; Holden, Richard J; Alder, Catherine A; Bodke, Kunal; Boustani, Malaz

2017-10-01

Mental healthcare is a critical but largely unexplored application domain for human factors/ergonomics. This paper reports on a work system evaluation of a home-based dementia and depression care program for older adults, the Aging Brain Care program. The Workflow Elements Model was used to guide data collection and analysis of 59 h of observation, supplemented by key informant input. We identified four actors, 37 artifacts across seven types, ten action categories, and ten outcomes including improved health and safety. Five themes emerged regarding barriers and facilitators to care delivery in the program: the centrality of relationship building; the use of adaptive workarounds; performance of duplicate work; travel and scheduling challenges; and communication-related factors. Findings offer new insight into how mental healthcare services are delivered in a community-based program and key work-related factors shaping program outcomes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dimensional Model for Estimating Factors influencing Childhood Obesity: Path Analysis Based Modeling

PubMed Central

Kheirollahpour, Maryam; Shohaimi, Shamarina

2014-01-01

The main objective of this study is to identify and develop a comprehensive model which estimates and evaluates the overall relations among the factors that lead to weight gain in children by using structural equation modeling. The proposed models in this study explore the connection among the socioeconomic status of the family, parental feeding practice, and physical activity. Six structural models were tested to identify the direct and indirect relationship between the socioeconomic status and parental feeding practice general level of physical activity, and weight status of children. Finally, a comprehensive model was devised to show how these factors relate to each other as well as to the body mass index (BMI) of the children simultaneously. Concerning the methodology of the current study, confirmatory factor analysis (CFA) was applied to reveal the hidden (secondary) effect of socioeconomic factors on feeding practice and ultimately on the weight status of the children and also to determine the degree of model fit. The comprehensive structural model tested in this study suggested that there are significant direct and indirect relationships among variables of interest. Moreover, the results suggest that parental feeding practice and physical activity are mediators in the structural model. PMID:25097878

Bayes factors based on robust TDT-type tests for family trio design.

PubMed

Yuan, Min; Pan, Xiaoqing; Yang, Yaning

2015-06-01

Adaptive transmission disequilibrium test (aTDT) and MAX3 test are two robust-efficient association tests for case-parent family trio data. Both tests incorporate information of common genetic models including recessive, additive and dominant models and are efficient in power and robust to genetic model specifications. The aTDT uses information of departure from Hardy-Weinberg disequilibrium to identify the potential genetic model underlying the data and then applies the corresponding TDT-type test, and the MAX3 test is defined as the maximum of the absolute value of three TDT-type tests under the three common genetic models. In this article, we propose three robust Bayes procedures, the aTDT based Bayes factor, MAX3 based Bayes factor and Bayes model averaging (BMA), for association analysis with case-parent trio design. The asymptotic distributions of aTDT under the null and alternative hypothesis are derived in order to calculate its Bayes factor. Extensive simulations show that the Bayes factors and the p-values of the corresponding tests are generally consistent and these Bayes factors are robust to genetic model specifications, especially so when the priors on the genetic models are equal. When equal priors are used for the underlying genetic models, the Bayes factor method based on aTDT is more powerful than those based on MAX3 and Bayes model averaging. When the prior placed a small (large) probability on the true model, the Bayes factor based on aTDT (BMA) is more powerful. Analysis of a simulation data about RA from GAW15 is presented to illustrate applications of the proposed methods.

Factor Analysis of Traffic Safety in Urban Roads Based on FTA-LEC

NASA Astrophysics Data System (ADS)

Shuicheng, TIAN; Xingbo, YANG; Xiaoqing, SHEN; Detao, ZHANG

2018-05-01

In order to reduce the number and the loss of urban road traffic accidents in our country, improve the safety of road traffic, a statistical analysis of the research report on major road traffic accidents in 2016 was conducted. The risk factors affecting urban road traffic in China were analyzed by using FTA to find the basic hidden events. Secondly, the risk value of the identified hidden danger events were calculated and classified into four levels I, II, III and IV through the LEC evaluation method. Finally, the graded results of risk factors are verified through a case of specific accidents in Beijing. The results show that: the case verified the scientificalness and effectiveness of hazard classification and provided guidance for urban road traffic management.

Factor Analysis of Intern Effectiveness

ERIC Educational Resources Information Center

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

2012-01-01

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

Factors that Affect Poverty Areas in North Sumatera Using Discriminant Analysis

NASA Astrophysics Data System (ADS)

Nasution, D. H.; Bangun, P.; Sitepu, H. R.

2018-04-01

In Indonesia, especially North Sumatera, the problem of poverty is one of the fundamental problems that become the focus of government both central and local government. Although the poverty rate decreased but the fact is there are many people who are poor. Poverty happens covers several aspects such as education, health, demographics, and also structural and cultural. This research will discuss about several factors such as population density, Unemployment Rate, GDP per capita ADHK, ADHB GDP per capita, economic growth and life expectancy that affect poverty in Indonesia. To determine the factors that most influence and differentiate the level of poverty of the Regency/City North Sumatra used discriminant analysis method. Discriminant analysis is one multivariate analysis technique are used to classify the data into a group based on the dependent variable and independent variable. Using discriminant analysis, it is evident that the factor affecting poverty is Unemployment Rate.

Robust Bayesian Factor Analysis

ERIC Educational Resources Information Center

Hayashi, Kentaro; Yuan, Ke-Hai

2003-01-01

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

THz spectral data analysis and components unmixing based on non-negative matrix factorization methods

NASA Astrophysics Data System (ADS)

Ma, Yehao; Li, Xian; Huang, Pingjie; Hou, Dibo; Wang, Qiang; Zhang, Guangxin

2017-04-01

In many situations the THz spectroscopic data observed from complex samples represent the integrated result of several interrelated variables or feature components acting together. The actual information contained in the original data might be overlapping and there is a necessity to investigate various approaches for model reduction and data unmixing. The development and use of low-rank approximate nonnegative matrix factorization (NMF) and smooth constraint NMF (CNMF) algorithms for feature components extraction and identification in the fields of terahertz time domain spectroscopy (THz-TDS) data analysis are presented. The evolution and convergence properties of NMF and CNMF methods based on sparseness, independence and smoothness constraints for the resulting nonnegative matrix factors are discussed. For general NMF, its cost function is nonconvex and the result is usually susceptible to initialization and noise corruption, and may fall into local minima and lead to unstable decomposition. To reduce these drawbacks, smoothness constraint is introduced to enhance the performance of NMF. The proposed algorithms are evaluated by several THz-TDS data decomposition experiments including a binary system and a ternary system simulating some applications such as medicine tablet inspection. Results show that CNMF is more capable of finding optimal solutions and more robust for random initialization in contrast to NMF. The investigated method is promising for THz data resolution contributing to unknown mixture identification.

THz spectral data analysis and components unmixing based on non-negative matrix factorization methods.

PubMed

Ma, Yehao; Li, Xian; Huang, Pingjie; Hou, Dibo; Wang, Qiang; Zhang, Guangxin

2017-04-15

In many situations the THz spectroscopic data observed from complex samples represent the integrated result of several interrelated variables or feature components acting together. The actual information contained in the original data might be overlapping and there is a necessity to investigate various approaches for model reduction and data unmixing. The development and use of low-rank approximate nonnegative matrix factorization (NMF) and smooth constraint NMF (CNMF) algorithms for feature components extraction and identification in the fields of terahertz time domain spectroscopy (THz-TDS) data analysis are presented. The evolution and convergence properties of NMF and CNMF methods based on sparseness, independence and smoothness constraints for the resulting nonnegative matrix factors are discussed. For general NMF, its cost function is nonconvex and the result is usually susceptible to initialization and noise corruption, and may fall into local minima and lead to unstable decomposition. To reduce these drawbacks, smoothness constraint is introduced to enhance the performance of NMF. The proposed algorithms are evaluated by several THz-TDS data decomposition experiments including a binary system and a ternary system simulating some applications such as medicine tablet inspection. Results show that CNMF is more capable of finding optimal solutions and more robust for random initialization in contrast to NMF. The investigated method is promising for THz data resolution contributing to unknown mixture identification. Copyright © 2017 Elsevier B.V. All rights reserved.

Superpixel Based Factor Analysis and Target Transformation Method for Martian Minerals Detection

NASA Astrophysics Data System (ADS)

Wu, X.; Zhang, X.; Lin, H.

2018-04-01

The Factor analysis and target transformation (FATT) is an effective method to test for the presence of particular mineral on Martian surface. It has been used both in thermal infrared (Thermal Emission Spectrometer, TES) and near-infrared (Compact Reconnaissance Imaging Spectrometer for Mars, CRISM) hyperspectral data. FATT derived a set of orthogonal eigenvectors from a mixed system and typically selected first 10 eigenvectors to least square fit the library mineral spectra. However, minerals present only in a limited pixels will be ignored because its weak spectral features compared with full image signatures. Here, we proposed a superpixel based FATT method to detect the mineral distributions on Mars. The simple linear iterative clustering (SLIC) algorithm was used to partition the CRISM image into multiple connected image regions with spectral homogeneous to enhance the weak signatures by increasing their proportion in a mixed system. A least square fitting was used in target transformation and performed to each region iteratively. Finally, the distribution of the specific minerals in image was obtained, where fitting residual less than a threshold represent presence and otherwise absence. We validate our method by identifying carbonates in a well analysed CRISM image in Nili Fossae on Mars. Our experimental results indicate that the proposed method work well both in simulated and real data sets.

Factors influencing evidence-based practice in prosthetics and orthotics.

PubMed

Andrysek, Jan; Christensen, James; Dupuis, Annie

2011-03-01

The importance of evidence-based practice is being recognized across a broad range of healthcare disciplines as a means for improving patient outcomes and also efficiently managing healthcare resources. The objective of this work was to obtain information from clinicians about the underlying barriers and facilitators relating to evidence-based practice in prosthetics and orthotics. Cross sectional survey. An internet survey was developed and distributed to 300 prosthetists and orthotists currently practicing in Canada. A principal component factor analysis of the survey results revealed ten primary factors affecting evidence-based practice. These include time constraints, workload and system demands, limited relevant evidence from research, and gaps in skills and knowledge required to perform evidence-based practice. Clinicians value research as a means of improving clinical practice, but they are faced with a number of practical barriers in performing evidence-based practice. This study provides empirical data about the underlying barriers and facilitators relating to evidence-based practice in prosthetics and orthotics. Such data are essential in order to inform those involved in improving existing clinical practices, including educators, professional organizations, and governing bodies.

Pathway-based factor analysis of gene expression data produces highly heritable phenotypes that associate with age.

PubMed

Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

2015-03-09

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 "pathway phenotypes" that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold ([Formula: see text]). These phenotypes are more heritable ([Formula: see text]) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. Copyright © 2015 Brown et al.

Pathway-Based Factor Analysis of Gene Expression Data Produces Highly Heritable Phenotypes That Associate with Age

PubMed Central

Anand Brown, Andrew; Ding, Zhihao; Viñuela, Ana; Glass, Dan; Parts, Leopold; Spector, Tim; Winn, John; Durbin, Richard

2015-01-01

Statistical factor analysis methods have previously been used to remove noise components from high-dimensional data prior to genetic association mapping and, in a guided fashion, to summarize biologically relevant sources of variation. Here, we show how the derived factors summarizing pathway expression can be used to analyze the relationships between expression, heritability, and aging. We used skin gene expression data from 647 twins from the MuTHER Consortium and applied factor analysis to concisely summarize patterns of gene expression to remove broad confounding influences and to produce concise pathway-level phenotypes. We derived 930 “pathway phenotypes” that summarized patterns of variation across 186 KEGG pathways (five phenotypes per pathway). We identified 69 significant associations of age with phenotype from 57 distinct KEGG pathways at a stringent Bonferroni threshold (P<5.38×10−5). These phenotypes are more heritable (h2=0.32) than gene expression levels. On average, expression levels of 16% of genes within these pathways are associated with age. Several significant pathways relate to metabolizing sugars and fatty acids; others relate to insulin signaling. We have demonstrated that factor analysis methods combined with biological knowledge can produce more reliable phenotypes with less stochastic noise than the individual gene expression levels, which increases our power to discover biologically relevant associations. These phenotypes could also be applied to discover associations with other environmental factors. PMID:25758824

Risk Factors for Child Malnutrition in Bangladesh: A Multilevel Analysis of a Nationwide Population-Based Survey.

PubMed

Chowdhury, Mohammad Rocky Khan; Rahman, Mohammad Shafiur; Khan, Mohammad Mubarak Hossain; Mondal, Mohammad Nazrul Islam; Rahman, Mohammad Mosiur; Billah, Baki

2016-05-01

To identify the prevalence and risk factors of child malnutrition in Bangladesh. Data was extracted from the Bangladesh Demographic Health Survey (2011). The outcome measures were stunting, wasting, and underweight. χ(2) analysis was performed to find the association of outcome variables with selected factors. Multilevel logistic regression models with a random intercept at each of the household and community levels were used to identify the risk factors of stunting, wasting, and underweight. From the 2011 survey, 7568 children less than 5 years of age were included in the current analysis. The overall prevalence of stunting, wasting, and underweight was 41.3% (95% CI 39.0-42.9). The χ(2) test and multilevel logistic regression analysis showed that the variables age, sex, mother's body mass index, mother's educational status, father's educational status, place of residence, socioeconomic status, community status, religion, region of residence, and food security are significant factors of child malnutrition. Children with poor socioeconomic and community status were at higher risk of malnutrition. Children from food insecure families were more likely to be malnourished. Significant community- and household-level variations were found. The prevalence of child malnutrition is still high in Bangladesh, and the risk was assessed at several multilevel factors. Therefore, prevention of malnutrition should be given top priority as a major public health intervention. Copyright © 2016 Elsevier Inc. All rights reserved.

A discriminant analysis prediction model of non-syndromic cleft lip with or without cleft palate based on risk factors.

PubMed

Li, Huixia; Luo, Miyang; Luo, Jiayou; Zheng, Jianfei; Zeng, Rong; Du, Qiyun; Fang, Junqun; Ouyang, Na

2016-11-23

A risk prediction model of non-syndromic cleft lip with or without cleft palate (NSCL/P) was established by a discriminant analysis to predict the individual risk of NSCL/P in pregnant women. A hospital-based case-control study was conducted with 113 cases of NSCL/P and 226 controls without NSCL/P. The cases and the controls were obtained from 52 birth defects' surveillance hospitals in Hunan Province, China. A questionnaire was administered in person to collect the variables relevant to NSCL/P by face to face interviews. Logistic regression models were used to analyze the influencing factors of NSCL/P, and a stepwise Fisher discriminant analysis was subsequently used to construct the prediction model. In the univariate analysis, 13 influencing factors were related to NSCL/P, of which the following 8 influencing factors as predictors determined the discriminant prediction model: family income, maternal occupational hazards exposure, premarital medical examination, housing renovation, milk/soymilk intake in the first trimester of pregnancy, paternal occupational hazards exposure, paternal strong tea drinking, and family history of NSCL/P. The model had statistical significance (lambda = 0.772, chi-square = 86.044, df = 8, P < 0.001). Self-verification showed that 83.8 % of the participants were correctly predicted to be NSCL/P cases or controls with a sensitivity of 74.3 % and a specificity of 88.5 %. The area under the receiver operating characteristic curve (AUC) was 0.846. The prediction model that was established using the risk factors of NSCL/P can be useful for predicting the risk of NSCL/P. Further research is needed to improve the model, and confirm the validity and reliability of the model.

Exploring Context and the Factors Shaping Team-Based Primary Healthcare Policies in Three Canadian Provinces: A Comparative Analysis.

PubMed

Misfeldt, Renée; Suter, Esther; Mallinson, Sara; Boakye, Omenaa; Wong, Sabrina; Nasmith, Louise

2017-08-01

This paper discusses findings from a high-level scan of the contextual factors and actors that influenced policies on team-based primary healthcare in three Canadian provinces: British Columbia, Alberta and Saskatchewan. The team searched diverse sources (e.g., news reports, press releases, discussion papers) for contextual information relevant to primary healthcare teams. We also conducted qualitative interviews with key health system informants from the three provinces. Data from documents and interviews were analyzed qualitatively using thematic analysis. We then wrote narrative summaries highlighting pivotal policy and local system events and the influence of actors and context. Our overall findings highlight the value of reviewing the context, relationships and power dynamics, which come together and create "policy windows" at different points in time. We observed physician-centric policy processes with some recent moves to rebalance power and be inclusive of other actors and perspectives. The context review also highlighted the significant influence of changes in political leadership and prioritization in driving policies on team-based care. While this existed in different degrees in the three provinces, the push and pull of political and professional power dynamics shaped Canadian provincial policies governing team-based care. If we are to move team-based primary healthcare forward in Canada, the provinces need to review the external factors and the complex set of relationships and trade-offs that underscore the policy process. Copyright © 2017 Longwoods Publishing.

Human error analysis of commercial aviation accidents using the human factors analysis and classification system (HFACS)

DOT National Transportation Integrated Search

2001-02-01

The Human Factors Analysis and Classification System (HFACS) is a general human error framework : originally developed and tested within the U.S. military as a tool for investigating and analyzing the human : causes of aviation accidents. Based upon ...

The Infinitesimal Jackknife with Exploratory Factor Analysis

ERIC Educational Resources Information Center

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…

Quality of physical therapy from a patient's perspective; factor analysis on web-based survey data revealed three dimensions on patient experiences with physical therapy.

PubMed

Scholte, Marijn; Calsbeek, Hilly; Nijhuis-van der Sanden, Maria W G; Braspenning, Jozé

2014-06-18

Assessing quality of care from the patient's perspective has changed from patient satisfaction to the more general term patient experience, as satisfaction measures turned out to be less discriminative due to high scores. Literature describes four to ten dimensions of patient experience, tailored to specific conditions or types of care. Given the administrative burden on patients, less dimensions and items could increase feasibility. Ten dimensions of patient experiences with physical therapy (PT) were proposed in the Netherlands in a consensus-based process with patients, physical therapists, health insurers, and policy makers. The aim of this paper is to detect the number of dimensions from data of a field study using factor analysis at item level. A web-based survey yielded data of 2,221 patients from 52 PT practices on 41 items. Principal component factor analysis at item level was used to assess the proposed distinction between the ten dimensions. Factor analysis revealed two dimensions: 'personal interaction' and 'practice organisation'. The dimension 'patient reported outcome' was artificially established. The three dimensions 'personal interaction' (14 items) (median(practice level) = 91.1; IQR = 2.4), 'practice organisation' (9 items) (median(practice level) = 88.9; IQR = 6.0) and 'outcome' (3 items) (median(practice level) = 80.6; IQR = 19.5) reduced the number of dimensions from ten to three and the number of items by more than a third. Factor analysis revealed three dimensions and achieved an item reduction of more than a third. It is a relevant step in the development process of a quality measurement tool to reduce respondent burden, increase clarity, and promote feasibility.

Molecular genetic analysis of activation-tagged transcription factors thought to be involved in photomorphogenesis

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

Neff, Michael M.

This is a final report for Department of Energy Grant No. DE-FG02-08ER15927 entitled “Molecular Genetic Analysis of Activation-Tagged Transcription Factors Thought to be Involved in Photomorphogenesis”. Based on our preliminary photobiological and genetic analysis of the sob1-D mutant, we hypothesized that OBP3 is a transcription factor involved in both phytochrome and cryptochrome-mediated signal transduction. In addition, we hypothesized that OBP3 is involved in auxin signaling and root development. Based on our preliminary photobiological and genetic analysis of the sob2-D mutant, we also hypothesized that a related gene, LEP, is involved in hormone signaling and seedling development.

Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

PubMed

Roberson, Richard B; Elliott, Timothy R; Chang, Jessica E; Hill, Jessica N

2014-11-01

Our objective was to examine the use and quality of exploratory factor analysis (EFA) in articles published in Rehabilitation Psychology. Trained raters examined 66 separate exploratory factor analyses in 47 articles published between 1999 and April 2014. The raters recorded the aim of the EFAs, the distributional statistics, sample size, factor retention method(s), extraction and rotation method(s), and whether the pattern coefficients, structure coefficients, and the matrix of association were reported. The primary use of the EFAs was scale development, but the most widely used extraction and rotation method was principle component analysis, with varimax rotation. When determining how many factors to retain, multiple methods (e.g., scree plot, parallel analysis) were used most often. Many articles did not report enough information to allow for the duplication of their results. EFA relies on authors' choices (e.g., factor retention rules extraction, rotation methods), and few articles adhered to all of the best practices. The current findings are compared to other empirical investigations into the use of EFA in published research. Recommendations for improving EFA reporting practices in rehabilitation psychology research are provided.

A Confirmatory Factor Analysis of Reilly's Role Overload Scale

ERIC Educational Resources Information Center

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…

On the stability analysis of approximate factorization methods for 3D Euler and Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Demuren, A. O.; Ibraheem, S. O.

1993-01-01

The convergence characteristics of various approximate factorizations for the 3D Euler and Navier-Stokes equations are examined using the von-Neumann stability analysis method. Three upwind-difference based factorizations and several central-difference based factorizations are considered for the Euler equations. In the upwind factorizations both the flux-vector splitting methods of Steger and Warming and van Leer are considered. Analysis of the Navier-Stokes equations is performed only on the Beam and Warming central-difference scheme. The range of CFL numbers over which each factorization is stable is presented for one-, two-, and three-dimensional flow. Also presented for each factorization is the CFL number at which the maximum eigenvalue is minimized, for all Fourier components, as well as for the high frequency range only. The latter is useful for predicting the effectiveness of multigrid procedures with these schemes as smoothers. Further, local mode analysis is performed to test the suitability of using a uniform flow field in the stability analysis. Some inconsistencies in the results from previous analyses are resolved.

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

NASA Astrophysics Data System (ADS)

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.

Phenotypic factor analysis of psychopathology reveals a new body-related transdiagnostic factor.

PubMed

Pezzoli, Patrizia; Antfolk, Jan; Santtila, Pekka

2017-01-01

Comorbidity challenges the notion of mental disorders as discrete categories. An increasing body of literature shows that symptoms cut across traditional diagnostic boundaries and interact in shaping the latent structure of psychopathology. Using exploratory and confirmatory factor analysis, we reveal the latent sources of covariation among nine measures of psychopathological functioning in a population-based sample of 13024 Finnish twins and their siblings. By implementing unidimensional, multidimensional, second-order, and bifactor models, we illustrate the relationships between observed variables, specific, and general latent factors. We also provide the first investigation to date of measurement invariance of the bifactor model of psychopathology across gender and age groups. Our main result is the identification of a distinct "Body" factor, alongside the previously identified Internalizing and Externalizing factors. We also report relevant cross-disorder associations, especially between body-related psychopathology and trait anger, as well as substantial sex and age differences in observed and latent means. The findings expand the meta-structure of psychopathology, with implications for empirical and clinical practice, and demonstrate shared mechanisms underlying attitudes towards nutrition, self-image, sexuality and anger, with gender- and age-specific features.

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

PubMed

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

2015-02-01

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

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

PubMed Central

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

2016-01-01

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

Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty

DOE PAGES

Opgenoord, Max M. J.; Allaire, Douglas L.; Willcox, Karen E.

2016-09-12

Sensitivity analysis plays a critical role in quantifying uncertainty in the design of engineering systems. A variance-based global sensitivity analysis is often used to rank the importance of input factors, based on their contribution to the variance of the output quantity of interest. However, this analysis assumes that all input variability can be reduced to zero, which is typically not the case in a design setting. Distributional sensitivity analysis (DSA) instead treats the uncertainty reduction in the inputs as a random variable, and defines a variance-based sensitivity index function that characterizes the relative contribution to the output variance as amore » function of the amount of uncertainty reduction. This paper develops a computationally efficient implementation for the DSA formulation and extends it to include distributions commonly used in engineering design under uncertainty. Application of the DSA method to the conceptual design of a commercial jetliner demonstrates how the sensitivity analysis provides valuable information to designers and decision-makers on where and how to target uncertainty reduction efforts.« less

Variance-Based Sensitivity Analysis to Support Simulation-Based Design Under Uncertainty

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

Opgenoord, Max M. J.; Allaire, Douglas L.; Willcox, Karen E.

Sensitivity analysis plays a critical role in quantifying uncertainty in the design of engineering systems. A variance-based global sensitivity analysis is often used to rank the importance of input factors, based on their contribution to the variance of the output quantity of interest. However, this analysis assumes that all input variability can be reduced to zero, which is typically not the case in a design setting. Distributional sensitivity analysis (DSA) instead treats the uncertainty reduction in the inputs as a random variable, and defines a variance-based sensitivity index function that characterizes the relative contribution to the output variance as amore » function of the amount of uncertainty reduction. This paper develops a computationally efficient implementation for the DSA formulation and extends it to include distributions commonly used in engineering design under uncertainty. Application of the DSA method to the conceptual design of a commercial jetliner demonstrates how the sensitivity analysis provides valuable information to designers and decision-makers on where and how to target uncertainty reduction efforts.« less

Confirmatory Factor Analysis of the Minnesota Nicotine Withdrawal Scale

PubMed Central

Toll, Benjamin A.; O’Malley, Stephanie S.; McKee, Sherry A.; Salovey, Peter; Krishnan-Sarin, Suchitra

2008-01-01

The authors examined the factor structure of the Minnesota Nicotine Withdrawal Scale (MNWS) using confirmatory factor analysis in clinical research samples of smokers trying to quit (n = 723). Three confirmatory factor analytic models, based on previous research, were tested with each of the 3 study samples at multiple points in time. A unidimensional model including all 8 MNWS items was found to be the best explanation of the data. This model produced fair to good internal consistency estimates. Additionally, these data revealed that craving should be included in the total score of the MNWS. Factor scores derived from this single-factor, 8-item model showed that increases in withdrawal were associated with poor smoking outcome for 2 of the clinical studies. Confirmatory factor analyses of change scores showed that the MNWS symptoms cohere as a syndrome over time. Future investigators should report a total score using all of the items from the MNWS. PMID:17563141

Estimation of Hydrogen-Exchange Protection Factors from MD Simulation Based on Amide Hydrogen Bonding Analysis.

PubMed

Park, In-Hee; Venable, John D; Steckler, Caitlin; Cellitti, Susan E; Lesley, Scott A; Spraggon, Glen; Brock, Ansgar

2015-09-28

Hydrogen exchange (HX) studies have provided critical insight into our understanding of protein folding, structure, and dynamics. More recently, hydrogen exchange mass spectrometry (HX-MS) has become a widely applicable tool for HX studies. The interpretation of the wealth of data generated by HX-MS experiments as well as other HX methods would greatly benefit from the availability of exchange predictions derived from structures or models for comparison with experiment. Most reported computational HX modeling studies have employed solvent-accessible-surface-area based metrics in attempts to interpret HX data on the basis of structures or models. In this study, a computational HX-MS prediction method based on classification of the amide hydrogen bonding modes mimicking the local unfolding model is demonstrated. Analysis of the NH bonding configurations from molecular dynamics (MD) simulation snapshots is used to determine partitioning over bonded and nonbonded NH states and is directly mapped into a protection factor (PF) using a logistics growth function. Predicted PFs are then used for calculating deuteration values of peptides and compared with experimental data. Hydrogen exchange MS data for fatty acid synthase thioesterase (FAS-TE) collected for a range of pHs and temperatures was used for detailed evaluation of the approach. High correlation between prediction and experiment for observable fragment peptides is observed in the FAS-TE and additional benchmarking systems that included various apo/holo proteins for which literature data were available. In addition, it is shown that HX modeling can improve experimental resolution through decomposition of in-exchange curves into rate classes, which correlate with prediction from MD. Successful rate class decompositions provide further evidence that the presented approach captures the underlying physical processes correctly at the single residue level. This assessment is further strengthened in a comparison of

Estimation of Hydrogen-Exchange Protection Factors from MD Simulation Based on Amide Hydrogen Bonding Analysis

PubMed Central

Park, In-Hee; Venable, John D.; Steckler, Caitlin; Cellitti, Susan E.; Lesley, Scott A.; Spraggon, Glen; Brock, Ansgar

2015-01-01

Hydrogen exchange (HX) studies have provided critical insight into our understanding of protein folding, structure and dynamics. More recently, Hydrogen Exchange Mass Spectrometry (HX-MS) has become a widely applicable tool for HX studies. The interpretation of the wealth of data generated by HX-MS experiments as well as other HX methods would greatly benefit from the availability of exchange predictions derived from structures or models for comparison with experiment. Most reported computational HX modeling studies have employed solvent-accessible-surface-area based metrics in attempts to interpret HX data on the basis of structures or models. In this study, a computational HX-MS prediction method based on classification of the amide hydrogen bonding modes mimicking the local unfolding model is demonstrated. Analysis of the NH bonding configurations from Molecular Dynamics (MD) simulation snapshots is used to determine partitioning over bonded and non-bonded NH states and is directly mapped into a protection factor (PF) using a logistics growth function. Predicted PFs are then used for calculating deuteration values of peptides and compared with experimental data. Hydrogen exchange MS data for Fatty acid synthase thioesterase (FAS-TE) collected for a range of pHs and temperatures was used for detailed evaluation of the approach. High correlation between prediction and experiment for observable fragment peptides is observed in the FAS-TE and additional benchmarking systems that included various apo/holo proteins for which literature data were available. In addition, it is shown that HX modeling can improve experimental resolution through decomposition of in-exchange curves into rate classes, which correlate with prediction from MD. Successful rate class decompositions provide further evidence that the presented approach captures the underlying physical processes correctly at the single residue level. This assessment is further strengthened in a comparison of

47 CFR 69.502 - Base factor allocation.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 3 2011-10-01 2011-10-01 false Base factor allocation. 69.502 Section 69.502... Segregation of Common Line Element Revenue Requirement § 69.502 Base factor allocation. Projected revenues from the following shall be deducted from the base factor portion to determine the amount that is...

47 CFR 69.502 - Base factor allocation.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 47 Telecommunication 3 2013-10-01 2013-10-01 false Base factor allocation. 69.502 Section 69.502... Segregation of Common Line Element Revenue Requirement § 69.502 Base factor allocation. Projected revenues from the following shall be deducted from the base factor portion to determine the amount that is...

47 CFR 69.502 - Base factor allocation.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 47 Telecommunication 3 2012-10-01 2012-10-01 false Base factor allocation. 69.502 Section 69.502... Segregation of Common Line Element Revenue Requirement § 69.502 Base factor allocation. Projected revenues from the following shall be deducted from the base factor portion to determine the amount that is...

47 CFR 69.502 - Base factor allocation.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 47 Telecommunication 3 2010-10-01 2010-10-01 false Base factor allocation. 69.502 Section 69.502... Segregation of Common Line Element Revenue Requirement § 69.502 Base factor allocation. Projected revenues from the following shall be deducted from the base factor portion to determine the amount that is...

Recovery of Weak Factor Loadings When Adding the Mean Structure in Confirmatory Factor Analysis: A Simulation Study

PubMed Central

Ximénez, Carmen

2016-01-01

This article extends previous research on the recovery of weak factor loadings in confirmatory factor analysis (CFA) by exploring the effects of adding the mean structure. This issue has not been examined in previous research. This study is based on the framework of Yung and Bentler (1999) and aims to examine the conditions that affect the recovery of weak factor loadings when the model includes the mean structure, compared to analyzing the covariance structure alone. A simulation study was conducted in which several constraints were defined for one-, two-, and three-factor models. Results show that adding the mean structure improves the recovery of weak factor loadings and reduces the asymptotic variances for the factor loadings, particularly for the models with a smaller number of factors and a small sample size. Therefore, under certain circumstances, modeling the means should be seriously considered for covariance models containing weak factor loadings. PMID:26779071

FACTORS AFFECTING INFECTION OR REINFECTION WITH SCHISTOSOMA HAEMATOBIUM IN COASTAL KENYA: SURVIVAL ANALYSIS DURING A NINE-YEAR, SCHOOL-BASED TREATMENT PROGRAM

PubMed Central

SATAYATHUM, SUDTIDA A.; MUCHIRI, ERIC M.; OUMA, JOHN H.; WHALEN, CHRISTOPHER C.; KING, CHARLES H.

2010-01-01

Urinary schistosomiasis remains a significant burden for Africa and the Middle East. Success of regional control strategies will depend, in part, on what influence local environmental and behavioral factors have on individual risk for primary infection and/or reinfection. Based on experience in a multi-year (1984–1992), school-based Schistosoma haematobium control program in Coast Province, Kenya, we examined risk for infection outcomes as a function of age, sex, pretreatment morbidity, treatment regimen, water contact, and residence location, with the use of life tables and Cox proportional-hazards analysis. After adjustment, location of residence, age less than 12 years, pretreatment hematuria, and incomplete treatment were the significant independent predictors of infection, whereas sex and frequency of water contact were not. We conclude that local physical features and age-related factors play a predominant role in S. haematobium transmission in this setting. In large population-based control programs, treatment allocation strategies may need to be tailored to local conditions on a village-by-village basis. PMID:16837713

A Comparison of Imputation Methods for Bayesian Factor Analysis Models

ERIC Educational Resources Information Center

Merkle, Edgar C.

2011-01-01

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

A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

NASA Astrophysics Data System (ADS)

Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.

2018-02-01

Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.

Socio-economic factors of bacillary dysentery based on spatial correlation analysis in Guangxi Province, China.

PubMed

Nie, Chengjing; Li, Hairong; Yang, Linsheng; Zhong, Gemei; Zhang, Lan

2014-01-01

In the past decade, bacillary dysentery was still a big public health problem in China, especially in Guangxi Province, where thousands of severe diarrhea cases occur every year. Reported bacillary dysentery cases in Guangxi Province were obtained from local Centers for Diseases Prevention and Control. The 14 socio-economic indexes were selected as potential explanatory variables for the study. The spatial correlation analysis was used to explore the associations between the selected factors and bacillary dysentery incidence at county level, which was based on the software of ArcGIS10.2 and GeoDA 0.9.5i. The proportion of primary industry, the proportion of younger than 5-year-old children in total population, the number of hospitals per thousand persons and the rates of bacillary dysentery incidence show statistically significant positive correlation. But the proportion of secondary industry, per capital GDP, per capital government revenue, rural population proportion, popularization rate of tap water in rural area, access rate to the sanitation toilets in rural, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons and the rate of bacillary dysentery incidence show statistically significant negative correlation. The socio-economic factors can be divided into four aspects, including economic development, health development, medical development and human own condition. The four aspects were not isolated from each other, but interacted with each other.

Factor analysis of the contextual fine motor questionnaire in children.

PubMed

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

2014-02-01

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

Network based transcription factor analysis of regenerating axolotl limbs

PubMed Central

2011-01-01

Background Studies on amphibian limb regeneration began in the early 1700's but we still do not completely understand the cellular and molecular events of this unique process. Understanding a complex biological process such as limb regeneration is more complicated than the knowledge of the individual genes or proteins involved. Here we followed a systems biology approach in an effort to construct the networks and pathways of protein interactions involved in formation of the accumulation blastema in regenerating axolotl limbs. Results We used the human orthologs of proteins previously identified by our research team as bait to identify the transcription factor (TF) pathways and networks that regulate blastema formation in amputated axolotl limbs. The five most connected factors, c-Myc, SP1, HNF4A, ESR1 and p53 regulate ~50% of the proteins in our data. Among these, c-Myc and SP1 regulate 36.2% of the proteins. c-Myc was the most highly connected TF (71 targets). Network analysis showed that TGF-β1 and fibronectin (FN) lead to the activation of these TFs. We found that other TFs known to be involved in epigenetic reprogramming, such as Klf4, Oct4, and Lin28 are also connected to c-Myc and SP1. Conclusions Our study provides a systems biology approach to how different molecular entities inter-connect with each other during the formation of an accumulation blastema in regenerating axolotl limbs. This approach provides an in silico methodology to identify proteins that are not detected by experimental methods such as proteomics but are potentially important to blastema formation. We found that the TFs, c-Myc and SP1 and their target genes could potentially play a central role in limb regeneration. Systems biology has the potential to map out numerous other pathways that are crucial to blastema formation in regeneration-competent limbs, to compare these to the pathways that characterize regeneration-deficient limbs and finally, to identify stem cell markers in

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

PubMed

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

2016-04-01

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

A single factor underlies the metabolic syndrome: a confirmatory factor analysis.

PubMed

Pladevall, Manel; Singal, Bonita; Williams, L Keoki; Brotons, Carlos; Guyer, Heidi; Sadurni, Josep; Falces, Carles; Serrano-Rios, Manuel; Gabriel, Rafael; Shaw, Jonathan E; Zimmet, Paul Z; Haffner, Steven

2006-01-01

Confirmatory factor analysis (CFA) was used to test the hypothesis that the components of the metabolic syndrome are manifestations of a single common factor. Three different datasets were used to test and validate the model. The Spanish and Mauritian studies included 207 men and 203 women and 1,411 men and 1,650 women, respectively. A third analytical dataset including 847 men was obtained from a previously published CFA of a U.S. population. The one-factor model included the metabolic syndrome core components (central obesity, insulin resistance, blood pressure, and lipid measurements). We also tested an expanded one-factor model that included uric acid and leptin levels. Finally, we used CFA to compare the goodness of fit of one-factor models with the fit of two previously published four-factor models. The simplest one-factor model showed the best goodness-of-fit indexes (comparative fit index 1, root mean-square error of approximation 0.00). Comparisons of one-factor with four-factor models in the three datasets favored the one-factor model structure. The selection of variables to represent the different metabolic syndrome components and model specification explained why previous exploratory and confirmatory factor analysis, respectively, failed to identify a single factor for the metabolic syndrome. These analyses support the current clinical definition of the metabolic syndrome, as well as the existence of a single factor that links all of the core components.

Risk analysis of the thermal sterilization process. Analysis of factors affecting the thermal resistance of microorganisms.

PubMed

Akterian, S G; Fernandez, P S; Hendrickx, M E; Tobback, P P; Periago, P M; Martinez, A

1999-03-01

A risk analysis was applied to experimental heat resistance data. This analysis is an approach for processing experimental thermobacteriological data in order to study the variability of D and z values of target microorganisms depending on the deviations range of environmental factors, to determine the critical factors and to specify their critical tolerance. This analysis is based on sets of sensitivity functions applied to a specific case of experimental data related to the thermoresistance of Clostridium sporogenes and Bacillus stearothermophilus spores. The effect of the following factors was analyzed: the type of target microorganism; nature of the heating substrate; pH, temperature; type of acid employed and NaCl concentration. The type of target microorganism to be inactivated, the nature of the substrate (reference or real food) and the heating temperature were identified as critical factors, determining about 90% of the alteration of the microbiological risk. The effect of the type of acid used for the acidification of products and the concentration of NaCl can be assumed to be negligible factors for the purposes of engineering calculations. The critical non-uniformity in temperature during thermobacteriological studies was set as 0.5% and the critical tolerances of pH value and NaCl concentration were 5%. These results are related to a specific case study, for that reason their direct generalization is not correct.

Anthropometric data reduction using confirmatory factor analysis.

PubMed

Rohani, Jafri Mohd; Olusegun, Akanbi Gabriel; Rani, Mat Rebi Abdul

2014-01-01

The unavailability of anthropometric data especially in developing countries has remained a limiting factor towards the design of learning facilities with sufficient ergonomic consideration. Attempts to use anthropometric data from developed countries have led to provision of school facilities unfit for the users. The purpose of this paper is to use factor analysis to investigate the suitability of the collected anthropometric data as a database for school design in Nigerian tertiary institutions. Anthropometric data were collected from 288 male students in a Federal Polytechnic in North-West of Nigeria. Their age is between 18-25 years. Nine vertical anthropometric dimensions related to heights were collected using the conventional traditional equipment. Exploratory factor analysis was used to categorize the variables into a model consisting of two factors. Thereafter, confirmatory factor analysis was used to investigate the fit of the data to the proposed model. A just identified model, made of two factors, each with three variables was developed. The variables within the model accounted for 81% of the total variation of the entire data. The model was found to demonstrate adequate validity and reliability. Various measuring indices were used to verify that the model fits the data properly. The final model reveals that stature height and eye height sitting were the most stable variables for designs that have to do with standing and sitting construct. The study has shown the application of factor analysis in anthropometric data analysis. The study highlighted the relevance of these statistical tools to investigate variability among anthropometric data involving diverse population, which has not been widely used for analyzing previous anthropometric data. The collected data is therefore suitable for use while designing for Nigerian students.

Community Violence, Protective Factors, and Adolescent Mental Health: A Profile Analysis

ERIC Educational Resources Information Center

Copeland-Linder, Nikeea; Lambert, Sharon F.; Ialongo, Nicholas S.

2010-01-01

This study examined interrelationships among community violence exposure, protective factors, and mental health in a sample of urban, predominantly African American adolescents (N = 504). Latent Profile Analysis was conducted to identify profiles of adolescents based on a combination of community violence exposure, self-worth, parental monitoring,…

Perception on obesity among university students: A case study using factor analysis

NASA Astrophysics Data System (ADS)

Hassan, Suriani; Rahman, Nur Amira Abdol; Ghazali, Khadizah; Ismail, Norlita; Budin, Kamsia

2014-07-01

The purpose of this study was to examine the university students' perceptions on obesity and to compare the difference in mean scores factor based on demographic factors. Data was collected randomly using questionnaires. There were 321 university students participated in this study. Descriptive statistics, factor analysis, normality test, independent t test, one-way ANOVA and non-parametric tests were used in this study. Factor analysis results managed to retrieve three new factors namely impact of the health, impact of the physical appearance and personal factors. The study found that Science students have higher awareness and perceptions than Art students on Factor 1, impact of the health towards overweight problems and obesity. The findings of the study showed students, whose family background has obesity problem have higher awareness and perceptions than students' whose family background has no obesity problem on Factor 1, impact of the health towards overweight problems and obesity. The study also found that students' whose father with primary school level had the lowest awareness and perceptions on Factor 2, impact of the physical appearance towards overweight problems and obesity than other students whose father with higher academic level.

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

PubMed

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.

Comparisons of Exploratory and Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Daniel, Larry G.

Historically, most researchers conducting factor analysis have used exploratory methods. However, more recently, confirmatory factor analytic methods have been developed that can directly test theory either during factor rotation using "best fit" rotation methods or during factor extraction, as with the LISREL computer programs developed…

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

PubMed

Song, Malin; Chen, Yu; An, Qingxian

2018-05-01

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

Socio-Economic Factors of Bacillary Dysentery Based on Spatial Correlation Analysis in Guangxi Province, China

PubMed Central

Nie, Chengjing; Li, Hairong; Yang, Linsheng; Zhong, Gemei; Zhang, Lan

2014-01-01

Background In the past decade, bacillary dysentery was still a big public health problem in China, especially in Guangxi Province, where thousands of severe diarrhea cases occur every year. Methods Reported bacillary dysentery cases in Guangxi Province were obtained from local Centers for Diseases Prevention and Control. The 14 socio-economic indexes were selected as potential explanatory variables for the study. The spatial correlation analysis was used to explore the associations between the selected factors and bacillary dysentery incidence at county level, which was based on the software of ArcGIS10.2 and GeoDA 0.9.5i. Results The proportion of primary industry, the proportion of younger than 5-year-old children in total population, the number of hospitals per thousand persons and the rates of bacillary dysentery incidence show statistically significant positive correlation. But the proportion of secondary industry, per capital GDP, per capital government revenue, rural population proportion, popularization rate of tap water in rural area, access rate to the sanitation toilets in rural, number of beds in hospitals per thousand persons, medical and technical personnel per thousand persons and the rate of bacillary dysentery incidence show statistically significant negative correlation. The socio-economic factors can be divided into four aspects, including economic development, health development, medical development and human own condition. The four aspects were not isolated from each other, but interacted with each other. PMID:25036182

Modified friction factor correlation for CICC's based on a porous media analogy

NASA Astrophysics Data System (ADS)

Lewandowska, Monika; Bagnasco, Maurizio

2011-09-01

A modified correlation for the bundle friction factor in CICC's based on a porous media analogy is presented. The correlation is obtained by the analysis of the collected pressure drop data measured for 23 CICC's. The friction factors predicted by the proposed correlation are compared with those resulting from the pressure drop data for two CICC's measured recently using cryogenic helium in the SULTAN test facility at EPFL-CRPP.

SCOR based key success factors in cooking oil supply chain buyers perspective in Padang City

NASA Astrophysics Data System (ADS)

Zahara, Fatimah; Hadiguna, Rika Ampuh

2017-11-01

Supply chain of cooking oil is a network of companies from palm oil as raw material to retailers which work to create the value and deliver products into the end consumers. This paper is aimed to study key success factors based on consumer's perspective as the last stage in the supply chain. Consumers who are examined in this study are restaurants management or owners. Restaurant is the biggest consumption of cooking oil. The factors is studied based on Supply Chain Operation Reference (SCOR) version 10.0. Factors used are formulated based on the third-level metrics of SCOR Model. Factors are analyzed using factors analysis. This study found factors which become key success factors in managing supply chain of cooking oil encompass reliability, responsiveness and agility. Key success factors can be applied by governments as policy making and cooking oil companies as formulation of the distribution strategies.

[Cultural regionalization for Notopterygium incisum based on 3S technology platform. I. Evaluation for growth suitability for N. incisum based on ecological factors analysis by Maxent and ArcGIS model].

PubMed

Sun, Hong-bing; Sun, Hui; Jiang, Shun-yuan; Zhou, Yi; Cao, Wen-long; Ji, Ming-chang; Zhy, Wen-tao; Yan, Han-jing

2015-03-01

Growth suitability as assessment indicators for medicinal plants cultivation was proposed based on chemical quality determination and ecological factors analysis by Maxent and ArcGIS model. Notopterygium incisum, an endangered Chinese medicinal plant, was analyzed as a case, its potential distribution areas at different suitability grade and regionalization map were formulated based on growth suitability theory. The results showed that the most suitable habitats is Sichuan province, and more than 60% of the most suitable areawas located in the western Sichuan such as Aba and Ganzi prefectures for N. incisum. The results indicated that habitat altitude, average air temperature in September, and vegetation types were the dominant factors contributing to the grade of plant growth, precipitation and slope were the major factors contributing to notopterol accumulation in its underground parts, while isoimperatorin in its underground parts was negatively corelated with precipitation and slope of its habitat. However, slope as a factor influencing chemical components seemed to be a pseudo corelationship. Therefore, there were distinguishing differences between growth suitability and quality suitability for medicinal plants, which was helpful to further research and practice of cultivation regionalization, wild resource monitoring and large-scale cultivation of traditional Chinese medicine plants.

Diagnostic throughput factor analysis for en-route airspace and optimal aircraft trajectory generation based on capacity prediction and controller workload

NASA Astrophysics Data System (ADS)

Shin, Sanghyun

Today's National Airspace System (NAS) is approaching its limit to efficiently cope with the increasing air traffic demand. Next Generation Air Transportation System (NextGen) with its ambitious goals aims to make the air travel more predictable with fewer delays, less time sitting on the ground and holding in the air to improve the performance of the NAS. However, currently the performance of the NAS is mostly measured using delay-based metrics which do not capture a whole range of important factors that determine the quality and level of utilization of the NAS. The factors affecting the performance of the NAS are themselves not well defined to begin with. To address these issues, motivated by the use of throughput-based metrics in many areas such as ground transportation, wireless communication and manufacturing, this thesis identifies the different factors which majorly affect the performance of the NAS as demand (split into flight cancellation and flight rerouting), safe separation (split into conflict and metering) and weather (studied as convective weather) through careful comparison with other applications and performing empirical sensitivity analysis. Additionally, the effects of different factors on the NAS's performance are quantitatively studied using real traffic data with the Future ATM Concepts Evaluation Tool (FACET) for various sectors and centers of the NAS on different days. In this thesis we propose a diagnostic tool which can analyze the factors that have greater responsibility for regions of poor and better performances of the NAS. Based on the throughput factor analysis for en-route airspace, it was found that weather and controller workload are the major factors that decrease the efficiency of the airspace. Also, since resources such as air traffic controllers, infrastructure and airspace are limited, it is becoming increasingly important to use the available resources efficiently. To alleviate the impact of the weather and controller

Bootstrap Standard Error Estimates in Dynamic Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Browne, Michael W.

2010-01-01

Dynamic factor analysis summarizes changes in scores on a battery of manifest variables over repeated measurements in terms of a time series in a substantially smaller number of latent factors. Algebraic formulae for standard errors of parameter estimates are more difficult to obtain than in the usual intersubject factor analysis because of the…

Factor Analysis of the Modified Sexual Adjustment Questionnaire-Male

PubMed Central

Wilmoth, Margaret C.; Hanlon, Alexandra L.; Ng, Lit Soo; Bruner, Debra W.

2015-01-01

Background and Purpose The Sexual Adjustment Questionnaire (SAQ) is used in National Cancer Institute–sponsored clinical trials as an outcome measure for sexual functioning. The tool was revised to meet the needs for a clinically useful, theory-based outcome measure for use in both research and clinical settings. This report describes the modifications and validity testing of the modified Sexual Adjustment Questionnaire-Male (mSAQ-Male). Methods This secondary analysis of data from a large Radiation Therapy Oncology Group trial employed principal axis factor analytic techniques in estimating validity of the revised tool. The sample size was 686; most subjects were White, older than the age 60 years, and with a high school education and a Karnofsky performance scale (KPS) score of greater than 90. Results A 16-item, 3-factor solution resulted from the factor analysis. The mSAQ-Male was also found to be sensitive to changes in physical sexual functioning as measured by the KPS. Conclusion The mSAQ-Male is a valid self-report measure of sexuality that can be used clinically to detect changes in male sexual functioning. PMID:25255676

How Factor Analysis Can Be Used in Classification.

ERIC Educational Resources Information Center

Harman, Harry H.

This is a methodological study that suggests a taxometric technique for objective classification of yeasts. It makes use of the minres method of factor analysis and groups strains of yeast according to their factor profiles. The similarities are judged in the higher-dimensional space determined by the factor analysis, but otherwise rely on the…

Beam propagation factor based on the Rényi entropy.

PubMed

Vaveliuk, Pablo; da Silva, Marcone Lopes

2008-09-15

A beam width measure based on Rényi entropy was introduced by Luis [Opt. Lett 31, 3644 (2006)]. That one-dimensional analysis was limited to beam profiles with rectangular symmetry. In this Letter, we derive a general Rényi beam width measure that accounts for the diffraction properties of beams with profiles of arbitrary symmetry. We also show that the square of this measure has a quadratic dependence as a function of the propagation coordinate, so that it can be applied to propagation through arbitrary ABCD paraxial systems. The Rényi beam propagation factor, here introduced, is discussed in examples where the M(2) factor seems to have a limited effectiveness in describing the beam spreading.

Centre of pressure patterns in the golf swing: individual-based analysis.

PubMed

Ball, Kevin; Best, Russell

2012-06-01

Weight transfer has been identified as important in group-based analyses. The aim of this study was to extend this work by examining the importance of weight transfer in the golf swing on an individual basis. Five professional and amateur golfers performed 50 swings with the driver, hitting a ball into a net. The golfer's centre of pressure position and velocity, parallel with the line of shot, were measured by two force plates at eight swing events that were identified from high-speed video. The relationships between these parameters and club head velocity at ball contact were examined using regression statistics. The results did support the use of group-based analysis, with all golfers returning significant relationships. However, results were also individual-specific, with golfers returning different combinations of significant factors. Furthermore, factors not identified in group-based analysis were significant on an individual basis. The most consistent relationship was a larger weight transfer range associated with a larger club head velocity (p < 0.05). All golfers also returned at least one significant relationship with rate of weight transfer at swing events (p < 0.01). Individual-based analysis should form part of performance-based biomechanical analysis of sporting skills.

Factors affecting reproducibility between genome-scale siRNA-based screens

PubMed Central

Barrows, Nicholas J.; Le Sommer, Caroline; Garcia-Blanco, Mariano A.; Pearson, James L.

2011-01-01

RNA interference-based screening is a powerful new genomic technology which addresses gene function en masse. To evaluate factors influencing hit list composition and reproducibility, we performed two identically designed small interfering RNA (siRNA)-based, whole genome screens for host factors supporting yellow fever virus infection. These screens represent two separate experiments completed five months apart and allow the direct assessment of the reproducibility of a given siRNA technology when performed in the same environment. Candidate hit lists generated by sum rank, median absolute deviation, z-score, and strictly standardized mean difference were compared within and between whole genome screens. Application of these analysis methodologies within a single screening dataset using a fixed threshold equivalent to a p-value ≤ 0.001 resulted in hit lists ranging from 82 to 1,140 members and highlighted the tremendous impact analysis methodology has on hit list composition. Intra- and inter-screen reproducibility was significantly influenced by the analysis methodology and ranged from 32% to 99%. This study also highlighted the power of testing at least two independent siRNAs for each gene product in primary screens. To facilitate validation we conclude by suggesting methods to reduce false discovery at the primary screening stage. In this study we present the first comprehensive comparison of multiple analysis strategies, and demonstrate the impact of the analysis methodology on the composition of the “hit list”. Therefore, we propose that the entire dataset derived from functional genome-scale screens, especially if publicly funded, should be made available as is done with data derived from gene expression and genome-wide association studies. PMID:20625183

Train integrity detection risk analysis based on PRISM

NASA Astrophysics Data System (ADS)

Wen, Yuan

2018-04-01

GNSS based Train Integrity Monitoring System (TIMS) is an effective and low-cost detection scheme for train integrity detection. However, as an external auxiliary system of CTCS, GNSS may be influenced by external environments, such as uncertainty of wireless communication channels, which may lead to the failure of communication and positioning. In order to guarantee the reliability and safety of train operation, a risk analysis method of train integrity detection based on PRISM is proposed in this article. First, we analyze the risk factors (in GNSS communication process and the on-board communication process) and model them. Then, we evaluate the performance of the model in PRISM based on the field data. Finally, we discuss how these risk factors influence the train integrity detection process.

A Review of CEFA Software: Comprehensive Exploratory Factor Analysis Program

ERIC Educational Resources Information Center

Lee, Soon-Mook

2010-01-01

CEFA 3.02(Browne, Cudeck, Tateneni, & Mels, 2008) is a factor analysis computer program designed to perform exploratory factor analysis. It provides the main properties that are needed for exploratory factor analysis, namely a variety of factoring methods employing eight different discrepancy functions to be minimized to yield initial…

The effects of common risk factors on stock returns: A detrended cross-correlation analysis

NASA Astrophysics Data System (ADS)

Ruan, Qingsong; Yang, Bingchan

2017-10-01

In this paper, we investigate the cross-correlations between Fama and French three factors and the return of American industries on the basis of cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). Qualitatively, we find that the return series of Fama and French three factors and American industries were overall significantly cross-correlated based on the analysis of a statistic. Quantitatively, we find that the cross-correlations between three factors and the return of American industries were strongly multifractal, and applying MF-DCCA we also investigate the cross-correlation of industry returns and residuals. We find that there exists multifractality of industry returns and residuals. The result of correlation coefficients we can verify that there exist other factors which influence the industry returns except Fama three factors.

Structural Analysis of Correlated Factors: Lessons from the Verbal-Performance Dichotomy of the Wechsler Scales.

ERIC Educational Resources Information Center

Macmann, Gregg M.; Barnett, David W.

1994-01-01

Describes exploratory and confirmatory analyses of verbal-performance procedures to illustrate concepts and procedures for analysis of correlated factors. Argues that, based on convergent and discriminant validity criteria, factors should have higher correlations with variables that they purport to measure than with other variables. Discusses…

Entrance and exit region friction factor models for annular seal analysis. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Elrod, David Alan

1988-01-01

The Mach number definition and boundary conditions in Nelson's nominally-centered, annular gas seal analysis are revised. A method is described for determining the wall shear stress characteristics of an annular gas seal experimentally. Two friction factor models are developed for annular seal analysis; one model is based on flat-plate flow theory; the other uses empirical entrance and exit region friction factors. The friction factor predictions of the models are compared to experimental results. Each friction model is used in an annular gas seal analysis. The seal characteristics predicted by the two seal analyses are compared to experimental results and to the predictions of Nelson's analysis. The comparisons are for smooth-rotor seals with smooth and honeycomb stators. The comparisons show that the analysis which uses empirical entrance and exit region shear stress models predicts the static and stability characteristics of annular gas seals better than the other analyses. The analyses predict direct stiffness poorly.

A Bibliometric Analysis of U.S.-Based Research on the Behavioral Risk Factor Surveillance System

PubMed Central

Khalil, George M.; Gotway Crawford, Carol A.

2017-01-01

Background Since Alan Pritchard defined bibliometrics as “the application of statistical methods to media of communication” in 1969, bibliometric analyses have become widespread. To date, however, bibliometrics has not been used to analyze publications related to the U.S. Behavioral Risk Factor Surveillance System (BRFSS). Purpose To determine the most frequently cited BRFSS-related topical areas, institutions, and journals. Methods A search of the Web of Knowledge database in 2013 identified U.S.-published studies related to BRFSS, from its start in 1984 through 2012. Search terms were BRFSS, Behavioral Risk Factor Surveillance System, or Behavioral Risk Survey. The resulting 1,387 articles were analyzed descriptively and produced data for VOSviewer, a computer program that plotted a relevance distance–based map and clustered keywords from text in titles and abstracts. Results Topics, journals, and publishing institutions ranged widely. Most research was clustered by content area, such as cancer screening, access to care, heart health, and quality of life. The American Journal of Preventive Medicine and American Journal of Public Health published the most BRFSS-related papers (95 and 70, respectively). Conclusions Bibliometrics can help identify the most frequently published BRFSS-related topics, publishing journals, and publishing institutions. BRFSS data are widely used, particularly by CDC and academic institutions such as the University of Washington and other universities hosting top-ranked schools of public health. Bibliometric analysis and mapping provides an innovative way of quantifying and visualizing the plethora of research conducted using BRFSS data and summarizing the contribution of this surveillance system to public health. PMID:25442231

Analysis on factors affecting consumers decision on purchasing simple-type houses

NASA Astrophysics Data System (ADS)

Rumintang, A.; Sholichin, I.

2018-01-01

In line with the increase of the population and the need of comfortable houses, as affected by modernization era, the house demand is getting higher. Hence, conducting a research on consumers need and want in buying a house should be seriously attempted to succeed marketing activity. Using an analysis consumers’ behavior, the researcher will know few affecting factors related to consumers’ satisfaction in buying a house. Among other, the factors in question include: house price, house condition, facilities, location and accessability. The sample of this research was drawn from the residents of Graha Asri Housing, Taman Bulang Permai, and Sukodono Permai. Based on the analysis and discussion, some conclusions are made as follow: the factors and variables affecting the consumers’ decision on each choice of house is different and also the same variables on three sources of data include housing atmosphere, cleaning service, ease of access to shopping center, health clinics or hospitals, tourism spot, schools, and the bus station.

Key factors regulating protein carbonylation by α,β unsaturated carbonyls: A structural study based on a retrospective meta-analysis.

PubMed

Vistoli, Giulio; Mantovani, Chiara; Gervasoni, Silvia; Pedretti, Alessandro; Aldini, Giancarlo

2017-11-01

Protein carbonylation represents one of the most important oxidative-based modifications involving nucleophilic amino acids and affecting protein folding and function. Protein carbonylation is induced by electrophilic carbonyl species and is an highly selective process since few nucleophilic residues are carbonylated within each protein. While considering the great interest for protein carbonylation, few studies investigated the factors which render a nucleophilic residue susceptible to carbonylation. Hence, the present study is aimed to delve into the factors which modulate the reactivity of cysteine, histidine and lysine residues towards α,β unsaturated carbonyls by a retrospective analysis of the available studies which identified the adducted residues for proteins, the structure of which was resolved. Such an analysis involved different parameters including exposure, nucleophilicity, surrounding residues and capacity to attract carbonyl species (as derived by docking simulations). The obtained results allowed a meaningful clustering of the analyzed proteins suggesting that on average carbonylation selectivity increases with protein size. The comparison between adducted and unreactive residues revealed differences in all monitored parameters which are markedly more pronounced for cysteines compared to lysines and histidines. Overall, these results suggest that cysteine's carbonylation is a finely (and reasonably purposely) modulated process, while the carbonylation of lysines and histidines seems to be a fairly random event in which limited differences influence their reactivity. Copyright © 2017 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

An Analysis of Losses to the Southern Commercial Timberland Base

Treesearch

Ian A. Munn; David Cleaves

1998-01-01

Demographic and physical factors influencing the conversion of commercial timberland iu the south to non-forestry uses between the last two Forest Inventory Analysis (FIA) surveys were investigated. GIS techniques linked Census data and FIA plot level data. Multinomial logit regression identified factors associated with losses to the timberland base. Conversion to...

A Fatigue Life Prediction Method Based on Strain Intensity Factor

PubMed Central

Zhang, Wei; Liu, Huili; Wang, Qiang; He, Jingjing

2017-01-01

In this paper, a strain-intensity-factor-based method is proposed to calculate the fatigue crack growth under the fully reversed loading condition. A theoretical analysis is conducted in detail to demonstrate that the strain intensity factor is likely to be a better driving parameter correlated with the fatigue crack growth rate than the stress intensity factor (SIF), especially for some metallic materials (such as 316 austenitic stainless steel) in the low cycle fatigue region with negative stress ratios R (typically R = −1). For fully reversed cyclic loading, the constitutive relation between stress and strain should follow the cyclic stress-strain curve rather than the monotonic one (it is a nonlinear function even within the elastic region). Based on that, a transformation algorithm between the SIF and the strain intensity factor is developed, and the fatigue crack growth rate testing data of 316 austenitic stainless steel and AZ31 magnesium alloy are employed to validate the proposed model. It is clearly observed that the scatter band width of crack growth rate vs. strain intensity factor is narrower than that vs. the SIF for different load ranges (which indicates that the strain intensity factor is a better parameter than the stress intensity factor under the fully reversed load condition). It is also shown that the crack growth rate is not uniquely determined by the SIF range even under the same R, but is also influenced by the maximum loading. Additionally, the fatigue life data (strain-life curve) of smooth cylindrical specimens are also used for further comparison, where a modified Paris equation and the equivalent initial flaw size (EIFS) are involved. The results of the proposed method have a better agreement with the experimental data compared to the stress intensity factor based method. Overall, the strain intensity factor method shows a fairly good ability in calculating the fatigue crack propagation, especially for the fully reversed cyclic

A multifactorial analysis of obesity as CVD risk factor: use of neural network based methods in a nutrigenetics context.

PubMed

Valavanis, Ioannis K; Mougiakakou, Stavroula G; Grimaldi, Keith A; Nikita, Konstantina S

2010-09-08

Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm. PDM-ANN and GA-ANN were comparatively assessed in terms of their ability to identify the most important factors among the initial 63 variables describing genetic variations, nutrition and gender, able to classify a subject into one of the BMI related classes: normal and overweight. The methods were designed and evaluated using appropriate training and testing sets provided by 3-fold Cross Validation (3-CV) resampling. Classification accuracy, sensitivity, specificity and area under receiver operating characteristics curve were utilized to evaluate the resulted predictive ANN models. The most parsimonious set of factors was obtained by the GA-ANN method and included gender, six genetic variations and 18 nutrition-related variables. The corresponding predictive model was characterized by a mean accuracy equal of 61.46% in the 3-CV testing sets. The ANN based methods revealed factors

A multifactorial analysis of obesity as CVD risk factor: Use of neural network based methods in a nutrigenetics context

PubMed Central

2010-01-01

Background Obesity is a multifactorial trait, which comprises an independent risk factor for cardiovascular disease (CVD). The aim of the current work is to study the complex etiology beneath obesity and identify genetic variations and/or factors related to nutrition that contribute to its variability. To this end, a set of more than 2300 white subjects who participated in a nutrigenetics study was used. For each subject a total of 63 factors describing genetic variants related to CVD (24 in total), gender, and nutrition (38 in total), e.g. average daily intake in calories and cholesterol, were measured. Each subject was categorized according to body mass index (BMI) as normal (BMI ≤ 25) or overweight (BMI > 25). Two artificial neural network (ANN) based methods were designed and used towards the analysis of the available data. These corresponded to i) a multi-layer feed-forward ANN combined with a parameter decreasing method (PDM-ANN), and ii) a multi-layer feed-forward ANN trained by a hybrid method (GA-ANN) which combines genetic algorithms and the popular back-propagation training algorithm. Results PDM-ANN and GA-ANN were comparatively assessed in terms of their ability to identify the most important factors among the initial 63 variables describing genetic variations, nutrition and gender, able to classify a subject into one of the BMI related classes: normal and overweight. The methods were designed and evaluated using appropriate training and testing sets provided by 3-fold Cross Validation (3-CV) resampling. Classification accuracy, sensitivity, specificity and area under receiver operating characteristics curve were utilized to evaluate the resulted predictive ANN models. The most parsimonious set of factors was obtained by the GA-ANN method and included gender, six genetic variations and 18 nutrition-related variables. The corresponding predictive model was characterized by a mean accuracy equal of 61.46% in the 3-CV testing sets. Conclusions The ANN

Setting Standards for Medically-Based Running Analysis

PubMed Central

Vincent, Heather K.; Herman, Daniel C.; Lear-Barnes, Leslie; Barnes, Robert; Chen, Cong; Greenberg, Scott; Vincent, Kevin R.

2015-01-01

Setting standards for medically based running analyses is necessary to ensure that runners receive a high-quality service from practitioners. Medical and training history, physical and functional tests, and motion analysis of running at self-selected and faster speeds are key features of a comprehensive analysis. Self-reported history and movement symmetry are critical factors that require follow-up therapy or long-term management. Pain or injury is typically the result of a functional deficit above or below the site along the kinematic chain. PMID:25014394

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

NASA Astrophysics Data System (ADS)

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

Study of risk factors for gastric cancer by populational databases analysis

PubMed Central

Ferrari, Fangio; Reis, Marco Antonio Moura

2013-01-01

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

Understanding the Support Needs of People with Intellectual and Related Developmental Disabilities through Cluster Analysis and Factor Analysis of Statewide Data

ERIC Educational Resources Information Center

Viriyangkura, Yuwadee

2014-01-01

Through a secondary analysis of statewide data from Colorado, people with intellectual and related developmental disabilities (ID/DD) were classified into five clusters based on their support needs characteristics using cluster analysis techniques. Prior latent factor models of support needs in the field of ID/DD were examined to investigate the…

A comparison study on detection of key geochemical variables and factors through three different types of factor analysis

NASA Astrophysics Data System (ADS)

Hoseinzade, Zohre; Mokhtari, Ahmad Reza

2017-10-01

Large numbers of variables have been measured to explain different phenomena. Factor analysis has widely been used in order to reduce the dimension of datasets. Additionally, the technique has been employed to highlight underlying factors hidden in a complex system. As geochemical studies benefit from multivariate assays, application of this method is widespread in geochemistry. However, the conventional protocols in implementing factor analysis have some drawbacks in spite of their advantages. In the present study, a geochemical dataset including 804 soil samples collected from a mining area in central Iran in order to search for MVT type Pb-Zn deposits was considered to outline geochemical analysis through various fractal methods. Routine factor analysis, sequential factor analysis, and staged factor analysis were applied to the dataset after opening the data with (additive logratio) alr-transformation to extract mineralization factor in the dataset. A comparison between these methods indicated that sequential factor analysis has more clearly revealed MVT paragenesis elements in surface samples with nearly 50% variation in F1. In addition, staged factor analysis has given acceptable results while it is easy to practice. It could detect mineralization related elements while larger factor loadings are given to these elements resulting in better pronunciation of mineralization.

Job compensable factors and factor weights derived from job analysis data.

PubMed

Chi, Chia-Fen; Chang, Tin-Chang; Hsia, Ping-Ling; Song, Jen-Chieh

2007-06-01

Government data on 1,039 job titles in Taiwan were analyzed to assess possible relationships between job attributes and compensation. For each job title, 79 specific variables in six major classes (required education and experience, aptitude, interest, work temperament, physical demands, task environment) were coded to derive the statistical predictors of wage for managers, professionals, technical, clerical, service, farm, craft, operatives, and other workers. Of the 79 variables, only 23 significantly related to pay rate were subjected to a factor and multiple regression analysis for predicting monthly wages. Given the heterogeneous nature of collected job titles, a 4-factor solution (occupational knowledge and skills, human relations skills, work schedule hardships, physical hardships) explaining 43.8% of the total variance but predicting only 23.7% of the monthly pay rate was derived. On the other hand, multiple regression with 9 job analysis items (required education, professional training, professional certificate, professional experience, coordinating, leadership and directing, demand on hearing, proportion of shift working indoors, outdoors and others, rotating shift) better predicted pay and explained 32.5% of the variance. A direct comparison of factors and subfactors of job evaluation plans indicated mental effort and responsibility (accountability) had not been measured with the current job analysis data. Cross-validation of job evaluation factors and ratings with the wage rates is required to calibrate both.

Factors associated with the implementation of community-based peer-led health promotion programs: A scoping review.

PubMed

Lorthios-Guilledroit, Agathe; Richard, Lucie; Filiatrault, Johanne

2018-06-01

Peer education is growing in popularity as a useful health promotion strategy. However, optimal conditions for implementing peer-led health promotion programs (HPPs) remain unclear. This scoping review aimed to describe factors that can influence implementation of peer-led HPPs targeting adult populations. Five databases were searched using the keywords "health promotion/prevention", "implementation", "peers", and related terms. Studies were included if they reported at least one factor associated with the implementation of community-based peer-led HPPs. Fifty-five studies were selected for the analysis. The method known as "best fit framework synthesis" was used to analyze the factors identified in the selected papers. Many factors included in existing implementation conceptual frameworks were deemed applicable to peer-led HPPs. However, other factors related to individuals, programs, and implementation context also emerged from the analysis. Based on this synthesis, an adapted theoretical framework was elaborated, grounded in a complex adaptive system perspective and specifying potential mechanisms through which factors may influence implementation of community-based peer-led HPPs. Further research is needed to test the theoretical framework against empirical data. Findings from this scoping review increase our knowledge of the optimal conditions for implementing peer-led HPPs and thereby maximizing the benefits of such programs. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Commonality of Risk Factors for Mothers' Poor Oral Health and General Health: Baseline Analysis of a Population-Based Birth Cohort Study.

PubMed

Ha, Diep H; Spencer, A John; Thomson, W Murray; Scott, Jane A; Do, Loc G

2018-04-01

Objective The association between and commonality of risk factors for poor self-rated oral health (SROH) and general health (SRGH) among new mothers has not been reported. The purpose of this paper is to assess the commonality of risk factors for poor SROH and SRGH, and self-reported obesity and dental pain, among a population-based sample of new mothers in Australia. It also investigated health conditions affecting new mothers' general health. Methods Data collected at baseline of a population-based birth cohort was used. Mothers of newborns in Adelaide were approached to participate. Mothers completed a questionnaire collecting data on socioeconomic status (SES), health behaviours, dental pain, SROH, self-reported height and weight and SRGH. Analysis was conducted sequentially from bivariate to multivariable regression to estimate prevalence rate (PR) of reporting poor/fair SROH and SRGH. Results of the 1895 new mothers, some 21 and 6% rated their SROH and SRGH as poor/fair respectively. Dental pain was associated with low income and smoking status, while being obese was associated with low SES, low education and infrequent tooth brushing. SROH and SRGH was associated with low SES, smoking, and dental pain. SROH was also associated with SRGH [PR: 3.06 (2.42-3.88)]. Conclusion for practice There was a commonality of factors associated with self-rated oral health and general health. Strong associations between OH and GH were also observed. Given the importance of maternal health for future generations, there would be long-term societal benefit from addressing common risk factors for OH and GH in integrated programs.

Research on the Multiple Factors Influencing Human Identification Based on Pyroelectric Infrared Sensors

PubMed Central

Lou, Ping; Hu, Jianmin

2018-01-01

Analysis of the multiple factors affecting human identification ability based on pyroelectric infrared technology is a complex problem. First, we examine various sensed pyroelectric waveforms of the human body thermal infrared signal and reveal a mechanism for affecting human identification. Then, we find that the mechanism is decided by the distance, human target, pyroelectric infrared (PIR) sensor, the body type, human moving velocity, signal modulation mask, and Fresnel lens. The mapping relationship between the sensed waveform and multiple influencing factors is established, and a group of mathematical models are deduced which fuse the macro factors and micro factors. Finally, the experimental results show the macro-factors indirectly affect the recognition ability of human based on the pyroelectric technology. At the same time, the correctness and effectiveness of the mathematical models is also verified, which make it easier to obtain more pyroelectric infrared information about the human body for discriminating human targets. PMID:29462908

Delineation of geochemical anomalies based on stream sediment data utilizing fractal modeling and staged factor analysis

NASA Astrophysics Data System (ADS)

Afzal, Peyman; Mirzaei, Misagh; Yousefi, Mahyar; Adib, Ahmad; Khalajmasoumi, Masoumeh; Zarifi, Afshar Zia; Foster, Patrick; Yasrebi, Amir Bijan

2016-07-01

Recognition of significant geochemical signatures and separation of geochemical anomalies from background are critical issues in interpretation of stream sediment data to define exploration targets. In this paper, we used staged factor analysis in conjunction with the concentration-number (C-N) fractal model to generate exploration targets for prospecting Cr and Fe mineralization in Balvard area, SE Iran. The results show coexistence of derived multi-element geochemical signatures of the deposit-type sought and ultramafic-mafic rocks in the NE and northern parts of the study area indicating significant chromite and iron ore prospects. In this regard, application of staged factor analysis and fractal modeling resulted in recognition of significant multi-element signatures that have a high spatial association with host lithological units of the deposit-type sought, and therefore, the generated targets are reliable for further prospecting of the deposit in the study area.

Prognostic factors and genes associated with endometrial cancer based on gene expression profiling by bioinformatics analysis.

PubMed

Zhang, Ying; Zhang, Wei; Li, Xinglan; Li, Dapeng; Zhang, Xiaoling; Yin, Yajie; Deng, Xiangyun; Sheng, Xiugui

2016-06-01

Endometrial cancer (EC) is the most prevalent malignancy worldwide. Although several efforts had been made to explore the molecular mechanism responsible for EC progression, it is still not fully understood. To evaluate the clinical characteristics and prognostic factors of patients with EC, and further to search for novel genes associated with EC progression. We recruited 328 patients with EC and analyzed prognostic factors using Cox proportional hazard regression model. Further, a gene expression profile of EC was used to identify the differentially expressed genes (DEGs) between normal samples and tumor samples. Subsequently, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis ( http://www.genome.jp/kegg/ ) for DEGs were performed, and then protein-protein interaction (PPI) network of DEGs as well as the subnetwork of PPI were constructed with plug-in, MCODE by mapping DEGs into the Search Tool for the Retrieval of Interacting Genes database. Our results showed that body mass index (BMI), hypertension, myometrial invasion, pathological type, and Glut4 positive expression were prognostic factors in EC (P < 0.05). Bioinformatics analysis showed that upregulated DEGs were associated with cell cycle, and downregulated DEGs were related to MAPK pathway. Meanwhile, PPI network analysis revealed that upregulated CDK1 and CCNA2 as well as downregulated JUN and FOS were listed in top two nodes with high degrees. Patients with EC should be given more focused attentions in respect of pathological type, BMI, hypertension, and Glut4-positive expression. In addition, CDK1, CCNA2, JUN, and FOS might play important roles in EC development.

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

NASA Astrophysics Data System (ADS)

Kuo, Yi-Ming; Liu, Wen-Wen

2015-04-01

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

Using BMDP and SPSS for a Q factor analysis.

PubMed

Tanner, B A; Koning, S M

1980-12-01

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

Internal and external environmental factors affecting the performance of hospital-based home nursing care.

PubMed

Noh, J-W; Kwon, Y-D; Yoon, S-J; Hwang, J-I

2011-06-01

Numerous studies on HNC services have been carried out by signifying their needs, efficiency and effectiveness. However, no study has ever been performed to determine the critical factors associated with HNC's positive results despite the deluge of positive studies on the service. This study included all of the 89 training hospitals that were practising HNC service in Korea as of November 2006. The input factors affecting the performance were classified as either internal or external environmental factors. This analysis was conducted to understand the impact that the corresponding factors had on performance. Data were analysed by using multiple linear regressions. The internal and external environment variables affected the performance of HNC based on univariate analysis. The meaningful variables were internal environmental factors. Specifically, managerial resource (the number of operating beds and the outpatient/inpatient ratio) were meaningful when the multiple linear regression analysis was performed. Indeed, the importance of organizational culture (the passion of HNC nurses) was significant. This study, considering the limited market size of Korea, illustrates that the critical factor for the development of hospital-led HNC lies with internal environmental factors rather than external ones. Among the internal environmental factors, the hospitals' managerial resource-related factors (specifically, the passion of nurses) were the most important contributing element. © 2011 The Authors. International Nursing Review © 2011 International Council of Nurses.

Bayesian analysis of factors associated with fibromyalgia syndrome subjects

NASA Astrophysics Data System (ADS)

Jayawardana, Veroni; Mondal, Sumona; Russek, Leslie

2015-01-01

Factors contributing to movement-related fear were assessed by Russek, et al. 2014 for subjects with Fibromyalgia (FM) based on the collected data by a national internet survey of community-based individuals. The study focused on the variables, Activities-Specific Balance Confidence scale (ABC), Primary Care Post-Traumatic Stress Disorder screen (PC-PTSD), Tampa Scale of Kinesiophobia (TSK), a Joint Hypermobility Syndrome screen (JHS), Vertigo Symptom Scale (VSS-SF), Obsessive-Compulsive Personality Disorder (OCPD), Pain, work status and physical activity dependent from the "Revised Fibromyalgia Impact Questionnaire" (FIQR). The study presented in this paper revisits same data with a Bayesian analysis where appropriate priors were introduced for variables selected in the Russek's paper.

A Quantitative Analysis of the Extrinsic and Intrinsic Turnover Factors of Relational Database Support Professionals

ERIC Educational Resources Information Center

Takusi, Gabriel Samuto

2010-01-01

This quantitative analysis explored the intrinsic and extrinsic turnover factors of relational database support specialists. Two hundred and nine relational database support specialists were surveyed for this research. The research was conducted based on Hackman and Oldham's (1980) Job Diagnostic Survey. Regression analysis and a univariate ANOVA…

Comparing the Fit of Item Response Theory and Factor Analysis Models

ERIC Educational Resources Information Center

Maydeu-Olivares, Alberto; Cai, Li; Hernandez, Adolfo

2011-01-01

Linear factor analysis (FA) models can be reliably tested using test statistics based on residual covariances. We show that the same statistics can be used to reliably test the fit of item response theory (IRT) models for ordinal data (under some conditions). Hence, the fit of an FA model and of an IRT model to the same data set can now be…

Factors influencing societal response of nanotechnology: an expert stakeholder analysis

NASA Astrophysics Data System (ADS)

Gupta, Nidhi; Fischer, Arnout R. H.; van der Lans, Ivo A.; Frewer, Lynn J.

2012-05-01

Nanotechnology can be described as an emerging technology and, as has been the case with other emerging technologies such as genetic modification, different socio-psychological factors will potentially influence societal responses to its development and application. These factors will play an important role in how nanotechnology is developed and commercialised. This article aims to identify expert opinion on factors influencing societal response to applications of nanotechnology. Structured interviews with experts on nanotechnology from North West Europe were conducted using repertory grid methodology in conjunction with generalized Procrustes analysis to examine the psychological constructs underlying societal uptake of 15 key applications of nanotechnology drawn from different areas (e.g. medicine, agriculture and environment, chemical, food, military, sports, and cosmetics). Based on expert judgement, the main factors influencing societal response to different applications of nanotechnology will be the extent to which applications are perceived to be beneficial, useful, and necessary, and how 'real' and physically close to the end-user these applications are perceived to be by the public.

What School Psychologists Need to Know about Factor Analysis

ERIC Educational Resources Information Center

McGill, Ryan J.; Dombrowski, Stefan C.

2017-01-01

Factor analysis is a versatile class of psychometric techniques used by researchers to provide insight into the psychological dimensions (factors) that may account for the relationships among variables in a given dataset. The primary goal of a factor analysis is to determine a more parsimonious set of variables (i.e., fewer than the number of…

Item Factor Analysis: Current Approaches and Future Directions

ERIC Educational Resources Information Center

Wirth, R. J.; Edwards, Michael C.

2007-01-01

The rationale underlying factor analysis applies to continuous and categorical variables alike; however, the models and estimation methods for continuous (i.e., interval or ratio scale) data are not appropriate for item-level data that are categorical in nature. The authors provide a targeted review and synthesis of the item factor analysis (IFA)…

Q-Type Factor Analysis of Healthy Aged Men.

ERIC Educational Resources Information Center

Kleban, Morton H.

Q-type factor analysis was used to re-analyze baseline data collected in 1957, on 47 men aged 65-91. Q-type analysis is the use of factor methods to study persons rather than tests. Although 550 variables were originally studied involving psychiatry, medicine, cerebral metabolism and chemistry, personality, audiometry, dichotic and diotic memory,…

Mixture Factor Analysis for Approximating a Nonnormally Distributed Continuous Latent Factor with Continuous and Dichotomous Observed Variables

ERIC Educational Resources Information Center

Wall, Melanie M.; Guo, Jia; Amemiya, Yasuo

2012-01-01

Mixture factor analysis is examined as a means of flexibly estimating nonnormally distributed continuous latent factors in the presence of both continuous and dichotomous observed variables. A simulation study compares mixture factor analysis with normal maximum likelihood (ML) latent factor modeling. Different results emerge for continuous versus…

Factor analysis methods and validity evidence: A systematic review of instrument development across the continuum of medical education

NASA Astrophysics Data System (ADS)

Wetzel, Angela Payne

Previous systematic reviews indicate a lack of reporting of reliability and validity evidence in subsets of the medical education literature. Psychology and general education reviews of factor analysis also indicate gaps between current and best practices; yet, a comprehensive review of exploratory factor analysis in instrument development across the continuum of medical education had not been previously identified. Therefore, the purpose for this study was critical review of instrument development articles employing exploratory factor or principal component analysis published in medical education (2006--2010) to describe and assess the reporting of methods and validity evidence based on the Standards for Educational and Psychological Testing and factor analysis best practices. Data extraction of 64 articles measuring a variety of constructs that have been published throughout the peer-reviewed medical education literature indicate significant errors in the translation of exploratory factor analysis best practices to current practice. Further, techniques for establishing validity evidence tend to derive from a limited scope of methods including reliability statistics to support internal structure and support for test content. Instruments reviewed for this study lacked supporting evidence based on relationships with other variables and response process, and evidence based on consequences of testing was not evident. Findings suggest a need for further professional development within the medical education researcher community related to (1) appropriate factor analysis methodology and reporting and (2) the importance of pursuing multiple sources of reliability and validity evidence to construct a well-supported argument for the inferences made from the instrument. Medical education researchers and educators should be cautious in adopting instruments from the literature and carefully review available evidence. Finally, editors and reviewers are encouraged to recognize

Analysis of Plug-In hybrid Electric Vehicles' utility factors using GPS-based longitudinal travel data

NASA Astrophysics Data System (ADS)

Aviquzzaman, Md

The benefit of using a Plug-in Hybrid Electric Vehicle (PHEV) comes from its ability of substituting gasoline with electricity in operation. Defined as the share of distance traveled in the electric mode, the utility factor (UF) depends mostly on the battery capacity but also on many other factors, such as travel pattern and recharging pattern. Conventionally, the UFs are calculated from the daily vehicle miles traveled (DVMT) of vehicles by assuming motorists leaving home in the morning with full battery and return home in the evening. Such assumption, however, ignores the impact of the heterogeneity in both travel and charging behavior. The main objective of the thesis is to compare the UF by using multiday GPS-based travel data in regards to the charging decision. This thesis employs the global positioning system (GPS) based longitudinal travel data (covering 3-18 months) collected from 403 vehicles in the Seattle metropolitan area to investigate the impacts of such travel and charging behavior on UFs by analyzing the DVMT and home and work related tours. The UFs based on the DVMT are found close to those based on home-to-home tours. On the other hand, it is seen that the workplace charge opportunities largely improve UFs if the battery capacity is no more than 50 miles. It is also found that the gasoline price does not have significant impact on the UFs.

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

PubMed

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

2011-10-01

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

The Construct Validity of Scores on the Ways of Coping Questionnaire: Confirmatory Analysis of Alternative Factor Structures.

ERIC Educational Resources Information Center

Edwards, Jeffrey R.; O'Neill, Regina M.

1998-01-01

Confirmatory factor analysis was used to evaluate alternative factor structures, based on previous exploratory factor analyses and coping dimensions derived from the theory of R. Lazarus, for the Ways of Coping Questionnaire (S. Folkman and R. Lazarus, 1988). Results from responses of 654 college graduates provide little support for the factor…

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

PubMed

Kim, Hee-Ju

2008-03-01

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

Empirical Study on Total Factor Productive Energy Efficiency in Beijing-Tianjin-Hebei Region-Analysis based on Malmquist Index and Window Model

NASA Astrophysics Data System (ADS)

Xu, Qiang; Ding, Shuai; An, Jingwen

2017-12-01

This paper studies the energy efficiency of Beijing-Tianjin-Hebei region and to finds out the trend of energy efficiency in order to improve the economic development quality of Beijing-Tianjin-Hebei region. Based on Malmquist index and window analysis model, this paper estimates the total factor energy efficiency in Beijing-Tianjin-Hebei region empirically by using panel data in this region from 1991 to 2014, and provides the corresponding political recommendations. The empirical result shows that, the total factor energy efficiency in Beijing-Tianjin-Hebei region increased from 1991 to 2014, mainly relies on advances in energy technology or innovation, and obvious regional differences in energy efficiency to exist. Throughout the window period of 24 years, the regional differences of energy efficiency in Beijing-Tianjin-Hebei region shrank. There has been significant convergent trend in energy efficiency after 2000, mainly depends on the diffusion and spillover of energy technologies.

Item Parameter Estimation for the MIRT Model: Bias and Precision of Confirmatory Factor Analysis-Based Models

ERIC Educational Resources Information Center

Finch, Holmes

2010-01-01

The accuracy of item parameter estimates in the multidimensional item response theory (MIRT) model context is one that has not been researched in great detail. This study examines the ability of two confirmatory factor analysis models specifically for dichotomous data to properly estimate item parameters using common formulae for converting factor…

Derived Basic Ability Factors: A Factor Analysis Replication Study.

ERIC Educational Resources Information Center

Lee, Mickey, M.; Lee, Lynda Newby

The purpose of this study was to replicate the study conducted by Potter, Sagraves, and McDonald to determine whether their recommended analysis could separate criterion variables into similar factors that were stable from year to year and from school to school. The replication samples consisted of all students attending Louisiana State University…

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

PubMed

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 (P<0.001). Recurrence was found in 18 cases of the benign group and 39 cases of the malignant group, and results were significantly different (P<0.001). Tumor recurrence was shorter in patients with a higher McCormick grade (P<0.001). Recurrence was found in 13 patients with resection and all the patients with partial resection or biopsy/decompression. The results were significantly different (P<0.001). Logistic regression analysis of total resection-related factors showed that total resection

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

PubMed Central

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

2018-01-01

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 (P<0.001). Recurrence was found in 18 cases of the benign group and 39 cases of the malignant group, and results were significantly different (P<0.001). Tumor recurrence was shorter in patients with a higher McCormick grade (P<0.001). Recurrence was found in 13 patients with resection and all the patients with partial resection or biopsy/decompression. The results were significantly different (P<0.001). Logistic regression analysis of total resection-related factors showed that total resection

Analysis of plug-in hybrid electric vehicles' utility factors using GPS-based longitudinal travel data

DOE PAGES

Wu, Xing; Aviquzzaman, Md.; Lin, Zhenhong

2015-05-29

The benefit of using a PHEV comes from its ability to substitute gasoline with electricity in operation. Defined as the proportion of distance traveled in the electric mode, the utility factor (UF) depends mostly on the battery capacity, but also on many other factors, such as travel pattern and recharging pattern. Conventionally, the UFs are calculated based on the daily vehicle miles traveled (DVMT) by assuming motorists leave home in the morning with a full battery, and no charge occurs before returning home in the evening. Such an assumption, however, ignores the impact of the heterogeneity in both travel andmore » charging behavior, such as going back home more than once in a day, the impact of available charging time, and the price of gasoline. In addition, the conventional UFs are based on the National Household Travel Survey (NHTS) data, which are one-day travel data of each sample vehicle. A motorist's daily distance variation is ignored. This paper employs the GPS-based longitudinal travel data (covering 3-18 months) collected from 403 vehicles in the Seattle metropolitan area to investigate how such travel and charging behavior affects UFs. To do this, for each vehicle, we organized trips to a series of home and work related tours. The UFs based on the DVMT are found close to those based on home-to-home tours. However, it is seen that the workplace charge opportunities significantly increase UFs if the CD range is no more than 40 miles.« less

Analysis of plug-in hybrid electric vehicles' utility factors using GPS-based longitudinal travel data

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

Wu, Xing; Aviquzzaman, Md.; Lin, Zhenhong

The benefit of using a PHEV comes from its ability to substitute gasoline with electricity in operation. Defined as the proportion of distance traveled in the electric mode, the utility factor (UF) depends mostly on the battery capacity, but also on many other factors, such as travel pattern and recharging pattern. Conventionally, the UFs are calculated based on the daily vehicle miles traveled (DVMT) by assuming motorists leave home in the morning with a full battery, and no charge occurs before returning home in the evening. Such an assumption, however, ignores the impact of the heterogeneity in both travel andmore » charging behavior, such as going back home more than once in a day, the impact of available charging time, and the price of gasoline. In addition, the conventional UFs are based on the National Household Travel Survey (NHTS) data, which are one-day travel data of each sample vehicle. A motorist's daily distance variation is ignored. This paper employs the GPS-based longitudinal travel data (covering 3-18 months) collected from 403 vehicles in the Seattle metropolitan area to investigate how such travel and charging behavior affects UFs. To do this, for each vehicle, we organized trips to a series of home and work related tours. The UFs based on the DVMT are found close to those based on home-to-home tours. However, it is seen that the workplace charge opportunities significantly increase UFs if the CD range is no more than 40 miles.« less

On the Likelihood Ratio Test for the Number of Factors in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Hayashi, Kentaro; Bentler, Peter M.; Yuan, Ke-Hai

2007-01-01

In the exploratory factor analysis, when the number of factors exceeds the true number of factors, the likelihood ratio test statistic no longer follows the chi-square distribution due to a problem of rank deficiency and nonidentifiability of model parameters. As a result, decisions regarding the number of factors may be incorrect. Several…

Multivariate analysis of factors influencing medical costs of acute pancreatitis hospitalizations based on a national administrative database.

PubMed

Murata, Atsuhiko; Matsuda, Shinya; Mayumi, Toshihiko; Okamoto, Kohji; Kuwabara, Kazuaki; Ichimiya, Yukako; Fujino, Yoshihisa; Kubo, Tatsuhiko; Fujimori, Kenji; Horiguchi, Hiromasa

2012-02-01

Little information is available on the analysis of medical costs of acute pancreatitis hospitalizations. This study aimed to determine the factors affecting medical costs of patients with acute pancreatitis during hospitalization using a Japanese administrative database. A total of 7193 patients with acute pancreatitis were referred to 776 hospitals. We defined "patients with high medical costs" as patients whose medical costs exceeded the 90th percentile in medical costs during hospitalization and identified the independent factors for patients with high medical costs with and without controlling for length of stay. Multiple logistic regression analysis demonstrated that necrosectomy was the most significant factor for medical costs of acute pancreatitis during hospitalization. The odds ratio of necrosectomy was 33.64 (95% confidence interval, 14.14-80.03; p<0.001). Use of an intensive care unit was the most significant factor for medical costs after controlling for LOS. The OR of an ICU was 6.44 (95% CI, 4.72-8.81; p<0.001). This study demonstrated that necrosectomy and use of an ICU significantly affected the medical costs of acute pancreatitis hospitalization. These results highlight the need for health care implementations to reduce medical costs whilst maintaining the quality of patient care, and targeting patients with severe acute pancreatitis. Copyright © 2011 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Definition of the thermographic regions of interest in cycling by using a factor analysis

NASA Astrophysics Data System (ADS)

Priego Quesada, Jose Ignacio; Lucas-Cuevas, Angel Gabriel; Salvador Palmer, Rosario; Pérez-Soriano, Pedro; Cibrián Ortiz de Anda, Rosa M.^a.

2016-03-01

Research in exercise physiology using infrared thermography has increased in the last years. However, the definition of the Regions of Interest (ROIs) varies strongly between studies. Therefore, the aim of this study was to use a factor analysis approach to define highly correlated groups of thermographic ROIs during a cycling test. Factor analyses were performed based on the moment of measurement and on the variation of skin temperatures as a result of the cycling exercise. 19 male participants cycled during 45 min at 50% of their individual peak power output with a cadence of 90 rpm. Infrared thermography was used to measure skin temperatures in sixteen ROIs of the trunk and lower limbs at three moments: before, immediately after and 10 min after the cycling test. Factor analyses were used to identify groups of ROIs based on the skin absolute temperatures at each moment of measurement as well as on skin temperature variations between moments. All the factor analyses performed for each moment and skin temperature variation explained more than the 80% of the variance. Different groups of ROIs were obtained when the analysis was based on the moment of measurement or on the effect of exercise on the skin temperature. Furthermore, some ROIs were grouped in the same way in both analyses (e.g. the ROIs of the trunk), whereas other regions (legs and their joints) were grouped differently in each analysis. Differences between groups of ROIs are related to their tissue composition, muscular activity and capacity of sweating. In conclusion, the resultant groups of ROIs were coherent and could help researchers to define the ROIs in future thermal studies.

A Brief History of the Philosophical Foundations of Exploratory Factor Analysis.

ERIC Educational Resources Information Center

Mulaik, Stanley A.

1987-01-01

Exploratory factor analysis derives its key ideas from many sources, including Aristotle, Francis Bacon, Descartes, Pearson and Yule, and Kant. The conclusions of exploratory factor analysis are never complete without subsequent confirmatory factor analysis. (Author/GDC)

[Analysis on accuracy and influencing factors of oral fluid-based rapid HIV self-testing among men who have sex with men].

PubMed

Li, Youfang; Wang, Yumiao; Zhang, Renzhong; Wang, Jue; Li, Zhiqing; Wang, Ling; Pan, Songfeng; Yang, Yanling; Ma, Yanling; Jia, Manhong

2016-01-01

To understood the accuracy of oral fluid-based rapid HIV self-testing among men who have sex with men (MSM) and related factors. Survey was conducted among MSM selected through non-probability sampling to evaluate the quality of their rapid HIV self-testing, and related information was analyzed. The most MSM were aged 21-30 years (57.0%). Among them, 45.7% had educational level of college or above, 78.5% were unmarried, 59.3% were casual laborers. The overall accuracy rate of oral fluid based self-testing was 95.0%, the handling of"inserting test paper into tube as indicated by arrow on it"had the highest accuracy rate (98.0%), and the handling of"gently upsetting tube for 3 times"had lowest accuracy rate (65.0%); Chi-square analysis showed that educational level, no touch with middle part of test paper, whether reading the instruction carefully, whether understanding the instruction and inserting test paper into tube as indicated by the arrow on it were associated with the accuracy of oral fluid-based rapid HIV self-testing, (P<0.05). Multivariate logistic regression analysis indicated that educational level, no touch with middle part of test paper and understanding instructions were associated with the accuracy of oral fluid-based rapid HIV self-testing. The accuracy of oral fluid-based rapid HIV self-testing was high among MSM, the accuracy varied with the educational level of the MSM. Touch with the middle part of test paper or not and understanding the instructions or not might influence the accuracy of the self-testing.

The Use of Major Risk Factors for Computer-Based Distinction of Diabetic Patients with Ischemic Stroke and Without Stroke

DTIC Science & Technology

2001-10-25

THE USE of MAJOR RISK FACTORS for COMPUTER-BASED DISTINCTION of DIABETIC PATIENTS with ISCHEMIC STROKE and WITHOUT STROKE Sibel Oge Merey1...highlighting the major risk factors of diabetic patients with non-embolic stroke and without stroke by performing dependency analysis and decision making...of Major Risk Factors for Computer-Based Distinction of Diabetic Patients with Ischemic Stroke and Without Stroke Contract Number Grant Number

Chapter 11. Community analysis-based methods

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

Cao, Y.; Wu, C.H.; Andersen, G.L.

2010-05-01

Microbial communities are each a composite of populations whose presence and relative abundance in water or other environmental samples are a direct manifestation of environmental conditions, including the introduction of microbe-rich fecal material and factors promoting persistence of the microbes therein. As shown by culture-independent methods, different animal-host fecal microbial communities appear distinctive, suggesting that their community profiles can be used to differentiate fecal samples and to potentially reveal the presence of host fecal material in environmental waters. Cross-comparisons of microbial communities from different hosts also reveal relative abundances of genetic groups that can be used to distinguish sources. Inmore » increasing order of their information richness, several community analysis methods hold promise for MST applications: phospholipid fatty acid (PLFA) analysis, denaturing gradient gel electrophoresis (DGGE), terminal restriction fragment length polymorphism (TRFLP), cloning/sequencing, and PhyloChip. Specific case studies involving TRFLP and PhyloChip approaches demonstrate the ability of community-based analyses of contaminated waters to confirm a diagnosis of water quality based on host-specific marker(s). The success of community-based MST for comprehensively confirming fecal sources relies extensively upon using appropriate multivariate statistical approaches. While community-based MST is still under evaluation and development as a primary diagnostic tool, results presented herein demonstrate its promise. Coupled with its inherently comprehensive ability to capture an unprecedented amount of microbiological data that is relevant to water quality, the tools for microbial community analysis are increasingly accessible, and community-based approaches have unparalleled potential for translation into rapid, perhaps real-time, monitoring platforms.« less

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

ERIC Educational Resources Information Center

Reali, Florencia

2017-01-01

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

Hand function evaluation: a factor analysis study.

PubMed

Jarus, T; Poremba, R

1993-05-01

The purpose of this study was to investigate hand function evaluations. Factor analysis with varimax rotation was used to assess the fundamental characteristics of the items included in the Jebsen Hand Function Test and the Smith Hand Function Evaluation. The study sample consisted of 144 subjects without disabilities and 22 subjects with Colles fracture. Results suggest a four factor solution: Factor I--pinch movement; Factor II--grasp; Factor III--target accuracy; and Factor IV--activities of daily living. These categories differentiated the subjects without Colles fracture from the subjects with Colles fracture. A hand function evaluation consisting of these four factors would be useful. Such an evaluation that can be used for current clinical purposes is provided.

What Factors Affect Voluntary Uptake of Community-Based Health Insurance Schemes in Low- and Middle-Income Countries? A Systematic Review and Meta-Analysis

PubMed Central

Hossain, S. A. Shahed; Pérez Koehlmoos, Tracey Lynn; John, Denny

2016-01-01

Introduction This research article reports on factors influencing initial voluntary uptake of community-based health insurance (CBHI) schemes in low- and middle-income countries (LMIC), and renewal decisions. Methods Following PRISMA protocol, we conducted a comprehensive search of academic and gray literature, including academic databases in social science, economics and medical sciences (e.g., Econlit, Global health, Medline, Proquest) and other electronic resources (e.g., Eldis and Google scholar). Search strategies were developed using the thesaurus or index terms (e.g., MeSH) specific to the databases, combined with free text terms related to CBHI or health insurance. Searches were conducted from May 2013 to November 2013 in English, French, German, and Spanish. From the initial search yield of 15,770 hits, 54 relevant studies were retained for analysis of factors influencing enrolment and renewal decisions. The quantitative synthesis (informed by meta-analysis) and the qualitative analysis (informed by thematic synthesis) were compared to gain insight for an overall synthesis of findings/statements. Results Meta-analysis suggests that enrolments in CBHI were positively associated with household income, education and age of the household head (HHH), household size, female-headed household, married HHH and chronic illness episodes in the household. The thematic synthesis suggests the following factors as enablers for enrolment: (a) knowledge and understanding of insurance and CBHI, (b) quality of healthcare, (c) trust in scheme management. Factors found to be barriers to enrolment include: (a) inappropriate benefits package, (b) cultural beliefs, (c) affordability, (d) distance to healthcare facility, (e) lack of adequate legal and policy frameworks to support CBHI, and (f) stringent rules of some CBHI schemes. HHH education, household size and trust in the scheme management were positively associated with member renewal decisions. Other motivators were: (a

What Factors Affect Voluntary Uptake of Community-Based Health Insurance Schemes in Low- and Middle-Income Countries? A Systematic Review and Meta-Analysis.

PubMed

Dror, David Mark; Hossain, S A Shahed; Majumdar, Atanu; Pérez Koehlmoos, Tracey Lynn; John, Denny; Panda, Pradeep Kumar

2016-01-01

This research article reports on factors influencing initial voluntary uptake of community-based health insurance (CBHI) schemes in low- and middle-income countries (LMIC), and renewal decisions. Following PRISMA protocol, we conducted a comprehensive search of academic and gray literature, including academic databases in social science, economics and medical sciences (e.g., Econlit, Global health, Medline, Proquest) and other electronic resources (e.g., Eldis and Google scholar). Search strategies were developed using the thesaurus or index terms (e.g., MeSH) specific to the databases, combined with free text terms related to CBHI or health insurance. Searches were conducted from May 2013 to November 2013 in English, French, German, and Spanish. From the initial search yield of 15,770 hits, 54 relevant studies were retained for analysis of factors influencing enrolment and renewal decisions. The quantitative synthesis (informed by meta-analysis) and the qualitative analysis (informed by thematic synthesis) were compared to gain insight for an overall synthesis of findings/statements. Meta-analysis suggests that enrolments in CBHI were positively associated with household income, education and age of the household head (HHH), household size, female-headed household, married HHH and chronic illness episodes in the household. The thematic synthesis suggests the following factors as enablers for enrolment: (a) knowledge and understanding of insurance and CBHI, (b) quality of healthcare, (c) trust in scheme management. Factors found to be barriers to enrolment include: (a) inappropriate benefits package, (b) cultural beliefs, (c) affordability, (d) distance to healthcare facility, (e) lack of adequate legal and policy frameworks to support CBHI, and (f) stringent rules of some CBHI schemes. HHH education, household size and trust in the scheme management were positively associated with member renewal decisions. Other motivators were: (a) knowledge and understanding of

Analysis of functional redundancies within the Arabidopsis TCP transcription factor family.

PubMed

Danisman, Selahattin; van Dijk, Aalt D J; Bimbo, Andrea; van der Wal, Froukje; Hennig, Lars; de Folter, Stefan; Angenent, Gerco C; Immink, Richard G H

2013-12-01

Analyses of the functions of TEOSINTE-LIKE1, CYCLOIDEA, and PROLIFERATING CELL FACTOR1 (TCP) transcription factors have been hampered by functional redundancy between its individual members. In general, putative functionally redundant genes are predicted based on sequence similarity and confirmed by genetic analysis. In the TCP family, however, identification is impeded by relatively low overall sequence similarity. In a search for functionally redundant TCP pairs that control Arabidopsis leaf development, this work performed an integrative bioinformatics analysis, combining protein sequence similarities, gene expression data, and results of pair-wise protein-protein interaction studies for the 24 members of the Arabidopsis TCP transcription factor family. For this, the work completed any lacking gene expression and protein-protein interaction data experimentally and then performed a comprehensive prediction of potential functional redundant TCP pairs. Subsequently, redundant functions could be confirmed for selected predicted TCP pairs by genetic and molecular analyses. It is demonstrated that the previously uncharacterized class I TCP19 gene plays a role in the control of leaf senescence in a redundant fashion with TCP20. Altogether, this work shows the power of combining classical genetic and molecular approaches with bioinformatics predictions to unravel functional redundancies in the TCP transcription factor family.

Analysis of functional redundancies within the Arabidopsis TCP transcription factor family

PubMed Central

Danisman, Selahattin; de Folter, Stefan; Immink, Richard G. H.

2013-01-01

Analyses of the functions of TEOSINTE-LIKE1, CYCLOIDEA, and PROLIFERATING CELL FACTOR1 (TCP) transcription factors have been hampered by functional redundancy between its individual members. In general, putative functionally redundant genes are predicted based on sequence similarity and confirmed by genetic analysis. In the TCP family, however, identification is impeded by relatively low overall sequence similarity. In a search for functionally redundant TCP pairs that control Arabidopsis leaf development, this work performed an integrative bioinformatics analysis, combining protein sequence similarities, gene expression data, and results of pair-wise protein–protein interaction studies for the 24 members of the Arabidopsis TCP transcription factor family. For this, the work completed any lacking gene expression and protein–protein interaction data experimentally and then performed a comprehensive prediction of potential functional redundant TCP pairs. Subsequently, redundant functions could be confirmed for selected predicted TCP pairs by genetic and molecular analyses. It is demonstrated that the previously uncharacterized class I TCP19 gene plays a role in the control of leaf senescence in a redundant fashion with TCP20. Altogether, this work shows the power of combining classical genetic and molecular approaches with bioinformatics predictions to unravel functional redundancies in the TCP transcription factor family. PMID:24129704

Analysis of factors affecting satisfaction level on problem based learning approach using structural equation modeling

NASA Astrophysics Data System (ADS)

Hussain, Nur Farahin Mee; Zahid, Zalina

2014-12-01

Nowadays, in the job market demand, graduates are expected not only to have higher performance in academic but they must also be excellent in soft skill. Problem-Based Learning (PBL) has a number of distinct advantages as a learning method as it can deliver graduates that will be highly prized by industry. This study attempts to determine the satisfaction level of engineering students on the PBL Approach and to evaluate their determinant factors. The Structural Equation Modeling (SEM) was used to investigate how the factors of Good Teaching Scale, Clear Goals, Student Assessment and Levels of Workload affected the student satisfaction towards PBL approach.

Can an Internet-based health risk assessment highlight problems of heart disease risk factor awareness? A cross-sectional analysis.

PubMed

Dickerson, Justin B; McNeal, Catherine J; Tsai, Ginger; Rivera, Cathleen M; Smith, Matthew Lee; Ohsfeldt, Robert L; Ory, Marcia G

2014-04-18

Health risk assessments are becoming more popular as a tool to conveniently and effectively reach community-dwelling adults who may be at risk for serious chronic conditions such as coronary heart disease (CHD). The use of such instruments to improve adults' risk factor awareness and concordance with clinically measured risk factor values could be an opportunity to advance public health knowledge and build effective interventions. The objective of this study was to determine if an Internet-based health risk assessment can highlight important aspects of agreement between respondents' self-reported and clinically measured CHD risk factors for community-dwelling adults who may be at risk for CHD. Data from an Internet-based cardiovascular health risk assessment (Heart Aware) administered to community-dwelling adults at 127 clinical sites were analyzed. Respondents were recruited through individual hospital marketing campaigns, such as media advertising and print media, found throughout inpatient and outpatient facilities. CHD risk factors from the Framingham Heart Study were examined. Weighted kappa statistics were calculated to measure interrater agreement between respondents' self-reported and clinically measured CHD risk factors. Weighted kappa statistics were then calculated for each sample by strata of overall 10-year CHD risk. Three samples were drawn based on strategies for treating missing data: a listwise deleted sample, a pairwise deleted sample, and a multiple imputation (MI) sample. The MI sample (n=16,879) was most appropriate for addressing missing data. No CHD risk factor had better than marginal interrater agreement (κ>.60). High-density lipoprotein cholesterol (HDL-C) exhibited suboptimal interrater agreement that deteriorated (eg, κ<.30) as overall CHD risk increased. Conversely, low-density lipoprotein cholesterol (LDL-C) interrater agreement improved (eg, up to κ=.25) as overall CHD risk increased. Overall CHD risk of the sample was lower than

Factors influencing a problem-based learning implementation: A case study of IT courses

NASA Astrophysics Data System (ADS)

Darus, Norida Muhd; Mohd, Haslina; Baharom, Fauziah; Saip, Mohamed Ali; Puteh, Nurnasran; Marzuki @ Matt, Zaharin; Husain, Mohd Zabidin; Yasin, Azman

2016-08-01

IT students must be trained to work efficiently as teamwork. One of the techniques that can be used to train them is through Problem-Based Learning (PBL) approach. The PBL implementation can be influenced by various factors depending on the ultimate goal of the study. This study is focusing on the IT students' perception of the PBL implementation. The student's perception is important to ensure the successfulness of the PBL implementation. Therefore, it is important to identify the factors that might influence the implementation of PBL of IT courses. This study aims to identify some catalyst factors that may influence the PBL implementation of IT courses. The study involved three (3) main phases: identifying PBL implementation factors, constructing a PBL model, and PBL model validation using statistical analysis. Four main factors are identified: PBL Characteristics, PBL Course Assessment, PBL Practices, and PBL Perception. Based on these four factors, a PBL model is constructed. Then, based on the proposed PBL model, four hypotheses are formulated and analyzed to validate the model. All hypotheses are significantly acceptable. The result shows that the PBL Characteristics and PBL Course Assessment factors are significantly influenced the PBL Practices and indirectly influenced the Students' Perception of the PBL Implementation for IT courses. This PBL model can assist decision makers in enhancing the PBL teaching and learning strategy for IT courses. It is also can be tested to other courses in the future.

Environmental Determinants of Cardiovascular Diseases Risk Factors: A Qualitative Directed Content Analysis

PubMed Central

Sabzmakan, Leila; Mohammadi, Eesa; Morowatisharifabad, Mohammad Ali; Afaghi, Ahmad; Naseri, Mohammad Hassan; Mirzaei, Masoud

2014-01-01

Background: Cardiovascular diseases (CVDs) are the number one cause of death in the world. In most analyses of health problems, environment plays a significant and modifiable role in causing the problem either directly or indirectly through behavior. Objectives: This study aims to understand the patients and healthcare providers’ experiences about the environmental determinants of CVD risk factors based on the Precede Model. Patients and Methods: This qualitative study conducted over six months in 2012 at Diabetes Units of Health Centers associated with Alborz University of Medical Sciences and Health Services which is located in Karaj, Iran. The data were collected based on individual semi-structured interviews with 50 patients and 12 healthcare providers. Data analysis was performed simultaneous with data collection using the content analysis directed method. Results: Lack of behaviors like stress control, healthy eating and physical activity were the roots of the risk factors for CVD. The environmental factor is one of the barriers for conducting these behaviors. The environmental barriers included of structural environment including “availability and accessibility of health resources”, “new skills”, and “law and policies” which are located in enabling category and social environment including “social support”, “motivation to comply” and “consequences of behavior” which are located in reinforcing category. The most barriers to performing health behaviors were often structural. Conclusions: The environmental factors were barriers for doing healthy behaviors. These factors need to be considered to design health promotion interventions. Policymakers should not only focus on patients’ education but also should provide specific facilities to enhance economic, social and cultural status. PMID:25031848

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

NASA Astrophysics Data System (ADS)

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.

A Note on Procrustean Rotation in Exploratory Factor Analysis: A Computer Intensive Approach to Goodness-of-Fit Evaluation.

ERIC Educational Resources Information Center

Raykov, Tenko; Little, Todd D.

1999-01-01

Describes a method for evaluating results of Procrustean rotation to a target factor pattern matrix in exploratory factor analysis. The approach, based on the bootstrap method, yields empirical approximations of the sampling distributions of: (1) differences between target elements and rotated factor pattern matrices; and (2) the overall…

[Cultural regionalization for Coptis chinensis based on 3S technology platform Ⅰ. Study on growth suitability for Coptis chinensis based on ecological factors analysis by Maxent and ArcGIS model].

PubMed

Liu, Xin; Yang, Yan-Fang; Song, Hong-Ping; Zhang, Xiao-Bo; Huang, Lu-Qi; Wu, He-Zhen

2016-09-01

At the urgent request of Coptis chinensis planting,growth suitability as assessment indicators for C. chinensis cultivation was proposed and analyzed in this paper , based on chemical quality determination and ecological fators analysis by Maxent and ArcGIS model. Its potential distribution areas at differernt suitability grade and regionalization map were formulated based on statistical theory and growth suitability theory. The results showed that the most suitable habitats is some parts of Chongqing and Hubei province, such as Shizhu, Lichuan, Wulong, Wuxi, Enshi. There are seven ecological factor is the main ecological factors affect the growth of Coptidis Rhizoma, including altitude, precipitation in February and September and the rise of precipitation and altitude is conducive to the accumulation of total alkaloid content in C. chinensis. Therefore, The results of the study not only illustrates the most suitable for the surroundings of Coptidis Rhizoma, also helpful to further research and practice of cultivation regionalization, wild resource monitoring and large-scale cultivation of traditional Chinese medicine plants. Copyright© by the Chinese Pharmaceutical Association.

Structural Decomposition Analysis of China’s Industrial Energy Consumption Based on Input-Output Analysis

NASA Astrophysics Data System (ADS)

Huang, X. Y.; Zhou, J. Q.; Wang, Z.; Deng, L. C.; Hong, S.

2017-05-01

China is now at a stage of accelerated industrialization and urbanization, with energy-intensive industries contributing a large proportion of economic growth. In this study, we examined industrial energy consumption by decomposition analysis to describe the driving factors of energy consumption in China. Based on input-output (I-O) tables from the World Input-Output Database (WIOD) website and China’s energy use data from 1995 to 2011, we studied the sectorial changes of energy efficiency during the examined period. The results showed that all industries increased their energy efficiency. Energy consumption was decomposed into three factors by the logarithmic mean Divisia index (LMDI) method. The increase in production output was the leading factor that drives up China’s energy consumption. World Trade Organization accession and financial crises had great impact on the energy consumption. Based on these results, a series of energy policy suggestions for decision-makers has been proposed.

Microelectromechanical System (MEMS) Gyroscope Noise Analysis and Scale Factor Characterization over Temperature Variation

DTIC Science & Technology

2016-07-01

bias and scale factor tests. By testing state-of-the-art gyroscopes, the effect of input rate stability and accuracy may be examined. Based on the...tumble test or bias analysis at a tilted position to remove the effect of Earth’s rotation in the scale factor test • A rate table with better rate...format guide and test procedure for coriolis vibratory gyros. Piscataway (NJ): IEEE; 2004 Dec. 3. Maio A, Smith G, Knight R, Nothwang W, Conroy J

Obesity as a risk factor for developing functional limitation among older adults: A conditional inference tree analysis

USDA-ARS?s Scientific Manuscript database

Objective: To examine the risk factors of developing functional decline and make probabilistic predictions by using a tree-based method that allows higher order polynomials and interactions of the risk factors. Methods: The conditional inference tree analysis, a data mining approach, was used to con...

The effect of choosing three different C factor formulae derived from NDVI on a fully raster-based erosion modelling

NASA Astrophysics Data System (ADS)

Sulistyo, Bambang

2016-11-01

The research was aimed at studying the efect of choosing three different C factor formulae derived from NDVI on a fully raster-based erosion modelling of The USLE using remote sensing data and GIS technique. Methods applied was by analysing all factors affecting erosion such that all data were in the form of raster. Those data were R, K, LS, C and P factors. Monthly R factor was evaluated based on formula developed by Abdurachman. K factor was determined using modified formula used by Ministry of Forestry based on soil samples taken in the field. LS factor was derived from Digital Elevation Model. Three C factors used were all derived from NDVI and developed by Suriyaprasit (non-linear) and by Sulistyo (linear and non-linear). P factor was derived from the combination between slope data and landcover classification interpreted from Landsat 7 ETM+. Another analysis was the creation of map of Bulk Density used to convert erosion unit. To know the model accuracy, model validation was done by applying statistical analysis and by comparing Emodel with Eactual. A threshold value of ≥ 0.80 or ≥ 80% was chosen to justify. The research result showed that all Emodel using three formulae of C factors have coeeficient of correlation value of > 0.8. The results of analysis of variance showed that there was significantly difference between Emodel and Eactual when using C factor formula developed by Suriyaprasit and Sulistyo (non-linear). Among the three formulae, only Emodel using C factor formula developed by Sulistyo (linear) reached the accuracy of 81.13% while the other only 56.02% as developed by Sulistyo (nonlinear) and 4.70% as developed by Suriyaprasit, respectively.

Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer

NASA Astrophysics Data System (ADS)

Zhang, Yucheng; Oikonomou, Anastasia; Wong, Alexander; Haider, Masoom A.; Khalvati, Farzad

2017-04-01

Radiomics characterizes tumor phenotypes by extracting large numbers of quantitative features from radiological images. Radiomic features have been shown to provide prognostic value in predicting clinical outcomes in several studies. However, several challenges including feature redundancy, unbalanced data, and small sample sizes have led to relatively low predictive accuracy. In this study, we explore different strategies for overcoming these challenges and improving predictive performance of radiomics-based prognosis for non-small cell lung cancer (NSCLC). CT images of 112 patients (mean age 75 years) with NSCLC who underwent stereotactic body radiotherapy were used to predict recurrence, death, and recurrence-free survival using a comprehensive radiomics analysis. Different feature selection and predictive modeling techniques were used to determine the optimal configuration of prognosis analysis. To address feature redundancy, comprehensive analysis indicated that Random Forest models and Principal Component Analysis were optimum predictive modeling and feature selection methods, respectively, for achieving high prognosis performance. To address unbalanced data, Synthetic Minority Over-sampling technique was found to significantly increase predictive accuracy. A full analysis of variance showed that data endpoints, feature selection techniques, and classifiers were significant factors in affecting predictive accuracy, suggesting that these factors must be investigated when building radiomics-based predictive models for cancer prognosis.

Arterial stiffness estimation based photoplethysmographic pulse wave analysis

NASA Astrophysics Data System (ADS)

Huotari, Matti; Maatta, Kari; Kostamovaara, Juha

2010-11-01

Arterial stiffness is one of the indices of vascular healthiness. It is based on pulse wave analysis. In the case we decompose the pulse waveform for the estimation and determination of arterial elasticity. Firstly, optically measured with photoplethysmograph and then investigating means by four lognormal pulse waveforms for which we can find very good fit between the original and summed decomposed pulse wave. Several studies have demonstrated that these kinds of measures predict cardiovascular events. While dynamic factors, e.g., arterial stiffness, depend on fixed structural features of the vascular wall. Arterial stiffness is estimated based on pulse wave decomposition analysis in the radial and tibial arteries. Elucidation of the precise relationship between endothelial function and vascular stiffness awaits still further study.

Sequence information gain based motif analysis.

PubMed

Maynou, Joan; Pairó, Erola; Marco, Santiago; Perera, Alexandre

2015-11-09

The detection of regulatory regions in candidate sequences is essential for the understanding of the regulation of a particular gene and the mechanisms involved. This paper proposes a novel methodology based on information theoretic metrics for finding regulatory sequences in promoter regions. This methodology (SIGMA) has been tested on genomic sequence data for Homo sapiens and Mus musculus. SIGMA has been compared with different publicly available alternatives for motif detection, such as MEME/MAST, Biostrings (Bioconductor package), MotifRegressor, and previous work such Qresiduals projections or information theoretic based detectors. Comparative results, in the form of Receiver Operating Characteristic curves, show how, in 70% of the studied Transcription Factor Binding Sites, the SIGMA detector has a better performance and behaves more robustly than the methods compared, while having a similar computational time. The performance of SIGMA can be explained by its parametric simplicity in the modelling of the non-linear co-variability in the binding motif positions. Sequence Information Gain based Motif Analysis is a generalisation of a non-linear model of the cis-regulatory sequences detection based on Information Theory. This generalisation allows us to detect transcription factor binding sites with maximum performance disregarding the covariability observed in the positions of the training set of sequences. SIGMA is freely available to the public at http://b2slab.upc.edu.

Adjusting for multiple prognostic factors in the analysis of randomised trials

PubMed Central

2013-01-01

Background When multiple prognostic factors are adjusted for in the analysis of a randomised trial, it is unclear (1) whether it is necessary to account for each of the strata, formed by all combinations of the prognostic factors (stratified analysis), when randomisation has been balanced within each stratum (stratified randomisation), or whether adjusting for the main effects alone will suffice, and (2) the best method of adjustment in terms of type I error rate and power, irrespective of the randomisation method. Methods We used simulation to (1) determine if a stratified analysis is necessary after stratified randomisation, and (2) to compare different methods of adjustment in terms of power and type I error rate. We considered the following methods of analysis: adjusting for covariates in a regression model, adjusting for each stratum using either fixed or random effects, and Mantel-Haenszel or a stratified Cox model depending on outcome. Results Stratified analysis is required after stratified randomisation to maintain correct type I error rates when (a) there are strong interactions between prognostic factors, and (b) there are approximately equal number of patients in each stratum. However, simulations based on real trial data found that type I error rates were unaffected by the method of analysis (stratified vs unstratified), indicating these conditions were not met in real datasets. Comparison of different analysis methods found that with small sample sizes and a binary or time-to-event outcome, most analysis methods lead to either inflated type I error rates or a reduction in power; the lone exception was a stratified analysis using random effects for strata, which gave nominal type I error rates and adequate power. Conclusions It is unlikely that a stratified analysis is necessary after stratified randomisation except in extreme scenarios. Therefore, the method of analysis (accounting for the strata, or adjusting only for the covariates) will not

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

PubMed

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

2018-06-23

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

Do review articles boost journal impact factors? A longitudinal analysis for five pharmacology journals.

PubMed

Amiri, Marjan; Michel, Martin C

2018-06-21

The impact factor is a frequently applied tool in research output analytics. Based on five consecutive publication years each of five pharmacology journals, we have analyzed to which extent review articles yield more impact factor-relevant citations than original articles. Our analysis shows that review articles are quoted about twice as often as original articles published in the same year in the same journal. We conclude that inclusion of review articles does not substantially affect the impact factor of a journal unless they account for considerably more than 10% of all published articles.

Using factor analysis to identify neuromuscular synergies during treadmill walking

NASA Technical Reports Server (NTRS)

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

1998-01-01

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

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

PubMed

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; 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.

Risk Factors for Chronic and Recurrent Otitis Media–A Meta-Analysis

PubMed Central

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; 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. PMID:24466073

Human error and commercial aviation accidents: an analysis using the human factors analysis and classification system.

PubMed

Shappell, Scott; Detwiler, Cristy; Holcomb, Kali; Hackworth, Carla; Boquet, Albert; Wiegmann, Douglas A

2007-04-01

The aim of this study was to extend previous examinations of aviation accidents to include specific aircrew, environmental, supervisory, and organizational factors associated with two types of commercial aviation (air carrier and commuter/ on-demand) accidents using the Human Factors Analysis and Classification System (HFACS). HFACS is a theoretically based tool for investigating and analyzing human error associated with accidents and incidents. Previous research has shown that HFACS can be reliably used to identify human factors trends associated with military and general aviation accidents. Using data obtained from both the National Transportation Safety Board and the Federal Aviation Administration, 6 pilot-raters classified aircrew, supervisory, organizational, and environmental causal factors associated with 1020 commercial aviation accidents that occurred over a 13-year period. The majority of accident causal factors were attributed to aircrew and the environment, with decidedly fewer associated with supervisory and organizational causes. Comparisons were made between HFACS causal categories and traditional situational variables such as visual conditions, injury severity, and regional differences. These data will provide support for the continuation, modification, and/or development of interventions aimed at commercial aviation safety. HFACS provides a tool for assessing human factors associated with accidents and incidents.

Analysis of psychological factors for quality assessment of interactive multimodal service

NASA Astrophysics Data System (ADS)

Yamagishi, Kazuhisa; Hayashi, Takanori

2005-03-01

We proposed a subjective quality assessment model for interactive multimodal services. First, psychological factors of an audiovisual communication service were extracted by using the semantic differential (SD) technique and factor analysis. Forty subjects participated in subjective tests and performed point-to-point conversational tasks on a PC-based TV phone that exhibits various network qualities. The subjects assessed those qualities on the basis of 25 pairs of adjectives. Two psychological factors, i.e., an aesthetic feeling and a feeling of activity, were extracted from the results. Then, quality impairment factors affecting these two psychological factors were analyzed. We found that the aesthetic feeling is mainly affected by IP packet loss and video coding bit rate, and the feeling of activity depends on delay time and video frame rate. We then proposed an opinion model derived from the relationships among quality impairment factors, psychological factors, and overall quality. The results indicated that the estimation error of the proposed model is almost equivalent to the statistical reliability of the subjective score. Finally, using the proposed model, we discuss guidelines for quality design of interactive audiovisual communication services.

Theory of sampling: four critical success factors before analysis.

PubMed

Wagner, Claas; Esbensen, Kim H

2015-01-01

Food and feed materials characterization, risk assessment, and safety evaluations can only be ensured if QC measures are based on valid analytical data, stemming from representative samples. The Theory of Sampling (TOS) is the only comprehensive theoretical framework that fully defines all requirements to ensure sampling correctness and representativity, and to provide the guiding principles for sampling in practice. TOS also defines the concept of material heterogeneity and its impact on the sampling process, including the effects from all potential sampling errors. TOS's primary task is to eliminate bias-generating errors and to minimize sampling variability. Quantitative measures are provided to characterize material heterogeneity, on which an optimal sampling strategy should be based. Four critical success factors preceding analysis to ensure a representative sampling process are presented here.

Socio-economic factors and tuberculosis: a district-based ecological analysis in Hong Kong.

PubMed

Leung, C C; Yew, W W; Tam, C M; Chan, C K; Chang, K C; Law, W S; Wong, M Y; Au, K F

2004-08-01

Relatively little is known about the impact of socio-economic factors on tuberculosis in a metropolitan city with high disease incidence. District-specific tuberculosis notification rates for 1995--1997 and 2000--2002 were indirectly sex- and age-adjusted and compared with the socio-economic characteristics in the 1996 by-census and 2001 census. The differences between the 18 districts persisted after 3-year averaging and indirect standardisation. Only the percentage of population born locally, the percentage of the population widowed or divorced and the percentage of households residing in rooms or bedsits were consistently associated with the standardised notification ratios (SNR) for both periods, the first being negatively so (all P < 0.05). In a combined analysis with a general linear model for both periods, birth in China, residence <7 years, speaking other Asian languages, being married and in a single household were also significantly associated with the SNR (all P < 0.05). Using a backward conditional approach, only local birth, being married, and residing in rooms or bedsits were independent predictors of SNR (all P < 0.05). There was no significant association between SNR and socio-economic indices on education, occupation, unemployment and income. Socio-economic factors other than simple poverty are affecting the district-specific tuberculosis rates in Hong Kong.

Sampling factors influencing accuracy of sperm kinematic analysis.

PubMed

Owen, D H; Katz, D F

1993-01-01

Sampling conditions that influence the accuracy of experimental measurement of sperm head kinematics were studied by computer simulation methods. Several archetypal sperm trajectories were studied. First, mathematical models of typical flagellar beats were input to hydrodynamic equations of sperm motion. The instantaneous swimming velocities of such sperm were computed over sequences of flagellar beat cycles, from which the resulting trajectories were determined. In a second, idealized approach, direct mathematical models of trajectories were utilized, based upon similarities to the previous hydrodynamic constructs. In general, it was found that analyses of sampling factors produced similar results for the hydrodynamic and idealized trajectories. A number of experimental sampling factors were studied, including the number of sperm head positions measured per flagellar beat, and the time interval over which these measurements are taken. It was found that when one flagellar beat is sampled, values of amplitude of lateral head displacement (ALH) and linearity (LIN) approached their actual values when five or more sample points per beat were taken. Mean angular displacement (MAD) values, however, remained sensitive to sampling rate even when large sampling rates were used. Values of MAD were also much more sensitive to the initial starting point of the sampling procedure than were ALH or LIN. On the basis of these analyses of measurement accuracy for individual sperm, simulations were then performed of cumulative effects when studying entire populations of motile cells. It was found that substantial (double digit) errors occurred in the mean values of curvilinear velocity (VCL), LIN, and MAD under the conditions of 30 video frames per second and 0.5 seconds of analysis time. Increasing the analysis interval to 1 second did not appreciably improve the results. However, increasing the analysis rate to 60 frames per second significantly reduced the errors. These findings

A Factor Analysis of the BSRI and the PAQ.

ERIC Educational Resources Information Center

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…

Establishing Factor Validity Using Variable Reduction in Confirmatory Factor Analysis.

ERIC Educational Resources Information Center

Hofmann, Rich

1995-01-01

Using a 21-statement attitude-type instrument, an iterative procedure for improving confirmatory model fit is demonstrated within the context of the EQS program of P. M. Bentler and maximum likelihood factor analysis. Each iteration systematically eliminates the poorest fitting statement as identified by a variable fit index. (SLD)

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

PubMed

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

2013-03-01

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

Improving Measurement of the EFNEP Outcomes Using Factor Analysis of the Behavior Checklist

ERIC Educational Resources Information Center

Hoerr, Sharon L.; Abdulkadri, Abdullahi O.; Miller, Steven; Waltersdorf, Christine; LaShore, Margaret; Martin, Karen; Newkirk, Cathy

2011-01-01

This article advances the literature on assessment of EFNEP's effectiveness. Factor analysis of Behavior Checklist items were performed to arrive at a parsimonious set of constructs used to assess the effects of program attributes on participants' behavior change. Based on the data from Michigan EFNEP, the use of constructs demonstrated a robust…

Obesity as a risk factor for developing functional limitation among older adults: A conditional inference tree analysis.

PubMed

Cheng, Feon W; Gao, Xiang; Bao, Le; Mitchell, Diane C; Wood, Craig; Sliwinski, Martin J; Smiciklas-Wright, Helen; Still, Christopher D; Rolston, David D K; Jensen, Gordon L

2017-07-01

To examine the risk factors of developing functional decline and make probabilistic predictions by using a tree-based method that allows higher order polynomials and interactions of the risk factors. The conditional inference tree analysis, a data mining approach, was used to construct a risk stratification algorithm for developing functional limitation based on BMI and other potential risk factors for disability in 1,951 older adults without functional limitations at baseline (baseline age 73.1 ± 4.2 y). We also analyzed the data with multivariate stepwise logistic regression and compared the two approaches (e.g., cross-validation). Over a mean of 9.2 ± 1.7 years of follow-up, 221 individuals developed functional limitation. Higher BMI, age, and comorbidity were consistently identified as significant risk factors for functional decline using both methods. Based on these factors, individuals were stratified into four risk groups via the conditional inference tree analysis. Compared to the low-risk group, all other groups had a significantly higher risk of developing functional limitation. The odds ratio comparing two extreme categories was 9.09 (95% confidence interval: 4.68, 17.6). Higher BMI, age, and comorbid disease were consistently identified as significant risk factors for functional decline among older individuals across all approaches and analyses. © 2017 The Obesity Society.

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

PubMed

Gormley, Denise K

2003-04-01

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

Analysis of risk factors for schizophrenia with two different case definitions: a nationwide register-based external validation study.

PubMed

Sørensen, Holger J; Larsen, Janne T; Mors, Ole; Nordentoft, Merete; Mortensen, Preben B; Petersen, Liselotte

2015-03-01

Different case definitions of schizophrenia have been used in register based research. However, no previous study has externally validated two different case definitions of schizophrenia against a wide range of risk factors for schizophrenia. We investigated hazard ratios (HRs) for a wide range of risk factors for ICD-10 DCR schizophrenia using a nationwide Danish sample of 2,772,144 residents born in 1955-1997. We compared one contact only (OCO) (the case definition of schizophrenia used in Danish register based studies) with two or more contacts (TMC) (a case definition of at least 2 inpatient contacts with schizophrenia). During the follow-up, the OCO definition included 15,074 and the TMC 7562 cases; i.e. half as many. The TMC case definition appeared to select for a worse illness course. A wide range of risk factors were uniformly associated with both case definitions and only slightly higher risk estimates were found for the TMC definition. Choosing at least 2 inpatient contacts with schizophrenia (TMC) instead of the currently used case definition would result in almost similar risk estimates for many well-established risk factors. However, this would also introduce selection and include considerably fewer cases and reduce power of e.g. genetic studies based on register-diagnosed cases only. Copyright © 2015 Elsevier B.V. All rights reserved.

The Recoverability of P-Technique Factor Analysis

ERIC Educational Resources Information Center

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…

Genome-wide identification and expression analysis of TCP transcription factors in Gossypium raimondii.

PubMed

Ma, Jun; Wang, Qinglian; Sun, Runrun; Xie, Fuliang; Jones, Don C; Zhang, Baohong

2014-10-16

Plant-specific TEOSINTE-BRANCHED1/CYCLOIDEA/PCF (TCP) transcription factors play versatile functions in multiple aspects of plant growth and development. However, no systematical study has been performed in cotton. In this study, we performed for the first time the genome-wide identification and expression analysis of the TCP transcription factor family in Gossypium raimondii. A total of 38 non-redundant cotton TCP encoding genes were identified. The TCP transcription factors were divided into eleven subgroups based on phylogenetic analysis. Most TCP genes within the same subfamily demonstrated similar exon and intron organization and the motif structures were highly conserved among the subfamilies. Additionally, the chromosomal distribution pattern revealed that TCP genes were unevenly distributed across 11 out of the 13 chromosomes; segmental duplication is a predominant duplication event for TCP genes and the major contributor to the expansion of TCP gene family in G. raimondii. Moreover, the expression profiles of TCP genes shed light on their functional divergence.

Genome-wide identification and expression analysis of TCP transcription factors in Gossypium raimondii

PubMed Central

Ma, Jun; Wang, Qinglian; Sun, Runrun; Xie, Fuliang; Jones, Don C.; Zhang, Baohong

2014-01-01

Plant-specific TEOSINTE-BRANCHED1/CYCLOIDEA/PCF (TCP) transcription factors play versatile functions in multiple aspects of plant growth and development. However, no systematical study has been performed in cotton. In this study, we performed for the first time the genome-wide identification and expression analysis of the TCP transcription factor family in Gossypium raimondii. A total of 38 non-redundant cotton TCP encoding genes were identified. The TCP transcription factors were divided into eleven subgroups based on phylogenetic analysis. Most TCP genes within the same subfamily demonstrated similar exon and intron organization and the motif structures were highly conserved among the subfamilies. Additionally, the chromosomal distribution pattern revealed that TCP genes were unevenly distributed across 11 out of the 13 chromosomes; segmental duplication is a predominant duplication event for TCP genes and the major contributor to the expansion of TCP gene family in G. raimondii. Moreover, the expression profiles of TCP genes shed light on their functional divergence. PMID:25322260

Identification of estrogen-responsive genes using a genome-wide analysis of promoter elements for transcription factor binding sites.

PubMed

Kamalakaran, Sitharthan; Radhakrishnan, Senthil K; Beck, William T

2005-06-03

We developed a pipeline to identify novel genes regulated by the steroid hormone-dependent transcription factor, estrogen receptor, through a systematic analysis of upstream regions of all human and mouse genes. We built a data base of putative promoter regions for 23,077 human and 19,984 mouse transcripts from National Center for Biotechnology Information annotation and 8793 human and 6785 mouse promoters from the Data Base of Transcriptional Start Sites. We used this data base of putative promoters to identify potential targets of estrogen receptor by identifying estrogen response elements (EREs) in their promoters. Our program correctly identified EREs in genes known to be regulated by estrogen in addition to several new genes whose putative promoters contained EREs. We validated six genes (KIAA1243, NRIP1, MADH9, NME3, TPD52L, and ABCG2) to be estrogen-responsive in MCF7 cells using reverse transcription PCR. To allow for extensibility of our program in identifying targets of other transcription factors, we have built a Web interface to access our data base and programs. Our Web-based program for Promoter Analysis of Genome, PAGen@UIC, allows a user to identify putative target genes for vertebrate transcription factors through the analysis of their upstream sequences. The interface allows the user to search the human and mouse promoter data bases for potential target genes containing one or more listed transcription factor binding sites (TFBSs) in their upstream elements, using either regular expression-based consensus or position weight matrices. The data base can also be searched for promoters harboring user-defined TFBSs given as a consensus or a position weight matrix. Furthermore, the user can retrieve putative promoter sequences for any given gene together with identified TFBSs located on its promoter. Orthologous promoters are also analyzed to determine conserved elements.

The Factor Structure of the English Language Development Assessment: A Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Kuriakose, Anju

2011-01-01

This study investigated the internal factor structure of the English language development Assessment (ELDA) using confirmatory factor analysis. ELDA is an English language proficiency test developed by a consortium of multiple states and is used to identify and reclassify English language learners in kindergarten to grade 12. Scores on item…

Influential Observations in Principal Factor Analysis.

ERIC Educational Resources Information Center

Tanaka, Yutaka; Odaka, Yoshimasa

1989-01-01

A method is proposed for detecting influential observations in iterative principal factor analysis. Theoretical influence functions are derived for two components of the common variance decomposition. The major mathematical tool is the influence function derived by Tanaka (1988). (SLD)

The Analysis of the Contribution of Human Factors to the In-Flight Loss of Control Accidents

NASA Technical Reports Server (NTRS)

Ancel, Ersin; Shih, Ann T.

2012-01-01

In-flight loss of control (LOC) is currently the leading cause of fatal accidents based on various commercial aircraft accident statistics. As the Next Generation Air Transportation System (NextGen) emerges, new contributing factors leading to LOC are anticipated. The NASA Aviation Safety Program (AvSP), along with other aviation agencies and communities are actively developing safety products to mitigate the LOC risk. This paper discusses the approach used to construct a generic integrated LOC accident framework (LOCAF) model based on a detailed review of LOC accidents over the past two decades. The LOCAF model is comprised of causal factors from the domain of human factors, aircraft system component failures, and atmospheric environment. The multiple interdependent causal factors are expressed in an Object-Oriented Bayesian belief network. In addition to predicting the likelihood of LOC accident occurrence, the system-level integrated LOCAF model is able to evaluate the impact of new safety technology products developed in AvSP. This provides valuable information to decision makers in strategizing NASA's aviation safety technology portfolio. The focus of this paper is on the analysis of human causal factors in the model, including the contributions from flight crew and maintenance workers. The Human Factors Analysis and Classification System (HFACS) taxonomy was used to develop human related causal factors. The preliminary results from the baseline LOCAF model are also presented.

[Worrying behaviour in pre-school children aged three to seven years: a factor analysis of the results of a questionnaire].

PubMed

Pilecki, Maciej Wojciech; Kowal, Małgorzata; Woronkowicz, Agnieszka; Sobiecki, Jan; Kryst, Łukasz; Kamińska-Reyman, Jadwiga

2014-01-01

The aims of the study were: 1) the assessment of the interaction between the factors specified for behavioural problems observed in pre-school children based on a factor analysis and 2) the assessment of the relationship the specified factors have with the age and gender of the study group. A factor analysis based on a Principal Component Analysis of the main results of a Disturbing Behaviour Questionnaire (DBQ) completed by pre-school teachers, which includes categories of behaviour observed among pre-school age children that provoke the greatest concern among parents, guardians and educators. Nine-hundred and sixty-one children aged from 2.7 to 7.9 years (mean: 5.4; SD 1.13) from randomly chosen pre-schools in all districts of Krak6w. Based on a screen plot, as well as on a substantive analysis of the results, a decision was taken to employ a four-factor analysis (Lagging behind, Excessive behaviour, Eating-avoidance and Overeating) explaining 68% of the common factor variance. A very high Cronbach's alpha value was returned for the reliability of the individual scales. The conducted analysis of the relationship of the scales with age and gender indicated a greater intensity of disturbing behaviour in boys for the Lagging behind factor, the Excessive behaviour factor and the overall scale for the Disturbing Behaviour Questionnaire (DBQ). These were the scales, along with the Eating-avoidance scale, that were found to be related to age. A greater intensity of disturbing behaviour was found to occur in the younger children. The relationship between the Overeating and Excessive behaviour scales that was found among girls but not among boys indicated that--even at such a young age--the characteristics associated with eating in the context of gender were already present. The authors consider that the coherence of the results obtained and their consistency with other studies ofpre-school age children provide a sound platform for further analyses using the questionnaire

Factors associated with quality of life in active childhood epilepsy: a population-based study.

PubMed

Reilly, Colin; Atkinson, Patricia; Das, Krishna B; Chin, Richard F M; Aylett, Sarah E; Burch, Victoria; Gillberg, Christopher; Scott, Rod C; Neville, Brian G R

2015-05-01

Improving health-related quality of life (HRQOL), rather than just reducing seizures, should be the principal goal in comprehensive management of childhood epilepsy. There is a lack of population-based data on predictors of HRQOL in childhood epilepsy. The Children with Epilepsy in Sussex Schools (CHESS) study is a prospective, population-based study involving school-aged children (5-15 years) with active epilepsy (on one or more AED and/or had a seizure in the last year) in a defined geographical area in the UK. Eighty-five of 115 (74% of eligible population) children underwent comprehensive psychological assessment including measures of cognition, behaviour, and motor functioning. Parents of the children completed the Quality of Life in Childhood Epilepsy (QOLCE).Clinical data on eligible children was extracted using a standardised pro forma. Linear regression analysis was undertaken to identify factors significantly associated with total Quality of Life in this population. Factors independently significantly associated (p < .05) with total QOLCE scores were seizures before 24 months, cognitive impairment (IQ < 85), anxiety, and parent reported school attendance difficulty. These factors were also significantly associated with total QOLCE when children with IQ < 50 were excluded from analysis. The majority of factors associated with parent reported HRQOL in active childhood epilepsy are related to neurobehavioural and/or psychosocial aspects of the condition. Copyright © 2015 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

A dictionary based informational genome analysis

PubMed Central

2012-01-01

Background In the post-genomic era several methods of computational genomics are emerging to understand how the whole information is structured within genomes. Literature of last five years accounts for several alignment-free methods, arisen as alternative metrics for dissimilarity of biological sequences. Among the others, recent approaches are based on empirical frequencies of DNA k-mers in whole genomes. Results Any set of words (factors) occurring in a genome provides a genomic dictionary. About sixty genomes were analyzed by means of informational indexes based on genomic dictionaries, where a systemic view replaces a local sequence analysis. A software prototype applying a methodology here outlined carried out some computations on genomic data. We computed informational indexes, built the genomic dictionaries with different sizes, along with frequency distributions. The software performed three main tasks: computation of informational indexes, storage of these in a database, index analysis and visualization. The validation was done by investigating genomes of various organisms. A systematic analysis of genomic repeats of several lengths, which is of vivid interest in biology (for example to compute excessively represented functional sequences, such as promoters), was discussed, and suggested a method to define synthetic genetic networks. Conclusions We introduced a methodology based on dictionaries, and an efficient motif-finding software application for comparative genomics. This approach could be extended along many investigation lines, namely exported in other contexts of computational genomics, as a basis for discrimination of genomic pathologies. PMID:22985068

Application of factor analysis to the water quality in reservoirs

NASA Astrophysics Data System (ADS)

Silva, Eliana Costa e.; Lopes, Isabel Cristina; Correia, Aldina; Gonçalves, A. Manuela

2017-06-01

In this work we present a Factor Analysis of chemical and environmental variables of the water column and hydro-morphological features of several Portuguese reservoirs. The objective is to reduce the initial number of variables, keeping their common characteristics. Using the Factor Analysis, the environmental variables measured in the epilimnion and in the hypolimnion, together with the hydromorphological characteristics of the dams were reduced from 63 variables to only 13 factors, which explained a total of 83.348% of the variance in the original data. After performing rotation using the Varimax method, the relations between the factors and the original variables got clearer and more explainable, which provided a Factor Analysis model for these environmental variables using 13 varifactors: Water quality and distance to the source, Hypolimnion chemical composition, Sulfite-reducing bacteria and nutrients, Coliforms and faecal streptococci, Reservoir depth, Temperature, Location, among other factors.

[Exploration of influencing factors of price of herbal based on VAR model].

PubMed

Wang, Nuo; Liu, Shu-Zhen; Yang, Guang

2014-10-01

Based on vector auto-regression (VAR) model, this paper takes advantage of Granger causality test, variance decomposition and impulse response analysis techniques to carry out a comprehensive study of the factors influencing the price of Chinese herbal, including herbal cultivation costs, acreage, natural disasters, the residents' needs and inflation. The study found that there is Granger causality relationship between inflation and herbal prices, cultivation costs and herbal prices. And in the total variance analysis of Chinese herbal and medicine price index, the largest contribution to it is from its own fluctuations, followed by the cultivation costs and inflation.

Analysis of Factors Related to Hypopituitarism in Patients with Nonsellar Intracranial Tumor.

PubMed

Lu, Song-Song; Gu, Jian-Jun; Luo, Xiao-Hong; Zhang, Jian-He; Wang, Shou-Sen

2017-09-01

Previous studies have suggested that postoperative hypopituitarism in patients with nonsellar intracranial tumors is caused by traumatic surgery. However, with development of minimally invasive and precise neurosurgical techniques, the degree of injury to brain tissue has been reduced significantly, especially for parenchymal tumors. Therefore, understanding preexisting hypopituitarism and related risk factors can improve perioperative management for patients with nonsellar intracranial tumors. Chart data were collected retrospectively from 83 patients with nonsellar intracranial tumors admitted to our hospital from May 2014 to April 2015. Pituitary function of each subject was determined based on results of preoperative serum pituitary hormone analysis. Univariate and multivariate logistic regression methods were used to analyze relationships between preoperative hypopituitarism and factors including age, sex, history of hypertension and secondary epilepsy, course of disease, tumor mass effect, site of tumor, intracranial pressure (ICP), cerebrospinal fluid content, and pituitary morphology. A total of 30 patients (36.14%) presented with preoperative hypopituitarism in either 1 axis or multiple axes; 23 (27.71%) were affected in 1 axis, and 7 (8.43%) were affected in multiple axes. Univariate analysis showed that risk factors for preoperative hypopituitarism in patients with a nonsellar intracranial tumor include an acute or subacute course (≤3 months), intracranial hypertension (ICP >200 mm H 2 O), and mass effect (P < 0.05). Multivariate logistic regression analysis showed that mass effect is an independent risk factor for preoperative hypopituitarism in patients with nonsellar intracranial tumors (P < 0.05; odds ratio, 3.197). Prevalence of hypopituitarism is high in patients with nonsellar intracranial tumors. The occurrence of hypopituitarism is correlated with factors including an acute or subacute course (≤3 months), intracranial hypertension (ICP >200

LPL is the strongest prognostic factor in a comparative analysis of RNA-based markers in early chronic lymphocytic leukemia.

PubMed

Kaderi, Mohd Arifin; Kanduri, Meena; Buhl, Anne Mette; Sevov, Marie; Cahill, Nicola; Gunnarsson, Rebeqa; Jansson, Mattias; Smedby, Karin Ekström; Hjalgrim, Henrik; Jurlander, Jesper; Juliusson, Gunnar; Mansouri, Larry; Rosenquist, Richard

2011-08-01

The expression levels of LPL, ZAP70, TCL1A, CLLU1 and MCL1 have recently been proposed as prognostic factors in chronic lymphocytic leukemia. However, few studies have systematically compared these different RNA-based markers. Using real-time quantitative PCR, we measured the mRNA expression levels of these genes in unsorted samples from 252 newly diagnosed chronic lymphocytic leukemia patients and correlated our data with established prognostic markers (for example Binet stage, CD38, IGHV gene mutational status and genomic aberrations) and clinical outcome. High expression levels of all RNA-based markers, except MCL1, predicted shorter overall survival and time to treatment, with LPL being the most significant. In multivariate analysis including the RNA-based markers, LPL expression was the only independent prognostic marker for overall survival and time to treatment. When studying LPL expression and the established markers, LPL expression retained its independent prognostic strength for overall survival. All of the RNA-based markers, albeit with varying ability, added prognostic information to established markers, with LPL expression giving the most significant results. Notably, high LPL expression predicted a worse outcome in good-prognosis subgroups, such as patients with mutated IGHV genes, Binet stage A, CD38 negativity or favorable cytogenetics. In particular, the combination of LPL expression and CD38 could further stratify Binet stage A patients. LPL expression is the strongest RNA-based prognostic marker in chronic lymphocytic leukemia that could potentially be applied to predict outcome in the clinical setting, particularly in the large group of patients with favorable prognosis.

Genomic identification of WRKY transcription factors in carrot (Daucus carota) and analysis of evolution and homologous groups for plants.

PubMed

Li, Meng-Yao; Xu, Zhi-Sheng; Tian, Chang; Huang, Ying; Wang, Feng; Xiong, Ai-Sheng

2016-03-15

WRKY transcription factors belong to one of the largest transcription factor families. These factors possess functions in plant growth and development, signal transduction, and stress response. Here, we identified 95 DcWRKY genes in carrot based on the carrot genomic and transcriptomic data, and divided them into three groups. Phylogenetic analysis of WRKY proteins from carrot and Arabidopsis divided these proteins into seven subgroups. To elucidate the evolution and distribution of WRKY transcription factors in different species, we constructed a schematic of the phylogenetic tree and compared the WRKY family factors among 22 species, which including plants, slime mold and protozoan. An in-depth study was performed to clarify the homologous factor groups of nine divergent taxa in lower and higher plants. Based on the orthologous factors between carrot and Arabidopsis, 38 DcWRKY proteins were calculated to interact with other proteins in the carrot genome. Yeast two-hybrid assay showed that DcWRKY20 can interact with DcMAPK1 and DcMAPK4. The expression patterns of the selected DcWRKY genes based on transcriptome data and qRT-PCR suggested that those selected DcWRKY genes are involved in root development, biotic and abiotic stress response. This comprehensive analysis provides a basis for investigating the evolution and function of WRKY genes.

Prognostic factors in patients with spinal metastasis: a systematic review and meta-analysis.

PubMed

Luksanapruksa, Panya; Buchowski, Jacob M; Hotchkiss, William; Tongsai, Sasima; Wilartratsami, Sirichai; Chotivichit, Areesak

2017-05-01

Incidence of symptomatic spinal metastasis has increased owing to improvement in treatment of the disease. One of the key factors that influences decision-making is expected patient survival. To our knowledge, no systematic reviews or meta-analysis have been conducted that review independent prognostic factors in spinal metastases. This study aimed to determine independent prognostic factors that affect outcome in patients with metastatic spine disease. This is a systematic literature review and meta-analysis of publications for prognostic factors in spinal metastatic disease. Pooled patient results from cohort and observational studies. Meta-analysis for poor prognostic factors as determined by hazard ratio (HR) and 95% confidential interval (95% CI). We systematically searched relevant publications in PubMed and Embase. The following search terms were used: ("'spinal metastases'" OR "'vertebral metastases'" OR "spinal metastasis" OR 'vertebral metastases') AND ('"prognostic factors"' OR "'survival'"). Inclusion criteria were prospective and retrospective cohort series that report HR and 95% CI of independent prognostic factors from multivariate analysis. Two reviewers independently assessed all papers. The quality of included papers was assessed by using Newcastle-Ottawa Scale for cohort studies and publication bias was assessed by using funnel plot, Begg test, and Egger test. The prognostic factors that were mentioned in at least three publications were pooled. Meta-analysis was performed using HR and 95% CI as the primary outcomes of interest. Heterogeneity was assessed using the I 2 method. A total of 3,959 abstracts (1,382 from PubMed and 2,577 from Embase) were identified through database search and 40 publications were identified through review of cited publications. The reviewers selected a total of 51 studies for qualitative synthesis and 43 studies for meta-analysis. Seventeen poor prognostic factors were identified. These included presence of a

A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis

PubMed Central

Lin, Johnny; Bentler, Peter M.

2012-01-01

Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne’s asymptotically distribution-free method and Satorra Bentler’s mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler’s statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby’s study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic. PMID:23144511

A Third Moment Adjusted Test Statistic for Small Sample Factor Analysis.

PubMed

Lin, Johnny; Bentler, Peter M

2012-01-01

Goodness of fit testing in factor analysis is based on the assumption that the test statistic is asymptotically chi-square; but this property may not hold in small samples even when the factors and errors are normally distributed in the population. Robust methods such as Browne's asymptotically distribution-free method and Satorra Bentler's mean scaling statistic were developed under the presumption of non-normality in the factors and errors. This paper finds new application to the case where factors and errors are normally distributed in the population but the skewness of the obtained test statistic is still high due to sampling error in the observed indicators. An extension of Satorra Bentler's statistic is proposed that not only scales the mean but also adjusts the degrees of freedom based on the skewness of the obtained test statistic in order to improve its robustness under small samples. A simple simulation study shows that this third moment adjusted statistic asymptotically performs on par with previously proposed methods, and at a very small sample size offers superior Type I error rates under a properly specified model. Data from Mardia, Kent and Bibby's study of students tested for their ability in five content areas that were either open or closed book were used to illustrate the real-world performance of this statistic.

A Large-Scale Analysis of Impact Factor Biased Journal Self-Citations.

PubMed

Chorus, Caspar; Waltman, Ludo

2016-01-01

Based on three decades of citation data from across scientific fields of science, we study trends in impact factor biased self-citations of scholarly journals, using a purpose-built and easy to use citation based measure. Our measure is given by the ratio between i) the relative share of journal self-citations to papers published in the last two years, and ii) the relative share of journal self-citations to papers published in preceding years. A ratio higher than one suggests that a journal's impact factor is disproportionally affected (inflated) by self-citations. Using recently reported survey data, we show that there is a relation between high values of our proposed measure and coercive journal self-citation malpractices. We use our measure to perform a large-scale analysis of impact factor biased journal self-citations. Our main empirical result is, that the share of journals for which our measure has a (very) high value has remained stable between the 1980s and the early 2000s, but has since risen strongly in all fields of science. This time span corresponds well with the growing obsession with the impact factor as a journal evaluation measure over the last decade. Taken together, this suggests a trend of increasingly pervasive journal self-citation malpractices, with all due unwanted consequences such as inflated perceived importance of journals and biased journal rankings.

The Impact of Clinical, Demographic and Risk Factors on Rates of HIV Transmission: A Population-based Phylogenetic Analysis in British Columbia, Canada

PubMed Central

Poon, Art F. Y.; Joy, Jeffrey B.; Woods, Conan K.; Shurgold, Susan; Colley, Guillaume; Brumme, Chanson J.; Hogg, Robert S.; Montaner, Julio S. G.; Harrigan, P. Richard

2015-01-01

Background. The diversification of human immunodeficiency virus (HIV) is shaped by its transmission history. We therefore used a population based province wide HIV drug resistance database in British Columbia (BC), Canada, to evaluate the impact of clinical, demographic, and behavioral factors on rates of HIV transmission. Methods. We reconstructed molecular phylogenies from 27 296 anonymized bulk HIV pol sequences representing 7747 individuals in BC—about half the estimated HIV prevalence in BC. Infections were grouped into clusters based on phylogenetic distances, as a proxy for variation in transmission rates. Rates of cluster expansion were reconstructed from estimated dates of HIV seroconversion. Results. Our criteria grouped 4431 individuals into 744 clusters largely separated with respect to risk factors, including large established clusters predominated by injection drug users and more-recently emerging clusters comprising men who have sex with men. The mean log10 viral load of an individual's phylogenetic neighborhood (composed of 5 other individuals with shortest phylogenetic distances) increased their odds of appearing in a cluster by >2-fold per log10 viruses per milliliter. Conclusions. Hotspots of ongoing HIV transmission can be characterized in near real time by the secondary analysis of HIV resistance genotypes, providing an important potential resource for targeting public health initiatives for HIV prevention. PMID:25312037

Factors influencing societal response of nanotechnology: an expert stakeholder analysis.

PubMed

Gupta, Nidhi; Fischer, Arnout R H; van der Lans, Ivo A; Frewer, Lynn J

2012-05-01

Nanotechnology can be described as an emerging technology and, as has been the case with other emerging technologies such as genetic modification, different socio-psychological factors will potentially influence societal responses to its development and application. These factors will play an important role in how nanotechnology is developed and commercialised. This article aims to identify expert opinion on factors influencing societal response to applications of nanotechnology. Structured interviews with experts on nanotechnology from North West Europe were conducted using repertory grid methodology in conjunction with generalized Procrustes analysis to examine the psychological constructs underlying societal uptake of 15 key applications of nanotechnology drawn from different areas (e.g. medicine, agriculture and environment, chemical, food, military, sports, and cosmetics). Based on expert judgement, the main factors influencing societal response to different applications of nanotechnology will be the extent to which applications are perceived to be beneficial, useful, and necessary, and how 'real' and physically close to the end-user these applications are perceived to be by the public. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11051-012-0857-x) contains supplementary material, which is available to authorized users.

Human factors in the Naval Air Systems Command: Computer based training

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

Seamster, T.L.; Snyder, C.E.; Terranova, M.

1988-01-01

Military standards applied to the private sector contracts have a substantial effect on the quality of Computer Based Training (CBT) systems procured for the Naval Air Systems Command. This study evaluated standards regulating the following areas in CBT development and procurement: interactive training systems, cognitive task analysis, and CBT hardware. The objective was to develop some high-level recommendations for evolving standards that will govern the next generation of CBT systems. One of the key recommendations is that there be an integration of the instructional systems development, the human factors engineering, and the software development standards. Recommendations were also made formore » task analysis and CBT hardware standards. (9 refs., 3 figs.)« less

Identification of Genetic Bases of Vibrio fluvialis Species-Specific Biochemical Pathways and Potential Virulence Factors by Comparative Genomic Analysis

PubMed Central

Lu, Xin; Liang, Weili; Wang, Yunduan; Xu, Jialiang

2014-01-01

Vibrio fluvialis is an important food-borne pathogen that causes diarrheal illness and sometimes extraintestinal infections in humans. In this study, we sequenced the genome of a clinical V. fluvialis strain and determined its phylogenetic relationships with other Vibrio species by comparative genomic analysis. We found that the closest relationship was between V. fluvialis and V. furnissii, followed by those with V. cholerae and V. mimicus. Moreover, based on genome comparisons and gene complementation experiments, we revealed genetic mechanisms of the biochemical tests that differentiate V. fluvialis from closely related species. Importantly, we identified a variety of genes encoding potential virulence factors, including multiple hemolysins, transcriptional regulators, and environmental survival and adaptation apparatuses, and the type VI secretion system, which is indicative of complex regulatory pathways modulating pathogenesis in this organism. The availability of V. fluvialis genome sequences may promote our understanding of pathogenic mechanisms for this emerging pathogen. PMID:24441165

Factor-Analysis Methods for Higher-Performance Neural Prostheses

PubMed Central

Santhanam, Gopal; Yu, Byron M.; Gilja, Vikash; Ryu, Stephen I.; Afshar, Afsheen; Sahani, Maneesh; Shenoy, Krishna V.

2009-01-01

Neural prostheses aim to provide treatment options for individuals with nervous-system disease or injury. It is necessary, however, to increase the performance of such systems before they can be clinically viable for patients with motor dysfunction. One performance limitation is the presence of correlated trial-to-trial variability that can cause neural responses to wax and wane in concert as the subject is, for example, more attentive or more fatigued. If a system does not properly account for this variability, it may mistakenly interpret such variability as an entirely different intention by the subject. We report here the design and characterization of factor-analysis (FA)–based decoding algorithms that can contend with this confound. We characterize the decoders (classifiers) on experimental data where monkeys performed both a real reach task and a prosthetic cursor task while we recorded from 96 electrodes implanted in dorsal premotor cortex. The decoder attempts to infer the underlying factors that comodulate the neurons' responses and can use this information to substantially lower error rates (one of eight reach endpoint predictions) by ≲75% (e.g., ∼20% total prediction error using traditional independent Poisson models reduced to ∼5%). We also examine additional key aspects of these new algorithms: the effect of neural integration window length on performance, an extension of the algorithms to use Poisson statistics, and the effect of training set size on the decoding accuracy of test data. We found that FA-based methods are most effective for integration windows >150 ms, although still advantageous at shorter timescales, that Gaussian-based algorithms performed better than the analogous Poisson-based algorithms and that the FA algorithm is robust even with a limited amount of training data. We propose that FA-based methods are effective in modeling correlated trial-to-trial neural variability and can be used to substantially increase overall

Independent Confirmatory Factor Analysis of the Cognitive Assessment System (CAS): What Does CAS Measure?

ERIC Educational Resources Information Center

Kranzler, John H.; Keith, Timothy Z.

1999-01-01

Uses confirmatory factor analysis (CFA) to address unresolved issues concerning the structure of the Cognitive Assessment System, a test of intelligence based upon the planning, attention, and simultaneous-successive (PASS) processes theory of human cognition. Results reveal that the CFA of the standardization data do not support use of the CAS…

Replace-approximation method for ambiguous solutions in factor analysis of ultrasonic hepatic perfusion

NASA Astrophysics Data System (ADS)

Zhang, Ji; Ding, Mingyue; Yuchi, Ming; Hou, Wenguang; Ye, Huashan; Qiu, Wu

2010-03-01

Factor analysis is an efficient technique to the analysis of dynamic structures in medical image sequences and recently has been used in contrast-enhanced ultrasound (CEUS) of hepatic perfusion. Time-intensity curves (TICs) extracted by factor analysis can provide much more diagnostic information for radiologists and improve the diagnostic rate of focal liver lesions (FLLs). However, one of the major drawbacks of factor analysis of dynamic structures (FADS) is nonuniqueness of the result when only the non-negativity criterion is used. In this paper, we propose a new method of replace-approximation based on apex-seeking for ambiguous FADS solutions. Due to a partial overlap of different structures, factor curves are assumed to be approximately replaced by the curves existing in medical image sequences. Therefore, how to find optimal curves is the key point of the technique. No matter how many structures are assumed, our method always starts to seek apexes from one-dimensional space where the original high-dimensional data is mapped. By finding two stable apexes from one dimensional space, the method can ascertain the third one. The process can be continued until all structures are found. This technique were tested on two phantoms of blood perfusion and compared to the two variants of apex-seeking method. The results showed that the technique outperformed two variants in comparison of region of interest measurements from phantom data. It can be applied to the estimation of TICs derived from CEUS images and separation of different physiological regions in hepatic perfusion.

National Institutes of Health Toolbox Emotion Battery for English- and Spanish-speaking adults: normative data and factor-based summary scores.

PubMed

Babakhanyan, Ida; McKenna, Benjamin S; Casaletto, Kaitlin B; Nowinski, Cindy J; Heaton, Robert K

2018-01-01

The National Institutes of Health Toolbox Emotion Battery (NIHTB-EB) is a "common currency", computerized assessment developed to measure the full spectrum of emotional health. Though comprehensive, the NIHTB-EB's 17 scales may be unwieldy for users aiming to capture more global indices of emotional functioning. NIHTB-EB was administered to 1,036 English-speaking and 408 Spanish-speaking adults as a part of the NIH Toolbox norming project. We examined the factor structure of the NIHTB-EB in English- and Spanish-speaking adults and developed factor analysis-based summary scores. Census-weighted norms were presented for English speakers, and sample-weighted norms were presented for Spanish speakers. Exploratory factor analysis for both English- and Spanish-speaking cohorts resulted in the same 3-factor solution: 1) negative affect, 2) social satisfaction, and 3) psychological well-being. Confirmatory factor analysis supported similar factor structures for English- and Spanish-speaking cohorts. Model fit indices fell within the acceptable/good range, and our final solution was optimal compared to other solutions. Summary scores based upon the normative samples appear to be psychometrically supported and should be applied to clinical samples to further validate the factor structures and investigate rates of problematic emotions in medical and psychiatric populations.

Cardiometabolic Risk Clustering in Spinal Cord Injury: Results of Exploratory Factor Analysis

PubMed Central

2013-01-01

Background: 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. Objective: The purpose of this study was to describe unique clustering of cardiometabolic risk factors differentiated by level of injury. Methods: 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). Results: 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. Conclusions: 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. PMID:23960702

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

PubMed

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.

A replication of a factor analysis of motivations for trapping

USGS Publications Warehouse

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.

Analysis of factors affecting employee satisfaction: A case study from Pakistan.

PubMed

Rukh, Lala; Choudhary, Muhammad Abbas; Abbasi, Saddam Akber

2015-01-01

Employee job satisfaction has been a research focal point throughout the world. It is a key factor when measuring the performance of an organization and individuals. A leading engineering goods manufacturing enterprise in Pakistan, has been used in this case study. In Pakistan, very limited research has been done with respect to factors affecting job satisfaction. Some research has been done in medical institutions, banks, universities and the information technology sector but large public sector organizations in Pakistan have not been studied. A theoretical foundation for researching factors affecting job satisfaction in large organizations is outlined. The objective of this research is to analyze various demographic, financial and non-financial factors affecting the satisfaction level of employees and to study the effects across different employee groups. This study is based on quantitative data analysis. The employees of the organization under study have been divided into 10 homogeneous groups based on their departments. Information on job related factors (affecting the satisfaction level) have been collected from subsamples of each group using a self-administered questionnaire. An overall sample of 250 (out of total 1100) employees has been selected. Before conducting the survey, reliability of the questionnaire was measured using Cronbach's alpha. The normality of data was also examined using the Kolmogorov Smirnov test. Hypotheses devised to address the research questions were tested by using non-parametric Spearman correlation and Kruskal-Wallis tests. The response rate was 73.2%. Research findings indicated the significant factors that affect the satisfaction level of employees. Median group differences existed between responses based on age, work experience, salary and designation (i.e. job position/rank) of employees. Job satisfaction was also positively and significantly associated with job related factors such as pay, promotion, relation with employees

On the Relations among Regular, Equal Unique Variances, and Image Factor Analysis Models.

ERIC Educational Resources Information Center

Hayashi, Kentaro; Bentler, Peter M.

2000-01-01

Investigated the conditions under which the matrix of factor loadings from the factor analysis model with equal unique variances will give a good approximation to the matrix of factor loadings from the regular factor analysis model. Extends the results to the image factor analysis model. Discusses implications for practice. (SLD)

Analysis of Traffic Crashes Involving Pedestrians Using Big Data: Investigation of Contributing Factors and Identification of Hotspots.

PubMed

Xie, Kun; Ozbay, Kaan; Kurkcu, Abdullah; Yang, Hong

2017-08-01

This study aims to explore the potential of using big data in advancing the pedestrian risk analysis including the investigation of contributing factors and the hotspot identification. Massive amounts of data of Manhattan from a variety of sources were collected, integrated, and processed, including taxi trips, subway turnstile counts, traffic volumes, road network, land use, sociodemographic, and social media data. The whole study area was uniformly split into grid cells as the basic geographical units of analysis. The cell-structured framework makes it easy to incorporate rich and diversified data into risk analysis. The cost of each crash, weighted by injury severity, was assigned to the cells based on the relative distance to the crash site using a kernel density function. A tobit model was developed to relate grid-cell-specific contributing factors to crash costs that are left-censored at zero. The potential for safety improvement (PSI) that could be obtained by using the actual crash cost minus the cost of "similar" sites estimated by the tobit model was used as a measure to identify and rank pedestrian crash hotspots. The proposed hotspot identification method takes into account two important factors that are generally ignored, i.e., injury severity and effects of exposure indicators. Big data, on the one hand, enable more precise estimation of the effects of risk factors by providing richer data for modeling, and on the other hand, enable large-scale hotspot identification with higher resolution than conventional methods based on census tracts or traffic analysis zones. © 2017 Society for Risk Analysis.

Analysis of Pre-Analytic Factors Affecting the Success of Clinical Next-Generation Sequencing of Solid Organ Malignancies.

PubMed

Chen, Hui; Luthra, Rajyalakshmi; Goswami, Rashmi S; Singh, Rajesh R; Roy-Chowdhuri, Sinchita

2015-08-28

Application of next-generation sequencing (NGS) technology to routine clinical practice has enabled characterization of personalized cancer genomes to identify patients likely to have a response to targeted therapy. The proper selection of tumor sample for downstream NGS based mutational analysis is critical to generate accurate results and to guide therapeutic intervention. However, multiple pre-analytic factors come into play in determining the success of NGS testing. In this review, we discuss pre-analytic requirements for AmpliSeq PCR-based sequencing using Ion Torrent Personal Genome Machine (PGM) (Life Technologies), a NGS sequencing platform that is often used by clinical laboratories for sequencing solid tumors because of its low input DNA requirement from formalin fixed and paraffin embedded tissue. The success of NGS mutational analysis is affected not only by the input DNA quantity but also by several other factors, including the specimen type, the DNA quality, and the tumor cellularity. Here, we review tissue requirements for solid tumor NGS based mutational analysis, including procedure types, tissue types, tumor volume and fraction, decalcification, and treatment effects.

Analysis of major risk factors affecting those working in the agrarian sector (based on a sociological survey).

PubMed

Krekoten, Olena M; Dereziuk, Anatolii V; Ihnaschuk, Olena V; Holovchanska, Svitlana E

Issues related to labour potential, its state and problems have consistently been a focus of attention for the International Labour Organisation (ILO). Its respective analysis shows that labour potential problems remain unresolved in many countries of the world. According to the World Health Organisation (WHO), adverse working conditions are among major factors of occupational disease development in Europe and the reason for disabilities of economically active population during 2.5% of their lifetime. The aim of the present study is to identify and analyse major risk factors, which have a bearing on people working in agriculture in the course of exercising their occupation, with account of forms of ownership of agricultural enterprises. Carried out was a cross-sectional study involving a sociological survey of 412 respondents - those working in agriculture - who made up the primary group and the control group. The study revealed 21 risk factors, 9 of which were work-related. A modified elementary cybernetic model of studying impact efficiency was developed with the view of carrying out a structural analysis of the sample group and choosing relevant methodological approaches. It has been established that harmful factors related to working environment and one's lifestyle are decisive in the agrarian sector, particularly for workers of privately owned businesses. For one out of three respondents harmful working conditions manifested themselves as industrial noise (31.7±3.4), vibration (29.0±2.1) trunk bending and constrained working posture (36.6±3.4). The vast majority of agricultural workers (91.6±2.5) admitted they could not afford proper rest during their annual leave; male respondents abused alcohol (70.6±3.0) and smoking (41.4±2.0 per 100 workers). The research established the structure of risk factors, which is sequentially represented by the following groups: behavioral (smoking, drinking of alcohol, rest during annual leave, physical culture), working

Design factors of femur fracture fixation plates made of shape memory alloy based on the Taguchi method by finite element analysis.

PubMed

Ko, Cheolwoong; Yang, Mikyung; Byun, Taemin; Lee, Sang-Wook

2018-05-01

This study proposed a way to design femur fracture fixation plates made of shape memory alloy based on computed tomography (CT) images of Korean cadaveric femurs. To this end, 3 major design factors of femur fracture fixation plates (circumference angle, thickness, and inner diameter) were selected based on the contact pressure when a femur fracture fixation plate was applied to a cylinder model using the Taguchi method. Then, the effects of the design factors were analyzed. It was shown that the design factors were statistically significant at a level of p = 0.05 concerning the inner diameter and the thickness. The factors affecting the contact pressure were inner diameter, thickness, and circumference angle, in that order. Particularly, in the condition of Case 9 (inner diameter 27 mm, thickness 2.4 mm, and circumference angle 270°), the max. average contact pressure was 21.721 MPa, while the min. average contact pressure was 3.118 MPa in Case 10 (inner diameter 29 mm, thickness 2.0 mm, and circumference angle 210°). When the femur fracture fixation plate was applied to the cylinder model, the displacement due to external sliding and pulling forces was analyzed. As a result, the displacement in the sliding condition was at max. 3.75 times greater than that in the pulling condition, which indicated that the cohesion strength between the femur fracture fixation plate and the cylinder model was likely to be greater in the pulling condition. When a human femur model was applied, the max. average contact pressure was 10.76 MPa, which was lower than the yield strength of a human femur (108 MPa). In addition, the analysis of the rib behaviors of the femur fracture fixation plate in relation to the recovery effect of the shape memory alloy showed that the rib behaviors varied depending on the arbitrarily curved shapes of the femur sections. Copyright © 2018 John Wiley & Sons, Ltd.

Electronic health record analysis via deep poisson factor models

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

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Electronic health record analysis via deep poisson factor models

DOE PAGES

Henao, Ricardo; Lu, James T.; Lucas, Joseph E.; ...

2016-01-01

Electronic Health Record (EHR) phenotyping utilizes patient data captured through normal medical practice, to identify features that may represent computational medical phenotypes. These features may be used to identify at-risk patients and improve prediction of patient morbidity and mortality. We present a novel deep multi-modality architecture for EHR analysis (applicable to joint analysis of multiple forms of EHR data), based on Poisson Factor Analysis (PFA) modules. Each modality, composed of observed counts, is represented as a Poisson distribution, parameterized in terms of hidden binary units. In-formation from different modalities is shared via a deep hierarchy of common hidden units. Activationmore » of these binary units occurs with probability characterized as Bernoulli-Poisson link functions, instead of more traditional logistic link functions. In addition, we demon-strate that PFA modules can be adapted to discriminative modalities. To compute model parameters, we derive efficient Markov Chain Monte Carlo (MCMC) inference that scales efficiently, with significant computational gains when compared to related models based on logistic link functions. To explore the utility of these models, we apply them to a subset of patients from the Duke-Durham patient cohort. We identified a cohort of over 12,000 patients with Type 2 Diabetes Mellitus (T2DM) based on diagnosis codes and laboratory tests out of our patient population of over 240,000. Examining the common hidden units uniting the PFA modules, we identify patient features that represent medical concepts. Experiments indicate that our learned features are better able to predict mortality and morbidity than clinical features identified previously in a large-scale clinical trial.« less

Factor Analysis of the Brazilian Version of UPPS Impulsive Behavior Scale

PubMed Central

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.

PubMed

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.

CLUSFAVOR 5.0: hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles

PubMed Central

Peterson, Leif E

2002-01-01

CLUSFAVOR (CLUSter and Factor Analysis with Varimax Orthogonal Rotation) 5.0 is a Windows-based computer program for hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles. CLUSFAVOR 5.0 standardizes input data; sorts data according to gene-specific coefficient of variation, standard deviation, average and total expression, and Shannon entropy; performs hierarchical cluster analysis using nearest-neighbor, unweighted pair-group method using arithmetic averages (UPGMA), or furthest-neighbor joining methods, and Euclidean, correlation, or jack-knife distances; and performs principal-component analysis. PMID:12184816

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

PubMed

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.

Human error analysis of commercial aviation accidents: application of the Human Factors Analysis and Classification system (HFACS).

PubMed

Wiegmann, D A; Shappell, S A

2001-11-01

The Human Factors Analysis and Classification System (HFACS) is a general human error framework originally developed and tested within the U.S. military as a tool for investigating and analyzing the human causes of aviation accidents. Based on Reason's (1990) model of latent and active failures, HFACS addresses human error at all levels of the system, including the condition of aircrew and organizational factors. The purpose of the present study was to assess the utility of the HFACS framework as an error analysis and classification tool outside the military. The HFACS framework was used to analyze human error data associated with aircrew-related commercial aviation accidents that occurred between January 1990 and December 1996 using database records maintained by the NTSB and the FAA. Investigators were able to reliably accommodate all the human causal factors associated with the commercial aviation accidents examined in this study using the HFACS system. In addition, the classification of data using HFACS highlighted several critical safety issues in need of intervention research. These results demonstrate that the HFACS framework can be a viable tool for use within the civil aviation arena. However, additional research is needed to examine its applicability to areas outside the flight deck, such as aircraft maintenance and air traffic control domains.

An exploration of the structure of mentors' behavior in nursing education using exploratory factor analysis and Mokken scale analysis.

PubMed

Chen, Yanhua; Watson, Roger; Hilton, Andrea

2016-05-01

To understand nursing students' expectation from their mentors and assess mentors' performance, a scale of mentors' behavior was developed based on literature review and focus group in China. This study aims to explore the structure of mentors' behavior. A cross-sectional survey. Data were collected from nursing students in three hospitals in southwest China in 2014. A total of 669 pre-registered nursing students in their final year clinical learning participated in this study. Exploratory factor analysis and Mokken scale analysis was employed to explore the structure and hierarchical property of mentors' behavior. Three dimensions (professional development, facilitating learning and psychosocial support) were identified by factor analysis and confirmed by Mokken scaling analysis. The three sub-scales showed internal consistency reliability from 87% to 91%, and moderate to strong precision in ordering students' expectation about mentors' behavior and a small Mokken scale showing hierarchy was identified. Some insight into the structure of mentoring in nursing education has been obtained and a scale which could be used in the study of mentoring and in the preparation of mentors has been developed. Copyright © 2016 Elsevier Ltd. All rights reserved.

A theory of planned behaviour-based analysis of TIMSS 2011 to determine factors influencing inquiry teaching practices in high-performing countries

NASA Astrophysics Data System (ADS)

Pongsophon, Pongprapan; Herman, Benjamin C.

2017-07-01

Given the abundance of literature describing the strong relationship between inquiry-based teaching and student achievement, more should be known about the factors impacting science teachers' classroom inquiry implementation. This study utilises the theory of planned behaviour to propose and validate a causal model of inquiry-based teaching through analysing data relating to high-performing countries retrieved from the 2011 Trends in International Mathematics and Science Study assessments. Data analysis was completed through structural equation modelling using a polychoric correlation matrix for data input and diagonally weighted least squares estimation. Adequate fit of the full model to the empirical data was realised. The model demonstrates that the extent the teachers participated in academic collaborations was positively related to their occupational satisfaction, confidence in teaching inquiry, and classroom inquiry practices. Furthermore, the teachers' confidence with implementing inquiry was positively related to their classroom inquiry implementation and occupational satisfaction. However, perceived student-generated constraints demonstrated a negative relationship with the teachers' confidence with implementing inquiry and occupational satisfaction. Implications from this study include supporting teachers through promoting collaborative opportunities that facilitate inquiry-based practices and occupational satisfaction.

A Factor Analysis of Learning Data and Selected Ability Test Scores

ERIC Educational Resources Information Center

Jones, Dorothy L.

1976-01-01

A verbal concept-learning task permitting the externalizing and quantifying of learning behavior and 16 ability tests were administered to female graduate students. Data were analyzed by alpha factor analysis and incomplete image analysis. Six alpha factors and 12 image factors were extracted and orthogonally rotated. Four areas of cognitive…

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach

PubMed Central

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions. PMID:29033978

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach.

PubMed

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions.

Factors affecting secondary science teachers' appraisal and adoption of technology-rich project-based learning environments

NASA Astrophysics Data System (ADS)

Luehmann, April Lynn

We are learning much about how to design project-based curriculum that leverages technology, but we know less about the everyday needs of teachers and the implicit and explicit factors that influence their curriculum adoption decisions. Given that teachers are the gatekeepers of their classrooms, it is essential that designers and reformers understand the criteria teachers use to support their judgments regarding the appraisal and adoption of innovative curricula if they wish to see widespread use of their designs. Toward this end, this dissertation examines the perceptions of teachers as they appraise and consider the adoption of one innovative, technology-rich, project-based curriculum. Thirty secondary science teachers in Indiana were recruited. This study took place in two phases. During the first phase, data consisted of teachers' comments in the form of "think aloud's" and observations as teachers interacted with an Internet-based science program: Web-Based Inquiry Science Environment. Through an examination of these data, six implicit factors were identified: Trust, Identity, Self-Efficacy, Process Goals, Situational Constraints, and Contextual Idiosyncrasies. Examination of the content related to these categories suggests that curricular adoption is not simply an academic process but is also a personal one. Also, trust between the teacher and both the change facilitator and the innovation plays an influential role. Data collected during the second phase included item analysis of factors that emerged during semi structured interviews and rated by the teachers in terms of their importance in influencing their adoption of the WISE-water quality program. Teacher identified factors were collapsed into 26 explicit factors and analyzed using cluster analysis, resulting in five clusters of teacher profiles: Logistically Focused, Subject-Matter Focused, Scaffolded Optimists, Accountability Focused, and Pedagogically Savvy. This study reveals that factors affecting

Risk factors for operated carpal tunnel syndrome: a multicenter population-based case-control study

PubMed Central

Mattioli, Stefano; Baldasseroni, Alberto; Bovenzi, Massimo; Curti, Stefania; Cooke, Robin MT; Campo, Giuseppe; Barbieri, Pietro G; Ghersi, Rinaldo; Broccoli, Marco; Cancellieri, Maria Pia; Colao, Anna Maria; dell'Omo, Marco; Fateh-Moghadam, Pirous; Franceschini, Flavia; Fucksia, Serenella; Galli, Paolo; Gobba, Fabriziomaria; Lucchini, Roberto; Mandes, Anna; Marras, Teresa; Sgarrella, Carla; Borghesi, Stefano; Fierro, Mauro; Zanardi, Francesca; Mancini, Gianpiero; Violante, Francesco S

2009-01-01

Background Carpal tunnel syndrome (CTS) is a socially and economically relevant disease caused by compression or entrapment of the median nerve within the carpal tunnel. This population-based case-control study aims to investigate occupational/non-occupational risk factors for surgically treated CTS. Methods Cases (n = 220) aged 18-65 years were randomly drawn from 13 administrative databases of citizens who were surgically treated with carpal tunnel release during 2001. Controls (n = 356) were randomly sampled from National Health Service registry records and were frequency matched by age-gender-specific CTS hospitalization rates. Results At multivariate analysis, risk factors were blue-collar/housewife status, BMI ≥ 30 kg/m2, sibling history of CTS and coexistence of trigger finger. Being relatively tall (cut-offs based on tertiles: women ≥165 cm; men ≥175 cm) was associated with lower risk. Blue-collar work was a moderate/strong risk factor in both sexes. Raised risks were apparent for combinations of biomechanical risk factors that included frequent repetitivity and sustained force. Conclusion This study strongly underlines the relevance of biomechanical exposures in both non-industrial and industrial work as risk factors for surgically treated CTS. PMID:19758429

Biological risk factors for suicidal behaviors: a meta-analysis

PubMed Central

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

2016-01-01

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

Genomic identification of WRKY transcription factors in carrot (Daucus carota) and analysis of evolution and homologous groups for plants

PubMed Central

Li, Meng-Yao; Xu, Zhi-Sheng; Tian, Chang; Huang, Ying; Wang, Feng; Xiong, Ai-Sheng

2016-01-01

WRKY transcription factors belong to one of the largest transcription factor families. These factors possess functions in plant growth and development, signal transduction, and stress response. Here, we identified 95 DcWRKY genes in carrot based on the carrot genomic and transcriptomic data, and divided them into three groups. Phylogenetic analysis of WRKY proteins from carrot and Arabidopsis divided these proteins into seven subgroups. To elucidate the evolution and distribution of WRKY transcription factors in different species, we constructed a schematic of the phylogenetic tree and compared the WRKY family factors among 22 species, which including plants, slime mold and protozoan. An in-depth study was performed to clarify the homologous factor groups of nine divergent taxa in lower and higher plants. Based on the orthologous factors between carrot and Arabidopsis, 38 DcWRKY proteins were calculated to interact with other proteins in the carrot genome. Yeast two-hybrid assay showed that DcWRKY20 can interact with DcMAPK1 and DcMAPK4. The expression patterns of the selected DcWRKY genes based on transcriptome data and qRT-PCR suggested that those selected DcWRKY genes are involved in root development, biotic and abiotic stress response. This comprehensive analysis provides a basis for investigating the evolution and function of WRKY genes. PMID:26975939

Modeling and projection of dengue fever cases in Guangzhou based on variation of weather factors.

PubMed

Li, Chenlu; Wang, Xiaofeng; Wu, Xiaoxu; Liu, Jianing; Ji, Duoying; Du, Juan

2017-12-15

Dengue fever is one of the most serious vector-borne infectious diseases, especially in Guangzhou, China. Dengue viruses and their vectors Aedes albopictus are sensitive to climate change primarily in relation to weather factors. Previous research has mainly focused on identifying the relationship between climate factors and dengue cases, or developing dengue case models with some non-climate factors. However, there has been little research addressing the modeling and projection of dengue cases only from the perspective of climate change. This study considered this topic using long time series data (1998-2014). First, sensitive weather factors were identified through meta-analysis that included literature review screening, lagged analysis, and collinear analysis. Then, key factors that included monthly average temperature at a lag of two months, and monthly average relative humidity and monthly average precipitation at lags of three months were determined. Second, time series Poisson analysis was used with the generalized additive model approach to develop a dengue model based on key weather factors for January 1998 to December 2012. Data from January 2013 to July 2014 were used to validate that the model was reliable and reasonable. Finally, future weather data (January 2020 to December 2070) were input into the model to project the occurrence of dengue cases under different climate scenarios (RCP 2.6 and RCP 8.5). Longer time series analysis and scientifically selected weather variables were used to develop a dengue model to ensure reliability. The projections suggested that seasonal disease control (especially in summer and fall) and mitigation of greenhouse gas emissions could help reduce the incidence of dengue fever. The results of this study hope to provide a scientifically theoretical basis for the prevention and control of dengue fever in Guangzhou. Copyright © 2017 Elsevier B.V. All rights reserved.

Spousal Violence in 5 Transitional Countries: A Population-Based Multilevel Analysis of Individual and Contextual Factors.

PubMed

Ismayilova, Leyla

2015-11-01

I examined the individual- and community-level factors associated with spousal violence in post-Soviet countries. I used population-based data from the Demographic and Health Survey conducted between 2005 and 2012. My sample included currently married women of reproductive age (n = 3932 in Azerbaijan, n = 4053 in Moldova, n = 1932 in Ukraine, n = 4361 in Kyrgyzstan, and n = 4093 in Tajikistan). I selected respondents using stratified multistage cluster sampling. Because of the nested structure of the data, multilevel logistic regressions for survey data were fitted to examine factors associated with spousal violence in the last 12 months. Partner's problem drinking was the strongest risk factor associated with spousal violence in all 5 countries. In Moldova, Ukraine, and Kyrgyzstan, women with greater financial power than their spouses were more likely to experience violence. Effects of community economic deprivation and of empowerment status of women in the community on spousal violence differed across countries. Women living in communities with a high tolerance of violence faced a higher risk of spousal violence in Moldova and Ukraine. In more traditional countries (Azerbaijan, Kyrgyzstan, and Tajikistan), spousal violence was lower in conservative communities with patriarchal gender beliefs or higher financial dependency on husbands. My findings underscore the importance of examining individual risk factors in the context of community-level factors and developing individual- and community-level interventions.

Analysis of influence mechanism of energy-related carbon emissions in Guangdong: evidence from regional China based on the input-output and structural decomposition analysis.

PubMed

Wang, Changjian; Wang, Fei; Zhang, Xinlin; Deng, Haijun

2017-11-01

It is important to analyze the influence mechanism of energy-related carbon emissions from a regional perspective to effectively achieve reductions in energy consumption and carbon emissions in China. Based on the "energy-economy-carbon emissions" hybrid input-output analysis framework, this study conducted structural decomposition analysis (SDA) on carbon emissions influencing factors in Guangdong Province. Systems-based examination of direct and indirect drivers for regional emission is presented. (1) Direct effects analysis of influencing factors indicated that the main driving factors of increasing carbon emissions were economic and population growth. Carbon emission intensity was the main contributing factor restraining carbon emissions growth. (2) Indirect effects analysis of influencing factors showed that international and interprovincial trades significantly affected the total carbon emissions. (3) Analysis of the effects of different final demands on the carbon emissions of industrial sector indicated that the increase in carbon emission arising from international and interprovincial trades is mainly concentrated in energy- and carbon-intensive industries. (4) Guangdong had to compromise a certain amount of carbon emissions during the development of its export-oriented economy because of industry transfer arising from the economic globalization, thereby pointing to the existence of the "carbon leakage" problem. At the same time, interprovincial export and import resulted in Guangdong transferring a part of its carbon emissions to other provinces, thereby leading to the occurrence of "carbon transfer."

Modifiable partner factors associated with perinatal depression and anxiety: a systematic review and meta-analysis.

PubMed

Pilkington, Pamela D; Milne, Lisa C; Cairns, Kathryn E; Lewis, James; Whelan, Thomas A

2015-06-01

Perinatal distress is a significant public health problem that adversely impacts the individual and their family. The primary objective of this systematic review and meta-analysis was to identify factors that partners can modify to protect each other from developing perinatal depression and anxiety. In accordance with the PRISMA statement, we reviewed the risk and protective factors associated with perinatal depression and anxiety symptoms that partners can potentially modify without professional assistance (PROSPERO reference CRD42014007524). Participants were new or expectant parents aged 16 years or older. The partner factors were sub-grouped into themes (e.g., instrumental support) based on a content analysis of the scale items and measure descriptions. A series of meta-analyses were conducted to estimate the pooled effect sizes of associations. We included 120 publications, reporting 245 associations with depression and 44 with anxiety. Partner factors with sound evidence that they protect against both perinatal depression and anxiety are: emotional closeness and global support. Partner factors with a sound evidence base for depression only are communication, conflict, emotional and instrumental support, and relationship satisfaction. This review is limited by the lack of generalizability to single parents and the inability to systematically review moderators and mediators, or control for baseline symptoms. The findings suggest that future prevention programs targeting perinatal depression and anxiety should aim to enhance relationship satisfaction, communication, and emotional closeness, facilitate instrumental and emotional support, and minimize conflict between partners. Copyright © 2015 Elsevier B.V. All rights reserved.

Rotation to a Partially Specified Target Matrix in Exploratory Factor Analysis: How Many Targets?

ERIC Educational Resources Information Center

Myers, Nicholas D.; Ahn, Soyeon; Jin, Ying

2013-01-01

The purpose of this study was to explore the influence of the number of targets specified on the quality of exploratory factor analysis solutions with a complex underlying structure and incomplete substantive measurement theory. Three Monte Carlo studies were performed based on the ratio of the number of observed variables to the number of…

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

PubMed

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

1997-01-01

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

Bayesian Factor Analysis When Only a Sample Covariance Matrix Is Available

ERIC Educational Resources Information Center

Hayashi, Kentaro; Arav, Marina

2006-01-01

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

Evaluation of Parallel Analysis Methods for Determining the Number of Factors

ERIC Educational Resources Information Center

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…

Improvement of Quench Factor Analysis in Phase and Hardness Prediction of a Quenched Steel

NASA Astrophysics Data System (ADS)

Kianezhad, M.; Sajjadi, S. A.

2013-05-01

The accurate prediction of alloys' properties introduced by heat treatment has been considered by many researchers. The advantages of such predictions are reduction of test trails and materials' consumption as well as time and energy saving. One of the most important methods to predict hardness in quenched steel parts is Quench Factor Analysis (QFA). Classical QFA is based on the Johnson-Mehl-Avrami-Kolmogorov (JMAK) equation. In this study, a modified form of the QFA based on the work by Rometsch et al. is compared with the classical QFA, and they are applied to prediction of hardness of steels. For this purpose, samples of CK60 steel were utilized as raw material. They were austenitized at 1103 K (830 °C). After quenching in different environments, they were cut and their hardness was determined. In addition, the hardness values of the samples were fitted using the classical and modified equations for the quench factor analysis and the results were compared. Results showed a significant improvement in fitted values of the hardness and proved the higher efficiency of the new method.

Risk-based planning analysis for a single levee

NASA Astrophysics Data System (ADS)

Hui, Rui; Jachens, Elizabeth; Lund, Jay

2016-04-01

Traditional risk-based analysis for levee planning focuses primarily on overtopping failure. Although many levees fail before overtopping, few planning studies explicitly include intermediate geotechnical failures in flood risk analysis. This study develops a risk-based model for two simplified levee failure modes: overtopping failure and overall intermediate geotechnical failure from through-seepage, determined by the levee cross section represented by levee height and crown width. Overtopping failure is based only on water level and levee height, while through-seepage failure depends on many geotechnical factors as well, mathematically represented here as a function of levee crown width using levee fragility curves developed from professional judgment or analysis. These levee planning decisions are optimized to minimize the annual expected total cost, which sums expected (residual) annual flood damage and annualized construction costs. Applicability of this optimization approach to planning new levees or upgrading existing levees is demonstrated preliminarily for a levee on a small river protecting agricultural land, and a major levee on a large river protecting a more valuable urban area. Optimized results show higher likelihood of intermediate geotechnical failure than overtopping failure. The effects of uncertainty in levee fragility curves, economic damage potential, construction costs, and hydrology (changing climate) are explored. Optimal levee crown width is more sensitive to these uncertainties than height, while the derived general principles and guidelines for risk-based optimal levee planning remain the same.

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

ERIC Educational Resources Information Center

Honjo, Shuji; And Others

1998-01-01

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

Model-free data analysis for source separation based on Non-Negative Matrix Factorization and k-means clustering (NMFk)

NASA Astrophysics Data System (ADS)

Vesselinov, V. V.; Alexandrov, B.

2014-12-01

The identification of the physical sources causing spatial and temporal fluctuations of state variables such as river stage levels and aquifer hydraulic heads is challenging. The fluctuations can be caused by variations in natural and anthropogenic sources such as precipitation events, infiltration, groundwater pumping, barometric pressures, etc. The source identification and separation can be crucial for conceptualization of the hydrological conditions and characterization of system properties. If the original signals that cause the observed state-variable transients can be successfully "unmixed", decoupled physics models may then be applied to analyze the propagation of each signal independently. We propose a new model-free inverse analysis of transient data based on Non-negative Matrix Factorization (NMF) method for Blind Source Separation (BSS) coupled with k-means clustering algorithm, which we call NMFk. NMFk is capable of identifying a set of unique sources from a set of experimentally measured mixed signals, without any information about the sources, their transients, and the physical mechanisms and properties controlling the signal propagation through the system. A classical BSS conundrum is the so-called "cocktail-party" problem where several microphones are recording the sounds in a ballroom (music, conversations, noise, etc.). Each of the microphones is recording a mixture of the sounds. The goal of BSS is to "unmix'" and reconstruct the original sounds from the microphone records. Similarly to the "cocktail-party" problem, our model-freee analysis only requires information about state-variable transients at a number of observation points, m, where m > r, and r is the number of unknown unique sources causing the observed fluctuations. We apply the analysis on a dataset from the Los Alamos National Laboratory (LANL) site. We identify and estimate the impact and sources are barometric pressure and water-supply pumping effects. We also estimate the

Cross-Cultural Validation of the Modified Practice Attitudes Scale: Initial Factor Analysis and a New Factor Model.

PubMed

Park, Heehoon; Ebesutani, Chad K; Chung, Kyong-Mee; Stanick, Cameo

2018-01-01

The objective of this study was to create the Korean version of the Modified Practice Attitudes Scale (K-MPAS) to measure clinicians' attitudes toward evidence-based treatments (EBTs) in the Korean mental health system. Using 189 U.S. therapists and 283 members from the Korean mental health system, we examined the reliability and validity of the MPAS scores. We also conducted the first exploratory and confirmatory factor analysis on the MPAS and compared EBT attitudes across U.S. and Korean therapists. Results revealed that the inclusion of both "reversed-worded" and "non-reversed-worded" items introduced significant method effects that compromised the integrity of the one-factor MPAS model. Problems with the one-factor structure were resolved by eliminating the "non-reversed-worded" items. Reliability and validity were adequate among both Korean and U.S. therapists. Korean therapists also reported significantly more negative attitudes toward EBTs on the MPAS than U.S. therapists. The K-MPAS is the first questionnaire designed to measure Korean service providers' attitudes toward EBTs to help advance the dissemination of EBTs in Korea. The current study also demonstrated the negative impacts that can be introduced by incorporating oppositely worded items into a scale, particularly with respect to factor structure and detecting significant group differences.

Application of Factor Analysis on the Financial Ratios of Indian Cement Industry and Validation of the Results by Cluster Analysis

NASA Astrophysics Data System (ADS)

De, Anupam; Bandyopadhyay, Gautam; Chakraborty, B. N.

2010-10-01

Financial ratio analysis is an important and commonly used tool in analyzing financial health of a firm. Quite a large number of financial ratios, which can be categorized in different groups, are used for this analysis. However, to reduce number of ratios to be used for financial analysis and regrouping them into different groups on basis of empirical evidence, Factor Analysis technique is being used successfully by different researches during the last three decades. In this study Factor Analysis has been applied over audited financial data of Indian cement companies for a period of 10 years. The sample companies are listed on the Stock Exchange India (BSE and NSE). Factor Analysis, conducted over 44 variables (financial ratios) grouped in 7 categories, resulted in 11 underlying categories (factors). Each factor is named in an appropriate manner considering the factor loads and constituent variables (ratios). Representative ratios are identified for each such factor. To validate the results of Factor Analysis and to reach final conclusion regarding the representative ratios, Cluster Analysis had been performed.

Comparative analysis based on factor analysis of integrate production capacity of foodstuff in main foodstuff provinces

NASA Astrophysics Data System (ADS)

Zhang, Dehua; Zhou, Huiqiu

2011-10-01

Under great background of financial crisis, large fluctuation on international foodstuff price and frequent happening of natural disasters, each nation attaches importance to foodstuff safety problem increasingly. As a Great Power of population, China pays more attention to foodstuff safety problem definitely. Large foodstuff provinces play a major role on ensuring it. The paper arrives at the conclusion that each province has advantages and disadvantages in different factors through factor analyses on influencing factors of integrated production capacity of foodstuff in each province. Then we arrange the factor score, analyze the result of each large foodstuff province and ultimately give out feasible suggestions.

Factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus: decision-curve analysis.

PubMed

Kondo, M; Nagao, Y; Mahbub, M H; Tanabe, T; Tanizawa, Y

2018-04-29

To identify factors predicting early postpartum glucose intolerance in Japanese women with gestational diabetes mellitus, using decision-curve analysis. A retrospective cohort study was performed. The participants were 123 Japanese women with gestational diabetes who underwent 75-g oral glucose tolerance tests at 8-12 weeks after delivery. They were divided into a glucose intolerance and a normal glucose tolerance group based on postpartum oral glucose tolerance test results. Analysis of the pregnancy oral glucose tolerance test results showed predictive factors for postpartum glucose intolerance. We also evaluated the clinical usefulness of the prediction model based on decision-curve analysis. Of 123 women, 78 (63.4%) had normoglycaemia and 45 (36.6%) had glucose intolerance. Multivariable logistic regression analysis showed insulinogenic index/fasting immunoreactive insulin and summation of glucose levels, assessed during pregnancy oral glucose tolerance tests (total glucose), to be independent risk factors for postpartum glucose intolerance. Evaluating the regression models, the best discrimination (area under the curve 0.725) was obtained using the basic model (i.e. age, family history of diabetes, BMI ≥25 kg/m 2 and use of insulin during pregnancy) plus insulinogenic index/fasting immunoreactive insulin <1.1. Decision-curve analysis showed that combining insulinogenic index/fasting immunoreactive insulin <1.1 with basic clinical information resulted in superior net benefits for prediction of postpartum glucose intolerance. Insulinogenic index/fasting immunoreactive insulin calculated using oral glucose tolerance test results during pregnancy is potentially useful for predicting early postpartum glucose intolerance in Japanese women with gestational diabetes. © 2018 Diabetes UK.

Factor Analysis by Generalized Least Squares.

ERIC Educational Resources Information Center

Joreskog, Karl G.; Goldberger, Arthur S.

Aitkin's generalized least squares (GLS) principle, with the inverse of the observed variance-covariance matrix as a weight matrix, is applied to estimate the factor analysis model in the exploratory (unrestricted) case. It is shown that the GLS estimates are scale free and asymptotically efficient. The estimates are computed by a rapidly…

Factors affecting and affected by user acceptance of computer-based nursing documentation: results of a two-year study.

PubMed

Ammenwerth, Elske; Mansmann, Ulrich; Iller, Carola; Eichstädter, Ronald

2003-01-01

The documentation of the nursing process is an important but often neglected part of clinical documentation. Paper-based systems have been introduced to support nursing process documentation. Frequently, however, problems such as low quality of documentation are reported. It is unclear whether computer-based documentation systems can reduce these problems and which factors influence their acceptance by users. We introduced a computer-based nursing documentation system on four wards of the University Hospitals of Heidelberg and systematically evaluated its preconditions and its effects in a pretest-posttest intervention study. For the analysis of user acceptance, we concentrated on subjective data drawn from questionnaires and interviews. A questionnaire was developed using items from published questionnaires and items that had to be developed for the special purpose of this study. The quantitative results point to two factors influencing the acceptance of a new computer-based documentation system: the previous acceptance of the nursing process and the previous amount of self-confidence when using computers. On one ward, the diverse acceptance scores heavily declined after the introduction of the nursing documentation system. Explorative qualitative analysis on this ward points to further success factors of computer-based nursing documentation systems. Our results can be used to assist the planning and introduction of computer-based nursing documentation systems. They demonstrate the importance of computer experience and acceptance of the nursing process on a ward but also point to other factors such as the fit between nursing workflow and the functionality of a nursing documentation system.

Human factors evaluation of remote afterloading brachytherapy. Volume 2, Function and task analysis

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

Callan, J.R.; Gwynne, J.W. III; Kelly, T.T.

1995-05-01

A human factors project on the use of nuclear by-product material to treat cancer using remotely operated afterloaders was undertaken by the Nuclear Regulatory Commission. The purpose of the project was to identify factors that contribute to human error in the system for remote afterloading brachytherapy (RAB). This report documents the findings from the first phase of the project, which involved an extensive function and task analysis of RAB. This analysis identified the functions and tasks in RAB, made preliminary estimates of the likelihood of human error in each task, and determined the skills needed to perform each RAB task.more » The findings of the function and task analysis served as the foundation for the remainder of the project, which evaluated four major aspects of the RAB system linked to human error: human-system interfaces; procedures and practices; training and qualifications of RAB staff; and organizational practices and policies. At its completion, the project identified and prioritized areas for recommended NRC and industry attention based on all of the evaluations and analyses.« less

Exploratory Factor Analysis of a Force Concept Inventory Data Set

ERIC Educational Resources Information Center

Scott, Terry F.; Schumayer, Daniel; Gray, Andrew R.

2012-01-01

We perform a factor analysis on a "Force Concept Inventory" (FCI) data set collected from 2109 respondents. We address two questions: the appearance of conceptual coherence in student responses to the FCI and some consequences of this factor analysis on the teaching of Newtonian mechanics. We will highlight the apparent conflation of Newton's…

Transcriptome-wide analysis of WRKY transcription factors in wheat and their leaf rust responsive expression profiling.

PubMed

Satapathy, Lopamudra; Singh, Dharmendra; Ranjan, Prashant; Kumar, Dhananjay; Kumar, Manish; Prabhu, Kumble Vinod; Mukhopadhyay, Kunal

2014-12-01

WRKY, a plant-specific transcription factor family, has important roles in pathogen defense, abiotic cues and phytohormone signaling, yet little is known about their roles and molecular mechanism of function in response to rust diseases in wheat. We identified 100 TaWRKY sequences using wheat Expressed Sequence Tag database of which 22 WRKY sequences were novel. Identified proteins were characterized based on their zinc finger motifs and phylogenetic analysis clustered them into six clades consisting of class IIc and class III WRKY proteins. Functional annotation revealed major functions in metabolic and cellular processes in control plants; whereas response to stimuli, signaling and defense in pathogen inoculated plants, their major molecular function being binding to DNA. Tag-based expression analysis of the identified genes revealed differential expression between mock and Puccinia triticina inoculated wheat near isogenic lines. Gene expression was also performed with six rust-related microarray experiments at Gene Expression Omnibus database. TaWRKY10, 15, 17 and 56 were common in both tag-based and microarray-based differential expression analysis and could be representing rust specific WRKY genes. The obtained results will bestow insight into the functional characterization of WRKY transcription factors responsive to leaf rust pathogenesis that can be used as candidate genes in molecular breeding programs to improve biotic stress tolerance in wheat.

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

PubMed

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

2012-09-01

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

Analysis of Factors Influencing Creative Personality of Elementary School Students

ERIC Educational Resources Information Center

Park, Jongman; Kim, Minkee; Jang, Shinho

2017-01-01

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

Generalized five-dimensional dynamic and spectral factor analysis

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

El Fakhri, Georges; Sitek, Arkadiusz; Zimmerman, Robert E.

2006-04-15

We have generalized the spectral factor analysis and the factor analysis of dynamic sequences (FADS) in SPECT imaging to a five-dimensional general factor analysis model (5D-GFA), where the five dimensions are the three spatial dimensions, photon energy, and time. The generalized model yields a significant advantage in terms of the ratio of the number of equations to that of unknowns in the factor analysis problem in dynamic SPECT studies. We solved the 5D model using a least-squares approach. In addition to the traditional non-negativity constraints, we constrained the solution using a priori knowledge of both time and energy, assuming thatmore » primary factors (spectra) are Gaussian-shaped with full-width at half-maximum equal to gamma camera energy resolution. 5D-GFA was validated in a simultaneous pre-/post-synaptic dual isotope dynamic phantom study where {sup 99m}Tc and {sup 123}I activities were used to model early Parkinson disease studies. 5D-GFA was also applied to simultaneous perfusion/dopamine transporter (DAT) dynamic SPECT in rhesus monkeys. In the striatal phantom, 5D-GFA yielded significantly more accurate and precise estimates of both primary {sup 99m}Tc (bias=6.4%{+-}4.3%) and {sup 123}I (-1.7%{+-}6.9%) time activity curves (TAC) compared to conventional FADS (biases=15.5%{+-}10.6% in {sup 99m}Tc and 8.3%{+-}12.7% in {sup 123}I, p<0.05). Our technique was also validated in two primate dynamic dual isotope perfusion/DAT transporter studies. Biases of {sup 99m}Tc-HMPAO and {sup 123}I-DAT activity estimates with respect to estimates obtained in the presence of only one radionuclide (sequential imaging) were significantly lower with 5D-GFA (9.4%{+-}4.3% for {sup 99m}Tc-HMPAO and 8.7%{+-}4.1% for {sup 123}I-DAT) compared to biases greater than 15% for volumes of interest (VOI) over the reconstructed volumes (p<0.05). 5D-GFA is a novel and promising approach in dynamic SPECT imaging that can also be used in other modalities. It allows accurate and

[Factors affecting maternal physical activities: an analysis based on the structural equation modeling].

PubMed

Liu, Yi; Luo, Bi-Ru

2016-11-20

To analyze the factors affecting maternal physical activities at different stages among pregnant women. Self-designed questionnaires were used to investigate the physical activities of women in different stages, including 650 in the first, 650 in the second, and 750 in the third trimester of pregnancy. The factors affecting maternal physical activities were analyzed using the structural equation model that comprised 4 latent variables (attitude, norm, behavioral attention and behavior) with observed variables that matched the latent variables. The participants ranged from 18 to 35 years of age. The women and their husbands, but not their mothers or mothers-in-law, were all well educated. The caregiver during pregnancy was mostly the mother followed by the husband. For traveling, the women in the first, second and third trimesters preferred walking, bus, and personal escort, respectively; the main physical activity was walking in all trimesters, and the women in different trimester were mostly sedentary, a greater intensity of exercise was associated with less exercise time. Structural equation modeling (SEM) analysis showed that the physical activities of pregnant women was affected by behavioral intention (with standardized regression coefficient of 0.372); attitude and subjective norms affected physical activity by indirectly influencing the behavior intention (standardized regression coefficients of 0.140 and 0.669). The pregnant women in different stages have inappropriate physical activities with insufficient exercise time and intensity. The subjective norms affects the physical activities of the pregnant women by influencing their attitudes and behavior intention indirectly, suggesting the need of health education of the caregivers during pregnancy.

49 CFR Appendix D to Part 172 - Rail Risk Analysis Factors

Code of Federal Regulations, 2011 CFR

2011-10-01

... 49 Transportation 2 2011-10-01 2011-10-01 false Rail Risk Analysis Factors D Appendix D to Part... REQUIREMENTS, AND SECURITY PLANS Pt. 172, App. D Appendix D to Part 172—Rail Risk Analysis Factors A. This... safety and security risk analyses required by § 172.820. The risk analysis to be performed may be...

49 CFR Appendix D to Part 172 - Rail Risk Analysis Factors

Code of Federal Regulations, 2010 CFR

2010-10-01

... 49 Transportation 2 2010-10-01 2010-10-01 false Rail Risk Analysis Factors D Appendix D to Part... REQUIREMENTS, AND SECURITY PLANS Pt. 172, App. D Appendix D to Part 172—Rail Risk Analysis Factors A. This... safety and security risk analyses required by § 172.820. The risk analysis to be performed may be...

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

PubMed

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

2011-12-01

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

The significance of alternative transcripts for Caenorhabditis elegans transcription factor genes, based on expression pattern analysis

PubMed Central

2013-01-01

Background Sequence-specific DNA-binding proteins, with their paramount importance in the regulation of expression of the genetic material, are encoded by approximately 5% of the genes in an animal’s genome. But it is unclear to what extent alternative transcripts from these genes may further increase the complexity of the transcription factor complement. Results Of the 938 potential C. elegans transcription factor genes, 197 were annotated in WormBase as encoding at least two distinct isoforms. Evaluation of prior evidence identified, with different levels of confidence, 50 genes with alternative transcript starts, 23 with alternative transcript ends, 35 with alternative splicing and 34 with alternative transcripts generated by a combination of mechanisms, leaving 55 that were discounted. Expression patterns were determined for transcripts for a sample of 29 transcription factor genes, concentrating on those with alternative transcript starts for which the evidence was strongest. Seamless fosmid recombineering was used to generate reporter gene fusions with minimal modification to assay expression of specific transcripts while maintaining the broad genomic DNA context and alternative transcript production. Alternative transcription factor gene transcripts were typically expressed with identical or substantially overlapping distributions rather than in distinct domains. Conclusions Increasingly sensitive sequencing technologies will reveal rare transcripts but many of these are clearly non-productive. The majority of the transcription factor gene alternative transcripts that are productive may represent tolerable noise rather than encoding functionally distinct isoforms. PMID:23586691

Spousal Violence in 5 Transitional Countries: A Population-Based Multilevel Analysis of Individual and Contextual Factors

PubMed Central

2015-01-01

Objectives. I examined the individual- and community-level factors associated with spousal violence in post-Soviet countries. Methods. I used population-based data from the Demographic and Health Survey conducted between 2005 and 2012. My sample included currently married women of reproductive age (n = 3932 in Azerbaijan, n = 4053 in Moldova, n = 1932 in Ukraine, n = 4361 in Kyrgyzstan, and n = 4093 in Tajikistan). I selected respondents using stratified multistage cluster sampling. Because of the nested structure of the data, multilevel logistic regressions for survey data were fitted to examine factors associated with spousal violence in the last 12 months. Results. Partner’s problem drinking was the strongest risk factor associated with spousal violence in all 5 countries. In Moldova, Ukraine, and Kyrgyzstan, women with greater financial power than their spouses were more likely to experience violence. Effects of community economic deprivation and of empowerment status of women in the community on spousal violence differed across countries. Women living in communities with a high tolerance of violence faced a higher risk of spousal violence in Moldova and Ukraine. In more traditional countries (Azerbaijan, Kyrgyzstan, and Tajikistan), spousal violence was lower in conservative communities with patriarchal gender beliefs or higher financial dependency on husbands. Conclusions. My findings underscore the importance of examining individual risk factors in the context of community-level factors and developing individual- and community-level interventions. PMID:26378858

The impact of chimerism in DNA-based forensic sex determination analysis.

PubMed

George, Renjith; Donald, Preethy Mary; Nagraj, Sumanth Kumbargere; Idiculla, Jose Joy; Hj Ismail, Rashid

2013-01-01

Sex determination is the most important step in personal identification in forensic investigations. DNA-based sex determination analysis is comparatively more reliable than the other conventional methods of sex determination analysis. Advanced technology like real-time polymerase chain reaction (PCR) offers accurate and reproducible results and is at the level of legal acceptance. But still there are situations like chimerism where an individual possess both male and female specific factors together in their body. Sex determination analysis in such cases can give erroneous results. This paper discusses the phenomenon of chimerism and its impact on sex determination analysis in forensic investigations.

Risk factors for Cryptosporidium infection in low and middle income countries: A systematic review and meta-analysis.

PubMed

Bouzid, Maha; Kintz, Erica; Hunter, Paul R

2018-06-07

Cryptosporidium infection causes gastrointestinal disease and has a worldwide distribution. The highest burden is in developing countries. We sought to conduct a systematic review and meta-analysis to identify Cryptosporidium risk factors in Low and Middle Income countries (LMICs). Medline Ovid and Scopus databases were searched with no restriction on year or language of publication. All references were screened independently in duplicate and were included if they presented data on at least 3 risk factors. Meta-analyses using random effects models were used to calculate overall estimates for each exposure. The most frequently reported risk factors in the 15 included studies were overcrowding, household diarrhoea, poor quality drinking water, animal contact, open defecation/ lack of toilet and breastfeeding. The combined odds ratio for animal contact was 1.98 (95%CI: 1.11-3.54) based on 11 studies and for diarrhoea in the household 1.98 (95%CI: 1.13-3.49) based on 4 studies. Open defecation was associated with a pooled odds ratio of 1.82 (95%CI: 1.19-2.8) based on 5 studies. Poor drinking water quality was not associated with a significant Cryptosporidium risk, odds ratio 1.06 (95%CI: 0.77-1.47). Breastfeeding was protective with pooled odds ratio 0.4 (95%CI: 0.13-1.22), which was not statistically significant. Based on the included studies, crowded living conditions, animal contact and open defecation are responsible for the majority of Cryptosporidium cases in LMICs. Future studies investigating Cryptosporidium risk factors should have a good study design and duration, include appropriate number of cases, select suitable controls, investigate multiple relevant risk factors, fully report data and perform multivariate analysis.

Examining evolving performance on the Force Concept Inventory using factor analysis

NASA Astrophysics Data System (ADS)

Semak, M. R.; Dietz, R. D.; Pearson, R. H.; Willis, C. W.

2017-06-01

The application of factor analysis to the Force Concept Inventory (FCI) has proven to be problematic. Some studies have suggested that factor analysis of test results serves as a helpful tool in assessing the recognition of Newtonian concepts by students. Other work has produced at best ambiguous results. For the FCI administered as a pre- and post-test, we see factor analysis as a tool by which the changes in conceptual associations made by our students may be gauged given the evolution of their response patterns. This analysis allows us to identify and track conceptual linkages, affording us insight as to how our students have matured due to instruction. We report on our analysis of 427 pre- and post-tests. The factor models for the pre- and post-tests are explored and compared along with the methodology by which these models were fit to the data. The post-test factor pattern is more aligned with an expert's interpretation of the questions' content, as it allows for a more readily identifiable relationship between factors and physical concepts. We discuss this evolution in the context of approaching the characteristics of an expert with force concepts. Also, we find that certain test items do not significantly contribute to the pre- or post-test factor models and attempt explanations as to why this is so. This may suggest that such questions may not be effective in probing the conceptual understanding of our students.

Assessment of awareness of connectedness as a culturally-based protective factor for Alaska native youth.

PubMed

Mohatt, Nathaniel V; Fok, Carlotta Ching Ting; Burket, Rebekah; Henry, David; Allen, James

2011-10-01

Research with Native Americans has identified connectedness as a culturally based protective factor against substance abuse and suicide. Connectedness refers to the interrelated welfare of the individual, one's family, one's community, and the natural environment. We developed an 18-item quantitative assessment of awareness of connectedness and tested it with 284 Alaska Native youth. Evaluation with confirmatory factor analysis and item response theory identified a 12-item subset that functions satisfactorily in a second-order four-factor model. The proposed Awareness of Connectedness Scale (ACS) displays good convergent and discriminant validity, and correlates positively with hypothesized protective factors such as reasons for living and communal mastery. The measure has utility in the study of culture-specific protective factors and as an outcomes measure for behavioral health programs with Native American youth.

Assessment of Awareness of Connectedness as a Culturally-based Protective Factor for Alaska Native Youth

PubMed Central

Mohatt, Nathaniel V.; Fok, Carlotta Ching Ting; Burket, Rebekah; Henry, David; Allen, James

2011-01-01

Research with Native Americans has identified connectedness as a culturally-based protective factor against substance abuse and suicide. Connectedness refers to the interrelated welfare of the individual, one’s family, one’s community, and the natural environment. We developed an 18-item quantitative assessment of awareness of connectedness and tested it with 284 Alaska Native youth. Evaluation with confirmatory factor analysis and item response theory identified a 12-item subset that functions satisfactorily in a second-order, four-factor model. The proposed Awareness of Connectedness Scale displays good convergent and discriminant validity and correlates positively with hypothesized protective factors such as reasons for living and communal mastery. The measure has utility in the study of culture-specific protective factors and as an outcomes measure for behavioral health programs with Native American youth. PMID:21988583

Confirmatory factor analysis using Microsoft Excel.

PubMed

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.

Factors influencing the demand of the service of community based animal health care in Zimbabwe.

PubMed

Mutambara, J; Dube, I; Matangi, E; Majeke, F

2013-11-01

This study was done to find out about animal health service providers and factors that determined demand for community based veterinary service delivery in smallholder sector of Zimbabwe. Focus group discussions and a questionnaire was used to collect data on veterinary services providers and socio-economic factors related to animal health from a sample (N=333) smallholder livestock farmers from Gutu district of Masvingo province in Zimbabwe. Analytical techniques used were descriptive statistics, K-mean cluster analysis and Tobit regression model. Results showed that the majority of farmers (45%) obtained services from both Community Based Animal Health Workers (CBAHWs) and Department of Veterinary Service (DVS), 25% DVS only, 20% used CBAHWs while 10% did not seek any services. Further analysis showed that distance to CBAHW, distance to AHMC and employment status were significantly related to demand for CBAHWs with coefficients of -1.5, 0.7 and -10.3, respectively. The study thus concluded that CBAHW is an alternative animal health service delivery approach already practiced in smallholder farming sectors of Zimbabwe. Socio-economic factors significantly influenced the demand for CBAHW services. Given limited resources by state sponsored veterinary services, it is recommended that the CBAHWs approach should be encouraged as supplementary service provider especially in areas further DVS. These community organizations can be empowered by the state to deliver more improved services based on hygiene and modern science at a relatively low cost to farmers. Copyright © 2013 Elsevier B.V. All rights reserved.

Eating Behaviour in the General Population: An Analysis of the Factor Structure of the German Version of the Three-Factor-Eating-Questionnaire (TFEQ) and Its Association with the Body Mass Index

PubMed Central

Löffler, Antje; Luck, Tobias; Then, Francisca S.; Sikorski, Claudia; Kovacs, Peter; Böttcher, Yvonne; Breitfeld, Jana; Tönjes, Anke; Horstmann, Annette; Löffler, Markus; Engel, Christoph; Thiery, Joachim; Villringer, Arno; Stumvoll, Michael; Riedel-Heller, Steffi G.

2015-01-01

The Three-Factor-Eating-Questionnaire (TFEQ) is an established instrument to assess eating behaviour. Analysis of the TFEQ-factor structure was based on selected, convenient and clinical samples so far. Aims of this study were (I) to analyse the factor structure of the German version of the TFEQ and (II)—based on the refined factor structure—to examine the association between eating behaviour and the body mass index (BMI) in a general population sample of 3,144 middle-aged and older participants (40–79 years) of the ongoing population based cohort study of the Leipzig Research Center for Civilization Diseases (LIFE Health Study). The factor structure was examined in a split-half analysis with both explorative and confirmatory factor analysis. Associations between TFEQ-scores and BMI values were tested with multiple regression analyses controlled for age, gender, and education. We found a three factor solution for the TFEQ with an ‘uncontrolled eating’, a ‘cognitive restraint’ and an ‘emotional eating’ domain including 29 of the original 51 TFEQ-items. Scores of the ‘uncontrolled eating domain’ showed the strongest correlation with BMI values (partial r = 0.26). Subjects with scores above the median in both ‘uncontrolled eating’ and ‘emotional eating’ showed the highest BMI values (mean = 29.41 kg/m²), subjects with scores below the median in all three domains showed the lowest BMI values (mean = 25.68 kg/m²; F = 72.074, p<0.001). Our findings suggest that the TFEQ is suitable to identify subjects with specific patterns of eating behaviour that are associated with higher BMI values. Such information may help health care professionals to develop and implement more tailored interventions for overweight and obese individuals. PMID:26230264

Evolution of chemical-specific adjustment factors (CSAF) based on recent international experience; increasing utility and facilitating regulatory acceptance.

PubMed

Bhat, Virunya S; Meek, M E Bette; Valcke, Mathieu; English, Caroline; Boobis, Alan; Brown, Richard

2017-10-01

The application of chemical-specific toxicokinetic or toxicodynamic data to address interspecies differences and human variability in the quantification of hazard has potential to reduce uncertainty and better characterize variability compared with the use of traditional default or categorically-based uncertainty factors. The present review summarizes the state-of-the-science since the introduction of the World Health Organization/International Programme on Chemical Safety (WHO/IPCS) guidance on chemical-specific adjustment factors (CSAF) in 2005 and the availability of recent applicable guidance including the WHO/IPCS guidance on physiologically-based pharmacokinetic (PBPK) modeling in 2010 as well as the U.S. EPA guidance on data-derived extrapolation factors in 2014. A summary of lessons learned from an analysis of more than 100 case studies from global regulators or published literature illustrates the utility and evolution of CSAF in regulatory decisions. Challenges in CSAF development related to the adequacy of, or confidence in, the supporting data, including verification or validation of PBPK models. The analysis also identified issues related to adequacy of CSAF documentation, such as inconsistent terminology and often limited and/or inconsistent reporting, of both supporting data and/or risk assessment context. Based on this analysis, recommendations for standardized terminology, documentation and relevant interdisciplinary research and engagement are included to facilitate the continuing evolution of CSAF development and guidance.

Prognostic Factors in Amyotrophic Lateral Sclerosis: A Population-Based Study.

PubMed

Moura, Mirian Conceicao; Novaes, Maria Rita Carvalho Garbi; Eduardo, Emanoel Junio; Zago, Yuri S S P; Freitas, Ricardo Del Negro Barroso; Casulari, Luiz Augusto

2015-01-01

To determine the prognostic factors associated with survival in amyotrophic lateral sclerosis at diagnosis. This retrospective population-based study evaluated 218 patients treated with riluzole between 2005 and 2014 and described their clinical and demographic profiles after the analysis of clinical data and records from the mortality information system in the Federal District, Brazil. Cox multivariate regression analysis was conducted for the parameters found. The study sample consisted of 132 men and 86 women with a mean age at disease onset of 57.2±12.3 years; 77.6% of them were Caucasian. The mean periods between disease onset and diagnosis were 22.7 months among men and 23.5 months among women, and the mean survival periods were 45.7±47.0 months among men and 39.3±29.8 months among women. In addition, 80.3% patients presented non-bulbar-onset amyotrophic lateral sclerosis, and 19.7% presented bulbar-onset. Cox regression analysis indicated worse prognosis for body mass index (BMI) <25 kg/m2 (relative risk [RR]: 3.56, 95% confidence interval [CI]: 1.44-8.86), age >75 years (RR: 12.47, 95% CI: 3.51-44.26), and bulbar-onset (RR: 4.56, 95% CI: 2.06-10.12). Electromyography did not confirm the diagnosis in 55.6% of the suspected cases and in 27.9% of the bulbar-onset cases. The factors associated with lower survival in amyotrophic lateral sclerosis were age >75 years, BMI <25 kg/m2, and bulbar-onset.

Prognostic Factors in Amyotrophic Lateral Sclerosis: A Population-Based Study

PubMed Central

Moura, Mirian Conceicao; Novaes, Maria Rita Carvalho Garbi; Eduardo, Emanoel Junio; Zago, Yuri S. S. P.; Freitas, Ricardo Del Negro Barroso; Casulari, Luiz Augusto

2015-01-01

Objective To determine the prognostic factors associated with survival in amyotrophic lateral sclerosis at diagnosis. Methods This retrospective population-based study evaluated 218 patients treated with riluzole between 2005 and 2014 and described their clinical and demographic profiles after the analysis of clinical data and records from the mortality information system in the Federal District, Brazil. Cox multivariate regression analysis was conducted for the parameters found. Results The study sample consisted of 132 men and 86 women with a mean age at disease onset of 57.2±12.3 years; 77.6% of them were Caucasian. The mean periods between disease onset and diagnosis were 22.7 months among men and 23.5 months among women, and the mean survival periods were 45.7±47.0 months among men and 39.3±29.8 months among women. In addition, 80.3% patients presented non-bulbar-onset amyotrophic lateral sclerosis, and 19.7% presented bulbar-onset. Cox regression analysis indicated worse prognosis for body mass index (BMI) <25 kg/m2 (relative risk [RR]: 3.56, 95% confidence interval [CI]: 1.44–8.86), age >75 years (RR: 12.47, 95% CI: 3.51–44.26), and bulbar-onset (RR: 4.56, 95% CI: 2.06–10.12). Electromyography did not confirm the diagnosis in 55.6% of the suspected cases and in 27.9% of the bulbar-onset cases. Conclusions The factors associated with lower survival in amyotrophic lateral sclerosis were age >75 years, BMI <25 kg/m2, and bulbar-onset. PMID:26517122

Sleep disturbances as an evidence-based suicide risk factor.

PubMed

Bernert, Rebecca A; Kim, Joanne S; Iwata, Naomi G; Perlis, Michael L

2015-03-01

Increasing research indicates that sleep disturbances may confer increased risk for suicidal behaviors, including suicidal ideation, suicide attempts, and death by suicide. Despite increased investigation, a number of methodological problems present important limitations to the validity and generalizability of findings in this area, which warrant additional focus. To evaluate and delineate sleep disturbances as an evidence-based suicide risk factor, a systematic review of the extant literature was conducted with methodological considerations as a central focus. The following methodologic criteria were required for inclusion: the report (1) evaluated an index of sleep disturbance; (2) examined an outcome measure for suicidal behavior; (3) adjusted for presence of a depression diagnosis or depression severity, as a covariate; and (4) represented an original investigation as opposed to a chart review. Reports meeting inclusion criteria were further classified and reviewed according to: study design and timeframe; sample type and size; sleep disturbance, suicide risk, and depression covariate assessment measure(s); and presence of positive versus negative findings. Based on keyword search, the following search engines were used: PubMed and PsycINFO. Search criteria generated N = 82 articles representing original investigations focused on sleep disturbances and suicide outcomes. Of these, N = 18 met inclusion criteria for review based on systematic analysis. Of the reports identified, N = 18 evaluated insomnia or poor sleep quality symptoms, whereas N = 8 assessed nightmares in association with suicide risk. Despite considerable differences in study designs, samples, and assessment techniques, the comparison of such reports indicates preliminary, converging evidence for sleep disturbances as an empirical risk factor for suicidal behaviors, while highlighting important, future directions for increased investigation.

A multivariate analysis of clinical and morphological prognostic factors in squamous cell carcinoma of the vulva.

PubMed

Smyczek-Gargya, B; Volz, B; Geppert, M; Dietl, J

1997-01-01

Clinical and histological data of 168 patients with squamous cell carcinoma of the vulva were analyzed with respect to survival. 151 patients underwent surgery, 12 patients were treated with primary radiation and in 5 patients no treatment was performed. Follow-up lasted from at least 2 up to 22 years' posttreatment. In univariate analysis, the following factors were highly significant: presurgery lymph node status, tumor infiltration beyond the vulva, tumor grading, histological inguinal lymph node status, pre- and postsurgery tumor stage, depth of invasion and tumor diameter. In the multivariate analysis (Cox regression), the most powerful factors were shown to be histological inguinal lymph node status, tumor diameter and tumor grading. The multivariate logistic regression analysis worked out as main prognostic factors for metastases of inguinal lymph nodes: presurgery inguinal lymph node status, tumor size, depth of invasion and tumor grading. Based on these results, tumor biology seems to be the decisive factor concerning recurrence and survival. Therefore, we suggest a more conservative treatment of vulvar carcinoma. Patients with confined carcinoma to the vulva, with a tumor diameter up to 3 cm and without clinical suspected lymph nodes, should be treated by wide excision/partial vulvectomy with ipsilateral lymphadenectomy.

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

PubMed

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.

[Analysis of virulence factors of Porphyromonas endodontalis based on comparative proteomics technique].

PubMed

Li, H; Ji, H; Wu, S S; Hou, B X

2016-12-09

Objective: To analyze the protein expression profile and the potential virulence factors of Porphyromonas endodontalis (Pe) via comparison with that of two strains of Porphyromonas gingivalis (Pg) with high and low virulences, respectively. Methods: Whole cell comparative proteomics of Pe ATCC35406 was examined and compared with that of high virulent strain Pg W83 andlow virulent strain Pg ATCC33277, respectively. Isobaric tags for relative and absolute quantitation (iTRAQ) combined with nano liquid chromatography-tandem mass spectrometry (Nano-LC-MS/MS) were adopted to identify and quantitate the proteins of Pe and two strains of Pg with various virulences by using the methods of isotopically labeled peptides, mass spectrometric detection and bioinformatics analysis. The biological functions of similar proteins expressed by Pe ATCC35406 and two strains of Pg were quantified and analyzed. Results: Totally 1 210 proteins were identified while Pe compared with Pg W83. There were 130 proteins (10.74% of the total proteins) expressed similarly, including 89 known functional proteins and 41 proteins of unknown functions. Totally 1 223 proteins were identified when Pe compared with Pg ATCC33277. There were 110 proteins (8.99% of the total proteins) expressed similarly, including 72 known functional proteins and 38 proteins of unknown functions. The similarly expressed proteins in Pe and Pg strains with various virulences mainly focused on catalytic activity and binding function, including recombination activation gene (RagA), lipoprotein, chaperonin Dnak, Clp family proteins (ClpC and ClpX) and various iron-binding proteins. They were involved in metabolism and cellular processes. In addition, the type and number of similar virulence proteins between Pe and high virulence Pg were higher than those between Pe and low virulence Pg. Conclusions: Lipoprotein, oxygen resistance protein, iron binding protein were probably the potential virulence factors of Pe ATCC35406. It was

Use of Language Sample Analysis by School-Based SLPs: Results of a Nationwide Survey

ERIC Educational Resources Information Center

Pavelko, Stacey L.; Owens, Robert E., Jr.; Ireland, Marie; Hahs-Vaughn, Debbie L.

2016-01-01

Purpose: This article examines use of language sample analysis (LSA) by school-based speech-language pathologists (SLPs), including characteristics of language samples, methods of transcription and analysis, barriers to LSA use, and factors affecting LSA use, such as American Speech-Language-Hearing Association certification, number of years'…

Exploratory factor analysis of borderline personality disorder criteria in hospitalized adolescents.

PubMed

Becker, Daniel F; McGlashan, Thomas H; Grilo, Carlos M

2006-01-01

The authors examined the factor structure of borderline personality disorder (BPD) in hospitalized adolescents and also sought to add to the theoretical and clinical understanding of any homogeneous components by determining whether they may be related to specific forms of Axis I pathology. Subjects were 123 adolescent inpatients, who were reliably assessed with structured diagnostic interviews for Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition Axes I and II disorders. Exploratory factor analysis identified BPD components, and logistic regression analyses tested whether these components were predictive of specific Axis I disorders. Factor analysis revealed a 4-factor solution that accounted for 67.0% of the variance. Factor 1 ("suicidal threats or gestures" and "emptiness or boredom") predicted depressive disorders and alcohol use disorders. Factor 2 ("affective instability," "uncontrolled anger," and "identity disturbance") predicted anxiety disorders and oppositional defiant disorder. Factor 3 ("unstable relationships" and "abandonment fears") predicted only anxiety disorders. Factor 4 ("impulsiveness" and "identity disturbance") predicted conduct disorder and substance use disorders. Exploratory factor analysis of BPD criteria in adolescent inpatients revealed 4 BPD factors that appear to differ from those reported for similar studies of adults. The factors represent components of self-negation, irritability, poorly modulated relationships, and impulsivity--each of which is associated with characteristic Axis I pathology. These findings shed light on the nature of BPD in adolescents and may also have implications for treatment.

Exploratory factor analysis of the Oral Health Impact Profile.

PubMed

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

2014-09-01

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

Factor analysis of an instrument to measure the impact of disease on daily life.

PubMed

Pedrosa, Rafaela Batista Dos Santos; Rodrigues, Roberta Cunha Matheus; Padilha, Kátia Melissa; Gallani, Maria Cecília Bueno Jayme; Alexandre, Neusa Maria Costa

2016-01-01

to verify the structure of factors of an instrument to measure the Heart Valve Disease Impact on Daily Life (IDCV) when applied to coronary artery disease patients. the study included 153 coronary artery disease patients undergoing outpatient follow-up care. The IDCV structure of factors was initially assessed by means of confirmatory factor analysis and, subsequently, by exploratory factor analysis. The Varimax rotation method was used to estimate the main components of analysis, eigenvalues greater than one for extraction of factors, and factor loading greater than 0.40 for selection of items. Internal consistency was estimated using Cronbach's alpha coefficient. confirmatory factor analysis did not confirm the original structure of factors of the IDCV. Exploratory factor analysis showed three dimensions, which together explained 78% of the measurement variance. future studies with expansion of case selection are necessary to confirm the IDCV new structure of factors.

Human Factors Considerations for Performance-Based Navigation

NASA Technical Reports Server (NTRS)

Barhydt, Richard; Adams, Catherine A.

2006-01-01

A transition toward a performance-based navigation system is currently underway in both the United States and around the world. Performance-based navigation incorporates Area Navigation (RNAV) and Required Navigation Performance (RNP) procedures that do not rely on the location of ground-based navigation aids. These procedures offer significant benefits to both operators and air traffic managers. Under sponsorship from the Federal Aviation Administration (FAA), the National Aeronautics and Space Administration (NASA) has undertaken a project to document human factors issues that have emerged during RNAV and RNP operations and propose areas for further consideration. Issues were found to include aspects of air traffic control and airline procedures, aircraft systems, and procedure design. Major findings suggest the need for human factors-specific instrument procedure design guidelines. Ongoing industry and government activities to address air-ground communication terminology, procedure design improvements, and chart-database commonality are strongly encouraged.

a Buffer Analysis Based on Co-Location Algorithm

NASA Astrophysics Data System (ADS)

Zhou, G.; Huang, S.; Wang, H.; Zhang, R.; Wang, Q.; Sha, H.; Liu, X.; Pan, Q.

2018-05-01

Buffer analysis is a common tool of spatial analysis, which deals with the problem of proximity in GIS. Buffer analysis researches the relationship between the center object and other objects around a certain distance. Buffer analysis can make the complicated problem be more scientifically and visually, and provide valuable information for users. Over the past decades, people have done a lot of researches on buffer analysis. Along with the constantly improvement of spatial analysis accuracy needed by people, people hope that the results of spatial analysis can be more exactly express the actual situation. Due to the influence of some certain factors, the impact scope and contact range of a geographic elements on the surrounding objects are uncertain. As all we know, each object has its own characteristics and changing rules in the nature. They are both independent and relative to each other. However, almost all the generational algorithms of existing buffer analysis are based on fixed buffer distance, which do not consider the co-location relationship among instances. Consequently, it is a waste of resource to retrieve the useless information, and useful information is ignored.

Profiling the different needs and expectations of patients for population-based medicine: a case study using segmentation analysis

PubMed Central

2012-01-01

Background This study illustrates an evidence-based method for the segmentation analysis of patients that could greatly improve the approach to population-based medicine, by filling a gap in the empirical analysis of this topic. Segmentation facilitates individual patient care in the context of the culture, health status, and the health needs of the entire population to which that patient belongs. Because many health systems are engaged in developing better chronic care management initiatives, patient profiles are critical to understanding whether some patients can move toward effective self-management and can play a central role in determining their own care, which fosters a sense of responsibility for their own health. A review of the literature on patient segmentation provided the background for this research. Method First, we conducted a literature review on patient satisfaction and segmentation to build a survey. Then, we performed 3,461 surveys of outpatient services users. The key structures on which the subjects’ perception of outpatient services was based were extrapolated using principal component factor analysis with varimax rotation. After the factor analysis, segmentation was performed through cluster analysis to better analyze the influence of individual attitudes on the results. Results Four segments were identified through factor and cluster analysis: the “unpretentious,” the “informed and supported,” the “experts” and the “advanced” patients. Their policies and managerial implications are outlined. Conclusions With this research, we provide the following: – a method for profiling patients based on common patient satisfaction surveys that is easily replicable in all health systems and contexts; – a proposal for segments based on the results of a broad-based analysis conducted in the Italian National Health System (INHS). Segments represent profiles of patients requiring different strategies for delivering health services. Their

A human factors analysis of EVA time requirements

NASA Technical Reports Server (NTRS)

Pate, D. W.

1996-01-01

Human Factors Engineering (HFE), also known as Ergonomics, is a discipline whose goal is to engineer a safer, more efficient interface between humans and machines. HFE makes use of a wide range of tools and techniques to fulfill this goal. One of these tools is known as motion and time study, a technique used to develop time standards for given tasks. A human factors motion and time study was initiated with the goal of developing a database of EVA task times and a method of utilizing the database to predict how long an ExtraVehicular Activity (EVA) should take. Initial development relied on the EVA activities performed during the STS-61 mission (Hubble repair). The first step of the analysis was to become familiar with EVAs and with the previous studies and documents produced on EVAs. After reviewing these documents, an initial set of task primitives and task time modifiers was developed. Videotaped footage of STS-61 EVAs were analyzed using these primitives and task time modifiers. Data for two entire EVA missions and portions of several others, each with two EVA astronauts, was collected for analysis. Feedback from the analysis of the data will be used to further refine the primitives and task time modifiers used. Analysis of variance techniques for categorical data will be used to determine which factors may, individually or by interactions, effect the primitive times and how much of an effect they have.

Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

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

Stevens, Andrew J.; Pu, Yunchen; Sun, Yannan

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-rankmore » impacts both overcompleteness and sparsity.« less

Analysis of algae growth mechanism and water bloom prediction under the effect of multi-affecting factor.

PubMed

Wang, Li; Wang, Xiaoyi; Jin, Xuebo; Xu, Jiping; Zhang, Huiyan; Yu, Jiabin; Sun, Qian; Gao, Chong; Wang, Lingbin

2017-03-01

The formation process of algae is described inaccurately and water blooms are predicted with a low precision by current methods. In this paper, chemical mechanism of algae growth is analyzed, and a correlation analysis of chlorophyll-a and algal density is conducted by chemical measurement. Taking into account the influence of multi-factors on algae growth and water blooms, the comprehensive prediction method combined with multivariate time series and intelligent model is put forward in this paper. Firstly, through the process of photosynthesis, the main factors that affect the reproduction of the algae are analyzed. A compensation prediction method of multivariate time series analysis based on neural network and Support Vector Machine has been put forward which is combined with Kernel Principal Component Analysis to deal with dimension reduction of the influence factors of blooms. Then, Genetic Algorithm is applied to improve the generalization ability of the BP network and Least Squares Support Vector Machine. Experimental results show that this method could better compensate the prediction model of multivariate time series analysis which is an effective way to improve the description accuracy of algae growth and prediction precision of water blooms.

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

ERIC Educational Resources Information Center

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,…

Confirmatory factor analysis applied to the Force Concept Inventory

NASA Astrophysics Data System (ADS)

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.

The impact of clinical, demographic and risk factors on rates of HIV transmission: a population-based phylogenetic analysis in British Columbia, Canada.

PubMed

Poon, Art F Y; Joy, Jeffrey B; Woods, Conan K; Shurgold, Susan; Colley, Guillaume; Brumme, Chanson J; Hogg, Robert S; Montaner, Julio S G; Harrigan, P Richard

2015-03-15

The diversification of human immunodeficiency virus (HIV) is shaped by its transmission history. We therefore used a population based province wide HIV drug resistance database in British Columbia (BC), Canada, to evaluate the impact of clinical, demographic, and behavioral factors on rates of HIV transmission. We reconstructed molecular phylogenies from 27,296 anonymized bulk HIV pol sequences representing 7747 individuals in BC-about half the estimated HIV prevalence in BC. Infections were grouped into clusters based on phylogenetic distances, as a proxy for variation in transmission rates. Rates of cluster expansion were reconstructed from estimated dates of HIV seroconversion. Our criteria grouped 4431 individuals into 744 clusters largely separated with respect to risk factors, including large established clusters predominated by injection drug users and more-recently emerging clusters comprising men who have sex with men. The mean log10 viral load of an individual's phylogenetic neighborhood (composed of 5 other individuals with shortest phylogenetic distances) increased their odds of appearing in a cluster by >2-fold per log10 viruses per milliliter. Hotspots of ongoing HIV transmission can be characterized in near real time by the secondary analysis of HIV resistance genotypes, providing an important potential resource for targeting public health initiatives for HIV prevention. © The Author 2014. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

ERIC Educational Resources Information Center

Knight, Jennifer L.

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

Quantitative Analysis of Critical Factors for the Climate Impact of Landfill Mining.

PubMed

Laner, David; Cencic, Oliver; Svensson, Niclas; Krook, Joakim

2016-07-05

Landfill mining has been proposed as an innovative strategy to mitigate environmental risks associated with landfills, to recover secondary raw materials and energy from the deposited waste, and to enable high-valued land uses at the site. The present study quantitatively assesses the importance of specific factors and conditions for the net contribution of landfill mining to global warming using a novel, set-based modeling approach and provides policy recommendations for facilitating the development of projects contributing to global warming mitigation. Building on life-cycle assessment, scenario modeling and sensitivity analysis methods are used to identify critical factors for the climate impact of landfill mining. The net contributions to global warming of the scenarios range from -1550 (saving) to 640 (burden) kg CO2e per Mg of excavated waste. Nearly 90% of the results' total variation can be explained by changes in four factors, namely the landfill gas management in the reference case (i.e., alternative to mining the landfill), the background energy system, the composition of the excavated waste, and the applied waste-to-energy technology. Based on the analyses, circumstances under which landfill mining should be prioritized or not are identified and sensitive parameters for the climate impact assessment of landfill mining are highlighted.

Educating the ambulance technician, paramedic, and clinical supervisor: using factor analysis to inform the curriculum

PubMed Central

Kilner, T

2004-01-01

Methods: Data generated by a Delphi study investigating the desirable attributes of ambulance technician, paramedic, and clinical supervisor were subject to factor analysis to explore inter-relations between the variables or desirable attributes. Variables that loaded onto any factor at a correlation level of >0.3 were included in the analysis. Results: Three factors emerged in each of the occupational groups. In respect of the ambulance technician these factors may be described as; core professional skills, individual and collaborative approaches to health and safety, and the management of self and clinical situations. For the paramedic the themes are; core professional skills, management of self and clinical situations, and approaches to health and safety. For the clinical supervisor there is again a theme described as core professional skills, with a further two themes described as role model and lifelong learning. Conclusions: The profile of desirable attributes emerging from this study are remarkably similar to the generic benchmark statements for health care programmes outlined by the Quality Assurance Agency for Higher Education. It seems that a case is emerging for a revision of the curriculum currently used for the education and training of ambulance staff, which is more suited to a consumer led health service and which reflects the broader professional base seen in programmes associated with other healthcare professions. This study has suggested outline content, and module structure for the education of the technician, paramedic, and clinical supervisor, based on empirical evidence. PMID:15107389

Using an interdisciplinary approach to identify factors that affect clinicians' compliance with evidence-based guidelines.

PubMed

Gurses, Ayse P; Marsteller, Jill A; Ozok, A Ant; Xiao, Yan; Owens, Sharon; Pronovost, Peter J

2010-08-01

Our objective was to identify factors that affect clinicians' compliance with the evidence-based guidelines using an interdisciplinary approach and develop a conceptual framework that can provide a comprehensive and practical guide for designing effective interventions. A literature review and a brainstorming session with 11 researchers from a variety of scientific disciplines were used to identify theoretical and conceptual models describing clinicians' guideline compliance. MEDLINE, EMBASE, CINAHL, and the bibliographies of the papers identified were used as data sources for identifying the relevant theoretical and conceptual models. Thirteen different models that originated from various disciplines including medicine, rural sociology, psychology, human factors and systems engineering, organizational management, marketing, and health education were identified. Four main categories of factors that affect compliance emerged from our analysis: clinician characteristics, guideline characteristics, system characteristics, and implementation characteristics. Based on these findings, we developed an interdisciplinary conceptual framework that specifies the expected interrelationships among these four categories of factors and their impact on clinicians' compliance. An interdisciplinary approach is needed to improve clinicians' compliance with evidence-based guidelines. The conceptual framework from this research can provide a comprehensive and systematic guide to identify barriers to guideline compliance and design effective interventions to improve patient safety.

SEPARABLE FACTOR ANALYSIS WITH APPLICATIONS TO MORTALITY DATA

PubMed Central

Fosdick, Bailey K.; Hoff, Peter D.

2014-01-01

Human mortality data sets can be expressed as multiway data arrays, the dimensions of which correspond to categories by which mortality rates are reported, such as age, sex, country and year. Regression models for such data typically assume an independent error distribution or an error model that allows for dependence along at most one or two dimensions of the data array. However, failing to account for other dependencies can lead to inefficient estimates of regression parameters, inaccurate standard errors and poor predictions. An alternative to assuming independent errors is to allow for dependence along each dimension of the array using a separable covariance model. However, the number of parameters in this model increases rapidly with the dimensions of the array and, for many arrays, maximum likelihood estimates of the covariance parameters do not exist. In this paper, we propose a submodel of the separable covariance model that estimates the covariance matrix for each dimension as having factor analytic structure. This model can be viewed as an extension of factor analysis to array-valued data, as it uses a factor model to estimate the covariance along each dimension of the array. We discuss properties of this model as they relate to ordinary factor analysis, describe maximum likelihood and Bayesian estimation methods, and provide a likelihood ratio testing procedure for selecting the factor model ranks. We apply this methodology to the analysis of data from the Human Mortality Database, and show in a cross-validation experiment how it outperforms simpler methods. Additionally, we use this model to impute mortality rates for countries that have no mortality data for several years. Unlike other approaches, our methodology is able to estimate similarities between the mortality rates of countries, time periods and sexes, and use this information to assist with the imputations. PMID:25489353

Detectability Factors for Earth-based Imaging of the LCROSS Ejecta Plume

NASA Astrophysics Data System (ADS)

Strycker, Paul D.; Schotte, Jonathan M.; Temme, Ruth L.; Chanover, Nancy J.

2017-10-01

NASA’s Lunar Crater Observation and Sensing Satellite (LCROSS) mission delivered a kinetic impactor into Cabeus Crater on 9 October 2009 [1, 2]. Observing campaigns from Earth-based telescopes at multiple facilities attempted to obtain temporally-resolved imaging of the ejecta plume [3], but no Earth-based imaging detections were reported until 2013 after processing images with Principal Component Analysis (PCA) filtering [4]. Subsequently, PCA filtering has revealed plume detections in two additional cameras and also confirmed a non-detection from one telescope [5, 6]. This combination of detection and non-detection data is useful in determining the criteria for detectability in future observations of transient events. The goal of this work is to identify factors contributing to detectability and to establish thresholds applicable to the LCROSS event. We take the data containing detections and then degrade a specific factor in them until the plume is no longer detectable. These derived thresholds for factors (e.g., scattered light, temporal resolution, spatial resolution, field of view, and signal-to-noise of the illuminated foreground of Cabeus) can be compared to the properties of the actual non-detection data to identify problems specific to its observing conditions or observational setup. The percent differences between the thresholds and both the detection data and non-detection data may also reveal the relative importance of these detectability factors. This work was supported by NASA’s Lunar Data Analysis Program through grant number NNX15AP92G. Observations reported here were obtained at the MMT Observatory, a joint facility of the Smithsonian Institution and the University of Arizona.References: [1] Colaprete, A. et al. (2010) Science, 330, 463-468. [2] Schultz, P. H. et al. (2010) Science, 330, 468-472. [3] Heldmann, J. L. et al. (2012) Space Sci. Rev., 167:93-140, doi:10.1007/s11214-011-9759-y. [4] Strycker, P. D. et al. (2013) Nat. Commun., 4

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Rainfall or parameter uncertainty? The power of sensitivity analysis on grouped factors

NASA Astrophysics Data System (ADS)

Nossent, Jiri; Pereira, Fernando; Bauwens, Willy

2017-04-01

Hydrological models are typically used to study and represent (a part of) the hydrological cycle. In general, the output of these models mostly depends on their input rainfall and parameter values. Both model parameters and input precipitation however, are characterized by uncertainties and, therefore, lead to uncertainty on the model output. Sensitivity analysis (SA) allows to assess and compare the importance of the different factors for this output uncertainty. Hereto, the rainfall uncertainty can be incorporated in the SA by representing it as a probabilistic multiplier. Such multiplier can be defined for the entire time series, or several of these factors can be determined for every recorded rainfall pulse or for hydrological independent storm events. As a consequence, the number of parameters included in the SA related to the rainfall uncertainty can be (much) lower or (much) higher than the number of model parameters. Although such analyses can yield interesting results, it remains challenging to determine which type of uncertainty will affect the model output most due to the different weight both types will have within the SA. In this study, we apply the variance based Sobol' sensitivity analysis method to two different hydrological simulators (NAM and HyMod) for four diverse watersheds. Besides the different number of model parameters (NAM: 11 parameters; HyMod: 5 parameters), the setup of our sensitivity and uncertainty analysis-combination is also varied by defining a variety of scenarios including diverse numbers of rainfall multipliers. To overcome the issue of the different number of factors and, thus, the different weights of the two types of uncertainty, we build on one of the advantageous properties of the Sobol' SA, i.e. treating grouped parameters as a single parameter. The latter results in a setup with a single factor for each uncertainty type and allows for a straightforward comparison of their importance. In general, the results show a clear

Fractal analysis and its impact factors on pore structure of artificial cores based on the images obtained using magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Wang, Heming; Liu, Yu; Song, Yongchen; Zhao, Yuechao; Zhao, Jiafei; Wang, Dayong

2012-11-01

Pore structure is one of important factors affecting the properties of porous media, but it is difficult to describe the complexity of pore structure exactly. Fractal theory is an effective and available method for quantifying the complex and irregular pore structure. In this paper, the fractal dimension calculated by box-counting method based on fractal theory was applied to characterize the pore structure of artificial cores. The microstructure or pore distribution in the porous material was obtained using the nuclear magnetic resonance imaging (MRI). Three classical fractals and one sand packed bed model were selected as the experimental material to investigate the influence of box sizes, threshold value, and the image resolution when performing fractal analysis. To avoid the influence of box sizes, a sequence of divisors of the image was proposed and compared with other two algorithms (geometric sequence and arithmetic sequence) with its performance of partitioning the image completely and bringing the least fitted error. Threshold value selected manually and automatically showed that it plays an important role during the image binary processing and the minimum-error method can be used to obtain an appropriate or reasonable one. Images obtained under different pixel matrices in MRI were used to analyze the influence of image resolution. Higher image resolution can detect more quantity of pore structure and increase its irregularity. With benefits of those influence factors, fractal analysis on four kinds of artificial cores showed the fractal dimension can be used to distinguish the different kinds of artificial cores and the relationship between fractal dimension and porosity or permeability can be expressed by the model of D = a - bln(x + c).

Dive Risk Factors, Gas Bubble Formation, and Decompression Illness in Recreational SCUBA Diving: Analysis of DAN Europe DSL Data Base.

PubMed

Cialoni, Danilo; Pieri, Massimo; Balestra, Costantino; Marroni, Alessandro

2017-01-01

Introduction: The popularity of SCUBA diving is steadily increasing together with the number of dives and correlated diseases per year. The rules that govern correct decompression procedures are considered well known even if the majority of Decompression Sickness (DCS) cases are considered unexpected confirming a bias in the "mathematical ability" to predict DCS by the current algorithms. Furthermore, little is still known about diving risk factors and any individual predisposition to DCS. This study provides an in-depth epidemiological analysis of the diving community, to include additional risk factors correlated with the development of circulating bubbles and DCS. Materials and Methods: An originally developed database (DAN DB) including specific questionnaires for data collection allowed the statistical analysis of 39,099 electronically recorded open circuit dives made by 2,629 European divers (2,189 males 83.3%, 440 females 16.7%) over 5 years. The same dive parameters and risk factors were investigated also in 970 out of the 39,099 collected dives investigated for bubble formation, by 1-min precordial Doppler, and in 320 sea-level dives followed by DCS symptoms. Results: Mean depth and GF high of all the recorded dives were 27.1 m, and 0.66, respectively; the average ascent speed was lower than the currently recommended "safe" one (9-10 m/min). We found statistically significant relationships between higher bubble grades and BMI, fat mass, age, and diving exposure. Regarding incidence of DCS, we identified additional non-bubble related risk factors, which appear significantly related to a higher DCS incidence, namely: gender, strong current, heavy exercise, and workload during diving. We found that the majority of the recorded DCS cases were not predicted by the adopted decompression algorithm and would have therefore been defined as "undeserved." Conclusion: The DAN DB analysis shows that most dives were made in a "safe zone," even if data show an evident

Analysis of spatio-temporal variability of C-factor derived from remote sensing data

NASA Astrophysics Data System (ADS)

Pechanec, Vilem; Benc, Antonin; Purkyt, Jan; Cudlin, Pavel

2016-04-01

In some risk areas water erosion as the present task has got the strong influence on agriculture and can threaten inhabitants. In our country combination of USLE and RUSLE models has been used for water erosion assessment (Krása et al., 2013). Role of vegetation cover is characterized by the help of vegetation protection factor, so-called C- factor. Value of C-factor is given by the ratio of washing-off on a plot with arable crops to standard plot which is kept as fallow regularly spud after any rain (Janeček et al., 2012). Under conditions we cannot identify crop structure and its turn, determination of C-factor can be problem in large areas. In such case we only determine C-factor according to the average crop representation. New technologies open possibilities for acceleration and specification of the approach. Present-day approach for the C-factor determination is based on the analysis of multispectral image data. Red and infrared spectrum is extracted and these parts of image are used for computation of vegetation index series (NDVI, TSAVI). Acquired values for fractional time sections (during vegetation period) are averaged out. At the same time values of vegetation indices for a forest and cleared area are determined. Also regressive coefficients are computed. Final calculation is done by the help of regressive equations expressing relation between values of NDVI and C-factor (De Jong, 1994; Van der Knijff, 1999; Karaburun, 2010). Up-to-date land use layer is used for the determination of erosion threatened areas on the base of selection of individual landscape segments of erosion susceptible categories of land use. By means of Landsat 7 data C-factor has been determined for the whole area of the Czech Republic in every month of the year of 2014. At the model area in a small watershed C-factor has been determined by the conventional (tabular) procedure. Analysis was focused on: i) variability assessment of C-factor values while using the conventional

Physics Metacognition Inventory Part Ii: Confirmatory Factor Analysis and Rasch Analysis

ERIC Educational Resources Information Center

Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

2015-01-01

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,…

Prognostic factors and risk stratification in patients with castration-resistant prostate cancer receiving docetaxel-based chemotherapy.

PubMed

Yamashita, Shimpei; Kohjimoto, Yasuo; Iguchi, Takashi; Koike, Hiroyuki; Kusumoto, Hiroki; Iba, Akinori; Kikkawa, Kazuro; Kodama, Yoshiki; Matsumura, Nagahide; Hara, Isao

2016-03-22

While novel drugs have been developed, docetaxel remains one of the standard initial systemic therapies for castration-resistant prostate cancer (CRPC) patients. Despite the excellent anti-tumor effect of docetaxel, its severe adverse effects sometimes distress patients. Therefore, it would be very helpful to predict the efficacy of docetaxel before treatment. The aims of this study were to evaluate the potential value of patient characteristics in predicting overall survival (OS) and to develop a risk classification for CRPC patients treated with docetaxel-based chemotherapy. This study included 79 patients with CRPC treated with docetaxel. The variables, including patient characteristics at diagnosis and at the start of chemotherapy, were retrospectively collected. Prognostic factors predicting OS were analyzed using the Cox proportional hazard model. Risk stratification for overall survival was determined based on the results of multivariate analysis. PSA response ≥50 % was observed in 55 (69.6 %) of all patients, and the median OS was 22.5 months. The multivariate analysis showed that age, serum PSA level at the start of chemotherapy, and Hb were independent prognostic factors for OS. In addition, ECOG performance status (PS) and the CRP-to-albumin ratio were not significant but were considered possible predictors for OS. Risk stratification according to the number of these risk factors could effectively stratify CRPC patients treated with docetaxel in terms of OS. Age, serum PSA level at the start of chemotherapy, and Hb were identified as independent prognostic factors of OS. ECOG PS and the CRP-to-albumin ratio were not significant, but were considered possible predictors for OS in Japanese CRPC patients treated with docetaxel. Risk stratification based on these factors could be helpful for estimating overall survival.

Nanodiamond-based injectable hydrogel for sustained growth factor release: Preparation, characterization and in vitro analysis.

PubMed

Pacelli, Settimio; Acosta, Francisca; Chakravarti, Aparna R; Samanta, Saheli G; Whitlow, Jonathan; Modaresi, Saman; Ahmed, Rafeeq P H; Rajasingh, Johnson; Paul, Arghya

2017-08-01

Nanodiamonds (NDs) represent an emerging class of carbon nanomaterials that possess favorable physical and chemical properties to be used as multifunctional carriers for a variety of bioactive molecules. Here we report the synthesis and characterization of a new injectable ND-based nanocomposite hydrogel which facilitates a controlled release of therapeutic molecules for regenerative applications. In particular, we have formulated a thermosensitive hydrogel using gelatin, chitosan and NDs that provides a sustained release of exogenous human vascular endothelial growth factor (VEGF) for wound healing applications. Addition of NDs improved the mechanical properties of the injectable hydrogels without affecting its thermosensitive gelation properties. Biocompatibility of the generated hydrogel was verified by in vitro assessment of apoptotic gene expressions and anti-inflammatory interleukin productions. NDs were complexed with VEGF and the inclusion of this complex in the hydrogel network enabled the sustained release of the angiogenic growth factor. These results suggest for the first time that NDs can be used to formulate a biocompatible, thermosensitive and multifunctional hydrogel platform that can function both as a filling agent to modulate hydrogel properties, as well as a delivery platform for the controlled release of bioactive molecules and growth factors. One of the major drawbacks associated with the use of conventional hydrogels as carriers of growth factors is their inability to control the release kinetics of the loaded molecules. In fact, in most cases, a burst release is inevitable leading to diminished therapeutic effects and unsuccessful therapies. As a potential solution to this issue, we hereby propose a strategy of incorporating ND complexes within an injectable hydrogel matrix. The functional groups on the surface of the NDs can establish interactions with the model growth factor VEGF and promote a prolonged release from the polymer network

Resilience Analysis of Countries under Disasters Based on Multisource Data.

PubMed

Zhang, Nan; Huang, Hong

2018-01-01

Disasters occur almost daily in the world. Because emergencies frequently have no precedent, are highly uncertain, and can be very destructive, improving a country's resilience is an efficient way to reduce risk. In this article, we collected more than 20,000 historical data points from disasters from 207 countries to enable us to calculate the severity of disasters and the danger they pose to countries. In addition, 6 primary indices (disaster, personal attribute, infrastructure, economics, education, and occupation) including 38 secondary influencing factors are considered in analyzing the resilience of countries. Using these data, we obtained the danger, expected number of deaths, and resilience of all 207 countries. We found that a country covering a large area is more likely to have a low resilience score. Through sensitivity analysis of all secondary indices, we found that population density, frequency of disasters, and GDP are the three most critical factors affecting resilience. Based on broad-spectrum resilience analysis of the different continents, Oceania and South America have the highest resilience, while Asia has the lowest. Over the past 50 years, the resilience of many countries has been improved sharply, especially in developing countries. Based on our results, we analyze the comprehensive resilience and provide some optimal suggestions to efficiently improve resilience. © 2017 Society for Risk Analysis.

Knowledge-Based Image Analysis.

DTIC Science & Technology

1981-04-01

UNCLASSIF1 ED ETL-025s N IIp ETL-0258 AL Ai01319 S"Knowledge-based image analysis u George C. Stockman Barbara A. Lambird I David Lavine Laveen N. Kanal...extraction, verification, region classification, pattern recognition, image analysis . 3 20. A. CT (Continue on rever.. d. It necessary and Identify by...UNCLgSTFTF n In f SECURITY CLASSIFICATION OF THIS PAGE (When Date Entered) .L1 - I Table of Contents Knowledge Based Image Analysis I Preface

Analysis of risk factors for persistent infection of asymptomatic women with high-risk human papilloma virus.

PubMed

Shi, Nianmin; Lu, Qiang; Zhang, Jiao; Li, Li; Zhang, Junnan; Zhang, Fanglei; Dong, Yanhong; Zhang, Xinyue; Zhang, Zheng; Gao, Wenhui

2017-06-03

This study aims to prevent persistentinfection, reduce the incidence of cervical cancer, and improve women's health by understanding the theoretical basis of the risk factors for continuous infection of asymptomatic women with high-risk human papilloma virus (HPV) strains via information collected, which includes the persistent infection rate and the most prevalent HPV strain types of high risk to asymptomatic women in the high-risk area of cervical cancer in Linfen, Shanxi Province. Based on the method of cluster sampling, locations were chosen from the industrial county and agricultural county of Linfen, Shanxi Province, namely the Xiangfen and Quwo counties. Use of the convenience sampling (CS) method enables the identification of women who have sex but without symptoms of abnormal cervix for analyzing risk factors of HPV-DNA detection and performing a retrospective questionnaire survey in these 2 counties. Firstly, cervical exfoliated cell samples were collected for thin-layer liquid-based cytology test (TCT), and simultaneously testing high-risk type HPV DNA, then samples with positive testing results were retested to identify the infected HPV types. The 6-month period of testing was done to derive the 6-month persistent infection rate. The retrospective survey included concepts addressed in the questionnaire: basic situation of the research objects, menstrual history, marital status, pregnancy history, sexual habits and other aspects. The questionnaire was divided into a case group and a comparison group, which are based on the high-risk HPV-DNA testing result to ascertain whether or not there is persistent infection. Statistical analysis employed Epidate3.1 software for date entry, SPSS17.0 for date statistical analysis. Select statistic charts, Chi-Square Analysis, single-factor analysis and multivariate Logistic regression analysis to analyze the protective factors and risk factors of high-risk HPV infection. Risk factors are predicted by using the

Cost Analysis of an Office-based Surgical Suite

PubMed Central

LaBove, Gabrielle

2016-01-01

Introduction: Operating costs are a significant part of delivering surgical care. Having a system to analyze these costs is imperative for decision making and efficiency. We present an analysis of surgical supply, labor and administrative costs, and remuneration of procedures as a means for a practice to analyze their cost effectiveness; this affects the quality of care based on the ability to provide services. The costs of surgical care cannot be estimated blindly as reconstructive and cosmetic procedures have different percentages of overhead. Methods: A detailed financial analysis of office-based surgical suite costs for surgical procedures was determined based on company contract prices and average use of supplies. The average time spent on scheduling, prepping, and doing the surgery was factored using employee rates. Results: The most expensive, minor procedure supplies are suture needles. The 4 most common procedures from the most expensive to the least are abdominoplasty, breast augmentation, facelift, and lipectomy. Conclusions: Reconstructive procedures require a greater portion of collection to cover costs. Without the adjustment of both patient and insurance remuneration in the practice, the ability to provide quality care will be increasingly difficult. PMID:27536482

Connectivism in Postsecondary Online Courses: An Exploratory Factor Analysis

ERIC Educational Resources Information Center

Hogg, Nanette; Lomicky, Carol S.

2012-01-01

This study explores 465 postsecondary students' experiences in online classes through the lens of connectivism. Downes' 4 properties of connectivism (diversity, autonomy, interactivity, and openness) were used as the study design. An exploratory factor analysis was performed. This study found a 4-factor solution. Subjects indicated that autonomy…

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

PubMed

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

2017-01-01

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

Factors influencing implementation of a preschool-based physical activity intervention

PubMed Central

Lau, Erica Y.; Saunders, Ruth P.; Beets, Michael W.; Cai, Bo; Pate, Russell R.

2017-01-01

Abstract Examining factors that influence implementation of key program components that underlie an intervention’s success provides important information to inform the development of effective dissemination strategies. We examined direct and indirect effects of preschool capacity, quality of prevention support system and teacher characteristics on implementation levels of a component, called Move Outside (i.e., preschool classroom teachers to provide at least 40 min of outdoor recess per day), that was fundamental to the success of a preschool-based physical activity intervention. Level of implementation, defined as the percent of daily goal met for the Move Outside component, was assessed via direct observation. Items assessing preschool capacity, quality of prevention support system and teacher characteristics were selected from surveys and an environmental checklist completed by preschool directors and teachers. Preschool classroom was used as the unit of analysis (Year 1: n = 19; Year 2: n = 17). Results from Bayesian path analyses showed that the three factors were not significantly associated with level of implementation in Year 1, but preschool capacity was directly associated with level of implementation in Year 2 (β= 0.528, 95% CI: 0.134, 0.827). The current findings suggest that factors that influence level of implementation appear to differ as an intervention evolved over time. PMID:28158420

Model-Based Safety Analysis

NASA Technical Reports Server (NTRS)

Joshi, Anjali; Heimdahl, Mats P. E.; Miller, Steven P.; Whalen, Mike W.

2006-01-01

System safety analysis techniques are well established and are used extensively during the design of safety-critical systems. Despite this, most of the techniques are highly subjective and dependent on the skill of the practitioner. Since these analyses are usually based on an informal system model, it is unlikely that they will be complete, consistent, and error free. In fact, the lack of precise models of the system architecture and its failure modes often forces the safety analysts to devote much of their effort to gathering architectural details about the system behavior from several sources and embedding this information in the safety artifacts such as the fault trees. This report describes Model-Based Safety Analysis, an approach in which the system and safety engineers share a common system model created using a model-based development process. By extending the system model with a fault model as well as relevant portions of the physical system to be controlled, automated support can be provided for much of the safety analysis. We believe that by using a common model for both system and safety engineering and automating parts of the safety analysis, we can both reduce the cost and improve the quality of the safety analysis. Here we present our vision of model-based safety analysis and discuss the advantages and challenges in making this approach practical.

Efficiency limit factor analysis for the Francis-99 hydraulic turbine

NASA Astrophysics Data System (ADS)

Zeng, Y.; Zhang, L. X.; Guo, J. P.; Guo, Y. K.; Pan, Q. L.; Qian, J.

2017-01-01

The energy loss in hydraulic turbine is the most direct factor that affects the efficiency of the hydraulic turbine. Based on the analysis theory of inner energy loss of hydraulic turbine, combining the measurement data of the Francis-99, this paper calculates characteristic parameters of inner energy loss of the hydraulic turbine, and establishes the calculation model of the hydraulic turbine power. Taken the start-up test conditions given by Francis-99 as case, characteristics of the inner energy of the hydraulic turbine in transient and transformation law are researched. Further, analyzing mechanical friction in hydraulic turbine, we think that main ingredients of mechanical friction loss is the rotation friction loss between rotating runner and water body, and defined as the inner mechanical friction loss. The calculation method of the inner mechanical friction loss is given roughly. Our purpose is that explore and research the method and way increasing transformation efficiency of water flow by means of analysis energy losses in hydraulic turbine.

Environmental factor analysis of cholera in China using remote sensing and geographical information systems.

PubMed

Xu, M; Cao, C X; Wang, D C; Kan, B; Xu, Y F; Ni, X L; Zhu, Z C

2016-04-01

Cholera is one of a number of infectious diseases that appears to be influenced by climate, geography and other natural environments. This study analysed the environmental factors of the spatial distribution of cholera in China. It shows that temperature, precipitation, elevation, and distance to the coastline have significant impact on the distribution of cholera. It also reveals the oceanic environmental factors associated with cholera in Zhejiang, which is a coastal province of China, using both remote sensing (RS) and geographical information systems (GIS). The analysis has validated the correlation between indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local number of cholera cases based on 8-year monthly data from 2001 to 2008. The results show the number of cholera cases has been strongly affected by the variables of SST, SSH and OCC. Utilizing this information, a cholera prediction model has been established based on the oceanic and climatic environmental factors. The model indicates that RS and GIS have great potential for designing an early warning system for cholera.

Risk Factors for Chronic Subdural Hematoma Recurrence Identified Using Quantitative Computed Tomography Analysis of Hematoma Volume and Density.

PubMed

Stavrinou, Pantelis; Katsigiannis, Sotirios; Lee, Jong Hun; Hamisch, Christina; Krischek, Boris; Mpotsaris, Anastasios; Timmer, Marco; Goldbrunner, Roland

2017-03-01

Chronic subdural hematoma (CSDH), a common condition in elderly patients, presents a therapeutic challenge with recurrence rates of 33%. We aimed to identify specific prognostic factors for recurrence using quantitative analysis of hematoma volume and density. We retrospectively reviewed radiographic and clinical data of 227 CSDHs in 195 consecutive patients who underwent evacuation of the hematoma through a single burr hole, 2 burr holes, or a mini-craniotomy. To examine the relationship between hematoma recurrence and various clinical, radiologic, and surgical factors, we used quantitative image-based analysis to measure the hematoma and trapped air volumes and the hematoma densities. Recurrence of CSDH occurred in 35 patients (17.9%). Multivariate logistic regression analysis revealed that the percentage of hematoma drained and postoperative CSDH density were independent risk factors for recurrence. All 3 evacuation methods were equally effective in draining the hematoma (71.7% vs. 73.7% vs. 71.9%) without observable differences in postoperative air volume captured in the subdural space. Quantitative image analysis provided evidence that percentage of hematoma drained and postoperative CSDH density are independent prognostic factors for subdural hematoma recurrence. Copyright © 2016 Elsevier Inc. All rights reserved.

Establishing Evidence for Internal Structure Using Exploratory Factor Analysis

ERIC Educational Resources Information Center

Watson, Joshua C.

2017-01-01

Exploratory factor analysis (EFA) is a data reduction technique used to condense data into smaller sets of summary variables by identifying underlying factors potentially accounting for patterns of collinearity among said variables. Using an illustrative example, the 5 general steps of EFA are described with best practices for decision making…

Evidence based management of polyps of the gall bladder: A systematic review of the risk factors of malignancy.

PubMed

Bhatt, Nikita R; Gillis, Amy; Smoothey, Craig O; Awan, Faisal N; Ridgway, Paul F

2016-10-01

There are no evidence-based guidelines to dictate when Gallbladder Polyps (GBPs) of varying sizes should be resected. To identify factors that accurately predict malignant disease in GBP; to provide an evidence-based algorithm for management. A systematic review following PRISMA guidelines was performed using terms "gallbladder polyps" AND "polypoid lesion of gallbladder", from January 1993 and September 2013. Inclusion criteria required histopathological report or follow-up of 2 years. RTI-IB tool was used for quality analysis. Correlation with GBP size and malignant potential was analysed using Euclidean distance; a logistics mixed effects model was used for assessing independent risk factors for malignancy. Fifty-three articles were included in review. Data from 21 studies was pooled for analysis. Optimum size cut-off for resection of GBPs was 10 mm. Probability of malignancy is approximately zero at size <4.15 mm. Patient age >50 years, sessile and single polyps were independent risk factors for malignancy. For polyps sized 4 mm-10 mm, a risk assessment model was formulated. This review and analysis has provided an evidence-based algorithm for the management of GBPs. Longitudinal studies are needed to better understand the behaviour of polyps <10 mm, that are not at a high risk of malignancy, but may change over time. Copyright © 2016 Royal College of Surgeons of Edinburgh (Scottish charity number SC005317) and Royal College of Surgeons in Ireland. Published by Elsevier Ltd. All rights reserved.

An analysis of the structure of the compound biological effectiveness factor.

PubMed

Ono, Koji

2016-08-01

This report is an analysis of the structure of the compound biological effectiveness (CBE) factor. The value of the CBE factor previously reported was revalued for the central nervous system, skin and lung. To describe the structure, the following terms are introduced: the vascular CBE (v-CBE), intraluminal CBE (il-CBE), extraluminal CBE (el-CBE) and non-vascular CBE (nv-CBE) factors and the geometric biological factor (GBF), i.e. the contributions that are derived from the total dose to the vasculature, each dose to vasculature from the intraluminal side and the extraluminal side, the dose to the non-vascular tissue and the factor to calculate el-CBE from il-CBE, respectively. The el-CBE factor element was also introduced to relate il-CBE to el-CBE factors. A CBE factor of 0.36 for disodium mercaptoundecahydrododecaborate (BSH) for the CNS was independent of the (10)B level in the blood; however, that for p-Boron-L-phenylalanine (BPA) increased with the (10)B level ratio of the normal tissue to the blood (N/B). The CBE factor was expressed as follows: factor = 0.32 + N/B × 1.65. The factor of 0.32 at 0 of N/B was close to the CBE factor for BSH. GBFs had similar values, between BSH and BPA, 1.39 and 1.52, respectively. The structure of the CBE factor for BPA to the lung was also elucidated based on this idea. The factor is described as follows: CBE factor = 0.32 + N/B × 1.80. By this elucidation of the structure of the CBE factor, it is expected that basic and clinical research into boron neutron capture therapy will progress. © The Author 2016. Published by Oxford University Press on behalf of The Japan Radiation Research Society and Japanese Society for Radiation Oncology.

Modeling of Individual and Organizational Factors Affecting Traumatic Occupational Injuries Based on the Structural Equation Modeling: A Case Study in Large Construction Industries.

PubMed

Mohammadfam, Iraj; Soltanzadeh, Ahmad; Moghimbeigi, Abbas; Akbarzadeh, Mehdi

2016-09-01

Individual and organizational factors are the factors influencing traumatic occupational injuries. The aim of the present study was the short path analysis of the severity of occupational injuries based on individual and organizational factors. The present cross-sectional analytical study was implemented on traumatic occupational injuries within a ten-year timeframe in 13 large Iranian construction industries. Modeling and data analysis were done using the structural equation modeling (SEM) approach and the IBM SPSS AMOS statistical software version 22.0, respectively. The mean age and working experience of the injured workers were 28.03 ± 5.33 and 4.53 ± 3.82 years, respectively. The portions of construction and installation activities of traumatic occupational injuries were 64.4% and 18.1%, respectively. The SEM findings showed that the individual, organizational and accident type factors significantly were considered as effective factors on occupational injuries' severity (P < 0.05). Path analysis of occupational injuries based on the SEM reveals that individual and organizational factors and their indicator variables are very influential on the severity of traumatic occupational injuries. So, these should be considered to reduce occupational accidents' severity in large construction industries.

Why People Choose to Teach in Urban Schools: The Case for a Push-Pull Factor Analysis

ERIC Educational Resources Information Center

Knell, Paul F.; Castro, Antonio J.

2014-01-01

This qualitative research study traces the motivations for teaching of 13 teacher candidates enrolled in an urban-based alternative certification program. After using a push-pull factor analysis, the data suggest that most participants left their previous careers due to financial shortcomings or work instability. As a result, these participants…

Human factors evaluation of teletherapy: Function and task analysis. Volume 2

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

Kaye, R.D.; Henriksen, K.; Jones, R.

1995-07-01

As a treatment methodology, teletherapy selectively destroys cancerous and other tissue by exposure to an external beam of ionizing radiation. Sources of radiation are either a radioactive isotope, typically Cobalt-60 (Co-60), or a linear accelerator. Records maintained by the NRC have identified instances of teletherapy misadministration where the delivered radiation dose has differed from the radiation prescription (e.g., instances where fractions were delivered to the wrong patient, to the wrong body part, or were too great or too little with respect to the defined treatment volume). Both human error and machine malfunction have led to misadministrations. Effective and safe treatmentmore » requires a concern for precision and consistency of human-human and human-machine interactions throughout the course of therapy. The present study is the first part of a series of human factors evaluations for identifying the root causes that lead to human error in the teletherapy environment. The human factors evaluations included: (1) a function and task analysis of teletherapy activities, (2) an evaluation of the human-system interfaces, (3) an evaluation of procedures used by teletherapy staff, (4) an evaluation of the training and qualifications of treatment staff (excluding the oncologists), (5) an evaluation of organizational practices and policies, and (6) an identification of problems and alternative approaches for NRC and industry attention. The present report addresses the function and task analysis of teletherapy activities and provides the foundation for the conduct of the subsequent evaluations. The report includes sections on background, methodology, a description of the function and task analysis, and use of the task analysis findings for the subsequent tasks. The function and task analysis data base also is included.« less

Model-based meta-analysis to evaluate optimal doses of direct oral factor Xa inhibitors in atrial fibrillation patients

PubMed Central

Yoshioka, Hideki; Sato, Hiromi; Hatakeyama, Hiroto

2018-01-01

The noninferiority of direct oral factor Xa (FXa) inhibitors (rivaroxaban, apixaban, and edoxaban) in treatment of atrial fibrillation were demonstrated compared with warfarin by several large clinical trials; however, subsequent meta-analyses reported a higher risk of major bleeding with rivaroxaban than with the other FXa inhibitors. In the present study, we first estimated the changes of prothrombin time (PT) in 5 randomized trials based on reported population pharmacokinetic and pharmacodynamic models and then carried out a model-based meta-analysis to obtain models describing the relationship between PT changes and the event rates of ischemic stroke/systemic embolism (SE) and of major bleeding. By using the models, we simulated the optimal therapeutic doses for each FXa inhibitor. It was suggested that dose reduction of rivaroxaban from the current 20 mg/d to 10 mg/d would decrease patient deaths from major bleeding (hazard ratio [HR], 0.69; 95% confidence interval [CI], 0.64-0.74) with little increase in those for ischemic stroke/SE (HR, 1.11; 95% CI, 1.07-1.20). The overall decrease in the mortality caused by both events was estimated as 5.81 per 10 000 patient-years (95% CI, 3.92-8.16), with an HR of 0.87 (95% CI, 0.83-0.91). For apixaban and edoxaban, no distinct change in the overall mortality was simulated by dose modification. This study suggested that the current dose of rivaroxaban might be excessive and would need to be reduced to decrease the excess risk of major bleeding. PMID:29760204

Aligning faith-based and national HIV/AIDS prevention responses? Factors influencing the HIV/AIDS prevention policy process and response of faith-based NGOs in Tanzania.

PubMed

Morgan, Rosemary; Green, Andrew; Boesten, Jelke

2014-05-01

Faith-based organizations (FBOs) have a long tradition of providing HIV/AIDS prevention and mitigation services in Africa. The overall response of FBOs, however, has been controversial, particularly in regard to HIV/AIDS prevention and FBO's rejection of condom use and promotion, which can conflict with and negatively influence national HIV/AIDS prevention response efforts. This article reports the findings from a study that explored the factors influencing the HIV/AIDS prevention policy process within faith-based non-governmental organizations (NGOs) of different faiths. These factors were examined within three faith-based NGOs in Dar es Salaam, Tanzania-a Catholic, Anglican and Muslim organization. The research used an exploratory, qualitative case-study approach, and employed a health policy analysis framework, examining the context, actor and process factors and how they interact to form content in terms of policy and its implementation within each organization. Three key factors were found to influence faith-based NGOs' HIV/AIDS prevention response in terms of both policy and its implementation: (1) the faith structure in which the organizations are a part, (2) the presence or absence of organizational policy and (3) the professional nature of the organizations and its actors. The interaction between these factors, and how actors negotiate between them, was found to shape the organizations' HIV/AIDS prevention response. This article reports on these factors and analyses the different HIV/AIDS prevention responses found within each organization. By understanding the factors that influence faith-based NGOs' HIV/AIDS prevention policy process, the overall faith-based response to HIV/AIDS, and how it corresponds to national response efforts, is better understood. It is hoped that by doing so the government will be better able to identify how to best work with FBOs to meet national HIV/AIDS prevention targets, improving the overall role of FBOs in the fight against

Examining Evolving Performance on the Force Concept Inventory Using Factor Analysis

ERIC Educational Resources Information Center

Semak, M. R.; Dietz, R. D.; Pearson, R. H.; Willis, C. W

2017-01-01

The application of factor analysis to the "Force Concept Inventory" (FCI) has proven to be problematic. Some studies have suggested that factor analysis of test results serves as a helpful tool in assessing the recognition of Newtonian concepts by students. Other work has produced at best ambiguous results. For the FCI administered as a…

A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis

ERIC Educational Resources Information Center

Edwards, Michael C.

2010-01-01

Item factor analysis has a rich tradition in both the structural equation modeling and item response theory frameworks. The goal of this paper is to demonstrate a novel combination of various Markov chain Monte Carlo (MCMC) estimation routines to estimate parameters of a wide variety of confirmatory item factor analysis models. Further, I show…

An Exploratory Study on Using Principal-Component Analysis and Confirmatory Factor Analysis to Identify Bolt-On Dimensions: The EQ-5D Case Study.

PubMed

Finch, Aureliano Paolo; Brazier, John Edward; Mukuria, Clara; Bjorner, Jakob Bue

2017-12-01

Generic preference-based measures such as the EuroQol five-dimensional questionnaire (EQ-5D) are used in economic evaluation, but may not be appropriate for all conditions. When this happens, a possible solution is adding bolt-ons to expand their descriptive systems. Using review-based methods, studies published to date claimed the relevance of bolt-ons in the presence of poor psychometric results. This approach does not identify the specific dimensions missing from the Generic preference-based measure core descriptive system, and is inappropriate for identifying dimensions that might improve the measure generically. This study explores the use of principal-component analysis (PCA) and confirmatory factor analysis (CFA) for bolt-on identification in the EQ-5D. Data were drawn from the international Multi-Instrument Comparison study, which is an online survey on health and well-being measures in five countries. Analysis was based on a pool of 92 items from nine instruments. Initial content analysis provided a theoretical framework for PCA results interpretation and CFA model development. PCA was used to investigate the underlining dimensional structure and whether EQ-5D items were represented in the identified constructs. CFA was used to confirm the structure. CFA was cross-validated in random halves of the sample. PCA suggested a nine-component solution, which was confirmed by CFA. This included psychological symptoms, physical functioning, and pain, which were covered by the EQ-5D, and satisfaction, speech/cognition,relationships, hearing, vision, and energy/sleep which were not. These latter factors may represent relevant candidate bolt-ons. PCA and CFA appear useful methods for identifying potential bolt-ons dimensions for an instrument such as the EQ-5D. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Improving Your Exploratory Factor Analysis for Ordinal Data: A Demonstration Using FACTOR

ERIC Educational Resources Information Center

Baglin, James

2014-01-01

Exploratory factor analysis (EFA) methods are used extensively in the field of assessment and evaluation. Due to EFA's widespread use, common methods and practices have come under close scrutiny. A substantial body of literature has been compiled highlighting problems with many of the methods and practices used in EFA, and, in response, many…

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

PubMed

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

2010-03-15

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

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

PubMed Central

2010-01-01

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

Success Factors of European Syndromic Surveillance Systems: A Worked Example of Applying Qualitative Comparative Analysis.

PubMed

Ziemann, Alexandra; Fouillet, Anne; Brand, Helmut; Krafft, Thomas

2016-01-01

Syndromic surveillance aims at augmenting traditional public health surveillance with timely information. To gain a head start, it mainly analyses existing data such as from web searches or patient records. Despite the setup of many syndromic surveillance systems, there is still much doubt about the benefit of the approach. There are diverse interactions between performance indicators such as timeliness and various system characteristics. This makes the performance assessment of syndromic surveillance systems a complex endeavour. We assessed if the comparison of several syndromic surveillance systems through Qualitative Comparative Analysis helps to evaluate performance and identify key success factors. We compiled case-based, mixed data on performance and characteristics of 19 syndromic surveillance systems in Europe from scientific and grey literature and from site visits. We identified success factors by applying crisp-set Qualitative Comparative Analysis. We focused on two main areas of syndromic surveillance application: seasonal influenza surveillance and situational awareness during different types of potentially health threatening events. We found that syndromic surveillance systems might detect the onset or peak of seasonal influenza earlier if they analyse non-clinical data sources. Timely situational awareness during different types of events is supported by an automated syndromic surveillance system capable of analysing multiple syndromes. To our surprise, the analysis of multiple data sources was no key success factor for situational awareness. We suggest to consider these key success factors when designing or further developing syndromic surveillance systems. Qualitative Comparative Analysis helped interpreting complex, mixed data on small-N cases and resulted in concrete and practically relevant findings.

Assessing suicide risk among callers to crisis hotlines: a confirmatory factor analysis.

PubMed

Witte, Tracy K; Gould, Madelyn S; Munfakh, Jimmie Lou Harris; Kleinman, Marjorie; Joiner, Thomas E; Kalafat, John

2010-09-01

Our goal was to investigate the factor structure of a risk assessment tool utilized by suicide hotlines and to determine the predictive validity of the obtained factors in predicting subsequent suicidal behavior. We conducted an Exploratory Factor Analysis (EFA), an EFA in a Confirmatory Factor Analysis (EFA/CFA) framework, and a CFA on independent subsamples derived from a total sample of 1,085. Similar to previous studies, we found consistent evidence for a two-factor solution, with one factor representing a more pernicious form of suicide risk (i.e., Resolved Plans and Preparations; RPP) and one factor representing milder suicidal ideation (i.e., Suicidal Desire and Ideation; SDI). The RPP factor trended toward being more predictive of suicidal ideation at follow-up than the SDI factor. (c) 2010 Wiley Periodicals, Inc.

Factor analysis of serogroups botanica and aurisina of Leptospira biflexa.

PubMed

Cinco, M

1977-11-01

Factor analysis is performed on serovars of Botanica and Aurisina serogroup of Leptospira biflexa. The results show the arrangement of main factors serovar and serogroup specific, as well as the antigens common with serovars of heterologous serogroups.

Risk factors for baclofen pump infection in children: a multivariate analysis.

PubMed

Spader, Heather S; Bollo, Robert J; Bowers, Christian A; Riva-Cambrin, Jay

2016-06-01

OBJECTIVE Intrathecal baclofen infusion systems to manage severe spasticity and dystonia are associated with higher infection rates in children than in adults. Factors unique to this population, such as poor nutrition and physical limitations for pump placement, have been hypothesized as the reasons for this disparity. The authors assessed potential risk factors for infection in a multivariate analysis. METHODS Patients who underwent implantation of a programmable pump and intrathecal catheter for baclofen infusion at a single center between January 1, 2000, and March 1, 2012, were identified in this retrospective cohort study. The primary end point was infection. Potential risk factors investigated included preoperative (i.e., demographics, body mass index [BMI], gastrostomy tube, tracheostomy, previous spinal fusion), intraoperative (i.e., surgeon, antibiotics, pump size, catheter location), and postoperative (i.e., wound dehiscence, CSF leak, and number of revisions) factors. Univariate analysis was performed, and a multivariate logistic regression model was created to identify independent risk factors for infection. RESULTS A total of 254 patients were evaluated. The overall infection rate was 9.8%. Univariate analysis identified young age, shorter height, lower weight, dehiscence, CSF leak, and number of revisions within 6 months of pump placement as significantly associated with infection. Multivariate analysis identified young age, dehiscence, and number of revisions as independent risk factors for infection. CONCLUSIONS Young age, wound dehiscence, and number of revisions were independent risk factors for infection in this pediatric cohort. A low BMI and the presence of either a gastrostomy or tracheostomy were not associated with infection and may not be contraindications for this procedure.

Risk factor and cost accounting analysis for dialysis patients in Taiwan.

PubMed

Su, Bin-Guang; Tsai, Kai-Li; Yeh, Shu-Hsing; Ho, Yi-Yi; Liu, Shin-Yi; Rivers, Patrick A

2010-05-01

According to the 2004 US Renal Data System's annual report, the incidence rate of chronic renal failure in Taiwan increased from 120 to 352 per million populations between 1990 and 2003. This incidence rate is the highest in the world. The prevalence rate, which ranks number two in the world (Japan ranks number one), also increased from 384 to 1630 per million populations. Based on 2005 Taiwan national statistics, there were 52,958 end-stage renal disease (ESRD) patients receiving routine dialysis treatment. This number, which comprised less than 0.2% of the total population and consumed $2.6 billion New Taiwan dollars, was more than 6.12% of the total annual spending of national health insurance during 2005. Dialysis expenditures for patients with ESRD rank the highest among all major injuries (traumas) and diseases. This article identifies and discusses the risk factors associated with consumption of medical resources during dialysis. Instead of using reimbursement data to estimate cost, as seen in previous studies, this study uses cost data within organizations and focuses on evaluating and predicting the resource consumption pattern for dialysis patients with different risk factors. Multiple regression analysis was used to identify 23 risk factors for routine dialysis patients. Of these risk factors, six were associated with the increase of dialysis cost: age (i.e. 75 years old and older), liver function disorder, hypertension, bile-duct disorder, cancer and high blood lipids. Patients with liver function disorder incurred much higher costs for injection medication and supplies. Hypertensive patients incurred higher costs for injection medication, supplies and oral medication. Patients with bile-duct disorder incurred a significant difference in check-up costs (i.e. costs were higher for those aged 75 years and older than those who were younger than 30 years of age). Cancer patients also incurred significant differences in cost of medical supplies. Patients

Evaluating WAIS-IV structure through a different psychometric lens: structural causal model discovery as an alternative to confirmatory factor analysis.

PubMed

van Dijk, Marjolein J A M; Claassen, Tom; Suwartono, Christiany; van der Veld, William M; van der Heijden, Paul T; Hendriks, Marc P H

Since the publication of the WAIS-IV in the U.S. in 2008, efforts have been made to explore the structural validity by applying factor analysis to various samples. This study aims to achieve a more fine-grained understanding of the structure of the Dutch language version of the WAIS-IV (WAIS-IV-NL) by applying an alternative analysis based on causal modeling in addition to confirmatory factor analysis (CFA). The Bayesian Constraint-based Causal Discovery (BCCD) algorithm learns underlying network structures directly from data and assesses more complex structures than is possible with factor analysis. WAIS-IV-NL profiles of two clinical samples of 202 patients (i.e. patients with temporal lobe epilepsy and a mixed psychiatric outpatient group) were analyzed and contrasted with a matched control group (N = 202) selected from the Dutch standardization sample of the WAIS-IV-NL to investigate internal structure by means of CFA and BCCD. With CFA, the four-factor structure as proposed by Wechsler demonstrates acceptable fit in all three subsamples. However, BCCD revealed three consistent clusters (verbal comprehension, visual processing, and processing speed) in all three subsamples. The combination of Arithmetic and Digit Span as a coherent working memory factor could not be verified, and Matrix Reasoning appeared to be isolated. With BCCD, some discrepancies from the proposed four-factor structure are exemplified. Furthermore, these results fit CHC theory of intelligence more clearly. Consistent clustering patterns indicate these results are robust. The structural causal discovery approach may be helpful in better interpreting existing tests, the development of new tests, and aid in diagnostic instruments.

A human factors systems approach to understanding team-based primary care: a qualitative analysis

PubMed Central

Mundt, Marlon P.; Swedlund, Matthew P.

2016-01-01

Background. Research shows that high-functioning teams improve patient outcomes in primary care. However, there is no consensus on a conceptual model of team-based primary care that can be used to guide measurement and performance evaluation of teams. Objective. To qualitatively understand whether the Systems Engineering Initiative for Patient Safety (SEIPS) model could serve as a framework for creating and evaluating team-based primary care. Methods. We evaluated qualitative interview data from 19 clinicians and staff members from 6 primary care clinics associated with a large Midwestern university. All health care clinicians and staff in the study clinics completed a survey of their communication connections to team members. Social network analysis identified key informants for interviews by selecting the respondents with the highest frequency of communication ties as reported by their teammates. Semi-structured interviews focused on communication patterns, team climate and teamwork. Results. Themes derived from the interviews lent support to the SEIPS model components, such as the work system (Team, Tools and Technology, Physical Environment, Tasks and Organization), team processes and team outcomes. Conclusions. Our qualitative data support the SEIPS model as a promising conceptual framework for creating and evaluating primary care teams. Future studies of team-based care may benefit from using the SEIPS model to shift clinical practice to high functioning team-based primary care. PMID:27578837

Comparison of Factorization-Based Filtering for Landing Navigation

NASA Technical Reports Server (NTRS)

McCabe, James S.; Brown, Aaron J.; DeMars, Kyle J.; Carson, John M., III

2017-01-01

This paper develops and analyzes methods for fusing inertial navigation data with external data, such as data obtained from an altimeter and a star camera. The particular filtering techniques are based upon factorized forms of the Kalman filter, specifically the UDU and Cholesky factorizations. The factorized Kalman filters are utilized to ensure numerical stability of the navigation solution. Simulations are carried out to compare the performance of the different approaches along a lunar descent trajectory using inertial and external data sources. It is found that the factorized forms improve upon conventional filtering techniques in terms of ensuring numerical stability for the investigated landing navigation scenario.

FACTOR 9.2: A Comprehensive Program for Fitting Exploratory and Semiconfirmatory Factor Analysis and IRT Models

ERIC Educational Resources Information Center

Lorenzo-Seva, Urbano; Ferrando, Pere J.

2013-01-01

FACTOR 9.2 was developed for three reasons. First, exploratory factor analysis (FA) is still an active field of research although most recent developments have not been incorporated into available programs. Second, there is now renewed interest in semiconfirmatory (SC) solutions as suitable approaches to the complex structures are commonly found…

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

USDA-ARS?s Scientific Manuscript database