Three WRKY transcription factors additively repress abscisic acid and gibberellin signaling in aleurone cells.

PubMed

Zhang, Liyuan; Gu, Lingkun; Ringler, Patricia; Smith, Stanley; Rushton, Paul J; Shen, Qingxi J

2015-07-01

Members of the WRKY transcription factor superfamily are essential for the regulation of many plant pathways. Functional redundancy due to duplications of WRKY transcription factors, however, complicates genetic analysis by allowing single-mutant plants to maintain wild-type phenotypes. Our analyses indicate that three group I WRKY genes, OsWRKY24, -53, and -70, act in a partially redundant manner. All three showed characteristics of typical WRKY transcription factors: each localized to nuclei and yeast one-hybrid assays indicated that they all bind to W-boxes, including those present in their own promoters. Quantitative real time-PCR (qRT-PCR) analyses indicated that the expression levels of the three WRKY genes varied in the different tissues tested. Particle bombardment-mediated transient expression analyses indicated that all three genes repress the GA and ABA signaling in a dosage-dependent manner. Combination of all three WRKY genes showed additive antagonism of ABA and GA signaling. These results suggest that these WRKY proteins function as negative transcriptional regulators of GA and ABA signaling. However, different combinations of these WRKY genes can lead to varied strengths in suppression of their targets. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Method for exploiting bias in factor analysis using constrained alternating least squares algorithms

DOEpatents

Keenan, Michael R.

2008-12-30

Bias plays an important role in factor analysis and is often implicitly made use of, for example, to constrain solutions to factors that conform to physical reality. However, when components are collinear, a large range of solutions may exist that satisfy the basic constraints and fit the data equally well. In such cases, the introduction of mathematical bias through the application of constraints may select solutions that are less than optimal. The biased alternating least squares algorithm of the present invention can offset mathematical bias introduced by constraints in the standard alternating least squares analysis to achieve factor solutions that are most consistent with physical reality. In addition, these methods can be used to explicitly exploit bias to provide alternative views and provide additional insights into spectral data sets.

Method for factor analysis of GC/MS data

DOEpatents

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

2012-09-11

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

34 CFR 472.23 - What additional factor does the Secretary consider?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 3 2010-07-01 2010-07-01 false What additional factor does the Secretary consider? 472.23 Section 472.23 Education Regulations of the Offices of the Department of Education (Continued) OFFICE OF VOCATIONAL AND ADULT EDUCATION, DEPARTMENT OF EDUCATION NATIONAL WORKPLACE LITERACY PROGRAM How...

34 CFR 648.32 - What additional factors does the Secretary consider?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 3 2010-07-01 2010-07-01 false What additional factors does the Secretary consider? 648.32 Section 648.32 Education Regulations of the Offices of the Department of Education (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION GRADUATE ASSISTANCE IN AREAS OF NATIONAL NEED...

34 CFR 490.22 - What additional factor does the Secretary consider?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 3 2010-07-01 2010-07-01 false What additional factor does the Secretary consider? 490.22 Section 490.22 Education Regulations of the Offices of the Department of Education (Continued) OFFICE OF VOCATIONAL AND ADULT EDUCATION, DEPARTMENT OF EDUCATION LIFE SKILLS FOR STATE AND LOCAL...

34 CFR 490.22 - What additional factor does the Secretary consider?

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 3 2011-07-01 2011-07-01 false What additional factor does the Secretary consider? 490.22 Section 490.22 Education Regulations of the Offices of the Department of Education (Continued) OFFICE OF VOCATIONAL AND ADULT EDUCATION, DEPARTMENT OF EDUCATION LIFE SKILLS FOR STATE AND LOCAL...

Factors affecting construction performance: exploratory factor analysis

NASA Astrophysics Data System (ADS)

Soewin, E.; Chinda, T.

2018-04-01

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

7 CFR 91.38 - Additional fees for appeal of analysis.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 3 2010-01-01 2010-01-01 false Additional fees for appeal of analysis. 91.38 Section... LABORATORY TESTING PROGRAMS SERVICES AND GENERAL INFORMATION Fees and Charges § 91.38 Additional fees for appeal of analysis. (a) The applicant for appeal sample testing will be charged a fee at the hourly rate...

7 CFR 91.38 - Additional fees for appeal of analysis.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 3 2013-01-01 2013-01-01 false Additional fees for appeal of analysis. 91.38 Section... LABORATORY TESTING PROGRAMS SERVICES AND GENERAL INFORMATION Fees and Charges § 91.38 Additional fees for appeal of analysis. (a) The applicant for appeal sample testing will be charged a fee at the hourly rate...

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…

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

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

PubMed

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

1997-07-01

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

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.

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

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.

An Analysis Of Additive Manufacturing Production Problems And Solutions

DTIC Science & Technology

2016-12-01

democratization of manufacturing (Hornick, 2015). AM has three distinct advantages over subtractive manufacturing : product customization, design flexibility...58 develops software and other technology solutions for the design , analysis, testing, manufacture , and validation of products (Diane Ryan, personal...NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA MBA PROFESSIONAL REPORT AN ANALYSIS OF ADDITIVE MANUFACTURING PRODUCTION

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

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 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.

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

NASA Astrophysics Data System (ADS)

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

2011-11-01

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

Additional EIPC Study Analysis. Final Report

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

Hadley, Stanton W; Gotham, Douglas J.; Luciani, Ralph L.

Between 2010 and 2012 the Eastern Interconnection Planning Collaborative (EIPC) conducted a major long-term resource and transmission study of the Eastern Interconnection (EI). With guidance from a Stakeholder Steering Committee (SSC) that included representatives from the Eastern Interconnection States Planning Council (EISPC) among others, the project was conducted in two phases. Phase 1 involved a long-term capacity expansion analysis that involved creation of eight major futures plus 72 sensitivities. Three scenarios were selected for more extensive transmission- focused evaluation in Phase 2. Five power flow analyses, nine production cost model runs (including six sensitivities), and three capital cost estimations weremore » developed during this second phase. The results from Phase 1 and 2 provided a wealth of data that could be examined further to address energy-related questions. A list of 14 topics was developed for further analysis. This paper brings together the earlier interim reports of the first 13 topics plus one additional topic into a single final report.« less

Effects of additional data on Bayesian clustering.

PubMed

Yamazaki, Keisuke

2017-10-01

Hierarchical probabilistic models, such as mixture models, are used for cluster analysis. These models have two types of variables: observable and latent. In cluster analysis, the latent variable is estimated, and it is expected that additional information will improve the accuracy of the estimation of the latent variable. Many proposed learning methods are able to use additional data; these include semi-supervised learning and transfer learning. However, from a statistical point of view, a complex probabilistic model that encompasses both the initial and additional data might be less accurate due to having a higher-dimensional parameter. The present paper presents a theoretical analysis of the accuracy of such a model and clarifies which factor has the greatest effect on its accuracy, the advantages of obtaining additional data, and the disadvantages of increasing the complexity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Factor Analysis of Intern Effectiveness

ERIC Educational Resources Information Center

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

2012-01-01

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

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.

Adiponectin provides additional information to conventional cardiovascular risk factors for assessing the risk of atherosclerosis in both genders.

PubMed

Yoon, Jin-Ha; Kim, Sung-Kyung; Choi, Ho-June; Choi, Soo-In; Cha, So-Youn; Koh, Sang-Baek; Kang, Hee-Taik; Ahn, Song Vogue

2013-01-01

This study evaluated the relation between adiponectin and atherosclerosis in both genders, and investigated whether adiponectin provides useful additional information for assessing the risk of atherosclerosis. We measured serum adiponectin levels and other cardiovascular risk factors in 1033 subjects (454 men, 579 women) from the Korean Genomic Rural Cohort study. Carotid intima-media-thickness (CIMT) was used as measure of atherosclerosis. Odds ratios (ORs) with 95% confidence intervals (95% CI) were calculated using multiple logistic regression, and receiver operating characteristic curves (ROC), the category-free net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated. After adjustment for conventional cardiovascular risk factors, such as age, waist circumference, smoking history, low-density and high-density lipoprotein cholesterol, triglycerides, systolic blood pressure and insulin resistance, the ORs (95%CI) of the third tertile adiponectin group were 0.42 (0.25-0.72) in men and 0.47 (0.29-0.75) in women. The area under the curve (AUC) on the ROC analysis increased significantly by 0.025 in men and 0.022 in women when adiponectin was added to the logistic model of conventional cardiovascular risk factors (AUC in men: 0.655 to 0.680, p = 0.038; AUC in women: 0.654 to 0.676, p = 0.041). The NRI was 0.32 (95%CI: 0.13-0.50, p<0.001), and the IDI was 0.03 (95%CI: 0.01-0.04, p<0.001) for men. For women, the category-free NRI was 0.18 (95%CI: 0.02-0.34, p = 0.031) and the IDI was 0.003 (95%CI: -0.002-0.008, p = 0.189). Adiponectin and atherosclerosis were significantly related in both genders, and these relationships were independent of conventional cardiovascular risk factors. Furthermore, adiponectin provided additional information to conventional cardiovascular risk factors regarding the risk of atherosclerosis.

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…

Computed Tomography Inspection and Analysis for Additive Manufacturing Components

NASA Technical Reports Server (NTRS)

Beshears, Ronald D.

2016-01-01

Computed tomography (CT) inspection was performed on test articles additively manufactured from metallic materials. Metallic AM and machined wrought alloy test articles with programmed flaws were inspected using a 2MeV linear accelerator based CT system. Performance of CT inspection on identically configured wrought and AM components and programmed flaws was assessed using standard image analysis techniques to determine the impact of additive manufacturing on inspectability of objects with complex geometries.

Analysis of Air Toxics From NOAA WP-3 Aircraft Measurements During the TexAQS 2006 Campaign: Comparison With Emission Inventories and Additive Inhalation Risk Factors

NASA Astrophysics Data System (ADS)

Del Negro, L. A.; Warneke, C.; de Gouw, J. A.; Atlas, E.; Lueb, R.; Zhu, X.; Pope, L.; Schauffler, S.; Hendershot, R.; Washenfelder, R.; Fried, A.; Richter, D.; Walega, J. G.; Weibring, P.

2007-12-01

Benzene and nine other air toxics classified as human carcinogens by the International Agency for Research on Cancer (IARC) were measured from the NOAA WP-3 aircraft during the TexAQS 2006 campaign. In-situ measurements of benzene, measured with a PTR-MS instrument, are used to estimate emission fluxes for comparison with point source emission inventories developed by the Texas Commission on Environmental Quality. Mean and median mixing ratios for benzene, acetaldehyde, formaldehyde, 1,3-butadiene, carbon tetrachloride, chloroform, 1,2-dichloroethane, dibromoethane, dichloromethane, and vinyl chloride, encountered over the city of Houston during the campaign, are combined with inhalation unit risk factor values developed by the California Environmental Protection Agency and the United States Environmental Protection Agency to estimate the additive inhalation risk factor. This additive risk factor represents the risk associated with lifetime (70 year) exposure at the levels measured and should not be used as an absolute indicator of risk to individuals. However, the results are useful for assessments of changing relative risk over time, and for identifying dominant contributions to the overall air toxic risk.

Additional risk factors for lethal hypothermia.

PubMed

Bright, Fiona; Gilbert, John D; Winskog, Calle; Byard, Roger W

2013-08-01

An 86-year-old woman was found dead lying on her back on the floor of an unkempt kitchen. She had last been seen four days before. Her dress was pulled up and she was not wearing underpants. The house was noted to be in "disarray" with papers covering most surfaces and the floor. Rubbish was piled up against one of the doors. At autopsy the major findings were of a fractured left neck of femur, fresh pressure areas over her right buttock, Wischnewski spots of the stomach and foci of pancreatic necrosis, in keeping with hypothermia. No significant underlying organic diseases were identified and there was no other evidence of trauma. Death was due to hypothermia complicating immobility from a fractured neck of femur. This case confirms the vulnerability of frail, elderly and socially-isolated individuals to death from hypothermia if a significant illness or injury occurs. Additional risk factors for hypothermia are also illustrated in this case that involve inadequate housing construction with absent insulation and window double glazing. The approach to hypothermic deaths should, therefore, include checking for these features as well as measuring room and environmental temperatures, evaluating the type and quality of heating and the nature of the floor and its coverings, Given the ageing population in many Western countries, increasing social isolation of the elderly, cost of fuel and electricity, and lack of energy efficient housing, this type of death may become an increasingly witnessed occurrence during the colder months of the year. Copyright © 2012 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

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

PubMed

Rahim, M A; Magner, N R

1996-10-01

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

NUCLEAR FACTOR Y Transcription Factors Have Both Opposing and Additive Roles in ABA-Mediated Seed Germination

PubMed Central

Kumimoto, Roderick W.; Siriwardana, Chamindika L.; Gayler, Krystal K.; Risinger, Jan R.; Siefers, Nicholas; Holt, Ben F.

2013-01-01

In the model organism Arabidopsis thaliana the heterotrimeric transcription factor NUCLEAR FACTOR Y (NF-Y) has been shown to play multiple roles in facilitating plant growth and development. Although NF-Y itself represents a multi-protein transcriptional complex, recent studies have shown important interactions with other transcription factors, especially those in the bZIP family. Here we add to the growing evidence that NF-Y and bZIP form common complexes to affect many processes. We carried out transcriptional profiling on nf-yc mutants and through subsequent analyses found an enrichment of bZIP binding sites in the promoter elements of misregulated genes. Using NF-Y as bait, yeast two hybrid assays yielded interactions with bZIP proteins that are known to control ABA signaling. Accordingly, we find that plants mutant for several NF-Y subunits show characteristic phenotypes associated with the disruption of ABA signaling. While previous reports have shown additive roles for NF-YC family members in photoperiodic flowering, we found that they can have opposing roles in ABA signaling. Collectively, these results demonstrated the importance and complexity of NF-Y in the integration of environmental and hormone signals. PMID:23527203

A Human Factors Analysis of EVA Time Requirements

NASA Technical Reports Server (NTRS)

Pate, Dennis W.

1997-01-01

Human Factors Engineering (HFE) 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. During the summer of 1995, a human factors motion and time study was initiated with the goals of developing a database of EVA task times and developing a method of utilizing the database to predict how long an EVA should take. Initial development relied on the EVA activities performed during the STS-61 (Hubble) mission. The first step of the study was to become familiar with EVA's, the previous task-time studies, and documents produced on EVA's. After reviewing these documents, an initial set of task primitives and task-time modifiers was developed. Data was collected from videotaped footage of two entire STS-61 EVA missions and portions of several others, each with two EVA astronauts. Feedback from the analysis of the data was used to further refine the primitives and modifiers used. The project was continued during the summer of 1996, during which data on human errors was also collected and analyzed. Additional data from the STS-71 mission was also collected. Analysis of variance techniques for categorical data was used to determine which factors may affect the primitive times and how much of an effect they have. Probability distributions for the various task were also generated. Further analysis of the modifiers and interactions is planned.

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…

Factor Retention in Exploratory Factor Analysis: A Comparison of Alternative Methods.

ERIC Educational Resources Information Center

Mumford, Karen R.; Ferron, John M.; Hines, Constance V.; Hogarty, Kristine Y.; Kromrey, Jeffery D.

This study compared the effectiveness of 10 methods of determining the number of factors to retain in exploratory common factor analysis. The 10 methods included the Kaiser rule and a modified Kaiser criterion, 3 variations of parallel analysis, 4 regression-based variations of the scree procedure, and the minimum average partial procedure. The…

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.

Research on the Additional Secondary Phase Factor for Automatic Identification System Signals Transmitted over a Rough Sea Surface

PubMed Central

Zhang, Shufang; Sun, Xiaowen

2018-01-01

This paper investigates the Additional Secondary Phase Factor (ASF) characteristics of Automatic Identification System (AIS) signals spreading over a rough sea surface. According to the change of the ASFs for AIS signals in different signal form, the influences of the different propagation conditions on the ASFs are analyzed. The expression, numerical calculation, and simulation analysis of the ASFs of AIS signal are performed in the rough sea surface. The results contribute to the high-accuracy propagation delay measurement of AIS signals spreading over the rough sea surface as, well as providing a reference for reliable communication link design in marine engineering for Very High Frequency (VHF) signals. PMID:29462995

Optimal Multicomponent Analysis Using the Generalized Standard Addition Method.

ERIC Educational Resources Information Center

Raymond, Margaret; And Others

1983-01-01

Describes an experiment on the simultaneous determination of chromium and magnesium by spectophotometry modified to include the Generalized Standard Addition Method computer program, a multivariate calibration method that provides optimal multicomponent analysis in the presence of interference and matrix effects. Provides instructions for…

Validation analysis of probabilistic models of dietary exposure to food additives.

PubMed

Gilsenan, M B; Thompson, R L; Lambe, J; Gibney, M J

2003-10-01

The validity of a range of simple conceptual models designed specifically for the estimation of food additive intakes using probabilistic analysis was assessed. Modelled intake estimates that fell below traditional conservative point estimates of intake and above 'true' additive intakes (calculated from a reference database at brand level) were considered to be in a valid region. Models were developed for 10 food additives by combining food intake data, the probability of an additive being present in a food group and additive concentration data. Food intake and additive concentration data were entered as raw data or as a lognormal distribution, and the probability of an additive being present was entered based on the per cent brands or the per cent eating occasions within a food group that contained an additive. Since the three model components assumed two possible modes of input, the validity of eight (2(3)) model combinations was assessed. All model inputs were derived from the reference database. An iterative approach was employed in which the validity of individual model components was assessed first, followed by validation of full conceptual models. While the distribution of intake estimates from models fell below conservative intakes, which assume that the additive is present at maximum permitted levels (MPLs) in all foods in which it is permitted, intake estimates were not consistently above 'true' intakes. These analyses indicate the need for more complex models for the estimation of food additive intakes using probabilistic analysis. Such models should incorporate information on market share and/or brand loyalty.

Drag reduction by polymer additives from turbulent spectra.

PubMed

Calzetta, Esteban

2010-12-01

We extend the analysis of the friction factor for turbulent pipe flow reported by G. Gioia and P. Chakraborty [Phys. Rev. Lett. 96, 044502 (2006)] to the case where drag is reduced by polymer additives.

Adiponectin Provides Additional Information to Conventional Cardiovascular Risk Factors for Assessing the Risk of Atherosclerosis in Both Genders

PubMed Central

Yoon, Jin-Ha; Kim, Sung-Kyung; Choi, Ho-June; Choi, Soo-In; Cha, So-Youn; Koh, Sang-Baek

2013-01-01

Background This study evaluated the relation between adiponectin and atherosclerosis in both genders, and investigated whether adiponectin provides useful additional information for assessing the risk of atherosclerosis. Methods We measured serum adiponectin levels and other cardiovascular risk factors in 1033 subjects (454 men, 579 women) from the Korean Genomic Rural Cohort study. Carotid intima–media-thickness (CIMT) was used as measure of atherosclerosis. Odds ratios (ORs) with 95% confidence intervals (95% CI) were calculated using multiple logistic regression, and receiver operating characteristic curves (ROC), the category-free net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were calculated. Results After adjustment for conventional cardiovascular risk factors, such as age, waist circumference, smoking history, low-density and high-density lipoprotein cholesterol, triglycerides, systolic blood pressure and insulin resistance, the ORs (95%CI) of the third tertile adiponectin group were 0.42 (0.25–0.72) in men and 0.47 (0.29–0.75) in women. The area under the curve (AUC) on the ROC analysis increased significantly by 0.025 in men and 0.022 in women when adiponectin was added to the logistic model of conventional cardiovascular risk factors (AUC in men: 0.655 to 0.680, p = 0.038; AUC in women: 0.654 to 0.676, p = 0.041). The NRI was 0.32 (95%CI: 0.13–0.50, p<0.001), and the IDI was 0.03 (95%CI: 0.01–0.04, p<0.001) for men. For women, the category-free NRI was 0.18 (95%CI: 0.02–0.34, p = 0.031) and the IDI was 0.003 (95%CI: −0.002–0.008, p = 0.189). Conclusion Adiponectin and atherosclerosis were significantly related in both genders, and these relationships were independent of conventional cardiovascular risk factors. Furthermore, adiponectin provided additional information to conventional cardiovascular risk factors regarding the risk of atherosclerosis. PMID:24116054

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

PubMed

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

2018-03-22

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

Congruence of Additive and Non-Additive Effects on Gene Expression Estimated from Pedigree and SNP Data

PubMed Central

Powell, Joseph E.; Henders, Anjali K.; McRae, Allan F.; Kim, Jinhee; Hemani, Gibran; Martin, Nicholas G.; Dermitzakis, Emmanouil T.; Gibson, Greg

2013-01-01

There is increasing evidence that heritable variation in gene expression underlies genetic variation in susceptibility to disease. Therefore, a comprehensive understanding of the similarity between relatives for transcript variation is warranted—in particular, dissection of phenotypic variation into additive and non-additive genetic factors and shared environmental effects. We conducted a gene expression study in blood samples of 862 individuals from 312 nuclear families containing MZ or DZ twin pairs using both pedigree and genotype information. From a pedigree analysis we show that the vast majority of genetic variation across 17,994 probes is additive, although non-additive genetic variation is identified for 960 transcripts. For 180 of the 960 transcripts with non-additive genetic variation, we identify expression quantitative trait loci (eQTL) with dominance effects in a sample of 339 unrelated individuals and replicate 31% of these associations in an independent sample of 139 unrelated individuals. Over-dominance was detected and replicated for a trans association between rs12313805 and ETV6, located 4MB apart on chromosome 12. Surprisingly, only 17 probes exhibit significant levels of common environmental effects, suggesting that environmental and lifestyle factors common to a family do not affect expression variation for most transcripts, at least those measured in blood. Consistent with the genetic architecture of common diseases, gene expression is predominantly additive, but a minority of transcripts display non-additive effects. PMID:23696747

Congruence of additive and non-additive effects on gene expression estimated from pedigree and SNP data.

PubMed

Powell, Joseph E; Henders, Anjali K; McRae, Allan F; Kim, Jinhee; Hemani, Gibran; Martin, Nicholas G; Dermitzakis, Emmanouil T; Gibson, Greg; Montgomery, Grant W; Visscher, Peter M

2013-05-01

There is increasing evidence that heritable variation in gene expression underlies genetic variation in susceptibility to disease. Therefore, a comprehensive understanding of the similarity between relatives for transcript variation is warranted--in particular, dissection of phenotypic variation into additive and non-additive genetic factors and shared environmental effects. We conducted a gene expression study in blood samples of 862 individuals from 312 nuclear families containing MZ or DZ twin pairs using both pedigree and genotype information. From a pedigree analysis we show that the vast majority of genetic variation across 17,994 probes is additive, although non-additive genetic variation is identified for 960 transcripts. For 180 of the 960 transcripts with non-additive genetic variation, we identify expression quantitative trait loci (eQTL) with dominance effects in a sample of 339 unrelated individuals and replicate 31% of these associations in an independent sample of 139 unrelated individuals. Over-dominance was detected and replicated for a trans association between rs12313805 and ETV6, located 4MB apart on chromosome 12. Surprisingly, only 17 probes exhibit significant levels of common environmental effects, suggesting that environmental and lifestyle factors common to a family do not affect expression variation for most transcripts, at least those measured in blood. Consistent with the genetic architecture of common diseases, gene expression is predominantly additive, but a minority of transcripts display non-additive effects.

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.

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.

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.

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

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…

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…

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…

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

PubMed

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

2014-07-01

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

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

PubMed

Pushpanathan, Maria E; Loftus, Andrea M; Gasson, Natalie; Thomas, Meghan G; Timms, Caitlin F; Olaithe, Michelle; Bucks, Romola S

2018-01-01

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

Confirmatory factor analysis of the Child Health Questionnaire-Parent Form 50 in a predominantly minority sample.

PubMed

Hepner, Kimberly A; Sechrest, Lee

2002-12-01

The Child Health Questionnaire-Parent Form 50 (CHQ-PF50; Landgraf JM et al., The CHQ User's Manual. Boston, MA: The Health Institute, New England Medical Centre, 1996) appears to be a useful method of assessing children's health. The CHQ-PF50 is designed to measure general functional status and well-being and is available in several versions to suit the needs of the health researcher. Several publications have reported favorably on the psychometric properties of the CHQ. Landgraf et al. reported the results of an exploratory factor analysis at the scale level that provided evidence for a two-factor structure representing physical and psychosocial dimensions of health. In order to cross-validate and extend these results, a confirmatory factor analysis was conducted with an independent sample of generally healthy, predominantly minority children. Results of the analysis indicate that a two-factor model provides a good fit to the data, confirming previous exploratory analyses with this questionnaire. One additional method factor seems likely because of the substantial similarity of three of the scales, but that does not affect the substantive two-factor interpretation overall.

[Analysis of mitochondrial SNPs in addition to conventional STR-typing in a case of aggravated theft].

PubMed

Röper, Andrea; Reichert, Walter; Mattern, Rainer

2007-01-01

In the field of forensic DNA typing, the analysis of Short Tandem Repeats (STRs) can fail in cases of degraded DNA. The typing of coding region Single Nucleotide Polymorphisms (SNPs) of the mitochondrial genome provides an approach to acquire additional information. In the examined case of aggravated theft, both suspects could be excluded of having left the analyzed hair on the crime scene by SNP typing. This conclusion was not possible subsequent to STR typing. SNP typing of the trace on the torch light left on the crime scene increased the likelihood for suspect no. 2 to be the origin of this trace. This finding was already indicated by STR analysis. Suspect no. 1 was excluded for being the origin of this trace by SNP typing which was also indicated by STR analysis. A limiting factor for the analysis of SNPs is the maternal inheritance of mitochondrial DNA. Individualisation is not possible. In conclusion, it can be said that in the case of traces which cause problems with conventional STR typing the supplementary analysis of coding region SNPs from the mitochondrial genome is very reasonable and greatly contributes to the refinement of analysis methods in the field of forensic genetics.

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…

Determination of important topographic factors for landslide mapping analysis using MLP network.

PubMed

Alkhasawneh, Mutasem Sh; Ngah, Umi Kalthum; Tay, Lea Tien; Mat Isa, Nor Ashidi; Al-batah, Mohammad Subhi

2013-01-01

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

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

PubMed Central

Alkhasawneh, Mutasem Sh.; Ngah, Umi Kalthum; Mat Isa, Nor Ashidi; Al-batah, Mohammad Subhi

2013-01-01

Landslide is one of the natural disasters that occur in Malaysia. Topographic factors such as elevation, slope angle, slope aspect, general curvature, plan curvature, and profile curvature are considered as the main causes of landslides. In order to determine the dominant topographic factors in landslide mapping analysis, a study was conducted and presented in this paper. There are three main stages involved in this study. The first stage is the extraction of extra topographic factors. Previous landslide studies had identified mainly six topographic factors. Seven new additional factors have been proposed in this study. They are longitude curvature, tangential curvature, cross section curvature, surface area, diagonal line length, surface roughness, and rugosity. The second stage is the specification of the weight of each factor using two methods. The methods are multilayer perceptron (MLP) network classification accuracy and Zhou's algorithm. At the third stage, the factors with higher weights were used to improve the MLP performance. Out of the thirteen factors, eight factors were considered as important factors, which are surface area, longitude curvature, diagonal length, slope angle, elevation, slope aspect, rugosity, and profile curvature. The classification accuracy of multilayer perceptron neural network has increased by 3% after the elimination of five less important factors. PMID:24453846

THE VALIDITY OF CLINICAL DIFFERENTIATION BETWEEN ANXIETY AND DEPRESSIVE NEUROSES BY FACTOR ANALYSIS

PubMed Central

Singh, Gurmeet; Sharma, Ravinder Kumar

1986-01-01

SUMMARY Ninety subjects consisting of 30 patients of generalized anxiety disorder, 30 of dysthymic disorder (depressive neurosis) according to D. S. M. III criteria and 30 patients of mixed anxiety-depressive disorder were given a detailed psychiatric examination, in addition, they were administered the Humilton rating scales for anxiety and depression, and also the Taylor manifest anxiety scale and Amritsar depressive inventory. All the symptoms elicited were then subjected to factor analysis, five factors were isolated-two of them co-relating with the depressive rating scales and three with the anxiety rating scales. However there was considerable overlap with anxious mood having highest loading on the depressive factor. Thus anxiety and depression could not be isolated as distinct entities factorially. PMID:21927176

34 CFR 658.34 - What additional factors does the Secretary consider in selecting grant recipients?

Code of Federal Regulations, 2010 CFR

2010-07-01

... 34 Education 3 2010-07-01 2010-07-01 false What additional factors does the Secretary consider in selecting grant recipients? 658.34 Section 658.34 Education Regulations of the Offices of the Department of Education (Continued) OFFICE OF POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION UNDERGRADUATE INTERNATIONAL...

Anti-wear Mechanism Analysis of Nano-CaCO3 Additives

NASA Astrophysics Data System (ADS)

Xu, Zhen; Sun, Junfeng

2018-06-01

In this paper, the wear test was carried on with cylinder piston by the wear test device, receiving the results of the piston ring wear and abrasive characteristics by monitoring the wear process, the thesis analysis and put forward the nano-CaCO3 lubricating oil additive anti wear mechanism by the ferrography analysis technology, and provide the technical reference for the relevant measures to reduce wear and the friction, and provide reference value for further study on the related theories of reducing wear and reducing friction.

Analysis of redox additive-based overcharge protection for rechargeable lithium batteries

NASA Technical Reports Server (NTRS)

Narayanan, S. R.; Surampudi, S.; Attia, A. I.; Bankston, C. P.

1991-01-01

The overcharge condition in secondary lithium batteries employing redox additives for overcharge protection, has been theoretically analyzed in terms of a finite linear diffusion model. The analysis leads to expressions relating the steady-state overcharge current density and cell voltage to the concentration, diffusion coefficient, standard reduction potential of the redox couple, and interelectrode distance. The model permits the estimation of the maximum permissible overcharge rate for any chosen set of system conditions. Digital simulation of the overcharge experiment leads to numerical representation of the potential transients, and estimate of the influence of diffusion coefficient and interelectrode distance on the transient attainment of the steady state during overcharge. The model has been experimentally verified using 1,1-prime-dimethyl ferrocene as a redox additive. The analysis of the experimental results in terms of the theory allows the calculation of the diffusion coefficient and the formal potential of the redox couple. The model and the theoretical results may be exploited in the design and optimization of overcharge protection by the redox additive approach.

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

NASA Astrophysics Data System (ADS)

Drake, Joshua P.

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

Effect of Ferrous Additives on Magnesia Stone Hydration

NASA Astrophysics Data System (ADS)

Zimich, V.

2017-11-01

The article deals with the modification of the magnesia binder with additives containing two- and three-valent iron cations which could be embedded in the chloromagnesium stone structure and also increase the strength from 60 MPa in a non-additive stone to 80MPa, water resistance from 0.58 for clear stone to 0.8 and reduce the hygroscopicity from 8% in the non-additive stone to 2% in the modified chloromagnesium stone. It is proposed to use the iron hydroxide sol as an additive in the quantities of up to 1% of the weight of the binder. The studies were carried out using the modern analysis methods: the differentialthermal and X-ray phase analysis. The structure was studied with an electron microscope with an X-ray microanalyzer. A two-factor plan-experiment was designed which allowed constructing mathematical models characterizing the influence of variable factors, such as the density of the zatcher and the amount of sol in the binder, on the basic properties of the magnesian stone. The result of the research was the magnesia stone with the claimed properties and formed from minerals characteristic for magnesian materials as well as additionally formed from amachenite and goethite. It has been established that a highly active iron hydroxide sol the ion sizes of which are commensurate with magnesium ions is actively incorporated into the structure of pentahydroxychloride and magnesium hydroxide changing the habit of crystals compacting the structure of the stone and changing its hygroscopicity.

7 CFR 91.38 - Additional fees for appeal of analysis.

Code of Federal Regulations, 2014 CFR

2014-01-01

... LABORATORY TESTING PROGRAMS SERVICES AND GENERAL INFORMATION Fees and Charges § 91.38 Additional fees for appeal of analysis. (a) The applicant for appeal sample testing will be charged a fee at the hourly rate for laboratory service that appears in this paragraph. The new fiscal year for Science and Technology...

7 CFR 91.38 - Additional fees for appeal of analysis.

Code of Federal Regulations, 2011 CFR

2011-01-01

... LABORATORY TESTING PROGRAMS SERVICES AND GENERAL INFORMATION Fees and Charges § 91.38 Additional fees for appeal of analysis. (a) The applicant for appeal sample testing will be charged a fee at the hourly rate for laboratory service that appears in this paragraph. The new fiscal year for Science and Technology...

7 CFR 91.38 - Additional fees for appeal of analysis.

Code of Federal Regulations, 2012 CFR

2012-01-01

... LABORATORY TESTING PROGRAMS SERVICES AND GENERAL INFORMATION Fees and Charges § 91.38 Additional fees for appeal of analysis. (a) The applicant for appeal sample testing will be charged a fee at the hourly rate for laboratory service that appears in this paragraph. The new fiscal year for Science and Technology...

Stimulation of terrestrial ecosystem carbon storage by nitrogen addition: a meta-analysis

PubMed Central

Yue, Kai; Peng, Yan; Peng, Changhui; Yang, Wanqin; Peng, Xin; Wu, Fuzhong

2016-01-01

Elevated nitrogen (N) deposition alters the terrestrial carbon (C) cycle, which is likely to feed back to further climate change. However, how the overall terrestrial ecosystem C pools and fluxes respond to N addition remains unclear. By synthesizing data from multiple terrestrial ecosystems, we quantified the response of C pools and fluxes to experimental N addition using a comprehensive meta-analysis method. Our results showed that N addition significantly stimulated soil total C storage by 5.82% ([2.47%, 9.27%], 95% CI, the same below) and increased the C contents of the above- and below-ground parts of plants by 25.65% [11.07%, 42.12%] and 15.93% [6.80%, 25.85%], respectively. Furthermore, N addition significantly increased aboveground net primary production by 52.38% [40.58%, 65.19%] and litterfall by 14.67% [9.24%, 20.38%] at a global scale. However, the C influx from the plant litter to the soil through litter decomposition and the efflux from the soil due to microbial respiration and soil respiration showed insignificant responses to N addition. Overall, our meta-analysis suggested that N addition will increase soil C storage and plant C in both above- and below-ground parts, indicating that terrestrial ecosystems might act to strengthen as a C sink under increasing N deposition. PMID:26813078

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.

Relative Importance and Additive Effects of Maternal and Infant Risk Factors on Childhood Asthma

PubMed Central

Rosas-Salazar, Christian; James, Kristina; Escobar, Gabriel; Gebretsadik, Tebeb; Li, Sherian Xu; Carroll, Kecia N.; Walsh, Eileen; Mitchel, Edward; Das, Suman; Kumar, Rajesh; Yu, Chang; Dupont, William D.; Hartert, Tina V.

2016-01-01

Background Environmental exposures that occur in utero and during early life may contribute to the development of childhood asthma through alteration of the human microbiome. The objectives of this study were to estimate the cumulative effect and relative importance of environmental exposures on the risk of childhood asthma. Methods We conducted a population-based birth cohort study of mother-child dyads who were born between 1995 and 2003 and were continuously enrolled in the PRIMA (Prevention of RSV: Impact on Morbidity and Asthma) cohort. The individual and cumulative impact of maternal urinary tract infections (UTI) during pregnancy, maternal colonization with group B streptococcus (GBS), mode of delivery, infant antibiotic use, and older siblings at home, on the risk of childhood asthma were estimated using logistic regression. Dose-response effect on childhood asthma risk was assessed for continuous risk factors: number of maternal UTIs during pregnancy, courses of infant antibiotics, and number of older siblings at home. We further assessed and compared the relative importance of these exposures on the asthma risk. In a subgroup of children for whom maternal antibiotic use during pregnancy information was available, the effect of maternal antibiotic use on the risk of childhood asthma was estimated. Results Among 136,098 singleton birth infants, 13.29% developed asthma. In both univariate and adjusted analyses, maternal UTI during pregnancy (odds ratio [OR] 1.2, 95% confidence interval [CI] 1.18, 1.25; adjusted OR [AOR] 1.04, 95%CI 1.02, 1.07 for every additional UTI) and infant antibiotic use (OR 1.21, 95%CI 1.20, 1.22; AOR 1.16, 95%CI 1.15, 1.17 for every additional course) were associated with an increased risk of childhood asthma, while having older siblings at home (OR 0.92, 95%CI 0.91, 0.93; AOR 0.85, 95%CI 0.84, 0.87 for each additional sibling) was associated with a decreased risk of childhood asthma, in a dose-dependent manner. Compared with vaginal

Relative Importance and Additive Effects of Maternal and Infant Risk Factors on Childhood Asthma.

PubMed

Wu, Pingsheng; Feldman, Amy S; Rosas-Salazar, Christian; James, Kristina; Escobar, Gabriel; Gebretsadik, Tebeb; Li, Sherian Xu; Carroll, Kecia N; Walsh, Eileen; Mitchel, Edward; Das, Suman; Kumar, Rajesh; Yu, Chang; Dupont, William D; Hartert, Tina V

2016-01-01

Environmental exposures that occur in utero and during early life may contribute to the development of childhood asthma through alteration of the human microbiome. The objectives of this study were to estimate the cumulative effect and relative importance of environmental exposures on the risk of childhood asthma. We conducted a population-based birth cohort study of mother-child dyads who were born between 1995 and 2003 and were continuously enrolled in the PRIMA (Prevention of RSV: Impact on Morbidity and Asthma) cohort. The individual and cumulative impact of maternal urinary tract infections (UTI) during pregnancy, maternal colonization with group B streptococcus (GBS), mode of delivery, infant antibiotic use, and older siblings at home, on the risk of childhood asthma were estimated using logistic regression. Dose-response effect on childhood asthma risk was assessed for continuous risk factors: number of maternal UTIs during pregnancy, courses of infant antibiotics, and number of older siblings at home. We further assessed and compared the relative importance of these exposures on the asthma risk. In a subgroup of children for whom maternal antibiotic use during pregnancy information was available, the effect of maternal antibiotic use on the risk of childhood asthma was estimated. Among 136,098 singleton birth infants, 13.29% developed asthma. In both univariate and adjusted analyses, maternal UTI during pregnancy (odds ratio [OR] 1.2, 95% confidence interval [CI] 1.18, 1.25; adjusted OR [AOR] 1.04, 95%CI 1.02, 1.07 for every additional UTI) and infant antibiotic use (OR 1.21, 95%CI 1.20, 1.22; AOR 1.16, 95%CI 1.15, 1.17 for every additional course) were associated with an increased risk of childhood asthma, while having older siblings at home (OR 0.92, 95%CI 0.91, 0.93; AOR 0.85, 95%CI 0.84, 0.87 for each additional sibling) was associated with a decreased risk of childhood asthma, in a dose-dependent manner. Compared with vaginal delivery, C

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.

Clustering of leptin and physical activity with components of metabolic syndrome in Iranian population: an exploratory factor analysis.

PubMed

Esteghamati, Alireza; Zandieh, Ali; Khalilzadeh, Omid; Morteza, Afsaneh; Meysamie, Alipasha; Nakhjavani, Manouchehr; Gouya, Mohammad Mehdi

2010-10-01

Metabolic syndrome (MetS), manifested by insulin resistance, dyslipidemia, central obesity, and hypertension, is conceived to be associated with hyperleptinemia and physical activity. The aim of this study was to elucidate the factors underlying components of MetS and also to test the suitability of leptin and physical activity as additional components of this syndrome. Data of the individuals without history of diabetes mellitus, aged 25-64 years, from third national surveillance of risk factors of non-communicable diseases (SuRFNCD-2007), were analyzed. Performing factor analysis on waist circumference, homeostasis model assessment of insulin resistance, systolic blood pressure, triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C) led to extraction of two factors which explained around 59.0% of the total variance in both genders. When TG and HDL-C were replaced by TG to HDL-C ratio, a single factor was obtained. In contrast to physical activity, addition of leptin was consistent with one-factor structure of MetS and improved the ability of suggested models to identify obesity (BMI≥30 kg/m2, P<0.01), using receiver-operator characteristics curve analysis. In general, physical activity loaded on the first identified factor. Our study shows that one underlying factor structure of MetS is also plausible and the inclusion of leptin does not interfere with this structure. Further, this study suggests that physical activity influences MetS components via modulation of the main underlying pathophysiologic pathway of this syndrome.

Consolidation & Factors Influencing Sintering Process in Polymer Powder Based Additive Manufacturing

NASA Astrophysics Data System (ADS)

Sagar, M. B.; Elangovan, K.

2017-08-01

Additive Manufacturing (AM) is two decade old technology; where parts are build layer manufacturing method directly from a CAD template. Over the years, AM techniques changes the future way of part fabrication with enhanced intricacy and custom-made features are aimed. Commercially polymers, metals, ceramic and metal-polymer composites are in practice where polymers enhanced the expectations in AM and are considered as a kind of next industrial revolution. Growing trend in polymer application motivated to study their feasibility and properties. Laser sintering, Heat sintering and Inhibition sintering are the most successful AM techniques for polymers but having least application. The presentation gives up selective sintering of powder polymers and listed commercially available polymer materials. Important significant factors for effective processing and analytical approaches to access them are discussed.

Likelihood-Based Confidence Intervals in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Oort, Frans J.

2011-01-01

In exploratory or unrestricted factor analysis, all factor loadings are free to be estimated. In oblique solutions, the correlations between common factors are free to be estimated as well. The purpose of this article is to show how likelihood-based confidence intervals can be obtained for rotated factor loadings and factor correlations, by…

Interactive effects of global change factors on soil respiration and its components: a meta-analysis.

PubMed

Zhou, Lingyan; Zhou, Xuhui; Shao, Junjiong; Nie, Yuanyuan; He, Yanghui; Jiang, Liling; Wu, Zhuoting; Hosseini Bai, Shahla

2016-09-01

As the second largest carbon (C) flux between the atmosphere and terrestrial ecosystems, soil respiration (Rs) plays vital roles in regulating atmospheric CO2 concentration ([CO2 ]) and climatic dynamics in the earth system. Although numerous manipulative studies and a few meta-analyses have been conducted to determine the responses of Rs and its two components [i.e., autotrophic (Ra) and heterotrophic (Rh) respiration] to single global change factors, the interactive effects of the multiple factors are still unclear. In this study, we performed a meta-analysis of 150 multiple-factor (≥2) studies to examine the main and interactive effects of global change factors on Rs and its two components. Our results showed that elevated [CO2 ] (E), nitrogen addition (N), irrigation (I), and warming (W) induced significant increases in Rs by 28.6%, 8.8%, 9.7%, and 7.1%, respectively. The combined effects of the multiple factors, EN, EW, DE, IE, IN, IW, IEW, and DEW, were also significantly positive on Rs to a greater extent than those of the single-factor ones. For all the individual studies, the additive interactions were predominant on Rs (90.6%) and its components (≈70.0%) relative to synergistic and antagonistic ones. However, the different combinations of global change factors (e.g., EN, NW, EW, IW) indicated that the three types of interactions were all important, with two combinations for synergistic effects, two for antagonistic, and five for additive when at least eight independent experiments were considered. In addition, the interactions of elevated [CO2 ] and warming had opposite effects on Ra and Rh, suggesting that different processes may influence their responses to the multifactor interactions. Our study highlights the crucial importance of the interactive effects among the multiple factors on Rs and its components, which could inform regional and global models to assess the climate-biosphere feedbacks and improve predictions of the future states of the

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,…

Multivariate qualitative analysis of banned additives in food safety using surface enhanced Raman scattering spectroscopy

NASA Astrophysics Data System (ADS)

He, Shixuan; Xie, Wanyi; Zhang, Wei; Zhang, Liqun; Wang, Yunxia; Liu, Xiaoling; Liu, Yulong; Du, Chunlei

2015-02-01

A novel strategy which combines iteratively cubic spline fitting baseline correction method with discriminant partial least squares qualitative analysis is employed to analyze the surface enhanced Raman scattering (SERS) spectroscopy of banned food additives, such as Sudan I dye and Rhodamine B in food, Malachite green residues in aquaculture fish. Multivariate qualitative analysis methods, using the combination of spectra preprocessing iteratively cubic spline fitting (ICSF) baseline correction with principal component analysis (PCA) and discriminant partial least squares (DPLS) classification respectively, are applied to investigate the effectiveness of SERS spectroscopy for predicting the class assignments of unknown banned food additives. PCA cannot be used to predict the class assignments of unknown samples. However, the DPLS classification can discriminate the class assignment of unknown banned additives using the information of differences in relative intensities. The results demonstrate that SERS spectroscopy combined with ICSF baseline correction method and exploratory analysis methodology DPLS classification can be potentially used for distinguishing the banned food additives in field of food safety.

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

NASA Astrophysics Data System (ADS)

Rahmawati, Sela; Suprijadi, Jadi; Zulhanif

2017-03-01

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

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…

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

PubMed

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

2017-04-19

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

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.

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

Additional weekend therapy may reduce length of rehabilitation stay after stroke: a meta-analysis of individual patient data.

PubMed

English, Coralie; Shields, Nora; Brusco, Natasha K; Taylor, Nicholas F; Watts, Jennifer J; Peiris, Casey; Bernhardt, Julie; Crotty, Maria; Esterman, Adrian; Segal, Leonie; Hillier, Susan

2016-07-01

Among people receiving inpatient rehabilitation after stroke, does additional weekend physiotherapy and/or occupational therapy reduce the length of rehabilitation hospital stay compared to those who receive a weekday-only service, and does this change after controlling for individual factors? Does additional weekend therapy improve the ability to walk and perform activities of daily living, measured at discharge? Does additional weekend therapy improve health-related quality of life, measured 6 months after discharge from rehabilitation? Which individual, clinical and hospital characteristics are associated with shorter length of rehabilitation hospital stay? This study pooled individual data from two randomised, controlled trials (n=350) using an individual patient data meta-analysis and multivariate regression. People with stroke admitted to inpatient rehabilitation facilities. Additional weekend therapy (physiotherapy and/or occupational therapy) compared to usual care (5 days/week therapy). Length of rehabilitation hospital stay, independence in activities of daily living measured with the Functional Independence Measure, walking speed and health-related quality of life. Participants who received weekend therapy had a shorter length of rehabilitation hospital stay. In the un-adjusted analysis, this was not statistically significant (MD -5.7 days, 95% CI -13.0 to 1.5). Controlling for hospital site, age, walking speed and Functional Independence Measure score on admission, receiving weekend therapy was significantly associated with a shorter length of rehabilitation hospital stay (β=7.5, 95% CI 1.7 to 13.4, p=0.001). There were no significant between-group differences in Functional Independence Measure scores (MD 1.9 points, 95% CI -2.8 to 6.6), walking speed (MD 0.06 m/second, 95% CI -0.15 to 0.04) or health-related quality of life (SMD -0.04, 95% CI -0.26 to 0.19) at discharge. Modest evidence indicates that additional weekend therapy might reduce

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…

Risk factors for persistent problems following acute whiplash injury: update of a systematic review and meta-analysis.

PubMed

Walton, David M; Macdermid, Joy C; Giorgianni, Anthony A; Mascarenhas, Joanna C; West, Stephen C; Zammit, Caroline A

2013-02-01

Systematic review and meta-analysis. To update a previous review and meta-analysis on risk factors for persistent problems following whiplash secondary to a motor vehicle accident. Prognosis in whiplash-associated disorder (WAD) has become an active area of research, perhaps owing to the difficulty of treating chronic problems. A previously published review and meta-analysis of prognostic factors included primary sources up to May 2007. Since that time, more research has become available, and an update to that original review is warranted. A systematic search of international databases was conducted, with rigorous inclusion criteria focusing on studies published between May 2007 and May 2012. Articles were scored, and data were extracted and pooled to estimate the odds ratio for any factor that had at least 3 independent data points in the literature. Four new cohorts (n = 1121) were identified. In combination with findings of a previous review, 12 variables were found to be significant predictors of poor outcome following whiplash, 9 of which were new (n = 2) or revised (n = 7) as a result of additional data. The significant variables included high baseline pain intensity (greater than 5.5/10), report of headache at inception, less than postsecondary education, no seatbelt in use during the accident, report of low back pain at inception, high Neck Disability Index score (greater than 14.5/50), preinjury neck pain, report of neck pain at inception (regardless of intensity), high catastrophizing, female sex, WAD grade 2 or 3, and WAD grade 3 alone. Those variables robust to publication bias included high pain intensity, female sex, report of headache at inception, less than postsecondary education, high Neck Disability Index score, and WAD grade 2 or 3. Three existing variables (preaccident history of headache, rear-end collision, older age) and 1 additional novel variable (collision severity) were refined or added in this updated review but showed no significant

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)

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

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

PubMed

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

2018-06-15

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

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.

Multivariate qualitative analysis of banned additives in food safety using surface enhanced Raman scattering spectroscopy.

PubMed

He, Shixuan; Xie, Wanyi; Zhang, Wei; Zhang, Liqun; Wang, Yunxia; Liu, Xiaoling; Liu, Yulong; Du, Chunlei

2015-02-25

A novel strategy which combines iteratively cubic spline fitting baseline correction method with discriminant partial least squares qualitative analysis is employed to analyze the surface enhanced Raman scattering (SERS) spectroscopy of banned food additives, such as Sudan I dye and Rhodamine B in food, Malachite green residues in aquaculture fish. Multivariate qualitative analysis methods, using the combination of spectra preprocessing iteratively cubic spline fitting (ICSF) baseline correction with principal component analysis (PCA) and discriminant partial least squares (DPLS) classification respectively, are applied to investigate the effectiveness of SERS spectroscopy for predicting the class assignments of unknown banned food additives. PCA cannot be used to predict the class assignments of unknown samples. However, the DPLS classification can discriminate the class assignment of unknown banned additives using the information of differences in relative intensities. The results demonstrate that SERS spectroscopy combined with ICSF baseline correction method and exploratory analysis methodology DPLS classification can be potentially used for distinguishing the banned food additives in field of food safety. Copyright © 2014 Elsevier B.V. All rights reserved.

Home care nurses' attitudes toward computers. A confirmatory factor analysis of the Stronge and Brodt instrument.

PubMed

Stricklin, Mary Lou; Bierer, S Beth; Struk, Cynthia

2003-01-01

Point-of-care technology for home care use will be the final step in enterprise-wide healthcare electronic communications. Successful implementation of home care point-of-care technology hinges upon nurses' attitudes toward point-of-care technology and its use in clinical practice. This study addresses the factors associated with home care nurses' attitudes using Stronge and Brodt's Nurse Attitudes Toward Computers instrument. In this study, the Nurses Attitudes Toward Computers instrument was administered to a convenience sample of 138 nurses employed by a large midwestern home care agency, with an 88% response rate. Confirmatory factor analysis corroborated the Nurses Attitudes Toward Computers' 3-dimensional factor structure for practicing nurses, which was labeled as nurses' work, security issues, and perceived barriers. Results from the confirmatory factor analysis also suggest that these 3 factors are internally correlated and represent multiple dimensions of a higher order construct labeled as nurses' attitudes toward computers. Additionally, two of these factors, nurses' work and perceived barriers, each appears to explain more variance in nurses' attitudes toward computers than security issues. Instrument reliability was high for the sample (.90), with subscale reliabilities ranging from 86 to 70.

Spectral Analysis: From Additive Perspective to Multiplicative Perspective

NASA Astrophysics Data System (ADS)

Wu, Z.

2017-12-01

The early usage of trigonometric functions can be traced back to at least 17th century BC. It was Bhaskara II of the 12th century CE who first proved the mathematical equivalence between the sum of two trigonometric functions of any given angles and the product of two trigonometric functions of related angles, which has been taught these days in middle school classroom. The additive perspective of trigonometric functions led to the development of the Fourier transform that is used to express any functions as the sum of a set of trigonometric functions and opened a new mathematical field called harmonic analysis. Unfortunately, Fourier's sum cannot directly express nonlinear interactions between trigonometric components of different periods, and thereby lacking the capability of quantifying nonlinear interactions in dynamical systems. In this talk, the speaker will introduce the Huang transform and Holo-spectrum which were pioneered by Norden Huang and emphasizes the multiplicative perspective of trigonometric functions in expressing any function. Holo-spectrum is a multi-dimensional spectral expression of a time series that explicitly identifies the interactions among different scales and quantifies nonlinear interactions hidden in a time series. Along with this introduction, the developing concepts of physical, rather than mathematical, analysis of data will be explained. Various enlightening applications of Holo-spectrum analysis in atmospheric and climate studies will also be presented.

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.

Job strain as a risk factor for clinical depression: systematic review and meta-analysis with additional individual participant data.

PubMed

Madsen, I E H; Nyberg, S T; Magnusson Hanson, L L; Ferrie, J E; Ahola, K; Alfredsson, L; Batty, G D; Bjorner, J B; Borritz, M; Burr, H; Chastang, J-F; de Graaf, R; Dragano, N; Hamer, M; Jokela, M; Knutsson, A; Koskenvuo, M; Koskinen, A; Leineweber, C; Niedhammer, I; Nielsen, M L; Nordin, M; Oksanen, T; Pejtersen, J H; Pentti, J; Plaisier, I; Salo, P; Singh-Manoux, A; Suominen, S; Ten Have, M; Theorell, T; Toppinen-Tanner, S; Vahtera, J; Väänänen, A; Westerholm, P J M; Westerlund, H; Fransson, E I; Heikkilä, K; Virtanen, M; Rugulies, R; Kivimäki, M

2017-06-01

Adverse psychosocial working environments characterized by job strain (the combination of high demands and low control at work) are associated with an increased risk of depressive symptoms among employees, but evidence on clinically diagnosed depression is scarce. We examined job strain as a risk factor for clinical depression. We identified published cohort studies from a systematic literature search in PubMed and PsycNET and obtained 14 cohort studies with unpublished individual-level data from the Individual-Participant-Data Meta-analysis in Working Populations (IPD-Work) Consortium. Summary estimates of the association were obtained using random-effects models. Individual-level data analyses were based on a pre-published study protocol. We included six published studies with a total of 27 461 individuals and 914 incident cases of clinical depression. From unpublished datasets we included 120 221 individuals and 982 first episodes of hospital-treated clinical depression. Job strain was associated with an increased risk of clinical depression in both published [relative risk (RR) = 1.77, 95% confidence interval (CI) 1.47-2.13] and unpublished datasets (RR = 1.27, 95% CI 1.04-1.55). Further individual participant analyses showed a similar association across sociodemographic subgroups and after excluding individuals with baseline somatic disease. The association was unchanged when excluding individuals with baseline depressive symptoms (RR = 1.25, 95% CI 0.94-1.65), but attenuated on adjustment for a continuous depressive symptoms score (RR = 1.03, 95% CI 0.81-1.32). Job strain may precipitate clinical depression among employees. Future intervention studies should test whether job strain is a modifiable risk factor for depression.

A systematic review of methodology: time series regression analysis for environmental factors and infectious diseases.

PubMed

Imai, Chisato; Hashizume, Masahiro

2015-03-01

Time series analysis is suitable for investigations of relatively direct and short-term effects of exposures on outcomes. In environmental epidemiology studies, this method has been one of the standard approaches to assess impacts of environmental factors on acute non-infectious diseases (e.g. cardiovascular deaths), with conventionally generalized linear or additive models (GLM and GAM). However, the same analysis practices are often observed with infectious diseases despite of the substantial differences from non-infectious diseases that may result in analytical challenges. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, systematic review was conducted to elucidate important issues in assessing the associations between environmental factors and infectious diseases using time series analysis with GLM and GAM. Published studies on the associations between weather factors and malaria, cholera, dengue, and influenza were targeted. Our review raised issues regarding the estimation of susceptible population and exposure lag times, the adequacy of seasonal adjustments, the presence of strong autocorrelations, and the lack of a smaller observation time unit of outcomes (i.e. daily data). These concerns may be attributable to features specific to infectious diseases, such as transmission among individuals and complicated causal mechanisms. The consequence of not taking adequate measures to address these issues is distortion of the appropriate risk quantifications of exposures factors. Future studies should pay careful attention to details and examine alternative models or methods that improve studies using time series regression analysis for environmental determinants of infectious diseases.

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)

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.

Which dimensions of disability does the HIV Disability Questionnaire (HDQ) measure? A factor analysis.

PubMed

O'Brien, Kelly K; Bayoumi, Ahmed M; Stratford, Paul; Solomon, Patricia

2015-01-01

To assess the dimensions of disability measured by the HIV Disability Questionnaire (HDQ), a newly developed 72-item self-administered questionnaire that describes the presence, severity and episodic nature of disability experienced by people living with HIV. We recruited adults living with HIV from hospital clinics, AIDS service organizations and a specialty hospital and administered the HDQ followed by a demographic questionnaire. We conducted an exploratory factor analysis using disability severity scores to determine the domains of disability in the HDQ. We used the following steps: (a) ensured correlations between items were >0.30 and <0.80; (b) conducted a principal components analysis to extract factors; (c) used the Scree Test and eigenvalue threshold >1.5 to determine the number of factors to retain; and d) used oblique rotation to simplify the factor loading matrix. We assigned items to factors based on factor loadings of >0.30. Of the 361 participants, 80% were men and 77% reported living with at least two concurrent health conditions in addition to HIV. The exploratory factor analysis suggested retaining six factors. Items related to symptoms and impairments loaded on three factors (physical [20 items], cognitive [3 items], and mental and emotional health [11 items]) and items related to worrying about the future, daily activities, and personal relationships loaded on three additional factors (uncertainty [14 items], difficulties with day-to-day activities [9 items], social inclusion [12 items]). The HDQ has six domains: physical symptoms and impairments; cognitive symptoms and impairments; mental and emotional health symptoms and impairments; uncertainty; difficulties with day-to-day activities and challenges to social inclusion. These domains establish the scoring structure for the dimensions of disability measured by the HDQ. Implications for Rehabilitation As individuals live longer and age with HIV, they may be living with the health

Marital status is an independent prognostic factor for tracheal cancer patients: an analysis of the SEER database.

PubMed

Li, Mu; Dai, Chen-Yang; Wang, Yu-Ning; Chen, Tao; Wang, Long; Yang, Ping; Xie, Dong; Mao, Rui; Chen, Chang

2016-11-22

Although marital status is an independent prognostic factor in many cancers, its prognostic impact on tracheal cancer has not yet been determined. The goal of this study was to examine the relationship between marital status and survival in patients with tracheal cancer. Compared with unmarried patients (42.67%), married patients (57.33%) had better 5-year OS (25.64% vs. 35.89%, p = 0.009) and 5-year TCSS (44.58% vs. 58.75%, p = 0.004). Results of multivariate analysis indicated that marital status is an independent prognostic factor, with married patients showing better OS (hazard ratio [HR] = 0.78, 95% confidence interval [CI] 0.64-0.95, p = 0.015) and TCSS (HR = 0.70, 95% CI 0.54-0.91, p = 0.008). In addition, subgroup analysis suggested that marital status plays a more important role in the TCSS of patients with non-low-grade malignant tumors (HR = 0.71, 95% CI 0.53-0.93, p = 0.015). We extracted 600 cases from the Surveillance, Epidemiology, and End Results (SEER) database. Variables were compared by Pearson chi-squared test, t-test, log-rank test, and multivariate Cox regression analysis. Overall survival (OS) and tracheal cancer-specific survival (TCSS) were compared between subgroups with different pathologic features and tumor stages. Marital status is an independent prognostic factor for survival in patients with tracheal cancer. For that reason, additional social support may be needed for unmarried patients, especially those with non-low-grade malignant tumors.

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…

Analysis of variability in additive manufactured open cell porous structures.

PubMed

Evans, Sam; Jones, Eric; Fox, Pete; Sutcliffe, Chris

2017-06-01

In this article, a novel method of analysing build consistency of additively manufactured open cell porous structures is presented. Conventionally, methods such as micro computed tomography or scanning electron microscopy imaging have been applied to the measurement of geometric properties of porous material; however, high costs and low speeds make them unsuitable for analysing high volumes of components. Recent advances in the image-based analysis of open cell structures have opened up the possibility of qualifying variation in manufacturing of porous material. Here, a photogrammetric method of measurement, employing image analysis to extract values for geometric properties, is used to investigate the variation between identically designed porous samples measuring changes in material thickness and pore size, both intra- and inter-build. Following the measurement of 125 samples, intra-build material thickness showed variation of ±12%, and pore size ±4% of the mean measured values across five builds. Inter-build material thickness and pore size showed mean ranges higher than those of intra-build, ±16% and ±6% of the mean material thickness and pore size, respectively. Acquired measurements created baseline variation values and demonstrated techniques suitable for tracking build deviation and inspecting additively manufactured porous structures to indicate unwanted process fluctuations.

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)

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.

Using Multilevel Factor Analysis with Clustered Data: Investigating the Factor Structure of the Positive Values Scale

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.

2016-01-01

Advances in multilevel modeling techniques now make it possible to investigate the psychometric properties of instruments using clustered data. Factor models that overlook the clustering effect can lead to underestimated standard errors, incorrect parameter estimates, and model fit indices. In addition, factor structures may differ depending on…

25 CFR 39.1101 - Addition of pre-kindergarten as a weight factor to the Indian School Equalization Formula in...

Code of Federal Regulations, 2011 CFR

2011-04-01

... 25 Indians 1 2011-04-01 2011-04-01 false Addition of pre-kindergarten as a weight factor to the Indian School Equalization Formula in fiscal year 1982. 39.1101 Section 39.1101 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR EDUCATION THE INDIAN SCHOOL EQUALIZATION PROGRAM Pre-kindergarten Programs § 39.1101 Addition of...

25 CFR 39.1101 - Addition of pre-kindergarten as a weight factor to the Indian School Equalization Formula in...

Code of Federal Regulations, 2014 CFR

2014-04-01

... 25 Indians 1 2014-04-01 2014-04-01 false Addition of pre-kindergarten as a weight factor to the Indian School Equalization Formula in fiscal year 1982. 39.1101 Section 39.1101 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR EDUCATION THE INDIAN SCHOOL EQUALIZATION PROGRAM Pre-kindergarten Programs § 39.1101 Addition of...

25 CFR 39.1101 - Addition of pre-kindergarten as a weight factor to the Indian School Equalization Formula in...

Code of Federal Regulations, 2013 CFR

2013-04-01

... 25 Indians 1 2013-04-01 2013-04-01 false Addition of pre-kindergarten as a weight factor to the Indian School Equalization Formula in fiscal year 1982. 39.1101 Section 39.1101 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR EDUCATION THE INDIAN SCHOOL EQUALIZATION PROGRAM Pre-kindergarten Programs § 39.1101 Addition of...

25 CFR 39.1101 - Addition of pre-kindergarten as a weight factor to the Indian School Equalization Formula in...

Code of Federal Regulations, 2010 CFR

2010-04-01

... 25 Indians 1 2010-04-01 2010-04-01 false Addition of pre-kindergarten as a weight factor to the Indian School Equalization Formula in fiscal year 1982. 39.1101 Section 39.1101 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR EDUCATION THE INDIAN SCHOOL EQUALIZATION PROGRAM Pre-kindergarten Programs § 39.1101 Addition of...

25 CFR 39.1101 - Addition of pre-kindergarten as a weight factor to the Indian School Equalization Formula in...

Code of Federal Regulations, 2012 CFR

2012-04-01

... 25 Indians 1 2012-04-01 2011-04-01 true Addition of pre-kindergarten as a weight factor to the Indian School Equalization Formula in fiscal year 1982. 39.1101 Section 39.1101 Indians BUREAU OF INDIAN AFFAIRS, DEPARTMENT OF THE INTERIOR EDUCATION THE INDIAN SCHOOL EQUALIZATION PROGRAM Pre-kindergarten Programs § 39.1101 Addition of...

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…

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…

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

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)

Analysis of significant factors for dengue fever incidence prediction.

PubMed

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

2016-04-16

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

Confirmatory Factor Analysis and Test-Retest Reliability of the Alcohol and Drug Confrontation Scale (ADCS)

PubMed Central

Polcin, Douglas L.; Galloway, Gantt P.; Bond, Jason; Korcha, Rachael; Greenfield, Thomas K.

2008-01-01

The addiction field lacks an accepted definition and reliable measure of confrontation. The Alcohol and Drug Confrontation Scale (ADCS) defines confrontation as warnings about the potential consequences of substance use. To assess psychometric properties, 323 individual entering recovery houses in U.S. urban and suburban areas were interviewed between 2003 and 2005 (20% women, 68% white). Analyses included test-retest reliability, confirmatory factor analysis, and measures of internal consistency. Findings support the ADCS as a reliable way of assessing two factors: Internal Support and External intensity. Confrontation was experienced as supportive, accurate and helpful. Additional studies should assess confrontation in different contexts. PMID:20686635

A Systematic Review of Methodology: Time Series Regression Analysis for Environmental Factors and Infectious Diseases

PubMed Central

Imai, Chisato; Hashizume, Masahiro

2015-01-01

Background: Time series analysis is suitable for investigations of relatively direct and short-term effects of exposures on outcomes. In environmental epidemiology studies, this method has been one of the standard approaches to assess impacts of environmental factors on acute non-infectious diseases (e.g. cardiovascular deaths), with conventionally generalized linear or additive models (GLM and GAM). However, the same analysis practices are often observed with infectious diseases despite of the substantial differences from non-infectious diseases that may result in analytical challenges. Methods: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, systematic review was conducted to elucidate important issues in assessing the associations between environmental factors and infectious diseases using time series analysis with GLM and GAM. Published studies on the associations between weather factors and malaria, cholera, dengue, and influenza were targeted. Findings: Our review raised issues regarding the estimation of susceptible population and exposure lag times, the adequacy of seasonal adjustments, the presence of strong autocorrelations, and the lack of a smaller observation time unit of outcomes (i.e. daily data). These concerns may be attributable to features specific to infectious diseases, such as transmission among individuals and complicated causal mechanisms. Conclusion: The consequence of not taking adequate measures to address these issues is distortion of the appropriate risk quantifications of exposures factors. Future studies should pay careful attention to details and examine alternative models or methods that improve studies using time series regression analysis for environmental determinants of infectious diseases. PMID:25859149

Comprehensive analysis of TCP transcription factors and their expression during cotton (Gossypium arboreum) fiber early development

PubMed Central

Ma, Jun; Liu, Fang; Wang, Qinglian; Wang, Kunbo; Jones, Don C.; Zhang, Baohong

2016-01-01

TCP proteins are plant-specific transcription factors implicated to perform a variety of physiological functions during plant growth and development. In the current study, we performed for the first time the comprehensive analysis of TCP gene family in a diploid cotton species, Gossypium arboreum, including phylogenetic analysis, chromosome location, gene duplication status, gene structure and conserved motif analysis, as well as expression profiles in fiber at different developmental stages. Our results showed that G. arboreum contains 36 TCP genes, distributing across all of the thirteen chromosomes. GaTCPs within the same subclade of the phylogenetic tree shared similar exon/intron organization and motif composition. In addition, both segmental duplication and whole-genome duplication contributed significantly to the expansion of GaTCPs. Many these TCP transcription factor genes are specifically expressed in cotton fiber during different developmental stages, including cotton fiber initiation and early development. This suggests that TCP genes may play important roles in cotton fiber development. PMID:26857372

Comprehensive analysis of TCP transcription factors and their expression during cotton (Gossypium arboreum) fiber early development.

PubMed

Ma, Jun; Liu, Fang; Wang, Qinglian; Wang, Kunbo; Jones, Don C; Zhang, Baohong

2016-02-09

TCP proteins are plant-specific transcription factors implicated to perform a variety of physiological functions during plant growth and development. In the current study, we performed for the first time the comprehensive analysis of TCP gene family in a diploid cotton species, Gossypium arboreum, including phylogenetic analysis, chromosome location, gene duplication status, gene structure and conserved motif analysis, as well as expression profiles in fiber at different developmental stages. Our results showed that G. arboreum contains 36 TCP genes, distributing across all of the thirteen chromosomes. GaTCPs within the same subclade of the phylogenetic tree shared similar exon/intron organization and motif composition. In addition, both segmental duplication and whole-genome duplication contributed significantly to the expansion of GaTCPs. Many these TCP transcription factor genes are specifically expressed in cotton fiber during different developmental stages, including cotton fiber initiation and early development. This suggests that TCP genes may play important roles in cotton fiber development.

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.

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.

Independent and additive interaction between polymorphisms of tumor necrosis factor α-308 and lymphotoxin α+252 on risk of hepatocellular carcinoma related to hepatitis B.

PubMed

Tsai, Jung-Fa; Chen, Shinn-Chern; Lin, Zu-Yau; Dai, Chia-Yen; Huang, Jee-Fu; Yu, Min-Lung; Chuang, Wan-Long

2017-09-01

This case-control study was aimed to assess the effect of genetic variants of tumor necrosis factor (TNF) α-308 and lymphotoxin (LT) α+252 on development of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). Their gene-gene interaction was also investigated. We enrolled 200 pairs of age- and sex-matched patients with cirrhotic HBV-HCC and unrelated patients with HBV-cirrhosis alone. Polymorphisms of TNFα-308 and LTα+252 were genotyped. Synergy index was used to calculate interaction between the variant genotypes. The results indicated that the frequency distribution of the variant genotypes (TNFα-308 G/A and LTα+252 G/G) in patients with HCC were significantly higher than those in patients with cirrhosis alone. Multivariate analysis indicated that TNFα-308 G/A (odds ratio [OR], 2.34) and LTα+252 G/G (OR, 2.04) were independent risk factors for HCC. By the clinical characteristics of study population, multivariate analysis demonstrated that independent factors associated with harboring the variant genotypes included cirrhosis with Child-Pugh C (OR = 6.47 in cases and OR = 11.56 in controls) and thrombocytopenia (OR = 8.86 in cases and OR = 7.74 in controls). Calculation of synergy index (SI) indicated that there are additive interaction between TNFα-308 G/A and LTα+252 G/G on risk of HCC (SI = 1.29). There are independent and additive interactions between TNFα-308 G/A and LTα+252 G/G on risk for HBV-HCC. They correlated with advanced hepatic fibrosis and severe liver damage, which might contribute to a higher risk for HCC. Copyright © 2017 Kaohsiung Medical University. Published by Elsevier Taiwan. All rights reserved.

Factor Analysis of Persistent Post-Concussive Symptoms within a Military Sample with Blast Exposure

PubMed Central

Franke, L.M.; Czarnota, J.N.; Ketchum, J.M.; Walker, W.C.

2014-01-01

Objective To determine the factor structure of persistent post-concussive syndrome (PPCS) symptoms in a blast-exposed military sample and validate factors against objective and symptom measures. Setting Veterans Affairs medical center and military bases. Participants One hundred eighty-one service members and veterans with at least one significant exposure to blast during deployment within the two years prior to study enrollment. Design Confirmatory and exploratory factor analysis of the Rivermead Post-concussion Questionnaire (RPQ). Main Measures RPQ, PTSD Symptom Checklist-Civilian, Center for Epidemiologic Studies Depression inventory, Sensory Organization Test, Paced Auditory Serial Addition Test, California Verbal Learning Test, Delis-Kaplan Executive Function System subtests. Results The three-factor structure of PPCS was not confirmed. A four-factor structure was extracted, and factors were interpreted as reflecting emotional, cognitive, visual, and vestibular functions. All factors were associated with scores on psychological symptom inventories; visual and vestibular factors were also associated with balance performance. There was no significant association between the cognitive factor and neuropsychological performance, nor between a history of mTBI and factor scores. Conclusion Persistent post-concussive symptoms observed months after blast exposure seem to be related to four distinct forms of distress, but not to mTBI per se, with vestibular and visual factors possibly related to injury of sensory organs by blast. PMID:24695267

Patients retrieving additional information via the Internet: a trend analysis in a Swedish population, 2000-05.

PubMed

Rahmqvist, Mikael; Bara, Ana-Claudia

2007-01-01

To examine the trends over five years for patients' seeking online additional health information about their disease/health problem to what the doctor has been giving, and investigate any differences in information-seeking behaviour according to age, gender, self-perceived health status, living area, and type of medical encounter. Data from three independent surveys conducted in 2000, 2002, and 2005 of a population with a recent experience of outpatient care[n]typesetter: please remove blue shading here and elsewhere[/n], including 24,800 respondents aged between 20 and 95, were analysed in a trend analysis and a logistic regression regarding background factors that may influence the seeking behaviour. During the study period, there was a significant increase in Internet use in most age groups. The total use among men 20-95 years old increased from 7% in 2000 to 18% in 2005 and from 9% to 25% for women respectively. The predictors for using the Internet as a source of information were: age, gender, self-perceived health status, living area, and the type of medical encounter (first or repeated). In 2005, women aged 20-49 used the Internet as a source to a significantly greater extent than men, even when all background factors were controlled for (OR 1.46 and CI 1.21-1.77). Swedish patients, especially the young and middle-aged, are to a substantial degree using the Internet to gather additional information on their disease. The benefits of this increase include more informed patients; however, there are inherent quality issues that require strategies for ensuring public access to high-quality health information online.

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

Factors Associated with Fatal Occupational Accidents among Mexican Workers: A National Analysis

PubMed Central

Gonzalez-Delgado, Mery; Gómez-Dantés, Héctor; Fernández-Niño, Julián Alfredo; Robles, Eduardo; Borja, Víctor H.; Aguilar, Miriam

2015-01-01

Objective To identify the factors associated with fatal occupational injuries in Mexico in 2012 among workers affiliated with the Mexican Social Security Institute. Methods Analysis of secondary data using information from the National Occupational Risk Information System, with the consequence of the occupational injury (fatal versus non-fatal) as the response variable. The analysis included 406,222 non-fatal and 1,140 fatal injuries from 2012. The factors associated with the lethality of the injury were identified using a logistic regression model with the Firth approach. Results Being male (OR=5.86; CI95%: 4.22-8.14), age (OR=1.04; CI95%: 1.03-1.06), employed in the position for 1 to 10 years (versus less than 1 year) (OR=1.37; CI95%: 1.15-1.63), working as a facilities or machine operator or assembler (OR: 3.28; CI95%: 2.12- 5.07) and being a worker without qualifications (OR=1.96; CI95%: 1.18-3.24) (versus an office worker) were associated with fatality in the event of an injury. Additionally, companies classified as maximum risk (OR=1.90; CI 95%: 1.38-2.62), workplace conditions (OR=7.15; CI95%: 3.63-14.10) and factors related to the work environment (OR=9.18; CI95%:4.36-19.33) were identified as risk factors for fatality in the event of an occupational injury. Conclusions Fatality in the event of an occupational injury is associated with factors related to sociodemographics (age, sex and occupation), the work environment and workplace conditions. Worker protection policies should be created for groups with a higher risk of fatal occupational injuries in Mexico. PMID:25790063

Molecular Phylogenetic and Expression Analysis of the Complete WRKY Transcription Factor Family in Maize

PubMed Central

Wei, Kai-Fa; Chen, Juan; Chen, Yan-Feng; Wu, Ling-Juan; Xie, Dao-Xin

2012-01-01

The WRKY transcription factors function in plant growth and development, and response to the biotic and abiotic stresses. Although many studies have focused on the functional identification of the WRKY transcription factors, much less is known about molecular phylogenetic and global expression analysis of the complete WRKY family in maize. In this study, we identified 136 WRKY proteins coded by 119 genes in the B73 inbred line from the complete genome and named them in an orderly manner. Then, a comprehensive phylogenetic analysis of five species was performed to explore the origin and evolutionary patterns of these WRKY genes, and the result showed that gene duplication is the major driving force for the origin of new groups and subgroups and functional divergence during evolution. Chromosomal location analysis of maize WRKY genes indicated that 20 gene clusters are distributed unevenly in the genome. Microarray-based expression analysis has revealed that 131 WRKY transcripts encoded by 116 genes may participate in the regulation of maize growth and development. Among them, 102 transcripts are stably expressed with a coefficient of variation (CV) value of <15%. The remaining 29 transcripts produced by 25 WRKY genes with the CV value of >15% are further analysed to discover new organ- or tissue-specific genes. In addition, microarray analyses of transcriptional responses to drought stress and fungal infection showed that maize WRKY proteins are involved in stress responses. All these results contribute to a deep probing into the roles of WRKY transcription factors in maize growth and development and stress tolerance. PMID:22279089

Molecular phylogenetic and expression analysis of the complete WRKY transcription factor family in maize.

PubMed

Wei, Kai-Fa; Chen, Juan; Chen, Yan-Feng; Wu, Ling-Juan; Xie, Dao-Xin

2012-04-01

The WRKY transcription factors function in plant growth and development, and response to the biotic and abiotic stresses. Although many studies have focused on the functional identification of the WRKY transcription factors, much less is known about molecular phylogenetic and global expression analysis of the complete WRKY family in maize. In this study, we identified 136 WRKY proteins coded by 119 genes in the B73 inbred line from the complete genome and named them in an orderly manner. Then, a comprehensive phylogenetic analysis of five species was performed to explore the origin and evolutionary patterns of these WRKY genes, and the result showed that gene duplication is the major driving force for the origin of new groups and subgroups and functional divergence during evolution. Chromosomal location analysis of maize WRKY genes indicated that 20 gene clusters are distributed unevenly in the genome. Microarray-based expression analysis has revealed that 131 WRKY transcripts encoded by 116 genes may participate in the regulation of maize growth and development. Among them, 102 transcripts are stably expressed with a coefficient of variation (CV) value of <15%. The remaining 29 transcripts produced by 25 WRKY genes with the CV value of >15% are further analysed to discover new organ- or tissue-specific genes. In addition, microarray analyses of transcriptional responses to drought stress and fungal infection showed that maize WRKY proteins are involved in stress responses. All these results contribute to a deep probing into the roles of WRKY transcription factors in maize growth and development and stress tolerance.

A systematic review of the relationship factor between women and health professionals within the multivariant analysis of maternal satisfaction.

PubMed

Macpherson, Ignacio; Roqué-Sánchez, María V; Legget Bn, Finola O; Fuertes, Ferran; Segarra, Ignacio

2016-10-01

personalised support provided to women by health professionals is one of the prime factors attaining women's satisfaction during pregnancy and childbirth. However the multifactorial nature of 'satisfaction' makes difficult to assess it. Statistical multivariate analysis may be an effective technique to obtain in depth quantitative evidence of the importance of this factor and its interaction with the other factors involved. This technique allows us to estimate the importance of overall satisfaction in its context and suggest actions for healthcare services. systematic review of studies that quantitatively measure the personal relationship between women and healthcare professionals (gynecologists, obstetricians, nurse, midwifes, etc.) regarding maternity care satisfaction. The literature search focused on studies carried out between 1970 and 2014 that used multivariate analyses and included the woman-caregiver relationship as a factor of their analysis. twenty-four studies which applied various multivariate analysis tools to different periods of maternity care (antenatal, perinatal, post partum) were selected. The studies included discrete scale scores and questionnaires from women with low-risk pregnancies. The "personal relationship" factor appeared under various names: care received, personalised treatment, professional support, amongst others. The most common multivariate techniques used to assess the percentage of variance explained and the odds ratio of each factor were principal component analysis and logistic regression. the data, variables and factor analysis suggest that continuous, personalised care provided by the usual midwife and delivered within a family or a specialised setting, generates the highest level of satisfaction. In addition, these factors foster the woman's psychological and physiological recovery, often surpassing clinical action (e.g. medicalization and hospital organization) and/or physiological determinants (e.g. pain, pathologies, etc

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.

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)

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

PubMed

Nie, Sasa; Feng, Zhe; Tang, Li; Wang, Xiaolong; He, Yani; Fang, Jingai; Li, Suhua; Yang, Yibin; Mao, Huijuan; Jiao, Jundong; Liu, Wenhu; Cao, Ning; Wang, Wenge; Sun, Jifeng; Shao, Fengmin; Li, Wenge; He, Qiang; Jiang, Hongli; Lin, Hongli; Fu, Ping; Zhang, Xinzhou; Liu, Yinghong; Wu, Yonggui; Xi, ChunSheng; Liang, Meng; Qu, Zhijie; Zhu, Jun; Wu, Guangli; Zheng, Yali; Na, Yu; Li, Ying; Li, Wei; Cai, Guangyan; Chen, Xiangmei

2017-01-01

Risk factor studies for acute kidney injury (AKI) in China are lacking, especially those regarding non-traditional risk factors, such as laboratory indicators. All adult patients admitted to 38 tertiary and 22 secondary hospitals in China in any one month between July and December 2014 were surveyed. AKI patients were screened according to the Kidney Disease: Improving Global Outcomes' definition of AKI. Logistic regression was used to analyze the risk factors for AKI, and Cox regression was used to analyze the risk of in-hospital mortality for AKI patients; additionally, a propensity score analysis was used to reconfirm the risk factors among laboratory indicators for mortality. The morbidity of AKI was 0.97%. Independent risk factors for AKI were advancing age, male gender, hypertension, and chronic kidney disease. All-cause mortality was 16.5%. The predictors of mortality in AKI patients were advancing age, tumor, higher uric acid level and increases in Acute Physiologic Assessment and Chronic Health Evaluation II and Sequential Organ Failure Assessment scores. The hazard ratio (HR) for mortality with uric acid levels > 9.1 mg/dl compared with ≤ 5.2 mg/dl was 1.78 (95% CI: 1.23 to 2.58) for the AKI patients as a group, and was 1.73 (95% CI: 1.24 to 2.42) for a propensity score-matched set. In addition to traditional risk factors, uric acid level is an independent predictor of all-cause mortality after AKI. © 2017 The Author(s). Published by S. Karger AG, Basel.

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.

Predictive Factor Analysis of Response-Adapted Radiation Therapy for Chemotherapy-Sensitive Pediatric Hodgkin Lymphoma: Analysis of the Children's Oncology Group AHOD 0031 Trial

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

Charpentier, Anne-Marie; Friedman, Debra L.; Wolden, Suzanne

Purpose: To evaluate whether clinical risk factors could further distinguish children with intermediate-risk Hodgkin lymphoma (HL) with rapid early and complete anatomic response (RER/CR) who benefit significantly from involved-field RT (IFRT) from those who do not, and thereby aid refinement of treatment selection. Methods and Materials: Children with intermediate-risk HL treated on the Children's Oncology Group AHOD 0031 trial who achieved RER/CR with 4 cycles of chemotherapy, and who were randomized to 21-Gy IFRT or no additional therapy (n=716) were the subject of this study. Recursive partitioning analysis was used to identify factors associated with clinically and statistically significant improvement inmore » event-free survival (EFS) after randomization to IFRT. Bootstrap sampling was used to evaluate the robustness of the findings. Result: Although most RER/CR patients did not benefit significantly from IFRT, those with a combination of anemia and bulky limited-stage disease (n=190) had significantly better 4-year EFS with the addition of IFRT (89.3% vs 77.9% without IFRT; P=.019); this benefit was consistently reproduced in bootstrap analyses and after adjusting for other prognostic factors. Conclusion: Although most patients achieving RER/CR had favorable outcomes with 4 cycles of chemotherapy alone, those children with initial bulky stage I/II disease and anemia had significantly better EFS with the addition of IFRT as part of combined-modality therapy. Further work evaluating the interaction of clinical and biologic factors and imaging response is needed to further optimize and refine treatment selection.« less

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…

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

On an Additive Semigraphoid Model for Statistical Networks With Application to Pathway Analysis.

PubMed

Li, Bing; Chun, Hyonho; Zhao, Hongyu

2014-09-01

We introduce a nonparametric method for estimating non-gaussian graphical models based on a new statistical relation called additive conditional independence, which is a three-way relation among random vectors that resembles the logical structure of conditional independence. Additive conditional independence allows us to use one-dimensional kernel regardless of the dimension of the graph, which not only avoids the curse of dimensionality but also simplifies computation. It also gives rise to a parallel structure to the gaussian graphical model that replaces the precision matrix by an additive precision operator. The estimators derived from additive conditional independence cover the recently introduced nonparanormal graphical model as a special case, but outperform it when the gaussian copula assumption is violated. We compare the new method with existing ones by simulations and in genetic pathway analysis.

A Risk Analysis Methodology to Address Human and Organizational Factors in Offshore Drilling Safety: With an Emphasis on Negative Pressure Test

NASA Astrophysics Data System (ADS)

Tabibzadeh, Maryam

According to the final Presidential National Commission report on the BP Deepwater Horizon (DWH) blowout, there is need to "integrate more sophisticated risk assessment and risk management practices" in the oil industry. Reviewing the literature of the offshore drilling industry indicates that most of the developed risk analysis methodologies do not fully and more importantly, systematically address the contribution of Human and Organizational Factors (HOFs) in accident causation. This is while results of a comprehensive study, from 1988 to 2005, of more than 600 well-documented major failures in offshore structures show that approximately 80% of those failures were due to HOFs. In addition, lack of safety culture, as an issue related to HOFs, have been identified as a common contributing cause of many accidents in this industry. This dissertation introduces an integrated risk analysis methodology to systematically assess the critical role of human and organizational factors in offshore drilling safety. The proposed methodology in this research focuses on a specific procedure called Negative Pressure Test (NPT), as the primary method to ascertain well integrity during offshore drilling, and analyzes the contributing causes of misinterpreting such a critical test. In addition, the case study of the BP Deepwater Horizon accident and their conducted NPT is discussed. The risk analysis methodology in this dissertation consists of three different approaches and their integration constitutes the big picture of my whole methodology. The first approach is the comparative analysis of a "standard" NPT, which is proposed by the author, with the test conducted by the DWH crew. This analysis contributes to identifying the involved discrepancies between the two test procedures. The second approach is a conceptual risk assessment framework to analyze the causal factors of the identified mismatches in the previous step, as the main contributors of negative pressure test

Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

PubMed

Stankov, L

1979-07-01

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

A simulations approach for meta-analysis of genetic association studies based on additive genetic model.

PubMed

John, Majnu; Lencz, Todd; Malhotra, Anil K; Correll, Christoph U; Zhang, Jian-Ping

2018-06-01

Meta-analysis of genetic association studies is being increasingly used to assess phenotypic differences between genotype groups. When the underlying genetic model is assumed to be dominant or recessive, assessing the phenotype differences based on summary statistics, reported for individual studies in a meta-analysis, is a valid strategy. However, when the genetic model is additive, a similar strategy based on summary statistics will lead to biased results. This fact about the additive model is one of the things that we establish in this paper, using simulations. The main goal of this paper is to present an alternate strategy for the additive model based on simulating data for the individual studies. We show that the alternate strategy is far superior to the strategy based on summary statistics.

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.

Mars-GRAM 2010: Additions and Resulting Improvements

NASA Technical Reports Server (NTRS)

Justh, Hilary L.; Burns, K. Lee

2013-01-01

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission applications. Mars-GRAM has been utilized during previous aerobraking operations in the atmosphere of Mars. Mars-GRAM has also been used in the prediction and validation of Mars Pathfinder hypersonic aerodynamics, the aerothermodynamic and entry dynamics studies for Mars Polar Lander, the landing site selection process for the Mars Science Laboratory (MSL), the Mars Aerocapture System Study (MASS) as well as the Aerocapture Technology Assessment Group (TAG). Most recently, Mars-GRAM 2010 was used to develop the onboard atmospheric density estimator that is part of the Autonomous Aerobraking Development Plan. The most recent release of Mars-GRAM 2010 contains several changes including an update to Fortran 90/95 and the addition of adjustment factors. Following the completion of a comparison analysis between Mars-GRAM, Thermal Emission Spectrometer (TES), as well as Mars Global Surveyor (MGS), Mars Odyssey (ODY), and Mars Reconnaissance Orbiter (MRO) aerobraking density data, adjustment factors were added to Mars-GRAM 2010 that alter the input data from National Aeronautics and Space Administration (NASA) Ames Mars General Circulation Model (MGCM) and the University of Michigan Mars Thermospheric General Circulation Model (MTGCM) for the mapping year 0 user-controlled dust case. The addition of adjustment factors resolved the issue of previous versions of Mars-GRAM being less than realistic when used for sensitivity studies for mapping year 0 and large optical depth values, such as tau equal to 3. Mars-GRAM was evaluated at locations and times of TES limb observations and adjustment factors were determined. For altitudes above 80 km and below 135 km, Mars-GRAM (MTGCM) densities were compared to aerobraking densities measured by Mars Global Surveyor (MGS), Mars Odyssey (ODY), and Mars Reconnaissance Orbiter (MRO) to determine the adjustment

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.

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…

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

PubMed

Romaniuk, Madeline; Khawaja, Nigar G

2013-09-25

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

Non-valvular atrial fibrillation patients with none or one additional risk factor of the CHA2DS2-VASc score. A comprehensive net clinical benefit analysis for warfarin, aspirin, or no therapy.

PubMed

Lip, Gregory Y H; Skjøth, Flemming; Nielsen, Peter B; Larsen, Torben Bjerregaard

2015-10-01

Oral anticoagulation (OAC) to prevent stroke has to be balanced against the potential harm of serious bleeding, especially intracranial haemorrhage (ICH). We determined the net clinical benefit (NCB) balancing effectiveness and safety of no antithrombotic therapy, aspirin and warfarin in AF patients with none or one stroke risk factor. Using Danish registries, we determined NCB using various definitions intrinsic to our cohort (Danish weights at 1 and 5 year follow-up), with risk weights which were derived from the hazard ratio (HR) of death following an event, relative to HR of death after ischaemic stroke. When aspirin was compared to no treatment, NCB was neutral or negative for both risk strata. For warfarin vs no treatment, NCB using Danish weights was neutral where no risk factors were present and using five years follow-up. For one stroke risk factor, NCB was positive for warfarin vs no treatment, for one year and five year follow-up. For warfarin vs aspirin use in patients with no risk factors, NCB was positive with one year follow-up, but neutral with five year follow-up. With one risk factor, NCB was generally positive for warfarin vs aspirin. In conclusion, we show a positive overall advantage (i.e. positive NCB) of effective stroke prevention with OAC, compared to no therapy or aspirin with one additional stroke risk factor, using Danish weights. 'Low risk' AF patients with no additional stroke risk factors (i.e.CHA2DS2-VASc 0 in males, 1 in females) do not derive any advantage (neutral or negative NCB) with aspirin, nor with warfarin therapy in the long run.

Detecting and correcting the bias of unmeasured factors using perturbation analysis: a data-mining approach.

PubMed

Lee, Wen-Chung

2014-02-05

The randomized controlled study is the gold-standard research method in biomedicine. In contrast, the validity of a (nonrandomized) observational study is often questioned because of unknown/unmeasured factors, which may have confounding and/or effect-modifying potential. In this paper, the author proposes a perturbation test to detect the bias of unmeasured factors and a perturbation adjustment to correct for such bias. The proposed method circumvents the problem of measuring unknowns by collecting the perturbations of unmeasured factors instead. Specifically, a perturbation is a variable that is readily available (or can be measured easily) and is potentially associated, though perhaps only very weakly, with unmeasured factors. The author conducted extensive computer simulations to provide a proof of concept. Computer simulations show that, as the number of perturbation variables increases from data mining, the power of the perturbation test increased progressively, up to nearly 100%. In addition, after the perturbation adjustment, the bias decreased progressively, down to nearly 0%. The data-mining perturbation analysis described here is recommended for use in detecting and correcting the bias of unmeasured factors in observational studies.

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.

20 CFR 670.410 - Are there additional factors which are considered in selecting an eligible applicant for enrollment?

Code of Federal Regulations, 2010 CFR

2010-04-01

... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Are there additional factors which are considered in selecting an eligible applicant for enrollment? 670.410 Section 670.410 Employees' Benefits... INVESTMENT ACT Recruitment, Eligibility, Screening, Selection and Assignment, and Enrollment § 670.410 Are...

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

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…

A confirmatory factor analysis of the Beck Depression Inventory-II in end-stage renal disease patients.

PubMed

Chilcot, Joseph; Norton, Sam; Wellsted, David; Almond, Mike; Davenport, Andrew; Farrington, Ken

2011-09-01

We sought to examine several competing factor structures of the Beck Depression Inventory-II (BDI) in a sample of patients with End-Stage Renal Disease (ESRD), in which setting the factor structure is poorly defined, though depression symptoms are common. In addition, demographic and clinical correlates of the identified factors were examined. The BDI was administered to clinical sample of 460 ESRD patients attending 4 UK renal centres. Competing models of the factor structure of the BDI were evaluated using confirmatory factor analysis. The best fitting model consisted of general depression factor that accounted for 81% of the common variance between all items along with orthogonal cognitive and somatic factors (G-S-C model, CFI=.983, TLI=.979, RMSEA=.037), which explained 8% and 9% of the common variance, respectively. Age, diabetes, and ethnicity were significantly related to the cognitive factor, whereas albumin, dialysis adequacy, and ethnicity were related to the somatic factor. No demographic or clinical variable was associated with the general factor. The general-factor model provides the best fitting and conceptually most acceptable interpretation of the BDI. Furthermore, the cognitive and somatic factors appear to be related to specific demographic and clinical factors. Copyright © 2011 Elsevier Inc. All rights reserved.

ROBNCA: robust network component analysis for recovering transcription factor activities.

PubMed

Noor, Amina; Ahmad, Aitzaz; Serpedin, Erchin; Nounou, Mohamed; Nounou, Hazem

2013-10-01

Network component analysis (NCA) is an efficient method of reconstructing the transcription factor activity (TFA), which makes use of the gene expression data and prior information available about transcription factor (TF)-gene regulations. Most of the contemporary algorithms either exhibit the drawback of inconsistency and poor reliability, or suffer from prohibitive computational complexity. In addition, the existing algorithms do not possess the ability to counteract the presence of outliers in the microarray data. Hence, robust and computationally efficient algorithms are needed to enable practical applications. We propose ROBust Network Component Analysis (ROBNCA), a novel iterative algorithm that explicitly models the possible outliers in the microarray data. An attractive feature of the ROBNCA algorithm is the derivation of a closed form solution for estimating the connectivity matrix, which was not available in prior contributions. The ROBNCA algorithm is compared with FastNCA and the non-iterative NCA (NI-NCA). ROBNCA estimates the TF activity profiles as well as the TF-gene control strength matrix with a much higher degree of accuracy than FastNCA and NI-NCA, irrespective of varying noise, correlation and/or amount of outliers in case of synthetic data. The ROBNCA algorithm is also tested on Saccharomyces cerevisiae data and Escherichia coli data, and it is observed to outperform the existing algorithms. The run time of the ROBNCA algorithm is comparable with that of FastNCA, and is hundreds of times faster than NI-NCA. The ROBNCA software is available at http://people.tamu.edu/∼amina/ROBNCA

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…

Confirmatory Factor Analysis of the "World Health Organization Quality of Life Questionnaire--Brief Version" for Individuals with Spinal Cord Injury

ERIC Educational Resources Information Center

Miller, Susan M.; Chan, Fong; Ferrin, James M.; Lin, Chen-Ping; Chan, Jacob Y. C.

2008-01-01

This study examined the factorial structure of the "World Health Organization Quality of Life Questionnaire--Brief Version" in a community sample of Canadians with spinal cord injuries. A confirmatory factor analysis provides evidence that the instrument is a multidimensional measure of quality of life. Additionally, the questionnaire is…

[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…

Analysis of Maternal Risk Factors Associated With Congenital Vertebral Malformations

PubMed Central

Hesemann, Jennifer; Lauer, Emily; Ziska, Stephen; Noonan, Kenneth; Nemeth, Blaise; Scott-Schwoerer, Jessica; McCarty, Catherine; Rasmussen, Kristen; Goldberg, Jacob M.; Sund, Sarah; Eickhoff, Jens; Raggio, Cathleen L.; Giampietro, Philip F.

2014-01-01

Study Design A retrospective chart review of cases with congenital vertebral malformations (CVM) and controls with normal spine morphology. Objective To determine the relative contribution of maternal environmental factors (MEF) during pregnancy including maternal insulin dependent diabetes mellitus, valproic acid, alcohol, smoking, hyperthermia, twin gestation, assisted reproductive technology, in-vitro fertilization and maternal clomiphene usage to CVM development. Summary of Background Data Congenital vertebral malformations (CVM) represent defects in formation and segmentation of somites occurring with an estimated incidence of between 0.13–0.50 per 1000 live births. CVM may be associated with congenital scoliosis, Klippel-Feil syndrome, hemifacial microsomia and VACTERL syndromes, and represent significant morbidity due to pain and cosmetic disfigurement. Methods A multicenter retrospective chart review of 229 cases with CVM and 267 controls with normal spine morphology between the ages of 1–50 years was performed in order to obtain the odds ratio (OR) of MEF related to CVM among cases vs. controls. CVM due to an underlying syndrome associated with a known gene mutation or chromosome etiology were excluded. An imputation based analysis was performed in which subjects with no documentation of MEF history were treated as no maternal exposure.” Univariate and multivariate analysis was conducted to calculate the OR. Results Of the 229 total cases, 104 cases had single or multiple CVM without additional congenital malformations (CM) (Group 1) and 125 cases had single or multiple CVM and additional CM (Group 2). Nineteen percent of total cases had an identified MEF. The OR (95% CI, P-value) for MEF history for Group 1 was 6.0 (2.4–15.1, P<0.001) in the univariate analysis. The OR for MEF history in Group 2 was 9.1 (95%CI, P-value) (3.8–21.6, P<0.001) in the univariate analysis. The results were confirmed in the multivariate analysis, after adjusting for

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. �

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...

Analysis of factors that affect shoulder balance after correction surgery in scoliosis: a global analysis of all the curvature types.

PubMed

Hong, Jae-Young; Suh, Seung-Woo; Modi, Hitesh N; Yang, Jae-Hyuk; Park, Si-Young

2013-06-01

To identify factors that can affect postoperative shoulder balance in AIS. 89 adolescent idiopathic scoliosis patients with six types of curvatures who underwent surgery were included in this study. Whole spine antero-posterior and lateral radiographs were obtained pre- and postoperatively. In radiograms, shape and changes in curvatures were analyzed. In addition, four shoulder parameters and coronal balance were analyzed in an effort to identify factors significantly related to postoperative shoulder balance. In general, all the four shoulder parameters (CHD, CA, CRID, RSH) were slightly increased at final follow up (t test, P < 0.05), although there was a decrease in Lenke type II and IV curvatures. However, pre- and postoperative shoulder parameters were not significantly different between each curvature types (ANOVA, P > 0.05). Moreover, no significant differences of pre- and postoperative shoulder level between different level of proximal fusion groups (ANOVA, P > 0.05) existed. In the analysis of coronal curvature changes, no difference was observed in every individual coronal curvatures between improved shoulder balance and aggravated groups (P > 0.05). However, the middle to distal curve change ratio was significantly lower in patients with aggravated shoulder balance (P < 0.05). In addition, patients with smaller preoperative shoulder imbalance showed the higher chance of aggravation after surgery with similar postoperative changes (P < 0.05). Significant relations were found between correction rate of middle, and distal curvature, and postoperative shoulder balance. In addition, preoperative shoulder level difference can be a determinant of postoperative shoulder balance.

The effects of workplace psychosocial factors on whether Japanese dual-earner couples with preschool children have additional children: a prospective study

PubMed Central

EGUCHI, Hisashi; SHIMAZU, Akihito; FUJIWARA, Takeo; IWATA, Noboru; SHIMADA, Kyoko; TAKAHASHI, Masaya; TOKITA, Masahito; WATAI, Izumi; KAWAKAMI, Norito

2016-01-01

This study explored the effect of workplace psychosocial factors (job demand, job control, and workplace social support) on dual-earner couples in Japan having additional children, using a prospective study design. We conducted a 2-year prospective cohort study with 103 dual-earner couples with preschool children in Japan, as part of the Tokyo Work–Family Interface Study II. We used multivariable logistic regression analyses to evaluate the prospective association of job strain (categorized into low-strain job, active job, passive job, and strain job groups) and workplace social support (high and low) with couples having additional children during the follow-up period, adjusting for age, for men and women separately. Men in the active job group (i.e., with high job demands and high job control) had a significantly higher odds ratio (OR) of having additional children during the follow-up period, after controlling for age (OR 9.07, 95% confidence interval: 1.27–64.85). No significant association between any workplace psychosocial factor and having additional children was confirmed among women. Having an active job may have a positive influence on having additional children among men in dual-earner couples. PMID:27760893

The effects of workplace psychosocial factors on whether Japanese dual-earner couples with preschool children have additional children: a prospective study.

PubMed

Eguchi, Hisashi; Shimazu, Akihito; Fujiwara, Takeo; Iwata, Noboru; Shimada, Kyoko; Takahashi, Masaya; Tokita, Masahito; Watai, Izumi; Kawakami, Norito

2016-12-07

This study explored the effect of workplace psychosocial factors (job demand, job control, and workplace social support) on dual-earner couples in Japan having additional children, using a prospective study design. We conducted a 2-year prospective cohort study with 103 dual-earner couples with preschool children in Japan, as part of the Tokyo Work-Family Interface Study II. We used multivariable logistic regression analyses to evaluate the prospective association of job strain (categorized into low-strain job, active job, passive job, and strain job groups) and workplace social support (high and low) with couples having additional children during the follow-up period, adjusting for age, for men and women separately. Men in the active job group (i.e., with high job demands and high job control) had a significantly higher odds ratio (OR) of having additional children during the follow-up period, after controlling for age (OR 9.07, 95% confidence interval: 1.27-64.85). No significant association between any workplace psychosocial factor and having additional children was confirmed among women. Having an active job may have a positive influence on having additional children among men in dual-earner couples.

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.

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.

Characterization and analysis of surface notches on Ti-alloy plates fabricated by additive manufacturing techniques

NASA Astrophysics Data System (ADS)

Chan, Kwai S.

2015-12-01

Rectangular plates of Ti-6Al-4V with extra low interstitial (ELI) were fabricated by layer-by-layer deposition techniques that included electron beam melting (EBM) and laser beam melting (LBM). The surface conditions of these plates were characterized using x-ray micro-computed tomography. The depth and radius of surface notch-like features on the LBM and EBM plates were measured from sectional images of individual virtual slices of the rectangular plates. The stress concentration factors of individual surface notches were computed and analyzed statistically to determine the appropriate distributions for the notch depth, notch radius, and stress concentration factor. These results were correlated with the fatigue life of the Ti-6Al-4V ELI alloys from an earlier investigation. A surface notch analysis was performed to assess the debit in the fatigue strength due to the surface notches. The assessment revealed that the fatigue lives of the additively manufactured plates with rough surface topographies and notch-like features are dominated by the fatigue crack growth of large cracks for both the LBM and EBM materials. The fatigue strength reduction due to the surface notches can be as large as 60%-75%. It is concluded that for better fatigue performance, the surface notches on EBM and LBM materials need to be removed by machining and the surface roughness be improved to a surface finish of about 1 μm.

Analysis of the Use of Frame Construction and Modular Additions in City Centre

NASA Astrophysics Data System (ADS)

Milwicz, Roman; Milwicz, Natalia; Dubas, Sebastian

2017-10-01

The living urban fabric can be characterized by the continuous introduction of changes and additions. The city centre is subject to specific restrictions due to the conservation protection and high demand on aesthetics aspect, thermal insulation, construction cost and the ratio of usable area of the building area. This article presents a comparative analysis of traditional construction with light frame and modular construction for the above-mentioned issues. Timber frame structure technology was suggested as effective, economic and innovative solutions for modular additions on buildings in city centres.

Assessing State Nuclear Weapons Proliferation: Using Bayesian Network Analysis of Social Factors

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

Coles, Garill A.; Brothers, Alan J.; Olson, Jarrod

A Bayesian network (BN) model of social factors can support proliferation assessments by estimating the likelihood that a state will pursue a nuclear weapon. Social factors including political, economic, nuclear capability, security, and national identity and psychology factors may play as important a role in whether a State pursues nuclear weapons as more physical factors. This paper will show how using Bayesian reasoning on a generic case of a would-be proliferator State can be used to combine evidence that supports proliferation assessment. Theories and analysis by political scientists can be leveraged in a quantitative and transparent way to indicate proliferationmore » risk. BN models facilitate diagnosis and inference in a probabilistic environment by using a network of nodes and acyclic directed arcs between the nodes whose connections, or absence of, indicate probabilistic relevance, or independence. We propose a BN model that would use information from both traditional safeguards and the strengthened safeguards associated with the Additional Protocol to indicate countries with a high risk of proliferating nuclear weapons. This model could be used in a variety of applications such a prioritization tool and as a component of state safeguards evaluations. This paper will discuss the benefits of BN reasoning, the development of Pacific Northwest National Laboratory’s (PNNL) BN state proliferation model and how it could be employed as an analytical tool.« less

Bioinformatics Identification of Modules of Transcription Factor Binding Sites in Alzheimer's Disease-Related Genes by In Silico Promoter Analysis and Microarrays

PubMed Central

Augustin, Regina; Lichtenthaler, Stefan F.; Greeff, Michael; Hansen, Jens; Wurst, Wolfgang; Trümbach, Dietrich

2011-01-01

The molecular mechanisms and genetic risk factors underlying Alzheimer's disease (AD) pathogenesis are only partly understood. To identify new factors, which may contribute to AD, different approaches are taken including proteomics, genetics, and functional genomics. Here, we used a bioinformatics approach and found that distinct AD-related genes share modules of transcription factor binding sites, suggesting a transcriptional coregulation. To detect additional coregulated genes, which may potentially contribute to AD, we established a new bioinformatics workflow with known multivariate methods like support vector machines, biclustering, and predicted transcription factor binding site modules by using in silico analysis and over 400 expression arrays from human and mouse. Two significant modules are composed of three transcription factor families: CTCF, SP1F, and EGRF/ZBPF, which are conserved between human and mouse APP promoter sequences. The specific combination of in silico promoter and multivariate analysis can identify regulation mechanisms of genes involved in multifactorial diseases. PMID:21559189

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

PubMed

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

2016-08-01

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

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.

Body composition analysis and adipocytokine concentrations in haemodialysis patients: abdominal fat gain as an additional cardiovascular risk factor.

PubMed

González, Elena; Díez, Juan J; Pérez Torres, Almudena; Bajo, María Auxiliadora; Del Peso, Gloria; Sánchez-Villanueva, Rafael; Grande, Cristina; Rodríguez, Olaia; Coronado, Mónica; Gómez Candela, Carmen; Díaz-Almirón, Mariana; Iglesias, Pedro; Selgas, Rafael

Abdominal fat and its increment over time in particular has become a cardiovascular risk factor in uraemic patients. To analyse changes in abdominal fat in haemodialysis patients over one year and study their possible correlation with the variation in adipocytokine serum levels. As a secondary objective, we tried to validate the data obtained by bioelectrical impedance analysis (BIA) with data obtained by dual X-ray absorptiometry (DXA). A prospective one-year study was performed in 18 patients on haemodialysis (HD). In each patient, body composition by BIA and DXA was estimated at baseline and after one year. Several adipocytokine and biochemical parameters were determined. A significant increase in phase angle [4.8° (4.1-5.6) vs. 5.2° (4.4-5.8), P<.05], BIA intracellular water [48.3% (43.1-52.3) vs. 50.3% (45.7-53.4), P<.05] and the ratio between the percentage of android/gynecoid (A/G) distribution of fat measured by DXA [1.00 (0.80-1.26) vs. 1.02 (0.91-1.30), P<.05] was observed. A statistically significant relationship between leptin and adiponectin concentrations and the percentage of fat mass measured by BIA, as well as the abdominal fat percentage estimated by DXA, was found (P<.01). HD patients exhibit a gain in fat mass over time, especially in the abdomen, evidenced by an increased A/G ratio. These findings might explain the increased cardiovascular risk in these patients. Copyright © 2016 Sociedad Española de Nefrología. Published by Elsevier España, S.L.U. All rights reserved.

Re-analysis of survival data of cancer patients utilizing additive homeopathy.

PubMed

Gleiss, Andreas; Frass, Michael; Gaertner, Katharina

2016-08-01

In this short communication we present a re-analysis of homeopathic patient data in comparison to control patient data from the same Outpatient´s Unit "Homeopathy in malignant diseases" of the Medical University of Vienna. In this analysis we took account of a probable immortal time bias. For patients suffering from advanced stages of cancer and surviving the first 6 or 12 months after diagnosis, respectively, the results show that utilizing homeopathy gives a statistically significant (p<0.001) advantage over control patients regarding survival time. In conclusion, bearing in mind all limitations, the results of this retrospective study suggest that patients with advanced stages of cancer might benefit from additional homeopathic treatment until a survival time of up to 12 months after diagnosis. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

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.

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.…

Quantification method analysis of the relationship between occupant injury and environmental factors in traffic accidents.

PubMed

Ju, Yong Han; Sohn, So Young

2011-01-01

Injury analysis following a vehicle crash is one of the most important research areas. However, most injury analyses have focused on one-dimensional injury variables, such as the AIS (Abbreviated Injury Scale) or the IIS (Injury Impairment Scale), at a time in relation to various traffic accident factors. However, these studies cannot reflect the various injury phenomena that appear simultaneously. In this paper, we apply quantification method II to the NASS (National Automotive Sampling System) CDS (Crashworthiness Data System) to find the relationship between the categorical injury phenomena, such as the injury scale, injury position, and injury type, and the various traffic accident condition factors, such as speed, collision direction, vehicle type, and seat position. Our empirical analysis indicated the importance of safety devices, such as restraint equipment and airbags. In addition, we found that narrow impact, ejection, air bag deployment, and higher speed are associated with more severe than minor injury to the thigh, ankle, and leg in terms of dislocation, abrasion, or laceration. Copyright © 2010 Elsevier Ltd. 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.

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,…

Brain-Derived Neurotrophic Factor Levels in Autism: A Systematic Review and Meta-Analysis.

PubMed

Saghazadeh, Amene; Rezaei, Nima

2017-04-01

Brain-derived neurotrophic factor (BDNF) plays an important role in activity-dependent synaptic plasticity. Altered blood BDNF levels have been frequently identified in people with autism spectrum disorders (ASD). There are however wide discrepancies in the evidence. Therefore, we performed the present systematic review and meta-analysis aimed at qualitative and quantitative synthesis of studies that measured blood BDNF levels in ASD and control subjects. Observational studies were identified through electronic database searching and also hand-searching of reference lists of relevant articles. A total of 183 papers were initially identified for review and eventually twenty studies were included in the meta-analysis. A meta-analysis of blood BDNF in 887 patients with ASD and 901 control subjects demonstrated significantly higher BDNF levels in ASD compared to controls with the SMD of 0.47 (95% CI 0.07-0.86, p = 0.02). In addition subgroup meta-analyses were performed based on the BDNF specimen. The present meta-analysis study led to conclusion that BDNF might play role in autism initiation/ propagation and therefore it can be considered as a possible biomarker of ASD.

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.

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.

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.

Studies on a complex mechanism for the activation of plasminogen by kaolin and by chloroform: the participation of Hageman factor and additional cofactors

PubMed Central

Ogston, Derek; Ogston, C. Marie; Ratnoff, Oscar D.; Forbes, Charles D.

1969-01-01

As demonstrated by others, fibrinolytic activity was generated in diluted, acidified normal plasma exposed to kaolin, a process requiring Hageman factor (Factor XII). Generation was impaired by adsorbing plasma with glass or similar agents under conditions which did not deplete its content of Hageman factor or plasminogen. The defect could be repaired by addition of a noneuglobulin fraction of plasma or an agent or agents eluted from diatomaceous earth which had been exposed to normal plasma. The restorative agent, tentatively called Hageman factor-cofactor, was partially purified by chromatography and had an apparent molecular weight of approximately 165,000. It could be distinguished from plasma thromboplastin antecedent (Factor XI) and plasma kallikrein, other substrates of Hageman factor, and from the streptokinase-activated pro-activator of plasminogen. Evidence is presented that an additional component may be needed for the generation of fibrinolytic activity in mixtures containing Hageman factor, HF-cofactor, and plasminogen. The long-recognized generation of plasmin activity in chloroform-treated euglobulin fractions of plasma was found to be dependent upon the presence of Hageman factor. Whether chloroform activation of plasminogen requires Hageman factor-cofactor was not determined, but glass-adsorbed plasma, containing Hageman factor and plasminogen, did not generate appreciable fibrinolytic or caseinolytic activity. These studies emphasize the complex nature of the mechanisms which lead to the generation of plasmin in human plasma. PMID:4241814

Can pain and function be distinguished in the Oxford Hip Score in a meaningful way? : an exploratory and confirmatory factor analysis.

PubMed

Harris, K K; Price, A J; Beard, D J; Fitzpatrick, R; Jenkinson, C; Dawson, J

2014-11-01

The objective of this study was to explore dimensionality of the Oxford Hip Score (OHS) and examine whether self-reported pain and functioning can be distinguished in the form of subscales. This was a secondary data analysis of the UK NHS hospital episode statistics/patient-reported outcome measures dataset containing pre-operative OHS scores on 97 487 patients who were undergoing hip replacement surgery. The proposed number of factors to extract depended on the method of extraction employed. Velicer's Minimum Average Partial test and the Parallel Analysis suggested one factor, the Cattell's scree test and Kaiser-over-1 rule suggested two factors. Exploratory factor analysis demonstrated that the two-factor OHS had most of the items saliently loading either of the two factors. These factors were named 'Pain' and 'Function' and their respective subscales were created. There was some cross-loading of items: 8 (pain on standing up from a chair) and 11 (pain during work). These items were assigned to the 'Pain' subscale. The final 'Pain' subscale consisted of items 1, 8, 9, 10, 11 and 12. The 'Function' subscale consisted of items 2, 3, 4, 5, 6 and 7, with the recommended scoring of the subscales being from 0 (worst) to 100 (best). Cronbach's alpha was 0.855 for the 'Pain' subscale and 0.861 for the 'Function' subscale. A confirmatory factor analysis demonstrated that the two-factor model of the OHS had a better fit. However, none of the one-factor or two-factor models was rejected. Factor analyses demonstrated that, in addition to current usage as a single summary scale, separate information on pain and self-reported function can be extracted from the OHS in a meaningful way in the form of subscales. Cite this article: Bone Joint Res 2014;3:305-9. ©2014 The British Editorial Society of Bone & Joint Surgery.

Decreasing Cloudiness Over China: An Updated Analysis Examining Additional Variables

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

Kaiser, D.P.

2000-01-14

As preparation of the IPCC's Third Assessment Report takes place, one of the many observed climate variables of key interest is cloud amount. For several nations of the world, there exist records of surface-observed cloud amount dating back to the middle of the 20th Century or earlier, offering valuable information on variations and trends. Studies using such databases include Sun and Groisman (1999) and Kaiser and Razuvaev (1995) for the former Soviet Union, Angel1 et al. (1984) for the United States, Henderson-Sellers (1986) for Europe, Jones and Henderson-Sellers (1992) for Australia, and Kaiser (1998) for China. The findings of Kaisermore » (1998) differ from the other studies in that much of China appears to have experienced decreased cloudiness over recent decades (1954-1994), whereas the other land regions for the most part show evidence of increasing cloud cover. This paper expands on Kaiser (1998) by analyzing trends in additional meteorological variables for Chi na [station pressure (p), water vapor pressure (e), and relative humidity (rh)] and extending the total cloud amount (N) analysis an additional two years (through 1996).« less

Characterization of Factors Affecting Nanoparticle Tracking Analysis Results With Synthetic and Protein Nanoparticles.

PubMed

Krueger, Aaron B; Carnell, Pauline; Carpenter, John F

2016-04-01

In many manufacturing and research areas, the ability to accurately monitor and characterize nanoparticles is becoming increasingly important. Nanoparticle tracking analysis is rapidly becoming a standard method for this characterization, yet several key factors in data acquisition and analysis may affect results. Nanoparticle tracking analysis is prone to user input and bias on account of a high number of parameters available, contains a limited analysis volume, and individual sample characteristics such as polydispersity or complex protein solutions may affect analysis results. This study systematically addressed these key issues. The integrated syringe pump was used to increase the sample volume analyzed. It was observed that measurements recorded under flow caused a reduction in total particle counts for both polystyrene and protein particles compared to those collected under static conditions. In addition, data for polydisperse samples tended to lose peak resolution at higher flow rates, masking distinct particle populations. Furthermore, in a bimodal particle population, a bias was seen toward the larger species within the sample. The impacts of filtration on an agitated intravenous immunoglobulin sample and operating parameters including "MINexps" and "blur" were investigated to optimize the method. Taken together, this study provides recommendations on instrument settings and sample preparations to properly characterize complex samples. Copyright © 2016. Published by Elsevier Inc.

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…

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.

Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing

DOE PAGES

Steed, Chad A.; Halsey, William; Dehoff, Ryan; ...

2017-02-16

Flexible visual analysis of long, high-resolution, and irregularly sampled time series data from multiple sensor streams is a challenge in several domains. In the field of additive manufacturing, this capability is critical for realizing the full potential of large-scale 3D printers. Here, we propose a visual analytics approach that helps additive manufacturing researchers acquire a deep understanding of patterns in log and imagery data collected by 3D printers. Our specific goals include discovering patterns related to defects and system performance issues, optimizing build configurations to avoid defects, and increasing production efficiency. We introduce Falcon, a new visual analytics system thatmore » allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations, all with adjustable scale options. To illustrate the effectiveness of Falcon at providing thorough and efficient knowledge discovery, we present a practical case study involving experts in additive manufacturing and data from a large-scale 3D printer. The techniques described are applicable to the analysis of any quantitative time series, though the focus of this paper is on additive manufacturing.« less

Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing

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

Steed, Chad A.; Halsey, William; Dehoff, Ryan

Flexible visual analysis of long, high-resolution, and irregularly sampled time series data from multiple sensor streams is a challenge in several domains. In the field of additive manufacturing, this capability is critical for realizing the full potential of large-scale 3D printers. Here, we propose a visual analytics approach that helps additive manufacturing researchers acquire a deep understanding of patterns in log and imagery data collected by 3D printers. Our specific goals include discovering patterns related to defects and system performance issues, optimizing build configurations to avoid defects, and increasing production efficiency. We introduce Falcon, a new visual analytics system thatmore » allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations, all with adjustable scale options. To illustrate the effectiveness of Falcon at providing thorough and efficient knowledge discovery, we present a practical case study involving experts in additive manufacturing and data from a large-scale 3D printer. The techniques described are applicable to the analysis of any quantitative time series, though the focus of this paper is on additive manufacturing.« less

Analysis of occupational accidents: prevention through the use of additional technical safety measures for machinery.

PubMed

Dźwiarek, Marek; Latała, Agata

2016-01-01

This article presents an analysis of results of 1035 serious and 341 minor accidents recorded by Poland's National Labour Inspectorate (PIP) in 2005-2011, in view of their prevention by means of additional safety measures applied by machinery users. Since the analysis aimed at formulating principles for the application of technical safety measures, the analysed accidents should bear additional attributes: the type of machine operation, technical safety measures and the type of events causing injuries. The analysis proved that the executed tasks and injury-causing events were closely connected and there was a relation between casualty events and technical safety measures. In the case of tasks consisting of manual feeding and collecting materials, the injuries usually occur because of the rotating motion of tools or crushing due to a closing motion. Numerous accidents also happened in the course of supporting actions, like removing pollutants, correcting material position, cleaning, etc.

Additional risk factors for infection by multidrug-resistant pathogens in healthcare-associated infection: a large cohort study.

PubMed

Cardoso, Teresa; Ribeiro, Orquídea; Aragão, Irene César; Costa-Pereira, Altamiro; Sarmento, António Eugénio

2012-12-26

There is a lack of consensus regarding the definition of risk factors for healthcare-associated infection (HCAI). The purpose of this study was to identify additional risk factors for HCAI, which are not included in the current definition of HCAI, associated with infection by multidrug-resistant (MDR) pathogens, in all hospitalized infected patients from the community. This 1-year prospective cohort study included all patients with infection admitted to a large, tertiary care, university hospital. Risk factors not included in the HCAI definition, and independently associated with MDR pathogen infection, namely MDR Gram-negative (MDR-GN) and ESKAPE microorganisms (vancomycin-resistant Enterococcus faecium, methicillin-resistant Staphylococcus aureus, extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella species, carbapenem-hydrolyzing Klebsiella pneumonia and MDR Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter species), were identified by logistic regression among patients admitted from the community (either with community-acquired or HCAI). There were 1035 patients with infection, 718 from the community. Of these, 439 (61%) had microbiologic documentation; 123 were MDR (28%). Among MDR: 104 (85%) had MDR-GN and 41 (33%) had an ESKAPE infection. Independent risk factors associated with MDR and MDR-GN infection were: age (adjusted odds ratio (OR) = 1.7 and 1.5, p = 0.001 and p = 0.009, respectively), and hospitalization in the previous year (between 4 and 12 months previously) (adjusted OR = 2.0 and 1,7, p = 0.008 and p = 0.048, respectively). Infection by pathogens from the ESKAPE group was independently associated with previous antibiotic therapy (adjusted OR = 7.2, p < 0.001) and a Karnofsky index <70 (adjusted OR = 3.7, p = 0.003). Patients with infection by MDR, MDR-GN and pathogens from the ESKAPE group had significantly higher rates of inadequate antibiotic therapy than those without (46% vs 7%, 44% vs 10%, 61% vs 15

Additional risk factors for infection by multidrug-resistant pathogens in healthcare-associated infection: a large cohort study

PubMed Central

2012-01-01

Background There is a lack of consensus regarding the definition of risk factors for healthcare-associated infection (HCAI). The purpose of this study was to identify additional risk factors for HCAI, which are not included in the current definition of HCAI, associated with infection by multidrug-resistant (MDR) pathogens, in all hospitalized infected patients from the community. Methods This 1-year prospective cohort study included all patients with infection admitted to a large, tertiary care, university hospital. Risk factors not included in the HCAI definition, and independently associated with MDR pathogen infection, namely MDR Gram-negative (MDR-GN) and ESKAPE microorganisms (vancomycin-resistant Enterococcus faecium, methicillin-resistant Staphylococcus aureus, extended-spectrum beta-lactamase-producing Escherichia coli and Klebsiella species, carbapenem-hydrolyzing Klebsiella pneumonia and MDR Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter species), were identified by logistic regression among patients admitted from the community (either with community-acquired or HCAI). Results There were 1035 patients with infection, 718 from the community. Of these, 439 (61%) had microbiologic documentation; 123 were MDR (28%). Among MDR: 104 (85%) had MDR-GN and 41 (33%) had an ESKAPE infection. Independent risk factors associated with MDR and MDR-GN infection were: age (adjusted odds ratio (OR) = 1.7 and 1.5, p = 0.001 and p = 0.009, respectively), and hospitalization in the previous year (between 4 and 12 months previously) (adjusted OR = 2.0 and 1,7, p = 0.008 and p = 0.048, respectively). Infection by pathogens from the ESKAPE group was independently associated with previous antibiotic therapy (adjusted OR = 7.2, p < 0.001) and a Karnofsky index <70 (adjusted OR = 3.7, p = 0.003). Patients with infection by MDR, MDR-GN and pathogens from the ESKAPE group had significantly higher rates of inadequate antibiotic therapy than those without (46% vs 7

Dynamic Proteomic Analysis of Pancreatic Mesenchyme Reveals Novel Factors That Enhance Human Embryonic Stem Cell to Pancreatic Cell Differentiation.

PubMed

Russ, Holger A; Landsman, Limor; Moss, Christopher L; Higdon, Roger; Greer, Renee L; Kaihara, Kelly; Salamon, Randy; Kolker, Eugene; Hebrok, Matthias

2016-01-01

Current approaches in human embryonic stem cell (hESC) to pancreatic beta cell differentiation have largely been based on knowledge gained from developmental studies of the epithelial pancreas, while the potential roles of other supporting tissue compartments have not been fully explored. One such tissue is the pancreatic mesenchyme that supports epithelial organogenesis throughout embryogenesis. We hypothesized that detailed characterization of the pancreatic mesenchyme might result in the identification of novel factors not used in current differentiation protocols. Supplementing existing hESC differentiation conditions with such factors might create a more comprehensive simulation of normal development in cell culture. To validate our hypothesis, we took advantage of a novel transgenic mouse model to isolate the pancreatic mesenchyme at distinct embryonic and postnatal stages for subsequent proteomic analysis. Refined sample preparation and analysis conditions across four embryonic and prenatal time points resulted in the identification of 21,498 peptides with high-confidence mapping to 1,502 proteins. Expression analysis of pancreata confirmed the presence of three potentially important factors in cell differentiation: Galectin-1 (LGALS1), Neuroplastin (NPTN), and the Laminin α-2 subunit (LAMA2). Two of the three factors (LGALS1 and LAMA2) increased expression of pancreatic progenitor transcript levels in a published hESC to beta cell differentiation protocol. In addition, LAMA2 partially blocks cell culture induced beta cell dedifferentiation. Summarily, we provide evidence that proteomic analysis of supporting tissues such as the pancreatic mesenchyme allows for the identification of potentially important factors guiding hESC to pancreas differentiation.

Dynamic Proteomic Analysis of Pancreatic Mesenchyme Reveals Novel Factors That Enhance Human Embryonic Stem Cell to Pancreatic Cell Differentiation

PubMed Central

Russ, Holger A.; Landsman, Limor; Moss, Christopher L.; Higdon, Roger; Greer, Renee L.; Kaihara, Kelly; Salamon, Randy; Kolker, Eugene; Hebrok, Matthias

2016-01-01

Current approaches in human embryonic stem cell (hESC) to pancreatic beta cell differentiation have largely been based on knowledge gained from developmental studies of the epithelial pancreas, while the potential roles of other supporting tissue compartments have not been fully explored. One such tissue is the pancreatic mesenchyme that supports epithelial organogenesis throughout embryogenesis. We hypothesized that detailed characterization of the pancreatic mesenchyme might result in the identification of novel factors not used in current differentiation protocols. Supplementing existing hESC differentiation conditions with such factors might create a more comprehensive simulation of normal development in cell culture. To validate our hypothesis, we took advantage of a novel transgenic mouse model to isolate the pancreatic mesenchyme at distinct embryonic and postnatal stages for subsequent proteomic analysis. Refined sample preparation and analysis conditions across four embryonic and prenatal time points resulted in the identification of 21,498 peptides with high-confidence mapping to 1,502 proteins. Expression analysis of pancreata confirmed the presence of three potentially important factors in cell differentiation: Galectin-1 (LGALS1), Neuroplastin (NPTN), and the Laminin α-2 subunit (LAMA2). Two of the three factors (LGALS1 and LAMA2) increased expression of pancreatic progenitor transcript levels in a published hESC to beta cell differentiation protocol. In addition, LAMA2 partially blocks cell culture induced beta cell dedifferentiation. Summarily, we provide evidence that proteomic analysis of supporting tissues such as the pancreatic mesenchyme allows for the identification of potentially important factors guiding hESC to pancreas differentiation. PMID:26681951

Regression analysis of informative current status data with the additive hazards model.

PubMed

Zhao, Shishun; Hu, Tao; Ma, Ling; Wang, Peijie; Sun, Jianguo

2015-04-01

This paper discusses regression analysis of current status failure time data arising from the additive hazards model in the presence of informative censoring. Many methods have been developed for regression analysis of current status data under various regression models if the censoring is noninformative, and also there exists a large literature on parametric analysis of informative current status data in the context of tumorgenicity experiments. In this paper, a semiparametric maximum likelihood estimation procedure is presented and in the method, the copula model is employed to describe the relationship between the failure time of interest and the censoring time. Furthermore, I-splines are used to approximate the nonparametric functions involved and the asymptotic consistency and normality of the proposed estimators are established. A simulation study is conducted and indicates that the proposed approach works well for practical situations. An illustrative example is also provided.

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…

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…

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.

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.

Nationwide analysis on the impact of socioeconomic land use factors and incidence of urothelial carcinoma.

PubMed

Brandt, Maximilian P; Gust, Kilian M; Mani, Jens; Vallo, Stefan; Höfner, Thomas; Borgmann, Hendrik; Tsaur, Igor; Thomas, Christian; Haferkamp, Axel; Herrmann, Eva; Bartsch, Georg

2018-02-01

Incidence rates for urothelial carcinoma (UC) have been reported to differ between countries within the European Union (EU). Besides occupational exposure to chemicals, other substances such as tobacco and nitrite in groundwater have been identified as risk factors for UC. We investigated if regional differences in UC incidence rates are associated with agricultural, industrial and residential land use. Newly diagnosed cases of UC between 2003 and 2010 were included. Information within 364 administrative districts of Germany from 2004 for land use factors were obtained and calculated as a proportion of the total area of the respective administrative district and as a smoothed proportion. Furthermore, information on smoking habits was included in our analysis. Kulldorff spatial clustering was used to detect different clusters. A negative binomial model was used to test the spatial association between UC incidence as a ratio of observed versus expected incidence rates, land use and smoking habits. We identified 437,847,834 person years with 171,086 cases of UC. Cluster analysis revealed areas with higher incidence of UC than others (p=0.0002). Multivariate analysis including significant pairwise interactions showed that the environmental factors were independently associated with UC (p<0.001). The RR was 1.066 (95% CI 1.052-1.080), 1.066 (95% CI 1.042-1.089) and 1.067 (95% CI 1.045-1.093) for agricultural, industrial and residential areas, respectively, and 0.996 (95% CI 0.869-0.999) for the proportion of never smokers. This study displays regional differences in incidence of UC in Germany. Additionally, results suggest that socioeconomic factors based on agricultural, industrial and residential land use may be associated with UC incidence rates. Copyright © 2017 Elsevier Ltd. All rights reserved.

College Students’ Drinking Motives and Social-Contextual Factors: Comparing Associations across Levels of Analysis

PubMed Central

O'Hara, Ross E.; Armeli, Stephen; Tennen, Howard

2014-01-01

Prior investigations have established between-person associations between drinking motives and both levels of alcohol use and social-contextual factors surrounding that use, but these relations have yet to be examined at the within-person level of analysis. Moreover, exploring previously posited subtypes of coping motives (i.e., coping with depression, anxiety, and anger) may shed light on the within-person processes underlying drinking to cope. In this daily diary study of college student drinking (N = 722; 54% female), students reported each day how many drinks they consumed the previous evening in both social and nonsocial settings along with their motives for each drinking episode. Additionally, they reported whether they attended a party the evening before, the number of people they were with, the gender makeup of that group, and their perceptions of their companions’ drinking prevalence and quantity. External reasons for drinking—social and conformity motives—showed patterns largely consistent across levels of analysis and in agreement with motivational models. However, internal reasons for drinking—enhancement and coping motives—demonstrated divergent associations that suggest different processes across levels of analysis. Finally, coping subtypes showed differing associations with drinking levels and social-contextual factors dependent on the predisposing emotion and the level of analysis. These results suggest that internal drinking motives have unique state and trait components, which could have important implications for the application of motivational models to prevention and treatment efforts. We recommend including drinking motives (including coping subtypes) as within-person measures in future micro-longitudinal studies. PMID:25546143

College students' drinking motives and social-contextual factors: Comparing associations across levels of analysis.

PubMed

O'Hara, Ross E; Armeli, Stephen; Tennen, Howard

2015-06-01

Prior investigations have established between-person associations between drinking motives and both levels of alcohol use and social-contextual factors surrounding that use, but these relations have yet to be examined at the within-person level of analysis. Moreover, exploring previously posited subtypes of coping motives (i.e., coping with depression, anxiety, and anger) may shed light on the within-person processes underlying drinking to cope. In this daily diary study of college student drinking (N = 722; 54% female), students reported each day how many drinks they consumed the previous evening in both social and nonsocial settings along with their motives for each drinking episode. Additionally, they reported whether they attended a party the evening before, the number of people they were with, the gender makeup of that group, and their perceptions of their companions' drinking prevalence and quantity. External reasons for drinking-social and conformity motives-showed patterns largely consistent across levels of analysis and in agreement with motivational models. However, internal reasons for drinking-enhancement and coping motives-demonstrated divergent associations that suggest different processes across levels of analysis. Finally, coping subtypes showed differing associations with drinking levels and social-contextual factors dependent on the predisposing emotion and the level of analysis. These results suggest that internal drinking motives have unique state and trait components, which could have important implications for the application of motivational models to prevention and treatment efforts. We recommend including drinking motives (including coping subtypes) as within-person measures in future microlongitudinal studies. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Analysis of occupational accidents: prevention through the use of additional technical safety measures for machinery

PubMed Central

Dźwiarek, Marek; Latała, Agata

2016-01-01

This article presents an analysis of results of 1035 serious and 341 minor accidents recorded by Poland's National Labour Inspectorate (PIP) in 2005–2011, in view of their prevention by means of additional safety measures applied by machinery users. Since the analysis aimed at formulating principles for the application of technical safety measures, the analysed accidents should bear additional attributes: the type of machine operation, technical safety measures and the type of events causing injuries. The analysis proved that the executed tasks and injury-causing events were closely connected and there was a relation between casualty events and technical safety measures. In the case of tasks consisting of manual feeding and collecting materials, the injuries usually occur because of the rotating motion of tools or crushing due to a closing motion. Numerous accidents also happened in the course of supporting actions, like removing pollutants, correcting material position, cleaning, etc. PMID:26652689

[Total analysis of organic rubber additives].

PubMed

He, Wen-Xuan; Robert, Shanks; You, Ye-Ming

2010-03-01

In the present paper, after middle pressure chromatograph separation using both positive phase and reversed-phase conditions, the organic additives in ethylene-propylene rubber were identified by infrared spectrometer. At the same time, by using solid phase extraction column to maintain the main component-fuel oil in organic additves to avoid its interfering with minor compounds, other organic additves were separated and analysed by GC/Ms. In addition, the remaining active compound such as benzoyl peroxide was identified by CC/Ms, through analyzing acetone extract directly. Using the above mentioned techniques, soften agents (fuel oil, plant oil and phthalte), curing agent (benzoylperoxide), vulcanizing accelerators (2-mercaptobenzothiazole, ethyl thiuram and butyl thiuram), and antiagers (2, 6-Di-tert-butyl-4-methyl phenol and styrenated phenol) in ethylene-propylene rubber were identified. Although the technique was established in ethylene-propylene rubber system, it can be used in other rubber system.

Enhanced photo-fermentative H2 production using Rhodobacter sphaeroides by ethanol addition and analysis of soluble microbial products

PubMed Central

2014-01-01

Background Biological fermentation routes can provide an environmentally friendly way of producing H2 since they use renewable biomass as feedstock and proceed under ambient temperature and pressure. In particular, photo-fermentation has superior properties in terms of achieving high H2 yield through complete degradation of substrates. However, long-term H2 production data with stable performance is limited, and this data is essential for practical applications. In the present work, continuous photo-fermentative H2 production from lactate was attempted using the purple non-sulfur bacterium, Rhodobacter sphaeroides KD131. As a gradual drop in H2 production was observed, we attempted to add ethanol (0.2% v/v) to the medium. Results As continuous operation went on, H2 production was not sustained and showed a negligible H2 yield (< 0.5 mol H2/mol lactateadded) within two weeks. Electron balance analysis showed that the reason for the gradual drop in H2 production was ascribed to the increase in production of soluble microbial products (SMPs). To see the possible effect of ethanol addition, a batch test was first conducted. The presence of ethanol significantly increased the H2 yield from 1.15 to 2.20 mol H2/mol lactateadded, by suppressing the production of SMPs. The analysis of SMPs by size exclusion chromatography showed that, in the later period of fermentation, more than half of the low molecular weight SMPs (< 1 kDa) were consumed and used for H2 production when ethanol had been added, while the concentration of SMPs continuously increased in the absence of ethanol. It was found that the addition of ethanol facilitated the utilization of reducing power, resulting in an increase in the cellular levels of NAD+ and NADP+. In continuous operation, ethanol addition was effective, such that stable H2 production was attained with an H2 yield of 2.5 mol H2/mol lactateadded. Less than 15% of substrate electrons were used for SMP production, whereas 35% were used in

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 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

Process factors of enzyme concentration, time, power and frequency were investigated for ultrasound-enhanced bioscouring of greige cotton. A fractional factorial experimental design and subsequent regression analysis of the process factors were employed to determine the significance of each factor a...

[Risk factors for anorexia in children].

PubMed

Liu, Wei-Xiao; Lang, Jun-Feng; Zhang, Qin-Feng

2016-11-01

To investigate the risk factors for anorexia in children, and to reduce the prevalence of anorexia in children. A questionnaire survey and a case-control study were used to collect the general information of 150 children with anorexia (case group) and 150 normal children (control group). Univariate analysis and multivariate logistic stepwise regression analysis were performed to identify the risk factors for anorexia in children. The results of the univariate analysis showed significant differences between the case and control groups in the age in months when supplementary food were added, feeding pattern, whether they liked meat, vegetables and salty food, whether they often took snacks and beverages, whether they liked to play while eating, and whether their parents asked them to eat food on time (P<0.05). The results of the multivariate logistic regression analysis showed that late addition of supplementary food (OR=5.408), high frequency of taking snacks and/or drinks (OR=11.813), and eating while playing (OR=6.654) were major risk factors for anorexia in children. Liking of meat (OR=0.093) and vegetables (OR=0.272) and eating on time required by parents (OR=0.079) were protective factors against anorexia in children. Timely addition of supplementary food, a proper diet, and development of children's proper eating and living habits can reduce the incidence of anorexia in children.

Identifying influential factors of business process performance using dependency analysis

NASA Astrophysics Data System (ADS)

Wetzstein, Branimir; Leitner, Philipp; Rosenberg, Florian; Dustdar, Schahram; Leymann, Frank

2011-02-01

We present a comprehensive framework for identifying influential factors of business process performance. In particular, our approach combines monitoring of process events and Quality of Service (QoS) measurements with dependency analysis to effectively identify influential factors. The framework uses data mining techniques to construct tree structures to represent dependencies of a key performance indicator (KPI) on process and QoS metrics. These dependency trees allow business analysts to determine how process KPIs depend on lower-level process metrics and QoS characteristics of the IT infrastructure. The structure of the dependencies enables a drill-down analysis of single factors of influence to gain a deeper knowledge why certain KPI targets are not met.

Confirmatory Factor Analysis and Differential Relationships of the Two Subdomains of Negative Symptoms in Chronically Ill Psychotic Patients

PubMed Central

Stiekema, Annemarie P. M.; Liemburg, Edith J.; van der Meer, Lisette; Castelein, Stynke; Stewart, Roy; van Weeghel, Jaap; Aleman, André; Bruggeman, Richard

2016-01-01

Research suggests a two factor structure for negative symptoms in patients with psychotic disorders: social amotivation (SA) and expressive deficits (ED). Applying this two-factor structure in clinical settings may provide valuable information with regard to outcomes and to target treatments. We aimed to investigate 1) whether the factor structure is also supported in chronically ill patients with a psychotic disorder and 2) what the relationship is between these factors and functioning (overall functioning and living situation), depressive symptoms and quality of life. 1157 Patients with a psychotic disorder and a duration of illness of 5 years or more were included in the analysis (data selected from the Pharmacotherapy Monitoring Outcome Survey; PHAMOUS). A confirmatory factor analysis was performed using items of the Positive and Negative Syndrome Scale that were previously identified to reflect negative symptoms (N1-4, N6, G5, G7, G13, G16). Subsequently, regression analysis was performed on outcomes. The results confirmed the distinction between SA (N2, N4, G16) and ED (N1, N3, N6, G5, G7, G13) in chronically ill patients. Both factors were related to worse overall functioning as measured with the Health of the Nation Outcome Scales, ED was uniquely associated with residential living status. Higher scores for SA were associated with more depressive symptoms and worse quality of life. Thus, SA is most strongly related to level of social-emotional functioning, while ED are more related to living situation and thereby are indicative of level of everyday functioning. This subdivision may be useful for research purposes and be a valuable additional tool in clinical practice and treatment development. PMID:26895203

Analysis of the effects of geological and geomorphological factors on earthquake triggered landslides using artificial neural networks (ANN)

NASA Astrophysics Data System (ADS)

Kawabata, D.; Bandibas, J.

2007-12-01

The occurrence of landslide is the result of the interaction of complex and diverse environmental factors. The geomorphic and geologic features, rock types and vegetative cover are important base factors of landslide occurrence. However, determining the relationship between these factors and landslide occurrence is very difficult using conventional mathematical analysis. The use of an advanced computing technique for this kind of analysis is very important. Artificial neural network (ANN) has recently been included in the list of analytical tools for a wide range of applications in the natural sciences research fields. One of the advantages of using ANN for pattern recognition is that it can handle data at any measurement scale ranging from nominal, ordinal to linear and ratio, and any form of data distribution (Wang et al., 1995). In addition, it can easily handle qualitative variables making it widely used in integrated analysis of spatial data from multiple sources for predicting and classification. This study focuses on the definition of the relationship between geological factors and landslide occurrence using artificial neural networks. The study also focuses on the effect of the DTMs (e.g. ASTER DTM, ALSM, digitized from paper map and digital photogrammetric measurement data). The main aim of the study is to generate landslide susceptibility index map using the defined relationship using ANN. Landslide data in the Chuetsu region were used in this research. The 2004 earthquake triggered many landslides in the region. The initial results of the study showed that ANN is more accurate in defining the relationship between geological and geomorphological factors and landslide occurrence. It also determined the best combination of geological and geomorphological factors that is directly related to landslide occurrence.

Confirmatory Factor Analysis of the WISC-III with Child Psychiatric Inpatients.

ERIC Educational Resources Information Center

Tupa, David J.; Wright, Margaret O'Dougherty; Fristad, Mary A.

1997-01-01

Factor models of the Wechsler Intelligence Scale for Children-Third Edition (WISC-III) for one, two, three, and four factors were tested using confirmatory factor analysis with a sample of 177 child psychiatric inpatients. The four-factor model proposed in the WISC-III manual provided the best fit to the data. (SLD)

Gender difference in sickness absence from work: a multiple mediation analysis of psychosocial factors.

PubMed

Casini, Annalisa; Godin, Isabelle; Clays, Els; Kittel, France

2013-08-01

Previous research has shown that job characteristics, private life and psychosocial factors partially account for gender difference in work absences because of sickness. Most studies have analysed these factors separately. The aim of the present study was to evaluate whether these explanatory factors act as mediators when they are considered simultaneously. The evaluated data set comprises the merger of two Belgian longitudinal studies, BELSTRESS III and SOMSTRESS. It includes 3821 workers (1541 men) aged 21-66 years, employed in eight organizations. A multiple mediation analysis was performed to explain the higher prevalence among women. Estimated factors were occupational grade, total number of paid working hours per week, job strain, overcommitment, home-work interference and social support at and outside work. Prospective data concerning duration and frequency of medically justified sickness absence (registered by the organizations) were used as outcomes. Overall, the mediating factors partially account for gender difference in sickness absence. The strongest mediator for both outcomes is job strain. In addition, difference in absence duration is mediated by social support at work, whereas difference in frequency is mediated by professional grade and home-work interference. Our results call attention to the necessity to elaborate actual preventive actions aiming at favouring a better positioning of women on the labour market in term of hierarchical level as well as in terms of quality of work for reducing sickness absence in this group.

Emotional experiences and motivating factors associated with fingerprint analysis.

PubMed

Charlton, David; Fraser-Mackenzie, Peter A F; Dror, Itiel E

2010-03-01

In this study, we investigated the emotional and motivational factors involved in fingerprint analysis in day-to-day routine case work and in significant and harrowing criminal investigations. Thematic analysis was performed on interviews with 13 experienced fingerprint examiners from a variety of law enforcement agencies. The data revealed factors relating to job satisfaction and the use of skill. Individual satisfaction related to catching criminals was observed; this was most notable in solving high profile, serious, or long-running cases. There were positive emotional effects associated with matching fingerprints and apparent fear of making errors. Finally, we found evidence for a need of cognitive closure in fingerprint examiner decision-making.

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.

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.

Factors affecting survival outcomes of patients with non-metastatic Ewing's sarcoma family tumors in the spine: a retrospective analysis of 63 patients in a single center.

PubMed

Wan, Wei; Lou, Yan; Hu, Zhiqi; Wang, Ting; Li, Jinsong; Tang, Yu; Wu, Zhipeng; Xu, Leqin; Yang, Xinghai; Song, Dianwen; Xiao, Jianru

2017-01-01

Little information has been published in the literature regarding survival outcomes of patients with Ewing's sarcoma family tumors (ESFTs) of the spine. The purpose of this study is to explore factors that may affect the prognosis of patients with non-metastatic spinal ESFTs. A retrospective analysis of survival outcomes was performed in patients with non-metastatic spinal ESFTs. Univariate and multivariate analyses were employed to identify prognostic factors for recurrence and survival. Recurrence-free survival (RFS) and overall survival (OS) were defined as the date of surgery to the date of local relapse and death. Kaplan-Meier methods were applied to estimate RFS and OS. Log-rank test was used to analyze single factors for RFS and OS. Factors with p values ≤0.1 were subjected to multivariate analysis. A total of 63 patients with non-metastatic spinal ESFTs were included in this study. The mean follow-up period was 35.1 months (range 1-155). Postoperative recurrence was detected in 25 patients, and distant metastasis and death occurred in 22 and 36 patients respectively. The result of multivariate analysis suggested that age older than 25 years and neoadjuvant chemotherapy were favorable independent prognostic factors for RFS and OS. In addition, total en-bloc resection, postoperative chemotherapy, radiotherapy and non-distant metastasis were favorable independent prognostic factors for OS. Age older than 25 years and neoadjuvant chemotherapy are favorable prognostic factors for both RFS and OS. In addition, total en-bloc resection, postoperative chemotherapy, radiotherapy and non-distant metastasis are closely associated with favorable survival.

Analysis of human factors effects on the safety of transporting radioactive waste materials: Technical report

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

Abkowitz, M.D.; Abkowitz, S.B.; Lepofsky, M.

1989-04-01

This report examines the extent of human factors effects on the safety of transporting radioactive waste materials. It is seen principally as a scoping effort, to establish whether there is a need for DOE to undertake a more formal approach to studying human factors in radioactive waste transport, and if so, logical directions for that program to follow. Human factors effects are evaluated on driving and loading/transfer operations only. Particular emphasis is placed on the driving function, examining the relationship between human error and safety as it relates to the impairment of driver performance. Although multi-modal in focus, the widespreadmore » availability of data and previous literature on truck operations resulted in a primary study focus on the trucking mode from the standpoint of policy development. In addition to the analysis of human factors accident statistics, the report provides relevant background material on several policies that have been instituted or are under consideration, directed at improving human reliability in the transport sector. On the basis of reported findings, preliminary policy areas are identified. 71 refs., 26 figs., 5 tabs.« less

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.

Main and interactive effects of multiple global-change factors on soil respiration and its components: a meta-analysis

NASA Astrophysics Data System (ADS)

Zhou, Xuhui

2014-05-01

Global change usually involves simultaneous changes in multiple environmental factors, which may considerably affect ecosystem structure and functioning and alter ecosystem services to human society. With increased awareness of their potential interactions, some multi-factorial studies have been conducted to investigate their main and interactive effects on carbon (C) cycling in terrestrial ecosystem. However, how multiple global-change factors affected soil respiration (Rs) and its components (i.e., autotrophic (Ra) and heterotrophic respiration (Rh)) remains controversial among individual studies. In this study, we conducted a meta-analysis to examine the main and possible 2- or 3-factor interactive effects with warming (W), elevated CO2 (E), nitrogen addition (N), increased precipitation (I) and drought (D) on Rs and its components from 150 published papers. Our results show that E, W, I and N significantly stimulated Rs by 29.23%, 7.19%, 22.95%, and 16.90% (p<0.05), respectively, while I depressed it by 16.90% (p<0.01). E consistently induced a significant positive effect on both Ra and Rh, while I affected them with an opposite trend. Among nine two-way interactive effects on Rs, synergistic interaction (i.e., the effect of combined treatment > the additive effects of single two main factors) occurred in E×N, E×W, I×N, and D×W, while neutral interaction (i.e., the effect of combined treatment ≡ the additive one) and antagonistic interaction (i.e., the effect of combined treatment < the additive one)was rare, only in I×W for neutral one and in N×W and I×E for the latter. In addition, E×W and E×N displayed synergistic interactions on Rh. The more dominance of synergistic interactions in two-way interactive effects on Rs and Rh may determine a central positive tendency of Rs in future, and affect the feedback of terrestrial C cycle to the climate system correspondingly.

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

PubMed

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

2015-09-01

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

Source apportionment of PAH in Hamilton Harbour suspended sediments: comparison of two factor analysis methods.

PubMed

Sofowote, Uwayemi M; McCarry, Brian E; Marvin, Christopher H

2008-08-15

A total of 26 suspended sediment samples collected over a 5-year period in Hamilton Harbour, Ontario, Canada and surrounding creeks were analyzed for a suite of polycyclic aromatic hydrocarbons and sulfur heterocycles. Hamilton Harbour sediments contain relatively high levels of polycyclic aromatic compounds and heavy metals due to emissions from industrial and mobile sources. Two receptor modeling methods using factor analyses were compared to determine the profiles and relative contributions of pollution sources to the harbor; these methods are principal component analyses (PCA) with multiple linear regression analysis (MLR) and positive matrix factorization (PMF). Both methods identified four factors and gave excellent correlation coefficients between predicted and measured levels of 25 aromatic compounds; both methods predicted similar contributions from coal tar/coal combustion sources to the harbor (19 and 26%, respectively). One PCA factor was identified as contributions from vehicular emissions (61%); PMF was able to differentiate vehicular emissions into two factors, one attributed to gasoline emissions sources (28%) and the other to diesel emissions sources (24%). Overall, PMF afforded better source identification than PCA with MLR. This work constitutes one of the few examples of the application of PMF to the source apportionment of sediments; the addition of sulfur heterocycles to the analyte list greatly aided in the source identification process.

What Is Rotating in Exploratory Factor Analysis?

ERIC Educational Resources Information Center

Osborne, Jason W.

2015-01-01

Exploratory factor analysis (EFA) is one of the most commonly-reported quantitative methodology in the social sciences, yet much of the detail regarding what happens during an EFA remains unclear. The goal of this brief technical note is to explore what "rotation" is, what exactly is rotating, and why we use rotation when performing…

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).

Confirmatory Factor Analysis of the Delirium Rating Scale Revised-98 (DRS-R98).

PubMed

Thurber, Steven; Kishi, Yasuhiro; Trzepacz, Paula T; Franco, Jose G; Meagher, David J; Lee, Yanghyun; Kim, Jeong-Lan; Furlanetto, Leticia M; Negreiros, Daniel; Huang, Ming-Chyi; Chen, Chun-Hsin; Kean, Jacob; Leonard, Maeve

2015-01-01

Principal components analysis applied to the Delirium Rating Scale-Revised-98 contributes to understanding the delirium construct. Using a multisite pooled international delirium database, the authors applied confirmatory factor analysis to Delirium Rating Scale-Revised-98 scores from 859 adult patients evaluated by delirium experts (delirium, N=516; nondelirium, N=343). Confirmatory factor analysis found all diagnostic features and core symptoms (cognitive, language, thought process, sleep-wake cycle, motor retardation), except motor agitation, loaded onto factor 1. Motor agitation loaded onto factor 2 with noncore symptoms (delusions, affective lability, and perceptual disturbances). Factor 1 loading supports delirium as a single construct, but when accompanied by psychosis, motor agitation's role may not be solely as a circadian activity indicator.

Factors Affecting Arsenic Methylation in Arsenic-Exposed Humans: A Systematic Review and Meta-Analysis.

PubMed

Shen, Hui; Niu, Qiang; Xu, Mengchuan; Rui, Dongsheng; Xu, Shangzhi; Feng, Gangling; Ding, Yusong; Li, Shugang; Jing, Mingxia

2016-02-06

Chronic arsenic exposure is a critical public health issue in many countries. The metabolism of arsenic in vivo is complicated because it can be influenced by many factors. In the present meta-analysis, two researchers independently searched electronic databases, including the Cochrane Library, PubMed, Springer, Embase, and China National Knowledge Infrastructure, to analyze factors influencing arsenic methylation. The concentrations of the following arsenic metabolites increase (p< 0.000001) following arsenic exposure: inorganic arsenic (iAs), monomethyl arsenic (MMA), dimethyl arsenic (DMA), and total arsenic. Additionally, the percentages of iAs (standard mean difference (SMD): 1.00; 95% confidence interval (CI): 0.60-1.40; p< 0.00001) and MMA (SMD: 0.49; 95% CI: 0.21-0.77; p = 0.0006) also increase, while the percentage of DMA (SMD: -0.57; 95% CI: -0.80--0.31; p< 0.0001), primary methylation index (SMD: -0.57; 95% CI: -0.94--0.20; p = 0.002), and secondary methylation index (SMD: -0.27; 95% CI: -0.46--0.90; p = 0.004) decrease. Smoking, drinking, and older age can reduce arsenic methylation, and arsenic methylation is more efficient in women than in men. The results of this analysis may provide information regarding the role of arsenic oxidative methylation in the arsenic poisoning process.

A Meta-Analysis of Factors Influencing the Development of Trust in Automation: Implications for Understanding Autonomy in Future Systems.

PubMed

Schaefer, Kristin E; Chen, Jessie Y C; Szalma, James L; Hancock, P A

2016-05-01

We used meta-analysis to assess research concerning human trust in automation to understand the foundation upon which future autonomous systems can be built. Trust is increasingly important in the growing need for synergistic human-machine teaming. Thus, we expand on our previous meta-analytic foundation in the field of human-robot interaction to include all of automation interaction. We used meta-analysis to assess trust in automation. Thirty studies provided 164 pairwise effect sizes, and 16 studies provided 63 correlational effect sizes. The overall effect size of all factors on trust development was ḡ = +0.48, and the correlational effect was [Formula: see text]  = +0.34, each of which represented medium effects. Moderator effects were observed for the human-related (ḡ  = +0.49; [Formula: see text] = +0.16) and automation-related (ḡ = +0.53; [Formula: see text] = +0.41) factors. Moderator effects specific to environmental factors proved insufficient in number to calculate at this time. Findings provide a quantitative representation of factors influencing the development of trust in automation as well as identify additional areas of needed empirical research. This work has important implications to the enhancement of current and future human-automation interaction, especially in high-risk or extreme performance environments. © 2016, Human Factors and Ergonomics Society.

Factor Analysis of the Aberrant Behavior Checklist in Individuals with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Brinkley, Jason; Nations, Laura; Abramson, Ruth K.; Hall, Alicia; Wright, Harry H.; Gabriels, Robin; Gilbert, John R.; Pericak-Vance, Margaret A. O.; Cuccaro, Michael L.

2007-01-01

Exploratory factor analysis (varimax and promax rotations) of the aberrant behavior checklist-community version (ABC) in 275 individuals with Autism spectrum disorder (ASD) identified four- and five-factor solutions which accounted for greater than 70% of the variance. Confirmatory factor analysis (Lisrel 8.7) revealed indices of moderate fit for…

Analysis of Factors Associated With Rhytidectomy Malpractice Litigation Cases.

PubMed

Kandinov, Aron; Mutchnick, Sean; Nangia, Vaibhuv; Svider, Peter F; Zuliani, Giancarlo F; Shkoukani, Mahdi A; Carron, Michael A

2017-07-01

This study investigates the financial burden of medical malpractice litigation associated with rhytidectomies, as well as factors that contribute to litigation and poor defendant outcomes, which can help guide physician practices. To comprehensively evaluate rhytidectomy malpractice litigation. Jury verdict and settlement reports related to rhytidectomy malpractice litigations were obtained using the Westlaw Next database. Use of medical malpractice in conjunction with several terms for rhytidectomy, to account for the various procedure names associated with the procedure, yielded 155 court cases. Duplicate and nonrelevant cases were removed, and 89 cases were included in the analysis and reviewed for outcomes, defendant specialty, payments, and other allegations raised in proceedings. Data were collected from November 21, 2015, to December 25, 2015. Data analysis took place from December 25, 2015, to January 20, 2016. A total of 89 cases met our inclusion criteria. Most plaintiffs were female (81 of 88 with known sex [92%]), and patient age ranged from 40 to 76 years (median age, 56 years). Fifty-three (60%) were resolved in the defendant's favor, while the remaining 36 cases (40%) were resolved with either a settlement or a plaintiff verdict payment. The mean payment was $1.4 million. A greater proportion of cases involving plastic surgeon defendants were resolved with payment compared with cases involving defendants with ear, nose, and throat specialty (15 [36%] vs 4 [24%]). The most common allegations raised in litigation were intraoperative negligence (61 [69%]), poor cosmesis or disfigurement (57 [64%]), inadequate informed consent (30 [34%]), additional procedures required (14 [16%]), postoperative negligence (12 [14%]), and facial nerve injury (10 [11%]). Six cases (7%) involved alleged negligence surrounding a "lifestyle-lift" procedure, which tightens or oversews the superficial muscular aponeurosis system layer. In this study, although most cases of

A factor analysis of landscape pattern and structure metrics

Treesearch

Kurt H. Riitters; R.V. O' Neill; C.T. Hunsaker; James D. Wickham; D.H. Yankee; S.P. Timmins; K.B. Jones; B.L. Jackson

1995-01-01

Fifty-five metrics of landscape pattern and structure were calculated for 85 maps of land use and land cover. A multivariate factor analysis was used to identify the common axes (or dimensions) of pattern and structure which were measured by a reduced set of 26 metrics. The first six factors explained about 87% of the variation in the 26 landscape metrics. These...

Dried blood spot analysis of creatinine with LC-MS/MS in addition to immunosuppressants analysis.

PubMed

Koster, Remco A; Greijdanus, Ben; Alffenaar, Jan-Willem C; Touw, Daan J

2015-02-01

In order to monitor creatinine levels or to adjust the dosage of renally excreted or nephrotoxic drugs, the analysis of creatinine in dried blood spots (DBS) could be a useful addition to DBS analysis. We developed a LC-MS/MS method for the analysis of creatinine in the same DBS extract that was used for the analysis of tacrolimus, sirolimus, everolimus, and cyclosporine A in transplant patients with the use of Whatman FTA DMPK-C cards. The method was validated using three different strategies: a seven-point calibration curve using the intercept of the calibration to correct for the natural presence of creatinine in reference samples, a one-point calibration curve at an extremely high concentration in order to diminish the contribution of the natural presence of creatinine, and the use of creatinine-[(2)H3] with an eight-point calibration curve. The validated range for creatinine was 120 to 480 μmol/L (seven-point calibration curve), 116 to 7000 μmol/L (1-point calibration curve), and 1.00 to 400.0 μmol/L for creatinine-[(2)H3] (eight-point calibration curve). The precision and accuracy results for all three validations showed a maximum CV of 14.0% and a maximum bias of -5.9%. Creatinine in DBS was found stable at ambient temperature and 32 °C for 1 week and at -20 °C for 29 weeks. Good correlations were observed between patient DBS samples and routine enzymatic plasma analysis and showed the capability of the DBS method to be used as an alternative for creatinine plasma measurement.

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.

Bayes factor design analysis: Planning for compelling evidence.

PubMed

Schönbrodt, Felix D; Wagenmakers, Eric-Jan

2018-02-01

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

Application of the Bootstrap Methods in Factor Analysis.

ERIC Educational Resources Information Center

Ichikawa, Masanori; Konishi, Sadanori

1995-01-01

A Monte Carlo experiment was conducted to investigate the performance of bootstrap methods in normal theory maximum likelihood factor analysis when the distributional assumption was satisfied or unsatisfied. Problems arising with the use of bootstrap methods are highlighted. (SLD)

Exploratory Factor Analysis with Small Sample Sizes

ERIC Educational Resources Information Center

de Winter, J. C. F.; Dodou, D.; Wieringa, P. A.

2009-01-01

Exploratory factor analysis (EFA) is generally regarded as a technique for large sample sizes ("N"), with N = 50 as a reasonable absolute minimum. This study offers a comprehensive overview of the conditions in which EFA can yield good quality results for "N" below 50. Simulations were carried out to estimate the minimum required "N" for different…

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.

Space Human Factors Engineering Gap Analysis Project Final Report

NASA Technical Reports Server (NTRS)

Hudy, Cynthia; Woolford, Barbara

2006-01-01

Humans perform critical functions throughout each phase of every space mission, beginning with the mission concept and continuing to post-mission analysis (Life Sciences Division, 1996). Space missions present humans with many challenges - the microgravity environment, relative isolation, and inherent dangers of the mission all present unique issues. As mission duration and distance from Earth increases, in-flight crew autonomy will increase along with increased complexity. As efforts for exploring the moon and Mars advance, there is a need for space human factors research and technology development to play a significant role in both on-orbit human-system interaction, as well as the development of mission requirements and needs before and after the mission. As part of the Space Human Factors Engineering (SHFE) Project within the Human Research Program (HRP), a six-month Gap Analysis Project (GAP) was funded to identify any human factors research gaps or knowledge needs. The overall aim of the project was to review the current state of human factors topic areas and requirements to determine what data, processes, or tools are needed to aid in the planning and development of future exploration missions, and also to prioritize proposals for future research and technology development.

Assessing Suicide Risk Among Callers to Crisis Hotlines: A Confirmatory Factor Analysis

PubMed Central

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

2012-01-01

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. 1,085 suicidal callers to crisis hotlines were divided into three sub-samples, which allowed us to conduct an independent Exploratory Factor Analysis (EFA), EFA in a Confirmatory Factor Analysis (EFA/CFA) framework, and CFA. Similar to previous factor analytic studies (Beck et al., 1997; Holden & DeLisle, 2005; Joiner, Rudd, & Rajab, 1997; Witte et al., 2006), 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) and one factor representing more mild suicidal ideation (i.e., Suicidal Desire and Ideation). Using structural equation modeling techniques, we found preliminary evidence that the Resolved Plans and Preparations factor trended toward being more predictive of suicidal ideation than the Suicidal Desire and Ideation factor. This factor analytic study is the first longitudinal study of the obtained factors. PMID:20578186

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

PubMed

Islam, S M

1986-01-01

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

A hierarchical factor analysis of a safety culture survey.

PubMed

Frazier, Christopher B; Ludwig, Timothy D; Whitaker, Brian; Roberts, D Steve

2013-06-01

Recent reviews of safety culture measures have revealed a host of potential factors that could make up a safety culture (Flin, Mearns, O'Connor, & Bryden, 2000; Guldenmund, 2000). However, there is still little consensus regarding what the core factors of safety culture are. The purpose of the current research was to determine the core factors, as well as the structure of those factors that make up a safety culture, and establish which factors add meaningful value by factor analyzing a widely used safety culture survey. A 92-item survey was constructed by subject matter experts and was administered to 25,574 workers across five multi-national organizations in five different industries. Exploratory and hierarchical confirmatory factor analyses were conducted revealing four second-order factors of a Safety Culture consisting of Management Concern, Personal Responsibility for Safety, Peer Support for Safety, and Safety Management Systems. Additionally, a total of 12 first-order factors were found: three on Management Concern, three on Personal Responsibility, two on Peer Support, and four on Safety Management Systems. The resulting safety culture model addresses gaps in the literature by indentifying the core constructs which make up a safety culture. This clarification of the major factors emerging in the measurement of safety cultures should impact the industry through a more accurate description, measurement, and tracking of safety cultures to reduce loss due to injury. Copyright © 2013 National Safety Council and Elsevier Ltd. All rights reserved.

Identifying items to assess methodological quality in physical therapy trials: a factor analysis.

PubMed

Armijo-Olivo, Susan; Cummings, Greta G; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

2014-09-01

Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). A methodological research design was used, and an EFA was performed. Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor analysis of these results are needed to validate these items. �

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

Graphical augmentations to the funnel plot assess the impact of additional evidence on a meta-analysis.

PubMed

Langan, Dean; Higgins, Julian P T; Gregory, Walter; Sutton, Alexander J

2012-05-01

We aim to illustrate the potential impact of a new study on a meta-analysis, which gives an indication of the robustness of the meta-analysis. A number of augmentations are proposed to one of the most widely used of graphical displays, the funnel plot. Namely, 1) statistical significance contours, which define regions of the funnel plot in which a new study would have to be located to change the statistical significance of the meta-analysis; and 2) heterogeneity contours, which show how a new study would affect the extent of heterogeneity in a given meta-analysis. Several other features are also described, and the use of multiple features simultaneously is considered. The statistical significance contours suggest that one additional study, no matter how large, may have a very limited impact on the statistical significance of a meta-analysis. The heterogeneity contours illustrate that one outlying study can increase the level of heterogeneity dramatically. The additional features of the funnel plot have applications including 1) informing sample size calculations for the design of future studies eligible for inclusion in the meta-analysis; and 2) informing the updating prioritization of a portfolio of meta-analyses such as those prepared by the Cochrane Collaboration. Copyright © 2012 Elsevier Inc. All rights reserved.

Confirmatory Factor Analysis of the Cancer Locus of Control Scale.

ERIC Educational Resources Information Center

Henderson, Jessica W.; Donatelle, Rebecca J.; Acock, Alan C.

2002-01-01

Conducted a confirmatory factor analysis of the Cancer Locus of Control scale (M. Watson and others, 1990), administered to 543 women with a history of breast cancer. Results support a three-factor model of the scale and support use of the scale to assess control dimensions. (SLD)

Analysis of Social Cohesion in Health Data by Factor Analysis Method: The Ghanaian Perspective

ERIC Educational Resources Information Center

Saeed, Bashiru I. I.; Xicang, Zhao; Musah, A. A. I.; Abdul-Aziz, A. R.; Yawson, Alfred; Karim, Azumah

2013-01-01

We investigated the study of the overall social cohesion of Ghanaians. In this study, we considered the paramount interest of the involvement of Ghanaians in their communities, their views of other people and institutions, and their level of interest in both local and national politics. The factor analysis method was employed for analysis using R…

Evidence Regarding the Internal Structure: Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Lewis, Todd F.

2017-01-01

American Educational Research Association (AERA) standards stipulate that researchers show evidence of the internal structure of instruments. Confirmatory factor analysis (CFA) is one structural equation modeling procedure designed to assess construct validity of assessments that has broad applicability for counselors interested in instrument…

Factor Structure of the Student-Teacher Relationship Scale for Norwegian School-Age Children Explored with Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Drugli, May Britt; Hjemdal, Odin

2013-01-01

The validity of the Student-Teacher Relationship Scale (STRS) was examined in a national sample of 863 Norwegian schoolchildren in grades 1-7 (aged 6-13). The original factor structure of the STRS was tested by confirmatory factor analysis (CFA). The CFA results did not support the original three-factor structure of the STRS. Subsequent CFA of the…

Future Directions in Vulnerability to Depression among Youth: Integrating Risk Factors and Processes across Multiple Levels of Analysis

PubMed Central

Hankin, Benjamin L.

2014-01-01

Depression is a developmental phenomenon. Considerable progress has been made in describing the syndrome, establishing its prevalence and features, providing clues as to its etiology, and developing evidence-based treatment and prevention options. Despite considerable headway in distinct lines of vulnerability research, there is an explanatory gap in the field ability to more comprehensively explain and predict who is likely to become depressed, when, and why. Still, despite clear success in predicting moderate variance for future depression, especially with empirically rigorous methods and designs, the heterogeneous and multi-determined nature of depression suggests that additional etiologies need to be included to advance knowledge on developmental pathways to depression. This paper advocates for a multiple levels of analysis approach to investigating vulnerability to depression across the lifespan and providing a more comprehensive understanding of its etiology. One example of a multiple levels of analysis model of vulnerabilities to depression is provided that integrates the most accessible, observable factors (e.g., cognitive and temperament risks), intermediate processes and endophenotypes (e.g., information processing biases, biological stress physiology, and neural activation and connectivity), and genetic influences (e.g., candidate genes and epigenetics). Evidence for each of these factors as well as their cross-level integration is provided. Methodological and conceptual considerations important for conducting integrative, multiple levels of depression vulnerability research are discussed. Finally, translational implications for how a multiple levels of analysis perspective may confer additional leverage to reduce the global burden of depression and improve care are considered. PMID:22900513

The School Counselor Leadership Survey: Instrument Development and Exploratory Factor Analysis

ERIC Educational Resources Information Center

Young, Anita; Bryan, Julia

2015-01-01

This study examined the factor structure of the School Counselor Leadership Survey (SCLS). Survey development was a threefold process that resulted in a 39-item survey of 801 school counselors and school counselor supervisors. The exploratory factor analysis indicated a five-factor structure that revealed five key dimensions of school counselor…

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.…

A Primer on Bootstrap Factor Analysis as Applied to Health Studies Research

ERIC Educational Resources Information Center

Lu, Wenhua; Miao, Jingang; McKyer, E. Lisako J.

2014-01-01

Objectives: To demonstrate how the bootstrap method could be conducted in exploratory factor analysis (EFA) with a syntax written in SPSS. Methods: The data obtained from the Texas Childhood Obesity Prevention Policy Evaluation project (T-COPPE project) were used for illustration. A 5-step procedure to conduct bootstrap factor analysis (BFA) was…

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.

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

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

with high blood lipids incurred significant differences in cost of oral medication. This study identified the relationship between cost and risk factors of dialysis procedures for ESRD patients based on average variable costs for each dialysis treatment. The results show that certain risk factors (e.g. aged 75 and older, hypertension, bile-duct disease, cancer and high blood lipids) are associated with higher cost. The results from this study could enable health policy makers and the National Health Insurance Bureau to design a fairer and more convincible reimbursement system for dialysis procedures. This study also provides a better understanding of what risk factors play more influential roles in affecting ESRD patients to receive haemodialysis treatment. It will help policy makers and health-care providers in better control or even prevent the disease and manage the distribution of the treatment. In addition, with the results from the analysis of cost information, we can tell which risk factors have more impacts on the dialysis cost. It will further help us control the cost for those high-risk dialysis patients more efficiently.

In-situ AFM measurement of single fibrin fiber stiffness before and after addition of Factor XIII

NASA Astrophysics Data System (ADS)

Houser, John; O'Brien, E. Timothy; Lord, Susan T.; Superfine, Richard; Falvo, Michael R.

2008-10-01

Fibrin fibers are the main structural component of blood clots. Ligation of fibrin by native Factor XIII (FXIII) serves to fine tune the mechanical properties of the clot. Mechanical alteration is important because a clot must be stiff enough to resist forces from blood flow but compliant enough to prevent embolism (fracture). Cone and Plate measurements of fibrin gels, which represent the vast majority of mechanical measurements on fibrin, show that FXIII increases clot stiffness. More recently, measurements on individual fibrin fibers show that they exhibit remarkable extensibility, breaking at strains up to 300%. As of yet, the origin of this extensibility is not fully understood. The different responses of ligated and unligated fibrin fibers can give us clues as to it's mechanism of extension. We use a combined fluorescence/atomic force microscope to stretch individual, isolated, fibrin fibers and then compare force extension curves of the same fiber before and after addition of FXIII. We found up to a 3.5-fold increase in fiber stiffness after addition of FXIII. We also show stiffening of individual fibrin fibers after crosslinking by gluteraldehyde.

Clinical efficacy analysis of Ahmed glaucoma valve implantation in neovascular glaucoma and influencing factors

PubMed Central

He, Ye; Tian, Ying; Song, Weitao; Su, Ting; Jiang, Haibo; Xia, Xiaobo

2017-01-01

Abstract This study aimed to evaluate the efficacy of Ahmed glaucoma valve (AGV) implantation in treating neovascular glaucoma (NVG) and to analyze the factors influencing the surgical success rate. This is a retrospective review of 40 eyes of 40 NVG patients who underwent AGV implantation at Xiangya Hospital of Central South University, China, between January 2014 and December 2016. Pre- and postoperative intraocular pressure (IOP), visual acuity, surgical success rate, medications, and complications were observed. Surgical success criteria were defined as IOP ≤21 and >6 mm Hg with or without additional medications. Kaplan–Meier survival curves and Multivariate cox regression analysis were used to examine success rates and risk factors for surgical outcomes. The mean follow-up period was 8.88 ± 3.12 months (range: 3–17). IOP declined at each visit postoperatively and it was statistically significant (P < .001). An average of 3.55 ± 0.86 drugs was applied preoperatively, while an average of 0.64 ± 0.90 drugs was used postoperatively, with the difference being of statistical significance (P < .05). The complete surgical success rate of 3, 6, and 12 months after the operation was 85%, 75%, and 65%, respectively. Meanwhile, the qualified success rate of 3, 6, and 12 months after the operation was 85%, 80%, and 77.5%, respectively. The multivariate cox regression analysis showed that age (hazard ratio: 3.717, 7.246; 95% confidence interval: 1.149–12.048, 1.349–38.461; P = .028, .021) was influencing factors for complete success rate and qualified success rate among all NVG patients. Gender, previous operation history, primary disease, and preoperative IOP were found to be not significant. AGV implantation is an effective and safe surgical method to treat NVG. Age is an important factor influencing the surgical success rate. PMID:29049253

The Edinburgh Postnatal Depression Scale: Screening Tool for Postpartum Anxiety as Well? Findings from a Confirmatory Factor Analysis of the Hebrew Version.

PubMed

Bina, Rena; Harrington, Donna

2016-04-01

The Edinburgh Postnatal Depression Scale (EPDS) was originally created as a uni-dimensional scale to screen for postpartum depression (PPD); however, evidence from various studies suggests that it is a multi-dimensional scale measuring mainly anxiety in addition to depression. The factor structure of the EPDS seems to differ across various language translations, raising questions regarding its stability. This study examined the factor structure of the Hebrew version of the EPDS to assess whether it is uni- or multi-dimensional. Seven hundred and fifteen (n = 715) women were screened at 6 weeks postpartum using the Hebrew version of the EPDS. Confirmatory factor analysis (CFA) was used to test four models derived from the literature. Of the four CFA models tested, a 9-item two factor model fit the data best, with one factor representing an underlying depression construct and the other representing an underlying anxiety construct. for Practice The Hebrew version of the EPDS appears to consist of depression and anxiety sub-scales. Given the widespread PPD screening initiatives, anxiety symptoms should be addressed in addition to depressive symptoms, and a short scale, such as the EPDS, assessing both may be efficient.

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

ERIC Educational Resources Information Center

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

2015-01-01

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

Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation.

PubMed

Yang, Hongyu; Huang, Di; Wang, Yunhong; Wang, Heng; Tang, Yuanyan

2016-06-01

Face aging simulation has received rising investigations nowadays, whereas it still remains a challenge to generate convincing and natural age-progressed face images. In this paper, we present a novel approach to such an issue using hidden factor analysis joint sparse representation. In contrast to the majority of tasks in the literature that integrally handle the facial texture, the proposed aging approach separately models the person-specific facial properties that tend to be stable in a relatively long period and the age-specific clues that gradually change over time. It then transforms the age component to a target age group via sparse reconstruction, yielding aging effects, which is finally combined with the identity component to achieve the aged face. Experiments are carried out on three face aging databases, and the results achieved clearly demonstrate the effectiveness and robustness of the proposed method in rendering a face with aging effects. In addition, a series of evaluations prove its validity with respect to identity preservation and aging effect generation.

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.

Chemical factor analysis of skin cancer FTIR-FEW spectroscopic data

NASA Astrophysics Data System (ADS)

Bruch, Reinhard F.; Sukuta, Sydney

2002-03-01

Chemical Factor Analysis (CFA) algorithms were applied to transform complex Fourier transform infrared fiberoptical evanescent wave (FTIR-FEW) normal and malignant skin tissue spectra into factor spaces for analysis and classification. The factor space approach classified melanoma beyond prior pathological classifications related to specific biochemical alterations to health states in cluster diagrams allowing diagnosis with more biochemical specificity, resolving biochemical component spectra and employing health state eigenvector angular configurations as disease state sensors. This study demonstrated a wealth of new information from in vivo FTIR-FEW spectral tissue data, without extensive a priori information or clinically invasive procedures. In particular, we employed a variety of methods used in CFA to select the rank of spectroscopic data sets of normal benign and cancerous skin tissue. We used the Malinowski indicator function (IND), significance level and F-Tests to rank our data matrices. Normal skin tissue, melanoma and benign tumors were modeled by four, two and seven principal abstract factors, respectively. We also showed that the spectrum of the first eigenvalue was equivalent to the mean spectrum. The graphical depiction of angular disparities between the first abstract factors can be adopted as a new way to characterize and diagnose melanoma cancer.

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

PubMed Central

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

2011-01-01

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

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

PubMed

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

2015-01-01

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

Effect of Previous Abdominal Surgery on Laparoscopic Liver Resection: Analysis of Feasibility and Risk Factors for Conversion.

PubMed

Cipriani, Federica; Ratti, Francesca; Fiorentini, Guido; Catena, Marco; Paganelli, Michele; Aldrighetti, Luca

2018-03-28

Previous abdominal surgery has traditionally been considered an additional element of difficulty to later laparoscopic procedures. The aim of the study is to analyze the effect of previous surgery on the feasibility and safety of laparoscopic liver resection (LLR), and its role as a risk factor for conversion. After matching, 349 LLR in patients known for previous abdominal surgery (PS group) were compared with 349 LLR on patients with a virgin abdomen (NPS group). Subgroup analysis included 161 patients with previous upper abdominal surgery (UPS subgroup). Feasibility and safety were evaluated in terms of conversion rate, reasons for conversion and outcomes, and risk factors for conversion assessed via uni/multivariable analysis. Conversion rate was 9.4%, and higher for PS patients compared with NPS patients (13.7% versus 5.1%, P = .021). Difficult adhesiolysis resulted the commonest reason for conversion in PS group (5.7%). However, operative time (P = .840), blood loss (P = .270), transfusion (P = .650), morbidity rate (P = .578), hospital stay (P = .780), and R1 rate (P = .130) were comparable between PS and NPS group. Subgroup analysis confirmed higher conversion rates for UPS patients (23%) compared with both NPS (P = .015) and PS patients (P = .041). Previous surgery emerged as independent risk factor for conversion (P = .033), alongside the postero-superior location and major hepatectomy. LLR are feasible in case of previous surgery and proved to be safe and maintain the benefits of LLR carried out in standard settings. However, a history of surgery should be considered a risk factor for conversion.

[Soft tissue sarcoma of the upper extremities. Analysis of factors relevant for prognosis in 160 patients].

PubMed

Lehnhardt, M; Hirche, C; Daigeler, A; Goertz, O; Ring, A; Hirsch, T; Drücke, D; Hauser, J; Steinau, H U

2012-02-01

Soft tissue sarcomas (STS) are a rare entity with reduced prognosis due to their aggressive biology. For an optimal treatment of STS identification of independent prognostic factors is crucial in order to reduce tumor-related mortality and recurrence rates. The surgical oncological concept includes wide excisions with resection safety margins >1 cm which enables acceptable functional results and reduced rates of amputation of the lower extremities. In contrast, individual anatomy of the upper extremities, in particular of the hand, leads to an intentional reduction of resection margins in order to preserve the extremity and its function with the main intention of tumor-free resection margins. In this study, the oncological safety and outcome as well as functional results were validated by a retrospective analysis of survival rate, recurrence rate and potential prognostic factors. A total of 160 patients who had been treated for STS of the upper extremities were retrospectively included. Independent prognostic factors were analyzed (primary versus recurrent tumor, tumor size, resection status, grade of malignancy, additional therapy, localization in the upper extremity). Kaplan-Meier analyses for survival rate and local control were calculated. Further outcome measures were functional results validated by the DASH score and rate of amputation. In 130 patients (81%) wide tumor excision (R0) was performed and in 19 patients (12%) an amputation was necessary. The 5-year overall survival rate was 70% and the 5-year survival rate in primary tumors was 81% whereas in recurrences 55% relapsed locally. The 10-year overall survival rate was 45% and the 5-year recurrence rate was 18% for primary STS and 43% for recurrent STS. Variance analysis revealed primary versus recurrent tumor, tumor size, resection status and grade of malignancy as independent prognostic factors. Analysis of functional results showed a median DASH score of 37 (0-100; 0=contralateral extremity). The 5

Factoring local sequence composition in motif significance analysis.

PubMed

Ng, Patrick; Keich, Uri

2008-01-01

We recently introduced a biologically realistic and reliable significance analysis of the output of a popular class of motif finders. In this paper we further improve our significance analysis by incorporating local base composition information. Relying on realistic biological data simulation, as well as on FDR analysis applied to real data, we show that our method is significantly better than the increasingly popular practice of using the normal approximation to estimate the significance of a finder's output. Finally we turn to leveraging our reliable significance analysis to improve the actual motif finding task. Specifically, endowing a variant of the Gibbs Sampler with our improved significance analysis we demonstrate that de novo finders can perform better than has been perceived. Significantly, our new variant outperforms all the finders reviewed in a recently published comprehensive analysis of the Harbison genome-wide binding location data. Interestingly, many of these finders incorporate additional information such as nucleosome positioning and the significance of binding data.

An Empirical Analysis of Factors Affecting Honors Program Completion Rates

ERIC Educational Resources Information Center

Savage, Hallie; Raehsler, Rod D.; Fiedor, Joseph

2014-01-01

One of the most important issues in any educational environment is identifying factors that promote academic success. A plethora of research on such factors exists across most academic fields, involving a wide range of student demographics, and the definition of student success varies across the range of studies published. The analysis in this…

Factors of Spatial Visualization: An Analysis of the PSVT:R

ERIC Educational Resources Information Center

Ernst, Jeremy V.; Willams, Thomas O.; Clark, Aaron C.; Kelly, Daniel P.

2017-01-01

The Purdue Spatial Visualization Test: Visualization of Rotations (PVST:R) is among the most commonly used measurement instruments to assess spatial ability among engineering students. Previous analysis that explores the factor structure of the PSVT:R indicates a single-factor measure of the instrument. With this as a basis, this research seeks to…

Single cell qPCR reveals that additional HAND2 and microRNA-1 facilitate the early reprogramming progress of seven-factor-induced human myocytes

PubMed Central

Bektik, Emre; Dennis, Adrienne; Prasanna, Prateek; Madabhushi, Anant

2017-01-01

The direct reprogramming of cardiac fibroblasts into induced cardiomyocyte (CM)-like cells (iCMs) holds great promise in restoring heart function. We previously found that human fibroblasts could be reprogrammed toward CM-like cells by 7 reprogramming factors; however, iCM reprogramming in human fibroblasts is both more difficult and more time-intensive than that in mouse cells. In this study, we investigated if additional reprogramming factors could quantitatively and/or qualitatively improve 7-factor-mediated human iCM reprogramming by single-cell quantitative PCR. We first validated 46 pairs of TaqMan® primers/probes that had sufficient efficiency and sensitivity to detect the significant difference of gene expression between individual H9 human embryonic stem cell (ESC)-differentiated CMs (H9CMs) and human fibroblasts. The expression profile of these 46 genes revealed an improved reprogramming in 12-week iCMs compared to 4-week iCMs reprogrammed by 7 factors, indicating a prolonged stochastic phase during human iCM reprogramming. Although none of additional one reprogramming factor yielded a greater number of iCMs, our single-cell qPCR revealed that additional HAND2 or microRNA-1 could facilitate the silencing of fibroblast genes and yield a better degree of reprogramming in more reprogrammed iCMs. Noticeably, the more HAND2 expressed, the higher-level were cardiac genes activated in 7Fs+HAND2-reprogrammed iCMs. In conclusion, HAND2 and microRNA-1 could help 7 factors to facilitate the early progress of iCM-reprogramming from human fibroblasts. Our study provides valuable information to further optimize a method of direct iCM-reprogramming in human cells. PMID:28796841

Single cell qPCR reveals that additional HAND2 and microRNA-1 facilitate the early reprogramming progress of seven-factor-induced human myocytes.

PubMed

Bektik, Emre; Dennis, Adrienne; Prasanna, Prateek; Madabhushi, Anant; Fu, Ji-Dong

2017-01-01

The direct reprogramming of cardiac fibroblasts into induced cardiomyocyte (CM)-like cells (iCMs) holds great promise in restoring heart function. We previously found that human fibroblasts could be reprogrammed toward CM-like cells by 7 reprogramming factors; however, iCM reprogramming in human fibroblasts is both more difficult and more time-intensive than that in mouse cells. In this study, we investigated if additional reprogramming factors could quantitatively and/or qualitatively improve 7-factor-mediated human iCM reprogramming by single-cell quantitative PCR. We first validated 46 pairs of TaqMan® primers/probes that had sufficient efficiency and sensitivity to detect the significant difference of gene expression between individual H9 human embryonic stem cell (ESC)-differentiated CMs (H9CMs) and human fibroblasts. The expression profile of these 46 genes revealed an improved reprogramming in 12-week iCMs compared to 4-week iCMs reprogrammed by 7 factors, indicating a prolonged stochastic phase during human iCM reprogramming. Although none of additional one reprogramming factor yielded a greater number of iCMs, our single-cell qPCR revealed that additional HAND2 or microRNA-1 could facilitate the silencing of fibroblast genes and yield a better degree of reprogramming in more reprogrammed iCMs. Noticeably, the more HAND2 expressed, the higher-level were cardiac genes activated in 7Fs+HAND2-reprogrammed iCMs. In conclusion, HAND2 and microRNA-1 could help 7 factors to facilitate the early progress of iCM-reprogramming from human fibroblasts. Our study provides valuable information to further optimize a method of direct iCM-reprogramming in human cells.

Enhancing antioxidant activity of sesamol at frying temperature by addition of additives through reducing volatility

USDA-ARS?s Scientific Manuscript database

Additives were evaluated to investigate their effects on volatility of sesamol at frying temperature with the hypothesis that the interaction between an additive and sesamol would reduce sesamol volatility. Twenty-two additive:sesamol combinations were examined by thermogravimetric analysis (TGA) un...

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.

Psychometric Properties of the Persian Language Version of Yang Internet Addiction Questionnaire: An Explanatory Factor Analysis.

PubMed

Mohammadsalehi, Narges; Mohammadbeigi, Abolfazl; Jadidi, Rahmatollah; Anbari, Zohreh; Ghaderi, Ebrahim; Akbari, Mojtaba

2015-09-01

Reliability and validity are the key concepts in measurement processes. Young internet addiction test (YIAT) is regarded as a valid and reliable questionnaire in English speaking countries for diagnosis of Internet-related behavior disorders. This study aimed at validating the Persian version of YIAT in the Iranian society. A pilot and a cross-sectional study were conducted on 28 and 254 students of Qom University of Medical Sciences, respectively, in order to validate the Persian version of YIAT. Forward and backward translations were conducted to develop a Persian version of the scale. Reliability was measured by test-retest, Cronbach's alpha and interclass correlation coefficient (ICC). Face, content and construct validity were approved by the importance score index, content validity ratio (CVR), content validity index (CVI), correlation matrix and factor analysis. The SPSS software was used for data analysis. The Cronbach's alpha was 0.917 (CI 95%; 0.901 - 0.931). The average of scale-level CVI was calculated to be 0.74; the CVI index for each item was higher than 0.83 and the average of CVI index was equal to 0.89. Factor analysis extracted three factors including personal activities disorder (PAD), emotional and mood disorder (EMD) and social activities disorder (SAD), with more than 55.8% of total variances. The ICC for different factors of Persian version of Young Questionnaire including PAD, EMD and for SAD was r = 0.884; CI 95%; 0.861 - 0.904, r = 0.766; CI 95%; 0.718 - 0.808 and r = 0.745; CI 95%; 0.686 - 0.795, respectively. Our study showed that the Persian version of YIAT is good and usable on Iranian people. The reliability of the instrument was very good. Moreover, the validity of the Persian translated version of the scale was sufficient. In addition, the reliability and validity of the three extracted factors of YIAT were evaluated and were acceptable.

Psychometric Properties of the Persian Language Version of Yang Internet Addiction Questionnaire: An Explanatory Factor Analysis

PubMed Central

Mohammadsalehi, Narges; Mohammadbeigi, Abolfazl; Jadidi, Rahmatollah; Anbari, Zohreh; Ghaderi, Ebrahim; Akbari, Mojtaba

2015-01-01

Background: Reliability and validity are the key concepts in measurement processes. Young internet addiction test (YIAT) is regarded as a valid and reliable questionnaire in English speaking countries for diagnosis of Internet-related behavior disorders. Objectives: This study aimed at validating the Persian version of YIAT in the Iranian society. Patients and Methods: A pilot and a cross-sectional study were conducted on 28 and 254 students of Qom University of Medical Sciences, respectively, in order to validate the Persian version of YIAT. Forward and backward translations were conducted to develop a Persian version of the scale. Reliability was measured by test-retest, Cronbach’s alpha and interclass correlation coefficient (ICC). Face, content and construct validity were approved by the importance score index, content validity ratio (CVR), content validity index (CVI), correlation matrix and factor analysis. The SPSS software was used for data analysis. Results: The Cronbach’s alpha was 0.917 (CI 95%; 0.901 - 0.931). The average of scale-level CVI was calculated to be 0.74; the CVI index for each item was higher than 0.83 and the average of CVI index was equal to 0.89. Factor analysis extracted three factors including personal activities disorder (PAD), emotional and mood disorder (EMD) and social activities disorder (SAD), with more than 55.8% of total variances. The ICC for different factors of Persian version of Young Questionnaire including PAD, EMD and for SAD was r = 0.884; CI 95%; 0.861 - 0.904, r = 0.766; CI 95%; 0.718 - 0.808 and r = 0.745; CI 95%; 0.686 - 0.795, respectively. Conclusions: Our study showed that the Persian version of YIAT is good and usable on Iranian people. The reliability of the instrument was very good. Moreover, the validity of the Persian translated version of the scale was sufficient. In addition, the reliability and validity of the three extracted factors of YIAT were evaluated and were acceptable. PMID:26495253

Integrating products of Bessel functions with an additional exponential or rational factor

NASA Astrophysics Data System (ADS)

Van Deun, Joris; Cools, Ronald

2008-04-01

We provide two MATLAB programs to compute integrals of the form ex∏i=1kJν_i(ax)dxand 0∞xr+x∏i=1kJν_i(ax)dx with Jν_i(x) the Bessel function of the first kind and (real) order ν. The parameter m is a real number such that ∑ν+m>-1 (to assure integrability near zero), r is real and the numbers c and a are all strictly positive. The program can deliver accurate error estimates. Program summaryProgram title: BESSELINTR, BESSELINTC Catalogue identifier: AEAH_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAH_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 1601 No. of bytes in distributed program, including test data, etc.: 13 161 Distribution format: tar.gz Programming language: Matlab (version ⩾6.5), Octave (version ⩾2.1.69) Computer: All supporting Matlab or Octave Operating system: All supporting Matlab or Octave RAM: For k Bessel functions our program needs approximately ( 500+140k) double precision variables Classification: 4.11 Nature of problem: The problem consists in integrating an arbitrary product of Bessel functions with an additional rational or exponential factor over a semi-infinite interval. Difficulties arise from the irregular oscillatory behaviour and the possible slow decay of the integrand, which prevents truncation at a finite point. Solution method: The interval of integration is split into a finite and infinite part. The integral over the finite part is computed using Gauss-Legendre quadrature. The integrand on the infinite part is approximated using asymptotic expansions and this approximation is integrated exactly with the aid of the upper incomplete gamma function. In the case where a rational factor is present, this factor is first expanded in a Taylor series around infinity. Restrictions: Some (and eventually all

The risk factors for avian influenza on poultry farms: a meta-analysis.

PubMed

Wang, Youming; Li, Peng; Wu, Yangli; Sun, Xiangdong; Yu, Kangzhen; Yu, Chuanhua; Qin, Aijian

2014-11-01

Avian influenza is a severe threat both to humans and poultry, but so far, no systematic review on the identification and evaluation of the risk factors of avian influenza infection has been published. The objective of this meta-analysis is to provide evidence for decision-making and further research on AI prevention through identifying the risk factors associated with AI infection on poultry farms. The results from 15 selected studies on risk factors for AI infections on poultry farms were analyzed quantitatively by meta-analysis. Open water source (OR=2.89), infections on nearby farms (OR=4.54), other livestock (OR=1.90) and disinfection of farm (OR=0.54) have significant association with AI infection on poultry farms. The subgroup analysis results indicate that there exist different risk factors for AI infections in different types of farms. The main risk factors for AI infection in poultry farms are environmental conditions (open water source, infections on nearby farms), keeping other livestock on the same farm and no disinfection of the farm. Copyright © 2014 Elsevier B.V. All rights reserved.

Identifying Items to Assess Methodological Quality in Physical Therapy Trials: A Factor Analysis

PubMed Central

Cummings, Greta G.; Fuentes, Jorge; Saltaji, Humam; Ha, Christine; Chisholm, Annabritt; Pasichnyk, Dion; Rogers, Todd

2014-01-01

Background Numerous tools and individual items have been proposed to assess the methodological quality of randomized controlled trials (RCTs). The frequency of use of these items varies according to health area, which suggests a lack of agreement regarding their relevance to trial quality or risk of bias. Objective The objectives of this study were: (1) to identify the underlying component structure of items and (2) to determine relevant items to evaluate the quality and risk of bias of trials in physical therapy by using an exploratory factor analysis (EFA). Design A methodological research design was used, and an EFA was performed. Methods Randomized controlled trials used for this study were randomly selected from searches of the Cochrane Database of Systematic Reviews. Two reviewers used 45 items gathered from 7 different quality tools to assess the methodological quality of the RCTs. An exploratory factor analysis was conducted using the principal axis factoring (PAF) method followed by varimax rotation. Results Principal axis factoring identified 34 items loaded on 9 common factors: (1) selection bias; (2) performance and detection bias; (3) eligibility, intervention details, and description of outcome measures; (4) psychometric properties of the main outcome; (5) contamination and adherence to treatment; (6) attrition bias; (7) data analysis; (8) sample size; and (9) control and placebo adequacy. Limitation Because of the exploratory nature of the results, a confirmatory factor analysis is needed to validate this model. Conclusions To the authors' knowledge, this is the first factor analysis to explore the underlying component items used to evaluate the methodological quality or risk of bias of RCTs in physical therapy. The items and factors represent a starting point for evaluating the methodological quality and risk of bias in physical therapy trials. Empirical evidence of the association among these items with treatment effects and a confirmatory factor

[Introduction to Exploratory Factor Analysis (EFA)].

PubMed

Martínez, Carolina Méndez; Sepúlveda, Martín Alonso Rondón

2012-03-01

Exploratory Factor Analysis (EFA) has become one of the most frequently used statistical techniques, especially in the medical and social sciences. Given its popularity, it is essential to understand the basic concepts necessary for its proper application and to take into consideration the main strengths and weaknesses of this technique. To present in a clear and concise manner the main applications of this technique, to determine the basic requirements for its use providing a description step by step of its methodology, and to establish the elements that must be taken into account during its preparation in order to not incur in erroneous results and interpretations. Narrative review. This review identifies the basic concepts and briefly describes the objectives, design, assumptions, and methodology to achieve factor derivation, global adjustment evaluation, and adequate interpretation of results. Copyright © 2012 Asociación Colombiana de Psiquiatría. Publicado por Elsevier España. All rights reserved.

Investigation on Constrained Matrix Factorization for Hyperspectral Image Analysis

DTIC Science & Technology

2005-07-25

analysis. Keywords: matrix factorization; nonnegative matrix factorization; linear mixture model ; unsupervised linear unmixing; hyperspectral imagery...spatial resolution permits different materials present in the area covered by a single pixel. The linear mixture model says that a pixel reflectance in...in r. In the linear mixture model , r is considered as the linear mixture of m1, m2, …, mP as nMαr += (1) where n is included to account for

Dyadic confirmatory factor analysis of the inflammatory bowel disease family responsibility questionnaire.

PubMed

Greenley, Rachel Neff; Reed-Knight, Bonney; Blount, Ronald L; Wilson, Helen W

2013-09-01

Evaluate the factor structure of youth and maternal involvement ratings on the Inflammatory Bowel Disease Family Responsibility Questionnaire, a measure of family allocation of condition management responsibilities in pediatric inflammatory bowel disease. Participants included 251 youth aged 11-18 years with inflammatory bowel disease and their mothers. Item-level descriptive analyses, subscale internal consistency estimates, and confirmatory factor analyses of youth and maternal involvement were conducted using a dyadic data-analytic approach. Results supported the validity of 4 conceptually derived subscales including general health maintenance, social aspects, condition management tasks, and nutrition domains. Additionally, results indicated adequate support for the factor structure of a 21-item youth involvement measure and strong support for a 16-item maternal involvement measure. Additional empirical support for the validity of the Inflammatory Bowel Disease Family Responsibility Questionnaire was provided. Future research to replicate current findings and to examine the measure's clinical utility is warranted.

Precessing rotating flows with additional shear: stability analysis.

PubMed

Salhi, A; Cambon, C

2009-03-01

We consider unbounded precessing rotating flows in which vertical or horizontal shear is induced by the interaction between the solid-body rotation (with angular velocity Omega(0)) and the additional "precessing" Coriolis force (with angular velocity -epsilonOmega(0)), normal to it. A "weak" shear flow, with rate 2epsilon of the same order of the Poincaré "small" ratio epsilon , is needed for balancing the gyroscopic torque, so that the whole flow satisfies Euler's equations in the precessing frame (the so-called admissibility conditions). The base flow case with vertical shear (its cross-gradient direction is aligned with the main angular velocity) corresponds to Mahalov's [Phys. Fluids A 5, 891 (1993)] precessing infinite cylinder base flow (ignoring boundary conditions), while the base flow case with horizontal shear (its cross-gradient direction is normal to both main and precessing angular velocities) corresponds to the unbounded precessing rotating shear flow considered by Kerswell [Geophys. Astrophys. Fluid Dyn. 72, 107 (1993)]. We show that both these base flows satisfy the admissibility conditions and can support disturbances in terms of advected Fourier modes. Because the admissibility conditions cannot select one case with respect to the other, a more physical derivation is sought: Both flows are deduced from Poincaré's [Bull. Astron. 27, 321 (1910)] basic state of a precessing spheroidal container, in the limit of small epsilon . A Rapid distortion theory (RDT) type of stability analysis is then performed for the previously mentioned disturbances, for both base flows. The stability analysis of the Kerswell base flow, using Floquet's theory, is recovered, and its counterpart for the Mahalov base flow is presented. Typical growth rates are found to be the same for both flows at very small epsilon , but significant differences are obtained regarding growth rates and widths of instability bands, if larger epsilon values, up to 0.2, are considered. Finally

Factors Affecting Arsenic Methylation in Arsenic-Exposed Humans: A Systematic Review and Meta-Analysis

PubMed Central

Shen, Hui; Niu, Qiang; Xu, Mengchuan; Rui, Dongsheng; Xu, Shangzhi; Feng, Gangling; Ding, Yusong; Li, Shugang; Jing, Mingxia

2016-01-01

Chronic arsenic exposure is a critical public health issue in many countries. The metabolism of arsenic in vivo is complicated because it can be influenced by many factors. In the present meta-analysis, two researchers independently searched electronic databases, including the Cochrane Library, PubMed, Springer, Embase, and China National Knowledge Infrastructure, to analyze factors influencing arsenic methylation. The concentrations of the following arsenic metabolites increase (p< 0.000001) following arsenic exposure: inorganic arsenic (iAs), monomethyl arsenic (MMA), dimethyl arsenic (DMA), and total arsenic. Additionally, the percentages of iAs (standard mean difference (SMD): 1.00; 95% confidence interval (CI): 0.60–1.40; p< 0.00001) and MMA (SMD: 0.49; 95% CI: 0.21–0.77; p = 0.0006) also increase, while the percentage of DMA (SMD: −0.57; 95% CI: −0.80–−0.31; p< 0.0001), primary methylation index (SMD: −0.57; 95% CI: −0.94–−0.20; p = 0.002), and secondary methylation index (SMD: −0.27; 95% CI: −0.46–−0.90; p = 0.004) decrease. Smoking, drinking, and older age can reduce arsenic methylation, and arsenic methylation is more efficient in women than in men. The results of this analysis may provide information regarding the role of arsenic oxidative methylation in the arsenic poisoning process. PMID:26861378

Children's patterns of reasoning about reading and addition concepts.

PubMed

Farrington-Flint, Lee; Canobi, Katherine H; Wood, Clare; Faulkner, Dorothy

2010-06-01

Children's reasoning was examined within two educational contexts (word reading and addition) so as to understand the factors that contribute to relational reasoning in the two domains. Sixty-seven 5- to 7-year-olds were given a series of related words to read or single-digit addition items to solve (interspersed with unrelated items). The frequency, accuracy, and response times of children's self-reports on the conceptually related items provided a measure of relational reasoning, while performance on the unrelated addition and reading items provided a measure of procedural skill. The results indicated that the children's ability to use conceptual relations to solve both reading and addition problems enhanced speed and accuracy levels, increased with age, and was related to procedural skill. However, regression analyses revealed that domain-specific competencies can best explain the use of conceptual relations in both reading and addition. Moreover, a cluster analysis revealed that children differ according to the academic domain in which they first apply conceptual relations and these differences are related to individual variation in their procedural skills within these particular domains. These results highlight the developmental significance of relational reasoning in the context of reading and addition and underscore the importance of concept-procedure links in explaining children's literacy and arithmetical development.

Meta-analysis of the Brief Psychiatric Rating Scale Factor Structure

ERIC Educational Resources Information Center

Shafer, Alan

2005-01-01

A meta-analysis (N=17,620; k=26) of factor analyses of the Brief Psychiatric Rating Scale (BPRS) was conducted. Analysis of the 12 items from Overall et al.'s (J. E. Overall, L. E. Hollister, & P. Pichot, 1974) 4 subscales found support for his 4 subscales. Analysis of all 18 BPRS items found 4 components similar to those of Overall et al. In a…

Detecting Outliers in Factor Analysis Using the Forward Search Algorithm

ERIC Educational Resources Information Center

Mavridis, Dimitris; Moustaki, Irini

2008-01-01

In this article we extend and implement the forward search algorithm for identifying atypical subjects/observations in factor analysis models. The forward search has been mainly developed for detecting aberrant observations in regression models (Atkinson, 1994) and in multivariate methods such as cluster and discriminant analysis (Atkinson, Riani,…

Quantitative Analysis of Guanine Nucleotide Exchange Factors (GEFs) as Enzymes

PubMed Central

Randazzo, Paul A; Jian, Xiaoying; Chen, Pei-Wen; Zhai, Peng; Soubias, Olivier; Northup, John K

2014-01-01

The proteins that possess guanine nucleotide exchange factor (GEF) activity, which include about ~800 G protein coupled receptors (GPCRs),1 15 Arf GEFs,2 81 Rho GEFs,3 8 Ras GEFs,4 and others for other families of GTPases,5 catalyze the exchange of GTP for GDP on all regulatory guanine nucleotide binding proteins. Despite their importance as catalysts, relatively few exchange factors (we are aware of only eight for ras superfamily members) have been rigorously characterized kinetically.5–13 In some cases, kinetic analysis has been simplistic leading to erroneous conclusions about mechanism (as discussed in a recent review14). In this paper, we compare two approaches for determining the kinetic properties of exchange factors: (i) examining individual equilibria, and; (ii) analyzing the exchange factors as enzymes. Each approach, when thoughtfully used,14,15 provides important mechanistic information about the exchange factors. The analysis as enzymes is described in further detail. With the focus on the production of the biologically relevant guanine nucleotide binding protein complexed with GTP (G•GTP), we believe it is conceptually simpler to connect the kinetic properties to cellular effects. Further, the experiments are often more tractable than those used to analyze the equilibrium system and, therefore, more widely accessible to scientists interested in the function of exchange factors. PMID:25332840

Evaluation of a Human Factors Analysis and Classification System as used by simulated mishap boards.

PubMed

O'Connor, Paul; Walker, Peter

2011-01-01

The reliability of the Department of Defense Human Factors Analysis and Classification System (DOD-HFACS) has been examined when used by individuals working alone to classify the causes of summary, or partial, information about a mishap. However, following an actual mishap a team of investigators would work together to gather and analyze a large amount of information before identifying the causal factors and coding them with DOD-HFACS. There were 204 military Aviation Safety Officer students who were divided into 30 groups. Each group was provided with evidence collected from one of two military aviation mishaps. DOD-HFACS was used to classify the mishap causal factors. Averaged across the two mishaps, acceptable levels of reliability were only achieved for 56.9% of nanocodes. There were high levels of agreement regarding the factors that did not contribute to the incident (a mean agreement of 50% or greater between groups for 91.0% of unselected nanocodes); the level of agreement on the factors that did cause the incident as classified using DOD-HFACS were low (a mean agreement of 50% or greater between the groups for 14.6% of selected nanocodes). Despite using teams to carry out the classification, the findings from this study are consistent with other studies of DOD-HFACS reliability with individuals. It is suggested that in addition to simplifying DOD-HFACS itself, consideration should be given to involving a human factors/organizational psychologist in mishap investigations to ensure the human factors issues are identified and classified in a consistent and reliable manner.

Students' motivation to study dentistry in Malaysia: an analysis using confirmatory factor analysis.

PubMed

Musa, Muhd Firdaus Che; Bernabé, Eduardo; Gallagher, Jennifer E

2015-06-12

Malaysia has experienced a significant expansion of dental schools over the past decade. Research into students' motivation may inform recruitment and retention of the future dental workforce. The objectives of this study were to explore students' motivation to study dentistry and whether that motivation varied by students' and school characteristics. All 530 final-year students in 11 dental schools (6 public and 5 private) in Malaysia were invited to participate at the end of 2013. The self-administered questionnaire, developed at King's College London, collected information on students' motivation to study dentistry and demographic background. Responses on students' motivation were collected using five-point ordinal scales. Confirmatory factor analysis (CFA) was used to evaluate the underlying structure of students' motivation to study dentistry. Multivariate analysis of variance (MANOVA) was used to compare factor scores for overall motivation and sub-domains by students' and school characteristics. Three hundred and fifty-six final-year students in eight schools (all public and two private) participated in the survey, representing an 83% response rate for these schools and 67% of all final-year students nationally. The majority of participants were 24 years old (47%), female (70%), Malay (56%) and from middle-income families (41%) and public schools (78%). CFA supported a model with five first-order factors (professional job, healthcare and people, academic, careers advising and family and friends) which were linked to a single second-order factor representing overall students' motivation. Academic factors and healthcare and people had the highest standardized factor loadings (0.90 and 0.71, respectively), suggesting they were the main motivation to study dentistry. MANOVA showed that students from private schools had higher scores for healthcare and people than those in public schools whereas Malay students had lower scores for family and friends than those

[Determination of the Plant Origin of Licorice Oil Extract, a Natural Food Additive, by Principal Component Analysis Based on Chemical Components].

PubMed

Tada, Atsuko; Ishizuki, Kyoko; Sugimoto, Naoki; Yoshimatsu, Kayo; Kawahara, Nobuo; Suematsu, Takako; Arifuku, Kazunori; Fukai, Toshio; Tamura, Yukiyoshi; Ohtsuki, Takashi; Tahara, Maiko; Yamazaki, Takeshi; Akiyama, Hiroshi

2015-01-01

"Licorice oil extract" (LOE) (antioxidant agent) is described in the notice of Japanese food additive regulations as a material obtained from the roots and/or rhizomes of Glycyrrhiza uralensis, G. inflata or G. glabra. In this study, we aimed to identify the original Glycyrrhiza species of eight food additive products using LC/MS. Glabridin, a characteristic compound in G. glabra, was specifically detected in seven products, and licochalcone A, a characteristic compound in G. inflata, was detected in one product. In addition, Principal Component Analysis (PCA) (a kind of multivariate analysis) using the data of LC/MS or (1)H-NMR analysis was performed. The data of thirty-one samples, including LOE products used as food additives, ethanol extracts of various Glycyrrhiza species and commercially available Glycyrrhiza species-derived products were assessed. Based on the PCA results, the majority of LOE products was confirmed to be derived from G. glabra. This study suggests that PCA using (1)H-NMR analysis data is a simple and useful method to identify the plant species of origin of natural food additive products.

An Analysis of Selected Factors Influencing Enrollment Patterns.

ERIC Educational Resources Information Center

Heck, James

This report presents an analysis of factors influencing enrollment patterns at Lake City Community College (LCCC; Florida) and recommends ways to increase enrollments at the college. Section I reviews the methods of collecting data for the report, which included interviews with key college personnel, an examination of social indicators such as…

Dynamic Factor Analysis Models with Time-Varying Parameters

ERIC Educational Resources Information Center

Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian

2011-01-01

Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…

Understanding Child Stunting in India: A Comprehensive Analysis of Socio-Economic, Nutritional and Environmental Determinants Using Additive Quantile Regression

PubMed Central

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A.

2013-01-01

Background Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. Objective We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Design Using cross-sectional data for children aged 0–24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. Results At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Conclusions Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role. PMID:24223839

Understanding child stunting in India: a comprehensive analysis of socio-economic, nutritional and environmental determinants using additive quantile regression.

PubMed

Fenske, Nora; Burns, Jacob; Hothorn, Torsten; Rehfuess, Eva A

2013-01-01

Most attempts to address undernutrition, responsible for one third of global child deaths, have fallen behind expectations. This suggests that the assumptions underlying current modelling and intervention practices should be revisited. We undertook a comprehensive analysis of the determinants of child stunting in India, and explored whether the established focus on linear effects of single risks is appropriate. Using cross-sectional data for children aged 0-24 months from the Indian National Family Health Survey for 2005/2006, we populated an evidence-based diagram of immediate, intermediate and underlying determinants of stunting. We modelled linear, non-linear, spatial and age-varying effects of these determinants using additive quantile regression for four quantiles of the Z-score of standardized height-for-age and logistic regression for stunting and severe stunting. At least one variable within each of eleven groups of determinants was significantly associated with height-for-age in the 35% Z-score quantile regression. The non-modifiable risk factors child age and sex, and the protective factors household wealth, maternal education and BMI showed the largest effects. Being a twin or multiple birth was associated with dramatically decreased height-for-age. Maternal age, maternal BMI, birth order and number of antenatal visits influenced child stunting in non-linear ways. Findings across the four quantile and two logistic regression models were largely comparable. Our analysis confirms the multifactorial nature of child stunting. It emphasizes the need to pursue a systems-based approach and to consider non-linear effects, and suggests that differential effects across the height-for-age distribution do not play a major role.

Factors which Limit the Value of Additional Redundancy in Human Rated Launch Vehicle Systems

NASA Technical Reports Server (NTRS)

Anderson, Joel M.; Stott, James E.; Ring, Robert W.; Hatfield, Spencer; Kaltz, Gregory M.

2008-01-01

The National Aeronautics and Space Administration (NASA) has embarked on an ambitious program to return humans to the moon and beyond. As NASA moves forward in the development and design of new launch vehicles for future space exploration, it must fully consider the implications that rule-based requirements of redundancy or fault tolerance have on system reliability/risk. These considerations include common cause failure, increased system complexity, combined serial and parallel configurations, and the impact of design features implemented to control premature activation. These factors and others must be considered in trade studies to support design decisions that balance safety, reliability, performance and system complexity to achieve a relatively simple, operable system that provides the safest and most reliable system within the specified performance requirements. This paper describes conditions under which additional functional redundancy can impede improved system reliability. Examples from current NASA programs including the Ares I Upper Stage will be shown.

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

Understanding influential factors on implementing green supply chain management practices: An interpretive structural modelling analysis.

PubMed

Agi, Maher A N; Nishant, Rohit

2017-03-01

In this study, we establish a set of 19 influential factors on the implementation of Green Supply Chain Management (GSCM) practices and analyse the interaction between these factors and their effect on the implementation of GSCM practices using the Interpretive Structural Modelling (ISM) method and the "Matrice d'Impacts Croisés Multiplication Appliquée à un Classement" (MICMAC) analysis on data compiled from interviews with supply chain (SC) executives based in the Gulf countries (Middle East region). The study reveals a strong influence and driving power of the nature of the relationships between SC partners on the implementation of GSCM practices. We especially found that dependence, trust, and durability of the relationship with SC partners have a very high influence. In addition, the size of the company, the top management commitment, the implementation of quality management and the employees training and education exert a critical influence on the implementation of GSCM practices. Contextual elements such as the industry sector and region and their effect on the prominence of specific factors are also highlighted through our study. Finally, implications for research and practice are discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

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…

Human Factors Virtual Analysis Techniques for NASA's Space Launch System Ground Support using MSFC's Virtual Environments Lab (VEL)

NASA Technical Reports Server (NTRS)

Searcy, Brittani

2017-01-01

Using virtual environments to assess complex large scale human tasks provides timely and cost effective results to evaluate designs and to reduce operational risks during assembly and integration of the Space Launch System (SLS). NASA's Marshall Space Flight Center (MSFC) uses a suite of tools to conduct integrated virtual analysis during the design phase of the SLS Program. Siemens Jack is a simulation tool that allows engineers to analyze human interaction with CAD designs by placing a digital human model into the environment to test different scenarios and assess the design's compliance to human factors requirements. Engineers at MSFC are using Jack in conjunction with motion capture and virtual reality systems in MSFC's Virtual Environments Lab (VEL). The VEL provides additional capability beyond standalone Jack to record and analyze a person performing a planned task to assemble the SLS at Kennedy Space Center (KSC). The VEL integrates Vicon Blade motion capture system, Siemens Jack, Oculus Rift, and other virtual tools to perform human factors assessments. By using motion capture and virtual reality, a more accurate breakdown and understanding of how an operator will perform a task can be gained. By virtual analysis, engineers are able to determine if a specific task is capable of being safely performed by both a 5% (approx. 5ft) female and a 95% (approx. 6'1) male. In addition, the analysis will help identify any tools or other accommodations that may to help complete the task. These assessments are critical for the safety of ground support engineers and keeping launch operations on schedule. Motion capture allows engineers to save and examine human movements on a frame by frame basis, while virtual reality gives the actor (person performing a task in the VEL) an immersive view of the task environment. This presentation will discuss the need of human factors for SLS and the benefits of analyzing tasks in NASA MSFC's VEL.

The quantitative surface analysis of an antioxidant additive in a lubricant oil matrix by desorption electrospray ionization mass spectrometry

PubMed Central

Da Costa, Caitlyn; Reynolds, James C; Whitmarsh, Samuel; Lynch, Tom; Creaser, Colin S

2013-01-01

RATIONALE Chemical additives are incorporated into commercial lubricant oils to modify the physical and chemical properties of the lubricant. The quantitative analysis of additives in oil-based lubricants deposited on a surface without extraction of the sample from the surface presents a challenge. The potential of desorption electrospray ionization mass spectrometry (DESI-MS) for the quantitative surface analysis of an oil additive in a complex oil lubricant matrix without sample extraction has been evaluated. METHODS The quantitative surface analysis of the antioxidant additive octyl (4-hydroxy-3,5-di-tert-butylphenyl)propionate in an oil lubricant matrix was carried out by DESI-MS in the presence of 2-(pentyloxy)ethyl 3-(3,5-di-tert-butyl-4-hydroxyphenyl)propionate as an internal standard. A quadrupole/time-of-flight mass spectrometer fitted with an in-house modified ion source enabling non-proximal DESI-MS was used for the analyses. RESULTS An eight-point calibration curve ranging from 1 to 80 µg/spot of octyl (4-hydroxy-3,5-di-tert-butylphenyl)propionate in an oil lubricant matrix and in the presence of the internal standard was used to determine the quantitative response of the DESI-MS method. The sensitivity and repeatability of the technique were assessed by conducting replicate analyses at each concentration. The limit of detection was determined to be 11 ng/mm2 additive on spot with relative standard deviations in the range 3–14%. CONCLUSIONS The application of DESI-MS to the direct, quantitative surface analysis of a commercial lubricant additive in a native oil lubricant matrix is demonstrated. © 2013 The Authors. Rapid Communications in Mass Spectrometry published by John Wiley & Sons, Ltd. PMID:24097398

An Analysis of Factors that Influence Enlistment Decisions in the U.S. Army

DTIC Science & Technology

1998-03-01

NAVAL POSTGRADUATE SCHOOL Monterey, California CM THESIS AN ANALYSIS OF FACTORS THAT INFLUENCE ENLISTMENT DECISIONS IN THE U.S. ARMY by Young...TITLE AND SUBTITLE : AN ANALYSIS OF FACTORS THAT INFLUENCE ENLISTMENT DECISIONS IN THE U.S. ARMY 6. AUTHOR(S) Oh, Young Yeol 7...200 words) The purpose of this thesis is to analyze factors that influence decisions to enlist in the U.S. Army. This thesis uses 1997 New Recruit

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

PubMed Central

van der Eijk, Cees; Rose, Jonathan

2015-01-01

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

Teacher's Corner: Examining Identification Issues in Factor Analysis

ERIC Educational Resources Information Center

Hayashi, Kentaro; Marcoulides, George A.

2006-01-01

One hundred years have passed since the birth of factor analysis, during which time there have been some major developments and extensions to the methodology. Unfortunately, one issue where the widespread accumulation of knowledge has been rather slow concerns identification. This article provides a didactic discussion of the topic in an attempt…

Modular Open-Source Software for Item Factor Analysis

ERIC Educational Resources Information Center

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

2015-01-01

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

Catchment process affecting drinking water quality, including the significance of rainfall events, using factor analysis and event mean concentrations.

PubMed

Cinque, Kathy; Jayasuriya, Niranjali

2010-12-01

To ensure the protection of drinking water an understanding of the catchment processes which can affect water quality is important as it enables targeted catchment management actions to be implemented. In this study factor analysis (FA) and comparing event mean concentrations (EMCs) with baseline values were techniques used to asses the relationships between water quality parameters and linking those parameters to processes within an agricultural drinking water catchment. FA found that 55% of the variance in the water quality data could be explained by the first factor, which was dominated by parameters usually associated with erosion. Inclusion of pathogenic indicators in an additional FA showed that Enterococcus and Clostridium perfringens (C. perfringens) were also related to the erosion factor. Analysis of the EMCs found that most parameters were significantly higher during periods of rainfall runoff. This study shows that the most dominant processes in an agricultural catchment are surface runoff and erosion. It also shows that it is these processes which mobilise pathogenic indicators and are therefore most likely to influence the transport of pathogens. Catchment management efforts need to focus on reducing the effect of these processes on water quality.

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.

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

An Evaluation of the Effects of Variable Sampling on Component, Image, and Factor Analysis.

ERIC Educational Resources Information Center

Velicer, Wayne F.; Fava, Joseph L.

1987-01-01

Principal component analysis, image component analysis, and maximum likelihood factor analysis were compared to assess the effects of variable sampling. Results with respect to degree of saturation and average number of variables per factor were clear and dramatic. Differential effects on boundary cases and nonconvergence problems were also found.…

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

PubMed

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

2014-02-01

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

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.

Exploring factors that influence work analysis data: A meta-analysis of design choices, purposes, and organizational context.

PubMed

DuVernet, Amy M; Dierdorff, Erich C; Wilson, Mark A

2015-09-01

Work analysis is fundamental to designing effective human resource systems. The current investigation extends previous research by identifying the differential effects of common design decisions, purposes, and organizational contexts on the data generated by work analyses. The effects of 19 distinct factors that span choices of descriptor, collection method, rating scale, and data source, as well as project purpose and organizational features, are explored. Meta-analytic results cumulated from 205 articles indicate that many of these variables hold significant consequences for work analysis data. Factors pertaining to descriptor choice, collection method, rating scale, and the purpose for conducting the work analysis each showed strong associations with work analysis data. The source of the work analysis information and organizational context in which it was conducted displayed fewer relationships. Findings can be used to inform choices work analysts make about methodology and postcollection evaluations of work analysis information. (c) 2015 APA, all rights reserved).

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

PubMed Central

Farrokhi, Farahman

2011-01-01

Objective The aim of this study is to explore the confirmatory factor analysis results of the Persian adaptation of Abbreviated Math Anxiety Scale (AMAS), proposed by Hopko, Mahadevan, Bare & Hunt. Method The validity and reliability assessments of the scale were performed on 298 college students chosen randomly from Tabriz University in Iran. The confirmatory factor analysis (CFA) was carried out to determine the factor structures of the Persian version of AMAS. Results As expected, the two-factor solution provided a better fit to the data than a single factor. Moreover, multi-group analyses showed that this two-factor structure was invariant across sex. Hence, AMAS provides an equally valid measure for use among college students. Conclusions Brief AMAS demonstrates adequate reliability and validity. The AMAS scores can be used to compare symptoms of math anxiety between male and female students. The study both expands and adds support to the existing body of math anxiety literature. PMID:22952521

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

PubMed

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

2011-01-01

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

Comprehensive Behavioral Analysis of Activating Transcription Factor 5-Deficient Mice

PubMed Central

Umemura, Mariko; Ogura, Tae; Matsuzaki, Ayako; Nakano, Haruo; Takao, Keizo; Miyakawa, Tsuyoshi; Takahashi, Yuji

2017-01-01

Activating transcription factor 5 (ATF5) is a member of the CREB/ATF family of basic leucine zipper transcription factors. We previously reported that ATF5-deficient (ATF5-/-) mice demonstrated abnormal olfactory bulb development due to impaired interneuron supply. Furthermore, ATF5-/- mice were less aggressive than ATF5+/+ mice. Although ATF5 is widely expressed in the brain, and involved in the regulation of proliferation and development of neurons, the physiological role of ATF5 in the higher brain remains unknown. Our objective was to investigate the physiological role of ATF5 in the higher brain. We performed a comprehensive behavioral analysis using ATF5-/- mice and wild type littermates. ATF5-/- mice exhibited abnormal locomotor activity in the open field test. They also exhibited abnormal anxiety-like behavior in the light/dark transition test and open field test. Furthermore, ATF5-/- mice displayed reduced social interaction in the Crawley’s social interaction test and increased pain sensitivity in the hot plate test compared with wild type. Finally, behavioral flexibility was reduced in the T-maze test in ATF5-/- mice compared with wild type. In addition, we demonstrated that ATF5-/- mice display disturbances of monoamine neurotransmitter levels in several brain regions. These results indicate that ATF5 deficiency elicits abnormal behaviors and the disturbance of monoamine neurotransmitter levels in the brain. The behavioral abnormalities of ATF5-/- mice may be due to the disturbance of monoamine levels. Taken together, these findings suggest that ATF5-/- mice may be a unique animal model of some psychiatric disorders. PMID:28744205

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

ERIC Educational Resources Information Center

Ritter, Nicola L.

2012-01-01

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

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

Landslides geotechnical analysis. Qualitative assessment by valuation factors

NASA Astrophysics Data System (ADS)

Cuanalo Oscar, Sc D.; Oliva Aldo, Sc D.; Polanco Gabriel, M. E.

2012-04-01

In general, a landslide can cause a disaster when it is combined a number of factors such as an extreme event related to a geological phenomenon, vulnerable elements exposed in a specific geographic area, and the probability of loss and damage evaluated in terms of lives and economic assets, in a certain period of time. This paper presents the qualitative evaluation of slope stability through of Valuation Factors, obtained from the characterization of the determinants and triggers factors that influence the instability; for the first the morphology and topography, geology, soil mechanics, hydrogeology and vegetation to the second, the rain, earthquakes, erosion and scour, human activity, and ultimately dependent factors of the stability analysis, and its influence ranges which greatly facilitate the selection of construction processes best suited to improve the behavior of a slope or hillside. The Valuation Factors are a set of parameters for assessing the influence of conditioning and triggering factors that influence the stability of slopes and hillsides. The characteristics of each factor must be properly categorized to involve its effect on behavior; a way to do this is by assigning a weighted value range indicating its effect on the stability of a slope. It is proposed to use Valuation Factors with weighted values between 0 and 1 (arbitrarily selected but common sense and logic), the first corresponds to no or minimal effect on stability (no effect or very little influence) and the second, the greatest impact on it (has a significant influence). The meddle effects are evaluated with intermediate values.

Risk factors and prediction analysis of cutaneous leishmaniasis due to Leishmania tropica in Southwestern Morocco.

PubMed

El Alem, Mohamed Mahmoud Mohamed; Hakkour, Maryam; Hmamouch, Asmae; Halhali, Meryem; Delouane, Bouchra; Habbari, Khalid; Fellah, Hajiba; Sadak, Abderrahim; Sebti, Faiza

2018-07-01

Cutaneous leishmaniasis is currently a serious public health problem in northern Africa, especially in Morocco. The causative parasite is transmitted to a human host through the bite of infected female sandflies of the genus Phlebotomus. The objective of the present study is to characterize the causative organisms and to predict the risk of cutaneous leishmaniasis (CL) cases in six provinces in southwestern Morocco, based on the spatial distribution of cases in relation to environmental factors and other risk factors such as socio-economic status and demographics. A molecular study was carried out using ITS1 PCR-RFLP method of the ribosomal DNA of Leishmania. An epidemiological study on CL cases was reported between 2000 and 2016 in this current investigation in six provinces in southwestern Morocco. Statistical analysis was performed using a linear regression model to identify the impact as well as the interaction between all predictor variables on the distribution of CL in the studied provinces. The forecast Holt-Winters (HW) method was used to describe the trend and seasonality of CL cases. The ITS1-PCR- RFLP analysis revealed the presence of Leishmania tropica in all studied provinces. The spatial distribution of CL cases documented in all studied provinces during the sixteen years showed a heterogeneous pattern and fluctuation trend with an average prevalence of 9.92 per 100,000 inhabitants. In addition, the forecast HW model predicts continued variability of trend and seasonality of CL cases in the upcoming years. This study confirmed the importance of socioeconomic factors, in particular poverty and the vulnerability rate, on distribution and emergence of CL. This study revealed a relationship between increasing risk of CL occurrence due to Leishmania tropica, as well as the distribution and emergence thereof, and socioeconomic factors in the investigated area. Copyright © 2018 Elsevier B.V. All rights reserved.

The manifestation of depression in the context of urban poverty: a factor analysis of the Children's Depression Inventory in low-income urban youth.

PubMed

Taylor, Jeremy J; Grant, Kathryn E; Amrhein, Kelly; Carter, Jocelyn Smith; Farahmand, Farahnaz; Harrison, Aubrey; Thomas, Kina J; Carleton, Russell A; Lugo-Hernandez, Eduardo; Katz, Brian N

2014-12-01

The current study used confirmatory factor analysis (CFA) to compare the fit of 2 factor structures for the Children's Depression Inventory (CDI) in an urban community sample of low-income youth. Results suggest that the 6-factor model developed by Craighead and colleagues (1998) was a strong fit to the pattern of symptoms reported by low-income urban youth and was a superior fit with these data than the original 5-factor model of the CDI (Kovacs, 1992). Additionally, results indicated that all 6 factors from the Craighead model contributed to the measurement of depression, including School Problems and Externalizing Problems especially for older adolescents. This pattern of findings may reflect distinct contextual influences of urban poverty on the manifestation and measurement of depression in youth. (c) 2014 APA, all rights reserved.

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

ERIC Educational Resources Information Center

Mittag, Kathleen Cage

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

Reporting Practices in Confirmatory Factor Analysis: An Overview and Some Recommendations

ERIC Educational Resources Information Center

Jackson, Dennis L.; Gillaspy, J. Arthur, Jr.; Purc-Stephenson, Rebecca

2009-01-01

Reporting practices in 194 confirmatory factor analysis studies (1,409 factor models) published in American Psychological Association journals from 1998 to 2006 were reviewed and compared with established reporting guidelines. Three research questions were addressed: (a) how do actual reporting practices compare with published guidelines? (b) how…

[Schizotypal Personality Questionnaire-Brief - Likert format: Factor structure analysis in general population in France].

PubMed

Ferchiou, A; Todorov, L; Lajnef, M; Baudin, G; Pignon, B; Richard, J-R; Leboyer, M; Szöke, A; Schürhoff, F

2017-12-01

The main objective of the study was to explore the factorial structure of the French version of the Schizotypal Personality Questionnaire-Brief (SPQ-B) in a Likert format, in a representative sample of the general population. In addition, differences in the dimensional scores of schizotypy according to gender and age were analyzed. As the study in the general population of schizotypal traits and its determinants has been recently proposed as a way toward the understanding of aetiology and pathophysiology of schizophrenia, consistent self-report tools are crucial to measure psychometric schizotypy. A shorter version of the widely used Schizotypal Personality Questionnaire (SPQ-Brief) has been extensively investigated in different countries, particularly in samples of students or clinical adolescents, and more recently, a few studies used a Likert-type scale format which allows partial endorsement of items and reduces the risk of defensive answers. A sample of 233 subjects representative of the adult population from an urban area near Paris (Créteil) was recruited using the "itinerary method". They completed the French version of the SPQ-B with a 5-point Likert-type response format (1=completely disagree; 5=completely agree). We examined the dimensional structure of the French version of the SPQ-B with a Principal Components Analysis (PCA) followed by a promax rotation. Factor selection was based on Eigenvalues over 1.0 (Kaiser's criterion), Cattell's Scree-plot test, and interpretability of the factors. Items with loadings greater than 0.4 were retained for each dimension. The internal consistency estimate of the dimensions was calculated with Cronbach's α. In order to study the influence of age and gender, we carried out a simple linear regression with the subscales as dependent variables. Our sample was composed of 131 women (mean age=52.5±18.2 years) and 102 men (mean age=53±18.1 years). SPQ-B Likert total scores ranged from 22 to 84 points (mean=43.6�

The significance of oral streptococci in patients with pneumonia with risk factors for aspiration: the bacterial floral analysis of 16S ribosomal RNA gene using bronchoalveolar lavage fluid.

PubMed

Akata, Kentaro; Yatera, Kazuhiro; Yamasaki, Kei; Kawanami, Toshinori; Naito, Keisuke; Noguchi, Shingo; Fukuda, Kazumasa; Ishimoto, Hiroshi; Taniguchi, Hatsumi; Mukae, Hiroshi

2016-05-11

Aspiration pneumonia has been a growing interest in an aging population. Anaerobes are important pathogens, however, the etiology of aspiration pneumonia is not fully understood. In addition, the relationship between the patient clinical characteristics and the causative pathogens in pneumonia patients with aspiration risk factors are unclear. To evaluate the relationship between the patient clinical characteristics with risk factors for aspiration and bacterial flora in bronchoalveolar lavage fluid (BALF) in pneumonia patients, the bacterial floral analysis of 16S ribosomal RNA gene was applied in addition to cultivation methods in BALF samples. From April 2010 to February 2014, BALF samples were obtained from the affected lesions of pneumonia via bronchoscopy, and were evaluated by the bacterial floral analysis of 16S rRNA gene in addition to cultivation methods in patients with community-acquired pneumonia (CAP) and healthcare-associated pneumonia (HCAP). Factors associated with aspiration risks in these patients were analyzed. A total of 177 (CAP 83, HCAP 94) patients were enrolled. According to the results of the bacterial floral analysis, detection rate of oral streptococci as the most detected bacterial phylotypes in BALF was significantly higher in patients with aspiration risks (31.0 %) than in patients without aspiration risks (14.7 %) (P = 0.009). In addition, the percentages of oral streptococci in each BALF sample were significantly higher in patients with aspiration risks (26.6 ± 32.0 %) than in patients without aspiration risks (13.8 ± 25.3 %) (P = 0.002). A multiple linear regression analysis showed that an Eastern Cooperative Oncology Group (ECOG) performance status (PS) of ≥3, the presence of comorbidities, and a history of pneumonia within a previous year were significantly associated with a detection of oral streptococci in BALF. The bacterial floral analysis of 16S rRNA gene revealed that oral streptococci were mostly

Indonesian railway accidents--utilizing Human Factors Analysis and Classification System in determining potential contributing factors.

PubMed

Iridiastadi, Hardianto; Ikatrinasari, Zulfa Fitri

2012-01-01

The prevalence of Indonesian railway accidents has not been declining, with hundreds of fatalities reported in the past decade. As an effort to help the National Transportation Safety Committee (NTSC), this study was conducted that aimed at understanding factors that might have contributed to the accidents. Human Factors Analysis and Classification System (HFACS) was utilized for this purpose. A total of nine accident reports (provided by the Indonesian NTSC) involving fatalities were studied using the technique. Results of this study indicated 72 factors that were closely related to the accidents. Of these, roughly 22% were considered as operator acts while about 39% were related to preconditions for operator acts. Supervisory represented 14% of the factors, and the remaining (about 25%) were associated with organizational factors. It was concluded that, while train drivers indeed played an important role in the accidents, interventions solely directed toward train drivers may not be adequate. A more comprehensive approach in minimizing the accidents should be conducted that addresses all the four aspects of HFACS.

[Analysis of the factors related to the needs of patients with cancer].

PubMed

Lee, Jung A; Lee, Sun Hee; Park, Jong Hyock; Park, Jae Hyun; Kim, Sung Gyeong; Seo, Ju Hyun

2010-05-01

Limited research has investigated the specific needs of patients with cancer. This study was performed to explore patients needs and the related factors. The data were collected by 1 National Cancer Center and 9 regional cancer centers in Korea. An interview survey was performed with using a structured questionnaire for the subjects (2,661 patients who gave written informed consent to participate) survey 4 months after diagnosis and review of medical records. Data were analyzed using t-test, ANOVA and multiple regression analysis. When comparing the relating factors related with patient needs to the sociodemographic characteristics, the female group showed a higher level of recognition for physical symptoms, social support needs. The younger group showed a significantly higher level of recognition for health care staff, psychological problems, information and education, social support, hospital services needs. In addition, the higher educated group showed a higher level of recognition for health care staff, physical symptoms, social support needs. The higher income and office workers group showed a higher level of recognition for hospital services needs. When comparing the relating factors related with patient needs to the cancer, the breast cancer group showed a higher level of recognition for all needs excluding physical symptoms, accessibility and financial support needs. The combined radiotherapy with surgery and chemotherapy group showed a higher level of recognition for psychological problems, information and education, social support needs. This study showed that needs on patient with cancer was significantly influenced by female, higher education, lower income, having religion, office worker, liver cancer, breast cancer, colon cancer, chemotherapy, and combined therapy.

Frequency of recommendations for additional imaging in diagnostic ultrasound examinations: Evaluation of radiologist, technologist, and other examination-related factors.

PubMed

Margolis, Nathaniel E; Rosenkrantz, Andrew B; Babb, James S; Macari, Michael

2015-10-01

Our aim in this study was to evaluate the effect of the radiologist, technologist, and other examination-related factors on the frequency of recommendations for additional imaging (RAI) during sonographic (US) interpretation. We retrospectively reviewed 719 US reports from a single academic medical center for the presence of RAI. All studies had been interpreted by one of three abdominal radiologists. Examinations were performed at an outpatient radiology facility with no onsite radiologist (n = 299) or at an inpatient emergency department or hospital-based outpatient setting that had an onsite radiologist (n = 420). Possible associations between the frequency of RAI and the presence of an onsite radiologist, location of the examination, body part or region imaged, patient age, technologist performing the exam, and radiologist reading the exam were evaluated. There were significant differences between each pair of radiologists in terms of overall frequency of RAI (p < 0.001) (radiologist 1: 12.0% [22/184]; radiologist 2: 21.6% [78/361]; and radiologist 3: 45.5% [79/174]). In addition, there were statistically significant differences in the frequency of RAI among studies scanned by the 10 different US technologists (13.6%-40.0%, p = 0.03). However, other factors such as patient age, patient sex, US unit, patient location, and radiologist location were not associated with the frequency of RAI (p = 0.15-0.93). The individual radiologist and technologist influenced the frequency of RAI for US examinations, whereas other examination-related factors did not. The observed substantial variability in RAI between radiologists and technologists warrants further study, with consideration of strategies to optimize RAI within US reports. © 2015 Wiley Periodicals, Inc.

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

Meta-Analysis of Early Nonmotor Features and Risk Factors for Parkinson Disease

PubMed Central

Noyce, Alastair J; Bestwick, Jonathan P; Silveira-Moriyama, Laura; Hawkes, Christopher H; Giovannoni, Gavin; Lees, Andrew J; Schrag, Anette

2012-01-01

Objective To evaluate the association between diagnosis of Parkinson disease (PD) and risk factors or early symptoms amenable to population-based screening. Methods A systematic review and meta-analysis of risk factors for PD. Results The strongest associations with later diagnosis of PD were found for having a first-degree or any relative with PD (odds ratio [OR], 3.23; 95% confidence interval [CI], 2.65–3.93 and OR, 4.45; 95% CI, 3.39–5.83) or any relative with tremor (OR, 2.74; 95% CI, 2.10–3.57), constipation (relative risk [RR], 2.34; 95% CI, 1.55–3.53), or lack of smoking history (current vs never: RR, 0.44; 95% CI, 0.39–0.50), each at least doubling the risk of PD. Further positive significant associations were found for history of anxiety or depression, pesticide exposure, head injury, rural living, beta-blockers, farming occupation, and well-water drinking, and negative significant associations were found for coffee drinking, hypertension, nonsteroidal anti-inflammatory drugs, calcium channel blockers, and alcohol, but not for diabetes mellitus, cancer, oral contraceptive pill use, surgical menopause, hormone replacement therapy, statins, acetaminophen/paracetamol, aspirin, tea drinking, history of general anesthesia, or gastric ulcers. In the systematic review, additional associations included negative associations with raised serum urate, and single studies or studies with conflicting results. Interpretation The strongest risk factors associated with later PD diagnosis are having a family history of PD or tremor, a history of constipation, and lack of smoking history. Further factors also but less strongly contribute to risk of PD diagnosis or, as some premotor symptoms, require further standardized studies to demonstrate the magnitude of risk associated with them. ANN NEUROL 2012 PMID:23071076

Analysis of stationary and dynamic factors affecting highway accident occurrence: A dynamic correlated grouped random parameters binary logit approach.

PubMed

Fountas, Grigorios; Sarwar, Md Tawfiq; Anastasopoulos, Panagiotis Ch; Blatt, Alan; Majka, Kevin

2018-04-01

Traditional accident analysis typically explores non-time-varying (stationary) factors that affect accident occurrence on roadway segments. However, the impact of time-varying (dynamic) factors is not thoroughly investigated. This paper seeks to simultaneously identify pre-crash stationary and dynamic factors of accident occurrence, while accounting for unobserved heterogeneity. Using highly disaggregate information for the potential dynamic factors, and aggregate data for the traditional stationary elements, a dynamic binary random parameters (mixed) logit framework is employed. With this approach, the dynamic nature of weather-related, and driving- and pavement-condition information is jointly investigated with traditional roadway geometric and traffic characteristics. To additionally account for the combined effect of the dynamic and stationary factors on the accident occurrence, the developed random parameters logit framework allows for possible correlations among the random parameters. The analysis is based on crash and non-crash observations between 2011 and 2013, drawn from urban and rural highway segments in the state of Washington. The findings show that the proposed methodological framework can account for both stationary and dynamic factors affecting accident occurrence probabilities, for panel effects, for unobserved heterogeneity through the use of random parameters, and for possible correlation among the latter. The comparative evaluation among the correlated grouped random parameters, the uncorrelated random parameters logit models, and their fixed parameters logit counterpart, demonstrate the potential of the random parameters modeling, in general, and the benefits of the correlated grouped random parameters approach, specifically, in terms of statistical fit and explanatory power. Published by Elsevier Ltd.

Replication Analysis in Exploratory Factor Analysis: What It Is and Why It Makes Your Analysis Better

ERIC Educational Resources Information Center

Osborne, Jason W.; Fitzpatrick, David C.

2012-01-01

Exploratory Factor Analysis (EFA) is a powerful and commonly-used tool for investigating the underlying variable structure of a psychometric instrument. However, there is much controversy in the social sciences with regard to the techniques used in EFA (Ford, MacCallum, & Tait, 1986; Henson & Roberts, 2006) and the reliability of the outcome.…

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

PubMed Central

2014-01-01

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

Pediatric cochlear implants: additional disabilities prevalence, risk factors, and effect on language outcomes.

PubMed

Birman, Catherine S; Elliott, Elizabeth J; Gibson, William P R

2012-10-01

To determine the prevalence of additional disabilities in a pediatric cochlear population, to identify medical and radiologic conditions associated with additional disabilities, and to identify the effect of additional disabilities on speech perception and language at 12 months postoperatively. Retrospective case review. Tertiary referral center and cochlear implant program. Records were reviewed for children 0 to 16 years old inclusive, who had cochlear implant-related operations over a 12-month period. Diagnostic and rehabilitative. Additional disabilities prevalence; medical history and radiologic abnormalities; and the effect on Categories of Auditory Performance (CAP) score at 12 months postoperatively. Eighty-eight children having 96 operations were identified. The overall prevalence of additional disabilities (including developmental delay, cerebral palsy, visual impairment, autism and attention deficit disorder) was 33%. The main conditions associated with additional disabilities were syndromes and chromosomal abnormalities (87%), jaundice (86%), prematurity (62%), cytomegalovirus (60%), and inner ear abnormalities including cochlea nerve hypoplasia or aplasia (75%) and semicircular canal anomalies (56%). At 12 months postoperatively, almost all (96%) of the children without additional disabilities had a CAP score of 5 or greater (speech), compared with 52% of children with additional disabilities. Children with developmental delay had a median CAP score of 4, at 12 months compared with 6 for those without developmental delay. Additional disabilities are prevalent in approximately a third of pediatric cochlear implant patients. Additional disabilities significantly affect the outcomes of cochlear implants.

Interactome analysis of transcriptional coactivator multiprotein bridging factor 1 unveils a yeast AP-1-like transcription factor involved in oxidation tolerance of mycopathogen Beauveria bassiana.

PubMed

Chu, Xin-Ling; Dong, Wei-Xia; Ding, Jin-Li; Feng, Ming-Guang; Ying, Sheng-Hua

2018-02-01

Oxidation tolerance is an important determinant to predict the virulence and biocontrol potential of Beauveria bassiana, a well-known entomopathogenic fungus. As a transcriptional coactivator, multiprotein bridging factor 1 mediates the activity of transcription factor in diverse physiological processes, and its homolog in B. bassiana (BbMBF1) contributes to fungal oxidation tolerance. In this study, the BbMBF1-interactomes under oxidative stress and normal growth condition were deciphered by mass spectrometry integrated with the immunoprecipitation. BbMBF1p factor has a broad interaction with proteins that are involved in various cellular processes, and this interaction is dynamically regulated by oxidative stress. Importantly, a B. bassiana homolog of yeast AP-1-like transcription factor (BbAP-1) was specifically associated with the BbMBF1-interactome under oxidation and significantly contributed to fungal oxidation tolerance. In addition, qPCR analysis revealed that several antioxidant genes are jointly controlled by BbAP-1 and BbMBF1. Conclusively, it is proposed that BbMBF1p protein mediates BbAP-1p factor to transcribe the downstream antioxidant genes in B. bassiana under oxidative stress. This study demonstrates for the first time a proteomic view of the MBF1-interactome in fungi, and presents an initial framework to probe the transcriptional mechanism involved in fungal response to oxidation, which will provide a new strategy to improve the biocontrol efficacy of B. bassiana.

An analysis of thermal response factors and how to reduce their computational time requirement

NASA Technical Reports Server (NTRS)

Wiese, M. R.

1982-01-01

Te RESFAC2 version of the Thermal Response Factor Program (RESFAC) is the result of numerous modifications and additions to the original RESFAC. These modifications and additions have significantly reduced the program's computational time requirement. As a result of this work, the program is more efficient and its code is both readable and understandable. This report describes what a thermal response factor is; analyzes the original matrix algebra calculations and root finding techniques; presents a new root finding technique and streamlined matrix algebra; supplies ten validation cases and their results.

Exploratory factor analysis of the functional movement screen in elite athletes.

PubMed

Li, Yongming; Wang, Xiong; Chen, Xiaoping; Dai, Boyi

2015-01-01

The functional movement screen is developed to examine individuals' movement patterns through 7 functional tasks. The purpose of this study was to identify the internal consistency and factor structure of the 7 tasks of the functional movement screen in elite athletes; 290 elite athletes from a variety of Chinese national teams were assessed using the functional movement screen. Cronbach's alpha was calculated for the scores of the 7 tasks. Exploratory factor analysis was performed to explore the factor structure of the functional movement screen. The mean and standard deviation of the sum score were 15.2 ± 3.0. A low Cronbach's alpha (0.58) was found for the scores of the 7 tasks. Exploratory factor analysis extracted 2 factors with eigenvalues greater than 1, and these 2 factors explained 47.3% of the total variance. The first factor had a high loading on the rotatory stability (loading = 0.99) and low loadings on the other 6 tasks (loading range: 0.04-0.34). The second factor had high loadings on the deep squat, hurdle step and inline lunge (loading range: 0.46-0.61) and low loadings on the other 3 tasks (loading range: 0.12-0.32). The 7 tasks of the functional movement screen had low internal consistency and were not indicators of a single factor. Evidence for unidimensionality was not found for the functional movement screen in elite athletes. More attention should be paid to the score of each task rather than the sum score when we interpret the functional movement screen scores.

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

PubMed

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

2012-10-10

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

Confirmatory factor analysis of the female sexual function index.

PubMed

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

2013-01-01

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

The School Counseling Program Implementation Survey: Initial Instrument Development and Exploratory Factor Analysis

ERIC Educational Resources Information Center

Clemens, Elysia V.; Carey, John C.; Harrington, Karen M.

2010-01-01

This article details the initial development of the School Counseling Program Implementation Survey and psychometric results including reliability and factor structure. An exploratory factor analysis revealed a three-factor model that accounted for 54% of the variance of the intercorrelation matrix and a two-factor model that accounted for 47% of…

Exploratory and Confirmatory Factor Analysis of the Career Decision-Making Difficulties Questionnaire

PubMed Central

Farrokhi, Farahman; Mahdavi, Ali; Moradi, Samad

2012-01-01

Objective The present study aimed at validating the structure of Career Decision-making Difficulties Questionnaire (CDDQ). Methods Five hundred and eleven undergraduate students took part in this research; from these participants, 63 males and 200 females took part in the first study, and 63 males and 185 females completed the survey for the second study. Results The results of exploratory factor analysis (EFA) indicated strong support for the three-factor structure, consisting of lack of information about the self, inconsistent information, lack of information and lack of readiness factors. A confirmatory factor analysis was run with the second sample using structural equation modeling. As expected, the three-factor solution provided a better fit to the data than the alternative models. Conclusion CDDQ was recommended to be used for college students in this study due to the fact that this instrument measures all three aspects of the model. Future research is needed to learn whether this model would fit other different samples. PMID:22952549

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

Difference in adherence to and influencing factors of a healthy lifestyle between middle-aged and elderly people in Korea: A multilevel analysis.

PubMed

Son, Ki Young; Park, Sang Min; Lee, Juhyun; Kim, Chang Yup

2015-06-01

Comprehensive research for factors related to healthy lifestyles of the elderly is limited. The present study aimed to elucidate the factors associated with adherence to a healthy lifestyle by age groups. The present study was based on data from the 2005 Korea National Health and Nutrition Examination Survey. We calculated crude proportions and adjusted proportions of cigarette smokers, problem alcohol drinkers, and physically inactive people in two age groups (40-59 years and ≥60 years). We carried out multilevel analysis to elucidate factors associated with healthy lifestyles. Of 3194 respondents included in the analysis, 1154 (36.13%) were aged 60 years or older. Older participants smoked less (23.0% vs 17.4%) and exercised less frequently (52.4% vs 66.9%; all P < 0.001) than their middle-aged counterparts. After adjustment, the proportion of regular exercisers was inversed (adjusted proportion 0.468, 95% CI 0.436-0.501 vs 0.377, 95% CI 0.337-0.419, P = 0.004). In multilevel analysis, contextual factors, such as local tax per capita, was associated significantly with cigarette smoking only in the elderly (OR 1.037, 95% CI 1.005-1.070). Different factors were associated with healthy lifestyles of elderly people when compared with middle-aged people. In addition, local tax per capita, an area level variable, was more likely to be associated with smoking in the elderly than the middle-aged group. © 2014 Japan Geriatrics Society.

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 Fully Non-Metallic Gas Turbine Engine Enabled by Additive Manufacturing Part I: System Analysis, Component Identification, Additive Manufacturing, and Testing of Polymer Composites

NASA Technical Reports Server (NTRS)

Grady, Joseph E.; Haller, William J.; Poinsatte, Philip E.; Halbig, Michael C.; Schnulo, Sydney L.; Singh, Mrityunjay; Weir, Don; Wali, Natalie; Vinup, Michael; Jones, Michael G.;

Prognostic factors of early metastasis and mortality in dogs with appendicular osteosarcoma after receiving surgery: an individual patient data meta-analysis.

PubMed

Schmidt, A F; Nielen, M; Klungel, O H; Hoes, A W; de Boer, A; Groenwold, R H H; Kirpensteijn, J

2013-11-01

Recently an aggregated data meta-analysis showed that serum alkaline phosphatase (SALP) and proximal humerus location are predictors for shorter survival in canine osteosarcoma. To identify additional prognostic factors of mortality and metastasis an individual patient data meta-analysis (IPDMA) was conducted. Individual patient data from 20 studies, identified via the VSSO society, were pooled. Univariable and multivariable hazard ratios (HR) for metastasis and mortality were assessed, using stratified Cox models. The study included 1405 dogs who received surgical treatment, of which the metastasis status was measured in 1155 dogs and mortality status in 1336 dogs; median survival was 256 days. High versus normal SALP and weight (kg) were associated with an increase in hazard of metastasis [HR 1.34 (95%CI 1.07; 1.68) and HR 1.02 (per kg increase) (95%CI 1.01; 1.03)] and for mortality [HR 1.43 (95%CI 1.16; 1.77) and HR 1.02 (95%CI 1.01; 1.02)]. Distal radius tumor was associated with a lower hazard of metastasis compared to other locations: HR 0.75 (95%CI 0.58; 0.96). Proximal humerus and distal femur or proximal tibia location were related with an increased mortality: HR 1.53 (95%CI 1.26; 1.84) and HR 1.23 (95%CI 1.01; 1.49) compared to other locations. Older age (years) was associated with a higher hazard for mortality [HR 1.06 per year (95%CI 1.03; 1.09)] but not for metastasis: HR 1.03 (95%CI 0.99; 1.06). These results confirm findings from a recent aggregated data meta-analysis and (in addition) showed that tumor location, SALP, weight were prognostic factors for both mortality and metastasis. Age was a prognostic factor for mortality but not for metastasis. Copyright © 2013 Elsevier B.V. All rights reserved.

Risk factor analysis for long-term tunneled dialysis catheter-related bacteremias.

PubMed

Jean, G; Charra, B; Chazot, C; Vanel, T; Terrat, J C; Hurot, J M; Laurent, G

2002-07-01

Infection, mainly related to vascular access, is one of the main causes of morbidity and a preventable cause of death in hemodialysis patients. From January 1994 to April 1998 we conducted a prospective study to assess the incidence and risk factors of catheter-related bacteremia. One hundred and twenty-nine tunneled dual-lumen hemodialysis catheters were inserted percutaneously into the internal jugular vein in 89 patients. Bacteremia (n = 56) occurred at least once with 37 (29%) of the catheters (an incidence of 1.1/1,000 catheter-days); local infection (n = 45, 1/1,000 catheter-days) was associated with bacteremia in 18 cases. Death in 1 case was directly related to Staphylococcus aureus (SA) septic shock, and septicemia contributed to deaths in 2 additional cases. Catheters were removed in 48% of the bacteremic episodes. Treatment comprised intravenous double antimicrobial therapy for 15-20 days. Bacteriological data of bacteremia showed 55% involvement of SA. Nasal carriage of SA was observed in 35% of the patients with catheters. Bacteremic catheters were more frequently observed in patients with diabetes mellitus (p = 0.03), peripheral atherosclerosis (p = 0.001), a previous history of bacteremia (p = 0.05), nasal carriage of SA (p = 0.0001), longer catheter survival time (p = 0.001), higher total intravenous iron dose (p = 0.001), more frequent urokinase catheter infusion (p < 0.01), and local infection (p < 0.001) compared with non-bacteremic catheters. Monovariate survival analysis showed that significant initial risk factors for bacteremia were nasal carriage of SA (p = 0.00001), previous bacteremia (p = 0.0001), peripheral atherosclerosis (p = 0.005), and diabetes (p = 0.04). This study confirms the relatively high incidence of bacteremia with tunneled double-lumen silicone catheters and its potential complications. Possible preventive actions are discussed according to the risk factors. Copyright 2002 S. Karger AG, Basel

The additional value of bioelectrical impedance analysis-derived muscle mass as a screening tool in geriatric assessment for fall prevention.

PubMed

Van Puyenbroeck, Karolien; Roelandts, Lieven; Van Deun, Thomas; Van Royen, Paul; Verhoeven, Veronique

2012-01-01

The decline in skeletal muscle in old age is a factor in the development of functional limitations. The objective of this study was to assess if there is a correlation between muscle mass based on bioelectrical impedance analysis (BIA) detection and the fall incidence in nursing home residents and to examine the risk factors for falling in nursing home residents. This prospective cohort study was part of a longitudinal study on nutritional issues in 52 nursing homes in Antwerp (Belgium) from October 2007 to April 2008. Two hundred and seventy-six people aged 65 years and older were included. Each subject was assessed with BIA, the timed get-up-and-go test, the Katz score, the Mini Nutritional Assessment - Short Form and the 36-Item Short Form Health Survey. The primary outcome parameter was fall incidence during the study. The prevalence of sarcopenia varied from 24.3 to 81.5% depending on which definition was used. No association was found between BIA-derived muscle mass and fall incidence. Logistic regression analysis showed that gait speed (odds ratio 1.029; p = 0.003) and mental health (odds ratio 0.981; p = 0.015) are significantly associated with fall incidence in nursing homes. A receiver operating characteristic curve showed that none of the BIA-derived muscle parameters are good predictors of the risk of falling. This study shows that there is no association between sarcopenia based on BIA and fall incidence and that BIA-derived muscle mass has no additional value in predicting fall incidents compared to the timed get-up-and-go test. Copyright © 2012 S. Karger AG, Basel.

Confirmatory Factor Analysis of the Elementary School Success Profile for Teachers

ERIC Educational Resources Information Center

Webber, Kristina C.; Rizo, Cynthia F.; Bowen, Natasha K.

2012-01-01

Objectives: This study examines the factor structure and scale quality of data collected with the online Elementary School Success Profile (ESSP) for Teachers from a sample of teachers of 1,145 third through fifth graders. Methods: Confirmatory factor analysis (CFA) using Mplus and weighted least squares means and variances adjusted (WLSMV)…

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

ERIC Educational Resources Information Center

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

2011-01-01

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

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

ERIC Educational Resources Information Center

Benligiray, Serdar; Onay, Ahmet

2017-01-01

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

Discriminative factor analysis of juvenile delinquency in South Korea.

PubMed

Kim, Hyun Sil; Kim, Hun Soo

2006-12-01

The present study was intended to compare difference in research variables between delinquent adolescents and student adolescents, and to analyze discriminative factors of delinquent behaviors among Korean adolescents. The research design of this study was a questionnaire survey. Questionnaires were administered to 2,167 adolescents (1,196 students and 971 delinquents), sampled from 8 middle and high school and 6 juvenile corrective institutions, using the proportional stratified random sampling method. Statistical methods employed were Chi-square, t-test, and logistic regression analysis. The discriminative factors of delinquent behaviors were smoking, alcohol use, other drug use, being sexually abused, viewing time of media violence and pornography. Among these discriminative factors, the factor most strongly associated with delinquency was smoking (odds ratio: 32.32). That is, smoking adolescent has a 32-fold higher possibility of becoming a delinquent adolescent than a non-smoking adolescent. Our findings, that smoking was the strongest discriminative factor of delinquent behavior, suggest that educational strategies to prevent adolescent smoking may reduce the rate of juvenile delinquency. Antismoking educational efforts are therefore urgently needed in South Korea.

Tsallis non-additive entropy and natural time analysis of seismicity

NASA Astrophysics Data System (ADS)

Sarlis, N. V.; Skordas, E. S.; Varotsos, P.

2017-12-01

Within the context of Tsallis non-additive entropy [1] statistical mechanics -in the frame of which kappa distributions arise [2,3]- a derivation of the Gutenberg-Richter (GR) law of seismicity has been proposed [4,5]. Such an analysis leads to a generalized GR law [6,7] which is applied here to the earthquakes in Japan and California. These seismic data are also studied in natural time [6] revealing that although some properties of seismicity may be recovered by the non-additive entropy approach, temporal correlations between successive earthquake magnitudes should be also taken into account [6,8]. The importance of such correlations is strengthened by the observation of periods of long range correlated earthquake magnitude time series [9] a few months before all earthquakes of magnitude 7.6 or larger in the entire Japanese area from 1 January 1984 to 11 March 2011 (the day of the magnitude 9.0 Tohoku-Oki earthquake) almost simultaneously with characteristic order parameter variations of seismicity [10]. These variations appear approximately when low frequency abnormal changes of the electric and magnetic field of the Earth (less than around 1Hz) are recorded [11] before strong earthquakes as the magnitude 9.0 Tohoku-Oki earthquake in Japan in 2011 [12]. 1. C Tsallis, J Stat Phys 52 (1988) 479 2. G Livadiotis, and D J McComas, J Geophys Res 114 (2009) A11105 3. G Livadiotis, Kappa Distributions. (Elsevier, Amsterdam) 2017. doi: 10.1016/B978-0-12-804638-8.01001-9 4. O Sotolongo-Costa, A Posadas, Phys Rev Lett 92 (2004) 048501 5. R Silva, G França, C Vilar, J Alcaniz, Phys Rev E 73 (2006) 026102 6. N Sarlis, E Skordas, P Varotsos, Phys Rev E 82 (2010) 021110 7. L Telesca, Bull Seismol Soc Am 102 (2012) 886-891 8. P Varotsos, N Sarlis, E Skordas, Natural Time Analysis: The new view of time. (Springer, Berlin) 2011. doi: 10.1007/978-3-642-16449-1 9. P Varotsos, N Sarlis, E Skordas, J Geophys Res Space Physics 119 (2014) 9192. 10. N Sarlis, E Skordas, P Varotsos, T

Acid Rain Analysis by Standard Addition Titration.

ERIC Educational Resources Information Center

Ophardt, Charles E.

1985-01-01

The standard addition titration is a precise and rapid method for the determination of the acidity in rain or snow samples. The method requires use of a standard buret, a pH meter, and Gran's plot to determine the equivalence point. Experimental procedures used and typical results obtained are presented. (JN)

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.

Food additives.

PubMed

Berglund, F

1978-01-01

The use of additives to food fulfils many purposes, as shown by the index issued by the Codex Committee on Food Additives: Acids, bases and salts; Preservatives, Antioxidants and antioxidant synergists; Anticaking agents; Colours; Emulfifiers; Thickening agents; Flour-treatment agents; Extraction solvents; Carrier solvents; Flavours (synthetic); Flavour enhancers; Non-nutritive sweeteners; Processing aids; Enzyme preparations. Many additives occur naturally in foods, but this does not exclude toxicity at higher levels. Some food additives are nutrients, or even essential nutritents, e.g. NaCl. Examples are known of food additives causing toxicity in man even when used according to regulations, e.g. cobalt in beer. In other instances, poisoning has been due to carry-over, e.g. by nitrate in cheese whey - when used for artificial feed for infants. Poisonings also occur as the result of the permitted substance being added at too high levels, by accident or carelessness, e.g. nitrite in fish. Finally, there are examples of hypersensitivity to food additives, e.g. to tartrazine and other food colours. The toxicological evaluation, based on animal feeding studies, may be complicated by impurities, e.g. orthotoluene-sulfonamide in saccharin; by transformation or disappearance of the additive in food processing in storage, e.g. bisulfite in raisins; by reaction products with food constituents, e.g. formation of ethylurethane from diethyl pyrocarbonate; by metabolic transformation products, e.g. formation in the gut of cyclohexylamine from cyclamate. Metabolic end products may differ in experimental animals and in man: guanylic acid and inosinic acid are metabolized to allantoin in the rat but to uric acid in man. The magnitude of the safety margin in man of the Acceptable Daily Intake (ADI) is not identical to the "safety factor" used when calculating the ADI. The symptoms of Chinese Restaurant Syndrome, although not hazardous, furthermore illustrate that the whole ADI

Factor structure of the Halstead-Reitan Neuropsychological Battery for children: a brief report supplement.

PubMed

Ross, Sylvia An; Allen, Daniel N; Goldstein, Gerald

2014-01-01

The Halstead-Reitan Neuropsychological Battery (HRNB) is the first factor-analyzed neuropsychological battery and consists of three batteries for young children, older children, and adults. Halstead's original factor analysis extracted four factors from the adult version of the battery, which were the basis for his theory of biological intelligence. These factors were called Central Integrative Field, Abstraction, Power, and Directional. Since this original analysis, Reitan's additions to the battery, and the development of the child versions of the test, this factor-analytic research continued. An introduction and the adult literature are reviewed in Ross, Allen, and Goldstein ( in press ). In this supplemental article, factor-analytic studies of the HRNB with children are reviewed. It is concluded that factor analysis of the HRNB or Reitan-Indiana Neuropsychological Battery with children does not replicate the extensiveness of the adult literature, although there is some evidence that when the traditional battery for older children is used, the factor structure is similar to what is found in adult studies. Reitan's changes to the battery appear to have added factors including language and sensory-perceptual factors. When other tests and scoring methods are used in addition to the core battery, differing solutions are produced.

Dual-Tracer PET Using Generalized Factor Analysis of Dynamic Sequences

PubMed Central

Fakhri, Georges El; Trott, Cathryn M.; Sitek, Arkadiusz; Bonab, Ali; Alpert, Nathaniel M.

2013-01-01

Purpose With single-photon emission computed tomography, simultaneous imaging of two physiological processes relies on discrimination of the energy of the emitted gamma rays, whereas the application of dual-tracer imaging to positron emission tomography (PET) imaging has been limited by the characteristic 511-keV emissions. Procedures To address this limitation, we developed a novel approach based on generalized factor analysis of dynamic sequences (GFADS) that exploits spatio-temporal differences between radiotracers and applied it to near-simultaneous imaging of 2-deoxy-2-[18F]fluoro-D-glucose (FDG) (brain metabolism) and 11C-raclopride (D2) with simulated human data and experimental rhesus monkey data. We show theoretically and verify by simulation and measurement that GFADS can separate FDG and raclopride measurements that are made nearly simultaneously. Results The theoretical development shows that GFADS can decompose the studies at several levels: (1) It decomposes the FDG and raclopride study so that they can be analyzed as though they were obtained separately. (2) If additional physiologic/anatomic constraints can be imposed, further decomposition is possible. (3) For the example of raclopride, specific and nonspecific binding can be determined on a pixel-by-pixel basis. We found good agreement between the estimated GFADS factors and the simulated ground truth time activity curves (TACs), and between the GFADS factor images and the corresponding ground truth activity distributions with errors less than 7.3±1.3 %. Biases in estimation of specific D2 binding and relative metabolism activity were within 5.9±3.6 % compared to the ground truth values. We also evaluated our approach in simultaneous dual-isotope brain PET studies in a rhesus monkey and obtained accuracy of better than 6 % in a mid-striatal volume, for striatal activity estimation. Conclusions Dynamic image sequences acquired following near-simultaneous injection of two PET radiopharmaceuticals

Confirmatory factor analysis of the School Refusal Assessment Scale – Revised in an African American community sample

PubMed Central

Lyon, Aaron R.

2010-01-01

The current study used confirmatory factor analysis techniques to investigate the construct validity of the child version of the School Refusal Assessment Scale – Revised (SRAS-R) in a community sample of low socioeconomic status, urban, African American fifth and sixth graders (n = 174). The SRAS-R is the best-researched measure of school refusal behavior in youth and typically yields four functional dimensions. Results of the investigation suggested that a modified version of the four-factor model, in which three items from the tangible reinforcement dimension are removed, may have construct validity in the current sample of youth. In addition, youth endorsement of the dimension measuring avoidance of social and/or evaluative situations was positively associated with unexcused absences. Implications for further psychometric research and early identification and prevention of problematic absenteeism in low-SES, ethnic minority community samples are highlighted. PMID:20567603

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.

Factor weighting in DRASTIC modeling.

PubMed

Pacheco, F A L; Pires, L M G R; Santos, R M B; Sanches Fernandes, L F

2015-02-01

Evaluation of aquifer vulnerability comprehends the integration of very diverse data, including soil characteristics (texture), hydrologic settings (recharge), aquifer properties (hydraulic conductivity), environmental parameters (relief), and ground water quality (nitrate contamination). It is therefore a multi-geosphere problem to be handled by a multidisciplinary team. The DRASTIC model remains the most popular technique in use for aquifer vulnerability assessments. The algorithm calculates an intrinsic vulnerability index based on a weighted addition of seven factors. In many studies, the method is subject to adjustments, especially in the factor weights, to meet the particularities of the studied regions. However, adjustments made by different techniques may lead to markedly different vulnerabilities and hence to insecurity in the selection of an appropriate technique. This paper reports the comparison of 5 weighting techniques, an enterprise not attempted before. The studied area comprises 26 aquifer systems located in Portugal. The tested approaches include: the Delphi consensus (original DRASTIC, used as reference), Sensitivity Analysis, Spearman correlations, Logistic Regression and Correspondence Analysis (used as adjustment techniques). In all cases but Sensitivity Analysis, adjustment techniques have privileged the factors representing soil characteristics, hydrologic settings, aquifer properties and environmental parameters, by leveling their weights to ≈4.4, and have subordinated the factors describing the aquifer media by downgrading their weights to ≈1.5. Logistic Regression predicts the highest and Sensitivity Analysis the lowest vulnerabilities. Overall, the vulnerability indices may be separated by a maximum value of 51 points. This represents an uncertainty of 2.5 vulnerability classes, because they are 20 points wide. Given this ambiguity, the selection of a weighting technique to integrate a vulnerability index may require additional

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

PubMed Central