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.

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…

Treatment for liver metastases from breast cancer: Results and prognostic factors

PubMed Central

Li, Xiao-Ping; Meng, Zhi-Qiang; Guo, Wei-Jian; Li, Jie

2005-01-01

AIM: Liver metastases from breast cancer (BCLM) are associated with poor prognosis. Cytotoxic chemotherapy can result in regression of tumor lesions and a decrease in symptoms. Available data, in the literature, also suggest a subgroup of patients may benefit from surgery, but few talked about transcatheter arterial chemoembolization (TACE). We report the results of TACE and systemic chemotherapy for patients with liver metastases from breast cancer and evaluate the prognostic factors. METHODS: Forty-eight patients with liver metastases, from proved breast primary cancer were treated with TACE or systemic chemotherapy between January 1995 and December 2000. Treatment results were assessed according to WHO criteria, along with analysis of prognostic factors for survival using Cox regression model. RESULTS: The median follow-up was 28 mo (1-72 mo). Response rates were calculated for the TACE group and chemotherapy group, being 35.7% and 7.1%, respectively. The difference was significant. The one-, two- and three-year Survival rates for the TACE group were 63.04%, 30.35%, and 13.01%, and those for the systemic chemotherapy group were 33.88%, 11.29%, and 0%. According to univariate analysis, variables significantly associated with survival were the lymph node status of the primary cancer, the clinical stage of liver metastases, the Child-Pugh grade, loss of weight. Other factors such as age, the intervals between the primary to the metastases, the maximal diameter of the liver metastases, the number of liver metastases, extrahepatic metastasis showed no prognostic significances. These factors mentioned above such as the lymph node status of the primary cancer, the clinical stage of liver metastases, the Child-Pugh grade, loss of weight were also independent factors in multivariate analysis. CONCLUSION: TACE treatment of liver metastases from breast cancer may prolong survival in certain patients. This approach offers new promise for the curative treatment of the

Factor analysis of metabolic syndrome components and predicting type 2 diabetes: Results of 10-year follow-up in a Middle Eastern population.

PubMed

Ayubi, Erfan; Khalili, Davood; Delpisheh, Ali; Hadaegh, Farzad; Azizi, Fereidoun

2015-11-01

The relationship among components of metabolic syndrome (MetS) and their association with diabetes is unclear in West Asia. The aim of the present study was to conduct factor analysis of MetS components and the effect these factors have on the incidence of type 2 diabetes (T2D) in a population-based cohort study of the Tehran Lipid and Glucose Study (TLGS). The present study enrolled 1861 men and 2706 women (20-60 years of age), from Tehran (Iran) who were free of diabetes at baseline and followed them for 10 years. A principal component analysis was performed to extract standardized factors from MetS components. Logistic regression was used to detect associations between the extracted factors and the incidence of diabetes. A propensity score was used to correct differential selection bias resulting from loss to follow-up. Factor analysis identified three factors (blood pressure, lipids and glycemia). Waist circumference was shared in three all factors. Blood pressure, lipids and glycemia were related to the incidence of diabetes with odds ratios (95% confidence intervals) of 2.23 (1.31-3.78), 1.89 (1.27-3.67), and 7.54 (4.09-13.91), respectively, in men and 2.13 (1.34-3.40), 2.06 (1.35-3.15), and 13.91 (7.29-26.51), respectively, in women for the third versus the first tertile of these standardized factors. Central adiposity may have a pivotal role in MetS linking other risk factors together. Glycemia had a high impact on the incidence of diabetes, whereas blood pressure and lipid had a similar moderate effect on the incidence of diabetes. © 2014 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd.

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.

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

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…

Treatment results and prognostic factors of pediatric neuroblastoma: a retrospective study.

PubMed

El-Sayed, Mohamed I; Ali, Amany M; Sayed, Heba A; Zaky, Eman M

2010-12-24

We conducted a retrospective analysis to investigate treatment results and prognostic factors of pediatric neuroblastoma patients. This retrospective study was carried out analyzing the medical records of patients with the pathological diagnosis of neuroblastoma seen at South Egypt Cancer Institute, Assiut University during the period from January 2001 and January 2010. After induction chemotherapy, response according to international neuoblastoma response criteria was assessed. Radiotherapy to patients with residual primary tumor was applied. Overall and event free survival (OAS and EFS) rates were estimated using Graphed prism program. The Log-rank test was used to examine differences in OAS and EFS rates. Cox-regression multivariate analysis was done to determine the independent prognostic factors affecting survival rates. Fifty three cases were analyzed. The median follow-up duration was 32 months and ranged from 2 to 84 months. The 3-year OAS and EFS rates were 39.4% and 29.3% respectively. Poor prognostic factors included age >1 year of age, N-MYC amplification, and high risk group. The majority of patients (68%) presented in high risk group, where treatment outcome was poor, as only 21% of patients survived for 3 year. Multivariate analysis confirmed only the association between survival and risk group. However, in univariate analysis, local radiation therapy resulted in significant survival improvement. Therefore, radiotherapy should be given to patients with residual tumor evident after induction chemotherapy and surgery. Future attempts to improve OAS in high risk group patients with aggressive chemotherapy and bone marrow transplantation should be considered.

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.

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

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…

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.

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)

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…

Examining construct and predictive validity of the Health-IT Usability Evaluation Scale: confirmatory factor analysis and structural equation modeling results

PubMed Central

Yen, Po-Yin; Sousa, Karen H; Bakken, Suzanne

2014-01-01

Background In a previous study, we developed the Health Information Technology Usability Evaluation Scale (Health-ITUES), which is designed to support customization at the item level. Such customization matches the specific tasks/expectations of a health IT system while retaining comparability at the construct level, and provides evidence of its factorial validity and internal consistency reliability through exploratory factor analysis. Objective In this study, we advanced the development of Health-ITUES to examine its construct validity and predictive validity. Methods The health IT system studied was a web-based communication system that supported nurse staffing and scheduling. Using Health-ITUES, we conducted a cross-sectional study to evaluate users’ perception toward the web-based communication system after system implementation. We examined Health-ITUES's construct validity through first and second order confirmatory factor analysis (CFA), and its predictive validity via structural equation modeling (SEM). Results The sample comprised 541 staff nurses in two healthcare organizations. The CFA (n=165) showed that a general usability factor accounted for 78.1%, 93.4%, 51.0%, and 39.9% of the explained variance in ‘Quality of Work Life’, ‘Perceived Usefulness’, ‘Perceived Ease of Use’, and ‘User Control’, respectively. The SEM (n=541) supported the predictive validity of Health-ITUES, explaining 64% of the variance in intention for system use. Conclusions The results of CFA and SEM provide additional evidence for the construct and predictive validity of Health-ITUES. The customizability of Health-ITUES has the potential to support comparisons at the construct level, while allowing variation at the item level. We also illustrate application of Health-ITUES across stages of system development. PMID:24567081

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.

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.

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.

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

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,…

Factors influencing the results of faculty evaluation in Isfahan University of Medical Sciences

PubMed Central

Kamali, Farahnaz; Yamani, Nikoo; Changiz, Tahereh; Zoubin, Fatemeh

2018-01-01

OBJECTIVE: This study aimed to explore factors influencing the results of faculty member evaluation from the viewpoints of faculty members affiliated with Isfahan University of Medical Sciences, Isfahan, Iran. MATERIALS AND METHODS: This qualitative study was done using a conventional content analysis method. Participants were faculty members of Isfahan University of Medical Sciences who, considering maximum variation in sampling, were chosen with a purposive sampling method. Semi-structured interviews were held with 11 faculty members until data saturation was reached. The interviews were transcribed verbatim and analyzed with conventional content analysis method for theme development. Further, the MAXQDA software was used for data management. RESULTS: The data analysis led to the development of two main themes, namely, “characteristics of the educational system” and “characteristics of the faculty member evaluation system.” The first main theme consists of three categories, i.e. “characteristics of influential people in evaluation,” “features of the courses,” and “background characteristics.” The other theme has the following as its categories: “evaluation methods,” “evaluation tools,” “evaluation process,” and “application of evaluation results.” Each category will have its subcategories. CONCLUSIONS: Many factors affect the evaluation of faculty members that should be taken into account by educational policymakers for improving the quality of the educational process. In addition to the factors that directly influence the educational system, methodological problems in the evaluation system need special attention. PMID:29417073

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.

Treatment Results of Postoperative Radiotherapy on Squamous Cell Carcinoma of the Oral Cavity: Coexistence of Multiple Minor Risk Factors Results in Higher Recurrence Rates

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

Fan, Kang-Hsing; Taipei Chang Gung Head and Neck Oncology Group, Chang Gung Memorial Hospital, Taiwan; Graduate Institute of Clinical Medical Sciences, Taiwan

2010-07-15

Purpose: The aim of this study was to investigate the treatment results of postoperative radiotherapy (PORT) on squamous cell carcinoma of the oral cavity (OSCC). Materials and Methods: This study included 302 OSCC patients who were treated by radical surgery and PORT. Indications for PORT include Stage III or IV OSCC according to the 2002 criteria of the American Joint Committee on Cancer, the presence of perineural invasion or lymphatic invasion, the depth of tumor invasion, or a close surgical margin. Patients with major risk factors, such as multiple nodal metastases, a positive surgical margin, or extracapsular spreading, were excluded.more » The prescribed dose of PORT ranged from 59.4 to 66.6Gy (median, 63Gy). Results: The 3-year overall and recurrence-free survival rates were 73% and 70%, respectively. Univariate analysis revealed that differentiation, perineural invasion, lymphatic invasion, bone invasion, location (hard palate and retromolar trigone), invasion depths {>=}10mm, and margin distances {<=}4mm were significant prognostic factors. The presence of multiple significant factors of univariate analysis correlated with disease recurrence. The 3-year recurrence-free survival rates were 82%, 76%, and 45% for patients with no risk factors, one or two risk factors, and three or more risk factors, respectively. After multivariate analysis, the number of risk factors and lymphatic invasion were significant prognostic factors. Conclusion: PORT may be an adequate adjuvant therapy for OSCC patients with one or two risk factors of recurrence. The presence of multiple risk factors and lymphatic invasion correlated with poor prognosis, and more aggressive treatment may need to be considered.« less

Analysis of Factors Influencing Measurement Accuracy of Al Alloy Tensile Test Results

NASA Astrophysics Data System (ADS)

Podgornik, Bojan; Žužek, Borut; Sedlaček, Marko; Kevorkijan, Varužan; Hostej, Boris

2016-02-01

In order to properly use materials in design, a complete understanding of and information on their mechanical properties, such as yield and ultimate tensile strength must be obtained. Furthermore, as the design of automotive parts is constantly pushed toward higher limits, excessive measuring uncertainty can lead to unexpected premature failure of the component, thus requiring reliable determination of material properties with low uncertainty. The aim of the present work was to evaluate the effect of different metrology factors, including the number of tested samples, specimens machining and surface quality, specimens input diameter, type of testing and human error on the tensile test results and measurement uncertainty when performed on 2xxx series Al alloy. Results show that the most significant contribution to measurement uncertainty comes from the number of samples tested, which can even exceed 1 %. Furthermore, moving from experimental laboratory conditions to very intense industrial environment further amplifies measurement uncertainty, where even if using automated systems human error cannot be neglected.

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.

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.

Factor Analysis of Intern Effectiveness

ERIC Educational Resources Information Center

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

2012-01-01

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

Factors influencing the results of faculty evaluation in Isfahan University of Medical Sciences.

PubMed

Kamali, Farahnaz; Yamani, Nikoo; Changiz, Tahereh; Zoubin, Fatemeh

2018-01-01

This study aimed to explore factors influencing the results of faculty member evaluation from the viewpoints of faculty members affiliated with Isfahan University of Medical Sciences, Isfahan, Iran. This qualitative study was done using a conventional content analysis method. Participants were faculty members of Isfahan University of Medical Sciences who, considering maximum variation in sampling, were chosen with a purposive sampling method. Semi-structured interviews were held with 11 faculty members until data saturation was reached. The interviews were transcribed verbatim and analyzed with conventional content analysis method for theme development. Further, the MAXQDA software was used for data management. The data analysis led to the development of two main themes, namely, "characteristics of the educational system" and "characteristics of the faculty member evaluation system." The first main theme consists of three categories, i.e. "characteristics of influential people in evaluation," "features of the courses," and "background characteristics." The other theme has the following as its categories: "evaluation methods," "evaluation tools," "evaluation process," and "application of evaluation results." Each category will have its subcategories. Many factors affect the evaluation of faculty members that should be taken into account by educational policymakers for improving the quality of the educational process. In addition to the factors that directly influence the educational system, methodological problems in the evaluation system need special attention.

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…

Using Formative Scenario Analysis approach for landslide risk analysis in a relatively scarce data environment: preliminary results

NASA Astrophysics Data System (ADS)

Zumpano, Veronica; Balteanu, Dan; Mazzorana, Bruno; Micu, Mihai

2014-05-01

It is increasingly important to provide to stakeholders tools that will enable them to better understand what is the state of the environment in which they live and manage and to help them to make decisions that aim to minimize the consequences of hydro-meteorological hazards. Very often, however, quantitative studies, especially for large areas, are difficult to perform. This is due to the fact that unfortunately isn't often possible to have the numerous data required to perform the analysis. In addition it has been proven that in scenario analysis, often deterministic approaches are not able to detect some features of the system revealing unexpected behaviors, and resulting in underestimation or omission of some impact factors. Here are presented some preliminary results obtained applying Formative Scenario Analysis that can be considered a possible solution for landslide risk analysis in cases where the data needed even if existent are not available. This method is an expert based approach that integrates intuitions and qualitative evaluations of impact factors with the quantitative analysis of relations between these factors: a group of experts with different but pertinent expertise, determine (by a rating procedure) quantitative relations between these factors, then through mathematical operations the scenarios describing a certain state of the system are obtained. The approach is applied to Buzau County (Romania), an area belonging to the Curvature Romanian Carpathians and Subcarpathians, a region strongly affected by environmental hazards. The region has been previously involved in numerous episodes of severe hydro-meteorological events that caused considerable damages (1975, 2005, 2006). In this application we are referring only to one type of landslides that can be described as shallow and medium-seated with a (mainly) translational movement that can go from slide to flow. The material involved can be either soil, debris or a mixture of both, in Romanian

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.

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

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.

Marital status is an independent prognostic factor for pancreatic neuroendocrine tumors patients: An analysis of the Surveillance, Epidemiology, and End Results (SEER) database.

PubMed

Zhou, Huaqiang; Zhang, Yuanzhe; Song, Yiyan; Tan, Wulin; Qiu, Zeting; Li, Si; Chen, Qinchang; Gao, Shaowei

2017-09-01

Marital status's prognostic impact on pancreatic neuroendocrine tumors (PNET) has not been rigorously studied. We aimed to explore the relationship between marital status and outcomes of PNET. We retrospectively investigated 2060 PNET cases between 2004 and 2010 from Surveillance, Epidemiology, and End Results (SEER) database. Variables were compared by Chi 2 test, t-test as appropriate. Kaplan-Meier methods and COX proportional hazard models were used to ascertain independent prognostic factors. Married patients had better 5-year overall survival (OS) (53.37% vs. 42.27%, P<0.001) and 5-year pancreatic neuroendocrine tumor specific survival (PNSS) (67.76% vs. 59.82%, P=0.001) comparing with unmarried patients. Multivariate analysis revealed marital status is an independent prognostic factor, with married patients showing better OS (HR=0.74; 95% CI: 0.65-0.84; P<0.001) and PNSS (HR=0.78; 95% CI: 0.66-0.92; P=0.004). Subgroup analysis suggested marital status plays a more important role in the PNET patients with distant stage rather than regional or localized disease. Marital status is an independent prognostic factor for survival in PNET patients. Poor prognosis in unmarried patients may be associated with a delayed diagnosis with advanced tumor stage, psychosocial and socioeconomic factors. Further studies are needed. Copyright © 2017. Published by Elsevier Masson SAS.

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…

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 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…

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)

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…

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…

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).

Analysis of Factors that Affect the Teacher Certification Exam Results in a University System in Puerto Rico

ERIC Educational Resources Information Center

Garofalo, Jorge H.

2009-01-01

The purpose of this study was to analyze the factors that affect a teacher preparation exam results within a University System in Puerto Rico. Using Bertalanffy's System Theory as theoretical framework, this mixed methods study examined factors in the university system that could have affected student's preparation for a teacher exam (PCMAS by its…

Examining construct and predictive validity of the Health-IT Usability Evaluation Scale: confirmatory factor analysis and structural equation modeling results.

PubMed

Yen, Po-Yin; Sousa, Karen H; Bakken, Suzanne

2014-10-01

In a previous study, we developed the Health Information Technology Usability Evaluation Scale (Health-ITUES), which is designed to support customization at the item level. Such customization matches the specific tasks/expectations of a health IT system while retaining comparability at the construct level, and provides evidence of its factorial validity and internal consistency reliability through exploratory factor analysis. In this study, we advanced the development of Health-ITUES to examine its construct validity and predictive validity. The health IT system studied was a web-based communication system that supported nurse staffing and scheduling. Using Health-ITUES, we conducted a cross-sectional study to evaluate users' perception toward the web-based communication system after system implementation. We examined Health-ITUES's construct validity through first and second order confirmatory factor analysis (CFA), and its predictive validity via structural equation modeling (SEM). The sample comprised 541 staff nurses in two healthcare organizations. The CFA (n=165) showed that a general usability factor accounted for 78.1%, 93.4%, 51.0%, and 39.9% of the explained variance in 'Quality of Work Life', 'Perceived Usefulness', 'Perceived Ease of Use', and 'User Control', respectively. The SEM (n=541) supported the predictive validity of Health-ITUES, explaining 64% of the variance in intention for system use. The results of CFA and SEM provide additional evidence for the construct and predictive validity of Health-ITUES. The customizability of Health-ITUES has the potential to support comparisons at the construct level, while allowing variation at the item level. We also illustrate application of Health-ITUES across stages of system development. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

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…

[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.

Prospective Coronary Heart Disease Screening in Asymptomatic Hodgkin Lymphoma Patients Using Coronary Computed Tomography Angiography: Results and Risk Factor Analysis

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

Girinsky, Theodore, E-mail: girinsky.theodore@orange.fr; M’Kacher, Radhia; Lessard, Nathalie

Purpose: To prospectively investigate the coronary artery status using coronary CT angiography (CCTA) in patients with Hodgkin lymphoma treated with combined modalities and mediastinal irradiation. Methods and Materials: All consecutive asymptomatic patients with Hodgkin lymphoma entered the study during follow-up, from August 2007 to May 2012. Coronary CT angiography was performed, and risk factors were recorded along with leukocyte telomere length (LTL) measurements. Results: One hundred seventy-nine patients entered the 5-year study. The median follow-up was 11.6 years (range, 2.1-40.2 years), and the median interval between treatment and the CCTA was 9.5 years (range, 0.5-40 years). Coronary artery abnormalities were demonstrated in 46 patientsmore » (26%). Coronary CT angiography abnormalities were detected in nearly 15% of the patients within the first 5 years after treatment. A significant increase (34%) occurred 10 years after treatment (P=.05). Stenoses were mostly nonostial. Severe stenoses were observed in 12 (6.7%) of the patients, entailing surgery with either angioplasty with stent placement or bypass grafting in 10 of them (5.5%). A multivariate analysis demonstrated that age at treatment, hypertension, and hypercholesterolemia, as well as radiation dose to the coronary artery origins, were prognostic factors. In the group of patients with LTL measurements, hypertension and LTL were the only independent risk factors. Conclusions: The findings suggest that CCTA can identify asymptomatic individuals at risk of acute coronary artery disease who might require either preventive or curative measures. Conventional risk factors and the radiation dose to coronary artery origins were independent prognostic factors. The prognostic value of LTL needs further investigation.« less

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.

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.

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. �

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

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

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 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.

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. �

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.

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…

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

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

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…

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…

Evaluation of Factors Determining the Results of Vocational Rehabilitation. Norwegian Monographs on Medical Science.

ERIC Educational Resources Information Center

Gogstad, Anders C.

Physical disability from disease or injury often results in a permanent state of social insufficiency, especially when the disability is reinforced by individual or environmental factors. In a study of almost 700 persons treated at a Norwegian rehabilitation center, regression analysis was used to compare those who benefited from the program with…

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…

Practical results from a mathematical analysis of guard patrols

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

Indusi, Joseph P.

1978-12-01

Using guard patrols as a primary detection mechanism is not generally viewed as a highly efficient detection method when compared to electronic means. Many factors such as visibility, alertness, and the space-time coincidence of guard and adversary presence all have an effect on the probability of detection. Mathematical analysis of the guard patrol detection problem is related to that of classical search theory originally developed for naval search operations. The results of this analysis tend to support the current practice of using guard forces to assess and respond to previously detected intrusions and not as the primary detection mechanism. 6more » refs.« less

Risk factors associated with NSAID-induced upper gastrointestinal bleeding resulting in hospital admissions: A cross-sectional, retrospective, case series analysis in valencia, spain

PubMed Central

Marco, José Luis; Amariles, Pedro; Boscá, Beatriz; Castelló, Ana

2007-01-01

Abstract Background NSAIDs are a significant cause of drug-related hospital admissions and deaths. The therapeutic effects of NSAIDs have been associated with the risk for developing adverse events, mainly in the gastrointestinal tract. Objectives The focus of this study was to identify the most common risk factors associated with NSAID-induced upper gastrointestinal bleeding (UGIB) resulting in hospital admissions. A secondary end point was the relationship between use of gastroprotective treatment and relevant risk factors to NSAID-induced UGIB in the selected population. Methods This study was a cross-sectional, retrospective, case-series analysis of NSAID-induced UGIB resulting in hospital admission to the Requena General Hospital, Valencia, Spain, occurring from 1997 to 2005. International Classification of Diseases, Ninth Revision, Clinical Modification codes were used to identify UGIB admissions associated with NSAIDs. To estimate the probability of association between UGIB and the use of NSAIDs, the Naranjo adverse drug reaction probability was used. Patients were categorized as high-risk to develop UGIB if they met ≥1 of the following risk criteria (relevant risk factors): aged ≥65 years (age risk factor); peptic ulcer disease or NSAID gastropathy occurring in the year before their hospital admission (history risk factor); and concomitant use of other NSAIDs, systemic corticoids, oral anticoagulants, or platelet aggregation inhibitors (concomitant medication risk factor). Patients were categorized as candidates to use gastroprotections if they met ≥1 of the relevant risk factors. Patients were categorized as users of gastroprotective treatment if they used proton pump inhibitors, histamine H2-receptor antagonists, or misoprostol at hospital admission. Results This study comprised 209 cases of NSAID-induced UGIB (129 men, 80 women: mean [SD] age, 71.5 [13.8] years; 128 [61.2%] receiving acetyl salicylic acid [ASA], with 72 [34.4%] receiving low

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…

Chronic lymphocytic leukaemia with 17p deletion: a retrospective analysis of prognostic factors and therapy results.

PubMed

Delgado, Julio; Espinet, Blanca; Oliveira, Ana C; Abrisqueta, Pau; de la Serna, Javier; Collado, Rosa; Loscertales, Javier; Lopez, Montserrat; Hernandez-Rivas, Jose A; Ferra, Christelle; Ramirez, Angel; Roncero, Josep M; Lopez, Cristina; Aventin, Anna; Puiggros, Anna; Abella, Eugenia; Carbonell, Felix; Costa, Dolors; Carrio, Anna; Gonzalez, Marcos

2012-04-01

Patients with chronic lymphocytic leukaemia (CLL) whose tumour cells harbour a 17p deletion (17p-) are universally considered to have a poor prognosis. The deletion can be detected at diagnosis or during the evolution of the disease, particularly in patients who have received chemotherapy. We sought to evaluate the natural history of patients with 17p- CLL, identify predictive factors within this prognostic subgroup, and evaluate the results of different therapeutic approaches. Data from 294 patients with 17p- CLL followed up at 20 different institutions was retrospectively collected and analysed. Median age was 68 (range 27-98) years at the time of fluorescence in situ hybridization analysis. After 17p- documentation, 52% received treatment, achieving an overall response rate of 50%. Median overall survival was 41 months, and was significantly shorter in patients with elevated beta(2)-microglobulin concentration (P < 0·001), B symptoms (P = 0·016), higher percentage of cells with deletion (P < 0·001), and acquired deletions (P = 0·012). These findings suggest that patients with 17p- CLL have a variable prognosis that can be refined using simple clinical and laboratory features, including 17p- clone size, beta2-microglobulin concentration, presence of B symptoms and type of deletion (de novo versus acquired). © 2012 Blackwell Publishing Ltd.

Organizational Analysis With Results Using Transactional Analysis

ERIC Educational Resources Information Center

Clary, Thomas C.; Clary, Erica W.

1976-01-01

OARTA (Organization Analysis with Results Using Transactional Analysis) is a way of thinking designed to resolve problems and reach goals through action-oriented research and analysis--a learning experience in which members of an organization can develop themselves and their organization. (ABM)

Factor analysis of the adolescent version of the Eating Disorders Examination Questionnaire (EDE-Q): results from Swedish general population and clinical samples.

PubMed

Forsén Mantilla, Emma; Birgegård, Andreas; Clinton, David

2017-01-01

Although the Eating Disorder Examination Questionnaire (EDE-Q) is perhaps the single most widely used self-report measure of eating disorder (ED) symptoms, important questions remain about its validity and applicability in relation to particular groups of individuals, especially adolescents of both genders. The present study investigated the factor structure of the adolescent version of the Eating Disorder Examination Questionnaire (EDE-Q) in samples of Swedish girls and boys from the general population and girls with a diagnosed eating disorder. Girls ( N  = 239) and boys ( N  = 248) aged between 13 and 15 years who were attending school, and girls ( N  = 570) aged between 12 and 14 years who were in treatment for an eating disorder at a specialist eating disorder clinic were assessed on the adolescent version of the EDE-Q. The adolescent version of the EDE-Q demonstrated satisfactory levels of internal consistency. However, confirmatory factor analysis (CFA) failed to support the four-factor model of the EDE-Q. Parallel analysis (PA) and subsequent exploratory factor analysis (EFA) suggested that the adolescent version of the EDE-Q comprises one underlying factor in young adolescent girls (both clinical and general population), centred on Dissatisfaction with Shape and Weight. In boys three factors were found: Weight-related Concerns, Body Discomfort and Restraint. The EDE-Q appears to measure different underlying aspects of eating disorder psychopathology in young teenagers compared to adults. The dimensions underlying disordered eating in young girls may become increasingly differentiated with time. There appear to be important gender-based differences in the dimensions underlying the EDE-Q in young teenagers. Therapists should be alert to beliefs that girls have about the importance of shape and weight, while in boys it may be more important to be attentive to how they feel about their bodies in relation to weight.

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

Differences in prostate and adipose tissue basic fibroblast growth factor: analysis of preliminary results.

PubMed

Mydlo, J H; Kral, J G; Macchia, R J

1997-09-01

Basic fibroblast growth factor (bFGF or FGF-2) is mitogenic to human prostate epithelial and stromal cells, and it is reported to be elevated in the serum and urine of patients with various cancers, including prostate cancer. Obesity, with increased body fat, is a risk factor for prostate cancer through unknown mechanisms. Because adipose tissue is a source of FGF-2, we determined the quantity and quality of activity of FGF-2 in omental adipose tissue and compared it with normal and cancerous prostate tissues. Using heparin-Sepharose chromatography, we extracted proteins from human omental adipose tissue, adenocarcinoma of the prostate, and benign prostatic hypertrophic (BPH) tissues. Each of the mitogenic proteins eluted with NaCl concentrations between 1.4 M and 1.8 M, similar to control FGF-2. Using FGF-2 antisera (which inhibited the mitogenic activity of the proteins), we performed Western blot analysis to confirm their homology to FGF-2. We also assessed recovery, mitogenicity, and angiogenicity of each of the proteins using thymidine incorporation into human umbilical vein endothelial cells and the chorioallantoic membrane assay. There was greater recovery of FGF-2 from omental adipose tissue compared with cancerous or BPH homogenates (40 micrograms [2.0 micrograms/g] versus 25 micrograms [1.25 micrograms/g] and 20 micrograms [1.0 microgram/g], respectively). Moreover. FGF-2 from adipose tissue had greater mitogenic activity (96.2% versus 74.8% and 54%; P < 0.05) and a greater angiogenic activity (5.1 vessels versus 2.9 and 1.8 vessels; P < 0.05) on the chorioallantoic assay. We suggest that human omental adipose tissue FGF-2 may demonstrate greater mitogenic and angiogenic activity than either BPH or prostate cancer tissue FGF-2. It is not known whether FGF-2 from adipose tissue qualitatively or quantitatively may underlie the relationship between obesity and prostate cancer.

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.

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.

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…

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.

A Confirmatory Factor Analysis of the Professional Opinion Scale

ERIC Educational Resources Information Center

Greeno, Elizabeth J.; Hughes, Anne K.; Hayward, R. Anna; Parker, Karen L.

2007-01-01

The Professional Opinion Scale (POS) was developed to measure social work values orientation. Objective: A confirmatory factor analysis was performed on the POS. Method: This cross-sectional study used a mailed survey design with a national random (simple) sample of members of the National Association of Social Workers. Results: The study…

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

NASA Technical Reports Server (NTRS)

Elrod, David Alan

1988-01-01

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

[Factors Affecting Long-Term Cosmetic Results after Minimally Invasive Video-Assisted Thyroidectomy and Conventional Thyroid Surgery].

PubMed

Sahm, Maik; Otto, Ronny; Pross, Matthias; Mantke, Rene

2018-06-25

Approximately 90,000 thyroid operations are performed in Germany each year. Minimally invasive video-assisted thyroidectomy (MIVAT) accounts for 5 - 10% of these operations. There are few data that compare long-term cosmetic results after MIVAT to those after conventional surgery. Current systematic reviews show no advantage for MIVAT. The goal of this study was to analyse the long-term postoperative results in both procedures and the evaluation of relevant factors. The analysis of the long-term results is based on follow-up examinations using a validated method for scar appraisal (POSAS). Cohort analysis was performed on MIVAT operations in our hospital between 2004 and 2011 and conventional thyroid operations in 2011. Follow-up examination data were analysed from 117 patients from the MIVAT group and 102 patients from the conventional group. The follow-up examination was performed with a mean of 23.1 vs. 23.6 months postoperatively (MIVAT vs. conventional). The Friedman Test showed that scar pigmentation (mean rank 4.79) and scar surface structure (mean rank 3.62) were the deciding factors influencing the long-term cosmetic results. Both MIVAT and conventional surgery gave very good long-term cosmetic results. From the patient's perspective, there is no significant advantage with conventional surgery. The evaluation of the long-term results largely depends on factors such as scar pigmentation and surface structure that can only be influenced to a limited extent by the surgical procedure. Georg Thieme Verlag KG Stuttgart · New York.

A Confirmatory Factor Analysis of the Academic Motivation Scale with Black College Students

ERIC Educational Resources Information Center

Cokley, Kevin

2015-01-01

The factor structure of the Academic Motivation Scale (AMS) was examined with a sample of 578 Black college students. A confirmatory factor analysis of the AMS was conducted. Results indicated that the hypothesized seven-factor model did not fit the data. Implications for future research with the AMS are discussed.

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.

Psychosocial factors of caregiver burden in child caregivers: results from the new national study of caregiving.

PubMed

Cohen, Steven A; Cook, Sarah; Kelley, Lauren; Sando, Trisha; Bell, Allison E

2015-08-07

Over 50 million informal caregivers in the United States provide care to an aging adult, saving the economy hundreds of billions of dollars annually from costly hospitalization or institutionalization. Despite the benefits associated with caregiving, caregiver stress can lead to negative physical and mental health consequences, or "caregiver burden". Given these potential negative consequences of caregiver burden, it is important not only to understand the multidimensional components of burden but to also understand the experience from the perspective of the caregiver themselves. Therefore, the objectives of our study are to use exploratory factor analysis to obtain a set of latent factors among a subset of caregiver burden questions identified in previous studies and assess their reliability. All data was obtained from the 2011 National Study of Caregiving (NSOC). Exploratory factor analysis (EFA) was performed to identify a set of latent factors assessing four domains of caregiver burden in "child caregivers": those informal caregivers who provide care to a parent or stepparent. Sensitivity analysis was also conducted by repeating the EFA on demographic subsets of caregivers. After multiple factor analyses, four consistent caregiver burden factors emerged from the 23 questions analyzed: Negative emotional, positive emotional, social, and financial. Reliability of each factor varied, and was strongest for the positive emotional domain for caregiver burden. These domains were generally consistent across demographic subsets of informal caregivers. These results provide researchers a more comprehensive understanding of caregiver burden to target interventions to protect caregiver health and maintain this vital component of the US health care system.

Sampling factors influencing accuracy of sperm kinematic analysis.

PubMed

Owen, D H; Katz, D F

1993-01-01

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

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.

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.

[Attention deficits and response to drug therapy in patients with treatment-resistant schizophrenia: results through confirmatory factor analysis].

PubMed

Sánchez, Pedro; Ojeda, Natalia; Elizagárate, Edorta; Peña, Javier; Ballesteros, Javier; Yoller, Ana B; Gutiérrez, Miguel; Casais, Leonardo; Ezcurra, Jesús

2010-04-01

There are no experimental data that demonstrate whether patients with neuroleptic-resistant schizophrenia differ or not in their pattern of neuropsychological functioning from patients with adequate drug response. Fifty-two patients with drug-resistant psychosis (DRP) and 42 patients with schizophrenia not resistant to treatment (NDRP) were recruited following the criteria of Kane et al (1988). A sample of 45 healthy controls matched by age, sex and educational level was also recruited. The clinical evaluations used were the Positive and Negative Symptom Scale (PANSS), functional disability (WHO-DAS) and the Clinical Global Impression (CGI) scale. Through the use of confirmatory factor analysis, we obtained a latent cognitive structure of six cognitive factors: attention, processing speed, verbal memory, working memory, verbal fluency and executive functions. As expected, the control group performed better than the two patient groups (both DRP and NDRP) in all neuropsychological domains. Additionally, the DRP group scored significantly worse in attention than the NDRP group even though no differences between these two groups were found in age of disease onset, number of hospitalizations or length of hospitalization. From a clinical point of view, the DRP group showed greater severity of positive symptoms (p<0.01) and higher global deterioration (p<0.01), which did not translate into greater functional disability. The results obtained do not allow us to conclude that there is a specific neuropsychological profile in neuroleptic-resistant patients. The only differential parameter was performance in the attentional domain. Our findings better fit the hypothesis of a «clinical continuum» and differ from the categoric classification of this mental disorder. Copyright © 2009 SEP y SEPB. Published by Elsevier Espana. All rights reserved.

Confirmatory Factor Analysis of the WISC-IV in a Hospital Referral Sample

ERIC Educational Resources Information Center

Devena, Sarah E.; Gay, Catherine E.; Watkins, Marley W.

2013-01-01

Confirmatory factor analysis was used to determine the factor structure of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) scores of 297 children referred to a children's hospital in the Southwestern United States. Results support previous findings that indicate the WISC-IV is best represented by a direct hierarchical…

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

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.

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.

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.

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.

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…

Synthesizing Regression Results: A Factored Likelihood Method

ERIC Educational Resources Information Center

Wu, Meng-Jia; Becker, Betsy Jane

2013-01-01

Regression methods are widely used by researchers in many fields, yet methods for synthesizing regression results are scarce. This study proposes using a factored likelihood method, originally developed to handle missing data, to appropriately synthesize regression models involving different predictors. This method uses the correlations reported…

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 feasibility study on age-related factors of wrist pulse using principal component analysis.

PubMed

Jang-Han Bae; Young Ju Jeon; Sanghun Lee; Jaeuk U Kim

2016-08-01

Various analysis methods for examining wrist pulse characteristics are needed for accurate pulse diagnosis. In this feasibility study, principal component analysis (PCA) was performed to observe age-related factors of wrist pulse from various analysis parameters. Forty subjects in the age group of 20s and 40s were participated, and their wrist pulse signal and respiration signal were acquired with the pulse tonometric device. After pre-processing of the signals, twenty analysis parameters which have been regarded as values reflecting pulse characteristics were calculated and PCA was performed. As a results, we could reduce complex parameters to lower dimension and age-related factors of wrist pulse were observed by combining-new analysis parameter derived from PCA. These results demonstrate that PCA can be useful tool for analyzing wrist pulse signal.

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…

Analysis of factors influencing the overall effect of racecadotril on childhood acute diarrhea. Results from a real-world and post-authorization surveillance study in Venezuela.

PubMed

Chacón, Jose

2010-07-21

Drug efficacy might differ from clinical trial results when performed in clinical daily conditions. Therefore, it is mandatory to conduct trials about effectiveness to improve external validity. This post-authorization, open-label, noncontrolled, prospective, multicenter, observational, and naturalistic trial was designed to search for factors influencing the racecadotril overall effect on childhood acute watery diarrhea in a real-world setting of Venezuela. There were 3,873 children with acute watery diarrhea treated with racecadotril, an enkephalin breakdown blocker plus oral rehydration therapy by 97 pediatricians. Evaluations were carried out daily until emission of two consecutive formed stools or absence of watery bowel movements for 24 hours. The primary end-point was time-to-relief, defined as the time from first racecadotril dose to the last watery bowel movement time. Age, gender, nursing type, nursing status during diarrhea, diarrhea severity, and co-medication were considered as factors in the statistical analysis. The primary end-point was evaluated by factors using UNIANOVA, and post-hoc tests were done. A multiple regression analysis was carried out to identify factors affecting drug performance, racecadotril effectiveness and tolerability overall assessment was searched by physicians and patients, and inter-observer agreement was evaluated by kappa statistics. The mean time-to-relief was 18.5 +/- 12.5 hours [95% confidence interval 17.9-19.0] and the diarrhea severity was the only variable with significant and independent weight on racecadotril effectiveness explaining 23% of time-to-relief variance, but even in severe diarrhea cases this time was less than 24 hours. High agreement about satisfactory perception on effectiveness and tolerability was reached among physicians and patients. In conclusion, the racecadotril overall effect, evaluated in a real-world setting of Venezuela, was in agreement with results of some earlier controlled trials. It

Analysis of factors influencing the overall effect of racecadotril on childhood acute diarrhea. Results from a real-world and post-authorization surveillance study in Venezuela

PubMed Central

Chacón, Jose

2010-01-01

Drug efficacy might differ from clinical trial results when performed in clinical daily conditions. Therefore, it is mandatory to conduct trials about effectiveness to improve external validity. This post-authorization, open-label, noncontrolled, prospective, multicenter, observational, and naturalistic trial was designed to search for factors influencing the racecadotril overall effect on childhood acute watery diarrhea in a real-world setting of Venezuela. There were 3,873 children with acute watery diarrhea treated with racecadotril, an enkephalin breakdown blocker plus oral rehydration therapy by 97 pediatricians. Evaluations were carried out daily until emission of two consecutive formed stools or absence of watery bowel movements for 24 hours. The primary end-point was time-to-relief, defined as the time from first racecadotril dose to the last watery bowel movement time. Age, gender, nursing type, nursing status during diarrhea, diarrhea severity, and co-medication were considered as factors in the statistical analysis. The primary end-point was evaluated by factors using UNIANOVA, and post-hoc tests were done. A multiple regression analysis was carried out to identify factors affecting drug performance, racecadotril effectiveness and tolerability overall assessment was searched by physicians and patients, and inter-observer agreement was evaluated by kappa statistics. The mean time-to-relief was 18.5 ± 12.5 hours [95% confidence interval 17.9–19.0] and the diarrhea severity was the only variable with significant and independent weight on racecadotril effectiveness explaining 23% of time-to-relief variance, but even in severe diarrhea cases this time was less than 24 hours. High agreement about satisfactory perception on effectiveness and tolerability was reached among physicians and patients. In conclusion, the racecadotril overall effect, evaluated in a real-world setting of Venezuela, was in agreement with results of some earlier controlled trials. It

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,…

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.

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.

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

PubMed Central

2010-01-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

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.

A Meta-Analysis on the Factors That Best Reduce the Achievement Gap

ERIC Educational Resources Information Center

Jeynes, William H.

2015-01-01

A meta-analyses was undertaken to determine the factors that are most related with reducing the achievement gap. The meta-analysis included 30 studies that examined attempts to bridge the achievement gap between White students on one hand and Black and Latino students on the other. The results indicate that several factors are associated with a…

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.

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.

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…

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.

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)

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.

Simulating the Effects of Common and Specific Abilities on Test Performance: An Evaluation of Factor Analysis

ERIC Educational Resources Information Center

McFarland, Dennis J.

2014-01-01

Purpose: Factor analysis is a useful technique to aid in organizing multivariate data characterizing speech, language, and auditory abilities. However, knowledge of the limitations of factor analysis is essential for proper interpretation of results. The present study used simulated test scores to illustrate some characteristics of factor…

Schizophrenia with prominent catatonic features ('catatonic schizophrenia'). II. Factor analysis of the catatonic syndrome.

PubMed

Ungvari, Gabor S; Goggins, William; Leung, Siu-Kau; Gerevich, Jozsef

2007-03-30

Previous factor analyses of catatonia have yielded conflicting results for several reasons including small and/or diagnostically heterogeneous samples and incomparability or lack of standardized assessment. This study examined the factor structure of catatonia in a large, diagnostically homogenous sample of patients with chronic schizophrenia using standardized rating instruments. A random sample of 225 Chinese inpatients diagnosed with schizophrenia according to DSM-IV criteria were selected from the long-stay wards of a psychiatric hospital. They were assessed with a battery of rating scales measuring psychopathology, extrapyramidal motor status, and level of functioning. Catatonia was rated using the Bush-Francis Catatonia Rating Scale. Factor analysis using principal component analysis and Varimax rotation with Kaiser normalization was performed. Four factors were identified with Eigenvalues of 3.27, 2.58, 2.28 and 1.88. The percentage of variance explained by each of the four factors was 15.9%, 12.0%, 11.8% and 10.2% respectively, and together they explained 49.9% of the total variance. Factor 1 loaded on "negative/withdrawn" phenomena, Factor 2 on "automatic" phenomena, Factor 3 on "repetitive/echo" phenomena and Factor 4 on "agitated/resistive" phenomena. In multivariate linear regression analysis negative symptoms and akinesia were associated with 'negative' catatonic symptoms, antipsychotic doses and atypical antipsychotics with 'automatic' symptoms, length of current admission, severity of psychopathology and younger age at onset with 'repetitive' symptoms and age, poor functioning and severity of psychopathology with 'agitated' catatonic symptom scores. The results support recent findings that four main factors underlie catatonic signs/symptoms in chronic schizophrenia.

The Impact of Risk Factors of Chronic Pancreatitis on Secretin Pancreatic Function Testing: Results of a 20-Year Study.

PubMed

Kothari, Darshan; Ketwaroo, Gyanprakash; Freedman, Steven D; Sheth, Sunil G

2017-08-01

The aim of this study was to determine the effect of established risk factors on the outcome of secretin pancreatic function testing (sPFT) in patients undergoing work-up for suspected chronic pancreatitis. We completed a retrospective review of patients who underwent sPFT for suspected chronic pancreatitis over 20 years. We compared peak bicarbonate concentrations between groups and completed univariate and multivariate analyses to determine associations between risk factors and positive sPFT results (peak bicarbonate <80 mEq/L). Forty-three of 162 patients had positive sPFT results. There were significant differences in peak bicarbonate concentrations in patients with and without recurrent acute pancreatitis (RAP) and with local complications from acute pancreatitis (AP) (P ≤ 0.05). The bicarbonate concentration in patients with and without other risk factors such as tobacco use, alcohol use, and family history of pancreatitis was not significantly different. Female sex, a history of AP, and a history of RAP were associated with positive sPFT results on univariate analysis (P ≤ 0.05). On multivariate analysis, sex and RAP remained significant. Our study demonstrates that female sex, history of AP and RAP, and AP with local complications are associated with positive sPFT results or lower peak bicarbonate concentration. However, other risk factors do not impact the results of sPFT.

Confirmatory factor analysis for two questionnaires of caregiving in eating disorders

PubMed Central

Hibbs, Rebecca; Rhind, Charlotte; Sallis, Hannah; Goddard, Elizabeth; Raenker, Simone; Ayton, Agnes; Bamford, Bryony; Arcelus, Jon; Boughton, Nicky; Connan, Frances; Goss, Ken; Lazlo, Bert; Morgan, John; Moore, Kim; Robertson, David; Schreiber-Kounine, Christa; Sharma, Sonu; Whitehead, Linette; Lacey, Hubert; Schmidt, Ulrike; Treasure, Janet

2014-01-01

Objective: Caring for someone diagnosed with an eating disorder (ED) is associated with a high level of burden and psychological distress which can inadvertently contribute to the maintenance of the illness. The Eating Disorders Symptom Impact Scale (EDSIS) and Accommodation and Enabling Scale for Eating Disorders (AESED) are self-report scales to assess elements of caregiving theorised to contribute to the maintenance of an ED. Further validation and confirmation of the factor structures for these scales are necessary for rigorous evaluation of complex interventions which target these modifiable elements of caregiving. Method: EDSIS and AESED data from 268 carers of people with anorexia nervosa (AN), recruited from consecutive admissions to 15 UK inpatient or day patient hospital units, were subjected to confirmatory factor analysis to test model fit by applying the existing factor structures: (a) four-factor structure for the EDSIS and (b) five-factor structure for the AESED. Results: Confirmatory factor analytic results support the existing four-factor and five-factor structures for the EDSIS and the AESED, respectively. Discussion: The present findings provide further validation of the EDSIS and the AESED as tools to assess modifiable elements of caregiving for someone with an ED. PMID:25750785

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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

PubMed

Di Nuovo, Santo F; Buono, Serafino

2006-12-01

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

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

PubMed

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

2008-11-01

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

Psychological factors related to donation behaviour among Chinese adults: results from a longitudinal investigation.

PubMed

Hu, H; Wang, T; Fu, Q

2017-10-01

Little is known about the psychological factors currently influencing blood donation in China. This study investigated the structure of psychological factors and their correlation with donation behaviour of adults in a transforming city in China over a 6-month period. Participants were recruited in Nanjing from May 2013 to April 2014. Preliminary focus group interviews with 102 participants were conducted to generate new items for a Theory of Planned Behaviour (TPB) questionnaire. The questionnaires were completed by 300 participants, and responses were subjected to factor analysis. We confirmed the resulting factorial structure with 861 respondents and examined the associations between these factors and donation behaviour during the next 6 months using structural equation modelling. Factor analysis and structural equation modelling of the data supported an extended TPB model with self-reported past donation behaviour as a covariate. After controlling for past donation behaviour, attitudes towards blood donation (β = 0·288), subjective norm (β = 0·149), self-efficacy (β = 0·199), trust in third-party health professionals (β = 0·237), mistrust towards blood collection agencies (BCAs) (β = -0·085) and traditional Chinese beliefs (β = -0·046) were significantly related to donation intention, whilst donation intention was positively (β = 0·212) associated with donation behaviour. These findings confirm that psychological factors such as attitudes are predictors of blood donation. Recruitment efforts using public information campaigns and interpersonal communications should focus on strengthening positive attitudes, increasing trust in third-party health professionals, elevating self-efficacy, changing traditional Chinese beliefs and relieving mistrust in blood collection agencies (BCAs). © 2017 British Blood Transfusion Society.

Factors associated with secondhand smoke exposure in different settings: Results from the German Health Update (GEDA) 2012.

PubMed

Fischer, Florian; Kraemer, Alexander

2016-04-14

The ubiquity of secondhand smoke (SHS) exposure at home or in private establishments, workplaces and public areas poses several challenges for the reduction of SHS exposure. This study aimed to describe the prevalence of SHS exposure in Germany and key factors associated with exposure. Results were also differentiated by place of exposure. A secondary data analysis based on the public use file of the German Health Update 2012 was conducted (n = 13,933). Only non-smokers were included in the analysis. In a multivariable logistic regression model the factors associated with SHS exposure were calculated. In addition, a further set of multivariable logistic regressions were calculated for factors associated with the place of SHS exposure (workplace, at home, bars/discotheques, restaurants, at the house of a friend). More than a quarter of non-smoking study participants were exposed to SHS. The main area of exposure was the workplace (40.9 %). The multivariable logistic regression indicated young age as the most important factor associated with SHS exposure. The odds for SHS exposure was higher in men than in women. The likelihood of SHS exposure decreased with higher education. SHS exposure and the associated factors varied between different places of exposure. Despite several actions to protect non-smokers which were implemented in Germany during the past years, SHS exposure still remains a relevant risk factor at a population level. According to the results of this study, particularly the workplace and other public places such as bars and discotheques have to be taken into account for the development of strategies to reduce SHS exposure.

Factor Analysis of the Alcohol and Drug Confrontation Scale (ADCS)

PubMed Central

Polcin, Douglas L.; Galloway, Gantt P.; Bostrom, Alan; Greenfield, Thomas K.

2007-01-01

The Alcohol and Drug Confrontation Scale (ADCS) is a 72-item instrument that defines confrontation as an individual being told “bad things” might happen if they do not make changes to address alcohol or drug problems or maintain sobriety. Preliminary assessment of the ADCS using substance abusers entering SLH's revealed: 1) Scale items were frequently endorsed; 2) Confrontation was often experienced as accurate and helpful; and 3) Confronters' statements were viewed supportive and accurate. This study reports the results of a factor analysis on a larger sample 179 participants using baseline and 6 month follow-up data. Results yielded a clear two factor solution: 1) Internal Support (alpha = 0.80) and 2) External Intensity (alpha = 0.63). The two factors accounted for 58% of the variance. The ADCS offers a fresh and broader view of confrontation that can be reliably measured. PMID:17270360

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)

Analysis of psychological factors for quality assessment of interactive multimodal service

NASA Astrophysics Data System (ADS)

Yamagishi, Kazuhisa; Hayashi, Takanori

2005-03-01

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

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

NASA Astrophysics Data System (ADS)

Nossent, Jiri; Pereira, Fernando; Bauwens, Willy

2017-04-01

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

Analysis of factors that influencing the interest of Bali State Polytechnic’s students in entrepreneurship

NASA Astrophysics Data System (ADS)

Ayuni, N. W. D.; Sari, I. G. A. M. K. K.

2018-01-01

The high rate of unemployment results the economic growth to be hampered. To solve this situation, the government try to change the students’ mindset from becoming a job seeker to become a job creator or entrepreneur. One real action that usually been held in Bali State Polytechnic is Student Entrepreneurial Program. The purpose of this research is to identify and analyze the factors that influence the interest of Bali State Polytechnic’s Students in entrepreneurship, especially in the Entrepreneurial Student Program. Method used in this research is Factor Analysis including Bartlett Test, Kaiser-Mayer Olkin (KMO), Measure of Sampling Adequacy (MSA), factor extraction using Principal Component Analysis (PCA), factor selection using eigen value and scree plot, and factor rotation using orthogonal rotation varimax. Result shows that there are four factors that influencing the interest of Bali State Polytechnic’s Students in Entrepreneurship which are Contextual Factor (including Entrepreneurship Training, Academic Support, Perceived Confidence, and Economic Challenge), Self Efficacy Factor (including Leadership, Mental Maturity, Relation with Entrepreneur, and Authority), Subjective Norm Factor (including Support of Important Relative, Support of Friends, and Family Role), and Attitude Factor (including Self Realization).

Coping Patterns of African American Adolescents: A Confirmatory Factor Analysis and Cluster Analysis of the Children's Coping Strategies Checklist

ERIC Educational Resources Information Center

Gaylord-Harden, Noni K.; Gipson, Polly; Mance, GiShawn; Grant, Kathryn E.

2008-01-01

The current study examined patterns of coping strategies in a sample of 497 low-income urban African American adolescents (mean age = 12.61 years). Results of confirmatory factor analysis indicated that the 4-factor structure of the Children's Coping Strategies Checklist (T. S. Ayers, I. N. Sandler, S. G. West, & M. W. Roosa, 1996) was not…

Multilevel Confirmatory Factor Analysis of a Scale Measuring Interagency Collaboration of Children's Mental Health Agencies

ERIC Educational Resources Information Center

Dedrick, Robert F.; Greenbaum, Paul E.

2011-01-01

Multilevel confirmatory factor analysis was used to evaluate the factor structure underlying the 12-item, three-factor "Interagency Collaboration Activities Scale" (ICAS) at the informant level and at the agency level. Results from 378 professionals (104 administrators, 201 service providers, and 73 case managers) from 32 children's mental health…

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

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…

A human factors analysis of fatal and serious injury accidents in Alaska, 2004-2009.

DOT National Transportation Integrated Search

2011-12-01

"This report summarizes the analysis of 97 general aviation accidents in Alaska that resulted in a fatality or serious : injury to one or more aircraft occupants for the years 2004-2009. The accidents were analyzed using the Human : Factors Analysis ...

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)

Signal Detection Analysis of Factors Associated with Diabetes among Semirural Mexican American Adults

ERIC Educational Resources Information Center

Hanni, K. D.; Ahn, D. A.; Winkleby, M. A.

2013-01-01

Signal detection analysis was used to evaluate a combination of sociodemographic, acculturation, mental health, health care, and chronic disease risk factors potentially associated with diabetes in a sample of 4,505 semirural Mexican American adults. Overall, 8.9% of adults had been diagnosed with diabetes. The analysis resulted in 12 mutually…

Looks good but feels bad: factors that contribute to poor results after total knee arthroplasty.

PubMed

Fisher, David A; Dierckman, Brian; Watts, Melanie R; Davis, Kenneth

2007-09-01

The purpose of this study was to evaluate patient factors that might contribute to a poor result after total knee arthroplasty (TKA). Seventy-one knees (6.9%) of 1024 primary TKAs were identified at 1 year follow-up as having a poor result because of either stiffness or pain. Radiographs demonstrated well-fixed and aligned implants. This group was compared with a matched control group of 148 nonpainful or stiff TKAs, with similar range of motion preoperatively. Logistic regression analysis was performed to compare age, sex, body mass index, comorbidities, previous surgeries, preoperative narcotic use, tobacco or alcohol use, work status, insurance status, and any history of depression. Factors that were significantly associated with a stiff or painful outcome included female sex, higher body mass index, previous knee surgery, patients on disability, diabetes mellitus, pulmonary disease, and depression.

Factors affecting the results of comprehensive pre-internship exam among medical students of Kermanshah University of Medical Sciences.

PubMed

Khazaei, Mohammad Rasool; Zarin, Afshin; Rezaei, Mansuor; Khazaei, Mozafar

2018-06-01

This study was aimed to evaluate the factors affecting the results of comprehensive pre-internship exam (CPIE) among medicals students of Kermanshah University of Medical Sciences. In this descriptive-analytical study, all students (n=240) participating in CPIE over a 3-year period (2012-2014) were selected. Data were gathered by a questionnaire, including the CPIE results and educational and demographic data. Spearman correlation coefficient, Mann-Whitney U-test, and analysis of variance were used to analyze the association of students' success with study variables. Also, regression analysis was applied to determine the role of independent variables in students' success. The frequency of the failed units in apprenticeship course was one of the most important risk factors associated with failure in CPIE. Average scores of pre-internship course were the most important factors of success in CPIE. The CPIE score had the highest direct relationship with grade point average (GPA) of apprenticeship course, total GPA of all three courses, GPAs of physiopathology and basic sciences courses, and score of comprehensive basic sciences examination, respectively. CPIE showed the highest inverse correlation with the number of failed units in apprenticeship course. The most important factors influencing this exam were failure in apprenticeship course and GPA of previous educational stages.

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

NASA Astrophysics Data System (ADS)

Ruan, Qingsong; Yang, Bingchan

2017-10-01

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

Factors associated with negative T-SPOT.TB results among smear-negative tuberculosis patients in China.

PubMed

Kang, Wanli; Wu, Meiying; Yang, Kunyun; Ertai, A; Wu, Shucai; Geng, Shujun; Li, Zhihui; Li, Mingwu; Pang, Yu; Tang, Shenjie

2018-03-09

We compared the positive rates of T-SPOT.TB and bacterial culture in the smear-negative PTB, and analyzed the factors affecting the results of negative T-SPOT.TB and bacterial culture. Retrospective evaluation of data from smear-negative PTB patients who underwent T-SPOT.TB and bacterial culture were done. The agreement and concordance were analyzed between T-SPOT.TB and bacterial culture. Multivariable logistic regression analysis was used to explore the factors associated with positive results of T-SPOT.TB and bacterial culture in smear-negative PTB. 858 eligible smear-negative PTB patients were included in the study. The agreement rate was 25.6% (22.7~28.5%) between T-SPOT.TB and bacterial culture in smear- negative PTB patients. The positive rate of T-SPOT.TB was higher than that of bacterial culture in smear-negative PTB patients (p < 0.001). There were nearly no concordance between T-SPOT.TB and bacterial culture (p > 0.05). Using multivariable logistic regression analysis we found that older age ≥ 60 years (OR = 0.469, 95% CI: 0.287-0.768) and decreased albumin (OR = 0.614, 95% CI: 0.380-0.992) were associated with negative diagnostic results of T-SPOT.TB in smear-negative PTB patients. Female (OR = 0.654, 95% CI: 0.431-0.992) were associated with negative diagnostic results of bacteria culture in smear-negative PTB patients. Our results indicated that the older age and decreased albumin were independently associated with negative T-SPOT.TB responses.

[Risk factors in the results of the colour vision test Roth 28-hue (E) desaturated in glaucoma patients].

PubMed

Jass, C M; Böhringer, D; Erb, C; Jordan, J F

2013-11-01

Glaucoma is an ocular disease with typical progressive damage of the optic nerve. In the past it was postulated that glaucoma induces acquired colour vision disorders. Until now all studies about glaucoma and colour vision disorders did not include vascular risk factors. In the present study we determined several vascular risk factors concerning the results of the colour vision test Roth 28-hue (E) desaturated in glaucoma patients. On the basis of an analysis of variance (ANOVA) we determined the influence of several risk factors, such as arteriosclerotic and vasospastic risk factors, on the results of the colour vision test Roth 28-hue (E) desaturated in glaucoma patients. 353 glaucoma patients were included in this study. We detected a strong influence of age and mean defect in perimetry and an additional effect of arteriosclerotic and vasospastic risk factors on the results of the colour vision test Roth 28-hue (E) desaturated in glaucoma patients. We suspect that arteriosclerotic and vasospastic risk factors independently to glaucoma have an influence on colour vision. In the future attention additionally has to be given to vascular risk factors in the colour vision testing of glaucoma patients. Georg Thieme Verlag KG Stuttgart · New York.

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.

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

ERIC Educational Resources Information Center

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

2010-01-01

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

The 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)

Causes of death and competing risk analysis of the associated factors for non-small cell lung cancer using the Surveillance, Epidemiology, and End Results database.

PubMed

Wei, Shenhai; Tian, Jintao; Song, Xiaoping; Wu, Bingqun; Liu, Limin

2018-01-01

To investigate the probability of death (POD) from any causes by time after diagnosis of non-small cell lung cancer (NSCLC) and the factors associated with survival for NSCLC patients. A total of 202,914 patients with NSCLC from 2004 to 2013 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. The overall survival (OS) and lung cancer-specific survival (LCSS) were calculated and POD from any causes at different time periods after diagnosis was explored. The predictive factors for OS, LCSS and survival from non-lung cancer deaths were investigated using multivariate analysis with Cox proportional hazards regression and competing risk regression analysis. The 5- and 10-year OS were 20.4% and 11.5%, accordingly that for LCSS were 25.5% and 18.4%, respectively. Lung cancer contributed 88.3% (n = 128,402) of the deaths. The POD from lung cancer decreased with time after diagnosis. In multivariate analysis, advanced age and advanced stage of NSCLC were associated with decreased OS and LCSS. Comparing to no surgery, any kind of resection conferred lower risk of death from lung cancer and higher risk of dying from non-lung cancer conditions except lobectomy or bilobectomy, which was associated with lower risk of death from both lung cancer and non-lung cancer conditions. Most of the patients with NSCLC died from lung cancer. Rational surveillance and treatment policies should be made for them. Early stage and lobectomy or bilobectomy were associated with improved OS and LCSS. It is reasonable to focus on early detection and optimal surgical treatment for NSCLC.

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

ERIC Educational Resources Information Center

Reilly, Amysue; Eaves, Ronald C.

2000-01-01

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

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 plasma filling factor of coronal bright points. II. Combined EIS and TRACE results

NASA Astrophysics Data System (ADS)

Dere, K. P.

2009-04-01

Aims: In a previous paper, the volumetric plasma filling factor of coronal bright points was determined from spectra obtained with the Extreme ultraviolet Imaging Spectrometer (EIS). The analysis of these data showed that the median plasma filling factor was 0.015. One interpretation of this result was that the small filling factor was consistent with a single coronal loop with a width of 1-2´´, somewhat below the apparent width. In this paper, higher spatial resolution observations with the Transition Region and Corona Explorer (TRACE) are used to test this interpretation. Methods: Rastered spectra of regions of the quiet Sun were recorded by the EIS during operations with the Hinode satellite. Many of these regions were simultaneously observed with TRACE. Calibrated intensities of Fe xii lines were obtained and images of the quiet corona were constructed from the EIS measurements. Emission measures were determined from the EIS spectra and geometrical widths of coronal bright points were obtained from the TRACE images. Electron densities were determined from density-sensitive line ratios measured with EIS. A comparison of the emission measure and bright point widths with the electron densities yielded the plasma filling factor. Results: The median electron density of coronal bright points is 3 × 109 cm-3 at a temperature of 1.6 × 106 K. The volumetric plasma filling factor of coronal bright points was found to vary from 3 × 10-3 to 0.3 with a median value of 0.04. Conclusions: The current set of EIS and TRACE coronal bright-point observations indicate the median value of their plasma filling factor is 0.04. This can be interpreted as evidence of a considerable subresolution structure in coronal bright points or as the result of a single completely filled plasma loop with widths on the order of 0.2-1.5´´ that has not been spatially resolved in these measurements.

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

NASA Astrophysics Data System (ADS)

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

2010-03-01

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

A Human Factors Analysis of Proactive Support in Human-Robot Teaming

DTIC Science & Technology

2015-09-28

teammate is remotely controlling a robot while working with an intelligent robot teammate ‘Mary’. Our main result shows that the subjects generally...IEEE/RSJ Intl. Conference on Intelligent Robots and Systems Conference Date: September 28, 2015 A Human Factors Analysis of Proactive Support in Human...human teammate is remotely controlling a robot while working with an intelligent robot teammate ‘Mary’. Our main result shows that the subjects

Confirmatory factors analysis of science teacher leadership in the Thailand world-class standard schools

NASA Astrophysics Data System (ADS)

Thawinkarn, Dawruwan

2018-01-01

This research aims to analyze factors of science teacher leadership in the Thailand World-Class Standard Schools. The research instrument was a five scale rating questionnaire with reliability 0.986. The sample group included 500 science teachers from World-Class Standard Schools who had been selected by using the stratified random sampling technique. Factor analysis of science teacher leadership in the Thailand World-Class Standard Schools was conducted by using M plus for Windows. The results are as follows: The results of confirmatory factor analysis on science teacher leadership in the Thailand World-Class Standard Schools revealed that the model significantly correlated with the empirical data. The consistency index value was x2 = 105.655, df = 88, P-Value = 0.086, TLI = 0.997, CFI = 0.999, RMSEA = 0.022, and SRMR = 0.019. The value of factor loading of science teacher leadership was positive, with statistical significance at the level of 0.01. The value of six factors was between 0.880-0.996. The highest factor loading was the professional learning community, followed by child-centered instruction, participation in development, the role model in teaching, transformational leaders, and self-development with factor loading at 0.996, 0.928, 0.911, 0.907, 0.901, and 0.871, respectively. The reliability of each factor was 99.1%, 86.0%, 83.0%, 82.2%, 81.0%, and 75.8%, respectively.

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.

Psychosocial factors at work and self reported health: comparative results of cross sectional and prospective analyses of the French GAZEL cohort

PubMed Central

Niedhammer, I; Chea, M

2003-01-01

Background: Psychosocial factors at work have been found to be significant contributors to health, especially cardiovascular health. Aims: To explore the relation between psychosocial factors at work and self reported health, using cross sectional and prospective analyses for a large occupational cohort of men and women. Methods: Psychosocial factors at work were evaluated using the Karasek questionnaire, designed to measure psychological demands, decision latitude, social support, and physical demands. Self reported health was used as health outcome. Covariates included chronic diseases, and sociodemographic, occupational, and behavioural factors. The cross sectional and prospective analyses concerned respectively 11 447 and 7664 workers. Men and women were analysed separately. Results: Cross sectional analysis revealed significant associations between psychological demands, decision latitude, social support, and physical demands, and self reported health for both men and women. Prospective analysis showed that high psychological demands for both genders, low decision authority for men, and low social support and high physical demands for women were predictive of poor self reported health. These results were independent of potential confounding variables. Conclusions: Results highlight the predictive effects of psychosocial factors at work on self reported health in a one year follow up study. They also underline the need for longitudinal study design and separate analyses for men and women in the field of psychosocial factors at work. PMID:12819285

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

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Factors for Success: Academic Library Development Survey Results.

ERIC Educational Resources Information Center

Hoffman, Irene M.; Smith, Amy; DiBona, Leslie

2000-01-01

Discusses the results of a nationwide survey (57 survey questions) of academic libraries that investigated fund-raising programs, including personnel involved; goals and costs of fund-raising; library donors, friends, and advisory groups; priorities; and factors of success, including involvement of the director and time on task. A copy of the…

Statistical Analysis of NAS Parallel Benchmarks and LINPACK Results

NASA Technical Reports Server (NTRS)

Meuer, Hans-Werner; Simon, Horst D.; Strohmeier, Erich; Lasinski, T. A. (Technical Monitor)

1994-01-01

In the last three years extensive performance data have been reported for parallel machines both based on the NAS Parallel Benchmarks, and on LINPACK. In this study we have used the reported benchmark results and performed a number of statistical experiments using factor, cluster, and regression analyses. In addition to the performance results of LINPACK and the eight NAS parallel benchmarks, we have also included peak performance of the machine, and the LINPACK n and n(sub 1/2) values. Some of the results and observations can be summarized as follows: 1) All benchmarks are strongly correlated with peak performance. 2) LINPACK and EP have each a unique signature. 3) The remaining NPB can grouped into three groups as follows: (CG and IS), (LU and SP), and (MG, FT, and BT). Hence three (or four with EP) benchmarks are sufficient to characterize the overall NPB performance. Our poster presentation will follow a standard poster format, and will present the data of our statistical analysis in detail.

Clinical and atopic parameters and airway inflammatory markers in childhood asthma: a factor analysis

PubMed Central

Leung, T; Wong, G; Ko, F; Lam, C; Fok, T

2005-01-01

Background: Recent studies have repeatedly shown weak correlations among lung function parameters, atopy, exhaled nitric oxide level (FeNO), and airway inflammatory markers, suggesting that they are non-overlapping characteristics of asthma in adults. A study was undertaken to determine, using factor analysis, whether the above features represent separate dimensions of childhood asthma. Methods: Clinically stable asthmatic patients aged 7–18 years underwent spirometric testing, methacholine bronchial challenge, blood sampling for atopy markers and chemokine levels (macrophage derived chemokine (MDC), thymus and activation regulated chemokine (TARC), and eotaxin), FeNO, and chemokines (MDC and eotaxin) and leukotriene B4 measurements in exhaled breath condensate (EBC). Results: The mean (SD) forced expiratory volume in 1 second (FEV1) and FeNO of 92 patients were 92.1 (15.9)% predicted and 87.3 (65.7) ppb, respectively. 59% of patients received inhaled corticosteroids. Factor analysis selected four different factors, explaining 55.5% of total variance. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.587. Plasma total and specific IgE levels, peripheral blood eosinophil percentage, and FeNO loaded on factor 1; plasma TARC and MDC concentrations on factor 2; MDC, eotaxin and leukotriene B4 concentrations in EBC on factor 3; and plasma eotaxin concentration together with clinical indices including body mass index and disease severity score loaded on factor 4. Post hoc factor analyses revealed similar results when outliers were excluded. Conclusions: The results suggest that atopy related indices and airway inflammation are separate dimensions in the assessment of childhood asthma, and inflammatory markers in peripheral blood and EBC are non-overlapping factors of asthma. PMID:16055623

Using decision tree analysis to identify risk factors for relapse to smoking

PubMed Central

Piper, Megan E.; Loh, Wei-Yin; Smith, Stevens S.; Japuntich, Sandra J.; Baker, Timothy B.

2010-01-01

This research used classification tree analysis and logistic regression models to identify risk factors related to short- and long-term abstinence. Baseline and cessation outcome data from two smoking cessation trials, conducted from 2001 to 2002, in two Midwestern urban areas, were analyzed. There were 928 participants (53.1% women, 81.8% white) with complete data. Both analyses suggest that relapse risk is produced by interactions of risk factors and that early and late cessation outcomes reflect different vulnerability factors. The results illustrate the dynamic nature of relapse risk and suggest the importance of efficient modeling of interactions in relapse prediction. PMID:20397871

A replication of a factor analysis of motivations for trapping

USGS Publications Warehouse

Schroeder, Susan; Fulton, David C.

2015-01-01

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

[Analysis of characteristics and influence factors of diagnostic delay of endometriosis].

PubMed

Han, X T; Guo, H Y; Kong, D L; Han, J S; Zhang, L F

2018-02-25

Objective: To access the influence factors of diagnostic delay of endometriosis. Methods: We designed a questionnaire of diagnostic delay of endometriosis. From February 2014 to February 2016, 400 patients who had dysmenorrhea and diagnosed with endometriosis by surgery in Peking University Third Hospital were surveyed retrospectively. Time and risk factors of diagnostic delay were analyzed. Results: The diagnostic delay of 400 patients was 13.0 years (0.2-43.0 years), 78.5%(314/400) patients thought pain was a normal phenomenon and didn't see the doctor. Patients who suffered dysmenorrhea at menarche experienced longer diagnostic delay than those who had dysmenorrhea after menarche (18.0 vs 4.5 years; Z= 191.800, P< 0.01) . Patients who suffered aggravating dysmenorrhea experienced shorter delay time than those who suffered stable or relieving dysmenorrhea (11.0 vs 12.5 vs 18.0 years; Z= 8.270, P< 0.05) , with the difference statistically significant, single factor analysis shows. Severe dysmenorrhea, deep infiltration endometriosis (DIE) , family history of dysmenorrhea or endometriosis, previous surgical history of endometriosis, high stage, with infertility, adenomyoma or other symptoms, could help to shorten diagnostic delay with no significant difference ( P> 0.05) . By multiple logistic regression analysis, the results shown that whether have dysmenorrhea at menarche and clinical diagnosis time were the independent factors affecting delayed diagnosis ( P< 0.01) . Conclusions: Diagnostic delay of endometriosis is common and the mean delay time is 13.0 years mainly due to the unawareness of dysmenorrhea. Dysmenorrhea at menarche, clinical diagnosis time and dysmenorrhea intensity are the factors affecting time of diagnostic delay.

An Exploratory Factor Analysis of the URICA among Couple Therapy Participants

ERIC Educational Resources Information Center

Tambling, Rachel B.; Johnson, Lee N.

2012-01-01

Assessing and measuring client motivation to change has been of great interest to therapists and researchers in a variety of fields. This article presents the results of an exploratory factor analysis of the University of Rhode Island Change Assessment (URICA), a measure of motivation to change, in a sample of individuals in couple therapy. Four…

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.

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

PubMed

Wang, H-Y; Lin, C-K

2015-10-01

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

Exploratory factor analysis of the Research and Development Culture Index among qualified nurses.

PubMed

Watson, Bill; Clarke, Charlotte; Swallow, Vera; Forster, Stewart

2005-10-01

This paper presents the exploratory factor analysis of a rating instrument for assessing the strength of organizational Research and Development (R&D) culture. Despite nursing's limited research capacity, the discipline is capitalizing upon opportunities to become involved in research and is making strong progress. Within the context of the debate on nursing research capacity, the R&D Culture Index was developed as a means of appraising R&D culture within health care organizations. Factor analysis was carried out on data collected from 485 nursing staff. The method of extraction was Principal Components Analysis with oblique rotation. The Index was developed from the findings of qualitative research conducted with NHS staff. Eighteen items, encompassing the main themes from the data, were initially included in the Index. This pilot instrument was distributed to nursing staff within three different types of NHS Trust. Factor analysis resulted in rejection of two items and the analysis was repeated using the remaining 16 items. Three latent factors were extracted accounting for 58.0% of the variance in the data. The factors were: R&D Support, describing the perceived support within the working environment for R&D activity; Personal R&D Skills and Aptitude, describing an individual's perception of their ability towards R&D activity; and Personal R&D Intention, describing an individual's willingness to engage in R&D activity. Each factor had good internal reliability, as did the overall index. The R&D Culture Index provides an efficient means of assessing the strength of an organization's R&D culture in a way that captures the role of the individual practitioner and the organizational environment. These findings suggest that the continuing promotion of R&D within health care organizations is dependent upon a multi-faceted approach that addresses the learning needs of the organization as well as those of the individual practitioners.

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

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.

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

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.

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

PubMed

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

2013-12-01

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

Analysis of functional redundancies within the Arabidopsis TCP transcription factor family

PubMed Central

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

2013-01-01

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

Bayesian Factor Analysis When Only a Sample Covariance Matrix Is Available

ERIC Educational Resources Information Center

Hayashi, Kentaro; Arav, Marina

2006-01-01

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

Evaluation of Parallel Analysis Methods for Determining the Number of Factors

ERIC Educational Resources Information Center

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

2010-01-01

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

Measurement Structure of the Trait Hope Scale in Persons with Spinal Cord Injury: A Confirmatory Factor Analysis

ERIC Educational Resources Information Center

Smedema, Susan Miller; Pfaller, Joseph; Moser, Erin; Tu, Wei-Mo; Chan, Fong

2013-01-01

Objective: To evaluate the measurement structure of the Trait Hope Scale (THS) among individuals with spinal cord injury. Design: Confirmatory factor analysis and reliability and validity analyses were performed. Participants: 242 individuals with spinal cord injury. Results: Results support the two-factor measurement model for the THS with agency…

Prognostic factors in left-sided endocarditis: results from the Andalusian multicenter cohort.

PubMed

Gálvez-Acebal, Juan; Rodríguez-Baño, Jesús; Martínez-Marcos, Francisco J; Reguera, Jose M; Plata, Antonio; Ruiz, Josefa; Marquez, Manuel; Lomas, Jose M; de la Torre-Lima, Javier; Hidalgo-Tenorio, Carmen; de Alarcón, Arístides

2010-01-22

Despite medical advances, mortality in infective endocarditis (IE) is still very high. Previous studies on prognosis in IE have observed conflicting results. The aim of this study was to identify predictors of in-hospital mortality in a large multicenter cohort of left-sided IE. An observational multicenter study was conducted from January 1984 to December 2006 in seven hospitals in Andalusia, Spain. Seven hundred and five left-side IE patients were included. The main outcome measure was in-hospital mortality. Several prognostic factors were analysed by univariate tests and then by multilogistic regression model. The overall mortality was 29.5% (25.5% from 1984 to 1995 and 31.9% from 1996 to 2006; Odds Ratio 1.25; 95% Confidence Interval: 0.97-1.60; p = 0.07). In univariate analysis, age, comorbidity, especially chronic liver disease, prosthetic valve, virulent microorganism such as Staphylococcus aureus, Streptococcus agalactiae and fungi, and complications (septic shock, severe heart failure, renal insufficiency, neurologic manifestations and perivalvular extension) were related with higher mortality. Independent factors for mortality in multivariate analysis were: Charlson comorbidity score (OR: 1.2; 95% CI: 1.1-1.3), prosthetic endocarditis (OR: 1.9; CI: 1.2-3.1), Staphylococcus aureus aetiology (OR: 2.1; CI: 1.3-3.5), severe heart failure (OR: 5.4; CI: 3.3-8.8), neurologic manifestations (OR: 1.9; CI: 1.2-2.9), septic shock (OR: 4.2; CI: 2.3-7.7), perivalvular extension (OR: 2.4; CI: 1.3-4.5) and acute renal failure (OR: 1.69; CI: 1.0-2.6). Conversely, Streptococcus viridans group etiology (OR: 0.4; CI: 0.2-0.7) and surgical treatment (OR: 0.5; CI: 0.3-0.8) were protective factors. Several characteristics of left-sided endocarditis enable selection of a patient group at higher risk of mortality. This group may benefit from more specialised attention in referral centers and should help to identify those patients who might benefit from more aggressive diagnostic

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

PubMed

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

2016-10-01

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

Lack of efficacy of resveratrol on C-reactive protein and selected cardiovascular risk factors--Results from a systematic review and meta-analysis of randomized controlled trials.

PubMed

Sahebkar, Amirhossein; Serban, Corina; Ursoniu, Sorin; Wong, Nathan D; Muntner, Paul; Graham, Ian M; Mikhailidis, Dimitri P; Rizzo, Manfredi; Rysz, Jacek; Sperling, Laurence S; Lip, Gregory Y H; Banach, Maciej

2015-01-01

Numerous studies have suggested that oral supplementation with resveratrol exerts cardioprotective effects, but evidence of the effects on C-reactive protein (CRP) plasma levels and other cardiovascular (CV) risk factors is inconclusive. Therefore, we performed a meta-analysis to evaluate the efficacy of resveratrol supplementation on plasma CRP concentrations and selected predictors of CV risk. The search included PUBMED, Cochrane Library, Web of Science, Scopus, and EMBASE (up to August 31, 2014) to identify RCTs investigating the effects of resveratrol supplementation on selected CV risk factors. Quantitative data synthesis was performed using a random-effects model, with weighted mean difference (WMD) and 95% confidence intervals (CI) as summary statistics. Meta-analysis of data from 10 RCTs (11 treatment arms) did not support a significant effect of resveratrol supplementation in altering plasma CRP concentrations (WMD: -0.144 mg/L, 95% CI: -0.968-0.680, p = 0.731). Resveratrol supplementation was not found to alter plasma levels of total cholesterol (WMD: 1.49 mg/dL, 95% CI: -14.96-17.93, p = 0.859), low density lipoprotein cholesterol (WMD: -0.31 mg/dL, 95% CI: -9.57-8.95, p = 0.948), triglycerides (WMD: 2.67 mg/dL, 95% CI: -28.34-33.67, p = 0.866), and glucose (WMD: 1.28 mg/dL, 95% CI: -5.28-7.84, p = 0.703). It also slightly reduced high density lipoprotein cholesterol concentrations (WMD: -4.18 mg/dL, 95% CI: -6.54 to -1.82, p = 0.001). Likewise, no significant effect was observed on systolic (WMD: 0.82 mmHg, 95% CI: -8.86-10.50, p = 0.868) and diastolic blood pressure (WMD: 1.72 mm Hg, 95% CI: -6.29-9.73, p=0.674). This meta-analysis of available RCTs does not suggest any benefit of resveratrol supplementation on CV risk factors. Larger, well-designed trials are necessary to confirm these results. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Confirmatory Factor Analysis of the WHO Violence Against Women Instrument in Pregnant Women: Results from the BRISA Prenatal Cohort

PubMed Central

Ribeiro, Marizélia Rodrigues Costa; Alves, Maria Teresa Seabra Soares de Britto e.; Batista, Rosângela Fernandes Lucena; Ribeiro, Cecília Cláudia Costa; Schraiber, Lilia Blima; Barbieri, Marco Antônio; Bettiol, Heloisa; da Silva, Antônio Augusto Moura

2014-01-01

Background Screening for violence during pregnancy is one of the strategies for the prevention of abuse against women. Since violence is difficult to measure, it is necessary to validate questionnaires that can provide a good measure of the phenomenon. The present study analyzed the psychometric properties of the World Health Organization Violence Against Women (WHO VAW) instrument for the measurement of violence against pregnant women. Methods Data from the Brazilian Ribeirão Preto and São Luís birth cohort studies (BRISA) were used. The sample consisted of 1,446 pregnant women from São Luís and 1,378 from Ribeirão Preto, interviewed in 2010 and 2011. Thirteen variables were selected from a self-applied questionnaire. Confirmatory factor analysis was used to investigate whether violence is a uni-or-multidimensional construct consisting of psychological, physical and sexual dimensions. The mean-and-variance-adjusted weighted least squares estimator was used. Models were fitted separately for each city and a third model combining data from the two settings was also tested. Models suggested from modification indices were tested to determine whether changes in the WHO VAW model would produce a better fit. Results The unidimensional model did not show good fit (Root mean square error of approximation [RMSEA]  = 0.060, p<0.001 for the combined model). The multidimensional WHO VAW model showed good fit (RMSEA = 0.036, p = 0.999 for the combined model) and standardized factor loadings higher than 0.70, except for the sexual dimension for SL (0.65). The models suggested by the modification indices with cross loadings measuring simultaneously physical and psychological violence showed a significantly better fit compared to the original WHO model (p<0.001 for the difference between the model chi-squares). Conclusions Violence is a multidimensional second-order construct consisting of psychological, physical and sexual dimensions. The WHO VAW model and the

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.

Confirmatory Factor Analysis of a Questionnaire Measure of Managerial Stigma Towards Employee Depression.

PubMed

Martin, Angela J; Giallo, Rebecca

2016-12-01

Managers' attitudes play a key role in how organizations respond to employees with depression. We examine the measurement properties of a questionnaire designed to assess managerial stigma towards employees with depression. Using data from a sample of 469 Australian managers representing a wide range of industries and work settings, we conducted a confirmatory factor analysis to assess three proposed subscales representing affective, cognitive and behavioural forms of stigma. Results were equivocal indicating acceptable fit for two-factor (affective and cognitive + behavioural), three-factor (affective, cognitive and behavioural) and higher order models. Failure to demonstrate the discriminant validity of the cognitive and behavioural dimensions, even though they are theoretically distinct, suggests that further work on the scale is warranted. These results provide an extension to the psychometric profile of this measure (exploratory factor analysis; Martin, ). Development of strategies to operationalize this construct will benefit occupational health research and practice, particularly in interventions that aim to reduce the stigma of mental health issues in the workplace or where managers' attitudes are a key mechanism in intervention efficacy. We encourage future research on this measure pertaining in particular to further enhancing all aspects of its construct validity. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

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

PubMed

Kobayashi, Takumi; Tanaka, Masashi; Shida, Masahiro

2016-01-01

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

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…

BFDCA: A Comprehensive Tool of Using Bayes Factor for Differential Co-Expression Analysis.

PubMed

Wang, Duolin; Wang, Juexin; Jiang, Yuexu; Liang, Yanchun; Xu, Dong

2017-02-03

Comparing the gene-expression profiles between biological conditions is useful for understanding gene regulation underlying complex phenotypes. Along this line, analysis of differential co-expression (DC) has gained attention in the recent years, where genes under one condition have different co-expression patterns compared with another. We developed an R package Bayes Factor approach for Differential Co-expression Analysis (BFDCA) for DC analysis. BFDCA is unique in integrating various aspects of DC patterns (including Shift, Cross, and Re-wiring) into one uniform Bayes factor. We tested BFDCA using simulation data and experimental data. Simulation results indicate that BFDCA outperforms existing methods in accuracy and robustness of detecting DC pairs and DC modules. Results of using experimental data suggest that BFDCA can cluster disease-related genes into functional DC subunits and estimate the regulatory impact of disease-related genes well. BFDCA also achieves high accuracy in predicting case-control phenotypes by using significant DC gene pairs as markers. BFDCA is publicly available at http://dx.doi.org/10.17632/jdz4vtvnm3.1. Copyright © 2016 Elsevier Ltd. All rights reserved.

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…

[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.

An empirical examination of WISE/NEOWISE asteroid analysis and results

NASA Astrophysics Data System (ADS)

Myhrvold, Nathan

2017-10-01

Observations made by the WISE space telescope and subsequent analysis by the NEOWISE project represent the largest corpus of asteroid data to date, describing the diameter, albedo, and other properties of the ~164,000 asteroids in the collection. I present a critical reanalysis of the WISE observational data, and NEOWISE results published in numerous papers and in the JPL Planetary Data System (PDS). This analysis reveals shortcomings and a lack of clarity, both in the original analysis and in the presentation of results. The procedures used to generate NEOWISE results fall short of established thermal modelling standards. Rather than using a uniform protocol, 10 modelling methods were applied to 12 combinations of WISE band data. Over half the NEOWISE results are based on a single band of data. Most NEOWISE curve fits are poor quality, frequently missing many or all the data points. About 30% of the single-band results miss all the data; 43% of the results derived from the most common multiple-band combinations miss all the data in at least one band. The NEOWISE data processing procedures rely on inconsistent assumptions, and introduce bias by systematically discarding much of the original data. I show that error estimates for the WISE observational data have a true uncertainty factor of ~1.2 to 1.9 times larger than previously described, and that the error estimates do not fit a normal distribution. These issues call into question the validity of the NEOWISE Monte-Carlo error analysis. Comparing published NEOWISE diameters to published estimates using radar, occultation, or spacecraft measurements (ROS) reveals 150 for which the NEOWISE diameters were copied exactly from the ROS source. My findings show that the accuracy of diameter estimates for NEOWISE results depend heavily on the choice of data bands and model. Systematic errors in the diameter estimates are much larger than previously described. Systematic errors for diameters in the PDS range from -3% to

Postoperative Strontium-90 Brachytherapy in the Prevention of Keloids: Results and Prognostic Factors

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

Viani, Gustavo A.; Stefano, Eduardo J.; Afonso, Sergio L.

2009-04-01

Purpose: The aim of this study was to evaluate the results of keloidectomy and strontium 90 brachytherapy in the prevention of keloid recurrence following excision and to identify outcome and the prognostic factors that predict keloid recurrence after irradiation. Methods and Materials: Data of 612 patients with 892 keloids treated between 1992 and 2006 were evaluated retrospectively. Brachytherapy was performed using a Sr-90Y surface applicator. Total dose was 20 Gy in 10 fractions. Results: With a median follow-up of 61 months, the overall recurrence-free response rate for all keloids was 87.6%. Multivariate analysis revealed the following prognostic factors for recurrence:more » keloid size > 5 cm (p < 0.0001), burn scars as the keloid etiology (p < 0.0001), and previous treatment (p < 0.0001). Outcome was not found to be significantly related to the interval between surgery and radiotherapy, sex, or age. Pruritus and skin reddening were the most common symptoms of keloids, but all signs and symptoms abated with time after treatment. Cosmetic results from the keloid treatment were considered good or excellent in 70.6% of the patients. Conclusion: Our study findings show that excision plus Sr-90 brachytherapy is effective in the eradication of keloids. Sr-90 radiotherapy (20 Gy in 10 fractions) achieved a similar local control rate, as have higher doses per fraction in other series. It also resulted in a good cosmetic rate and relief of symptoms. Our data further suggest that the initiation of postoperative irradiation within hours of surgical excision is not important to therapeutic outcome.« less

Analysis of Factors Influencing Creative Personality of Elementary School Students

ERIC Educational Resources Information Center

Park, Jongman; Kim, Minkee; Jang, Shinho

2017-01-01

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

Generalized five-dimensional dynamic and spectral factor analysis

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

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

2006-04-15

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

Analysis of Risk Factors for Postoperative Morbidity in Perforated Peptic Ulcer

PubMed Central

Kim, Jae-Myung; Jeong, Sang-Ho; Park, Soon-Tae; Choi, Sang-Kyung; Hong, Soon-Chan; Jung, Eun-Jung; Ju, Young-Tae; Jeong, Chi-Young; Ha, Woo-Song

2012-01-01

Purpose Emergency operations for perforated peptic ulcer are associated with a high incidence of postoperative complications. While several studies have investigated the impact of perioperative risk factors and underlying diseases on the postoperative morbidity after abdominal surgery, only a few have analyzed their role in perforated peptic ulcer disease. The purpose of this study was to determine any possible associations between postoperative morbidity and comorbid disease or perioperative risk factors in perforated peptic ulcer. Materials and Methods In total, 142 consecutive patients, who underwent surgery for perforated peptic ulcer, at a single institution, between January 2005 and October 2010 were included in this study. The clinical data concerning the patient characteristics, operative methods, and complications were collected retrospectively. Results The postoperative morbidity rate associated with perforated peptic ulcer operations was 36.6% (52/142). Univariate analysis revealed that a long operating time, the open surgical method, age (≥60), sex (female), high American Society of Anesthesiologists (ASA) score and presence of preoperative shock were significant perioperative risk factors for postoperative morbidity. Significant comorbid risk factors included hypertension, diabetes mellitus and pulmonary disease. Multivariate analysis revealed a long operating time, the open surgical method, high ASA score and the presence of preoperative shock were all independent risk factors for the postoperative morbidity in perforated peptic ulcer. Conclusions A high ASA score, preoperative shock, open surgery and long operating time of more than 150 minutes are high risk factors for morbidity. However, there is no association between postoperative morbidity and comorbid disease in patients with a perforated peptic ulcer. PMID:22500261

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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...

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

PubMed Central

Vahedi, Shahram; Farrokhi, Farahman

2011-01-01

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

Factor analysis and predictive validity of microcomputer-based tests

NASA Technical Reports Server (NTRS)

Kennedy, R. S.; Baltzley, D. R.; Turnage, J. J.; Jones, M. B.

1989-01-01

11 tests were selected from two microcomputer-based performance test batteries because previously these tests exhibited rapid stability (less than 10 min, of practice) and high retest reliability efficiencies (r greater than 0.707 for each 3 min. of testing). The battery was administered three times to each of 108 college students (48 men and 60 women) and a factor analysis was performed. Two of the three identified factors appear to be related to information processing ("encoding" and "throughput/decoding"), and the third named an "output/speed" factor. The spatial, memory, and verbal tests loaded on the "encoding" factor and included Grammatical Reasoning, Pattern Comparison, Continuous Recall, and Matrix Rotation. The "throughput/decoding" tests included perceptual/numerical tests like Math Processing, Code Substitution, and Pattern Comparison. The output speed factor was identified by Tapping and Reaction Time tests. The Wonderlic Personnel Test was group administered before the first and after the last administration of the performance tests. The multiple Rs in the total sample between combined Wonderlic as a criterion and less than 5 min. of microcomputer testing on Grammatical Reasoning and Math Processing as predictors ranged between 0.41 and 0.52 on the three test administrations. Based on these results, the authors recommend a core battery which, if time permits, would consist of two tests from each factor. Such a battery is now known to permit stable, reliable, and efficient assessment.

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.

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

Factors Associated With Burnout Among US Hospital Clinical Pharmacy Practitioners: Results of a Nationwide Pilot Survey.

PubMed

Jones, G Morgan; Roe, Neil A; Louden, Les; Tubbs, Crystal R

2017-12-01

Background: In health care, burnout has been defined as a psychological process whereby human service professionals attempting to positively impact the lives of others become overwhelmed and frustrated by unforeseen job stressors. Burnout among various physician groups who primarily practice in the hospital setting has been extensively studied; however, no evidence exists regarding burnout among hospital clinical pharmacists. Objective: The aim of this study was to characterize the level of and identify factors independently associated with burnout among clinical pharmacists practicing in an inpatient hospital setting within the United States. Methods: We conducted a prospective, cross-sectional pilot study utilizing an online, Qualtrics survey. Univariate analysis related to burnout was conducted, with multivariable logistic regression analysis used to identify factors independently associated with the burnout. Results: A total of 974 responses were analyzed (11.4% response rate). The majority were females who had practiced pharmacy for a median of 8 years. The burnout rate was high (61.2%) and largely driven by high emotional exhaustion. On multivariable analysis, we identified several subjective factors as being predictors of burnout, including inadequate administrative and teaching time, uncertainty of health care reform, too many nonclinical duties, difficult pharmacist colleagues, and feeling that contributions are underappreciated. Conclusions: The burnout rate of hospital clinical pharmacy providers was very high in this pilot survey. However, the overall response rate was low at 11.4%. The negative effects of burnout require further study and intervention to determine the influence of burnout on the lives of clinical pharmacists and on other health care-related outcomes.

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

ERIC Educational Resources Information Center

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

1998-01-01

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

Automated pre-processing and multivariate vibrational spectra analysis software for rapid results in clinical settings

NASA Astrophysics Data System (ADS)

Bhattacharjee, T.; Kumar, P.; Fillipe, L.

2018-02-01

Vibrational spectroscopy, especially FTIR and Raman, has shown enormous potential in disease diagnosis, especially in cancers. Their potential for detecting varied pathological conditions are regularly reported. However, to prove their applicability in clinics, large multi-center multi-national studies need to be undertaken; and these will result in enormous amount of data. A parallel effort to develop analytical methods, including user-friendly software that can quickly pre-process data and subject them to required multivariate analysis is warranted in order to obtain results in real time. This study reports a MATLAB based script that can automatically import data, preprocess spectra— interpolation, derivatives, normalization, and then carry out Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) of the first 10 PCs; all with a single click. The software has been verified on data obtained from cell lines, animal models, and in vivo patient datasets, and gives results comparable to Minitab 16 software. The software can be used to import variety of file extensions, asc, .txt., .xls, and many others. Options to ignore noisy data, plot all possible graphs with PCA factors 1 to 5, and save loading factors, confusion matrices and other parameters are also present. The software can provide results for a dataset of 300 spectra within 0.01 s. We believe that the software will be vital not only in clinical trials using vibrational spectroscopic data, but also to obtain rapid results when these tools get translated into clinics.

Emotional Intelligence and Nurse Recruitment: Rasch and confirmatory factor analysis of the trait emotional intelligence questionnaire short form.

PubMed

Snowden, Austyn; Watson, Roger; Stenhouse, Rosie; Hale, Claire

2015-12-01

To examine the construct validity of the Trait Emotional Intelligence Questionnaire Short form. Emotional intelligence involves the identification and regulation of our own emotions and the emotions of others. It is therefore a potentially useful construct in the investigation of recruitment and retention in nursing and many questionnaires have been constructed to measure it. Secondary analysis of existing dataset of responses to Trait Emotional Intelligence Questionnaire Short form using concurrent application of Rasch analysis and confirmatory factor analysis. First year undergraduate nursing and computing students completed Trait Emotional Intelligence Questionnaire-Short Form in September 2013. Responses were analysed by synthesising results of Rasch analysis and confirmatory factor analysis. Participants (N = 938) completed Trait Emotional Intelligence Questionnaire Short form. Rasch analysis showed the majority of the Trait Emotional Intelligence Questionnaire-Short Form items made a unique contribution to the latent trait of emotional intelligence. Five items did not fit the model and differential item functioning (gender) accounted for this misfit. Confirmatory factor analysis revealed a four-factor structure consisting of: self-confidence, empathy, uncertainty and social connection. All five misfitting items from the Rasch analysis belonged to the 'social connection' factor. The concurrent use of Rasch and factor analysis allowed for novel interpretation of Trait Emotional Intelligence Questionnaire Short form. Much of the response variation in Trait Emotional Intelligence Questionnaire Short form can be accounted for by the social connection factor. Implications for practice are discussed. © 2015 John Wiley & Sons Ltd.

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

PubMed

Molenaar, Peter C M

2010-05-01

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

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

PubMed

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

2015-12-15

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

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.

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

PubMed

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

2018-04-29

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

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.

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

PubMed

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

2018-06-23

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

Sensitivity Analysis of the USLE Soil Erodibility Factor to Its Determining Parameters

NASA Astrophysics Data System (ADS)

Mitova, Milena; Rousseva, Svetla

2014-05-01

Soil erosion is recognized as one of the most serious soil threats worldwide. Soil erosion prediction is the first step in soil conservation planning. The Universal Soil Loss Equation (USLE) is one of the most widely used models for soil erosion predictions. One of the five USLE predictors is the soil erodibility factor (K-factor), which evaluates the impact of soil characteristics on soil erosion rates. Soil erodibility nomograph defines K-factor depending on soil characteristics, such as: particle size distribution (fractions finer that 0.002 mm and from 0.1 to 0.002 mm), organic matter content, soil structure and soil profile water permeability. Identifying the soil characteristics, which mostly influence the K-factor would give an opportunity to control the soil loss through erosion by controlling the parameters, which reduce the K-factor value. The aim of the report is to present the results of analysis of the relative weight of these soil characteristics in the K-factor values. The relative impact of the soil characteristics on K-factor was studied through a series of statistical analyses of data from the geographic database for soil erosion risk assessments in Bulgaria. Degree of correlation between K-factor values and the parameters that determine it was studied by correlation analysis. The sensitivity of the K-factor was determined by studying the variance of each parameter within the range between minimum and maximum possible values considering average value of the other factors. Normalizing transformation of data sets was applied because of the different dimensions and the orders of variation of the values of the various parameters. The results show that the content of particles finer than 0.002 mm has the most significant relative impact on the soil erodibility, followed by the content of particles with size from 0.1 mm to 0.002 mm, the class of the water permeability of the soil profile, the content of organic matter and the aggregation class. The

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

PubMed

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

2017-09-01

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

The Interest Checklist: a factor analysis.

PubMed

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

1997-01-01

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

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.

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

PubMed

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

2003-01-01

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

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

PubMed Central

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

2009-01-01

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

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.…

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

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

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.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Endovascular Treatment of Malignant Superior Vena Cava Syndrome: Results and Predictive Factors of Clinical Efficacy

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

Fagedet, Dorothee, E-mail: DFagedet@chu-grenoble.fr; Thony, Frederic, E-mail: FThony@chu-grenoble.fr; Timsit, Jean-Francois, E-mail: JFTimsit@chu-grenoble.fr

To demonstrate the effectiveness of endovascular treatment (EVT) with self-expandable bare stents for malignant superior vena cava syndrome (SVCS) and to analyze predictive factors of EVT efficacy. Retrospective review of the 164 patients with malignant SVCS treated with EVT in our hospital from August 1992 to December 2007 and followed until February 2009. Endovascular treatment includes angioplasty before and after stent placement. We used self-expandable bare stents. We studied results of this treatment and looked for predictive factors of clinical efficacy, recurrence, and complications by statistical analysis. Endovascular treatment was clinically successful in 95% of cases, with an acceptable ratemore » of early mortality (2.4%). Thrombosis of the superior vena cava was the only independent factor for EVT failure. The use of stents over 16 mm in diameter was a predictive factor for complications (P = 0.008). Twenty-one complications (12.8%) occurred during the follow-up period. Relapse occurred in 36 patients (21.9%), with effective restenting in 75% of cases. Recurrence of SVCS was significantly increased in cases of occlusion (P = 0.01), initial associated thrombosis (P = 0.006), or use of steel stents (P = 0.004). Long-term anticoagulant therapy did not influence the risk of recurrence or complications. In malignancy, EVT with self-expandable bare stents is an effective SVCS therapy. These results prompt us to propose treatment with stents earlier in the clinical course of patients with SVCS and to avoid dilatation greater than 16 mm.« less

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,…

46 CFR 164.007-7 - Analysis of results.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 46 Shipping 6 2013-10-01 2013-10-01 false Analysis of results. 164.007-7 Section 164.007-7...: SPECIFICATIONS AND APPROVAL MATERIALS Structural Insulations § 164.007-7 Analysis of results. (a) When only one sample is tested, the results of the test shall be binding and no analysis by the Coast Guard will be...

46 CFR 164.007-7 - Analysis of results.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 46 Shipping 6 2010-10-01 2010-10-01 false Analysis of results. 164.007-7 Section 164.007-7...: SPECIFICATIONS AND APPROVAL MATERIALS Structural Insulations § 164.007-7 Analysis of results. (a) When only one sample is tested, the results of the test shall be binding and no analysis by the Coast Guard will be...

46 CFR 164.007-7 - Analysis of results.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 46 Shipping 6 2011-10-01 2011-10-01 false Analysis of results. 164.007-7 Section 164.007-7...: SPECIFICATIONS AND APPROVAL MATERIALS Structural Insulations § 164.007-7 Analysis of results. (a) When only one sample is tested, the results of the test shall be binding and no analysis by the Coast Guard will be...

46 CFR 164.007-7 - Analysis of results.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 46 Shipping 6 2012-10-01 2012-10-01 false Analysis of results. 164.007-7 Section 164.007-7...: SPECIFICATIONS AND APPROVAL MATERIALS Structural Insulations § 164.007-7 Analysis of results. (a) When only one sample is tested, the results of the test shall be binding and no analysis by the Coast Guard will be...

46 CFR 164.007-7 - Analysis of results.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 46 Shipping 6 2014-10-01 2014-10-01 false Analysis of results. 164.007-7 Section 164.007-7...: SPECIFICATIONS AND APPROVAL MATERIALS Structural Insulations § 164.007-7 Analysis of results. (a) When only one sample is tested, the results of the test shall be binding and no analysis by the Coast Guard will be...

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

PubMed

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

2017-11-15

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

Postoperative strontium-90 brachytherapy in the prevention of keloids: results and prognostic factors.

PubMed

Viani, Gustavo A; Stefano, Eduardo J; Afonso, Sergio L; De Fendi, Ligia I

2009-04-01

The aim of this study was to evaluate the results of keloidectomy and strontium 90 brachytherapy in the prevention of keloid recurrence following excision and to identify outcome and the prognostic factors that predict keloid recurrence after irradiation. Data of 612 patients with 892 keloids treated between 1992 and 2006 were evaluated retrospectively. Brachytherapy was performed using a Sr-90Y surface applicator. Total dose was 20 Gy in 10 fractions. With a median follow-up of 61 months, the overall recurrence-free response rate for all keloids was 87.6%. Multivariate analysis revealed the following prognostic factors for recurrence: keloid size > 5 cm (p < 0.0001), burn scars as the keloid etiology (p < 0.0001), and previous treatment (p < 0.0001). Outcome was not found to be significantly related to the interval between surgery and radiotherapy, sex, or age. Pruritus and skin reddening were the most common symptoms of keloids, but all signs and symptoms abated with time after treatment. Cosmetic results from the keloid treatment were considered good or excellent in 70.6% of the patients. Our study findings show that excision plus Sr-90 brachytherapy is effective in the eradication of keloids. Sr-90 radiotherapy (20 Gy in 10 fractions) achieved a similar local control rate, as have higher doses per fraction in other series. It also resulted in a good cosmetic rate and relief of symptoms. Our data further suggest that the initiation of postoperative irradiation within hours of surgical excision is not important to therapeutic outcome.

Identification of Analytical Factors Affecting Complex Proteomics Profiles Acquired in a Factorial Design Study with Analysis of Variance: Simultaneous Component Analysis.

PubMed

Mitra, Vikram; Govorukhina, Natalia; Zwanenburg, Gooitzen; Hoefsloot, Huub; Westra, Inge; Smilde, Age; Reijmers, Theo; van der Zee, Ate G J; Suits, Frank; Bischoff, Rainer; Horvatovich, Péter

2016-04-19

Complex shotgun proteomics peptide profiles obtained in quantitative differential protein expression studies, such as in biomarker discovery, may be affected by multiple experimental factors. These preanalytical factors may affect the measured protein abundances which in turn influence the outcome of the associated statistical analysis and validation. It is therefore important to determine which factors influence the abundance of peptides in a complex proteomics experiment and to identify those peptides that are most influenced by these factors. In the current study we analyzed depleted human serum samples to evaluate experimental factors that may influence the resulting peptide profile such as the residence time in the autosampler at 4 °C, stopping or not stopping the trypsin digestion with acid, the type of blood collection tube, different hemolysis levels, differences in clotting times, the number of freeze-thaw cycles, and different trypsin/protein ratios. To this end we used a two-level fractional factorial design of resolution IV (2(IV)(7-3)). The design required analysis of 16 samples in which the main effects were not confounded by two-factor interactions. Data preprocessing using the Threshold Avoiding Proteomics Pipeline (Suits, F.; Hoekman, B.; Rosenling, T.; Bischoff, R.; Horvatovich, P. Anal. Chem. 2011, 83, 7786-7794, ref 1) produced a data-matrix containing quantitative information on 2,559 peaks. The intensity of the peaks was log-transformed, and peaks having intensities of a low t-test significance (p-value > 0.05) and a low absolute fold ratio (<2) between the two levels of each factor were removed. The remaining peaks were subjected to analysis of variance (ANOVA)-simultaneous component analysis (ASCA). Permutation tests were used to identify which of the preanalytical factors influenced the abundance of the measured peptides most significantly. The most important preanalytical factors affecting peptide intensity were (1) the hemolysis level

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…

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.

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

ERIC Educational Resources Information Center

Raykov, Tenko; Little, Todd D.

1999-01-01

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

Psychometric evaluation of the revised Illness Perception Questionnaire (IPQ-R) in cancer patients: confirmatory factor analysis and Rasch analysis.

PubMed

Ashley, Laura; Smith, Adam B; Keding, Ada; Jones, Helen; Velikova, Galina; Wright, Penny

2013-12-01

To provide new insights into the psychometrics of the revised Illness Perception Questionnaire (IPQ-R) in cancer patients. To undertake, for the first time using data from breast, colorectal and prostate cancer patients, a confirmatory factor analysis (CFA) to assess the validity of the IPQ-R's core seven-factor structure. Also, for the first time in any illness group, to undertake Rasch analysis to explore the extent to which the IPQ-R factors form unidimensional scales, with linear measurement properties and no Differential Item Functioning (DIF). Patients with potentially curable breast, colorectal or prostate cancer, within 6months post-diagnosis, completed the IPQ-R online (N=531). CFA was conducted, including multi-sample analysis, and for each IPQ-R factor fit to the Rasch model was assessed by examining, amongst other things, item fit, DIF and unidimensionality. The CFA showed a moderate fit of the data to the IPQ-R model, and stability across diagnosis, although fit was significantly improved following the removal of selected items. All seven factors achieved fit to the Rasch model, and exhibited unidimensionality and minimal DIF, although in most cases this was after some item rescoring and/or deletion. In both analyses, IPQ-R items 12, 18 and 24 were indicated as misfitting and removed. Given the rigorous standard of Rasch measurement, and the generic nature of the IPQ-R, it stood up well to the demands of the Rasch model in this study. Importantly, the results show that with some relatively minor, pragmatic modifications the IPQ-R could possess Rasch-standard measurement in cancer patients. © 2013.

Study on the factors affecting the quality of public bus transportation service in Bali Province using factor analysis

NASA Astrophysics Data System (ADS)

Susilawati, M.; Nilakusmawati, D. P. E.

2017-06-01

The volume of mobility flows are increasing day by day and the condition of the number of people using private transport modes contribute to traffic congestion. With the limited capacity of the road, one of the alternatives solution to reduce congestion is to optimize the use of public transport. The purposes of this study are to determine the factors that influence user’s satisfaction on the quality of public bus transportation service and determine variables that became identifier on the dominant factor affecting user’s satisfaction. The study was conducted for the public bus transportation between districts in the province of Bali, which is among the eight regencies and one municipality, using a questionnaire as a data collection instrument. Service variables determinant of user’s satisfaction in this study, described in 25 questions, which were analyzed using factor analysis. The results showed there were six factors that explain the satisfaction of users of public transport in Bali, with a total diversity of data that can be parsed by 61.436%. These factors are: Safety and comfort, Responsiveness, Capacity, Tangible, Safety, Reliability. The dominant factor affecting public transport user satisfaction is the safety and comfort, with the most influential variable is feeling concerned about the personal safety of users when on the bus.

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…

Physiological Factors Analysis in Unpressurized Aircraft Cabins

NASA Astrophysics Data System (ADS)

Patrao, Luis; Zorro, Sara; Silva, Jorge

2016-11-01

Amateur and sports flight is an activity with growing numbers worldwide. However, the main cause of flight incidents and accidents is increasingly pilot error, for a number of reasons. Fatigue, sleep issues and hypoxia, among many others, are some that can be avoided, or, at least, mitigated. This article describes the analysis of psychological and physiological parameters during flight in unpressurized aircraft cabins. It relates cerebral oximetry and heart rate with altitude, as well as with flight phase. The study of those parameters might give clues on which variations represent a warning sign to the pilot, thus preventing incidents and accidents due to human factors. Results show that both cerebral oximetry and heart rate change along the flight and altitude in the alert pilot. The impaired pilot might not reveal these variations and, if this is detected, he can be warned in time.

Analysis of the influencing factors of global energy interconnection development

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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…

A meta-analysis of peripheral blood nerve growth factor levels in patients with schizophrenia.

PubMed

Qin, X-Y; Wu, H-T; Cao, C; Loh, Y P; Cheng, Y

2017-09-01

Neurotrophins particularly brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) are crucial modulators in the neurodevelopment and maintenance of central and peripheral nervous systems. Neurotrophin hypothesis of schizophrenia (SCZ) postulated that the changes in the brains of SCZ patients are the result of disturbances of developing processes involving neurotrophic factors. This hypothesis was mainly supported by the abnormal regulation of BDNF in SCZ, especially the decreased peripheral blood BDNF levels in SCZ patients validated by several meta-analyses. However, the regulation of NGF in SCZ remains unclear because of the inconsistent findings from the clinical studies. Therefore, we undertook, to the best of our knowledge, the first systematic review with a meta-analysis to quantitatively summarize the peripheral blood NGF data in SCZ patients compared with healthy control (HC) subjects. A systematic search of Pubmed, PsycINFO and Web of Science identified 13 articles encompassing a sample of 1693 individuals for the meta-analysis. Random-effects meta-analysis showed that patients with SCZ had significantly decreased peripheral blood levels of NGF when compared with the HC subjects (Hedges's g=-0.633, 95% confidence interval (CI)=-0.948 to -0.318, P<0.001). Subgroup analyses revealed reduced NGF levels both in serum (Hedges's g=-0.671, 95% CI=-1.259 to -0.084, P=0.025) and plasma (Hedges's g=-0.621, 95% CI=-0.980 to -0.261, P<0.001) of the patients, and in drug-free (Hedges's g=-0.670, 95% CI=-1.118 to -0.222, P=0.003) and medicated (Hedges's g=-0.357, 95% CI=-0.592 to -0.123, P=0.003) patients with SCZ. Furthermore, meta-regression analyses showed that age, gender and sample size had no moderating effects on the outcome of the meta-analysis, whereas disease severity might be a confounding factor for the meta-analysis. These results demonstrated that patients with SCZ are accompanied by the decreased peripheral blood NGF levels, strengthening

Identification of Scoliosis Research Society-22r Health-Related Quality of Life questionnaire domains using factor analysis methodology.

PubMed

Lai, Sue-Min; Asher, Marc A; Burton, Douglas C; Carlson, Brandon B

2010-05-20

Cross-sectional mail questionnaire. Examination of the underlying construct validity of the Scoliosis Research Society-22r (SRS-22r) Health-Related Quality of Life (HRQoL) Questionnaire using factor analysis. The original SRS-24 HRQoL questionnaire has undergone a series of modifications in an effort to further improve its psychometric properties and validate its use in patients from 10 years of age until well into adulthood. The SRS-22r questionnaire is the result of this effort. To date, the underlying construct validity of the original English version has not been analyzed by factor analysis. A questionnaire including all questions on the SRS-24, -23, -22, and -22r questionnaires (49 total questions) was mailed to a consecutive series of 235 patients who had received primary posterior or anterior instrumentation and arthrodesis. Domain structure of the SRS-22r questions was analyzed using iterated principal factor analysis with orthogonal rotation. One hundred twenty-one (51%) of the patients, age 23.34 +/- 4.52 years (range, 14.16-34.57 years), returned the questionnaire at 8.63 +/- 4.00 years (range, 2.32-15.94 years) following surgery. Factor analysis using all 22 questions resulted in 3 factors with many shared items because of significant collinearity of the satisfaction/dissatisfaction with management questions with the others. After 18 iterations, factor analysis using the 20 nonmanagement questions revealed 4 factors that explained 98% of the variance. These factors parallel the assigned domains of the SRS-22r questionnaire. Three questions (2 self-image and 1 function) were identified that had high loading in 2 factors. However, internal consistency was best when 2 of the questions (1 self-image and 1 function) were retained in their assigned SRS-22r domains and the third decreased self-image internal consistency by only 0.01%. The internal consistencies (Cronbach alpha) of the assigned SRS-22r nonmanagement domains were excellent or very good: function

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.

Preliminary Results Obtained in Integrated Safety Analysis of NASA Aviation Safety Program Technologies

NASA Technical Reports Server (NTRS)

Reveley, Mary S.

2003-01-01

The goal of the NASA Aviation Safety Program (AvSP) is to develop and demonstrate technologies that contribute to a reduction in the aviation fatal accident rate by a factor of 5 by the year 2007 and by a factor of 10 by the year 2022. Integrated safety analysis of day-to-day operations and risks within those operations will provide an understanding of the Aviation Safety Program portfolio. Safety benefits analyses are currently being conducted. Preliminary results for the Synthetic Vision Systems (SVS) and Weather Accident Prevention (WxAP) projects of the AvSP have been completed by the Logistics Management Institute under a contract with the NASA Glenn Research Center. These analyses include both a reliability analysis and a computer simulation model. The integrated safety analysis method comprises two principal components: a reliability model and a simulation model. In the reliability model, the results indicate how different technologies and systems will perform in normal, degraded, and failed modes of operation. In the simulation, an operational scenario is modeled. The primary purpose of the SVS project is to improve safety by providing visual-flightlike situation awareness during instrument conditions. The current analyses are an estimate of the benefits of SVS in avoiding controlled flight into terrain. The scenario modeled has an aircraft flying directly toward a terrain feature. When the flight crew determines that the aircraft is headed toward an obstruction, the aircraft executes a level turn at speed. The simulation is ended when the aircraft completes the turn.

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.

Exploratory Factor Analysis of the Beck Anxiety Inventory and the Beck Depression Inventory-II in a Psychiatric Outpatient Population

PubMed Central

2018-01-01

Background To further understand the relationship between anxiety and depression, this study examined the factor structure of the combined items from two validated measures for anxiety and depression. Methods The participants were 406 patients with mixed psychiatric diagnoses including anxiety and depressive disorders from a psychiatric outpatient unit at a university-affiliated medical center. Responses of the Beck Anxiety Inventory (BAI), Beck Depression Inventory (BDI)-II, and Symptom Checklist-90-Revised (SCL-90-R) were analyzed. We conducted an exploratory factor analysis of 42 items from the BAI and BDI-II. Correlational analyses were performed between subscale scores of the SCL-90-R and factors derived from the factor analysis. Scores of individual items of the BAI and BDI-II were also compared between groups of anxiety disorder (n = 185) and depressive disorder (n = 123). Results Exploratory factor analysis revealed the following five factors explaining 56.2% of the total variance: somatic anxiety (factor 1), cognitive depression (factor 2), somatic depression (factor 3), subjective anxiety (factor 4), and autonomic anxiety (factor 5). The depression group had significantly higher scores for 12 items on the BDI while the anxiety group demonstrated higher scores for six items on the BAI. Conclusion Our results suggest that anxiety and depressive symptoms as measured by the BAI and BDI-II can be empirically differentiated and that particularly items of the cognitive domain in depression and those of physical domain in anxiety are noteworthy. PMID:29651821

Exchange nailing for nonunion of diaphyseal fractures of the tibia: our results and an analysis of the risk factors for failure.

PubMed

Tsang, S T J; Mills, L A; Frantzias, J; Baren, J P; Keating, J F; Simpson, A H R W

2016-04-01

The aim of this study was to identify risk factors for the failure of exchange nailing in nonunion of tibial diaphyseal fractures. A cohort of 102 tibial diaphyseal nonunions in 101 patients with a mean age of 36.9 years (15 to 74) were treated between January 1992 and December 2012 by exchange nailing. Of which 33 (32%) were initially open injuries. The median time from primary fixation to exchange nailing was 6.5 months (interquartile range (IQR) 4.3 to 9.8 months). The main outcome measures were union, number of secondary fixation procedures required to achieve union and time to union. Univariate analysis and multiple regression were used to identify risk factors for failure to achieve union. Multiple causes for the primary nonunion were found for 28 (27%) tibiae, with infection present in 32 (31%). Six patients were lost to follow-up. Further surgical procedures were required in 35 (36%) nonunions. Other fixation modalities were required in five fractures. A single nail exchange procedure achieved union in 60/96 (63%) of all nonunions. Only 11 out of 31 infected nonunions (35.4%) healed after one exchange nail procedure. Up to five repeated exchange nailings, with or without bone grafting, ultimately achieved union in 89 (93%) fractures. The median time to union after exchange nailing was 8.7 months (IQR 5.7 to 14.0 months). Univariate analysis confirmed that an oligotrophic/atrophic pattern of nonunion (p = 0.002), a bone gap of 5 mm or more (p = 0.04) and infection (p < 0.001), were predictive for failure of exchange nailing Multiple regression analysis found that infection was the strongest predictor of failure (p < 0.001). Exchange nailing is an effective treatment for aseptic tibial diaphyseal nonunion. However, in the presence of severe infection with a highly resistant organism, or extensive sclerosis of the bone, other fixation modalities, such as Ilizarov treatment, should be considered. Exchange nailing is an effective treatment for aseptic tibial

Dynamic factor analysis for estimating ground water arsenic trends.

PubMed

Kuo, Yi-Ming; Chang, Fi-John

2010-01-01

Drinking ground water containing high arsenic (As) concentrations has been associated with blackfoot disease and the occurrence of cancer along the southwestern coast of Taiwan. As a result, 28 ground water observation wells were installed to monitor the ground water quality in this area. Dynamic factor analysis (DFA) is used to identify common trends that represent unexplained variability in ground water As concentrations of decommissioned wells and to investigate whether explanatory variables (total organic carbon [TOC], As, alkalinity, ground water elevation, and rainfall) affect the temporal variation in ground water As concentration. The results of the DFA show that rainfall dilutes As concentration in areas under aquacultural and agricultural use. Different combinations of geochemical variables (As, alkalinity, and TOC) of nearby monitoring wells affected the As concentrations of the most decommissioned wells. Model performance was acceptable for 11 wells (coefficient of efficiency >0.50), which represents 52% (11/21) of the decommissioned wells. Based on DFA results, we infer that surface water recharge may be effective for diluting the As concentration, especially in the areas that are relatively far from the coastline. We demonstrate that DFA can effectively identify the important factors and common effects representing unexplained variability common to decommissioned wells on As variation in ground water and extrapolate information from existing monitoring wells to the nearby decommissioned wells.

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.

Quality factor analysis for aberrated laser beam

NASA Astrophysics Data System (ADS)

Ghafary, B.; Alavynejad, M.; Kashani, F. D.

2006-12-01

The quality factor of laser beams has attracted considerable attention and some different approaches have been reported to treat the problem. In this paper we analyze quality factor of laser beam and compare the effect of different aberrations on beam quality by expanding pure phase term of wavefront in terms of Zernike polynomials. Also we analyze experimentally the change of beam quality for different Astigmatism aberrations, and compare theoretical results with experimentally results. The experimental and theoretical results are in good agreement.

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

PubMed Central

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

2016-01-01

Introduction Syndromic surveillance aims at augmenting traditional public health surveillance with timely information. To gain a head start, it mainly analyses existing data such as from web searches or patient records. Despite the setup of many syndromic surveillance systems, there is still much doubt about the benefit of the approach. There are diverse interactions between performance indicators such as timeliness and various system characteristics. This makes the performance assessment of syndromic surveillance systems a complex endeavour. We assessed if the comparison of several syndromic surveillance systems through Qualitative Comparative Analysis helps to evaluate performance and identify key success factors. Materials and Methods We compiled case-based, mixed data on performance and characteristics of 19 syndromic surveillance systems in Europe from scientific and grey literature and from site visits. We identified success factors by applying crisp-set Qualitative Comparative Analysis. We focused on two main areas of syndromic surveillance application: seasonal influenza surveillance and situational awareness during different types of potentially health threatening events. Results We found that syndromic surveillance systems might detect the onset or peak of seasonal influenza earlier if they analyse non-clinical data sources. Timely situational awareness during different types of events is supported by an automated syndromic surveillance system capable of analysing multiple syndromes. To our surprise, the analysis of multiple data sources was no key success factor for situational awareness. Conclusions We suggest to consider these key success factors when designing or further developing syndromic surveillance systems. Qualitative Comparative Analysis helped interpreting complex, mixed data on small-N cases and resulted in concrete and practically relevant findings. PMID:27182731

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...

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 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)

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

PubMed

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

1999-10-01

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

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.

Automated processing of first-pass radionuclide angiocardiography by factor analysis of dynamic structures.

PubMed

Cavailloles, F; Bazin, J P; Capderou, A; Valette, H; Herbert, J L; Di Paola, R

1987-05-01

A method for automatic processing of cardiac first-pass radionuclide study is presented. This technique, factor analysis of dynamic structures (FADS) provides an automatic separation of anatomical structures according to their different temporal behaviour, even if they are superimposed. FADS has been applied to 76 studies. A description of factor patterns obtained in various pathological categories is presented. FADS provides easy diagnosis of shunts and tricuspid insufficiency. Quantitative information derived from the factors (cardiac output and mean transit time) were compared to those obtained by the region of interest method. Using FADS, a higher correlation with cardiac catheterization was found for cardiac output calculation. Thus compared to the ROI method, FADS presents obvious advantages: a good separation of overlapping cardiac chambers is obtained; this operator independant method provides more objective and reproducible results. A number of parameters of the cardio-pulmonary function can be assessed by first-pass radionuclide angiocardiography (RNA) [1,2]. Usually, they are calculated using time-activity curves (TAC) from regions of interest (ROI) drawn on the cardiac chambers and the lungs. This method has two main drawbacks: (1) the lack of inter and intra-observers reproducibility; (2) the problem of crosstalk which affects the evaluation of the cardio-pulmonary performance. The crosstalk on planar imaging is due to anatomical superimposition of the cardiac chambers and lungs. The activity measured in any ROI is the sum of the activity in several organs and 'decontamination' of the TAC cannot easily be performed using the ROI method [3]. Factor analysis of dynamic structures (FADS) [4,5] can solve the two problems mentioned above. It provides an automatic separation of anatomical structures according to their different temporal behaviour, even if they are superimposed. The resulting factors are estimates of the time evolution of the activity in each

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.

[Risk factors for the development of pneumonia in multiple injured patients. Results of a prospective clinical trial].

PubMed

Andermahr, J; Hensler, T; Sauerland, S; Greb, A; Helling, H-J; Prokop, A; Neugebauer, E A M; Rehm, K E

2003-05-01

Pneumonia is the most common infectious complication in multiple trauma patients. In a prospective clinical cohort study, 266 multiply injured patients were examined for the development of pneumonia. Various risk factors were tested in uni- and multivariate analyses. Three different definitions of pneumonia were used in order to examine how results depended on definition. The incidence of pneumonia was 41%, but varied with definition (30-50%). Injuries to the thorax, head,and abdomen were associated with a significantly increased risk of pneumonia (adjusted relative risk: 1.77, 1.97,and 1.52, respectively).Furthermore, increasing age led to a higher risk of pneumonia. Although the primary analysis revealed a higher pneumonia risk in male patients (adjusted relative risk: 2.23; 95% CI: 1.43-3.05), this result could not be consistently reproduced when using other definitions of pneumonia. Trunk and head injuries and age are proven risk factors for developing posttraumatic pneumonia. The association between male gender and an increased rate of infectious complications remained questionable.

Organic Solvents as Risk Factor for Autoimmune Diseases: A Systematic Review and Meta-Analysis

PubMed Central

Barragán-Martínez, Carolina; Speck-Hernández, Cesar A.; Montoya-Ortiz, Gladis; Mantilla, Rubén D.; Anaya, Juan-Manuel; Rojas-Villarraga, Adriana

2012-01-01

Background Genetic and epigenetic factors interacting with the environment over time are the main causes of complex diseases such as autoimmune diseases (ADs). Among the environmental factors are organic solvents (OSs), which are chemical compounds used routinely in commercial industries. Since controversy exists over whether ADs are caused by OSs, a systematic review and meta-analysis were performed to assess the association between OSs and ADs. Methods and Findings The systematic search was done in the PubMed, SCOPUS, SciELO and LILACS databases up to February 2012. Any type of study that used accepted classification criteria for ADs and had information about exposure to OSs was selected. Out of a total of 103 articles retrieved, 33 were finally included in the meta-analysis. The final odds ratios (ORs) and 95% confidence intervals (CIs) were obtained by the random effect model. A sensitivity analysis confirmed results were not sensitive to restrictions on the data included. Publication bias was trivial. Exposure to OSs was associated to systemic sclerosis, primary systemic vasculitis and multiple sclerosis individually and also to all the ADs evaluated and taken together as a single trait (OR: 1.54; 95% CI: 1.25–1.92; p-value<0.001). Conclusion Exposure to OSs is a risk factor for developing ADs. As a corollary, individuals with non-modifiable risk factors (i.e., familial autoimmunity or carrying genetic factors) should avoid any exposure to OSs in order to avoid increasing their risk of ADs. PMID:23284705

Saxagliptin efficacy and safety in patients with type 2 diabetes mellitus and cardiovascular disease history or cardiovascular risk factors: results of a pooled analysis of phase 3 clinical trials.

PubMed

Cook, William; Bryzinski, Brian; Slater, Jill; Frederich, Robert; Allen, Elsie

2013-05-01

This post hoc analysis sought to assess the efficacy, safety, and tolerability of saxagliptin in patients with type 2 diabetes mellitus and cardiovascular (CV) risk factors or disease (CVD). Data from 5 randomized controlled trials were pooled to compare saxagliptin 5 mg with placebo: 2 studies of saxagliptin as monotherapy in drug-naïve patients and 1 each of saxagliptin as add-on therapy to metformin, glyburide, or a thiazolidinedione. Analysis was performed according to the following baseline/trial entry criteria: 1) history/no history of CVD; 2) ≥ 2 versus 0 to 1 CV risk factors; 3) statin use versus no statin use; and 4) hypertension versus no hypertension. Change from baseline glycated hemoglobin (HbA1c), fasting plasma glucose, and postprandial glucose levels; and the proportion of patients achieving an HbA1c level < 7% were analyzed (week 24). Safety was assessed by adverse events, hypoglycemia, and body weight. In total, 882 patients received saxagliptin 5 mg and 799 received placebo. Differences in adjusted mean change from baseline HbA1c (95% CI) were greater with saxagliptin compared with placebo in patients with a history of CVD (-0.64% [-0.90 to -0.38]) and no history of CVD (-0.68% [-0.78 to -0.58]); with ≥ 2 CV risk factors (-0.73% [-0.85 to -0.60]) and 0 to 1 CV risk factor (-0.62% [-0.75 to -0.48]); with statin use (-0.70% [-0.89 to -0.52]) and no statin use (-0.66% [-0.77 to -0.56]); and with hypertension (-0.69% [-0.82 to -0.57]) and no hypertension (-0.66% [-0.80 to -0.52]). Saxagliptin was well tolerated, with similar adverse event rates and types compared with placebo. There was a < 1% rate of confirmed hypoglycemia in all groups except in patients with CV history who received placebo (2.1%). Saxagliptin improved glycemic measures, resulted in low rates of confirmed hypoglycemia, and was well tolerated in patients with or without CVD and CV risk factors.

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…

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

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

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

Analysis of nucleon electromagnetic form factors from light-front holographic QCD: The spacelike region

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

Sufian, Raza Sabbir; de Teramond, Guy F.; Brodsky, Stanley J.

We present a comprehensive analysis of the space-like nucleon electromagnetic form factors and their flavor decomposition within the framework of light-front holographic QCD. We show that the inclusion of the higher Fock componentsmore » $$|{qqqq\\bar{q}}$$ has a significant effect on the spin-flip elastic Pauli form factor and almost zero effect on the spin-conserving Dirac form factor. We present light-front holographic QCD results for the proton and neutron form factors at any momentum transfer range, including asymptotic predictions, and show that our results agree with the available experimental data with high accuracy. In order to correctly describe the Pauli form factor we need an admixture of a five quark state of about 30$$\\%$$ in the proton and about 40$$\\%$$ in the neutron. We also extract the nucleon charge and magnetic radii and perform a flavor decomposition of the nucleon electromagnetic form factors. The free parameters needed to describe the experimental nucleon form factors are very few: two parameters for the probabilities of higher Fock states for the spin-flip form factor and a phenomenological parameter $r$, required to account for possible SU(6) spin-flavor symmetry breaking effects in the neutron, whereas the Pauli form factors are normalized to the experimental values of the anomalous magnetic moments. As a result, the covariant spin structure for the Dirac and Pauli nucleon form factors prescribed by AdS$$_5$$ semiclassical gravity incorporates the correct twist scaling behavior from hard scattering and also leads to vector dominance at low energy.« less

Analysis of nucleon electromagnetic form factors from light-front holographic QCD: The spacelike region

DOE PAGES

Sufian, Raza Sabbir; de Teramond, Guy F.; Brodsky, Stanley J.; ...

2017-01-10

We present a comprehensive analysis of the space-like nucleon electromagnetic form factors and their flavor decomposition within the framework of light-front holographic QCD. We show that the inclusion of the higher Fock componentsmore » $$|{qqqq\\bar{q}}$$ has a significant effect on the spin-flip elastic Pauli form factor and almost zero effect on the spin-conserving Dirac form factor. We present light-front holographic QCD results for the proton and neutron form factors at any momentum transfer range, including asymptotic predictions, and show that our results agree with the available experimental data with high accuracy. In order to correctly describe the Pauli form factor we need an admixture of a five quark state of about 30$$\\%$$ in the proton and about 40$$\\%$$ in the neutron. We also extract the nucleon charge and magnetic radii and perform a flavor decomposition of the nucleon electromagnetic form factors. The free parameters needed to describe the experimental nucleon form factors are very few: two parameters for the probabilities of higher Fock states for the spin-flip form factor and a phenomenological parameter $r$, required to account for possible SU(6) spin-flavor symmetry breaking effects in the neutron, whereas the Pauli form factors are normalized to the experimental values of the anomalous magnetic moments. As a result, the covariant spin structure for the Dirac and Pauli nucleon form factors prescribed by AdS$$_5$$ semiclassical gravity incorporates the correct twist scaling behavior from hard scattering and also leads to vector dominance at low energy.« less

Incarcerated Youths’ Perspectives on Protective Factors and Risk Factors for Juvenile Offending: A Qualitative Analysis

PubMed Central

Perry, Raymond; Azzi, Veronica F.; Shetgiri, Rashmi; Ryan, Gery; Dudovitz, Rebecca; Zima, Bonnie; Chung, Paul J.

2015-01-01

Objectives. We sought to understand incarcerated youths’ perspectives on the role of protective factors and risk factors for juvenile offending. Methods. We performed an in-depth qualitative analysis of interviews (conducted October–December 2013) with 20 incarcerated youths detained in the largest juvenile hall in Los Angeles. Results. The adolescent participants described their homes, schools, and neighborhoods as chaotic and unsafe. They expressed a need for love and attention, discipline and control, and role models and perspective. Youths perceived that when home or school failed to meet these needs, they spent more time on the streets, leading to incarceration. They contrasted the path through school with the path to jail, reporting that the path to jail felt easier. All of them expressed the insight that they had made bad decisions and that the more difficult path was not only better but also still potentially achievable. Conclusions. Breaking cycles of juvenile incarceration will require that the public health community partner with legislators, educators, community leaders, and youths to determine how to make success, rather than incarceration, the easier path for disadvantaged adolescents. PMID:25521878

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Test 6, Test 7, and Gas Standard Analysis Results

NASA Technical Reports Server (NTRS)

Perez, Horacio, III

2007-01-01

This viewgraph presentation shows results of analyses on odor, toxic off gassing and gas standards. The topics include: 1) Statistical Analysis Definitions; 2) Odor Analysis Results NASA Standard 6001 Test 6; 3) Toxic Off gassing Analysis Results NASA Standard 6001 Test 7; and 4) Gas Standard Results NASA Standard 6001 Test 7;

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.

Discovering Hematopoietic Mechanisms Through Genome-Wide Analysis of GATA Factor Chromatin Occupancy

PubMed Central

Fujiwara, Tohru; O'Geen, Henriette; Keles, Sunduz; Blahnik, Kimberly; Linnemann, Amelia K.; Kang, Yoon-A; Choi, Kyunghee; Farnham, Peggy J.; Bresnick, Emery H.

2009-01-01

SUMMARY GATA factors interact with simple DNA motifs (WGATAR) to regulate critical processes, including hematopoiesis, but very few WGATAR motifs are occupied in genomes. Given the rudimentary knowledge of mechanisms underlying this restriction, and how GATA factors establish genetic networks, we used ChIP-seq to define GATA-1 and GATA-2 occupancy genome-wide in erythroid cells. Coupled with genetic complementation analysis and transcriptional profiling, these studies revealed a rich collection of targets containing a characteristic binding motif of greater complexity than WGATAR. GATA factors occupied loci encoding multiple components of the Scl/TAL1 complex, a master regulator of hematopoiesis and leukemogenic target. Mechanistic analyses provided evidence for cross-regulatory and autoregulatory interactions among components of this complex, including GATA-2 induction of the hematopoietic corepressor ETO-2 and an ETO-2 negative autoregulatory loop. These results establish fundamental principles underlying GATA factor mechanisms in chromatin and illustrate a complex network of considerable importance for the control of hematopoiesis. PMID:19941826

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…

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

PubMed

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

2018-01-01

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

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...

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

PubMed

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

2016-06-30

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

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)

[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

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.

Analysis of Factors Influencing Diagnostic Accuracy of T-SPOT.TB for Active Tuberculosis in Clinical Practice.

PubMed

Zhang, Lifan; Shi, Xiaochun; Zhang, Yueqiu; Zhang, Yao; Huo, Feifei; Zhou, Baotong; Deng, Guohua; Liu, Xiaoqing

2017-08-10

T-SPOT.TB didn't perform a perfect diagnosis for active tuberculosis (ATB), and some factors may influence the results. We did this study to evaluate possible factors associated with the sensitivity and specificity of T-SPOT.TB, and the diagnostic parameters under varied conditions. Patients with suspected ATB were enrolled prospectively. Influencing factors of the sensitivity and specificity of T-SPOT.TB were evaluated using logistic regression models. Sensitivity, specificity, predictive values (PV), and likelihood ratios (LR) were calculated with consideration of relevant factors. Of the 865 participants, 205 (23.7%) had ATB, including 58 (28.3%) microbiologically confirmed TB and 147 (71.7%) clinically diagnosed TB. 615 (71.7%) were non-TB. 45 (5.2%) cases were clinically indeterminate and excluded from the final analysis. In multivariate analysis, serous effusion was the only independent risk factor related to lower sensitivity (OR = 0.39, 95% CI: 0.18-0.81) among patients with ATB. Among non-TB patients, age, TB history, immunosuppressive agents/glucocorticoid treatment and lymphocyte count were the independent risk factors related to specificity of T-SPOT.TB. Sensitivity, specificity, PV+, PV-, LR+ and LR- of T-SPOT.TB for diagnosis of ATB were 78.5%, 74.1%, 50.3%, 91.2%, 3.0 and 0.3, respectively. This study suggests that influencing factors of sensitivity and specificity of T-SPOT.TB should be considered for interpretation of T-SPOT.TB results.

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

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

PubMed

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

1997-01-01

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

Factors associated with adolescent cigarette smoking in Greece: Results from a cross sectional study (GYTS Study)

PubMed Central

Rachiotis, George; Muula, Adamson S; Rudatsikira, Emmanuel; Siziya, Seter; Kyrlesi, Athina; Gourgoulianis, Konstantinos; Hadjichristodoulou, Christos

2008-01-01

Background Data about the predictors of smoking among adolescents in Greece are sparse. We tried to identify factors associated with current cigarette smoking among in-school adolescents in Greece in the context of GYTS study. Methods A secondary analysis of data from a questionnaire study using the Global Youth Tobacco Survey methodology was conducted to identify factors associated with smoking among adolescents in Greece. Data were collected in 2004–2005. The outcome variable was cigarette smoking within the past 30 days preceding the survey while independent variables included age, gender, parental educational status, parental smoking, perception of harmfulness of smoking, and the amount of pocket money at the adolescent's disposal. Results 6141 adolescents (51.5% males and 48.5% females) participated in the study. In multivariate analysis, cigarette smoking was associated with male gender (OR: 1.62; 95% CI: 1, 08–3.08), parental smoking (OR: 2.59; 95% CI: 1.45–5.89), and having pocket money ≥ 16 Euros (OR: 2.64; 95% CI: 1.19–5.98). Conclusion Male gender, parental smoking, and having pocket-money ≥ 16 Euros were independently associated with current smoking among Greek students. These findings could be taken into account in order to formulate a comprehensive anti-smoking strategy in Greece. PMID:18793389

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.

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…

New results from FRECOPA analysis

NASA Technical Reports Server (NTRS)

Durin, Christian

1993-01-01

New results from the ongoing analysis of the FRECOPA's (FREnch COoperative PAssive payload) system hardware are discussed. FRECOPA (AO138) was one of the 57 experiments flown on the LDEF satellite. The experiment was located on the trailing edge (Tray B3) and was exposed to UV radiation (11,100 equivalent sun hours), approximately equal to 34,000 thermal cycles, higher vacuum levels than the leading edge, a low atomic oxygen flux, and minor doses of protons and electrons. Due to LDEF's extended mission (5.8 years), CNES decided to set up a team to analyze the FRECOPA system. Initial results were presented at the First Post-Retrieval Conference, June, 1991. The results obtained since then are summarized.

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…

Initial Data Analysis Results for ATD-2 ISAS HITL Simulation

NASA Technical Reports Server (NTRS)

Lee, Hanbong

2017-01-01

To evaluate the operational procedures and information requirements for the core functional capabilities of the ATD-2 project, such as tactical surface metering tool, APREQ-CFR procedure, and data element exchanges between ramp and tower, human-in-the-loop (HITL) simulations were performed in March, 2017. This presentation shows the initial data analysis results from the HITL simulations. With respect to the different runway configurations and metering values in tactical surface scheduler, various airport performance metrics were analyzed and compared. These metrics include gate holding time, taxi-out in time, runway throughput, queue size and wait time in queue, and TMI flight compliance. In addition to the metering value, other factors affecting the airport performance in the HITL simulation, including run duration, runway changes, and TMI constraints, are also discussed.

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

ERIC Educational Resources Information Center

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

2010-01-01

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

Psychometric Properties and Confirmatory Factor Analysis of the Student Engagement in School Success Skills

ERIC Educational Resources Information Center

Brigman, Greg; Wells, Craig; Webb, Linda; Villares, Elizabeth; Carey, John C.; Harrington, Karen

2015-01-01

This article describes the confirmatory factor analysis of the Student Engagement in School Success Skills (SESSS) instrument. The results of this study confirm that the SESSS has potential to be a useful self-report measure of elementary students' use of strategies and skills associated with enhanced academic learning and achievement.

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

ERIC Educational Resources Information Center

Kranzler, John H.; Keith, Timothy Z.

1999-01-01

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

Factor VII assay performance: an analysis of the North American Specialized Coagulation Laboratory Association proficiency testing results.

PubMed

Zantek, N D; Hsu, P; Refaai, M A; Ledford-Kraemer, M; Meijer, P; Van Cott, E M

2013-06-01

The performance of factor VII (FVII) assays currently used by clinical laboratories was examined in North American Specialized Coagulation Laboratory Association (NASCOLA) proficiency tests. Data from 12 surveys conducted between 2008 and 2010, involving 20 unique specimens plus four repeat-tested specimens, were analyzed. The number of laboratories per survey was 49-54 with a total of 1224 responses. Numerous reagent/instrument combinations were used. For FVII > 80 or <40 U/dL, 99.5% of results (859/863) were correctly classified by laboratories as normal/abnormal. Classification of specimens with 40-73 U/dL FVII was heterogeneous. Interlaboratory precision was better for normal specimens (coefficient of variation (CV) 10.7%) than for FVII<20 U/dL (CV 33.1%), with a mean CV of 17.2% per specimen. Intralaboratory precision for repeated specimens demonstrated no significant difference between the paired survey results (mean absolute difference 2.5-5.0 U/dL). For specimens with FVII >50 U/dL, among commonly used methods, one thromboplastin and one calibrator produced results 5-6 U/dL higher and another thromboplastin and calibrator produced results 5-6 U/dL lower than all other methods, and human thromboplastin differed from rabbit by +7.6 U/dL. Preliminary evidence suggests these differences could be due to the calibrator. For FVII <50 U/dL, differences among the commonly used reagents and calibrators were generally not significant. © 2013 Blackwell Publishing Ltd.

Case-control vaccine effectiveness studies: Data collection, analysis and reporting results.

PubMed

Verani, Jennifer R; Baqui, Abdullah H; Broome, Claire V; Cherian, Thomas; Cohen, Cheryl; Farrar, Jennifer L; Feikin, Daniel R; Groome, Michelle J; Hajjeh, Rana A; Johnson, Hope L; Madhi, Shabir A; Mulholland, Kim; O'Brien, Katherine L; Parashar, Umesh D; Patel, Manish M; Rodrigues, Laura C; Santosham, Mathuram; Scott, J Anthony; Smith, Peter G; Sommerfelt, Halvor; Tate, Jacqueline E; Victor, J Chris; Whitney, Cynthia G; Zaidi, Anita K; Zell, Elizabeth R

2017-06-05

The case-control methodology is frequently used to evaluate vaccine effectiveness post-licensure. The results of such studies provide important insight into the level of protection afforded by vaccines in a 'real world' context, and are commonly used to guide vaccine policy decisions. However, the potential for bias and confounding are important limitations to this method, and the results of a poorly conducted or incorrectly interpreted case-control study can mislead policies. In 2012, a group of experts met to review recent experience with case-control studies evaluating vaccine effectiveness; we summarize the recommendations of that group regarding best practices for data collection, analysis, and presentation of the results of case-control vaccine effectiveness studies. Vaccination status is the primary exposure of interest, but can be challenging to assess accurately and with minimal bias. Investigators should understand factors associated with vaccination as well as the availability of documented vaccination status in the study context; case-control studies may not be a valid method for evaluating vaccine effectiveness in settings where many children lack a documented immunization history. To avoid bias, it is essential to use the same methods and effort gathering vaccination data from cases and controls. Variables that may confound the association between illness and vaccination are also important to capture as completely as possible, and where relevant, adjust for in the analysis according to the analytic plan. In presenting results from case-control vaccine effectiveness studies, investigators should describe enrollment among eligible cases and controls as well as the proportion with no documented vaccine history. Emphasis should be placed on confidence intervals, rather than point estimates, of vaccine effectiveness. Case-control studies are a useful approach for evaluating vaccine effectiveness; however careful attention must be paid to the collection

What is hypomania? Tetrachoric factor analysis and kernel estimation of DSM-IV hypomanic symptoms.

PubMed

Benazzi, Franco

2009-11-01

The DSM-IV definition of hypomania, which relies on clinical consensus and historical tradition, includes several "nonspecific" symptoms. The aim of this study was to identify the core symptoms of DSM-IV hypomania. In an outpatient private practice, 266 bipolar II disorder (BP-II) and 138 major depressive disorder (MDD) remitted patients were interviewed by a bipolar-trained psychiatrist, for different study goals. Patients were questioned, using the Structured Clinical Interview for DSM-IV, about the most common symptoms and duration of recent threshold and subthreshold hypomanic episodes. Data were recorded between 2002 and 2006. Four different samples, assessed with the same methodology, were pooled for the present analyses. Tetrachoric factor analysis was used to identify core hypomanic symptoms. Distribution of symptoms by kernel estimation was inspected for bimodality. Validity of core hypomania was tested by receiver operating characteristic (ROC) analysis. The distribution of subthreshold and threshold hypomanic episodes did not show bimodality. Tetrachoric factor analysis found 2 uncorrelated factors: factor 1 included the "classic" symptoms elevated mood, inflated self-esteem, decreased need for sleep, talkativeness, and increase in goal-directed activity (overactivity); factor 2 included the "nonspecific" symptoms irritable mood, racing/crowded thoughts, and distractibility. Factor 1 discriminatory accuracy for distinguishing BP-II versus MDD was high (ROC area = 0.94). The distribution of the 5-symptom episodes of factor 1 showed clear-cut bimodality. Similar results were found for episodes limited to 3 behavioral symptoms of factor 1 (decreased need for sleep, talkativeness, and overactivity) and 4 behavioral symptoms of factor 1 (adding elevated mood), with high discriminatory accuracy. A core, categorical DSM-IV hypomania was found that included 3 to 5 symptoms, ie, behavioral symptoms and elevated mood. Behavioral symptoms (overactivity domain

Comparison of Seven Methods for Boolean Factor Analysis and Their Evaluation by Information Gain.

PubMed

Frolov, Alexander A; Húsek, Dušan; Polyakov, Pavel Yu

2016-03-01

An usual task in large data set analysis is searching for an appropriate data representation in a space of fewer dimensions. One of the most efficient methods to solve this task is factor analysis. In this paper, we compare seven methods for Boolean factor analysis (BFA) in solving the so-called bars problem (BP), which is a BFA benchmark. The performance of the methods is evaluated by means of information gain. Study of the results obtained in solving BP of different levels of complexity has allowed us to reveal strengths and weaknesses of these methods. It is shown that the Likelihood maximization Attractor Neural Network with Increasing Activity (LANNIA) is the most efficient BFA method in solving BP in many cases. Efficacy of the LANNIA method is also shown, when applied to the real data from the Kyoto Encyclopedia of Genes and Genomes database, which contains full genome sequencing for 1368 organisms, and to text data set R52 (from Reuters 21578) typically used for label categorization.

Psychosocial work factors, major depressive and generalised anxiety disorders: results from the French national SIP study.

PubMed

Murcia, Marie; Chastang, Jean-François; Niedhammer, Isabelle

2013-04-25

Anxiety and depression are prevalent mental disorders in working populations. The risk factors of these disorders are not completely well known. Developing knowledge on occupational risk factors for mental disorders appears crucial. This study investigates the association between various classical and emergent psychosocial work factors and major depressive and generalised anxiety disorders in the French working population. The study was based on a national random sample of 3765 men and 3944 women of the French working population (SIP 2006 survey). Major Depressive Disorder (MDD) and Generalised Anxiety Disorder (GAD) were measured using a standardised diagnostic interview (MINI). Occupational factors included psychosocial work factors as well as biomechanical, physical, and chemical exposures. Adjustment variables included age, occupation, marital status, social support, and life events. Multivariate analysis was performed using logistic regression analysis. Low decision latitude, overcommitment, and emotional demands were found to be risk factors for both MDD-GAD among both genders. Other risk factors were observed: high psychological demands, low reward, ethical conflict, and job insecurity, but differences were found according to gender and outcome. Significant interaction terms were observed suggesting that low decision latitude, high psychological demands, and job insecurity had stronger effects on mental disorders for men than for women. Given the cross-sectional study design, no causal conclusion could be drawn. This study showed significant associations between classical and emergent psychosocial work factors and MDD-GAD. Preventive actions targeting various psychosocial work factors, including emergent factors, may help to reduce mental disorders at the workplace. Copyright © 2012 Elsevier B.V. All rights reserved.

Results and analysis of the switchyard impact tests

DOT National Transportation Integrated Search

1980-01-01

This report presents the results and analysis of series 3 through 7 and series 10 of the FRA/RPI/AAR Switchyard Impact Tests. The test results and analysis are used to evaluate the head shield and the shelf-E coupler as protective devices for hazardo...

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…

Hypoxia-Inducible Factor-1α Polymorphisms and Risk of Cancer Metastasis: A Meta-Analysis

PubMed Central

Shi, Bin; Weng, Wenjun; Chen, Zhipeng; Guo, Nannan; Hua, Yibing; Zhu, Lingjun

2013-01-01

Background HIF-1α is a major regulator in tumor progression and metastasis which responds to hypoxia. Many studies have demonstrated that hypoxia-inducible factor1-α (HIF-1α) polymorphisms are significantly associated with cancer metastasis, but the results are inconsistent. We conducted a comprehensive meta-analysis to estimate the associations between HIF-1α C1772 T polymorphism and cancer metastasis. Methods Comprehensive searches were conducted on PubMed and EMBASE database. Fifteen studies were included in the meta-analysis. We used the OR and 95%CI to assess the associations between HIF-1α C1772T polymorphism and cancer metastasis. Heterogeneity and publication bias were also assessed by Q test, I 2, and funnel plot. Results Totally, fifteen studies including 1239 cases with metastasis-positive (M+) and 2711 cases with metastasis-negative (M−) were performed in this meta-analysis. The results showed that HIF-1a C1772T polymorphism was associated with the increased risk of cancer metastasis (T allele vs. C allele, OR  = 1.36, 95% CI  = 1.12–1.64; TT+ TC vs. CC, OR  = 1.39, 95% CI  = 1.13–1.71; TT vs. TC+ CC, OR  = 1.93, 95% CI  = 0.86–4.36). In the subgroup analyses, the significant associations remained significant among Asians, Caucasians and other cancers in the dominant model. Publication bias was not observed in the analysis. Conclusions Our results indicate that the HIF-1αC1772T polymorphism T allele may increase the risk of cancer metastasis, which might be a potential risk factor of cancer progress. PMID:24015181

Results from a Web Impact Factor Crawler.

ERIC Educational Resources Information Center

Thelwall, Mike

2001-01-01

Discusses Web impact factors (WIFs), Web versions of the impact factors for journals, and how they can be calculated by using search engines. Highlights include HTML and document indexing; Web page links; a Web crawler designed for calculating WIFs; and WIFs for United Kingdom universities that measured research profiles or capability. (Author/LRW)

An empirical evaluation of the structure of DSM-IV personality disorders in a nationally representative sample: results of confirmatory factor analysis in the National Epidemiologic Survey on Alcohol and Related Conditions Waves 1 and 2.

PubMed

Cox, Brian J; Clara, Ian P; Worobec, Lydia M; Grant, Bridget F

2012-12-01

Individual personality disorders (PD) are grouped into three clusters in the DSM-IV (A, B, and C). There is very little empirical evidence available concerning the validity of this model in the general population. The current study included all 10 of the DSM-IV PD assessed in Wave 1 and Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Confirmatory factor analysis was used to evaluate three plausible models of the structure of Axis II personality disorders (the current hierarchical DSM-IV three-factor model in which individual PD are believed to load on their assigned clusters, which in turn load onto a single Axis II factor; a general single-factor model; and three independent factors). Each of these models was tested in both the total and also separately for gender. The higher order DSM-IV model demonstrated good fit to the data on a number of goodness-of-fit indices. The results for this model were very similar across genders. A model of PD based on the current DSM-IV hierarchical conceptualization of a higher order classification scheme received strong empirical support through confirmatory factor analysis using a number of goodness-of-fit indices in a nationally representative sample. Other models involving broad, higher order personality domains such as neuroticism in relation to personality disorders have yet to be tested in epidemiologic surveys and represent an important avenue for future research.

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

PubMed

Xu, Ruirui; Sun, Peng; Jia, Fengjuan; Lu, Longtao; Li, Yuanyuan; Zhang, Shizhong; Huang, Jinguang

2014-12-01

Teosinte branched 1/cycloidea/proliferating cell factor 1 (TCP) proteins are a large family of transcriptional regulators in angiosperms. They are involved in various biological processes, including development and plant metabolism pathways. In this study, a total of 52 TCP genes were identified in apple (Malus domestica) genome. Bioinformatic methods were employed to predicate and analyse their relevant gene classification, gene structure, chromosome location, sequence alignment and conserved domains of MdTCP proteins. Expression analysis from microarray data showed that the expression levels of 28 and 51 MdTCP genes changed during the ripening and rootstock-scion interaction processes, respectively. The expression patterns of 12 selected MdTCP genes were analysed in different tissues and in response to abiotic stresses. All of the selected genes were detected in at least one of the tissues tested, and most of them were modulated by adverse treatments indicating that the MdTCPs were involved in various developmental and physiological processes. To the best of our knowledge, this is the first study of a genomewide analysis of apple TCP gene family. These results provide valuable information for studies on functions of the TCP transcription factor genes in apple.

Analysis of the factors creating consumer attributes of roasted beef steaks.

PubMed

Guzek, Dominika; Głąbska, Dominika; Gutkowska, Krystyna; Wierzbicki, Jerzy; Woźniak, Alicja; Wierzbicka, Agnieszka

2015-03-01

The aim of the study was to analyze the factors creating consumer attributes of roasted beef steaks of various animals. Eight cuts from 30 carcasses (characterized by various types of animal, conformation and fat class, rib fat thickness, ossification score) were selected. Samples were prepared using the roasting method and consumers rated the tenderness, juiciness, flavor, overall acceptability (rated in a 100-point scale), and satisfaction (rated from 2 to 5) for analyzed samples. No influence of type of animal, fat class, conformation class or ossification score on the results of consumer analysis was observed. For all analyzed factors, the influence of cut on consumer analysis was observed (the highest values of all consumer attributes were observed for tenderloin - for juiciness significantly higher than for other cuts, for tenderness, flavor and MQ4 comparable only with rump (RMP231), while for overall acceptability and satisfaction - with both rump cuts). For rib fat thickness consumer attributes of roasted beef meat were not linear, but the influence was observed - the highest values of consumer attributes were observed for 13 mm rib fat thickness. © 2014 Japanese Society of Animal Science.

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

PubMed Central

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

2011-01-01

Objective Major depressive disorder (MDD) during pregnancy increases the risk of adverse maternal and infant outcomes. Maternal nutritional status may be a modifiable risk factor for antenatal depression. We evaluated the association between patterns in mid-pregnancy nutritional biomarkers and MDD. Design Prospective cohort study Setting Pittsburgh, Pennsylvania, USA Subjects Women who enrolled at ≤20 weeks gestation had a diagnosis of MDD made with the Structured Clinical Interview for DSM-IV at 20-, 30-, and 36-week study visits. A total of 135 women contributed 345 person-visits. Non-fasting blood drawn at enrollment was assayed for red cell essential fatty acids, plasma folate, homocysteine, and ascorbic acid; serum 25-hydroxyvitamin D, retinol, vitamin E, carotenoids, ferritin, and soluble transferrin receptors. Nutritional biomarkers were entered into principal components analysis. Results Three factors emerged: Factor 1, Essential Fatty Acids; Factor 2, Micronutrients; and Factor 3, Carotenoids. MDD was prevalent in 21.5% of women. In longitudinal multivariable logistic models, there was no association between the Essential Fatty Acid or Micronutrient patterns and MDD either before or after adjustment for employment, education, or prepregnancy BMI. In unadjusted analysis, women with Carotenoid factor scores in the middle and upper tertiles were 60% less likely than women in the bottom tertile to have MDD during pregnancy, but after adjustment for confounders, the associations were no longer statistically significant. Conclusions While meaningful patterns were derived using nutritional biomarkers, significant associations with MDD were not observed in multivariable adjusted analyses. Larger, more diverse samples are needed to understand nutrition-depression relationships during pregnancy. PMID:22152590

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…

Molecular cloning and functional analysis of tumor necrosis factor receptor-associated factor 6 (TRAF6) in Crossastrea gigas.

PubMed

Mao, Fan; Li, Jun; Zhang, Yuehuan; Xiang, Zhiming; Zhang, Yang; Yu, Ziniu

2017-09-01

Tumor necrosis factor receptor-associated factor 6 (TRAF6) has been demonstrated to be a key signaling molecule involved in adaptive and innate immunity. In this study, we obtained the full length CgTRAF6 cDNA and analyzed the characteristics of the ORF and the peptide sequence in Crassostrea gigas. The deduced protein sequence of CgTRAF6 includes a conserved C-terminal TRAF domain following the RING and the zinc finger domain. The TRAF domain is composed of coiled-coil TRAF-N and MATH (meprin and TRAF-C homology) subdomains. Furthermore, phylogenetic analysis revealed that CgTRAF6 is clustered together with other members TRAF6 family and is placed in a sub-cluster singly which had a close relationship with Drosophila melanogaster. Expression analysis of CgTRAF6 indicated its constitutive expression in all tissues including mantle, adductor muscle, digestive tract, gonads, heart, gill, and hemocyte. Immune challenge with Vibrio alginolyticus and poly I:C resulted in significant up-regulation of CgTRAF6 expression. Dual-luciferase reporter assays showed that CgTRAF6 could activate both pNF-κB-Luc and pISRE-Luc expression, suggesting CgTRAF6 is potentially involved in NF-κB and the interferon signaling pathway. Furthermore, RNAi mediated knockdown of CgTRAF6 resulted in the down-regulation of several putative anti-viral signaling (IRF) and effector (PKR & Viperin) molecules coding genes, 7 days post-injection. These results collectively indicate that CgTRAF6 is a member of TRAF6 sub-family and is potentially involved in immune defense system against invading bacteria and viruses in Crassostrea gigas. Copyright © 2017 Elsevier Ltd. All rights reserved.

Results of a diabetic retinopathy screening. Risk markers analysis.

PubMed

Ancochea, G; Martín Sánchez, M D

2016-01-01

To identify risk markers for retinopathy in patients from our geographic area, and to compare them with those published in other studies. To design a screening interval strategy, taking into account these results, and compare it with intervals suggested in published studies. Cross-sectional observational study on 383 diabetic patients with no previous retinopathy diagnosis, who were screened for diabetic retinopathy. An analysis was made on the possible association between patient factors and presence of retinopathy. A greater probability for finding retinopathy in diabetic patients was associated to insulin treatment in our study, with a statistical significance level of 95%. In patients with less than 10year onset of their diabetes, only mild retinopathy without macular oedema was found. Insulin treatment and time of onset of diabetes should be taken into account when designing efficient screening strategies for diabetic retinopathy. Copyright © 2015 Sociedad Española de Oftalmología. Published by Elsevier España, S.L.U. All rights reserved.

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.

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

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

PubMed

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

1997-01-01

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

Brazilian version of the Jefferson Scale of Empathy: psychometric properties and factor analysis

PubMed Central

2012-01-01

Background Empathy is a central characteristic of medical professionalism and has recently gained attention in medical education research. The Jefferson Scale of Empathy is the most commonly used measure of empathy worldwide, and to date it has been translated in 39 languages. This study aimed to adapt the Jefferson Scale of Empathy to the Brazilian culture and to test its reliability and validity among Brazilian medical students. Methods The Portuguese version of the Jefferson Scale of Empathy was adapted to Brazil using back-translation techniques. This version was pretested among 39 fifth-year medical students in September 2010. During the final fifth- and sixth-year Objective Structured Clinical Examination (October 2011), 319 students were invited to respond to the scale anonymously. Cronbach’s alpha, exploratory factor analysis, item-total correlation, and gender comparisons were performed to check the reliability and validity of the scale. Results The student response rate was 93.7% (299 students). Cronbach’s coefficient for the scale was 0.84. A principal component analysis confirmed the construct validity of the scale for three main factors: Compassionate Care (first factor), Ability to Stand in the Patient’s Shoes (second factor), and Perspective Taking (third factor). Gender comparisons did not reveal differences in the scores between female and male students. Conclusions The adapted Brazilian version of the Jefferson Scale of Empathy proved to be a valid, reliable instrument for use in national and cross-cultural studies in medical education. PMID:22873730

An average/deprivation/inequality (ADI) analysis of chronic disease outcomes and risk factors in Argentina

PubMed Central

De Maio, Fernando G; Linetzky, Bruno; Virgolini, Mario

2009-01-01

Background Recognition of the global economic and epidemiological burden of chronic non-communicable diseases has increased in recent years. However, much of the research on this issue remains focused on individual-level risk factors and neglects the underlying social patterning of risk factors and disease outcomes. Methods Secondary analysis of Argentina's 2005 Encuesta Nacional de Factores de Riesgo (National Risk Factor Survey, N = 41,392) using a novel analytical strategy first proposed by the United Nations Development Programme (UNDP), which we here refer to as the Average/Deprivation/Inequality (ADI) framework. The analysis focuses on two risk factors (unhealthy diet and obesity) and one related disease outcome (diabetes), a notable health concern in Latin America. Logistic regression is used to examine the interplay between socioeconomic and demographic factors. The ADI analysis then uses the results from the logistic regression to identify the most deprived, the best-off, and the difference between the two ideal types. Results Overall, 19.9% of the sample reported being in poor/fair health, 35.3% reported not eating any fruits or vegetables in five days of the week preceding the interview, 14.7% had a BMI of 30 or greater, and 8.5% indicated that a health professional had told them that they have diabetes or high blood pressure. However, significant variation is hidden by these summary measures. Educational attainment displayed the strongest explanatory power throughout the models, followed by household income, with both factors highlighting the social patterning of risk factors and disease outcomes. As educational attainment and household income increase, the probability of poor health, unhealthy diet, obesity, and diabetes decrease. The analyses also point toward important provincial effects and reinforce the notion that both compositional factors (i.e., characteristics of individuals) and contextual factors (i.e., characteristics of places) are

Dispersive analysis of the pion transition form factor

NASA Astrophysics Data System (ADS)

Hoferichter, M.; Kubis, B.; Leupold, S.; Niecknig, F.; Schneider, S. P.

2014-11-01

We analyze the pion transition form factor using dispersion theory. We calculate the singly-virtual form factor in the time-like region based on data for the cross section, generalizing previous studies on decays and scattering, and verify our result by comparing to data. We perform the analytic continuation to the space-like region, predicting the poorly-constrained space-like transition form factor below , and extract the slope of the form factor at vanishing momentum transfer . We derive the dispersive formalism necessary for the extension of these results to the doubly-virtual case, as required for the pion-pole contribution to hadronic light-by-light scattering in the anomalous magnetic moment of the muon.

Maximizing the Information and Validity of a Linear Composite in the Factor Analysis Model for Continuous Item Responses

ERIC Educational Resources Information Center

Ferrando, Pere J.

2008-01-01

This paper develops results and procedures for obtaining linear composites of factor scores that maximize: (a) test information, and (b) validity with respect to external variables in the multiple factor analysis (FA) model. I treat FA as a multidimensional item response theory model, and use Ackerman's multidimensional information approach based…

A meta-analysis of the factors influencing development rate variation in Aedes aegypti (Diptera: Culicidae)

PubMed Central

2014-01-01

Background Development rates of Aedes aegypti are known to vary with respect to many abiotic and biotic factors including temperature, resource availability, and intraspecific competition. The relative importance of these factors and their interactions are not well established across populations. We performed meta-analysis on a dataset of development rate estimates from 49 studies. Results Meta-analytic results indicated that the environmental factor of temperature is sufficient to explain development rate variability in Ae. aegypti. While diet and density may greatly impact other developmental phenotypes, these results suggest that for development rate these factors should never be considered to the exclusion of temperature. The effect of temperature on development rate is not homogenous or constant. The sources of heterogeneity of the effect of temperature are difficult to analyze due to lack of consistent reporting of larval rearing methods. Conclusions Temperature is the most important ecological determinant of development rate in Ae. aegypti, but its effect is heterogeneous. Ignoring this heterogeneity is problematic for models of vector population and vector-borne disease transmission. PMID:24495345

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…

Collinear Latent Variables in Multilevel Confirmatory Factor Analysis

PubMed Central

van de Schoot, Rens; Hox, Joop

2014-01-01

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

An empirical examination of WISE/NEOWISE asteroid analysis and results

NASA Astrophysics Data System (ADS)

Myhrvold, Nathan

2018-11-01

Asteroid observations by the WISE space telescope and the analysis of those observations by the NEOWISE project have provided more information about the diameter, albedo, and other properties of approximately 164,000 asteroids, more than all other sources combined. The raw data set from this mission will likely be the largest and most important such data on asteroids available for many years. To put this trove of data to productive use, we must understand its strengths and weaknesses, and we need clear and reproducible methods for analyzing the data set. This study critically examines the WISE observational data and the NEOWISE results published in both the original papers and the NASA Planetary Data System (PDS). There seem to be multiple areas where the analysis might benefit from improvement or independent verification. The NEOWISE results were obtained by the application of 10 different modeling methods, many of which are not adequately explained or even defined, to 12 different combinations of WISE band data. More than half of NEOWISE results are based on a single band of data. The majority of curve fits to the data in the NEOWISE results are of poor quality, frequently missing most or all of the data points on which they are based. Complete misses occur for about 30% of single-band results, and among the results derived from the most common multiple-band combinations, about 43% miss all data points in at least one band. The NEOWISE data analysis relies on assumptions that are in many cases inconsistent with each other. A substantial fraction of WISE data was systematically excluded from the NEOWISE analysis. Building on methods developed by Hanuš et al. (2015), I show that error estimates for the WISE observational data were not well characterized, and all observations have true uncertainty at least a factor of 1.3-2.5 times larger than previously described, depending on the band. I also show that the error distribution is not well fit by a normal

A Factor Analysis of The Social Interest Index--Revised.

ERIC Educational Resources Information Center

Zarski, John J.; And Others

1983-01-01

Factor analyzed the Social Interest Index-Revised (SII-R), which measures levels of social interest attained in each of four life task areas. Four factors (N=308) were defined, i.e., a self-significance factor, a love factor, a friendship factor, and a work factor. Results support the empirical validity of the scale. (Author/PAS)

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

PubMed Central

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

2014-01-01

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

Pediatric differentiated thyroid carcinoma in stage I: risk factor analysis for disease free survival

PubMed Central

2009-01-01

Background To examine the outcomes and risk factors in pediatric differentiated thyroid carcinoma (DTC) patients who were defined as TNM stage I because some patients develop disease recurrence but treatment strategy for such stage I pediatric patients is still controversial. Methods We reviewed 57 consecutive TNM stage I patients (15 years or less) with DTC (46 papillary and 11 follicular) who underwent initial treatment at Ito Hospital between 1962 and 2004 (7 males and 50 females; mean age: 13.1 years; mean follow-up: 17.4 years). Clinicopathological results were evaluated in all patients. Multivariate analysis was performed to reveal the risk factors for disease-free survival (DFS) in these 57 patients. Results Extrathyroid extension and clinical lymphadenopathy at diagnosis were found in 7 and 12 patients, respectively. Subtotal/total thyroidectomy was performed in 23 patients, modified neck dissection in 38, and radioactive iodine therapy in 10. Pathological node metastasis was confirmed in 37 patients (64.9%). Fifteen patients (26.3%) exhibited local recurrence and 3 of them also developed metachronous lung metastasis. Ten of these 15 achieved disease-free after further treatments and no patients died of disease. In multivariate analysis, male gender (p = 0.017), advanced tumor (T3, 4a) stage (p = 0.029), and clinical lymphadenopathy (p = 0.006) were risk factors for DFS in stage I pediatric patients. Conclusion Male gender, tumor stage, and lymphadenopathy are risk factors for DFS in stage I pediatric DTC patients. Aggressive treatment (total thyroidectomy, node dissection, and RI therapy) is considered appropriate for patients with risk factors, whereas conservative or stepwise approach may be acceptable for other patients. PMID:19723317

Modifying pro-drug risk factors in adolescents: results from project ALERT.

PubMed

Ghosh-Dastidar, Bonnie; Longshore, Douglas L; Ellickson, Phyllis L; McCaffrey, Daniel F

2004-06-01

The objective of this study was to evaluate the impact of a revised state-of-the-art drug prevention program, Project ALERT, on risk factors for drug use in mostly rural midwestern schools and communities. Fifty-five middle schools from South Dakota were randomly assigned to treatment or control conditions. Treatment-group students received 11 lessons in Grade 7 and 3 more in Grade 8. Effects for 4276 eighth graders were assessed 18 months after baseline. Results indicate that Project ALERT had statistically significant effects on all the targeted risk factors associated with cigarette and marijuana use and more modest gains with the pro-alcohol risk factors. The program helped adolescents at low, moderate, and high risk for future use, with the effect sizes typically stronger for the low- and moderate-risk groups. Thus, school-based drug prevention programs can lower risk factors that correlate with drug use, help low- to high-risk adolescents, and be effective in diverse school environments.

Association between anthropometry, cardiometabolic risk factors, & early life factors & adult measures of endothelial function: Results from the New Delhi Birth Cohort

PubMed Central

Huffman, Mark D.; Khalil, Anita; Osmond, Clive; Fall, Caroline H. D.; Tandon, Nikhil; Lakshmy, Ramakrishnan; Ramji, Siddharth; Gera, Tarun; Prabhakaran, Poornima; Dey Biswas, S. K.; Reddy, K. Srinath; Bhargava, Santosh K.; Sachdev, Harshpal S.; Prabhakaran, Dorairaj

2015-01-01

Background & objectives: Abnormal endothelial function represents a preclinical marker of atherosclerosis. This study was conducted to evaluate associations between anthropometry, cardiometabolic risk factors, and early life factors and adult measures of endothelial function in a young urban Indian cohort free of clinical cardiovascular disease. Methods: Absolute changes in brachial artery diameter following cuff inflation and sublingual nitroglycerin (400 µg) were recorded to evaluate endothelium-dependent and -independent measures of endothelial function in 600 participants (362 men; 238 women) from the New Delhi Birth Cohort (2006-2009). Data on anthropometry, cardiometabolic risk factors, medical history, socio-economic position, and lifestyle habits were collected. Height and weight were recorded at birth, two and 11 yr of age. Age- and sex-adjusted linear regression models were developed to evaluate these associations. Results: The mean age of participants was 36±1 yr. Twenty two per cent men and 29 per cent women were obese (BMI > 30 kg/m2). Mean systolic blood pressure (SBP) was 131±14 and 119±13 mmHg, and diabetes prevalence was 12 and 8 per cent for men and women, respectively. Brachial artery diameter was higher for men compared with women both before (3.48±0.37 and 2.95±0.35 cm) and after hyperaemia (3.87±0.37 vs. 3.37±0.35 cm). A similar difference was seen before and after nitroglycerin. Markers of increased adiposity, smoking, SBP, and metabolic syndrome, but not early life anthropometry, were inversely associated with endothelial function after adjustment for age and sex. Interpretation & conclusions: The analysis of the current prospective data from a young urban Indian cohort showed that cardiometabolic risk factors, but not early life anthropometry, were associated with worse endothelial function. PMID:26831418

Factor Analysis of the Autism Spectrum Screening Questionnaire

ERIC Educational Resources Information Center

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

2008-01-01

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

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

PubMed

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

2017-03-01

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

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

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.

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

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.

Lunar Reconnaissance Orbiter K-Band (26 GHz) Signal Analysis: Initial Study Results

NASA Astrophysics Data System (ADS)

Morabito, D. D.; Heckman, D.

2017-11-01

Lower frequency telemetry bands are becoming more limited in bandwidth due to increased competition between flight projects and other entities. Higher frequency bands offer significantly more bandwidth and hence the prospect of much higher data rates. Future or prospective flight projects considering higher frequency bands such as Ka-band (32 GHz) for deep-space and K-band (26 GHz) for near-Earth telemetry links are interested in past flight experience with available received data at these frequencies. Given that there is increased degradation due to the atmosphere at these higher frequencies, there is an effort to retrieve flight data of received signal strength to analyze performance under a variety of factors. Such factors include elevation angle, season, and atmospheric conditions. This article reports on the analysis findings of over 10 million observations of received signal strength of the Lunar Reconnaissance Orbiter (LRO) spacecraft collected between 2014 and 2017. We analyzed these data to characterize link performance over a wide range of weather conditions, season, and as a function of elevation angle. Based on this analysis, we have confirmed the safety of using a 3-dB margin for preflight planning purposes. These results suggest that a 3-dB margin with respect to adverse conditions will ensure a 98 to 99 percent data return under 95 percent weather conditions at 26 GHz (K-band), thus confirming expectations from link budget predictions. The results suggest that this margin should be applicable for all elevation angles above 10 deg. Thus, missions that have sufficient power for their desired data rates may opt to use 10 deg as their minimum elevation angle. Limitations of this study include climate variability and the fact that the observations require removal of hotbody noise in order to perform an adequate cumulative distribution function (CDF) analysis, which is planned for a future comprehensive study. Flight projects may use other link margins

Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

PubMed

Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

2017-07-15

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal

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…

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

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.

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

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

PubMed Central

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

2015-01-01

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

Human Factors Analysis to Improve the Processing of Ares-1 Launch Vehicle

NASA Technical Reports Server (NTRS)

Dippolito, Gregory M.; Stambolian, Damon B.

2011-01-01

The Constellation Program (CxP) is composed of an array of vehicles used to go to the Moon and Mars. The Ares vehicle one of the components of CxP, goes through several stages of processing before it is launched at the Kennedy Space Center. In order to have efficient and effective ground processing inside and outside the vehicle, all of the ground processing activities should be analyzed. The analysis for this program was performed, by engineers, technicians, and human factors experts with spacecraft processing experience. The procedure used to gather data was accomplished by observing human activities within physical mockups. The paper will focus on the procedures, analysis and results from these observations.

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

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…

Analysis of risk factors for T. brucei rhodesiense sleeping sickness within villages in south-east Uganda

PubMed Central

Zoller, Thomas; Fèvre, Eric M; Welburn, Susan C; Odiit, Martin; Coleman, Paul G

2008-01-01

Background Sleeping sickness (HAT) caused by T.b. rhodesiense is a major veterinary and human public health problem in Uganda. Previous studies have investigated spatial risk factors for T.b. rhodesiense at large geographic scales, but none have properly investigated such risk factors at small scales, i.e. within affected villages. In the present work, we use a case-control methodology to analyse both behavioural and spatial risk factors for HAT in an endemic area. Methods The present study investigates behavioural and occupational risk factors for infection with HAT within villages using a questionnaire-based case-control study conducted in 17 villages endemic for HAT in SE Uganda, and spatial risk factors in 4 high risk villages. For the spatial analysis, the location of homesteads with one or more cases of HAT up to three years prior to the beginning of the study was compared to all non-case homesteads. Analysing spatial associations with respect to irregularly shaped geographical objects required the development of a new approach to geographical analysis in combination with a logistic regression model. Results The study was able to identify, among other behavioural risk factors, having a family member with a history of HAT (p = 0.001) as well as proximity of a homestead to a nearby wetland area (p < 0.001) as strong risk factors for infection. The novel method of analysing complex spatial interactions used in the study can be applied to a range of other diseases. Conclusion Spatial risk factors for HAT are maintained across geographical scales; this consistency is useful in the design of decision support tools for intervention and prevention of the disease. Familial aggregation of cases was confirmed for T. b. rhodesiense HAT in the study and probably results from shared behavioural and spatial risk factors amongmembers of a household. PMID:18590541

Gene expression factor analysis to differentiate pathways linked to fibromyalgia, chronic fatigue syndrome, and depression in a diverse patient sample

PubMed Central

Iacob, Eli; Light, Alan R.; Donaldson, Gary W.; Okifuji, Akiko; Hughen, Ronald W.; White, Andrea T.; Light, Kathleen C.

2015-01-01

Objective To determine if independent candidate genes can be grouped into meaningful biological factors and if these factors are associated with the diagnosis of chronic fatigue syndrome (CFS) and fibromyalgia (FMS) while controlling for co-morbid depression, sex, and age. Methods We included leukocyte mRNA gene expression from a total of 261 individuals including healthy controls (n=61), patients with FMS only (n=15), CFS only (n=33), co-morbid CFS and FMS (n=79), and medication-resistant (n=42) or medication-responsive (n=31) depression. We used Exploratory Factor Analysis (EFA) on 34 candidate genes to determine factor scores and regression analysis to examine if these factors were associated with specific diagnoses. Results EFA resulted in four independent factors with minimal overlap of genes between factors explaining 51% of the variance. We labeled these factors by function as: 1) Purinergic and cellular modulators; 2) Neuronal growth and immune function; 3) Nociception and stress mediators; 4) Energy and mitochondrial function. Regression analysis predicting these biological factors using FMS, CFS, depression severity, age, and sex revealed that greater expression in Factors 1 and 3 was positively associated with CFS and negatively associated with depression severity (QIDS score), but not associated with FMS. Conclusion Expression of candidate genes can be grouped into meaningful clusters, and CFS and depression are associated with the same 2 clusters but in opposite directions when controlling for co-morbid FMS. Given high co-morbid disease and interrelationships between biomarkers, EFA may help determine patient subgroups in this population based on gene expression. PMID:26097208

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

PubMed

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

2016-08-26

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

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…

Causes of accidents in terrain parks: an exploratory factor analysis of recreational freestylers' views.

PubMed

Carús, Luis

2014-03-01

This study examines ski and snowboard terrain park users' views on aspects associated with accidents by identifying and assessing variables that may influence the occurrence of accidents and the resulting injuries. The research was conducted in a major resort in the Spanish Pyrenees, using information gathered from freestyle skiers and snowboarders aged 6 or older. To identify interrelationships among variables and to group the variables belonging to unified concepts, an exploratory factor analysis was performed using varimax rotation. The results revealed 5 factors that grouped the measured variables that may influence the occurrence of accidents while freestyling in terrain parks. The park features, conditions of the activity, and the user's personal conditions were found to have the most substantial influence on the freestylers' perceptions. Variables identified as components of the main factors of accident risk in terrain parks should be incorporated into resort management communication and policies. © 2013 Wilderness Medical Society Published by Wilderness Medical Society All rights reserved.

Breast Cancer Risk From Modifiable and Non-Modifiable Risk Factors among Women in Southeast Asia: A Meta-Analysis

PubMed

Nindrea, Ricvan Dana; Aryandono, Teguh; Lazuardi, Lutfan

2017-12-28

Objective: The aim of this study was to determine breast cancer risk from modifiable and non-modifiable factors among women in Southeast Asia. Methods: This meta-analysis was performed on research articles on breast cancer risk factors in PubMed, ProQuest and EBSCO databases published between 1997 and October 2017. Pooled odds ratios (OR) are calculated using fixed and random-effect models. Data were processed using Review Manager 5.3 (RevMan 5.3). Results: From a total of 1,211 articles, 15 studies (1 cohort and 14 case control studies) met the criteria for systematic review. Meta-analysis results showed that of the known modifiable risk factors for breast cancer, parity (nulipara) had the highest odd ratio (OR = 1.85 [95% CI 1.47-2.32]) followed by body mass index (overweight) (OR = 1.61 [95% CI 1.43-1.80]) and use of oral contraceptives (OR = 1.27 [95% CI 1.07-1.51]). Of non-modifiable risk factors, family history of breast cancer had the highest odd ratio (OR = 2.53 [95% CI 1.25-5.09]), followed by age (≥ 40 years) (OR = 1.53 [95% CI 1.34-1.76]) and menopausal status (OR = 1.44 [95% CI 1.26-1.65]). Conclusion: This analysis confirmed associations between both modifiable risk factors (parity, body mass index and use of oral contraceptives) and non-modifiable risk factors (family history of breast cancer, age and menopausal status) with breast cancer. Creative Commons Attribution License

A Study of Algorithms for Covariance Structure Analysis with Specific Comparisons Using Factor Analysis.

ERIC Educational Resources Information Center

Lee, S. Y.; Jennrich, R. I.

1979-01-01

A variety of algorithms for analyzing covariance structures are considered. Additionally, two methods of estimation, maximum likelihood, and weighted least squares are considered. Comparisons are made between these algorithms and factor analysis. (Author/JKS)

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

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

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

PubMed

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

2016-01-01

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

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…