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.

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…

Exploratory factor analysis in Rehabilitation Psychology: a content analysis.

PubMed

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

2014-11-01

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

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…

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…

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.

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…

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…

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…

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…

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)

What School Psychologists Need to Know about Factor Analysis

ERIC Educational Resources Information Center

McGill, Ryan J.; Dombrowski, Stefan C.

2017-01-01

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

Item Factor Analysis: Current Approaches and Future Directions

ERIC Educational Resources Information Center

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

2007-01-01

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

Q-Type Factor Analysis of Healthy Aged Men.

ERIC Educational Resources Information Center

Kleban, Morton H.

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

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

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.

Factor Rotation and Standard Errors in Exploratory Factor Analysis

ERIC Educational Resources Information Center

Zhang, Guangjian; Preacher, Kristopher J.

2015-01-01

In this article, we report a surprising phenomenon: Oblique CF-varimax and oblique CF-quartimax rotation produced similar point estimates for rotated factor loadings and factor correlations but different standard error estimates in an empirical example. Influences of factor rotation on asymptotic standard errors are investigated using a numerical…

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.

Donor retention in health care in Iran: a factor analysis

PubMed Central

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

2017-01-01

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

The 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…

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 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)

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.

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.

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.

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)

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.

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

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

Hierarchical Factoring Based On Image Analysis And Orthoblique Rotations.

PubMed

Stankov, L

1979-07-01

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

A Factor Analysis of the BSRI and the PAQ.

ERIC Educational Resources Information Center

Edwards, Teresa A.; And Others

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

Analysis of 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…

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…

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.…

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)

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.

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

NASA Astrophysics Data System (ADS)

Taasoobshirazi, Gita; Bailey, MarLynn; Farley, John

2015-11-01

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

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…

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.

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.

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)

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.

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 the Brazilian Version of UPPS Impulsive Behavior Scale

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

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.

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.

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 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…

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…

Purification and characterization of an abnormal factor IX (Christmas factor) molecule. Factor IX Chapel Hill.

PubMed Central

Chung, K S; Madar, D A; Goldsmith, J C; Kingdon, H S; Roberts, H R

1978-01-01

Human Factor IX (Christmas factor) was isolated from the plasma of a patient with mild hemophilia B. The patient's plasma contained 5% Factor IX clotting activity but 100% Factor IX antigenic activity as determined by immunological assays, which included inhibitor neutralization and a radioimmunoassay for Factor IX. This abnormal Factor IX is called Factor IX Chapel Hill (Factor IXCH). Both normal Factor IX and Factor IXCH have tyrosine as the NH2-terminal amino acid. The two proteins have a similar molecular weight, a similar amino acid analysis, the same number of gamma-carboxyglutamic acid residues (10 gamma-carboxyglutamic acid residues), and a similar carbohydrate content. Both exist as a single-chain glycoprotein in plasma. The major difference between normal Factor IX and Factor IXCH is that the latter exhibits delayed activation to Factor IXa in the presence of Factor XIa and Ca2+. Thus, Factor IXCH differs from other previously described abnormal Factor IX molecules. Images PMID:711853

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.

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

PubMed

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

2010-09-01

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

Factor Analysis 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…

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.

Deep Learning with Hierarchical Convolutional Factor Analysis

PubMed Central

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

2013-01-01

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

Factor analysis 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.

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

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…

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)

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.

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.

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

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…

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 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.

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

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…

Landslides geotechnical analysis. Qualitative assessment by valuation factors

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

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...

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.

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.

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.

Confirmatory factor analysis of the female sexual function index.

PubMed

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

2013-01-01

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

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.

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).

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...

Tensor-Dictionary Learning with Deep Kruskal-Factor Analysis

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

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

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

Analysis of 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.

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,…

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.

Analysis of vehicle classification data, including monthly and seasonal ADT factors, hourly distribution factors, and lane distribution factors

DOT National Transportation Integrated Search

1998-11-01

This report documents the development of monthly and seasonal average daily traffic (ADT) factors for performing estimating AADTs. It appears that seasonal factors can estimate AADT as well as monthly factors, and it is recommended that seasonal fact...

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 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…

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.

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.

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.

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…

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 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)

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.

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.

Examining Evolving Performance on the Force Concept Inventory Using Factor Analysis

ERIC Educational Resources Information Center

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

2017-01-01

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

A Markov Chain Monte Carlo Approach to Confirmatory Item Factor Analysis

ERIC Educational Resources Information Center

Edwards, Michael C.

2010-01-01

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

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.

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.

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

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

PubMed

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

2011-01-01

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

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.…

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.

Multiple Interacting Risk Factors: On Methods for Allocating Risk Factor Interactions.

PubMed

Price, Bertram; MacNicoll, Michael

2015-05-01

A persistent problem in health risk analysis where it is known that a disease may occur as a consequence of multiple risk factors with interactions is allocating the total risk of the disease among the individual risk factors. This problem, referred to here as risk apportionment, arises in various venues, including: (i) public health management, (ii) government programs for compensating injured individuals, and (iii) litigation. Two methods have been described in the risk analysis and epidemiology literature for allocating total risk among individual risk factors. One method uses weights to allocate interactions among the individual risk factors. The other method is based on risk accounting axioms and finding an optimal and unique allocation that satisfies the axioms using a procedure borrowed from game theory. Where relative risk or attributable risk is the risk measure, we find that the game-theory-determined allocation is the same as the allocation where risk factor interactions are apportioned to individual risk factors using equal weights. Therefore, the apportionment problem becomes one of selecting a meaningful set of weights for allocating interactions among the individual risk factors. Equal weights and weights proportional to the risks of the individual risk factors are discussed. © 2015 Society for Risk Analysis.

[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.

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…

Discriminative factor analysis of juvenile delinquency in South Korea.

PubMed

Kim, Hyun Sil; Kim, Hun Soo

2006-12-01

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

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.

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.

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

ERIC Educational Resources Information Center

Mittag, Kathleen Cage

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

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…

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

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. �

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

PubMed

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

2015-01-01

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

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…

Confirmatory factor analysis of posttraumatic stress symptoms in sexually harassed women.

PubMed

Palmieri, Patrick A; Fitzgerald, Louise F

2005-12-01

Posttraumatic stress disorder (PTSD) factor analytic research to date has not provided a clear consensus on the structure of posttraumatic stress symptoms. Seven hypothesized factor structures were evaluated using confirmatory factor analysis of the Posttraumatic Stress Disorder Checklist, a paper-and-pencil measure of posttraumatic stress symptom severity, in a sample of 1,218 women who experienced a broad range of workplace sexual harassment. The model specifying correlated re-experiencing, effortful avoidance, emotional numbing, and hyperarousal factors provided the best fit to the data. Virtually no support was obtained for the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV; American Psychiatric Association, 1994) three-factor model of re-experiencing, avoidance, and hyperarousal factors. Different patterns of correlations with external variables were found for the avoidance and emotional numbing factors, providing further validation of the supported model.

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.

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.

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

PubMed

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

2016-06-01

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

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 the Bootstrap Methods in Factor Analysis.

ERIC Educational Resources Information Center

Ichikawa, Masanori; Konishi, Sadanori

1995-01-01

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

Exploratory Factor Analysis with Small Sample Sizes

ERIC Educational Resources Information Center

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

2009-01-01

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

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.

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

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

PubMed

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

2018-03-22

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

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

ERIC Educational Resources Information Center

Ritter, Nicola L.

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-10-01

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

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.

Factor Covariance Analysis in Subgroups.

ERIC Educational Resources Information Center

Pennell, Roger

The problem considered is that of an investigator sampling two or more correlation matrices and desiring to fit a model where a factor pattern matrix is assumed to be identical across samples and we need to estimate only the factor covariance matrix and the unique variance for each sample. A flexible, least squares solution is worked out and…

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.

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.

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…

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…

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.

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.

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

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.

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

PubMed

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

2015-01-01

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

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…

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

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

ERIC Educational Resources Information Center

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

2009-01-01

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

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.

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

ERIC Educational Resources Information Center

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

2011-01-01

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

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 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.

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

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

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

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

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 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.

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,…

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

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…

Confirmatory Factor Analysis of the Elementary School Success Profile for Teachers

ERIC Educational Resources Information Center

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

2012-01-01

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

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

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

Risk factors associated with chronic otitis media (COM) and recurrent otitis media (ROM) have been investigated in previous studies. The objective of this study was to integrate the findings and determine the possible risk factors for COM/ROM based on our meta-analysis. A comprehensive search of electronic bibliographic databases (PubMed, Embase, CNKI and Wanfang database) from 1964 to Dec 2012, as well as a manual search of references of articles, was performed. A total of 2971 articles were searched, and 198 full-text articles were assessed for eligibility; 24 studies were eligible for this meta-analysis. Regarding risk factors for COM/ROM, there were two to nine different studies from which the odds ratios (ORs) could be pooled. The presence of allergy or atopy increased the risk of COM/ROM (OR, 1.36; 95% CI, 1.13–1.64; P = 0.001). An upper respiratory tract infection (URTI) significantly increased the risk of COM/ROM (OR, 6.59; 95% CI, 3.13–13.89; P<0.00001). Snoring appeared to be a significant risk factor for COM/ROM (OR, 1.96; 95% CI, 1.78–2.16; P<0.00001). A patient history of acute otitis media (AOM)/ROM increased the risk of COM/ROM (OR, 11.13; 95% CI, 1.06–116.44; P = 0.04). Passive smoke significantly increased the risk of COM/ROM (OR, 1.39; 95% CI, 1.02–1.89 P = 0.04). Low social status appeared to be a risk factor for COM/ROM (OR, 3.82; 95% CI, 1.11–13.15; P = 0.03). Our meta-analysis identified reliable conclusions that allergy/atopy, URTI, snoring, previous history of AOM/ROM, Second-hand smoke and low social status are important risk factors for COM/ROM. Other unidentified risk factors need to be identified in further studies with critical criteria. PMID:24466073

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.

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

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…

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…

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

PubMed

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

2018-01-01

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

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

Arabidopsis transcription factors: genome-wide comparative analysis among eukaryotes.

PubMed

Riechmann, J L; Heard, J; Martin, G; Reuber, L; Jiang, C; Keddie, J; Adam, L; Pineda, O; Ratcliffe, O J; Samaha, R R; Creelman, R; Pilgrim, M; Broun, P; Zhang, J Z; Ghandehari, D; Sherman, B K; Yu, G

2000-12-15

The completion of the Arabidopsis thaliana genome sequence allows a comparative analysis of transcriptional regulators across the three eukaryotic kingdoms. Arabidopsis dedicates over 5% of its genome to code for more than 1500 transcription factors, about 45% of which are from families specific to plants. Arabidopsis transcription factors that belong to families common to all eukaryotes do not share significant similarity with those of the other kingdoms beyond the conserved DNA binding domains, many of which have been arranged in combinations specific to each lineage. The genome-wide comparison reveals the evolutionary generation of diversity in the regulation of transcription.

Human Factors Analysis of Pipeline Monitoring and Control Operations: Final Technical Report

DOT National Transportation Integrated Search

2008-11-26

The purpose of the Human Factors Analysis of Pipeline Monitoring and Control Operations project was to develop procedures that could be used by liquid pipeline operators to assess and manage the human factors risks in their control rooms that may adv...

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

PubMed

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

1997-07-01

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

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.

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.

Erikson Psychosocial Stage Inventory: A Factor Analysis

ERIC Educational Resources Information Center

Gray, Mary McPhail; And Others

1986-01-01

The 72-item Erikson Psychosocial Stage Inventory (EPSI) was factor analyzed for a group of 534 university freshmen and sophomore students. Seven factors emerged, which were labeled Initiative, Industry, Identity, Friendship, Dating, Goal Clarity, and Self-Confidence. Item's representing Erikson's factors, Trust and Autonomy, were dispersed across…

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2010-03-15

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

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

PubMed Central

2010-01-01

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

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…

Factors influencing societal response of nanotechnology: an expert stakeholder analysis

NASA Astrophysics Data System (ADS)

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

2012-05-01

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

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

Analysis of risk factors for postoperative morbidity in perforated peptic ulcer.

PubMed

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

2012-03-01

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. 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. 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. 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.

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.

Memory systems, processes, and tasks: taxonomic clarification via factor analysis.

PubMed

Bruss, Peter J; Mitchell, David B

2009-01-01

The nature of various memory systems was examined using factor analysis. We reanalyzed data from 11 memory tasks previously reported in Mitchell and Bruss (2003). Four well-defined factors emerged, closely resembling episodic and semantic memory and conceptual and perceptual implicit memory, in line with both memory systems and transfer-appropriate processing accounts. To explore taxonomic issues, we ran separate analyses on the implicit tasks. Using a cross-format manipulation (pictures vs. words), we identified 3 prototypical tasks. Word fragment completion and picture fragment identification tasks were "factor pure," tapping perceptual processes uniquely. Category exemplar generation revealed its conceptual nature, yielding both cross-format priming and a picture superiority effect. In contrast, word stem completion and picture naming were more complex, revealing attributes of both processes.

Final Technical Report: Advanced Measurement and Analysis of PV Derate Factors.

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

King, Bruce Hardison; Burton, Patrick D.; Hansen, Clifford

2015-12-01

The Advanced Measurement and Analysis of PV Derate Factors project focuses on improving the accuracy and reducing the uncertainty of PV performance model predictions by addressing a common element of all PV performance models referred to as “derates”. Widespread use of “rules of thumb”, combined with significant uncertainty regarding appropriate values for these factors contribute to uncertainty in projected energy production.

A Bayes factor meta-analysis of Bem's ESP claim.

PubMed

Rouder, Jeffrey N; Morey, Richard D

2011-08-01

In recent years, statisticians and psychologists have provided the critique that p-values do not capture the evidence afforded by data and are, consequently, ill suited for analysis in scientific endeavors. The issue is particular salient in the assessment of the recent evidence provided for ESP by Bem (2011) in the mainstream Journal of Personality and Social Psychology. Wagenmakers, Wetzels, Borsboom, and van der Maas (Journal of Personality and Social Psychology, 100, 426-432, 2011) have provided an alternative Bayes factor assessment of Bem's data, but their assessment was limited to examining each experiment in isolation. We show here that the variant of the Bayes factor employed by Wagenmakers et al. is inappropriate for making assessments across multiple experiments, and cannot be used to gain an accurate assessment of the total evidence in Bem's data. We develop a meta-analytic Bayes factor that describes how researchers should update their prior beliefs about the odds of hypotheses in light of data across several experiments. We find that the evidence that people can feel the future with neutral and erotic stimuli to be slight, with Bayes factors of 3.23 and 1.57, respectively. There is some evidence, however, for the hypothesis that people can feel the future with emotionally valenced nonerotic stimuli, with a Bayes factor of about 40. Although this value is certainly noteworthy, we believe it is orders of magnitude lower than what is required to overcome appropriate skepticism of ESP.

Discriminatory Analysis II. Factor Analysis and Discrimination

DTIC Science & Technology

1950-10-01

present In a given-’test. The last phase of factor ana2lysis is concerned -- -kv’-~ ’psyc Ig hological-siLr ifi-cance to the rectors, extract -, aed*-hee...tests. However, as IHotelling t s procedu~re is an iterative ~ one,.it can be stopped after the extraction of’ any nuLmber of coiuponenta if., one -deems...need not extract 22 ’l p factors and that one can factior R1 by this method as well as R, However, the fact remains that the coomrponents do not have

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

PubMed Central

2013-01-01

Background: Evidence suggests an elevated prevalence of cardiometabolic risks among persons with spinal cord injury (SCI); however, the unique clustering of risk factors in this population has not been fully explored. Objective: The purpose of this study was to describe unique clustering of cardiometabolic risk factors differentiated by level of injury. Methods: One hundred twenty-one subjects (mean 37 ± 12 years; range, 18–73) with chronic C5 to T12 motor complete SCI were studied. Assessments included medical histories, anthropometrics and blood pressure, and fasting serum lipids, glucose, insulin, and hemoglobin A1c (HbA1c). Results: The most common cardiometabolic risk factors were overweight/obesity, high levels of low-density lipoprotein (LDL-C), and low levels of high-density lipoprotein (HDL-C). Risk clustering was found in 76.9% of the population. Exploratory principal component factor analysis using varimax rotation revealed a 3–factor model in persons with paraplegia (65.4% variance) and a 4–factor solution in persons with tetraplegia (73.3% variance). The differences between groups were emphasized by the varied composition of the extracted factors: Lipid Profile A (total cholesterol [TC] and LDL-C), Body Mass-Hypertension Profile (body mass index [BMI], systolic blood pressure [SBP], and fasting insulin [FI]); Glycemic Profile (fasting glucose and HbA1c), and Lipid Profile B (TG and HDL-C). BMI and SBP formed a separate factor only in persons with tetraplegia. Conclusions: Although the majority of the population with SCI has risk clustering, the composition of the risk clusters may be dependent on level of injury, based on a factor analysis group comparison. This is clinically plausible and relevant as tetraplegics tend to be hypo- to normotensive and more sedentary, resulting in lower HDL-C and a greater propensity toward impaired carbohydrate metabolism. PMID:23960702

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

PubMed

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

2013-01-01

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

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.…

Modifiable risk factors for schizophrenia and autism--shared risk factors impacting on brain development.

PubMed

Hamlyn, Jess; Duhig, Michael; McGrath, John; Scott, James

2013-05-01

Schizophrenia and autism are two poorly understood clinical syndromes that differ in age of onset and clinical profile. However, recent genetic and epidemiological research suggests that these two neurodevelopmental disorders share certain risk factors. The aims of this review are to describe modifiable risk factors that have been identified in both disorders, and, where available, collate salient systematic reviews and meta-analyses that have examined shared risk factors. Based on searches of Medline, Embase and PsycINFO, inspection of review articles and expert opinion, we first compiled a set of candidate modifiable risk factors associated with autism. Where available, we next collated systematic-reviews (with or without meta-analyses) related to modifiable risk factors associated with both autism and schizophrenia. We identified three modifiable risk factors that have been examined in systematic reviews for both autism and schizophrenia. Advanced paternal age was reported as a risk factor for schizophrenia in a single meta-analysis and as a risk factor in two meta-analyses for autism. With respect to pregnancy and birth complications, for autism one meta-analysis identified maternal diabetes and bleeding during pregnancy as risks factors for autism whilst a meta-analysis of eight studies identified obstetric complications as a risk factor for schizophrenia. Migrant status was identified as a risk factor for both autism and schizophrenia. Two separate meta-analyses were identified for each disorder. Despite distinct clinical phenotypes, the evidence suggests that at least some non-genetic risk factors are shared between these two syndromes. In particular, exposure to drugs, nutritional excesses or deficiencies and infectious agents lend themselves to public health interventions. Studies are now needed to quantify any increase in risk of either autism or schizophrenia that is associated with these modifiable environmental factors. Copyright © 2012 Elsevier Inc

Analysis of the financial factors governing the profitability of lunar helium-3

NASA Technical Reports Server (NTRS)

Kulcinski, G. L.; Thompson, H.; Ott, S.

1989-01-01

Financial factors influencing the profitability of the mining and utilization of lunar helium-3 are examined. The analysis addressed the following questions: (1) which financial factors have the greatest leverage on the profitability of He-3; (2) over what range can these factors be varied to keep the He-3 option profitable; and (3) what ultimate effect could this energy source have on the price of electricity for U.S. consumers. Two complementary methods of analysis were used in the assessment: rate of return on incremental investment required and reduction revenue requirements (total cost to customers) achieved. Some of the factors addressed include energy demand, power generation costs with and without fusion, profitability for D-He(3) fusion, annual capital and operating costs, launch mass and costs, He-3 price, and government funding. Specific conclusions are made with respect to each of the companies considered: utilities, lunar mining company, and integrated energy company.

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

PubMed Central

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

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

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

PubMed

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

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

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,…

Rotation Criteria and Hypothesis Testing for Exploratory Factor Analysis: Implications for Factor Pattern Loadings and Interfactor Correlations

ERIC Educational Resources Information Center

Schmitt, Thomas A.; Sass, Daniel A.

2011-01-01

Exploratory factor analysis (EFA) has long been used in the social sciences to depict the relationships between variables/items and latent traits. Researchers face many choices when using EFA, including the choice of rotation criterion, which can be difficult given that few research articles have discussed and/or demonstrated their differences.…

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.

An Analysis of Factors That Affect the Educational Performance of Agricultural Students

ERIC Educational Resources Information Center

Greenway, Gina

2012-01-01

Many factors contribute to student achievement. This study focuses on three areas: how students learn, how student personality type affects performance, and how course format affects performance outcomes. The analysis sought to improve understanding of the direction and magnitude with which each of these factors impacts student success. Improved…

Connections between Graphical Gaussian Models and Factor Analysis

ERIC Educational Resources Information Center

Salgueiro, M. Fatima; Smith, Peter W. F.; McDonald, John W.

2010-01-01

Connections between graphical Gaussian models and classical single-factor models are obtained by parameterizing the single-factor model as a graphical Gaussian model. Models are represented by independence graphs, and associations between each manifest variable and the latent factor are measured by factor partial correlations. Power calculations…

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

PubMed

Ono, Koji

2016-08-01

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

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.

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.

Human Factors in Financial Trading: An Analysis of Trading Incidents.

PubMed

Leaver, Meghan; Reader, Tom W

2016-09-01

This study tests the reliability of a system (FINANS) to collect and analyze incident reports in the financial trading domain and is guided by a human factors taxonomy used to describe error in the trading domain. Research indicates the utility of applying human factors theory to understand error in finance, yet empirical research is lacking. We report on the development of the first system for capturing and analyzing human factors-related issues in operational trading incidents. In the first study, 20 incidents are analyzed by an expert user group against a referent standard to establish the reliability of FINANS. In the second study, 750 incidents are analyzed using distribution, mean, pathway, and associative analysis to describe the data. Kappa scores indicate that categories within FINANS can be reliably used to identify and extract data on human factors-related problems underlying trading incidents. Approximately 1% of trades (n = 750) lead to an incident. Slip/lapse (61%), situation awareness (51%), and teamwork (40%) were found to be the most common problems underlying incidents. For the most serious incidents, problems in situation awareness and teamwork were most common. We show that (a) experts in the trading domain can reliably and accurately code human factors in incidents, (b) 1% of trades incur error, and (c) poor teamwork skills and situation awareness underpin the most critical incidents. This research provides data crucial for ameliorating risk within financial trading organizations, with implications for regulation and policy. © 2016, Human Factors and Ergonomics Society.

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…

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.

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.

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

NASA Astrophysics Data System (ADS)

Rumintang, A.; Sholichin, I.

2018-01-01

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

A COMBINED FACTOR ANALYSIS OF CREATIVITY AND INTELLIGENCE.

PubMed

Cave, R L

1970-04-01

A battery of tests was given to 447 studenits in the secondary schools of Alcoa, Tennessee. The tests were composed of the Lorge-Thorndike Intelligence Tests, and five selected creativity tests. The combined battery of tests was factor analyzed and rotated to an oblique simple structure, and then to a hierachical solution. Three factors were found: the verbal intelligence and reasoning factors identified in many previous studies, and a creativity faotor. The structure was very oblique. The second order factor, g, was found to count for 77% of the variance of the verbal facbor, 89% of the reasoning factor and 48% of the creativity factor. These results were compared with those of previous studies of creativity and intelligence.

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

PubMed

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

2017-04-19

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

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

NASA Astrophysics Data System (ADS)

Yan, F.; Ma, X. F.

2016-08-01

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

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

PubMed

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

2017-06-01

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

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

PubMed

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

2013-12-01

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

Analysis of functional redundancies within the Arabidopsis TCP transcription factor family

PubMed Central

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

2013-01-01

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

Analysis of factors 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).

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

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

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…

Analytic Couple Modeling Introducing Device Design Factor, Fin Factor, Thermal Diffusivity Factor, and Inductance Factor

NASA Technical Reports Server (NTRS)

Mackey, Jon; Sehirlioglu, Alp; Dynys, Fred

2014-01-01

A set of convenient thermoelectric device solutions have been derived in order to capture a number of factors which are previously only resolved with numerical techniques. The concise conversion efficiency equations derived from governing equations provide intuitive and straight-forward design guidelines. These guidelines allow for better device design without requiring detailed numerical modeling. The analytical modeling accounts for factors such as i) variable temperature boundary conditions, ii) lateral heat transfer, iii) temperature variable material properties, and iv) transient operation. New dimensionless parameters, similar to the figure of merit, are introduced including the device design factor, fin factor, thermal diffusivity factor, and inductance factor. These new device factors allow for the straight-forward description of phenomenon generally only captured with numerical work otherwise. As an example a device design factor of 0.38, which accounts for thermal resistance of the hot and cold shoes, can be used to calculate a conversion efficiency of 2.28 while the ideal conversion efficiency based on figure of merit alone would be 6.15. Likewise an ideal couple with efficiency of 6.15 will be reduced to 5.33 when lateral heat is accounted for with a fin factor of 1.0.

Exploratory factor analysis of the Clinical Learning Environment, Supervision and Nurse Teacher Scale (CLES+T).

PubMed

Watson, Paul Barry; Seaton, Philippa; Sims, Deborah; Jamieson, Isabel; Mountier, Jane; Whittle, Rose; Saarikoski, Mikko

2014-01-01

The Clinical Learning Environment, Supervision and Nurse Teacher (CLES+T) scale measures student nurses' perceptions of clinical learning environments. This study evaluates the construct validity and internal reliability of the CLES+T in hospital settings in New Zealand. Comparisons are made between New Zealand and Finnish data. The CLES+T scale was completed by 416 Bachelor of Nursing students following hospital clinical placements between October 2008 and December 2009. Construct validity and internal reliability were assessed using exploratory factor analysis and Cronbach's alpha. Exploratory factor analysis supports 4 factors. Cronbach's alpha ranged from .82 to .93. All items except 1 loaded on the same factors found in unpublished Finnish data. The first factor combined 2 previous components from the published Finnish component analysis and was renamed: connecting with, and learning in, communities of clinical practice. The remaining 3 factors (Nurse teacher, Supervisory relationship, and Leadership style of the manager) corresponded to previous components and their conceptualizations. The CLES+T has good internal reliability and a consistent factor structure across samples. The consistency across international samples supports faculties and hospitals using the CLES+T to benchmark the quality of clinical learning environments provided to students.

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)

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

PubMed

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

2015-07-01

We sought to understand incarcerated youths' perspectives on the role of protective factors and risk factors for juvenile offending. 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. 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. 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.

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

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…

Developing Multidimensional Likert Scales Using Item Factor Analysis: The Case of Four-Point Items

ERIC Educational Resources Information Center

Asún, Rodrigo A.; Rdz-Navarro, Karina; Alvarado, Jesús M.

2016-01-01

This study compares the performance of two approaches in analysing four-point Likert rating scales with a factorial model: the classical factor analysis (FA) and the item factor analysis (IFA). For FA, maximum likelihood and weighted least squares estimations using Pearson correlation matrices among items are compared. For IFA, diagonally weighted…

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…

A CRITERION FACTOR ANALYSIS OF THE SIXTEEN PERSONALITY FACTOR QUESTIONNAIRE.

ERIC Educational Resources Information Center

MAZER, GILBERT E.

THE CORRELATION OF REPORTED VARIATIONS IN COUNSELOR PRACTICES WITH WELL-IDENTIFIED PERSONALITY TRAITS WAS STUDIED. THE SIXTEEN PERSONALITY FACTOR QUESTIONNAIRE (WHICH MEASURES 15 PERSONALITY TRAITS AND INTELLIGENCE) AND THE INVENTORY OF COUNSELING PRACTICES (WHICH EVALUATES 75 COUNSELING PRACTICES) WERE GIVEN TO 120 GRADUATE GUIDANCE STUDENTS AT…

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.

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.

[Analysis on influencing factors of prognosis of patients with acute organophosphorus pesticide poisoning].

PubMed

Guo, C F; Wang, Y; Liu, J H; Shen, P; Wang, H; Wei, Y J; Shi, X F; Zhou, X J; Wang, W W

2016-05-20

To analyze the relationship between risk factors and prognosis of acute organophosphorus pesticide poisoning (AOPP). The clinical data including APACHEⅡ, D-dimer, C-reactive protein, procalcitonin, lactic acid of the 67 cases of acute organophosphorus pesticide poisoning which respectively divided into survival group and death group by the outcome were collected. The independent influcing factors were got by logistic regression analysis. The analysis showed that APACHEⅡ, D-dimer、C-reactive protein and Procalcitonin were influencing factors to evaluate prognosis of AOPP (P<0.05) .Meanwhile, APACHEⅡ and CRP were the independent influencing factors to evaluate prognosis of AOPP (P<0.05). APACHEⅡ26was the optimum thresholds to acess the prognosis of AOPP and its Youden index was largest. APACHEⅡ and CRP played an important role in the assessment of prognosis on AOPP. When APACHEⅡwas more than 26, it suggested the patient of AOPP will have a bad prognosis.

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

PubMed

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

2012-05-01

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

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

Is the Factor Observed in Investigations on the Item-Position Effect Actually the Difficulty Factor?

ERIC Educational Resources Information Center

Schweizer, Karl; Troche, Stefan

2018-01-01

In confirmatory factor analysis quite similar models of measurement serve the detection of the difficulty factor and the factor due to the item-position effect. The item-position effect refers to the increasing dependency among the responses to successively presented items of a test whereas the difficulty factor is ascribed to the wide range of…

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

PubMed

Song, Malin; Chen, Yu; An, Qingxian

2018-05-01

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

[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.

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.

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.

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

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.

Vascular endothelial growth factor and platelet-derived growth factor are potential angiogenic and metastatic factors in human breast cancer.

PubMed

Anan, K; Morisaki, T; Katano, M; Ikubo, A; Kitsuki, H; Uchiyama, A; Kuroki, S; Tanaka, M; Torisu, M

1996-03-01

Angiogenesis is a prerequisite for tumor growth and metastasis. Tumor angiogenesis may be mediated by several angiogenic factors such as vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF), transforming growth factor-alpha, and basic fibroblast growth factor. Differential mRNA expressions of VEGF, PDGF (A chain), transforming growth factor-alpha and basic fibroblast growth factor in 32 primary invasive breast tumors were examined by reverse transcriptase-polymerase chain reaction. We analyzed relationships between mRNA expressions of these angiogenic factors and the degree of angiogenesis, tumor size, and metastasis. Quantification of angiogenesis was achieved by the immunohistochemical staining of endothelial cells with antibody to CD31. VEGF and PDGF-A mRNAs were expressed more frequently in breast tumors than in nontumor breast tissues, whereas no difference was found in expression frequency of either transforming growth factor-alpha or basic fibroblast growth factor mRNA. Vascular counts in tumors correlated with each expression frequency of VEGF and PDGF-A mRNA. PDGF-A mRNA was expressed more frequently in tumors with lymph node metastasis than in those without metastasis. Expression of VEGF and PDGF mRNAs detected by reverse transcriptase-polymerase chain reaction in breast tumors correlates with tumor-related characteristics of angiogenesis and metastatic potential. Analysis of these mRNAs by reverse transcriptase-polymerase chain reaction may be useful for assessing the biologic behavior of a breast tumor before surgical treatment.

A Study of Item Bias for Attitudinal Measurement Using Maximum Likelihood Factor Analysis.

ERIC Educational Resources Information Center

Mayberry, Paul W.

A technique for detecting item bias that is responsive to attitudinal measurement considerations is a maximum likelihood factor analysis procedure comparing multivariate factor structures across various subpopulations, often referred to as SIFASP. The SIFASP technique allows for factorial model comparisons in the testing of various hypotheses…

Analysis of significant factors for dengue fever incidence prediction.

PubMed

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

2016-04-16

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

Meta-analysis of the predictive factors of postpartum fatigue.

PubMed

Badr, Hanan A; Zauszniewski, Jaclene A

2017-08-01

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

Dynamic Factor Analysis of Nonstationary Multivariate Time Series.

ERIC Educational Resources Information Center

Molenaar, Peter C. M.; And Others

1992-01-01

The dynamic factor model proposed by P. C. Molenaar (1985) is exhibited, and a dynamic nonstationary factor model (DNFM) is constructed with latent factor series that have time-varying mean functions. The use of a DNFM is illustrated using data from a television viewing habits study. (SLD)

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.

Factor analysis of financial and operational performance measures of non-profit hospitals.

PubMed

Das, Dhiman

2009-01-01

To understand the important dimensions of the financial and operational performance of non-profit hospitals. Secondary data for non-profit US hospitals between 1996 and 2004. I use iterative principal factor analysis of hospitals' financial and operational ratios for each year of the study. For factor interpretation, I use oblique rotation. Financial ratios were created using cost report data from HCRIS 2552-96 available from the Centers for Medicaid & Medicare Services (CMS). I identify five factors--capital structure, profitability, activity, liquidity, and an operational factor--that explain most of the variation in the performance of non-profit hospitals. I also find that capital structure is more important than profitability in determining the performance of these hospitals. The importance of capital structure highlights a significant shift in the organization of the non-profit hospitals' finances.

[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.

A Confirmatory Factor Analysis of Reilly's Role Overload Scale

ERIC Educational Resources Information Center

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

2006-01-01

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

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

Development and human factors analysis of neuronavigation vs. augmented reality.

PubMed

Pandya, Abhilash; Siadat, Mohammad-Reza; Auner, Greg; Kalash, Mohammad; Ellis, R Darin

2004-01-01

This paper is focused on the human factors analysis comparing a standard neuronavigation system with an augmented reality system. We use a passive articulated arm (Microscribe, Immersion technology) to track a calibrated end-effector mounted video camera. In real time, we superimpose the live video view with the synchronized graphical view of CT-derived segmented object(s) of interest within a phantom skull. Using the same robotic arm, we have developed a neuronavigation system able to show the end-effector of the arm on orthogonal CT scans. Both the AR and the neuronavigation systems have been shown to be within 3mm of accuracy. A human factors study was conducted in which subjects were asked to draw craniotomies and answer questions to gage their understanding of the phantom objects. The human factors study included 21 subjects and indicated that the subjects performed faster, with more accuracy and less errors using the Augmented Reality interface.

Epidermal growth factor receptor gene mutation as risk factor for recurrence in patients with surgically resected lung adenocarcinoma: a matched-pair analysis.

PubMed

Matsumura, Yuki; Owada, Yuki; Yamaura, Takumi; Muto, Satoshi; Osugi, Jun; Hoshino, Mika; Higuchi, Mitsunori; Ohira, Tetsuya; Suzuki, Hiroyuki; Gotoh, Mitsukazu

2016-08-01

Epidermal growth factor receptor (EGFR) mutation is a robust prognostic factor in patients with lung adenocarcinoma (ADC). However, the role of EGFR mutation status as a recurrence-risk factor remains unknown because the presence of such mutations is associated with other background characteristics. We therefore conducted a matched-pair analysis to compare recurrence-free survival (RFS) in matched cohorts of patients with lung ADC. We enrolled 379 patients who underwent surgical resection for lung ADC between 2005 and 2012. We determined the EGFR mutation status of each tumour. Matching their age, gender, smoking history and pathological stage (pStage), we compared RFS between matched cohorts with and without EGFR mutation (n = 86 each). The median age was 67 years, there were 39 (45%) men, 39 (45%) ex- or current smokers and pStage I: 71 (83%), II: 5 (6%), III: 8 (9%), IV: 2 (2%) in each group. The 3- and 5-year RFS rates in patients with mutant and wild-type EGFR were 85 and 78%, and 74 and 60%, respectively, with significant differences between the groups (P = 0.040). Multivariate analysis identified vascular invasion and lymphatic permeation, but not EGFR mutation status, as independent risk factors for recurrence. EGFR-gene mutation might be a favourable recurrence-risk factor in patients with surgically resected lung ADC, but further studies in larger cohorts are needed to verify this hypothesis. © The Author 2016. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

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…

Metropolis-Hastings Robbins-Monro Algorithm for Confirmatory Item Factor Analysis

ERIC Educational Resources Information Center

Cai, Li

2010-01-01

Item factor analysis (IFA), already well established in educational measurement, is increasingly applied to psychological measurement in research settings. However, high-dimensional confirmatory IFA remains a numerical challenge. The current research extends the Metropolis-Hastings Robbins-Monro (MH-RM) algorithm, initially proposed for…

Latent Factor Structure of the Das-Naglieri Cognitive Assessment System: A Confirmatory Factor Analysis in a Chinese Setting

ERIC Educational Resources Information Center

Deng, Ci-ping; Liu, Ming; Wei, Wei; Chan, Raymond C. K.; Das, J. P.

2011-01-01

This study aims to measure the psychometric properties of the Das-Naglieri Cognitive Assessment System (D-N CAS) and to determine its clinical utility in a Chinese context. Confirmatory factor analysis (CFA) was conducted to examine the construct validity of the Chinese version of the D-N CAS among a group of 567, normally developed children.…

Factors influencing wound dehiscence.

PubMed

Riou, J P; Cohen, J R; Johnson, H

1992-03-01

Thirty-one abdominal fascial wound dehiscences occurred in 2,761 patients undergoing major abdominal surgery during a 5-year period (1%). Twenty-two specific local and systemic risk factors were analyzed and compared with the risk factors of a control group of 38 patients undergoing similar procedures without dehiscence. Through multivariate analysis, each factor was assessed as an independent statistical variable. Significant factors (p less than 0.05) were found to include age over 65, wound infection, pulmonary disease, hemodynamic instability, and ostomies in the incision. Additional systemic risk factors that were found to be significant included hypoproteinemia, systemic infection, obesity, uremia, hyperalimentation, malignancy, ascites, steroid use, and hypertension. Risk factors not found to be important independent variables included sex, type of incision, type of closure, foreign body in the wound, anemia, jaundice, and diabetes. When dehiscence and control groups were combined, 30% of patients with at least five significant risk factors developed dehiscence, and all the patients with more than eight risk factors developed a wound dehiscence. There was an overall mortality of 29%, which was directly related to the number of significant risk factors. The co-existence of 9 risk factors portended death in one third of the patients, and all the patients with more than 10 risk factors died.

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

PubMed

Oh, Juyeon; Kim, Jung A

2018-02-01

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

Risk Factors for Internet Gaming Disorder: Psychological Factors and Internet Gaming Characteristics.

PubMed

Rho, Mi Jung; Lee, Hyeseon; Lee, Taek-Ho; Cho, Hyun; Jung, Dong Jin; Kim, Dai-Jin; Choi, In Young

2017-12-27

Background : Understanding the risk factors associated with Internet gaming disorder (IGD) is important to predict and diagnose the condition. The purpose of this study is to identify risk factors that predict IGD based on psychological factors and Internet gaming characteristics; Methods : Online surveys were conducted between 26 November and 26 December 2014. There were 3568 Korean Internet game users among a total of 5003 respondents. We identified 481 IGD gamers and 3087 normal Internet gamers, based on Diagnostic and Statistical Manual for Mental Disorders (DSM-5) criteria. Logistic regression analysis was applied to identify significant risk factors for IGD; Results : The following eight risk factors were found to be significantly associated with IGD: functional and dysfunctional impulsivity (odds ratio: 1.138), belief self-control (1.034), anxiety (1.086), pursuit of desired appetitive goals (1.105), money spent on gaming (1.005), weekday game time (1.081), offline community meeting attendance (2.060), and game community membership (1.393; p < 0.05 for all eight risk factors); Conclusions : These risk factors allow for the prediction and diagnosis of IGD. In the future, these risk factors could also be used to inform clinical services for IGD diagnosis and treatment.

Spatial Dependence and Heterogeneity in Bayesian Factor Analysis: A Cross-National Investigation of Schwartz Values

ERIC Educational Resources Information Center

Stakhovych, Stanislav; Bijmolt, Tammo H. A.; Wedel, Michel

2012-01-01

In this article, we present a Bayesian spatial factor analysis model. We extend previous work on confirmatory factor analysis by including geographically distributed latent variables and accounting for heterogeneity and spatial autocorrelation. The simulation study shows excellent recovery of the model parameters and demonstrates the consequences…

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)

Profile and Risk Factor Analysis of Unintentional Injuries in Children.

PubMed

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

2016-10-01

To study the profile and various risk factors associated with unintentional injuries in children. The study is a cross sectional analysis of data collected from 351 children presenting with unintentional injury to a tertiary care hospital in Navi Mumbai, India. Data were collected about variables based on Haddon Phase Factor Matrix - host, environment and agent factors. Proportions for categorical variables across various groups were compared using Chi square test or Fisher's exact test. Logistic regression model was used to evaluate the factors. Falls (36 %) were the most common injuries followed by bites (23 %). Majority of children were school going children (38 %) followed by preschool children (29 %). Forty-seven percent were from lower socioeconomic class. Commonest place of injury was home (48 %) and the commonest time was evening (49 %). Though there was male predominance in injuries, the difference across gender did not vary significantly (p = 0.15). Poisonings were significantly more common in infants and toddlers and in rural population (p < 0.001); kerosene being the commonest agent. Rural population is at more risk of bites compared to urban (p < 0.001); dog bites being the commonest followed by scorpion bites. Foreign bodies were significantly more common in upper and middle socioeconomic class and bites, in lower socioeconomic class (p < 0.005). Injuries from rural area and lower socioeconomic class were more serious, requiring hospitalization; they were also more likely to present late to the hospital (p < 0.05). Profile of injuries varies widely as per the variations in agent, host and environmental factors. Socio-environmental, economic conditions and infancy-toddler age groups are predisposing risk factors for bites and poisoning. Although rural areas and lower socioeconomic class population are more vulnerable to serious types of injuries, they still lack essential basic medical care.

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

PubMed

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

2013-05-01

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

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…

Factors Predictive of Mathematics Achievement in Kindergarten, First and Third Grades: An Opportunity-Propensity Analysis

ERIC Educational Resources Information Center

Byrnes, James P.; Wasik, Barbara A.

2009-01-01

A secondary analysis of the Early Childhood Longitudinal Study-Kindergarten Sample (N = 17,401) was conducted to determine the factors that are most strongly associated with math achievement during kindergarten, first grade, and third grade. Factors from the following three categories were considered: antecedent factors (e.g., family…

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

Risk factors for incidental durotomy during lumbar surgery: a retrospective study by multivariate analysis.

PubMed

Chen, Zhixiang; Shao, Peng; Sun, Qizhao; Zhao, Dong

2015-03-01

The purpose of the present study was to use a prospectively collected data to evaluate the rate of incidental durotomy (ID) during lumbar surgery and determine the associated risk factors by using univariate and multivariate analysis. We retrospectively reviewed 2184 patients who underwent lumbar surgery from January 1, 2009 to December 31, 2011 at a single hospital. Patients with ID (n=97) were compared with the patients without ID (n=2019). The influences of several potential risk factors that might affect the occurrence of ID were assessed using univariate and multivariate analyses. The overall incidence of ID was 4.62%. Univariate analysis demonstrated that older age, diabetes, lumbar central stenosis, posterior approach, revision surgery, prior lumber surgery and minimal invasive surgery are risk factors for ID during lumbar surgery. However, multivariate analysis identified older age, prior lumber surgery, revision surgery, and minimally invasive surgery as independent risk factors. Older age, prior lumber surgery, revision surgery, and minimal invasive surgery were independent risk factors for ID during lumbar surgery. These findings may guide clinicians making future surgical decisions regarding ID and aid in the patient counseling process to alleviate risks and complications. Copyright © 2015 Elsevier B.V. All rights reserved.

Analysis of ecological factors limiting the destruction of high-moor peat

NASA Astrophysics Data System (ADS)

Dobrovol'skaya, T. G.; Golovchenko, A. V.; Zvyagintsev, D. G.

2014-03-01

This review presents an analysis of literature data and original studies by the authors aimed at revealing the factors inhibiting the destruction of high-moor (oligotrophic) peat. Each of the ecological factors that prevent the decomposition of the high-moor peat by different groups of microorganisms is considered. The acid reaction, low temperatures, and lack of nutrients were found not to be the primary factors inhibiting the destruction of the peat. The limited content of oxygen in the peatbogs leads to a drastic decrease in the number of mycelial microorganisms and a reduction of the activity of hydrolytic and oxidizing enzymes. The main factor inhibiting the decomposition of sphagnum is its mechanical and chemical stability, since animals crushing sphagnum are absent in the soil, and this moss has polysaccharides of special composition. The toxicity of phenol compounds, which is manifested under the aerobic conditions, prevents the activity of all the hydrolytic enzymes. This is the main reason for the slow decomposition of sphagnum peat and the long-term preservation of the residues of bodies and food in high-moor peatlands.

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…

Risk factors in laparoscopic cholecystectomy: a multivariate analysis.

PubMed

Kanakala, Venkatesh; Borowski, David W; Pellen, Michael G C; Dronamraju, Shridhar S; Woodcock, Sean A A; Seymour, Keith; Attwood, Stephen E A; Horgan, Liam F

2011-01-01

Laparoscopic cholecystectomy (LC) is the operation of choice in the treatment of symptomatic gallstone disease. The aim of this study is to identify risk factors for LC, outcomes include operating time, length of stay, conversion rate, morbidity and mortality. All patients undergoing LC between 1998 and 2007 in a single district general hospital. Risk factors were examined using uni- and multivariate analysis. 2117 patients underwent LC, with 1706 (80.6%) patients operated on electively. Male patients were older, had more co-morbidity and more emergency surgery than females. The median post-operative hospital stay was one day, and was positively correlated with the complexity of surgery. Conversion rates were higher in male patients (OR 1.47, p = 0.047) than in females, and increased with co-morbidity. Emergency surgery (OR 1.75, p = 0.005), male gender (OR 1.68, p = 0.005), increasing co-morbidity and complexity of surgery were all positively associated with the incidence of complications (153/2117 [7.2%]), whereas only male gender was significantly associated with mortality (OR 5.71, p = 0.025). Adverse outcome from LC is particularly associated with male gender, but also the patient's co-morbidity, complexity and urgency of surgery. Risk-adjusted outcome analysis is desirable to ensure an informed consent process. Copyright © 2011 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

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.

Modification and Factor Analysis of the Grief Experience Inventory in Non-Death Loss/Bereavement Situations.

ERIC Educational Resources Information Center

Zinner, Ellen S.; And Others

1991-01-01

Administered Grief Experience Inventory (GEI) to 102 mothers of brain-injured adolescents and young adults across 3 years postinjury. Factor analysis of data was computed and compared to factors derived from original GEI General Reference Group (n=135). Found strikingly similar factor structures between modified nondeath form and original GEI.…

A risk-factor analysis of medical litigation judgments related to fall injuries in Korea.

PubMed

Kim, Insook; Won, Seonae; Lee, Mijin; Lee, Won

2018-01-01

The aim of this study was to find out the risk factors through analysis of seven medical malpractice judgments related to fall injuries. The risk factors were analysed by using the framework that approaches falls from a systems perspective and comprised people, organisational or environmental factors, with each factor being comprised of subfactors. The risk factors found in each of the seven judgments were aggregated into one framework. The risk factors related to patients (i.e. the people factor) were age, pain, related disease, activities and functional status, urination state, cognitive function impairment, past history of fall, blood transfusion, sleep endoscopy state and uncooperative attitude. The risk factors related to the medical staff and caregivers (i.e. people factor) were observation negligence, no fall prevention activities and negligence in managing high-risk group for fall. Organisational risk factors were a lack of workforce, a lack of training, neglecting the management of the high-risk group, neglecting the management of caregivers and the absence of a fall prevention procedure. Regarding the environment, the risk factors were found to be the emergency room, chairs without a backrest and the examination table. Identifying risk factors is essential for preventing fall accidents, since falls are preventable patient-safety incidents. Falls do not happen as a result of a single risk factor. Therefore, a systems approach is effective to identify risk factors, especially organisational and environmental factors.

Organizational commitment and job satisfaction among nurses in Serbia: a factor analysis.

PubMed

Veličković, Vladica M; Višnjić, Aleksandar; Jović, Slađana; Radulović, Olivera; Šargić, Čedomir; Mihajlović, Jovan; Mladenović, Jelena

2014-01-01

One of the basic prerequisites of efficient organizational management in health institutions is certainly monitoring and measuring satisfaction of employees and their commitment to the health institution in which they work. The aim of this article was to identify and test factors that may have a predictive effect on job satisfaction and organizational commitment. We conducted a cross-sectional study that included 1,337 nurses from Serbia. Data were analyzed by using exploratory factor analysis, multivariate regressions, and descriptive statistics. The study identified three major factors of organizational commitment: affective commitment, disloyalty, and continuance commitment. The most important predictors of these factors were positive professional identification, extrinsic job satisfaction, and intrinsic job satisfaction (p < .0001). Predictors significantly affecting both job satisfaction and organizational commitment were identified as well; the most important of which was positive professional identification (p < .0001). This study identified the main factors affecting job satisfaction and organizational commitment of nurses, which formed a good basis for the creation of organizational management policy and human resource management policy in health institutions in Serbia. Copyright © 2014 Elsevier Inc. All rights reserved.

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

DOEpatents

Keenan, Michael R.

2008-12-30

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

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

PubMed

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

2011-08-15

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

Path analysis of risk factors leading to premature birth.

PubMed

Fields, S J; Livshits, G; Sirotta, L; Merlob, P

1996-01-01

The present study tested whether various sociodemographic, anthropometric, behavioral, and medical/physiological factors act in a direct or indirect manner on the risk of prematurity using path analysis on a sample of Israeli births. The path model shows that medical complications, primarily toxemia, chorioammionitis, and a previous low birth weight delivery directly and significantly act on the risk of prematurity as do low maternal pregnancy weight gain and ethnicity. Other medical complications, including chronic hypertension, preclampsia, and placental abruption, although significantly correlated with prematurity, act indirectly on prematurity through toxemia. The model further shows that the commonly accepted sociodemographic, anthropometric, and behavioral risk factors act by modifying the development of medical complications that lead to prematurity as opposed to having a direct effect on premature delivery. © 1996 Wiley-Liss, Inc. Copyright © 1996 Wiley-Liss, Inc.

Multi-criteria Analysis of Factors for Application of Concrete Composites Considering Their Environmental Harmfulness

NASA Astrophysics Data System (ADS)

Paulikova, A.; Estokova, A.; Mitterpach, J.

2017-10-01

The analysis of factors is important in insight of the selection of proper building material with environmental added value. A comprehensive solution is possible if at the beginning there are all the relevant factors in detail characterized predominately that have got a major impact on the area in terms of environmentalharmfulness prevention. There are many groups of environmental factors. In this article only four factors are considered, i.e. contain of CrVI (mg/kg) and index of mass activity for radionuclides (Ra, Th, K) which are the most harmful. These factors can be evaluated by means of a supplementary tool, e.g. multi-criteriaanalysis, which improves and supports decision processes in the framework of construction bybuilding management, etc.

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

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

PubMed

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

2007-04-01

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

Risk Factors for Internet Gaming Disorder: Psychological Factors and Internet Gaming Characteristics

PubMed Central

Lee, Hyeseon; Lee, Taek-Ho; Cho, Hyun; Kim, Dai-Jin; Choi, In Young

2017-01-01

Background: Understanding the risk factors associated with Internet gaming disorder (IGD) is important to predict and diagnose the condition. The purpose of this study is to identify risk factors that predict IGD based on psychological factors and Internet gaming characteristics; Methods: Online surveys were conducted between 26 November and 26 December 2014. There were 3568 Korean Internet game users among a total of 5003 respondents. We identified 481 IGD gamers and 3087 normal Internet gamers, based on Diagnostic and Statistical Manual for Mental Disorders (DSM-5) criteria. Logistic regression analysis was applied to identify significant risk factors for IGD; Results: The following eight risk factors were found to be significantly associated with IGD: functional and dysfunctional impulsivity (odds ratio: 1.138), belief self-control (1.034), anxiety (1.086), pursuit of desired appetitive goals (1.105), money spent on gaming (1.005), weekday game time (1.081), offline community meeting attendance (2.060), and game community membership (1.393; p < 0.05 for all eight risk factors); Conclusions: These risk factors allow for the prediction and diagnosis of IGD. In the future, these risk factors could also be used to inform clinical services for IGD diagnosis and treatment. PMID:29280953

Tumour Necrosis Factor-alpha and Nuclear Factor-kappa B Gene Variants in Sepsis.

PubMed

Acar, Leyla; Atalan, Nazan; Karagedik, E Hande; Ergen, Arzu

2018-01-20

The humoral system is activated and various cytokines are released due to infections in tissues and traumatic damage. Nuclear factor-kappa B dimers are encoded by nuclear factor-kappa B genes and regulate transcription of several crucial proteins of inflammation such as tumour necrosis factor-alpha. To investigate the possible effect of polymorphisms on tumour necrosis factor-alpha serum levels with clinical and prognostic parameters of sepsis by determining the nuclear factor-kappa B-1-94 ins/del ATTG and tumour necrosis factor-alpha (-308 G/A) gene polymorphisms and tumour necrosis factor-alpha serum levels. Case-control study. Seventy-two patients with sepsis and 104 healthy controls were included in the study. In order to determine the polymorphisms of nuclear factor-kappa B-1-94 ins/del ATTG and tumour necrosis factor-alpha (-308 G/A), polymerase chain reaction-restriction fragment length polymorphism analysis was performed and serum tumour necrosis factor-alpha levels were determined using an enzyme-linked immunosorbent assay. We observed no significant differences in tumour necrosis factor-alpha serum levels between the study groups. In the patient group, an increase in the tumour necrosis factor-alpha serum levels in patients carrying the tumour necrosis factor-alpha (-308 G/A) A allele compared to those without the A allele was found to be statistically significant. Additionally, an increase in the tumour necrosis factor-alpha serum levels in patients carrying tumour necrosis factor-alpha (-308 G/A) AA genotype compared with patients carrying the AG or GG genotypes was statistically significant. No significant differences were found in these 2 polymorphisms between the patient and control groups (p>0.05). Our results showed the AA genotype and the A allele of the tumour necrosis factor-alpha (-308 G/A) polymorphism may be used as a predictor of elevated tumour necrosis factor-alpha levels in patients with sepsis.

Validation of the Adolescent Concerns Measure (ACM): evidence from exploratory and confirmatory factor analysis.

PubMed

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

2007-01-01

This article reports the development and initial validation of scores obtained from the Adolescent Concerns Measure (ACM), a scale which assesses concerns of Asian adolescent students. In Study 1, findings from exploratory factor analysis using 619 adolescents suggested a 24-item scale with four correlated factors--Family Concerns (9 items), Peer Concerns (5 items), Personal Concerns (6 items), and School Concerns (4 items). Initial estimates of convergent validity for ACM scores were also reported. The four-factor structure of ACM scores derived from Study 1 was confirmed via confirmatory factor analysis in Study 2 using a two-fold cross-validation procedure with a separate sample of 811 adolescents. Support was found for both the multidimensional and hierarchical models of adolescent concerns using the ACM. Internal consistency and test-retest reliability estimates were adequate for research purposes. ACM scores show promise as a reliable and potentially valid measure of Asian adolescents' concerns.

Multifactorial analysis of factors affecting recurrence of stroke in Japan.

PubMed

Omori, Toyonori; Kawagoe, Masahiro; Moriyama, Michiko; Yasuda, Takeshi; Ito, Yasuhiro; Hyakuta, Takeshi; Nagatsuka, Kazuyuki; Matsumoto, Masayasu

2015-03-01

Data on factors affecting stroke recurrence are relatively limited. The authors examined potential factors affecting stroke recurrence, retrospectively. The study participants were 1087 patients who were admitted to stroke centers suffering from first-ever ischemic stroke and returned questionnaires with usable information after discharge. The authors analyzed the association between clinical parameters of the patients and their prognosis. Recurrence rate of during an average of 2 years after discharge was 21.3%, and there were differences among stroke subtypes. It was found that the disability level of the patients after discharge correlated well with the level at discharge (r s = 0.66). Multivariate logistic regression analysis of the data shows that modified Rankin Scale score, National Institute of Health Stroke Scale score, gender, age, and family history had statistically significant impacts on stroke recurrence, and the impact was different depending on subtypes. These findings suggest that aggressive and persistent health education for poststroke patients and management of risk factors are essential to reduce stroke recurrence. © 2012 APJPH.

A hierarchical factor analysis of a safety culture survey.

PubMed

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

2013-06-01

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

Dental Students' Perceptions of Risk Factors for Musculoskeletal Disorders: Adapting the Job Factors Questionnaire for Dentistry.

PubMed

Presoto, Cristina D; Wajngarten, Danielle; Domingos, Patrícia A S; Campos, Juliana A D B; Garcia, Patrícia P N S

2018-01-01

The aims of this study were to adapt the Job Factors Questionnaire to the field of dentistry, evaluate its psychometric properties, evaluate dental students' perceptions of work/study risk factors for musculoskeletal disorders, and determine the influence of gender and academic level on those perceptions. All 580 students enrolled in two Brazilian dental schools in 2015 were invited to participate in the study. A three-factor structure (Repetitiveness, Work Posture, and External Factors) was tested through confirmatory factor analysis. Convergent validity was estimated using the average variance extracted (AVE), discriminant validity was based on the correlational analysis of the factors, and reliability was assessed. A causal model was created using structural equation modeling to evaluate the influence of gender and academic level on students' perceptions. A total of 480 students completed the questionnaire for an 83% response rate. The responding students' average age was 21.6 years (SD=2.98), and 74.8% were women. Higher scores were observed on the Work Posture factor items. The refined model presented proper fit to the studied sample. Convergent validity was compromised only for External Factors (AVE=0.47), and discriminant validity was compromised for Work Posture and External Factors (r 2 =0.69). Reliability was adequate. Academic level did not have a significant impact on the factors, but the women students exhibited greater perception. Overall, the adaptation resulted in a useful instrument for assessing perceptions of risk factors for musculoskeletal disorders. Gender was found to significantly influence all three factors, with women showing greater perception of the risk factors.

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.

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

PubMed

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

2016-05-01

The risk factors for cement leakage were retrospectively reviewed in 192 patients who underwent percutaneous vertebral augmentation (PVA). To discuss the factors related to the cement leakage in PVA procedure for the treatment of osteoporotic vertebral compression fractures. PVA is widely applied for the treatment of osteoporotic vertebral fractures. Cement leakage is a major complication of this procedure. The risk factors for cement leakage were controversial. A retrospective review of 192 patients who underwent PVA was conducted. The following data were recorded: age, sex, bone density, number of fractured vertebrae before surgery, number of treated vertebrae, severity of the treated vertebrae, operative approach, volume of injected bone cement, preoperative vertebral compression ratio, preoperative local kyphosis angle, intraosseous clefts, preoperative vertebral cortical bone defect, and ratio and type of cement leakage. To study the correlation between each factor and cement leakage ratio, bivariate regression analysis was employed to perform univariate analysis, whereas multivariate linear regression analysis was employed to perform multivariate analysis. The study included 192 patients (282 treated vertebrae), and cement leakage occurred in 100 vertebrae (35.46%). The vertebrae with preoperative cortical bone defects generally exhibited higher cement leakage ratio, and the leakage is typically type C. Vertebrae with intact cortical bones before the procedure tend to experience type S leakage. Univariate analysis showed that patient age, bone density, number of fractured vertebrae before surgery, and vertebral cortical bone were associated with cement leakage ratio (P<0.05). Multivariate analysis showed that the main factors influencing bone cement leakage are bone density and vertebral cortical bone defect, with standardized partial regression coefficients of -0.085 and 0.144, respectively. High bone density and vertebral cortical bone defect are

WOrk-Related Questionnaire for UPper extremity disorders (WORQ-UP): Factor Analysis and Internal Consistency.

PubMed

Aerts, Bas R; Kuijer, P Paul; Beumer, Annechien; Eygendaal, Denise; Frings-Dresen, Monique H

2018-04-17

To test a 17-item questionnaire, the WOrk-Related Questionnaire for UPper extremity disorders (WORQ-UP), for dimensionality of the items (factor analysis) and internal consistency. Cross-sectional study. Outpatient clinic. A consecutive sample of patients (N=150) consisting of all new referral patients (either from a general physician or other hospital) who visited the orthopedic outpatient clinic because of an upper extremity musculoskeletal disorder. Not applicable. Number and dimensionality of the factors in the WORQ-UP. Four factors with eigenvalues (EVs) >1.0 were found. The factors were named exertion, dexterity, tools & equipment, and mobility. The EVs of the factors were, respectively, 5.78, 2.38, 1.81, and 1.24. The factors together explained 65.9% of the variance. The Cronbach alpha values for these factors were, respectively, .88, .74, .87, and .66. The 17 items of the WORQ-UP resemble 4 factors-exertion, dexterity, tools & equipment, and mobility-with a good internal consistency. Copyright © 2018 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

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.

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 Operability Timeline Analysis to Improve the Processing Flow of the Orion Spacecraft

NASA Technical Reports Server (NTRS)

Stambolian, Damon B.; Schlierf, Roland; Miller, Darcy; Posada, Juan; Haddock, Mike; Haddad, Mike; Tran, Donald; Henderon, Gena; Barth, Tim

2011-01-01

This slide presentation reviews the use of Human factors and timeline analysis to have a more efficient and effective processing flow. The solution involved developing a written timeline of events that included each activity within each functional flow block. Each activity had computer animation videos and pictures of the people involved and the hardware. The Human Factors Engineering Analysis Tool (HFEAT) was improved by modifying it to include the timeline of events. The HFEAT was used to define the human factors requirements and design solutions were developed for these requirements. An example of a functional flow block diagram is shown, and a view from one of the animations (i.e., short stack pallet) is shown and explained.

A Comparison of Imputation Methods for Bayesian Factor Analysis Models

ERIC Educational Resources Information Center

Merkle, Edgar C.

2011-01-01

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

Confirmatory Factor Analysis of the KABC-II in Preschool Children

ERIC Educational Resources Information Center

Morgan, Kimberly E.; Rothlisberg, Barbara A.; McIntosh, David E.; Hunt, Madeline S.

2009-01-01

The present study assessed the Kaufman Assessment Battery for Children, Second Edition (KABC-II) in relation to the synthesized Cattell-Horn-Carroll (CHC) theory of intelligence with a preschool sample. Participants were 200 preschool children between four and five years of age. A confirmatory factor analysis (CFA) was conducted, and different…

The activation of plasminogen by Hageman factor (Factor XII) and Hageman factor fragments.

PubMed Central

Goldsmith, G H; Saito, H; Ratnoff, O S

1978-01-01

Activation of plasminogen through surface-mediated reactions is well recognized. In the presence of kaolin, purified Hageman factor (Factor XII) changed plasminogen to plasmin, as assayed upon a synthetic amide substrate and by fibrinolysis. Kinetic studies suggested an enzymatic action of Hageman factor upon its substrate, plasminogen. Hageman factor fragments, at a protein concentration equivalent to whole Hageman factor, activated plasminogen to a lesser extent. These protein preparations were not contaminated with other agents implicated in surface-mediated fibrinolysis. Diisopropyl fluorophosphate treatment of plasminogen did not inhibit its activation by Hageman factor. These studies indicate that Hageman factor has a hitherto unsuspected function, the direct activation of plasminogen. PMID:659637

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

Confirmatory factor analysis of the Oral Health Impact Profile.

PubMed

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

2014-09-01

Previous exploratory analyses suggest that the Oral Health Impact Profile (OHIP) consists of four correlated dimensions and that individual differences in OHIP total scores reflect an underlying higher-order factor. The aim of this report is to corroborate these findings in the Dimensions of Oral Health-Related Quality of Life (DOQ) Project, an international study of general population subjects and prosthodontic patients. Using the project's Validation Sample (n = 5022), we conducted confirmatory factor analyses in a sample of 4993 subjects with sufficiently complete data. In particular, we compared the psychometric performance of three models: a unidimensional model, a four-factor model and a bifactor model that included one general factor and four group factors. Using model-fit criteria and factor interpretability as guides, the four-factor model was deemed best in terms of strong item loadings, model fit (RMSEA = 0·05, CFI = 0·99) and interpretability. These results corroborate our previous findings that four highly correlated factors - which we have named Oral Function, Oro-facial Pain, Oro-facial Appearance and Psychosocial Impact - can be reliably extracted from the OHIP item pool. However, the good fit of the unidimensional model and the high interfactor correlations in the four-factor solution suggest that OHRQoL can also be sufficiently described with one score. © 2014 John Wiley & Sons Ltd.

Constructing the Japanese version of the Maslach Burnout Inventory-Student Survey: Confirmatory factor analysis.

PubMed

Tsubakita, Takashi; Shimazaki, Kazuyo

2016-01-01

To examine the factorial validity of the Maslach Burnout Inventory-Student Survey, using a sample of 2061 Japanese university students majoring in the medical and natural sciences (67.9% male, 31.8% female; Mage  = 19.6 years, standard deviation = 1.5). The back-translated scale used unreversed items to assess inefficacy. The inventory's descriptive properties and Cronbach's alphas were calculated using SPSS software. The present authors compared fit indices of the null, one factor, and default three factor models via confirmatory factor analysis with maximum-likelihood estimation using AMOS software, version 21.0. Intercorrelations between exhaustion, cynicism, and inefficacy were relatively higher than in prior studies. Cronbach's alphas were 0.76, 0.85, and 0.78, respectively. Although fit indices of the hypothesized three factor model did not meet the respective criteria, the model demonstrated better fit than did the null and one factor models. The present authors added four paths between error variables within items, but the modified model did not show satisfactory fit. Subsequent analysis revealed that a bi-factor model fit the data better than did the hypothesized or modified three factor models. The Japanese version of the Maslach Burnout Inventory-Student Survey needs minor changes to improve the fit of its three factor model, but the scale as a whole can be used to adequately assess overall academic burnout in Japanese university students. Although the scale was back-translated, two items measuring exhaustion whose expressions overlapped should be modified, and all items measuring inefficacy should be reversed in order to statistically clarify the factorial difference between the scale's three factors. © 2015 The Authors. Japan Journal of Nursing Science © 2015 Japan Academy of Nursing Science.

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

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

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

PubMed

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

2012-10-10

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

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.

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

PubMed Central

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

2014-01-01

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

Nattokinase decreases plasma levels of fibrinogen, factor VII, and factor VIII in human subjects.

PubMed

Hsia, Chien-Hsun; Shen, Ming-Ching; Lin, Jen-Shiou; Wen, Yao-Ke; Hwang, Kai-Lin; Cham, Thau-Ming; Yang, Nae-Cherng

2009-03-01

Nattokinase, a serine proteinase from Bacillus subtilis, is considered to be one of the most active functional ingredients found in natto. In this study, we hypothesized that nattokinase could reduce certain factors of blood clotting and lipids that are associated with an increase risk for cardiovascular disease (CVD). Thus, an open-label, self-controlled clinical trial was conducted on subjects of the following groups: healthy volunteers (Healthy Group), patients with cardiovascular risk factors (Cardiovascular Group), and patients undergoing dialysis (Dialysis Group). All subjects ingested 2 capsules of nattokinase (2000 fibrinolysis units per capsule) daily orally for 2 months. The laboratory measurements were performed on the screening visit and, subsequently, regularly after the initiation of the study. The intent-to-treat analysis was performed on all 45 enrolled subjects. By use of mixed model analysis, a significant time effect, but not group effect, was observed in the change from baseline of fibrinogen (P = .003), factor VII (P < .001), and factor VIII (P < .001), suggesting that the plasma levels of the 3 coagulation factors continuously declined during intake; also, the extents of decrease were similar between groups. After 2 months of administration, fibrinogen, factor VII, and factor VIII decreased 9%, 14%, and 17%, respectively, for the Healthy Group; 7%, 13%, and 19%, respectively, for the Cardiovascular Group; and 10%, 7%, and 19%, respectively, for the Dialysis Group, whereas blood lipids were unaffected by nattokinase. No significant changes of uric acid or notable adverse events were observed in any of the subjects. In summary, this study showed that oral administration of nattokinase could be considered as a CVD nutraceutical by decreasing plasma levels of fibrinogen, factor VII, and factor VIII.

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.

Does the Factor Structure of Military Sexual Stressors in Men Correspond to Women's? A Confirmatory Factor Analysis Using the Sexual Harassment Inventory.

PubMed

Reddy, Madhavi K; Murdoch, Maureen

2016-02-01

Unwanted sexual stressors experienced by military men and women are associated with a host of negative physical and mental health problems. Government officials are making it a priority to put a stop to these unwanted sexual experiences. However, the measure typically used measures sexual stressors much better for women than for men. The purpose of the present study was to test the factor structure of an alternative measure, the Sexual Harassment Inventory (SHI), to examine whether sexual stressors experienced by men correspond to women's experiences. We used three preexisting datasets in which the SHI was used to assess active and former military members' sexual stressor experiences. We conducted an exploratory factor analysis to identify women's response patterns and a confirmatory factor analysis to determine whether men's response patterns corresponded to women's. Findings showed that the SHI has evidence of factorial validity in female service members and adequate, but not exceptional, factorial fit for male service members. It is imperative that more work be done to better understand how men experience and perceive potential military sexual stressors and how those perceptions and experiences compare to women's. Reprint & Copyright © 2016 Association of Military Surgeons of the U.S.

Human Modeling for Ground Processing Human Factors Engineering Analysis

NASA Technical Reports Server (NTRS)

Stambolian, Damon B.; Lawrence, Brad A.; Stelges, Katrine S.; Steady, Marie-Jeanne O.; Ridgwell, Lora C.; Mills, Robert E.; Henderson, Gena; Tran, Donald; Barth, Tim

2011-01-01

There have been many advancements and accomplishments over the last few years using human modeling for human factors engineering analysis for design of spacecraft. The key methods used for this are motion capture and computer generated human models. The focus of this paper is to explain the human modeling currently used at Kennedy Space Center (KSC), and to explain the future plans for human modeling for future spacecraft designs

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

Endoscopic carpal tunnel release: a prospective analysis of factors associated with unsatisfactory results.

PubMed

Straub, T A

1999-04-01

The first 100 consecutive cases of endoscopic carpal tunnel release (ECTR) performed by the author were studied prospectively during 6 to 24 months follow-up. Various preoperative and postoperative factors were subjected to statistical analysis to determine possible associations with unsatisfactory results. Overall, 92% of hands had a satisfactory result from ECTR, although not all were rendered symptom-free. There were no significant complications. Preoperative factors associated with an increased likelihood of unsatisfactory results included hands with preoperative weakness, widened two-point discrimination, myofascial pain syndrome or fibromyalgia, involvement in litigation, multiple compressive neuropathies, or the presence of abnormal psychological factors. A trend to less satisfactory results was present in Workers' Compensation cases and patients with normal motor latencies on nerve conduction studies. Multiple postoperative factors correlated with unsatisfactory results.

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)

Identification of regional activation by factorization of high-density surface EMG signals: A comparison of Principal Component Analysis and Non-negative Matrix factorization.

PubMed

Gallina, Alessio; Garland, S Jayne; Wakeling, James M

2018-05-22

In this study, we investigated whether principal component analysis (PCA) and non-negative matrix factorization (NMF) perform similarly for the identification of regional activation within the human vastus medialis. EMG signals from 64 locations over the VM were collected from twelve participants while performing a low-force isometric knee extension. The envelope of the EMG signal of each channel was calculated by low-pass filtering (8 Hz) the monopolar EMG signal after rectification. The data matrix was factorized using PCA and NMF, and up to 5 factors were considered for each algorithm. Association between explained variance, spatial weights and temporal scores between the two algorithms were compared using Pearson correlation. For both PCA and NMF, a single factor explained approximately 70% of the variance of the signal, while two and three factors explained just over 85% or 90%. The variance explained by PCA and NMF was highly comparable (R > 0.99). Spatial weights and temporal scores extracted with non-negative reconstruction of PCA and NMF were highly associated (all p < 0.001, mean R > 0.97). Regional VM activation can be identified using high-density surface EMG and factorization algorithms. Regional activation explains up to 30% of the variance of the signal, as identified through both PCA and NMF. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

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

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…

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

Dispersive analysis of the pion transition form factor.

PubMed

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

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 [Formula: see text] cross section, generalizing previous studies on [Formula: see text] decays and [Formula: see text] scattering, and verify our result by comparing to [Formula: see text] data. We perform the analytic continuation to the space-like region, predicting the poorly-constrained space-like transition form factor below [Formula: see text], and extract the slope of the form factor at vanishing momentum transfer [Formula: see text]. 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.

Risk Factor Analysis in Low-Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (GPFA-AB)

DOE Data Explorer

Teresa E. Jordan

2015-09-30

This submission contains information used to compute the risk factors for the GPFA-AB project (DE-EE0006726). The risk factors are natural reservoir quality, thermal resource quality, potential for induced seismicity, and utilization. The methods used to combine the risk factors included taking the product, sum, and minimum of the four risk factors. The files are divided into images, rasters, shapefiles, and supporting information. The image files show what the raster and shapefiles should look like. The raster files contain the input risk factors, calculation of the scaled risk factors, and calculation of the combined risk factors. The shapefiles include definition of the fairways, definition of the US Census Places, the center of the raster cells, and locations of industries. Supporting information contains details of the calculations or processing used in generating the files. An image of the raster will have the same name except *.png as the file ending instead of *.tif. Images with “fairways” or “industries” added to the name are composed of a raster with the relevant shapefile added. The file About_GPFA-AB_Phase1RiskAnalysisTask5DataUpload.pdf contains information the citation, special use considerations, authorship, etc. More details on each file are given in the spreadsheet “list_of_contents.csv” in the folder “SupportingInfo”. Code used to calculate values is available at https://github.com/calvinwhealton/geothermal_pfa under the folder “combining_metrics”.

Risk factors for osteoarthritis and contributing factors to current arthritic pain in South Korean older adults.

PubMed

Lee, Kyoung Min; Chung, Chin Youb; Sung, Ki Hyuk; Lee, Seung Yeol; Won, Sung Hun; Kim, Tae Gyun; Choi, Young; Kwon, Soon Sun; Kim, Yeon Ho; Park, Moon Seok

2015-01-01

Although previous studies have focused on risk factors for osteoarthritis, there is some debate on this issue. Furthermore, associated factors with arthritic symptom (arthralgia) have not been sufficiently investigated, despite its clinical importance in the management of osteoarthritis. This study was performed to examine the risk factors for osteoarthritis and the contributing factors to current arthritic pain in older adults. The Fourth Korean National Health and Nutrition Examination Surveys was conducted in 2009. Therein, 720 males and 1008 females aged 65 years and older were included. Comprehensive data on habitual, socioeconomic, medical, nutritional, and psychological factors were collected along with the presence of osteoarthritis and arthritic pain. After univariate analysis, binary logistic regression analysis was performed to identify risk factors for osteoarthritis and contributing factors to current arthritic pain. Age (p=0.005), female gender (p<0.001), higher body mass index (BMI) (p<0.001), and osteoporosis (p<0.001) were significant risk factors for osteoarthritis, while higher education level (p=0.025) was a protective factor for osteoarthritis. Higher BMI (p=0.047), lack of weekly moderate intensity activity (p<0.001), and unfavorable subjective health status (p<0.001) were significant factors contributing to current arthritic pain among subjects with osteoarthritis. Both osteoarthritis and current arthritic pain adversely affected health related quality of life. Higher BMI, lack of weekly moderate intensity activity, and unfavorable subjective health status were significant factors contributing to current arthritic pain. More attention needs to be paid to psychiatric effects on osteoarthritis and joint related pain.

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

ERIC Educational Resources Information Center

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

2007-01-01

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

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

ERIC Educational Resources Information Center

Karami, Hossein

2015-01-01

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

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

Postpartum Depression in Women: A Risk Factor Analysis.

PubMed

Zaidi, Farheen; Nigam, Aruna; Anjum, Ruby; Agarwalla, Rashmi

2017-08-01

Postpartum Depression (PPD) is a known entity affecting not only the women but the whole family. It affects women more harshly and chronically due to their increased stress sensitivity, maladaptive coping strategies and multiple social roles in the community. To estimate the commonly associated risk factors of PPD among the women coming to a tertiary hospital in New Delhi, India. It was a longitudinal study conducted at the antenatal clinic for a period of one year. Total 260 women were screened at > 36 weeks of gestation, of which 149 postnatal women completed the questionnaire for PPD at six weeks of their delivery. The inform consent, demographical data and obstetrical details from each participant was taken before commencing the screening. Various risk factors and their association were determined by odds-ratio and significant association was accepted at < 5% level of error. In order to identify the most important confounding variables, logistic regression analysis was used. PPD is a common mental health problem seen among the postnatal women as it was found in 12.75% (19 out of 149) of subjects at six weeks of their delivery. Moreover, it has significant association with the young maternal age (p-value=0.040), birth of the female child (p-value=0.015), previous stressful life events (p-value= 0.003), low self-esteem and feeling of loneliness (p-value=0.007). This study provides important information regarding the risk factors associated with development of PPD in this region of India. Female sex of the new born and the younger age play an important role in the development of PPD.

Analysis of nasopharyngeal carcinoma risk factors with Bayesian networks.

PubMed

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

2012-01-01

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

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

PubMed

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

2012-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Psychosocial job factors and biological cardiovascular risk factors in Mexican workers.

PubMed

Garcia-Rojas, Isabel Judith; Choi, BongKyoo; Krause, Niklas

2015-03-01

Psychosocial job factors (PJF) have been implicated in the development of cardiovascular disease. The paucity of data from developing economies including Mexico hampers the development of worksite intervention efforts in those regions. This cross-sectional study of 2,330 Mexican workers assessed PJF (job strain [JS], social support [SS], and job insecurity [JI]) and biological cardiovascular disease risk factors [CVDRF] by questionnaire and on-site physical examinations. Alternative formulations of the JS scales were developed based on factor analysis and literature review. Associations between both traditional and alternative job factor scales with CVDRF were examined in multiple regression models, adjusting for physical workload, and socio-demographic factors. Alternative formulations of the job demand and control scales resulted in substantial changes in effect sizes or statistical significance when compared with the original scales. JS and JI showed hypothesized associations with most CVDRF, but they were inversely associated with diastolic blood pressure and some adiposity measures. SS was mainly protective against CVDRF. Among Mexican workers, alternative PJF scales predicted health outcomes better than traditional scales, and psychosocial stressors were associated with most CVDRF. © 2015 Wiley Periodicals, Inc.

Pressure and protective factors influencing nursing students' self-esteem: A content analysis study.

PubMed

Valizadeh, Leila; Zamanzadeh, Vahid; Gargari, Rahim Badri; Ghahramanian, Akram; Tabrizi, Faranak Jabbarzadeh; Keogh, Brian

2016-01-01

A review of the literature shows that the range of self-esteem in nursing students ranges from normal to low. It is hypothesized that different contextual factors could affect levels of self-esteem. The main aim of this study was to explore these factors from the viewpoint of Iranian nursing students using a qualitative approach. A qualitative content analysis study. Faculty of Nursing and Midwifery, 2014. Fourteen student nurses and two qualified nurses. This study has been applied to various depths of interpretation. Semi-structured interviews were used to collect the data. Fourteen student nurses and two qualified nurses were interviewed. Two main themes of the "pressure factors" with subthemes: low self-efficacy, sense of triviality, ineffective instructor-student interaction, low self-confidence and "protective factors" with subthemes: knowledge acquisition, mirror of valuability, professional autonomy, religious beliefs, and choosing the nursing field with interest was extracted in this study. Results showed that these themes have interaction with each other like a seesaw, as pressure factors decrease, the effect of protective factors on the self-esteem are increased. Nurse educators not only should try to improve the students' skills and knowledge, but should also try to enhance the protective factors and decrease pressure factors by enhancing the nursing students' feeling of being important, using participatory teaching methods, considering students' feedback, and attempting to improve facilities at the clinics are also recommended. Copyright © 2015. Published by Elsevier Ltd.

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

PubMed

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

Zhou, Libing

2017-04-01

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

Charmless two-body B decays: A global analysis with QCD factorization

NASA Astrophysics Data System (ADS)

Du, Dongsheng; Sun, Junfeng; Yang, Deshan; Zhu, Guohuai

2003-01-01

In this paper, we perform a global analysis of B→PP and PV decays with the QCD factorization approach. It is encouraging to observe that the predictions of QCD factorization are in good agreement with experiment. The best fit γ is around 79 °. The penguin-diagram to tree-diagram ratio |Pππ/Tππ| of π+π- decays is preferred to be larger than 0.3. We also show the confidence levels for some interesting channels: B0→π0π0, K+K-, and B+→ωπ+, ωK+. For B→πK* decays, they are expected to have smaller branching ratios with more precise measurements.

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

A projection operator method for the analysis of magnetic neutron form factors

NASA Astrophysics Data System (ADS)

Kaprzyk, S.; Van Laar, B.; Maniawski, F.

1981-03-01

A set of projection operators in matrix form has been derived on the basis of decomposition of the spin density into a series of fully symmetrized cubic harmonics. This set of projection operators allows a formulation of the Fourier analysis of magnetic form factors in a convenient way. The presented method is capable of checking the validity of various theoretical models used for spin density analysis up to now. The general formalism is worked out in explicit form for the fcc and bcc structures and deals with that part of spin density which is contained within the sphere inscribed in the Wigner-Seitz cell. This projection operator method has been tested on the magnetic form factors of nickel and iron.

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

PubMed

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

2015-01-01

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

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

PubMed

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

2016-08-17

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

Factor Analysis of Linear Type Traits and Their Relation with Longevity in Brazilian Holstein Cattle

PubMed Central

Kern, Elisandra Lurdes; Cobuci, Jaime Araújo; Costa, Cláudio Napolis; Pimentel, Concepta Margaret McManus

2014-01-01

In this study we aimed to evaluate the reduction in dimensionality of 20 linear type traits and more final score in 14,943 Holstein cows in Brazil using factor analysis, and indicate their relationship with longevity and 305 d first lactation milk production. Low partial correlations (−0.19 to 0.38), the medium to high Kaiser sampling mean (0.79) and the significance of the Bartlett sphericity test (p<0.001), indicated correlations between type traits and the suitability of these data for a factor analysis, after the elimination of seven traits. Two factors had autovalues greater than one. The first included width and height of posterior udder, udder texture, udder cleft, loin strength, bone quality and final score. The second included stature, top line, chest width, body depth, fore udder attachment, angularity and final score. The linear regression of the factors on several measures of longevity and 305 d milk production showed that selection considering only the first factor should lead to improvements in longevity and 305 milk production. PMID:25050015

Analysis of risk factors for cluster behavior of dental implant failures.

PubMed

Chrcanovic, Bruno Ramos; Kisch, Jenö; Albrektsson, Tomas; Wennerberg, Ann

2017-08-01

Some studies indicated that implant failures are commonly concentrated in few patients. To identify and analyze cluster behavior of dental implant failures among subjects of a retrospective study. This retrospective study included patients receiving at least three implants only. Patients presenting at least three implant failures were classified as presenting a cluster behavior. Univariate and multivariate logistic regression models and generalized estimating equations analysis evaluated the effect of explanatory variables on the cluster behavior. There were 1406 patients with three or more implants (8337 implants, 592 failures). Sixty-seven (4.77%) patients presented cluster behavior, with 56.8% of all implant failures. The intake of antidepressants and bruxism were identified as potential negative factors exerting a statistically significant influence on a cluster behavior at the patient-level. The negative factors at the implant-level were turned implants, short implants, poor bone quality, age of the patient, the intake of medicaments to reduce the acid gastric production, smoking, and bruxism. A cluster pattern among patients with implant failure is highly probable. Factors of interest as predictors for implant failures could be a number of systemic and local factors, although a direct causal relationship cannot be ascertained. © 2017 Wiley Periodicals, Inc.

Prognostic factors in canine appendicular osteosarcoma - a meta-analysis.

PubMed

Boerman, Ilse; Selvarajah, Gayathri T; Nielen, Mirjam; Kirpensteijn, Jolle

2012-05-15

Appendicular osteosarcoma is the most common malignant primary canine bone tumor. When treated by amputation or tumor removal alone, median survival times (MST) do not exceed 5 months, with the majority of dogs suffering from metastatic disease. This period can be extended with adequate local intervention and adjuvant chemotherapy, which has become common practice. Several prognostic factors have been reported in many different studies, e.g. age, breed, weight, sex, neuter status, location of tumor, serum alkaline phosphatase (SALP), bone alkaline phosphatase (BALP), infection, percentage of bone length affected, histological grade or histological subtype of tumor. Most of these factors are, however, only reported as confounding factors in larger studies. Insight in truly significant prognostic factors at time of diagnosis may contribute to tailoring adjuvant therapy for individual dogs suffering from osteosarcoma. The objective of this study was to systematically review the prognostic factors that are described for canine appendicular osteosarcoma and validate their scientific importance. A literature review was performed on selected studies and eligible data were extracted. Meta-analyses were done for two of the three selected possible prognostic factors (SALP and location), looking at both survival time (ST) and disease free interval (DFI). The third factor (age) was studied in a qualitative manner. Both elevated SALP level and the (proximal) humerus as location of the primary tumor are significant negative prognostic factors for both ST and DFI in dogs with appendicular osteosarcoma. Increasing age was associated with shorter ST and DFI, however, was not statistically significant because information of this factor was available in only a limited number of papers. Elevated SALP and proximal humeral location are significant negative prognosticators for canine osteosarcoma.

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

PubMed

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

2014-10-16

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

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

PubMed Central

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

2014-01-01

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

Factor Analysis of the Aftereffects of Drinking in Alcoholics.

ERIC Educational Resources Information Center

Watson, Charles G.; And Others

1985-01-01

Performed factor analyses of 100 alcoholics' reports of the effects that they experience after alcohol consumption. Five factors emerged: Hangover, Euphoria, Flushing, Seizures, and Sleepiness. These factors may be helpful in assessing theories on the etiology of alcoholism and in studies of ethanol's effects on subsets of alcohol abusers. (BH)

Risk factors for gastric cancer in Latin-America: a meta-analysis

PubMed Central

Bonequi, Patricia; Meneses-González, Fernando; Correa, Pelayo; Rabkin, Charles S.; Camargo, M. Constanza

2013-01-01

Background Latin America has among the highest gastric cancer incidence rates in the world, for reasons that are still unknown. In order to identify region-specific risk factors for gastric cancer, we conducted a meta-analysis summarizing published literature. Methods Searches of PubMed and regional databases for relevant studies published up to December 2011 yielded a total of 29 independent case-control studies. We calculated summary odds ratios (OR) for risk factors reported in at least five studies, including socioeconomic status (education), lifestyle habits (smoking and alcohol use), dietary factors (consumption of fruits, total vegetables, green vegetables, chili pepper, total meat, processed meat, red meat, fish and salt) and host genetic variants (IL1B-511T, IL1B-31C, IL1RN*2, TNFA-308A, TP53 codon 72 Arg and GSTM1 null). Study-specific ORs were extracted and summarized using random-effects models. Results Chili pepper was the only region-specific factor reported in at least five studies. Consistent with multifactorial pathogenesis, smoking, alcohol use, high consumption of red meat or processed meat, excessive salt intake and carriage of IL1RN*2 were each associated with a moderate increase in gastric cancer risk. Conversely, higher levels of education, fruit consumption, and total vegetable consumption were each associated with a moderately decreased risk. The other exposures were not significantly associated. No prospective study data were identified. Conclusion Risk factor associations for gastric cancer in Latin America are based on case-control comparisons that have uncertain reliability, particularly with regard to diet; the specific factors identified and their magnitudes of association are largely similar to those globally recognized. Future studies should emphasize prospective data collection and focus on region-specific exposures that may explain high gastric cancer risk. PMID:23224270

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

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.

2016-01-01

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

Sufficient Forecasting Using Factor Models

PubMed Central

Fan, Jianqing; Xue, Lingzhou; Yao, Jiawei

2017-01-01

We consider forecasting a single time series when there is a large number of predictors and a possible nonlinear effect. The dimensionality was first reduced via a high-dimensional (approximate) factor model implemented by the principal component analysis. Using the extracted factors, we develop a novel forecasting method called the sufficient forecasting, which provides a set of sufficient predictive indices, inferred from high-dimensional predictors, to deliver additional predictive power. The projected principal component analysis will be employed to enhance the accuracy of inferred factors when a semi-parametric (approximate) factor model is assumed. Our method is also applicable to cross-sectional sufficient regression using extracted factors. The connection between the sufficient forecasting and the deep learning architecture is explicitly stated. The sufficient forecasting correctly estimates projection indices of the underlying factors even in the presence of a nonparametric forecasting function. The proposed method extends the sufficient dimension reduction to high-dimensional regimes by condensing the cross-sectional information through factor models. We derive asymptotic properties for the estimate of the central subspace spanned by these projection directions as well as the estimates of the sufficient predictive indices. We further show that the natural method of running multiple regression of target on estimated factors yields a linear estimate that actually falls into this central subspace. Our method and theory allow the number of predictors to be larger than the number of observations. We finally demonstrate that the sufficient forecasting improves upon the linear forecasting in both simulation studies and an empirical study of forecasting macroeconomic variables. PMID:29731537

40 CFR 1042.245 - Deterioration factors.

Code of Federal Regulations, 2014 CFR

2014-07-01

... to meet the Tier 1 and Tier 2 emission standards would qualify as established technology. We must... deterioration factors for Category 1 and Category 2 engines, either with an engineering analysis, with pre... deterioration factors for an engine family with established technology based on engineering analysis instead of...

40 CFR 1042.245 - Deterioration factors.

Code of Federal Regulations, 2012 CFR

2012-07-01

... to meet the Tier 1 and Tier 2 emission standards would qualify as established technology. We must... deterioration factors for Category 1 and Category 2 engines, either with an engineering analysis, with pre... deterioration factors for an engine family with established technology based on engineering analysis instead of...

40 CFR 1042.245 - Deterioration factors.

Code of Federal Regulations, 2010 CFR

2010-07-01

... to meet the Tier 1 and Tier 2 emission standards would qualify as established technology. We must... deterioration factors for Category 1 and Category 2 engines, either with an engineering analysis, with pre... deterioration factors for an engine family with established technology based on engineering analysis instead of...

40 CFR 1042.245 - Deterioration factors.

Code of Federal Regulations, 2011 CFR

2011-07-01

... to meet the Tier 1 and Tier 2 emission standards would qualify as established technology. We must... deterioration factors for Category 1 and Category 2 engines, either with an engineering analysis, with pre... deterioration factors for an engine family with established technology based on engineering analysis instead of...

40 CFR 1042.245 - Deterioration factors.

Code of Federal Regulations, 2013 CFR

2013-07-01

... to meet the Tier 1 and Tier 2 emission standards would qualify as established technology. We must... deterioration factors for Category 1 and Category 2 engines, either with an engineering analysis, with pre... deterioration factors for an engine family with established technology based on engineering analysis instead of...

Is the Factor Observed in Investigations on the Item-Position Effect Actually the Difficulty Factor?

PubMed

Schweizer, Karl; Troche, Stefan

2018-02-01

In confirmatory factor analysis quite similar models of measurement serve the detection of the difficulty factor and the factor due to the item-position effect. The item-position effect refers to the increasing dependency among the responses to successively presented items of a test whereas the difficulty factor is ascribed to the wide range of item difficulties. The similarity of the models of measurement hampers the dissociation of these factors. Since the item-position effect should theoretically be independent of the item difficulties, the statistical ex post manipulation of the difficulties should enable the discrimination of the two types of factors. This method was investigated in two studies. In the first study, Advanced Progressive Matrices (APM) data of 300 participants were investigated. As expected, the factor thought to be due to the item-position effect was observed. In the second study, using data simulated to show the major characteristics of the APM data, the wide range of items with various difficulties was set to zero to reduce the likelihood of detecting the difficulty factor. Despite this reduction, however, the factor now identified as item-position factor, was observed in virtually all simulated datasets.

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

PubMed Central

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

2015-01-01

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

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.

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

PubMed

Amiri, Marjan; Michel, Martin C

2018-06-21

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

Factor analysis in predominantly severe COPD: identification of disease heterogeneity by easily measurable characteristics.

PubMed

Postma, Dirkje S; Anzueto, Antonio R; Jenkins, Christine; Make, Barry J; Similowski, Thomas; Östlund, Ollie; Eriksson, Göran S; Calverley, Peter M

2013-12-01

The clinical and demographic variables defining the heterogeneity of chronic obstructive pulmonary disease (COPD) are unclear. A post-hoc analysis of five randomised studies in patients with a history of previous exacerbations examined the clinical and demographic characteristics describing moderate-to-very-severe COPD. Factor analysis was performed on all continuous baseline demographic and clinical data, without variable selection. Analyses were based on the full cohort and on stratifications by pack-years smoked, smoking status, gender, and comorbidities; patient exacerbation history was analysed in two of the five studies. 6162 COPD patients were evaluated (70% male; 40% current smokers; mean pre-bronchodilator forced expiratory volume in 1 s [FEV1] 35.2% predicted). Baseline clinical and demographic variables loaded differentially on six factors with minimal overlap, explaining 60.4% of the heterogeneity: 1) symptoms (cough, dyspnoea, sleep disturbance), health status, reliever use; 2) pre-bronchodilator FEV1, FEV1/forced vital capacity, morning peak expiratory flow (PEF), body mass index (BMI); 3) blood pressure; 4) age, months since first COPD symptoms; 5) PEF variability; 6) pulse, FEV1 reversibility. Most factors loaded similarly in stratified and exacerbation analyses. BMI loaded with reversibility in females, and with age and months since first COPD symptoms in ex-smokers. Exacerbations loaded to factor 6. Readily available data can explain ≈ 60% of COPD heterogeneity in a large dataset of predominantly severe COPD patients. Factors were robust over determinants of disease outcome; gender, smoking status, pack-years smoked, and comorbidities. The main factors were largely unchanged by adding exacerbations. Only BMI loaded to other factors. Copyright © 2013. Published by Elsevier Ltd.

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.

Recurrent-neural-network-based Boolean factor analysis and its application to word clustering.

PubMed

Frolov, Alexander A; Husek, Dusan; Polyakov, Pavel Yu

2009-07-01

The objective of this paper is to introduce a neural-network-based algorithm for word clustering as an extension of the neural-network-based Boolean factor analysis algorithm (Frolov , 2007). It is shown that this extended algorithm supports even the more complex model of signals that are supposed to be related to textual documents. It is hypothesized that every topic in textual data is characterized by a set of words which coherently appear in documents dedicated to a given topic. The appearance of each word in a document is coded by the activity of a particular neuron. In accordance with the Hebbian learning rule implemented in the network, sets of coherently appearing words (treated as factors) create tightly connected groups of neurons, hence, revealing them as attractors of the network dynamics. The found factors are eliminated from the network memory by the Hebbian unlearning rule facilitating the search of other factors. Topics related to the found sets of words can be identified based on the words' semantics. To make the method complete, a special technique based on a Bayesian procedure has been developed for the following purposes: first, to provide a complete description of factors in terms of component probability, and second, to enhance the accuracy of classification of signals to determine whether it contains the factor. Since it is assumed that every word may possibly contribute to several topics, the proposed method might be related to the method of fuzzy clustering. In this paper, we show that the results of Boolean factor analysis and fuzzy clustering are not contradictory, but complementary. To demonstrate the capabilities of this attempt, the method is applied to two types of textual data on neural networks in two different languages. The obtained topics and corresponding words are at a good level of agreement despite the fact that identical topics in Russian and English conferences contain different sets of keywords.

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.

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

PubMed

Su, Bin-Guang; Tsai, Kai-Li; Yeh, Shu-Hsing; Ho, Yi-Yi; Liu, Shin-Yi; Rivers, Patrick A

2010-05-01

According to the 2004 US Renal Data System's annual report, the incidence rate of chronic renal failure in Taiwan increased from 120 to 352 per million populations between 1990 and 2003. This incidence rate is the highest in the world. The prevalence rate, which ranks number two in the world (Japan ranks number one), also increased from 384 to 1630 per million populations. Based on 2005 Taiwan national statistics, there were 52,958 end-stage renal disease (ESRD) patients receiving routine dialysis treatment. This number, which comprised less than 0.2% of the total population and consumed $2.6 billion New Taiwan dollars, was more than 6.12% of the total annual spending of national health insurance during 2005. Dialysis expenditures for patients with ESRD rank the highest among all major injuries (traumas) and diseases. This article identifies and discusses the risk factors associated with consumption of medical resources during dialysis. Instead of using reimbursement data to estimate cost, as seen in previous studies, this study uses cost data within organizations and focuses on evaluating and predicting the resource consumption pattern for dialysis patients with different risk factors. Multiple regression analysis was used to identify 23 risk factors for routine dialysis patients. Of these risk factors, six were associated with the increase of dialysis cost: age (i.e. 75 years old and older), liver function disorder, hypertension, bile-duct disorder, cancer and high blood lipids. Patients with liver function disorder incurred much higher costs for injection medication and supplies. Hypertensive patients incurred higher costs for injection medication, supplies and oral medication. Patients with bile-duct disorder incurred a significant difference in check-up costs (i.e. costs were higher for those aged 75 years and older than those who were younger than 30 years of age). Cancer patients also incurred significant differences in cost of medical supplies. Patients

Factors affecting the retention of nurses. A survival analysis.

PubMed

Alonazi, Noufa A; Omar, Maye A

2013-03-01

To identify and explore factors that mostly influence nurses' turnover and retention, and to estimate the length of employment for nurses in the hospital. This is a retrospective cohort study examining the standard Exit Questionnaires completed by all the female pediatric nurses who joined and left the hospital during the period between January 2006 and October 2010. The Developed Questionnaires where completed by nurses who were still employees in October 2010. The nurses who left the job will be considered as events and the nurses who are still working will be considered as censored. The study took place at the Pediatric Department, Prince Sultan Military Medical City (PSMMC), Riyadh, Saudi Arabia. A total of 254 nurses were included in the study. Most of the nurses left their jobs due to family reasons (39.7%) followed by other reasons (37.3%). Seventy five percent of all the pediatric nurses remained in their jobs, on average, for 2.2 years. Both simple and multivariate analysis indicated a strong positive correlation between length of employment (turnover) and the demographic and organization factors. This study has identified several factors that played a key role in staff retention, which can help in predicting nursing turnover at PSMMC. The findings of this study could help PSMMC and its Nursing Administration, in particular, to understand the seriousness of the high turnover rates, to develop and implement strategies to reduce this problem, and improve the retention of nursing staff.

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.

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

PubMed Central

2010-01-01

Background Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. Results Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. Conclusions Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data. PMID:21062443

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

PubMed

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

2010-11-09

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

Assessing Stress in Cancer Patients: A Second-Order Factor Analysis Model for the Perceived Stress Scale

ERIC Educational Resources Information Center

Golden-Kreutz, Deanna M.; Browne, Michael W.; Frierson, Georita M.; Andersen, Barbara L.

2004-01-01

Using the Perceived Stress Scale (PSS), perceptions of global stress were assessed in 111women following breast cancer surgery and at 12 and 24 months later. This is the first study to factor analyze the PSS. The PSS data were factor analyzed each time using exploratory factor analysis with oblique direct quartimin rotation. Goodness-of-fit…

Confirmatory Factor Analysis of U.S. Merit Systems Protection Board's Survey of Sexual Harassment: The Fit of a Three-Factor Model.

ERIC Educational Resources Information Center

Stockdale, Margaret S.; Hope, Kathryn G.

1997-01-01

Factor analysis of data from 1,070 federal employees, 575 undergraduates and 575 graduate students, faculty, and staff uncovered some weaknesses in the Merit Systems Protection Board's sexual harassment survey instrument. This type of survey does not adequately measure sexual coercion or quid pro quo forms of harassment. (SK)

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

ERIC Educational Resources Information Center

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

2010-01-01

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

Systems analysis of multiple regulator perturbations allows discovery of virulence factors in Salmonella

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

Yoon, Hyunjin; Ansong, Charles; McDermott, Jason E.

Background: Systemic bacterial infections are highly regulated and complex processes that are orchestrated by numerous virulence factors. Genes that are coordinately controlled by the set of regulators required for systemic infection are potentially required for pathogenicity. Results: In this study we present a systems biology approach in which sample-matched multi-omic measurements of fourteen virulence-essential regulator mutants were coupled with computational network analysis to efficiently identify Salmonella virulence factors. Immunoblot experiments verified network-predicted virulence factors and a subset was determined to be secreted into the host cytoplasm, suggesting that they are virulence factors directly interacting with host cellular components. Two ofmore » these, SrfN and PagK2, were required for full mouse virulence and were shown to be translocated independent of either of the type III secretion systems in Salmonella or the type III injectisome-related flagellar mechanism. Conclusions: Integrating multi-omic datasets from Salmonella mutants lacking virulence regulators not only identified novel virulence factors but also defined a new class of translocated effectors involved in pathogenesis. The success of this strategy at discovery of known and novel virulence factors suggests that the approach may have applicability for other bacterial pathogens.« less

Confirmatory factor analysis reveals a latent cognitive structure common to bipolar disorder, schizophrenia, and normal controls.

PubMed

Schretlen, David J; Peña, Javier; Aretouli, Eleni; Orue, Izaskun; Cascella, Nicola G; Pearlson, Godfrey D; Ojeda, Natalia

2013-06-01

We sought to determine whether a single hypothesized latent factor structure would characterize cognitive functioning in three distinct groups. We assessed 576 adults (340 community controls, 126 adults with bipolar disorder, and 110 adults with schizophrenia) using 15 measures derived from nine cognitive tests. Confirmatory factor analysis (CFA) was conducted to examine the fit of a hypothesized six-factor model. The hypothesized factors included attention, psychomotor speed, verbal memory, visual memory, ideational fluency, and executive functioning. The six-factor model provided an excellent fit for all three groups [for community controls, root mean square error of approximation (RMSEA) <0.048 and comparative fit index (CFI) = 0.99; for adults with bipolar disorder, RMSEA = 0.071 and CFI = 0.99; and for adults with schizophrenia, RMSEA = 0.06 and CFI = 0.98]. Alternate models that combined fluency with processing speed or verbal and visual memory reduced the goodness of fit. Multi-group CFA results supported factor invariance across the three groups. Confirmatory factor analysis supported a single six-factor structure of cognitive functioning among patients with schizophrenia or bipolar disorder and community controls. While the three groups clearly differ in level of performance, they share a common underlying architecture of information processing abilities. These cognitive factors could provide useful targets for clinical trials of treatments that aim to enhance information processing in persons with neurological and neuropsychiatric disorders. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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).

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

PubMed Central

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

2018-01-01

Objectives To estimate the prevalence of intimate partner violence (IPV) among a sample of rural Chinese women and to explore associated factors. Design Cross-sectional study. Setting Rural areas of Guangyuan City, Sichuan, China. Participants We recruited 1501 women, aged 16 years and older, who had been living locally for at least 2 years and reported being married or in a relationship during the past 12 months. They were among a sample of 1898 potential participants from our larger parent study on the prevalence of depressive-distress symptoms. Methods Participants completed demographic and social economic measures, the Short Form of the Revised Conflict Tactics Scale and the Duke Social Support Index. We applied χ2 test, analysis of variance and confirmatory factor analysis for analysis. Results The overall prevalence of IPV in the past 12 months was 29.05%; the prevalence of physical, psychological and sexual violence was 7.66%, 26.58% and 3.20%, respectively. The overall prevalence was highest among women aged 16–29 years, and was more common among those without a high school diploma and who saw their family’s financial status as very poor or stagnant. Women who were not victims of IPV had higher levels of social support. Confirmatory factor analysis showed that the total effects of social support on physical, psychological and sexual violence were −0.12, –0.35 and −0.12, respectively. The indirect effects of objective economic status on physical, psychological and sexual violence were −0.047, –0.014 and −0.047, respectively, but the total effect was not significant. The indirect effect of education on psychological violence was −0.056. Conclusion IPV is common in rural Guangyuan. Our data are comparable with the findings from north-west of China. Social support is an important protective factor. Future work is needed to develop, test and later disseminate potential IPV interventions, with a focus on building actual and perceived supportive

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

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

Neff, Michael M.

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

Examining the Dimensionality of ADHD Symptomatology in Young Adults Using Factor Analysis and Outcome Prediction

ERIC Educational Resources Information Center

McKee, Tara E.

2012-01-01

Objective: Current diagnostic criteria specify that ADHD involves difficulties with inattention and/or hyperactivity/impulsivity. Researchers using factor analysis have consistently found support for an inattention factor in both children and adults. Findings have been mixed regarding whether hyperactivity and impulsivity reflect one or two…

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

ERIC Educational Resources Information Center

Macmann, Gregg M.; Barnett, David W.

1994-01-01

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

Question Number Two: How Many Factors?

ERIC Educational Resources Information Center

Goodwyn, Fara

2012-01-01

Exploratory factor analysis involves five key decisions. The second decision, how many factors to retain, is the focus of the current paper. Extracting too many or too few factors often leads to devastating effects on study results. The advantages and disadvantages of the most effective and/or most utilized strategies to determine the number of…

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

ERIC Educational Resources Information Center

Osborne, Jason W.; Fitzpatrick, David C.

2012-01-01

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

An Exploratory Analysis of Factors Affecting Participation in Air Force Knowledge Now Communities of Practice

DTIC Science & Technology

2004-03-01

reliability coefficients are presented in chapter four in the factor analysis section. Along with Crobach’s Alpha coefficients, the Kaiser - Meyer - Olkin ...the pattern of correlation coefficients > 0.300 in the correlation matrix • Kaiser - Meyer - Olkin Measure of Sampling Adequacy (MSA) > 0.700 • Bartlett’s...exploratory factor analysis. The Kaiser - Meyer - Olkin measure of sampling adequacy yielded a value of .790, and Bartlett’s test of sphericity yielded a

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.

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

Multi-Factor Analysis for Selecting Lunar Exploration Soft Landing Area and the best Cruise Route

NASA Astrophysics Data System (ADS)

Mou, N.; Li, J.; Meng, Z.; Zhang, L.; Liu, W.

2018-04-01

Selecting the right soft landing area and planning a reasonable cruise route are the basic tasks of lunar exploration. In this paper, the Von Karman crater in the Antarctic Aitken basin on the back of the moon is used as the study area, and multi-factor analysis is used to evaluate the landing area and cruise route of lunar exploration. The evaluation system mainly includes the factors such as the density of craters, the impact area of craters, the formation of the whole area and the formation of some areas, such as the vertical structure, rock properties and the content of (FeO + TiO2), which can reflect the significance of scientific exploration factor. And the evaluation of scientific exploration is carried out on the basis of safety and feasibility. On the basis of multi-factor superposition analysis, three landing zones A, B and C are selected, and the appropriate cruising route is analyzed through scientific research factors. This study provides a scientific basis for the lunar probe landing and cruise route planning, and it provides technical support for the subsequent lunar exploration.

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

NASA Astrophysics Data System (ADS)

Drake, Joshua P.

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

Source Apportionment and Influencing Factor Analysis of Residential Indoor PM2.5 in Beijing

PubMed Central

Yang, Yibing; Liu, Liu; Xu, Chunyu; Li, Na; Liu, Zhe; Wang, Qin; Xu, Dongqun

2018-01-01

In order to identify the sources of indoor PM2.5 and to check which factors influence the concentration of indoor PM2.5 and chemical elements, indoor concentrations of PM2.5 and its related elements in residential houses in Beijing were explored. Indoor and outdoor PM2.5 samples that were monitored continuously for one week were collected. Indoor and outdoor concentrations of PM2.5 and 15 elements (Al, As, Ca, Cd, Cu, Fe, K, Mg, Mn, Na, Pb, Se, Tl, V, Zn) were calculated and compared. The median indoor concentration of PM2.5 was 57.64 μg/m3. For elements in indoor PM2.5, Cd and As may be sensitive to indoor smoking, Zn, Ca and Al may be related to indoor sources other than smoking, Pb, V and Se may mainly come from outdoor. Five factors were extracted for indoor PM2.5 by factor analysis, explained 76.8% of total variance, outdoor sources contributed more than indoor sources. Multiple linear regression analysis for indoor PM2.5, Cd and Pb was performed. Indoor PM2.5 was influenced by factors including outdoor PM2.5, smoking during sampling, outdoor temperature and time of air conditioner use. Indoor Cd was affected by factors including smoking during sampling, outdoor Cd and building age. Indoor Pb concentration was associated with factors including outdoor Pb and time of window open per day, building age and RH. In conclusion, indoor PM2.5 mainly comes from outdoor sources, and the contributions of indoor sources also cannot be ignored. Factors associated indoor and outdoor air exchange can influence the concentrations of indoor PM2.5 and its constituents. PMID:29621164

Source Apportionment and Influencing Factor Analysis of Residential Indoor PM2.5 in Beijing.

PubMed

Yang, Yibing; Liu, Liu; Xu, Chunyu; Li, Na; Liu, Zhe; Wang, Qin; Xu, Dongqun

2018-04-05

In order to identify the sources of indoor PM 2.5 and to check which factors influence the concentration of indoor PM 2.5 and chemical elements, indoor concentrations of PM 2.5 and its related elements in residential houses in Beijing were explored. Indoor and outdoor PM 2.5 samples that were monitored continuously for one week were collected. Indoor and outdoor concentrations of PM 2.5 and 15 elements (Al, As, Ca, Cd, Cu, Fe, K, Mg, Mn, Na, Pb, Se, Tl, V, Zn) were calculated and compared. The median indoor concentration of PM 2.5 was 57.64 μg/m³. For elements in indoor PM 2.5 , Cd and As may be sensitive to indoor smoking, Zn, Ca and Al may be related to indoor sources other than smoking, Pb, V and Se may mainly come from outdoor. Five factors were extracted for indoor PM 2.5 by factor analysis, explained 76.8% of total variance, outdoor sources contributed more than indoor sources. Multiple linear regression analysis for indoor PM 2.5 , Cd and Pb was performed. Indoor PM 2.5 was influenced by factors including outdoor PM 2.5 , smoking during sampling, outdoor temperature and time of air conditioner use. Indoor Cd was affected by factors including smoking during sampling, outdoor Cd and building age. Indoor Pb concentration was associated with factors including outdoor Pb and time of window open per day, building age and RH. In conclusion, indoor PM 2.5 mainly comes from outdoor sources, and the contributions of indoor sources also cannot be ignored. Factors associated indoor and outdoor air exchange can influence the concentrations of indoor PM 2.5 and its constituents.

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