Significance Testing in Confirmatory Factor Analytic Models.

ERIC Educational Resources Information Center

Khattab, Ali-Maher; Hocevar, Dennis

Traditionally, confirmatory factor analytic models are tested against a null model of total independence. Using randomly generated factors in a matrix of 46 aptitude tests, this approach is shown to be unlikely to reject even random factors. An alternative null model, based on a single general factor, is suggested. In addition, an index of model…

Brief report: Bifactor modeling of general vs. specific factors of religiousness differentially predicting substance use risk in adolescence.

PubMed

Kim-Spoon, Jungmeen; Longo, Gregory S; Holmes, Christopher J

2015-08-01

Religiousness is important to adolescents in the U.S., and the significant link between high religiousness and low substance use is well known. There is a debate between multidimensional and unidimensional perspectives of religiousness (Gorsuch, 1984); yet, no empirical study has tested this hierarchical model of religiousness related to adolescent health outcomes. The current study presents the first attempt to test a bifactor model of religiousness related to substance use among adolescents (N = 220, 45% female). Our bifactor model using structural equation modeling suggested the multidimensional nature of religiousness as well as the presence of a superordinate general religiousness factor directly explaining the covariation among the specific factors including organizational and personal religiousness and religious social support. The general religiousness factor was inversely related to substance use. After accounting for the contribution of the general religiousness factor, high organizational religiousness related to low substance use, whereas personal religiousness and religious support were positively related to substance use. The findings present the first evidence that supports hierarchical structures of adolescent religiousness that contribute differentially to adolescent substance use. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

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

PubMed

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

2011-09-01

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

Escaping the snare of chronological growth and launching a free curve alternative: general deviance as latent growth model.

PubMed

Wood, Phillip Karl; Jackson, Kristina M

2013-08-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating "protective" or "launch" factors or as "developmental snares." These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of "general deviance" over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the "general deviance" model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of "general deviance" can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the "snares" alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control.

Escaping the snare of chronological growth and launching a free curve alternative: General deviance as latent growth model

PubMed Central

WOOD, PHILLIP KARL; JACKSON, KRISTINA M.

2014-01-01

Researchers studying longitudinal relationships among multiple problem behaviors sometimes characterize autoregressive relationships across constructs as indicating “protective” or “launch” factors or as “developmental snares.” These terms are used to indicate that initial or intermediary states of one problem behavior subsequently inhibit or promote some other problem behavior. Such models are contrasted with models of “general deviance” over time in which all problem behaviors are viewed as indicators of a common linear trajectory. When fit of the “general deviance” model is poor and fit of one or more autoregressive models is good, this is taken as support for the inhibitory or enhancing effect of one construct on another. In this paper, we argue that researchers consider competing models of growth before comparing deviance and time-bound models. Specifically, we propose use of the free curve slope intercept (FCSI) growth model (Meredith & Tisak, 1990) as a general model to typify change in a construct over time. The FCSI model includes, as nested special cases, several statistical models often used for prospective data, such as linear slope intercept models, repeated measures multivariate analysis of variance, various one-factor models, and hierarchical linear models. When considering models involving multiple constructs, we argue the construct of “general deviance” can be expressed as a single-trait multimethod model, permitting a characterization of the deviance construct over time without requiring restrictive assumptions about the form of growth over time. As an example, prospective assessments of problem behaviors from the Dunedin Multidisciplinary Health and Development Study (Silva & Stanton, 1996) are considered and contrasted with earlier analyses of Hussong, Curran, Moffitt, and Caspi (2008), which supported launch and snare hypotheses. For antisocial behavior, the FCSI model fit better than other models, including the linear chronometric growth curve model used by Hussong et al. For models including multiple constructs, a general deviance model involving a single trait and multimethod factors (or a corresponding hierarchical factor model) fit the data better than either the “snares” alternatives or the general deviance model previously considered by Hussong et al. Taken together, the analyses support the view that linkages and turning points cannot be contrasted with general deviance models absent additional experimental intervention or control. PMID:23880389

Examining the ethnoracial invariance of a bifactor model of anxiety sensitivity and the incremental validity of the physical domain-specific factor in a primary-care patient sample.

PubMed

Fergus, Thomas A; Kelley, Lance P; Griggs, Jackson O

2017-10-01

There is growing support for a bifactor conceptualization of the Anxiety Sensitivity Index-3 (ASI-3; Taylor et al., 2007), consisting of a General factor and 3 domain-specific factors (i.e., Physical, Cognitive, Social). Earlier studies supporting a bifactor model of the ASI-3 used samples that consisted of predominantly White respondents. In addition, extant research has yet to support the incremental validity of the Physical domain-specific factor while controlling for the General factor. The present study is an examination of a bifactor model of the ASI-3 and the measurement invariance of that model among an ethnoracially diverse sample of primary-care patients (N = 533). Results from multiple-group confirmatory factor analysis supported the configural and metric/scalar invariance of the bifactor model of the ASI-3 across self-identifying Black, Latino, and White respondents. The Physical domain-specific factor accounted for unique variance in an index of health anxiety beyond the General factor. These results provide support for the generalizability of a bifactor model of the ASI-3 across 3 ethnoracial groups, as well as indication of the incremental explanatory power of the Physical domain-specific factor. Study implications are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Examining the Factor Structure and Discriminant Validity of the 12-Item General Health Questionnaire (GHQ-12) Among Spanish Postpartum Women

ERIC Educational Resources Information Center

Aguado, Jaume; Campbell, Alistair; Ascaso, Carlos; Navarro, Purificacion; Garcia-Esteve, Lluisa; Luciano, Juan V.

2012-01-01

In this study, the authors tested alternative factor models of the 12-item General Health Questionnaire (GHQ-12) in a sample of Spanish postpartum women, using confirmatory factor analysis. The authors report the results of modeling three different methods for scoring the GHQ-12 using estimation methods recommended for categorical and binary data.…

External validity of a hierarchical dimensional model of child and adolescent psychopathology: Tests using confirmatory factor analyses and multivariate behavior genetic analyses.

PubMed

Waldman, Irwin D; Poore, Holly E; van Hulle, Carol; Rathouz, Paul J; Lahey, Benjamin B

2016-11-01

Several recent studies of the hierarchical phenotypic structure of psychopathology have identified a General psychopathology factor in addition to the more expected specific Externalizing and Internalizing dimensions in both youth and adult samples and some have found relevant unique external correlates of this General factor. We used data from 1,568 twin pairs (599 MZ & 969 DZ) age 9 to 17 to test hypotheses for the underlying structure of youth psychopathology and the external validity of the higher-order factors. Psychopathology symptoms were assessed via structured interviews of caretakers and youth. We conducted phenotypic analyses of competing structural models using Confirmatory Factor Analysis and used Structural Equation Modeling and multivariate behavior genetic analyses to understand the etiology of the higher-order factors and their external validity. We found that both a General factor and specific Externalizing and Internalizing dimensions are necessary for characterizing youth psychopathology at both the phenotypic and etiologic levels, and that the 3 higher-order factors differed substantially in the magnitudes of their underlying genetic and environmental influences. Phenotypically, the specific Externalizing and Internalizing dimensions were slightly negatively correlated when a General factor was included, which reflected a significant inverse correlation between the nonshared environmental (but not genetic) influences on Internalizing and Externalizing. We estimated heritability of the general factor of psychopathology for the first time. Its moderate heritability suggests that it is not merely an artifact of measurement error but a valid construct. The General, Externalizing, and Internalizing factors differed in their relations with 3 external validity criteria: mother's smoking during pregnancy, parent's harsh discipline, and the youth's association with delinquent peers. Multivariate behavior genetic analyses supported the external validity of the 3 higher-order factors by suggesting that the General, Externalizing, and Internalizing factors were correlated with peer delinquency and parent's harsh discipline for different etiologic reasons. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Confirmatory factor analytic investigation of variance composition, gender invariance, and validity of the Male Role Norms Inventory-Adolescent-revised (MRNI-A-r).

PubMed

Levant, Ronald F; McDermott, Ryon C; Hewitt, Amber A; Alto, Kathleen M; Harris, Kyle T

2016-10-01

Confirmatory factor analysis of responses to the Male Role Norms Inventory-Adolescent-revised (MRNI-A-r) from 384 middle school students (163 boys, 221 girls) indicated that the best fit to the data was a bifactor model incorporating the hypothesized 3-factor structure while explicitly modeling an additional, general factor. Specifically, each item-level indicator loaded simultaneously on 2 factors: a general traditional masculinity ideology factor and a specific factor corresponding to 1 of the 3 hypothesized masculine norms for adolescents: Emotionally Detached Dominance, Toughness, and Avoidance of Femininity. Invariance testing across gender supported metric invariance for the general factor only. Although item loadings on the general factor were similar across boys and girls, the specific factor loadings varied substantially, with many becoming nonsignificant in the presence of the general factor for girls. A structural regression analysis predicting latent variables of the Meanings of Adolescent Masculinity Scale (MAMS), the Rosenberg Self-esteem Scale, and the Discipline, School Difficulties, and Positive Behavior Scale (DSDPBS) indicated that the general factor was a strong predictor of MAMS for both genders and DSDPBS for girls. Findings indicate that the MRNI-A-r general factor is a valid and reliable indicator of overall internalization of traditional masculinity ideology in adolescents; however, the specific factors may have different meanings for boys as compared with girls and lack validity in the presence of the general factor. These findings are consistent with a developmental perspective of gender ideology that views adolescence as a time when a differentiated cognitive schema of masculine norms is beginning to develop. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Bifactor structure of the Wechsler Preschool and Primary Scale of Intelligence--Fourth Edition.

PubMed

Watkins, Marley W; Beaujean, A Alexander

2014-03-01

The Wechsler Preschool and Primary Scale of Intelligence--Fourth Edition (WPPSI-IV; Wechsler, 2012) represents a substantial departure from its predecessor, including omission of 4 subtests, addition of 5 new subtests, and modification of the contents of the 5 retained subtests. Wechsler (2012) explicitly assumed a higher-order structure with general intelligence (g) as the second-order factor that explained all the covariation of several first-order factors but failed to consider a bifactor model. The WPPSI-IV normative sample contains 1,700 children aged 2 years and 6 months through 7 years and 7 months, bifurcated into 2 age groups: 2:6-3:11 year olds (n = 600) and 4:0-7:7 year olds (n = 1,100). This study applied confirmatory factor analysis to the WPPSI-IV normative sample data to test the fit of a bifactor model and to determine the reliability of the resulting factors. The bifactor model fit the WPPSI-IV normative sample data as well as or better than the higher-order models favored by Wechsler (2012). In the bifactor model, the general factor accounted for more variance in every subtest than did its corresponding domain-specific factor and the general factor accounted for more total and common variance than all domain-specific factors combined. Further, the domain-specific factors exhibited poor reliability independent of g (i.e., ωh coefficients of .05 to .33). These results suggest that only the general intelligence dimension was sufficiently robust and precise for clinical use. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Description of the General Equilibrium Model of Ecosystem Services (GEMES)

Treesearch

Travis Warziniack; David Finnoff; Jenny Apriesnig

2017-01-01

This paper serves as documentation for the General Equilibrium Model of Ecosystem Services (GEMES). GEMES is a regional computable general equilibrium model that is composed of values derived from natural capital and ecosystem services. It models households, producing sectors, and governments, linked to one another through commodity and factor markets. GEMES was...

Measuring and Examining General Self-Efficacy among Community College Students: A Structural Equation Modeling Approach

ERIC Educational Resources Information Center

Chen, Yu; Starobin, Soko S.

2018-01-01

This study examined a psychosocial mechanism of how general self-efficacy interacts with other key factors and influences degree aspiration for students enrolled in an urban diverse community college. Using general self-efficacy scales, the authors hypothesized the General Self-efficacy model for Community College students (the GSE-CC model). A…

Comparing Factor, Class, and Mixture Models of Cannabis Initiation and DSM Cannabis Use Disorder Criteria, Including Craving, in the Brisbane Longitudinal Twin Study

PubMed Central

Kubarych, Thomas S.; Kendler, Kenneth S.; Aggen, Steven H.; Estabrook, Ryne; Edwards, Alexis C.; Clark, Shaunna L.; Martin, Nicholas G.; Hickie, Ian B.; Neale, Michael C.; Gillespie, Nathan A.

2014-01-01

Accumulating evidence suggests that the Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria for cannabis abuse and dependence are best represented by a single underlying factor. However, it remains possible that models with additional factors, or latent class models or hybrid models, may better explain the data. Using structured interviews, 626 adult male and female twins provided complete data on symptoms of cannabis abuse and dependence, plus a craving criterion. We compared latent factor analysis, latent class analysis, and factor mixture modeling using normal theory marginal maximum likelihood for ordinal data. Our aim was to derive a parsimonious, best-fitting cannabis use disorder (CUD) phenotype based on DSM-IV criteria and determine whether DSM-5 craving loads onto a general factor. When compared with latent class and mixture models, factor models provided a better fit to the data. When conditioned on initiation and cannabis use, the association between criteria for abuse, dependence, withdrawal, and craving were best explained by two correlated latent factors for males and females: a general risk factor to CUD and a factor capturing the symptoms of social and occupational impairment as a consequence of frequent use. Secondary analyses revealed a modest increase in the prevalence of DSM-5 CUD compared with DSM-IV cannabis abuse or dependence. It is concluded that, in addition to a general factor with loadings on cannabis use and symptoms of abuse, dependence, withdrawal, and craving, a second clinically relevant factor defined by features of social and occupational impairment was also found for frequent cannabis use. PMID:24588857

Male Role Norms Inventory-Short Form (MRNI-SF): development, confirmatory factor analytic investigation of structure, and measurement invariance across gender.

PubMed

Levant, Ronald F; Hall, Rosalie J; Rankin, Thomas J

2013-04-01

The current study reports the development from the Male Role Norms Inventory-Revised (MRNI-R; Levant, Rankin, Williams, Hasan, & Smalley, 2010) of the 21-item MRNI-Short Form (MRNI-SF). Confirmatory factor analysis of MRNI-SF responses from a sample of 1,017 undergraduate participants (549 men, 468 women) indicated that the best fitting "bifactor" model incorporated the hypothesized 7-factor structure while explicitly modeling an additional, general traditional masculinity ideology factor. Specifically, each item-level indicator loaded on 2 factors: a general traditional masculinity ideology factor and a specific factor corresponding to 1 of the 7 hypothesized traditional masculinity ideology norms. The bifactor model was assessed for measurement invariance across gender groups, with findings of full configural invariance and partial metric invariance, such that factor loadings were equivalent across the gender groups for the 7 specific factors but not for the general traditional masculinity ideology factor. Theoretical explanations for this latter result include the potential that men's sense of self or identity may be engaged when responding to questions asking to what extent they agree or disagree with normative statements about their behavior, a possibility that could be investigated in future research by examining the associations of the general and specific factors with measures of masculine identity. Additional exploratory invariance analyses demonstrated latent mean differences between men and women on 4 of the 8 factors, and equivocal results for invariance of item intercepts, item uniquenesses, and factor variances-covariances.

Shifting attention from objective risk factors to patients' self-assessed health resources: a clinical model for general practice.

PubMed

Hollnagel, H; Malterud, K

1995-12-01

The study was designed to present and apply theoretical and empirical knowledge for the construction of a clinical model intended to shift the attention of the general practitioner from objective risk factors to self-assessed health resources in male and female patients. Review, discussion and analysis of selected theoretical models about personal health resources involving assessing existing theories according to their emphasis concerning self-assessed vs. doctor-assessed health resources, specific health resources vs. life and coping in general, abstract vs. clinically applicable theory, gender perspective explicitly included or not. Relevant theoretical models on health and coping (salutogenesis, coping and social support, control/demand, locus of control, health belief model, quality of life), and the perspective of the underprivileged Other (critical theory, feminist standpoint theory, the patient-centred clinical method) were presented and assessed. Components from Antonovsky's salutogenetic perspective and McWhinney's patient-centred clinical method, supported by gender perspectives, were integrated to a clinical model which is presented. General practitioners are recommended to shift their attention from objective risk factors to self-assessed health resources by means of the clinical model. The relevance and feasibility of the model should be explored in empirical research.

The latent structure of the functional dyspepsia symptom complex: a taxometric analysis.

PubMed

Van Oudenhove, L; Jasper, F; Walentynowicz, M; Witthöft, M; Van den Bergh, O; Tack, J

2016-07-01

Rome III introduced a subdivision of functional dyspepsia (FD) into postprandial distress syndrome and epigastric pain syndrome, characterized by early satiation/postprandial fullness, and epigastric pain/burning, respectively. However, evidence on their degree of overlap is mixed. We aimed to investigate the latent structure of FD to test whether distinguishable symptom-based subgroups exist. Consecutive tertiary care Rome II FD patients completed the dyspepsia symptom severity scale. Confirmatory factor analysis (CFA) was used to compare the fit of a single factor model, a correlated three-factor model based on Rome III subgroups and a bifactor model consisting of a general FD factor and orthogonal subgroup factors. Taxometric analyses were subsequently used to investigate the latent structure of FD. Nine hundred and fifty-seven FD patients (71.1% women, age 41 ± 14.8) participated. In CFA, the bifactor model yielded a significantly better fit than the two other models (χ² difference tests both p < 0.001). All symptoms had significant loadings on both the general and the subgroup-specific factors (all p < 0.05). Somatization was associated with the general (r = 0.72, p < 0.01), but not the subgroup-specific factors (all r < 0.13, p > 0.05). Taxometric analyses supported a dimensional structure of FD (all CCFI<0.38). We found a dimensional rather than categorical latent structure of the FD symptom complex in tertiary care. A combination of a general dyspepsia symptom reporting factor, which was associated with somatization, and symptom-specific factors reflecting the Rome III subdivision fitted the data best. This has implications for classification, pathophysiology, and treatment of FD. © 2016 John Wiley & Sons Ltd.

Factor structure and construct validity of the Generalized Anxiety Disorder 7-item (GAD-7) among Portuguese college students.

PubMed

Bártolo, Ana; Monteiro, Sara; Pereira, Anabela

2017-09-28

: The Generalized Anxiety Disorder 7-item (GAD-7) scale has been presented as a reliable and valid measure to assess generalized anxiety symptoms in several clinical settings and among the general population. However, some researches did not support the original one-dimensional structure of the GAD-7 tool. Our main aim was to examine the factor structure of GAD-7 comparing the one-factor model fit with a two-factor model (3 somatic nature symptoms and 4 cognitive-emotional nature symptoms) in a sample of college students. This validation study with data collected cross-sectionally included 1,031 Portuguese college students attending courses in the six schools of the Polytechnic Institute of Coimbra, Coimbra, Portugal. Measures included the GAD-7, Hospital Anxiety and Depression Scale (HADS) and the University Student Risk Behaviors Questionnaire. Confirmatory factor analysis (CFA) procedures confirmed that neither factor structure was well fitting. Thus, a modified single factor model allowing the error terms of items associated with relaxing difficulties and irritability to covary was an appropriate solution. Additionally, this factor structure revealed configural and metric invariance across gender. A good convergent validity was found by correlating global anxiety and depression. However, this measure showed a weak association with consumption behaviors. Our results are relevant to clinical practice, since the comprehensive approach to GAD-7 contributes to knowing generalized anxiety symptoms trajectory and their correlates within the university setting.

Assessing the Evaluative Content of Personality Questionnaires Using Bifactor Models.

PubMed

Biderman, Michael D; McAbee, Samuel T; Job Chen, Zhuo; Hendy, Nhung T

2018-01-01

Exploratory bifactor models with keying factors were applied to item response data for the NEO-FFI-3 and HEXACO-PI-R questionnaires. Loadings on a general factor and positive and negative keying factors correlated with independent estimates of item valence, suggesting that item valence influences responses to these questionnaires. Correlations between personality domain scores and measures of self-esteem, depression, and positive and negative affect were all reduced significantly when the influence of evaluative content represented by the general and keying factors was removed. Findings support the need to model personality inventories in ways that capture reactions to evaluative item content.

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.

Modeling Differentiation of Cognitive Abilities within the Higher-Order Factor Model Using Moderated Factor Analysis

ERIC Educational Resources Information Center

Molenaar, Dylan; Dolan, Conor V.; Wicherts, Jelte M.; van der Maas, Han L. J.

2010-01-01

The general differentiation hypothesis states that the strength of the correlations among a set of IQ subtests varies with a given variable. Instances of the general differentiation hypothesis that have been considered in the literature include age and ability differentiation. Traditionally, the differentiation effect is attributed to the varying…

The Computation of Orthogonal Independent Cluster Solutions and Their Oblique Analogs in Factor Analysis.

ERIC Educational Resources Information Center

Hofmann, Richard J.

A very general model for the computation of independent cluster solutions in factor analysis is presented. The model is discussed as being either orthogonal or oblique. Furthermore, it is demonstrated that for every orthogonal independent cluster solution there is an oblique analog. Using three illustrative examples, certain generalities are made…

A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint.

PubMed

Kang, Chaogui; Liu, Yu; Guo, Diansheng; Qin, Kun

2015-01-01

We generalized the recently introduced "radiation model", as an analog to the generalization of the classic "gravity model", to consolidate its nature of universality for modeling diverse mobility systems. By imposing the appropriate scaling exponent λ, normalization factor κ and system constraints including searching direction and trip OD constraint, the generalized radiation model accurately captures real human movements in various scenarios and spatial scales, including two different countries and four different cities. Our analytical results also indicated that the generalized radiation model outperformed alternative mobility models in various empirical analyses.

The utility of the bifactor model in understanding unique components of anxiety sensitivity in a South Korean sample.

PubMed

Ebesutani, Chad; Kim, Mirihae; Park, Hee-Hoon

2016-08-01

The present study was the first to examine the applicability of the bifactor structure underlying the Anxiety Sensitivity Index-3 (ASI-3) in an East Asian (South Korean) sample and to determine which factors in the bifactor model were significantly associated with anxiety, depression, and negative affect. Using a sample of 289 South Korean university students, we compared (a) the original 3-factor AS model, (b) a 3-group bifactor AS model, and (c) a 2-group bifactor AS model (with only the physical and social concern group factors present). Results revealed that the 2-group bifactor AS model fit the ASI-3 data the best. Relatedly, although all ASI-3 items loaded on the general AS factor, the Cognitive Concern group factor was not defined in the bifactor model and may therefore need to be omitted in order to accurately model AS when conducting factor analysis and structural equation modeling (SEM) in cross cultural contexts. SEM results also revealed that the general AS factor was the only factor from the 2-group bifactor model that significantly predicted anxiety, depression, and negative affect. Implications and importance of this new bifactor structure of Anxiety Sensitivity in East Asian samples are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

[A competency model of rural general practitioners: theory construction and empirical study].

PubMed

Yang, Xiu-Mu; Qi, Yu-Long; Shne, Zheng-Fu; Han, Bu-Xin; Meng, Bei

2015-04-01

To perform theory construction and empirical study of the competency model of rural general practitioners. Through literature study, job analysis, interviews, and expert team discussion, the questionnaire of rural general practitioners competency was constructed. A total of 1458 rural general practitioners were surveyed by the questionnaire in 6 central provinces. The common factors were constructed using the principal component method of exploratory factor analysis and confirmatory factor analysis. The influence of the competency characteristics on the working performance was analyzed using regression equation analysis. The Cronbach 's alpha coefficient of the questionnaire was 0.974. The model consisted of 9 dimensions and 59 items. The 9 competency dimensions included basic public health service ability, basic clinical skills, system analysis capability, information management capability, communication and cooperation ability, occupational moral ability, non-medical professional knowledge, personal traits and psychological adaptability. The rate of explained cumulative total variance was 76.855%. The model fitting index were Χ(2)/df 1.88, GFI=0.94, NFI=0.96, NNFI=0.98, PNFI=0.91, RMSEA=0.068, CFI=0.97, IFI=0.97, RFI=0.96, suggesting good model fitting. Regression analysis showed that the competency characteristics had a significant effect on job performance. The rural general practitioners competency model provides reference for rural doctor training, rural order directional cultivation of medical students, and competency performance management of the rural general practitioners.

Variance composition, measurement invariance by gender, and construct validity of the Femininity Ideology Scale-Short Form.

PubMed

Levant, Ronald F; Alto, Kathleen M; McKelvey, Daniel K; Richmond, Katherine A; McDermott, Ryon C

2017-11-01

The current study extended prior work on the Femininity Ideology Scale (FIS), a multidimensional measure of traditional femininity ideology (TFI), in several ways. First, we conducted exploratory factor and bifactor analyses, which revealed a general TFI factor and 3 specific factors: dependence/deference, purity, and emotionality/traditional roles. Second, based on these results we developed the 12-item FIS-Short Form (FIS-SF). Third, we assessed the FIS-SF using confirmatory factor analysis on a separate sample, finding that the items loaded on the general factor and 3 specific factors as hypothesized, and that the bifactor model fit better than common factors and unidimensional models. Fourth, model-based reliability estimates tentatively support the use of raw scores to represent the general TFI factor and the emotionality/traditional roles specific factor, but the other 2 specific factors are best measured using SEM or by ipsatizing their scores. Fifth, we assessed measurement invariance across 2 gender groups, finding evidence for configural invariance for all factors, and for partial metric invariance for the specific factors. Sixth, we found evidence for the convergent construct validity of the FIS-SF general factor and the emotionality/traditional roles specific factors by examining relationships with the latent variables of several constructs in the nomological network. The results are discussed in relationship to prior literature, future research directions, applications to counseling practice, and limitations. Data (N = 1,472, 907 women, 565 men, 530 people of color) were from community and college participants who responded to an online survey. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Use of Factor Mixture Modeling to Capture Spearman's Law of Diminishing Returns

ERIC Educational Resources Information Center

Reynolds, Matthew R.; Keith, Timothy Z.; Beretvas, S. Natasha

2010-01-01

Spearman's law of diminishing returns (SLODR) posits that at higher levels of general cognitive ability the general factor ("g") performs less well in explaining individual differences in cognitive test performance. Research has generally supported SLODR, but previous research has required the a priori division of respondents into…

Can Optimism, Pessimism, Hope, Treatment Credibility and Treatment Expectancy Be Distinguished in Patients Undergoing Total Hip and Total Knee Arthroplasty?

PubMed Central

Haanstra, Tsjitske M.; Tilbury, Claire; Kamper, Steven J.; Tordoir, Rutger L.; Vliet Vlieland, Thea P. M.; Nelissen, Rob G. H. H.; Cuijpers, Pim; de Vet, Henrica C. W.; Dekker, Joost; Knol, Dirk L.; Ostelo, Raymond W.

2015-01-01

Objectives The constructs optimism, pessimism, hope, treatment credibility and treatment expectancy are associated with outcomes of medical treatment. While these constructs are grounded in different theoretical models, they nonetheless show some conceptual overlap. The purpose of this study was to examine whether currently available measurement instruments for these constructs capture the conceptual differences between these constructs within a treatment setting. Methods Patients undergoing Total Hip and Total Knee Arthroplasty (THA and TKA) (Total N = 361; 182 THA; 179 TKA), completed the Life Orientation Test-Revised for optimism and pessimism, the Hope Scale, the Credibility Expectancy Questionnaire for treatment credibility and treatment expectancy. Confirmatory factor analysis was used to examine whether the instruments measure distinct constructs. Four theory-driven models with one, two, four and five latent factors were evaluated using multiple fit indices and Δχ2 tests, followed by some posthoc models. Results The results of the theory driven confirmatory factor analysis showed that a five factor model in which all constructs loaded on separate factors yielded the most optimal and satisfactory fit. Posthoc, a bifactor model in which (besides the 5 separate factors) a general factor is hypothesized accounting for the commonality of the items showed a significantly better fit than the five factor model. All specific factors, except for the hope factor, showed to explain a substantial amount of variance beyond the general factor. Conclusion Based on our primary analyses we conclude that optimism, pessimism, hope, treatment credibility and treatment expectancy are distinguishable in THA and TKA patients. Postdoc, we determined that all constructs, except hope, showed substantial specific variance, while also sharing some general variance. PMID:26214176

Can Optimism, Pessimism, Hope, Treatment Credibility and Treatment Expectancy Be Distinguished in Patients Undergoing Total Hip and Total Knee Arthroplasty?

PubMed

Haanstra, Tsjitske M; Tilbury, Claire; Kamper, Steven J; Tordoir, Rutger L; Vliet Vlieland, Thea P M; Nelissen, Rob G H H; Cuijpers, Pim; de Vet, Henrica C W; Dekker, Joost; Knol, Dirk L; Ostelo, Raymond W

2015-01-01

The constructs optimism, pessimism, hope, treatment credibility and treatment expectancy are associated with outcomes of medical treatment. While these constructs are grounded in different theoretical models, they nonetheless show some conceptual overlap. The purpose of this study was to examine whether currently available measurement instruments for these constructs capture the conceptual differences between these constructs within a treatment setting. Patients undergoing Total Hip and Total Knee Arthroplasty (THA and TKA) (Total N = 361; 182 THA; 179 TKA), completed the Life Orientation Test-Revised for optimism and pessimism, the Hope Scale, the Credibility Expectancy Questionnaire for treatment credibility and treatment expectancy. Confirmatory factor analysis was used to examine whether the instruments measure distinct constructs. Four theory-driven models with one, two, four and five latent factors were evaluated using multiple fit indices and Δχ2 tests, followed by some posthoc models. The results of the theory driven confirmatory factor analysis showed that a five factor model in which all constructs loaded on separate factors yielded the most optimal and satisfactory fit. Posthoc, a bifactor model in which (besides the 5 separate factors) a general factor is hypothesized accounting for the commonality of the items showed a significantly better fit than the five factor model. All specific factors, except for the hope factor, showed to explain a substantial amount of variance beyond the general factor. Based on our primary analyses we conclude that optimism, pessimism, hope, treatment credibility and treatment expectancy are distinguishable in THA and TKA patients. Postdoc, we determined that all constructs, except hope, showed substantial specific variance, while also sharing some general variance.

One Factor or Two Parallel Processes? Comorbidity and Development of Adolescent Anxiety and Depressive Disorder Symptoms

ERIC Educational Resources Information Center

Hale, William W., III; Raaijmakers, Quinten A. W.; Muris, Peter; van Hoof, Anne; Meeus, Wim H. J.

2009-01-01

Background: This study investigates whether anxiety and depressive disorder symptoms of adolescents from the general community are best described by a model that assumes they are indicative of one general factor or by a model that assumes they are two distinct disorders with parallel growth processes. Additional analyses were conducted to explore…

Alternative Factor Models and Heritability of the Short Leyton Obsessional Inventory--Children's Version

ERIC Educational Resources Information Center

Moore, Janette; Smith, Gillian W.; Shevlin, Mark; O'Neill, Francis A.

2010-01-01

An alternative models framework was used to test three confirmatory factor analytic models for the Short Leyton Obsessional Inventory-Children's Version (Short LOI-CV) in a general population sample of 517 young adolescent twins (11-16 years). A one-factor model as implicit in current classification systems of Obsessive-Compulsive Disorder (OCD),…

Measurement invariance of the alcohol use disorders identification test: Establishing its factor structure in different settings and across gender.

PubMed

Moehring, Anne; Krause, Kristian; Guertler, Diana; Bischof, Gallus; Hapke, Ulfert; Freyer-Adam, Jennis; Baumann, Sophie; Batra, Anil; Rumpf, Hans-Juergen; Ulbricht, Sabina; John, Ulrich; Meyer, Christian

2018-05-31

The Alcohol Use Disorders Identification Test (AUDIT) is an internationally well-established screening tool for the assessment of hazardous and harmful alcohol consumption. To be valid for group comparisons, the AUDIT should measure the same latent construct with the same structure across groups. This is determined by measurement invariance. So far, measurement invariance of the AUDIT has rarely been investigated. We analyzed measurement invariance across gender and samples from different settings (i.e., inpatients from general hospital, patients from general medical practices, general population). A sample of n = 28,345 participants from general hospitals, general medical practices and the general population was provided from six studies. First, we used Confirmatory Factor Analysis (CFA) to establish the factorial structure of the AUDIT by comparing a single-factor model to a two-factor model for each group. Next, Multiple Group CFA was used to investigate measurement invariance. The two-factor structure was shown to be preferable for all groups. Furthermore, strict measurement invariance was established across all groups for the AUDIT. A two-factor structure for the AUDIT is preferred. Nevertheless, the one-factor structure also showed a good fit to the data. The findings support the AUDIT as a psychometrically valid and reliable screening instrument. Copyright © 2018 Elsevier B.V. All rights reserved.

Recurrent personality dimensions in inclusive lexical studies: indications for a big six structure.

PubMed

Saucier, Gerard

2009-10-01

Previous evidence for both the Big Five and the alternative six-factor model has been drawn from lexical studies with relatively narrow selections of attributes. This study examined factors from previous lexical studies using a wider selection of attributes in 7 languages (Chinese, English, Filipino, Greek, Hebrew, Spanish, and Turkish) and found 6 recurrent factors, each with common conceptual content across most of the studies. The previous narrow-selection-based six-factor model outperformed the Big Five in capturing the content of the 6 recurrent wideband factors. Adjective markers of the 6 recurrent wideband factors showed substantial incremental prediction of important criterion variables over and above the Big Five. Correspondence between wideband 6 and narrowband 6 factors indicate they are variants of a "Big Six" model that is more general across variable-selection procedures and may be more general across languages and populations.

A Generalized Radiation Model for Human Mobility: Spatial Scale, Searching Direction and Trip Constraint

PubMed Central

Kang, Chaogui; Liu, Yu; Guo, Diansheng; Qin, Kun

2015-01-01

We generalized the recently introduced “radiation model”, as an analog to the generalization of the classic “gravity model”, to consolidate its nature of universality for modeling diverse mobility systems. By imposing the appropriate scaling exponent λ, normalization factor κ and system constraints including searching direction and trip OD constraint, the generalized radiation model accurately captures real human movements in various scenarios and spatial scales, including two different countries and four different cities. Our analytical results also indicated that the generalized radiation model outperformed alternative mobility models in various empirical analyses. PMID:26600153

Modeling containment of large wildfires using generalized linear mixed-model analysis

Treesearch

Mark Finney; Isaac C. Grenfell; Charles W. McHugh

2009-01-01

Billions of dollars are spent annually in the United States to contain large wildland fires, but the factors contributing to suppression success remain poorly understood. We used a regression model (generalized linear mixed-model) to model containment probability of individual fires, assuming that containment was a repeated-measures problem (fixed effect) and...

Meteorological influences on the interannual variability of meningitis incidence in northwest Nigeria.

NASA Astrophysics Data System (ADS)

Abdussalam, Auwal; Monaghan, Andrew; Dukic, Vanja; Hayden, Mary; Hopson, Thomas; Leckebusch, Gregor

2013-04-01

Northwest Nigeria is a region with high risk of bacterial meningitis. Since the first documented epidemic of meningitis in Nigeria in 1905, the disease has been endemic in the northern part of the country, with epidemics occurring regularly. In this study we examine the influence of climate on the interannual variability of meningitis incidence and epidemics. Monthly aggregate counts of clinically confirmed hospital-reported cases of meningitis were collected in northwest Nigeria for the 22-year period spanning 1990-2011. Several generalized linear statistical models were fit to the monthly meningitis counts, including generalized additive models. Explanatory variables included monthly records of temperatures, humidity, rainfall, wind speed, sunshine and dustiness from weather stations nearest to the hospitals, and a time series of polysaccharide vaccination efficacy. The effects of other confounding factors -- i.e., mainly non-climatic factors for which records were not available -- were estimated as a smooth, monthly-varying function of time in the generalized additive models. Results reveal that the most important explanatory climatic variables are mean maximum monthly temperature, relative humidity and dustiness. Accounting for confounding factors (e.g., social processes) in the generalized additive models explains more of the year-to-year variation of meningococcal disease compared to those generalized linear models that do not account for such factors. Promising results from several models that included only explanatory variables that preceded the meningitis case data by 1-month suggest there may be potential for prediction of meningitis in northwest Nigeria to aid decision makers on this time scale.

Generalized ghost pilgrim dark energy in F(T,TG) cosmology

NASA Astrophysics Data System (ADS)

Sharif, M.; Nazir, Kanwal

2016-07-01

This paper is devoted to study the generalized ghost pilgrim dark energy (PDE) model in F(T,TG) gravity with flat Friedmann-Robertson-Walker (FRW) universe. In this scenario, we reconstruct F(T,TG) models and evaluate the corresponding equation of state (EoS) parameter for different choices of the scale factors. We assume power-law scale factor, scale factor for unification of two phases, intermediate and bouncing scale factor. We study the behavior of reconstructed models and EoS parameters graphically. It is found that all the reconstructed models show decreasing behavior for PDE parameter u = -2. On the other hand, the EoS parameter indicates transition from dust-like matter to phantom era for all choices of the scale factor except intermediate for which this is less than - 1. We conclude that all the results are in agreement with PDE phenomenon.

The reliability of multidimensional neuropsychological measures: from alpha to omega.

PubMed

Watkins, Marley W

To demonstrate that Coefficient omega, a model-based estimate, is more a more appropriate index of reliability than coefficient alpha for the multidimensional scales that are commonly employed by neuropsychologists. As an illustration, a structural model of an overarching general factor and four first-order factors for the WAIS-IV based on the standardization sample of 2200 participants was identified and omega coefficients were subsequently computed for WAIS-IV composite scores. Alpha coefficients were ≥ .90 and omega coefficients ranged from .75 to .88 for WAIS-IV factor index scores, indicating that the blend of general and group factor variance in each index score created a reliable multidimensional composite. However, the amalgam of variance from general and group factors did not allow the precision of Full Scale IQ (FSIQ) and factor index scores to be disentangled. In contrast, omega hierarchical coefficients were low for all four factor index scores (.10-.41), indicating that most of the reliable variance of each factor index score was due to the general intelligence factor. In contrast, the omega hierarchical coefficient for the FSIQ score was .84. Meaningful interpretation of WAIS-IV factor index scores as unambiguous indicators of group factors is imprecise, thereby fostering unreliable identification of neurocognitive strengths and weaknesses, whereas the WAIS-IV FSIQ score can be interpreted as a reliable measure of general intelligence. It was concluded that neuropsychologists should base their clinical decisions on reliable scores as indexed by coefficient omega.

Validation of the Sexual Orientation Microaggression Inventory In Two Diverse Samples of LGBTQ Youth

PubMed Central

Swann, Gregory; Minshew, Reese; Newcomb, Michael E.; Mustanski, Brian

2016-01-01

Critical race theory asserts that microaggressions, or low-level, covert acts of aggression, are commonplace in the lives of people of color. These theorists also assert a taxonomy of microaggressions, which includes “microassaults,” “microinsults,” and “microinvalidations.” The theory of microaggressions has been adopted by researchers of LGBTQ communities. This study investigated the three-factor taxonomy as it relates to a diverse sample of LGBTQ youth using the newly developed Sexual Orientation Microaggression Inventory (SOMI). Exploratory factor analysis was used to determine the number of factors that exist in SOMI in a sample of 206 LGBTQ-identifying youth. Follow up confirmatory factor analyses (CFAs) were conducted in order to compare single factor, unrestricted four factor, second order, and bi-factor models in a separate sample of 363 young men who have sex with men. The best fitting model was used to predict victimization, depressive symptoms, and depression diagnosis in order to test validity. The best fitting model was a bi-factor model utilizing 19 of the original 26 items with a general factor and four specific factors representing anti-gay attitudes (“microinsults”), denial of homosexuality, heterosexism (“microinvalidations”), and societal disapproval (“microassaults”). Reliability analyses found that the majority of reliable variance was accounted for by the general factor. The general factor was a significant predictor of victimization and depressive symptoms, as well as unrelated to social desirability, suggesting convergent, criterion-related, and discriminant validity. SOMI emerged as a scale with evidence of validity for assessing exposure to microaggressions in a diverse sample of LGBTQ youth. PMID:27067241

Validation of the Sexual Orientation Microaggression Inventory in Two Diverse Samples of LGBTQ Youth.

PubMed

Swann, Gregory; Minshew, Reese; Newcomb, Michael E; Mustanski, Brian

2016-08-01

Critical race theory asserts that microaggressions, or low-level, covert acts of aggression, are commonplace in the lives of people of color. These theorists also assert a taxonomy of microaggressions, which includes "microassaults," "microinsults," and "microinvalidations". The theory of microaggressions has been adopted by researchers of LGBTQ communities. This study investigated the three-factor taxonomy as it relates to a diverse sample of LGBTQ youth using the newly developed Sexual Orientation Microaggression Inventory (SOMI). Exploratory factor analysis was used to determine the number of factors that exist in SOMI in a sample of 206 LGBTQ-identifying youth. Follow up confirmatory factor analyses were conducted in order to compare single-factor, unrestricted four-factor, second-order, and bi-factor models in a separate sample of 363 young men who have sex with men. The best fitting model was used to predict victimization, depressive symptoms, and depression diagnosis in order to test validity. The best fitting model was a bi-factor model utilizing 19 of the original 26 items with a general factor and four specific factors representing anti-gay attitudes ("microinsults"), denial of homosexuality, heterosexism ("microinvalidations"), and societal disapproval ("microassaults"). Reliability analyses found that the majority of reliable variance was accounted for by the general factor. The general factor was a significant predictor of victimization and depressive symptoms, as well as unrelated to social desirability, suggesting convergent, criterion-related, and discriminant validity. SOMI emerged as a scale with evidence of validity for assessing exposure to microaggressions in a diverse sample of LGBTQ youth.

Relating Factor Models for Longitudinal Data to Quasi-Simplex and NARMA Models

ERIC Educational Resources Information Center

Rovine, Michael J.; Molenaar, Peter C. M.

2005-01-01

In this article we show the one-factor model can be rewritten as a quasi-simplex model. Using this result along with addition theorems from time series analysis, we describe a common general model, the nonstationary autoregressive moving average (NARMA) model, that includes as a special case, any latent variable model with continuous indicators…

The factor structure of the 12-item general health questionnaire (GHQ-12) in young Chinese civil servants.

PubMed

Liang, Ying; Wang, Lei; Yin, Xican

2016-09-26

The 12-item General Health Questionnaire (GHQ-12) is a commonly used screening instrument for measuring mental disorders. However, few studies have measured the mental health of Chinese professionals or explored the factor structure of the GHQ-12 through investigations of young Chinese civil servants. This study analyses the factor structure of the GHQ-12 on young Chinese civil servants. Respondents include 1051 participants from six cities in eastern China. Exploratory Factor Analysis (EFA) is used to identify the potential factor structure of the GHQ-12. Confirmatory Factor Analysis (CFA) models of previous studies are referred to for model fitting. The results indicate the GHQ-12 has very good reliability and validity. All ten CFA models are well fitted with the actual data. All the ten models are feasible and fit the data equally well. The Chinese version of the GHQ-12 is suitable for professional groups and can serve as a screening tool to detect anxiety and psychiatric disorders.

Explaining compound generalization in associative and causal learning through rational principles of dimensional generalization.

PubMed

Soto, Fabian A; Gershman, Samuel J; Niv, Yael

2014-07-01

How do we apply learning from one situation to a similar, but not identical, situation? The principles governing the extent to which animals and humans generalize what they have learned about certain stimuli to novel compounds containing those stimuli vary depending on a number of factors. Perhaps the best studied among these factors is the type of stimuli used to generate compounds. One prominent hypothesis is that different generalization principles apply depending on whether the stimuli in a compound are similar or dissimilar to each other. However, the results of many experiments cannot be explained by this hypothesis. Here, we propose a rational Bayesian theory of compound generalization that uses the notion of consequential regions, first developed in the context of rational theories of multidimensional generalization, to explain the effects of stimulus factors on compound generalization. The model explains a large number of results from the compound generalization literature, including the influence of stimulus modality and spatial contiguity on the summation effect, the lack of influence of stimulus factors on summation with a recovered inhibitor, the effect of spatial position of stimuli on the blocking effect, the asymmetrical generalization decrement in overshadowing and external inhibition, and the conditions leading to a reliable external inhibition effect. By integrating rational theories of compound and dimensional generalization, our model provides the first comprehensive computational account of the effects of stimulus factors on compound generalization, including spatial and temporal contiguity between components, which have posed long-standing problems for rational theories of associative and causal learning. (c) 2014 APA, all rights reserved.

Explaining Compound Generalization in Associative and Causal Learning Through Rational Principles of Dimensional Generalization

PubMed Central

Soto, Fabian A.; Gershman, Samuel J.; Niv, Yael

2014-01-01

How do we apply learning from one situation to a similar, but not identical, situation? The principles governing the extent to which animals and humans generalize what they have learned about certain stimuli to novel compounds containing those stimuli vary depending on a number of factors. Perhaps the best studied among these factors is the type of stimuli used to generate compounds. One prominent hypothesis is that different generalization principles apply depending on whether the stimuli in a compound are similar or dissimilar to each other. However, the results of many experiments cannot be explained by this hypothesis. Here we propose a rational Bayesian theory of compound generalization that uses the notion of consequential regions, first developed in the context of rational theories of multidimensional generalization, to explain the effects of stimulus factors on compound generalization. The model explains a large number of results from the compound generalization literature, including the influence of stimulus modality and spatial contiguity on the summation effect, the lack of influence of stimulus factors on summation with a recovered inhibitor, the effect of spatial position of stimuli on the blocking effect, the asymmetrical generalization decrement in overshadowing and external inhibition, and the conditions leading to a reliable external inhibition effect. By integrating rational theories of compound and dimensional generalization, our model provides the first comprehensive computational account of the effects of stimulus factors on compound generalization, including spatial and temporal contiguity between components, which have posed longstanding problems for rational theories of associative and causal learning. PMID:25090430

On the Relation between the Linear Factor Model and the Latent Profile Model

ERIC Educational Resources Information Center

Halpin, Peter F.; Dolan, Conor V.; Grasman, Raoul P. P. P.; De Boeck, Paul

2011-01-01

The relationship between linear factor models and latent profile models is addressed within the context of maximum likelihood estimation based on the joint distribution of the manifest variables. Although the two models are well known to imply equivalent covariance decompositions, in general they do not yield equivalent estimates of the…

Modeling non-linear growth responses to temperature and hydrology in wetland trees

NASA Astrophysics Data System (ADS)

Keim, R.; Allen, S. T.

2016-12-01

Growth responses of wetland trees to flooding and climate variations are difficult to model because they depend on multiple, apparently interacting factors, but are a critical link in hydrological control of wetland carbon budgets. To more generally understand tree growth to hydrological forcing, we modeled non-linear responses of tree ring growth to flooding and climate at sub-annual time steps, using Vaganov-Shashkin response functions. We calibrated the model to six baldcypress tree-ring chronologies from two hydrologically distinct sites in southern Louisiana, and tested several hypotheses of plasticity in wetlands tree responses to interacting environmental variables. The model outperformed traditional multiple linear regression. More importantly, optimized response parameters were generally similar among sites with varying hydrological conditions, suggesting generality to the functions. Model forms that included interacting responses to multiple forcing factors were more effective than were single response functions, indicating the principle of a single limiting factor is not correct in wetlands and both climatic and hydrological variables must be considered in predicting responses to hydrological or climate change.

Activities, self-referent memory beliefs, and cognitive performance: evidence for direct and mediated relations.

PubMed

Jopp, Daniela; Hertzog, Christopher

2007-12-01

In this study, the authors investigated the role of activities and self-referent memory beliefs for cognitive performance in a life-span sample. A factor analysis identified 8 activity factors, including Developmental Activities, Experiential Activities, Social Activities, Physical Activities, Technology Use, Watching Television, Games, and Crafts. A second-order general activity factor was significantly related to a general factor of cognitive function as defined by ability tests. Structural regression models suggested that prediction of cognition by activity level was partially mediated by memory beliefs, controlling for age, education, health, and depressive affect. Models adding paths from general and specific activities to aspects of crystallized intelligence suggested additional unique predictive effects for some activities. In alternative models, nonsignificant effects of beliefs on activities were detected when cognition predicted both variables, consistent with the hypothesis that beliefs derive from monitoring cognition and have no influence on activity patterns. PsycINFO Database Record (c) 2008 APA, all rights reserved.

Coherent dynamic structure factors of strongly coupled plasmas: A generalized hydrodynamic approach

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

Luo, Di; Hu, GuangYue; Gong, Tao

2016-05-15

A generalized hydrodynamic fluctuation model is proposed to simplify the calculation of the dynamic structure factor S(ω, k) of non-ideal plasmas using the fluctuation-dissipation theorem. In this model, the kinetic and correlation effects are both included in hydrodynamic coefficients, which are considered as functions of the coupling strength (Γ) and collision parameter (kλ{sub ei}), where λ{sub ei} is the electron-ion mean free path. A particle-particle particle-mesh molecular dynamics simulation code is also developed to simulate the dynamic structure factors, which are used to benchmark the calculation of our model. A good agreement between the two different approaches confirms the reliabilitymore » of our model.« less

A Comparison of Factor Score Estimation Methods in the Presence of Missing Data: Reliability and an Application to Nicotine Dependence

ERIC Educational Resources Information Center

Estabrook, Ryne; Neale, Michael

2013-01-01

Factor score estimation is a controversial topic in psychometrics, and the estimation of factor scores from exploratory factor models has historically received a great deal of attention. However, both confirmatory factor models and the existence of missing data have generally been ignored in this debate. This article presents a simulation study…

Multi-Group Covariance and Mean Structure Modeling of the Relationship between the WAIS-III Common Factors and Sex and Educational Attainment in Spain

ERIC Educational Resources Information Center

Dolan, Conor V.; Colom, Roberto; Abad, Francisco J.; Wicherts, Jelte M.; Hessen, David J.; van de Sluis, Sophie

2006-01-01

We investigated sex effects and the effects of educational attainment (EA) on the covariance structure of the WAIS-III in a subsample of the Spanish standardization data. We fitted both first order common factor models and second order common factor models. The latter include general intelligence ("g") as a second order common factor.…

Cross-cultural confirmation of bi-factor models of a symptom distress measure: Symptom Checklist-90-Revised in clinical samples.

PubMed

Urbán, Róbert; Arrindell, Willem A; Demetrovics, Zsolt; Unoka, Zsolt; Timman, Reinier

2016-05-30

Four decades have elapsed since the introduction for clinical and research purposes of the Symptom Checklist-90(-R). Yet, its underlying dimensional structure has not been clearly delineated. A shift has been observed in the methods utilized-from predominantly exploratory factor analytic in nature in the first two decades or so to different confirmatory methods in recent years. A need remains to search for a structure that remains invariant across samples and nations. In that context, the present study attempted to replicate and extend recent findings yielded in a Hungarian general population sample (N=2,874) with two psychiatric patient samples from Hungary (N=972) and The Netherlands (N=1,902). In doing so, four models were contrasted: the one-factor model, Derogatis' nine factor model, a second-ordered factor model, and a bi-factor model. The bi-factor model was shown to yield the closest fit to the data in both countries. Further studies are needed to determine the stable number and kind of subscale scores that reflect the specific (primary) symptoms best, that is, those subscales with minimal shared variance with the overall general psychological distress dimension. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Dimensionality of DSM-5 posttraumatic stress disorder and its association with suicide attempts: results from the National Epidemiologic Survey on Alcohol and Related Conditions-III.

PubMed

Chen, Chiung M; Yoon, Young-Hee; Harford, Thomas C; Grant, Bridget F

2017-06-01

Emerging confirmatory factor analytic (CFA) studies suggest that posttraumatic stress disorder (PTSD) as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) is best characterized by seven factors, including re-experiencing, avoidance, negative affect, anhedonia, externalizing behaviors, and anxious and dysphoric arousal. The seven factors, however, have been found to be highly correlated, suggesting that one general factor may exist to explain the overall correlations among symptoms. Using data from the National Epidemiologic Survey on Alcohol and Related Conditions-III, a large, national survey of 36,309 U.S. adults ages 18 and older, this study proposed and tested an exploratory bifactor hybrid model for DSM-5 PTSD symptoms. The model posited one general and seven specific latent factors, whose associations with suicide attempts and mediating psychiatric disorders were used to validate the PTSD dimensionality. The exploratory bifactor hybrid model fitted the data extremely well, outperforming the 7-factor CFA hybrid model and other competing CFA models. The general factor was found to be the single dominant latent trait that explained most of the common variance (~76%) and showed significant, positive associations with suicide attempts and mediating psychiatric disorders, offering support to the concurrent validity of the PTSD construct. The identification of the primary latent trait of PTSD confirms PTSD as an independent psychiatric disorder and helps define PTSD severity in clinical practice and for etiologic research. The accurate specification of PTSD factor structure has implications for treatment efforts and the prevention of suicidal behaviors.

The Traditional Model Does Not Explain Attitudes Toward Euthanasia: A Web-Based Survey of the General Public in Finland.

PubMed

Terkamo-Moisio, Anja; Kvist, Tarja; Laitila, Teuvo; Kangasniemi, Mari; Ryynänen, Olli-Pekka; Pietilä, Anna-Maija

2017-08-01

The debate about euthanasia is ongoing in several countries including Finland. However, there is a lack of information on current attitudes toward euthanasia among general Finnish public. The traditional model for predicting individuals' attitudes to euthanasia is based on their age, gender, educational level, and religiosity. However, a new evaluation of religiosity is needed due to the limited operationalization of this factor in previous studies. This study explores the connections between the factors of the traditional model and the attitudes toward euthanasia among the general public in the Finnish context. The Finnish public's attitudes toward euthanasia have become remarkably more positive over the last decade. Further research is needed on the factors that predict euthanasia attitudes. We suggest two different explanatory models for consideration: one that emphasizes the value of individual autonomy and another that approaches euthanasia from the perspective of fears of death or the process of dying.

A confirmatory factor analysis of the Impact of Event Scale using a sample of World War II and Korean War veterans.

PubMed

Shevlin, M; Hunt, N; Robbins, I

2000-12-01

This study assessed the factor structure of the Impact of Event Scale (IES), a measure of intrusion and avoidance, using a sample of World War II and Korean War veterans who had experienced combat 40-50 years earlier. A series of 3 confirmatory factor analytic models were specified and estimated using LISREL 8.3. Model 1 specified a 1-factor model. Model 2 specified a correlated 2-factor model. Model 3 specified a 2-factor model with additional cross-factor loadings for Items 2 and 12. Model 3 was found to fit the data. In addition, this model was found to be a better explanation of the data than the other models. Also in addition, the correlations between the Intrusion and Avoidance factors and the 4 subscales of the 28-item General Health Questionnaire were examined to determine the distinctiveness of the two IES factors.

The Analysis of Three-Way Contingency Tables by Three-Mode Association Models.

ERIC Educational Resources Information Center

Anderson, Carolyn J.

1996-01-01

Generalizations of L. A. Goodman's RC(M) association model (1991 and earlier) are presented for three-way tables. These three-mode association models use L. R. Tucker's three-mode components model (1964, 1966) to represent the three-factor interaction or the combined effects of two- and three-factor interactions. (SLD)

Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling.

PubMed

Golay, Philippe; Reverte, Isabelle; Rossier, Jérôme; Favez, Nicolas; Lecerf, Thierry

2013-06-01

The interpretation of the Wechsler Intelligence Scale for Children--Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all cross-loadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8-12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores. PsycINFO Database Record (c) 2013 APA, all rights reserved.

An Empirical Comparison of Competing Factor Structures for the Repeatable Battery for the Assessment of Neuropsychological Status: A Project FRONTIER Study†

PubMed Central

Torrence, Nicole D.; John, Samantha E.; Gavett, Brandon E.; O'Bryant, Sid E.

2016-01-01

The original factor structure of the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) has received little empirical support, but at least eight alternative factor structures have been identified in the literature. The current study used confirmatory factor analysis to compare the original RBANS model with eight alternatives, which were adjusted to include a general factor. Participant data were obtained from Project FRONTIER, an epidemiological study of rural health, and comprised 341 adults (229 women, 112 men) with mean age of 61.2 years (SD = 12.1) and mean education of 12.4 years (SD = 3.3). A bifactor version of the model proposed by Duff and colleagues provided the best fit to the data (CFI = 0.98; root-mean-squared error of approximation = 0.07), but required further modification to produce appropriate factor loadings. The results support the inclusion of a general factor and provide partial replication of the Duff and colleagues RBANS model. PMID:26429558

Replication and extension of a hierarchical model of social anxiety and depression: fear of positive evaluation as a key unique factor in social anxiety.

PubMed

Weeks, Justin W

2015-01-01

Wang, Hsu, Chiu, and Liang (2012, Journal of Anxiety Disorders, 26, 215-224) recently proposed a hierarchical model of social interaction anxiety and depression to account for both the commonalities and distinctions between these conditions. In the present paper, this model was extended to more broadly encompass the symptoms of social anxiety disorder, and replicated in a large unselected, undergraduate sample (n = 585). Structural equation modeling (SEM) and hierarchical regression analyses were employed. Negative affect and positive affect were conceptualized as general factors shared by social anxiety and depression; fear of negative evaluation (FNE) and disqualification of positive social outcomes were operationalized as specific factors, and fear of positive evaluation (FPE) was operationalized as a factor unique to social anxiety. This extended hierarchical model explicates structural relationships among these factors, in which the higher-level, general factors (i.e., high negative affect and low positive affect) represent vulnerability markers of both social anxiety and depression, and the lower-level factors (i.e., FNE, disqualification of positive social outcomes, and FPE) are the dimensions of specific cognitive features. Results from SEM and hierarchical regression analyses converged in support of the extended model. FPE is further supported as a key symptom that differentiates social anxiety from depression.

Factorial invariance of pediatric patient self-reported fatigue across age and gender: a multigroup confirmatory factor analysis approach utilizing the PedsQL™ Multidimensional Fatigue Scale.

PubMed

Varni, James W; Beaujean, A Alexander; Limbers, Christine A

2013-11-01

In order to compare multidimensional fatigue research findings across age and gender subpopulations, it is important to demonstrate measurement invariance, that is, that the items from an instrument have equivalent meaning across the groups studied. This study examined the factorial invariance of the 18-item PedsQL™ Multidimensional Fatigue Scale items across age and gender and tested a bifactor model. Multigroup confirmatory factor analysis (MG-CFA) was performed specifying a three-factor model across three age groups (5-7, 8-12, and 13-18 years) and gender. MG-CFA models were proposed in order to compare the factor structure, metric, scalar, and error variance across age groups and gender. The analyses were based on 837 children and adolescents recruited from general pediatric clinics, subspecialty clinics, and hospitals in which children were being seen for well-child checks, mild acute illness, or chronic illness care. A bifactor model of the items with one general factor influencing all the items and three domain-specific factors representing the General, Sleep/Rest, and Cognitive Fatigue domains fit the data better than oblique factor models. Based on the multiple measures of model fit, configural, metric, and scalar invariance were found for almost all items across the age and gender groups, as was invariance in the factor covariances. The PedsQL™ Multidimensional Fatigue Scale demonstrated strict factorial invariance for child and adolescent self-report across gender and strong factorial invariance across age subpopulations. The findings support an equivalent three-factor structure across the age and gender groups studied. Based on these data, it can be concluded that pediatric patients across the groups interpreted the items in a similar manner regardless of their age or gender, supporting the multidimensional factor structure interpretation of the PedsQL™ Multidimensional Fatigue Scale.

Relationship between FEV1 and Cardiovascular Risk Factors in General Population without Airflow Limitation.

PubMed

Lee, Jeong Hyeon; Kang, Yun-Seong; Jeong, Yun-Jeong; Yoon, Young-Soon; Kwack, Won Gun; Oh, Jin Young

2016-01-01

Purpose. We aimed to determine the value of lung function measurement for predicting cardiovascular (CV) disease by evaluating the association between FEV1 (%) and CV risk factors in general population. Materials and Methods. This was a cross-sectional, retrospective study of subjects above 18 years of age who underwent health examinations. The relationship between FEV1 (%) and presence of carotid plaque and thickened carotid IMT (≥0.8 mm) was analyzed by multiple logistic regression, and the relationship between FEV1 (%) and PWV (%), and serum uric acid was analyzed by multiple linear regression. Various factors were adjusted by using Model 1 and Model 2. Results. 1,003 subjects were enrolled in this study and 96.7% ( n = 970) of the subjects were men. In both models, the odds ratio of the presence of carotid plaque and thickened carotid IMT had no consistent trend and statistical significance. In the analysis of the PWV (%) and uric acid, there was no significant relationship with FEV1 (%) in both models. Conclusion. FEV1 had no significant relationship with CV risk factors. The result suggests that FEV1 may have no association with CV risk factors or may be insensitive to detecting the association in general population without airflow limitation.

A New Lease of Life for Thomson's Bonds Model of Intelligence

ERIC Educational Resources Information Center

Bartholomew, David J.; Deary, Ian J.; Lawn, Martin

2009-01-01

Modern factor analysis is the outgrowth of Spearman's original "2-factor" model of intelligence, according to which a mental test score is regarded as the sum of a general factor and a specific factor. As early as 1914, Godfrey Thomson realized that the data did not require this interpretation and he demonstrated this by proposing what became…

A psychometric investigation of gender differences and common processes across Borderline and Antisocial Personality Disorders

PubMed Central

Chun, Seokjoon; Harris, Alexa; Carrion, Margely; Rojas, Elizabeth; Stark, Stephen; Lejuez, Carl; Lechner, William V.; Bornovalova, Marina A.

2016-01-01

The comorbidity between Borderline Personality Disorder (BPD) and Antisocial Personality Disorder (ASPD) is well-established, and the two disorders share many similarities. However, there are also differences across disorders: most notably, BPD is diagnosed more frequently in females and ASPD in males. We investigated if a) comorbidity between BPD and ASPD is attributable to two discrete disorders or the expression of common underlying processes, and b) if the model of comorbidity is true across sex. Using a clinical sample of 1400 drug users in residential substance abuse treatment, we tested three competing models to explore whether the comorbidity of ASPD and BPD should be represented by a single common factor, two correlated factors, or a bifactor structure involving a general and disorder-specific factors. Next, we tested whether our resulting model was meaningful by examining its relationship with criterion variables previously reported to be associated with BPD and ASPD. The bifactor model provided the best fit and was invariant across sex. Overall, the general factor of the bifactor model significantly accounted for a large percentage of the variance in criterion variables, whereas the BPD and AAB specific factors added little to the models. The association of the general and specific factor with all criterion variables was equal for males and females. Our results suggest common underlying vulnerability accounts for both the comorbidity between BPD and AAB (across sex), and this common vulnerability drives the association with other psychopathology and maladaptive behavior. This in turn has implications for diagnostic classification systems and treatment. General scientific summary This study found that, for both males and females, borderline and antisocial personality disorders show a large degree of overlap, and little uniqueness. The commonality between BPD and ASPD mainly accounted for associations with criterion variables. This suggests that BPD and ASPD show a large common core that accounts for their comorbidity. PMID:27808543

Parental Self-Efficacy and Bullying in Elementary School

ERIC Educational Resources Information Center

Malm, Esther Kweiki; Henrich, Christopher; Varjas, Kris; Meyers, Joel

2017-01-01

This study investigated associations of general and specific parental self-efficacy factors with bullying and peer victimization behaviors among 142 fourth and fifth graders and their parents. Using structural equation modeling, exploratory factor analysis was used to examine one general parenting self-efficacy measure and a bullying-specific…

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…

Measurement of Coronary-Prone Behavior and Autonomic Reactivity.

DTIC Science & Technology

1981-05-01

function or emotionality, suggests a three-factor model: a general autonomic e:tivity factor identical with anxiety and two other autonomic activity...alerting response may be an example of Cattell’s general anxiety factor. Other studies have focused on similarities of physiological responses across...approach. Zuckerman et al. (81) examined the relationships amon: anxiety , depression, hostility, GSR, heart rate, and breathing during a cold pressor

FACTORS INFLUENCING THE DESIGN OF BIOACCUMULATION FACTOR AND BIOTA-SEDIMENT ACCUMULATION FACTOR FIELD STUDIES

EPA Science Inventory

General guidance for designing field studies to measure bioaccumulation factors (BAFs) and biota-sediment accumulation factors (BSAFs) is not available. To develop such guidance, a series of modeling simulations were performed to evaluate the underlying factors and principles th...

Global sensitivity analysis for urban water quality modelling: Terminology, convergence and comparison of different methods

NASA Astrophysics Data System (ADS)

Vanrolleghem, Peter A.; Mannina, Giorgio; Cosenza, Alida; Neumann, Marc B.

2015-03-01

Sensitivity analysis represents an important step in improving the understanding and use of environmental models. Indeed, by means of global sensitivity analysis (GSA), modellers may identify both important (factor prioritisation) and non-influential (factor fixing) model factors. No general rule has yet been defined for verifying the convergence of the GSA methods. In order to fill this gap this paper presents a convergence analysis of three widely used GSA methods (SRC, Extended FAST and Morris screening) for an urban drainage stormwater quality-quantity model. After the convergence was achieved the results of each method were compared. In particular, a discussion on peculiarities, applicability, and reliability of the three methods is presented. Moreover, a graphical Venn diagram based classification scheme and a precise terminology for better identifying important, interacting and non-influential factors for each method is proposed. In terms of convergence, it was shown that sensitivity indices related to factors of the quantity model achieve convergence faster. Results for the Morris screening method deviated considerably from the other methods. Factors related to the quality model require a much higher number of simulations than the number suggested in literature for achieving convergence with this method. In fact, the results have shown that the term "screening" is improperly used as the method may exclude important factors from further analysis. Moreover, for the presented application the convergence analysis shows more stable sensitivity coefficients for the Extended-FAST method compared to SRC and Morris screening. Substantial agreement in terms of factor fixing was found between the Morris screening and Extended FAST methods. In general, the water quality related factors exhibited more important interactions than factors related to water quantity. Furthermore, in contrast to water quantity model outputs, water quality model outputs were found to be characterised by high non-linearity.

Multiple robustness in factorized likelihood models.

PubMed

Molina, J; Rotnitzky, A; Sued, M; Robins, J M

2017-09-01

We consider inference under a nonparametric or semiparametric model with likelihood that factorizes as the product of two or more variation-independent factors. We are interested in a finite-dimensional parameter that depends on only one of the likelihood factors and whose estimation requires the auxiliary estimation of one or several nuisance functions. We investigate general structures conducive to the construction of so-called multiply robust estimating functions, whose computation requires postulating several dimension-reducing models but which have mean zero at the true parameter value provided one of these models is correct.

Internal structure of the Community Assessment of Psychic Experiences-Positive (CAPE-P15) scale: Evidence for a general factor.

PubMed

Núñez, D; Arias, V; Vogel, E; Gómez, L

2015-07-01

Psychotic-like experiences (PLEs) are prevalent in the general population and are associated with poor mental health and a higher risk of psychiatric disorders. The Community Assessment of Psychic Experiences-Positive (CAPE-P15) scale is a self-screening questionnaire to address subclinical positive psychotic symptoms (PPEs) in community contexts. Although its psychometric properties seem to be adequate to screen PLEs, further research is needed to evaluate certain validity aspects, particularly its internal structure and its functioning in different populations. To uncover the optimal factor structure of the CAPE-P15 scale in adolescents aged 13 to 18 years using factorial analysis methods suitable to manage categorical variables. A sample of 727 students from six secondary public schools and 245 university students completed the CAPE-P15. The dimensionality of the CAPE-P15 was tested through exploratory structural equation models (ESEMs). Based on the ESEM results, we conducted a confirmatory factor analysis (CFA) to contrast two factorial structures that potentially underlie the symptoms described by the scale: a) three correlated factors and b) a hierarchical model composed of a general PLE factor plus three specific factors (persecutory ideation, bizarre experiences, and perceptual abnormalities). The underlying structure of PLEs assessed by the CAPE-P15 is consistent with both multidimensional and hierarchical solutions. However, the latter show the best fit. Our findings reveal the existence of a strong general factor underlying scale scores. Compared with the specific factors, the general factor explains most of the common variance observed in subjects' responses. The findings suggest that the factor structure of subthreshold psychotic experiences addressed by the CAPE-P15 can be adequately represented by a general factor and three separable specific traits, supporting the hypothesis according to which there might be a common source underlying PLEs. Copyright © 2015 Elsevier B.V. All rights reserved.

A measurement model for general noise reaction in response to aircraft noise.

PubMed

Kroesen, Maarten; Schreckenberg, Dirk

2011-01-01

In this paper a measurement model for general noise reaction (GNR) in response to aircraft noise is developed to assess the performance of aircraft noise annoyance and a direct measure of general reaction as indicators of this concept. For this purpose GNR is conceptualized as a superordinate latent construct underlying particular manifestations. This conceptualization is empirically tested through estimation of a second-order factor model. Data from a community survey at Frankfurt Airport are used for this purpose (N=2206). The data fit the hypothesized factor structure well and support the conceptualization of GNR as a superordinate construct. It is concluded that noise annoyance and a direct measure of general reaction to noise capture a large part of the negative feelings and emotions in response to aircraft noise but are unable to capture all relevant variance. The paper concludes with recommendations for the valid measurement of community reaction and several directions for further research.

Common Genetic Influences on Negative Emotionality and a General Psychopathology Factor in Childhood and Adolescence

PubMed Central

Tackett, Jennifer L.; Lahey, Benjamin B.; Hulle, Carol Van; Waldman, Irwin; Krueger, Robert F.; Rathouz, Paul J.

2014-01-01

Previous research using confirmatory factor analysis to model psychopathology comorbidity supported the hypothesis of a broad general factor (i.e., a “bifactor”; Holzinger & Swineford, 1937) of psychopathology in children, adolescents, and adults, with more specific higher-order internalizing and externalizing factors reflecting additional shared variance in symptoms (Lahey et al., 2012; Lahey, Van Hulle, Singh, Waldman, & Rathouz, 2011). The psychological nature of this general factor has not been explored, however. The current study tests a prediction derived from the spectrum hypothesis of personality and psychopathology, that variance in a general psychopathology bifactor overlaps substantially—at both phenotypic and genetic levels—with the dispositional trait of negative emotionality. Data on psychopathology symptoms and dispositional traits were collected from both parents and youth in a representative sample of 1,569 twin pairs (ages 9–17) from Tennessee. Predictions based on the spectrum hypothesis were supported, with variance in negative emotionality and the general factor overlapping substantially at both phenotypic and etiologic levels. Furthermore, stronger correlations were found between negative emotionality and the general psychopathology factor than among other dispositions and other psychopathology factors. PMID:24364617

Common genetic influences on negative emotionality and a general psychopathology factor in childhood and adolescence.

PubMed

Tackett, Jennifer L; Lahey, Benjamin B; van Hulle, Carol; Waldman, Irwin; Krueger, Robert F; Rathouz, Paul J

2013-11-01

Previous research using confirmatory factor analysis to model psychopathology comorbidity has supported the hypothesis of a broad general factor (i.e., a "bifactor"; Holzinger & Swineford, 1937) of psychopathology in children, adolescents, and adults, with more specific higher order internalizing and externalizing factors reflecting additional shared variance in symptoms (Lahey et al., 2012; Lahey, van Hulle, Singh, Waldman, & Rathouz, 2011). The psychological nature of this general factor has not been explored, however. The current study tested a prediction, derived from the spectrum hypothesis of personality and psychopathology, that variance in a general psychopathology bifactor overlaps substantially-at both phenotypic and genetic levels-with the dispositional trait of negative emotionality. Data on psychopathology symptoms and dispositional traits were collected from both parents and youth in a representative sample of 1,569 twin pairs (ages 9-17 years) from Tennessee. Predictions based on the spectrum hypothesis were supported, with variance in negative emotionality and the general factor overlapping substantially at both phenotypic and etiologic levels. Furthermore, stronger correlations were found between negative emotionality and the general psychopathology factor than among other dispositions and other psychopathology factors. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Volatility in GARCH Models of Business Tendency Index

NASA Astrophysics Data System (ADS)

Wahyuni, Dwi A. S.; Wage, Sutarman; Hartono, Ateng

2018-01-01

This paper aims to obtain a model of business tendency index by considering volatility factor. Volatility factor detected by ARCH (Autoregressive Conditional Heteroscedasticity). The ARCH checking was performed using the Lagrange multiplier test. The modeling is Generalized Autoregressive Conditional Heteroscedasticity (GARCH) are able to overcome volatility problems by incorporating past residual elements and residual variants.

An ecological model of intimate partner violence perpetration at different levels of severity.

PubMed

Smith Slep, Amy M; Foran, Heather M; Heyman, Richard E

2014-08-01

Intimate partner violence (IPV) is a significant public health concern. This study proposed and tested an ecological model of both general and clinically significant (i.e., injurious or fear-evoking) IPV perpetration (IPVPerp). Risk and promotive factors from multiple ecological levels of influence (i.e., individual, family, workplace, community) were hypothesized to be important in the prediction of IPVPerp. Although clinically significant IPVPerp and general IPVPerp were hypothesized to relate, specific risks for clinically significant IPVPerp were hypothesized. U.S. Air Force active duty members and civilian spouses (N = 34,861 men; 24,331 women) from 82 sites worldwide completed the 2006 Community Assessment, an anonymous online survey assessing IPVPerp along with a variety of potential risk and promotive factors. Final structural equation models for men and women, cross-validated in holdout samples, clearly supported the relevance of an ecological approach to IPVPerp. Factors from all 4 levels were associated with both general IPVPerp and clinically significant IPVPerp, with relatively distal community and workplace factors operating via more proximal individual and family level variables (e.g., relationship satisfaction). The results suggest a variety of both established and novel potential targets for indirectly targeting general and clinically significant IPVPerp by improving risk profiles at the individual, family, workplace, and community levels.

Development of the Internet addiction scale based on the Internet Gaming Disorder criteria suggested in DSM-5.

PubMed

Cho, Hyun; Kwon, Min; Choi, Ji-Hye; Lee, Sang-Kyu; Choi, Jung Seok; Choi, Sam-Wook; Kim, Dai-Jin

2014-09-01

This study was conducted to develop and validate a standardized self-diagnostic Internet addiction (IA) scale based on the diagnosis criteria for Internet Gaming Disorder (IGD) in the Diagnostic and Statistical Manual of Mental Disorder, 5th edition (DSM-5). Items based on the IGD diagnosis criteria were developed using items of the previous Internet addiction scales. Data were collected from a community sample. The data were divided into two sets, and confirmatory factor analysis (CFA) was performed repeatedly. The model was modified after discussion with professionals based on the first CFA results, after which the second CFA was performed. The internal consistency reliability was generally good. The items that showed significantly low correlation values based on the item-total correlation of each factor were excluded. After the first CFA was performed, some factors and items were excluded. Seven factors and 26 items were prepared for the final model. The second CFA results showed good general factor loading, Squared Multiple Correlation (SMC) and model fit. The model fit of the final model was good, but some factors were very highly correlated. It is recommended that some of the factors be refined through further studies. Copyright © 2014. Published by Elsevier Ltd.

A Class of Factor Analysis Estimation Procedures with Common Asymptotic Sampling Properties

ERIC Educational Resources Information Center

Swain, A. J.

1975-01-01

Considers a class of estimation procedures for the factor model. The procedures are shown to yield estimates possessing the same asymptotic sampling properties as those from estimation by maximum likelihood or generalized last squares, both special members of the class. General expressions for the derivatives needed for Newton-Raphson…

Roles of General versus Second Language (L2) Knowledge in L2 Reading Comprehension

ERIC Educational Resources Information Center

Guo, Ying; Roehrig, Alysia D.

2011-01-01

We examined the roles of metacognitive awareness of reading strategies, syntactic awareness in English, and English vocabulary knowledge in the English reading comprehension of Chinese-speaking university students (n = 278). Results suggested a two-factor model of a General Reading Knowledge factor (metacognitive awareness employed during the…

Acceptability of Family Violence: Underlying Ties Between Intimate Partner Violence and Child Abuse.

PubMed

Gracia, Enrique; Rodriguez, Christina M; Martín-Fernández, Manuel; Lila, Marisol

2017-05-01

Intimate partner violence (IPV) and child abuse (CA) are two forms of family violence with shared qualities and risk factors, and are forms of violence that tend to overlap. Acceptability of violence in partner relationships is a known risk factor in IPV just as acceptability of parent-child aggression is a risk factor in CA. We hypothesized that these acceptability attitudes may be linked and represent the expression of a general, underlying nonspecific acceptance of violence in close family relationships. The sample involved 164 male IPV offenders participating in a batterer intervention program. Implicit measures, which assess constructs covertly to minimize response distortions, were administered to assess acceptability of partner violence against women and acceptability of parent-child aggression. To determine whether acceptability attitudes regarding both forms of violence were related to a higher order construct tapping general acceptance of family violence, Bayesian confirmatory factor analyses were conducted. Findings supported a hierarchical (bifactor) model with a general factor expressing a nonspecific acceptance of family violence, and two specific factors reflecting acceptability of violence in intimate partner and parent-child relationships, respectively. This hierarchical model supporting a general acceptance of violence in close family relationships can inform future research aiming to better understand the connections between IPV and CA.

Influence of gender and other factors on medical student specialty interest.

PubMed

Boyle, Veronica; Shulruf, Boaz; Poole, Phillippa

2014-09-12

Medical schools must select and educate to meet anticipated health needs. Factors influencing career choice include those of the student and their background as well as subsequent experience. Women have comprised over 50% of medical classes for over 20 years. This study describes gender patterns of current specialty interest among medical students at the University of Auckland, and models the predictive effect of gender compared to other career influencing factors. The study analysed career intention survey data from 711 graduating medical students (response rate, 79%) from 2006 to 2011. Interest level was highest for medicine, followed by subspecialty surgery, general practice and paediatrics. There were differences by gender for most specialties, but not for general practice. Women were more likely than men to be interested in Obstetrics and Gynaecology, Paediatrics, Geriatrics, Public Health or General Medicine, and less interested in Surgery, Anaesthesia, Emergency Medicine or post graduate study. Each specialty had a different pattern of influencing factors with the most important factor being the experience on a clinical attachment. Factors in career choice are complex and vary by gender and specialty. General practice levels of interest are too low for workforce needs. Predictive models need to be validated in longer term studies but may help guide selection and curriculum design.

Structural validity of the Wechsler Intelligence Scale for Children-Fifth Edition: Confirmatory factor analyses with the 16 primary and secondary subtests.

PubMed

Canivez, Gary L; Watkins, Marley W; Dombrowski, Stefan C

2017-04-01

The factor structure of the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V; Wechsler, 2014a) standardization sample (N = 2,200) was examined using confirmatory factor analyses (CFA) with maximum likelihood estimation for all reported models from the WISC-V Technical and Interpretation Manual (Wechsler, 2014b). Additionally, alternative bifactor models were examined and variance estimates and model-based reliability estimates (ω coefficients) were provided. Results from analyses of the 16 primary and secondary WISC-V subtests found that all higher-order CFA models with 5 group factors (VC, VS, FR, WM, and PS) produced model specification errors where the Fluid Reasoning factor produced negative variance and were thus judged inadequate. Of the 16 models tested, the bifactor model containing 4 group factors (VC, PR, WM, and PS) produced the best fit. Results from analyses of the 10 primary WISC-V subtests also found the bifactor model with 4 group factors (VC, PR, WM, and PS) produced the best fit. Variance estimates from both 16 and 10 subtest based bifactor models found dominance of general intelligence (g) in accounting for subtest variance (except for PS subtests) and large ω-hierarchical coefficients supporting general intelligence interpretation. The small portions of variance uniquely captured by the 4 group factors and low ω-hierarchical subscale coefficients likely render the group factors of questionable interpretive value independent of g (except perhaps for PS). Present CFA results confirm the EFA results reported by Canivez, Watkins, and Dombrowski (2015); Dombrowski, Canivez, Watkins, and Beaujean (2015); and Canivez, Dombrowski, and Watkins (2015). (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Applying the Technology Acceptance Model and flow theory to Cyworld user behavior: implication of the Web2.0 user acceptance.

PubMed

Shin, Dong-Hee; Kim, Won-Yong; Kim, Won-Young

2008-06-01

This study explores attitudinal and behavioral patterns when using Cyworld by adopting an expanded Technology Acceptance Model (TAM). A model for Cyworld acceptance is used to examine how various factors modified from the TAM influence acceptance and its antecedents. This model is examined through an empirical study involving Cyworld users using structural equation modeling techniques. The model shows reasonably good measurement properties and the constructs are validated. The results not only confirm the model but also reveal general factors applicable to Web2.0. A set of constructs in the model can be the Web2.0-specific factors, playing as enhancing factor to attitudes and intention.

Factors Influencing the Incidence of Obesity in Australia: A Generalized Ordered Probit Model.

PubMed

Avsar, Gulay; Ham, Roger; Tannous, W Kathy

2017-02-10

The increasing health costs of and the risks factors associated with obesity are well documented. From this perspective, it is important that the propensity of individuals towards obesity is analyzed. This paper uses longitudinal data from the Household Income and Labour Dynamics in Australia (HILDA) Survey for 2005 to 2010 to model those variables which condition the probability of being obese. The model estimated is a random effects generalized ordered probit, which exploits two sources of heterogeneity; the individual heterogeneity of panel data models and heterogeneity across body mass index (BMI) categories. The latter is associated with non-parallel thresholds in the generalized ordered model, where the thresholds are functions of the conditioning variables, which comprise economic, social, and demographic and lifestyle variables. To control for potential predisposition to obesity, personality traits augment the empirical model. The results support the view that the probability of obesity is significantly determined by the conditioning variables. Particularly, personality is found to be important and these outcomes reinforce other work examining personality and obesity.

Prediction of the presence of insulin resistance using general health checkup data in Japanese employees with metabolic risk factors.

PubMed

Takahara, Mitsuyoshi; Katakami, Naoto; Kaneto, Hideaki; Noguchi, Midori; Shimomura, Iichiro

2014-01-01

The aim of the current study was to develop a predictive model of insulin resistance using general health checkup data in Japanese employees with one or more metabolic risk factors. We used a database of 846 Japanese employees with one or more metabolic risk factors who underwent general health checkup and a 75-g oral glucose tolerance test (OGTT). Logistic regression models were developed to predict existing insulin resistance evaluated using the Matsuda index. The predictive performance of these models was assessed using the C statistic. The C statistics of body mass index (BMI), waist circumference and their combined use were 0.743, 0.732 and 0.749, with no significant differences. The multivariate backward selection model, in which BMI, the levels of plasma glucose, high-density lipoprotein (HDL) cholesterol, log-transformed triglycerides and log-transformed alanine aminotransferase and hypertension under treatment remained, had a C statistic of 0.816, with a significant difference compared to the combined use of BMI and waist circumference (p＜0.01). The C statistic was not significantly reduced when the levels of log-transformed triglycerides and log-transformed alanine aminotransferase and hypertension under treatment were simultaneously excluded from the multivariate model (p=0.14). On the other hand, further exclusion of any of the remaining three variables significantly reduced the C statistic (all p＜0.01). When predicting the presence of insulin resistance using general health checkup data in Japanese employees with metabolic risk factors, it is important to take into consideration the BMI and fasting plasma glucose and HDL cholesterol levels.

The Structure of Personality Disorders in Individuals with Posttraumatic Stress Disorder

PubMed Central

Wolf, Erika J.; Miller, Mark W.; Brown, Timothy A.

2015-01-01

Research on the structure of personality disorders (PDs) has relied primarily on exploratory analyses to evaluate trait-based models of the factors underlying the covariation of these disorders. This study used confirmatory factor analysis to evaluate whether a model that included both PD traits and a general personality dysfunction factor would account for the comorbidity of the PDs better than a trait-only model. It also examined if the internalizing/externalizing model of psychopathology, developed previously through research on the structure of Axis I disorders, might similarly account for the covariation of the Axis II disorders in a sample of 245 veterans and non-veterans with posttraumatic stress disorder. Results indicated that the best fitting model was a modified bifactor structure composed of nine lower-order common factors. These factors indexed pathology ranging from aggression to dependency, with the correlations among them accounted for by higher-order Internalizing and Externalizing factors. Further, a general factor, reflecting a construct that we termed boundary disturbance, accounted for additional variance and covariance across nearly all the indicators. The Internalizing, Externalizing, and Boundary Disturbance factors evidenced differential associations with trauma-related covariates. These findings suggest continuity in the underlying structure of psychopathology across DSM-IV Axes I & II and provide empirical evidence of a pervasive, core disturbance in the boundary between self and other across the PDs. PMID:22448802

The short-form version of the Depression Anxiety Stress Scales (DASS-21): construct validity and normative data in a large non-clinical sample.

PubMed

Henry, Julie D; Crawford, John R

2005-06-01

To test the construct validity of the short-form version of the Depression anxiety and stress scale (DASS-21), and in particular, to assess whether stress as indexed by this measure is synonymous with negative affectivity (NA) or whether it represents a related, but distinct, construct. To provide normative data for the general adult population. Cross-sectional, correlational and confirmatory factor analysis (CFA). The DASS-21 was administered to a non-clinical sample, broadly representative of the general adult UK population (N = 1,794). Competing models of the latent structure of the DASS-21 were evaluated using CFA. The model with optimal fit (RCFI = 0.94) had a quadripartite structure, and consisted of a general factor of psychological distress plus orthogonal specific factors of depression, anxiety, and stress. This model was a significantly better fit than a competing model that tested the possibility that the Stress scale simply measures NA. The DASS-21 subscales can validly be used to measure the dimensions of depression, anxiety, and stress. However, each of these subscales also taps a more general dimension of psychological distress or NA. The utility of the measure is enhanced by the provision of normative data based on a large sample.

Exploratory Bi-Factor Analysis: The Oblique Case

ERIC Educational Resources Information Center

Jennrich, Robert I.; Bentler, Peter M.

2012-01-01

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

Quantifying cardiometabolic risk using modifiable non-self-reported risk factors.

PubMed

Marino, Miguel; Li, Yi; Pencina, Michael J; D'Agostino, Ralph B; Berkman, Lisa F; Buxton, Orfeu M

2014-08-01

Sensitive general cardiometabolic risk assessment tools of modifiable risk factors would be helpful and practical in a range of primary prevention interventions or for preventive health maintenance. To develop and validate a cumulative general cardiometabolic risk score that focuses on non-self-reported modifiable risk factors such as glycosylated hemoglobin (HbA1c) and BMI so as to be sensitive to small changes across a span of major modifiable risk factors, which may not individually cross clinical cut-off points for risk categories. We prospectively followed 2,359 cardiovascular disease (CVD)-free subjects from the Framingham offspring cohort over a 14-year follow-up. Baseline (fifth offspring examination cycle) included HbA1c and cholesterol measurements. Gender-specific Cox proportional hazards models were considered to evaluate the effects of non-self-reported modifiable risk factors (blood pressure, total cholesterol, high-density lipoprotein cholesterol, smoking, BMI, and HbA1c) on general CVD risk. We constructed 10-year general cardiometabolic risk score functions and evaluated its predictive performance in 2012-2013. HbA1c was significantly related to general CVD risk. The proposed cardiometabolic general CVD risk model showed good predictive performance as determined by cross-validated discrimination (male C-index=0.703, 95% CI=0.668, 0.734; female C-index=0.762, 95% CI=0.726, 0.801) and calibration (lack-of-fit chi-square=9.05 [p=0.338] and 12.54 [p=0.128] for men and women, respectively). This study presents a risk factor algorithm that provides a convenient and informative way to quantify cardiometabolic risk on the basis of modifiable risk factors that can motivate an individual's commitment to prevention and intervention. Copyright © 2014 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Quantifying Cardiometabolic Risk Using Modifiable Non–Self-Reported Risk Factors

PubMed Central

Marino, Miguel; Li, Yi; Pencina, Michael J.; D’Agostino, Ralph B.; Berkman, Lisa F.; Buxton, Orfeu M.

2014-01-01

Background Sensitive general cardiometabolic risk assessment tools of modifiable risk factors would be helpful and practical in a range of primary prevention interventions or for preventive health maintenance. Purpose To develop and validate a cumulative general cardiometabolic risk score that focuses on non–self-reported modifiable risk factors such as glycosylated hemoglobin (HbA1c) and BMI so as to be sensitive to small changes across a span of major modifiable risk factors, which may not individually cross clinical cut off points for risk categories. Methods We prospectively followed 2,359 cardiovascular disease (CVD)-free subjects from the Framingham offspring cohort over a 14–year follow-up. Baseline (fifth offspring examination cycle) included HbA1c and cholesterol measurements. Gender–specific Cox proportional hazards models were considered to evaluate the effects of non–self-reported modifiable risk factors (blood pressure, total cholesterol, high–density lipoprotein cholesterol, smoking, BMI, and HbA1c) on general CVD risk. We constructed 10–year general cardiometabolic risk score functions and evaluated its predictive performance in 2012–2013. Results HbA1c was significantly related to general CVD risk. The proposed cardiometabolic general CVD risk model showed good predictive performance as determined by cross-validated discrimination (male C-index=0.703, 95% CI=0.668, 0.734; female C-index=0.762, 95% CI=0.726, 0.801) and calibration (lack-of-fit χ2=9.05 [p=0.338] and 12.54 [p=0.128] for men and women, respectively). Conclusions This study presents a risk factor algorithm that provides a convenient and informative way to quantify cardiometabolic risk based on modifiable risk factors that can motivate an individual’s commitment to prevention and intervention. PMID:24951039

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

PubMed

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

2012-12-01

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

The Development of the General Factor of Psychopathology 'p Factor' Through Childhood and Adolescence.

PubMed

Murray, Aja Louise; Eisner, Manuel; Ribeaud, Denis

2016-11-01

Recent studies have suggested that the structure of psychopathology may be usefully represented in terms of a general factor of psychopathology (p-factor) capturing variance common to a broad range of symptoms transcending diagnostic domains in addition to specific factors capturing variance common to smaller subsets of more closely related symptoms. Little is known about how the general co-morbidity captured by this p-factor develops and whether general co-morbidity increases or decreases over childhood and adolescence. We evaluated two competing hypotheses: 1) dynamic mutualism which predicts growth in general co-morbidity and associated p-factor strength over time and 2) p-differentiation which predicts that manifestations of liabilities towards psychopathology become increasingly specific over time. Data came from the Zurich Project on the Social Development of Children and Youths (z-proso), a longitudinal study of a normative sample (approx. 50 % male) measured at 8 time points from ages 7 to 15. We operationalised general co-morbidity as p-factor strength in a bi-factor model and used omega hierarchical to track how this changed over development. In contrast to the predictions of both dynamic mutualism and p-differentiation, p-factor strength remained relatively constant over the studied period suggesting that such processes do not govern the interplay between psychopathological symptoms during this phase of development. Future research should focus on earlier phases of development and on factors that maintain the consistency of symptom-general covariation across this period.

Stochastic nature of Landsat MSS data

NASA Technical Reports Server (NTRS)

Labovitz, M. L.; Masuoka, E. J.

1987-01-01

A multiple series generalization of the ARIMA models is used to model Landsat MSS scan lines as sequences of vectors, each vector having four elements (bands). The purpose of this work is to investigate if Landsat scan lines can be described by a general multiple series linear stochastic model and if the coefficients of such a model vary as a function of satellite system and target attributes. To accomplish this objective, an exploratory experimental design was set up incorporating six factors, four representing target attributes - location, cloud cover, row (within location), and column (within location) - and two factors representing system attributes - satellite number and detector bank. Each factor was included in the design at two levels and, with two replicates per treatment, 128 scan lines were analyzed. The results of the analysis suggests that a multiple AR(4) model is an adequate representation across all scan lines. Furthermore, the coefficients of the AR(4) model vary with location, particularly changes in physiography (slope regimes), and with percent cloud cover, but are insensitive to changes in system attributes.

Student Engagement as a General Factor of Classroom Experience: Associations with Student Practices and Educational Outcomes in a University Gateway Course

PubMed Central

Shernof, David J.; Ruzek, Erik A.; Sannella, Alexander J.; Schorr, Roberta Y.; Sanchez-Wall, Lina; Bressler, Denise M.

2017-01-01

The purpose of this study was to evaluate a model for considering general and specific elements of student experience in a gateway course in undergraduate Financial Accounting in a large university on the East Coast, USA. Specifically, the study evaluated a bifactor analytic strategy including a general factor of student classroom experience, conceptualized as student engagement as rooted in flow theory, as well as factors representing specific dimensions of experience. The study further evaluated the association between these general and specific factors and both student classroom practices and educational outcomes. The sample of students (N = 407) in two cohorts of the undergraduate financial accounting course participated in the Experience Sampling Method (ESM) measuring students' classroom practices, perceptions, engagement, and perceived learning throughout the one-semester course. Course grade information was also collected. Results showed that a two-level bifactor model fit the data better than two traditional (i.e., non-bifactor) models and also avoided significant multicollinearity of the traditional models. In addition to student engagement (general factor), specific dimensions of classroom experience in the bifactor model at the within-student level included intrinsic motivation, academic intensity, salience, and classroom self-esteem. At the between-student level, specific aspects included work orientation, learning orientation, classroom self-esteem, and disengagement. Multilevel Structural Equation Modeling (MSEM) demonstrated that sitting in the front of the classroom (compared to the sitting in the back), taking notes, active listening, and working on problems during class had a positive effect on within-student variation in student engagement and attention. Engagement, in turn, predicted perceived learning. With respect to between-student effects, the tendency to sit in front seats had a significant effect on student engagement, which in turn had a significant effect on perceived learning and course grades. A significant indirect relationship of seating and active learning strategies on learning and course grade as mediated by student engagement was found. Support for the general aspect of student classroom experience was interpreted with flow theory and suggested the need for additional research. Findings also suggested that active learning strategies are associated with positive learning outcomes even in educational environments where possibilities for action are relatively constrained. PMID:28663733

Student Engagement as a General Factor of Classroom Experience: Associations with Student Practices and Educational Outcomes in a University Gateway Course.

PubMed

Shernof, David J; Ruzek, Erik A; Sannella, Alexander J; Schorr, Roberta Y; Sanchez-Wall, Lina; Bressler, Denise M

2017-01-01

The purpose of this study was to evaluate a model for considering general and specific elements of student experience in a gateway course in undergraduate Financial Accounting in a large university on the East Coast, USA. Specifically, the study evaluated a bifactor analytic strategy including a general factor of student classroom experience, conceptualized as student engagement as rooted in flow theory, as well as factors representing specific dimensions of experience. The study further evaluated the association between these general and specific factors and both student classroom practices and educational outcomes. The sample of students ( N = 407) in two cohorts of the undergraduate financial accounting course participated in the Experience Sampling Method (ESM) measuring students' classroom practices, perceptions, engagement, and perceived learning throughout the one-semester course. Course grade information was also collected. Results showed that a two-level bifactor model fit the data better than two traditional (i.e., non-bifactor) models and also avoided significant multicollinearity of the traditional models. In addition to student engagement (general factor), specific dimensions of classroom experience in the bifactor model at the within-student level included intrinsic motivation, academic intensity, salience, and classroom self-esteem. At the between-student level, specific aspects included work orientation, learning orientation, classroom self-esteem, and disengagement. Multilevel Structural Equation Modeling (MSEM) demonstrated that sitting in the front of the classroom (compared to the sitting in the back), taking notes, active listening, and working on problems during class had a positive effect on within-student variation in student engagement and attention. Engagement, in turn, predicted perceived learning. With respect to between-student effects, the tendency to sit in front seats had a significant effect on student engagement, which in turn had a significant effect on perceived learning and course grades. A significant indirect relationship of seating and active learning strategies on learning and course grade as mediated by student engagement was found. Support for the general aspect of student classroom experience was interpreted with flow theory and suggested the need for additional research. Findings also suggested that active learning strategies are associated with positive learning outcomes even in educational environments where possibilities for action are relatively constrained.

Linkage of a Physically Based Distributed Watershed Model and a Dynamic Plant Growth Model

DTIC Science & Technology

2006-12-01

i.e., Universal Soil Loss Equation ( USLE ) factors, K, C, and P). The K, C, and P factors are empiri- cal coefficients with the same conceptual...with general ecosystem models designed to make long-term projections of ecosystem dynamics. This development effort investigated the linkage of soil ...20 EDYS soil module

Study on characteristics of the aperture-averaging factor of atmospheric scintillation in terrestrial optical wireless communication

NASA Astrophysics Data System (ADS)

Shen, Hong; Liu, Wen-xing; Zhou, Xue-yun; Zhou, Li-ling; Yu, Long-Kun

2018-02-01

In order to thoroughly understand the characteristics of the aperture-averaging effect of atmospheric scintillation in terrestrial optical wireless communication and provide references for engineering design and performance evaluation of the optics system employed in the atmosphere, we have theoretically deduced the generally analytic expression of the aperture-averaging factor of atmospheric scintillation, and numerically investigated characteristics of the apertureaveraging factor under different propagation conditions. The limitations of the current commonly used approximate calculation formula of aperture-averaging factor have been discussed, and the results showed that the current calculation formula is not applicable for the small receiving aperture under non-uniform turbulence link. Numerical calculation has showed that aperture-averaging factor of atmospheric scintillation presented an exponential decline model for the small receiving aperture under non-uniform turbulent link, and the general expression of the model was given. This model has certain guiding significance for evaluating the aperture-averaging effect in the terrestrial optical wireless communication.

Using avian radar to examine relationships among avian activity, bird strikes, and meteorological factors

USGS Publications Warehouse

Coates, Peter S.; Casazza, Michael L.; Halstead, Brian J.; Fleskes, Joseph P.; Laughlin, James A.

2011-01-01

Radar systems designed to detect avian activity at airfields are useful in understanding factors that influence the risk of bird and aircraft collisions (bird strikes). We used an avian radar system to measure avian activity at Beale Air Force Base, California, USA, during 2008 and 2009. We conducted a 2-part analysis to examine relationships among avian activity, bird strikes, and meteorological and time-dependent factors. We found that avian activity around the airfield was greater at times when bird strikes occurred than on average using a permutation resampling technique. Second, we developed generalized linear mixed models of an avian activity index (AAI). Variation in AAI was first explained by seasons that were based on average migration dates of birds at the study area. We then modeled AAI by those seasons to further explain variation by meteorological factors and daily light levels within a 24-hour period. In general, avian activity increased with decreased temperature, wind, visibility, precipitation, and increased humidity and cloud cover. These effects differed by season. For example, during the spring bird migration period, most avian activity occurred before sunrise at twilight hours on clear days with low winds, whereas during fall migration, substantial activity occurred after sunrise, and birds generally were more active at lower temperatures. We report parameter estimates (i.e., constants and coefficients) averaged across models and a relatively simple calculation for safety officers and wildlife managers to predict AAI and the relative risk of bird strike based on time, date, and meteorological values. We validated model predictability and assessed model fit. These analyses will be useful for general inference of avian activity and risk assessment efforts. Further investigation and ongoing data collection will refine these inference models and improve our understanding of factors that influence avian activity, which is necessary to inform management decisions aimed at reducing risk of bird strikes.

On the factor structure of the Rosenberg (1965) General Self-Esteem Scale.

PubMed

Alessandri, Guido; Vecchione, Michele; Eisenberg, Nancy; Łaguna, Mariola

2015-06-01

Since its introduction, the Rosenberg General Self-Esteem Scale (RGSE, Rosenberg, 1965) has been 1 of the most widely used measures of global self-esteem. We conducted 4 studies to investigate (a) the goodness-of-fit of a bifactor model positing a general self-esteem (GSE) factor and 2 specific factors grouping positive (MFP) and negative items (MFN) and (b) different kinds of validity of the GSE, MFN, and MFP factors of the RSGE. In the first study (n = 11,028), the fit of the bifactor model was compared with those of 9 alternative models proposed in literature for the RGSE. In Study 2 (n = 357), the external validities of GSE, MFP, and MFN were evaluated using objective grade point average data and multimethod measures of prosociality, aggression, and depression. In Study 3 (n = 565), the across-rater robustness of the bifactor model was evaluated. In Study 4, measurement invariance of the RGSE was further supported across samples in 3 European countries, Serbia (n = 1,010), Poland (n = 699), and Italy (n = 707), and in the United States (n = 1,192). All in all, psychometric findings corroborate the value and the robustness of the bifactor structure and its substantive interpretation. (c) 2015 APA, all rights reserved).

A generalized linear factor model approach to the hierarchical framework for responses and response times.

PubMed

Molenaar, Dylan; Tuerlinckx, Francis; van der Maas, Han L J

2015-05-01

We show how the hierarchical model for responses and response times as developed by van der Linden (2007), Fox, Klein Entink, and van der Linden (2007), Klein Entink, Fox, and van der Linden (2009), and Glas and van der Linden (2010) can be simplified to a generalized linear factor model with only the mild restriction that there is no hierarchical model at the item side. This result is valuable as it enables all well-developed modelling tools and extensions that come with these methods. We show that the restriction we impose on the hierarchical model does not influence parameter recovery under realistic circumstances. In addition, we present two illustrative real data analyses to demonstrate the practical benefits of our approach. © 2014 The British Psychological Society.

Theory of ground state factorization in quantum cooperative systems.

PubMed

Giampaolo, Salvatore M; Adesso, Gerardo; Illuminati, Fabrizio

2008-05-16

We introduce a general analytic approach to the study of factorization points and factorized ground states in quantum cooperative systems. The method allows us to determine rigorously the existence, location, and exact form of separable ground states in a large variety of, generally nonexactly solvable, spin models belonging to different universality classes. The theory applies to translationally invariant systems, irrespective of spatial dimensionality, and for spin-spin interactions of arbitrary range.

Predicting homophobic behavior among heterosexual youth: domain general and sexual orientation-specific factors at the individual and contextual level.

PubMed

Poteat, V Paul; DiGiovanni, Craig D; Scheer, Jillian R

2013-03-01

As a form of bias-based harassment, homophobic behavior remains prominent in schools. Yet, little attention has been given to factors that underlie it, aside from bullying and sexual prejudice. Thus, we examined multiple domain general (empathy, perspective-taking, classroom respect norms) and sexual orientation-specific factors (sexual orientation identity importance, number of sexual minority friends, parents' sexual minority attitudes, media messages). We documented support for a model in which these sets of factors converged to predict homophobic behavior, mediated through bullying and prejudice, among 581 students in grades 9-12 (55 % female). The structural equation model indicated that, with the exception of media messages, these additional factors predicted levels of prejudice and bullying, which in turn predicted the likelihood of students to engage in homophobic behavior. These findings highlight the importance of addressing multiple interrelated factors in efforts to reduce bullying, prejudice, and discrimination among youth.

FACTOR ANALYTIC MODELS OF CLUSTERED MULTIVARIATE DATA WITH INFORMATIVE CENSORING

EPA Science Inventory

This paper describes a general class of factor analytic models for the analysis of clustered multivariate data in the presence of informative missingness. We assume that there are distinct sets of cluster-level latent variables related to the primary outcomes and to the censorin...

General and Culturally Specific Factors Influencing Black and White Rape Survivors' Self-Esteem

ERIC Educational Resources Information Center

Neville, Helen A.; Heppner, Mary J.; Oh, Euna; Spanierman, Lisa B.; Clark, Mary

2004-01-01

Grounded in a culturally inclusive ecological model of sexual assault recovery framework, the influence of personal (e.g., prior victimization), rape context (e.g., degree of injury during last assault), and postrape response factors (e.g., general and cultural attributions, rape related coping) on self-esteem of Black and White college women, who…

Exploratory structural equation modeling of personality data.

PubMed

Booth, Tom; Hughes, David J

2014-06-01

The current article compares the use of exploratory structural equation modeling (ESEM) as an alternative to confirmatory factor analytic (CFA) models in personality research. We compare model fit, factor distinctiveness, and criterion associations of factors derived from ESEM and CFA models. In Sample 1 (n = 336) participants completed the NEO-FFI, the Trait Emotional Intelligence Questionnaire-Short Form, and the Creative Domains Questionnaire. In Sample 2 (n = 425) participants completed the Big Five Inventory and the depression and anxiety scales of the General Health Questionnaire. ESEM models provided better fit than CFA models, but ESEM solutions did not uniformly meet cutoff criteria for model fit. Factor scores derived from ESEM and CFA models correlated highly (.91 to .99), suggesting the additional factor loadings within the ESEM model add little in defining latent factor content. Lastly, criterion associations of each personality factor in CFA and ESEM models were near identical in both inventories. We provide an example of how ESEM and CFA might be used together in improving personality assessment. © The Author(s) 2014.

Sex similarities and differences in risk factors for recurrence of major depression.

PubMed

van Loo, Hanna M; Aggen, Steven H; Gardner, Charles O; Kendler, Kenneth S

2017-11-27

Major depression (MD) occurs about twice as often in women as in men, but it is unclear whether sex differences subsist after disease onset. This study aims to elucidate potential sex differences in rates and risk factors for MD recurrence, in order to improve prediction of course of illness and understanding of its underlying mechanisms. We used prospective data from a general population sample (n = 653) that experienced a recent episode of MD. A diverse set of potential risk factors for recurrence of MD was analyzed using Cox models subject to elastic net regularization for males and females separately. Accuracy of the prediction models was tested in same-sex and opposite-sex test data. Additionally, interactions between sex and each of the risk factors were investigated to identify potential sex differences. Recurrence rates and the impact of most risk factors were similar for men and women. For both sexes, prediction models were highly multifactorial including risk factors such as comorbid anxiety, early traumas, and family history. Some subtle sex differences were detected: for men, prediction models included more risk factors concerning characteristics of the depressive episode and family history of MD and generalized anxiety, whereas for women, models included more risk factors concerning early and recent adverse life events and socioeconomic problems. No prominent sex differences in risk factors for recurrence of MD were found, potentially indicating similar disease maintaining mechanisms for both sexes. Course of MD is a multifactorial phenomenon for both males and females.

The structure of psychopathology in adolescence and its common personality and cognitive correlates.

PubMed

Castellanos-Ryan, Natalie; Brière, Frederic N; O'Leary-Barrett, Maeve; Banaschewski, Tobias; Bokde, Arun; Bromberg, Uli; Büchel, Christian; Flor, Herta; Frouin, Vincent; Gallinat, Juergen; Garavan, Hugh; Martinot, Jean-Luc; Nees, Frauke; Paus, Tomas; Pausova, Zdenka; Rietschel, Marcella; Smolka, Michael N; Robbins, Trevor W; Whelan, Robert; Schumann, Gunter; Conrod, Patricia

2016-11-01

The traditional view that mental disorders are distinct, categorical disorders has been challenged by evidence that disorders are highly comorbid and exist on a continuum (e.g., Caspi et al., 2014; Tackett et al., 2013). The first objective of this study was to use structural equation modeling to model the structure of psychopathology in an adolescent community-based sample (N = 2,144) including conduct disorder, attention-deficit/hyperactivity disorder (ADHD), oppositional-defiant disorder (ODD), obsessive-compulsive disorder, eating disorders, substance use, anxiety, depression, phobias, and other emotional symptoms, assessed at 16 years. The second objective was to identify common personality and cognitive correlates of psychopathology, assessed at 14 years. Results showed that psychopathology at 16 years fit 2 bifactor models equally well: (a) a bifactor model, reflecting a general psychopathology factor, as well as specific externalizing (representing mainly substance misuse and low ADHD) and internalizing factors; and (b) a bifactor model with a general psychopathology factor and 3 specific externalizing (representing mainly ADHD and ODD), substance use and internalizing factors. The general psychopathology factor was related to high disinhibition/impulsivity, low agreeableness, high neuroticism and hopelessness, high delay-discounting, poor response inhibition and low performance IQ. Substance use was specifically related to high novelty-seeking, sensation-seeking, extraversion, high verbal IQ, and risk-taking. Internalizing psychopathology was specifically related to high neuroticism, hopelessness and anxiety-sensitivity, low novelty-seeking and extraversion, and an attentional bias toward negatively valenced verbal stimuli. Findings reveal several nonspecific or transdiagnostic personality and cognitive factors that may be targeted in new interventions to potentially prevent the development of multiple psychopathologies. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The Structure of Psychopathology in Adolescence and Its Common Personality and Cognitive Correlates

PubMed Central

2016-01-01

The traditional view that mental disorders are distinct, categorical disorders has been challenged by evidence that disorders are highly comorbid and exist on a continuum (e.g., Caspi et al., 2014; Tackett et al., 2013). The first objective of this study was to use structural equation modeling to model the structure of psychopathology in an adolescent community-based sample (N = 2,144) including conduct disorder, attention-deficit/hyperactivity disorder (ADHD), oppositional-defiant disorder (ODD), obsessive–compulsive disorder, eating disorders, substance use, anxiety, depression, phobias, and other emotional symptoms, assessed at 16 years. The second objective was to identify common personality and cognitive correlates of psychopathology, assessed at 14 years. Results showed that psychopathology at 16 years fit 2 bifactor models equally well: (a) a bifactor model, reflecting a general psychopathology factor, as well as specific externalizing (representing mainly substance misuse and low ADHD) and internalizing factors; and (b) a bifactor model with a general psychopathology factor and 3 specific externalizing (representing mainly ADHD and ODD), substance use and internalizing factors. The general psychopathology factor was related to high disinhibition/impulsivity, low agreeableness, high neuroticism and hopelessness, high delay-discounting, poor response inhibition and low performance IQ. Substance use was specifically related to high novelty-seeking, sensation-seeking, extraversion, high verbal IQ, and risk-taking. Internalizing psychopathology was specifically related to high neuroticism, hopelessness and anxiety-sensitivity, low novelty-seeking and extraversion, and an attentional bias toward negatively valenced verbal stimuli. Findings reveal several nonspecific or transdiagnostic personality and cognitive factors that may be targeted in new interventions to potentially prevent the development of multiple psychopathologies. PMID:27819466

Science anxiety and social cognitive factors predicting STEM career aspirations of high school freshmen in general science class

NASA Astrophysics Data System (ADS)

Skells, Kristin Marie

Extant data was used to consider the association between science anxiety, social cognitive factors and STEM career aspirations of high school freshmen in general science classes. An adapted model based on social cognitive career theory (SCCT) was used to consider these relationships, with science anxiety functioning as a barrier in the model. The study assessed the following research questions: (1) Do social cognitive variables relate in the expected way to STEM career aspirations based on SCCT for ninth graders taking general science classes? (2) Is there an association between science anxiety and outcomes and processes identified in the SCCT model for ninth graders taking general science classes? (3) Does gender moderate these relationships? Results indicated that support was found for many of the central tenants of the SCCT model. Science anxiety was associated with prior achievement, self-efficacy, and science interest, although it did not relate directly to STEM career goals. Gender was found to moderate only the relationship between prior achievement and science self-efficacy.

Effect of Retention in Elementary Grades on Grade 9 Motivation for Educational Attainment

PubMed Central

Cham, Heining; Hughes, Jan N.; West, Stephen G.; Im, Myung Hee

2014-01-01

This study investigated the effect of grade retention in elementary school on students’ motivation for educational attainment in grade 9. We equated retained and promoted students on 67 covariates assessed in grade 1 through propensity score weighting. Retained students (31.55%, nretained = 177) and continuously promoted students (68.45%, npromoted = 384) were compared on the bifactor model of motivation for educational attainment (Cham, Hughes, West, & Im, 2014). This model consists of a General factor (student’s overall motivation for educational attainment), and three specific factors: student perceived Teacher Educational Expectations, Peer Educational Aspirations, and Value of Education. Measurement invariance between retained and promoted groups was established. Retained students scored significantly higher than promoted students on each specific factor but not on the General factor. Results showed that the retained and promoted students did not significantly differ on the General factor. The retained students had significantly higher scores on each specific factor than the promoted students. The results suggested that grade retention may not have the negative effects so widely assumed in the published literature; it is an expensive intervention with minimal evidence of benefits to the retained student. PMID:25636258

Itinerant deaf educator and general educator perceptions of the D/HH push-in model.

PubMed

Rabinsky, Rebecca J

2013-01-01

A qualitative case study using the deaf and hard of hearing (D/HH) push-in model was conducted on the perceptions of 3 itinerant deaf educators and 3 general educators working in 1 school district. Participants worked in pairs of 1 deaf educator and 1 general educator at 3 elementary schools. Open-ended research questions guided the study, which was concerned with teachers' perceptions of the model in general and with the model's advantages, disadvantages, and effectiveness. Data collected from observations, one-to-one interviews, and a focus group interview enabled the investigator to uncover 4 themes: Participants (a) had an overall positive experience, (b) viewed general education immersion as an advantage, (c) considered high noise levels a disadvantage, and (d) believed the effectiveness of the push-in model was dependent on several factors, in particular, the needs of the student and the nature of the general education classroom environment.

Integrating social capital theory, social cognitive theory, and the technology acceptance model to explore a behavioral model of telehealth systems.

PubMed

Tsai, Chung-Hung

2014-05-07

Telehealth has become an increasingly applied solution to delivering health care to rural and underserved areas by remote health care professionals. This study integrated social capital theory, social cognitive theory, and the technology acceptance model (TAM) to develop a comprehensive behavioral model for analyzing the relationships among social capital factors (social capital theory), technological factors (TAM), and system self-efficacy (social cognitive theory) in telehealth. The proposed framework was validated with 365 respondents from Nantou County, located in Central Taiwan. Structural equation modeling (SEM) was used to assess the causal relationships that were hypothesized in the proposed model. The finding indicates that elderly residents generally reported positive perceptions toward the telehealth system. Generally, the findings show that social capital factors (social trust, institutional trust, and social participation) significantly positively affect the technological factors (perceived ease of use and perceived usefulness respectively), which influenced usage intention. This study also confirmed that system self-efficacy was the salient antecedent of perceived ease of use. In addition, regarding the samples, the proposed model fitted considerably well. The proposed integrative psychosocial-technological model may serve as a theoretical basis for future research and can also offer empirical foresight to practitioners and researchers in the health departments of governments, hospitals, and rural communities.

Integrating Social Capital Theory, Social Cognitive Theory, and the Technology Acceptance Model to Explore a Behavioral Model of Telehealth Systems

PubMed Central

Tsai, Chung-Hung

2014-01-01

Telehealth has become an increasingly applied solution to delivering health care to rural and underserved areas by remote health care professionals. This study integrated social capital theory, social cognitive theory, and the technology acceptance model (TAM) to develop a comprehensive behavioral model for analyzing the relationships among social capital factors (social capital theory), technological factors (TAM), and system self-efficacy (social cognitive theory) in telehealth. The proposed framework was validated with 365 respondents from Nantou County, located in Central Taiwan. Structural equation modeling (SEM) was used to assess the causal relationships that were hypothesized in the proposed model. The finding indicates that elderly residents generally reported positive perceptions toward the telehealth system. Generally, the findings show that social capital factors (social trust, institutional trust, and social participation) significantly positively affect the technological factors (perceived ease of use and perceived usefulness respectively), which influenced usage intention. This study also confirmed that system self-efficacy was the salient antecedent of perceived ease of use. In addition, regarding the samples, the proposed model fitted considerably well. The proposed integrative psychosocial-technological model may serve as a theoretical basis for future research and can also offer empirical foresight to practitioners and researchers in the health departments of governments, hospitals, and rural communities. PMID:24810577

Perceived experiences of atheist discrimination: Instrument development and evaluation.

PubMed

Brewster, Melanie E; Hammer, Joseph; Sawyer, Jacob S; Eklund, Austin; Palamar, Joseph

2016-10-01

The present 2 studies describe the development and initial psychometric evaluation of a new instrument, the Measure of Atheist Discrimination Experiences (MADE), which may be used to examine the minority stress experiences of atheist people. Items were created from prior literature, revised by a panel of expert researchers, and assessed psychometrically. In Study 1 (N = 1,341 atheist-identified people), an exploratory factor analysis with 665 participants suggested the presence of 5 related dimensions of perceived discrimination. However, bifactor modeling via confirmatory factor analysis and model-based reliability estimates with data from the remaining 676 participants affirmed the presence of a strong "general" factor of discrimination and mixed to poor support for substantive subdimensions. In Study 2 (N = 1,057 atheist-identified people), another confirmatory factor analysis and model-based reliability estimates strongly supported the bifactor model from Study 1 (i.e., 1 strong "general" discrimination factor) and poor support for subdimensions. Across both studies, the MADE general factor score demonstrated evidence of good reliability (i.e., Cronbach's alphas of .94 and .95; omega hierarchical coefficients of .90 and .92), convergent validity (i.e., with stigma consciousness, β = .56; with awareness of public devaluation, β = .37), and preliminary evidence for concurrent validity (i.e., with loneliness β = .18; with psychological distress β = .27). Reliability and validity evidence for the MADE subscale scores was not sufficient to warrant future use of the subscales. Limitations and implications for future research and clinical work with atheist individuals are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Identification and treatment of risk factors for coronary heart disease in general practice: a possible screening model

PubMed Central

Jones, Alan; Davies, D H; Dove, J R; Collinson, M A; Brown, Pamela M R

1988-01-01

A screening programme for the identification of risk factors for coronary heart disease in all patients aged 25-55 years in a general practice population was studied. The identification of risk factors included measurement of obesity, blood pressure, hypercholesterolaemia, and urinalysis, together with questions about family history, cigarette smoking, alcohol intake, and lifestyle. The patients with identified risk factors were invited to attend a lifestyle intervention clinic organised by the practice nurses and run by the health visitors, with the help of the local authority dietitian. Of 2646 (62%) patients who attended for screening, 78 (64%) of the 121 shown to have a high cholesterol concentration experienced a drop in cholesterol concentration. The mean fall in cholesterol concentration in the 78 patients who showed a positive response to intervention was 1·1 mmol/l. The study was intended as a possible flexible model for screening for coronary heart disease in general practice that could be complemented rather than replaced by opportunistic screening. The issues of organisation, cost, manpower, non-attendance, and effectiveness in a busy general practice environment are discussed. PMID:3135890

Construct validity evidence for the Male Role Norms Inventory-Short Form: A structural equation modeling approach using the bifactor model.

PubMed

Levant, Ronald F; Hall, Rosalie J; Weigold, Ingrid K; McCurdy, Eric R

2016-10-01

The construct validity of the Male Role Norms Inventory-Short Form (MRNI-SF) was assessed using a latent variable approach implemented with structural equation modeling (SEM). The MRNI-SF was specified as having a bifactor structure, and validation scales were also specified as latent variables. The latent variable approach had the advantages of separating effects of general and specific factors and controlling for some sources of measurement error. Data (N = 484) were from a diverse sample (38.8% men of color, 22.3% men of diverse sexualities) of community-dwelling and college men who responded to an online survey. The construct validity of the MRNI-SF General Traditional Masculinity Ideology factor was supported for all 4 of the proposed latent correlations with: (a) Male Role Attitudes Scale; (b) general factor of Conformity to Masculine Norms Inventory-46; (c) higher-order factor of Gender Role Conflict Scale; and (d) Personal Attributes Questionnaire-Masculinity Scale. Significant correlations with relevant other latent factors provided concurrent validity evidence for the MRNI-SF specific factors of Negativity toward Sexual Minorities, Importance of Sex, Restrictive Emotionality, and Toughness, with all 8 of the hypothesized relationships supported. However, 3 relationships concerning Dominance were not supported. (The construct validity of the remaining 2 MRNI-SF specific factors-Avoidance of Femininity and Self-Reliance through Mechanical Skills was not assessed.) Comparisons were made, and meaningful differences noted, between the latent correlations emphasized in this study and their raw variable counterparts. Results are discussed in terms of the advantages of an SEM approach and the unique characteristics of the bifactor model. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Extracurricular activity participation moderates impact of family and school factors on adolescents' disruptive behavioural problems.

PubMed

Driessens, Corine M E F

2015-11-11

The prevalence of problem behaviours among British adolescents has increased in the past decades. Following Erikson's psychosocial developmental theory and Bronfenbrenner's developmental ecological model, it was hypothesized that youth problem behaviour is shaped in part by social environment. The aim of this project was to explore potential protective factors within the social environment of British youth's for the presentation of disruptive behavioural problems. This study used secondary data from the Longitudinal Study of Young People in England, a cohort study of secondary school students. These data were analysed with generalized estimation equations to take the correlation between the longitudinal observations into account. Three models were built. The first model determined the effect of family, school, and extracurricular setting on presentation of disruptive behavioural problems. The second model expanded the first model by assuming extracurricular activities as protective factors that moderated the interaction between family and school factors with disruptive behavioural problems. The third model described the effect of prior disruptive behaviour on current disruptive behaviour. Associations were found between school factors, family factors, involvement in extracurricular activities and presence of disruptive behavioural problems. Results from the second generalized estimating equation (GEE) logistic regression models indicated that extracurricular activities buffered the impact of school and family factors on the presence of disruptive behavioural problems. For instance, participation in sports activities decreased the effect of bullying on psychological distress. Results from the third model indicated that prior acts of disruptive behaviour reinforced current disruptive behaviour. This study supports Erikson's psychosocial developmental theory and Bronfenbrenner's developmental ecological model; social environment did influence the presence of disruptive behavioural problems for British adolescents. The potential of extracurricular activities to intervention strategies addressing disruptive behavioural problems of adolescents is discussed.

Perceived threat and corroboration: key factors that improve a predictive model of trust in internet-based health information and advice.

PubMed

Harris, Peter R; Sillence, Elizabeth; Briggs, Pam

2011-07-27

How do people decide which sites to use when seeking health advice online? We can assume, from related work in e-commerce, that general design factors known to affect trust in the site are important, but in this paper we also address the impact of factors specific to the health domain. The current study aimed to (1) assess the factorial structure of a general measure of Web trust, (2) model how the resultant factors predicted trust in, and readiness to act on, the advice found on health-related websites, and (3) test whether adding variables from social cognition models to capture elements of the response to threatening, online health-risk information enhanced the prediction of these outcomes. Participants were asked to recall a site they had used to search for health-related information and to think of that site when answering an online questionnaire. The questionnaire consisted of a general Web trust questionnaire plus items assessing appraisals of the site, including threat appraisals, information checking, and corroboration. It was promoted on the hungersite.com website. The URL was distributed via Yahoo and local print media. We assessed the factorial structure of the measures using principal components analysis and modeled how well they predicted the outcome measures using structural equation modeling (SEM) with EQS software. We report an analysis of the responses of participants who searched for health advice for themselves (N = 561). Analysis of the general Web trust questionnaire revealed 4 factors: information quality, personalization, impartiality, and credible design. In the final SEM model, information quality and impartiality were direct predictors of trust. However, variables specific to eHealth (perceived threat, coping, and corroboration) added substantially to the ability of the model to predict variance in trust and readiness to act on advice on the site. The final model achieved a satisfactory fit: χ(2) (5) = 10.8 (P = .21), comparative fit index = .99, root mean square error of approximation = .052. The model accounted for 66% of the variance in trust and 49% of the variance in readiness to act on the advice. Adding variables specific to eHealth enhanced the ability of a model of trust to predict trust and readiness to act on advice.

Perceived Threat and Corroboration: Key Factors That Improve a Predictive Model of Trust in Internet-based Health Information and Advice

PubMed Central

Harris, Peter R; Briggs, Pam

2011-01-01

Background How do people decide which sites to use when seeking health advice online? We can assume, from related work in e-commerce, that general design factors known to affect trust in the site are important, but in this paper we also address the impact of factors specific to the health domain. Objective The current study aimed to (1) assess the factorial structure of a general measure of Web trust, (2) model how the resultant factors predicted trust in, and readiness to act on, the advice found on health-related websites, and (3) test whether adding variables from social cognition models to capture elements of the response to threatening, online health-risk information enhanced the prediction of these outcomes. Methods Participants were asked to recall a site they had used to search for health-related information and to think of that site when answering an online questionnaire. The questionnaire consisted of a general Web trust questionnaire plus items assessing appraisals of the site, including threat appraisals, information checking, and corroboration. It was promoted on the hungersite.com website. The URL was distributed via Yahoo and local print media. We assessed the factorial structure of the measures using principal components analysis and modeled how well they predicted the outcome measures using structural equation modeling (SEM) with EQS software. Results We report an analysis of the responses of participants who searched for health advice for themselves (N = 561). Analysis of the general Web trust questionnaire revealed 4 factors: information quality, personalization, impartiality, and credible design. In the final SEM model, information quality and impartiality were direct predictors of trust. However, variables specific to eHealth (perceived threat, coping, and corroboration) added substantially to the ability of the model to predict variance in trust and readiness to act on advice on the site. The final model achieved a satisfactory fit: χ2 5 = 10.8 (P = .21), comparative fit index = .99, root mean square error of approximation = .052. The model accounted for 66% of the variance in trust and 49% of the variance in readiness to act on the advice. Conclusions Adding variables specific to eHealth enhanced the ability of a model of trust to predict trust and readiness to act on advice. PMID:21795237

Does Sluggish Cognitive Tempo Fit within a Bi-factor Model of Attention-Deficit/Hyperactivity Disorder?

PubMed Central

Garner, Annie A.; Peugh, James; Becker, Stephen P.; Kingery, Kathleen M.; Tamm, Leanne; Vaughn, Aaron J.; Ciesielski, Heather; Simon, John O.; Loren, Richard E. A.; Epstein, Jeffery N.

2014-01-01

Objective Studies demonstrate sluggish cognitive tempo (SCT) symptoms to be distinct from inattentive and hyperactive-impulsive dimensions of Attention-Deficit/Hyperactivity Disorder (ADHD). No study has examined SCT within a bi-factor model of ADHD whereby SCT may form a specific factor distinct from inattention and hyperactivity/impulsivity while still fitting within a general ADHD factor, which was the purpose of the current study. Method 168 children were recruited from an ADHD clinic. Most (92%) met diagnostic criteria for ADHD. Parents and teachers completed measures of ADHD and SCT. Results Although SCT symptoms were strongly associated with inattention they loaded onto a factor independent of ADHD ‘g’. Results were consistent across parent and teacher ratings. Conclusions SCT is structurally distinct from inattention as well as from the general ADHD latent symptom structure. Findings support a growing body of research suggesting SCT to be distinct and separate from ADHD. PMID:25005039

Empirical Investigation of a Model of Sexual Minority Specific and General Risk Factors for Intimate Partner Violence among Lesbian Women.

PubMed

Lewis, Robin J; Mason, Tyler B; Winstead, Barbara A; Kelley, Michelle L

2017-01-01

This study proposed and tested the first conceptual model of sexual minority specific (discrimination, internalized homophobia) and more general risk factors (perpetrator and partner alcohol use, anger, relationship satisfaction) for intimate partner violence among partnered lesbian women. Self-identified lesbian women ( N =1048) were recruited from online market research panels. Participants completed an online survey that included measures of minority stress, anger, alcohol use and alcohol-related problems, relationship satisfaction, psychological aggression, and physical violence. The model demonstrated good fit and significant links from sexual minority discrimination to internalized homophobia and anger, from internalized homophobia to anger and alcohol problems, and from alcohol problems to intimate partner violence. Partner alcohol use predicted partner physical violence. Relationship dissatisfaction was associated with physical violence via psychological aggression. Physical violence was bidirectional. Minority stress, anger, alcohol use and alcohol-related problems play an important role in perpetration of psychological aggression and physical violence in lesbian women's intimate partner relationships. The results of this study provide evidence of potentially modifiable sexual minority specific and more general risk factors for lesbian women's partner violence.

Conceptualizations of Personality Disorders with the Five Factor Model-Count and Empathy Traits

ERIC Educational Resources Information Center

Kajonius, Petri J.; Dåderman, Anna M.

2017-01-01

Previous research has long advocated that emotional and behavioral disorders are related to general personality traits, such as the Five Factor Model (FFM). The addition of section III in the latest "Diagnostic and Statistical Manual of Mental Disorders" (DSM) recommends that extremity in personality traits together with maladaptive…

The assessment of mindfulness skills: the "what" and the "how".

PubMed

Iani, Luca; Lauriola, Marco; Cafaro, Valentina

2017-10-06

The five facets mindfulness questionnaire-short form (FFMQ-SF) is a new, brief measure for the assessment of mindfulness skills in clinical and nonclinical samples. The construct validity of the FFMQ-SF has not been previously assessed in community samples. The present study investigated the factor structure of the Italian version of the FFMQ-SF. Structured equation modeling was used to test the fit of three alternative models in a sample of highly educated adults (n = 211). A hierarchical model with a single second-order factor loaded by observing, describing, and acting with awareness (i.e. the mindfulness "what" skills) performed slightly better than both a five-factor model with correlated factors and a hierarchical model with a general second-order factor. The FFMQ-SF scores were significantly higher than those reported in both Dutch depressed patients and Australian undergraduate students for all facets (but nonreactivity for the Australian sample). Data support the multifaceted nature of mindfulness skills. Because of its brevity and simplicity of use, the FFMQ-SF is a promising questionnaire in longitudinal and clinical research. This questionnaire can serve as a guideline to help clinicians assess and monitor mindfulness skills acquisition, strengthening, and generalization, and prioritize mindfulness skills that need immediate attention.

A note on local BRST cohomology of Yang-Mills type theories with free Abelian factors

NASA Astrophysics Data System (ADS)

Barnich, Glenn; Boulanger, Nicolas

2018-05-01

We extend previous work on antifield dependent local Becchi-Rouet-Stora-Tyutin (BRST) cohomology for matter coupled gauge theories of Yang-Mills type to the case of gauge groups that involve free Abelian factors. More precisely, we first investigate in a model independent way how the dynamics enters the computation of the cohomology for a general class of Lagrangians in general spacetime dimensions. We then discuss explicit solutions in the case of specific models. Our analysis has implications for the structure of characteristic cohomology and for consistent deformations of the classical models, as well as for divergences/counterterms and for gauge anomalies that may appear during perturbative quantization.

Attention-deficit/hyperactivity disorder dimensionality: the reliable 'g' and the elusive 's' dimensions.

PubMed

Wagner, Flávia; Martel, Michelle M; Cogo-Moreira, Hugo; Maia, Carlos Renato Moreira; Pan, Pedro Mario; Rohde, Luis Augusto; Salum, Giovanni Abrahão

2016-01-01

The best structural model for attention-deficit/hyperactivity disorder (ADHD) symptoms remains a matter of debate. The objective of this study is to test the fit and factor reliability of competing models of the dimensional structure of ADHD symptoms in a sample of randomly selected and high-risk children and pre-adolescents from Brazil. Our sample comprised 2512 children aged 6-12 years from 57 schools in Brazil. The ADHD symptoms were assessed using parent report on the development and well-being assessment (DAWBA). Fit indexes from confirmatory factor analysis were used to test unidimensional, correlated, and bifactor models of ADHD, the latter including "g" ADHD and "s" symptom domain factors. Reliability of all models was measured with omega coefficients. A bifactor model with one general factor and three specific factors (inattention, hyperactivity, impulsivity) exhibited the best fit to the data, according to fit indices, as well as the most consistent factor loadings. However, based on omega reliability statistics, the specific inattention, hyperactivity, and impulsivity dimensions provided very little reliable information after accounting for the reliable general ADHD factor. Our study presents some psychometric evidence that ADHD specific ("s") factors might be unreliable after taking common ("g" factor) variance into account. These results are in accordance with the lack of longitudinal stability among subtypes, the absence of dimension-specific molecular genetic findings and non-specific effects of treatment strategies. Therefore, researchers and clinicians might most effectively rely on the "g" ADHD to characterize ADHD dimensional phenotype, based on currently available symptom items.

Examining General and Specific Factors in the Dimensionality of Oral Language and Reading in 4th–10th Grades

PubMed Central

Foorman, Barbara R.; Koon, Sharon; Petscher, Yaacov; Mitchell, Alison; Truckenmiller, Adrea

2015-01-01

The objective of this study was to explore dimensions of oral language and reading and their influence on reading comprehension in a relatively understudied population—adolescent readers in 4th through 10th grades. The current study employed latent variable modeling of decoding fluency, vocabulary, syntax, and reading comprehension so as to represent these constructs with minimal error and to examine whether residual variance unaccounted for by oral language can be captured by specific factors of syntax and vocabulary. A 1-, 3-, 4-, and bifactor model were tested with 1,792 students in 18 schools in 2 large urban districts in the Southeast. Students were individually administered measures of expressive and receptive vocabulary, syntax, and decoding fluency in mid-year. At the end of the year students took the state reading test as well as a group-administered, norm-referenced test of reading comprehension. The bifactor model fit the data best in all 7 grades and explained 72% to 99% of the variance in reading comprehension. The specific factors of syntax and vocabulary explained significant unique variance in reading comprehension in 1 grade each. The decoding fluency factor was significantly correlated with the reading comprehension and oral language factors in all grades, but, in the presence of the oral language factor, was not significantly associated with the reading comprehension factor. Results support a bifactor model of lexical knowledge rather than the 3-factor model of the Simple View of Reading, with the vast amount of variance in reading comprehension explained by a general oral language factor. PMID:26346839

Applications of multivariate modeling to neuroimaging group analysis: A comprehensive alternative to univariate general linear model

PubMed Central

Chen, Gang; Adleman, Nancy E.; Saad, Ziad S.; Leibenluft, Ellen; Cox, RobertW.

2014-01-01

All neuroimaging packages can handle group analysis with t-tests or general linear modeling (GLM). However, they are quite hamstrung when there are multiple within-subject factors or when quantitative covariates are involved in the presence of a within-subject factor. In addition, sphericity is typically assumed for the variance–covariance structure when there are more than two levels in a within-subject factor. To overcome such limitations in the traditional AN(C)OVA and GLM, we adopt a multivariate modeling (MVM) approach to analyzing neuroimaging data at the group level with the following advantages: a) there is no limit on the number of factors as long as sample sizes are deemed appropriate; b) quantitative covariates can be analyzed together with within- subject factors; c) when a within-subject factor is involved, three testing methodologies are provided: traditional univariate testing (UVT)with sphericity assumption (UVT-UC) and with correction when the assumption is violated (UVT-SC), and within-subject multivariate testing (MVT-WS); d) to correct for sphericity violation at the voxel level, we propose a hybrid testing (HT) approach that achieves equal or higher power via combining traditional sphericity correction methods (Greenhouse–Geisser and Huynh–Feldt) with MVT-WS. PMID:24954281

The Relationship Between Life Satisfaction and ADHD Symptoms in Middle School Students: Using a Bifactor Model.

PubMed

Ogg, Julia A; Bateman, Lisa; Dedrick, Robert F; Suldo, Shannon M

2016-05-01

ADHD is associated with increased academic and social difficulties and comorbid psychopathology which may lead to decreased life satisfaction (LS). The current study utilized a bifactor model of ADHD consisting of a general factor and two specific factors (inattention and hyperactivity-impulsivity) to determine if ADHD symptoms place middle school students (n= 183) at risk for diminished LS and if this relationship differed depending on whether teachers versus students reported ADHD symptoms. Confirmatory factor analyses indicated that the bifactor model provided very good fit to the ADHD symptoms reported by students (comparative fit index [CFI] = .995; root mean square error of approximation [RMSEA] = .028) and teachers (CFI = .997; RMSEA = .043). Results also demonstrated that when students rated ADHD symptoms, the general ADHD factor and inattention were negatively related to LS; however, when teachers rated ADHD symptoms, only inattention was negatively related to LS. Implications and future directions related to these results are discussed. © The Author(s) 2014.

Maladaptive Personality Trait Models: Validating the Five-Factor Model Maladaptive Trait Measures With the Personality Inventory for DSM-5 and NEO Personality Inventory.

PubMed

Helle, Ashley C; Mullins-Sweatt, Stephanie N

2017-05-01

Eight measures have been developed to assess maladaptive variants of the five-factor model (FFM) facets specific to personality disorders (e.g., Five-Factor Borderline Inventory [FFBI]). These measures can be used in their entirety or as facet-based scales (e.g., FFBI Affective Dysregulation) to improve the comprehensiveness of assessment of pathological personality. There are a limited number of studies examining these scales with other measures of similar traits (e.g., DSM-5 alternative model). The current study examined the FFM maladaptive scales in relation to the respective general personality traits of the NEO Personality Inventory-Revised and the pathological personality traits of the DSM-5 alternative model using the Personality Inventory for DSM-5. The results indicated the FFM maladaptive trait scales predominantly converged with corresponding NEO Personality Inventory-Revised, and Personality Inventory for DSM-5 traits, providing further validity for these measures as extensions of general personality traits and evidence for their relation to the pathological trait model. Benefits and applications of the FFM maladaptive scales in clinical and research settings are discussed.

A Test of an Integrative Model Using Social Factors and Personality Traits: Prediction on the Delinquency of South Korean Youth.

PubMed

Yun, Minwoo; Kim, Eunyoung; Park, Woong-Sub

2017-08-01

To more fully comprehend juvenile delinquency, it is necessary to take an integrative approach, with consideration of both personality traits of social risk factors. Many scholars argue the necessity and strength of integrative approach on the ground that juvenile delinquency is an outcome of interplay of individual and social factors. The present study examines the general applicability of an integrative model of personal traits and social risk factors to youth delinquency in the South Korean context. The empirical results show that the delinquency predictors in the current South Korean sample are closely aligned to Loeber and Farrington's theoretical propositions and that found in Western nations. Perhaps this is because South Korea has undergone rapid Westernization for the last decades. Because the correlates in this sample and Western theoretical propositions and studies overlap, an integrative model of personality trait and social risk factors is indeed generally applicable to South Korea. This finding also depicts the extent of Westernization in the South Korean society at least among adolescents. Limitations of the present study and directions for the future study are discussed.

Optimizing Surgical Quality Datasets to Care for Older Adults: Lessons from the American College of Surgeons NSQIP Geriatric Surgery Pilot.

PubMed

Berian, Julia R; Zhou, Lynn; Hornor, Melissa A; Russell, Marcia M; Cohen, Mark E; Finlayson, Emily; Ko, Clifford Y; Robinson, Thomas N; Rosenthal, Ronnie A

2017-12-01

Surgical quality datasets can be better tailored toward older adults. The American College of Surgeons (ACS) NSQIP Geriatric Surgery Pilot collected risk factors and outcomes in 4 geriatric-specific domains: cognition, decision-making, function, and mobility. This study evaluated the contributions of geriatric-specific factors to risk adjustment in modeling 30-day outcomes and geriatric-specific outcomes (postoperative delirium, new mobility aid use, functional decline, and pressure ulcers). Using ACS NSQIP Geriatric Surgery Pilot data (January 2014 to December 2016), 7 geriatric-specific risk factors were evaluated for selection in 14 logistic models (morbidities/mortality) in general-vascular and orthopaedic surgery subgroups. Hierarchical models evaluated 4 geriatric-specific outcomes, adjusting for hospitals-level effects and including Bayesian-type shrinkage, to estimate hospital performance. There were 36,399 older adults who underwent operations at 31 hospitals in the ACS NSQIP Geriatric Surgery Pilot. Geriatric-specific risk factors were selected in 10 of 14 models in both general-vascular and orthopaedic surgery subgroups. After risk adjustment, surrogate consent (odds ratio [OR] 1.5; 95% CI 1.3 to 1.8) and use of a mobility aid (OR 1.3; 95% CI 1.1 to 1.4) increased the risk for serious morbidity or mortality in the general-vascular cohort. Geriatric-specific factors were selected in all 4 geriatric-specific outcomes models. Rates of geriatric-specific outcomes were: postoperative delirium in 12.1% (n = 3,650), functional decline in 42.9% (n = 13,000), new mobility aid in 29.7% (n = 9,257), and new or worsened pressure ulcers in 1.7% (n = 527). Geriatric-specific risk factors are important for patient-centered care and contribute to risk adjustment in modeling traditional and geriatric-specific outcomes. To provide optimal patient care for older adults, surgical datasets should collect measures that address cognition, decision-making, mobility, and function. Copyright © 2017 American College of Surgeons. All rights reserved.

Generalized reduced rank latent factor regression for high dimensional tensor fields, and neuroimaging-genetic applications

PubMed Central

Tao, Chenyang; Nichols, Thomas E.; Hua, Xue; Ching, Christopher R.K.; Rolls, Edmund T.; Thompson, Paul M.; Feng, Jianfeng

2017-01-01

We propose a generalized reduced rank latent factor regression model (GRRLF) for the analysis of tensor field responses and high dimensional covariates. The model is motivated by the need from imaging-genetic studies to identify genetic variants that are associated with brain imaging phenotypes, often in the form of high dimensional tensor fields. GRRLF identifies from the structure in the data the effective dimensionality of the data, and then jointly performs dimension reduction of the covariates, dynamic identification of latent factors, and nonparametric estimation of both covariate and latent response fields. After accounting for the latent and covariate effects, GRLLF performs a nonparametric test on the remaining factor of interest. GRRLF provides a better factorization of the signals compared with common solutions, and is less susceptible to overfitting because it exploits the effective dimensionality. The generality and the flexibility of GRRLF also allow various statistical models to be handled in a unified framework and solutions can be efficiently computed. Within the field of neuroimaging, it improves the sensitivity for weak signals and is a promising alternative to existing approaches. The operation of the framework is demonstrated with both synthetic datasets and a real-world neuroimaging example in which the effects of a set of genes on the structure of the brain at the voxel level were measured, and the results compared favorably with those from existing approaches. PMID:27666385

Specificity of disgust domains in the prediction of contamination anxiety and avoidance: a multimodal examination.

PubMed

Olatunji, Bunmi O; Ebesutani, Chad; Haidt, Jonathan; Sawchuk, Craig N

2014-07-01

Although core, animal-reminder, and contamination disgust are viewed as distinct "types" of disgust vulnerabilities, the extent to which individual differences in the three disgust domains uniquely predict contamination-related anxiety and avoidance remains unclear. Three studies were conducted to fill this important gap in the literature. Study 1 was conducted to first determine if the three types of disgust could be replicated in a larger and more heterogeneous sample. Confirmatory factor analysis revealed that a bifactor model consisting of a "general disgust" dimension and the three distinct disgust dimensions yielded a better fit than a one-factor model. Structural equation modeling in Study 2 showed that while latent core, animal-reminder, and contamination disgust factors each uniquely predicted a latent "contamination anxiety" factor above and beyond general disgust, only animal-reminder uniquely predicted a latent "non-contamination anxiety" factor above and beyond general disgust. However, Study 3 found that only contamination disgust uniquely predicted behavioral avoidance in a public restroom where contamination concerns are salient. These findings suggest that although the three disgust domains are associated with contamination anxiety and avoidance, individual differences in contamination disgust sensitivity appear to be most uniquely predictive of contamination-related distress. The implications of these findings for the development and maintenance of anxiety-related disorders marked by excessive contamination concerns are discussed. Copyright © 2014. Published by Elsevier Ltd.

Human factors with nonhumans - Factors that affect computer-task performance

NASA Technical Reports Server (NTRS)

Washburn, David A.

1992-01-01

There are two general strategies that may be employed for 'doing human factors research with nonhuman animals'. First, one may use the methods of traditional human factors investigations to examine the nonhuman animal-to-machine interface. Alternatively, one might use performance by nonhuman animals as a surrogate for or model of performance by a human operator. Each of these approaches is illustrated with data in the present review. Chronic ambient noise was found to have a significant but inconsequential effect on computer-task performance by rhesus monkeys (Macaca mulatta). Additional data supported the generality of findings such as these to humans, showing that rhesus monkeys are appropriate models of human psychomotor performance. It is argued that ultimately the interface between comparative psychology and technology will depend on the coordinated use of both strategies of investigation.

Predicting Cost/Reliability/Maintainability of Advanced General Aviation Avionics Equipment

NASA Technical Reports Server (NTRS)

Davis, M. R.; Kamins, M.; Mooz, W. E.

1978-01-01

A methodology is provided for assisting NASA in estimating the cost, reliability, and maintenance (CRM) requirements for general avionics equipment operating in the 1980's. Practical problems of predicting these factors are examined. The usefulness and short comings of different approaches for modeling coast and reliability estimates are discussed together with special problems caused by the lack of historical data on the cost of maintaining general aviation avionics. Suggestions are offered on how NASA might proceed in assessing cost reliability CRM implications in the absence of reliable generalized predictive models.

Structural and incremental validity of the Wechsler Adult Intelligence Scale-Fourth Edition with a clinical sample.

PubMed

Nelson, Jason M; Canivez, Gary L; Watkins, Marley W

2013-06-01

Structural and incremental validity of the Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV; Wechsler, 2008a) was examined with a sample of 300 individuals referred for evaluation at a university-based clinic. Confirmatory factor analysis indicated that the WAIS-IV structure was best represented by 4 first-order factors as well as a general intelligence factor in a direct hierarchical model. The general intelligence factor accounted for the most common and total variance among the subtests. Incremental validity analyses indicated that the Full Scale IQ (FSIQ) generally accounted for medium to large portions of academic achievement variance. For all measures of academic achievement, the first-order factors combined accounted for significant achievement variance beyond that accounted for by the FSIQ, but individual factor index scores contributed trivial amounts of achievement variance. Implications for interpreting WAIS-IV results are discussed. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

Structure of the Wechsler Intelligence Scale for Children--Fourth Edition among a national sample of referred students.

PubMed

Watkins, Marley W

2010-12-01

The structure of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV; D. Wechsler, 2003a) was analyzed via confirmatory factor analysis among a national sample of 355 students referred for psychoeducational evaluation by 93 school psychologists from 35 states. The structure of the WISC-IV core battery was best represented by four first-order factors as per D. Wechsler (2003b), plus a general intelligence factor in a direct hierarchical model. The general factor was the predominate source of variation among WISC-IV subtests, accounting for 48% of the total variance and 75% of the common variance. The largest 1st-order factor, Processing Speed, only accounted for 6.1% total and 9.5% common variance. Given these explanatory contributions, recommendations favoring interpretation of the 1st-order factor scores over the general intelligence score appear to be misguided.

Right-Sizing Statistical Models for Longitudinal Data

PubMed Central

Wood, Phillip K.; Steinley, Douglas; Jackson, Kristina M.

2015-01-01

Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to “right-size” the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting overly parsimonious models to more complex better fitting alternatives, and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically under-identified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A three-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation/covariation patterns. The orthogonal, free-curve slope-intercept (FCSI) growth model is considered as a general model which includes, as special cases, many models including the Factor Mean model (FM, McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, Hierarchical Linear Models (HLM), Repeated Measures MANOVA, and the Linear Slope Intercept (LinearSI) Growth Model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparison of several candidate parametric growth and chronometric models in a Monte Carlo study. PMID:26237507

Right-sizing statistical models for longitudinal data.

PubMed

Wood, Phillip K; Steinley, Douglas; Jackson, Kristina M

2015-12-01

Arguments are proposed that researchers using longitudinal data should consider more and less complex statistical model alternatives to their initially chosen techniques in an effort to "right-size" the model to the data at hand. Such model comparisons may alert researchers who use poorly fitting, overly parsimonious models to more complex, better-fitting alternatives and, alternatively, may identify more parsimonious alternatives to overly complex (and perhaps empirically underidentified and/or less powerful) statistical models. A general framework is proposed for considering (often nested) relationships between a variety of psychometric and growth curve models. A 3-step approach is proposed in which models are evaluated based on the number and patterning of variance components prior to selection of better-fitting growth models that explain both mean and variation-covariation patterns. The orthogonal free curve slope intercept (FCSI) growth model is considered a general model that includes, as special cases, many models, including the factor mean (FM) model (McArdle & Epstein, 1987), McDonald's (1967) linearly constrained factor model, hierarchical linear models (HLMs), repeated-measures multivariate analysis of variance (MANOVA), and the linear slope intercept (linearSI) growth model. The FCSI model, in turn, is nested within the Tuckerized factor model. The approach is illustrated by comparing alternative models in a longitudinal study of children's vocabulary and by comparing several candidate parametric growth and chronometric models in a Monte Carlo study. (c) 2015 APA, all rights reserved).

Developmental and Individual Differences in Chinese Writing

PubMed Central

Guan, Connie Qun; Ye, Feifei; Wagner, Richard K.; Meng, Wanjin

2015-01-01

The goal of the present study was to examine the generalizability of a model of the underlying dimensions of written composition across writing systems (Chinese Mandarin vs. English) and level of writing skill. A five-factor model of writing originally developed from analyses of 1st and 4th grade English writing samples was applied to Chinese writing samples obtained from 4th and 7th grade students. Confirmatory factor analysis was used to compare the fits of alternative models of written composition. The results suggest that the five-factor model of written composition generalizes to Chinese writing samples and applies to both less skilled (Grade 4) and more skilled (Grade 7) writing, with differences in factor means between grades that vary in magnitude across factors. PMID:26038631

Profile formation of academic self-concept in elementary school students in grades 1 to 4.

PubMed

Schmidt, Isabelle; Brunner, Martin; Keller, Lena; Scherrer, Vsevolod; Wollschläger, Rachel; Baudson, Tanja Gabriele; Preckel, Franzis

2017-01-01

Academic self-concept (ASC) is comprised of individual perceptions of one's own academic ability. In a cross-sectional quasi-representative sample of 3,779 German elementary school children in grades 1 to 4, we investigated (a) the structure of ASC, (b) ASC profile formation, an aspect of differentiation that is reflected in lower correlations between domain-specific ASCs with increasing grade level, (c) the impact of (internal) dimensional comparisons of one's own ability in different school subjects for profile formation of ASC, and (d) the role played by differences in school grades between subjects for these dimensional comparisons. The nested Marsh/Shavelson model, with general ASC at the apex and math, writing, and reading ASC as specific factors nested under general ASC fitted the data at all grade levels. A first-order factor model with math, writing, reading, and general ASCs as correlated factors provided a good fit, too. ASC profile formation became apparent during the first two to three years of school. Dimensional comparisons across subjects contributed to ASC profile formation. School grades enhanced these comparisons, especially when achievement profiles were uneven. In part, findings depended on the assumed structural model of ASCs. Implications for further research are discussed with special regard to factors influencing and moderating dimensional comparisons.

Profile formation of academic self-concept in elementary school students in grades 1 to 4

PubMed Central

Schmidt, Isabelle; Brunner, Martin; Keller, Lena; Scherrer, Vsevolod; Wollschläger, Rachel; Baudson, Tanja Gabriele; Preckel, Franzis

2017-01-01

Academic self-concept (ASC) is comprised of individual perceptions of one’s own academic ability. In a cross-sectional quasi-representative sample of 3,779 German elementary school children in grades 1 to 4, we investigated (a) the structure of ASC, (b) ASC profile formation, an aspect of differentiation that is reflected in lower correlations between domain-specific ASCs with increasing grade level, (c) the impact of (internal) dimensional comparisons of one’s own ability in different school subjects for profile formation of ASC, and (d) the role played by differences in school grades between subjects for these dimensional comparisons. The nested Marsh/Shavelson model, with general ASC at the apex and math, writing, and reading ASC as specific factors nested under general ASC fitted the data at all grade levels. A first-order factor model with math, writing, reading, and general ASCs as correlated factors provided a good fit, too. ASC profile formation became apparent during the first two to three years of school. Dimensional comparisons across subjects contributed to ASC profile formation. School grades enhanced these comparisons, especially when achievement profiles were uneven. In part, findings depended on the assumed structural model of ASCs. Implications for further research are discussed with special regard to factors influencing and moderating dimensional comparisons. PMID:28542384

The Cyber Aggression in Relationships Scale: A New Multidimensional Measure of Technology-Based Intimate Partner Aggression.

PubMed

Watkins, Laura E; Maldonado, Rosalita C; DiLillo, David

2018-07-01

The purpose of this study was to develop and provide initial validation for a measure of adult cyber intimate partner aggression (IPA): the Cyber Aggression in Relationships Scale (CARS). Drawing on recent conceptual models of cyber IPA, items from previous research exploring general cyber aggression and cyber IPA were modified and new items were generated for inclusion in the CARS. Two samples of adults 18 years or older were recruited online. We used item factor analysis to test the factor structure, model fit, and invariance of the measure structure across women and men. Results confirmed that three-factor models for both perpetration and victimization demonstrated good model fit, and that, in general, the CARS measures partner cyber aggression similarly for women and men. The CARS also demonstrated validity through significant associations with in-person IPA, trait anger, and jealousy. Findings suggest the CARS is a useful tool for assessing cyber IPA in both research and clinical settings.

SCL-90-R emotional distress ratings in substance use and impulse control disorders: One-factor, oblique first-order, higher-order, and bi-factor models compared.

PubMed

Arrindell, Willem A; Urbán, Róbert; Carrozzino, Danilo; Bech, Per; Demetrovics, Zsolt; Roozen, Hendrik G

2017-09-01

To fully understand the dimensionality of an instrument in a certain population, rival bi-factor models should be routinely examined and tested against oblique first-order and higher-order structures. The present study is among the very few studies that have carried out such a comparison in relation to the Symptom Checklist-90-R. In doing so, it utilized a sample comprising 2593 patients with substance use and impulse control disorders. The study also included a test of a one-dimensional model of general psychological distress. Oblique first-order factors were based on the original a priori 9-dimensional model advanced by Derogatis (1977); and on an 8-dimensional model proposed by Arrindell and Ettema (2003)-Agoraphobia, Anxiety, Depression, Somatization, Cognitive-performance deficits, Interpersonal sensitivity and mistrust, Acting-out hostility, and Sleep difficulties. Taking individual symptoms as input, three higher-order models were tested with at the second-order levels either (1) General psychological distress; (2) 'Panic with agoraphobia', 'Depression' and 'Extra-punitive behavior'; or (3) 'Irritable-hostile depression' and 'Panic with agoraphobia'. In line with previous studies, no support was found for the one-factor model. Bi-factor models were found to fit the dataset best relative to the oblique first-order and higher-order models. However, oblique first-order and higher-order factor models also fit the data fairly well in absolute terms. Higher-order solution (2) provided support for R.F. Krueger's empirical model of psychopathology which distinguishes between fear, distress, and externalizing factors (Krueger, 1999). The higher-order model (3), which combines externalizing and distress factors (Irritable-hostile depression), fit the data numerically equally well. Overall, findings were interpreted as supporting the hypothesis that the prevalent forms of symptomatology addressed have both important common and unique features. Proposals were made to improve the Depression subscale as its scores represent more of a very common construct as is measured with the severity (total) scale than of a specific measure that purports to measure what it should assess-symptoms of depression. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

QCD Sum Rules and Models for Generalized Parton Distributions

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

Anatoly Radyushkin

2004-10-01

I use QCD sum rule ideas to construct models for generalized parton distributions. To this end, the perturbative parts of QCD sum rules for the pion and nucleon electromagnetic form factors are interpreted in terms of GPDs and two models are discussed. One of them takes the double Borel transform at adjusted value of the Borel parameter as a model for nonforward parton densities, and another is based on the local duality relation. Possible ways of improving these Ansaetze are briefly discussed.

Estimation of group means when adjusting for covariates in generalized linear models.

PubMed

Qu, Yongming; Luo, Junxiang

2015-01-01

Generalized linear models are commonly used to analyze categorical data such as binary, count, and ordinal outcomes. Adjusting for important prognostic factors or baseline covariates in generalized linear models may improve the estimation efficiency. The model-based mean for a treatment group produced by most software packages estimates the response at the mean covariate, not the mean response for this treatment group for the studied population. Although this is not an issue for linear models, the model-based group mean estimates in generalized linear models could be seriously biased for the true group means. We propose a new method to estimate the group mean consistently with the corresponding variance estimation. Simulation showed the proposed method produces an unbiased estimator for the group means and provided the correct coverage probability. The proposed method was applied to analyze hypoglycemia data from clinical trials in diabetes. Copyright © 2014 John Wiley & Sons, Ltd.

Effect of retention in elementary grades on grade 9 motivation for educational attainment.

PubMed

Cham, Heining; Hughes, Jan N; West, Stephen G; Im, Myung Hee

2015-02-01

This study investigated the effect of grade retention in elementary school on students' motivation for educational attainment in grade 9. We equated retained and promoted students on 67 covariates assessed in grade 1 through propensity score weighting. Retained students (31.55%, nretained=177) and continuously promoted students (68.45%, npromoted=384) were compared on the bifactor model of motivation for educational attainment (Cham, Hughes, West & Im, 2014). This model consists of a General factor (student's overall motivation for educational attainment), and three specific factors: student perceived Teacher Educational Expectations, Peer Educational Aspirations, and Value of Education. Measurement invariance between retained and promoted groups was established. Retained students scored significantly higher than promoted students on each specific factor but not on the General factor. Results showed that the retained and promoted students did not significantly differ on the General factor. The retained students had significantly higher scores on each specific factor than those of the promoted students. The results suggested that grade retention may not have the negative effects so widely assumed in the published literature; it is an expensive intervention with minimal evidence of benefits to the retained student. Copyright © 2014 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

The Influence of Self-Efficacy and Motivational Factors on Academic Performance in General Chemistry Course: A Modeling Study

ERIC Educational Resources Information Center

Alci, Bulent

2015-01-01

This study aims to determine the predictive and explanatory model in terms of university students' academic performance in "General Chemistry" course and their motivational features. The participants were 169 university students in the 1st grade at university. Of the participants, 132 were female and 37 were male students. Regarding…

Performance Analysis and Optimization on the UCLA Parallel Atmospheric General Circulation Model Code

NASA Technical Reports Server (NTRS)

Lou, John; Ferraro, Robert; Farrara, John; Mechoso, Carlos

1996-01-01

An analysis is presented of several factors influencing the performance of a parallel implementation of the UCLA atmospheric general circulation model (AGCM) on massively parallel computer systems. Several modificaitons to the original parallel AGCM code aimed at improving its numerical efficiency, interprocessor communication cost, load-balance and issues affecting single-node code performance are discussed.

Parenting Practices and Adolescent Sexual Behavior: A Longitudinal Study

ERIC Educational Resources Information Center

Bersamin, Melina; Todd, Michael; Fisher, Deborah A.; Hill, Douglas L.; Grube, Joel W.; Walker, Samantha

2008-01-01

The effects of parental attitudes, practices, and television mediation on adolescent sexual behaviors were investigated in a study of adolescent sexuality and media (N = 887). Confirmatory factor analyses supported an eight-factor parenting model with television mediation factors as constructs distinct from general parenting practices. Logistic…

One factor or two parallel processes? Comorbidity and development of adolescent anxiety and depressive disorder symptoms.

PubMed

Hale, William W; Raaijmakers, Quinten A W; Muris, Peter; van Hoof, Anne; Meeus, Wim H J

2009-10-01

This study investigates whether anxiety and depressive disorder symptoms of adolescents from the general community are best described by a model that assumes they are indicative of one general factor or by a model that assumes they are two distinct disorders with parallel growth processes. Additional analyses were conducted to explore the comorbidity of adolescent anxiety and depressive disorder symptoms and the effects that adolescent anxiety and depressive disorder symptoms have on each other's symptom severity growth. Two cohorts of early (N = 923; Age range 10-15 years; Mean age = 12.4, SD = .59; Girls = 49%) and middle adolescent (N = 390; Age range 16-20 years; Mean age = 16.7, SD = .80; Girls = 57%) boys and girls from the general community were prospectively studied annually for five years. These two adolescent cohorts were divided into five groups: one group at-risk for developing a specific anxiety disorder and four additional groups of healthy adolescents that differed in age and sex. Self-reported anxiety and depressive disorder symptoms were analyzed with latent growth modeling. Comparison of the fit statistics of the two models clearly demonstrates the superiority of the distinct disorders with parallel growth processes model above the one factor model. It was also demonstrated that the initial symptom severity of either anxiety or depression is predictive of the development of the other, though in different ways for the at-risk and healthy adolescent groups. The results of this study established that the development of anxiety and depressive disorder symptoms of adolescents from the general community occurs as two distinct disorders with parallel growth processes, each with their own unique growth characteristics.

Towards a General Model of Temporal Discounting

ERIC Educational Resources Information Center

van den Bos, Wouter; McClure, Samuel M.

2013-01-01

Psychological models of temporal discounting have now successfully displaced classical economic theory due to the simple fact that many common behavior patterns, such as impulsivity, were unexplainable with classic models. However, the now dominant hyperbolic model of discounting is itself becoming increasingly strained. Numerous factors have…

Using a latent variable model with non-constant factor loadings to examine PM2.5 constituents related to secondary inorganic aerosols.

PubMed

Zhang, Zhenzhen; O'Neill, Marie S; Sánchez, Brisa N

2016-04-01

Factor analysis is a commonly used method of modelling correlated multivariate exposure data. Typically, the measurement model is assumed to have constant factor loadings. However, from our preliminary analyses of the Environmental Protection Agency's (EPA's) PM 2.5 fine speciation data, we have observed that the factor loadings for four constituents change considerably in stratified analyses. Since invariance of factor loadings is a prerequisite for valid comparison of the underlying latent variables, we propose a factor model that includes non-constant factor loadings that change over time and space using P-spline penalized with the generalized cross-validation (GCV) criterion. The model is implemented using the Expectation-Maximization (EM) algorithm and we select the multiple spline smoothing parameters by minimizing the GCV criterion with Newton's method during each iteration of the EM algorithm. The algorithm is applied to a one-factor model that includes four constituents. Through bootstrap confidence bands, we find that the factor loading for total nitrate changes across seasons and geographic regions.

[Lake eutrophication modeling in considering climatic factors change: a review].

PubMed

Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

2012-11-01

Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

Calibration and validation of a general infiltration model

NASA Astrophysics Data System (ADS)

Mishra, Surendra Kumar; Ranjan Kumar, Shashi; Singh, Vijay P.

1999-08-01

A general infiltration model proposed by Singh and Yu (1990) was calibrated and validated using a split sampling approach for 191 sets of infiltration data observed in the states of Minnesota and Georgia in the USA. Of the five model parameters, fc (the final infiltration rate), So (the available storage space) and exponent n were found to be more predictable than the other two parameters: m (exponent) and a (proportionality factor). A critical examination of the general model revealed that it is related to the Soil Conservation Service (1956) curve number (SCS-CN) method and its parameter So is equivalent to the potential maximum retention of the SCS-CN method and is, in turn, found to be a function of soil sorptivity and hydraulic conductivity. The general model was found to describe infiltration rate with time varying curve number.

The Issue of Power in the Identification of "g" with Lower-Order Factors

ERIC Educational Resources Information Center

Matzke, Dora; Dolan, Conor V.; Molenaar, Dylan

2010-01-01

In higher order factor models, general intelligence (g) is often found to correlate perfectly with lower-order common factors, suggesting that g and some well-defined cognitive ability, such as working memory, may be identical. However, the results of studies that addressed the equivalence of g and lower-order factors are inconsistent. We suggest…

The General Aggression Model.

PubMed

Allen, Johnie J; Anderson, Craig A; Bushman, Brad J

2018-02-01

The General Aggression Model (GAM) is a comprehensive, integrative, framework for understanding aggression. It considers the role of social, cognitive, personality, developmental, and biological factors on aggression. Proximate processes of GAM detail how person and situation factors influence cognitions, feelings, and arousal, which in turn affect appraisal and decision processes, which in turn influence aggressive or nonaggressive behavioral outcomes. Each cycle of the proximate processes serves as a learning trial that affects the development and accessibility of aggressive knowledge structures. Distal processes of GAM detail how biological and persistent environmental factors can influence personality through changes in knowledge structures. GAM has been applied to understand aggression in many contexts including media violence effects, domestic violence, intergroup violence, temperature effects, pain effects, and the effects of global climate change. Copyright © 2017 Elsevier Ltd. All rights reserved.

A generalized nonlinear model-based mixed multinomial logit approach for crash data analysis.

PubMed

Zeng, Ziqiang; Zhu, Wenbo; Ke, Ruimin; Ash, John; Wang, Yinhai; Xu, Jiuping; Xu, Xinxin

2017-02-01

The mixed multinomial logit (MNL) approach, which can account for unobserved heterogeneity, is a promising unordered model that has been employed in analyzing the effect of factors contributing to crash severity. However, its basic assumption of using a linear function to explore the relationship between the probability of crash severity and its contributing factors can be violated in reality. This paper develops a generalized nonlinear model-based mixed MNL approach which is capable of capturing non-monotonic relationships by developing nonlinear predictors for the contributing factors in the context of unobserved heterogeneity. The crash data on seven Interstate freeways in Washington between January 2011 and December 2014 are collected to develop the nonlinear predictors in the model. Thirteen contributing factors in terms of traffic characteristics, roadway geometric characteristics, and weather conditions are identified to have significant mixed (fixed or random) effects on the crash density in three crash severity levels: fatal, injury, and property damage only. The proposed model is compared with the standard mixed MNL model. The comparison results suggest a slight superiority of the new approach in terms of model fit measured by the Akaike Information Criterion (12.06 percent decrease) and Bayesian Information Criterion (9.11 percent decrease). The predicted crash densities for all three levels of crash severities of the new approach are also closer (on average) to the observations than the ones predicted by the standard mixed MNL model. Finally, the significance and impacts of the contributing factors are analyzed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Empirical Investigation of a Model of Sexual Minority Specific and General Risk Factors for Intimate Partner Violence among Lesbian Women

PubMed Central

Lewis, Robin J.; Mason, Tyler B.; Winstead, Barbara A.; Kelley, Michelle L.

2015-01-01

Objective This study proposed and tested the first conceptual model of sexual minority specific (discrimination, internalized homophobia) and more general risk factors (perpetrator and partner alcohol use, anger, relationship satisfaction) for intimate partner violence among partnered lesbian women. Method Self-identified lesbian women (N=1048) were recruited from online market research panels. Participants completed an online survey that included measures of minority stress, anger, alcohol use and alcohol-related problems, relationship satisfaction, psychological aggression, and physical violence. Results The model demonstrated good fit and significant links from sexual minority discrimination to internalized homophobia and anger, from internalized homophobia to anger and alcohol problems, and from alcohol problems to intimate partner violence. Partner alcohol use predicted partner physical violence. Relationship dissatisfaction was associated with physical violence via psychological aggression. Physical violence was bidirectional. Conclusions Minority stress, anger, alcohol use and alcohol-related problems play an important role in perpetration of psychological aggression and physical violence in lesbian women's intimate partner relationships. The results of this study provide evidence of potentially modifiable sexual minority specific and more general risk factors for lesbian women's partner violence. PMID:28239508

The factor structure of the Values in Action Inventory of Strengths (VIA-IS): An item-level exploratory structural equation modeling (ESEM) bifactor analysis.

PubMed

Ng, Vincent; Cao, Mengyang; Marsh, Herbert W; Tay, Louis; Seligman, Martin E P

2017-08-01

The factor structure of the Values in Action Inventory of Strengths (VIA-IS; Peterson & Seligman, 2004) has not been well established as a result of methodological challenges primarily attributable to a global positivity factor, item cross-loading across character strengths, and questions concerning the unidimensionality of the scales assessing character strengths. We sought to overcome these methodological challenges by applying exploratory structural equation modeling (ESEM) at the item level using a bifactor analytic approach to a large sample of 447,573 participants who completed the VIA-IS with all 240 character strengths items and a reduced set of 107 unidimensional character strength items. It was found that a 6-factor bifactor structure generally held for the reduced set of unidimensional character strength items; these dimensions were justice, temperance, courage, wisdom, transcendence, humanity, and an overarching general factor that is best described as dispositional positivity. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Modeling zoonotic cutaneous leishmaniasis incidence in central Tunisia from 2009-2015: Forecasting models using climate variables as predictors

PubMed Central

Bellali, Hedia; Ben-Alaya, Nissaf; Saez, Marc; Malouche, Dhafer; Chahed, Mohamed Kouni

2017-01-01

Transmission of zoonotic cutaneous leishmaniasis (ZCL) depends on the presence, density and distribution of Leishmania major rodent reservoir and the development of these rodents is known to have a significant dependence on environmental and climate factors. ZCL in Tunisia is one of the most common forms of leishmaniasis. The aim of this paper was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Monthly reported ZCL cases, environmental and bioclimatic data were collected over 6 years (2009–2015). Three rural areas in the governorate of Sidi Bouzid were selected as the study area. Cross-correlation analysis was used to identify the relevant lagged effects of possible risk factors, associated with ZCL cases. Non-parametric modeling techniques known as generalized additive model (GAM) and generalized additive mixed models (GAMM) were applied in this work. These techniques have the ability to approximate the relationship between the predictors (inputs) and the response variable (output), and express the relationship mathematically. The goodness-of-fit of the constructed model was determined by Generalized cross-validation (GCV) score and residual test. There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The results showed seasonal distribution of reported ZCL cases from August to January. The model highlighted that rodent density, average temperature, cumulative rainfall and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence. The GAMM model could be applied to predict the occurrence of ZCL in central Tunisia and could help for the establishment of an early warning system to control and prevent ZCL in central Tunisia. PMID:28841642

Modeling zoonotic cutaneous leishmaniasis incidence in central Tunisia from 2009-2015: Forecasting models using climate variables as predictors.

PubMed

Talmoudi, Khouloud; Bellali, Hedia; Ben-Alaya, Nissaf; Saez, Marc; Malouche, Dhafer; Chahed, Mohamed Kouni

2017-08-01

Transmission of zoonotic cutaneous leishmaniasis (ZCL) depends on the presence, density and distribution of Leishmania major rodent reservoir and the development of these rodents is known to have a significant dependence on environmental and climate factors. ZCL in Tunisia is one of the most common forms of leishmaniasis. The aim of this paper was to build a regression model of ZCL cases to identify the relationship between ZCL occurrence and possible risk factors, and to develop a predicting model for ZCL's control and prevention purposes. Monthly reported ZCL cases, environmental and bioclimatic data were collected over 6 years (2009-2015). Three rural areas in the governorate of Sidi Bouzid were selected as the study area. Cross-correlation analysis was used to identify the relevant lagged effects of possible risk factors, associated with ZCL cases. Non-parametric modeling techniques known as generalized additive model (GAM) and generalized additive mixed models (GAMM) were applied in this work. These techniques have the ability to approximate the relationship between the predictors (inputs) and the response variable (output), and express the relationship mathematically. The goodness-of-fit of the constructed model was determined by Generalized cross-validation (GCV) score and residual test. There were a total of 1019 notified ZCL cases from July 2009 to June 2015. The results showed seasonal distribution of reported ZCL cases from August to January. The model highlighted that rodent density, average temperature, cumulative rainfall and average relative humidity, with different time lags, all play role in sustaining and increasing the ZCL incidence. The GAMM model could be applied to predict the occurrence of ZCL in central Tunisia and could help for the establishment of an early warning system to control and prevent ZCL in central Tunisia.

The dimensionality of between-person differences in white matter microstructure in old age.

PubMed

Lövdén, Martin; Laukka, Erika Jonsson; Rieckmann, Anna; Kalpouzos, Grégoria; Li, Tie-Qiang; Jonsson, Tomas; Wahlund, Lars-Olof; Fratiglioni, Laura; Bäckman, Lars

2013-06-01

Between-person differences in white matter microstructure may partly generalize across the brain and partly play out differently for distinct tracts. We used diffusion-tensor imaging and structural equation modeling to investigate this issue in a sample of 260 adults aged 60-87 years. Mean fractional anisotropy and mean diffusivity of seven white matter tracts in each hemisphere were quantified. Results showed good fit of a model positing that individual differences in white matter microstructure are structured according to tracts. A general factor, although accounting for variance in the measures, did not adequately represent the individual differences. This indicates the presence of a substantial amount of tract-specific individual differences in white matter microstructure. In addition, individual differences are to a varying degree shared between tracts, indicating that general factors also affect white matter microstructure. Age-related differences in white matter microstructure were present for all tracts. Correlations among tract factors did not generally increase as a function of age, suggesting that aging is not a process with homogenous effects on white matter microstructure across the brain. These findings highlight the need for future research to examine whether relations between white matter microstructure and diverse outcomes are specific or general. Copyright © 2011 Wiley Periodicals, Inc.

Quantification of source impact to PM using three-dimensional weighted factor model analysis on multi-site data

NASA Astrophysics Data System (ADS)

Shi, Guoliang; Peng, Xing; Huangfu, Yanqi; Wang, Wei; Xu, Jiao; Tian, Yingze; Feng, Yinchang; Ivey, Cesunica E.; Russell, Armistead G.

2017-07-01

Source apportionment technologies are used to understand the impacts of important sources of particulate matter (PM) air quality, and are widely used for both scientific studies and air quality management. Generally, receptor models apportion speciated PM data from a single sampling site. With the development of large scale monitoring networks, PM speciation are observed at multiple sites in an urban area. For these situations, the models should account for three factors, or dimensions, of the PM, including the chemical species concentrations, sampling periods and sampling site information, suggesting the potential power of a three-dimensional source apportionment approach. However, the principle of three-dimensional Parallel Factor Analysis (Ordinary PARAFAC) model does not always work well in real environmental situations for multi-site receptor datasets. In this work, a new three-way receptor model, called "multi-site three way factor analysis" model is proposed to deal with the multi-site receptor datasets. Synthetic datasets were developed and introduced into the new model to test its performance. Average absolute error (AAE, between estimated and true contributions) for extracted sources were all less than 50%. Additionally, three-dimensional ambient datasets from a Chinese mega-city, Chengdu, were analyzed using this new model to assess the application. Four factors are extracted by the multi-site WFA3 model: secondary source have the highest contributions (64.73 and 56.24 μg/m3), followed by vehicular exhaust (30.13 and 33.60 μg/m3), crustal dust (26.12 and 29.99 μg/m3) and coal combustion (10.73 and 14.83 μg/m3). The model was also compared to PMF, with general agreement, though PMF suggested a lower crustal contribution.

A heteroscedastic generalized linear model with a non-normal speed factor for responses and response times.

PubMed

Molenaar, Dylan; Bolsinova, Maria

2017-05-01

In generalized linear modelling of responses and response times, the observed response time variables are commonly transformed to make their distribution approximately normal. A normal distribution for the transformed response times is desirable as it justifies the linearity and homoscedasticity assumptions in the underlying linear model. Past research has, however, shown that the transformed response times are not always normal. Models have been developed to accommodate this violation. In the present study, we propose a modelling approach for responses and response times to test and model non-normality in the transformed response times. Most importantly, we distinguish between non-normality due to heteroscedastic residual variances, and non-normality due to a skewed speed factor. In a simulation study, we establish parameter recovery and the power to separate both effects. In addition, we apply the model to a real data set. © 2017 The Authors. British Journal of Mathematical and Statistical Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.

Technosocial Modeling of IED Threat Scenarios and Attacks

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

Whitney, Paul D.; Brothers, Alan J.; Coles, Garill A.

2009-03-23

This paper describes an approach for integrating sociological and technical models to develop more complete threat assessment. Current approaches to analyzing and addressing threats tend to focus on the technical factors. This paper addresses development of predictive models that encompass behavioral as well as these technical factors. Using improvised explosive device (IED) attacks as motivation, this model supports identification of intervention activities 'left of boom' as well as prioritizing attack modalities. We show how Bayes nets integrate social factors associated with IED attacks into general threat model containing technical and organizational steps from planning through obtaining the IED to initiationmore » of the attack. The social models are computationally-based representations of relevant social science literature that describes human decision making and physical factors. When combined with technical models, the resulting model provides improved knowledge integration into threat assessment for monitoring. This paper discusses the construction of IED threat scenarios, integration of diverse factors into an analytical framework for threat assessment, indicator identification for future threats, and future research directions.« less

Antibiotic Resistances in Livestock: A Comparative Approach to Identify an Appropriate Regression Model for Count Data

PubMed Central

Hüls, Anke; Frömke, Cornelia; Ickstadt, Katja; Hille, Katja; Hering, Johanna; von Münchhausen, Christiane; Hartmann, Maria; Kreienbrock, Lothar

2017-01-01

Antimicrobial resistance in livestock is a matter of general concern. To develop hygiene measures and methods for resistance prevention and control, epidemiological studies on a population level are needed to detect factors associated with antimicrobial resistance in livestock holdings. In general, regression models are used to describe these relationships between environmental factors and resistance outcome. Besides the study design, the correlation structures of the different outcomes of antibiotic resistance and structural zero measurements on the resistance outcome as well as on the exposure side are challenges for the epidemiological model building process. The use of appropriate regression models that acknowledge these complexities is essential to assure valid epidemiological interpretations. The aims of this paper are (i) to explain the model building process comparing several competing models for count data (negative binomial model, quasi-Poisson model, zero-inflated model, and hurdle model) and (ii) to compare these models using data from a cross-sectional study on antibiotic resistance in animal husbandry. These goals are essential to evaluate which model is most suitable to identify potential prevention measures. The dataset used as an example in our analyses was generated initially to study the prevalence and associated factors for the appearance of cefotaxime-resistant Escherichia coli in 48 German fattening pig farms. For each farm, the outcome was the count of samples with resistant bacteria. There was almost no overdispersion and only moderate evidence of excess zeros in the data. Our analyses show that it is essential to evaluate regression models in studies analyzing the relationship between environmental factors and antibiotic resistances in livestock. After model comparison based on evaluation of model predictions, Akaike information criterion, and Pearson residuals, here the hurdle model was judged to be the most appropriate model. PMID:28620609

[Treatment of generalized anxiety disorder in terms of cognitive behavioral].

PubMed

Kamrowska, Anna; Gmitrowicz, Agnieszka

2016-02-01

Risk of generalized anxiety disorder (GAD) within life is estimated at 2.6-5.1%. Amongst etiological factors that affect the development of the disorder are: biological and psychological problems, including cognitive models. There are known several cognitive models: metacognitive, Borkovec'c model and the model developed in Quebec. Key cognitive contents that occur with generalized anxiety disorder are focused on two aspects: metacognitive beliefs and intolerance of uncertainty. A primary purpose of cognitive-behavioural therapy (CBT) is the modification of dysfunctional beliefs about worry. Cognitive behavioural therapy is effective in reducing anxiety, makes it easier to operate in the professional sphere and improves the quality of life. © 2016 MEDPRESS.

Best Design for Multidimensional Computerized Adaptive Testing With the Bifactor Model

PubMed Central

Seo, Dong Gi; Weiss, David J.

2015-01-01

Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm (MCAT) with a bifactor model using simulated data. Four item selection methods in MCAT were examined for three bifactor pattern designs using two multidimensional item response theory models. To compare MCAT item selection and estimation methods, a fixed test length was used. The Ds-optimality item selection improved θ estimates with respect to a general factor, and either D- or A-optimality improved estimates of the group factors in three bifactor pattern designs under two multidimensional item response theory models. The MCAT model without a guessing parameter functioned better than the MCAT model with a guessing parameter. The MAP (maximum a posteriori) estimation method provided more accurate θ estimates than the EAP (expected a posteriori) method under most conditions, and MAP showed lower observed standard errors than EAP under most conditions, except for a general factor condition using Ds-optimality item selection. PMID:29795848

Cloud immersion building shielding factors for US residential structures.

PubMed

Dickson, E D; Hamby, D M

2014-12-01

This paper presents validated building shielding factors designed for contemporary US housing-stock under an idealized, yet realistic, exposure scenario within a semi-infinite cloud of radioactive material. The building shielding factors are intended for use in emergency planning and level three probabilistic risk assessments for a variety of postulated radiological events in which a realistic assessment is necessary to better understand the potential risks for accident mitigation and emergency response planning. Factors are calculated from detailed computational housing-units models using the general-purpose Monte Carlo N-Particle computational code, MCNP5, and are benchmarked from a series of narrow- and broad-beam measurements analyzing the shielding effectiveness of ten common general-purpose construction materials and ten shielding models representing the primary weather barriers (walls and roofs) of likely US housing-stock. Each model was designed to scale based on common residential construction practices and include, to the extent practical, all structurally significant components important for shielding against ionizing radiation. Calculations were performed for floor-specific locations as well as for computing a weighted-average representative building shielding factor for single- and multi-story detached homes, both with and without basement, as well for single-wide manufactured housing-units.

[Does the GHQ-12 scoring system affect its factor structure? An exploratory study of Ibero American students].

PubMed

Urzúa, Alfonso; Caqueo-Urízar, Alejandra; Bargsted, Mariana; Irarrázaval, Matías

2015-06-01

This study aimed to evaluate whether the scoring system of the General Health Questionnaire (GHQ-12) alters the instrument's factor structure. The method considered 1,972 university students from nine Ibero American countries. Modeling was performed with structural equations for 1, 2, and 3 latent factors. The mechanism for scoring the questions was analyzed within each type of structure. The results indicate that models with 2 and 3 factors show better goodness-of-fit. In relation to scoring mechanisms, procedure 0-1-1-1 for models with 2 and 3 factors showed the best fit. In conclusion, there appears to be a relationship between the response format and the number of factors identified in the instrument's structure. The model with the best fit was 3-factor 0-1-1-1-formatted, but 0-1-2-3 has acceptable and more stable indicators and provides a better format for two- and three-dimensional models.

A MATHEMATICAL MODEL OF ELECTROSTATIC PRECIPITATION. (REVISION 1): VOLUME I. MODELING AND PROGRAMMING

EPA Science Inventory

The report briefly describes the fundamental mechanisms and limiting factors involved in the electrostatic precipitation process. It discusses theories and procedures used in the computer model to describe the physical mechanisms, and generally describes the major operations perf...

An Underlying Common Factor, Influenced by Genetics and Unique Environment, Explains the Covariation Between Major Depressive Disorder, Generalized Anxiety Disorder, and Burnout: A Swedish Twin Study.

PubMed

Mather, Lisa; Blom, Victoria; Bergström, Gunnar; Svedberg, Pia

2016-12-01

Depression and anxiety are highly comorbid due to shared genetic risk factors, but less is known about whether burnout shares these risk factors. We aimed to examine whether the covariation between major depressive disorder (MDD), generalized anxiety disorder (GAD), and burnout is explained by common genetic and/or environmental factors. This cross-sectional study included 25,378 Swedish twins responding to a survey in 2005-2006. Structural equation models were used to analyze whether the trait variances and covariances were due to additive genetics, non-additive genetics, shared environment, and unique environment. Univariate analyses tested sex limitation models and multivariate analysis tested Cholesky, independent pathway, and common pathway models. The phenotypic correlations were 0.71 (0.69-0.74) between MDD and GAD, 0.58 (0.56-0.60) between MDD and burnout, and 0.53 (0.50-0.56) between GAD and burnout. Heritabilities were 45% for MDD, 49% for GAD, and 38% for burnout; no statistically significant sex differences were found. A common pathway model was chosen as the final model. The common factor was influenced by genetics (58%) and unique environment (42%), and explained 77% of the variation in MDD, 69% in GAD, and 44% in burnout. GAD and burnout had additive genetic factors unique to the phenotypes (11% each), while MDD did not. Unique environment explained 23% of the variability in MDD, 20% in GAD, and 45% in burnout. In conclusion, the covariation was explained by an underlying common factor, largely influenced by genetics. Burnout was to a large degree influenced by unique environmental factors not shared with MDD and GAD.

Unification and mechanistic detail as drivers of model construction: models of networks in economics and sociology.

PubMed

Kuorikoski, Jaakko; Marchionni, Caterina

2014-12-01

We examine the diversity of strategies of modelling networks in (micro) economics and (analytical) sociology. Field-specific conceptions of what explaining (with) networks amounts to or systematic preference for certain kinds of explanatory factors are not sufficient to account for differences in modelling methodologies. We argue that network models in both sociology and economics are abstract models of network mechanisms and that differences in their modelling strategies derive to a large extent from field-specific conceptions of the way in which a good model should be a general one. Whereas the economics models aim at unification, the sociological models aim at a set of mechanism schemas that are extrapolatable to the extent that the underlying psychological mechanisms are general. These conceptions of generality induce specific biases in mechanistic explanation and are related to different views of when knowledge from different fields should be seen as relevant.

Comparison of Survival Models for Analyzing Prognostic Factors in Gastric Cancer Patients

PubMed

Habibi, Danial; Rafiei, Mohammad; Chehrei, Ali; Shayan, Zahra; Tafaqodi, Soheil

2018-03-27

Objective: There are a number of models for determining risk factors for survival of patients with gastric cancer. This study was conducted to select the model showing the best fit with available data. Methods: Cox regression and parametric models (Exponential, Weibull, Gompertz, Log normal, Log logistic and Generalized Gamma) were utilized in unadjusted and adjusted forms to detect factors influencing mortality of patients. Comparisons were made with Akaike Information Criterion (AIC) by using STATA 13 and R 3.1.3 softwares. Results: The results of this study indicated that all parametric models outperform the Cox regression model. The Log normal, Log logistic and Generalized Gamma provided the best performance in terms of AIC values (179.2, 179.4 and 181.1, respectively). On unadjusted analysis, the results of the Cox regression and parametric models indicated stage, grade, largest diameter of metastatic nest, largest diameter of LM, number of involved lymph nodes and the largest ratio of metastatic nests to lymph nodes, to be variables influencing the survival of patients with gastric cancer. On adjusted analysis, according to the best model (log normal), grade was found as the significant variable. Conclusion: The results suggested that all parametric models outperform the Cox model. The log normal model provides the best fit and is a good substitute for Cox regression. Creative Commons Attribution License

General Oral Health Assessment Index: A new evaluation proposal.

PubMed

Campos, Juliana A D B; Zucoloto, Miriane L; Bonafé, Fernanda S S; Maroco, João

2017-09-01

To validity the General Oral Health Assessment Index (GOHAI) among adults who sought dental care and to present a new proposal for calculating scores on self-perception of oral health. There is no study that presents a GOHAI scores using weight of the items. The one-factor model, the three-factor model (physical function, psychosocial/psychological function and pain/discomfort) and the second-order hierarchical model (SOHM) were evaluated from confirmatory factor analysis (λ, χ 2 /df, CFI,GFI and RMSEA). The reliability (CR,α) was estimated. Concurrent validity was assessed using the Oral Health Impact Profile (OHIP-14). The invariance of the models was estimated in independent samples. The calculation of an overall score using the factor scores was proposed to obtain the overall weighted scores. These overall weighted scores were compared to the scores estimated as the simple arithmetic mean (overall unweighted scores) using a repeated measures analysis of variance. A total of 1000 individuals participated (74.1% female; age: 40.7 (SD=14.3) years). Three items of the GOHAI were excluded (λ<0.40). The one-factor model (λ=0.40-0.77; χ 2 /df=6.291; CFI=0.947; GFI=0.960; RMSEA=0.073) and the three-factor model (λ=0.40-0.78; χ 2 /df=8.321; CFI=0.932; GFI=0.954; RMSEA=0.086) each presented an adequate fit. Reliability was adequate (one-factor: CR=0.83/α=0.83; three-factor: CR=0.53-0.76/α=0.53-0.73), with the exception of the pain/discomfort factor. The GOHAI was invariant in independent samples, and the concurrent validity was adequate. The overall unweighted scores overestimated self-perceptions of oral health when compared with the weighted scores. Both the one-factor and three-factor models of the GOHAI were found to be valid, reliable and invariant for the sample after the exclusion of three items. The use of overall weighted scores is recommended for calculating the score of self-perception of oral health. © 2017 John Wiley & Sons A/S and The Gerodontology Association. Published by John Wiley & Sons Ltd.

Factor Scores, Structure and Communality Coefficients: A Primer

ERIC Educational Resources Information Center

Odum, Mary

2011-01-01

(Purpose) The purpose of this paper is to present an easy-to-understand primer on three important concepts of factor analysis: Factor scores, structure coefficients, and communality coefficients. Given that statistical analyses are a part of a global general linear model (GLM), and utilize weights as an integral part of analyses (Thompson, 2006;…

Generalized Effective Medium Theory for Particulate Nanocomposite Materials

PubMed Central

Siddiqui, Muhammad Usama; Arif, Abul Fazal M.

2016-01-01

The thermal conductivity of particulate nanocomposites is strongly dependent on the size, shape, orientation and dispersion uniformity of the inclusions. To correctly estimate the effective thermal conductivity of the nanocomposite, all these factors should be included in the prediction model. In this paper, the formulation of a generalized effective medium theory for the determination of the effective thermal conductivity of particulate nanocomposites with multiple inclusions is presented. The formulated methodology takes into account all the factors mentioned above and can be used to model nanocomposites with multiple inclusions that are randomly oriented or aligned in a particular direction. The effect of inclusion dispersion non-uniformity is modeled using a two-scale approach. The applications of the formulated effective medium theory are demonstrated using previously published experimental and numerical results for several particulate nanocomposites. PMID:28773817

Using a general model of personality to identify the basic elements of psychopathy.

PubMed

Lynam, Donald R; Widiger, Thomas A

2007-04-01

In the present paper, we outline why we believe that factor analyses of the Hare Psychopathy Checklist Revised (Hare, 2003) are unlikely to yield the basic elements of psychopathy. As an alternative approach, we suggest embedding psychopathy within a broad model of general personality functioning, namely the five factor model (McCrae & Costa, 1990). Drawing on our previous work in the area using expert ratings, correlational approaches, and a "translation" of the PCL-R, we provide a consensus description of the core elements of psychopathy: extremely high interpersonal antagonism, pan-impulsivity, the absence of negative self-directed affect, the presence of angry hostility, and interpersonal assertiveness. We end with a discussion of the implications of this analysis for understanding, researching, and measuring psychopathy.

The results of a limited study of approaches to the design, fabrication, and testing of a dynamic model of the NASA IOC space station. Executive summary

NASA Technical Reports Server (NTRS)

Brooks, George W.

1985-01-01

The options for the design, construction, and testing of a dynamic model of the space station were evaluated. Since the definition of the space station structure is still evolving, the Initial Operating Capacity (IOC) reference configuration was used as the general guideline. The results of the studies treat: general considerations of the need for and use of a dynamic model; factors which deal with the model design and construction; and a proposed system for supporting the dynamic model in the planned Large Spacecraft Laboratory.

Measuring pathology using the PANSS across diagnoses: Inconsistency of the positive symptom domain across schizophrenia, schizoaffective, and bipolar disorder.

PubMed

Anderson, Ariana E; Mansolf, Maxwell; Reise, Steven P; Savitz, Adam; Salvadore, Giacomo; Li, Qingqin; Bilder, Robert M

2017-12-01

Although the Positive and Negative Syndrome Scale (PANSS) was developed for use in schizophrenia (SZ), antipsychotic drug trials use the PANSS to measure symptom change also for bipolar (BP) and schizoaffective (SA) disorder, extending beyond its original indications. If the dimensions measured by the PANSS are different across diagnoses, then the same score change for the same drug condition may have different meanings depending on which group is being studied. Here, we evaluated whether the factor structure in the PANSS was consistent across schizophrenia (n = 3647), bipolar disorder (n = 858), and schizoaffective disorder (n = 592). Along with congruency coefficients, Hancock's H, and Jaccard indices, we used target rotations and statistical tests of invariance based on confirmatory factor models. We found the five symptom dimensions measured by the 30-item PANSS did not generalize well to schizoaffective and bipolar disorders. A model based on an 18-item version of the PANSS generalized better across SZ and BP groups, but significant problems remained in generalizing some of the factors to the SA sample. Schizophrenia and bipolar disorder showed greater similarity in factor structure than did schizophrenia and schizoaffective disorder. The Anxiety/Depression factor was the most consistent across disorders, while the Positive factor was the least consistent. Copyright © 2017 Elsevier B.V. All rights reserved.

Towards a model of pion generalized parton distributions from Dyson-Schwinger equations

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

Moutarde, H.

2015-04-10

We compute the pion quark Generalized Parton Distribution H{sup q} and Double Distributions F{sup q} and G{sup q} in a coupled Bethe-Salpeter and Dyson-Schwinger approach. We use simple algebraic expressions inspired by the numerical resolution of Dyson-Schwinger and Bethe-Salpeter equations. We explicitly check the support and polynomiality properties, and the behavior under charge conjugation or time invariance of our model. We derive analytic expressions for the pion Double Distributions and Generalized Parton Distribution at vanishing pion momentum transfer at a low scale. Our model compares very well to experimental pion form factor or parton distribution function data.

Profile-Likelihood Approach for Estimating Generalized Linear Mixed Models with Factor Structures

ERIC Educational Resources Information Center

Jeon, Minjeong; Rabe-Hesketh, Sophia

2012-01-01

In this article, the authors suggest a profile-likelihood approach for estimating complex models by maximum likelihood (ML) using standard software and minimal programming. The method works whenever setting some of the parameters of the model to known constants turns the model into a standard model. An important class of models that can be…

Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief

PubMed Central

Pletzer, Belinda; Wood, Guilherme; Scherndl, Thomas; Kerschbaum, Hubert H.; Nuerk, Hans-Christoph

2016-01-01

Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors “Mathematical Test Anxiety” (MTA) and “Numerical Anxiety” (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established. PMID:26924996

Components of Mathematics Anxiety: Factor Modeling of the MARS30-Brief.

PubMed

Pletzer, Belinda; Wood, Guilherme; Scherndl, Thomas; Kerschbaum, Hubert H; Nuerk, Hans-Christoph

2016-01-01

Mathematics anxiety involves feelings of tension, discomfort, high arousal, and physiological reactivity interfering with number manipulation and mathematical problem solving. Several factor analytic models indicate that mathematics anxiety is rather a multidimensional than unique construct. However, the factor structure of mathematics anxiety has not been fully clarified by now. This issue shall be addressed in the current study. The Mathematics Anxiety Rating Scale (MARS) is a reliable measure of mathematics anxiety (Richardson and Suinn, 1972), for which several reduced forms have been developed. Most recently, a shortened version of the MARS (MARS30-brief) with comparable reliability was published. Different studies suggest that mathematics anxiety involves up to seven different factors. Here we examined the factor structure of the MARS30-brief by means of confirmatory factor analysis. The best model fit was obtained by a six-factor model, dismembering the known two general factors "Mathematical Test Anxiety" (MTA) and "Numerical Anxiety" (NA) in three factors each. However, a more parsimonious 5-factor model with two sub-factors for MTA and three for NA fitted the data comparably well. Factors were differentially susceptible to sex differences and differences between majors. Measurement invariance for sex was established.

[Dimensional structure of the Brazilian version of the Scale of Satisfaction with Interpersonal Processes of General Medical Care].

PubMed

Nascimento, Maria Isabel do; Reichenheim, Michael Eduardo; Monteiro, Gina Torres Rego

2011-12-01

The objective of this study was to reassess the dimensional structure of a Brazilian version of the Scale of Satisfaction with Interpersonal Processes of General Medical Care, proposed originally as a one-dimensional instrument. Strict confirmatory factor analysis (CFA) and exploratory factor analysis modeled within a CFA framework (E/CFA) were used to identify the best model. An initial CFA rejected the one-dimensional structure, while an E/CFA suggested a two-dimensional structure. The latter structure was followed by a new CFA, which showed that the model without cross-loading was the most parsimonious, with adequate fit indices (CFI = 0.982 and TLI = 0.988), except for RMSEA (0.062). Although the model achieved convergent validity, discriminant validity was questionable, with the square-root of the mean variance extracted from dimension 1 estimates falling below the respective factor correlation. According to these results, there is not sufficient evidence to recommend the immediate use of the instrument, and further studies are needed for a more in-depth analysis of the postulated structures.

DSM-5 alternative personality disorder model traits as maladaptive extreme variants of the five-factor model: An item-response theory analysis.

PubMed

Suzuki, Takakuni; Samuel, Douglas B; Pahlen, Shandell; Krueger, Robert F

2015-05-01

Over the past two decades, evidence has suggested that personality disorders (PDs) can be conceptualized as extreme, maladaptive variants of general personality dimensions, rather than discrete categorical entities. Recognizing this literature, the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) alternative PD model in Section III defines PDs partially through 25 maladaptive traits that fall within 5 domains. Empirical evidence based on the self-report measure of these traits, the Personality Inventory for DSM-5 (PID-5), suggests that these five higher-order domains share a structure and correlate in meaningful ways with the five-factor model (FFM) of general personality. In the current study, item response theory was used to compare the DSM-5 alternative PD model traits to those from a normative FFM inventory (the International Personality Item Pool-NEO [IPIP-NEO]) in terms of their measurement precision along the latent dimensions. Within a combined sample of 3,517 participants, results strongly supported the conclusion that the DSM-5 alternative PD model traits and IPIP-NEO traits are complimentary measures of 4 of the 5 FFM domains (with perhaps the exception of openness to experience vs. psychoticism). Importantly, the two measures yield largely overlapping information curves on these four domains. Differences that did emerge suggested that the PID-5 scales generally have higher thresholds and provide more information at the upper levels, whereas the IPIP-NEO generally had an advantage at the lower levels. These results support the general conceptualization that 4 domains of the DSM-5 alternative PD model traits are maladaptive, extreme versions of the FFM. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Psychometric properties of the Intrinsic Motivation Inventory in a competitive sport setting: a confirmatory factor analysis.

PubMed

McAuley, E; Duncan, T; Tammen, V V

1989-03-01

The present study was designed to assess selected psychometric properties of the Intrinsic Motivation Inventory (IMI) (Ryan, 1982), a multidimensional measure of subjects' experience with regard to experimental tasks. Subjects (N = 116) competed in a basketball free-throw shooting game, following which they completed the IMI. The LISREL VI computer program was employed to conduct a confirmatory factor analysis to assess the tenability of a five factor hierarchical model representing four first-order factors or dimensions and a second-order general factor representing intrinsic motivation. Indices of model acceptability tentatively suggest that the sport data adequately fit the hypothesized five factor hierarchical model. Alternative models were tested but did not result in significant improvements in the goodness-of-fit indices, suggesting the proposed model to be the most accurate of the models tested. Coefficient alphas for the four dimensions and the overall scale indicated adequate reliability. The results are discussed with regard to the importance of accurate assessment of psychological constructs and the use of linear structural equations in confirming the factor structures of measures.

Investigation of under-ascertainment in epidemiological studies based in general practice.

PubMed

Sethi, D; Wheeler, J; Rodrigues, L C; Fox, S; Roderick, P

1999-02-01

One of the aims of the Study of Infectious Intestinal Disease (IID) in England is to estimate the incidence of IID presenting to general practice. This sub-study aims to estimate and correct the degree of under-ascertainment in the national study. Cases of presumed IID which presented to general practice in the national study had been ascertained by their GP. In 26 general practices, cases with computerized diagnoses suggestive of IID were identified retrospectively. Cases which fulfilled the case definition of IID and should have been ascertained to the coordinating centre but were not, represented the under-ascertainment. Logistic regression modelling was used to identify independent factors which influenced under-ascertainment. The records of 2021 patients were examined, 1514 were eligible and should have been ascertained but only 974 (64%) were. There was variation in ascertainment between the practices (30% to 93%). Patient-related factors independently associated with ascertainment were: i) vomiting only as opposed to diarrhoea with and without vomiting (OR 0.37) and ii) consultation in the surgery as opposed to at home (OR 2.18). Practice-related factors independently associated with ascertainment were: i) participation in the enumeration study component (OR 1.78), ii) a larger number of partners (OR 0.3 for 7-8 partners); iii) rural location (OR 2.27) and iv) previous research experience (OR 1.92). Predicted ascertainment percentages were calculated according to practice characteristics. Under-ascertainment of IID was substantial (36%) and non-random and had to be corrected. Practice characteristics influencing variation in ascertainment were identified and a multivariate model developed to identify adjustment factors which could be applied to individual practices. Researchers need to be aware of factors which influence ascertainment in acute epidemiological studies based in general practice.

A quasi-likelihood approach to non-negative matrix factorization

PubMed Central

Devarajan, Karthik; Cheung, Vincent C.K.

2017-01-01

A unified approach to non-negative matrix factorization based on the theory of generalized linear models is proposed. This approach embeds a variety of statistical models, including the exponential family, within a single theoretical framework and provides a unified view of such factorizations from the perspective of quasi-likelihood. Using this framework, a family of algorithms for handling signal-dependent noise is developed and its convergence proven using the Expectation-Maximization algorithm. In addition, a measure to evaluate the goodness-of-fit of the resulting factorization is described. The proposed methods allow modeling of non-linear effects via appropriate link functions and are illustrated using an application in biomedical signal processing. PMID:27348511

Generalized Structured Component Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Takane, Yoshio

2004-01-01

We propose an alternative method to partial least squares for path analysis with components, called generalized structured component analysis. The proposed method replaces factors by exact linear combinations of observed variables. It employs a well-defined least squares criterion to estimate model parameters. As a result, the proposed method…

The Houdini Transformation: True, but Illusory.

PubMed

Bentler, Peter M; Molenaar, Peter C M

2012-01-01

Molenaar (2003, 2011) showed that a common factor model could be transformed into an equivalent model without factors, involving only observed variables and residual errors. He called this invertible transformation the Houdini transformation. His derivation involved concepts from time series and state space theory. This paper verifies the Houdini transformation on a general latent variable model using algebraic methods. The results show that the Houdini transformation is illusory, in the sense that the Houdini transformed model remains a latent variable model. Contrary to common knowledge, a model that is a path model with only observed variables and residual errors may, in fact, be a latent variable model.

The Houdini Transformation: True, but Illusory

PubMed Central

Bentler, Peter M.; Molenaar, Peter C. M.

2012-01-01

Molenaar (2003, 2011) showed that a common factor model could be transformed into an equivalent model without factors, involving only observed variables and residual errors. He called this invertible transformation the Houdini transformation. His derivation involved concepts from time series and state space theory. This paper verifies the Houdini transformation on a general latent variable model using algebraic methods. The results show that the Houdini transformation is illusory, in the sense that the Houdini transformed model remains a latent variable model. Contrary to common knowledge, a model that is a path model with only observed variables and residual errors may, in fact, be a latent variable model. PMID:23180888

General equation for the differential pathlength factor of the frontal human head depending on wavelength and age.

PubMed

Scholkmann, Felix; Wolf, Martin

2013-10-01

Continuous-wave near-infrared spectroscopy and near-infrared imaging enable the measurement of relative concentration changes in oxy- and deoxyhemoglobin and thus hemodynamics and oxygenation. The accuracy of determined changes depends mainly on the modeling of the light transport through the probed tissue. Due to the highly scattering nature of tissue, the light path is longer than the source-detector separation (d). This is incorporated in modeling by multiplying d by a differential pathlength factor (DPF) which depends on several factors such as wavelength, age of the subject, and type of tissue. In the present work, we derive a general DPF equation for the frontal human head, incorporating dependency on wavelength and age, based on published data. We validated the equation using different data sets of experimentally determined DPFs from six independent studies.

Endangered species toxicity extrapolation using ICE models

EPA Science Inventory

The National Research Council’s (NRC) report on assessing pesticide risks to threatened and endangered species (T&E) included the recommendation of using interspecies correlation models (ICE) as an alternative to general safety factors for extrapolating across species. ...

A Generalized Deforestation and Land-Use Change Scenario Generator for Use in Climate Modelling Studies

PubMed Central

Tompkins, Adrian Mark; Caporaso, Luca; Biondi, Riccardo; Bell, Jean Pierre

2015-01-01

A new deforestation and land-use change scenario generator model (FOREST-SAGE) is presented that is designed to interface directly with dynamic vegetation models used in latest generation earth system models. The model requires a regional-scale scenario for aggregate land-use change that may be time-dependent, provided by observational studies or by regional land-use change/economic models for future projections. These land-use categories of the observations/economic model are first translated into equivalent plant function types used by the particular vegetation model, and then FOREST-SAGE disaggregates the regional-scale scenario to the local grid-scale of the earth system model using a set of risk-rules based on factors such as proximity to transport networks, distance weighted population density, forest fragmentation and presence of protected areas and logging concessions. These rules presently focus on the conversion of forest to agriculture and pasture use, but could be generalized to other land use change conversions. After introducing the model, an evaluation of its performance is shown for the land-cover changes that have occurred in the Central African Basin from 2001–2010 using retrievals from MODerate Resolution Imaging Spectroradiometer Vegetation Continuous Field data. The model is able to broadly reproduce the spatial patterns of forest cover change observed by MODIS, and the use of the local-scale risk factors enables FOREST-SAGE to improve land use change patterns considerably relative to benchmark scenarios used in the latest Coupled Model Intercomparison Project integrations. The uncertainty to the various risk factors is investigated using an ensemble of investigations, and it is shown that the model is sensitive to the population density, forest fragmentation and reforestation factors specified. PMID:26394392

Psychometric properties of the Survey of Personal Beliefs: a rational-emotive measure of irrational thinking.

PubMed

Demaria, T P; Kassinove, H; Dill, C A

1989-01-01

A test consistency and confirmatory factor analyses were performed on the Survey of Personal Beliefs, a new measure of irrational thinking based on rational-emotive personality theory. The survey, which was logically derived, includes a general rationality factor and subscales measuring five hypothesized core categories of irrational beliefs. Subjects included a nonclinical sample of 130 men and 150 women, with a mean age of 46. Results indicated that the Survey of Personal Beliefs had satisfactory total and scale reliability. The confirmatory analyses supported a higher order factor model including 5 first-order factors ( awfulizing, self-directed shoulds, other-directed shoulds, low frustration tolerance, and self-worth) and 1 second-order or general factor.

General and specific attention-deficit/hyperactivity disorder factors of children 4 to 6 years of age: An exploratory structural equation modeling approach to assessing symptom multidimensionality.

PubMed

Arias, Víctor B; Ponce, Fernando P; Martínez-Molina, Agustín; Arias, Benito; Núñez, Daniel

2016-01-01

We tested first-order factor and bifactor models of attention-deficit/hyperactivity disorder (ADHD) using confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM) to adequately summarize the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, (DSM-IV-TR) symptoms observed in a Spanish sample of preschoolers and kindergarteners. Six ESEM and CFA models were estimated based on teacher evaluations of the behavior of 638 children 4 to 6 years of age. An ESEM bifactor model with a central dimension plus 3 specific factors (inattention, hyperactivity, and impulsivity) showed the best fit and interpretability. Strict invariance between the sexes was observed. The bifactor model provided a solution to previously encountered inconsistencies in the factorial models of ADHD in young children. However, the low reliability of the specific factors casts doubt on the utility of the subscales for ADHD measurement. More research is necessary to clarify the nature of G and S factors of ADHD. (c) 2016 APA, all rights reserved.

The use of the bi-factor model to test the uni-dimensionality of a battery of reasoning tests.

PubMed

Primi, Ricardo; Rocha da Silva, Marjorie Cristina; Rodrigues, Priscila; Muniz, Monalisa; Almeida, Leandro S

2013-02-01

The Battery of Reasoning Tests 5 (BPR-5) aims to assess the reasoning ability of individuals, using sub-tests with different formats and contents that require basic processes of inductive and deductive reasoning for their resolution. The BPR has three sequential forms: BPR-5i (for children from first to fifth grade), BPR-5 - Form A (for children from sixth to eighth grade) and BPR-5 - form B (for high school and undergraduate students). The present study analysed 412 questionnaires concerning BPR-5i, 603 questionnaires concerning BPR-5 - Form A and 1748 questionnaires concerning BPR-5 - Form B. The main goal was to test the uni-dimensionality of the battery and its tests in relation to items using the bi-factor model. Results suggest that the g factor loadings (extracted by the uni-dimensional model) do not change when the data is adjusted for a more flexible multi-factor model (bi-factor model). A general reasoning factor underlying different contents items is supported.

Generalized mathematical model of red muds’ thickener of alumina production

NASA Astrophysics Data System (ADS)

Fedorova, E. R.; Vinogradova, A. A.

2018-03-01

The article describes the principle of a generalized mathematical model of the red mud’s thickener construction. The model of the red muds’ thickener of alumina production consists of sub-models of flocculation zones containing solid fraction feed slurry, free-fall and cramped sedimentation zones or effective sedimentation zones, bleaching zones. The generalized mathematical model of thickener allows predicting the content of solid fraction in the condensed product and in the upper discharge. The sub-model of solid phase aggregation allows one to count up average size of floccules, which is created during the flocculation process in feedwell. The sub-model of the free-fall and cramped sedimentation zone allows one to count up the concentration profile taking into account the variable cross-sectional area of the thickener. The sub-model of the bleaching zone is constructed on the basis of the theory of the precipitation of Kinc, supplemented by correction factors.

Organisational quality, nurse staffing and the quality of chronic disease management in primary care: observational study using routinely collected data.

PubMed

Griffiths, Peter; Maben, Jill; Murrells, Trevor

2011-10-01

An association between quality of care and staffing levels, particularly registered nurses, has been established in acute hospitals. Recently an association between nurse staffing and quality of care for several chronic conditions has also been demonstrated for primary care in English general practice. A smaller body of literature identifies organisational factors, in particular issues of human resource management, as being a dominant factor. However the literature has tended to consider staffing and organisational factors separately. We aim to determine whether relationships between the quality of clinical care and nurse staffing in general practice are attenuated or enhanced when organisational factors associated with quality of care are considered. We further aim to determine the relative contribution and interaction between these factors. We used routinely collected data from 8409 English general practices. The data, on organisational factors and the quality of clinical care for a range of long term conditions, is gathered as part of "Quality and Outcomes Framework" pay for performance system. Regression models exploring the relationship of staffing and organisational factors with care quality were fitted using MPLUS statistical modelling software. Higher levels of nurse staffing, clinical recording, education and reflection on the results of patient surveys were significantly associated with improved clinical care for COPD, CHD, Diabetes and Hypothyroidism after controlling for organisational factors. There was some evidence of attenuation of the estimated nurse staffing effect when organisational factors were considered, but this was small. The effect of staffing interacted significantly with the effect of organisational factors. Overall however, the characteristics that emerged as the strongest predictors of quality of clinical care were not staffing levels but the organisational factors of clinical recording, education and training and use of patient experience surveys. Organisational factors contribute significantly to observed variation in the quality of care in English general practices. Levels of nurse staffing have an independent association with quality but also interact with organisational factors. The observed relationships are not necessarily causal but a causal relationship is plausible. The benefits and importance of education, training and personal development of nursing and other practice staff was clearly indicated. Copyright © 2011. Published by Elsevier Ltd.

Five Factor Model personality disorder scales: An introduction to a special section on assessment of maladaptive variants of the five factor model.

PubMed

Bagby, R Michael; Widiger, Thomas A

2018-01-01

The Five-Factor Model (FFM) is a dimensional model of general personality structure, consisting of the domains of neuroticism (or emotional instability), extraversion versus introversion, openness (or unconventionality), agreeableness versus antagonism, and conscientiousness (or constraint). The FFM is arguably the most commonly researched dimensional model of general personality structure. However, a notable limitation of existing measures of the FFM has been a lack of coverage of its maladaptive variants. A series of self-report inventories has been developed to assess for the maladaptive personality traits that define Diagnostic and Statistical Manual of Mental Disorders (fifth edition; DSM-5) Section II personality disorders (American Psychiatric Association [APA], 2013) from the perspective of the FFM. In this paper, we provide an introduction to this Special Section, presenting the rationale and empirical support for these measures and placing them in the historical context of the recent revision to the APA diagnostic manual. This introduction is followed by 5 papers that provide further empirical support for these measures and address current issues within the personality assessment literature. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

General U(1)×U(1) F-theory compactifications and beyond: geometry of unHiggsings and novel matter structure

DOE PAGES

Cvetic, Mirjam; Klevers, Denis; Piragua, Hernan; ...

2015-11-30

We construct the general form of an F-theory compactification with two U(1) factors based on a general elliptically fibered Calabi-Yau manifold with Mordell-Weil group of rank two. This construction produces broad classes of models with diverse matter spectra, including many that are not realized in earlier F-theory constructions with U(1)×U(1) gauge symmetry. Generic U(1)×U(1) models can be related to a Higgsed non-Abelian model with gauge group SU(2)×SU(2)×SU(3), SU(2) 3×SU(3), or a subgroup thereof. The nonlocal horizontal divisors of the Mordell-Weil group are replaced with local vertical divisors associated with the Cartan generators of non-Abelian gauge groups from Kodaira singularities. Wemore » give a global resolution of codimension two singularities of the Abelian model; we identify the full anomaly free matter content, and match it to the unHiggsed non-Abelian model. The non-Abelian Weierstrass model exhibits a new algebraic description of the singularities in the fibration that results in the first explicit construction of matter in the symmetric representation of SU(3). This matter is realized on double point singularities of the discriminant locus. In conclusion, the construction suggests a generalization to U(1) k factors with k > 2, which can be studied by Higgsing theories with larger non-Abelian gauge groups.« less

Health, well-being, and psychopathology in a clinical population: Structure and discriminant validity of Mental Health Continuum Short Form (MHC-SF).

PubMed

van Erp Taalman Kip, Rogier M; Hutschemaekers, Giel J M

2018-03-30

The literature suggests a distinction between illness (negative health) and the ability to cope with challenges such as illness (positive health). The two continua model of mental health distinguishes psychiatric symptoms (illness) from well-being (positive health). Well-being consists of hedonic, eudaimonic, and social well-being, constituting one factor that is moderately correlated with psychopathology in the general population. In a mental health care population, we examined whether the three dimensions of well-being are distinguishable and whether well-being is also moderately correlated with symptoms. A representative sample of 1,069 patients (63% female, 47% male; mean age: 42 years) voluntarily completed the Mental Health Continuum-Short Form (MHC-SF), a 14-item test that assesses three components of well-being. Confirmatory factor analysis revealed a model with strong correlations between the three subscales of the MHC-SF, indicating poor discriminant validity. Furthermore, the MHC-SF was strongly correlated (r = -.71) with the symptomatic distress scale of the OQ-45. Exploratory factor analysis permitted a two-factor solution, providing support for the two continua model of mental health. However, the explained variance of the second factor (well-being) was meager in comparison with the first factor (psychopathology). The results of a canonic correlation did not confirm the two continua model, and only a model with one common canonical factor was significant. For patients with clinical levels of psychopathology, the level of well-being and psychopathology correlate much higher than in the general population. Well-being and psychopathology are so entwined that the supposed distinction should be seriously questioned. © 2018 Wiley Periodicals, Inc.

A Linear Variable-[theta] Model for Measuring Individual Differences in Response Precision

ERIC Educational Resources Information Center

Ferrando, Pere J.

2011-01-01

Models for measuring individual response precision have been proposed for binary and graded responses. However, more continuous formats are quite common in personality measurement and are usually analyzed with the linear factor analysis model. This study extends the general Gaussian person-fluctuation model to the continuous-response case and…

Is the Hospital Anxiety and Depression Scale (HADS) a valid measure in a general population 65-80 years old? A psychometric evaluation study.

PubMed

Djukanovic, Ingrid; Carlsson, Jörg; Årestedt, Kristofer

2017-10-04

The HADS (Hospital Anxiety and Depression Scale) aims to measure symptoms of anxiety (HADS Anxiety) and depression (HADS Depression). The HADS is widely used but has shown ambiguous results both regarding the factor structure and sex differences in the prevalence of depressive symptoms. There is also a lack of psychometric evaluations of the HADS in non-clinical samples of older people. The aim of the study was to evaluate the factor structure of the HADS in a general population 65-80 years old and to exam possible presence of differential item functioning (DIF) with respect to sex. This study was based on data from a Swedish sample, randomized from the total population in the age group 65-80 years (n = 6659). Confirmatory factor analyses (CFA) were performed to examine the factor structure. Ordinal regression analyses were conducted to detect DIF for sex. Reliability was examined by both ordinal as well as traditional Cronbach's alpha. The CFA showed a two-factor model with cross-loadings for two items (7 and 8) had excellent model fit. Internal consistency was good in both subscales, measured with ordinal and traditional alpha. Floor effects were presented for all items. No indication for meaningful DIF regarding sex was found for any of the subscales. HADS Anxiety and HADS Depression are unidimensional measures with acceptable internal consistency and are invariant with regard to sex. Despite pronounced ceiling effects and cross-loadings for item 7 and 8, the hypothesized two-factor model of HADS can be recommended to assess psychological distress among a general population 65-80 years old.

Extension of the general thermal field equation for nanosized emitters

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

Kyritsakis, A., E-mail: akyritsos1@gmail.com; Xanthakis, J. P.

2016-01-28

During the previous decade, Jensen et al. developed a general analytical model that successfully describes electron emission from metals both in the field and thermionic regimes, as well as in the transition region. In that development, the standard image corrected triangular potential barrier was used. This barrier model is valid only for planar surfaces and therefore cannot be used in general for modern nanometric emitters. In a recent publication, the authors showed that the standard Fowler-Nordheim theory can be generalized for highly curved emitters if a quadratic term is included to the potential model. In this paper, we extend thismore » generalization for high temperatures and include both the thermal and intermediate regimes. This is achieved by applying the general method developed by Jensen to the quadratic barrier model of our previous publication. We obtain results that are in good agreement with fully numerical calculations for radii R > 4 nm, while our calculated current density differs by a factor up to 27 from the one predicted by the Jensen's standard General-Thermal-Field (GTF) equation. Our extended GTF equation has application to modern sharp electron sources, beam simulation models, and vacuum breakdown theory.« less

Extracurricular participation among children with epilepsy in Canada.

PubMed

Kamath, Sangita; Fayed, Nora; Goodman, Carly; Streiner, David L; Ronen, Gabriel M

2016-03-01

Participation in extracurricular activities creates opportunities for children to foster friendships, promote a sense of belonging, and improve physical and mental well-being. The objective of this study was to determine the relationship(s) of personal factors, seizure variables, and social supports with extracurricular participation in children with epilepsy (CWE). Baseline analysis of the QUALITÉ longitudinal study cohort of children aged 8-14 years (N=426) was conducted. Variables hypothesized to be related to the participation of CWE were classified using the International Classification of Functioning, Disability and Health according to body functions (presence of generalized tonic-clonic seizures in the past month, on/off AEDs, and seizure severity), environmental factors (perceived social support from parents and friends), and personal factors (sex, age, family structure, and family income). Analysis of variables related to extracurricular participation was conducted with regression modeling. Personal factors of age, gender, and family structure as well as body function variables of generalized tonic-clonic seizures and seizure severity were found to be the most important to extracurricular participation based on how frequently they were included in the final models (16/16 and 13/16 times, respectively). When parental support was found to be related to participation, the association was negative in 6 out of 16 models. The personal factors that are related to extracurricular participation among children with epilepsy mirror samples based on the general population, although seizures also play an important role. The relationship between perceived parental support and actual participation levels warrants further exploration. Copyright © 2015 Elsevier Inc. All rights reserved.

An evaluation of evaluative personality terms: a comparison of the big seven and five-factor model in predicting psychopathology.

PubMed

Durrett, Christine; Trull, Timothy J

2005-09-01

Two personality models are compared regarding their relationship with personality disorder (PD) symptom counts and with lifetime Axis I diagnoses. These models share 5 similar domains, and the Big 7 model also includes 2 domains assessing self-evaluation: positive and negative valence. The Big 7 model accounted for more variance in PDs than the 5-factor model, primarily because of the association of negative valence with most PDs. Although low-positive valence was associated with most Axis I diagnoses, the 5-factor model generally accounted for more variance in Axis I diagnoses than the Big 7 model. Some predicted associations between self-evaluation and psychopathology were not found, and unanticipated associations emerged. These findings are discussed regarding the utility of evaluative terms in clinical assessment.

Exploratory Study of Factors Influencing Job-Related Stress in Japanese Psychiatric Nurses

PubMed Central

Yada, Hironori; Lu, Xi; Omori, Hisamitsu; Abe, Hiroshi; Matsuo, Hisae; Ishida, Yasushi; Katoh, Takahiko

2015-01-01

This study explored the factor structure of psychiatric nurses' job-related stress and examined the specificity of the related stressors using the job stressor scale of the Brief Job Stress Questionnaire (BJSQ). The stressor scale of the BJSQ was administered to 296 nurses and assistant nurses. Answers were examined statistically. Exploratory factor analysis was performed to identify factor structures; two factors (overload and job environment) were valid. Confirmatory factor analysis was conducted to examine the two-factor structure and found 11 items with factor loadings of >0.40 (model 1), 13 items with factor loadings from 0.30 to <0.40 (model 2), and 17 items with factor loadings from 0.20 to <0.30 (model 3) for one factor; model 1 demonstrated the highest goodness of fit. Then, we observed that the two-factor structure (model 1) showed a higher goodness of fit than the original six-factor structure. This differed from subscales based on general workers' job-related stressors, suggesting that the factor structure of psychiatric nurses' job-related stressors is specific. Further steps may be necessary to reduce job-related stress specifically related to overload including attention to many needs of patients and job environment including complex ethical dilemmas in psychiatric nursing. PMID:25922763

Exploratory study of factors influencing job-related stress in Japanese psychiatric nurses.

PubMed

Yada, Hironori; Lu, Xi; Omori, Hisamitsu; Abe, Hiroshi; Matsuo, Hisae; Ishida, Yasushi; Katoh, Takahiko

2015-01-01

This study explored the factor structure of psychiatric nurses' job-related stress and examined the specificity of the related stressors using the job stressor scale of the Brief Job Stress Questionnaire (BJSQ). The stressor scale of the BJSQ was administered to 296 nurses and assistant nurses. Answers were examined statistically. Exploratory factor analysis was performed to identify factor structures; two factors (overload and job environment) were valid. Confirmatory factor analysis was conducted to examine the two-factor structure and found 11 items with factor loadings of >0.40 (model 1), 13 items with factor loadings from 0.30 to <0.40 (model 2), and 17 items with factor loadings from 0.20 to <0.30 (model 3) for one factor; model 1 demonstrated the highest goodness of fit. Then, we observed that the two-factor structure (model 1) showed a higher goodness of fit than the original six-factor structure. This differed from subscales based on general workers' job-related stressors, suggesting that the factor structure of psychiatric nurses' job-related stressors is specific. Further steps may be necessary to reduce job-related stress specifically related to overload including attention to many needs of patients and job environment including complex ethical dilemmas in psychiatric nursing.

Investigation of factors affecting the injury severity of single-vehicle rollover crashes: A random-effects generalized ordered probit model.

PubMed

Anarkooli, Alireza Jafari; Hosseinpour, Mehdi; Kardar, Adele

2017-09-01

Rollover crashes are responsible for a notable number of serious injuries and fatalities; hence, they are of great concern to transportation officials and safety researchers. However, only few published studies have analyzed the factors associated with severity outcomes of rollover crashes. This research has two objectives. The first objective is to investigate the effects of various factors, of which some have been rarely reported in the existing studies, on the injury severities of single-vehicle (SV) rollover crashes based on six-year crash data collected on the Malaysian federal roads. A random-effects generalized ordered probit (REGOP) model is employed in this study to analyze injury severity patterns caused by rollover crashes. The second objective is to examine the performance of the proposed approach, REGOP, for modeling rollover injury severity outcomes. To this end, a mixed logit (MXL) model is also fitted in this study because of its popularity in injury severity modeling. Regarding the effects of the explanatory variables on the injury severity of rollover crashes, the results reveal that factors including dark without supplemental lighting, rainy weather condition, light truck vehicles (e.g., sport utility vehicles, vans), heavy vehicles (e.g., bus, truck), improper overtaking, vehicle age, traffic volume and composition, number of travel lanes, speed limit, undulating terrain, presence of central median, and unsafe roadside conditions are positively associated with more severe SV rollover crashes. On the other hand, unpaved shoulder width, area type, driver occupation, and number of access points are found as the significant variables decreasing the probability of being killed or severely injured (i.e., KSI) in rollover crashes. Land use and side friction are significant and positively associated only with slight injury category. These findings provide valuable insights into the causes and factors affecting the injury severity patterns of rollover crashes, and thus can help develop effective countermeasures to reduce the severity of rollover crashes. The model comparison results show that the REGOP model is found to outperform the MXL model in terms of goodness-of-fit measures, and also is significantly superior to other extensions of ordered probit models, including generalized ordered probit and random-effects ordered probit (REOP) models. As a result, this research introduces REGOP as a promising tool for future research focusing on crash injury severity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimating the actual subject-specific genetic correlations in behavior genetics.

PubMed

Molenaar, Peter C M

2012-10-01

Generalization of the standard behavior longitudinal genetic factor model for the analysis of interindividual phenotypic variation to a genetic state space model for the analysis of intraindividual variation enables the possibility to estimate subject-specific heritabilities.

Constraints on the H˜ generalized parton distribution from deep virtual Compton scattering measured at HERMES

NASA Astrophysics Data System (ADS)

Guidal, M.

2010-09-01

We have analyzed the longitudinally polarized proton target asymmetry data of the Deep Virtual Compton process recently published by the HERMES Collaboration in terms of Generalized Parton Distributions. We have fitted these new data in a largely model-independent fashion and the procedure results in numerical constraints on the accent="true">H˜Im Compton Form Factor. We present its t- and ξ-dependencies. We also find improvement on the determination of two other Compton Form Factors, HRe and HIm.

Critical factors for EIA implementation: literature review and research options.

PubMed

Zhang, Jie; Kørnøv, Lone; Christensen, Per

2013-01-15

After decades of development, the gap between expectations of Environment Impact Assessments (EIA) and their practical performance remains significant. Research has been done to identify the critical factors for an effective implementation of EIA. However, this research, to a large extent, has not been cumulated and analysed comprehensively according to the stages of the EIA process. This paper contributes to the critical review of the literature on EIA implementation and effectiveness by cumulating mainly empirical findings in an implementation theoretical perspective. It focuses on the links between different critical factors and how they relate to different stages in the EIA and thus influence the decision making process. After reviewing 33 refereed journal articles published between 1999 and 2011, we identified 203 notions of critical factors. Of these, 102 related to different stages defined in our comprehensive EIA implementation model, and 101 were identified as general factors related to the whole EIA system. The number of notions of stage factors and general factors is thus about equal. An overlap between stage factors and general factors was found, which demonstrates that critical factors function differently in different cases. The function of the critical factors is complex and it is difficult to determine contingencies and causations. In the sources we examined, there is evidently an imbalance between in-depth empirical research and general knowledge, and the paper offers some suggestions for future research. Copyright © 2012 Elsevier Ltd. All rights reserved.

42 CFR § 510.300 - Determination of episode target prices.

Code of Federal Regulations, 2010 CFR

2016-10-01

... SERVICES (CONTINUED) HEALTH CARE INFRASTRUCTURE AND MODEL PROGRAMS COMPREHENSIVE CARE FOR JOINT REPLACEMENT MODEL Pricing and Payment § 510.300 Determination of episode target prices. (a) General. CMS establishes... expenditures from the CJR model as described in this section. (1) Discount factor for reconciliation payments...

A Survey of Model Evaluation Approaches with a Tutorial on Hierarchical Bayesian Methods

ERIC Educational Resources Information Center

Shiffrin, Richard M.; Lee, Michael D.; Kim, Woojae; Wagenmakers, Eric-Jan

2008-01-01

This article reviews current methods for evaluating models in the cognitive sciences, including theoretically based approaches, such as Bayes factors and minimum description length measures; simulation approaches, including model mimicry evaluations; and practical approaches, such as validation and generalization measures. This article argues…

Right Fronto-Subcortical White Matter Microstructure Predicts Cognitive Control Ability on the Go/No-go Task in a Community Sample.

PubMed

Hinton, Kendra E; Lahey, Benjamin B; Villalta-Gil, Victoria; Boyd, Brian D; Yvernault, Benjamin C; Werts, Katherine B; Plassard, Andrew J; Applegate, Brooks; Woodward, Neil D; Landman, Bennett A; Zald, David H

2018-01-01

Go/no-go tasks are widely used to index cognitive control. This construct has been linked to white matter microstructure in a circuit connecting the right inferior frontal gyrus (IFG), subthalamic nucleus (STN), and pre-supplementary motor area. However, the specificity of this association has not been tested. A general factor of white matter has been identified that is related to processing speed. Given the strong processing speed component in successful performance on the go/no-go task, this general factor could contribute to task performance, but the general factor has often not been accounted for in past studies of cognitive control. Further, studies on cognitive control have generally employed small unrepresentative case-control designs. The present study examined the relationship between go/no-go performance and white matter microstructure in a large community sample of 378 subjects that included participants with a range of both clinical and subclinical nonpsychotic psychopathology. We found that white matter microstructure properties in the right IFG-STN tract significantly predicted task performance, and remained significant after controlling for dimensional psychopathology. The general factor of white matter only reached statistical significance when controlling for dimensional psychopathology. Although the IFG-STN and general factor tracts were highly correlated, when both were included in the model, only the IFG-STN remained a significant predictor of performance. Overall, these findings suggest that while a general factor of white matter can be identified in a young community sample, white matter microstructure properties in the right IFG-STN tract show a specific relationship to cognitive control. The findings highlight the importance of examining both specific and general correlates of cognition, especially in tasks with a speeded component.

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.

The structure of DSM-IV-TR personality disorder diagnoses in NESARC: a reanalysis.

PubMed

Trull, Timothy J; Vergés, Alvaro; Wood, Phillip K; Sher, Kenneth J

2013-12-01

Cox, Clara, Worobec, and Grant (2012) recently presented results from a series of analyses aimed at identifying the factor structure underlying the DSM-IV-TR (APA, 2000) personality diagnoses assessed in the large NESARC study. Cox et al. (2012) concluded that the best fitting model was one that modeled three lower-order factors (the three clusters of PDs as outlined by DSM-IV-TR), which in turn loaded on a single PD higher-order factor. Our reanalyses of the NESARC Wave 1 and Wave 2 data for personality disorder diagnoses revealed that the best fitting model was that of a general PD factor that spans each of the ten DSM-IV PD diagnoses, and our reanalyses do not support the three-cluster hierarchical structure outlined by Cox et al. (2012) and DSM-IV-TR. Finally, we note the importance of modeling the Wave 2 assessment method factor in analyses of NESARC PD data.

Understanding the Home Math Environment and Its Role in Predicting Parent Report of Children's Math Skills.

PubMed

Hart, Sara A; Ganley, Colleen M; Purpura, David J

2016-01-01

There is a growing literature concerning the role of the home math environment in children's math development. In this study, we examined the relation between these constructs by specifically addressing three goals. The first goal was to identify the measurement structure of the home math environment through a series of confirmatory factor analyses. The second goal was to examine the role of the home math environment in predicting parent report of children's math skills. The third goal was to test a series of potential alternative explanations for the relation between the home math environment and parent report of children's skills, specifically the direct and indirect role of household income, parent math anxiety, and parent math ability as measured by their approximate number system performance. A final sample of 339 parents of children aged 3 through 8 drawn from Mechanical Turk answered a questionnaire online. The best fitting model of the home math environment was a bifactor model with a general factor representing the general home math environment, and three specific factors representing the direct numeracy environment, the indirect numeracy environment, and the spatial environment. When examining the association of the home math environment factors to parent report of child skills, the general home math environment factor and the spatial environment were the only significant predictors. Parents who reported doing more general math activities in the home reported having children with higher math skills, whereas parents who reported doing more spatial activities reported having children with lower math skills.

Understanding the Home Math Environment and Its Role in Predicting Parent Report of Children’s Math Skills

PubMed Central

Ganley, Colleen M.; Purpura, David J.

2016-01-01

There is a growing literature concerning the role of the home math environment in children’s math development. In this study, we examined the relation between these constructs by specifically addressing three goals. The first goal was to identify the measurement structure of the home math environment through a series of confirmatory factor analyses. The second goal was to examine the role of the home math environment in predicting parent report of children’s math skills. The third goal was to test a series of potential alternative explanations for the relation between the home math environment and parent report of children’s skills, specifically the direct and indirect role of household income, parent math anxiety, and parent math ability as measured by their approximate number system performance. A final sample of 339 parents of children aged 3 through 8 drawn from Mechanical Turk answered a questionnaire online. The best fitting model of the home math environment was a bifactor model with a general factor representing the general home math environment, and three specific factors representing the direct numeracy environment, the indirect numeracy environment, and the spatial environment. When examining the association of the home math environment factors to parent report of child skills, the general home math environment factor and the spatial environment were the only significant predictors. Parents who reported doing more general math activities in the home reported having children with higher math skills, whereas parents who reported doing more spatial activities reported having children with lower math skills. PMID:28005925

Dimensions and categories: the "big five" factors and the DSM personality disorders.

PubMed

Morey, L C; Gunderson, J; Quigley, B D; Lyons, M

2000-09-01

The five-factor model of personality, which has been widely studied in personality psychology, has been hypothesized to have specific relevance for DSM-defined personality disorders. To evaluate hypothesized relationships of the five-factor model of personality to personality disorders, 144 patients with personality disorders (diagnosed via a structured interview) completed an inventory to assess the five-factor model. Results indicated that the majority of the personality disorders can be differentiated in theoretically predictable ways using the five-factor model of personality. However, while the personality disorders as a whole appear to be differentiable from normal personality functioning on the five factors, the patterns are quite similar across the disorders, a finding that may provide some insight into the general nature of personality pathology but may also suggest problems with discriminant validity. Third, it does not appear that considering disorders as special combinations of features (as might be expected in some categorical models) is more informative than considering them as the sum of certain features (as might be expected in a dimensional model).

The Kansas Collaborative Research Network, KanCRN: Teaching science content through process

NASA Astrophysics Data System (ADS)

Case, Steven B.

The Kansas Collaborative Research Network, KanCRN is an Internet-based research community, in which citizens, teachers and students can engage in authentic, meaningful scientific inquiry. Recent efforts to reform science education in the United States have strongly emphasized that understanding of the nature of science is an essential component of general scientific literacy. The National Science Education Standards suggest that engaging students in scientific inquiry is one opportunity to develop an understanding of the nature of science. Extending the philosophical understanding of science to specific science classroom organization, KanCRN is large-scale, systemic project that attempts to achieve the vision of scientific inquiry in the National Science Education Standards. The underlying question of standards-based reform still remains; does participation in scientific inquiry provide compelling evidence of an increase in the understanding of the process of science and the ability to apply these skills in novel situations? This study took advantage of the Kansas City Kansas Public Schools involvement in districtwide systemic reform, First Things First. Each year the students in grades 3--12 complete a district First Things First questionnaire. Since longitudinal measures of student attitudes are generally difficult to obtain, this study tapped into this wealth of attitude measures gained from these questionnaires. These data sets include general demographics of the students, attitudinal data toward school and learning, and general achievement data. Running a factor analysis on these data sets allowed factoring out the influence of non-critical variables. In running this initial factor analysis of the First Things First data sets, several factors emerged as related to student's academic success on the Science Performance Assessment; Academic Effort, Teacher Quality, Project-based Learning, General Academic Ability (Self-Attitude Data), and Parental Support. Using the technique of Structural Equation Modeling, these factors were combined with participation in the KanCRN research model; this study created and tested a model of science classroom variables related to scores on a science performance assessment. Models were run separately for samples of middle school students (grades 6--8) and high school students (grades 9--12). The middle school model indicates that participation in the KanCRN research model is an independent, positive, direct, and meaningful predictor of science performance. Examination of the magnitude of the standardized coefficients and the R 2 values indicates that 27% of the variance on science achievement is accounted for by the middle school model. The high school model indicated that student attitudes were unrelated to KanCRN participation however, the relationship between participation in KanCRN and students performance on the assessment was not a significant path. Examination of the magnitude of the standardized coefficients and the R2 values for the high school model indicates that 7% of the variance on science achievement is accounted for by the model. This is identical the explanatory power of the high school model that only included information about KanCRN participation and student background characteristics, but leaving out the attitude data. The finding that KanCRN participation is significant at the middle school and is insignificant at the high school raises a number of interesting questions that requires further investigation.

Estimating plant available water for general crop simulations in ALMANAC/APEX/EPIC/SWAT

USDA-ARS?s Scientific Manuscript database

Process-based simulation models ALMANAC/APEX/EPIC/SWAT contain generalized plant growth subroutines to predict biomass and crop yield. Environmental constraints typically restrict plant growth and yield. Water stress is often an important limiting factor; it is calculated as the sum of water use f...

Disentangling depression and anxiety in relation to neuroticism, extraversion, suicide, and self-harm among adult psychiatric inpatients with serious mental illness.

PubMed

Subica, Andrew M; Allen, Jon G; Frueh, B Christopher; Elhai, Jon D; Fowler, J Christopher

2016-11-01

Little is known about depression-anxiety comorbidity and its association with personality traits and suicide/self-harm in adult psychiatric inpatients with serious mental illness (SMI), impacting clinical assessment and treatment. This study sought to determine the symptom structure of depression-anxiety comorbidity and its relation to neuroticism, extraversion, and suicide/self-harm behaviour in this high-risk population. Nine hundred and sixty-two adults receiving inpatient care at a private psychiatric hospital completed questionnaires at admission. Confirmatory factor analyses compared a bifactor solution specifying a general distress factor and two specific depression and anxiety factors against unidimensional and correlated factors solutions. The bifactor solutions' factors were subsequently correlated with neuroticism and extraversion subscales and pre-hospitalization suicide/self-harm behaviours. The bifactor model rendered superior fit to sample data and a robust general factor - accounting for 77.61% of common item variance - providing the first evidence for a tripartite structure of depression and anxiety among adult inpatients. The bifactor solution-outputted independent general distress, depression, and anxiety factors positively correlated with neuroticism, the personality dimension corresponding to trait negative affectivity. The general distress and depression factors associated with recent self-harm, but factors showed no associations with prior suicidal behaviour. In adult psychiatric inpatients, general distress substantially underlies comorbid depression and anxiety symptom variation and may contribute to recent incidence of self-harm. Transdiagnostic assessments and interventions targeting general distress may temper depression, anxiety, and self-harm in adult inpatients. Clinical implications Depression-anxiety comorbidity symptomology in adult psychiatric inpatients is primarily composed of general distress. General distress and specific depression are associated with recent self-harm but not suicidal behaviour. Assessing and treating general distress rather than depression or anxiety specifically may best mitigate comorbid depression and anxiety, and reduce self-harm behaviour in this clinical population. Cautions and limitations The large sample lacked ethnocultural diversity, and data were cross-sectional. The use of brief self-report measures to assess depression and anxiety may have reduced measurement range. © 2015 The British Psychological Society.

Contaminant deposition building shielding factors for US residential structures.

PubMed

Dickson, Elijah; Hamby, David; Eckerman, Keith

2017-10-10

This paper presents validated building shielding factors designed for contemporary US housing-stock under an idealized, yet realistic, exposure scenario from contaminant deposition on the roof and surrounding surfaces. The building shielding factors are intended for use in emergency planning and level three probabilistic risk assessments for a variety of postulated radiological events in which a realistic assessment is necessary to better understand the potential risks for accident mitigation and emergency response planning. Factors are calculated from detailed computational housing-units models using the general-purpose Monte Carlo N-Particle computational code, MCNP5, and are benchmarked from a series of narrow- and broad-beam measurements analyzing the shielding effectiveness of ten common general-purpose construction materials and ten shielding models representing the primary weather barriers (walls and roofs) of likely US housing-stock. Each model was designed to scale based on common residential construction practices and include, to the extent practical, all structurally significant components important for shielding against ionizing radiation. Calculations were performed for floor-specific locations from contaminant deposition on the roof and surrounding ground as well as for computing a weighted-average representative building shielding factor for single- and multi-story detached homes, both with and without basement as well for single-wide manufactured housing-unit. © 2017 IOP Publishing Ltd.

Contaminant deposition building shielding factors for US residential structures.

PubMed

Dickson, E D; Hamby, D M; Eckerman, K F

2015-06-01

This paper presents validated building shielding factors designed for contemporary US housing-stock under an idealized, yet realistic, exposure scenario from contaminant deposition on the roof and surrounding surfaces. The building shielding factors are intended for use in emergency planning and level three probabilistic risk assessments for a variety of postulated radiological events in which a realistic assessment is necessary to better understand the potential risks for accident mitigation and emergency response planning. Factors are calculated from detailed computational housing-units models using the general-purpose Monte Carlo N-Particle computational code, MCNP5, and are benchmarked from a series of narrow- and broad-beam measurements analyzing the shielding effectiveness of ten common general-purpose construction materials and ten shielding models representing the primary weather barriers (walls and roofs) of likely US housing-stock. Each model was designed to scale based on common residential construction practices and include, to the extent practical, all structurally significant components important for shielding against ionizing radiation. Calculations were performed for floor-specific locations from contaminant deposition on the roof and surrounding ground as well as for computing a weighted-average representative building shielding factor for single- and multi-story detached homes, both with and without basement as well for single-wide manufactured housing-unit.

Paranormal experiences in the general population.

PubMed

Ross, C A; Joshi, S

1992-06-01

The Dissociative Disorders Interview Schedule was administered to a random sample of 502 adults in the general population of Winnipeg, a midwestern Canadian city. Results showed that paranormal/extrasensory experiences were common in the general population. They were linked to a history of childhood trauma and to other dissociative symptom clusters. A factor analysis of the paranormal experiences identified three factors which together accounted for 44.0% of the combined variance of the scores. A model is proposed in which paranormal experiences are conceptualized as an aspect of normal dissociation. Like dissociation in general, paranormal experiences can be triggered by trauma, especially childhood physical or sexual abuse. Such experiences discriminate individuals with childhood trauma histories from those without at high levels of significance.

Multimodal electromechanical model of piezoelectric transformers by Hamilton's principle.

PubMed

Nadal, Clement; Pigache, Francois

2009-11-01

This work deals with a general energetic approach to establish an accurate electromechanical model of a piezoelectric transformer (PT). Hamilton's principle is used to obtain the equations of motion for free vibrations. The modal characteristics (mass, stiffness, primary and secondary electromechanical conversion factors) are also deduced. Then, to illustrate this general electromechanical method, the variational principle is applied to both homogeneous and nonhomogeneous Rosen-type PT models. A comparison of modal parameters, mechanical displacements, and electrical potentials are presented for both models. Finally, the validity of the electrodynamical model of nonhomogeneous Rosen-type PT is confirmed by a numerical comparison based on a finite elements method and an experimental identification.

The making of the modern airport executive: Causal connections among key attributes in career development, compromise, and satisfaction in airport management

NASA Astrophysics Data System (ADS)

Byers, David Alan

The purpose of this study was to identify specific career development attributes of contemporary senior-level airport executives and to evaluate the relationship of these attributes to the level of satisfaction airport executives have in their career choice. Attribute sets that were examined included early aviation interests, health factors, psychological factors, demographic factors, formal education, and other aviation-related experiences. A hypothesized causal model that expressed direct and indirect effects among these attributes relative to airport executives' career satisfaction was tested using sample data collected from 708 airport executives from general aviation and commercial service airport throughout the United States. Applying a multiple regression analysis strategy to the model, the overall results revealed that 16% of the variability in airport executives' career satisfaction scores was due to the collective influence of the six research attribute sets, this was significant. The results of the path analysis also indicated that four attribute sets (early aviation interests, health factors, formal education, and other aviation-related experiences) had respective direct significant effects on participants' career satisfaction. Early aviation interests, health factors, and demographic factors had additional indirect effects on career satisfaction; all were mediated by formal education attitude. These results were inconsistent with the hypothesized path model and a revised model was developed to reflect the sample data. The findings suggest that airport executives, as a group, are satisfied with their career choice. Early aviation interests appear to play an important role for influencing the career field selection phase of career development. The study also suggests health factors, formal education, and other aviation-related experiences such as flight training or military experience influence the compromise phase of career development. Each of these four factors had significant effects on career satisfaction. In addition to its applicability to airport executives, the study provides a generalized path model for investigating factors influencing the career development, compromise, and satisfaction process in other vocations.

Experience with a vectorized general circulation weather model on Star-100

NASA Technical Reports Server (NTRS)

Soll, D. B.; Habra, N. R.; Russell, G. L.

1977-01-01

A version of an atmospheric general circulation model was vectorized to run on a CDC STAR 100. The numerical model was coded and run in two different vector languages, CDC and LRLTRAN. A factor of 10 speed improvement over an IBM 360/95 was realized. Efficient use of the STAR machine required some redesigning of algorithms and logic. This precludes the application of vectorizing compilers on the original scalar code to achieve the same results. Vector languages permit a more natural and efficient formulation for such numerical codes.

Characterizing the Intersection of Co-Occurring Risk Factors for Illicit Drug Abuse and Dependence in a U.S. Nationally Representative Sample

PubMed Central

Kurti, Allison N.; Keith, Diana R.; Noble, Alyssa; Priest, Jeff S.; Sprague, Brian; Higgins, Stephen T.

2016-01-01

Few studies have attempted to characterize how co-occurring risk factors for substance use disorders intersect. A recent study examined this question regarding cigarette smoking and demonstrated that co-occurring risk factors generally act independently. The present study examines whether that same pattern of independent intersection of risk factors extends to illicit drug abuse/dependence using a U.S. nationally representative sample (National Survey on Drug Use and Health, 2011–2013). Logistic regression and classification and regression tree (CART) modeling were used to examine risk of past-year drug abuse/dependence associated with a well-established set of risk factors for substance use (age, gender, race/ethnicity, education, poverty, smoking status, alcohol abuse/dependence, mental illness). Each of these risk factors was associated with significant increases in the odds of drug abuse/dependence in univariate logistic regressions. Each remained significant in a multivariate model examining all eight risk factors simultaneously. CART modeling of these 8 risk factors identified subpopulation risk profiles wherein drug abuse/dependence prevalence varied from < 1% to > 80% corresponding to differing combinations of risk factors present. Alcohol abuse/dependence and cigarette smoking had the strongest associations with drug abuse/dependence risk. These results demonstrate that co-occurring risk factors for illicit drug/abuse dependence generally intersect in the same independent manner as risk factors for cigarette smoking, underscoring further fundamental commonalities across these different types of substance use disorders. These results also underscore the fundamental importance of differences in the presence of co-occurring risk factors when considering the often strikingly different prevalence rates of illicit drug abuse/dependence in U.S. population subgroups. PMID:27687534

An antenna model for the Purcell effect

PubMed Central

Krasnok, Alexander E.; Slobozhanyuk, Alexey P.; Simovski, Constantin R.; Tretyakov, Sergei A.; Poddubny, Alexander N.; Miroshnichenko, Andrey E.; Kivshar, Yuri S.; Belov, Pavel A.

2015-01-01

The Purcell effect is defined as a modification of the spontaneous emission rate of a quantum emitter at the presence of a resonant cavity. However, a change of the emission rate of an emitter caused by an environment has a classical counterpart. Any small antenna tuned to a resonance can be described as an oscillator with radiative losses, and the effect of the environment on its radiation can be modeled and measured in terms of the antenna radiation resistance, similar to a quantum emitter. We exploit this analogue behavior to develop a general approach for calculating the Purcell factors of different systems and various frequency ranges including both electric and magnetic Purcell factors. Our approach is illustrated by a general equivalent scheme, and it allows resenting the Purcell factor through the continuous radiation of a small antenna at the presence of an electromagnetic environment. PMID:26256529

Psychometric Features of the General Aptitude Test-Verbal Part (GAT-V): A Large-Scale Assessment of High School Graduates in Saudi Arabia

ERIC Educational Resources Information Center

Dimitrov, Dimiter M.; Shamrani, Abdul Rahman

2015-01-01

This study examines the psychometric features of a General Aptitude Test-Verbal Part, which is used with assessments of high school graduates in Saudi Arabia. The data supported a bifactor model, with one general factor and three content domains (Analogy, Sentence Completion, and Reading Comprehension) as latent aspects of verbal aptitude.

Confirmatory Factor Analysis of the Behavior Rating Inventory of Executive Function-Adult Version in Healthy Adults and Application to Attention-Deficit/Hyperactivity Disorder

PubMed Central

Roth, Robert M.; Lance, Charles E.; Isquith, Peter K.; Fischer, Adina S.; Giancola, Peter R.

2013-01-01

The Behavior Rating Inventory of Executive Function-Adult Version (BRIEF-A) is a questionnaire measure designed to assess executive functioning in everyday life. Analysis of data from the BRIEF-A standardization sample yielded a two-factor solution (labeled Behavioral Regulation and Metacognition). The present investigation employed confirmatory factor analysis (CFA) to evaluate four alternative models of the factor structure of the BRIEF-A self-report form in a sample of 524 healthy young adults. Results indicated that a three-factor model best fits the data: a Metacognition factor, a Behavioral Regulation factor consisting of the Inhibit and Self-Monitor scales, and an Emotional Regulation factor composed of the Emotional Control and Shift scales. The three factors contributed 14%, 19%, and 24% of unique variance to the model, respectively, and a second-order general factor accounted for 41% of variance overall. This three-factor solution is consistent with recent CFAs of the Parent report form of the BRIEF. Furthermore, although the Behavioral Regulation factor score in the two-factor model did not differ between adults with attention-deficit/hyperactivity disorder and a matched healthy comparison group, greater impairment on the Behavioral Regulation factor but not the Emotional Regulation factor was found using the three-factor model. Together, these findings support the multidimensional nature of executive function and the clinical relevance of a three-factor model of the BRIEF-A. PMID:23676185

Measurement: The Boon and Bane of Investigating Religion.

ERIC Educational Resources Information Center

Gorsuch, Richard L.

1984-01-01

A major problem of research into religion is whether religion is uni- or multi-dimensional; a model maintaining the advantages of both approaches is suggested with general religiousness as a broad construct (higher order factor) that is subdivided into a set of more specific factors. (CMG)

Orthogonal Higher Order Structure and Confirmatory Factor Analysis of the French Wechsler Adult Intelligence Scale (WAIS-III)

ERIC Educational Resources Information Center

Golay, Philippe; Lecerf, Thierry

2011-01-01

According to the most widely accepted Cattell-Horn-Carroll (CHC) model of intelligence measurement, each subtest score of the Wechsler Intelligence Scale for Adults (3rd ed.; WAIS-III) should reflect both 1st- and 2nd-order factors (i.e., 4 or 5 broad abilities and 1 general factor). To disentangle the contribution of each factor, we applied a…

[Mathematic concept model of accumulation of functional disorders associated with environmental factors].

PubMed

Zaĭtseva, N V; Trusov, P V; Kir'ianov, D A

2012-01-01

The mathematic concept model presented describes accumulation of functional disorders associated with environmental factors, plays predictive role and is designed for assessments of possible effects caused by heterogenous factors with variable exposures. Considering exposure changes with self-restoration process opens prospects of using the model to evaluate, analyse and manage occupational risks. To develop current theoretic approaches, the authors suggested a model considering age-related body peculiarities, systemic interactions of organs, including neuro-humoral regulation, accumulation of functional disorders due to external factors, rehabilitation of functions during treatment. General objective setting covers defining over a hundred unknow coefficients that characterize speed of various processes within the body. To solve this problem, the authors used iteration approach, successive identification, that starts from the certain primary approximation of the model parameters and processes subsequent updating on the basis of new theoretic and empirical knowledge.

Evaluating the Evidence for the General Factor of Personality across Multiple Inventories

PubMed Central

Hopwood, Christopher J.; Wright, Aidan G.C.; Donnellan, M. Brent

2012-01-01

A general factor of personality (GFP) has been proposed as the apex of a personality trait hierarchy that explains covariance among the lower-order factors measured by various personality inventories. In this study we evaluated the GFP hypothesis across several personality inventories, unlike most previous research in which the GFP has been derived from individual instruments in isolation. Exploratory analyses did not produce substantial evidence for the existence of a single cross-instrument higher-order factor of factors and efforts to specify a range of GFP-inspired models in a confirmatory framework led to significant estimation difficulties and poor fit to the data. Overall these results fail to support a common GFP that is positioned at the top of a personality trait hierarchy. PMID:22879686

Implicit theories of a desire for fame.

PubMed

Maltby, John; Day, Liz; Giles, David; Gillett, Raphael; Quick, Marianne; Langcaster-James, Honey; Linley, P Alex

2008-05-01

The aim of the present studies was to generate implicit theories of a desire for fame among the general population. In Study 1, we were able to develop a nine-factor analytic model of conceptions of the desire to be famous that initially comprised nine separate factors; ambition, meaning derived through comparison with others, psychologically vulnerable, attention seeking, conceitedness, social access, altruistic, positive affect, and glamour. Analysis that sought to examine replicability among these factors suggested that three factors (altruistic, positive affect, and glamour) neither display factor congruence nor display adequate internal reliability. A second study examined the validity of these factors in predicting profiles of individuals who may desire fame. The findings from this study suggested that two of the nine factors (positive affect and altruism) could not be considered strong factors within the model. Overall, the findings suggest that implicit theories of a desire for fame comprise six factors. The discussion focuses on how an implicit model of a desire for fame might progress into formal theories of a desire for fame.

Different neurodevelopmental symptoms have a common genetic etiology.

PubMed

Pettersson, Erik; Anckarsäter, Henrik; Gillberg, Christopher; Lichtenstein, Paul

2013-12-01

Although neurodevelopmental disorders are demarcated as discrete entities in the Diagnostic Statistical Manual of mental disorders, empirical evidence indicates that there is a high degree of overlap among them. The first aim of this investigation was to explore if a single general factor could account for the large degree of observed overlap among neurodevelopmental problems, and explore whether this potential factor was primarily genetic or environmental in origin. The second aim was to explore whether there was systematic covariation, either genetic or environmental, over and above that contributed by the potential general factor, unique to each syndrome. Parents of all Swedish 9- and 12-year-old twin pairs born between 1992 and 2002 were targeted for interview regarding problems typical of autism spectrum disorders, ADHD and other neurodevelopmental conditions (response rate: 80 percent). Structural equation modeling was conducted on 6,595 pairs to examine the genetic and environmental structure of 53 neurodevelopmental problems. One general genetic factor accounted for a large proportion of the phenotypic covariation among the 53 symptoms. Three specific genetic subfactors identified 'impulsivity,' 'learning problems,' and 'tics and autism,' respectively. Three unique environment factors identified 'autism,' 'hyperactivity and impulsivity,' and 'inattention and learning problems,' respectively. One general genetic factor was responsible for the wide-spread phenotypic overlap among all neurodevelopmental symptoms, highlighting the importance of addressing broad patient needs rather than specific diagnoses. The unique genetic factors may help guide diagnostic nomenclature, whereas the unique environmental factors may highlight that neurodevelopmental symptoms are responsive to change at the individual level and may provide clues into different mechanisms and treatments. Future research would benefit from assessing the general factor separately from specific factors to better understand observed overlap among neurodevelopmental problems. © 2013 The Authors. Journal of Child Psychology and Psychiatry © 2013 Association for Child and Adolescent Mental Health.

The NEO Five-Factor Inventory: Latent Structure and Relationships with Dimensions of Anxiety and Depressive Disorders in a Large Clinical Sample

ERIC Educational Resources Information Center

Rosellini, Anthony J.; Brown, Timothy A.

2011-01-01

The present study evaluated the latent structure of the NEO Five-Factor Inventory (NEO FFI) and relations between the five-factor model (FFM) of personality and dimensions of "DSM-IV" anxiety and depressive disorders (panic disorder, generalized anxiety disorder [GAD], obsessive-compulsive disorder, social phobia [SOC], major depressive disorder…

The accuracy of climate models' simulated season lengths and the effectiveness of grid scale correction factors

DOE PAGES

Winterhalter, Wade E.

2011-09-01

Global climate change is expected to impact biological populations through a variety of mechanisms including increases in the length of their growing season. Climate models are useful tools for predicting how season length might change in the future. However, the accuracy of these models tends to be rather low at regional geographic scales. Here, I determined the ability of several atmosphere and ocean general circulating models (AOGCMs) to accurately simulate historical season lengths for a temperate ectotherm across the continental United States. I also evaluated the effectiveness of regional-scale correction factors to improve the accuracy of these models. I foundmore » that both the accuracy of simulated season lengths and the effectiveness of the correction factors to improve the model's accuracy varied geographically and across models. These results suggest that regional specific correction factors do not always adequately remove potential discrepancies between simulated and historically observed environmental parameters. As such, an explicit evaluation of the correction factors' effectiveness should be included in future studies of global climate change's impact on biological populations.« less

Biotic and abiotic factors predicting the global distribution and population density of an invasive large mammal

PubMed Central

Lewis, Jesse S.; Farnsworth, Matthew L.; Burdett, Chris L.; Theobald, David M.; Gray, Miranda; Miller, Ryan S.

2017-01-01

Biotic and abiotic factors are increasingly acknowledged to synergistically shape broad-scale species distributions. However, the relative importance of biotic and abiotic factors in predicting species distributions is unclear. In particular, biotic factors, such as predation and vegetation, including those resulting from anthropogenic land-use change, are underrepresented in species distribution modeling, but could improve model predictions. Using generalized linear models and model selection techniques, we used 129 estimates of population density of wild pigs (Sus scrofa) from 5 continents to evaluate the relative importance, magnitude, and direction of biotic and abiotic factors in predicting population density of an invasive large mammal with a global distribution. Incorporating diverse biotic factors, including agriculture, vegetation cover, and large carnivore richness, into species distribution modeling substantially improved model fit and predictions. Abiotic factors, including precipitation and potential evapotranspiration, were also important predictors. The predictive map of population density revealed wide-ranging potential for an invasive large mammal to expand its distribution globally. This information can be used to proactively create conservation/management plans to control future invasions. Our study demonstrates that the ongoing paradigm shift, which recognizes that both biotic and abiotic factors shape species distributions across broad scales, can be advanced by incorporating diverse biotic factors. PMID:28276519

Game analysis and benefit allocation in international projects among owner, supervisor and contractor

NASA Astrophysics Data System (ADS)

Ding, Hao; Wang, Yong; Guo, Sini; Xu, Xiaofeng; Che, Cheng

2016-04-01

International projects are different from general domestic ones. In order to analyse the differences, a tripartite game model is built up to describe the relationship among owner, supervisor and general contractor, and some measures are given for the owner to more effectively complete the project. In addition, a project schedule selection model is formulated and a new benefit allocation method is proposed by introducing a new modified Shapley value with weighted factor.

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

PubMed Central

Kheirollahpour, Maryam; Shohaimi, Shamarina

2014-01-01

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

General practice registrars' intentions for future practice: implications for rural medical workforce planning.

PubMed

Harding, Catherine; Seal, Alexa; McGirr, Joe; Caton, Tim

2016-11-01

The models of practice that general practice registrars (GPRs) envisage undertaking will affect workforce supply. The aim of this research was to determine practice intentions of current GPRs in a regional general practice training program (Coast City Country General Practice Training). Questionnaires were circulated to 220 GPRs undertaking general practice placements to determine characteristics of ideal practice models and intentions for future practice. Responses were received for 99 participants (45%). Current GPRs intend to work an average of less than eight half-day sessions/week, with male participants intending to work more hours (t(91)=3.528, P=0.001). More than one-third of this regional cohort intends to practice in metropolitan centres. Proximity to family and friends was the most important factor influencing the choice of practice location. Men ranked remuneration for work as more important (t (88)=-4.280, P<0.001) and women ranked the ability to work part-time higher (t(94)=3.697, P<0.001). Fee-for-service payment alone, or in combination with capitation, was the preferred payment system. Only 22% of Australian medical graduates intend to own their own practice compared with 52% of international medical graduates (χ 2 (1)=8.498, P=0.004). Future general practitioners (GPs) intend to work fewer hours than current GPs. Assumptions about lifestyle factors, practice models and possible professional roles should be carefully evaluated when developing strategies to recruit GPs and GPRs into rural practice.

Examining the validity of the Homework Performance Questionnaire: Multi-informant assessment in elementary and middle school.

PubMed

Power, Thomas J; Watkins, Marley W; Mautone, Jennifer A; Walcott, Christy M; Coutts, Michael J; Sheridan, Susan M

2015-06-01

Methods for measuring homework performance have been limited primarily to parent reports of homework deficits. The Homework Performance Questionnaire (HPQ) was developed to assess the homework functioning of students in Grades 1 to 8 from the perspective of both teachers and parents. The purpose of this study was to examine the factorial validity of teacher and parent versions of this scale, and to evaluate gender and grade-level differences in factor scores. The HPQ was administered in 4 states from varying regions of the United States. The validation sample consisted of students (n = 511) for whom both parent and teacher ratings were obtained (52% female, mean of 9.5 years of age, 79% non-Hispanic, and 78% White). The cross-validation sample included 1,450 parent ratings and 166 teacher ratings with similar demographic characteristics. The results of confirmatory factor analyses demonstrated that the best-fitting model for teachers was a bifactor solution including a general factor and 2 orthogonal factors, referring to student self-regulation and competence. The best-fitting model for parents was also a bifactor solution, including a general factor and 3 orthogonal factors, referring to student self-regulation, student competence, and teacher support of homework. Gender differences were identified for the general and self-regulation factors of both versions. Overall, the findings provide strong support for the HPQ as a multi-informant, multidimensional measure of homework performance that has utility for the assessment of elementary and middle school students. (c) 2015 APA, all rights reserved).

Depression Anxiety Stress Scales (DASS-21): Factor Structure in Traumatic Brain Injury Rehabilitation.

PubMed

Randall, Diane; Thomas, Matt; Whiting, Diane; McGrath, Andrew

To confirm the construct validity of the Depression Anxiety Stress Scales-21 (DASS-21) by investigating the fit of published factor structures in a sample of adults with moderate to severe traumatic brain injury (posttraumatic amnesia > 24 hours). Archival data from 504 patient records at the Brain Injury Rehabilitation Unit at Liverpool Hospital, Australia. Participants were aged between 16 and 71 years and were engaged in a specialist rehabilitation program. The DASS-21. Two of the 6 models had adequate fit using structural equation modeling. The data best fit Henry and Crawford's quadripartite model, which comprised a Depression, Anxiety and Stress factor, as well as a General Distress factor. The data also adequately fit Lovibond and Lovibond's original 3-factor model, and the internal consistencies of each factor were very good (α = 0.82-0.90). This study confirms the structure and construct validity of the DASS-21 and provides support for its use as a screening tool in traumatic brain injury rehabilitation.

Monitoring hand, foot and mouth disease by combining search engine query data and meteorological factors.

PubMed

Huang, Da-Cang; Wang, Jin-Feng

2018-01-15

Hand, foot and mouth disease (HFMD) has been recognized as a significant public health threat and poses a tremendous challenge to disease control departments. To date, the relationship between meteorological factors and HFMD has been documented, and public interest of disease has been proven to be trackable from the Internet. However, no study has explored the combination of these two factors in the monitoring of HFMD. Therefore, the main aim of this study was to develop an effective monitoring model of HFMD in Guangzhou, China by utilizing historical HFMD cases, Internet-based search engine query data and meteorological factors. To this end, a case study was conducted in Guangzhou, using a network-based generalized additive model (GAM) including all factors related to HFMD. Three other models were also constructed using some of the variables for comparison. The results suggested that the model showed the best estimating ability when considering all of the related factors. Copyright © 2017 Elsevier B.V. All rights reserved.

Flow assignment model for quantitative analysis of diverting bulk freight from road to railway

PubMed Central

Liu, Chang; Wang, Jiaxi; Xiao, Jie; Liu, Siqi; Wu, Jianping; Li, Jian

2017-01-01

Since railway transport possesses the advantage of high volume and low carbon emissions, diverting some freight from road to railway will help reduce the negative environmental impacts associated with transport. This paper develops a flow assignment model for quantitative analysis of diverting truck freight to railway. First, a general network which considers road transportation, railway transportation, handling and transferring is established according to all the steps in the whole transportation process. Then general functions which embody the factors which the shippers will pay attention to when choosing mode and path are formulated. The general functions contain the congestion cost on road, the capacity constraints of railways and freight stations. Based on the general network and general cost function, a user equilibrium flow assignment model is developed to simulate the flow distribution on the general network under the condition that all shippers choose transportation mode and path independently. Since the model is nonlinear and challenging, we adopt a method that uses tangent lines to constitute envelope curve to linearize it. Finally, a numerical example is presented to test the model and show the method of making quantitative analysis of bulk freight modal shift between road and railway. PMID:28771536

The role of general psychosocial factors for the use of cancer screening-Findings of a population-based observational study among older adults in Germany.

PubMed

Hajek, André; Bock, Jens-Oliver; König, Hans-Helmut

2017-12-01

Within the framework of the health-belief model, some studies exist investigating the association between illness-specific psychosocial factors and the use of cancer screenings. However, studies investigating the association between general psychosocial factors and the use of cancer screenings are missing. Thus, this study aimed at examining the association between well-established general psychosocial factors and the use of cancer screenings. Data were gathered from a large, population-based sample of community-dwelling individuals aged 40 and above in Germany (n = 7673; in 2014). Loneliness, cognitive well-being, affective well-being (negative and positive affect), optimism, self-efficacy, self-esteem, self-regulation, perceived autonomy, perceived stress, and perceived social exclusion were used as general psychosocial factors. Furthermore, individuals were asked whether they regularly underwent early cancer screening in the past years (yes; no). A total of 65.6% of the individuals used cancer screening. Adjusting for sociodemographic factors, self-rated health, morbidity and lifestyle factors, multiple logistic regressions revealed that the use of cancer screening is positively associated with decreased loneliness, cognitive well-being, optimism, self-efficacy, self-esteem, self-regulation, perceived autonomy, decreased perceived stress, decreased perceived social exclusion, and positive affect, while it is not associated with negative affect. This study stresses the strong association between general psychosocial factors and the use of cancer screening. This knowledge might be fruitful to address individuals at risk for underuse. © 2017 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Evaluating the Factor Validity of the Children's Organizational Skills Scale in Youth with ADHD.

PubMed

Molitor, Stephen J; Langberg, Joshua M; Evans, Steven W; Dvorsky, Melissa R; Bourchtein, Elizaveta; Eddy, Laura D; Smith, Zoe R; Oddo, Lauren E

2017-06-01

Children and adolescents with ADHD often have difficulties with organization, time management, and planning (OTMP) skills, and these skills are a common target of intervention. A limited array of tools for measuring these abilities in youth is available, and one of the most prominent measures is the Children's Organizational Skills Scale (COSS). Although the COSS fills an important need, a replication of the COSS factor structure outside of initial measure development has not been conducted in any population. Given that the COSS is frequently used in ADHD research, the current study evaluated the factor structure of the parent-rated COSS in a sample ( N = 619) of adolescents with ADHD. Results indicated that the original factor structure could be replicated, although the use of item parcels appeared to affect model fit statistics. An alternative bi-factor model was also tested that did not require the use of parcels, with results suggesting similar model fit in comparison to the original factor structure. Exploratory validity tests indicated that the domain-general factor of the bi-factor model appears related to broad executive functioning abilities.

Black Carbon Concentration from Worldwide Aerosol Robotic Network (AERONET) Measurements

NASA Technical Reports Server (NTRS)

Schuster, Gregory L.; Dubovik, Oleg; Holben, Brent N.; Clothiaux, Eugene E.

2006-01-01

The carbon emissions inventories used to initialize transport models and general circulation models are highly parameterized, and created on the basis of multiple sparse datasets (such as fuel use inventories and emission factors). The resulting inventories are uncertain by at least a factor of 2, and this uncertainty is carried forward to the model output. [Bond et al., 1998, Bond et al., 2004, Cooke et al., 1999, Streets et al., 2001] Worldwide black carbon concentration measurements are needed to assess the efficacy of the carbon emissions inventory and transport model output on a continuous basis.

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

Factorial invariance of posttraumatic stress disorder symptoms across three veteran samples.

PubMed

McDonald, Scott D; Beckham, Jean C; Morey, Rajendra; Marx, Christine; Tupler, Larry A; Calhoun, Patrick S

2008-06-01

Research generally supports a 4-factor structure of posttraumatic stress disorder (PTSD) symptoms. However, few studies have established factor invariance by comparing multiple groups. This study examined PTSD symptom structure using the Davidson Trauma Scale (DTS) across three veteran samples: treatment-seeking Vietnam-era veterans, treatment-seeking post-Vietnam-era veterans, and Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF) veteran research participants. Confirmatory factor analyses of DTS items demonstrated that a 4-factor structural model of the DTS (reexperiencing, avoidance, numbing, and hyperarousal) was superior to five alternate models, including the conventional 3-factor model proposed by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV; American Psychiatric Association, 1994). Results supported factor invariance across the three veteran cohorts, suggesting that cross-group comparisons are interpretable. Implications and applications for DSM-IV nosology and the validity of symptom measures are discussed.

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 precise dynamic analysis while compensating for Compton scatter and cross-talk.« less

Constrained low-rank matrix estimation: phase transitions, approximate message passing and applications

NASA Astrophysics Data System (ADS)

Lesieur, Thibault; Krzakala, Florent; Zdeborová, Lenka

2017-07-01

This article is an extended version of previous work of Lesieur et al (2015 IEEE Int. Symp. on Information Theory Proc. pp 1635-9 and 2015 53rd Annual Allerton Conf. on Communication, Control and Computing (IEEE) pp 680-7) on low-rank matrix estimation in the presence of constraints on the factors into which the matrix is factorized. Low-rank matrix factorization is one of the basic methods used in data analysis for unsupervised learning of relevant features and other types of dimensionality reduction. We present a framework to study the constrained low-rank matrix estimation for a general prior on the factors, and a general output channel through which the matrix is observed. We draw a parallel with the study of vector-spin glass models—presenting a unifying way to study a number of problems considered previously in separate statistical physics works. We present a number of applications for the problem in data analysis. We derive in detail a general form of the low-rank approximate message passing (Low-RAMP) algorithm, that is known in statistical physics as the TAP equations. We thus unify the derivation of the TAP equations for models as different as the Sherrington-Kirkpatrick model, the restricted Boltzmann machine, the Hopfield model or vector (xy, Heisenberg and other) spin glasses. The state evolution of the Low-RAMP algorithm is also derived, and is equivalent to the replica symmetric solution for the large class of vector-spin glass models. In the section devoted to result we study in detail phase diagrams and phase transitions for the Bayes-optimal inference in low-rank matrix estimation. We present a typology of phase transitions and their relation to performance of algorithms such as the Low-RAMP or commonly used spectral methods.

DYNAMO-HIA--a Dynamic Modeling tool for generic Health Impact Assessments.

PubMed

Lhachimi, Stefan K; Nusselder, Wilma J; Smit, Henriette A; van Baal, Pieter; Baili, Paolo; Bennett, Kathleen; Fernández, Esteve; Kulik, Margarete C; Lobstein, Tim; Pomerleau, Joceline; Mackenbach, Johan P; Boshuizen, Hendriek C

2012-01-01

Currently, no standard tool is publicly available that allows researchers or policy-makers to quantify the impact of policies using epidemiological evidence within the causal framework of Health Impact Assessment (HIA). A standard tool should comply with three technical criteria (real-life population, dynamic projection, explicit risk-factor states) and three usability criteria (modest data requirements, rich model output, generally accessible) to be useful in the applied setting of HIA. With DYNAMO-HIA (Dynamic Modeling for Health Impact Assessment), we introduce such a generic software tool specifically designed to facilitate quantification in the assessment of the health impacts of policies. DYNAMO-HIA quantifies the impact of user-specified risk-factor changes on multiple diseases and in turn on overall population health, comparing one reference scenario with one or more intervention scenarios. The Markov-based modeling approach allows for explicit risk-factor states and simulation of a real-life population. A built-in parameter estimation module ensures that only standard population-level epidemiological evidence is required, i.e. data on incidence, prevalence, relative risks, and mortality. DYNAMO-HIA provides a rich output of summary measures--e.g. life expectancy and disease-free life expectancy--and detailed data--e.g. prevalences and mortality/survival rates--by age, sex, and risk-factor status over time. DYNAMO-HIA is controlled via a graphical user interface and is publicly available from the internet, ensuring general accessibility. We illustrate the use of DYNAMO-HIA with two example applications: a policy causing an overall increase in alcohol consumption and quantifying the disease-burden of smoking. By combining modest data needs with general accessibility and user friendliness within the causal framework of HIA, DYNAMO-HIA is a potential standard tool for health impact assessment based on epidemiologic evidence.

A General Multidimensional Model for the Measurement of Cultural Differences.

ERIC Educational Resources Information Center

Olmedo, Esteban L.; Martinez, Sergio R.

A multidimensional model for measuring cultural differences (MCD) based on factor analytic theory and techniques is proposed. The model assumes that a cultural space may be defined by means of a relatively small number of orthogonal dimensions which are linear combinations of a much larger number of cultural variables. Once a suitable,…

Systematizing Web Search through a Meta-Cognitive, Systems-Based, Information Structuring Model (McSIS)

ERIC Educational Resources Information Center

Abuhamdieh, Ayman H.; Harder, Joseph T.

2015-01-01

This paper proposes a meta-cognitive, systems-based, information structuring model (McSIS) to systematize online information search behavior based on literature review of information-seeking models. The General Systems Theory's (GST) prepositions serve as its framework. Factors influencing information-seekers, such as the individual learning…

Measuring the effects of socioeconomic factors on mental health among migrants in urban China: a multiple indicators multiple causes model.

PubMed

Guan, Ming

2017-01-01

Since 1978, rural-urban migrants mainly contribute Chinese urbanization. The purpose of this paper is to examine the effects of socioeconomic factors on mental health of them. Their mental health was measured by 12-item general health questionnaire (GHQ-12). The study sample comprised 5925 migrants obtained from the 2009 rural-to-urban migrants survey (RUMiC). The relationships among the instruments were assessed by the correlation analysis. The one-factor (overall items), two-factor (positive vs. negative items), and model conducted by principal component analysis were tested in the confirmatory factor analysis (CFA). On the basis of three CFA models, the three multiple indicators multiple causes (MIMIC) models with age, gender, marriage, ethnicity, and employment were constructed to investigate the concurrent associations between socioeconomic factors and GHQ-12. Of the sample, only 1.94% were of ethnic origin and mean age was 31.63 (SD = ±10.43) years. The one-factor, two-factor, and three-factor structure (i.e. semi-positive/negative/independent usefulness) had good model fits in the CFA analysis and gave order (i.e. 2 factor>3 factor>1 factor), which suggests that the three models can be used to assess psychological symptoms of migrants in urban China. All MIMIC models had acceptable fit and gave order (i.e. one-dimensional model>two-dimensional model>three-dimensional model). There were weak associations of socioeconomic factors with mental health among migrants in urban China. Policy discussion suggested that improvement of socioeconomic status of rural-urban migrants and mental health systems in urban China should be highlighted and strengthened.

Dimensional analysis of depressive, anxious and somatic symptoms presented by primary care patients and their relationship with ICD-11 PHC proposed diagnoses.

PubMed

Ziebold, Carolina; Goldberg, David P; Reed, Geoffrey M; Minhas, Fareed; Razzaque, Bushra; Fortes, Sandra; Robles, Rebeca; Lam, Tai Pong; Bobes, Julio; Iglesias, Celso; Cogo-Moreira, Hugo; García, José Ángel; Mari, Jair J

2018-06-04

A study conducted as part of the development of the Eleventh International Classification of Mental Disorders for Primary Health Care (ICD-11 PHC) provided an opportunity to test the relationships among depressive, anxious and somatic symptoms in PHC. Primary care physicians participating in the ICD-11 PHC field studies in five countries selected patients who presented with somatic symptoms not explained by known physical pathology by applying a 29-item screening on somatic complaints that were under study for bodily stress disorder. Patients were interviewed using the Clinical Interview Schedule-Revised and assessed using two five-item scales that measure depressive and anxious symptoms. Structural models of anxious-depressive symptoms and somatic complaints were tested using a bi-factor approach. A total of 797 patients completed the study procedures. Two bi-factor models fit the data well: Model 1 had all symptoms loaded on a general factor, along with one of three specific depression, anxiety and somatic factors [x2 (627) = 741.016, p < 0.0011, RMSEA = 0.015, CFI = 0.911, TLI = 0.9]. Model 2 had a general factor and two specific anxious depression and somatic factors [x2 (627) = 663.065, p = 0.1543, RMSEA = 0.008, CFI = 0.954, TLI = 0.948]. These data along with those of previous studies suggest that depressive, anxious and somatic symptoms are largely different presentations of a common latent phenomenon. This study provides support for the ICD-11 PHC conceptualization of mood disturbance, especially anxious depression, as central among patients who present multiple somatic symptoms.

Broad Bandwidth or High Fidelity? Evidence from the Structure of Genetic and Environmental Effects on the Facets of the Five Factor Model

PubMed Central

Briley, Daniel A.; Tucker-Drob, Elliot M.

2017-01-01

The Five Factor Model (FFM) of personality is well-established at the phenotypic level, but much less is known about the coherence of the genetic and environmental influences within each personality domain. Univariate behavioral genetic analyses have consistently found the influence of additive genes and nonshared environment on multiple personality facets, but the extent to which genetic and environmental influences on specific facets reflect more general influences on higher order factors is less clear. We applied a multivariate quantitative-genetic approach to scores on the CPI-Big Five facets for 490 monozygotic and 317 dizygotic twins who took part in the National Merit Twin Study. Our results revealed a complex genetic structure for facets composing all five factors, with both domain-general and facet-specific genetic and environmental influences. Models that required common genetic and environmental influences on each facet to occur by way of effects on a higher order trait did not fit as well as models allowing for common genetic and environmental effects to act directly on the facets for three of the Big Five domains. These results add to the growing body of literature indicating that important variation in personality occurs at the facet level which may be overshadowed by aggregating to the trait level. Research at the facet level, rather than the factor level, is likely to have pragmatic advantages in future research on the genetics of personality. PMID:22695681

Chinese Students' Implicit Theories of Intelligence and Other Personal Attributes: Cross-Domain Generality and Age-Related Differences.

ERIC Educational Resources Information Center

Cheng, Zi-Juan; Hau, Kit-Tai; Wen, Jian-Bing; Kong, Chit-Kwong

Using structural equation modeling (SEM), researchers examined whether there was a general dominating factor that governed students' implicit theories of intelligence, morality, personality, creativity, and social intelligence. The possible age-related changes of students' implicit theories were also studied. In all, 1,650 elementary and junior…

ENED-GEM: A Conceptual Framework Model for Psychological Enjoyment Factors and Learning Mechanisms in Educational Games about the Environment.

PubMed

Fjællingsdal, Kristoffer S; Klöckner, Christian A

2017-01-01

Based on a thorough review of psychological literature, this article seeks to develop a model of game enjoyment and environmental learning (ENvironmental EDucational Game Enjoyment Model, ENED-GEM) and delineate psychological processes that might facilitate learning and inspire behavioral change from educational games about the environment. A critically acclaimed digital educational game about environmental issues (Fate of the World by Red Redemption/Soothsayer Games) was used as a case study. Two hundred forty-nine reviews of the game from the popular gaming and reviewing platform known as Steam were analyzed by means of a thematic content analysis in order to identify key player enjoyment factors believed to be relevant to the process of learning from games, as well as to gain an understanding of positive and negative impressions about the game's general content. The end results of the thematic analysis were measured up to the suggested ENED-GEM framework. Initial results generally support the main elements of the ENED-GEM, and future research into the importance of these individual core factors is outlined.

ENED-GEM: A Conceptual Framework Model for Psychological Enjoyment Factors and Learning Mechanisms in Educational Games about the Environment

PubMed Central

Fjællingsdal, Kristoffer S.; Klöckner, Christian A.

2017-01-01

Based on a thorough review of psychological literature, this article seeks to develop a model of game enjoyment and environmental learning (ENvironmental EDucational Game Enjoyment Model, ENED-GEM) and delineate psychological processes that might facilitate learning and inspire behavioral change from educational games about the environment. A critically acclaimed digital educational game about environmental issues (Fate of the World by Red Redemption/Soothsayer Games) was used as a case study. Two hundred forty-nine reviews of the game from the popular gaming and reviewing platform known as Steam were analyzed by means of a thematic content analysis in order to identify key player enjoyment factors believed to be relevant to the process of learning from games, as well as to gain an understanding of positive and negative impressions about the game’s general content. The end results of the thematic analysis were measured up to the suggested ENED-GEM framework. Initial results generally support the main elements of the ENED-GEM, and future research into the importance of these individual core factors is outlined. PMID:28701988

Applying Latent Class Analysis to Risk Stratification for Perioperative Mortality in Patients Undergoing Intraabdominal General Surgery.

PubMed

Kim, Minjae; Wall, Melanie M; Li, Guohua

2016-07-01

Perioperative risk stratification is often performed using individual risk factors without consideration of the syndemic of these risk factors. We used latent class analysis (LCA) to identify the classes of comorbidities and risk factors associated with perioperative mortality in patients presenting for intraabdominal general surgery. The 2005 to 2010 American College of Surgeons National Surgical Quality Improvement Program was used to obtain a cohort of patients undergoing intraabdominal general surgery. Risk factors and comorbidities were entered into LCA models to identify the latent classes, and individuals were assigned to a class based on the highest posterior probability of class membership. Relative risk regression was used to determine the associations between the latent classes and 30-day mortality, with adjustments for procedure. A 9-class model was fit using LCA on 466,177 observations. After combining classes with similar adjusted mortality risks, 5 risk classes were obtained. Compared with the class with average mortality risk (class 4), the risk ratios (95% confidence interval) ranged from 0.020 (0.014-0.027) in the lowest risk class (class 1) to 6.75 (6.46-7.02) in the highest risk class. After adjusting for procedure and ASA physical status, the latent classes remained significantly associated with 30-day mortality. The addition of the risk class variable to a model containing ASA physical status and surgical procedure demonstrated a significant increase in the area under the receiver operator characteristic curve (0.892 vs 0.915; P < 0.0001). Latent classes of risk factors and comorbidities in patients undergoing intraabdominal surgery are predictive of 30-day mortality independent of the ASA physical status and improve risk prediction with the ASA physical status.

Structural Behavioral Study on the General Aviation Network Based on Complex Network

NASA Astrophysics Data System (ADS)

Zhang, Liang; Lu, Na

2017-12-01

The general aviation system is an open and dissipative system with complex structures and behavioral features. This paper has established the system model and network model for general aviation. We have analyzed integral attributes and individual attributes by applying the complex network theory and concluded that the general aviation network has influential enterprise factors and node relations. We have checked whether the network has small world effect, scale-free property and network centrality property which a complex network should have by applying degree distribution of functions and proved that the general aviation network system is a complex network. Therefore, we propose to achieve the evolution process of the general aviation industrial chain to collaborative innovation cluster of advanced-form industries by strengthening network multiplication effect, stimulating innovation performance and spanning the structural hole path.

Application of General Regression Neural Network to the Prediction of LOD Change

NASA Astrophysics Data System (ADS)

Zhang, Xiao-Hong; Wang, Qi-Jie; Zhu, Jian-Jun; Zhang, Hao

2012-01-01

Traditional methods for predicting the change in length of day (LOD change) are mainly based on some linear models, such as the least square model and autoregression model, etc. However, the LOD change comprises complicated non-linear factors and the prediction effect of the linear models is always not so ideal. Thus, a kind of non-linear neural network — general regression neural network (GRNN) model is tried to make the prediction of the LOD change and the result is compared with the predicted results obtained by taking advantage of the BP (back propagation) neural network model and other models. The comparison result shows that the application of the GRNN to the prediction of the LOD change is highly effective and feasible.

When to use discrete event simulation (DES) for the economic evaluation of health technologies? A review and critique of the costs and benefits of DES.

PubMed

Karnon, Jonathan; Haji Ali Afzali, Hossein

2014-06-01

Modelling in economic evaluation is an unavoidable fact of life. Cohort-based state transition models are most common, though discrete event simulation (DES) is increasingly being used to implement more complex model structures. The benefits of DES relate to the greater flexibility around the implementation and population of complex models, which may provide more accurate or valid estimates of the incremental costs and benefits of alternative health technologies. The costs of DES relate to the time and expertise required to implement and review complex models, when perhaps a simpler model would suffice. The costs are not borne solely by the analyst, but also by reviewers. In particular, modelled economic evaluations are often submitted to support reimbursement decisions for new technologies, for which detailed model reviews are generally undertaken on behalf of the funding body. This paper reports the results from a review of published DES-based economic evaluations. Factors underlying the use of DES were defined, and the characteristics of applied models were considered, to inform options for assessing the potential benefits of DES in relation to each factor. Four broad factors underlying the use of DES were identified: baseline heterogeneity, continuous disease markers, time varying event rates, and the influence of prior events on subsequent event rates. If relevant, individual-level data are available, representation of the four factors is likely to improve model validity, and it is possible to assess the importance of their representation in individual cases. A thorough model performance evaluation is required to overcome the costs of DES from the users' perspective, but few of the reviewed DES models reported such a process. More generally, further direct, empirical comparisons of complex models with simpler models would better inform the benefits of DES to implement more complex models, and the circumstances in which such benefits are most likely.

Loneliness and Schizotypy Are Distinct Constructs, Separate from General Psychopathology.

PubMed

Badcock, Johanna C; Barkus, Emma; Cohen, Alex S; Bucks, Romola; Badcock, David R

2016-01-01

Loneliness is common in youth and associated with a significantly increased risk of psychological disorders. Although loneliness is strongly associated with psychosis, its relationship with psychosis proneness is unclear. Our aim in this paper was to test the hypothesis that loneliness and schizotypal traits, conveying risk for schizophrenia spectrum disorders, are similar but separate constructs. Pooling data from two non-clinical student samples (N = 551) we modeled the structure of the relationship between loneliness and trait schizotypy. Loneliness was assessed with the University of California, Los Angeles Loneliness Scale (UCLA-3), whilst negative (Social Anhedonia) and positive (Perceptual Aberrations) schizotypal traits were assessed with the Wisconsin Schizotypy Scales-Brief (WSS-B). Fit statistics indicated that the best fitting model of UCLA-3 scores comprises three correlated factors (Isolation, Related Connectedness, and Collective Connectedness), consistent with previous reports. Fit statistics for a two factor model of positive and negative schizotypy were excellent. Next, bi-factor analysis was used to model a general psychopatholgy factor (p) across the three loneliness factors and separate negative and positive schizotypy traits. The results showed that all items (except 1) co-loaded on p. However, with the influence of p removed, additional variance remained within separate sub-factors, indicating that loneliness and negative and positive trait schizotypy are distinct and separable constructs. Similarly, once shared variance with p was removed, correlations between sub-factors of loneliness and schizotypal traits were non-significant. These findings have important clinical implications since they suggest that loneliness should not be conflated with the expression of schizotypy. Rather, loneliness needs to be specifically targeted for assessment and treatment in youth at risk for psychosis.

Dissociative absorption: An empirically unique, clinically relevant, dissociative factor.

PubMed

Soffer-Dudek, Nirit; Lassri, Dana; Soffer-Dudek, Nir; Shahar, Golan

2015-11-01

Research of dissociative absorption has raised two questions: (a) Is absorption a unique dissociative factor within a three-factor structure, or a part of one general dissociative factor? Even when three factors are found, the specificity of the absorption factor is questionable. (b) Is absorption implicated in psychopathology? Although commonly viewed as "non-clinical" dissociation, absorption was recently hypothesized to be specifically associated with obsessive-compulsive symptoms. To address these questions, we conducted exploratory and confirmatory factor analyses on 679 undergraduates. Analyses supported the three-factor model, and a "purified" absorption scale was extracted from the original inclusive absorption factor. The purified scale predicted several psychopathology scales. As hypothesized, absorption was a stronger predictor of obsessive-compulsive symptoms than of general psychopathology. In addition, absorption was the only dissociative scale that longitudinally predicted obsessive-compulsive symptoms. We conclude that absorption is a unique and clinically relevant dissociative tendency that is particularly meaningful to obsessive-compulsive symptoms. Copyright © 2015 Elsevier Inc. All rights reserved.

Patients' Needs for Care in Public Mental Health: Unity and Diversity of Self-Assessed Needs for Care.

PubMed

Bellier-Teichmann, Tanja; Golay, Philippe; Bonsack, Charles; Pomini, Valentino

2016-01-01

Needs assessment is recognized to be a key element of mental health care. Patients tend to present heterogeneous profiles of needs. However, there is no consensus in previous research about how patients' needs are organized. This study investigates both general and specific dimensions of patients' needs for care. Patients' needs were assessed with ELADEB, an 18-domain self-report scale. The use of a self-assessment scale represents a unique way of obtaining patients' perceptions. A patient-centered psychiatric practice facilitates empowerment as it is based on the patients' personal motivations, needs, and wants. Four seventy-one patients' profiles were analyzed through exploratory factor analysis. A four-factor bifactor model, including one general factor and three specific factors of needs, was most adequate. Specific factors were (a) "finances" and "administrative tasks"; (b) "transports," "public places," "self-care," "housework," and "food"; and (c) "family," "children," "intimate relationships," and "friendship." As revealed by the general factor, patients expressing urgent needs in some domains are also more susceptible to report urgent needs in several other domains. This general factor relates to high versus low utilizers of public mental healthcare. Patients also present specific needs in life domains, which are organized in three dimensions: management, functional disabilities, and familial and interpersonal relationships. These dimensions relate to the different types of existing social support described in the literature.

Psychometric modeling of abuse and dependence symptoms across six illicit substances indicates novel dimensions of misuse

PubMed Central

Clark, Shaunna L.; Gillespie, Nathan A.; Adkins, Daniel E.; Kendler, Kenneth S.; Neale, Michael C.

2015-01-01

Aims This study explored the factor structure of DSM III-R/IV symptoms for substance abuse and dependence across six illicit substance categories in a population-based sample of males. Method DSM III-R/IV drug abuse and dependence symptoms for cannabis, sedatives, stimulants, cocaine, opioids and hallucinogens from 4179 males born 1940-1970 from the population-based Virginia Adult Twin Study of Psychiatric and Substance Use Disorders were analyzed. Confirmatory factor analyses tested specific hypotheses regarding the latent structure of substance misuse for a comprehensive battery of 13 misuse symptoms measured across six illicit substance categories (78 items). Results Among the models fit, the latent structure of substance misuse was best represented by a combination of substance-specific factors and misuse symptom-specific factors. We found no support for a general liability factor to illicit substance misuse. Conclusions Results indicate that liability to misuse illicit substances is drug class specific, with little evidence for a general liability factor. Additionally, unique dimensions capturing propensity toward specific misuse symptoms (e.g., tolerance, withdrawal) across substances were identified. While this finding requires independent replication, the possibility of symptom-specific misuse factors, present in multiple substances, raises the prospect of genetic, neurobiological and behavioral predispositions toward distinct, narrowly defined features of drug abuse and dependence. PMID:26517709

From Family Violence Exposure to Violent Offending: Examining Effects of Race and Mental Health in a Moderated Mediation Model Among Confined Male Juveniles.

PubMed

Fix, Rebecca L; Alexander, Apryl A; Burkhart, Barry R

2017-09-01

Depression, substance use, and impulsivity have been linked to family violence exposure and to the development of violent offending during adolescence. Additionally, the indirect effects associated with these factors may not generalize across different racial/ethnic adolescent populations. The present study tested whether race/ethnicity moderated the mediated relationship between family violence exposure and violent offending, with depression, substance use, and impulsivity as mediators. A sample of 1,359 male adolescents was obtained from a juvenile correctional program. Between-racial/ethnic group comparisons were generally consistent with previous findings. The overall moderated mediation model was significant in predicting violence for both racial/ethnic groups. Different factors influenced violent offending among African Americans and European Americans in the tested model. Furthermore, race/ethnicity moderated the relationship between family violence exposure and impulsivity and substance use. Implications and future directions resolving issues are discussed concerning whether race/ethnicity should be included as a moderator in models of violence.

Improving estimations of greenhouse gas transfer velocities by atmosphere-ocean couplers in Earth-System and regional models

NASA Astrophysics Data System (ADS)

Vieira, V. M. N. C. S.; Sahlée, E.; Jurus, P.; Clementi, E.; Pettersson, H.; Mateus, M.

2015-09-01

Earth-System and regional models, forecasting climate change and its impacts, simulate atmosphere-ocean gas exchanges using classical yet too simple generalizations relying on wind speed as the sole mediator while neglecting factors as sea-surface agitation, atmospheric stability, current drag with the bottom, rain and surfactants. These were proved fundamental for accurate estimates, particularly in the coastal ocean, where a significant part of the atmosphere-ocean greenhouse gas exchanges occurs. We include several of these factors in a customizable algorithm proposed for the basis of novel couplers of the atmospheric and oceanographic model components. We tested performances with measured and simulated data from the European coastal ocean, having found our algorithm to forecast greenhouse gas exchanges largely different from the forecasted by the generalization currently in use. Our algorithm allows calculus vectorization and parallel processing, improving computational speed roughly 12× in a single cpu core, an essential feature for Earth-System models applications.

Evaluating a Computational Model of Social Causality and Responsibility

DTIC Science & Technology

2006-01-01

Evaluating a Computational Model of Social Causality and Responsibility Wenji Mao University of Southern California Institute for Creative...empirically evaluate a computa- tional model of social causality and responsibility against human social judgments. Results from our experimental...developed a general computational model of social cau- sality and responsibility [10, 11] that formalizes the factors people use in reasoning about

Risk Factors for Bovine Tuberculosis (bTB) in Cattle in Ethiopia.

PubMed

Dejene, Sintayehu W; Heitkönig, Ignas M A; Prins, Herbert H T; Lemma, Fitsum A; Mekonnen, Daniel A; Alemu, Zelalem E; Kelkay, Tessema Z; de Boer, Willem F

2016-01-01

Bovine tuberculosis (bTB) infection is generally correlated with individual cattle's age, sex, body condition, and with husbandry practices such as herd composition, cattle movement, herd size, production system and proximity to wildlife-including bTB maintenance hosts. We tested the correlation between those factors and the prevalence of bTB, which is endemic in Ethiopia's highland cattle, in the Afar Region and Awash National Park between November 2013 and April 2015. A total of 2550 cattle from 102 herds were tested for bTB presence using the comparative intradermal tuberculin test (CITT). Data on herd structure, herd movement, management and production system, livestock transfer, and contact with wildlife were collected using semi-structured interviews with cattle herders and herd owners. The individual overall prevalence of cattle bTB was 5.5%, with a herd prevalence of 46%. Generalized Linear Mixed Models with a random herd-effect were used to analyse risk factors of cattle reactors within each herd. The older the age of the cattle and the lower the body condition the higher the chance of a positive bTB test result, but sex, lactation status and reproductive status were not correlated with bTB status. At herd level, General Linear Models showed that pastoral production systems with transhumant herds had a higher bTB prevalence than sedentary herds. A model averaging analysis identified herd size, contact with wildlife, and the interaction of herd size and contact with wildlife as significant risk factors for bTB prevalence in cattle. A subsequent Structural Equation Model showed that the probability of contact with wildlife was influenced by herd size, through herd movement. Larger herds moved more and grazed in larger areas, hence the probability of grazing in an area with wildlife and contact with either infected cattle or infected wildlife hosts increased, enhancing the chances for bTB infection. Therefore, future bTB control strategies in cattle in pastoral areas should consider herd size and movement as important risk factors.

The General Assessment of Personality Disorder (GAPD): factor structure, incremental validity of self-pathology, and relations to DSM-IV personality disorders.

PubMed

Hentschel, Annett G; Livesley, W John

2013-01-01

Recent developments in the classification of personality disorder, especially moves toward more dimensional systems, create the need to assess general personality disorder apart from individual differences in personality pathology. The General Assessment of Personality Disorder (GAPD) is a self-report questionnaire designed to evaluate general personality disorder. The measure evaluates 2 major components of disordered personality: self or identity problems and interpersonal dysfunction. This study explores whether there is a single factor reflecting general personality pathology as proposed by the Diagnostic and Statistical Manual of Mental Disorders (5th ed.), whether self-pathology has incremental validity over interpersonal pathology as measured by GAPD, and whether GAPD scales relate significantly to Diagnostic and Statistical Manual of Mental Disorders (4th ed. [DSM-IV]) personality disorders. Based on responses from a German psychiatric sample of 149 participants, parallel analysis yielded a 1-factor model. Self Pathology scales of the GAPD increased the predictive validity of the Interpersonal Pathology scales of the GAPD. The GAPD scales showed a moderate to high correlation for 9 of 12 DSM-IV personality disorders.

To What Extent Do School Leaders in Slovenia Understand Physical School Environments as a Learning Factor?

ERIC Educational Resources Information Center

Cencic, Majda

2017-01-01

School leaders are a central factor of the quality of learning and teaching in schools. It is generally believed that the staff model their behaviour on leaders, which means if school leaders understand the physical school environment to be an important factor of learning, school staff (teachers and other professional staff) will also do so. To…

General principles of institutional risks influence on pension systems

NASA Astrophysics Data System (ADS)

Nepp, A. N.; Shilkov, A. A.; Sheveleva, A. Y.; Mamedbakov, M. R.

2016-12-01

This paper examines the tools used to study the influence of institutional factors on investment returns. The research object are the tools used in the evaluation of institutional risks in the pension system, in particular, the correlation model of factors impacting on the `anti-director' index, econometric estimates combining the different determinants of savings, the model of endogenous institutional change, etc. Research work focusing on issues of institutional factors affecting pension systems (authored by La Porta, Guiso, Gianetti, El-Mekkaouide Freitas, Neyapti B., and others) is reviewed. The model is examined in terms of the impact of institutional risks on pension systems, especially with regard to the funded part. The study identified the following factors that affect financial institutions, including pension institutions: management quality, regulation quality, rule of law, political stability, and corruption control.

The importance of emotional intelligence and meaning in life in psycho-oncology.

PubMed

Teques, Andreia Pereira; Carrera, Glória Bueno; Ribeiro, José Pais; Teques, Pedro; Ramón, Ginés Llorca

2016-03-01

Cancer was considered the disease of the 20th century, and the management, treatment, and adaptation of patients to general wellbeing were worldwide concerns. Emotional intelligence has frequently been associated with wellbeing and considered one important factor to optimal human functioning. The purpose of the present study was to test the differences regarding the relationship between emotional intelligence, purpose in life, and satisfaction with life between cancer and healthy people. This model was tested using structural path analysis in two independent samples. First, in a general Portuguese population without chronic disease, 214 participants (nmale  = 41, nfemale  = 173; Mage  = 53). Second, in 202 patients with cancer (nmale  = 40, nfemale  = 162; Mage  = 58.65). A two-step methodology was used to test the research hypothesis. First, a confirmatory factor analysis supported the measurement model. All factors also show reliability, convergent, and discriminate validity. Second, the path coefficients for each model indicate that the proposed relationships differ significantly according to the groups. The perception capacities of emotional intelligence were more related to satisfaction with life and purpose in life in oncologic patients than in the general population without chronic disease, specifically emotional understanding and regulation. Likewise, the relationship between purpose in life and satisfaction with life in oncologic patients was significantly higher than for the general population. The current findings thus suggest that emotional intelligence and purpose in life are potential components to promoting satisfaction in life in healthy people and more so in oncologic patients. Copyright © 2015 John Wiley & Sons, Ltd.

The dimensional structure of psychopathology in 22q11.2 Deletion Syndrome.

PubMed

Niarchou, Maria; Moore, Tyler M; Tang, Sunny X; Calkins, Monica E; McDonald-McGuinn, Donna M; Zackai, Elaine H; Emanuel, Beverly S; Gur, Ruben C; Gur, Raquel E

2017-09-01

22q11.2 Deletion Syndrome (22q11.2DS) is one of the strongest known genetic risk factors for developing schizophrenia. Individuals with 22q11.2DS have high rates of neurodevelopmental disorders in childhood, while in adulthood ∼25% develop schizophrenia. Similar to the general population, high rates of comorbidity are common in 22q11.2DS. Employing a dimensional approach where psychopathology is examined at the symptom-level as complementary to diagnostic categories in a population at such high genetic risk for schizophrenia can help gain a better understanding of how psychopathology is structured as well as its genetic underpinnings. This is the first study to examine the dimensional structure of a wide spectrum of psychopathology in the context of a homogeneous genetic etiology like 22q11.2DS. We evaluated 331 individuals with 22q11.2DS, mean age (SD) = 16.9(8.7); 51% males, who underwent prospective comprehensive phenotyping. We sought to replicate previous findings by examining a bi-factor model that derives a general factor of psychopathology in addition to more specific dimensions of psychopathology (i.e., internalizing, externalizing and thought disorder). Psychopathology in 22q11.2DS was divided into one 'general psychopathology' factor and four specific dimensions (i.e., 'anxiety', 'mood', 'ADHD' and 'psychosis'). The 'psychosis' symptoms loaded strongly on the 'general psychopathology' factor. The similarity of the symptom structure of psychopathology between 22q11.2DS and community and clinical populations without the deletion indicate that 22q11.2DS can provide a model to explore alternative approaches to our current nosology. Our findings add to a growing literature indicating the need to reorganize current diagnostic classification systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Robust Consumption-Investment Problem on Infinite Horizon

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

Zawisza, Dariusz, E-mail: dariusz.zawisza@im.uj.edu.pl

In our paper we consider an infinite horizon consumption-investment problem under a model misspecification in a general stochastic factor model. We formulate the problem as a stochastic game and finally characterize the saddle point and the value function of that game using an ODE of semilinear type, for which we provide a proof of an existence and uniqueness theorem for its solution. Such equation is interested on its own right, since it generalizes many other equations arising in various infinite horizon optimization problems.

A Factor Analysis of Functional Independence and Functional Assessment Measure Scores Among Focal and Diffuse Brain Injury Patients: The Importance of Bifactor Models.

PubMed

Gunn, Sarah; Burgess, Gerald H; Maltby, John

2018-04-30

To explore the factor structure of the UK Functional Independence Measure and Functional Assessment Measure (FIM+FAM) among focal and diffuse acquired brain injury patients. Criterion standard. A National Health Service acute acquired brain injury inpatient rehabilitation hospital. Referred sample of N=447 adults admitted for inpatient treatment following an acquired brain injury significant enough to justify intensive inpatient neurorehabilitation INTERVENTION: Not applicable. Functional Independence Measure and Functional Assessment Measure. Exploratory factor analysis suggested a 2-factor structure to FIM+FAM scores, among both focal-proximate and diffuse-proximate acquired brain injury aetiologies. Confirmatory factor analysis suggested a 3-factor bifactor structure presented the best fit of the FIM+FAM score data across both aetiologies. However, across both analyses, a convergence was found towards a general factor, demonstrated by high correlations between factors in the exploratory factor analysis, and by a general factor explaining the majority of the variance in scores on confirmatory factor analysis. Our findings suggested that although factors describing specific functional domains can be derived from FIM+FAM item scores, there is a convergence towards a single factor describing overall functioning. This single factor informs the specific group factors (eg, motor, psychosocial, and communication function) after brain injury. Further research into the comparative value of the general and group factors as evaluative/prognostic measures is indicated. Copyright © 2018 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Bifactor Models Show a Superior Model Fit: Examination of the Factorial Validity of Parent-Reported and Self-Reported Symptoms of Attention-Deficit/Hyperactivity Disorders in Children and Adolescents.

PubMed

Rodenacker, Klaas; Hautmann, Christopher; Görtz-Dorten, Anja; Döpfner, Manfred

2016-01-01

Various studies have demonstrated that bifactor models yield better solutions than models with correlated factors. However, the kind of bifactor model that is most appropriate is yet to be examined. The current study is the first to test bifactor models across the full age range (11-18 years) of adolescents using self-reports, and the first to test bifactor models with German subjects and German questionnaires. The study sample included children and adolescents aged between 6 and 18 years recruited from a German clinical sample (n = 1,081) and a German community sample (n = 642). To examine the factorial validity, we compared unidimensional, correlated factors and higher-order and bifactor models and further tested a modified incomplete bifactor model for measurement invariance. Bifactor models displayed superior model fit statistics compared to correlated factor models or second-order models. However, a more parsimonious incomplete bifactor model with only 2 specific factors (inattention and impulsivity) showed a good model fit and a better factor structure than the other bifactor models. Scalar measurement invariance was given in most group comparisons. An incomplete bifactor model would suggest that the specific inattention and impulsivity factors represent entities separable from the general attention-deficit/hyperactivity disorder construct and might, therefore, give way to a new approach to subtyping of children beyond and above attention-deficit/hyperactivity disorder. © 2016 S. Karger AG, Basel.

The longitudinal course and outcome of panic disorder.

PubMed

Pollack, M H; Smoller, J W

1995-12-01

Converging lines of evidence from a variety of methods of inquiry support a developmental model for panic disorder that includes a constitutional predisposition for anxiety influenced by genetic, familial, cognitive-behavioral and psychosocial factors, early expression during childhood, and variable manifestations during the life-cycle. Studies of patients followed up after acute pharmacotherapy trials and those treated naturalistically are consistent with this model and portray panic disorder as a generally chronic condition with a longitudinal course marked by relatively brief intervals of remission and high rates of recurrence and relapse. Longitudinal and follow-up studies suggest that panic attack frequency responds more readily and rapidly to pharmacotherapy than do other aspects of panic disorder such as agoraphobia and generalized anxiety. In general, the presence of agoraphobia is associated with more severe symptoms, greater chronicity, and more limited response to treatment. Other variables associated with chronicity and treatment resistance include patient-related factors (psychiatric and medical comorbidity, anxiety sensitivity) and pharmacologic factors (adequacy of dose, duration, and compliance). Although it is currently difficult to predict the duration of treatment needed for an individual patient, available evidence suggests that a substantial proportion of patients may require chronic treatment for panic disorder.

Individual Differences in the Speed of Facial Emotion Recognition Show Little Specificity but Are Strongly Related with General Mental Speed: Psychometric, Neural and Genetic Evidence

PubMed Central

Liu, Xinyang; Hildebrandt, Andrea; Recio, Guillermo; Sommer, Werner; Cai, Xinxia; Wilhelm, Oliver

2017-01-01

Facial identity and facial expression processing are crucial socio-emotional abilities but seem to show only limited psychometric uniqueness when the processing speed is considered in easy tasks. We applied a comprehensive measurement of processing speed and contrasted performance specificity in socio-emotional, social and non-social stimuli from an individual differences perspective. Performance in a multivariate task battery could be best modeled by a general speed factor and a first-order factor capturing some specific variance due to processing emotional facial expressions. We further tested equivalence of the relationships between speed factors and polymorphisms of dopamine and serotonin transporter genes. Results show that the speed factors are not only psychometrically equivalent but invariant in their relation with the Catechol-O-Methyl-Transferase (COMT) Val158Met polymorphism. However, the 5-HTTLPR/rs25531 serotonin polymorphism was related with the first-order factor of emotion perception speed, suggesting a specific genetic correlate of processing emotions. We further investigated the relationship between several components of event-related brain potentials with psychometric abilities, and tested emotion specific individual differences at the neurophysiological level. Results revealed swifter emotion perception abilities to go along with larger amplitudes of the P100 and the Early Posterior Negativity (EPN), when emotion processing was modeled on its own. However, after partialling out the shared variance of emotion perception speed with general processing speed-related abilities, brain-behavior relationships did not remain specific for emotion. Together, the present results suggest that speed abilities are strongly interrelated but show some specificity for emotion processing speed at the psychometric level. At both genetic and neurophysiological levels, emotion specificity depended on whether general cognition is taken into account or not. These findings keenly suggest that general speed abilities should be taken into account when the study of emotion recognition abilities is targeted in its specificity. PMID:28848411

In silico mining and PCR-based approaches to transcription factor discovery in non-model plants: gene discovery of the WRKY transcription factors in conifers.

PubMed

Liu, Jun-Jun; Xiang, Yu

2011-01-01

WRKY transcription factors are key regulators of numerous biological processes in plant growth and development, as well as plant responses to abiotic and biotic stresses. Research on biological functions of plant WRKY genes has focused in the past on model plant species or species with largely characterized transcriptomes. However, a variety of non-model plants, such as forest conifers, are essential as feed, biofuel, and wood or for sustainable ecosystems. Identification of WRKY genes in these non-model plants is equally important for understanding the evolutionary and function-adaptive processes of this transcription factor family. Because of limited genomic information, the rarity of regulatory gene mRNAs in transcriptomes, and the sequence divergence to model organism genes, identification of transcription factors in non-model plants using methods similar to those generally used for model plants is difficult. This chapter describes a gene family discovery strategy for identification of WRKY transcription factors in conifers by a combination of in silico-based prediction and PCR-based experimental approaches. Compared to traditional cDNA library screening or EST sequencing at transcriptome scales, this integrated gene discovery strategy provides fast, simple, reliable, and specific methods to unveil the WRKY gene family at both genome and transcriptome levels in non-model plants.

A comprehensive examination of the psychometric properties of the Hare Psychopathy Checklist-Revised in a Canadian multisite sample of indigenous and non-indigenous offenders.

PubMed

Olver, Mark E; Neumann, Craig S; Sewall, Lindsay A; Lewis, Kathy; Hare, Robert D; Wong, Stephen C P

2018-06-01

The present study examined the psychometric properties of Hare Psychopathy Checklist-Revised (PCL-R; Hare, 2003) scores in a multisite sample of 1,163 federally incarcerated Canadian indigenous and non-indigenous offenders from the Prairie Region of the Correctional Service of Canada. The research occurred against the backdrop of the Ewert v. Canada (2015) matter, in which the PCL-R was originally impugned in Federal Court for use with indigenous persons (later overturned in Canada v. Ewert, 2016). Indigenous men scored higher than non-indigenous men on most components of the PCL-R and had higher rates of recidivism, irrespective of follow-up. Discrimination analyses, however, supported the predictive efficacy of PCL-R total, factor, and facet scores for violent and general recidivism across both ancestral groups, with most group differences in area under the curve (AUC) magnitudes being small and nonsignificant. Calibration analyses demonstrated that higher PCL-R scores were associated with higher rates of general and violent recidivism for both ancestral groups, although higher recidivism rates were observed and estimated for indigenous men at specific PCL-R score thresholds. Confirmatory factor analyses supported the 4-factor model of psychopathy and hence, structural invariance, of PCL-R scores across ancestral groups. Structural equation modeling affirmed the predictive efficacy of the 4-factor model for recidivism. We discuss these findings in terms of clinical applications of the PCL-R and the psychopathy construct in general, with male offenders of indigenous ancestry. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The Five-Factor Model of personality disorder and DSM-5.

PubMed

Trull, Timothy J

2012-12-01

The Five-Factor Model of personality disorders (FFMPD; Widiger & Mullins-Sweatt, ) developed from the recognition that the popular Five-Factor Model (FFM) of personality could be used to describe and understand the official personality disorder (PD) constructs from the American Psychiatric Association's (APA) diagnostic manuals (e.g., DSM-IV-TR, APA, ). This article provides an overview of the FFM, highlighting its validity and utility in characterizing PDs as well as its ability to provide a comprehensive account of personality pathology in general. In 2013, DSM-5 is scheduled to appear, and the "hybrid" PD proposal will emphasize a 25-personality trait model. I present the current version of this new model, compare it to the FFMPD, and discuss issues related to the implementation of the FFMPD. © 2012 The Author. Journal of Personality © 2012, Wiley Periodicals, Inc.

Investigation of traveler acceptance factors in short haul air carrier operations

NASA Technical Reports Server (NTRS)

Kuhlthau, A. R.; Jacobson, I. D.

1972-01-01

The development of a mathematical model for human reaction to variables involved in transportation systems is discussed. The techniques, activities, and results related to defining certain specific inputs to the model are presented. A general schematic diagram of the problem solution is developed. The application of the model to short haul air carrier operations is examined.

Crystal plasticity investigation of the microstructural factors influencing dislocation channeling in a model irradiated bcc material

DOE PAGES

Patra, Anirban; McDowell, David L.

2016-03-25

We use a continuum crystal plasticity framework to study the effect of microstructure and mesoscopic factors on dislocation channeling and flow localization in an irradiated model bcc alloy. For simulated dislocation channeling characteristics we correlate the dislocation and defect densities in the substructure, local Schmid factor, and stress triaxiality, in terms of their temporal and spatial evolution. A metric is introduced to assess the propensity for localization and is correlated to the grain-level Schmid factor. We also found that localization generally takes place in grains with a local Schmid factor in the range 0.42 or higher. Surface slip step heightsmore » are computed at free surfaces and compared to relevant experiments.« less

Soil moisture gradients and controls on a southern Appalachian hillslope from drought through recharge

Treesearch

J.A. Yeakley; W.T. Swank; L.W. Swift; G.M. Hornberger; H.H. Shugart

1998-01-01

Soil moisture gradients along hillslopes in humid watersheds, although indicated by vegetation gradients and by studies using models, have been difficult to confirm empirically. While soil properties and topographic features are the two general physiographic factors controlling soil moisture on hillslopes, studies have shown conflicting results regarding which factor...

A Comparison of Imputation Methods for Bayesian Factor Analysis Models

ERIC Educational Resources Information Center

Merkle, Edgar C.

2011-01-01

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

A Five-Factor Measure of Schizotypal Personality Traits

ERIC Educational Resources Information Center

Edmundson, Maryanne; Lynam, Donald R.; Miller, Joshua D.; Gore, Whitney L.; Widiger, Thomas A.

2011-01-01

The current study provides convergent, discriminant, and incremental validity data for a new measure of schizotypy from the perspective of the five-factor model (FFM) of general personality structure. Nine schizotypy scales were constructed as maladaptive variants of respective facets of the FFM (e.g., Aberrant Ideas as a maladaptive variant of…

Environmental Factors Affecting Computer Assisted Language Learning Success: A Complex Dynamic Systems Conceptual Model

ERIC Educational Resources Information Center

Marek, Michael W.; Wu, Wen-Chi Vivian

2014-01-01

This conceptual, interdisciplinary inquiry explores Complex Dynamic Systems as the concept relates to the internal and external environmental factors affecting computer assisted language learning (CALL). Based on the results obtained by de Rosnay ["World Futures: The Journal of General Evolution", 67(4/5), 304-315 (2011)], who observed…

Is bad living better than good death? Impact of demographic and cultural factors on health state preference.

PubMed

Jin, Xuejing; Liu, Gordon Guoen; Luo, Nan; Li, Hongchao; Guan, Haijing; Xie, Feng

2016-04-01

The aim of this study was to examine the impact of demographic and cultural factors on health preferences among Chinese general population. The Chinese EQ-5D-5L valuation study was conducted between December 2012 and January 2013. A total of 1296 participants were recruited from the general public at Beijing, Chengdu, Guiyang, Nanjing, and Shenyang. Each participant was interviewed to measure preferences for ten EQ-5D-5L health states using composite time trade-off and seven pairs of states using discrete choice experiment (data were not included in this study). At the end of the interview, each participant was also asked to provide their demographic information and answers to two questions about their attitudes towards whether bad living is better than good death (LBD) and whether they believe in an afterlife. Generalized linear model and random effects logistic models were used to examine the impact of demographic and cultural factors on health preferences. Participants who had serious illness experience received college or higher education, or agree with LBD were more likely to value health states positively and have a narrower score range. Participants at Beijing were more likely to be non-traders, value health states positively, less likely to reach the lowest possible score, and have narrower score range compared with all other four cities after controlling for all other demographic and culture factors. Health state preference is significantly affected by factors beyond demographics. These factors should be considered in achieving a representative sample in valuation studies in China.

Demographic and obstetric factors affecting women's sexual functioning during pregnancy.

PubMed

Abouzari-Gazafroodi, Kobra; Najafi, Fatemeh; Kazemnejad, Ehsan; Rahnama, Parvin; Montazeri, Ali

2015-08-19

Sexual desire and frequency of sexual relationships during pregnancy remains challenging. This study aimed to assess factors that affect women's sexual functioning during pregnancy. This was a cross sectional study carried out at prenatal care clinics of public health services in Iran. An author-designed structured questionnaire including items on socio-demographic characteristics, obstetric history, the current pregnancy, and women's sexual functioning during pregnancy was used to collect data. The generalized linear model was performed in order to find out factors that affect women's sexual functioning during pregnancy. In all, 518 pregnant women participated in the study. The mean age of participants was 26.4 years (SD = 4.7). Overall 309 women (59.7%) scored less than mean on sexual functioning. The results obtained from generalized linear model demonstrated that that lower education, unwanted pregnancy, earlier stage of pregnancy, older age, and longer duration of marriage were the most important factors contributing to disturbed sexual functioning among couples. The findings suggest that sexual function during pregnancy might be disturbed due to several factors. Indeed issues on sexual relationship should be included as part of prenatal care and reproductive health programs for every woman.

The Whiteley Index-6: An Examination of Measurement Invariance Among Self-Identifying Black, Latino, and White Respondents in Primary Care.

PubMed

Fergus, Thomas A; Kelley, Lance P; Griggs, Jackson O

2018-03-01

Brief measures that are comparable across disparate groups are particularly likely to be useful in primary care settings. Prior research has supported a six-item short form of the Whiteley Index (WI), a commonly used measure of health anxiety, among English-speaking respondents. This study examined the measurement invariance of the WI-6 among Black ( n = 183), Latino ( n = 173), and White ( n = 177) respondents seeking treatment at a U.S. community health center. Results supported a bifactor model of the WI-6 among the composite sample ( N = 533), suggesting the presence of a general factor and two domain-specific factors. Results supported the incremental validity of one of the domain-specific factors in accounting for unique variance in somatic symptom severity scores beyond the general factor. Multiple-groups confirmatory factor analysis supported the configural, metric, ands scalar invariance of the bifactor WI-6 model across the three groups of respondents. Results provide support for the measurement invariance of the WI-6 among Black, Latino, and White respondents. The potential use of the WI-6 in primary care, and broader, settings is discussed.

Probabilistic graphs as a conceptual and computational tool in hydrology and water management

NASA Astrophysics Data System (ADS)

Schoups, Gerrit

2014-05-01

Originally developed in the fields of machine learning and artificial intelligence, probabilistic graphs constitute a general framework for modeling complex systems in the presence of uncertainty. The framework consists of three components: 1. Representation of the model as a graph (or network), with nodes depicting random variables in the model (e.g. parameters, states, etc), which are joined together by factors. Factors are local probabilistic or deterministic relations between subsets of variables, which, when multiplied together, yield the joint distribution over all variables. 2. Consistent use of probability theory for quantifying uncertainty, relying on basic rules of probability for assimilating data into the model and expressing unknown variables as a function of observations (via the posterior distribution). 3. Efficient, distributed approximation of the posterior distribution using general-purpose algorithms that exploit model structure encoded in the graph. These attributes make probabilistic graphs potentially useful as a conceptual and computational tool in hydrology and water management (and beyond). Conceptually, they can provide a common framework for existing and new probabilistic modeling approaches (e.g. by drawing inspiration from other fields of application), while computationally they can make probabilistic inference feasible in larger hydrological models. The presentation explores, via examples, some of these benefits.

Decision-case mix model for analyzing variation in cesarean rates.

PubMed

Eldenburg, L; Waller, W S

2001-01-01

This article contributes a decision-case mix model for analyzing variation in c-section rates. Like recent contributions to the literature, the model systematically takes into account the effect of case mix. Going beyond past research, the model highlights differences in physician decision making in response to obstetric factors. Distinguishing the effects of physician decision making and case mix is important in understanding why c-section rates vary and in developing programs to effect change in physician behavior. The model was applied to a sample of deliveries at a hospital where physicians exhibited considerable variation in their c-section rates. Comparing groups with a low versus high rate, the authors' general conclusion is that the difference in physician decision tendencies (to perform a c-section), in response to specific obstetric factors, is at least as important as case mix in explaining variation in c-section rates. The exact effects of decision making versus case mix depend on how the model application defines the obstetric condition of interest and on the weighting of deliveries by their estimated "risk of Cesarean." The general conclusion is supported by an additional analysis that uses the model's elements to predict individual physicians' annual c-section rates.

Fundamental factors versus herding in the 2000 2005 US stock market and prediction

NASA Astrophysics Data System (ADS)

Zhou, Wei-Xing; Sornette, Didier

2006-02-01

We present a general methodology to incorporate fundamental economic factors to the theory of herding developed in our group to describe bubbles and antibubbles. We start from the strong form of rational expectation and derive the general method to incorporate factors in addition to the log-periodic power law (LPPL) signature of herding developed in ours and others’ works. These factors include interest rate, interest spread, historical volatility, implied volatility and exchange rates. Standard statistical AIC and Wilks tests allow us to compare the explanatory power of the different proposed factor models. We find that the historical volatility played the key role before August of 2002. Around October 2002, the interest rate dominated. In the first six months of 2003, the foreign exchange rate became the key factor. Since the end of 2003, all factors have played an increasingly large role. However, the most surprising result is that the best model is the second-order LPPL without any factor. We thus present a scenario for the future evolution of the US stock market based on the extrapolation of the fit of the second-order LPPL formula, which suggests that herding is still the dominating force and that the unraveling of the US stock market antibubble since 2000 is still qualitatively similar to (but quantitatively different from) the Japanese Nikkei case after 1990.

The effects of Wechsler Intelligence Scale for Children-Fourth Edition cognitive abilities on math achievement.

PubMed

Parkin, Jason R; Beaujean, A Alexander

2012-02-01

This study used structural equation modeling to examine the effect of Stratum III (i.e., general intelligence) and Stratum II (i.e., Comprehension-Knowledge, Fluid Reasoning, Short-Term Memory, Processing Speed, and Visual Processing) factors of the Cattell-Horn-Carroll (CHC) cognitive abilities, as operationalized by the Wechsler Intelligence Scale for Children, Fourth Edition (WISC-IV; Wechsler, 2003a) subtests, on Quantitative Knowledge, as operationalized by the Wechsler Individual Achievement Test, Second Edition (WIAT-II; Wechsler, 2002) subtests. Participants came from the WISC-IV/WIAT-II linking sample (n=550). We compared models that predicted Quantitative Knowledge using only Stratum III factors, only Stratum II factors, and both Stratum III and Stratum II factors. Results indicated that the model with only the Stratum III factor predicting Quantitative Knowledge best fit the data. Copyright © 2011 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Effects of dietary L-glutamine supplementation on specific and general defense responses in mice immunized with inactivated Pasteurella multocida vaccine.

PubMed

Chen, Shuai; Liu, Shuping; Zhang, Fengmei; Ren, Wenkai; Li, Nengzhang; Yin, Jie; Duan, Jielin; Peng, Yuanyi; Liu, Gang; Yin, Yulong; Wu, Guoyao

2014-10-01

Little is known about effects of dietary glutamine supplementation on specific and general defense responses in a vaccine-immunized animal model. Thus, this study determined roles for dietary glutamine supplementation in specific and general defense responses in mice immunized with inactivated Pasteurella multocida vaccine. The measured variables included: (1) the production of pathogen-specific antibodies; (2) mRNA levels for pro-inflammatory cytokines, toll-like receptors and anti-oxidative factors; and (3) the distribution of P. multocida in tissues and the expression of its major virulence factors in vivo. Dietary supplementation with 0.5 % glutamine had a better protective role than 1 or 2 % glutamine against P. multocida infection in vaccine-immunized mice, at least partly resulting from its effects in modulation of general defense responses. Dietary glutamine supplementation had little effects on the production of P. multocida-specific antibodies. Compared to the non-supplemented group, dietary supplementation with 0.5 % glutamine had no effect on bacterial burden in vivo but decreased the expression of major virulence factors in the spleen. Collectively, supplementing 0.5 % glutamine to a conventional diet provides benefits in vaccine-immunized mice by enhancing general defense responses and decreasing expression of specific virulence factors.

Presentation of a Novel Model for Evaluation of Commercialization of Research and Development: Case Study of the Pharmaceutical Biotechnology Industry

PubMed Central

Emami, Hassan; Radfar, Reza

2017-01-01

The current situation in Iran suggests an appropriate basis for developing biotechnology industries, because the patents for the majority of hi-tech medicines registered in developed countries are ending. Biosimilar and technology-oriented companies which do not have patents will have the opportunity to enter the biosimilar market and move toward innovative initiatives. The present research proposed a model by which one can evaluate commercialization of achievements obtained from research with a focus on the pharmaceutical biotechnology industry. This is a descriptive-analytic study where mixed methodology is followed by a heuristic approach. The statistical population was pharmaceutical biotechnology experts at universities and research centers in Iran. Structural equations were employed in this research. The results indicate that there are three effective layers within commercialization in the proposed model. These are a general layer (factors associated with management, human capital, legal infrastructure, communication infrastructure, a technical and executive infrastructures, and financial factors), industrial layer (internal industrial factors and pharmaceutical industry factors), and a third layer that included national and international aspects. These layers comprise 6 domains, 21 indices, 41 dimensions, and 126 components. Compilation of these layers (general layer, industrial layer, and national and international aspects) can serve commercialization of research and development as an effective evaluation package. PMID:29201110

From the big five to the general factor of personality: a dynamic approach.

PubMed

Micó, Joan C; Amigó, Salvador; Caselles, Antonio

2014-10-28

An integrating and dynamic model of personality that allows predicting the response of the basic factors of personality, such as the Big Five Factors (B5F) or the general factor of personality (GFP) to acute doses of drug is presented in this paper. Personality has a dynamic nature, i.e., as a consequence of a stimulus, the GFP dynamics as well as each one of the B5F of personality dynamics can be explained by the same model (a system of three coupled differential equations). From this invariance hypothesis, a partial differential equation, whose solution relates the GFP with each one of the B5F, is deduced. From this dynamic approach, a co-evolution of the GFP and each one of the B5F occurs, rather than an unconnected evolution, as a consequence of the same stimulus. The hypotheses and deductions are validated through an experimental design centered on the individual, where caffeine is the considered stimulus. Thus, as much from a theoretical point of view as from an applied one, the models here proposed open a new perspective in the understanding and study of personality like a global system that interacts intimately with the environment, being a clear bet for the high level inter-disciplinary research.

Presentation of a Novel Model for Evaluation of Commercialization of Research and Development: Case Study of the Pharmaceutical Biotechnology Industry.

PubMed

Emami, Hassan; Radfar, Reza

2017-01-01

The current situation in Iran suggests an appropriate basis for developing biotechnology industries, because the patents for the majority of hi-tech medicines registered in developed countries are ending. Biosimilar and technology-oriented companies which do not have patents will have the opportunity to enter the biosimilar market and move toward innovative initiatives. The present research proposed a model by which one can evaluate commercialization of achievements obtained from research with a focus on the pharmaceutical biotechnology industry. This is a descriptive-analytic study where mixed methodology is followed by a heuristic approach. The statistical population was pharmaceutical biotechnology experts at universities and research centers in Iran. Structural equations were employed in this research. The results indicate that there are three effective layers within commercialization in the proposed model. These are a general layer (factors associated with management, human capital, legal infrastructure, communication infrastructure, a technical and executive infrastructures, and financial factors), industrial layer (internal industrial factors and pharmaceutical industry factors), and a third layer that included national and international aspects. These layers comprise 6 domains, 21 indices, 41 dimensions, and 126 components. Compilation of these layers (general layer, industrial layer, and national and international aspects) can serve commercialization of research and development as an effective evaluation package.

Panel data models with spatial correlation: Estimation theory and an empirical investigation of the United States wholesale gasoline industry

NASA Astrophysics Data System (ADS)

Kapoor, Mudit

The first part of my dissertation considers the estimation of a panel data model with error components that are both spatially and time-wise correlated. The dissertation combines widely used model for spatial correlation (Cliff and Ord (1973, 1981)) with the classical error component panel data model. I introduce generalizations of the generalized moments (GM) procedure suggested in Kelejian and Prucha (1999) for estimating the spatial autoregressive parameter in case of a single cross section. I then use those estimators to define feasible generalized least squares (GLS) procedures for the regression parameters. I give formal large sample results concerning the consistency of the proposed GM procedures, as well as the consistency and asymptotic normality of the proposed feasible GLS procedures. The new estimators remain computationally feasible even in large samples. The second part of my dissertation employs a Cliff-Ord-type model to empirically estimate the nature and extent of price competition in the US wholesale gasoline industry. I use data on average weekly wholesale gasoline price for 289 terminals (distribution facilities) in the US. Data on demand factors, cost factors and market structure that affect price are also used. I consider two time periods, a high demand period (August 1999) and a low demand period (January 2000). I find a high level of competition in prices between neighboring terminals. In particular, price in one terminal is significantly and positively correlated to the price of its neighboring terminal. Moreover, I find this to be much higher during the low demand period, as compared to the high demand period. In contrast to previous work, I include for each terminal the characteristics of the marginal customer by controlling for demand factors in the neighboring location. I find these demand factors to be important during period of high demand and insignificant during the low demand period. Furthermore, I have also considered spatial correlation in unobserved factors that affect price. I find it to be high and significant only during the low demand period. Not correcting for it leads to incorrect inferences regarding exogenous explanatory variables.

Doctors' experience of coordination across care levels and associated factors. A cross-sectional study in public healthcare networks of six Latin American countries.

PubMed

Vázquez, María-Luisa; Vargas, Ingrid; Garcia-Subirats, Irene; Unger, Jean-Pierre; De Paepe, Pierre; Mogollón-Pérez, Amparo Susana; Samico, Isabella; Eguiguren, Pamela; Cisneros, Angelica-Ivonne; Huerta, Adriana; Muruaga, María-Cecilia; Bertolotto, Fernando

2017-06-01

Improving coordination between primary care (PC) and secondary care (SC) has become a policy priority in recent years for many Latin American public health systems looking to reinforce a healthcare model based on PC. However, despite being a longstanding concern, it has scarcely been analyzed in this region. This paper analyses the level of clinical coordination between PC and SC experienced by doctors and explores influencing factors in public healthcare networks of Argentina, Brazil, Chile, Colombia, Mexico and Uruguay. A cross-sectional study was carried out based on a survey of doctors working in the study networks (348 doctors per country). The COORDENA questionnaire was applied to measure their experiences of clinical management and information coordination, and their related factors. Descriptive analyses were conducted and a multivariate logistic regression model was generated to assess the relationship between general perception of care coordination and associated factors. With some differences between countries, doctors generally reported limited care coordination, mainly in the transfer of information and communication for the follow-up of patients and access to SC for referred patients, especially in the case of PC doctors and, to a lesser degree, inappropriate clinical referrals and disagreement over treatments, in the case of SC doctors. Factors associated with a better general perception of coordination were: being a SC doctor, considering that there is enough time for coordination within consultation hours, job and salary satisfaction, identifying the PC doctor as the coordinator of patient care across levels, knowing the doctors of the other care level and trusting in their clinical skills. These results provide evidence of problems in the implementation of a primary care-based model that require changes in aspects of employment, organization and interaction between doctors, all key factors for coordination. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Subjective happiness among mothers of children with disabilities: The role of stress, attachment, guilt and social support.

PubMed

Findler, Liora; Klein Jacoby, Ayelet; Gabis, Lidia

2016-08-01

Parenting a child with disabilities might affect the happiness of the mothers. Hence we adapted Wallander, Varni, Babani, Banis, and Wilcox's (1989) disability-stress-coping model to examine the impact of risk factors (specific stressors related to the child's disability) on the mother's adaptation (happiness). Intrapersonal factors (attachment) and social-ecological factors (social support) were hypothesized to predict adaptation. Both constitute 'risk-resistant' factors, which are mediated by the mother's perceived general stress and guilt. 191 mothers of a child with a developmental disability (ages 3-7) answered questionnaires on happiness, specific and general stress, attachment, guilt and social support. Attachment avoidance was directly and negatively associated with mothers' happiness. General stress was negatively associated with happiness, and mediated the association between anxious attachment, support, and specific stress with happiness. Guilt was negatively associated with happiness, and served as a mediator between attachment anxiety and support and happiness. The findings of the current research show direct and indirect associations of risk factors with happiness and the role of general stress and feelings of guilt as mediators. This study stresses the importance of attachment and social support to happiness and sheds light on the unique role of guilt in promoting or inhibiting happiness. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

Yuan, Min; Pan, Xiaoqing; Yang, Yaning

2015-06-01

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

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.

Energy risk in the arbitrage pricing model: an empirical and theoretical study

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

Bremer, M.A.

1986-01-01

This dissertation empirically explores the Arbitrage Pricing Theory in the context of energy risk for securities over the 1960s, 1970s, and early 1980s. Starting from a general multifactor pricing model, the paper develops a two factor model based on a market-like factor and an energy factor. This model is then tested on portfolios of securities grouped according to industrial classification using several econometric techniques designed to overcome some of the more serious estimation problems common to these models. The paper concludes that energy risk is priced in the 1970s and possibly even in the 1960s. Energy risk is found tomore » be priced in the sense that investors who hold assets subjected to energy risk are paid for this risk. The classic version of the Capital Asset Pricing Model which posits the market as the single priced factor is rejected in favor of the Arbitrage Pricing Theory or multi-beta versions of the Capital Asset Pricing Model. The study introduces some original econometric methodology to carry out empirical tests.« less

Temperament factors and dimensional, latent bifactor models of child psychopathology: Transdiagnostic and specific associations in two youth samples.

PubMed

Hankin, Benjamin L; Davis, Elysia Poggi; Snyder, Hannah; Young, Jami F; Glynn, Laura M; Sandman, Curt A

2017-06-01

Common emotional and behavioral symptoms co-occur and are associated with core temperament factors. This study investigated links between temperament and dimensional, latent psychopathology factors, including a general common psychopathology factor (p factor) and specific latent internalizing and externalizing liabilities, as captured by a bifactor model, in two independent samples of youth. Specifically, we tested the hypothesis that temperament factors of negative affectivity (NA), positive affectivity (PA), and effortful control (EC) could serve as both transdiagnostic and specific risks in relation to recent bifactor models of child psychopathology. Sample 1 included 571 youth (average age 13.6, SD =2.37, range 9.3-17.5) with both youth and parent report. Sample 2 included 554 preadolescent children (average age 7.7, SD =1.35, range =5-11 years) with parent report. Structural equation modeling showed that the latent bifactor models fit in both samples. Replicated in both samples, the p factor was associated with lower EC and higher NA (transdiagnostic risks). Several specific risks replicated in both samples after controlling for co-occurring symptoms via the p factor: internalizing was associated with higher NA and lower PA, lower EC related to externalizing problems. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Distinguishing General and Specific Personality Disorder Features and Implications for Substance Dependence Comorbidity

PubMed Central

Jahng, Seungmin; Trull, Timothy J.; Wood, Phillip K.; Tragesser, Sarah L.; Tomko, Rachel; Grant, Julia D.; Bucholz, Kathleen K.; Sher, Kenneth J.

2014-01-01

Clinical and population-based samples show high comorbidity between Substance Use Disorders (SUDs) and Axis II Personality Disorders (PDs). However, Axis II disorders are frequently comorbid with each other, and existing research has generally failed to distinguish the extent to which SUD/PD comorbidity is general or specific with respect to both specific types of PDs and specific types of SUDs. We sought to determine whether ostensibly specific comorbid substance dependence-Axis II diagnoses (e.g., alcohol use dependence and borderline personality disorder) are reflective of more pervasive or general personality pathology or whether the comorbidity is specific to individual PDs. Face-to-face interview data from Wave 1 and Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions were analyzed. Participants included 34,653 adults living in households in the United States. We used hierarchical factor models to statistically partition general and specific personality disorder dimensions while simultaneously testing for specific PD-substance dependence relations. Results indicated that substance dependence-Axis II comorbidity is characterized by general (pervasive) pathology and by Cluster B PD pathology over and above the relationship to the general PD factor. Further, these relations between PD factors and substance dependence diagnoses appeared to largely account for the comorbidity among substance dependence diagnoses in the younger but not older participants. Our findings suggest that a failure to consider the general PD factor, which we interpret as reflecting interpersonal dysfunction, can lead to potential mischaracterizations of the nature of certain PD and SUD comorbidities. PMID:21604829

HealthPartners adopts community business model to deepen focus on nonclinical factors of health outcomes.

PubMed

Isham, George J; Zimmerman, Donna J; Kindig, David A; Hornseth, Gary W

2013-08-01

Clinical care contributes only 20 percent to overall health outcomes, according to a population health model developed at the University of Wisconsin. Factors contributing to the remainder include lifestyle behaviors, the physical environment, and social and economic forces--all generally considered outside the realm of care. In 2010 Minnesota-based HealthPartners decided to target nonclinical community health factors as a formal part of its strategic business plan to improve public health in the Twin Cities area. The strategy included creating partnerships with businesses and institutions that are generally unaccustomed to working together or considering how their actions could help improve community health. This article describes efforts to promote healthy eating in schools, reduce the stigma of mental illness, improve end-of-life decision making, and strengthen an inner-city neighborhood. Although still in their early stages, the partnerships can serve as encouragement for organizations inside and outside health care that are considering undertaking similar efforts in their markets.

Reassessment of Resuspension Factor Following Radionuclide Dispersal: Toward a General-purpose Rate Constant

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

Marshall, Shaun; Potter, Charles; Medich, David

A recent analysis of historical radionuclide resuspension datasets con rmed the general applicability of the Anspaugh and modified Anspaugh models of resuspension factors following both controlled and disastrous releases. The observations appear to increase in variance earlier in time, however all points were equally weighted in statistical fit calculations, inducing a positive skewing of resuspension coeffcients. Such data are extracted from the available deposition experiments spanning 2900 days. Measurements within a 3-day window are grouped into singular sample sets to construct standard deviations. A refitting is performed using a relative instrumental weighting of the observations. The resulting best-fit equations producesmore » tamer exponentials which give decreased integrated resuspension factor values relative to those reported by Anspaugh. As expected, the fits attenuate greater error amongst the data at earlier time. The reevaluation provides a sharper contrast between the empirical models, and reafirms their deficiencies in the short-lived timeframe wherein the dynamics of particulate dispersion dominate the resuspension process.« less

Cosmological models with a hybrid scale factor in an extended gravity theory

NASA Astrophysics Data System (ADS)

Mishra, B.; Tripathy, S. K.; Tarai, Sankarsan

2018-03-01

A general formalism to investigate Bianchi type V Ih universes is developed in an extended theory of gravity. A minimally coupled geometry and matter field is considered with a rescaled function of f(R,T) substituted in place of the Ricci scalar R in the geometrical action. Dynamical aspects of the models are discussed by using a hybrid scale factor (HSF) that behaves as power law in an initial epoch and as an exponential form at late epoch. The power law behavior and the exponential behavior appear as two extreme cases of the present model.

Effects of workplace, family and cultural influences on low back pain: what opportunities exist to address social factors in general consultations?

PubMed

Shaw, William S; Campbell, Paul; Nelson, Candace C; Main, Chris J; Linton, Steven J

2013-10-01

Social factors are widely acknowledged in behavioural models of pain and pain management, but incorporating these factors into general medical consultations for low back pain (LBP) can be challenging. While there is no compelling evidence that social factors contribute to LBP onset, these factors have been shown to influence functional limitation and disability, especially the effects of organisational support in the workplace, spousal support, family conflict and social disadvantage. A number of barriers exist to address such social factors in routine medical encounters for LBP, but there is emerging evidence that improving social and organisational support may be an effective strategy to reduce the negative lifestyle consequences of LBP. For clinicians to address these factors in LBP treatment requires a clearer psychosocial framework in assessment and screening, more individualised problem-solving efforts, more patient-centred interventions involving family, peers and workplace supports and a less biomechanical and diagnostic approach. Copyright © 2013 Elsevier Ltd. All rights reserved.

Approximated adjusted fractional Bayes factors: A general method for testing informative hypotheses.

PubMed

Gu, Xin; Mulder, Joris; Hoijtink, Herbert

2018-05-01

Informative hypotheses are increasingly being used in psychological sciences because they adequately capture researchers' theories and expectations. In the Bayesian framework, the evaluation of informative hypotheses often makes use of default Bayes factors such as the fractional Bayes factor. This paper approximates and adjusts the fractional Bayes factor such that it can be used to evaluate informative hypotheses in general statistical models. In the fractional Bayes factor a fraction parameter must be specified which controls the amount of information in the data used for specifying an implicit prior. The remaining fraction is used for testing the informative hypotheses. We discuss different choices of this parameter and present a scheme for setting it. Furthermore, a software package is described which computes the approximated adjusted fractional Bayes factor. Using this software package, psychological researchers can evaluate informative hypotheses by means of Bayes factors in an easy manner. Two empirical examples are used to illustrate the procedure. © 2017 The British Psychological Society.

The PROMIS fatigue item bank has good measurement properties in patients with fibromyalgia and severe fatigue.

PubMed

Yost, Kathleen J; Waller, Niels G; Lee, Minji K; Vincent, Ann

2017-06-01

Efficient management of fibromyalgia (FM) requires precise measurement of FM-specific symptoms. Our objective was to assess the measurement properties of the Patient-Reported Outcome Measurement Information System (PROMIS) fatigue item bank (FIB) in people with FM. We applied classical psychometric and item response theory methods to cross-sectional PROMIS-FIB data from two samples. Data on the clinical FM sample were obtained at a tertiary medical center. Data for the U.S. general population sample were obtained from the PROMIS network. The full 95-item bank was administered to both samples. We investigated dimensionality of the item bank in both samples by separately fitting a bifactor model with two group factors; experience and impact. We assessed measurement invariance between samples, and we explored an alternate factor structure with the normative sample and subsequently confirmed that structure in the clinical sample. Finally, we assessed whether reporting FM subdomain scores added value over reporting a single total score. The item bank was dominated by a general fatigue factor. The fit of the initial bifactor model and evidence of measurement invariance indicated that the same constructs were measured across the samples. An alternative bifactor model with three group factors demonstrated slightly improved fit. Subdomain scores add value over a total score. We demonstrated that the PROMIS-FIB is appropriate for measuring fatigue in clinical samples of FM patients. The construct can be presented by a single score; however, subdomain scores for the three group factors identified in the alternative model may also be reported.

Modelling alpha-diversities of coastal lagoon fish assemblages from the Mediterranean Sea

NASA Astrophysics Data System (ADS)

Riera, R.; Tuset, V. M.; Betancur-R, R.; Lombarte, A.; Marcos, C.; Pérez-Ruzafa, A.

2018-07-01

Coastal lagoons are marine ecosystems spread worldwide with high ecological value; however, they are increasingly becoming deteriorated as a result of anthropogenic activity. Their conservation requires a better understanding of the biodiversity factors that may help identifying priority areas. The present study is focused on 37 Mediterranean coastal lagoons and we use predictive modelling approaches based on Generalized Linear Model (GLM) analysis to investigate variables (geomorphological, environmental, trophic or biogeographic) that may predict variations in alpha-diversity. It included taxonomic diversity, average taxonomic distinctness, and phylogenetic and functional diversity. Two GLM models by index were built depending on available variables for lagoons: in the model 1 all lagoons were used, and in the model 2 only 23. All alpha-diversity indices showed variability between lagoons associated to exogenous factors considered. The biogeographic region strongly conditioned most of models, being the first variable introduced in the models. The salinity and chlorophyll a concentration played a secondary role for the models 1 and 2, respectively. In general, the highest values of alpha-diversities were found in northwestern Mediterranean (Balearic Sea, Alborán Sea and Gulf of Lion), hence they might be considered "hotspots" at the Mediterranean scale and should have a special status for their protection.

Bayes factors for the linear ballistic accumulator model of decision-making.

PubMed

Evans, Nathan J; Brown, Scott D

2018-04-01

Evidence accumulation models of decision-making have led to advances in several different areas of psychology. These models provide a way to integrate response time and accuracy data, and to describe performance in terms of latent cognitive processes. Testing important psychological hypotheses using cognitive models requires a method to make inferences about different versions of the models which assume different parameters to cause observed effects. The task of model-based inference using noisy data is difficult, and has proven especially problematic with current model selection methods based on parameter estimation. We provide a method for computing Bayes factors through Monte-Carlo integration for the linear ballistic accumulator (LBA; Brown and Heathcote, 2008), a widely used evidence accumulation model. Bayes factors are used frequently for inference with simpler statistical models, and they do not require parameter estimation. In order to overcome the computational burden of estimating Bayes factors via brute force integration, we exploit general purpose graphical processing units; we provide free code for this. This approach allows estimation of Bayes factors via Monte-Carlo integration within a practical time frame. We demonstrate the method using both simulated and real data. We investigate the stability of the Monte-Carlo approximation, and the LBA's inferential properties, in simulation studies.

Adult Body Height Is a Good Predictor of Different Dimensions of Cognitive Function in Aged Individuals: A Cross-Sectional Study.

PubMed

Pereira, Vitor H; Costa, Patrício S; Santos, Nadine C; Cunha, Pedro G; Correia-Neves, Margarida; Palha, Joana A; Sousa, Nuno

2016-01-01

Background: Adult height, weight, and adiposity measures have been suggested by some studies to be predictors of depression, cognitive impairment, and dementia. However, the presence of confounding factors and the lack of a thorough neuropsychological evaluation in many of these studies have precluded a definitive conclusion about the influence of anthropometric measures in cognition and depression. In this study we aimed to assess the value of height, weight, and abdominal perimeter to predict cognitive impairment and depressive symptoms in aged individuals. Methods and Findings: Cross-sectional study performed between 2010 and 2012 in the Portuguese general community. A total of 1050 participants were included in the study and randomly selected from local area health authority registries. The cohort was representative of the general Portuguese population with respect to age (above 50 years of age) and gender. Cognitive function was assessed using a battery of tests grouped in two dimensions: general executive function and memory. Two-step hierarchical multiple linear regression models were conducted to determine the predictive value of anthropometric measures in cognitive performance and mood before and after correction for possible confounding factors (gender, age, school years, physical activity, alcohol consumption, and smoking habits). We found single associations of weight, height, body mass index, abdominal perimeter, and age with executive function, memory and depressive symptoms. However, when included in a predictive model adjusted for gender, age, school years, and lifestyle factors only height prevailed as a significant predictor of general executive function (β = 0.139; p < 0.001) and memory (β = 0.099; p < 0.05). No relation was found between mood and any of the anthropometric measures studied. Conclusions and Relevance: Height is an independent predictor of cognitive function in late-life and its effects on the general and executive function and memory are independent of age, weight, education level, gender, and lifestyle factors. Altogether, our data suggests that modulators of adult height during childhood may irreversibly contribute to cognitive function in adult life and that height should be used in models to predict cognitive performance.

Co-occurring risk factors for current cigarette smoking in a U.S. nationally representative sample

PubMed Central

Higgins, Stephen T.; Kurti, Allison N.; Redner, Ryan; White, Thomas J.; Keith, Diana R.; Gaalema, Diann E.; Sprague, Brian L.; Stanton, Cassandra A.; Roberts, Megan E.; Doogan, Nathan J.; Priest, Jeff S.

2016-01-01

Introduction Relatively little has been reported characterizing cumulative risk associated with co-occurring risk factors for cigarette smoking. The purpose of the present study was to address that knowledge gap in a U.S. nationally representative sample. Methods Data were obtained from 114,426 adults (≥ 18 years) in the U.S. National Survey on Drug Use and Health (years 2011–13). Multiple logistic regression and classification and regression tree (CART) modeling were used to examine risk of current smoking associated with eight co-occurring risk factors (age, gender, race/ethnicity, educational attainment, poverty, drug abuse/dependence, alcohol abuse/dependence, mental illness). Results Each of these eight risk factors was independently associated with significant increases in the odds of smoking when concurrently present in a multiple logistic regression model. Effects of risk-factor combinations were typically summative. Exceptions to that pattern were in the direction of less-than-summative effects when one of the combined risk factors was associated with generally high or low rates of smoking (e.g., drug abuse/dependence, age ≥65). CART modeling identified subpopulation risk profiles wherein smoking prevalence varied from a low of 11% to a high of 74% depending on particular risk factor combinations. Being a college graduate was the strongest independent predictor of smoking status, classifying 30% of the adult population. Conclusions These results offer strong evidence that the effects associated with common risk factors for cigarette smoking are independent, cumulative, and generally summative. The results also offer potentially useful insights into national population risk profiles around which U.S. tobacco policies can be developed or refined. PMID:26902875

Cancer and heart attack survivors' expectations of employment status: results from the English Longitudinal Study of Ageing.

PubMed

Duijts, Saskia F A; van der Beek, Allard J; Bleiker, Eveline M A; Smith, Lee; Wardle, Jane

2017-08-07

Sociodemographic, health- and work-related factors have been found to influence return to work in cancer survivors. It is feasible though that behavioural factors, such as expectation of being at work, could also affect work-related outcomes. Therefore, the effect of earlier identified factors and expectation of being at work on future employment status in cancer survivors was explored. To assess the degree to which these factors specifically concern cancer survivors, a comparison with heart attack survivors was made. Data from the English Longitudinal Study of Ageing were used. Cancer and heart attack survivors of working age in the UK were included and followed up for 2 years. Baseline characteristics of both cancer and heart attack survivors were compared regarding employment status. Univariate and multivariate regression analyses were performed in survivors at work, and the interaction between independent variables and diagnose group was assessed. In cancer survivors at work (N = 159), alcohol consumption, participating in moderate or vigorous sport activities, general health and participation were univariate associated with employment status at two-year follow-up. Only fair general health (compared to very good general health) remained statistically significant in the multivariate model (OR 0.31; 95% CI 0.13-0.76; p = 0.010). In heart attack survivors at work (N = 78), gender, general health and expectation of being at work were univariate associated with employment status at follow-up. Female gender (OR 0.03; 95% CI 0.00-0.57; p = 0.018) and high expectation of being at work (OR 10.68; 95% CI 1.23-93.92; p = 0.033) remained significant in the multivariate model. The influence of gender (p = 0.066) and general health (p = 0.020) regarding employment status was found to differ significantly between cancer and heart attack survivors. When predicting future employment status in cancer survivors in the UK, general health is the most relevant factor to consider. While expectation of being at work did not show any significant influence in cancer survivors, in heart attack survivors, it should not be disregarded though, when developing interventions to affect their employment status. Future research should focus on more specific measures for expectation, and additional behavioural factors, such as self-efficacy, and their effect on employment status.

PESTEL Model Analysis and Legal Guarantee of Tourism Environmental Protection in China

NASA Astrophysics Data System (ADS)

Zhiyong, Xian

2017-08-01

On the basis of summarizing the general situation of tourism environmental protection in China, this paper analyses the macro factors of tourism environmental protection by using PESTEL model. On this basis, this paper explores the improvement paths of tourism environmental protection based on PESTEL model. Finally, it puts forward the legal guarantee suggestion of tourism environment protection.

A Multidimensional Model of School Dropout from an 8-Year Longitudinal Study in a General High School Population

ERIC Educational Resources Information Center

Fortin, Laurier; Marcotte, Diane; Diallo, Thierno; Potvin, Pierre; Royer, Egide

2013-01-01

This study tests an empirical multidimensional model of school dropout, using data collected in the first year of an 8-year longitudinal study, with first year high school students aged 12-13 years. Structural equation modeling analyses show that five personal, family, and school latent factors together contribute to school dropout identified at…

Independent Verification of Mars-GRAM 2010 with Mars Climate Sounder Data

NASA Technical Reports Server (NTRS)

Justh, Hilary L.; Burns, Kerry L.

2014-01-01

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission and engineering applications. Applications of Mars-GRAM include systems design, performance analysis, and operations planning for aerobraking, entry, descent and landing, and aerocapture. Atmospheric influences on landing site selection and long-term mission conceptualization and development can also be addressed utilizing Mars-GRAM. Mars-GRAM's perturbation modeling capability is commonly used, in a Monte Carlo mode, to perform high-fidelity engineering end-to-end simulations for entry, descent, and landing. Mars-GRAM is an evolving software package resulting in improved accuracy and additional features. Mars-GRAM 2005 has been validated against Radio Science data, and both nadir and limb data from the Thermal Emission Spectrometer (TES). From the surface to 80 km altitude, Mars-GRAM is based on the NASA Ames Mars General Circulation Model (MGCM). Above 80 km, Mars-GRAM is based on the University of Michigan Mars Thermospheric General Circulation Model (MTGCM). The most recent release of Mars-GRAM 2010 includes an update to Fortran 90/95 and the addition of adjustment factors. These adjustment factors are applied to the input data from the MGCM and the MTGCM for the mapping year 0 user-controlled dust case. The adjustment factors are expressed as a function of height (z), latitude and areocentric solar longitude (Ls).

Specialty choice preference of medical students according to personality traits by Five-Factor Model.

PubMed

Kwon, Oh Young; Park, So Youn

2016-03-01

The purpose of this study was to determine the relationship between personality traits, using the Five-Factor Model, and characteristics and motivational factors affecting specialty choice in Korean medical students. A questionnaire survey of Year 4 medical students (n=110) in July 2015 was administered. We evaluated the personality traits of Extraversion, Agreeableness, Conscientiousness, Neuroticism, and Openness by using the Korean version of Big Five Inventory. Questions about general characteristics, medical specialties most preferred as a career, motivational factors in determining specialty choice were included. Data between five personality traits and general characteristics and motivational factors affecting specialty choice were analyzed using Student t-test, Mann-Whitney test and analysis of variance. Of the 110 eligible medical students, 105 (95.4% response rate) completed the questionnaire. More Agreeableness students preferred clinical medicine to basic medicine (p=0.010) and more Openness students preferred medical departments to others (p=0.031). Personal interest was the significant motivational factors in more Openness students (p=0.003) and Conscientiousness students (p=0.003). Medical students with more Agreeableness were more likely to prefer clinical medicine and those with more Openness preferred medical departments. Personal interest was a significant influential factor determining specialty choice in more Openness and Conscientiousness students. These findings may be helpful to medical educators or career counselors in the specialty choice process.

A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance.

PubMed

Meads, Catherine; Ahmed, Ikhlaaq; Riley, Richard D

2012-04-01

A risk prediction model is a statistical tool for estimating the probability that a currently healthy individual with specific risk factors will develop a condition in the future such as breast cancer. Reliably accurate prediction models can inform future disease burdens, health policies and individual decisions. Breast cancer prediction models containing modifiable risk factors, such as alcohol consumption, BMI or weight, condom use, exogenous hormone use and physical activity, are of particular interest to women who might be considering how to reduce their risk of breast cancer and clinicians developing health policies to reduce population incidence rates. We performed a systematic review to identify and evaluate the performance of prediction models for breast cancer that contain modifiable factors. A protocol was developed and a sensitive search in databases including MEDLINE and EMBASE was conducted in June 2010. Extensive use was made of reference lists. Included were any articles proposing or validating a breast cancer prediction model in a general female population, with no language restrictions. Duplicate data extraction and quality assessment were conducted. Results were summarised qualitatively, and where possible meta-analysis of model performance statistics was undertaken. The systematic review found 17 breast cancer models, each containing a different but often overlapping set of modifiable and other risk factors, combined with an estimated baseline risk that was also often different. Quality of reporting was generally poor, with characteristics of included participants and fitted model results often missing. Only four models received independent validation in external data, most notably the 'Gail 2' model with 12 validations. None of the models demonstrated consistently outstanding ability to accurately discriminate between those who did and those who did not develop breast cancer. For example, random-effects meta-analyses of the performance of the 'Gail 2' model showed the average C statistic was 0.63 (95% CI 0.59-0.67), and the expected/observed ratio of events varied considerably across studies (95% prediction interval for E/O ratio when the model was applied in practice was 0.75-1.19). There is a need for models with better predictive performance but, given the large amount of work already conducted, further improvement of existing models based on conventional risk factors is perhaps unlikely. Research to identify new risk factors with large additionally predictive ability is therefore needed, alongside clearer reporting and continual validation of new models as they develop.

Multivariate analysis of fears in dental phobic patients according to a reduced FSS-II scale.

PubMed

Hakeberg, M; Gustafsson, J E; Berggren, U; Carlsson, S G

1995-10-01

This study analyzed and assessed dimensions of a questionnaire developed to measure general fears and phobias. A previous factor analysis among 109 dental phobics had revealed a five-factor structure with 22 items and an explained total variance of 54%. The present study analyzed the same material using a multivariate statistical procedure (LISREL) to reveal structural latent variables. The LISREL analysis, based on the correlation matrix, yielded a chi-square of 216.6 with 195 degrees of freedom (P = 0.138) and showed a model with seven latent variables. One was a general fear factor correlated to all 22 items. The other six factors concerned "Illness & Death" (5 items), "Failures & Embarrassment" (5 items), "Social situations" (5 items), "Physical injuries" (4 items), "Animals & Natural phenomena" (4 items). One item (opposite sex) was included in both "Failures & Embarrassment" and "Social situations". The last factor, "Social interaction", combined all the items in "Failures & Embarrassment" and "Social situations" (9 items). In conclusion, this multivariate statistical analysis (LISREL) revealed and confirmed a factor structure similar to our previous study, but added two important dimensions not shown with a traditional factor analysis. This reduced FSS-II version measures general fears and phobias and may be used on a routine clinical basis as well as in dental phobia research.

Perturbation of Chromatin Structure Globally Affects Localization and Recruitment of Splicing Factors

PubMed Central

Risso, Guillermo J.; Pawellek, Andrea; Ule, Jernej; Lamond, Angus I.; Kornblihtt, Alberto R.

2012-01-01

Chromatin structure is an important factor in the functional coupling between transcription and mRNA processing, not only by regulating alternative splicing events, but also by contributing to exon recognition during constitutive splicing. We observed that depolarization of neuroblastoma cell membrane potential, which triggers general histone acetylation and regulates alternative splicing, causes a concentration of SR proteins in nuclear speckles. This prompted us to analyze the effect of chromatin structure on splicing factor distribution and dynamics. Here, we show that induction of histone hyper-acetylation results in the accumulation in speckles of multiple splicing factors in different cell types. In addition, a similar effect is observed after depletion of the heterochromatic protein HP1α, associated with repressive chromatin. We used advanced imaging approaches to analyze in detail both the structural organization of the speckle compartment and nuclear distribution of splicing factors, as well as studying direct interactions between splicing factors and their association with chromatin in vivo. The results support a model where perturbation of normal chromatin structure decreases the recruitment efficiency of splicing factors to nascent RNAs, thus causing their accumulation in speckles, which buffer the amount of free molecules in the nucleoplasm. To test this, we analyzed the recruitment of the general splicing factor U2AF65 to nascent RNAs by iCLIP technique, as a way to monitor early spliceosome assembly. We demonstrate that indeed histone hyper-acetylation decreases recruitment of U2AF65 to bulk 3′ splice sites, coincident with the change in its localization. In addition, prior to the maximum accumulation in speckles, ∼20% of genes already show a tendency to decreased binding, while U2AF65 seems to increase its binding to the speckle-located ncRNA MALAT1. All together, the combined imaging and biochemical approaches support a model where chromatin structure is essential for efficient co-transcriptional recruitment of general and regulatory splicing factors to pre-mRNA. PMID:23152763

A model for field toxicity tests

USGS Publications Warehouse

Kaiser, Mark S.; Finger, Susan E.

1996-01-01

Toxicity tests conducted under field conditions present an interesting challenge for statistical modelling. In contrast to laboratory tests, the concentrations of potential toxicants are not held constant over the test. In addition, the number and identity of toxicants that belong in a model as explanatory factors are not known and must be determined through a model selection process. We present one model to deal with these needs. This model takes the record of mortalities to form a multinomial distribution in which parameters are modelled as products of conditional daily survival probabilities. These conditional probabilities are in turn modelled as logistic functions of the explanatory factors. The model incorporates lagged values of the explanatory factors to deal with changes in the pattern of mortalities over time. The issue of model selection and assessment is approached through the use of generalized information criteria and power divergence goodness-of-fit tests. These model selection criteria are applied in a cross-validation scheme designed to assess the ability of a model to both fit data used in estimation and predict data deleted from the estimation data set. The example presented demonstrates the need for inclusion of lagged values of the explanatory factors and suggests that penalized likelihood criteria may not provide adequate protection against overparameterized models in model selection.

Do work-related factors contribute to differences in doctor-certified sick leave? A prospective study comparing women in health and social occupations with women in the general working population.

PubMed

Aagestad, Cecilie; Tyssen, Reidar; Sterud, Tom

2016-03-08

Doctor -certified sick leave is prevalent in the health and social sector. We examined whether the higher risk of doctor-certified sick leave in women in health and social occupations compared to women in other occupations was explained by particular work-related psychosocial and mechanical risk factors. A randomly drawn cohort aged 18-69 years from the general population in Norway was surveyed in 2009 (n = 12,255, response at baseline = 60.9 %), and was followed up in the national registry of social transfer payments in 2010. Eligible respondents were women registered with an active employee relationship for ≥100 actual working days in 2009 and 2010 (n = 3032). Using this sample, we compared health and social workers (n = 661) with the general working population (n = 2371). The outcome of interest was long-term sick leave (LTSL) ≥21 working days during 2010. Eight psychosocial and eight mechanical factors were evaluated. After adjusting for age, previous LTSL, education and working hours/week, women in health and social occupations had a higher risk for LTSL compared with women in the general working population (OR = 1.42, 95 % CI = 1.13-1.79; p = 0.003). After adjusting for psychosocial and mechanical factors, 70 % of the excess risk for LTSL was explained compared with the initial model. The main contributory factors to the increased risk were threats of violence and violence, emotional demands and awkward lifting. Psychosocial and mechanical factors explained much of the excess risk for LTSL in women in health and social occupations compared with working women in general. Psychosocial risk factors were the most important contributors.

Anisotropic Rabi model

NASA Astrophysics Data System (ADS)

Xie, Qiong-Tao; Cui, Shuai; Cao, Jun-Peng; Amico, Luigi; Fan, Heng

2014-04-01

We define the anisotropic Rabi model as the generalization of the spin-boson Rabi model: The Hamiltonian system breaks the parity symmetry; the rotating and counterrotating interactions are governed by two different coupling constants; a further parameter introduces a phase factor in the counterrotating terms. The exact energy spectrum and eigenstates of the generalized model are worked out. The solution is obtained as an elaboration of a recently proposed method for the isotropic limit of the model. In this way, we provide a long-sought solution of a cascade of models with immediate relevance in different physical fields, including (i) quantum optics, a two-level atom in single-mode cross-electric and magnetic fields; (ii) solid-state physics, electrons in semiconductors with Rashba and Dresselhaus spin-orbit coupling; and (iii) mesoscopic physics, Josephson-junction flux-qubit quantum circuits.

Multi-Population Invariance with Dichotomous Measures: Combining Multi-Group and MIMIC Methodologies in Evaluating the General Aptitude Test in the Arabic Language

ERIC Educational Resources Information Center

Sideridis, Georgios D.; Tsaousis, Ioannis; Al-harbi, Khaleel A.

2015-01-01

The purpose of the present study was to extend the model of measurement invariance by simultaneously estimating invariance across multiple populations in the dichotomous instrument case using multi-group confirmatory factor analytic and multiple indicator multiple causes (MIMIC) methodologies. Using the Arabic version of the General Aptitude Test…

Gender and General Strain Theory: A Comparison of Strains, Mediating, and Moderating Effects Explaining Three Types of Delinquency

ERIC Educational Resources Information Center

Moon, Byongook; Morash, Merry

2017-01-01

The present study of 659 Korean adolescents tests General Strain Theory's (GST) utility in explaining gender differences in delinquency causation. It models the effects of key strains, negative emotions, and a composite measure of several conditioning factors separately for boys and girls and for delinquency. Consistent with the theory, males and…

Optimisation of a parallel ocean general circulation model

NASA Astrophysics Data System (ADS)

Beare, M. I.; Stevens, D. P.

1997-10-01

This paper presents the development of a general-purpose parallel ocean circulation model, for use on a wide range of computer platforms, from traditional scalar machines to workstation clusters and massively parallel processors. Parallelism is provided, as a modular option, via high-level message-passing routines, thus hiding the technical intricacies from the user. An initial implementation highlights that the parallel efficiency of the model is adversely affected by a number of factors, for which optimisations are discussed and implemented. The resulting ocean code is portable and, in particular, allows science to be achieved on local workstations that could otherwise only be undertaken on state-of-the-art supercomputers.

Investigating Interruptions: Implications for Flightdeck Performance

NASA Technical Reports Server (NTRS)

Latorella, Kara A.

1999-01-01

A fundamental aspect of multiple task management is attending to new stimuli and integrating associated task requirements into an ongoing task set; this is "interruption management" (IM). Anecdotal evidence and field studies indicate the frequency and consequences of interruptions, however experimental investigations of mechanisms influencing IM are scarce. Interruptions on commercial flightdecks are numerous, of various forms, and have been cited as contributing factors in many aviation incident and accident reports. This research grounds an experimental investigation of flightdeck interruptions in a proposed IM stage model. This model organizes basic research, identifies influencing mechanisms, and suggests appropriate dependent measures for IM. Fourteen airline pilots participated in a flightdeck simulation experiment to investigate the general effects of performing an interrupting task and interrupted procedure, and the effects of specific task factors: (1) modality; (2) embeddedness, or goal-level, of an interruption; (3) strength of association, or coupling-strength, between interrupted tasks; (4) semantic similarity; and (5) environmental stress. General effects of interruptions were extremely robust. All individual task factors significantly affected interruption management, except "similarity." Results extend the Interruption Management model, and are interpreted for their implications for interrupted flightdeck performance and intervention strategies for mitigating their effects on the flightdeck.

Summary of spin technology as related to light general-aviation airplanes

NASA Technical Reports Server (NTRS)

Bowman, J. S., Jr.

1971-01-01

A summary was made of all NASA (and NACA) research and experience related to the spin and recovery characteristics of light personal-owner-type general-aviation airplanes. Very little of the research deals with light general-aviation airplanes as such, but many of the airplanes and models tested before and during World War II were similar to present-day light general-aviation airplanes with regard to the factors that are important in spinning. The material is based mainly on the results of spin-tunnel tests of free-spinning dynamically scaled models of about 100 different airplane designs and, whenever possible, includes correlation with full-scale spin tests. The research results are discussed in terms of airplane design considerations and the proper use of controls for recovery.

Evolution of adaptation mechanisms: Adaptation energy, stress, and oscillating death.

PubMed

Gorban, Alexander N; Tyukina, Tatiana A; Smirnova, Elena V; Pokidysheva, Lyudmila I

2016-09-21

In 1938, Selye proposed the notion of adaptation energy and published 'Experimental evidence supporting the conception of adaptation energy.' Adaptation of an animal to different factors appears as the spending of one resource. Adaptation energy is a hypothetical extensive quantity spent for adaptation. This term causes much debate when one takes it literally, as a physical quantity, i.e. a sort of energy. The controversial points of view impede the systematic use of the notion of adaptation energy despite experimental evidence. Nevertheless, the response to many harmful factors often has general non-specific form and we suggest that the mechanisms of physiological adaptation admit a very general and nonspecific description. We aim to demonstrate that Selye׳s adaptation energy is the cornerstone of the top-down approach to modelling of non-specific adaptation processes. We analyze Selye׳s axioms of adaptation energy together with Goldstone׳s modifications and propose a series of models for interpretation of these axioms. Adaptation energy is considered as an internal coordinate on the 'dominant path' in the model of adaptation. The phenomena of 'oscillating death' and 'oscillating remission' are predicted on the base of the dynamical models of adaptation. Natural selection plays a key role in the evolution of mechanisms of physiological adaptation. We use the fitness optimization approach to study of the distribution of resources for neutralization of harmful factors, during adaptation to a multifactor environment, and analyze the optimal strategies for different systems of factors. Copyright © 2016 Elsevier Ltd. All rights reserved.

The complex impact of risk and protective factors on suicide mortality: a study of the Ukrainian general population.

PubMed

Yur'yev, Andriy; Yur'yeva, Lyudmyla; Värnik, Peeter; Lumiste, Kaur; Värnik, Airi

2015-01-01

This study assesses the complex impact of risk and protective factors on suicide mortality in the Ukrainian general population. Data on suicide rates and socioeconomic and medical factors were obtained from the Ukrainian State Statistical Office, WHO, and the European Social Survey. Structural equation modeling was used for data analysis. Religion and education were negatively associated with suicide. The relationship between drug addiction/alcoholism and suicide was positive. The association between urbanization and suicide mortality was negative. The relationship between gross regional product (GRP) and female suicide was slightly negative. Religiosity was the protective factor most strongly linked with suicide mortality followed by urbanization. The harmful role of drug addiction and alcoholism was confirmed. The role of education and GRP is controversial. No striking gender differences were found.

Assessing the factor structures of the 55- and 22-item versions of the conformity to masculine norms inventory.

PubMed

Owen, Jesse

2011-03-01

The current study examined the psychometric properties of the abbreviated versions, 55- and 22-items, of the Conformity to Masculine Norms Inventory (CMNI). The authors tested the factor structure for the 11 subscales of the CMNI-55 and the global masculinity factor for the CMNI-55 and the CMNI-22. In a clinical sample of men and women (n=522), the results supported the 11-factor model. Furthermore, the factor structure was invariant for men and women. The higher order model, which tested the utility of the global masculine score, demonstrated marginal fit. The factor structures for the global masculinity score for the CMNI-22 demonstrated poor fit. Collectively, the results suggest that the CMNI-55 is better represented in a multidimensional construct. The subscales' alpha levels and factor loadings were, generally, within acceptable limits. Gender and ethnic mean level differences are also reported. © The Author(s) 2011

Empirical evidence for an invariant three-factor structure of the Parental Bonding Instrument in six European countries.

PubMed

Heider, Dirk; Matschinger, Herbert; Bernert, Sebastian; Vilagut, Gemma; Martínez-Alonso, Montserrat; Dietrich, Sandra; Angermeyer, Matthias C

2005-06-30

The objective of the present study was to test the Parental Bonding Instrument's (PBI) three-factor structure (care, overprotection, and authoritarianism) found by [Cox, B.J., Enns, M.W., Clara, I.P. 2000, The Parental Bonding Instrument: confirmatory evidence for a three-factor model in a psychiatric clinical sample and in the National Comorbidity Survey, Social Psychiatry and Psychiatric Epidemiology 35 (2000) 353-357.] on an eight-item short form of the scale. A total of 8813 respondents from the six European countries participating in the ESEMeD project (Belgium, France, Germany, Italy, The Netherlands, and Spain) completed either the PBI-paternal or the PBI-maternal scale. Maximum likelihood confirmatory factor analysis was used to compare the original factor model of Cox et al. with a three-factor solution that emerged from an exploration of the structure with principal component factor analysis. When gender and age subgroups, as well as different countries, were taken into account, the accuracy of the model was confirmed. The fit indices for the new model indicated a generally better model fit than the ones for the model originally developed by Cox et al. Further efforts should be directed to the modeling of the dimension authoritarianism. The results provide the opportunity to estimate the influence of the extracted factors on mental disorders in different countries. The application of the short form of the PBI seems suitable primarily for large epidemiological studies.

A refined shear deformation theory for the analysis of laminated plates

NASA Technical Reports Server (NTRS)

Reddy, J. N.

1986-01-01

A refined, third-order plate theory that accounts for the transverse shear strains is presented, the Navier solutions are derived for certain simply supported cross-ply and antisymmetric angle-ply laminates, and finite-element models are developed for general laminates. The new theory does not require the shear correction factors of the first-order theory (i.e., the Reissner-Mindlin plate theory) because the transverse shear stresses are represented parabolically in the present theory. A mixed finite-element model that uses independent approximations of the generalized displacements and generalized moments, and a displacement model that uses only the generalized displacements as degrees of freedom are developed. The displacement model requires C sup 1-continuity of the transverse deflection across the inter-element boundaries, whereas the mixed model requires a C sup 0-element. Also, the mixed model does not require continuous approximations (between elements) of the bending moments. Numerical results are presented to show the accuracy of the present theory in predicting the transverse stresses. Numerical results are also presented for the nonlinear bending of plates, and the results compare well with the experimental results available in the literature.

Risk factors for venous thromboembolic events in pediatric surgical patients: Defining indications for prophylaxis.

PubMed

Cairo, Sarah B; Lautz, Timothy B; Schaefer, Beverly A; Yu, Guan; Naseem, Hibbut-Ur-Rauf; Rothstein, David H

2017-12-27

Venous thromboembolism (VTE) in pediatric surgical patients is a rare event. The risk factors for VTE in pediatric general surgery patients undergoing abdominopelvic procedures are unknown. The American College of Surgeon's National Surgical Quality Improvement Program-Pediatric (NSQIP-P) database (2012-2015) was queried for patients with VTE after abdominopelvic general surgery procedures. Patient and operative variables were assessed to identify risk factors associated with VTE and develop a pediatric risk score. From 2012-2015, 68 of 34,813 (0.20%) patients who underwent abdominopelvic general surgery procedures were diagnosed with VTE. On multivariate analysis, there was no increased risk of VTE based on concomitant malignancy, chemotherapy, inflammatory bowel disease, or laparoscopic surgical approach, while a higher rate of VTE was identified among female patients. The odds of experiencing VTE were increased on stepwise regression for patients older than 15 years and those with preexisting renal failure or a diagnosis of septic shock, patients with American Society of Anesthesia (ASA) classification ≥ 2, and for anesthesia time longer than 2 h. The combination of age > 15 years, ASA classification ≥ 2, anesthesia time > 2 h, renal failure, and septic shock was included in a model for predicting risk of VTE (AUC = 0.907, sensitivity 84.4%, specificity 88.2%). VTE is rare in pediatric patients, but prediction modeling may help identify those patients at heightened risk. Additional studies are needed to validate the factors identified in this study in a risk assessment model as well as to assess the efficacy and cost-effectiveness of prophylaxis methods. Level III, retrospective comparative study. Copyright © 2018. Published by Elsevier Inc.

Computable general equilibrium model fiscal year 2013 capability development report

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

Edwards, Brian Keith; Rivera, Michael Kelly; Boero, Riccardo

This report documents progress made on continued developments of the National Infrastructure Simulation and Analysis Center (NISAC) Computable General Equilibrium Model (NCGEM), developed in fiscal year 2012. In fiscal year 2013, NISAC the treatment of the labor market and tests performed with the model to examine the properties of the solutions computed by the model. To examine these, developers conducted a series of 20 simulations for 20 U.S. States. Each of these simulations compared an economic baseline simulation with an alternative simulation that assumed a 20-percent reduction in overall factor productivity in the manufacturing industries of each State. Differences inmore » the simulation results between the baseline and alternative simulations capture the economic impact of the reduction in factor productivity. While not every State is affected in precisely the same way, the reduction in manufacturing industry productivity negatively affects the manufacturing industries in each State to an extent proportional to the reduction in overall factor productivity. Moreover, overall economic activity decreases when manufacturing sector productivity is reduced. Developers ran two additional simulations: (1) a version of the model for the State of Michigan, with manufacturing divided into two sub-industries (automobile and other vehicle manufacturing as one sub-industry and the rest of manufacturing as the other subindustry); and (2) a version of the model for the United States, divided into 30 industries. NISAC conducted these simulations to illustrate the flexibility of industry definitions in NCGEM and to examine the simulation properties of in more detail.« less

"A psychometric investigation of gender differences and common processes across borderline and antisocial personality disorders": Correction to Chun et al. (2017).

PubMed

2017-07-01

Reports an error in "A psychometric investigation of gender differences and common processes across borderline and antisocial personality disorders" by Seokjoon Chun, Alexa Harris, Margely Carrion, Elizabeth Rojas, Stephen Stark, Carl Lejuez, William V. Lechner and Marina A. Bornovalova ( Journal of Abnormal Psychology , 2017[Jan], Vol 126[1], 76-88). In the article, there were two errors in the article's supplemental material. The supplemental material stated, "In each case, if the relaxed model fit significantly better than the baseline model (i.e., Δ X ²> 3.84, Δ df =2), then the item under investigation was flagged as noninvariant; otherwise the item was marked as invariant." The value for Δ X ² should have been 5.99. The supplemental material also stated, "If there was no decrement in fit as a function of constraining a given item, the item in question was flagged as noninvariant." It should have stated that these items were flagged as invariant. The online version of this article has been corrected. (The following abstract of the original article appeared in record 2016-53090-001.) The comorbidity between borderline personality disorder (BPD) and antisocial personality disorder (ASPD) is well-established, and the 2 disorders share many similarities. However, there are also differences across disorders: most notably, BPD is diagnosed more frequently in women and ASPD in men. We investigated if (a) comorbidity between BPD and ASPD is attributable to 2 discrete disorders or the expression of common underlying processes, and (b) if the model of comorbidity is true across sex. Using a clinical sample of 1,400 drug users in residential substance abuse treatment, we tested 3 competing models to explore whether the comorbidity of ASPD and BPD should be represented by a single common factor, 2 correlated factors, or a bifactor structure involving a general and disorder-specific factors. Next, we tested whether our resulting model was meaningful by examining its relationship with criterion variables previously reported to be associated with BPD and ASPD. The bifactor model provided the best fit and was invariant across sex. Overall, the general factor of the bifactor model significantly accounted for a large percentage of the variance in criterion variables, whereas the BPD and AAB specific factors added little to the models. The association of the general and specific factor with all criterion variables was equal for men and women. Our results suggest common underlying vulnerability accounts for both the comorbidity between BPD and AAB (across sex), and this common vulnerability drives the association with other psychopathology and maladaptive behavior. This in turn has implications for diagnostic classification systems and treatment. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Global sensitivity analysis of GEOS-Chem modeled ozone and hydrogen oxides during the INTEX campaigns

NASA Astrophysics Data System (ADS)

Christian, Kenneth E.; Brune, William H.; Mao, Jingqiu; Ren, Xinrong

2018-02-01

Making sense of modeled atmospheric composition requires not only comparison to in situ measurements but also knowing and quantifying the sensitivity of the model to its input factors. Using a global sensitivity method involving the simultaneous perturbation of many chemical transport model input factors, we find the model uncertainty for ozone (O3), hydroxyl radical (OH), and hydroperoxyl radical (HO2) mixing ratios, and apportion this uncertainty to specific model inputs for the DC-8 flight tracks corresponding to the NASA Intercontinental Chemical Transport Experiment (INTEX) campaigns of 2004 and 2006. In general, when uncertainties in modeled and measured quantities are accounted for, we find agreement between modeled and measured oxidant mixing ratios with the exception of ozone during the Houston flights of the INTEX-B campaign and HO2 for the flights over the northernmost Pacific Ocean during INTEX-B. For ozone and OH, modeled mixing ratios were most sensitive to a bevy of emissions, notably lightning NOx, various surface NOx sources, and isoprene. HO2 mixing ratios were most sensitive to CO and isoprene emissions as well as the aerosol uptake of HO2. With ozone and OH being generally overpredicted by the model, we find better agreement between modeled and measured vertical profiles when reducing NOx emissions from surface as well as lightning sources.

Socio-Historical Factors Mediating Collaborative Teaching and Learning: A Design-Based Investigation and Intervention

ERIC Educational Resources Information Center

Hackett, Jacob

2016-01-01

Collaborative (Co-)teaching is a complex instructional delivery model used to improve teaching practice in inclusive settings. The model involves multiple certified teachers--representing both special and general education--sharing the same space and presenting material to classrooms with a wide variance in learning needs. Co-teaching has become…

Pathways to STEMM Professions for Students from Noncollege Homes

ERIC Educational Resources Information Center

Miller, Jon D.; Pearson, Willie, Jr.

2012-01-01

In this article we use data from the Longitudinal Study of American Youth to examine the influence of parent education on pathways to science, technology, engineering, mathematics, and medicine (STEMM) professions. Building on a general model of factors related to STEMM education and employment, we employ a two-group structural equation model to…

Modelling Question Difficulty in an A Level Physics Examination

ERIC Educational Resources Information Center

Crisp, Victoria; Grayson, Rebecca

2013-01-01

"Item difficulty modelling" is a technique used for a number of purposes such as to support future item development, to explore validity in relation to the constructs that influence difficulty and to predict the difficulty of items. This research attempted to explore the factors influencing question difficulty in a general qualification…

Measuring Experiential Avoidance: A Preliminary Test of a Working Model

ERIC Educational Resources Information Center

Hayes, Steven C.; Strosahl, Kirk; Wilson, Kelly G.; Bissett, Richard T.; Pistorello, Jacqueline; Toarmino, Dosheen; Polusny, Melissa A.; Dykstra, Thane A.; Batten, Sonja V.; Bergan, John; Stewart, Sherry H.; Zvolensky, Michael J.; Eifert, Georg H.; Bond, Frank W.; Forsyth, John P.; Karekla, Maria; Mccurry, Susan M.

2004-01-01

The present study describes the development of a short, general measure of experiential avoidance, based on a specific theoretical approach to this process. A theoretically driven iterative exploratory analysis using structural equation modeling on data from a clinical sample yielded a single factor comprising 9 items. A fully confirmatory factor…

Validated linear dynamic model of electrically-shunted magnetostrictive transducers with application to structural vibration control

NASA Astrophysics Data System (ADS)

Scheidler, Justin J.; Asnani, Vivake M.

2017-03-01

This paper presents a linear model of the fully-coupled electromechanical behavior of a generally-shunted magnetostrictive transducer. The impedance and admittance representations of the model are reported. The model is used to derive the effect of the shunt’s electrical impedance on the storage modulus and loss factor of the transducer without neglecting the inherent resistance of the transducer’s coil. The expressions are normalized and then shown to also represent generally-shunted piezoelectric materials that have a finite leakage resistance. The generalized expressions are simplified for three shunts: resistive, series resistive-capacitive, and inductive, which are considered for shunt damping, resonant shunt damping, and stiffness tuning, respectively. For each shunt, the storage modulus and loss factor are plotted for a wide range of the normalized parameters. Then, important trends and their impact on different applications are discussed. An experimental validation of the transducer model is presented for the case of resistive and resonant shunts. The model closely predicts the measured response for a variety of operating conditions. This paper also introduces a model for the dynamic compliance of a vibrating structure that is coupled to a magnetostrictive transducer for shunt damping and resonant shunt damping applications. This compliance is normalized and then shown to be analogous to that of a structure that is coupled to a piezoelectric material. The derived analogies allow for the observations and equations in the existing literature on structural vibration control using shunted piezoelectric materials to be directly applied to the case of shunted magnetostrictive transducers.

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.

Determination of the key parameters affecting historic communications satellite trends

NASA Technical Reports Server (NTRS)

Namkoong, D.

1984-01-01

Data representing 13 series of commercial communications satellites procured between 1968 and 1982 were analyzed to determine the factors that have contributed to the general reduction over time of the per circuit cost of communications satellites. The model by which the data were analyzed was derived from a general telecommunications application and modified to be more directly applicable for communications satellites. In this model satellite mass, bandwidth-years, and technological change were the variable parameters. A linear, least squares, multiple regression routine was used to obtain the measure of significance of the model. Correlation was measured by coefficient of determination (R super 2) and t-statistic. The results showed that no correlation could be established with satellite mass. Bandwidth-year however, did show a significant correlation. Technological change in the bandwidth-year case was a significant factor in the model. This analysis and the conclusions derived are based on mature technologies, i.e., satellite designs that are evolutions of earlier designs rather than the first of a new generation. The findings, therefore, are appropriate to future satellites only if they are a continuation of design evolution.

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 influence of the weights in the different SA scenarios. However, working with grouped factors resolves this issue and leads to clear importance results.

Ego-resiliency reloaded: a three-component model of general resiliency.

PubMed

Farkas, Dávid; Orosz, Gábor

2015-01-01

Ego-resiliency (ER) is a capacity that enables individuals to adapt to constantly changing environmental demands. The goal of our research was to identify components of Ego-resiliency, and to test the reliability and the structural and convergent validity of the refined version of the ER11 Ego-resiliency scale. In Study 1 we used a factor analytical approach to assess structural validity and to identify factors of Ego-resiliency. Comparing alternative factor-structures, a hierarchical model was chosen including three factors: Active Engagement with the World (AEW), Repertoire of Problem Solving Strategies (RPSS), and Integrated Performance under Stress (IPS). In Study 2, the convergent and divergent validity of the ER11 scale and its factors and their relationship with resilience were tested. The results suggested that resiliency is a double-faced construct, with one function to keep the personality system stable and intact, and the other function to adjust the personality system in an adaptive way to the dynamically changing environment. The stability function is represented by the RPSS and IPS components of ER. Their relationship pattern is similar to other constructs of resilience, e.g. the Revised Connor-Davidson Resilience Scale (R-CD-RISC). The flexibility function is represented by the unit of RPSS and AEW components. In Study 3 we tested ER11 on a Hungarian online representative sample and integrated the results in a model of general resiliency. This framework allows us to grasp both the stability-focused and the plasticity-focused nature of resiliency.

Ego-Resiliency Reloaded: A Three-Component Model of General Resiliency

PubMed Central

Farkas, Dávid; Orosz, Gábor

2015-01-01

Ego-resiliency (ER) is a capacity that enables individuals to adapt to constantly changing environmental demands. The goal of our research was to identify components of Ego-resiliency, and to test the reliability and the structural and convergent validity of the refined version of the ER11 Ego-resiliency scale. In Study 1 we used a factor analytical approach to assess structural validity and to identify factors of Ego-resiliency. Comparing alternative factor-structures, a hierarchical model was chosen including three factors: Active Engagement with the World (AEW), Repertoire of Problem Solving Strategies (RPSS), and Integrated Performance under Stress (IPS). In Study 2, the convergent and divergent validity of the ER11 scale and its factors and their relationship with resilience were tested. The results suggested that resiliency is a double-faced construct, with one function to keep the personality system stable and intact, and the other function to adjust the personality system in an adaptive way to the dynamically changing environment. The stability function is represented by the RPSS and IPS components of ER. Their relationship pattern is similar to other constructs of resilience, e.g. the Revised Connor-Davidson Resilience Scale (R-CD-RISC). The flexibility function is represented by the unit of RPSS and AEW components. In Study 3 we tested ER11 on a Hungarian online representative sample and integrated the results in a model of general resiliency. This framework allows us to grasp both the stability-focused and the plasticity-focused nature of resiliency. PMID:25815881

The structure of intelligence in children and adults with high functioning autism

PubMed Central

Goldstein, Gerald; Allen, Daniel N.; Minshew, Nancy J.; Williams, Diane L.; Volkmar, Fred; Klin, Ami; Schultz, Robert J.

2011-01-01

Confirmatory factor analyses of the traditional 11 subtests of the Wechsler child and adult intelligence scales were accomplished for 137 children and 118 adults with high functioning autism (HFA) and for comparable age groups from the standardization samples contained in the Wechsler manuals. The objective was determining whether HFA groups produced similar best fitting models to those found in the normative samples or formed a separate “social intelligence” factor. Four-factor models incorporating a “social intelligence” factor provided the best fit in both the autism and normative, but the subtest intercorrelations were generally lower in the autism samples. Findings were interpreted in terms of underconnectivity or reduced communication among brain regions in autism. PMID:18444708

Unsteady Aerodynamic Modeling in Roll for the NASA Generic Transport Model

NASA Technical Reports Server (NTRS)

Murphy, Patrick C.; Klein, Vladislav; Frink, Neal T.

2012-01-01

Reducing the impact of loss-of-control conditions on commercial transport aircraft is a primary goal of the NASA Aviation Safety Program. One aspect in developing the supporting technologies is to improve the aerodynamic models that represent these adverse conditions. Aerodynamic models appropriate for loss of control conditions require a more general mathematical representation to predict nonlinear unsteady behaviors. In this paper, a more general mathematical model is proposed for the subscale NASA Generic Transport Model (GTM) that covers both low and high angles of attack. Particular attention is devoted to the stall region where full-scale transports have demonstrated a tendency for roll instability. The complete aerodynamic model was estimated from dynamic wind-tunnel data. Advanced computational methods are used to improve understanding and visualize the flow physics within the region where roll instability is a factor.

Incorporating Neutrophil-to-lymphocyte Ratio and Platelet-to-lymphocyte Ratio in Place of Neutrophil Count and Platelet Count Improves Prognostic Accuracy of the International Metastatic Renal Cell Carcinoma Database Consortium Model

PubMed Central

Chrom, Pawel; Stec, Rafal; Bodnar, Lubomir; Szczylik, Cezary

2018-01-01

Purpose The study investigated whether a replacement of neutrophil count and platelet count by neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) within the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model would improve its prognostic accuracy. Materials and Methods This retrospective analysis included consecutive patients with metastatic renal cell carcinoma treated with first-line tyrosine kinase inhibitors. The IMDC and modified-IMDC models were compared using: concordance index (CI), bias-corrected concordance index (BCCI), calibration plots, the Grønnesby and Borgan test, Bayesian Information Criterion (BIC), generalized R2, Integrated Discrimination Improvement (IDI), and continuous Net Reclassification Index (cNRI) for individual risk factors and the three risk groups. Results Three hundred and twenty-one patients were eligible for analyses. The modified-IMDC model with NLR value of 3.6 and PLR value of 157 was selected for comparison with the IMDC model. Both models were well calibrated. All other measures favoured the modified-IMDC model over the IMDC model (CI, 0.706 vs. 0.677; BCCI, 0.699 vs. 0.671; BIC, 2,176.2 vs. 2,190.7; generalized R2, 0.238 vs. 0.202; IDI, 0.044; cNRI, 0.279 for individual risk factors; and CI, 0.669 vs. 0.641; BCCI, 0.669 vs. 0.641; BIC, 2,183.2 vs. 2,198.1; generalized R2, 0.163 vs. 0.123; IDI, 0.045; cNRI, 0.165 for the three risk groups). Conclusion Incorporation of NLR and PLR in place of neutrophil count and platelet count improved prognostic accuracy of the IMDC model. These findings require external validation before introducing into clinical practice. PMID:28253564

Incorporating Neutrophil-to-lymphocyte Ratio and Platelet-to-lymphocyte Ratio in Place of Neutrophil Count and Platelet Count Improves Prognostic Accuracy of the International Metastatic Renal Cell Carcinoma Database Consortium Model.

PubMed

Chrom, Pawel; Stec, Rafal; Bodnar, Lubomir; Szczylik, Cezary

2018-01-01

The study investigated whether a replacement of neutrophil count and platelet count by neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) within the International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) model would improve its prognostic accuracy. This retrospective analysis included consecutive patients with metastatic renal cell carcinoma treated with first-line tyrosine kinase inhibitors. The IMDC and modified-IMDC models were compared using: concordance index (CI), bias-corrected concordance index (BCCI), calibration plots, the Grønnesby and Borgan test, Bayesian Information Criterion (BIC), generalized R 2 , Integrated Discrimination Improvement (IDI), and continuous Net Reclassification Index (cNRI) for individual risk factors and the three risk groups. Three hundred and twenty-one patients were eligible for analyses. The modified-IMDC model with NLR value of 3.6 and PLR value of 157 was selected for comparison with the IMDC model. Both models were well calibrated. All other measures favoured the modified-IMDC model over the IMDC model (CI, 0.706 vs. 0.677; BCCI, 0.699 vs. 0.671; BIC, 2,176.2 vs. 2,190.7; generalized R 2 , 0.238 vs. 0.202; IDI, 0.044; cNRI, 0.279 for individual risk factors; and CI, 0.669 vs. 0.641; BCCI, 0.669 vs. 0.641; BIC, 2,183.2 vs. 2,198.1; generalized R 2 , 0.163 vs. 0.123; IDI, 0.045; cNRI, 0.165 for the three risk groups). Incorporation of NLR and PLR in place of neutrophil count and platelet count improved prognostic accuracy of the IMDC model. These findings require external validation before introducing into clinical practice.

Types of work-family interface: well-being correlates of negative and positive spillover between work and family.

PubMed

Kinnunen, Ulla; Feldt, Taru; Geurts, Sabine; Pulkkinen, Lea

2006-04-01

The aim of the present study was to test the structure of the work-family interface measure, which was intended to take into account both the positive and negative spillover between work and family demands in both directions. In addition, the links among the types of work-family spillover and the subjects' general and domain-specific well-being were examined. The sample (n = 202) consisted of Finnish employees, aged 42, who had a spouse/partner. Confirmatory factor analyses indicated that a four-factor model, including negative work-to-family spillover, negative family-to-work spillover, positive work-to-family spillover, and positive family-to-work spillover, was superior compared to the other factor models examined. Path analysis showed, as hypothesized, that the negative work-to-family spillover was most strongly related to low well-being at work (job exhaustion) and next strongly to low general well-being (psychological distress), whereas the negative family-to-work spillover was associated with low well-being in the domain of family (marital dissatisfaction). Positive work-to-family spillover was positively related both to well-being at work and general well-being. Inconsistent with our expectations, positive family-to-work spillover was not directly related to any of the well-being indicators examined.

General Health Questionnaire-12 validity in Colombia and factorial equivalence between clinical and nonclinical participants.

PubMed

Ruiz, Francisco J; García-Beltrán, Diana M; Suárez-Falcón, Juan C

2017-10-01

The General Health Questionnaire - 12 (GHQ-12) is a widely used screening self-report for emotional disorders among adults. However, there is little evidence concerning the validity of the GHQ-12 in Colombia and its factorial invariance between nonclinical and clinical samples. Accordingly, the current study aims to explore the GHQ-12 validity in Colombian nonclinical and clinical samples. The GHQ-12 was administered to a total of 1641 participants, including a sample of undergraduates, one of general population, and a clinical sample. The internal consistency of the GHQ-12 across samples was good (overall alpha of .90). The one-factor model showed a good fit to the data and was considered theoretically more coherent than the two-factor model with positive and negative items loading in separate factors. Metric and scalar invariance were observed across nonclinical and clinical samples. The GHQ-12 scores were strongly and positively related to emotional symptoms and experiential avoidance, and negatively related to life satisfaction. According to the receiver operating characteristic (ROC) curves, a threshold score of 11/12 was optimal to identify emotional disorders. In conclusion, the GHQ-12 is a valid screening self-report in Colombia that provides scores that can be compared across clinical and nonclinical participants. Copyright © 2017 Elsevier B.V. All rights reserved.

Clinical application of the five-factor model.

PubMed

Widiger, Thomas A; Presnall, Jennifer Ruth

2013-12-01

The Five-Factor Model (FFM) has become the predominant dimensional model of general personality structure. The purpose of this paper is to suggest a clinical application. A substantial body of research indicates that the personality disorders included within the American Psychiatric Association's (APA) Diagnostic and Statistical Manual of Mental Disorders (DSM) can be understood as extreme and/or maladaptive variants of the FFM (the acronym "DSM" refers to any particular edition of the APA DSM). In addition, the current proposal for the forthcoming fifth edition of the DSM (i.e., DSM-5) is shifting closely toward an FFM dimensional trait model of personality disorder. Advantages of this shifting conceptualization are discussed, including treatment planning. © 2012 Wiley Periodicals, Inc.

Crash data modeling with a generalized estimator.

PubMed

Ye, Zhirui; Xu, Yueru; Lord, Dominique

2018-08-01

The investigation of relationships between traffic crashes and relevant factors is important in traffic safety management. Various methods have been developed for modeling crash data. In real world scenarios, crash data often display the characteristics of over-dispersion. However, on occasions, some crash datasets have exhibited under-dispersion, especially in cases where the data are conditioned upon the mean. The commonly used models (such as the Poisson and the NB regression models) have associated limitations to cope with various degrees of dispersion. In light of this, a generalized event count (GEC) model, which can be generally used to handle over-, equi-, and under-dispersed data, is proposed in this study. This model was first applied to case studies using data from Toronto, characterized by over-dispersion, and then to crash data from railway-highway crossings in Korea, characterized with under-dispersion. The results from the GEC model were compared with those from the Negative binomial and the hyper-Poisson models. The cases studies show that the proposed model provides good performance for crash data characterized with over- and under-dispersion. Moreover, the proposed model simplifies the modeling process and the prediction of crash data. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling the rheological behavior of thermosonic extracted guava, pomelo, and soursop juice concentrates at different concentration and temperature using a new combination model

PubMed Central

Abdullah, Norazlin; Yusof, Yus A.; Talib, Rosnita A.

2017-01-01

Abstract This study has modeled the rheological behavior of thermosonic extracted pink‐fleshed guava, pink‐fleshed pomelo, and soursop juice concentrates at different concentrations and temperatures. The effects of concentration on consistency coefficient (K) and flow behavior index (n) of the fruit juice concentrates was modeled using a master curve which utilized the concentration‐temperature shifting to allow a general prediction of rheological behaviors covering a wide concentration. For modeling the effects of temperature on K and n, the integration of two functions from the Arrhenius and logistic sigmoidal growth equations has provided a new model which gave better description of the properties. It also alleviated the problems of negative region when using the Arrhenius model alone. The fitted regression using this new model has improved coefficient of determination, R 2 values above 0.9792 as compared to using the Arrhenius and logistic sigmoidal models alone, which presented minimum R 2 of 0.6243 and 0.9440, respectively. Practical applications In general, juice concentrate is a better form of food for transportation, preservation, and ingredient. Models are necessary to predict the effects of processing factors such as concentration and temperature on the rheological behavior of juice concentrates. The modeling approach allows prediction of behaviors and determination of processing parameters. The master curve model introduced in this study simplifies and generalized rheological behavior of juice concentrates over a wide range of concentration when temperature factor is insignificant. The proposed new mathematical model from the combination of the Arrhenius and logistic sigmoidal growth models has improved and extended description of rheological properties of fruit juice concentrates. It also solved problems of negative values of consistency coefficient and flow behavior index prediction using existing model, the Arrhenius equation. These rheological data modeling provide good information for the juice processing and equipment manufacturing needs. PMID:29479123

DYNAMO-HIA–A Dynamic Modeling Tool for Generic Health Impact Assessments

PubMed Central

Lhachimi, Stefan K.; Nusselder, Wilma J.; Smit, Henriette A.; van Baal, Pieter; Baili, Paolo; Bennett, Kathleen; Fernández, Esteve; Kulik, Margarete C.; Lobstein, Tim; Pomerleau, Joceline; Mackenbach, Johan P.; Boshuizen, Hendriek C.

2012-01-01

Background Currently, no standard tool is publicly available that allows researchers or policy-makers to quantify the impact of policies using epidemiological evidence within the causal framework of Health Impact Assessment (HIA). A standard tool should comply with three technical criteria (real-life population, dynamic projection, explicit risk-factor states) and three usability criteria (modest data requirements, rich model output, generally accessible) to be useful in the applied setting of HIA. With DYNAMO-HIA (Dynamic Modeling for Health Impact Assessment), we introduce such a generic software tool specifically designed to facilitate quantification in the assessment of the health impacts of policies. Methods and Results DYNAMO-HIA quantifies the impact of user-specified risk-factor changes on multiple diseases and in turn on overall population health, comparing one reference scenario with one or more intervention scenarios. The Markov-based modeling approach allows for explicit risk-factor states and simulation of a real-life population. A built-in parameter estimation module ensures that only standard population-level epidemiological evidence is required, i.e. data on incidence, prevalence, relative risks, and mortality. DYNAMO-HIA provides a rich output of summary measures – e.g. life expectancy and disease-free life expectancy – and detailed data – e.g. prevalences and mortality/survival rates – by age, sex, and risk-factor status over time. DYNAMO-HIA is controlled via a graphical user interface and is publicly available from the internet, ensuring general accessibility. We illustrate the use of DYNAMO-HIA with two example applications: a policy causing an overall increase in alcohol consumption and quantifying the disease-burden of smoking. Conclusion By combining modest data needs with general accessibility and user friendliness within the causal framework of HIA, DYNAMO-HIA is a potential standard tool for health impact assessment based on epidemiologic evidence. PMID:22590491

Predictors of good general health, well-being, and musculoskeletal disorders in Swedish dental hygienists.

PubMed

Ylipää, V; Arnetz, B B; Preber, H

1999-10-01

The aim of the present study was to examine how different personal, physical, and psychosocial work-associated factors are related to good general health, well-being, and musculoskeletal disorders in dental hygienists. A questionnaire was mailed to 575 dental hygienists who were randomly sampled from the Swedish Dental Hygienists' Association (86% responded). Data were analyzed with multiple-logistic regression models. The results showed that high clinical-practice fraction, active leisure, and high management support increased the odds for good general health, while work and family overload decreased the odds. Management support and mastery of work increased the odds for well-being, while work and family overload and high work efficiency decreased them. Scaling work increased the odds for general and work-related musculoskeletal disorders in all parts of the upper body and arms but not in the lower back. In the upper body, active leisure decreased the odds for general musculoskeletal disorders, while the odds for work-related musculoskeletal disorders increased from work and family overload and decreased from many weekly working hours. Many years in the profession increased the odds for general finger disorders. In conclusion, the results suggest that active leisure and several psychosocial work factors strongly influence good general health and well-being. Physical tasks influence musculoskeletal disorders more than active leisure and psychosocial work factors.

Implementing new care models: learning from the Greater Manchester demonstrator pilot experience.

PubMed

Elvey, Rebecca; Bailey, Simon; Checkland, Kath; McBride, Anne; Parkin, Stephen; Rothwell, Katy; Hodgson, Damian

2018-06-19

Current health policy focuses on improving accessibility, increasing integration and shifting resources from hospitals to community and primary care. Initiatives aimed at achieving these policy aims have supported the implementation of various 'new models of care', including general practice offering 'additional availability' appointments during evenings and at weekends. In Greater Manchester, six 'demonstrator sites' were funded: four sites delivered additional availability appointments, other services included case management and rapid response. The aim of this paper is to explore the factors influencing the implementation of services within a programme designed to improve access to primary care. The paper consists of a qualitative process evaluation undertaken within provider organisations, including general practices, hospitals and care homes. Semi-structured interviews, with the data subjected to thematic analysis. Ninety-one people participated in interviews. Six key factors were identified as important for the establishment and running of the demonstrators: information technology; information governance; workforce and organisational development; communications and engagement; supporting infrastructure; federations and alliances. These factors brought to light challenges in the attempt to provide new or modify existing services. Underpinning all factors was the issue of trust; there was consensus amongst our participants that trusting relationships, particularly between general practices, were vital for collaboration. It was also crucial that general practices trusted in the integrity of anyone external who was to work with the practice, particularly if they were to access data on the practice computer system. A dialogical approach was required, which enabled staff to see themselves as active rather than passive participants. The research highlights various challenges presented by the context within which extended access is implemented. Trust was the fundamental underlying issue; there was consensus amongst participants that trusting relationships were vital for effective collaboration in primary care.

The supply of general practitioners across local areas: accounting for spatial heterogeneity.

PubMed

McIsaac, Michelle; Scott, Anthony; Kalb, Guyonne

2015-10-03

The geographic distribution of general practitioners (GPs) remains persistently unequal in many countries despite notable increases in overall supply. This paper explores how the factors associated with the supply of general practitioners (GPs) are aligned with the arbitrary geographic boundaries imposed by the use of spatially referenced GP supply data. Data on GP supply in postcodes within Australia are matched to data on the population characteristics and levels of amenities in postcodes. Tobit regression models are used that examine the associations between GP supply and postcode characteristics, whilst accounting for spatial heterogeneity. The results demonstrate that GPs do not consider space in a one-dimensional sense. Location choice is related to both neighbourhood-specific factors, such as hospitals, and broader area factors, such as area income and proximity to private schools. Although the proportion of females and elderly were related to GPs supply, mortality rate was not. This paper represents the first attempt to map the factors influencing GP supply to the appropriate geographic level at which GPs may be considering that factor. We suggest that both neighbourhood and broader regional characteristics can influence GPs' locational choices. This finding is highly relevant to the design and evaluation of relocation incentive programmes.

The role of self-perceived usefulness and competence in the self-esteem of elderly adults: confirmatory factor analyses of the Bachman revision of Rosenberg's Self-Esteem Scale.

PubMed

Ranzijn, R; Keeves, J; Luszcz, M; Feather, N T

1998-03-01

This article reports on a confirmatory analytic study of the Bachman Revision (1970) of Rosenberg's Self-Esteem Scale (1965) that was used in the Australian Longitudinal Study of Ageing (ALSA). Participants comprised 1,087 elderly people aged between 70 and 103 years (mean 77 years). Five competing factor models were tested with LISREL8. The best-fitting model was a nested one, with a General Self-Esteem second-order factor and two first-order factors, Positive Self-regard and Usefulness/Competence. This model was validated with data from a later wave of ALSA. Usefulness and competence have received little attention in the gerontological literature to date. Preliminary results indicate that usefulness/competence may be an important predictor of well-being. Further work is required on the relationships among usefulness, competence, self-esteem, and well-being in elderly people.

Construct validation of SF-36 Malay version among type 2 diabetes mellitus patients

NASA Astrophysics Data System (ADS)

Yap, Bee Wah; Jannoo, Zeinab; Razali, Nornadiah Mohd; Ghani, Nor Azura Md.; Lazim, Mohamad Alias

2015-02-01

The Short Form 36 (SF-36) is one of the most widely used generic health status measure. This study used the SF-36 Health Survey instrument to investigate the functional health and well-being of Malay Type 2 Diabetes Mellitus patients in Malaysia. The survey was carried out in three local hospitals in Selangor. The method of questionnaire administration was both self-administered and interviewer administered. A total of 354 questionnaires was returned, but only 295 questionnaires with no missing data were analyzed. Confirmatory Factor Analysis (CFA) was used to confirm the first-order and third-order CFA models. The higher order analyses included a third-order CFA models with two second-order factors (physical and mental component) and three second-order factors (physical, general well-being and mental health) and both showed satisfactory model fit indices. This study confirmed the multidimensional factor structure of the SF-36.

General distress is more important than PTSD's cognition and mood alterations factor in accounting for PTSD and depression's comorbidity.

PubMed

Byllesby, Brianna M; Elhai, Jon D; Tamburrino, Marijo; Fine, Thomas H; Cohen, Gregory; Sampson, Laura; Shirley, Edwin; Chan, Philip K; Liberzon, Israel; Galea, Sandro; Calabrese, Joseph R

2017-03-15

Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are highly comorbid and exhibit strong correlations with each other at both the symptom level and latent factor level. Various theories have attempted to explain this relationship. Results have been inconsistent regarding whether PTSD's negative alterations in cognition and mood factor (NACM) is significantly more related to depression, in contrast to other factors of PTSD. Confirmatory factor analysis was used to attempt to address the relationships between PTSD and MDD in a large sample of trauma-exposed combat veterans from the Ohio National Guard as part of a larger longitudinal study. Confirmatory factor analysis was used to test a bifactor model of PTSD symptoms, testing relations between PTSD's factors and a latent depressive factor. After partitioning out the common variance into the bifactor, we found that in contrast to other PTSD factors, PTSD's NACM factor was not significantly more related to depression. Instead, only the general bifactor predicted depressive symptoms. The limitations of the present study include the following: the specific measures of PTSD and MDD used were based on self-report, and the sample consisted of non-clinical, non-treatment seeking veterans. The present study suggests that the high rate of comorbidity between posttraumatic stress disorder (PTSD) and major depressive disorder is more related to underlying general distress or negative affectivity than the symptom categories of the PTSD diagnostic criteria. Copyright © 2017 Elsevier B.V. All rights reserved.

The microcomputer scientific software series 3: general linear model--analysis of variance.

Treesearch

Harold M. Rauscher

1985-01-01

A BASIC language set of programs, designed for use on microcomputers, is presented. This set of programs will perform the analysis of variance for any statistical model describing either balanced or unbalanced designs. The program computes and displays the degrees of freedom, Type I sum of squares, and the mean square for the overall model, the error, and each factor...

Ethnicity, work-related stress and subjective reports of health by migrant workers: a multi-dimensional model.

PubMed

Capasso, Roberto; Zurlo, Maria Clelia; Smith, Andrew P

2018-02-01

This study integrates different aspects of ethnicity and work-related stress dimensions (based on the Demands-Resources-Individual-Effects model, DRIVE [Mark, G. M., and A. P. Smith. 2008. "Stress Models: A Review and Suggested New Direction." In Occupational Health Psychology, edited by J. Houdmont and S. Leka, 111-144. Nottingham: Nottingham University Press]) and aims to test a multi-dimensional model that combines individual differences, ethnicity dimensions, work characteristics, and perceived job satisfaction/stress as independent variables in the prediction of subjectives reports of health by workers differing in ethnicity. A questionnaire consisting of the following sections was submitted to 900 workers in Southern Italy: for individual and cultural characteristics, coping strategies, personality behaviours, and acculturation strategies; for work characteristics, perceived job demands and job resources/rewards; for appraisals, perceived job stress/satisfaction and racial discrimination; for subjective reports of health, psychological disorders and general health. To test the reliability and construct validity of the extracted factors referred to all dimensions involved in the proposed model and logistic regression analyses to evaluate the main effects of the independent variables on the health outcomes were conducted. Principal component analysis (PCA) yielded seven factors for individual and cultural characteristics (emotional/relational coping, objective coping, Type A behaviour, negative affectivity, social inhibition, affirmation/maintenance culture, and search identity/adoption of the host culture); three factors for work characteristics (work demands, intrinsic/extrinsic rewards, and work resources); three factors for appraisals (perceived job satisfaction, perceived job stress, perceived racial discrimination) and three factors for subjective reports of health (interpersonal disorders, anxious-depressive disorders, and general health). Logistic regression analyses showed main effects of specific individual and cultural differences, work characteristics and perceived job satisfaction/stress on the risk of suffering health problems. The suggested model provides a strong framework that illustrates how psychosocial and individual variables can influence occupational health in multi-cultural workplaces.

Assessment of adolescents' motivation for educational attainment.

PubMed

Cham, Heining; Hughes, Jan N; West, Stephen G; Im, Myung Hee

2014-06-01

The Adolescent Motivation for Educational Attainment Questionnaire is a 32-item questionnaire (we drew 20 items from 3 subscales of the Educational Motivation Questionnaire; Murdock, 1999) that was developed to measure multiple potential dimensions of adolescents' motivation to complete high school and enroll in post-secondary education, including competence and effort beliefs; perceived value of education; and peer, teacher, and parent support for educational attainment. We assessed a multiethnic sample (N = 569) of low-achieving students who started 1st grade together in 1 urban and 2 small city school districts. Participants were assessed over 2 consecutive years (Grades 8 and 9 given prior grade retention, or Grades 9 and 10 if not retained). Exploratory factor analyses identified 4 correlated dimensions underlying the questionnaire responses. Subsequent confirmatory factor analyses provided support for a bifactor model, which includes a general factor of students' basic educational motivation, and specific factors of (a) teacher educational expectations, (b) peer aspirations, and (c) value of education. Measurement invariance of the bifactor model was established across students' gender and ethnicity (Caucasian, African American, and Hispanic) and year of testing. Criterion-related validity of the general and specific factors with students' school belonging, student-teacher warmth and conflict, disciplinary practices, letter grade, conduct problems, and behavioral engagement was examined. Practical implications of the measure are discussed.

Assessment of Adolescents’ Motivation for Educational Attainment

PubMed Central

Cham, Heining; Hughes, Jan N.; West, Stephen G.; Im, Myung Hee

2015-01-01

The Adolescent Motivation for Educational Attainment Questionnaire is a 32-item questionnaire (we drew 20 items from 3 subscales of the Educational Motivation Questionnaire; Murdock, 1999) that was developed to measure multiple potential dimensions of adolescents’ motivation to complete high school and enroll in post-secondary education, including competence and effort beliefs; perceived value of education; and peer, teacher, and parent support for educational attainment. We assessed a multiethnic sample (N = 569) of low-achieving students who started 1st grade together in 1 urban and 2 small city school districts. Participants were assessed over 2 consecutive years (Grades 8 and 9 given prior grade retention, or Grades 9 and 10 if not retained). Exploratory factor analyses identified 4 correlated dimensions underlying the questionnaire responses. Subsequent confirmatory factor analyses provided support for a bifactor model, which includes a general factor of students’ basic educational motivation, and specific factors of (a) teacher educational expectations, (b) peer aspirations, and (c) value of education. Measurement invariance of the bifactor model was established across students’ gender and ethnicity (Caucasian, African American, and Hispanic) and year of testing. Criterion-related validity of the general and specific factors with students’ school belonging, student–teacher warmth and conflict, disciplinary practices, letter grade, conduct problems, and behavioral engagement was examined. Practical implications of the measure are discussed. PMID:24588748

Artificial neural network models for prediction of cardiovascular autonomic dysfunction in general Chinese population

PubMed Central

2013-01-01

Background The present study aimed to develop an artificial neural network (ANN) based prediction model for cardiovascular autonomic (CA) dysfunction in the general population. Methods We analyzed a previous dataset based on a population sample consisted of 2,092 individuals aged 30–80 years. The prediction models were derived from an exploratory set using ANN analysis. Performances of these prediction models were evaluated in the validation set. Results Univariate analysis indicated that 14 risk factors showed statistically significant association with CA dysfunction (P < 0.05). The mean area under the receiver-operating curve was 0.762 (95% CI 0.732–0.793) for prediction model developed using ANN analysis. The mean sensitivity, specificity, positive and negative predictive values were similar in the prediction models was 0.751, 0.665, 0.330 and 0.924, respectively. All HL statistics were less than 15.0. Conclusion ANN is an effective tool for developing prediction models with high value for predicting CA dysfunction among the general population. PMID:23902963

Towards realistic singularity-free cosmological models

NASA Astrophysics Data System (ADS)

Senovilla, José M. M.

1996-02-01

We present an explicit general family of inhomogeneous cosmological models. The family contains an arbitrary function of comoving time (interpretable as the cosmological scale factor) and four arbitrary parameters. In general, it is a solution of Einstein's field equations for a fluid with anisotropic pressures, but it also includes a big subfamily of perfect-fluid metrics. The most interesting feature of this family is that it contains both all the diagonal separable singularity-free cosmological models recently found and all the Friedmann-Lemaître-Robertson-Walker standard models. This property allows one to speculate on the construction of some interesting models in which the Universe has been FLRW-like from some time on (for instance, since the nucleeosynthesis time), but it also went through primordial singularity-free inhomogeneous epochs (in fact, there are quite natural possibilities in which these primordial epochs are inflationary) without ever violating energy conditions or other physical properties. Nevertheless, the physical processes leading to the isotropization and homogenization of the Universe are not fixed nor indicated by the models themselves. The interesting properties of the general model are studied in some detail. ¢ 1996 The American Physical Society.

The hierarchical structure of DSM-5 pathological personality traits.

PubMed

Wright, Aidan G C; Thomas, Katherine M; Hopwood, Christopher J; Markon, Kristian E; Pincus, Aaron L; Krueger, Robert F

2012-11-01

A multidimensional trait system has been proposed for representing personality disorder (PD) features in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) to address problematic classification issues such as comorbidity. In this model, which may also assist in providing scaffolding for the underlying structure of major forms of psychopathology more generally, 25 primary traits are organized by 5 higher order dimensions: Negative Affect, Detachment, Antagonism, Disinhibition, and Psychoticism. We examined (a) the generalizability of the structure proposed for DSM-5 PD traits, and (b) the potential for an integrative hierarchy based upon DSM-5 PD traits to represent the dimensions scaffolding psychopathology more generally. A large sample of student participants (N = 2,461) completed the Personality Inventory for DSM-5, which operationalizes the DSM-5 traits. Exploratory factor analysis replicated the initially reported 5-factor structure, as indicated by high factor congruencies. The 2-, 3-, and 4-factor solutions estimated in the hierarchy of the DSM-5 traits bear close resemblance to existing models of common mental disorders, temperament, and personality pathology. Thus, beyond the description of individual differences in personality disorder, the trait dimensions might provide a framework for the metastructure of psychopathology in the DSM-5 and the integration of a number of ostensibly competing models of personality trait covariation. (PsycINFO Database Record (c) 2012 APA, all rights reserved).

[Approach to the Development of Mind and Persona].

PubMed

Sawaguchi, Toshiko

2018-01-01

To access medical specialists by health specialists working in the regional health field, the possibility of utilizing the voice approach for dissociative identity disorder (DID) patients as a health assessment for medical access (HAMA) was investigated. The first step is to investigate whether the plural personae in a single DID patient can be discriminated by voice analysis. Voices of DID patients including these with different personae were extracted from YouTube and were analysed using the software PRAAT with basic frequency, oral factors, chin factors and tongue factors. In addition, RAKUGO story teller voices made artificially and dramatically were analysed in the same manner. Quantitive and qualitative analysis method were carried out and nested logistic regression and a nested generalized linear model was developed. The voice from different personae in one DID patient could be visually and easily distinquished using basic frequency curve, cluster analysis and factor analysis. In the canonical analysis, only Roy's maximum root was <0.01. In the nested generalized linear model, the model using a standard deviation (SD) indicator fit best and some other possibilities are shown here. In DID patients, the short transition time among plural personae could guide to the risky situation such as suicide. So if the voice approach can show the time threshold of changes between the different personae, it would be useful as an Access Assessment in the form of a simple HAMA.

The generality of working memory capacity: a latent-variable approach to verbal and visuospatial memory span and reasoning.

PubMed

Kane, Michael J; Hambrick, David Z; Tuholski, Stephen W; Wilhelm, Oliver; Payne, Tabitha W; Engle, Randall W

2004-06-01

A latent-variable study examined whether verbal and visuospatial working memory (WM) capacity measures reflect a primarily domain-general construct by testing 236 participants in 3 span tests each of verbal WM. visuospatial WM, verbal short-term memory (STM), and visuospatial STM. as well as in tests of verbal and spatial reasoning and general fluid intelligence (Gf). Confirmatory' factor analyses and structural equation models indicated that the WM tasks largely reflected a domain-general factor, whereas STM tasks, based on the same stimuli as the WM tasks, were much more domain specific. The WM construct was a strong predictor of Gf and a weaker predictor of domain-specific reasoning, and the reverse was true for the STM construct. The findings support a domain-general view of WM capacity, in which executive-attention processes drive the broad predictive utility of WM span measures, and domain-specific storage and rehearsal processes relate more strongly to domain-specific aspects of complex cognition. ((c) 2004 APA, all rights reserved)

Risk Factors for Running Away among a General Population Sample of Males and Females

ERIC Educational Resources Information Center

Tyler, Kimberly A.; Hagewen, Kellie J.; Melander, Lisa A.

2011-01-01

The present study examines risk factors for running away and homelessness among a sample of more than 7,000 currently housed youth using the National Longitudinal Study of Adolescent Health (Add Health). Structural equation modeling results revealed that those with greater levels of family instability and those who ran away at Wave 2 were…

Comparison of Five Modeling Approaches to Quantify and Estimate the Effect of Clouds on the Radiation Amplification Factor (RAF) for Solar Ultraviolet Radiation

EPA Science Inventory

A generally accepted value for the Radiation Amplification Factor (RAF), with respect to the erythemal action spectrum for sunburn of human skin, is −1.1, indicating that a 1.0% increase in stratospheric ozone leads to a 1.1% decrease in the biologically damaging UV radiation in ...

Gender and education impact on brain aging: a general cognitive factor approach.

PubMed

Proust-Lima, Cécile; Amieva, Hélène; Letenneur, Luc; Orgogozo, Jean-Marc; Jacqmin-Gadda, Hélène; Dartigues, Jean-François

2008-09-01

In cognitive aging research, the study of a general cognitive factor has been shown to have a substantial explanatory power over the study of isolated tests. The authors aimed at differentiating the impact of gender and education on global cognitive change with age from their differential impact on 4 psychometric tests using a new latent process approach, which intermediates between a single-factor longitudinal model for sum scores and an item-response theory approach for longitudinal data. The analysis was conducted on a sample of 2,228 subjects from PAQUID, a population-based cohort of older adults followed for 13 years with repeated measures of cognition. Adjusted for vascular factors, the analysis confirmed that women performed better in tests involving verbal components, while men performed better in tests involving visuospatial skills. In addition, the model suggested that women had a slightly steeper global cognitive decline with oldest age than men, even after excluding incident dementia or death. Subjects with higher education exhibited a better mean score for the 4 tests, but this difference tended to attenuate with age for tests involving a speed component. (c) 2008 APA, all rights reserved

General solution for diffusion-controlled dissolution of spherical particles. 1. Theory.

PubMed

Wang, J; Flanagan, D R

1999-07-01

Three classical particle dissolution rate expressions are commonly used to interpret particle dissolution rate phenomena. Our analysis shows that an assumption used in the derivation of the traditional cube-root law may not be accurate under all conditions for diffusion-controlled particle dissolution. Mathematical analysis shows that the three classical particle dissolution rate expressions are approximate solutions to a general diffusion layer model. The cube-root law is most appropriate when particle size is much larger than the diffusion layer thickness, the two-thirds-root expression applies when the particle size is much smaller than the diffusion layer thickness. The square-root expression is intermediate between these two models. A general solution to the diffusion layer model for monodispersed spherical particles dissolution was derived for sink and nonsink conditions. Constant diffusion layer thickness was assumed in the derivation. Simulated dissolution data showed that the ratio between particle size and diffusion layer thickness (a0/h) is an important factor in controlling the shape of particle dissolution profiles. A new semiempirical general particle dissolution equation is also discussed which encompasses the three classical particle dissolution expressions. The success of the general equation in explaining limitations of traditional particle dissolution expressions demonstrates the usefulness of the general diffusion layer model.

Examination of a Bifactor Model of Obsessive-Compulsive Symptom Dimensions.

PubMed

Olatunji, Bunmi O; Ebesutani, Chad; Abramowitz, Jonathan S

2017-01-01

Although obsessive-compulsive (OC) symptoms are observed along four dimensions (contamination, responsibility for harm, order/symmetry, and unacceptable thoughts), the structure of the dimensions remains unclear. The current study evaluated a bifactor model of OC symptoms among those with and without obsessive-compulsive disorder (OCD). The goals were (a) to evaluate if OC symptoms should be conceptualized as unidimensional or whether distinct dimensions should be interpreted and (b) to use structural equation modeling to examine the convergence of the OC dimensions above and beyond a general dimension with related criteria. Results revealed that a bifactor model fit the data well and that OC symptoms were influenced by a general dimension and by four dimensions. Measurement invariance of the bifactor model was also supported among those with and without OCD. However, the general OC dimension accounted for only half of the variability in OC symptoms, with the remaining variability accounted for by distinct dimensions. Despite evidence of multidimensionality, the dimensions were unreliable after covarying for the general OC dimension. However, the four dimensions did significantly converge with a latent OC spectrum factor above and beyond the general OC dimension. The implications of these findings for conceptualizing the structure of OCD are discussed. © The Author(s) 2015.

A Generalized Stability Analysis of the AMOC in Earth System Models: Implication for Decadal Variability and Abrupt Climate Change

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

Fedorov, Alexey V.

2015-01-14

The central goal of this research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) as related to climate variability and abrupt climate change within a hierarchy of climate models ranging from realistic ocean models to comprehensive Earth system models. Generalized Stability Analysis, a method that quantifies the transient and asymptotic growth of perturbations in the system, is one of the main approaches used throughout this project. The topics we have explored range from physical mechanisms that control AMOC variability to the factors that determine AMOC predictability in the Earth systemmore » models, to the stability and variability of the AMOC in past climates.« less

Relationships Between Self-Efficacy, Self-Esteem and Procrastination in Undergraduate Psychology Students

PubMed Central

Hajloo, Nader

2014-01-01

Objective: The present study aimed to review the relationships between procrastination and two self-factors self-efficacy and self-esteem. Methods: Participants were 140 undergraduates Psychology students enrolled in Mohagheg Ardabili University, Ardabil, Iran. Instruments used for collecting the required data were the student-version of the General Procrastination Scale (GP-S), General Self-Efficacy Scale (GSE) and Rosenberg’s Self-Esteem Scale (SES). Results: Using causal modeling, two models were compared; a model with self-esteem as a mediator versus a model with procrastination as a mediator. The self-esteem mediator model accounted for 21% of the variance in procrastination. The significance of the mediation effect was found by bootstrapping method. Conclusion: The relationship of procrastination with self-esteem and self-efficacy was revealed among undergraduate psychology students. PMID:25780374

Relationships between self-efficacy, self-esteem and procrastination in undergraduate psychology students.

PubMed

Hajloo, Nader

2014-01-01

The present study aimed to review the relationships between procrastination and two self-factors self-efficacy and self-esteem. Participants were 140 undergraduates Psychology students enrolled in Mohagheg Ardabili University, Ardabil, Iran. Instruments used for collecting the required data were the student-version of the General Procrastination Scale (GP-S), General Self-Efficacy Scale (GSE) and Rosenberg's Self-Esteem Scale (SES). Using causal modeling, two models were compared; a model with self-esteem as a mediator versus a model with procrastination as a mediator. The self-esteem mediator model accounted for 21% of the variance in procrastination. The significance of the mediation effect was found by bootstrapping method. The relationship of procrastination with self-esteem and self-efficacy was revealed among undergraduate psychology students.

Removing an intersubject variance component in a general linear model improves multiway factoring of event-related spectral perturbations in group EEG studies.

PubMed

Spence, Jeffrey S; Brier, Matthew R; Hart, John; Ferree, Thomas C

2013-03-01

Linear statistical models are used very effectively to assess task-related differences in EEG power spectral analyses. Mixed models, in particular, accommodate more than one variance component in a multisubject study, where many trials of each condition of interest are measured on each subject. Generally, intra- and intersubject variances are both important to determine correct standard errors for inference on functions of model parameters, but it is often assumed that intersubject variance is the most important consideration in a group study. In this article, we show that, under common assumptions, estimates of some functions of model parameters, including estimates of task-related differences, are properly tested relative to the intrasubject variance component only. A substantial gain in statistical power can arise from the proper separation of variance components when there is more than one source of variability. We first develop this result analytically, then show how it benefits a multiway factoring of spectral, spatial, and temporal components from EEG data acquired in a group of healthy subjects performing a well-studied response inhibition task. Copyright © 2011 Wiley Periodicals, Inc.

VISCOPLASTIC FLUID MODEL FOR DEBRIS FLOW ROUTING.

USGS Publications Warehouse

Chen, Cheng-lung

1986-01-01

This paper describes how a generalized viscoplastic fluid model, which was developed based on non-Newtonian fluid mechanics, can be successfully applied to routing a debris flow down a channel. The one-dimensional dynamic equations developed for unsteady clear-water flow can be used for debris flow routing if the flow parameters, such as the momentum (or energy) correction factor and the resistance coefficient, can be accurately evaluated. The writer's generalized viscoplastic fluid model can be used to express such flow parameters in terms of the rheological parameters for debris flow in wide channels. A preliminary analysis of the theoretical solutions reveals the importance of the flow behavior index and the so-called modified Froude number for uniformly progressive flow in snout profile modeling.

A Review and Conceptual Model of Factors Correlated with Postmortem Root Band Formation.

PubMed

Donfack, Joseph; Castillo, Hilda S

2018-03-12

It is generally accepted within the forensic trace evidence community that a postmortem root band (PMRB) can appear in the root of hairs attached to remains during decomposition. Presently, the specific sequences of events and/or exact molecular signals that lead to the formation of a PMRB are not well understood. The published literature addressing the abiotic and biotic factors that correlate with the formation of PMRBs is reviewed and a conceptual model for the formation of PMRBs is proposed. © 2018 American Academy of Forensic Sciences.

Designers' models of the human-computer interface

NASA Technical Reports Server (NTRS)

Gillan, Douglas J.; Breedin, Sarah D.

1993-01-01

Understanding design models of the human-computer interface (HCI) may produce two types of benefits. First, interface development often requires input from two different types of experts: human factors specialists and software developers. Given the differences in their backgrounds and roles, human factors specialists and software developers may have different cognitive models of the HCI. Yet, they have to communicate about the interface as part of the design process. If they have different models, their interactions are likely to involve a certain amount of miscommunication. Second, the design process in general is likely to be guided by designers' cognitive models of the HCI, as well as by their knowledge of the user, tasks, and system. Designers do not start with a blank slate; rather they begin with a general model of the object they are designing. The author's approach to a design model of the HCI was to have three groups make judgments of categorical similarity about the components of an interface: human factors specialists with HCI design experience, software developers with HCI design experience, and a baseline group of computer users with no experience in HCI design. The components of the user interface included both display components such as windows, text, and graphics, and user interaction concepts, such as command language, editing, and help. The judgments of the three groups were analyzed using hierarchical cluster analysis and Pathfinder. These methods indicated, respectively, how the groups categorized the concepts, and network representations of the concepts for each group. The Pathfinder analysis provides greater information about local, pairwise relations among concepts, whereas the cluster analysis shows global, categorical relations to a greater extent.

Modeling Long-term Behavior of Stock Market Prices Using Differential Equations

NASA Astrophysics Data System (ADS)

Yang, Xiaoxiang; Zhao, Conan; Mazilu, Irina

2015-03-01

Due to incomplete information available in the market and uncertainties associated with the price determination process, the stock prices fluctuate randomly during a short period of time. In the long run, however, certain economic factors, such as the interest rate, the inflation rate, and the company's revenue growth rate, will cause a gradual shift in the stock price. Thus, in this paper, a differential equation model has been constructed in order to study the effects of these factors on the stock prices. The model obtained accurately describes the general trends in the AAPL and XOM stock price changes over the last ten years.

Rainfall erosivity in the Fukushima Prefecture: implications for radiocesium mobilization and migration

NASA Astrophysics Data System (ADS)

Laceby, J. Patrick; Chartin, Caroline; Degan, Francesca; Onda, Yuichi; Evrard, Olivier; Cerdan, Olivier; Ayrault, Sophie

2015-04-01

The Fukushima Dai-ichi nuclear power plant (FDNPP) accident in March 2011 led to the fallout of predominantly radiocesium (137Cs and 134Cs) on soils of the Fukushima Prefecture. This radiocesium was primarily fixated to fine soil particles. Subsequently, rainfall and snow melt run-off events result in significant quantities of radiocesium being eroded and transported throughout the coastal catchments and ultimately exported to the Pacific Ocean. Erosion models, such as the Universal Soil Loss Equation (USLE), relate rainfall directly to soil erosion in that an increase in rainfall one month will directly result in a proportional increase in sediment generation. Understanding the rainfall regime of the region is therefore fundamental to modelling and predicting long-term radiocesium export. Here, we analyze rainfall data for ~40 stations within a 100 km radius of the FDNPP. First we present general information on the rainfall regime in the region based on monthly and annual rainfall totals. Second we present general information on rainfall erosivity, the R-factor of the USLE equation and its relationship to the general rainfall data. Third we examine rainfall trends over the last 100 years at several of the rainfall stations to understand temporal trends and whether ~20 years of data is sufficient to calculate the R-factor for USLE models. Fourth we present monthly R-factor maps for the Fukushima coastal catchments impacted by the FDNPP accident. The variability of the rainfall in the region, particularly during the typhoon season, is likely resulting in a similar variability in the transfer and migration of radiocesium throughout the coastal catchments of the Fukushima Prefecture. Characterizing the region's rainfall variability is fundamental to modelling sediment and the concomitant radiocesium migration and transfer throughout these catchments and ultimately to the Pacific Ocean.

Interpreting the g loadings of intelligence test composite scores in light of Spearman's law of diminishing returns.

PubMed

Reynolds, Matthew R

2013-03-01

The linear loadings of intelligence test composite scores on a general factor (g) have been investigated recently in factor analytic studies. Spearman's law of diminishing returns (SLODR), however, implies that the g loadings of test scores likely decrease in magnitude as g increases, or they are nonlinear. The purpose of this study was to (a) investigate whether the g loadings of composite scores from the Differential Ability Scales (2nd ed.) (DAS-II, C. D. Elliott, 2007a, Differential Ability Scales (2nd ed.). San Antonio, TX: Pearson) were nonlinear and (b) if they were nonlinear, to compare them with linear g loadings to demonstrate how SLODR alters the interpretation of these loadings. Linear and nonlinear confirmatory factor analysis (CFA) models were used to model Nonverbal Reasoning, Verbal Ability, Visual Spatial Ability, Working Memory, and Processing Speed composite scores in four age groups (5-6, 7-8, 9-13, and 14-17) from the DAS-II norming sample. The nonlinear CFA models provided better fit to the data than did the linear models. In support of SLODR, estimates obtained from the nonlinear CFAs indicated that g loadings decreased as g level increased. The nonlinear portion for the nonverbal reasoning loading, however, was not statistically significant across the age groups. Knowledge of general ability level informs composite score interpretation because g is less likely to produce differences, or is measured less, in those scores at higher g levels. One implication is that it may be more important to examine the pattern of specific abilities at higher general ability levels. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Moments of inertia of relativistic magnetized stars

NASA Astrophysics Data System (ADS)

Konno, K.

2001-06-01

We consider principal moments of inertia of axisymmetric, magnetically deformed stars in the context of general relativity. The general expression for the moment of inertia with respect to the symmetric axis is obtained. The numerical estimates are derived for several polytropic stellar models. We find that the values of the principal moments of inertia are modified by a factor of 2 at most from Newtonian estimates.

General Factor of Personality Questionnaire (GFPQ): only one factor to understand personality?

PubMed

Amigó, Salvador; Caselles, Antonio; Micó, Joan C

2010-05-01

This study proposes a psychometric approach to assess the General Factor of Personality (GFP) to explain the whole personality. This approach defends the existence of one basic factor that represents the overall personality. The General Factor of Personality Questionnaire (GFPQ) is presented to measure the basic, combined trait of the complete personality. The questionnaire includes 20 items and is constituted by two scales with 10 items each one: the Extraversion Scale (ES) and the Introversion Scale (IS). The GFPQ shows adequate internal consistency and construct validity, while the relationships with the personality factors of other models and with psychopathology are as expected. It correlates positively and significantly with Extraversion (E) and Psychoticism (P), and negatively with Neuroticism (N) of Eysenck's EPQ (Eysenck Personality Questionnaire); it correlates positively and significantly with the Sensation Seeking Scaled (SSS) of Zuckerman, and is inside the expected direction with Sensitivity to Reward (SR) and Sensitivity to Punishment (SP) of the Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ), which represent the approach and avoidance trends of behavior, respectively. It not only relates negatively with the personality disorders of the anxiety spectrum, but also with the emotional disorders in relation to anxiety and depression, and it relates positively with the antisocial personality disorder.

Sampling capacity underlies individual differences in human associative learning.

PubMed

Byrom, Nicola C; Murphy, Robin A

2014-04-01

Though much work has studied how external factors, such as stimulus properties, influence generalization of associative strength, there has been limited exploration of the influence that internal dispositions may contribute to stimulus processing. Here we report 2 studies using a modified negative patterning discrimination to test the relationship between global processing and generalization. Global processing was associated with stronger negative patterning discrimination, indicative of limited generalization between distinct stimulus compounds and their constituent elements. In Experiment 2, participants pretrained to adopt global processing similarly showed strong negative patterning discrimination. These results demonstrate considerable individual difference in capacity to engage in negative patterning discrimination and suggest that the tendency toward global processing may be one factor explaining this variability. The need for models of learning to account for this variability in learning is discussed.

The asset pricing model of musharakah factors

NASA Astrophysics Data System (ADS)

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

2015-02-01

The existing three-factor model developed by Fama and French for conventional investment was formulated based on risk-free rates element in which contradict with Shariah principles. We note that the underlying principles that govern Shariah investment were mutual risk and profit sharing between parties, the assurance of fairness for all and that transactions were based on an underlying asset. In addition, the three-factor model did not exclude stock that was not permissible by Shariah such as financial services based on riba (interest), gambling operator, manufacture or sale of non-halal products or related products and other activities deemed non-permissible according to Shariah. Our approach to construct the factor model for Shariah investment was based on the basic tenets of musharakah in tabulating the factors. We start by noting that Islamic stocks with similar characteristics should have similar returns and risks. This similarity between Islamic stocks was defined by the similarity of musharakah attributes such as business, management, profitability and capital. These attributes define factor exposures (or betas) to factors. The main takeaways were that musharakah attributes we chose had explain stock returns well in cross section and were significant in different market environments. The management factor seemed to be responsible for the general dynamics of the explanatory power.

Factor complexity of crash occurrence: An empirical demonstration using boosted regression trees.

PubMed

Chung, Yi-Shih

2013-12-01

Factor complexity is a characteristic of traffic crashes. This paper proposes a novel method, namely boosted regression trees (BRT), to investigate the complex and nonlinear relationships in high-variance traffic crash data. The Taiwanese 2004-2005 single-vehicle motorcycle crash data are used to demonstrate the utility of BRT. Traditional logistic regression and classification and regression tree (CART) models are also used to compare their estimation results and external validities. Both the in-sample cross-validation and out-of-sample validation results show that an increase in tree complexity provides improved, although declining, classification performance, indicating a limited factor complexity of single-vehicle motorcycle crashes. The effects of crucial variables including geographical, time, and sociodemographic factors explain some fatal crashes. Relatively unique fatal crashes are better approximated by interactive terms, especially combinations of behavioral factors. BRT models generally provide improved transferability than conventional logistic regression and CART models. This study also discusses the implications of the results for devising safety policies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Association of Coronary Artery Calcification with Estimated Coronary Heart Disease Risk from Prediction Models in a Community-Based Sample of Japanese Men: The Shiga Epidemiological Study of Subclinical Atherosclerosis (SESSA).

PubMed

Fujiyoshi, Akira; Arima, Hisatomi; Tanaka-Mizuno, Sachiko; Hisamatsu, Takahashi; Kadowaki, Sayaka; Kadota, Aya; Zaid, Maryam; Sekikawa, Akira; Yamamoto, Takashi; Horie, Minoru; Miura, Katsuyuki; Ueshima, Hirotsugu

2017-12-05

The clinical significance of coronary artery calcification (CAC) is not fully determined in general East Asian populations where background coronary heart disease (CHD) is less common than in USA/Western countries. We cross-sectionally assessed the association between CAC and estimated CHD risk as well as each major risk factor in general Japanese men. Participants were 996 randomly selected Japanese men aged 40-79 y, free of stroke, myocardial infarction, or revascularization. We examined an independent relationship between each risk factor used in prediction models and CAC score ≥100 by logistic regression. We then divided the participants into quintiles of estimated CHD risk per prediction model to calculate odds ratio of having CAC score ≥100. Receiver operating characteristic curve and c-index were used to examine discriminative ability of prevalent CAC for each prediction model. Age, smoking status, and systolic blood pressure were significantly associated with CAC score ≥100 in the multivariable analysis. The odds of having CAC score ≥100 were higher for those in higher quintiles in all prediction models (p-values for trend across quintiles ＜0.0001 for all models). All prediction models showed fair and similar discriminative abilities to detect CAC score ≥100, with similar c-statistics (around 0.70). In a community-based sample of Japanese men free of CHD and stroke, CAC score ≥100 was significantly associated with higher estimated CHD risk by prediction models. This finding supports the potential utility of CAC as a biomarker for CHD in a general Japanese male population.

Automating a human factors evaluation of graphical user interfaces for NASA applications: An update on CHIMES

NASA Technical Reports Server (NTRS)

Jiang, Jian-Ping; Murphy, Elizabeth D.; Bailin, Sidney C.; Truszkowski, Walter F.

1993-01-01

Capturing human factors knowledge about the design of graphical user interfaces (GUI's) and applying this knowledge on-line are the primary objectives of the Computer-Human Interaction Models (CHIMES) project. The current CHIMES prototype is designed to check a GUI's compliance with industry-standard guidelines, general human factors guidelines, and human factors recommendations on color usage. Following the evaluation, CHIMES presents human factors feedback and advice to the GUI designer. The paper describes the approach to modeling human factors guidelines, the system architecture, a new method developed to convert quantitative RGB primaries into qualitative color representations, and the potential for integrating CHIMES with user interface management systems (UIMS). Both the conceptual approach and its implementation are discussed. This paper updates the presentation on CHIMES at the first International Symposium on Ground Data Systems for Spacecraft Control.

The contribution of an animal model toward uncovering biological risk factors for PTSD.

PubMed

Cohen, Hagit; Matar, Michael A; Richter-Levin, Gal; Zohar, Joseph

2006-07-01

Clinical studies of posttraumatic stress disorder (PTSD) have elicited proposed risk factors for developing PTSD in the aftermath of stress exposure. Generally, these risk factors have arisen from retrospective analysis of premorbid characteristics of study populations. A valid animal model of PTSD can complement clinical studies and help to elucidate issues, such as the contribution of proposed risk factors, in ways which are not practicable in the clinical arena. Important qualities of animal models include the possibility to conduct controlled prospective studies, easy access to postmortem brains, and the availability of genetically manipulated subjects, which can be tailored to specific needs. When these qualities are further complemented by an approach which defines phenomenologic criteria to address the variance in individual response pattern and magnitude, enabling the animal subjects to be classified into definable groups for focused study, the model acquires added validity. This article presents an overview of a series of studies in such an animal model which examine the contribution of two proposed risk factors and the value of two early postexposure pharmacological manipulations on the prevalence rates of subjects displaying an extreme magnitude of behavioral response to a predator stress paradigm.

A response-time approach to comparing generalized rational and take-the-best models of decision making.

PubMed

Bergert, F Bryan; Nosofsky, Robert M

2007-01-01

The authors develop and test generalized versions of take-the-best (TTB) and rational (RAT) models of multiattribute paired-comparison inference. The generalized models make allowances for subjective attribute weighting, probabilistic orders of attribute inspection, and noisy decision making. A key new test involves a response-time (RT) approach. TTB predicts that RT is determined solely by the expected time required to locate the 1st discriminating attribute, whereas RAT predicts that RT is determined by the difference in summed evidence between the 2 alternatives. Critical test pairs are used that partially decouple these 2 factors. Under conditions in which ideal observer TTB and RAT strategies yield equivalent decisions, both the RT results and the estimated attribute weights suggest that the vast majority of subjects adopted the generalized TTB strategy. The RT approach is also validated in an experimental condition in which use of a RAT strategy is essentially forced upon subjects. (c) 2007 APA, all rights reserved.

Object detection in natural backgrounds predicted by discrimination performance and models

NASA Technical Reports Server (NTRS)

Rohaly, A. M.; Ahumada, A. J. Jr; Watson, A. B.

1997-01-01

Many models of visual performance predict image discriminability, the visibility of the difference between a pair of images. We compared the ability of three image discrimination models to predict the detectability of objects embedded in natural backgrounds. The three models were: a multiple channel Cortex transform model with within-channel masking; a single channel contrast sensitivity filter model; and a digital image difference metric. Each model used a Minkowski distance metric (generalized vector magnitude) to summate absolute differences between the background and object plus background images. For each model, this summation was implemented with three different exponents: 2, 4 and infinity. In addition, each combination of model and summation exponent was implemented with and without a simple contrast gain factor. The model outputs were compared to measures of object detectability obtained from 19 observers. Among the models without the contrast gain factor, the multiple channel model with a summation exponent of 4 performed best, predicting the pattern of observer d's with an RMS error of 2.3 dB. The contrast gain factor improved the predictions of all three models for all three exponents. With the factor, the best exponent was 4 for all three models, and their prediction errors were near 1 dB. These results demonstrate that image discrimination models can predict the relative detectability of objects in natural scenes.

Multi-factor energy price models and exotic derivatives pricing

NASA Astrophysics Data System (ADS)

Hikspoors, Samuel

The high pace at which many of the world's energy markets have gradually been opened to competition have generated a significant amount of new financial activity. Both academicians and practitioners alike recently started to develop the tools of energy derivatives pricing/hedging as a quantitative topic of its own. The energy contract structures as well as their underlying asset properties set the energy risk management industry apart from its more standard equity and fixed income counterparts. This thesis naturally contributes to these broad market developments in participating to the advances of the mathematical tools aiming at a better theory of energy contingent claim pricing/hedging. We propose many realistic two-factor and three-factor models for spot and forward price processes that generalize some well known and standard modeling assumptions. We develop the associated pricing methodologies and propose stable calibration algorithms that motivate the application of the relevant modeling schemes.

Self-consistent asset pricing models

NASA Astrophysics Data System (ADS)

Malevergne, Y.; Sornette, D.

2007-08-01

We discuss the foundations of factor or regression models in the light of the self-consistency condition that the market portfolio (and more generally the risk factors) is (are) constituted of the assets whose returns it is (they are) supposed to explain. As already reported in several articles, self-consistency implies correlations between the return disturbances. As a consequence, the alphas and betas of the factor model are unobservable. Self-consistency leads to renormalized betas with zero effective alphas, which are observable with standard OLS regressions. When the conditions derived from internal consistency are not met, the model is necessarily incomplete, which means that some sources of risk cannot be replicated (or hedged) by a portfolio of stocks traded on the market, even for infinite economies. Analytical derivations and numerical simulations show that, for arbitrary choices of the proxy which are different from the true market portfolio, a modified linear regression holds with a non-zero value αi at the origin between an asset i's return and the proxy's return. Self-consistency also introduces “orthogonality” and “normality” conditions linking the betas, alphas (as well as the residuals) and the weights of the proxy portfolio. Two diagnostics based on these orthogonality and normality conditions are implemented on a basket of 323 assets which have been components of the S&P500 in the period from January 1990 to February 2005. These two diagnostics show interesting departures from dynamical self-consistency starting about 2 years before the end of the Internet bubble. Assuming that the CAPM holds with the self-consistency condition, the OLS method automatically obeys the resulting orthogonality and normality conditions and therefore provides a simple way to self-consistently assess the parameters of the model by using proxy portfolios made only of the assets which are used in the CAPM regressions. Finally, the factor decomposition with the self-consistency condition derives a risk-factor decomposition in the multi-factor case which is identical to the principal component analysis (PCA), thus providing a direct link between model-driven and data-driven constructions of risk factors. This correspondence shows that PCA will therefore suffer from the same limitations as the CAPM and its multi-factor generalization, namely lack of out-of-sample explanatory power and predictability. In the multi-period context, the self-consistency conditions force the betas to be time-dependent with specific constraints.

Factorial Validity of the ADHD Adult Symptom Rating Scale in a French Community Sample: Results From the ChiP-ARD Study.

PubMed

Morin, Alexandre J S; Tran, Antoine; Caci, Hervé

2016-06-01

Recent publications reported that a bifactor model better represented the underlying structure of ADHD than classical models, at least in youth. The Adult ADHD Symptoms Rating Scale (ASRS) has been translated into many languages, but a single study compared its structure in adults across Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV) and International Classification of Diseases (ICD-10) classifications. We investigated the factor structure, reliability, and measurement invariance of the ASRS among a community sample of 1,171 adults. Results support a bifactor model, including one general ADHD factor and three specific Inattention, Hyperactivity, and Impulsivity factors corresponding to ICD-10, albeit the Impulsivity specific factor was weakly defined. Results also support the complete measurement invariance of this model across gender and age groups, and that men have higher scores than women on the ADHD G-factor but lower scores on all three S-factors. Results suggest that a total ASRS-ADHD score is meaningful, reliable, and valid in adults. (J. of Att. Dis. 2016; 20(6) 530-541). © The Author(s) 2013.

Factors Affecting Intention to Use in Social Networking Sites: An Empirical Study on Thai Society

NASA Astrophysics Data System (ADS)

Jairak, Rath; Sahakhunchai, Napath; Jairak, Kallaya; Praneetpolgrang, Prasong

This research aims to explore the factors that affect the intention to use in Social Networking Sites (SNS). We apply the theory of Technology Acceptance Model (TAM), intrinsic motivation, and trust properties to develop the theoretical framework for SNS users' intention. The results show that the important factors influencing SNS users' intention for general purpose and collaborative learning are task-oriented, pleasure-oriented, and familiarity-based trust. In marketing usage, dispositional trust and pleasure-oriented are two main factors that reflect intention to use in SNS.

Generalization of rapidly recurring seizures is suppressed in mice lacking glial cell line-derived neurotrophic factor family receptor alpha2.

PubMed

Nanobashvili, A; Kokaia, Z; Lindvall, O

2003-01-01

Recent experimental evidence indicates that neurotrophic factors play a role in the pathophysiology of epilepsy. The objective of this study was to explore whether signaling through one of the glial cell line-derived neurotrophic factor family receptors, GFRalpha2, influences the severity of kindling-evoked, rapidly recurring seizures and the subsequent development of permanent hyperexcitability. We applied the rapid kindling model to adult mice, using 40 threshold stimulations delivered with 5-min interval in the ventral hippocampus. Generalized seizures were fewer and developed later in response to kindling stimulations in mice lacking GFRalpha2. However, GFRalpha2 gene deletion did not influence the acquisition of the permanent abnormal excitability as assessed 4 weeks later. In situ hybridization revealed marked and dynamic changes of GFRalpha2 mRNA levels in several forebrain areas following the stimulus-evoked seizures. Our findings provide evidence that signaling through the GFRalpha2 receptor contributes to seizure generalization in rapid kindling.

Facial first impressions and partner preference models: Comparable or distinct underlying structures?

PubMed

South Palomares, Jennifer K; Sutherland, Clare A M; Young, Andrew W

2017-12-17

Given the frequency of relationships nowadays initiated online, where impressions from face photographs may influence relationship initiation, it is important to understand how facial first impressions might be used in such contexts. We therefore examined the applicability of a leading model of verbally expressed partner preferences to impressions derived from real face images and investigated how the factor structure of first impressions based on potential partner preference-related traits might relate to a more general model of facial first impressions. Participants rated 1,000 everyday face photographs on 12 traits selected to represent (Fletcher, et al. 1999, Journal of Personality and Social Psychology, 76, 72) verbal model of partner preferences. Facial trait judgements showed an underlying structure that largely paralleled the tripartite structure of Fletcher et al.'s verbal preference model, regardless of either face gender or participant gender. Furthermore, there was close correspondence between the verbal partner preference model and a more general tripartite model of facial first impressions derived from a different literature (Sutherland et al., 2013, Cognition, 127, 105), suggesting an underlying correspondence between verbal conceptual models of romantic preferences and more general models of facial first impressions. © 2017 The British Psychological Society.

A General Structure for Legal Arguments about Evidence Using Bayesian Networks

ERIC Educational Resources Information Center

Fenton, Norman; Neil, Martin; Lagnado, David A.

2013-01-01

A Bayesian network (BN) is a graphical model of uncertainty that is especially well suited to legal arguments. It enables us to visualize and model dependencies between different hypotheses and pieces of evidence and to calculate the revised probability beliefs about all uncertain factors when any piece of new evidence is presented. Although BNs…

A Model of Sexual Abuse's Effects on Suicidal Behavior and Delinquency: The Role of Emotions as Mediating Factors

ERIC Educational Resources Information Center

Sigfusdottir, Inga Dora; Asgeirsdottir, Bryndis Bjork; Gudjonsson, Gisli H.; Sigurdsson, Jon Fridrik

2008-01-01

Drawing on Agnew's general strain theory, we examined whether depressed mood and anger mediated the effects of sexual abuse on suicidal behavior and delinquency. Participants included 9,113 students attending high schools in Iceland. Structural equation modeling showed that, while controlling for family structure and parental education, being…

Comparative Validity of the Shedler and Westen Assessment Procedure-200

ERIC Educational Resources Information Center

Mullins-Sweatt, Stephanie N.; Widiger, Thomas A.

2008-01-01

A predominant dimensional model of general personality structure is the five-factor model (FFM). Quite a number of alternative instruments have been developed to assess the domains of the FFM. The current study compares the validity of 2 alternative versions of the Shedler and Westen Assessment Procedure (SWAP-200) FFM scales, 1 that was developed…

Supporting Smart School Teachers' Continuing Professional Development in and through ICT: A Model for Change

ERIC Educational Resources Information Center

Ming, Thang Siew; Hall, Carol; Azman, Hazita; Joyes, Gordon

2010-01-01

The general assumption that once the hardware is introduced in schools, ICT integration will automatically follow is not necessarily true. Teachers need to be supported and factors responsible for teachers' failure to integrate ICT into the classrooms identified and rectified. The paper proposes an online model based on the Improvement Quality…

Comment on "Information Processing in the Cerebral Hemispheres: Selective Activation and Capacity Limitations" by Hellige, Cox, and Litvac.

ERIC Educational Resources Information Center

Cohen, Gillian

1979-01-01

Kinsbourne's attentional model of hemisphere differences is reviewed, and some difficulties inherent in this model are described. Although others have succeeded in identifying some factors that govern effects of selective activation, effects of general activation are uncertain, so the overall outcome of concurrent memory loading is still difficult…

Adressing optimality principles in DGVMs: Dynamics of Carbon allocation changes

NASA Astrophysics Data System (ADS)

Pietsch, Stephan

2017-04-01

DGVMs are designed to reproduce and quantify ecosystem processes. Based on plant functions or species specific parameter sets, the energy, carbon, nitrogen and water cycles of different ecosystems are assessed. These models have been proven to be important tools to investigate ecosystem fluxes as they are derived by plant, site and environmental factors. The general model approach assumes steady state conditions and constant model parameters. Both assumptions, however, are wrong, since: (i) No given ecosystem ever is at steady state! (ii) Ecosystems have the capability to adapt to changes in growth conditions, e.g. via changes in allocation patterns! This presentation will give examples how these general failures within current DGVMs may be addressed.

Adressing optimality principles in DGVMs: Dynamics of Carbon allocation changes.

NASA Astrophysics Data System (ADS)

Pietsch, S.

2016-12-01

DGVMs are designed to reproduce and quantify ecosystem processes. Based on plant functions or species specific parameter sets, the energy, carbon, nitrogen and water cycles of different ecosystems are assessed. These models have been proven to be important tools to investigate ecosystem fluxes as they are derived by plant, site and environmental factors. The general model approach assumes steady state conditions and constant model parameters. Both assumptions, however, are wrong. Any given ecosystem never is at steady state! Ecosystems have the capability to adapt to changes in growth conditions, e.g. via changes in allocation patterns! This presentation will give examples how these general failures within current DGVMs may be addressed.

Quasi-likelihood generalized linear regression analysis of fatality risk data

DOT National Transportation Integrated Search

2009-01-01

Transportation-related fatality risks is a function of many interacting human, vehicle, and environmental factors. Statisitcally valid analysis of such data is challenged both by the complexity of plausable structural models relating fatality rates t...

Learning a generative model of images by factoring appearance and shape.

PubMed

Le Roux, Nicolas; Heess, Nicolas; Shotton, Jamie; Winn, John

2011-03-01

Computer vision has grown tremendously in the past two decades. Despite all efforts, existing attempts at matching parts of the human visual system's extraordinary ability to understand visual scenes lack either scope or power. By combining the advantages of general low-level generative models and powerful layer-based and hierarchical models, this work aims at being a first step toward richer, more flexible models of images. After comparing various types of restricted Boltzmann machines (RBMs) able to model continuous-valued data, we introduce our basic model, the masked RBM, which explicitly models occlusion boundaries in image patches by factoring the appearance of any patch region from its shape. We then propose a generative model of larger images using a field of such RBMs. Finally, we discuss how masked RBMs could be stacked to form a deep model able to generate more complicated structures and suitable for various tasks such as segmentation or object recognition.

A surrogate model for thermal characteristics of stratospheric airship

NASA Astrophysics Data System (ADS)

Zhao, Da; Liu, Dongxu; Zhu, Ming

2018-06-01

A simple and accurate surrogate model is extremely needed to reduce the analysis complexity of thermal characteristics for a stratospheric airship. In this paper, a surrogate model based on the Least Squares Support Vector Regression (LSSVR) is proposed. The Gravitational Search Algorithm (GSA) is used to optimize hyper parameters. A novel framework consisting of a preprocessing classifier and two regression models is designed to train the surrogate model. Various temperature datasets of the airship envelope and the internal gas are obtained by a three-dimensional transient model for thermal characteristics. Using these thermal datasets, two-factor and multi-factor surrogate models are trained and several comparison simulations are conducted. Results illustrate that the surrogate models based on LSSVR-GSA have good fitting and generalization abilities. The pre-treated classification strategy proposed in this paper plays a significant role in improving the accuracy of the surrogate model.

Generalized Structured Component Analysis with Uniqueness Terms for Accommodating Measurement Error

PubMed Central

Hwang, Heungsun; Takane, Yoshio; Jung, Kwanghee

2017-01-01

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling (SEM), where latent variables are approximated by weighted composites of indicators. It has no formal mechanism to incorporate errors in indicators, which in turn renders components prone to the errors as well. We propose to extend GSCA to account for errors in indicators explicitly. This extension, called GSCAM, considers both common and unique parts of indicators, as postulated in common factor analysis, and estimates a weighted composite of indicators with their unique parts removed. Adding such unique parts or uniqueness terms serves to account for measurement errors in indicators in a manner similar to common factor analysis. Simulation studies are conducted to compare parameter recovery of GSCAM and existing methods. These methods are also applied to fit a substantively well-established model to real data. PMID:29270146

Multiple dimensions of attitudes about homosexuality: development of a multifaceted scale measuring attitudes toward homosexuality.

PubMed

Adolfsen, Anna; Iedema, Jurjen; Keuzenkamp, Saskia

2010-01-01

Attitudes toward homosexuality are complex. To get a comprehensive view on the attitudes of people, different dimensions need to be included in research. Based on a review of the literature, we distinguish five dimensions: acceptance of homosexuality in a general sense; attitude toward equal rights; reactions to homosexuality "at close quarters"; reactions to homosexuality in public; and so-called modern homonegativity. In a study on a representative sample of Dutch Defence personnel (N = 1,607) we tested this model. Structural equation modeling of several items measuring the attitude toward homosexuality offers a six factor solution. These six factors are more or less comparable to the five dimensions we distinguished. The dimension "reactions to homosexuality at close quarters" is, however, empirically split in a dimension on affective reactions to homosexuality and homosexual persons in general and a dimension on affective reaction to homosexual friends or acquaintances.

[Quality-of-life-related factors in adolescents].

PubMed

Lima-Serrano, Marta; Martínez-Montilla, José Manuel; Guerra-Martín, María Dolores; Vargas-Martínez, Ana Magdalena; Lima-Rodríguez, Joaquín S

To determine quality of life (QoL) and its relationship to lifestyles in adolescents in high schools. Cross-sectional, observational study with 256 students aged 12 to 17 in Seville (Spain). Multiple linear regression models were tested (p <0.05). The boys had higher scores in most of the QoL areas. The female gender was inversely related to physical, psychological, familial QoL areas and the general QoL index. Family functionality and performing physical activity were the factors most associated with better QoL in all areas. All multivariate models were statistically significant and explained from 11% of social QoL variability to 35% of the general QoL index. The findings could be useful for developing interventions to promote health in schools, with the objective of promoting healthy lifestyles and QoL. Copyright © 2016 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

A general mixture theory. I. Mixtures of spherical molecules

NASA Astrophysics Data System (ADS)

Hamad, Esam Z.

1996-08-01

We present a new general theory for obtaining mixture properties from the pure species equations of state. The theory addresses the composition and the unlike interactions dependence of mixture equation of state. The density expansion of the mixture equation gives the exact composition dependence of all virial coefficients. The theory introduces multiple-index parameters that can be calculated from binary unlike interaction parameters. In this first part of the work, details are presented for the first and second levels of approximations for spherical molecules. The second order model is simple and very accurate. It predicts the compressibility factor of additive hard spheres within simulation uncertainty (equimolar with size ratio of three). For nonadditive hard spheres, comparison with compressibility factor simulation data over a wide range of density, composition, and nonadditivity parameter, gave an average error of 2%. For mixtures of Lennard-Jones molecules, the model predictions are better than the Weeks-Chandler-Anderson perturbation theory.

From cognition to the system: developing a multilevel taxonomy of patient safety in general practice.

PubMed

Kostopoulou, O

The paper describes the process of developing a taxonomy of patient safety in general practice. The methodologies employed included fieldwork, task analysis and confidential reporting of patient-safety events in five West Midlands practices. Reported events were traced back to their root causes and contributing factors. The resulting taxonomy is based on a theoretical model of human cognition, includes multiple levels of classification to reflect the chain of causation and considers affective and physiological influences on performance. Events are classified at three levels. At level one, the information-processing model of cognition is used to classify errors. At level two, immediate causes are identified, internal and external to the individual. At level three, more remote causal factors are classified as either 'work organization' or 'technical' with subcategories. The properties of the taxonomy (validity, reliability, comprehensiveness) as well as its usability and acceptability remain to be tested with potential users.

Have a little faith: measuring the impact of illness on positive and negative aspects of faith.

PubMed

Salsman, John M; Garcia, Sofia F; Lai, Jin-Shei; Cella, David

2012-12-01

The importance of faith and its associations with health are well documented. As part of the Patient Reported Outcomes Measurement Information System, items tapping positive and negative impact of illness (PII and NII) were developed across four content domains: Coping/Stress Response, Self-Concept, Social Connection/Isolation, and Meaning and Spirituality. Faith items were included within the concept of meaning and spirituality. This measurement model was tested on a heterogeneous group of 509 cancer survivors. To evaluate dimensionality, we applied two bi-factor models, specifying a general factor (PII or NII) and four local factors: Coping/Stress Response, Self-Concept, Social Connection/Isolation, and Meaning and Spirituality. Bi-factor analysis supported sufficient unidimensionality within PII and NII item sets. The unidimensionality of both PII and NII item sets was enhanced by extraction of the faith items from the rest of the questions. Of the 10 faith items, nine demonstrated higher local than general factor loadings (range for local factor loadings = 0.402 to 0.876), suggesting utility as a separate but related 'faith' factor. The same was true for only two of the remaining 63 items across the PII and NII item sets. Although conceptually and to a degree empirically related to Meaning and Spirituality, Faith appears to be a distinct subdomain of PII and NII, better handled by distinct assessment. A 10-item measure of the impact of illness upon faith (II-Faith) was therefore assembled. Copyright © 2011 John Wiley & Sons, Ltd.

Crossing the barrier between the laboratory working model and the practicable production model

NASA Astrophysics Data System (ADS)

Curby, William A.

1992-12-01

Transforming apparatus that has developed into a successfully working laboratory system into a system that is ready, or nearly ready for production, distribution and general use is not always accomplished in a cost effective or timely fashion. Several design elements must be considered interactively during the planning, construction, use and servicing of the final production form of the system. The basic design elements are: Operating Specifications, Reliability Factors, Safety Factors, Precision Limits, Accuracy Limits, Uniformity Factors, Cost Limits and Calibration Requirements. Secondary elements including: Human Engineering, Documentation, Training, Maintenance, Proprietary Rights, Protection, Marketing, Replacement of Parts, and Packing and Shipping must also be considered during the transition.

Construct validity of the Wechsler Intelligence Scale for Children - Fourth UK Edition with a referred Irish sample: Wechsler and Cattell-Horn-Carroll model comparisons with 15 subtests.

PubMed

Canivez, Gary L; Watkins, Marley W; Good, Rebecca; James, Kate; James, Trevor

2017-09-01

Irish educational psychologists frequently use the Wechsler Intelligence Scale for Children - Fourth UK Edition (WISC-IV UK ; Wechsler, 2004, Wechsler Intelligence Scale for Children-Fourth UK Edition, London, UK, Harcourt Assessment) in clinical assessments of children with learning difficulties. Unfortunately, reliability and validity studies of the WISC-IV UK standardization sample have not yet been reported. Watkins et al. (2013, International Journal of School and Educational Psychology, 1, 102) found support for a bifactor structure with a large sample (N = 794) of Irish children who were administered the 10 WISC-IV UK core subtests in clinical assessments of learning difficulties and dominance of general intelligence. Because only 10 subtests were available, Cattell-Horn-Carroll (CHC; McGrew, 1997, 2005, Contemporary intellectual assessment: Theories, tests, and issues, New York, NY: Guilford; Schneider & McGrew, 2012, Contemporary intellectual assessment: Theories, tests, and issues, New York, NY, Guilford Press) models could not be tested and compared. The present study utilized confirmatory factor analyses to test the latent factor structure of the WISC-IV UK with a sample of 245 Irish children administered all 15 WISC-IV UK subtests in evaluations assessing learning difficulties in order to examine CHC- and Wechsler-based models. One through five, oblique first-order factor models and higher order versus bifactor models were examined and compared using CFA. Meaningful differences in fit statistics were not observed between the Wechsler and CHC representations of higher-order or bifactor models. In all four structures, general intelligence accounted for the largest portions of explained common variance, whereas group factors accounted for small to miniscule portions of explained common variance. Omega-hierarchical subscale coefficients indicated that unit-weighted composites that would be generated by WISC-IV UK group factors (Wechsler or CHC) would contain little unique variance and thus be of little value. These results were similar to those from other investigations, further demonstrating the replication of the WISC-IV factor structure across cultures and the importance of focusing primary interpretation on the FSIQ. © 2017 The British Psychological Society.

Mining geographic variations of Plasmodium vivax for active surveillance: a case study in China.

PubMed

Shi, Benyun; Tan, Qi; Zhou, Xiao-Nong; Liu, Jiming

2015-05-27

Geographic variations of an infectious disease characterize the spatial differentiation of disease incidences caused by various impact factors, such as environmental, demographic, and socioeconomic factors. Some factors may directly determine the force of infection of the disease (namely, explicit factors), while many other factors may indirectly affect the number of disease incidences via certain unmeasurable processes (namely, implicit factors). In this study, the impact of heterogeneous factors on geographic variations of Plasmodium vivax incidences is systematically investigate in Tengchong, Yunnan province, China. A space-time model that resembles a P. vivax transmission model and a hidden time-dependent process, is presented by taking into consideration both explicit and implicit factors. Specifically, the transmission model is built upon relevant demographic, environmental, and biophysical factors to describe the local infections of P. vivax. While the hidden time-dependent process is assessed by several socioeconomic factors to account for the imported cases of P. vivax. To quantitatively assess the impact of heterogeneous factors on geographic variations of P. vivax infections, a Markov chain Monte Carlo (MCMC) simulation method is developed to estimate the model parameters by fitting the space-time model to the reported spatial-temporal disease incidences. Since there is no ground-truth information available, the performance of the MCMC method is first evaluated against a synthetic dataset. The results show that the model parameters can be well estimated using the proposed MCMC method. Then, the proposed model is applied to investigate the geographic variations of P. vivax incidences among all 18 towns in Tengchong, Yunnan province, China. Based on the geographic variations, the 18 towns can be further classify into five groups with similar socioeconomic causality for P. vivax incidences. Although this study focuses mainly on the transmission of P. vivax, the proposed space-time model is general and can readily be extended to investigate geographic variations of other diseases. Practically, such a computational model will offer new insights into active surveillance and strategic planning for disease surveillance and control.

Tachyon with an inverse power-law potential in a braneworld cosmology

NASA Astrophysics Data System (ADS)

Bilić, Neven; Domazet, Silvije; Djordjevic, Goran S.

2017-08-01

We study a tachyon cosmological model based on the dynamics of a 3-brane in the bulk of the second Randall-Sundrum model extended to more general warp functions. A well known prototype of such a generalization is the bulk with a selfinteracting scalar field. As a consequence of a generalized bulk geometry the cosmology on the observer brane is modified by the scale dependent four-dimensional gravitational constant. In particular, we study a power law warp factor which generates an inverse power-law potential V\\propto \\varphi-n of the tachyon field φ. We find a critical power n cr that divides two subclasses with distinct asymptotic behaviors: a dust universe for n>n_cr and a quasi de Sitter universe for 0.

Exploration of the factor structure of the Kirton Adaption-Innovation Inventory using bootstrapping estimation.

PubMed

Im, Subin; Min, Soonhong

2013-04-01

Exploratory factor analyses of the Kirton Adaption-Innovation Inventory (KAI), which serves to measure individual cognitive styles, generally indicate three factors: sufficiency of originality, efficiency, and rule/group conformity. In contrast, a 2005 study by Im and Hu using confirmatory factor analysis supported a four-factor structure, dividing the sufficiency of originality dimension into two subdimensions, idea generation and preference for change. This study extends Im and Hu's (2005) study of a derived version of the KAI by providing additional evidence of the four-factor structure. Specifically, the authors test the robustness of the parameter estimates to the violation of normality assumptions in the sample using bootstrap methods. A bias-corrected confidence interval bootstrapping procedure conducted among a sample of 356 participants--members of the Arkansas Household Research Panel, with middle SES and average age of 55.6 yr. (SD = 13.9)--showed that the four-factor model with two subdimensions of sufficiency of originality fits the data significantly better than the three-factor model in non-normality conditions.

User's guide to the douglas-fir beetle impact model. Forest Service general technical report

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

Marsden, M.A.; Eav, B.B.; Thompson, M.K.

1994-09-01

Douglas-fir beetle occurs throughout the range of its principal host, Douglas-fir. At epidemic levels, the beetle causes considerable mortality in large-diameter Douglas-fir trees. Wind storms, drought, fire, and other factors have been reported as precendent conditions for epidemics of Douglas-fir beetle. An impact model has been developed to simulate tree mortality during such epidemics. The model has been linked to the Stand Prognosis Model (Forest Vegetation Simulator). This is a guide for using the model.

A biopsychosocial model of violence when sleepwalking: review and reconceptualisation

PubMed Central

Bari, Andrea

2017-01-01

Summary Violence towards others during sleepwalking is relatively uncommon, but can result in serious injury or even death. Much of the research in this field has focused on the forensic consequences of violence during sleepwalking without sufficient attention to an understanding of the risk factors for violence during sleepwalking and the development of prevention and interventions based on these risk factors. This paper reviews the characteristics of impulsive violence in general and reconceptualises violence during sleepwalking as an extension of this prior vulnerability. We propose a biopsychosocial model of the risk for violence during sleepwalking that is supported through a review of empirical literature both within sleepwalking and violent behaviour more generally. Biological, psychological and social risk factors are hypothesised to mediate the relationship between sleepwalking and violence. Implications for prevention and treatment of this potentially fatal problem are discussed. Declaration of interest None. Copyright and usage © The Royal College of Psychiatrists 2017. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license. PMID:28446961

Factor Models for Ordinal Variables With Covariate Effects on the Manifest and Latent Variables: A Comparison of LISREL and IRT Approaches

ERIC Educational Resources Information Center

Moustaki, Irini; Joreskog, Karl G.; Mavridis, Dimitris

2004-01-01

We consider a general type of model for analyzing ordinal variables with covariate effects and 2 approaches for analyzing data for such models, the item response theory (IRT) approach and the PRELIS-LISREL (PLA) approach. We compare these 2 approaches on the basis of 2 examples, 1 involving only covariate effects directly on the ordinal variables…

Review of critical factors for SEA implementation

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

Zhang Jie, E-mail: jasmine@plan.aau.dk; Christensen, Per; Kornov, Lone

The implementation process involved in translating Strategic Environmental Assessment (SEA) intention into action is vital to an effective SEA. Many factors influence implementation and thus the effectiveness of an SEA. Empirical studies have identified and documented some factors influencing the implementation of an SEA. This research is fragmented, however, and it is still not clear what are the most critical factors of effective SEA performance, and how these relate to different stages of the implementation process or other contextual circumstances. The paper takes its point of departure in implementation theory. Firstly, we introduce implementation theory, and then use it inmore » practice to establish a more comprehensive model related to the stages in the implementation process. Secondly, we identify the critical factors in order to see how they are related to the different stages of SEA or are more general in character. Finally we map the different critical factors and how they influence the overall results of an SEA. Based on a literature review, we present a comprehensive picture of the critical factors and where they are found in the process. We conclude that most of the critical factors identified are of a more general character influencing the SEA process as such, while only one out of four of these factors relates to the specific stages of the SEA. Based on this mapping we can sketch a picture of the totality of critical factors. In this study 266 notions of critical factors were identified. Seen at the level of notions of critical factors, only 24% of these relate to specific stages while for 76% the critical factors are of a more general nature. These critical factors interact in complex ways and appear in different combinations in different stages of the implementation process so tracing the cause and effect is difficult. The pervasiveness of contextual and general factors also clearly suggests that there is no single way to put SEA into practice. The paper identifies some of the critical factors for effective SEA implementation, but further research is still needed to conclude which factors are more critical than others, just as the contingencies on which they depend are not easy to unravel. - Highlights: Black-Right-Pointing-Pointer The research on critical factors influencing SEA implementation is fragmented. Black-Right-Pointing-Pointer The critical factors are used to discuss 'hot-spots' in the implementation process. Black-Right-Pointing-Pointer Critical factors are just as broad as the concept of effectiveness. Black-Right-Pointing-Pointer Both stage and general factors are relevant in explaining the effectiveness of SEA.« less

Effect of Multiple Scattering on the Compton Recoil Current Generated in an EMP, Revisited

DOE PAGES

Farmer, William A.; Friedman, Alex

2015-06-18

Multiple scattering has historically been treated in EMP modeling through the obliquity factor. The validity of this approach is examined here. A simplified model problem, which correctly captures cyclotron motion, Doppler shifting due to the electron motion, and multiple scattering is first considered. The simplified problem is solved three ways: the obliquity factor, Monte-Carlo, and Fokker-Planck finite-difference. Because of the Doppler effect, skewness occurs in the distribution. It is demonstrated that the obliquity factor does not correctly capture this skewness, but the Monte-Carlo and Fokker-Planck finite-difference approaches do. Here, the obliquity factor and Fokker-Planck finite-difference approaches are then compared inmore » a fuller treatment, which includes the initial Klein-Nishina distribution of the electrons, and the momentum dependence of both drag and scattering. It is found that, in general, the obliquity factor is adequate for most situations. However, as the gamma energy increases and the Klein-Nishina becomes more peaked in the forward direction, skewness in the distribution causes greater disagreement between the obliquity factor and a more accurate model of multiple scattering.« less

Perioperative risk factors for mortality and length of hospitalization in mares with dystocia undergoing general anesthesia: A retrospective study

PubMed Central

Rioja, Eva; Cernicchiaro, Natalia; Costa, Maria Carolina; Valverde, Alexander

2012-01-01

This study investigated associations between perioperative factors and probability of death and length of hospitalization of mares with dystocia that survived following general anesthesia. Demographics and perioperative characteristics from 65 mares were reviewed retrospectively and used in a risk factor analysis. Mortality rate was 21.5% during the first 24 h post-anesthesia. The mean ± standard deviation number of days of hospitalization of surviving mares was 6.3 ± 5.4 d. Several factors were found in the univariable analysis to be significantly associated (P < 0.1) with increased probability of perianesthetic death, including: low preoperative total protein, high temperature and severe dehydration on presentation, prolonged dystocia, intraoperative hypotension, and drugs used during recovery. Type of delivery and day of the week the surgery was performed were significantly associated with length of hospitalization in the multivariable mixed effects model. The study identified some risk factors that may allow clinicians to better estimate the probability of mortality and morbidity in these mares. PMID:23115362

A General Econometric Model of the Determinants of Library Subscription Prices of Scholarly Journals: The Role of Exchange Rate Risk and Other Factors.

ERIC Educational Resources Information Center

Chressanthis, George A.; Chressanthis, June D.

1994-01-01

Provides regression-based empirical evidence of the effects of variations in exchange rate risk on 1985 library prices of the top-ranked 99 journals in economics. The relationship between individual journal prices and library prices is shown, and other factors associated with increases and decreases in library journal prices are given. (Contains…

Return on Investment Analysis for the Almond Board of California

DTIC Science & Technology

2004-06-01

general approach for the analysis is first to identify relevant factors concerning consumer behavior using exploratory factor analysis (EFA) and...That completed the intermediate stage of the conceptual model below, referring to the latent drivers of consumer behavior that affect the almond... consumer behavior remains a challenge that will have to be continuously addressed by the ABC management. Finally, to improve the methodology for

Object recognition in images via a factor graph model

NASA Astrophysics Data System (ADS)

He, Yong; Wang, Long; Wu, Zhaolin; Zhang, Haisu

2018-04-01

Object recognition in images suffered from huge search space and uncertain object profile. Recently, the Bag-of- Words methods are utilized to solve these problems, especially the 2-dimension CRF(Conditional Random Field) model. In this paper we suggest the method based on a general and flexible fact graph model, which can catch the long-range correlation in Bag-of-Words by constructing a network learning framework contrasted from lattice in CRF. Furthermore, we explore a parameter learning algorithm based on the gradient descent and Loopy Sum-Product algorithms for the factor graph model. Experimental results on Graz 02 dataset show that, the recognition performance of our method in precision and recall is better than a state-of-art method and the original CRF model, demonstrating the effectiveness of the proposed method.

Metal accumulation in the earthworm Lumbricus rubellus. Model predictions compared to field data

USGS Publications Warehouse

Veltman, K.; Huijbregts, M.A.J.; Vijver, M.G.; Peijnenburg, W.J.G.M.; Hobbelen, P.H.F.; Koolhaas, J.E.; van Gestel, C.A.M.; van Vliet, P.C.J.; Jan, Hendriks A.

2007-01-01

The mechanistic bioaccumulation model OMEGA (Optimal Modeling for Ecotoxicological Applications) is used to estimate accumulation of zinc (Zn), copper (Cu), cadmium (Cd) and lead (Pb) in the earthworm Lumbricus rubellus. Our validation to field accumulation data shows that the model accurately predicts internal cadmium concentrations. In addition, our results show that internal metal concentrations in the earthworm are less than linearly (slope < 1) related to the total concentration in soil, while risk assessment procedures often assume the biota-soil accumulation factor (BSAF) to be constant. Although predicted internal concentrations of all metals are generally within a factor 5 compared to field data, incorporation of regulation in the model is necessary to improve predictability of the essential metals such as zinc and copper. ?? 2006 Elsevier Ltd. All rights reserved.

A model of traffic signs recognition with convolutional neural network

NASA Astrophysics Data System (ADS)

Hu, Haihe; Li, Yujian; Zhang, Ting; Huo, Yi; Kuang, Wenqing

2016-10-01

In real traffic scenes, the quality of captured images are generally low due to some factors such as lighting conditions, and occlusion on. All of these factors are challengeable for automated recognition algorithms of traffic signs. Deep learning has provided a new way to solve this kind of problems recently. The deep network can automatically learn features from a large number of data samples and obtain an excellent recognition performance. We therefore approach this task of recognition of traffic signs as a general vision problem, with few assumptions related to road signs. We propose a model of Convolutional Neural Network (CNN) and apply the model to the task of traffic signs recognition. The proposed model adopts deep CNN as the supervised learning model, directly takes the collected traffic signs image as the input, alternates the convolutional layer and subsampling layer, and automatically extracts the features for the recognition of the traffic signs images. The proposed model includes an input layer, three convolutional layers, three subsampling layers, a fully-connected layer, and an output layer. To validate the proposed model, the experiments are implemented using the public dataset of China competition of fuzzy image processing. Experimental results show that the proposed model produces a recognition accuracy of 99.01 % on the training dataset, and yield a record of 92% on the preliminary contest within the fourth best.

What Do We Mean By Sensitivity Analysis? The Need For A Comprehensive Characterization Of Sensitivity In Earth System Models

NASA Astrophysics Data System (ADS)

Razavi, S.; Gupta, H. V.

2014-12-01

Sensitivity analysis (SA) is an important paradigm in the context of Earth System model development and application, and provides a powerful tool that serves several essential functions in modelling practice, including 1) Uncertainty Apportionment - attribution of total uncertainty to different uncertainty sources, 2) Assessment of Similarity - diagnostic testing and evaluation of similarities between the functioning of the model and the real system, 3) Factor and Model Reduction - identification of non-influential factors and/or insensitive components of model structure, and 4) Factor Interdependence - investigation of the nature and strength of interactions between the factors, and the degree to which factors intensify, cancel, or compensate for the effects of each other. A variety of sensitivity analysis approaches have been proposed, each of which formally characterizes a different "intuitive" understanding of what is meant by the "sensitivity" of one or more model responses to its dependent factors (such as model parameters or forcings). These approaches are based on different philosophies and theoretical definitions of sensitivity, and range from simple local derivatives and one-factor-at-a-time procedures to rigorous variance-based (Sobol-type) approaches. In general, each approach focuses on, and identifies, different features and properties of the model response and may therefore lead to different (even conflicting) conclusions about the underlying sensitivity. This presentation revisits the theoretical basis for sensitivity analysis, and critically evaluates existing approaches so as to demonstrate their flaws and shortcomings. With this background, we discuss several important properties of response surfaces that are associated with the understanding and interpretation of sensitivity. Finally, a new approach towards global sensitivity assessment is developed that is consistent with important properties of Earth System model response surfaces.

Human Factors Research for Space Exploration: Measurement, Modeling, and Mitigation

NASA Technical Reports Server (NTRS)

Kaiser, Mary K.; Allen, Christopher S.; Barshi, Immanuel; Billman, Dorrit; Holden, Kritina L.

2010-01-01

As part of NASA's Human Research Program, the Space Human Factors Engineering Project serves as the bridge between Human Factors research and Human Spaceflight applications. Our goal is to be responsive to the operational community while addressing issues at a sufficient level of abstraction to ensure that our tools and solutions generalize beyond the point design. In this panel, representatives from four of our research domains will discuss the challenges they face in solving current problems while also enabling future capabilities.

Computable General Equilibrium Model Fiscal Year 2013 Capability Development Report - April 2014

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

Edwards, Brian Keith; Rivera, Michael K.; Boero, Riccardo

2014-04-01

This report documents progress made on continued developments of the National Infrastructure Simulation and Analysis Center (NISAC) Computable General Equilibrium Model (NCGEM), developed in fiscal year 2012. In fiscal year 2013, NISAC the treatment of the labor market and tests performed with the model to examine the properties of the solutions computed by the model. To examine these, developers conducted a series of 20 simulations for 20 U.S. States. Each of these simulations compared an economic baseline simulation with an alternative simulation that assumed a 20-percent reduction in overall factor productivity in the manufacturing industries of each State. Differences inmore » the simulation results between the baseline and alternative simulations capture the economic impact of the reduction in factor productivity. While not every State is affected in precisely the same way, the reduction in manufacturing industry productivity negatively affects the manufacturing industries in each State to an extent proportional to the reduction in overall factor productivity. Moreover, overall economic activity decreases when manufacturing sector productivity is reduced. Developers ran two additional simulations: (1) a version of the model for the State of Michigan, with manufacturing divided into two sub-industries (automobile and other vehicle manufacturing as one sub-industry and the rest of manufacturing as the other subindustry); and (2) a version of the model for the United States, divided into 30 industries. NISAC conducted these simulations to illustrate the flexibility of industry definitions in NCGEM and to examine the simulation properties of in more detail.« less

Dimensions of the South Oaks Gambling Screen in Finland: A cross-sectional population study.

PubMed

Salonen, Anne H; Rosenström, Tom; Edgren, Robert; Volberg, Rachel; Alho, Hannu; Castrén, Sari

2017-06-01

The underlying structure of problematic gambling behaviors, such as those assessed by the South Oaks Gambling Screen (SOGS), remain unknown: Can problem gambling be assessed unidimensionally or should multiple qualitatively different dimensions be taken into account, and if so, what do these qualitative dimensions indicate? How significant are the deviations from unidimensionality in practice? A cross-sectional random sample of Finns aged 15-74 (n = 4,484) was drawn from the Population Information Registry and surveyed in 2011-2012. Analyses were conducted using descriptive statistics, Confirmatory factor analysis (CFA) and multidimensional item response theory (MIRT) models. Altogether, 14.9% of the population endorsed at least one of the 20 SOGS items, but nine items had low endorsement rates (≤ 0.2%). CFA and MIRT techniques suggested that individuals differed from each other in two positively correlated (r = 0.70) underlying dimensions: "impact on self primarily" and "impact on others also". This two-factor correlated-factors model can be reinterpreted as a bifactor model with one general gambling-problem factor and two specific factors with similar interpretation as in the correlated-factors model but with non-overlapping items. The two specific factors may provide clinically useful information without extra costs of assessment. © 2017 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

Challenges of developing a cardiovascular risk calculator for patients with rheumatoid arthritis.

PubMed

Crowson, Cynthia S; Rollefstad, Silvia; Kitas, George D; van Riel, Piet L C M; Gabriel, Sherine E; Semb, Anne Grete

2017-01-01

Cardiovascular disease (CVD) risk calculators designed for use in the general population do not accurately predict the risk of CVD among patients with rheumatoid arthritis (RA), who are at increased risk of CVD. The process of developing risk prediction models involves numerous issues. Our goal was to develop a CVD risk calculator for patients with RA. Thirteen cohorts of patients with RA originating from 10 different countries (UK, Norway, Netherlands, USA, Sweden, Greece, South Africa, Spain, Canada and Mexico) were combined. CVD risk factors and RA characteristics at baseline, in addition to information on CVD outcomes were collected. Cox models were used to develop a CVD risk calculator, considering traditional CVD risk factors and RA characteristics. Model performance was assessed using measures of discrimination and calibration with 10-fold cross-validation. A total of 5638 RA patients without prior CVD were included (mean age: 55 [SD: 14] years, 76% female). During a mean follow-up of 5.8 years (30139 person years), 389 patients developed a CVD event. Event rates varied between cohorts, necessitating inclusion of high and low risk strata in the models. The multivariable analyses revealed 2 risk prediction models including either a disease activity score including a 28 joint count and erythrocyte sedimentation rate (DAS28ESR) or a health assessment questionnaire (HAQ) along with age, sex, presence of hypertension, current smoking and ratio of total cholesterol to high-density lipoprotein cholesterol. Unfortunately, performance of these models was similar to general population CVD risk calculators. Efforts to develop a specific CVD risk calculator for patients with RA yielded 2 potential models including RA disease characteristics, but neither demonstrated improved performance compared to risk calculators designed for use in the general population. Challenges encountered and lessons learned are discussed in detail.

GamTest: Psychometric Evaluation and the Role of Emotions in an Online Self-Test for Gambling Behavior.

PubMed

Jonsson, Jakob; Munck, Ingrid; Volberg, Rachel; Carlbring, Per

2017-06-01

Recent increases in the number of online gambling sites have made gambling more available, which may contribute to an increase in gambling problems. At the same time, online gambling provides opportunities to introduce measures intended to prevent problem gambling. GamTest is an online test of gambling behavior that provides information that can be used to give players individualized feedback and recommendations for action. The aim of this study is to explore the dimensionality of GamTest and validate it against the Problem Gambling Severity Index (PGSI) and the gambler's own perceived problems. A recent psychometric approach, exploratory structural equation modeling (ESEM) is used. Well-defined constructs are identified in a two-step procedure fitting a traditional exploratory factor analysis model as well as a so-called bifactor model. Using data collected at four Nordic gambling sites in the autumn of 2009 (n = 10,402), the GamTest ESEM analyses indicate high correspondence with the players' own understanding of their problems and with the PGSI, a validated measure of problem gambling. We conclude that GamTest captures five dimensions of problematic gambling (i.e., overconsumption of money and time, and monetary, social and emotional negative consequences) with high reliability, and that the bifactor approach, composed of a general factor and specific residual factors, reproduces all these factors except one, the negative consequences emotional factor, which contributes to the dominant part of the general factor. The results underscore the importance of tailoring feedback and support to online gamblers with a particular focus on how to handle emotions in relation to their gambling behavior.

Lifetime risks for aneurysmal subarachnoid haemorrhage: multivariable risk stratification.

PubMed

Vlak, Monique H M; Rinkel, Gabriel J E; Greebe, Paut; Greving, Jacoba P; Algra, Ale

2013-06-01

The overall incidence of aneurysmal subarachnoid haemorrhage (aSAH) in western populations is around 9 per 100 000 person-years, which confers to a lifetime risk of around half per cent. Risk factors for aSAH are usually expressed as relative risks and suggest that absolute risks vary considerably according to risk factor profiles, but such estimates are lacking. We aimed to estimate incidence and lifetime risks of aSAH according to risk factor profiles. We used data from 250 patients admitted with aSAH and 574 sex-matched and age-matched controls, who were randomly retrieved from general practitioners files. We determined independent prognostic factors with multivariable logistic regression analyses and assessed discriminatory performance using the area under the receiver operating characteristic curve. Based on the prognostic model we predicted incidences and lifetime risks of aSAH for different risk factor profiles. The four strongest independent predictors for aSAH, namely current smoking (OR 6.0; 95% CI 4.1 to 8.6), a positive family history for aSAH (4.0; 95% CI 2.3 to 7.0), hypertension (2.4; 95% CI 1.5 to 3.8) and hypercholesterolaemia (0.2; 95% CI 0.1 to 0.4), were used in the final prediction model. This model had an area under the receiver operating characteristic curve of 0.73 (95% CI 0.69 to 0.76). Depending on sex, age and the four predictors, the incidence of aSAH ranged from 0.4/100 000 to 298/100 000 person-years and lifetime risk between 0.02% and 7.2%. The incidence and lifetime risk of aSAH in the general population varies widely according to risk factor profiles. Whether persons with high risks benefit from screening should be assessed in cost-effectiveness studies.

The School Adjustment of Students in Distinct Risk Configurations: Considerations for the Development of Selected and Indicated Interventions

ERIC Educational Resources Information Center

Petrin, Robert A.

2011-01-01

As indicated in papers 2 and 3 of this symposium and in published research from Project REAL, there is clear evidence that the SEALS model has a general positive impact on the school context during the early adolescent years. The purpose of this study was to identify key process factors that support gains to academic outcomes in general, but…

Customer satisfaction in medical service encounters -- a comparison between obstetrics and gynecology patients and general medical patients.

PubMed

Chang, Ching-Sheng; Weng, Hui-Ching; Chang, Hsin-Hsin; Hsu, Tsuen-Ho

2006-03-01

This study is concerned with the "service encounter", and seeks to describe, by use of the Service Encounter Evaluation Model, how the processes involved in the service encounter affect customer satisfaction. Its findings have implications for management practice and research directions, and recommendations are made. With the implementation of a national health insurance scheme, an ever-prospering economy and continually improving educational levels in Taiwan, demand among citizens for good health and medical care is ever increasing. Obstetrics and gynecology patients often differ greatly from general patients, in terms of their moods and emotions. This research involved an empirical study, whose subjects were 590 customers of general clinics and 339 customers of gynecology clinics, in various medical centers in southern Taiwan. By factor analysis, the study established four influencing factors, which were "Medical professionals", "Nursing professionals", "Service personnel" and "Space and facilities". Using the Linear Structural Relation Model (LISREL), it found that medical professionals, nursing professionals, service personnel and space and facilities were effective predictors of medical treatment satisfaction. We also found that the greatest positive impact on overall medical treatment satisfaction resulted from rises in satisfaction with medical professionals, but that the least impact was achieved in relation to service personnel in the general and gynecology clinics.

A deeper view of insight in schizophrenia: Insight dimensions, unawareness and misattribution of particular symptoms and its relation with psychopathological factors.

PubMed

Pousa, Esther; Ochoa, Susana; Cobo, Jesús; Nieto, Lourdes; Usall, Judith; Gonzalez, Beatriz; Garcia-Ribera, Carles; Pérez Solà, Victor; Ruiz, Ada-I; Baños, Iris; Cobo, Jesús; García-Ribera, Carles; González, Beatriz; Massons, Carmina; Nieto, Lourdes; Monserrat, Clara; Ochoa, Susana; Pousa, Esther; Ruiz, Ada-Inmaculada; Ruiz, Isabel; Sanchez-Cabezudo, Dolores; Usall, Judith

2017-11-01

1. To describe insight in a large sample of schizophrenia subjects from a multidimensional point of view, including unawareness of general insight dimensions as well as unawareness and misattribution of particular symptoms. 2. To explore the relationship between unawareness and clinical and socio-demographic variables. 248 schizophrenia patients were assessed with the Positive and Negative Syndrome Scale (PANSS, five factor model of Lindenmayer) and the full Scale of Unawareness of Mental Disorder (SUMD). Bivariate associations and multiple linear regression analyses were used to investigate the relationship between unawareness, symptoms and socio-demographic variables. Around 40% of the sample showed unawareness of mental disorder, of the need for medication and of the social consequences. Levels of unawareness and misattribution of particular symptoms varied considerably. General unawareness dimensions showed small significant correlations with positive, cognitive and excitement factors of psychopathology, whereas these symptom factors showed higher correlations with unawareness of particular symptoms. Similarly, regression models showed a small significant predictive value of positive symptoms in the three general unawareness dimensions while a moderate one in the prediction of particular symptoms. Misattribution showed no significant correlations with any symptom factors. Results confirm that insight in schizophrenia is a multi-phased phenomenon and that unawareness into particular symptoms varies widely. The overlap between unawareness dimensions and psychopathology is small and seems to be restricted to positive and cognitive symptoms, supporting the accounts from cognitive neurosciences that suggest that besides basic cognition poor insight may be in part a failure of self-reflection or strategic metacognition. Copyright © 2017 Elsevier B.V. All rights reserved.

A realistic host-vector transmission model for describing malaria prevalence pattern.

PubMed

Mandal, Sandip; Sinha, Somdatta; Sarkar, Ram Rup

2013-12-01

Malaria continues to be a major public health concern all over the world even after effective control policies have been employed, and considerable understanding of the disease biology have been attained, from both the experimental and modelling perspective. Interactions between different general and local processes, such as dependence on age and immunity of the human host, variations of temperature and rainfall in tropical and sub-tropical areas, and continued presence of asymptomatic infections, regulate the host-vector interactions, and are responsible for the continuing disease prevalence pattern.In this paper, a general mathematical model of malaria transmission is developed considering short and long-term age-dependent immunity of human host and its interaction with pathogen-infected mosquito vector. The model is studied analytically and numerically to understand the role of different parameters related to mosquitoes and humans. To validate the model with a disease prevalence pattern in a particular region, real epidemiological data from the north-eastern part of India was used, and the effect of seasonal variation in mosquito density was modelled based on local climactic data. The model developed based on general features of host-vector interactions, and modified simply incorporating local environmental factors with minimal changes, can successfully explain the disease transmission process in the region. This provides a general approach toward modelling malaria that can be adapted to control future outbreaks of malaria.

The General Factor of Personality: A General Critique.

PubMed

Revelle, William; Wilt, Joshua

2013-10-01

Recently, it has been proposed that all non-cognitive measures of personality share a general factor of personality. A problem with many of these studies is a lack of clarity in defining a general factor. In this paper we address the multiple ways in which a general factor has been identified and argue that many of these approaches find factors that are not in fact general. Through the use of artificial examples, we show that a general factor is not: The first factor or component of a correlation or covariance matrix.The first factor resulting from a bifactor rotation or biquartimin transformationNecessarily the result of a confirmatory factor analysis forcing a bifactor solution We consider how the definition of what constitutes a general factor can lead to confusion, and we will demonstrate alternative ways of estimating the general factor saturation that are more appropriate.

The General Factor of Personality: A General Critique

PubMed Central

Revelle, William; Wilt, Joshua

2013-01-01

Recently, it has been proposed that all non-cognitive measures of personality share a general factor of personality. A problem with many of these studies is a lack of clarity in defining a general factor. In this paper we address the multiple ways in which a general factor has been identified and argue that many of these approaches find factors that are not in fact general. Through the use of artificial examples, we show that a general factor is not: The first factor or component of a correlation or covariance matrix.The first factor resulting from a bifactor rotation or biquartimin transformationNecessarily the result of a confirmatory factor analysis forcing a bifactor solution We consider how the definition of what constitutes a general factor can lead to confusion, and we will demonstrate alternative ways of estimating the general factor saturation that are more appropriate. PMID:23956474

Bone fracture healing in mechanobiological modeling: A review of principles and methods.

PubMed

Ghiasi, Mohammad S; Chen, Jason; Vaziri, Ashkan; Rodriguez, Edward K; Nazarian, Ara

2017-06-01

Bone fracture is a very common body injury. The healing process is physiologically complex, involving both biological and mechanical aspects. Following a fracture, cell migration, cell/tissue differentiation, tissue synthesis, and cytokine and growth factor release occur, regulated by the mechanical environment. Over the past decade, bone healing simulation and modeling has been employed to understand its details and mechanisms, to investigate specific clinical questions, and to design healing strategies. The goal of this effort is to review the history and the most recent work in bone healing simulations with an emphasis on both biological and mechanical properties. Therefore, we provide a brief review of the biology of bone fracture repair, followed by an outline of the key growth factors and mechanical factors influencing it. We then compare different methodologies of bone healing simulation, including conceptual modeling (qualitative modeling of bone healing to understand the general mechanisms), biological modeling (considering only the biological factors and processes), and mechanobiological modeling (considering both biological aspects and mechanical environment). Finally we evaluate different components and clinical applications of bone healing simulation such as mechanical stimuli, phases of bone healing, and angiogenesis.

Suicidal Ideation and Interpersonal Needs: Factor Structure of a Short Version of the Interpersonal Needs Questionnaire in an At-Risk Military Sample.

PubMed

Allan, Nicholas P; Gros, Daniel F; Hom, Melanie A; Joiner, Thomas E; Stecker, Tracy

2016-01-01

The interpersonal-psychological theory of suicide posits that perceived burdensomeness (PB; i.e., the belief that others would be better off if one were dead) and thwarted belongingness (TB; i.e., the belief that one lacks meaningful social connections) are both necessary risk factors for the development of suicidal ideation. To test these relations, measures are needed that are well validated, especially in samples of at-risk adults. The current study was designed to examine the factor structure of an eight-item version of the Interpersonal Needs Questionnaire (INQ) in a sample of 405 U.S. past and current military personnel (M age  = 31.57 years, SD = 7.28; 90.4% male) who endorsed either current suicidal ideation and/or a past suicide attempt. Analyses were conducted using confirmatory factor analysis (CFA). A bifactor model comprising a general factor, labeled interpersonal needs, and two specific factors, labeled PB and TB, fit the data best. The general factor captured a high proportion of overall variance (81.9%). In contrast, the TB factor captured only a modest amount of variance in items meant to capture this factor (59.1%) and the PB factor captured very little variance in items meant to capture this factor (13.5%). Further, only the interpersonal needs factor was associated with lifetime and past-week suicidal ideation as well as suicidal ideation frequency and duration. The current findings indicate that, for the INQ-8 in high-risk military personnel, a general interpersonal needs factor accounted for the relations PB and TB share with suicidal ideation.

Scale factor duality for conformal cyclic cosmologies

NASA Astrophysics Data System (ADS)

Camara da Silva, U.; Alves Lima, A. L.; Sotkov, G. M.

2016-11-01

The scale factor duality is a symmetry of dilaton gravity which is known to lead to pre-big-bang cosmologies. A conformal time version of the scale factor duality (SFD) was recently implemented as a UV/IR symmetry between decelerated and accelerated phases of the post-big-bang evolution within Einstein gravity coupled to a scalar field. The problem investigated in the present paper concerns the employment of the conformal time SFD methods to the construction of pre-big-bang and cyclic extensions of these models. We demonstrate that each big-bang model gives rise to two qualitatively different pre-big-bang evolutions: a contraction/expansion SFD model and Penrose's Conformal Cyclic Cosmology (CCC). A few examples of SFD symmetric cyclic universes involving certain gauged Kähler sigma models minimally coupled to Einstein gravity are studied. We also describe the specific SFD features of the thermodynamics and the conditions for validity of the generalized second law in the case of Gauss-Bonnet (GB) extension of these selected CCC models.

Complementary exploratory and confirmatory factor analyses of the French WISC-V: Analyses based on the standardization sample.

PubMed

Lecerf, Thierry; Canivez, Gary L

2018-06-01

Interpretation of the French Wechsler Intelligence Scale for Children-Fifth Edition (French WISC-V; Wechsler, 2016a) is based on a 5-factor model including Verbal Comprehension (VC), Visual Spatial (VS), Fluid Reasoning (FR), Working Memory (WM), and Processing Speed (PS). Evidence for the French WISC-V factorial structure was established exclusively through confirmatory factor analyses (CFAs). However, as recommended by Carroll (1995); Reise (2012), and Brown (2015), factorial structure should derive from both exploratory factor analysis (EFA) and CFA. The first goal of this study was to examine the factorial structure of the French WISC-V using EFA. The 15 French WISC-V primary and secondary subtest scaled scores intercorrelation matrix was used and factor extraction criteria suggested from 1 to 4 factors. To disentangle the contribution of first- and second-order factors, the Schmid and Leiman (1957) orthogonalization transformation (SLT) was applied. Overall, no EFA evidence for 5 factors was found. Results indicated that the g factor accounted for about 67% of the common variance and that the contributions of the first-order factors were weak (3.6 to 11.9%). CFA was used to test numerous alternative models. Results indicated that bifactor models produced better fit to these data than higher-order models. Consistent with previous studies, findings suggested dominance of the general intelligence factor and that users should thus emphasize the Full Scale IQ (FSIQ) when interpreting the French WISC-V. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Attitudes toward psychotropic medications among patients with chronic psychiatric disorders and their family caregivers

PubMed Central

Grover, Sandeep; Chakrabarti, Subho; Sharma, Aarti; Tyagi, Shikha

2014-01-01

Aim: To examine attitudes towards psychotropic medications among patients with chronic psychiatric disorders as well as their family caregivers by using factor analysis. Materials and Methods: The study included 200 patients and their family caregivers with chronic psychiatric disorders who are attending the psychiatry outpatient services. A self-designed 18-item self-rated questionnaire was used to evaluate the attitude toward psychotropics and factor analysis was done to study the different models of attitudes. Results: In general both patients and caregivers had positive attitude toward the psychotropic medications and there was no significant difference between the patients and caregivers on the various items of the questionnaire assessing the attitude. Factor analysis of the questionnaire indicated that either two-factor or four-factor models explained the attitude of the patients and caregivers. In the two-factor model there was one positive and one negative attitude factor, whereas the four-factor model comprised of two positive and two negative attitude factors. The four-factor model of attitudes provided a more comprehensive solution to how attitudes might be formed among patients and their family caregivers. Factors one and four in the four-factor solution still reflected positive attitudes, but appeared to portray a risk-benefit approach, in which benefits such as the efficacy of psychotropic medications in treating mental illnesses and preventing relapse, and medications being better than other options were being contrasted with the risks of side effects and permanent damage or harm. Conclusion: Attitudes of patients with chronic psychiatric disorders and their caregivers toward psychotropic medications appear to be shaped by factors such as perceived efficacy or benefit from medicines, the necessity for taking treatment and concerns such as side effects, harm or expense. PMID:25288840

On the limitations of General Circulation Climate Models

NASA Technical Reports Server (NTRS)

Stone, Peter H.; Risbey, James S.

1990-01-01

General Circulation Models (GCMs) by definition calculate large-scale dynamical and thermodynamical processes and their associated feedbacks from first principles. This aspect of GCMs is widely believed to give them an advantage in simulating global scale climate changes as compared to simpler models which do not calculate the large-scale processes from first principles. However, it is pointed out that the meridional transports of heat simulated GCMs used in climate change experiments differ from observational analyses and from other GCMs by as much as a factor of two. It is also demonstrated that GCM simulations of the large scale transports of heat are sensitive to the (uncertain) subgrid scale parameterizations. This leads to the question whether current GCMs are in fact superior to simpler models for simulating temperature changes associated with global scale climate change.

[The role of art therapy in the rehabilitation of psycho-socially disabled people].

PubMed

Simon, Lajos; Kovács, Emese

2015-01-01

The present review focuses on the generally accepted and applied community psychiatry based models of psycho-social rehabilitation. The basics of the Strenghts model and the Recovery based model are introduced in this paper. Both models can be assisted by art therapy in various ways. The forms and the therapeutic factors of art therapy are also discussed, as well as the effects of the creating experience during the art therapy sessions. The authors introduce the good practice of the Moravcsik Foundation with highlights in two special areas that are beyond the generally applied art therapy work and representing important support in reaching the goals set during the rehabilitation process. Further, the authors describe the Budapest Art Brut Gallery and the PsychArt24 art marathon project in details.

Approximate probabilistic cellular automata for the dynamics of single-species populations under discrete logisticlike growth with and without weak Allee effects.

PubMed

Mendonça, J Ricardo G; Gevorgyan, Yeva

2017-05-01

We investigate one-dimensional elementary probabilistic cellular automata (PCA) whose dynamics in first-order mean-field approximation yields discrete logisticlike growth models for a single-species unstructured population with nonoverlapping generations. Beginning with a general six-parameter model, we find constraints on the transition probabilities of the PCA that guarantee that the ensuing approximations make sense in terms of population dynamics and classify the valid combinations thereof. Several possible models display a negative cubic term that can be interpreted as a weak Allee factor. We also investigate the conditions under which a one-parameter PCA derived from the more general six-parameter model can generate valid population growth dynamics. Numerical simulations illustrate the behavior of some of the PCA found.

Processing Technology Selection for Municipal Sewage Treatment Based on a Multi-Objective Decision Model under Uncertainty.

PubMed

Chen, Xudong; Xu, Zhongwen; Yao, Liming; Ma, Ning

2018-03-05

This study considers the two factors of environmental protection and economic benefits to address municipal sewage treatment. Based on considerations regarding the sewage treatment plant construction site, processing technology, capital investment, operation costs, water pollutant emissions, water quality and other indicators, we establish a general multi-objective decision model for optimizing municipal sewage treatment plant construction. Using the construction of a sewage treatment plant in a suburb of Chengdu as an example, this paper tests the general model of multi-objective decision-making for the sewage treatment plant construction by implementing a genetic algorithm. The results show the applicability and effectiveness of the multi-objective decision model for the sewage treatment plant. This paper provides decision and technical support for the optimization of municipal sewage treatment.

Temporal trend and climate factors of hemorrhagic fever with renal syndrome epidemic in Shenyang City, China

PubMed Central

2011-01-01

Background Hemorrhagic fever with renal syndrome (HFRS) is an important infectious disease caused by different species of hantaviruses. As a rodent-borne disease with a seasonal distribution, external environmental factors including climate factors may play a significant role in its transmission. The city of Shenyang is one of the most seriously endemic areas for HFRS. Here, we characterized the dynamic temporal trend of HFRS, and identified climate-related risk factors and their roles in HFRS transmission in Shenyang, China. Methods The annual and monthly cumulative numbers of HFRS cases from 2004 to 2009 were calculated and plotted to show the annual and seasonal fluctuation in Shenyang. Cross-correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on HFRS transmission and the autocorrelation of monthly HFRS cases. Principal component analysis was constructed by using climate data from 2004 to 2009 to extract principal components of climate factors to reduce co-linearity. The extracted principal components and autocorrelation terms of monthly HFRS cases were added into a multiple regression model called principal components regression model (PCR) to quantify the relationship between climate factors, autocorrelation terms and transmission of HFRS. The PCR model was compared to a general multiple regression model conducted only with climate factors as independent variables. Results A distinctly declining temporal trend of annual HFRS incidence was identified. HFRS cases were reported every month, and the two peak periods occurred in spring (March to May) and winter (November to January), during which, nearly 75% of the HFRS cases were reported. Three principal components were extracted with a cumulative contribution rate of 86.06%. Component 1 represented MinRH0, MT1, RH1, and MWV1; component 2 represented RH2, MaxT3, and MAP3; and component 3 represented MaxT2, MAP2, and MWV2. The PCR model was composed of three principal components and two autocorrelation terms. The association between HFRS epidemics and climate factors was better explained in the PCR model (F = 446.452, P < 0.001, adjusted R2 = 0.75) than in the general multiple regression model (F = 223.670, P < 0.000, adjusted R2 = 0.51). Conclusion The temporal distribution of HFRS in Shenyang varied in different years with a distinctly declining trend. The monthly trends of HFRS were significantly associated with local temperature, relative humidity, precipitation, air pressure, and wind velocity of the different previous months. The model conducted in this study will make HFRS surveillance simpler and the control of HFRS more targeted in Shenyang. PMID:22133347

Sampling Capacity Underlies Individual Differences in Human Associative Learning

PubMed Central

2014-01-01

Though much work has studied how external factors, such as stimulus properties, influence generalization of associative strength, there has been limited exploration of the influence that internal dispositions may contribute to stimulus processing. Here we report 2 studies using a modified negative patterning discrimination to test the relationship between global processing and generalization. Global processing was associated with stronger negative patterning discrimination, indicative of limited generalization between distinct stimulus compounds and their constituent elements. In Experiment 2, participants pretrained to adopt global processing similarly showed strong negative patterning discrimination. These results demonstrate considerable individual difference in capacity to engage in negative patterning discrimination and suggest that the tendency toward global processing may be one factor explaining this variability. The need for models of learning to account for this variability in learning is discussed. PMID:24446699

Integration of Occupational Safety to Contractors` or Subcontractors` Performance Evaluation in Construction Projects

NASA Astrophysics Data System (ADS)

Kozlovská, Mária; Struková, Zuzana

2013-06-01

Several factors should be considered by the owner and general contractor in the process of contractors` and subcontractors` selection and evaluation. The paper reviews the recent models addressed to guide general contractors in subcontractors' selection process and in evaluation of different contractors during the execution of the project. Moreover the paper suggests the impact of different contractors' performance to the overall level of occupational health and safety culture at the sites. It deals with the factors influencing the safety performance of contractors during construction and analyses the methods for assessing the safety performance of construction contractors. The results of contractors' safety performance evaluation could be a useful tool in motivating contractors to achieve better safety outcomes or could have effect on owners` or general contractors' decision making about contractors suitability for future contracting works.

The Willingness-to-Pay for General Practitioners in Contractual Service and Influencing Factors among Empty Nesters in Chongqing, China.

PubMed

Chen, Fei; Xu, Xiang-Long; Yang, Zhan; Tan, Hua-Wei; Zhang, Liang

2015-08-10

In 2012, a pilot health policy of contractual service relations between general practitioners and patients was implemented in China. Due to the decline in body and cognitive function, as well as the lack of family care and narrow social support networks, the demand of health services among the elderly is much higher than that among the general population. This study aims to probe into the empty nesters' willingness-to-pay for general practitioners using a contractual service policy, investigating empty nesters' payment levels for the service, and analyze the main factors affecting the willingness of empty-nesters' general practitioners using contractual service supply cost. This cross-sectional study adopted a multistage stratified sampling method to survey 865, city empty nesters (six communities in three districts of one city) aged 60-85 years. A condition value method was used to infer the distribution of the willingness-to-pay; Cox's proportional hazards regression model was used to analyze the influencing factors of willingness-to-pay. More than seventy percent (76.6%) of the empty nesters in this city were willing to pay general practitioners using contract service in Chongqing. The level of willingness-to-pay for the surveyed empty nesters was 34.1 yuan per year. The median value was 22.1 yuan per year, which was below the Chongqing urban and rural cooperative medical insurance individual funding level (60 yuan per year) in 2013. Cox's proportional hazards regression model analysis showed that the higher the education level was, the worse the self-reported health status would be, accompanied by higher family per capita income, higher satisfaction of community health service, and higher willingness-to-pay empty nesters using a contract service. Women had a higher willingness-to-pay than men. The willingness-to-pay for general practitioners by contractual service is high among city empty nesters in Chongqing, thus, individual financing is feasible. However, people are willing to pay less than half of the current personal financing of cooperative medical insurance of urban and rural residents. Education level, family per capita income, and self-reported health status are the main factors affecting the cost sharing intention for general practitioners using contract service supply. According to the existing situation of different empty nesters, it is important to perfect the design of general practitioners using a contractual service policy system, according to differentiated personal financing levels.

The Willingness-to-Pay for General Practitioners in Contractual Service and Influencing Factors among Empty Nesters in Chongqing, China

PubMed Central

Chen, Fei; Xu, Xiang-Long; Yang, Zhan; Tan, Hua-Wei; Zhang, Liang

2015-01-01

Background: In 2012, a pilot health policy of contractual service relations between general practitioners and patients was implemented in China. Due to the decline in body and cognitive function, as well as the lack of family care and narrow social support networks, the demand of health services among the elderly is much higher than that among the general population. This study aims to probe into the empty nesters’ willingness-to-pay for general practitioners using a contractual service policy, investigating empty nesters’ payment levels for the service, and analyze the main factors affecting the willingness of empty-nesters’ general practitioners using contractual service supply cost. Methods: This cross-sectional study adopted a multistage stratified sampling method to survey 865, city empty nesters (six communities in three districts of one city) aged 60–85 years. A condition value method was used to infer the distribution of the willingness-to-pay; Cox’s proportional hazards regression model was used to analyze the influencing factors of willingness-to-pay. Results: More than seventy percent (76.6%) of the empty nesters in this city were willing to pay general practitioners using contract service in Chongqing. The level of willingness-to-pay for the surveyed empty nesters was 34.1 yuan per year. The median value was 22.1 yuan per year, which was below the Chongqing urban and rural cooperative medical insurance individual funding level (60 yuan per year) in 2013. Cox’s proportional hazards regression model analysis showed that the higher the education level was, the worse the self-reported health status would be, accompanied by higher family per capita income, higher satisfaction of community health service, and higher willingness-to-pay empty nesters using a contract service. Women had a higher willingness-to-pay than men. Conclusions: The willingness-to-pay for general practitioners by contractual service is high among city empty nesters in Chongqing, thus, individual financing is feasible. However, people are willing to pay less than half of the current personal financing of cooperative medical insurance of urban and rural residents. Education level, family per capita income, and self-reported health status are the main factors affecting the cost sharing intention for general practitioners using contract service supply. According to the existing situation of different empty nesters, it is important to perfect the design of general practitioners using a contractual service policy system, according to differentiated personal financing levels. PMID:26266416

Factors Linked to Substance Use Disorder Counselors’ (Non)Implementation Likelihood of Tobacco Cessation 5 A's, Counseling, and Pharmacotherapy

PubMed Central

Laschober, Tanja C.; Muilenburg, Jessica L.; Eby, Lillian T.

2015-01-01

Study Background Despite efforts to promote the use of tobacco cessation services (TCS), implementation extensiveness remains limited. This study investigated three factors (cognitive, behavioral, environmental) identified by social cognitive theory as predictors of substance use disorder counselors’ likelihood of use versus non-use of tobacco cessation (TC) 5 A's (ask patients about tobacco use, advise to quit, assess willingness to quit, assist in quitting, arrange for follow-up contact), counseling, and pharmacotherapy with their patients who smoke cigarettes. Methods Data were collected in 2010 from 942 counselors working in 257 treatment programs that offered TCS. Cognitive factors included perceived job competence and TC attitudes. Behavioral factors encompassed TC-related skills and general training. External factors consisted of TC financial resource availability and coworker TC attitudes. Data were analyzed using logistic regression models with nested data. Results Approximately 86% of counselors used the 5 A's, 76% used counseling, and 53% used pharmacotherapy. When counselors had greater TC-related skills and greater general training they were more likely to implement the 5 A's. Implementation of counseling was more likely when counselors had more positive attitudes toward TC treatment, greater general training, greater financial resource availability, and when coworkers had more positive attitudes toward TC treatment. Implementation of pharmacotherapy was more likely when counselors had more positive attitudes toward TC treatment, greater general training, and greater financial resource availability. Conclusion Findings indicate that interventions to promote TCS implementation should consider all three factors simultaneously as suggested by social cognitive theory. PMID:26005696

Validation and psychometric properties of the Alcohol Positive and Negative Affect Schedule: Are drinking emotions distinct from general emotions?

PubMed

Lac, Andrew; Donaldson, Candice D

2018-02-01

People vary in experiences of positive and negative emotions from consuming alcohol, but no validated measurement instrument exclusively devoted to assessing drinking emotions exists in the literature. The current research validated and evaluated the psychometric properties of an alcohol affect scale based on adjectives from the Positive and Negative Affect Schedule (PANAS) and tested the extent that emotions incurred from drinking were distinct from general trait-based emotions. Three studies tested independent samples of adult alcohol users. In Study 1 (N = 494), exploratory factor analyses of the Alcohol PANAS revealed that both the 20-item model and the 9-parcel model (represented by similar mood content) supported the 2-factor dimensionality of alcohol positive and negative affect. In Study 2 (N = 302), confirmatory factor analyses corroborated the measurement structure of alcohol positive and negative affect, and both constructs evidenced statistical independence from general positive and negative affect. In Study 3 (N = 452), alcohol positive and negative affect exhibited discriminant, convergent, and criterion validity with established alcohol scales. Incremental validity tests demonstrated that alcohol positive and negative affect uniquely contributed (beyond general positive and negative affect) to alcohol expectancies, use, and problems. Findings support that alcohol emotions are conceptually distinct from trait emotions, and underscore the necessity of an assessment instrument tailored to the former to examine associations with alcohol beliefs and behaviors. The Alcohol PANAS confers theoretical and practical applications to understand the emotional consequences of drinking. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Emerging allied dental workforce models: considerations for academic dental institutions.

PubMed

McKinnon, Monette; Luke, Gina; Bresch, Jack; Moss, Myla; Valachovic, Richard W

2007-11-01

The U.S. surgeon general defined the national oral health care crisis in 2001 in Oral Health in America: A Report of the Surgeon General. The report concluded that the public infrastructure for oral health is not sufficient to meet the needs of disadvantaged groups and is disproportionately available depending upon certain racial, ethnic, and socioeconomic factors within the U.S. population. Now, several new workforce models are emerging that attempt to address shortcomings in the oral health care workforce. Access to oral health care is the most critical issue driving these new workforce models. Currently, three midlevel dental workforce models dominate the debate. The purpose of this report is to describe these models and their stage of development to assist the dental education community in preparing for the education of these new providers. The models are 1) the advanced dental hygiene practitioner; 2) the community dental health coordinator; and 3) the dental health aide therapist.

A quantitative model of application slow-down in multi-resource shared systems

DOE PAGES

Lim, Seung-Hwan; Kim, Youngjae

2016-12-26

Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price-resource contention among jobs increases job completion time. In this study, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job ismore » characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We extended the D-factor model to capture the slow-down of applications when multiple identical resources exist such as multi-core environments and multi-disks environments. Finally, validation results of the extended D-factor model with HPC checkpoint applications on the parallel file systems show that D-factor accurately captures the slow down of concurrent applications in such environments.« less

A quantitative model of application slow-down in multi-resource shared systems

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

Lim, Seung-Hwan; Kim, Youngjae

Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price-resource contention among jobs increases job completion time. In this study, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job ismore » characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We extended the D-factor model to capture the slow-down of applications when multiple identical resources exist such as multi-core environments and multi-disks environments. Finally, validation results of the extended D-factor model with HPC checkpoint applications on the parallel file systems show that D-factor accurately captures the slow down of concurrent applications in such environments.« less