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Sample records for mediating variable model

  1. About hidden influence of predictor variables: Suppressor and mediator variables

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    Milovanović Boško

    2013-01-01

    Full Text Available In this paper procedure for researching hidden influence of predictor variables in regression models and depicting suppressor variables and mediator variables is shown. It is also shown that detection of suppressor variables and mediator variables could provide refined information about the research problem. As an example for applying this procedure, relation between Atlantic atmospheric centers and air temperature and precipitation amount in Serbia is chosen. [Projekat Ministarstva nauke Republike Srbije, br. 47007

  2. Accounting for sex differences in PTSD: A multi-variable mediation model.

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    Christiansen, Dorte M; Hansen, Maj

    2015-01-01

    Approximately twice as many females as males are diagnosed with posttraumatic stress disorder (PTSD). However, little is known about why females report more PTSD symptoms than males. Prior studies have generally focused on few potential mediators at a time and have often used methods that were not ideally suited to test for mediation effects. Prior research has identified a number of individual risk factors that may contribute to sex differences in PTSD severity, although these cannot fully account for the increased symptom levels in females when examined individually. The present study is the first to systematically test the hypothesis that a combination of pre-, peri-, and posttraumatic risk factors more prevalent in females can account for sex differences in PTSD severity. The study was a quasi-prospective questionnaire survey assessing PTSD and related variables in 73.3% of all Danish bank employees exposed to bank robbery during the period from April 2010 to April 2011. Participants filled out questionnaires 1 week (T1, N=450) and 6 months after the robbery (T2, N=368; 61.1% females). Mediation was examined using an analysis designed specifically to test a multiple mediator model. Females reported more PTSD symptoms than males and higher levels of neuroticism, depression, physical anxiety sensitivity, peritraumatic fear, horror, and helplessness (the A2 criterion), tonic immobility, panic, dissociation, negative posttraumatic cognitions about self and the world, and feeling let down. These variables were included in the model as potential mediators. The combination of risk factors significantly mediated the association between sex and PTSD severity, accounting for 83% of the association. The findings suggest that females report more PTSD symptoms because they experience higher levels of associated risk factors. The results are relevant to other trauma populations and to other trauma-related psychiatric disorders more prevalent in females, such as depression

  3. Accounting for sex differences in PTSD: A multi-variable mediation model

    Directory of Open Access Journals (Sweden)

    Dorte M. Christiansen

    2015-01-01

    Full Text Available Background: Approximately twice as many females as males are diagnosed with posttraumatic stress disorder (PTSD. However, little is known about why females report more PTSD symptoms than males. Prior studies have generally focused on few potential mediators at a time and have often used methods that were not ideally suited to test for mediation effects. Prior research has identified a number of individual risk factors that may contribute to sex differences in PTSD severity, although these cannot fully account for the increased symptom levels in females when examined individually. Objective: The present study is the first to systematically test the hypothesis that a combination of pre-, peri-, and posttraumatic risk factors more prevalent in females can account for sex differences in PTSD severity. Method: The study was a quasi-prospective questionnaire survey assessing PTSD and related variables in 73.3% of all Danish bank employees exposed to bank robbery during the period from April 2010 to April 2011. Participants filled out questionnaires 1 week (T1, N=450 and 6 months after the robbery (T2, N=368; 61.1% females. Mediation was examined using an analysis designed specifically to test a multiple mediator model. Results: Females reported more PTSD symptoms than males and higher levels of neuroticism, depression, physical anxiety sensitivity, peritraumatic fear, horror, and helplessness (the A2 criterion, tonic immobility, panic, dissociation, negative posttraumatic cognitions about self and the world, and feeling let down. These variables were included in the model as potential mediators. The combination of risk factors significantly mediated the association between sex and PTSD severity, accounting for 83% of the association. Conclusions: The findings suggest that females report more PTSD symptoms because they experience higher levels of associated risk factors. The results are relevant to other trauma populations and to other trauma

  4. Accounting for sex differences in PTSD: A multi-variable mediation model

    DEFF Research Database (Denmark)

    Christiansen, Dorte M.; Hansen, Maj

    2015-01-01

    methods that were not ideally suited to test for mediation effects. Prior research has identified a number of individual risk factors that may contribute to sex differences in PTSD severity, although these cannot fully account for the increased symptom levels in females when examined individually....... Objective: The present study is the first to systematically test the hypothesis that a combination of pre-, peri-, and posttraumatic risk factors more prevalent in females can account for sex differences in PTSD severity. Method: The study was a quasi-prospective questionnaire survey assessing PTSD...... cognitions about self and the world, and feeling let down. These variables were included in the model as potential mediators. The combination of risk factors significantly mediated the association between sex and PTSD severity, accounting for 83% of the association. Conclusion: The findings suggest...

  5. Guidelines for the Investigation of Mediating Variables in Business Research.

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    MacKinnon, David P; Coxe, Stefany; Baraldi, Amanda N

    2012-03-01

    Business theories often specify the mediating mechanisms by which a predictor variable affects an outcome variable. In the last 30 years, investigations of mediating processes have become more widespread with corresponding developments in statistical methods to conduct these tests. The purpose of this article is to provide guidelines for mediation studies by focusing on decisions made prior to the research study that affect the clarity of conclusions from a mediation study, the statistical models for mediation analysis, and methods to improve interpretation of mediation results after the research study. Throughout this article, the importance of a program of experimental and observational research for investigating mediating mechanisms is emphasized.

  6. Mediating Variables in a Transtheoretical Model Dietary Intervention Program

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    Di Noia, Jennifer; Prochaska, James O.

    2010-01-01

    This study identified mediators of a Transtheoretical Model (TTM) intervention to increase fruit and vegetable consumption among economically disadvantaged African American adolescents (N = 549). Single-and multiple-mediator models were used to determine whether pros, cons, self-efficacy, and stages of change satisfied four conclusions necessary…

  7. Estimation of causal mediation effects for a dichotomous outcome in multiple-mediator models using the mediation formula.

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    Wang, Wei; Nelson, Suchitra; Albert, Jeffrey M

    2013-10-30

    Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a nonzero total mediation effect increases as the correlation coefficient between two mediators increases, whereas power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. Copyright © 2013 John Wiley & Sons, Ltd.

  8. Estimation of Causal Mediation Effects for a Dichotomous Outcome in Multiple-Mediator Models using the Mediation Formula

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    Nelson, Suchitra; Albert, Jeffrey M.

    2013-01-01

    Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a non-zero total mediation effect increases as the correlation coefficient between two mediators increases, while power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. PMID:23650048

  9. Estimation of indirect effect when the mediator is a censored variable.

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    Wang, Jian; Shete, Sanjay

    2017-01-01

    A mediation model explores the direct and indirect effects of an initial variable ( X) on an outcome variable ( Y) by including a mediator ( M). In many realistic scenarios, investigators observe censored data instead of the complete data. Current research in mediation analysis for censored data focuses mainly on censored outcomes, but not censored mediators. In this study, we proposed a strategy based on the accelerated failure time model and a multiple imputation approach. We adapted a measure of the indirect effect for the mediation model with a censored mediator, which can assess the indirect effect at both the group and individual levels. Based on simulation, we established the bias in the estimations of different paths (i.e. the effects of X on M [ a], of M on Y [ b] and of X on Y given mediator M [ c']) and indirect effects when analyzing the data using the existing approaches, including a naïve approach implemented in software such as Mplus, complete-case analysis, and the Tobit mediation model. We conducted simulation studies to investigate the performance of the proposed strategy compared to that of the existing approaches. The proposed strategy accurately estimates the coefficients of different paths, indirect effects and percentages of the total effects mediated. We applied these mediation approaches to the study of SNPs, age at menopause and fasting glucose levels. Our results indicate that there is no indirect effect of association between SNPs and fasting glucose level that is mediated through the age at menopause.

  10. An exponential decay model for mediation.

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    Fritz, Matthew S

    2014-10-01

    Mediation analysis is often used to investigate mechanisms of change in prevention research. Results finding mediation are strengthened when longitudinal data are used because of the need for temporal precedence. Current longitudinal mediation models have focused mainly on linear change, but many variables in prevention change nonlinearly across time. The most common solution to nonlinearity is to add a quadratic term to the linear model, but this can lead to the use of the quadratic function to explain all nonlinearity, regardless of theory and the characteristics of the variables in the model. The current study describes the problems that arise when quadratic functions are used to describe all nonlinearity and how the use of nonlinear functions, such as exponential decay, address many of these problems. In addition, nonlinear models provide several advantages over polynomial models including usefulness of parameters, parsimony, and generalizability. The effects of using nonlinear functions for mediation analysis are then discussed and a nonlinear growth curve model for mediation is presented. An empirical example using data from a randomized intervention study is then provided to illustrate the estimation and interpretation of the model. Implications, limitations, and future directions are also discussed.

  11. Comparison of methods for the analysis of relatively simple mediation models.

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    Rijnhart, Judith J M; Twisk, Jos W R; Chinapaw, Mai J M; de Boer, Michiel R; Heymans, Martijn W

    2017-09-01

    Statistical mediation analysis is an often used method in trials, to unravel the pathways underlying the effect of an intervention on a particular outcome variable. Throughout the years, several methods have been proposed, such as ordinary least square (OLS) regression, structural equation modeling (SEM), and the potential outcomes framework. Most applied researchers do not know that these methods are mathematically equivalent when applied to mediation models with a continuous mediator and outcome variable. Therefore, the aim of this paper was to demonstrate the similarities between OLS regression, SEM, and the potential outcomes framework in three mediation models: 1) a crude model, 2) a confounder-adjusted model, and 3) a model with an interaction term for exposure-mediator interaction. Secondary data analysis of a randomized controlled trial that included 546 schoolchildren. In our data example, the mediator and outcome variable were both continuous. We compared the estimates of the total, direct and indirect effects, proportion mediated, and 95% confidence intervals (CIs) for the indirect effect across OLS regression, SEM, and the potential outcomes framework. OLS regression, SEM, and the potential outcomes framework yielded the same effect estimates in the crude mediation model, the confounder-adjusted mediation model, and the mediation model with an interaction term for exposure-mediator interaction. Since OLS regression, SEM, and the potential outcomes framework yield the same results in three mediation models with a continuous mediator and outcome variable, researchers can continue using the method that is most convenient to them.

  12. Accommodating Binary and Count Variables in Mediation: A Case for Conditional Indirect Effects

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    Geldhof, G. John; Anthony, Katherine P.; Selig, James P.; Mendez-Luck, Carolyn A.

    2018-01-01

    The existence of several accessible sources has led to a proliferation of mediation models in the applied research literature. Most of these sources assume endogenous variables (e.g., M, and Y) have normally distributed residuals, precluding models of binary and/or count data. Although a growing body of literature has expanded mediation models to…

  13. SPSS and SAS programming for the testing of mediation models.

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    Dudley, William N; Benuzillo, Jose G; Carrico, Mineh S

    2004-01-01

    Mediation modeling can explain the nature of the relation among three or more variables. In addition, it can be used to show how a variable mediates the relation between levels of intervention and outcome. The Sobel test, developed in 1990, provides a statistical method for determining the influence of a mediator on an intervention or outcome. Although interactive Web-based and stand-alone methods exist for computing the Sobel test, SPSS and SAS programs that automatically run the required regression analyses and computations increase the accessibility of mediation modeling to nursing researchers. To illustrate the utility of the Sobel test and to make this programming available to the Nursing Research audience in both SAS and SPSS. The history, logic, and technical aspects of mediation testing are introduced. The syntax files sobel.sps and sobel.sas, created to automate the computation of the regression analysis and test statistic, are available from the corresponding author. The reported programming allows the user to complete mediation testing with the user's own data in a single-step fashion. A technical manual included with the programming provides instruction on program use and interpretation of the output. Mediation modeling is a useful tool for describing the relation between three or more variables. Programming and manuals for using this model are made available.

  14. Guidelines for the Investigation of Mediating Variables in Business Research

    OpenAIRE

    MacKinnon, David P.; Coxe, Stefany; Baraldi, Amanda N.

    2011-01-01

    Business theories often specify the mediating mechanisms by which a predictor variable affects an outcome variable. In the last 30 years, investigations of mediating processes have become more widespread with corresponding developments in statistical methods to conduct these tests. The purpose of this article is to provide guidelines for mediation studies by focusing on decisions made prior to the research study that affect the clarity of conclusions from a mediation study, the statistical mo...

  15. Multiple Regression and Mediator Variables can be used to Avoid Double Counting when Economic Values are Derived using Stochastic Herd Simulation

    DEFF Research Database (Denmark)

    Østergaard, Søren; Ettema, Jehan Frans; Hjortø, Line

    Multiple regression and model building with mediator variables was addressed to avoid double counting when economic values are estimated from data simulated with herd simulation modeling (using the SimHerd model). The simulated incidence of metritis was analyzed statistically as the independent v...... in multiparous cows. The merit of using this approach was demonstrated since the economic value of metritis was estimated to be 81% higher when no mediator variables were included in the multiple regression analysis......Multiple regression and model building with mediator variables was addressed to avoid double counting when economic values are estimated from data simulated with herd simulation modeling (using the SimHerd model). The simulated incidence of metritis was analyzed statistically as the independent...... variable, while using the traits representing the direct effects of metritis on yield, fertility and occurrence of other diseases as mediator variables. The economic value of metritis was estimated to be €78 per 100 cow-years for each 1% increase of metritis in the period of 1-100 days in milk...

  16. Variable system: An alternative approach for the analysis of mediated moderation.

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    Kwan, Joyce Lok Yin; Chan, Wai

    2018-06-01

    Mediated moderation (meMO) occurs when the moderation effect of the moderator (W) on the relationship between the independent variable (X) and the dependent variable (Y) is transmitted through a mediator (M). To examine this process empirically, 2 different model specifications (Type I meMO and Type II meMO) have been proposed in the literature. However, both specifications are found to be problematic, either conceptually or statistically. For example, it can be shown that each type of meMO model is statistically equivalent to a particular form of moderated mediation (moME), another process that examines the condition when the indirect effect from X to Y through M varies as a function of W. Consequently, it is difficult for one to differentiate these 2 processes mathematically. This study therefore has 2 objectives. First, we attempt to differentiate moME and meMO by proposing an alternative specification for meMO. Conceptually, this alternative specification is intuitively meaningful and interpretable, and, statistically, it offers meMO a unique representation that is no longer identical to its moME counterpart. Second, using structural equation modeling, we propose an integrated approach for the analysis of meMO as well as for other general types of conditional path models. VS, a computer software program that implements the proposed approach, has been developed to facilitate the analysis of conditional path models for applied researchers. Real examples are considered to illustrate how the proposed approach works in practice and to compare its performance against the traditional methods. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  17. mma: An R Package for Mediation Analysis with Multiple Mediators

    Directory of Open Access Journals (Sweden)

    Qingzhao Yu

    2017-04-01

    Full Text Available Mediation refers to the effect transmitted by mediators that intervene in the relationship between an exposure and a response variable. Mediation analysis has been broadly studied in many fields. However, it remains a challenge for researchers to consider complicated associations among variables and to differentiate individual effects from multiple mediators. [1] proposed general definitions of mediation effects that were adaptable to all different types of response (categorical or continuous, exposure, or mediation variables. With these definitions, multiple mediators of different types can be considered simultaneously, and the indirect effects carried by individual mediators can be separated from the total effect. Moreover, the derived mediation analysis can be performed with general predictive models. That is, the relationships among variables can be modeled using not only generalized linear models but also nonparametric models such as the Multiple Additive Regression Trees. Therefore, more complicated variable transformations and interactions can be considered in analyzing the mediation effects. The proposed method is realized by the R package 'mma'. We illustrate in this paper the proposed method and how to use 'mma' to estimate mediation effects and make inferences.

  18. Associated and Mediating Variables Related to Job Satisfaction among Professionals from Mental Health Teams.

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    Fleury, Marie-Josée; Grenier, Guy; Bamvita, Jean-Marie; Chiocchio, François

    2018-06-01

    Using a structural analysis, this study examines the relationship between job satisfaction among 315 mental health professionals from the province of Quebec (Canada) and a wide range of variables related to provider characteristics, team characteristics, processes, and emergent states, and organizational culture. We used the Job Satisfaction Survey to assess job satisfaction. Our conceptual framework integrated numerous independent variables adapted from the input-mediator-output-input (IMOI) model and the Integrated Team Effectiveness Model (ITEM). The structural equation model predicted 47% of the variance of job satisfaction. Job satisfaction was associated with eight variables: strong team support, participation in the decision-making process, closer collaboration, fewer conflicts among team members, modest knowledge production (team processes), firm affective commitment, multifocal identification (emergent states) and belonging to the nursing profession (provider characteristics). Team climate had an impact on six job satisfaction variables (team support, knowledge production, conflicts, affective commitment, collaboration, and multifocal identification). Results show that team processes and emergent states were mediators between job satisfaction and team climate. To increase job satisfaction among professionals, health managers need to pursue strategies that foster a positive climate within mental health teams.

  19. Mediation in dyadic data at the level of the dyads: a Structural Equation Modeling approach.

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    Ledermann, Thomas; Macho, Siegfried

    2009-10-01

    An extended version of the Common Fate Model (CFM) is presented to estimate and test mediation in dyadic data. The model can be used for distinguishable dyad members (e.g., heterosexual couples) or indistinguishable dyad members (e.g., homosexual couples) if (a) the variables measure characteristics of the dyadic relationship or shared external influences that affect both partners; if (b) the causal associations between the variables should be analyzed at the dyadic level; and if (c) the measured variables are reliable indicators of the latent variables. To assess mediation using Structural Equation Modeling, a general three-step procedure is suggested. The first is a selection of a good fitting model, the second a test of the direct effects, and the third a test of the mediating effect by means of bootstrapping. The application of the model along with the procedure for assessing mediation is illustrated using data from 184 couples on marital problems, communication, and marital quality. Differences with the Actor-Partner Interdependence Model and the analysis of longitudinal mediation by using the CFM are discussed.

  20. Antiretroviral treatment adherence as a mediating factor between psychosocial variables and HIV viral load.

    Science.gov (United States)

    Attonito, Jennifer; Dévieux, Jessy G; Lerner, Brenda D G; Hospital, Michelle M; Rosenberg, Rhonda

    2014-01-01

    Psychosocial factors may directly impact HIV health measures such as viral load (VL) whether or not patients are taking antiretroviral treatment (ART) consistently. Structural equation modeling plus Baron and Kenny's (1986) four-step approach were used to test a mediated model predicting VL among 246 HIV-infected adults who were on ART. Exogenous variables were social support, barriers to adherence, and stress. Moderators were alcohol use, marijuana use, and neurocognitive impairment. A small positive association between marijuana use and ART adherence approached significance. Only barriers to adherence predicted a decrease in adherence rates and an increase in VL. No other factors were significantly associated with either VL or adherence, and no interaction effects between exogenous variables and moderators were identified. The association between barriers to adherence and VL was partially mediated by ART adherence. Findings provide modest support for a direct link between psychosocial variables and a virologic response to ART. Copyright © 2014 Association of Nurses in AIDS Care. Published by Elsevier Inc. All rights reserved.

  1. A classical regression framework for mediation analysis: fitting one model to estimate mediation effects.

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    Saunders, Christina T; Blume, Jeffrey D

    2017-10-26

    Mediation analysis explores the degree to which an exposure's effect on an outcome is diverted through a mediating variable. We describe a classical regression framework for conducting mediation analyses in which estimates of causal mediation effects and their variance are obtained from the fit of a single regression model. The vector of changes in exposure pathway coefficients, which we named the essential mediation components (EMCs), is used to estimate standard causal mediation effects. Because these effects are often simple functions of the EMCs, an analytical expression for their model-based variance follows directly. Given this formula, it is instructive to revisit the performance of routinely used variance approximations (e.g., delta method and resampling methods). Requiring the fit of only one model reduces the computation time required for complex mediation analyses and permits the use of a rich suite of regression tools that are not easily implemented on a system of three equations, as would be required in the Baron-Kenny framework. Using data from the BRAIN-ICU study, we provide examples to illustrate the advantages of this framework and compare it with the existing approaches. © The Author 2017. Published by Oxford University Press.

  2. Estimation of Causal Mediation Effects for a Dichotomous Outcome in Multiple-Mediator Models using the Mediation Formula

    OpenAIRE

    Wang, Wei; Nelson, Suchitra; Albert, Jeffrey M.

    2013-01-01

    Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets ...

  3. Investigation of Mediational Processes Using Parallel Process Latent Growth Curve Modeling

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    Cheong, JeeWon; MacKinnon, David P.; Khoo, Siek Toon

    2010-01-01

    This study investigated a method to evaluate mediational processes using latent growth curve modeling. The mediator and the outcome measured across multiple time points were viewed as 2 separate parallel processes. The mediational process was defined as the independent variable influencing the growth of the mediator, which, in turn, affected the growth of the outcome. To illustrate modeling procedures, empirical data from a longitudinal drug prevention program, Adolescents Training and Learning to Avoid Steroids, were used. The program effects on the growth of the mediator and the growth of the outcome were examined first in a 2-group structural equation model. The mediational process was then modeled and tested in a parallel process latent growth curve model by relating the prevention program condition, the growth rate factor of the mediator, and the growth rate factor of the outcome. PMID:20157639

  4. The Combined Effects of Measurement Error and Omitting Confounders in the Single-Mediator Model.

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    Fritz, Matthew S; Kenny, David A; MacKinnon, David P

    2016-01-01

    Mediation analysis requires a number of strong assumptions be met in order to make valid causal inferences. Failing to account for violations of these assumptions, such as not modeling measurement error or omitting a common cause of the effects in the model, can bias the parameter estimates of the mediated effect. When the independent variable is perfectly reliable, for example when participants are randomly assigned to levels of treatment, measurement error in the mediator tends to underestimate the mediated effect, while the omission of a confounding variable of the mediator-to-outcome relation tends to overestimate the mediated effect. Violations of these two assumptions often co-occur, however, in which case the mediated effect could be overestimated, underestimated, or even, in very rare circumstances, unbiased. To explore the combined effect of measurement error and omitted confounders in the same model, the effect of each violation on the single-mediator model is first examined individually. Then the combined effect of having measurement error and omitted confounders in the same model is discussed. Throughout, an empirical example is provided to illustrate the effect of violating these assumptions on the mediated effect.

  5. The Combined Effects of Measurement Error and Omitting Confounders in the Single-Mediator Model

    Science.gov (United States)

    Fritz, Matthew S.; Kenny, David A.; MacKinnon, David P.

    2016-01-01

    Mediation analysis requires a number of strong assumptions be met in order to make valid causal inferences. Failing to account for violations of these assumptions, such as not modeling measurement error or omitting a common cause of the effects in the model, can bias the parameter estimates of the mediated effect. When the independent variable is perfectly reliable, for example when participants are randomly assigned to levels of treatment, measurement error in the mediator tends to underestimate the mediated effect, while the omission of a confounding variable of the mediator to outcome relation tends to overestimate the mediated effect. Violations of these two assumptions often co-occur, however, in which case the mediated effect could be overestimated, underestimated, or even, in very rare circumstances, unbiased. In order to explore the combined effect of measurement error and omitted confounders in the same model, the impact of each violation on the single-mediator model is first examined individually. Then the combined effect of having measurement error and omitted confounders in the same model is discussed. Throughout, an empirical example is provided to illustrate the effect of violating these assumptions on the mediated effect. PMID:27739903

  6. Socioeconomic status and Oppositional Defiant Disorder in preschoolers: parenting practices and executive functioning as mediating variables

    OpenAIRE

    Roser eGranero; Roser eGranero; Leonie eLouwaars; Lourdes eEzpeleta; Lourdes eEzpeleta

    2015-01-01

    Objectives. To investigate the mediating mechanisms of oppositional defiant disorder (ODD) in preschoolers through pathways analysis, considering the family socioeconomic status (SES) as the independent variable and the parenting style and the children’s executive functioning (EF) as the mediating factors.Method. Sample included 622 three years-old children from the general population. Multi-informant reports from parents and teachers were analyzed.Results. Structural Equation Modeling showed...

  7. Associated and mediating variables related to quality of life among service users with mental disorders.

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    Fleury, Marie-Josée; Grenier, Guy; Bamvita, Jean-Marie

    2018-02-01

    This study aimed to identify variables associated with quality of life (QoL) and mediating variables among 338 service users with mental disorders in Quebec (Canada). Data were collected using nine standardized questionnaires and participant medical records. Quality of life was assessed with the Satisfaction with Life Domains Scale. Independent variables were organized into a six-block conceptual framework. Using structural equation modeling, associated and mediating variables related to QoL were identified. Lower seriousness of needs was the strongest variable associated with QoL, followed by recovery, greater service continuity, gender (male), adequacy of help received, not living alone, absence of substance use or mood disorders, and higher functional status, in that order. Recovery was the single mediating variable linking lower seriousness of needs, higher service continuity, and reduced alcohol use with QoL. Findings suggest that greater service continuity creates favorable conditions for recovery, reducing seriousness of needs and increasing QoL among service users. Lack of recovery-oriented services may affect QoL among alcohol users, as substance use disorders were associated directly and negatively with QoL. Decision makers and mental health professionals should promote service continuity, and closer collaboration between primary care and specialized services, while supporting recovery-oriented services that encourage service user involvement in their treatment and follow-up. Community-based organizations should aim to reduce the seriousness of needs particularly for female service users and those living alone.

  8. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models.

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    Preacher, Kristopher J; Hayes, Andrew F

    2008-08-01

    Hypotheses involving mediation are common in the behavioral sciences. Mediation exists when a predictor affects a dependent variable indirectly through at least one intervening variable, or mediator. Methods to assess mediation involving multiple simultaneous mediators have received little attention in the methodological literature despite a clear need. We provide an overview of simple and multiple mediation and explore three approaches that can be used to investigate indirect processes, as well as methods for contrasting two or more mediators within a single model. We present an illustrative example, assessing and contrasting potential mediators of the relationship between the helpfulness of socialization agents and job satisfaction. We also provide SAS and SPSS macros, as well as Mplus and LISREL syntax, to facilitate the use of these methods in applications.

  9. The Relationship between Parent-Child Interactions and Prosocial Behavior among Fifth- and Sixth-Grade Students: Gratitude as a Mediating Variable

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    Wu, Ho-Tang; Tseng, Shu-Feng; Wu, Pai-Lu; Chen, Chun-Miao

    2016-01-01

    Parent-child interaction, gratitude and prosocial behavior have a crucial impact on psychological development. According to our literature review, these three variables are positively related to one another. Therefore, the authors created a model that treats parent-child interaction as an exogenous variable, gratitude as a mediating variable, and…

  10. Passion, Trait Self-Control, and Wellbeing: Comparing Two Mediation Models Predicting Wellbeing.

    Science.gov (United States)

    Briki, Walid

    2017-01-01

    Research has found that passion and trait self-control represented key determinants of wellbeing. Yet, no study to date has attempted to investigate the mediating influences of trait self-control and passion for accounting for the relationships between passion, trait self-control, and wellbeing (dependent variable). Using different frameworks, such as the dualistic model of passion and the neo-socioanalytic theory, the present study proposed two mediation models, considering either trait self-control (model 1) or passion (model 2) as the mediating variable. Five hundred nine volunteers from the United States (326 females and 183 males; M age = 31.74, SD age = 11.05, from 18 to 70 years old), who reported being passionate about a specific activity (e.g., fishing, swimming, blogging; M passion = 5.94, SD passion = 0.89), answered questionnaires assessing harmonious and obsessive passion, trait self-control, and wellbeing (measured through hedonic and eudaimonic wellbeing scales). Preliminary analyses revealed that both models were significant ( model 1: absolute GoF = 0.366, relative GoF = 0.971, outer model GoF = 0.997, inner model GoF = 0.973, R 2 = 18.300%, p passion, trait self-control, and wellbeing, and no relationships of obsessive passion with trait self-control and wellbeing. Mediation analyses revealed that trait self-control significantly mediated the relationship between harmonious passion and wellbeing (i.e., partial mediation, VAF = 33.136%). Harmonious passion appeared to significantly mediate the positive effect of trait self-control on wellbeing; however, the size of the mediating effect indicated that (almost) no mediation would take place (i.e., VAF = 11.144%). The present study is the first to examine the relationships between passion, trait self-control, and wellbeing, and supports the view that trait self-control and harmonious passion represent not only adaptive and powerful constructs, but also key determinants of wellbeing. Implications for

  11. Modelling food-web mediated effects of hydrological variability and environmental flows.

    Science.gov (United States)

    Robson, Barbara J; Lester, Rebecca E; Baldwin, Darren S; Bond, Nicholas R; Drouart, Romain; Rolls, Robert J; Ryder, Darren S; Thompson, Ross M

    2017-11-01

    Environmental flows are designed to enhance aquatic ecosystems through a variety of mechanisms; however, to date most attention has been paid to the effects on habitat quality and life-history triggers, especially for fish and vegetation. The effects of environmental flows on food webs have so far received little attention, despite food-web thinking being fundamental to understanding of river ecosystems. Understanding environmental flows in a food-web context can help scientists and policy-makers better understand and manage outcomes of flow alteration and restoration. In this paper, we consider mechanisms by which flow variability can influence and alter food webs, and place these within a conceptual and numerical modelling framework. We also review the strengths and weaknesses of various approaches to modelling the effects of hydrological management on food webs. Although classic bioenergetic models such as Ecopath with Ecosim capture many of the key features required, other approaches, such as biogeochemical ecosystem modelling, end-to-end modelling, population dynamic models, individual-based models, graph theory models, and stock assessment models are also relevant. In many cases, a combination of approaches will be useful. We identify current challenges and new directions in modelling food-web responses to hydrological variability and environmental flow management. These include better integration of food-web and hydraulic models, taking physiologically-based approaches to food quality effects, and better representation of variations in space and time that may create ecosystem control points. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

  12. Bias and Bias Correction in Multi-Site Instrumental Variables Analysis of Heterogeneous Mediator Effects

    Science.gov (United States)

    Reardon, Sean F.; Unlu, Faith; Zhu, Pei; Bloom, Howard

    2013-01-01

    We explore the use of instrumental variables (IV) analysis with a multi-site randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, as assumption known in the instrumental variables literature as the…

  13. The effect analysis of mediation variable of task productivity on the self-efficacy and employees’ performance

    Directory of Open Access Journals (Sweden)

    Annissa Chairum Soebandono

    2016-11-01

    Full Text Available This research was conducted for analyzing the effect of mediating variable that is individual task proactivity as one of the proactivities of behavior towards the relationship between self-efficacy and the employees’ performance in the logistics companies of shipping the goods. It uses convenience sampling, which is a non-probability sampling method for getting the sample of 52 employees. They were divided into two divisions, namely infrastructure and quality assurance. The questionnaire consists of two parts, in which some were assessed by themselves and others that were assessed by the supervisor. They were analyzed using path analysis using analytical tools developed by Hayes, Preacher-Hayes with the simple mediation models. It was found that employees have self-efficacy, individual task proactivity, and relatively high performance, in which individual task proactivity can be a mediating variable on the effect self-efficacy on performance.

  14. Improving quality-of-life outcomes for patients with cancer through mediating effects of depressive symptoms and functional status: a three-path mediation model.

    Science.gov (United States)

    Hsu, Mei-Chi; Tu, Chun-Hsien

    2014-09-01

    To test a hypothetical three-path mediation model evaluating the effects of functional status and depressive symptoms on the relationship between fatigue and quality of life in patients with cancer on the basis of the Theory of Unpleasant Symptoms. Patients with cancer often experience two or more concurrent, interrelated, mutually influential symptoms. Multiple unpleasant symptoms that have been proposed as mediating variables affecting quality of life in a model proposed in recent cancer studies are scanty. This study was a cross-sectional, descriptive, correlational design. Three hundred and twenty-six patients with cancer from oncology clinics were recruited in Taiwan between 2010-2011. Mediation models were tested and confirmed by applying structural modelling using Analysis of Moment Structures and the joint significance test. Fatigue affects patient quality of life directly or indirectly through functional status and depressive symptoms. These two mediating variables exhibited direct effects on quality of life. A path analysis approach revealed that 47·28 and 67·70% of the total effects of functional status and depressive symptoms, respectively, on the quality-of-life mediation models are attributable to 29·6 and 44·7% of the total effects between fatigue and quality of life, which mediated through two mediators, respectively. Quality of life may be enhanced by simultaneously improving physiological and psychological factors. An understanding of mediating effects is valuable in nursing care of patients with cancer, particularly in the early phase of treatment or in newly diagnosed stages I-III or recently treated patients with cancer in different disease stages. © 2013 John Wiley & Sons Ltd.

  15. Bias and Bias Correction in Multisite Instrumental Variables Analysis of Heterogeneous Mediator Effects

    Science.gov (United States)

    Reardon, Sean F.; Unlu, Fatih; Zhu, Pei; Bloom, Howard S.

    2014-01-01

    We explore the use of instrumental variables (IV) analysis with a multisite randomized trial to estimate the effect of a mediating variable on an outcome in cases where it can be assumed that the observed mediator is the only mechanism linking treatment assignment to outcomes, an assumption known in the IV literature as the exclusion restriction.…

  16. Mediator Variables in Headache Research: Methodological Critique and Exemplar Using Self-Efficacy as a Mediator of the Relationship Between Headache Severity and Disability.

    Science.gov (United States)

    Peck, Kelly R; Smitherman, Todd A

    2015-09-01

    Despite advances in headache medicine, there remains little research on process-related variables that mediate relations between headache and outcomes, as well as limited dissemination of optimal statistical methodology for conducting mediation analyses. The present paper thus aims to promote and demonstrate a contemporary approach to mediation analysis as applied to headache. An overview of a contemporary path-analytic approach to mediation analysis is presented, with an empirical exemplar for illustrative purposes. In the exemplar, headache management self-efficacy (HMSE) was proposed as a mediator between headache severity and disability. The sample included 907 young adults (M age = 19.03 [SD = 2.26]; 70.8% female) with primary headache. Direct and indirect effects of headache severity on headache disability through HMSE were assessed using the espoused methods. Pain severity was positively associated with headache disability (β = 2.91, 95% confidence interval [CI; 2.62, 3.19]) and negatively associated with HMSE (β = -3.50, 95% CI [-4.24, -2.76]); HMSE was negatively associated with headache disability (β = 0.07, 95% CI [-0.09, -0.04]). A positive indirect effect of pain severity on disability through HMSE was identified (point estimate = 0.24, 95% CI [0.14, 0.34]); thus, self-efficacy mediated the association between pain severity and disability. The proposed mediation model accounted for 38% of total variance in disability (P headache literature. In one exemplar application, self-efficacy partially accounted for the disability resulting from headache. We advocate for increased attention to intervening variables in headache via dissemination of contemporary mediation analyses. © 2015 American Headache Society.

  17. The mediation proportion: a structural equation approach for estimating the proportion of exposure effect on outcome explained by an intermediate variable

    DEFF Research Database (Denmark)

    Ditlevsen, Susanne; Christensen, Ulla; Lynch, John

    2005-01-01

    It is often of interest to assess how much of the effect of an exposure on a response is mediated through an intermediate variable. However, systematic approaches are lacking, other than assessment of a surrogate marker for the endpoint of a clinical trial. We review a measure of "proportion...... of several intermediate variables. Binary or categorical variables can be included directly through threshold models. We call this measure the mediation proportion, that is, the part of an exposure effect on outcome explained by a third, intermediate variable. Two examples illustrate the approach. The first...... example is a randomized clinical trial of the effects of interferon-alpha on visual acuity in patients with age-related macular degeneration. In this example, the exposure, mediator and response are all binary. The second example is a common problem in social epidemiology-to find the proportion...

  18. VARIABEL LATEN SEBAGAI MODERATOR DAN MEDIATOR DALAM HUBUNGAN KAUSAL

    Directory of Open Access Journals (Sweden)

    I KOMANG GEDE ANTARA

    2014-01-01

    Full Text Available Latent variables are variables that can not be measured directly. In analysis of causal relationship involving three latent variables, one latent variable can be a moderator or mediator variables. Goodness of Fit moderation and mediation model of latent variables is affected by the value of the canonical correlation between moderator/mediator latent variables with the independent latent variables and dependent latent variables. If the value of both canonical correlation is well , so the Goodness of Fit models of mediation is getting better, while the opposite Goodness of Fit models will be better moderation.

  19. VARIABEL LATEN SEBAGAI MODERATOR DAN MEDIATOR DALAM HUBUNGAN KAUSAL

    Directory of Open Access Journals (Sweden)

    I KOMANG GEDE ANTARA

    2013-11-01

    Full Text Available Latent variables are variables that can not be measured directly. In analysis of causal relationship involving three latent variables, one latent variable can be a moderator or mediator variables. Goodness of Fit moderation and mediation model of latent variables is affected by the value of the canonical correlation between moderator/mediator latent variables with the independent latent variables and dependent latent variables. If the value of both canonical correlation is well , so the Goodness of Fit models of mediation is getting better, while the opposite Goodness of Fit models will be better moderation.

  20. Assessing moderated mediation in linear models requires fewer confounding assumptions than assessing mediation.

    Science.gov (United States)

    Loeys, Tom; Talloen, Wouter; Goubert, Liesbet; Moerkerke, Beatrijs; Vansteelandt, Stijn

    2016-11-01

    It is well known from the mediation analysis literature that the identification of direct and indirect effects relies on strong no unmeasured confounding assumptions of no unmeasured confounding. Even in randomized studies the mediator may still be correlated with unobserved prognostic variables that affect the outcome, in which case the mediator's role in the causal process may not be inferred without bias. In the behavioural and social science literature very little attention has been given so far to the causal assumptions required for moderated mediation analysis. In this paper we focus on the index for moderated mediation, which measures by how much the mediated effect is larger or smaller for varying levels of the moderator. We show that in linear models this index can be estimated without bias in the presence of unmeasured common causes of the moderator, mediator and outcome under certain conditions. Importantly, one can thus use the test for moderated mediation to support evidence for mediation under less stringent confounding conditions. We illustrate our findings with data from a randomized experiment assessing the impact of being primed with social deception upon observer responses to others' pain, and from an observational study of individuals who ended a romantic relationship assessing the effect of attachment anxiety during the relationship on mental distress 2 years after the break-up. © 2016 The British Psychological Society.

  1. Parent-adolescent relationship and adolescent internet addiction: A moderated mediation model.

    Science.gov (United States)

    Wang, Wei; Li, Dongping; Li, Xian; Wang, Yanhui; Sun, Wenqiang; Zhao, Liyan; Qiu, Lilan

    2018-09-01

    Substantial research has found that positive parent-adolescent relationship is associated with low levels of adolescent Internet addiction (IA). However, little is known about the mediating and moderating mechanisms underlying this relation. The present study examined a moderated mediation model that included the parent-adolescent relationship (predictor variable), emotion regulation ability (mediator), stressful life events (moderator), and IA (outcome variable) simultaneously. A total of 998 (M age  = 15.15 years, SD = 1.57) Chinese adolescents completed the Parent-Adolescent Relationship Scale, Emotion Regulation Ability Scale, Adolescent Stressful Life Events Scale, and Internet Addiction Diagnostic Questionnaire. After controlling for adolescent gender, age, and family socioeconomic status, results revealed that good parent-adolescent relationship was positively associated with adolescent emotion regulation ability, which in turn was negatively associated with their IA. Moreover, stressful life events moderated the second part of the mediation process. In accordance with the reverse stress-buffering model, the relation between emotion regulation ability and adolescent IA was stronger for adolescents who experienced lower levels of stressful life events. The findings and their implications are discussed and a resilient contextual perspective proposed. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Using structural equation modeling to investigate relationships among ecological variables

    Science.gov (United States)

    Malaeb, Z.A.; Kevin, Summers J.; Pugesek, B.H.

    2000-01-01

    Structural equation modeling is an advanced multivariate statistical process with which a researcher can construct theoretical concepts, test their measurement reliability, hypothesize and test a theory about their relationships, take into account measurement errors, and consider both direct and indirect effects of variables on one another. Latent variables are theoretical concepts that unite phenomena under a single term, e.g., ecosystem health, environmental condition, and pollution (Bollen, 1989). Latent variables are not measured directly but can be expressed in terms of one or more directly measurable variables called indicators. For some researchers, defining, constructing, and examining the validity of latent variables may be the end task of itself. For others, testing hypothesized relationships of latent variables may be of interest. We analyzed the correlation matrix of eleven environmental variables from the U.S. Environmental Protection Agency's (USEPA) Environmental Monitoring and Assessment Program for Estuaries (EMAP-E) using methods of structural equation modeling. We hypothesized and tested a conceptual model to characterize the interdependencies between four latent variables-sediment contamination, natural variability, biodiversity, and growth potential. In particular, we were interested in measuring the direct, indirect, and total effects of sediment contamination and natural variability on biodiversity and growth potential. The model fit the data well and accounted for 81% of the variability in biodiversity and 69% of the variability in growth potential. It revealed a positive total effect of natural variability on growth potential that otherwise would have been judged negative had we not considered indirect effects. That is, natural variability had a negative direct effect on growth potential of magnitude -0.3251 and a positive indirect effect mediated through biodiversity of magnitude 0.4509, yielding a net positive total effect of 0

  3. The mediating role of metacognitive variables in the relationship between Thought-Action Fusion and obsessive-compulsive symptomatology

    Directory of Open Access Journals (Sweden)

    Paula Odriozola-González

    2016-07-01

    Full Text Available Diverse studies support the central role of Thought-Action Fusion (TAF and other metacognitive variables in the understanding of obsessive-compulsive disorder (OCD symptomatology. However, a more detailed study of the involvement of these variables is needed. This article seeks to assess the possible mediating role of the factors of the Metacognitions Questionnaire (MCQ in the relationship between TAF and OCD symptoms both in clinical and non-clinical samples. A cross-sectional design was used in which 120 participants, divided into three groups (two clinical and one non-clinical, completed the questionnaires assessing the constructs of interest. The mediational findings generally supported the proposed mediation model. Specifically, the mediational analyses focused on negative beliefs and the need to control (metacognitive factors of the MCQ showed that MCQ Negative beliefs mediated the effects of TAF-Total and TAF factors (except for the TAF-Moral on OCD symptomatology in the OCD group. The MCQ Need to control was non-significant as a mediator of the relationships between TAF and OCD. However, it was observed that this mediation approached significance, with considerable effect sizes. In the clinical-control group, the analyses showed that MCQ Negative beliefs mediated the effects of TAF-Likelihood-Oneself on OCD symptoms. In the remaining group, neither MCQ Negative beliefs nor MCQ Need to control were found to be significant mediators. It is generally concluded that certain beliefs, such as TAF, can evolve toward more complex metacognitive beliefs, which ultimately lead to the development of OCD symptoms.

  4. Physical frailty, disability, and dynamics in health perceptions: a preliminary mediation model

    Directory of Open Access Journals (Sweden)

    Mulasso A

    2016-03-01

    Full Text Available Anna Mulasso, Mattia Roppolo, Emanuela Rabaglietti Department of Psychology, University of Torino, Torino, Italy Purpose: Frailty is a condition characterized by loss of functional reserve and altered homeostatic capacity. The aging process is related with complex indicators of physiological state. This study aims, with a preliminary mediation model, to reveal the possible role of mediator of health perceptions variability in the relationship between frailty and disability. Patients and methods: A longitudinal study (100 days was performed. Data from 92 institutionalized older adults were used in the analysis. Frailty was assessed in baseline using the Italian version of the Survey of Health, Ageing and Retirement in Europe – Frailty Instrument; health perceptions were assessed on a daily basis by three visual analog scale questions; and disability was measured in baseline and post-test using the Katz Activities of Daily Living questionnaire. The product-of-coefficient mediation approach was used to test direct and indirect effects of frailty. Results: Results showed that daily variability of health perceptions plays the role of mediator between frailty and disability. In all the steps, statistically significant results were found. Conclusion: This preliminary result may indicate that physical frailty increases the variability in health perceptions contributing to disability. Keywords: functional decline, loss of autonomy, variability, health outcomes, dynamic systems

  5. The applied model of imagery use: Examination of moderation and mediation effects.

    Science.gov (United States)

    Koehn, S; Stavrou, N A M; Young, J A; Morris, T

    2016-08-01

    The applied model of mental imagery use proposed an interaction effect between imagery type and imagery ability. This study had two aims: (a) the examination of imagery ability as a moderating variable between imagery type and dispositional flow, and (b) the testing of alternative mediation models. The sample consisted of 367 athletes from Scotland and Australia, who completed the Sport Imagery Questionnaire, Sport Imagery Ability Questionnaire, and Dispositional Flow Scale-2. Hierarchical regression analysis showed direct effects of imagery use and imagery ability on flow, but no significant interaction. Mediation analysis revealed a significant indirect path, indicating a partially mediated relationship (P = 0.002) between imagery use, imagery ability, and flow. Partial mediation was confirmed when the effect of cognitive imagery use and cognitive imagery ability was tested, and a full mediation model was found between motivational imagery use, motivational imagery ability, and flow. The results are discussed in conjunction with potential future research directions on advancing theory and applications. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  6. Best (but oft-forgotten) practices: mediation analysis.

    Science.gov (United States)

    Fairchild, Amanda J; McDaniel, Heather L

    2017-06-01

    This contribution in the "Best (but Oft-Forgotten) Practices" series considers mediation analysis. A mediator (sometimes referred to as an intermediate variable, surrogate endpoint, or intermediate endpoint) is a third variable that explains how or why ≥2 other variables relate in a putative causal pathway. The current article discusses mediation analysis with the ultimate intention of helping nutrition researchers to clarify the rationale for examining mediation, avoid common pitfalls when using the model, and conduct well-informed analyses that can contribute to improving causal inference in evaluations of underlying mechanisms of effects on nutrition-related behavioral and health outcomes. We give specific attention to underevaluated limitations inherent in common approaches to mediation. In addition, we discuss how to conduct a power analysis for mediation models and offer an applied example to demonstrate mediation analysis. Finally, we provide an example write-up of mediation analysis results as a model for applied researchers. © 2017 American Society for Nutrition.

  7. Assessing Mediational Models: Testing and Interval Estimation for Indirect Effects.

    Science.gov (United States)

    Biesanz, Jeremy C; Falk, Carl F; Savalei, Victoria

    2010-08-06

    Theoretical models specifying indirect or mediated effects are common in the social sciences. An indirect effect exists when an independent variable's influence on the dependent variable is mediated through an intervening variable. Classic approaches to assessing such mediational hypotheses ( Baron & Kenny, 1986 ; Sobel, 1982 ) have in recent years been supplemented by computationally intensive methods such as bootstrapping, the distribution of the product methods, and hierarchical Bayesian Markov chain Monte Carlo (MCMC) methods. These different approaches for assessing mediation are illustrated using data from Dunn, Biesanz, Human, and Finn (2007). However, little is known about how these methods perform relative to each other, particularly in more challenging situations, such as with data that are incomplete and/or nonnormal. This article presents an extensive Monte Carlo simulation evaluating a host of approaches for assessing mediation. We examine Type I error rates, power, and coverage. We study normal and nonnormal data as well as complete and incomplete data. In addition, we adapt a method, recently proposed in statistical literature, that does not rely on confidence intervals (CIs) to test the null hypothesis of no indirect effect. The results suggest that the new inferential method-the partial posterior p value-slightly outperforms existing ones in terms of maintaining Type I error rates while maximizing power, especially with incomplete data. Among confidence interval approaches, the bias-corrected accelerated (BC a ) bootstrapping approach often has inflated Type I error rates and inconsistent coverage and is not recommended; In contrast, the bootstrapped percentile confidence interval and the hierarchical Bayesian MCMC method perform best overall, maintaining Type I error rates, exhibiting reasonable power, and producing stable and accurate coverage rates.

  8. Integrating Mediators and Moderators in Research Design

    Science.gov (United States)

    MacKinnon, David P.

    2011-01-01

    The purpose of this article is to describe mediating variables and moderating variables and provide reasons for integrating them in outcome studies. Separate sections describe examples of moderating and mediating variables and the simplest statistical model for investigating each variable. The strengths and limitations of incorporating mediating…

  9. VARIABEL LATEN SEBAGAI MODERATOR DAN MEDIATOR DALAM HUBUNGAN KAUSAL

    OpenAIRE

    I KOMANG GEDE ANTARA; I PUTU EKA NILA KENCANA; KETUT JAYANEGARA

    2014-01-01

    Latent variables are variables that can not be measured directly. In analysis of causal relationship involving three latent variables, one latent variable can be a moderator or mediator variables. Goodness of Fit moderation and mediation model of latent variables is affected by the value of the canonical correlation between moderator/mediator latent variables with the independent latent variables and dependent latent variables. If the value of both canonical correlation is well , so the Good...

  10. Best (but oft-forgotten) practices: mediation analysis12

    Science.gov (United States)

    McDaniel, Heather L

    2017-01-01

    This contribution in the “Best (but Oft-Forgotten) Practices” series considers mediation analysis. A mediator (sometimes referred to as an intermediate variable, surrogate endpoint, or intermediate endpoint) is a third variable that explains how or why ≥2 other variables relate in a putative causal pathway. The current article discusses mediation analysis with the ultimate intention of helping nutrition researchers to clarify the rationale for examining mediation, avoid common pitfalls when using the model, and conduct well-informed analyses that can contribute to improving causal inference in evaluations of underlying mechanisms of effects on nutrition-related behavioral and health outcomes. We give specific attention to underevaluated limitations inherent in common approaches to mediation. In addition, we discuss how to conduct a power analysis for mediation models and offer an applied example to demonstrate mediation analysis. Finally, we provide an example write-up of mediation analysis results as a model for applied researchers. PMID:28446497

  11. Abstract: Inference and Interval Estimation for Indirect Effects With Latent Variable Models.

    Science.gov (United States)

    Falk, Carl F; Biesanz, Jeremy C

    2011-11-30

    Models specifying indirect effects (or mediation) and structural equation modeling are both popular in the social sciences. Yet relatively little research has compared methods that test for indirect effects among latent variables and provided precise estimates of the effectiveness of different methods. This simulation study provides an extensive comparison of methods for constructing confidence intervals and for making inferences about indirect effects with latent variables. We compared the percentile (PC) bootstrap, bias-corrected (BC) bootstrap, bias-corrected accelerated (BC a ) bootstrap, likelihood-based confidence intervals (Neale & Miller, 1997), partial posterior predictive (Biesanz, Falk, and Savalei, 2010), and joint significance tests based on Wald tests or likelihood ratio tests. All models included three reflective latent variables representing the independent, dependent, and mediating variables. The design included the following fully crossed conditions: (a) sample size: 100, 200, and 500; (b) number of indicators per latent variable: 3 versus 5; (c) reliability per set of indicators: .7 versus .9; (d) and 16 different path combinations for the indirect effect (α = 0, .14, .39, or .59; and β = 0, .14, .39, or .59). Simulations were performed using a WestGrid cluster of 1680 3.06GHz Intel Xeon processors running R and OpenMx. Results based on 1,000 replications per cell and 2,000 resamples per bootstrap method indicated that the BC and BC a bootstrap methods have inflated Type I error rates. Likelihood-based confidence intervals and the PC bootstrap emerged as methods that adequately control Type I error and have good coverage rates.

  12. Hydrological models are mediating models

    Science.gov (United States)

    Babel, L. V.; Karssenberg, D.

    2013-08-01

    Despite the increasing role of models in hydrological research and decision-making processes, only few accounts of the nature and function of models exist in hydrology. Earlier considerations have traditionally been conducted while making a clear distinction between physically-based and conceptual models. A new philosophical account, primarily based on the fields of physics and economics, transcends classes of models and scientific disciplines by considering models as "mediators" between theory and observations. The core of this approach lies in identifying models as (1) being only partially dependent on theory and observations, (2) integrating non-deductive elements in their construction, and (3) carrying the role of instruments of scientific enquiry about both theory and the world. The applicability of this approach to hydrology is evaluated in the present article. Three widely used hydrological models, each showing a different degree of apparent physicality, are confronted to the main characteristics of the "mediating models" concept. We argue that irrespective of their kind, hydrological models depend on both theory and observations, rather than merely on one of these two domains. Their construction is additionally involving a large number of miscellaneous, external ingredients, such as past experiences, model objectives, knowledge and preferences of the modeller, as well as hardware and software resources. We show that hydrological models convey the role of instruments in scientific practice by mediating between theory and the world. It results from these considerations that the traditional distinction between physically-based and conceptual models is necessarily too simplistic and refers at best to the stage at which theory and observations are steering model construction. The large variety of ingredients involved in model construction would deserve closer attention, for being rarely explicitly presented in peer-reviewed literature. We believe that devoting

  13. Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models.

    Science.gov (United States)

    Gelfand, Lois A; MacKinnon, David P; DeRubeis, Robert J; Baraldi, Amanda N

    2016-01-01

    Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome-underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

  14. Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models

    Science.gov (United States)

    Gelfand, Lois A.; MacKinnon, David P.; DeRubeis, Robert J.; Baraldi, Amanda N.

    2016-01-01

    Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome—underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results. PMID:27065906

  15. Mediation Analysis with Survival Outcomes: Accelerated Failure Time Versus Proportional Hazards Models

    Directory of Open Access Journals (Sweden)

    Lois A Gelfand

    2016-03-01

    Full Text Available Objective: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH and fully parametric accelerated failure time (AFT approaches for illustration.Method: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively under varied data conditions, some including censoring. A simulated data set illustrates the findings.Results: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome – underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG.Conclusions: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

  16. Applying causal mediation analysis to personality disorder research.

    Science.gov (United States)

    Walters, Glenn D

    2018-01-01

    This article is designed to address fundamental issues in the application of causal mediation analysis to research on personality disorders. Causal mediation analysis is used to identify mechanisms of effect by testing variables as putative links between the independent and dependent variables. As such, it would appear to have relevance to personality disorder research. It is argued that proper implementation of causal mediation analysis requires that investigators take several factors into account. These factors are discussed under 5 headings: variable selection, model specification, significance evaluation, effect size estimation, and sensitivity testing. First, care must be taken when selecting the independent, dependent, mediator, and control variables for a mediation analysis. Some variables make better mediators than others and all variables should be based on reasonably reliable indicators. Second, the mediation model needs to be properly specified. This requires that the data for the analysis be prospectively or historically ordered and possess proper causal direction. Third, it is imperative that the significance of the identified pathways be established, preferably with a nonparametric bootstrap resampling approach. Fourth, effect size estimates should be computed or competing pathways compared. Finally, investigators employing the mediation method are advised to perform a sensitivity analysis. Additional topics covered in this article include parallel and serial multiple mediation designs, moderation, and the relationship between mediation and moderation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  17. Testing a multiple mediator model of the effect of childhood sexual abuse on adolescent sexual victimization.

    Science.gov (United States)

    Bramsen, Rikke H; Lasgaard, Mathias; Koss, Mary P; Shevlin, Mark; Elklit, Ask; Banner, Jytte

    2013-01-01

    The present study modeled the direct relationship between child sexual abuse (CSA) and adolescent peer-to-peer sexual victimization (APSV) and the mediated effect via variables representing the number of sexual partners, sexual risk behavior, and signaling sexual boundaries. A cross-sectional study on the effect of CSA on APSV was conducted, utilizing a multiple mediator model. Mediated and direct effects in the model were estimated employing Mplus using bootstrapped percentile based confidence intervals to test for significance of mediated effects. The study employed 327 Danish female adolescents with a mean age of 14.9 years (SD = 0.5). The estimates from the mediational model indicated full mediation of the effect of CSA on APSV via number of sexual partners and sexual risk behavior. The current study suggests that the link between CSA and APSV was mediated by sexual behaviors specifically pertaining to situations of social peer interaction, rather than directly on prior experiences of sexual victimization. The present study identifies a modifiable target area for intervention to reduce adolescent sexual revictimization. © 2013 American Orthopsychiatric Association.

  18. Socioeconomic status and oppositional defiant disorder in preschoolers: parenting practices and executive functioning as mediating variables.

    Science.gov (United States)

    Granero, Roser; Louwaars, Leonie; Ezpeleta, Lourdes

    2015-01-01

    To investigate the mediating mechanisms of oppositional defiant disorder (ODD) in preschoolers through pathways analysis, considering the family socioeconomic status (SES) as the independent variable and the parenting style and the children's executive functioning (EF) as the mediating factors. The sample included 622 three-year-old children from the general population. Multi-informant reports from parents and teachers were analyzed. Structural Equation Modeling showed that the associations between SES, EF, parenting style and ODD levels differed by children's gender: (a) for girls, the association of low SES and high ODD scores was partially mediated by difficulties in EF inhibition, and parenting practices defined by corporal punishment and inconsistent discipline obtained a quasi-significant indirect effect into the association between SES and ODD; (b) for boys, SES and EF (inhibition and emotional control) had a direct effect on ODD with no mediation. SES seems a good indicator to identify children at high-risk for prevention and intervention programs for ODD. Girls with ODD in families of low SES may particularly benefit from parent training practices and training in inhibition control.

  19. Metacognition as a Mediating Variable Between Neurocognition and Functional Outcome in First Episode Psychosis.

    Science.gov (United States)

    Davies, Geoff; Fowler, David; Greenwood, Kathryn

    2017-07-01

    Neurocognitive and functional outcome deficits have long been acknowledged in schizophrenia and neurocognition has been found to account for functional disability to a greater extent than psychopathology. Much of the variance in functional outcome however still remains unexplained and metacognition may mediate the relationship between neurocognition, functional capacity, and self-reported social and occupational function. Eighty first episode psychosis participants were recruited and completed measures of neurocognition (memory, executive function, and intelligence quotient), metacognition (Beck Cognitive Insight Scale, Metacognitive Awareness Interview), psychopathology (PANSS), and both functional capacity (UPSA) and real-life social and occupational function (The Time Use Survey). Path analyses investigated the relationships between variables through structural equation modeling. A series of path models demonstrated that metacognition partially mediates the relationship between neurocognition and functional capacity, and fully mediates the relationship between functional capacity and social and occupational function. The present study findings identify that metacognition may be critical to translating cognitive and functional skills into real-world contexts, and this relationship is found at early stages of illness. Understanding how individuals translate cognitive and functional skills into the real-world (the competence-performance gap) may offer valuable guidance to intervention programs. This finding is important to models of recovery as it suggests that intervention programs that focus on enhancing metacognition abilities may have a greater impact than traditional rehabilitation programs focusing on cognitive abilities, on social and occupational outcomes. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com

  20. A Comparison of Methods to Test Mediation and Other Intervening Variable Effects

    Science.gov (United States)

    MacKinnon, David P.; Lockwood, Chondra M.; Hoffman, Jeanne M.; West, Stephen G.; Sheets, Virgil

    2010-01-01

    A Monte Carlo study compared 14 methods to test the statistical significance of the intervening variable effect. An intervening variable (mediator) transmits the effect of an independent variable to a dependent variable. The commonly used R. M. Baron and D. A. Kenny (1986) approach has low statistical power. Two methods based on the distribution of the product and 2 difference-in-coefficients methods have the most accurate Type I error rates and greatest statistical power except in 1 important case in which Type I error rates are too high. The best balance of Type I error and statistical power across all cases is the test of the joint significance of the two effects comprising the intervening variable effect. PMID:11928892

  1. Exposure to family violence and attachment styles as predictors of dating violence perpetration among men and women: a mediational model.

    Science.gov (United States)

    Lee, Mary; Reese-Weber, Marla; Kahn, Jeffrey H

    2014-01-01

    This study examined a multiple mediator model explaining how sibling perpetration and one's attachment style mediate the relation between parent-to-child victimization and dating violence perpetration. A sample of undergraduate students (n = 392 women, n = 89 men) completed measures of the aforementioned variables on an Internet survey. For men, path analyses found no mediation; parent-to-child victimization had a direct association with dating violence perpetration, no association was found between sibling perpetration and dating violence perpetration, and attachment anxiety, but not attachment avoidance, was positively associated with dating violence perpetration for men. For women, the hypothesized mediation model was supported; parent-to-child victimization had a direct association with dating violence perpetration, and sibling perpetration and attachment anxiety served as mediating variables. Attachment avoidance was not associated with dating violence perpetration for women. Implications for future research and clinical practice are discussed.

  2. The integrated model of sport confidence: a canonical correlation and mediational analysis.

    Science.gov (United States)

    Koehn, Stefan; Pearce, Alan J; Morris, Tony

    2013-12-01

    The main purpose of the study was to examine crucial parts of Vealey's (2001) integrated framework hypothesizing that sport confidence is a mediating variable between sources of sport confidence (including achievement, self-regulation, and social climate) and athletes' affect in competition. The sample consisted of 386 athletes, who completed the Sources of Sport Confidence Questionnaire, Trait Sport Confidence Inventory, and Dispositional Flow Scale-2. Canonical correlation analysis revealed a confidence-achievement dimension underlying flow. Bias-corrected bootstrap confidence intervals in AMOS 20.0 were used in examining mediation effects between source domains and dispositional flow. Results showed that sport confidence partially mediated the relationship between achievement and self-regulation domains and flow, whereas no significant mediation was found for social climate. On a subscale level, full mediation models emerged for achievement and flow dimensions of challenge-skills balance, clear goals, and concentration on the task at hand.

  3. Mediational Role of Age of Onset in Gambling Disorder, a Path Modeling Analysis.

    Science.gov (United States)

    Jiménez-Murcia, Susana; Granero, Roser; Tárrega, Salomé; Angulo, Ariadna; Fernández-Aranda, Fernando; Arcelus, Jon; Fagundo, Ana B; Aymamí, Neus; Moragas, Laura; Sauvaget, Anne; Grall-Bronnec, Marie; Gómez-Peña, Mónica; Menchón, José M

    2016-03-01

    The aim of the study is to assess a mediational pathway, which includes patients' sex, personality traits, age of onset of gambling disorder (GD) and gambling-related variables. The South Oaks Gambling Screen, the Symptom Checklist (SCL-90-R) and the Temperament and Character Inventory-R were administered to a large sample of 1632 outpatients attending a specialized outpatient GD unit. Sociodemographic variables were also recorded. A Structural Equation Model was adjusted to assess the pathway. Age of onset mediated between personality profile (novelty seeking and self-transcendence) and GD severity and depression symptoms (measured by SCL-90-R). Sex had a direct effect on GD onset and depression symptoms: men initiated the GD earlier and reported fewer depression symptoms. Age of onset is a mediating variable between sex, personality traits, GD severity and depression symptoms. These empirical results provide new evidence about the underlying etiological process of dysfunctional behaviors related to gambling, and may help to guide the development of more effective treatment and prevention programs aimed at high-risk groups such as young men with high levels of novelty seeking and self-transcendence.

  4. Can the measurement of brachial artery flow-mediated dilation be applied to the acute exercise model?

    Directory of Open Access Journals (Sweden)

    Harris Ryan A

    2007-11-01

    Full Text Available Abstract The measurement of flow-mediated dilation using high-resolution ultrasound has been utilized extensively in interventional trials evaluating the salutary effect of drugs and lifestyle modifications (i.e. diet or exercise training on endothelial function; however, until recently researchers have not used flow-mediated dilation to examine the role of a single bout of exercise on vascular function. Utilizing the acute exercise model can be advantageous as it allows for an efficient manipulation of exercise variables (i.e. mode, intensity, duration, etc. and permits greater experimental control of confounding variables. Given that the application of flow-mediated dilation in the acute exercise paradigm is expanding, the purpose of this review is to discuss methodological and physiological factors pertinent to flow-mediated dilation in the context of acute exercise. Although the scientific rationale for evaluating endothelial function in response to acute exercise is sound, few concerns warrant attention when interpreting flow-mediated dilation data following acute exercise. The following questions will be addressed in the present review: Does the measurement of flow-mediated dilation influence subsequent serial measures of flow-mediated dilation? Do we need to account for diurnal variation? Is there an optimal time to measure post-exercise flow-mediated dilation? Is the post-exercise flow-mediated dilation reproducible? How is flow-mediated dilation interpreted considering the hemodynamic and sympathetic changes associated with acute exercise? Can the measurement of endothelial-independent dilation affect the exercise? Evidence exists to support the methodological appropriateness for employing flow-mediated dilation in the acute exercise model; however, further research is warranted to clarify its interpretation following acute exercise.

  5. Variable importance in latent variable regression models

    NARCIS (Netherlands)

    Kvalheim, O.M.; Arneberg, R.; Bleie, O.; Rajalahti, T.; Smilde, A.K.; Westerhuis, J.A.

    2014-01-01

    The quality and practical usefulness of a regression model are a function of both interpretability and prediction performance. This work presents some new graphical tools for improved interpretation of latent variable regression models that can also assist in improved algorithms for variable

  6. Socioeconomic status and Oppositional Defiant Disorder in preschoolers: parenting practices and executive functioning as mediating variables

    Directory of Open Access Journals (Sweden)

    Roser eGranero

    2015-09-01

    Full Text Available Objectives. To investigate the mediating mechanisms of oppositional defiant disorder (ODD in preschoolers through pathways analysis, considering the family socioeconomic status (SES as the independent variable and the parenting style and the children’s executive functioning (EF as the mediating factors.Method. Sample included 622 three years-old children from the general population. Multi-informant reports from parents and teachers were analyzed.Results. Structural Equation Modeling showed that children’s gender achieved a moderating role into the pathways valuing the underlying process between SES, EF, parenting style and ODD levels: a for girls, the association of low SES and high ODD scores was mediated by parenting practices (punishment and inconsistent discipline and by difficulties in EF inhibition, and a direct predictive effect on ODD level was achieved for SES, punishment and inconsistence in rearing style and inhibition; b for boys, SES and EF (inhibition and emotional control had a direct effect on ODD with no mediation.Conclusion. SES seems a good indicator to identify at high-risk children for prevention and intervention programs for ODD. Girls with ODD in families of low SES may particularly benefit from parent training practices and training in inhibition control.

  7. What carries a mediation process? Configural analysis of mediation.

    Science.gov (United States)

    von Eye, Alexander; Mun, Eun Young; Mair, Patrick

    2009-09-01

    Mediation is a process that links a predictor and a criterion via a mediator variable. Mediation can be full or partial. This well-established definition operates at the level of variables even if they are categorical. In this article, two new approaches to the analysis of mediation are proposed. Both of these approaches focus on the analysis of categorical variables. The first involves mediation analysis at the level of configurations instead of variables. Thus, mediation can be incorporated into the arsenal of methods of analysis for person-oriented research. Second, it is proposed that Configural Frequency Analysis (CFA) can be used for both exploration and confirmation of mediation relationships among categorical variables. The implications of using CFA are first that mediation hypotheses can be tested at the level of individual configurations instead of variables. Second, this approach leaves the door open for different types of mediation processes to exist within the same set. Using a data example, it is illustrated that aggregate-level analysis can overlook mediation processes that operate at the level of individual configurations.

  8. The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations.

    Science.gov (United States)

    Baron, R M; Kenny, D A

    1986-12-01

    In this article, we attempt to distinguish between the properties of moderator and mediator variables at a number of levels. First, we seek to make theorists and researchers aware of the importance of not using the terms moderator and mediator interchangeably by carefully elaborating, both conceptually and strategically, the many ways in which moderators and mediators differ. We then go beyond this largely pedagogical function and delineate the conceptual and strategic implications of making use of such distinctions with regard to a wide range of phenomena, including control and stress, attitudes, and personality traits. We also provide a specific compendium of analytic procedures appropriate for making the most effective use of the moderator and mediator distinction, both separately and in terms of a broader causal system that includes both moderators and mediators.

  9. Exploring associations between parental and peer variables, personal variables and physical activity among adolescents: a mediation analysis.

    Science.gov (United States)

    Verloigne, Maïté; Veitch, Jenny; Carver, Alison; Salmon, Jo; Cardon, Greet; De Bourdeaudhuij, Ilse; Timperio, Anna

    2014-09-18

    This study aimed to investigate how parental and peer variables are associated with moderate- to-vigorous intensity physical activity (MVPA) on week- and weekend days among Australian adolescents (13-15 y), and whether perceived internal barriers (e.g. lack of time), external barriers (e.g. lack of others to be physically active with) and self-efficacy mediated these associations. Cross-sectional data were drawn from the Health, Eating and Play Study, conducted in Melbourne, Australia. Adolescents (mean age = 14.11 ± 0.59 years, 51% girls) and one of their parents completed a questionnaire and adolescents wore an ActiGraph accelerometer for a week (n = 134). Mediating effects of perceived barriers and self-efficacy were tested using MacKinnon's product-of-coefficients test based on multilevel linear regression analyses. Parental logistic support was positively related to MVPA on weekdays (τ = 0.035) and weekend days (τ = 0.078), peer interest (τ =0.036) was positively related to MVPA on weekdays, and parental control (τ = -0.056) and parental concern (τ = -0.180) were inversely related to MVPA on weekdays. Internal barriers significantly mediated the association between parental logistic support and MVPA on weekdays (42.9% proportion mediated). Self-efficacy and external barriers did not mediate any association. Interventions aiming to increase adolescents' MVPA should involve parents, as parental support may influence MVPA on weekdays by reducing adolescents' perceived internal barriers. Longitudinal and experimental research is needed to confirm these findings and to investigate other personal mediators.

  10. Spatio-temporal variability in western Baltic cod early life stage survival mediated by egg buoyancy, hydrography and hydrodynamics

    DEFF Research Database (Denmark)

    Hinrichsen, H-H.; Hüssy, K.; Huwer, B.

    2012-01-01

    Spatio-temporal variability in western Baltic cod early life stage survival mediated by egg buoyancy, hydrography and hydrodynamics. – ICES Journal of Marine Science, 69: 1744–1752.To disentangle the effects of different drivers on recruitment variability of marine fish, a spatially and temporally...... explicit understanding of both the spawning stock size and the early life stage dynamics is required. The objectives of this study are to assess the transport of western Baltic cod early life stages as well as the variability in environmentally-mediated survival along drift routes in relation to both...

  11. An agent-based model of cellular dynamics and circadian variability in human endotoxemia.

    Directory of Open Access Journals (Sweden)

    Tung T Nguyen

    Full Text Available As cellular variability and circadian rhythmicity play critical roles in immune and inflammatory responses, we present in this study an agent-based model of human endotoxemia to examine the interplay between circadian controls, cellular variability and stochastic dynamics of inflammatory cytokines. The model is qualitatively validated by its ability to reproduce circadian dynamics of inflammatory mediators and critical inflammatory responses after endotoxin administration in vivo. Novel computational concepts are proposed to characterize the cellular variability and synchronization of inflammatory cytokines in a population of heterogeneous leukocytes. Our results suggest that there is a decrease in cell-to-cell variability of inflammatory cytokines while their synchronization is increased after endotoxin challenge. Model parameters that are responsible for IκB production stimulated by NFκB activation and for the production of anti-inflammatory cytokines have large impacts on system behaviors. Additionally, examining time-dependent systemic responses revealed that the system is least vulnerable to endotoxin in the early morning and most vulnerable around midnight. Although much remains to be explored, proposed computational concepts and the model we have pioneered will provide important insights for future investigations and extensions, especially for single-cell studies to discover how cellular variability contributes to clinical implications.

  12. Adversity and persecutory ideation: A moderated mediational model.

    Science.gov (United States)

    Valiente, Carmen; Espinosa, Regina; Villavicencio, Patricia; Cantero, Dolores; Fuentenebro, Filiberto

    2017-12-01

    Adversity has been identified as an important factor in models of psychopathology and can help in understanding persecutory ideation, although potential moderators and mediators for adult psychopathology have not been sufficiently examined. Experiential avoidance (EA) and Self-esteem (SE) are relevant factors to understand how adversity leads to persecutory ideation. This study hypothesized that adversity would be associated with persecutory ideation through heightened EA, and that this association would be strengthened in individuals with a discrepant high SE. Participants with persecutory ideation (n = 52), with depression (n = 35) and healthy controls (n = 51) were assessed with the Trauma History Screen, the Paranoia and Deservedness Scale, and the Beck Depression Inventory. A SE discrepancy index was calculated subtracting the normalized explicit SE score from the normalized implicit SE score (measured by a version of a Go/No-go association task). Our analysis revealed that adversity was associated with higher levels of paranoia and was mediated by EA. In addition, we found that the relationship between adversity and EA was moderated by SE discrepancy. Identification of moderating and mediating variables allows for increased understanding of persecutory ideation and the processes that should be targeted in the course of recovery. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Impact of role models in business creation, mediators and gender effects; Incidencia de los modelos de referencia en la creacion de empresas. Efectos mediadores y de genero

    Energy Technology Data Exchange (ETDEWEB)

    Justo, R.; Diaz, C.

    2012-11-01

    Knowing other entrepreneurs contributes to the success of start-ups, serving among others as role models. We argue that this relationship may be mediated by perceptual variables such as entrepreneurial self-efficacy and alert, especially in the case of female entrepreneurs. Previous studies suggest that the benefits of a same sex role model are larger for women. Using survey data from GEM Spain, our study confirms that the effect of knowing other business-owner is mediated by perception variables, although self-efficacy's mediation is only established in the case of women. Sex of the role model is not crucial in any case. (Author) 67 refs.

  14. Adaptation of endothelial cells to physiologically-modeled, variable shear stress.

    Directory of Open Access Journals (Sweden)

    Joseph S Uzarski

    Full Text Available Endothelial cell (EC function is mediated by variable hemodynamic shear stress patterns at the vascular wall, where complex shear stress profiles directly correlate with blood flow conditions that vary temporally based on metabolic demand. The interactions of these more complex and variable shear fields with EC have not been represented in hemodynamic flow models. We hypothesized that EC exposed to pulsatile shear stress that changes in magnitude and duration, modeled directly from real-time physiological variations in heart rate, would elicit phenotypic changes as relevant to their critical roles in thrombosis, hemostasis, and inflammation. Here we designed a physiological flow (PF model based on short-term temporal changes in blood flow observed in vivo and compared it to static culture and steady flow (SF at a fixed pulse frequency of 1.3 Hz. Results show significant changes in gene regulation as a function of temporally variable flow, indicating a reduced wound phenotype more representative of quiescence. EC cultured under PF exhibited significantly higher endothelial nitric oxide synthase (eNOS activity (PF: 176.0±11.9 nmol/10(5 EC; SF: 115.0±12.5 nmol/10(5 EC, p = 0.002 and lower TNF-a-induced HL-60 leukocyte adhesion (PF: 37±6 HL-60 cells/mm(2; SF: 111±18 HL-60/mm(2, p = 0.003 than cells cultured under SF which is consistent with a more quiescent anti-inflammatory and anti-thrombotic phenotype. In vitro models have become increasingly adept at mimicking natural physiology and in doing so have clarified the importance of both chemical and physical cues that drive cell function. These data illustrate that the variability in metabolic demand and subsequent changes in perfusion resulting in constantly variable shear stress plays a key role in EC function that has not previously been described.

  15. Statistical properties of four effect-size measures for mediation models.

    Science.gov (United States)

    Miočević, Milica; O'Rourke, Holly P; MacKinnon, David P; Brown, Hendricks C

    2018-02-01

    This project examined the performance of classical and Bayesian estimators of four effect size measures for the indirect effect in a single-mediator model and a two-mediator model. Compared to the proportion and ratio mediation effect sizes, standardized mediation effect-size measures were relatively unbiased and efficient in the single-mediator model and the two-mediator model. Percentile and bias-corrected bootstrap interval estimates of ab/s Y , and ab(s X )/s Y in the single-mediator model outperformed interval estimates of the proportion and ratio effect sizes in terms of power, Type I error rate, coverage, imbalance, and interval width. For the two-mediator model, standardized effect-size measures were superior to the proportion and ratio effect-size measures. Furthermore, it was found that Bayesian point and interval summaries of posterior distributions of standardized effect-size measures reduced excessive relative bias for certain parameter combinations. The standardized effect-size measures are the best effect-size measures for quantifying mediated effects.

  16. Developing models of how cognitive improvements change functioning: Mediation, moderation and moderated mediation

    Science.gov (United States)

    Wykes, Til; Reeder, Clare; Huddy, Vyv; Taylor, Rumina; Wood, Helen; Ghirasim, Natalia; Kontis, Dimitrios; Landau, Sabine

    2012-01-01

    Background Cognitive remediation (CRT) affects functioning but the extent and type of cognitive improvements necessary are unknown. Aim To develop and test models of how cognitive improvement transfers to work behaviour using the data from a current service. Method Participants (N49) with a support worker and a paid or voluntary job were offered CRT in a Phase 2 single group design with three assessments: baseline, post therapy and follow-up. Working memory, cognitive flexibility, planning and work outcomes were assessed. Results Three models were tested (mediation — cognitive improvements drive functioning improvement; moderation — post treatment cognitive level affects the impact of CRT on functioning; moderated mediation — cognition drives functioning improvements only after a certain level is achieved). There was evidence of mediation (planning improvement associated with improved work quality). There was no evidence that cognitive flexibility (total Wisconsin Card Sorting Test errors) and working memory (Wechsler Adult Intelligence Scale III digit span) mediated work functioning despite significant effects. There was some evidence of moderated mediation for planning improvement if participants had poorer memory and/or made fewer WCST errors. The total CRT effect on work quality was d = 0.55, but the indirect (planning-mediated CRT effect) was d = 0.082 Conclusion Planning improvements led to better work quality but only accounted for a small proportion of the total effect on work outcome. Other specific and non-specific effects of CRT and the work programme are likely to account for some of the remaining effect. This is the first time complex models have been tested and future Phase 3 studies need to further test mediation and moderated mediation models. PMID:22503640

  17. Demonstration and evaluation of a method for assessing mediated moderation.

    Science.gov (United States)

    Morgan-Lopez, Antonio A; MacKinnon, David P

    2006-02-01

    Mediated moderation occurs when the interaction between two variables affects a mediator, which then affects a dependent variable. In this article, we describe the mediated moderation model and evaluate it with a statistical simulation using an adaptation of product-of-coefficients methods to assess mediation. We also demonstrate the use of this method with a substantive example from the adolescent tobacco literature. In the simulation, relative bias (RB) in point estimates and standard errors did not exceed problematic levels of +/- 10% although systematic variability in RB was accounted for by parameter size, sample size, and nonzero direct effects. Power to detect mediated moderation effects appears to be severely compromised under one particular combination of conditions: when the component variables that make up the interaction terms are correlated and partial mediated moderation exists. Implications for the estimation of mediated moderation effects in experimental and nonexperimental research are discussed.

  18. The Relationship Among School Safety, School Liking, and Students' Self-Esteem: Based on a Multilevel Mediation Model.

    Science.gov (United States)

    Zhang, Xinghui; Xuan, Xin; Chen, Fumei; Zhang, Cai; Luo, Yuhan; Wang, Yun

    2016-03-01

    Perceptions of school safety have an important effect on students' development. Based on the model of "context-process-outcomes," we examined school safety as a context variable to explore how school safety at the school level affected students' self-esteem. We used hierarchical linear modeling to examine the link between school safety at the school level and students' self-esteem, including school liking as a mediator. The data were from the National Children's Study of China (NCSC), in which 6618 fourth- to fifth-grade students in 79 schools were recruited from 100 counties in 31 provinces in China. Multilevel mediation analyses showed that the positive relationship between school safety at the school level and self-esteem was partially mediated by school liking, controlling for demographics at both student and school levels. Furthermore, a sex difference existed in the multilevel mediation model. For boys, school liking fully mediated the relationship between school safety at the school level and self-esteem. However, school liking partially mediated the relationship between school safety at the school level and self-esteem among girls. School safety should receive increasing attention from policymakers because of its impact on students' self-esteem. © 2016, American School Health Association.

  19. Current Directions in Mediation Analysis

    Science.gov (United States)

    MacKinnon, David P.; Fairchild, Amanda J.

    2010-01-01

    Mediating variables continue to play an important role in psychological theory and research. A mediating variable transmits the effect of an antecedent variable on to a dependent variable, thereby providing more detailed understanding of relations among variables. Methods to assess mediation have been an active area of research for the last two decades. This paper describes the current state of methods to investigate mediating variables. PMID:20157637

  20. Current Directions in Mediation Analysis

    OpenAIRE

    MacKinnon, David P.; Fairchild, Amanda J.

    2009-01-01

    Mediating variables continue to play an important role in psychological theory and research. A mediating variable transmits the effect of an antecedent variable on to a dependent variable, thereby providing more detailed understanding of relations among variables. Methods to assess mediation have been an active area of research for the last two decades. This paper describes the current state of methods to investigate mediating variables.

  1. Causal Models for Mediation Analysis: An Introduction to Structural Mean Models.

    Science.gov (United States)

    Zheng, Cheng; Atkins, David C; Zhou, Xiao-Hua; Rhew, Isaac C

    2015-01-01

    Mediation analyses are critical to understanding why behavioral interventions work. To yield a causal interpretation, common mediation approaches must make an assumption of "sequential ignorability." The current article describes an alternative approach to causal mediation called structural mean models (SMMs). A specific SMM called a rank-preserving model (RPM) is introduced in the context of an applied example. Particular attention is given to the assumptions of both approaches to mediation. Applying both mediation approaches to the college student drinking data yield notable differences in the magnitude of effects. Simulated examples reveal instances in which the traditional approach can yield strongly biased results, whereas the RPM approach remains unbiased in these cases. At the same time, the RPM approach has its own assumptions that must be met for correct inference, such as the existence of a covariate that strongly moderates the effect of the intervention on the mediator and no unmeasured confounders that also serve as a moderator of the effect of the intervention or the mediator on the outcome. The RPM approach to mediation offers an alternative way to perform mediation analysis when there may be unmeasured confounders.

  2. The Bensberg Mediation Model

    Directory of Open Access Journals (Sweden)

    Raluca - Marilena Mihalcioiu

    2011-05-01

    Full Text Available The basis of the conflict through the mediation represents the objectives and procedures ofmediation, mediation of a conflict. The conflict will not be disclosed to others, but the parties will be creditedthe authority to resolve the conflict, the conflict among themselves with the help of a mediator. The disputeshould be resolved by the parties with help of a third party. The parties in conflict (it may be several personsare jointly responsible for the solution. They seek together a way that leads to long-term settlement of theconflict. The assumption of responsibility in this process strengthens the confidence and the importance oftheir decision. Important is that losers usually have no peace, because they are out for revenge. Winners don’tneed peace. If both parties lose, remains disappointing, with the understanding of which the conflict isresolved, will understand each other better developed. Reconciliation is therefore a longer-term goal.Conflicts also help to clarify roles. The paper presents Bensberg Model of Mediation, because this isdeveloped as a win win solution and his possible implementation in Romanian schools.

  3. Cross-Sectional Analysis of Longitudinal Mediation Processes.

    Science.gov (United States)

    O'Laughlin, Kristine D; Martin, Monica J; Ferrer, Emilio

    2018-01-01

    Statistical mediation analysis can help to identify and explain the mechanisms behind psychological processes. Examining a set of variables for mediation effects is a ubiquitous process in the social sciences literature; however, despite evidence suggesting that cross-sectional data can misrepresent the mediation of longitudinal processes, cross-sectional analyses continue to be used in this manner. Alternative longitudinal mediation models, including those rooted in a structural equation modeling framework (cross-lagged panel, latent growth curve, and latent difference score models) are currently available and may provide a better representation of mediation processes for longitudinal data. The purpose of this paper is twofold: first, we provide a comparison of cross-sectional and longitudinal mediation models; second, we advocate using models to evaluate mediation effects that capture the temporal sequence of the process under study. Two separate empirical examples are presented to illustrate differences in the conclusions drawn from cross-sectional and longitudinal mediation analyses. Findings from these examples yielded substantial differences in interpretations between the cross-sectional and longitudinal mediation models considered here. Based on these observations, researchers should use caution when attempting to use cross-sectional data in place of longitudinal data for mediation analyses.

  4. A mediational model of PTSD in World War II veterans exposed to mustard gas.

    Science.gov (United States)

    Jankowski, M Kay; Schnurr, Paula P; Adams, Gary A; Green, Bonnie L; Ford, Julian D; Friedman, Matthew J

    2004-08-01

    Structural equation modeling (SEM) was used to examine associations among trauma-related contextual factors, initial psychological reactions, social support, and subsequent disclosure on posttraumatic stress disorder (PTSD) symptoms in a sample of World War II (WWII) veterans exposed to mustard gas (N = 305). A structural model suggested that initial psychological reaction mediated the relationship between variables related to the context of mustard gas exposure and severity of PTSD symptoms 50 years later. Unexpectedly, social support appeared to be positively related to PTSD symptoms, and not related to the contextual variables or initial psychological reactions. These findings contribute to our understanding of PTSD in older veterans, and have relevance for early intervention services to prevent PTSD among those at risk for exposure to toxic agents.

  5. Moderation and Mediation in Structural Equation Modeling: Applications for Early Intervention Research

    Science.gov (United States)

    Hopwood, Christopher J.

    2007-01-01

    Second-generation early intervention research typically involves the specification of multivariate relations between interventions, outcomes, and other variables. Moderation and mediation involve variables or sets of variables that influence relations between interventions and outcomes. Following the framework of Baron and Kenny's (1986) seminal…

  6. mma: An R Package for Mediation Analysis with Multiple Mediators

    OpenAIRE

    Qingzhao Yu; Bin Li

    2017-01-01

    Mediation refers to the effect transmitted by mediators that intervene in the relationship between an exposure and a response variable. Mediation analysis has been broadly studied in many fields. However, it remains a challenge for researchers to consider complicated associations among variables and to differentiate individual effects from multiple mediators. [1] proposed general definitions of mediation effects that were adaptable to all different types of response (categorical or continuous...

  7. Nonlinear Predictive Models for Multiple Mediation Analysis: With an Application to Explore Ethnic Disparities in Anxiety and Depression Among Cancer Survivors.

    Science.gov (United States)

    Yu, Qingzhao; Medeiros, Kaelen L; Wu, Xiaocheng; Jensen, Roxanne E

    2018-04-02

    Mediation analysis allows the examination of effects of a third variable (mediator/confounder) in the causal pathway between an exposure and an outcome. The general multiple mediation analysis method (MMA), proposed by Yu et al., improves traditional methods (e.g., estimation of natural and controlled direct effects) to enable consideration of multiple mediators/confounders simultaneously and the use of linear and nonlinear predictive models for estimating mediation/confounding effects. Previous studies find that compared with non-Hispanic cancer survivors, Hispanic survivors are more likely to endure anxiety and depression after cancer diagnoses. In this paper, we applied MMA on MY-Health study to identify mediators/confounders and quantify the indirect effect of each identified mediator/confounder in explaining ethnic disparities in anxiety and depression among cancer survivors who enrolled in the study. We considered a number of socio-demographic variables, tumor characteristics, and treatment factors as potential mediators/confounders and found that most of the ethnic differences in anxiety or depression between Hispanic and non-Hispanic white cancer survivors were explained by younger diagnosis age, lower education level, lower proportions of employment, less likely of being born in the USA, less insurance, and less social support among Hispanic patients.

  8. Depression and pain: testing of serial multiple mediators.

    Science.gov (United States)

    Wongpakaran, Tinakon; Wongpakaran, Nahathai; Tanchakvaranont, Sitthinant; Bookkamana, Putipong; Pinyopornpanish, Manee; Wannarit, Kamonporn; Satthapisit, Sirina; Nakawiro, Daochompu; Hiranyatheb, Thanita; Thongpibul, Kulvadee

    2016-01-01

    Despite the fact that pain is related to depression, few studies have been conducted to investigate the variables that mediate between the two conditions. In this study, the authors explored the following mediators: cognitive function, self-sacrificing interpersonal problems, and perception of stress, and the effects they had on pain symptoms among patients with depressive disorders. An analysis was performed on the data of 346 participants with unipolar depressive disorders. The 17-item Hamilton Depression Rating Scale, Mini-Mental State Examination, the pain subscale of the health-related quality of life (SF-36), the self-sacrificing subscale of the Inventory of Interpersonal Problems, and the Perceived Stress Scale were used. Parallel multiple mediator and serial multiple mediator models were used. An alternative model regarding the effect of self-sacrificing on pain was also proposed. Perceived stress, self-sacrificing interpersonal style, and cognitive function were found to significantly mediate the relationship between depression and pain, while controlling for demographic variables. The total effect of depression on pain was significant. This model, with an additional three mediators, accounted for 15% of the explained variance in pain compared to 9% without mediators. For the alternative model, after controlling for the mediators, a nonsignificant total direct effect level of self-sacrificing was found, suggesting that the effect of self-sacrificing on pain was based only on an indirect effect and that perceived stress was found to be the strongest mediator. Serial mediation may help us to see how depression and pain are linked and what the fundamental mediators are in the chain. No significant, indirect effect of self-sacrificing on pain was observed, if perceived stress was not part of the depression and/or cognitive function mediational chain. The results shown here have implications for future research, both in terms of testing the model and in

  9. Analyzing Statistical Mediation with Multiple Informants: A New Approach with an Application in Clinical Psychology.

    Science.gov (United States)

    Papa, Lesther A; Litson, Kaylee; Lockhart, Ginger; Chassin, Laurie; Geiser, Christian

    2015-01-01

    Testing mediation models is critical for identifying potential variables that need to be targeted to effectively change one or more outcome variables. In addition, it is now common practice for clinicians to use multiple informant (MI) data in studies of statistical mediation. By coupling the use of MI data with statistical mediation analysis, clinical researchers can combine the benefits of both techniques. Integrating the information from MIs into a statistical mediation model creates various methodological and practical challenges. The authors review prior methodological approaches to MI mediation analysis in clinical research and propose a new latent variable approach that overcomes some limitations of prior approaches. An application of the new approach to mother, father, and child reports of impulsivity, frustration tolerance, and externalizing problems (N = 454) is presented. The results showed that frustration tolerance mediated the relationship between impulsivity and externalizing problems. The new approach allows for a more comprehensive and effective use of MI data when testing mediation models.

  10. Community Mediation. A Model for Romania

    Directory of Open Access Journals (Sweden)

    Christian Radu CHEREJI

    2014-02-01

    Full Text Available Community mediation takes all forms and shapes all over the world. In order to better understand its limitations in adapting to different contexts, we have compared the evolution of community mediation services in two totally different systems, USA and Sri Lanka. Based on this analysis and the results of a research conducted in Cluj-Napoca in the fall of 2013, we have recommended a community mediation model suitable for the current Romanian social, economic and cultural framework.

  11. Insulin resistance and carotid intima-media thickness mediate the association between resting-state heart rate variability and executive function: A path modelling study.

    Science.gov (United States)

    Kemp, Andrew H; López, Santiago Rodríguez; Passos, Valeria M A; Bittencourt, Marcio S; Dantas, Eduardo M; Mill, José G; Ribeiro, Antonio L P; Thayer, Julian F; Bensenor, Isabela M; Lotufo, Paulo A

    2016-05-01

    Research has linked high-frequency heart rate variability (HF-HRV) to cognitive function. The present study adopts a modern path modelling approach to understand potential causal pathways that may underpin this relationship. Here we examine the association between resting-state HF-HRV and executive function in a large sample of civil servants from Brazil (N=8114) recruited for the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). HF-HRV was calculated from 10-min resting-state electrocardiograms. Executive function was assessed using the trail-making test (version B). Insulin resistance (a marker of type 2 diabetes mellitus) and carotid intima-media thickness (subclinical atherosclerosis) mediated the relationship between HRV and executive function in seriatim. A limitation of the present study is its cross-sectional design; therefore, conclusions must be confirmed in longitudinal study. Nevertheless, findings support that possibility that HRV provides a 'spark' that initiates a cascade of adverse downstream effects that subsequently leads to cognitive impairment. Copyright © 2016 Elsevier B.V. All rights reserved.

  12. EXPLORING MEDIATING ROLE OF INSTITUTIONAL IMAGE THROUGH A COMPLETE STRUCTURAL EQUATION MODELING (SEM: A PERSPECTVE OF HIGHER EDUCATION

    Directory of Open Access Journals (Sweden)

    Abu Osman

    2018-06-01

    Full Text Available The prime objective of this study is to investigate the mediating role of institutional image between student satisfaction, program quality, and service quality in the context of higher education. To attain this aim, the Nordic model was used as theoretical foundation of the study. The Structural Equation Modeling (SEM was used to analyze the influence of mediating variable and hypotheses testing. The population of this study was fourth-year business students of nine 'grade one' private universities in Bangladesh. Data (n=310 were gathered from students pursuing studies at different private universities in Bangladesh. The findings of this study revealed that image occupied full mediation role between student satisfaction and service quality. Furthermore, it also disclosed that the direct path of student satisfaction and service quality was not statistically significant. These exceptional findings indicate that academic experts should promote the institutional image, student satisfaction and program quality rigorously in order to enhance service quality of education. The outcomes of this study would provide substantial benefits to both practitioners and academics, especially in the context of private higher education. There is a deficiency of indirect link between student satisfaction, program quality and service quality. This study has integrated institutional image as a mediating variable to fulfill the deficiency between student satisfaction, program quality, and service quality.

  13. Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change.

    Directory of Open Access Journals (Sweden)

    Brooke E Penaluna

    Full Text Available Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007-2011, and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year, but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.

  14. POWER ANALYSIS FOR COMPLEX MEDIATIONAL DESIGNS USING MONTE CARLO METHODS

    OpenAIRE

    Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.

    2010-01-01

    Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex mediational models. The approach is based on the well known technique of generating a large number of samples in a Monte Carlo study, and estimating power...

  15. Confounding of three binary-variables counterfactual model

    OpenAIRE

    Liu, Jingwei; Hu, Shuang

    2011-01-01

    Confounding of three binary-variables counterfactual model is discussed in this paper. According to the effect between the control variable and the covariate variable, we investigate three counterfactual models: the control variable is independent of the covariate variable, the control variable has the effect on the covariate variable and the covariate variable affects the control variable. Using the ancillary information based on conditional independence hypotheses, the sufficient conditions...

  16. Power Analysis for Complex Mediational Designs Using Monte Carlo Methods

    Science.gov (United States)

    Thoemmes, Felix; MacKinnon, David P.; Reiser, Mark R.

    2010-01-01

    Applied researchers often include mediation effects in applications of advanced methods such as latent variable models and linear growth curve models. Guidance on how to estimate statistical power to detect mediation for these models has not yet been addressed in the literature. We describe a general framework for power analyses for complex…

  17. Violence as Mediating Variable in Mental Health Disparities Associated to Sexual Orientation Among Mexican Youths.

    Science.gov (United States)

    Mendoza-Pérez, Juan Carlos; Ortiz-Hernández, Luis

    2018-01-05

    In this study, we explored the role of sex as an effect-modifying variable in the association between sexual orientation and mental health in Mexican youth. In addition, we tested if violent experiences in the family and the school and attitudes toward homosexuality could act as mediating variables in such association. Data from three representative surveys performed in 2007, 2009, and 2013 among Mexican high school students were analyzed. Two dimensions of sexual orientation were evaluated: romantic partnership and sexual behavior. The outcomes were negative and positive mood, suicidal ideation and intent, self-concept, and self-esteem. There were differences by gender because in males, there were more disparities in mental health associated with sexual orientation (suicidal ideation and attempt, negative and positive mood, negative self-concept, and family-related self-esteem) than in females (suicidal ideation and negative mood). Experiences of school violence were mediators in the relationship between sexual orientation and most health outcomes in males.

  18. The mediation of mothers' self-fulfilling effects on their children's alcohol use: self-verification, informational conformity, and modeling processes.

    Science.gov (United States)

    Madon, Stephanie; Guyll, Max; Buller, Ashley A; Scherr, Kyle C; Willard, Jennifer; Spoth, Richard

    2008-08-01

    This research examined whether self-fulfilling prophecy effects are mediated by self-verification, informational conformity, and modeling processes. The authors examined these mediational processes across multiple time frames with longitudinal data obtained from two samples of mother-child dyads (N-sub-1 = 486; N-sub-2 = 287), with children's alcohol use as the outcome variable. The results provided consistent support for the mediational process of self-verification. In both samples and across several years of adolescence, there was a significant indirect effect of mothers' beliefs on children's alcohol use through children's self-assessed likelihood of drinking alcohol in the future. Comparatively less support was found for informational conformity and modeling processes as mediators of mothers' self-fulfilling effects. The potential for self-fulfilling prophecies to produce long-lasting changes in targets' behavior via self-verification processes are discussed. (c) 2008 APA, all rights reserved

  19. Mediating processes between stress and problematic marijuana use.

    Science.gov (United States)

    Ketcherside, Ariel; Filbey, Francesca M

    2015-06-01

    The literature widely reports that stress is associated with marijuana use, yet, to date, the path from stress to marijuana-related problems has not been tested. In this study, we evaluated whether negative affect mediates the relationship between stress and marijuana use. To that end, we tested models to determine mediators between problems with marijuana use (via Marijuana Problem Scale), stress (via Early Life Stress Questionnaire, Perceived Stress Scale), and negative affect (via Beck Depression Inventory; Beck Anxiety Inventory) in 157 current heavy marijuana users. Mediation tests and bootstrap confidence intervals were carried out via the "Mediation" package in R. Depression and anxiety scores both significantly mediated the relationship between perceived stress and problematic marijuana use. Only depression significantly mediated the relationship between early life stress and problematic marijuana use. Early life stress, perceived stress and problematic marijuana use were significant only as independent variables and dependent variables. These findings demonstrate that (1) depression mediated both early life stress and perceived stress, and problematic marijuana use, and, (2) anxiety mediated perceived stress and problematic marijuana use. This mediation analysis represents a strong first step toward understanding the relationship between these variables; however, longitudinal studies are needed to determine causality between these variables. To conclude, addressing concomitant depression and anxiety in those who report either perceived stress or early life stress is important for the prevention of cannabis use disorders. Copyright © 2015. Published by Elsevier Ltd.

  20. The whole relationship between environmental variables and firm performance: competitive advantage and firm resources as mediator variables.

    Science.gov (United States)

    López-Gamero, María D; Molina-Azorín, José F; Claver-Cortés, Enrique

    2009-07-01

    The examination of the possible direct link between environmental protection and firm performance in the literature has generally produced mixed results. The present paper contributes to the literature by using the resource-based view as a mediating process in this relationship. The study specifically tests whether or not the resource-based view of the firm mediates the positive relationships of proactive environmental management and improved environmental performance with competitive advantage, which also has consequences for financial performance. We also check the possible link between the adoption of a pioneering approach and good environmental management practices. Our findings support that early investment timing and intensity in environmental issues impact on the adoption of a proactive environmental management, which in turn helps to improve environmental performance. The findings also show that a firm's resources and competitive advantage act as mediator variables for a positive relationship between environmental protection and financial performance. This contribution is original because the present paper develops a comprehensive whole picture of this path process, which has previously only been partially discussed in the literature. In addition, this study clarifies a relevant point in the literature, namely that the effect of environmental protection on firm performance is not direct and can vary depending on the sector considered. Whereas competitive advantage in relation to costs influences financial performance in the IPPC law sector, the relevant influence in the hotel sector comes from competitive advantage through differentiation.

  1. The Mediation of Mothers’ Self-Fulfilling Effects on Their Children’s Alcohol Use: Self-Verification, Informational Conformity and Modeling Processes

    Science.gov (United States)

    Madon, Stephanie; Guyll, Max; Buller, Ashley A.; Scherr, Kyle C.; Willard, Jennifer; Spoth, Richard

    2010-01-01

    This research examined whether self-fulfilling prophecy effects are mediated by self-verification, informational conformity, and modeling processes. The authors examined these mediational processes across multiple time frames with longitudinal data obtained from two samples of mother – child dyads (N1 = 487; N2 = 287). Children’s alcohol use was the outcome variable. The results provided consistent support for the mediational process of self-verification. In both samples and across several years of adolescence, there was a significant indirect effect of mothers’ beliefs on children’s alcohol use through children’s self-assessed likelihood of drinking alcohol in the future. Comparatively less support was found for informational conformity and modeling processes as mediators of mothers’ self-fulfilling effects. The potential for self-fulfilling prophecies to produce long lasting changes in targets’ behavior via self-verification processes are discussed. PMID:18665708

  2. Analyzing Statistical Mediation with Multiple Informants: A New Approach with an Application in Clinical Psychology

    Directory of Open Access Journals (Sweden)

    Lesther ePapa

    2015-11-01

    Full Text Available Testing mediation models is critical for identifying potential variables that need to be targeted to effectively change one or more outcome variables. In addition, it is now common practice for clinicians to use multiple informant (MI data in studies of statistical mediation. By coupling the use of MI data with statistical mediation analysis, clinical researchers can combine the benefits of both techniques. Integrating the information from MIs into a statistical mediation model creates various methodological and practical challenges. The authors review prior methodological approaches to MI mediation analysis in clinical research and propose a new latent variable approach that overcomes some limitations of prior approaches. An application of the new approach to mother, father, and child reports of impulsivity, frustration tolerance, and externalizing problems (N = 454 is presented. The results showed that frustration tolerance mediated the relationship between impulsivity and externalizing problems. Advantages and limitations of the new approach are discussed. The new approach can help clinical researchers overcome limitations of prior techniques. It allows for a more comprehensive and effective use of MI data when testing mediation models.

  3. Stable SUSY breaking model with O(10) eV gravitino from combined D-term gauge mediation and U(1)' mediation

    International Nuclear Information System (INIS)

    Nakayama, Yu

    2008-01-01

    We show a calculable example of stable supersymmetry (SUSY) breaking models with O(10) eV gravitino mass based on the combination of D-term gauge mediation and U(1)' mediation. A potential problem of the negative mass squared for the SUSY standard model (SSM) sfermions in the D-term gauge mediation is solved by the contribution from the U(1)' mediation. On the other hand, the splitting between the SSM gauginos and sfermions in the U(1)' mediation is circumvented by the contributions from the D-term gauge mediation. Since the U(1)' mediation does not introduce any new SUSY vacua, we achieve a completely stable model under thermal effects. Our model, therefore, has no cosmological difficulty

  4. Depression and reduced heart rate variability after cardiac surgery: the mediating role of emotion regulation.

    Science.gov (United States)

    Patron, Elisabetta; Messerotti Benvenuti, Simone; Favretto, Giuseppe; Gasparotto, Renata; Palomba, Daniela

    2014-02-01

    Heart rate variability (HRV), as an index of autonomic nervous system (ANS) functioning, is reduced by depression after cardiac surgery, but the underlying mechanisms of this relationship are poorly understood. Poor emotion regulation as a core symptom of depression has also been associated with altered ANS functioning. The present study aimed to examine whether emotion dysregulation could be a mediator of the depression-reduced HRV relationship observed after cardiac surgery. Self-reported emotion regulation and four-minute HRV were measured in 25 depressed and 43 nondepressed patients after cardiac surgery. Mediation analysis was conducted to evaluate emotion regulation as a mediator of the depression-reduced HRV relationship. Compared to nondepressed patients, those with depression showed lower standard deviation of normal-to-normal (NN) intervals (pbehavior partially mediated the effect of depression on LF n.u. and HF n.u. Results confirmed previous findings showing that depression is associated with reduced HRV, especially a reduced vagal tone and a sympathovagal imbalance, after cardiac surgery. This study also provides preliminary evidence that increased trait levels of suppression of emotion-expressive behavior may mediate the depression-related sympathovagal imbalance after cardiac surgery. Copyright © 2013 Elsevier B.V. All rights reserved.

  5. Social cognitive mediators of parent-child sexual communication.

    Science.gov (United States)

    Evans, W Douglas; Blitstein, Jonathan L; Davis, Kevin C

    2011-07-01

    To test a social cognitive behavior change model and identify mediators of the effects of the Parents Speak Up National Campaign (PSUNC) on parent-child sexual communication. Investigators used 5 waves of data from an online randomized controlled trial. Latent variables were developed based on item response theory and confirmatory factor analysis. Structural equation modeling was used to test mediation. Outcome expectations mediated effects of social norms and self-efficacy on sexual communication. Other hypothesized mediators were not confirmed. Interventions to promote parent-child sexual communication should target outcome expectations. Future research should investigate parents' health information seeking.

  6. Eutrophication Modeling Using Variable Chlorophyll Approach

    International Nuclear Information System (INIS)

    Abdolabadi, H.; Sarang, A.; Ardestani, M.; Mahjoobi, E.

    2016-01-01

    In this study, eutrophication was investigated in Lake Ontario to identify the interactions among effective drivers. The complexity of such phenomenon was modeled using a system dynamics approach based on a consideration of constant and variable stoichiometric ratios. The system dynamics approach is a powerful tool for developing object-oriented models to simulate complex phenomena that involve feedback effects. Utilizing stoichiometric ratios is a method for converting the concentrations of state variables. During the physical segmentation of the model, Lake Ontario was divided into two layers, i.e., the epilimnion and hypolimnion, and differential equations were developed for each layer. The model structure included 16 state variables related to phytoplankton, herbivorous zooplankton, carnivorous zooplankton, ammonium, nitrate, dissolved phosphorus, and particulate and dissolved carbon in the epilimnion and hypolimnion during a time horizon of one year. The results of several tests to verify the model, close to 1 Nash-Sutcliff coefficient (0.98), the data correlation coefficient (0.98), and lower standard errors (0.96), have indicated well-suited model’s efficiency. The results revealed that there were significant differences in the concentrations of the state variables in constant and variable stoichiometry simulations. Consequently, the consideration of variable stoichiometric ratios in algae and nutrient concentration simulations may be applied in future modeling studies to enhance the accuracy of the results and reduce the likelihood of inefficient control policies.

  7. Do taste expectations mediate the impact of quality cues on consumers’ choice of chicken?

    DEFF Research Database (Denmark)

    Marian, Livia; Thøgersen, John; Krystallis Krontalis, Athanasios

    . The conjoint design was a metric traditional conjoint approach based on an additive model, where 405 respondents had to rate their willingness to buy and expectations regarding taste of each one of the nine different chickens on scales from 0 to 10. It was thus possible to conduct two different conjoint...... analyses, in order to determine the impact of the quality cues on buying intention on the one hand, and on the expected taste on the other hand. In these models, quality cues are initial variables, while expected taste and willingness to buy are both outcome variables. The two models are then integrated...... when testing whether or not expected taste mediates the effects of quality cues on willingness to buy. Hence, in the mediational model, quality cues are initial variables, willingness to buy is the outcome and expected taste is the mediator. The most effective way to do the mediation analysis is still...

  8. Capital Structure: Target Adjustment Model and a Mediation Moderation Model with Capital Structure as Mediator

    OpenAIRE

    Abedmajid, Mohammed

    2015-01-01

    This study consists of two models. Model one is conducted to check if there is a target adjustment toward optimal capital structure, in the context of Turkish firm listed on the stock market, over the period 2003-2014. Model 2 captures the interaction between firm size, profitability, market value and capital structure using the moderation mediation model. The results of model 1 have shown that there is a partial adjustment of the capital structure to reach target levels. The results of...

  9. Monte Carlo based statistical power analysis for mediation models: methods and software.

    Science.gov (United States)

    Zhang, Zhiyong

    2014-12-01

    The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.

  10. The protection motivation theory within the stages of the transtheoretical model - stage-specific interplay of variables and prediction of exercise stage transitions.

    Science.gov (United States)

    Lippke, Sonia; Plotnikoff, Ronald C

    2009-05-01

    Two different theories of health behaviour have been chosen with the aim of theory integration: a continuous theory (protection motivation theory, PMT) and a stage model (transtheoretical model, TTM). This is the first study to test whether the stages of the TTM moderate the interrelation of PMT-variables and the mediation of motivation, as well as PMT-variables' interactions in predicting stage transitions. Hypotheses were tested regarding (1) mean patterns, stage pair-comparisons and nonlinear trends using ANOVAs; (2) prediction-patterns for the different stage groups employing multi-group structural equation modelling (MSEM) and nested model analyses; and (3) stage transitions using binary logistic regression analyses. Adults (N=1,602) were assessed over a 6 month period on their physical activity stages, PMT-variables and subsequent behaviour. (1) Particular mean differences and nonlinear trends in all test variables were found. (2) The PMT adequately fitted the five stage groups. The MSEM revealed that covariances within threat appraisal and coping appraisal were invariant and all other constrains were stage-specific, i.e. stage was a moderator. Except for self-efficacy, motivation fully mediated the relationship between the social-cognitive variables and behaviour. (3) Predicting stage transitions with the PMT-variables underscored the importance of self-efficacy. Only when threat appraisal and coping appraisal were high, stage movement was more likely in the preparation stage. Results emphasize stage-specific differences of the PMT mechanisms, and hence, support the stage construct. The findings may guide further theory building and research integrating different theoretical approaches.

  11. Integrating mediation and moderation to advance theory development and testing.

    Science.gov (United States)

    Karazsia, Bryan T; Berlin, Kristoffer S; Armstrong, Bridget; Janicke, David M; Darling, Katherine E

    2014-03-01

    The concepts and associated analyses of mediation and moderation are important to the field of psychology. Although pediatric psychologists frequently incorporate mediation and moderation in their theories and empirical research, on few occasions have we integrated mediation and moderation. In this article, conceptual reasons for integrating mediation and moderation are offered. We illustrate a model that integrates mediation and moderation. In our illustration, the strength of an indirect or a mediating effect varied as a function of a moderating variable. Clinical implications of the integration of mediation and moderation are discussed, as is the potential of integrated models to advance research programs in pediatric psychology.

  12. Variable selection and model choice in geoadditive regression models.

    Science.gov (United States)

    Kneib, Thomas; Hothorn, Torsten; Tutz, Gerhard

    2009-06-01

    Model choice and variable selection are issues of major concern in practical regression analyses, arising in many biometric applications such as habitat suitability analyses, where the aim is to identify the influence of potentially many environmental conditions on certain species. We describe regression models for breeding bird communities that facilitate both model choice and variable selection, by a boosting algorithm that works within a class of geoadditive regression models comprising spatial effects, nonparametric effects of continuous covariates, interaction surfaces, and varying coefficients. The major modeling components are penalized splines and their bivariate tensor product extensions. All smooth model terms are represented as the sum of a parametric component and a smooth component with one degree of freedom to obtain a fair comparison between the model terms. A generic representation of the geoadditive model allows us to devise a general boosting algorithm that automatically performs model choice and variable selection.

  13. A strain-mediated corrosion model for bioabsorbable metallic stents.

    Science.gov (United States)

    Galvin, E; O'Brien, D; Cummins, C; Mac Donald, B J; Lally, C

    2017-06-01

    This paper presents a strain-mediated phenomenological corrosion model, based on the discrete finite element modelling method which was developed for use with the ANSYS Implicit finite element code. The corrosion model was calibrated from experimental data and used to simulate the corrosion performance of a WE43 magnesium alloy stent. The model was found to be capable of predicting the experimentally observed plastic strain-mediated mass loss profile. The non-linear plastic strain model, extrapolated from the experimental data, was also found to adequately capture the corrosion-induced reduction in the radial stiffness of the stent over time. The model developed will help direct future design efforts towards the minimisation of plastic strain during device manufacture, deployment and in-service, in order to reduce corrosion rates and prolong the mechanical integrity of magnesium devices. The need for corrosion models that explore the interaction of strain with corrosion damage has been recognised as one of the current challenges in degradable material modelling (Gastaldi et al., 2011). A finite element based plastic strain-mediated phenomenological corrosion model was developed in this work and was calibrated based on the results of the corrosion experiments. It was found to be capable of predicting the experimentally observed plastic strain-mediated mass loss profile and the corrosion-induced reduction in the radial stiffness of the stent over time. To the author's knowledge, the results presented here represent the first experimental calibration of a plastic strain-mediated corrosion model of a corroding magnesium stent. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

  14. Personality and leader effectiveness: a moderated mediation model of leadership self-efficacy, job demands, and job autonomy.

    Science.gov (United States)

    Ng, Kok-Yee; Ang, Soon; Chan, Kim-Yin

    2008-07-01

    The trait theory of leadership is advanced by a joint investigation of the mediating role of (a) leadership self-efficacy (LSE = leader's perceived capabilities to perform leader roles) in linking neuroticism, extraversion, and conscientiousness with leader effectiveness and (b) the moderating role of job demands and job autonomy in influencing the mediation. Using K. J. Preacher, D. D. Rucker, and A. F. Hayes' (2007) moderated mediation framework, the authors tested the model (over a 2-year period) with matched data from 394 military leaders and their supervisors. Results showed that LSE mediated the relationships for neuroticism, extraversion, and conscientiousness with leader effectiveness. Moderated mediation analyses further revealed that LSE mediated the relationships for (a) all 3 personality variables for only those leaders with low job demands; (b) neuroticism and conscientiousness for only those leaders with high job autonomy; and (c) extraversion, regardless of a leader's level of job autonomy. Results underscore the importance of accounting for leaders' situational contexts when examining the relationships between personality, LSE, and effectiveness.

  15. Evaluating mediation and moderation effects in school psychology: a presentation of methods and review of current practice.

    Science.gov (United States)

    Fairchild, Amanda J; McQuillin, Samuel D

    2010-02-01

    Third variable effects elucidate the relation between two other variables, and can describe why they are related or under what conditions they are related. This article demonstrates methods to analyze two third-variable effects: moderation and mediation. The utility of examining moderation and mediation effects in school psychology is described and current use of the analyses in applied school psychology research is reviewed and evaluated. Proper statistical methods to test the effects are presented, and different effect size measures for the models are provided. Extensions of the basic moderator and mediator models are also described.

  16. A Core Language for Separate Variability Modeling

    DEFF Research Database (Denmark)

    Iosif-Lazăr, Alexandru Florin; Wasowski, Andrzej; Schaefer, Ina

    2014-01-01

    Separate variability modeling adds variability to a modeling language without requiring modifications of the language or the supporting tools. We define a core language for separate variability modeling using a single kind of variation point to define transformations of software artifacts in object...... hierarchical dependencies between variation points via copying and flattening. Thus, we reduce a model with intricate dependencies to a flat executable model transformation consisting of simple unconditional local variation points. The core semantics is extremely concise: it boils down to two operational rules...

  17. Sparticle spectrum and constraints in anomaly mediated supersymmetry breaking models

    International Nuclear Information System (INIS)

    Huitu, K.; Laamanen, J.; Pandita, P.N.

    2002-01-01

    We study in detail the particle spectrum in anomaly mediated supersymmetry breaking models in which supersymmetry breaking terms are induced by the super-Weyl anomaly. We investigate the minimal anomaly mediated supersymmetry breaking models, gaugino assisted supersymmetry breaking models, as well as models with additional residual nondecoupling D-term contributions due to an extra U(1) gauge symmetry at a high energy scale. We derive sum rules for the sparticle masses in these models which can help in differentiating between them. We also obtain the sparticle spectrum numerically, and compare and contrast the results so obtained for the different types of anomaly mediated supersymmetry breaking models

  18. Causal mediation analysis with a binary outcome and multiple continuous or ordinal mediators: Simulations and application to an alcohol intervention

    OpenAIRE

    Nguyen, Trang Quynh; Webb-Vargas, Yenny; Koning, Ina M.; Stuart, Elizabeth A.

    2016-01-01

    We investigate a method to estimate the combined effect of multiple continuous/ordinal mediators on a binary outcome: 1) fit a structural equation model with probit link for the outcome and identity/probit link for continuous/ordinal mediators, 2) predict potential outcome probabilities, and 3) compute natural direct and indirect effects. Step 2 involves rescaling the latent continuous variable underlying the outcome to address residual mediator variance/covariance. We evaluate the estimation...

  19. The mediating role of organizational subcultures in health care organizations.

    Science.gov (United States)

    Lok, Peter; Rhodes, Jo; Westwood, Bob

    2011-01-01

    This study aims to investigate the mediating role of organizational subculture between job satisfaction, organizational commitment (dependent variables) and leadership, culture (independent variables) in health care organizations. A survey on nurses from 26 wards from various types of hospital was used. A total of 251 usable returns were collected for the analysis (i.e. response rate of 63 per cent). Structural equation analysis was conducted to obtain the best fit model and to determine the direction of the causal effect between job satisfaction and commitment, and the role of subculture as a mediating variable, between commitment of its other antecedents. Comparisons with alternative models confirmed satisfaction as an antecedent of commitment and the role of subculture as a mediating variable. The results of this study contribute to the clarification of the causal relations of the antecedents of commitment, and highlight the important role of local leadership and subculture in determining employees' job satisfaction and commitment. The results of this study should not be generalized to other industries and other national cultural context. Furthermore, a longitudinal study may be necessary to determine the causal relationship of variables used in this study. The findings could provide managers with valuable insight to focus their limited resources on improving the level of organizational commitment via the mediating role of organizational culture. The research findings provide managers with a new lens to examine organizational culture using the three perspectives of: bureaucratic, supportive, and innovative. Furthermore, the results could renew interest in developing other organizational subculture models that determine the relationship between organizational subculture and commitment

  20. The role of individual and social variables in predicting body dissatisfaction and eating disorder symptoms among Iranian adolescent girls: an expanding of the tripartite influence model

    Directory of Open Access Journals (Sweden)

    Shima Shahyad

    2018-03-01

    Full Text Available The aim of the present study was to examine the causal relationships between psychological and social factors, being independent variables and body image dissatisfaction plus symptoms of eating disorders as dependent variables through the mediation of social comparison and thin-ideal internalization. To conduct the study, 477 high-school students from Tehran were recruited by method of cluster sampling. Next, they filled out Rosenberg Self-esteem Scale (RSES, Physical Appearance Comparison Scale (PACS, Self-Concept Clarity Scale (SCCS, Appearance Perfectionism Scale (APS, Eating Disorder Inventory (EDI, Multidimensional Body Self Relations Questionnaire (MBSRQ and Sociocultural Attitudes towards Appearance Questionnaire (SATAQ-4. In the end, collected data were analyzed using structural equation modeling. Findings showed that the assumed model perfectly fitted the data after modification and as a result, all the path-coefficients of latent variables (except for the path between self-esteem and thin-ideal internalization were statistically significant (p<0.05. Also, in this model, 75% of scores' distribution of body dissatisfaction was explained through psychological variables, socio-cultural variables, social comparison and internalization of the thin ideal. The results of the present study provid experimental basis for the confirmation of proposed causal model. The combination of psychological, social and cultural variables could efficiently predict body image dissatisfaction of young girls in Iran. Key Words: Thin-ideal Internalization, Social comparison, Body image dissatisfaction, mediating effects model, eating disorder symptoms, psychological factors.

  1. Working conditions, burnout and stress symptoms in university professors: validating a structural model of the mediating effect of perceived personal competence.

    Science.gov (United States)

    Avargues Navarro, María Luisa; Borda Mas, Mercedes; López Jiménez, Ana María

    2010-05-01

    The purpose of this study has been to test, with a sample of 193 Professors of the University of Seville, a structural model on the mediating role of personal perceived competence in the appearance of burnout syndrome and stress symptoms under potentially stressful work conditions. The instruments used to evaluate were a socio-demographic and work-related data questionnaire, The Maslach Burnout Inventory (M.B.I.), The Labour Scale of Stress and the Magallanes Stress Scale. The model of strategy implementation and LISREL 8.71 were used. The estimated model was adjusted satisfactorily, ascertaining the mediating effect of perceived competence in the effect exerted by the work conditions studied on the depersonalization and personal fulfillment, as well as in the appearance of stress symptoms. The effect on the emotional exhaustion dimension was not confirmed. The latter also acted on the estimated model as a mediating variable, facilitating the negative impact of stressors on emotional exhaustion, depersonalization and personal accomplishment.

  2. Does anger regulation mediate the discrimination-mental health link among Mexican-origin adolescents? A longitudinal mediation analysis using multilevel modeling.

    Science.gov (United States)

    Park, Irene J K; Wang, Lijuan; Williams, David R; Alegría, Margarita

    2017-02-01

    [Correction Notice: An Erratum for this article was reported in Vol 53(2) of Developmental Psychology (see record 2017-04475-001). In the article, there were several typographical errors in the Recruitment and Procedures section. The percentage of mothers who responded to survey items should have been 99.3%. Additionally, the youths surveyed at T2 and T3 should have been n 246. Accordingly, the percentage of youths surveyed in T2 and T3 should have been 91.4% and the percentage of mothers surveyed at T2 and T3 should have been 90.7%. Finally, the youths missing at T2 should have been n 23, and therefore the attrition rate for youth participants should have been 8.6. All versions of this article have been corrected.] Although prior research has consistently documented the association between racial/ethnic discrimination and poor mental health outcomes, the mechanisms that underlie this link are still unclear. The present 3-wave longitudinal study tested the mediating role of anger regulation in the discrimination-mental health link among 269 Mexican-origin adolescents ( M age = 14.1 years, SD = 1.6; 57% girls), 12 to 17 years old. Three competing anger regulation variables were tested as potential mediators: outward anger expression, anger suppression, and anger control. Longitudinal mediation analyses were conducted using multilevel modeling that disaggregated within-person effects from between-person effects. Results indicated that outward anger expression was a significant mediator; anger suppression and anger control were not significant mediators. Within a given individual, greater racial/ethnic discrimination was associated with more frequent outward anger expression. In turn, more frequent outward anger expression was associated with higher levels of anxiety and depression at a given time point. Gender, age, and nativity status were not significant moderators of the hypothesized mediation models. By identifying outward anger expression as an explanatory

  3. Impact of mass generation for spin-1 mediator simplified models

    International Nuclear Information System (INIS)

    Bell, Nicole F.; Cai, Yi; Leane, Rebecca K.

    2017-01-01

    In the simplified dark matter models commonly studied, the mass generation mechanism for the dark fields is not typically specified. We demonstrate that the dark matter interaction types, and hence the annihilation processes relevant for relic density and indirect detection, are strongly dictated by the mass generation mechanism chosen for the dark sector particles, and the requirement of gauge invariance. We focus on the class of models in which fermionic dark matter couples to a spin-1 vector or axial-vector mediator. However, in order to generate dark sector mass terms, it is necessary in most cases to introduce a dark Higgs field and thus a spin-0 scalar mediator will also be present. In the case that all the dark sector fields gain masses via coupling to a single dark sector Higgs field, it is mandatory that the axial-vector coupling of the spin-1 mediator to the dark matter is non-zero; the vector coupling may also be present depending on the charge assignments. For all other mass generation options, only pure vector couplings between the spin-1 mediator and the dark matter are allowed. If these coupling restrictions are not obeyed, unphysical results may be obtained such as a violation of unitarity at high energies. These two-mediator scenarios lead to important phenomenology that does not arise in single mediator models. We survey two-mediator dark matter models which contain both vector and scalar mediators, and explore their relic density and indirect detection phenomenology.

  4. Evaluating mediation and moderation effects in school psychology: A presentation of methods and review of current practice

    Science.gov (United States)

    Fairchild, Amanda J.; McQuillin, Samuel D.

    2017-01-01

    Third variable effects elucidate the relation between two other variables, and can describe why they are related or under what conditions they are related. This article demonstrates methods to analyze two third-variable effects: moderation and mediation. The utility of examining moderation and mediation effects in school psychology is described and current use of the analyses in applied school psychology research is reviewed and evaluated. Proper statistical methods to test the effects are presented, and different effect size measures for the models are provided. Extensions of the basic moderator and mediator models are also described. PMID:20006988

  5. The relationship of sociodemographic and psychological variables with chronic pain variables in a low-income population.

    Science.gov (United States)

    Newman, Andrea K; Van Dyke, Benjamin P; Torres, Calia A; Baxter, Jacob W; Eyer, Joshua C; Kapoor, Shweta; Thorn, Beverly E

    2017-09-01

    Chronic pain is a pervasive condition that is complicated by economic, educational, and racial disparities. This study analyzes key factors associated with chronic pain within an understudied and underserved population. The sample is characterized by a triple disparity with respect to income, education/literacy, and racial barriers that substantially increase the vulnerability to the negative consequences of chronic pain. The study examined the pretreatment data of 290 participants enrolled in the Learning About My Pain trial, a randomized controlled comparative effectiveness trial of psychosocial interventions (B.E.T., Principal Investigator, Patient-Centered Outcomes Research Institute Contract No. 941; clinicaltrials.gov identifier NCT01967342) for chronic pain. Hierarchical multiple regression analyses evaluated the relationships among sociodemographic (sex, age, race, poverty status, literacy, and education level) and psychological (depressive symptoms and pain catastrophizing) variables and pain interference, pain severity, and disability. The indirect effects of depressive symptoms and pain catastrophizing on the sociodemographic and pain variables were investigated using bootstrap resampling. Reversed mediation models were also examined. Results suggested that the experience of chronic pain within this low-income sample is better accounted for by psychological factors than sex, age, race, poverty status, literacy, and education level. Depressive symptoms and pain catastrophizing mediated the relationships between age and pain variables, whereas pain catastrophizing mediated the effects of primary literacy and poverty status. Some reversed models were equivalent to the hypothesized models, suggesting the possibility of bidirectionality. Although cross-sectional findings cannot establish causality, our results highlight the critical role psychological factors play in individuals with chronic pain and multiple health disparities.

  6. The Peace Mediator effect: Heterogeneous agents can foster consensus in continuous opinion models

    Science.gov (United States)

    Vilone, Daniele; Carletti, Timoteo; Bagnoli, Franco; Guazzini, Andrea

    2016-11-01

    Statistical mechanics has proven to be able to capture the fundamental rules underlying phenomena of social aggregation and opinion dynamics, well studied in disciplines like sociology and psychology. This approach is based on the underlying paradigm that the interesting dynamics of multi-agent systems emerge from the correct definition of few parameters governing the evolution of each individual. In this context, we propose a particular model of opinion dynamics based on the psychological construct named ;cognitive dissonance;. Our system is made of interacting individuals, the agents, each bearing only two dynamical variables (respectively ;opinion; and ;affinity;) self-consistently adjusted during time evolution. We also define two special classes of interacting entities, both acting for a peace mediation process but via different course of action: ;diplomats; and ;auctoritates;. The behavior of the system with and without peace mediators (PMs) is investigated and discussed with reference to corresponding psychological and social implications.

  7. An amodal shared resource model of language-mediated visual attention

    Directory of Open Access Journals (Sweden)

    Alastair Charles Smith

    2013-08-01

    Full Text Available Language-mediated visual attention describes the interaction of two fundamental components of the human cognitive system, language and vision. Within this paper we present an amodal shared resource model of language-mediated visual attention that offers a description of the information and processes involved in this complex multimodal behaviour and a potential explanation for how this ability is acquired. We demonstrate that the model is not only sufficient to account for the experimental effects of Visual World Paradigm studies but also that these effects are emergent properties of the architecture of the model itself, rather than requiring separate information processing channels or modular processing systems. The model provides an explicit description of the connection between the modality-specific input from language and vision and the distribution of eye gaze in language mediated visual attention. The paper concludes by discussing future applications for the model, specifically its potential for investigating the factors driving observed individual differences in language mediated eye gaze.

  8. Bayesian modeling of measurement error in predictor variables

    NARCIS (Netherlands)

    Fox, Gerardus J.A.; Glas, Cornelis A.W.

    2003-01-01

    It is shown that measurement error in predictor variables can be modeled using item response theory (IRT). The predictor variables, that may be defined at any level of an hierarchical regression model, are treated as latent variables. The normal ogive model is used to describe the relation between

  9. Vacuum stability bounds in anomaly and gaugino mediated supersymmetry breaking models

    International Nuclear Information System (INIS)

    Gabrielli, Emidio; Huitu, Katri; Roy, Sourov

    2002-01-01

    We constrain the parameter space of the minimal and gaugino-assisted anomaly mediation, and gaugino mediation models by requiring that the electroweak vacuum corresponds to the deepest minimum of the scalar potential. In the framework of anomaly mediation models we find strong lower bounds on slepton and squark masses. In the gaugino mediation models the mass spectrum is forced to be at the TeV scale. We find extensive regions of the parameter space which are ruled out, even at low tanβ. The implications of these results on the g-2 of the muon are also analyzed

  10. Caregiver Burden Among Caregivers of Individuals With Severe Mental Illness: Testing the Moderation and Mediation Models of Resilience.

    Science.gov (United States)

    Mulud, Zamzaliza Abdul; McCarthy, Geraldine

    2017-02-01

    The association between the socio-demographic characteristics of caregivers, such as gender and caregiver burden, is well documented; however, the process underlying this relationship is poorly understood. Based on the stress process model, we designed a cross-sectional study to examine the mediating and moderating effect of resilience on the relationship between gender and caregiver burden. Caregivers of individuals with severe mental illness (n=201) were recruited in two psychiatric outpatient clinics in Malaysia. The relationship between the gender of the caregiver and caregiver burden was mediated by resilience, thus supporting the stress process model. The findings from the present research contribute to the growing evidence of the interaction between socio-demographic variables of caregivers and resilience, and caregiver burden. Copyright © 2016 Elsevier Inc. All rights reserved.

  11. A new model of how celebrity endorsements work: attitude toward the endorsement as a mediator of celebrity source and endorsement effects

    OpenAIRE

    Bergkvist, Lars; Hjalmarson, Hanna; Mägi, Anne W.

    2015-01-01

    This research introduces attitude towards the endorsement as a mediating variable in the relationships between celebrity source and endorsement factors and brand attitude. It also includes perceived celebrity motive, a variable rarely studied in the previous literature, as an endorsement factor. In a survey study, respondents evaluated four celebrity endorsement campaigns. Mediation analyses show that attitude towards the endorsement mediates the effects of three variables on brand attitude; ...

  12. Method for evaluating multiple mediators: mediating effects of smoking and COPD on the association between the CHRNA5-A3 variant and lung cancer risk.

    Science.gov (United States)

    Wang, Jian; Spitz, Margaret R; Amos, Christopher I; Wu, Xifeng; Wetter, David W; Cinciripini, Paul M; Shete, Sanjay

    2012-01-01

    A mediation model explores the direct and indirect effects between an independent variable and a dependent variable by including other variables (or mediators). Mediation analysis has recently been used to dissect the direct and indirect effects of genetic variants on complex diseases using case-control studies. However, bias could arise in the estimations of the genetic variant-mediator association because the presence or absence of the mediator in the study samples is not sampled following the principles of case-control study design. In this case, the mediation analysis using data from case-control studies might lead to biased estimates of coefficients and indirect effects. In this article, we investigated a multiple-mediation model involving a three-path mediating effect through two mediators using case-control study data. We propose an approach to correct bias in coefficients and provide accurate estimates of the specific indirect effects. Our approach can also be used when the original case-control study is frequency matched on one of the mediators. We employed bootstrapping to assess the significance of indirect effects. We conducted simulation studies to investigate the performance of the proposed approach, and showed that it provides more accurate estimates of the indirect effects as well as the percent mediated than standard regressions. We then applied this approach to study the mediating effects of both smoking and chronic obstructive pulmonary disease (COPD) on the association between the CHRNA5-A3 gene locus and lung cancer risk using data from a lung cancer case-control study. The results showed that the genetic variant influences lung cancer risk indirectly through all three different pathways. The percent of genetic association mediated was 18.3% through smoking alone, 30.2% through COPD alone, and 20.6% through the path including both smoking and COPD, and the total genetic variant-lung cancer association explained by the two mediators was 69.1%.

  13. Method for evaluating multiple mediators: mediating effects of smoking and COPD on the association between the CHRNA5-A3 variant and lung cancer risk.

    Directory of Open Access Journals (Sweden)

    Jian Wang

    Full Text Available A mediation model explores the direct and indirect effects between an independent variable and a dependent variable by including other variables (or mediators. Mediation analysis has recently been used to dissect the direct and indirect effects of genetic variants on complex diseases using case-control studies. However, bias could arise in the estimations of the genetic variant-mediator association because the presence or absence of the mediator in the study samples is not sampled following the principles of case-control study design. In this case, the mediation analysis using data from case-control studies might lead to biased estimates of coefficients and indirect effects. In this article, we investigated a multiple-mediation model involving a three-path mediating effect through two mediators using case-control study data. We propose an approach to correct bias in coefficients and provide accurate estimates of the specific indirect effects. Our approach can also be used when the original case-control study is frequency matched on one of the mediators. We employed bootstrapping to assess the significance of indirect effects. We conducted simulation studies to investigate the performance of the proposed approach, and showed that it provides more accurate estimates of the indirect effects as well as the percent mediated than standard regressions. We then applied this approach to study the mediating effects of both smoking and chronic obstructive pulmonary disease (COPD on the association between the CHRNA5-A3 gene locus and lung cancer risk using data from a lung cancer case-control study. The results showed that the genetic variant influences lung cancer risk indirectly through all three different pathways. The percent of genetic association mediated was 18.3% through smoking alone, 30.2% through COPD alone, and 20.6% through the path including both smoking and COPD, and the total genetic variant-lung cancer association explained by the two

  14. Exploring individual cognitions, self-regulation skills, and environmental-level factors as mediating variables of two versions of a Web-based computer-tailored nutrition education intervention aimed at adults: A randomized controlled trial.

    Science.gov (United States)

    Springvloet, Linda; Lechner, Lilian; Candel, Math J J M; de Vries, Hein; Oenema, Anke

    2016-03-01

    This study explored whether the determinants that were targeted in two versions of a Web-based computer-tailored nutrition education intervention mediated the effects on fruit, high-energy snack, and saturated fat intake among adults who did not comply with dietary guidelines. A RCT was conducted with a basic (tailored intervention targeting individual cognitions and self-regulation), plus (additionally targeting environmental-level factors), and control group (generic nutrition information). Participants were recruited from the general Dutch adult population and randomly assigned to one of the study groups. Online self-reported questionnaires assessed dietary intake and potential mediating variables (behavior-specific cognitions, action- and coping planning, environmental-level factors) at baseline and one (T1) and four (T2) months post-intervention (i.e. four and seven months after baseline). The joint-significance test was used to establish mediating variables at different time points (T1-mediating variables - T2-intake; T1-mediating variables - T1-intake; T2-mediating variables - T2-intake). Educational differences were examined by testing interaction terms. The effect of the plus version on fruit intake was mediated (T2-T2) by intention and fruit availability at home and for high-educated participants also by attitude. Among low/moderate-educated participants, high-energy snack availability at home mediated (T1-T1) the effect of the basic version on high-energy snack intake. Subjective norm mediated (T1-T1) the effect of the basic version on fat intake among high-educated participants. Only some of the targeted determinants mediated the effects of both intervention versions on fruit, high-energy snack, and saturated fat intake. A possible reason for not finding a more pronounced pattern of mediating variables is that the educational content was tailored to individual characteristics and that participants only received feedback for relevant and not for all

  15. Handbook of latent variable and related models

    CERN Document Server

    Lee, Sik-Yum

    2011-01-01

    This Handbook covers latent variable models, which are a flexible class of models for modeling multivariate data to explore relationships among observed and latent variables.- Covers a wide class of important models- Models and statistical methods described provide tools for analyzing a wide spectrum of complicated data- Includes illustrative examples with real data sets from business, education, medicine, public health and sociology.- Demonstrates the use of a wide variety of statistical, computational, and mathematical techniques.

  16. Self-consistent Dark Matter simplified models with an s-channel scalar mediator

    Energy Technology Data Exchange (ETDEWEB)

    Bell, Nicole F.; Busoni, Giorgio; Sanderson, Isaac W., E-mail: n.bell@unimelb.edu.au, E-mail: giorgio.busoni@unimelb.edu.au, E-mail: isanderson@student.unimelb.edu.au [ARC Centre of Excellence for Particle Physics at the Terascale, School of Physics, The University of Melbourne, Victoria 3010 (Australia)

    2017-03-01

    We examine Simplified Models in which fermionic DM interacts with Standard Model (SM) fermions via the exchange of an s -channel scalar mediator. The single-mediator version of this model is not gauge invariant, and instead we must consider models with two scalar mediators which mix and interfere. The minimal gauge invariant scenario involves the mixing of a new singlet scalar with the Standard Model Higgs boson, and is tightly constrained. We construct two Higgs doublet model (2HDM) extensions of this scenario, where the singlet mixes with the 2nd Higgs doublet. Compared with the one doublet model, this provides greater freedom for the masses and mixing angle of the scalar mediators, and their coupling to SM fermions. We outline constraints on these models, and discuss Yukawa structures that allow enhanced couplings, yet keep potentially dangerous flavour violating processes under control. We examine the direct detection phenomenology of these models, accounting for interference of the scalar mediators, and interference of different quarks in the nucleus. Regions of parameter space consistent with direct detection measurements are determined.

  17. Self-consistent Dark Matter simplified models with an s-channel scalar mediator

    International Nuclear Information System (INIS)

    Bell, Nicole F.; Busoni, Giorgio; Sanderson, Isaac W.

    2017-01-01

    We examine Simplified Models in which fermionic DM interacts with Standard Model (SM) fermions via the exchange of an s -channel scalar mediator. The single-mediator version of this model is not gauge invariant, and instead we must consider models with two scalar mediators which mix and interfere. The minimal gauge invariant scenario involves the mixing of a new singlet scalar with the Standard Model Higgs boson, and is tightly constrained. We construct two Higgs doublet model (2HDM) extensions of this scenario, where the singlet mixes with the 2nd Higgs doublet. Compared with the one doublet model, this provides greater freedom for the masses and mixing angle of the scalar mediators, and their coupling to SM fermions. We outline constraints on these models, and discuss Yukawa structures that allow enhanced couplings, yet keep potentially dangerous flavour violating processes under control. We examine the direct detection phenomenology of these models, accounting for interference of the scalar mediators, and interference of different quarks in the nucleus. Regions of parameter space consistent with direct detection measurements are determined.

  18. A toy model for gauge-mediation in intersecting brane models

    International Nuclear Information System (INIS)

    Kumar, Jason

    2009-01-01

    We discuss the phenomenology of a toy intersecting brane model where supersymmetry is dynamically broken in an open-string hidden sector and gauge-mediated to the visible sector. Scalar masses ∼TeV are easily realizable, and R-symmetry is broken. These ideas are easily generalizable to other intersecting brane models.

  19. Mediators and moderators in early intervention research.

    Science.gov (United States)

    Breitborde, Nicholas J K; Srihari, Vinod H; Pollard, Jessica M; Addington, Donald N; Woods, Scott W

    2010-05-01

    The goal of this paper is to provide clarification with regard to the nature of mediator and moderator variables and the statistical methods used to test for the existence of these variables. Particular attention will be devoted to discussing the ways in which the identification of mediator and moderator variables may help to advance the field of early intervention in psychiatry. We completed a literature review of the methodological strategies used to test for mediator and moderator variables. Although several tests for mediator variables are currently available, recent evaluations suggest that tests which directly evaluate the indirect effect are superior. With regard to moderator variables, two approaches ('pick-a-point' and regions of significance) are available, and we provide guidelines with regard to how researchers can determine which approach may be most appropriate to use for their specific study. Finally, we discuss how to evaluate the clinical importance of mediator and moderator relationships as well as the methodology to calculate statistical power for tests of mediation and moderation. Further exploration of mediator and moderator variables may provide valuable information with regard to interventions provided early in the course of a psychiatric illness.

  20. Relapse May Serve as a Mediator Variable in Longitudinal Outcomes in Multiple Sclerosis.

    Science.gov (United States)

    Stone, Lael Anne; Cutter, Gary Raymond; Fisher, Elizabeth; Richert, Nancy; McCartin, Jennifer; Ohayon, Joan; Bash, Craig; McFarland, Henry

    2016-05-01

    Contrast-enhancing lesions (CEL) on magnetic resonance imaging (MRI) are believed to represent inflammatory disease activity in multiple sclerosis (MS), but their relationship to subsequent long-term disability and progression is unclear, particularly at longer time periods such as 8-10 years. Between 1989 and 1994, 111 MS patients were seen at the National Institutes of Health for clinical evaluations and 3 monthly contrast-enhanced MRI scans. Of these, 94 patients were re-evaluated a mean of 8 years later (range 6.1-10.5 years) with a single MRI scan and clinical evaluation. CEL number and volume were determined at baseline and follow-up. The number of relapses was ascertained over the follow-up period and annualized relapse rates were calculated. Other MRI parameters, such as T2 hyperintensity volume, T1 volume, and brain parenchymal fraction, were also calculated. While there was no direct correlation between CEL number or volume at baseline and disability status at follow-up, CEL measures at baseline did correlate with number of relapses observed in the subsequent years, and the number of relapses in turn correlated with subsequent disability as well as transition to progressive MS. While number and volume of CEL at baseline do not directly correlate with disability in the longer term in MS, our data suggest that 1 route to disability involves relapses as a mediator variable in the causal sequence of MS progression from CEL to disability. Further studies using relapse as a mediator variable in a larger data set may be warranted. Copyright © 2015 by the American Society of Neuroimaging.

  1. SPSS and SAS procedures for estimating indirect effects in simple mediation models.

    Science.gov (United States)

    Preacher, Kristopher J; Hayes, Andrew F

    2004-11-01

    Researchers often conduct mediation analysis in order to indirectly assess the effect of a proposed cause on some outcome through a proposed mediator. The utility of mediation analysis stems from its ability to go beyond the merely descriptive to a more functional understanding of the relationships among variables. A necessary component of mediation is a statistically and practically significant indirect effect. Although mediation hypotheses are frequently explored in psychological research, formal significance tests of indirect effects are rarely conducted. After a brief overview of mediation, we argue the importance of directly testing the significance of indirect effects and provide SPSS and SAS macros that facilitate estimation of the indirect effect with a normal theory approach and a bootstrap approach to obtaining confidence intervals, as well as the traditional approach advocated by Baron and Kenny (1986). We hope that this discussion and the macros will enhance the frequency of formal mediation tests in the psychology literature. Electronic copies of these macros may be downloaded from the Psychonomic Society's Web archive at www.psychonomic.org/archive/.

  2. Selecting a model of supersymmetry breaking mediation

    International Nuclear Information System (INIS)

    AbdusSalam, S. S.; Allanach, B. C.; Dolan, M. J.; Feroz, F.; Hobson, M. P.

    2009-01-01

    We study the problem of selecting between different mechanisms of supersymmetry breaking in the minimal supersymmetric standard model using current data. We evaluate the Bayesian evidence of four supersymmetry breaking scenarios: mSUGRA, mGMSB, mAMSB, and moduli mediation. The results show a strong dependence on the dark matter assumption. Using the inferred cosmological relic density as an upper bound, minimal anomaly mediation is at least moderately favored over the CMSSM. Our fits also indicate that evidence for a positive sign of the μ parameter is moderate at best. We present constraints on the anomaly and gauge mediated parameter spaces and some previously unexplored aspects of the dark matter phenomenology of the moduli mediation scenario. We use sparticle searches, indirect observables and dark matter observables in the global fit and quantify robustness with respect to prior choice. We quantify how much information is contained within each constraint.

  3. Variable Selection for Regression Models of Percentile Flows

    Science.gov (United States)

    Fouad, G.

    2017-12-01

    Percentile flows describe the flow magnitude equaled or exceeded for a given percent of time, and are widely used in water resource management. However, these statistics are normally unavailable since most basins are ungauged. Percentile flows of ungauged basins are often predicted using regression models based on readily observable basin characteristics, such as mean elevation. The number of these independent variables is too large to evaluate all possible models. A subset of models is typically evaluated using automatic procedures, like stepwise regression. This ignores a large variety of methods from the field of feature (variable) selection and physical understanding of percentile flows. A study of 918 basins in the United States was conducted to compare an automatic regression procedure to the following variable selection methods: (1) principal component analysis, (2) correlation analysis, (3) random forests, (4) genetic programming, (5) Bayesian networks, and (6) physical understanding. The automatic regression procedure only performed better than principal component analysis. Poor performance of the regression procedure was due to a commonly used filter for multicollinearity, which rejected the strongest models because they had cross-correlated independent variables. Multicollinearity did not decrease model performance in validation because of a representative set of calibration basins. Variable selection methods based strictly on predictive power (numbers 2-5 from above) performed similarly, likely indicating a limit to the predictive power of the variables. Similar performance was also reached using variables selected based on physical understanding, a finding that substantiates recent calls to emphasize physical understanding in modeling for predictions in ungauged basins. The strongest variables highlighted the importance of geology and land cover, whereas widely used topographic variables were the weakest predictors. Variables suffered from a high

  4. Authentic leadership and organizational commitment: the mediating role of positive psychological capital

    International Nuclear Information System (INIS)

    Rego, P.; Pereira Lopes, M.; Nascimento, J.

    2016-01-01

    Purpose: This study analyzes the mediating role of positive psychological capital in the relationship between authentic leadership and organizational commitment. Design/methodology/approach: This quantitative study presents a model in which were considered as variables mediating the relationship between authentic leadership and organizational commitment, the four dimensions of positive psychological capital (optimism, resilience, self-efficacy, hope). Findings: The results showed that positive psychological capital mediates the relationship between authentic leadership and organizational commitment. However, they also indicate that this mediation is only made for three of the four dimensions of positive psychological capital (self-efficacy, hope and optimism). They also show that resilience negatively affects organizational commitment. Originality/value: The value of this study is to strengthen the interest in the study of positive psychological capital as a mediating variable and the importance of development that each of its dimensions and the impact they may have on other variables, as demonstrated by the results. (Author)

  5. Authentic leadership and organizational commitment: the mediating role of positive psychological capital

    Energy Technology Data Exchange (ETDEWEB)

    Rego, P.; Pereira Lopes, M.; Nascimento, J.

    2016-07-01

    Purpose: This study analyzes the mediating role of positive psychological capital in the relationship between authentic leadership and organizational commitment. Design/methodology/approach: This quantitative study presents a model in which were considered as variables mediating the relationship between authentic leadership and organizational commitment, the four dimensions of positive psychological capital (optimism, resilience, self-efficacy, hope). Findings: The results showed that positive psychological capital mediates the relationship between authentic leadership and organizational commitment. However, they also indicate that this mediation is only made for three of the four dimensions of positive psychological capital (self-efficacy, hope and optimism). They also show that resilience negatively affects organizational commitment. Originality/value: The value of this study is to strengthen the interest in the study of positive psychological capital as a mediating variable and the importance of development that each of its dimensions and the impact they may have on other variables, as demonstrated by the results. (Author)

  6. Authentic leadership and organizational commitment: The mediating role of positive psychological capital

    Directory of Open Access Journals (Sweden)

    Paulo Rego

    2016-02-01

    Full Text Available Purpose: This study analyzes the mediating role of positive psychological capital in the relationship between authentic leadership and organizational commitment. Design/methodology/approach: This quantitative study presents a model in which were considered as variables mediating the relationship between authentic leadership and organizational commitment, the four dimensions of positive psychological capital (optimism, resilience, self-efficacy, hope. Findings: The results showed that positive psychological capital mediates the relationship between authentic leadership and organizational commitment. However, they also indicate that this mediation is only made for three of the four dimensions of positive psychological capital (self-efficacy, hope and optimism. They also show that resilience negatively affects organizational commitment. Originality/value: The value of this study is to strengthen the interest in the study of positive psychological capital as a mediating variable and the importance of development that each of its dimensions and the impact they may have on other variables, as demonstrated by the results.

  7. Comparison of methods for the analysis of relatively simple mediation models

    NARCIS (Netherlands)

    Rijnhart, Judith J.M.; Twisk, Jos W.R.; Chinapaw, Mai J.M.; de Boer, Michiel R.; Heymans, Martijn W.

    2017-01-01

    Background/aims Statistical mediation analysis is an often used method in trials, to unravel the pathways underlying the effect of an intervention on a particular outcome variable. Throughout the years, several methods have been proposed, such as ordinary least square (OLS) regression, structural

  8. Preliminary Multi-Variable Parametric Cost Model for Space Telescopes

    Science.gov (United States)

    Stahl, H. Philip; Hendrichs, Todd

    2010-01-01

    This slide presentation reviews creating a preliminary multi-variable cost model for the contract costs of making a space telescope. There is discussion of the methodology for collecting the data, definition of the statistical analysis methodology, single variable model results, testing of historical models and an introduction of the multi variable models.

  9. How to get rid of W: a latent variables approach to modelling spatially lagged variables

    NARCIS (Netherlands)

    Folmer, H.; Oud, J.

    2008-01-01

    In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are

  10. How to get rid of W : a latent variables approach to modelling spatially lagged variables

    NARCIS (Netherlands)

    Folmer, Henk; Oud, Johan

    2008-01-01

    In this paper we propose a structural equation model (SEM) with latent variables to model spatial dependence. Rather than using the spatial weights matrix W, we propose to use latent variables to represent spatial dependence and spillover effects, of which the observed spatially lagged variables are

  11. Internal variability of a 3-D ocean model

    Directory of Open Access Journals (Sweden)

    Bjarne Büchmann

    2016-11-01

    Full Text Available The Defence Centre for Operational Oceanography runs operational forecasts for the Danish waters. The core setup is a 60-layer baroclinic circulation model based on the General Estuarine Transport Model code. At intervals, the model setup is tuned to improve ‘model skill’ and overall performance. It has been an area of concern that the uncertainty inherent to the stochastical/chaotic nature of the model is unknown. Thus, it is difficult to state with certainty that a particular setup is improved, even if the computed model skill increases. This issue also extends to the cases, where the model is tuned during an iterative process, where model results are fed back to improve model parameters, such as bathymetry.An ensemble of identical model setups with slightly perturbed initial conditions is examined. It is found that the initial perturbation causes the models to deviate from each other exponentially fast, causing differences of several PSUs and several kelvin within a few days of simulation. The ensemble is run for a full year, and the long-term variability of salinity and temperature is found for different regions within the modelled area. Further, the developing time scale is estimated for each region, and great regional differences are found – in both variability and time scale. It is observed that periods with very high ensemble variability are typically short-term and spatially limited events.A particular event is examined in detail to shed light on how the ensemble ‘behaves’ in periods with large internal model variability. It is found that the ensemble does not seem to follow any particular stochastic distribution: both the ensemble variability (standard deviation or range as well as the ensemble distribution within that range seem to vary with time and place. Further, it is observed that a large spatial variability due to mesoscale features does not necessarily correlate to large ensemble variability. These findings bear

  12. Generalized latent variable modeling multilevel, longitudinal, and structural equation models

    CERN Document Server

    Skrondal, Anders; Rabe-Hesketh, Sophia

    2004-01-01

    This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models, and structural equation models.

  13. Perceived Workplace Culture as an Antecedent of Job Stress: The Mediating Role of Work-Family Conflict

    OpenAIRE

    Aminah Ahmad; Zoharah Omar

    2010-01-01

    Problem statement: Few studies have tested the mediating effect of work-family conflict on the relationship between workplace culture and job stress. Approach: This study tested a mediation model consisting of job stress as the dependent variable, perceived family-supportive work culture as the independent variable and work-family conflict as the mediator. Data were gathered from 693 employees from private service organizations in the Klang Valley, Malaysia, using self-administered questionna...

  14. "Does anger regulation mediate the discrimination-mental health link among Mexican-origin adolescents? A longitudinal mediation analysis using multilevel modeling": Correction to Park et al. (2016).

    Science.gov (United States)

    2017-02-01

    Reports an error in "Does Anger Regulation Mediate the Discrimination-Mental Health Link Among Mexican-Origin Adolescents? A Longitudinal Mediation Analysis Using Multilevel Modeling" by Irene J. K. Park, Lijuan Wang, David R. Williams and Margarita Alegría ( Developmental Psychology , Advanced Online Publication, Nov 28, 2016, np). In the article, there were several typographical errors in the Recruitment and Procedures section. The percentage of mothers who responded to survey items should have been 99.3%. Additionally, the youths surveyed at T2 and T3 should have been n=246 . Accordingly, the percentage of youths surveyed in T2 and T3 should have been 91.4% and the percentage of mothers surveyed at T2 and T3 should have been 90.7%. Finally, the youths missing at T2 should have been n= 23, and therefore the attrition rate for youth participants should have been 8.6. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2016-57671-001.) Although prior research has consistently documented the association between racial/ethnic discrimination and poor mental health outcomes, the mechanisms that underlie this link are still unclear. The present 3-wave longitudinal study tested the mediating role of anger regulation in the discrimination-mental health link among 269 Mexican-origin adolescents ( M age = 14.1 years, SD = 1.6; 57% girls), 12 to 17 years old. Three competing anger regulation variables were tested as potential mediators: outward anger expression, anger suppression, and anger control. Longitudinal mediation analyses were conducted using multilevel modeling that disaggregated within-person effects from between-person effects. Results indicated that outward anger expression was a significant mediator; anger suppression and anger control were not significant mediators. Within a given individual, greater racial/ethnic discrimination was associated with more frequent outward anger expression. In turn

  15. Defining a Family of Cognitive Diagnosis Models Using Log-Linear Models with Latent Variables

    Science.gov (United States)

    Henson, Robert A.; Templin, Jonathan L.; Willse, John T.

    2009-01-01

    This paper uses log-linear models with latent variables (Hagenaars, in "Loglinear Models with Latent Variables," 1993) to define a family of cognitive diagnosis models. In doing so, the relationship between many common models is explicitly defined and discussed. In addition, because the log-linear model with latent variables is a general model for…

  16. A mediational model of self-esteem and social problem-solving in anorexia nervosa.

    Science.gov (United States)

    Paterson, Gillian; Power, Kevin; Collin, Paula; Greirson, David; Yellowlees, Alex; Park, Katy

    2011-01-01

    Poor problem-solving and low self-esteem are frequently cited as significant factors in the development and maintenance of anorexia nervosa. The current study examines the multi-dimensional elements of these measures and postulates a model whereby self-esteem mediates the relationship between social problems-solving and anorexic pathology and considers the implications of this pathway. Fifty-five inpatients with a diagnosis of anorexia nervosa and 50 non-clinical controls completed three standardised multi-dimensional questionnaires pertaining to social problem-solving, self-esteem and eating pathology. Significant differences were yielded between clinical and non-clinical samples on all measures. Within the clinical group, elements of social problem-solving most significant to anorexic pathology were positive problem orientation, negative problem orientation and avoidance. Components of self-esteem most significant to anorexic pathology were eating, weight and shape concern but not eating restraint. The mediational model was upheld with social problem-solving impacting on anorexic pathology through the existence of low self-esteem. Problem orientation, that is, the cognitive processes of social problem-solving appear to be more significant than problem-solving methods in individuals with anorexia nervosa. Negative perceptions of eating, weight and shape appear to impact on low self-esteem but level of restriction does not. Finally, results indicate that self-esteem is a significant factor in the development and execution of positive or negative social problem-solving in individuals with anorexia nervosa by mediating the relationship between those two variables. Copyright © 2010 John Wiley & Sons, Ltd and Eating Disorders Association.

  17. On the explaining-away phenomenon in multivariate latent variable models.

    Science.gov (United States)

    van Rijn, Peter; Rijmen, Frank

    2015-02-01

    Many probabilistic models for psychological and educational measurements contain latent variables. Well-known examples are factor analysis, item response theory, and latent class model families. We discuss what is referred to as the 'explaining-away' phenomenon in the context of such latent variable models. This phenomenon can occur when multiple latent variables are related to the same observed variable, and can elicit seemingly counterintuitive conditional dependencies between latent variables given observed variables. We illustrate the implications of explaining away for a number of well-known latent variable models by using both theoretical and real data examples. © 2014 The British Psychological Society.

  18. On the (In)Validity of Tests of Simple Mediation: Threats and Solutions

    OpenAIRE

    Pek, Jolynn; Hoyle, Rick H.

    2016-01-01

    Mediation analysis is a popular framework for identifying underlying mechanisms in social psychology. In the context of simple mediation, we review and discuss the implications of three facets of mediation analysis: (a) conceptualization of the relations between the variables, (b) statistical approaches, and (c) relevant elements of design. We also highlight the issue of equivalent models that are inherent in simple mediation. The extent to which results are meaningful stem directly from choi...

  19. A biophysical model of endocannabinoid-mediated short term depression in hippocampal inhibition.

    Directory of Open Access Journals (Sweden)

    Margarita Zachariou

    Full Text Available Memories are believed to be represented in the synaptic pathways of vastly interconnected networks of neurons. The plasticity of synapses, that is, their strengthening and weakening depending on neuronal activity, is believed to be the basis of learning and establishing memories. An increasing number of studies indicate that endocannabinoids have a widespread action on brain function through modulation of synaptic transmission and plasticity. Recent experimental studies have characterised the role of endocannabinoids in mediating both short- and long-term synaptic plasticity in various brain regions including the hippocampus, a brain region strongly associated with cognitive functions, such as learning and memory. Here, we present a biophysically plausible model of cannabinoid retrograde signalling at the synaptic level and investigate how this signalling mediates depolarisation induced suppression of inhibition (DSI, a prominent form of short-term synaptic depression in inhibitory transmission in hippocampus. The model successfully captures many of the key characteristics of DSI in the hippocampus, as observed experimentally, with a minimal yet sufficient mathematical description of the major signalling molecules and cascades involved. More specifically, this model serves as a framework to test hypotheses on the factors determining the variability of DSI and investigate under which conditions it can be evoked. The model reveals the frequency and duration bands in which the post-synaptic cell can be sufficiently stimulated to elicit DSI. Moreover, the model provides key insights on how the state of the inhibitory cell modulates DSI according to its firing rate and relative timing to the post-synaptic activation. Thus, it provides concrete suggestions to further investigate experimentally how DSI modulates and is modulated by neuronal activity in the brain. Importantly, this model serves as a stepping stone for future deciphering of the role of

  20. Mediation analysis in nursing research: a methodological review.

    Science.gov (United States)

    Liu, Jianghong; Ulrich, Connie

    2016-12-01

    Mediation statistical models help clarify the relationship between independent predictor variables and dependent outcomes of interest by assessing the impact of third variables. This type of statistical analysis is applicable for many clinical nursing research questions, yet its use within nursing remains low. Indeed, mediational analyses may help nurse researchers develop more effective and accurate prevention and treatment programs as well as help bridge the gap between scientific knowledge and clinical practice. In addition, this statistical approach allows nurse researchers to ask - and answer - more meaningful and nuanced questions that extend beyond merely determining whether an outcome occurs. Therefore, the goal of this paper is to provide a brief tutorial on the use of mediational analyses in clinical nursing research by briefly introducing the technique and, through selected empirical examples from the nursing literature, demonstrating its applicability in advancing nursing science.

  1. Depression and pain: testing of serial multiple mediators

    Directory of Open Access Journals (Sweden)

    Wongpakaran T

    2016-07-01

    Full Text Available Tinakon Wongpakaran,1 Nahathai Wongpakaran,1 Sitthinant Tanchakvaranont,2 Putipong Bookkamana,3 Manee Pinyopornpanish,1 Kamonporn Wannarit,4 Sirina Satthapisit,5 Daochompu Nakawiro,6 Thanita Hiranyatheb,6 Kulvadee Thongpibul7 1Department of Psychiatry, Faculty of Medicine, Chiang Mai University, Chiang Mai, Kingdom of Thailand; 2Department of Psychiatry, Queen Savang Vadhana Memorial Hospital, Chonburi, Kingdom of Thailand; 3Department of Statistics, Faculty of Science, Chiang Mai University, Chiang Mai, Kingdom of Thailand; 4Department of Psychiatry, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Kingdom of Thailand; 5Department of Psychiatry, Khon Kaen Regional Hospital, Khon Kaen, Kingdom of Thailand; 6Department of Psychiatry, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Kingdom of Thailand; 7Department of Psychology, Faculty of Humanities, Chiang Mai University, Chiang Mai, Kingdom of Thailand Purpose: Despite the fact that pain is related to depression, few studies have been conducted to investigate the variables that mediate between the two conditions. In this study, the authors explored the following mediators: cognitive function, self-sacrificing interpersonal problems, and perception of stress, and the effects they had on pain symptoms among patients with depressive disorders.Participants and methods: An analysis was performed on the data of 346 participants with unipolar depressive disorders. The 17-item Hamilton Depression Rating Scale, Mini-Mental State Examination, the pain subscale of the health-related quality of life (SF-36, the self-sacrificing subscale of the Inventory of Interpersonal Problems, and the Perceived Stress Scale were used. Parallel multiple mediator and serial multiple mediator models were used. An alternative model regarding the effect of self-sacrificing on pain was also proposed.Results: Perceived stress, self-sacrificing interpersonal style, and cognitive

  2. Single-Level and Multilevel Mediation Analysis

    Science.gov (United States)

    Tofighi, Davood; Thoemmes, Felix

    2014-01-01

    Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural…

  3. Linear latent variable models: the lava-package

    DEFF Research Database (Denmark)

    Holst, Klaus Kähler; Budtz-Jørgensen, Esben

    2013-01-01

    are implemented including robust standard errors for clustered correlated data, multigroup analyses, non-linear parameter constraints, inference with incomplete data, maximum likelihood estimation with censored and binary observations, and instrumental variable estimators. In addition an extensive simulation......An R package for specifying and estimating linear latent variable models is presented. The philosophy of the implementation is to separate the model specification from the actual data, which leads to a dynamic and easy way of modeling complex hierarchical structures. Several advanced features...

  4. A General Model for Testing Mediation and Moderation Effects

    Science.gov (United States)

    MacKinnon, David P.

    2010-01-01

    This paper describes methods for testing mediation and moderation effects in a dataset, both together and separately. Investigations of this kind are especially valuable in prevention research to obtain information on the process by which a program achieves its effects and whether the program is effective for subgroups of individuals. A general model that simultaneously estimates mediation and moderation effects is presented, and the utility of combining the effects into a single model is described. Possible effects of interest in the model are explained, as are statistical methods to assess these effects. The methods are further illustrated in a hypothetical prevention program example. PMID:19003535

  5. Preventing and De-Escalating Ethical Conflict: A Communication-Training Mediation Model.

    Science.gov (United States)

    Levin, Tomer T; Parker, Patricia A

    2015-01-01

    While ethical conflicts in the provision of healthcare are common, the current third-party mediator model is limited by a lack of expert ethical mediators, who are often not on site when conflict escalates. In order to improve clinical outcomes in situations such as conflicts at the end of life, we suggest that clinicians-physicians, nurses and social workers-be trained to prevent and de-escalate emerging conflicts. This can be achieved using a mediation model framed by a communication-training approach. A case example is presented and the model is discussed. The implication of this preventative/early intervention model for improving clinical outcomes, in particular end-of life conflict, is considered. Copyright 2015 The Journal of Clinical Ethics. All rights reserved.

  6. Gait variability: methods, modeling and meaning

    Directory of Open Access Journals (Sweden)

    Hausdorff Jeffrey M

    2005-07-01

    Full Text Available Abstract The study of gait variability, the stride-to-stride fluctuations in walking, offers a complementary way of quantifying locomotion and its changes with aging and disease as well as a means of monitoring the effects of therapeutic interventions and rehabilitation. Previous work has suggested that measures of gait variability may be more closely related to falls, a serious consequence of many gait disorders, than are measures based on the mean values of other walking parameters. The Current JNER series presents nine reports on the results of recent investigations into gait variability. One novel method for collecting unconstrained, ambulatory data is reviewed, and a primer on analysis methods is presented along with a heuristic approach to summarizing variability measures. In addition, the first studies of gait variability in animal models of neurodegenerative disease are described, as is a mathematical model of human walking that characterizes certain complex (multifractal features of the motor control's pattern generator. Another investigation demonstrates that, whereas both healthy older controls and patients with a higher-level gait disorder walk more slowly in reduced lighting, only the latter's stride variability increases. Studies of the effects of dual tasks suggest that the regulation of the stride-to-stride fluctuations in stride width and stride time may be influenced by attention loading and may require cognitive input. Finally, a report of gait variability in over 500 subjects, probably the largest study of this kind, suggests how step width variability may relate to fall risk. Together, these studies provide new insights into the factors that regulate the stride-to-stride fluctuations in walking and pave the way for expanded research into the control of gait and the practical application of measures of gait variability in the clinical setting.

  7. Multi-wheat-model ensemble responses to interannual climatic variability

    DEFF Research Database (Denmark)

    Ruane, A C; Hudson, N I; Asseng, S

    2016-01-01

    We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and ......-term warming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.......We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981–2010 grain yield, and we...... evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal...

  8. Work Demands-Burnout and Job Engagement-Job Satisfaction Relationships: Teamwork as a Mediator and Moderator.

    Science.gov (United States)

    Mijakoski, Dragan; Karadzinska-Bislimovska, Jovanka; Basarovska, Vera; Minov, Jordan; Stoleski, Sasho; Angeleska, Nada; Atanasovska, Aneta

    2015-03-15

    Few studies have examined teamwork as mediator and moderator of work demands-burnout and job engagement-job satisfaction relationships in healthcare workers (HCWs) in South-East Europe. To assess mediation and moderation effect of teamwork on the relationship between independent (work demands or job engagement) and dependent (burnout or job satisfaction) variables. Work demands, burnout, job engagement, and job satisfaction were measured with Hospital Experience Scale, Maslach Burnout Inventory, Utrecht Work Engagement Scale, and Job Satisfaction Survey, respectively. Hospital Survey on Patient Safety Culture was used for assessment of teamwork. In order to examine role of teamwork as a mediating variable we fit series of regression models for burnout and job satisfaction. We also fit regression models predicting outcome (burnout or job satisfaction) from predictor (work demands or job engagement) and moderator (teamwork) variable. Teamwork was partial mediator of work demands-burnout relationship and full mediator of job engagement-job satisfaction relationship. We found that only job engagement-job satisfaction relationship was moderated by teamwork. Occupational health services should target detection of burnout in HCWs and implementation of organizational interventions in hospitals, taking into account findings that teamwork predicted reduced burnout and higher job satisfaction.

  9. Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

    Science.gov (United States)

    Ruane, Alex C.; Hudson, Nicholas I.; Asseng, Senthold; Camarrano, Davide; Ewert, Frank; Martre, Pierre; Boote, Kenneth J.; Thorburn, Peter J.; Aggarwal, Pramod K.; Angulo, Carlos

    2016-01-01

    We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

  10. Are revised models better models? A skill score assessment of regional interannual variability

    Science.gov (United States)

    Sperber, Kenneth R.; Participating AMIP Modelling Groups

    1999-05-01

    Various skill scores are used to assess the performance of revised models relative to their original configurations. The interannual variability of all-India, Sahel and Nordeste rainfall and summer monsoon windshear is examined in integrations performed under the experimental design of the Atmospheric Model Intercomparison Project. For the indices considered, the revised models exhibit greater fidelity at simulating the observed interannual variability. Interannual variability of all-India rainfall is better simulated by models that have a more realistic rainfall climatology in the vicinity of India, indicating the beneficial effect of reducing systematic model error.

  11. Mediation designs for tobacco prevention research

    Science.gov (United States)

    MacKinnon, David P.; Taborga, Marcia P.; Morgan-Lopez, Antonio A.

    2010-01-01

    This paper describes research designs and statistical analyses to investigate how tobacco prevention programs achieve their effects on tobacco use. A theoretical approach to program development and evaluation useful for any prevention program guides the analysis. The theoretical approach focuses on action theory for how the program affects mediating variables and on conceptual theory for how mediating variables are related to tobacco use. Information on the mediating mechanisms by which tobacco prevention programs achieve effects is useful for the development of efficient programs and provides a test of the theoretical basis of prevention efforts. Examples of these potential mediating mechanisms are described including mediated effects through attitudes, social norms, beliefs about positive consequences, and accessibility to tobacco. Prior research provides evidence that changes in social norms are a critical mediating mechanism for successful tobacco prevention. Analysis of mediating variables in single group designs with multiple mediators are described as well as multiple group randomized designs which are the most likely to accurately uncover important mediating mechanisms. More complicated dismantling and constructive designs are described and illustrated based on current findings from tobacco research. Mediation analysis for categorical outcomes and more complicated statistical methods are outlined. PMID:12324176

  12. Coevolution of variability models and related software artifacts

    DEFF Research Database (Denmark)

    Passos, Leonardo; Teixeira, Leopoldo; Dinztner, Nicolas

    2015-01-01

    models coevolve with other artifact types, we study a large and complex real-world variant-rich software system: the Linux kernel. Specifically, we extract variability-coevolution patterns capturing changes in the variability model of the Linux kernel with subsequent changes in Makefiles and C source...

  13. From Training to Organizational Behavior: A Mediation Model through Absorptive and Innovative Capacities.

    Science.gov (United States)

    Yáñez-Araque, Benito; Hernández-Perlines, Felipe; Moreno-Garcia, Juan

    2017-01-01

    The training of human resources improves business performance: myth or reality? While the literature has extensively addressed this issue, the transfer that occurs from training to performance still remains unresolved. The present study suggests an empirical solution to this gap, through a multiple mediation model of dynamic capabilities. Accordingly, the study makes a major contribution to the effectiveness of an organizational-level training: the "true" relationship between training and performance is mediated by absorptive and innovative capacities. It is difficult from training to directly affect the results: it must be done through a chain of intermediate variables. Training can be argued to be indirectly related to performance, through absorptive capacity in the first place, and innovative capacity in the second, sequentially in this order (three-path mediated effect). Of all immediate relationships received by performance, its explained variance is achieved partly via absorptive capacity and partly via innovation. The direct relationship through training is not significant and only explains a small percentage of the variance in performance. These results have been corroborated by combining two methods of analysis: PLS-SEM and fsQCA, using data from an online survey. This dual methodology in the study of the same phenomenon allows overcoming the limitations of each method, which would not have been possible with a single methodological approach, and confirming the findings obtained by any of them.

  14. Assessing Mediation in Dyadic Data Using the Actor-Partner Interdependence Model

    Science.gov (United States)

    Ledermann, Thomas; Macho, Siegfried; Kenny, David A.

    2011-01-01

    The assessment of mediation in dyadic data is an important issue if researchers are to test process models. Using an extended version of the actor-partner interdependence model the estimation and testing of mediation is complex, especially when dyad members are distinguishable (e.g., heterosexual couples). We show how the complexity of the model…

  15. Flavor changing processes in supersymmetric models with hybrid gauge- and gravity-mediation

    International Nuclear Information System (INIS)

    Hiller, Gudrun; Hochberg, Yonit; Nir, Yosef

    2009-01-01

    We consider supersymmetric models where gauge mediation provides the dominant contributions to the soft supersymmetry breaking terms while gravity mediation provides sub-dominant yet non-negligible contributions. We further assume that the gravity-mediated contributions are subject to selection rules that follow from a Froggatt-Nielsen symmetry. This class of models constitutes an example of viable and natural non-minimally flavor violating models. The constraints from K 0 -K-bar 0 mixing imply that the modifications to the Standard Model predictions for B d -B-bar d and B s - B-bar s mixing are generically at most at the percent level, but can be of order ten percent for large tan β. The modifications for D 0 -D-bar 0 mixing are generically at most of order a few percent, but in a special subclass of models they can be of order one. We point out ΔB = 1 processes relevant for flavor violation in hybrid mediation.

  16. Mediator and moderator effects in developmental and behavioral pediatric research.

    Science.gov (United States)

    Rose, Brigid M; Holmbeck, Grayson N; Coakley, Rachael Millstein; Franks, Elizabeth A

    2004-02-01

    The terms mediation and moderation are defined and clarified with particular emphasis on the role of mediational and moderational analyses in developmental and behavioral pediatric research. The article highlights the applicability of mediational and moderational analyses to longitudinal, intervention, and risk and protective factor research, and it provides basic information about how these analyses might be conducted. Also included is a discussion of various ways that both mediator and moderator variables can be incorporated into a single model. The article concludes with extended examples of both types of analyses using a longitudinal pediatric study for illustration. The article provides recommendations for applying mediational and moderational research in clinical practice.

  17. Variable selection in Logistic regression model with genetic algorithm.

    Science.gov (United States)

    Zhang, Zhongheng; Trevino, Victor; Hoseini, Sayed Shahabuddin; Belciug, Smaranda; Boopathi, Arumugam Manivanna; Zhang, Ping; Gorunescu, Florin; Subha, Velappan; Dai, Songshi

    2018-02-01

    Variable or feature selection is one of the most important steps in model specification. Especially in the case of medical-decision making, the direct use of a medical database, without a previous analysis and preprocessing step, is often counterproductive. In this way, the variable selection represents the method of choosing the most relevant attributes from the database in order to build a robust learning models and, thus, to improve the performance of the models used in the decision process. In biomedical research, the purpose of variable selection is to select clinically important and statistically significant variables, while excluding unrelated or noise variables. A variety of methods exist for variable selection, but none of them is without limitations. For example, the stepwise approach, which is highly used, adds the best variable in each cycle generally producing an acceptable set of variables. Nevertheless, it is limited by the fact that it commonly trapped in local optima. The best subset approach can systematically search the entire covariate pattern space, but the solution pool can be extremely large with tens to hundreds of variables, which is the case in nowadays clinical data. Genetic algorithms (GA) are heuristic optimization approaches and can be used for variable selection in multivariable regression models. This tutorial paper aims to provide a step-by-step approach to the use of GA in variable selection. The R code provided in the text can be extended and adapted to other data analysis needs.

  18. Prototype Willingness Model Drinking Cognitions Mediate Personalized Normative Feedback Efficacy.

    Science.gov (United States)

    Lewis, Melissa A; Litt, Dana M; Tomkins, Mary; Neighbors, Clayton

    2017-05-01

    Personalized normative feedback (PNF) interventions have been shown to be efficacious at reducing college student drinking. Because descriptive norms have been shown to mediate PNF efficacy, the current study focused on examining additional prototype willingness model social reaction cognitions, namely, prototypes and willingness, as mediators of intervention efficacy. We expected the PNF interventions to be associated with increased prototype favorability of students who do not drink, which would in turn be associated with decreased willingness to drink and subsequently, less drinking. The current study included 622 college students (53.2% women; 62% Caucasian) who reported one or more heavy drinking episodes in the past month and completed baseline and three-month follow-up assessments. As posited by the framework of the prototype willingness model, sequential mediation analyses were conducted to evaluate increases in abstainer prototype favorability on willingness on drinking, and subsequently willingness to drink on drinking behavior. Mediation results revealed significant indirect effects of PNF on three-month drinking through three-month prototypes and willingness, indicating that the social reaction pathway of the prototype willingness model was supported. Findings have important implications for PNF interventions aiming to reduce high-risk drinking among college students. Study findings suggest that we should consider looking at additional socially-based mediators of PNF efficacy in addition to perceived descriptive norms.

  19. Gauge vs. gravity mediation in models with anomalous U(1)'s

    International Nuclear Information System (INIS)

    Dudas, E.; Mambrini, Y.; Romagnoni, A.; Trapletti, M.; Pokorski, S.

    2009-01-01

    In an attempt to implement gauge mediation in string theory, we study string effective supergravity models of supersymmetry breaking, containing anomalous gauge factors. We discuss subtleties related to gauge invariance and the stabilization of the Green-Schwarz moduli, which set non-trivial constraints on the transmission of supersymmetry breaking to MSSM via gauge interactions. Given those constraints, it is difficult to obtain the dominance of gauge mediation over gravity mediation. Furthermore, generically the gauge contributions to soft terms contain additional non-standard terms coming from D-term contributions. Motivated by this, we study the phenomenology of recently proposed hybrid models, where gravity and gauge mediations compete at the GUT scale, and show that such a scenario can respect WMAP constraints and would be easily testable at LHC.

  20. Improved variable reduction in partial least squares modelling by Global-Minimum Error Uninformative-Variable Elimination.

    Science.gov (United States)

    Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C

    2017-08-22

    The calibration performance of Partial Least Squares regression (PLS) can be improved by eliminating uninformative variables. For PLS, many variable elimination methods have been developed. One is the Uninformative-Variable Elimination for PLS (UVE-PLS). However, the number of variables retained by UVE-PLS is usually still large. In UVE-PLS, variable elimination is repeated as long as the root mean squared error of cross validation (RMSECV) is decreasing. The set of variables in this first local minimum is retained. In this paper, a modification of UVE-PLS is proposed and investigated, in which UVE is repeated until no further reduction in variables is possible, followed by a search for the global RMSECV minimum. The method is called Global-Minimum Error Uninformative-Variable Elimination for PLS, denoted as GME-UVE-PLS or simply GME-UVE. After each iteration, the predictive ability of the PLS model, built with the remaining variable set, is assessed by RMSECV. The variable set with the global RMSECV minimum is then finally selected. The goal is to obtain smaller sets of variables with similar or improved predictability than those from the classical UVE-PLS method. The performance of the GME-UVE-PLS method is investigated using four data sets, i.e. a simulated set, NIR and NMR spectra, and a theoretical molecular descriptors set, resulting in twelve profile-response (X-y) calibrations. The selective and predictive performances of the models resulting from GME-UVE-PLS are statistically compared to those from UVE-PLS and 1-step UVE, one-sided paired t-tests. The results demonstrate that variable reduction with the proposed GME-UVE-PLS method, usually eliminates significantly more variables than the classical UVE-PLS, while the predictive abilities of the resulting models are better. With GME-UVE-PLS, a lower number of uninformative variables, without a chemical meaning for the response, may be retained than with UVE-PLS. The selectivity of the classical UVE method

  1. Simplified dark matter models with a spin-2 mediator at the LHC

    Energy Technology Data Exchange (ETDEWEB)

    Kraml, Sabine [Universite Grenoble-Alpes, CNRS/IN2P3, Laboratoire de Physique Subatomique et de Cosmologie, Grenoble (France); Laa, Ursula [Universite Grenoble-Alpes, CNRS/IN2P3, Laboratoire de Physique Subatomique et de Cosmologie, Grenoble (France); LAPTh, Universite Savoie Mont Blanc, CNRS, B.P.110, Annecy Cedex (France); Mawatari, Kentarou [Universite Grenoble-Alpes, CNRS/IN2P3, Laboratoire de Physique Subatomique et de Cosmologie, Grenoble (France); Theoretische Natuurkunde and IIHE/ELEM, Vrije Universiteit Brussel, and International Solvay Institutes, Brussels (Belgium); Yamashita, Kimiko [Ochanomizu University, Department of Physics, Graduate School of Humanities and Sciences, and Program for Leading Graduate Schools, Tokyo (Japan)

    2017-05-15

    We consider simplified dark matter models where a dark matter candidate couples to the standard model (SM) particles via an s-channel spin-2 mediator, and study constraints on the model parameter space from the current LHC data. Our focus lies on the complementarity among different searches, in particular monojet and multijet plus missing-energy searches and resonance searches. For universal couplings of the mediator to SM particles, missing-energy searches can give stronger constraints than WW, ZZ, dijet, dihiggs, t anti t, b anti b resonance searches in the low-mass region and/or when the coupling of the mediator to dark matter is much larger than its couplings to SM particles. The strongest constraints, however, come from diphoton and dilepton resonance searches. Only if these modes are suppressed, missing-energy searches can be competitive in constraining dark matter models with a spin-2 mediator. (orig.)

  2. Simplified dark matter models with a spin-2 mediator at the LHC

    International Nuclear Information System (INIS)

    Kraml, Sabine; Laa, Ursula; Mawatari, Kentarou; Yamashita, Kimiko

    2017-01-01

    We consider simplified dark matter models where a dark matter candidate couples to the standard model (SM) particles via an s-channel spin-2 mediator, and study constraints on the model parameter space from the current LHC data. Our focus lies on the complementarity among different searches, in particular monojet and multijet plus missing-energy searches and resonance searches. For universal couplings of the mediator to SM particles, missing-energy searches can give stronger constraints than WW, ZZ, dijet, dihiggs, t anti t, b anti b resonance searches in the low-mass region and/or when the coupling of the mediator to dark matter is much larger than its couplings to SM particles. The strongest constraints, however, come from diphoton and dilepton resonance searches. Only if these modes are suppressed, missing-energy searches can be competitive in constraining dark matter models with a spin-2 mediator. (orig.)

  3. On the (In)Validity of Tests of Simple Mediation: Threats and Solutions

    Science.gov (United States)

    Pek, Jolynn; Hoyle, Rick H.

    2015-01-01

    Mediation analysis is a popular framework for identifying underlying mechanisms in social psychology. In the context of simple mediation, we review and discuss the implications of three facets of mediation analysis: (a) conceptualization of the relations between the variables, (b) statistical approaches, and (c) relevant elements of design. We also highlight the issue of equivalent models that are inherent in simple mediation. The extent to which results are meaningful stem directly from choices regarding these three facets of mediation analysis. We conclude by discussing how mediation analysis can be better applied to examine causal processes, highlight the limits of simple mediation, and make recommendations for better practice. PMID:26985234

  4. Causal Mediation Analysis of Survival Outcome with Multiple Mediators.

    Science.gov (United States)

    Huang, Yen-Tsung; Yang, Hwai-I

    2017-05-01

    Mediation analyses have been a popular approach to investigate the effect of an exposure on an outcome through a mediator. Mediation models with multiple mediators have been proposed for continuous and dichotomous outcomes. However, development of multimediator models for survival outcomes is still limited. We present methods for multimediator analyses using three survival models: Aalen additive hazard models, Cox proportional hazard models, and semiparametric probit models. Effects through mediators can be characterized by path-specific effects, for which definitions and identifiability assumptions are provided. We derive closed-form expressions for path-specific effects for the three models, which are intuitively interpreted using a causal diagram. Mediation analyses using Cox models under the rare-outcome assumption and Aalen additive hazard models consider effects on log hazard ratio and hazard difference, respectively; analyses using semiparametric probit models consider effects on difference in transformed survival time and survival probability. The three models were applied to a hepatitis study where we investigated effects of hepatitis C on liver cancer incidence mediated through baseline and/or follow-up hepatitis B viral load. The three methods show consistent results on respective effect scales, which suggest an adverse estimated effect of hepatitis C on liver cancer not mediated through hepatitis B, and a protective estimated effect mediated through the baseline (and possibly follow-up) of hepatitis B viral load. Causal mediation analyses of survival outcome with multiple mediators are developed for additive hazard and proportional hazard and probit models with utility demonstrated in a hepatitis study.

  5. A Mediated Moderation Model of Conformative Peer Bullying

    Science.gov (United States)

    Cho, Yoonju; Chung, Ock-Boon

    2012-01-01

    We investigated the relationship between conformative peer bullying and issues of peer conformity among adolescents. This relationship is examined through the establishment of a mediated moderation model for conformative peer bullying using structural equation modeling in a sample of 391 second-year middle school students in Seoul, South Korea. We…

  6. From Transition Systems to Variability Models and from Lifted Model Checking Back to UPPAAL

    DEFF Research Database (Denmark)

    Dimovski, Aleksandar; Wasowski, Andrzej

    2017-01-01

    efficient lifted (family-based) model checking for real-time variability models. This reduces the cost of maintaining specialized family-based real-time model checkers. Real-time variability models can be model checked using the standard UPPAAL. We have implemented abstractions as syntactic source...

  7. Anxiety and burnout in young athletes: The mediating role of cognitive appraisal.

    Science.gov (United States)

    Gomes, A R; Faria, S; Vilela, C

    2017-12-01

    This study tested the relationship between trait anxiety, cognitive appraisal, and athletes' burnout proposing two hypotheses: (a) there is a direct relationship between athletes' trait anxiety and cognitive appraisal and burnout, and (b) cognitive appraisal mediates the relationship between trait anxiety and burnout, and this mediation occurs despite the competitive level and sport records of athletes. The study included 673 young athletes and provided measures of trait anxiety, cognitive appraisal, and burnout. Structural equation modeling indicated that cognitive appraisal mediates the relationship between trait anxiety and burnout, confirming hypothesis 2, and this model provided better fit than the direct model of hypothesis 1. However, the mediation also indicated that the direct relationship between trait anxiety and burnout should be considered. The mediating model was invariant according to competitive levels and sport records. In conclusion, cognitive appraisal is an important variable in explaining athletes' burnout. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  8. Causal mediation analysis with a binary outcome and multiple continuous or ordinal mediators: Simulations and application to an alcohol intervention.

    Science.gov (United States)

    Nguyen, Trang Quynh; Webb-Vargas, Yenny; Koning, Ina M; Stuart, Elizabeth A

    We investigate a method to estimate the combined effect of multiple continuous/ordinal mediators on a binary outcome: 1) fit a structural equation model with probit link for the outcome and identity/probit link for continuous/ordinal mediators, 2) predict potential outcome probabilities, and 3) compute natural direct and indirect effects. Step 2 involves rescaling the latent continuous variable underlying the outcome to address residual mediator variance/covariance. We evaluate the estimation of risk-difference- and risk-ratio-based effects (RDs, RRs) using the ML, WLSMV and Bayes estimators in Mplus. Across most variations in path-coefficient and mediator-residual-correlation signs and strengths, and confounding situations investigated, the method performs well with all estimators, but favors ML/WLSMV for RDs with continuous mediators, and Bayes for RRs with ordinal mediators. Bayes outperforms WLSMV/ML regardless of mediator type when estimating RRs with small potential outcome probabilities and in two other special cases. An adolescent alcohol prevention study is used for illustration.

  9. Spatial variability and parametric uncertainty in performance assessment models

    International Nuclear Information System (INIS)

    Pensado, Osvaldo; Mancillas, James; Painter, Scott; Tomishima, Yasuo

    2011-01-01

    The problem of defining an appropriate treatment of distribution functions (which could represent spatial variability or parametric uncertainty) is examined based on a generic performance assessment model for a high-level waste repository. The generic model incorporated source term models available in GoldSim ® , the TDRW code for contaminant transport in sparse fracture networks with a complex fracture-matrix interaction process, and a biosphere dose model known as BDOSE TM . Using the GoldSim framework, several Monte Carlo sampling approaches and transport conceptualizations were evaluated to explore the effect of various treatments of spatial variability and parametric uncertainty on dose estimates. Results from a model employing a representative source and ensemble-averaged pathway properties were compared to results from a model allowing for stochastic variation of transport properties along streamline segments (i.e., explicit representation of spatial variability within a Monte Carlo realization). We concluded that the sampling approach and the definition of an ensemble representative do influence consequence estimates. In the examples analyzed in this paper, approaches considering limited variability of a transport resistance parameter along a streamline increased the frequency of fast pathways resulting in relatively high dose estimates, while those allowing for broad variability along streamlines increased the frequency of 'bottlenecks' reducing dose estimates. On this basis, simplified approaches with limited consideration of variability may suffice for intended uses of the performance assessment model, such as evaluation of site safety. (author)

  10. Mediating mechanisms of a military Web-based alcohol intervention.

    Science.gov (United States)

    Williams, Jason; Herman-Stahl, Mindy; Calvin, Sara L; Pemberton, Michael; Bradshaw, Michael

    2009-03-01

    This study explored the mediating mechanisms of two Web-based alcohol interventions in a sample of active duty United States military personnel. Personnel were recruited from eight bases and received the Drinker's Check-Up (N=1483), Alcohol Savvy (N=688), or served as controls (N=919). The interventions drew on motivational interviewing and social learning theory and targeted multiple mediators including social norms, perceived risks and benefits, readiness to change, and coping strategies. Baseline data were collected prior to the intervention and follow-up data on alcohol consumption were gathered 1 month and 6 months after program completion. Two mediation models were examined: (1) a longitudinal two-wave model with outcomes and mediators assessed concurrently at the 1-month follow-up; and (2) a three-wave model in which the causal chain was fully lagged. Results indicated strong support for the role of perceived descriptive norms in transmitting the effects of the Drinker's Check-Up, with consistent mediation across the majority of alcohol outcome measures for both the concurrent and fully lagged mediation models. These results suggest that web-based interventions that are effective in lowering perceived norms about the frequency and quantity of drinking may be a viable strategy for reducing alcohol consumption in military populations. The results did not support program mediation by the other targeted variables, indicating the need for future research on the effective components of alcohol interventions. The mediation models also suggest reasons why program effects were not found for some outcomes or were different across programs.

  11. Simplified dark matter models with charged mediators: prospects for direct detection

    Energy Technology Data Exchange (ETDEWEB)

    Sandick, Pearl; Sinha, Kuver; Teng, Fei [Department of Physics and Astronomy, University of Utah,Salt Lake City, UT 84112 (United States)

    2016-10-05

    We consider direct detection prospects for a class of simplified models of fermionic dark matter (DM) coupled to left and right-handed Standard Model fermions via two charged scalar mediators with arbitrary mixing angle α. DM interactions with the nucleus are mediated by higher electromagnetic moments, which, for Majorana DM, is the anapole moment. After giving a full analytic calculation of the anapole moment, including its α dependence, and matching with limits in the literature, we compute the DM-nucleon scattering cross-section and show the LUX and future LZ constraints on the parameter space of these models. We then compare these results with constraints coming from Fermi-LAT continuum and line searches. Results in the supersymmetric limit of these simplified models are provided in all cases. We find that future direct detection experiments will be able to probe most of the parameter space of these models for O(100−200) GeV DM and lightest mediator mass ≲O(5%) larger than the DM mass. The direct detection prospects dwindle for larger DM mass and larger mass gap between the DM and the lightest mediator mass, although appreciable regions are still probed for O(200) GeV DM and lightest mediator mass ≲O(20%) larger than the DM mass. The direct detection bounds are also attenuated near certain “blind spots' in the parameter space, where the anapole moment is severely suppressed due to cancellation of different terms. We carefully study these blind spots and the associated Fermi-LAT signals in these regions.

  12. School Processes Mediate School Compositional Effects: Model Specification and Estimation

    Science.gov (United States)

    Liu, Hongqiang; Van Damme, Jan; Gielen, Sarah; Van Den Noortgate, Wim

    2015-01-01

    School composition effects have been consistently verified, but few studies ever attempted to study how school composition affects school achievement. Based on prior research findings, we employed multilevel mediation modeling to examine whether school processes mediate the effect of school composition upon school outcomes based on the data of 28…

  13. Mediation Analysis in a Latent Growth Curve Modeling Framework

    Science.gov (United States)

    von Soest, Tilmann; Hagtvet, Knut A.

    2011-01-01

    This article presents several longitudinal mediation models in the framework of latent growth curve modeling and provides a detailed account of how such models can be constructed. Logical and statistical challenges that might arise when such analyses are conducted are also discussed. Specifically, we discuss how the initial status (intercept) and…

  14. Low vagally-mediated heart rate variability and increased susceptibility to ventricular arrhythmias in rats bred for high anxiety.

    Science.gov (United States)

    Carnevali, Luca; Trombini, Mimosa; Graiani, Gallia; Madeddu, Denise; Quaini, Federico; Landgraf, Rainer; Neumann, Inga D; Nalivaiko, Eugene; Sgoifo, Andrea

    2014-04-10

    In humans, there is a documented association between anxiety disorders and cardiovascular disease. Putative underlying mechanisms may include an impairment of the autonomic nervous system control of cardiac function. The primary objective of the present study was to characterize cardiac autonomic modulation and susceptibility to arrhythmias in genetic lines of rats that differ largely in their anxiety level. To reach this goal, electrocardiographic recordings were performed in high-anxiety behavior (HAB, n=10) and low-anxiety behavior (LAB, n=10) rats at rest, during stressful stimuli and under autonomic pharmacological manipulations, and analyzed by means of time- and frequency-domain indexes of heart rate variability. During resting conditions, HAB rats displayed a reduced heart rate variability, mostly in terms of lower parasympathetic (vagal) modulation compared to LAB rats. In HAB rats, this relatively low cardiac vagal control was associated with smaller heart rate responsiveness to acute stressors compared to LAB counterparts. In addition, beta-adrenergic pharmacological stimulation induced a larger incidence of ventricular tachyarrhythmias in HABs compared to LABs. At sacrifice, a moderate increase in heart-body weight ratio was observed in HAB rats. We conclude that high levels of anxiety-related behavior in rats are associated with signs of i) impaired autonomic modulation of heart rate (low vagally-mediated heart rate variability), ii) poor adaptive heart rate responsiveness to stressful stimuli, iii) increased arrhythmia susceptibility, and iv) cardiac hypertrophy. These results highlight the utility of the HAB/LAB model for investigating the mechanistic basis of the comorbidity between anxiety disorders and cardiovascular disease. Copyright © 2014 Elsevier Inc. All rights reserved.

  15. New models of gauge- and gravity-mediated supersymmetry breaking

    International Nuclear Information System (INIS)

    Poppitz, E.; Trivedi, S.P.

    1997-01-01

    We show that supersymmetry breaking in a class of theories with SU(N)xSU(N-2) gauge symmetry can be studied in a calculable σ model. We use the σ model to show that the supersymmetry-breaking vacuum in these theories leaves a large subgroup of flavor symmetries intact, and to calculate the masses of the low-lying states. By embedding the standard model gauge groups in the unbroken flavor symmetry group we construct a class of models in which supersymmetry breaking is communicated by both gravitational and gauge interactions. One distinguishing feature of these models is that the messenger fields, responsible for the gauge-mediated communication of supersymmetry breaking, are an integral part of the supersymmetry-breaking sector. We also show how, by lowering the scale that suppresses the nonrenormalizable operators, a class of purely gauge-mediated models with a combined supersymmetry-breaking-cum-messenger sector can be built. We briefly discuss the phenomenological features of the models we construct. copyright 1997 The American Physical Society

  16. Low heart rate variability in unemployed men: The possible mediating effects of life satisfaction.

    Science.gov (United States)

    Jandackova, V K; Jackowska, M

    2015-01-01

    Unemployment has consistently been associated with increased risk of cardiovascular disease and premature mortality, and impaired autonomic modulation of the heart might be one mechanism partly explaining this. This study examined whether the possible effect of unemployment on cardiac autonomic modulation is in part mediated by lower psychological well-being. The sample comprised of 15 job-seeking men aged 30-49 years matched with 15 employed men on age, type of job, smoking habits, alcohol intake, frequency of physical activity, and body mass index. Heart rate variability (HRV) during a modified orthostatic test was the measure of cardiac autonomic modulation, and life satisfaction was the measure of psychological well-being. Unemployed men had significantly lower overall HRV (p = .040) than controls. This association was partially mediated through lower general life satisfaction, and in particular, by low financial satisfaction, independently of demographic and/or behavioral factors that influence HRV. These findings suggest that seeking a job is a potential stressor that may reduce overall HRV and contribute towards disturbance of cardiac autonomic modulation in men. Financial difficulties could be one mechanism through which the effects of unemployment are translated into impaired autonomic modulation.

  17. Assessing Mediation Using Marginal Structural Models in the Presence of Confounding and Moderation

    Science.gov (United States)

    Coffman, Donna L.; Zhong, Wei

    2012-01-01

    This article presents marginal structural models with inverse propensity weighting (IPW) for assessing mediation. Generally, individuals are not randomly assigned to levels of the mediator. Therefore, confounders of the mediator and outcome may exist that limit causal inferences, a goal of mediation analysis. Either regression adjustment or IPW…

  18. Preliminary Multi-Variable Cost Model for Space Telescopes

    Science.gov (United States)

    Stahl, H. Philip; Hendrichs, Todd

    2010-01-01

    Parametric cost models are routinely used to plan missions, compare concepts and justify technology investments. This paper reviews the methodology used to develop space telescope cost models; summarizes recently published single variable models; and presents preliminary results for two and three variable cost models. Some of the findings are that increasing mass reduces cost; it costs less per square meter of collecting aperture to build a large telescope than a small telescope; and technology development as a function of time reduces cost at the rate of 50% per 17 years.

  19. Computational modeling identifies key gene regulatory interactions underlying phenobarbital-mediated tumor promotion

    Science.gov (United States)

    Luisier, Raphaëlle; Unterberger, Elif B.; Goodman, Jay I.; Schwarz, Michael; Moggs, Jonathan; Terranova, Rémi; van Nimwegen, Erik

    2014-01-01

    Gene regulatory interactions underlying the early stages of non-genotoxic carcinogenesis are poorly understood. Here, we have identified key candidate regulators of phenobarbital (PB)-mediated mouse liver tumorigenesis, a well-characterized model of non-genotoxic carcinogenesis, by applying a new computational modeling approach to a comprehensive collection of in vivo gene expression studies. We have combined our previously developed motif activity response analysis (MARA), which models gene expression patterns in terms of computationally predicted transcription factor binding sites with singular value decomposition (SVD) of the inferred motif activities, to disentangle the roles that different transcriptional regulators play in specific biological pathways of tumor promotion. Furthermore, transgenic mouse models enabled us to identify which of these regulatory activities was downstream of constitutive androstane receptor and β-catenin signaling, both crucial components of PB-mediated liver tumorigenesis. We propose novel roles for E2F and ZFP161 in PB-mediated hepatocyte proliferation and suggest that PB-mediated suppression of ESR1 activity contributes to the development of a tumor-prone environment. Our study shows that combining MARA with SVD allows for automated identification of independent transcription regulatory programs within a complex in vivo tissue environment and provides novel mechanistic insights into PB-mediated hepatocarcinogenesis. PMID:24464994

  20. Mediation and moderation of treatment effects in randomised controlled trials of complex interventions.

    Science.gov (United States)

    Emsley, Richard; Dunn, Graham; White, Ian R

    2010-06-01

    Complex intervention trials should be able to answer both pragmatic and explanatory questions in order to test the theories motivating the intervention and help understand the underlying nature of the clinical problem being tested. Key to this is the estimation of direct effects of treatment and indirect effects acting through intermediate variables which are measured post-randomisation. Using psychological treatment trials as an example of complex interventions, we review statistical methods which crucially evaluate both direct and indirect effects in the presence of hidden confounding between mediator and outcome. We review the historical literature on mediation and moderation of treatment effects. We introduce two methods from within the existing causal inference literature, principal stratification and structural mean models, and demonstrate how these can be applied in a mediation context before discussing approaches and assumptions necessary for attaining identifiability of key parameters of the basic causal model. Assuming that there is modification by baseline covariates of the effect of treatment (i.e. randomisation) on the mediator (i.e. covariate by treatment interactions), but no direct effect on the outcome of these treatment by covariate interactions leads to the use of instrumental variable methods. We describe how moderation can occur through post-randomisation variables, and extend the principal stratification approach to multiple group methods with explanatory models nested within the principal strata. We illustrate the new methodology with motivating examples of randomised trials from the mental health literature.

  1. Analysis models for variables associated with breastfeeding duration

    Directory of Open Access Journals (Sweden)

    Edson Theodoro dos S. Neto

    2013-09-01

    Full Text Available OBJECTIVE To analyze the factors associated with breastfeeding duration by two statistical models. METHODS A population-based cohort study was conducted with 86 mothers and newborns from two areas primary covered by the National Health System, with high rates of infant mortality in Vitória, Espírito Santo, Brazil. During 30 months, 67 (78% children and mothers were visited seven times at home by trained interviewers, who filled out survey forms. Data on food and sucking habits, socioeconomic and maternal characteristics were collected. Variables were analyzed by Cox regression models, considering duration of breastfeeding as the dependent variable, and logistic regression (dependent variables, was the presence of a breastfeeding child in different post-natal ages. RESULTS In the logistic regression model, the pacifier sucking (adjusted Odds Ratio: 3.4; 95%CI 1.2-9.55 and bottle feeding (adjusted Odds Ratio: 4.4; 95%CI 1.6-12.1 increased the chance of weaning a child before one year of age. Variables associated to breastfeeding duration in the Cox regression model were: pacifier sucking (adjusted Hazard Ratio 2.0; 95%CI 1.2-3.3 and bottle feeding (adjusted Hazard Ratio 2.0; 95%CI 1.2-3.5. However, protective factors (maternal age and family income differed between both models. CONCLUSIONS Risk and protective factors associated with cessation of breastfeeding may be analyzed by different models of statistical regression. Cox Regression Models are adequate to analyze such factors in longitudinal studies.

  2. Beyond total treatment effects in randomised controlled trials: Baseline measurement of intermediate outcomes needed to reduce confounding in mediation investigations.

    Science.gov (United States)

    Landau, Sabine; Emsley, Richard; Dunn, Graham

    2018-06-01

    Random allocation avoids confounding bias when estimating the average treatment effect. For continuous outcomes measured at post-treatment as well as prior to randomisation (baseline), analyses based on (A) post-treatment outcome alone, (B) change scores over the treatment phase or (C) conditioning on baseline values (analysis of covariance) provide unbiased estimators of the average treatment effect. The decision to include baseline values of the clinical outcome in the analysis is based on precision arguments, with analysis of covariance known to be most precise. Investigators increasingly carry out explanatory analyses to decompose total treatment effects into components that are mediated by an intermediate continuous outcome and a non-mediated part. Traditional mediation analysis might be performed based on (A) post-treatment values of the intermediate and clinical outcomes alone, (B) respective change scores or (C) conditioning on baseline measures of both intermediate and clinical outcomes. Using causal diagrams and Monte Carlo simulation, we investigated the performance of the three competing mediation approaches. We considered a data generating model that included three possible confounding processes involving baseline variables: The first two processes modelled baseline measures of the clinical variable or the intermediate variable as common causes of post-treatment measures of these two variables. The third process allowed the two baseline variables themselves to be correlated due to past common causes. We compared the analysis models implied by the competing mediation approaches with this data generating model to hypothesise likely biases in estimators, and tested these in a simulation study. We applied the methods to a randomised trial of pragmatic rehabilitation in patients with chronic fatigue syndrome, which examined the role of limiting activities as a mediator. Estimates of causal mediation effects derived by approach (A) will be biased if one of

  3. Bayesian approach to errors-in-variables in regression models

    Science.gov (United States)

    Rozliman, Nur Aainaa; Ibrahim, Adriana Irawati Nur; Yunus, Rossita Mohammad

    2017-05-01

    In many applications and experiments, data sets are often contaminated with error or mismeasured covariates. When at least one of the covariates in a model is measured with error, Errors-in-Variables (EIV) model can be used. Measurement error, when not corrected, would cause misleading statistical inferences and analysis. Therefore, our goal is to examine the relationship of the outcome variable and the unobserved exposure variable given the observed mismeasured surrogate by applying the Bayesian formulation to the EIV model. We shall extend the flexible parametric method proposed by Hossain and Gustafson (2009) to another nonlinear regression model which is the Poisson regression model. We shall then illustrate the application of this approach via a simulation study using Markov chain Monte Carlo sampling methods.

  4. Mediating objects: scientific and public functions of models in nineteenth-century biology.

    Science.gov (United States)

    Ludwig, David

    2013-01-01

    The aim of this article is to examine the scientific and public functions of two- and three-dimensional models in the context of three episodes from nineteenth-century biology. I argue that these models incorporate both data and theory by presenting theoretical assumptions in the light of concrete data or organizing data through theoretical assumptions. Despite their diverse roles in scientific practice, they all can be characterized as mediators between data and theory. Furthermore, I argue that these different mediating functions often reflect their different audiences that included specialized scientists, students, and the general public. In this sense, models in nineteenth-century biology can be understood as mediators between theory, data, and their diverse audiences.

  5. Understanding and forecasting polar stratospheric variability with statistical models

    Directory of Open Access Journals (Sweden)

    C. Blume

    2012-07-01

    Full Text Available The variability of the north-polar stratospheric vortex is a prominent aspect of the middle atmosphere. This work investigates a wide class of statistical models with respect to their ability to model geopotential and temperature anomalies, representing variability in the polar stratosphere. Four partly nonstationary, nonlinear models are assessed: linear discriminant analysis (LDA; a cluster method based on finite elements (FEM-VARX; a neural network, namely the multi-layer perceptron (MLP; and support vector regression (SVR. These methods model time series by incorporating all significant external factors simultaneously, including ENSO, QBO, the solar cycle, volcanoes, to then quantify their statistical importance. We show that variability in reanalysis data from 1980 to 2005 is successfully modeled. The period from 2005 to 2011 can be hindcasted to a certain extent, where MLP performs significantly better than the remaining models. However, variability remains that cannot be statistically hindcasted within the current framework, such as the unexpected major warming in January 2009. Finally, the statistical model with the best generalization performance is used to predict a winter 2011/12 with warm and weak vortex conditions. A vortex breakdown is predicted for late January, early February 2012.

  6. Gaussian Mixture Model of Heart Rate Variability

    Science.gov (United States)

    Costa, Tommaso; Boccignone, Giuseppe; Ferraro, Mario

    2012-01-01

    Heart rate variability (HRV) is an important measure of sympathetic and parasympathetic functions of the autonomic nervous system and a key indicator of cardiovascular condition. This paper proposes a novel method to investigate HRV, namely by modelling it as a linear combination of Gaussians. Results show that three Gaussians are enough to describe the stationary statistics of heart variability and to provide a straightforward interpretation of the HRV power spectrum. Comparisons have been made also with synthetic data generated from different physiologically based models showing the plausibility of the Gaussian mixture parameters. PMID:22666386

  7. Causal mediation analysis with multiple causally non-ordered mediators.

    Science.gov (United States)

    Taguri, Masataka; Featherstone, John; Cheng, Jing

    2018-01-01

    In many health studies, researchers are interested in estimating the treatment effects on the outcome around and through an intermediate variable. Such causal mediation analyses aim to understand the mechanisms that explain the treatment effect. Although multiple mediators are often involved in real studies, most of the literature considered mediation analyses with one mediator at a time. In this article, we consider mediation analyses when there are causally non-ordered multiple mediators. Even if the mediators do not affect each other, the sum of two indirect effects through the two mediators considered separately may diverge from the joint natural indirect effect when there are additive interactions between the effects of the two mediators on the outcome. Therefore, we derive an equation for the joint natural indirect effect based on the individual mediation effects and their interactive effect, which helps us understand how the mediation effect works through the two mediators and relative contributions of the mediators and their interaction. We also discuss an extension for three mediators. The proposed method is illustrated using data from a randomized trial on the prevention of dental caries.

  8. Verification of models for ballistic movement time and endpoint variability.

    Science.gov (United States)

    Lin, Ray F; Drury, Colin G

    2013-01-01

    A hand control movement is composed of several ballistic movements. The time required in performing a ballistic movement and its endpoint variability are two important properties in developing movement models. The purpose of this study was to test potential models for predicting these two properties. Twelve participants conducted ballistic movements of specific amplitudes using a drawing tablet. The measured data of movement time and endpoint variability were then used to verify the models. This study was successful with Hoffmann and Gan's movement time model (Hoffmann, 1981; Gan and Hoffmann 1988) predicting more than 90.7% data variance for 84 individual measurements. A new theoretically developed ballistic movement variability model, proved to be better than Howarth, Beggs, and Bowden's (1971) model, predicting on average 84.8% of stopping-variable error and 88.3% of aiming-variable errors. These two validated models will help build solid theoretical movement models and evaluate input devices. This article provides better models for predicting end accuracy and movement time of ballistic movements that are desirable in rapid aiming tasks, such as keying in numbers on a smart phone. The models allow better design of aiming tasks, for example button sizes on mobile phones for different user populations.

  9. Latent variable modeling%建立隐性变量模型

    Institute of Scientific and Technical Information of China (English)

    蔡力

    2012-01-01

    @@ A latent variable model, as the name suggests,is a statistical model that contains latent, that is, unobserved, variables.Their roots go back to Spearman's 1904 seminal work[1] on factor analysis,which is arguably the first well-articulated latent variable model to be widely used in psychology, mental health research, and allied disciplines.Because of the association of factor analysis with early studies of human intelligence, the fact that key variables in a statistical model are, on occasion, unobserved has been a point of lingering contention and controversy.The reader is assured, however, that a latent variable,defined in the broadest manner, is no more mysterious than an error term in a normal theory linear regression model or a random effect in a mixed model.

  10. Galactic models with variable spiral structure

    International Nuclear Information System (INIS)

    James, R.A.; Sellwood, J.A.

    1978-01-01

    A series of three-dimensional computer simulations of disc galaxies has been run in which the self-consistent potential of the disc stars is supplemented by that arising from a small uniform Population II sphere. The models show variable spiral structure, which is more pronounced for thin discs. In addition, the thin discs form weak bars. In one case variable spiral structure associated with this bar has been seen. The relaxed discs are cool outside resonance regions. (author)

  11. A variable-order fractal derivative model for anomalous diffusion

    Directory of Open Access Journals (Sweden)

    Liu Xiaoting

    2017-01-01

    Full Text Available This paper pays attention to develop a variable-order fractal derivative model for anomalous diffusion. Previous investigations have indicated that the medium structure, fractal dimension or porosity may change with time or space during solute transport processes, results in time or spatial dependent anomalous diffusion phenomena. Hereby, this study makes an attempt to introduce a variable-order fractal derivative diffusion model, in which the index of fractal derivative depends on temporal moment or spatial position, to characterize the above mentioned anomalous diffusion (or transport processes. Compared with other models, the main advantages in description and the physical explanation of new model are explored by numerical simulation. Further discussions on the dissimilitude such as computational efficiency, diffusion behavior and heavy tail phenomena of the new model and variable-order fractional derivative model are also offered.

  12. Higher-dimensional cosmological model with variable gravitational ...

    Indian Academy of Sciences (India)

    We have studied five-dimensional homogeneous cosmological models with variable and bulk viscosity in Lyra geometry. Exact solutions for the field equations have been obtained and physical properties of the models are discussed. It has been observed that the results of new models are well within the observational ...

  13. The biobehavioral family model: testing social support as an additional exogenous variable.

    Science.gov (United States)

    Woods, Sarah B; Priest, Jacob B; Roush, Tara

    2014-12-01

    This study tests the inclusion of social support as a distinct exogenous variable in the Biobehavioral Family Model (BBFM). The BBFM is a biopsychosocial approach to health that proposes that biobehavioral reactivity (anxiety and depression) mediates the relationship between family emotional climate and disease activity. Data for this study included married, English-speaking adult participants (n = 1,321; 55% female; M age = 45.2 years) from the National Comorbidity Survey Replication, a nationally representative epidemiological study of the frequency of mental disorders in the United States. Participants reported their demographics, marital functioning, social support from friends and relatives, anxiety and depression (biobehavioral reactivity), number of chronic health conditions, and number of prescription medications. Confirmatory factor analyses supported the items used in the measures of negative marital interactions, social support, and biobehavioral reactivity, as well as the use of negative marital interactions, friends' social support, and relatives' social support as distinct factors in the model. Structural equation modeling indicated a good fit of the data to the hypothesized model (χ(2)  = 846.04, p = .000, SRMR = .039, CFI = .924, TLI = .914, RMSEA = .043). Negative marital interactions predicted biobehavioral reactivity (β = .38, p social support, inversely (β = -.16, p social support as a predicting factor in the model. © 2014 Family Process Institute.

  14. General gauge mediation

    International Nuclear Information System (INIS)

    Meade, Patrick; Seiberg, Nathan; Shih, David

    2009-01-01

    We give a general definition of gauge mediated supersymmetry breaking which encompasses all the known gauge mediation models. In particular, it includes both models with messengers as well as direct mediation models. A formalism for computing the soft terms in the generic model is presented. Such a formalism is necessary in strongly-coupled direct mediation models where perturbation theory cannot be used. It allows us to identify features of the entire class of gauge mediation models and to distinguish them from specific signatures of various subclasses. (author)

  15. Testing theories of dietary behavior change in youth using the mediating variable model with intervention programs

    Science.gov (United States)

    Our purpose was to review and critique current experimentally based evidence of theoretical mechanisms of dietary behavior change in youth, and provide recommendations on ways to enhance theory evaluation. Interventions that examined mediators of dietary behavior change in youth (age 5-18 years) wer...

  16. The Dark Side of Resilience and Burnout: A Moderation-Mediation Model.

    Directory of Open Access Journals (Sweden)

    Luke Treglown

    Full Text Available This study tested whether specific dark-side traits may be beneficial in manifesting and maintaining Resilience, whilst others are vulnerability factors for Burnout. Four hundred and fifty-one (50 female ambulance personnel completed three questionnaires as a part of a selection and development assessment. The study utilised the Hogan Development survey as a measure of dark side personality, the Copenhagen Burnout Inventory to assess work-related burnout, and the Resilience Scale- 14 to measure resilience levels. Those high on Excitable and Cautious but low on Bold and Reserved were linked to an increased vulnerability to Burnout. Also those high on Bold and Diligent yet low on the Excitable, Cautious, and Imaginative scales were more resilient. Structural Equation Modelling revealed that resilience plays both a mediating and moderating role on personality and burnout. Theoretical implications suggest future research assessing the predictive capacity of psychological variables on burnout should account the indirect effect of resilience.

  17. The Dark Side of Resilience and Burnout: A Moderation-Mediation Model.

    Science.gov (United States)

    Treglown, Luke; Palaiou, Kat; Zarola, Anthony; Furnham, Adrian

    2016-01-01

    This study tested whether specific dark-side traits may be beneficial in manifesting and maintaining Resilience, whilst others are vulnerability factors for Burnout. Four hundred and fifty-one (50 female) ambulance personnel completed three questionnaires as a part of a selection and development assessment. The study utilised the Hogan Development survey as a measure of dark side personality, the Copenhagen Burnout Inventory to assess work-related burnout, and the Resilience Scale- 14 to measure resilience levels. Those high on Excitable and Cautious but low on Bold and Reserved were linked to an increased vulnerability to Burnout. Also those high on Bold and Diligent yet low on the Excitable, Cautious, and Imaginative scales were more resilient. Structural Equation Modelling revealed that resilience plays both a mediating and moderating role on personality and burnout. Theoretical implications suggest future research assessing the predictive capacity of psychological variables on burnout should account the indirect effect of resilience.

  18. Assessing mediation using marginal structural models in the presence of confounding and moderation

    OpenAIRE

    Coffman, Donna L.; Zhong, Wei

    2012-01-01

    This paper presents marginal structural models (MSMs) with inverse propensity weighting (IPW) for assessing mediation. Generally, individuals are not randomly assigned to levels of the mediator. Therefore, confounders of the mediator and outcome may exist that limit causal inferences, a goal of mediation analysis. Either regression adjustment or IPW can be used to take confounding into account, but IPW has several advantages. Regression adjustment of even one confounder of the mediator and ou...

  19. Multi-scale climate modelling over Southern Africa using a variable-resolution global model

    CSIR Research Space (South Africa)

    Engelbrecht, FA

    2011-12-01

    Full Text Available -mail: fengelbrecht@csir.co.za Multi-scale climate modelling over Southern Africa using a variable-resolution global model FA Engelbrecht1, 2*, WA Landman1, 3, CJ Engelbrecht4, S Landman5, MM Bopape1, B Roux6, JL McGregor7 and M Thatcher7 1 CSIR Natural... improvement. Keywords: multi-scale climate modelling, variable-resolution atmospheric model Introduction Dynamic climate models have become the primary tools for the projection of future climate change, at both the global and regional scales. Dynamic...

  20. Schooling relates to mental health problems in adolescents with cochlear implants – mediation by hearing and family variables

    Directory of Open Access Journals (Sweden)

    Maria eHuber

    2015-12-01

    Full Text Available Aim of this multicenter study was to investigate whether schooling relates to mental health problems of adolescents with cochlear implants (CI and how this relationship is mediated by hearing and family variables. 140 secondary school students with CI (mean age = 14.7 years, SD = 1.5, their hearing parents and teachers completed the Strengths and Difficulties Questionnaire (SDQ. Additional audiological tests (speech comprehension tests in quiet and noise were performed. Students of special schools for hearing impaired persons (SSHIs showed significantly more conduct problems (p<0.05 and a significantly higher total difficulty score (p<0.05 compared to students of mainstream schools. Mental health problems did not differ between SSHI students with sign language education and SSHI students with oral education. Late implanted students and those with indication for additional handicaps were equally distributed among mainstream schools and SSHIs. However, students in SSHIs were more restricted to understand speech in noise, had a lower social background and were more likely to come from single-parent families. These factors were found to be partial mediators of the differences in mental health problems between the two school types. However, no variable could explain comprehensively, why students of SSHIs have more mental health problems than mainstream pupils.

  1. Customer Satisfaction as a Mediator Variable between Service Quality and Customer Loyalty for PT. BNI (Persero Tbk Aceh Province, Indonesia

    Directory of Open Access Journals (Sweden)

    Beby Karina Fawzea SEMBIRING

    2017-09-01

    Full Text Available This study aims to analyze the effect of service quality toward satisfaction and customer loyalty for PT. BNI (Persero Tbk, Aceh Province. The article also analyses customer satisfaction as a mediator variable between service quality and customer loyalty. The sampling technique in the study was based on cluster and convenience sampling with corresponding criteria; each respondent has a bank account and saving for at least one year. The primary data were collected from respondents using the structured questionnaires. A total of 220 questionnaires were distributed in five branch offices of PT. BNI (Persero Tbk operating in Aceh Province, namely the branchs of Lhokseumawe, Bireuen, Langsa, Sigli and Meulaboh. The results showed that service quality has a significant and positive effect toward satisfaction and customer loyalty for PT. BNI (Persero Tbk Aceh Province. Meanwhile, the variable of customer satisfaction can mediate the effect of service quality toward customer loyalty. However, the study found that service quality is the important element in increasing satisfaction and customer loyalty in national banking.

  2. Modelling the co-evolution of indirect genetic effects and inherited variability.

    Science.gov (United States)

    Marjanovic, Jovana; Mulder, Han A; Rönnegård, Lars; Bijma, Piter

    2018-03-28

    When individuals interact, their phenotypes may be affected not only by their own genes but also by genes in their social partners. This phenomenon is known as Indirect Genetic Effects (IGEs). In aquaculture species and some plants, however, competition not only affects trait levels of individuals, but also inflates variability of trait values among individuals. In the field of quantitative genetics, the variability of trait values has been studied as a quantitative trait in itself, and is often referred to as inherited variability. Such studies, however, consider only the genetic effect of the focal individual on trait variability and do not make a connection to competition. Although the observed phenotypic relationship between competition and variability suggests an underlying genetic relationship, the current quantitative genetic models of IGE and inherited variability do not allow for such a relationship. The lack of quantitative genetic models that connect IGEs to inherited variability limits our understanding of the potential of variability to respond to selection, both in nature and agriculture. Models of trait levels, for example, show that IGEs may considerably change heritable variation in trait values. Currently, we lack the tools to investigate whether this result extends to variability of trait values. Here we present a model that integrates IGEs and inherited variability. In this model, the target phenotype, say growth rate, is a function of the genetic and environmental effects of the focal individual and of the difference in trait value between the social partner and the focal individual, multiplied by a regression coefficient. The regression coefficient is a genetic trait, which is a measure of cooperation; a negative value indicates competition, a positive value cooperation, and an increasing value due to selection indicates the evolution of cooperation. In contrast to the existing quantitative genetic models, our model allows for co-evolution of

  3. The Impact of Affective Constraints on Shaping Environmental Literacy: Model Testing Using Mediator and Moderator Variables

    Science.gov (United States)

    Öztürk, Nilay; Teksöz, Gaye

    2016-01-01

    The aims of this study were; first to investigate the mediating effects of pre-service teachers' (PTs) attitude toward environment on the relationship between their environmental concern and environmental responsibility, and second, to explore the moderating effect of gender on the relationships between; PTs' environmental concern and…

  4. Causal mediation analysis for longitudinal data with exogenous exposure.

    Science.gov (United States)

    Bind, M-A C; Vanderweele, T J; Coull, B A; Schwartz, J D

    2016-01-01

    Mediation analysis is a valuable approach to examine pathways in epidemiological research. Prospective cohort studies are often conducted to study biological mechanisms and often collect longitudinal measurements on each participant. Mediation formulae for longitudinal data have been developed. Here, we formalize the natural direct and indirect effects using a causal framework with potential outcomes that allows for an interaction between the exposure and the mediator. To allow different types of longitudinal measures of the mediator and outcome, we assume two generalized mixed-effects models for both the mediator and the outcome. The model for the mediator has subject-specific random intercepts and random exposure slopes for each cluster, and the outcome model has random intercepts and random slopes for the exposure, the mediator, and their interaction. We also expand our approach to settings with multiple mediators and derive the mediated effects, jointly through all mediators. Our method requires the absence of time-varying confounding with respect to the exposure and the mediator. This assumption is achieved in settings with exogenous exposure and mediator, especially when exposure and mediator are not affected by variables measured at earlier time points. We apply the methodology to data from the Normative Aging Study and estimate the direct and indirect effects, via DNA methylation, of air pollution, and temperature on intercellular adhesion molecule 1 (ICAM-1) protein levels. Our results suggest that air pollution and temperature have a direct effect on ICAM-1 protein levels (i.e. not through a change in ICAM-1 DNA methylation) and that temperature has an indirect effect via a change in ICAM-1 DNA methylation. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  5. Testing Theories of Dietary Behavior Change in Youth Using the Mediating Variable Model with Intervention Programs

    Science.gov (United States)

    Cerin, Ester; Barnett, Anthony; Baranowski, Tom

    2009-01-01

    Objective: To review and critique current experimentally-based evidence of theoretical mechanisms of dietary behavior change in youth and provide recommendations on ways to enhance theory evaluation. Methods: Interventions that examined mediators of dietary behavior change in youth (age 5-18 years) were identified via electronic database searches…

  6. Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective

    Energy Technology Data Exchange (ETDEWEB)

    Cole, Wesley [National Renewable Energy Lab. (NREL), Golden, CO (United States); Frew, Bethany [National Renewable Energy Lab. (NREL), Golden, CO (United States); Mai, Trieu [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sun, Yinong [National Renewable Energy Lab. (NREL), Golden, CO (United States); Bistline, John [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Blanford, Geoffrey [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Young, David [Electric Power Research Inst. (EPRI), Knoxville, TN (United States); Marcy, Cara [U.S. Energy Information Administration, Washington, DC (United States); Namovicz, Chris [U.S. Energy Information Administration, Washington, DC (United States); Edelman, Risa [US Environmental Protection Agency (EPA), Washington, DC (United States); Meroney, Bill [US Environmental Protection Agency (EPA), Washington, DC (United States); Sims, Ryan [US Environmental Protection Agency (EPA), Washington, DC (United States); Stenhouse, Jeb [US Environmental Protection Agency (EPA), Washington, DC (United States); Donohoo-Vallett, Paul [Dept. of Energy (DOE), Washington DC (United States)

    2017-11-01

    Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision-makers. With the recent surge in variable renewable energy (VRE) generators — primarily wind and solar photovoltaics — the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. This report summarizes the analyses and model experiments that were conducted as part of two workshops on modeling VRE for national-scale capacity expansion models. It discusses the various methods for treating VRE among four modeling teams from the Electric Power Research Institute (EPRI), the U.S. Energy Information Administration (EIA), the U.S. Environmental Protection Agency (EPA), and the National Renewable Energy Laboratory (NREL). The report reviews the findings from the two workshops and emphasizes the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making. This research is intended to inform the energy modeling community on the modeling of variable renewable resources, and is not intended to advocate for or against any particular energy technologies, resources, or policies.

  7. Optimism on quality of life in Portuguese chronic patients: moderator/mediator?

    Science.gov (United States)

    Vilhena, Estela; Pais-Ribeiro, José; Silva, Isabel; Pedro, Luísa; Meneses, Rute F; Cardoso, Helena; Silva, António Martins da; Mendonça, Denisa

    2014-07-01

    optimism is an important variable that has consistently been shown to affect adjustment to quality of life in chronic diseases. This study aims to clarify if dispositional optimism exerts a moderating or a mediating influence on the personality traits-quality of life association, in Portuguese chronic patients. multiple regression models were used to test the moderation and mediation effects of dispositional optimism in quality of life. A sample of 729 patients was recruited in Portugal's main hospitals and completed self-reported questionnaires assessing socio-demographic and clinical variables, personality, dispositional optimism, quality of life (QoL) and subjective well-being (SWB). the results of the regression models showed that dispositional optimism did not moderate the relationships between personality traits and quality of life. After controlling for gender, age, education level and severity of disease perception, the effects of personality traits on QoL and in SWB were mediated by dispositional optimism (partially and completely), except for the links between neuroticism/openness to experience and physical health. dispositional optimism is more likely to play a mediating, rather than a moderating role in personality traits-quality of life pathway in Portuguese chronic patients, suggesting that "the expectation that good things will happen" contributes to a better quality of life and subjective well-being.

  8. Sources and Impacts of Modeled and Observed Low-Frequency Climate Variability

    Science.gov (United States)

    Parsons, Luke Alexander

    Here we analyze climate variability using instrumental, paleoclimate (proxy), and the latest climate model data to understand more about the sources and impacts of low-frequency climate variability. Understanding the drivers of climate variability at interannual to century timescales is important for studies of climate change, including analyses of detection and attribution of climate change impacts. Additionally, correctly modeling the sources and impacts of variability is key to the simulation of abrupt change (Alley et al., 2003) and extended drought (Seager et al., 2005; Pelletier and Turcotte, 1997; Ault et al., 2014). In Appendix A, we employ an Earth system model (GFDL-ESM2M) simulation to study the impacts of a weakening of the Atlantic meridional overturning circulation (AMOC) on the climate of the American Tropics. The AMOC drives some degree of local and global internal low-frequency climate variability (Manabe and Stouffer, 1995; Thornalley et al., 2009) and helps control the position of the tropical rainfall belt (Zhang and Delworth, 2005). We find that a major weakening of the AMOC can cause large-scale temperature, precipitation, and carbon storage changes in Central and South America. Our results suggest that possible future changes in AMOC strength alone will not be sufficient to drive a large-scale dieback of the Amazonian forest, but this key natural ecosystem is sensitive to dry-season length and timing of rainfall (Parsons et al., 2014). In Appendix B, we compare a paleoclimate record of precipitation variability in the Peruvian Amazon to climate model precipitation variability. The paleoclimate (Lake Limon) record indicates that precipitation variability in western Amazonia is 'red' (i.e., increasing variability with timescale). By contrast, most state-of-the-art climate models indicate precipitation variability in this region is nearly 'white' (i.e., equally variability across timescales). This paleo-model disagreement in the overall

  9. The necessity of connection structures in neural models of variable binding.

    Science.gov (United States)

    van der Velde, Frank; de Kamps, Marc

    2015-08-01

    In his review of neural binding problems, Feldman (Cogn Neurodyn 7:1-11, 2013) addressed two types of models as solutions of (novel) variable binding. The one type uses labels such as phase synchrony of activation. The other ('connectivity based') type uses dedicated connections structures to achieve novel variable binding. Feldman argued that label (synchrony) based models are the only possible candidates to handle novel variable binding, whereas connectivity based models lack the flexibility required for that. We argue and illustrate that Feldman's analysis is incorrect. Contrary to his conclusion, connectivity based models are the only viable candidates for models of novel variable binding because they are the only type of models that can produce behavior. We will show that the label (synchrony) based models analyzed by Feldman are in fact examples of connectivity based models. Feldman's analysis that novel variable binding can be achieved without existing connection structures seems to result from analyzing the binding problem in a wrong frame of reference, in particular in an outside instead of the required inside frame of reference. Connectivity based models can be models of novel variable binding when they possess a connection structure that resembles a small-world network, as found in the brain. We will illustrate binding with this type of model with episode binding and the binding of words, including novel words, in sentence structures.

  10. Social support as a mediator variable of the relationship between depression and life satisfaction in a sample of Saudi caregivers of patients with Alzheimer's disease.

    Science.gov (United States)

    Khusaifan, Shatha Jamil; El Keshky, Mogeda El Sayed

    2017-02-01

    Caring for someone with Alzheimer's disease (AD) is very challenging. Social support may play a crucial role in helping caregivers to adapt better to their caregiving role. The aim of this study is to explore the role of social support as a moderator variable of the relationship between depression and life satisfaction in caregivers for patients with AD in Saudi Arabia. In this cross-sectional study, 122 caregivers for patients with AD completed questionnaires assessing informal social support, depressive symptoms, and general life satisfaction. The demographic characteristics showed that 79% (n = 96) of caregivers were females and between the ages of 20 and 50. Higher levels of social support positively correlated with reported higher levels of life satisfaction (r = 0.483, p Depression was negatively correlated with social support (r = -0.418, p Social support was found to be a partial mediator variable, mediating approximately 23.05% of the total effect of depression on life satisfaction (Sobel = -3.065, p = 0.002). Informal social support can act as a mediator variable in the relationship of depression and life satisfaction in caregivers of AD patients. Improving the informal social support networks may help in coping with caregiving burden and better quality of life.

  11. Principal Empowering Leadership and Teacher Innovative Behavior: A Moderated Mediation Model

    Science.gov (United States)

    Gkorezis, Panagiotis

    2016-01-01

    Purpose: The purpose of this paper is to contribute to extant literature by linking principal empowering leadership to teachers' innovative work behavior. By doing so, the author attempts to provide a more nuanced understanding of this relationship by examining a moderated mediation model which encompasses exploration as a mediator and role…

  12. A Non-Gaussian Spatial Generalized Linear Latent Variable Model

    KAUST Repository

    Irincheeva, Irina; Cantoni, Eva; Genton, Marc G.

    2012-01-01

    We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

  13. A Non-Gaussian Spatial Generalized Linear Latent Variable Model

    KAUST Repository

    Irincheeva, Irina

    2012-08-03

    We consider a spatial generalized linear latent variable model with and without normality distributional assumption on the latent variables. When the latent variables are assumed to be multivariate normal, we apply a Laplace approximation. To relax the assumption of marginal normality in favor of a mixture of normals, we construct a multivariate density with Gaussian spatial dependence and given multivariate margins. We use the pairwise likelihood to estimate the corresponding spatial generalized linear latent variable model. The properties of the resulting estimators are explored by simulations. In the analysis of an air pollution data set the proposed methodology uncovers weather conditions to be a more important source of variability than air pollution in explaining all the causes of non-accidental mortality excluding accidents. © 2012 International Biometric Society.

  14. Modelling Toehold-Mediated RNA Strand Displacement

    OpenAIRE

    Šulc, Petr; Ouldridge, Thomas E.; Romano, Flavio; Doye, Jonathan P.K.; Louis, Ard A.

    2015-01-01

    We study the thermodynamics and kinetics of an RNA toehold-mediated strand displacement reaction with a recently developed coarse-grained model of RNA. Strand displacement, during which a single strand displaces a different strand previously bound to a complementary substrate strand, is an essential mechanism in active nucleic acid nanotechnology and has also been hypothesized to occur in vivo. We study the rate of displacement reactions as a function of the length of the toehold and temperat...

  15. The mediating and moderating role of burnout and emotional intelligence in the relationship between organizational justice and work misbehavior

    OpenAIRE

    Or Shkoler; Aharon Tziner

    2017-01-01

    The current research (Figure 1) examined the antecedents of work misbehaviors (WMBs) by means of organizational justice perceptions (as a predictor), experienced burnout (as a mediator), and emotional intelligence (as a buffer). A heterogeneous sample of 243 employees was acquired in order to assess correlative associations between the variables, a mediation effect, and two moderation effects. In order to test the mediation effect further and the model fit, structural equation modelling (SEM)...

  16. The mediating and moderating role of burnout and emotional intelligence in the relationship between organizational justice and work misbehavior

    OpenAIRE

    Shkoler, Or; Tziner, Aharon

    2017-01-01

    Abstract The current research (Figure 1) examined the antecedents of work misbehaviors (WMBs) by means of organizational justice perceptions (as a predictor), experienced burnout (as a mediator), and emotional intelligence (as a buffer). A heterogeneous sample of 243 employees was acquired in order to assess correlative associations between the variables, a mediation effect, and two moderation effects. In order to test the mediation effect further and the model fit, structural equation modell...

  17. Adolescent survivors of childhood sexual abuse: the mediating role of attachment style and coping in psychological and interpersonal functioning.

    Science.gov (United States)

    Shapiro, D L; Levendosky, A A

    1999-11-01

    To examine attachment style and coping strategies as potential mediating variables between childhood sexual abuse (CSA) and psychological and interpersonal functioning in an attempt to explain variability in extent of disorder and level of functioning. Eighty adolescent females, aged 14-16 years, answered questions regarding abuse history, attachment style, coping with an interpersonal stressor, depression and trauma symptomatology, and conflict with a best friend. Structural equation modeling analyses indicated that attachment style mediates the effects of CSA and child abuse and neglect on coping and psychological distress. The indirect effects of CSA and other abuse through attachment accounted for most of the effects on coping and psychological distress. Avoidant and cognitive coping strategies also served as mediators in the models, accounting for most of the effects of the other variables on interpersonal conflict. The findings indicate that attachment style and coping strategies influence psychological and interpersonal functioning, mediating the direct effects of CSA and other types of child abuse and neglect. These results have implications for therapeutic intervention with children and adolescents who have experienced child abuse.

  18. A default Bayesian hypothesis test for mediation

    NARCIS (Netherlands)

    Nuijten, M.B.; Wetzels, R.; Matzke, D.; Dolan, C.V.; Wagenmakers, E.J.

    2015-01-01

    In order to quantify the relationship between multiple variables, researchers often carry out a mediation analysis. In such an analysis, a mediator (e.g., knowledge of a healthy diet) transmits the effect from an independent variable (e.g., classroom instruction on a healthy diet) to a dependent

  19. Mediator effect of statistical process control between Total Quality Management (TQM) and business performance in Malaysian Automotive Industry

    Science.gov (United States)

    Ahmad, M. F.; Rasi, R. Z.; Zakuan, N.; Hisyamudin, M. N. N.

    2015-12-01

    In today's highly competitive market, Total Quality Management (TQM) is vital management tool in ensuring a company can success in their business. In order to survive in the global market with intense competition amongst regions and enterprises, the adoption of tools and techniques are essential in improving business performance. There are consistent results between TQM and business performance. However, only few previous studies have examined the mediator effect namely statistical process control (SPC) between TQM and business performance. A mediator is a third variable that changes the association between an independent variable and an outcome variable. This study present research proposed a TQM performance model with mediator effect of SPC with structural equation modelling, which is a more comprehensive model for developing countries, specifically for Malaysia. A questionnaire was prepared and sent to 1500 companies from automotive industry and the related vendors in Malaysia, giving a 21.8 per cent rate. Attempts were made at findings significant impact of mediator between TQM practices and business performance showed that SPC is important tools and techniques in TQM implementation. The result concludes that SPC is partial correlation between and TQM and BP with indirect effect (IE) is 0.25 which can be categorised as high moderator effect.

  20. Improved variable reduction in partial least squares modelling based on predictive-property-ranked variables and adaptation of partial least squares complexity.

    Science.gov (United States)

    Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C

    2011-10-31

    The calibration performance of partial least squares for one response variable (PLS1) can be improved by elimination of uninformative variables. Many methods are based on so-called predictive variable properties, which are functions of various PLS-model parameters, and which may change during the variable reduction process. In these methods variable reduction is made on the variables ranked in descending order for a given variable property. The methods start with full spectrum modelling. Iteratively, until a specified number of remaining variables is reached, the variable with the smallest property value is eliminated; a new PLS model is calculated, followed by a renewed ranking of the variables. The Stepwise Variable Reduction methods using Predictive-Property-Ranked Variables are denoted as SVR-PPRV. In the existing SVR-PPRV methods the PLS model complexity is kept constant during the variable reduction process. In this study, three new SVR-PPRV methods are proposed, in which a possibility for decreasing the PLS model complexity during the variable reduction process is build in. Therefore we denote our methods as PPRVR-CAM methods (Predictive-Property-Ranked Variable Reduction with Complexity Adapted Models). The selective and predictive abilities of the new methods are investigated and tested, using the absolute PLS regression coefficients as predictive property. They were compared with two modifications of existing SVR-PPRV methods (with constant PLS model complexity) and with two reference methods: uninformative variable elimination followed by either a genetic algorithm for PLS (UVE-GA-PLS) or an interval PLS (UVE-iPLS). The performance of the methods is investigated in conjunction with two data sets from near-infrared sources (NIR) and one simulated set. The selective and predictive performances of the variable reduction methods are compared statistically using the Wilcoxon signed rank test. The three newly developed PPRVR-CAM methods were able to retain

  1. Phenomenology of mixed modulus-anomaly mediation in fluxed string compactifications and brane models

    International Nuclear Information System (INIS)

    Choi, Kiwoon; Jeong, Kwang-Sik; Okumura, Ken-ichi

    2005-01-01

    In some string compactifications, for instance the recently proposed KKLT set-up, light moduli are stabilized by nonperturbative effects at supersymmetric AdS vacuum which is lifted to a dS vacuum by supersymmetry breaking uplifting potential. In such models, soft supersymmetry breaking terms are determined by a specific mixed modulus-anomaly mediation in which the two mediations typically give comparable contributions to soft parameters. Similar pattern of soft terms can arise also in brane models to stabilize the radion by nonperturbative effects. We examine some phenomenological consequences of this mixed modulus-anomaly mediation, including the pattern of low energy sparticle spectrum and the possibility of electroweak symmetry breaking. It is noted that adding the anomaly-mediated contributions at M GUT amounts to replacing the messenger scale of the modulus mediation by a mirage messenger scale (m 3/2 /M Pl ) α/2 M GUT where α = m 3/2 /[M 0 ln (M Pl /m 3/2 )] for M 0 denoting the modulus-mediated contribution to the gaugino mass at M GUT . The minimal KKLT set-up predicts α = 1. As a consequence, for α = O(1), the model can lead to a highly distinctive pattern of sparticle masses at TeV scale, particularly when α = 2

  2. Modeling of carbon sequestration in coal-beds: A variable saturated simulation

    International Nuclear Information System (INIS)

    Liu Guoxiang; Smirnov, Andrei V.

    2008-01-01

    Storage of carbon dioxide in deep coal seams is a profitable method to reduce the concentration of green house gases in the atmosphere while the methane as a byproduct can be extracted during carbon dioxide injection into the coal seam. In this procedure, the key element is to keep carbon dioxide in the coal seam without escaping for a long term. It is depended on many factors such as properties of coal basin, fracture state, phase equilibrium, etc., especially the porosity, permeability and saturation of the coal seam. In this paper, a variable saturation model was developed to predict the capacity of carbon dioxide sequestration and coal-bed methane recovery. This variable saturation model can be used to track the saturation variability with the partial pressures change caused by carbon dioxide injection. Saturation variability is a key factor to predict the capacity of carbon dioxide storage and methane recovery. Based on this variable saturation model, a set of related variables including capillary pressure, relative permeability, porosity, coupled adsorption model, concentration and temperature equations were solved. From results of the simulation, historical data agree with the variable saturation model as well as the adsorption model constructed by Langmuir equations. The Appalachian basin, as an example, modeled the carbon dioxide sequestration in this paper. The results of the study and the developed models can provide the projections for the CO 2 sequestration and methane recovery in coal-beds within different regional specifics

  3. Marital Conflicts and Parent-Adolescent Conflicts: The Mediator Role of Adolescents' Appraisals of Interparental Conflicts

    Directory of Open Access Journals (Sweden)

    ایرج مختارنیا

    2017-03-01

    Full Text Available The aim of this study was to investigate the effect of mediating role of adolescents' appraisals from interparents conflict on the relationship of marital conflicts and parent-adolescent conflict. The study was descriptive correlational and the population of this study included students of Qods town of Tehran province. Sample size was 700 students that were selected by multistage random sampling. The data were collected by Parent-Adolescent Conflict Questionnaire (PACQ, Marital Conflict Scale (MCS and Children's Appraisals of Interparental Conflict Scale (CPIC. The results of structural equation modeling analysis showed that the theoretical model of the study included in the model was properly fitted with the data. This means that the variable of adolescent's appraisals of interparents’ conflict can be considered as a mediator variable in the relationship of marital conflict and parent-adolescent conflict. Furthermore, in this model all direct and indirect paths to predict parent-adolescent conflict were recognized. Therefore, marital conflict can predict parent-adolescent conflicts through mediating factors. Also, it can be concluded that the model of cognitive-contextual is capable of explaining the parent-adolescent conflicts.

  4. A default Bayesian hypothesis test for mediation.

    Science.gov (United States)

    Nuijten, Michèle B; Wetzels, Ruud; Matzke, Dora; Dolan, Conor V; Wagenmakers, Eric-Jan

    2015-03-01

    In order to quantify the relationship between multiple variables, researchers often carry out a mediation analysis. In such an analysis, a mediator (e.g., knowledge of a healthy diet) transmits the effect from an independent variable (e.g., classroom instruction on a healthy diet) to a dependent variable (e.g., consumption of fruits and vegetables). Almost all mediation analyses in psychology use frequentist estimation and hypothesis-testing techniques. A recent exception is Yuan and MacKinnon (Psychological Methods, 14, 301-322, 2009), who outlined a Bayesian parameter estimation procedure for mediation analysis. Here we complete the Bayesian alternative to frequentist mediation analysis by specifying a default Bayesian hypothesis test based on the Jeffreys-Zellner-Siow approach. We further extend this default Bayesian test by allowing a comparison to directional or one-sided alternatives, using Markov chain Monte Carlo techniques implemented in JAGS. All Bayesian tests are implemented in the R package BayesMed (Nuijten, Wetzels, Matzke, Dolan, & Wagenmakers, 2014).

  5. Two-condition within-participant statistical mediation analysis: A path-analytic framework.

    Science.gov (United States)

    Montoya, Amanda K; Hayes, Andrew F

    2017-03-01

    Researchers interested in testing mediation often use designs where participants are measured on a dependent variable Y and a mediator M in both of 2 different circumstances. The dominant approach to assessing mediation in such a design, proposed by Judd, Kenny, and McClelland (2001), relies on a series of hypothesis tests about components of the mediation model and is not based on an estimate of or formal inference about the indirect effect. In this article we recast Judd et al.'s approach in the path-analytic framework that is now commonly used in between-participant mediation analysis. By so doing, it is apparent how to estimate the indirect effect of a within-participant manipulation on some outcome through a mediator as the product of paths of influence. This path-analytic approach eliminates the need for discrete hypothesis tests about components of the model to support a claim of mediation, as Judd et al.'s method requires, because it relies only on an inference about the product of paths-the indirect effect. We generalize methods of inference for the indirect effect widely used in between-participant designs to this within-participant version of mediation analysis, including bootstrap confidence intervals and Monte Carlo confidence intervals. Using this path-analytic approach, we extend the method to models with multiple mediators operating in parallel and serially and discuss the comparison of indirect effects in these more complex models. We offer macros and code for SPSS, SAS, and Mplus that conduct these analyses. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  6. Adult attachment, perceived social support, cultural orientation, and depressive symptoms: A moderated mediation model.

    Science.gov (United States)

    Zhu, Wenzhen; Wang, Chiachih Dc; Chong, Chu Chian

    2016-11-01

    In the current study, we tested a moderated mediation model in which cultural orientation moderated the mediation model of adult attachment-perceived social support-depressive symptoms, using 2 comparable cross-cultural samples of college students recruited from China and the U.S. (n = 363 for each group). Results indicated that perceived social support mediated the effect of attachment anxiety on depressive symptoms as well as the link between attachment avoidance and depression in both samples. Moderated mediation analyses using PROCESS revealed that interdependent self-construal significantly buffered the indirect effect of attachment avoidance (via perceived social support) on depressive symptoms. The findings indicated significant differences in the mediation models between the U.S. and China groups and interdependent self-construal accounted for the between-country differences. Limitations, implications of the findings, and future research directions are discussed from the perspectives of cross-cultural variation of adult attachment functioning. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  7. A Comparative Study of Early Afterdepolarization-Mediated Fibrillation in Two Mathematical Models for Human Ventricular Cells.

    Directory of Open Access Journals (Sweden)

    Soling Zimik

    Full Text Available Early afterdepolarizations (EADs, which are abnormal oscillations of the membrane potential at the plateau phase of an action potential, are implicated in the development of cardiac arrhythmias like Torsade de Pointes. We carry out extensive numerical simulations of the TP06 and ORd mathematical models for human ventricular cells with EADs. We investigate the different regimes in both these models, namely, the parameter regimes where they exhibit (1 a normal action potential (AP with no EADs, (2 an AP with EADs, and (3 an AP with EADs that does not go back to the resting potential. We also study the dependence of EADs on the rate of at which we pace a cell, with the specific goal of elucidating EADs that are induced by slow or fast rate pacing. In our simulations in two- and three-dimensional domains, in the presence of EADs, we find the following wave types: (A waves driven by the fast sodium current and the L-type calcium current (Na-Ca-mediated waves; (B waves driven only by the L-type calcium current (Ca-mediated waves; (C phase waves, which are pseudo-travelling waves. Furthermore, we compare the wave patterns of the various wave-types (Na-Ca-mediated, Ca-mediated, and phase waves in both these models. We find that the two models produce qualitatively similar results in terms of exhibiting Na-Ca-mediated wave patterns that are more chaotic than those for the Ca-mediated and phase waves. However, there are quantitative differences in the wave patterns of each wave type. The Na-Ca-mediated waves in the ORd model show short-lived spirals but the TP06 model does not. The TP06 model supports more Ca-mediated spirals than those in the ORd model, and the TP06 model exhibits more phase-wave patterns than does the ORd model.

  8. A Comparative Study of Early Afterdepolarization-Mediated Fibrillation in Two Mathematical Models for Human Ventricular Cells

    Science.gov (United States)

    Zimik, Soling; Vandersickel, Nele; Nayak, Alok Ranjan; Panfilov, Alexander V.; Pandit, Rahul

    2015-01-01

    Early afterdepolarizations (EADs), which are abnormal oscillations of the membrane potential at the plateau phase of an action potential, are implicated in the development of cardiac arrhythmias like Torsade de Pointes. We carry out extensive numerical simulations of the TP06 and ORd mathematical models for human ventricular cells with EADs. We investigate the different regimes in both these models, namely, the parameter regimes where they exhibit (1) a normal action potential (AP) with no EADs, (2) an AP with EADs, and (3) an AP with EADs that does not go back to the resting potential. We also study the dependence of EADs on the rate of at which we pace a cell, with the specific goal of elucidating EADs that are induced by slow or fast rate pacing. In our simulations in two- and three-dimensional domains, in the presence of EADs, we find the following wave types: (A) waves driven by the fast sodium current and the L-type calcium current (Na-Ca-mediated waves); (B) waves driven only by the L-type calcium current (Ca-mediated waves); (C) phase waves, which are pseudo-travelling waves. Furthermore, we compare the wave patterns of the various wave-types (Na-Ca-mediated, Ca-mediated, and phase waves) in both these models. We find that the two models produce qualitatively similar results in terms of exhibiting Na-Ca-mediated wave patterns that are more chaotic than those for the Ca-mediated and phase waves. However, there are quantitative differences in the wave patterns of each wave type. The Na-Ca-mediated waves in the ORd model show short-lived spirals but the TP06 model does not. The TP06 model supports more Ca-mediated spirals than those in the ORd model, and the TP06 model exhibits more phase-wave patterns than does the ORd model. PMID:26125185

  9. Mediterranean climate modelling: variability and climate change scenarios

    International Nuclear Information System (INIS)

    Somot, S.

    2005-12-01

    Air-sea fluxes, open-sea deep convection and cyclo-genesis are studied in the Mediterranean with the development of a regional coupled model (AORCM). It accurately simulates these processes and their climate variabilities are quantified and studied. The regional coupling shows a significant impact on the number of winter intense cyclo-genesis as well as on associated air-sea fluxes and precipitation. A lower inter-annual variability than in non-coupled models is simulated for fluxes and deep convection. The feedbacks driving this variability are understood. The climate change response is then analysed for the 21. century with the non-coupled models: cyclo-genesis decreases, associated precipitation increases in spring and autumn and decreases in summer. Moreover, a warming and salting of the Mediterranean as well as a strong weakening of its thermohaline circulation occur. This study also concludes with the necessity of using AORCMs to assess climate change impacts on the Mediterranean. (author)

  10. Anxiety, affect, self-esteem, and stress: mediation and moderation effects on depression.

    Science.gov (United States)

    Nima, Ali Al; Rosenberg, Patricia; Archer, Trevor; Garcia, Danilo

    2013-01-01

    Mediation analysis investigates whether a variable (i.e., mediator) changes in regard to an independent variable, in turn, affecting a dependent variable. Moderation analysis, on the other hand, investigates whether the statistical interaction between independent variables predict a dependent variable. Although this difference between these two types of analysis is explicit in current literature, there is still confusion with regard to the mediating and moderating effects of different variables on depression. The purpose of this study was to assess the mediating and moderating effects of anxiety, stress, positive affect, and negative affect on depression. Two hundred and two university students (males  = 93, females  = 113) completed questionnaires assessing anxiety, stress, self-esteem, positive and negative affect, and depression. Mediation and moderation analyses were conducted using techniques based on standard multiple regression and hierarchical regression analyses. The results indicated that (i) anxiety partially mediated the effects of both stress and self-esteem upon depression, (ii) that stress partially mediated the effects of anxiety and positive affect upon depression, (iii) that stress completely mediated the effects of self-esteem on depression, and (iv) that there was a significant interaction between stress and negative affect, and between positive affect and negative affect upon depression. The study highlights different research questions that can be investigated depending on whether researchers decide to use the same variables as mediators and/or moderators.

  11. Predictive and Descriptive CoMFA Models: The Effect of Variable Selection.

    Science.gov (United States)

    Sepehri, Bakhtyar; Omidikia, Nematollah; Kompany-Zareh, Mohsen; Ghavami, Raouf

    2018-01-01

    Aims & Scope: In this research, 8 variable selection approaches were used to investigate the effect of variable selection on the predictive power and stability of CoMFA models. Three data sets including 36 EPAC antagonists, 79 CD38 inhibitors and 57 ATAD2 bromodomain inhibitors were modelled by CoMFA. First of all, for all three data sets, CoMFA models with all CoMFA descriptors were created then by applying each variable selection method a new CoMFA model was developed so for each data set, 9 CoMFA models were built. Obtained results show noisy and uninformative variables affect CoMFA results. Based on created models, applying 5 variable selection approaches including FFD, SRD-FFD, IVE-PLS, SRD-UVEPLS and SPA-jackknife increases the predictive power and stability of CoMFA models significantly. Among them, SPA-jackknife removes most of the variables while FFD retains most of them. FFD and IVE-PLS are time consuming process while SRD-FFD and SRD-UVE-PLS run need to few seconds. Also applying FFD, SRD-FFD, IVE-PLS, SRD-UVE-PLS protect CoMFA countor maps information for both fields. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  12. Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression

    OpenAIRE

    Nima, Ali Al; Rosenberg, Patricia; Archer, Trevor; Garcia, Danilo

    2013-01-01

    Background Mediation analysis investigates whether a variable (i.e., mediator) changes in regard to an independent variable, in turn, affecting a dependent variable. Moderation analysis, on the other hand, investigates whether the statistical interaction between independent variables predict a dependent variable. Although this difference between these two types of analysis is explicit in current literature, there is still confusion with regard to the mediating and moderating effects of differ...

  13. Theory of Mind as a mediator variable between neurocognition and functioning in young individuals in treatment with secondary services for non-psychotic disorders.

    Science.gov (United States)

    Francesconi, Marta; Minichino, Amedeo; Carrión, Ricardo E; Chiaie, Roberto Delle; Bevilacqua, Arturo; Parisi, Maurizio; Rullo, Santo; Bersani, Francesco Saverio; Biondi, Massimo; Cadenhead, Kristin

    2016-12-30

    A large body of studies provides evidence for a link between neurocognition, theory of mind (ToM) and functioning in psychotic spectrum disorders (PSDs), with ToM mediating the effect that neurocognition has on functioning. These three constructs and the related mediation effect may characterize different psychiatric syndromes other than PSDs. Structural equation modelling (SEM) was applied to baseline data from a longitudinal study of 138 young individuals with a recent-onset psychiatric disorder. Using SEM, we tested the hypothesis that ToM mediates the effect of neurocognition on functioning independent of the level of psychosis risk and the diagnostic category. In the mediation model the bootstrapping estimate revealed a significant indirect effect that was the association of social cognition with neurocognition and with functional outcome. ToM was significantly associated with neurocognition and the path from neurocognition to functioning was no longer significant as soon as the mediator (ToM) was entered into the mediation model consistent with a complete mediation effect through ToM. This mediation was independent of the psychosis-risk status and the psychiatric diagnoses. Our results provide useful information on a young psychiatric sample, in which specific therapeutic interventions have the potential to significantly limit functional disability. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  14. Mediators Linking Childhood Adversities and Trauma to Suicidality in Individuals at Risk for Psychosis

    Directory of Open Access Journals (Sweden)

    Stefanie J. Schmidt

    2017-11-01

    Full Text Available Suicidality is highly prevalent in patients at clinical high risk (CHR for psychosis. Childhood adversities and trauma are generally predictive of suicidality. However, the differential effects of adversity/trauma-domains and CHR-criteria, i.e., ultra-high risk and basic symptom criteria, on suicidality remain unclear. Furthermore, the underlying mechanisms and, thus, worthwhile targets for suicide-prevention are still poorly understood. Therefore, structural equation modeling was used to test theory-driven models in 73 CHR-patients. Mediators were psychological variables, i.e., beliefs about one’s own competencies as well as the controllability of events and coping styles. In addition, symptomatic variables (depressiveness, basic symptoms, attenuated psychotic symptoms were hypothesized to mediate the effect of psychological mediators on suicidality as the final outcome variable. Results showed two independent pathways. In the first pathway, emotional and sexual but not physical adversity/trauma was associated with suicidality, which was mediated by dysfunctional competence/control beliefs, a lack of positive coping-strategies and depressiveness. In the second pathway, cognitive basic symptoms but not attenuated psychotic symptoms mediated the relationship between trauma/adversity and suicidality. CHR-patients are, thus, particularly prone to suicidality if adversity/trauma is followed by the development of depressiveness. Regarding the second pathway, this is the first study showing that adversity/trauma led to suicidality through an increased risk for psychosis as indicated by cognitive basic symptoms. As insight is generally associated with suicidality, this may explain why self-experienced basic symptoms increase the risk for it. Consequently, these mediators should be monitored regularly and targeted by integrated interventions as early as possible to enhance resilience against suicidality.

  15. Variable-Structure Control of a Model Glider Airplane

    Science.gov (United States)

    Waszak, Martin R.; Anderson, Mark R.

    2008-01-01

    A variable-structure control system designed to enable a fuselage-heavy airplane to recover from spin has been demonstrated in a hand-launched, instrumented model glider airplane. Variable-structure control is a high-speed switching feedback control technique that has been developed for control of nonlinear dynamic systems.

  16. Distance to food stores & adolescent male fruit and vegetable consumption: mediation effects

    Directory of Open Access Journals (Sweden)

    Cullen Karen W

    2007-09-01

    Full Text Available Abstract Background The physical environments in which adolescents reside and their access to food stores may influence their consumption of fruit and vegetables. This association could either be direct or mediated via psychosocial variables or home availability of fruit and vegetables. A greater understanding of these associations would aide the design of new interventions. The purpose of this study was to examine associations between distance to food stores and restaurants and fruit and vegetable consumption and the possible mediating role of psychosocial variables and home availability. Methods Fruit and vegetable consumption of 204 Boy Scouts was assessed by a food frequency questionnaire in 2003. Participant addresses were geo-coded and distance to different types of food stores and restaurants calculated. Fruit and vegetable preferences, home availability and self-efficacy were measured. Regression models were run with backward deletion of non-significant environmental and psychosocial variables. Mediation tests were performed. Results Residing further away from a small food store (SFS (convenience store and drug store was associated with increased fruit and juice and low fat vegetable consumption. Residing closer to a fast food restaurant was associated with increased high fat vegetable and fruit and juice consumption. Vegetable preferences partially mediated (26% the relationship between low fat vegetable consumption and distance to the nearest SFS. Conclusion Distance to SFS and fast food restaurants were associated with fruit and vegetable consumption among male adolescents. Vegetable preferences partially mediated the distance to low fat vegetable relationship. More research is needed to elucidate how environmental variables impact children's dietary intake.

  17. Job demands-resources model in the context of recovery : Testing recovery experiences as mediators

    OpenAIRE

    Kinnunen, Ulla; Feldt, Taru; Siltaloppi, Marjo; Sonnentag, Sabine

    2011-01-01

    The aim of the present study was to extend the original Job Demands– Resources (JD-R) model by taking into account recovery as an important mediation mechanism between work characteristics and well-being/ill-health. Specifically, we examined whether recovery experiences—strategies promoting recovery—might have a mediating role in the JD-R model among 527 employees from a variety of different jobs. The results showed that psychological detachment fully mediated the effects of job demands on fa...

  18. Computational Fluid Dynamics Modeling of a Supersonic Nozzle and Integration into a Variable Cycle Engine Model

    Science.gov (United States)

    Connolly, Joseph W.; Friedlander, David; Kopasakis, George

    2015-01-01

    This paper covers the development of an integrated nonlinear dynamic simulation for a variable cycle turbofan engine and nozzle that can be integrated with an overall vehicle Aero-Propulso-Servo-Elastic (APSE) model. A previously developed variable cycle turbofan engine model is used for this study and is enhanced here to include variable guide vanes allowing for operation across the supersonic flight regime. The primary focus of this study is to improve the fidelity of the model's thrust response by replacing the simple choked flow equation convergent-divergent nozzle model with a MacCormack method based quasi-1D model. The dynamic response of the nozzle model using the MacCormack method is verified by comparing it against a model of the nozzle using the conservation element/solution element method. A methodology is also presented for the integration of the MacCormack nozzle model with the variable cycle engine.

  19. Breastfeeding and Childhood IQ: The Mediating Role of Gray Matter Volume

    Science.gov (United States)

    Luby, Joan L.; Belden, Andy C.; Whalen, Diana; Harms, Michael P.; Barch, Deanna M.

    2016-01-01

    Objective A substantial body of literature has established the positive effect of breastfeeding on child developmental outcomes. There is increasing consensus that breastfed children have higher IQs after accounting for key variables, including maternal education, IQ, and socioeconomic status. Cross-sectional investigations of the effects of breastfeeding on structural brain development suggest that breastfed infants have larger whole brain, cortical, and white matter volumes. To date, few studies have related these measures of brain structure to IQ in breastfed versus nonbreastfed children in a longitudinal sample. Method Data were derived from the Preschool Depression Study (PDS), a prospective longitudinal study in which children and caregivers were assessed annually for 8 waves over 11 years. A subset completed neuroimaging between the ages of 9.5 and 14.11 years. A total of 148 individuals had breastfeeding data at baseline and complete data on all variables of interest, including IQ and structural neuroimaging. General linear models and process mediation models were used. Results Breastfed children had significantly higher IQ scores and larger whole brain, total gray matter, total cortical gray matter, and subcortical gray matter volumes compared with the nonbreastfed group in models that covaried for key variables. Subcortical gray matter volume significantly mediated the association between breast-feeding and children's IQ scores. Conclusion The study findings suggest that the effects of breastfeeding on child IQ are mediated through subcortical gray volume. This effect and putative mechanism is of public health significance and further supports the importance of breastfeeding in mental health promotion. PMID:27126850

  20. Analytical Model for LLC Resonant Converter With Variable Duty-Cycle Control

    DEFF Research Database (Denmark)

    Shen, Yanfeng; Wang, Huai; Blaabjerg, Frede

    2016-01-01

    are identified and discussed. The proposed model enables a better understanding of the operation characteristics and fast parameter design of the LLC converter, which otherwise cannot be achieved by the existing simulation based methods and numerical models. The results obtained from the proposed model......In LLC resonant converters, the variable duty-cycle control is usually combined with a variable frequency control to widen the gain range, improve the light-load efficiency, or suppress the inrush current during start-up. However, a proper analytical model for the variable duty-cycle controlled LLC...... converter is still not available due to the complexity of operation modes and the nonlinearity of steady-state equations. This paper makes the efforts to develop an analytical model for the LLC converter with variable duty-cycle control. All possible operation models and critical operation characteristics...

  1. Can Environmental Regulations Promote Corporate Environmental Responsibility? Evidence from the Moderated Mediating Effect Model and an Empirical Study in China

    Directory of Open Access Journals (Sweden)

    Benhong Peng

    2018-02-01

    Full Text Available Based on the Stakeholder theory, a moderated mediating effect model is developed to reach the study objective, revealing an important connection that suggests environmental regulations (ERs influence corporate environmental responsibility (CER (Porter Hypothesis. In building the model, the validity of the questionnaire data was analyzed with factor analysis. By employing a two-step approach, a regression analysis is utilized to discuss the mediating effect of altruistic motivation and moderating effect of green innovation, and a structural equation model is used to explore the interactive mechanism of different variables. It is found that altruistic motivation plays a medium role in the relationship between ERs and CER, and green innovation engages a positive coordination in the relationship. The empirical study identifies factors affecting enterprises’ willingness to undertake environmental responsibility, including environment policies, corporate culture, and personal characters among others. It is also revealed that altruistic motivation is conducive to forming a community interests among enterprises and enhancing their resistance to market risks, which explains and corroborates the Stakeholder theory; and the higher the level of green innovation, the more willing enterprises are to implement environmentally friendly operations.

  2. Structural Model of the Effect of Psychological Capital on Success with Due to the Mediating Role of Commitment and Satisfaction

    Directory of Open Access Journals (Sweden)

    M Golparvar

    2016-09-01

    Full Text Available This research was administered with the aim of investigating structural model of the effect of psychological capital on career success with due to the mediating role of satisfaction and commitment among employees of Telecom Company. Research statistical population was male and female employees of Telecom in Isfahan city, who among them two hundred and eighty five persons were selected using convenience sampling. Research instruments were Nguyen et al. Psychological Capital questionnaire, Nabi Job Success (career success Questionnaire, Spector Job Satisfaction Questionnaire and Speier and Venkatesh Organizational Commitment Questionnaire. Data were analyzed using structural equation modeling. Results of structural equation modeling revealed thatin aseriesof sequential relationships, there is a significant effect from psychological capital also on job satisfaction and organizational commitment and there is a significant effect also from job satisfaction and organizational commitment on job success (career success. The results also showed that psychological capital impact on career success was indirectly through job satisfaction and organizational commitment. Overall, the results of this study showed that job satisfaction and organizational commitment were mediating variables in the relationship between psychological capital and career success.

  3. A model for AGN variability on multiple time-scales

    Science.gov (United States)

    Sartori, Lia F.; Schawinski, Kevin; Trakhtenbrot, Benny; Caplar, Neven; Treister, Ezequiel; Koss, Michael J.; Urry, C. Megan; Zhang, C. E.

    2018-05-01

    We present a framework to link and describe active galactic nuclei (AGN) variability on a wide range of time-scales, from days to billions of years. In particular, we concentrate on the AGN variability features related to changes in black hole fuelling and accretion rate. In our framework, the variability features observed in different AGN at different time-scales may be explained as realisations of the same underlying statistical properties. In this context, we propose a model to simulate the evolution of AGN light curves with time based on the probability density function (PDF) and power spectral density (PSD) of the Eddington ratio (L/LEdd) distribution. Motivated by general galaxy population properties, we propose that the PDF may be inspired by the L/LEdd distribution function (ERDF), and that a single (or limited number of) ERDF+PSD set may explain all observed variability features. After outlining the framework and the model, we compile a set of variability measurements in terms of structure function (SF) and magnitude difference. We then combine the variability measurements on a SF plot ranging from days to Gyr. The proposed framework enables constraints on the underlying PSD and the ability to link AGN variability on different time-scales, therefore providing new insights into AGN variability and black hole growth phenomena.

  4. Mediation analysis with time varying exposures and mediators.

    Science.gov (United States)

    VanderWeele, Tyler J; Tchetgen Tchetgen, Eric J

    2017-06-01

    In this paper we consider causal mediation analysis when exposures and mediators vary over time. We give non-parametric identification results, discuss parametric implementation, and also provide a weighting approach to direct and indirect effects based on combining the results of two marginal structural models. We also discuss how our results give rise to a causal interpretation of the effect estimates produced from longitudinal structural equation models. When there are time-varying confounders affected by prior exposure and mediator, natural direct and indirect effects are not identified. However, we define a randomized interventional analogue of natural direct and indirect effects that are identified in this setting. The formula that identifies these effects we refer to as the "mediational g-formula." When there is no mediation, the mediational g-formula reduces to Robins' regular g-formula for longitudinal data. When there are no time-varying confounders affected by prior exposure and mediator values, then the mediational g-formula reduces to a longitudinal version of Pearl's mediation formula. However, the mediational g-formula itself can accommodate both mediation and time-varying confounders and constitutes a general approach to mediation analysis with time-varying exposures and mediators.

  5. Mixed Mediation of Supersymmetry Breaking in Models with Anomalous U(1) Gauge Symmetry

    International Nuclear Information System (INIS)

    Choi, Kiwoon

    2010-01-01

    There can be various built-in sources of supersymmetry breaking in models with anomalous U(1) gauge symmetry, e.g. the U(1) D-term, the F-components of the modulus superfield required for the Green-Schwarz anomaly cancellation mechanism and the chiral matter superfields required to cancel the Fayet-Iliopoulos term, and finally the supergravity auxiliary component which can be parameterized by the F-component of chiral compensator. The relative strength between these supersymmetry breaking sources depends crucially on the characteristics of D-flat direction and also on how the D-flat direction is stabilized at a vacuum with nearly vanishing cosmological constant. We examine the possible pattern of the mediation of supersymmetry breaking in models with anomalous U(1) gauge symmetry, and find that various different mixed mediation scenarios can be realized, including the mirage mediation which corresponds to a mixed modulus-anomaly mediation, D-term domination giving a split sparticle spectrum, and also a mixed gauge-D-term mediation scenario.

  6. Two-step estimation in ratio-of-mediator-probability weighted causal mediation analysis.

    Science.gov (United States)

    Bein, Edward; Deutsch, Jonah; Hong, Guanglei; Porter, Kristin E; Qin, Xu; Yang, Cheng

    2018-04-15

    This study investigates appropriate estimation of estimator variability in the context of causal mediation analysis that employs propensity score-based weighting. Such an analysis decomposes the total effect of a treatment on the outcome into an indirect effect transmitted through a focal mediator and a direct effect bypassing the mediator. Ratio-of-mediator-probability weighting estimates these causal effects by adjusting for the confounding impact of a large number of pretreatment covariates through propensity score-based weighting. In step 1, a propensity score model is estimated. In step 2, the causal effects of interest are estimated using weights derived from the prior step's regression coefficient estimates. Statistical inferences obtained from this 2-step estimation procedure are potentially problematic if the estimated standard errors of the causal effect estimates do not reflect the sampling uncertainty in the estimation of the weights. This study extends to ratio-of-mediator-probability weighting analysis a solution to the 2-step estimation problem by stacking the score functions from both steps. We derive the asymptotic variance-covariance matrix for the indirect effect and direct effect 2-step estimators, provide simulation results, and illustrate with an application study. Our simulation results indicate that the sampling uncertainty in the estimated weights should not be ignored. The standard error estimation using the stacking procedure offers a viable alternative to bootstrap standard error estimation. We discuss broad implications of this approach for causal analysis involving propensity score-based weighting. Copyright © 2018 John Wiley & Sons, Ltd.

  7. Mindfulness facets, trait emotional intelligence, emotional distress, and multiple health behaviors: A serial two-mediator model.

    Science.gov (United States)

    Jacobs, Ingo; Wollny, Anna; Sim, Chu-Won; Horsch, Antje

    2016-06-01

    In the present study, we tested a serial mindfulness facets-trait emotional intelligence (TEI)-emotional distress-multiple health behaviors mediation model in a sample of N = 427 German-speaking occupational therapists. The mindfulness facets-TEI-emotional distress section of the mediation model revealed partial mediation for the mindfulness facets Act with awareness (Act/Aware) and Accept without judgment (Accept); inconsistent mediation was found for the Describe facet. The serial two-mediator model included three mediational pathways that may link each of the four mindfulness facets with multiple health behaviors. Eight out of 12 indirect effects reached significance and fully mediated the links between Act/Aware and Describe to multiple health behaviors; partial mediation was found for Accept. The mindfulness facet Observe was most relevant for multiple health behaviors, but its relation was not amenable to mediation. Implications of the findings will be discussed. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

  8. Classification criteria of syndromes by latent variable models

    DEFF Research Database (Denmark)

    Petersen, Janne

    2010-01-01

    patient's characteristics. These methods may erroneously reduce multiplicity either by combining markers of different phenotypes or by mixing HALS with other processes such as aging. Latent class models identify homogenous groups of patients based on sets of variables, for example symptoms. As no gold......The thesis has two parts; one clinical part: studying the dimensions of human immunodeficiency virus associated lipodystrophy syndrome (HALS) by latent class models, and a more statistical part: investigating how to predict scores of latent variables so these can be used in subsequent regression...... standard exists for diagnosing HALS the normally applied diagnostic models cannot be used. Latent class models, which have never before been used to diagnose HALS, make it possible, under certain assumptions, to: statistically evaluate the number of phenotypes, test for mixing of HALS with other processes...

  9. Anxiety, affect, self-esteem, and stress: mediation and moderation effects on depression.

    Directory of Open Access Journals (Sweden)

    Ali Al Nima

    Full Text Available Mediation analysis investigates whether a variable (i.e., mediator changes in regard to an independent variable, in turn, affecting a dependent variable. Moderation analysis, on the other hand, investigates whether the statistical interaction between independent variables predict a dependent variable. Although this difference between these two types of analysis is explicit in current literature, there is still confusion with regard to the mediating and moderating effects of different variables on depression. The purpose of this study was to assess the mediating and moderating effects of anxiety, stress, positive affect, and negative affect on depression.Two hundred and two university students (males  = 93, females  = 113 completed questionnaires assessing anxiety, stress, self-esteem, positive and negative affect, and depression. Mediation and moderation analyses were conducted using techniques based on standard multiple regression and hierarchical regression analyses.The results indicated that (i anxiety partially mediated the effects of both stress and self-esteem upon depression, (ii that stress partially mediated the effects of anxiety and positive affect upon depression, (iii that stress completely mediated the effects of self-esteem on depression, and (iv that there was a significant interaction between stress and negative affect, and between positive affect and negative affect upon depression.The study highlights different research questions that can be investigated depending on whether researchers decide to use the same variables as mediators and/or moderators.

  10. Anxiety, Affect, Self-Esteem, and Stress: Mediation and Moderation Effects on Depression

    Science.gov (United States)

    Nima, Ali Al; Rosenberg, Patricia; Archer, Trevor; Garcia, Danilo

    2013-01-01

    Background Mediation analysis investigates whether a variable (i.e., mediator) changes in regard to an independent variable, in turn, affecting a dependent variable. Moderation analysis, on the other hand, investigates whether the statistical interaction between independent variables predict a dependent variable. Although this difference between these two types of analysis is explicit in current literature, there is still confusion with regard to the mediating and moderating effects of different variables on depression. The purpose of this study was to assess the mediating and moderating effects of anxiety, stress, positive affect, and negative affect on depression. Methods Two hundred and two university students (males  = 93, females  = 113) completed questionnaires assessing anxiety, stress, self-esteem, positive and negative affect, and depression. Mediation and moderation analyses were conducted using techniques based on standard multiple regression and hierarchical regression analyses. Main Findings The results indicated that (i) anxiety partially mediated the effects of both stress and self-esteem upon depression, (ii) that stress partially mediated the effects of anxiety and positive affect upon depression, (iii) that stress completely mediated the effects of self-esteem on depression, and (iv) that there was a significant interaction between stress and negative affect, and between positive affect and negative affect upon depression. Conclusion The study highlights different research questions that can be investigated depending on whether researchers decide to use the same variables as mediators and/or moderators. PMID:24039896

  11. Optimism on quality of life in Portuguese chronic patients: moderator/mediator?

    Directory of Open Access Journals (Sweden)

    Estela Vilhena

    2014-07-01

    Full Text Available Objective: optimism is an important variable that has consistently been shown to affect adjustment to quality of life in chronic diseases. This study aims to clarify if dispositional optimism exerts a moderating or a mediating influence on the personality traits-quality of life association, in Portuguese chronic patients. Methods: multiple regression models were used to test the moderation and mediation effects of dispositional optimism in quality of life. A sample of 729 patients was recruited in Portugal's main hospitals and completed self-reported questionnaires assessing socio-demographic and clinical variables, personality, dispositional optimism, quality of life (QoL and subjective well-being (SWB. Results: the results of the regression models showed that dispositional optimism did not moderate the relationships between personality traits and quality of life. After controlling for gender, age, education level and severity of disease perception, the effects of personality traits on QoL and in SWB were mediated by dispositional optimism (partially and completely, except for the links between neuroticism/openness to experience and physical health. Conclusion: dispositional optimism is more likely to play a mediating, rather than a moderating role in personality traits-quality of life pathway in Portuguese chronic patients, suggesting that "the expectation that good things will happen" contributes to a better quality of life and subjective well-being.

  12. The mediating and moderating role of burnout and emotional intelligence in the relationship between organizational justice and work misbehavior

    Directory of Open Access Journals (Sweden)

    Or Shkoler

    2017-07-01

    Full Text Available The current research (Figure 1 examined the antecedents of work misbehaviors (WMBs by means of organizational justice perceptions (as a predictor, experienced burnout (as a mediator, and emotional intelligence (as a buffer. A heterogeneous sample of 243 employees was acquired in order to assess correlative associations between the variables, a mediation effect, and two moderation effects. In order to test the mediation effect further and the model fit, structural equation modelling (SEM was employed. Theoretical and practical implications are discussed.

  13. Divergent pathways to influence: Cognition and behavior differentially mediate the effects of optimism on physical and mental quality of life in Chinese university students.

    Science.gov (United States)

    Ramsay, Jonathan E; Yang, Fang; Pang, Joyce S; Lai, Ching-Man; Ho, Roger Cm; Mak, Kwok-Kei

    2015-07-01

    Previous research has indicated that both cognitive and behavioral variables mediate the positive effect of optimism on quality of life; yet few attempts have been made to accommodate these constructs into a single explanatory framework. Adopting Fredrickson's broaden-and-build perspective, we examined the relationships between optimism, self-rated health, resilience, exercise, and quality of life in 365 Chinese university students using path analysis. For physical quality of life, a two-stage model, in which the effects of optimism were sequentially mediated by cognitive and behavioral variables, provided the best fit. A one-stage model, with full mediation by cognitive variables, provided the best fit for mental quality of life. This suggests that optimism influences physical and mental quality of life via different pathways. © The Author(s) 2013.

  14. Fixed transaction costs and modelling limited dependent variables

    NARCIS (Netherlands)

    Hempenius, A.L.

    1994-01-01

    As an alternative to the Tobit model, for vectors of limited dependent variables, I suggest a model, which follows from explicitly using fixed costs, if appropriate of course, in the utility function of the decision-maker.

  15. The Mediating Roles of Internal Context Variables in the Relationship between Distributed Leadership Perceptions and Continuous Change Behaviours of Public School Teachers

    Science.gov (United States)

    Kondakci, Yasar; Zayim, Merve; Beycioglu, Kadir; Sincar, Mehmet; Ugurlu, Celal T

    2016-01-01

    This study aims at building a theoretical base for continuous change in education and using this base to test the mediating roles of two key contextual variables, knowledge sharing and trust, in the relationship between the distributed leadership perceptions and continuous change behaviours of teachers. Data were collected from 687 public school…

  16. Sparse modeling of spatial environmental variables associated with asthma.

    Science.gov (United States)

    Chang, Timothy S; Gangnon, Ronald E; David Page, C; Buckingham, William R; Tandias, Aman; Cowan, Kelly J; Tomasallo, Carrie D; Arndt, Brian G; Hanrahan, Lawrence P; Guilbert, Theresa W

    2015-02-01

    Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. Evaluating two model reduction approaches for large scale hedonic models sensitive to omitted variables and multicollinearity

    DEFF Research Database (Denmark)

    Panduro, Toke Emil; Thorsen, Bo Jellesmark

    2014-01-01

    Hedonic models in environmental valuation studies have grown in terms of number of transactions and number of explanatory variables. We focus on the practical challenge of model reduction, when aiming for reliable parsimonious models, sensitive to omitted variable bias and multicollinearity. We...

  18. Change in goal ratings as a mediating variable between self-efficacy and physical activity in older men.

    Science.gov (United States)

    Hall, Katherine S; Crowley, Gail M; McConnell, Eleanor S; Bosworth, Hayden B; Sloane, Richard; Ekelund, Carola C; Morey, Miriam C

    2010-06-01

    Few studies have examined the associations between exercise self-efficacy, goals, and physical activity over time. This study examines whether self-selected goals mediate the changes in exercise self-efficacy on physical activity over 12 months. Data are derived from 313 older men participating in the Veterans LIFE Study. Changes in exercise self-efficacy were significantly associated with changes in physical activity both directly (betas = 0.25 and 0.24, p goal ratings (betas = 0.19 and 0.20, p goal setting continued to partially mediate the relationship between exercise self-efficacy and physical activity when covariates were added to the models. This study extends the application of social cognitive and goal-setting theories to physical activity by showing that goals partially mediate the relationship between exercise self-efficacy and physical activity over time.

  19. When ab ≠ c - c': published errors in the reports of single-mediator models.

    Science.gov (United States)

    Petrocelli, John V; Clarkson, Joshua J; Whitmire, Melanie B; Moon, Paul E

    2013-06-01

    Accurate reports of mediation analyses are critical to the assessment of inferences related to causality, since these inferences are consequential for both the evaluation of previous research (e.g., meta-analyses) and the progression of future research. However, upon reexamination, approximately 15% of published articles in psychology contain at least one incorrect statistical conclusion (Bakker & Wicherts, Behavior research methods, 43, 666-678 2011), disparities that beget the question of inaccuracy in mediation reports. To quantify this question of inaccuracy, articles reporting standard use of single-mediator models in three high-impact journals in personality and social psychology during 2011 were examined. More than 24% of the 156 models coded failed an equivalence test (i.e., ab = c - c'), suggesting that one or more regression coefficients in mediation analyses are frequently misreported. The authors cite common sources of errors, provide recommendations for enhanced accuracy in reports of single-mediator models, and discuss implications for alternative methods.

  20. Utilized social support and self-esteem mediate the relationship between perceived social support and suicide ideation. A test of a multiple mediator model.

    Science.gov (United States)

    Kleiman, Evan M; Riskind, John H

    2013-01-01

    While perceived social support has received considerable research as a protective factor for suicide ideation, little attention has been given to the mechanisms that mediate its effects. We integrated two theoretical models, Joiner's (2005) interpersonal theory of suicide and Leary's (Leary, Tambor, Terdal, & Downs, 1995) sociometer theory of self-esteem to investigate two hypothesized mechanisms, utilization of social support and self-esteem. Specifically, we hypothesized that individuals must utilize the social support they perceive that would result in increased self-esteem, which in turn buffers them from suicide ideation. Participants were 172 college students who completed measures of social support, self-esteem, and suicide ideation. Tests of simple mediation indicate that utilization of social support and self-esteem may each individually help to mediate the perceived social support/suicide ideation relationship. Additionally, a test of multiple mediators using bootstrapping supported the hypothesized multiple-mediator model. The use of a cross-sectional design limited our ability to find true cause-and-effect relationships. Results suggested that utilized social support and self-esteem both operate as individual moderators in the social support/self-esteem relationship. Results further suggested, in a comprehensive model, that perceived social support buffers suicide ideation through utilization of social support and increases in self-esteem.

  1. Variability aware compact model characterization for statistical circuit design optimization

    Science.gov (United States)

    Qiao, Ying; Qian, Kun; Spanos, Costas J.

    2012-03-01

    Variability modeling at the compact transistor model level can enable statistically optimized designs in view of limitations imposed by the fabrication technology. In this work we propose an efficient variabilityaware compact model characterization methodology based on the linear propagation of variance. Hierarchical spatial variability patterns of selected compact model parameters are directly calculated from transistor array test structures. This methodology has been implemented and tested using transistor I-V measurements and the EKV-EPFL compact model. Calculation results compare well to full-wafer direct model parameter extractions. Further studies are done on the proper selection of both compact model parameters and electrical measurement metrics used in the method.

  2. Interannual modes of variability of Southern Hemisphere atmospheric circulation in CMIP3 models

    International Nuclear Information System (INIS)

    Grainger, S; Frederiksen, C S; Zheng, X

    2010-01-01

    The atmospheric circulation acts as a bridge between large-scale sources of climate variability, and climate variability on regional scales. Here a statistical method is applied to monthly mean Southern Hemisphere 500hPa geopotential height to separate the interannual variability of the seasonal mean into intraseasonal and slowly varying (time scales of a season or longer) components. Intraseasonal and slow modes of variability are estimated from realisations of models from the Coupled Model Intercomparison Project Phase 3 (CMIP3) twentieth century coupled climate simulation (20c3m) and are evaluated against those estimated from reanalysis data. The intraseasonal modes of variability are generally well reproduced across all CMIP3 20c3m models for both Southern Hemisphere summer and winter. The slow modes are in general less well reproduced than the intraseasonal modes, and there are larger differences between realisations than for the intraseasonal modes. New diagnostics are proposed to evaluate model variability. It is found that differences between realisations from each model are generally less than inter-model differences. Differences between model-mean diagnostics are found. The results obtained are applicable to assessing the reliability of changes in atmospheric circulation variability in CMIP3 models and for their suitability for further studies of regional climate variability.

  3. Socio-hydrologic modeling to understand and mediate the competition for water between agriculture development and environmental health: Murrumbidgee River basin, Australia

    Science.gov (United States)

    van Emmerik, T. H. M.; Li, Z.; Sivapalan, M.; Pande, S.; Kandasamy, J.; Savenije, H. H. G.; Chanan, A.; Vigneswaran, S.

    2014-10-01

    Competition for water between humans and ecosystems is set to become a flash point in the coming decades in many parts of the world. An entirely new and comprehensive quantitative framework is needed to establish a holistic understanding of that competition, thereby enabling the development of effective mediation strategies. This paper presents a modeling study centered on the Murrumbidgee River basin (MRB). The MRB has witnessed a unique system dynamics over the last 100 years as a result of interactions between patterns of water management and climate driven hydrological variability. Data analysis has revealed a pendulum swing between agricultural development and restoration of environmental health and ecosystem services over different stages of basin-scale water resource development. A parsimonious, stylized, quasi-distributed coupled socio-hydrologic system model that simulates the two-way coupling between human and hydrological systems of the MRB is used to mimic and explain dominant features of the pendulum swing. The model consists of coupled nonlinear ordinary differential equations that describe the interaction between five state variables that govern the co-evolution: reservoir storage, irrigated area, human population, ecosystem health, and environmental awareness. The model simulations track the propagation of the external climatic and socio-economic drivers through this coupled, complex system to the emergence of the pendulum swing. The model results point to a competition between human "productive" and environmental "restorative" forces that underpin the pendulum swing. Both the forces are endogenous, i.e., generated by the system dynamics in response to external drivers and mediated by humans through technology change and environmental awareness, respectively. Sensitivity analysis carried out with the model further reveals that socio-hydrologic modeling can be used as a tool to explain or gain insight into observed co-evolutionary dynamics of diverse

  4. Moderated mediation analysis: An illustration using the association of gender with delinquency and mental health.

    Science.gov (United States)

    Miles, Jeremy N V; Kulesza, Magdalena; Ewing, Brett; Shih, Regina A; Tucker, Joan S; D'Amico, Elizabeth J

    When researchers find an association between two variables, it is useful to evaluate the role of other constructs in this association. While assessing these mediation effects, it is important to determine if results are equal for different groups. It is possible that the strength of a mediation effect may differ for males and females, for example - such an effect is known as moderated mediation. Participants were 2532 adolescents from diverse ethnic/racial backgrounds and equally distributed across gender. The goal of this study was to investigate parental respect as a potential mediator of the relationship between gender and delinquency and mental health, and to determine whether observed mediation is moderated by gender. Parental respect mediated the association between gender and both delinquency and mental health. Specifically, parental respect was a protective factor against delinquency and mental health problems for both females and males. Demonstrated the process of estimating models in Lavaan, using two approaches (i.e. single group regression and multiple group regression model), and including covariates in both models.

  5. Benchmark validation of statistical models: Application to mediation analysis of imagery and memory.

    Science.gov (United States)

    MacKinnon, David P; Valente, Matthew J; Wurpts, Ingrid C

    2018-03-29

    This article describes benchmark validation, an approach to validating a statistical model. According to benchmark validation, a valid model generates estimates and research conclusions consistent with a known substantive effect. Three types of benchmark validation-(a) benchmark value, (b) benchmark estimate, and (c) benchmark effect-are described and illustrated with examples. Benchmark validation methods are especially useful for statistical models with assumptions that are untestable or very difficult to test. Benchmark effect validation methods were applied to evaluate statistical mediation analysis in eight studies using the established effect that increasing mental imagery improves recall of words. Statistical mediation analysis led to conclusions about mediation that were consistent with established theory that increased imagery leads to increased word recall. Benchmark validation based on established substantive theory is discussed as a general way to investigate characteristics of statistical models and a complement to mathematical proof and statistical simulation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  6. Within-subject mediation analysis for experimental data in cognitive psychology and neuroscience.

    Science.gov (United States)

    Vuorre, Matti; Bolger, Niall

    2017-12-15

    Statistical mediation allows researchers to investigate potential causal effects of experimental manipulations through intervening variables. It is a powerful tool for assessing the presence and strength of postulated causal mechanisms. Although mediation is used in certain areas of psychology, it is rarely applied in cognitive psychology and neuroscience. One reason for the scarcity of applications is that these areas of psychology commonly employ within-subjects designs, and mediation models for within-subjects data are considerably more complicated than for between-subjects data. Here, we draw attention to the importance and ubiquity of mediational hypotheses in within-subjects designs, and we present a general and flexible software package for conducting Bayesian within-subjects mediation analyses in the R programming environment. We use experimental data from cognitive psychology to illustrate the benefits of within-subject mediation for theory testing and comparison.

  7. A novel methodology improves reservoir characterization models using geologic fuzzy variables

    Energy Technology Data Exchange (ETDEWEB)

    Soto B, Rodolfo [DIGITOIL, Maracaibo (Venezuela); Soto O, David A. [Texas A and M University, College Station, TX (United States)

    2004-07-01

    One of the research projects carried out in Cusiana field to explain its rapid decline during the last years was to get better permeability models. The reservoir of this field has a complex layered system that it is not easy to model using conventional methods. The new technique included the development of porosity and permeability maps from cored wells following the same trend of the sand depositions for each facie or layer according to the sedimentary facie and the depositional system models. Then, we used fuzzy logic to reproduce those maps in three dimensions as geologic fuzzy variables. After multivariate statistical and factor analyses, we found independence and a good correlation coefficient between the geologic fuzzy variables and core permeability and porosity. This means, the geologic fuzzy variable could explain the fabric, the grain size and the pore geometry of the reservoir rock trough the field. Finally, we developed a neural network permeability model using porosity, gamma ray and the geologic fuzzy variable as input variables. This model has a cross-correlation coefficient of 0.873 and average absolute error of 33% compared with the actual model with a correlation coefficient of 0.511 and absolute error greater than 250%. We tested different methodologies, but this new one showed dramatically be a promiser way to get better permeability models. The use of the models have had a high impact in the explanation of well performance and workovers, and reservoir simulation models. (author)

  8. Plasticity models of material variability based on uncertainty quantification techniques

    Energy Technology Data Exchange (ETDEWEB)

    Jones, Reese E. [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Rizzi, Francesco [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Boyce, Brad [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Templeton, Jeremy Alan [Sandia National Lab. (SNL-CA), Livermore, CA (United States); Ostien, Jakob [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

    2017-11-01

    The advent of fabrication techniques like additive manufacturing has focused attention on the considerable variability of material response due to defects and other micro-structural aspects. This variability motivates the development of an enhanced design methodology that incorporates inherent material variability to provide robust predictions of performance. In this work, we develop plasticity models capable of representing the distribution of mechanical responses observed in experiments using traditional plasticity models of the mean response and recently developed uncertainty quantification (UQ) techniques. Lastly, we demonstrate that the new method provides predictive realizations that are superior to more traditional ones, and how these UQ techniques can be used in model selection and assessing the quality of calibrated physical parameters.

  9. Stressors and anxiety in dementia caregiving: multiple mediation analysis of rumination, experiential avoidance, and leisure.

    Science.gov (United States)

    Romero-Moreno, R; Losada, A; Márquez-González, M; Mausbach, B T

    2016-11-01

    Despite the robust associations between stressors and anxiety in dementia caregiving, there is a lack of research examining which factors contribute to explain this relationship. This study was designed to test a multiple mediation model of behavioral and psychological symptoms of dementia (BPSD) and anxiety that proposes higher levels of rumination and experiential avoidance and lower levels of leisure satisfaction as potential mediating variables. The sample consisted of 256 family caregivers. In order to test a simultaneously parallel multiple mediation model of the BPSD to anxiety pathway, a PROCESS method was used and bias-corrected and accelerated bootstrapping method was used to test confidence intervals. Higher levels of stressors significantly predicted anxiety. Greater stressors significantly predicted higher levels of rumination and experiential avoidance, and lower levels of leisure satisfaction. These three coping variables significantly predicted anxiety. Finally, rumination, experiential avoidance, and leisure satisfaction significantly mediated the link between stressors and anxiety. The explained variance for the final model was 47.09%. Significant contrasts were found between rumination and leisure satisfaction, with rumination being a significantly higher mediator. The results suggest that caregivers' experiential avoidance, rumination, and leisure satisfaction may function as mechanisms through which BPSD influence on caregivers' anxiety. Training caregivers in reducing their levels of experiential avoidance and rumination by techniques that foster their ability of acceptance of their negative internal experiences, and increase their level of leisure satisfaction, may be helpful to reduce their anxiety symptoms developed by stressors.

  10. Efficient Business Service Consumption by Customization with Variability Modelling

    Directory of Open Access Journals (Sweden)

    Michael Stollberg

    2010-07-01

    Full Text Available The establishment of service orientation in industry determines the need for efficient engineering technologies that properly support the whole life cycle of service provision and consumption. A central challenge is adequate support for the efficient employment of komplex services in their individual application context. This becomes particularly important for large-scale enterprise technologies where generic services are designed for reuse in several business scenarios. In this article we complement our work regarding Service Variability Modelling presented in a previous publication. There we presented an approach for the customization of services for individual application contexts by creating simplified variants, based on model-driven variability management. That work presents our revised service variability metamodel, new features of the variability tools and an applicability study, which reveals that substantial improvements on the efficiency of standard business service consumption under both usability and economic aspects can be achieved.

  11. mediation: R Package for Causal Mediation Analysis

    Directory of Open Access Journals (Sweden)

    Dustin Tingley

    2014-09-01

    Full Text Available In this paper, we describe the R package mediation for conducting causal mediation analysis in applied empirical research. In many scientific disciplines, the goal of researchers is not only estimating causal effects of a treatment but also understanding the process in which the treatment causally affects the outcome. Causal mediation analysis is frequently used to assess potential causal mechanisms. The mediation package implements a comprehensive suite of statistical tools for conducting such an analysis. The package is organized into two distinct approaches. Using the model-based approach, researchers can estimate causal mediation effects and conduct sensitivity analysis under the standard research design. Furthermore, the design-based approach provides several analysis tools that are applicable under different experimental designs. This approach requires weaker assumptions than the model-based approach. We also implement a statistical method for dealing with multiple (causally dependent mediators, which are often encountered in practice. Finally, the package also offers a methodology for assessing causal mediation in the presence of treatment noncompliance, a common problem in randomized trials.

  12. The Mediated MIMIC Model for Understanding the Underlying Mechanism of DIF

    Science.gov (United States)

    Cheng, Ying; Shao, Can; Lathrop, Quinn N.

    2016-01-01

    Due to its flexibility, the multiple-indicator, multiple-causes (MIMIC) model has become an increasingly popular method for the detection of differential item functioning (DIF). In this article, we propose the mediated MIMIC model method to uncover the underlying mechanism of DIF. This method extends the usual MIMIC model by including one variable…

  13. Attributional style as a mediator between parental abuse risk and child internalizing symptomatology.

    Science.gov (United States)

    Rodriguez, Christina M

    2006-05-01

    This study examined a model wherein children's attributional style mediates the relationship between parental physical child-abuse risk and children's internalizing problems. Using structural equation modeling, three indices of abuse risk were selected (child abuse potential, physical discipline use, and dysfunctional parenting style) and two indices of children's internalizing problems (depression and anxiety). The sample included 75 parent-child dyads, in which parents reported on their abuse risk and children independently completed measures of depressive and anxious symptomatology and a measure on their attributional style. Findings supported the model that children's attributional style for positive events (but not negative events) partially mediated the relationship between abuse risk and internalizing symptoms, with significant direct and indirect effects of abuse risk on internalizing symptomatology. Future directions to continue evaluating additional mediators and other possible contextual variables are discussed.

  14. Testing a multiple mediation model of Asian American college students' willingness to see a counselor.

    Science.gov (United States)

    Kim, Paul Youngbin; Park, Irene J K

    2009-07-01

    Adapting the theory of reasoned action, the present study examined help-seeking beliefs, attitudes, and intent among Asian American college students (N = 110). A multiple mediation model was tested to see if the relation between Asian values and willingness to see a counselor was mediated by attitudes toward seeking professional psychological help and subjective norm. A bootstrapping procedure was used to test the multiple mediation model. Results indicated that subjective norm was the sole significant mediator of the effect of Asian values on willingness to see a counselor. The findings highlight the importance of social influences on help-seeking intent among Asian American college students.

  15. Peer Victimization and Dating Violence Victimization: The Mediating Role of Loneliness, Depressed Mood, and Life Satisfaction.

    Science.gov (United States)

    Cava, María-Jesús; Buelga, Sofía; Tomás, Inés

    2018-03-01

    Peer victimization and dating violence victimization have serious negative effects on adolescents' health, and they seem to be related. However, the mediating processes in this relationship have not been sufficiently analyzed. The purpose of this study was to analyze the direct and indirect relationships between peer victimization and dating violence victimization, considering the possible mediator role of loneliness, depressed mood, and life satisfaction. These relationships are analyzed in boys and girls, and in early and middle adolescence. From an initial sample of 1,038 Spanish adolescents, those who had or had had in the past 12 months a dating relationship (647 adolescents; 49.1% boys, M = 14.38, SD = 1.43) were included in this study. Multigroup structural equation modeling was used to test a double mediation model simultaneously for boys and girls, testing the invariance of the relationships among variables across genders. The same technique was used to test the model simultaneously for early and middle adolescence, testing the invariance of the relationships among variables across age groups. Results revealed a positive direct relationship between peer victimization and dating violence victimization, as well as the partial mediating role of loneliness and life satisfaction in this relationship. The mediator role of depressed mood was not supported. The same mediational model was confirmed in boys and girls, and in early and middle adolescence. These results highlight the important role of loneliness and life satisfaction to explain the link between peer victimization and dating violence victimization in adolescence. These findings may be useful for developing intervention programs aimed at preventing situations of multiple victimization during adolescence.

  16. Local models of Gauge Mediated Supersymmetry Breaking in String Theory

    CERN Document Server

    Garcia-Etxebarria, I; Uranga, Angel M; Garcia-Etxebarria, Inaki; Saad, Fouad; Uranga, Angel M.

    2006-01-01

    We describe local Calabi-Yau geometries with two isolated singularities at which systems of D3- and D7-branes are located, leading to chiral sectors corresponding to a semi-realistic visible sector and a hidden sector with dynamical supersymmetry breaking. We provide explicit models with a 3-family MSSM-like visible sector, and a hidden sector breaking supersymmetry at a meta-stable minimum. For singularities separated by a distance smaller than the string scale, this construction leads to a simple realization of gauge mediated supersymmetry breaking in string theory. The models are simple enough to allow the explicit computation of the massive messenger sector, using dimer techniques for branes at singularities. The local character of the configurations makes manifest the UV insensitivity of the supersymmetry breaking mediation.

  17. Within-Subject Mediation Analysis in AB/BA Crossover Designs.

    Science.gov (United States)

    Josephy, Haeike; Vansteelandt, Stijn; Vanderhasselt, Marie-Anne; Loeys, Tom

    2015-05-01

    Crossover trials are widely used to assess the effect of a reversible exposure on an outcome of interest. To gain further insight into the underlying mechanisms of this effect, researchers may be interested in exploring whether or not it runs through a specific intermediate variable: the mediator. Mediation analysis in crossover designs has received scant attention so far and is mostly confined to the traditional Baron and Kenny approach. We aim to tackle mediation analysis within the counterfactual framework and elucidate the assumptions under which the direct and indirect effects can be identified in AB/BA crossover studies. Notably, we show that both effects are identifiable in certain statistical models, even in the presence of unmeasured time-independent (or upper-level) confounding of the mediator-outcome relation. Employing the mediation formula, we derive expressions for the direct and indirect effects in within-subject designs for continuous outcomes that lend themselves to linear modelling, under a large variety of settings. We discuss an estimation approach based on regressing differences in outcomes on differences in mediators and show how to allow for period effects as well as different types of moderation. The performance of this approach is compared to other existing methods through simulations and is illustrated with data from a neurobehavioural study. Lastly, we demonstrate how a sensitivity analysis can be performed that is able to assess the robustness of both the direct and indirect effect against violation of the "no unmeasured lower-level mediator-outcome confounding" assumption.

  18. Shyness, Masculine Ideology, Physical Attractiveness, and Emotional Inexpressiveness: Testing a Mediational Model of Men's Interpersonal Competence.

    Science.gov (United States)

    Bruch, Monroe A.; Berko, Eric H.; Haase, Richard F.

    1998-01-01

    A model was tested in which emotional inexpressiveness fully mediates the relationship of shyness, gender identity, and physical attractiveness with men's interpersonal competence. In a second study, a partially mediated model explained the data better. Implications for further modifications and testing of the model and for counseling practice are…

  19. Generalized Network Psychometrics : Combining Network and Latent Variable Models

    NARCIS (Netherlands)

    Epskamp, S.; Rhemtulla, M.; Borsboom, D.

    2017-01-01

    We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between

  20. A realistic extension of gauge-mediated SUSY-breaking model with superconformal hidden sector

    International Nuclear Information System (INIS)

    Asano, Masaki; Hisano, Junji; Okada, Takashi; Sugiyama, Shohei

    2009-01-01

    The sequestering of supersymmetry (SUSY) breaking parameters, which is induced by superconformal hidden sector, is one of the solutions for the μ/B μ problem in gauge-mediated SUSY-breaking scenario. However, it is found that the minimal messenger model does not derive the correct electroweak symmetry breaking. In this Letter we present a model which has the coupling of the messengers with the SO(10) GUT-symmetry breaking Higgs fields. The model is one of the realistic extensions of the gauge mediation model with superconformal hidden sector. It is shown that the extension is applicable for a broad range of conformality breaking scale

  1. Can Geostatistical Models Represent Nature's Variability? An Analysis Using Flume Experiments

    Science.gov (United States)

    Scheidt, C.; Fernandes, A. M.; Paola, C.; Caers, J.

    2015-12-01

    The lack of understanding in the Earth's geological and physical processes governing sediment deposition render subsurface modeling subject to large uncertainty. Geostatistics is often used to model uncertainty because of its capability to stochastically generate spatially varying realizations of the subsurface. These methods can generate a range of realizations of a given pattern - but how representative are these of the full natural variability? And how can we identify the minimum set of images that represent this natural variability? Here we use this minimum set to define the geostatistical prior model: a set of training images that represent the range of patterns generated by autogenic variability in the sedimentary environment under study. The proper definition of the prior model is essential in capturing the variability of the depositional patterns. This work starts with a set of overhead images from an experimental basin that showed ongoing autogenic variability. We use the images to analyze the essential characteristics of this suite of patterns. In particular, our goal is to define a prior model (a minimal set of selected training images) such that geostatistical algorithms, when applied to this set, can reproduce the full measured variability. A necessary prerequisite is to define a measure of variability. In this study, we measure variability using a dissimilarity distance between the images. The distance indicates whether two snapshots contain similar depositional patterns. To reproduce the variability in the images, we apply an MPS algorithm to the set of selected snapshots of the sedimentary basin that serve as training images. The training images are chosen from among the initial set by using the distance measure to ensure that only dissimilar images are chosen. Preliminary investigations show that MPS can reproduce fairly accurately the natural variability of the experimental depositional system. Furthermore, the selected training images provide

  2. Reasons for Testing Mediation in the Absence of an Intervention Effect: A Research Imperative in Prevention and Intervention Research.

    Science.gov (United States)

    O'Rourke, Holly P; MacKinnon, David P

    2018-03-01

    Mediation models are used in prevention and intervention research to assess the mechanisms by which interventions influence outcomes. However, researchers may not investigate mediators in the absence of intervention effects on the primary outcome variable. There is emerging evidence that in some situations, tests of mediated effects can be statistically significant when the total intervention effect is not statistically significant. In addition, there are important conceptual and practical reasons for investigating mediation when the intervention effect is nonsignificant. This article discusses the conditions under which mediation may be present when an intervention effect does not have a statistically significant effect and why mediation should always be considered important. Mediation may be present in the following conditions: when the total and mediated effects are equal in value, when the mediated and direct effects have opposing signs, when mediated effects are equal across single and multiple-mediator models, and when specific mediated effects have opposing signs. Mediation should be conducted in every study because it provides the opportunity to test known and replicable mediators, to use mediators as an intervention manipulation check, and to address action and conceptual theory in intervention models. Mediators are central to intervention programs, and mediators should be investigated for the valuable information they provide about the success or failure of interventions.

  3. Causal Mediation Analysis for the Cox Proportional Hazards Model with a Smooth Baseline Hazard Estimator.

    Science.gov (United States)

    Wang, Wei; Albert, Jeffrey M

    2017-08-01

    An important problem within the social, behavioral, and health sciences is how to partition an exposure effect (e.g. treatment or risk factor) among specific pathway effects and to quantify the importance of each pathway. Mediation analysis based on the potential outcomes framework is an important tool to address this problem and we consider the estimation of mediation effects for the proportional hazards model in this paper. We give precise definitions of the total effect, natural indirect effect, and natural direct effect in terms of the survival probability, hazard function, and restricted mean survival time within the standard two-stage mediation framework. To estimate the mediation effects on different scales, we propose a mediation formula approach in which simple parametric models (fractional polynomials or restricted cubic splines) are utilized to approximate the baseline log cumulative hazard function. Simulation study results demonstrate low bias of the mediation effect estimators and close-to-nominal coverage probability of the confidence intervals for a wide range of complex hazard shapes. We apply this method to the Jackson Heart Study data and conduct sensitivity analysis to assess the impact on the mediation effects inference when the no unmeasured mediator-outcome confounding assumption is violated.

  4. Plasmon point spread functions: How do we model plasmon-mediated emission processes?

    Science.gov (United States)

    Willets, Katherine A.

    2014-02-01

    A major challenge with studying plasmon-mediated emission events is the small size of plasmonic nanoparticles relative to the wavelength of light. Objects smaller than roughly half the wavelength of light will appear as diffraction-limited spots in far-field optical images, presenting a significant experimental challenge for studying plasmonic processes on the nanoscale. Super-resolution imaging has recently been applied to plasmonic nanosystems and allows plasmon-mediated emission to be resolved on the order of ˜5 nm. In super-resolution imaging, a diffraction-limited spot is fit to some model function in order to calculate the position of the emission centroid, which represents the location of the emitter. However, the accuracy of the centroid position strongly depends on how well the fitting function describes the data. This Perspective discusses the commonly used two-dimensional Gaussian fitting function applied to super-resolution imaging of plasmon-mediated emission, then introduces an alternative model based on dipole point spread functions. The two fitting models are compared and contrasted for super-resolution imaging of nanoparticle scattering/luminescence, surface-enhanced Raman scattering, and surface-enhanced fluorescence.

  5. Internal variability in a regional climate model over West Africa

    Energy Technology Data Exchange (ETDEWEB)

    Vanvyve, Emilie; Ypersele, Jean-Pascal van [Universite catholique de Louvain, Institut d' astronomie et de geophysique Georges Lemaitre, Louvain-la-Neuve (Belgium); Hall, Nicholas [Laboratoire d' Etudes en Geophysique et Oceanographie Spatiales/Centre National d' Etudes Spatiales, Toulouse Cedex 9 (France); Messager, Christophe [University of Leeds, Institute for Atmospheric Science, Environment, School of Earth and Environment, Leeds (United Kingdom); Leroux, Stephanie [Universite Joseph Fourier, Laboratoire d' etude des Transferts en Hydrologie et Environnement, BP53, Grenoble Cedex 9 (France)

    2008-02-15

    Sensitivity studies with regional climate models are often performed on the basis of a few simulations for which the difference is analysed and the statistical significance is often taken for granted. In this study we present some simple measures of the confidence limits for these types of experiments by analysing the internal variability of a regional climate model run over West Africa. Two 1-year long simulations, differing only in their initial conditions, are compared. The difference between the two runs gives a measure of the internal variability of the model and an indication of which timescales are reliable for analysis. The results are analysed for a range of timescales and spatial scales, and quantitative measures of the confidence limits for regional model simulations are diagnosed for a selection of study areas for rainfall, low level temperature and wind. As the averaging period or spatial scale is increased, the signal due to internal variability gets smaller and confidence in the simulations increases. This occurs more rapidly for variations in precipitation, which appear essentially random, than for dynamical variables, which show some organisation on larger scales. (orig.)

  6. Estimating and Testing Mediation Effects with Censored Data

    Science.gov (United States)

    Wang, Lijuan; Zhang, Zhiyong

    2011-01-01

    This study investigated influences of censored data on mediation analysis. Mediation effect estimates can be biased and inefficient with censoring on any one of the input, mediation, and output variables. A Bayesian Tobit approach was introduced to estimate and test mediation effects with censored data. Simulation results showed that the Bayesian…

  7. Impulsive synchronization and parameter mismatch of the three-variable autocatalator model

    International Nuclear Information System (INIS)

    Li, Yang; Liao, Xiaofeng; Li, Chuandong; Huang, Tingwen; Yang, Degang

    2007-01-01

    The synchronization problems of the three-variable autocatalator model via impulsive control approach are investigated; several theorems on the stability of impulsive control systems are also investigated. These theorems are then used to find the conditions under which the three-variable autocatalator model can be asymptotically controlled to the equilibrium point. This Letter derives some sufficient conditions for the stabilization and synchronization of a three-variable autocatalator model via impulsive control with varying impulsive intervals. Furthermore, we address the chaos quasi-synchronization in the presence of single-parameter mismatch. To illustrate the effectiveness of the new scheme, several numerical examples are given

  8. The Relationship between SES and Reading Comprehension in Chinese: A Mediation Model

    Directory of Open Access Journals (Sweden)

    Yahua Cheng

    2017-04-01

    Full Text Available An increasing body of research provides evidence that socioeconomic status (SES was significantly related to children’s reading development; however, the psychological mechanism underlying the association between them remained an open question. The present study is designed to test the hypothesized three-path effect of vocabulary knowledge and morphological awareness as mediators between SES and sentence reading comprehension in Chinese first-graders. Results of mediation model showed that SES exerted its effect on sentence reading comprehension through the indirect path via the simple mediating effect of morphological awareness and the three-path mediating effect of vocabulary knowledge and morphological awareness. The findings highlight a previously unidentified mechanism of the relationship between SES and reading comprehension in Chinese young children.

  9. Variable cycle control model for intersection based on multi-source information

    Science.gov (United States)

    Sun, Zhi-Yuan; Li, Yue; Qu, Wen-Cong; Chen, Yan-Yan

    2018-05-01

    In order to improve the efficiency of traffic control system in the era of big data, a new variable cycle control model based on multi-source information is presented for intersection in this paper. Firstly, with consideration of multi-source information, a unified framework based on cyber-physical system is proposed. Secondly, taking into account the variable length of cell, hysteresis phenomenon of traffic flow and the characteristics of lane group, a Lane group-based Cell Transmission Model is established to describe the physical properties of traffic flow under different traffic signal control schemes. Thirdly, the variable cycle control problem is abstracted into a bi-level programming model. The upper level model is put forward for cycle length optimization considering traffic capacity and delay. The lower level model is a dynamic signal control decision model based on fairness analysis. Then, a Hybrid Intelligent Optimization Algorithm is raised to solve the proposed model. Finally, a case study shows the efficiency and applicability of the proposed model and algorithm.

  10. Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

    Science.gov (United States)

    Li, Spencer D.

    2011-01-01

    Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

  11. Hidden Markov latent variable models with multivariate longitudinal data.

    Science.gov (United States)

    Song, Xinyuan; Xia, Yemao; Zhu, Hongtu

    2017-03-01

    Cocaine addiction is chronic and persistent, and has become a major social and health problem in many countries. Existing studies have shown that cocaine addicts often undergo episodic periods of addiction to, moderate dependence on, or swearing off cocaine. Given its reversible feature, cocaine use can be formulated as a stochastic process that transits from one state to another, while the impacts of various factors, such as treatment received and individuals' psychological problems on cocaine use, may vary across states. This article develops a hidden Markov latent variable model to study multivariate longitudinal data concerning cocaine use from a California Civil Addict Program. The proposed model generalizes conventional latent variable models to allow bidirectional transition between cocaine-addiction states and conventional hidden Markov models to allow latent variables and their dynamic interrelationship. We develop a maximum-likelihood approach, along with a Monte Carlo expectation conditional maximization (MCECM) algorithm, to conduct parameter estimation. The asymptotic properties of the parameter estimates and statistics for testing the heterogeneity of model parameters are investigated. The finite sample performance of the proposed methodology is demonstrated by simulation studies. The application to cocaine use study provides insights into the prevention of cocaine use. © 2016, The International Biometric Society.

  12. Personal and Environmental Resources Mediate the Positivity-Emotional Dysfunction Relationship.

    Science.gov (United States)

    Lehrer, H Matthew; Janus, Katherine C; Gloria, Christian T; Steinhardt, Mary A

    2017-03-01

    We investigated the relationships among positivity, perceived personal and environmental resources, and emotional dysfunction in adolescent girls. We hypothesized that perceived resources would mediate the relationship between positivity and emotional dysfunction. Participants (N = 510) attending an all-girls public school completed a survey assessing emotional dysfunction (depressive symptoms and perceived stress), positivity (positive/negative emotions), and personal/ environmental resources (resilience, hope, percent adaptive coping, community connectedness, social support, and school connectedness). Perceived resources were combined into one latent variable, and structural equation modeling tested the mediating effect of perceived resources on the relationship between positivity and emotional dysfunction. The model accounted for 63% of the variance in emotional dysfunction. Positivity exerted a significant direct effect on emotional dysfunction (β = -.14, p emotional dysfunction is primarily but not entirely mediated by perceived personal and environmental resources. Schools should consider strategies to enhance experiences of positive emotions and/or decrease experiences of negative emotions, in conjunction with encouraging student awareness and development of personal and environmental resources.

  13. A variable resolution nonhydrostatic global atmospheric semi-implicit semi-Lagrangian model

    Science.gov (United States)

    Pouliot, George Antoine

    2000-10-01

    The objective of this project is to develop a variable-resolution finite difference adiabatic global nonhydrostatic semi-implicit semi-Lagrangian (SISL) model based on the fully compressible nonhydrostatic atmospheric equations. To achieve this goal, a three-dimensional variable resolution dynamical core was developed and tested. The main characteristics of the dynamical core can be summarized as follows: Spherical coordinates were used in a global domain. A hydrostatic/nonhydrostatic switch was incorporated into the dynamical equations to use the fully compressible atmospheric equations. A generalized horizontal variable resolution grid was developed and incorporated into the model. For a variable resolution grid, in contrast to a uniform resolution grid, the order of accuracy of finite difference approximations is formally lost but remains close to the order of accuracy associated with the uniform resolution grid provided the grid stretching is not too significant. The SISL numerical scheme was implemented for the fully compressible set of equations. In addition, the generalized minimum residual (GMRES) method with restart and preconditioner was used to solve the three-dimensional elliptic equation derived from the discretized system of equations. The three-dimensional momentum equation was integrated in vector-form to incorporate the metric terms in the calculations of the trajectories. Using global re-analysis data for a specific test case, the model was compared to similar SISL models previously developed. Reasonable agreement between the model and the other independently developed models was obtained. The Held-Suarez test for dynamical cores was used for a long integration and the model was successfully integrated for up to 1200 days. Idealized topography was used to test the variable resolution component of the model. Nonhydrostatic effects were simulated at grid spacings of 400 meters with idealized topography and uniform flow. Using a high

  14. The indirect association of job strain with long-term sickness absence through bullying: a mediation analysis using structural equation modeling.

    Science.gov (United States)

    Janssens, Heidi; Braeckman, Lutgart; De Clercq, Bart; Casini, Annalisa; De Bacquer, Dirk; Kittel, France; Clays, Els

    2016-08-22

    In this longitudinal study the complex interplay between both job strain and bullying in relation to sickness absence was investigated. Following the "work environment hypothesis", which establishes several work characteristics as antecedents of bullying, we assumed that job strain, conceptualized by the Job-Demand-Control model, has an indirect relation with long-term sickness absence through bullying. The sample consisted of 2983 Belgian workers, aged 30 to 55 years, who participated in the Belstress III study. They completed a survey, including the Job Content Questionnaire and a bullying inventory, at baseline. Their sickness absence figures were registered during 1 year follow-up. Long-term sickness absence was defined as at least 15 consecutive days. A mediation analysis, using structural equation modeling, was performed to examine the indirect association of job strain through bullying with long-term sickness absence. The full structural model was adjusted for several possible confounders: age, gender, occupational group, educational level, company, smoking habits, alcohol use, body mass index, self-rated health, baseline long-term sickness absence and neuroticism. The results support the hypothesis: a significant indirect association of job strain with long-term sickness absence through bullying was observed, suggesting that bullying is an intermediate variable between job strain and long-term sickness absence. No evidence for the reversed pathway of an indirect association of bullying through job strain was found. Bullying was observed as a mediating variable in the relation between job strain and sickness absence. The results suggest that exposure to job strain may create circumstances in which a worker risks to become a target of bullying. Our findings are generally in line with the work environment hypothesis, which emphasizes the importance of organizational work factors in the origin of bullying. This study highlights that remodeling jobs to reduce

  15. TV, Social Media, and College Students' Binge Drinking Intentions: Moderated Mediation Models.

    Science.gov (United States)

    Yang, Bo; Zhao, Xinyan

    2018-01-01

    Many studies to date have examined how media influence health-related behavior through social norms. However, most studies focused on traditional media. In the era of traditional and social media integration, our study advances health and mass communication scholarship by examining the influence of both traditional and social media mediated through social norms. Also, we examined a boundary condition for the norms-mediated media influence process. Namely, in the context of college binge drinking, we predict that exposure to TV and social media prodrinking messages can influence college students' binge drinking intentions through perceived peer descriptive and injunctive norms. We also predict that group identification will moderate this indirect effect. Our moderated mediation models were tested via structural equation modeling (N = 609). We found that college students' exposure to social media prodrinking messages indirectly influenced their binge drinking intentions via perceived injunctive norms, and students' identification with their peers moderated this indirect effect. However, neither descriptive nor injunctive norms mediated the influence of students' exposure to TV prodrinking messages on their binge drinking intentions. Theoretical and practical implications of the findings are discussed.

  16. Variable Fidelity Aeroelastic Toolkit - Structural Model, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The proposed innovation is a methodology to incorporate variable fidelity structural models into steady and unsteady aeroelastic and aeroservoelastic analyses in...

  17. Core Mediator structure at 3.4 Å extends model of transcription initiation complex.

    Science.gov (United States)

    Nozawa, Kayo; Schneider, Thomas R; Cramer, Patrick

    2017-05-11

    Mediator is a multiprotein co-activator that binds the transcription pre-initiation complex (PIC) and regulates RNA polymerase (Pol) II. The Mediator head and middle modules form the essential core Mediator (cMed), whereas the tail and kinase modules play regulatory roles. The architecture of Mediator and its position on the PIC are known, but atomic details are limited to Mediator subcomplexes. Here we report the crystal structure of the 15-subunit cMed from Schizosaccharomyces pombe at 3.4 Å resolution. The structure shows an unaltered head module, and reveals the intricate middle module, which we show is globally required for transcription. Sites of known Mediator mutations cluster at the interface between the head and middle modules, and in terminal regions of the head subunits Med6 (ref. 16) and Med17 (ref. 17) that tether the middle module. The structure led to a model for Saccharomyces cerevisiae cMed that could be combined with the 3.6 Å cryo-electron microscopy structure of the core PIC (cPIC). The resulting atomic model of the cPIC-cMed complex informs on interactions of the submodules forming the middle module, called beam, knob, plank, connector, and hook. The hook is flexibly linked to Mediator by a conserved hinge and contacts the transcription initiation factor IIH (TFIIH) kinase that phosphorylates the carboxy (C)-terminal domain (CTD) of Pol II and was recently positioned on the PIC. The hook also contains residues that crosslink to the CTD and reside in a previously described cradle. These results provide a framework for understanding Mediator function, including its role in stimulating CTD phosphorylation by TFIIH.

  18. A Moderated Mediation Model for Board Diversity and Corporate Performance in ASEAN Countries

    Directory of Open Access Journals (Sweden)

    Sahar E-Vahdati

    2018-02-01

    Full Text Available Despite the major investigations in prior studies for direct links among board diversity and corporate performance, the literature has not covered many indirect associations among them. This article analyzes the association between board diversity (gender and foreigner and corporate performance by focusing on the mediating role of corporate social responsibility reporting (CSRR and the moderated mediation role of South East Asian (ASEAN countries through new institutional theory, which consists of legitimacy and institutional theories. According to a sample of 264 corporates from all industries by using GRI G3 guideline from 2011 to 2013, we found that foreign and gender diversity have partial and full mediation effects in ASEAN countries. The main conclusion of the current article indicates that board diversity affects directly with corporate performance and indirectly with CSRR through moderated path analysis. The implications are valuable for academics, managers, and policy makers who are interested to determine the impact of intervening variables on the board diversity and corporate performance relationship in ASEAN countries.

  19. The Properties of Model Selection when Retaining Theory Variables

    DEFF Research Database (Denmark)

    Hendry, David F.; Johansen, Søren

    Economic theories are often fitted directly to data to avoid possible model selection biases. We show that embedding a theory model that specifies the correct set of m relevant exogenous variables, x{t}, within the larger set of m+k candidate variables, (x{t},w{t}), then selection over the second...... set by their statistical significance can be undertaken without affecting the estimator distribution of the theory parameters. This strategy returns the theory-parameter estimates when the theory is correct, yet protects against the theory being under-specified because some w{t} are relevant....

  20. Tumour–stromal interactions in acid-mediated invasion: A mathematical model

    KAUST Repository

    Martin, Natasha K.; Gaffney, Eamonn A.; Gatenby, Robert A.; Maini, Philip K.

    2010-01-01

    constraint. In particular, the production of acid by tumour cells and the subsequent creation of a low extracellular pH environment has been explored in several 'acid-mediated tumour invasion' models where the acidic environment facilitates normal cell death

  1. Covariate measurement error correction methods in mediation analysis with failure time data.

    Science.gov (United States)

    Zhao, Shanshan; Prentice, Ross L

    2014-12-01

    Mediation analysis is important for understanding the mechanisms whereby one variable causes changes in another. Measurement error could obscure the ability of the potential mediator to explain such changes. This article focuses on developing correction methods for measurement error in the mediator with failure time outcomes. We consider a broad definition of measurement error, including technical error, and error associated with temporal variation. The underlying model with the "true" mediator is assumed to be of the Cox proportional hazards model form. The induced hazard ratio for the observed mediator no longer has a simple form independent of the baseline hazard function, due to the conditioning event. We propose a mean-variance regression calibration approach and a follow-up time regression calibration approach, to approximate the partial likelihood for the induced hazard function. Both methods demonstrate value in assessing mediation effects in simulation studies. These methods are generalized to multiple biomarkers and to both case-cohort and nested case-control sampling designs. We apply these correction methods to the Women's Health Initiative hormone therapy trials to understand the mediation effect of several serum sex hormone measures on the relationship between postmenopausal hormone therapy and breast cancer risk. © 2014, The International Biometric Society.

  2. Emotional competence relating to perceived stress and burnout in Spanish teachers: a mediator model

    OpenAIRE

    Lourdes Rey; Natalio Extremera; Mario Pena

    2016-01-01

    This study examined direct associations between emotional competence, perceived stress and burnout in 489 Spanish teachers. In addition, a model in which perceived stress mediated pathways linking emotional competence to teacher burnout symptoms was also examined. Results showed that emotional competence and stress were significantly correlated with teacher burnout symptoms in the expected direction. Moreover, mediational analysis indicated that perceived stress partly mediated the relationsh...

  3. Characteristics of the home food environment that mediate immediate and sustained increases in child fruit and vegetable consumption: mediation analysis from the Healthy Habits cluster randomised controlled trial.

    Science.gov (United States)

    Wyse, Rebecca; Wolfenden, Luke; Bisquera, Alessandra

    2015-09-17

    The home food environment can influence the development of dietary behaviours in children, and interventions that modify characteristics of the home food environment have been shown to increase children's fruit and vegetable consumption. However to date, interventions to increase children's fruit and vegetable consumption have generally produced only modest effects. Mediation analysis can help in the design of more efficient and effective interventions by identifying the mechanisms through which interventions have an effect. This study aimed to identify characteristics of the home food environment that mediated immediate and sustained increases in children's fruit and vegetable consumption following the 4-week Healthy Habits telephone-based parent intervention. Analysis was conducted using 2-month (immediate) and 12-month (sustained) follow-up data from a cluster randomised control trial of a home food environment intervention to increase the fruit and vegetable consumption of preschool children. Using recursive path analysis, a series of mediation models were created to investigate the direct and indirect effects of immediate and sustained changes to characteristics of the home food environment (fruit and vegetable availability, accessibility, parent intake, parent providing behaviour, role-modelling, mealtime eating practices, child feeding strategies, and pressure to eat), on the change in children's fruit and vegetable consumption. Of the 394 participants in the randomised trial, 357 and 329 completed the 2- and 12-month follow-up respectively. The final mediation model suggests that the effect of the intervention on the children's fruit and vegetable consumption was mediated by parent fruit and vegetable intake and parent provision of these foods at both 2- and 12-month follow-up. Analysis of data from the Healthy Habits trial suggests that two environmental variables (parental intake and parent providing) mediate the immediate and sustained effect of the

  4. Potential mediating pathways through which sports participation relates to reduced risk of suicidal ideation.

    Science.gov (United States)

    Taliaferro, Lindsay A; Rienzo, Barbara A; Miller, M David; Pigg, R Morgan; Dodd, Virginia J

    2010-09-01

    Suicide ranks as the third leading cause of death for American youth. Researchers examining sport participation and suicidal behavior have regularly found inverse relationships. This study represents the first effort to test a model depicting potential mechanisms through which sport participation relates to reduced risk of suicidal ideation. The participants were 450 undergraduate students. Measures assessed participants' involvement in university-run sports and other activities; frequency of physical activity; and perceived social support, self-esteem, depression, hopelessness, loneliness, and suicidal ideation. Regression analyses confirmed a path model and tested for mediation effects. Vigorous activity mediated relationships between sport participation and self-esteem and depression; and self-esteem and depression mediated the relationship between vigorous activity and suicidal ideation. Social support mediated relationships between sport participation and depression, hopelessness, and loneliness; and each of these risk factors partially mediated the relationship between social support and suicidal ideation. However no variable fully mediated the relationship between sport participation and suicidal ideation. This study provides a foundation for research designed to examine pathways through which sport participation relates to reduced risk of suicidal behavior.

  5. Breastfeeding and Childhood IQ: The Mediating Role of Gray Matter Volume.

    Science.gov (United States)

    Luby, Joan L; Belden, Andy C; Whalen, Diana; Harms, Michael P; Barch, Deanna M

    2016-05-01

    A substantial body of literature has established the positive effect of breastfeeding on child developmental outcomes. There is increasing consensus that breastfed children have higher IQs after accounting for key variables, including maternal education, IQ, and socioeconomic status. Cross-sectional investigations of the effects of breastfeeding on structural brain development suggest that breastfed infants have larger whole brain, cortical, and white matter volumes. To date, few studies have related these measures of brain structure to IQ in breastfed versus nonbreastfed children in a longitudinal sample. Data were derived from the Preschool Depression Study (PDS), a prospective longitudinal study in which children and caregivers were assessed annually for 8 waves over 11 years. A subset completed neuroimaging between the ages of 9.5 and 14.11 years. A total of 148 individuals had breastfeeding data at baseline and complete data on all variables of interest, including IQ and structural neuroimaging. General linear models and process mediation models were used. Breastfed children had significantly higher IQ scores and larger whole brain, total gray matter, total cortical gray matter, and subcortical gray matter volumes compared with the nonbreastfed group in models that covaried for key variables. Subcortical gray matter volume significantly mediated the association between breastfeeding and children's IQ scores. The study findings suggest that the effects of breastfeeding on child IQ are mediated through subcortical gray volume. This effect and putative mechanism is of public health significance and further supports the importance of breastfeeding in mental health promotion. Copyright © 2016 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

  6. Family dynamics and alcohol and marijuana use among adolescents: The mediating role of negative emotional symptoms and sensation seeking.

    Science.gov (United States)

    Trujillo, Ángela; Obando, Diana; Trujillo, Carlos A

    2016-11-01

    The literature indicates a close relationship between family dynamics and psychoactive substance use among adolescents, and multi-causality among substance use-related problems, including personal adolescent characteristics as potential influential aspects in this relationship. The purpose of this study is to investigate the role of emotional symptoms and sensation seeking as mediators in the relationship between family dynamics and alcohol and marijuana use among adolescents. The sample consisted of 571 high school students with a mean age of 14.63, who completed the Communities That Care Youth Survey in its Spanish version. We propose and test a mediation-in-serial model to identify the relationships between the study variables. The results of the mediation models indicate that, in most cases, the relationship between family dynamics and the substance use variables is meaningfully carried through the proposed mediators, first through negative emotional symptoms, and then through sensation seeking. The meaning of the mediation varies as a function of the facet of family dynamics (conflict or attachment) and the use aspect (age of onset, frequency of use, and use intention). We discuss the implications of these findings for intervention and prevention strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.

  7. Towards a moderated mediation model of innovative work behaviour enhancement

    NARCIS (Netherlands)

    Stoffers, Jol M.; van der Heijden, Beatrice; Notelaers, Guy L.A.

    2014-01-01

    Purpose – The purpose of this paper is to investigate a moderated mediation model of innovative work behaviour enhancement. Perceived firm (organizational and market) performance was assumed to moderate the relationships between leader-member exchange (LMX) and organizational citizenship behaviour

  8. Inverse odds ratio-weighted estimation for causal mediation analysis.

    Science.gov (United States)

    Tchetgen Tchetgen, Eric J

    2013-11-20

    An important scientific goal of studies in the health and social sciences is increasingly to determine to what extent the total effect of a point exposure is mediated by an intermediate variable on the causal pathway between the exposure and the outcome. A causal framework has recently been proposed for mediation analysis, which gives rise to new definitions, formal identification results and novel estimators of direct and indirect effects. In the present paper, the author describes a new inverse odds ratio-weighted approach to estimate so-called natural direct and indirect effects. The approach, which uses as a weight the inverse of an estimate of the odds ratio function relating the exposure and the mediator, is universal in that it can be used to decompose total effects in a number of regression models commonly used in practice. Specifically, the approach may be used for effect decomposition in generalized linear models with a nonlinear link function, and in a number of other commonly used models such as the Cox proportional hazards regression for a survival outcome. The approach is simple and can be implemented in standard software provided a weight can be specified for each observation. An additional advantage of the method is that it easily incorporates multiple mediators of a categorical, discrete or continuous nature. Copyright © 2013 John Wiley & Sons, Ltd.

  9. Big five personality and adolescent Internet addiction: The mediating role of coping style.

    Science.gov (United States)

    Zhou, Yueyue; Li, Dongping; Li, Xian; Wang, Yanhui; Zhao, Liyan

    2017-01-01

    This study examined the unique associations between big five personality traits and adolescent Internet addiction (IA), as well as the mediating role of coping style underlying these relations. Our theoretical model was tested with 998 adolescents. Participants provided self-report data on demographic variables, big five personality traits, coping style, and IA. After controlling for demographic variables, it was found that agreeableness and conscientiousness were negatively associated with IA, whereas extraversion, neuroticism, and openness to experience were positively associated with IA. Mediation analyses further indicated that conscientiousness had an indirect impact on adolescent IA through decreased emotion-focused coping, whereas extraversion, neuroticism, openness to experience had indirect impacts on adolescent IA through increased emotion-focused coping. In contrast, problem-focused coping had no mediating role. These findings suggest that emotion-focused coping may, in part, account for the association between big five personality and adolescent IA. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. Approaches for modeling within subject variability in pharmacometric count data analysis: dynamic inter-occasion variability and stochastic differential equations.

    Science.gov (United States)

    Deng, Chenhui; Plan, Elodie L; Karlsson, Mats O

    2016-06-01

    Parameter variation in pharmacometric analysis studies can be characterized as within subject parameter variability (WSV) in pharmacometric models. WSV has previously been successfully modeled using inter-occasion variability (IOV), but also stochastic differential equations (SDEs). In this study, two approaches, dynamic inter-occasion variability (dIOV) and adapted stochastic differential equations, were proposed to investigate WSV in pharmacometric count data analysis. These approaches were applied to published count models for seizure counts and Likert pain scores. Both approaches improved the model fits significantly. In addition, stochastic simulation and estimation were used to explore further the capability of the two approaches to diagnose and improve models where existing WSV is not recognized. The results of simulations confirmed the gain in introducing WSV as dIOV and SDEs when parameters vary randomly over time. Further, the approaches were also informative as diagnostics of model misspecification, when parameters changed systematically over time but this was not recognized in the structural model. The proposed approaches in this study offer strategies to characterize WSV and are not restricted to count data.

  11. Influences of variables on ship collision probability in a Bayesian belief network model

    International Nuclear Information System (INIS)

    Hänninen, Maria; Kujala, Pentti

    2012-01-01

    The influences of the variables in a Bayesian belief network model for estimating the role of human factors on ship collision probability in the Gulf of Finland are studied for discovering the variables with the largest influences and for examining the validity of the network. The change in the so-called causation probability is examined while observing each state of the network variables and by utilizing sensitivity and mutual information analyses. Changing course in an encounter situation is the most influential variable in the model, followed by variables such as the Officer of the Watch's action, situation assessment, danger detection, personal condition and incapacitation. The least influential variables are the other distractions on bridge, the bridge view, maintenance routines and the officer's fatigue. In general, the methods are found to agree on the order of the model variables although some disagreements arise due to slightly dissimilar approaches to the concept of variable influence. The relative values and the ranking of variables based on the values are discovered to be more valuable than the actual numerical values themselves. Although the most influential variables seem to be plausible, there are some discrepancies between the indicated influences in the model and literature. Thus, improvements are suggested to the network.

  12. Uncertainty and variability in computational and mathematical models of cardiac physiology.

    Science.gov (United States)

    Mirams, Gary R; Pathmanathan, Pras; Gray, Richard A; Challenor, Peter; Clayton, Richard H

    2016-12-01

    Mathematical and computational models of cardiac physiology have been an integral component of cardiac electrophysiology since its inception, and are collectively known as the Cardiac Physiome. We identify and classify the numerous sources of variability and uncertainty in model formulation, parameters and other inputs that arise from both natural variation in experimental data and lack of knowledge. The impact of uncertainty on the outputs of Cardiac Physiome models is not well understood, and this limits their utility as clinical tools. We argue that incorporating variability and uncertainty should be a high priority for the future of the Cardiac Physiome. We suggest investigating the adoption of approaches developed in other areas of science and engineering while recognising unique challenges for the Cardiac Physiome; it is likely that novel methods will be necessary that require engagement with the mathematics and statistics community. The Cardiac Physiome effort is one of the most mature and successful applications of mathematical and computational modelling for describing and advancing the understanding of physiology. After five decades of development, physiological cardiac models are poised to realise the promise of translational research via clinical applications such as drug development and patient-specific approaches as well as ablation, cardiac resynchronisation and contractility modulation therapies. For models to be included as a vital component of the decision process in safety-critical applications, rigorous assessment of model credibility will be required. This White Paper describes one aspect of this process by identifying and classifying sources of variability and uncertainty in models as well as their implications for the application and development of cardiac models. We stress the need to understand and quantify the sources of variability and uncertainty in model inputs, and the impact of model structure and complexity and their consequences for

  13. Behavioral and Nondirective Guided Self-Help for Parents of Children with Externalizing Behavior: Mediating Mechanisms in a Head-To-Head Comparison.

    Science.gov (United States)

    Katzmann, Josepha; Hautmann, Christopher; Greimel, Lisa; Imort, Stephanie; Pinior, Julia; Scholz, Kristin; Döpfner, Manfred

    2017-05-01

    Parent training (PT) delivered as a guided self-help intervention may be a cost- and time-effective intervention in the treatment of children with externalizing disorders. In face-to-face PT, parenting strategies have repeatedly been identified as mediating mechanisms for the decrease of children's problem behavior. Few studies have examined possible mediating effects in guided self-help interventions for parents. The present study aimed to investigate possible mediating variables of a behaviorally oriented guided self-help program for parents of children with externalizing problems compared to a nondirective intervention in a clinical sample. A sample of 110 parents of children with externalizing disorders (80 % boys) were randomized to either a behaviorally oriented or a nondirective guided self-help program. Four putative mediating variables were examined simultaneously in a multiple mediation model using structural equation modelling. The outcomes were child symptoms of ADHD and ODD as well as child externalizing problems, assessed at posttreatment. Analyses showed a significant indirect effect for dysfunctional parental attributions in favor of the group receiving the behavioral program, and significant effects of the behavioral program on positive and negative parenting and parental self-efficacy, compared to the nondirective intervention. Our results indicate that a decrease of dysfunctional parental attributions leads to a decrease of child externalizing problems when parents take part in a behaviorally oriented guided self-help program. However, none of the putative mediating variables could explain the decrease in child externalizing behavior problems in the nondirective group. A change in dysfunctional parental attributions should be considered as a possible mediator in the context of PT.

  14. Natural climate variability in a coupled model

    International Nuclear Information System (INIS)

    Zebiak, S.E.; Cane, M.A.

    1990-01-01

    Multi-century simulations with a simplified coupled ocean-atmosphere model are described. These simulations reveal an impressive range of variability on decadal and longer time scales, in addition to the dominant interannual el Nino/Southern Oscillation signal that the model originally was designed to simulate. Based on a very large sample of century-long simulations, it is nonetheless possible to identify distinct model parameter sensitivities that are described here in terms of selected indices. Preliminary experiments motivated by general circulation model results for increasing greenhouse gases suggest a definite sensitivity to model global warming. While these results are not definitive, they strongly suggest that coupled air-sea dynamics figure prominently in global change and must be included in models for reliable predictions

  15. Revisiting Mediation in the Social and Behavioral Sciences

    Directory of Open Access Journals (Sweden)

    Aurelio José Figueredo

    2013-11-01

    Full Text Available The process of mediation is of critical importance to the social and behavioral sciences and to evolutionary social psychology in particular. As with the concept of evolutionary adaptation, however, one can argue that causal mediation is in need of explicit theoretical justification and empirical support. Mainstream evolutionary social psychology proposes, for example, that organisms are “adaptation executers”, and not “fitness maximizers”. The execution of adaptations is triggered by fitness-relevant ecological contingencies at both ultimate and proximate levels of analysis. This logic is essentially equivalent to what methodologists refer to as the process of mediation; the adaptations to be executed (or not, depending upon the prevailing environmental circumstances causally mediate the effects of the ecological contingencies upon the fitness outcomes. Thus, the process of mediation can be generally conceptualized as a causal chain of events leading to a given outcome or set of outcomes. If a predictor variable operates through an intervening variable to affect a criterion variable, then mediation is said to exist. Nevertheless, it does not appear that some psychologists (particularly evolutionary-social psychologists are sufficiently well-versed in the fundamental logic and quantitative methodology of establishing causal mediation to support such claims. In the current paper, we set out to review the ways researchers support their use of mediation statements and also propose critical considerations on this front. We start with more conventional methods for testing mediation, discuss variants of the conventional approach, discuss the limitations of such methods as we see them, and end with our preferred mediation approach. DOI: 10.2458/azu_jmmss.v4i1.17761

  16. Developing models to predict 8th grade students' achievement levels on timss science based on opportunity-to-learn variables

    Science.gov (United States)

    Whitford, Melinda M.

    Science educational reforms have placed major emphasis on improving science classroom instruction and it is therefore vital to study opportunity-to-learn (OTL) variables related to student science learning experiences and teacher teaching practices. This study will identify relationships between OTL and student science achievement and will identify OTL predictors of students' attainment at various distinct achievement levels (low/intermediate/high/advanced). Specifically, the study (a) address limitations of previous studies by examining a large number of independent and control variables that may impact students' science achievement and (b) it will test hypotheses of structural relations to how the identified predictors and mediating factors impact on student achievement levels. The study will follow a multi-stage and integrated bottom-up and top-down approach to identify predictors of students' achievement levels on standardized tests using TIMSS 2011 dataset. Data mining or pattern recognition, a bottom-up approach will identify the most prevalent association patterns between different student achievement levels and variables related to student science learning experiences, teacher teaching practices and home and school environments. The second stage is a top-down approach, testing structural equation models of relations between the significant predictors and students' achievement levels according.

  17. Dialectic Antidotes to Critics of the Technology Acceptance Model: Conceptual, Methodological, and Replication Treatments for Behavioural Modelling in Technology-Mediated Environments

    Directory of Open Access Journals (Sweden)

    Weng Marc Lim

    2018-01-01

    Full Text Available The technology acceptance model (TAM is a prominent and parsimonious conceptual lens that is often applied for behavioural modelling in technology-mediated environments. However, TAM has received a great deal of criticism in recent years. This article aims to address some of the most pertinent issues confronting TAM through a rejoinder that offers dialectic antidotes—in the form of conceptual, methodological, and replication treatments—to support the continued use of TAM to understand the peculiarities of user interactions with technology in technology-mediated environments. In doing so, this article offers a useful response to a common but often inadequately answered question about how TAM can continue to be relevant for behavioural modelling in contemporary technology-mediated environments.

  18. Implementing general gauge mediation

    International Nuclear Information System (INIS)

    Carpenter, Linda M.; Dine, Michael; Festuccia, Guido; Mason, John D.

    2009-01-01

    Recently there has been much progress in building models of gauge mediation, often with predictions different than those of minimal gauge mediation. Meade, Seiberg, and Shih have characterized the most general spectrum which can arise in gauge-mediated models. We discuss some of the challenges of building models of general gauge mediation, especially the problem of messenger parity and issues connected with R symmetry breaking and CP violation. We build a variety of viable, weakly coupled models which exhibit some or all of the possible low energy parameters.

  19. Statistical grand rounds: understanding the mechanism: mediation analysis in randomized and nonrandomized studies.

    Science.gov (United States)

    Mascha, Edward J; Dalton, Jarrod E; Kurz, Andrea; Saager, Leif

    2013-10-01

    In comparative clinical studies, a common goal is to assess whether an exposure, or intervention, affects the outcome of interest. However, just as important is to understand the mechanism(s) for how the intervention affects outcome. For example, if preoperative anemia was shown to increase the risk of postoperative complications by 15%, it would be important to quantify how much of that effect was due to patients receiving intraoperative transfusions. Mediation analysis attempts to quantify how much, if any, of the effect of an intervention on outcome goes though prespecified mediator, or "mechanism" variable(s), that is, variables sitting on the causal pathway between exposure and outcome. Effects of an exposure on outcome can thus be divided into direct and indirect, or mediated, effects. Mediation is claimed when 2 conditions are true: the exposure affects the mediator and the mediator (adjusting for the exposure) affects the outcome. Understanding how an intervention affects outcome can validate or invalidate one's original hypothesis and also facilitate further research to modify the responsible factors, and thus improve patient outcome. We discuss the proper design and analysis of studies investigating mediation, including the importance of distinguishing mediator variables from confounding variables, the challenge of identifying potential mediators when the exposure is chronic versus acute, and the requirements for claiming mediation. Simple designs are considered, as well as those containing multiple mediators, multiple outcomes, and mixed data types. Methods are illustrated with data collected by the National Surgical Quality Improvement Project (NSQIP) and utilized in a companion paper which assessed the effects of preoperative anemic status on postoperative outcomes.

  20. [Socioeconomical level and behavior in school-age children: the mediating role of parents].

    Science.gov (United States)

    Ulloa Vidal, Natalia; Cova Solar, Félix; Bustos N, Claudio

    2017-06-01

    A determinant of particular relevance in human development is the socioeconomic status (SES) and, specifically, low SES and poverty. Likewise, family environment is essential in the development of children and a potential mediator or moderator of the effect of broader social conditions. To analyze the role of parenting stress as a mediating variable of the relationship between SES and both externalized and internalized behaviors in preschool children. Descriptive secondary base study based on the Longitudinal Survey of Chilean First Infancy that selected a stratified sample, representative by clusters, of 9.996 children from 3 to 5 years old and their caregivers, that completed a battery of instruments for measuring SES variables, parenting stress and externalized and internalized behaviors. The analysis used a linear model with least square estimate. As hypothesis testing, the Dm (an adaptation of the F-test for multiple imputation method) was used. The mediation model of parenting stress in the relationship between SES and both externalized and internalized behaviors was confirmed for the latter; regarding externalized behaviors a model of moderation was observed, being the stress influence lower on the low SES. Parental stress showed a clear relationship with the presence of externalized and internalized behaviors, stronger than the SES. The relationship between SES and parenting stress is very important to understand the processes that affect children’s development.

  1. AMOC decadal variability in Earth system models: Mechanisms and climate impacts

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, Alexey [Yale Univ., New Haven, CT (United States)

    2017-09-06

    This is the final report for the project titled "AMOC decadal variability in Earth system models: Mechanisms and climate impacts". The central goal of this one-year research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) within a hierarchy of climate models ranging from realistic ocean GCMs to Earth system models. The AMOC is a key element of ocean circulation responsible for oceanic transport of heat from low to high latitudes and controlling, to a large extent, climate variations in the North Atlantic. The questions of the AMOC stability, variability and predictability, directly relevant to the questions of climate predictability, were at the center of the research work.

  2. The Use of Propensity Scores in Mediation Analysis

    Science.gov (United States)

    Jo, Booil; Stuart, Elizabeth A.; MacKinnon, David P.; Vinokur, Amiram D.

    2011-01-01

    Mediation analysis uses measures of hypothesized mediating variables to test theory for how a treatment achieves effects on outcomes and to improve subsequent treatments by identifying the most efficient treatment components. Most current mediation analysis methods rely on untested distributional and functional form assumptions for valid…

  3. Higher-dimensional cosmological model with variable gravitational ...

    Indian Academy of Sciences (India)

    variable G and bulk viscosity in Lyra geometry. Exact solutions for ... a comparative study of Robertson–Walker models with a constant deceleration .... where H is defined as H =(˙A/A)+(1/3)( ˙B/B) and β0,H0 are representing present values of β ...

  4. Identifying cis-mediators for trans-eQTLs across many human tissues using genomic mediation analysis.

    Science.gov (United States)

    Yang, Fan; Wang, Jiebiao; Pierce, Brandon L; Chen, Lin S

    2017-11-01

    The impact of inherited genetic variation on gene expression in humans is well-established. The majority of known expression quantitative trait loci (eQTLs) impact expression of local genes ( cis -eQTLs). More research is needed to identify effects of genetic variation on distant genes ( trans -eQTLs) and understand their biological mechanisms. One common trans -eQTLs mechanism is "mediation" by a local ( cis ) transcript. Thus, mediation analysis can be applied to genome-wide SNP and expression data in order to identify transcripts that are " cis -mediators" of trans -eQTLs, including those " cis -hubs" involved in regulation of many trans -genes. Identifying such mediators helps us understand regulatory networks and suggests biological mechanisms underlying trans -eQTLs, both of which are relevant for understanding susceptibility to complex diseases. The multitissue expression data from the Genotype-Tissue Expression (GTEx) program provides a unique opportunity to study cis -mediation across human tissue types. However, the presence of complex hidden confounding effects in biological systems can make mediation analyses challenging and prone to confounding bias, particularly when conducted among diverse samples. To address this problem, we propose a new method: Genomic Mediation analysis with Adaptive Confounding adjustment (GMAC). It enables the search of a very large pool of variables, and adaptively selects potential confounding variables for each mediation test. Analyses of simulated data and GTEx data demonstrate that the adaptive selection of confounders by GMAC improves the power and precision of mediation analysis. Application of GMAC to GTEx data provides new insights into the observed patterns of cis -hubs and trans -eQTL regulation across tissue types. © 2017 Yang et al.; Published by Cold Spring Harbor Laboratory Press.

  5. The Sources of Science Teaching Self-efficacy among Elementary School Teachers: A mediational model approach

    Science.gov (United States)

    Wang, Ya-Ling; Tsai, Chin-Chung; Wei, Shih-Hsuan

    2015-09-01

    This study aimed to investigate the factors accounting for science teaching self-efficacy and to examine the relationships among Taiwanese teachers' science teaching self-efficacy, teaching and learning conceptions, technological-pedagogical content knowledge for the Internet (TPACK-I), and attitudes toward Internet-based instruction (Attitudes) using a mediational model approach. A total of 233 science teachers from 41 elementary schools in Taiwan were invited to take part in the study. After ensuring the validity and reliability of each questionnaire, the results indicated that each measure had satisfactory validity and reliability. Furthermore, through mediational models, the results revealed that TPACK-I and Attitudes mediated the relationship between teaching and learning conceptions and science teaching self-efficacy, suggesting that (1) knowledge of and attitudes toward Internet-based instruction (KATII) mediated the positive relationship between constructivist conceptions of teaching and learning and outcome expectancy, and that (2) KATII mediated the negative correlations between traditional conceptions of teaching and learning and teaching efficacy.

  6. Modeling temporal and spatial variability of traffic-related air pollution: Hourly land use regression models for black carbon

    Science.gov (United States)

    Dons, Evi; Van Poppel, Martine; Kochan, Bruno; Wets, Geert; Int Panis, Luc

    2013-08-01

    Land use regression (LUR) modeling is a statistical technique used to determine exposure to air pollutants in epidemiological studies. Time-activity diaries can be combined with LUR models, enabling detailed exposure estimation and limiting exposure misclassification, both in shorter and longer time lags. In this study, the traffic related air pollutant black carbon was measured with μ-aethalometers on a 5-min time base at 63 locations in Flanders, Belgium. The measurements show that hourly concentrations vary between different locations, but also over the day. Furthermore the diurnal pattern is different for street and background locations. This suggests that annual LUR models are not sufficient to capture all the variation. Hourly LUR models for black carbon are developed using different strategies: by means of dummy variables, with dynamic dependent variables and/or with dynamic and static independent variables. The LUR model with 48 dummies (weekday hours and weekend hours) performs not as good as the annual model (explained variance of 0.44 compared to 0.77 in the annual model). The dataset with hourly concentrations of black carbon can be used to recalibrate the annual model, resulting in many of the original explaining variables losing their statistical significance, and certain variables having the wrong direction of effect. Building new independent hourly models, with static or dynamic covariates, is proposed as the best solution to solve these issues. R2 values for hourly LUR models are mostly smaller than the R2 of the annual model, ranging from 0.07 to 0.8. Between 6 a.m. and 10 p.m. on weekdays the R2 approximates the annual model R2. Even though models of consecutive hours are developed independently, similar variables turn out to be significant. Using dynamic covariates instead of static covariates, i.e. hourly traffic intensities and hourly population densities, did not significantly improve the models' performance.

  7. Gauge coupling unification in heterotic string models with gauge mediated supersymmetry breaking

    International Nuclear Information System (INIS)

    Anandakrishnan, Archana; Raby, Stuart

    2011-01-01

    We calculate the weak scale minimal supersymmetric standard model spectrum starting from a heterotic string theory compactified on an anisotropic orbifold. Supersymmetry breaking is mediated by vectorlike exotics that arise naturally in heterotic string theories. The messengers that mediate supersymmetry breaking come in incomplete grand unified theory (GUT) multiplets and give rise to nonuniversal gaugino masses at the GUT scale. Models with nonuniversal gaugino masses at the GUT scale have the attractive feature of allowing for precision gauge coupling unification at the GUT scale with negligible contributions from threshold corrections near the unification scale. The unique features of this minimally supersymmetric standard model spectrum are light gluinos and also large mass differences between the lightest and the next-to-lightest neutralinos and charginos which could lead to interesting signatures at the colliders.

  8. Computer-Mediated Intersensory Learning Model for Students with Learning Disabilities

    Science.gov (United States)

    Seok, Soonhwa; DaCosta, Boaventura; Kinsell, Carolyn; Poggio, John C.; Meyen, Edward L.

    2010-01-01

    This article proposes a computer-mediated intersensory learning model as an alternative to traditional instructional approaches for students with learning disabilities (LDs) in the inclusive classroom. Predominant practices of classroom inclusion today reflect the six principles of zero reject, nondiscriminatory evaluation, appropriate education,…

  9. Childhood adversity and social functioning in psychosis: Exploring clinical and cognitive mediators.

    Science.gov (United States)

    Palmier-Claus, Jasper; Berry, Katherine; Darrell-Berry, Hannah; Emsley, Richard; Parker, Sophie; Drake, Richard; Bucci, Sandra

    2016-04-30

    Childhood adversity may increase risk of impaired social functioning across the continuum of psychosis. However, the pathways by which adversity dictates functional outcome remain underexplored. This study investigated the association between childhood adversity and social functioning, and the clinical and cognitive mediators of this relationship. Fifty-four clinical (20 chronic, 20 first episode, 14 at ultra-high risk) and 120 non-clinical participants completed standardised questionnaires, semi-structured interviews and tests of theory of mind ability. The authors used multiple group structural equation modelling to fit mediation models allowing for differential relationships between the clinical and non-clinical samples. When examining each pathway separately, depression, paranoia and anxious attachment mediated the effect of childhood adversity on social functioning. In a combined model, depression was the only significant mediating variable with greater adversity predicting lower mood across groups. Childhood adversity did not significantly predict theory of mind ability in any of the models. This is the first study to indicate that childhood adversity acts on social functioning by increasing levels of depression, suggesting a common mechanism across the spectrum of psychosis. Clinical interventions should target low mood in order to improve social functioning at all stages of psychotic disorder. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  10. Reheating temperature and gauge mediation models of supersymmetry breaking

    International Nuclear Information System (INIS)

    Olechowski, Marek; Pokorski, Stefan; Turzynski, Krzysztof; Wells, James D.

    2009-01-01

    For supersymmetric theories with gravitino dark matter, the maximal reheating temperature consistent with big bang nucleosynthesis bounds arises when the physical gaugino masses are degenerate. We consider the cases of a stau or sneutrino next-to-lightest superpartner, which have relatively less constraint from big bang nucleosynthesis. The resulting parameter space is consistent with leptogenesis requirements, and can be reached in generalized gauge mediation models. Such models illustrate a class of theories that overcome the well-known tension between big bang nucleosynthesis and leptogenesis.

  11. Variable selection for mixture and promotion time cure rate models.

    Science.gov (United States)

    Masud, Abdullah; Tu, Wanzhu; Yu, Zhangsheng

    2016-11-16

    Failure-time data with cured patients are common in clinical studies. Data from these studies are typically analyzed with cure rate models. Variable selection methods have not been well developed for cure rate models. In this research, we propose two least absolute shrinkage and selection operators based methods, for variable selection in mixture and promotion time cure models with parametric or nonparametric baseline hazards. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods. We illustrate the use of the methods using data from a study of childhood wheezing. © The Author(s) 2016.

  12. The mediating role of coping strategy in the association between family functioning and nonsuicidal self-injury among Taiwanese adolescents.

    Science.gov (United States)

    Ren, Yaxuan; Lin, Min-Pei; Liu, Yin-Han; Zhang, Xu; Wu, Jo Yung-Wei; Hu, Wei-Hsuan; Xu, Sian; You, Jianing

    2018-01-22

    Nock's (2009) integrated theoretical model suggests that both intrapersonal and interpersonal factors contribute to the development of nonsuicidal self-injury (NSSI). Based on this model, the present study examined the roles of family functioning and coping strategy in predicting NSSI, as well as the mediating effect of coping strategy in the relationship between family functioning and NSSI. Gender differences on the associations of these variables were also examined. A sample of 1,989 secondary school students (52.0% females) in Taiwan was assessed by self-report measures of perceived family functioning, coping strategy, and NSSI. Results showed that both family functioning and avoidance/emotion-focused coping strategy predicted NSSI. Additionally, the association between family functioning and NSSI was mediated by avoidance/emotion-focused coping strategy. Gender differences were not found on the associations among these study variables. These data provided evidences that the Nock's (2009) integrated theoretical model may help to explain how coping strategy mediates the effect of family functioning on NSSI. The implications of the findings for future research and intervention were discussed. © 2018 Wiley Periodicals, Inc.

  13. Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

    Science.gov (United States)

    Fahimi, Farzad; Yaseen, Zaher Mundher; El-shafie, Ahmed

    2017-05-01

    Since the middle of the twentieth century, artificial intelligence (AI) models have been used widely in engineering and science problems. Water resource variable modeling and prediction are the most challenging issues in water engineering. Artificial neural network (ANN) is a common approach used to tackle this problem by using viable and efficient models. Numerous ANN models have been successfully developed to achieve more accurate results. In the current review, different ANN models in water resource applications and hydrological variable predictions are reviewed and outlined. In addition, recent hybrid models and their structures, input preprocessing, and optimization techniques are discussed and the results are compared with similar previous studies. Moreover, to achieve a comprehensive view of the literature, many articles that applied ANN models together with other techniques are included. Consequently, coupling procedure, model evaluation, and performance comparison of hybrid models with conventional ANN models are assessed, as well as, taxonomy and hybrid ANN models structures. Finally, current challenges and recommendations for future researches are indicated and new hybrid approaches are proposed.

  14. Model Predictive Control of a Nonlinear System with Known Scheduling Variable

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2012-01-01

    Model predictive control (MPC) of a class of nonlinear systems is considered in this paper. We will use Linear Parameter Varying (LPV) model of the nonlinear system. By taking the advantage of having future values of the scheduling variable, we will simplify state prediction. Consequently...... the control problem of the nonlinear system is simplied into a quadratic programming. Wind turbine is chosen as the case study and we choose wind speed as the scheduling variable. Wind speed is measurable ahead of the turbine, therefore the scheduling variable is known for the entire prediction horizon....

  15. A geometric model for magnetizable bodies with internal variables

    Directory of Open Access Journals (Sweden)

    Restuccia, L

    2005-11-01

    Full Text Available In a geometrical framework for thermo-elasticity of continua with internal variables we consider a model of magnetizable media previously discussed and investigated by Maugin. We assume as state variables the magnetization together with its space gradient, subjected to evolution equations depending on both internal and external magnetic fields. We calculate the entropy function and necessary conditions for its existence.

  16. Linking subordinate political skill to supervisor dependence and reward recommendations: a moderated mediation model.

    Science.gov (United States)

    Shi, Junqi; Johnson, Russell E; Liu, Yihao; Wang, Mo

    2013-03-01

    In this study, we examined the relations of subordinate political skill with supervisor's dependence on the subordinate and supervisor reward recommendation, as well as mediating (interaction frequency with supervisor) and moderating (supervisor political behavior) variables of these relations. Our theoretical model was tested using data collected from employees in a company that specialized in construction management. Analyses of multisource and lagged data from 53 construction management team supervisors and 296 subordinates indicated that subordinate political skill was positively related to supervisor reward recommendation via subordinate's interaction frequency with supervisor. Although interaction frequency with a supervisor was also positively related to the supervisor's dependence on the subordinate, the indirect effect of subordinate political skill on dependence was not significant. Further, both the relationship between subordinate political skill and interaction frequency with a supervisor and the indirect relationships between subordinate political skill and supervisor reward recommendation were stronger when supervisors exhibited more political behavior.

  17. Causal mediation analysis with multiple mediators in the presence of treatment noncompliance.

    Science.gov (United States)

    Park, Soojin; Kürüm, Esra

    2018-05-20

    Randomized experiments are often complicated because of treatment noncompliance. This challenge prevents researchers from identifying the mediated portion of the intention-to-treated (ITT) effect, which is the effect of the assigned treatment that is attributed to a mediator. One solution suggests identifying the mediated ITT effect on the basis of the average causal mediation effect among compliers when there is a single mediator. However, considering the complex nature of the mediating mechanisms, it is natural to assume that there are multiple variables that mediate through the causal path. Motivated by an empirical analysis of a data set collected in a randomized interventional study, we develop a method to estimate the mediated portion of the ITT effect when both multiple dependent mediators and treatment noncompliance exist. This enables researchers to make an informed decision on how to strengthen the intervention effect by identifying relevant mediators despite treatment noncompliance. We propose a nonparametric estimation procedure and provide a sensitivity analysis for key assumptions. We conduct a Monte Carlo simulation study to assess the finite sample performance of the proposed approach. The proposed method is illustrated by an empirical analysis of JOBS II data, in which a job training intervention was used to prevent mental health deterioration among unemployed individuals. Copyright © 2018 John Wiley & Sons, Ltd.

  18. Perceived parental monitoring and adolescent internet addiction: A moderated mediation model.

    Science.gov (United States)

    Ding, Qingwen; Li, Dongping; Zhou, Yueyue; Dong, Hongning; Luo, Jinjing

    2017-11-01

    Bronfenbrenner's (1979) ecological model focuses on the interrelation between different contexts and the interaction between individuals and their proximal contexts. Based on this theory, the present study tested a moderated mediation model of family, peer, and individual characteristics to investigate how they impact adolescent Internet addiction. Specifically, we examined whether deviant peer affiliation partially mediated the relation between perceived parental monitoring and adolescent Internet addiction, and whether this indirect relation was moderated by effortful control. A total of 747 Chinese middle school students filled out anonymous questionnaires concerning perceived parental monitoring, deviant peer affiliation, effortful control, and Internet addiction. The findings indicated that while the impact of parental monitoring on Internet addiction was partially mediated by deviant peer affiliation, effortful control moderated the first stage of the indirect relationship. For low effortful control adolescents, perceived parental monitoring negatively predicted deviant peer affiliation. Conversely, the indirect path was not significant for high effortful control adolescents. These findings highlight the need to consider family, peer and individual factors simultaneously when evaluating risks associated with adolescent Internet addiction and have important implications for the prevention and intervention of adolescent Internet addiction. Copyright © 2017 Elsevier Ltd. All rights reserved.

  19. Examples of EOS Variables as compared to the UMM-Var Data Model

    Science.gov (United States)

    Cantrell, Simon; Lynnes, Chris

    2016-01-01

    In effort to provide EOSDIS clients a way to discover and use variable data from different providers, a Unified Metadata Model for Variables is being created. This presentation gives an overview of the model and use cases we are handling.

  20. Local variability mediates vulnerability of trout populations to land use and climate change

    Science.gov (United States)

    Brooke E. Penaluna; Jason B. Dunham; Steve F. Railsback; Ivan Arismendi; Sherri L. Johnson; Robert E. Bilby; Mohammad Safeeq; Arne E. Skaugset; James P. Meador

    2015-01-01

    Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of...

  1. Youth Engagement and Suicide Risk: Testing a Mediated Model in a Canadian Community Sample

    Science.gov (United States)

    Ramey, Heather L.; Busseri, Michael A.; Khanna, Nishad; Rose-Krasnor, Linda

    2010-01-01

    Suicide is a leading cause of death among adolescents in many industrialized countries. We report evidence from a mediation model linking greater youth activity engagement, spanning behavioral and psychological components, with lower suicide risk through five hypothesized intrapersonal and interpersonal mediating factors. Self-report survey data…

  2. Dose- and time-dependence of the host-mediated response to paclitaxel therapy: a mathematical modeling approach.

    Science.gov (United States)

    Benguigui, Madeleine; Alishekevitz, Dror; Timaner, Michael; Shechter, Dvir; Raviv, Ziv; Benzekry, Sebastien; Shaked, Yuval

    2018-01-05

    It has recently been suggested that pro-tumorigenic host-mediated processes induced in response to chemotherapy counteract the anti-tumor activity of therapy, and thereby decrease net therapeutic outcome. Here we use experimental data to formulate a mathematical model describing the host response to different doses of paclitaxel (PTX) chemotherapy as well as the duration of the response. Three previously described host-mediated effects are used as readouts for the host response to therapy. These include the levels of circulating endothelial progenitor cells in peripheral blood and the effect of plasma derived from PTX-treated mice on migratory and invasive properties of tumor cells in vitro . A first set of mathematical models, based on basic principles of pharmacokinetics/pharmacodynamics, did not appropriately describe the dose-dependence and duration of the host response regarding the effects on invasion. We therefore provide an alternative mathematical model with a dose-dependent threshold, instead of a concentration-dependent one, that describes better the data. This model is integrated into a global model defining all three host-mediated effects. It not only precisely describes the data, but also correctly predicts host-mediated effects at different doses as well as the duration of the host response. This mathematical model may serve as a tool to predict the host response to chemotherapy in cancer patients, and therefore may be used to design chemotherapy regimens with improved therapeutic outcome by minimizing host mediated effects.

  3. Bayesian dynamic mediation analysis.

    Science.gov (United States)

    Huang, Jing; Yuan, Ying

    2017-12-01

    Most existing methods for mediation analysis assume that mediation is a stationary, time-invariant process, which overlooks the inherently dynamic nature of many human psychological processes and behavioral activities. In this article, we consider mediation as a dynamic process that continuously changes over time. We propose Bayesian multilevel time-varying coefficient models to describe and estimate such dynamic mediation effects. By taking the nonparametric penalized spline approach, the proposed method is flexible and able to accommodate any shape of the relationship between time and mediation effects. Simulation studies show that the proposed method works well and faithfully reflects the true nature of the mediation process. By modeling mediation effect nonparametrically as a continuous function of time, our method provides a valuable tool to help researchers obtain a more complete understanding of the dynamic nature of the mediation process underlying psychological and behavioral phenomena. We also briefly discuss an alternative approach of using dynamic autoregressive mediation model to estimate the dynamic mediation effect. The computer code is provided to implement the proposed Bayesian dynamic mediation analysis. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  4. Parental Bonds, Attachment Anxiety, Media Susceptibility, and Body Dissatisfaction: A Mediation Model

    Science.gov (United States)

    Patton, Sarah C.; Beaujean, A. Alexander; Benedict, Helen E.

    2014-01-01

    The developmental trajectory of body image dissatisfaction is unclear. Researchers have investigated sociocultural and developmental risk factors; however, the literature needs an integrative etiological model. In 2009, Cheng and Mallinckrodt proposed a dual mediation model, positing that poor-quality parental bonds, via the mechanisms of…

  5. Speech-discrimination scores modeled as a binomial variable.

    Science.gov (United States)

    Thornton, A R; Raffin, M J

    1978-09-01

    Many studies have reported variability data for tests of speech discrimination, and the disparate results of these studies have not been given a simple explanation. Arguments over the relative merits of 25- vs 50-word tests have ignored the basic mathematical properties inherent in the use of percentage scores. The present study models performance on clinical tests of speech discrimination as a binomial variable. A binomial model was developed, and some of its characteristics were tested against data from 4120 scores obtained on the CID Auditory Test W-22. A table for determining significant deviations between scores was generated and compared to observed differences in half-list scores for the W-22 tests. Good agreement was found between predicted and observed values. Implications of the binomial characteristics of speech-discrimination scores are discussed.

  6. Optimal variable-grid finite-difference modeling for porous media

    International Nuclear Information System (INIS)

    Liu, Xinxin; Yin, Xingyao; Li, Haishan

    2014-01-01

    Numerical modeling of poroelastic waves by the finite-difference (FD) method is more expensive than that of acoustic or elastic waves. To improve the accuracy and computational efficiency of seismic modeling, variable-grid FD methods have been developed. In this paper, we derived optimal staggered-grid finite difference schemes with variable grid-spacing and time-step for seismic modeling in porous media. FD operators with small grid-spacing and time-step are adopted for low-velocity or small-scale geological bodies, while FD operators with big grid-spacing and time-step are adopted for high-velocity or large-scale regions. The dispersion relations of FD schemes were derived based on the plane wave theory, then the FD coefficients were obtained using the Taylor expansion. Dispersion analysis and modeling results demonstrated that the proposed method has higher accuracy with lower computational cost for poroelastic wave simulation in heterogeneous reservoirs. (paper)

  7. Comparison of climate envelope models developed using expert-selected variables versus statistical selection

    Science.gov (United States)

    Brandt, Laura A.; Benscoter, Allison; Harvey, Rebecca G.; Speroterra, Carolina; Bucklin, David N.; Romañach, Stephanie; Watling, James I.; Mazzotti, Frank J.

    2017-01-01

    Climate envelope models are widely used to describe potential future distribution of species under different climate change scenarios. It is broadly recognized that there are both strengths and limitations to using climate envelope models and that outcomes are sensitive to initial assumptions, inputs, and modeling methods Selection of predictor variables, a central step in modeling, is one of the areas where different techniques can yield varying results. Selection of climate variables to use as predictors is often done using statistical approaches that develop correlations between occurrences and climate data. These approaches have received criticism in that they rely on the statistical properties of the data rather than directly incorporating biological information about species responses to temperature and precipitation. We evaluated and compared models and prediction maps for 15 threatened or endangered species in Florida based on two variable selection techniques: expert opinion and a statistical method. We compared model performance between these two approaches for contemporary predictions, and the spatial correlation, spatial overlap and area predicted for contemporary and future climate predictions. In general, experts identified more variables as being important than the statistical method and there was low overlap in the variable sets (0.9 for area under the curve (AUC) and >0.7 for true skill statistic (TSS). Spatial overlap, which compares the spatial configuration between maps constructed using the different variable selection techniques, was only moderate overall (about 60%), with a great deal of variability across species. Difference in spatial overlap was even greater under future climate projections, indicating additional divergence of model outputs from different variable selection techniques. Our work is in agreement with other studies which have found that for broad-scale species distribution modeling, using statistical methods of variable

  8. Genomic Characterization of Variable Surface Antigens Reveals a Telomere Position Effect as a Prerequisite for RNA Interference-Mediated Silencing in Paramecium tetraurelia

    Science.gov (United States)

    Baranasic, Damir; Oppermann, Timo; Cheaib, Miriam; Cullum, John; Schmidt, Helmut

    2014-01-01

    ABSTRACT Antigenic or phenotypic variation is a widespread phenomenon of expression of variable surface protein coats on eukaryotic microbes. To clarify the mechanism behind mutually exclusive gene expression, we characterized the genetic properties of the surface antigen multigene family in the ciliate Paramecium tetraurelia and the epigenetic factors controlling expression and silencing. Genome analysis indicated that the multigene family consists of intrachromosomal and subtelomeric genes; both classes apparently derive from different gene duplication events: whole-genome and intrachromosomal duplication. Expression analysis provides evidence for telomere position effects, because only subtelomeric genes follow mutually exclusive transcription. Microarray analysis of cultures deficient in Rdr3, an RNA-dependent RNA polymerase, in comparison to serotype-pure wild-type cultures, shows cotranscription of a subset of subtelomeric genes, indicating that the telomere position effect is due to a selective occurrence of Rdr3-mediated silencing in subtelomeric regions. We present a model of surface antigen evolution by intrachromosomal gene duplication involving the maintenance of positive selection of structurally relevant regions. Further analysis of chromosome heterogeneity shows that alternative telomere addition regions clearly affect transcription of closely related genes. Consequently, chromosome fragmentation appears to be of crucial importance for surface antigen expression and evolution. Our data suggest that RNAi-mediated control of this genetic network by trans-acting RNAs allows rapid epigenetic adaptation by phenotypic variation in combination with long-term genetic adaptation by Darwinian evolution of antigen genes. PMID:25389173

  9. Parameter estimation of variable-parameter nonlinear Muskingum model using excel solver

    Science.gov (United States)

    Kang, Ling; Zhou, Liwei

    2018-02-01

    Abstract . The Muskingum model is an effective flood routing technology in hydrology and water resources Engineering. With the development of optimization technology, more and more variable-parameter Muskingum models were presented to improve effectiveness of the Muskingum model in recent decades. A variable-parameter nonlinear Muskingum model (NVPNLMM) was proposed in this paper. According to the results of two real and frequently-used case studies by various models, the NVPNLMM could obtain better values of evaluation criteria, which are used to describe the superiority of the estimated outflows and compare the accuracies of flood routing using various models, and the optimal estimated outflows by the NVPNLMM were closer to the observed outflows than the ones by other models.

  10. Cre-mediated cell ablation contests mast cell contribution in models of antibody- and T cell-mediated autoimmunity.

    Science.gov (United States)

    Feyerabend, Thorsten B; Weiser, Anne; Tietz, Annette; Stassen, Michael; Harris, Nicola; Kopf, Manfred; Radermacher, Peter; Möller, Peter; Benoist, Christophe; Mathis, Diane; Fehling, Hans Jörg; Rodewald, Hans-Reimer

    2011-11-23

    Immunological functions of mast cells remain poorly understood. Studies in Kit mutant mice suggest key roles for mast cells in certain antibody- and T cell-mediated autoimmune diseases. However, Kit mutations affect multiple cell types of both immune and nonimmune origin. Here, we show that targeted insertion of Cre-recombinase into the mast cell carboxypeptidase A3 locus deleted mast cells in connective and mucosal tissues by a genotoxic Trp53-dependent mechanism. Cre-mediated mast cell eradication (Cre-Master) mice had, with the exception of a lack of mast cells and reduced basophils, a normal immune system. Cre-Master mice were refractory to IgE-mediated anaphylaxis, and this defect was rescued by mast cell reconstitution. This mast cell-deficient strain was fully susceptible to antibody-induced autoimmune arthritis and to experimental autoimmune encephalomyelitis. Differences comparing Kit mutant mast cell deficiency models to selectively mast cell-deficient mice call for a systematic re-evaluation of immunological functions of mast cells beyond allergy. Copyright © 2011 Elsevier Inc. All rights reserved.

  11. Self-efficacy: a mediator of smoking behavior and depression among college students.

    Science.gov (United States)

    Mee, Susan

    2014-01-01

    Cigarette smoking is a growing problem among adolescents. This correlational study tested theoretical relationships between the dependent variable (smoking behavior) and the independent variables (depression and smoking resistance self-efficacy) in a convenience sample of 364 college students ages 18 to 21 years recruited from a large urban public college. An a priori mediational model tested the role of smoking resistance self-efficacy as a mediator in the relationship between smoking behavior and depression. Findings showed there was a statistically significant positive relationship between depression and smoking behavior (r = 0.122, p = 0.01). There was a statistically significant negative relationship between smoking resistance self-efficacy and smoking behavior (r = -0.744, p = 0.01). Additionally, smoking resistance self-efficacy was a mediator of the relationship between depression and smoking behavior (beta = -0.757, p = 0.001). This study identifies a need for further theory-driven study of the relation of adolescent depression and smoking behavior. The findings of this study have implications for nursing interventions targeted to both current smokers and smoking initiation prevention programs.

  12. Angiotensin II and CRF Receptors in the Central Nucleus of the Amygdala Mediate Hemodynamic Response Variability to Cocaine in Conscious Rats

    OpenAIRE

    Watanabe, Mari A.; Kucenas, Sarah; Bowman, Tamara A.; Ruhlman, Melissa; Knuepfer, Mark M.

    2009-01-01

    Stress or cocaine evokes either a large increase in systemic vascular resistance (SVR) or a smaller increase in SVR accompanied by an increase in cardiac output (designated vascular and mixed responders, respectively) in Sprague-Dawley rats. We hypothesized that the central nucleus of the amygdala (CeA) mediates this variability. Conscious, freely-moving rats, instrumented for measurement of arterial pressure and cardiac output and for drug delivery into the CeA, were given cocaine (5 mg/kg, ...

  13. Toward a mediation model for nurses' well-being and psychological distress effects of quality of leadership and social support at work.

    Science.gov (United States)

    Van der Heijden, Beatrice I J M; Mulder, Regina H; König, Christoph; Anselmann, Veronika

    2017-04-01

    Given the lack of active nurses in industrialized countries throughout the world, in combination with demographic changes, it is of utmost importance to protect nurses' well-being and to prevent psychological distress, because of their strong association with premature occupational leave. The aim of this study was to investigate the effects of quality of leadership and social support at work on well-being and psychological distress of nurses and to determine whether nurses' overcommitment mediates the relationship between the abovementioned determinants and the outcomes. A cross-sectional survey design was used to gather our data. This study utilized part of the database of the Nurses' Early Exit Study. A total of 34,771 nurses (covering all nurse qualifications) working in hospitals, nursing homes, and home-care institutions in 8 European countries filled out a questionnaire (response rate = 51.4%). For all model variables (job satisfaction, satisfaction with salary, positive affectivity, personal burnout, negative affectivity, quality of leadership, social support from immediate supervisor, social support from near colleagues, and overcommitment), psychometrically sound, that is, valid and reliable measures were used. Outcomes from testing a structural equation mediation model indicated that, respectively, positive and negative influences of leadership quality and social support from supervisor and colleagues on nurses' well-being and psychological distress are partially mediated, that is, reduced, by nurses' overcommitment. Social work environment is highly important in relation to nurses' well-being and psychological distress.

  14. BehavePlus fire modeling system, version 5.0: Variables

    Science.gov (United States)

    Patricia L. Andrews

    2009-01-01

    This publication has been revised to reflect updates to version 4.0 of the BehavePlus software. It was originally published as the BehavePlus fire modeling system, version 4.0: Variables in July, 2008.The BehavePlus fire modeling system is a computer program based on mathematical models that describe wildland fire behavior and effects and the...

  15. Flexible Mediation Analysis With Multiple Mediators.

    Science.gov (United States)

    Steen, Johan; Loeys, Tom; Moerkerke, Beatrijs; Vansteelandt, Stijn

    2017-07-15

    The advent of counterfactual-based mediation analysis has triggered enormous progress on how, and under what assumptions, one may disentangle path-specific effects upon combining arbitrary (possibly nonlinear) models for mediator and outcome. However, current developments have largely focused on single mediators because required identification assumptions prohibit simple extensions to settings with multiple mediators that may depend on one another. In this article, we propose a procedure for obtaining fine-grained decompositions that may still be recovered from observed data in such complex settings. We first show that existing analytical approaches target specific instances of a more general set of decompositions and may therefore fail to provide a comprehensive assessment of the processes that underpin cause-effect relationships between exposure and outcome. We then outline conditions for obtaining the remaining set of decompositions. Because the number of targeted decompositions increases rapidly with the number of mediators, we introduce natural effects models along with estimation methods that allow for flexible and parsimonious modeling. Our procedure can easily be implemented using off-the-shelf software and is illustrated using a reanalysis of the World Health Organization's Large Analysis and Review of European Housing and Health Status (WHO-LARES) study on the effect of mold exposure on mental health (2002-2003). © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  16. Moderation and Mediation of an Efficacious Sexual Risk-Reduction Intervention for South African Adolescents

    Science.gov (United States)

    O’Leary, Ann; Jemmott, John B.; Jemmott, Loretta Sweet; Bellamy, Scarlett; Ngwane, Zolani; Icard, Larry

    2015-01-01

    Background “Let Us Protect Our Future” is a sexual risk-reduction intervention for sixth-grade adolescents in South Africa. Tested in a cluster-randomized controlled trial, the intervention significantly reduced self-reported intercourse and unprotected intercourse during a 12-month follow-up period. Purpose The present analyses were conducted to identify moderators of the intervention’s efficacy as well as which theory-based variables mediated the intervention’s effects. Methods: Intervention efficacy over the 3-, 6-, and 12-month follow-ups was tested using generalized estimating equation (GEE) models. Results Living with their father in the home, parental strictness, and religiosity moderated the efficacy of the intervention in reducing unprotected intercourse. Self-efficacy to avoid risky situations and expected parental disapproval of their having intercourse, derived from Social Cognitive Theory, significantly mediated the intervention’s effect on abstinence. Conclusions This is the first study to demonstrate that Social Cognitive variables mediate the efficacy of a sexual risk-reduction intervention among South African adolescents. PMID:22618963

  17. Partitioning the impacts of spatial and climatological rainfall variability in urban drainage modeling

    Science.gov (United States)

    Peleg, Nadav; Blumensaat, Frank; Molnar, Peter; Fatichi, Simone; Burlando, Paolo

    2017-03-01

    The performance of urban drainage systems is typically examined using hydrological and hydrodynamic models where rainfall input is uniformly distributed, i.e., derived from a single or very few rain gauges. When models are fed with a single uniformly distributed rainfall realization, the response of the urban drainage system to the rainfall variability remains unexplored. The goal of this study was to understand how climate variability and spatial rainfall variability, jointly or individually considered, affect the response of a calibrated hydrodynamic urban drainage model. A stochastic spatially distributed rainfall generator (STREAP - Space-Time Realizations of Areal Precipitation) was used to simulate many realizations of rainfall for a 30-year period, accounting for both climate variability and spatial rainfall variability. The generated rainfall ensemble was used as input into a calibrated hydrodynamic model (EPA SWMM - the US EPA's Storm Water Management Model) to simulate surface runoff and channel flow in a small urban catchment in the city of Lucerne, Switzerland. The variability of peak flows in response to rainfall of different return periods was evaluated at three different locations in the urban drainage network and partitioned among its sources. The main contribution to the total flow variability was found to originate from the natural climate variability (on average over 74 %). In addition, the relative contribution of the spatial rainfall variability to the total flow variability was found to increase with longer return periods. This suggests that while the use of spatially distributed rainfall data can supply valuable information for sewer network design (typically based on rainfall with return periods from 5 to 15 years), there is a more pronounced relevance when conducting flood risk assessments for larger return periods. The results show the importance of using multiple distributed rainfall realizations in urban hydrology studies to capture the

  18. Modeling Turbulent Combustion for Variable Prandtl and Schmidt Number

    Science.gov (United States)

    Hassan, H. A.

    2004-01-01

    This report consists of two abstracts submitted for possible presentation at the AIAA Aerospace Science Meeting to be held in January 2005. Since the submittal of these abstracts we are continuing refinement of the model coefficients derived for the case of a variable Turbulent Prandtl number. The test cases being investigated are a Mach 9.2 flow over a degree ramp and a Mach 8.2 3-D calculation of crossing shocks. We have developed an axisymmetric code for treating axisymmetric flows. In addition the variable Schmidt number formulation was incorporated in the code and we are in the process of determining the model constants.

  19. The Mediating Roles of Anxiety Depression, and Hopelessness on Adolescent Suicidal Behaviors

    Science.gov (United States)

    Thompson, Elaine Adams; Mazza, James J.; Herting, Jerald R.; Randell, Brooke P.; Eggert, Leona L.

    2005-01-01

    The purpose of this study was to explore the roles of anxiety, depression, and hopelessness as mediators between known risk factors and suicidal behaviors among 1,287 potential high school dropouts. As a step toward theory development, a model was tested that posited the relationships among these variables and their effects on suicidal behaviors.…

  20. Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

    Science.gov (United States)

    Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

    2018-05-01

    Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed

  1. Impact of socio-demographic factors on the mitigating actions for climate change: a path analysis with mediating effects of attitudinal variables.

    Science.gov (United States)

    Masud, Muhammad Mehedi; Akhatr, Rulia; Nasrin, Shamima; Adamu, Ibrahim Mohammed

    2017-12-01

    Socio-demographic factors play a significant role in increasing the individual's climate change awareness and in setting a favorable individual attitude towards its mitigation. To better understand how the adversative effects of climate change can be mitigated, this study attempts to investigate the impact of socio-demographic factors on the mitigating actions of the individuals (MAOI) on climate change. Qualitative data were collected from a face-to-face survey of 360 respondents in the Kuala Lumpur region of Malaysia through a close-ended questionnaire. Analysis was conducted on the mediating effects of attitudinal variables through the path model by using the SEM. Findings indicate that the socio-demographic factors such as gender, age, education, income, and ethnicity can greatly influence the individual's awareness, attitude, risk perception, and knowledge of climate change issues. The results drawn from this study also revealed that the attitudinal factors act as a mediating effect between the socio-demographic factors and the MAOI, thereby, indicating that both the socio-demographic factors and the attitudinal factors have significant effects on the MAOI towards climate change. The outcome of this study can help policy makers and other private organizations to decide on the appropriate actions to take in managing climate change effects. These actions which encompass improving basic climate change education and making the public more aware of the local dimensions of climate change are important for harnessing public engagement and support that can also stimulate climate change awareness and promote mitigating actions to n protect the environment from the impact of climate change.

  2. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method.

    Science.gov (United States)

    Yang, Jun-He; Cheng, Ching-Hsue; Chan, Chia-Pan

    2017-01-01

    Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir's water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir's water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  3. A Model for Positively Correlated Count Variables

    DEFF Research Database (Denmark)

    Møller, Jesper; Rubak, Ege Holger

    2010-01-01

    An α-permanental random field is briefly speaking a model for a collection of non-negative integer valued random variables with positive associations. Though such models possess many appealing probabilistic properties, many statisticians seem unaware of α-permanental random fields...... and their potential applications. The purpose of this paper is to summarize useful probabilistic results, study stochastic constructions and simulation techniques, and discuss some examples of α-permanental random fields. This should provide a useful basis for discussing the statistical aspects in future work....

  4. Interacting ghost dark energy models with variable G and Λ

    Science.gov (United States)

    Sadeghi, J.; Khurshudyan, M.; Movsisyan, A.; Farahani, H.

    2013-12-01

    In this paper we consider several phenomenological models of variable Λ. Model of a flat Universe with variable Λ and G is accepted. It is well known, that varying G and Λ gives rise to modified field equations and modified conservation laws, which gives rise to many different manipulations and assumptions in literature. We will consider two component fluid, which parameters will enter to Λ. Interaction between fluids with energy densities ρ1 and ρ2 assumed as Q = 3Hb(ρ1+ρ2). We have numerical analyze of important cosmological parameters like EoS parameter of the composed fluid and deceleration parameter q of the model.

  5. Mediation of social cognitive theory variables in the relationship of exercise and improved eating in sedentary adults with severe obesity.

    Science.gov (United States)

    Annesi, James J; Tennant, Gisèle A

    2013-01-01

    Results from behavioral treatments for obesity have been disappointing due to an inability to sustain healthy eating. The concurrent use of theory, research, and practical application has the potential of reducing overeating through innovative treatments. When overweight individuals begin an exercise program their eating tends to improve, however, the basis of this relationship is not determined. If the psychosocial mediators of the relationship between exercise and improved eating are better understood, supported exercise may be a key component for improving the efficacy of behavioral weight management treatments. In Phase 1 of this research, psychosocial variables derived from social cognitive theory were tested as possible mediators of the relationship of exercise participation with increased fruit and vegetable intake in severely obese adults initiating a 26-week treatment of supported exercise and standard nutrition education (n = 161). Change in self-regulation for healthy eating and self-regulation at treatment end was a strong mediator; with the addition of mood and self-efficacy for healthy eating being additional mediators that notably increased effect ratios. In Phase 2, participants in a cognitive-behavioral nutrition treatment tailored to improve the identified mediators (n = 163) were contrasted with the original group. The cognitive-behavioral nutrition treatment was associated with significantly greater increases than standard nutrition education in self-regulation, p = 0.023, CIs [4.69, 6.48], and [3.19, 5.02], respectively; self-efficacy, p = 0.013, CIs [19.72, 29.41], and [11.70, 20.71], respectively; and a marginally significant decrease in negative mood, p = 0.062, CIs [-14.26, -9.36], and [-10.90, -6.45], respectively. Findings served to inform treatment designs concerning the use of supported exercise and cognitive-behavioral means to derive better outcomes related to nutrition and weight loss in individuals with severe

  6. Representing general theoretical concepts in structural equation models: The role of composite variables

    Science.gov (United States)

    Grace, J.B.; Bollen, K.A.

    2008-01-01

    Structural equation modeling (SEM) holds the promise of providing natural scientists the capacity to evaluate complex multivariate hypotheses about ecological systems. Building on its predecessors, path analysis and factor analysis, SEM allows for the incorporation of both observed and unobserved (latent) variables into theoretically-based probabilistic models. In this paper we discuss the interface between theory and data in SEM and the use of an additional variable type, the composite. In simple terms, composite variables specify the influences of collections of other variables and can be helpful in modeling heterogeneous concepts of the sort commonly of interest to ecologists. While long recognized as a potentially important element of SEM, composite variables have received very limited use, in part because of a lack of theoretical consideration, but also because of difficulties that arise in parameter estimation when using conventional solution procedures. In this paper we present a framework for discussing composites and demonstrate how the use of partially-reduced-form models can help to overcome some of the parameter estimation and evaluation problems associated with models containing composites. Diagnostic procedures for evaluating the most appropriate and effective use of composites are illustrated with an example from the ecological literature. It is argued that an ability to incorporate composite variables into structural equation models may be particularly valuable in the study of natural systems, where concepts are frequently multifaceted and the influence of suites of variables are often of interest. ?? Springer Science+Business Media, LLC 2007.

  7. Inter-model variability and biases of the global water cycle in CMIP3 coupled climate models

    International Nuclear Information System (INIS)

    Liepert, Beate G; Previdi, Michael

    2012-01-01

    Observed changes such as increasing global temperatures and the intensification of the global water cycle in the 20th century are robust results of coupled general circulation models (CGCMs). In spite of these successes, model-to-model variability and biases that are small in first order climate responses, however, have considerable implications for climate predictability especially when multi-model means are used. We show that most climate simulations of the 20th and 21st century A2 scenario performed with CMIP3 (Coupled Model Inter-comparison Project Phase 3) models have deficiencies in simulating the global atmospheric moisture balance. Large biases of only a few models (some biases reach the simulated global precipitation changes in the 20th and 21st centuries) affect the multi-model mean global moisture budget. An imbalanced flux of −0.14 Sv exists while the multi-model median imbalance is only −0.02 Sv. Moreover, for most models the detected imbalance changes over time. As a consequence, in 13 of the 18 CMIP3 models examined, global annual mean precipitation exceeds global evaporation, indicating that there should be a ‘leaking’ of moisture from the atmosphere whereas for the remaining five models a ‘flooding’ is implied. Nonetheless, in all models, the actual atmospheric moisture content and its variability correctly increases during the course of the 20th and 21st centuries. These discrepancies therefore imply an unphysical and hence ‘ghost’ sink/source of atmospheric moisture in the models whose atmospheres flood/leak. The ghost source/sink of moisture can also be regarded as atmospheric latent heating/cooling and hence as positive/negative perturbation of the atmospheric energy budget or non-radiative forcing in the range of −1 to +6 W m −2 (median +0.1 W m −2 ). The inter-model variability of the global atmospheric moisture transport from oceans to land areas, which impacts the terrestrial water cycle, is also quite high and ranges

  8. Mediating and Marketing Factors Influence the Prescription Behavior of Physicians: An Empirical Investigation

    Directory of Open Access Journals (Sweden)

    Rizwan Raheem Ahmed

    2016-02-01

    Full Text Available The authors present general review of the literature and the results of an empirical research on the subject. A cross-sectional questionnaire-based survey was conducted, being answered by 350 respondents: mix of graduate and post graduate doctors of private and public hospitals of Karachi City, and pharmaceutical personnel (mix of sales and marketing of national and multinational pharmaceutical companies operating in Pakistan. To test hypothesis, structural equation modelling (SEM was employed using AMOS 7 software package. As data are normally distributed, maximum likelihood method of estimation was used. Factorial ANOVA also enables us to examine the interaction effect between the factors. The results from factorial ANOVA test all the hypotheses of model, and results were declared significant at p <0.05. Findings are interesting as they establish association between variables (scientific literatures, promotional material, regular follow up, CMEs & conferences, personalized activities and prescription behavior of doctors mediated by strong phenomenon of medical representative PR and brand image of a company/product in changing the prescription behavior of doctors. Based on the results of this study, the pharmaceutical companies can device better marketing strategies keeping in view of these mediating effects. The article presents only two mediating and five marketing factors, whereas, more marketing and mediating variables can be added and tested, so, in future this gape can be overcome by other researchers. Moreover, a larger sample size could be applied and the scope of study can be enhanced.

  9. Customer Satisfaction, Perceived Service Quality and Mediating Role of Perceived Value

    OpenAIRE

    Malik, Saif Ullah

    2012-01-01

    The main objective of this study is to first find out perceived service quality using SERVQUAL and then the role of perceived value as a mediating variable in the service sector of Pakistan. Both descriptive and inferential statistical techniques are used to analyze the effects of independent variables (i.e. perceived service quality) on customer satisfaction (dependent variable) and the role of mediating variable (i.e. perceived value). Stepwise regression analysis is used to examine the eff...

  10. How ocean lateral mixing changes Southern Ocean variability in coupled climate models

    Science.gov (United States)

    Pradal, M. A. S.; Gnanadesikan, A.; Thomas, J. L.

    2016-02-01

    The lateral mixing of tracers represents a major uncertainty in the formulation of coupled climate models. The mixing of tracers along density surfaces in the interior and horizontally within the mixed layer is often parameterized using a mixing coefficient ARedi. The models used in the Coupled Model Intercomparison Project 5 exhibit more than an order of magnitude range in the values of this coefficient used within the Southern Ocean. The impacts of such uncertainty on Southern Ocean variability have remained unclear, even as recent work has shown that this variability differs between different models. In this poster, we change the lateral mixing coefficient within GFDL ESM2Mc, a coarse-resolution Earth System model that nonetheless has a reasonable circulation within the Southern Ocean. As the coefficient varies from 400 to 2400 m2/s the amplitude of the variability varies significantly. The low-mixing case shows strong decadal variability with an annual mean RMS temperature variability exceeding 1C in the Circumpolar Current. The highest-mixing case shows a very similar spatial pattern of variability, but with amplitudes only about 60% as large. The suppression of mixing is larger in the Atlantic Sector of the Southern Ocean relatively to the Pacific sector. We examine the salinity budgets of convective regions, paying particular attention to the extent to which high mixing prevents the buildup of low-saline waters that are capable of shutting off deep convection entirely.

  11. A State Space Modeling Approach to Mediation Analysis

    Science.gov (United States)

    Gu, Fei; Preacher, Kristopher J.; Ferrer, Emilio

    2014-01-01

    Mediation is a causal process that evolves over time. Thus, a study of mediation requires data collected throughout the process. However, most applications of mediation analysis use cross-sectional rather than longitudinal data. Another implicit assumption commonly made in longitudinal designs for mediation analysis is that the same mediation…

  12. The mediating role of pain acceptance during mindfulness-based cognitive therapy for headache.

    Science.gov (United States)

    Day, Melissa A; Thorn, Beverly E

    2016-04-01

    This study aimed to determine if mindfulness-based cognitive therapy (MBCT) engenders improvement in headache outcomes via the mechanisms specified by theory: (1) change in psychological process, (i.e., pain acceptance); and concurrently (2) change in cognitive content, (i.e., pain catastrophizing; headache management self-efficacy). A secondary analysis of a randomized controlled trial comparing MBCT to a medical treatment as usual, delayed treatment (DT) control was conducted. Participants were individuals with headache pain who completed MBCT or DT (N=24) at the Kilgo Headache Clinic or psychology clinic. Standardized measures of the primary outcome (pain interference) and proposed mediators were administered at pre- and post-treatment; change scores were calculated. Bootstrap mediation models were conducted. Pain acceptance emerged as a significant mediator of the group-interference relation (pMediation models examining acceptance subscales showed nuances in this effect, with activity engagement emerging as a significant mediator (pmediation due to a non-significant pathway from the mediator to outcome. Criteria for mediation was also not met for the catastrophizing or self-efficacy models as neither of these variables significantly predicted pain interference. Pain acceptance, and specifically engagement in valued activities despite pain, may be a key mechanism underlying improvement in pain outcome during a MBCT for headache pain intervention. The theorized mediating role of cognitive content factors was not supported in this preliminary study. A large, definitive trial is warranted to replicate and extend the findings in order to streamline and optimize MBCT for headache. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. A Composite Likelihood Inference in Latent Variable Models for Ordinal Longitudinal Responses

    Science.gov (United States)

    Vasdekis, Vassilis G. S.; Cagnone, Silvia; Moustaki, Irini

    2012-01-01

    The paper proposes a composite likelihood estimation approach that uses bivariate instead of multivariate marginal probabilities for ordinal longitudinal responses using a latent variable model. The model considers time-dependent latent variables and item-specific random effects to be accountable for the interdependencies of the multivariate…

  14. Input variable selection for data-driven models of Coriolis flowmeters for two-phase flow measurement

    International Nuclear Information System (INIS)

    Wang, Lijuan; Yan, Yong; Wang, Xue; Wang, Tao

    2017-01-01

    Input variable selection is an essential step in the development of data-driven models for environmental, biological and industrial applications. Through input variable selection to eliminate the irrelevant or redundant variables, a suitable subset of variables is identified as the input of a model. Meanwhile, through input variable selection the complexity of the model structure is simplified and the computational efficiency is improved. This paper describes the procedures of the input variable selection for the data-driven models for the measurement of liquid mass flowrate and gas volume fraction under two-phase flow conditions using Coriolis flowmeters. Three advanced input variable selection methods, including partial mutual information (PMI), genetic algorithm-artificial neural network (GA-ANN) and tree-based iterative input selection (IIS) are applied in this study. Typical data-driven models incorporating support vector machine (SVM) are established individually based on the input candidates resulting from the selection methods. The validity of the selection outcomes is assessed through an output performance comparison of the SVM based data-driven models and sensitivity analysis. The validation and analysis results suggest that the input variables selected from the PMI algorithm provide more effective information for the models to measure liquid mass flowrate while the IIS algorithm provides a fewer but more effective variables for the models to predict gas volume fraction. (paper)

  15. Social modeling of eating mediated by mirror neuron activity: A causal model moderated by frontal asymmetry and BMI.

    Science.gov (United States)

    McGeown, Laura; Davis, Ron

    2018-02-15

    The social modeling of eating effect refers to the consistently demonstrated phenomenon that individuals tend to match their quantity of food intake to their eating companion. The current study sought to explore whether activity within the mirror neuron system (MNS) mediates the social modeling of eating effect as a function of EEG frontal asymmetry and body mass index (BMI). Under the guise of rating empathy, 93 female undergraduates viewed a female video confederate "incidentally" consume either a low or high intake of chips while electroencephalogram (EEG) activity was recorded. Subsequent ad libitum chip consumption was quantified. A first- and second-stage dual moderation model revealed that frontal asymmetry and BMI moderated an indirect effect of model consumption on participants' food consumption as mediated by MNS activity at electrode site C3, a 3 b 3 =-0.718, SE=0.365, 95% CI [-1.632, -0.161]. Left frontal asymmetry was associated with greater mu activity and a positive association between model and participant chip consumption, while right frontal asymmetry was associated with less mu activity and a negative association between model and participant consumption. Across all levels of frontal asymmetry, the effect was only significant among those with a BMI at the 50th percentile or lower. Thus, among leaner individuals, the MNS was demonstrated to mediate social modeling of eating, as moderated by frontal asymmetry. These findings are integrated within the normative account of social modeling of eating. It is proposed that the normative framework may benefit from consideration of both conscious and unconscious operation of intake norms. Copyright © 2017 Elsevier B.V. All rights reserved.

  16. Ensembling Variable Selectors by Stability Selection for the Cox Model

    Directory of Open Access Journals (Sweden)

    Qing-Yan Yin

    2017-01-01

    Full Text Available As a pivotal tool to build interpretive models, variable selection plays an increasingly important role in high-dimensional data analysis. In recent years, variable selection ensembles (VSEs have gained much interest due to their many advantages. Stability selection (Meinshausen and Bühlmann, 2010, a VSE technique based on subsampling in combination with a base algorithm like lasso, is an effective method to control false discovery rate (FDR and to improve selection accuracy in linear regression models. By adopting lasso as a base learner, we attempt to extend stability selection to handle variable selection problems in a Cox model. According to our experience, it is crucial to set the regularization region Λ in lasso and the parameter λmin properly so that stability selection can work well. To the best of our knowledge, however, there is no literature addressing this problem in an explicit way. Therefore, we first provide a detailed procedure to specify Λ and λmin. Then, some simulated and real-world data with various censoring rates are used to examine how well stability selection performs. It is also compared with several other variable selection approaches. Experimental results demonstrate that it achieves better or competitive performance in comparison with several other popular techniques.

  17. Materialism and addictive buying in women: the mediating role of anxiety and depression.

    Science.gov (United States)

    Otero-López, José Manuel; Villardefrancos, Estíbaliz

    2013-08-01

    There is empirical evidence regarding the interrelationships between materialism, negative emotions, and addictive buying. The aim of this study was to clarify the direction of the relationships among these variables. Specifically, the main objective was to explore the possible mediating roles of anxiety and depression in the link between materialism and addictive buying. Path analysis results, using a sample of 685 women, generally supported the suitability of the proposed model in which anxiety and depression mediated the effects of the materialism dimensions, "importance" and "success," on addictive buying, and that depression also mediates the influence of the "importance" and "happiness" dimensions. Moreover, a direct effect of the importance dimension on addictive buying was found.

  18. A Rabbit Model for Testing Helper-Dependent Adenovirus-Mediated Gene Therapy for Vein Graft Atherosclerosis.

    Science.gov (United States)

    Bi, Lianxiang; Wacker, Bradley K; Bueren, Emma; Ham, Ervin; Dronadula, Nagadhara; Dichek, David A

    2017-12-15

    Coronary artery bypass vein grafts are a mainstay of therapy for human atherosclerosis. Unfortunately, the long-term patency of vein grafts is limited by accelerated atherosclerosis. Gene therapy, directed at the vein graft wall, is a promising approach for preventing vein graft atherosclerosis. Because helper-dependent adenovirus (HDAd) efficiently transduces grafted veins and confers long-term transgene expression, HDAd is an excellent candidate for delivery of vein graft-targeted gene therapy. We developed a model of vein graft atherosclerosis in fat-fed rabbits and demonstrated long-term (≥20 weeks) persistence of HDAd genomes after graft transduction. This model enables quantitation of vein graft hemodynamics, wall structure, lipid accumulation, cellularity, vector persistence, and inflammatory markers on a single graft. Time-course experiments identified 12 weeks after transduction as an optimal time to measure efficacy of gene therapy on the critical variables of lipid and macrophage accumulation. We also used chow-fed rabbits to test whether HDAd infusion in vein grafts promotes intimal growth and inflammation. HDAd did not increase intimal growth, but had moderate-yet significant-pro-inflammatory effects. The vein graft atherosclerosis model will be useful for testing HDAd-mediated gene therapy; however, pro-inflammatory effects of HdAd remain a concern in developing HDAd as a therapy for vein graft disease.

  19. Longitudinal Mediation Modeling of Unhealthy Behaviors as Mediators between Workplace Demands/Support and Depressive Symptoms

    Science.gov (United States)

    Magnusson Hanson, Linda L.; Peristera, Paraskevi; Chungkham, Holendro Singh; Westerlund, Hugo

    2016-01-01

    Lifestyle has been regarded as a key pathway through which adverse psychosocial working characteristics can give rise to long-term health problems. The purpose of this study was to estimate the indirect/mediated effect of health behaviors in the longitudinal work characteristics-depression relationship. The analyses were based on the Swedish Longitudinal Occupational Survey of Health, including 3706 working participants with repeat survey measures on four occasions (2008, 2010, 2012 and 2014). Psychosocial work characteristics including demands and social support were analyzed in relation to depressive symptoms. Autoregressive longitudinal mediation models using structural equation modeling were used to estimate the intermediate effects of unhealthy behaviors including current smoking, excessive alcohol consumption, unhealthy diet and physical inactivity. Both workplace demands and social support were related to later depressive symptoms. In bivariate models we found no significant paths from workplace demands to health behaviors, but two out of three significant time-specific paths from workplace support to excessive drinking and from excessive drinking to depressive symptoms. Social support was also associated with subsequent unhealthy diet, and one path from unhealthy diet to depressive symptoms was found. However, despite indications of certain longitudinal relationships between psychosocial working conditions and health behaviors as well as between health behaviors and depressive symptoms, no significant intermediate effects were found (p>0.05). We conclude that changes in unhealthy behaviors over a period of two years are unlikely to act as strong intermediaries in the longitudinal relationship between job demands and depressive symptoms and between social support and depressive symptoms. PMID:28036376

  20. Longitudinal Mediation Modeling of Unhealthy Behaviors as Mediators between Workplace Demands/Support and Depressive Symptoms.

    Science.gov (United States)

    Magnusson Hanson, Linda L; Peristera, Paraskevi; Chungkham, Holendro Singh; Westerlund, Hugo

    2016-01-01

    Lifestyle has been regarded as a key pathway through which adverse psychosocial working characteristics can give rise to long-term health problems. The purpose of this study was to estimate the indirect/mediated effect of health behaviors in the longitudinal work characteristics-depression relationship. The analyses were based on the Swedish Longitudinal Occupational Survey of Health, including 3706 working participants with repeat survey measures on four occasions (2008, 2010, 2012 and 2014). Psychosocial work characteristics including demands and social support were analyzed in relation to depressive symptoms. Autoregressive longitudinal mediation models using structural equation modeling were used to estimate the intermediate effects of unhealthy behaviors including current smoking, excessive alcohol consumption, unhealthy diet and physical inactivity. Both workplace demands and social support were related to later depressive symptoms. In bivariate models we found no significant paths from workplace demands to health behaviors, but two out of three significant time-specific paths from workplace support to excessive drinking and from excessive drinking to depressive symptoms. Social support was also associated with subsequent unhealthy diet, and one path from unhealthy diet to depressive symptoms was found. However, despite indications of certain longitudinal relationships between psychosocial working conditions and health behaviors as well as between health behaviors and depressive symptoms, no significant intermediate effects were found (p>0.05). We conclude that changes in unhealthy behaviors over a period of two years are unlikely to act as strong intermediaries in the longitudinal relationship between job demands and depressive symptoms and between social support and depressive symptoms.

  1. The Mediational Role of Coping Strategies in the Relationship Between Self-Esteem and Risk of Internet Addiction

    Directory of Open Access Journals (Sweden)

    Rocco Servidio

    2018-03-01

    Full Text Available The aim of the present study is to explore, through a mediation model, the relationship among self-esteem, coping strategies, and the risk of Internet addiction in a sample of 300 Italian university students. We submitted the data to a descriptive, mediational comparison between variables (t-test, and correlational statistical analyses. The results confirmed the effect of self-esteem on the risk of Internet addiction. However, we found that the introduction of coping strategies as a mediator gives rise to partial mediation. A low level of self-esteem is a predictor of avoidance-oriented coping that, in turn, affects the risk of Internet addiction.

  2. Multiscale thermohydrologic model: addressing variability and uncertainty at Yucca Mountain

    International Nuclear Information System (INIS)

    Buscheck, T; Rosenberg, N D; Gansemer, J D; Sun, Y

    2000-01-01

    Performance assessment and design evaluation require a modeling tool that simultaneously accounts for processes occurring at a scale of a few tens of centimeters around individual waste packages and emplacement drifts, and also on behavior at the scale of the mountain. Many processes and features must be considered, including non-isothermal, multiphase-flow in rock of variable saturation and thermal radiation in open cavities. Also, given the nature of the fractured rock at Yucca Mountain, a dual-permeability approach is needed to represent permeability. A monolithic numerical model with all these features requires too large a computational cost to be an effective simulation tool, one that is used to examine sensitivity to key model assumptions and parameters. We have developed a multi-scale modeling approach that effectively simulates 3D discrete-heat-source, mountain-scale thermohydrologic behavior at Yucca Mountain and captures the natural variability of the site consistent with what we know from site characterization and waste-package-to-waste-package variability in heat output. We describe this approach and present results examining the role of infiltration flux, the most important natural-system parameter with respect to how thermohydrologic behavior influences the performance of the repository

  3. Modelling toehold-mediated RNA strand displacement.

    Science.gov (United States)

    Šulc, Petr; Ouldridge, Thomas E; Romano, Flavio; Doye, Jonathan P K; Louis, Ard A

    2015-03-10

    We study the thermodynamics and kinetics of an RNA toehold-mediated strand displacement reaction with a recently developed coarse-grained model of RNA. Strand displacement, during which a single strand displaces a different strand previously bound to a complementary substrate strand, is an essential mechanism in active nucleic acid nanotechnology and has also been hypothesized to occur in vivo. We study the rate of displacement reactions as a function of the length of the toehold and temperature and make two experimentally testable predictions: that the displacement is faster if the toehold is placed at the 5' end of the substrate; and that the displacement slows down with increasing temperature for longer toeholds. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  4. A Time-Series Water Level Forecasting Model Based on Imputation and Variable Selection Method

    Directory of Open Access Journals (Sweden)

    Jun-He Yang

    2017-01-01

    Full Text Available Reservoirs are important for households and impact the national economy. This paper proposed a time-series forecasting model based on estimating a missing value followed by variable selection to forecast the reservoir’s water level. This study collected data from the Taiwan Shimen Reservoir as well as daily atmospheric data from 2008 to 2015. The two datasets are concatenated into an integrated dataset based on ordering of the data as a research dataset. The proposed time-series forecasting model summarily has three foci. First, this study uses five imputation methods to directly delete the missing value. Second, we identified the key variable via factor analysis and then deleted the unimportant variables sequentially via the variable selection method. Finally, the proposed model uses a Random Forest to build the forecasting model of the reservoir’s water level. This was done to compare with the listing method under the forecasting error. These experimental results indicate that the Random Forest forecasting model when applied to variable selection with full variables has better forecasting performance than the listing model. In addition, this experiment shows that the proposed variable selection can help determine five forecast methods used here to improve the forecasting capability.

  5. Teacher’s Autonomy Support and Engagement in Math: Multiple Mediating Roles of Self-efficacy, Intrinsic Value, and Boredom

    Science.gov (United States)

    Wang, Jia; Liu, Ru-De; Ding, Yi; Xu, Le; Liu, Ying; Zhen, Rui

    2017-01-01

    Previous studies have highlighted the impacts of environmental factors (teacher’s autonomy support) and individual factors (self-efficacy, intrinsic value, and boredom) on academic engagement. This study aimed to investigate these variables and examine the relations among them. Three structural equation models tested the multiple mediational roles of self-efficacy, intrinsic value, and boredom in the relation between teacher’s autonomy support and behavioral, emotional, and cognitive engagement, respectively, in math. A total of 637 Chinese middle school students (313 males, 324 females; mean age = 14.82) voluntarily participated in this study. Results revealed that self-efficacy, intrinsic value, and boredom played important and mediating roles between perceived teacher’s autonomy support and student engagement. Specifically, these three individual variables partly mediated the relations between perceived teacher’s autonomy support and behavioral and cognitive engagement, while fully mediating the relation between perceived teacher’s autonomy support and emotional engagement. These findings complement and extend the understanding of factors affecting students’ engagement in math. PMID:28690560

  6. Shared Authentic Leadership in Research Teams: Testing a Multiple Mediation Model

    NARCIS (Netherlands)

    Günter, Hannes; Gardner, William L.; Davis McCauley, Kelly; Randolph-Seng, Brandon; P. Prahbu, Veena

    2017-01-01

    Research teams face complex leadership and coordination challenges. We propose shared authentic leadership (SAL) as a timely approach to addressing these challenges. Drawing from authentic and functional leadership theories, we posit a multiple mediation model that suggests three mechanisms whereby

  7. Oracle Efficient Variable Selection in Random and Fixed Effects Panel Data Models

    DEFF Research Database (Denmark)

    Kock, Anders Bredahl

    This paper generalizes the results for the Bridge estimator of Huang et al. (2008) to linear random and fixed effects panel data models which are allowed to grow in both dimensions. In particular we show that the Bridge estimator is oracle efficient. It can correctly distinguish between relevant...... and irrelevant variables and the asymptotic distribution of the estimators of the coefficients of the relevant variables is the same as if only these had been included in the model, i.e. as if an oracle had revealed the true model prior to estimation. In the case of more explanatory variables than observations......, we prove that the Marginal Bridge estimator can asymptotically correctly distinguish between relevant and irrelevant explanatory variables. We do this without restricting the dependence between covariates and without assuming sub Gaussianity of the error terms thereby generalizing the results...

  8. Variable Renewable Energy in Long-Term Planning Models: A Multi-Model Perspective

    Energy Technology Data Exchange (ETDEWEB)

    Cole, Wesley J. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Frew, Bethany A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Mai, Trieu T. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Sun, Yinong [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Bistline, John [Electric Power Research Inst., Palo Alto, CA (United States); Blanford, Geoffrey [Electric Power Research Inst., Palo Alto, CA (United States); Young, David [Electric Power Research Inst., Palo Alto, CA (United States); Marcy, Cara [Energy Information Administration, Washington, DC (United States); Namovicz, Chris [Energy Information Administration, Washington, DC (United States); Edelman, Risa [Environmental Protection Agency, Washington, DC (United States); Meroney, Bill [Environmental Protection Agency; Sims, Ryan [Environmental Protection Agency; Stenhouse, Jeb [Environmental Protection Agency; Donohoo-Vallett, Paul [U.S. Department of Energy

    2017-11-03

    Long-term capacity expansion models of the U.S. electricity sector have long been used to inform electric sector stakeholders and decision makers. With the recent surge in variable renewable energy (VRE) generators - primarily wind and solar photovoltaics - the need to appropriately represent VRE generators in these long-term models has increased. VRE generators are especially difficult to represent for a variety of reasons, including their variability, uncertainty, and spatial diversity. To assess current best practices, share methods and data, and identify future research needs for VRE representation in capacity expansion models, four capacity expansion modeling teams from the Electric Power Research Institute, the U.S. Energy Information Administration, the U.S. Environmental Protection Agency, and the National Renewable Energy Laboratory conducted two workshops of VRE modeling for national-scale capacity expansion models. The workshops covered a wide range of VRE topics, including transmission and VRE resource data, VRE capacity value, dispatch and operational modeling, distributed generation, and temporal and spatial resolution. The objectives of the workshops were both to better understand these topics and to improve the representation of VRE across the suite of models. Given these goals, each team incorporated model updates and performed additional analyses between the first and second workshops. This report summarizes the analyses and model 'experiments' that were conducted as part of these workshops as well as the various methods for treating VRE among the four modeling teams. The report also reviews the findings and learnings from the two workshops. We emphasize the areas where there is still need for additional research and development on analysis tools to incorporate VRE into long-term planning and decision-making.

  9. Separation of variables in anisotropic models: anisotropic Rabi and elliptic Gaudin model in an external magnetic field

    Science.gov (United States)

    Skrypnyk, T.

    2017-08-01

    We study the problem of separation of variables for classical integrable Hamiltonian systems governed by non-skew-symmetric non-dynamical so(3)\\otimes so(3) -valued elliptic r-matrices with spectral parameters. We consider several examples of such models, and perform separation of variables for classical anisotropic one- and two-spin Gaudin-type models in an external magnetic field, and for Jaynes-Cummings-Dicke-type models without the rotating wave approximation.

  10. Work-family conflict and alcohol use: examination of a moderated mediation model.

    Science.gov (United States)

    Wolff, Jennifer M; Rospenda, Kathleen M; Richman, Judith A; Liu, Li; Milner, Lauren A

    2013-01-01

    Research consistently documents the negative effects of work-family conflict; however, little research focuses on alcohol use. This study embraces a tension reduction theory of drinking, wherein alcohol use is thought to reduce the negative effects of stress. The purpose of the study was to test a moderated mediation model of the relationship between work-family conflict and alcohol use in a Chicagoland community sample of 998 caregivers. Structural equation models showed that distress mediated the relationship between work-family conflict and alcohol use. Furthermore, tension reduction expectancies of alcohol exacerbated the relationship between distress and alcohol use. The results advance the study of work-family conflict and alcohol use, helping explain this complicated relationship using sophisticated statistical techniques. Implications for theory and practice are discussed.

  11. Modelling the effects of spatial variability on radionuclide migration

    International Nuclear Information System (INIS)

    1998-01-01

    The NEA workshop reflect the present status in national waste management program, specifically in spatial variability and performance assessment of geologic disposal sites for deed repository system the four sessions were: Spatial Variability: Its Definition and Significance to Performance Assessment and Site Characterisation; Experience with the Modelling of Radionuclide Migration in the Presence of Spatial Variability in Various Geological Environments; New Areas for Investigation: Two Personal Views; What is Wanted and What is Feasible: Views and Future Plans in Selected Waste Management Organisations. The 26 papers presented on the four oral sessions and on the poster session have been abstracted and indexed individually for the INIS database. (R.P.)

  12. Effort-reward imbalance and organisational injustice among aged nurses: a moderated mediation model.

    Science.gov (United States)

    Topa, Gabriela; Guglielmi, Dina; Depolo, Marco

    2016-09-01

    To test the effort-reward imbalance model among older nurses, expanding it to include the moderation of overcommitment and age in the stress-health complaints relationship, mediated by organisational injustice. The theoretical framework included the effort-reward imbalance, the uncertainty management and the socio-emotional selectivity models. Employing a two-wave design, the participants were 255 nurses aged 45 years and over, recruited from four large hospitals in Spain (Madrid and Basque Country). The direct effect of imbalance on health complaints was supported: it was significant when overcommitment was low but not when it was high. Organisational injustice mediated the influence of effort-reward imbalance on health complaints. The conditional effect of the mediation of organisational injustice was significant in three of the overcommitment/age conditions but it weakened, becoming non-significant, when the level of overcommitment was low and age was high. The study tested the model in nursing populations and expanded it to the settings of occupational health and safety at work. The results of this study highlight the importance of effort-reward imbalance and organisational justice for creating healthy work environments. © 2016 John Wiley & Sons Ltd.

  13. Understanding magnetic nanoparticle osteoblast receptor-mediated endocytosis using experiments and modeling

    International Nuclear Information System (INIS)

    Tran, Nhiem; Webster, Thomas J

    2013-01-01

    Iron oxide nanoparticles are promising candidates for controlling drug delivery through an external magnetic force to treat a wide range of diseases, including osteoporosis. Previous studies have demonstrated that in the presence of hydroxyapatite coated magnetite (Fe 3 O 4 ) nanoparticles, osteoblast (or bone forming cell) proliferation and long-term functions (such as calcium deposition) were significantly enhanced. Hydroxyapatite is the major inorganic component of bone. As a further attempt to understand why, in the current study, the uptake of such nanoparticles into osteoblasts was experimentally investigated and mathematically modeled. Magnetite nanoparticles were synthesized using a co-precipitation method and were coated with hydroxyapatite. A cellular uptake experiment at low temperatures indicated that receptor-mediated endocytosis contributed to the internalization of the magnetic nanoparticles into osteoblasts. A model was further developed to explain the uptake of magnetic nanoparticles into osteoblasts using receptor-mediated endocytosis. This model may explain the internalization of hydroxyapatite into osteoblasts to elevate intracellular calcium levels necessary to promote osteoblast functions to treat a wide range of orthopedic problems, including osteoporosis. (paper)

  14. Evaluation of a concentric biopsychosocial model of well-being in persons with spinal cord injuries.

    Science.gov (United States)

    Smedema, Susan Miller

    2017-05-01

    The objective of this study was to evaluate a concentric biopsychosocial model of well-being in individuals with spinal cord injuries (SCI). Adults (N = 235) with SCI participated in this study. A cross-sectional design with hierarchical regression and Andrew Hayes' (2013) PROCESS mediation analysis procedure was used to evaluate the model. Each step of the hierarchical regression on life satisfaction, in which biological variables were entered first, social variables were entered second, and psychological variables were entered third, was significant. Examining the standardized partial coefficients, pain, interpersonal self-efficacy, social support, hope-agency, and self-esteem were all significantly associated with life satisfaction, controlling for variables in each outward ring of the concentric model. Four serial mediational analyses were also conducted in which the social and psychological variables significantly partially mediated the relationship between pain and life satisfaction. The results provide support for a concentric biopsychosocial model of well-being in persons with SCI. Rehabilitation interventions should focus on augmenting biopsychosocial factors to allow for maximum improvement in well-being outcomes in individuals with SCI. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

  15. AeroPropulsoServoElasticity: Dynamic Modeling of the Variable Cycle Propulsion System

    Science.gov (United States)

    Kopasakis, George

    2012-01-01

    This presentation was made at the 2012 Fundamental Aeronautics Program Technical Conference and it covers research work for the Dynamic Modeling of the Variable cycle Propulsion System that was done under the Supersonics Project, in the area of AeroPropulsoServoElasticity. The presentation covers the objective for the propulsion system dynamic modeling work, followed by the work that has been done so far to model the variable Cycle Engine, modeling of the inlet, the nozzle, the modeling that has been done to model the affects of flow distortion, and finally presenting some concluding remarks and future plans.

  16. Ocean carbon and heat variability in an Earth System Model

    Science.gov (United States)

    Thomas, J. L.; Waugh, D.; Gnanadesikan, A.

    2016-12-01

    Ocean carbon and heat content are very important for regulating global climate. Furthermore, due to lack of observations and dependence on parameterizations, there has been little consensus in the modeling community on the magnitude of realistic ocean carbon and heat content variability, particularly in the Southern Ocean. We assess the differences between global oceanic heat and carbon content variability in GFDL ESM2Mc using a 500-year, pre-industrial control simulation. The global carbon and heat content are directly out of phase with each other; however, in the Southern Ocean the heat and carbon content are in phase. The global heat mutli-decadal variability is primarily explained by variability in the tropics and mid-latitudes, while the variability in global carbon content is primarily explained by Southern Ocean variability. In order to test the robustness of this relationship, we use three additional pre-industrial control simulations using different mesoscale mixing parameterizations. Three pre-industrial control simulations are conducted with the along-isopycnal diffusion coefficient (Aredi) set to constant values of 400, 800 (control) and 2400 m2 s-1. These values for Aredi are within the range of parameter settings commonly used in modeling groups. Finally, one pre-industrial control simulation is conducted where the minimum in the Gent-McWilliams parameterization closure scheme (AGM) increased to 600 m2 s-1. We find that the different simulations have very different multi-decadal variability, especially in the Weddell Sea where the characteristics of deep convection are drastically changed. While the temporal frequency and amplitude global heat and carbon content changes significantly, the overall spatial pattern of variability remains unchanged between the simulations.

  17. Predictive-property-ranked variable reduction in partial least squares modelling with final complexity adapted models: comparison of properties for ranking.

    Science.gov (United States)

    Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C

    2013-01-14

    The calibration performance of partial least squares regression for one response (PLS1) can be improved by eliminating uninformative variables. Many variable-reduction methods are based on so-called predictor-variable properties or predictive properties, which are functions of various PLS-model parameters, and which may change during the steps of the variable-reduction process. Recently, a new predictive-property-ranked variable reduction method with final complexity adapted models, denoted as PPRVR-FCAM or simply FCAM, was introduced. It is a backward variable elimination method applied on the predictive-property-ranked variables. The variable number is first reduced, with constant PLS1 model complexity A, until A variables remain, followed by a further decrease in PLS complexity, allowing the final selection of small numbers of variables. In this study for three data sets the utility and effectiveness of six individual and nine combined predictor-variable properties are investigated, when used in the FCAM method. The individual properties include the absolute value of the PLS1 regression coefficient (REG), the significance of the PLS1 regression coefficient (SIG), the norm of the loading weight (NLW) vector, the variable importance in the projection (VIP), the selectivity ratio (SR), and the squared correlation coefficient of a predictor variable with the response y (COR). The selective and predictive performances of the models resulting from the use of these properties are statistically compared using the one-tailed Wilcoxon signed rank test. The results indicate that the models, resulting from variable reduction with the FCAM method, using individual or combined properties, have similar or better predictive abilities than the full spectrum models. After mean-centring of the data, REG and SIG, provide low numbers of informative variables, with a meaning relevant to the response, and lower than the other individual properties, while the predictive abilities are

  18. Building models of gauge-mediated supersymmetry breaking without a messenger sector

    International Nuclear Information System (INIS)

    Arkani-Hamed, N.; Murayama, H.; March-Russell, J.

    1998-01-01

    We propose a general scheme for constructing models in which the Standard Model (SM) gauge interactions are the mediators of supersymmetry breaking to the fields in the supersymmetric SM, but where the SM gauge groups couple directly to the sector which breaks supersymmetry dynamically. Despite the direct coupling, the models preserve perturbative unification of the SM gauge coupling constants. Furthermore, the supergravity contributions to the squark and slepton masses can be naturally small, typically being much less than 1% of the gauge-mediated (GM) contributions. Both of these goals can be achieved without need of a fine-tuning or a very small coupling constant. This scheme requires run-away directions at the renormalizable level which are only lifted by non-renormalizable terms in the superpotential. To study the proposed scheme in practice, we develop a modified class of models based on SU(N) x SU(N-1) which allows us to gauge an SU(N-2) global symmetry. However, we point out a new problem which can exist in models where the dynamical supersymmetry breaking sector and the ordinary sector are directly coupled - the two-loop renormalization group has contributions which can induce negative (mass) 2 for the squarks and sleptons. We clarify the origin of the problem and argue that it is likely to be surmountable. We give a recipe for a successful model. (orig.)

  19. Effect of climate variables on cocoa black pod incidence in Sabah using ARIMAX model

    Science.gov (United States)

    Ling Sheng Chang, Albert; Ramba, Haya; Mohd. Jaaffar, Ahmad Kamil; Kim Phin, Chong; Chong Mun, Ho

    2016-06-01

    Cocoa black pod disease is one of the major diseases affecting the cocoa production in Malaysia and also around the world. Studies have shown that the climate variables have influenced the cocoa black pod disease incidence and it is important to quantify the black pod disease variation due to the effect of climate variables. Application of time series analysis especially auto-regressive moving average (ARIMA) model has been widely used in economics study and can be used to quantify the effect of climate variables on black pod incidence to forecast the right time to control the incidence. However, ARIMA model does not capture some turning points in cocoa black pod incidence. In order to improve forecasting performance, other explanatory variables such as climate variables should be included into ARIMA model as ARIMAX model. Therefore, this paper is to study the effect of climate variables on the cocoa black pod disease incidence using ARIMAX model. The findings of the study showed ARIMAX model using MA(1) and relative humidity at lag 7 days, RHt - 7 gave better R square value compared to ARIMA model using MA(1) which could be used to forecast the black pod incidence to assist the farmers determine timely application of fungicide spraying and culture practices to control the black pod incidence.

  20. The Effects of Job Autonomy on Work Outcomes: Self Efficacy as an Intervening Variable

    OpenAIRE

    Susanti Saragih

    2011-01-01

    The purpose of this research was to examine the relationship between job autonomy and work outcomes (job performance, job satisfaction and job stress), self efficacy as a mediating variable. This research also investigated the impact of job satisfaction on job performance and job stress on job performance. Va-riables in this research were measured via a survey of 190 banking salespersons in D.I. Yogyakarta and Solo. Structural Equation Modeling (SEM) were used to examine the effects of job au...

  1. Incorporating Latent Variables into Discrete Choice Models - A Simultaneous Estimation Approach Using SEM Software

    Directory of Open Access Journals (Sweden)

    Dirk Temme

    2008-12-01

    Full Text Available Integrated choice and latent variable (ICLV models represent a promising new class of models which merge classic choice models with the structural equation approach (SEM for latent variables. Despite their conceptual appeal, applications of ICLV models in marketing remain rare. We extend previous ICLV applications by first estimating a multinomial choice model and, second, by estimating hierarchical relations between latent variables. An empirical study on travel mode choice clearly demonstrates the value of ICLV models to enhance the understanding of choice processes. In addition to the usually studied directly observable variables such as travel time, we show how abstract motivations such as power and hedonism as well as attitudes such as a desire for flexibility impact on travel mode choice. Furthermore, we show that it is possible to estimate such a complex ICLV model with the widely available structural equation modeling package Mplus. This finding is likely to encourage more widespread application of this appealing model class in the marketing field.

  2. a modified intervention model for gross domestic product variable

    African Journals Online (AJOL)

    observations on a variable that have been measured at ... assumption that successive values in the data file ... these interventions, one may try to evaluate the effect of ... generalized series by comparing the distinct periods. A ... the process of checking for adequacy of the model based .... As a result, the model's forecast will.

  3. Assessing the accuracy and stability of variable selection methods for random forest modeling in ecology.

    Science.gov (United States)

    Fox, Eric W; Hill, Ryan A; Leibowitz, Scott G; Olsen, Anthony R; Thornbrugh, Darren J; Weber, Marc H

    2017-07-01

    Random forest (RF) modeling has emerged as an important statistical learning method in ecology due to its exceptional predictive performance. However, for large and complex ecological data sets, there is limited guidance on variable selection methods for RF modeling. Typically, either a preselected set of predictor variables are used or stepwise procedures are employed which iteratively remove variables according to their importance measures. This paper investigates the application of variable selection methods to RF models for predicting probable biological stream condition. Our motivating data set consists of the good/poor condition of n = 1365 stream survey sites from the 2008/2009 National Rivers and Stream Assessment, and a large set (p = 212) of landscape features from the StreamCat data set as potential predictors. We compare two types of RF models: a full variable set model with all 212 predictors and a reduced variable set model selected using a backward elimination approach. We assess model accuracy using RF's internal out-of-bag estimate, and a cross-validation procedure with validation folds external to the variable selection process. We also assess the stability of the spatial predictions generated by the RF models to changes in the number of predictors and argue that model selection needs to consider both accuracy and stability. The results suggest that RF modeling is robust to the inclusion of many variables of moderate to low importance. We found no substantial improvement in cross-validated accuracy as a result of variable reduction. Moreover, the backward elimination procedure tended to select too few variables and exhibited numerous issues such as upwardly biased out-of-bag accuracy estimates and instabilities in the spatial predictions. We use simulations to further support and generalize results from the analysis of real data. A main purpose of this work is to elucidate issues of model selection bias and instability to ecologists interested in

  4. Perceived medication adherence barriers mediating effects between gastrointestinal symptoms and health-related quality of life in pediatric inflammatory bowel disease.

    Science.gov (United States)

    Varni, James W; Shulman, Robert J; Self, Mariella M; Saeed, Shehzad A; Zacur, George M; Patel, Ashish S; Nurko, Samuel; Neigut, Deborah A; Franciosi, James P; Saps, Miguel; Denham, Jolanda M; Dark, Chelsea Vaughan; Bendo, Cristiane B; Pohl, John F

    2018-01-01

    The primary objective was to investigate the mediating effects of patient-perceived medication adherence barriers in the relationship between gastrointestinal symptoms and generic health-related quality of life (HRQOL) in adolescents with inflammatory bowel disease (IBD). The secondary objective explored patient health communication and gastrointestinal worry as additional mediators with medication adherence barriers in a serial multiple mediator model. The Pediatric Quality of Life Inventory™ Gastrointestinal Symptoms, Medicines, Communication, Gastrointestinal Worry, and Generic Core Scales were completed in a 9-site study by 172 adolescents with IBD. Gastrointestinal Symptoms Scales measuring stomach pain, constipation, or diarrhea and perceived medication adherence barriers were tested for bivariate and multivariate linear associations with HRQOL. Mediational analyses were conducted to test the hypothesized mediating effects of perceived medication adherence barriers as an intervening variable between gastrointestinal symptoms and HRQOL. The predictive effects of gastrointestinal symptoms on HRQOL were mediated in part by perceived medication adherence barriers. Patient health communication was a significant additional mediator. In predictive analytics models utilizing multiple regression analyses, demographic variables, gastrointestinal symptoms (stomach pain, constipation, or diarrhea), and perceived medication adherence barriers significantly accounted for 45, 38, and 29 percent of the variance in HRQOL (all Ps barriers explain in part the effects of gastrointestinal symptoms on HRQOL in adolescents with IBD. Patient health communication to healthcare providers and significant others further explain the mechanism in the relationship between gastrointestinal symptoms, perceived medication adherence barriers, and HRQOL.

  5. Gross Motor Skills and Cardiometabolic Risk in Children: A Mediation Analysis.

    Science.gov (United States)

    Burns, Ryan D; Brusseau, Timothy A; Fu, You; Hannon, James C

    2017-04-01

    The purpose of this study was to examine the linear relationship between gross motor skills and cardiometabolic risk, with aerobic fitness as a mediator variable, in low-income children from the United States. Participants were a convenience sample of 224 children (mean ± SD age = 9.1 ± 1.1 yr; 129 girls and 95 boys) recruited from five low-income elementary schools from the Mountain West Region of the United States. Gross motor skills were assessed using the Test for Gross Motor Development, 3rd Edition. Gross motor skills were analyzed using a locomotor skill, a ball skill, and a total gross motor skill score. Aerobic fitness was assessed using the Progressive Aerobic Cardiovascular Endurance Run that was administered during physical education class. A continuous and age- and sex-adjusted metabolic syndrome score (MetS) was calculated from health and blood marker measurements collected in a fasted state before school hours. Total effects, average direct effects, and indirect effects (average causal mediation effect) were calculated using a bootstrap mediation analysis method via a linear regression algorithm. The average causal mediation effect of gross locomotor skills on MetS scores, using aerobic fitness as the mediator variable, was statistically significant (β = -0.055, 95% confidence interval = -0.097 to -0.021, P = 0.003). The model explained approximately 17.5% of the total variance in MetS with approximately 43.7% of the relationship between locomotor skills and MetS mediated through aerobic fitness. Ball skills did not significantly relate with cardiometabolic risk. There is a significant relationship between gross locomotor skills and cardiometabolic risk that is partially mediated through aerobic fitness in a sample of low-income children from the United States.

  6. Emotional Exhaustion and Job Satisfaction in Airport Security Officers - Work-Family Conflict as Mediator in the Job Demands-Resources Model.

    Science.gov (United States)

    Baeriswyl, Sophie; Krause, Andreas; Schwaninger, Adrian

    2016-01-01

    The growing threat of terrorism has increased the importance of aviation security and the work of airport security officers (screeners). Nonetheless, airport security research has yet to focus on emotional exhaustion and job satisfaction as major determinants of screeners' job performance. The present study bridges this research gap by applying the job demands-resources (JD-R) model and using work-family conflict (WFC) as an intervening variable to study relationships between work characteristics (workload and supervisor support), emotional exhaustion, and job satisfaction in 1,127 screeners at a European airport. Results of structural equation modeling revealed that (a) supervisor support as a major job resource predicted job satisfaction among screeners; (b) workload as a major job demand predicted their emotional exhaustion; and (c) WFC proved to be a promising extension to the JD-R model that partially mediated the impact of supervisor support and workload on job satisfaction and emotional exhaustion. Theoretical and practical implications are discussed.

  7. Shared Authentic Leadership in Research Teams: Testing a Multiple Mediation Model.

    Science.gov (United States)

    Guenter, Hannes; Gardner, William L; Davis McCauley, Kelly; Randolph-Seng, Brandon; Prabhu, Veena P

    2017-12-01

    Research teams face complex leadership and coordination challenges. We propose shared authentic leadership (SAL) as a timely approach to addressing these challenges. Drawing from authentic and functional leadership theories, we posit a multiple mediation model that suggests three mechanisms whereby SAL influences team effectiveness: shared mental models (SMM), team trust, and team coordination. To test our hypotheses, we collected survey data on leadership and teamwork within 142 research teams that recently published an article in a peer-reviewed management journal. The results indicate team coordination represents the primary mediating mechanism accounting for the relationship between SAL and research team effectiveness. While teams with high trust and SMM felt more successful and were more satisfied, they were less successful in publishing in high-impact journals. We also found the four SAL dimensions (i.e., self-awareness, relational transparency, balanced processing, and internalized moral perspective) to associate differently with team effectiveness.

  8. Mother-adolescent conflict as a mediator between adolescent problem behaviors and maternal psychological control.

    Science.gov (United States)

    Steeger, Christine M; Gondoli, Dawn M

    2013-04-01

    This study examined mother-adolescent conflict as a mediator of longitudinal reciprocal relations between adolescent aggression and depressive symptoms and maternal psychological control. Motivated by family systems theory and the transactions that occur between individual and dyadic levels of the family system, we examined the connections among these variables during a developmental period when children and parents experience significant psychosocial changes. Three years of self-report data were collected from 168 mother-adolescent dyads, beginning when the adolescents (55.4% girls) were in 6th grade. Models were tested using longitudinal path analysis. Results indicated that the connection between adolescent aggression (and depressive symptoms) and maternal psychological control was best characterized as adolescent-driven, indirect, and mediated by mother-adolescent conflict; there were no indications of parent-driven indirect effects. That is, prior adolescent aggression and depressive symptoms were associated with increased conflict. In turn, conflict was associated with increased psychological control. Within our mediation models, reciprocal direct effects between both problem behaviors and conflict and between conflict and psychological control were also found. Additionally, exploratory analyses regarding the role of adolescent gender as a moderator of variable relations were conducted. These analyses revealed no gender-related patterns of moderation, whether moderated mediation or specific path tests for moderation were considered. This study corroborates prior research finding support for child effects on parenting behaviors during early adolescence. (PsycINFO Database Record (c) 2013 APA, all rights reserved).

  9. Changes in Southern Hemisphere circulation variability in climate change modelling experiments

    International Nuclear Information System (INIS)

    Grainger, Simon; Frederiksen, Carsten; Zheng, Xiaogu

    2007-01-01

    Full text: The seasonal mean of a climate variable can be considered as a statistical random variable, consisting of a signal and noise components (Madden 1976). The noise component consists of internal intraseasonal variability, and is not predictable on time-scales of a season or more ahead. The signal consists of slowly varying external and internal variability, and is potentially predictable on seasonal time-scales. The method of Zheng and Frederiksen (2004) has been applied to monthly time series of 500hPa Geopotential height from models submitted to the Coupled Model Intercomparison Project (CMIP3) experiment to obtain covariance matrices of the intraseasonal and slow components of covariability for summer and winter. The Empirical Orthogonal Functions (EOFs) of the intraseasonal and slow covariance matrices for the second half of the 20th century are compared with those observed by Frederiksen and Zheng (2007). The leading EOF in summer and winter for both the intraseasonal and slow components of covariability is the Southern Annular Mode (see, e.g. Kiladis and Mo 1998). This is generally reproduced by the CMIP3 models, although with different variance amounts. The observed secondary intraseasonal covariability modes of wave 4 patterns in summer and wave 3 or blocking in winter are also generally seen in the models, although the actual spatial pattern is different. For the slow covariabilty, the models are less successful in reproducing the two observed ENSO modes, with generally only one of them being represented among the leading EOFs. However, most models reproduce the observed South Pacific wave pattern. The intraseasonal and slow covariances matrices of 500hPa geopotential height under three climate change scenarios are also analysed and compared with those found for the second half of the 20th century. Through aggregating the results from a number of CMIP3 models, a consensus estimate of the changes in Southern Hemisphere variability, and their

  10. The indirect association of job strain with long-term sickness absence through bullying: a mediation analysis using structural equation modeling

    Directory of Open Access Journals (Sweden)

    Heidi Janssens

    2016-08-01

    Full Text Available Abstract Background In this longitudinal study the complex interplay between both job strain and bullying in relation to sickness absence was investigated. Following the “work environment hypothesis”, which establishes several work characteristics as antecedents of bullying, we assumed that job strain, conceptualized by the Job-Demand-Control model, has an indirect relation with long-term sickness absence through bullying. Methods The sample consisted of 2983 Belgian workers, aged 30 to 55 years, who participated in the Belstress III study. They completed a survey, including the Job Content Questionnaire and a bullying inventory, at baseline. Their sickness absence figures were registered during 1 year follow-up. Long-term sickness absence was defined as at least 15 consecutive days. A mediation analysis, using structural equation modeling, was performed to examine the indirect association of job strain through bullying with long-term sickness absence. The full structural model was adjusted for several possible confounders: age, gender, occupational group, educational level, company, smoking habits, alcohol use, body mass index, self-rated health, baseline long-term sickness absence and neuroticism. Results The results support the hypothesis: a significant indirect association of job strain with long-term sickness absence through bullying was observed, suggesting that bullying is an intermediate variable between job strain and long-term sickness absence. No evidence for the reversed pathway of an indirect association of bullying through job strain was found. Conclusions Bullying was observed as a mediating variable in the relation between job strain and sickness absence. The results suggest that exposure to job strain may create circumstances in which a worker risks to become a target of bullying. Our findings are generally in line with the work environment hypothesis, which emphasizes the importance of organizational work factors in the

  11. Discrimination, Subjective Wellbeing, and the Role of Gender: A Mediation Model of LGB Minority Stress.

    Science.gov (United States)

    Conlin, Sarah E; Douglass, Richard P; Ouch, Staci

    2017-10-26

    The present study examined the link between discrimination and the three components of subjective wellbeing (positive and negative affect and life satisfaction) among a cisgender sample of lesbian, gay, and bisexual (LGB) adults. Specifically, we investigated internalized homonegativity and expectations of rejection as potential mediators of the links between discrimination and subjective wellbeing among a sample of 215 participants. Results from our structural equation model demonstrated a strong, positive direct link between discrimination and negative affect. Discrimination also had small, negative indirect effects on life satisfaction through our two mediators. Interestingly, neither discrimination nor our two mediators were related with positive affect, demonstrating the need for future research to uncover potential buffers of this link. Finally, our model evidenced configural, metric, and scalar invariance, suggesting that our model applies well for both women and men. Practical implications and future directions for research are discussed.

  12. Modeling key processes causing climate change and variability

    Energy Technology Data Exchange (ETDEWEB)

    Henriksson, S.

    2013-09-01

    Greenhouse gas warming, internal climate variability and aerosol climate effects are studied and the importance to understand these key processes and being able to separate their influence on the climate is discussed. Aerosol-climate model ECHAM5-HAM and the COSMOS millennium model consisting of atmospheric, ocean and carbon cycle and land-use models are applied and results compared to measurements. Topics at focus are climate sensitivity, quasiperiodic variability with a period of 50-80 years and variability at other timescales, climate effects due to aerosols over India and climate effects of northern hemisphere mid- and high-latitude volcanic eruptions. The main findings of this work are (1) pointing out the remaining challenges in reducing climate sensitivity uncertainty from observational evidence, (2) estimates for the amplitude of a 50-80 year quasiperiodic oscillation in global mean temperature ranging from 0.03 K to 0.17 K and for its phase progression as well as the synchronising effect of external forcing, (3) identifying a power law shape S(f) {proportional_to} f-{alpha} for the spectrum of global mean temperature with {alpha} {approx} 0.8 between multidecadal and El Nino timescales with a smaller exponent in modelled climate without external forcing, (4) separating aerosol properties and climate effects in India by season and location (5) the more efficient dispersion of secondary sulfate aerosols than primary carbonaceous aerosols in the simulations, (6) an increase in monsoon rainfall in northern India due to aerosol light absorption and a probably larger decrease due to aerosol dimming effects and (7) an estimate of mean maximum cooling of 0.19 K due to larger northern hemisphere mid- and high-latitude volcanic eruptions. The results could be applied or useful in better isolating the human-caused climate change signal, in studying the processes further and in more detail, in decadal climate prediction, in model evaluation and in emission policy

  13. Latent variable models are network models.

    Science.gov (United States)

    Molenaar, Peter C M

    2010-06-01

    Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.

  14. a Latent Variable Path Analysis Model of Secondary Physics Enrollments in New York State.

    Science.gov (United States)

    Sobolewski, Stanley John

    The Percentage of Enrollment in Physics (PEP) at the secondary level nationally has been approximately 20% for the past few decades. For a more scientifically literate citizenry as well as specialists to continue scientific research and development, it is desirable that more students enroll in physics. Some of the predictor variables for physics enrollment and physics achievement that have been identified previously includes a community's socioeconomic status, the availability of physics, the sex of the student, the curriculum, as well as teacher and student data. This study isolated and identified predictor variables for PEP of secondary schools in New York. Data gathered by the State Education Department for the 1990-1991 school year was used. The source of this data included surveys completed by teachers and administrators on student characteristics and school facilities. A data analysis similar to that done by Bryant (1974) was conducted to determine if the relationships between a set of predictor variables related to physics enrollment had changed in the past 20 years. Variables which were isolated included: community, facilities, teacher experience, number of type of science courses, school size and school science facilities. When these variables were isolated, latent variable path diagrams were proposed and verified by the Linear Structural Relations computer modeling program (LISREL). These diagrams differed from those developed by Bryant in that there were more manifest variables used which included achievement scores in the form of Regents exam results. Two criterion variables were used, percentage of students enrolled in physics (PEP) and percent of students enrolled passing the Regents physics exam (PPP). The first model treated school and community level variables as exogenous while the second model treated only the community level variables as exogenous. The goodness of fit indices for the models was 0.77 for the first model and 0.83 for the second

  15. Strongly coupled semidirect mediation of supersymmetry breaking

    International Nuclear Information System (INIS)

    Ibe, M.; Izawa, K.-I.; Nakai, Y.

    2009-01-01

    Strongly coupled semidirect gauge mediation models of supersymmetry breaking through massive mediators with standard-model charges are investigated by means of composite degrees of freedom. Sizable mediation is realized to generate the standard-model gaugino masses for a small mediator mass without breaking the standard-model symmetries.

  16. How to save the WIMP. Global analysis of a dark matter model with two s-channel mediators

    International Nuclear Information System (INIS)

    Duerr, Michael; Kahlhoefer, Felix; Schmidt-Hoberg, Kai; Schwetz, Thomas; Vogl, Stefan

    2016-06-01

    A reliable comparison of different dark matter (DM) searches requires models that satisfy certain consistency requirements like gauge invariance and perturbative unitarity. As a well-motivated example, we study two-mediator DM (2MDM). The model is based on a spontaneously broken U(1)"' gauge symmetry and contains a Majorana DM particle as well as two s-channel mediators, one vector (the Z"') and one scalar (the dark Higgs). We perform a global scan over the parameters of the model assuming that the DM relic density is obtained by thermal freeze-out in the early Universe and imposing a large set of constraints: direct and indirect DM searches, monojet, dijet and dilepton searches at colliders, Higgs observables, electroweak precision tests and perturbative unitarity. We conclude that thermal DM is only allowed either close to an s-channel resonance or if at least one mediator is lighter than the DM particle. In these cases a thermal DM abundance can be obtained although DM couplings to the Standard Model are tiny. Interestingly, we find that vector-mediated DM-nucleon scattering leads to relevant constraints despite the velocity-suppressed cross section, and that indirect detection can be important if DM annihilations into both mediators are kinematically allowed.

  17. Mathematical modeling on T-cell mediated adaptive immunity in primary dengue infections.

    Science.gov (United States)

    Sasmal, Sourav Kumar; Dong, Yueping; Takeuchi, Yasuhiro

    2017-09-21

    At present, dengue is the most common mosquito-borne viral disease in the world, and the global dengue incidence is increasing day by day due to climate changing. Here, we present a mathematical model of dengue viruses (DENVs) dynamics in micro-environment (cellular level) consisting of healthy cells, infected cells, virus particles and T-cell mediated adaptive immunity. We have considered the explicit role of cytokines and antibody in our model. We find that the virus load goes down to zero within 6 days as it is common for DENV infection. From our analysis, we have identified the important model parameters and done the numerical simulation with respect to such important parameters. We have shown that the cytokine mediated virus clearance plays a very important role in dengue dynamics. It can change the dynamical behavior of the system and causes essential extinction of the virus. Finally, we have incorporated the antiviral treatment for dengue in our model and shown that the basic reproduction number is directly proportional to the antiviral treatment effects. Copyright © 2017 Elsevier Ltd. All rights reserved.

  18. Maternal Factors as Moderators or Mediators of PTSD Symptoms in Very Young Children: A Two-Year Prospective Study.

    Science.gov (United States)

    Scheeringa, Michael S; Myers, Leann; Putnam, Frank W; Zeanah, Charles H

    2015-07-01

    Research has suggested that parenting behaviors and other parental factors impact the long-term outcome of children's posttraumatic stress disorder (PTSD) symptoms. In a sample of 62 children between the ages of one and six who experienced life-threatening traumas, PTSD was measured prospectively two years apart. Seven maternal factors were measured in a multi-method, multi-informant design. Both moderation and mediation models, with different theoretical and mechanism implications, were tested. Moderation models were not significant. Mediation models were significant when the mediator variable was maternal symptoms of PTSD or depression (measured at Time 1), self-report of maternal escape/avoidance coping (measured at Time 2), or self-report emotional sensitivity (measured at Time 2). Greater maternal emotional sensitivity was associated with greater Time 2 PTSD symptoms among children. Observational measures of emotional sensitivity as the mediator were not supported. Correlation of parents' and children's symptoms is a robust finding, however caution is warranted in attributing children's PTSD symptoms to insensitive parenting.

  19. Mediators and Metaphorical Analysis: A Phenomenological Study of Florida Family Court Mediators

    Science.gov (United States)

    Storrow, Rebecca A.

    2012-01-01

    Florida family court mediation programs have typically been assessed with quantitative analysis. To understand the complexity of the experience of being a family mediator, it was necessary to explore how mediators practiced through qualitative research. Metaphors have been considered to be representations of mediators' mental models regarding…

  20. The relationship among self-efficacy, negative self-referent cognitions, and social anxiety in children: a multiple mediator model.

    Science.gov (United States)

    Rudy, Brittany M; Davis, Thompson E; Matthews, Russell A

    2012-09-01

    Evidence suggests that general self-efficacy, an individual's beliefs about his global abilities, and social self-efficacy, an individual's beliefs in his ability to navigate social situations, are strongly connected to levels of social anxiety. Negative self-statements, also known as negative self-referent cognitions, have also been linked with levels of social anxiety. Although self-efficacy and negative self-statements have been shown to be important variables in the phenomenology and maintenance of social anxiety in children, they have yet to be examined in conjunction with one another. The purpose of this study was to examine the relationship between negative self-referent cognitions and self-efficacy and to examine both general self-efficacy and social self-efficacy as mediator variables in the relationship between negative self-statements and social anxiety. Results were based on a sample of 126 children ages 11 to 14 years. A significant association between negative self-statements and both general self-efficacy and social self-efficacy was established. Results also indicated that general self-efficacy fully mediated the relationship between negative self-statements and social anxiety; however, contrary to hypotheses, social self-efficacy did not mediate the relationship between negative self-statements and social anxiety. Implications and future recommendations are discussed. Copyright © 2011. Published by Elsevier Ltd.

  1. Social skills training and play group intervention for children with oppositional-defiant disorders/conduct disorder: Mediating mechanisms in a head-to-head comparison.

    Science.gov (United States)

    Katzmann, Josepha; Goertz-Dorten, Anja; Hautmann, Christopher; Doepfner, Manfred

    2018-01-19

    Social-cognitive information processing, social skills, and social interactions are problem-maintaining variables for aggressive behavior in children. We hypothesized that these factors may be possible mediators of the mechanism of change in the child-centered treatment of conduct disorders (CDs). The aim of the present study (Clinical trials.gov Identifier: NCT01406067) was to examine putative mechanisms of change for the decrease in oppositional-defiant behavior resulting from child-centered treatment of patients with oppositional-defiant disorder (ODD) or CD. 91 children (age 6-12 years) with ODD/CD were randomized to receive either social skills training or to a resource activating play group. Mediator analyses were conducted using path analyses. The assumed mediating effects were not significant. However, alternative models with the putative mediators and outcome in reversed positions showed significant indirect effects of the oppositional-defiant symptoms as mediator for the decrease of disturbance of social-information processing, social skills, and social interactions. The proposed model for mechanisms of change could not be confirmed, with the results pointing to a reversed causality. Variables other than those hypothesized must be responsible for mediating the effects of the intervention on child oppositional-defiant behavior. Possible mechanisms of change were discussed.

  2. Variability of concrete properties: experimental characterisation and probabilistic modelling for calcium leaching

    International Nuclear Information System (INIS)

    De Larrard, Th.

    2010-09-01

    Evaluating structures durability requires taking into account the variability of material properties. The thesis has two main aspects: on the one hand, an experimental campaign aimed at quantifying the variability of many indicators of concrete behaviour; on the other hand, a simple numerical model for calcium leaching is developed in order to implement probabilistic methods so as to estimate the lifetime of structures such as those related to radioactive waste disposal. The experimental campaign consisted in following up two real building sites, and quantifying the variability of these indicators, studying their correlation, and characterising the random fields variability for the considered variables (especially the correlation length). To draw any conclusion from the accelerated leaching tests with ammonium nitrate by overcoming the effects of temperature, an inverse analysis tool based on the theory of artificial neural networks was developed. Simple numerical tools are presented to investigate the propagation of variability in durability issues, quantify the influence of this variability on the lifespan of structures and explain the variability of the input parameters of the numerical model and the physical measurable quantities of the material. (author)

  3. A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability.

    Science.gov (United States)

    Barik, Debashis; Ball, David A; Peccoud, Jean; Tyson, John J

    2016-12-01

    The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization) of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally.

  4. A Stochastic Model of the Yeast Cell Cycle Reveals Roles for Feedback Regulation in Limiting Cellular Variability.

    Directory of Open Access Journals (Sweden)

    Debashis Barik

    2016-12-01

    Full Text Available The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally.

  5. A single-level random-effects cross-lagged panel model for longitudinal mediation analysis.

    Science.gov (United States)

    Wu, Wei; Carroll, Ian A; Chen, Po-Yi

    2017-12-06

    Cross-lagged panel models (CLPMs) are widely used to test mediation with longitudinal panel data. One major limitation of the CLPMs is that the model effects are assumed to be fixed across individuals. This assumption is likely to be violated (i.e., the model effects are random across individuals) in practice. When this happens, the CLPMs can potentially yield biased parameter estimates and misleading statistical inferences. This article proposes a model named a random-effects cross-lagged panel model (RE-CLPM) to account for random effects in CLPMs. Simulation studies show that the RE-CLPM outperforms the CLPM in recovering the mean indirect and direct effects in a longitudinal mediation analysis when random effects exist in the population. The performance of the RE-CLPM is robust to a certain degree, even when the random effects are not normally distributed. In addition, the RE-CLPM does not produce harmful results when the model effects are in fact fixed in the population. Implications of the simulation studies and potential directions for future research are discussed.

  6. The Integration of Continuous and Discrete Latent Variable Models: Potential Problems and Promising Opportunities

    Science.gov (United States)

    Bauer, Daniel J.; Curran, Patrick J.

    2004-01-01

    Structural equation mixture modeling (SEMM) integrates continuous and discrete latent variable models. Drawing on prior research on the relationships between continuous and discrete latent variable models, the authors identify 3 conditions that may lead to the estimation of spurious latent classes in SEMM: misspecification of the structural model,…

  7. Personality and job performance: test of the mediating effects of motivation among sales representatives.

    Science.gov (United States)

    Barrick, Murray R; Stewart, Greg L; Piotrowski, Mike

    2002-02-01

    Research shows consistent relations between personality and job performance. In this study the authors develop and test a model of job performance that examines the mediating effects of cognitive-motivational work orientations on the relationships between personality traits and performance in a sales job (N = 164). Covariance structural analyses revealed proximal motivational variables to be influential mechanisms through which distal personality traits affect job performance. Specifically, striving for status and accomplishment mediate the effects of Extraversion and Conscientiousness on ratings of sales performance. Although Agreeableness was related to striving for communion, neither Agreeableness nor communion striving was related to success in this sales job. The importance of the proposed motivational orientations model is discussed.

  8. Gene expression profiles of immune mediators and histopathological findings in animal models of leptospirosis: comparison between susceptible hamsters and resistant mice.

    Science.gov (United States)

    Matsui, Mariko; Rouleau, Vincent; Bruyère-Ostells, Lilian; Goarant, Cyrille

    2011-11-01

    Leptospirosis is a widespread zoonosis characterized by multiple organ failure and variable host susceptibility toward pathogenic Leptospira strains. In this study, we put the role of inflammatory mediators in parallel with bacterial burdens and organ lesions by comparing a susceptible animal model, the hamster, and a resistant one, the Oncins France 1 (OF1) mouse, both infected with virulent Leptospira interrogans serovar Icterohaemorrhagiae strain Verdun. Histological observations evidenced edema, congestion, hemorrhage, and inflammatory infiltration in the organs of hamsters, in contrast to limited changes in mice. Using reverse transcription-quantitative PCR techniques, we showed that the relative Leptospira burden progressively increased in hamster tissues, while a rapid clearance was observed in mouse tissues. The early regulation of the proinflammatory mediators interleukin-1β (IL-1β), IL-6, tumor necrosis factor alpha, and cyclo-oxygenase-2 and the chemokines gamma interferon-inducible protein 10 kDa/CXCL10 and macrophage inflammatory protein-1α/CCL3 in mouse tissues contrasted with their delayed and massive overexpression in hamster tissues. Conversely, the induction of the anti-inflammatory cytokine IL-10 was faster in the resistant than in the susceptible animal model. The role of these cytokines in the pathophysiology of leptospirosis and the implications of their differential regulation in the development of this disease are discussed.

  9. Effects of Teachers' Organizational Justice Perceptions on Intention to Quit: Mediation Role of Organizational Identification

    Science.gov (United States)

    Basar, Ufuk; Sigri, Ünsal

    2015-01-01

    This research aims to discover the effects of teachers' organizational justice perceptions on intention to quit as well as the mediation role of teachers' organizational identification in this process. Interactions between research variables were measured using structural equation models. The sample used comprised teachers working at primary and…

  10. Symptoms of Depression and Anxiety in Adolescents with Sickle Cell Disease: The Role of Intrapersonal Characteristics and Stress Processing Variables

    Science.gov (United States)

    Simon, Katherine; Barakat, Lamia P.; Patterson, Chavis A.; Dampier, Carlton

    2009-01-01

    Sickle cell disease (SCD) complications place patients at risk for poor psychosocial adaptation, including depression and anxiety symptoms. This study aimed to test a mediator model based on the Risk and Resistance model to explore the role of intrapersonal characteristics and stress processing variables in psychosocial functioning. Participants…

  11. Modeling Source Water TOC Using Hydroclimate Variables and Local Polynomial Regression.

    Science.gov (United States)

    Samson, Carleigh C; Rajagopalan, Balaji; Summers, R Scott

    2016-04-19

    To control disinfection byproduct (DBP) formation in drinking water, an understanding of the source water total organic carbon (TOC) concentration variability can be critical. Previously, TOC concentrations in water treatment plant source waters have been modeled using streamflow data. However, the lack of streamflow data or unimpaired flow scenarios makes it difficult to model TOC. In addition, TOC variability under climate change further exacerbates the problem. Here we proposed a modeling approach based on local polynomial regression that uses climate, e.g. temperature, and land surface, e.g., soil moisture, variables as predictors of TOC concentration, obviating the need for streamflow. The local polynomial approach has the ability to capture non-Gaussian and nonlinear features that might be present in the relationships. The utility of the methodology is demonstrated using source water quality and climate data in three case study locations with surface source waters including river and reservoir sources. The models show good predictive skill in general at these locations, with lower skills at locations with the most anthropogenic influences in their streams. Source water TOC predictive models can provide water treatment utilities important information for making treatment decisions for DBP regulation compliance under future climate scenarios.

  12. Search for SUSY in gauge mediated and anomaly mediated supersymmetry breaking models

    International Nuclear Information System (INIS)

    Nunnnemann, Thomas

    2004-01-01

    In this note, recent results on the search for Gauge Mediated Supersymmetry Breaking (GMSB) and Anomaly Mediated Supersymmetry Breaking (AMSB) at the LEP and Tevatron colliders are summarized. We report on DOe's search for GMSB in di-photon events with large missing transverse energy and discuss the sensitivity of similar searches based on future Tevatron integrated luminosities. (orig.)

  13. General resonance mediation

    International Nuclear Information System (INIS)

    McGarrie, Moritz

    2012-07-01

    We extend the framework of general gauge mediation to cases where the mediating fields have a nontrivial spectral function, as might arise from strong dynamics. We demonstrate through examples that this setup describes a broad class of possible models of gauge mediated supersymmetry breaking. A main emphasis is to give general formulas for cross sections for σ(visible → hidden) in these resonance models. We will also give formulas for soft masses, A-terms and demonstrate the framework with a holographic setup.

  14. General resonance mediation

    Energy Technology Data Exchange (ETDEWEB)

    McGarrie, Moritz

    2012-07-15

    We extend the framework of general gauge mediation to cases where the mediating fields have a nontrivial spectral function, as might arise from strong dynamics. We demonstrate through examples that this setup describes a broad class of possible models of gauge mediated supersymmetry breaking. A main emphasis is to give general formulas for cross sections for {sigma}(visible {yields} hidden) in these resonance models. We will also give formulas for soft masses, A-terms and demonstrate the framework with a holographic setup.

  15. The link between perceived human resource management practices, engagement and employee behaviour : A moderated mediation model

    NARCIS (Netherlands)

    Alfes, K.; Shantz, A.D.; Truss, C.; Soane, E.C.

    2013-01-01

    This study contributes to our understanding of the mediating and moderating processes through which human resource management (HRM) practices are linked with behavioural outcomes. We developed and tested a moderated mediation model linking perceived HRM practices to organisational citizenship

  16. Linking Inflammation, Cardiorespiratory Variability, and Neural Control in Acute Inflammation via Computational Modeling.

    Science.gov (United States)

    Dick, Thomas E; Molkov, Yaroslav I; Nieman, Gary; Hsieh, Yee-Hsee; Jacono, Frank J; Doyle, John; Scheff, Jeremy D; Calvano, Steve E; Androulakis, Ioannis P; An, Gary; Vodovotz, Yoram

    2012-01-01

    Acute inflammation leads to organ failure by engaging catastrophic feedback loops in which stressed tissue evokes an inflammatory response and, in turn, inflammation damages tissue. Manifestations of this maladaptive inflammatory response include cardio-respiratory dysfunction that may be reflected in reduced heart rate and ventilatory pattern variabilities. We have developed signal-processing algorithms that quantify non-linear deterministic characteristics of variability in biologic signals. Now, coalescing under the aegis of the NIH Computational Biology Program and the Society for Complexity in Acute Illness, two research teams performed iterative experiments and computational modeling on inflammation and cardio-pulmonary dysfunction in sepsis as well as on neural control of respiration and ventilatory pattern variability. These teams, with additional collaborators, have recently formed a multi-institutional, interdisciplinary consortium, whose goal is to delineate the fundamental interrelationship between the inflammatory response and physiologic variability. Multi-scale mathematical modeling and complementary physiological experiments will provide insight into autonomic neural mechanisms that may modulate the inflammatory response to sepsis and simultaneously reduce heart rate and ventilatory pattern variabilities associated with sepsis. This approach integrates computational models of neural control of breathing and cardio-respiratory coupling with models that combine inflammation, cardiovascular function, and heart rate variability. The resulting integrated model will provide mechanistic explanations for the phenomena of respiratory sinus-arrhythmia and cardio-ventilatory coupling observed under normal conditions, and the loss of these properties during sepsis. This approach holds the potential of modeling cross-scale physiological interactions to improve both basic knowledge and clinical management of acute inflammatory diseases such as sepsis and trauma.

  17. The role of co-parenting alliance as a mediator between trait anxiety, family system maladjustment, and parenting stress in a sample of non-clinical Italian parents.

    Science.gov (United States)

    Delvecchio, Elisa; Sciandra, Andrea; Finos, Livio; Mazzeschi, Claudia; Riso, Daniela Di

    2015-01-01

    This study investigated the role of co-parenting alliance in mediating the influence of parents' trait anxiety on family system maladjustment and parenting stress. A sample of 1606 Italian parents (803 mothers and 803 fathers) of children aged one to 13 years completed measures of trait anxiety (State Trait Anxiety Inventory-Y), co-parenting alliance (Parenting Alliance Measure), family system maladjustment (Family Assessment Measure-III), and parenting stress (Parenting Stress Inventory-Short Form). These variables were investigated together comparing two structural equations model-fitting including both partners. A model for both mothers and fathers was empirically devised as a series of associations between parent trait anxiety (independent variable), family system maladjustment and parenting stress (dependent variables), mediated by co-parenting alliance, with the insertion of cross predictions between mothers and fathers and correlations between dependent variables for both parents. Results indicated that the relation between mothers and fathers' trait anxiety, family system maladjustment and parenting stress was mediated by the level of co-parenting alliance. Understanding the role of couples' co-parenting alliance could be useful during the family assessment and/or treatment, since it is an efficient and effective tool to improve the family system maladjustment and stress.

  18. An Atmospheric Variability Model for Venus Aerobraking Missions

    Science.gov (United States)

    Tolson, Robert T.; Prince, Jill L. H.; Konopliv, Alexander A.

    2013-01-01

    Aerobraking has proven to be an enabling technology for planetary missions to Mars and has been proposed to enable low cost missions to Venus. Aerobraking saves a significant amount of propulsion fuel mass by exploiting atmospheric drag to reduce the eccentricity of the initial orbit. The solar arrays have been used as the primary drag surface and only minor modifications have been made in the vehicle design to accommodate the relatively modest aerothermal loads. However, if atmospheric density is highly variable from orbit to orbit, the mission must either accept higher aerothermal risk, a slower pace for aerobraking, or a tighter corridor likely with increased propulsive cost. Hence, knowledge of atmospheric variability is of great interest for the design of aerobraking missions. The first planetary aerobraking was at Venus during the Magellan mission. After the primary Magellan science mission was completed, aerobraking was used to provide a more circular orbit to enhance gravity field recovery. Magellan aerobraking took place between local solar times of 1100 and 1800 hrs, and it was found that the Venusian atmospheric density during the aerobraking phase had less than 10% 1 sigma orbit to orbit variability. On the other hand, at some latitudes and seasons, Martian variability can be as high as 40% 1 sigmaFrom both the MGN and PVO mission it was known that the atmosphere, above aerobraking altitudes, showed greater variability at night, but this variability was never quantified in a systematic manner. This paper proposes a model for atmospheric variability that can be used for aerobraking mission design until more complete data sets become available.

  19. Appraisal and Reliability of Variable Engagement Model Prediction ...

    African Journals Online (AJOL)

    The variable engagement model based on the stress - crack opening displacement relationship and, which describes the behaviour of randomly oriented steel fibres composite subjected to uniaxial tension has been evaluated so as to determine the safety indices associated when the fibres are subjected to pullout and with ...

  20. Testing a Mediational Model of Communication Among Medical Staff and Families of Cancer Patients

    Science.gov (United States)

    Gionta, Dana A.; Harlow, Lisa L.; Loitman, Jane E.; Leeman, Joanne M.

    2005-01-01

    Three structural equation models of communication between family members and medical staff were examined to understand relations among staff accessibility, inhibitory family attitudes, getting communication needs met, perceived stress, and satisfaction with communication. Compared to full and direct models, a mediational model fit best in which…

  1. Structural Equation Model of Smartphone Addiction Based on Adult Attachment Theory: Mediating Effects of Loneliness and Depression.

    Science.gov (United States)

    Kim, EunYoung; Cho, Inhyo; Kim, Eun Joo

    2017-06-01

    This study investigated the mediating effects of loneliness and depression on the relationship between adult attachment and smartphone addiction in university students. A total of 200 university students participated in this study. The data was analysed using descriptive statistics, correlation analysis, and structural equation modeling. There were significant positive relationships between attachment anxiety, loneliness, depression, and smartphone addiction. However, attachment anxiety was not significantly correlated with smartphone addiction. The results also showed that loneliness did not directly mediate between attachment anxiety and smartphone addiction. In addition, loneliness and depression serially mediated between attachment anxiety and smartphone addiction. The results suggest there are mediating effects of loneliness and depression in the relationship between attachment anxiety and smartphone addiction. The hypothesized model was found to be a suitable model for predicting smartphone addiction among university students. Future study is required to find a causal path to prevent smartphone addiction among university students. Copyright © 2017. Published by Elsevier B.V.

  2. Prediction of childhood ADHD symptoms to quality of life in young adults: adult ADHD and anxiety/depression as mediators.

    Science.gov (United States)

    Yang, Hui-Nien; Tai, Yueh-Ming; Yang, Li-Kuang; Gau, Susan Shur-Fen

    2013-10-01

    Childhood attention-deficit/hyperactivity disorder (ADHD) symptoms may persist, co-occur with anxiety and depression (ANX/DEP), and influence quality of life (QoL) in later life. However, the information about whether these persistent ADHD and ANX/DEP mediate the influence of childhood ADHD on adverse QoL in adulthood is lacking. This study aimed to determine whether adult ADHD symptoms and/or ANX/DEP mediated the association between childhood ADHD and QoL. We assessed 1382 young men aged 19-30 years in Taiwan using self-administered questionnaires for retrospective recall of ADHD symptoms at ages 6-12, and assessment of current ADHD and ANX/DEP symptoms, and QoL. We conducted mediation analyses and compared the values of mediation ratio (PM) by adding mediators (adult ADHD and ANX/DEP), individually and simultaneously into a regression model with childhood ADHD as an independent variable and QoL as a dependent variable. Our results showed that both adult ADHD and ANX/DEP symptoms significantly mediated the association between childhood ADHD and QoL (PM=0.71 for ANX/DEP, PM=0.78 for adult ADHD symptoms, and PM=0.91 for both). The significance of negative correlations between childhood ADHD and four domains of adult QoL disappeared after adding these two mediators in the model. Our findings suggested that the strong relationship between childhood ADHD and adult life quality can be explained by the presence of persistent ADHD symptoms and co-occurring ANX/DEP. These two mediators are recommended to be included in the assessment and intervention for ADHD to offset the potential adverse life quality outcome in ADHD. Copyright © 2013 Elsevier Ltd. All rights reserved.

  3. Conditional Mediation of Absorptive Capacity and Environment in International Entrepreneurial Orientation of Family Businesses.

    Science.gov (United States)

    Hernández-Perlines, Felipe; Xu, Wenkai

    2018-01-01

    This study analyzes the effect of conditional mediation of environment-absorptive capacity in international entrepreneurial orientation of family businesses. Results involve data from 218 Spanish family businesses, analyzed with SmartPLS 3.2.7 software. This paper presents a relevant contribution both to the academic field and the performance of family firms, helping to understand the process of transforming international entrepreneurial orientation into a better international performance through absorptive capacity while family businesses invest their efforts in aligning international entrepreneurial orientation and absorptive capacity with international results, bearing in mind the positive moderator effect of environment. The most relevant contribution of this work is to integrate in the same model the mediating effect of the absorption capacity and the moderating effect of the environment: the effect of the international entrepreneurial orientation on the international performance of family businesses improves with the mediation of the absorptive capacity (the variability of international performance goes from 32.5 to 40.6%) and the moderation of the environment (to variability of international performance goes from 40.6 to 45.3%).

  4. Organizational climate, occupational stress, and employee mental health: mediating effects of organizational efficiency.

    Science.gov (United States)

    Arnetz, Bengt B; Lucas, Todd; Arnetz, Judith E

    2011-01-01

    To determine whether the relationship between organizational climate and employee mental health is consistent (ie, invariant) or differs across four large hospitals, and whether organizational efficiency mediates this relationship. Participants (total N = 5316) completed validated measures of organizational climate variables (social climate, participatory management, goal clarity, and performance feedback), organizational efficiency, occupational stress, and mental health. Path analysis best supported a model in which organizational efficiency partially mediated relationships between organizational climate, occupational stress, and mental health. Focusing on improving both the psychosocial work environment and organizational efficiency might contribute to decreased employee stress, improved mental well-being, and organizational performance.

  5. Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part II: climate variability

    Science.gov (United States)

    Rackow, T.; Goessling, H. F.; Jung, T.; Sidorenko, D.; Semmler, T.; Barbi, D.; Handorf, D.

    2018-04-01

    This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse 1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to 0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (`hiatus' analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent

  6. Mediating role of work engagement in the relationship between job resources and personal resources with turnover intention among female nurses.

    Science.gov (United States)

    Shahpouri, Samira; Namdari, Kourosh; Abedi, Ahmad

    2016-05-01

    One of the latest models proposed with regard to work engagement is the detailed model put forward by Bakker and Demerouti (2007). The present study aims at investigating the effect of job resources and personal resources on turnover intention with the mediator role of work engagement among female nurses at Isfahan Alzahra Hospital. In the current study, job and personal resources were considered as the predictors of job turnover and work engagement was considered as the mediator variable among predictive and criterion variables. The data of the present study were collected from 208 female nurses who were selected by systematic random sampling. As for the analysis of the collected data, structural equations model, normal distribution method, and Bootstrap method in Macro, Preacher and Hayes, (2004) program were deployed. The findings showed that the personal resources affect the turnover intention both directly and indirectly (through work engagement); however, job resources are just associated with turnover intention with the mediating role of work engagement. The results of the study have important implications for organizations' managers about improving work engagement. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. Adolescent overweight, obesity and chronic disease-related health practices: mediation by body image.

    Science.gov (United States)

    Farhat, Tilda; Iannotti, Ronald J; Caccavale, Laura J

    2014-01-01

    To examine whether body image mediates the association between overweight/obesity and chronic disease-related health practices (CDRHP), including lack of physical activity (PA), infrequent breakfast consumption (IBC), screen-based media use (SBM), and smoking. The 2006 Health Behaviors in School-Age Children survey was administered to a nationally representative sample of US students (n = 8,028) in grades 6-10 (mean age = 14.3 years). Outcome variables included self-reported measures of PA, SBM, IBC, and smoking. Body image was assessed with 5 items from the Body Investment Scale (α = 0.87) asking for agreement/disagreement with statements about one's body. Stratifying on gender, an initial regression model estimated the association between overweight/obesity and CDRHP. Mediation models that included body image were then compared to the initial model to determine the role of body image in the relationship between overweight/obesity and CDRHP. Among boys, body image mediated the relationships of overweight/obesity with SBM, and of obesity with IBC. Among girls, it mediated the relationships of obesity with PA, IBC, and smoking, and of overweight with SBM. As the prevalence of overweight/obesity among adolescent boys and girls remains high, efforts to improve their body image could result in less frequent engagement in CDRHP. © 2013 S. Karger GmbH, Freiburg.

  8. Adolescent Overweight, Obesity and Chronic Disease-Related Health Practices: Mediation by Body Image

    Directory of Open Access Journals (Sweden)

    Tilda Farhat

    2013-12-01

    Full Text Available Background/Aims: To examine whether body image mediates the association between overweight/obesity and chronic disease-related health practices (CDRHP, including lack of physical activity (PA, infrequent breakfast consumption (IBC, screen-based media use (SBM, and smoking. Methods: The 2006 Health Behaviors in School-Age Children survey was administered to a nationally representative sample of US students (n = 8,028 in grades 6-10 (mean age = 14.3 years. Outcome variables included self-reported measures of PA, SBM, IBC, and smoking. Body image was assessed with 5 items from the Body Investment Scale (α = 0.87 asking for agreement/disagreement with statements about one's body. Stratifying on gender, an initial regression model estimated the association between overweight/obesity and CDRHP. Mediation models that included body image were then compared to the initial model to determine the role of body image in the relationship between overweight/obesity and CDRHP. Results: Among boys, body image mediated the relationships of overweight/obesity with SBM, and of obesity with IBC. Among girls, it mediated the relationships of obesity with PA, IBC, and smoking, and of overweight with SBM. Conclusion: As the prevalence of overweight/obesity among adolescent boys and girls remains high, efforts to improve their body image could result in less frequent engagement in CDRHP.

  9. Viscous cosmological models with a variable cosmological term ...

    African Journals Online (AJOL)

    Einstein's field equations for a Friedmann-Lamaitre Robertson-Walker universe filled with a dissipative fluid with a variable cosmological term L described by full Israel-Stewart theory are considered. General solutions to the field equations for the flat case have been obtained. The solution corresponds to the dust free model ...

  10. Automatic Welding Control Using a State Variable Model.

    Science.gov (United States)

    1979-06-01

    A-A10 610 NAVEAL POSTGRADUATE SCH4O.M CEAY CA0/ 13/ SAUTOMATIC WELDING CONTROL USING A STATE VARIABLE MODEL.W()JUN 79 W V "my UNCLASSIFIED...taverse Drive Unit // Jbint Path /Fixed Track 34 (servomotor positioning). Additional controls of heave (vertical), roll (angular rotation about the

  11. Mediating effects of emotional exhaustion on the relationship between job demand–control model and mental health.

    Science.gov (United States)

    Huang, Yu-Hwa; Du, Pey-Ian; Chen, Chin-Hui; Yang, Chin-Ann; Huang, Ing-Chung

    2011-04-01

    This study attempted to investigate the role of emotional exhaustion as a mediator on the relationship between job demands-control (JDC) model and mental health. Three-wave data from 297 employees were collected. The results showed that job demands were positively related to emotional exhaustion, and increasing job demands will increase the level of emotional exhaustion. Job control was negatively associated with emotional exhaustion; therefore, increasing job control will decrease the level of emotional exhaustion. Emotional exhaustion was negatively related to mental health. Emotional exhaustion fully mediated the relationship between job demands and mental health, and partially mediated the positive relationship between job control and mental health. In addition, job control was positively associated with mental health directly. The remarkable finding of the present study was that emotional exhaustion served as the key mediator between the JDC model and mental health. Theoretical and managerial implications and limitations were discussed.

  12. On the ""early-time"" evolution of variables relevant to turbulence models for the Rayleigh-Taylor instability

    Energy Technology Data Exchange (ETDEWEB)

    Rollin, Bertrand [Los Alamos National Laboratory; Andrews, Malcolm J [Los Alamos National Laboratory

    2010-01-01

    We present our progress toward setting initial conditions in variable density turbulence models. In particular, we concentrate our efforts on the BHR turbulence model for turbulent Rayleigh-Taylor instability. Our approach is to predict profiles of relevant variables before fully turbulent regime and use them as initial conditions for the turbulence model. We use an idealized model of mixing between two interpenetrating fluids to define the initial profiles for the turbulence model variables. Velocities and volume fractions used in the idealized mixing model are obtained respectively from a set of ordinary differential equations modeling the growth of the Rayleigh-Taylor instability and from an idealization of the density profile in the mixing layer. A comparison between predicted profiles for the turbulence model variables and profiles of the variables obtained from low Atwood number three dimensional simulations show reasonable agreement.

  13. Sensitivity Modeling of On-chip Capacitances : Parasitics Extraction for Manufacturing Variability

    NARCIS (Netherlands)

    Bi, Y.

    2012-01-01

    With each new generation of IC process technologies, the impact of manufacturing variability is increasing. As such, design optimality is harder and harder to achieve and effective modeling tools and methods are needed to capture the effects of variability in such a way that it is understandable and

  14. Emotional Exhaustion and Job Satisfaction in Airport Security Officers − Work−Family Conflict as Mediator in the Job Demands–Resources Model

    Directory of Open Access Journals (Sweden)

    Sophie eBaeriswyl

    2016-05-01

    Full Text Available The growing threat of terrorism has increased the importance of aviation security and the work of airport security officers (screeners. Nonetheless, airport security research has yet to focus on emotional exhaustion and job satisfaction as major determinants of screeners’ job performance. The present study bridges this research gap by applying the job demands–resources (JD−R model and using work–family conflict (WFC as an intervening variable to study relationships between work characteristics (workload and supervisor support, emotional exhaustion, and job satisfaction in 1,127 screeners at a European airport. Results of structural equation modeling revealed that (a supervisor support as a major job resource predicted job satisfaction among screeners; (b workload as a major job demand predicted their emotional exhaustion; and (c WFC proved to be a promising extension to the JD–R model that partially mediated the impact of supervisor support and workload on job satisfaction and emotional exhaustion. Theoretical and practical implications are discussed.

  15. Emotional Exhaustion and Job Satisfaction in Airport Security Officers – Work–Family Conflict as Mediator in the Job Demands–Resources Model

    Science.gov (United States)

    Baeriswyl, Sophie; Krause, Andreas; Schwaninger, Adrian

    2016-01-01

    The growing threat of terrorism has increased the importance of aviation security and the work of airport security officers (screeners). Nonetheless, airport security research has yet to focus on emotional exhaustion and job satisfaction as major determinants of screeners’ job performance. The present study bridges this research gap by applying the job demands–resources (JD–R) model and using work–family conflict (WFC) as an intervening variable to study relationships between work characteristics (workload and supervisor support), emotional exhaustion, and job satisfaction in 1,127 screeners at a European airport. Results of structural equation modeling revealed that (a) supervisor support as a major job resource predicted job satisfaction among screeners; (b) workload as a major job demand predicted their emotional exhaustion; and (c) WFC proved to be a promising extension to the JD–R model that partially mediated the impact of supervisor support and workload on job satisfaction and emotional exhaustion. Theoretical and practical implications are discussed. PMID:27242581

  16. Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

    Science.gov (United States)

    Wei, Jiangfeng; Dirmeyer, Paul A.; Yang, Zong-Liang; Chen, Haishan

    2017-10-01

    Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.

  17. A Rabbit Model for Testing Helper-Dependent Adenovirus-Mediated Gene Therapy for Vein Graft Atherosclerosis

    Directory of Open Access Journals (Sweden)

    Lianxiang Bi

    2017-12-01

    Full Text Available Coronary artery bypass vein grafts are a mainstay of therapy for human atherosclerosis. Unfortunately, the long-term patency of vein grafts is limited by accelerated atherosclerosis. Gene therapy, directed at the vein graft wall, is a promising approach for preventing vein graft atherosclerosis. Because helper-dependent adenovirus (HDAd efficiently transduces grafted veins and confers long-term transgene expression, HDAd is an excellent candidate for delivery of vein graft-targeted gene therapy. We developed a model of vein graft atherosclerosis in fat-fed rabbits and demonstrated long-term (≥20 weeks persistence of HDAd genomes after graft transduction. This model enables quantitation of vein graft hemodynamics, wall structure, lipid accumulation, cellularity, vector persistence, and inflammatory markers on a single graft. Time-course experiments identified 12 weeks after transduction as an optimal time to measure efficacy of gene therapy on the critical variables of lipid and macrophage accumulation. We also used chow-fed rabbits to test whether HDAd infusion in vein grafts promotes intimal growth and inflammation. HDAd did not increase intimal growth, but had moderate—yet significant—pro-inflammatory effects. The vein graft atherosclerosis model will be useful for testing HDAd-mediated gene therapy; however, pro-inflammatory effects of HdAd remain a concern in developing HDAd as a therapy for vein graft disease.

  18. Using hierarchical linear growth models to evaluate protective mechanisms that mediate science achievement

    Science.gov (United States)

    von Secker, Clare Elaine

    The study of students at risk is a major topic of science education policy and discussion. Much research has focused on describing conditions and problems associated with the statistical risk of low science achievement among individuals who are members of groups characterized by problems such as poverty and social disadvantage. But outcomes attributed to these factors do not explain the nature and extent of mechanisms that account for differences in performance among individuals at risk. There is ample theoretical and empirical evidence that demographic differences should be conceptualized as social contexts, or collections of variables, that alter the psychological significance and social demands of life events, and affect subsequent relationships between risk and resilience. The hierarchical linear growth models used in this dissertation provide greater specification of the role of social context and the protective effects of attitude, expectations, parenting practices, peer influences, and learning opportunities on science achievement. While the individual influences of these protective factors on science achievement were small, their cumulative effect was substantial. Meta-analysis conducted on the effects associated with psychological and environmental processes that mediate risk mechanisms in sixteen social contexts revealed twenty-two significant differences between groups of students. Positive attitudes, high expectations, and more intense science course-taking had positive effects on achievement of all students, although these factors were not equally protective in all social contexts. In general, effects associated with authoritative parenting and peer influences were negative, regardless of social context. An evaluation comparing the performance and stability of hierarchical linear growth models with traditional repeated measures models is included as well.

  19. On the Use of Variability Operations in the V-Modell XT Software Process Line

    DEFF Research Database (Denmark)

    Kuhrmann, Marco; Méndez Fernández, Daniel; Ternité, Thomas

    2016-01-01

    . In this article, we present a study on the feasibility of variability operations to support the development of software process lines in the context of the V-Modell XT. We analyze which variability operations are defined and practically used. We provide an initial catalog of variability operations...... as an improvement proposal for other process models. Our findings show that 69 variability operation types are defined across several metamodel versions of which, however, 25 remain unused. The found variability operations allow for systematically modifying the content of process model elements and the process......Software process lines provide a systematic approach to develop and manage software processes. It defines a reference process containing general process assets, whereas a well-defined customization approach allows process engineers to create new process variants, e.g., by extending or modifying...

  20. Organizational climate and self-efficacy as predictors of staff strain in caring for dementia residents: A mediation model.

    Science.gov (United States)

    Karantzas, Gery C; McCabe, Marita P; Mellor, David; Von Treuer, Kathryn; Davison, Tanya E; O'Connor, Daniel; Haselden, Rachel; Konis, Anastasia

    2016-01-01

    To date, no research has investigated how the organizational climate of aged care influences the self-efficacy of staff in caring for residents with dementia, or, how self-efficacy is associated with the strain experienced by staff. This study sought to investigate the extent to which the self-efficacy of aged care staff mediates the association between organizational climate variables (such as autonomy, trusting and supportive workplace relations, and the recognition of competence and ability, and perceptions of workplace pressure) and staff strain. A cross-sectional survey design was implemented in which 255 residential aged care staff recruited across aged care facilities in Melbourne, Australia. Staff completed self-report measures of organizational climate, self-efficacy, and strains in caring for residents with dementia. Indirect effects analyses using bootstrapping indicated that self-efficacy of staff mediated the association between the organizational climate variables of autonomy, trust, support, pressure, and staff strain. The findings of this study emphasize that the aged care sector needs to target organizational climate variables that enhance the self-efficacy of staff, and that this in turn, can help ameliorate the strain experienced by staff caring for residents experiencing dementia. Copyright © 2016. Published by Elsevier Ireland Ltd.

  1. A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

    Energy Technology Data Exchange (ETDEWEB)

    Ghasemi, Jahan B.; Zolfonoun, Ehsan [Toosi University of Technology, Tehran (Korea, Republic of)

    2012-05-15

    Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.

  2. A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

    International Nuclear Information System (INIS)

    Ghasemi, Jahan B.; Zolfonoun, Ehsan

    2012-01-01

    Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms

  3. Modelling the Spatial Isotope Variability of Precipitation in Syria

    Energy Technology Data Exchange (ETDEWEB)

    Kattan, Z.; Kattaa, B. [Department of Geology, Atomic Energy Commission of Syria (AECS), Damascus (Syrian Arab Republic)

    2013-07-15

    Attempts were made to model the spatial variability of environmental isotope ({sup 18}O, {sup 2}H and {sup 3}H) compositions of precipitation in syria. Rainfall samples periodically collected on a monthly basis from 16 different stations were used for processing and demonstrating the spatial distributions of these isotopes, together with those of deuterium excess (d) values. Mathematically, the modelling process was based on applying simple polynomial models that take into consideration the effects of major geographic factors (Lon.E., Lat.N., and altitude). The modelling results of spatial distribution of stable isotopes ({sup 18}O and {sup 2}H) were generally good, as shown from the high correlation coefficients (R{sup 2} = 0.7-0.8), calculated between the observed and predicted values. In the case of deuterium excess and tritium distributions, the results were most likely approximates (R{sup 2} = 0.5-0.6). Improving the simulation of spatial isotope variability probably requires the incorporation of other local meteorological factors, such as relative air humidity, precipitation amount and vapour pressure, which are supposed to play an important role in such an arid country. (author)

  4. Simple model for crop photosynthesis in terms of weather variables ...

    African Journals Online (AJOL)

    A theoretical mathematical model for describing crop photosynthetic rate in terms of the weather variables and crop characteristics is proposed. The model utilizes a series of efficiency parameters, each of which reflect the fraction of possible photosynthetic rate permitted by the different weather elements or crop architecture.

  5. Model for expressing leaf photosynthesis in terms of weather variables

    African Journals Online (AJOL)

    A theoretical mathematical model for describing photosynthesis in individual leaves in terms of weather variables is proposed. The model utilizes a series of efficiency parameters, each of which reflect the fraction of potential photosynthetic rate permitted by the different environmental elements. These parameters are useful ...

  6. Gaugino-assisted anomaly mediation

    International Nuclear Information System (INIS)

    Kribs, Graham D.

    2001-01-01

    I present a model of supersymmetry breaking mediated through a small extra dimension. Standard model matter multiplets and a supersymmetry-breaking (or 'hidden') sector are confined to opposite four-dimensional boundaries while gauge multiplets live in the bulk. The hidden sector does not contain a singlet and the dominant contribution to gaugino masses is via anomaly-mediated supersymmetry breaking. Scalar masses get contributions from both anomaly mediation and a tiny hard breaking of supersymmetry by operators on the hidden-sector boundary. These operators contribute to scalar masses at one loop and in most of parameter space, their contribution dominates. Thus it is easy to make all squared scalar masses positive. As no additional fields or symmetries are required below the Planck scale, this is among the simplest working models of anomaly mediation. The gaugino spectrum is left untouched and the phenomenology of the model is roughly similar to anomaly mediated supersymmetry breaking with a universal scalar mass added. Finally, the main differences in the spectrum between this model and other approaches are identified. This talk is based on work [1] done in collaboration with David E. Kaplan