Resilience,Leadership and Work Engagement: The Mediating Role of Positive Affect

This study examines the influence of resilience and transformational leadership on work engagement, and it investigates the mediating effect of positive affect. A total of 422 employees at a large IT company participated the survey. Participants completed established measures of resilience, transformational leadership, positive affect, and work engagement. The results indicate that resilience and transformational leadership are positively related to work engagement. Structural equation modeling analysis shows that positive affect partially mediates the relationships between resilience, transformational leadership, and work engagement. Theoretical contributions, practical implications, and future research directions are discussed.     

Zur Bedeutung von Faultlines als Grenzen bei der Teamarbeit

This report focuses on the divisions within and between teams. Such research is often associated with the phenomenon of “diversity”. Empirical evidence regarding the effects of diversity on teamwork is inconsistent, partly due to methodological limitations. We propose to use the concept of “faultlines” as hypothetical lines that divide teams into homogenous subgroups. Measuring faultlines as an objective indicator of team composition represents an innovative method for integrating several diversity attributes (e.?g., age, gender, and ethnicity). We provide an overview of the current research on faultlines and show detrimental effects of faultlines on team performance. Additionally, we present the results of two studies from the automotive industry, focusing on the relation between faultlines and organizational outcomes such as employee health, team performance and team identification. Finally, we conclude that the analysis of objective faultlines offers relevant implications for research and practice. Future research should also consider the role of subjectively experienced faultlines.     

MIMCA: multiple imputation for categorical variables with multiple correspondence analysis

We propose a multiple imputation method to deal with incomplete categorical data. This method imputes the missing entries using the principal component method dedicated to categorical data: multiple correspondence analysis (MCA). The uncertainty concerning the parameters of the imputation model is reflected using a non-parametric bootstrap. Multiple imputation using MCA (MIMCA) requires estimating a small number of parameters due to the dimensionality reduction property of MCA. It allows the user to impute a large range of data sets. In particular, a high number of categories per variable, a high number of variables or a small number of individuals are not an issue for MIMCA. Through a simulation study based on real data sets, the method is assessed and compared to the reference methods (multiple imputation using the loglinear model, multiple imputation by logistic regressions) as well to the latest works on the topic (multiple imputation by random forests or by the Dirichlet process mixture of products of multinomial distributions model). The proposed method provides a good point estimate of the parameters of the analysis model considered, such as the coefficients of a main effects logistic regression model, and a reliable estimate of the variability of the estimators. In addition, MIMCA has the great advantage that it is substantially less time consuming on data sets of high dimensions than the other multiple imputation methods.     

The impact of child support on child health

The broad goals of child support policy are to keep children in single-parent families out of poverty and to make sure that their material needs are met. One potentially important, but relatively understudied, set of measures of child well-being are health outcomes. A fixed-effects analysis of data from the Child and Young Adult file of the 1979 National Longitudinal Survey of Youth shows that, conditional upon receipt of some amount of child support, higher payment levels are associated with significantly greater odds of having private health insurance coverage and significantly lower odds of poor or declining health status. These effects persist even after controlling for other factors that are likely to be correlated with child support payments, including total family income and paternal visitation patterns.     

A method for choosing the smoothing parameter in a semi-parametric model for detecting change-points in blood flow

In a smoothing spline model with unknown change-points, the choice of the smoothing parameter strongly influences the estimation of the change-point locations and the function at the change-points. In a tumor biology example, where change-points in blood flow in response to treatment were of interest, choosing the smoothing parameter based on minimizing generalized cross-validation (GCV) gave unsatisfactory estimates of the change-points. We propose a new method, aGCV, that re-weights the residual sum of squares and generalized degrees of freedom terms from GCV. The weight is chosen to maximize the decrease in the generalized degrees of freedom as a function of the weight value, while simultaneously minimizing aGCV as a function of the smoothing parameter and the change-points. Compared with GCV, simulation studies suggest that the aGCV method yields improved estimates of the change-point and the value of the function at the change-point.     

《唐摭言》成书时间考

唐五代著名的笔记小说《唐摭言》专述有唐一代之科举之人事,有丰富的史料价值。但此书成书时间历来所论不一,本文试以《唐摭言》文本为据,在有关前人论述的基础上再详加考述,初步推定为南汉大有初或大有中王定保任宁远节度使期间所撰。     

The Relation Between Therapeutic Alliance and Treatment Motivation in Residential Youth Care: A Cross-Lagged Panel Analysis

This study investigated the longitudinal relation between therapeutic alliance and treatment motivation in a sample of 174 adolescents receiving residential treatment in the Netherlands. Structural equation modeling with a cross-lagged panel design was used to examine the relation between therapeutic alliance and treatment motivation up to 9 months of treatment. Results revealed that autoregressive associations between initial therapeutic alliance and alliance at subsequent time points were significant, whereas for treatment motivation a significant association was found after 6 months, but not after 9 months. Results also showed that a higher level of therapeutic alliance after 3 months was predictive of a higher level of treatment motivation after 6 months. Furthermore, a higher level of therapeutic alliance after 6 months was predictive of a higher level of treatment motivation after 9 months. Implications for research and clinical practice are discussed.