Generalized additive models with unknown link function including variable selection

The generalized additive model is a well established and strong tool that allows modelling smooth effects of predictors on the response. However, if the link function, which is typically chosen as the canonical link, is misspecified, estimates can be biased. A procedure is proposed that simultaneously estimates the form of the link function and the unknown form of the predictor functions including selection of predictors. The procedure is based on boosting methodology, which obtains estimates by using a sequence of weak learners. It strongly dominates fitting procedures that are unable to modify a given link function if the true link function deviates from the fixed function. The performance of the procedure is shown in simulation studies and illustrated by real world examples.     

Linearizable special cases of the QAP

We consider special cases of the quadratic assignment problem (QAP) that are linearizable in the sense of Bookhold. We provide combinatorial characterizations of the linearizable instances of the weighted feedback arc set QAP, and of the linearizable instances of the traveling salesman QAP. As a by-product, this yields a new well-solvable special case of the weighted feedback arc set problem.     

The Travelling Salesman Problem on Permuted Monge Matrices

We consider traveling salesman problems (TSPs) with a permuted Monge matrix as cost matrix where the associated patching graph has a specially simple structure: a multistar, a multitree or a planar graph. In the case of multistars, we give a complete, concise and simplified presentation of Gaikov's theory. These results are then used for designing an O(m3 + mn) algorithm in the case of multitrees, where n is the number of cities and m is the number of subtours in an optimal assignment. Moreover we show that for planar patching graphs, the problem of finding an optimal subtour patching remains NP-complete.     

Beratung virtueller Teams im interkulturellen Kontext – ein Bericht aus der Praxis

Tasks are nowadays increasingly assigned to teams composed of members from different cultures who have to work together regardless of country borders or time zones. This causes special challenges for all parties involved in such work settings. Consultancy has accordingly to face the resulting increase of complexity: within the scope of an intercultural consulting process it becomes vital to take into consideration the often postulated focus on both differences and commonalities as well as to consider the dynamics within team processes. This article tries to reflect our work with “virtual teams” which consist of members having different cultures. We try to combine popular intercultural models with a systemic-constructivistic approach as well as with knowledge about group dynamics in order to make sure that a productive outcome is possible in a consulting process. In doing so we work on three levels: individual reflection with the participants’ own culture which is then combined with those of the other team members and then finally the group’s specific team culture is addressed and discussed. At the end of the article we summarize implications for consulting and management when working with virtual teams in an intercultural setting.     

Introduction to stochastic actor-based models for network dynamics

Stochastic actor-based models are models for network dynamics that can represent a wide variety of influences on network change, and allow to estimate parameters expressing such influences, and test corresponding hypotheses. The nodes in the network represent social actors, and the collection of ties represents a social relation. The assumptions posit that the network evolves as a stochastic process ‘driven by the actors’, i.e., the model lends itself especially for representing theories about how actors change their outgoing ties. The probabilities of tie changes are in part endogenously determined, i.e., as a function of the current network structure itself, and in part exogenously, as a function of characteristics of the nodes (‘actor covariates’) and of characteristics of pairs of nodes (‘dyadic covariates’). In an extended form, stochastic actor-based models can be used to analyze longitudinal data on social networks jointly with changing attributes of the actors: dynamics of networks and behavior.     

Regression Analysis of Multivariate Binary Response Variables Using Rasch-Type Models and Finite-Mixture Methods

A model is considered for the regression analysis of multivariate binary data such as repeated-measures data (for example, panel data) or multiple-indicators with measures of some underlying characteristic such as attitude or ability (for example, surveys or tests). The model is related to the usual Rasch model, the usual latent-class model, and other familiar models such as logistic regression. In addition to a regression specification, the model includes parameters that describe heterogeneity not accounted for by the predictors. In contrast to most other approaches, a nonparametric specification of the latent mixing distribution is used, leading to a formulation based on scaled latent classes. We examine the relationship between this model and several other models, give a tractable formulation of the likelihood function and likelihood equations, present an algorithm for maximum-likelihood estimation, and analyze marginal and conditional latent structures. The approach is illustrated with longitudinal data from the German Socioeconomic Panel.     

Successful yet insufficient: German policies for higher employment rates among older age groups

In recent years among the OECD countries, Germany has witnessed the largest increase in the employment rates of older people. This increase, and general German employment rates, are associated with both supply side measures in the fields of pensions and unemployment policies and employment promotion policies. Yet, supply side measures and Germany's shift from conservative towards liberal policy goals and policies in the case of older workers have resulted in economic inequality. These policies could be complemented by pro‐employability measures in order to become fully effective. This article describes recent policy reforms in the main policy fields of retirement, unemployment, and employment promotion, considers their effects on employment and inequality, and offers reform suggestions to raise further older worker employment rates without increasing inequality.     

Norms,moods, and free lunch: Longitudinal evidence on payments from a Pay-What-You-Want restaurant

We study the distribution and evolution of payments in a Pay-What-You-Want restaurant. Despite missing price tags and despite the option to pay nothing at all, we observe that the vast majority of guests makes strictly positive payments. Over the two years covered by our data, average payments decline slightly, converging at a positive level. At the same time, the number of daily guests increases steadily, resulting in a considerable increase in total revenues. We discuss one possible interpretation of the long-term trend in payments in terms of social norms. We further show that short-term fluctuations in average payments are partly explained by exogenous weather changes. We provide evidence that – in line with work in psychology – weather-induced changes in mood affect payments.     

The connection between maternal employment and childhood obesity: inspecting the mechanisms

This paper investigates the channels through which maternal employment affects childhood obesity. We use time diaries and interview responses from the Child Development Supplement of the Panel Study of Income Dynamics which combines information on children’s time allocation, children’s BMI, and mother’s labor force participation. We find some evidence that supervision and nutrition play significant but small roles in the relationship between maternal employment and childhood obesity. Although the difference in the effect of maternal employment varies by mother’s education, we find few differences in the mechanisms by mother’s education.

The Development of an Internet-Based Treatment for Problem Gamblers and Concerned Significant Others: A Pilot Randomized Controlled Trial

Problem gambling creates significant harm for the gambler and for concerned significant others (CSOs). While several studies have investigated the effects of individual cognitive behavioral therapy (CBT) for problem gambling, less is known about the effects of involving CSOs in treatment. Behavioral couples therapy (BCT) has shown promising results when working with substance use disorders by involving both the user and a CSO. This pilot study investigated BCT for problem gambling, as well as the feasibility of performing a larger scale randomized controlled trial. 36 participants, 18 gamblers and 18 CSOs, were randomized to either BCT or individual CBT for the gambler. Both interventions were Internet-delivered self-help interventions with therapist support. Both groups of gamblers improved on all outcome measures, but there were no differences between the groups. The CSOs in the BCT group lowered their scores on anxiety and depression more than the CSOs of those randomized to the individual CBT group did. The implications of the results and the feasibility of the trial are discussed.