Simultaneous Small Sample Inference for Linear Combinations of Generalized Linear Model Parameters

A method is proposed to construct simultaneous confidence intervals for multiple linear combinations of generalized linear model parameters, that uses a multivariate normal- or t-distribution together with the signed likelihood root statistic. In an application to a case study simultaneous confidence bands for logistic regression are calculated. A simulation study based on the example evaluation suggests superior performance compared to the common Wald-type approaches. The proposed methods are readily implemented in the R extension package mcprofile.     

Probabilistic Projections of the Total Fertility Rate for All Countries

We describe a Bayesian projection model to produce country-specific projections of the total fertility rate (TFR) for all countries. The model decomposes the evolution of TFR into three phases: pre-transition high fertility, the fertility transition, and post-transition low fertility. The model for the fertility decline builds on the United Nations Population Division’s current deterministic projection methodology, which assumes that fertility will eventually fall below replacement level. It models the decline in TFR as the sum of two logistic functions that depend on the current TFR level, and a random term. A Bayesian hierarchical model is used to project future TFR based on both the country’s TFR history and the pattern of all countries. It is estimated from United Nations estimates of past TFR in all countries using a Markov chain Monte Carlo algorithm. The post-transition low fertility phase is modeled using an autoregressive model, in which long-term TFR projections converge toward and oscillate around replacement level. The method is evaluated using out-of-sample projections for the period since 1980 and the period since 1995, and is found to be well calibrated.     

Similarity in friendship networks: Selection or influence? The effect of constraining contexts and non-visible individual attributes

Most research on similarity in friendship networks focuses on clearly visible individual attributes (i.e. attitudes and behaviors) in contexts where choices whom to befriend are relatively unconstrained. These studies often reveal that social selection rather than social influence is the dominant cause of similarity among friends. We argue that in a setting where social collaboration is crucial and friendship choices are more constrained, influence might be the main reason for similarity found among friends. In addition, we examined whether social categorization and peer control amplifies the social influence process among friends. Using a stochastic actor-based model for network dynamics, we analyzed a three-wave dataset of first year Royal Netherlands Naval College officer students on friendship formation and military discipline. The data supports our first hypothesis that students adjust their own military discipline to that of their friends. Contrary to our expectations, we did not find support for the idea that individuals adjust their discipline more to friends who are of the same military specialty, and neither more to friends who exert peer control. We elaborate on these findings in the discussion.     

On the definition of public relations: a European view

The article confronts a U.S.-based definition of public relations as relationship management with a European view that besides a relational, argues also for a reflective paradigm that is concerned with publics and the public sphere; not only with relational (which can in principle be private), but also with public consequences of organizational behavior. The article is based on a three year research project on the European Public Relations Body of Knowledge and it reflects on the consequence of that project for definitional activities in the US practitioner and academic communities.     

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.     

Tree-based modeling of time-varying coefficients in discrete time-to-event models

Lifetime Data Analysis - Hazard models are popular tools for the modeling of discrete time-to-event data. In particular two approaches for modeling time dependent effects are in common use. The...     

Tree-structured modelling of varying coefficients

Statistics and Computing - The varying-coefficient model is a strong tool for the modelling of interactions in generalized regression. It is easy to apply if both the variables that are modified as...     

Asymptotically Optimal Design Points for Rejection Algorithms

ABSTRACT

Very fast automatic rejection algorithms were developed recently which allow us to generate random variates from large classes of unimodal distributions. They require the choice of several design points which decompose the domain of the distribution into small sub-intervals. The optimal choice of these points is an important but unsolved problem. Therefore, we present an approach that allows us to characterize optimal design points in the asymptotic case (when their number tends to infinity) under mild regularity conditions. We describe a short algorithm to calculate these asymptotically optimal points in practice. Numerical experiments indicate that they are very close to optimal even when only six or seven design points are calculated.