Fully Bayesian Binary Markov Random Field Models: Prior Specification and Posterior Simulation

We propose a flexible prior model for the parameters of binary Markov random fields (MRF), defined on rectangular lattices and with maximal cliques defined from a template maximal clique. The prior model allows higher‐order interactions to be included. We also define a reversible jump Markov chain Monte Carlo algorithm to sample from the associated posterior distribution. The number of possible parameters for a higher‐order MRF becomes high, even for small template maximal cliques. We define a flexible parametric form where the parameters have interpretation as potentials for clique configurations, and limit the effective number of parameters by assigning apriori discrete probabilities for events where groups of parameter values are equal. To cope with the computationally intractable normalising constant of MRFs, we adopt a previously defined approximation of binary MRFs. We demonstrate the flexibility of our prior formulation with simulated and real data examples.     

Personal Assistance for People with Intellectual Impairments: experiences and dilemmas

The article gives an account of how personal assistance is adapted to people with intellectual impairments in Norway and the experiences with the arrangement for this target group. Most space, however, is given to a discussion of the challenges and dilemmas of including people with intellectual impairments in the target group for personal assistance, since other people than the user as a rule fill the role as manager of the service. Special attention is paid to the parents' role since they often act as managers on behalf of their sons/daughters. Furthermore, the assistants' role is discussed and the importance of how they meet the users. Finally, there is a discussion of the consequences the extension of personal assistance to intellectually impaired users might have both for personal assistance as a service and for the ordinary care services.     

Boosted coefficient models

Regression methods typically construct a mapping from the covariates into the real numbers. Here, however, we consider regression problems where the task is to form a mapping from the covariates into a set of (univariate) real-valued functions. Examples are given by conditional density estimation, hazard regression and regression with a functional response. Our approach starts by modeling the function of interest using a sum of B-spline basis functions. To model dependence on the covariates, the coefficients of this expansion are each modeled as functions of the covariates. We propose to estimate these coefficient functions using boosted tree models. Algorithms are provided for the above three situations, and real data sets are used to investigate their performance. The results indicate that the proposed methodology performs well. In addition, it is both straightforward, and capable of handling a large number of covariates.     

Smoking,information sources,and risk perceptions—New results on Swedish data

Using data on Swedish adolescents, this study examines (1) perceptions of the addictiveness and mortality risk of smoking, (2) the effects of these perceptions on smoking behaviour, and (3) the role of various smoking risk information sources. The average respondent believed that 46 out of 100 smokers would die from diseases caused by their smoking. As to addictiveness perceptions, the average respondent believed that 68 out of 100 smokers trying to quit would not succeed. Both a higher perceived addictiveness and a higher perceived mortality risk were negatively related to smoking participation. The results showed substantial variation in the weight that the teenagers attached to the various information sources.

Teenagers’ risky health behaviors and time use during the great recession

This paper uses individual-level data from both the 2003–2011 American Time Use Survey and Youth Risk Behavior Survey along with state-level unemployment rates to examine the effects of a weakening economy during the Great Recession on U.S. teenagers’ activities. Black male teenagers had less sex and spent more time with their parents. Hispanic male teenagers spent less time playing sports and more time watching time TV, and were more likely to be obese. Female teenagers, on the other hand, spent less time working, but made greater investments in their education. However, there were signs that female teenagers were stressed by the weak economic conditions, because they slept less and were more likely to smoke daily. Black females also consumed more alcohol.     

The health-schooling relationship: evidence from Swedish twins

Health and education are known to be highly correlated, but the mechanisms behind the relationship are not well understood. In particular, there is sparse evidence on whether adolescent health may influence educational attainment. Using a large registry dataset of twins, including comprehensive information on health status at the age of 18 and later educational attainment, we investigate whether health predicts final education within monozygotic (identical) twin pairs. We find no evidence of this and conclude that health in adolescence may not have an influence on the level of schooling. Instead, raw correlations between adolescent health and schooling appear to be driven by genes and twin-pair-specific environmental factors.     

The Impact of Child Behaviour Problems on Maternal Employment: A Longitudinal Cohort Study

This prospective population-based study examined associations between children’s behaviour problems and maternal employment. Information on children’s behaviour problems at 3 years from 22,115 mothers employed before pregnancy and participating in the Norwegian Mother and Child Cohort Study were linked to national register data on employment and relevant social background factors, mothers’ self-reported susceptibility to anxiety/depression and mother-reports of day-care attendance and fathers’ income. Mothers reporting their child to have severe (>2 SD) internalizing or severe combined behaviour problems (5 %) had excess risk of leaving paid employment irrespective of other important characteristics generally associated with maternal employment (RR 1.24–1.31). The attributable risk percent ranged from 30.3 % (internalizing problems) to 32.4 % (combined problems). Externalizing behaviour problems were not uniquely associated with mothers leaving employment.     

Eliciting and Combining Decision Criteria Using a Limited Palette of Utility Functions and Uncertainty Distributions: Illustrated by Application to Pest Risk Analysis

Utility functions in the form of tables or matrices have often been used to combine discretely rated decision‐making criteria. Matrix elements are usually specified individually, so no one rule or principle can be easily stated for the utility function as a whole. A series of five matrices are presented that aggregate criteria two at a time using simple rules that express a varying degree of constraint of the lower rating over the higher. A further nine possible matrices were obtained by using a different rule either side of the main axis of the matrix to describe situations where the criteria have a differential influence on the outcome. Uncertainties in the criteria are represented by three alternative frequency distributions from which the assessors select the most appropriate. The output of the utility function is a distribution of rating frequencies that is dependent on the distributions of the input criteria. In pest risk analysis (PRA), seven of these utility functions were required to mimic the logic by which assessors for the European and Mediterranean Plant Protection Organization arrive at an overall rating of pest risk. The framework enables the development of PRAs that are consistent and easy to understand, criticize, compare, and change. When tested in workshops, PRA practitioners thought that the approach accorded with both the logic and the level of resolution that they used in the risk assessments.