MEANINGFUL REGRESSION AND ASSOCIATION MODELS FOR CLUSTERED ORDINAL DATA

Many proposed methods for analyzing clustered ordinal data focus on the regression model and consider the association structure within a cluster as a nuisance. However, the association structure is often of equal interest—for example, temporal association in longitudinal studies and association between responses to similar questions in a survey. We discuss the use, appropriateness, and interpretability of various latent variable and Markov models for the association structure and propose a new structure that exploits the ordinality of the response. The models are illustrated with a study concerning opinions regarding government spending and an analysis of stability and change in teenage marijuana use over time, where we reveal different behavioral patterns for boys and girls through a comprehensive investigation of individual response profiles.     

Campylobacter QMRA: A Bayesian Estimation of Prevalence and Concentration in Retail Foods Under Clustering and Heavy Censoring

A Bayesian statistical temporal‐prevalence‐concentration model (TPCM) was built to assess the prevalence and concentration of pathogenic campylobacter species in batches of fresh chicken and turkey meat at retail. The data set was collected from Finnish grocery stores in all the seasons of the year. Observations at low concentration levels are often censored due to the limit of determination of the microbiological methods. This model utilized the potential of Bayesian methods to borrow strength from related samples in order to perform under heavy censoring. In this extreme case the majority of the observed batch‐specific concentrations was below the limit of determination. The hierarchical structure was included in the model in order to take into account the within‐batch and between‐batch variability, which may have a significant impact on the sample outcome depending on the sampling plan. Temporal changes in the prevalence of campylobacter were modeled using a Markovian time series. The proposed model is adaptable for other pathogens if the same type of data set is available. The computation of the model was performed using OpenBUGS software.     

Learning discrete decomposable graphical models via constraint optimization

Statistical model learning problems are traditionally solved using either heuristic greedy optimization or stochastic simulation, such as Markov chain Monte Carlo or simulated annealing. Recently, there has been an increasing interest in the use of combinatorial search methods, including those based on computational logic. Some of these methods are particularly attractive since they can also be successful in proving the global optimality of solutions, in contrast to stochastic algorithms that only guarantee optimality at the limit. Here we improve and generalize a recently introduced constraint-based method for learning undirected graphical models. The new method combines perfect elimination orderings with various strategies for solution pruning and offers a dramatic improvement both in terms of time and memory complexity. We also show that the method is capable of efficiently handling a more general class of models, called stratified/labeled graphical models, which have an astronomically larger model space.     

Organizational and supervisory justice effects on experienced threat during change: The moderating role of leader in-group representativeness

We explore the complex interplay between organizational justice and supervisory justice when predicting group members' threat perceptions in a context of organizational change. Based on the assumptions of relational models of procedural justice and prior research done in the multifoci justice framework, we hypothesize that the extent to which a supervisor is seen to embody and represent key in-group attributes will moderate the interaction between the supervisor's own interactional justice and the overall organizational procedural justice. Specifically, organizational justice is expected to decrease employees' feelings of threat particularly when the supervisor treats group members fairly and is perceived to be in-group representative rather than non-representative. We found support for this hypothesis across two studies, a cross-sectional survey and a scenario experiment. The findings confirm the particularly powerful role that an in-group representative leader's interactional fairness has in managing group members' responses to fundamental organizational processes. The implications for further research and practice are discussed.     

Transition to Work: Effects of Preparedness and Goal Construction on Employment and Depressive Symptoms

This study examines the mediating role of employment preparedness in improving employment, mental health, and construction of work‐life goals among young vocational school graduates who participated in the School‐to‐Work effectiveness trial. The trial included a 1‐week intervention program that focused on enhancing employment preparedness. In this trial, 416 graduates of secondary vocational institutes were randomized into a control and experimental group. All the study participants were assessed at baseline, immediately after the intervention, and 10 months later. The results showed that the School‐to‐Work intervention increased employment preparedness, which in turn increased employment at the 10‐month follow‐up. Furthermore, employment predicted work‐life‐related personal goals and lower financial strain, which in turn was associated with lower depressive symptoms. The implications for theory and practice are discussed.     

Labelled Graphical Models

A class of log‐linear models, referred to as labelled graphical models (LGMs), is introduced for multinomial distributions. These models generalize graphical models (GMs) by employing partial conditional independence restrictions which are valid only in subsets of an outcome space. Theoretical results concerning model identifiability, decomposability and estimation are derived. A decision theoretical framework and a search algorithm for the identification of plausible models are described. Real data sets are used to illustrate that LGMs may provide a simpler interpretation of a dependence structure than GMs.     

Sparse Markov Chains for Sequence Data

Finite memory sources and variable‐length Markov chains have recently gained popularity in data compression and mining, in particular, for applications in bioinformatics and language modelling. Here, we consider denser data compression and prediction with a family of sparse Bayesian predictive models for Markov chains in finite state spaces. Our approach lumps transition probabilities into classes composed of invariant probabilities, such that the resulting models need not have a hierarchical structure as in context tree‐based approaches. This can lead to a substantially higher rate of data compression, and such non‐hierarchical sparse models can be motivated for instance by data dependence structures existing in the bioinformatics context. We describe a Bayesian inference algorithm for learning sparse Markov models through clustering of transition probabilities. Experiments with DNA sequence and protein data show that our approach is competitive in both prediction and classification when compared with several alternative methods on the basis of variable memory length.     

Women's Responsibilities,Freedoms, and Pleasures

In the building of the Swedish welfare state, men and women have been seen as equal in their roles as parents, breadwinners, and citizens. This conception is not confirmed by the images produced by advertising. The article presents an analysis of alcohol-related advertisements published in Swedish women's magazines from the 1960s to the 2000s. The advertisements are approached as representations of gendered performances in which gender is made visible “here and now” by placing women in particular subject positions that are related to private or public spheres and associated with specific kinds of gender norms reflecting women's shifting responsibilities, freedoms, and pleasures. The article asks what kind of drinking-related subject positions have been portrayed as desirable in women's magazine advertisements over the past few decades and how those positions have changed as we move closer to the present day. The analysis reveals both continuity and variability in alcohol-related subject positions in Swedish women's magazine advertisements. It shows how women's responsibilities, freedoms, and pleasures have expanded from the traditional domain of the private sphere to multiple new areas as Sweden has developed from a modern welfare state to a late-modern competition state. However, this does not mean that the traditional gender norms have disintegrated and been replaced by equal gender norms. Rather, it seems that traditional gender norms continue to be reproduced in alcohol-related advertising.     

From Mothers of the “People's Home” to Biologically Rational Consumers

The aim of the present article is to study how women's alcohol consumption has been defined and contested in the Swedish press from 1955 to 2010 in relation to the development of Swedish society from a social democratic welfare state to a neoliberal competition state. Our material consists of articles published in the largest Swedish national and regional newspapers in 1955, 1965, 1977, 1982, 1995, 2004, and 2010. In the study, we apply Fraser's concepts of recognition and redistribution to analyse how the press contributed to the formation of cultural injustices and counter-claims through its recognition of women's drinking, and how these cultural injustices and counter-claims have conditioned the redistribution of societal resources. Our analysis shows that, during the study period, women were recognized in the Swedish press in limited and stigmatizing subject positions. These dominating representations of drinking women changed over time in an unpredictable way. As collectively shared, widely accepted cultural images, they tended to downplay the possibility of women achieving equal and just participation in cultural interaction, social activities, and healthcare services. In counter-discourses, the possibilities for women to formulate public claims in order to make surrounding structures more “enabling” of their independency, weakened during the study period.