Generic reversible jump MCMC using graphical models

Markov chain Monte Carlo techniques have revolutionized the field of Bayesian statistics. Their power is so great that they can even accommodate situations in which the structure of the statistical model itself is uncertain. However, the analysis of such trans-dimensional (TD) models is not easy and available software may lack the flexibility required for dealing with the complexities of real data, often because it does not allow the TD model to be simply part of some bigger model. In this paper we describe a class of widely applicable TD models that can be represented by a generic graphical model, which may be incorporated into arbitrary other graphical structures without significantly affecting the mechanism of inference. We also present a decomposition of the reversible jump algorithm into abstract and problem-specific components, which provides infrastructure for applying the method to all models in the class considered. These developments represent a first step towards a context-free method for implementing TD models that will facilitate their use by applied scientists for the practical exploration of model uncertainty. Our approach makes use of the popular WinBUGS framework as a sampling engine and we illustrate its use via two simple examples in which model uncertainty is a key feature.     

Social work supervision of young people

This paper summarizes findings on 50 teenagers supervised by local authority social services (work) departments. Interviews were held with social workers, young people and parents at the start of intervention and about a year later. Pre-tests and post-tests were also used to complement other statistical and qualitative data. After identifying the main reasons for the teenagers being on formal or informal supervision, the paper moves on to discuss the process, content and outcome of supervision as perceived by each of the three key actors. It also outlines what the young people and their parents found positive and helpful about supervision. Finally the paper demonstrates that forms of help and control need not be opposites and that social workers can help some very troubled teenagers. However, in order for services to have an impact, they have to be deployed as part of a package rather than as alternatives.     

Testing the proportional odds assumption in multiply imputed ordinal longitudinal data

A popular choice when analyzing ordinal data is to consider the cumulative proportional odds model to relate the marginal probabilities of the ordinal outcome to a set of covariates. However, application of this model relies on the condition of identical cumulative odds ratios across the cut-offs of the ordinal outcome; the well-known proportional odds assumption. This paper focuses on the assessment of this assumption while accounting for repeated and missing data. In this respect, we develop a statistical method built on multiple imputation (MI) based on generalized estimating equations that allows to test the proportionality assumption under the missing at random setting. The performance of the proposed method is evaluated for two MI algorithms for incomplete longitudinal ordinal data. The impact of both MI methods is compared with respect to the type I error rate and the power for situations covering various numbers of categories of the ordinal outcome, sample sizes, rates of missingness, well-balanced and skewed data. The comparison of both MI methods with the complete-case analysis is also provided. We illustrate the use of the proposed methods on a quality of life data from a cancer clinical trial.     

Comparison of two methods of measuring physical activity in South African older adults

The aim of this study was to assess the validity and reliability of the Yale Physical Activity Survey (YPAS) and the short version of the International Physical Activity Questionnaire (IPAQ) in older South African adults. The YPAS includes measures of weekly energy expenditure (EE) for housework, yard work, caregiving, exercise, and recreation. The IPAQ measures total time and EE during vigorous and moderate activity, walking, and sitting. The instruments were administered twice for test-retest reliability (men, n = 52, 68 +/- 5.4 years, and women, n = 70, 66 +/- 5.8 years). Data for criterion validity were obtained from accelerometers. YPAS reliability ranged from r = .44 to.80 for men and r = .59 to .99 for women (p < .0001). IPAQ reliability was lower for men (r = .29 to .76) than for women (r = .46 to .77). Criterion validity of the YPAS was .31 to .54 for men and .26 to .29 for women. The YPAS and short IPAQ had comparable results for reliability and criterion validity.     

Enough Time for Housework? Low‐Wage Work and Desired Housework Time Adjustments

Although studies examine preferences for hours spent in paid employment, little attention has been given to preferences for hours spent in unpaid household labor. This study examines the extent to which women working in low‐paid retail jobs would prefer to spend more or less time on household work and how alignment between preferred and actual time on housework is related to characteristics of paid work. Using original survey data and company records on a sample of women working at a U.S. retail firm (N = 277), the authors found that mismatch between preferred and actual time on household work was common. Roughly 42% wanted more time on household work and 18% wanted less. Working multiple jobs, work schedule unpredictability, and nonstandard work timing contributed to wanting more time on housework. Findings add to understanding of how low‐wage, precarious employment shapes workers' ability to attend to necessary tasks of household management.     

Between “Families in Trouble” and “Children at Risk”: Historicising “Troubled Family” Policy in England since 1945

The launch of the Troubled Families Programme in 2011 has thrown into sharp relief how governments develop policies and practices to intervene in the lives of so‐called ‘troubled families’. Commentators were quick to make comparisons with historic efforts to rehabilitate ‘problem families’ in the post‐war period. However, beyond discursive similarities, there are also marked continuities in how family policies have been developed and implemented. This review narrates the rise, fall and rise of concern about ‘problem’ and ‘troubled’ families in England in the context of anxieties about child and family welfare, and the appropriate response of the state.     

On the use of extreme value tail modeling for generalized pairwise comparisons with censored outcomes

In randomized clinical trials, methods of pairwise comparisons such as the ‘Net Benefit’ or the ‘win ratio’ have recently gained much attention when interests lies in assessing the effect of a treatment as compared to a standard of care. Among other advantages, these methods are usually praised for delivering a treatment measure that can easily handle multiple outcomes of different nature, while keeping a meaningful interpretation for patients and clinicians. For time-to-event outcomes, a recent suggestion emerged in the literature for estimating these treatment measures by providing a natural handling of censored outcomes. However, this estimation procedure may lead to biased estimates when tails of survival functions cannot be reliably estimated using Kaplan–Meier estimators. The problem then extrapolates to the other outcomes incorporated in the pairwise comparison construction. In this work, we suggest to extend the procedure by the consideration of a hybrid survival function estimator that relies on an extreme value tail model through the Generalized Pareto distribution. We provide an estimator of treatment effect measures that notably improves on bias and remains easily apprehended for practical implementation. This is illustrated in an extensive simulation study as well as in an actual trial of a new cancer immunotherapy.