State space mixed models for longitudinal observations with binary and binomial responses

We propose a new class of state space models for longitudinal discrete response data where the observation equation is specified in an additive form involving both deterministic and random linear predictors. These models allow us to explicitly address the effects of trend, seasonal or other time-varying covariates while preserving the power of state space models in modeling serial dependence in the data. We develop a Markov chain Monte Carlo algorithm to carry out statistical inference for models with binary and binomial responses, in which we invoke de Jong and Shephard’s (Biometrika 82(2):339–350, 1995) simulation smoother to establish an efficient sampling procedure for the state variables. To quantify and control the sensitivity of posteriors on the priors of variance parameters, we add a signal-to-noise ratio type parameter in the specification of these priors. Finally, we illustrate the applicability of the proposed state space mixed models for longitudinal binomial response data in both simulation studies and data examples.     

Bayesian clustering for row effects models

We deal with two-way contingency tables having ordered column categories. We use a row effects model wherein each interaction term is assumed to have a multiplicative form involving a row effect parameter and a fixed column score. We propose a methodology to cluster row effects in order to simplify the interaction structure and to enhance the interpretation of the model. Our method uses a product partition model with a suitable specification of the cohesion function, so that we can carry out our analysis on a collection of models of varying dimensions using a straightforward MCMC sampler. The methodology is illustrated with reference to simulated and real data sets.     

Different Reasons,Different Results: Implications of Migration by Gender and Family Status

Previous research on migration and gendered career outcomes centers on couples and rarely examines the reason for the move. The implicit assumption is usually that households migrate in response to job opportunities. Based on a two-year panel from the Current Population Survey, this article uses stated reasons for geographic mobility to compare earnings outcomes among job migrants, family migrants, and quality-of-life migrants by gender and family status. We further assess the impact of migration on couples’ internal household economy. The effects of job-related moves that we find are reduced substantially in the fixed-effects models, indicating strong selection effects. Married women who moved for family reasons experience significant and substantial earnings declines. Consistent with conventional models of migration, we find that household earnings and income and gender specialization increase following job migration. Married women who are secondary earners have increased odds of reducing their labor supply following migration for job or family reasons. However, we also find that migrating women who contributed as equals to the household economy before the move are no more likely than nonmigrant women to exit work or to work part-time. Equal breadwinner status may protect women from becoming tied movers.     

On the detection of changes in autoregressive time series,II. Resampling procedures

We study an autoregressive time series model with a possible change in the regression parameters. Approximations to the critical values for change-point tests are obtained through various bootstrapping methods. Theoretical results show that the bootstrapping procedures have the same limiting behavior as their asymptotic counterparts discussed in Hušková et al. [2007. On the detection of changes in autoregressive time series, I. Asymptotics. J. Statist. Plann. Inference 137, 1243–1259]. In fact, a small simulation study illustrates that the bootstrap tests behave better than the original asymptotic tests if performance is measured by the α$\alpha$- and β$\beta$-errors, respectively.     

Black African Children and the Child Protection System

This paper explores black African children’s experiencesof the child protection system in the UK. The central focusof the paper is a review of the available literature on thesocial circumstances and environmental influences affectingmany black African families involved in the child protectionsystem; specific parenting practices and care-giving environments;and their experiences of social work and other professionalinterventions aimed at safeguarding and promoting the needsof African children. This paper examines these themes to elucidatethe factors that contribute to the provision of effective, culturallycompetent interventions with black African children at riskof significant harm. It suggests that there are a number oftensions inherent for professionals in working with culturallydiverse African families such as reconciling different beliefsand behaviours concerning child-rearing practices; affirmingthe parenting practices of these families in the engagementprocess; adopting a strengths-based orientation whilst at thesame time safeguarding and promoting the welfare of vulnerablechildren. The paper concludes with a discussion of the implicationsfor practice.     

Multiple motives of pro-social behavior: evidence from the solidarity game

The article analyses experimental “solidarity games” with two benefactors and one beneficiary. Depending on their motive for giving—e.g., warm glow, altruism, or guilt—the benefactors’ response functions are either constant, decreasing, or increasing. If motives interact, or if envy is a concern, then more complex (unimodal) shapes may emerge. Controlling for random utility perturbations, we determine which and how many motives affect individual decision making. The main findings are that the motives of about 75% of the subjects can be identified fairly sharply, that all of the motives discussed in the literature co-exist in the population, and that for any given individual no more than two motives (out of six motives considered overall) are identified. We conclude that a unifying motive for solidarity cannot be derived even when we allow for individually heterogeneous parameterization: different subjects give for different reasons and all existing social preference theories are partially correct.     

Non nested model selection for spatial count regression models with application to health insurance

In this paper we consider spatial regression models for count data. We examine not only the Poisson distribution but also the generalized Poisson capable of modeling over-dispersion, the negative Binomial as well as the zero-inflated Poisson distribution which allows for excess zeros as possible response distribution. We add random spatial effects for modeling spatial dependency and develop and implement MCMC algorithms in $R$ for Bayesian estimation. The corresponding R library ‘spatcounts’ is available on CRAN. In an application the presented models are used to analyze the number of benefits received per patient in a German private health insurance company. Since the deviance information criterion is only appropriate for exponential family models, we use in addition the Vuong and Clarke test with a Schwarz correction to compare possibly non nested models. We illustrate how they can be used in a Bayesian context.     

Global prior distributions for the analysis of discrete graphical models

Summary We propose a new class of prior distributions for the analysis of discrete graphical models. Such a class, obtained following a conditional approach, generalizes the hyper Dirichlet distributions of Dawid and Lauritzen (1993), since it can be extended to non decomposable graphical models. The two classes are compared in terms of model selection, with an application to a medical data-set illustrating the performance of the two resulting procedures. The proposed class turns out to select simpler, more par-simonious structures.     

Through a glass darkly: Chronic illness in the therapist

This paper is about doing psychotherapy while suffering from a chronic illness. The purpose is to describe the manner in which ongoing irreversible pain integrates itself into the life of any human being, but specifically that of the therapist. The process of weaving the experience into the life narrative and in turn the therapeutic narrative is explored.