A critical look at Lo's modified R/S statistic

We report on an empirical investigation of the modified rescaled adjusted range or R/S statistic that was proposed by Lo, 1991. Econometrica 59, 1279–1313, as a test for long-range dependence with good robustness properties under ‘extra’ short-range dependence. In contrast to the classical R/S statistic that uses the standard deviation S to normalize the rescaled range R, Lo's modified R/S-statistic V_q is normalized by a modified standard deviation S_q which takes into account the covariances of the first q lags, so as to discount the influence of the short-range dependence structure that might be present in the data. Depending on the value of the resulting test-statistic V_q, the null hypothesis of no long-range dependence is either rejected or accepted. By performing Monte-Carlo simulations with ‘truly’ long-range- and short-range dependent time series, we study the behavior of V_q, as a function of q, and uncover a number of serious drawbacks to using Lo's method in practice. For example, we show that as the truncation lag q increases, the test statistic V_q has a strong bias toward accepting the null hypothesis (i.e., no long-range dependence), even in ideal situations of ‘purely’ long-range dependent data.     

When Social Partners Unite – Explaining Continuity and Change in Austrian and Dutch Labour Market Governance

Why do Austria and the Netherlands, two highly corporatist, coordinated, consensual countries diverge with respect to the involvement of social partners in their Public Employment Service? By comparing and contrasting the competing predictions of the power‐resource, employer‐centred and social partnership approaches, we identify a key omitted variable that can explain the observed variations: the ability of the social partners to unite on reform positions. We demonstrate that when the social partners are divided, their collective power is reduced and partisan‐based policy outcomes become more pronounced. In turn, when the social partners jointly favour a particular outcome, their collective power increases and they can override governmental reform plans, even if the government holds a large legislative majority. These findings highlight the causal importance of power relations between and within the social partners for institutional continuity and change.     

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.     

Two-stage hierarchical modeling for analysis of subpopulations in conditional distributions

In this work, we develop modeling and estimation approach for the analysis of cross-sectional clustered data with multimodal conditional distributions where the main interest is in analysis of subpopulations. It is proposed to model such data in a hierarchical model with conditional distributions viewed as finite mixtures of normal components. With a large number of observations in the lowest level clusters, a two-stage estimation approach is used. In the first stage, the normal mixture parameters in each lowest level cluster are estimated using robust methods. Robust alternatives to the maximum likelihood estimation are used to provide stable results even for data with conditional distributions such that their components may not quite meet normality assumptions. Then the lowest level cluster-specific means and standard deviations are modeled in a mixed effects model in the second stage. A small simulation study was conducted to compare performance of finite normal mixture population parameter estimates based on robust and maximum likelihood estimation in stage 1. The proposed modeling approach is illustrated through the analysis of mice tendon fibril diameters data. Analyses results address genotype differences between corresponding components in the mixtures and demonstrate advantages of robust estimation in stage 1.     

The Social Work Role in Reducing 30-Day Readmissions: The Effectiveness of the Bridge Model of Transitional Care

The hospital experience is taxing and confusing for patients and their families, particularly those with limited economic and social resources. This complexity often leads to disengagement, poor adherence to the plan of care, and high readmission rates. Novel approaches to addressing the complexities of transitional care are emerging as possible solutions. The Bridge Model is a person-centered, social work-led, interdisciplinary transitional care intervention that helps older adults safely transition from the hospital back to their homes and communities. The Bridge Model combines 3 key components—care coordination, case management, and patient engagement—which provide a seamless transition during this stressful time and improve the overall quality of transitional care for older adults, including reducing hospital readmissions. The post Affordable Care Act (ACA) and managed care environment’s emphasis on value and quality support further development and expansion of transitional care strategies, such as the Bridge Model, which offer promising avenues to fulfil the triple aim by improving the quality of individual patient care while also impacting population health and controlling per capita costs.     

Efficient circular neighbour designs for spatial interference model

We consider circular block designs for field-trials when there are two-sided spatial interference between neighbouring plots of the same blocks. The parameter of interest is total effects that is the sum of direct effect of treatment and neighbour effects, which correspond to the use of a single treatment in the whole field. We determine universally optimal approximate designs. When the number of blocks may be large, we propose efficient exact designs generated by a single sequence of treatment. We also give efficiency factors of the usual binary block neighbour balanced designs which can be used when the number of blocks is small.     

Measles: Current Status and Outbreak Control on Campus

Abstract

This study is part of a nationwide research project dealing with all suicides in Finland. It includes all suicides among university students during the 1-year period from April 1, 1987, to March 31, 1988. Ten students (6 men and 4 women) committed suicide during the period studied. The observed suicide rates per 100,000 students per year were 13.8 (95% CI = 5.1–30.1) for men and 9.0 (95% CI = 2.4–22.8) for women. The difference between the observed and expected suicide rate for men (13.8 v 47.7, standard mortality rate [SMR] = 29) was statistically significant. For women (9.0 v 8.3, SMR = 108), the difference was not statistically significant. Most of the suicides had experienced serious difficulties since early childhood, including narcissistic problems, difficulties in human relations, severe depressive periods, previous suicidal behavior, and alcohol problems; they had also had earlier psychiatric treatment.     

Recognising the face of the other: Difference,identity and community

Social work's role in creating social solidarity requires an engagement with identity politics through careful negotiation of the boundary between the private and the public spheres and hence ensuring a balance between personal freedom to define one's specific identity and the public entitlement to belong to a political community as citizens. Current political and cultural trends, reflected also in social policies, impact severely on that boundary maintenance task inasmuch as privatisation encroaches on formerly public domains while simultaneously details of private concerns receive public attention through their commercialisation by the new media. It is suggested that social work's political role be asserted more explicitly in terms of the application of the Global Agenda which needs to penetrate to the level of person‐to‐person interaction.