Is It the Government’s Responsibility to Reduce Income Inequality? An Age-Period-Cohort Analysis of Public Opinion toward Redistributive Policy in the United States, 1978 to 2016

This study examines age, period, and cohort (APC) effects on changing opinions among the American public toward the federal government’s responsibility for income redistribution. More specifically, we use the hierarchical age–period–cohort (HAPC) model to analyze time periods and birth cohorts as contextual variables and age as an individual-level variable to address the identification problem inherent in APC analysis. Our results show that while cohort effects on public opinion toward redistributive policy exist, such effects are explained by individual-level compositional differences among cohorts, and while period effects are evident, particular trends in that regard are difficult to discern. What our results make abundantly clear, however, is the significant impact of age on opinions toward redistributive policy. As people age, they become significantly less supportive of federal redistribution policies, a relationship that is robust in the presence of cohort and period effects as well as a full range of controls. In the context of a rapidly aging population, the implication is that more conservative policy preferences linked to older age provide little reason to believe that mass support for government redistribution is in the offing.     

Outlyingness: Which variables contribute most?

Outlier detection is an inevitable step to most statistical data analyses. However, the mere detection of an outlying case does not always answer all scientific questions associated with that data point. Outlier detection techniques, classical and robust alike, will typically flag the entire case as outlying, or attribute a specific case weight to the entire case. In practice, particularly in high dimensional data, the outlier will most likely not be outlying along all of its variables, but just along a subset of them. If so, the scientific question why the case has been flagged as an outlier becomes of interest. In this article, a fast and efficient method is proposed to detect variables that contribute most to an outlier’s outlyingness. Thereby, it helps the analyst understand in which way an outlier lies out. The approach pursued in this work is to estimate the univariate direction of maximal outlyingness. It is shown that the problem of estimating that direction can be rewritten as the normed solution of a classical least squares regression problem. Identifying the subset of variables contributing most to outlyingness, can thus be achieved by estimating the associated least squares problem in a sparse manner. From a practical perspective, sparse partial least squares (SPLS) regression, preferably by the fast sparse NIPALS (SNIPLS) algorithm, is suggested to tackle that problem. The performed method is demonstrated to perform well both on simulated data and real life examples.

     

On estimands and the analysis of adverse events in the presence of varying follow‐up times within the benefit assessment of therapies

The analysis of adverse events (AEs) is a key component in the assessment of a drug's safety profile. Inappropriate analysis methods may result in misleading conclusions about a therapy's safety and consequently its benefit‐risk ratio. The statistical analysis of AEs is complicated by the fact that the follow‐up times can vary between the patients included in a clinical trial. This paper takes as its focus the analysis of AE data in the presence of varying follow‐up times within the benefit assessment of therapeutic interventions. Instead of approaching this issue directly and solely from an analysis point of view, we first discuss what should be estimated in the context of safety data, leading to the concept of estimands. Although the current discussion on estimands is mainly related to efficacy evaluation, the concept is applicable to safety endpoints as well. Within the framework of estimands, we present statistical methods for analysing AEs with the focus being on the time to the occurrence of the first AE of a specific type. We give recommendations which estimators should be used for the estimands described. Furthermore, we state practical implications of the analysis of AEs in clinical trials and give an overview of examples across different indications. We also provide a review of current practices of health technology assessment (HTA) agencies with respect to the evaluation of safety data. Finally, we describe problems with meta‐analyses of AE data and sketch possible solutions.     

What Makes Inheritance Fair in Stepfamilies? Examining Perceptions and Complexities

This article examines the complexity of fairness in the inheritance process within the context of divorce, remarriage, and stepchildren. Interpersonal social justice theory and qualitative vignette methods were used to explore family members' perceptions of fair inheritance outcomes and processes for financial assets and personal possessions. Findings identify decision rules for determining fair outcomes, including treating biological and stepchildren equally and differently. Who participates, what structures are relied upon, the role of information, and ethical interpersonal treatment were identified as key factors when determining fair processes. Understanding fairness provides a sound basis for helping stepfamily members navigate unavoidable inheritance decisions.     

Policing a menstrual monster: how working class girls discuss their menstrual reactions and experiences

Much of the research on menarche and menstruation has been conducted with white, middle-class, heterosexual participants. The purpose of this study was to investigate among a group of urban, working-class participants how social identities shape girls’ construction of their preparation for menarche, emotional responses to the event, and subsequent menstrual maintenance practices. Fifteen adolescent girls (ages 11–16) participated in flexible in-depth interviews meant to explore their family and life history, their menarcheal experiences and menstrual practices, and transition to womanhood more broadly. Thematic analysis of the data revealed three significant themes highlighting how participants made sense of menstruation. Participants discussed a culture of silence around menstruation which contributed to their feeling poorly prepared for menarche; noted negative and uncontrollable emotional reactions to menstruation; and expressed embodied suffering and efforts to engage in self-policing in order to take back a perceived loss of control of their bodies. It is argued that more research taking into consideration how social identities can impact the experience of menarche is needed to create sensitive and informed education that targets the unique needs of working-class adolescents.     

Structural racism as the fundamental cause of the academic achievement gap

Over six decades since the Supreme Court ruled that all American children have the right to a high quality education, the academic achievement gap remains an important social problem in the United States. Researchers interested in understanding the achievement gap generally seek to find the mechanisms that can explain why Black students continue to achieve at lower levels than their White counterparts. This research has shown that differences in socioeconomic status, family cultural resources, school quality and racial composition, and bias and prejudice in schools all act as mechanisms that link race to academic achievement. In this paper, we review studies from the past 10 years on the academic achievement gap. We argue that while all of the factors identified in the literature can add insight to how race structures educational achievement, the fundamental cause of the achievement gap is structural racism, a system of social organization that privileges White Americans and disadvantages Americans of color. We argue that acknowledging structural racism as the fundamental cause of the achievement gap can provide a unifying framework for interpreting findings from studies of specific mechanisms link race to academic outcomes.     

Commitment and Relationship Maintenance Behaviors as Marital Protective Factors during Economic Pressure

Using a contemporary national sample of married couples (N?=?1368 couples) and a dyadic path analysis, the authors examined whether commitment and relationship maintenance behaviors facilitate marital quality resilience for wives and husbands reporting recession-related financial stressors and economic pressure. Relationship maintenance behaviors moderated the association between economic pressure and marital quality for wives. Wives reported higher levels of marital satisfaction and lower levels of divorce proneness during economic pressure when husbands reported higher levels of relationship maintenance behaviors. Unexpectedly, wives reported higher levels of divorce proneness during economic pressure when husbands reported higher levels of marital commitment.     

Built community: architecture,community, and participation in a permanent supportive housing project

Housing and the social processes that create it are an important part of a better world. The permanent supportive housing movement holds that housing, in addition to a variety of human services, is the most dignified and effective way to help people without homes. But the design of such initiatives matters. This community-based, qualitative research project investigates the connection between space, participation, and community. It draws on the experiences of residents of an innovative housing organization on Skid Row in Los Angeles, California. Residents of the program find community space to be both promising and contested. Their experiences also reveal the way that institutional space can be trauma-informed and impact their overall wellbeing and opportunities for interacting with others. However, their feelings of being a part of the community and their involvement in activities are not always connected, as identity and social context can cause residents to identify or dis-identify with their community despite how involved or uninvolved they are. Intentionally designed community spaces in permanent supportive housing units can respond to trauma and set the stage for interaction, but they cannot solve all problems.     

Do Simulated Gambling Activities Predict Gambling with Real Money During Adolescence? Empirical Findings from a Longitudinal Study

As technology has developed, the international gambling market has changed markedly in recent years. The supply of internet-based gambling opportunities has become ever more significant. At the same time, the introduction of new gambling opportunities always brings a demand for evidence-based scientific evaluation, with regard to the associated risks of addiction. Simulated internet gambling, which is the focus of this study, represents a relatively new product group located at the interface between gambling and computer gaming. Concerns have been raised in scientific literature, especially with regard to the adolescent age group, as to whether participation in simulated internet gambling directly promotes recruitment to the world of monetary gambling, as defined in the gateway hypothesis. The research design was based on a standardized, representative longitudinal survey (over a 1-year period) with a total of 1178 school pupils from Northern Germany (M = 13.6 years; 47.5% male). It must be borne in mind that 12% of the adolescents belonged to the subgroup of “onset gamblers” and first reported experience with monetary gambling at the second stage of surveying. Logistic regression analysis demonstrates that this migration process is fostered by (1) participation from home in simulated gambling on social networks and (2) significant exposure to advertising (relating to both simulated and monetary gambling). Within the subgroup of simulated internet gamblers, variables such as particular patterns of use (including breadth and depth of involvement with simulated internet gambling, certain motives for participation, and microtransactions) do not serve as significant predictors. Despite this, important needs for action for the purposes of prevention and research can be identified.