Powers of Discrete Goodness-of-Fit Test Statistics for a Uniform Null Against a Selection of Alternative Distributions

The comparative powers of six discrete goodness-of-fit test statistics for a uniform null distribution against a variety of fully specified alternative distributions are discussed. The results suggest that the test statistics based on the empirical distribution function for ordinal data (Kolmogorov–Smirnov, Cramér–von Mises, and Anderson–Darling) are generally more powerful for trend alternative distributions. The test statistics for nominal (Pearson's chi-square and the nominal Kolmogorov–Smirnov) and circular data (Watson's test statistic) are shown to be generally more powerful for the investigated triangular (∨), flat (or platykurtic type), sharp (or leptokurtic type), and bimodal alternative distributions.     

What you say,and how you say it: Preschoolers' growth in vocabulary and communication skills differentially predict kindergarten academic achievement and self‐regulation

The idea that language skills support school readiness, predicting later self‐regulation and academic success, is widely accepted. Although vocabulary is often emphasized in the developmental literature, the ability to use language appropriately in the classroom, or social communication skills, may also be critical. This article examined longitudinal contributions of children's vocabulary and social communication skills, from preschool to kindergarten, to kindergarten academic achievement (reading and math) and self‐regulation (executive functions and learning behaviors). Participants were 164 children (14% Latinx, 30% Black, 56% White; 57% girls) enrolled in Head Start programs. Results revealed that initial levels and growth in vocabulary and communication skills predicted better academic achievement. Social communication skills uniquely predicted self‐regulation, after accounting for vocabulary. We discuss potential mechanisms for these links and recommend that strategies to build social communication skills be incorporated in preschool interventions promoting school readiness.     

Reviewing challenges and the future for qualitative interviewing

ABSTRACT

In this article, we consider challenges for the existence and practice of qualitative research interviews. We review key features of qualitative interviewing, in particular the debate over the radical critique of interviewing and the nature of the data it generates, to set the scene for our arguments about the current standing and future prognosis for the method of generating data and the technologies that enable this. We look at qualitative interviewing in the context of the political project of neoliberalism and the regime of austerity associated with it, and the linked turn to what is known as ‘big data’, a feature of digital technological developments in garnering data. Qualitative researchers using interview methods have been creative in working with and resisting features of neoliberal austerity pragmatically and politically, and we provide some examples. We also consider an epistemological challenge and resistance from outside of the dominant framework – interviewing in indigenous methodologies. We argue that it is the relationship between the interview as a method of data generation for research and the ways of knowing about the world, that is the epistemology that the interview-based research proceeds from, that is crucial in considering the potentials for the method’s practice.     

Heteroscedasticity and Distributional Assumptions in the Censored Regression Model

Data censoring causes ordinary least-square estimators of linear models to be biased and inconsistent. The Tobit estimator yields consistent estimators in the presence of data censoring if the errors are normally distributed. However, nonnormality or heteroscedasticity results in the Tobit estimators being inconsistent. Various estimators have been proposed for circumventing the normality assumption. Some of these estimators include censored least absolute deviations (CLAD), symmetrically censored least-square (SCLS), and partially adaptive estimators. CLAD and SCLS will be consistent in the presence of heteroscedasticity; however, SCLS performs poorly in the presence of asymmetric errors. This article extends the partially adaptive estimation approach to accommodate possible heteroscedasticity as well as nonnormality. A simulation study is used to investigate the estimators’ relative performance in these settings. The partially adaptive censored regression estimators have little efficiency loss for censored normal errors and appear to outperform the Tobit and semiparametric estimators for nonnormal error distributions and be less sensitive to the presence of heteroscedasticity. An empirical example is considered, which supports these results.     

Intellectual disability and faith communities: perspectives of Catholic religious leaders

Faith communities create community and are important to many individuals with intellectual disability. However, relatively little is known about how intellectual disability is construed among faith leaders and the inclusion of people with intellectual disability in faith communities. To address these gaps in knowledge, we interviewed 12 Catholic priests, parochial vicars, and deacons to explore: their experiences with individuals with intellectual disability; their beliefs towards the involvement of individuals with intellectual disability within faith communities; and how religion informs their understanding of intellectual disability. We identified five religiously-anchored narratives of intellectual disability, and explore implications for individuals with intellectual disability and faith communities.     

Altruism and efficient allocations in three-generation households

Journal of Risk and Uncertainty - In this paper we test the efficiency of family resource allocation in three-generation households. Understanding how the so-called “squeezed middle”...     

Social Media(tion) and the Reshaping of Public/Private Boundaries in Employment Relations

Tensions surrounding social media in the employment relationship are increasingly evident in the media, public rhetoric, and courts and employment tribunals. Yet the underlying causes and dimensions of these tensions have remained largely unexplored. This article firstly reviews the available literature addressing social media and employment, outlining three primary sources of contestation: profiling, disparaging posts and blogs, and private use of social media during work time. In each area, the key dynamics and underlying concerns of the central actors involved are identified. The article then seeks to canvas explanations for these forms of contestation associated with social media at work. It is argued that the architecture of social media disrupts traditional relations in organisational life by driving employer and employee actions that (re)shape and (re)constitute the boundaries between public and private spheres. Although employers and employees are using the same social technologies, their respective concerns about and points of entry to these technologies, in contrast to traditional manifestations of conflict and resistance, are asymmetric. The article concludes with a representational summary of the relative legitimacy of concerns for organisational actors and outlines areas for future research.