Incorporating disabled students within an inclusive higher education environment

This study investigated disabled students' perceptions and experiences of learning in a single university. The paper reports the views of disabled student volunteers with a range of impairments who were selected to discuss experiences of teaching and assessment that they commonly encountered. Four group interviews were organized in 2002, before the Disability Discriminants Act (DDA) part IV came on stream, in which disabled students were invited to reflect together on their experiences as learners at the case study university. In addition to teaching and assessment, the students also identified issues to do with access to, and the use of, information as important in their learning experience. We conclude that further studies will need to adopt a more integrated approach to understanding disabled students' experiences as learners.     

Flexible Cure Rate Modeling Under Latent Activation Schemes

With rapid improvements in medical treatment and health care, many datasets dealing with time to relapse or death now reveal a substantial portion of patients who are cured (i.e., who never experience the event). Extended survival models called cure rate models account for the probability of a subject being cured and can be broadly classified into the classical mixture models of Berkson and Gage (BG type) or the stochastic tumor models pioneered by Yakovlev and extended to a hierarchical framework by Chen, Ibrahim, and Sinha (YCIS type). Recent developments in Bayesian hierarchical cure models have evoked significant interest regarding relationships and preferences between these two classes of models. Our present work proposes a unifying class of cure rate models that facilitates flexible hierarchical model-building while including both existing cure model classes as special cases. This unifying class enables robust modeling by accounting for uncertainty in underlying mechanisms leading to cure. Issues such as regressing on the cure fraction and propriety of the associated posterior distributions under different modeling assumptions are also discussed. Finally, we offer a simulation study and also illustrate with two datasets (on melanoma and breast cancer) that reveal our framework's ability to distinguish among underlying mechanisms that lead to relapse and cure.     

The Control of Sociological Theory: In Praise of the Interregnum*

The argument advanced here contends that integrative efforts within sociology exacerbate, rather than mitigate, theoretical and organizational fragmentation. Viewing epistemologically driven movements towards theoretical control as counter- productive, this study contains a proposal for a greater analytical focus on ontology as a better way to promote and preserve the sociological enterprise. Such a move would reflect a return to the ethos of sociology's classical project and encourage embracing theoretical diversity as a desirable condition.     

The two-way proportional hazards model

Summary. Survival analysis problems often involve dual timescales, most commonly calendar date and lifetime, the latter being the elapsed time since an initiating event such as a heart transplant. In our main example attention is focused on the hazard rate of 'death' as a function of calendar date. Three different estimates are discussed, one each from proportional hazards analyses on the lifetime and the calendar date scales, and one from a symmetric approach called here the 'two-way proportional hazards model', a multiplicative hazards model going back to Lexis in the 1870s. The three are connected through a Poisson generalized linear model for the Lexis diagram. The two-way model is shown to combine the information from the two 'one-way' proportional hazards analyses efficiently, at the cost of more extensive parametric modelling.     

Leader–member exchange (LMX) in context: How LMX differentiation and LMX relational separation attenuate LMX's influence on OCB and turnover intention

Using the group engagement model, we hypothesize that two differentiated leadership constructs – LMX differentiation at the group level and a new construct, LMX relational separation, at the individual-within-group level – interact with LMX to affect follower citizenship behaviors (OCB) and turnover intentions. Data from 223 followers and their leaders situated across 60 workgroups demonstrate that the effects of individual perceived LMX quality are contingent upon a group's overall variability in LMX (i.e., LMX differentiation) and employees' similarity in terms of LMX with their coworkers (i.e., LMX relational separation). Specifically, the effects of high quality LMX relationships on OCB and turnover intentions are weaker when group LMX differentiation or employees' LMX relational separation is higher, rather than lower. Our findings contribute to a growing stream of multilevel LMX research incorporating climate effects and offer an alternative view of differentiated leadership in groups. Key implications for theory and practice are discussed.     

Addressing the impact of trauma before diagnosing mental illness in child welfare

Congress set requirements for child welfare agencies to respond to emotional trauma associated with child maltreatment and removal. In meeting these requirements, agencies should develop policies that address child trauma. To assist in policy development, this study analyzes more than 14,000 clinical assessments from child welfare in Illinois. Based on the analysis, the study recommends child welfare agencies adopt policies requiring that (1) mental health screenings and assessments of all youth in child welfare include measures of traumatic events and trauma-related symptoms; (2) evidence-based, trauma-focused treatment begin when a youth in child welfare demonstrates a trauma-related symptom; and (3) a clinician not diagnose a youth in child welfare with a mental illness without first addressing the impact of trauma. The study also raises the issue of treatment reimbursement based on diagnosis.     

ESTIMATING THE STOCK‐FLOW MATCHING MODEL USING MICRO DATA

We estimate the stock‐flow matching model using micro‐level data from a well‐defined labor market. Using a dataset of complete labor‐market histories for both sides of the market, we estimate hazard functions for job‐seekers and vacancies. We find that the stock of new vacancies has a significant positive impact on the job‐seeker hazard, over and above that of the total stock of vacancies. There is an even stronger robust result for vacancy hazards. Thus we find evidence in favor of stock‐flow matching, even when controlling for unobserved search heterogeneity and stratifying into submarkets defined by location and occupation.     

A Unified Bayesian Decision Theory

This paper provides new foundations for Bayesian Decision Theory based on a representation theorem for preferences defined on a set of prospects containing both factual and conditional possibilities. This use of a rich set of prospects not only provides a framework within which the main theoretical claims of Savage, Ramsey, Jeffrey and others can be stated and compared, but also allows for the postulation of an extended Bayesian model of rational belief and desire from which they can be derived as special cases. The main theorem of the paper establishes the existence of a such a Bayesian representation of preferences over conditional prospects, i.e. the existence of a pair of real-valued functions respectively measuring the agent’s degrees of belief and desire and which satisfy the postulated rationality conditions on partial belief and desire. The representation of partial belief is shown to be unique and that of partial desire, unique up to a linear transformation.