Conditional moving linear regression: Modeling the recruitment process for ALLHAT

Effective recruitment is a prerequisite for successful execution of a clinical trial. ALLHAT, a large hypertension treatment trial (N = 42,418), provided an opportunity to evaluate adaptive modeling of recruitment processes using conditional moving linear regression. Our statistical modeling of recruitment, comparing Brownian and fractional Brownian motion, indicates that fractional Brownian motion combined with moving linear regression is better than classic Brownian motion in terms of higher conditional probability of achieving a global recruitment goal in 4-week ahead projections. Further research is needed to evaluate how recruitment modeling can assist clinical trialists in planning and executing clinical trials.     

Reports of Conferences,Institutes, and Seminars

Abstract

Late winter and early spring of 2009 was a busy conference time for librarians. Some of the conferences held during that time are reported herein: the American Library Association Midwinter Conference, January 23–28; Electronic Resources and Libraries (E&;RL), February 9–12; the North Carolina Serials Conference, March 27; the New England Technical Services Librarians' (NETSL) Spring Conference, April 17; and the Technical, Electronic and Digital Services Interest Group (TEDSIG) Spring Meeting, April 24.     

Serials spoken here: reports of conferences,institutes, and seminars

Abstract

Reports on the Ohio Valley Group of Technical Services Librarians (OVGTSL) Annual Conference, the April 2004 New England Technical Services Librarians (NETSL) Conference, the 2004 Acquisitions Institute at Timberline Lodge, and the 2004 Conference of the North American Serials Interest Group (NASIG).

Reports are from four conferences held in various parts of the United States and cover a wide range of topics. The Ohio Valley Group of Technical Services Librarians program emphasized the relationship between technical and public services. Education, both formal and continuing, was the theme for the New England Technical Services Librarians. Timberline Lodge hosted another Acquisitions Institute featuring sessions on new discoveries. The report on the 2004 North American Serials Group Annual Conference allows Conference Student Grant Award winner Chris Brady to include some personal reflections along with summaries of the sessions he attended.     

Asymptotic equivalence of the harrell-davis median estimator and the sample median

This paper presents an asymptotic equivalence result with a sharp rate of convergence forthe sample median and the Harrell-Davis median estimator. The consequences of this result are discussed.     

Bayesian credible intervals for response surface optima

In response surface methodology, one is usually interested in estimating the optimal conditions based on a small number of experimental runs which are designed to optimally sample the experimental space. Typically, regression models are constructed from the experimental data and interrogated in order to provide a point estimate of the independent variable settings predicted to optimize the response. Unfortunately, these point estimates are rarely accompanied with uncertainty intervals. Though classical frequentist confidence intervals can be constructed for unconstrained quadratic models, higher order, constrained or nonlinear models are often encountered in practice. Existing techniques for constructing uncertainty estimates in such situations have not been implemented widely, due in part to the need to set adjustable parameters or because of limited or difficult applicability to constrained or nonlinear problems. To address these limitations a Bayesian method of determining credible intervals for response surface optima was developed. The approach shows good coverage probabilities on two test problems, is straightforward to implement and is readily applicable to the kind of constrained and/or nonlinear problems that frequently appear in practice.     

Digital identities – overcoming visual bias through virtual embodiment

ABSTRACT

This study sheds new light on the role of identity in virtual environments when virtual representation of self is in support of disabled individuals and the potential impact of their virtual identity on work opportunities. It is widely understood that individuals who live with disability often experience a lifetime of bullying, exclusion, marginalization and rejection. They often experience workplace bias and discrimination. Yet, when they can create an identity and experience embodiment in virtual environments, the results can be extraordinarily powerful – even life-changing. This research builds on nearly a decade of ethnographic research in 3D online immersive social virtual worlds; seven of those years working with disability communities to answer the following: RQ1: In a virtual world where one can choose any avatar form, how does that visual sense of self-representation influence one’s ability to gain access to a social network, to be a leader in that network, and to find work? RQ2: How does realism in representation influence work experiences in these digital worlds? The results reveal the importance of choice in online representation of avatars in creating work and online social engagement. Implications contribute to our understanding of visual bias in the workplace and how emerging virtual reality technologies may open new avenues for meaningful work and social interactions for people with disabilities.