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.     

Model free audit methodology for bias evaluation of tumour progression in oncology

Many oncology studies incorporate a blinded independent central review (BICR) to make an assessment of the integrity of the primary endpoint, progression free survival. Recently, it has been suggested that, in order to assess the potential for bias amongst investigators, a BICR amongst only a sample of patients could be performed; if evidence of bias is detected, according to a predefined threshold, the BICR is then assessed in all patients, otherwise, it is concluded that the sample was sufficient to rule out meaningful levels of bias. In this paper, we present an approach that adapts a method originally created for defining futility bounds in group sequential designs. The hazard ratio ratio, the ratio of the hazard ratio (HR) for the treatment effect estimated from the BICR to the corresponding HR for the investigator assessments, is used as the metric to define bias. The approach is simple to implement and ensures a high probability that a substantial true bias will be detected. In the absence of bias, there is a high probability of accepting the accuracy of local evaluations based on the sample, in which case an expensive BICR of all patients is avoided. The properties of the approach are demonstrated by retrospective application to a completed Phase III trial in colorectal cancer. The same approach could easily be adapted for other disease settings, and for test statistics other than the hazard ratio. Copyright © 2015 John Wiley & Sons, Ltd.     

Conceptualizations of Heterosexual Anal Sex and HIV Risk in Five East African Communities

Heterosexual anal sex is underresearched and little understood, particularly in the African context. Existing prevalence data indicate that heterosexual anal sex is a widespread practice, yet little is known about the way in which it is conceptualized and understood. Describing findings from qualitative research conducted in Kenya, Tanzania, and Uganda, we shed light on conceptualizations of heterosexual anal sex and its relation to human immunodeficiency virus (HIV). These findings suggest that penile-anal sex is practiced by men and women in Africa for a range of reasons, including virginity maintenance, contraception, fulfillment of male pleasure, relationship security, menstruation, in the presence of vaginal complications, financial gain, fidelity, and prestige. Despite anal sex being the most efficient way to transmit HIV sexually, there is widespread lack of knowledge about its risks. These findings describe the ways in which anal sex is conceptualized in five East African communities, highlighting how penile-anal intercourse is often not considered “sex” and how the omission of anal sex in safe-sex messaging is interpreted as meaning that anal sex is safe. In light of its frequency and risks, greater attention must be paid to heterosexual anal sex in Africa to ensure a comprehensive approach to HIV prevention.     

A new method for finding hierarchical subgroups from networks

We present a new method for decomposing a social network into an optimal number of hierarchical subgroups. With a perfect hierarchical subgroup defined as one in which every member is automorphically equivalent to each other, the method uses the REGGE algorithm to measure the similarities among nodes and applies the k-means method to group the nodes that have congruent profiles of dissimilarities with other nodes into various numbers of hierarchical subgroups. The best number of subgroups is determined by minimizing the intra-cluster variance of dissimilarity subject to the constraint that the improvement in going to more subgroups is better than a network whose n nodes are maximally dispersed in the n-dimensional space would achieve. We also describe a decomposability metric that assesses the deviation of a real network from the ideal one that contains only perfect hierarchical subgroups. Four well known network data sets are used to demonstrate the method and metric. These demonstrations indicate the utility of our approach and suggest how it can be used in a complementary way to Generalized Blockmodeling for hierarchical decomposition.     

After a Disaster: Lessons in Survey Methodology from Hurricane Katrina

In 2005, the National Science Foundation funded a number of projects to study the impact of Hurricane Katrina. The current article provides an overview of several research approaches used to conduct post-Katrina research. Each method had some advantages and disadvantages. The post-disaster context meant that experience from traditional survey methods often did not apply. Comparisons of advantages and disadvantages associated with each sampling method serve to inform future post-disaster research and illuminate the limits of classical research methods.     

Disability, Eugenics and the Current Ideology of Segregation: a modern moral tale

Recently, an amalgamation of articles have appeared in a wide range of publications linking together community and school inclusion, and facilitated communication research as an unholy trinity of anti-empiricism eroding the disability fields. The authors of these critiques suggest that there exists a scientific basis for state institutions, segregated learning and a non-critical acceptance of traditional interpretations of expressive ability on the part of people with disabilities. In this article we expose not science, but an ideology of segregated control behind these claims. This ideology permeates the disabilityrelated professions and is cloaked in the language of the natural sciences. We trace this use of the natural sciences to the eugenics movement of the early twentieth century and explore the legacy of the ideology of control as it impacts current understanding of disability.     

Recruitment,enrollment & data collection with victims of elder abuse and neglect identified from police incident reports

ABSTRACT

This study evaluated the success of researcher-generated recruitment, enrollment, data collection, and safety protocols for field research with victims of elder abuse and neglect (EAN) identified from police incident reports in terms of their success including cost-effectiveness, ability to generate a representative sample, and safety. After reviewing 492 police incident reports involving victims age 65 years or older to identify cases of EAN 62 victims were identified. Mail, phone, and in-person recruitment strategies were used. After 259 recruitment attempts, 52 (84%) eligible victims were contacted, of which 24 (46%) consented to participate. Phone calls were the least expensive mechanism to produce a successfully enrolled participant. Findings from a regression show completion of a research interview could not be predicted by victim, suspect, or offense characteristics, indicating that the recruited victims likely represent the population they were drawn from. No safety or adverse events occurred.     

Effects of the Mechanism of Receptor-Mediated Gene Expression on the Shape of the Dose-Response Curve

A mathematical model of receptor-mediated gene expression that includes receptor binding of natural and xenobiotic ligands, protein synthesis and degradation, and metabolism of the xenobiotic ligand was created to identify the determinants of the shape of the dose-response profile. Values of the model's parameters were varied to reflect alternative mechanisms of expression of the protein. These assumptions had dramatic effects on the computed response to a bolus dose of the xenobiotic ligand. If all processes in the model exhibit hyperbolic kinetics, the dose-response curves can appear sigmoidal but actually be linear with a positive slope at low doses. The slope of the curve only approached zero at low dose, indicative of a threshold for response, if binding of the xenobiotic ligand to the receptor exhibited positive cooperativity (ligand binding at one site increases the affinity for ligand at another binding site on the receptor). Positive cooperativity in the rate-limiting step of protein synthesis produced dose-response curves which were "U-shaped" at low doses, also indicative of a threshold. Positive cooperativity in the metabolism of the xenobiotic ligand produced dose-response curves that increased more rapidly than linearly with increasing dose. The model illustrates the fact that response cannot be predicted from qualitative mechanistic arguments alone; any assessment of risk to health from xenobiotic chemicals must be based on a detailed quantitative examination of the kinetic behavior of each chemical species individually.