Response‐adaptive designs for binary responses: How to offer patient benefit while being robust to time trends?

Response‐adaptive randomisation (RAR) can considerably improve the chances of a successful treatment outcome for patients in a clinical trial by skewing the allocation probability towards better performing treatments as data accumulates. There is considerable interest in using RAR designs in drug development for rare diseases, where traditional designs are not either feasible or ethically questionable. In this paper, we discuss and address a major criticism levelled at RAR: namely, type I error inflation due to an unknown time trend over the course of the trial. The most common cause of this phenomenon is changes in the characteristics of recruited patients—referred to as patient drift. This is a realistic concern for clinical trials in rare diseases due to their lengthly accrual rate. We compute the type I error inflation as a function of the time trend magnitude to determine in which contexts the problem is most exacerbated. We then assess the ability of different correction methods to preserve type I error in these contexts and their performance in terms of other operating characteristics, including patient benefit and power. We make recommendations as to which correction methods are most suitable in the rare disease context for several RAR rules, differentiating between the 2‐armed and the multi‐armed case. We further propose a RAR design for multi‐armed clinical trials, which is computationally efficient and robust to several time trends considered.     

A Diamond-Stiglitz approach to the demand for self-protection

The existing research concerning the relationship between risk aversion and prudence and the demand for self-protection assumes that the loss variable follows a Bernoulli distribution, and that changes in the level of self-protection are mean preserving. The analysis here replaces these two very strong conditions with ones which are more general. When doing this, the method of analysis is also significantly modified. This modification includes representing a change in the level of self-protection using the procedure developed by Diamond and Stiglitz (Journal of Economic Theory 8:337-360, 1974) for representing a change in risk. This alternate representation allows the existing findings to be generalized considerably, and also simplifies the analysis.     

Bayesian analysis of a general growth curve model with predictions using power transformations and AR(1) autoregressive dependence

In this paper, we consider a Bayesian analysis of the unbalanced (general) growth curve model with AR(1) autoregressive dependence, while applying the Box-Cox power transformations. We propose exact, simple and Markov chain Monte Carlo approximate parameter estimation and prediction of future values. Numerical results are illustrated with real and simulated data.     

Differential Recovery Migration across the Rural–Urban Gradient: Minimal and Short-Term Population Gains for Rural Disaster-Affected Gulf Coast Counties

Places affected or threatened by extreme environmental disturbances confront a number of significant issues, including whether their populations will stay the same or change through migration. Research on Hurricanes Katrina and Rita shows some displaced residents returned to their disaster-affected communities once the built environment was restored, new migrants settled in affected places as part of the rebuilding effort, and the regional migration system grew more urbanized and spatially concentrated during post-disaster years. Research also shows that not all disaster-affected places recovered their populations. Our study examines whether differential recovery is systematically patterned along the rural–urban gradient. Using U.S. Census Bureau estimates and IRS county-to-county migration data, we investigate whether the 2005 hurricane season differentially exacerbated or altered previous migration trends across a rural–urban gradient that incorporates proximity to metropolitan areas and disaster-related housing loss. We find a rural–urban differential in Gulf Coast recovery migration: The disaster boosted migration among non-metropolitan counties, yet these increases were smaller and short-lived compared to the patterns found for metropolitan counties, most especially high loss metropolitan counties. Our findings encourage theories of environmental migration to incorporate spatial differentiation and scenarios of environmental changes to account for differential impacts on settlement patterns across the rural–urban continuum.     

Estimating Recent Local Impacts of Sea-Level Rise on Current Real-Estate Losses: A Housing Market Case Study in Miami-Dade,Florida

Sea-Level Rise (SLR) Projections from the National Oceanic and Atmospheric Administration (NOAA) and the U.S. Army Corp of Engineers (USACE) indicate increasing, and imminent, risk to coastal communities from tidal flooding and hurricane storm surge. Building on recent research related to the potential demographic impacts of such changes (Hauer et al. 2016, in Nat Clim Chang 3:802–806, 2017; Neumann et al. 2015; Curtis and Schneider in Popul Environ 33:28–54, 2011), localized flooding projections in the Miami Beach area (Wdowinski et al. in Ocean Coast Manag 126:1–8, 2016) and projected economic losses associated with this rise in projected SLR (Fu et al. Ocean Coast Manag 133:11–17, 2016); this research investigates the accrued current cost, in terms of real-estate dollars lost, due to recurrent tidal flooding and projected increases of flooding in Miami-Dade County. Most directly related to this line of research, Keenan et al. (2018) have recently produced results indicating that Climate Gentrification is taking place in Miami, FL with higher elevations in flood prone areas appreciating at a higher rate. In that vein of thinking, we seek to answer a question posed by such research: What is the actual accrued loss to sea-level rise over the recent past? To answer this question, we replicate well-documented estimation methods by combining publicly available sea-level rise projections, tide gauge trends, and property lot elevation data to identify areas regularly at risk of flooding. Combining recent patterns of flooding inundation with future forecasts, we find that properties projected to be inundated with tidal flooding in 2032 have lost $3.08 each year on each square foot of living area, and properties near roads that will be inundated with tidal flooding in 2032 have lost $3.71 each year on each square foot of living area. These effects total over $465 million in lost real-estate market value between 2005 and 2016 in the Miami-Dade area.     

Sport and the Cornish: difference and identity on the English periphery in the twentieth century

Cornwall differs from other English counties, not least because a significant percentage of those who live there self-identify as ‘Cornish’ rather than ‘English’ or British'. Sport has helped to underpin ‘the persistence of difference’. Distinctive versions of hurling and wrestling were key signifiers in this respect. In addition, Cornwall developed a particular affinity for rugby, similar to that found in Wales. In the late twentieth century, with indigenous Cornish culture threatened by deindustrialisation and in-migration, the county's rugby team enjoyed considerable success. Sport, in these conditions, became a signifier not merely of difference, but of a self-conscious Cornish identity.