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.     

Sampling schemes for price index construction: a performance comparison across the classification of individual consumption by purpose food groups

Five sampling schemes (SS) for price index construction – one cut-off sampling technique and four probability-proportional-to-size (pps) methods – are evaluated by comparing their performance on a homescan market research data set across 21 months for each of the 13 classification of individual consumption by purpose (COICOP) food groups. Classifications are derived for each of the food groups and the population index value is used as a reference to derive performance error measures, such as root mean squared error, bias and standard deviation for each food type. Repeated samples are taken for each of the pps schemes and the resulting performance error measures analysed using regression of three of the pps schemes to assess the overall effect of SS and COICOP group whilst controlling for sample size, month and population index value. Cut-off sampling appears to perform less well than pps methods and multistage pps seems to have no advantage over its single-stage counterpart. The jackknife resampling technique is also explored as a means of estimating the standard error of the index and compared with the actual results from repeated sampling.     

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.     

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.     

“Thank You for Including Us!” – Introducing a Community‐Based Collaborative Approach to Translating Clinic Materials

When working with clients in another language, having culturally relevant and properly translated clinic materials is vital to effective clinical practice. Not having them presents a barrier for bilingual therapists and their clients. This paper reviews common translation methods and introduces a multi‐level, community‐based approach for translating clinic materials for non‐English speaking clients. Informed by decolonizing practices, this five‐tier method includes members from the target community as cultural brokers to verify the accuracy and nuances of language for their cultural group, as well as a constant comparative method to ensure methodological rigor in the process of inclusion. We present community member's feedback and recommendations, as well as discuss advantages and challenges of using this collaborative culturally responsive translation method.     

ASSOCIATIONS BETWEEN AIR POLLUTION AND HOSPITAL VISITS FOR CARDIOVASCULAR DISEASES IN THE ELDERLY IN SYDNEY USING BAYESIAN STATISTICAL METHODS

Using generalized linear models (GLMs), Jalaludin  et al. (2006;  J. Exposure Analysis and Epidemiology   16 , 225–237) studied the association between the daily number of visits to emergency departments for cardiovascular disease by the elderly (65+) and five measures of ambient air pollution. Bayesian methods provide an alternative approach to classical time series modelling and are starting to be more widely used. This paper considers Bayesian methods using the dataset used by Jalaludin  et al.  (2006) , and compares the results from Bayesian methods with those obtained by Jalaludin  et al.  (2006) using GLM methods.     

Modeling Synergy and Learning under Multiple Advanced Manufacturing Technologies

The advent of the wide variety of new, highly integrated, advanced manufacturing technologies available for acquisition by a firm's managers has brought to light an accompanying set of unexpected issues. These issues include expectations for the benefits and costs of these technologies, determining the appropriate order of implementation and finding a way to justify acquisition when many of the benefits are a function of the technology's learning and synergistic effects on other operations and technologies. We present here a model that captures the interaction effects of these highly integrated technologies and discuss the data requirements for application of the construct. We then illustrate the model's workings with a number of multitechnology examples and show the danger of ignoring the synergistic and learning effects of these technologies when considering their acquisition.