Tracing the Density Impulse in Rural Settlement Systems: A Quantitative Analysis of the Factors Underlying Rural Population Density Across South-Eastern Australia, 1981–2001

Rural population density has a very significant independent influence over important socio-economic and demographic characteristics of developed world rural communities. Additionally, it is a fundamental variable in public policy and planning, both expressing and influencing the relative cost-efficiency of servicing populations. Yet density is itself produced by more fundamental qualities (e.g. environmental resources, nature and time of colonisation) which may themselves change over time. Treating rural population density as a dependent variable produced by a wide variety of factors, we build and test two causal models that attempt to explain the observed pattern of rural densities across south-eastern Australia (n = 414 communities). We distinguish between a “productivist” model—applicable for most of white Australia’s history—and a consumptionist model that takes account of recent counter-urbanisation trends. These models are applied to the entire study area and, in recognition of the study area’s internal heterogeneity, to five clusters of communities. In the drier inland and remoter zones, the productivist model exhibits the greatest explanatory power, while in the more accessible and well-watered “multifunctional” zones, an expanded model that incorporates a measure of “amenity” produces the best results. The research finds that simple environmental factors, coupled with relative location within the national space economy, act as dominant controls over rural population density in early 21st century Australia.

Factors associated with exercise participation in adults with arthritis

Most people with arthritis are not regularly active. Understanding what factors influence exercise is essential for designing programs to increase participation. The objective of this study was to examine the correlates of exercise in people with arthritis. Using a cross-sectional design, sociodemographic, health-related, and psychosocial variables were collected from community-dwelling individuals with arthritis (N = 141). Associations with exercise level were examined with bivariate statistics (ANOVAs, chi-squares) and logistic-regression analyses. Exercisers were less likely than nonexercisers and insufficiently active people to report that arthritis negatively affected their physical and social functioning, and they reported more positive affect and greater self-efficacy (p < .05). Exercisers also reported less pain than nonexercisers (p < .05). In multiple logistic-regression analyses, self-efficacy and physical limitations remained independent predictors of exercise. The results suggest the need to target exercise self-efficacy when designing exercise interventions. Results also suggest the need to tailor exercise programs to individuals' physical limitations.     

Adjusting overall survival for treatment switches: commonly used methods and practical application

In parallel group trials, long‐term efficacy endpoints may be affected if some patients switch or cross over to the alternative treatment arm prior to the event. In oncology trials, switch to the experimental treatment can occur in the control arm following disease progression and potentially impact overall survival. It may be a clinically relevant question to estimate the efficacy that would have been observed if no patients had switched, for example, to estimate ‘real‐life’ clinical effectiveness for a health technology assessment. Several commonly used statistical methods are available that try to adjust time‐to‐event data to account for treatment switching, ranging from naive exclusion and censoring approaches to more complex inverse probability of censoring weighting and rank‐preserving structural failure time models. These are described, along with their key assumptions, strengths, and limitations. Best practice guidance is provided for both trial design and analysis when switching is anticipated. Available statistical software is summarized, and examples are provided of the application of these methods in health technology assessments of oncology trials. Key considerations include having a clearly articulated rationale and research question and a well‐designed trial with sufficient good quality data collection to enable robust statistical analysis. No analysis method is universally suitable in all situations, and each makes strong untestable assumptions. There is a need for further research into new or improved techniques. This information should aid statisticians and their colleagues to improve the design and analysis of clinical trials where treatment switch is anticipated. Copyright © 2013 John Wiley & Sons, Ltd.     

On an Integral Related to the Burr XII Distribution

This article considers an integral which arises in the consideration of the Fisher Information for Pareto, Burr, and related distributions, and which has also been considered by Brazauskas (2003 Brazauskas , V. ( 2003 ). Information matrix for Pareto (IV), Burr, and related distributions . Commun. Statist. Theor. Meth. 32 : 315 – 325 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). The approach here is, arguably, simpler, and the methods involved in establishing it here are capable of generalization.     

PERCEIVED INFORMATION STRUCTURE: IMPLICATIONS FOR DECISION SUPPORT SYSTEM DESIGN

Top-level decision making in business organizations is characterized by high degrees of uncertainty, incomplete information, and conflicting objectives. To support top-level decision making effectively, decision support systems (DSSs) have been proposed. Information supplied by a DSS must be selective in that not all possible information sets may be feasibly or economically represented in the data base. This study suggests that discovery of perceptual complexity (dimensionality) of information items, and the subsequent categorization of decision makers having the same perceptions of those information items, is a first step in the ultimate design of an effective DSS. Through the use of multidimensional scaling in a field setting, this study shows the feasibility of creating relatively homogeneous groups of decision makers according to the content and number of dimensions associated with various information items. Further results of the research suggest that information can be tailored to classes of users, which has cost-benefit implications as well as the potential to improve the quality of the resultant decisions.     

Much ado about very little: The dubious connection between ethnic minority business policy and ethnic minority entrepreneurship

This article presents a historical reprise of 40 years of policy interest in ethnic minority businesses in the UK. It contrasts the pronouncements of policymakers with the reality of ethnic minority entrepreneurship. Such an exercise is surprisingly rare given the activism of policymakers in this arena and growing scholarly interest in this field. Our historical overview is informed by a novel research method that plots references to ethnic minority entrepreneurship in the British Houses of Parliament. Though the UK has been the site of some interesting policy experiments on ethnic minority entrepreneurship, their impact has been slight when set against the context of broader political-economic change.