Utility values in health technology assessments: a statistician's perspective

This paper provides an introduction to utilities for statisticians working mainly in clinical research who have not had experience of health technology assessment work. Utility is the numeric valuation applied to a health state based on the preference of being in that state relative to perfect health. Utilities are often combined with survival data in health economic modelling to obtain quality‐adjusted life years. There are several methods available for deriving the preference weights and the health states to which they are applied, and combining them to estimate utilities, and the clinical statistician has valuable skills that can be applied in ensuring the robustness of the trial design, data collection and analyses to obtain and handle this data. In addition to raising awareness of the subject and providing source references, the paper outlines the concepts and approaches around utilities using examples, discusses some of the key issues, and proposes areas where statisticians can collaborate with health economic colleagues to improve the quality of this important element of health technology assessment. Copyright © 2014 John Wiley & Sons, Ltd.     

Citizens Advice Bureaux: Problems of an Emerging Service in Rural Areas

Nineteen eighty nine marked the Golden Jubilee of the CABx in the UK. Over the past 50 years it has established itself nationally as the prime provider of generalist advice, but there are special problems associated with delivering the service in rural areas. These include: the logistical difficulties of serving remote communities with small and scattered populations; maintaining the independence of bureau, especially from the local authorities that mainly fund them; and matching the professional standards now demanded by NACAB. These issues are examined with reference to a questionnaire survey of bureaux managers in Cornwall and Devon carried out as part of the AJRBP project at the University of Exeter.     

The density of social networks and fertility decisions: evidence from south nyanza district, kenya

Demographers have argued increasingly that social interaction is an important mechanism for understanding fertility behavior. Yet it is still quite uncertain whether social learning or social influence is the dominant mechanism through which social networks affect individuals' contraceptive decisions. In this paper we argue that these mechanisms can be distinguished by analyzing the density of the social network and its interaction with the proportion of contraceptive users among network partners. Our analyses indicate that social learning is most relevant with high market activity; in regions with only modest market activity, however, social influence is the dominant means by which social networks affect women's contraceptive use.     

Discrete simulation modelling for corporate manpower planning

Manpower planners within South African companies have very few, if any, decision support tools at their disposal to assist them in the formulation of their manpower strategies. Such quantitative tools as do exist are mathematically too sophisticated to be easily understood and implemented by manpower managers who are, on the whole, non numerate. The approach proposed in this paper, namely simulation modelling, discusses and demonstrates a powerful quantitative method which is conceptually easy to understand and whose results are easily interpreted. This particular simulation model examines the impact on organisational staffing levels over time as a result of specific present/proposed manpower policies in the areas of procurement and promotion. Through manipulating the inputs, the manpower planner can, with relative ease, examine the consequences of a range of alternative policies within a very short period of time.     

Social networks and changes in contraceptive use over time: evidence from a longitudinal study in rural Kenya

The impacts of social networks on changes in contraception in rural Kenya are investigated using special data from a longitudinal household survey. An analytic model, informed by detailed knowledge of the setting, yielded estimates that indicate that (1) social networks have substantial effects even after unobserved factors (e.g., homophily) that may determine social networks are controlled; (2) controlling for these unobserved factors may substantially alter the estimated effects of networks (these controls were not used in previous studies); (3) network effects are important for both men and women; and (4) network effects are nonlinear and asymmetric, suggesting that networks provide information primarily through social learning, rather than by exerting social influence.     

The resilience of social networks to changes in mobility and propinquity

Very little is known of the resilience of social networks in situations where individuals within a social network remain in situ, but the physical links which enable interaction between them are radically altered. This paper examines the long-term disruption of social networks following the collapse of the Tasman Bridge in Hobart, Tasmania. This accident divided the city in two for almost three years and radically altered normal patterns of mobility and accessibility.     

Tracking residential outcomes of supported independent living programs for persons with serious mental illness

This study seeks to document patterns and reasons of leaving housing, and identify factors associated with different types of exits for a cohort of 452 residents with serious mental illness entering supported independent living (SIL) in Philadelphia, PA. The study cohort was tracked through an integrated administrative database comprised information on basic demographic and clinical characteristics, length of stay, homeless shelter use, and publicly funded behavioral health services use. A convenience sample of 46 SIL leavers and their support staff provided data on scenarios of leaving. The findings of this study suggest that departure from SIL is not a unitary phenomenon, but involving plausibly favorable as well as unfavorable circumstances. Multivariate analysis based on administrative tracking data suggests demographic and clinical factors, housing setting, and service use factors to have effects on leaving SIL and distinct types of exit examined in this study. Data procured from the convenience sample highlight the potential roles that program rules and resident–staff relationships play in affecting housing tenure. Implications of the findings for the development of permanent supportive housing for persons with serious mental illness are discussed.     

Technology and institutions: living in a material world

This article addresses the relationship between technology and institutions and asks whether technology itself is an institution. The argument is that social theorists need to attend better to materiality: the world of things and objects of which technical things form an important class. It criticizes the new institutionalism in sociology for its failure to sufficiently open up the black box of technology. Recent work in science and technology studies (S&TS) and in particular the sociology of technology is reviewed as another route into dealing with technology and materiality. The recent ideas in sociology of technology are exemplified with the author’s study of the development of the electronic music synthesizer.

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Estimating the Relative Density of Snapper in and around a Marine Reserve Using a Log-Linear Mixed-Effects Model

Angling from small recreational fishing boats was used as a sampling method to quantify the relative density of snapper ( Pagrus auratus ) in six areas within the Cape Rodney-Okakari Point Marine Reserve (New Zealand) and four areas adjacent to the reserve. Penalized quasi-likelihood was used to fit a log-linear mixed-effects model having area and date as fixed effects and boat as a random effect. Simulation and first-order bias correction formulae were employed to assess the validity of the estimates of the area effects. The bias correction is known to be unsuitable for general use because it typically over-estimatesbias, and this was observed here. However, it was qualitatively useful for indicating the direction of bias and for indicating when estimators were approximately unbiased. The parameter of primary interest was the ratio of snapper density in the marine reserve versus snapper density outside the reserve, and the estimator of this parameter was first-order asymptotically unbiased. This ratio of snapper densities was estimated to be 11 (±3).