A practical approach to goal modelling for time-constrained projects

Goal modelling is a well known rigorous method for analysing problem rationale and developing requirements. Under the pressures typical of time-constrained projects its benefits are not accessible. This is because of the effort and time needed to create the graph and because reading the results can be difficult owing to the effects of crosscutting concerns. Here we introduce an adaptation of KAOS to meet the needs of rapid turn around and clarity. The main aim is to help the stakeholders gain an insight into the larger issues that might be overlooked if they make a premature start into implementation. The method emphasises the use of obstacles, accepts under-refined goals and has new methods for managing crosscutting concerns and strategic decision making. It is expected to be of value to agile as well as traditional processes.

The calculative turn in land value capture: lessons from the English planning system

For over three decades, negotiated planning obligations have been the primary form of land value capture in England. Diffusing and evolving over the last decade, a significant policy innovation has been the use of financial calculations to estimate the extent to which policies on planning obligations for actual, proposed development projects and in plan making affect the financial viability of development. This paper assesses the extent to which the use of financial appraisals has provided a robust, just and practical procedure to support land value capture. It is concluded that development viability appraisals are saturated with intrinsic uncertainty and that land value capture that is based on such calculations is, to some extent, capricious. In addition, clear incentives for developers and land owners to bias viability calculations, the economic dependence of many viability consultants on developers and land owners, a lack of transparency, contested or ambiguous guidance and the opportunities created by input uncertainty for bias are further failings. It is argued that how viability calculations are applied has been, is being and will continue to be shaped by power relations.

Reflections on practical approaches to involving children and young people in the data analysis process

This article reflects on key methodological issues emerging from children and young people's involvement in data analysis processes. We outline a pragmatic framework illustrating different approaches to engaging children, using two case studies of children's experiences of participating in data analysis. The article highlights methods of engagement and important issues such as the balance of power between adults and children, training, support, ethical considerations, time and resources. We argue that involving children in data analysis processes can have several benefits, including enabling a greater understanding of children's perspectives and helping to prioritise children's agendas in policy and practice. (C) 2007 The Author(s). Journal compilation (C) 2007 National Children's Bureau.

A practical comparison of group-sequential and adaptive designs

Sequential methods provide a formal framework by which clinical trial data can be monitored as they accumulate. The results from interim analyses can be used either to modify the design of the remainder of the trial or to stop the trial as soon as sufficient evidence of either the presence or absence of a treatment effect is available. The circumstances under which the trial will be stopped with a claim of superiority for the experimental treatment, must, however, be determined in advance so as to control the overall type I error rate. One approach to calculating the stopping rule is the group-sequential method. A relatively recent alternative to group-sequential approaches is the adaptive design method. This latter approach provides considerable flexibility in changes to the design of a clinical trial at an interim point. However, a criticism is that the method by which evidence from different parts of the trial is combined means that a final comparison of treatments is not based on a sufficient statistic for the treatment difference, suggesting that the method may lack power. The aim of this paper is to compare two adaptive design approaches with the group-sequential approach. We first compare the form of the stopping boundaries obtained using the different methods. We then focus on a comparison of the power of the different trials when they are designed so as to be as similar as possible. We conclude that all methods acceptably control type I error rate and power when the sample size is modified based on a variance estimate, provided no interim analysis is so small that the asymptotic properties of the test statistic no longer hold. In the latter case, the group-sequential approach is to be preferred. Provided that asymptotic assumptions hold, the adaptive design approaches control the type I error rate even if the sample size is adjusted on the basis of an estimate of the treatment effect, showing that the adaptive designs allow more modifications than the group-sequential method.

Terrestrial carnivores and human food production: impact and management

1. The production of food for human consumption has led to an historical and global conflict with terrestrial carnivores, which in turn has resulted in the extinction or extirpation of many species, although some have benefited. At present, carnivores affect food production by: (i) killing human producers; killing and/or eating (ii) fish/shellfish; (iii) game/wildfowl; (iv) livestock; (v) damaging crops; (vi) transmitting diseases; and (vii) through trophic interactions with other species in agricultural landscapes. Conversely, carnivores can themselves be a source of dietary protein (bushmeat). 2. Globally, the major areas of conflict are predation on livestock and the transmission of rabies. At a broad scale, livestock predation is a customary problem where predators are present and has been quantified for a broad range of carnivore species, although the veracity of these estimates is equivocal. Typically, but not always, losses are small relative to the numbers held, but can be a significant proportion of total livestock mortality. Losses experienced by producers are often highly variable, indicating that factors such as husbandry practices and predator behaviour may significantly affect the relative vulnerability of properties in the wider landscape. Within livestock herds, juvenile animals are particularly vulnerable. 3. Proactive and reactive culling are widely practised as a means to limit predation on livestock and game. Historic changes in species' distributions and abundance illustrate that culling programmes can be very effective at reducing predator density, although such substantive impacts are generally considered undesirable for native predators. However, despite their prevalence, the effectiveness, efficiency and the benefit:cost ratio of culling programmes have been poorly studied. 4. A wide range of non-lethal methods to limit predation has been studied. However, many of these have their practical limitations and are unlikely to be widely applicable. 5. Lethal approaches are likely to dominate the management of terrestrial carnivores for the foreseeable future, but animal welfare considerations are increasingly likely to influence management strategies. The adoption of non-lethal approaches will depend upon proof of their effectiveness and the willingness of stakeholders to implement them, and, in some cases, appropriate licensing and legislation. 6. Overall, it is apparent that we still understand relatively little about the importance of factors affecting predation on livestock and how to manage this conflict effectively. We consider the following avenues of research to be essential: (i) quantified assessments of the loss of viable livestock; (ii) landscape-level studies of contiguous properties to quantify losses associated with variables such as different husbandry practices; (iii) replicated experimental manipulations to identify the relative benefit of particular management practices, incorporating (iv) techniques to identify individual predators killing stock; and (v) economic analyses of different management approaches to quantify optimal production strategies.

A practical approach to a multi-level analysis with a sparse binary outcome within a large surgical trial

Objectives: To assess the potential source of variation that surgeon may add to patient outcome in a clinical trial of surgical procedures. Methods: Two large (n = 1380) parallel multicentre randomized surgical trials were undertaken to compare laparoscopically assisted hysterectomy with conventional methods of abdominal and vaginal hysterectomy; involving 43 surgeons. The primary end point of the trial was the occurrence of at least one major complication. Patients were nested within surgeons giving the data set a hierarchical structure. A total of 10% of patients had at least one major complication, that is, a sparse binary outcome variable. A linear mixed logistic regression model (with logit link function) was used to model the probability of a major complication, with surgeon fitted as a random effect. Models were fitted using the method of maximum likelihood in SAS((R)). Results: There were many convergence problems. These were resolved using a variety of approaches including; treating all effects as fixed for the initial model building; modelling the variance of a parameter on a logarithmic scale and centring of continuous covariates. The initial model building process indicated no significant 'type of operation' across surgeon interaction effect in either trial, the 'type of operation' term was highly significant in the abdominal trial, and the 'surgeon' term was not significant in either trial. Conclusions: The analysis did not find a surgeon effect but it is difficult to conclude that there was not a difference between surgeons. The statistical test may have lacked sufficient power, the variance estimates were small with large standard errors, indicating that the precision of the variance estimates may be questionable.