Managing structural uncertainty in health economic decision models: a discrepancy approach

Healthcare resource allocation decisions are commonly informed by computer model predictions of population mean costs and health effects. It is common to quantify the uncertainty in the prediction due to uncertain model inputs, but methods for quantifying uncertainty due to inadequacies in model structure are less well developed. We introduce an example of a model that aims to predict the costs and health effects of a physical activity promoting intervention. Our goal is to develop a framework in which we can manage our uncertainty about the costs and health effects due to deficiencies in the model structure. We describe the concept of `model discrepancy': the difference between the model evaluated at its true inputs, and the true costs and health effects. We then propose a method for quantifying discrepancy based on decomposing the cost-effectiveness model into a series of sub-functions, and considering potential error at each sub-function. We use a variance based sensitivity analysis to locate important sources of discrepancy within the model in order to guide model refinement. The resulting improved model is judged to contain less structural error, and the distribution on the model output better reflects our true uncertainty about the costs and effects of the intervention

Quantifying institutional impacts and development synergies in water resource programs : a methodology with application to the Kala Oya basin, Sri Lanka

The success of development programs, including water resource projects, depends on two key factors: the role of underlying institutions and the impact synergies from other closely related programs. Existing methodologies have limitations in accounting for these critical factors. This paper fills this gap by developing a methodology, which quantifies both the roles that institutions play in impact generation and the extent of impact synergies that flows from closely related programs within a unified framework. The methodology is applied to the Kala Oya Basin in Sri Lanka in order to evaluate the impacts of three water-related programs and the roles of 11 institutions in the context of food security. The results provide considerable insights on the relative role of institutions and the flow of development synergies both within and across different impact pathways. The methodology can also be used to locate slack in impact chains and identify policy options to enhance the impact flows.Economic Theory&Research,Food&Beverage Industry,E-Business,Rural Poverty Reduction,Climate Change

Usability Evaluation in Virtual Environments: Classification and Comparison of Methods

Virtual environments (VEs) are a relatively new type of human-computer interface in which users perceive and act in a three-dimensional world. The designers of such systems cannot rely solely on design guidelines for traditional two-dimensional interfaces, so usability evaluation is crucial for VEs. We present an overview of VE usability evaluation. First, we discuss some of the issues that differentiate VE usability evaluation from evaluation of traditional user interfaces such as GUIs. We also present a review of VE evaluation methods currently in use, and discuss a simple classification space for VE usability evaluation methods. This classification space provides a structured means for comparing evaluation methods according to three key characteristics: involvement of representative users, context of evaluation, and types of results produced. To illustrate these concepts, we compare two existing evaluation approaches: testbed evaluation [Bowman, Johnson, & Hodges, 1999], and sequential evaluation [Gabbard, Hix, & Swan, 1999]. We conclude by presenting novel ways to effectively link these two approaches to VE usability evaluation

Attention, effort, and fatigue: Neuropsychological perspectives

Models of attention, effort, and fatigue are reviewed. Methods are discussed for measuring these phenomena from a neuropsychological and psychophysiological perspective. The following methodologies are included: (1) the autonomic measurement of cognitive effort and quality of encoding; (2) serial assessment approaches to neurophysiological assessment; and (3) the assessment of subjective reports of fatigue using multidimensional ratings and their relationship to neurobehavioral measures

How can Francis Bacon help forensic science? The four idols of human biases

Much debate has focused on whether forensic science is indeed a science. This paper is not aimed at answering, or even trying to contribute to, this question. Rather, in this paper I try to find ways to improve forensic science by identifying potential vulnerabilities. To this end I use Francis Bacon's doctrine of idols which distinguishes between different types of human biases that may prevent scientific and objective inquiry. Bacon’s doctrine contains four sources for such biases: Idols Tribus (of the 'tribe'), Idols Specus (of the 'den'/'cave'), Idols Fori (of the 'market'), and Idols Theatre (of the 'theatre'). While his 400 year old doctrine does not, of course, perfectly match up with our current world view, it still provides a productive framework for examining and cataloguing some of the potential weaknesses and limitations in our current approach to forensic science

QoE Modelling, Measurement and Prediction: A Review

In mobile computing systems, users can access network services anywhere and anytime using mobile devices such as tablets and smart phones. These devices connect to the Internet via network or telecommunications operators. Users usually have some expectations about the services provided to them by different operators. Users' expectations along with additional factors such as cognitive and behavioural states, cost, and network quality of service (QoS) may determine their quality of experience (QoE). If users are not satisfied with their QoE, they may switch to different providers or may stop using a particular application or service. Thus, QoE measurement and prediction techniques may benefit users in availing personalized services from service providers. On the other hand, it can help service providers to achieve lower user-operator switchover. This paper presents a review of the state-the-art research in the area of QoE modelling, measurement and prediction. In particular, we investigate and discuss the strengths and shortcomings of existing techniques. Finally, we present future research directions for developing novel QoE measurement and prediction technique

Assessing farmer behaviour as affected by policy and technological innovations: bio-economic farm models

Farm Management,

Online discussion compensates for suboptimal timing of supportive information presentation in a digitally supported learning environment

This study used a sequential set-up to investigate the consecutive effects of timing of supportive information presentation (information before vs. information during the learning task clusters) in interactive digital learning materials (IDLMs) and type of collaboration (personal discussion vs. online discussion) in computer-supported collaborative learning (CSCL) on student knowledge construction. Students (N = 87) were first randomly assigned to the two information presentation conditions to work individually on a case-based assignment in IDLM. Students who received information during learning task clusters tended to show better results on knowledge construction than those who received information only before each cluster. The students within the two separate information presentation conditions were then randomly assigned to pairs to discuss the outcomes of their assignments under either the personal discussion or online discussion condition in CSCL. When supportive information had been presented before each learning task cluster, online discussion led to better results than personal discussion. When supportive information had been presented during the learning task clusters, however, the online and personal discussion conditions had no differential effect on knowledge construction. Online discussion in CSCL appeared to compensate for suboptimal timing of presentation of supportive information before the learning task clusters in IDLM