Relaxation Penalties and Priors for Plausible Modeling of Nonidentified Bias Sources

In designed experiments and surveys, known laws or design feat ures provide checks on the most relevant aspects of a model and identify the target parameters. In contrast, in most observational studies in the health and social sciences, the primary study data do not identify and may not even bound target parameters. Discrepancies between target and analogous identified parameters (biases) are then of paramount concern, which forces a major shift in modeling strategies. Conventional approaches are based on conditional testing of equality constraints, which correspond to implausible point-mass priors. When these constraints are not identified by available data, however, no such testing is possible. In response, implausible constraints can be relaxed into penalty functions derived from plausible prior distributions. The resulting models can be fit within familiar full or partial likelihood frameworks. The absence of identification renders all analyses part of a sensitivity analysis. In this view, results from single models are merely examples of what might be plausibly inferred. Nonetheless, just one plausible inference may suffice to demonstrate inherent limitations of the data. Points are illustrated with misclassified data from a study of sudden infant death syndrome. Extensions to confounding, selection bias and more complex data structures are outlined.Comment: Published in at http://dx.doi.org/10.1214/09-STS291 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Exploring the use of a gap analysis approach for quantitative evaluation of teaching effectiveness

The article investigates the potential of an adaptation of the SERVQUAL approach for obtaining student feedback. The technique involves measuring the gaps between what students want in terms of teaching delivery and what they actually receive, thereby enabling areas for improvement to be identified. Improving the effectiveness of classroom teaching so as to enhance the students’ learning experience is frequently viewed as a key to raising retention rates. Student feedback, just one of many indicators of teaching quality, plays a crucial role in teaching enhancement. Whilst informal methods are also useful for teaching appraisal, this project investigates a formal approach for obtaining student feedback. If a SERVQUAL type approach can be adapted using a fairly short questionnaire then it may prove a useful alternative / supplement to traditional survey methods for evaluating teaching effectiveness. The project focuses on several undergraduate and postgraduate business Marketing modules and was conducted to see whether the technique offers any particular benefits which the Department of Business and Service Sector Management may use in the future

Comment: The Need for Syncretism in Applied Statistics

Comment on "The Need for Syncretism in Applied Statistics" [arXiv:1012.1161]Comment: Published in at http://dx.doi.org/10.1214/10-STS308A the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Decentralized control of Markovian decision processes: Existence Sigma-admissable policies

The problem of formulating and analyzing Markov decision models having decentralized information and decision patterns is examined. Included are basic examples as well as the mathematical preliminaries needed to understand Markov decision models and, further, to superimpose decentralized decision structures on them. The notion of a variance admissible policy for the model is introduced and it is proved that there exist (possibly nondeterministic) optional policies from the class of variance admissible policies. Directions for further research are explored

An Opportunity Not To Be Missed: Vaccination as an Entry Point for Hygiene Promotion and Diarrhoeal Disease Reduction in Nepal

This report aims to ascertain whether or not vaccination programmes offer a useful entry point for hygiene promotion and to define options for piloting and scaling up of a hygiene promotion intervention in Nepal

Optically driven silicon-based quantum gates with potential for high-temperature operation

We propose a new approach to constructing gates for quantum information processing, exploiting the proper-ties of impurities in silicon. Quantum information, embodied in electron spins bound to deep donors, is coupled via optically induced electronic excitation. Gates are manipulated by magnetic fields and optical light pulses; individual gates are addressed by exploiting spatial and spectroscopic selectivity. Such quantum gates do not rely on small energy scales for operation, so might function at or near room temperature. We show the scheme can produce the classes of gates necessary to construct a universal quantum computer

Parametric CubeSat flight simulation architecture

This paper presents the architecture of a system of models that provides realistic simulation of the dynamic, in-orbit behaviour of a CubeSat. Time-dependent relationships between sub-systems and between the satellite and external nodes (ground stations and celestial bodies) are captured through numerical analysis of a multi-disciplinary set of state variables including position, attitude, stored energy, stored data and system temperature. Model-Based Systems Engineering and parametric modelling techniques are employed throughout to help visualise the models and ensure flexibility and expandability. Operational mode states are also incorporated within the design, allowing the systems engineer to assess flight behaviour over a range of mission scenarios. Finally, both long and short term dynamics are captured using a coupled-model philosophy; described as Lifetime and Operations models. An example mission is analysed and preliminary results are presented as an illustration of early capabilities

Through-life modelling of nano-satellite power system dynamics

This paper presents a multi-fidelity approach to finding optimal, mission-specific power system configurations for CubeSats. The methodology begins with propagation of the orbit elements over the mission lifetime, via a continuous-time model, accounting for orbital perturbations (drag, solar radiation and non-spherical geo-potential). Analytical sizing of the power system is then achieved at discrete long-term intervals, to account for the effects of variations in environmental conditions over the mission life. This sizing is based on worst case power demand and provides inputs to a numerical assessment of the in-flight energy collection for each potential solar array deployment configuration. Finally, two objective functions (minimum deviation about the orbit average power and maximum average power over the entire mission) are satisfied to identify the configurations most suitable for the specific mission requirement. Most Nano-satellites are designed with relatively simple, static-models only and tend to be over-engineered as a result, often leading to a power-limited system. The approach described here aims to reduce the uncertainty in energy collection during flight and provide a robust approach to finding the optimal solution for a given set of mission requirements

Fractionation of fluorine, chlorine and other trace elements during differentiation of a tholeiitic magma

Trace element variation during magmetic differentiation of tholeiitic rock sample from Tasmania - chlorine and fluorine in hydroxyl lattice site