bluuebunny/crossref_metadata_2025_split huggingface dataset:
PROXY CONSENT AND COUNTERFACTUALS
Authors: NAGASAWA YUJIN 
Published: October 2007

ABSTRACTWhen patients are in vegetative states and their lives are maintained by medical devices, their surrogates might offer proxy consents on their behalf in order to terminate the use of the devices. The so‐called ‘substituted judgment thesis’ has been adopted by the courts regularly in order to determine the validity of such proxy consents. The thesis purports to evaluate proxy consents by appealing to putative counterfactual truths about what the patients would choose, were they to be competent. The aim of this paper is to reveal a significant limitation of the thesis, which has hitherto been recognised only vaguely and intuitively. By appealing to the metaphysics of counterfactuals I explain how the thesis fails to determine the validity of proxy consents in a number of actual cases.
INTERNATIONAL ETHICAL REGULATIONS ON PLACEBO‐USE IN CLINICAL TRIALS: A COMPARATIVE ANALYSIS
Authors: EHNI HANS‐JÖRG , WIESING URBAN 
Published: October 2007

ABSTRACTThe ethical aspects of placebo control in clinical trials have been extensively and controversially debated in the last decade. However, a thorough analytical comparison of the different existing international regulations, their terminologies and their ethical principles concerning placebo, is still missing. The central issue in the ongoing controversy is the justification of placebo‐use, if proven treatment exists. All present versions of the examined guidelines propose such justifications, but each guideline differs from the others in relevant details. Therefore the conditions justifying placebo‐use according to each guideline are the focus of our attention. We will first propose a formalized general principle that defines the ethical acceptability of placebo‐use. Then we will analyse three categories of conditions put forward by the different documents: the risk of harm or burden, compelling scientific reasons, and the availability of proven treatment. The analysis shows important normative discrepancies and contradictions between the examined guidelines. Especially striking is the fact that some guidelines allow the participants in clinical trials to be exposed to a risk of serious harm, while others do not. Finally, we try to show how the normative difference of each guideline could influence the decision of researchers or IRBs concerning the ethical acceptabililty of placebo‐use.
AUTHORITATIVE REGULATION AND THE STEM CELL DEBATE
Authors: CAPPS BENJAMIN 
Published: October 2007

ABSTRACTIn this paper I argue that liberal democratic communities are justified in regulating the activities of their members because of the inevitable existence of conflicting conceptions of what is considered as morally right. This will often lead to tension and disputes, and in such circumstances, reliance on peaceful or orderly co‐existence will not normally suffice. In such pluralistic societies, the boundary between permissible and impermissible activities will be unclear; and this becomes a particular concern in controversial issues which raise specific anxieties and uncertainty. One context that has repeatedly raised issues in this regard is that of biotechnology and, in particular, the recent stem cell debate, on which this paper concentrates. While such developments have the potential to make significant improvements to therapeutic progress, we should also be sceptical because predicting the impact of these developments remains uncertain and complex.For the sake of socio‐political stability, it will therefore be necessary to enact and enforce rules which limit these competing claims in public policy but which may not be compatible with what individual moral commitments ideally permit. One way to achieve this is to establish procedural frameworks to resolve potential disputes in the public sphere about what is right, wrong, or permissible conduct. I argue that for one to commit to authoritative regulation, an idea of harm prevention through state intervention is necessary; and that this requires optimum mechanisms of procedure which allow the individual the opportunity to compromise and yet to continue to oppose or fight for changes as demanded by his or her moral position.
RATIONALIZING VACCINE INJURY COMPENSATION
Authors: MELLO MICHELLE M. 
Published: October 2007

ABSTRACTLegislation recently adopted by the United States Congress provides producers of pandemic vaccines with near‐total immunity from civil lawsuits without making individuals injured by those vaccines eligible for compensation through the Vaccine Injury Compensation Program. The unusual decision not to provide an alternative mechanism for compensation is indicative of a broader problem of inconsistency in the American approach to vaccine‐injury compensation policy. Compensation policies have tended to reflect political pressures and economic considerations more than any cognizable set of principles. This article identifies a set of ethical principles bearing on the circumstances in which vaccine injuries should be compensated, both inside and outside public health emergencies. A series of possible bases for compensation rules, some grounded in utilitarianism and some nonconsequentialist, are discussed and evaluated. Principles of fairness and reasonableness are found to constitute the strongest bases. An ethically defensible compensation policy grounded in these principles would make a compensation fund available to all individuals with severe injuries and to individuals with less‐severe injuries whenever the vaccination was required by law or professional duty.
Contradictions between the virtual and physical high school classroom: A third‐generation Activity Theory perspective
Authors: Murphy Elizabeth , Manzanares María A. Rodríguez 
Published: October 2007

AbstractThis paper uses a third‐generation Activity Theory perspective to gain insight into the contradictions between the activity systems of the physical and virtual high school classroom from the perspective of teachers who had transitioned from one system to the other. Data collection relied on semi‐structured interviews conducted with e‐teachers as well as management/support personnel of an organisation charged with delivering web‐based high school courses in the Canadian province of Newfoundland and Labrador. Contradictions related to time and workload, physical presence, interaction and rapport building, and use of direct messaging and email. The contradictions can be explained by a difference between the mediating tools in each activity system. The absence in the virtual classroom of body language and visual presence as mediators requires e‐teachers to find new ways of interacting and building rapport and necessitates a shift from a practice of controlling to engaging students’ attention.
Measuring the quality of e‐learning
Authors: Hay David B. , Kehoe Caroline , Miquel Marc E. , Hatzipanagos Stylianos , Kinchin Ian M. , Keevil Steve F. , Lygo‐Baker Simon 
Published: October 2007

AbstractThis paper shows how concept mapping can be used to measure the quality of e‐learning. Six volunteers (all of them 3rd‐year medical students) took part in a programme of e‐learning designed to teach the principles of magnetic resonance imaging (MRI). Their understanding of MRI was measured before and after the course by the use of concept mapping. The quality of change in individuals' maps was assessed using criteria developed to distinguish between meaningful and rote‐learning outcomes. Student maps were also scored for evidence of conceptual richness and understanding. Finally, each map was compared directly with the content of the electronic teaching material.The results show that many of the student misconceptions were put right in the course of their learning but that many of the key concepts introduced in the teaching were ignored (or sometimes learnt by rote) by the students. This was because the teaching material locked these new ideas in structures and terminology that precluded meaning‐making among non‐experts. Our data suggest that students' prior knowledge is a key determinant of meaningful learning. We suggest that this must be acknowledged if the design and use of electronic teaching material is also to be meaningful. Ultimately, measures of student learning are the only authentic indicators of the quality of teaching through technology.
Increasing interactivity in blended classrooms through a cutting‐edge mobile learning system
Authors: Shen Ruimin , Wang Minjuan , Pan Xiaoyan 
Published: October 2007

AbstractChinese classrooms, whether on school grounds or online, have long suffered from a lack of interactivity. Many online classes simply provide recorded lectures to which students listen after downloading. This format only reinforces the negative effects of passive non‐participatory learning. At the e‐Learning Lab of Shanghai Jiaotong University researchers and developers actively seek technologic interventions that can greatly increase interactivity in blended classes. They developed a cutting‐edge mobile learning system that can deliver live broadcast of real‐time classroom teaching to online students with mobile devices. Their system allows students to customise means of content‐reception, based on when and where the students are tuning in to the broadcast. The system also supports short text messaging and instant polls. Through these venues, students can ask questions and make suggestions in real time, and the instructor can address them immediately. Here we describe this system in detail, and also report results from a test implementation of the system with a blended classroom of 1000 students (250 campus and 750 online).
Does the discussion help? The impact of a formally assessed online discussion on final student results
Authors: Palmer Stuart , Holt Dale , Bray Sharyn 
Published: October 2007

AbstractWhile there is agreement that participation in online asynchronous discussions can enhance student learning, it has also been identified that there is a need to investigate the impact of participation in online discussions on student course performance. This paper presents a case study based on an undergraduate engineering management unit employing a formally assessed online discussion area. It was observed that while many students read a significant number of discussion postings, generally, the posting of new and reply messages occurred at the minimum level required to qualify for the assignment marks. Based on correlation and multiple regression analysis, it was observed that two variables were significantly related to a student's final unit mark—prior academic ability and the number of new postings made to the online discussion. Each new posting contributed three times as much to the final unit mark as its nominal assessment value, suggesting that the work in preparing their new discussion postings assisted students in the completion of a range of assessable tasks for the unit. The number of postings read was not significantly correlated with the final unit mark, suggesting that passive lurking in this online discussion did not significantly contribute to student learning outcomes.
Student‐facilitators' roles in moderating online discussions
Authors: Wang Qiyun 
Published: October 2007

AbstractIntellectual, social, managerial and technical are four commonly reported categories of facilitation in online discussions. The purpose of this study was to investigate whether these four broad categories of facilitation were equally applied in online discussions and which specific skills were perceived to be more important. In this study, students were facilitators of online discussions. Each student‐facilitator led a group discussion and participated in two additional discussions moderated by other student‐facilitators. Three groups of students were selected for data collection. Results indicated that the intellectual, social and managerial categories of facilitation were highly applied, while technical facilitation was less used in the online discussions. Also, summarising discussions was perceived to be the top facilitation skill. This paper presents findings of the study and discusses issues involved in the study.
Parameter Estimation for Differential Equations: a Generalized Smoothing Approach
Authors: Ramsay J. O. , Hooker G. , Campbell D. , Cao J. 
Published: October 2007

SummaryWe propose a new method for estimating parameters in models that are defined by a system of non-linear differential equations. Such equations represent changes in system outputs by linking the behaviour of derivatives of a process to the behaviour of the process itself. Current methods for estimating parameters in differential equations from noisy data are computationally intensive and often poorly suited to the realization of statistical objectives such as inference and interval estimation. The paper describes a new method that uses noisy measurements on a subset of variables to estimate the parameters defining a system of non-linear differential equations. The approach is based on a modification of data smoothing methods along with a generalization of profiled estimation. We derive estimates and confidence intervals, and show that these have low bias and good coverage properties respectively for data that are simulated from models in chemical engineering and neurobiology. The performance of the method is demonstrated by using real world data from chemistry and from the progress of the autoimmune disease lupus.
Measurement Error Modelling with an Approximate Instrumental Variable
Authors: Gustafson Paul 
Published: October 2007

SummaryConsider using regression modelling to relate an exposure (predictor) variable to a disease outcome (response) variable. If the exposure variable is measured with error, but this error is ignored in the analysis, then misleading inferences can result. This problem is well known and has spawned a large literature on methods which adjust for measurement error in predictor variables. One theme is that the requisite assumptions about the nature of the measurement error can be stronger than what is actually known in many practical situations. In particular, the assumptions that are required to yield a model which is formally identified from the observable data can be quite strong. The paper deals with one particular strategy for measurement error modelling, namely that of seeking an instrumental variable, i.e. a covariate S which is associated with exposure and conditionally independent of the outcome given exposure. If these two conditions hold exactly, then we call S an exact instrumental variable, and an identified model results. However, the second is not checkable empirically, since the actual exposure is unobserved. In practice then, investigators typically seek a covariate which is plausibly thought to satisfy it. We study inferences which acknowledge the approximate nature of this assumption. In particular, we consider Bayesian inference with a prior distribution that posits that S is probably close to conditionally independent of outcome given exposure. We refer to this as an approximate instrumental variable assumption. Although the approximate instrumental variable assumption is more realistic for most applications, concern arises that a non-identified model may result. Thus the paper contrasts inferences arising from the approximate instrumental variable assumption with their exact instrumental variable counterparts, with particular emphasis on the benefit of basing inferences on a more realistic model versus the cost of basing inferences on a non-identified model.
Order-Free Co-Regionalized Areal Data Models with Application to Multiple-Disease Mapping
Authors: Jin Xiaoping , Banerjee Sudipto , Carlin Bradley P. 
Published: October 2007

SummaryWith the ready availability of spatial databases and geographical information system software, statisticians are increasingly encountering multivariate modelling settings featuring associations of more than one type: spatial associations between data locations and associations between the variables within the locations. Although flexible modelling of multivariate point-referenced data has recently been addressed by using a linear model of co-regionalization, existing methods for multivariate areal data typically suffer from unnecessary restrictions on the covariance structure or undesirable dependence on the conditioning order of the variables. We propose a class of Bayesian hierarchical models for multivariate areal data that avoids these restrictions, permitting flexible and order-free modelling of correlations both between variables and across areal units. Our framework encompasses a rich class of multivariate conditionally autoregressive models that are computationally feasible via modern Markov chain Monte Carlo methods. We illustrate the strengths of our approach over existing models by using simulation studies and also offer a real data application involving annual lung, larynx and oesophageal cancer death-rates in Minnesota counties between 1990 and 2000.
Statistical Classification with Missing Covariates
Authors: Mojirsheibani Majid , Montazeri Zahra 
Published: October 2007

SummarySome results related to statistical classification in the presence of missing covariates are presented. We derive representations for the best (Bayes) classifier when some of the covariates can be missing; this is done without imposing any assumptions on the underlying missing probability mechanism. Furthermore, without assuming any missingness-at-random type of conditions, we also construct Bayes consistent classifiers that do not require any imputation-based techniques. Both parametric and non-parametric situations are considered but the emphasis is on the latter. In addition to simple missingness patterns, we also consider the full Swiss cheese model, where the missing covariates can be anywhere. Both mechanics and the theoretical validity of our results are discussed.
Non-Parametric Regression Estimation from Data Contaminated by a Mixture of Berkson and Classical Errors
Authors: Carroll Raymond J. , Delaigle Aurore , Hall Peter 
Published: October 2007

SummaryEstimation of a regression function is a well-known problem in the context of errors in variables, where the explanatory variable is observed with random noise. This noise can be of two types, which are known as classical or Berkson, and it is common to assume that the error is purely of one of these two types. In practice, however, there are many situations where the explanatory variable is contaminated by a mixture of the two errors. In such instances, the Berkson component typically arises because the variable of interest is not directly available and can only be assessed through a proxy, whereas the inaccuracy that is related to the observation of the latter causes an error of classical type. We propose a non-parametric estimator of a regression function from data that are contaminated by a mixture of the two errors. We prove consistency of our estimator, derive rates of convergence and suggest a data-driven implementation. Finite sample performance is illustrated via simulated and real data examples.
Semiparametric Estimation of Treatment Effects Given Base-Line Covariates on an Outcome Measured After a Post-Randomization Event Occurs
Authors: Jemiai Yannis , Rotnitzky Andrea , Shepherd Bryan E. , Gilbert Peter B. 
Published: October 2007

SummaryWe consider estimation, from a double-blind randomized trial, of treatment effect within levels of base-line covariates on an outcome that is measured after a post-treatment event E has occurred in the subpopulation 𝒫E,E that would experience event E regardless of treatment. Specifically, we consider estimation of the parameters γ indexing models for the outcome mean conditional on treatment and base-line covariates in the subpopulation 𝒫E,E. Such parameters are not identified from randomized trial data but become identified if additionally it is assumed that the subpopulation 𝒫E,E of subjects that would experience event E under the second treatment but not under the first is empty and a parametric model for the conditional probability that a subject experiences event E if assigned to the first treatment given that the subject would experience the event if assigned to the second treatment, his or her outcome under the second treatment and his or her pretreatment covariates. We develop a class of estimating equations whose solutions comprise, up to asymptotic equivalence, all consistent and asymptotically normal estimators of γ under these two assumptions. In addition, we derive a locally semiparametric efficient estimator of γ. We apply our methods to estimate the effect on mean viral load of vaccine versus placebo after infection with human immunodeficiency virus (the event E) in a placebo-controlled randomized acquired immune deficiency syndrome vaccine trial.
A New Test for the Parametric Form of the Variance Function in Non-Parametric Regression
Authors: Dette Holger , Neumeyer Natalie , Keilegom Ingrid Van 
Published: October 2007

SummaryIn the common non-parametric regression model the problem of testing for the parametric form of the conditional variance is considered. A stochastic process based on the difference between the empirical processes that are obtained from the standardized non-parametric residuals under the null hypothesis (of a specific parametric form of the variance function) and the alternative is introduced and its weak convergence established. This result is used for the construction of a Kolmogorov–Smirnov and a Cramér–von Mises type of statistic for testing the parametric form of the conditional variance. The consistency of a bootstrap approximation is established, and the finite sample properties of this approximation are investigated by means of a simulation study. In particular the new procedure is compared with some of the currently available methods for this problem.
The Turing Test as Interactive Proof
Authors: Shieber Stuart M. 
Published: October 2007

AbstractIn 1950, Alan Turing proposed his eponymous test based on indistinguishability of verbal behavior as a replacement for the question “Can machines think?” Since then, two mutually contradictory but well‐founded attitudes towards the Turing Test have arisen in the philosophical literature. On the one hand is the attitude that has become philosophical conventional wisdom, viz., that the Turing Test is hopelessly flawed as a sufficient condition for intelligence, while on the other hand is the overwhelming sense that were a machine to pass a real live full‐fledged Turing Test, it would be a sign of nothing but our orneriness to deny it the attribution of intelligence. The arguments against the sufficiency of the Turing Test for determining intelligence rely on showing that some extra conditions are logically necessary for intelligence beyond the behavioral properties exhibited by an agent under a Turing Test. Therefore, it cannot follow logically from passing a Turing Test that the agent is intelligent. I argue that these extra conditions can be revealed by the Turing Test, so long as we allow a very slight weakening of the criterion from one of logical proof to one of statistical proof under weak realizability assumptions. The argument depends on the notion of interactive proof developed in theoretical computer science, along with some simple physical facts that constrain the information capacity of agents. Crucially, the weakening is so slight as to make no conceivable difference from a practical standpoint. Thus, the Gordian knot between the two opposing views of the sufficiency of the Turing Test can be cut.