Le malade génétique responsable « La loi des suspects »

A patient suffers of a genetical disease. He does not wish to inform his family. Is he responsible for a lost of chances of his parents, chances to prevent the disease, or to receive care? Is there a second class of patients?     

Holism and Horizon: Husserl and McDowell on Non-conceptual Content

John McDowell rejects the idea that non-conceptual content can rationally justify empirical claims—a task for which it is ill-fitted by its non-conceptual nature. This paper considers three possible objections to his views: he cannot distinguish empty conception from the perceptual experience of an object; perceptual discrimination outstrips the capacity of concepts to keep pace; and experience of the empirical world is more extensive than the conceptual focusing within it. While endorsing McDowell’s rejection of what he means by non-conceptual content, and appreciating his insight into the experiential synthesis of intuition and conception (in particular, its role in grasping objects), I will argue that Edmund Husserl presents an even more comprehensive account of perceptual experience that explains how we experience the contribution of receptivity and sensibility and how they cooperate in perceptual discrimination. Further, it reveals “horizons”—a unique kind of contents, surplus content (rather than independent non-conceptual content)—beyond the synthesis of intuitive and conceptual contents through which objects are grasped. Such horizons play a constitutive role, making experience with its conceptual dimensions and justificatory potential possible; they in no way function like a bare given that is to fulfill some independent justificatory role. Whereas McDowell focuses on how experience does not take place in isolation from the exercise of conceptual capacities, Husserl complements his view by situating experience in a more encompassing whole and by elucidating the surplus-horizons that exceed the conceptual content of experience; play an inseparable, constitutive role within it; and indicate the limits of conceptual comprehension.

Latent Class Models for Diary Method Data: Parameter Estimation by Local Computations

The increasing use of diary methods calls for the development of appropriate statistical methods. For the resulting panel data, latent Markov models can be used to model both individual differences and temporal dynamics. The computational burden associated with these models can be overcome by exploiting the conditional independence relations implied by the model. This is done by associating a probabilistic model with a directed acyclic graph, and applying transformations to the graph. The structure of the transformed graph provides a factorization of the joint probability function of the manifest and latent variables, which is the basis of a modified and more efficient E-step of the EM algorithm. The usefulness of the approach is illustrated by estimating a latent Markov model involving a large number of measurement occasions and, subsequently, a hierarchical extension of the latent Markov model that allows for transitions at different levels. Furthermore, logistic regression techniques are used to incorporate restrictions on the conditional probabilities and to account for the effect of covariates. Throughout, models are illustrated with an experience sampling methodology study on the course of emotions among anorectic patients. Frank Rijmen was partly supported by the Fund for Scientific Research Flanders (FWO).     

How Risk is Perceived, Constructed and Interpreted by Clients in Clinical Genetics, and the Effects on Decision Making: Systematic Review

As an individual’s understanding of their genetic risk may influence risk management decisions, it is important to understand the ways in which risk is constructed and interpreted. We systematically reviewed the literature, undertaking a narrative synthesis of 59 studies presenting data on the ways in which individuals perceive, construct and interpret their risk, and the subsequent effects. While most studies assessed perceived risk quantitatively, the combined evidence suggests individuals find risk difficult to accurately quantify, with a tendency to overestimate. Rather than being a stand-alone concept, risk is something lived and experienced and the process of constructing risk is complex and influenced by many factors. While evidence of the effects of perceived risk is limited and inconsistent, there is some evidence to suggest high risk estimations may adversely affect health and lead to inappropriate uptake of medical surveillance and preventative measures by some individuals. A more focused approach to research is needed with greater exploration of the ways in which risk is constructed, along with the development of stronger theoretical models, to facilitate effective and patient-centered counseling strategies.     

The Importance of Program Evaluation: How Can it be Applied to Diverse Genetics Education Settings?

The role of a genetic counselor often entails providing education to patient, community and/or health professional groups. While counseling supervision assists genetic counselors to be reflective about their clinical work and to enhance clinical skills, evaluation is a rather analogous process in the provision of education. Program evaluation of education activities can be applied to provide information about the needs of the target group (needs assessment), the delivery of the program (process evaluation) as well as determining the extent to which the education activity has met its intended aims (summative evaluation). Evaluation assists the educator to assess the impact of their program and provides an evidence base about genetics education. Although program evaluation can be a complex activity, the tools are ones that can be used by individuals to evaluate single or simple education activities. The components of evaluation are discussed with reference to genetic counseling practice and three very different examples of actual evaluations are provided to illustrate the diversity of evaluation strategy and programs to which it can be applied.     

Maximum likelihood estimation of latent interaction effects with the LMS method

In the context of structural equation modeling, a general interaction model with multiple latent interaction effects is introduced. A stochastic analysis represents the nonnormal distribution of the joint indicator vector as a finite mixture of normal distributions. The Latent Moderated Structural Equations (LMS) approach is a new method developed for the analysis of the general interaction model that utilizes the mixture distribution and provides a ML estimation of model parameters by adapting the EM algorithm. The finite sample properties and the robustness of LMS are discussed. Finally, the applicability of the new method is illustrated by an empirical example. This research has been supported by a grant from the Deutsche Forschungsgemeinschaft, Germany, No. Mo 474/1 and Mo 474/2. The data for the empirical example have been provided by Andreas Thiele of the University of Frankfurt, Germany. The authors are indebted to an associate editor and to three anonymous reviewers ofPsychometrika whose comments and suggestions have been very helpful.     

A New Concurrent Calibration Method for Nonequivalent Group Design under Nonrandom Assignment

This study proposes a new item parameter linking method for the common-item nonequivalent groups design in item response theory (IRT). Previous studies assumed that examinees are randomly assigned to either test form. However, examinees can frequently select their own test forms and tests often differ according to examinees’ abilities. In such cases, concurrent calibration or multiple group IRT modeling without modeling test form selection behavior can yield severely biased results. We proposed a model wherein test form selection behavior depends on test scores and used a Monte Carlo expectation maximization (MCEM) algorithm. This method provided adequate estimates of testing parameters.     

Categorical structure among shared features in networks of early-learned nouns

The shared features that characterize the noun categories that young children learn first are a formative basis of the human category system. To investigate the potential categorical information contained in the features of early-learned nouns, we examine the graph-theoretic properties of noun-feature networks. The networks are built from the overlap of words normatively acquired by children prior to 2½ years of age and perceptual and conceptual (functional) features acquired from adult feature generation norms. The resulting networks have small-world structure, indicative of a high degree of feature overlap in local clusters. However, perceptual features - due to their abundance and redundancy - generate networks more robust to feature omissions, while conceptual features are more discriminating and, per feature, offer more categorical information than perceptual features. Using a network specific cluster identification algorithm (the clique percolation method) we also show that shared features among these early-learned nouns create higher-order groupings common to adult taxonomic designations. Again, perceptual and conceptual features play distinct roles among different categories, typically with perceptual features being more inclusive and conceptual features being more exclusive of category memberships. The results offer new and testable hypotheses about the role of shared features in human category knowledge.     

项目反应时间的对数偏正态模型

近年来,项目反应时间数据的建模是心理和教育测量领域的热门方向之一。针对反应时间的对数正态模型和Box-Cox正态模型的不足,本文在van der Linden的分层模型框架下基于偏正态分布建立一个反应时间的对数线性模型,并成功给出模型参数估计的马尔科夫链蒙特卡罗（Markov Chain Monte Carlo, MCMC）算法。模拟研究和实例分析的结果均表明,与对数正态模型和Box-Cox正态模型相比,对数偏正态模型表现出更加优良的拟合效果,具有更强的灵活性和适用性。