Subjectivity and unconsciousness

Concepts of the unconscious were crucial to both Jung's and Freud's thinking. Psychoanalytic and analytical psychological views of the unconscious are compared and contrasted, and both are critically reviewed. It is suggested that we need to revise our conceptualization so as to take better account of the role of the analyst's expectations and inferences, and therefore of his or her subjectivity, whenever he or she makes a clinical judgement that unconscious mental processes are in operation. Some technical implications of a revised definition of unconsciousness are considered, especially indications for self-disclosure by an analyst of his or her own experience of events within the treatment.     

Bayesian inference for finite mixtures of generalized linear models with random effects

We present an hierarchical Bayes approach to modeling parameter heterogeneity in generalized linear models. The model assumes that there are relevant subpopulations and that within each subpopulation the individual-level regression coefficients have a multivariate normal distribution. However, class membership is not known a priori, so the heterogeneity in the regression coefficients becomes a finite mixture of normal distributions. This approach combines the flexibility of semiparametric, latent class models that assume common parameters for each sub-population and the parsimony of random effects models that assume normal distributions for the regression parameters. The number of subpopulations is selected to maximize the posterior probability of the model being true. Simulations are presented which document the performance of the methodology for synthetic data with known heterogeneity and number of sub-populations. An application is presented concerning preferences for various aspects of personal computers.     

过度自信的研究展望

过度自信是个体高估自身判断精确度的一种认知偏差。过高估计和过高定位作为过度自信的两种主要类型被认为是个体在评价其绝对能力和相对能力时的表现。一般认为信息加工的偏差与判断误差的无偏性是造成过高估计的主要原因。自我提升动机、权重差异与信息的差异被认为是产生过高定位的原因。但是过度自信的这两种类型却在不同难度的任务巾出现了分离现象。最近,研究者提出了贝叶斯过度自信,用贝叶斯推理对不同任务中二者的分离进行了整合。过度自信产生的原因和内在心理机制、过度自信对决策的影响以及过度自信中的个体差异研究将会成为该领域日后研究的趋势。     

Where do "constraints" come from? A comparison between inferences in biology and in word learning

In this paper, as a commentary on the papers in this special issue, the nature of constraints is discussed in terms of the comparison between inferences in biology and in word learning. Young children's inferences in biology could be constrained by three sources of information: factual knowledge, expectations based on a theory, and ontological knowledge. For example, young children's inference about the length of noses could be constrained by the facts the children know about the animals, the similarity between the animals and humans, and the ontological distinction between living things and nonliving things. In the same way, young children might figure out word meanings by linguistic and pragmatic knowledge, expectations of word meanings (e.g., the whole-object assumption), and ontological knowledge. Interactions among these sources of knowledge are documented by the papers in this special issue and related studies. It is argued that learning biases such as the whole-object assumption could not be induced only by linguistic and pragmatic cues in a social context, but should be regarded as a product of the interaction between a social context and children's theories.     

Principles for Designing Randomized Preventive Trials in Mental Health: An Emerging Developmental Epidemiology Paradigm

An emerging population-based paradigm is now being used to guide the design of preventive trials used to test developmental models. We discuss elements of the designs of several ongoing randomized preventive trials involving reduction of risk for children of divorce, for children who exhibit behavioral or learning problems, and for children whose parents are being treated for depression. To test developmental models using this paradigm, we introduce three classes of design issues: design for prerandomization, design for intervention, and design for postintervention. For each of these areas, we present quantitative results from power calculations. Both scientific and cost implications of these power calculations are discussed in terms of variation among subjects on preintervention measures, unit of intervention, assignment, balancing, number of pretest and posttest measures, and the examination of moderation effects.     

Binary action based estimation of propensities

An observer is to make inference statements about a quantityp, called apropensity and bounded between 0 and 1, based on the observation thatp does or does not exceed a constantc. The propensityp may have an interpretation as a proportion, as a long-run relative frequency, or as a personal probability held by some subject. Applications in medicine, engineering, political science, and, most especially, human decision making are indicated. Bayes solutions for the observer are obtained based on prior distributions in the mixture of beta distribution family; these are then specialized to power-function prior distributions. Inference about logp and log odds is considered. Multiple-action problems are considered in which the focus of inference shifts to theprocess generating the propensitiesp, both in the case of a process parameter known to the subject and unknown. Empirical Bayes techniques are developed for observer inference aboutc when is known to the subject. A Bayes rule, a minimax rule and a beta-minimax rule are constructed for the subject when he is uncertain about.This research was partially supported by the Defense Advanced Research Projects Agency of the Department of Defense and was monitored by ONR under Contract No. N00014-77-C-0095. Any opinions, findings, conclusions or recommendations expressed herein are those of the author and do not necessarily reflect the views of the Defense Advanced Research Projects Agency, the Office of Naval Research, or Carnegie-Mellon University.     

Clinical judgment in forensic neuropsychology: A comment on the risks of claiming more than can be delivered

There is a vast and growing literature in psychology demonstrating the general limits of human judgment and clinical inference. These findings clearly apply in the new specialty of clinical neuropsychology, and there is little empirical research to support the widespread belief that judgmental accuracy correlates substantially with experience, professional stature, or reputation as a neuropsychologist. However, the demand characteristics of expert testimony in the forensic arena may encourage individual neuropsychologists to state or intimate that they have unique or special expertise in understanding brain-behavior relationships, or in predicting outcomes following cerebral insult or injury. These claims will be increasingly difficult to substantiate as attorneys become more conversant with the literature on human judgment.