SUMMARY The propensity score is the conditional probability of assignment to a particular treatment given a vector of observed covariates. Both large and small sample theory show that adjustment for the scalar propensity score is sufficient to remove bias due to all observed covariates. Applications include: (i) matched sampling on the univariate propensity score, which is a generalization of discriminant matching, (ii) multivariate adjustment by subclassification on the propensity score where the same subclasses are used to estimate treatment effects for all outcome variables and in all subpopulations, and (iii) visual representation of multivariate covariance adjustment by a twodimensional plot.

Most current models in health psychology assume that stress adversely affects physical health. We re-examined this assumption by reviewing extensive data from the literature and from six samples of our own, in which we collected measures of personality, health and fitness, stress, and current emotional functioning. Results indicate that self-report health measures reflect a pervasive mood disposition of negative affectivity (NA); self-report stress scales also contain a substantial NA component. However, although NA is correlated with health complaint scales, it is not strongly or consistently related to actual, Jong-term health status, and thus will act as a general nuisance factor in health research. Because self-report measures of stress and health both contain a significant NA component, correlations between such measures likely overestimate the true association between stress and health. Results demonstrate the importance of including different types of health measures in health psychology research. Various types of health models have been adopted by clinical, social, and medical researchers. Most of these models assume that psychosocial stressors adversely affect physical health as well as psychological well-being. In recent years, researchers have studied a number of hypothesized precursors of health, including major life changes (e.g., divorce, death of spouse or

Articial intelligence researchers attempting to create engaging apparently living creatures may nd important insight in the work of artists who have explored the idea of believable character In particular appropriately timed and clearly expressed emotion is a central requirement for believable

of access control is unfounded and inappropriate for many commercial and civilian government organizations. The paper describes a type of non-discretionary access control - role-based access control (RBAC) - that is more central to the secure processing needs of non-military systems then DAC. 1 Introduction

and culture play a central role. This has become feasible because the capital required for social production and exchange in the networked information economy is relatively cheap and widely distributed. Much of the book argues the perceived advantages of the networked information economy from a multi

Given the central role that software development plays in the delivery and application of information technology, managers are increasingly focusing on process improvement in the software development area. This demand has spurred the provision of a number of new and/or improved approaches

how it adapts to the transient computational and storage demands that occur in comprehension. Working memory plays a central role in all forms of complex thinking, such as reasoning, problem solving, and language comprehension. However, its function in language comprehension is especially evident

-level functional partitioning. These partitions are mapped into information process-ing modules. The modules are assigned to nodes of the distributed information systems. A central role is assigned to modules that mediate between the users ' workstations and data re-sources. Mediators contain

ABSTRACT: The present article examines the nature and function of human agency within the conceptual model of triadic reciprocal causation. In analyzing the operation of human agency in this interactional causal structure, social cognitive theory accords a central role to cognitive, vicarious, self

divisions of a network. Here we show that this maximization process can be written in terms of the eigenspectrum of a matrix we call the modularity matrix, which plays a role in community detection similar to that played by the graph Laplacian in graph partitioning calculations. This result leads us to a