Cox regression analysis in presence of collinearity: an application to assessment of health risks associated with occupational radiation exposure

This paper considers the analysis of time to event data in the presence of collinearity between covariates. In linear and logistic regression models, the ridge regression estimator has been applied as an alternative to the maximum likelihood estimator in the presence of collinearity. The advantage of the ridge regression estimator over the usual maximum likelihood estimator is that the former often has a smaller total mean square error and is thus more precise. In this paper, we generalized this approach for addressing collinearity to the Cox proportional hazards model. Simulation studies were conducted to evaluate the performance of the ridge regression estimator. Our approach was motivated by an occupational radiation study conducted at Oak Ridge National Laboratory to evaluate health risks associated with occupational radiation exposure in which the exposure tends to be correlated with possible confounders such as years of exposure and attained age. We applied the proposed methods to this study to evaluate the association of radiation exposure with all-cause mortality.     

AN EMPIRICAL EXAMINATION OF SOCIAL POWER IN TERMS OF DECISION THEORY1

The paper presents an extension of decision theory to the analysis of social power. The power of a person, A, over another person, B, is viewed in terms of the effect A has on B's decision. The analysis is based on the idea that B's decision regarding the performance of alternative behaviors is a function of 1) B's utility for the consequences of the behaviors and 2) B's subjective probabilities that the behaviors will lead to these consequences. In these terms, A's power over B lies in A's ability to mediate various consequences for B, contingent upon B's compliance or noncompliance. Subjects were asked to consider eight situations in which hypothetical individuals had to make a choice between two courses of action. In each situation another person (A) was attempting to induce the hypothetical individual (B) to choose one of the alternatives, while various situational factors were influencing B to choose the other alternative. The subjects were asked to consider B's utilities and subjective probabilities in each situation and to indicate whether or not B should comply with A and to make ratings of A's power. The decision theory analysis did well in predicting whether or not subjects would indicate that B should comply with A. Also, subjects generally were able to correctly specify whether A or the situational factors had more influence over B's decision. Finally, the subjects' ratings of A's power in the eight situations were highly related to the decision theoretic measure of power.     

Advanced Behavioral Applications in Schools: A Review of R. Douglas Greer’s Designing Teaching Strategies: An Applied Behavior Analysis Systems Approach

The Analysis of Verbal Behavior - R. Douglas Greer1s Designing Teaching Strategies is an important book directed to advanced students in applied behavior analysis for classrooms. This review...     

The role of small firms in the emergence of new technologies

It is clear from research policy statements throughout Europe and in the USA and Japan that governments are becoming increasingly interested in the well-being of small firms. This is based on a belief in their ability to generate employment, their potential for the industrial regeneration of the so-called development areas and their ability to produce technological innovations. It is to this latter issue—the innovation potential of small firms—that this article is addressed. Further, while most studies of the role of small firms in innovation have been concerned with ‘innovation counts’ and have adopted a rather static approach, we are here concerned with their role in the dynamics of the introduction and diffusion of new technologies, specifically semiconductors and computer aided design (CAD). Moreover, there has in the past been a tendency to emphasize the role of the small firms or the role of large firms in innovation; we reject this rather sterile view and demonstrate the interrelationship between the two. In both areas—semiconductors and CAD—the initial breakthroughs were made in the R&D laboratories of large companies which produced components and equipment for their own use; it was through the actions of new technology-based small firms that these innovations were diffused into more general use. Again in both cases, the basic technological know-how, the entrepreneurs themselves and often the risk capital, derived from the original innovating large companies. Thus, policies that do not take into account the dynamic complementarities between the large and the small clearly are of only limited utility.     

Problem-based Learning: Potential and Implementation Issues

This study addresses the issues associated with the application of problem-based learning, examines the key design dimensions of a problem-based learning course and considers the implications of problem-based learning for learners and educators.     

On the identification of ARMA echelon-form models

An identification procedure for multivariate autoregressive moving average (ARMA) echelon-form models is proposed. It is based on the study of the linear dependence between rows of the Hankel matrix of serial correlations. To that end, we define a statistical test for checking the linear dependence between vectors of serial correlations. It is shown that the test statistic t?_n considered is distributed asymptotically as a finite linear combination of independent chi-square random variables with one degree of freedom under the null hypothesis, whereas under the alternative hypothesis, t?_N/N converges in probability to a positive constant. These results allow us, in particular, to compute the asymptotic probability of making a specification error with the proposed procedure. Links to other methods based on the application of canonical analysis are discussed. A simulation experiment was done in order to study the performance of the procedure. It is seen that the graphical representation of t?_N, as a function of N, can be very useful in identifying the dynamic structure of ARMA models. Furthermore, for the model considered, the proposed identification procedure performs very well for series of 100 observations or more and reasonably well with short series of 50 observations.