Some values guiding community research and action

The dual purposes of applied research-contributing to understanding and improvement-are only partially served by method systems that encourage studying (with increasing precision) a narrow range of questions of modest societal importance. To optimize contributions to challenging societal problems, a field's cherished standards should be adapted to support more adventuresome forms of community research and action. This paper outlines 10 values for community research and action, based on insights from the fields of behavioral and community psychology. These values-reflect the goals and challenges of establishing collaborative relationships with research participants, determining research goals and methods, designing and disseminating interventions, communicating research findings, and advocating for community change. Critical challenges are outlined, and implications for the field and its clients are discussed.     

FUNCTIONAL COMMUNICATION TRAINING TO REDUCE CHALLENGING BEHAVIOR: MAINTENANCE AND APPLICATION IN NEW SETTINGS

We evaluated the initial effectiveness, maintenance, and transferability of the results of functional communication training as an intervention for the challenging behaviors exhibited by 3 students. Assessment indicated that escape from academic demands was involved in the maintenance of the challenging behaviors. Social attention was also implicated as controlling the behavior of 1 student. The intervention involved teaching alternative assistance-seeking and attention-getting phrases to the students in an effort to replace challenging behavior with these verbal equivalents. Multiple baseline data collected across the 3 students indicated that not only did the intervention substantially reduce challenging behavior but also that these results transferred across new tasks, environments, and teachers, and were generally maintained from 18 to 24 months following the introduction of functional communication training. These results are discussed in light of recent efforts to develop effective interventions for severe challenging behavior and to understand the processes underlying transfer and maintenance of intervention effects.     

Fitting longitudinal reduced-rank regression models by alternating least squares

An alternating least squares method for iteratively fitting the longitudinal reduced-rank regression model is proposed. The method uses ordinary least squares and majorization substeps to estimate the unknown parameters in the system and measurement equations of the model. In an example with cross-sectional data, it is shown how the results conform closely to results from eigenanalysis. Optimal scaling of nominal and ordinal variables is added in a third substep, and illustrated with two examples involving cross-sectional and longitudinal data.Financial support by the Institute for Traffic Safety Research (SWOV) in Leidschendam, The Netherlands is gratefully acknowledged.     

Decomposing the encoding of action events: A dual conception

Two experiments are reported in which we tested the hypothesis that encoding of verbal features of subject-performed tasks or SPTs (e.g., bounce the ball, lift the spoon) is attention-demanding and effortful, whereas physical features of this memory task (e.g., color, weight) are acquired with little effort, and without deliberate encoding strategies. In Experiment 1, subjects were asked to perform a series of SPTs and were examined on recall of verbal instructions and colors of objects involved under conditions of focused or divided attention. In Experiment 2, performance of a series of SPTs was followed by recall of verbal instructions and recall of weights of objects involved. Results of both experiments indicated that recall of the verbal task component was negatively affected by requirements of dual-task performance, whereas recall of both physical task features was equally good in both encoding conditions. The obtained pattern of outcome is interpreted as supportive of the dual conception hypothesis of the nature of the encoding of action events.     

Do medical decision analyses' largest gains grow from the smallest trees?

Some decision analysts recommend reserving their models for careful, complete study of complex problems. Others believe simple problem analyses provide the greatest gains. To clarify these issues, I tested: (1) whether simple published analyses compared to complex ones, produced results as non-intuitive; and (2) whether non-intuitiveness represented analytic gain (or equivalently, intuitive loss). Very limited data also examined (3) the gain from adding model intricacy for a given problem vs. selecting more complex problems for analysis. To assess two non-intuitiveness measures, 75 subjects (33 physicians and 42) non-physicians stated their intuitive preferences in 40 (22 published and 18 unpublished) medical dilemmas. For both physicians and non-physicians, simpler models (those with lees than 30 terminal branches in the decision tree) had about one third the non-intuitiveness of more complex ones. Three tests also supported the premise that analyses outperform intuition, therefore that on average the formers' non-intuitiveness reflects less analytic gain. In addition, for different models of the same problem, tree complexity did not correlate with gain. Thus, simpler trees may not generally gain less because they inadequately describe problems. Instead, simpler analyses may represent simpler problems, with more similar intuitive and formal solutions. If so, these findings may help us avoid some costly but unnecessary simple analyses.     

Pierre de La Ramée et le déclin de la rhétorique

This article provides a basic general introduction to Ramus, and evaluates his role in the history of logic and rhetoric, especially with relation to the study of argumentation. The author agrees with Ong and other historians of logic that Ramus is not to be taken seriously as a logician, and that his undoubted importance in the history of ideas is to be found elsewhere.Ramus advocates a belief in nature, experience and reason, and rejects the reliance on the authority of ancient philosophers, above all Aristotle, though experience does not mean scientific experiment and, paradoxically, includes the example of great philosophers and writers. In the end Ramus is seen as responsible for substituting for ancient classical rhetoric an entirely ornamental rhetoric of figures which was to take over education (with the exception of the Jesuit schools) almost until our own day. This curtailing and diminishing of rhetoric is seen as a degeneration. Ancient five-part rhetoric had been concerned with convincing and persuading: Aristotle distinguished the analytic, scientific reasoning of logic, from dialectic which was based on opinion and probability and had close links with rhetoric; by the time of Cicero and Quintilian, who addressed themselves to jurists and politicians, logic has given way to dialectic. In the Middle Ages and the Renaissance the two become assimilated; the evolution of this is traced here through the thirteenth-century Summulae logicales of Peter of Spain to the fifteenth-century German humanist logician Rudolph Agricola, who influenced Ramus partly through the intermediary of Johann Sturm. Ramus took over their topical theories but restricted them to logic/dialectic, and left rhetoric with little more than tropes and figures. He believed that there was only one method for teaching all the arts, and one dialectic common to them all. The distinction between analytical and dialectical has disappeared, with far-reaching consequences for the study of argumentation. Over the centuries logic has lost its connection with controversy and persuasion. With the development of the post-Cartesian, post-Baconian emphasis on the clarity of scientific discourse, and the mid-nineteenth-century interest in mathematical and formal logic, the process was complete. Argumentation, or the new rhetoric, aims to fill the gap thus created.

     

The problem: American education the solution: Use behavior analytic technology

In spite of numerous demonstrations that America's youth can be effectively educated with behavior analytic teaching techniques, few of the country's children are benefiting from the technology. In addition scholarly reviews of effective teaching strategies have often omitted reference to behavior analysis. One way to look at this problem is as a two-step operation. First, it is necessary to determine procedures that work; second it is necessary to devise strategies for effective dissemination. The present issue of JOBE (Vol. 1, No. 3, Sept. 1991) contains the recommendations of six outstanding behavioral educators as to how to deal with the dissemination problem. The initial article by Pumroy and McIntire describes the activities of an organization which trains school psychologists and teachers to use behavioral procedures and advocates for the techniques with a number of audiences. Next, Engelmann suggests that the public have more control over school activities and that legal action be taken against irresponsible administrative decisions. Hall advocates for less labor-intensive procedures and the sale of curricular materials based on behavioral principles. Binder proposes that dissemination of the technology become a private endeavor that responds to consumer needs. Rosenfield describes a collaborative model of consultation that increases treatment adherence. Finally, Albers and Greer describe research that isolates a key teacher behavior that results in greater academic proficiency.     

Gennclus: New models for general nonhierarchical clustering analysis

A general class of nonhierarchical clustering models and associated algorithms for fitting them are presented. These (metric) clustering models generalize the Shepard-Arabie Additive Clusters model in allowing for: (1). either overlapping or nonoverlapping clusters; (2). either symmetric (one-way clustering) or nonsymmetric (two-way clustering) proximities (input data); and, (3). either symmetric or diagonal weights. The GENNCLUS algorithms utilize alternating least-squares methods combining ordinary and constrained least-squares, nonlinear constrained mathematical programming, and combinatorial optimization techniques in estimating model parameters. In addition to developing the mathematical bases of these models, a comprehensive set of Monte Carlo simulations of the different models is reported. Two applications concerning brand-switching data and celebrity-brand proximities are discussed. Finally, extensions to three-way models, nonmetric analyses, and other model specifications are provided.Wayne S. DeSarbo is a Member of Technical Staff in the Mathematics and Statistics Research Center at Bell Laboratories in Murray Hill, N.J. I wish to thank R. Gnanadesikan, J. D. Carroll, and P. Arabie for their comments on a previous draft of this paper. I also wish to acknowledge the computer assistance provided by Linda Clark. Finally, I wish to thank the reviewers and editor for their very complete reviews and comments.     

On the optimality of the simultaneous redundancy transformations

The objective of this paper is to introduce and motivate additional properties and interpretations for the redundancy variables. It is shown that these variables can be derived by application of certain invariance arguments and without reference to the index of redundancy. In addition, an optimality property for the variables is presented which is important whenever one restricts attention in a study to a subset of the redundancy variables. This optimality property pertains to the subset rather than to the individual variables.This paper is based in part on the author's doctoral dissertation, Department of Statistics, Princeton, University. Research was conducted under the supervision of Lawrence S. Mayer.