Generating interior search directions for multiobjective linear programming

A new multiobjective linear programming (MOLP) algorithm is presented. The algorithm uses a variant of Karmarkar's interior-point algorithm known as the affine-scaling primal algorithm. Using this single-objective algorithm, interior search directions are generated and used to provide an approximation to the gradient of the (implicitly known) utility function. The approximation is guided by assessing locally relevant preference information for the various interior directions through interaction with a decision maker (DM). The resulting algorithm is an interactive approach that makes its progress towards the solution through the interior of the constraints polytope.     

A comparison of skill-building and desensitization strategies for intervention with aggressive children

Social skills training and desensitization interventions were conducted with 41 institutionalized aggressive children aged 7–13. Subjects were randomly assigned after blocking by aggression and cooperative play to either of the treatments. Dependent measures were direct observations of playground play and teacher ratings. Subjects in the social skills program mastered the basic cognitive skills presented to them. Observational data indicated that both groups experienced marked reduction in aggressive behavior and increases in cooperative play. The social skills training intervention engendered incremental improvement in aggression in comparison to the desensitization condition. However, none of the behavioral changes evident in the observations were reflected in teacher ratings.     

An information - expectation framework for decisions under uncertainty

Despite being in existence for many decades, normative decision theory has not become a commonly used tool for real-world decisions. This paper considers the reasons for this situation and suggestions for circumventing them. The main suggestion involves a two-stage framework in terms of the information available to the decision maker and his/her expectations under the available acts. This framework is well suited for decisions with incomplete structure, which is typical of real decision situations. Within this framework a specific multiplicative model is also discussed.     

The effects of statistical training on choice heuristics in choice under uncertainty

Kahneman and Tversky (1984) proposed that decision makers perceive choice uncertainty in two ways: (1) as a distribution of possible outcomes or (2) as a single uncertain outcome. Using statistical training as a factor that influences these perceptions, and thus the type of decision approach individuals use, we found that individuals with different levels of experience displayed differences in the decisions they made and in the choice heuristics used to make those decisions. Statistically naive individuals were more likely to prefer loss-minimizing alternatives, use a more non-compensatory heuristic, and spend more time on loss-related information than their statistically experienced counterparts. When a distributional cue, indicating the distributional nature of choice outcomes, was presented to both experience groups, the naive group was found to use a decision approach similar to the experienced group and to make similar decisions. The results are discussed in terms of the need to include factors that alter individuals' approaches to uncertainty in future behavioral models of uncertain choice.     

Using Lexicographic Parametric Programming for Searching a Non-dominated Set in Multiple-Objective Linear Programming

In this paper we propose an approach which makes it possible to search non-dominated and only non-dominated solutions in multiple-objective linear programming. The approach is based on the use of a reference direction and lexicographic parametric programming. The requisite theory is developed in the paper. The use of the approach is illustrated with a numerical example.     

Sex differences in the perceived causal structure of date rape: A preliminary report

The present study examines the perceived causes of date rape by the use of network analysis. The 142 subjects in the study were presented with grids containing 9 causes listed by row and column. They were asked to indicate if they belived there was a causal link between each of the 72 causal pairings. The resulting network placed emphasis on male and female drunkenness, norms of dating, and society's attitude to date rape as distal causes of date rape. Misunderstanding of behavior by men, male attitude that date rape is unimportant, and need by males for dominance were seen as proximal causes. Further networks for each sex were constructed: these showed clear division of opinion on the causes of date rape. © 1995 Wiley-Liss, Inc.     

The Role of Professional Training Experiences and Manualized Programs in ABA Providers’ Use of Parent Training With Children With Autism

Parent training, in which providers teach parents intervention strategies to promote their children’s skill acquisition and/or behavior management, is considered a best practice in the treatment for children with autism spectrum disorder (ASD) and yet is underutilized in community settings. The present study examined the role of training experiences and manual use in promoting the use of parent training by community providers who serve children with ASD. Applied behavior analysis (ABA) providers (N = 1,089) from across the United States completed self-report questionnaires online. The total number of professional training experiences related to parent training significantly predicted the extensiveness of providers’ use of parent training. Receiving supervision in parent training, being trained in a specific parent training approach, taking a course related to parent training, and participating in self-guided learning (e.g., webinar) were unique predictors of parent training extensiveness. While only 15% of ABA providers used manualized parent training programs, using a manual was also a unique predictor of parent training extensiveness. Parallel multiple mediator analyses demonstrated that family-, provider-, and organization-level barriers all partially mediated the relationship between number of training experiences and parent training extensiveness; only provider- and organization-level barriers mediated the relationship between manual use and parent training extensiveness. Recommendations for training and supporting providers at the pre-service and in-service levels are discussed as a means of increasing access to parent training for children with ASD in community settings.     

The danger of conflating level-specific effects of control variables when primary interest lies in level-2 effects

In the multilevel modelling literature, methodologists widely acknowledge that a level-1 variable can have distinct within-cluster and between-cluster effects, and that failing to disaggregate these can yield a slope estimate that is an uninterpretable, conflated blend of the two. Methodologists have stated, however, that including conflated slopes of level-1 variables in a model is not problematic if substantive interest lies only in effects of level-2 predictors. Researchers commonly follow this advice and use methods that do not disaggregate effects of level-1 control variables (e.g., grand mean centering) when examining effects of level-2 predictors. The primary purpose of this paper is to show that this is a dangerous practice. When level-specific effects of level-1 variables differ, failing to disaggregate them can severely bias estimation of level-2 predictor slopes. We show mathematically why this is the case and highlight factors that can exacerbate such bias. We corroborate these findings with simulations and present an empirical example, showing how such distortions can severely alter substantive conclusions. We ultimately recommend that simply including the cluster mean of the level-1 variable as a control will alleviate the problem.