Item-specific adaptation and the conflict-monitoring hypothesis: a computational model

M. M. Botvinick, T. S. Braver, D. M. Barch, C. S. Carter, and J. D. Cohen (2001) implemented their conflict-monitoring hypothesis of cognitive control in a series of computational models. The authors of the current article first demonstrate that M. M. Botvinick et al.'s (2001) conflict-monitoring Stroop model fails to simulate L. L. Jacoby, D. S. Lindsay, and S. Hessels's (2003) report of an item-specific proportion-congruent (ISPC) effect in the Stroop task. The authors then implement a variant of M. M. Botvinick et al.'s model based on the assumption that control must be able to operate at the item level. This model successfully simulates the ISPC effect. In addition, the model provides an alternative to M. M. Botvinick et al.'s explanation of the list-level proportion-congruent effect in terms of an ISPC effect. Implications of the present modeling effort are discussed.     

On bad luck: Job and jesus

I reflect on certain random events that befall us and to those we love, random events we never would have chosen because of the pain and suffering they involve. A distinction is drawn between the bad luck of physical assaults, such as genetic defects and the bad luck growing out of value conflicts. Illuminated by the writings of two philosophers— Wilcox and Wolterstorff—I examine the story of Job's maturing response to bad luck. I conclude with some reflections on Christ's response to pain and suffering and its implications for our response to bad luck.     

Traditional difference-score analyses of reasoning are flawed

Studies of the belief bias effect in syllogistic reasoning have relied on three traditional difference score measures: the logic index, belief index, and interaction index. Dube, Rotello, and Heit (2010, 2011) argued that the interaction index incorrectly assumes a linear receiver operating characteristic (ROC). Here, all three measures are addressed. Simulations indicated that traditional analyses of reasoning experiments are likely to lead to incorrect conclusions. Two new experiments examined the role of instructional manipulations on the belief bias effect. The form of the ROCs violated assumptions of traditional measures. In comparison, signal detection theory (SDT) model-based analyses were a better match for the form of the ROCs, and implied that belief bias and instructional manipulations are predominantly response bias effects. Finally, reanalyses of previous studies of conditional reasoning also showed non-linear ROCs, violating assumptions of traditional analyses. Overall, reasoning research using traditional measures is at risk of drawing incorrect conclusions.     

Robust ANCOVA using a smoother with bootstrap bagging

Many robust analogs of the classic analysis of covariance (ANCOVA) method have been proposed, some of which are based on some type of regression smoother. A method that first appeared in this journal, which is relatively simple and performs well in simulations, is based on a running interval smoother combined with comparing medians or 20% trimmed means. It makes no parametric assumption about the regression lines and does not assume that the regression lines are parallel. A possible way of improving the efficiency of the running interval smoother is to use bootstrap bagging and a minor goal here is to report some results supporting this approach. The major goal is to consider how ANCOVA might be performed when bootstrap bagging is used. Simple extensions of extant approaches that use some type of bootstrap method were found to be unsatisfactory. However, a basic percentile bootstrap method was found to perform well in simulations. And a reanalysis of data dealing with teachers' expectations about the cognitive ability of students illustrates that bootstrap bagging can make a practical difference.     

Developing an Acceptance-Based Behavioral Treatment for Binge Eating Disorder: Rationale and Challenges

Binge eating disorder (BED), characterized by recurrent eating episodes in which individuals eat an objectively large amount of food within a short time period accompanied by a sense of loss of control, is the most common eating disorder. While existing treatments, such as cognitive behavioral therapy (CBT), produce remission in a large percentage of individuals with BED, room for improvement in outcomes remains. Two reasons some patients may continue to experience binge eating after a course of treatment are: (a) Difficulty complying with the prescribed behavioral components of CBT due to the discomfort of implementing such strategies; and (b) a lack of focus in current treatments on strategies for coping with high levels of negative affect that often drive binge eating. To optimize treatment outcomes, it is therefore crucial to provide patients with strategies to overcome these issues. A small but growing body of research suggests that acceptance-based treatment approaches may be effective for the treatment of binge eating. The goal of the current paper is to describe the development of an acceptance-based group treatment for BED, discuss the structure of the manual and the rationale and challenges associated with integrating acceptance-based strategies into a CBT protocol, and to discuss clinical strategies for successfully implementing the intervention.     

Maximum likelihood estimation in multidimensional scaling

A variety of distributional assumptions for dissimilarity judgments are considered, with the lognormal distribution being favored for most situations. An implicit equation is discussed for the maximum likelihood estimation of the configuration with or without individual weighting of dimensions. A technique for solving this equation is described and a number of examples offered to indicate its performance in practice. The estimation of a power transformation of dissimilarity is also considered. A number of likelihood ratio hypothesis tests are discussed and a small Monte Carlo experiment described to illustrate the behavior of the test of dimensionality in small samples.The research reported here was supported by grant number APA 320 to the author by the National Research Council of Canada.     

MSA for a special spearman matrix

Kaiser's measure of sampling adequacy is applied to a special Spearman matrix and a specialq-cluster generalization. The result supports the contention that the measure should be no less than .5 for data to be appropriate for factor analysis.The research reported in this note was supported in part by the Program in Applied Mathematics and Statistics, National Science Foundation, and by the National Institute of Education, Department of Health, Education, and Welfare.     

The preventive and therapeutic effects of two school mental health programs

In 30 classrooms randomly assigned to experimental conditions, effects on mothers' reports of behavior symptoms were compared for (a) a parent education program; (b) an in-school program of consultation, counseling, training, and referral; and (c) control classrooms. A sample of 426 families were followed for 30 months from the child's entry into third grade. A simple unweighted count of the number of symptoms reported in a home interview had adequate validity, good reliability, low reactivity, and intrinsic significance. Both programs had significant preventive and therapeutic effects on boys but not on girls. Effects were immediate in the upper middle class families, delayed in the lower class families.The larger study on which this article is based was initiated some years ago by Professor Glidewell and his colleagues, and represents a pioneering research effort in the field of community psychology. The present article was prepared by the authors in response to an invitation from the Editor to report important and still timely aspects of the original study that were not previously published in archival sources. We are grateful to Professor Glidewell and his colleagues for giving us this opportunity to make their findings more generally available to community psychology researchers.This work was supported by research grant M-592 from the National Institute of Mental Health, U.S. Public Health Service, and the St. Louis County Health Department.     

Analyzing mothers' speech to young autistic children: A methodological study

The development of a technique for analyzing mothers' speech to young children is described. The need for such a measure arose from two linked studies of autistic children, one comparing them with developmental dysphasic children and the other evaluating the results of a home-based approach to treatment. A 17-category system was developed which could encompass almost all the types of speech shown by mothers of young autistic and normal children and which differentiated between the speech used by different mothers in a way that was meaningfully related to the child's level of language development. The categories proved to be easily applicable and to show good inter-observer reliability. Tape-recordings made during home observations were found to be the best source of speech samples. The problems of time sampling, length and nature of speech sample, and observer effects are discussed.We are most grateful to our colleagues Dr. Lionel Hersov and Mr. William Yule for many helpful suggestions in developing the measures and for their comments on an earlier draft of the paper. The study is supported by a grant from the (British) Department of Health and Social Security.