Units of analysis and kinetic structure of behavioral repertoires

It is suggested that molar streams of behavior are constructed of various arrangements of three elementary constituents (elicited, evoked, and emitted response classes). An eight-cell taxonomy is elaborated as a framework for analyzing and synthesizing complex behavioral repertoires based on these functional units. It is proposed that the local force binding functional units into a smoothly articulated kinetic sequence arises from temporally arranged relative response probability relationships. Behavioral integration is thought to reflect the joint influence of the organism's hierarchy of relative response probabilities, fluctuating biological states, and the arrangement of environmental and behavioral events in time.     

Multiaxial taxonomy of fibromyalgia syndrome patients

Pain, disability, and depression are present in various degrees in patients with fibromyalgia syndrome. Cluster analysis was used in this research to ascertain the existence of subgroups of patients in a fibromyalgia sample based on these variables. Two clusters were defined: one characterized by high levels of pain, disability, and depression (n=51) and another characterized by low levels of pain, disability, and depression (n=67). Multivariate analysis of variance (MANOVA) confirmed differences between clusters on these health status factors and a second MANOVA revealed that the subgroup with a poorer health status reported greater passive coping, helplessness, and stress, and less satisfaction with social support, than the subgroup with better health status. Logistic regression indicated that the best discriminator of subgroup membership was helplessness. These results suggest that different approaches to patient management, particularly intervention strategies aimed at reducing helplessness, may be beneficial for patients with high levels of pain, disability, and depression.     

Behavioral coaching in the development of skills in football, gymnastics, and tennis

A review of the literature indicates that methods of skill acquisition based on the operant paradigm have been scientifically validated with many motor behaviors. However, these procedures have been limited to the use of positive reinforcement for correct performance when applied to the acquisition of complex sports skills in natural settings. To find complementary procedures to enhance skill acquisition, a coaching method involving several behavioral techniques was developed that focused on remediation of errors. This coaching method combined the following components: (1) systematic use of verbal instructions and feedback, (2) positive and negative reinforcement, (3) positive practice, and (4) time out. Three sports, football, gymnastics, and tennis, were selected to determine the effectiveness and generality of this behavioral coaching method. A total of 23 male and female subjects, ranging in age from 11 to 35, was included in this study. Baseline data were first collected for each sport under standard coaching conditions. Next, the behavioral coaching method was evaluated depending on the sport in either a multiple baseline or a reversal design. The behavioral dimensions selected were blocking in football; backward walkovers, front hand springs, and reverse kips in gymnastics; and the forehand, backhand, and serve in tennis. Behavioral coaching was immediately effective in increasing the correct execution of complex skills in all three sports. Gains of up to 10 times the baseline performance were achieved in each sport. In football, behavioral coaching resulted in an increase in correct blocking performance from a baseline average of 5% to 51.3%. Gymnasts' performances increased from baseline averages of 2.7% to 52.6% across the three skills. In tennis, standard coaching produced an average of 6% correct performance which increased dramatically under behavioral coaching to 57% across the three strokes. The success of the behavioral coaching package used here suggests that a technology of behavior may offer additional and complementary strategies to the acquisition of motor skills in the natural environment.     

Essential independence and likelihood-based ability estimation for polytomous items

A definition ofessential independence is proposed for sequences of polytomous items. For items satisfying the reasonable assumption that the expected amount of credit awarded increases with examinee ability, we develop a theory ofessential unidimensionality which closely parallels that of Stout. Essentially unidimensional item sequences can be shown to have a unique (up to change-of-scale) dominant underlying trait, which can be consistently estimated by a monotone transformation of the sum of the item scores. In more general polytomous-response latent trait models (with or without ordered responses), anM-estimator based upon maximum likelihood may be shown to be consistent for under essentially unidimensional violations of local independence and a variety of monotonicity/identifiability conditions. A rigorous proof of this fact is given, and the standard error of the estimator is explored. These results suggest that ability estimation methods that rely on the summation form of the log likelihood under local independence should generally be robust under essential independence, but standard errors may vary greatly from what is usually expected, depending on the degree of departure from local independence. An index of departure from local independence is also proposed.This work was supported in part by Office of Naval Research Grant N00014-87-K-0277 and National Science Foundation Grant NSF-DMS-88-02556. The author is grateful to William F. Stout for many helpful comments, and to an anonymous reviewer for raising the questions addressed in section 2. A preliminary version of section 6 appeared in the author's Ph.D. thesis.     

A look,by simulation,at the validity of some asymptotic distribution results for rotated loadings

In the last few years, a number of asymptotic results for the distribution of unrotated and rotated factor loadings have been given. This paper investigates the validity of some of these results based on simulation techniques. In particular, it looks at principal component extraction and quartimax rotation on a problem with 13 variables. The indication is that the asymptotic results are quite good.     

A note on computing Louis’ observed information matrix identity for IRT and cognitive diagnostic models

Using Louis’ formula, it is possible to obtain the observed information matrix and the corresponding large-sample standard error estimates after the expectation–maximization (EM) algorithm has converged. However, Louis’ formula is commonly de-emphasized due to its relatively complex integration representation, particularly when studying latent variable models. This paper provides a holistic overview that demonstrates how Louis’ formula can be applied efficiently to item response theory (IRT) models and other popular latent variable models, such as cognitive diagnostic models (CDMs). After presenting the algebraic components required for Louis’ formula, two real data analyses, with accompanying numerical illustrations, are presented. Next, a Monte Carlo simulation is presented to compare the computational efficiency of Louis’ formula with previously existing methods. Results from these presentations suggest that Louis’ formula should be adopted as a standard method when computing the observed information matrix for IRT models and CDMs fitted with the EM algorithm due to its computational efficiency and flexibility.     

身体表征的分离:二分解释模型及其证据

身体表征是一种内部结构,它具有追踪身体状态并对其进行编码的功能。这种结构可以对身体进行错误的表征,并可以从身体中分离出来。来自海豹肢症与躯体失认症等方面的病例,证实部分身体畸形与脑损伤患者的身体表征存在分离;来自橡胶手错觉与全身错觉的实验证据,验证了健康个体身体表征分离的事实。基于上述证据,以身体图式和身体意象为二分维度的模型解释了身体表征的分离。未来的研究可以从神经心理学实验和虚拟现实技术着手,对身体表征的分离进行深入探究。     

Concise formulas for the standard errors of component loading estimates

Concise formulas for the asymptotic standard errors of component loading estimates were derived. The formulas cover the cases of principal component analysis for unstandardized and standardized variables with orthogonal and oblique rotations. The formulas can be used under any distributions for observed variables as long as the asymptotic covariance matrix for sample covariances/correlations is available. The estimated standard errors in numerical examples were shown to be equivalent to those by the methods using information matrices.The author is indebted to anonymous reviewers for the corrections and suggestions on this study, which have led to improvements of earlier versions of this article.     

A unified approach to exploratory factor analysis with missing data,nonnormal data,and in the presence of outliers

Factor analysis is regularly used for analyzing survey data. Missing data, data with outliers and consequently nonnormal data are very common for data obtained through questionnaires. Based on covariance matrix estimates for such nonstandard samples, a unified approach for factor analysis is developed. By generalizing the approach of maximum likelihood under constraints, statistical properties of the estimates for factor loadings and error variances are obtained. A rescaled Bartlett-corrected statistic is proposed for evaluating the number of factors. Equivariance and invariance of parameter estimates and their standard errors for canonical, varimax, and normalized varimax rotations are discussed. Numerical results illustrate the sensitivity of classical methods and advantages of the proposed procedures.This project was supported by a University of North Texas Faculty Research Grant, Grant #R49/CCR610528 for Disease Control and Prevention from the National Center for Injury Prevention and Control, and Grant DA01070 from the National Institute on Drug Abuse. The results do not necessarily represent the official view of the funding agencies. The authors are grateful to three reviewers for suggestions that improved the presentation of this paper.