Maximum Likelihood Methods in Treating Outliers and Symmetrically Heavy-Tailed Distributions for Nonlinear Structural Equation Models with Missing Data

By means of more than a dozen user friendly packages, structural equation models (SEMs) are widely used in behavioral, education, social, and psychological research. As the underlying theory and methods in these packages are vulnerable to outliers and distributions with longer-than-normal tails, a fundamental problem in the field is the development of robust methods to reduce the influence of outliers and the distributional deviation in the analysis. In this paper we develop a maximum likelihood (ML) approach that is robust to outliers and symmetrically heavy-tailed distributions for analyzing nonlinear SEMs with ignorable missing data. The analytic strategy is to incorporate a general class of distributions into the latent variables and the error measurements in the measurement and structural equations. A Monte Carlo EM (MCEM) algorithm is constructed to obtain the ML estimates, and a path sampling procedure is implemented to compute the observed-data log-likelihood and then the Bayesian information criterion for model comparison. The proposed methodologies are illustrated with simulation studies and an example. The research described herein was fully supported by a grant (CUHK 4243/03H) from the Rearch Grants Council of the Hong Kong Special Administration Region. The authors are thankful to the Editor, the Associate Editor, and anonymous reviewers for valuable comments which improve the paper significantly, and are grateful to ICPSR and the relevant funding agency for allowing the use of their data. Requests for reprints should be sent to S. Y. Lee, Department of Statistics, The Chinese University of Hong Kong, Shatin, N. T., Hong Kong.     

The Suitability of an Inhibitory Learning Approach in Exposure When Habituation Fails: A Clinical Application to Misophonia

Recent findings have led to a reconceptualization of the mechanisms that account for the efficacy of exposure-based treatments. Termed the “inhibitory learning model,” this approach emphasizes new learning when confronted with previously avoided stimuli rather than merely the cessation of fear or aversive emotional responding. In this paper, we propose the applicability of the inhibitory learning model for conditions and contexts in which simple exposure does not produce habituation. We illustrate this application from an in-progress randomized controlled treatment trial for adults with misophonia. Misophonia is a condition marked by strong aversive reactions to specific sounds. It is a difficult to treat and understudied syndrome. All participants in the trial received exposure, either before or after a stress management module of treatment. Exposure treatment emphasized altered expectancies for the target sounds as well as deliberate practice in hearing sounds on the individually developed hierarchy. Inhibitory learning strategies were employed to increase treatment adherence and commitment, shape patient behavior during exposures, manufacture negative prediction errors, increase perceived control over reactions, and promote learning that generalized to functional improvements. The findings are discussed in the context of future applications of the inhibitory learning model for psychopathology associated with avoidance.     

关注肝炎的"过度医疗"

肝炎诊疗领域存在的过度医疗现象是最具代表性的,集中体现为过度使用联合治疗、过度进行化验等辅助检查、过度使用新特药物、虚假广告泛滥等等,肝炎患者承担了额外风险,不但身心受损,而且经济支出严重超标,因病返贫、因病致贫的现象比比皆是.过度医疗是目前不规范的经济大环境的必然产物,救死扶伤、人道主义本应是医疗工作的准则,现在拜金主义、经济效应第一成为医疗活动的目的,过度诊疗在所难免.另外患者的无知和盲目,以及尚不规范的市场环境加剧了过度医疗现象.制定行业规范,建立社会监督机制,与国际肝炎诊疗指南接轨,是克服和纠正诊疗过度的有效方法.     

内隐学习的主观测量标准

近40年来,验证知识的内隐性一直是内隐学习研究的焦点。传统三大范式常以自由言语报告或是迫选测验作为验证知识内隐性的外显指标,然而各种迹象表明,言语报告和迫选测验存在一定的局限性。由此,Dienes等人提出了内隐学习的主观测量。文章将从言语报告和追选测验的局限性着手,阐述主观测量诞生的必要性及其在衡量知识意识性上的效度。     

Shaping approach responses as intervention for specific phobia in a child with autism

We evaluated contact desensitization (reinforcing approach responses) as intervention for specific phobia with a child diagnosed with autism. During hospital-based intervention, the boy was able to encounter previously avoided stimuli. Parental report suggested that results were maintained postdischarge.     

Shaping exhale durations for breath CO detection for men with mild mental retardation

Roll, Higgins, and Badger (1996) used a carbon monoxide (CO) detector to determine whether participants smoked in a smoking-cessation study. We sought to replicate their work with adults with mild mental retardation. However, verbal instructions were inadequate to establish stable exhalations of sufficient durations for reliable and accurate CO evaluation. This report describes a shaping procedure that enabled 3 of 4 participants to achieve 20-s exhalation durations.     

Toward a unified theory of decision criterion learning in perceptual categorization

Optimal decision criterion placement maximizes expected reward and requires sensitivity to the category base rates (prior probabilities) and payoffs (costs and benefits of incorrect and correct responding). When base rates are unequal, human decision criterion is nearly optimal, but when payoffs are unequal, suboptimal decision criterion placement is observed, even when the optimal decision criterion is identical in both cases. A series of studies are reviewed that examine the generality of this finding, and a unified theory of decision criterion learning is described (Maddox & Dodd, 2001). The theory assumes that two critical mechanisms operate in decision criterion learning. One mechanism involves competition between reward and accuracy maximization: The observer attempts to maximize reward, as instructed, but also places some importance on accuracy maximization. The second mechanism involves a flat-maxima hypothesis that assumes that the observer's estimate of the reward-maximizing decision criterion is determined from the steepness of the objective reward function that relates expected reward to decision criterion placement. Experiments used to develop and test the theory require each observer to complete a large number of trials and to participate in all conditions of the experiment. This provides maximal control over the reinforcement history of the observer and allows a focus on individual behavioral profiles. The theory is applied to decision criterion learning problems that examine category discriminability, payoff matrix multiplication and addition effects, the optimal classifier's independence assumption, and different types of trial-by-trial feedback. In every case the theory provides a good account of the data, and, most important, provides useful insights into the psychological processes involved in decision criterion learning.     

放弃治疗的伦理选择

放弃治疗在临床上是一个十分复杂的现象 ,只有将其放在“医学———文化”框架中进行全方位考察 ,才能从整体上加以正确把握。就伦理选择而言 ,放弃治疗必然面对诸多伦理冲突 ,临床医师若要化解伦理冲突 ,实现优化选择 ,就必须熟知和遵循基本的伦理准则。     

Time and memory: towards a pacemaker-free theory of interval timing

A popular view of interval timing in animals is that it is driven by a discrete pacemaker-accumulator mechanism that yields a linear scale for encoded time. But these mechanisms are fundamentally at odds with the Weber law property of interval timing, and experiments that support linear encoded time can be interpreted in other ways. We argue that the dominant pacemaker-accumulator theory, scalar expectancy theory (SET), fails to explain some basic properties of operant behavior on interval-timing procedures and can only accommodate a number of discrepancies by modifications and elaborations that raise questions about the entire theory. We propose an alternative that is based on principles of memory dynamics derived from the multiple-time-scale (MTS) model of habituation. The MTS timing model can account for data from a wide variety of time-related experiments: proportional and Weber law temporal discrimination, transient as well as persistent effects of reinforcement omission and reinforcement magnitude, bisection, the discrimination of relative as well as absolute duration, and the choose-short effect and its analogue in number-discrimination experiments. Resemblances between timing and counting are an automatic consequence of the model. We also argue that the transient and persistent effects of drugs on time estimates can be interpreted as well within MTS theory as in SET. Recent real-time physiological data conform in surprising detail to the assumptions of the MTS habituation model. Comparisons between the two views suggest a number of novel experiments.     

Factor analysis and AIC

The information criterion AIC was introduced to extend the method of maximum likelihood to the multimodel situation. It was obtained by relating the successful experience of the order determination of an autoregressive model to the determination of the number of factors in the maximum likelihood factor analysis. The use of the AIC criterion in the factor analysis is particularly interesting when it is viewed as the choice of a Bayesian model. This observation shows that the area of application of AIC can be much wider than the conventional i.i.d. type models on which the original derivation of the criterion was based. The observation of the Bayesian structure of the factor analysis model leads us to the handling of the problem of improper solution by introducing a natural prior distribution of factor loadings.The author would like to express his thanks to Jim Ramsay, Yoshio Takane, Donald Ramirez and Hamparsum Bozdogan for helpful comments on the original version of the paper. Thanks are also due to Emiko Arahata for her help in computing.