Estimation of the Nonlinear Random Coefficient Model when Some Random Effects Are Separable

A method is presented for marginal maximum likelihood estimation of the nonlinear random coefficient model when the response function has some linear parameters. This is done by writing the marginal distribution of the repeated measures as a conditional distribution of the response given the nonlinear random effects. The resulting distribution then requires an integral equation that is of dimension equal to the number of nonlinear terms. For nonlinear functions that have linear coefficients, the improvement in computational speed and accuracy using the new algorithm can be dramatic. An illustration of the method with repeated measures data from a learning experiment is presented.     

Neuropsychological Assessment of HIV-Infected Populations in International Settings

Resource-limited regions of the world represent the areas most affected by the global HIV epidemic. Currently, there are insufficient data on the neurocognitive effects of HIV in these areas and neuropsychological studies that have been carried out thus far are marked by inconsistent methods, test batteries, and rating systems for levels of cognitive impairment. These differences in methods, along with genetic variability of both virus and host, differences in co-infections and other co-morbidities, differences in language and culture, and infrastructural deficiencies in many international settings create challenges to the assessment of neurocognitive functioning and interpretation of neuropsychological data. Identifying neurocognitive impairment directly attributable to HIV, exploring relationships between HIV-associated neurocognitive impairment, disease variables, and everyday functioning, evaluating differences in HIV-1 subtype associated neuropathology, and determining implications for treatment remain complicated and challenging goals. Endeavors to establish a more standardized approach to neurocognitive assessments across international studies in addition to accumulating appropriate normative data that will allow more accurate rating of neuropsychological test performance will be crucial to future efforts attempting to achieve these goals.     

Measuring Moral Progress

The study provides an in-depth analysis of two young adult subjects from a longitudinal study who underwent successive and significant developmental changes. Their developmental patterns, however, are only revealed by a new conception of moral stages, which is both more comprehensive and more detailed than Kohlberg’s original approach. In particular, the suggested alternative taxonomy neatly accommodates what appears as developmental anomalies in the Kohlbergian frame of reference. What is more, apart from merely matching with the observed data, the new theory also explains why the subjects developed the way they did, since it reveals the inherent cognitive conflicts at each stage and how these are resolved at the following one. Although the theory stands against the Kohlberg theory as it is, it may be understood as an extension and further development of the latter, in the sense that Kohlbergian stages are differentiated, supplemented, and theoretically substantiated within the new framework.

A class of multidimensional IRT models for testing unidimensionality and clustering items

We illustrate a class of multidimensional item response theory models in which the items are allowed to have different discriminating power and the latent traits are represented through a vector having a discrete distribution. We also show how the hypothesis of unidimensionality may be tested against a specific bidimensional alternative by using a likelihood ratio statistic between two nested models in this class. For this aim, we also derive an asymptotically equivalent Wald test statistic which is faster to compute. Moreover, we propose a hierarchical clustering algorithm which can be used, when the dimensionality of the latent structure is completely unknown, for dividing items into groups referred to different latent traits. The approach is illustrated through a simulation study and an application to a dataset collected within the National Assessment of Educational Progress, 1996. The author would like to thank the Editor, an Associate Editor and three anonymous referees for stimulating comments. I also thank L. Scaccia, F. Pennoni and M. Lupparelli for having done part of the simulations.     

A Statistical Interpretive Method for Neuropsychological Test Data

The accurate interpretation of large numbers of neuropsychological tests within a flexible battery approach is a difficult and sometimes controversial process. We present a statistically based method of interpretation (Rohling's Interpretive Method or RIM) and evaluation of neuropsychological data that allows for varying numbers of tests along a varying number of cognitive domains, yet remains psychometrically based. This method requires informed clinical judgment in that the level of confidence for tests, cognitive domains, and global indices are used as the backdrop for interpretive decisions. Specific procedures for use are presented in a systematic, detailed fashion to allow the interested reader to replicate the method. Two case examples are presented: a straightforward case of cerebrovascular insult and a more complicated case of mixed etiology. Examples include a variety of different neuropsychological tests commonly used in a flexible battery approach. A discussion of the practicality, ease of use, and potential limitations of this method are further presented.     

A method for analyzing changes in response efficiency.

Although experimental effects typically are evaluated by summarizing levels of responding across time (e.g., calculating the mean levels of problem behavior during 10‐min sessions), these data summaries may obscure important mechanisms that may be responsible for changes in responding. A case study is reported to illustrate alternative methods of data analysis when decreasing trends in responding may be due to increases in response efficiency.     

人工智能辅助下的心理健康新型测评

近年来,人工智能技术的飞速发展及应用催生了"智能化心理健康测评"这一领域。智能化心理健康测评能够弥补传统方法的不足,降低漏诊率并提高诊断效率,这对于心理健康问题的普查及预警具有重大意义。目前,智能化心理健康测评处于初步发展阶段,研究者基于在线行为数据、便携式设备数据等开展主要以数据驱动为导向的探索研究,旨在实现更高的预测准确率,但是测评结果的可解释性等指标尚不够理想。未来的智能化心理健康测评需要强调心理学领域知识和经验的深度介入,提高测评的针对性和精细化程度,加强信效度检验,这对于智能化心理健康测评工具的进一步发展和应用至关重要。     

人工智能辅助的自闭症早期患者的筛查与诊断

自闭症谱系障碍(AutisticSpectrumDisorders,ASD)的症状早在婴幼儿期就会显现,越早发现,越早干预,治疗效果越好。传统自闭症早期筛查与诊断在评估方法、流程上存在局限,无法满足大规模筛查和诊断需求。随着人工智能技术的快速发展,使用智能化方法进行自闭症早期大规模无感筛查与诊断逐渐成为可能。近10年间,国内外对自闭症智能化识别方法的探索在经典任务行为、面部表情和情绪、眼动、脑影像、运动控制和运动模式、多模态6个领域积累了丰富的研究成果。未来研究应围绕构建国内自闭症早期智能医学筛查与诊断体系,开发针对婴幼儿患者的筛查工具,构建融合多模态数据的自闭症婴幼儿智能化识别模型,建立结合脑影像技术的自闭症精细化诊断方法等方面来开展。     

Normative values on the marks and mathews fear questionnaire: A comparison as a function of age and sex

While the Marks and Mathews Fear Questionnaire (1979) has gained widespread use, little information on its psychometric characteristics has been reported. Thus, one purpose of this investigation was to provide normative information on this device. A second purpose was to examine differences in reported fears as a function of age and sex. Fear Questionnaires were administered to a large sample of high-school students, college students, and adults. Means and standard deviations on the Fear Questionnaire are reported for the various groups. Significant differences were found between groups, with college and high-school women reporting more fears than corresponding men, college and high-school women reporting more fears than adult women, and college men showing a trend toward more fears than other men.Portions of this paper were presented at the Annual Meeting of the Association for the Advancement of Behavior Therapy, November 1985, Houston, Texas.