On structural models for analyzing change

The recommendation to base the analysis of multi-wave data upon explicit models for change is advocated. Several univariate and multivariate models are described, which emerge from an interaction between the classical test theory and the structural equation modeling approach. The resulting structural models for analyzing change reflect in some of their parameters substantively interesting aspects of intra- and interindividual change in follow-up studies. The models are viewed as an alternative to an ANOVA-based analysis of longitudinal data, and are illustrated on data from a cognitive intervention study of old adults (Bakes et al , 1986). The approach presents a useful means of analyzing change over time, and is applicable for purposes of (latent) growth curve analysis when analysis of variance assumptions are violated (e.g., Schaie & Hertzog, 1982; Morrison, 1976).     

Using Qualitative Methods to Develop Contextually Relevant Measures and Preventive Interventions: An Illustration

Qualitative methods were used to develop a contextually relevant quantitative measure of parenting stress and inform the design of family-focused interventions aimed at preventing adolescent mental and behavioral health problems. The study focused on the experiences of low-income one- and two-parent families representing three ethnic groups (Mexican, African, and European Americans) living in low-income neighborhoods in a large Southwestern city. This report describes the place of this study in a broader program of prevention research, the qualitative methods and data analysis procedures employed, and how the results were used to develop a new measure of parenting stress and inform future program design. The report also includes reflective comments on the methods used and lessons gained.     

Reliability and validity of two widely-used worry questionnaires: self-report and self-peer convergence

The reliability and validity of the Penn State Worry Questionnaire (PSWQ) and the Worry Domains Questionnaire (WDQ) were examined with self-ratings from a non-clinical sample of 148 students in a test-retest design across four weeks. Ratings from three well-acquainted peers were also obtained. With internal consistencies and test-retest correlations of at least 0.85, the present study confirmed the high reliability of the questionnaires. Moreover, both measures demonstrated substantial convergent validity: Average agreement among peers was 0.42 (PSWQ) and 0.47 (WDQ) and aggregated self-peer agreement was 0.55 (PSWQ) and 0.49 (WDQ). Self-peer agreement was not biased by social desirability. These findings challenge views that worry is an unreliable and unobservable phenomenon.     

Measuring Child Mental Health Status for Services Research

Epidemiological studies of the prevalence of mental health disorders typically contain multiple measures of mental health, using different instruments and different informants (child, parent, and interviewer). We used the Methods for the Epidemiology of Child and Adolescents Mental Disorder (MECA) study of U.S. youth to assess the effects of employing a range of these measures in mental health services research. We examined the effect of including various measures of mental health status in regressions of income on mental health service use. The estimated effect of income on service use varied widely, depending on the measure of mental health status used. Some measures of mental health status have little explanatory power in service use regressions. Measures of mental health status based on parental assessment of impairment or need, such as the Columbia Impairment Scale, are less costly to collect and also have good explanatory power, but are more strongly correlated with income. The Non-Clinician Child Global Assessment Scale (NC-CGAS) performs best in terms of explanatory power and correlation with income. Higher income parents appeared to judge behaviors differently from lower income parents, so analyses based on measures derived from parental report may lead to an understatement of the effect of income on service use.     

A classification scheme for discipline: type, mode of administration, context

This paper reviews research related to parental disciplinary practices and presents a classification scheme discipline that separates discipline into the type and the mode of administration used. Previous research has not kept important constructs related to discipline distinct and has ignored some types of discipline, as well as the mode of administration. The classification scheme presented is meant to try to foster conceptual clarity, to advocate for attention to important aspects of disciplinary practices in future research, and to lay the groundwork for development of additional measurement tools — particularly for survey design research.     

选择性注意的ERP研究方法

注意理论的基本问题中,关于注意过滤器的位置,存在着早期与晚期选择的长期争论;关于自动加工与控制性加工,其机制与相互作用也有待明确。采用相同感觉通路的双耳分听和跨通路等实验范式,使ERP作为注意的客观电生理指标成为可能。但此类研究,涉及注意与非注意、听觉通路与视觉通路、标准刺激与偏差刺激等复杂的实验条件,并利用不同状态之间的相减技术以及由此而来的波幅测量问题.在当前国际上许多主要的ERP实验室均未能很好解决,尚处于摸索阶段。本文针对上述问题作一介绍,以供同行参考。1实验范式——刺激的设置1.1通路内的选择…     

Structural analysis of subjective categorical data

A general approach to the analysis of subjective categorical data is considered, in which agreement matrices of two or more raters are directly expressed in terms of error and agreement parameters. The method provides focused analyses of ratings from several raters for whom ratings have measurement error distributions that may induce bias in the evaluation of substantive questions of interest. Each rater's judgment process is modeled as a mixture of two components: an error variable that is unique for the rater in question as well as an agreement variable that operationalizes the true values of the units of observation. The statistical problems of identification, estimation, and testing of such measurement models are discussed.The general model is applied in several special cases. The most simple situation is that underlying Cohen's Kappa, where two raters place units into unordered categories. The model provides a generalization and systematization of the Kappa-idea to correct for agreement by chance. In applications with typical research designs, including a between-subjects design and a mixed within-subjects, between-subjects design, the model is shown to disentangle structural and measurement components of the observations, thereby controlling for possible confounding effects of systematic rater bias. Situations considered include the case of more than two raters as well as the case of ordered categories. The different analyses are illustrated by means of real data sets.The authors wish to thank Lawrence Hubert and Ivo Molenaar for helpful and detailed comments on a previous draft of this paper. Thanks are also due to Jens Möller und Bernd Strauß for the data from the 1992 Olympic Games. We thank the editor and three anonymous reviewers for valuable comments on an earlier draft.     

Best linear prediction of composite universe scores

The problem of predicting universe scores for samples of examinees based on their responses to samples of items is treated. A general measurement procedure is described in which multiple test forms are developed from a table of specifications and each form is administered to a different sample of examinees. The measurement model categorizes items according to the cells of such a table, and the linear function derived for minimizing error variance in prediction uses responses to these categories. In addition, some distinctions are drawn between aspects of the approach taken here and the familiar regressed score estimates.The author thanks Robert L. Brennan, Michael J. Kolen, and Richard Sawyer for helpful comments and corrections, and anonymous reviewers for suggested improvements.     

Choice between response units: The rate constancy model

In a conjoint schedule, reinforcement is available simultaneously on two or more schedules for the same response. The present experiments provided food for key pecking on both a random-interval and a differential-reinforcement-of-low-rate (DRL) schedule. Experiment 1 involved ordinary DRL schedules; Experiment 2 added an external stimulus to indicate when the required interresponse time had elapsed. In both experiments, the potential reinforcer frequency from each component was varied by means of a second-order fixed-ratio schedule, and the DRL time parameter was changed as well. Response rates were described by a model stating that time allocation to each component matches the relative frequency of reinforcement for that component. When spending time in a given component, the subject is assumed to respond at the rate characteristic of baseline performance. This model appeared preferable to the absolute-rate version of the matching law. The model was shown to be applicable to multiple-response concurrent schedules as well as to conjoint schedules, and it described some of the necessary conditions for response matching, undermatching, and bias. In addition, the pigeons did not optimize reinforcer frequency.