Multisystemic Therapy and Functional Family Therapy Compared on their Effectiveness Using the Propensity Score Method

Multisystemic Therapy (MST) and Functional Family Therapy (FFT) have overlapping target populations and treatment goals. In this study, these interventions were compared on their effectiveness using a quasi-experimental design. Between October, 2009 and June, 2014, outcome data were collected from 697 adolescents (mean age 15.3 (SD 1.48), 61.9% male) assigned to either MST or FFT (422 MST; 275 FFT). Data were gathered during Routine Outcome Monitoring. The primary outcome was externalizing problem behavior (Child Behavior Checklist and Youth Self Report). Secondary outcomes were the proportion of adolescents living at home, engaged in school or work, and who lacked police contact during treatment. Because of the non-random assignment, a propensity score method was used to control for observed pre-treatment differences. Because the risk-need-responsivity (RNR) model guided treatment assignment, effectiveness was also estimated in youth with and without a court order as an indicator of their risk level. Looking at the whole sample, no difference in effect was found with regard to externalizing problems. For adolescents without a court order, effects on externalizing problems were larger after MST. Because many more adolescents with a court order were assigned to MST compared to FFT, the propensity score method could not balance the treatment groups in this subsample. In conclusion, few differences between MST and FFT were found. In line with the RNR model, higher risk adolescents were assigned to the more intensive treatment, namely MST. In the group with lower risk adolescents, this more intensive treatment was more effective in reducing externalizing problems.     

使用题组反应模型缓解局部题目依赖性对多阶段测验的危害

尽管多阶段测验(MST)在保持自适应测验优点的同时允许测验编制者按照一定的约束条件去建构每一个模块和题板,但建构测验时若因忽视某些潜在的因素而导致题目之间出现局部题目依赖性(LID)时,也会对MST测验结果带来一定的危害。为探究"LID对MST的危害"这一问题,本研究首先介绍了MST和LID等相关概念;然后通过模拟研究比较探讨该问题,结果表明LID的存在会影响被试能力估计的精度但仍为估计偏差较小,且该危害不限于某一特定的路由规则;之后为消除该危害,使用了题组反应模型作为MST施测过程中的分析模型,结果表明尽管该方法能够消除部分危害但效果有限。这一方面表明LID对MST中被试能力估计精度所带来的危害确实值得关注,另一方面也表明在今后关于如何消除MST中由LID造成危害的方法仍值得进一步探究的。     

On Insensitivity of the Chi-Square Model Test to Nonlinear Misspecification in Structural Equation Models

In this paper, we show that for some structural equation models (SEM), the classical chi-square goodness-of-fit test is unable to detect the presence of nonlinear terms in the model. As an example, we consider a regression model with latent variables and interactions terms. Not only the model test has zero power against that type of misspecifications, but even the theoretical (chi-square) distribution of the test is not distorted when severe interaction term misspecification is present in the postulated model. We explain this phenomenon by exploiting results on asymptotic robustness in structural equation models. The importance of this paper is to warn against the conclusion that if a proposed linear model fits the data well according to the chi-quare goodness-of-fit test, then the underlying model is linear indeed; it will be shown that the underlying model may, in fact, be severely nonlinear. In addition, the present paper shows that such insensitivity to nonlinear terms is only a particular instance of a more general problem, namely, the incapacity of the classical chi-square goodness-of-fit test to detect deviations from zero correlation among exogenous regressors (either being them observable, or latent) when the structural part of the model is just saturated.     

Statistical aspects of a three-mode factor analysis model

A special case of Bloxom's version of Tucker's three-mode model is developed statistically. A distinction is made between modes in terms of whether they are fixed or random. Parameter matrices are associated with the fixed modes, while no parameters are associated with the mode representing random observation vectors. The identification problem is discussed, and unknown parameters of the model are estimated by a weighted least squares method based upon a Gauss-Newton algorithm. A goodness-of-fit statistic is presented. An example based upon self-report and peer-report measures of personality shows that the model is applicable to real data. The model represents a generalization of Thurstonian factor analysis; weighted least squares estimators and maximum likelihood estimators of the factor model can be obtained using the proposed theory.This investigation was supported in part by a Research Scientist Development Award (K02-DA00017) and a research grant (DA01070) from the U. S. Public Health Service. The very helpful comments of several anonymous reviewers are gratefully acknowledged.     

ThurCatD: A tool for analyzing ratings on an ordinal category scale

An algorithm for analyzing ordinal scaling results is described. Frequency data on ordinal categories are modeled for unidimensional psychological attributes according to Thurstone’s judgment scaling model. The algorithm applies maximum likelihood estimation of model parameters. The Cramér-Rao bounds of the standard errors of the estimated parameters are calculated, and a stress measure and a goodness-of-fit measure are supplied.     

Analyzing experimental data using the Rasch model

We present a method for studying experimental data based on a psychometric model, the “Rasch model” (Rasch, 1966; Thissen & Steinberg, 1986). We illustrate the method with the use of a data set in the field of concept research. More specifically, we investigate whether a conjunctive concept can be seen as an additive combination of its constituents. High correlations between model and data are obtained, but a formal goodness-of-fit test indicates that the model does not completely account for the data. We then alter the Rasch model in such a way as to capture our idea of why the model deviates from the data. This results in higher correlations and a strong increase in goodness-of-fit. It is concluded that our ideas, as incorporated in the model, adequately summarize the data. More generally, this research illustrates that applying the Rasch model and altering it according to one’s hypotheses is an excellent way to analyze experimental data.     

Assessing model mimicry using the parametric bootstrap

We present a general sampling procedure to quantify model mimicry, defined as the ability of a model to account for data generated by a competing model. This sampling procedure, called the parametric bootstrap cross-fitting method (PBCM; cf. Williams (J. R. Statist. Soc. B 32 (1970) 350; Biometrics 26 (1970) 23)), generates distributions of differences in goodness-of-fit expected under each of the competing models. In the data informed version of the PBCM, the generating models have specific parameter values obtained by fitting the experimental data under consideration. The data informed difference distributions can be compared to the observed difference in goodness-of-fit to allow a quantification of model adequacy. In the data uninformed version of the PBCM, the generating models have a relatively broad range of parameter values based on prior knowledge. Application of both the data informed and the data uninformed PBCM is illustrated with several examples.     

A confirmatory factor analysis of the Impact of Event Scale using a sample of World War II and Korean War veterans

This study assessed the factor structure of the Impact of Event Scale (IES), a measure of intrusion and avoidance, using a sample of World War II and Korean War veterans who had experienced combat 40-50 years earlier. A series of 3 confirmatory factor analytic models were specified and estimated using LISREL 8.3. Model 1 specified a 1-factor model. Model 2 specified a correlated 2-factor model. Model 3 specified a 2-factor model with additional cross-factor loadings for Items 2 and 12. Model 3 was found to fit the data. In addition, this model was found to be a better explanation of the data than the other models. Also in addition, the correlations between the Intrusion and Avoidance factors and the 4 subscales of the 28-item General Health Questionnaire were examined to determine the distinctiveness of the two IES factors.     

The Importance of Complexity in Model Selection

Model selection should be based not solely on goodness-of-fit, but must also consider model complexity. While the goal of mathematical modeling in cognitive psychology is to select one model from a set of competing models that best captures the underlying mental process, choosing the model that best fits a particular set of data will not achieve this goal. This is because a highly complex model can provide a good fit without necessarily bearing any interpretable relationship with the underlying process. It is shown that model selection based solely on the fit to observed data will result in the choice of an unnecessarily complex model that overfits the data, and thus generalizes poorly. The effect of over-fitting must be properly offset by model selection methods. An application example of selection methods using artificial data is also presented. Copyright 2000 Academic Press.     

Multisystemic therapy for young offenders: families' experiences of therapeutic processes and outcomes

Multisystemic Therapy (MST) has been found to be effective in reducing youth antisocial behavior, but little is known about the process and impact of MST from the perspective of families themselves. This qualitative study explored parents' and young people's experiences of MST, focusing on aspects of the intervention that promoted or limited change. Thirty-seven semistructured interviews were conducted with a consecutive sample of 21 families (21 parent interviews, 16 young people) who had participated in a randomized controlled trial of MST for young offenders in the United Kingdom. Thematic analysis yielded 10 themes, organized into two domains: (a) engagement in MST and initial processes of change captures the central importance of the therapeutic relationship and the MST engagement model in families' positive experiences of MST; and (b) outcomes are complex reflects the range of positive outcomes reported (notably increased parental confidence and skills, improved family relationships, a return to education, and greater reflection and aspiration on the part of the young person) and mixed behavior outcomes. Even when the young person had reoffended, respondents indicated a range of other benefits for the family. The findings support the MST theory of change as well as point to some outcomes not usually measured in MST outcome studies. They also suggest some adaptations that may increase the impact of the intervention, including more attention to the influence of deviant peers, and ongoing support for families struggling to maintain strategies beyond the prescribed treatment period.     

Exact person fit indexes for the rasch model for arbitrary alternatives

A new algorithm for obtaining exact person fit indexes for the Rasch model is introduced which realizes most powerful tests for a very general family of alternative hypotheses, including tests concerning DIF as well as model-deviating item correlations. The method is also used as a goodness-of-fit test for whole data sets where the item parameters are assumed to be known. For tests with 30 items at most, exact values are obtained, for longer tests a Monte Carlo-algorithm is proposed. Simulated examples and an empirical investigation demonstrate test power and applicability to item elimination.The author wishes to thank Elisabeth Ponocny-Seliger and the reviewers for many helpful comments. All exact goodness-of-fit tests proposed in this article are implemented in the menu-driven program T-Rasch 1.0 by Ponocny and Ponocny-Seliger (1999) which can be obtained from ProGAMMA (WWW: http://www.gamma.rug.nl) and also performs nonparametric tests.     

初中词汇理解能力量表的编制

应用项目反应理论为初中各年级编制了词汇理解能力的测验,其中包含了１４３个多项选择的词汇项目,经过反复预测和大规模的正式测试,证关了这三个测验的量表拟全于２ＰＬ模型,项目特征曲线拟合度良好的项目占全体项目数９０％以上,能力的一维性也得以确认,经等值化后,各年级的区分度均值分别为０．６１（初一）,０．５９（初二）,０．５５（初三）难度均值分别为－１．６１,－１．３０,－０．５６。     

Multisystemic therapy: monitoring treatment fidelity

The challenges of specifying a complex and individualized treatment model and measuring fidelity thereto are described, using multisystemic therapy (MST) as an example. Relations between therapist adherence to MST principles and instrumental and ultimate outcome variables are examined, as are relations between clinical supervision and therapist adherence. The findings provide modest support for the associations between MST adherence measures and instrumental and ultimate outcomes. Results also show that adherence can be altered when clinical supervision and adherence monitoring procedures are fortified. The modest associations between adherence measures and youth outcomes argue for further refinement and validation of the MST adherence measure, especially in light of the well-established effectiveness of MST with challenging clinical populations and the increasing dissemination of MST programs.     

The Confounding Role of Basic Needs Satisfaction Between Self-Determined Motivation and Well-Being

In this study three different theories grounded on Self-determination macro-theory (Basic Psychological Needs Theory, Organismic Integration Theory, and Hierarchical Model of Intrinsic and Extrinsic Motivation) were combined into a single structural model to evaluate its goodness-of-fit to empirical data. It consisted on a model where basic psychological needs satisfaction was associated directly to well-being, and indirectly through the mediation of self-determined motivation. Since in this model the satisfaction of basic psychological needs would predict positively both self-determined motivation and well-being, basic psychological needs is considered to function as a confounding variable. The participants of the study consisted of 673 Spanish secondary education students (334 girls and 339 boys) with a mean age of 14.0 years (SD = 1.4). The model was confirmed partially. Direct associations between basic psychological needs satisfaction and psychological consequences were found and in the expected directionality. On the contrary, indirect associations between basic psychological needs satisfaction and psychological consequences were found, but generally with the opposite expected directionality. The sign of these indirect associations depended on whether components involved on the associations (basic psychological needs satisfaction, self-determined motivation and psychological consequences) were measured at the same or at different levels. Finally, the results found evidence of the confounding role of basic psychological needs between self-determined motivation and psychological consequences. Implications of these results for Basic Psychological Needs Theory, Organismic Integration Theory, and Hierarchical Model of Intrinsic and Extrinsic Motivation are discussed.     

Assessment of Working Memory Capacity in Preschool Children Using the Missing Scan Task

The purpose of this study was to investigate the feasibility and validity of a modified version of Buschke's missing scan methodology, the Missing Scan Task (MST), to assess working memory capacity (WMC) and cognitive control processes in preschool children 3–6 years in age. Forty typically developing monolingual English‐speaking children between 36 and 84 months in age participated in the study. The children were tested on measures of WMC (MST), verbal and nonverbal memory (NEPSY Narrative Memory and Memory for Designs subtests), and language skills (Peabody Picture Vocabulary Test, fourth edition). Children showed increased working memory capacity scores with age, as measured by the MST, with significant differences between 3‐ and 5‐year‐olds and 3‐ and 6‐year‐olds. Significant correlations were also found between the MST and language and verbal and nonverbal memory scores. MST scores still remained significantly correlated with the other measures of memory even after age and global language were accounted for in a regression analysis, demonstrating that the MST captures unique variance related specifically to WMC and cognitive control processes used to retrieve and scan information in short‐term memory (STM). The results of this study demonstrate that the MST is a feasible and valid methodology for assessing WMC in preschool children as young 3 years of age. Copyright © 2014 John Wiley & Sons, Ltd.     

Inferring the structure of latent class

Present optimization techniques in latent class analysis apply the expectation maximization algorithm or the Newton-Raphson algorithm for optimizing the parameter values of a prespecified model. These techniques can be used to find maximum likelihood estimates of the parameters, given the specified structure of the model, which is defined by the number of classes and, possibly, fixation and equality constraints. The model structure is usually chosen on theoretical grounds. A large variety of structurally different latent class models can be compared using goodness-of-fit indices of the chi-square family, Akaike’s information criterion, the Bayesian information criterion, and various other statistics. However, finding the optimal structure for a given goodness-of-fit index often requires a lengthy search in which all kinds of model structures are tested. Moreover, solutions may depend on the choice of initial values for the parameters. This article presents a new method by which one can simultaneously infer the model structure from the data and optimize the parameter values. The method consists of a genetic algorithm in which any goodness-of-fit index can be used as a fitness criterion. In a number of test cases in which data sets from the literature were used, it is shown that this method provides models that fit equally well as or better than the models suggested in the original articles.     

Testing Process Factor Analysis Models Using the Parametric Bootstrap

Process factor analysis (PFA) is a latent variable model for intensive longitudinal data. It combines P-technique factor analysis and time series analysis. The goodness-of-fit test in PFA is currently unavailable. In the paper, we propose a parametric bootstrap method for assessing model fit in PFA. We illustrate the test with an empirical data set in which 22 participants rated their effects everyday over a period of 90 days. We also explore Type I error and power of the parametric bootstrap test with simulated data.     

贫困大学生元刻板印象威胁对群际关系的影响:群际焦虑的中介和自尊的调节作用

元刻板印象威胁是指消极元刻板印象所导致的群体成员的一种社会心理困境和认知不平衡状态,会诱发压力和害怕体验,进而损害其行为表现。基于群际焦虑模型,本研究拟考查元刻板印象、群际焦虑、自尊等因素对群际关系的影响,具体为贫困大学生消极元刻板印象对群际关系的影响及群际焦虑的中介作用、自尊的调节作用。研究以江苏省徐州市某高校的158名贫困大学生为被试,通过操控指导语的方式将其随机分为威胁组（消极元刻板印象激活组）和无威胁组（元刻板印象未激活组）。结果如下：（1）威胁组被试的群际焦虑水平显著高于无威胁组,群际关系水平显著低于无威胁组;（2）群际焦虑在元刻板印象威胁与群际关系间起中介作用,自尊在前半路径（元刻板印象和群际焦虑间）和后半路径（群际焦虑与群际关系间）均起调节作用。结论：激活贫困大学生消极元刻板印象会对群际关系产生威胁效应。