Modeling Intensive Polytomous Time-Series Eye-Tracking Data: A Dynamic Tree-Based Item Response Model

This paper presents a dynamic tree-based item response (IRTree) model as a novel extension of the autoregressive generalized linear mixed effect model (dynamic GLMM). We illustrate the unique utility of the dynamic IRTree model in its capability of modeling differentiated processes indicated by intensive polytomous time-series eye-tracking data. The dynamic IRTree was inspired by but is distinct from the dynamic GLMM which was previously presented by Cho, Brown-Schmidt, and Lee (Psychometrika 83(3):751–771, 2018). Unlike the dynamic IRTree, the dynamic GLMM is suitable for modeling intensive binary time-series eye-tracking data to identify visual attention to a single interest area over all other possible fixation locations. The dynamic IRTree model is a general modeling framework which can be used to model change processes (trend and autocorrelation) and which allows for decomposing data into various sources of heterogeneity. The dynamic IRTree model was illustrated using an experimental study that employed the visual-world eye-tracking technique. The results of a simulation study showed that parameter recovery of the model was satisfactory and that ignoring trend and autoregressive effects resulted in biased estimates of experimental condition effects in the same conditions found in the empirical study.

     

Accuracy of Predicting a Child's Response to Potential Threat: A Comparison of Children and Their Mothers

Considerable research has indicated that children and their parents often demonstrate marked discrepancies in their reporting of anxiety-related phenomena. In such cases, the question arises as to whether children are capable of accurately reporting on their anxiety. In the present study, 50 children (aged 5 to 14 years) were asked to approach a large, German Shepherd dog. Prior to the task, both the mother and child independently predicted the closest point likely to be reached by the child and the degree of anxiety likely to be experienced. These predictions were then compared with the actual phenomena displayed by the child during the task. On the behavioural measure (closest step reached), both the child and mother demonstrated equivalent predictive accuracy. On the subjective measure (fear ratings) children were considerably more accurate than their mothers. The data were not influenced by gender, age, or clinical status. The results indicate the ability of children to accurately predict their anxious responses, and support the value of incorporating children's self-reports in the assessment of emotional disorders.     

项目反应理论中潜在心理特质“填补”的参数估计方法及其演变

在心理与教育测量中, 项目反应理论(Item Response Theory, IRT)模型的参数估计方法是理论研究与实践应用的基本工具。最近, 由于IRT模型的不断扩展与EM (expectation-maximization)算法自身的固有问题, 参数估计方法的改进与发展显得尤为重要。这里介绍了IRT模型中边际极大似然估计的发展, 提出了它的阶段性特征, 即联合极大似然估计阶段、确定性潜在心理特质“填补”阶段、随机潜在心理特质“填补”阶段, 重点阐述了它的潜在心理特质“填补” (data augmentation)思想。EM算法与Metropolis-Hastings Robbins-Monro (MH-RM)算法作为不同的潜在心理特质“填补”方法, 都是边际极大似然估计的思想跨越。目前, 潜在心理特质“填补”的参数估计方法仍在不断发展与完善。     

Treatment of Adolescent Panic Disorder: A Nonrandomized Comparison of Intensive Versus Weekly CBT

This study compared the relative efficacy of intensive versus weekly panic control treatment (PCT) for adolescent panic disorder with agoraphobia (PDA). Twenty-six adolescents participated in weekly sessions and 25 received intensive treatment involving daily sessions. Both groups demonstrated significant and comparable reductions in panic disorder severity and general anxiety symptoms, which maintained over time. Participants receiving weekly treatment showed significant decreases in depressive symptoms, whereas those in the intensive program reported no change. Findings support the efficacy of the intensive approach for adolescent PDA, but suggest that adolescents receiving intensive treatment may benefit from a brief course of additional weekly sessions.     

Detecting Curvilinear Relationships: A Comparison of Scoring Approaches Based on Different Item Response Models

There is a growing use of noncognitive assessments around the world, and recent research has posited an ideal point response process underlying such measures. A critical issue is whether the typical use of dominance approaches (e.g., average scores, factor analysis, and the Samejima's graded response model) in scoring such measures is adequate. This study examined the performance of an ideal point scoring approach (e.g., the generalized graded unfolding model) as compared to the typical dominance scoring approaches in detecting curvilinear relationships between scored trait and external variable. Simulation results showed that when data followed the ideal point model, the ideal point approach generally exhibited more power and provided more accurate estimates of curvilinear effects than the dominance approaches. No substantial difference was found between ideal point and dominance scoring approaches in terms of Type I error rate and bias across different sample sizes and scale lengths, although skewness in the distribution of trait and external variable can potentially reduce statistical power. For dominance data, the ideal point scoring approach exhibited convergence problems in most conditions and failed to perform as well as the dominance scoring approaches. Practical implications for scoring responses to Likert-type surveys to examine curvilinear effects are discussed.     

2PL模型的两种马尔可夫蒙特卡洛缺失数据处理方法比较

马尔科夫蒙特卡洛（MCMC）是项目反应理论中处理缺失数据的一种典型方法。文章通过模拟研究比较了在不同被试人数,项目数,缺失比例下两种MCMC方法（M-H within Gibbs和DA-T Gibbs）参数估计的精确性,并结合了实证研究。研究结果表明,两种方法是有差异的,项目参数估计均受被试人数影响很大,受缺失比例影响相对更小。在样本较大缺失比例较小时,M-H within Gibbs参数估计的均方误差（RMSE）相对略小,随着样本数的减少或缺失比例的增加,DA-T Gibbs方法逐渐优于M-H within Gibbs方法     

Predicting Readmission to a Child Psychiatric Inpatient Unit: The Impact of Parenting Styles

The risk of rehospitalization after a child receives psychiatric inpatient treatment is generally high. Although disorder-specific behavior contributes to the need for treatment, other environmental variables may also play a role in the need for inpatient psychiatric treatment. Therefore, we examined the influence of parenting styles (authoritarian, authoritative, and permissive) on children’s risk for readmission to an inpatient psychiatric facility. Analyses were conducted with a sample of 80 children (57 males, 50% Black) ranging from 6 to 12 years of age (mean age = 8.90 years). Race was examined as a moderator of the relation between parenting style and risk for readmission. Permissive parenting was the only parenting style that was associated with an increased risk for readmission. The relation between parenting styles and risk for readmission was not moderated by race.     

Item Response Modeling of Paired Comparison and Ranking Data

The comparative format used in ranking and paired comparisons tasks can significantly reduce the impact of uniform response biases typically associated with rating scales. Thurstone's (1927, 1931) model provides a powerful framework for modeling comparative data such as paired comparisons and rankings. Although Thurstonian models are generally presented as scaling models, that is, stimuli-centered models, they can also be used as person-centered models. In this article, we discuss how Thurstone's model for comparative data can be formulated as item response theory models so that respondents' scores on underlying dimensions can be estimated. Item parameters and latent trait scores can be readily estimated using a widely used statistical modeling program. Simulation studies show that item characteristic curves can be accurately estimated with as few as 200 observations and that latent trait scores can be recovered to a high precision. Empirical examples are given to illustrate how the model may be applied in practice and to recommend guidelines for designing ranking and paired comparisons tasks in the future.     

Short- and Long-Term Effects of Inpatient Cognitive-Behavioral Treatment of Adolescents With Anxious-Depressed School Absenteeism: A Within-Subject Comparison of Changes

The effects of inpatient treatment, including manual-guided cognitive-behavioral treatment (CBT), were examined for 36 adolescents (12–18 years) with chronic school absenteeism and mental health problems. Using a within-subject control group design, no changes were noted during the untreated waiting period, whereas there was a strong, statistically significant reduction in school absence rates and mental health problems from the start to the end of inpatient treatment. At discharge, 88.9% of adolescents attended school regularly or were employed (86.1 and 63.9% at 2- and 9-months follow-up, respectively). Self- and parent-reported mental health problems were significantly reduced during treatment and remained stable during follow-up.     

A Comparison of Two Approaches to Counselor-Free Career Exploration

This study was conducted to advance previous research in the use of computer-based, counselor-free career guidance systems instead of conventional counselor-free systems. The participants, Undergraduate college students (20 men and 20 women), were asked to rate their reactions to using the DISCOVER II microcomputer career guidance system and the Self-Directed Search. The majority of the participants preferred the DISCOVER II as a vocational exploration program.     

Women and Alcoholism: A Biopsychosocial Perspective and Treatment Approaches

Viewing alcoholism in women from a biopsychosocial perspective reveals a unique set of circumstances and challenges that women alcoholics face when compared with men. Biologically, women react differently to alcohol ingestion than do men. Women reach higher blood alcohol levels and sustain more somatic and cognitive damage than men when consuming equivalent amounts of alcohol. Psychosocially, women alcoholics face societal rebuke and chastisement of a greater magnitude than do men. Finally, barriers to treatment faced by women, such as the need for child care, cost of treatment, familial opposition, denial of alcoholism, and inadequate diagnostic training of physicians, must be overcome to create successful treatment approaches for the female alcoholic. Obstacles to and implications for treatment are also discussed.     

Review of Growth Modeling: Structural Equation and Multilevel Modeling Approaches (Grimm,Ram & Estabrook, 2017)

Research questions that address developmental processes are becoming more prevalent in psychology and other areas of social science. Growth models have become a popular tool to model multiple individuals measured over several time points. These types of models allow researchers to answer a wide variety of research questions, such as modeling inter- and intra-individual differences and variability in longitudinal process (Molenaar 2004). The recently published book, Growth Modeling: Structural Equation and Multilevel Modeling Approaches (Grimm, Ram & Estabrook 2017), provides a solid foundation for both beginners and more advanced researchers interested in longitudinal data analysis by juxtaposing both the multilevel and structural equation modeling frameworks for several different models. By providing both sufficient technical background and practical coding examples in a variety of both commercial and open-source software, this book should serve as an excellent reference tool for behavioral and methodological researchers interested in growth modeling.

     

Greater Expectations: Using Hierarchical Linear Modeling to Examine Expectancy for Treatment Outcome as a Predictor of Treatment Response

A client's expectation that therapy will be beneficial has long been considered an important factor contributing to therapeutic outcomes, but recent empirical work examining this hypothesis has primarily yielded null findings. The present study examined the contribution of expectancies for treatment outcome to actual treatment outcome from the start of therapy through 12-month follow-up in a clinical sample of individuals (n = 72) treated for fear of flying with either in vivo exposure or virtual reality exposure therapy. Using a piecewise hierarchical linear model, outcome expectancy predicted treatment gains made during therapy but not during follow-up. Compared to lower levels, higher expectations for treatment outcome yielded stronger rates of symptom reduction from the beginning to the end of treatment on 2 standardized self-report questionnaires on fear of flying. The analytic approach of the current study is one potential reason that findings contrast with prior literature. The advantages of using hierarchical linear modeling to assess interindividual differences in longitudinal data are discussed.     

A Comparison of University Students' Approaches to Learning Across Taiwan and Turkey

In this study, university students'approaches to studying were investigated across Turkey and Taiwan. Four hundred sixty-four Turkish university students and 546 Taiwanese university students filled out the Approaches to Studying Inventory (ASI). Approaches to studying was treated as a multidimensional scale with the subdimensions of Meaning Orientation, Reproducing Orientation, and Strategic Orientation. This 3-factor model was fitted across the cultures through the use of linear structural modeling and for each dimension mean differences between Turkish and Taiwanese students were evaluated. The 3-factor model gave sufficient fit regarding goodness-of-fit (GFI) and adjusted goodness-of-fit (AGFI) indexes, and moderate fit regarding the root mean square error of approximation (RMSEA) index within each culture and across the cultures. The means of the Turkish students were found to be significantly greater than the Taiwanese students in all the dimensions.     

Moral Injury,Chaplaincy and Mental Health Provider Approaches to Treatment: A Scoping Review

Journal of Religion and Health - The aim of this research was to describe the evidence examining the approaches taken by mental health providers (MHPs) and chaplains to address symptoms related to...     

Factor Analysis of Ordinal Variables: A Comparison of Three Approaches

Theory and methodology for exploratory factor analysis have been well developed for continuous variables. In practice, observed or measured variables are often ordinal. However, ordinality is most often ignored and numbers such as 1, 2, 3, 4, representing ordered categories, are treated as numbers having metric properties, a procedure which is incorrect in several ways. In this article we describe four approaches to factor analysis of ordinal variables which take proper account of ordinality and compare three of them with respect to parameter estimates and fit. The comparison is made both in terms of their relative methodological advantages and in terms of an empirical data example and two generated data examples. In particular, we discuss the issue of how to test the model and to measure model fit.     

Predicting the Completion of an Integrative and Intensive Outpatient Chronic Pain Treatment With the Personality Assessment Inventory

The X-zero distinction has been used as the operational definition of MMPI item subtlety in previous research. A consistent finding has been that the X items, which are obvious in terms of pathological content, can be faked whereas the more subtle zero items cannot be faked. The present study examined the relationship between instructional sets and endorsement patterns, using a more refined, comprehensive measure of item subtlety. Sixty (30 male, 30 female) subjects completed two MMPI protocols, one under a standard instructional set and the other under either a fake-good or fake-bad response set. Order of administration and sex were counterbalanced. In general, the findings for the subtle-obvious dimension paralleled the previous findings with the X-zero distinction. Endorsement of obvious items was a direct function of instructional set, whereas endorsement of subtle items was inversely related to instructional set. Because subtle items did not appear to measure the constructs for which they had been originally intended, other uses for subtle items were discussed.     

Incorporating Mobility in Growth Modeling for Multilevel and Longitudinal Item Response Data

Multilevel data often cannot be represented by the strict form of hierarchy typically assumed in multilevel modeling. A common example is the case in which subjects change their group membership in longitudinal studies (e.g., students transfer schools; employees transition between different departments). In this study, cross-classified and multiple membership models for multilevel and longitudinal item response data (CCMM-MLIRD) are developed to incorporate such mobility, focusing on students' school change in large-scale longitudinal studies. Furthermore, we investigate the effect of incorrectly modeling school membership in the analysis of multilevel and longitudinal item response data. Two types of school mobility are described, and corresponding models are specified. Results of the simulation studies suggested that appropriate modeling of the two types of school mobility using the CCMM-MLIRD yielded good recovery of the parameters and improvement over models that did not incorporate mobility properly. In addition, the consequences of incorrectly modeling the school effects on the variance estimates of the random effects and the standard errors of the fixed effects depended upon mobility patterns and model specifications. Two sets of large-scale longitudinal data are analyzed to illustrate applications of the CCMM-MLIRD for each type of school mobility.