Robust Methods for Moderation Analysis with a Two-Level Regression Model

Moderation analysis has many applications in social sciences. Most widely used estimation methods for moderation analysis assume that errors are normally distributed and homoscedastic. When these assumptions are not met, the results from a classical moderation analysis can be misleading. For more reliable moderation analysis, this article proposes two robust methods with a two-level regression model when the predictors do not contain measurement error. One method is based on maximum likelihood with Student's t distribution and the other is based on M-estimators with Huber-type weights. An algorithm for obtaining the robust estimators is developed. Consistent estimates of standard errors of the robust estimators are provided. The robust approaches are compared against normal-distribution-based maximum likelihood (NML) with respect to power and accuracy of parameter estimates through a simulation study. Results show that the robust approaches outperform NML under various distributional conditions. Application of the robust methods is illustrated through a real data example. An R program is developed and documented to facilitate the application of the robust methods.     

The Temporal Relations of PTSD Symptoms Among Treatment-Seeking Victims of Sexual Assault: A Longitudinal Study

This prospective study assessed the temporal relationships between the symptom clusters of PTSD in two nonprobability samples of treatment-seeking victims of sexual abuse: rape victims and adult survivors of childhood sexual abuse. Both groups were assessed at three time periods using self-report measures of PTSD symptomology. Findings from two cross-lagged panel analyses indicated weak temporal relationships between the symptom clusters of PTSD; however, avoidance and emotional numbing symptoms were found to exert the strongest cross-lagged effects. Avoidance and emotional numbing symptoms were also found to be the strongest predictor of subsequently meeting caseness for PTSD in both samples. Results suggest that there are minimal cross-lagged effects between the PTSD symptom clusters after three months from traumatic exposure.     

Random effects and extended generalized partial credit models

In this paper it is shown that under the random effects generalized partial credit model for the measurement of a single latent variable by a set of polytomously scored items, the joint marginal probability distribution of the item scores has a closed-form expression in terms of item category location parameters, parameters that characterize the distribution of the latent variable in the subpopulation of examinees with a zero score on all items, and item-scaling parameters. Due to this closed-form expression, all parameters of the random effects generalized partial credit model can be estimated using marginal maximum likelihood estimation without assuming a particular distribution of the latent variable in the population of examinees and without using numerical integration. Also due to this closed-form expression, new special cases of the random effects generalized partial credit model can be identified. In addition to these new special cases, a slightly more general model than the random effects generalized partial credit model is presented. This slightly more general model is called the extended generalized partial credit model. Attention is paid to maximum likelihood estimation of the parameters of the extended generalized partial credit model and to assessing the goodness of fit of the model using generalized likelihood ratio tests. Attention is also paid to person parameter estimation under the random effects generalized partial credit model. It is shown that expected a posteriori estimates can be obtained for all possible score patterns. A simulation study is carried out to show the usefulness of the proposed models compared to the standard models that assume normality of the latent variable in the population of examinees. In an empirical example, some of the procedures proposed are demonstrated.     

Efficacy of Dialectical Behavior Therapy for Adolescents in a Partial Hospitalization Program

This study evaluated dialectical behavior therapy for adolescents (DBT‐A) vs. treatment as usual within a 6‐week partial hospitalization program. The 103 adolescent participants (mean age = 15.27 years) were predominantly girls (n = 63, 61%) with a variety of primary mental health diagnoses. Results indicated that DBT‐A was superior for decreasing symptoms of depression and interpersonal sensitivity, but no statistically significant difference was detected for anxiety or hostility. Implications for treating youth with transdiagnostic identities are discussed.     

Deformation of nanograined Ni–60Co alloy with low stacking fault energy

The evolution of deformation texture in a Ni–60Co alloy with low stacking fault energy and a grain size in the nanometre range has been investigated. The analyses of texture and microstructure suggest different mechanisms of deformation in nanocrystalline as compared to microcrystalline Ni–60Co alloy. In nanocrystalline material, the mechanism responsible for texture formation has been identified as partial slip, whereas in microcrystalline material, a characteristic texture forms due to twinning and shear banding.     

A tutorial on how to do a Mokken scale analysis on your test and questionnaire data

Over the past decade, Mokken scale analysis (MSA) has rapidly grown in popularity among researchers from many different research areas. This tutorial provides researchers with a set of techniques and a procedure for their application, such that the construction of scales that have superior measurement properties is further optimized, taking full advantage of the properties of MSA. First, we define the conceptual context of MSA, discuss the two item response theory (IRT) models that constitute the basis of MSA, and discuss how these models differ from other IRT models. Second, we discuss dos and don'ts for MSA; the don'ts include misunderstandings we have frequently encountered with researchers in our three decades of experience with real‐data MSA. Third, we discuss a methodology for MSA on real data that consist of a sample of persons who have provided scores on a set of items that, depending on the composition of the item set, constitute the basis for one or more scales, and we use the methodology to analyse an example real‐data set.     

Explanations determine the impact of information on financial investment judgments

Previous research has shown that some types of judgments are influenced by the results of an explanation‐seeking comprehension process. The present experiments investigated novice investors' stock price forecasts and investment decisions. Information presented in a narrative story order was hypothesized to promote the construction of a coherent mental representation that would affect how information was interpreted and subsequently used to predict stock price changes. The results showed that outcome information had a distinctively high impact, but only when the information was read in story order. These results imply that presentation order affects the mental representation of evidence relevant to the forecast, and the form of that mental representation moderates the impact of individual pieces of information on the ultimate judgment. Copyright © 2005 John Wiley & Sons, Ltd.     

Radical Semantics: A New Theory of Meaning

This paper extends Parikh’s earlier work in semantics with games of partial information and attempts to derive and represent the full content of an utterance from first principles. It also discusses various ways in which this content may be indeterminate.     

身份交换对多身份追踪表现的影响

本研究探讨了身份交换对多身份追踪表现的影响。实验1和实验2分别考察了全部报告法和部分报告法下身份交换对多身份追踪表现的具体影响。结果均发现, 身份交换对身份−位置绑定干扰程度越大, 位置追踪和身份识别容量也均越低, 但位置容量始终高于身份容量, 并且这些特性在不同追踪负荷上相同。此外, 部分报告法比全部报告法更具有容量测量优势。实验3则进一步从听觉通道上控制了语音复述对当前任务的干扰, 所得结果仍支持实验1和实验2。这表明, 身份交换对多身份追踪的干扰机制是身份−位置绑定机制受到损害, 而非语音复述的作用。