Nonlinear Indicator-Level Moderation in Latent Variable Models

Linear, nonlinear, and nonparametric moderated latent variable models have been developed to investigate possible interaction effects between a latent variable and an external continuous moderator on the observed indicators in the latent variable model. Most moderation models have focused on moderators that vary across persons but not across the indicators (e.g., moderators like age and socioeconomic status). However, in many applications, the values of the moderator may vary both across persons and across indicators (e.g., moderators like response times and confidence ratings). Indicator-level moderation models are available for categorical moderators and linear interaction effects. However, these approaches require respectively categorization of the continuous moderator and the assumption of linearity of the interaction effect. In this article, parametric nonlinear and nonparametric indicator-level moderation methods are developed. In a simulation study, we demonstrate the viability of these methods. In addition, the methods are applied to a real data set pertaining to arithmetic ability.     

Motion planning strategies in human control of non-rigid objects with internal degrees of freedom

The paper deals with modeling of human-like reaching movements in dynamic environments. A simple but not trivial example of reaching in a dynamic environment is the rest-to-rest manipulation of a multi-mass flexible object with the elimination of residual vibrations. Two approaches to the prediction of reaching movements are formulated in position and force actuation settings. In the first approach, either the position of the hand or the hand force is specified by the lowest order polynomial satisfying the boundary conditions of the reaching task. The second approach is based on the minimization of either the hand jerk or the hand force-change, with taking into account the dynamics of the flexible object. To verify the resulting four mathematical models, an experiment on the manipulation of a ten-masses flexible object of low stiffness is conducted. The experimental results show that the second approach gives a significantly better prediction of human movements, with the minimum hand force-change model having a slight but consistent edge over the minimum hand jerk one.     

Trait rumination and response to negative evaluative lab-induced stress: neuroendocrine,affective, and cognitive outcomes

Theoretical models of depression posit that, under stress, elevated trait rumination predicts more pronounced or prolonged negative affective and neuroendocrine responses, and that trait rumination hampers removing irrelevant negative information from working memory. We examined several gaps regarding these models in the context of lab-induced stress. Non-depressed undergraduates completed a rumination questionnaire and either a negative-evaluative Trier Social Stress Test (n?=?55) or a non-evaluative control condition (n?=?69), followed by a modified Sternberg affective working memory task assessing the extent to which irrelevant negative information can be emptied from working memory. We measured shame, negative and positive affect, and salivary cortisol four times. Multilevel growth curve models showed rumination and stress interactively predicted cortisol reactivity; however, opposite predictions, greater rumination was associated with blunted cortisol reactivity to stress. Elevated trait rumination interacted with stress to predict augmented shame reactivity. Rumination and stress did not significantly interact to predict working memory performance, but under control conditions, rumination predicted greater difficulty updating working memory. Results support a vulnerability-stress model of trait rumination with heightened shame reactivity and cortisol dysregulation rather than hyper-reactivity in non-depressed emerging adults, but we cannot provide evidence that working memory processes are critical immediately following acute stress.     

Biased belief in the Bayesian brain: A deeper look at the evidence

A recent critique of hierarchical Bayesian models of delusion argues that, contrary to a key assumption of these models, belief formation in the healthy (i.e., neurotypical) mind is manifestly non-Bayesian. Here we provide a deeper examination of the empirical evidence underlying this critique. We argue that this evidence does not convincingly refute the assumption that belief formation in the neurotypical mind approximates Bayesian inference. Our argument rests on two key points. First, evidence that purports to reveal the most damning violation of Bayesian updating in human belief formation is counterweighted by substantial evidence that indicates such violations are the rare exception—not a common occurrence. Second, the remaining evidence does not demonstrate convincing violations of Bayesian inference in human belief updating; primarily because this evidence derives from study designs that produce results that are not obviously inconsistent with Bayesian principles.     

恋爱受挫对自我—他人工作模型的影响

摘 要 该研究使用内隐联想测验（IAT）考察了成人依恋的主要表现形式恋爱关系中,恋爱受挫对被试自我—他人工作模型的影响。结果表明：（1）虽然实验组与控制组在依恋焦虑、依恋回避得分上均无显著差异,但IAT结果发现,组别、依恋类型在IAT效应（自我积极—他人消极模型指标）上的主效应显著,其交互作用也显著。除了回避型被试,安全型和焦虑型实验组的IAT效应显著高于控制组。（2）控制组中,焦虑型被试相容部分反应时显著大于不相容部分,回避型被试则相容部分反应时显著小于不相容部分,安全型被试无显著差异。     

使用验证性补偿多维IRT模型进行认知诊断评估

随着人们对测验反馈结果精细化的需求逐渐提高, 具有认知诊断功能的测量方法逐渐受到人们的关注。在认知诊断模型(CDMs)闪耀着光芒的同时, 另一类能够在连续量尺上提供精细反馈的多维IRT模型(MIRTMs)似乎受到些许冷落。为探究MIRTMs潜在的认知诊断功能, 本文以补偿模型为视角, 聚焦于分别属于MIRTMs的多维两参数logistic模型(M2PLM)和属于CDMs的线性logistic模型(LLM); 之后为使两者具有可比性, 可对补偿M2PLM引入验证性矩阵(Q矩阵)来界定题目与维度之间的关系, 进而得到验证性的补偿M2PLM (CC-M2PLM), 并通过把潜在特质按切点划分为跨界属性, 以期使CC-M2PLM展现出其本应具有的认知诊断功能; 预研究表明logistic量尺上的0点可作为相对合理的切点; 然后, 通过模拟研究对比探究CC-M2PLM和LLM的认知诊断功能, 结果表明CC-M2PLM可用于分析诊断测验数据, 且认知诊断功能与直接使用LLM的效果相当; 最后, 以两则实证数据为例来说明CC-M2PLM在实际诊断测验分析中的可行性。     

Logistic加权模型的理论构建与模拟分析

试题难度、试题考查重要性程度加权是多级记分试题的两个基本属性, 因而在IRT项目特征函数中需用不同参数来表示。以往多级记分模型用多个难度参数来描述多级记分试题的难度, 不能有效的表达多级记分试题的分数权重作用。从多级记分试题的分数加权作用角度, 本文提出Logistic加权模型并论述了理论构建思想。在Logistic加权模型下对项目参数估计的EM算法进行推导并编写了相应的参数估计程序。在Logistic加权模型下进行测验模拟, 发现项目参数估计的模拟返真性能良好。     

Response style analysis with threshold and multi‐process IRT models: A review and tutorial

Two different item response theory model frameworks have been proposed for the assessment and control of response styles in rating data. According to one framework, response styles can be assessed by analysing threshold parameters in Rasch models for ordinal data and in mixture‐distribution extensions of such models. A different framework is provided by multi‐process item response tree models, which can be used to disentangle response processes that are related to the substantive traits and response tendencies elicited by the response scale. In this tutorial, the two approaches are reviewed, illustrated with an empirical data set of the two‐dimensional ‘Personal Need for Structure’ construct, and compared in terms of multiple criteria. Mplus is used as a software framework for (mixed) polytomous Rasch models and item response tree models as well as for demonstrating how parsimonious model variants can be specified to test assumptions on the structure of response styles and attitude strength. Although both frameworks are shown to account for response styles, they differ on the quantitative criteria of model selection, practical aspects of model estimation, and conceptual issues of representing response styles as continuous and multidimensional sources of individual differences in psychological assessment.     

Animal cognition + optimal choice = behavior: A review of adaptive behavior and learning, 2nd Ed., by J. E. R. Staddon

Staddon discusses a vast array of topics in comparative psychology in this book. His view is that adaptive behavior in most cases is the result of optimal choice acting on an animal's knowledge about the world. Staddon refers to this as a functional teleonomic approach inasmuch as it attempts to understand an animal's behavior in terms of goals. He builds mathematical models based on this idea that are designed to reproduce specific sets of empirical observations, usually qualitatively. A natural consequence of Staddon's approach is that many models are developed, each of which applies to a specific set of observations. An alternative to functional teleonomy is a functional approach that builds on prior principles. In most cases, this approach favors a single‐theory account of behavior. Prior principles can be understood as functional stand‐ins for antecedent material causes, which means that these accounts are closer to mechanistic theories than are goal‐based teleonomic accounts. An ontological perspective, referred to as supervenient realism, is a means of understanding the relationship between functional theories and the material world. According to this perspective, the algorithmic operation of a successful functional theory may be understood to supervene on the material operation of the nervous system.     

(Re)evaluating the Implications of the Autoregressive Latent Trajectory Model Through Likelihood Ratio Tests of Its Initial Conditions

The autoregressive latent trajectory (ALT) model synthesizes the autoregressive model and the latent growth curve model. The ALT model is flexible enough to produce a variety of discrepant model-implied change trajectories. While some researchers consider this a virtue, others have cautioned that this may confound interpretations of the model's parameters. In this article, we show that some—but not all—of these interpretational difficulties may be clarified mathematically and tested explicitly via likelihood ratio tests (LRTs) imposed on the initial conditions of the model. We show analytically the nested relations among three variants of the ALT model and the constraints needed to establish equivalences. A Monte Carlo simulation study indicated that LRTs, particularly when used in combination with information criterion measures, can allow researchers to test targeted hypotheses about the functional forms of the change process under study. We further demonstrate when and how such tests may justifiably be used to facilitate our understanding of the underlying process of change using a subsample (N = 3,995) of longitudinal family income data from the National Longitudinal Survey of Youth.