Three case studies in the Bayesian analysis of cognitive models

Bayesian statistical inference offers a principled and comprehensive approach for relating psychological models to data. This article presents Bayesian analyses of three influential psychological models: multidimensional scaling models of stimulus representation, the generalized context model of category learning, and a signal detection theory model of decision making. In each case, the model is recast as a probabilistic graphical model and is evaluated in relation to a previously considered data set. In each case, it is shown that Bayesian inference is able to provide answers to important theoretical and empirical questions easily and coherently. The generality of the Bayesian approach and its potential for the understanding of models and data in psychology are discussed.     

Neural network applications in consumer behavior

This article introduces the concepts and terminology of artificial neural networks. The approach is demonstrated on data that represent a domain of interest to the consumer psychologist. ANNs are mathematical models that are commonly used in business applications to model relationships between variables. A key strength of ANNs is their flexibility, i.e. their ability to easily accommodate linear and non-linear relationships without any a priori functional form specification. They can easily be used to study topics of interest to consumer psychologists such as persuasion, influence, segmentation etc and can offer distinct advantages over traditional statistical techniques such as ANOVA and regression. We demonstrate the application of ANNs in three different areas: regression, non-linear principal component analysis and classification.     

Assessing the distinguishability of models and the informativeness of data

A difficulty in the development and testing of psychological models is that they are typically evaluated solely on their ability to fit experimental data, with little consideration given to their ability to fit other possible data patterns. By examining how well model A fits data generated by model B, and vice versa (a technique that we call landscaping), much safer inferences can be made about the meaning of a model's fit to data. We demonstrate the landscaping technique using four models of retention and 77 historical data sets, and show how the method can be used to: (1) evaluate the distinguishability of models, (2) evaluate the informativeness of data in distinguishing between models, and (3) suggest new ways to distinguish between models. The generality of the method is demonstrated in two other research areas (information integration and categorization), and its relationship to the important notion of model complexity is discussed.     

Two Models of Moral Judgment

This paper compares two theories and their two corresponding computational models of human moral judgment. In order to better address psychological realism and generality of theories of moral judgment, more detailed and more psychologically nuanced models are needed. In particular, a motivationally based theory of moral judgment (and its corresponding computational model) is developed in this paper that provides a more accurate account of human moral judgment than an existing emotion‐reason conflict theory. Simulations based on the theory capture and explain a range of relevant human data. They account not only for the original data that were used to support the emotion – reason conflict theory, but also for a wider range of data and phenomena.     

我国近十年来心理学研究中HLM方法的应用述评

以2002-2011年中国期刊网收录的50例应用多层线性模型(HLM)的心理学期刊论文为研究对象,从样本描述、模型发展与规范、数据准备、估计方法与假设检验4个角度进行文献计量和内容分析,对我国心理学研究中HLM方法的使用现状进行评估。结果表明,HLM方法主要用于管理、发展和教育心理学,绝大多数应用都是两层模型且层2样本量较大。HLM方法在广泛应用的同时仍存在忽略前提假设检验、分析过程中的重要信息和结果报告不完整等问题,随后提供了4条建议。     

二分数据的多层线性模型:原理与应用

分类数据的多层线性模型在我国的心理学研究中鲜有使用。本研究旨在将这种模型引入到我国心理学研究之中。论文首先介绍了二分数据的多层线性模型的原理和假设条件、参数估计和假设检验,然后以6187名小学生为被试,采用二分变量的多层线性模型,说明了个体因素和学校因素对儿童攻击行为的影响,并对分析结果进行了解释。     

人工智能辅助下的心理健康新型测评

近年来, 人工智能技术的飞速发展及应用催生了“智能化心理健康测评”这一领域。智能化心理健康测评能够弥补传统方法的不足, 降低漏诊率并提高诊断效率, 这对于心理健康问题的普查及预警具有重大意义。目前, 智能化心理健康测评处于初步发展阶段, 研究者基于在线行为数据、便携式设备数据等开展主要以数据驱动为导向的探索研究, 旨在实现更高的预测准确率, 但是测评结果的可解释性等指标尚不够理想。未来的智能化心理健康测评需要强调心理学领域知识和经验的深度介入, 提高测评的针对性和精细化程度, 加强信效度检验, 这对于智能化心理健康测评工具的进一步发展和应用至关重要。     

A modular approach for item response theory modeling with the R package flirt

The new R package flirt is introduced for flexible item response theory (IRT) modeling of psychological, educational, and behavior assessment data. flirt integrates a generalized linear and nonlinear mixed modeling framework with graphical model theory. The graphical model framework allows for efficient maximum likelihood estimation. The key feature of flirt is its modular approach to facilitate convenient and flexible model specifications. Researchers can construct customized IRT models by simply selecting various modeling modules, such as parametric forms, number of dimensions, item and person covariates, person groups, link functions, etc. In this paper, we describe major features of flirt and provide examples to illustrate how flirt works in practice.     

A better lemon squeezer? Maximum-likelihood regression with beta-distributed dependent variables

Uncorrectable skew and heteroscedasticity are among the "lemons" of psychological data, yet many important variables naturally exhibit these properties. For scales with a lower and upper bound, a suitable candidate for models is the beta distribution, which is very flexible and models skew quite well. The authors present maximum-likelihood regression models assuming that the dependent variable is conditionally beta distributed rather than Gaussian. The approach models both means (location) and variances (dispersion) with their own distinct sets of predictors (continuous and/or categorical), thereby modeling heteroscedasticity. The location sub-model link function is the logit and thereby analogous to logistic regression, whereas the dispersion sub-model is log linear. Real examples show that these models handle the independent observations case readily. The article discusses comparisons between beta regression and alternative techniques, model selection and interpretation, practical estimation, and software.     

Between the analytic and the arbitrary: A case study of psychological research

It is argued that psychological theories must be seen as attempts to explicate the conceptual network embedded in ordinary language and that psychological data must be seen as historically constituted. Hence, psychological theory is regarded as, potentially, a system of logically necessary (analytic) theorems, analogous to, e. g., Euclidean geometry, and psychological data are seen as determined by the historical (arbitrary) circumstances that happen to prevail. An instance of published psychological research is shown to contain many unrecognized analytic and arbitrary elements. Its pretensions to generality are contradicted by its highly situation- and culture-bound assumptions, and its pretensions to being empirical are contradicted by the prevalence of necessarily true and necessarily false assumptions. The level of theoretical precision is seen as very low.     

Paradigms in psychosomatic research: a dialectic perspective

By tradition, psychosomatic research has relied on a linear causality model where various psychological and social factors have been correlated to organic disorders. It has become increasingly evident, however, that etiological models based on single causal factors are inadequate. Recently, a reorientation has been noted towards system-oriented multicausality models, which assume that social, psychological, and physiological factors interact in the pathogenesis of a disease. In this review, the limitations and potentials of the linear and system-oriented paradigms are discussed. It is suggested that these perspectives are complementary, and may be applied simultaneously in an integrated, dialectic approach.     

Model-Based Approaches for Teaching and Practicing Personality Assessment

Psychological assessment is a complex professional skill. Competence in assessment requires an extensive knowledge of personality, neuropsychology, social behavior, and psychopathology, a background in psychometrics, familiarity with a range of multimethod tools, cognitive flexibility, skepticism, and interpersonal sensitivity. This complexity makes assessment a challenge to teach and learn, particularly as the investment of resources and time in assessment has waned in psychological training programs over the last few decades. In this article, we describe 3 conceptual models that can assist teaching and learning psychological assessments. The transtheoretical model of personality provides a personality systems-based framework for understanding how multimethod assessment data relate to major personality systems and can be combined to describe and explain complex human behavior. The quantitative psychopathology—personality trait model is an empirical model based on the hierarchical organization of individual differences. Application of this model can help students understand diagnostic comorbidity and symptom heterogeneity, focus on more meaningful high-order domains, and identify the most effective assessment tools for addressing a given question. The interpersonal situation model is rooted in interpersonal theory and can help students connect test data to here-and-now interactions with patients. We conclude by demonstrating the utility of these models using a case example.     

Using connectionist models to guide assessment of psychological disorder

Connectionist models are introduced as promising tools for understanding the nature of psychological disorders and guiding their assessment. Specifically, ways in which connectionist models can guide the following aspects of the assessment process are described: understanding what constructs are relevant to assess, designing approaches to assessing these constructs, and understanding individual differences in data from assessments. Two extended examples are given based on the authors' research on cognitive aspects of depression and Alzheimer's disease.     

心理健康素质测评系统·基本概念、理论与编制构思

作为《心理健康素质测评系统的研制》的开篇报告,本文界定了《心理健康素质测评系统》中所涉及的几个基本概念:素质,心理素质,心理健康,心理健康素质。在经典的素质-应激模型的基础上,提出"应激-素质相互作用模型",作为心理素质影响健康的理论模型。确定了可以用来反映中国成年人心理健康素质的8种心理特质和"类特质"(自我概念,人际心理素质,坚韧性,弹性特质,情绪性,社会期许性,生活信念和健康信念)和两种"亚特质"(认知风格和应对风格)。制定了测评系统的研制计划,并规定了量表编制的技术要求和所要达到的心理测量学指标。     

Note on functional measurement and data analysis

The guiding idea of functional measurement is that measurement theory and substantive theory form an organic unity. Psychological scales are inherent in the statement of quantitative psychological laws, and these laws themselves form the base and frame for psychological measurement. Valid scales thus depend on empirically valid laws. But establishing empirical validity of any law requires appropriate data analysis. Several statistical problems are discussed with respect to simple algebraic laws. To illustrate the necessity for proper tests of goodness of fit for algebraic models, five sets of experimental data are reanalyzed. In each case, the factorial plot and the analysis of variance showed that the data were nonadditive. Nevertheless, an additive model was fit to the data. The correlations between the data and the predictions from the additive model were extremely high, ranging from .964 to .9997. The corresponding observed-predicted scatterplots also gave little sign of the deviations from additivity. These correlation-scatterplot analyses conceal and obscure what the factorial plot and the analysis of variance reveal and make clear. Other topics discussed are accepting and rejecting the null hypothesis, the use of nonmetric smoothing for parameter estimation, and problems of stimulus-response-model generality. An extension of functional measurement is suggested for a practicable error theory for nonmetric analysis.     

Bayes factors for the linear ballistic accumulator model of decision-making

Evidence accumulation models of decision-making have led to advances in several different areas of psychology. These models provide a way to integrate response time and accuracy data, and to describe performance in terms of latent cognitive processes. Testing important psychological hypotheses using cognitive models requires a method to make inferences about different versions of the models which assume different parameters to cause observed effects. The task of model-based inference using noisy data is difficult, and has proven especially problematic with current model selection methods based on parameter estimation. We provide a method for computing Bayes factors through Monte-Carlo integration for the linear ballistic accumulator (LBA; Brown and Heathcote, 2008), a widely used evidence accumulation model. Bayes factors are used frequently for inference with simpler statistical models, and they do not require parameter estimation. In order to overcome the computational burden of estimating Bayes factors via brute force integration, we exploit general purpose graphical processing units; we provide free code for this. This approach allows estimation of Bayes factors via Monte-Carlo integration within a practical time frame. We demonstrate the method using both simulated and real data. We investigate the stability of the Monte-Carlo approximation, and the LBA’s inferential properties, in simulation studies.     

A model for the behavioral assessment of behavior disorders in children: Measurement considerations and practical application

School psychologists have traditionally experienced difficulty in assessing children referred to them for behavior disorders. Given this reported difficulty, a behavioral assessment model is proposed which specifies three types of assessment information: direct observations, rating scale data, and interview data. Characteristics of these three types of assessment information are discussed, along with recommendations for their use. Two psychological models are suggested to guide school psychologists through the assessment process. Bergan's behavioral consultation model is recommended for securing valid and reliable interview and observational data, and Campbell and Fiske's multitrait-multimethod model is proposed as a means of logically integrating behavioral assessment information. The notion of convergence or agreement between dissimilar assessment methods is discussed.     

运用基因表达式编程的自陈量表数据建模

探讨基因表达式编程对自陈量表测量数据的建模方法。运用威廉斯创造力测验和认知需求量表获得400位中学生的测量分数,通过数据清洗,保留383个被试的分数作为建模的数据集。运用哈曼单因素检验方法没有发现共同方法偏差。采用均匀设计方法对基因表达式编程中的5个参数进行优化配置,在测试拟合度最大的试验条件下,找到了测试误差最小的模型。比较基因表达式编程和BP神经网络、支持向量回归机、多元线性回归、二次多项式回归所建模型的预测精度。研究表明,基因表达式编程能用于自陈量表测量数据的建模,该模型比传统方法所建的模型具有更高的预测精度,而且模型是稳健的。     

Contemporary perspectives on the study of psychological climate: A commentary

At the individual level of analysis, we address how work environment perceptions (psychological climate) are conceptualized and measured with respect to three perspectives in the applied psychology literature: (1) social constructionist, (2) general psychological, and (3) multiple stakeholder. Similarities and differences between these perspectives regarding the hypothesized bases of work environment perceptions, factor models for capturing these perceptions, and the generality/specificity of psychological climate factors are discussed. A general framework for conceptualizing and measuring climate perceptions with respect to different referents, organizational levels, industries or sectors, and stakeholder groups is then presented. This framework is posited to include core, generalizable dimensions associated with each relevant stakeholder group. Finally, we recommend methods and discuss future research directions related to the aggregation of individual level climate perceptions to organizational levels.     

Video tape recording: A provocative tool for the school psychologist

The video-tape recorder (VTR) is one of the newest and most versatile instruments available for collection of assessment and research data. It has been used by a psychological consultant to the schools (a) to collect observational data in order to complete referral information and formal test data, (b) to facilitate multiple consultation, and (c) to provide models for test administration for teachers or paraprofessionals. Innovative and imaginative use of the VTR is encouraged.