The typology of parricide and the role of mental illness: Data-driven approach

Parricide is a rare type of homicide in which mental illness is often an important factor. The aims of this study were (a) to describe the characteristics of parricide offenders with a focus on mental illness and clinical care and (b) to examine Heide's widely used typology of parricide through a data-driven approach. We analyzed all homicides in England and Wales between 1997 and 2014. Parricide offenders in our sample were most often male, unmarried, and unemployed, with a third of offenders diagnosed with schizophrenia; 28% had been in contact with mental health services before the offense. The latent class analysis resulted in three types of parricide offenders: middle-aged with affective disorder, previously abused, and seriously mentally Ill, which confirmed, to an extent, Heide's typology. Health and social care services should actively engage with carers of people with mental illness and support to those caring for older relatives and victims of abuse.     

Applying theory to the black box: A model for empirically scoring biodata

Despite being an effective predictor of job performance, empirically keyed biodata assessments have been criticized as black box empiricism unlikely to generalize to new contexts. This paper introduces a model that challenges this perspective, explicating how biodata content, job demands, and criterion variables collectively influence the construct validity, and generalizability of empirically scored biodata. Across two field studies, expected changes in scale correlations with external measures were found that coincided with changes in the contextual similarity between calibration and holdout contexts, the criteria used, and the content validity of biodata items. Collectively, this paper offers a framework that helps understand and optimize empirical biodata keying in practice, furthering confidence for their use in applied settings.     

中学教师工作狂类型与工作绩效的关系研究：基于潜在剖面分析

以229名中学教师对研究对象,采用潜在剖面分析方法探索其工作狂类型,并进一步揭示这些类型与工作绩效间的关系。结果表明:（1）教师按工作狂得分可分为三类：重度工作狂、中等偏高工作狂和中等偏低工作狂;（2）不同类别工作狂会对工作绩效产生不同程度的影响。     

变量间的网络分析模型及其应用

变量间的网络分析模型近年来被广泛应用于心理学研究。不同于将潜变量作为观测变量的共同先导因素的潜变量模型, 网络分析模型将观测变量作为初级指标, 采用图论的方法建立观测变量之间的关系网络, 其中变量为网络的节点, 而变量间的关系是节点之间的连线。因此网络分析可以突显观测变量之间的联系以及观测变量相互影响而形成的系统。通过变量网络中基于各个节点特征的指标(如中心性)以及基于整体结构特征的指标(如小世界性), 网络分析为研究各种心理现象提供了新的可视化的描述方式和理解视角。近10年来, 网络分析的方法已在人格心理学、社会心理学和临床心理学等领域得到一定的应用。未来研究应继续发展和完善网络分析模型的理论和方法, 使之运用到更多的数据类型和更广的研究领域中。     

Idiographic network analysis of discrete mood states prior to treatment

Idiographic network models based on time‐series data have received recent attention for their ability to model relationships among symptoms and behaviours as they unfold in time within a single individual (cf. Epskamp, Borsboom, & Fried, 2018; Fisher, Medaglia, & Jeronimus, 2018). Rather than examine the correlational relationships between variables in a sample of individuals, an idiographic network examines correlations within a single person, averaged over many time points. Because the approach averages over time, the data must be stationary (i.e. relatively consistent over time). If individuals experience varying states over time—different mixtures of symptoms and behaviours in one moment or another—then averaging over categorically different moments may undermine model accuracy. Fisher and Bosley (2019) address these concerns via the application of Gaussian finite mixture modelling to identify latent classes of time points in intraindividual time‐series data from a sample of adults with major depressive disorder and/or generalised anxiety disorder (n = 45). The present paper outlines an extension of this work, wherein network analysis is used to model within‐class covariation of symptoms. To illustrate this approach, network models were constructed for each intraindividual class identified by Fisher and Bosley (137 networks across the 45 participants, mean classes/person = ~3, range = 2–4 classes/person). We examine the relative consistency in symptom organisation between each individual's multiple mood state networks and assess emergent group‐level patterns. We highlight opportunities for enhanced treatment personalisation and review nomothetic patterns relevant to transdiagnostic conceptualisations of psychopathology. We address opportunities for integrating this approach into clinical practice and outline potential shortcomings.     

Psychometric Modeling of response speed and accuracy with mixed and conditional regression

Human performance in cognitive testing and experimental psychology is expressed in terms of response speed and accuracy. Data analysis is often limited to either speed or accuracy, and/or to crude summary measures like mean response time (RT) or the percentage correct responses. This paper proposes the use of mixed regression for the psychometric modeling of response speed and accuracy in testing and experiments. Mixed logistic regression of response accuracy extends logistic item response theory modeling to multidimensional models with covariates and interactions. Mixed linear regression of response time extends mixed ANOVA to unbalanced designs with covariates and heterogeneity of variance. Related to mixed regression is conditional regression, which requires no normality assumption, but is limited to unidimensional models. Mixed and conditional methods are both applied to an experimental study of mental rotation. Univariate and bivariate analyzes show how within-subject correlation between response and RT can be distinguished from between-subject correlation, and how latent traits can be detected, given careful item design or content analysis. It is concluded that both response and RT must be recorded in cognitive testing, and that mixed regression is a versatile method for analyzing test data.I am grateful to Rogier Donders for putting his data at my disposal.     

A person-fit index for polytomous rasch models,latent class models,and their mixture generalizations

A normally distributed person-fit index is proposed for detecting aberrant response patterns in latent class models and mixture distribution IRT models for dichotomous and polytomous data.This article extends previous work on the null distribution of person-fit indices for the dichotomous Rasch model to a number of models for categorical data. A comparison of two different approaches to handle the skewness of the person-fit index distribution is included.Major parts of this paper were written while the first author worked at the Institute for Science Education, Kiel, Germany. Any opinions expressed in this paper are those of the authors and not necessarily of Educational Testing Service. The results presented in this paper were improved by valuable comments from J. Rost, K. Yamamoto, N.D. Verhelst, E. Bedrick and two anonymous reviewers.     

Distractor effect on the latent inhibition of conditioned flavor aversion in rats

Using a conditioned flavor aversion procedure with rats as subjects, the effect of the addition of a distractor stimulus on the magnitude of the latent inhibition effect was examined. Experiment 1 showed that latent inhibition to vinegar was attenuated by the addition of sucrose during preexposure. On the other hand, sucrose added during conditioning to vinegar did not attenuate latent inhibition. It was also found that the degree of latent inhibition to the vinegar-sucrose compound solution was less when vinegar alone was preexposed (i.e., when sucrose was added only during conditioning) than when the compound solution was preexposed (i.e., when sucrose was added both during preexposure and during conditioning). Experiment 2 gave similar results but with sucrose assigned as the target flavor and vinegar as the distractor. These findings are in full agreement with the generalization decrement account of latent inhibition.     

无均值结构的潜变量交互效应模型的标准化估计

潜变量交互效应建模研究近年来有两项重要进展, 一是提出了潜变量交互效应模型的标准化估计及其计算公式; 二是发现无均值结构模型可以取代传统的有均值结构模型, 建模大为简化。但标准化估计是在传统的有均值结构模型中建立的, 在简化的模型中同样适用吗？本文在无均值结构模型的框架内, 给出了潜变量交互效应模型的标准化形式、计算公式和建模步骤, 并通过模拟研究比较了极大似然和广义最小二乘两种估计方法、配对乘积指标和全部乘积指标两种指标类型, 结果表明, 在计算交互效应的标准化估计时, 应当使用配对乘积指标建模, 并且首选极大似然估计。