A maximum likelihood approach to the “test of inclusion”

The method of scoring is used to obtain maximum likelihood estimates of the parameters in the White and Clark learning hierarchy validation model. From the estimate of the proportion of the population possessing only the superordinate skill in a pair of hierarchical skills, and its variance, the hypothesis of inclusion is tested. An illustrative example of the procedure is given.This study is based on doctoral dissertation submitted to the University of Ottawa. The author is indebted to Martin Cooper, Marvin Boss and Jean-Paul Dionne for their assistance.     

A scaling model with response errors and intrinsically unscalable respondents

Goodman contributed to the theory of scaling by including a category of intrinsically unscalable respondents in addition to the usual scale-type respondents. However, his formulation permits only error-free responses by respondents from the scale types. This paper presents new scaling models which have the properties that: (1) respondents in the scale types are subject to response errors; (2) a test of significance can be constructed to assist in deciding on the necessity for including an intrinsically unscalable class in the model; and (3) when an intrinsically unscalable class is not needed to explain the data, the model reduces to a probabilistic, rather than to a deterministic, form. Three data sets are analyzed with the new models and are used to illustrate stages of hypothesis testing.     

On scaling models applied to data from several groups

Statistical methods are presented to facilitate a more complete analysis of results obtained when a scaling model is applied to data from two or more groups. These methods can be used to (a) compare the corresponding estimated latent distributions obtained using the scaling model applied to the different groups, (b) compare the corresponding estimated item reliabilities (or item response error rates) for the different groups, and (c) test whether the scaling model applied to the several groups can be replaced by a more parsimonious scaling model that includes various homogeneity constraints (i.e., constraints that describe which parameters in the model are the same for the several groups). Various kinds of scaling models are considered here in the multiple-group context.Support for this research was provided in part by the National Science Foundation, to Clogg by Grant No. SES-7823759 and to Goodman by Grant No. SES-8303838. Clogg and Goodman were Fellows at the Center for Advanced Study in the Behavioral Sciences when part of the research was done, with financial support provided in part by National Science Foundation grant BNS-8011494 to the Center. The authors are indebted to Mark P. Becker and James W. Shockey for helpful comments.     

On the estimation of parameters in latent structure analysis

In this note, we describe the iterative procedure introduced earlier by Goodman to calculate the maximum likelihood estimates of the parameters in latent structure analysis, and we provide here a simple and direct proof of the fact that the parameter estimates obtained with the iterative procedure cannot lie outside the allowed interval. Formann recently stated that Goodman's algorithm can yield parameter estimates that lie outside the allowed interval, and we prove in the present note that Formann's contention is incorrect.This research was supported in part by Research Contract No. NSF SOC 76-80389 from the Division of the Social Sciences of the National Science Foundation. The author is indebted to C. C. Clogg for helpful comments and for the numerical results reported here (see, e.g., Table 1).     

The use of latent class models for assessing prerequisite relations and transference among traits

This paper presents a strategy for pairwise assessment which may be used to evaluate the nature of both prerequisite and transference relations existing among a set of traits. This strategy is appropriate for use both within a confirmatory context, in which an attempt is made to establish the validity of some specified set of relations among traits, as well as within an exploratory context, in which a search is made for unconjectured prerequisite and transference relations existing between pairs of traits. Both uses of this strategy are based on a variety of latent class models which are representative of various possible relational states existing between pairs of traits. Thus, the nature of trait relations may be investigated through the use of statistical assessments of both absolute and relative fit attained by these models. An application is presented to exemplify how this strategy may be used within the exploratory context.The author is obliged to Clifford Clogg, C. Mitchell, Dayton, and William Schafer for helpful comments made regarding a previous draft of this paper as well as to Mary Papageorgiou who provided access to the data which was considered in this study.     

Defining a Family of Cognitive Diagnosis Models Using Log-Linear Models with Latent Variables

This paper uses log-linear models with latent variables (Hagenaars, in Loglinear Models with Latent Variables, 1993) to define a family of cognitive diagnosis models. In doing so, the relationship between many common models is explicitly defined and discussed. In addition, because the log-linear model with latent variables is a general model for cognitive diagnosis, new alternatives to modeling the functional relationship between attribute mastery and the probability of a correct response are discussed.     

A probabilistic model for validation of behavioral hierarchies

A probabilistic model for the validation of behavioral hierarchies is presented. Estimation is by means of iterative convergence to maximum likelihood estimates, and two approaches to assessing the fit of the model to sample data are discussed. The relation of this general probabilistic model to other more restricted models which have been presented previously is explored and three cases of the general model are applied to exemplary data.     

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。     

Estimating multiple classification latent class models

This paper presents a new class of models for persons-by-items data. The essential new feature of this class is the representation of the persons: every person is represented by its membership tomultiple latent classes, each of which belongs to onelatent classification. The models can be considered as a formalization of the hypothesis that the responses come about in a process that involves the application of a number ofmental operations. Two algorithms for maximum likelihood (ML) and maximum a posteriori (MAP) estimation are described. They both make use of the tractability of the complete data likelihood to maximize the observed data likelihood. Properties of the MAP estimators (i.e., uniqueness and goodness-of-recovery) and the existence of asymptotic standard errors were examined in a simulation study. Then, one of these models is applied to the responses to a set of fraction addition problems. Finally, the models are compared to some related models in the literature.Thanks are to Paul De Boeck for creating the intellectually stimulating atmosphere in which this class of models came about, Iven van Mechelen for theone-sided idea, Kikumi Tatsuoka for the use of her data, and Theodoor Bouw for running part of the simulation study.     

Hard-working in general but lazy at home? Generalized Big Five traits and relationship-specific traits in romantic couples over time

To acknowledge the significance of contexts for personality, this study focused on personality in romantic relationships and the concept of relationship-specific traits. Specifically, we were interested in how relationship-specific traits (i.e., how people report to be in their relationship) relate to generalized Big Five traits, and whether both constructs codevelop over time. We computed dyadic bivariate latent growth curve models, using data from 551 couples (M_age = 32.23 years) over 1 year. The findings indicated that generalized traits and relationship-specific traits were positively correlated in their intercepts but did not codevelop over time. Furthermore, baseline relationship satisfaction explained variance in traits, particularly in relationship-specific traits. These findings have implications for how to study personality development in the romantic relationship context.     

Still Doing Fine? The Interplay of Negative Life Events and Self‐Esteem During Young Adulthood

This longitudinal study investigated the bidirectional relationship between negative life events and self‐esteem during the transition from adolescence to young adulthood (N = 2272). Drawing on theories of human development over the lifespan and just‐world theory, we analyzed age‐graded changes in self‐esteem and their interplay with negative life events at three measurement points over a 12‐year period. We addressed both the short‐term and the longer term effects of single as well as multiple negative life events on changes in self‐esteem (socialization effects). We further investigated whether the pre‐event level of self‐esteem affected the likelihood of negative life events occurring (selection effects) and, finally, whether it had protective effects in terms of helping people adjust to negative events. Latent change models yielded four main findings: (i) self‐esteem increased during young adulthood; (ii) socialization effects were observed over shorter and longer timespans, but (iii) selection effects were only found for multiple negative life events, with low self‐esteem predicting a high number of negative life events; (iv) high pre‐event self‐esteem acted as a protective factor, attenuating declines in self‐esteem after experience of multiple negative life events. Copyright © 2016 European Association of Personality Psychology     

君子有三畏:大学生君子人格的异质性及其与敬畏感的网络关系*

中华优秀传统文化孕育的君子人格对新时代培育积极社会心态具有重要意义。本研究采用整群抽样法,以1235名大学生为对象进行问卷调查,探讨君子人格的异质性及其与敬畏感的网络关系。研究结果表明,大学生君子人格存在异质性,可以分为狷者（32.52%）、中行者（56.92%）和狂者 （10.56%）;不同亚组大学生的敬畏感存在显著差异,以狂者最高;三个亚组的核心节点均为生命敬畏感、道德敬畏感、自然敬畏感和恭而有礼,但在狂者中,恭而有礼的预期影响更大,生命敬畏感、道德敬畏感和自然敬畏感的预期影响更小,恭而有礼与智仁勇的正向关联性、有所不为与关系敬畏感的负向关联性更强。本研究对新时代大学生理想人格塑造和敬畏感培育具有一定的启示,彰显了文化自信。     

Categories and Dimensions

ABSTRACT— The distinction between categories and dimensions has important consequences for basic and applied science in many areas of psychological research. Decisions as to whether individuals should be assigned to groups or located along one or more continua often are based on personal preferences or discipline-specific measurement traditions, which can lead to the creation, use, or reification of spurious categories or dimensions. Methods for evaluating the latent structure of psychological constructs, using powerful and informative tests between competing models, are available. Rather than choosing on a priori grounds, investigators can perform structural research to evaluate the strength and consistency with which results tease apart categorical and dimensional models. Here, we review why researchers should make this distinction empirically, briefly discuss methods available for doing so, and describe the breadth of areas ripe for exploiting the largely untapped potential of structural research.     

Multicomponent latent trait models for ability tests

A major research direction for ability measurement has been to identify the information-processes that are involved in solving test items through mathematical modeling of item difficulty. However, this research has had limited impact on ability measurement, since person parameters are not included in the process models. The current paper presents some multicomponent latent trait models for reproducing test performance from both item and person parameters on processing components. Components are identified from item subtasks, in which performance is a logistic function (i.e., Rasch model) of person and item parameters, and then are combined according to a mathematical model of processing on the composite item.The author would like to thank David Thissen for his invaluable insights concerning this model and an anonymous reviewer for his suggestion about the sample space for the model.This research was partially supported by National Institute of Education grant number NIE-6-7-0156 to Susan E. Whitely, principal investigator. However the opinions expressed herein do not necessarily reflect the position or policy of the National Institute of Education, and no official endorsement by the National Institute of Education should be referred. Part of this paper was presented at the annual meeting of thePsychometric Society, Monterey, California: June, 1979.     

Personality profiles and health: Longitudinal evidence among Finnish adults

Kinnunen, M.‐L., Metsäpelto, R. L., Feldt, T., Kokko, K., Tolvanen, A., Kinnunen, U., Leppänen, E. & Pulkkinen, L. (2012). Personality profiles and health: Longitudinal evidence among Finnish adults. Scandinavian Journal of Psychology 53, 512–522. This study investigates the associations of longitudinal Big Five personality profiles with long‐term health in 304 adults (53% males). Personality traits (Neuroticism, Extraversion, Openness, Conscientiousness, Agreeableness) were assessed at ages 33, 42, and 50. Subjective (self‐rated health, symptoms, psychological distress) and objective (body mass index, waist‐to‐hip ratio, blood pressure, cholesterol, triglycerides) indicators of health were measured at ages 42 and 50. Five longitudinally stable personality profiles were extracted over 17 years by latent profile analysis. The levels of traits were the same in each profile at each age. Resilient individuals (N = 65; Neuroticism low, other traits high) had the best subjective health and Overcontrolled individuals (N = 40; Neuroticism high, other traits low) the poorest health over eight years. Reserved individuals (N = 25; high Conscientiousness, other traits low), Undercontrolled (N = 41; high Openness and Extraversion, low Conscientiousness), and Ordinary (N = 133; all traits scored medium) individuals were in the middle of these extremes in subjective health. No differences between the profiles were found in the objective indicators of health. Thus, overcontrol and resilience were most discriminative in terms of good health. Moreover, personality profiles revealed associations with health to be more nuanced than simply being composed of single traits. High Extraversion needed to be combined with high Conscientiousness (Resilients) in order to be associated with the best health; high Extraversion with low Conscientiousness (Undercontrolled) was associated with average health; and low Extraversion with high Neuroticism (Overcontrolled) was associated with the poorest health.