A latent class unfolding model for analyzing single stimulus preference ratings

A multidimensional unfolding model is developed that assumes that the subjects can be clustered into a small number of homogeneous groups or classes. The subjects that belong to the same group are represented by a single ideal point. Since it is not known in advance to which group of class a subject belongs, a mixture distribution model is formulated that can be considered as a latent class model for continuous single stimulus preference ratings. A GEM algorithm is described for estimating the parameters in the model. The M-step of the algorithm is based on a majorization procedure for updating the estimates of the spatial model parameters. A strategy for selecting the appropriate number of classes and the appropriate number of dimensions is proposed and fully illustrated on some artificial data. The latent class unfolding model is applied to political science data concerning party preferences from members of the Dutch Parliament. Finally, some possible extensions of the model are discussed.The first author is supported as Bevoegdverklaard Navorser of the Belgian Nationaal Fonds voor Wetenschappelijk Onderzoek. Part of this paper was presented at the Distancia meeting held in Rennes, France, June 1992.     

An approximation for the bias function of the maximum likelihood estimate of a latent variable for the general case where the item responses are discrete

Lord developed an approximation for the bias function for the maximum likelihood estimate in the context of the three-parameter logistic model. Using Taylor's expansion of the likelihood equation, he obtained an equation that includes the conditional expectation, given true ability, of the discrepancy between the maximum likelihood estimate and true ability. All terms of orders higher thann ^?1 are ignored wheren indicates the number of items. Lord assumed that all item and individual parameters are bounded, all item parameters are known or well-estimated, and the number of items is reasonably large. In the present paper, an approximation for the bias function of the maximum likelihood estimate of the latent trait, or ability, will be developed using the same assumptions for the more general case where item responses are discrete. This will include the dichotomous response level, for which the three-parameter logistic model has been discussed, the graded response level and the nominal response level. Some observations will be made for both dichotomous and graded response levels.     

Linguistic characteristics of neurotic, borderline and psychotic personality organization

Thirty patients were subjected to a Structural Interview by means of which 10 of them received the diagnosis NPO (Neurotic Personality Organization), 10 BPO (Borderline Personality Organization) and 10 PPO (Psychotic Personality Organization). About 2500 words and groups of words were extracted from the patients' utterances for analysis. The word-frequencies thus found were analyzed by a PLS discriminant analysis which yielded two significant principal components (main dimensions) explaining 57% of the variance. This analysis showed that the three groups of patients are well separated from one another and that there is a definite correlation between personality organization and linguistic variables. The main features of the BPO-patients in this study seem to be that they refer to positions outside themselves and their language is impersonal; we see this as an exemple of a vacillating identity. The NPO-group is characterized by an intense and rich language, signs of a more advanced symbolizing ability, deixis and high level defenses. The language of the PPO-patients is poor and its predominant feature is a lack of words; in our interpretation this indicates foreclosure and a lack of identity.     

儿童最初词汇的获得及其过程

本文追踪研究了两名儿童获得最初词汇的过程。结果表明:在儿童最初语音发展过程中,所发出的音节日益丰富、分化,产生了连续音节,随意性和指向性逐渐增强。儿童获得最初词汇的过程,是连续音节逐渐被有指向的词取代的过程。根据连续音节和有指向的词的比例及沟通作用的变化,儿童获得最初词汇的过程可分为各具特点的三个阶段。两名儿童的最初词汇在其词类构成和功能意义上具有很高的一致性。结合两名儿童之间的个别差异,本文还初步探讨影响儿童获得最初词汇的因素——言语中枢和言语器官的发展、认知的发展,并探讨它们之间可能存在的相互关系。     

信度系数与观测分数和潜在特质的相关比

在经典真分数模型中,信度系数R=D(T)/D(X)。通常认为,信度系数与项目反应理论没有什么联系。事实上,信度系数恰好等于考生观测分数与潜在特质分数的非线性相关比η_(xθ)~2=1-MD(x|θ)/D(X),据此我们得出估计信度系数的一种新途径,同时讨论了x、θ的相关系数与相关比η_(xθ)~2的关系。     

The Relative Contribution of Diagnostic and Psychosocial Variables to Severity of Suicidal Ideation

The present study examined the relative contribution of diagnostic and psychosocial factors to the prediction of severity of suicidal ideation in a sample of 78 college students. Using hierarchical regression analyses to control for each set of factors, psychosocial variables were found to consistently predict level of suicidal ideation. In contrast, diagnostic variables including diagnosis of substance abuse and composite scores for depression and anxiety were unrelated to level of suicidality. An examination of individual diagnoses revealed no predictable relationships with severity of suicidality in this population. The results were discussed from several methodological viewpoints.     

Generalized latent trait models

In this paper we discuss a general model framework within which manifest variables with different distributions in the exponential family can be analyzed with a latent trait model. A unified maximum likelihood method for estimating the parameters of the generalized latent trait model will be presented. We discuss in addition the scoring of individuals on the latent dimensions. The general framework presented allows, not only the analysis of manifest variables all of one type but also the simultaneous analysis of a collection of variables with different distributions. The approach used analyzes the data as they are by making assumptions about the distribution of the manifest variables directly.     

Bayesian inference for finite mixtures of generalized linear models with random effects

We present an hierarchical Bayes approach to modeling parameter heterogeneity in generalized linear models. The model assumes that there are relevant subpopulations and that within each subpopulation the individual-level regression coefficients have a multivariate normal distribution. However, class membership is not known a priori, so the heterogeneity in the regression coefficients becomes a finite mixture of normal distributions. This approach combines the flexibility of semiparametric, latent class models that assume common parameters for each sub-population and the parsimony of random effects models that assume normal distributions for the regression parameters. The number of subpopulations is selected to maximize the posterior probability of the model being true. Simulations are presented which document the performance of the methodology for synthetic data with known heterogeneity and number of sub-populations. An application is presented concerning preferences for various aspects of personal computers.     

Logistic positive exponent family of models: Virtue of asymmetric item characteristic curves

The paper addresses and discusses whether the tradition of accepting point-symmetric item characteristic curves is justified by uncovering the inconsistent relationship between the difficulties of items and the order of maximum likelihood estimates of ability. This inconsistency is intrinsic in models that provide point-symmetric item characteristic curves, and in this paper focus is put on the normal ogive model for observation. It is also questioned if in the logistic model the sufficient statistic has forfeited the rationale that is appropriate to the psychological reality. It is observed that the logistic model can be interpreted as the case in which the inconsistency in ordering the maximum likelihood estimates is degenerated.The paper proposes a family of models, called the logistic positive exponent family, which provides asymmetric item chacteristic curves. A model in this family has a consistent principle in ordering the maximum likelihood estimates of ability. The family is divided into two subsets each of which has its own principle, and includes the logistic model as a transition from one principle to the other. Rationale and some illustrative examples are given.     

Classifying the sense of community trajectories among South Korea adolescents

We examined the longitudinal patterns of the sense of community among the middle and the late adolescents. For this purpose, we used the latent class growth analysis to explore the trajectories of the sense of community, and multinomial logistic regression was conducted to identify the significant predictors. The data for this study were taken from the Korean Children and Youth Panel Survey from 2010 to 2016. The major findings are as follows. First, three latent classes were identified: low‐, middle‐, and high‐level increasing group. Gender, mobile phone addiction, parental affection, household income, peer and teacher relationship, and school activities were significantly associated with the latent classes. On the basis of the results, implications with suggestions for future research were discussed.