Conditions for factor (in)determinacy in factor analysis

The subject of factor indeterminacy has a vast history in factor analysis (Guttman, 1955; Lederman, 1938; Wilson, 1928). It has lead to strong differences in opinion (Steiger, 1979). The current paper gives necessary and sufficient conditions for observability of factors in terms of the parameter matrices and a finite number of variables. Five conditions are given which rigorously define indeterminacy. It is shown that (un)observable factors are (in)determinate. Specifically, the indeterminacy proof by Guttman is extended to Heywood cases. The results are illustrated by two examples and implications for indeterminacy are discussed.     

THE IMPACT OF APPLIED BEHAVIOR ANALYSIS ON DIVERSE AREAS OF RESEARCH1

The impact of applied behavior analysis on various disciplines and areas of research was assessed through two major analyses. First, the relationship of applied behavior analysis to the general area of “behavior modification” was evaluated by examining the citation characteristics of journal articles in JABA and three other behavior-modification journals. Second, the penetration of applied behavior analysis into diverse areas and disciplines, including behavior modification, psychiatry, clinical psychology, education, special education, retardation, speech and hearing, counselling, and law enforcement and correction was assessed. Twenty-five journals representing diverse research areas were evaluated from 1968 to 1974 to assess the extent to which operant techniques were applied for therapeutic, rehabilitative, and educative purposes and the degree to which methodological desiderata of applied behavior analysis were met. The analyses revealed diverse publication outlets for applied behavior analysis in various disciplines.     

Integrating personality and career adaptability into vocational interest space

The relations between interests, personality and career adaptability were explored in two separate studies. In the first study, the RIASEC measure Occupational Preference Scale was applied along with personality inventories HEXACO-PI-(R)-100 and IPIP-50 on a sample of 602 university students and young adults. In the second study, PGI-Short, HEXACO-60 and Career Adapt-Abilities Scale were applied on a sample of 981 high-school graduates. Results from both studies were discussed together, and general conclusions about overlapping of interests, personality and career adaptability domains were drawn on the basis of correlational analyses and property vector fitting. Both studies have shown weak to moderate relations between interests and personality. In the HEXACO framework, it was found that Openness to Experience was positively related to creative interests, Emotionality was positively related to social interests and negatively related to technical interests, Extraversion was positively related to social and managing interests, and Honesty–Humility was negatively related to interests for business and finance. In the Big Five framework, Agreeableness was related to Social and Artistic interests, and Intellect to Artistic interests. The HEXACO personality domains showed predictive advantage for explaining interests in comparison to Big Five dimensions. The relation between career adaptability and interests was weak, and almost negligible when personality was included in hierarchical regression analysis. Career adaptability was weakly related to highly prestigious interests. Adaptability facets Concern, Control and Confidence were oriented toward data pole of interest space. The general factor of interests was weakly correlated with Openness Extraversion, Career Adaptability, and adaptability facets Confidence and Curiosity. Observed findings are as expected and in line with previous research.     

Multi‐set factor analysis by means of Parafac2

We consider multi‐set data consisting of observations, k = 1,…, K (e.g., subject scores), on J variables in K different samples. We introduce a factor model for the J × J covariance matrices , k = 1,…, K, where the common part is modelled by Parafac2 and the unique variances , k = 1,…, K, are diagonal. The Parafac2 model implies a common loadings matrix that is rescaled for each k, and a common factor correlation matrix. We estimate the unique variances by minimum rank factor analysis on for each k. The factors can be chosen orthogonal or oblique. We present a novel algorithm to estimate the Parafac2 part and demonstrate its performance in a simulation study. Also, we fit our model to a data set in the literature. Our model is easy to estimate and interpret. The unique variances, the factor correlation matrix and the communalities are guaranteed to be proper, and a percentage of explained common variance can be computed for each k. Also, the Parafac2 part is rotationally unique under mild conditions.     

Moving in Parallel Toward a Modern Modeling Epistemology: Bayes Factors and Frequentist Modeling Methods

The Bayesian-frequentist debate typically portrays these statistical perspectives as opposing views. However, both Bayesian and frequentist statisticians have expanded their epistemological basis away from a singular focus on the null hypothesis, to a broader perspective involving the development and comparison of competing statistical/mathematical models. For frequentists, statistical developments such as structural equation modeling and multilevel modeling have facilitated this transition. For Bayesians, the Bayes factor has facilitated this transition. The Bayes factor is treated in articles within this issue of Multivariate Behavioral Research. The current presentation provides brief commentary on those articles and more extended discussion of the transition toward a modern modeling epistemology. In certain respects, Bayesians and frequentists share common goals.     

Nesselroade and Molenaar's Measurement Concerns and Proposals: An Introduction

In this special section Nesselroade and Molenaar (N & M) propose a provocative new approach to measurement invariance. When measures are collected repeatedly over time (e.g., daily diary studies), a potentially unique measurement model relating the items to the underlying construct can be created for each individual. If hypothesized causal paths specified between constructs (e.g., frustration → aggression) can be constrained to be equal across the individuals, a model with idiographic measurement of the constructs, but with nomothetic structural relationships can be specified. Three commentaries react to N & M's proposal. Revelle and Wilt challenge the priority given by N & M to unique individual measurement structures, arguing that between subjects differences in structural relationships are empirically important and meaningful. Markus's uses David Hume's framework to raise philosophy of science challenges for N & M's approach. Maydeu-Olivares challenges the incremental validity of N & M's approach, arguing that N & M's approach is unlikely to improve the prediction of between subjects criteria. Finally, N & M present a rejoinder to the three commentaries.     

Cross‐cultural Generalizability of the Alternative Five‐factor Model Using the Zuckerman–Kuhlman–Aluja Personality Questionnaire

Several personality models are known for being replicable across cultures, such as the Five‐Factor Model (FFM) or Eysenck's Psychoticism–Extraversion–Neuroticism (PEN) model, and are for this reason considered universal. The aim of the current study was to evaluate the cross‐cultural replicability of the recently revised Alternative FFM (AFFM). A total of 15 048 participants from 23 cultures completed the Zuckerman–Kuhlman–Aluja Personality Questionnaire (ZKA‐PQ) aimed at assessing personality according to this revised AFFM. Internal consistencies, gender differences and correlations with age were similar across cultures for all five factors and facet scales. The AFFM structure was very similar across samples and can be considered as highly replicable with total congruence coefficients ranging from .94 to .99. Measurement invariance across cultures was assessed using multi‐group confirmatory factor analyses, and each higher‐order personality factor did reach configural and metric invariance. Scalar invariance was never reached, which implies that culture‐specific norms should be considered. The underlying structure of the ZKA‐PQ replicates well across cultures, suggesting that this questionnaire can be used in a large diversity of cultures and that the AFFM might be as universal as the FFM or the PEN model. This suggests that more research is needed to identify and define an integrative framework underlying these personality models. Copyright © 2016 European Association of Personality Psychology     

结构需求:概念、测量及与相关变量的关系

结构需求是个体对简单结构、清晰有条理的事物与环境的偏爱和需要,其本质是一种动机,个体通常会以结构严密、有条理或简化复杂信息的认知加工方式将其表现出来。结构需求存在着个体差异性。高结构需求水平的个体能够简化复杂的信息和环境,以清晰和简单的表征与描述去理解、建构他们的世界,从而减少认知资源的支出和消耗,提高认知操作的效率,维持认知与行为倾向的内在稳定。研究者梳理了结构需求的概念内涵、理论基础,介绍了两种主要的结构需求测量工具(PNS-12量表,PNS-11量表),以及结构需求的相关研究,分别从结构需求的前因变量、结果变量的角度对其相关研究进行了阐述。未来研究应深入探究结构需求的概念与结构,拓展其研究方法,研发更加有效的测评工具,深入探讨其影响机制,开展结构需求的中国化研究。