Idiodynamic Profiles of Cardiovascular Activity: A P-technique Approach

A study was conducted to expand the conventional view of cardiovascular (CV) reactivity by using the idiodynamic paradigm for investigation of individuals. Patterns of autonomic CV regulation were assessed in six subjects across diverse laboratory tasks on three separate occasions. Individual CV profiles were derived from these data with P-technique factor analysis, and then group aggregated with chain P-technique. The composite pattern suggested a three-component solution consisting of cardiac rate, cardiac contractility, and peripheral resistance factors. Individual profiles were compared to the composite pattern; these profiles differed in the number of components derived, percentage variance explained by these components, and relative dominance of specific CV components. A hypothesis that emerged is that the subjects differed in the complexity of CV control. It appears that the idiodynamic framework, combined with novel research designs and statistical methods, may help expand the view of CV reactivity beyond the traditional unitary view as response magnitude.     

Idiodynamic profiles of cardiovascular activity: A P-technique approach

A study was conducted to expand the conventional view of cardiovascular (CV) reactivity by using the idiodynamic paradigm for investigation of individuals. Patterns of autonomic CV regulation were assessed in six subjects across diverse laboratory tasks on three separate occasions. Individual CV profiles were derived from these data with P-technique factor analysis, and then group aggregated with chain P-technique. The composite pattern suggested a three-component solution consisting of cardiac rate, cardiac contractility, and peripheral resistance factors. Individual profiles were compared to the composite pattern; these profiles differed in the number of components derived, percentage variance explained by these components, and relative dominance of specific CV components. A hypothesis that emerged is that the subjects differed in the complexity of CV control. It appears that the idiodynamic framework, combined with novel research designs and statistical methods, may help expand the view of CV reactivity beyond the traditional unitary view as response magnitude.     

探索性因素分析因子抽取方法的比较

探索性因素分析决定因子抽取的方法主要有Bartlett法、K1原则、碎石检验法、Aaker原则、PA、MAP等六种,通过对样本1的395名大学生的学习过程问卷调查获得真实数据,运用这六种方法进行因素分析分别抽取7、4、2、4、3、2个因子;应用样本2的383名大学生的问卷调查数据进行验证性因素分析,结果显示,碎石检验方法与MAP方法抽取的二因素模型更理想。研究表明,因子抽取需兼顾“简约性原则”与“完备性原则”,同时要根据一定的理论建构、专业知识和经验来决定因子数。     

平行分析在探索性因素分析中的应用

平行分析是探索性因素分析中用来确定所保留的凶子个数的一种方法。探索性因素分析中常用的确定因子个数的方法有特征值大于1准则和碎石图,但这两种方法又各有不足。平行分析则为探索性因素分析中所保留因子个数的确定提供了另一种新思路。本文详细介绍了平行分析的步骤、潜在逻辑以及进行平行分析所用的软件,并通过实例来说明其在探索性因素分析中如何应用。     

Intraindividual differences dimensions of mood change during pregnancy identified in five P-technique factor analyses

Daily-self-ratings of mood and state were obtained for approximately 120 days of observation from five pregnant subjects. Measurements were based on a total pool of 75 adjectives culled from the literature to represent eight dimensions of affect established in primarily cross-sectional studies. The data were analyzed in a P-technique factor analysis context to determine both the extent to which interindividual differences and intraindividual variability concepts were interchangeable and how general such intraindividual variability concepts were among different subjects. Although evidence was found that subjects construe many adjectives differently, for dimensions such as Energy, Well Being, Fatigue, and Concentration, the data indicate that cross-sectionally and longitudinally based personality concepts exhibit a fair degree of convergence.     

P-technique demonstrated in determining psycho-physiological source traits in a normal individual

P-technique, a method employing intra-individual correlation, is tried out for the first time. As part of the general design it uses some variables the same as those in a coordinatedR-technique study and a second, parallelP-technique study with a clinical case. Definite factors are obtained among the psychological and physiological variables, which can be mutually matched. One is a fatigue factor, but the rest are general personality factors readily identifiable with those obtained in pastR-technique researches.     

The Infinitesimal Jackknife with Exploratory Factor Analysis

The infinitesimal jackknife, a nonparametric method for estimating standard errors, has been used to obtain standard error estimates in covariance structure analysis. In this article, we adapt it for obtaining standard errors for rotated factor loadings and factor correlations in exploratory factor analysis with sample correlation matrices. Both maximum likelihood estimation and ordinary least squares estimation are considered.     

全息项目因素分析在心理学研究中的应用

文章首先指出了经典线性因素分析的种种局限;然后介绍了一种基于“被试—项目矩阵”而非仅仅协方差矩阵或相关矩阵的全息项目因素分析,该方法能克服经典线性因素分析的种种局限,在心理学研究中尤其是人格研究中有着其他因素分析方法不可替代的作用。     

P-technique factor analyses of the Multiple Affect Adjective Check List (MAACL)

The Multiple Affect Adjective Check List (MAACL) has been found to have five first-order factors representing Anxiety, Depression, Hostility, Positive Affect, and Sensation Seeking and two second-order factors representing Positive Affect and Sensation Seeking (PASS) and Dysphoria. The present study examines whether these first- and second-order conceptions of affect (based on R-technique factor analysis) can also account for patterns of intraindividual variability in affect (based on P-technique factor analysis) in eight elderly women. Although the hypothesized five-factor model of affect was not testable in all of the present P-technique datasets, the results were consistent with this interindividual model of affect. Moreover, evidence of second-order (PASS and Dysphoria) and third-order (generalized distress) factors was found in one data set. Sufficient convergence in findings between the present P-technique research and prior R-technique research suggests that the MAACL is robust in describing both inter- and intraindividual components of affect in elderly women.This paper is based on the doctoral research of the first author and was partially supported by the National Institute of Aging Grant T32 AC 00048-12 to The Pennsylvania State University and a Grant-in-Aid of Research from Sigma Xi, The Scientific Research Society. The authors wish to thank John R. Nesselroade for his helpful comments on an early draft of this paper.     

Clustered Common Factor Exploration in Factor Analysis

Psychometrika - The factor analysis (FA) model does not permit unique estimation of the common and unique factor scores. This weakness is notorious as the factor indeterminacy in FA. Luckily, some...     

Factor Analysis via Components Analysis

When the factor analysis model holds, component loadings are linear combinations of factor loadings, and vice versa. This interrelation permits us to define new optimization criteria and estimation methods for exploratory factor analysis. Although this article is primarily conceptual in nature, an illustrative example and a small simulation show the methodology to be promising.     

The Factor Structure of the Figural Torrance Tests of Creative Thinking: A Meta-Confirmatory Factor Analysis

To investigate the factor structure of the Figural Torrance Tests of Creative Thinking (Figural TTCT), a meta-confirmatory factor analysis was performed. A sample of 33 correlation matrices from 26 studies (N_individuals = 6,982) was included in the meta-analysis. Four different factor models previously presented in the literature were tested to determine which model fits the data best. The results supported a 2-factor structure model in which fluency and originality subscales loaded on the innovative factor; elaboration, abstractness of titles, and resistance to premature closure subscales loaded on the adaptive factor. Implications, limitations, and suggestions for future research are discussed.     

管理人员个性的因子分析及其科学评价问题的研究

本研究通过对管理人员进行卡特尔个性测验,经过因素分析得出管理人员个性的主要因素子。通过多重方差分析,发现不同级别的管理人员主要的个性差异。这些人性特征是选择和评价管理人员的主要方面。     

用验证性因素分析法对控制源量表的分析研究

验证性因素分析方法克服了传统的探索性因素分析的不足,为心理学发展和研究的精细化、数学化提供了更可行的途径。本研究运用验证性因素分析方法对心理控制源量表进行了分析研究,研究发现L1SREL软件对SPSS不能分析出来的因素可以进一步地给予精确数据。     

医患认知差异的因素分析与调适研究

医患认知差异是指医生与患者在诊疗过程中对同一事实和现象的认知之间的差异、矛盾与对立,它是导致医患冲突的深层次诱因。从传统生物医学模式的制约、医忘双方社会角色意识的差异以及医患个体心理特征的差异三方面分析了医患认知差异产生的原因,并从转变角色意识、相互理解和配合、有效的双向沟通以及尊重双方的人格和权利几方面提出了化解矛盾、认知趋同的措施。     

The Use of Exploratory Factor Analysis and Principal Components Analysis in Communication Research

Exploratory factor analysis is a popular statistical technique used in communication research. Although exploratory factor analysis (EFA) and principal components analysis (PCA) are different techniques, PCA is often employed incorrectly to reveal latent constructs (i.e., factors) of observed variables, which is the purpose of EFA. PCA is more appropriate for reducing measured variables into a smaller set of variables (i.e., components) by keeping as much variance as possible out of the total variance in the measured variables. Furthermore, the popular use of varimax rotation raises some concerns about the relationships among the factors that researchers claim to discover. This paper discusses the distinct purposes of PCA and EFA, using two data sets as examples to highlight the differences in results between these procedures, and also reviews the use of each technique in three major communication journals: Communication Monographs, Human Communication Research, and Communication Research.     

因子混合模型:潜在类别分析与因子分析的整合

因子混合模型(FMM)是考虑了群体潜在异质性后的因子分析模型,它将潜在类别分析(LCA)与传统的因子分析(FA)整合在同一框架内,既保留了两种分析技术的优点,同时又展现出独特优势。FMM的应用主要包括描述变量的潜在结构、对被试进行分组以及探测社会称许偏差等。我们建议分别采用FA、LCA与FMM三种模型拟合数据,参考拟合指数和模型可解释性选择最优模型。总结了FMM的分析步骤以及软件使用,并用于探讨大学生社会面子意识的测量模型。未来研究应关注FMM分析过程的简化,继续深化对拟合指数等方面的探讨。     

Factor Analysis of Physique-Stereotyped Traits

Abstract

The prevalence of rape myths contributes to victims' reluctance to report rapes. Black (n = 30) and White (n = 96) U.S. college students responded to the Rape Myth Scale (Burt, 1980) and read a scenario of an acquaintance rape; the race of the perpetrator and victim (Black or White) were varied. The respondents assessed the victim's and perpetrator's responsibility and evaluated the incident. As hypothesized, the respondents with strong beliefs in rape myths were more tolerant of the rapist and less tolerant of the victim than were those with weaker beliefs. There was limited support for the myth of the Black rapist and White victim; however, the myth of the Black rapist appeared particularly strong among the Black respondents. The women responded more negatively to the rapist and more positively to the victim than the men did. Such biases in attitudes toward rape could keep women from reporting rapes and accused rapists from receiving fair trials.     

Nonmetric Factor Analysis: A Rank Reducing Alternative To Linear Factor Analysis

As part of the routine service procedures, 159 profoundly deaf rehabilitation candidates wre extensively tested on a variety of nonverbal intelligence and ability measures and rated on 10 communication variables. Two principal components factor analyses followed by Varimax rotations were performed, one on the total sample which spanned the age range from 16 to 67 years, and the second on a subsample of 87 clients between the ages of 16 and 25 years.