The factor structure of the Multiple Affect Adjective Check List-Revised (MAACL-R): Some statistical considerations

In response to Zuckerman's comments on my factor analyses of the MAACL-R, I focus on the statistical issues of the cutoff criterion for factor loadings and the evidence for the discriminant validity of the five-factor solution. Based upon the conclusions I draw in these two areas, I recommend that researchers either (a) use the two factor solution to the MAACL-R represented in the summary scores of Dysphoria and Positive Affect + Sensation Seeking or (b) include all MAACL-R scales in their studies and analyze their data to determine whether it is statistically appropriate to report results from a single scale (A, D, H, PA, or SS) rather than from the summary scores.     

Factor structure of the mobility inventory for agoraphobia: A validational study with australian samples of agoraphobic patients

This study examines the factor structure of the Mobility Inventory for Agoraphobia and attempts to validate the inventory, using an Australian sample of agoraphobic patients, by comparison with other scales. One hundred twentyfour panic disorder with agoraphobia patients were studied. Factor analysis showed that a two-factor solution was the most suitable both when subjects were accompanied (accompanied condition) and when alone (alone condition). Factor I represented public, crowded, or social situations including department stores, supermarkets, restaurants, theaters, and panics and social gatherings. Factor II reflected enclosed or riding situations such as elevators, parking garages, enclosed spaces, and riding in subways or airplanes. These two factors accounted for 46.6% and 44.3% of the variance on the accompanied condition and the alone condition, respectively. The Mobility Inventory was significantly correlated with the Agoraphobia factor of the Fear Questionnaire and the Social Avoidance and Distress scale. These results indicated that the Mobility Inventory is a valid instrument to measure agoraphobic behavior.     

Psychometric properties and factor structure of the Fear Questionnaire phobia subscale items in two normative samples

Normative data for the Fear Questionnaire (Marks & Mathews, 1979), a popular self-report instrument measuring phobic concerns, were collected from both a community and a collegiate sample. The covariation and internal consistency of the blood-injury phobia (BI), social phobia (SO), and agoraphobia (AG) subscales were assessed in each sample, and the factor structure of the items from these three subscales was examined. Results indicated that, in general, community subjects reported more phobic concerns than did collegiate subjects, and females reported greater phobic concerns than did males. Results from confirmatory factor analyses suggest that the three factors of BI, SO, and AG did not emerge from either data set. Follow-up exploratory factor analyses did identify the general factors of blood-injury phobia and agoraphobia. Normative data from the present study are compared to those obtained previously, and directions for future research are provided.     

Interpreting canonical correlation analysis through biplots of structure correlations and weights

This paper extends the biplot technique to canonical correlation analysis and redundancy analysis. The plot of structure correlations is shown to the optimal for displaying the pairwise correlations between the variables of the one set and those of the second. The link between multivariate regression and canonical correlation analysis/redundancy analysis is exploited for producing an optimal biplot that displays a matrix of regression coefficients. This plot can be made from the canonical weights of the predictors and the structure correlations of the criterion variables. An example is used to show how the proposed biplots may be interpreted.     

New lower and upper bounds for communality in factor analysis

We derive several relationships between communalities and the eigenvalues for ap ×p correlation matrix under the usual factor analysis model. For suitable choices ofj, _j (), where _j () is thej-th largest eigenvalue of , provides either a lower or an upper bound to the communalities for some of the variables. We show that for at least one variable, 1 - _p () improves on the use of squared mulitiple correlation coefficient as a lower bound.This research was done while the second author was at Tokyo Institute of Technology.     

Type A behaviour in pre-school children: Interrater reliability, stability over six months and subcomponents

Type A behaviour was measured in 250 boys and 245 girls (ages 3-7) using a Swedish version of Matthews' Youth Test for Health (MYTH). In addition, speech and voice characteristics (speed, loudness, response latency) were measured. Each child was independently rated by two play group leaders and measurements were repeated after a six month interval. Interrater reliability (first session) was 0.76 for both sexes and did not change with the age of the child. Boys obtained significantly (p less than 0.0001) higher scores than girls. Correlations over the six month period were 0.64 and 0.60 (p less than 0.001) for the two possible combinations of different raters and slightly higher (0.75 and 0.68, p less than 0.001) when the same rater was used. Two components of Type A behaviour were identified from a factor analysis of the data: impatience and competitiveness, and they accounted for 57% of the total variance. As for the total scale, boys obtained significantly higher scores than girls on both subscales. Scores on the competitiveness scale increased systematically with age. Speech and voice characteristics correlated significantly with Type A scores (total Type A behaviour: r = 0.50, using different raters, and 0.71, using the same raters, p less than 0.001) and, once again, boys obtained significantly (p less than 0.001) higher scores than girls. The results are in close agreement with the American findings from the original scale. It was concluded that the scale provides a reliable and valid instrument for measuring Type A or Type A-like behaviours in pre-school children.     

Continuous and discrete latent structure models for item response data

Relations are examined between latent trait and latent class models for item response data. Conditions are given for the two-latent class and two-parameter normal ogive models to agree, and relations between their item parameters are presented. Generalizationss are then made to continuous models with more than one latent trait and discrete models with more than two latent classes, and methods are presented for relating latent class models to factor models for dichotomized variables. Results are illustrated using data from the Law School Admission Test, previously analyzed by several authors.     

快速书写条件下硬笔笔迹变量与认知及个性特征的关系

以圆珠笔为书写工具．北京市某中学高一学生为被试,有效数据169人．探讨了在快速抄写条件下,笔迹书写特征与认知及个性的关系：18个笔迹变量可抽取笔压、结构、特征、字体和空间五个反映字的书写特征的因素;书写特征与认知因素间,横、竖笔压与概念形成速度。整篇压与视力追踪、字位与眼手协调相关显著;横笔压与16PF测验中的畏缩退怯——冒险敢为有正相关;竖笔压与艾森克个性因素的N有高相关。     

Finite mixtures in confirmatory factor-analysis models

In this paper, various types of finite mixtures of confirmatory factor-analysis models are proposed for handling data heterogeneity. Under the proposed mixture approach, observations are assumed to be drawn from mixtures of distinct confirmatory factor-analysis models. But each observation does not need to be identified to a particular model prior to model fitting. Several classes of mixture models are proposed. These models differ by their unique representations of data heterogeneity. Three different sampling schemes for these mixture models are distinguished. A mixed type of the these three sampling schemes is considered throughout this article. The proposed mixture approach reduces to regular multiple-group confirmatory factor-analysis under a restrictive sampling scheme, in which the structural equation model for each observation is assumed to be known. By assuming a mixture of multivariate normals for the data, maximum likelihood estimation using the EM (Expectation-Maximization) algorithm and the AS (Approximate-Scoring) method are developed, respectively. Some mixture models were fitted to a real data set for illustrating the application of the theory. Although the EM algorithm and the AS method gave similar sets of parameter estimates, the AS method was found computationally more efficient than the EM algorithm. Some comments on applying the mixture approach to structural equation modeling are made.Note: This paper is one of the Psychometric Society's 1995 Dissertation Award papers.—EditorThis article is based on the dissertation of the author. The author would like to thank Peter Bentler, who was the dissertation chair, for guidance and encouragement of this work. Eric Holman, Robert Jennrich, Bengt Muthén, and Thomas Wickens, who served as the committee members for the dissertation, had been very supportive and helpful. Michael Browne is appreciated for discussing some important points about the use of the approximate information in the dissertation. Thanks also go to an anonymous associate editor, whose comments were very useful for the revision of an earlier version of this article.     

初级指挥官人格类型与PM领导行为类型有效性的关系

通过对陆军初级指挥官人格心理类型与领导行为有效性的心理学研究 ,探讨个人的领导潜能、人格心理类型对领导行为有效性的影响。研究发现 :1方差分析表明 ,具有不同领导行为的指挥官在人格维度上存在明显的统计学差异。提示了指挥官的领导行为取向与人格因素有密切的关系。2卡方分析结果也表明 ,PM型行为的军官在其人格特征上具有“ESTJ”组合特征 ,而 pm型的军官则正好相反 ;另外 ,pm型的军官在成就动机上获得高分的人数最少。3系统聚类分析显示 ,“成就动机”、“感觉”和“判断”三种人格因素与军事指挥官完成整体领导职能有着更为密切的关系。