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.     

Natural ways are better: Adolescents and the ‘anti-obesity’ gene

Empirical research with young people in Finland, Germany, Spain and Britain was carried out as part of the BIOCULT project funded by the European Union. The project focused on their attitudes to biotechnology and, in particular, the formation of arguments about risk and safety. This paper looks at the responses of 14–18 year olds to a story about the so called anti-obesity gene, in the form of advice to a friend who is taking it. The majority advised against taking it with some differences by gender and country. Most reservations were on grounds of safety and the feeling that ‘natural’ ways to lose weight are better: A minority questioned the idea of striving for a ‘perfect’ body. The types of arguments used by the young people reveal underlying perspectives on the place of human beings in the world and whether they have a right to manipulate nature and their own bodies. Marie Levitt is a sociologist with research interests in attitudes and values in relation to biotechnology, health and religion.     

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.     

计量测验效度的一种方法——测量目标结构空间的实证性因素分析

该文提出了计量测验效度的一种统一方法。首先,根据测量目标由测验编制者提出一组可能的线性拟合模型,拟合模型的集合称作“测量目标结构空间”。然后运用实证性因素分析对各个假设的拟合模型进行多方面的拟合良好性检验。若其中的某一假设模型能最优地拟合预测资料,则该模型中的公共因素的方差总贡献与观测变量的总方差的比就可定义为该测验的效度     

教育因素对认知功能年老化过程的影响

应用言语－操作和人机对话两种方式共１２项作业,完成年龄和教育因素对认知功能影响的研究,被试共７３４人,４６－７５岁．结果表明：（１）年龄和教育因素对认知成绩的影响因作业而异,分别为年龄影响明显（图象自由回忆和无意义图形再认）、教育因素影响明显（卡片分类、图象分类和矩阵填图）、年龄和教育因素影响均明显（符号数字、词对联想学习、听觉和视觉数字广度）或均不明显（心算）．（２）四项非词语性作业速度明显受年龄和教育因素的双重影响．     

Application of the bootstrap methods in factor analysis

A Monte Carlo experiment is conducted to investigate the performance of the bootstrap methods in normal theory maximum likelihood factor analysis both when the distributional assumption is satisfied and unsatisfied. The parameters and their functions of interest include unrotated loadings, analytically rotated loadings, and unique variances. The results reveal that (a) bootstrap bias estimation performs sometimes poorly for factor loadings and nonstandardized unique variances; (b) bootstrap variance estimation performs well even when the distributional assumption is violated; (c) bootstrap confidence intervals based on the Studentized statistics are recommended; (d) if structural hypothesis about the population covariance matrix is taken into account then the bootstrap distribution of the normal theory likelihood ratio test statistic is close to the corresponding sampling distribution with slightly heavier right tail.This study was carried out in part under the ISM cooperative research program (91-ISM · CRP-85, 92-ISM · CRP-102). The authors would like to thank the editor and three reviewers for their helpful comments and suggestions which improved the quality of this paper considerably.     

An integrated mindfulness and acceptance-based program for young elite female basketball players: Exploratory study of how it works and for whom it works best

In order to better understand how an integrated mindfulness and acceptance-based intervention works and for whom it works best, study objectives were to examine (i) the trajectories of mindfulness skills and performance-related outcomes during the intervention, and athletes’ perceptions of the impact of the intervention; and (ii) the potential moderating effects of personality characteristics on changes in targeted variables associated with the intervention. The sample consisted of 40 young elite female basketball players (M = 16.33, SD = 0.75 years) from three incoming groups at the French Federal Basketball Center over a 3-year period. All players participated in a 15-week Mindfulness BasketBall Integrated program. They completed online questionnaires measuring personality traits 10 months before the intervention, as well as pre-, mid- and post-intervention measurements of mindfulness skills, intensity and directional interpretation of stress, and performance satisfaction. They also participated in semi-structured social validation interviews conducted one month after the intervention. The results of the multilevel growth curve (MGCA) and thematic analyses revealed how the mindfulness skills and performance-related outcomes evolved over the course of the intervention and how these changes were perceived by the athletes. Specifically, the MGCA showed significant linear increases in acceptance, positive stress direction, and performance satisfaction. The complementary social validation data indicated perceived improvements in mindfulness skills and performance. The MGCA also showed that baseline personality traits moderated the effects of the program on acceptance and experience of stress. These findings may be used to inform the design of more effective integrated mindfulness and acceptance-based interventions.     

Factor structure of the basic personality inventory with incarcerated offenders

The item and scale factor structure of the Basic Personality Inventory (BPI) was examined in a sample of 486 offenders incarcerated for violent and sexual crimes. Separate principal-component analyses of the items for each of the 11 clinical scales, critical item scale, and social desirability scale indicated a one-dimensional factor solution for all scales except Depression and Persecutory Ideation. The Depression scale's two factors were Hopelessness and Depressive Affect and the Persecutory Ideation scale's two factors were General Paranoia and Perception of External Control. Although the factors for these two scales may assist in interpretation, the correlations between the factors and the total score of their respective scale were high. Confirmatory factor analysis of the 220 items from the 11 clinical scales supported the factorial logic of the scoring key. Analysis of the 11 clinical scales resulted in two factors: General Psychopathology/Adjustment and Antisocial Orientation. The results suggest that all but two scales can be viewed as unidimensional thereby allowing for a straightforward clinical interpretation. These analyses support the internal structure of the BPI and lend credence to external validity work with forensic populations.