Personality correlates of life values

The present study sought to determine whether significant relationships exist between life value preferences and personality traits and to describe the nature of any relationships identified. Administered to 310 undergraduate and graduate students were the 16 PF personality inventory and a 55-item Life Values Inventory which assessed values governing life styles and orientations. A factor analysis of the Life Values Inventory resulted in the identification of 14 life values dimensions. Factor scores for these 14 dimensions were then employed in a canonical analysis and a factor analysis with the 16 PF scores. The canonical analysis yielded results significant at the .001 level. The factor analysis yielded 10 factors, many of which displayed shared common-factor variance between Life Values and 16 PF variables. The interpretation of that shared variance identified several personality correlates of life values that suggested causal and developmental interactions of some value in describing and explaining human behavior.     

Relationships between redundancy analysis,canonical correlation,and multivariate regression

This paper attempts to clarify the nature of redundancy analysis and its relationships to canonical correlation and multivariate multiple linear regression. Stewart and Love introduced redundancy analysis to provide non-symmetric measures of the dependence of one set of variables on the other, as channeled through the canonical variates. Van den Wollenberg derived sets of variates which directly maximize the between set redundancy. Multivariate multiple linear regression on component scores (such as principal components) is considered. The problem is extended to include an orthogonal rotation of the components. The solution is shown to be identical to van den Wollenberg's maximum redundancy solution.This research was supported in part by U.S. Environmental Protection Agency contract 68-02-3402. The author gratefully acknowledges the stimulation of Maurice Tatsuoka and Beth Dawson-Saunders in first interesting him in redundancy analysis, as well as a useful change suggested by Warren Sarle.     

Personality factors underlying coronary prone behavior patterns among employees

The structure of the coronary prone behavior syndrome was mapped onto the personality trait domain with a sample of 222 adult men and women (mean age=31). The subjects completed the Sixteen Personality Factor (16PF) and the Jenkins Activity Survey (JAS) questionnaires and canonical correlation analysis was used to derive the structure of common variance between the two sets of scales. Coronary prone behavior, when viewed within personality source trait structure, can be thought of as heavily influenced by anxiety and extraversion. Additional regression analyses were conducted to analyze interdomain relationships among the 16PF and JAS.     

Gender differences in the relationship between hostility and the type A behavior pattern

A group of 97 male and 111 female undergraduates completed the Jenkins Activity Survey, the Framingham Type A Scale, the Adjective Checklist Type A Scale, the Spielberger State-Trait Anxiety Inventory, and the Buss-Durkee Hostility Inventory. A factor analysis revealed three dimensions: Anger-Emotionality, Anger-Aggression, and Residual Pattern A. All Type A measures loaded highly on the Type A factor, with the Jenkins Activity Survey loading the highest. The Framingham Type A Scale was related to Anger-Emotionality, the Adjective Checklist Type A Scale was related to Anger-Aggression, and the Jenkins Activity Survey was related to neither of the anger dimensions. Women scored higher than men on Anger-Emotionality and the Guilt, Resentment, and Irritability subscales and lower than men on the Assaultiveness subscale. Women showed higher correlations between Type A and the Guilt subscale, and men between Type A and the Suspiciousness subscale. We conclude that Type A is a multidimensional construct that manifests itself differently in men and women.     

A Multivariate Analysis of Psychographic Variables

This study examined the relationship between demographic and personality variables through the use of a multivariate technique, canonical analysis. The principal advantage of such a technique lies in its ability to simultaneously consider sets of variables rather than focusing narrowly in a single predictor or criterion variable. The four demographic variables examined, sex, age, education, and marital status, produced four statistically significant relationships with personality traits measured by the Edwards Personal Preference Schedule. These relations were examined and suggestions made as to how the results might be used to indicate areas for further research.     

Development of covert and overt hostility scales from the Buss-Durkee Inventory

The purpose of this study was to develop covert and overt hostility scales from the Buss-Durkee Inventory. First, 22 covert hostility and 29 overt hostility items were identified by the authors. Second, an item analysis was done to assess the content saturation of the individual items on these scales. This analysis yielded the final form for 7 items for covert hostility and 14 for overt hostility. Cronbach alphas for the covert and overt scales were .67 and .77, respectively, and their intercorrelation was .08. Correlations for these Buss-Durkee scales with several existing measures of anger expression were consistent with expectations.     

Canonical/redundancy factoring analysis

The interrelationships between two sets of measurements made on the same subjects can be studied by canonical correlation. Originally developed by Hotelling [1936], the canonical correlation is the maximum correlation betweenlinear functions (canonical factors) of the two sets of variables. An alternative statistic to investigate the interrelationships between two sets of variables is the redundancy measure, developed by Stewart and Love [1968]. Van Den Wollenberg [1977] has developed a method of extracting factors which maximize redundancy, as opposed to canonical correlation.A component method is presented which maximizes user specified convex combinations of canonical correlation and the two nonsymmetric redundancy measures presented by Stewart and Love. Monte Carlo work comparing canonical correlation analysis, redundancy analysis, and various canonical/redundancy factoring analyses on the Van Den Wollenberg data is presented. An empirical example is also provided.Wayne S. DeSarbo is a Member of Technical Staff at Bell Laboratories in the Mathematics and Statistics Research Group at Murray Hill, N.J. I wish to express my appreciation to J. Kettenring, J. Kruskal, C. Mallows, and R. Gnanadesikan for their valuable technical assistance and/or for comments on an earlier draft of this paper. I also wish to thank the editor and reviewers of this paper for their insightful remarks.     

The Relationship Between Emotional Intelligence and Performance Among College Basketball Players

This study explored the nature of the relationship between muscle dysmorphia symptoms and self-concept as well as negative affect variables. Female (n = 183) and male (n = 103) college students completed a packet of questionnaires. Data were analyzed using canonical correlation analyses and revealed significant relationships between the sets of variables. Specifically, the variance explained by muscle dysmorphia symptoms in self-concept and negative affect variables was greater than the variance explained in muscle dysmorphia symptoms by self-concept and negative affect. Perceived body attractiveness and social physique anxiety were the individual variables that predominantly contributed to the multivariate relationships.     

Relationships between the Vocational Preference Inventory and the Edwards Personal Preference Schedule

The Vocational Preference Inventory and the Edwards Personal Preference Schedule were administered to 372 undergraduates. The two instruments were compared using canonical analysis. The analysis revealed three significant relationships between components of the two instruments. The relationships were viewed as supportive of Holland's theory of personality types.     

Functional Multiple-Set Canonical Correlation Analysis

We propose functional multiple-set canonical correlation analysis for exploring associations among multiple sets of functions. The proposed method includes functional canonical correlation analysis as a special case when only two sets of functions are considered. As in classical multiple-set canonical correlation analysis, computationally, the method solves a matrix eigen-analysis problem through the adoption of a basis expansion approach to approximating data and weight functions. We apply the proposed method to functional magnetic resonance imaging (fMRI) data to identify networks of neural activity that are commonly activated across subjects while carrying out a working memory task.     

Multivariate relationships between measures of learning style and memory

Three self-report instruments assessing “learning style” were administered to 106 undergraduate students: the Inventory of Learning Processes, the Study Behavior Questionnaire, and the Learning Style Inventory. Performance measures on word list and prose learning tasks were also obtained using both immediate and delayed retention tests. Canonical correlation analysis of the pairs of learning style instruments indicated that there was a small to moderate amount of overlapped variance. Inspection of the canonical variates revealed that what overlap existed was generally due to a common factor related to the depth of processing conception of memory. No significant canonical correlations were obtained between any of the learning style instruments and word list retention measures. However, the Inventory of Learning Processes and the Learning Style Inventory each obtained one significant canonical correlation with the set of prose retention measures. There was little overlap between sets of retention measures derived separately from prose and word list tasks. The findings have implications concerning (a) the validity and equivalency of available self-report instruments assessing learning style, (b) the role of the learning task in studying individual differences in learning and memory processes, and (c) the assessment of “depth of processing” at the level of individual differences.     

A Multivariate Analysis of Relationships Between Personality Traits and Value Choice

A canonical analysis disclosed significant relationships between personality traits and value choice. These relationships were interpreted in terms of their usefulness in understanding human behavior.     

Canonical correlations with fallible data

The technique of canonical correlation may be used to determine the extent to which two sets of measurements reflect the same underlying traits. However, if the two sets are not perfectly reliable, the unreliability may obscure the fact that they are essentially dependent on similar processes. If we attempt to determine sets of weights so as to maximize the correlation between linear composites after correction for attenuation in the composites, it turns out that the results may be obtained by determining the canonical correlations and canonical regression weights between the true score components of the measures making up the two sets. In addition, formulas are developed for calculating the correlations between the canonical variates and original measures, both corrected and uncorrected for attenuation. A numerical example relating the verbal to the performance subtests of the Wechsler Intelligence Scale for Children is presented.     

Orthogonal inter-battery factor analysis

It is the purpose of this paper to present a method of analysis for obtaining (i) inter-battery factors and (ii) battery specific factors for two sets of tests when the complete correlation matrix including communalities is given. In particular, the procedure amounts to constructing an orthogonal transformation such that its application to an orthogonal factor solution of the combined sets of tests results in a factor matrix of a certain desired form. The factors isolated are orthogonal but may be subjected to any suitable final rotation, provided the above classification of factors into (i) and (ii) is preserved. The general coordinate-free solution of the problem is obtained with the help of methods pertaining to the theory of linear spaces. The actual numerical analysis determined by the coordinate-free solution turns out to be a generalization of the formalism of canonical correlation analysis for two sets of variables. A numerical example is provided.This investigation has been supported by the U.S. Office of Naval Research under Contract Nonr-2752(00).     

K-fold Crossvalidation in Canonical Analysis

A computer-assisted, K-fold crossvalidation technique is discussed within the framework of canonical correlation analysis of randomly generated data sets. Results of the analysis suggest that this technique of multi-crossvalidation can be an effective method to reduce the contamination of canonical variates and canonical correlations by sample-specific variance components.     

中小学教师工作满意度与教学动机的关系

以1197名中小学教师为被试,通过问卷调查考察工作满意度与教学动机的关系。典型相关分析发现两组变量之间存在三对典型相关关系:环境满意度、升迁进修满意度、收入满意度和管理满意度作为抑制变量强化了活动满意度与内部动机的正相关;活动满意度和收入满意度对环境满意度与外部动机的正相关关系有调节作用,管理满意度作为抑制变量影响着升迁进修满意度、环境满意度与外部内化动机之间的负相关关系。鉴于工作满意度对教学动机的影响更为明显,采用分层回归分析进一步明确了可能存在显著回归效应。     

Reading Ability as a Predictor of Academic Procrastination Among African American Graduate Students

The present study examined the relationship between reading ability (i.e., reading comprehension and reading vocabulary) and academic procrastination among 120 African American graduate students. A canonical correlation analysis revealed statistically significant and practically significant multivariate relationships between these two reading ability variables and graduate students' levels of academic procrastination. Specifically, the first canonical correlation analysis revealed a statistically significant and practically significant multivariate relationship between reading ability and academic procrastination resulting from fear of failure. The second canonical correlation analysis revealed a statistically significant and practically significant multivariate relationship between reading ability and academic procrastination associated with writing a term paper, performing administrative tasks, attending meetings, keeping up with weekly reading assignments, and, most notably, performing academic tasks. Implications are discussed in the context of designing and implementing strategies designed to improve African American student performance and instruction in graduate-level courses.     

A unified approach to multiple‐set canonical correlation analysis and principal components analysis

Multiple‐set canonical correlation analysis and principal components analysis are popular data reduction techniques in various fields, including psychology. Both techniques aim to extract a series of weighted composites or components of observed variables for the purpose of data reduction. However, their objectives of performing data reduction are different. Multiple‐set canonical correlation analysis focuses on describing the association among several sets of variables through data reduction, whereas principal components analysis concentrates on explaining the maximum variance of a single set of variables. In this paper, we provide a unified framework that combines these seemingly incompatible techniques. The proposed approach embraces the two techniques as special cases. More importantly, it permits a compromise between the techniques in yielding solutions. For instance, we may obtain components in such a way that they maximize the association among multiple data sets, while also accounting for the variance of each data set. We develop a single optimization function for parameter estimation, which is a weighted sum of two criteria for multiple‐set canonical correlation analysis and principal components analysis. We minimize this function analytically. We conduct simulation studies to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of functional neuroimaging data to illustrate its empirical usefulness.     

Discriminating violent individuals by means of various psychological tests

Attempted to clarify the 43/4-8(8-4) controversy and further research the relationship between assaultiveness and other non-MMPI measures. Sixty-one male adolescent prisoners divided into four groups according to Race and Level of Assaultiveness served as subjects for this study. Each prisoner was administered the MMPI, the Buss-Durkee Hostility Scale and the Rotter I-E scale. The results suggest that the 4-3 code type is not an accurate predictor of violence; that elevations of F4897&6 describe the offender population (with) 8-4 describing the violent profile type); and that the Buss-Durkee Hostility scale may be valuable in assessing the violent personality.     

Global optimality of the successive Maxbet algorithm

The Maxbet method is an alternative to the method of generalized canonical correlation analysis and of Procrustes analysis. Contrary to these methods, it does not maximize the inner products (covariances) between linear composites, but also takes their sums of squares (variances) into account. It is well-known that the Maxbet algorithm, which has been proven to converge monotonically, may converge to local maxima. The present paper discusses an eigenvalue criterion which is sufficient, but not necessary for global optimality. However, in two special cases, the eigenvalue criterion is shown to be necessary and sufficient for global optimality. The first case is when there are only two data sets involved; the second case is when the inner products between all variables involved are positive, regardless of the number of data sets.The authors are obliged to Henk Kiers for critical comments on a previous draft.