心理旋转的角色效应研究

本研究采用2×4混合实验设计,通过对旋转类型和旋转角度的控制,探讨第一人称角色和第三人称角色心理旋转的差异性。实验结果表明,空间表征转换的角色方式是影响心理旋转的重要因素,第三人称角色心理旋转易于第一人称角色心理旋转。     

Selection of variables in exploratory factor analysis: An empirical comparison of a stepwise and traditional approach

The purpose of this study was to investigate and compare the performance of a stepwise variable selection algorithm to traditional exploratory factor analysis. The Monte Carlo study included six factors in the design; the number of common factors; the number of variables explained by the common factors; the magnitude of factor loadings; the number of variables not explained by the common factors; the type of anomaly evidenced by the poorly explained variables; and sample size. The performance of the methods was evaluated in terms of selection and pattern accuracy, and bias and root mean squared error of the structure coefficients. Results indicate that the stepwise algorithm was generally ineffective at excluding anomalous variables from the factor model. The poor selection accuracy of the stepwise approach suggests that it should be avoided.     

Sex differences in spatial ability: a lateralization of function approach

The current study was designed to examine whether the extent of the male advantage in performance on a spatial task was determined by the extent to which the task was right-hemisphere dependent. Participants included 108 right-handed men and women who completed the mental rotation, waterlevel, and paperfolding tasks, all of which were presented bilaterally. The results partially supported the hypothesis. On the mental rotation task, men showed a right-hemisphere advantage, whereas women showed no hemispheric differences; however, no overall sex differences were observed. On the waterlevel task, men outperformed women, and both men and women showed a right-hemisphere advantage. On the paperfolding task, no sex or hemispheric differences were observed. Although the findings of the current study were mixed, the study provides a framework for examining sex differences across different types of spatial ability.     

How do young children determine location? Evidence from disorientation tasks

Previous studies show that following disorientation children use the geometry of an enclosed space to locate an object hidden in one of the corners [e.g. (Hermer, L., & Spelke, E. (1996). Modularity and development: A case of spatial reorientation. Cognition, 61, 195-232)]. These studies have used a disorientation procedure that involves rotating the viewer (with eyes closed). Here, we examine 18- to 25-month-olds' spatial coding in two disorientation tasks--involving either viewer or space rotation. Importantly, the rotational movements in both tasks could not be visually tracked. Children were tested in either task (viewer- or space-movement) from either inside or outside a triangular (isosceles) space (with one unique and two equivalent corners). In the viewer-movement task, performance was above chance, regardless of which corner contained the object. In the space-movement task, performance was above chance at only the unique corner. On both tasks, performance was better from inside the space than from outside. The implications for how children determine location are discussed.     

Oblique factors and components with independent clusters

Relationships between the results of factor analysis and component analysis are derived when oblique factors have independent clusters with equal variances of unique factors. The factor loadings are analytically shown to be smaller than the corresponding component loadings while the factor correlations are shown to be greater than the corresponding component correlations. The condition for the inequality of the factor/component contributions is derived in the case with different variances for unique factors. Further, the asymptotic standard errors of parameter estimates are obtained for a simplified model with the assumption of multivariate normality, which shows that the component loading estimate is more stable than the corresponding factor loading estimate.     

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.     

Coefficients alpha and reliabilities of unrotated and rotated components

It has been shown by Kaiser that the sum of coefficients alpha of a set of principal components does not change when the components are transformed by an orthogonal rotation. In this paper, Kaiser's result is generalized. First, the invariance property is shown to hold for any set of orthogonal components. Next, a similar invariance property is derived for the reliability of any set of components. Both generalizations are established by considering simultaneously optimal weights for components with maximum alpha and with maximum reliability, respectively. A short-cut formula is offered to evaluate the coefficients alpha for orthogonally rotated principal components from rotation weights and eigenvalues of the correlation matrix. Finally, the greatest lower bound to reliability and a weighted version are discussed.Comments by Henk A.L. Kiers and by anonymous referees are gratefully acknowledged.     

A note on the identification of restricted factor loading matrices

It is shown that problems of rotational equivalence of restricted factor loading matrices in orthogonal factor analysis are equivalent to problems of identification in simultaneous equations systems with covariance restrictions. A necessary (under a regularity assumption) and sufficient condition for local uniqueness is given and a counterexample is provided to a theorem by J. Algina concerning necessary and sufficient conditions for global uniqueness.     

Factor simplicity index and transformations

A scale-invariant index of factorial simplicity is proposed as a summary statistic for principal components and factor analysis. The index ranges from zero to one, and attains its maximum when all variables are simple rather than factorially complex. A factor scale-free oblique transformation method is developed to maximize the index. In addition, a new orthogonal rotation procedure is developed. These factor transformation methods are implemented using rapidly convergent computer programs. Observed results indicate that the procedures produce meaningfully simple factor pattern solutions.This investigation was supported in part by a Research Scientist Development Award (K02-DA00017) and research grants (MH24149 and DA01070) from the U. S. Public Health Service. The assistance of Andrew L. Comrey, Henry F. Kaiser, Bonnie Barron, Marion Hee, and several anonymous reviewers is gratefully acknowledged.