Descriptor
| Factor Analysis | 39 |
| Matrices | 39 |
| Correlation | 16 |
| Orthogonal Rotation | 13 |
| Statistical Analysis | 13 |
| Mathematical Models | 11 |
| Comparative Analysis | 9 |
| Factor Structure | 9 |
| Oblique Rotation | 6 |
| Sampling | 5 |
| Algorithms | 3 |
| More ▼ | |
Source
| Multivariate Behavioral… | 39 |
Author
Publication Type
| Journal Articles | 16 |
| Reports - Research | 7 |
| Reports - Evaluative | 4 |
| Reports - Descriptive | 2 |
| Reports - General | 2 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
| California Psychological… | 1 |
What Works Clearinghouse Rating
Peer reviewedNicewander, W. Alan – Multivariate Behavioral Research, 1974
Descriptors: Correlation, Factor Analysis, Matrices, Statistics
Peer reviewedWalkey, Frank H. – Multivariate Behavioral Research, 1983
Some effects of using inappropriate criteria for sufficiency of factors are discussed, and examples from the literature are used to show how procedures leading to the rotation of large numbers of factors may result in fragmentation and difficulty in interpretation. (Author/JKS)
Descriptors: Factor Analysis, Matrices, Questionnaires, Scaling
Peer reviewedSchneeweiss, Hans – Multivariate Behavioral Research, 1997
A sufficient condition in terms of the unique variances of a common factor model is given for the results of factor analysis to come closer to those of principal components analysis. In general, vectors corresponding to loading matrices can be related to each other by a specific measure of closeness, which is illustrated. (SLD)
Descriptors: Factor Analysis, Factor Structure, Matrices
Peer reviewedKaiser, Henry F. – Multivariate Behavioral Research, 1974
A desirable property of the equamax criterion for analytic rotation in factor analysis is presented. (Author)
Descriptors: Correlation, Factor Analysis, Matrices, Orthogonal Rotation
Peer reviewedShirkey, Edwin C.; Dziuban, Charles D. – Multivariate Behavioral Research, 1976
Distributional characteristics of the measure of sampling adequacy (MSA) were investigated in sample correlation matrices generated from multivariate normal populations with covariance matrix equal to the identity. Systematic variation of sample size and number of variables resulted in minimal fluctuation of the overall MSA from .50. (Author/RC)
Descriptors: Factor Analysis, Matrices, Sampling, Statistical Analysis
Peer reviewedLevin, Joseph – Multivariate Behavioral Research, 1988
A means of transforming multitrait-multimethod (MTMM) matrices into a classical multiple group factor analysis is outlined. A reanalysis of two numerical illustrations shows that the classical procedure yields results similar to those reached by D. N. Jackson's (1975) two-step procedure for analysis of MTMM matrices. (TJH)
Descriptors: Factor Analysis, Matrices, Multitrait Multimethod Techniques
Peer reviewedGuadagnoli, Edward; Velicer, Wayne – Multivariate Behavioral Research, 1991
In matrix comparison, the performance of four vector matching indices (the coefficient of congruence, the Pearson product moment correlation, the "s"-statistic, and kappa) was evaluated. Advantages and disadvantages of each index are discussed, and the performance of each was assessed within the framework of principal components…
Descriptors: Comparative Analysis, Factor Analysis, Mathematical Models, Matrices
Peer reviewedHofmann, Richard J. – Multivariate Behavioral Research, 1975
A generalized matrix procedure is developed for computing the proportionate contribution of a factor, either orthogonal or oblique, to the total common variance of a factor solution. (Author)
Descriptors: Algorithms, Factor Analysis, Matrices, Oblique Rotation
Peer reviewedHumphreys, Lloyd G.; Montanelli, Richard G. – Multivariate Behavioral Research, 1975
Descriptors: Correlation, Factor Analysis, Matrices, Sampling
Peer reviewedKaiser, Henry F.; Horst, Paul – Multivariate Behavioral Research, 1975
Descriptors: Correlation, Error of Measurement, Factor Analysis, Matrices
Peer reviewedTrendafilov, Nickolay T. – Multivariate Behavioral Research, 1996
An iterative process is proposed for obtaining an orthogonal simple structure solution. At each iteration, a target matrix is constructed such that the relative contributions of the target majorize the original ones, factor by factor. The convergence of the procedure is proven, and the algorithm is illustrated. (SLD)
Descriptors: Algorithms, Factor Analysis, Factor Structure, Matrices
Peer reviewedLinn, Robert L.; And Others – Multivariate Behavioral Research, 1975
Factor structures of student ratings of instruction resulting from total group, between group, and within group analyses were compared. Six factors obtained from responses by students to 31 items were used to approximate the between group covariance matrix based on 437 classroom means and the pooled within classroom covariance matrix. (Author/BJG)
Descriptors: Factor Analysis, Factor Structure, Matrices, Student Evaluation
Peer reviewedHofmann, Richard J. – Multivariate Behavioral Research, 1978
A computational algorithm, called the orthotran solution, is developed for determining oblique factor analytic solutions utilizing orthogonal transformation matrices. Selected results from illustrative studies are provided. (Author/JKS)
Descriptors: Factor Analysis, Mathematical Models, Matrices, Oblique Rotation
Peer reviewedReynolds, Thomas J. – Multivariate Behavioral Research, 1980
Order analysis, a technique to isolate unidimensional hierarchies representing multidimensional structure of binary data, is reviewed. Several theoretical flaws inherent in the probalistic version are presented. Suggestions of possible directions for future research are offered. (Author)
Descriptors: Factor Analysis, Item Analysis, Matrices, Statistical Analysis
Peer reviewedTrendafilov, Nickolay T. – Multivariate Behavioral Research, 1994
An alternative to the PROMAX exploratory method is presented for constructing a target matrix in Procrustean rotation in factor analysis. A technique is proposed based on vector majorization. The approach is illustrated with several standard numerical examples. (SLD)
Descriptors: Equations (Mathematics), Factor Analysis, Factor Structure, Matrices


