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| Gupta, Sunil | 1 |
| Kaplan, David | 1 |
| Kiiveri, H. T. | 1 |
| Lehmann, Donald R. | 1 |
| Marsh, Herbert W. | 1 |
| Schumacker, Randall E. | 1 |
| Stelzl, Ingeborg | 1 |
| Wilson, Mark | 1 |
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| Journal Articles | 5 |
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Peer reviewedStelzl, Ingeborg – Multivariate Behavioral Research, 1991
Criteria for factor identification in factor analysis according to J. Algina (1980) are summarized, and a procedure is presented to determine rotationally underidentified factors by adding restrictors and to carry out the rotation for old and new restrictions and in latent path analysis. Two illustrations are presented. (SLD)
Descriptors: Equations (Mathematics), Hypothesis Testing, Mathematical Models, Path Analysis
Peer reviewedKaplan, David – Multivariate Behavioral Research, 1989
The sampling variability and zeta-values of parameter estimates for misspecified structural equation models were examined. A Monte Carlo study was used. Results are discussed in terms of asymptotic theory and the implications for the practice of structural equation models. (SLD)
Descriptors: Error of Measurement, Estimation (Mathematics), Mathematical Models, Monte Carlo Methods
Peer reviewedWilson, Mark – Journal of Educational Statistics, 1989
An empirical sampling approach was used to assess the accuracy of a Taylor approximation for the estimation of sampling errors. The sampling errors were in the statistics involved in estimating a path model based on medium-sized samples gathered using five sample designs commonly used in educational research. (TJH)
Descriptors: Educational Research, Error of Measurement, Estimation (Mathematics), Mathematical Models
Peer reviewedLehmann, Donald R.; Gupta, Sunil – Applied Psychological Measurement, 1989
Path Analysis of Covariance Matrix (PACM) is described as a way to separately estimate measurement and structural models using standard least squares procedures. PACM was empirically compared to simultaneous maximum likelihood estimation and use of the LISREL computer program, and its advantages are identified. (SLD)
Descriptors: Estimation (Mathematics), Least Squares Statistics, Mathematical Models, Maximum Likelihood Statistics
Peer reviewedKiiveri, H. T. – Psychometrika, 1987
Covariance structures associated with linear structural equation models are discussed. Algorithms for computing maximum likelihood estimates (namely, the EM algorithm) are reviewed. An example of using likelihood ratio tests based on complete and incomplete data to improve the fit of a model is given. (SLD)
Descriptors: Algorithms, Analysis of Covariance, Computer Simulation, Equations (Mathematics)
Download full textSchumacker, Randall E. – 1989
The relationship of multiple linear regression to various multivariate statistical techniques is discussed. The importance of the standardized partial regression coefficient (beta weight) in multiple linear regression as it is applied in path, factor, LISREL, and discriminant analyses is emphasized. The multivariate methods discussed in this paper…
Descriptors: Comparative Analysis, Discriminant Analysis, Equations (Mathematics), Factor Analysis
Marsh, Herbert W. – 1986
Newman (1984) examined the causal relations between math self-concept and math achievement in an 8-year longitudinal study using Linear Structural Relations (LISREL) analyses. He concluded that math self-concept did not influence subsequent math achievement. However, the study suffered in that math self-concept was inferred from a single-item…
Descriptors: Attribution Theory, Correlation, Effect Size, Elementary Secondary Education
