Descriptor
| Individual Differences | 3 |
| Mathematical Models | 3 |
| Multidimensional Scaling | 3 |
| Computer Programs | 1 |
| Factor Analysis | 1 |
| Goodness of Fit | 1 |
| Monte Carlo Methods | 1 |
| Perception | 1 |
| Research Methodology | 1 |
| Statistical Analysis | 1 |
Source
| Psychometrika | 3 |
Author
| MacCallum, Robert C. | 3 |
| Cornelius, Edwin T., III | 1 |
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Peer reviewedMacCallum, Robert C. – Psychometrika, 1977
The role of conditionality in the INDSCAL and ALSCAL multidimensional scaling procedures is explained. The effects of conditionality on subject weights produced by these procedures is illustrated via a single set of simulated data. Results emphasize the need for caution in interpreting subject weights provided by these techniques. (Author/JKS)
Descriptors: Individual Differences, Mathematical Models, Multidimensional Scaling, Statistical Analysis
Peer reviewedMacCallum, Robert C.; Cornelius, Edwin T., III – Psychometrika, 1977
A Monte Carlo study was carried out to investigate the ability of the ALSCAL multidimensional scaling program to recover true structure inherent in simulated proximity data. The results under varying conditions were mixed. Practical implications and suggestions for further research are discussed. (Author/JKS)
Descriptors: Computer Programs, Individual Differences, Mathematical Models, Monte Carlo Methods
Peer reviewedMacCallum, Robert C. – Psychometrika, 1976
Concerned with consequences of employing the INDSCAL model when one of its assumptions are known to be violated. Under study is the notion that all individuals perceive the object space dimensions to be independent. (RC)
Descriptors: Factor Analysis, Goodness of Fit, Individual Differences, Mathematical Models
