Descriptor
Algorithms | 4 |
Correlation | 4 |
Cluster Analysis | 2 |
Computer Simulation | 2 |
Data Analysis | 2 |
Equations (Mathematics) | 2 |
Estimation (Mathematics) | 2 |
Mathematical Models | 2 |
Multivariate Analysis | 2 |
Children | 1 |
Classification | 1 |
More ▼ |
Source
Multivariate Behavioral… | 4 |
Author
Dreger, Ralph Mason | 1 |
Hartmann, Wolfgang M. | 1 |
McDonald, Roderick P. | 1 |
Schweizer, Karl | 1 |
Tyler, David E. | 1 |
Publication Type
Journal Articles | 4 |
Reports - Evaluative | 3 |
Reports - Research | 1 |
Education Level
Audience
Location
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating

Tyler, David E. – Multivariate Behavioral Research, 1982
Miller and Farr's algorithm for the index of redundancy is shown to be incorrect by means of a counterexample. The consequences of this error for other conclusions drawn by the authors are discussed. (Author/JKS)
Descriptors: Algorithms, Correlation, Data Analysis, Multivariate Analysis

McDonald, Roderick P.; Hartmann, Wolfgang M. – Multivariate Behavioral Research, 1992
An algorithm for obtaining initial values for the minimization process in covariance structure analysis is developed that is more generally applicable for computing parameters connected to latent variables than the currently existing ones. The algorithm is formulated in terms of the RAM model but can be extended. (SLD)
Descriptors: Algorithms, Correlation, Equations (Mathematics), Estimation (Mathematics)

Schweizer, Karl – Multivariate Behavioral Research, 1991
A mathematical formula is introduced for the effect of integrating data. A method is then derived to eliminate the effect from correlations of variables, including mean composites, thus allowing for a clustering algorithm that requires allocation of variables according to the magnitude of their correlations. Examples illustrate the procedure. (SLD)
Descriptors: Algorithms, Classification, Cluster Analysis, Computer Simulation

Dreger, Ralph Mason; And Others – Multivariate Behavioral Research, 1988
Seven data sets (namely, clinical data on children) were subjected to clustering by seven algorithms--the B-coefficient, Linear Typal Analysis; elementary linkage analysis, Numerical Taxonomy System, Statistical Analysis System hierarchical clustering method, Taxonomy, and Bolz's Type Analysis. The little-known B-coefficient method compared…
Descriptors: Algorithms, Children, Clinical Diagnosis, Cluster Analysis