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Direct linkWaller, Niels G.; Jones, Jeff A. – Psychometrika, 2010
A general theory on the use of correlation weights in linear prediction has yet to be proposed. In this paper we take initial steps in developing such a theory by describing the conditions under which correlation weights perform well in population regression models. Using OLS weights as a comparison, we define cases in which the two weighting…
Descriptors: Least Squares Statistics, Correlation, Comparative Analysis, Prediction
Peer reviewedKoopman, Raymond F. – Psychometrika, 1976
This note proposes an alternative implementation of the regression method which should be slightly faster than the principal components methods for estimating missing data. (RC)
Descriptors: Comparative Analysis, Data Analysis, Factor Analysis, Multiple Regression Analysis
Peer reviewedHunter, John E.; Cohen, Stanley H. – Psychometrika, 1974
Descriptors: Attitude Change, Attitudes, Comparative Analysis, Models
Peer reviewedLee, S. Y.; Jennrich, R. I. – Psychometrika, 1979
A variety of algorithms for analyzing covariance structures are considered. Additionally, two methods of estimation, maximum likelihood, and weighted least squares are considered. Comparisons are made between these algorithms and factor analysis. (Author/JKS)
Descriptors: Analysis of Covariance, Comparative Analysis, Correlation, Factor Analysis
