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Fast Regression Estimates of Missing Data

Published online by Cambridge University Press:  01 January 2025

Raymond F. Koopman*
Affiliation:
Simon Fraser University
*
Requests for reprints should be sent to R. F. Koopman, Department of Psychology, Simon Fraser University, Burnaby, British Columbia, Canada V5A 1S6.

Abstract

A recent comparison of methods for estimating missing data concluded that when there is sufficient redundancy to justify using a more elaborate method than the mean of each variable, the principal components and regression methods are equally good and superior to the other methods investigated. Principal components was preferred because of its “tremendous computational savings over the regression method.” This note proposes an alternate implementation of the regression method which should be slightly faster than the principal components method.

Keywords

Type
Original Paper
Copyright
Copyright © 1976 The Psychometric Society

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References

Gleason, T. C. and Staelin, R. A proposal for handling missing data. Psychometrika, 1975, 40, 229252.CrossRefGoogle Scholar