Hostname: page-component-745bb68f8f-b95js Total loading time: 0 Render date: 2025-01-08T09:30:32.106Z Has data issue: false hasContentIssue false
  • English
  • Français

Fast Regression Estimates of Missing Data

Published online by Cambridge University Press:  01 January 2025

Raymond F. Koopman
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.
Get access Rights & Permissions [Opens in a new window]

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

none
Type
Original Paper
Information
Psychometrika , Volume 41 , Issue 2 , June 1976 , pp. 277
Copyright
Copyright © 1976 The Psychometric Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Gleason, T. C. and Staelin, R. A proposal for handling missing data. Psychometrika, 1975, 40, 229–252.CrossRefGoogle Scholar