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The Estimation of Variance-Covariance and Correlation Matrices from Incomplete Data

Published online by Cambridge University Press:  01 January 2025

Neil H. Timm
Neil H. Timm*
Affiliation:
Carnegie Commission on the Future of Higher Education University of California, Berkeley
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Abstract

Employing simulated data, several methods for estimating correlation and variance-covariance matrices are studied for observations missing at random from data matrices. The effect of sample size, number of variables, percent of missing data and average intercorrelations of variables are examined for several proposed methods.

Information

Type
Original Paper
Information
Psychometrika , Volume 35 , Issue 4 , December 1970 , pp. 417 - 437
Copyright
Copyright © 1970 The Psychometric Society

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Footnotes

*

The author is indebted to Professors Leonard A. Marascuilo, Gus W. Haggstrom, espsecially Henry F. Kaiser for their invaluable suggestions throughout this work. Appreciation is also extended to the Computer Center facility of the University of California at Berkeley for the use of computer time to complete the necessary computations.

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