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Noniterative Least Squares Estimates, Standard Errors, and F-Tests for Any Analysis of Variance With Missing Data

Rubin, Donald B.
Publication Year:
Report Number:
ETS Research Bulletin
Document Type:
Page Count:
Subject/Key Words:
Analysis of Variance (ANOVA), Computer Software, Data Analysis, Mathematical Formulas, Statistical Analysis


This article generalizes Rubin's method of least squares estimation of missing values in any analysis of variance. The general method produces not only least squares estimates of all parameters and the residual mean square, but also the correct least squares standard error and t-test of any contrast as well as the least squares sum of squares and F-test due to any collection of contrasts. The method is noniterative and requires only those subroutines designed to handle complete data plus a subroutine to find the inverse of an m x m symmetric matrix, where m is the number of missing values. (20pp.)

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