A Note on the Geisser-Greenhouse Correction for Incomplete Data Split-Plot Analysis

Abstract

Growth curve, wear curve, and repeated measurement experiments frequently are analyzed as split-plot designs with time used as the subplot treatment. This method is particularly convenient when the data have missing values in the repeated measurements since multivariate methods are not easily adapted to data with different dispersion matrices. This article establishes that the dispersion structure which guarantees that the subplot test ratio has an F distribution for complete data applies to incomplete data as well.

Key Words:

• Geisser-Greenhouse correction
• Growth curves
• Missing data
• Regression
• Split-plot analysis
• Wear curves