Data Imputation in Switchback Designs Using a Mixed Model with Correlated Errors

Luis Fernando Grajales  & Luis Alberto López        

 

 

Abstract

The problem of predicting individual measurements in switchback designs with correlated errors is considered. The predictions and imputations are done using the BLUP (Best Linear Unbiased Predictions), which have been suggested by Barroso et al. (1998). Three covariance structures were compared by the eigenvalues of the matrices of mean square errors. The results suggest that structures σ²I and AR(1) are better than CS.

 

Key words: Missing data, Generalized least squares, Best linear unbiased prediction, Covariance structure.  

 

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