On Covariance Adjustment In The Analysis Of Time-Structured Data
Abstract:
Covariance adjustment in the analysis of time-structured data may increase the efficiency of the estimates. The selection of an adequate set of covariates depends on the pattern of the unknown population covariance matrix, and Grizzle and Allen (1969) and Rao (1966) proposed selection on the basis of the correlations between the variates and covariates. This article uses heuristic arguments to propose a measure for covariate selection and demonstrates its effectiveness using data given by Grizzle and Allen and data generated from a population with a simplex and a circumplex covariance pattern.
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