Abstract:
:A stochastic model is presented for the analysis of incomplete repeated-measures experiments. The general linear model is used to relate the response measures to other variables which are thought to account for inherent variation; an autoregressive moving average (ARMA) time series representation is used to model disturbance terms. Maximum likelihood estimation procedures are considered, and the properties of these estimators are derived. It is concluded that while the assumptions underpinning the ARMA covariance models may be somewhat restrictive, they provide a useful inferential vehicle, particularly in the presence of missing values.
journal_name
Biometricsjournal_title
Biometricsauthors
Rochon J,Helms RWsubject
Has Abstractpub_date
1989-03-01 00:00:00pages
207-18issue
1eissn
0006-341Xissn
1541-0420journal_volume
45pub_type
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