On Total Least Squares Estimation for Longitudinal Errors-in-Variables Models
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The objective of this study is to evaluate the total least squares (TLS) estimator for the linear mixed model when the design matrix is subject to measurement errors, with special focus on models for longitudinal or repeated-measures data. We consider measurement errors only in the design matrix concerning the fixed part of the model and estimate its corresponding parameter vector under the TLS set up. After treating two variants of the general case, the random coefficient model is discussed as a special case. We evaluate conditions, on the design matrices as well as on variance component parameters, under which a reasonable TLS estimator can be expected in such models. Analysis of a real data example is also provided.
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2018 ◽
Vol 28
(10-11)
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pp. 3392-3403
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2012 ◽
Vol 239-240
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pp. 1352-1355
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2019 ◽
Vol 16
(14)
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pp. 2603
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2019 ◽
Vol 30
(6)
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pp. NP1-NP2
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2013 ◽
Vol 24
(09)
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pp. 789-806
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