Growth Models for Repeated Measurement Mixture Experiments: Optimal Designs for Parameter Estimation and Growth Prediction

Manisha Pal, Nripes K. Mandal and Bikas K. Sinha ()
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Manisha Pal: Calcutta University
Nripes K. Mandal: Calcutta University
Bikas K. Sinha: Indian Statistical Institute

A chapter in Advances in Growth Curve and Structural Equation Modeling, 2018, pp 81-94 from Springer

Abstract: Abstract The present study focuses on the problems of parameter estimation and growth prediction in a quadratic growth model based on repeated measurements of growth, where the parameters in the model are assumed to be functions of ‘treatments’ which are treated as mixtures. The study concentrates not only on the optimality aspects of designs for most efficient estimation of the parameters but also on optimal prediction of growth at designated time points.

Keywords: D- and A-optimal designs; Mixtures; Parameter estimation; Prediction; Quadratic growth model; Repeated measurements (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-13-0980-9_6

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DOI: 10.1007/978-981-13-0980-9_6

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