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Determining amino acid requirements from repeated observations on indicator amino acid oxidation method by mixed-effect change-point regression models
In nutrition studies, it is often of primary interest to determine the critical threshold value of some biological quantities. To determine the amino acid requirement, the tracer approach including the indicator amino acid oxidation method is useful for the investigation of human subjects. In this a...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
the Society for Free Radical Research Japan
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3171677/ https://www.ncbi.nlm.nih.gov/pubmed/21980227 http://dx.doi.org/10.3164/jcbn.10-146 |
Sumario: | In nutrition studies, it is often of primary interest to determine the critical threshold value of some biological quantities. To determine the amino acid requirement, the tracer approach including the indicator amino acid oxidation method is useful for the investigation of human subjects. In this approach, measurements of amino acids other than the test amino acid are often repeatedly carried out with various intakes of the test amino acid. Change-point regression models have often been applied to determine the amino acid requirement. However, within-subject dependence due to repeated measurements has not been sufficiently taken into account. In this paper, we propose a mixed-effect change-point model to estimate the amino acid requirements when utilizing the tracer approach. Inference based on Akaike Information Criteria is introduced to include selection of the optimal model and construction of a confidence interval. Our method can easily be applied with a standard software package, and we found that appropriate accounting for within-subject dependence may lead to a much narrower confidence interval. We recommend application of a mixed-effect change-point regression model to determine the amino acid requirements in studies utilizing the tracer approach. |
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