A mixed-effects model for growth curves analysis in a two-way crossed classification layout
We propose a mixed-effects linear model for analyzing growth curves data obtained using a two-way classification experiment. The model combines an unconstrained means model and a regression model on the time, in which the coefficients are considered random. The model allows for experimental unit cov...
| Main Authors: | , |
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| Format: | Article |
| Language: | Spanish |
| Published: |
Universidad de Costa Rica
2009-02-01
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| Series: | Revista de Matemática: Teoría y Aplicaciones |
| Online Access: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/245 |
| Summary: | We propose a mixed-effects linear model for analyzing growth curves data obtained
using a two-way classification experiment. The model combines an unconstrained
means model and a regression model on the time, in which the coefficients are considered
random. The model allows for experimental unit covariates so as to study the
trend and the variability of the individual growth curves. Comments on data analysis
strategies are provided. An application of the model is illustrated using a data-set
comes from a chrysanthemum growth experiment.
Keywords: multilevel linear regression models, random coefficients models, means models,
data analysis strategies. |
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| ISSN: | 2215-3373 |