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 obtainedusing a two-way classification experiment. The model combines an unconstrainedmeans model and a regression model on the time, in which the coefficients are consideredrandom. The model allows for experimental unit covari...

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Autores Principales: Ojeda, Mario Miguel, Sahai, Hardeo
Formato: Artículo
Idioma: Español
Publicado: 2015
Acceso en línea: http://revistas.ucr.ac.cr/index.php/matematica/article/view/245
http://hdl.handle.net/10669/12890
Sumario: We propose a mixed-effects linear model for analyzing growth curves data obtainedusing a two-way classification experiment. The model combines an unconstrainedmeans model and a regression model on the time, in which the coefficients are consideredrandom. The model allows for experimental unit covariates so as to study thetrend and the variability of the individual growth curves. Comments on data analysisstrategies are provided. An application of the model is illustrated using a data-setcomes from a chrysanthemum growth experiment.Keywords: multilevel linear regression models, random coefficients models, means models,data analysis strategies.