A mixed-effects model for growth curves analysis in a two-way crossed classification layout

Abstract

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.