title: Non-linear Models for Longitudinal Data.
abstract: While marginal models, random-effects models, and conditional models are routinely considered to be the three main modeling families for continuous and discrete repeated measures with linear and generalized linear mean structures, respectively, it is less common to consider non-linear models, let alone frame them within the above taxonomy. In the latter situation, indeed, when considered at all, the focus is often exclusively on random-effects models. In this paper, we consider all three families, exemplify their great flexibility and relative ease of use, and apply them to a simple but illustrative set of data on tree circumference growth of orange trees.
authors.affiliation: Department of Methodology and Statistics, Maastricht University, Peter Debyeplein 1, 6229 HA Maastricht, the Netherlands.
authors.forename: Jan
authors.initials: J
authors.lastname: Serroyen
authors.forename: Geert
authors.initials: G
authors.lastname: Molenberghs
authors.forename: Geert
authors.initials: G
authors.lastname: Verbeke
authors.forename: Marie
authors.initials: M
authors.lastname: Davidian