Non-linear Models for Longitudinal Data.

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Serroyen, J; Molenberghs, G; Verbeke, G; Davidian, M

Published Date

  • November 1, 2009

Published In

Volume / Issue

  • 63 / 4

Start / End Page

  • 378 - 388

PubMed ID

  • 20160890

Pubmed Central ID

  • 20160890

International Standard Serial Number (ISSN)

  • 0003-1305

Digital Object Identifier (DOI)

  • 10.1198/tast.2009.07256

Language

  • eng

Conference Location

  • England