Analysis of Linear and Non-Linear Growth Models with Random Parameters

  • N. M. Laird
Part of the Advanced Series in Agricultural Sciences book series (AGRICULTURAL, volume 18)

Abstract

This paper discusses the analysis of growth data using mixed models. Both Bayes and frequentist approaches are outlined for the linear model. The use of the EM algorithm is shown to offer a flexible and straightforward computational approach to the analysis. Extensions to non-linear models are described.

Keywords

Covariance 

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Copyright information

© Springer-Verlag Berlin Heidelberg 1990

Authors and Affiliations

  • N. M. Laird
    • 1
  1. 1.Department of BiostatisticsHarvard School of Public HealthBostonUSA

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