On modelling mean-covariance structures in longitudinal studies

Pan, Jianxin and Mackenzie, Gilbert (2003) On modelling mean-covariance structures in longitudinal studies. Biometrika, 90 (1). pp. 239-244. ISSN 0006-3444

PDF 239.pdf Restricted to Repository staff only Download (149kB)

Abstract

We exploit a reparameterisation of the marginal covariance matrix arising in longitudinal studies (Pourahmadi, 1999, 2000) to model, jointly, the mean and covariance structures in terms of three polynomial functions of time.By reanalysing Kenward's (1987) cattle data, we compare model selection procedures based on regressogram estimation with these based on a global search of the model space. Using a BIC-based model selection criterion to identify the optimum degree triple of the three polynomials, we show that the use of a saturated mean model is not optimal and explain why regressogram-based model estimation may be misleading. We also suggest a new computational method for finding the global optimum based on a criterion involving three pairwise saturated profile likelihoods.

Item Type:	Article
Uncontrolled Keywords:	Cholesky decomposition; Global optimisation; Joint mean-covariance model; Longitudinal data analysis
Subjects:	MSC 2010, the AMS's Mathematics Subject Classification > 60 Probability theory and stochastic processes MSC 2010, the AMS's Mathematics Subject Classification > 62 Statistics
Depositing User:	Ms Lucy van Russelt
Date Deposited:	16 Aug 2006
Last Modified:	20 Oct 2017 14:12
URI:	https://eprints.maths.manchester.ac.uk/id/eprint/524

Actions (login required)

View Item