Statistical Modelling 6 (2006), 337–351
Analyzing the emergence times of permanent teeth: an example of
modeling the covariance matrix with interval-censored data
Silvia Cecere, Alejandro Jara, and Emmanuel Lesaffre
Biostatistical Centre
Catholic University of Leuven
Kapucijnenvoer 35
B–3000 Leuven
Belgium
eMail:
emmanuel.lesaffre@med.kuleuven.be
Abstract:
Based on a data set obtained in a large dental longitudinal study,
conducted in Flanders (Belgium), the joint emergence distribution of
seven teeth was modeled as a function of gender and caries experience
on primary teeth. Besides establishing the marginal dependence of
emergence on the covariates, there was also interest in examining the
impact of the covariates on the association among emergence times.
This allows the establishment of the preferred rankings of emergence
and their dependence on covariates. To this end, the covariance matrix
was modeled as a function of covariates. Modeling the covariance matrix
in this way needs to ensure the positive definiteness of the covariance
matrix and it is preferable that the regression parameters of the model
are interpretable. The modified Cholesky decomposition of the covariance
matrix, as suggested by Pourahmadi, splits up the covariance matrix
into two parts where the parameters can be interpreted, given a natural
ranking of the responses. This approach was used here taking into
account that the emergence times are interval-censored. Hence, we
opted for a Bayesian implementation of the data augmentation algorithm.
Keywords:
bivariate survival; covariance matrix; data augmentation;
emergence times; interval-censored; multivariate normality
Downloads:
A zipped
archive contains
R-code, C source code and an MS-Windows
DLL. The data are publicly available, please contact Emmanuel Lesaffre at
emmanuel.lesaffre@med.kuleuven.be.
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