Estimating local and global measures of association for bivariate interval censored data with a smooth estimate of the density

K Bogaerts, Emmanuel Lesaffre

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Measures of association for bivariate interval censored data have not yet been studied extensively. Betensky and Finkelstein (Statist, Med. 1999 18:3101-3109) Proposed to calculate Kendall's coefficient of concordance using a multiple imputation technique, but their method becomes computer intensive for moderate to large data sets. We suggest a different approach consisting of two steps. Firstly, a bivariate smooth estimate of the density of log-event times is determined. The smoothing technique is based on a mixture of given the Gaussian densities fixed on it,rid with weights determined by a penalized likelihood approach. Secondly. given the smooth approximation several local and global Measures of association can be estimated readily. The performance of our method is illustrated by an extensive simulation Study and is applied to tooth emergence data of permanent teeth Measured on 4468 children front the Signal-Tandmobiel (R) study. Copyright (C) 2008 John Wiley, & Sons, Ltd.
Original languageUndefined/Unknown
Pages (from-to)5941-5955
Number of pages15
JournalStatistics in Medicine
Issue number28
Publication statusPublished - 2008

Research programs

  • EMC NIHES-01-66-01

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