Binary partitioning for continuous longitudinal data: categorizing a prognostic variable
- 24 October 2002
- journal article
- research article
- Published by Wiley in Statistics in Medicine
- Vol. 21 (22) , 3395-3409
- https://doi.org/10.1002/sim.1266
Abstract
We investigate a binary partitioning algorithm in the case of a continuous repeated measures outcome. The procedure is based on the use of the likelihood ratio statistic to evaluate the performance of individual splits. The procedure partitions a set of longitudinal data into two mutually exclusive groups based on an optimal split of a continuous prognostic variable. A permutation test is used to assess the level of significance associated with the optimal split, and a bootstrap confidence interval is obtained for the optimal split. Copyright © 2002 John Wiley & Sons, Ltd.Keywords
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