Résumé
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.
| Langue d'origine | English |
|---|---|
| Pages (de-à) | 3395-3409 |
| Nombre de pages | 15 |
| Journal | Statistics in Medicine |
| Volume | 21 |
| Numéro de publication | 22 |
| DOI | |
| Statut de publication | Published - nov. 30 2002 |
| Publié à l'externe | Oui |
ASJC Scopus Subject Areas
- Epidemiology
- Statistics and Probability
Empreinte numérique
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Abdolell, M., LeBlanc, M., Stephens, D., & Harrison, R. V. (2002). Binary partitioning for continuous longitudinal data: Categorizing a prognostic variable. Statistics in Medicine, 21(22), 3395-3409. https://doi.org/10.1002/sim.1266