A bidimensional finite mixture model for longitudinal data subject to dropout.
In longitudinal studies, subjects may be lost to follow up and, thus, present incomplete response sequences. When the mechanism underlying the dropout is nonignorable, we need to account for dependence between the longitudinal and the dropout process. We propose to model such a dependence through di...
| Publicado en: | Statistics in Medicine Vol. 37; no. 20; pp. 2998 - 3012 |
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| Autores principales: | , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
9/10/2018
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| Acceso en línea: | Ver este registro en EBSCOhost |