Sensitivity analysis of longitudinal data with intermittent missing values-Reference-Cited by-同舟云学术

Sensitivity analysis of longitudinal data with intermittent missing values

Published:2007-04 Issue:2 Volume:4 Page:217-226
ISSN:1572-3127
Container-title:Statistical Methodology
language:en
Short-container-title:Statistical Methodology

Author:

Gad Ahmed M.,Ahmed Abeer S.

Publisher

Elsevier BV

Subject

Statistics and Probability

Reference27 articles.

1. The SEM algorithm: A probabilistic teacher algorithm derived from the EM algorithm for the mixture problem;Celeux;Computational Statistics Quarterly,1985

2. Modelling Binary Data;Collett,1991

3. Reparameterizing the pattern mixture model for sensitivity analyses under informative dropout;Daniels;Biometrics,2000

4. Stochastic EM algorithm: Method and application;Diebolt,1996

5. Informative dropout in longitudinal data analysis;Diggle;Journal of Royal Statistical Society. Series B.,1994

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