Journal of the Korean Data and Information Science Society
- 제17권4호
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- Pages.1053-1065
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- 2006
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- 1598-9402(pISSN)
A Study on One Factorial Longitudinal Data Analysis with Informative Drop-out
초록
This paper proposes a method in one-way layouts for longitudinal data with informative drop-out. When dropouts are informative, that is, correlated with unobserved data and/or the previous observed data, the simple imputation methods such as 'last observation carried forward' (LOCF) methods would arise the bias of the testing models. The maximum likelihood procedure combined with a logit model for the drop-out process is proposed to test treatment effects for one factorial designs and compared with LOCF method in two examples.