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As this could potentially be due to different disease patterns in women and men, we separately analyzed incomplete revascularization patterns in relation to the number of diseased vessels.
When such complex samples are analyzed, incomplete chromatographic separations are often observed (note that this is also expected theoretically [ 30, 31]).
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MLM does not require sphericity, it takes the sampling hierarchy into account, and it is capable of analyzing incomplete data.
The paper concludes with a set of guidelines for analyzing incomplete longitudinal data that can improve the validity of research findings in developmental neuroimaging research.
A joint model for analyzing incomplete data from crossover trials is proposed in this article; the model includes a measurement model and an outcome dependent informative model for the dropout process.
The goal of this paper is to provide conceptual clarity of the issues and non-issues that arise from analyzing incomplete data in longitudinal studies with particular focus on neuroimaging data.
Several approaches are available to analyze incomplete data.
Multiple imputation (MI) is becoming increasingly popular as a strategy for analyzing incomplete data [ 1, 2].
When examining genetic difference between strains, analyzing incomplete genomes or standard nuclear markers may be misleading.
Yang and Shoptaw (2005) [ 21] present a thorough discussion of conceptual and practical issues in analyzing incomplete longitudinal data.
However, case-cohort studies represent a special type of incomplete data, and methods for analyzing incomplete data should be appropriate, in particular multiple imputation (MI).
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