A Latent‐Class Mixture Model for Incomplete Longitudinal Gau…

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A Latent‐Class Mixture Model for Incomplete Longitudinal Gaussian Data

Article 2007 EN

In the analyses of incomplete longitudinal clinical trial data, there has been a shift, away from simple methods that are valid only if the data are missing completely at random, to more principled ignorable analyses, which are valid under the less restrictive missing at random assumption. The availability of the necessary standard statistical software nowadays allows for such analyses in practice…

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4

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4 authors
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1 Caroline Beunckens Corresponding Hasselt University (BE) —
2 Geert Molenberghs Hasselt University (BE)
3 Geert N. Verbeke KU Leuven (BE)
4 Craig H. Mallinckrodt Eli Lilly (United States) (US)

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