Titlebook: Linear Mixed Models for Longitudinal Data; Geert Verbeke,Geert Molenberghs Book 2000 Springer Science+Business Media New York 2000 Fitting

In-Situ

Exploratory Data Analysis,rved profiles averaged over (sub)populations. Three aspects of the data will be looked at in turn: the average evolution, the variance function, and the correlation structure. Afterward, in Section 4.3, we will discuss some procedures for exploring the observed profiles in a subject-specific way.

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Inference for the Random Effects,or detecting special profiles (i.e., outlying individuals) or groups of individuals evolving differently in time. Also, estimates for the random effects are needed whenever interest is in prediction of subject-specific evolutions (see Section 7.5).

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Local Influence for the Linear Mixed Model, eliminated from the analysis, or they may suggest that additional data need to be collected or that the current model is inadequate. Of course, an extended investigation of influential cases is only possible once they have been identified.

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Control-Group

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Ccu106

e past decade, image-guided surgeries and image-guided minimally invasive interventions have emerged as advances that can be used in place of traditional invasive approaches. Advanced imaging technologies such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomog

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e past decade, image-guided surgeries and image-guided minimally invasive interventions have emerged as advances that can be used in place of traditional invasive approaches. Advanced imaging technologies such as magnetic resonance imaging (MRI), computed tomography (CT), and positron emission tomog

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