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Mixed Effects Models for Complex Data - Lang Wu

Anglų
2009-11-11
304,42 € 405,90 €

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Presenting effective approaches to address missing data, measurement errors, censoring, and outliers in longitudinal data, this book covers linear, nonlinear, generalized linear, nonparametric, and semiparametric mixed effects models. It links each mixed effects model with the corresponding class of regression model for cross-sectional data and discusses computational strategies for likelihood estimations o ... Visas aprašymas

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Presenting effective approaches to address missing data, measurement errors, censoring, and outliers in longitudinal data, this book covers linear, nonlinear, generalized linear, nonparametric, and semiparametric mixed effects models. It links each mixed effects model with the corresponding class of regression model for cross-sectional data and discusses computational strategies for likelihood estimations of mixed effects models. The author briefly describes generalized estimating equations methods and Bayesian mixed effects models and explains how to implement standard models using R and S-Plus. The real-world data examples used throughout encompass studies on mental distress, AIDS, and more.

Daugiau informacijos

Autorius Lang Wu
Leidėjas CRC Press
Išleidimo metai 2009
Viršelio tipas Kieti viršeliai
EAN 9781420074024
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304,42 € 405,90 €