Lang Wu

Mixed Effects Models for Complex Data (eBook, ePUB)

• Format: ePub

Produktbeschreibung

Although standard mixed effects models are useful in a range of studies, other approaches must often be used in correlation with them when studying complex or incomplete data. Mixed Effects Models for Complex Data discusses commonly used mixed effects models and presents appropriate approaches to address dropouts, missing data, measurement errors,

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Erscheinungstermin: 11. November 2009
• Englisch
• ISBN-13: 9781040171042
• Artikelnr.: 72583636

Autorenporträt

Lang Wu is an associate professor in the Department of Statistics at the University of British Columbia in Vancouver, Canada.

Inhaltsangabe

Introduction. Mixed Effects Models. Missing Data, Measurement Errors, and
Outliers. Mixed Effects Models with Missing Data. Mixed Effects Models with
Covariate Measurement Errors. Mixed Effects Models with Censoring. Survival
Mixed Effects (Frailty) Models. Joint Modeling Longitudinal and Survival
Data. Robust Mixed Effects Models. Generalized Estimating Equations (GEEs).
Bayesian Mixed Effects Models. Appendix. References. Index. Abstract.