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,

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

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.