Mixed Effects Models for Complex Data (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)

Book Detail
Edition: 1
Release: 2009-11-11
Publisher: Chapman and Hall/CRC
Binding: Hardcover
ISBN/ASIN: 1420074024
Format: hardcover, kindle, PDF, EPUB

Mixed Effects Models for Complex Data (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) pdf
Description

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, censoring, and outliers. For each class of mixed effects model, the author reviews the corresponding class of regression model for cross-sectional data. An overview of general models and methods, along with motivating examples
After presenting real data examples and outlining general approaches to the analysis of longitudinal/clustered data and incomplete data, the book introduces linear mixed effects (LME) models, generalized linear mixed models (GLMMs), nonlinear mixed effects (NLME) models, and semiparametric and nonparametric mixed effects models. It also includes general approaches for the analysis of complex data with missing values Download Mixed Effects Models for Complex Data (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) for free via rapidshare, mediafire, 4shared, dropBox, uploading, fileserve

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