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Linear Mixed Models for Longitudinal Data

Name: Linear Mixed Models for Longitudinal Data
SKU: 9781441902993
Price: 1466.1 NOK
Availability: BackOrder
ISBN: 9781441902993

Av Geert Molenberghs, Geert Verbeke, 2009.Del av serien Springer Series in Statistics.

This book provides a comprehensive treatment of linear mixed models for continuous longitudinal data. Next to model formulation, this edition puts major emphasis on exploratory data analysis for all aspects of the model, such as the marginal model, subject-specific profiles, and residual covariance structure. Further, model diagnostics and missing data receive extensive treatment. Sensitivity analysis for incomplete data is given a prominent place.

Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.

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Linear Mixed Models for Longitudinal Data

Av Geert Molenberghs, Geert Verbeke, 2009.Del av serien Springer Series in Statistics.

Most analyses were done with the MIXED procedure of the SAS software package, but the data analyses are presented in a software-independent fashion.

Oppdag mer

Andre bøker i serien Springer Series in Statistics

Gaussian and Non-Gaussian Linear Time Series and Random Fields

1 124,-

Linear and Generalized Linear Mixed Models and Their Applications

1 340,-

Models for Discrete Longitudinal Data

2 186,-

Model-based Geostatistics

1 340,-

The Linear Model and Hypothesis

611,-

Regression Modeling Strategies

1 124,-

Targeted Learning

2 159,-

Linear and Generalized Linear Mixed Models and Their Applications

1 340,-

Model-based Geostatistics

1 826,-

Semiparametric Theory and Missing Data

2 654,-

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Applied Surrogate Endpoint Evaluation Methods With SAS and R

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Normalpris: 1 629,-

1 466,-

Spar 163,-

Innbundet — ikke tilgjengelig

Pocket

E-bok — ikke tilgjengelig

Lydbok — ikke tilgjengelig

Språk: Engelsk

Ikke tilgjengelig for Klikk&Hent

Midlertidig utsolgtBestillingsvare. Forventes sendt om ca 20 dager

1 466,-

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Linear Mixed Models for Longitudinal Data

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