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02494nam a22005175i 4500 |
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978-0-387-22775-7 |
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|a 9780387227757
|9 978-0-387-22775-7
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|a 10.1007/b98969
|2 doi
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|d GrThAP
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|a TA342-343
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|a 003.3
|2 23
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|a Verbeke, Geert.
|e author.
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|a Linear Mixed Models for Longitudinal Data
|h [electronic resource] /
|c by Geert Verbeke, Geert Molenberghs.
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|a New York, NY :
|b Springer New York,
|c 2000.
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|a XXII, 568 p.
|b online resource.
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|a text
|b txt
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|a computer
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|a online resource
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|a text file
|b PDF
|2 rda
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|a Springer Series in Statistics,
|x 0172-7397
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|a Examples -- A Model for Longitudinal Data -- Exploratory Data Analysis -- Estimation of the Marginal Model -- Inference for the Marginal Model -- Inference for the Random Effects -- Fitting Linear Mixed Models with SAS -- General Guidelines for Model Building -- Exploring Serial Correlation -- Local Influence for the Linear Mixed Model -- The Heterogeneity Model -- Conditional Linear Mixed Models -- Exploring Incomplete Data -- Joint Modeling of Measurements and Missingness -- Simple Missing Data Methods -- Selection Models -- Pattern-Mixture Models -- Sensitivity Analysis for Selection Models -- Sensitivity Analysis for Pattern-Mixture Models -- How Ignorable Is Missing At Random ? -- The Expectation-Maximization Algorithm -- Design Considerations -- Case Studies.
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|a Mathematics.
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|a Mathematical models.
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|a Probabilities.
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|a Statistics.
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|a Mathematics.
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|a Mathematical Modeling and Industrial Mathematics.
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|a Probability Theory and Stochastic Processes.
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|a Statistical Theory and Methods.
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|a Molenberghs, Geert.
|e author.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9780387950273
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|a Springer Series in Statistics,
|x 0172-7397
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|u http://dx.doi.org/10.1007/b98969
|z Full Text via HEAL-Link
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|a ZDB-2-SMA
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|a ZDB-2-BAE
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|a Mathematics and Statistics (Springer-11649)
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