Linear Mixed Models for Longitudinal Data [electronic resource] /
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.
Main Authors: | , , |
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Format: | Texto biblioteca |
Language: | eng |
Published: |
New York, NY : Springer New York,
2000
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Subjects: | Mathematics., Mathematical models., Probabilities., Statistics., Mathematical Modeling and Industrial Mathematics., Probability Theory and Stochastic Processes., Statistical Theory and Methods., |
Online Access: | http://dx.doi.org/10.1007/b98969 |
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Summary: | 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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