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Linear mixed models for longitudinal data / Geert Verbeke, Geert Molenberghs.

By: Contributor(s): Material type: TextTextSeries: Springer series in statisticsPublication details: New York : Springer, 2000.Edition: Description: xxii, 568 p. : ill. ; 25 cmISBN:
  • 0387950273
Subject(s): NLM classification:
  • QA 279 2000VE
Contents:
Introduction -- Ch 2.Examples -- Ch 3 Model for Longitudinal Data -- Ch.4 Exploratory Data Analysis -- Ch.5 Estimation of the Marginal Model -- Ch.6 Inference for the Marginal Model -- Ch.7 Inference for the Random Effects -- Ch.8 Fitting Linear Mixed Models with SAS -- Ch.9 General Guidelines for Model Building -- Ch. 10 Exploring Serial Correlation -- Ch.11 Local Influence for the Linear Mixed Model -- Ch.12 The Heterogeneity Model -- Ch. 13 Conditional Linear Mixed Models -- Ch.14 Exploring Incomplete Data -- Ch.15 Joint Modeling of Measurements and Missingness -- Ch.16 Simple Missing Data Methods -- Ch.17 Selection Models -- Ch.18 Pattern-Mixture Models -- Ch.19 Sensitivity Analysis for Selection Models -- Ch.20 Sensitivity Analysis for Pattern-Mixture Models -- Ch.21 How Ignorable Is Missing At Random? -- Ch. 22 The Expectation-Maximization Algorithm -- Ch.23 Design Considerations 3 -- Ch.24 Case Studies -- App. A: Software -- App. B Technical Details for Sensitivity Analysis -- References -- Index .
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Item type Current library Call number Copy number Status Date due Barcode
Books Books WHO HQ BORROWABLE-COLL-STACKS QA 279 2000VE (Browse shelf(Opens below)) 1 Available 00076301

Introduction -- Ch 2.Examples -- Ch 3 Model for Longitudinal Data -- Ch.4 Exploratory Data Analysis -- Ch.5 Estimation of the Marginal Model -- Ch.6 Inference for the Marginal Model -- Ch.7 Inference for the Random Effects -- Ch.8 Fitting Linear Mixed Models with SAS -- Ch.9 General Guidelines for Model Building -- Ch. 10 Exploring Serial Correlation -- Ch.11 Local Influence for the Linear Mixed Model -- Ch.12 The Heterogeneity Model -- Ch. 13 Conditional Linear Mixed Models -- Ch.14 Exploring Incomplete Data -- Ch.15 Joint Modeling of Measurements and Missingness -- Ch.16 Simple Missing Data Methods -- Ch.17 Selection Models -- Ch.18 Pattern-Mixture Models -- Ch.19 Sensitivity Analysis for Selection Models -- Ch.20 Sensitivity Analysis for Pattern-Mixture Models -- Ch.21 How Ignorable Is Missing At Random? -- Ch. 22 The Expectation-Maximization Algorithm -- Ch.23 Design Considerations 3 -- Ch.24 Case Studies -- App. A: Software -- App. B Technical Details for Sensitivity Analysis -- References -- Index .

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