Linear Mixed Models for Longitudinal Data / by Geert Verbeke, Geert Molenberghs
(Springer Series in Statistics)
| データ種別 | 電子ブック |
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| 出版者 | New York, NY : Springer New York |
| 出版年 | 2000 |
| 本文言語 | 英語 |
| 大きさ | XXII, 568 p : online resource |
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| 内容注記 | 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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| 著者標目 | *Verbeke, Geert author Molenberghs, Geert author SpringerLink (Online service) |
| 件 名 | LCSH:Mathematics LCSH:Mathematical models LCSH:Probabilities LCSH:Statistics FREE:Mathematics FREE:Mathematical Modeling and Industrial Mathematics FREE:Probability Theory and Stochastic Processes FREE:Statistical Theory and Methods |
| 分 類 | DC23:003.3 |
| 巻冊次 | ISBN:9780387227757 
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| ISBN | 9780387227757 |
| URL | http://dx.doi.org/10.1007/b98969 |
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