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Applied longitudinal analysis / Garrett M. Fitzmaurice, Nan M. Laird, James H. Ware.
Connect to full text Available online
View online- Format:
- Book
- Author/Creator:
- Fitzmaurice, Garrett M., 1962-
- Series:
- Wiley series in probability and statistics
- Language:
- English
- Subjects (All):
- Longitudinal method.
- Regression analysis.
- Multivariate analysis.
- Medical statistics.
- Biometry--methods.
- Longitudinal Studies.
- Regression Analysis.
- Multivariate Analysis.
- Medical Subjects:
- Biometry--methods.
- Longitudinal Studies.
- Regression Analysis.
- Multivariate Analysis.
- Physical Description:
- 1 online resource (xxv, 701 pages) : illustrations.
- Edition:
- Second edition.
- Place of Publication:
- Hoboken, N.J. : Wiley, [2011]
- System Details:
- text file
- Summary:
- Three biostaticians at the Harvard School of Public Health update and enlarge their 2004 textbook for a graduate course introducing modern statistical methods for longitudinal data analysis that can then serve as a continuing reference for graduate students of statistics or substantive fields in which statistics are used, and statisticians working in public or private health-related contexts. It covers longitudinal and clustered data, linear models for longitudinal continuous data, generalized linear models for longitudinal data, missing data and dropout, and advanced topics for longitudinal and clustered data. Annotation ©2011 Book News, Inc., Portland, OR (booknews.com)
- Contents:
- Longitudinal and clustered data
- Longitudinal data: basic concepts
- overview of linear models for longitudinal data
- Estimation and statistics inference
- Modeling the mean: analyzing response profiles
- Modeling the mean: parametric curves
- Modeling the covariance
- Linear mixed effect models
- Fixed effects versus random effects models
- Residual analyses and diagnostics
- Review of generalized linear models
- Marginal models: introduction and overview
- Marginal models: generalized estimating equations (GEE)
- Generalized linear mixed effect models
- Generalized linear mixed effect models: approximate methods of estimation
- Contrasting marginal and mixed effects models
- Missing data and dropout: overview of concepts and methods
- Missing data and dropouts: multiple imputation and weighting methods
- Smoothing longitudinal data: semiparametric regression models
- Sample size and power
- Repeated measures and related designs
- Multilevel models
- Notes:
- Includes bibliographical references (pages 671-693) and index.
- Electronic reproduction. Hoboken, N.J. Available via World Wide Web.
- Description based on print version record.
- ISBN:
- 9781119513469
- 1119513464
- Publisher Number:
- 99985011086
- Access Restriction:
- Restricted for use by site license.
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