Springer Texts in Statistics / Applied longitudinal Data Analysis
(Sprache: Englisch)
The goal of this book is to provide an overview of statistical models and methods that are useful in the analysis of longitudinal data; that is, data in the form of repeated measurements on the same experimental unit over time. The intended audience is a...
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The goal of this book is to provide an overview of statistical models and methods that are useful in the analysis of longitudinal data; that is, data in the form of repeated measurements on the same experimental unit over time. The intended audience is a combination of non- statistics graduate students who have taken an applied methods course covering linear regression and Analysis of Variance and masters-level statistics students looking for an applied intro course.
Inhaltsverzeichnis zu „Springer Texts in Statistics / Applied longitudinal Data Analysis “
- Introduction and Motivation - Review of Matrix Algebra
- Random Vectors and Multivariate Normal Distribution
- Univariate Repeated Measures Analysis of Variance
- Multivariate Repeated Measures Analysis of Variance
- Drawbacks and Limitations of Classicial Methods
- General Linear Models for Longitudinal Data
- Random Coefficient Models for Multivariate Normal Data
- Linear Mixed Effects Models for Multivariate Normal Data
- Generalized Linear Models for NonNormal Response
- Population-averaged Models for Nonnormal Repeated Measurements
- Advanced Topics
Bibliographische Angaben
- Autor: Marie Davidian
- 2010, 504 Seiten, Gebunden, Englisch
- Verlag: Springer, Berlin
- ISBN-10: 038740337X
- ISBN-13: 9780387403373
Sprache:
Englisch
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