Linear Mixed-Effects Models Using R A Step-by-Step Approach /
Linear mixed-effects models (LMMs) are an important class of statistical models that can be used to analyze correlated data. Such data are encountered in a variety of fields including biostatistics, public health, psychometrics, educational measurement, and sociology. This book aims to support a wid...
| Main Authors: | , |
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| Corporate Author: | |
| Format: | Electronic |
| Language: | English |
| Published: |
New York, NY :
Springer New York : Imprint: Springer,
2013.
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| Series: | Springer Texts in Statistics,
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| Subjects: | |
| Online Access: | https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-1-4614-3900-4 |
Table of Contents:
- Introduction
- Linear Models for Independent Observations
- Linear Fixed-effects Models for Correlated Data
- Linear Mixed-effects Models.