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Springer Linear Mixed-Effects Models Using R Textbook

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Description

Master the implementation of Linear Mixed-Effects Models (LMMs) with this Springer textbook. Designed for applied researchers, this guide provides state-of-the-art descriptions for analyzing correlated data within the R programming environment. Linear mixed-effects models are essential tools for various scientific disciplines. This book supports professionals in biostatistics, public health, psychometrics, educational measurement, and sociology. By following a step-by-step approach, readers can learn to handle complex data structures effectively. The text includes a review of model features and specific details for carrying out analysis in R, making it a practical resource for those needing to implement these statistical models in real-world research settings.

Key Features

This Springer publication provides a step-by-step approach to implementing Linear Mixed-Effects Models in R.

The text offers state-of-the-art descriptions specifically designed for applied researchers using R.

Learn to analyze correlated data used in fields such as biostatistics, public health, and sociology.

The book includes a review of model features to help readers become familiar with LMM implementation details.

This resource supports diverse research needs in psychometrics and educational measurement through R-based modeling.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
05 February 2013
Listed Since
14 July 2012

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