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CRC Press Nonparametric Models for Longitudinal Data - R Implementation

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Description

Nonparametric Models for Longitudinal Data: With Implementation in R by CRC Press provides a comprehensive guide to advanced nonparametric models and smoothing methods for analysing repeated measurements over time. This Chapman & Hall/CRC monograph is designed for graduate students in statistics, data scientists, and biomedical statisticians working with longitudinal data in modern research environments. The book covers essential methods, theories, and practical applications particularly valuable for biomedical studies in the era of big data and precision medicine. It equips readers with flexible tools to describe temporal trends, quantify covariate effects, and model correlation structures inherent in repeated measurements, making it an indispensable resource for professionals developing sophisticated statistical models and analysing complex longitudinal datasets.

Key Features

Comprehensive coverage of nonparametric models and smoothing methods tailored for longitudinal data analysis.

Practical implementation guidance using R programming, with code examples and techniques for biomedical applications.

Methods for modelling temporal trends and covariate effects in repeated measurements from longitudinal studies.

Tools for understanding correlation structures within longitudinal data to improve statistical inference.

Content designed for graduate students, data scientists, and biomedical statisticians conducting precision medicine research.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
05 February 2016
Listed Since
08 June 2013

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