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Nonparametric Models for Longitudinal Data - With Implementation in R (Hardcover)
Loot Price: R4,069
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Nonparametric Models for Longitudinal Data - With Implementation in R (Hardcover)
Series: Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Expected to ship within 10 - 15 working days
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Nonparametric Models for Longitudinal Data with Implementations in
R presents a comprehensive summary of major advances in
nonparametric models and smoothing methods with longitudinal data.
It covers methods, theories, and applications that are particularly
useful for biomedical studies in the era of big data and precision
medicine. It also provides flexible tools to describe the temporal
trends, covariate effects and correlation structures of repeated
measurements in longitudinal data. This book is intended for
graduate students in statistics, data scientists and statisticians
in biomedical sciences and public health. As experts in this area,
the authors present extensive materials that are balanced between
theoretical and practical topics. The statistical applications in
real-life examples lead into meaningful interpretations and
inferences. Features: * Provides an overview of parametric and
semiparametric methods * Shows smoothing methods for unstructured
nonparametric models * Covers structured nonparametric models with
time-varying coefficients * Discusses nonparametric
shared-parameter and mixed-effects models * Presents nonparametric
models for conditional distributions and functionals * Illustrates
implementations using R software packages * Includes datasets and
code in the authors' website * Contains asymptotic results and
theoretical derivations
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