Nonparametric Models for Longitudinal Data
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Nonparametric Models for Longitudinal Data: With Implementation in R

Nonparametric Models for Longitudinal Data: With Implementation in R

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About the Book

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

Table of Contents:
Overview of Longitudinal Analysis. Parametric and Semiparametric Methods. Nonparametric Models for Conditional-Means. Nonparametric Models with Missing. Functional Linear Models. Nonparametric Joint-Models with Survival Data. Methods for Time-Dependent and Outcome-Adaptive Covariate. Nonparametric Models for Distribution Functions. Structural Nonparametric Methods for Quantile Regression. Appendices.


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Product Details
  • ISBN-13: 9780429939075
  • Publisher: Taylor & Francis Ltd
  • Publisher Imprint: Chapman & Hall/CRC
  • Language: English
  • ISBN-10: 0429939078
  • Publisher Date: 23 May 2018
  • Binding: Digital (delivered electronically)
  • Sub Title: With Implementation in R


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Nonparametric Models for Longitudinal Data: With Implementation in R
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