Longitudinal Data Analysis

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advanced statistical methods
biostatistics
Category=JHBC
clinical trial data modeling
Conditional Expectation
Discrete Longitudinal Data
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Garrett Fitzmauruce
Gee Approach
generalized
Generalized Linear Mixed Model
Generalized Linear Models
IPWA Estimator
Joint Models
linear
Linear Mixed Model
Local Polynomial Kernel
longitudinal data analysis
longitudinal study methodology
MAR Assumption
MAR Model
marginal
Marginal Models
mechanisms
missing
Missing Data
Missing Data Mechanism
mixed
mixture
model
Multiple Imputation
NMAR Mechanism
Non-linear Mixed Models
nonparametric method
parametric modeling
pattern
PMM
Random Intercept
Regression Parameters
Regression Spline
repeated measures analysis
semiparametric estimation
Shared Parameter Models
shared-parameter
Smoothing Parameter
Smoothing Spline Estimator
time series in medical research
time-varying exposures

Product details

  • ISBN 9781584886587
  • Weight: 1315g
  • Dimensions: 178 x 254mm
  • Publication Date: 11 Aug 2008
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Although many books currently available describe statistical models and methods for analyzing longitudinal data, they do not highlight connections between various research threads in the statistical literature. Responding to this void, Longitudinal Data Analysis provides a clear, comprehensive, and unified overview of state-of-the-art theory and applications. It also focuses on the assorted challenges that arise in analyzing longitudinal data.

After discussing historical aspects, leading researchers explore four broad themes: parametric modeling, nonparametric and semiparametric methods, joint models, and incomplete data. Each of these sections begins with an introductory chapter that provides useful background material and a broad outline to set the stage for subsequent chapters. Rather than focus on a narrowly defined topic, chapters integrate important research discussions from the statistical literature. They seamlessly blend theory with applications and include examples and case studies from various disciplines.

Destined to become a landmark publication in the field, this carefully edited collection emphasizes statistical models and methods likely to endure in the future. Whether involved in the development of statistical methodology or the analysis of longitudinal data, readers will gain new perspectives on the field.

Garrett Fitzmaurice, Marie Davidian, Geert Verbeke, Geert Molenberghs