Topics in Modelling of Clustered Data
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€210.80
advanced regression models
Association Parameter
Benchmark Dose
beta
Beta Binomial Model
binary
binomial
biomedical data analysis
Category=PBT
Category=PBWH
Cluster Level Covariates
clustered data analysis for medical research
conditional
Conditional Model
developmental
Developmental Toxicity Studies
Dose Response Modeling
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
equations
estimating
Fetal Weight
Fractional Polynomial Models
Fractional Polynomials
Generalized Estimating Equations
Generalized Linear Mixed Models
hierarchical data modeling
Individual Level Covariates
Intracluster Correlation
Ith Cluster
Litter Size
Ln Fs
Local Polynomial
marginal
Marginal Models
multilevel statistical analysis
National Toxicology Program Data
Orthogonal Series Estimators
Pseudo-likelihood Ratio Tests
Quantitative Risk Assessment
robust inference techniques
Safe Dose
studies
survey sampling methods
toxicity
Wald Test
Product details
- ISBN 9781584881858
- Weight: 780g
- Dimensions: 152 x 229mm
- Publication Date: 29 May 2002
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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Many methods for analyzing clustered data exist, all with advantages and limitations in particular applications. Compiled from the contributions of leading specialists in the field, Topics in Modelling of Clustered Data describes the tools and techniques for modelling the clustered data often encountered in medical, biological, environmental, and social science studies. It focuses on providing a comprehensive treatment of marginal, conditional, and random effects models using, among others, likelihood, pseudo-likelihood, and generalized estimating equations methods.
The authors motivate and illustrate all aspects of these models in a variety of real applications. They discuss several variations and extensions, including individual-level covariates and combined continuous and discrete outcomes. Flexible modelling with fractional and local polynomials, omnibus lack-of-fit tests, robustification against misspecification, exact, and bootstrap inferential procedures all receive extensive treatment. The applications discussed center primarily, but not exclusively, on developmental toxicity, which leads naturally to discussion of other methodologies, including risk assessment and dose-response modelling.
Clearly written, Topics in Modelling of Clustered Data offers a practical, easily accessible survey of important modelling issues. Overview models give structure to a multitude of approaches, figures help readers visualize model characteristics, and a generous use of examples illustrates all aspects of the modelling process.
Marc Aerts, Helena Geys, Geert Molenberghs, Louise M. Ryan
