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9780470740545

Robust Methods in Biostatistics

by ; ; ;
  • ISBN13:

    9780470740545

  • ISBN10:

    047074054X

  • Format: eBook
  • Copyright: 2009-04-01
  • Publisher: Wiley
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Summary

Regulatory bodies and medical journals regularly raise their standards in terms of the quality of statistical analyses presented, wanting to ensure statistical methods are not misused leading to wrong conclusions. Following this trend there is a growing need for robust statistics in medical research. Robust statistics is an extension of classical statistics that specifically takes into account that the underlying models used to describe data are only approximate. Its basic philosophy is to produce statistical procedures which are stable withy respect to changes in the data or model departures.Robust Methods in Biostatistics is the first book on robust methodology to be directed specifically at biostatistics, which would benefit both fields greatly. It allows students, biostatisticians and researchers of all levels easy access by introducing each chapter's topic with the classical approach before explaining the robust alternatives.

Table of Contents

Introduction
What is Robust Statistics?
Against What is Robust Statistics Robust?
Are Diagnostic Methods an Alternative to Robust Statistics?
How do Robust Statistics Compare with Other Statistical Procedures in Practice?
Key Measures and Results
Introduction
Statistical Tools for Measuring Robustness Properties
General Approaches for Robust Estimation
Statistical Tools for Measuring the Robustness of Tests
General Approaches for Robust Testing
Linear Regression
Introduction
Estimating the Regression Parameters
Testing the Regression Parameters
Checking and Selecting the Model
Cardiovascular Risk Factors Data Example
Mixed Linear Models
Introduction
The MLM
Classical Estimation and Inference
Robust Estimation
Robust Inference
Checking the Model
Further Examples
Discussion and Extensions
Generalized Linear Models
Introduction
The GLM
A Class of M-estimators for GLMs
Robust Inference
Breastfeeding Data Example
Doctor Visits Data Example
Discussion and Extensions
Marginal Longitudinal Data Analysis
Introduction
The Marginal Longitudinal Data Model (MLDA) and Alternatives
A Robust GEE-type Estimator
Robust Inference
LEI Data Example
Stillbirth in Piglets Data Example
Discussion and Extensions
Survival Analysis
Introduction
The Cox Model
Robust Estimation and Inference in the Cox Model
The VeteranÆs Administration Lung Cancer Data
Structural Misspecifications
Censored Regression Quantiles
Appendices
Starting Estimators for MM-estimators of Regression Parameters
Efficiency, LRT? RAIC and RCp with Biweight ?-function for the Regression Model
An Algorithm Procedure for the Constrained S-estimator
Some Distributions of the Exponential Family
Computations for the Robust GLM Estimator
FisherConsistencyCorrections
AsymptoticVariance
IRWLSAlgorithmforRobustGLM
Computations for the Robust GEE Estimator
IRWLSAlgorithmforRobustGEE
FisherConsistencyCorrections
Computation of the CRQ
References
Index
Table of Contents provided by Publisher. All Rights Reserved.

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