Advances in Statistical Methods for the Health Sciences:Applications to Cancer and AIDS Studies Genome Sequence Analysis and Survival Analysis

Statistical methods have become increasingly important and now form
integral part of research in the health sciences. Many sophisticated
methodologies have been developed for specific applications and
problems. This self-contained volume, an outgrowth of
an "International Conference on Statistical Methods in Health
Sciences," covers a wide range of topics pertaining to new
statistical methods and novel applications in the health sciences.


The chapters, written by leading experts in their respective fields,
are thematically divided into the following areas:

* Prognostic studies and general epidemiology

* Pharmacovigilance

* Quality of life

* Survival analysis

* Clustering

* Safety and efficacy assessment

* Clinical design

* Models for the environment

* Genomic analysis

* Animal health

This comprehensive volume will be highly useful an of great interest
to the health science community as well as practitioners,
researchers, and graduate students in applied probability,
statistics, and biostatistics.

Preface

Contributors

List of Tables

List of Figures

Part I: Prognostic Studies and General Epidemiology

Systematic Review of Multiple Studies of Prognosis: The Feasibility
of Obtaining Individual Patient Data \ D.G. Altman, M. Trivella, F.
Pezzella, A.L. Harris, and U. Pastorino

On Statistical Approaches for the Multivariate Analysis of Prognostic
Marker Studies \ N. Hollander and W. Sauerbrei

Where Next for Evidence Synthesis of Prognostic Marker Studies?
Improving the Quality and Reporting of Primary Studies to Facilitate
Clinically Relevant Evidence-Based Results \ R.D. Riley, K.R. Abrams,
P.C. Lambert, A.J. Sutton, and D.G. Altman

Part II: Pharmacovigilance

Sentinel Event Methods for Monitoring Unanticipated Adverse Events \
P.A. Lachenbruch and J. Wittes

Spontaneous Reporting System Modelling for the Evaluation of
Automatic Signal Generation Methods in Pharmacovigilance \ E. Roux,
F. Thiessard, A. Fourier, B. Begaud, and P. Tubert-Bitter

Part III: Quality of Life

Latent Covariates in Generalized Linear Models: A Rasch Model
Approach \ K.B. Christensen

Sequential Analysis of Quality of Life Measurements with the Mixed
Partial Credit Model \ V. Sebille, T. Challa, and M. Mesbah

A Parametric Degradation Model Used in Reliability, Survival
Analysis, and Quality of Life \ M. Nikulin, L. Gerville-Reache, and
S. Orazio

Agreement Between Two Ratings with Different Ordinal Scales \ S.
Natarajan, M.B. McHenry, S. Lipsitz, N. Klar, and S. Lipshultz

Part IV: Survival Analysis

The Role of Correlated Frailty Models in Studies of Human Health,
Ageing, and Longevity \ A. Wienke, P. Lichtenstein, K. Czene, and
A.I. Yashin

Prognostic Factors and Prediction of Residual Survival for
Hospitalized Elderly Patients \ M.L. Calle, P. Roura, A. Arnau, A.
Yanez, and A. Leiva

New Models and Methods for Survival Analysis of Experimental Data \
G.V. Semenchenko, A.I. Yashin, T.E. Johnson, and J.W. Cypser

Uniform Consistency for Conditional Lifetime Distribution Estimators
Under Random Right-Censorhip \ P. Deheuvels and G. Derzko

Sequential Estimation for the Semiparametric Additive Hazard Model \
L. Bordes and C. Breuils

Variance Estimation of a Survival Function with Doubly Censored
Failure Time Data \ C. Zhu and J. Sun

Part V: Clustering

Statistical Models and Artificial Neural Networks: Supervised
Classification and Prediction Via Soft Trees \ A. Ciampi and Y.
Lechevallier

Multilevel Clustering for Large Databases \ Y. Lechevallier and A.
Ciampi

Neural Networks: An Application for Predicting Smear Negative
Pulmonary Tuberculosis \ A.M. Santos, B.B. Pereira, J.M. Seixas,
F.C.Q. Mello, and A.L. Kritski

Assessing Drug Resistance in HIV Infection Using Viral Load Using
Segmented Regression \ H. Liang, W.-Y. Tan, and X. Xiong

Assessment of Treatment Effects on HI