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

ISBN-13: 9780817643683 / Angielski / Twarda / 2006 / 540 str.

Jean-Louis Auget; N. Balakrishnan; Geert Molenberghs

Opis

Statistical methods have become an increasingly important and integral part of research in the health sciences. Many sophisticated methodologies have been developed for specific applications and problems. This self-contained comprehensive volume covers a wide range of topics pertaining to new statistical methods in the health sciences, including epidemiology, pharmacovigilance, quality of life, survival analysis, and genomics. The book will serve the health science community as well as practitioners, researchers, and graduate students in applied probability, statistics, and biostatistics.

Recenzje

From the reviews:

"This edited volume is an outgrowth of an 'International Conference on Statistical Methods' so-called in the Health Sciences in 2004. It is a well presented volume with lists of tables and figures. ... Clearly this volume covers a wide range of topics pertaining to statistical methods in the area of health sciences. ... In summary, it is a welcome addition to the literature of statistical science." (Technometrics, Vol. 49 (3), August, 2007)

Spis treści

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, and A.L. Harris On Statistical Approaches for the Multivariate Analysis of Prognostic Marker Studies \ N. Holländer 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. Bégaud, 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. Sébille, T. Challa, and M. Mesbah A Parametric Degradation Model Used in Reliability, Survival Analysis, and Quality of Life \ M. Nikulin, L. Gerville-Réache, 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. Yáñez, 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 HIV Pathogenesis Under Treatment by State Space Models \ W.-Y. Tan, P. Zhang, X. Xiong, and P. Flynn Part VI: Safety and Efficacy Assessment Safety Assessment Versus Efficacy Assessment \ M.A. Foulkes Cancer Clinical Trials with Efficacy and Toxicity Endpoints: A Simulation Study to Compare Two Nonparametric Methods \ A. Letierce and P. Tubert-Bitter Safety Assessment in Pilot Studies When Zero Events are Observed \ R.E. Carter and R.F. Woolson Part VII: Clinical Designs An Assessment of Up-and-Down Designs and Associated Estimators in Phase I Trials \ H.K.T. Ng, S.G. Mohanty, and N. Balakrishnan Design of Multicentre Clinical Trials with Random Enrolment \ V.V. Anisimov and V.V. Fedorov Statistical Methods for Combining Clinical Trial Phases II and III \ N. Stallard and S. Tod

O autorze

N. BALAKRISHNAN, PhD, is Professor of Mathematics and Statistics at McMaster University in Hamilton, Ontario, Canada.V. B. NEVZOROV, PhD, DS, is Professor of Probability and Statistics at St. Petersburg State University in St. Petersburg, Russia.

Blurb

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.