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Analysis of Clinical Trials Using SAS: A Practical Guide

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Analysis of Clinical Trials Using SAS: A Practical Guide 公卫人
By: Alex Dmitrienko, Geert Molenberghs, Christy Chuang-Stein, and Walter Offen
Price: 69.95 USD
440 pages
ISBN: 978-1-59047-504-1
Publisher: SAS Press
Copyright Date: February 2005

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Description

In Analysis of Clinical Trials Using SAS: A Practical Guide, Alex Dmitrienko, Geert Molenberghs, Christy Chuang-Stein, and Walter Offen bridge the gap between modern statistical methodology and real-world clinical trial applications. Step-by-step instructions illustrated with examples from actual trials and case studies serve to define a statistical method and its relevance in a clinical trials setting and to illustrate how to implement the method rapidly and efficiently using the power of SAS software. Topics reflect the International Conference on Harmonization (ICH) guidelines for the pharmaceutical industry and address important statistical problems encountered in clinical trials, including analysis of stratified data, incomplete data, multiple inferences, issues arising in safety and efficacy monitoring, and reference intervals for extreme safety and diagnostic measurements. Clinical statisticians, research scientists, and graduate students in biostatistics will greatly benefit from the decades of clinical research experience compiled in this book. Numerous ready-to-use SAS macros and example code are included.

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Contents

1 Analysis of Stratified Data 1
Introduction 1
Continuous Endpoints 3
Categorical Endpoints 19
Time-to-Event Endpoints 40
Tests for Qualitative Interactions 56
2 Multiple Comparisons and Multiple Endpoints 67

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Introduction 67
Single-Step Tests 70
Closed Testing Methods 74
Fixed-Sequence Testing Methods 84
Resampling-Based Testing Methods 89
Testing Procedures for Multiple Endpoints 94
Gatekeeping Strategies 104
3 Analysis of Safety and Diagnostic Data 129
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Introduction 129
Reference Intervals for Safety and Diagnostic Measures 130
Analysis of Shift Tables 157
4 Interim Data Monitoring 177
Introduction 177
Repeated Significance Tests 181
Stochastic Curtailment Tests 235
5 Analysis of Incomplete Data 269
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Introduction 269
Case Studies 271
Data Setting and Modeling Framework 273
Analysis of Complete Growth Data 276
Simple Methods and MCAR 287
Available Case Methods 300
Likelihood-Based Ignorable Analyses 301
:A Practical Guide 公卫人
Multiple Imputation 308
The EM Algorithm 326
Categorical Data 332
MNAR and Sensitivity Analysis 353
Summary 354
Appendix 355
References 391
Index 405

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Authors

Alex Dmitrienko, Ph.D.
Alex Dmitrienko, Ph.D., is Principal Research Scientist at Eli Lilly and Company. Actively involved in biostatistical research, Alex has published papers on multiple testing, group sequential inferences, and analysis of categorical data with clinical trial applications. His other professional interests include software implementation of new and existing statistical methods.

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Geert Molenberghs, Ph.D.
Geert Molenberghs, Ph.D., is Professor of Biostatistics at the Center for Statistics at Limburgs Universitair Centrum, Belgium. Geert has co-authored books on longitudinal data analysis, mixed models, and incomplete data and has published papers on incomplete and longitudinal data. He has acted as a consultant for the government as well as several pharmaceutical companies and research institutes. 公卫考场

Christy Chuang-Stein, Ph.D.
Christy Chuang-Stein, Ph.D., is Senior Director of the Statistical Research and Consulting Center at Pfizer. She has more than 20 years of experience in the pharmaceutical industry and has published over 80 papers in statistical and medical journals. Christy's professional interests include technical subjects relating to statistical theory and applications as well as the development of pharmaceutical statistics and the general statistics profession. 公卫论坛

Walter Offen, Ph.D.
Walter Offen, Ph.D., is Research Fellow at Eli Lilly and Company and has 23 years of experience in clinical trials for numerous therapeutic areas. Walter led a development team at Lilly that created an analysis system for clinical trials that was based on SAS software and is still in use today. He has been involved with Pharmaceutical Research and Manufacturers of America (PhRMA) and has participated in or led several PhRMA expert teams.

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