Alex Dmitrienko
Founder and President of Mediana Inc.
Alex Dmitrienko, PhD, is Founder and President of Mediana Inc. He is actively involved in biostatistical research with an emphasis on multiplicity issues in clinical trials, subgroup analysis, innovative trial designs, and clinical trial optimization. Dr. Dmitrienko coauthored the first edition of Analysis of Clinical Trials Using SAS®: A Practical Guide, and he coedited Pharmaceutical Statistics Using SAS®: A Practical Guide.
By This Author
Analysis of Clinical Trials Using SAS®: A Practical Guide, Second Edition
Edited by Alex Dmitrienko and Gary G. Koch
Analyze your clinical trial data with ease. This book bridges 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.
*Our books are also available in print and e-book formats
from your local bookstore or favorite online bookseller.
Pharmaceutical Statistics Using SAS®: A Practical Guide
Edited by Alex Dmitrienko, Christy Chuang-Stein, and Ralph B. D'Agostino
Introduces a range of data analysis problems encountered in drug development and illustrates them using case studies from actual pre-clinical experiments and clinical studies. Includes a discussion of methodological issues, practical advice from subject matter experts, and review of relevant regulatory guidelines.
*Our books are also available in print and e-book formats
from your local bookstore or favorite online bookseller.
Analysis of Clinical Trials Using SAS®: A Practical Guide
By Alex Dmitrienko, Geert Molenberghs, Christy Chuang-Stein, and Walter Offen
This comprehensive guide bridges the gap between statistical methodology and real-world clinical trial applications. Topics reflect the International Conference on Harmonization (ICH) guidelines for the pharmaceutical industry and address important statistical problems encountered in clinical trials.