Beschreibung
Large format paperback, ix + 444 pages, NOT ex-library. Weight over 1.3kg. Light wear only, faint handling marks on outer page edges. Interior is clean and bright with unmarked text, free of inscriptions and stamps, firmly bound. Uncreased spine. -- This comprehensive guide revolutionizes the application of statistical methodologies in pharmaceutical drug development, bridging the chasm between cutting-edge biostatistical theory and industry practices. Authored by renowned experts in the field, Pharmaceutical Statistics Using SAS delivers a practical, case-study-driven approach to navigating the labyrinthine world of drug discovery, preclinical trials, and clinical studies. Spanning 14 chapters, the book demystifies complex statistical techniques - from modern classification methods in drug discovery and optimal experimental design to survival analysis in clinical trials - through real-world examples, step-by-step SAS implementations, and regulatory insights. Unlike theoretical texts, this volume empowers practitioners - biostatisticians, pharmacologists, regulatory scientists - with actionable tools to tackle pressing challenges: validating analytical methods, assessing dose-response trends, handling missing data, and applying decision theory for Go/No-Go decisions. By harmonizing innovative statistical frameworks with industry-grade SAS coding, the authors democratize advanced analytics, enabling even novice statisticians to confidently drive drug development processes. This is not merely a textbook; it's a survival kit for today's data-driven pharmaceutical landscape, ensuring faster discoveries, safer therapies, and smarter regulatory strategies. Whether you're a seasoned biostatistician or an aspiring drug developer, this book transforms statistical theory into tangible solutions for real-world drug development bottlenecks.
Bestandsnummer des Verkäufers 011985
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