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Pharmaceutical Statistics: Practical and Clinical Applications, Fifth Edition: Drugs and the Pharmaceutical Sciences

Autor Sanford Bolton, Charles Bon
en Limba Engleză Hardback – 23 dec 2009
Through the use of practical examples and solutions, Pharmaceutical Statistics: Practical and Clinical Applications, Fifth Edition provides the most complete and comprehensive guide to the various statistical applications and research issues in the pharmaceutical industry, particularly in clinical trials and bioequivalence studies.
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Specificații

ISBN-13: 9781420074222
ISBN-10: 1420074229
Pagini: 674
Ilustrații: 180 b/w images
Dimensiuni: 178 x 254 x 41 mm
Greutate: 1.32 kg
Ediția:Revizuită
Editura: CRC Press
Colecția CRC Press
Seria Drugs and the Pharmaceutical Sciences

Locul publicării:Boca Raton, United States

Public țintă

Academic, Professional, and Professional Practice & Development

Cuprins

1. Basic Definitions and Concepts. 2. Data Graphics. 3. Introduction to Probability: The Binomial and Normal Probability Distributions. 4. Choosing Samples. 5. Statistical Inference: Estimation and Hypothesis. 6. Sample Size and Power. 7. Linear Regression and Correlation. 8. Analysis of Variance. 9. Factorial Designs. 10. Transformations and Outliers. 11. Experimental Design in Clinical Trials. 12. Quality Control. 13. Validation. 14. Computer-Intensive Methods. 15. Nonparametric Methods. 16. Optimization Techniques and Screening Designs.

Descriere

Through the use of practical examples and solutions, this volume examines various statistical applications and research issues in the pharmaceutical industry, particularly in clinical trials and bioequivalence studies. It covers the in vitro-in vivo correlation, and how it can be used in the drug development process. It discusses adaptive designs in clinical research, advanced statistical designs, and one- and two-sided statistical tests. It also examines interim and sequential analysis for clinical trials and bioequivalence studies, discusses assumptions and applications of nonparametric methods, and expands on the concepts of multiple and logistic regression.