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Jozef Nauta
Statistics in Clinical Vaccine Trials
2011. 2014. xviii, 153 S. 9 Tabellen. 235 mm
Verlag/Jahr: SPRINGER, BERLIN; SPRINGER BERLIN HEIDELBERG 2014
ISBN: 3-642-44191-2 (3642441912)
Neue ISBN: 978-3-642-44191-2 (9783642441912)
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This book offers training and expertise on the statistical analysis of data from clinical vaccine trials, i.e., immunogenicity and vaccine field efficacy studies. With many worked-out real-life examples, its scope is more practical than theoretical.
This monograph offers well-founded training and expertise on the statistical analysis of data from clinical vaccine trials, i.e., immunogenicity and vaccine field efficacy studies. The book´s scope is practical rather than theoretical. It opens with two introductory chapters on the immunology of vaccines to provide readers with the necessary background knowledge. It then continues with an in-depth exploration of the statistical methodology. Many real-life examples and SAS codes are presented, making application of the methods straightforward. Topics discussed include maximum likelihood estimation for censored antibody titers, ANCOVA for antibody values, analysis of equivalence and non-inferiority immunogenicity trial data, analysis of data from vaccine field efficacy trials (including data from studies with recurrent infection data), fitting protection curves to data of challenge or field efficacy studies, and the analysis of vaccine safety data.
Basic Concepts of Vaccine Immunology.- Humoral and Cellular Immunity.- Standard Statistical Methods for the Analysis of Immunogenicity Data.- Antibody Titres and Two Types of Bias.- Adjusting for Imbalance in Pre-vaccination State.- Vaccine Equivalence and Non-Inferiority Immunogenicity Trials.- Vaccine Field Efficacy Trials.- Correlates of Protection.- Safety of Vaccines.- Appendices: SAS and Floating Point Format for Calculated Variables.- Closed-Form Solutions for the Constrained ML Estimators Ro.- Simulation Results on Jewell´s Correction for the Rate Ratio.- Proof of Inequality.- A Generalized Worst-Case Sensitivity Analysis for a Single
Seroresponse Rate for Which the Confidence Interval Must Fall Above a Pre-Specified Bound.
From the book reviews:
"The presentation of the book is lucid. The author is to be congratulated for mixing his vast practical experience with his knowledge to make this book readable and practically valuable." (Subir Ghosh, Technometrics, Vol. 55 (3), August, 2013)