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02997nam a22003975i 4500 |
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978-3-642-14691-6 |
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20141002022631.0 |
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101013s2011 gw | s |||| 0|eng d |
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|a 9783642146916
|9 978-3-642-14691-6
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|a 10.1007/978-3-642-14691-6
|2 doi
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|a QA276-280
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|a MAT029000
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|a 519.5
|2 23
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|a Nauta, Jozef.
|e author.
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|a Statistics in Clinical Vaccine Trials
|h [electronic resource] /
|c by Jozef Nauta.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2011.
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|a XVIII, 153 p.
|b online resource.
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|a text
|b txt
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|a computer
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|a text file
|b PDF
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|a 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.
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|a 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.
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|a Statistics.
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|a Statistics.
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|a Statistics, general.
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710 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783642146909
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|u http://dx.doi.org/10.1007/978-3-642-14691-6
|z Full Text via HEAL-Link
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|a ZDB-2-SMA
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|a Mathematics and Statistics (Springer-11649)
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