Exposure-response modeling

Exposure-response modeling: methods and practical implementation

by Wang, Jixian

Type Book
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Discover the Latest Statistical Approaches for Modeling Exposure-Response RelationshipsWritten by an applied statistician with extensive practical experience in drug development, Exposure-Response Modeling: Methods and Practical Implementation explores a wide range of topics in exposure-response modeling, from traditional pharmacokinetic-pharmacodynamic (PKPD) modeling to other areas in drug development and beyond. It incorporates numerous examples and software programs for implementing novel m…

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Title Statements

  • Full title :Exposure-response modeling : methods and practical implementation / Jixian Wang.

Summary

Discover the Latest Statistical Approaches for Modeling Exposure-Response RelationshipsWritten by an applied statistician with extensive practical experience in drug development, Exposure-Response Modeling: Methods and Practical Implementation explores a wide range of topics in exposure-response modeling, from traditional pharmacokinetic-pharmacodynamic (PKPD) modeling to other areas in drug development and beyond. It incorporates numerous examples and software programs for implementing novel methods.The book describes using measurement error models to treat sequential modeling, fitting models.

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Edition Statements

  • Publication Date:©2016

Publication Statements

  • Publisher(s):CRC Press
  • Place of Publication:Boca Raton, Florida
  • Language:eng
  • Publication Date:©2016

Notes

"A Chapman & Hall book."

The Physical Object

  • Description:1 online resource (348 pages) : : illustrations.

Edition Identifiers

  • ISBN:9781466573215, 146657321X
  • oclc:ocn988463863
  • LC Classification:RC489.C63
  • Dewey Decimal:615.8

Table of Contents

1. Introduction -- 2. Basic exposure and exposure-response models -- 3. Dose-exposure and exposure-response models for longitudinal data -- 4. Sequential and simultaneous exposure-response modeling -- 5. Exposure-risk modeling for time-to-event data -- 6. Modeling dynamic exposure-response relationships -- 7. Bayesian modeling and model-based decision analysis -- 8. Confounding bias and causal inference in exposure-response modeling -- 9. Dose-response relationship, dose determination, and adjustment -- 10. Implementation using software.

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Subjects

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