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Inference Framework and Method Read chapter Read first chapter

2017 | OriginalPaper | Chapter

7. Case–Control Studies with Measurement Error or Misclassification

Author : Grace Y. Yi

Published in: Statistical Analysis with Measurement Error or Misclassification

Publisher: Springer New York

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Abstract

In epidemiological research case–control studies provide an important method to investigate factors contributing to certain medical conditions, such as disease statuses. Case–control studies are quick and cheap to conduct. They enable us to study rare health outcomes without having to follow up a large number of subjects over a long period of time. Analysis of case–control studies dates back to Broders (1920) and Lane-Claypon (1926). Various statistical analysis methods for case–control data have been developed since the landmark paper by Cornfield (1951). Those methods are, however, vulnerable to measurement error and misclassification that commonly accompany case–control studies. This chapter deals with this topic and discusses inference methods for handling error-prone data arising from case–control studies.

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previous chapter Multi-State Models with Error-Prone Data
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Metadata
Title
Case–Control Studies with Measurement Error or Misclassification
Author
Grace Y. Yi
Copyright Year
2017
Publisher
Springer New York
Book
Statistical Analysis with Measurement Error or Misclassification

Print ISBN: 978-1-4939-6638-7

Electronic ISBN: 978-1-4939-6640-0

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-1-4939-6640-0_7

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