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Self-Controlled Case Series Studies : A Modelling Guide with R

By: (Author) Heather Whitaker , (Author) Paddy Farrington , (Author) Yonas Ghebremichael Weldeselassie

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Ksh 18,900.00

Format: Hardback or Cased Book

ISBN-10: 1498781594

ISBN-13: 9781498781596

Series: Chapman & Hall/CRC Biostatistics Series

Publisher: Taylor & Francis Inc

Imprint: Chapman & Hall/CRC

Country of Manufacture: US

Country of Publication: GB

Publication Date: May 2nd, 2018

Print length: 362 Pages

Weight: 696 grams

Dimensions (height x width x thickness): 24.10 x 16.80 x 2.50 cms

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This book provides the first comprehensive account of the self-controlled case series (SCCS) method, a statistical method for investigating associations between outcome events and time-varying exposures.

Self-Controlled Case Series Studies: A Modelling Guide with R provides the first comprehensive account of the self-controlled case series (SCCS) method, a statistical technique for investigating associations between outcome events and time-varying exposures. The method only requires information from individuals who have experienced the event of interest, and automatically controls for multiplicative time-invariant confounders, even when these are unmeasured or unknown. It is increasingly being used in epidemiology, most frequently to study the safety of vaccines and pharmaceutical drugs.

Key features of the book include:

  • A thorough yet accessible description of the SCCS method, with mathematical details provided in separate starred sections.
  • Comprehensive discussion of assumptions and how they may be verified.
  • A detailed account of different SCCS models, extensions of the SCCS method, and the design of SCCS studies.
  • Extensive practical illustrations and worked examples from epidemiology.
  • Full computer code from the associated R package SCCS, which includes all the data sets used in the book.

The book is aimed at a broad range of readers, including epidemiologists and medical statisticians who wish to use the SCCS method, and also researchers with an interest in statistical methodology. The three authors have been closely involved with the inception, development, popularisation and programming of the SCCS method.


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