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.
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.

Self-Controlled Case Series Studies: A Modelling Guide with R
376
Self-Controlled Case Series Studies: A Modelling Guide with R
376Product Details
ISBN-13: | 9781498781596 |
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Publisher: | Taylor & Francis |
Publication date: | 05/02/2018 |
Series: | Chapman & Hall/CRC Biostatistics Series |
Pages: | 376 |
Product dimensions: | 6.12(w) x 9.19(h) x (d) |