Self-Controlled Case Series Studies: A Modelling Guide with R (Chapman & Hall/CRC Biostatistics Series)

Name: Self-Controlled Case Series Studies: A Modelling Guide with R (Chapman & Hall/CRC Biostatistics Series)
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Book Synopsis: 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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Unlock the power of self-controlled case series studies with our comprehensive guide, "Self-Controlled Case Series Studies: A Modelling Guide with R." This book offers a unique approach to investigating associations between outcome events and time-varying exposures, making it an essential resource for epidemiologists, medical statisticians, and researchers interested in statistical methodology.

Discover the simplicity and effectiveness of the SCCS method, which only requires data from individuals who have experienced the event of interest. With automatic control for multiplicative time-invariant confounders, even when they are unmeasured or unknown, this technique is revolutionizing the field of epidemiology. Stay ahead of the curve and harness the power of SCCS studies to examine the safety of vaccines and pharmaceutical drugs.

With a clear and accessible description of the SCCS method, detailed mathematical explanations, practical illustrations, and R code examples, this book provides everything you need to master SCCS modeling. Whether you are a seasoned epidemiologist or a researcher looking to expand your statistical toolkit, "Self-Controlled Case Series Studies: A Modelling Guide with R" is your ultimate guide to unlocking new insights in your research.

Get your copy now and take your epidemiological research to the next level with the definitive guide to the SCCS method!

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