Self-Controlled Case Series Studies
A Modelling Guide with R
Language
EnglishAbstract
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.
Keywords
Relative Incidence;SCCS Method;case-control studies;SCCS;cohort studies;Risk Period;epidemiology;Time Invariant Covariates;exposure;MMR Vaccine;vaccinations;MMR Vaccination;drug reactions;Monte Carlo Standard Error;Heather Whitaker;Time Invariant Confounders;Yonas Ghebremichael Weldeselassie;Non-homogeneous Poisson Process;Case Crossover Method;Primary Time Line;Smoothing Parameter;Asymptotic Relative Efficiency;Hib Vaccine;Hexavalent Vaccines;Spline Model;Sample Size Formula;Data SetsDOI
10.1201/9780429491313ISBN
9781032095530, 9780429957512, 9780429957529, 9780429491313, 9781498781596, 9780429957536Publisher
Taylor & FrancisPublisher website
https://taylorandfrancis.com/Publication date and place
2018Grantor
Imprint
Chapman and Hall/CRCSeries
Chapman & Hall/CRC Biostatistics Series,Classification
Biology, life sciences
Probability and statistics
Epidemiology and Medical statistics