Cai, Kaida (2015) The self-controlled case series design: a simulation study. Masters thesis, Memorial University of Newfoundland.
- Accepted Version
Available under License - The author retains copyright ownership and moral rights in this thesis. Neither the thesis nor substantial extracts from it may be printed or otherwise reproduced without the author's permission.
The self-controlled case series (SCCS) design is an outcome dependent sampling design developed to investigate the association between time-varying exposures and outcome events. This design automatically adjusts for all fixed covariates acting multiplicatively on the intensity function of a subject. It is based only on cases, and ignores controls. Since only cases are included, it is economically and computationally efficient compared with a cohort design. This property of the SCCS design also helps protecting data privacy. Because of these reasons, the SCCS design is an important alternative to the cohort design especially when the outcome of interest is a rare event, and has been used in many studies in medicine, epidemiology and pharmacoepidemiology. Therefore, the main objective of this thesis is to investigate the SCCS design through simulations. We considered parametric, semiparametric and weakly parametric SCCS models, and compared them with well-known models based on the classical cohort design. We also illustarted the methods with a real life data set from medicine.
|Item Type:||Thesis (Masters)|
|Additional Information:||Includes bibliographical references (pages 78-89).|
|Keywords:||Self-Controlled Case Series Design, Case Cohort Design, Piecewise-Constant Rate Function, Recurrent Events, Simulation Study|
|Department(s):||Science, Faculty of > Mathematics and Statistics|
|Library of Congress Subject Heading:||Estimation theory; Case-control method; Poisson processes; Cohort analysis|
Actions (login required)