Tutorial in biostatistics: the self‐controlled case series method

TLDR

The self‑controlled case series method was developed to assess associations between acute outcomes and transient exposures using only case data, with inference within individuals that implicitly controls for fixed covariates. We describe the origins, assumptions, limitations, and uses of the method. The authors explain the model’s rationale and likelihood derivation, illustrate it with a vaccine‑safety example, provide STATA code, and demonstrate extensions using additional vaccine‑safety datasets and design pointers. The data sets, STATA code, and further implementation details in SAS, GENSTAT and GLIM are available from an associated website. © 2005 John Wiley & Sons, Ltd.

Abstract

Abstract The self‐controlled case series method was developed to investigate associations between acute outcomes and transient exposures, using only data on cases, that is, on individuals who have experienced the outcome of interest. Inference is within individuals, and hence fixed covariates effects are implicitly controlled for within a proportional incidence framework. We describe the origins, assumptions, limitations, and uses of the method. The rationale for the model and the derivation of the likelihood are explained in detail using a worked example on vaccine safety. Code for fitting the model in the statistical package STATA is described. Two further vaccine safety data sets are used to illustrate a range of modelling issues and extensions of the basic model. Some brief pointers on the design of case series studies are provided. The data sets, STATA code, and further implementation details in SAS, GENSTAT and GLIM are available from an associated website. Copyright © 2005 John Wiley & Sons, Ltd.