Tutorial in biostatistics: the self-controlled case series method.
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.
Whitaker
Heather J
HJ
Department of Statistics, The Open University, Milton Keynes, MK7 6AA, UK. h.j.whitaker@open.ac.uk
Farrington
C Paddy
CP
Spiessens
Bart
B
Musonda
Patrick
P
D001699:Biometry / Q000379:methods*; D002675:Child, Preschool; D003627:Data Interpretation, Statistical; D006801:Humans; D007223:Infant; D007443:Intussusception / Q000209:etiology; D022542:Measles-Mumps-Rubella Vaccine / Q000009:adverse effects; D008587:Meningitis, Viral / Q000209:etiology; D008954:Models, Biological; D015233:Models, Statistical; D011055:Poliovirus Vaccine, Oral / Q000009:adverse effects; D011696:Purpura, Thrombocytopenic / Q000209:etiology; D012306:Risk; D014611:Vaccination / Q000009:adverse effects
D022542:Measles-Mumps-Rubella Vaccine; D011055:Poliovirus Vaccine, Oral