Related Experiment Video
Updated: May 11, 2026

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups
Published on: May 13, 2022
A simulation study to compare three self-controlled case series approaches: correction for violation of assumption
Wei Hua1, Guoying Sun, Caitlin N Dodd
1Office of Biostatistics and Epidemiology, Center for Biologics Evaluation and Research, Food and Drug Administration, Rockville, MD 20852, USA. wei.hua@fda.hhs.gov
Purpose:
The assumption that the occurrence of outcome event must not alter subsequent exposure probability is critical for preserving the validity of the self-controlled case series (SCCS) method. This assumption is violated in scenarios in which the event constitutes a contraindication for exposure. In this simulation study, we compared the performance of the standard SCCS approach and two alternative approaches when the event-independent exposure assumption was violated.
Methods:
Using the 2009 H1N1 and seasonal influenza vaccines and Guillain-Barré syndrome as a model, we simulated a scenario in which an individual may encounter multiple unordered exposures and each exposure may be contraindicated by the occurrence of outcome event. The degree of contraindication was varied at 0%, 50%, and 100%. The first alternative approach used only cases occurring after exposure with follow-up time starting from exposure. The second used a pseudo-likelihood method.
Results:
When the event-independent exposure assumption was satisfied, the standard SCCS approach produced nearly unbiased relative incidence estimates. When this assumption was partially or completely violated, two alternative SCCS approaches could be used. While the post-exposure cases only approach could handle only one exposure, the pseudo-likelihood approach was able to correct bias for both exposures.
Conclusions:
Violation of the event-independent exposure assumption leads to an overestimation of relative incidence which could be corrected by alternative SCCS approaches. In multiple exposure situations, the pseudo-likelihood approach is optimal; the post-exposure cases only approach is limited in handling a second exposure and may introduce additional bias, thus should be used with caution.
Related Concept Videos
Bias
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Bias in Epidemiological Studies
Comparing the Survival Analysis of Two or More Groups
Strategies for Assessing and Addressing Confounding
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Assumptions of Survival Analysis
