Modeling Strategies for Observational Comparative Effectiveness Research: What Works Best When? [Methods Study], 2013-2018

Comparative effectiveness research compares two or more treatments to see which one works better for which patients. In some studies, researchers assign patients by chance to several treatments or to have or not have a treatment. But approaches that assign patients by chance are not always suitable. For example, assigning patients to a new treatment may not be good medical care.
For this reason, researchers sometimes do studies using data collected when patients and their doctors choose the treatments. Data from such studies are observational data. When using observational data for research, it can be hard to know if the effect of a treatment is because of the treatment or other factors, such as patients' age or health history. In these cases, researchers use statistical methods to understand the effect of the treatment. Depending on the study's focus and design, some methods work better than others.
In this study, the research team developed guidance for researchers to help them choose methods for their study.
To access the methods and software, please visit the DECODE CER Tool website.