Abstract:
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Both patients and clinicians want to understand what treatments work best when making complicated health-related decisions. The decisions may be supported by findings from randomized trials or, when these are not available, by the findings from observational data analyses that explicitly emulate a hypothetical randomized trial: the target trial. Funded by PCORI, we designed and developed CERBOT (Comparative Effectiveness Research Based on Observational data to Emulate a Target Trial), freely available at www.cerbot.org. It is a web-based tool that provides a structured standardized algorithm to define and emulate a target trial. Using the 5 modules - eligibility, outcomes, follow-up, treatment strategies, and causal contrast of interest, CERBOT synthesizes the information entered by the users and provides specific recommendations for causal inference analytical methods based on each user's individual research question. This talk will also discuss how to use CERBOT as a complement to many other causal inference introductory tools and/or educational materials that now exist, for use in observational data to assess causality better and, allow for less biased estimates of effect.
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