Situational Choice Experiments in Healthcare

Join Keith Chrzan, VP of Analytics at Sawtooth Software, for a 45-minute free webinar as he discusses how a Situational Choice Experiment works. While in conjoint analysis we model choices as a function of the attributes and levels that describe the products, in a Situational Choice Experiment we model choices as a function of attributes of the chooser or the situation. For example, which of the several available treatments would a physician prescribe if a patient had symptoms X and Y? How about if the patient is 35 years old, 60 or 85, male or female? While the products themselves don't change from one choice set to the next, the patient description does. Another example might be modeling workers' retirement timing decisions as a function of their financial situation and an experimentally designed set of macroeconomic conditions - the choice alternatives (retire, go down to part time, keep working full time) aren't varying, but the conditions that influence choice are. The tool that helps researchers answer that question is a Situational Choice Experiment (SCE), which is a not-so-distant cousin of the conjoint analysis. Keith will explain how SCEs differ from conjoint experiments, plus how to design and analyze a SCE study. A must-attend for anyone looking to learn new skills and capabilities.