At-risk-measure sampling in case-control studies with aggregated data
Secondary sources of mobile-device data (e.g., as collected by commercial smartphone apps) can measure transient exposure with high accuracy and low researcher burden but present some challenges. First, these data commonly only sample the target population, so a case-control design may be useful. Second, data are often aggregated by location to preserve anonymity of users.
In this seminar, the speaker will discuss his paper, “At-risk-measure sampling in case-control studies with aggregated data”, which describes a method for using these types of data to estimate the incidence rate ratio from a hypothetical cohort study. Unlike incidence density sampling, a similar method, the described method directly samples the measure of the at-risk experience, such as person-distance travelled in studies of transportation risk.
Michael D. Garber, PhD MPH, Postdoctoral Researcher, Rojas Public Health Lab, Colorado State University