Abstract:Passively-generated location data have the potential to augment mobility and transportation research, as demonstrated by a decade of research. A common trait of these data is a high proportion of missingness. Naïve handling, including list-wise deletion of subjects or days, or linear interpolation across time gaps, has the potential to bias summary results. On the other hand, it is unfeasible to collect mobility data at frequencies high enough to reflect all possible movements. In this paper, we describe the r… Show more
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