Journal of Data Science

Abstract: The creation of data sets using observational methods for the lag-sequential study of behavior requires selection of a recording time unit. This is an important issue, because standard methods such as momentary sampling and partial-interval sampling, for instance, consistently underestimate the frequency of some behaviors. This leads to inaccurate estimation of both unconditional and conditional probabilities of the different behaviors, the basic descriptive and analytic tools of sequential analysis methodology. The purpose of this paper is to investigate the creation of data sets usable for the purpose of sequential analysis. We show that such data vary depending on the time resolution and that inaccurate choices lead to biased estimations of transition probabilities.