Optimal matching analysis and life course data: the importance of duration

The Optimal Matching Algorithm is widely used for sequenace analysis in sociology. It has a natural interpretation for discrete-time sequences, but is also widely used for life history data, which is continuous in time. Life history data is arguably better dealt with in terms of episodes rather than as a string of time-unit observations, and the paper addresses the question of whether standard the OM algorithm is unsuitable for such sequences. A modified version of the algorithm is proposed, which weights OM’s elementary operations inversely with episode length. In the general case, the modified algorithm produces pairwise distances much lower than the standard algorithm, the more the sequences are composed of long spells in the same state. However, where all the sequences in a data set consist of few long spells, and there is low variability in the number of spells, the modified algorithm generates an overall pattern of distances that is not very different from standard OM.