Brendan Halpin: Optimal Matching Analysis and Life-Course Data: The Importance of Duration, Sociological Methods Research 2010 38: 365-388.
The optimal matching (OM) algorithm is widely used for sequence analysis insociology. It has a natural interpretation for discrete-time sequences but isalso widely used for life-history data, which are continuous in time. Life history data are arguably better dealt with in terms of episodes rather than as strings of time-unit observations, and in this article, the authorexamines whether the OM algorithm is unsuitable for such sequences. Amodified version of the algorithm is proposed, weighting OM’s elementaryoperations inversely with episode length. In the general case, the modifiedalgorithm produces pairwise distances much lower than the standard algorithm,the more the sequences are composed of long spells in the samestate. However, where all the sequences in a data set consist of few longspells, and there is low variability in the number of spells, the modified algorithmgenerates an overall pattern of distances that is not very differentfrom standard OM.
Keywords: life-course, sequence analysis, optimal matching