Optimal Matching Analysis and Life-Course Data: The Importance of Duration

Abstract

The optimal matching (OM) algorithm is widely used for sequence analysis in sociology. It has a natural interpretation for discrete-time sequences but is also 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 author examines whether the OM algorithm is unsuitable for such sequences. A modified version of the algorithm is proposed, weighting 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.

Using occupational history calendars to capture lengthy and complex working lives: a mixed method approach with older people

“…This method has been criticised because of concerns about how researchers determine the substitution and indel costs that are used to calculate the dissimilarity matrix (Halpin, 2003(Halpin, , 2010Piccarreta, 2012). Ideally these costs should be determined by theory but this is not usually practical (Davia & Legazpe, 2014).…”

Spell Sequences, State Proximities, and Distance Metrics

“…If 0 < a < 1, then longer spells will weight comparatively less. Halpin (2010) has argued that this is an interesting feature. Finally, if a > 1, then small spells will be less important in sequences comparison.…”

“…Largely motivated by the problems of determining the weight or cost of the edit operations involved, many variants of the metric have been proposed, some quite general (e.g., Gauthier et al 2009;Halpin 2010;Moen 2000), others more application-specific like in, for example, Lesnard (2008). For a comprehensive overview of OM variants, the reader is referred to Studer (2012).…”

Partnership formation and dissolution over the life course: applying sequence analysis and event history analysis in the study of recurrent events

“…The latter way is automatic and has been said to reduce subjectivity (Aisenbrey & Fasang, 2010;Gauthier, Widmer, Bucher, & Notredame, 2009 ongoing debate and many modifications to the basic options have been suggested (e.g. Aisenbrey & Fasang, 2010;Gauthier et al, 2009;Halpin, 2010;Hollister, 2009;Lesnard, 2010). We set costs that would lead to clusters that separate histories of stable and unstable partnerships from those with long periods of living single or divorced/separated.…”