방법 비교

	Optimal Matching Analysis	Sequence Analysis
분야	Sociology	Sociology
계열	Process / pipeline	Process / pipeline
기원 연도	1970 (algorithm); 1980s (sociology)	1980s–2000 (sociological consolidation)
창시자	Needleman & Wunsch (algorithm); Andrew Abbott (sociological use)	Andrew Abbott (introduced to sociology)
유형	Edit-distance dissimilarity between categorical sequences	Holistic analysis of categorical state sequences over time
원전	Abbott, A., & Tsay, A. (2000). Sequence analysis and optimal matching methods in sociology: review and prospect. Sociological Methods & Research, 29(1), 3–33.	Abbott, A., & Tsay, A. (2000). Sequence analysis and optimal matching methods in sociology: review and prospect. Sociological Methods & Research, 29(1), 3–33.
별칭	optimal matching, OMA, edit-distance sequence comparison, Levenshtein sequence distance	social sequence analysis, life-course sequence analysis, categorical sequence analysis, trajectory analysis
관련	5	5
요약	Optimal matching analysis measures how dissimilar two categorical sequences are by computing the minimum total cost of editing one sequence into the other through substitution and insertion/deletion operations. Borrowed from computer science and molecular biology and introduced to sociology by Andrew Abbott, it supplies the pairwise distances that underpin sequence analysis of careers, family histories, and other life-course trajectories.	Sequence analysis is a holistic method for studying ordered categorical trajectories — such as month-by-month employment states, family life-course events, or daily activity patterns — by treating each individual's whole sequence as a unit, measuring how dissimilar pairs of sequences are, and grouping them into a typology of characteristic pathways. Introduced to sociology by Andrew Abbott, it shifts attention from isolated transitions to the shape of entire life courses.