Using Sequence Analysis to Quantify How Strongly Life Courses Are Linked

Dyadic or, more generally, polyadic life course sequences can be associated within dyads or polyads than between randomly assigned dyadic/polyadic member sequences, a phenomenon reflecting the principle of linked lives. In this article, I propose method U and V measures for quantifying assessing trajectories in sequence data. Specifically, compare distance members an observed dyad/polyad against set generated dyads/polyads. TheU measure quantifies how much greater, terms given measure, resemble one another do dyads/polyads, degree lives dyads/polyads outperform randomized present simulation study, empirical study analyzing dyadic family formation data from Longitudinal Study Generations, random seed sensitivity analysis online supplement. Through these analyses, demonstrate versatility usefulness proposed with The has broad applicability to course, business organizational, social network research.