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

May 13, 2010

Brendan Halpin: Optimal Matching Analysis and Life-Course Data: The Importance of Duration, Sociological Methods Research 2010 38: 365-388.

Brendan HalpinThe 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 Read the rest of this entry »

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New Life for Old Ideas: The ‘‘Second Wave’’ of Sequence Analysis Bringing the ‘‘Course’’ Back Into the Life Course

May 13, 2010

Silke Aisenbrey and Anette E. Fasang: New Life for Old Ideas: The ‘‘Second Wave’’ of Sequence Analysis Bringing the ‘‘Course’’ Back Into the Life Course, Sociological Methods Research 2010 38: 420-462.

Silke AisenbreyAnette E. FasangIn this article the authors draw attention to the most recent and promising developments of sequence analysis. Read the rest of this entry »


John Mirowsky and Jinyoung Kim Graphing Age Trajectories: Vector Graphs, Synthetic and Virtual Cohort Projections, and Virtual Cohort Projections, and Cross-Sectional Profiles of Depression Sociological Methods & Research 2007 35: 497-541.

February 7, 2010

Surveys often sample adults across a broad range of ages, measuring the same outcomes in several interviews spaced during a period of years and comparing the changes observed across segments of the adult life course. Put in sequence, those change vectors provide a composite image of the outcome’s life course trajectory. To illustrate, the authors estimate depression vectors in a sample of U.S. adults ages 18 and older at baseline in 1995, with follow-up interviews in 1998 and 2001. They show the vector equations and their graphs and also their synthetic-cohort projection. The authors introduce the trend-function and virtual-cohort projection, showing how they provide tests of “convergence” and other hypotheses about trajectories and trends. Results show depression dropping and then rising across adulthood more steeply than suggested by cross-sectional differences among age groups. They also indicate a rise and fall in age-specific levels of depression across cohorts.

Key Words: depression • life course • latent growth models • age-period-cohort