Studying relationships between time-varying covariates and trajectories in a medium term perspective

What is it about?

Many researches are interested in the relationships between processes and time-varying covariates. Event history analysis has often been chosen for this purpose when the outcomes can be meaningfully specified as simple instantaneous events or transitions. On the other hand, sequence analysis has increasingly used in the social sciences to analyze trajectories in a holistic perspective. We propose here an original combination of these two approaches called Sequence Analysis Multistate Model (SAMM) procedure. The SAMM procedure allows studying the relationship between time-varying covariates and trajectories of categorical states that unfold over time while keeping a medium term perspective on trajectories. The added value is illustrated through an example from life-course sociology, on how 1) time-varying family status is associated with women's employment trajectories in East and West Germany, and 2) how the German reunification affected these trajectories in the two sub-societies.

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Why is it important?

Many research aims to study transitions that cannot be meaningfully considered as instantaneous and simple events, but should rather be considered as lasting transitions. Common examples include the transition to adulthood, professional integration or even leaving the parental home. However, considering lasting transition usually prevents the study of the effect of changing situations (such as macro-social or family-related changes) on these processes. We propose here a new procedure to study how “lasting” transitions are linked to time-varying conditions such as family status or macro-social changes.