Estimating the Relationship between Time-varying Covariates and Trajectories: The Sequence Analysis Multistate Model Procedure

Abstract: The relationship between processes and time-varying covariates is of central theoretical interest in addressing many social science research questions. On the one hand, event history analysis (EHA) has been the chosen method to study these kinds of relationships when the outcomes can be meaningfully specified as simple instantaneous events or transitions. On the other hand, sequence analysis (SA) has made increasing inroads into the social sciences to analyze trajectories as holistic “process outcomes.” We propose an original combination of these two approaches called the sequence analysis multistate model (SAMM) procedure. The SAMM procedure allows the study of the relationship between time-varying covariates and trajectories of categorical states specified as process outcomes that unfold over time. The SAMM is a stepwise procedure: (1) SA-related methods are used to identify ideal-typical patterns of changes within trajectories obtained by considering the sequence of states over

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch
Notes
Veröffentlichungsversion
begutachtet (peer reviewed)
In: Sociological Methodology ; 48 (2018) 1 ; 103-135

Classification
Wirtschaft

Event
Veröffentlichung
(where)
Mannheim
(who)
SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.
(when)
2018
Creator
Studer, Matthias
Fasang, Anette E.
Struffolino, Emanuela

DOI
10.1177/0081175017747122
URN
urn:nbn:de:101:1-2021100709172855885503
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:21 AM CEST

Data provider

This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.

Associated

  • Studer, Matthias
  • Fasang, Anette E.
  • Struffolino, Emanuela
  • SSOAR, GESIS – Leibniz-Institut für Sozialwissenschaften e.V.

Time of origin

  • 2018

Other Objects (12)