Advances in Data Management pp 155-175
Converting between Various Sequence Representations
This chapter is concerned with the organization of categorical sequence data. We first build a typology of sequences distinguishing for example between chronological sequences and sequences without time content. This permits to identify the kind of information that the data organization should preserve. Focusing then mainly on chronological sequences, we discuss the advantages and limits of different ways of representing time stamped event and state sequence data and present solutions for automatically converting between various formats, e.g., between horizontal and vertical presentations but also from state sequences into event sequences and reciprocally. Special attention is also drawn to the handling of missing values in these conversion processes.
KeywordsSequence data organization State sequence Event sequence Transition Converting between sequence formats
Unable to display preview. Download preview PDF.
- 2.Blossfeld, H.P., Golsch, K., Rohwer, G.: Event History Analysis with Stata. Lawrence Erlbaum, Mahwah (2007)Google Scholar
- 4.Gabadinho, A., Ritschard, G., Studer, M., Müller, N.S.: Mining sequence data in R with TraMineR: A user’s guide for version 1.1. Technical report, Department of Econometrics and Laboratory of Demography, University of Geneva, Geneva (2009), http://mephisto.unige.ch/traminer
- 5.Gauthier, J.A., Widmer, E.D., Bucher, P., Notredame, C.: Multichannel sequence analysis applied to social science data, University of Lausanne (2007) (manuscript) (under review)Google Scholar
- 7.Karweit, N., Kertzer, D.: Data organization and conceptualization. In: Giele, J.Z., Elder, G.H. (eds.) Methods of Life Course Research: Qualitative and Quantitative Approaches, pp. 81–97. Sage, Thousand Oaks (1998)Google Scholar
- 9.Ritschard, G., Oris, M.: Life course data in demography and social sciences: Statistical and data mining approaches. In: Levy, R., Ghisletta, P., Le Goff, J.M., Spini, D., Widmer, E. (eds.) Towards an Interdisciplinary Perspective on the Life Course, Advances in Life Course Research, vol. 10, pp. 289–320. Elsevier, Amsterdam (2005)Google Scholar
- 10.Yamaguchi, K.: Event history analysis. In: ASRM 28. Sage, Newbury Park (1991)Google Scholar