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Autoren Helske, Satu; Helske, Jouni; Eerola, Mervi  
Titel Combining sequence analysis and hidden Markov Models in the analysis of complex life sequence data.  
URL https://doi.org/10.1007/978-3-319-95420-2_11  
Sammelwerk Ritschard, Gilbert (Hrsg.); Studer, Matthias (Hrsg.): Sequence analysis and related approaches. Innovative methods and applications. 1. Aufl.  
ISBN 978-3-319-95419-6; 978-3-319-95420-2  
Dokumenttyp Sammelwerksbeitrag; online; gedruckt  
Beigaben Literaturangaben; Abbildungen; Tabellen  
Sprache englisch  
Forschungsschwerpunkt Bildungspanel (NEPS)  
Schlagwörter Datenerhebung; Markowscher Prozess; Analyse; Daten; Sequenz; NEPS (National Educational Panel Study)  
Abstract Life course data often consists of multiple parallel sequences, one for each life domain of interest. Multichannel sequence analysis has been used for computing pairwise dissimilarities and finding clusters in this type of multichannel (or multidimensional) sequence data. Describing and visualizing such data is, however, often challenging. We propose an approach for compressing, interpreting, and visualizing the information within multichannel sequences by finding (1) groups of similar trajectories and (2) similar phases within trajectories belonging to the same group. For these tasks we combine multichannel sequence analysis and hidden Markov modelling. We illustrate this approach with an empirical application to life course data but the proposed approach can be useful in various longitudinal problems. (Orig.).  
Förderkennzeichen 01GJ0888