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Gilbert Ritschard · Matthias Studer Editors Innovative Methods and Applications Life Course Research and Social Policies 10 Gilbert Ritschard · Matthias Studer Editors Sequence Analysis and Related Approaches Innovative Methods and Applications Life Course Research and Social Policies Volume 10 Series editors Laura Bernardi Dario Spini Jean-Michel Bonvin Life course research has been developing quickly these last decades for good reasons. Life course approaches focus on essential questions about individuals’ trajectories, longitudinal analyses, cross-fertilization across disciplines like life-span psychology, developmental social psychology, sociology of the life course, social demography, socio-economics, social history. Life course is also at the crossroads of several fields of specialization like family and social relationships, migration, education, professional training and employment, and health. This Series invites academic scholars to present theoretical, methodological, and empirical advances in the analysis of the life course, and to elaborate on possible implications for society and social policies applications. More information about this series at http://www.springer.com/series/10158 Gilbert Ritschard • Matthias Studer Editors Sequence Analysis and Related Approaches Innovative Methods and Applications Editors Gilbert Ritschard Matthias Studer NCCR LIVES and Geneva School NCCR LIVES and Geneva School of Social Sciences of Social Sciences University of Geneva University of Geneva Geneva, Switzerland Geneva, Switzerland ISSN 2211-7776 ISSN 2211-7784 (electronic) Life Course Research and Social Policies ISBN 978-3-319-95419-6 ISBN 978-3-319-95420-2 (eBook) https://doi.org/10.1007/978-3-319-95420-2 Library of Congress Control Number: 2018957117 © The Editor(s) (if applicable) and The Author(s) 2018, corrected publication 2018. This book is an open access publication Open Access This book is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this book are included in the book’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the book’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Preface This volume provides innovative methods and applications of sequence analysis (SA) to life course and time use data with a focus on the relationship between SA and other methods for longitudinal data. It originated in the International Conference on Sequence Analysis and Related Methods (LaCOSA II) held in Lausanne, 8–10 June, 2016. The 15 articles that, together with the introduction chapter, constitute the book were selected among 25 propositions received in response to a call for papers addressed to the participants and members of the scientific committee of the Conference. The selection was conducted through peer reviewing with each paper being evaluated by at least three reviewers. How to Read the Book The chapters are self-contained and each one can be picked-up independently of the others. They are not ordered by difficulty level but have been organized so as to optimize the topical and methodological consistency in the succession of the chapters. The retained storyline is based on the kind of SA involved and on how SA relates to other methods for longitudinal analysis. There are six parts each with two or three chapters. In order to guide the reader in selecting the chapters, Table 1 below characterizes their nature by means of a series of attributes. The column “SA type” gives an idea of the kind of knowledge involved. In addition, the reader will find useful information for her/his choices in the introductory chapter that summarizes the development of SA to date, enshrines the editors’ view on the future of SA, explains the storyline of the book, and gives a short overview of what you find in each chapter. The chapters in Part I by Courgeau and by Eerola that overview different approaches for longitudinal analysis and their relationship with SA are the most general. They probably also are the most difficult papers because of the number of v vi Preface Table 1 Characteristics of the chapters Classic Primary Innovative Original method Mathematical Chapter SA typea SA applied method combination level Ritschard, Studer overview Courgeau overview Eerola D,other x ++ Malin, Wise G, S x Lundevaller et al. D,S x x Rossignon et al. D,S x x x x Cornwell N,I,G + Hamberger N,G x x + Collas D,G x x + Borgna, Struffolino D,other x x Helske et al. M,D,G x x + Taushanov, Berchtold M x x + Studer D,G x x + Bison, Scalcon D,I x x ++ Manzoni, Mooi-Reci I x x + Ritschard et al. I x + aType of SA: D dissimilarity-based, N sequence network, M Markov-based, I individual sequence summary numbers, S survival approach, G graphical sequence representation concepts and approaches they refer to. Moreover, the chapter by Eerola is one of most demanding mathematically. Nevertheless, these two chapters are important by demonstrating the range of possibilities and advantages of using SA in conjunction with related approaches. Courgeau’s text highlights the added value of SA with regard to other methods used in demography to study the dynamics of trajectories. Eerola’s contribution addresses the combination of SA with probabilistic models rarely considered in social sciences, which opens new perspectives for the analysis of life processes. The first two chapters in Part II, i.e., those by Malin and Wise and by Lundevaller and colleagues, are easily accessible even for newcomers to SA. These chapters are pure applications in which SA is used in combination with event history analysis (EHA) and require just basic knowledge in EHA (i.e., survival analysis). Chapters that use or deal with classic SA, i.e., with the clustering of sequences from pairwise dissimilarities, should also be easily comprehensible especially by readers with basic experience in SA. The other chapters either deal with non-clustering aspects of SA or consider alternative approaches such as sequence networks or Markov-based models. They may require basic knowledge in the concerned fields to grasp all the details. Preface vii Acknowledgments As editors, we would like to thank the authors of the chapters for their insights and contributions to the book. We also warmly acknowledge the members of the review committee and the associated referees—listed on next page—for their involvement in the review process of the chapters. Their in-depth reviewing, criticisms, and constructive remarks significantly contributed to the high quality of the retained papers. Thanks to an anonymous advisor for her/his valuable comments on the overall book. Many thanks also to Springer and the editors of the Series Life Course Research and Social Policies for their confidence in our project. This book benefited from the support of the Swiss National Centre of Compe- tence in Research LIVES – Overcoming Vulnerability: Life Course Perspectives, which is financed by the Swiss National Science Foundation (Grant number: 51NF40-160590). The editors are grateful to the Swiss National Science Foundation for its financial assistance. Geneva, Switzerland Gilbert Ritschard November 2017 Matthias Studer Review Committee • Silke Aisenbrey, Yeshiva University, USA • Jake Anders, UCL Institute of Education, UK • André Berchtold, University of Lausanne, Switzerland • Torsten Biemann, University of Mannheim, Germany • Ivano Bison, University of Trento, Italy • Philippe Blanchard, The University of Warwick, UK • Benjamin Cornwell, Cornell University, USA • Daniel Courgeau, INED, France • Cees Elzinga, Vrije Universiteit Amsterdam, Netherlands • Anette Fasang, Humboldt University of Berlin, Germany • Jacques-Antoine Gauthier, University of Lausanne, Switzerland • Brendan Halpin, University of Limerick, Ireland • Satu Helske, University of Oxford, UK • Jean-Marie Le Goff, University of Lausanne, Switzerland • Eva Lelièvre, INED, France • Tim Liao, University of Illinois at Urbana-Champaign, USA • Léonard Moulin, INED, France • Madalina Olteanu, SAMM, Université Paris 1, France • Raffaella Piccarreta, Bocconi University, Italy • Gary Pollock, Manchester Metropolitan University, UK • Nicolas Robette, UVSQ, France • Emanuela
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