Sequence Analysis and Related Approaches Innovative Methods and Applications

• Main Authors: Ritschard, Gilbert, Studer, Matthias
• Format: eBook
• Language: English
• Published: Cham Springer International Publishing AG 2018; Springer International Publishing
• Edition: 1
• Series: Life Course Research and Social Policies
• Subjects: Business; Management; Nonfiction; Sociology
• ISBN: 9783319954196; 3319954199; 9783319954202; 3319954202

This open access book provides innovative methods and original applications of sequence analysis (SA) and related methods for analysing longitudinal data describing life trajectories such as professional careers, family paths, the succession of health statuses, or the time use. The applications as w...

Table of Contents:

• Intro -- Preface -- How to Read the Book -- Acknowledgments -- Review Committee -- Associated Reviewers -- Contents -- Contributors -- Sequence Analysis: Where Are We, Where Are We Going? -- 1 Sequence Analysis: Optimal Matching and Much More -- 2 Towards Stronger Interaction with Related Approaches -- 3 Directions for the Future: The Chapters of this Book -- 4 Conclusion -- References -- Part I About Different Longitudinal Approaches in Longitudinal Analysis -- Do Different Approaches in Population Science Lead to Divergent or Convergent Models? -- 1 Introduction -- 2 Different Approaches -- 2.1 An Approach Based on Duration Models -- 2.2 An Event Sequences Approach -- 2.3 A Level Based Approach -- 2.4 A Network Based Approach -- 3 Toward a Synthesis -- 4 Conclusion -- References -- Case Studies of Combining Sequence Analysis and Modelling -- 1 Introduction -- 2 Case Study 1: Prediction of Excess Depressive Symptoms and Life Events -- 2.1 Multistate Models -- 2.2 Sequence Analysis -- 3 Case Study 2: Antecedents and Consequences of Transitional Pathways to Adulthood -- 3.1 Model for Strategies Accounting for Depressive Symptoms -- 3.2 Model for Transitional Pathways Accounting for Strategies -- 3.3 Model for Depressive Symptoms When Accounting for Pathways -- 4 Case Study 3: Pathways to Social Exclusion -- 4.1 Sequence Analysis -- 4.2 Risk Pattern Analysis -- 4.3 Predictions of Positive Trajectories -- 5 Discussion -- References -- Part II Sequence Analysis and Event History Analysis -- Glass Ceilings, Glass Escalators and Revolving Doors -- 1 Introduction -- 2 Theoretical Considerations and Hypotheses -- 2.1 Gender and Upward Occupational Mobility -- 2.2 Gender Composition and Upward Occupational Mobility -- 2.3 Gender Composition and Upward Occupational Mobility, by Gender -- 3 Data and Methods -- 3.1 Data and Sample -- 3.2 Variables
• 3 Combining Sequence Analysis and Hidden Markov Models for Complex Life Sequences -- 4 Data -- 4.1 Sequences -- 5 Analysis -- 5.1 Sequence Analysis and Clustering -- 5.2 Hidden Markov Models for Clusters -- 5.3 Software -- 6 Results -- 7 Discussion -- References -- Part V Advances in Sequence Clustering -- Markovian-Based Clustering of Internet Addiction Trajectories -- 1 Introduction -- 2 Data and Methods -- 2.1 Data -- 2.2 Clustering Using the HMTD Model -- 2.3 GMM as a Gold Standard Alternative -- 2.4 Statistical Analyses -- 3 Results -- 3.1 HMTD Clustering -- 3.2 Usefulness of the Covariates -- 3.3 GMM Clustering -- 4 Comparison of HMTD and GMM -- 5 Conclusion -- References -- Divisive Property-Based and Fuzzy Clustering for Sequence Analysis -- 1 Introduction -- 2 Sample Issue -- 3 Property-Based Clustering -- 3.1 Principle -- 3.2 Property Extraction -- 3.3 Running the Analysis in R -- 4 Fuzzy Clustering -- 4.1 Fanny Algorithm -- 4.2 Plotting and Describing a Fuzzy Typology -- 4.2.1 Most Typical Members -- 4.2.2 Weight-Based Presentation -- 4.3 Analyzing Cluster Membership Using Dirichlet Regression -- 4.4 Running the Analysis in R -- 5 Conclusion -- References -- From 07.00 to 22.00: A Dual-Earner Couple's Typical Day in Italy -- 1 Introduction -- 2 The Lexicographic Index -- 3 The Data, Their Organization and the Coding of the Activities in a Multichannel Approach -- 4 From 7.00 to 22.00: A Typical Working Dayof a Dual-Earner Couple in Italy -- 5 Conclusions -- References -- Part VI Appraising Sequence Quality -- Measuring Sequence Quality -- 1 Introduction: The Quality of Binary Sequencesof Successes and Failures -- 2 Common Methods for Studying Sequence Trajectories -- 3 Developing a Measure of Sequence Quality: Formal Properties -- 4 Using S-Positions: Successes Weighed by Frequency and Recency
• 3.2.1 Upward Occupational Mobility -- 3.2.2 Gender and Gender-Type of Occupation -- 3.3 Methods -- 4 Results -- 4.1 Leadership Position by Gender and Gender-Typical Occupation -- 4.2 Access to Leadership Positions -- 4.2.1 Kaplan-Meier Survivor Function -- 4.2.2 Regression Results -- 4.3 Leaving Leadership Positions -- 4.3.1 Kaplan-Meier Survivor Function -- 4.3.2 Regression Results -- 5 Discussion -- References -- Modelling Mortality Using Life Trajectories of Disabled and Non-Disabled Individuals in Nineteenth-Century Sweden -- 1 Introduction -- 2 Methods -- 3 Data -- 3.1 Area Selected for Analysis -- 3.2 Digitised Parish Registers Indicating Disabilities -- 4 Results -- 4.1 Sequence Analysis Results -- 4.2 Kaplan-Meier Curves -- 4.3 Cox Regression Results -- 5 Discussion -- References -- Sequence History Analysis (SHA): Estimating the Effect of Past Trajectories on an Upcoming Event -- 1 Introduction -- 1.1 Sequence History Analysis: A Combination of Sequence Analysis and Event History Analysis -- 1.2 Sequence History Analysis: Operationalizing Previous Trajectories -- 1.3 Event History Analysis: Estimating the Effect of Typical Past Trajectories on the Event Under Study -- 2 Empirical Application: Childhood Co-residence Trajectories and Leaving Home -- 3 Data -- 3.1 Control Variables -- 4 Analysis -- 4.1 Sequence Analysis: Operationalizing Previous Co-residence Trajectories -- 4.2 Event History Analysis: Estimating the Effect of Typical Past Trajectories on the Event Under Study -- 5 Discussion -- 6 Conclusion -- References -- Part III The Sequence Network Approach -- Network Analysis of Sequence Structures -- 1 From Sequence Pathways to Sequence-Networks -- 2 Sequence Pathways in Everyday Life -- 2.1 Activity Sequences in Networks -- 2.2 Organizing the Data as a Sequence-Network -- 3 Analyzing Sequence-Network Structure
• 3.1 Describing Sequence-Network Structure -- 3.2 Comparing Sequence-Networks -- 4 Illustrative Analysis: Activity Sequencing by Age -- 4.1 The Activity Sequence Data -- 4.2 Sequence-Network Analysis Findings -- 5 Discussion and Conclusion -- References -- Relational Sequence Networks as a Tool for Studying Gendered Mobility Patterns -- 1 Introduction -- 2 Method -- 2.1 Basic Concepts -- 2.2 Data -- 2.3 Software Tools -- 3 Results -- 3.1 Personal Networks -- 3.2 Sequence Networks -- 4 Conclusion -- References -- Part IV Unfolding the Process -- Multiphase Sequence Analysis -- 1 Introduction -- 2 Sequences as Multiphase Structures -- 2.1 Characteristics of Multiphase Sequences -- 2.2 Two Formal Properties of Phases and Two Methodological Assumptions -- 3 Division into Phases: Reference Frame, Alphabet(s) and Phase-Structure -- 3.1 A First Hint: The Extended Example -- 3.2 Three Aspects of Division into Phases -- 4 Rendering Multiphase Sequences -- 4.1 Simple Alignment on a Specific Event -- 4.2 Multiple Alignment by Sliced Representation -- 5 Measure and Interpretation of Pairwise Distances Between Multiphase Sequences: Multiphase Optimal Matching -- 5.1 Analytical Logic -- 5.2 MPOM Applied to Careers of Participants in `Pâtissier' Competitions -- 5.3 MPOM Compared -- 6 Conclusion -- References -- Unpacking Configurational Dynamics: Sequence Analysis and Qualitative Comparative Analysis as a Mixed-Method Design -- 1 Introduction -- 2 Sequence Analysis and Qualitative Comparative as a Sequential Mixed-Methods Design -- 3 Empirical Illustration -- 3.1 Background -- 3.2 Empirical Analysis -- 3.2.1 Step 1: Sequence Analysis -- 3.2.2 Step 2: Qualitative Comparative Analysis -- 4 Concluding Remarks -- References -- Combining Sequence Analysis and Hidden Markov Models in the Analysis of Complex Life Sequence Data -- 1 Introduction -- 2 Hidden Markov Model
• 5 An Application: The Quality of Labor Market Careers Among the Unemployed -- 5.1 Data -- 5.2 Method -- 5.3 Findings -- 6 Conclusion and Discussion -- References -- An Index of Precarity for Measuring Early Employment Insecurity -- 1 Introduction -- 2 Rising Precarity Among Young People -- 3 Conceptualising Precarity -- 4 The Precarity Index -- 4.1 Defining the Index -- 4.2 Tuning the Index -- 4.3 Behavior of the Precarity Index -- 4.4 Relaxing the Strict State Ordering Requirement -- 5 Application to the School to Work Transition -- 6 Conclusion -- References -- Correction to: Unpacking Configurational Dynamics: Sequence Analysis and Qualitative Comparative Analysis as a Mixed-Method Design -- Index