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Quantitative Applications in the Social Sciences Ser.: Sequence Analysis by Marcel Raab and Emanuela Struffolino (2022, Trade Paperback)
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About this product
Product Identifiers
PublisherSAGE Publications, Incorporated
ISBN-101071801880
ISBN-139781071801888
eBay Product ID (ePID)21057257631
Product Key Features
Number of Pages192 Pages
LanguageEnglish
Publication NameSequence Analysis
SubjectSociology / General, Statistics
Publication Year2022
TypeTextbook
Subject AreaSocial Science
AuthorMarcel Raab, Emanuela Struffolino
SeriesQuantitative Applications in the Social Sciences Ser.
FormatTrade Paperback
Dimensions
Item Height0.4 in
Item Weight10 Oz
Item Length8.5 in
Item Width5.5 in
Additional Product Features
Intended AudienceCollege Audience
LCCN2022-278940
ReviewsThis book provides a comprehensive and updated introduction to sequence analysis, I highly recommend it for anyone who wants to learn the topic systematically., This book provides a comprehensive and updated introduction to sequence analysis, I highly recommend it for anyone who wants to learn the topic systematically, This book provides a comprehensive and updated introduction to sequence analysis, I highly recommend it for anyone who wants to learn the topic systematically -- Tim F. Liao
Dewey Edition23
IllustratedYes
Dewey Decimal301.01/51954
Table Of ContentSeries Editor's IntroductionAcknowledgmentsPrefaceAbout the AuthorsChapter 1. Introduction 1.1 Sequence Analysis in the Social Sciences 1.2 Organization of the Book 1.3 Software, Data, and Companion WebpageChapter 2: Describing and Visualizing Sequences 2.1 Basic Concepts and Terminology 2.1 Basic Concepts and Terminology 2.3 Description of Sequence Data I: The Basics 2.4 Visualization of Sequences 2.5 Description of Sequences II: Assessing SequenceChapter 3: Comparing Sequences 3.1 Dissimilarity Measures to Compare Sequences 3.2 Alignment Techniques 3.3 Alignment-Based Extensions of OM 3.4 Nonalignment Techniques 3.5 Comparing Dissimilarity Matrices 3.6 Comparing Sequences of Different Length 3.7 Beyond the Standard Full-Sample Pairwise Sequence ComparisonChapter 4: Identifying Groups in Data: Analyses Based On Dissimilarities Between Sequences 4.1 Clustering Sequences to Uncover Typologies 4.2 Illustrative Application 4.3 "Construct Validity" for Typologies From Cluster Analysis to Sequences 4.4 Using Typologies as Dependent and Independent Variables in a Regression FrameworkChapter 5: Multidimensional Sequence Analysis 5.1 Accounting for Simultaneous Temporal Processes 5.2 Expanding the Alphabet: Combining Multiple Channels Into a Single Alphabet 5.3 Cross-Tabulation of Groups Identified From Different Dissimilarity Matrices 5.4 Combining Domain-Specific Dissimilarities 5.5 Multichannel Sequence AnalysisChapter 6: Examining Group Differences Without Cluster Analysis 6.1 Comparing Within-Group Discrepancies 6.2 Measuring Associations Between Sequences and Covariates 6.3 Statistical Implicative AnalysisChapter 7: Combining Sequence Analysis With Other Explanatory Methods 7.1 The Rationale Behind the Combination of Stochastic and Algorithmic Analytical Tools 7.2 Competing Trajectories Analysis 7.3 Sequence Analysis Multistate Model Procedure 7.4 Combining SA and (Propensity Score) MatchingChapter 8: Conclusions 8.1 Summary of Recommendations: An Extended Checklist 8.2 Achievements, Unresolved Issues, and Ongoing InnovationReferences
SynopsisFounded in 1965, SAGE is a leading independent academic and professional publisher of innovative, high-quality content. Known for our commitment to quality and innovation, SAGE has helped inform and educate a global community of scholars, practitioners, researchers, and students across a broad range of subject areas. Book jacket., Sequence analysis (SA) was developed to study social processes that unfold over time as sequences of events. It has gained increasing attention as the availability of longitudinal data made it possible to address sequence-oriented questions. This volume introduces the basics of SA to guide practitioners and support instructors through the basic workflow of sequence analysis. In addition to the basics, this book outlines recent advances and innovations in SA. The presentation of statistical, substantive, and theoretical foundations is enriched by examples to help the reader understand the repercussions of specific analytical choices. The extensive ancillary material supports self-learning based on real-world survey data and research questions from the field of life course research., Sequence analysis (SA) was developed to study social processes that unfold over time as sequences of events. It has gained increasing attention as the availability of longitudinal data made it possible to address sequence-oriented questions. This volume introduces the basics of SA to guide practitioners and support instructors through the basic workflow of sequence analysis. In addition to the basics, this book outlines recent advances and innovations in SA. The presentation of statistical, substantive, and theoretical foundations is enriched by examples to help the reader understand the repercussions of specific analytical choices. The extensive ancillary material supports self-learning based on real-world survey data and research questions from the field of life course research. Data and code and a variety of additional resources to enrich the use of this book are available on an accompanying website.
LC Classification NumberHM585
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