{"title":"使用序列分析选择定性案例:一种深入了解生命历程轨迹的混合方法","authors":"Guillaume Le Roux , Matthias Studer , Arnaud Bringé , Catherine Bonvalet","doi":"10.1016/j.alcr.2023.100530","DOIUrl":null,"url":null,"abstract":"<div><p><span>In this paper, we propose a sequence analysis-based method for selecting qualitative cases depending on quantitative results. Inspired by tools developed for cross-sectional analyses, we propose indicators suitable for longitudinal study of the life course in a holistic perspective and a set of corresponding analysis guidelines. Two complementary indicators are introduced, </span><em>marginality</em> and <em>gain</em><span>, that allows labeling observations according to both their typicality within their group and their illustrativeness of a given quantitative relationship. These indicators allow selecting a diversity of cases depending on their contributions to a quantitative relationship between trajectories and a covariate or a typology. The computation of the indicators is made available in the TraMineRextras R package.</span></p><p><span>The method and its advantages are illustrated through an original study of the relationships between residential trajectories in the Paris region and residential socialization during childhood. Using the </span><em>Biographies et Entourage</em><span> [Event history and entourage] survey and qualitative interviews conducted with a subsample of respondents, the analysis shows the contributions of the method not only to improve the understanding of statistical associations, but also to identify their limitations. Extension and generalization of the method are finally proposed to cover a wider scope of situations.</span></p></div>","PeriodicalId":47126,"journal":{"name":"Advances in Life Course Research","volume":"57 ","pages":"Article 100530"},"PeriodicalIF":3.4000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Selecting qualitative cases using sequence analysis: A mixed-method for in-depth understanding of life course trajectories\",\"authors\":\"Guillaume Le Roux , Matthias Studer , Arnaud Bringé , Catherine Bonvalet\",\"doi\":\"10.1016/j.alcr.2023.100530\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span>In this paper, we propose a sequence analysis-based method for selecting qualitative cases depending on quantitative results. Inspired by tools developed for cross-sectional analyses, we propose indicators suitable for longitudinal study of the life course in a holistic perspective and a set of corresponding analysis guidelines. Two complementary indicators are introduced, </span><em>marginality</em> and <em>gain</em><span>, that allows labeling observations according to both their typicality within their group and their illustrativeness of a given quantitative relationship. These indicators allow selecting a diversity of cases depending on their contributions to a quantitative relationship between trajectories and a covariate or a typology. The computation of the indicators is made available in the TraMineRextras R package.</span></p><p><span>The method and its advantages are illustrated through an original study of the relationships between residential trajectories in the Paris region and residential socialization during childhood. Using the </span><em>Biographies et Entourage</em><span> [Event history and entourage] survey and qualitative interviews conducted with a subsample of respondents, the analysis shows the contributions of the method not only to improve the understanding of statistical associations, but also to identify their limitations. Extension and generalization of the method are finally proposed to cover a wider scope of situations.</span></p></div>\",\"PeriodicalId\":47126,\"journal\":{\"name\":\"Advances in Life Course Research\",\"volume\":\"57 \",\"pages\":\"Article 100530\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Life Course Research\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1040260823000059\",\"RegionNum\":2,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Life Course Research","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1040260823000059","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
Selecting qualitative cases using sequence analysis: A mixed-method for in-depth understanding of life course trajectories
In this paper, we propose a sequence analysis-based method for selecting qualitative cases depending on quantitative results. Inspired by tools developed for cross-sectional analyses, we propose indicators suitable for longitudinal study of the life course in a holistic perspective and a set of corresponding analysis guidelines. Two complementary indicators are introduced, marginality and gain, that allows labeling observations according to both their typicality within their group and their illustrativeness of a given quantitative relationship. These indicators allow selecting a diversity of cases depending on their contributions to a quantitative relationship between trajectories and a covariate or a typology. The computation of the indicators is made available in the TraMineRextras R package.
The method and its advantages are illustrated through an original study of the relationships between residential trajectories in the Paris region and residential socialization during childhood. Using the Biographies et Entourage [Event history and entourage] survey and qualitative interviews conducted with a subsample of respondents, the analysis shows the contributions of the method not only to improve the understanding of statistical associations, but also to identify their limitations. Extension and generalization of the method are finally proposed to cover a wider scope of situations.
期刊介绍:
Advances in Life Course Research publishes articles dealing with various aspects of the human life course. Seeing life course research as an essentially interdisciplinary field of study, it invites and welcomes contributions from anthropology, biosocial science, demography, epidemiology and statistics, gerontology, economics, management and organisation science, policy studies, psychology, research methodology and sociology. Original empirical analyses, theoretical contributions, methodological studies and reviews accessible to a broad set of readers are welcome.