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Autor(en): 
  • Jacques A. Hagenaars
  • Marcel A. Croon
  • Wicher Bergsma
  • Marginal Models: For Dependent, Clustered, and Longitudinal Categorical Data 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  November 2010  
    Genre:  Schulbücher 
     
    B / Economics, finance, business & management / Mathematics and Statistics / Modeling / Panel Data / Probability & statistics / repeated measurements / Social research & statistics
    ISBN:  9781441918734 
    EAN-Code: 
    9781441918734 
    Verlag:  Springer EN 
    Einband:  Kartoniert  
    Sprache:  English  
    Serie:  Statistics for Social and Behavioral Sciences  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Gewicht:  439 gr 
    Seiten:  268 
    Illustration:  XI, 268 p. 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Marginal Models for Dependent, Clustered, and Longitudinal Categorical Data provides a comprehensive overview of the basic principles of marginal modeling and offers a wide range of possible applications. Marginal models are often the best choice for answering important research questions when dependent observations are involved, as the many real world examples in this book show.

    In the social, behavioral, educational, economic, and biomedical sciences, data are often collected in ways that introduce dependencies in the observations to be compared. For example, the same respondents are interviewed at several occasions, several members of networks or groups are interviewed within the same survey, or, within families, both children and parents are investigated. Statistical methods that take the dependencies in the data into account must then be used, e.g., when observations at time one and time two are compared in longitudinal studies. At present, researchers almost automatically turn to multi-level models or to GEE estimation to deal with these dependencies. Despite the enormous potential and applicability of these recent developments, they require restrictive assumptions on the nature of the dependencies in the data. The marginal models of this book provide another way of dealing with these dependencies, without the need for such assumptions, and can be used to answer research questions directly at the intended marginal level. The maximum likelihood method, with its attractive statistical properties, is used for fitting the models.

    This book has mainly been written with applied researchers in mind. It includes many real world examples, explains the types of research questions for which marginal modeling is useful, and provides a detailed description of how to apply marginal models for a great diversity of research questions. All these examples are presented on the book's website (www.cmm.st), along with user friendly programs.

    Wicher Bergsmais Senior Lecturer at the London School of Economics and Political Science. His current research interests are categorical data analysis, measurement of association, nonparametric regression, and maximum likelihood estimation.

    Marcel Croon is associate professor at Tilburg University. He is especially interested in measurement problems, structural equation modeling, latent variables, and random effect models.

    Jacques Hagenaars is full professor at Tilburg University and at present chair of the board of IOPS, the Dutch PhD School for Sociometrics and Psychometrics. His main research interests are research designs, longitudinal research, categorical data analysis and latent variable models.

      



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