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6 produkter
6 produkter
1 064 kr
Skickas inom 10-15 vardagar
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.
481 kr
Skickas inom 7-10 vardagar
Applied Latent Class Analysis introduces several innovations in latent class analysis to a wider audience of researchers. Many of the world's leading innovators in the field of latent class analysis contributed essays to this volume, each presenting a key innovation to the basic latent class model and illustrating how it can prove useful in situations typically encountered in actual research.
1 653 kr
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Applied Latent Class Analysis introduces several innovations in latent class analysis to a wider audience of researchers. Many of the world's leading innovators in the field of latent class analysis contributed essays to this volume, each presenting a key innovation to the basic latent class model and illustrating how it can prove useful in situations typically encountered in actual research.
Del 94 - Quantitative Applications in the Social Sciences
Loglinear Models with Latent Variables
Häftad, Engelska, 1993
804 kr
Skickas inom 3-6 vardagar
Sociologists with a quantitative bent will doubtless find it useful. . . . well-written, with a wealth of explanation. . . --Dougal Hutchison in Educational Research "Loglinear Models with Latent Variables, by Jacques A. Hagenaars, is a timely contribution to the literature that serves to inform researchers of the richness of loglinear approaches to analyzing latent categorical variables. . . . The author provides a clear exposition of the loglinear model." --Scott L. Hershberger in Structural Equation Modeling Since the 1980s, the loglinear model has become the dominant form of categorical data analysis as researchers have expanded it into new directions. Jacques A. Hagenaars' book shows researchers the applications of one of these new developments--how uniting ordinary loglinear analysis and latent class analysis into a general loglinear model with latent variables can result in a modified LISREL approach. This modified LISREL model will enable researchers to analyze categorical data in the same way that they have been able to use LISREL to analyze continuous data. Beginning with an introduction to ordinary loglinear modeling and standard latent class analysis, Hagenaars explains the general principles of loglinear modeling with latent variables; the application of loglinear models with latent variables as a causal model, as well as a tool for the analysis of categorical longitudinal data; the strengths and limitations of this technique; and lastly, a summary of computer programs that are available for executing this technique.
1 064 kr
Skickas inom 10-15 vardagar
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.
Analyse von Tabellen und kategorialen Daten
Log-lineare Modelle, latente Klassenanalyse, logistische Regression und GSK-Ansatz
Häftad, Tyska, 1997
353 kr
Skickas inom 10-15 vardagar
Dieses Buch behandelt Modelle zur Analyse kategorialer Daten. Kategoriale Daten sind Variablen, die eine begrenzte Anzahl von Ausprägungen (Kategorien) haben. Bei vielen der in Umfrageforschung und amtlicher Statistik erhobenen Merkmale handelt es sich um kategoriale Daten. Beispiele wären etwa das Geschlecht einer Befragungsperson, ihre Parteipräferenz, die Anzahl der Mitbewohner im Haushalt dieser Person, ihre Schichtzugehörigkeit und ähnliches mehr. In diesem Lehrbuch geht es um eine anwendungsorientierte Einführung in die multivariate Analyse kategorialer Daten. Konkret werden vier Ansätze vorgestellt: die gewichtete Regression nach Grizzle, Starmer und Koch (GSK-Ansatz), die Klasse der log-linearen Modelle, die logistische Regression und die Analyse latenter Klassen.