Isbn: 9780761920847 - an introduction to generalized linear models (quantitative applications in the social sciences) (16 risultati)

Softcover. Condizione: Très bon. Ancien livre de bibliothèque avec équipements. Edition 2005. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 2005. Ammareal gives back up to 15% of this item's net price to charity organizations. …

Condizione: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,200grams, ISBN:9780761920847.

paperback. Condizione: Very Good. Connecting readers with great books since 1972! Used books may not include companion materials, and may have some shelf wear or limited writing. We ship orders daily and Customer Service is our top priority.

Condizione: Very Good. : Este libro es una introducción accesible pero completa a los Modelos Lineales Generalizados (GLM), la distribución de la familia exponencial y la estimación de máxima verosimilitud. Incluye una discusión sobre la comprobación de la adecuación del modelo y una descripción de cómo utilizar SAS para ajustar GLM. Describe la conexión entre el análisis de supervivencia y GLM. Este libro es un texto ideal para los investigadores de las ciencias sociales que no tienen una sólida formación estadística, pero que desean aprender técnicas más avanzadas después de haber realizado un curso introductorio que cubra el análisis de regresión. EAN: 9780761920847 Tipo: Libros Categoría: Tecnología|Educación|Ciencias Título: An Introduction to Generalized Linear Models Autor: George H. Dunteman| Moon-Ho R. Ho Editorial: SAGE Publications, Inc Idioma: en Páginas: 88 Formato: tapa blanda.…

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Paperback. Condizione: Brand New. 1st edition. 72 pages. 8.50x5.50x0.25 inches. In Stock.

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Paperback / softback. Condizione: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents a discussion of fundamental statistical modeling concepts in a multiple regression framework. This book provides an introduction to GLM, exponential family distribution, and maximum likelihood estimation. It is useful for social science researchers.…

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Do you have data that is not normally distributed and don't know how to analyze it using generalized linear models (GLM) Beginning with a discussion of fundamental statistical modeling concepts in a multiple regression framework, the authors extend these concepts toáGLM (including Poisson regression. logistic regression, and proportional hazards models) and demonstrate the similarity of various regression models to GLM. Each procedure is illustrated using real life data sets, and the computer instructions and results will be presented for each example. Throughout the book, there is an emphasis on link functions and error distribution and how the model specifications translate into likelihood functions that can, through maximum likelihood estimation be used to estimate the regression parameters and their associated standard errors. This book provides readers with basic modeling principles that are applicable to a wide variety of situations.Key Features:- Provides an accessible but thorough introduction to GLM, exponential family distribution, and maximum likelihood estimation- Includes discussion on checking model adequacy and description on how to use SAS to fit GLM- Describes the connection between survival analysis and GLMáThis book is an ideal text for social science researchers who do not have a strong statistical background, but would like to learn more advanced techniques having taken an introductory course covering regression analysis.…