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Broschiert. Zustand: Gut. 169 Seiten Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber. Es befindet sich lediglich ein Bibliotheksstempel im Buch; ordnungsgemäß entwidmet. Sprache: Englisch Gewicht in Gramm: 250.

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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Random Effect and Latent Variable Model Selection In recent years, there has been a dramatic increase in the collection of multivariate and correlated data in a wide variety of elds. For example, it is now standard pr- tice to routinely collect many response variables on each individual in a study. The different variables may correspond to repeated measurements over time, to a battery of surrogates for one or more latent traits, or to multiple types of outcomes having an unknown dependence structure. Hierarchical models that incorporate subje- speci c parameters are one of the most widely-used tools for analyzing multivariate and correlated data. Such subject-speci c parameters are commonly referred to as random effects, latent variables or frailties. There are two modeling frameworks that have been particularly widely used as hierarchical generalizations of linear regression models. The rst is the linear mixed effects model (Laird and Ware , 1982) and the second is the structural equation model (Bollen , 1989). Linear mixed effects (LME) models extend linear regr- sion to incorporate two components, with the rst corresponding to xed effects describing the impact of predictors on the mean and the second to random effects characterizing the impact on the covariance. LMEs have also been increasingly used for function estimation. In implementing LME analyses, model selection problems are unavoidable. For example, there may be interest in comparing models with and without a predictor in the xed and/or random effects component.

Taschenbuch. Zustand: Neu. Random Effect and Latent Variable Model Selection | David Dunson | Taschenbuch | x | Englisch | 2008 | Springer New York | EAN 9780387767208 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Zustand: New. Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Doanld B. RubinWinner of the 2016 De Groot Prize from the International Society for Bayesian AnalysisNow in its third edition, this classic book is wid.

Hardcover. Zustand: Brand New. 3rd edition. 800 pages. 10.20x7.09x1.65 inches. In Stock.