Order Total (1 Item Items):
Shipping Destination:
Random Effect Latent Variable Model by Dunson (17 results)
Skip to main search results
Search filters
Product Type
- All Product Types
- Books (17)
- Magazines & Periodicals (No further results match this refinement)
- Comics (No further results match this refinement)
- Sheet Music (No further results match this refinement)
- Art, Prints & Posters (No further results match this refinement)
- Photographs (No further results match this refinement)
- Maps (No further results match this refinement)
- Manuscripts & Paper Collectibles (No further results match this refinement)
Condition Learn more
- New (14)
- As New, Fine or Near Fine (1)
- Very Good or Good (2)
- Fair or Poor (No further results match this refinement)
- As Described (No further results match this refinement)
Binding
- All Bindings
- Hardcover (No further results match this refinement)
- Softcover (17)
Collectible Attributes
- First Edition (No further results match this refinement)
- Signed (No further results match this refinement)
- Dust Jacket (No further results match this refinement)
- Seller-Supplied Images (5)
- Not Print on Demand (14)
Language (1)
Free Shipping
Seller Location
Seller Rating
-
paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
-
Random Effect and Latent Variable Model Selection Lecture Notes in Statistics 192
Book 43 of 72: Lecture Notes in StatisticsSeller: books4less (Versandantiquariat Petra Gros GmbH & Co. KG), Welling, Germany
Seller rating 5 out of 5 stars
Broschiert. Condition: 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.
-
Condition: New. pp. 188.
-
Condition: New. pp. 188 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.
-
Condition: New. pp. 188.
-
Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
-
Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
-
Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
-
International EditionUS$ 67.34
US$ 8.15 shipping
Ships from United Kingdom to U.S.A.Quantity: 19 available
Add to basketCondition: New. Brand New ! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
-
Random Effect and Latent Variable Model Selection (Lecture Notes in Statistics, 192)
Book 43 of 72: Lecture Notes in StatisticsSeller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 70.66
US$ 16.30 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
-
Taschenbuch. Condition: 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. Condition: 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.
-
Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.
-
Soft cover. Condition: New. ISBN:9780387767208.
-
Random Effect and Latent Variable Model Selection
Book 43 of 72: Lecture Notes in StatisticsLanguage: English
Published by Springer New York Aug 2008, 2008
ISBN 10: 0387767207 ISBN 13: 9780387767208
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 170 pp. Englisch.
-
Random Effect and Latent Variable Model Selection
Book 43 of 72: Lecture Notes in StatisticsLanguage: English
Published by Springer-Verlag New York Inc., 2008
ISBN 10: 0387767207 ISBN 13: 9780387767208
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
US$ 80.54
US$ 23.20 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketPaperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
-
Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. - Practically motivated and clear overview of methods for selecting random effects.- Leading researchers in the field describe how to appropriately test variance components equal to zero.- Bayesian and frequentist approaches for model selec.
