Generalized Latent Variable Modeling, Skrondal, Anders

Автор: Finch
Название: Latent Variable Modeling with R
ISBN: 0415832454 ISBN-13(EAN): 9780415832458
Издательство: Taylor&Francis
Рейтинг:
Цена: 58170.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results. Each chapter features a detailed example including the analysis of the data using R, the relevant theory, the assumptions underlying the model, and other statistical details to help readers better understand the models and interpret the results. Every R command necessary for conducting the analyses is described along with the resulting output which provides readers with a template to follow when they apply the methods to their own data. The basic information pertinent to each model, the newest developments in these areas, and the relevant R code to use them are reviewed. Each chapter also features an introduction, summary, and suggested readings. A glossary of the text’s boldfaced key terms and key R commands serve as helpful resources. The book is accompanied by a website with exercises, an answer key, and the in-text example data sets. Latent Variable Modeling with R: -Provides some examples that use messy data providing a more realistic situation readers will encounter with their own data. -Reviews a wide range of LVMs including factor analysis, structural equation modeling, item response theory, and mixture models and advanced topics such as fitting nonlinear structural equation models, nonparametric item response theory models, and mixture regression models. -Demonstrates how data simulation can help researchers better understand statistical methods and assist in selecting the necessary sample size prior to collecting data. -www.routledge.com/9780415832458 provides exercises that apply the models along with annotated R output answer keys and the data that corresponds to the in-text examples so readers can replicate the results and check their work. The book opens with basic instructions in how to use R to read data, download functions, and conduct basic analyses. From there, each chapter is dedicated to a different latent variable model including exploratory and confirmatory factor analysis (CFA), structural equation modeling (SEM), multiple groups CFA/SEM, least squares estimation, growth curve models, mixture models, item response theory (both dichotomous and polytomous items), differential item functioning (DIF), and correspondance analysis. ?The book concludes with a discussion of how data simulation can be used to better understand the workings of a statistical method and assist researchers in deciding on the necessary sample size prior to collecting data.? A mixture of independently developed R code along with available libraries for simulating latent models in R are provided so readers can use these simulations to analyze data using the methods introduced in the previous chapters. Intended for use in graduate or advanced undergraduate courses in latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, and social and health sciences, researchers in these fields also appreciate this book’s practical approach. The book provides sufficient conceptual background information to serve as a standalone text.? Familiarity with basic statistical concepts is assumed but basic knowledge of R is not.

Автор: Finch
Название: Latent Variable Modeling with R
ISBN: 0415832446 ISBN-13(EAN): 9780415832441
Издательство: Taylor&Francis
Рейтинг:
Цена: 163330.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book demonstrates how to conduct latent variable modeling (LVM) in R by highlighting the features of each model, their specialized uses, examples, sample code and output, and an interpretation of the results. Each chapter features a detailed example including the analysis of the data using R, the relevant theory, the assumptions underlying the model, and other statistical details to help readers better understand the models and interpret the results. Every R command necessary for conducting the analyses is described along with the resulting output which provides readers with a template to follow when they apply the methods to their own data. The basic information pertinent to each model, the newest developments in these areas, and the relevant R code to use them are reviewed. Each chapter also features an introduction, summary, and suggested readings. A glossary of the text’s boldfaced key terms and key R commands serve as helpful resources. The book is accompanied by a website with exercises, an answer key, and the in-text example data sets. Latent Variable Modeling with R: -Provides some examples that use messy data providing a more realistic situation readers will encounter with their own data. -Reviews a wide range of LVMs including factor analysis, structural equation modeling, item response theory, and mixture models and advanced topics such as fitting nonlinear structural equation models, nonparametric item response theory models, and mixture regression models. -Demonstrates how data simulation can help researchers better understand statistical methods and assist in selecting the necessary sample size prior to collecting data. -www.routledge.com/9780415832458 provides exercises that apply the models along with annotated R output answer keys and the data that corresponds to the in-text examples so readers can replicate the results and check their work. The book opens with basic instructions in how to use R to read data, download functions, and conduct basic analyses. From there, each chapter is dedicated to a different latent variable model including exploratory and confirmatory factor analysis (CFA), structural equation modeling (SEM), multiple groups CFA/SEM, least squares estimation, growth curve models, mixture models, item response theory (both dichotomous and polytomous items), differential item functioning (DIF), and correspondance analysis. ?The book concludes with a discussion of how data simulation can be used to better understand the workings of a statistical method and assist researchers in deciding on the necessary sample size prior to collecting data.? A mixture of independently developed R code along with available libraries for simulating latent models in R are provided so readers can use these simulations to analyze data using the methods introduced in the previous chapters. Intended for use in graduate or advanced undergraduate courses in latent variable modeling, factor analysis, structural equation modeling, item response theory, measurement, or multivariate statistics taught in psychology, education, human development, and social and health sciences, researchers in these fields also appreciate this book’s practical approach. The book provides sufficient conceptual background information to serve as a standalone text.? Familiarity with basic statistical concepts is assumed but basic knowledge of R is not.

Автор: Marcoulides, George A.
Название: Latent Variable and Latent Structure Models
ISBN: 080584046X ISBN-13(EAN): 9780805840469
Издательство: Taylor&Francis
Рейтинг:
Цена: 148010.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.

Автор: Holm Altenbach; Alexander Belyaev; Victor A. Ereme
Название: Dynamical Processes in Generalized Continua and Structures
ISBN: 3030116646 ISBN-13(EAN): 9783030116644
Издательство: Springer
Рейтинг:
Цена: 93160.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents a collection of chapters on the current problems of the theory of dynamical processes in generalized continua and structures, and has been compiled to commemorate the 70th birthday of Prof. Dmitry Indeitsev – a leading specialist in the field of dynamical processes in solids, fluids and structures. It discusses various applications related to Prof. Indeitsev’s contributions, including various discrete and continuous dynamic models of structures and media, as well as a number of dynamical processes in generalized media.

Автор: W. Hennevogl; Ludwig Fahrmeir; Gerhard Tutz
Название: Multivariate Statistical Modelling Based on Generalized Linear Models
ISBN: 1441929002 ISBN-13(EAN): 9781441929006
Издательство: Springer
Рейтинг:
Цена: 181670.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book is aimed at applied statisticians, graduate students of statistics, and students and researchers with a strong interest in statistics and data analysis. This second edition is extensively revised, especially those sections relating with Bayesian concepts.

Автор: Jonathan Pearson
Название: Generalized Perturbations in Modified Gravity and Dark Energy
ISBN: 3319347489 ISBN-13(EAN): 9783319347486
Издательство: Springer
Рейтинг:
Цена: 95770.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this thesis the author constructs a comprehensive unifying framework for understanding the observational impact of general classes of dark sector theories, by formulating equations of state for the dark sector perturbations.

Автор: Michael Holzhauser
Название: Generalized Network Improvement and Packing Problems
ISBN: 3658168110 ISBN-13(EAN): 9783658168117
Издательство: Springer
Рейтинг:
Цена: 60550.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Michael Holzhauser discusses generalizations of well-known network flow and packing problems by additional or modified side constraints.

Автор: Jonathan Pearson
Название: Generalized Perturbations in Modified Gravity and Dark Energy
ISBN: 3319012096 ISBN-13(EAN): 9783319012094
Издательство: Springer
Рейтинг:
Цена: 130430.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this thesis the author constructs a comprehensive unifying framework for understanding the observational impact of general classes of dark sector theories, by formulating equations of state for the dark sector perturbations.

Автор: Shashi K. Mishra; Shouyang Wang; Kin Keung Lai
Название: Generalized Convexity and Vector Optimization
ISBN: 3642099300 ISBN-13(EAN): 9783642099304
Издательство: Springer
Рейтинг:
Цена: 153720.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses the Kuhn-Tucker Optimality, Karush-Kuhn-Tucker Necessary and Sufficient Optimality Conditions in presence of various types of generalized convexity assumptions. It details the present state of knowledge on research done in this area.

Автор: Mcculloch, Charles E. Searle, Shayle R. Neuhaus, J
Название: Generalized, linear, and mixed models
ISBN: 0470073713 ISBN-13(EAN): 9780470073711
Издательство: Wiley
Рейтинг:
Цена: 167850.00 T
Наличие на складе: Поставка под заказ.
Описание: - This new edition presents a unified, accessible, and self-contained treatment of the latest statistical methods for analyzing correlated, non-normally distributed data. - The book`s unified treatment addresses the needs of applications-oriented users of statistical packages and also graduate students in statistics.

Автор: Plamen Angelov; Sotir Sotirov
Название: Imprecision and Uncertainty in Information Representation and Processing
ISBN: 3319263013 ISBN-13(EAN): 9783319263014
Издательство: Springer
Рейтинг:
Цена: 139310.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book offers a comprehensive and timely overview of advanced mathematical tools for both uncertainty analysis and modeling of parallel processes, with a special emphasis on intuitionistic fuzzy sets and generalized nets.