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Download the fantastic book titled Latent Variable Modeling with R written by W. Holmes Finch, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Latent Variable Modeling with R", which was released on 26 June 2015. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Psychology genre.

Summary of Latent Variable Modeling with R by W. Holmes Finch PDF

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.


Detail About Latent Variable Modeling with R PDF

  • Author : W. Holmes Finch
  • Publisher : Routledge
  • Genre : Psychology
  • Total Pages : 328 pages
  • ISBN : 1317970756
  • PDF File Size : 19,7 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Latent Variable Modeling with R

Latent Variable Modeling with R
  • Publisher : Routledge
  • File Size : 30,8 Mb
  • Release Date : 26 June 2015
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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

Latent Variable Modeling Using R

Latent Variable Modeling Using R
  • Publisher : Routledge
  • File Size : 28,5 Mb
  • Release Date : 09 May 2014
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This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help

Latent Variable Models

Latent Variable Models
  • Publisher : Psychology Press
  • File Size : 33,9 Mb
  • Release Date : 20 May 2004
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This book introduces multiple-latent variable models by utilizing path diagrams to explain the underlying relationships in the models. This approach helps less mathematically inclined students grasp the underlying relationships between

Latent Variable Modeling Using R

Latent Variable Modeling Using R
  • Publisher : Routledge
  • File Size : 51,6 Mb
  • Release Date : 09 May 2014
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This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help

Advances in Latent Class Analysis

Advances in Latent Class Analysis
  • Publisher : IAP
  • File Size : 47,7 Mb
  • Release Date : 01 May 2019
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What is latent class analysis? If you asked that question thirty or forty years ago you would have gotten a different answer than you would today. Closer to its time

Generalized Latent Variable Modeling

Generalized Latent Variable Modeling
  • Publisher : CRC Press
  • File Size : 23,5 Mb
  • Release Date : 11 May 2004
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This book unifies and extends latent variable models, including multilevel or generalized linear mixed models, longitudinal or panel models, item response or factor models, latent class or finite mixture models,

Latent Variable Models and Factor Analysis

Latent Variable Models and Factor Analysis
  • Publisher : Wiley
  • File Size : 28,7 Mb
  • Release Date : 10 August 1999
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Hitherto latent variable modelling has hovered on the fringes of the statistical mainstream but if the purpose of statistics is to deal with real problems, there is every reason for

Latent Variable Models

Latent Variable Models
  • Publisher : Routledge
  • File Size : 50,7 Mb
  • Release Date : 07 December 2016
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Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces latent variable models by utilizing path diagrams to explain the relationships in the models. This approach helps

Composite-Based Structural Equation Modeling

Composite-Based Structural Equation Modeling
  • Publisher : Guilford Publications
  • File Size : 41,9 Mb
  • Release Date : 24 December 2020
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This book presents powerful tools for integrating interrelated composites--such as capabilities, policies, treatments, indices, and systems--into structural equation modeling (SEM). Jörg Henseler introduces the types of research questions that

Computational Genomics with R

Computational Genomics with R
  • Publisher : CRC Press
  • File Size : 54,7 Mb
  • Release Date : 16 December 2020
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Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers