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Comparison Of Maximum Likelihood Bayesian Partial Least Squares And Generalized Structured Component Analysis Methods For Estimation Of Structural Equation Models With Small Samples
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Book Synopsis Comparison of Maximum Likelihood, Bayesian, Partial Least Squares, and Generalized Structured Component Analysis Methods for Estimation of Structural Equation Models with Small Samples by : Frances L. Chumney
Download or read book Comparison of Maximum Likelihood, Bayesian, Partial Least Squares, and Generalized Structured Component Analysis Methods for Estimation of Structural Equation Models with Small Samples written by Frances L. Chumney and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Advances in Bioengineering by : Renu Vyas
Download or read book Advances in Bioengineering written by Renu Vyas and published by Springer Nature. This book was released on 2020-05-11 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a single source of information on three major bioengineering areas: engineering at the cellular and molecular level; biomedical devices / instrument engineering; and data engineering. It explores the latest strategies that are essential to advancing our understanding of the mechanisms of human diseases, the development of new enzyme-based technologies, diagnostics, prosthetics, high-performance computing platforms for managing huge amounts of biological data, and the use of deep learning methods to create predictive models. The book also highlights the growing importance of integrating chemistry into life sciences research, most notably concerning the development and evaluation of nanomaterials and nanoparticles and their interactions with biological material. The underlying interdisciplinary theme of bioengineering is addressed in a range of multifaceted applications and worked out examples provided in each chapter.
Book Synopsis Bayesian Structural Equation Modeling by : Sarah Depaoli
Download or read book Bayesian Structural Equation Modeling written by Sarah Depaoli and published by Guilford Publications. This book was released on 2021-08-16 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers researchers a systematic and accessible introduction to using a Bayesian framework in structural equation modeling (SEM). Stand-alone chapters on each SEM model clearly explain the Bayesian form of the model and walk the reader through implementation. Engaging worked-through examples from diverse social science subfields illustrate the various modeling techniques, highlighting statistical or estimation problems that are likely to arise and describing potential solutions. For each model, instructions are provided for writing up findings for publication, including annotated sample data analysis plans and results sections. Other user-friendly features in every chapter include "Major Take-Home Points," notation glossaries, annotated suggestions for further reading, and sample code in both Mplus and R. The companion website (www.guilford.com/depaoli-materials) supplies data sets; annotated code for implementation in both Mplus and R, so that users can work within their preferred platform; and output for all of the book’s examples.
Book Synopsis Handbook of Market Research by : Christian Homburg
Download or read book Handbook of Market Research written by Christian Homburg and published by Springer. This book was released on 2021-12-03 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this handbook, internationally renowned scholars outline the current state-of-the-art of quantitative and qualitative market research. They discuss focal approaches to market research and guide students and practitioners in their real-life applications. Aspects covered include topics on data-related issues, methods, and applications. Data-related topics comprise chapters on experimental design, survey research methods, international market research, panel data fusion, and endogeneity. Method-oriented chapters look at a wide variety of data analysis methods relevant for market research, including chapters on regression, structural equation modeling (SEM), conjoint analysis, and text analysis. Application chapters focus on specific topics relevant for market research such as customer satisfaction, customer retention modeling, return on marketing, and return on price promotions. Each chapter is written by an expert in the field. The presentation of the material seeks to improve the intuitive and technical understanding of the methods covered.
Book Synopsis Partial Least Squares Structural Equation Modeling by : Necmi K. Avkiran
Download or read book Partial Least Squares Structural Equation Modeling written by Necmi K. Avkiran and published by Springer. This book was released on 2018-02-16 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book pulls together robust practices in Partial Least Squares Structural Equation Modeling (PLS-SEM) from other disciplines and shows how they can be used in the area of Banking and Finance. In terms of empirical analysis techniques, Banking and Finance is a conservative discipline. As such, this book will raise awareness of the potential of PLS-SEM for application in various contexts. PLS-SEM is a non-parametric approach designed to maximize explained variance in latent constructs. Latent constructs are directly unobservable phenomena such as customer service quality and managerial competence. Explained variance refers to the extent we can predict, say, customer service quality, by examining other theoretically related latent constructs such as conduct of staff and communication skills. Examples of latent constructs at the microeconomic level include customer service quality, managerial effectiveness, perception of market leadership, etc.; macroeconomic-level latent constructs would be found in contagion of systemic risk from one financial sector to another, herd behavior among fund managers, risk tolerance in financial markets, etc. Behavioral Finance is bound to provide a wealth of opportunities for applying PLS-SEM. The book is designed to expose robust processes in application of PLS-SEM, including use of various software packages and codes, including R. PLS-SEM is already a popular tool in marketing and management information systems used to explain latent constructs. Until now, PLS-SEM has not enjoyed a wide acceptance in Banking and Finance. Based on recent research developments, this book represents the first collection of PLS-SEM applications in Banking and Finance. This book will serve as a reference book for those researchers keen on adopting PLS-SEM to explain latent constructs in Banking and Finance.
Book Synopsis Bayesian Estimation and Testing of Structural Equation Models by : Richard Scheines
Download or read book Bayesian Estimation and Testing of Structural Equation Models written by Richard Scheines and published by . This book was released on 1995 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: "The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameters can be computed from these samples. If the prior distribution over the parameters is uninformative, the posterior is proportional to the likelihood, and asymptotically the inferences based on the Gibbs sample are the same as those based on the maximum likelihood solution, e.g., output from LISREL or EQS. In small samples, however, the likelihood surface is not multivariate normal and in some cases not even unimodal. Nevertheless, the Gibbs sampler draws a sample from the true posterior distribution over the parameters regardless of the sample size and the shape of the likelihood surface. With an informative prior distribution over the parameters, it can be used to estimate underidentified models, as we illustrate on a simple errors-in-variables model."
Book Synopsis A Comparison of Frequentist and Bayesian Approaches for Confirmatory Factor Analysis by : Menglin Xu
Download or read book A Comparison of Frequentist and Bayesian Approaches for Confirmatory Factor Analysis written by Menglin Xu and published by . This book was released on 2019 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model fit indices within the framework of structural equation models are crucial in evaluating and selecting the most appropriate model to fit data. The performance of fit indices under varying suboptimal conditions requires further investigation. Moreover, with the increasing interest in applying Bayesian method to social sciences data, the comparison of Bayesian estimation and robust maximum likelihood (MLR) estimation methods in evaluating models and estimating parameters is of vital importance. This study aims 1 ) to investigate the performance of MLR associated model fit indices under various conditions of model misfit, data distribution, and sample sizes; 2) to compare the performance of Bayesian and MLR methods in model fit and parameter estimation based on a confirmatory factor analysis (CFA) model. Data were simulated based on a population CFA model consistent with Curran, West and Finch’s (1996) study using R 3.4.0. Simulation conditions include 3 sample sizes (N = 200, 500, 1000), 3 degrees of model misfit (none: RMSEA = 0; mild: RMSEA = .05; moderate: RMSEA = .10), and 3 degrees of data nonnormality (normal: skewness = 0, kurtosis = 0; mild: skewness = 1, kurtosis = 3; moderate: skewness = 2, kurtosis = 7). Model misfit was introduced using Cudeck and Browne’s (1992) method through the R package MBESS. Data were fit using the R package lavaan for MLR method and blavaan for Bayesian method. Results show that scaled CFI and scaled TLI are the most robust model fit indices to variousiii suboptimal conditions; compared to p values associated with MLR, PP p values associated with the Bayesian method are robust to small sample size and data nonnormality under correctly specified models, less sensitive to models with ignorable degree of misfit, and have sufficient statistical power to reject moderately misspecified models; Bayesian and MLR methods have similar performance in point estimation; MLR method produces more robust standard error estimations. Implications and suggestions for future students are discussed.
Book Synopsis Basic and Advanced Bayesian Structural Equation Modeling by : Sik-Yum Lee
Download or read book Basic and Advanced Bayesian Structural Equation Modeling written by Sik-Yum Lee and published by John Wiley & Sons. This book was released on 2012-07-05 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides clear instructions to researchers on how to apply Structural Equation Models (SEMs) for analyzing the inter relationships between observed and latent variables. Basic and Advanced Bayesian Structural Equation Modeling introduces basic and advanced SEMs for analyzing various kinds of complex data, such as ordered and unordered categorical data, multilevel data, mixture data, longitudinal data, highly non-normal data, as well as some of their combinations. In addition, Bayesian semiparametric SEMs to capture the true distribution of explanatory latent variables are introduced, whilst SEM with a nonparametric structural equation to assess unspecified functional relationships among latent variables are also explored. Statistical methodologies are developed using the Bayesian approach giving reliable results for small samples and allowing the use of prior information leading to better statistical results. Estimates of the parameters and model comparison statistics are obtained via powerful Markov Chain Monte Carlo methods in statistical computing. Introduces the Bayesian approach to SEMs, including discussion on the selection of prior distributions, and data augmentation. Demonstrates how to utilize the recent powerful tools in statistical computing including, but not limited to, the Gibbs sampler, the Metropolis-Hasting algorithm, and path sampling for producing various statistical results such as Bayesian estimates and Bayesian model comparison statistics in the analysis of basic and advanced SEMs. Discusses the Bayes factor, Deviance Information Criterion (DIC), and $L_\nu$-measure for Bayesian model comparison. Introduces a number of important generalizations of SEMs, including multilevel and mixture SEMs, latent curve models and longitudinal SEMs, semiparametric SEMs and those with various types of discrete data, and nonparametric structural equations. Illustrates how to use the freely available software WinBUGS to produce the results. Provides numerous real examples for illustrating the theoretical concepts and computational procedures that are presented throughout the book. Researchers and advanced level students in statistics, biostatistics, public health, business, education, psychology and social science will benefit from this book.
Book Synopsis Mathematical Reviews by : American Mathematical Society
Download or read book Mathematical Reviews written by American Mathematical Society and published by American Mathematical Society(RI). This book was released on 1986-12 with total page 780 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Mplus Version 8 User's Guide by : Linda K. Muthen
Download or read book Mplus Version 8 User's Guide written by Linda K. Muthen and published by . This book was released on 2017-04-10 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Quantitative Sociology by : H.M. Blalock
Download or read book Quantitative Sociology written by H.M. Blalock and published by Academic Press. This book was released on 2013-10-22 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantitative Sociology: International Perspective on Mathematical and Statistical Modeling presents diverse mathematical modeling procedures involving different strategies for understanding sociology. This book is organized into three parts encompassing 22 chapters that also describe meta-mathematical models suggesting general ways of conceptualizing or expressing phenomena in mathematical or logical languages. Part I deals with the diachronic process analysis, causation of conditional probabilities, and graph-theoretical formulations. Part II highlights the different fields of applied statistics, including experimental designs, survey sampling and panel designs, multivariate analysis, econometrics, multiple classification analysis, and other approaches to data analysis and measurement. This part also treats the elimination of distortions or artifacts of various kinds, such as sampling errors or biases stemming from faulty designs, measurement errors, or incorrectly specified equations. Part III explores other mathematical models for a deductive or semideductive system containing axioms, definitions, and theorems that may then be examined both in terms of internal consistency using mathematical reasoning and their ability to explain real-world phenomena. This book is of value to sociologists, applied and statistical mathematicians, and researchers.
Book Synopsis Modeling Ordered Choices by : William H. Greene
Download or read book Modeling Ordered Choices written by William H. Greene and published by Cambridge University Press. This book was released on 2010-04-08 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is increasingly common for analysts to seek out the opinions of individuals and organizations using attitudinal scales such as degree of satisfaction or importance attached to an issue. Examples include levels of obesity, seriousness of a health condition, attitudes towards service levels, opinions on products, voting intentions, and the degree of clarity of contracts. Ordered choice models provide a relevant methodology for capturing the sources of influence that explain the choice made amongst a set of ordered alternatives. The methods have evolved to a level of sophistication that can allow for heterogeneity in the threshold parameters, in the explanatory variables (through random parameters), and in the decomposition of the residual variance. This book brings together contributions in ordered choice modeling from a number of disciplines, synthesizing developments over the last fifty years, and suggests useful extensions to account for the wide range of sources of influence on choice.
Book Synopsis Bayesian Versus Maximum Likelihood Estimation of Term Structure Models Driven by Latent Diffusions by : Paul Schneider
Download or read book Bayesian Versus Maximum Likelihood Estimation of Term Structure Models Driven by Latent Diffusions written by Paul Schneider and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper provides an econometric analysis of parameter estimation for continuous-time affine term structure models that are driven by latent diffusions. Simulating an affine two factor short rate model where one process is Gaussian and the other factor is square root we perform a comparison between Markov Chain Monte Carlo (MCMC) and maximum likelihood (ML) estimation. To cope with the discrepancy between a continuous-time formulation and data only available in discrete time, we use closed-form expansions of the transition densities. In order to find reasonable starting values for both MCMC and ML estimation we employ genetic algorithms with penalty functions for the parameter restrictions. For ML estimation we employ both simplex and gradient based solvers. We find that with only a few exceptions the MCMC estimates reveal the true parameters and are in general more consistent within different estimation procedures than maximum likelihood estimation. For both estimation methodologies we observe negative correlation between the estimates of the factor loadings and the estimates of the unconditional mean of the square root process. Finally we find that both methodologies identify time series of latent state variables that are more likely than the data generating process itself.
Author :Vincenzo Esposito Vinzi Publisher :Springer Science & Business Media ISBN 13 :3540328270 Total Pages :791 pages Book Rating :4.5/5 (43 download)
Book Synopsis Handbook of Partial Least Squares by : Vincenzo Esposito Vinzi
Download or read book Handbook of Partial Least Squares written by Vincenzo Esposito Vinzi and published by Springer Science & Business Media. This book was released on 2010-03-10 with total page 791 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook provides a comprehensive overview of Partial Least Squares (PLS) methods with specific reference to their use in marketing and with a discussion of the directions of current research and perspectives. It covers the broad area of PLS methods, from regression to structural equation modeling applications, software and interpretation of results. The handbook serves both as an introduction for those without prior knowledge of PLS and as a comprehensive reference for researchers and practitioners interested in the most recent advances in PLS methodology.
Book Synopsis Generalized Principal Component Analysis by : René Vidal
Download or read book Generalized Principal Component Analysis written by René Vidal and published by Springer. This book was released on 2016-04-11 with total page 590 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive introduction to the latest advances in the mathematical theory and computational tools for modeling high-dimensional data drawn from one or multiple low-dimensional subspaces (or manifolds) and potentially corrupted by noise, gross errors, or outliers. This challenging task requires the development of new algebraic, geometric, statistical, and computational methods for efficient and robust estimation and segmentation of one or multiple subspaces. The book also presents interesting real-world applications of these new methods in image processing, image and video segmentation, face recognition and clustering, and hybrid system identification etc. This book is intended to serve as a textbook for graduate students and beginning researchers in data science, machine learning, computer vision, image and signal processing, and systems theory. It contains ample illustrations, examples, and exercises and is made largely self-contained with three Appendices which survey basic concepts and principles from statistics, optimization, and algebraic-geometry used in this book. René Vidal is a Professor of Biomedical Engineering and Director of the Vision Dynamics and Learning Lab at The Johns Hopkins University. Yi Ma is Executive Dean and Professor at the School of Information Science and Technology at ShanghaiTech University. S. Shankar Sastry is Dean of the College of Engineering, Professor of Electrical Engineering and Computer Science and Professor of Bioengineering at the University of California, Berkeley.
Book Synopsis Discrete Choice Methods with Simulation by : Kenneth Train
Download or read book Discrete Choice Methods with Simulation written by Kenneth Train and published by Cambridge University Press. This book was released on 2009-07-06 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
Book Synopsis Principles and Practice of Structural Equation Modeling by : Rex B. Kline
Download or read book Principles and Practice of Structural Equation Modeling written by Rex B. Kline and published by Guilford Publications. This book was released on 2015-10-08 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has been replaced by Principles and Practice of Structural Equation Modeling, Fifth Edition, ISBN 978-1-4625-5191-0.
