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Structural Equation Modelling with Partial Least Squares Using Stata and R

Partial least squares structural equation modelling (PLS-SEM) is becoming a popular statistical framework in many fields and disciplines;

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Structural Equation Modelling with Partial Least Squares Using Stata and R

Partial least squares structural equation modelling (PLS-SEM) is becoming a popular statistical framework in many fields and disciplines;

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A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)

The third edition of A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) guides readers through learning and mastering;

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Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R

Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships;

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Advanced Issues in Partial Least Squares Structural Equation Modeling

A practical and applied text on PLS-SEM that combines simple explanations of complex statistical concepts with examples and case studies;

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A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)

A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), by Hair, Hult, Ringle, and Sarstedt, provides a concise;

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A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM)

Written with those with limited mathematical and statistical knowledge in mind, this concise and practical guide helps researchers to do;

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Handbook of Partial Least Squares

This handbook provides a comprehensive overview of Partial Least Squares (PLS) methods with specific reference to their use in marketing;

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Applied Structural Equation Modelling for Researchers and Practitioners

(SEM). Focusing on R and Stata to implement and perform various structural equation models, Ramlall examines the types, benefits, and;

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Composite-Based Structural Equation Modeling

using partial least squares path modeling, maximum likelihood, and other estimators, as well as how to interpret findings and report the results;

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Discovering Structural Equation Modeling Using Stata

Discovering Structural Equation Modeling Using Stata, Revised Edition is devoted to Stata's sem command and all it can do. Learn about its;

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Research Methods in Accounting

modelling and partial least-squares analysis Further discussion on the topic of theoretical foundations when choosing between research methods;

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Introduction To Structural Equation Modelling Using Spss And Amos

Introduction to Structural Equation Modelling using SPSS and AMOS is a complete guide to carrying out your own structural equation;

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Achieving Brand Loyalty in China through After Sales Services

the critical success factors of after-sales services via partial least squares structural equation modelling. After-sales services have become;

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Structural Equation Modelling

Structural Equation Modeling provides a conceptual and mathematical understanding of structural equation modelling, helping readers across;

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Structural Equation Modelling

Structural Equation Modeling provides a conceptual and mathematical understanding of structural equation modelling, helping readers across;

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Generalized Structured Component Analysis

structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and;

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Generalized Structured Component Analysis

analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model;

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Applying Partial Least Squares in Tourism and Hospitality Research

Partial-least-squares path modeling (PLS-PM), a composite-based form of structural equation modeling (SEM), offers great practical;

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Quantitative Methods in Tourism

* the use of similarity and diversity indexes for comparing samples * observations about the partial least squares (PLS) approach to path;

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Recent Developments on Structural Equation Models

professionally dealing with Structural Equation Modelling to enhance their knowledge of the type of models covered and the technical problems involved;

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An Introduction to Modern Econometrics Using Stata

Econometrics Using Stata focuses on the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical;

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Partial Update Least-Square Adaptive Filtering

Least Squares CMA (LSCMA), EDS, and CG. The PU methods are also applied to CMA1-2 and NCMA to compare with the performance of the LSCMA;

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Partial Update Least-Square Adaptive Filtering

Least Squares CMA (LSCMA), EDS, and CG. The PU methods are also applied to CMA1-2 and NCMA to compare with the performance of the LSCMA;

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Data Analysis Using Hierarchical Generalized Linear Models with R

within the field and, using data examples, illustrates how to analyse various kinds of data using R. It provides a likelihood approach to;

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