Structural Equation Modelling with Partial Least Squares Using Stata and R
暫譯: 使用 Stata 和 R 的偏最小二乘結構方程模型分析

Mehmetoglu, Mehmet, Venturini, Sergio

Structural Equation Modelling with Partial Least Squares Using Stata and R
  • 出版商: CRC
  • 出版日期: 2021-03-09
  • 售價: $5,550
  • 貴賓價: 9.5 折 $5,273
  • 語言: 英文
  • 頁數: 382
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1482227819
  • ISBN-13: 9781482227819

    • 海外代購書籍(需單獨結帳)

商品描述

Partial least squares structural equation modelling (PLS-SEM) is becoming a popular statistical framework in many fields and disciplines of the social sciences. The main reason for this popularity is that PLS-SEM can be used to estimate models including latent variables, observed variables, or a combination of these. The popularity of PLS-SEM is predicted to increase even more as a result of the development of new and more robust estimation approaches, such as consistent PLS-SEM. The traditional and modern estimation methods for PLS-SEM are now readily facilitated by both open-source and commercial software packages.

This book presents PLS-SEM as a useful practical statistical toolbox that can be used for estimating many different types of research models. In so doing, the authors provide the necessary technical prerequisites and theoretical treatment of various aspects of PLS-SEM prior to practical applications. What makes the book unique is the fact that it thoroughly explains and extensively uses comprehensive Stata (plssem) and R (cSEM and plspm) packages for carrying out PLS-SEM analysis. The book aims to help the reader understand the mechanics behind PLS-SEM as well as performing it for publication purposes.

Features:

  • Intuitive and technical explanations of PLS-SEM methods

  • Complete explanations of Stata and R packages

  • Lots of example applications of the methodology

  • Detailed interpretation of software output

  • Reporting of a PLS-SEM study

  • Github repository for supplementary book material

The book is primarily aimed at researchers and graduate students from statistics, social science, psychology, and other disciplines. Technical details have been moved from the main body of the text into appendices, but it would be useful if the reader has a solid background in linear regression analysis.

商品描述(中文翻譯)

部分最小二乘結構方程模型（PLS-SEM）在社會科學的許多領域和學科中正變得越來越受歡迎。這種受歡迎的主要原因是PLS-SEM可以用來估計包括潛在變數、觀察變數或這些變數的組合的模型。隨著新穎且更穩健的估計方法的發展，例如一致性PLS-SEM，預測PLS-SEM的受歡迎程度將會進一步增加。傳統和現代的PLS-SEM估計方法現在都可以通過開源和商業軟體包輕鬆使用。

本書將PLS-SEM呈現為一個有用的實用統計工具箱，可用於估計許多不同類型的研究模型。在此過程中，作者提供了進行實際應用之前所需的技術前提和PLS-SEM各個方面的理論處理。本書的獨特之處在於它徹底解釋並廣泛使用綜合的Stata（plssem）和R（cSEM和plspm）套件來進行PLS-SEM分析。本書旨在幫助讀者理解PLS-SEM背後的機制，以及為出版目的進行PLS-SEM分析。

特色：
- PLS-SEM方法的直觀和技術解釋
- Stata和R套件的完整解釋
- 大量方法論的示例應用
- 軟體輸出的詳細解釋
- PLS-SEM研究的報告
- 用於補充書籍材料的Github資料庫

本書主要針對統計學、社會科學、心理學及其他學科的研究人員和研究生。技術細節已從正文移至附錄，但如果讀者具備線性回歸分析的堅實背景，將會更有幫助。

作者簡介

Mehmet Mehmetoglu is a professor of research methods in the Department of Psychology at the Norwegian University of Science and Technology (NTNU). His research interests include consumer psychology, evolutionary psychology and statistical methods. Mehmetoglu has co/publications in about 30 different refereed international journals such as Journal of Statistical Software, Personality and Individual Differences, and Evolutionary Psychological Science.

Sergio Venturini is an Associate Professor of Statistics in the Management Department at the Università degli Studi di Torino (Italy). His research interests include Bayesian data analysis methods,　meta-analysis　and　statistical computing. He coauthored many publications that have been published in different　refereed international journals such as Annals of Applied Statistics, Bayesian Analysis and Journal of Statistical Software.

作者簡介(中文翻譯)

梅赫梅特·梅赫梅托格魯是挪威科技大學（NTNU）心理學系的研究方法教授。他的研究興趣包括消費者心理學、進化心理學和統計方法。梅赫梅托格魯在約30本不同的國際期刊上發表過共同/獨立的論文，這些期刊包括《統計軟體期刊》（Journal of Statistical Software）、《人格與個體差異》（Personality and Individual Differences）以及《進化心理科學》（Evolutionary Psychological Science）。

塞爾吉奧·文圖里尼 是意大利都靈大學（Università degli Studi di Torino）管理系的統計學副教授。他的研究興趣包括貝葉斯數據分析方法、元分析以及統計計算。他共同撰寫了許多發表在不同的國際期刊上的論文，這些期刊包括《應用統計年鑑》（Annals of Applied Statistics）、《貝葉斯分析》（Bayesian Analysis）和《統計軟體期刊》（Journal of Statistical Software）。

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